diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS
index d28b70c3..ab24b817 100644
--- a/.github/CODEOWNERS
+++ b/.github/CODEOWNERS
@@ -3,6 +3,6 @@
 # precedence.
 
 # Default owners for everything:
-* @Asamartino
+* @wirednkod
 
 # See https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners
\ No newline at end of file
diff --git a/assets/Gov_PBA6_Lucerne_2025.pdf b/assets/Gov_PBA6_Lucerne_2025.pdf
new file mode 100644
index 00000000..d03c0dee
Binary files /dev/null and b/assets/Gov_PBA6_Lucerne_2025.pdf differ
diff --git a/assets/Slides_Singapore.odp b/assets/Slides_Singapore.odp
new file mode 100644
index 00000000..e605d450
Binary files /dev/null and b/assets/Slides_Singapore.odp differ
diff --git a/assets/Slides_Singapore.pdf b/assets/Slides_Singapore.pdf
new file mode 100644
index 00000000..2c97ce35
Binary files /dev/null and b/assets/Slides_Singapore.pdf differ
diff --git a/assets/Slides_Singapore.pptx b/assets/Slides_Singapore.pptx
new file mode 100644
index 00000000..308fdf7b
Binary files /dev/null and b/assets/Slides_Singapore.pptx differ
diff --git a/assets/advanced_blockchain-dkg.pdf b/assets/advanced_blockchain-dkg.pdf
new file mode 100644
index 00000000..428efd5b
Binary files /dev/null and b/assets/advanced_blockchain-dkg.pdf differ
diff --git a/assets/favicon.png b/assets/favicon.png
new file mode 100644
index 00000000..fe659d7f
Binary files /dev/null and b/assets/favicon.png differ
diff --git a/assets/favicon.svg b/assets/favicon.svg
new file mode 100644
index 00000000..c2292edf
--- /dev/null
+++ b/assets/favicon.svg
@@ -0,0 +1,18 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg id="Layer_1" data-name="Layer 1" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 13.87">
+  <defs>
+    <style>
+      .cls-1 {
+        fill: #e6007a;
+      }
+
+      .cls-2 {
+        fill: #321d47;
+      }
+    </style>
+  </defs>
+  <path class="cls-2" d="m12.67,11.21v.05c-.04,1.52-2.17,2.68-4.74,2.6-2.58-.09-4.63-1.38-4.59-2.91l-.02-3.96h9.33l.02,4.22h0Z"/>
+  <path class="cls-1" d="m7.26,10.23L.55,6.19c-.74-.44-.74-1.51,0-1.95L7.26.2c.45-.27,1.02-.27,1.47,0l6.71,4.03c.74.44.74,1.51,0,1.95l-6.71,4.03c-.45.27-1.02.27-1.47,0Z"/>
+  <path class="cls-2" d="m14.51,9.27c-.32,0-.58-.26-.58-.58v-1.6l-1.73-.98c-.28-.16-.37-.51-.22-.79.16-.28.51-.37.79-.22l2.02,1.14c.18.1.29.29.29.5v1.93c0,.32-.26.58-.58.58h0Z"/>
+  <circle class="cls-1" cx="14.51" cy="10.86" r="1"/>
+</svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/AI & Computing.svg b/assets/icons/polkadot/2color/AI & Computing.svg
new file mode 100644
index 00000000..4d7fb0fc
--- /dev/null
+++ b/assets/icons/polkadot/2color/AI & Computing.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="5" cy="14" r="2" transform="rotate(-180 5 14)"></circle><path d="M6.90002 14L10.9 14"></path><circle cx="9" cy="6" r="2"></circle><path d="M17 11H11V17H17V11Z"></path><path d="M11 6H14V11" fill="none"></path><circle cx="19" cy="22" r="2" transform="rotate(-180 19 22)"></circle><path d="M17 22L14 22L14 17" fill="none"></path><circle cx="23.4" cy="14" r="2"></circle><path d="M21.5 14H17.5"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Account Portability.svg b/assets/icons/polkadot/2color/Account Portability.svg
new file mode 100644
index 00000000..825555af
--- /dev/null
+++ b/assets/icons/polkadot/2color/Account Portability.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8 13.7644L2 13.7644"></path><path d="M6.16985 16.6807L9.08611 13.7643L6.16985 10.848" fill="none"></path><path d="M19.6117 14.6402L20.3804 13.716C21.6924 12.1387 21.5873 9.82174 20.1379 8.36968C18.5861 6.81497 16.067 6.81497 14.5152 8.36968C13.0658 9.82174 12.9608 12.1387 14.2727 13.716L15.0413 14.64C15.5323 15.2302 15.251 16.1304 14.5113 16.3361L13.47 16.6257C10.6189 17.4185 8.64612 20.0149 8.64612 22.9741V25.8286H26V22.9692C26 20.0124 24.0291 17.4182 21.1806 16.6255L20.1415 16.3363C19.402 16.1305 19.1208 15.2304 19.6117 14.6402Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Action Left.svg b/assets/icons/polkadot/2color/Action Left.svg
new file mode 100644
index 00000000..e4c35357
--- /dev/null
+++ b/assets/icons/polkadot/2color/Action Left.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19 22L10 14.4925L19 7" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Action Right.svg b/assets/icons/polkadot/2color/Action Right.svg
new file mode 100644
index 00000000..b1c44df6
--- /dev/null
+++ b/assets/icons/polkadot/2color/Action Right.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9 6L18 13.5075L9 21" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Add key pair.svg b/assets/icons/polkadot/2color/Add key pair.svg
new file mode 100644
index 00000000..a5af3978
--- /dev/null
+++ b/assets/icons/polkadot/2color/Add key pair.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.7641 17.1156L14.7641 11.7782"></path><path d="M17.4328 14.4469L12.0954 14.4469"></path><path d="M9.34094 24.5222C8.99891 24.8358 8.59843 25.0788 8.16238 25.2375C7.72632 25.3962 7.26323 25.4674 6.79954 25.4471C6.33586 25.4267 5.88066 25.3153 5.45993 25.119C5.03921 24.9228 4.6612 24.6456 4.34749 24.3033C3.72289 23.6055 3.40063 22.6884 3.4515 21.7536C3.50237 20.8187 3.92221 19.9425 4.6188 19.3174C4.96083 19.0038 5.36131 18.7608 5.79736 18.6021C6.23342 18.4434 6.69651 18.3722 7.1602 18.3925C7.62388 18.4128 8.07908 18.5243 8.49981 18.7206C8.92053 18.9168 9.29854 19.194 9.61225 19.5362C10.2365 20.2342 10.5585 21.1512 10.5077 22.086C10.4568 23.0208 10.0372 23.8969 9.34094 24.5222Z" fill="none"></path><path d="M10.6179 21.7082L26 21.7106"></path><path d="M18.4265 22.3872L18.4239 25.6594L23.3242 25.6653L23.3256 22.3942"></path><path d="M9.33963 9.39374C8.9976 9.70728 8.59712 9.95033 8.16107 10.109C7.72502 10.2677 7.26193 10.3389 6.79824 10.3186C6.33455 10.2983 5.87935 10.1868 5.45863 9.99056C5.03791 9.79432 4.6599 9.51715 4.34619 9.17487C3.72159 8.47703 3.39933 7.55996 3.4502 6.62508C3.50107 5.69021 3.92091 4.81399 4.6175 4.1889C4.95953 3.87536 5.36001 3.63231 5.79606 3.47362C6.23211 3.31494 6.6952 3.24372 7.15889 3.26404C7.62258 3.28437 8.07778 3.39583 8.4985 3.59208C8.91923 3.78832 9.29723 4.06549 9.61094 4.40777C10.2352 5.10576 10.5572 6.02276 10.5064 6.95752C10.4555 7.89228 10.0359 8.76845 9.33963 9.39374Z" fill="none"></path><path d="M10.6166 6.57965L25.9987 6.58208"></path><path d="M18.4252 7.25862L18.4226 10.5309L23.3229 10.5368L23.3243 7.26568"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Add user.svg b/assets/icons/polkadot/2color/Add user.svg
new file mode 100644
index 00000000..129511f3
--- /dev/null
+++ b/assets/icons/polkadot/2color/Add user.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.9991 9.00464V3.00464"></path><path d="M26.9991 6.00464L20.9991 6.00464"></path><path d="M10.5497 13.747L9.64035 12.6538C8.08843 10.788 8.21272 8.04735 9.92716 6.32973C11.7628 4.49069 14.7426 4.49069 16.5782 6.32973C18.2926 8.04735 18.4169 10.788 16.865 12.6538L15.9559 13.7467C15.3751 14.4449 15.7079 15.5097 16.5828 15.7531L17.8145 16.0956C21.187 17.0335 23.5206 20.1046 23.5206 23.6051V26.9816H2.99304V23.5992C2.99304 20.1017 5.32433 17.0331 8.69379 16.0954L9.92292 15.7533C10.7978 15.5099 11.1304 14.4451 10.5497 13.747Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Add.svg b/assets/icons/polkadot/2color/Add.svg
new file mode 100644
index 00000000..2a8fb943
--- /dev/null
+++ b/assets/icons/polkadot/2color/Add.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9883 2C20.6157 2 25.9883 7.37258 25.9883 14C25.9883 20.6274 20.6157 26 13.9883 26C7.36086 26 1.98828 20.6274 1.98828 14C1.98828 7.37258 7.36086 2 13.9883 2Z"></path><path d="M8.7937 13.4606L19.1833 13.5167"></path><path d="M14.0176 8.29507L13.9614 18.6846"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Address book.svg b/assets/icons/polkadot/2color/Address book.svg
new file mode 100644
index 00000000..e239faa0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Address book.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5 19.6359L2 19.6359"></path><path d="M5 8.32184L2 8.32184"></path><path d="M25.9999 2.00003L25.9999 26.0031L5.22522 26.003L5.22522 2.00003L25.9999 2.00003Z"></path><path d="M17.001 12.8205L17.5027 12.2248C18.4049 11.1536 18.333 9.56902 17.3374 8.58397C16.2905 7.54814 14.6048 7.54814 13.5579 8.58397C12.5623 9.56902 12.4904 11.1536 13.3926 12.2248L13.8942 12.8203C14.2261 13.2144 14.0379 13.8197 13.5411 13.9561L12.8161 14.1552C10.8827 14.6862 9.54258 16.444 9.54258 18.449V20.3358H21.3479V18.4457C21.3479 16.4423 20.0092 14.686 18.0775 14.1551L17.3539 13.9563C16.8572 13.8197 16.6691 13.2145 17.001 12.8205Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Airplane Mode.svg b/assets/icons/polkadot/2color/Airplane Mode.svg
new file mode 100644
index 00000000..acdee6d1
--- /dev/null
+++ b/assets/icons/polkadot/2color/Airplane Mode.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 24" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.2538 19.1308L9.47419 22.7394L13.9318 21.6569L18.3887 22.7394L15.5932 19.1308L15.6222 14.682L25.8701 17.4504L15.666 9.53824L15.7125 4.08386C15.7348 1.47108 12.4046 1.44054 12.3823 4.05333L12.3356 9.53824L2.04451 17.4503L12.2917 14.682C12.2978 16.1649 12.2664 17.6479 12.2538 19.1308Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Alert.svg b/assets/icons/polkadot/2color/Alert.svg
new file mode 100644
index 00000000..8c5746c2
--- /dev/null
+++ b/assets/icons/polkadot/2color/Alert.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9898 3.12793L2.19775 24.872H25.7818L13.9898 3.12793Z" stroke-miterlimit="10"></path><path d="M13.9992 17.7247L13.9897 10.5945" stroke-miterlimit="10"></path><path d="M14.0093 21.1309L13.9912 21.1128" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Algorithm.svg b/assets/icons/polkadot/2color/Algorithm.svg
new file mode 100644
index 00000000..c239d657
--- /dev/null
+++ b/assets/icons/polkadot/2color/Algorithm.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M18.9557 22.7289H15.2495V5.42358H19.0515" fill="none" data-nofill="true"></path><path d="M11.9375 13.9775H14.9584"></path><path d="M26.7702 1.56445H19.0513V9.28338H26.7702V1.56445Z"></path><path d="M11.9378 13.9775L6.86572 8.9054L1.79361 13.9775L6.86572 19.0496L11.9378 13.9775Z"></path><path d="M22.9107 26.4355C25.0423 26.4355 26.7702 24.7075 26.7702 22.576C26.7702 20.4445 25.0423 18.7166 22.9107 18.7166C20.7792 18.7166 19.0513 20.4445 19.0513 22.576C19.0513 24.7075 20.7792 26.4355 22.9107 26.4355Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Alice.svg b/assets/icons/polkadot/2color/Alice.svg
new file mode 100644
index 00000000..48517b9f
--- /dev/null
+++ b/assets/icons/polkadot/2color/Alice.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.0433 10.5398L11.0695 9.41161C9.51415 7.61093 9.63743 4.90867 11.3497 3.25618C13.0856 1.58127 15.8364 1.58127 17.5724 3.25618C19.2846 4.90867 19.4079 7.61093 17.8526 9.41161L16.8787 10.5386C16.3694 11.1276 23.9295 22.6689 23.9295 22.6689H19.444V26H9.48052V22.6689H5C5 22.6689 12.5514 11.1301 12.0433 10.5398Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Ambassadors.svg b/assets/icons/polkadot/2color/Ambassadors.svg
new file mode 100644
index 00000000..3b2c92a1
--- /dev/null
+++ b/assets/icons/polkadot/2color/Ambassadors.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3.3167 18.2338C4.07764 19.5517 5.76294 20.0033 7.08092 19.2424L8.54062 18.3913C12.7495 16.0327 17.4091 15.0552 21.0684 15.6442L17.7517 9.8996L14.4351 4.15498C13.1156 7.61851 9.93917 11.1651 5.79211 13.6308L4.32532 14.4695C3.00733 15.2305 2.55576 16.9158 3.3167 18.2338Z"></path><path d="M19.7145 5.64923C19.7145 5.64923 21.0466 6.40554 21.7209 7.54587C22.3951 8.6862 22.4218 10.192 22.4218 10.192" fill="none" data-nofill="true"></path><path d="M20.7148 2C20.7148 2 23.3154 3.47646 24.6316 5.70262C25.9479 7.92878 26 11.351 26 11.351" fill="none" data-nofill="true"></path><path d="M10.0083 17.53L8.63049 15.1436L7.25269 12.7572"></path><path d="M10.0161 17.5781L6.77264 19.4507L9.99432 25.0308L13.2378 23.1582L10.0161 17.5781Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Announcement.svg b/assets/icons/polkadot/2color/Announcement.svg
new file mode 100644
index 00000000..1aae71f8
--- /dev/null
+++ b/assets/icons/polkadot/2color/Announcement.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.4009 21.0053C18.387 21.5294 22.8539 17.9122 23.378 12.9261C23.9021 7.93998 20.2849 3.47306 15.2988 2.94896C10.3127 2.42487 5.84576 6.04205 5.32166 11.0282C5.06161 13.5023 5.82119 15.8486 7.26172 17.6487L4.7449 23.6804L10.0308 19.9645C11.0454 20.5136 12.1823 20.8772 13.4009 21.0053Z"></path><path d="M14.5327 13.1188L14.5255 7.64001" stroke-miterlimit="10"></path><path d="M14.543 16.0295L14.5259 16.0124" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Anonymous Proxy.svg b/assets/icons/polkadot/2color/Anonymous Proxy.svg
new file mode 100644
index 00000000..b7ee05c5
--- /dev/null
+++ b/assets/icons/polkadot/2color/Anonymous Proxy.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.2243 25.0435C24.7573 25.0435 26 23.8008 26 22.2679C26 20.7349 24.7573 19.4922 23.2243 19.4922C21.6914 19.4922 20.4487 20.7349 20.4487 22.2679C20.4487 23.8008 21.6914 25.0435 23.2243 25.0435Z"></path><path d="M4.77567 25.0434C6.30863 25.0434 7.55134 23.8007 7.55134 22.2677C7.55134 20.7348 6.30863 19.4921 4.77567 19.4921C3.24271 19.4921 2 20.7348 2 22.2677C2 23.8007 3.24271 25.0434 4.77567 25.0434Z"></path><path d="M4.77571 19.4975L4.77571 16.2949L22.8386 16.2949L22.8386 19.4975" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M11.2739 4.77561C11.2739 3.24265 12.5167 1.99994 14.0496 1.99994C15.5826 1.99994 16.8253 3.24265 16.8253 4.77561C16.8253 6.30857 15.5826 7.55128 14.0496 7.55128V9.38381M14.0496 12.8443V12.8545" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Arbitrary Message.svg b/assets/icons/polkadot/2color/Arbitrary Message.svg
new file mode 100644
index 00000000..cf272e89
--- /dev/null
+++ b/assets/icons/polkadot/2color/Arbitrary Message.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.5083 9.30676H2V21.9626H6.13717V25.9716L11.4003 21.9626H20.2912V16.3554"></path><path d="M19.6729 15.9608C23.095 15.9608 25.8691 13.1866 25.8691 9.76457C25.8691 6.3425 23.095 3.56836 19.6729 3.56836C16.2508 3.56836 13.4767 6.3425 13.4767 9.76457C13.4767 13.1866 16.2508 15.9608 19.6729 15.9608Z"></path><path d="M17.0001 10.0568L18.7652 11.5684L22.0001 8.56836"></path><path d="M7.01814 16.0181L7 16" stroke-miterlimit="10"></path><path d="M11.0181 16.0181L11 16" stroke-miterlimit="10"></path><path d="M15.0544 16.0181L15.0363 16" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Archive Node.svg b/assets/icons/polkadot/2color/Archive Node.svg
new file mode 100644
index 00000000..3ec27008
--- /dev/null
+++ b/assets/icons/polkadot/2color/Archive Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5358 21.0126L18.5124 16.611"></path><path d="M9.50999 16.6247L6.44708 20.999"></path><path d="M20.4564 23.2116C20.4564 24.7425 21.6974 25.9834 23.2282 25.9834C24.759 25.9834 26 24.7425 26 23.2116C26 21.6808 24.759 20.4398 23.2282 20.4398C21.6974 20.4398 20.4564 21.6808 20.4564 23.2116Z"></path><path d="M2.00001 23.2116C2.00001 24.7425 3.24099 25.9834 4.77183 25.9834C6.30266 25.9834 7.54364 24.7425 7.54364 23.2116C7.54364 21.6808 6.30266 20.4398 4.77183 20.4398C3.24099 20.4398 2.00001 21.6808 2.00001 23.2116Z"></path><path d="M5.99593 10.0054C5.99593 14.4267 9.58006 18.0108 14.0013 18.0108C18.4226 18.0108 22.0067 14.4267 22.0067 10.0054C22.0067 5.58414 18.4226 2 14.0013 2C9.58006 2 5.99593 5.58414 5.99593 10.0054Z" stroke-miterlimit="10"></path><path d="M12.1736 12.0799L16.1694 8.08414"></path><path d="M16.1693 12.0799L12.1736 8.08414"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Arrow Back.svg b/assets/icons/polkadot/2color/Arrow Back.svg
new file mode 100644
index 00000000..3f71da8c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Arrow Back.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21 26L7 13.988L21 2" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Arrow Down.svg b/assets/icons/polkadot/2color/Arrow Down.svg
new file mode 100644
index 00000000..ed10adad
--- /dev/null
+++ b/assets/icons/polkadot/2color/Arrow Down.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9914 25L13.9914 2" fill="none" data-nofill="true"></path><path d="M24 15.8003L13.9914 26L4 15.8003" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Arrow Left.svg b/assets/icons/polkadot/2color/Arrow Left.svg
new file mode 100644
index 00000000..0f51626b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Arrow Left.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 13.9914L26 13.9914" fill="none" data-nofill="true"></path><path d="M12.1997 24L2 13.9914L12.1997 4" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Arrow Right.svg b/assets/icons/polkadot/2color/Arrow Right.svg
new file mode 100644
index 00000000..54bec482
--- /dev/null
+++ b/assets/icons/polkadot/2color/Arrow Right.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 14.0086L2 14.0086" fill="none" data-nofill="true"></path><path d="M15.8003 4L26 14.0086L15.8003 24" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Arrow Up.svg b/assets/icons/polkadot/2color/Arrow Up.svg
new file mode 100644
index 00000000..99d1d976
--- /dev/null
+++ b/assets/icons/polkadot/2color/Arrow Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.0086 3L14.0086 26" fill="none" data-nofill="true"></path><path d="M4 12.1997L14.0086 2L24 12.1997" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Article.svg b/assets/icons/polkadot/2color/Article.svg
new file mode 100644
index 00000000..4502fb6c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Article.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M5.19507 27.0057V1.5332H17.9313L24.7893 8.39118V27.0057H5.19507Z"></path><path d="M24.5 8.85798H18V2"></path><path d="M14.0125 5.45215H9.11389V10.3507H14.0125V5.45215Z" stroke-miterlimit="10"></path><path d="M9.11382 17.2087H20.8704" stroke-miterlimit="10"></path><path d="M9.11382 23.0869H20.8704" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Attack.svg b/assets/icons/polkadot/2color/Attack.svg
new file mode 100644
index 00000000..8fadd48a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Attack.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 2C7.37258 2 2 7.37258 2 14C2 16.1857 2.58437 18.235 3.60539 20H7.32682V26H20.6602V20H24.3946C25.4156 18.235 26 16.1857 26 14C26 7.37258 20.6274 2 14 2Z"></path><circle cx="9.28605" cy="13.0698" r="1.88557"></circle><circle cx="18.7139" cy="13.0698" r="1.88557"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Auctions.svg b/assets/icons/polkadot/2color/Auctions.svg
new file mode 100644
index 00000000..276b1e07
--- /dev/null
+++ b/assets/icons/polkadot/2color/Auctions.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M17.2186 1.99999L6.34143 12.8772L11.78 18.3158L22.6572 7.43859L17.2186 1.99999Z" stroke-miterlimit="10"></path><path d="M18.5783 11.5176L15.859 14.2369L23.2641 21.6421L25.9834 18.9228L18.5783 11.5176Z" stroke-miterlimit="10"></path><path d="M14.4984 26L2 26" stroke-miterlimit="10"></path><path d="M12.5756 22.6308L3.92285 22.6308" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Authority.svg b/assets/icons/polkadot/2color/Authority.svg
new file mode 100644
index 00000000..1cd1f644
--- /dev/null
+++ b/assets/icons/polkadot/2color/Authority.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 30 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M12.3081 11.555L10.9968 7.84508C10.4958 6.42792 10.7907 4.85109 11.7698 3.71065C13.4453 1.75907 16.4658 1.75907 18.1413 3.71065C19.1204 4.85109 19.4153 6.42792 18.9143 7.84508L17.6032 11.5545C17.2574 12.5328 17.6423 13.6197 18.5268 14.1623L23.9184 17.4701V22.4414H6V17.4696L11.3852 14.1626C12.2692 13.6197 12.6538 12.5331 12.3081 11.555Z"></path><path d="M22.1264 26.3617H8.25928"></path><path d="M6.55548 17.9524L23.3402 17.9524"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Back Up.svg b/assets/icons/polkadot/2color/Back Up.svg
new file mode 100644
index 00000000..10ddea8c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Back Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M13.9981 25.5L13.9981 10.5M10.3377 12.9485L14 9.28807L17.6654 12.9474"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Balance.svg b/assets/icons/polkadot/2color/Balance.svg
new file mode 100644
index 00000000..bf9cdc3f
--- /dev/null
+++ b/assets/icons/polkadot/2color/Balance.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 4H2V24.219H26V4Z"></path><path d="M15.6374 10.8382H13.4541C13.0244 10.8393 12.6127 11.011 12.309 11.3155C12.0054 11.6201 11.8346 12.0327 11.834 12.4631V12.4826C11.8346 12.913 12.0054 13.3256 12.309 13.6302C12.6127 13.9347 13.0244 14.1064 13.4541 14.1075H14.5371C14.7507 14.1067 14.9623 14.148 15.1599 14.2293C15.3575 14.3106 15.5371 14.4302 15.6884 14.5811C15.8398 14.7321 15.9598 14.9115 16.0418 15.1091C16.1237 15.3066 16.1659 15.5185 16.1659 15.7324C16.1664 15.9465 16.1248 16.1586 16.0432 16.3566C15.9617 16.5545 15.8419 16.7343 15.6907 16.8857C15.5396 17.0371 15.36 17.1571 15.1624 17.2388C14.9648 17.3205 14.753 17.3622 14.5393 17.3616H12.1719"></path><path d="M13.9959 10.7942V9.63696"></path><path d="M13.9959 18.5815V17.514"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Batch Transaction.svg b/assets/icons/polkadot/2color/Batch Transaction.svg
new file mode 100644
index 00000000..6e63f7fd
--- /dev/null
+++ b/assets/icons/polkadot/2color/Batch Transaction.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M25.4728 16L15.4728 26" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M12 2.61932L2 12.6193" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M2.10724 26L25.5 2.60724" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M20.4478 15.3989L25.9819 15.3807L26 20.9302" fill="none" data-nofill="true"></path><path d="M6.97498 2.01823L12.5091 2L12.5272 7.54949" fill="none" data-nofill="true"></path><path d="M20.4478 2.01823L25.9819 2L26 7.54949" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Bid.svg b/assets/icons/polkadot/2color/Bid.svg
new file mode 100644
index 00000000..6bc18e8e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Bid.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.5053 19.0106C18.2027 19.0106 22.0106 15.2027 22.0106 10.5053C22.0106 5.80796 18.2027 2 13.5053 2C8.80796 2 5 5.80796 5 10.5053C5 15.2027 8.80796 19.0106 13.5053 19.0106Z"></path><path d="M10.1033 10.4833L12.5053 13.3403L16.9075 7.67007"></path><path d="M13.5054 26L13.5054 19.0107" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Block Explorer.svg b/assets/icons/polkadot/2color/Block Explorer.svg
new file mode 100644
index 00000000..945bdfdd
--- /dev/null
+++ b/assets/icons/polkadot/2color/Block Explorer.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="4" y="2" width="20" height="24"></rect><path d="M19.4584 8.33936L11.9206 8.33936M8.43256 8.33936L8.42177 8.33936"></path><path d="M19.4584 13.75L11.9206 13.75M8.43256 13.75L8.42177 13.75"></path><path d="M19.4584 19.3394L11.9206 19.3394M8.43256 19.3394L8.42177 19.3394"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Block Number.svg b/assets/icons/polkadot/2color/Block Number.svg
new file mode 100644
index 00000000..3b9e269e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Block Number.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 14.4276H4.57235"></path><path d="M23.4277 14.4276H26"></path><path d="M23.4277 5H4.57235V23.8553H23.4277V5Z"></path><path d="M11.8745 10.114L11.8745 18.599" stroke-miterlimit="10"></path><path d="M16.1651 10.114L16.1651 18.599" stroke-miterlimit="10"></path><path d="M18.2623 12.2115L9.77731 12.2115" stroke-miterlimit="10"></path><path d="M18.2623 16.5021L9.77731 16.5021" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Block Search.svg b/assets/icons/polkadot/2color/Block Search.svg
new file mode 100644
index 00000000..ddb2f4f1
--- /dev/null
+++ b/assets/icons/polkadot/2color/Block Search.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.831 19.662C18.7088 19.662 22.662 15.7078 22.662 10.831C22.662 5.95423 18.7088 2 13.831 2C8.95327 2 5 5.95423 5 10.831C5 15.7078 8.95423 19.662 13.831 19.662Z" stroke-miterlimit="10"></path><path d="M10.8704 7.93085H16.6735V13.7302H10.8704V7.93085Z"></path><path d="M19.7446 17.3763C18.5887 18.4218 17.1612 19.1706 15.5734 19.4883L19.3318 26L23.3734 23.6662L19.7446 17.3763Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Block.svg b/assets/icons/polkadot/2color/Block.svg
new file mode 100644
index 00000000..f6bf68a7
--- /dev/null
+++ b/assets/icons/polkadot/2color/Block.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 14C26 20.6274 20.6274 26 14 26C7.37254 26 1.99996 20.6274 1.99996 14C1.99996 7.37258 7.37254 2 14 2C20.6274 2 26 7.37258 26 14Z"></path><path d="M5.75624 22.47L22.4838 5.74284"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Blockchain.svg b/assets/icons/polkadot/2color/Blockchain.svg
new file mode 100644
index 00000000..e438e25b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Blockchain.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M11.2309 2H2V11.2309H11.2309V2Z"></path><path d="M11.2308 16.7692H2V26H11.2308V16.7692Z"></path><path d="M26.0001 2H16.7692V11.2309H26.0001V2Z"></path><path d="M26 16.7692H16.7692V26H26V16.7692Z"></path><path d="M11.3457 6.7023H16.7692"></path><path d="M16.5569 21.534L11.3457 21.534"></path><path d="M11.1746 16.8253L16.8262 11.1737"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Blog Post.svg b/assets/icons/polkadot/2color/Blog Post.svg
new file mode 100644
index 00000000..f7d347a6
--- /dev/null
+++ b/assets/icons/polkadot/2color/Blog Post.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M22.8977 4.21835C23.8359 3.2802 25.3573 3.2802 26.2964 4.21835C27.2345 5.15651 27.2345 6.67794 26.2964 7.61704L19.1979 14.7155L14.5345 15.9764L15.7993 11.3177L22.8977 4.2193V4.21835Z"></path><path d="M19.1978 14.7156L14.5344 15.9765L15.7991 11.3178L22.8975 4.21941C23.2515 3.86454 23.6884 3.64463 24.1462 3.5578V3H3V26.1962L11.651 21.2005H24.1462V9.76716L19.1978 14.7156Z"></path><path d="M11.1708 15.9766H7.32574"></path><path d="M16.8356 9.25095H6.98218"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Bob.svg b/assets/icons/polkadot/2color/Bob.svg
new file mode 100644
index 00000000..5c31936f
--- /dev/null
+++ b/assets/icons/polkadot/2color/Bob.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.0297 11.5875L11.1215 10.5361C9.67139 8.85746 9.78596 6.33823 11.3824 4.79815C13.001 3.23677 15.5651 3.23677 17.1837 4.79815C18.7801 6.33823 18.8947 8.85746 17.4446 10.5361L16.5366 11.5872C16.0621 12.1365 16.2218 12.9845 16.8636 13.3235L18.4551 14.1643C21.6036 15.8277 23.5735 19.0963 23.5735 22.6572L23.5736 26H5.00006L5.00004 22.6523C5.00002 19.094 6.96791 15.8274 10.1136 14.1642L11.703 13.3238C12.3446 12.9845 12.5042 12.1367 12.0297 11.5875Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Bond.svg b/assets/icons/polkadot/2color/Bond.svg
new file mode 100644
index 00000000..1541ff2a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Bond.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M20.5726 6.52721C20.5726 9.02776 17.5323 11.0549 13.781 11.0549C10.0971 11.0549 7.10583 9.09799 7 6.65902V10.0861C7 12.5866 10.0403 14.6138 13.7916 14.6138C17.5429 14.6138 20.5832 12.5866 20.5832 10.0861C20.5832 9.77725 20.6621 6.81873 20.5736 6.52625L20.5726 6.52721Z"></path><path d="M13.8078 11.0555C17.5582 11.0555 20.5994 9.02828 20.5994 6.52773C20.5994 4.02719 17.5591 2 13.8078 2C10.0565 2 7.01621 4.02719 7.01621 6.52773C7.01621 9.02828 10.0565 11.0555 13.8078 11.0555Z"></path><path d="M13.8081 26L13.8081 19.3212M10.1068 22.0224L13.808 18.3212L17.5093 22.0224" stroke-miterlimit="10" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Bonded Time.svg b/assets/icons/polkadot/2color/Bonded Time.svg
new file mode 100644
index 00000000..153074c9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Bonded Time.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7.55817 8.82291L7.55818 6.82267V6.82267C7.55818 4.15918 9.71736 2 12.3808 2V2C15.0443 2 17.2035 4.15918 17.2035 6.82267V6.82267L17.2035 8.82291" fill="none"></path><path d="M21.7615 13.2941V8.82581H3V22.4706H13.9412"></path><path d="M19.941 26C23.4496 26 26.294 23.1557 26.294 19.6471C26.294 16.1384 23.4496 13.2941 19.941 13.2941C16.4324 13.2941 13.5881 16.1384 13.5881 19.6471C13.5881 23.1557 16.4324 26 19.941 26Z"></path><path d="M20.063 17.1428V19.853L19 21.1428"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Boot Node.svg b/assets/icons/polkadot/2color/Boot Node.svg
new file mode 100644
index 00000000..0ec4980b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Boot Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5358 21.0126L18.5124 16.6109"></path><path d="M9.50999 16.6247L6.44708 20.999"></path><path d="M20.4564 23.2116C20.4564 24.7425 21.6974 25.9834 23.2282 25.9834C24.759 25.9834 26 24.7425 26 23.2116C26 21.6808 24.759 20.4398 23.2282 20.4398C21.6974 20.4398 20.4564 21.6808 20.4564 23.2116Z"></path><path d="M2.00001 23.2116C2.00001 24.7425 3.24099 25.9834 4.77183 25.9834C6.30266 25.9834 7.54364 24.7425 7.54364 23.2116C7.54364 21.6808 6.30266 20.4398 4.77183 20.4398C3.24099 20.4398 2.00001 21.6808 2.00001 23.2116Z"></path><path d="M5.99593 10.0054C5.99593 14.4267 9.58006 18.0108 14.0013 18.0108C18.4226 18.0108 22.0067 14.4267 22.0067 10.0054C22.0067 5.58414 18.4226 2 14.0013 2C9.58006 2 5.99593 5.58414 5.99593 10.0054Z" stroke-miterlimit="10"></path><path d="M14.0012 6.57411L14.0012 12.5M11.0078 10.4461L14.0012 13.4394L16.9945 10.4461"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Bridge.svg b/assets/icons/polkadot/2color/Bridge.svg
new file mode 100644
index 00000000..ea2f4c52
--- /dev/null
+++ b/assets/icons/polkadot/2color/Bridge.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.9986 20.3965L25 8.39652L3 8.39648L3.00008 20.3965L5.75 20.3965C5.75 20.3965 8.57808 16.3182 14.039 16.3182C19.5 16.3182 22.25 20.3965 22.25 20.3965L24.9986 20.3965Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Bridges.svg b/assets/icons/polkadot/2color/Bridges.svg
new file mode 100644
index 00000000..1697c805
--- /dev/null
+++ b/assets/icons/polkadot/2color/Bridges.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.9344 11.1342L5.93432 7.39648L26 7.39651L25.9986 18.0195H22.2622"></path><path d="M22.0643 22.3474L22.0656 11.331L2 11.3309L2.00008 22.3473L4.5082 22.3474C4.5082 22.3474 7.08762 18.6034 12.0684 18.6034C17.0492 18.6034 19.5574 22.3473 19.5574 22.3473L22.0643 22.3474Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Build.svg b/assets/icons/polkadot/2color/Build.svg
new file mode 100644
index 00000000..7ea84bdb
--- /dev/null
+++ b/assets/icons/polkadot/2color/Build.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M4 22.5743V12.0632L13.0655 16.4888V27L4 22.5743Z"></path><path d="M26.16 22.5743V12.0632L17.0945 16.4888V27L26.16 22.5743Z"></path><path d="M13.0268 3.97772L15.08 3L17.1332 3.97772M13.0268 11.7994L15.08 12.7772L17.1332 11.7994M22.9017 9.05252L25.346 7.88858L22.9017 6.72463M7.25825 6.72463L4.81396 7.88858L7.25825 9.05252" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Builders _ Developers.svg b/assets/icons/polkadot/2color/Builders _ Developers.svg
new file mode 100644
index 00000000..4883df53
--- /dev/null
+++ b/assets/icons/polkadot/2color/Builders _ Developers.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 24 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8 7V6C8 3.791 9.791 2 12 2C14.209 2 16 3.791 16 6V7H8Z"></path><path d="M18 7H6"></path><path d="M16.458 15.565L15.222 15.227C14.383 14.997 14.066 13.975 14.627 13.311L15.467 12.317C16.761 10.786 16.862 8.638 15.849 7H8.14202C7.12902 8.637 7.23002 10.785 8.52402 12.317L9.36402 13.311C9.92502 13.975 9.60802 14.997 8.76902 15.227L7.53602 15.565C4.26602 16.461 1.99902 19.432 1.99902 22.823V26H22V22.828C22 19.435 19.731 16.461 16.458 15.565Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Built-in Security.svg b/assets/icons/polkadot/2color/Built-in Security.svg
new file mode 100644
index 00000000..70144ddc
--- /dev/null
+++ b/assets/icons/polkadot/2color/Built-in Security.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.7808 24.1821L17.2887 26.9686L23.0111 23.6745L21.9164 20.1316L22.354 18.8179L26.3849 18.1253V11.3141L22.7723 10.4881L21.9463 9.055L23.0908 5.51209L17.3783 2.21797L14.8306 4.95478H13.2084L10.7105 2.16821L4.98805 5.46233L6.09273 9.06495L5.30652 10.4383L1.60437 11.2146V17.8227L5.27666 18.6587L6.07282 20.0321L4.89848 23.6247L10.6209 26.9288L13.1587 24.1821H14.7808Z" stroke-miterlimit="10"></path><path d="M18.3612 13.521H9.63867V19.0227H18.3612V13.521Z"></path><path d="M11.2649 13.2998V11.3034C11.2649 10.578 11.553 9.88235 12.066 9.36943C12.5789 8.85651 13.2746 8.56836 13.9999 8.56836C14.7235 8.57115 15.4164 8.86054 15.9271 9.37316C16.4377 9.88577 16.7244 10.5798 16.7244 11.3034V13.2998"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Burn.svg b/assets/icons/polkadot/2color/Burn.svg
new file mode 100644
index 00000000..e416df07
--- /dev/null
+++ b/assets/icons/polkadot/2color/Burn.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7.04912 19.2857C7.52476 22.6895 10.158 25 13.3536 25C17.5634 25 19.5687 22.8234 19.953 19.2857C20.2632 16.4294 18.9369 12.3422 18.9369 12.3422L16.5333 16.8182L13.3536 5L10.4667 12.2727L8.44959 9.01993C8.44959 9.01993 6.68661 16.6916 7.04912 19.2857Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/C++.svg b/assets/icons/polkadot/2color/C++.svg
new file mode 100644
index 00000000..80168955
--- /dev/null
+++ b/assets/icons/polkadot/2color/C++.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 26 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 20.4615L13.0769 26L24.1538 20.4615V7.53846L13.0769 2L2 7.53846V20.4615Z"></path><path d="M14.29 18.9378C13.5147 19.306 12.6612 19.4994 11.7948 19.5031C10.9284 19.5068 10.0719 19.3207 9.29088 18.9592C8.50984 18.5976 7.82488 18.07 7.28834 17.4168C6.7518 16.7635 6.37787 16.0019 6.19513 15.1901C6.01239 14.3783 6.02567 13.5378 6.23396 12.7328C6.44225 11.9278 6.84003 11.1796 7.39691 10.5454C7.95379 9.91125 8.65504 9.40783 9.44707 9.07363C10.2391 8.73943 11.101 8.58331 11.9668 8.61719C12.8355 8.64962 13.6852 8.87373 14.4498 9.27204"></path><path d="M12.0288 14.0482L15.0229 14.0482" stroke-miterlimit="10"></path><path d="M13.526 12.5582L13.526 15.539" stroke-miterlimit="10"></path><path d="M18.1739 14.0482L21.168 14.0482" stroke-miterlimit="10"></path><path d="M19.6711 12.5582L19.6711 15.539" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Calendar.svg b/assets/icons/polkadot/2color/Calendar.svg
new file mode 100644
index 00000000..36cd599e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Calendar.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M18.6289 26H2V3.88452H26V18.9448V26H18.6289Z" stroke-miterlimit="10"></path><path d="M9.42346 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34183V2.00012" stroke-miterlimit="10"></path><path d="M3 11.2501H25" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Career.svg b/assets/icons/polkadot/2color/Career.svg
new file mode 100644
index 00000000..93bd6dba
--- /dev/null
+++ b/assets/icons/polkadot/2color/Career.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M10.3813 7.45019V3H19.6192V7.5" fill="none"></path><path d="M27 7.62796H3V24.2377H27V7.62796Z"></path><path d="M4 14.3445L26 14.3445"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Certificate.svg b/assets/icons/polkadot/2color/Certificate.svg
new file mode 100644
index 00000000..887ae781
--- /dev/null
+++ b/assets/icons/polkadot/2color/Certificate.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.9559 19.3827V26.7229H4.38208V1.27689H23.9559V20.381"></path><path d="M16.9644 13.0457L20.0411 14.3537V5.00011L13.89 5V14.3606L16.9644 13.0457Z" stroke-miterlimit="10"></path><path d="M20.0411 22.8083H8.29675" stroke-miterlimit="10"></path><path d="M20.0411 18.8933H8.29675" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Cex.svg b/assets/icons/polkadot/2color/Cex.svg
new file mode 100644
index 00000000..68bf59d0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Cex.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.0019 7.29055C15.5315 7.29055 16.7715 6.05026 16.7715 4.52028C16.7715 2.99029 15.5315 1.75 14.0019 1.75C12.4723 1.75 11.2323 2.99029 11.2323 4.52028C11.2323 6.05026 12.4723 7.29055 14.0019 7.29055Z"></path><path d="M7.47419 25.7403C9.00379 25.7403 10.2438 24.5001 10.2438 22.9701C10.2438 21.4401 9.00379 20.1998 7.47419 20.1998C5.94458 20.1998 4.70459 21.4401 4.70459 22.9701C4.70459 24.5001 5.94458 25.7403 7.47419 25.7403Z"></path><path d="M4.7696 14.6779C6.2992 14.6779 7.53919 13.4376 7.53919 11.9076C7.53919 10.3777 6.2992 9.13736 4.7696 9.13736C3.23999 9.13736 2 10.3777 2 11.9076C2 13.4376 3.23999 14.6779 4.7696 14.6779Z"></path><path d="M23.2332 14.6779C24.7628 14.6779 26.0028 13.4376 26.0028 11.9076C26.0028 10.3777 24.7628 9.13736 23.2332 9.13736C21.7036 9.13736 20.4636 10.3777 20.4636 11.9076C20.4636 13.4376 21.7036 14.6779 23.2332 14.6779Z"></path><path d="M20.4551 25.75C21.9847 25.75 23.2247 24.5097 23.2247 22.9797C23.2247 21.4497 21.9847 20.2094 20.4551 20.2094C18.9255 20.2094 17.6855 21.4497 17.6855 22.9797C17.6855 24.5097 18.9255 25.75 20.4551 25.75Z"></path><path d="M14.0006 18.63C16.1827 18.63 17.9517 16.8606 17.9517 14.678C17.9517 12.4953 16.1827 10.726 14.0006 10.726C11.8185 10.726 10.0496 12.4953 10.0496 14.678C10.0496 16.8606 11.8185 18.63 14.0006 18.63Z"></path><path d="M11.501 17.965L8.92651 20.5395"></path><path d="M16.4661 18.0051L19.0005 20.5394"></path><path d="M14.0012 10.726L14.0012 7.29065"></path><path d="M10.1505 13.7689L7.41382 12.8087M17.8281 13.7583L20.5886 12.8087"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Chain Spec.svg b/assets/icons/polkadot/2color/Chain Spec.svg
new file mode 100644
index 00000000..27c00193
--- /dev/null
+++ b/assets/icons/polkadot/2color/Chain Spec.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.8289 2.00001L25.4517 8.6228L18.7983 15.2762L12.1755 8.65344L18.8289 2.00001Z"></path><path d="M8.61599 12.1604L15.2388 18.7832L8.62279 25.3992L1.99999 18.7764L8.61599 12.1604Z"></path><path d="M17.9941 9.41468L9.42018 17.9886"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Check.svg b/assets/icons/polkadot/2color/Check.svg
new file mode 100644
index 00000000..941f1e29
--- /dev/null
+++ b/assets/icons/polkadot/2color/Check.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 13.9459L10.7663 21L25 7" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Checked.svg b/assets/icons/polkadot/2color/Checked.svg
new file mode 100644
index 00000000..0f0990b5
--- /dev/null
+++ b/assets/icons/polkadot/2color/Checked.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 2H2V26H26V2Z"></path><path d="M8.99963 14.3184L12.6078 17.6884L19.2205 11"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Chevron Down.svg b/assets/icons/polkadot/2color/Chevron Down.svg
new file mode 100644
index 00000000..a3d2614a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Chevron Down.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25.9883 8.5625L14.9772 21.5625L3.98828 8.5625" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Chevron Up.svg b/assets/icons/polkadot/2color/Chevron Up.svg
new file mode 100644
index 00000000..9b937886
--- /dev/null
+++ b/assets/icons/polkadot/2color/Chevron Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 21.1309L14.011 8.13086L25 21.1309" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Claim.svg b/assets/icons/polkadot/2color/Claim.svg
new file mode 100644
index 00000000..8bd48df8
--- /dev/null
+++ b/assets/icons/polkadot/2color/Claim.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.00001 26V2H17L23.4615 8.46154V26H5.00001Z"></path><path d="M22.5 8.46155H17V3"></path><path d="M15.9251 12.7784H13.6415C13.4179 12.7769 13.1962 12.8196 12.9892 12.9041C12.7822 12.9885 12.5939 13.1132 12.4353 13.2707C12.2766 13.4283 12.1507 13.6157 12.0648 13.8221C11.9789 14.0285 11.9346 14.2499 11.9346 14.4735C11.9378 14.9241 12.119 15.3552 12.4387 15.6728C12.7585 15.9903 13.1908 16.1685 13.6415 16.1685H14.8186C15.2692 16.1685 15.7016 16.3467 16.0214 16.6643C16.3411 16.9818 16.5223 17.4129 16.5254 17.8636C16.5352 18.0976 16.4967 18.3312 16.4123 18.5497C16.328 18.7682 16.1995 18.967 16.035 19.1337C15.8705 19.3005 15.6734 19.4315 15.456 19.5188C15.2387 19.6061 15.0057 19.6477 14.7715 19.641H12.2996"></path><path d="M14.2065 12.7308V11.4595"></path><path d="M14.2065 20.9713V19.7589"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Close.svg b/assets/icons/polkadot/2color/Close.svg
new file mode 100644
index 00000000..6e2bbd2b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Close.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M4.89252 4.23135L24.6915 24.0303" fill="none" data-nofill="true"></path><path d="M24.6915 4.23135L4.89248 24.0303" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Cloud.svg b/assets/icons/polkadot/2color/Cloud.svg
new file mode 100644
index 00000000..20be5eb2
--- /dev/null
+++ b/assets/icons/polkadot/2color/Cloud.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M22.4647 22.2436H9.06277C5.71439 22.2436 3 19.5292 3 16.1809C3 12.8325 5.71439 10.1181 9.06277 10.1181C9.50272 10.1181 9.93174 10.165 10.3451 10.254C10.5 8.85565 11.9169 7.05177 13.0652 6.24989C16.1449 4.09916 20.3438 4.79319 22.4436 7.80005C23.7349 9.64905 23.5 11.8557 23.256 13.7969C24.2553 13.8564 25.2376 14.2679 26.0011 15.0315C27.6574 16.6877 27.6574 19.373 26.0011 21.0292C25.0632 21.9671 23.741 22.2495 22.5711 22.2495"></path><path d="M13.7635 12.3517C12.9098 11.3049 11.7132 10.5486 10.3451 10.254M20.0034 15.0315C20.8961 14.1388 22.0877 13.7273 23.2561 13.7969"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Code.svg b/assets/icons/polkadot/2color/Code.svg
new file mode 100644
index 00000000..1f7de3be
--- /dev/null
+++ b/assets/icons/polkadot/2color/Code.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7.97391 18.5638L2.00391 13.5938L7.97391 8.61377" fill="none" data-nofill="true"></path><path d="M20.0737 8.604L26.0637 13.594L20.0737 18.574" fill="none" data-nofill="true"></path><path d="M17.0488 4.59375L10.9988 22.5837" fill="none" data-nofill="true"></path></svg>
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diff --git a/assets/icons/polkadot/2color/Collapse.svg b/assets/icons/polkadot/2color/Collapse.svg
new file mode 100644
index 00000000..111cfe9d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Collapse.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.00927 25.9096L14.5662 18.0334L21.1362 25.9096" fill="none" data-nofill="true"></path><path d="M21.1357 3.13086L14.5525 11.0334L7.9824 3.13086" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Collators.svg b/assets/icons/polkadot/2color/Collators.svg
new file mode 100644
index 00000000..28968584
--- /dev/null
+++ b/assets/icons/polkadot/2color/Collators.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.3843 16.3044L21.3844 11.4024L6.61576 11.4027L6.61559 16.3047" fill="none" data-nofill="true"></path><path d="M11.2307 16.3044H2V25.5351H11.2307V16.3044Z"></path><path d="M26 16.3044H16.7693V25.5351H26V16.3044Z"></path><path d="M10.245 5.87389L14.081 2.01263L17.9358 5.8421" fill="none" data-nofill="true"></path><path d="M14.0001 3.64456V11.1735" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Collective.svg b/assets/icons/polkadot/2color/Collective.svg
new file mode 100644
index 00000000..0813667b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Collective.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.8277 19.1904C25.5298 15.9686 25.5343 12.0847 23.8414 8.85944M19.139 4.17209C15.8766 2.47308 11.9466 2.50626 8.71031 4.27164M4.18173 8.88422C2.50178 12.1046 2.51068 15.9769 4.20841 19.1904M19.152 23.8449C15.9452 25.5204 12.0909 25.5204 8.88413 23.8449" fill="none" data-nofill="true"></path><circle cx="21.8596" cy="6.1703" r="3.32689" transform="rotate(45 21.8596 6.1703)"></circle><circle cx="6.17678" cy="21.8533" r="3.32689" transform="rotate(45 6.17678 21.8533)"></circle><circle cx="6.17645" cy="6.1703" r="3.32689" transform="rotate(45 6.17645 6.1703)"></circle><circle cx="21.8596" cy="21.8535" r="3.32689" transform="rotate(45 21.8596 21.8535)"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Communications And Media.svg b/assets/icons/polkadot/2color/Communications And Media.svg
new file mode 100644
index 00000000..bcd6c445
--- /dev/null
+++ b/assets/icons/polkadot/2color/Communications And Media.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M15.5589 17.9552C14.2554 19.7707 12.0408 20.8544 9.65901 20.6041C8.79582 20.5134 7.99056 20.2558 7.27188 19.8668L3.52769 22.4989L5.31043 18.2265C4.29006 16.9514 3.75202 15.2894 3.93623 13.5369C4.23879 10.6584 6.39652 8.42401 9.09652 7.89684"></path><path d="M15.9185 2.77813C20.0071 2.34838 23.6699 5.31441 24.0996 9.40294C24.3128 11.4317 23.69 13.3556 22.5088 14.8317L24.5725 19.7775L20.2382 16.7306C19.4062 17.1808 18.474 17.479 17.4748 17.584C16.5998 17.676 15.7442 17.6124 14.9357 17.4156C11.9665 16.6928 9.63149 14.1727 9.29372 10.9592C9.17739 9.85252 9.30987 8.77702 9.64607 7.78839C10.5519 5.12465 12.9367 3.09156 15.9185 2.77813Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Community Events And Outreach.svg b/assets/icons/polkadot/2color/Community Events And Outreach.svg
new file mode 100644
index 00000000..6b259e01
--- /dev/null
+++ b/assets/icons/polkadot/2color/Community Events And Outreach.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.6289 26.5685H2V4.453H26V19.5133V26.5685H18.6289Z" stroke-miterlimit="10"></path><path d="M9.4234 6.91007V2.56836" stroke-miterlimit="10"></path><path d="M18.5766 6.91031V2.5686" stroke-miterlimit="10"></path><path d="M2.10089 11.8185H25.9999" stroke-miterlimit="10"></path><path d="M20 25.7112C20 23.62 18.6356 21.7857 16.6643 21.2257L15.9439 21.0206C15.432 20.8756 15.2372 20.2396 15.5768 19.8225L16.1083 19.1694C17.0157 18.0553 16.9432 16.4181 15.9409 15.392C14.8682 14.2938 13.1259 14.2938 12.0532 15.392C11.0509 16.4181 10.9785 18.0553 11.8858 19.1694L12.4173 19.8225C12.7569 20.2396 12.5631 20.8756 12.0512 21.0206L11.3328 21.2247C9.36248 21.7847 8 23.618 8 25.7072"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Community.svg b/assets/icons/polkadot/2color/Community.svg
new file mode 100644
index 00000000..6b0b2abc
--- /dev/null
+++ b/assets/icons/polkadot/2color/Community.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M24.3295 13.8044L23.5935 13.5994C23.0705 13.4544 22.8725 12.8184 23.2195 12.4014L23.7625 11.7484C24.6895 10.6344 24.6155 8.99745 23.5915 7.97145C22.4955 6.87345 20.7155 6.87345 19.6195 7.97145C18.5955 8.99745 18.5215 10.6344 19.4485 11.7484L19.9915 12.4014C20.3385 12.8184 20.1395 13.4544 19.6175 13.5994L18.8835 13.8034C18.3195 13.9604 17.8115 14.2254 17.3625 14.5594C17.3555 14.5674 17.3515 14.5774 17.3445 14.5854L16.8015 15.2384C16.4545 15.6554 16.6535 16.2914 17.1755 16.4364L17.9115 16.6414C19.6565 17.1264 20.9315 18.5694 21.2425 20.3054H27.7385V18.2884C27.7385 16.1974 26.3445 14.3634 24.3305 13.8034L24.3295 13.8044Z"></path><path d="M12.782 16.5625L13.1967 16.4384C13.5377 16.3434 13.5412 15.8799 13.5442 15.5639C12.9412 14.6559 12.2137 14.1134 11.1077 13.8054L10.3737 13.6014C9.85166 13.4564 9.65266 12.8204 9.99966 12.4034L10.5427 11.7504C11.4697 10.6364 11.3957 8.9994 10.3717 7.9734C9.27566 6.8754 7.49566 6.8754 6.39966 7.9734C5.37566 8.9994 5.30166 10.6364 6.22866 11.7504L6.77166 12.4034C7.11866 12.8204 6.91966 13.4564 6.39766 13.6014L5.66166 13.8064C3.64766 14.3664 2.25366 16.2004 2.25366 18.2914V20.3084H9.13566C9.44566 18.5724 10.7197 17.1294 12.4647 16.6444L12.782 16.5625Z"></path><path d="M13.5718 15.2393L13.0288 14.5863C12.1018 13.4723 12.1758 11.8353 13.1998 10.8093C14.2958 9.71134 16.0758 9.71134 17.1718 10.8093C18.1958 11.8353 18.2698 13.4723 17.3428 14.5863L16.7998 15.2393C16.4528 15.6563 16.6518 16.2923 17.1748 16.4373L17.9108 16.6423C19.9248 17.2023 21.3188 19.0363 21.3188 21.1273V23.1433H9.05884V21.1233C9.05884 19.0343 10.4508 17.2013 12.4638 16.6413L13.1978 16.4373C13.7208 16.2923 13.9188 15.6563 13.5718 15.2393Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Companion Account (in Bridge context).svg b/assets/icons/polkadot/2color/Companion Account (in Bridge context).svg
new file mode 100644
index 00000000..c7313c60
--- /dev/null
+++ b/assets/icons/polkadot/2color/Companion Account (in Bridge context).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.322 12.0015L15.1859 10.9629C16.6598 9.19058 16.5418 6.58738 14.913 4.95579C13.1691 3.20899 10.3393 3.20899 8.59532 4.95579C6.96656 6.58738 6.84853 9.19058 8.32244 10.9629L9.1864 12.0015C9.73782 12.6643 9.42245 13.6765 8.5906 13.9069L7.42072 14.2327C4.21701 15.1231 2 18.0407 2 21.3662L2 24.5737H21.4999V21.3605C21.4999 18.0378 19.2857 15.1231 16.0848 14.2327L14.9168 13.9079C14.0859 13.6765 13.7696 12.6643 14.322 12.0015Z"></path><path d="M12.7102 3.74915C13.5175 3.92572 14.2861 4.32795 14.914 4.9568C16.5428 6.5884 16.6608 9.19159 15.1869 10.9639L14.3229 12.0025C13.7715 12.6653 14.0869 13.6766 14.9178 13.9079L16.0858 14.2327C19.2866 15.1231 21.5008 18.0379 21.5008 21.3606V22.927H26V19.7139C26 16.3912 23.7858 13.4764 20.5849 12.586L19.417 12.2612C18.586 12.0299 18.2697 11.0186 18.8221 10.3558L19.6861 9.31717C21.16 7.54489 21.0419 4.94169 19.4132 3.31009C17.6692 1.5633 14.8394 1.5633 13.0955 3.31009C12.9557 3.44984 12.8282 3.59619 12.7102 3.74915Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Connect Wallet_Address.svg b/assets/icons/polkadot/2color/Connect Wallet_Address.svg
new file mode 100644
index 00000000..3352f8fe
--- /dev/null
+++ b/assets/icons/polkadot/2color/Connect Wallet_Address.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.1556 15.7924L14.1556 20.4568"></path><path d="M26 23.2284L16.8586 23.2284M2 23.2284L11.2816 23.2284"></path><path d="M14.0751 26C15.608 26 16.8507 24.7591 16.8507 23.2284C16.8507 21.6977 15.608 20.4568 14.0751 20.4568C12.5421 20.4568 11.2994 21.6977 11.2994 23.2284C11.2994 24.7591 12.5421 26 14.0751 26Z"></path><path d="M22.3687 2H6V15.79H22.3687V2Z"></path><path d="M21.56 5.67551H16.6018C14.8237 5.67551 13.3823 7.1169 13.3823 8.89496C13.3823 10.673 14.8237 12.1144 16.6018 12.1144H21.56C22.0117 12.1144 22.3778 11.7483 22.3778 11.2966V6.49328C22.3778 6.04164 22.0117 5.67551 21.56 5.67551Z"></path><path d="M16.438 8.85698L16.4228 8.84174" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Connected.svg b/assets/icons/polkadot/2color/Connected.svg
new file mode 100644
index 00000000..c60ba3e0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Connected.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M17.4675 18.6279L22.241 18.6279C24.8532 18.6279 26.9708 16.5103 26.9708 13.8981V13.8981C26.9708 11.2859 24.8532 9.16832 22.241 9.16832L17.4675 9.16832" fill="none" data-nofill="true"></path><path d="M12.4206 9.13085L7.70051 9.13085C5.08831 9.13085 2.9707 11.2485 2.9707 13.8607V13.8607C2.9707 16.4728 5.08831 18.5905 7.70051 18.5905L12.4206 18.5905" fill="none" data-nofill="true"></path><path d="M21.079 13.8675L8.83264 13.8675" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Connection Via Light Node.svg b/assets/icons/polkadot/2color/Connection Via Light Node.svg
new file mode 100644
index 00000000..1305ed6d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Connection Via Light Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11.4052 9.67229C12.9211 11.1883 15.379 11.1883 16.895 9.67229C18.411 8.15631 18.411 5.69841 16.895 4.18243C15.379 2.66645 12.9211 2.66645 11.4052 4.18243C9.88917 5.69841 9.88917 8.15631 11.4052 9.67229Z"></path><path d="M21.8326 20.2595L18.6832 15.6744"></path><path d="M9.3056 15.6887L6.11505 20.2453"></path><path d="M20.7082 22.5502C20.7082 24.1448 22.0009 25.4375 23.5955 25.4375C25.1901 25.4375 26.4828 24.1448 26.4828 22.5502C26.4828 20.9555 25.1901 19.6628 23.5955 19.6628C22.0009 19.6628 20.7082 20.9555 20.7082 22.5502Z"></path><path d="M1.4826 22.5502C1.4826 24.1448 2.7753 25.4375 4.36993 25.4375C5.96456 25.4375 7.25726 24.1448 7.25726 22.5502C7.25726 20.9555 5.96456 19.6628 4.36993 19.6628C2.7753 19.6628 1.4826 20.9555 1.4826 22.5502Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Connection Via Remote Node.svg b/assets/icons/polkadot/2color/Connection Via Remote Node.svg
new file mode 100644
index 00000000..d0b4a563
--- /dev/null
+++ b/assets/icons/polkadot/2color/Connection Via Remote Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.6088 6.31161L18.7289 2.1188"></path><path d="M10.1536 2.13193L7.23602 6.29865"></path><path d="M20.5806 8.40625C20.5806 9.86444 21.7627 11.0465 23.2209 11.0465C24.679 11.0465 25.8611 9.86444 25.8611 8.40625C25.8611 6.94806 24.679 5.76596 23.2209 5.76596C21.7627 5.76596 20.5806 6.94806 20.5806 8.40625Z"></path><path d="M3 8.40625C3 9.86444 4.1821 11.0465 5.64029 11.0465C7.09848 11.0465 8.28058 9.86444 8.28058 8.40625C8.28058 6.94806 7.09848 5.76596 5.64029 5.76596C4.1821 5.76596 3 6.94806 3 8.40625Z"></path><path d="M11.9205 23.4899C13.3067 24.8762 15.5543 24.8762 16.9406 23.4899C18.3269 22.1037 18.3269 19.8561 16.9406 18.4698C15.5543 17.0835 13.3067 17.0835 11.9205 18.4698C10.5342 19.8561 10.5342 22.1037 11.9205 23.4899Z"></path><path d="M14.445 13.1975L14.4451 2.00001M17.5406 10.7918L14.4215 13.9109L11.3024 10.7917" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Consensus.svg b/assets/icons/polkadot/2color/Consensus.svg
new file mode 100644
index 00000000..d79dd863
--- /dev/null
+++ b/assets/icons/polkadot/2color/Consensus.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 2C20.6274 2 26 6.00877 26 10.9538C26 13.3124 24.7688 15.392 22.7711 16.9912L24.4427 23.6403L18.283 19.247C17.7411 19.3992 16.9172 19.5922 16.2083 19.6813L14.0407 24.6403L11.5962 19.657C10.9222 19.5699 10.2602 19.3957 9.72631 19.248L3.55603 23.6431L5.23852 16.9971C3.24087 15.3979 2 13.3124 2 10.9538C2 6.00877 7.37258 2 14 2Z"></path><path d="M9.38666 11.0673L13.0277 14.468L19.7007 7.71863"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Contract.svg b/assets/icons/polkadot/2color/Contract.svg
new file mode 100644
index 00000000..77b97bda
--- /dev/null
+++ b/assets/icons/polkadot/2color/Contract.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.5874 17.1336L14.457 18.11L15.4333 13.9786L20.3809 9.03099V8.99469V2.16336H2.16339V25.8459H11.2721H20.3809V15.3411L18.5874 17.1336Z"></path><path d="M16.7372 5.80707H5.80707" stroke-miterlimit="10"></path><path d="M12.1833 9.44983H5.80707" stroke-miterlimit="10"></path><path d="M12.1824 21.2892H5.80707" stroke-miterlimit="10"></path><path d="M22.0282 7.38367C22.8993 6.51253 24.3121 6.51253 25.1833 7.38367C26.0544 8.2548 26.0544 9.6676 25.1833 10.5387L18.5883 17.1337L14.457 18.11L15.4333 13.9786L22.0282 7.38367Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Cooling Period.svg b/assets/icons/polkadot/2color/Cooling Period.svg
new file mode 100644
index 00000000..20c9533d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Cooling Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 26H2V3.88452H26V26Z" stroke-miterlimit="10"></path><path d="M9.42337 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34177V2.00006" stroke-miterlimit="10"></path><path d="M19.2884 18.2949L17.1375 16.1441M17.1375 16.1441L19.2885 13.9931M17.1375 16.1441L11.1802 16.1441M9.00003 13.9931L11.1509 16.144L8.99999 18.295"></path><path d="M11.9934 21.2884L14.1443 19.1375M14.1443 19.1375L16.2952 21.2885M14.1443 19.1375L14.1443 13.1802M16.2952 11L14.1443 13.1509L11.9934 11"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Copy _ Paste.svg b/assets/icons/polkadot/2color/Copy _ Paste.svg
new file mode 100644
index 00000000..85f89d9b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Copy _ Paste.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M8.99414 8.5V2H25.9941V19H19.4941"></path><path d="M18.9941 9H1.99414V26H18.9941V9Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Costly To Maintain.svg b/assets/icons/polkadot/2color/Costly To Maintain.svg
new file mode 100644
index 00000000..7e919f5e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Costly To Maintain.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/2color/Council.svg b/assets/icons/polkadot/2color/Council.svg
new file mode 100644
index 00000000..f1017f94
--- /dev/null
+++ b/assets/icons/polkadot/2color/Council.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.6501 14.6921H23.9518C23.8887 12.3445 22.3113 10.3001 20.0372 9.6682L19.1896 9.43278C18.5879 9.26516 18.3591 8.53252 18.7583 8.05226L19.3836 7.29985C20.4515 6.01632 20.3658 4.13011 19.1859 2.94923C17.9231 1.68359 15.873 1.68359 14.6102 2.94923C13.4302 4.13105 13.3455 6.01632 14.4124 7.29985L15.0377 8.05226C15.437 8.53252 15.2082 9.26516 14.6064 9.43278L13.7608 9.6682C12.4735 10.026 11.4207 10.8463 10.7266 11.9075C10.7426 12.2607 10.9724 12.595 11.3547 12.7014L12.2004 12.9368C14.21 13.4962 15.6781 15.1583 16.035 17.1575H19.6482L19.6501 14.6921Z"></path><path d="M10.9254 11.3208L11.5506 10.5684C12.6185 9.28489 12.5328 7.39868 11.3529 6.2178C10.0901 4.95216 8.04002 4.95216 6.77721 6.2178C5.59727 7.39962 5.51251 9.28489 6.57945 10.5684L7.20474 11.3208C7.60401 11.8011 7.37518 12.5337 6.77344 12.7014L5.92592 12.9368C3.60559 13.5818 2 15.695 2 18.1038V20.427H16.1235V18.1001C16.1235 15.6941 14.5198 13.5828 12.2014 12.9368L11.3557 12.7014C10.754 12.5337 10.5251 11.8011 10.9244 11.3208H10.9254Z"></path><path d="M26 25.1949V14.6922H19.6511V25.2005L22.8246 23.9085L26 25.1949Z"></path></svg>
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diff --git a/assets/icons/polkadot/2color/Countdown.svg b/assets/icons/polkadot/2color/Countdown.svg
new file mode 100644
index 00000000..c27809a8
--- /dev/null
+++ b/assets/icons/polkadot/2color/Countdown.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M6.99408 26.125L23.9941 26.125"></path><path d="M6.99414 2.125L23.9941 2.125"></path><path d="M21.9171 8.365V2.125L8.99402 2.125L8.99402 8.365L15.4556 14.125L21.9171 8.365Z"></path><path d="M8.9941 19.885L8.9941 26.125L21.9172 26.125L21.9172 19.885L15.4556 14.125L8.9941 19.885Z"></path></g></svg>
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diff --git a/assets/icons/polkadot/2color/Create New From Source.svg b/assets/icons/polkadot/2color/Create New From Source.svg
new file mode 100644
index 00000000..afd066f1
--- /dev/null
+++ b/assets/icons/polkadot/2color/Create New From Source.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.636 18.7083L18.636 25.125L3.05265 25.125L3.05266 9.54167L9.01099 9.54167"></path><path d="M9.4694 18.7083L25.0527 18.7083L25.0527 3.12498L9.4694 3.12498L9.4694 18.7083Z"></path><path d="M13.1581 10.8424L21.2598 10.8862"></path><path d="M17.2319 6.81445L17.1881 14.9161"></path></svg>
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diff --git a/assets/icons/polkadot/2color/Cross-Chain Application.svg b/assets/icons/polkadot/2color/Cross-Chain Application.svg
new file mode 100644
index 00000000..88a9ca98
--- /dev/null
+++ b/assets/icons/polkadot/2color/Cross-Chain Application.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M1.99997 26.4316L26.2441 26.4316L26.2441 2.43164L1.99997 2.43164L1.99997 26.4316Z"></path><path d="M26.2371 9.01086H2.00026"></path><path d="M9.32502 5.89942L9.30768 5.88208" stroke-miterlimit="10"></path><path d="M5.50117 5.89942L5.48383 5.88208" stroke-miterlimit="10"></path><path d="M19.1895 9.93164L19.1895 14.2167M19.1895 25.4316L19.1895 20.9517"></path><path d="M9 9.93164L9 14.2167M8.99998 25.4316L8.99998 20.9517"></path><path d="M12.2806 14.458H6V20.7386H12.2806V14.458Z"></path><path d="M22.3295 14.458H16.0489V20.7386H22.3295V14.458Z"></path><path d="M12.2808 17.5984L16.0493 17.5984"></path></svg>
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diff --git a/assets/icons/polkadot/2color/Cross-Chain Certification.svg b/assets/icons/polkadot/2color/Cross-Chain Certification.svg
new file mode 100644
index 00000000..af99ec4d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Cross-Chain Certification.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8 12.8684L2 12.8684L2 22.0992H11.2308L11.2308 16.7327"></path><path d="M20.5 12.8685L25.9998 12.8685V22.0993H16.769V17"></path><path d="M11.2308 17.4836L16.7694 17.4836"></path><path d="M14.4286 17.2889C17.9791 17.2889 20.8573 14.4107 20.8573 10.8603C20.8573 7.30984 17.9791 4.43164 14.4286 4.43164C10.8782 4.43164 8 7.30984 8 10.8603C8 14.4107 10.8782 17.2889 14.4286 17.2889Z"></path><path d="M12.0362 10.5404L13.9691 12.3458L17.2771 9"></path></svg>
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diff --git a/assets/icons/polkadot/2color/Cross-Chain Transfers.svg b/assets/icons/polkadot/2color/Cross-Chain Transfers.svg
new file mode 100644
index 00000000..188c1554
--- /dev/null
+++ b/assets/icons/polkadot/2color/Cross-Chain Transfers.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Cross-Chain.svg b/assets/icons/polkadot/2color/Cross-Chain.svg
new file mode 100644
index 00000000..618bea72
--- /dev/null
+++ b/assets/icons/polkadot/2color/Cross-Chain.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M6.46256 2L6.46256 9.02948M6.46254 26L6.46254 18.9235"></path><path d="M21.3759 2L21.3759 9.02948M21.3759 26L21.3759 18.9235"></path><path d="M11.2265 9.38394H2V18.6105H11.2265V9.38394Z"></path><path d="M25.9891 9.38394H16.7626V18.6105H25.9891V9.38394Z"></path><path d="M12.1115 13.9972L15.8775 13.9972"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Crowdloans.svg b/assets/icons/polkadot/2color/Crowdloans.svg
new file mode 100644
index 00000000..39ca7d44
--- /dev/null
+++ b/assets/icons/polkadot/2color/Crowdloans.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M25.8173 25.8292L22 22.022M21.476 25.1348L21.464 21.4874L25.115 21.4754" stroke-miterlimit="10"></path><path d="M25.8173 2.17082L21.9881 6M21.476 2.86516L21.464 6.51259L25.115 6.52456" stroke-miterlimit="10"></path><path d="M2.18269 25.8292L5.97493 22.047M6.52398 25.1348L6.53597 21.4874L2.88498 21.4754" stroke-miterlimit="10"></path><path d="M2.18269 2.17082L6 5.97804M6.52398 2.86516L6.53597 6.51259L2.88498 6.52456" stroke-miterlimit="10"></path><path d="M19.8726 12.4064C19.8726 14.6668 17.117 16.4992 13.717 16.4992C10.378 16.4992 7.66682 14.7302 7.5709 12.5256V15.6234C7.5709 17.8838 10.3265 19.7162 13.7266 19.7162C17.1266 19.7162 19.8822 17.8838 19.8822 15.6234C19.8822 15.3443 19.9537 12.6699 19.8735 12.4055L19.8726 12.4064Z"></path><path d="M13.7169 16.4993C17.116 16.4993 19.8725 14.6668 19.8725 12.4065C19.8725 10.1461 17.1169 8.31367 13.7169 8.31367C10.3168 8.31367 7.56121 10.1461 7.56121 12.4065C7.56121 14.6668 10.3168 16.4993 13.7169 16.4993Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Cryptocurrency.svg b/assets/icons/polkadot/2color/Cryptocurrency.svg
new file mode 100644
index 00000000..76d93b2d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Cryptocurrency.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 26" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.8885 11.3879C23.3217 11.3879 26.1049 14.1711 26.1049 17.6043C26.1049 21.0375 23.3217 23.8207 19.8885 23.8207C17.3384 23.8207 15.1469 22.2851 14.1882 20.0882" stroke-miterlimit="10"></path><path d="M13.8626 15C14.2286 15.7922 14.4328 16.6744 14.4328 17.6044C14.4328 21.0376 11.6496 23.8208 8.21643 23.8208C4.78322 23.8208 2.00006 21.0376 2.00006 17.6044C2.00006 14.2107 4.71949 11.4522 8.09809 11.3891" stroke-miterlimit="10"></path><path d="M13.9888 14.4327C17.422 14.4327 20.2051 11.6496 20.2051 8.21637C20.2051 4.78316 17.422 2 13.9888 2C10.5556 2 7.7724 4.78316 7.7724 8.21637C7.7724 11.6496 10.5556 14.4327 13.9888 14.4327Z" stroke-miterlimit="10"></path></svg>
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diff --git a/assets/icons/polkadot/2color/Customisation.svg b/assets/icons/polkadot/2color/Customisation.svg
new file mode 100644
index 00000000..a69d9fff
--- /dev/null
+++ b/assets/icons/polkadot/2color/Customisation.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/DAOs.svg b/assets/icons/polkadot/2color/DAOs.svg
new file mode 100644
index 00000000..2870c85d
--- /dev/null
+++ b/assets/icons/polkadot/2color/DAOs.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/2color/DEX.svg b/assets/icons/polkadot/2color/DEX.svg
new file mode 100644
index 00000000..707d885f
--- /dev/null
+++ b/assets/icons/polkadot/2color/DEX.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Dapps.svg b/assets/icons/polkadot/2color/Dapps.svg
new file mode 100644
index 00000000..cfb39653
--- /dev/null
+++ b/assets/icons/polkadot/2color/Dapps.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Data & Analytics.svg b/assets/icons/polkadot/2color/Data & Analytics.svg
new file mode 100644
index 00000000..89fe254c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Data & Analytics.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.00616 11.1632L11.3374 4.83194L17.6687 11.1632L23.303 4.55295" fill="none"></path><path d="M11.3313 11.3865L11.3313 23.2954" fill="none"></path><path d="M5 15.6073L5 23.2953" fill="none"></path><path d="M17.6625 15.6073L17.6625 23.2954" fill="none"></path><path d="M23.9938 12.4418L23.9938 23.2954" fill="none"></path><path d="M19.7792 3.99998L23.9938 3.99998L23.9938 8.22083" fill="none"></path></svg>
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diff --git a/assets/icons/polkadot/2color/Day_Light Mode.svg b/assets/icons/polkadot/2color/Day_Light Mode.svg
new file mode 100644
index 00000000..7c657920
--- /dev/null
+++ b/assets/icons/polkadot/2color/Day_Light Mode.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.0528 19.1297C16.8142 19.1297 19.0528 16.8901 19.0528 14.1273C19.0528 11.3646 16.8142 9.12502 14.0528 9.12502C11.2914 9.12502 9.0528 11.3646 9.0528 14.1273C9.0528 16.8901 11.2914 19.1297 14.0528 19.1297Z"></path><path d="M14.0527 26.125L14.0527 23.125"></path><path d="M14.5381 5.125L14.5381 2.125"></path><path d="M2.05273 14.125L5.05273 14.125"></path><path d="M23.0527 14.125L26.0527 14.125"></path><path d="M5.56722 22.6103L7.68854 20.489"></path><path d="M20.9019 7.76112L23.0232 5.6398"></path><path d="M6.05281 5.6397L8.17413 7.76102"></path><path d="M20.4167 20.4889L22.538 22.6102"></path></svg>
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diff --git a/assets/icons/polkadot/2color/DeFi.svg b/assets/icons/polkadot/2color/DeFi.svg
new file mode 100644
index 00000000..586503db
--- /dev/null
+++ b/assets/icons/polkadot/2color/DeFi.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M22.4125 13.4391V16.8098C22.4125 19.5404 19.0921 21.445 14.9961 21.445C10.9001 21.445 7.57971 19.5404 7.57971 16.8098V13.4391"></path><path d="M14.9961 17.8865C19.0921 17.8865 22.4125 15.6729 22.4125 12.9423C22.4125 10.2116 19.0921 7.99802 14.9961 7.99802C10.9001 7.99802 7.57971 10.2116 7.57971 12.9423C7.57971 15.6729 10.9001 17.8865 14.9961 17.8865Z"></path><path d="M4.71967 27.7494C6.08514 27.7494 7.19208 26.6407 7.19208 25.2731C7.19208 23.9054 6.08514 22.7967 4.71967 22.7967C3.35419 22.7967 2.24725 23.9054 2.24725 25.2731C2.24725 26.6407 3.35419 27.7494 4.71967 27.7494Z"></path><path d="M25.2917 27.7514C26.6413 27.7514 27.7353 26.6556 27.7353 25.3039C27.7353 23.9522 26.6413 22.8564 25.2917 22.8564C23.9422 22.8564 22.8481 23.9522 22.8481 25.3039C22.8481 26.6556 23.9422 27.7514 25.2917 27.7514Z"></path><path d="M4.71978 7.1869C6.08208 7.1869 7.18645 6.08076 7.18645 4.71627C7.18645 3.35178 6.08208 2.24564 4.71978 2.24564C3.35748 2.24564 2.25311 3.35178 2.25311 4.71627C2.25311 6.08076 3.35748 7.1869 4.71978 7.1869Z"></path><path d="M25.2965 7.14925C26.6487 7.14925 27.7449 6.05132 27.7449 4.69696C27.7449 3.34259 26.6487 2.24466 25.2965 2.24466C23.9443 2.24466 22.8481 3.34259 22.8481 4.69696C22.8481 6.05132 23.9443 7.14925 25.2965 7.14925Z"></path><path d="M9.26587 9.25372L6.57501 6.55472"></path><path d="M20.5292 9.45676L23.4245 6.55472"></path><path d="M20.4209 20.4608L23.4252 23.4653"></path><path d="M9.61944 20.4143L6.49255 23.5485"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Decentralised File Storage.svg b/assets/icons/polkadot/2color/Decentralised File Storage.svg
new file mode 100644
index 00000000..f0be1a97
--- /dev/null
+++ b/assets/icons/polkadot/2color/Decentralised File Storage.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M5.92887 21.9746L8.58764 19.4102M22.0787 5.94148C22.4963 6.36388 23.0756 6.62554 23.716 6.62554C24.9885 6.62554 26.0201 5.59228 26.0201 4.3177C26.0201 3.04312 24.9885 2.00986 23.716 2.00986C22.4435 2.00986 21.4119 3.04312 21.4119 4.3177C21.4119 4.95088 21.6665 5.5245 22.0787 5.94148ZM22.0787 5.94148L22.081 5.9392M22.0787 5.94148L18.4691 9.52873M5.98825 5.96243L7.22554 7.19972L8.11709 8.11709M22.081 21.9746C21.6227 22.3957 21.3354 23.0004 21.3354 23.6724C21.3354 24.9445 22.365 25.9757 23.6351 25.9757C24.9051 25.9757 25.9347 24.9445 25.9347 23.6724C25.9347 22.4003 24.9051 21.3691 23.6351 21.3691C23.0359 21.3691 22.4902 21.5986 22.081 21.9746ZM22.081 21.9746L22.0817 21.9753M22.081 21.9746L19.8807 19.4102M6.65354 23.6695C6.65354 24.9566 5.61181 26 4.32677 26C3.04173 26 2 24.9566 2 23.6695C2 22.3824 3.04173 21.339 4.32677 21.339C5.61181 21.339 6.65354 22.3824 6.65354 23.6695ZM6.65615 4.32511C6.65615 5.60922 5.61684 6.6502 4.33479 6.6502C3.05274 6.6502 2.01343 5.60922 2.01343 4.32511C2.01343 3.04099 3.05274 2.00002 4.33479 2.00002C5.61684 2.00002 6.65615 3.04099 6.65615 4.32511Z"></path><path d="M7.44904 8.62103H12.4695L14.2742 10.191H20.6825V18.8291H7.44904V8.62103Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Delete_Cancel.svg b/assets/icons/polkadot/2color/Delete_Cancel.svg
new file mode 100644
index 00000000..943855cf
--- /dev/null
+++ b/assets/icons/polkadot/2color/Delete_Cancel.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26.0527 6.125H9.35708L2.05273 14.4728L9.35708 22.8207H26.0527V6.125Z"></path><path d="M14.0527 17.9231L20.8875 11.1618"></path><path d="M14.091 11.125L20.8523 17.9598"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Democracy.svg b/assets/icons/polkadot/2color/Democracy.svg
new file mode 100644
index 00000000..198a634a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Democracy.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.4073 14.0779C17.4073 12.8246 17.4246 8.15076 17.4355 5.31269C17.4403 4.07636 16.4394 3.07286 15.203 3.07286V3.07286C13.9702 3.07286 12.9708 4.07226 12.9708 5.30509L12.9708 11.4237L12.9707 3.94594C12.9707 2.87123 11.9692 2 10.7339 2C9.49861 2 8.49719 2.87122 8.49719 3.94593L8.49719 11.4237L8.49719 7.09448C8.49719 6.01976 7.47206 5.14854 6.23674 5.14854C5.00142 5.14854 4 6.01976 4 7.09448L4 11.9943L4.00004 15.3687C4.00013 19.1459 7.76403 20.6571 7.76403 20.6571L7.76403 26L16.0785 26L16.0785 20.6571C16.0785 20.6571 17.3382 20.3811 20.3229 18.1508C23.0038 16.1475 23.4183 14.1302 23.4749 13.7403C23.4815 13.6948 23.4831 13.6499 23.4831 13.6038V13.6038C23.4831 11.9579 21.3989 11.1732 20.2377 12.3396C18.791 13.7928 17.4073 14.9538 17.4073 14.0779Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Deposit.svg b/assets/icons/polkadot/2color/Deposit.svg
new file mode 100644
index 00000000..a50d3b1b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Deposit.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.706 26L6 26" fill="none" data-nofill="true"></path><path d="M14.4865 2L14.4865 20.5M20.0165 15.921L14.4865 21.4482L8.95172 15.9227" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Derivation Path.svg b/assets/icons/polkadot/2color/Derivation Path.svg
new file mode 100644
index 00000000..c25681ea
--- /dev/null
+++ b/assets/icons/polkadot/2color/Derivation Path.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M5.57671 18.5456L5.57672 14.3724L22.2757 14.3724L22.2757 18.6534" fill="none" data-nofill="true"></path><path d="M14.0215 9.44831L14.0215 14.0507"></path><path d="M2 22.3774C2 24.4342 3.6674 26.1016 5.72424 26.1016C7.78108 26.1016 9.44848 24.4342 9.44848 22.3774C9.44848 20.3206 7.78108 18.6532 5.72424 18.6532C3.6674 18.6532 2 20.3206 2 22.3774Z"></path><path d="M18.5515 22.3774C18.5515 24.4342 20.2189 26.1016 22.2758 26.1016C24.3326 26.1016 26 24.4342 26 22.3774C26 20.3206 24.3326 18.6532 22.2758 18.6532C20.2189 18.6532 18.5515 20.3206 18.5515 22.3774Z"></path><path d="M10.2973 5.72424C10.2973 7.78108 11.9647 9.44848 14.0215 9.44848C16.0784 9.44848 17.7458 7.78108 17.7458 5.72424C17.7458 3.6674 16.0784 2 14.0215 2C11.9647 2 10.2973 3.6674 10.2973 5.72424Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Derive An Address.svg b/assets/icons/polkadot/2color/Derive An Address.svg
new file mode 100644
index 00000000..2b0b4390
--- /dev/null
+++ b/assets/icons/polkadot/2color/Derive An Address.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.1663 20.3708L6.57475 11.5642"></path><path d="M16.0958 20.3709L21.6328 11.748"></path><path d="M14.1048 11.7479L14.1048 19.6567"></path><path d="M14.1354 19.6568C15.7109 19.6568 16.9881 20.9339 16.9881 22.5094C16.9881 24.0849 15.7109 25.3621 14.1354 25.3621C12.56 25.3621 11.2828 24.0849 11.2828 22.5094C11.2828 20.9339 12.56 19.6568 14.1354 19.6568Z"></path><path d="M6.74805 7H2V11.7481H6.74805V7Z" stroke-miterlimit="10"></path><path d="M16.5096 7H11.7615V11.7481H16.5096V7Z" stroke-miterlimit="10"></path><path d="M26 7H21.2519V11.7481H26V7Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Derive Key Pair.svg b/assets/icons/polkadot/2color/Derive Key Pair.svg
new file mode 100644
index 00000000..5405ea35
--- /dev/null
+++ b/assets/icons/polkadot/2color/Derive Key Pair.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.34003 8.39429C7.99798 8.70785 7.59748 8.95091 7.16141 9.1096C6.72533 9.2683 6.26221 9.33952 5.7985 9.31919C5.33479 9.29887 4.87957 9.1874 4.45882 8.99115C4.03807 8.7949 3.66004 8.51771 3.34632 8.17541C2.72168 7.47754 2.3994 6.56041 2.45028 5.62549C2.50115 4.69056 2.92101 3.8143 3.61764 3.18917C3.95969 2.87561 4.36019 2.63255 4.79627 2.47385C5.23234 2.31516 5.69546 2.24394 6.15917 2.26426C6.62288 2.28459 7.07811 2.39606 7.49885 2.59231C7.9196 2.78856 8.29763 3.06575 8.61136 3.40805C9.23564 4.10608 9.55768 5.02313 9.50682 5.95794C9.45595 6.89275 9.03633 7.76896 8.34003 8.39429Z" fill="none"></path><path d="M9.61705 5.58008L25 5.58251"></path><path d="M17.4261 6.25908L17.4235 9.53152L22.324 9.53743L22.3255 6.26614"></path><path d="M8.34003 23.3901C7.99798 23.7036 7.59748 23.9467 7.16141 24.1054C6.72533 24.2641 6.26221 24.3353 5.7985 24.315C5.33479 24.2946 4.87957 24.1832 4.45882 23.9869C4.03807 23.7907 3.66004 23.5135 3.34632 23.1712C2.72168 22.4733 2.3994 21.5562 2.45028 20.6213C2.50115 19.6863 2.92101 18.8101 3.61764 18.1849C3.95969 17.8714 4.36019 17.6283 4.79627 17.4696C5.23234 17.3109 5.69546 17.2397 6.15917 17.26C6.62288 17.2804 7.07811 17.3918 7.49885 17.5881C7.9196 17.7843 8.29763 18.0615 8.61136 18.4038C9.23564 19.1019 9.55768 20.0189 9.50682 20.9537C9.45595 21.8885 9.03633 22.7647 8.34003 23.3901Z" fill="none"></path><path d="M9.61705 20.5759L25 20.5783"></path><path d="M17.4261 21.2549L17.4235 24.5273L22.324 24.5332L22.3255 21.2619"></path><path d="M13.1898 20.2033L13.1898 5.75341"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Disconnected.svg b/assets/icons/polkadot/2color/Disconnected.svg
new file mode 100644
index 00000000..e9706e29
--- /dev/null
+++ b/assets/icons/polkadot/2color/Disconnected.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M11.4498 8.99997L6.72975 8.99997C4.11756 8.99997 1.99996 11.1176 1.99996 13.7298V13.7298C1.99996 16.342 4.11756 18.4596 6.72975 18.4596L11.4498 18.4596" fill="none" data-nofill="true"></path><path d="M16.4966 18.4971L21.2701 18.4971C23.8823 18.4971 25.9999 16.3795 25.9999 13.7673V13.7673C25.9999 11.1551 23.8823 9.03753 21.2701 9.03753L16.4966 9.03753" fill="none" data-nofill="true"></path><path d="M20.1082 13.7365L7.86182 13.7365" fill="none" data-nofill="true"></path><path d="M2.99982 2L24.9998 26" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Distributed File Storage.svg b/assets/icons/polkadot/2color/Distributed File Storage.svg
new file mode 100644
index 00000000..0b2874ba
--- /dev/null
+++ b/assets/icons/polkadot/2color/Distributed File Storage.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2.98242 5H12.0874L15.3605 7.76827H26.9824V23H2.98242V5Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Documentations.svg b/assets/icons/polkadot/2color/Documentations.svg
new file mode 100644
index 00000000..080cb059
--- /dev/null
+++ b/assets/icons/polkadot/2color/Documentations.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.5 23H25.3781V7.65385L19.7242 2H9.2242V5"></path><path d="M24.5 7.65386H19.7242V3"></path><path d="M2.99995 26V4.99998H13.5L19.1538 10.6538V26H2.99995Z"></path><path d="M15.8128 21.1899H6.13055" stroke-miterlimit="10"></path><path d="M15.8128 17.9622H6.13055" stroke-miterlimit="10"></path><path d="M18.5 10.6538H13.5V6"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Download.svg b/assets/icons/polkadot/2color/Download.svg
new file mode 100644
index 00000000..a1a92e2d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Download.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M6 23.5V26L22.706 26V23.5" fill="none" data-nofill="true"></path><path d="M14.4865 2L14.4865 20.5M20.0165 15.921L14.4865 21.4482L8.95172 15.9227" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Draw.svg b/assets/icons/polkadot/2color/Draw.svg
new file mode 100644
index 00000000..d2811b95
--- /dev/null
+++ b/assets/icons/polkadot/2color/Draw.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.7143 23L26 16.5714L17.7827 17.0116M4.14286 6.28571L17.4286 2L2 17.8571L7.15792 17.5808" fill="none" data-nofill="true"></path><path d="M18.8649 6.05542L23.6589 10.8494L11.1359 23.3723L4.82555 24.8887L6.342 18.5784L18.8649 6.05542Z"></path><path d="M20.2346 14.2736L15.4407 9.47968M18.8649 6.05542L23.6589 10.8494L11.1359 23.3723L4.82555 24.8887L6.342 18.5784L18.8649 6.05542Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Drip.svg b/assets/icons/polkadot/2color/Drip.svg
new file mode 100644
index 00000000..8a0d95c9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Drip.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7 17.8836C7 23.4036 10.0031 26 14 26C17.9969 26 21 23.4036 21 17.8836C21 12.3636 14 3 14 3C14 3 7 12.3636 7 17.8836Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Dropdown Up.svg b/assets/icons/polkadot/2color/Dropdown Up.svg
new file mode 100644
index 00000000..ffd0d29c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Dropdown Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 19.9167L14 8L3 19.9167H25Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Dropdown.svg b/assets/icons/polkadot/2color/Dropdown.svg
new file mode 100644
index 00000000..0922524a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Dropdown.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 8L14 19.9167L25 8.00001L3 8Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Ecosystem Provisions.svg b/assets/icons/polkadot/2color/Ecosystem Provisions.svg
new file mode 100644
index 00000000..512d9b06
--- /dev/null
+++ b/assets/icons/polkadot/2color/Ecosystem Provisions.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M3.77234 15.5679C3.77234 17.8757 4.44922 20.3722 5.7042 22.1214M11.4484 5.78235C8.99324 6.48892 6.80576 8.0701 5.43494 10.1597M17.0581 5.78356C19.5102 6.48923 21.7085 8.08221 23.0796 10.1679M22.7661 22.1554C23.9544 20.4486 24.7999 18.1804 24.7999 15.943C24.7999 15.8061 24.7973 15.6698 24.7921 15.5341M10.0489 25.619C11.3369 26.1794 12.7586 26.4901 14.2528 26.4901C15.7199 26.4901 17.1171 26.1906 18.3864 25.6493"></path><path d="M14.2534 8.22364C15.815 8.22364 17.081 6.95766 17.081 5.396C17.081 3.83434 15.815 2.56836 14.2534 2.56836C12.6917 2.56836 11.4257 3.83434 11.4257 5.396C11.4257 6.95766 12.6917 8.22364 14.2534 8.22364Z"></path><path d="M7.58887 27.0554C9.15053 27.0554 10.4165 25.7895 10.4165 24.2278C10.4165 22.6661 9.15053 21.4001 7.58887 21.4001C6.02721 21.4001 4.76123 22.6661 4.76123 24.2278C4.76123 25.7895 6.02721 27.0554 7.58887 27.0554Z"></path><path d="M4.82758 15.7639C6.38924 15.7639 7.65522 14.4979 7.65522 12.9363C7.65522 11.3746 6.38924 10.1086 4.82758 10.1086C3.26592 10.1086 1.99994 11.3746 1.99994 12.9363C1.99994 14.4979 3.26592 15.7639 4.82758 15.7639Z"></path><path d="M23.6782 15.7639C25.2398 15.7639 26.5058 14.4979 26.5058 12.9363C26.5058 11.3746 25.2398 10.1086 23.6782 10.1086C22.1165 10.1086 20.8505 11.3746 20.8505 12.9363C20.8505 14.4979 22.1165 15.7639 23.6782 15.7639Z"></path><path d="M20.8418 27.0653C22.4035 27.0653 23.6694 25.7993 23.6694 24.2377C23.6694 22.676 22.4035 21.41 20.8418 21.41C19.2801 21.41 18.0142 22.676 18.0142 24.2377C18.0142 25.7993 19.2801 27.0653 20.8418 27.0653Z"></path><path d="M8.72546 21.6745V21.6745C8.72546 20.3602 9.60183 19.2071 10.8682 18.8551L12.6186 18.3687C13.1092 18.2324 13.2957 17.6352 12.9698 17.2439L12.4615 16.6337C11.5887 15.586 11.6586 14.0457 12.6226 13.0813V13.0813C13.6526 12.0509 15.323 12.0509 16.353 13.0813V13.0813C17.317 14.0457 17.3869 15.586 16.5141 16.6337L16.0059 17.2438C15.68 17.6351 15.8665 18.2323 16.3572 18.3686L18.1123 18.8559C19.3785 19.2076 20.2548 20.3604 20.2548 21.6745V21.6745" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Ecosystem.svg b/assets/icons/polkadot/2color/Ecosystem.svg
new file mode 100644
index 00000000..7bbb5b9c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Ecosystem.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M24.3292 15.1034C24.3292 17.159 23.601 19.241 22.5507 20.8712M5.81998 8.80014C7.0663 7.19819 8.82051 5.96311 10.7784 5.29788M3.73871 15C3.78622 17.1056 4.39892 19.3392 5.5 20.9729M10.1593 24.6987C11.3465 25.1747 12.6426 25.4366 13.9998 25.4366C15.3147 25.4366 16.5721 25.1908 17.7288 24.7427M22.3333 9C21.0431 7.25881 19.1524 5.91712 17.049 5.24194"></path><path d="M14.0005 7.54055C15.5299 7.54055 16.7697 6.30026 16.7697 4.77028C16.7697 3.24029 15.5299 2 14.0005 2C12.471 2 11.2312 3.24029 11.2312 4.77028C11.2312 6.30026 12.471 7.54055 14.0005 7.54055Z"></path><path d="M7.47355 25.9903C9.00298 25.9903 10.2428 24.7501 10.2428 23.2201C10.2428 21.6901 9.00298 20.4498 7.47355 20.4498C5.94413 20.4498 4.70428 21.6901 4.70428 23.2201C4.70428 24.7501 5.94413 25.9903 7.47355 25.9903Z"></path><path d="M4.76927 14.9279C6.29869 14.9279 7.53854 13.6876 7.53854 12.1576C7.53854 10.6277 6.29869 9.38736 4.76927 9.38736C3.23984 9.38736 2 10.6277 2 12.1576C2 13.6876 3.23984 14.9279 4.76927 14.9279Z"></path><path d="M23.2308 14.9279C24.7602 14.9279 26 13.6876 26 12.1576C26 10.6277 24.7602 9.38736 23.2308 9.38736C21.7013 9.38736 20.4615 10.6277 20.4615 12.1576C20.4615 13.6876 21.7013 14.9279 23.2308 14.9279Z"></path><path d="M20.4529 26C21.9823 26 23.2222 24.7597 23.2222 23.2297C23.2222 21.6997 21.9823 20.4594 20.4529 20.4594C18.9235 20.4594 17.6837 21.6997 17.6837 23.2297C17.6837 24.7597 18.9235 26 20.4529 26Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Edit-Off.svg b/assets/icons/polkadot/2color/Edit-Off.svg
new file mode 100644
index 00000000..d45437aa
--- /dev/null
+++ b/assets/icons/polkadot/2color/Edit-Off.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.8064 12.0645L15.9355 6.19357M20.129 2L26 7.87097L16.5346 17.3364L15.2654 18.6056L10.6636 23.2074L2.93548 25.0645L4.79262 17.3364L9.454 12.675L10.675 11.454L20.129 2Z"></path><path d="M2.33716 4.37223L23.6872 25.7223"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Edit-On.svg b/assets/icons/polkadot/2color/Edit-On.svg
new file mode 100644
index 00000000..423160c9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Edit-On.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M20.9168 12.1924L15.5546 6.83018M19.3848 3L24.747 8.36223L10.7395 22.3697L3.6811 24.0659L5.37732 17.0074L19.3848 3Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Elections.svg b/assets/icons/polkadot/2color/Elections.svg
new file mode 100644
index 00000000..788585d9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Elections.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M25.8716 14.9436V26H2L2.02488 15.7534"></path><path d="M17.0029 5.76299H22.1341L25.8725 14.8704V15.8763H2.00092V14.8695L5.77523 5.76299H10.8696"></path><path d="M8.27478 10.5318H19.5977"></path><path d="M17.0029 2H10.8696V10.5318H17.0029V2Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Email.svg b/assets/icons/polkadot/2color/Email.svg
new file mode 100644
index 00000000..84f26dcf
--- /dev/null
+++ b/assets/icons/polkadot/2color/Email.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 4H2V24.219H26V4Z"></path><path d="M3 5.31509L14 15.3151L25 5.31509"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Encryption.svg b/assets/icons/polkadot/2color/Encryption.svg
new file mode 100644
index 00000000..00cc44db
--- /dev/null
+++ b/assets/icons/polkadot/2color/Encryption.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.12128 9.66582L8.1213 7.41847V7.41847C8.1213 4.42593 10.5472 2 13.5398 2V2C16.5323 2 18.9582 4.42593 18.9582 7.41847V7.41847L18.9582 9.66582" fill="none"></path><path d="M24.0794 9.66956H3V25H24.0794V9.66956Z"></path><path d="M9.59457 14.9474L6.78784 17.2887L9.5 19.5465"></path><path d="M17.4755 19.6253L20.2916 17.284L17.5979 15.04"></path><path d="M15.1113 12.5991L11.9587 21.9733"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Ending Period.svg b/assets/icons/polkadot/2color/Ending Period.svg
new file mode 100644
index 00000000..bfb7a485
--- /dev/null
+++ b/assets/icons/polkadot/2color/Ending Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M13.9999 13.3519L5.87173 13.352"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Energy Deficiency.svg b/assets/icons/polkadot/2color/Energy Deficiency.svg
new file mode 100644
index 00000000..a5b8de81
--- /dev/null
+++ b/assets/icons/polkadot/2color/Energy Deficiency.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M6.52649 19.5832C8.22267 21.8663 10.9457 23.3465 14.0158 23.3465C19.1583 23.3465 23.3271 19.1934 23.3271 14.0702C23.3271 8.94703 19.5563 4.71485 14.4137 4.71485C13.155 4.71485 10.988 5.20555 9.89277 5.65653" stroke-dasharray="0.1 4.5" fill="none"></path><path d="M13.7787 10.2817L12.5601 14.1408H15.4713L14.1173 17.9999" fill="none"></path><path d="M5.30628 14.8423C5.19187 12.8048 5.74122 10.8835 6.76633 9.28875" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Energy Efficiency.svg b/assets/icons/polkadot/2color/Energy Efficiency.svg
new file mode 100644
index 00000000..61349b8b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Energy Efficiency.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.182 8.77164C20.2215 7.47849 18.9257 6.46269 17.4263 5.83979C15.6073 5.08408 13.5899 4.94877 11.6863 5.4548C9.78259 5.96083 8.09869 7.07999 6.89499 8.63919C5.69129 10.1984 5.03486 12.1108 5.02722 14.0805L5.08337 14.9644M8.45708 12.3279L5.1379 15.7374L1.72839 12.4182" fill="none"></path><path d="M6.78601 19.3839C7.73403 20.6646 9.01094 21.6752 10.4902 22.3024C12.3113 23.0746 14.3367 23.2226 16.2506 22.7233C18.1646 22.224 19.8596 21.1055 21.0714 19.5421C22.2831 17.9787 22.9436 16.0583 22.9498 14.0803L22.9047 13.2071M19.5096 15.7431L22.84 12.4092L26.2383 15.6764" fill="none"></path><path d="M13.8499 10.2246L12.6312 14.0837H15.5425L14.1884 17.9428" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Energy.svg b/assets/icons/polkadot/2color/Energy.svg
new file mode 100644
index 00000000..3cf91a42
--- /dev/null
+++ b/assets/icons/polkadot/2color/Energy.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 18 27" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2.02344 4.875L2.02344 25L15.9877 25L15.9877 4.875L12.2727 4.875L12.2913 2L5.73844 2L5.73844 4.875L2.02344 4.875Z"></path><path d="M8.78498 9.28687L7.08417 14.6728H11.1473L9.25747 20.0588"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Enterprise.svg b/assets/icons/polkadot/2color/Enterprise.svg
new file mode 100644
index 00000000..20fed5b4
--- /dev/null
+++ b/assets/icons/polkadot/2color/Enterprise.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.7057 26L22.7057 2.56836L7.79767 2.56836L7.79767 26"></path><path d="M4.54956 26.5681L25.8959 26.5681"></path><path d="M17.5428 25.7709V19.2742H12.9023V25.7709"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Error.svg b/assets/icons/polkadot/2color/Error.svg
new file mode 100644
index 00000000..480cc457
--- /dev/null
+++ b/assets/icons/polkadot/2color/Error.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 2C20.6274 2 26 7.37258 26 14C26 20.6274 20.6274 26 14 26C7.37258 26 2 20.6274 2 14C2 7.37258 7.37258 2 14 2Z"></path><path d="M10.3075 17.6221L17.6938 10.3153"></path><path d="M10.3489 10.2756L17.6558 17.6619"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Eve.svg b/assets/icons/polkadot/2color/Eve.svg
new file mode 100644
index 00000000..e038dac9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Eve.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.0297 11.5875L11.1215 10.5361C9.67139 8.85746 9.78596 6.33823 11.3824 4.79815C13.001 3.23677 15.5651 3.23677 17.1837 4.79815C18.7801 6.33823 18.8947 8.85746 17.4446 10.5361L16.5366 11.5872C16.0621 12.1365 16.2218 12.9845 16.8636 13.3235L18.4551 14.1643C21.6036 15.8277 23.5735 19.0963 23.5736 22.6572L23.5736 22.9455H18.4943V26H9.35223L9.35223 22.9455H5.00006L5.00006 22.6523C5.00002 19.094 6.96792 15.8274 10.1136 14.1642L11.703 13.3238C12.3446 12.9845 12.5042 12.1367 12.0297 11.5875Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Events.svg b/assets/icons/polkadot/2color/Events.svg
new file mode 100644
index 00000000..bd2195ea
--- /dev/null
+++ b/assets/icons/polkadot/2color/Events.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M18.6289 26H2V3.88454H26V18.9448L18.6289 26Z" stroke-miterlimit="10"></path><path d="M9.42334 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34178V2.00008" stroke-miterlimit="10"></path><path d="M2.10101 11.2501H26" stroke-miterlimit="10"></path><path d="M18.4785 25.2163V18.4537H25.6592" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Existential Deposit.svg b/assets/icons/polkadot/2color/Existential Deposit.svg
new file mode 100644
index 00000000..c22d9d8c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Existential Deposit.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 20.5V26H26V20.5" fill="none" data-nofill="true"></path><circle cx="14" cy="12.5" r="8"></circle><path d="M15.7943 9.02179H13.4727C13.0158 9.02301 12.578 9.20551 12.2551 9.52934C11.9322 9.85317 11.7506 10.2919 11.75 10.7496V10.7704C11.7506 11.228 11.9322 11.6668 12.2551 11.9906C12.578 12.3145 13.0158 12.497 13.4727 12.4982H14.6243C14.8514 12.4973 15.0765 12.5413 15.2866 12.6277C15.4967 12.7141 15.6876 12.8413 15.8486 13.0018C16.0095 13.1623 16.1372 13.3531 16.2243 13.5632C16.3114 13.7733 16.3563 13.9985 16.3563 14.226C16.3569 14.4537 16.3125 14.6792 16.2258 14.8897C16.1391 15.1002 16.0117 15.2914 15.851 15.4524C15.6903 15.6134 15.4994 15.741 15.2892 15.8278C15.0791 15.9147 14.8539 15.959 14.6266 15.9584H12.1093"></path><path d="M14.0488 8.97504V7.74445"></path><path d="M14.0488 17.2556V16.1204"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Export (M,L).svg b/assets/icons/polkadot/2color/Export (M,L).svg
new file mode 100644
index 00000000..37d81caa
--- /dev/null
+++ b/assets/icons/polkadot/2color/Export (M,L).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.7238 26L21.7238 10.2763L6.00002 10.2763L6.00002 26L21.7238 26Z"></path><path d="M10.1466 5.71254L13.859 2.0001L17.5777 5.71254" fill="none" data-nofill="true"></path><path d="M10.1466 5.71238L13.859 1.99994L17.5777 5.71238" fill="none" data-nofill="true"></path><path d="M13.8619 2.78161L13.8619 17.5825"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Export (XS,S).svg b/assets/icons/polkadot/2color/Export (XS,S).svg
new file mode 100644
index 00000000..5a5c556f
--- /dev/null
+++ b/assets/icons/polkadot/2color/Export (XS,S).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.1464 5.7126L13.8589 2.00016L17.5775 5.7126" fill="none" data-nofill="true"></path><path d="M6.00002 26.0001L22 26.0001L22 22.3334L22 15.0001L6.00001 15.0001L6 22.3334L6.00002 26.0001Z"></path><path d="M10.1464 5.71244L13.8589 2L17.5775 5.71244" fill="none" data-nofill="true"></path><path d="M13.8617 3L13.8617 17.5825" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Extension.svg b/assets/icons/polkadot/2color/Extension.svg
new file mode 100644
index 00000000..cec3da84
--- /dev/null
+++ b/assets/icons/polkadot/2color/Extension.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M9.44828 6.1379H2V13.5862H3.65517C5.02636 13.5862 6.13794 14.6978 6.13794 16.069C6.13794 17.4402 5.02636 18.5517 3.65517 18.5517H2V26H9.44828V24.3448C9.44828 22.9736 10.5599 21.8621 11.9311 21.8621C13.3022 21.8621 14.4138 22.9736 14.4138 24.3448V26H21.8621V17.7241H23.5172C24.8884 17.7241 26 16.6126 26 15.2414C26 13.8702 24.8884 12.7586 23.5172 12.7586H21.8621V6.1379H14.4138V4.48273C14.4138 3.11154 13.3022 2 11.9311 2C10.5599 2 9.44828 3.11154 9.44828 4.48273V6.1379Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Favorite To-Be.svg b/assets/icons/polkadot/2color/Favorite To-Be.svg
new file mode 100644
index 00000000..8b324f9f
--- /dev/null
+++ b/assets/icons/polkadot/2color/Favorite To-Be.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25.2741 11.3007L20.1148 17.125L20.8486 24.8295L13.6485 21.7798L6.47138 24.8524L7.18222 17.1479L2 11.3466L9.63574 9.64975L13.6256 3L17.6384 9.64975L25.2741 11.3007Z" stroke-miterlimit="10" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Favorite.svg b/assets/icons/polkadot/2color/Favorite.svg
new file mode 100644
index 00000000..943cd413
--- /dev/null
+++ b/assets/icons/polkadot/2color/Favorite.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 11.055L20.6798 17.1851L21.4365 25.2942L14.0118 22.0844L6.61084 25.3184L7.34384 17.2092L2 11.1032L9.87389 9.31731L13.9882 2.31836L18.1261 9.31731L26 11.055Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Feeless.svg b/assets/icons/polkadot/2color/Feeless.svg
new file mode 100644
index 00000000..a4345075
--- /dev/null
+++ b/assets/icons/polkadot/2color/Feeless.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 12.6799V16.6799C26 21.0982 20.6274 24.1799 14 24.1799C7.37258 24.1799 2 21.0982 2 16.6799V12.6799"></path><path d="M14 20.6799C20.6274 20.6799 26 17.0982 26 12.6799C26 8.26165 20.6274 4.67993 14 4.67993C7.37258 4.67993 2 8.26165 2 12.6799C2 17.0982 7.37258 20.6799 14 20.6799Z"></path><path d="M4.64807 25.8601L23.352 2.99976"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Fees.svg b/assets/icons/polkadot/2color/Fees.svg
new file mode 100644
index 00000000..7d256878
--- /dev/null
+++ b/assets/icons/polkadot/2color/Fees.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="18.8311" y="5.73572" width="4.08857" height="4.08857"></rect><path d="M7.33884 18.557L5.29456 22.6456H7.33884H9.38313L7.33884 18.557Z"></path><path d="M7.21388 12.205L4.39465 14.6213L1.97833 11.8021" fill="none" data-nofill="true"></path><path d="M20.8415 15.5617L23.6641 13.205L26.0754 15.983" fill="none" data-nofill="true"></path><path d="M13.2449 23.7238C18.9729 24.242 23.6304 19.5894 23.6304 14M14.9682 4.67616C9.20961 4.15517 5.25915 8.51366 4.52261 13.8284" fill="none" data-nofill="true"></path><path d="M15.386 11.7097H13.591C13.2377 11.7107 12.8991 11.8518 12.6495 12.1022C12.3998 12.3526 12.2594 12.6918 12.2589 13.0457V13.0617C12.2594 13.4156 12.3998 13.7549 12.6495 14.0053C12.8991 14.2557 13.2377 14.3968 13.591 14.3977H14.4814C14.657 14.397 14.831 14.431 14.9934 14.4979C15.1559 14.5647 15.3036 14.663 15.428 14.7871C15.5524 14.9112 15.6511 15.0588 15.7185 15.2212C15.7859 15.3836 15.8205 15.5578 15.8205 15.7337C15.821 15.9097 15.7867 16.0841 15.7197 16.2469C15.6526 16.4096 15.5541 16.5575 15.4299 16.6819C15.3056 16.8064 15.158 16.9051 14.9955 16.9722C14.833 17.0394 14.6589 17.0737 14.4831 17.0732H12.5367" fill="none" data-nofill="true"></path><path d="M14.0365 11.6736V10.722" fill="none" data-nofill="true"></path><path d="M14.0365 18.0763V17.1986" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Fiat.svg b/assets/icons/polkadot/2color/Fiat.svg
new file mode 100644
index 00000000..fb9247a1
--- /dev/null
+++ b/assets/icons/polkadot/2color/Fiat.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M8.88812 8.29893C9.93968 4.66101 13.296 2 17.273 2C22.093 2 26 5.907 26 10.727C26 14.7103 23.3309 18.0703 19.6837 19.1166"></path><path d="M10.727 25.9989C15.5468 25.9989 19.454 22.0917 19.454 17.2719C19.454 12.4521 15.5468 8.54492 10.727 8.54492C5.90721 8.54492 2 12.4521 2 17.2719C2 22.0917 5.90721 25.9989 10.727 25.9989Z"></path><path d="M12.6849 13.478H10.1519C9.65395 13.479 9.17595 13.678 8.82395 14.032C8.47195 14.385 8.27395 14.864 8.27295 15.363V15.386C8.27295 15.885 8.47195 16.364 8.82395 16.717C9.17595 17.07 9.65395 17.269 10.1519 17.271H11.4079C11.6559 17.271 11.9009 17.318 12.1299 17.412C12.3589 17.506 12.5679 17.645 12.7429 17.82C12.9189 17.995 13.0579 18.203 13.1529 18.432C13.2479 18.661 13.2969 18.907 13.2969 19.155C13.2969 19.403 13.2489 19.649 13.1549 19.879C13.0599 20.109 12.9209 20.317 12.7459 20.493C12.5709 20.669 12.3619 20.808 12.1329 20.903C11.9039 20.998 11.6579 21.046 11.4099 21.045H8.66395"></path><path d="M10.781 13.427V12.084"></path><path d="M10.781 22.4599V21.2219"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Filter.svg b/assets/icons/polkadot/2color/Filter.svg
new file mode 100644
index 00000000..6e14d79a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Filter.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 8.0388H25"></path><path d="M19.5 10.3959L19.5 5.68166"></path><path d="M3 15.1102H25"></path><path d="M7.71429 17.4673L7.71429 12.753"></path><path d="M3 22.4435H25"></path><path d="M14 24.5388L14 19.8245"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Finances.svg b/assets/icons/polkadot/2color/Finances.svg
new file mode 100644
index 00000000..cd866a0b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Finances.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M6.34558 21.3149C6.34558 26.7283 10.0228 26.5679 14.917 26.5679C19.8112 26.5679 23.4884 26.7283 23.4884 21.3149C23.4884 15.9015 18.667 9.42554 14.917 9.42554C11.167 9.42554 6.34558 15.9015 6.34558 21.3149Z"></path><path d="M11.488 8.56836L18.3452 8.56836"></path><path d="M16.2816 15.5408H14.5142C14.1663 15.5417 13.833 15.6806 13.5872 15.9272C13.3414 16.1737 13.2032 16.5077 13.2027 16.8561V16.8719C13.2032 17.2204 13.3414 17.5544 13.5872 17.8009C13.833 18.0474 14.1663 18.1864 14.5142 18.1873H15.3909C15.5638 18.1866 15.7351 18.2201 15.895 18.2859C16.055 18.3517 16.2004 18.4485 16.3229 18.5707C16.4454 18.6929 16.5426 18.8382 16.6089 18.9981C16.6752 19.158 16.7094 19.3295 16.7094 19.5027C16.7098 19.676 16.6761 19.8477 16.6101 20.0079C16.5441 20.1682 16.4471 20.3137 16.3247 20.4363C16.2024 20.5589 16.057 20.656 15.8971 20.7221C15.7371 20.7882 15.5657 20.822 15.3926 20.8216H13.4762"></path><path d="M14.9528 15.5052V14.5684"></path><path d="M14.9528 21.8093V20.9451"></path><path d="M15.0129 8.43266L18.5392 2.56836L11.4883 2.56836L15.0129 8.43266Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Fork.svg b/assets/icons/polkadot/2color/Fork.svg
new file mode 100644
index 00000000..c8588f0a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Fork.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.6821 9.85657H2V18.5387H10.6821V9.85657Z"></path><path d="M25.9999 3H17.3177V11.6822H25.9999V3Z"></path><path d="M25.9998 16.8913H17.3177V25.5735H25.9998V16.8913Z"></path><path d="M16.5927 8.5L11.2624 12.2323"></path><path d="M11.2333 16.3355L16.7327 20.1862"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/ForklessUpgrades.svg b/assets/icons/polkadot/2color/ForklessUpgrades.svg
new file mode 100644
index 00000000..ebda6826
--- /dev/null
+++ b/assets/icons/polkadot/2color/ForklessUpgrades.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M25.5743 6.69975L16.368 6.69975M15.9292 21.3911L18.6861 17.517M11.6479 21.3911L9.07848 17.7086M9.07848 12.7338L11.4805 9.39406" stroke-miterlimit="10"></path><path d="M25.5737 15.2132L23.1141 15.2132M2 15.2131L4.57076 15.2131M10.4359 15.2132L17.4014 15.2132" stroke-miterlimit="10"></path><path d="M16.1899 4.35102L11.3874 4.35102L11.3874 9.13458L16.1899 9.13458L16.1899 4.35102Z"></path><path d="M11.0675 23.3526C11.0675 24.8554 12.2858 26.0736 13.7886 26.0736C15.2914 26.0736 16.5096 24.8554 16.5096 23.3526C16.5096 21.8498 15.2914 20.6315 13.7886 20.6315C12.2858 20.6315 11.0675 21.8498 11.0675 23.3526Z"></path><path d="M17.5424 15.2134C17.5424 16.7162 18.7606 17.9345 20.2634 17.9345C21.7662 17.9345 22.9845 16.7162 22.9845 15.2134C22.9845 13.7107 21.7662 12.4924 20.2634 12.4924C18.7606 12.4924 17.5424 13.7107 17.5424 15.2134Z"></path><path d="M4.59851 15.2134C4.59851 16.7162 5.81676 17.9345 7.31956 17.9345C8.82235 17.9345 10.0406 16.7162 10.0406 15.2134C10.0406 13.7107 8.82235 12.4924 7.31956 12.4924C5.81676 12.4924 4.59851 13.7107 4.59851 15.2134Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Full Node.svg b/assets/icons/polkadot/2color/Full Node.svg
new file mode 100644
index 00000000..aa99b468
--- /dev/null
+++ b/assets/icons/polkadot/2color/Full Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5358 21.0126L18.5124 16.611"></path><path d="M9.50999 16.6247L6.44708 20.999"></path><path d="M20.4564 23.2116C20.4564 24.7425 21.6974 25.9834 23.2282 25.9834C24.759 25.9834 26 24.7425 26 23.2116C26 21.6808 24.759 20.4398 23.2282 20.4398C21.6974 20.4398 20.4564 21.6808 20.4564 23.2116Z"></path><path d="M2.00001 23.2116C2.00001 24.7425 3.24099 25.9834 4.77183 25.9834C6.30266 25.9834 7.54364 24.7425 7.54364 23.2116C7.54364 21.6808 6.30266 20.4398 4.77183 20.4398C3.24099 20.4398 2.00001 21.6808 2.00001 23.2116Z"></path><path d="M5.99593 10.0054C5.99593 14.4267 9.58006 18.0108 14.0013 18.0108C18.4226 18.0108 22.0067 14.4267 22.0067 10.0054C22.0067 5.58414 18.4226 2 14.0013 2C9.58006 2 5.99593 5.58414 5.99593 10.0054Z" stroke-miterlimit="10"></path><path d="M11.5364 12.6406C12.9917 14.0959 15.3513 14.0959 16.8066 12.6406C18.2619 11.1853 18.2619 8.82573 16.8066 7.3704C15.3513 5.91507 12.9917 5.91507 11.5364 7.3704C10.0811 8.82573 10.0811 11.1853 11.5364 12.6406Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Fund Account.svg b/assets/icons/polkadot/2color/Fund Account.svg
new file mode 100644
index 00000000..3cbbe8ce
--- /dev/null
+++ b/assets/icons/polkadot/2color/Fund Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M3 26.749L26.9834 26.749"></path><path d="M6.59839 11.4411L6.59839 26.749"></path><path d="M23.3994 11.4411L23.3994 26.749"></path><path d="M9.01234 11.4411H3.01672V11.2555L15.0024 3L27.0002 11.3521V11.4411H20.9779H9.01234Z"></path><path d="M21.1614 26.0519C21.1614 23.9777 19.7786 22.1585 17.7808 21.603L17.0508 21.3996C16.532 21.2558 16.3346 20.6249 16.6788 20.2113L17.2174 19.5635C18.1369 18.4585 18.0635 16.8346 17.0478 15.8169C15.9606 14.7277 14.1949 14.7277 13.1077 15.8169C12.0919 16.8346 12.0185 18.4585 12.9381 19.5635L13.4767 20.2113C13.8209 20.6249 13.6245 21.2558 13.1057 21.3996L12.3776 21.602C10.3808 22.1575 9 23.9758 9 26.048"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Fund Savings.svg b/assets/icons/polkadot/2color/Fund Savings.svg
new file mode 100644
index 00000000..32c683d6
--- /dev/null
+++ b/assets/icons/polkadot/2color/Fund Savings.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.2291 20.1446L18.7474 20.1446L18.7474 22.8113L22.3215 22.8113L22.3215 19.0335C23.0583 18.5015 23.5748 17.8561 23.9785 17.0335L26.9898 17.0335L26.9898 13.0335L24.3231 13.0335C23.7308 10.9989 22.0063 9.44662 19.8771 9.10423L19.8771 5.75236C17.4883 5.75236 15.5253 6.25236 15.5253 9.10421L11.2104 9.10421C8.1422 9.10421 5.65489 11.5915 5.65489 14.6598C5.65489 17.188 7.34385 19.3219 9.65498 19.9946L9.65498 22.8113L13.2291 22.8113L13.2291 20.1446Z"></path><path d="M5.65495 14.8113C4.18219 14.8113 2.98828 13.6173 2.98828 12.1446"></path><path d="M10.9884 12.6817H14.9884"></path><path d="M19.9883 12.6816L20.0064 12.6997" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Gaming.svg b/assets/icons/polkadot/2color/Gaming.svg
new file mode 100644
index 00000000..5a2b3c56
--- /dev/null
+++ b/assets/icons/polkadot/2color/Gaming.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2 18.8681C2 22.949 4.46926 25.144 7.19827 25.7927C8.34641 26.0656 9.53014 25.7604 10.6149 25.2958C12.8072 24.3568 15.2883 24.3568 17.4805 25.2958C18.5653 25.7604 19.749 26.0656 20.8972 25.7927C23.6262 25.144 26.0955 22.949 26.0955 18.8681C26.0955 14.9293 23.2304 11.7363 19.1247 11.7363H8.97079C4.30756 11.7363 2 14.9293 2 18.8681Z"></path><path d="M6.12368 18.723H11.4803"></path><path d="M8.80172 16.0446V21.4013"></path><path d="M17.8574 20.2845L17.8682 20.2845"></path><path d="M20.9302 20.2845L20.941 20.2845"></path><path d="M17.8574 17.1613L17.8682 17.1613"></path><path d="M20.92 17.1613L20.9308 17.1613"></path><path d="M14.0708 2V11.7361"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Genesis.svg b/assets/icons/polkadot/2color/Genesis.svg
new file mode 100644
index 00000000..c76003d6
--- /dev/null
+++ b/assets/icons/polkadot/2color/Genesis.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="2" y="5" width="17" height="18"></rect><path d="M26 14L12 14"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Gift.svg b/assets/icons/polkadot/2color/Gift.svg
new file mode 100644
index 00000000..2d04830e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Gift.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.8229 2C11.6591 2 12.461 2.32869 13.0522 2.91376C13.6435 3.49883 13.9756 4.29236 13.9756 5.11977V8.23954H10.8229C9.98674 8.23954 9.18483 7.91085 8.59358 7.32578C8.00233 6.74071 7.67017 5.94719 7.67017 5.11977C7.67017 4.29236 8.00233 3.49883 8.59358 2.91376C9.18483 2.32869 9.98674 2 10.8229 2V2Z" stroke-miterlimit="10" fill="none"></path><path d="M17.1283 2C17.9645 2 18.7664 2.32869 19.3576 2.91376C19.9489 3.49883 20.2811 4.29236 20.2811 5.11977C20.2811 5.94719 19.9489 6.74071 19.3576 7.32578C18.7664 7.91085 17.9645 8.23954 17.1283 8.23954H13.9756V5.11977C13.9756 4.29236 14.3077 3.49883 14.899 2.91376C15.4903 2.32869 16.2922 2 17.1283 2V2Z" stroke-miterlimit="10" fill="none"></path><path d="M4 14V25H24.5V14"></path><path d="M13.9756 14L13.9756 24.5" stroke-miterlimit="10"></path><path d="M2 8.23946H26V13.8389H2V8.23946Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Glossary.svg b/assets/icons/polkadot/2color/Glossary.svg
new file mode 100644
index 00000000..4b03fcb2
--- /dev/null
+++ b/assets/icons/polkadot/2color/Glossary.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2 19.8022V2L14 7.60066L26 2V19.8022L14 26L2 19.8022Z"></path><path d="M14 25V8"></path><path d="M17.5269 10.2101L22.4887 10.2101L22.4886 10.237L17.5195 17.4867L17.5195 17.5237L22.4815 17.5237"></path><path d="M5.36933 17.5717L7.91393 10.1571L7.92356 10.1569L10.786 17.5717M6.28654 16.1387L9.81205 16.1387"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Go.svg b/assets/icons/polkadot/2color/Go.svg
new file mode 100644
index 00000000..35481707
--- /dev/null
+++ b/assets/icons/polkadot/2color/Go.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 23C14 24.105 14.895 25 16 25C17.105 25 18 24.105 18 23V20H14V23Z"></path><path d="M10 23C10 24.105 10.895 25 12 25C13.105 25 14 24.105 14 23V20H10V23Z"></path><path d="M17.5 14H19C20.657 14 22 15.343 22 17C22 18.657 20.657 20 19 20H9C7.343 20 6 18.657 6 17C6 15.343 7.343 14 9 14H10.5"></path><path d="M7.5 10C5.567 10 4 8.433 4 6.5C4 4.567 5.567 3 7.5 3C9.433 3 11 4.567 11 6.5C11 8.433 9.433 10 7.5 10Z"></path><path d="M20.5 10C18.567 10 17 8.433 17 6.5C17 4.567 18.567 3 20.5 3C22.433 3 24 4.567 24 6.5C24 8.433 22.433 10 20.5 10Z"></path><path d="M17 13C17 14.657 15.657 16 14 16C12.343 16 11 14.657 11 13C11 11.343 12.343 10 14 10C15.657 10 17 11.343 17 13Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Governance.svg b/assets/icons/polkadot/2color/Governance.svg
new file mode 100644
index 00000000..eb131cbe
--- /dev/null
+++ b/assets/icons/polkadot/2color/Governance.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><circle cx="14.0001" cy="13.8747" r="3.30708"></circle><circle cx="14.0001" cy="24.1101" r="1.88976"></circle><circle cx="14.0001" cy="3.88976" r="1.88976"></circle><circle cx="24.1102" cy="13.9999" r="1.88976" transform="rotate(-90 24.1102 13.9999)"></circle><circle cx="3.88976" cy="13.9999" r="1.88976" transform="rotate(-90 3.88976 13.9999)"></circle><circle cx="21.149" cy="21.1491" r="1.88976" transform="rotate(-45 21.149 21.1491)"></circle><circle cx="6.85112" cy="6.85082" r="1.88976" transform="rotate(-45 6.85112 6.85082)"></circle><circle cx="21.149" cy="6.85099" r="1.88976" transform="rotate(-135 21.149 6.85099)"></circle><circle cx="6.85107" cy="21.149" r="1.88976" transform="rotate(-135 6.85107 21.149)"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Governments.svg b/assets/icons/polkadot/2color/Governments.svg
new file mode 100644
index 00000000..f3c5e493
--- /dev/null
+++ b/assets/icons/polkadot/2color/Governments.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 25.749L25.9834 25.749"></path><path d="M5.59839 10.4411L5.59839 25.749"></path><path d="M22.3994 10.4411L22.3994 25.749"></path><path d="M11.3259 10.4411V25.7491"></path><path d="M16.8198 10.4411V25.7491"></path><path d="M8.01234 10.4411H2.01672V10.2555L14.0024 2L26.0002 10.3521V10.4411H19.9779H8.01234Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Hackathon.svg b/assets/icons/polkadot/2color/Hackathon.svg
new file mode 100644
index 00000000..64d3d9d5
--- /dev/null
+++ b/assets/icons/polkadot/2color/Hackathon.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2.96952 21.1257L25.045 21.1257L25.045 3.33279L2.96952 3.3328L2.96952 21.1257Z"></path><rect x="1.26221" y="21.1257" width="25.4756" height="3.87427"></rect><path d="M9.6314 14.8193L6.52344 12.232L9.6314 9.6394"></path><path d="M18.3582 9.62899L21.4765 12.2268L18.3582 14.8193"></path><path d="M15.7403 7.03906L12.2494 17.4194"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Hash Function.svg b/assets/icons/polkadot/2color/Hash Function.svg
new file mode 100644
index 00000000..2208ef9c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Hash Function.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.4824 2L14.4824 4.41076"></path><path d="M14.4824 23.5892L14.4824 26"></path><path d="M19.1909 2L19.1909 4.41076"></path><path d="M9.77386 2L9.77387 4.41076"></path><path d="M12.5265 16.8856L5 8.21664L23.4938 8.21665L16.5408 16.8856L16.5408 19.7753L12.5131 19.7753L12.5265 16.8856Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Healthcare.svg b/assets/icons/polkadot/2color/Healthcare.svg
new file mode 100644
index 00000000..95b14d50
--- /dev/null
+++ b/assets/icons/polkadot/2color/Healthcare.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M4.02344 6.28188V14.6254C4.02344 18.0247 5.75033 21.1913 8.60811 23.0322L14.0977 26.5684L19.727 22.9405C22.5838 21.0994 24.3099 17.9334 24.3099 14.5348V6.28188L14.1621 2.56836L4.02344 6.28188Z"></path><path d="M10.7098 13.5192L17.3695 13.5552"></path><path d="M14.0586 10.2083L14.0226 16.868"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Help.svg b/assets/icons/polkadot/2color/Help.svg
new file mode 100644
index 00000000..cd4a79eb
--- /dev/null
+++ b/assets/icons/polkadot/2color/Help.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 26.6758C20.6274 26.6758 26 21.3032 26 14.6758C26 8.04836 20.6274 2.67578 14 2.67578C7.37258 2.67578 2 8.04836 2 14.6758C2 21.3032 7.37258 26.6758 14 26.6758Z"></path><path d="M14.0047 19.395C16.6109 19.395 18.7237 17.2823 18.7237 14.676C18.7237 12.0698 16.6109 9.95705 14.0047 9.95705C11.3985 9.95705 9.28571 12.0698 9.28571 14.676C9.28571 17.2823 11.3985 19.395 14.0047 19.395Z" fill="none"></path><path d="M10.8569 3.6758L13.3569 9.6758M17.1426 3.6758L14.6426 9.6758"></path><path d="M17.1427 25.6758L14.6427 19.6758M10.857 25.6758L13.357 19.6758"></path><path d="M24.9997 11.533L18.9997 14.033M24.9997 17.8187L18.9997 15.3187"></path><path d="M2.99988 17.8186L8.99988 15.3187M2.99988 11.5329L8.99988 14.0329"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Heterogeneous Sharding.svg b/assets/icons/polkadot/2color/Heterogeneous Sharding.svg
new file mode 100644
index 00000000..2613f458
--- /dev/null
+++ b/assets/icons/polkadot/2color/Heterogeneous Sharding.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7.1093 17.7642L10.2502 12.37" stroke-miterlimit="10"></path><path d="M20.8338 17.7642L17.693 12.37" stroke-miterlimit="10"></path><path d="M13.9553 6.49153C15.8158 6.49153 17.324 5.48605 17.324 4.24577C17.324 3.00548 15.8158 2 13.9553 2C12.0949 2 10.5867 3.00548 10.5867 4.24577C10.5867 5.48605 12.0949 6.49153 13.9553 6.49153V6.49153Z"></path><path d="M17.324 4.24583C17.324 5.48612 15.8158 6.4916 13.9553 6.4916C12.0949 6.4916 10.5867 5.48612 10.5867 4.24583V7.65046C10.5867 8.89075 12.0949 9.7561 13.9553 9.7561C15.8158 9.7561 17.324 8.89075 17.324 7.65046V4.24583Z"></path><rect x="4" y="21" width="5.14286" height="5.14286"></rect><path d="M22.5714 21L20 26.1429H22.5714H25.1429L22.5714 21Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Identify.svg b/assets/icons/polkadot/2color/Identify.svg
new file mode 100644
index 00000000..106e5c53
--- /dev/null
+++ b/assets/icons/polkadot/2color/Identify.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9,20.2c4.9,0,8.8-4,8.8-8.8c0-4.9-4-8.8-8.8-8.8C9,2.6,5,6.5,5,11.4C5,16.3,9,20.2,13.9,20.2z" stroke-miterlimit="10"></path><path d="M19.8,17.9c-1.2,1-2.6,1.8-4.2,2.1l3.8,6.5l4-2.3L19.8,17.9z" stroke-miterlimit="10"></path><path d="M20,17.6v-0.8c0-1.9-1.4-3.6-3.3-4.1L16,12.5c-0.5-0.1-0.7-0.7-0.4-1.1l0.5-0.6C17,9.7,17,8.3,16,7.3 c-1.1-1-2.8-1-3.9,0c-1,0.9-1.1,2.4-0.2,3.4l0.5,0.6c0.3,0.4,0.1,1-0.4,1.1l-0.7,0.2c-2,0.5-3.3,2.2-3.3,4.1v0.8"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Identity.svg b/assets/icons/polkadot/2color/Identity.svg
new file mode 100644
index 00000000..aa78bafc
--- /dev/null
+++ b/assets/icons/polkadot/2color/Identity.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 27 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="1.46045" y="1.47864" width="24.079" height="25.0421"></rect><path d="M7.23943 22.6682H19.7605" stroke-miterlimit="10"></path><path d="M15.15 10.8446L15.6821 10.2128C16.6391 9.07668 16.5628 7.39603 15.5068 6.35126C14.3964 5.25263 12.6086 5.25263 11.4982 6.35126C10.4422 7.39603 10.3659 9.07668 11.3229 10.2128L11.8549 10.8445C12.2069 11.2624 12.0073 11.9044 11.4804 12.0491L10.7114 12.2603C8.66075 12.8235 7.23943 14.6878 7.23943 16.8144V18.8156H19.7605V16.8109C19.7605 14.6861 18.3406 12.8233 16.2918 12.2602L15.5244 12.0493C14.9976 11.9045 14.7981 11.2625 15.15 10.8446Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Import Token.svg b/assets/icons/polkadot/2color/Import Token.svg
new file mode 100644
index 00000000..10513c67
--- /dev/null
+++ b/assets/icons/polkadot/2color/Import Token.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.0002 6.90186H26.0002V22.9019H10.0002"></path><circle cx="10" cy="14.9017" r="8"></circle><path d="M10.7999 14.9016H17.1999"></path><path d="M10.7999 10.9019H16.3999"></path><path d="M10.7999 18.9017H16.3999"></path><path d="M10.0002 6.90186V22.9019"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Indeterminate _ Negative.svg b/assets/icons/polkadot/2color/Indeterminate _ Negative.svg
new file mode 100644
index 00000000..52d0b4bf
--- /dev/null
+++ b/assets/icons/polkadot/2color/Indeterminate _ Negative.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26.9941 2.67578H2.99414V26.6758H26.9941V2.67578Z"></path><path d="M9.85114 14.6997L20.2407 14.7558"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Informational.svg b/assets/icons/polkadot/2color/Informational.svg
new file mode 100644
index 00000000..30b1ebd7
--- /dev/null
+++ b/assets/icons/polkadot/2color/Informational.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9883 26.6758C21.6157 26.6758 26.9883 21.3032 26.9883 14.6758C26.9883 8.04836 21.6157 2.67578 14.9883 2.67578C8.36086 2.67578 2.98828 8.04836 2.98828 14.6758C2.98828 21.3032 8.36086 26.6758 14.9883 26.6758Z"></path><path d="M14.998 13.082L15.0075 20.2122" stroke-miterlimit="10"></path><path d="M14.9881 8.67574L15.0063 8.69388" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Infrastructure.svg b/assets/icons/polkadot/2color/Infrastructure.svg
new file mode 100644
index 00000000..3abfacdf
--- /dev/null
+++ b/assets/icons/polkadot/2color/Infrastructure.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5 16V12H23V16" fill="none"></path><path d="M14.0335 7.54287C15.5641 7.54287 16.805 6.30206 16.805 4.77144C16.805 3.24081 15.5641 2 14.0335 2C12.5029 2 11.2621 3.24081 11.2621 4.77144C11.2621 6.30206 12.5029 7.54287 14.0335 7.54287Z"></path><path d="M13.9317 25.6754C15.4623 25.6754 16.7031 24.4346 16.7031 22.904C16.7031 21.3734 15.4623 20.1326 13.9317 20.1326C12.401 20.1326 11.1602 21.3734 11.1602 22.904C11.1602 24.4346 12.401 25.6754 13.9317 25.6754Z"></path><path d="M14.0128 7.65308L14.0128 20.1334"></path><path d="M4.77144 21.5152C6.30206 21.5152 7.54287 20.2743 7.54287 18.7437C7.54287 17.2131 6.30206 15.9723 4.77144 15.9723C3.24081 15.9723 2 17.2131 2 18.7437C2 20.2743 3.24081 21.5152 4.77144 21.5152Z"></path><path d="M23.2284 21.5152C24.759 21.5152 25.9998 20.2743 25.9998 18.7437C25.9998 17.2131 24.759 15.9723 23.2284 15.9723C21.6978 15.9723 20.457 17.2131 20.457 18.7437C20.457 20.2743 21.6978 21.5152 23.2284 21.5152Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Injected Account.svg b/assets/icons/polkadot/2color/Injected Account.svg
new file mode 100644
index 00000000..5819d379
--- /dev/null
+++ b/assets/icons/polkadot/2color/Injected Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9827 12.757L15.892 11.6638C17.4439 9.79803 17.3196 7.05736 15.6052 5.33974C13.7696 3.5007 10.7898 3.5007 8.95416 5.33974C7.23972 7.05736 7.11542 9.79803 8.66735 11.6638L9.57647 12.7568C10.1572 13.4549 9.82447 14.5198 8.94954 14.7631L7.71783 15.1056C4.34533 16.0435 2.01171 19.1146 2.01171 22.6151V25.9916H22.5393V22.6092C22.5393 19.1117 20.208 16.0431 16.8386 15.1054L15.6094 14.7633C14.7346 14.5199 14.402 13.4551 14.9827 12.757Z"></path><path d="M20.0093 5.00335L24.5 5.00334M22.8513 8.17789L25.9966 5.00334L22.8513 1.82128" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Interconnected.svg b/assets/icons/polkadot/2color/Interconnected.svg
new file mode 100644
index 00000000..206f620e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Interconnected.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.0096 15L19.6171 18.9072M8.58282 18.7747L14.0001 15V9.7512" fill="none" data-nofill="true"></path><path d="M17.9999 5.95697C17.9999 3.77166 16.2283 2.00011 14.043 2.00011C11.8577 2.00011 10.0862 3.77166 10.0862 5.95697C10.0862 8.14228 11.8577 9.91382 14.043 9.91382C16.2283 9.91382 17.9999 8.14228 17.9999 5.95697Z"></path><path d="M9.16639 21.0431C9.16639 18.8578 7.39485 17.0863 5.20954 17.0863C3.02423 17.0863 1.25269 18.8578 1.25269 21.0431C1.25269 23.2285 3.02423 25 5.20954 25C7.39485 25 9.16639 23.2285 9.16639 21.0431Z"></path><path d="M26.747 21.0431C26.747 18.8578 24.9754 17.0863 22.7901 17.0863C20.6048 17.0863 18.8333 18.8578 18.8333 21.0431C18.8333 23.2285 20.6048 25 22.7901 25C24.9754 25 26.747 23.2285 26.747 21.0431Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Interoperability.svg b/assets/icons/polkadot/2color/Interoperability.svg
new file mode 100644
index 00000000..72353353
--- /dev/null
+++ b/assets/icons/polkadot/2color/Interoperability.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.36649 24.4503C15.3574 26.7917 22.1118 23.8339 24.4529 17.8438C26.7939 11.8537 23.8351 5.09971 17.8442 2.75833C11.8533 0.416941 5.09886 3.3748 2.75781 9.36488C0.416752 15.355 3.37556 22.109 9.36649 24.4503Z"></path><path d="M10.3107 13.9197L12.2736 10.8418M16.7663 13.5669L15.2206 10.8713M15.4945 16.4535L12.1033 16.4399"></path><path d="M17.3645 18.9673C18.7605 19.5136 20.3365 18.8183 20.8845 17.4143C21.4325 16.0104 20.7451 14.4294 19.3491 13.8832C17.9531 13.3369 16.3771 14.0322 15.8291 15.4362C15.2811 16.8401 15.9685 18.4211 17.3645 18.9673Z"></path><path d="M7.81566 19.0113C9.21166 19.5575 10.7876 18.8622 11.3356 17.4583C11.8837 16.0543 11.1962 14.4734 9.80024 13.9271C8.40424 13.3809 6.82829 14.0762 6.28026 15.4801C5.73223 16.8841 6.41965 18.465 7.81566 19.0113Z"></path><path d="M12.7483 11.014C14.1443 11.5603 15.7203 10.865 16.2683 9.46104C16.8163 8.05709 16.1289 6.47614 14.7329 5.92989C13.3369 5.38364 11.761 6.07893 11.2129 7.48288C10.6649 8.88683 11.3523 10.4678 12.7483 11.014Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Investors.svg b/assets/icons/polkadot/2color/Investors.svg
new file mode 100644
index 00000000..a34a688c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Investors.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/IoT And Robotics.svg b/assets/icons/polkadot/2color/IoT And Robotics.svg
new file mode 100644
index 00000000..6ba38c72
--- /dev/null
+++ b/assets/icons/polkadot/2color/IoT And Robotics.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M15 10.9774L11.387 12.9992C10.8592 12.5718 10.2336 12.2502 9.53656 12.0676C6.85492 11.3652 4.11249 12.9691 3.41008 15.6508C3.22964 16.3396 3.20756 17.0262 3.30712 17.6832L7.19007 15.4053L8.90298 18.334L4.92689 20.6664C5.50308 21.1766 6.20599 21.5711 7.00147 21.7794C9.68311 22.4818 12.4255 20.8779 13.128 18.1962C13.332 17.4172 13.3367 16.6297 13.1805 15.8877L16.5 13.9934" stroke-miterlimit="10"></path><path d="M16.512 12.8858C17.6393 14.1541 19.5813 14.2684 20.8496 13.1411C22.1179 12.0138 22.2322 10.0718 21.105 8.80354C19.9777 7.53524 18.0357 7.42092 16.7674 8.54819C15.4991 9.67547 15.3848 11.6175 16.512 12.8858Z"></path><path d="M19.3769 14.5001L23.9529 21.6126L26.854 19.7462L22.192 12.5001"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/IoT.svg b/assets/icons/polkadot/2color/IoT.svg
new file mode 100644
index 00000000..41f96079
--- /dev/null
+++ b/assets/icons/polkadot/2color/IoT.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M15.4119 7.57826C16.9523 7.57826 18.201 6.32953 18.201 4.78913C18.201 3.24874 16.9523 2 15.4119 2C13.8715 2 12.6228 3.24874 12.6228 4.78913C12.6228 6.32953 13.8715 7.57826 15.4119 7.57826Z"></path><path d="M5.78913 21.4489C7.32953 21.4489 8.57826 20.2002 8.57826 18.6598C8.57826 17.1194 7.32953 15.8706 5.78913 15.8706C4.24874 15.8706 3 17.1194 3 18.6598C3 20.2002 4.24874 21.4489 5.78913 21.4489Z"></path><path d="M21.7582 26C23.2986 26 24.5473 24.7513 24.5473 23.2109C24.5473 21.6705 23.2986 20.4218 21.7582 20.4218C20.2178 20.4218 18.9691 21.6705 18.9691 23.2109C18.9691 24.7513 20.2178 26 21.7582 26Z"></path><path d="M15.4119 17.8724C16.9523 17.8724 18.201 16.6237 18.201 15.0833C18.201 13.5429 16.9523 12.2941 15.4119 12.2941C13.8715 12.2941 12.6228 13.5429 12.6228 15.0833C12.6228 16.6237 13.8715 17.8724 15.4119 17.8724Z"></path><path d="M12.1823 16.2561L9 17.4465"></path><path d="M17.5 17.7715L19.6315 20.5"></path><path d="M15.4113 11.5L15.4113 8.5"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Isolated.svg b/assets/icons/polkadot/2color/Isolated.svg
new file mode 100644
index 00000000..66a0e3ad
--- /dev/null
+++ b/assets/icons/polkadot/2color/Isolated.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="6.51454" cy="12.0567" r="3.19226" transform="rotate(45 6.51454 12.0567)"></circle><circle cx="6.51454" cy="21.4854" r="3.19226" transform="rotate(45 6.51454 21.4854)"></circle><circle cx="21.4858" cy="6.51454" r="3.19226" transform="rotate(45 21.4858 6.51454)"></circle><circle cx="15.9432" cy="21.4854" r="3.19226" transform="rotate(45 15.9432 21.4854)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/KeepAlive Check.svg b/assets/icons/polkadot/2color/KeepAlive Check.svg
new file mode 100644
index 00000000..09f055cd
--- /dev/null
+++ b/assets/icons/polkadot/2color/KeepAlive Check.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 5L26 14.5L26 23L2 23L2 14L2 5L26 5Z"></path><path d="M2 14H8L10 11L14 19L19 8.5L22 14H26"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Key.svg b/assets/icons/polkadot/2color/Key.svg
new file mode 100644
index 00000000..7a73183c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Key.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.55463 17.6863C9.20301 18.0092 8.7912 18.2597 8.34269 18.4234C7.89419 18.5871 7.41779 18.6608 6.94068 18.6403C6.46358 18.6199 5.99512 18.5056 5.56205 18.3041C5.12898 18.1026 4.73978 17.8178 4.41667 17.4659C3.77335 16.7485 3.4409 15.8052 3.49234 14.8433C3.54379 13.8814 3.97492 12.9794 4.69103 12.3356C5.04265 12.0127 5.45447 11.7622 5.90297 11.5985C6.35147 11.4348 6.82788 11.3611 7.30498 11.3816C7.78209 11.402 8.25055 11.5163 8.68362 11.7178C9.11669 11.9193 9.50589 12.2041 9.82899 12.556C10.4719 13.2736 10.8042 14.2168 10.7527 15.1786C10.7013 16.1404 10.2704 17.0423 9.55463 17.6863V17.6863Z" fill="none"></path><path d="M10.8674 14.7892L26 14.7775" fill="none"></path><path d="M18.184 15.4861L18.1872 19.6325L23.2291 19.6338L23.2247 15.4886"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Language.svg b/assets/icons/polkadot/2color/Language.svg
new file mode 100644
index 00000000..3528ab4d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Language.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9766 26.6758C21.604 26.6758 26.9766 21.3032 26.9766 14.6758C26.9766 8.04836 21.604 2.67578 14.9766 2.67578C8.34915 2.67578 2.97656 8.04836 2.97656 14.6758C2.97656 21.3032 8.34915 26.6758 14.9766 26.6758Z" stroke-miterlimit="10"></path><path d="M15.0687 2.90655C23.684 10.6789 23.684 18.525 15.0687 26.445"></path><path d="M15.0685 26.445C6.45315 18.6727 6.45315 10.8265 15.0685 2.90655"></path><path d="M3.8551 18.3679H25.8019"></path><path d="M3.85504 10.9833H26.2659"></path><path d="M15.0594 2.90655V26.4358"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Layer (Four).svg b/assets/icons/polkadot/2color/Layer (Four).svg
new file mode 100644
index 00000000..4581cef4
--- /dev/null
+++ b/assets/icons/polkadot/2color/Layer (Four).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.3014 19.285L25 21.1915L14.1947 26.5812L3 20.8108L6.90728 18.8619" stroke-miterlimit="10"></path><path d="M21.283 14.7928L25 16.7087L14.1947 22.0984L3 16.3281L6.71577 14.4747" stroke-miterlimit="10"></path><path d="M21.0712 10.2144L25 12.2396L14.1947 17.6293L3 11.8589L7.09859 9.81456" stroke-miterlimit="10"></path><path d="M25 7.77035L14.1947 13.16L3 7.3897L13.8053 2L25 7.77035Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Layer (One).svg b/assets/icons/polkadot/2color/Layer (One).svg
new file mode 100644
index 00000000..cd30ff89
--- /dev/null
+++ b/assets/icons/polkadot/2color/Layer (One).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 13.7704L14.1947 19.16L3 13.3897L13.8053 8L25 13.7704Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Layer (Three).svg b/assets/icons/polkadot/2color/Layer (Three).svg
new file mode 100644
index 00000000..85eff55e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Layer (Three).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M6.73274 16.4662L3 18.3281L14.1947 24.0984L25 18.7087L21.3521 16.8284" stroke-miterlimit="10"></path><path d="M21.155 12.2577L25 14.2396L14.1947 19.6293L3 13.8589L6.81434 11.9563" stroke-miterlimit="10"></path><path d="M25 9.77035L14.1947 15.16L3 9.3897L13.8053 4L25 9.77035Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Layer (Two).svg b/assets/icons/polkadot/2color/Layer (Two).svg
new file mode 100644
index 00000000..9a9fe368
--- /dev/null
+++ b/assets/icons/polkadot/2color/Layer (Two).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.3211 14.3433L25 16.2396L14.1947 21.6293L3 15.8589L6.6688 14.0289" stroke-miterlimit="10"></path><path d="M25 11.7704L14.1947 17.16L3 11.3897L13.8053 6L25 11.7704Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Layer.svg b/assets/icons/polkadot/2color/Layer.svg
new file mode 100644
index 00000000..e5bb8f31
--- /dev/null
+++ b/assets/icons/polkadot/2color/Layer.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.0036 13.999L21.008 18.0059L13.0011 26L5 17.9989L8.99863 14.0002" stroke-miterlimit="10"></path><path d="M21.0032 9.99642L13.0012 17.9989L5.00208 9.9991L13.0015 1.99985L21.0032 9.99642Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Learn More.svg b/assets/icons/polkadot/2color/Learn More.svg
new file mode 100644
index 00000000..8ce3c3cf
--- /dev/null
+++ b/assets/icons/polkadot/2color/Learn More.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9707 26.6758C21.5981 26.6758 26.9707 21.3032 26.9707 14.6758C26.9707 8.04836 21.5981 2.67578 14.9707 2.67578C8.34329 2.67578 2.9707 8.04836 2.9707 14.6758C2.9707 21.3032 8.34329 26.6758 14.9707 26.6758Z"></path><path d="M11.9707 12.4519C11.9707 10.9187 13.2136 9.67581 14.7468 9.67581C16.2799 9.67581 17.5228 10.9187 17.5228 12.4519C17.5228 13.985 16.2799 15.2279 14.7468 15.2279L14.7468 17.3796"></path><path d="M14.7468 20.6562L14.7468 20.6756"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Learn.svg b/assets/icons/polkadot/2color/Learn.svg
new file mode 100644
index 00000000..03243c85
--- /dev/null
+++ b/assets/icons/polkadot/2color/Learn.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M4.11078 23.0243V13.2732L13.5299 16.3413L22.9491 13.2732V23.0253L13.5299 26.42L4.11078 23.0243Z"></path><path d="M13.5289 26L13.5289 16.5"></path><path d="M10.47 11.8814L9.34205 12.1946C8.14881 12.526 7.10352 13.1515 6.2619 13.9734L13.528 16.3403L20.7922 13.9743C19.9506 13.1515 18.9034 12.5251 17.7102 12.1946L16.5803 11.8814C15.7781 11.6592 15.4726 10.685 16.0048 10.0461L16.8388 9.0461C18.2626 7.33917 18.1483 4.83242 16.5755 3.26152C14.8913 1.57949 12.158 1.57949 10.4729 3.26152C8.90011 4.83242 8.78578 7.34013 10.2096 9.0461L11.0435 10.0461C11.5768 10.685 11.2712 11.6582 10.468 11.8814H10.47Z"></path><path d="M23.5 19.2934C24.0306 19.2934 24.4607 18.8633 24.4607 18.3327C24.4607 17.8021 24.0306 17.3719 23.5 17.3719"></path><path d="M3.5 17.3685C2.96939 17.3685 2.53925 17.7986 2.53925 18.3293C2.53925 18.8599 2.96939 19.29 3.5 19.29"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Lease Duration.svg b/assets/icons/polkadot/2color/Lease Duration.svg
new file mode 100644
index 00000000..33651d50
--- /dev/null
+++ b/assets/icons/polkadot/2color/Lease Duration.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M27 27H3V4.88454H27V27Z" stroke-miterlimit="10"></path><path d="M10.4233 7.34171V3" stroke-miterlimit="10"></path><path d="M19.5764 7.34178V3.00008" stroke-miterlimit="10"></path><path d="M14.9994 22.9988C18.3128 22.9988 20.9988 20.3128 20.9988 16.9994C20.9988 13.686 18.3128 11 14.9994 11C11.686 11 9 13.686 9 16.9994C9 20.3128 11.686 22.9988 14.9994 22.9988Z"></path><path d="M15.1147 15.4439V18.0033L14.1109 19.2213"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Library.svg b/assets/icons/polkadot/2color/Library.svg
new file mode 100644
index 00000000..8511b3df
--- /dev/null
+++ b/assets/icons/polkadot/2color/Library.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><rect x="1.29297" y="2" width="4" height="24"></rect><rect x="9" y="2" width="4" height="24"></rect><rect x="16.3813" y="3.03516" width="4" height="24" transform="rotate(-15 16.3813 3.03516)"></rect></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Light Node.svg b/assets/icons/polkadot/2color/Light Node.svg
new file mode 100644
index 00000000..96ddd9fb
--- /dev/null
+++ b/assets/icons/polkadot/2color/Light Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5494 21.0257L18.5239 16.621"></path><path d="M9.51521 16.6348L6.4502 21.0121"></path><path d="M20.4691 23.2263C20.4691 24.7582 21.711 26 23.2429 26C24.7748 26 26.0166 24.7582 26.0166 23.2263C26.0166 21.6944 24.7748 20.4525 23.2429 20.4525C21.711 20.4525 20.4691 21.6944 20.4691 23.2263Z"></path><path d="M2.00003 23.2263C2.00003 24.7582 3.24187 26 4.77376 26C6.30564 26 7.54749 24.7582 7.54749 23.2263C7.54749 21.6944 6.30565 20.4525 4.77376 20.4525C3.24187 20.4525 2.00003 21.6944 2.00003 23.2263Z"></path><path d="M5.99873 10.0109C5.99873 14.4352 9.58534 18.0218 14.0096 18.0218C18.434 18.0218 22.0206 14.4352 22.0206 10.0109C22.0206 5.58661 18.434 2 14.0096 2C9.58534 2 5.99873 5.58661 5.99873 10.0109Z" stroke-miterlimit="10"></path><path d="M15.7405 13.4617C16.0497 13.293 16.3403 13.0778 16.602 12.8161C16.8576 12.5606 17.0688 12.2774 17.2356 11.9763M12.1604 13.4769C11.8406 13.3061 11.5403 13.0858 11.2707 12.8161C11.0466 12.592 10.8566 12.3467 10.7007 12.0867M15.8061 6.87589C16.0909 7.0387 16.3589 7.24167 16.602 7.48477C16.8462 7.729 17.05 7.9984 17.2132 8.28461M10.5977 8.39755C10.7702 8.06917 10.9945 7.76088 11.2707 7.48477C11.5443 7.21111 11.8496 6.98832 12.1747 6.81639"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Lights On.svg b/assets/icons/polkadot/2color/Lights On.svg
new file mode 100644
index 00000000..adc440cf
--- /dev/null
+++ b/assets/icons/polkadot/2color/Lights On.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9884 11.1283C12.227 11.1283 9.9884 13.3679 9.9884 16.1306C9.9884 18.1819 11.2225 19.9448 12.9884 20.7167L12.9883 25.7167H16.9883L16.9884 20.7167C18.7543 19.9448 19.9884 18.1819 19.9884 16.1306C19.9884 13.3679 17.7498 11.1283 14.9884 11.1283Z"></path><path d="M14.9883 7.12823L14.9883 4.12823"></path><path d="M2.98834 16.1282L5.98834 16.1282"></path><path d="M23.9883 16.1282L26.9883 16.1282"></path><path d="M21.3523 9.76437L23.4736 7.64305"></path><path d="M6.50283 7.64293L8.62415 9.76425"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Limited Supply.svg b/assets/icons/polkadot/2color/Limited Supply.svg
new file mode 100644
index 00000000..09103588
--- /dev/null
+++ b/assets/icons/polkadot/2color/Limited Supply.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M4.56793 24.4529H23.4045V7.51797H4.56793V24.4529Z"></path><path d="M2 7.51174H26V3H2V7.51174Z"></path><path d="M14.9603 19.876L19.351 19.8904L19.3655 15.5071"></path><path d="M8.11823 12.1604L12.0457 15.7778L13.8051 14.0185L18.482 18.9733"></path></svg>
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diff --git a/assets/icons/polkadot/2color/LinkedIn.svg b/assets/icons/polkadot/2color/LinkedIn.svg
new file mode 100644
index 00000000..46016a56
--- /dev/null
+++ b/assets/icons/polkadot/2color/LinkedIn.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 2H2V26H26V2Z"></path><path d="M8.87455 10.8805L8.87997 20.1966M13.4787 20.1966L13.4787 14M19.9888 20.1966L19.9888 14.8649C19.9888 13.208 18.6457 11.8649 16.9888 11.8649L15.6138 11.8649C14.4346 11.8649 13.4787 12.8208 13.4787 14V14M13.4787 10.8805L13.4787 14" stroke-miterlimit="10"></path><path d="M8.85718 7.14287L8.87837 7.16406" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Lock.svg b/assets/icons/polkadot/2color/Lock.svg
new file mode 100644
index 00000000..01295407
--- /dev/null
+++ b/assets/icons/polkadot/2color/Lock.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.12132 10.1541L8.12134 8.41857V8.41857C8.12134 5.42598 10.5473 3 13.5399 3V3C16.5325 3 18.9585 5.42598 18.9585 8.41857V8.41857L18.9585 10.1541" fill="none"></path><path d="M24.0798 10.6693H3V26H24.0798V10.6693Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Maintain.svg b/assets/icons/polkadot/2color/Maintain.svg
new file mode 100644
index 00000000..61fe3daa
--- /dev/null
+++ b/assets/icons/polkadot/2color/Maintain.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.2419 21.4536C20.5351 20.4931 21.5509 19.1973 22.1738 17.6979C22.9295 15.8789 23.0648 13.8615 22.5587 11.9579C22.0527 10.0542 20.9336 8.3703 19.3744 7.16659C17.8152 5.96289 15.9028 5.30646 13.933 5.29883L13.0491 5.35498M15.6857 8.72868L12.2762 5.4095L15.5954 2" fill="none" data-nofill="true"></path><path d="M8.62964 7.05725C7.34892 8.00527 6.3384 9.28218 5.71112 10.7614C4.9389 12.5825 4.79091 14.6079 5.29021 16.5219C5.7895 18.4358 6.90803 20.1308 8.47142 21.3426C10.0348 22.5544 11.9552 23.2148 13.9332 23.221L14.8064 23.1759M12.2705 19.7809L15.6044 23.1112L12.3372 26.5096" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Marketing.svg b/assets/icons/polkadot/2color/Marketing.svg
new file mode 100644
index 00000000..8fbdc7ac
--- /dev/null
+++ b/assets/icons/polkadot/2color/Marketing.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2.00011 16.7242C2.00011 22.0367 6.30674 26.3433 11.6192 26.3433C16.9317 26.3433 21.2383 22.0367 21.2383 16.7242C21.2383 11.4117 16.9317 7.1051 11.6192 7.1051C6.30673 7.1051 2.00011 11.4117 2.00011 16.7242Z"></path><path d="M6.18213 16.724C6.18213 19.7267 8.61631 22.1609 11.619 22.1609C14.6217 22.1609 17.0559 19.7267 17.0559 16.724C17.0559 13.7213 14.6217 11.2871 11.619 11.2871C8.6163 11.2871 6.18213 13.7213 6.18213 16.724Z"></path><path d="M12.0376 16.5693L19.8289 8.77795"></path><path d="M22.5962 3L19.7678 5.82842V9.36396H23.3033L26.1317 6.53553L22.9497 6.18198L22.5962 3Z"></path><path d="M10.3645 16.724C10.3645 17.417 10.9262 17.9787 11.6192 17.9787C12.3121 17.9787 12.8738 17.417 12.8738 16.724C12.8738 16.0311 12.3121 15.4694 11.6192 15.4694C10.9262 15.4694 10.3645 16.0311 10.3645 16.724Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Menu.svg b/assets/icons/polkadot/2color/Menu.svg
new file mode 100644
index 00000000..7243a761
--- /dev/null
+++ b/assets/icons/polkadot/2color/Menu.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2.98242 14.9616H26.9824"></path><path d="M2.98242 22.2532H26.9824"></path><path d="M2.98242 7.66992H26.9824"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Message.svg b/assets/icons/polkadot/2color/Message.svg
new file mode 100644
index 00000000..5069baa1
--- /dev/null
+++ b/assets/icons/polkadot/2color/Message.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M7.0197 19.8928V25.4819L14.3572 19.8928H26.7523V2.24902H1.25195V19.8928H7.0197Z"></path><circle cx="7.5" cy="11.5" r="1.5"></circle><circle cx="13.5" cy="11.5" r="1.5"></circle><circle cx="19.5" cy="11.5" r="1.5"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Metaverse.svg b/assets/icons/polkadot/2color/Metaverse.svg
new file mode 100644
index 00000000..ed0092c8
--- /dev/null
+++ b/assets/icons/polkadot/2color/Metaverse.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 20.4615L14.0769 26L25.1538 20.4615V7.53846L14.0769 2L3 7.53846V20.4615Z"></path><path d="M6 14C6 15.6701 7.02353 17.1011 8.47754 17.7001C9.41213 18.085 10.43 17.656 11.2193 17.0246C12.845 15.724 15.155 15.724 16.7807 17.0246C17.57 17.656 18.5879 18.085 19.5225 17.7001C20.9765 17.1011 22 15.6701 22 14C22 11.7909 20.2091 10 18 10H10C7.79086 10 6 11.7909 6 14Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Mitigating Mev.svg b/assets/icons/polkadot/2color/Mitigating Mev.svg
new file mode 100644
index 00000000..3dcf534c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Mitigating Mev.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.9496 23.0396V26.5684H8.06305V23.0396"></path><path d="M14.0059 7.19092L14.0059 11.1531"></path><path d="M24.5716 11.8135H3.44006V23.0396H24.5716V11.8135Z"></path><path d="M9.71367 19.7376C10.9901 19.7376 12.0249 18.7029 12.0249 17.4264C12.0249 16.1499 10.9901 15.1151 9.71367 15.1151C8.43719 15.1151 7.4024 16.1499 7.4024 17.4264C7.4024 18.7029 8.43719 19.7376 9.71367 19.7376Z"></path><path d="M14.0058 6.53053C15.0999 6.53053 15.9869 5.64357 15.9869 4.54944C15.9869 3.45532 15.0999 2.56836 14.0058 2.56836C12.9117 2.56836 12.0247 3.45532 12.0247 4.54944C12.0247 5.64357 12.9117 6.53053 14.0058 6.53053Z"></path><path d="M18.2983 19.7376C19.5748 19.7376 20.6096 18.7029 20.6096 17.4264C20.6096 16.1499 19.5748 15.1151 18.2983 15.1151C17.0218 15.1151 15.9871 16.1499 15.9871 17.4264C15.9871 18.7029 17.0218 19.7376 18.2983 19.7376Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Mobile App.svg b/assets/icons/polkadot/2color/Mobile App.svg
new file mode 100644
index 00000000..269e00ff
--- /dev/null
+++ b/assets/icons/polkadot/2color/Mobile App.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.5109 2.33008H6V26.3301H22.5109V2.33008Z"></path><path d="M13.3052 23.0423H15.205"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Monitor.svg b/assets/icons/polkadot/2color/Monitor.svg
new file mode 100644
index 00000000..4a5fea94
--- /dev/null
+++ b/assets/icons/polkadot/2color/Monitor.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 16.5029H26V20.5H2V16.5029Z"></path><path d="M2 2.5H26V16.5029H2V2.5Z"></path><path d="M10 25H18"></path><path d="M14 24.5L14 20.5"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/More Horizontal.svg b/assets/icons/polkadot/2color/More Horizontal.svg
new file mode 100644
index 00000000..e3b34cc9
--- /dev/null
+++ b/assets/icons/polkadot/2color/More Horizontal.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="4.33032" cy="14.3303" r="2.35489" transform="rotate(45 4.33032 14.3303)"></circle><circle cx="13.9998" cy="14.3303" r="2.35489" transform="rotate(45 13.9998 14.3303)"></circle><circle cx="23.6696" cy="14.3303" r="2.35489" transform="rotate(45 23.6696 14.3303)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/More Menu.svg b/assets/icons/polkadot/2color/More Menu.svg
new file mode 100644
index 00000000..5c2692d1
--- /dev/null
+++ b/assets/icons/polkadot/2color/More Menu.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 5.07416 14.2383)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 14.0002 14.2383)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 22.9264 14.2383)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 5.07416 23.183)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 14.0002 23.183)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 22.9264 23.183)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 5.07416 5.29354)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 14.0002 5.29354)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 22.9264 5.29354)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/More Vertical.svg b/assets/icons/polkadot/2color/More Vertical.svg
new file mode 100644
index 00000000..9cd0c77e
--- /dev/null
+++ b/assets/icons/polkadot/2color/More Vertical.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="14.9941" cy="4.89896" r="2.35489" transform="rotate(135 14.9941 4.89896)"></circle><circle cx="14.9941" cy="14.5685" r="2.35489" transform="rotate(135 14.9941 14.5685)"></circle><circle cx="14.9941" cy="24.2382" r="2.35489" transform="rotate(135 14.9941 24.2382)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Multichain Smart Contracts.svg b/assets/icons/polkadot/2color/Multichain Smart Contracts.svg
new file mode 100644
index 00000000..b797422c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Multichain Smart Contracts.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="2" y="2.56836" width="24" height="24"></rect><rect x="5.42859" y="17.9969" width="5.14286" height="5.14286"></rect><path d="M14 3.42554V25.7113"></path><path d="M25.1429 14.5684L2.85717 14.5684"></path><circle cx="20" cy="8.56838" r="2.57143"></circle><path d="M20 17.9969L17.4286 23.1398H20H22.5714L20 17.9969Z"></path><path d="M8.00002 5.99695L5.42859 11.1398H8.00002H10.5714L8.00002 5.99695Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Multichain Treasuries.svg b/assets/icons/polkadot/2color/Multichain Treasuries.svg
new file mode 100644
index 00000000..407623d0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Multichain Treasuries.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.2321 8.49051L13.994 2L4.54816 8.56634V26.0002L23.2321 26.0002V8.49051Z"></path><path d="M2.00006 26.0002H4.54816M25.9999 26.0002H23.2321"></path><path d="M26 10.4352L23.2321 8.49048M2.00012 10.3376L4.54816 8.56631"></path><rect x="7.94513" y="18.2858" width="4.24641" height="4.28571"></rect><ellipse cx="17.7118" cy="12.7141" rx="2.12321" ry="2.14286"></ellipse><path d="M17.7118 18.2858L15.5886 22.5715H17.7118H19.835L17.7118 18.2858Z"></path><path d="M10.0683 10.5713L7.94513 14.857H10.0683H12.1915L10.0683 10.5713Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Multisign Account.svg b/assets/icons/polkadot/2color/Multisign Account.svg
new file mode 100644
index 00000000..1555d563
--- /dev/null
+++ b/assets/icons/polkadot/2color/Multisign Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11.5288 3L14.5715 6.04263L6.69473 13.9194L2.51937 15.0482L3.6521 10.8767L11.5288 3Z"></path><path d="M22.9574 3L26 6.04263L18.1233 13.9194L13.9479 15.0482L15.0806 10.8767L22.9574 3Z"></path><path d="M23.7608 21.0003L2.16085 21.0003M20.9217 17.4899L24.4412 21.0004L20.9217 24.52" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Multisign.svg b/assets/icons/polkadot/2color/Multisign.svg
new file mode 100644
index 00000000..1cd0f54b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Multisign.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.3712 25.6559H1.28534" stroke-miterlimit="10"></path><path d="M22.0711 12.9278L25.2854 16.1421L16.9642 24.4633L12.5532 25.6559L13.7499 21.249L22.0711 12.9278Z"></path><path d="M22.0711 2L25.2854 5.21432L16.9642 13.5355L12.5532 14.7281L13.7499 10.3212L22.0711 2Z"></path><path d="M9.3712 14.728H1.28534" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/NFT Staking.svg b/assets/icons/polkadot/2color/NFT Staking.svg
new file mode 100644
index 00000000..d02a1f55
--- /dev/null
+++ b/assets/icons/polkadot/2color/NFT Staking.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 21.0299L14.0769 26.5684L25.1538 21.0299V8.10682L14.0769 2.56836L3 8.10682V21.0299Z"></path><path d="M17.448 13.4007L14.0767 10.8134L10.7055 13.4007"></path><path d="M14.0536 11.6296V18.2098"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Network Is Connected.svg b/assets/icons/polkadot/2color/Network Is Connected.svg
new file mode 100644
index 00000000..7db919a5
--- /dev/null
+++ b/assets/icons/polkadot/2color/Network Is Connected.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M4 5.9518V14.2953C4 17.6947 5.7269 20.8612 8.58467 22.7021L14.0743 26.2383L19.7036 22.6104C22.5604 20.7693 24.2865 17.6034 24.2865 14.2048V5.9518L14.1386 2.23828L4 5.9518Z"></path><path d="M14.0091 15.3685L13.9996 8.23825" stroke-miterlimit="10"></path><path d="M14.0187 19.7748L14.0006 19.7566" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Network Security Operations.svg b/assets/icons/polkadot/2color/Network Security Operations.svg
new file mode 100644
index 00000000..7715eabc
--- /dev/null
+++ b/assets/icons/polkadot/2color/Network Security Operations.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M6.38416 5.05048V9.32685C6.38416 12.7262 8.11105 15.8928 10.9688 17.7336L13.4887 19.3569L16.1077 17.6691C18.9644 15.828 20.6905 12.662 20.6905 9.26342V5.05048L13.5341 2.43164L6.38416 5.05048Z"></path><path d="M11.0864 10.8108L13.2208 13.1803L17.1326 8.47766"></path><path d="M13.5411 22.9513V21.8663L13.5411 19.3029M12.5304 23.3763C13.0934 22.8133 14.0055 22.8126 14.5677 23.3747C15.1298 23.9368 15.1291 24.849 14.5661 25.412C14.003 25.9751 13.0909 25.9758 12.5287 25.4137C11.9666 24.8515 11.9673 23.9394 12.5304 23.3763Z"></path><path d="M19.9885 20.4934L19.9885 17.8104L18.7251 16.5693M21.0037 20.9203C20.4382 20.3548 19.522 20.3541 18.9574 20.9187C18.3928 21.4833 18.3935 22.3995 18.959 22.965C19.5246 23.5306 20.4408 23.5313 21.0054 22.9667C21.57 22.402 21.5693 21.4859 21.0037 20.9203Z"></path><path d="M7.08645 20.4934L7.08645 17.8104L8.49101 16.4306M6.07122 20.9203C6.63675 20.3548 7.55293 20.3541 8.11755 20.9187C8.68218 21.4833 8.68144 22.3995 8.11591 22.965C7.55037 23.5306 6.6342 23.5313 6.06957 22.9667C5.50495 22.402 5.50568 21.4859 6.07122 20.9203Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/New Tab.svg b/assets/icons/polkadot/2color/New Tab.svg
new file mode 100644
index 00000000..cd40753a
--- /dev/null
+++ b/assets/icons/polkadot/2color/New Tab.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 16.9434V26.2383H2V2.23828H11.2908" fill="none" data-nofill="true"></path><path d="M11.4286 16.8097L25 3.23431" fill="none" data-nofill="true"></path><path d="M16.3685 2.29291H25.9474V11.8719" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/News.svg b/assets/icons/polkadot/2color/News.svg
new file mode 100644
index 00000000..437c9b8b
--- /dev/null
+++ b/assets/icons/polkadot/2color/News.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M19.9104 22.567C19.9104 24.8828 21.2555 25.8828 22.9122 25.8828C24.5689 25.8828 25.9104 24.3986 25.9104 22.567L25.9104 5.8388L19.9104 5.8388"></path><path d="M19.9104 1.88281H1.9104V25.8828H23.0099C20.8154 25.8828 19.9095 24.4486 19.9095 22.5708L19.9104 1.88281Z"></path><path d="M6.28784 20.8828H15.2878" stroke-miterlimit="10"></path><path d="M6.28784 15.8828L15.2878 15.8828" stroke-miterlimit="10"></path><rect x="6.28784" y="5.88281" width="9" height="5"></rect></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Nft.svg b/assets/icons/polkadot/2color/Nft.svg
new file mode 100644
index 00000000..d7832bcc
--- /dev/null
+++ b/assets/icons/polkadot/2color/Nft.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2.03345 20.7869L13.6488 26.5946L25.2642 20.7869V7.23566L13.6488 1.42798L2.03345 7.23566V20.7869Z"></path><path d="M6.14062 16.9801V11.0425H6.17163L9.62476 16.9801H9.65493V11.0424"></path><path d="M20.376 16.9999V11.2902"></path><path d="M21.8601 11.0221L18.8916 11.0221"></path><path d="M13.3555 16.9977V11.0005H15.1913"></path><path d="M15.1917 14.2847L13.3555 14.2847"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Night_Dark Mode.svg b/assets/icons/polkadot/2color/Night_Dark Mode.svg
new file mode 100644
index 00000000..cd78d8d6
--- /dev/null
+++ b/assets/icons/polkadot/2color/Night_Dark Mode.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.933 18.407C22.9658 20.0772 20.2425 20.7935 17.5563 20.0914C13.1808 18.9478 10.5609 14.4736 11.7045 10.0981C12.6333 6.54463 15.7587 4.14906 19.244 3.98694C18.5497 3.6436 17.8103 3.36531 17.0315 3.16175C10.8543 1.54717 4.53783 5.24589 2.92325 11.4231C1.30867 17.6002 5.00739 23.9167 11.1846 25.5313C16.9727 27.0442 22.8831 23.892 24.933 18.407Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Node.svg b/assets/icons/polkadot/2color/Node.svg
new file mode 100644
index 00000000..9f31c021
--- /dev/null
+++ b/assets/icons/polkadot/2color/Node.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5358 21.0126L18.5124 16.6109"></path><path d="M9.50999 16.6247L6.44708 20.999"></path><path d="M20.4564 23.2116C20.4564 24.7425 21.6974 25.9834 23.2282 25.9834C24.759 25.9834 26 24.7425 26 23.2116C26 21.6808 24.759 20.4398 23.2282 20.4398C21.6974 20.4398 20.4564 21.6808 20.4564 23.2116Z"></path><path d="M2.00001 23.2116C2.00001 24.7425 3.24099 25.9834 4.77183 25.9834C6.30266 25.9834 7.54364 24.7425 7.54364 23.2116C7.54364 21.6808 6.30266 20.4398 4.77183 20.4398C3.24099 20.4398 2.00001 21.6808 2.00001 23.2116Z"></path><path d="M5.99593 10.0054C5.99593 14.4267 9.58006 18.0108 14.0013 18.0108C18.4226 18.0108 22.0067 14.4267 22.0067 10.0054C22.0067 5.58414 18.4226 2 14.0013 2C9.58006 2 5.99593 5.58414 5.99593 10.0054Z" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Nominating.svg b/assets/icons/polkadot/2color/Nominating.svg
new file mode 100644
index 00000000..607e732d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Nominating.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.8063 10.2429C15.1482 10.2429 20.8017 10.224 24.0544 10.2127C25.3424 10.2082 26.3854 11.251 26.3854 12.539V12.539C26.3854 13.8236 25.3439 14.8651 24.0593 14.8651L15.8327 14.8651L18.4876 14.8652C19.6072 14.8652 20.5149 15.9086 20.5149 17.1956C20.5149 18.4826 19.6072 19.5259 18.4876 19.5259L15.8327 19.5259L17.3597 19.5259C18.4794 19.5259 19.387 20.5939 19.387 21.8809C19.387 23.1679 18.4794 24.2112 17.3597 24.2112L15.2382 24.2112L12.4615 24.2112C8.52621 24.2111 6.95186 20.0641 6.95186 20.0641L1.38538 20.0641L1.38538 11.3893L6.95186 11.3893C6.95186 11.3893 7.49398 9.97422 9.56296 7.2054C11.4093 4.73458 13.1113 4.36533 13.4562 4.31447C13.4992 4.30813 13.5415 4.30683 13.5849 4.30683V4.30683C15.3328 4.30683 16.1822 6.50551 14.9953 7.78866C13.7981 9.08303 12.961 10.2429 13.8063 10.2429Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Nominators.svg b/assets/icons/polkadot/2color/Nominators.svg
new file mode 100644
index 00000000..40e3e3b5
--- /dev/null
+++ b/assets/icons/polkadot/2color/Nominators.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.4273 6.57269H2V26H21.4273V6.57269Z"></path><path d="M7.11935 14.0187L12.3012 18.7889L25.0074 2" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Not Able To Upgrade.svg b/assets/icons/polkadot/2color/Not Able To Upgrade.svg
new file mode 100644
index 00000000..b42db7d0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Not Able To Upgrade.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M13.9998 6.94277L13.9998 21.0572M13.9998 6.94277L10.7449 10.1977M13.9998 6.94277L17.2547 10.1977"></path><path d="M7.35387 23.6934L22.1447 5.61578"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Not Scalable.svg b/assets/icons/polkadot/2color/Not Scalable.svg
new file mode 100644
index 00000000..a70a90cb
--- /dev/null
+++ b/assets/icons/polkadot/2color/Not Scalable.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.9809 22.0069C18.4058 22.0069 21.9929 18.4198 21.9929 13.9949C21.9929 9.57006 18.4058 5.98297 13.9809 5.98297C9.55603 5.98297 5.96894 9.57006 5.96894 13.9949C5.96894 18.4198 9.55603 22.0069 13.9809 22.0069Z" stroke-miterlimit="10"></path><path d="M16.0572 15.8242L12.0581 11.8251" fill="none" data-nofill="true"></path><path d="M16.0572 11.8251L12.0581 15.8242" fill="none" data-nofill="true"></path><path d="M20.857 2.01674L25.9632 2L25.98 7.09755" fill="none" data-nofill="true"></path><path d="M25.478 2.67471L19.708 8.36659" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M7.12301 2.01674L2.0168 2L2.00003 7.09755" fill="none" data-nofill="true"></path><path d="M2.50202 2.67471L8.28686 8.36681" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M2.01674 20.877L2 25.9832L7.09755 26" fill="none" data-nofill="true"></path><path d="M2.67472 25.4979L8.38563 19.7086" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M25.9635 20.877L25.9802 25.9832L20.8827 26" fill="none" data-nofill="true"></path><path d="M25.3055 25.498L19.5948 19.709" stroke-miterlimit="10" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Notification.svg b/assets/icons/polkadot/2color/Notification.svg
new file mode 100644
index 00000000..4bc0e83d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Notification.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13 24L13 25.7874C13 26.3435 13.4508 26.797 14.0069 26.8005C14.5629 26.8039 15.0137 26.3559 15.0137 25.7998L15.0137 24"></path><path d="M15 5.5L15 3.8259C15 3.26982 14.5492 2.81625 13.9931 2.81283C13.4371 2.8094 12.9863 3.25742 12.9863 3.8135L12.9863 5.5"></path><path d="M5 23.9507L23.1233 23.9507"></path><path d="M7.01355 23.5V12.4658C7.01355 8.65544 10.1025 5.56653 13.9128 5.56653C17.7232 5.56653 20.8121 8.65544 20.8121 12.4658V23.5047"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Off-Chain Computations.svg b/assets/icons/polkadot/2color/Off-Chain Computations.svg
new file mode 100644
index 00000000..391f13c9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Off-Chain Computations.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 7.13977H5M26 7.13977H23M11 7.13977H17.2523"></path><path d="M2 14.854H11M26 14.854H17"></path><path d="M2 22.854H5.42397M26 22.854H22.5M17.3319 22.854H10.5"></path><path d="M17.4287 7.09099C17.4287 8.4842 18.5581 9.61362 19.9513 9.61362C21.3445 9.61362 22.4739 8.4842 22.4739 7.09099C22.4739 5.69778 21.3445 4.56836 19.9513 4.56836C18.5581 4.56836 17.4287 5.69778 17.4287 7.09099Z"></path><path d="M5.42868 7.09099C5.42868 8.4842 6.5581 9.61362 7.95131 9.61362C9.34452 9.61362 10.4739 8.4842 10.4739 7.09099C10.4739 5.69778 9.34452 4.56836 7.95131 4.56836C6.5581 4.56836 5.42868 5.69778 5.42868 7.09099Z"></path><path d="M17.4287 22.5196C17.4287 23.9128 18.5581 25.0422 19.9513 25.0422C21.3445 25.0422 22.4739 23.9128 22.4739 22.5196C22.4739 21.1264 21.3445 19.9969 19.9513 19.9969C18.5581 19.9969 17.4287 21.1264 17.4287 22.5196Z"></path><path d="M5.42868 22.5196C5.42868 23.9128 6.5581 25.0422 7.95131 25.0422C9.34452 25.0422 10.4739 23.9128 10.4739 22.5196C10.4739 21.1264 9.34452 19.9969 7.95131 19.9969C6.5581 19.9969 5.42868 21.1264 5.42868 22.5196Z"></path><path d="M11.4287 14.8052C11.4287 16.1984 12.5581 17.3279 13.9513 17.3279C15.3445 17.3279 16.4739 16.1984 16.4739 14.8052C16.4739 13.412 15.3445 12.2826 13.9513 12.2826C12.5581 12.2826 11.4287 13.412 11.4287 14.8052Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Offboarding.svg b/assets/icons/polkadot/2color/Offboarding.svg
new file mode 100644
index 00000000..8234d289
--- /dev/null
+++ b/assets/icons/polkadot/2color/Offboarding.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M0.999939 27.1705H25.7123"></path><path d="M6.23971 16.9001L21.2391 21.4671C24.0383 22.3194 25.1269 18.7523 22.3277 17.9L16.4128 16.099C14.5477 11.649 12.9539 7.05398 11.2165 2.54914L10.9436 14.4225C8.88909 13.7969 7.32833 13.333 7.32833 13.333L6.17453 12.9817L3.18006 8.85216L3.33516 16.0427L5.11579 16.5683L6.23971 16.9001Z"></path><path d="M10.9436 13.7584L11.2166 2.54913L16.1301 15.2894"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/On-Chain Scheduling.svg b/assets/icons/polkadot/2color/On-Chain Scheduling.svg
new file mode 100644
index 00000000..b5f003ef
--- /dev/null
+++ b/assets/icons/polkadot/2color/On-Chain Scheduling.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.05891 17.8344H2L2 24.8933H9.05891V17.8344Z"></path><path d="M25.9999 17.8344H18.941V24.8933H25.9999V17.8344Z"></path><path d="M5.42847 20.7112V15.1398V9.56836H7.5M22.5712 20.7112V9.56836L20.5 9.56836" fill="none" data-nofill="true"></path><path d="M14.063 15.3989C17.3299 15.3989 19.9783 12.7505 19.9783 9.48362C19.9783 6.21671 17.3299 3.56836 14.063 3.56836C10.7961 3.56836 8.14777 6.21671 8.14777 9.48362C8.14777 12.7505 10.7961 15.3989 14.063 15.3989Z"></path><path d="M15.9061 9.00568L14.1709 10.0468L14.1708 6.82287"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Onboarding.svg b/assets/icons/polkadot/2color/Onboarding.svg
new file mode 100644
index 00000000..1d12a6ae
--- /dev/null
+++ b/assets/icons/polkadot/2color/Onboarding.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M1.9021 25.7822L25.5969 25.7822"></path><path d="M9.27793 18.6974L23.2046 14.101C25.8036 13.2432 24.7124 9.92991 22.1134 10.7877L16.6215 12.6003C12.7966 10.2046 9.10109 7.55184 5.34434 5.04545L11.5374 14.2676C9.62981 14.8972 8.18674 15.3841 8.18674 15.3841L7.11546 15.7377L2.60026 14.1959L6.59565 19.6081L8.24002 19.0498L9.27793 18.6974Z"></path><path d="M11.1794 13.7601L5.34448 5.04547L15.9691 12.1339"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Oracle.svg b/assets/icons/polkadot/2color/Oracle.svg
new file mode 100644
index 00000000..1e033aa9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Oracle.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M6.78715 20.9793H20.7785C23.093 19.0019 24.5657 16.0662 24.5657 12.7828C24.5657 6.82793 19.7377 2 13.7828 2C7.82793 2 3 6.82793 3 12.7828C3 16.0662 4.47262 19.001 6.78715 20.9793V20.9793Z"></path><path d="M19.3362 11.9438C19.3362 11.3037 19.0753 10.6914 18.6138 10.2479L17.3111 8.99609C16.8741 8.5748 16.3604 8.24299 15.7984 8.01903C14.6527 7.56987 13.3819 7.56987 12.2362 8.01903C11.6857 8.24671 11.1834 8.57832 10.756 8.99609L9.40974 10.2593C8.94549 10.6949 8.68213 11.3031 8.68213 11.9398V11.9398C8.68213 12.5569 8.92964 13.1482 9.36924 13.5813L10.7072 14.8995C11.3794 15.5257 12.2124 15.9486 13.1111 16.1199C14.0098 16.2912 14.9382 16.204 15.7902 15.8684C16.3503 15.6443 16.8635 15.3156 17.3029 14.8995L18.614 13.6395C19.0754 13.196 19.3362 12.5837 19.3362 11.9438V11.9438Z"></path><path d="M14.0386 11.9732L14.0092 11.9438" stroke-miterlimit="10"></path><path d="M21.4113 20.9793H6.15474C5.53974 22.3958 3.97095 26 3.97095 26H23.6059C22.8623 24.3317 22.1387 22.6547 21.4113 20.9793Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Oracles.svg b/assets/icons/polkadot/2color/Oracles.svg
new file mode 100644
index 00000000..840e853a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Oracles.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M10.3184 5.13758C12.0523 3.21126 14.5652 2 17.3609 2C22.5922 2 26.8335 6.24131 26.8335 11.4726C26.8335 14.357 25.5398 16.9361 23.5065 18.6732C24.1455 20.145 25.3371 21.6183 25.9903 23.0838H21.497"></path><path d="M7.32699 21.5893H19.6183C21.6516 19.8522 22.9453 17.2732 22.9453 14.3888C22.9453 9.15744 18.704 4.91614 13.4726 4.91614C8.24131 4.91614 4 9.15744 4 14.3888C4 17.2732 5.29369 19.8514 7.32699 21.5893V21.5893Z"></path><path d="M18.3513 13.6518C18.3513 13.0895 18.1221 12.5515 17.7167 12.162L16.5722 11.0622C16.1884 10.6921 15.7371 10.4006 15.2433 10.2039C14.2368 9.80931 13.1205 9.80931 12.114 10.2039C11.6304 10.4039 11.1891 10.6952 10.8136 11.0622L9.63096 12.1719C9.22312 12.5546 8.99176 13.089 8.99176 13.6482V13.6482C8.99176 14.1904 9.2092 14.7098 9.59538 15.0903L10.7708 16.2484C11.3613 16.7985 12.093 17.1699 12.8826 17.3204C13.6721 17.4709 14.4877 17.3944 15.2362 17.0995C15.7282 16.9027 16.1791 16.6139 16.5651 16.2484L17.7168 15.1414C18.1222 14.7518 18.3513 14.2139 18.3513 13.6518V13.6518Z"></path><path d="M13.6973 13.6776L13.6714 13.6517" stroke-miterlimit="10"></path><path d="M20.1742 21.5894H6.77142C6.23114 22.8337 4.85297 26 4.85297 26H22.1021C21.4489 24.5344 20.8132 23.0611 20.1742 21.5894Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Overview.svg b/assets/icons/polkadot/2color/Overview.svg
new file mode 100644
index 00000000..c552b802
--- /dev/null
+++ b/assets/icons/polkadot/2color/Overview.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M11.5 26.1934H2V10.6934L14 2.19336L26 10.6934V26.1934H17V17.6934H11.5V26.1934Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Paper Money.svg b/assets/icons/polkadot/2color/Paper Money.svg
new file mode 100644
index 00000000..d7d1d188
--- /dev/null
+++ b/assets/icons/polkadot/2color/Paper Money.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 6.80664H2V22.5308H26V6.80664Z"></path><path d="M13.9999 17.5652C15.5996 17.5652 16.8964 16.2684 16.8964 14.6687C16.8964 13.069 15.5996 11.7721 13.9999 11.7721C12.4002 11.7721 11.1033 13.069 11.1033 14.6687C11.1033 16.2684 12.4002 17.5652 13.9999 17.5652Z"></path><path d="M13.9999 17.5652C15.5996 17.5652 16.8964 16.2684 16.8964 14.6687C16.8964 13.069 15.5996 11.7721 13.9999 11.7721C12.4002 11.7721 11.1033 13.069 11.1033 14.6687C11.1033 16.2684 12.4002 17.5652 13.9999 17.5652Z"></path><path d="M13.9999 17.5652C15.5996 17.5652 16.8964 16.2684 16.8964 14.6687C16.8964 13.069 15.5996 11.7721 13.9999 11.7721C12.4002 11.7721 11.1033 13.069 11.1033 14.6687C11.1033 16.2684 12.4002 17.5652 13.9999 17.5652Z"></path><path d="M5.74127 7.04807C5.74127 8.98106 4.17427 10.5481 2.24127 10.5481"></path><path d="M22.2588 22.2894C22.2588 20.3564 23.8258 18.7894 25.7588 18.7894"></path><path d="M5.74133 22.2894C5.74133 20.3564 4.17433 18.7894 2.24133 18.7894"></path><path d="M22.2588 7.04803C22.2588 8.98103 23.8258 10.548 25.7588 10.548"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Parachains.svg b/assets/icons/polkadot/2color/Parachains.svg
new file mode 100644
index 00000000..4b2d1341
--- /dev/null
+++ b/assets/icons/polkadot/2color/Parachains.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="6" y="6" width="16" height="16"></rect><path d="M14 2L14 6"></path><path d="M10 2L10 6"></path><path d="M18 2L18 6"></path><path d="M14 22L14 26"></path><path d="M18 14.1738V13.8259C18 11.6168 16.2091 9.82593 14 9.82593C11.7909 9.82593 10 11.6168 10 13.8259V14.1738C10 16.3829 11.7909 18.1738 14 18.1738C16.2091 18.1738 18 16.3829 18 14.1738Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Payout.svg b/assets/icons/polkadot/2color/Payout.svg
new file mode 100644
index 00000000..d7676b04
--- /dev/null
+++ b/assets/icons/polkadot/2color/Payout.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7.8457 19.5327C8.01694 20.633 8.56691 21.6449 9.4082 22.3895C10.3604 23.2321 11.5002 23.5904 12.8786 23.5904H15.8779C16.4687 23.5919 17.0541 23.4799 17.6002 23.2608C18.1464 23.0416 18.6427 22.7197 19.0605 22.3134C19.4783 21.9072 19.8094 21.4247 20.0348 20.8936C20.2601 20.3625 20.3754 19.7934 20.3738 19.2189C20.3738 18.6449 20.2572 18.0765 20.0308 17.5464C19.8043 17.0163 19.4724 16.5349 19.0541 16.1298C18.6358 15.7247 18.1394 15.404 17.5933 15.1859C17.0472 14.9678 16.4622 14.8567 15.8719 14.859H12.8786C11.6909 14.856 10.5528 14.3954 9.71355 13.5783C8.87428 12.7612 8.40218 11.654 8.4006 10.4992V10.4468C8.40218 9.29195 8.87428 8.18477 9.71355 7.36764C10.5528 6.55051 11.6909 6.08999 12.8786 6.08691H15.4004C16.5 6.08691 18.0129 6.48212 18.9537 7.33758C19.4302 7.77089 19.8097 8.29077 20.0764 8.86328M14 6.10519V3M14 26.6956V23.5904" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Picture.svg b/assets/icons/polkadot/2color/Picture.svg
new file mode 100644
index 00000000..d67cd713
--- /dev/null
+++ b/assets/icons/polkadot/2color/Picture.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 4H2V24.7746H26V4Z" stroke-miterlimit="10"></path><path d="M2.2439 14.463C13.6494 9.65216 13.6494 23.5082 25.6491 17.5254"></path><circle cx="19.4855" cy="11.0887" r="1.41774"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Podcasts.svg b/assets/icons/polkadot/2color/Podcasts.svg
new file mode 100644
index 00000000..9a0cb9c7
--- /dev/null
+++ b/assets/icons/polkadot/2color/Podcasts.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2.91951 20.3041C2.73515 19.9815 2.56533 19.6515 2.41038 19.3151C1.64512 17.6535 1.24274 15.8354 1.24513 13.9832C1.25806 10.6088 2.60762 7.37703 4.99827 4.99554C7.38892 2.61405 10.6258 1.27692 14.0003 1.27695C15.673 1.27052 17.3305 1.59442 18.8777 2.23009C20.425 2.86576 21.8315 3.80068 23.0165 4.9812C24.2016 6.16173 25.1419 7.56463 25.7835 9.10942C26.4251 10.6542 26.7554 12.3105 26.7554 13.9832C26.7582 16.2105 26.1758 18.3883 25.081 20.3041" fill="none" data-nofill="true"></path><path d="M6.05907 17.3514C5.59587 16.2905 5.35077 15.1449 5.34088 13.9832C5.34087 12.8427 5.56614 11.7134 6.00378 10.6602C6.44142 9.60699 7.0828 8.6506 7.89109 7.84595C8.69937 7.0413 9.65864 6.40425 10.7138 5.97136C11.769 5.53847 12.8993 5.31827 14.0398 5.32342C16.3374 5.32342 18.5411 6.23548 20.1666 7.85923C21.7922 9.48297 22.7068 11.6856 22.7094 13.9832C22.6992 15.1441 22.4544 16.2888 21.992 17.3492" fill="none" data-nofill="true"></path><path d="M11.5739 17.7573L10.7591 16.7776C9.36829 15.1056 9.47968 12.6495 11.0161 11.1102C12.6611 9.46216 15.3315 9.46216 16.9765 11.1102C18.5129 12.6495 18.6243 15.1056 17.2335 16.7776L16.4188 17.7571C15.8984 18.3828 16.1965 19.337 16.9806 19.555L18.0844 19.862C21.1067 20.7025 23.198 23.4547 23.198 26.5917V26.678H4.802V26.5865C4.802 23.4522 6.89121 20.7022 9.91079 19.8618L11.0123 19.5553C11.7963 19.3371 12.0943 18.3829 11.5739 17.7573Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Privacy.svg b/assets/icons/polkadot/2color/Privacy.svg
new file mode 100644
index 00000000..3d2885ee
--- /dev/null
+++ b/assets/icons/polkadot/2color/Privacy.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M5 6.71352V15.057C5 18.4564 6.7269 21.6229 9.58467 23.4638L15.0743 27L20.7036 23.3721C23.5604 21.531 25.2865 18.3651 25.2865 14.9665V6.71352L15.1386 3L5 6.71352Z"></path><path d="M11.6684 14.882L14.695 18.2419L20.2419 11.5736"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Private Key.svg b/assets/icons/polkadot/2color/Private Key.svg
new file mode 100644
index 00000000..037a8123
--- /dev/null
+++ b/assets/icons/polkadot/2color/Private Key.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.4615 8.92308V2H5.00001V26H23.4615V7.98154"></path><path d="M12.7078 10.2655C12.4754 10.0111 12.2955 9.71338 12.1782 9.38936C12.0609 9.06533 12.0087 8.72134 12.0244 8.37703C12.0401 8.03272 12.1235 7.69484 12.2698 7.38267C12.4161 7.0705 12.6224 6.79016 12.877 6.55766C13.3961 6.09477 14.0775 5.85668 14.7717 5.89571C15.4659 5.93474 16.116 6.24769 16.5792 6.76581C16.8116 7.02023 16.9916 7.31795 17.1088 7.64198C17.2261 7.966 17.2784 8.30999 17.2626 8.6543C17.2469 8.99861 17.1635 9.33649 17.0172 9.64866C16.871 9.96083 16.6646 10.2412 16.41 10.4737C15.8909 10.9363 15.2095 11.1742 14.5154 11.1352C13.8213 11.0962 13.1712 10.7834 12.7078 10.2655V10.2655Z"></path><path d="M14.7961 11.2187L14.7747 22.1406"></path><path d="M14.2787 16.498L11.2861 16.4922L11.2751 20.1311L14.2669 20.1361"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Proof Of Stake.svg b/assets/icons/polkadot/2color/Proof Of Stake.svg
new file mode 100644
index 00000000..99bb2358
--- /dev/null
+++ b/assets/icons/polkadot/2color/Proof Of Stake.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.4059 21.6734C8.10701 21.6734 3 18.7439 3 14.5446V18.8713C3 23.0706 8.10701 26 14.4059 26C20.7049 26 25.8119 23.0706 25.8119 18.8713V14.5456C25.8119 18.7449 20.7049 21.6734 14.4059 21.6734Z"></path><path d="M14.4268 17.2079C20.7257 17.2079 25.8328 13.8032 25.8328 9.60396C25.8328 5.40467 20.7257 2 14.4268 2C8.12788 2 3.02087 5.40467 3.02087 9.60396C3.02087 13.8032 8.12788 17.2079 14.4268 17.2079Z"></path><path d="M14.4268 17.2079C8.45295 17.2079 3.5598 14.1445 3.06935 10.2465H3.02087V14.5447C3.02087 18.7439 8.12788 21.6734 14.4268 21.6734C20.7257 21.6734 25.8328 18.7439 25.8328 14.5447V10.2465H25.7843C25.2938 14.1445 20.4007 17.2079 14.4268 17.2079Z"></path><path d="M19.1556 8.5H9.6507V12.8204H19.1556V8.5Z"></path><path d="M11.8109 8.03779L11.8109 7.27783V7.27783C11.8109 6.26587 12.6312 5.44553 13.6432 5.44553H15.1631C16.175 5.44553 16.9954 6.26587 16.9954 7.27783V7.27783L16.9954 8.03779"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Proof Of Work.svg b/assets/icons/polkadot/2color/Proof Of Work.svg
new file mode 100644
index 00000000..b6a34655
--- /dev/null
+++ b/assets/icons/polkadot/2color/Proof Of Work.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.4059 21.6734C8.10701 21.6734 3 18.7439 3 14.5446V18.8713C3 23.0706 8.10701 26 14.4059 26C20.7049 26 25.8119 23.0706 25.8119 18.8713V14.5456C25.8119 18.7449 20.7049 21.6734 14.4059 21.6734Z"></path><path d="M14.4268 17.2079C20.7257 17.2079 25.8328 13.8032 25.8328 9.60396C25.8328 5.40467 20.7257 2 14.4268 2C8.12788 2 3.02087 5.40467 3.02087 9.60396C3.02087 13.8032 8.12788 17.2079 14.4268 17.2079Z"></path><path d="M14.4268 17.2079C8.45295 17.2079 3.5598 14.1445 3.06935 10.2465H3.02087V14.5447C3.02087 18.7439 8.12788 21.6734 14.4268 21.6734C20.7257 21.6734 25.8328 18.7439 25.8328 14.5447V10.2465H25.7843C25.2938 14.1445 20.4007 17.2079 14.4268 17.2079Z"></path><path d="M10.6013 12.099L16.3042 8.29703"></path><path d="M13.4526 6.42194L18.0414 9.24751L19.1556 8.58527L16.5364 7.00225L13.47 6.39603L13.4526 6.42194Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Proposal.svg b/assets/icons/polkadot/2color/Proposal.svg
new file mode 100644
index 00000000..19517bdb
--- /dev/null
+++ b/assets/icons/polkadot/2color/Proposal.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.4615 8.92308V2H5.00001V26H23.4615V7.98154"></path><path d="M19.7691 5.69211L8.6922 5.69211" stroke-miterlimit="10"></path><path d="M19.7692 9.38443H8.6922" stroke-miterlimit="10"></path><path d="M19.7693 17.879L16.2636 21.3846L14.8095 19.9305"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Proxy.svg b/assets/icons/polkadot/2color/Proxy.svg
new file mode 100644
index 00000000..2748ff32
--- /dev/null
+++ b/assets/icons/polkadot/2color/Proxy.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2 6.28348C2 8.64918 3.91778 10.567 6.28348 10.567H21.6409C24.0066 10.567 25.9244 8.64918 25.9244 6.28348C25.9244 3.91778 24.0066 2 21.6409 2H6.28348C3.91778 2 2 3.91778 2 6.28348Z"></path><path d="M13.9685 26H6.28348C3.91778 26 2 24.0822 2 21.7165C2 19.3508 3.91778 17.433 6.28348 17.433H13.9559H21.6409C24.0066 17.433 25.9244 19.3508 25.9244 21.7165C25.9244 24.0822 24.0066 26 21.6409 26H13.9685Z"></path><path d="M13.9872 17.4341L13.9872 10.5681" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/ProxyAccount.svg b/assets/icons/polkadot/2color/ProxyAccount.svg
new file mode 100644
index 00000000..3aaa697a
--- /dev/null
+++ b/assets/icons/polkadot/2color/ProxyAccount.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.2244 26.0188C24.7573 26.0188 26 24.7761 26 23.2431C26 21.7102 24.7573 20.4675 23.2244 20.4675C21.6914 20.4675 20.4487 21.7102 20.4487 23.2431C20.4487 24.7761 21.6914 26.0188 23.2244 26.0188Z"></path><path d="M4.77564 26.019C6.30859 26.019 7.55129 24.7763 7.55129 23.2433C7.55129 21.7104 6.30859 20.4677 4.77564 20.4677C3.2427 20.4677 2 21.7104 2 23.2433C2 24.7763 3.2427 26.019 4.77564 26.019Z"></path><path d="M4.77592 20.473L4.77592 17.2704L22.8386 17.2704L22.8386 20.473" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M15.5201 6.45341L15.9264 5.93216C16.6865 4.95702 16.597 3.56744 15.7181 2.69784C14.7675 1.75724 13.2368 1.75725 12.2861 2.69785C11.4072 3.56745 11.3177 4.95701 12.0778 5.93217L12.4839 6.45329C12.7613 6.80912 12.5908 7.33254 12.1571 7.45679L11.5759 7.62332C9.89503 8.10488 8.73661 9.64179 8.73661 11.3903V13.1463H19.2634V11.3873C19.2634 9.64034 18.1061 8.10469 16.4268 7.62322L15.8468 7.45693C15.4132 7.3326 15.2428 6.8092 15.5201 6.45341Z"></path><path d="M13.9998 13.3159L13.9999 17.0078"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Public Key.svg b/assets/icons/polkadot/2color/Public Key.svg
new file mode 100644
index 00000000..df357b3b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Public Key.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.00001 2H23.4615V26H5.00001V2Z"></path><path d="M12.736 12.4191L12.2852 11.8857C11.4629 10.9126 11.5284 9.47051 12.4355 8.576C13.3848 7.63988 14.91 7.63988 15.8593 8.576C16.7664 9.47051 16.8319 10.9126 16.0096 11.8857L15.5589 12.419C15.2578 12.7753 15.4281 13.3237 15.878 13.4468L16.5409 13.6283C18.2966 14.1088 19.514 15.7042 19.514 17.5245V19.2259H14.1474H8.78522V17.5214C8.78522 15.7028 10.0014 14.1087 11.7555 13.6282L12.417 13.447C12.8669 13.3237 13.0371 12.7754 12.736 12.4191Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/QR Code.svg b/assets/icons/polkadot/2color/QR Code.svg
new file mode 100644
index 00000000..2f4ea903
--- /dev/null
+++ b/assets/icons/polkadot/2color/QR Code.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.32 2.375H26V10.055" fill="none" data-nofill="true"></path><path d="M9.67999 26.375L1.99999 26.375L1.99999 17.735" fill="none" data-nofill="true"></path><path d="M26 18.695L26 26.375L18.32 26.375" fill="none" data-nofill="true"></path><path d="M2 10.055L2 2.37496L9.68 2.37496" fill="none" data-nofill="true"></path><path d="M12.0001 6.37503H6.00006V12.375H12.0001V6.37503Z"></path><path d="M22.0002 6.37506H16.0002V12.3751H22.0002V6.37506Z"></path><path d="M22.0002 16.375H16.0002V22.375H22.0002V16.375Z"></path><path d="M12.0001 16.375H6.00012V22.375H12.0001V16.375Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Randomness.svg b/assets/icons/polkadot/2color/Randomness.svg
new file mode 100644
index 00000000..116c491f
--- /dev/null
+++ b/assets/icons/polkadot/2color/Randomness.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M1.25914 7L4.48384 7C7.25724 7 9.83277 8.43641 11.2902 10.796L15.2481 17.204C16.7056 19.5636 19.2811 21 22.0545 21L24 21L25.5 21" fill="none" data-nofill="true"></path><path d="M22.3968 17L26.24 20.9998L22.3968 25" fill="none" data-nofill="true"></path><path d="M1.25914 21L4.48384 21C7.25724 21 9.83277 19.5636 11.2902 17.204L15.2481 10.796C16.7056 8.43642 19.2811 7 22.0545 7L24 7L25.5 7" fill="none" data-nofill="true"></path><path d="M22.3968 11L26.24 7.0002L22.3968 3" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Read Time.svg b/assets/icons/polkadot/2color/Read Time.svg
new file mode 100644
index 00000000..f20c9037
--- /dev/null
+++ b/assets/icons/polkadot/2color/Read Time.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M20.1537 15.8824V8.65379L14.5 3H4.00005V23.9998H12.5"></path><path d="M19.3281 8.6538H14.4999V4"></path><path d="M12.7499 19.1897H7.13043" stroke-miterlimit="10"></path><path d="M16 15.9621H7.13043" stroke-miterlimit="10"></path><path d="M18.5 27.25C21.6756 27.25 24.25 24.6756 24.25 21.5C24.25 18.3244 21.6756 15.75 18.5 15.75C15.3244 15.75 12.75 18.3244 12.75 21.5C12.75 24.6756 15.3244 27.25 18.5 27.25Z"></path><path d="M18.4153 19.1429V21.5143L17.4852 22.6429"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Recover Keys.svg b/assets/icons/polkadot/2color/Recover Keys.svg
new file mode 100644
index 00000000..7da5e30d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Recover Keys.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 2.37497C14.8573 2.37497 15.6936 2.46487 16.5 2.63576M14 26.375C14.8573 26.375 15.6936 26.2851 16.5 26.1142M20.8199 4.5C21.9947 5.31288 23.0174 6.32999 23.8366 7.5M25.765 12C25.9191 12.7677 26 13.5619 26 14.375C26 15.188 25.9191 15.9822 25.765 16.7499M20.8199 24.2499C21.9947 23.4371 23.0174 22.4199 23.8366 21.2499" fill="none"></path><path d="M14 2.37494C7.37258 2.37494 2 7.74752 2 14.3749C2 21.0024 7.37258 26.3749 14 26.3749" fill="none"></path><path d="M17 15.1404L14.0013 18.1404L11 15.1413" fill="none"></path><path d="M13.9999 17L13.9999 10" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Recovery.svg b/assets/icons/polkadot/2color/Recovery.svg
new file mode 100644
index 00000000..54f614e6
--- /dev/null
+++ b/assets/icons/polkadot/2color/Recovery.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.89111 14.2763C5.89111 9.15314 10.06 5 15.2025 5C20.345 5 24.5139 9.15314 24.5139 14.2763C24.5139 19.3995 20.345 23.5526 15.2025 23.5526C12.1324 23.5526 9.40941 22.0724 7.71323 19.7893" fill="none" data-nofill="true"></path><path d="M8.87428 12.4629L5.97656 15.4395L3 12.5417" fill="none" data-nofill="true"></path><path d="M15.8432 10.1934V16.1934L13 19.6388" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Reddit.svg b/assets/icons/polkadot/2color/Reddit.svg
new file mode 100644
index 00000000..4ff5c52a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Reddit.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.63636 21C9.63636 21 11.2727 22.0909 14 22.0909M24.9091 18.2727C24.9091 22.4902 20.0249 25.9091 14 25.9091C7.97508 25.9091 3.09091 22.4902 3.09091 18.2727C3.09091 17.7581 3.16363 17.2554 3.30227 16.7693L3.09091 16.6366C2.42848 16.139 2 15.3468 2 14.4545C2 12.9483 3.22104 11.7273 4.72727 11.7273C5.48668 11.7273 6.17359 12.0376 6.66808 12.5385L6.70692 12.5936C8.63936 11.3768 11.1962 10.6364 14 10.6364C16.7996 10.6364 19.3528 11.3745 21.2842 12.588C21.7817 12.0582 22.4886 11.7273 23.2727 11.7273C24.779 11.7273 26 12.9483 26 14.4545C26 15.4373 25.4801 16.2987 24.7004 16.7787C24.8373 17.2619 24.9091 17.7614 24.9091 18.2727Z"></path><path d="M14 22.0909C16.7273 22.0909 18.3636 21 18.3636 21"></path><path d="M22.1818 6.27273C23.0856 6.27273 23.8182 5.5401 23.8182 4.63636C23.8182 3.73263 23.0856 3 22.1818 3C21.2781 3 20.5455 3.73263 20.5455 4.63636C20.5455 5.5401 21.2781 6.27273 22.1818 6.27273Z"></path><path d="M14 10.6364L15.6364 3.54544L20.5455 4.63635" fill="none"></path><path d="M10.0002 16.3333L10.0222 16.3553" stroke-miterlimit="10"></path><path d="M18.0001 16.3333L18.0221 16.3553" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Referenda.svg b/assets/icons/polkadot/2color/Referenda.svg
new file mode 100644
index 00000000..c69fa522
--- /dev/null
+++ b/assets/icons/polkadot/2color/Referenda.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 25.5212V19.3907H26V25.5212" fill="none"></path><path d="M15.7884 2L4.45782 13.3306L10.5202 19.393H14.8053L23.9933 10.2049L15.7884 2Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Refresh _ Redo.svg b/assets/icons/polkadot/2color/Refresh _ Redo.svg
new file mode 100644
index 00000000..621d4e33
--- /dev/null
+++ b/assets/icons/polkadot/2color/Refresh _ Redo.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M27.0754 13.8553C27.3379 17.5252 25.916 21.274 22.9052 23.8638C17.8618 28.202 10.2698 27.6457 5.94795 22.6213C1.62613 17.5969 2.21108 10.007 7.25448 5.66887C12.2979 1.33071 19.8899 1.88701 24.2117 6.9114L24.5001 7.50003" fill="none" data-nofill="true"></path><path d="M19.7563 7.64948L25.1091 8.12419L25.5838 2.77136" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Registrars.svg b/assets/icons/polkadot/2color/Registrars.svg
new file mode 100644
index 00000000..7114cb76
--- /dev/null
+++ b/assets/icons/polkadot/2color/Registrars.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="4" y="2" width="20" height="24"></rect><path d="M11 20L13 22L17 18"></path><path d="M19.5184 8.23901L11.9806 8.23901M8.49249 8.23902L8.4817 8.23902"></path><path d="M19.5184 12.2612L11.9806 12.2612M8.49249 12.2612L8.4817 12.2612"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Regulators.svg b/assets/icons/polkadot/2color/Regulators.svg
new file mode 100644
index 00000000..ee3c7568
--- /dev/null
+++ b/assets/icons/polkadot/2color/Regulators.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M6.95403 17.4102L5.92378 14.4867C5.53027 13.3702 5.76224 12.1275 6.53047 11.2296C7.84622 9.69195 10.2185 9.69195 11.5343 11.2296C12.3034 12.1284 12.5345 13.3702 12.141 14.4867L11.1117 17.4093C10.8402 18.18 11.1426 19.0364 11.8367 19.4642L16.0713 22.0702V25.9868H2V22.0693L6.229 19.4642C6.92303 19.0364 7.22544 18.18 6.95403 17.4093V17.4102Z"></path><path d="M3 21.9131L15.3942 21.9131"></path><path d="M19.532 2H7.57003V10.4193L7.57191 10.4296C8.87545 9.78236 10.518 10.0415 11.5342 11.2295C12.3034 12.1284 12.5344 13.3702 12.1409 14.4866L11.1116 17.4093C10.8402 18.18 11.1426 19.0364 11.8366 19.4641L16.0712 22.0702L16.075 26H25.9718V8.46143L19.532 2Z"></path><path d="M25 8.46143H19.5321V3"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Relay Chain.svg b/assets/icons/polkadot/2color/Relay Chain.svg
new file mode 100644
index 00000000..696f33da
--- /dev/null
+++ b/assets/icons/polkadot/2color/Relay Chain.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M14 18C16.2091 18 18 16.2091 18 14C18 11.7909 16.2091 10 14 10C11.7909 10 10 11.7909 10 14C10 16.2091 11.7909 18 14 18Z"></path><path d="M14.0078 6.01711L13.9907 6" stroke-miterlimit="10"></path><path d="M14.0078 22L13.9907 21.9829" stroke-miterlimit="10"></path><path d="M21.9834 14.0086L22.0005 13.9915" stroke-miterlimit="10"></path><path d="M6 14.0086L6.01711 13.9915" stroke-miterlimit="10"></path><path d="M19.6507 8.36254V8.33691" stroke-miterlimit="10"></path><path d="M8.34877 19.6641V19.6385" stroke-miterlimit="10"></path><path d="M19.6379 19.6513H19.6636" stroke-miterlimit="10"></path><path d="M8.33597 8.34973H8.3616" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Remote Node.svg b/assets/icons/polkadot/2color/Remote Node.svg
new file mode 100644
index 00000000..3bbfd9b0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Remote Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.5521 9.40534L18.5262 5"></path><path d="M9.51626 5.0138L6.45081 9.39172"></path><path d="M20.4718 11.6062C20.4718 13.1383 21.7138 14.3803 23.2459 14.3803C24.778 14.3803 26.02 13.1383 26.02 11.6062C26.02 10.0741 24.778 8.83206 23.2459 8.83206C21.7138 8.83206 20.4718 10.0741 20.4718 11.6062Z"></path><path d="M2.00003 11.6062C2.00003 13.1383 3.24205 14.3803 4.77415 14.3803C6.30626 14.3803 7.54828 13.1383 7.54828 11.6062C7.54828 10.0741 6.30626 8.83206 4.77415 8.83206C3.24205 8.83206 2.00003 10.0741 2.00003 11.6062Z"></path><path d="M11.3726 20.6644C12.8292 22.1209 15.1907 22.1209 16.6473 20.6644C18.1038 19.2078 18.1038 16.8463 16.6473 15.3898C15.1907 13.9332 12.8292 13.9332 11.3726 15.3898C9.9161 16.8463 9.9161 19.2078 11.3726 20.6644Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Remove User.svg b/assets/icons/polkadot/2color/Remove User.svg
new file mode 100644
index 00000000..3b5b8814
--- /dev/null
+++ b/assets/icons/polkadot/2color/Remove User.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26.0029 5.00293L20.0029 5.00293"></path><path d="M14.9827 12.7571L15.892 11.6639C17.4439 9.79815 17.3196 7.05748 15.6052 5.33986C13.7696 3.50082 10.7898 3.50082 8.95416 5.33986C7.23972 7.05748 7.11542 9.79815 8.66735 11.6639L9.57647 12.7569C10.1572 13.4551 9.82447 14.5199 8.94954 14.7632L7.71783 15.1057C4.34533 16.0436 2.01171 19.1147 2.01171 22.6152V25.9917H22.5393V22.6094C22.5393 19.1119 20.208 16.0432 16.8386 15.1055L15.6094 14.7634C14.7346 14.52 14.402 13.4552 14.9827 12.7571Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Remove.svg b/assets/icons/polkadot/2color/Remove.svg
new file mode 100644
index 00000000..44ccf6b7
--- /dev/null
+++ b/assets/icons/polkadot/2color/Remove.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9883 2.375C21.6157 2.375 26.9883 7.74758 26.9883 14.375C26.9883 21.0024 21.6157 26.375 14.9883 26.375C8.36086 26.375 2.98828 21.0024 2.98828 14.375C2.98828 7.74758 8.36086 2.375 14.9883 2.375Z"></path><path d="M9.79437 14.3156L20.184 14.3718"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Report.svg b/assets/icons/polkadot/2color/Report.svg
new file mode 100644
index 00000000..f763d126
--- /dev/null
+++ b/assets/icons/polkadot/2color/Report.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M20.4999 5.99969H23.9994V26H7.99969V22.0003"></path><path d="M19.9997 2V21.9994H4V2H19.9997Z"></path><path d="M4.48828 16.6885L8.59276 12.5838L11.6647 15.1438L16.2727 10.5358"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Reputation Systems.svg b/assets/icons/polkadot/2color/Reputation Systems.svg
new file mode 100644
index 00000000..890d2f0d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Reputation Systems.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.1408 12.0528L10.4136 11.6793L8.2547 8.10168L6.10812 11.6793L2 12.5922L4.78809 15.7134L4.40566 19.8586L8.26704 18.2054L10.2039 19.0258" stroke-miterlimit="10"></path><path d="M16.0756 12.0152L17.5866 11.6794L19.7332 8.10181L21.8921 11.6794L26.0002 12.5677L23.2245 15.7012L23.6193 19.8463L19.7455 18.2056L17.8149 19.0321" stroke-miterlimit="10"></path><path d="M20.2609 13.611L17.4851 16.7445L17.8799 20.8897L14.0062 19.2489L10.1448 20.902L10.5272 16.7569L7.73914 13.6357L11.8473 12.7228L13.9938 9.14514L16.1528 12.7228L20.2609 13.611Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Research.svg b/assets/icons/polkadot/2color/Research.svg
new file mode 100644
index 00000000..05bd6a3b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Research.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.772 2L24.772 26L4 25.9999L4 2L24.772 2Z"></path><path d="M20.8444 13.2181L20.8444 1.99995L14.621 1.99995L14.621 13.2236L17.7317 11.0341L20.8444 13.2181Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Reserve Back Assets.svg b/assets/icons/polkadot/2color/Reserve Back Assets.svg
new file mode 100644
index 00000000..c4fccb29
--- /dev/null
+++ b/assets/icons/polkadot/2color/Reserve Back Assets.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.0001 15.7966C14.9468 15.7966 15.7143 15.0245 15.7143 14.072C15.7143 13.1195 14.9468 12.3474 14.0001 12.3474C13.0533 12.3474 12.2858 13.1195 12.2858 14.072C12.2858 15.0245 13.0533 15.7966 14.0001 15.7966Z"></path><path d="M1.99983 26.0001L25.9993 26.0001L25.9993 19.9642L25.9995 11.4133L19.9996 11.4133L19.9996 19.9642L18.2497 19.9642L1.99983 19.9642L1.99983 26.0001Z"></path><path d="M25.9999 1.99988L2.00049 1.99988L2.00049 8.03579L2.00024 16.5867L8.00012 16.5867L8.00012 8.03579L9.75009 8.03579L25.9999 8.03579L25.9999 1.99988Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Restore From BackUp.svg b/assets/icons/polkadot/2color/Restore From BackUp.svg
new file mode 100644
index 00000000..6ee41e83
--- /dev/null
+++ b/assets/icons/polkadot/2color/Restore From BackUp.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.87428 12.4629L5.97656 15.4395L3 12.5417" fill="none" data-nofill="true"></path><path d="M5.89111 14.2763C5.89111 9.15314 10.06 5 15.2025 5C20.345 5 24.5139 9.15314 24.5139 14.2763C24.5139 19.3995 20.345 23.5526 15.2025 23.5526C12.1324 23.5526 9.40941 22.0724 7.71323 19.7893" fill="none" data-nofill="true"></path><path d="M12.2654 14.6313L15.1631 11.6548L18.1396 14.5525" fill="none" data-nofill="true"></path><path d="M15.1631 12.5L15.1631 23.4966" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Retail And Ecommerce.svg b/assets/icons/polkadot/2color/Retail And Ecommerce.svg
new file mode 100644
index 00000000..5ea1fffb
--- /dev/null
+++ b/assets/icons/polkadot/2color/Retail And Ecommerce.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.4217 16.7805L20.8978 21.9579C20.8978 21.9579 7.0277 21.9579 5.27405 21.9579" fill="none"></path><path d="M3.98242 5.95508H22.6752L19.4216 16.7806H7.84633L3.98242 5.95508Z"></path><path d="M22.5 6L23.7088 2.5625H26.2811"></path><circle cx="8.12782" cy="25.1373" r="1.71486" transform="rotate(-45 8.12782 25.1373)"></circle><circle cx="18.4173" cy="25.1373" r="1.71486" transform="rotate(-45 18.4173 25.1373)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Robust System.svg b/assets/icons/polkadot/2color/Robust System.svg
new file mode 100644
index 00000000..fac7f659
--- /dev/null
+++ b/assets/icons/polkadot/2color/Robust System.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M15.1328 2.56837L6.73413 10.967L12.9571 16.8913L14.4041 15.4607L21.2146 8.65016L15.1328 2.56837Z"></path><path d="M4.9223 21.1604V25.7046H22.712V21.1604H4.9223Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Rust.svg b/assets/icons/polkadot/2color/Rust.svg
new file mode 100644
index 00000000..6dd69c8e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Rust.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.5701 23.6137L17.078 26.4003L22.8004 23.1061L21.7057 19.5632L22.0074 18.6669L26.1742 17.8088V10.7457L22.5616 9.91973L21.7356 8.48664L22.8801 4.94373L17.1676 1.64961L14.6199 4.38642H12.9977L10.4998 1.59985L4.77736 4.89397L5.88203 8.49659L5.09582 9.86997L1.39368 10.6462V17.2544L5.06597 18.0903L5.86213 19.4637L4.68779 23.0564L10.4102 26.3605L12.948 23.6137H14.5701Z" stroke-miterlimit="10"></path><path d="M10 18.5357V14.1329M10 14.1329V9.46436H16.11C19.3918 9.46436 19.5186 14.1329 16.11 14.1329C15.1266 14.1329 15.1527 14.1329 14.3196 14.1329C12.9594 14.1329 10.8752 14.1329 10 14.1329ZM18.5812 18.5188L14.6763 14.5"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Save.svg b/assets/icons/polkadot/2color/Save.svg
new file mode 100644
index 00000000..5e0bffd9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Save.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 10.3145L26 26.9434L2 26.9434L2 2.94336L18.3436 2.94336L26 10.3145Z" stroke-miterlimit="10"></path><path d="M10.5714 3.5V11.5148H2.5" stroke-miterlimit="10"></path><path d="M16.4643 18.0862C16.4643 19.605 15.2331 20.8362 13.7143 20.8362C12.1955 20.8362 10.9643 19.605 10.9643 18.0862C10.9643 16.5675 12.1955 15.3362 13.7143 15.3362C15.2331 15.3362 16.4643 16.5675 16.4643 18.0862Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Scalability.svg b/assets/icons/polkadot/2color/Scalability.svg
new file mode 100644
index 00000000..5883737e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Scalability.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M20.8572 2.01674L25.9634 2L25.9802 7.09755" fill="none" data-nofill="true"></path><path d="M7.12347 2.01674L2.01726 2L2.00049 7.09755" fill="none" data-nofill="true"></path><path d="M2.01674 20.877L2 25.9832L7.09755 26" fill="none" data-nofill="true"></path><path d="M25.964 20.877L25.9807 25.9832L20.8832 26" fill="none" data-nofill="true"></path><path d="M25.4783 2.67474L18.0904 9.96275" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M2.5026 2.67474L9.89059 9.96275" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M2.67484 25.498L9.96285 18.11" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M25.3061 25.498L18.0181 18.11" stroke-miterlimit="10" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Scale.svg b/assets/icons/polkadot/2color/Scale.svg
new file mode 100644
index 00000000..c12d9e2c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Scale.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.9909 22.0069C18.4194 22.0069 22.0094 18.4198 22.0094 13.9949C22.0094 9.56999 18.4194 5.98291 13.9909 5.98291C9.56233 5.98291 5.97229 9.56999 5.97229 13.9949C5.97229 18.4198 9.56233 22.0069 13.9909 22.0069Z" stroke-miterlimit="10"></path><path d="M14.0674 16.6526V10.9971" fill="none" data-nofill="true"></path><path d="M16.8975 13.8248L11.2373 13.8248" fill="none" data-nofill="true"></path><path d="M20.8724 2.01674L25.9828 2L25.9996 7.09755" fill="none" data-nofill="true"></path><path d="M25.4971 2.67468L19.7224 8.36656" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M7.12708 2.01674L2.01666 2L1.99988 7.09755" fill="none" data-nofill="true"></path><path d="M2.50257 2.67468L8.29218 8.36678" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M2.01675 20.877L2 25.9832L7.10175 25.9999" fill="none" data-nofill="true"></path><path d="M2.67505 25.498L8.39066 19.7087" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M25.9832 20.877L25.9999 25.9832L20.8982 25.9999" fill="none" data-nofill="true"></path><path d="M25.3246 25.498L19.6092 19.709" stroke-miterlimit="10" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Scaling.svg b/assets/icons/polkadot/2color/Scaling.svg
new file mode 100644
index 00000000..c07d7eff
--- /dev/null
+++ b/assets/icons/polkadot/2color/Scaling.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M16.4383 3.08008L25.4854 3.08009L25.4854 12.1331" fill="none" data-nofill="true"></path><path d="M16.4383 3.08008L25.4854 3.08009L25.4854 12.1331" fill="none" data-nofill="true"></path><path d="M25.3488 16.8559L25.3488 25.9029L16.2958 25.9029" fill="none" data-nofill="true"></path><path d="M2.52375 12.1301L2.52376 3.08306L11.5768 3.08306" fill="none" data-nofill="true"></path><path d="M11.5734 25.9059L2.52636 25.9059L2.52636 16.8528" fill="none" data-nofill="true"></path><path d="M24.8693 3.63065L3.12909 25.3708" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Scam Alert.svg b/assets/icons/polkadot/2color/Scam Alert.svg
new file mode 100644
index 00000000..f64ac333
--- /dev/null
+++ b/assets/icons/polkadot/2color/Scam Alert.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.9898 3.12793L2.19775 24.872H25.7818L13.9898 3.12793Z" stroke-miterlimit="10"></path><path d="M11.2275 17.3172C11.2275 18.8504 12.4704 20.0933 14.0036 20.0933C15.5368 20.0933 16.7796 18.8504 16.7796 17.3172C16.7796 16.1286 16.0326 15.1144 14.9824 14.7186C14.4656 14.5239 14.0036 14.0934 14.0036 13.5412V4.3623"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Search.svg b/assets/icons/polkadot/2color/Search.svg
new file mode 100644
index 00000000..f365e63b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Search.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 22 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.8551 19.6652C15.7493 19.6652 19.716 15.6976 19.716 10.8043C19.716 5.91098 15.7493 1.94336 10.8551 1.94336C5.9608 1.94336 1.99414 5.91098 1.99414 10.8043C1.99414 15.6976 5.96176 19.6652 10.8551 19.6652Z" stroke-miterlimit="10"></path><path d="M16.7885 17.3718C15.6288 18.4208 14.1964 19.1721 12.6032 19.491L16.3743 26.0247L20.4296 23.683L16.7885 17.3718Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Second A Proposal.svg b/assets/icons/polkadot/2color/Second A Proposal.svg
new file mode 100644
index 00000000..0a09cd61
--- /dev/null
+++ b/assets/icons/polkadot/2color/Second A Proposal.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.4615 8.92308V2H4.99999V26H23.4615V7.98154"></path><path d="M19.7691 5.69208L8.69221 5.69208" stroke-miterlimit="10"></path><path d="M19.7692 9.38446H8.69221" stroke-miterlimit="10"></path><path d="M20.2628 18.0844L16.963 21.3842L15.5942 20.0155"></path><path d="M13.0077 18.0844L9.70782 21.3842L8.3391 20.0155"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Secret Part Of The Derivation Path.svg b/assets/icons/polkadot/2color/Secret Part Of The Derivation Path.svg
new file mode 100644
index 00000000..261dd1f8
--- /dev/null
+++ b/assets/icons/polkadot/2color/Secret Part Of The Derivation Path.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26L14.0001 22.8711M14.0001 5.12893L14.0001 2"></path><path d="M1.99999 14L5.12892 14.0001M22.8711 14.0001L26 14.0001"></path><path d="M14.0043 22.7311C18.7503 22.7311 22.5976 18.8837 22.5976 14.1378C22.5976 9.39189 18.7503 5.54456 14.0043 5.54456C9.25842 5.54456 5.41109 9.39189 5.41109 14.1378C5.41109 18.8837 9.25842 22.7311 14.0043 22.7311Z"></path><path d="M11.9876 13.1907L11.9876 11.6747C11.9876 11.1408 12.1997 10.6288 12.5772 10.2513C12.9547 9.87382 13.4667 9.66174 14.0005 9.66174C14.5331 9.6638 15.0431 9.87679 15.4189 10.2541C15.7947 10.6313 16.0057 11.1422 16.0057 11.6747V13.1907"></path><path d="M17.2103 13.3083H10.7906V17.6772H17.2103V13.3083Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Secure Device.svg b/assets/icons/polkadot/2color/Secure Device.svg
new file mode 100644
index 00000000..41f069fc
--- /dev/null
+++ b/assets/icons/polkadot/2color/Secure Device.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.5109 2H6V26H22.5109V2Z"></path><path d="M13.3055 22.7122H15.2053"></path><path d="M12.011 9.94757L12.011 8.25744C12.011 7.66224 12.2475 7.09142 12.6684 6.67055C13.0892 6.24969 13.6601 6.01324 14.2552 6.01324C14.8489 6.01554 15.4175 6.25299 15.8365 6.67361C16.2555 7.09423 16.4908 7.66374 16.4908 8.25744V9.94757"></path><path d="M16.834 10.0771H11.6768C11.1245 10.0771 10.6768 10.5248 10.6768 11.0771V13.9479C10.6768 14.5002 11.1245 14.9479 11.6768 14.9479H16.834C17.3863 14.9479 17.834 14.5002 17.834 13.9479V11.0771C17.834 10.5248 17.3863 10.0771 16.834 10.0771Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Security Check.svg b/assets/icons/polkadot/2color/Security Check.svg
new file mode 100644
index 00000000..19671682
--- /dev/null
+++ b/assets/icons/polkadot/2color/Security Check.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3.35229 5.23344V14.2632C3.35229 17.6625 5.07919 20.8291 7.93697 22.67L13.9277 26.529L20.065 22.5737C22.9217 20.7326 24.6478 17.5667 24.6478 14.1681V5.23344L13.9952 1.33521L3.35229 5.23344Z"></path><path d="M11.2649 12.4983V11.1572C11.2649 10.4318 11.553 9.73611 12.066 9.22319C12.5789 8.71027 13.2746 8.42212 13.9999 8.42212C14.7235 8.42491 15.4164 8.7143 15.9271 9.22691C16.4377 9.73953 16.7244 10.4336 16.7244 11.1572V12.4983"></path><path d="M18.3612 12.4983H9.63867V18H18.3612V12.4983Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Seed Phrase.svg b/assets/icons/polkadot/2color/Seed Phrase.svg
new file mode 100644
index 00000000..4c677207
--- /dev/null
+++ b/assets/icons/polkadot/2color/Seed Phrase.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 14.2622L7.99997 14.2622" stroke-miterlimit="10"></path><path d="M12 14.2622L21 14.2622" stroke-miterlimit="10"></path><path d="M25 14.2622L26 14.2622" stroke-miterlimit="10"></path><path d="M2 18.5244L6 18.5244" stroke-miterlimit="10"></path><path d="M10 18.5244L12 18.5244" stroke-miterlimit="10"></path><path d="M16 18.5244L26 18.5244" stroke-miterlimit="10"></path><path d="M2 10L3.68974 10" stroke-miterlimit="10"></path><path d="M21.6897 10L25.6897 10" stroke-miterlimit="10"></path><path d="M7.68974 10L17.6897 10" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Select List Item.svg b/assets/icons/polkadot/2color/Select List Item.svg
new file mode 100644
index 00000000..03812eab
--- /dev/null
+++ b/assets/icons/polkadot/2color/Select List Item.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9824 25.9434C20.6098 25.9434 25.9824 20.5708 25.9824 13.9434C25.9824 7.31594 20.6098 1.94336 13.9824 1.94336C7.355 1.94336 1.98242 7.31594 1.98242 13.9434C1.98242 20.5708 7.355 25.9434 13.9824 25.9434Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Session.svg b/assets/icons/polkadot/2color/Session.svg
new file mode 100644
index 00000000..fb7b6d50
--- /dev/null
+++ b/assets/icons/polkadot/2color/Session.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.311 25.1507C19.4533 25.1507 23.6219 20.982 23.6219 15.8397C23.6219 10.6974 19.4533 6.52875 14.311 6.52875C9.16866 6.52875 5 10.6974 5 15.8397C5 20.982 9.16866 25.1507 14.311 25.1507Z"></path><path d="M14.3101 10.9698V16.6254L12.0919 19.3169"></path><path d="M14.2964 6.52924L14.2964 2.00003"></path><path d="M17.3588 2.01202L11.2617 2.01202"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Settings.svg b/assets/icons/polkadot/2color/Settings.svg
new file mode 100644
index 00000000..1d36a691
--- /dev/null
+++ b/assets/icons/polkadot/2color/Settings.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.7512 23.3034L17.1782 26L22.7159 22.8122L21.6565 19.3836L22.0799 18.1124L25.9807 17.4421V10.8507L22.4848 10.0514L21.6854 8.66453L22.7929 5.23596L17.2648 2.04815L14.7994 4.69663H13.2295L10.8122 2L5.27448 5.1878L6.3435 8.67416L5.58266 10.0032L2 10.7544V17.1493L5.55377 17.9583L6.32424 19.2873L5.1878 22.764L10.7255 25.9615L13.1814 23.3034H14.7512Z" stroke-miterlimit="10"></path><path d="M14 18C16.2091 18 18 16.2091 18 14C18 11.7909 16.2091 10 14 10C11.7909 10 10 11.7909 10 14C10 16.2091 11.7909 18 14 18Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Sharding.svg b/assets/icons/polkadot/2color/Sharding.svg
new file mode 100644
index 00000000..741b19f6
--- /dev/null
+++ b/assets/icons/polkadot/2color/Sharding.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.955 6.49153C15.8154 6.49153 17.3236 5.48604 17.3236 4.24576C17.3236 3.00548 15.8154 2 13.955 2C12.0945 2 10.5863 3.00548 10.5863 4.24576C10.5863 5.48604 12.0945 6.49153 13.955 6.49153V6.49153Z"></path><path d="M7.10977 17.7639L10.2502 12.3701"></path><path d="M20.8012 17.7639L17.6607 12.3701"></path><path d="M5.82499 26C7.93726 26 9.64998 24.8582 9.64998 23.4503C9.64998 22.0425 7.93726 20.9006 5.82499 20.9006C3.71273 20.9006 2 22.0425 2 23.4503C2 24.8582 3.71273 26 5.82499 26Z"></path><path d="M22.2015 26C24.3137 26 26.0264 24.8582 26.0264 23.4503C26.0264 22.0425 24.3137 20.9006 22.2015 20.9006C20.0892 20.9006 18.3765 22.0425 18.3765 23.4503C18.3765 24.8582 20.0892 26 22.2015 26Z"></path><path d="M17.3236 4.24585C17.3236 5.48613 15.8154 6.49161 13.955 6.49161C12.0946 6.49161 10.5863 5.48613 10.5863 4.24585V7.65047C10.5863 8.89075 12.0946 9.75611 13.955 9.75611C15.8154 9.75611 17.3236 8.89075 17.3236 7.65047V4.24585Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Share.svg b/assets/icons/polkadot/2color/Share.svg
new file mode 100644
index 00000000..7d5c8b35
--- /dev/null
+++ b/assets/icons/polkadot/2color/Share.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 23 27" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M16.177 5.8259L8.4267 11.2527"></path><path d="M8.38375 15.455L16.3078 21.0035"></path><path d="M18.4763 7.05535C20.0072 7.05535 21.2482 5.81437 21.2482 4.28354C21.2482 2.7527 20.0072 1.51172 18.4763 1.51172C16.9455 1.51172 15.7045 2.7527 15.7045 4.28354C15.7045 5.81437 16.9455 7.05535 18.4763 7.05535Z"></path><path d="M18.4763 25.5117C20.0072 25.5117 21.2482 24.2707 21.2482 22.7399C21.2482 21.2091 20.0072 19.9681 18.4763 19.9681C16.9455 19.9681 15.7045 21.2091 15.7045 22.7399C15.7045 24.2707 16.9455 25.5117 18.4763 25.5117Z"></path><path d="M7.90533 15.9753C9.36066 14.52 9.36066 12.1604 7.90533 10.7051C6.45 9.24977 4.09044 9.24977 2.63511 10.7051C1.17978 12.1604 1.17978 14.52 2.63511 15.9753C4.09044 17.4307 6.45 17.4307 7.90533 15.9753Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Shared Security.svg b/assets/icons/polkadot/2color/Shared Security.svg
new file mode 100644
index 00000000..3959757b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Shared Security.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.9349 25.9999C15.4059 25.9999 16.5981 24.8077 16.5981 23.3367C16.5981 21.8657 15.4059 20.6735 13.9349 20.6735C12.4639 20.6735 11.2716 21.8657 11.2716 23.3367C11.2716 24.8077 12.4639 25.9999 13.9349 25.9999V25.9999Z"></path><path d="M23.8451 8.52062C25.3161 8.52062 26.5083 7.32839 26.5083 5.85739C26.5083 4.38639 25.3161 3.19415 23.8451 3.19415C22.3741 3.19415 21.1818 4.38639 21.1818 5.85739C21.1818 7.32839 22.3741 8.52062 23.8451 8.52062Z"></path><path d="M4.66323 8.52068C6.13423 8.52068 7.32647 7.32845 7.32647 5.85745C7.32647 4.38645 6.13423 3.19421 4.66323 3.19421C3.19223 3.19421 2 4.38645 2 5.85745C2 7.32845 3.19223 8.52068 4.66323 8.52068Z"></path><path d="M23.8451 8.52063C22.3741 8.52063 21.1818 7.32839 21.1818 5.8574C21.1818 5.43394 21.2899 5.03942 21.4654 4.68445L14.1288 2L7.00237 4.61018C7.20204 4.98348 7.32647 5.40404 7.32647 5.8574C7.32647 7.32839 6.13424 8.52063 4.66324 8.52063C4.58028 8.52063 4.50215 8.50327 4.42113 8.49651V14.0313C4.42113 16.983 5.9201 19.7311 8.40103 21.3294L11.2871 23.1882C11.3652 21.7876 12.515 20.6735 13.9349 20.6735C15.4059 20.6735 16.5981 21.8657 16.5981 23.3367V23.3483L19.8661 21.2416C22.3461 19.6433 23.8451 16.8952 23.8451 13.9445V8.52063Z"></path><path d="M11.6575 11.9555V10.2395C11.6575 9.58362 11.9179 8.95374 12.3828 8.48978C12.8468 8.02581 13.4767 7.7644 14.1326 7.7644C14.7876 7.7673 15.4145 8.0287 15.8766 8.49267C16.3386 8.95664 16.5981 9.58459 16.5981 10.2395V11.9555"></path><path d="M18.0797 12.2469H10.1865V17.2251H18.0797V12.2469Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Sign A Transaction.svg b/assets/icons/polkadot/2color/Sign A Transaction.svg
new file mode 100644
index 00000000..5bb07c1a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Sign A Transaction.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.31907 24.7504H1.28955" stroke-miterlimit="10"></path><path d="M22.66 11.3802L26.0365 14.7567L17.6232 23.17L13.1 24.3123L14.2467 19.7935L22.66 11.3802Z"></path><path d="M12.9304 2.00269L16.2097 5.28203L12.9304 8.56689" fill="none" data-nofill="true"></path><path d="M15.3611 5.28467L1.95577 5.28468"></path><path d="M5.23512 15.1311L1.95577 11.8462L5.23512 8.56689" fill="none" data-nofill="true"></path><path d="M2.76658 11.8463L16.2054 11.8463"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Sign Specs.svg b/assets/icons/polkadot/2color/Sign Specs.svg
new file mode 100644
index 00000000..7f2a32a2
--- /dev/null
+++ b/assets/icons/polkadot/2color/Sign Specs.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26.9941 3.93292H2.99414V24.152H26.9941V3.93292Z"></path><path d="M19.4461 11.9332L14.724 16.6553L9.99401 11.9332"></path><path d="M14.7202 15.5L14.7202 4.5"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Sign.svg b/assets/icons/polkadot/2color/Sign.svg
new file mode 100644
index 00000000..fe6fe37b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Sign.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.74995 18.9047H2" stroke-miterlimit="10"></path><path d="M22.741 6L26 9.25894L17.5632 17.6957L13.091 18.9048L14.3043 14.4367L22.741 6Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Signal.svg b/assets/icons/polkadot/2color/Signal.svg
new file mode 100644
index 00000000..f3759fc0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Signal.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11.2222 13.5555L11.2222 26"></path><path d="M5 19.7778L5 26"></path><path d="M17.4444 8.22223L17.4444 26"></path><path d="M23.6667 2L23.6667 26"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Signature.svg b/assets/icons/polkadot/2color/Signature.svg
new file mode 100644
index 00000000..fbaed11e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Signature.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.7452 7L26 10.2548L17.5739 18.6809L13.1074 19.8885L14.3191 15.4261L22.7452 7Z"></path><path d="M9.77046 19.8888H9.02152C8.33752 19.8888 7.7297 19.5399 7.50598 19.0191L7.33759 18.6263C7.02251 17.9154 6.46324 17.5852 5.88964 17.5817C5.31605 17.5852 4.74795 17.9154 4.43288 18.6263L4.26448 19.0191C4.04076 19.5399 3.43294 19.8888 2.74895 19.8888H2" stroke-miterlimit="10" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Signifier Tab.svg b/assets/icons/polkadot/2color/Signifier Tab.svg
new file mode 100644
index 00000000..a8596b0b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Signifier Tab.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2.98828 14.5117H26.9883"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Smart Contract.svg b/assets/icons/polkadot/2color/Smart Contract.svg
new file mode 100644
index 00000000..842e4416
--- /dev/null
+++ b/assets/icons/polkadot/2color/Smart Contract.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.4846 4.61499H26.7098V9.94946V23.1078H12.4846V4.61499Z"></path><path d="M22.9999 8.68042H16.3901" stroke-miterlimit="10"></path><path d="M20.2458 12.6602H16.3901" stroke-miterlimit="10"></path><path d="M22.9999 19.3152H16.3901" stroke-miterlimit="10"></path><path d="M4.45978 14.1587L12.4465 14.1587" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M4.45977 5.18872L7.63774 5.18872L7.63774 23L4.45972 23" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M1.26074 5.18872L1.24995 5.18872"></path><path d="M1.26074 14.1587L1.24995 14.1587"></path><path d="M1.26074 23L1.24995 23"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Social Impact & Humanitarian.svg b/assets/icons/polkadot/2color/Social Impact & Humanitarian.svg
new file mode 100644
index 00000000..9865c88a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Social Impact & Humanitarian.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M16.782 17.1763L17.4326 16.4065C18.6193 15.0022 18.5248 12.9209 17.2157 11.6299C15.8456 10.2789 13.6445 10.2789 12.2744 11.6299C10.9653 12.9209 10.8707 15.0022 12.0575 16.4065L12.7079 17.1762C13.1425 17.6904 12.8968 18.4818 12.2474 18.6596L11.2907 18.9214C8.75691 19.615 6.99997 21.9175 6.99997 24.5445V27H22.4838V24.5401C22.4838 21.9154 20.7286 19.6147 18.1971 18.9213L17.2424 18.6598C16.5931 18.4819 16.3475 17.6905 16.782 17.1763Z"></path><path d="M18.9113 5.70968C18.9113 5.7294 18.8629 6.08376 18.015 6.50767C17.242 6.8942 16.0865 7.16935 14.742 7.16935C13.3974 7.16935 12.242 6.8942 11.4689 6.50767C10.6211 6.08376 10.5726 5.7294 10.5726 5.70968C10.5726 5.68995 10.6211 5.33559 11.4689 4.91168C12.242 4.52515 13.3974 4.25 14.742 4.25C16.0865 4.25 17.242 4.52515 18.015 4.91168C18.8629 5.33559 18.9113 5.68995 18.9113 5.70968Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Social Networking.svg b/assets/icons/polkadot/2color/Social Networking.svg
new file mode 100644
index 00000000..28e0a30a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Social Networking.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M16.5769 6.74188L16.9633 6.24627C17.686 5.31907 17.6009 3.99783 16.7652 3.17099C15.8613 2.27664 14.4059 2.27666 13.5019 3.171C12.6663 3.99784 12.5812 5.31907 13.3038 6.24628L13.6901 6.74177C13.9538 7.0801 13.7917 7.57778 13.3793 7.69593L12.8267 7.85426C11.2285 8.31215 10.127 9.77348 10.127 11.436V13.1056H20.1361V11.4332C20.1361 9.77209 19.0358 8.31197 17.4391 7.85417L16.8876 7.69606C16.4753 7.57784 16.3132 7.08018 16.5769 6.74188Z"></path><path d="M23.2969 20.1929L23.6832 19.6973C24.406 18.7701 24.3209 17.4489 23.4852 16.622C22.5813 15.7277 21.1258 15.7277 20.2219 16.6221C19.3862 17.4489 19.3011 18.7701 20.0238 19.6973L20.41 20.1928C20.6737 20.5311 20.5116 21.0288 20.0993 21.147L19.5466 21.3053C17.9484 21.7632 16.847 23.2245 16.847 24.887V26.5567H26.8561V24.8842C26.8561 23.2231 25.7558 21.763 24.159 21.3052L23.6075 21.1471C23.1952 21.0289 23.0332 20.5312 23.2969 20.1929Z"></path><path d="M9.84585 20.1929L10.2322 19.6973C10.9549 18.7701 10.8698 17.4489 10.0341 16.622C9.13021 15.7277 7.67479 15.7277 6.77087 16.6221C5.93519 17.4489 5.85007 18.7701 6.57277 19.6973L6.95898 20.1928C7.22268 20.5311 7.06059 21.0288 6.64823 21.147L6.09557 21.3053C4.49737 21.7632 3.39592 23.2245 3.39592 24.887V26.5567H13.405V24.8842C13.405 23.2231 12.3047 21.763 10.708 21.3052L10.1565 21.1471C9.74418 21.0289 9.58216 20.5312 9.84585 20.1929Z"></path><path d="M14.93 17.2586L19.4675 20.3067M10.5389 20.2033L14.9224 17.2586V13.1639" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Software Development.svg b/assets/icons/polkadot/2color/Software Development.svg
new file mode 100644
index 00000000..337682d3
--- /dev/null
+++ b/assets/icons/polkadot/2color/Software Development.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M1.99997 27L26.2441 27L26.2441 3L1.99997 3L1.99997 27Z"></path><path d="M26.2371 9.57935H2.00026"></path><path d="M9.32502 6.46778L9.30768 6.45044" stroke-miterlimit="10"></path><path d="M5.50117 6.46778L5.48383 6.45044" stroke-miterlimit="10"></path><path d="M10.2498 20.2866L7.39581 17.9107L10.2498 15.53"></path><path d="M18.2633 15.5205L21.1268 17.906L18.2633 20.2866"></path><path d="M15.8593 13.1421L12.6537 22.674"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Specialised.svg b/assets/icons/polkadot/2color/Specialised.svg
new file mode 100644
index 00000000..3d48e9a9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Specialised.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.8717 26.7691C20.9049 26.7691 26.6064 21.0676 26.6064 14.0344C26.6064 7.0013 20.9049 1.2998 13.8717 1.2998C6.83858 1.2998 1.13708 7.0013 1.13708 14.0344C1.13708 21.0676 6.83858 26.7691 13.8717 26.7691Z"></path><path d="M20.0753 12.2127L17.325 15.3174L17.7161 19.4246L13.8779 17.7988L10.0519 19.4368L10.4309 15.3297L7.66833 12.2371L11.7388 11.3326L13.8657 7.78772L16.0048 11.3326L20.0753 12.2127Z" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Stablecoin.svg b/assets/icons/polkadot/2color/Stablecoin.svg
new file mode 100644
index 00000000..4885480a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Stablecoin.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="6" cy="9" r="3"></circle><circle cx="22" cy="9" r="3"></circle><path d="M14.5 15H14.5276L19.2631 23.25H9.73682L14.5 15Z"></path><path d="M24 15L4 15"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Stake.svg b/assets/icons/polkadot/2color/Stake.svg
new file mode 100644
index 00000000..bceaf135
--- /dev/null
+++ b/assets/icons/polkadot/2color/Stake.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.735 15.924V18.5202C24.735 22.3374 20.0933 24.9999 14.3675 24.9999C8.64169 24.9999 4 22.3374 4 18.5202V15.924"></path><path d="M14.3675 21.9761C20.0933 21.9761 24.735 18.8817 24.735 15.0644C24.735 11.2472 20.0933 8.15277 14.3675 8.15277C8.64169 8.15277 4 11.2472 4 15.0644C4 18.8817 8.64169 21.9761 14.3675 21.9761Z"></path><path d="M14.3678 2.99997L14.3678 15.3903M11.3078 13.3305L14.3676 16.3902L17.4273 13.3305"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Staking.svg b/assets/icons/polkadot/2color/Staking.svg
new file mode 100644
index 00000000..d3068fe6
--- /dev/null
+++ b/assets/icons/polkadot/2color/Staking.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 12.958V16C25 20.0501 20.0751 22.875 14 22.875C7.92487 22.875 3 20.0501 3 16V12.958"></path><path d="M14 19.6667C20.0751 19.6667 25 16.3834 25 12.3333C25 8.28325 20.0751 5 14 5C7.92487 5 3 8.28325 3 12.3333C3 16.3834 7.92487 19.6667 14 19.6667Z"></path><path d="M11 13.5335L14.178 15.9725L17.356 13.5335"></path><path d="M14.1998 15.203L14.1998 9"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Starting Period.svg b/assets/icons/polkadot/2color/Starting Period.svg
new file mode 100644
index 00000000..54a1a84b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Starting Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M14.0002 14.0929L14.0001 5.9647"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Success.svg b/assets/icons/polkadot/2color/Success.svg
new file mode 100644
index 00000000..70eb70f1
--- /dev/null
+++ b/assets/icons/polkadot/2color/Success.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M9.53394 13.4026L13.1421 16.7726L19.7548 10.0842"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Supply Chain.svg b/assets/icons/polkadot/2color/Supply Chain.svg
new file mode 100644
index 00000000..95825eea
--- /dev/null
+++ b/assets/icons/polkadot/2color/Supply Chain.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.4636 5.76844C10.4636 7.84969 12.1507 9.53687 14.232 9.53687C16.3132 9.53688 18.0004 7.84969 18.0004 5.76844C18.0004 3.68719 16.3132 2 14.232 2C12.1507 2 10.4636 3.68719 10.4636 5.76844Z"></path><path d="M10.2056 5.76839L5.38863 5.76839L5.38863 18.5M8.66691 16.2038L5.38863 19.5819L2.00021 16.2933" fill="none"></path><path d="M16.838 22.2316C16.838 20.1503 15.1508 18.4631 13.0696 18.4631C10.9883 18.4631 9.30113 20.1503 9.30113 22.2316C9.30113 24.3128 10.9883 26 13.0696 26C15.1508 26 16.838 24.3128 16.838 22.2316Z"></path><path d="M17.0962 22.2316L21.9132 22.2316L21.9132 9.5M18.6349 11.7962L21.9132 8.41809L25.3016 11.7067" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Talent.svg b/assets/icons/polkadot/2color/Talent.svg
new file mode 100644
index 00000000..755fccbb
--- /dev/null
+++ b/assets/icons/polkadot/2color/Talent.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.1443 24.8612H2V21.6582C2 18.3465 4.20777 15.4407 7.39797 14.553L8.56208 14.2292C9.39049 13.9981 9.70546 12.99 9.15549 12.3295L8.29451 11.2947C6.82529 9.5283 6.94279 6.93349 8.56603 5.3063C10.3038 3.56457 13.1257 3.56457 14.8635 5.3063C16.4867 6.9325 16.6042 9.52732 15.135 11.2947L14.274 12.3295C13.7241 12.991 14.039 13.9991 14.8674 14.2292L17.0308 14.8305C18.0438 15.1119 18.8278 15.7784 19.2879 16.6157"></path><path d="M22.403 17.691L26 18.4869L23.5681 21.2258L23.9137 24.8544L20.527 23.4148L17.1433 24.8623L17.4829 21.2327L15.0451 18.4987L18.6411 17.695L20.5171 14.5591L22.402 17.691H22.403Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Technical Committee.svg b/assets/icons/polkadot/2color/Technical Committee.svg
new file mode 100644
index 00000000..83104957
--- /dev/null
+++ b/assets/icons/polkadot/2color/Technical Committee.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18 8.05658C21.2203 9.48819 23.4659 12.7152 23.4659 16.4666C23.4659 16.6457 23.4608 16.8235 23.4507 17M10.5337 8.05658C7.31336 9.48819 5.06775 12.7152 5.06775 16.4666C5.06775 16.6457 5.07286 16.8235 5.08295 17M8.98605 24C10.4806 25.0496 12.3018 25.6657 14.2668 25.6657C16.4348 25.6657 18.4276 24.9158 20 23.6611" stroke-miterlimit="10" fill="none" data-nofill="true"></path><circle cx="14.267" cy="7.26689" r="3.72426" transform="rotate(45 14.267 7.26689)"></circle><circle cx="6.26689" cy="21.0003" r="3.72426" transform="rotate(45 6.26689 21.0003)"></circle><circle cx="22.2669" cy="21.0003" r="3.72426" transform="rotate(45 22.2669 21.0003)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Teleport.svg b/assets/icons/polkadot/2color/Teleport.svg
new file mode 100644
index 00000000..8efe6b52
--- /dev/null
+++ b/assets/icons/polkadot/2color/Teleport.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M7.28001 23.3814C4.16031 22.7331 2 21.6545 2 20.4334C2 18.4518 7.37596 16.8457 14.0079 16.8457C20.6399 16.8457 26.0158 18.4518 26.0158 20.4334C26.0158 21.6545 23.8628 22.7331 20.7431 23.3814"></path><path d="M11.0109 16.9655C8.97356 17.3684 7.50525 19.1548 7.50525 21.2317V26H20.521V21.2317C20.521 19.1548 19.0527 17.3684 17.0153 16.9655C16.1358 16.9042 14.9497 16.8447 14.007 16.8447C13.036 16.8447 11.9149 16.9004 11.0109 16.9655Z"></path><path d="M9.09811 5.06738C4.91398 5.6279 2 6.8839 2 8.34278C2 10.3244 7.37596 11.9305 14.0079 11.9305C20.6399 11.9305 26.0158 10.3244 26.0158 8.34278C26.0158 6.88201 23.0943 5.62507 18.9017 5.06549"></path><path d="M12.7953 11.9123L10.6004 9.26915C9.13584 7.5083 9.25285 4.92271 10.8712 3.30152C12.6037 1.56616 15.4149 1.56616 17.1474 3.30152C18.7658 4.92271 18.8828 7.5083 17.4182 9.26915L15.2224 11.9123C14.8232 11.9246 14.4184 11.9302 14.0088 11.9302C13.5946 11.9302 13.1992 11.9246 12.7953 11.9123Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Testnet Token.svg b/assets/icons/polkadot/2color/Testnet Token.svg
new file mode 100644
index 00000000..c91a801c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Testnet Token.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 12.958V16C25 20.0501 20.0751 22.875 14 22.875C7.92487 22.875 3 20.0501 3 16V12.958"></path><path d="M14 19.6667C20.0751 19.6667 25 16.3834 25 12.3333C25 8.28325 20.0751 5 14 5C7.92487 5 3 8.28325 3 12.3333C3 16.3834 7.92487 19.6667 14 19.6667Z"></path><path d="M16.7515 9.63147L11.2514 15.1314"></path><path d="M16.7515 15.1315L11.2515 9.63143"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Thumbs Down.svg b/assets/icons/polkadot/2color/Thumbs Down.svg
new file mode 100644
index 00000000..ce54299d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Thumbs Down.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M16.1401 17.2978L23.2372 17.2978C24.5958 17.2978 25.6972 16.1964 25.6972 14.8378C25.6972 13.4792 24.5958 12.3778 23.2372 12.3778L22.2221 12.3778L23.894 12.3777C25.0442 12.3777 25.9766 11.2763 25.9766 9.9177C25.9766 8.5591 25.0442 7.45773 23.894 7.45773L21.7877 7.45773C22.9378 7.45773 23.8344 6.52958 23.8344 4.97169C23.8344 3.61309 22.5034 2.51172 21.3533 2.51172L18.9656 2.51172L15.3542 2.51177C11.3118 2.51187 9.69461 6.65141 9.69461 6.65141L3.97656 6.65141L3.97656 15.7957L9.69461 15.8378C9.69461 15.8378 12.1378 21.1212 14.1473 25.3328C14.7178 26.5283 16.1657 27.0065 17.3405 26.3945C18.3949 25.8453 18.8739 24.5958 18.4569 23.4825L16.1401 17.2978Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Thumbs Up.svg b/assets/icons/polkadot/2color/Thumbs Up.svg
new file mode 100644
index 00000000..2dd9c6a7
--- /dev/null
+++ b/assets/icons/polkadot/2color/Thumbs Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M16.1323 11.7257L23.2294 11.7257C24.588 11.7257 25.6894 12.827 25.6894 14.1856C25.6894 15.5442 24.588 16.6456 23.2294 16.6456L22.2143 16.6456L23.8862 16.6458C25.0364 16.6458 25.9687 17.7471 25.9687 19.1057C25.9687 20.4643 25.0364 21.5657 23.8862 21.5657L21.7799 21.5657C22.93 21.5657 23.8266 22.4939 23.8266 24.0517C23.8266 25.4103 22.4956 26.5117 21.3455 26.5117L18.9578 26.5117L15.3464 26.5117C11.304 26.5116 9.6868 22.372 9.6868 22.372L3.96875 22.372L3.96875 13.2277L9.6868 13.1857C9.6868 13.1857 12.13 7.90225 14.1395 3.69067C14.71 2.4951 16.1579 2.01692 17.3327 2.62891C18.3871 3.17815 18.8661 4.42765 18.4491 5.54096L16.1323 11.7257Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Time.svg b/assets/icons/polkadot/2color/Time.svg
new file mode 100644
index 00000000..43eebc8d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Time.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M18.6157 12.1538L14.0002 14.9229L14.0001 6.34801"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Token Holders.svg b/assets/icons/polkadot/2color/Token Holders.svg
new file mode 100644
index 00000000..f79e3063
--- /dev/null
+++ b/assets/icons/polkadot/2color/Token Holders.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.5492 22.0063H3V18.9346C3 15.7586 5.11729 12.9719 8.17677 12.1206L9.29317 11.81C10.0876 11.5884 10.3897 10.6216 9.86227 9.98815L9.03656 8.99578C7.62756 7.30176 7.74024 4.81327 9.29696 3.25276C10.9635 1.58241 13.6698 1.58241 15.3364 3.25276C16.8931 4.81233 17.0058 7.30081 15.5968 8.99578L14.7711 9.98815C14.2436 10.6226 14.5457 11.5894 15.3402 11.81L17.4148 12.3867C18.3864 12.6565 19.1382 13.2957 19.5795 14.0987"></path><path d="M25.3561 18.3923C25.3561 20.56 22.7134 22.3173 19.4527 22.3173C16.2506 22.3173 13.6505 20.6209 13.5585 18.5065V21.4774C13.5585 23.6452 16.2012 25.4025 19.4619 25.4025C22.7226 25.4025 25.3653 23.6452 25.3653 21.4774C25.3653 21.2097 25.4339 18.645 25.357 18.3914L25.3561 18.3923Z"></path><path d="M19.4526 22.3175C22.7125 22.3175 25.356 20.5601 25.356 18.3924C25.356 16.2247 22.7133 14.4673 19.4526 14.4673C16.1919 14.4673 13.5492 16.2247 13.5492 18.3924C13.5492 20.5601 16.1919 22.3175 19.4526 22.3175Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Token.svg b/assets/icons/polkadot/2color/Token.svg
new file mode 100644
index 00000000..a674de05
--- /dev/null
+++ b/assets/icons/polkadot/2color/Token.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 12.761V16.066C26 20.4843 20.6274 23.566 14 23.566C7.37258 23.566 2 20.4843 2 16.066V12.761"></path><path d="M14 20.0801C20.627 20.0801 26 16.4981 26 12.0801C26 7.66208 20.627 4.08008 14 4.08008C7.373 4.08008 2 7.66208 2 12.0801C2 16.4981 7.373 20.0801 14 20.0801Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Tools.svg b/assets/icons/polkadot/2color/Tools.svg
new file mode 100644
index 00000000..831307c1
--- /dev/null
+++ b/assets/icons/polkadot/2color/Tools.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11 7.00002H4M4 2L11 2V20.2857L7.5 26L4 20.2857L4 2Z"></path><path d="M20.5001 7.99993L17 7.99993M20.4998 13.9999H17M20.5001 19.6434H17M17 2L24 2V26H17V2Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Transaction.svg b/assets/icons/polkadot/2color/Transaction.svg
new file mode 100644
index 00000000..e8a6a7e0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Transaction.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 8.47366L25 8.47366M20.4787 2.95239L26 8.47366L20.4787 14.0044" fill="none"></path><path d="M25.9918 19.5213H3M7.52138 25.0521L2 19.5213L7.52138 14.0001" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Translate.svg b/assets/icons/polkadot/2color/Translate.svg
new file mode 100644
index 00000000..2a115997
--- /dev/null
+++ b/assets/icons/polkadot/2color/Translate.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M15.8744 21.235C15.2639 21.2887 14.6393 21.2849 14.0069 21.2184C12.7105 21.0822 11.5011 20.6953 10.4218 20.1112L4.79846 24.0642L7.47592 17.6476C5.94344 15.7325 5.13538 13.2365 5.41203 10.6044C5.69652 7.89795 7.10601 5.83942 9 4M12.8317 2.20431C13.8511 1.96766 14.9267 1.89399 16.026 2.00954C21.3304 2.56709 25.1785 7.31913 24.6209 12.6235C24.2828 15.8405 22.4716 18.3021 19.7768 19.8463" fill="none" data-nofill="true"></path><path d="M9.6192 7.73853L9.47795 3.24239L4.9818 3.38364" fill="none" data-nofill="true"></path><path d="M20.0228 15.5961L19.2373 20.0253L23.6665 20.8108" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Transparency.svg b/assets/icons/polkadot/2color/Transparency.svg
new file mode 100644
index 00000000..42a399b8
--- /dev/null
+++ b/assets/icons/polkadot/2color/Transparency.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.2303 26C18.9647 26 20.6601 25.4857 22.1022 24.5221C23.5443 23.5586 24.6683 22.189 25.332 20.5866C25.9957 18.9842 26.1694 17.2211 25.831 15.52C25.4927 13.8189 24.6575 12.2564 23.4311 11.03C22.2047 9.8036 20.6421 8.96841 18.9411 8.63005C17.24 8.29169 15.4768 8.46535 13.8744 9.12907C12.2721 9.79279 10.9025 10.9168 9.93894 12.3589C8.97537 13.8009 8.46106 15.4964 8.46106 17.2308C8.46106 17.8296 8.52231 18.4222 8.64135 19C8.98462 20.6663 9.80841 22.2105 11.0295 23.4316C12.6741 25.0761 14.9045 26 17.2303 26Z"></path><path d="M10.7692 19.5385C12.5036 19.5385 14.1991 19.0242 15.6411 18.0606C17.0832 17.097 18.2072 15.7274 18.8709 14.1251C19.5347 12.5227 19.7083 10.7595 19.37 9.05844C19.0316 7.35738 18.1964 5.79485 16.97 4.56845C15.7436 3.34205 14.1811 2.50686 12.48 2.1685C10.779 1.83014 9.01576 2.0038 7.41339 2.66752C5.81102 3.33124 4.44146 4.45522 3.47788 5.89731C2.51431 7.3394 2 9.03484 2 10.7692C2 13.095 2.9239 15.3255 4.56845 16.97C6.213 18.6146 8.44348 19.5385 10.7692 19.5385Z"></path><path d="M18.9411 8.63005C17.24 8.29169 15.4768 8.46535 13.8744 9.12907C12.2721 9.79279 10.9025 10.9168 9.93894 12.3589C8.97537 13.8009 8.46106 15.4964 8.46106 17.2308C8.46106 17.8296 8.52231 18.4222 8.64135 19"></path><path d="M11.6923 11.2307L16.7692 16.3076"></path><path d="M14.7827 9.24402L18.6992 13.1606"></path><path d="M9.52991 14.1307L14.2306 18.3481"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Treasury.svg b/assets/icons/polkadot/2color/Treasury.svg
new file mode 100644
index 00000000..9d96ee9a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Treasury.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.05532 10.5251H2.00006V10.3376L14.1049 2L26.2221 10.4352V10.5251H20.1399H8.05532Z"></path><path d="M2 26L26.222 26"></path><path d="M5.61755 11V25.5"></path><path d="M22.5933 11L22.5931 25.5"></path><path d="M15.7874 15.0547H13.5358C13.0926 15.0558 12.668 15.2277 12.3548 15.5326C12.0417 15.8375 11.8655 16.2506 11.8649 16.6815V16.701C11.8655 17.1319 12.0417 17.545 12.3548 17.8499C12.668 18.1548 13.0926 18.3267 13.5358 18.3278H14.6527C14.873 18.327 15.0912 18.3684 15.295 18.4498C15.4988 18.5311 15.684 18.6508 15.8401 18.802C15.9961 18.9531 16.12 19.1328 16.2045 19.3306C16.289 19.5284 16.3325 19.7404 16.3325 19.9546C16.3331 20.169 16.2901 20.3813 16.206 20.5795C16.1219 20.7777 15.9983 20.9577 15.8424 21.1093C15.6865 21.2609 15.5014 21.381 15.2976 21.4628C15.0938 21.5445 14.8754 21.5863 14.6549 21.5858H12.2134" fill="none" data-nofill="true"></path><path d="M14.0945 15.0107V13.8521" fill="none" data-nofill="true"></path><path d="M14.0945 22.8071V21.7383" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Twitter.svg b/assets/icons/polkadot/2color/Twitter.svg
new file mode 100644
index 00000000..553641ca
--- /dev/null
+++ b/assets/icons/polkadot/2color/Twitter.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.6909 4C16.0399 4 13.8909 6.2207 13.8909 8.96006C13.8909 9.34783 13.934 9.7252 14.0154 10.0874C14.0154 10.0874 10.463 9.63442 8.43636 8.62188C6.40973 7.60934 3.63636 4.90183 3.63636 4.90183C3.63636 4.90183 2.76727 6.3673 3.2 8.28369C3.63273 10.2001 5.16364 11.6656 5.16364 11.6656L2.98182 10.9892C2.98182 10.9892 3.09091 12.7414 4.18182 14.1456C5.27273 15.5497 6.90909 16.062 6.90909 16.062L4.72727 16.1747C4.72727 16.1747 5.38182 17.7589 6.58182 18.6547C7.78182 19.5506 9.30909 19.6693 9.30909 19.6693C9.30909 19.6693 7.54009 20.9234 6.25455 21.3602C4.6679 21.8994 2 21.8111 2 21.8111C2 21.8111 11.9273 27.0927 18.0364 21.2475C24.1455 15.4023 23.4909 8.96006 23.4909 8.96006C23.4909 8.96006 24.4192 8.36106 24.9091 7.83278C25.399 7.3045 26 6.25458 26 6.25458C26 6.25458 25.2234 6.64213 24.6909 6.81822C24.1584 6.99431 23.2727 7.1564 23.2727 7.1564C23.2727 7.1564 24.068 6.35395 24.4727 5.80366C24.8775 5.25337 25.3455 4.33819 25.3455 4.33819C25.3455 4.33819 24.2643 4.89081 23.6 5.12729C22.9948 5.34272 22.0973 5.46547 22.0973 5.46547C21.2277 4.56042 20.0226 4 18.6909 4Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Ui.svg b/assets/icons/polkadot/2color/Ui.svg
new file mode 100644
index 00000000..a8699148
--- /dev/null
+++ b/assets/icons/polkadot/2color/Ui.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2 25.7584L26 25.7584L26 2.00001L2 2.00002L2 25.7584Z"></path><path d="M25.993 8.51306H2.00028"></path><path d="M21.9614 21.5035H16.3515" stroke-miterlimit="10"></path><path d="M21.9614 16.7718H16.3515" stroke-miterlimit="10"></path><path d="M21.9614 12.3423H16.3515" stroke-miterlimit="10"></path><path d="M11.6991 21.5035H6.08917" stroke-miterlimit="10"></path><path d="M11.5463 12.3423H6.24258V16.7718H11.5463V12.3423Z" stroke-miterlimit="10"></path><path d="M9.25124 5.43288L9.23407 5.41571" stroke-miterlimit="10"></path><path d="M5.4659 5.43288L5.44873 5.41571" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Unbond.svg b/assets/icons/polkadot/2color/Unbond.svg
new file mode 100644
index 00000000..8283144b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Unbond.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M20.3038 6.43753C20.3038 8.88855 17.3237 10.8756 13.6467 10.8756C10.0357 10.8756 7.10374 8.95739 7 6.56673V9.92591C7 12.3769 9.98008 14.364 13.6571 14.364C17.3341 14.364 20.3142 12.3769 20.3142 9.92591C20.3142 9.62319 20.3915 6.72328 20.3047 6.43658L20.3038 6.43753Z"></path><path d="M13.673 10.8761C17.349 10.8761 20.33 8.88907 20.33 6.43805C20.33 3.98703 17.35 2 13.673 2C9.99596 2 7.01588 3.98703 7.01588 6.43805C7.01588 8.88907 9.99596 10.8761 13.673 10.8761Z"></path><path d="M13.6119 18.4733L13.6119 24.9733M17.2399 22.3721L13.612 26L9.98407 22.3721" stroke-miterlimit="10" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Unchecked.svg b/assets/icons/polkadot/2color/Unchecked.svg
new file mode 100644
index 00000000..57b1f69a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Unchecked.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26.9766 2.08008H2.97656V26.0801H26.9766V2.08008Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Unlock.svg b/assets/icons/polkadot/2color/Unlock.svg
new file mode 100644
index 00000000..e69de13a
--- /dev/null
+++ b/assets/icons/polkadot/2color/Unlock.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.6869 6.80748C17.4115 6.12236 17.0106 5.69148 16.7695 5.41665C15.7381 4.2427 14.4559 3.93051 12.9403 4.01224C11.1395 4.11153 9.60805 5.39009 9.027 7.05031C8.7804 7.75346 8.7028 8.64953 8.71804 10.5" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M23.1735 10.8618H4V24.8062H23.1735V10.8618Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Unstake.svg b/assets/icons/polkadot/2color/Unstake.svg
new file mode 100644
index 00000000..c448fec0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Unstake.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.735 16.924V19.5201C24.735 23.3374 20.0933 25.9998 14.3675 25.9998C8.64169 25.9998 4 23.3374 4 19.5201V16.924"></path><path d="M14.3675 22.9761C20.0933 22.9761 24.735 19.8816 24.735 16.0644C24.735 12.2472 20.0933 9.15271 14.3675 9.15271C8.64169 9.15271 4 12.2472 4 16.0644C4 19.8816 8.64169 22.9761 14.3675 22.9761Z"></path><path d="M14.3673 15.3902L14.3673 2.99994M17.4273 5.05973L14.3675 2L11.3078 5.05973" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Upgrade.svg b/assets/icons/polkadot/2color/Upgrade.svg
new file mode 100644
index 00000000..3fe34bbb
--- /dev/null
+++ b/assets/icons/polkadot/2color/Upgrade.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26.0002C20.6274 26.0002 26 20.6277 26 14.0002C26 7.37283 20.6274 2.00024 14 2.00024C7.37258 2.00024 2 7.37283 2 14.0002C2 20.6277 7.37258 26.0002 14 26.0002Z"></path><path d="M13.9998 21.0574L13.9998 8.00024M10.7449 10.1979L13.9998 6.94298L17.2547 10.1979"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Use Cases.svg b/assets/icons/polkadot/2color/Use Cases.svg
new file mode 100644
index 00000000..4aaa34d8
--- /dev/null
+++ b/assets/icons/polkadot/2color/Use Cases.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 4H6.87515V23.1248H26V4Z"></path><path d="M16.4376 9.04315L20.953 13.5586L16.4376 18.0816"></path><path d="M20.0024 13.5624L1.99994 13.5624"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Users.svg b/assets/icons/polkadot/2color/Users.svg
new file mode 100644
index 00000000..dd18a721
--- /dev/null
+++ b/assets/icons/polkadot/2color/Users.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M10.9523 11.4719L9.92866 10.2412C8.18155 8.14076 8.32148 5.05539 10.2515 3.12174C12.318 1.05141 15.6726 1.05141 17.7391 3.12174C19.6691 5.05539 19.8091 8.14076 18.062 10.2412L17.0385 11.4716C16.3847 12.2576 16.7593 13.4563 17.7443 13.7303L19.1309 14.1159C22.9276 15.1717 25.5547 18.6291 25.5547 22.5698V26.371H2.44531V22.5633C2.44531 18.6259 5.06981 15.1713 8.86305 14.1156L10.2468 13.7306C11.2316 13.4565 11.6061 12.2578 10.9523 11.4719Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Utility.svg b/assets/icons/polkadot/2color/Utility.svg
new file mode 100644
index 00000000..11652f38
--- /dev/null
+++ b/assets/icons/polkadot/2color/Utility.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M20.9399 24.3129L17.2934 26.4121L14.7854 23.6251H13.1634L10.6254 26.3721L4.90338 23.0681L6.07737 19.4751L5.28137 18.1021L1.60938 17.2661V10.6581L5.31138 9.88206L6.09737 8.50906L4.99237 4.90606L10.7144 1.61206L13.2124 4.39906H14.8344L17.3824 1.66206L23.0944 4.95606L21.9504 8.49906L22.7764 9.93206L26.3894 10.7581V18.2621L22.7564 19.0281L22.3441 19.2979"></path><path d="M16.3475 19.3776C15.5643 19.7935 14.6777 20.0435 13.736 20.0666C10.4945 20.1462 7.80311 17.5839 7.72349 14.3424C7.69987 13.3808 7.91538 12.463 8.30208 11.6501L12.212 15.3629L14.9484 12.4886L11.1299 8.86291C11.8361 8.53808 12.6148 8.34042 13.4475 8.31997C16.6889 8.24034 19.3803 10.8027 19.46 14.0442C19.4807 14.8868 19.3219 15.6941 19.0126 16.4257L26.1316 23.3577L23.3952 26.2319L16.3475 19.3776Z" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Ux.svg b/assets/icons/polkadot/2color/Ux.svg
new file mode 100644
index 00000000..8919a0f9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Ux.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5025 2L6.91705 2L6.91705 6.9637L21.5025 6.9637L21.5025 2Z"></path><path d="M13.9297 7.00257L13.9297 20.3938" fill="none" data-nofill="true"></path><path d="M13.9684 12.1343L23.396 12.1343L23.396 16.2048" fill="none" data-nofill="true"></path><path d="M13.7919 12.1343L4.46362 12.1343L4.46362 16.2048" fill="none" data-nofill="true"></path><path d="M6.91706 16.2047L2 16.2047L2 21.1024L6.91706 21.1024L6.91706 16.2047Z"></path><path d="M25.9127 16.2047L20.9956 16.2047L20.9956 21.1024L25.9127 21.1024L25.9127 16.2047Z"></path><path d="M16.3883 21.1024L11.4712 21.1024L11.4712 26L16.3883 26L16.3883 21.1024Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Validators.svg b/assets/icons/polkadot/2color/Validators.svg
new file mode 100644
index 00000000..1e2dc0c5
--- /dev/null
+++ b/assets/icons/polkadot/2color/Validators.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M8.03863 14.0733L13.0614 18.697L25.3774 2.42365" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Value Bearing Token.svg b/assets/icons/polkadot/2color/Value Bearing Token.svg
new file mode 100644
index 00000000..93307165
--- /dev/null
+++ b/assets/icons/polkadot/2color/Value Bearing Token.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 13.4443V16.7493C26 21.1676 20.6274 24.2493 14 24.2493C7.37258 24.2493 2 21.1676 2 16.7493V13.4443"></path><path d="M14 20.7634C20.627 20.7634 26 17.1814 26 12.7634C26 8.34543 20.627 4.76343 14 4.76343C7.373 4.76343 2 8.34543 2 12.7634C2 17.1814 7.373 20.7634 14 20.7634Z"></path><path d="M14 4.76343C12.935 4.76343 11.908 4.86543 10.924 5.03843V15.0144L13.998 13.6994L17.075 15.0074V5.03843C16.092 4.86443 15.065 4.76343 13.999 4.76343H14Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Verified Account.svg b/assets/icons/polkadot/2color/Verified Account.svg
new file mode 100644
index 00000000..abf054fc
--- /dev/null
+++ b/assets/icons/polkadot/2color/Verified Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.665 24.771H2V21.588C2 18.288 4.20059 15.3916 7.37984 14.5072L8.54142 14.1848C9.3664 13.9557 9.68037 12.9516 9.13258 12.2934L8.27554 11.2629C6.81225 9.50359 6.92916 6.92021 8.54613 5.30041C10.2772 3.56653 13.0859 3.56653 14.817 5.30041C16.433 6.92021 16.5508 9.50359 15.0876 11.2629L14.173 12.3623C13.6365 13.0072 13.9109 13.9896 14.7038 14.263L16.4703 14.7928"></path><path d="M26 19.2449C26 20.711 25.4173 22.1177 24.3811 23.1539C23.344 24.191 21.9382 24.7728 20.4721 24.7728C19.006 24.7728 17.5993 24.1901 16.5631 23.1539C15.526 22.1168 14.9433 20.711 14.9433 19.2449C14.9433 17.7788 15.526 16.3721 16.5631 15.3359C17.6002 14.2988 19.006 13.717 20.4721 13.717C21.9382 13.717 23.3449 14.2997 24.3811 15.3359C25.4182 16.373 26 17.7788 26 19.2449Z" stroke-miterlimit="10"></path><path d="M22.259 17.9769L19.7834 20.6706L18.4628 19.3491"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Verified Signed.svg b/assets/icons/polkadot/2color/Verified Signed.svg
new file mode 100644
index 00000000..eafd67f0
--- /dev/null
+++ b/assets/icons/polkadot/2color/Verified Signed.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M22.8036 18.8845L26.5599 16.0759L23.6835 12.4389L24.674 7.90114L20.1062 6.88196L17.8667 2.73581L13.745 4.80927L9.32082 2.99604L7.57176 7.19308L3.03621 8.56006L4.48019 12.9155L1.95365 16.8249L5.91469 19.3033L6.58009 23.9244L11.2032 23.3636L14.7506 26.5351L17.8744 23.1989L22.6429 23.4364L22.8036 18.8845Z" stroke-miterlimit="10"></path><path d="M9.58301 14.3475L12.7651 17.3196L18.5969 11.421" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Verify.svg b/assets/icons/polkadot/2color/Verify.svg
new file mode 100644
index 00000000..db6f20b3
--- /dev/null
+++ b/assets/icons/polkadot/2color/Verify.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.7397 4.99994L21.2397 6.99994L26.2397 2.99994" fill="none" data-nofill="true"></path><path d="M9.55662 12.7572L8.64731 11.664C7.09538 9.79821 7.21968 7.05754 8.93412 5.33992C10.7698 3.50088 13.7495 3.50088 15.5851 5.33992C17.2996 7.05754 17.4239 9.79821 15.872 11.664L14.9628 12.7569C14.3821 13.4551 14.7148 14.5199 15.5898 14.7632L16.8215 15.1058C20.194 16.0437 22.5276 19.1148 22.5276 22.6153V25.9918H2V22.6094C2 19.1119 4.33128 16.0433 7.70074 15.1056L8.92988 14.7635C9.80471 14.5201 10.1373 13.4553 9.55662 12.7572Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Version.svg b/assets/icons/polkadot/2color/Version.svg
new file mode 100644
index 00000000..6038a5fe
--- /dev/null
+++ b/assets/icons/polkadot/2color/Version.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M16.4735 3.99275C13.4795 0.873905 5.99424 2.49575 5.99424 2.49575L5.99424 14.5969C5.99424 14.5969 13.4795 12.975 16.4735 16.0939C19.4676 19.2127 25.4558 18.3394 25.4558 18.3394L25.4558 6.23832C25.4558 6.23832 19.4676 7.1116 16.4735 3.99275Z"></path><path d="M5.99414 3.61853L5.99414 26.0742"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Vesting Period.svg b/assets/icons/polkadot/2color/Vesting Period.svg
new file mode 100644
index 00000000..177c6652
--- /dev/null
+++ b/assets/icons/polkadot/2color/Vesting Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 26H2V3.88452H26V26Z" stroke-miterlimit="10"></path><path d="M9.42337 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34177V2.00006" stroke-miterlimit="10"></path><path d="M10.9154 13.364L10.9154 12.0846V12C10.9154 10.3431 12.2586 9 13.9154 9H14.0846C15.7415 9 17.0846 10.3431 17.0846 12V12.0846L17.0846 13.364"></path><path d="M20 13.3658H8V22.0931H20V13.3658Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Vesting.svg b/assets/icons/polkadot/2color/Vesting.svg
new file mode 100644
index 00000000..17337391
--- /dev/null
+++ b/assets/icons/polkadot/2color/Vesting.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11.1211 5.47856L11.1211 4.45884V4.45884C11.1211 3.10099 12.2218 2.00024 13.5797 2.00024V2.00024C14.9375 2.00024 16.0383 3.10099 16.0383 4.45884V4.45884L16.0383 5.47856" fill="none"></path><path d="M18.3618 5.48004H8.79722V12.4361H18.3618V5.48004Z"></path><path d="M8.01595 19.1049L8.00957 19.1065V19.1918C8.01117 19.1631 8.01356 19.1336 8.01595 19.1049Z"></path><path d="M19.2526 19.301C19.2526 21.3726 16.7339 23.052 13.6262 23.052C10.5743 23.052 8.09627 21.4308 8.00859 19.4102V22.2493C8.00859 24.3209 10.5273 26.0003 13.635 26.0003C16.7427 26.0003 19.2614 24.3209 19.2614 22.2493C19.2614 21.9935 19.3267 19.5425 19.2534 19.3002L19.2526 19.301Z"></path><path d="M13.6264 23.052C16.7333 23.052 19.2528 21.3726 19.2528 19.301C19.2528 17.2295 16.7341 15.5501 13.6264 15.5501C10.5187 15.5501 8 17.2295 8 19.301C8 21.3726 10.5187 23.052 13.6264 23.052Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Video Pause.svg b/assets/icons/polkadot/2color/Video Pause.svg
new file mode 100644
index 00000000..1b9cddd6
--- /dev/null
+++ b/assets/icons/polkadot/2color/Video Pause.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9883 26.0742C21.6157 26.0742 26.9883 20.7016 26.9883 14.0742C26.9883 7.4468 21.6157 2.07422 14.9883 2.07422C8.36086 2.07422 2.98828 7.4468 2.98828 14.0742C2.98828 20.7016 8.36086 26.0742 14.9883 26.0742Z"></path><path d="M17.9443 18.3023L17.9443 10.1176"></path><path d="M11.9883 10.0742V18.3023"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Video Play.svg b/assets/icons/polkadot/2color/Video Play.svg
new file mode 100644
index 00000000..1d89d8b5
--- /dev/null
+++ b/assets/icons/polkadot/2color/Video Play.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9824 26.0742C21.6098 26.0742 26.9824 20.7016 26.9824 14.0742C26.9824 7.4468 21.6098 2.07422 14.9824 2.07422C8.355 2.07422 2.98242 7.4468 2.98242 14.0742C2.98242 20.7016 8.355 26.0742 14.9824 26.0742Z"></path><path d="M19.8242 14.1882L12.9825 10.0742V18.3003L19.8242 14.1882Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Video.svg b/assets/icons/polkadot/2color/Video.svg
new file mode 100644
index 00000000..a6ea3d9c
--- /dev/null
+++ b/assets/icons/polkadot/2color/Video.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 2.99976H2V24.1198H26V2.99976Z" stroke-miterlimit="40"></path><path d="M18.32 15.4807L12.56 11.6398V19.3198L18.32 15.4807Z"></path><path d="M2 7.79974H26"></path><path d="M19.4972 3.55933L22.783 7.25587"></path><path d="M12 3.55933L15.2858 7.25587"></path><path d="M5 3.55933L8.28581 7.25587"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Videos.svg b/assets/icons/polkadot/2color/Videos.svg
new file mode 100644
index 00000000..ce47a27b
--- /dev/null
+++ b/assets/icons/polkadot/2color/Videos.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.8623 20.4786H26.0002V3H6.13812V6.72414" stroke-miterlimit="40"></path><path d="M21.8621 7.13794H2V24.6166H21.8621V7.13794Z" stroke-miterlimit="40"></path><path d="M15.5063 17.467L10.7394 14.2883V20.6442L15.5063 17.467Z"></path><path d="M2 11.1104H21.8621"></path><path d="M4.6192 7.77124L7.5 10.9999"></path><path d="M16.1174 7.74927L19 10.6318"></path><path d="M10.5771 7.77014L13.3915 10.5846"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Vote.svg b/assets/icons/polkadot/2color/Vote.svg
new file mode 100644
index 00000000..1ceaacd8
--- /dev/null
+++ b/assets/icons/polkadot/2color/Vote.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M16.0555 1.99997L4.49426 13.5612L10.68 19.747L15.0524 19.747L24.4274 10.3719L16.0555 1.99997Z"></path><path d="M12.6364 14.214L15.0919 14.3288L15.5422 8.03956"></path><path d="M2 26V19.7446H26.4885V26" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Voting Period.svg b/assets/icons/polkadot/2color/Voting Period.svg
new file mode 100644
index 00000000..0142eb06
--- /dev/null
+++ b/assets/icons/polkadot/2color/Voting Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 26H2V3.88452H26V26Z" stroke-miterlimit="10"></path><path d="M9.42337 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34177V2.00006" stroke-miterlimit="10"></path><path d="M15.2908 8.99999L6.64577 17.645L11.175 22.1742L14.6369 22.1742L21.551 15.2602L15.2908 8.99999Z"></path><path d="M21.5273 22.1729L6 22.1729" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Wallet Deposit.svg b/assets/icons/polkadot/2color/Wallet Deposit.svg
new file mode 100644
index 00000000..89a0a124
--- /dev/null
+++ b/assets/icons/polkadot/2color/Wallet Deposit.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.9449 2H5V17.9603H23.9449V2Z"></path><path d="M23.009 6.25403H17.2704C15.2125 6.25403 13.5443 7.92228 13.5443 9.98016C13.5443 12.0381 15.2125 13.7063 17.2704 13.7063H23.009C23.5317 13.7063 23.9555 13.2826 23.9555 12.7598V7.2005C23.9555 6.67778 23.5317 6.25403 23.009 6.25403Z"></path><path d="M17.213 22.741L14.0732 26L10.9388 22.741" fill="none" data-nofill="true"></path><path d="M14.0732 25L14.0732 18.3316"></path><path d="M17.0181 10.0181L17 10" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Wallet Withdraw.svg b/assets/icons/polkadot/2color/Wallet Withdraw.svg
new file mode 100644
index 00000000..a5f597b2
--- /dev/null
+++ b/assets/icons/polkadot/2color/Wallet Withdraw.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.8458 10.1229H4.99995V25.9998H23.8458V10.1229Z"></path><path d="M22.9147 14.3546H17.2061C15.159 14.3546 13.4995 16.0141 13.4995 18.0613C13.4995 20.1084 15.159 21.7679 17.2061 21.7679H22.9147C23.4347 21.7679 23.8562 21.3464 23.8562 20.8264V15.2961C23.8562 14.7761 23.4347 14.3546 22.9147 14.3546Z"></path><path d="M14.7695 9.62805L14.7695 3M11.6461 5.24169L14.7695 1.99976L17.8874 5.24169" fill="none" data-nofill="true"></path><path d="M17.0181 18.0181L17 18" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Wallet.svg b/assets/icons/polkadot/2color/Wallet.svg
new file mode 100644
index 00000000..dfaf590e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Wallet.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26.7599 3.24988H1.23975V24.7496H26.7599V3.24988Z"></path><path d="M26.7742 8.98047H17.7689C14.9968 8.98047 12.7495 11.2277 12.7495 13.9999C12.7495 16.772 14.9968 19.0192 17.7689 19.0192H26.7742V8.98047Z"></path><circle cx="18" cy="14" r="1"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Wallets.svg b/assets/icons/polkadot/2color/Wallets.svg
new file mode 100644
index 00000000..245afeb3
--- /dev/null
+++ b/assets/icons/polkadot/2color/Wallets.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M6.11719 7V2.86328H26.4695V20.0093H22.8445"></path><path d="M22.4695 7.49976H2.11719V24.6457H22.4695V7.49976Z"></path><path d="M21.4808 12.0699H15.2991C13.0883 12.0699 11.2961 13.8621 11.2961 16.0729C11.2961 18.2837 13.0883 20.0758 15.2991 20.0758H21.4808C22.0331 20.0758 22.4808 19.6281 22.4808 19.0758V13.0699C22.4808 12.5177 22.0331 12.0699 21.4808 12.0699Z"></path><path d="M15.0181 16.0181L15 16" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Wasm.svg b/assets/icons/polkadot/2color/Wasm.svg
new file mode 100644
index 00000000..623d6ffe
--- /dev/null
+++ b/assets/icons/polkadot/2color/Wasm.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.763 3.99976C17.763 6.08502 16.1319 7.85576 14 7.85576C11.9242 7.85576 10.1625 6.0858 10.237 3.99976H4V23.9998H24V3.99976H17.763Z"></path><path d="M10 12.9998L11.3333 19.3603H11.4172L14 12.9998H14.0651L16.6667 19.3603H16.7194L18 12.9998"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Web3.svg b/assets/icons/polkadot/2color/Web3.svg
new file mode 100644
index 00000000..072fce6e
--- /dev/null
+++ b/assets/icons/polkadot/2color/Web3.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.9999 1.27868C21.0256 1.27868 26.7211 6.97413 26.7211 13.9998C26.7211 21.0255 21.0256 26.7209 13.9999 26.7209C6.97425 26.7209 1.27881 21.0255 1.27881 13.9998C1.27881 6.97413 6.97425 1.27868 13.9999 1.27868Z"></path><path d="M6 11.1799L7.39339 17.5405H7.48107L10.1802 11.1799H10.2482L12.967 17.5405H13.022L14.3604 11.1799"></path><path d="M19.3003 14.18C20.1785 14.18 20.8905 14.8919 20.8905 15.7701C20.8905 16.6483 20.1785 17.3602 19.3003 17.3602H18.2402M19.3003 14.18C20.1785 14.18 20.8905 13.468 20.8905 12.5898C20.8905 11.7116 20.1785 10.9996 19.3003 10.9996H18.2402M19.3003 14.18H19.0984"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Whitepaper Download.svg b/assets/icons/polkadot/2color/Whitepaper Download.svg
new file mode 100644
index 00000000..a4d2a122
--- /dev/null
+++ b/assets/icons/polkadot/2color/Whitepaper Download.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.00001 26.0005V2.00049H17L23.4615 8.46203V26.0005H5.00001Z"></path><path d="M23 8.46201H17V2.50024"></path><path d="M14.462 12.0002L14.462 18.3181M17.424 16.3182L14.462 19.2802L11.5 16.3182"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Whitepaper Upload.svg b/assets/icons/polkadot/2color/Whitepaper Upload.svg
new file mode 100644
index 00000000..3962e262
--- /dev/null
+++ b/assets/icons/polkadot/2color/Whitepaper Upload.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M5.00001 26.0002V2.00024H17L23.4615 8.46178V26.0002H5.00001Z"></path><path d="M23 8.46176H17V2.5"></path><path d="M14.462 19.28L14.462 12.9621M11.5 14.9619L14.462 12L17.4239 14.9619"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Whitepaper.svg b/assets/icons/polkadot/2color/Whitepaper.svg
new file mode 100644
index 00000000..f707cf08
--- /dev/null
+++ b/assets/icons/polkadot/2color/Whitepaper.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.00001 26.0005V2.00049H17L23.4615 8.46203V26.0005H5.00001Z"></path><path d="M23 8.46201H17V2.50024"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/WiFi Off.svg b/assets/icons/polkadot/2color/WiFi Off.svg
new file mode 100644
index 00000000..689d7366
--- /dev/null
+++ b/assets/icons/polkadot/2color/WiFi Off.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><circle cx="14.0003" cy="23.6787" r="1.83075"></circle><path d="M8.40405 18.0865C9.08223 17.2586 9.93545 16.5912 10.9024 16.1325C11.8693 15.6737 12.9258 15.4348 13.996 15.4332C15.0663 15.4315 16.1236 15.667 17.0919 16.1228C18.0602 16.5786 18.9155 17.2432 19.5963 18.069" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M5.18091 13.7426C6.98148 11.3968 10.2637 9.82629 14.0138 9.82629C17.7453 9.82629 21.0134 11.3814 22.8198 13.7087" fill="none" data-nofill="true"></path><path d="M2 9.56293C3.47594 7.81883 5.31446 6.41758 7.38743 5.45683C9.4604 4.49607 11.718 3.99894 14.0027 4.00006C16.2875 4.00119 18.5446 4.50055 20.6166 5.46335C22.6886 6.42614 24.5258 7.82921 26 9.57476" fill="none" data-nofill="true"></path><path d="M2.99982 2L24.9998 26" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/WiFi.svg b/assets/icons/polkadot/2color/WiFi.svg
new file mode 100644
index 00000000..80510fb5
--- /dev/null
+++ b/assets/icons/polkadot/2color/WiFi.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><circle cx="14.9943" cy="23.747" r="1.83075"></circle><path d="M9.39825 18.1548C10.0764 17.3268 10.9297 16.6595 11.8966 16.2007C12.8635 15.7419 13.92 15.5031 14.9902 15.5014C16.0605 15.4997 17.1178 15.7353 18.0861 16.191C19.0544 16.6468 19.9097 17.3115 20.5905 18.1373" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M6.17468 13.8108C7.97526 11.465 11.2575 9.89453 15.0075 9.89453C18.7391 9.89453 22.0072 11.4497 23.8135 13.7769" fill="none" data-nofill="true"></path><path d="M2.99414 9.63123C4.47008 7.88713 6.3086 6.48588 8.38157 5.52513C10.4545 4.56437 12.7121 4.06724 14.9969 4.06836C17.2817 4.06949 19.5387 4.56885 21.6108 5.53164C23.6828 6.49444 25.5199 7.8975 26.9941 9.64305" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Wiki.svg b/assets/icons/polkadot/2color/Wiki.svg
new file mode 100644
index 00000000..298e28f9
--- /dev/null
+++ b/assets/icons/polkadot/2color/Wiki.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 1.49976C20.6274 1.49976 26 6.87234 26 13.4998C26 20.1272 20.6274 25.4998 14 25.4998C7.37258 25.4998 2 20.1272 2 13.4998C2 6.87234 7.37258 1.49976 14 1.49976Z"></path><path d="M12.2975 10.4158L16.3586 17.9578L20.4196 10.4158" fill="none" data-nofill="true"></path><path d="M7.65649 10.4158L11.7176 17.9578L15.7787 10.4158" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Withdraw.svg b/assets/icons/polkadot/2color/Withdraw.svg
new file mode 100644
index 00000000..f694e397
--- /dev/null
+++ b/assets/icons/polkadot/2color/Withdraw.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.706 26L6 26" fill="none" data-nofill="true"></path><path d="M14.4817 21.4482L14.4817 2.94818M8.95172 7.52722L14.4817 1.99997L20.0165 7.52548" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Workshop.svg b/assets/icons/polkadot/2color/Workshop.svg
new file mode 100644
index 00000000..ec41012d
--- /dev/null
+++ b/assets/icons/polkadot/2color/Workshop.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.29544 10.0459L9.80687 9.43105C10.6797 8.38166 10.6098 6.84019 9.64556 5.87413C8.61312 4.83977 6.93717 4.83977 5.90473 5.87412C4.94046 6.84019 4.87055 8.38166 5.74341 9.43105L6.25475 10.0458C6.58137 10.4385 6.39423 11.0374 5.90214 11.1742L5.20937 11.3669C3.31252 11.8944 2 13.6217 2 15.5905V17.4896H13.5456V15.5872C13.5456 13.6201 12.2344 11.8942 10.3393 11.3668L9.64794 11.1744C9.1559 11.0374 8.96883 10.4386 9.29544 10.0459Z"></path><path d="M18.7046 10.0459L18.1932 9.43105C17.3203 8.38166 17.3902 6.84019 18.3545 5.87413C19.387 4.83977 21.0629 4.83977 22.0953 5.87412C23.0596 6.84019 23.1295 8.38166 22.2567 9.43105L21.7453 10.0458C21.4187 10.4385 21.6058 11.0374 22.0979 11.1742L22.7907 11.3669C24.6876 11.8944 26.0001 13.6217 26.0001 15.5905V17.4896H14.4545V15.5872C14.4545 13.6201 15.7657 11.8942 17.6608 11.3668L18.3521 11.1744C18.8442 11.0374 19.0312 10.4386 18.7046 10.0459Z"></path><path d="M2.00025 25.1183V17.4898H25.9788V25.1183" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/XCM (Message).svg b/assets/icons/polkadot/2color/XCM (Message).svg
new file mode 100644
index 00000000..d1c06564
--- /dev/null
+++ b/assets/icons/polkadot/2color/XCM (Message).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11.2307 14.6156C11.2307 12.0666 9.16434 10.0002 6.61535 10.0002C4.06636 10.0002 2 12.0666 2 14.6156C2 17.1646 4.06636 19.2309 6.61535 19.2309C9.16434 19.2309 11.2307 17.1646 11.2307 14.6156Z"></path><path d="M26 10.0002H16.7693V19.231H26V10.0002Z"></path><path d="M11.4384 14.6184L21.3847 14.6184"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/2color/Youtube.svg b/assets/icons/polkadot/2color/Youtube.svg
new file mode 100644
index 00000000..71230aa4
--- /dev/null
+++ b/assets/icons/polkadot/2color/Youtube.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 5.39978H3V22.9998H25V5.39978Z" stroke-miterlimit="40"></path><path d="M18.5631 14.1395L11.9631 10.2886V17.9886L18.5631 14.1395Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/AI & Computing.svg b/assets/icons/polkadot/line/AI & Computing.svg
new file mode 100644
index 00000000..33cacaa1
--- /dev/null
+++ b/assets/icons/polkadot/line/AI & Computing.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="5" cy="14" r="2" transform="rotate(-180 5 14)"></circle><path d="M6.90002 14L10.9 14"></path><circle cx="9" cy="6" r="2"></circle><path d="M17 11H11V17H17V11Z"></path><path d="M11 6H14V11" fill="none"></path><circle cx="19" cy="22" r="2" transform="rotate(-180 19 22)"></circle><path d="M17 22L14 22L14 17" fill="none"></path><circle cx="23.4" cy="14" r="2"></circle><path d="M21.5 14H17.5"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Account Portability.svg b/assets/icons/polkadot/line/Account Portability.svg
new file mode 100644
index 00000000..601abe23
--- /dev/null
+++ b/assets/icons/polkadot/line/Account Portability.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8 13.7644L2 13.7644"></path><path d="M6.16985 16.6807L9.08611 13.7643L6.16985 10.848" fill="none"></path><path d="M19.6117 14.6402L20.3804 13.716C21.6924 12.1387 21.5873 9.82174 20.1379 8.36968C18.5861 6.81497 16.067 6.81497 14.5152 8.36968C13.0658 9.82174 12.9608 12.1387 14.2727 13.716L15.0413 14.64C15.5323 15.2302 15.251 16.1304 14.5113 16.3361L13.47 16.6257C10.6189 17.4185 8.64612 20.0149 8.64612 22.9741V25.8286H26V22.9692C26 20.0124 24.0291 17.4182 21.1806 16.6255L20.1415 16.3363C19.402 16.1305 19.1208 15.2304 19.6117 14.6402Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Action Left.svg b/assets/icons/polkadot/line/Action Left.svg
new file mode 100644
index 00000000..863c22e1
--- /dev/null
+++ b/assets/icons/polkadot/line/Action Left.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19 22L10 14.4925L19 7" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Action Right.svg b/assets/icons/polkadot/line/Action Right.svg
new file mode 100644
index 00000000..1ad062c8
--- /dev/null
+++ b/assets/icons/polkadot/line/Action Right.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9 6L18 13.5075L9 21" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Add key pair.svg b/assets/icons/polkadot/line/Add key pair.svg
new file mode 100644
index 00000000..2879ec19
--- /dev/null
+++ b/assets/icons/polkadot/line/Add key pair.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.7641 17.1156L14.7641 11.7782"></path><path d="M17.4328 14.4469L12.0954 14.4469"></path><path d="M9.34094 24.5222C8.99891 24.8358 8.59843 25.0788 8.16238 25.2375C7.72632 25.3962 7.26323 25.4674 6.79954 25.4471C6.33586 25.4267 5.88066 25.3153 5.45993 25.119C5.03921 24.9228 4.6612 24.6456 4.34749 24.3033C3.72289 23.6055 3.40063 22.6884 3.4515 21.7536C3.50237 20.8187 3.92221 19.9425 4.6188 19.3174C4.96083 19.0038 5.36131 18.7608 5.79736 18.6021C6.23342 18.4434 6.69651 18.3722 7.1602 18.3925C7.62388 18.4128 8.07908 18.5243 8.49981 18.7206C8.92053 18.9168 9.29854 19.194 9.61225 19.5362C10.2365 20.2342 10.5585 21.1512 10.5077 22.086C10.4568 23.0208 10.0372 23.8969 9.34094 24.5222Z" fill="none"></path><path d="M10.6179 21.7082L26 21.7106"></path><path d="M18.4265 22.3872L18.4239 25.6594L23.3242 25.6653L23.3256 22.3942"></path><path d="M9.33963 9.39374C8.9976 9.70728 8.59712 9.95033 8.16107 10.109C7.72502 10.2677 7.26193 10.3389 6.79824 10.3186C6.33455 10.2983 5.87935 10.1868 5.45863 9.99056C5.03791 9.79432 4.6599 9.51715 4.34619 9.17487C3.72159 8.47703 3.39933 7.55996 3.4502 6.62508C3.50107 5.69021 3.92091 4.81399 4.6175 4.1889C4.95953 3.87536 5.36001 3.63231 5.79606 3.47362C6.23211 3.31494 6.6952 3.24372 7.15889 3.26404C7.62258 3.28437 8.07778 3.39583 8.4985 3.59208C8.91923 3.78832 9.29723 4.06549 9.61094 4.40777C10.2352 5.10576 10.5572 6.02276 10.5064 6.95752C10.4555 7.89228 10.0359 8.76845 9.33963 9.39374Z" fill="none"></path><path d="M10.6166 6.57965L25.9987 6.58208"></path><path d="M18.4252 7.25862L18.4226 10.5309L23.3229 10.5368L23.3243 7.26568"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Add user.svg b/assets/icons/polkadot/line/Add user.svg
new file mode 100644
index 00000000..424af4f5
--- /dev/null
+++ b/assets/icons/polkadot/line/Add user.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.9991 9.00464V3.00464"></path><path d="M26.9991 6.00464L20.9991 6.00464"></path><path d="M10.5497 13.747L9.64035 12.6538C8.08843 10.788 8.21272 8.04735 9.92716 6.32973C11.7628 4.49069 14.7426 4.49069 16.5782 6.32973C18.2926 8.04735 18.4169 10.788 16.865 12.6538L15.9559 13.7467C15.3751 14.4449 15.7079 15.5097 16.5828 15.7531L17.8145 16.0956C21.187 17.0335 23.5206 20.1046 23.5206 23.6051V26.9816H2.99304V23.5992C2.99304 20.1017 5.32433 17.0331 8.69379 16.0954L9.92292 15.7533C10.7978 15.5099 11.1304 14.4451 10.5497 13.747Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Add.svg b/assets/icons/polkadot/line/Add.svg
new file mode 100644
index 00000000..f9dceb8c
--- /dev/null
+++ b/assets/icons/polkadot/line/Add.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9883 2C20.6157 2 25.9883 7.37258 25.9883 14C25.9883 20.6274 20.6157 26 13.9883 26C7.36086 26 1.98828 20.6274 1.98828 14C1.98828 7.37258 7.36086 2 13.9883 2Z"></path><path d="M8.7937 13.4606L19.1833 13.5167"></path><path d="M14.0176 8.29507L13.9614 18.6846"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Address book.svg b/assets/icons/polkadot/line/Address book.svg
new file mode 100644
index 00000000..5cb28bc3
--- /dev/null
+++ b/assets/icons/polkadot/line/Address book.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5 19.6359L2 19.6359"></path><path d="M5 8.32184L2 8.32184"></path><path d="M25.9999 2.00003L25.9999 26.0031L5.22522 26.003L5.22522 2.00003L25.9999 2.00003Z"></path><path d="M17.001 12.8205L17.5027 12.2248C18.4049 11.1536 18.333 9.56902 17.3374 8.58397C16.2905 7.54814 14.6048 7.54814 13.5579 8.58397C12.5623 9.56902 12.4904 11.1536 13.3926 12.2248L13.8942 12.8203C14.2261 13.2144 14.0379 13.8197 13.5411 13.9561L12.8161 14.1552C10.8827 14.6862 9.54258 16.444 9.54258 18.449V20.3358H21.3479V18.4457C21.3479 16.4423 20.0092 14.686 18.0775 14.1551L17.3539 13.9563C16.8572 13.8197 16.6691 13.2145 17.001 12.8205Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Airplane Mode.svg b/assets/icons/polkadot/line/Airplane Mode.svg
new file mode 100644
index 00000000..87799346
--- /dev/null
+++ b/assets/icons/polkadot/line/Airplane Mode.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 24" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.2538 19.1308L9.47419 22.7394L13.9318 21.6569L18.3887 22.7394L15.5932 19.1308L15.6222 14.682L25.8701 17.4504L15.666 9.53824L15.7125 4.08386C15.7348 1.47108 12.4046 1.44054 12.3823 4.05333L12.3356 9.53824L2.04451 17.4503L12.2917 14.682C12.2978 16.1649 12.2664 17.6479 12.2538 19.1308Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Alert.svg b/assets/icons/polkadot/line/Alert.svg
new file mode 100644
index 00000000..9c92c3ed
--- /dev/null
+++ b/assets/icons/polkadot/line/Alert.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9898 3.12793L2.19775 24.872H25.7818L13.9898 3.12793Z" stroke-miterlimit="10"></path><path d="M13.9992 17.7247L13.9897 10.5945" stroke-miterlimit="10"></path><path d="M14.0093 21.1309L13.9912 21.1128" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Algorithm.svg b/assets/icons/polkadot/line/Algorithm.svg
new file mode 100644
index 00000000..62b1d320
--- /dev/null
+++ b/assets/icons/polkadot/line/Algorithm.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M18.9557 22.7289H15.2495V5.42358H19.0515" fill="none" data-nofill="true"></path><path d="M11.9375 13.9775H14.9584"></path><path d="M26.7702 1.56445H19.0513V9.28338H26.7702V1.56445Z"></path><path d="M11.9378 13.9775L6.86572 8.9054L1.79361 13.9775L6.86572 19.0496L11.9378 13.9775Z"></path><path d="M22.9107 26.4355C25.0423 26.4355 26.7702 24.7075 26.7702 22.576C26.7702 20.4445 25.0423 18.7166 22.9107 18.7166C20.7792 18.7166 19.0513 20.4445 19.0513 22.576C19.0513 24.7075 20.7792 26.4355 22.9107 26.4355Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Alice.svg b/assets/icons/polkadot/line/Alice.svg
new file mode 100644
index 00000000..7259c905
--- /dev/null
+++ b/assets/icons/polkadot/line/Alice.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.0433 10.5398L11.0695 9.41161C9.51415 7.61093 9.63743 4.90867 11.3497 3.25618C13.0856 1.58127 15.8364 1.58127 17.5724 3.25618C19.2846 4.90867 19.4079 7.61093 17.8526 9.41161L16.8787 10.5386C16.3694 11.1276 23.9295 22.6689 23.9295 22.6689H19.444V26H9.48052V22.6689H5C5 22.6689 12.5514 11.1301 12.0433 10.5398Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Ambassadors.svg b/assets/icons/polkadot/line/Ambassadors.svg
new file mode 100644
index 00000000..41b3d380
--- /dev/null
+++ b/assets/icons/polkadot/line/Ambassadors.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3.3167 18.2338C4.07764 19.5517 5.76294 20.0033 7.08092 19.2424L8.54062 18.3913C12.7495 16.0327 17.4091 15.0552 21.0684 15.6442L17.7517 9.8996L14.4351 4.15498C13.1156 7.61851 9.93917 11.1651 5.79211 13.6308L4.32532 14.4695C3.00733 15.2305 2.55576 16.9158 3.3167 18.2338Z"></path><path d="M19.7145 5.64923C19.7145 5.64923 21.0466 6.40554 21.7209 7.54587C22.3951 8.6862 22.4218 10.192 22.4218 10.192" fill="none" data-nofill="true"></path><path d="M20.7148 2C20.7148 2 23.3154 3.47646 24.6316 5.70262C25.9479 7.92878 26 11.351 26 11.351" fill="none" data-nofill="true"></path><path d="M10.0083 17.53L8.63049 15.1436L7.25269 12.7572"></path><path d="M10.0161 17.5781L6.77264 19.4507L9.99432 25.0308L13.2378 23.1582L10.0161 17.5781Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Announcement.svg b/assets/icons/polkadot/line/Announcement.svg
new file mode 100644
index 00000000..15d158f3
--- /dev/null
+++ b/assets/icons/polkadot/line/Announcement.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.4009 21.0053C18.387 21.5294 22.8539 17.9122 23.378 12.9261C23.9021 7.93998 20.2849 3.47306 15.2988 2.94896C10.3127 2.42487 5.84576 6.04205 5.32166 11.0282C5.06161 13.5023 5.82119 15.8486 7.26172 17.6487L4.7449 23.6804L10.0308 19.9645C11.0454 20.5136 12.1823 20.8772 13.4009 21.0053Z"></path><path d="M14.5327 13.1188L14.5255 7.64001" stroke-miterlimit="10"></path><path d="M14.543 16.0295L14.5259 16.0124" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Anonymous Proxy.svg b/assets/icons/polkadot/line/Anonymous Proxy.svg
new file mode 100644
index 00000000..3d45f11e
--- /dev/null
+++ b/assets/icons/polkadot/line/Anonymous Proxy.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.2243 25.0435C24.7573 25.0435 26 23.8008 26 22.2679C26 20.7349 24.7573 19.4922 23.2243 19.4922C21.6914 19.4922 20.4487 20.7349 20.4487 22.2679C20.4487 23.8008 21.6914 25.0435 23.2243 25.0435Z"></path><path d="M4.77567 25.0434C6.30863 25.0434 7.55134 23.8007 7.55134 22.2677C7.55134 20.7348 6.30863 19.4921 4.77567 19.4921C3.24271 19.4921 2 20.7348 2 22.2677C2 23.8007 3.24271 25.0434 4.77567 25.0434Z"></path><path d="M4.77571 19.4975L4.77571 16.2949L22.8386 16.2949L22.8386 19.4975" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M11.2739 4.77561C11.2739 3.24265 12.5167 1.99994 14.0496 1.99994C15.5826 1.99994 16.8253 3.24265 16.8253 4.77561C16.8253 6.30857 15.5826 7.55128 14.0496 7.55128V9.38381M14.0496 12.8443V12.8545" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Arbitrary Message.svg b/assets/icons/polkadot/line/Arbitrary Message.svg
new file mode 100644
index 00000000..ac803df0
--- /dev/null
+++ b/assets/icons/polkadot/line/Arbitrary Message.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.5083 9.30676H2V21.9626H6.13717V25.9716L11.4003 21.9626H20.2912V16.3554"></path><path d="M19.6729 15.9608C23.095 15.9608 25.8691 13.1866 25.8691 9.76457C25.8691 6.3425 23.095 3.56836 19.6729 3.56836C16.2508 3.56836 13.4767 6.3425 13.4767 9.76457C13.4767 13.1866 16.2508 15.9608 19.6729 15.9608Z"></path><path d="M17.0001 10.0568L18.7652 11.5684L22.0001 8.56836"></path><path d="M7.01814 16.0181L7 16" stroke-miterlimit="10"></path><path d="M11.0181 16.0181L11 16" stroke-miterlimit="10"></path><path d="M15.0544 16.0181L15.0363 16" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Archive Node.svg b/assets/icons/polkadot/line/Archive Node.svg
new file mode 100644
index 00000000..3cd82bd3
--- /dev/null
+++ b/assets/icons/polkadot/line/Archive Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5358 21.0126L18.5124 16.611"></path><path d="M9.50999 16.6247L6.44708 20.999"></path><path d="M20.4564 23.2116C20.4564 24.7425 21.6974 25.9834 23.2282 25.9834C24.759 25.9834 26 24.7425 26 23.2116C26 21.6808 24.759 20.4398 23.2282 20.4398C21.6974 20.4398 20.4564 21.6808 20.4564 23.2116Z"></path><path d="M2.00001 23.2116C2.00001 24.7425 3.24099 25.9834 4.77183 25.9834C6.30266 25.9834 7.54364 24.7425 7.54364 23.2116C7.54364 21.6808 6.30266 20.4398 4.77183 20.4398C3.24099 20.4398 2.00001 21.6808 2.00001 23.2116Z"></path><path d="M5.99593 10.0054C5.99593 14.4267 9.58006 18.0108 14.0013 18.0108C18.4226 18.0108 22.0067 14.4267 22.0067 10.0054C22.0067 5.58414 18.4226 2 14.0013 2C9.58006 2 5.99593 5.58414 5.99593 10.0054Z" stroke-miterlimit="10"></path><path d="M12.1736 12.0799L16.1694 8.08414"></path><path d="M16.1693 12.0799L12.1736 8.08414"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Arrow Back.svg b/assets/icons/polkadot/line/Arrow Back.svg
new file mode 100644
index 00000000..96b70a2a
--- /dev/null
+++ b/assets/icons/polkadot/line/Arrow Back.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21 26L7 13.988L21 2" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Arrow Down.svg b/assets/icons/polkadot/line/Arrow Down.svg
new file mode 100644
index 00000000..045e4672
--- /dev/null
+++ b/assets/icons/polkadot/line/Arrow Down.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9914 25L13.9914 2" fill="none" data-nofill="true"></path><path d="M24 15.8003L13.9914 26L4 15.8003" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Arrow Left.svg b/assets/icons/polkadot/line/Arrow Left.svg
new file mode 100644
index 00000000..2342bc53
--- /dev/null
+++ b/assets/icons/polkadot/line/Arrow Left.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 13.9914L26 13.9914" fill="none" data-nofill="true"></path><path d="M12.1997 24L2 13.9914L12.1997 4" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Arrow Right.svg b/assets/icons/polkadot/line/Arrow Right.svg
new file mode 100644
index 00000000..81832ba2
--- /dev/null
+++ b/assets/icons/polkadot/line/Arrow Right.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 14.0086L2 14.0086" fill="none" data-nofill="true"></path><path d="M15.8003 4L26 14.0086L15.8003 24" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Arrow Up.svg b/assets/icons/polkadot/line/Arrow Up.svg
new file mode 100644
index 00000000..5dcddb82
--- /dev/null
+++ b/assets/icons/polkadot/line/Arrow Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.0086 3L14.0086 26" fill="none" data-nofill="true"></path><path d="M4 12.1997L14.0086 2L24 12.1997" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Article.svg b/assets/icons/polkadot/line/Article.svg
new file mode 100644
index 00000000..160e6701
--- /dev/null
+++ b/assets/icons/polkadot/line/Article.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M5.19507 27.0057V1.5332H17.9313L24.7893 8.39118V27.0057H5.19507Z"></path><path d="M24.5 8.85798H18V2"></path><path d="M14.0125 5.45215H9.11389V10.3507H14.0125V5.45215Z" stroke-miterlimit="10"></path><path d="M9.11382 17.2087H20.8704" stroke-miterlimit="10"></path><path d="M9.11382 23.0869H20.8704" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Attack.svg b/assets/icons/polkadot/line/Attack.svg
new file mode 100644
index 00000000..4c767bcc
--- /dev/null
+++ b/assets/icons/polkadot/line/Attack.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 2C7.37258 2 2 7.37258 2 14C2 16.1857 2.58437 18.235 3.60539 20H7.32682V26H20.6602V20H24.3946C25.4156 18.235 26 16.1857 26 14C26 7.37258 20.6274 2 14 2Z"></path><circle cx="9.28605" cy="13.0698" r="1.88557"></circle><circle cx="18.7139" cy="13.0698" r="1.88557"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Auctions.svg b/assets/icons/polkadot/line/Auctions.svg
new file mode 100644
index 00000000..43075259
--- /dev/null
+++ b/assets/icons/polkadot/line/Auctions.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M17.2186 1.99999L6.34143 12.8772L11.78 18.3158L22.6572 7.43859L17.2186 1.99999Z" stroke-miterlimit="10"></path><path d="M18.5783 11.5176L15.859 14.2369L23.2641 21.6421L25.9834 18.9228L18.5783 11.5176Z" stroke-miterlimit="10"></path><path d="M14.4984 26L2 26" stroke-miterlimit="10"></path><path d="M12.5756 22.6308L3.92285 22.6308" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Authority.svg b/assets/icons/polkadot/line/Authority.svg
new file mode 100644
index 00000000..13e04e75
--- /dev/null
+++ b/assets/icons/polkadot/line/Authority.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 30 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M12.3081 11.555L10.9968 7.84508C10.4958 6.42792 10.7907 4.85109 11.7698 3.71065C13.4453 1.75907 16.4658 1.75907 18.1413 3.71065C19.1204 4.85109 19.4153 6.42792 18.9143 7.84508L17.6032 11.5545C17.2574 12.5328 17.6423 13.6197 18.5268 14.1623L23.9184 17.4701V22.4414H6V17.4696L11.3852 14.1626C12.2692 13.6197 12.6538 12.5331 12.3081 11.555Z"></path><path d="M22.1264 26.3617H8.25928"></path><path d="M6.55548 17.9524L23.3402 17.9524"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Back Up.svg b/assets/icons/polkadot/line/Back Up.svg
new file mode 100644
index 00000000..1f1b9fdc
--- /dev/null
+++ b/assets/icons/polkadot/line/Back Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M13.9981 25.5L13.9981 10.5M10.3377 12.9485L14 9.28807L17.6654 12.9474"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Balance.svg b/assets/icons/polkadot/line/Balance.svg
new file mode 100644
index 00000000..124dd5f8
--- /dev/null
+++ b/assets/icons/polkadot/line/Balance.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 4H2V24.219H26V4Z"></path><path d="M15.6374 10.8382H13.4541C13.0244 10.8393 12.6127 11.011 12.309 11.3155C12.0054 11.6201 11.8346 12.0327 11.834 12.4631V12.4826C11.8346 12.913 12.0054 13.3256 12.309 13.6302C12.6127 13.9347 13.0244 14.1064 13.4541 14.1075H14.5371C14.7507 14.1067 14.9623 14.148 15.1599 14.2293C15.3575 14.3106 15.5371 14.4302 15.6884 14.5811C15.8398 14.7321 15.9598 14.9115 16.0418 15.1091C16.1237 15.3066 16.1659 15.5185 16.1659 15.7324C16.1664 15.9465 16.1248 16.1586 16.0432 16.3566C15.9617 16.5545 15.8419 16.7343 15.6907 16.8857C15.5396 17.0371 15.36 17.1571 15.1624 17.2388C14.9648 17.3205 14.753 17.3622 14.5393 17.3616H12.1719"></path><path d="M13.9959 10.7942V9.63696"></path><path d="M13.9959 18.5815V17.514"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Batch Transaction.svg b/assets/icons/polkadot/line/Batch Transaction.svg
new file mode 100644
index 00000000..ad06cefb
--- /dev/null
+++ b/assets/icons/polkadot/line/Batch Transaction.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M25.4728 16L15.4728 26" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M12 2.61932L2 12.6193" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M2.10724 26L25.5 2.60724" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M20.4478 15.3989L25.9819 15.3807L26 20.9302" fill="none" data-nofill="true"></path><path d="M6.97498 2.01823L12.5091 2L12.5272 7.54949" fill="none" data-nofill="true"></path><path d="M20.4478 2.01823L25.9819 2L26 7.54949" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Bid.svg b/assets/icons/polkadot/line/Bid.svg
new file mode 100644
index 00000000..486284bd
--- /dev/null
+++ b/assets/icons/polkadot/line/Bid.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.5053 19.0106C18.2027 19.0106 22.0106 15.2027 22.0106 10.5053C22.0106 5.80796 18.2027 2 13.5053 2C8.80796 2 5 5.80796 5 10.5053C5 15.2027 8.80796 19.0106 13.5053 19.0106Z"></path><path d="M10.1033 10.4833L12.5053 13.3403L16.9075 7.67007"></path><path d="M13.5054 26L13.5054 19.0107" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Block Explorer.svg b/assets/icons/polkadot/line/Block Explorer.svg
new file mode 100644
index 00000000..099cbc94
--- /dev/null
+++ b/assets/icons/polkadot/line/Block Explorer.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="4" y="2" width="20" height="24"></rect><path d="M19.4584 8.33936L11.9206 8.33936M8.43256 8.33936L8.42177 8.33936"></path><path d="M19.4584 13.75L11.9206 13.75M8.43256 13.75L8.42177 13.75"></path><path d="M19.4584 19.3394L11.9206 19.3394M8.43256 19.3394L8.42177 19.3394"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Block Number.svg b/assets/icons/polkadot/line/Block Number.svg
new file mode 100644
index 00000000..f1085491
--- /dev/null
+++ b/assets/icons/polkadot/line/Block Number.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 14.4276H4.57235"></path><path d="M23.4277 14.4276H26"></path><path d="M23.4277 5H4.57235V23.8553H23.4277V5Z"></path><path d="M11.8745 10.114L11.8745 18.599" stroke-miterlimit="10"></path><path d="M16.1651 10.114L16.1651 18.599" stroke-miterlimit="10"></path><path d="M18.2623 12.2115L9.77731 12.2115" stroke-miterlimit="10"></path><path d="M18.2623 16.5021L9.77731 16.5021" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Block Search.svg b/assets/icons/polkadot/line/Block Search.svg
new file mode 100644
index 00000000..909abf5b
--- /dev/null
+++ b/assets/icons/polkadot/line/Block Search.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.831 19.662C18.7088 19.662 22.662 15.7078 22.662 10.831C22.662 5.95423 18.7088 2 13.831 2C8.95327 2 5 5.95423 5 10.831C5 15.7078 8.95423 19.662 13.831 19.662Z" stroke-miterlimit="10"></path><path d="M10.8704 7.93085H16.6735V13.7302H10.8704V7.93085Z"></path><path d="M19.7446 17.3763C18.5887 18.4218 17.1612 19.1706 15.5734 19.4883L19.3318 26L23.3734 23.6662L19.7446 17.3763Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Block.svg b/assets/icons/polkadot/line/Block.svg
new file mode 100644
index 00000000..8ffae0f4
--- /dev/null
+++ b/assets/icons/polkadot/line/Block.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 14C26 20.6274 20.6274 26 14 26C7.37254 26 1.99996 20.6274 1.99996 14C1.99996 7.37258 7.37254 2 14 2C20.6274 2 26 7.37258 26 14Z"></path><path d="M5.75624 22.47L22.4838 5.74284"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Blockchain.svg b/assets/icons/polkadot/line/Blockchain.svg
new file mode 100644
index 00000000..61175e9d
--- /dev/null
+++ b/assets/icons/polkadot/line/Blockchain.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M11.2309 2H2V11.2309H11.2309V2Z"></path><path d="M11.2308 16.7692H2V26H11.2308V16.7692Z"></path><path d="M26.0001 2H16.7692V11.2309H26.0001V2Z"></path><path d="M26 16.7692H16.7692V26H26V16.7692Z"></path><path d="M11.3457 6.7023H16.7692"></path><path d="M16.5569 21.534L11.3457 21.534"></path><path d="M11.1746 16.8253L16.8262 11.1737"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Blog Post.svg b/assets/icons/polkadot/line/Blog Post.svg
new file mode 100644
index 00000000..956ece00
--- /dev/null
+++ b/assets/icons/polkadot/line/Blog Post.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M22.8977 4.21835C23.8359 3.2802 25.3573 3.2802 26.2964 4.21835C27.2345 5.15651 27.2345 6.67794 26.2964 7.61704L19.1979 14.7155L14.5345 15.9764L15.7993 11.3177L22.8977 4.2193V4.21835Z"></path><path d="M19.1978 14.7156L14.5344 15.9765L15.7991 11.3178L22.8975 4.21941C23.2515 3.86454 23.6884 3.64463 24.1462 3.5578V3H3V26.1962L11.651 21.2005H24.1462V9.76716L19.1978 14.7156Z"></path><path d="M11.1708 15.9766H7.32574"></path><path d="M16.8356 9.25095H6.98218"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Bob.svg b/assets/icons/polkadot/line/Bob.svg
new file mode 100644
index 00000000..5043e52d
--- /dev/null
+++ b/assets/icons/polkadot/line/Bob.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.0297 11.5875L11.1215 10.5361C9.67139 8.85746 9.78596 6.33823 11.3824 4.79815C13.001 3.23677 15.5651 3.23677 17.1837 4.79815C18.7801 6.33823 18.8947 8.85746 17.4446 10.5361L16.5366 11.5872C16.0621 12.1365 16.2218 12.9845 16.8636 13.3235L18.4551 14.1643C21.6036 15.8277 23.5735 19.0963 23.5735 22.6572L23.5736 26H5.00006L5.00004 22.6523C5.00002 19.094 6.96791 15.8274 10.1136 14.1642L11.703 13.3238C12.3446 12.9845 12.5042 12.1367 12.0297 11.5875Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Bond.svg b/assets/icons/polkadot/line/Bond.svg
new file mode 100644
index 00000000..13e01451
--- /dev/null
+++ b/assets/icons/polkadot/line/Bond.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M20.5726 6.52721C20.5726 9.02776 17.5323 11.0549 13.781 11.0549C10.0971 11.0549 7.10583 9.09799 7 6.65902V10.0861C7 12.5866 10.0403 14.6138 13.7916 14.6138C17.5429 14.6138 20.5832 12.5866 20.5832 10.0861C20.5832 9.77725 20.6621 6.81873 20.5736 6.52625L20.5726 6.52721Z"></path><path d="M13.8078 11.0555C17.5582 11.0555 20.5994 9.02828 20.5994 6.52773C20.5994 4.02719 17.5591 2 13.8078 2C10.0565 2 7.01621 4.02719 7.01621 6.52773C7.01621 9.02828 10.0565 11.0555 13.8078 11.0555Z"></path><path d="M13.8081 26L13.8081 19.3212M10.1068 22.0224L13.808 18.3212L17.5093 22.0224" stroke-miterlimit="10" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Bonded Time.svg b/assets/icons/polkadot/line/Bonded Time.svg
new file mode 100644
index 00000000..6c915451
--- /dev/null
+++ b/assets/icons/polkadot/line/Bonded Time.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7.55817 8.82291L7.55818 6.82267V6.82267C7.55818 4.15918 9.71736 2 12.3808 2V2C15.0443 2 17.2035 4.15918 17.2035 6.82267V6.82267L17.2035 8.82291" fill="none"></path><path d="M21.7615 13.2941V8.82581H3V22.4706H13.9412"></path><path d="M19.941 26C23.4496 26 26.294 23.1557 26.294 19.6471C26.294 16.1384 23.4496 13.2941 19.941 13.2941C16.4324 13.2941 13.5881 16.1384 13.5881 19.6471C13.5881 23.1557 16.4324 26 19.941 26Z"></path><path d="M20.063 17.1428V19.853L19 21.1428"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Boot Node.svg b/assets/icons/polkadot/line/Boot Node.svg
new file mode 100644
index 00000000..473c4274
--- /dev/null
+++ b/assets/icons/polkadot/line/Boot Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5358 21.0126L18.5124 16.6109"></path><path d="M9.50999 16.6247L6.44708 20.999"></path><path d="M20.4564 23.2116C20.4564 24.7425 21.6974 25.9834 23.2282 25.9834C24.759 25.9834 26 24.7425 26 23.2116C26 21.6808 24.759 20.4398 23.2282 20.4398C21.6974 20.4398 20.4564 21.6808 20.4564 23.2116Z"></path><path d="M2.00001 23.2116C2.00001 24.7425 3.24099 25.9834 4.77183 25.9834C6.30266 25.9834 7.54364 24.7425 7.54364 23.2116C7.54364 21.6808 6.30266 20.4398 4.77183 20.4398C3.24099 20.4398 2.00001 21.6808 2.00001 23.2116Z"></path><path d="M5.99593 10.0054C5.99593 14.4267 9.58006 18.0108 14.0013 18.0108C18.4226 18.0108 22.0067 14.4267 22.0067 10.0054C22.0067 5.58414 18.4226 2 14.0013 2C9.58006 2 5.99593 5.58414 5.99593 10.0054Z" stroke-miterlimit="10"></path><path d="M14.0012 6.57411L14.0012 12.5M11.0078 10.4461L14.0012 13.4394L16.9945 10.4461"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Bridge.svg b/assets/icons/polkadot/line/Bridge.svg
new file mode 100644
index 00000000..7d5fc3bc
--- /dev/null
+++ b/assets/icons/polkadot/line/Bridge.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.9986 20.3965L25 8.39652L3 8.39648L3.00008 20.3965L5.75 20.3965C5.75 20.3965 8.57808 16.3182 14.039 16.3182C19.5 16.3182 22.25 20.3965 22.25 20.3965L24.9986 20.3965Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Bridges.svg b/assets/icons/polkadot/line/Bridges.svg
new file mode 100644
index 00000000..7849a067
--- /dev/null
+++ b/assets/icons/polkadot/line/Bridges.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.9344 11.1342L5.93432 7.39648L26 7.39651L25.9986 18.0195H22.2622"></path><path d="M22.0643 22.3474L22.0656 11.331L2 11.3309L2.00008 22.3473L4.5082 22.3474C4.5082 22.3474 7.08762 18.6034 12.0684 18.6034C17.0492 18.6034 19.5574 22.3473 19.5574 22.3473L22.0643 22.3474Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Build.svg b/assets/icons/polkadot/line/Build.svg
new file mode 100644
index 00000000..93e3ab5b
--- /dev/null
+++ b/assets/icons/polkadot/line/Build.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M4 22.5743V12.0632L13.0655 16.4888V27L4 22.5743Z"></path><path d="M26.16 22.5743V12.0632L17.0945 16.4888V27L26.16 22.5743Z"></path><path d="M13.0268 3.97772L15.08 3L17.1332 3.97772M13.0268 11.7994L15.08 12.7772L17.1332 11.7994M22.9017 9.05252L25.346 7.88858L22.9017 6.72463M7.25825 6.72463L4.81396 7.88858L7.25825 9.05252" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Builders _ Developers.svg b/assets/icons/polkadot/line/Builders _ Developers.svg
new file mode 100644
index 00000000..308a14a9
--- /dev/null
+++ b/assets/icons/polkadot/line/Builders _ Developers.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 24 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8 7V6C8 3.791 9.791 2 12 2C14.209 2 16 3.791 16 6V7H8Z"></path><path d="M18 7H6"></path><path d="M16.458 15.565L15.222 15.227C14.383 14.997 14.066 13.975 14.627 13.311L15.467 12.317C16.761 10.786 16.862 8.638 15.849 7H8.14202C7.12902 8.637 7.23002 10.785 8.52402 12.317L9.36402 13.311C9.92502 13.975 9.60802 14.997 8.76902 15.227L7.53602 15.565C4.26602 16.461 1.99902 19.432 1.99902 22.823V26H22V22.828C22 19.435 19.731 16.461 16.458 15.565Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Built-in Security.svg b/assets/icons/polkadot/line/Built-in Security.svg
new file mode 100644
index 00000000..f26e553f
--- /dev/null
+++ b/assets/icons/polkadot/line/Built-in Security.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.7808 24.1821L17.2887 26.9686L23.0111 23.6745L21.9164 20.1316L22.354 18.8179L26.3849 18.1253V11.3141L22.7723 10.4881L21.9463 9.055L23.0908 5.51209L17.3783 2.21797L14.8306 4.95478H13.2084L10.7105 2.16821L4.98805 5.46233L6.09273 9.06495L5.30652 10.4383L1.60437 11.2146V17.8227L5.27666 18.6587L6.07282 20.0321L4.89848 23.6247L10.6209 26.9288L13.1587 24.1821H14.7808Z" stroke-miterlimit="10"></path><path d="M18.3612 13.521H9.63867V19.0227H18.3612V13.521Z"></path><path d="M11.2649 13.2998V11.3034C11.2649 10.578 11.553 9.88235 12.066 9.36943C12.5789 8.85651 13.2746 8.56836 13.9999 8.56836C14.7235 8.57115 15.4164 8.86054 15.9271 9.37316C16.4377 9.88577 16.7244 10.5798 16.7244 11.3034V13.2998"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Burn.svg b/assets/icons/polkadot/line/Burn.svg
new file mode 100644
index 00000000..2bb64dad
--- /dev/null
+++ b/assets/icons/polkadot/line/Burn.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7.04912 19.2857C7.52476 22.6895 10.158 25 13.3536 25C17.5634 25 19.5687 22.8234 19.953 19.2857C20.2632 16.4294 18.9369 12.3422 18.9369 12.3422L16.5333 16.8182L13.3536 5L10.4667 12.2727L8.44959 9.01993C8.44959 9.01993 6.68661 16.6916 7.04912 19.2857Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/C++.svg b/assets/icons/polkadot/line/C++.svg
new file mode 100644
index 00000000..d6cc128a
--- /dev/null
+++ b/assets/icons/polkadot/line/C++.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 26 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 20.4615L13.0769 26L24.1538 20.4615V7.53846L13.0769 2L2 7.53846V20.4615Z"></path><path d="M14.29 18.9378C13.5147 19.306 12.6612 19.4994 11.7948 19.5031C10.9284 19.5068 10.0719 19.3207 9.29088 18.9592C8.50984 18.5976 7.82488 18.07 7.28834 17.4168C6.7518 16.7635 6.37787 16.0019 6.19513 15.1901C6.01239 14.3783 6.02567 13.5378 6.23396 12.7328C6.44225 11.9278 6.84003 11.1796 7.39691 10.5454C7.95379 9.91125 8.65504 9.40783 9.44707 9.07363C10.2391 8.73943 11.101 8.58331 11.9668 8.61719C12.8355 8.64962 13.6852 8.87373 14.4498 9.27204"></path><path d="M12.0288 14.0482L15.0229 14.0482" stroke-miterlimit="10"></path><path d="M13.526 12.5582L13.526 15.539" stroke-miterlimit="10"></path><path d="M18.1739 14.0482L21.168 14.0482" stroke-miterlimit="10"></path><path d="M19.6711 12.5582L19.6711 15.539" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Calendar.svg b/assets/icons/polkadot/line/Calendar.svg
new file mode 100644
index 00000000..39b6535c
--- /dev/null
+++ b/assets/icons/polkadot/line/Calendar.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M18.6289 26H2V3.88452H26V18.9448V26H18.6289Z" stroke-miterlimit="10"></path><path d="M9.42346 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34183V2.00012" stroke-miterlimit="10"></path><path d="M3 11.2501H25" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Career.svg b/assets/icons/polkadot/line/Career.svg
new file mode 100644
index 00000000..dadc5600
--- /dev/null
+++ b/assets/icons/polkadot/line/Career.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M10.3813 7.45019V3H19.6192V7.5" fill="none"></path><path d="M27 7.62796H3V24.2377H27V7.62796Z"></path><path d="M4 14.3445L26 14.3445"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Certificate.svg b/assets/icons/polkadot/line/Certificate.svg
new file mode 100644
index 00000000..687ee391
--- /dev/null
+++ b/assets/icons/polkadot/line/Certificate.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.9559 19.3827V26.7229H4.38208V1.27689H23.9559V20.381"></path><path d="M16.9644 13.0457L20.0411 14.3537V5.00011L13.89 5V14.3606L16.9644 13.0457Z" stroke-miterlimit="10"></path><path d="M20.0411 22.8083H8.29675" stroke-miterlimit="10"></path><path d="M20.0411 18.8933H8.29675" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Cex.svg b/assets/icons/polkadot/line/Cex.svg
new file mode 100644
index 00000000..56e9c6c8
--- /dev/null
+++ b/assets/icons/polkadot/line/Cex.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.0019 7.29055C15.5315 7.29055 16.7715 6.05026 16.7715 4.52028C16.7715 2.99029 15.5315 1.75 14.0019 1.75C12.4723 1.75 11.2323 2.99029 11.2323 4.52028C11.2323 6.05026 12.4723 7.29055 14.0019 7.29055Z"></path><path d="M7.47419 25.7403C9.00379 25.7403 10.2438 24.5001 10.2438 22.9701C10.2438 21.4401 9.00379 20.1998 7.47419 20.1998C5.94458 20.1998 4.70459 21.4401 4.70459 22.9701C4.70459 24.5001 5.94458 25.7403 7.47419 25.7403Z"></path><path d="M4.7696 14.6779C6.2992 14.6779 7.53919 13.4376 7.53919 11.9076C7.53919 10.3777 6.2992 9.13736 4.7696 9.13736C3.23999 9.13736 2 10.3777 2 11.9076C2 13.4376 3.23999 14.6779 4.7696 14.6779Z"></path><path d="M23.2332 14.6779C24.7628 14.6779 26.0028 13.4376 26.0028 11.9076C26.0028 10.3777 24.7628 9.13736 23.2332 9.13736C21.7036 9.13736 20.4636 10.3777 20.4636 11.9076C20.4636 13.4376 21.7036 14.6779 23.2332 14.6779Z"></path><path d="M20.4551 25.75C21.9847 25.75 23.2247 24.5097 23.2247 22.9797C23.2247 21.4497 21.9847 20.2094 20.4551 20.2094C18.9255 20.2094 17.6855 21.4497 17.6855 22.9797C17.6855 24.5097 18.9255 25.75 20.4551 25.75Z"></path><path d="M14.0006 18.63C16.1827 18.63 17.9517 16.8606 17.9517 14.678C17.9517 12.4953 16.1827 10.726 14.0006 10.726C11.8185 10.726 10.0496 12.4953 10.0496 14.678C10.0496 16.8606 11.8185 18.63 14.0006 18.63Z"></path><path d="M11.501 17.965L8.92651 20.5395"></path><path d="M16.4661 18.0051L19.0005 20.5394"></path><path d="M14.0012 10.726L14.0012 7.29065"></path><path d="M10.1505 13.7689L7.41382 12.8087M17.8281 13.7583L20.5886 12.8087"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Chain Spec.svg b/assets/icons/polkadot/line/Chain Spec.svg
new file mode 100644
index 00000000..616e632d
--- /dev/null
+++ b/assets/icons/polkadot/line/Chain Spec.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.8289 2.00001L25.4517 8.6228L18.7983 15.2762L12.1755 8.65344L18.8289 2.00001Z"></path><path d="M8.61599 12.1604L15.2388 18.7832L8.62279 25.3992L1.99999 18.7764L8.61599 12.1604Z"></path><path d="M17.9941 9.41468L9.42018 17.9886"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Check.svg b/assets/icons/polkadot/line/Check.svg
new file mode 100644
index 00000000..09432dfc
--- /dev/null
+++ b/assets/icons/polkadot/line/Check.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 13.9459L10.7663 21L25 7" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Checked.svg b/assets/icons/polkadot/line/Checked.svg
new file mode 100644
index 00000000..24a433b8
--- /dev/null
+++ b/assets/icons/polkadot/line/Checked.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 2H2V26H26V2Z"></path><path d="M8.99963 14.3184L12.6078 17.6884L19.2205 11"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Chevron Down.svg b/assets/icons/polkadot/line/Chevron Down.svg
new file mode 100644
index 00000000..b9282b1e
--- /dev/null
+++ b/assets/icons/polkadot/line/Chevron Down.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25.9883 8.5625L14.9772 21.5625L3.98828 8.5625" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Chevron Up.svg b/assets/icons/polkadot/line/Chevron Up.svg
new file mode 100644
index 00000000..f1f9d634
--- /dev/null
+++ b/assets/icons/polkadot/line/Chevron Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 21.1309L14.011 8.13086L25 21.1309" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Claim.svg b/assets/icons/polkadot/line/Claim.svg
new file mode 100644
index 00000000..b2069f6b
--- /dev/null
+++ b/assets/icons/polkadot/line/Claim.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.00001 26V2H17L23.4615 8.46154V26H5.00001Z"></path><path d="M22.5 8.46155H17V3"></path><path d="M15.9251 12.7784H13.6415C13.4179 12.7769 13.1962 12.8196 12.9892 12.9041C12.7822 12.9885 12.5939 13.1132 12.4353 13.2707C12.2766 13.4283 12.1507 13.6157 12.0648 13.8221C11.9789 14.0285 11.9346 14.2499 11.9346 14.4735C11.9378 14.9241 12.119 15.3552 12.4387 15.6728C12.7585 15.9903 13.1908 16.1685 13.6415 16.1685H14.8186C15.2692 16.1685 15.7016 16.3467 16.0214 16.6643C16.3411 16.9818 16.5223 17.4129 16.5254 17.8636C16.5352 18.0976 16.4967 18.3312 16.4123 18.5497C16.328 18.7682 16.1995 18.967 16.035 19.1337C15.8705 19.3005 15.6734 19.4315 15.456 19.5188C15.2387 19.6061 15.0057 19.6477 14.7715 19.641H12.2996"></path><path d="M14.2065 12.7308V11.4595"></path><path d="M14.2065 20.9713V19.7589"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Close.svg b/assets/icons/polkadot/line/Close.svg
new file mode 100644
index 00000000..ba586549
--- /dev/null
+++ b/assets/icons/polkadot/line/Close.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M4.89252 4.23135L24.6915 24.0303" fill="none" data-nofill="true"></path><path d="M24.6915 4.23135L4.89248 24.0303" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Cloud.svg b/assets/icons/polkadot/line/Cloud.svg
new file mode 100644
index 00000000..85e9e6c2
--- /dev/null
+++ b/assets/icons/polkadot/line/Cloud.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M22.4647 22.2436H9.06277C5.71439 22.2436 3 19.5292 3 16.1809C3 12.8325 5.71439 10.1181 9.06277 10.1181C9.50272 10.1181 9.93174 10.165 10.3451 10.254C10.5 8.85565 11.9169 7.05177 13.0652 6.24989C16.1449 4.09916 20.3438 4.79319 22.4436 7.80005C23.7349 9.64905 23.5 11.8557 23.256 13.7969C24.2553 13.8564 25.2376 14.2679 26.0011 15.0315C27.6574 16.6877 27.6574 19.373 26.0011 21.0292C25.0632 21.9671 23.741 22.2495 22.5711 22.2495"></path><path d="M13.7635 12.3517C12.9098 11.3049 11.7132 10.5486 10.3451 10.254M20.0034 15.0315C20.8961 14.1388 22.0877 13.7273 23.2561 13.7969"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Code.svg b/assets/icons/polkadot/line/Code.svg
new file mode 100644
index 00000000..9d2a51c5
--- /dev/null
+++ b/assets/icons/polkadot/line/Code.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7.97391 18.5638L2.00391 13.5938L7.97391 8.61377" fill="none" data-nofill="true"></path><path d="M20.0737 8.604L26.0637 13.594L20.0737 18.574" fill="none" data-nofill="true"></path><path d="M17.0488 4.59375L10.9988 22.5837" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Collapse.svg b/assets/icons/polkadot/line/Collapse.svg
new file mode 100644
index 00000000..70d19dc8
--- /dev/null
+++ b/assets/icons/polkadot/line/Collapse.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.00927 25.9096L14.5662 18.0334L21.1362 25.9096" fill="none" data-nofill="true"></path><path d="M21.1357 3.13086L14.5525 11.0334L7.9824 3.13086" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Collators.svg b/assets/icons/polkadot/line/Collators.svg
new file mode 100644
index 00000000..0902dcd1
--- /dev/null
+++ b/assets/icons/polkadot/line/Collators.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.3843 16.3044L21.3844 11.4024L6.61576 11.4027L6.61559 16.3047" fill="none" data-nofill="true"></path><path d="M11.2307 16.3044H2V25.5351H11.2307V16.3044Z"></path><path d="M26 16.3044H16.7693V25.5351H26V16.3044Z"></path><path d="M10.245 5.87389L14.081 2.01263L17.9358 5.8421" fill="none" data-nofill="true"></path><path d="M14.0001 3.64456V11.1735" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Collective.svg b/assets/icons/polkadot/line/Collective.svg
new file mode 100644
index 00000000..0e9ae3bb
--- /dev/null
+++ b/assets/icons/polkadot/line/Collective.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.8277 19.1904C25.5298 15.9686 25.5343 12.0847 23.8414 8.85944M19.139 4.17209C15.8766 2.47308 11.9466 2.50626 8.71031 4.27164M4.18173 8.88422C2.50178 12.1046 2.51068 15.9769 4.20841 19.1904M19.152 23.8449C15.9452 25.5204 12.0909 25.5204 8.88413 23.8449" fill="none" data-nofill="true"></path><circle cx="21.8596" cy="6.1703" r="3.32689" transform="rotate(45 21.8596 6.1703)"></circle><circle cx="6.17678" cy="21.8533" r="3.32689" transform="rotate(45 6.17678 21.8533)"></circle><circle cx="6.17645" cy="6.1703" r="3.32689" transform="rotate(45 6.17645 6.1703)"></circle><circle cx="21.8596" cy="21.8535" r="3.32689" transform="rotate(45 21.8596 21.8535)"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Communications And Media.svg b/assets/icons/polkadot/line/Communications And Media.svg
new file mode 100644
index 00000000..846bd572
--- /dev/null
+++ b/assets/icons/polkadot/line/Communications And Media.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M15.5589 17.9552C14.2554 19.7707 12.0408 20.8544 9.65901 20.6041C8.79582 20.5134 7.99056 20.2558 7.27188 19.8668L3.52769 22.4989L5.31043 18.2265C4.29006 16.9514 3.75202 15.2894 3.93623 13.5369C4.23879 10.6584 6.39652 8.42401 9.09652 7.89684"></path><path d="M15.9185 2.77813C20.0071 2.34838 23.6699 5.31441 24.0996 9.40294C24.3128 11.4317 23.69 13.3556 22.5088 14.8317L24.5725 19.7775L20.2382 16.7306C19.4062 17.1808 18.474 17.479 17.4748 17.584C16.5998 17.676 15.7442 17.6124 14.9357 17.4156C11.9665 16.6928 9.63149 14.1727 9.29372 10.9592C9.17739 9.85252 9.30987 8.77702 9.64607 7.78839C10.5519 5.12465 12.9367 3.09156 15.9185 2.77813Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Community Events And Outreach.svg b/assets/icons/polkadot/line/Community Events And Outreach.svg
new file mode 100644
index 00000000..c98dd271
--- /dev/null
+++ b/assets/icons/polkadot/line/Community Events And Outreach.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.6289 26.5685H2V4.453H26V19.5133V26.5685H18.6289Z" stroke-miterlimit="10"></path><path d="M9.4234 6.91007V2.56836" stroke-miterlimit="10"></path><path d="M18.5766 6.91031V2.5686" stroke-miterlimit="10"></path><path d="M2.10089 11.8185H25.9999" stroke-miterlimit="10"></path><path d="M20 25.7112C20 23.62 18.6356 21.7857 16.6643 21.2257L15.9439 21.0206C15.432 20.8756 15.2372 20.2396 15.5768 19.8225L16.1083 19.1694C17.0157 18.0553 16.9432 16.4181 15.9409 15.392C14.8682 14.2938 13.1259 14.2938 12.0532 15.392C11.0509 16.4181 10.9785 18.0553 11.8858 19.1694L12.4173 19.8225C12.7569 20.2396 12.5631 20.8756 12.0512 21.0206L11.3328 21.2247C9.36248 21.7847 8 23.618 8 25.7072"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Community.svg b/assets/icons/polkadot/line/Community.svg
new file mode 100644
index 00000000..f1302854
--- /dev/null
+++ b/assets/icons/polkadot/line/Community.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Companion Account (in Bridge context).svg b/assets/icons/polkadot/line/Companion Account (in Bridge context).svg
new file mode 100644
index 00000000..f9dbc720
--- /dev/null
+++ b/assets/icons/polkadot/line/Companion Account (in Bridge context).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.322 12.0015L15.1859 10.9629C16.6598 9.19058 16.5418 6.58738 14.913 4.95579C13.1691 3.20899 10.3393 3.20899 8.59532 4.95579C6.96656 6.58738 6.84853 9.19058 8.32244 10.9629L9.1864 12.0015C9.73782 12.6643 9.42245 13.6765 8.5906 13.9069L7.42072 14.2327C4.21701 15.1231 2 18.0407 2 21.3662L2 24.5737H21.4999V21.3605C21.4999 18.0378 19.2857 15.1231 16.0848 14.2327L14.9168 13.9079C14.0859 13.6765 13.7696 12.6643 14.322 12.0015Z"></path><path d="M12.7102 3.74915C13.5175 3.92572 14.2861 4.32795 14.914 4.9568C16.5428 6.5884 16.6608 9.19159 15.1869 10.9639L14.3229 12.0025C13.7715 12.6653 14.0869 13.6766 14.9178 13.9079L16.0858 14.2327C19.2866 15.1231 21.5008 18.0379 21.5008 21.3606V22.927H26V19.7139C26 16.3912 23.7858 13.4764 20.5849 12.586L19.417 12.2612C18.586 12.0299 18.2697 11.0186 18.8221 10.3558L19.6861 9.31717C21.16 7.54489 21.0419 4.94169 19.4132 3.31009C17.6692 1.5633 14.8394 1.5633 13.0955 3.31009C12.9557 3.44984 12.8282 3.59619 12.7102 3.74915Z"></path></svg>
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diff --git a/assets/icons/polkadot/line/Connect Wallet_Address.svg b/assets/icons/polkadot/line/Connect Wallet_Address.svg
new file mode 100644
index 00000000..f6e9b4fa
--- /dev/null
+++ b/assets/icons/polkadot/line/Connect Wallet_Address.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.1556 15.7924L14.1556 20.4568"></path><path d="M26 23.2284L16.8586 23.2284M2 23.2284L11.2816 23.2284"></path><path d="M14.0751 26C15.608 26 16.8507 24.7591 16.8507 23.2284C16.8507 21.6977 15.608 20.4568 14.0751 20.4568C12.5421 20.4568 11.2994 21.6977 11.2994 23.2284C11.2994 24.7591 12.5421 26 14.0751 26Z"></path><path d="M22.3687 2H6V15.79H22.3687V2Z"></path><path d="M21.56 5.67551H16.6018C14.8237 5.67551 13.3823 7.1169 13.3823 8.89496C13.3823 10.673 14.8237 12.1144 16.6018 12.1144H21.56C22.0117 12.1144 22.3778 11.7483 22.3778 11.2966V6.49328C22.3778 6.04164 22.0117 5.67551 21.56 5.67551Z"></path><path d="M16.438 8.85698L16.4228 8.84174" stroke-miterlimit="10"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Connected.svg b/assets/icons/polkadot/line/Connected.svg
new file mode 100644
index 00000000..573c4ef5
--- /dev/null
+++ b/assets/icons/polkadot/line/Connected.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M17.4675 18.6279L22.241 18.6279C24.8532 18.6279 26.9708 16.5103 26.9708 13.8981V13.8981C26.9708 11.2859 24.8532 9.16832 22.241 9.16832L17.4675 9.16832" fill="none" data-nofill="true"></path><path d="M12.4206 9.13085L7.70051 9.13085C5.08831 9.13085 2.9707 11.2485 2.9707 13.8607V13.8607C2.9707 16.4728 5.08831 18.5905 7.70051 18.5905L12.4206 18.5905" fill="none" data-nofill="true"></path><path d="M21.079 13.8675L8.83264 13.8675" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Connection Via Light Node.svg b/assets/icons/polkadot/line/Connection Via Light Node.svg
new file mode 100644
index 00000000..c96f6bdf
--- /dev/null
+++ b/assets/icons/polkadot/line/Connection Via Light Node.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Connection Via Remote Node.svg b/assets/icons/polkadot/line/Connection Via Remote Node.svg
new file mode 100644
index 00000000..d61052f4
--- /dev/null
+++ b/assets/icons/polkadot/line/Connection Via Remote Node.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Consensus.svg b/assets/icons/polkadot/line/Consensus.svg
new file mode 100644
index 00000000..14edb247
--- /dev/null
+++ b/assets/icons/polkadot/line/Consensus.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 2C20.6274 2 26 6.00877 26 10.9538C26 13.3124 24.7688 15.392 22.7711 16.9912L24.4427 23.6403L18.283 19.247C17.7411 19.3992 16.9172 19.5922 16.2083 19.6813L14.0407 24.6403L11.5962 19.657C10.9222 19.5699 10.2602 19.3957 9.72631 19.248L3.55603 23.6431L5.23852 16.9971C3.24087 15.3979 2 13.3124 2 10.9538C2 6.00877 7.37258 2 14 2Z"></path><path d="M9.38666 11.0673L13.0277 14.468L19.7007 7.71863"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Contract.svg b/assets/icons/polkadot/line/Contract.svg
new file mode 100644
index 00000000..798c1bdf
--- /dev/null
+++ b/assets/icons/polkadot/line/Contract.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.5874 17.1336L14.457 18.11L15.4333 13.9786L20.3809 9.03099V8.99469V2.16336H2.16339V25.8459H11.2721H20.3809V15.3411L18.5874 17.1336Z"></path><path d="M16.7372 5.80707H5.80707" stroke-miterlimit="10"></path><path d="M12.1833 9.44983H5.80707" stroke-miterlimit="10"></path><path d="M12.1824 21.2892H5.80707" stroke-miterlimit="10"></path><path d="M22.0282 7.38367C22.8993 6.51253 24.3121 6.51253 25.1833 7.38367C26.0544 8.2548 26.0544 9.6676 25.1833 10.5387L18.5883 17.1337L14.457 18.11L15.4333 13.9786L22.0282 7.38367Z"></path></svg>
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diff --git a/assets/icons/polkadot/line/Cooling Period.svg b/assets/icons/polkadot/line/Cooling Period.svg
new file mode 100644
index 00000000..abe7a3c5
--- /dev/null
+++ b/assets/icons/polkadot/line/Cooling Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 26H2V3.88452H26V26Z" stroke-miterlimit="10"></path><path d="M9.42337 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34177V2.00006" stroke-miterlimit="10"></path><path d="M19.2884 18.2949L17.1375 16.1441M17.1375 16.1441L19.2885 13.9931M17.1375 16.1441L11.1802 16.1441M9.00003 13.9931L11.1509 16.144L8.99999 18.295"></path><path d="M11.9934 21.2884L14.1443 19.1375M14.1443 19.1375L16.2952 21.2885M14.1443 19.1375L14.1443 13.1802M16.2952 11L14.1443 13.1509L11.9934 11"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Copy _ Paste.svg b/assets/icons/polkadot/line/Copy _ Paste.svg
new file mode 100644
index 00000000..474d3012
--- /dev/null
+++ b/assets/icons/polkadot/line/Copy _ Paste.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M8.99414 8.5V2H25.9941V19H19.4941"></path><path d="M18.9941 9H1.99414V26H18.9941V9Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Costly To Maintain.svg b/assets/icons/polkadot/line/Costly To Maintain.svg
new file mode 100644
index 00000000..4de82f7e
--- /dev/null
+++ b/assets/icons/polkadot/line/Costly To Maintain.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7.81383 3.91949H4.48675C4.16099 3.91723 3.83801 3.97944 3.5364 4.10253C3.2348 4.22563 2.96053 4.40718 2.72939 4.63673C2.49824 4.86628 2.3148 5.13929 2.18962 5.44003C2.06444 5.74078 1.99999 6.06332 2 6.38908C2.00453 7.04563 2.26852 7.67374 2.73439 8.13639C3.20025 8.59904 3.83018 8.85868 4.48675 8.85867H6.20174C6.8583 8.85865 7.48822 9.11829 7.95408 9.58094C8.41995 10.0436 8.68394 10.6717 8.68847 11.3283C8.70273 11.6692 8.64666 12.0095 8.52374 12.3279C8.40082 12.6462 8.21367 12.9359 7.97397 13.1788C7.73427 13.4217 7.44715 13.6127 7.13045 13.7398C6.81375 13.867 6.47427 13.9276 6.13314 13.9179H2.53166" fill="none" data-nofill="true"></path><path d="M5.31042 3.85219V2"></path><path d="M5.30995 15.856V14.0896"></path><path d="M13.6198 16.3551C13.1888 15.4931 12.9409 14.5233 12.9409 13.4996C12.9409 9.97602 15.7964 7.12053 19.32 7.12053C20.3652 7.12053 21.3565 7.37914 22.2294 7.82093L18.0916 11.9695L21.141 15.0189L25.1818 10.9674C25.5159 11.7432 25.7098 12.5945 25.7098 13.4996C25.7098 17.0232 22.8543 19.8787 19.3308 19.8787C18.4148 19.8787 17.542 19.6847 16.7554 19.3291L9.89058 26L6.84113 22.9505L13.6198 16.3551Z" stroke-miterlimit="10"></path></svg>
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diff --git a/assets/icons/polkadot/line/Council.svg b/assets/icons/polkadot/line/Council.svg
new file mode 100644
index 00000000..4336c1db
--- /dev/null
+++ b/assets/icons/polkadot/line/Council.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.6501 14.6921H23.9518C23.8887 12.3445 22.3113 10.3001 20.0372 9.6682L19.1896 9.43278C18.5879 9.26516 18.3591 8.53252 18.7583 8.05226L19.3836 7.29985C20.4515 6.01632 20.3658 4.13011 19.1859 2.94923C17.9231 1.68359 15.873 1.68359 14.6102 2.94923C13.4302 4.13105 13.3455 6.01632 14.4124 7.29985L15.0377 8.05226C15.437 8.53252 15.2082 9.26516 14.6064 9.43278L13.7608 9.6682C12.4735 10.026 11.4207 10.8463 10.7266 11.9075C10.7426 12.2607 10.9724 12.595 11.3547 12.7014L12.2004 12.9368C14.21 13.4962 15.6781 15.1583 16.035 17.1575H19.6482L19.6501 14.6921Z"></path><path d="M10.9254 11.3208L11.5506 10.5684C12.6185 9.28489 12.5328 7.39868 11.3529 6.2178C10.0901 4.95216 8.04002 4.95216 6.77721 6.2178C5.59727 7.39962 5.51251 9.28489 6.57945 10.5684L7.20474 11.3208C7.60401 11.8011 7.37518 12.5337 6.77344 12.7014L5.92592 12.9368C3.60559 13.5818 2 15.695 2 18.1038V20.427H16.1235V18.1001C16.1235 15.6941 14.5198 13.5828 12.2014 12.9368L11.3557 12.7014C10.754 12.5337 10.5251 11.8011 10.9244 11.3208H10.9254Z"></path><path d="M26 25.1949V14.6922H19.6511V25.2005L22.8246 23.9085L26 25.1949Z"></path></svg>
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diff --git a/assets/icons/polkadot/line/Countdown.svg b/assets/icons/polkadot/line/Countdown.svg
new file mode 100644
index 00000000..49e87711
--- /dev/null
+++ b/assets/icons/polkadot/line/Countdown.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M6.99408 26.125L23.9941 26.125"></path><path d="M6.99414 2.125L23.9941 2.125"></path><path d="M21.9171 8.365V2.125L8.99402 2.125L8.99402 8.365L15.4556 14.125L21.9171 8.365Z"></path><path d="M8.9941 19.885L8.9941 26.125L21.9172 26.125L21.9172 19.885L15.4556 14.125L8.9941 19.885Z"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Create New From Source.svg b/assets/icons/polkadot/line/Create New From Source.svg
new file mode 100644
index 00000000..4527e980
--- /dev/null
+++ b/assets/icons/polkadot/line/Create New From Source.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.636 18.7083L18.636 25.125L3.05265 25.125L3.05266 9.54167L9.01099 9.54167"></path><path d="M9.4694 18.7083L25.0527 18.7083L25.0527 3.12498L9.4694 3.12498L9.4694 18.7083Z"></path><path d="M13.1581 10.8424L21.2598 10.8862"></path><path d="M17.2319 6.81445L17.1881 14.9161"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Cross-Chain Application.svg b/assets/icons/polkadot/line/Cross-Chain Application.svg
new file mode 100644
index 00000000..852e28dc
--- /dev/null
+++ b/assets/icons/polkadot/line/Cross-Chain Application.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M1.99997 26.4316L26.2441 26.4316L26.2441 2.43164L1.99997 2.43164L1.99997 26.4316Z"></path><path d="M26.2371 9.01086H2.00026"></path><path d="M9.32502 5.89942L9.30768 5.88208" stroke-miterlimit="10"></path><path d="M5.50117 5.89942L5.48383 5.88208" stroke-miterlimit="10"></path><path d="M19.1895 9.93164L19.1895 14.2167M19.1895 25.4316L19.1895 20.9517"></path><path d="M9 9.93164L9 14.2167M8.99998 25.4316L8.99998 20.9517"></path><path d="M12.2806 14.458H6V20.7386H12.2806V14.458Z"></path><path d="M22.3295 14.458H16.0489V20.7386H22.3295V14.458Z"></path><path d="M12.2808 17.5984L16.0493 17.5984"></path></svg>
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diff --git a/assets/icons/polkadot/line/Cross-Chain Certification.svg b/assets/icons/polkadot/line/Cross-Chain Certification.svg
new file mode 100644
index 00000000..10dfe874
--- /dev/null
+++ b/assets/icons/polkadot/line/Cross-Chain Certification.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Cross-Chain Transfers.svg b/assets/icons/polkadot/line/Cross-Chain Transfers.svg
new file mode 100644
index 00000000..d277d318
--- /dev/null
+++ b/assets/icons/polkadot/line/Cross-Chain Transfers.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Cross-Chain.svg b/assets/icons/polkadot/line/Cross-Chain.svg
new file mode 100644
index 00000000..17d77478
--- /dev/null
+++ b/assets/icons/polkadot/line/Cross-Chain.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Crowdloans.svg b/assets/icons/polkadot/line/Crowdloans.svg
new file mode 100644
index 00000000..93c0b349
--- /dev/null
+++ b/assets/icons/polkadot/line/Crowdloans.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Cryptocurrency.svg b/assets/icons/polkadot/line/Cryptocurrency.svg
new file mode 100644
index 00000000..9fe48c1a
--- /dev/null
+++ b/assets/icons/polkadot/line/Cryptocurrency.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Customisation.svg b/assets/icons/polkadot/line/Customisation.svg
new file mode 100644
index 00000000..29e6f8c5
--- /dev/null
+++ b/assets/icons/polkadot/line/Customisation.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/DAOs.svg b/assets/icons/polkadot/line/DAOs.svg
new file mode 100644
index 00000000..3e23d6da
--- /dev/null
+++ b/assets/icons/polkadot/line/DAOs.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/DEX.svg b/assets/icons/polkadot/line/DEX.svg
new file mode 100644
index 00000000..036953ef
--- /dev/null
+++ b/assets/icons/polkadot/line/DEX.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Dapps.svg b/assets/icons/polkadot/line/Dapps.svg
new file mode 100644
index 00000000..9db16584
--- /dev/null
+++ b/assets/icons/polkadot/line/Dapps.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Data & Analytics.svg b/assets/icons/polkadot/line/Data & Analytics.svg
new file mode 100644
index 00000000..aa9e2cb0
--- /dev/null
+++ b/assets/icons/polkadot/line/Data & Analytics.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Day_Light Mode.svg b/assets/icons/polkadot/line/Day_Light Mode.svg
new file mode 100644
index 00000000..50b4c80f
--- /dev/null
+++ b/assets/icons/polkadot/line/Day_Light Mode.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/DeFi.svg b/assets/icons/polkadot/line/DeFi.svg
new file mode 100644
index 00000000..12c9a2d8
--- /dev/null
+++ b/assets/icons/polkadot/line/DeFi.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Decentralised File Storage.svg b/assets/icons/polkadot/line/Decentralised File Storage.svg
new file mode 100644
index 00000000..6c1821b5
--- /dev/null
+++ b/assets/icons/polkadot/line/Decentralised File Storage.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Delete_Cancel.svg b/assets/icons/polkadot/line/Delete_Cancel.svg
new file mode 100644
index 00000000..4f3dce41
--- /dev/null
+++ b/assets/icons/polkadot/line/Delete_Cancel.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Democracy.svg b/assets/icons/polkadot/line/Democracy.svg
new file mode 100644
index 00000000..8311f6f6
--- /dev/null
+++ b/assets/icons/polkadot/line/Democracy.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.4073 14.0779C17.4073 12.8246 17.4246 8.15076 17.4355 5.31269C17.4403 4.07636 16.4394 3.07286 15.203 3.07286V3.07286C13.9702 3.07286 12.9708 4.07226 12.9708 5.30509L12.9708 11.4237L12.9707 3.94594C12.9707 2.87123 11.9692 2 10.7339 2C9.49861 2 8.49719 2.87122 8.49719 3.94593L8.49719 11.4237L8.49719 7.09448C8.49719 6.01976 7.47206 5.14854 6.23674 5.14854C5.00142 5.14854 4 6.01976 4 7.09448L4 11.9943L4.00004 15.3687C4.00013 19.1459 7.76403 20.6571 7.76403 20.6571L7.76403 26L16.0785 26L16.0785 20.6571C16.0785 20.6571 17.3382 20.3811 20.3229 18.1508C23.0038 16.1475 23.4183 14.1302 23.4749 13.7403C23.4815 13.6948 23.4831 13.6499 23.4831 13.6038V13.6038C23.4831 11.9579 21.3989 11.1732 20.2377 12.3396C18.791 13.7928 17.4073 14.9538 17.4073 14.0779Z"></path></svg>
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diff --git a/assets/icons/polkadot/line/Deposit.svg b/assets/icons/polkadot/line/Deposit.svg
new file mode 100644
index 00000000..604f1ddc
--- /dev/null
+++ b/assets/icons/polkadot/line/Deposit.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.706 26L6 26" fill="none" data-nofill="true"></path><path d="M14.4865 2L14.4865 20.5M20.0165 15.921L14.4865 21.4482L8.95172 15.9227" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Derivation Path.svg b/assets/icons/polkadot/line/Derivation Path.svg
new file mode 100644
index 00000000..9c7f7163
--- /dev/null
+++ b/assets/icons/polkadot/line/Derivation Path.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Derive An Address.svg b/assets/icons/polkadot/line/Derive An Address.svg
new file mode 100644
index 00000000..e04b5da2
--- /dev/null
+++ b/assets/icons/polkadot/line/Derive An Address.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Derive Key Pair.svg b/assets/icons/polkadot/line/Derive Key Pair.svg
new file mode 100644
index 00000000..b34b1367
--- /dev/null
+++ b/assets/icons/polkadot/line/Derive Key Pair.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Disconnected.svg b/assets/icons/polkadot/line/Disconnected.svg
new file mode 100644
index 00000000..aeb1c115
--- /dev/null
+++ b/assets/icons/polkadot/line/Disconnected.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Distributed File Storage.svg b/assets/icons/polkadot/line/Distributed File Storage.svg
new file mode 100644
index 00000000..d2128aea
--- /dev/null
+++ b/assets/icons/polkadot/line/Distributed File Storage.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2.98242 5H12.0874L15.3605 7.76827H26.9824V23H2.98242V5Z"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Documentations.svg b/assets/icons/polkadot/line/Documentations.svg
new file mode 100644
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--- /dev/null
+++ b/assets/icons/polkadot/line/Documentations.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Download.svg b/assets/icons/polkadot/line/Download.svg
new file mode 100644
index 00000000..714a30a5
--- /dev/null
+++ b/assets/icons/polkadot/line/Download.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Draw.svg b/assets/icons/polkadot/line/Draw.svg
new file mode 100644
index 00000000..6c4d1fde
--- /dev/null
+++ b/assets/icons/polkadot/line/Draw.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.7143 23L26 16.5714L17.7827 17.0116M4.14286 6.28571L17.4286 2L2 17.8571L7.15792 17.5808" fill="none" data-nofill="true"></path><path d="M18.8649 6.05542L23.6589 10.8494L11.1359 23.3723L4.82555 24.8887L6.342 18.5784L18.8649 6.05542Z"></path><path d="M20.2346 14.2736L15.4407 9.47968M18.8649 6.05542L23.6589 10.8494L11.1359 23.3723L4.82555 24.8887L6.342 18.5784L18.8649 6.05542Z"></path></svg>
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diff --git a/assets/icons/polkadot/line/Drip.svg b/assets/icons/polkadot/line/Drip.svg
new file mode 100644
index 00000000..09c49e63
--- /dev/null
+++ b/assets/icons/polkadot/line/Drip.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M7 17.8836C7 23.4036 10.0031 26 14 26C17.9969 26 21 23.4036 21 17.8836C21 12.3636 14 3 14 3C14 3 7 12.3636 7 17.8836Z"></path></svg>
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diff --git a/assets/icons/polkadot/line/Dropdown Up.svg b/assets/icons/polkadot/line/Dropdown Up.svg
new file mode 100644
index 00000000..7f51aede
--- /dev/null
+++ b/assets/icons/polkadot/line/Dropdown Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 19.9167L14 8L3 19.9167H25Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Dropdown.svg b/assets/icons/polkadot/line/Dropdown.svg
new file mode 100644
index 00000000..17c1a46e
--- /dev/null
+++ b/assets/icons/polkadot/line/Dropdown.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 8L14 19.9167L25 8.00001L3 8Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Ecosystem Provisions.svg b/assets/icons/polkadot/line/Ecosystem Provisions.svg
new file mode 100644
index 00000000..07a009ba
--- /dev/null
+++ b/assets/icons/polkadot/line/Ecosystem Provisions.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Ecosystem.svg b/assets/icons/polkadot/line/Ecosystem.svg
new file mode 100644
index 00000000..7e041ed8
--- /dev/null
+++ b/assets/icons/polkadot/line/Ecosystem.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Edit-Off.svg b/assets/icons/polkadot/line/Edit-Off.svg
new file mode 100644
index 00000000..05450ad3
--- /dev/null
+++ b/assets/icons/polkadot/line/Edit-Off.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.8064 12.0645L15.9355 6.19357M20.129 2L26 7.87097L16.5346 17.3364L15.2654 18.6056L10.6636 23.2074L2.93548 25.0645L4.79262 17.3364L9.454 12.675L10.675 11.454L20.129 2Z"></path><path d="M2.33716 4.37223L23.6872 25.7223"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Edit-On.svg b/assets/icons/polkadot/line/Edit-On.svg
new file mode 100644
index 00000000..4ba03b68
--- /dev/null
+++ b/assets/icons/polkadot/line/Edit-On.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Elections.svg b/assets/icons/polkadot/line/Elections.svg
new file mode 100644
index 00000000..669e7af5
--- /dev/null
+++ b/assets/icons/polkadot/line/Elections.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M25.8716 14.9436V26H2L2.02488 15.7534"></path><path d="M17.0029 5.76299H22.1341L25.8725 14.8704V15.8763H2.00092V14.8695L5.77523 5.76299H10.8696"></path><path d="M8.27478 10.5318H19.5977"></path><path d="M17.0029 2H10.8696V10.5318H17.0029V2Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Email.svg b/assets/icons/polkadot/line/Email.svg
new file mode 100644
index 00000000..c93e32fa
--- /dev/null
+++ b/assets/icons/polkadot/line/Email.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 4H2V24.219H26V4Z"></path><path d="M3 5.31509L14 15.3151L25 5.31509"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Encryption.svg b/assets/icons/polkadot/line/Encryption.svg
new file mode 100644
index 00000000..45bcde6a
--- /dev/null
+++ b/assets/icons/polkadot/line/Encryption.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.12128 9.66582L8.1213 7.41847V7.41847C8.1213 4.42593 10.5472 2 13.5398 2V2C16.5323 2 18.9582 4.42593 18.9582 7.41847V7.41847L18.9582 9.66582" fill="none"></path><path d="M24.0794 9.66956H3V25H24.0794V9.66956Z"></path><path d="M9.59457 14.9474L6.78784 17.2887L9.5 19.5465"></path><path d="M17.4755 19.6253L20.2916 17.284L17.5979 15.04"></path><path d="M15.1113 12.5991L11.9587 21.9733"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Ending Period.svg b/assets/icons/polkadot/line/Ending Period.svg
new file mode 100644
index 00000000..e45a6462
--- /dev/null
+++ b/assets/icons/polkadot/line/Ending Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M13.9999 13.3519L5.87173 13.352"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Energy Deficiency.svg b/assets/icons/polkadot/line/Energy Deficiency.svg
new file mode 100644
index 00000000..787818b4
--- /dev/null
+++ b/assets/icons/polkadot/line/Energy Deficiency.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M6.52649 19.5832C8.22267 21.8663 10.9457 23.3465 14.0158 23.3465C19.1583 23.3465 23.3271 19.1934 23.3271 14.0702C23.3271 8.94703 19.5563 4.71485 14.4137 4.71485C13.155 4.71485 10.988 5.20555 9.89277 5.65653" stroke-dasharray="0.1 4.5" fill="none"></path><path d="M13.7787 10.2817L12.5601 14.1408H15.4713L14.1173 17.9999" fill="none"></path><path d="M5.30628 14.8423C5.19187 12.8048 5.74122 10.8835 6.76633 9.28875" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Energy Efficiency.svg b/assets/icons/polkadot/line/Energy Efficiency.svg
new file mode 100644
index 00000000..40c69fe2
--- /dev/null
+++ b/assets/icons/polkadot/line/Energy Efficiency.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.182 8.77164C20.2215 7.47849 18.9257 6.46269 17.4263 5.83979C15.6073 5.08408 13.5899 4.94877 11.6863 5.4548C9.78259 5.96083 8.09869 7.07999 6.89499 8.63919C5.69129 10.1984 5.03486 12.1108 5.02722 14.0805L5.08337 14.9644M8.45708 12.3279L5.1379 15.7374L1.72839 12.4182" fill="none"></path><path d="M6.78601 19.3839C7.73403 20.6646 9.01094 21.6752 10.4902 22.3024C12.3113 23.0746 14.3367 23.2226 16.2506 22.7233C18.1646 22.224 19.8596 21.1055 21.0714 19.5421C22.2831 17.9787 22.9436 16.0583 22.9498 14.0803L22.9047 13.2071M19.5096 15.7431L22.84 12.4092L26.2383 15.6764" fill="none"></path><path d="M13.8499 10.2246L12.6312 14.0837H15.5425L14.1884 17.9428" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Energy.svg b/assets/icons/polkadot/line/Energy.svg
new file mode 100644
index 00000000..80701add
--- /dev/null
+++ b/assets/icons/polkadot/line/Energy.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 18 27" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2.02344 4.875L2.02344 25L15.9877 25L15.9877 4.875L12.2727 4.875L12.2913 2L5.73844 2L5.73844 4.875L2.02344 4.875Z"></path><path d="M8.78498 9.28687L7.08417 14.6728H11.1473L9.25747 20.0588"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Enterprise.svg b/assets/icons/polkadot/line/Enterprise.svg
new file mode 100644
index 00000000..b02958b4
--- /dev/null
+++ b/assets/icons/polkadot/line/Enterprise.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.7057 26L22.7057 2.56836L7.79767 2.56836L7.79767 26"></path><path d="M4.54956 26.5681L25.8959 26.5681"></path><path d="M17.5428 25.7709V19.2742H12.9023V25.7709"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Error.svg b/assets/icons/polkadot/line/Error.svg
new file mode 100644
index 00000000..0c7ac72a
--- /dev/null
+++ b/assets/icons/polkadot/line/Error.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 2C20.6274 2 26 7.37258 26 14C26 20.6274 20.6274 26 14 26C7.37258 26 2 20.6274 2 14C2 7.37258 7.37258 2 14 2Z"></path><path d="M10.3075 17.6221L17.6938 10.3153"></path><path d="M10.3489 10.2756L17.6558 17.6619"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Eve.svg b/assets/icons/polkadot/line/Eve.svg
new file mode 100644
index 00000000..bd901f2e
--- /dev/null
+++ b/assets/icons/polkadot/line/Eve.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.0297 11.5875L11.1215 10.5361C9.67139 8.85746 9.78596 6.33823 11.3824 4.79815C13.001 3.23677 15.5651 3.23677 17.1837 4.79815C18.7801 6.33823 18.8947 8.85746 17.4446 10.5361L16.5366 11.5872C16.0621 12.1365 16.2218 12.9845 16.8636 13.3235L18.4551 14.1643C21.6036 15.8277 23.5735 19.0963 23.5736 22.6572L23.5736 22.9455H18.4943V26H9.35223L9.35223 22.9455H5.00006L5.00006 22.6523C5.00002 19.094 6.96792 15.8274 10.1136 14.1642L11.703 13.3238C12.3446 12.9845 12.5042 12.1367 12.0297 11.5875Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Events.svg b/assets/icons/polkadot/line/Events.svg
new file mode 100644
index 00000000..5d76d90c
--- /dev/null
+++ b/assets/icons/polkadot/line/Events.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M18.6289 26H2V3.88454H26V18.9448L18.6289 26Z" stroke-miterlimit="10"></path><path d="M9.42334 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34178V2.00008" stroke-miterlimit="10"></path><path d="M2.10101 11.2501H26" stroke-miterlimit="10"></path><path d="M18.4785 25.2163V18.4537H25.6592" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Existential Deposit.svg b/assets/icons/polkadot/line/Existential Deposit.svg
new file mode 100644
index 00000000..5cdda962
--- /dev/null
+++ b/assets/icons/polkadot/line/Existential Deposit.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 20.5V26H26V20.5" fill="none" data-nofill="true"></path><circle cx="14" cy="12.5" r="8"></circle><path d="M15.7943 9.02179H13.4727C13.0158 9.02301 12.578 9.20551 12.2551 9.52934C11.9322 9.85317 11.7506 10.2919 11.75 10.7496V10.7704C11.7506 11.228 11.9322 11.6668 12.2551 11.9906C12.578 12.3145 13.0158 12.497 13.4727 12.4982H14.6243C14.8514 12.4973 15.0765 12.5413 15.2866 12.6277C15.4967 12.7141 15.6876 12.8413 15.8486 13.0018C16.0095 13.1623 16.1372 13.3531 16.2243 13.5632C16.3114 13.7733 16.3563 13.9985 16.3563 14.226C16.3569 14.4537 16.3125 14.6792 16.2258 14.8897C16.1391 15.1002 16.0117 15.2914 15.851 15.4524C15.6903 15.6134 15.4994 15.741 15.2892 15.8278C15.0791 15.9147 14.8539 15.959 14.6266 15.9584H12.1093"></path><path d="M14.0488 8.97504V7.74445"></path><path d="M14.0488 17.2556V16.1204"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Export (M,L).svg b/assets/icons/polkadot/line/Export (M,L).svg
new file mode 100644
index 00000000..037a25ef
--- /dev/null
+++ b/assets/icons/polkadot/line/Export (M,L).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.7238 26L21.7238 10.2763L6.00002 10.2763L6.00002 26L21.7238 26Z"></path><path d="M10.1466 5.71254L13.859 2.0001L17.5777 5.71254" fill="none" data-nofill="true"></path><path d="M10.1466 5.71238L13.859 1.99994L17.5777 5.71238" fill="none" data-nofill="true"></path><path d="M13.8619 2.78161L13.8619 17.5825"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Export (XS,S).svg b/assets/icons/polkadot/line/Export (XS,S).svg
new file mode 100644
index 00000000..91768f25
--- /dev/null
+++ b/assets/icons/polkadot/line/Export (XS,S).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.1464 5.7126L13.8589 2.00016L17.5775 5.7126" fill="none" data-nofill="true"></path><path d="M6.00002 26.0001L22 26.0001L22 22.3334L22 15.0001L6.00001 15.0001L6 22.3334L6.00002 26.0001Z"></path><path d="M10.1464 5.71244L13.8589 2L17.5775 5.71244" fill="none" data-nofill="true"></path><path d="M13.8617 3L13.8617 17.5825" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Extension.svg b/assets/icons/polkadot/line/Extension.svg
new file mode 100644
index 00000000..7cf63d30
--- /dev/null
+++ b/assets/icons/polkadot/line/Extension.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M9.44828 6.1379H2V13.5862H3.65517C5.02636 13.5862 6.13794 14.6978 6.13794 16.069C6.13794 17.4402 5.02636 18.5517 3.65517 18.5517H2V26H9.44828V24.3448C9.44828 22.9736 10.5599 21.8621 11.9311 21.8621C13.3022 21.8621 14.4138 22.9736 14.4138 24.3448V26H21.8621V17.7241H23.5172C24.8884 17.7241 26 16.6126 26 15.2414C26 13.8702 24.8884 12.7586 23.5172 12.7586H21.8621V6.1379H14.4138V4.48273C14.4138 3.11154 13.3022 2 11.9311 2C10.5599 2 9.44828 3.11154 9.44828 4.48273V6.1379Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Favorite To-Be.svg b/assets/icons/polkadot/line/Favorite To-Be.svg
new file mode 100644
index 00000000..42597465
--- /dev/null
+++ b/assets/icons/polkadot/line/Favorite To-Be.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25.2741 11.3007L20.1148 17.125L20.8486 24.8295L13.6485 21.7798L6.47138 24.8524L7.18222 17.1479L2 11.3466L9.63574 9.64975L13.6256 3L17.6384 9.64975L25.2741 11.3007Z" stroke-miterlimit="10" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Favorite.svg b/assets/icons/polkadot/line/Favorite.svg
new file mode 100644
index 00000000..22de1107
--- /dev/null
+++ b/assets/icons/polkadot/line/Favorite.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 11.055L20.6798 17.1851L21.4365 25.2942L14.0118 22.0844L6.61084 25.3184L7.34384 17.2092L2 11.1032L9.87389 9.31731L13.9882 2.31836L18.1261 9.31731L26 11.055Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Feeless.svg b/assets/icons/polkadot/line/Feeless.svg
new file mode 100644
index 00000000..5458f705
--- /dev/null
+++ b/assets/icons/polkadot/line/Feeless.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 12.6799V16.6799C26 21.0982 20.6274 24.1799 14 24.1799C7.37258 24.1799 2 21.0982 2 16.6799V12.6799"></path><path d="M14 20.6799C20.6274 20.6799 26 17.0982 26 12.6799C26 8.26165 20.6274 4.67993 14 4.67993C7.37258 4.67993 2 8.26165 2 12.6799C2 17.0982 7.37258 20.6799 14 20.6799Z"></path><path d="M4.64807 25.8601L23.352 2.99976"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Fees.svg b/assets/icons/polkadot/line/Fees.svg
new file mode 100644
index 00000000..ab4523d7
--- /dev/null
+++ b/assets/icons/polkadot/line/Fees.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="18.8311" y="5.73572" width="4.08857" height="4.08857"></rect><path d="M7.33884 18.557L5.29456 22.6456H7.33884H9.38313L7.33884 18.557Z"></path><path d="M7.21388 12.205L4.39465 14.6213L1.97833 11.8021" fill="none" data-nofill="true"></path><path d="M20.8415 15.5617L23.6641 13.205L26.0754 15.983" fill="none" data-nofill="true"></path><path d="M13.2449 23.7238C18.9729 24.242 23.6304 19.5894 23.6304 14M14.9682 4.67616C9.20961 4.15517 5.25915 8.51366 4.52261 13.8284" fill="none" data-nofill="true"></path><path d="M15.386 11.7097H13.591C13.2377 11.7107 12.8991 11.8518 12.6495 12.1022C12.3998 12.3526 12.2594 12.6918 12.2589 13.0457V13.0617C12.2594 13.4156 12.3998 13.7549 12.6495 14.0053C12.8991 14.2557 13.2377 14.3968 13.591 14.3977H14.4814C14.657 14.397 14.831 14.431 14.9934 14.4979C15.1559 14.5647 15.3036 14.663 15.428 14.7871C15.5524 14.9112 15.6511 15.0588 15.7185 15.2212C15.7859 15.3836 15.8205 15.5578 15.8205 15.7337C15.821 15.9097 15.7867 16.0841 15.7197 16.2469C15.6526 16.4096 15.5541 16.5575 15.4299 16.6819C15.3056 16.8064 15.158 16.9051 14.9955 16.9722C14.833 17.0394 14.6589 17.0737 14.4831 17.0732H12.5367" fill="none" data-nofill="true"></path><path d="M14.0365 11.6736V10.722" fill="none" data-nofill="true"></path><path d="M14.0365 18.0763V17.1986" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Fiat.svg b/assets/icons/polkadot/line/Fiat.svg
new file mode 100644
index 00000000..107e7b01
--- /dev/null
+++ b/assets/icons/polkadot/line/Fiat.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M8.88812 8.29893C9.93968 4.66101 13.296 2 17.273 2C22.093 2 26 5.907 26 10.727C26 14.7103 23.3309 18.0703 19.6837 19.1166"></path><path d="M10.727 25.9989C15.5468 25.9989 19.454 22.0917 19.454 17.2719C19.454 12.4521 15.5468 8.54492 10.727 8.54492C5.90721 8.54492 2 12.4521 2 17.2719C2 22.0917 5.90721 25.9989 10.727 25.9989Z"></path><path d="M12.6849 13.478H10.1519C9.65395 13.479 9.17595 13.678 8.82395 14.032C8.47195 14.385 8.27395 14.864 8.27295 15.363V15.386C8.27295 15.885 8.47195 16.364 8.82395 16.717C9.17595 17.07 9.65395 17.269 10.1519 17.271H11.4079C11.6559 17.271 11.9009 17.318 12.1299 17.412C12.3589 17.506 12.5679 17.645 12.7429 17.82C12.9189 17.995 13.0579 18.203 13.1529 18.432C13.2479 18.661 13.2969 18.907 13.2969 19.155C13.2969 19.403 13.2489 19.649 13.1549 19.879C13.0599 20.109 12.9209 20.317 12.7459 20.493C12.5709 20.669 12.3619 20.808 12.1329 20.903C11.9039 20.998 11.6579 21.046 11.4099 21.045H8.66395"></path><path d="M10.781 13.427V12.084"></path><path d="M10.781 22.4599V21.2219"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Filter.svg b/assets/icons/polkadot/line/Filter.svg
new file mode 100644
index 00000000..0092bc16
--- /dev/null
+++ b/assets/icons/polkadot/line/Filter.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 8.0388H25"></path><path d="M19.5 10.3959L19.5 5.68166"></path><path d="M3 15.1102H25"></path><path d="M7.71429 17.4673L7.71429 12.753"></path><path d="M3 22.4435H25"></path><path d="M14 24.5388L14 19.8245"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Finances.svg b/assets/icons/polkadot/line/Finances.svg
new file mode 100644
index 00000000..cd71e9e6
--- /dev/null
+++ b/assets/icons/polkadot/line/Finances.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Fork.svg b/assets/icons/polkadot/line/Fork.svg
new file mode 100644
index 00000000..a53598e7
--- /dev/null
+++ b/assets/icons/polkadot/line/Fork.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.6821 9.85657H2V18.5387H10.6821V9.85657Z"></path><path d="M25.9999 3H17.3177V11.6822H25.9999V3Z"></path><path d="M25.9998 16.8913H17.3177V25.5735H25.9998V16.8913Z"></path><path d="M16.5927 8.5L11.2624 12.2323"></path><path d="M11.2333 16.3355L16.7327 20.1862"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/ForklessUpgrades.svg b/assets/icons/polkadot/line/ForklessUpgrades.svg
new file mode 100644
index 00000000..b8f39298
--- /dev/null
+++ b/assets/icons/polkadot/line/ForklessUpgrades.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M25.5743 6.69975L16.368 6.69975M15.9292 21.3911L18.6861 17.517M11.6479 21.3911L9.07848 17.7086M9.07848 12.7338L11.4805 9.39406" stroke-miterlimit="10"></path><path d="M25.5737 15.2132L23.1141 15.2132M2 15.2131L4.57076 15.2131M10.4359 15.2132L17.4014 15.2132" stroke-miterlimit="10"></path><path d="M16.1899 4.35102L11.3874 4.35102L11.3874 9.13458L16.1899 9.13458L16.1899 4.35102Z"></path><path d="M11.0675 23.3526C11.0675 24.8554 12.2858 26.0736 13.7886 26.0736C15.2914 26.0736 16.5096 24.8554 16.5096 23.3526C16.5096 21.8498 15.2914 20.6315 13.7886 20.6315C12.2858 20.6315 11.0675 21.8498 11.0675 23.3526Z"></path><path d="M17.5424 15.2134C17.5424 16.7162 18.7606 17.9345 20.2634 17.9345C21.7662 17.9345 22.9845 16.7162 22.9845 15.2134C22.9845 13.7107 21.7662 12.4924 20.2634 12.4924C18.7606 12.4924 17.5424 13.7107 17.5424 15.2134Z"></path><path d="M4.59851 15.2134C4.59851 16.7162 5.81676 17.9345 7.31956 17.9345C8.82235 17.9345 10.0406 16.7162 10.0406 15.2134C10.0406 13.7107 8.82235 12.4924 7.31956 12.4924C5.81676 12.4924 4.59851 13.7107 4.59851 15.2134Z"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Full Node.svg b/assets/icons/polkadot/line/Full Node.svg
new file mode 100644
index 00000000..ecd39e75
--- /dev/null
+++ b/assets/icons/polkadot/line/Full Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5358 21.0126L18.5124 16.611"></path><path d="M9.50999 16.6247L6.44708 20.999"></path><path d="M20.4564 23.2116C20.4564 24.7425 21.6974 25.9834 23.2282 25.9834C24.759 25.9834 26 24.7425 26 23.2116C26 21.6808 24.759 20.4398 23.2282 20.4398C21.6974 20.4398 20.4564 21.6808 20.4564 23.2116Z"></path><path d="M2.00001 23.2116C2.00001 24.7425 3.24099 25.9834 4.77183 25.9834C6.30266 25.9834 7.54364 24.7425 7.54364 23.2116C7.54364 21.6808 6.30266 20.4398 4.77183 20.4398C3.24099 20.4398 2.00001 21.6808 2.00001 23.2116Z"></path><path d="M5.99593 10.0054C5.99593 14.4267 9.58006 18.0108 14.0013 18.0108C18.4226 18.0108 22.0067 14.4267 22.0067 10.0054C22.0067 5.58414 18.4226 2 14.0013 2C9.58006 2 5.99593 5.58414 5.99593 10.0054Z" stroke-miterlimit="10"></path><path d="M11.5364 12.6406C12.9917 14.0959 15.3513 14.0959 16.8066 12.6406C18.2619 11.1853 18.2619 8.82573 16.8066 7.3704C15.3513 5.91507 12.9917 5.91507 11.5364 7.3704C10.0811 8.82573 10.0811 11.1853 11.5364 12.6406Z"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Fund Account.svg b/assets/icons/polkadot/line/Fund Account.svg
new file mode 100644
index 00000000..bbc3696c
--- /dev/null
+++ b/assets/icons/polkadot/line/Fund Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M3 26.749L26.9834 26.749"></path><path d="M6.59839 11.4411L6.59839 26.749"></path><path d="M23.3994 11.4411L23.3994 26.749"></path><path d="M9.01234 11.4411H3.01672V11.2555L15.0024 3L27.0002 11.3521V11.4411H20.9779H9.01234Z"></path><path d="M21.1614 26.0519C21.1614 23.9777 19.7786 22.1585 17.7808 21.603L17.0508 21.3996C16.532 21.2558 16.3346 20.6249 16.6788 20.2113L17.2174 19.5635C18.1369 18.4585 18.0635 16.8346 17.0478 15.8169C15.9606 14.7277 14.1949 14.7277 13.1077 15.8169C12.0919 16.8346 12.0185 18.4585 12.9381 19.5635L13.4767 20.2113C13.8209 20.6249 13.6245 21.2558 13.1057 21.3996L12.3776 21.602C10.3808 22.1575 9 23.9758 9 26.048"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Fund Savings.svg b/assets/icons/polkadot/line/Fund Savings.svg
new file mode 100644
index 00000000..a6345cf9
--- /dev/null
+++ b/assets/icons/polkadot/line/Fund Savings.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Gaming.svg b/assets/icons/polkadot/line/Gaming.svg
new file mode 100644
index 00000000..97211371
--- /dev/null
+++ b/assets/icons/polkadot/line/Gaming.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2 18.8681C2 22.949 4.46926 25.144 7.19827 25.7927C8.34641 26.0656 9.53014 25.7604 10.6149 25.2958C12.8072 24.3568 15.2883 24.3568 17.4805 25.2958C18.5653 25.7604 19.749 26.0656 20.8972 25.7927C23.6262 25.144 26.0955 22.949 26.0955 18.8681C26.0955 14.9293 23.2304 11.7363 19.1247 11.7363H8.97079C4.30756 11.7363 2 14.9293 2 18.8681Z"></path><path d="M6.12368 18.723H11.4803"></path><path d="M8.80172 16.0446V21.4013"></path><path d="M17.8574 20.2845L17.8682 20.2845"></path><path d="M20.9302 20.2845L20.941 20.2845"></path><path d="M17.8574 17.1613L17.8682 17.1613"></path><path d="M20.92 17.1613L20.9308 17.1613"></path><path d="M14.0708 2V11.7361"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Genesis.svg b/assets/icons/polkadot/line/Genesis.svg
new file mode 100644
index 00000000..6be683e6
--- /dev/null
+++ b/assets/icons/polkadot/line/Genesis.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="2" y="5" width="17" height="18"></rect><path d="M26 14L12 14"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Gift.svg b/assets/icons/polkadot/line/Gift.svg
new file mode 100644
index 00000000..700dfffb
--- /dev/null
+++ b/assets/icons/polkadot/line/Gift.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.8229 2C11.6591 2 12.461 2.32869 13.0522 2.91376C13.6435 3.49883 13.9756 4.29236 13.9756 5.11977V8.23954H10.8229C9.98674 8.23954 9.18483 7.91085 8.59358 7.32578C8.00233 6.74071 7.67017 5.94719 7.67017 5.11977C7.67017 4.29236 8.00233 3.49883 8.59358 2.91376C9.18483 2.32869 9.98674 2 10.8229 2V2Z" stroke-miterlimit="10" fill="none"></path><path d="M17.1283 2C17.9645 2 18.7664 2.32869 19.3576 2.91376C19.9489 3.49883 20.2811 4.29236 20.2811 5.11977C20.2811 5.94719 19.9489 6.74071 19.3576 7.32578C18.7664 7.91085 17.9645 8.23954 17.1283 8.23954H13.9756V5.11977C13.9756 4.29236 14.3077 3.49883 14.899 2.91376C15.4903 2.32869 16.2922 2 17.1283 2V2Z" stroke-miterlimit="10" fill="none"></path><path d="M4 14V25H24.5V14"></path><path d="M13.9756 14L13.9756 24.5" stroke-miterlimit="10"></path><path d="M2 8.23946H26V13.8389H2V8.23946Z" stroke-miterlimit="10"></path></svg>
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diff --git a/assets/icons/polkadot/line/Glossary.svg b/assets/icons/polkadot/line/Glossary.svg
new file mode 100644
index 00000000..dc0b73c4
--- /dev/null
+++ b/assets/icons/polkadot/line/Glossary.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Go.svg b/assets/icons/polkadot/line/Go.svg
new file mode 100644
index 00000000..9ba08f25
--- /dev/null
+++ b/assets/icons/polkadot/line/Go.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 23C14 24.105 14.895 25 16 25C17.105 25 18 24.105 18 23V20H14V23Z"></path><path d="M10 23C10 24.105 10.895 25 12 25C13.105 25 14 24.105 14 23V20H10V23Z"></path><path d="M17.5 14H19C20.657 14 22 15.343 22 17C22 18.657 20.657 20 19 20H9C7.343 20 6 18.657 6 17C6 15.343 7.343 14 9 14H10.5"></path><path d="M7.5 10C5.567 10 4 8.433 4 6.5C4 4.567 5.567 3 7.5 3C9.433 3 11 4.567 11 6.5C11 8.433 9.433 10 7.5 10Z"></path><path d="M20.5 10C18.567 10 17 8.433 17 6.5C17 4.567 18.567 3 20.5 3C22.433 3 24 4.567 24 6.5C24 8.433 22.433 10 20.5 10Z"></path><path d="M17 13C17 14.657 15.657 16 14 16C12.343 16 11 14.657 11 13C11 11.343 12.343 10 14 10C15.657 10 17 11.343 17 13Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Governance.svg b/assets/icons/polkadot/line/Governance.svg
new file mode 100644
index 00000000..94364f8f
--- /dev/null
+++ b/assets/icons/polkadot/line/Governance.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><circle cx="14.0001" cy="13.8747" r="3.30708"></circle><circle cx="14.0001" cy="24.1101" r="1.88976"></circle><circle cx="14.0001" cy="3.88976" r="1.88976"></circle><circle cx="24.1102" cy="13.9999" r="1.88976" transform="rotate(-90 24.1102 13.9999)"></circle><circle cx="3.88976" cy="13.9999" r="1.88976" transform="rotate(-90 3.88976 13.9999)"></circle><circle cx="21.149" cy="21.1491" r="1.88976" transform="rotate(-45 21.149 21.1491)"></circle><circle cx="6.85112" cy="6.85082" r="1.88976" transform="rotate(-45 6.85112 6.85082)"></circle><circle cx="21.149" cy="6.85099" r="1.88976" transform="rotate(-135 21.149 6.85099)"></circle><circle cx="6.85107" cy="21.149" r="1.88976" transform="rotate(-135 6.85107 21.149)"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Governments.svg b/assets/icons/polkadot/line/Governments.svg
new file mode 100644
index 00000000..ea445d61
--- /dev/null
+++ b/assets/icons/polkadot/line/Governments.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Hackathon.svg b/assets/icons/polkadot/line/Hackathon.svg
new file mode 100644
index 00000000..845b5184
--- /dev/null
+++ b/assets/icons/polkadot/line/Hackathon.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2.96952 21.1257L25.045 21.1257L25.045 3.33279L2.96952 3.3328L2.96952 21.1257Z"></path><rect x="1.26221" y="21.1257" width="25.4756" height="3.87427"></rect><path d="M9.6314 14.8193L6.52344 12.232L9.6314 9.6394"></path><path d="M18.3582 9.62899L21.4765 12.2268L18.3582 14.8193"></path><path d="M15.7403 7.03906L12.2494 17.4194"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Hash Function.svg b/assets/icons/polkadot/line/Hash Function.svg
new file mode 100644
index 00000000..993eb00c
--- /dev/null
+++ b/assets/icons/polkadot/line/Hash Function.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.4824 2L14.4824 4.41076"></path><path d="M14.4824 23.5892L14.4824 26"></path><path d="M19.1909 2L19.1909 4.41076"></path><path d="M9.77386 2L9.77387 4.41076"></path><path d="M12.5265 16.8856L5 8.21664L23.4938 8.21665L16.5408 16.8856L16.5408 19.7753L12.5131 19.7753L12.5265 16.8856Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Healthcare.svg b/assets/icons/polkadot/line/Healthcare.svg
new file mode 100644
index 00000000..50915d6d
--- /dev/null
+++ b/assets/icons/polkadot/line/Healthcare.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M4.02344 6.28188V14.6254C4.02344 18.0247 5.75033 21.1913 8.60811 23.0322L14.0977 26.5684L19.727 22.9405C22.5838 21.0994 24.3099 17.9334 24.3099 14.5348V6.28188L14.1621 2.56836L4.02344 6.28188Z"></path><path d="M10.7098 13.5192L17.3695 13.5552"></path><path d="M14.0586 10.2083L14.0226 16.868"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Help.svg b/assets/icons/polkadot/line/Help.svg
new file mode 100644
index 00000000..9516994f
--- /dev/null
+++ b/assets/icons/polkadot/line/Help.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Heterogeneous Sharding.svg b/assets/icons/polkadot/line/Heterogeneous Sharding.svg
new file mode 100644
index 00000000..c36fa883
--- /dev/null
+++ b/assets/icons/polkadot/line/Heterogeneous Sharding.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Identify.svg b/assets/icons/polkadot/line/Identify.svg
new file mode 100644
index 00000000..eee4bf28
--- /dev/null
+++ b/assets/icons/polkadot/line/Identify.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9,20.2c4.9,0,8.8-4,8.8-8.8c0-4.9-4-8.8-8.8-8.8C9,2.6,5,6.5,5,11.4C5,16.3,9,20.2,13.9,20.2z" stroke-miterlimit="10"></path><path d="M19.8,17.9c-1.2,1-2.6,1.8-4.2,2.1l3.8,6.5l4-2.3L19.8,17.9z" stroke-miterlimit="10"></path><path d="M20,17.6v-0.8c0-1.9-1.4-3.6-3.3-4.1L16,12.5c-0.5-0.1-0.7-0.7-0.4-1.1l0.5-0.6C17,9.7,17,8.3,16,7.3 c-1.1-1-2.8-1-3.9,0c-1,0.9-1.1,2.4-0.2,3.4l0.5,0.6c0.3,0.4,0.1,1-0.4,1.1l-0.7,0.2c-2,0.5-3.3,2.2-3.3,4.1v0.8"></path></svg>
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diff --git a/assets/icons/polkadot/line/Identity.svg b/assets/icons/polkadot/line/Identity.svg
new file mode 100644
index 00000000..a172c9f5
--- /dev/null
+++ b/assets/icons/polkadot/line/Identity.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 27 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="1.46045" y="1.47864" width="24.079" height="25.0421"></rect><path d="M7.23943 22.6682H19.7605" stroke-miterlimit="10"></path><path d="M15.15 10.8446L15.6821 10.2128C16.6391 9.07668 16.5628 7.39603 15.5068 6.35126C14.3964 5.25263 12.6086 5.25263 11.4982 6.35126C10.4422 7.39603 10.3659 9.07668 11.3229 10.2128L11.8549 10.8445C12.2069 11.2624 12.0073 11.9044 11.4804 12.0491L10.7114 12.2603C8.66075 12.8235 7.23943 14.6878 7.23943 16.8144V18.8156H19.7605V16.8109C19.7605 14.6861 18.3406 12.8233 16.2918 12.2602L15.5244 12.0493C14.9976 11.9045 14.7981 11.2625 15.15 10.8446Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Import Token.svg b/assets/icons/polkadot/line/Import Token.svg
new file mode 100644
index 00000000..1bcd3a53
--- /dev/null
+++ b/assets/icons/polkadot/line/Import Token.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.0002 6.90186H26.0002V22.9019H10.0002"></path><circle cx="10" cy="14.9017" r="8"></circle><path d="M10.7999 14.9016H17.1999"></path><path d="M10.7999 10.9019H16.3999"></path><path d="M10.7999 18.9017H16.3999"></path><path d="M10.0002 6.90186V22.9019"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Indeterminate _ Negative.svg b/assets/icons/polkadot/line/Indeterminate _ Negative.svg
new file mode 100644
index 00000000..55bf9972
--- /dev/null
+++ b/assets/icons/polkadot/line/Indeterminate _ Negative.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26.9941 2.67578H2.99414V26.6758H26.9941V2.67578Z"></path><path d="M9.85114 14.6997L20.2407 14.7558"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Informational.svg b/assets/icons/polkadot/line/Informational.svg
new file mode 100644
index 00000000..f8eea970
--- /dev/null
+++ b/assets/icons/polkadot/line/Informational.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9883 26.6758C21.6157 26.6758 26.9883 21.3032 26.9883 14.6758C26.9883 8.04836 21.6157 2.67578 14.9883 2.67578C8.36086 2.67578 2.98828 8.04836 2.98828 14.6758C2.98828 21.3032 8.36086 26.6758 14.9883 26.6758Z"></path><path d="M14.998 13.082L15.0075 20.2122" stroke-miterlimit="10"></path><path d="M14.9881 8.67574L15.0063 8.69388" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Infrastructure.svg b/assets/icons/polkadot/line/Infrastructure.svg
new file mode 100644
index 00000000..004ce9a1
--- /dev/null
+++ b/assets/icons/polkadot/line/Infrastructure.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5 16V12H23V16" fill="none"></path><path d="M14.0335 7.54287C15.5641 7.54287 16.805 6.30206 16.805 4.77144C16.805 3.24081 15.5641 2 14.0335 2C12.5029 2 11.2621 3.24081 11.2621 4.77144C11.2621 6.30206 12.5029 7.54287 14.0335 7.54287Z"></path><path d="M13.9317 25.6754C15.4623 25.6754 16.7031 24.4346 16.7031 22.904C16.7031 21.3734 15.4623 20.1326 13.9317 20.1326C12.401 20.1326 11.1602 21.3734 11.1602 22.904C11.1602 24.4346 12.401 25.6754 13.9317 25.6754Z"></path><path d="M14.0128 7.65308L14.0128 20.1334"></path><path d="M4.77144 21.5152C6.30206 21.5152 7.54287 20.2743 7.54287 18.7437C7.54287 17.2131 6.30206 15.9723 4.77144 15.9723C3.24081 15.9723 2 17.2131 2 18.7437C2 20.2743 3.24081 21.5152 4.77144 21.5152Z"></path><path d="M23.2284 21.5152C24.759 21.5152 25.9998 20.2743 25.9998 18.7437C25.9998 17.2131 24.759 15.9723 23.2284 15.9723C21.6978 15.9723 20.457 17.2131 20.457 18.7437C20.457 20.2743 21.6978 21.5152 23.2284 21.5152Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Injected Account.svg b/assets/icons/polkadot/line/Injected Account.svg
new file mode 100644
index 00000000..d72c17e9
--- /dev/null
+++ b/assets/icons/polkadot/line/Injected Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9827 12.757L15.892 11.6638C17.4439 9.79803 17.3196 7.05736 15.6052 5.33974C13.7696 3.5007 10.7898 3.5007 8.95416 5.33974C7.23972 7.05736 7.11542 9.79803 8.66735 11.6638L9.57647 12.7568C10.1572 13.4549 9.82447 14.5198 8.94954 14.7631L7.71783 15.1056C4.34533 16.0435 2.01171 19.1146 2.01171 22.6151V25.9916H22.5393V22.6092C22.5393 19.1117 20.208 16.0431 16.8386 15.1054L15.6094 14.7633C14.7346 14.5199 14.402 13.4551 14.9827 12.757Z"></path><path d="M20.0093 5.00335L24.5 5.00334M22.8513 8.17789L25.9966 5.00334L22.8513 1.82128" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Interconnected.svg b/assets/icons/polkadot/line/Interconnected.svg
new file mode 100644
index 00000000..27e774b7
--- /dev/null
+++ b/assets/icons/polkadot/line/Interconnected.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.0096 15L19.6171 18.9072M8.58282 18.7747L14.0001 15V9.7512" fill="none" data-nofill="true"></path><path d="M17.9999 5.95697C17.9999 3.77166 16.2283 2.00011 14.043 2.00011C11.8577 2.00011 10.0862 3.77166 10.0862 5.95697C10.0862 8.14228 11.8577 9.91382 14.043 9.91382C16.2283 9.91382 17.9999 8.14228 17.9999 5.95697Z"></path><path d="M9.16639 21.0431C9.16639 18.8578 7.39485 17.0863 5.20954 17.0863C3.02423 17.0863 1.25269 18.8578 1.25269 21.0431C1.25269 23.2285 3.02423 25 5.20954 25C7.39485 25 9.16639 23.2285 9.16639 21.0431Z"></path><path d="M26.747 21.0431C26.747 18.8578 24.9754 17.0863 22.7901 17.0863C20.6048 17.0863 18.8333 18.8578 18.8333 21.0431C18.8333 23.2285 20.6048 25 22.7901 25C24.9754 25 26.747 23.2285 26.747 21.0431Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Interoperability.svg b/assets/icons/polkadot/line/Interoperability.svg
new file mode 100644
index 00000000..a9f81a5a
--- /dev/null
+++ b/assets/icons/polkadot/line/Interoperability.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.36649 24.4503C15.3574 26.7917 22.1118 23.8339 24.4529 17.8438C26.7939 11.8537 23.8351 5.09971 17.8442 2.75833C11.8533 0.416941 5.09886 3.3748 2.75781 9.36488C0.416752 15.355 3.37556 22.109 9.36649 24.4503Z"></path><path d="M10.3107 13.9197L12.2736 10.8418M16.7663 13.5669L15.2206 10.8713M15.4945 16.4535L12.1033 16.4399"></path><path d="M17.3645 18.9673C18.7605 19.5136 20.3365 18.8183 20.8845 17.4143C21.4325 16.0104 20.7451 14.4294 19.3491 13.8832C17.9531 13.3369 16.3771 14.0322 15.8291 15.4362C15.2811 16.8401 15.9685 18.4211 17.3645 18.9673Z"></path><path d="M7.81566 19.0113C9.21166 19.5575 10.7876 18.8622 11.3356 17.4583C11.8837 16.0543 11.1962 14.4734 9.80024 13.9271C8.40424 13.3809 6.82829 14.0762 6.28026 15.4801C5.73223 16.8841 6.41965 18.465 7.81566 19.0113Z"></path><path d="M12.7483 11.014C14.1443 11.5603 15.7203 10.865 16.2683 9.46104C16.8163 8.05709 16.1289 6.47614 14.7329 5.92989C13.3369 5.38364 11.761 6.07893 11.2129 7.48288C10.6649 8.88683 11.3523 10.4678 12.7483 11.014Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Investors.svg b/assets/icons/polkadot/line/Investors.svg
new file mode 100644
index 00000000..694d0b36
--- /dev/null
+++ b/assets/icons/polkadot/line/Investors.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M8.79878 16.402C12.9786 16.402 16.3671 13.0135 16.3671 8.83369C16.3671 4.65383 12.9786 1.26538 8.79878 1.26538C4.61892 1.26538 1.23047 4.65383 1.23047 8.83369C1.23047 13.0135 4.61892 16.402 8.79878 16.402Z" stroke-miterlimit="10"></path><path d="M10.3475 5.72636H8.2601C8.05572 5.72494 7.85307 5.76397 7.66384 5.8412C7.47461 5.91843 7.30253 6.03233 7.15751 6.17635C7.01249 6.32038 6.8974 6.49166 6.81886 6.68036C6.74032 6.86905 6.69989 7.07141 6.69989 7.2758C6.70273 7.68772 6.86836 8.0818 7.16065 8.37208C7.45294 8.66235 7.84816 8.82525 8.2601 8.82524H9.3361C9.74803 8.82523 10.1432 8.98813 10.4355 9.2784C10.7278 9.56867 10.8935 9.96275 10.8963 10.3747C10.9052 10.5886 10.8701 10.8021 10.7929 11.0018C10.7158 11.2016 10.5984 11.3833 10.448 11.5357C10.2976 11.6881 10.1175 11.808 9.91878 11.8877C9.72008 11.9675 9.50708 12.0055 9.29306 11.9994H7.03346"></path><path d="M8.79614 5.6865V4.52441"></path><path d="M8.79614 13.2189V12.1106"></path><path d="M26.1998 10.7344L16.5631 20.2407C16.376 20.4253 16.1237 20.5288 15.8608 20.5288H9.65815C9.44703 20.5288 9.24132 20.5956 9.07049 20.7197L1.80078 25.9997" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M21 10.2504L26.7784 10.2314L26.7974 16" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/IoT And Robotics.svg b/assets/icons/polkadot/line/IoT And Robotics.svg
new file mode 100644
index 00000000..b076c410
--- /dev/null
+++ b/assets/icons/polkadot/line/IoT And Robotics.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M15 10.9774L11.387 12.9992C10.8592 12.5718 10.2336 12.2502 9.53656 12.0676C6.85492 11.3652 4.11249 12.9691 3.41008 15.6508C3.22964 16.3396 3.20756 17.0262 3.30712 17.6832L7.19007 15.4053L8.90298 18.334L4.92689 20.6664C5.50308 21.1766 6.20599 21.5711 7.00147 21.7794C9.68311 22.4818 12.4255 20.8779 13.128 18.1962C13.332 17.4172 13.3367 16.6297 13.1805 15.8877L16.5 13.9934" stroke-miterlimit="10"></path><path d="M16.512 12.8858C17.6393 14.1541 19.5813 14.2684 20.8496 13.1411C22.1179 12.0138 22.2322 10.0718 21.105 8.80354C19.9777 7.53524 18.0357 7.42092 16.7674 8.54819C15.4991 9.67547 15.3848 11.6175 16.512 12.8858Z"></path><path d="M19.3769 14.5001L23.9529 21.6126L26.854 19.7462L22.192 12.5001"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/IoT.svg b/assets/icons/polkadot/line/IoT.svg
new file mode 100644
index 00000000..3757875b
--- /dev/null
+++ b/assets/icons/polkadot/line/IoT.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M15.4119 7.57826C16.9523 7.57826 18.201 6.32953 18.201 4.78913C18.201 3.24874 16.9523 2 15.4119 2C13.8715 2 12.6228 3.24874 12.6228 4.78913C12.6228 6.32953 13.8715 7.57826 15.4119 7.57826Z"></path><path d="M5.78913 21.4489C7.32953 21.4489 8.57826 20.2002 8.57826 18.6598C8.57826 17.1194 7.32953 15.8706 5.78913 15.8706C4.24874 15.8706 3 17.1194 3 18.6598C3 20.2002 4.24874 21.4489 5.78913 21.4489Z"></path><path d="M21.7582 26C23.2986 26 24.5473 24.7513 24.5473 23.2109C24.5473 21.6705 23.2986 20.4218 21.7582 20.4218C20.2178 20.4218 18.9691 21.6705 18.9691 23.2109C18.9691 24.7513 20.2178 26 21.7582 26Z"></path><path d="M15.4119 17.8724C16.9523 17.8724 18.201 16.6237 18.201 15.0833C18.201 13.5429 16.9523 12.2941 15.4119 12.2941C13.8715 12.2941 12.6228 13.5429 12.6228 15.0833C12.6228 16.6237 13.8715 17.8724 15.4119 17.8724Z"></path><path d="M12.1823 16.2561L9 17.4465"></path><path d="M17.5 17.7715L19.6315 20.5"></path><path d="M15.4113 11.5L15.4113 8.5"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Isolated.svg b/assets/icons/polkadot/line/Isolated.svg
new file mode 100644
index 00000000..c61484bd
--- /dev/null
+++ b/assets/icons/polkadot/line/Isolated.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="6.51454" cy="12.0567" r="3.19226" transform="rotate(45 6.51454 12.0567)"></circle><circle cx="6.51454" cy="21.4854" r="3.19226" transform="rotate(45 6.51454 21.4854)"></circle><circle cx="21.4858" cy="6.51454" r="3.19226" transform="rotate(45 21.4858 6.51454)"></circle><circle cx="15.9432" cy="21.4854" r="3.19226" transform="rotate(45 15.9432 21.4854)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/KeepAlive Check.svg b/assets/icons/polkadot/line/KeepAlive Check.svg
new file mode 100644
index 00000000..1248aa49
--- /dev/null
+++ b/assets/icons/polkadot/line/KeepAlive Check.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 5L26 14.5L26 23L2 23L2 14L2 5L26 5Z"></path><path d="M2 14H8L10 11L14 19L19 8.5L22 14H26"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Key.svg b/assets/icons/polkadot/line/Key.svg
new file mode 100644
index 00000000..7b79daa2
--- /dev/null
+++ b/assets/icons/polkadot/line/Key.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.55463 17.6863C9.20301 18.0092 8.7912 18.2597 8.34269 18.4234C7.89419 18.5871 7.41779 18.6608 6.94068 18.6403C6.46358 18.6199 5.99512 18.5056 5.56205 18.3041C5.12898 18.1026 4.73978 17.8178 4.41667 17.4659C3.77335 16.7485 3.4409 15.8052 3.49234 14.8433C3.54379 13.8814 3.97492 12.9794 4.69103 12.3356C5.04265 12.0127 5.45447 11.7622 5.90297 11.5985C6.35147 11.4348 6.82788 11.3611 7.30498 11.3816C7.78209 11.402 8.25055 11.5163 8.68362 11.7178C9.11669 11.9193 9.50589 12.2041 9.82899 12.556C10.4719 13.2736 10.8042 14.2168 10.7527 15.1786C10.7013 16.1404 10.2704 17.0423 9.55463 17.6863V17.6863Z" fill="none"></path><path d="M10.8674 14.7892L26 14.7775" fill="none"></path><path d="M18.184 15.4861L18.1872 19.6325L23.2291 19.6338L23.2247 15.4886"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Language.svg b/assets/icons/polkadot/line/Language.svg
new file mode 100644
index 00000000..c8daf7e1
--- /dev/null
+++ b/assets/icons/polkadot/line/Language.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9766 26.6758C21.604 26.6758 26.9766 21.3032 26.9766 14.6758C26.9766 8.04836 21.604 2.67578 14.9766 2.67578C8.34915 2.67578 2.97656 8.04836 2.97656 14.6758C2.97656 21.3032 8.34915 26.6758 14.9766 26.6758Z" stroke-miterlimit="10"></path><path d="M15.0687 2.90655C23.684 10.6789 23.684 18.525 15.0687 26.445"></path><path d="M15.0685 26.445C6.45315 18.6727 6.45315 10.8265 15.0685 2.90655"></path><path d="M3.8551 18.3679H25.8019"></path><path d="M3.85504 10.9833H26.2659"></path><path d="M15.0594 2.90655V26.4358"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Layer (Four).svg b/assets/icons/polkadot/line/Layer (Four).svg
new file mode 100644
index 00000000..ee9f4832
--- /dev/null
+++ b/assets/icons/polkadot/line/Layer (Four).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.3014 19.285L25 21.1915L14.1947 26.5812L3 20.8108L6.90728 18.8619" stroke-miterlimit="10"></path><path d="M21.283 14.7928L25 16.7087L14.1947 22.0984L3 16.3281L6.71577 14.4747" stroke-miterlimit="10"></path><path d="M21.0712 10.2144L25 12.2396L14.1947 17.6293L3 11.8589L7.09859 9.81456" stroke-miterlimit="10"></path><path d="M25 7.77035L14.1947 13.16L3 7.3897L13.8053 2L25 7.77035Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Layer (One).svg b/assets/icons/polkadot/line/Layer (One).svg
new file mode 100644
index 00000000..1ff50f2a
--- /dev/null
+++ b/assets/icons/polkadot/line/Layer (One).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 13.7704L14.1947 19.16L3 13.3897L13.8053 8L25 13.7704Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Layer (Three).svg b/assets/icons/polkadot/line/Layer (Three).svg
new file mode 100644
index 00000000..c8da74a2
--- /dev/null
+++ b/assets/icons/polkadot/line/Layer (Three).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M6.73274 16.4662L3 18.3281L14.1947 24.0984L25 18.7087L21.3521 16.8284" stroke-miterlimit="10"></path><path d="M21.155 12.2577L25 14.2396L14.1947 19.6293L3 13.8589L6.81434 11.9563" stroke-miterlimit="10"></path><path d="M25 9.77035L14.1947 15.16L3 9.3897L13.8053 4L25 9.77035Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Layer (Two).svg b/assets/icons/polkadot/line/Layer (Two).svg
new file mode 100644
index 00000000..312e8aee
--- /dev/null
+++ b/assets/icons/polkadot/line/Layer (Two).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.3211 14.3433L25 16.2396L14.1947 21.6293L3 15.8589L6.6688 14.0289" stroke-miterlimit="10"></path><path d="M25 11.7704L14.1947 17.16L3 11.3897L13.8053 6L25 11.7704Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Layer.svg b/assets/icons/polkadot/line/Layer.svg
new file mode 100644
index 00000000..d2d4e6d4
--- /dev/null
+++ b/assets/icons/polkadot/line/Layer.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.0036 13.999L21.008 18.0059L13.0011 26L5 17.9989L8.99863 14.0002" stroke-miterlimit="10"></path><path d="M21.0032 9.99642L13.0012 17.9989L5.00208 9.9991L13.0015 1.99985L21.0032 9.99642Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Learn More.svg b/assets/icons/polkadot/line/Learn More.svg
new file mode 100644
index 00000000..0906bc57
--- /dev/null
+++ b/assets/icons/polkadot/line/Learn More.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9707 26.6758C21.5981 26.6758 26.9707 21.3032 26.9707 14.6758C26.9707 8.04836 21.5981 2.67578 14.9707 2.67578C8.34329 2.67578 2.9707 8.04836 2.9707 14.6758C2.9707 21.3032 8.34329 26.6758 14.9707 26.6758Z"></path><path d="M11.9707 12.4519C11.9707 10.9187 13.2136 9.67581 14.7468 9.67581C16.2799 9.67581 17.5228 10.9187 17.5228 12.4519C17.5228 13.985 16.2799 15.2279 14.7468 15.2279L14.7468 17.3796"></path><path d="M14.7468 20.6562L14.7468 20.6756"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Learn.svg b/assets/icons/polkadot/line/Learn.svg
new file mode 100644
index 00000000..f54dbf45
--- /dev/null
+++ b/assets/icons/polkadot/line/Learn.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M4.11078 23.0243V13.2732L13.5299 16.3413L22.9491 13.2732V23.0253L13.5299 26.42L4.11078 23.0243Z"></path><path d="M13.5289 26L13.5289 16.5"></path><path d="M10.47 11.8814L9.34205 12.1946C8.14881 12.526 7.10352 13.1515 6.2619 13.9734L13.528 16.3403L20.7922 13.9743C19.9506 13.1515 18.9034 12.5251 17.7102 12.1946L16.5803 11.8814C15.7781 11.6592 15.4726 10.685 16.0048 10.0461L16.8388 9.0461C18.2626 7.33917 18.1483 4.83242 16.5755 3.26152C14.8913 1.57949 12.158 1.57949 10.4729 3.26152C8.90011 4.83242 8.78578 7.34013 10.2096 9.0461L11.0435 10.0461C11.5768 10.685 11.2712 11.6582 10.468 11.8814H10.47Z"></path><path d="M23.5 19.2934C24.0306 19.2934 24.4607 18.8633 24.4607 18.3327C24.4607 17.8021 24.0306 17.3719 23.5 17.3719"></path><path d="M3.5 17.3685C2.96939 17.3685 2.53925 17.7986 2.53925 18.3293C2.53925 18.8599 2.96939 19.29 3.5 19.29"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Lease Duration.svg b/assets/icons/polkadot/line/Lease Duration.svg
new file mode 100644
index 00000000..dd0f8388
--- /dev/null
+++ b/assets/icons/polkadot/line/Lease Duration.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M27 27H3V4.88454H27V27Z" stroke-miterlimit="10"></path><path d="M10.4233 7.34171V3" stroke-miterlimit="10"></path><path d="M19.5764 7.34178V3.00008" stroke-miterlimit="10"></path><path d="M14.9994 22.9988C18.3128 22.9988 20.9988 20.3128 20.9988 16.9994C20.9988 13.686 18.3128 11 14.9994 11C11.686 11 9 13.686 9 16.9994C9 20.3128 11.686 22.9988 14.9994 22.9988Z"></path><path d="M15.1147 15.4439V18.0033L14.1109 19.2213"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Library.svg b/assets/icons/polkadot/line/Library.svg
new file mode 100644
index 00000000..a6103e16
--- /dev/null
+++ b/assets/icons/polkadot/line/Library.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><rect x="1.29297" y="2" width="4" height="24"></rect><rect x="9" y="2" width="4" height="24"></rect><rect x="16.3813" y="3.03516" width="4" height="24" transform="rotate(-15 16.3813 3.03516)"></rect></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Light Node.svg b/assets/icons/polkadot/line/Light Node.svg
new file mode 100644
index 00000000..fdaef6eb
--- /dev/null
+++ b/assets/icons/polkadot/line/Light Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5494 21.0257L18.5239 16.621"></path><path d="M9.51521 16.6348L6.4502 21.0121"></path><path d="M20.4691 23.2263C20.4691 24.7582 21.711 26 23.2429 26C24.7748 26 26.0166 24.7582 26.0166 23.2263C26.0166 21.6944 24.7748 20.4525 23.2429 20.4525C21.711 20.4525 20.4691 21.6944 20.4691 23.2263Z"></path><path d="M2.00003 23.2263C2.00003 24.7582 3.24187 26 4.77376 26C6.30564 26 7.54749 24.7582 7.54749 23.2263C7.54749 21.6944 6.30565 20.4525 4.77376 20.4525C3.24187 20.4525 2.00003 21.6944 2.00003 23.2263Z"></path><path d="M5.99873 10.0109C5.99873 14.4352 9.58534 18.0218 14.0096 18.0218C18.434 18.0218 22.0206 14.4352 22.0206 10.0109C22.0206 5.58661 18.434 2 14.0096 2C9.58534 2 5.99873 5.58661 5.99873 10.0109Z" stroke-miterlimit="10"></path><path d="M15.7405 13.4617C16.0497 13.293 16.3403 13.0778 16.602 12.8161C16.8576 12.5606 17.0688 12.2774 17.2356 11.9763M12.1604 13.4769C11.8406 13.3061 11.5403 13.0858 11.2707 12.8161C11.0466 12.592 10.8566 12.3467 10.7007 12.0867M15.8061 6.87589C16.0909 7.0387 16.3589 7.24167 16.602 7.48477C16.8462 7.729 17.05 7.9984 17.2132 8.28461M10.5977 8.39755C10.7702 8.06917 10.9945 7.76088 11.2707 7.48477C11.5443 7.21111 11.8496 6.98832 12.1747 6.81639"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Lights On.svg b/assets/icons/polkadot/line/Lights On.svg
new file mode 100644
index 00000000..5ec3af77
--- /dev/null
+++ b/assets/icons/polkadot/line/Lights On.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9884 11.1283C12.227 11.1283 9.9884 13.3679 9.9884 16.1306C9.9884 18.1819 11.2225 19.9448 12.9884 20.7167L12.9883 25.7167H16.9883L16.9884 20.7167C18.7543 19.9448 19.9884 18.1819 19.9884 16.1306C19.9884 13.3679 17.7498 11.1283 14.9884 11.1283Z"></path><path d="M14.9883 7.12823L14.9883 4.12823"></path><path d="M2.98834 16.1282L5.98834 16.1282"></path><path d="M23.9883 16.1282L26.9883 16.1282"></path><path d="M21.3523 9.76437L23.4736 7.64305"></path><path d="M6.50283 7.64293L8.62415 9.76425"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Limited Supply.svg b/assets/icons/polkadot/line/Limited Supply.svg
new file mode 100644
index 00000000..997ef629
--- /dev/null
+++ b/assets/icons/polkadot/line/Limited Supply.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M4.56793 24.4529H23.4045V7.51797H4.56793V24.4529Z"></path><path d="M2 7.51174H26V3H2V7.51174Z"></path><path d="M14.9603 19.876L19.351 19.8904L19.3655 15.5071"></path><path d="M8.11823 12.1604L12.0457 15.7778L13.8051 14.0185L18.482 18.9733"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/LinkedIn.svg b/assets/icons/polkadot/line/LinkedIn.svg
new file mode 100644
index 00000000..002695a2
--- /dev/null
+++ b/assets/icons/polkadot/line/LinkedIn.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 2H2V26H26V2Z"></path><path d="M8.87455 10.8805L8.87997 20.1966M13.4787 20.1966L13.4787 14M19.9888 20.1966L19.9888 14.8649C19.9888 13.208 18.6457 11.8649 16.9888 11.8649L15.6138 11.8649C14.4346 11.8649 13.4787 12.8208 13.4787 14V14M13.4787 10.8805L13.4787 14" stroke-miterlimit="10"></path><path d="M8.85718 7.14287L8.87837 7.16406" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Lock.svg b/assets/icons/polkadot/line/Lock.svg
new file mode 100644
index 00000000..af3317af
--- /dev/null
+++ b/assets/icons/polkadot/line/Lock.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.12132 10.1541L8.12134 8.41857V8.41857C8.12134 5.42598 10.5473 3 13.5399 3V3C16.5325 3 18.9585 5.42598 18.9585 8.41857V8.41857L18.9585 10.1541" fill="none"></path><path d="M24.0798 10.6693H3V26H24.0798V10.6693Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Maintain.svg b/assets/icons/polkadot/line/Maintain.svg
new file mode 100644
index 00000000..ffd69169
--- /dev/null
+++ b/assets/icons/polkadot/line/Maintain.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.2419 21.4536C20.5351 20.4931 21.5509 19.1973 22.1738 17.6979C22.9295 15.8789 23.0648 13.8615 22.5587 11.9579C22.0527 10.0542 20.9336 8.3703 19.3744 7.16659C17.8152 5.96289 15.9028 5.30646 13.933 5.29883L13.0491 5.35498M15.6857 8.72868L12.2762 5.4095L15.5954 2" fill="none" data-nofill="true"></path><path d="M8.62964 7.05725C7.34892 8.00527 6.3384 9.28218 5.71112 10.7614C4.9389 12.5825 4.79091 14.6079 5.29021 16.5219C5.7895 18.4358 6.90803 20.1308 8.47142 21.3426C10.0348 22.5544 11.9552 23.2148 13.9332 23.221L14.8064 23.1759M12.2705 19.7809L15.6044 23.1112L12.3372 26.5096" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Marketing.svg b/assets/icons/polkadot/line/Marketing.svg
new file mode 100644
index 00000000..3ab53915
--- /dev/null
+++ b/assets/icons/polkadot/line/Marketing.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2.00011 16.7242C2.00011 22.0367 6.30674 26.3433 11.6192 26.3433C16.9317 26.3433 21.2383 22.0367 21.2383 16.7242C21.2383 11.4117 16.9317 7.1051 11.6192 7.1051C6.30673 7.1051 2.00011 11.4117 2.00011 16.7242Z"></path><path d="M6.18213 16.724C6.18213 19.7267 8.61631 22.1609 11.619 22.1609C14.6217 22.1609 17.0559 19.7267 17.0559 16.724C17.0559 13.7213 14.6217 11.2871 11.619 11.2871C8.6163 11.2871 6.18213 13.7213 6.18213 16.724Z"></path><path d="M12.0376 16.5693L19.8289 8.77795"></path><path d="M22.5962 3L19.7678 5.82842V9.36396H23.3033L26.1317 6.53553L22.9497 6.18198L22.5962 3Z"></path><path d="M10.3645 16.724C10.3645 17.417 10.9262 17.9787 11.6192 17.9787C12.3121 17.9787 12.8738 17.417 12.8738 16.724C12.8738 16.0311 12.3121 15.4694 11.6192 15.4694C10.9262 15.4694 10.3645 16.0311 10.3645 16.724Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Menu.svg b/assets/icons/polkadot/line/Menu.svg
new file mode 100644
index 00000000..01058006
--- /dev/null
+++ b/assets/icons/polkadot/line/Menu.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2.98242 14.9616H26.9824"></path><path d="M2.98242 22.2532H26.9824"></path><path d="M2.98242 7.66992H26.9824"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Message.svg b/assets/icons/polkadot/line/Message.svg
new file mode 100644
index 00000000..81c62d5c
--- /dev/null
+++ b/assets/icons/polkadot/line/Message.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M7.0197 19.8928V25.4819L14.3572 19.8928H26.7523V2.24902H1.25195V19.8928H7.0197Z"></path><circle cx="7.5" cy="11.5" r="1.5"></circle><circle cx="13.5" cy="11.5" r="1.5"></circle><circle cx="19.5" cy="11.5" r="1.5"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Metaverse.svg b/assets/icons/polkadot/line/Metaverse.svg
new file mode 100644
index 00000000..b668c9e9
--- /dev/null
+++ b/assets/icons/polkadot/line/Metaverse.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 20.4615L14.0769 26L25.1538 20.4615V7.53846L14.0769 2L3 7.53846V20.4615Z"></path><path d="M6 14C6 15.6701 7.02353 17.1011 8.47754 17.7001C9.41213 18.085 10.43 17.656 11.2193 17.0246C12.845 15.724 15.155 15.724 16.7807 17.0246C17.57 17.656 18.5879 18.085 19.5225 17.7001C20.9765 17.1011 22 15.6701 22 14C22 11.7909 20.2091 10 18 10H10C7.79086 10 6 11.7909 6 14Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Mitigating Mev.svg b/assets/icons/polkadot/line/Mitigating Mev.svg
new file mode 100644
index 00000000..cf78f831
--- /dev/null
+++ b/assets/icons/polkadot/line/Mitigating Mev.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.9496 23.0396V26.5684H8.06305V23.0396"></path><path d="M14.0059 7.19092L14.0059 11.1531"></path><path d="M24.5716 11.8135H3.44006V23.0396H24.5716V11.8135Z"></path><path d="M9.71367 19.7376C10.9901 19.7376 12.0249 18.7029 12.0249 17.4264C12.0249 16.1499 10.9901 15.1151 9.71367 15.1151C8.43719 15.1151 7.4024 16.1499 7.4024 17.4264C7.4024 18.7029 8.43719 19.7376 9.71367 19.7376Z"></path><path d="M14.0058 6.53053C15.0999 6.53053 15.9869 5.64357 15.9869 4.54944C15.9869 3.45532 15.0999 2.56836 14.0058 2.56836C12.9117 2.56836 12.0247 3.45532 12.0247 4.54944C12.0247 5.64357 12.9117 6.53053 14.0058 6.53053Z"></path><path d="M18.2983 19.7376C19.5748 19.7376 20.6096 18.7029 20.6096 17.4264C20.6096 16.1499 19.5748 15.1151 18.2983 15.1151C17.0218 15.1151 15.9871 16.1499 15.9871 17.4264C15.9871 18.7029 17.0218 19.7376 18.2983 19.7376Z"></path></svg>
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diff --git a/assets/icons/polkadot/line/Mobile App.svg b/assets/icons/polkadot/line/Mobile App.svg
new file mode 100644
index 00000000..c4477713
--- /dev/null
+++ b/assets/icons/polkadot/line/Mobile App.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.5109 2.33008H6V26.3301H22.5109V2.33008Z"></path><path d="M13.3052 23.0423H15.205"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Monitor.svg b/assets/icons/polkadot/line/Monitor.svg
new file mode 100644
index 00000000..410bf322
--- /dev/null
+++ b/assets/icons/polkadot/line/Monitor.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 16.5029H26V20.5H2V16.5029Z"></path><path d="M2 2.5H26V16.5029H2V2.5Z"></path><path d="M10 25H18"></path><path d="M14 24.5L14 20.5"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/More Horizontal.svg b/assets/icons/polkadot/line/More Horizontal.svg
new file mode 100644
index 00000000..d0a478fc
--- /dev/null
+++ b/assets/icons/polkadot/line/More Horizontal.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="4.33032" cy="14.3303" r="2.35489" transform="rotate(45 4.33032 14.3303)"></circle><circle cx="13.9998" cy="14.3303" r="2.35489" transform="rotate(45 13.9998 14.3303)"></circle><circle cx="23.6696" cy="14.3303" r="2.35489" transform="rotate(45 23.6696 14.3303)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/More Menu.svg b/assets/icons/polkadot/line/More Menu.svg
new file mode 100644
index 00000000..55b5de6c
--- /dev/null
+++ b/assets/icons/polkadot/line/More Menu.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 5.07416 14.2383)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 14.0002 14.2383)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 22.9264 14.2383)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 5.07416 23.183)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 14.0002 23.183)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 22.9264 23.183)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 5.07416 5.29354)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 14.0002 5.29354)"></circle><circle r="2.16708" transform="matrix(0.709281 0.704926 -0.709281 0.704926 22.9264 5.29354)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/More Vertical.svg b/assets/icons/polkadot/line/More Vertical.svg
new file mode 100644
index 00000000..b41e94ad
--- /dev/null
+++ b/assets/icons/polkadot/line/More Vertical.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="14.9941" cy="4.89896" r="2.35489" transform="rotate(135 14.9941 4.89896)"></circle><circle cx="14.9941" cy="14.5685" r="2.35489" transform="rotate(135 14.9941 14.5685)"></circle><circle cx="14.9941" cy="24.2382" r="2.35489" transform="rotate(135 14.9941 24.2382)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Multichain Smart Contracts.svg b/assets/icons/polkadot/line/Multichain Smart Contracts.svg
new file mode 100644
index 00000000..0ecece74
--- /dev/null
+++ b/assets/icons/polkadot/line/Multichain Smart Contracts.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="2" y="2.56836" width="24" height="24"></rect><rect x="5.42859" y="17.9969" width="5.14286" height="5.14286"></rect><path d="M14 3.42554V25.7113"></path><path d="M25.1429 14.5684L2.85717 14.5684"></path><circle cx="20" cy="8.56838" r="2.57143"></circle><path d="M20 17.9969L17.4286 23.1398H20H22.5714L20 17.9969Z"></path><path d="M8.00002 5.99695L5.42859 11.1398H8.00002H10.5714L8.00002 5.99695Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Multichain Treasuries.svg b/assets/icons/polkadot/line/Multichain Treasuries.svg
new file mode 100644
index 00000000..8214a165
--- /dev/null
+++ b/assets/icons/polkadot/line/Multichain Treasuries.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.2321 8.49051L13.994 2L4.54816 8.56634V26.0002L23.2321 26.0002V8.49051Z"></path><path d="M2.00006 26.0002H4.54816M25.9999 26.0002H23.2321"></path><path d="M26 10.4352L23.2321 8.49048M2.00012 10.3376L4.54816 8.56631"></path><rect x="7.94513" y="18.2858" width="4.24641" height="4.28571"></rect><ellipse cx="17.7118" cy="12.7141" rx="2.12321" ry="2.14286"></ellipse><path d="M17.7118 18.2858L15.5886 22.5715H17.7118H19.835L17.7118 18.2858Z"></path><path d="M10.0683 10.5713L7.94513 14.857H10.0683H12.1915L10.0683 10.5713Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Multisign Account.svg b/assets/icons/polkadot/line/Multisign Account.svg
new file mode 100644
index 00000000..24440b1e
--- /dev/null
+++ b/assets/icons/polkadot/line/Multisign Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11.5288 3L14.5715 6.04263L6.69473 13.9194L2.51937 15.0482L3.6521 10.8767L11.5288 3Z"></path><path d="M22.9574 3L26 6.04263L18.1233 13.9194L13.9479 15.0482L15.0806 10.8767L22.9574 3Z"></path><path d="M23.7608 21.0003L2.16085 21.0003M20.9217 17.4899L24.4412 21.0004L20.9217 24.52" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Multisign.svg b/assets/icons/polkadot/line/Multisign.svg
new file mode 100644
index 00000000..af9387b9
--- /dev/null
+++ b/assets/icons/polkadot/line/Multisign.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.3712 25.6559H1.28534" stroke-miterlimit="10"></path><path d="M22.0711 12.9278L25.2854 16.1421L16.9642 24.4633L12.5532 25.6559L13.7499 21.249L22.0711 12.9278Z"></path><path d="M22.0711 2L25.2854 5.21432L16.9642 13.5355L12.5532 14.7281L13.7499 10.3212L22.0711 2Z"></path><path d="M9.3712 14.728H1.28534" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/NFT Staking.svg b/assets/icons/polkadot/line/NFT Staking.svg
new file mode 100644
index 00000000..5c8fa33d
--- /dev/null
+++ b/assets/icons/polkadot/line/NFT Staking.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3 21.0299L14.0769 26.5684L25.1538 21.0299V8.10682L14.0769 2.56836L3 8.10682V21.0299Z"></path><path d="M17.448 13.4007L14.0767 10.8134L10.7055 13.4007"></path><path d="M14.0536 11.6296V18.2098"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Network Is Connected.svg b/assets/icons/polkadot/line/Network Is Connected.svg
new file mode 100644
index 00000000..676a7649
--- /dev/null
+++ b/assets/icons/polkadot/line/Network Is Connected.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M4 5.9518V14.2953C4 17.6947 5.7269 20.8612 8.58467 22.7021L14.0743 26.2383L19.7036 22.6104C22.5604 20.7693 24.2865 17.6034 24.2865 14.2048V5.9518L14.1386 2.23828L4 5.9518Z"></path><path d="M14.0091 15.3685L13.9996 8.23825" stroke-miterlimit="10"></path><path d="M14.0187 19.7748L14.0006 19.7566" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Network Security Operations.svg b/assets/icons/polkadot/line/Network Security Operations.svg
new file mode 100644
index 00000000..5d40d754
--- /dev/null
+++ b/assets/icons/polkadot/line/Network Security Operations.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M6.38416 5.05048V9.32685C6.38416 12.7262 8.11105 15.8928 10.9688 17.7336L13.4887 19.3569L16.1077 17.6691C18.9644 15.828 20.6905 12.662 20.6905 9.26342V5.05048L13.5341 2.43164L6.38416 5.05048Z"></path><path d="M11.0864 10.8108L13.2208 13.1803L17.1326 8.47766"></path><path d="M13.5411 22.9513V21.8663L13.5411 19.3029M12.5304 23.3763C13.0934 22.8133 14.0055 22.8126 14.5677 23.3747C15.1298 23.9368 15.1291 24.849 14.5661 25.412C14.003 25.9751 13.0909 25.9758 12.5287 25.4137C11.9666 24.8515 11.9673 23.9394 12.5304 23.3763Z"></path><path d="M19.9885 20.4934L19.9885 17.8104L18.7251 16.5693M21.0037 20.9203C20.4382 20.3548 19.522 20.3541 18.9574 20.9187C18.3928 21.4833 18.3935 22.3995 18.959 22.965C19.5246 23.5306 20.4408 23.5313 21.0054 22.9667C21.57 22.402 21.5693 21.4859 21.0037 20.9203Z"></path><path d="M7.08645 20.4934L7.08645 17.8104L8.49101 16.4306M6.07122 20.9203C6.63675 20.3548 7.55293 20.3541 8.11755 20.9187C8.68218 21.4833 8.68144 22.3995 8.11591 22.965C7.55037 23.5306 6.6342 23.5313 6.06957 22.9667C5.50495 22.402 5.50568 21.4859 6.07122 20.9203Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/New Tab.svg b/assets/icons/polkadot/line/New Tab.svg
new file mode 100644
index 00000000..868591b9
--- /dev/null
+++ b/assets/icons/polkadot/line/New Tab.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 16.9434V26.2383H2V2.23828H11.2908" fill="none" data-nofill="true"></path><path d="M11.4286 16.8097L25 3.23431" fill="none" data-nofill="true"></path><path d="M16.3685 2.29291H25.9474V11.8719" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/News.svg b/assets/icons/polkadot/line/News.svg
new file mode 100644
index 00000000..5e104292
--- /dev/null
+++ b/assets/icons/polkadot/line/News.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M19.9104 22.567C19.9104 24.8828 21.2555 25.8828 22.9122 25.8828C24.5689 25.8828 25.9104 24.3986 25.9104 22.567L25.9104 5.8388L19.9104 5.8388"></path><path d="M19.9104 1.88281H1.9104V25.8828H23.0099C20.8154 25.8828 19.9095 24.4486 19.9095 22.5708L19.9104 1.88281Z"></path><path d="M6.28784 20.8828H15.2878" stroke-miterlimit="10"></path><path d="M6.28784 15.8828L15.2878 15.8828" stroke-miterlimit="10"></path><rect x="6.28784" y="5.88281" width="9" height="5"></rect></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Nft.svg b/assets/icons/polkadot/line/Nft.svg
new file mode 100644
index 00000000..09f96fbc
--- /dev/null
+++ b/assets/icons/polkadot/line/Nft.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2.03345 20.7869L13.6488 26.5946L25.2642 20.7869V7.23566L13.6488 1.42798L2.03345 7.23566V20.7869Z"></path><path d="M6.14062 16.9801V11.0425H6.17163L9.62476 16.9801H9.65493V11.0424"></path><path d="M20.376 16.9999V11.2902"></path><path d="M21.8601 11.0221L18.8916 11.0221"></path><path d="M13.3555 16.9977V11.0005H15.1913"></path><path d="M15.1917 14.2847L13.3555 14.2847"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Night_Dark Mode.svg b/assets/icons/polkadot/line/Night_Dark Mode.svg
new file mode 100644
index 00000000..20d507e2
--- /dev/null
+++ b/assets/icons/polkadot/line/Night_Dark Mode.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.933 18.407C22.9658 20.0772 20.2425 20.7935 17.5563 20.0914C13.1808 18.9478 10.5609 14.4736 11.7045 10.0981C12.6333 6.54463 15.7587 4.14906 19.244 3.98694C18.5497 3.6436 17.8103 3.36531 17.0315 3.16175C10.8543 1.54717 4.53783 5.24589 2.92325 11.4231C1.30867 17.6002 5.00739 23.9167 11.1846 25.5313C16.9727 27.0442 22.8831 23.892 24.933 18.407Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Node.svg b/assets/icons/polkadot/line/Node.svg
new file mode 100644
index 00000000..e5735391
--- /dev/null
+++ b/assets/icons/polkadot/line/Node.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5358 21.0126L18.5124 16.6109"></path><path d="M9.50999 16.6247L6.44708 20.999"></path><path d="M20.4564 23.2116C20.4564 24.7425 21.6974 25.9834 23.2282 25.9834C24.759 25.9834 26 24.7425 26 23.2116C26 21.6808 24.759 20.4398 23.2282 20.4398C21.6974 20.4398 20.4564 21.6808 20.4564 23.2116Z"></path><path d="M2.00001 23.2116C2.00001 24.7425 3.24099 25.9834 4.77183 25.9834C6.30266 25.9834 7.54364 24.7425 7.54364 23.2116C7.54364 21.6808 6.30266 20.4398 4.77183 20.4398C3.24099 20.4398 2.00001 21.6808 2.00001 23.2116Z"></path><path d="M5.99593 10.0054C5.99593 14.4267 9.58006 18.0108 14.0013 18.0108C18.4226 18.0108 22.0067 14.4267 22.0067 10.0054C22.0067 5.58414 18.4226 2 14.0013 2C9.58006 2 5.99593 5.58414 5.99593 10.0054Z" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Nominating.svg b/assets/icons/polkadot/line/Nominating.svg
new file mode 100644
index 00000000..88207802
--- /dev/null
+++ b/assets/icons/polkadot/line/Nominating.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.8063 10.2429C15.1482 10.2429 20.8017 10.224 24.0544 10.2127C25.3424 10.2082 26.3854 11.251 26.3854 12.539V12.539C26.3854 13.8236 25.3439 14.8651 24.0593 14.8651L15.8327 14.8651L18.4876 14.8652C19.6072 14.8652 20.5149 15.9086 20.5149 17.1956C20.5149 18.4826 19.6072 19.5259 18.4876 19.5259L15.8327 19.5259L17.3597 19.5259C18.4794 19.5259 19.387 20.5939 19.387 21.8809C19.387 23.1679 18.4794 24.2112 17.3597 24.2112L15.2382 24.2112L12.4615 24.2112C8.52621 24.2111 6.95186 20.0641 6.95186 20.0641L1.38538 20.0641L1.38538 11.3893L6.95186 11.3893C6.95186 11.3893 7.49398 9.97422 9.56296 7.2054C11.4093 4.73458 13.1113 4.36533 13.4562 4.31447C13.4992 4.30813 13.5415 4.30683 13.5849 4.30683V4.30683C15.3328 4.30683 16.1822 6.50551 14.9953 7.78866C13.7981 9.08303 12.961 10.2429 13.8063 10.2429Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Nominators.svg b/assets/icons/polkadot/line/Nominators.svg
new file mode 100644
index 00000000..2119b3cd
--- /dev/null
+++ b/assets/icons/polkadot/line/Nominators.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.4273 6.57269H2V26H21.4273V6.57269Z"></path><path d="M7.11935 14.0187L12.3012 18.7889L25.0074 2" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Not Able To Upgrade.svg b/assets/icons/polkadot/line/Not Able To Upgrade.svg
new file mode 100644
index 00000000..5904c3ac
--- /dev/null
+++ b/assets/icons/polkadot/line/Not Able To Upgrade.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Not Scalable.svg b/assets/icons/polkadot/line/Not Scalable.svg
new file mode 100644
index 00000000..18b1f5b4
--- /dev/null
+++ b/assets/icons/polkadot/line/Not Scalable.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Notification.svg b/assets/icons/polkadot/line/Notification.svg
new file mode 100644
index 00000000..e815adb5
--- /dev/null
+++ b/assets/icons/polkadot/line/Notification.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Off-Chain Computations.svg b/assets/icons/polkadot/line/Off-Chain Computations.svg
new file mode 100644
index 00000000..c0276598
--- /dev/null
+++ b/assets/icons/polkadot/line/Off-Chain Computations.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Offboarding.svg b/assets/icons/polkadot/line/Offboarding.svg
new file mode 100644
index 00000000..de0f82bb
--- /dev/null
+++ b/assets/icons/polkadot/line/Offboarding.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/On-Chain Scheduling.svg b/assets/icons/polkadot/line/On-Chain Scheduling.svg
new file mode 100644
index 00000000..d9ee57b2
--- /dev/null
+++ b/assets/icons/polkadot/line/On-Chain Scheduling.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Onboarding.svg b/assets/icons/polkadot/line/Onboarding.svg
new file mode 100644
index 00000000..9cf4f12f
--- /dev/null
+++ b/assets/icons/polkadot/line/Onboarding.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Oracle.svg b/assets/icons/polkadot/line/Oracle.svg
new file mode 100644
index 00000000..8d90f259
--- /dev/null
+++ b/assets/icons/polkadot/line/Oracle.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Oracles.svg b/assets/icons/polkadot/line/Oracles.svg
new file mode 100644
index 00000000..9082b35b
--- /dev/null
+++ b/assets/icons/polkadot/line/Oracles.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M10.3184 5.13758C12.0523 3.21126 14.5652 2 17.3609 2C22.5922 2 26.8335 6.24131 26.8335 11.4726C26.8335 14.357 25.5398 16.9361 23.5065 18.6732C24.1455 20.145 25.3371 21.6183 25.9903 23.0838H21.497"></path><path d="M7.32699 21.5893H19.6183C21.6516 19.8522 22.9453 17.2732 22.9453 14.3888C22.9453 9.15744 18.704 4.91614 13.4726 4.91614C8.24131 4.91614 4 9.15744 4 14.3888C4 17.2732 5.29369 19.8514 7.32699 21.5893V21.5893Z"></path><path d="M18.3513 13.6518C18.3513 13.0895 18.1221 12.5515 17.7167 12.162L16.5722 11.0622C16.1884 10.6921 15.7371 10.4006 15.2433 10.2039C14.2368 9.80931 13.1205 9.80931 12.114 10.2039C11.6304 10.4039 11.1891 10.6952 10.8136 11.0622L9.63096 12.1719C9.22312 12.5546 8.99176 13.089 8.99176 13.6482V13.6482C8.99176 14.1904 9.2092 14.7098 9.59538 15.0903L10.7708 16.2484C11.3613 16.7985 12.093 17.1699 12.8826 17.3204C13.6721 17.4709 14.4877 17.3944 15.2362 17.0995C15.7282 16.9027 16.1791 16.6139 16.5651 16.2484L17.7168 15.1414C18.1222 14.7518 18.3513 14.2139 18.3513 13.6518V13.6518Z"></path><path d="M13.6973 13.6776L13.6714 13.6517" stroke-miterlimit="10"></path><path d="M20.1742 21.5894H6.77142C6.23114 22.8337 4.85297 26 4.85297 26H22.1021C21.4489 24.5344 20.8132 23.0611 20.1742 21.5894Z"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Overview.svg b/assets/icons/polkadot/line/Overview.svg
new file mode 100644
index 00000000..5b2fc514
--- /dev/null
+++ b/assets/icons/polkadot/line/Overview.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M11.5 26.1934H2V10.6934L14 2.19336L26 10.6934V26.1934H17V17.6934H11.5V26.1934Z"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Paper Money.svg b/assets/icons/polkadot/line/Paper Money.svg
new file mode 100644
index 00000000..b46e8f3c
--- /dev/null
+++ b/assets/icons/polkadot/line/Paper Money.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Parachains.svg b/assets/icons/polkadot/line/Parachains.svg
new file mode 100644
index 00000000..ba7dd01f
--- /dev/null
+++ b/assets/icons/polkadot/line/Parachains.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Payout.svg b/assets/icons/polkadot/line/Payout.svg
new file mode 100644
index 00000000..e38e43cd
--- /dev/null
+++ b/assets/icons/polkadot/line/Payout.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Picture.svg b/assets/icons/polkadot/line/Picture.svg
new file mode 100644
index 00000000..a3aa5c2d
--- /dev/null
+++ b/assets/icons/polkadot/line/Picture.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Podcasts.svg b/assets/icons/polkadot/line/Podcasts.svg
new file mode 100644
index 00000000..e2c8fbec
--- /dev/null
+++ b/assets/icons/polkadot/line/Podcasts.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Privacy.svg b/assets/icons/polkadot/line/Privacy.svg
new file mode 100644
index 00000000..521f3cb2
--- /dev/null
+++ b/assets/icons/polkadot/line/Privacy.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M5 6.71352V15.057C5 18.4564 6.7269 21.6229 9.58467 23.4638L15.0743 27L20.7036 23.3721C23.5604 21.531 25.2865 18.3651 25.2865 14.9665V6.71352L15.1386 3L5 6.71352Z"></path><path d="M11.6684 14.882L14.695 18.2419L20.2419 11.5736"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Private Key.svg b/assets/icons/polkadot/line/Private Key.svg
new file mode 100644
index 00000000..83f53d53
--- /dev/null
+++ b/assets/icons/polkadot/line/Private Key.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.4615 8.92308V2H5.00001V26H23.4615V7.98154"></path><path d="M12.7078 10.2655C12.4754 10.0111 12.2955 9.71338 12.1782 9.38936C12.0609 9.06533 12.0087 8.72134 12.0244 8.37703C12.0401 8.03272 12.1235 7.69484 12.2698 7.38267C12.4161 7.0705 12.6224 6.79016 12.877 6.55766C13.3961 6.09477 14.0775 5.85668 14.7717 5.89571C15.4659 5.93474 16.116 6.24769 16.5792 6.76581C16.8116 7.02023 16.9916 7.31795 17.1088 7.64198C17.2261 7.966 17.2784 8.30999 17.2626 8.6543C17.2469 8.99861 17.1635 9.33649 17.0172 9.64866C16.871 9.96083 16.6646 10.2412 16.41 10.4737C15.8909 10.9363 15.2095 11.1742 14.5154 11.1352C13.8213 11.0962 13.1712 10.7834 12.7078 10.2655V10.2655Z"></path><path d="M14.7961 11.2187L14.7747 22.1406"></path><path d="M14.2787 16.498L11.2861 16.4922L11.2751 20.1311L14.2669 20.1361"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Proof Of Stake.svg b/assets/icons/polkadot/line/Proof Of Stake.svg
new file mode 100644
index 00000000..4ac0bf4f
--- /dev/null
+++ b/assets/icons/polkadot/line/Proof Of Stake.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.4059 21.6734C8.10701 21.6734 3 18.7439 3 14.5446V18.8713C3 23.0706 8.10701 26 14.4059 26C20.7049 26 25.8119 23.0706 25.8119 18.8713V14.5456C25.8119 18.7449 20.7049 21.6734 14.4059 21.6734Z"></path><path d="M14.4268 17.2079C20.7257 17.2079 25.8328 13.8032 25.8328 9.60396C25.8328 5.40467 20.7257 2 14.4268 2C8.12788 2 3.02087 5.40467 3.02087 9.60396C3.02087 13.8032 8.12788 17.2079 14.4268 17.2079Z"></path><path d="M14.4268 17.2079C8.45295 17.2079 3.5598 14.1445 3.06935 10.2465H3.02087V14.5447C3.02087 18.7439 8.12788 21.6734 14.4268 21.6734C20.7257 21.6734 25.8328 18.7439 25.8328 14.5447V10.2465H25.7843C25.2938 14.1445 20.4007 17.2079 14.4268 17.2079Z"></path><path d="M19.1556 8.5H9.6507V12.8204H19.1556V8.5Z"></path><path d="M11.8109 8.03779L11.8109 7.27783V7.27783C11.8109 6.26587 12.6312 5.44553 13.6432 5.44553H15.1631C16.175 5.44553 16.9954 6.26587 16.9954 7.27783V7.27783L16.9954 8.03779"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Proof Of Work.svg b/assets/icons/polkadot/line/Proof Of Work.svg
new file mode 100644
index 00000000..fb4e2f24
--- /dev/null
+++ b/assets/icons/polkadot/line/Proof Of Work.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.4059 21.6734C8.10701 21.6734 3 18.7439 3 14.5446V18.8713C3 23.0706 8.10701 26 14.4059 26C20.7049 26 25.8119 23.0706 25.8119 18.8713V14.5456C25.8119 18.7449 20.7049 21.6734 14.4059 21.6734Z"></path><path d="M14.4268 17.2079C20.7257 17.2079 25.8328 13.8032 25.8328 9.60396C25.8328 5.40467 20.7257 2 14.4268 2C8.12788 2 3.02087 5.40467 3.02087 9.60396C3.02087 13.8032 8.12788 17.2079 14.4268 17.2079Z"></path><path d="M14.4268 17.2079C8.45295 17.2079 3.5598 14.1445 3.06935 10.2465H3.02087V14.5447C3.02087 18.7439 8.12788 21.6734 14.4268 21.6734C20.7257 21.6734 25.8328 18.7439 25.8328 14.5447V10.2465H25.7843C25.2938 14.1445 20.4007 17.2079 14.4268 17.2079Z"></path><path d="M10.6013 12.099L16.3042 8.29703"></path><path d="M13.4526 6.42194L18.0414 9.24751L19.1556 8.58527L16.5364 7.00225L13.47 6.39603L13.4526 6.42194Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Proposal.svg b/assets/icons/polkadot/line/Proposal.svg
new file mode 100644
index 00000000..c74c4cca
--- /dev/null
+++ b/assets/icons/polkadot/line/Proposal.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.4615 8.92308V2H5.00001V26H23.4615V7.98154"></path><path d="M19.7691 5.69211L8.6922 5.69211" stroke-miterlimit="10"></path><path d="M19.7692 9.38443H8.6922" stroke-miterlimit="10"></path><path d="M19.7693 17.879L16.2636 21.3846L14.8095 19.9305"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Proxy.svg b/assets/icons/polkadot/line/Proxy.svg
new file mode 100644
index 00000000..5da42bdd
--- /dev/null
+++ b/assets/icons/polkadot/line/Proxy.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2 6.28348C2 8.64918 3.91778 10.567 6.28348 10.567H21.6409C24.0066 10.567 25.9244 8.64918 25.9244 6.28348C25.9244 3.91778 24.0066 2 21.6409 2H6.28348C3.91778 2 2 3.91778 2 6.28348Z"></path><path d="M13.9685 26H6.28348C3.91778 26 2 24.0822 2 21.7165C2 19.3508 3.91778 17.433 6.28348 17.433H13.9559H21.6409C24.0066 17.433 25.9244 19.3508 25.9244 21.7165C25.9244 24.0822 24.0066 26 21.6409 26H13.9685Z"></path><path d="M13.9872 17.4341L13.9872 10.5681" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/ProxyAccount.svg b/assets/icons/polkadot/line/ProxyAccount.svg
new file mode 100644
index 00000000..f14c74b5
--- /dev/null
+++ b/assets/icons/polkadot/line/ProxyAccount.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.2244 26.0188C24.7573 26.0188 26 24.7761 26 23.2431C26 21.7102 24.7573 20.4675 23.2244 20.4675C21.6914 20.4675 20.4487 21.7102 20.4487 23.2431C20.4487 24.7761 21.6914 26.0188 23.2244 26.0188Z"></path><path d="M4.77564 26.019C6.30859 26.019 7.55129 24.7763 7.55129 23.2433C7.55129 21.7104 6.30859 20.4677 4.77564 20.4677C3.2427 20.4677 2 21.7104 2 23.2433C2 24.7763 3.2427 26.019 4.77564 26.019Z"></path><path d="M4.77592 20.473L4.77592 17.2704L22.8386 17.2704L22.8386 20.473" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M15.5201 6.45341L15.9264 5.93216C16.6865 4.95702 16.597 3.56744 15.7181 2.69784C14.7675 1.75724 13.2368 1.75725 12.2861 2.69785C11.4072 3.56745 11.3177 4.95701 12.0778 5.93217L12.4839 6.45329C12.7613 6.80912 12.5908 7.33254 12.1571 7.45679L11.5759 7.62332C9.89503 8.10488 8.73661 9.64179 8.73661 11.3903V13.1463H19.2634V11.3873C19.2634 9.64034 18.1061 8.10469 16.4268 7.62322L15.8468 7.45693C15.4132 7.3326 15.2428 6.8092 15.5201 6.45341Z"></path><path d="M13.9998 13.3159L13.9999 17.0078"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Public Key.svg b/assets/icons/polkadot/line/Public Key.svg
new file mode 100644
index 00000000..be99728f
--- /dev/null
+++ b/assets/icons/polkadot/line/Public Key.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.00001 2H23.4615V26H5.00001V2Z"></path><path d="M12.736 12.4191L12.2852 11.8857C11.4629 10.9126 11.5284 9.47051 12.4355 8.576C13.3848 7.63988 14.91 7.63988 15.8593 8.576C16.7664 9.47051 16.8319 10.9126 16.0096 11.8857L15.5589 12.419C15.2578 12.7753 15.4281 13.3237 15.878 13.4468L16.5409 13.6283C18.2966 14.1088 19.514 15.7042 19.514 17.5245V19.2259H14.1474H8.78522V17.5214C8.78522 15.7028 10.0014 14.1087 11.7555 13.6282L12.417 13.447C12.8669 13.3237 13.0371 12.7754 12.736 12.4191Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/QR Code.svg b/assets/icons/polkadot/line/QR Code.svg
new file mode 100644
index 00000000..17359907
--- /dev/null
+++ b/assets/icons/polkadot/line/QR Code.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.32 2.375H26V10.055" fill="none" data-nofill="true"></path><path d="M9.67999 26.375L1.99999 26.375L1.99999 17.735" fill="none" data-nofill="true"></path><path d="M26 18.695L26 26.375L18.32 26.375" fill="none" data-nofill="true"></path><path d="M2 10.055L2 2.37496L9.68 2.37496" fill="none" data-nofill="true"></path><path d="M12.0001 6.37503H6.00006V12.375H12.0001V6.37503Z"></path><path d="M22.0002 6.37506H16.0002V12.3751H22.0002V6.37506Z"></path><path d="M22.0002 16.375H16.0002V22.375H22.0002V16.375Z"></path><path d="M12.0001 16.375H6.00012V22.375H12.0001V16.375Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Randomness.svg b/assets/icons/polkadot/line/Randomness.svg
new file mode 100644
index 00000000..43805a0b
--- /dev/null
+++ b/assets/icons/polkadot/line/Randomness.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M1.25914 7L4.48384 7C7.25724 7 9.83277 8.43641 11.2902 10.796L15.2481 17.204C16.7056 19.5636 19.2811 21 22.0545 21L24 21L25.5 21" fill="none" data-nofill="true"></path><path d="M22.3968 17L26.24 20.9998L22.3968 25" fill="none" data-nofill="true"></path><path d="M1.25914 21L4.48384 21C7.25724 21 9.83277 19.5636 11.2902 17.204L15.2481 10.796C16.7056 8.43642 19.2811 7 22.0545 7L24 7L25.5 7" fill="none" data-nofill="true"></path><path d="M22.3968 11L26.24 7.0002L22.3968 3" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Read Time.svg b/assets/icons/polkadot/line/Read Time.svg
new file mode 100644
index 00000000..7c2496a5
--- /dev/null
+++ b/assets/icons/polkadot/line/Read Time.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M20.1537 15.8824V8.65379L14.5 3H4.00005V23.9998H12.5"></path><path d="M19.3281 8.6538H14.4999V4"></path><path d="M12.7499 19.1897H7.13043" stroke-miterlimit="10"></path><path d="M16 15.9621H7.13043" stroke-miterlimit="10"></path><path d="M18.5 27.25C21.6756 27.25 24.25 24.6756 24.25 21.5C24.25 18.3244 21.6756 15.75 18.5 15.75C15.3244 15.75 12.75 18.3244 12.75 21.5C12.75 24.6756 15.3244 27.25 18.5 27.25Z"></path><path d="M18.4153 19.1429V21.5143L17.4852 22.6429"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Recover Keys.svg b/assets/icons/polkadot/line/Recover Keys.svg
new file mode 100644
index 00000000..fdeaf363
--- /dev/null
+++ b/assets/icons/polkadot/line/Recover Keys.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 2.37497C14.8573 2.37497 15.6936 2.46487 16.5 2.63576M14 26.375C14.8573 26.375 15.6936 26.2851 16.5 26.1142M20.8199 4.5C21.9947 5.31288 23.0174 6.32999 23.8366 7.5M25.765 12C25.9191 12.7677 26 13.5619 26 14.375C26 15.188 25.9191 15.9822 25.765 16.7499M20.8199 24.2499C21.9947 23.4371 23.0174 22.4199 23.8366 21.2499" fill="none"></path><path d="M14 2.37494C7.37258 2.37494 2 7.74752 2 14.3749C2 21.0024 7.37258 26.3749 14 26.3749" fill="none"></path><path d="M17 15.1404L14.0013 18.1404L11 15.1413" fill="none"></path><path d="M13.9999 17L13.9999 10" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Recovery.svg b/assets/icons/polkadot/line/Recovery.svg
new file mode 100644
index 00000000..0618ea71
--- /dev/null
+++ b/assets/icons/polkadot/line/Recovery.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.89111 14.2763C5.89111 9.15314 10.06 5 15.2025 5C20.345 5 24.5139 9.15314 24.5139 14.2763C24.5139 19.3995 20.345 23.5526 15.2025 23.5526C12.1324 23.5526 9.40941 22.0724 7.71323 19.7893" fill="none" data-nofill="true"></path><path d="M8.87428 12.4629L5.97656 15.4395L3 12.5417" fill="none" data-nofill="true"></path><path d="M15.8432 10.1934V16.1934L13 19.6388" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Reddit.svg b/assets/icons/polkadot/line/Reddit.svg
new file mode 100644
index 00000000..eb387b14
--- /dev/null
+++ b/assets/icons/polkadot/line/Reddit.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.63636 21C9.63636 21 11.2727 22.0909 14 22.0909M24.9091 18.2727C24.9091 22.4902 20.0249 25.9091 14 25.9091C7.97508 25.9091 3.09091 22.4902 3.09091 18.2727C3.09091 17.7581 3.16363 17.2554 3.30227 16.7693L3.09091 16.6366C2.42848 16.139 2 15.3468 2 14.4545C2 12.9483 3.22104 11.7273 4.72727 11.7273C5.48668 11.7273 6.17359 12.0376 6.66808 12.5385L6.70692 12.5936C8.63936 11.3768 11.1962 10.6364 14 10.6364C16.7996 10.6364 19.3528 11.3745 21.2842 12.588C21.7817 12.0582 22.4886 11.7273 23.2727 11.7273C24.779 11.7273 26 12.9483 26 14.4545C26 15.4373 25.4801 16.2987 24.7004 16.7787C24.8373 17.2619 24.9091 17.7614 24.9091 18.2727Z"></path><path d="M14 22.0909C16.7273 22.0909 18.3636 21 18.3636 21"></path><path d="M22.1818 6.27273C23.0856 6.27273 23.8182 5.5401 23.8182 4.63636C23.8182 3.73263 23.0856 3 22.1818 3C21.2781 3 20.5455 3.73263 20.5455 4.63636C20.5455 5.5401 21.2781 6.27273 22.1818 6.27273Z"></path><path d="M14 10.6364L15.6364 3.54544L20.5455 4.63635" fill="none"></path><path d="M10.0002 16.3333L10.0222 16.3553" stroke-miterlimit="10"></path><path d="M18.0001 16.3333L18.0221 16.3553" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Referenda.svg b/assets/icons/polkadot/line/Referenda.svg
new file mode 100644
index 00000000..a522f750
--- /dev/null
+++ b/assets/icons/polkadot/line/Referenda.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 25.5212V19.3907H26V25.5212" fill="none"></path><path d="M15.7884 2L4.45782 13.3306L10.5202 19.393H14.8053L23.9933 10.2049L15.7884 2Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Refresh _ Redo.svg b/assets/icons/polkadot/line/Refresh _ Redo.svg
new file mode 100644
index 00000000..a90fc453
--- /dev/null
+++ b/assets/icons/polkadot/line/Refresh _ Redo.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M27.0754 13.8553C27.3379 17.5252 25.916 21.274 22.9052 23.8638C17.8618 28.202 10.2698 27.6457 5.94795 22.6213C1.62613 17.5969 2.21108 10.007 7.25448 5.66887C12.2979 1.33071 19.8899 1.88701 24.2117 6.9114L24.5001 7.50003" fill="none" data-nofill="true"></path><path d="M19.7563 7.64948L25.1091 8.12419L25.5838 2.77136" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Registrars.svg b/assets/icons/polkadot/line/Registrars.svg
new file mode 100644
index 00000000..6d542a9b
--- /dev/null
+++ b/assets/icons/polkadot/line/Registrars.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><rect x="4" y="2" width="20" height="24"></rect><path d="M11 20L13 22L17 18"></path><path d="M19.5184 8.23901L11.9806 8.23901M8.49249 8.23902L8.4817 8.23902"></path><path d="M19.5184 12.2612L11.9806 12.2612M8.49249 12.2612L8.4817 12.2612"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Regulators.svg b/assets/icons/polkadot/line/Regulators.svg
new file mode 100644
index 00000000..7adb8bff
--- /dev/null
+++ b/assets/icons/polkadot/line/Regulators.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Relay Chain.svg b/assets/icons/polkadot/line/Relay Chain.svg
new file mode 100644
index 00000000..2e92c4e5
--- /dev/null
+++ b/assets/icons/polkadot/line/Relay Chain.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M14 18C16.2091 18 18 16.2091 18 14C18 11.7909 16.2091 10 14 10C11.7909 10 10 11.7909 10 14C10 16.2091 11.7909 18 14 18Z"></path><path d="M14.0078 6.01711L13.9907 6" stroke-miterlimit="10"></path><path d="M14.0078 22L13.9907 21.9829" stroke-miterlimit="10"></path><path d="M21.9834 14.0086L22.0005 13.9915" stroke-miterlimit="10"></path><path d="M6 14.0086L6.01711 13.9915" stroke-miterlimit="10"></path><path d="M19.6507 8.36254V8.33691" stroke-miterlimit="10"></path><path d="M8.34877 19.6641V19.6385" stroke-miterlimit="10"></path><path d="M19.6379 19.6513H19.6636" stroke-miterlimit="10"></path><path d="M8.33597 8.34973H8.3616" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Remote Node.svg b/assets/icons/polkadot/line/Remote Node.svg
new file mode 100644
index 00000000..168f7d09
--- /dev/null
+++ b/assets/icons/polkadot/line/Remote Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.5521 9.40534L18.5262 5"></path><path d="M9.51626 5.0138L6.45081 9.39172"></path><path d="M20.4718 11.6062C20.4718 13.1383 21.7138 14.3803 23.2459 14.3803C24.778 14.3803 26.02 13.1383 26.02 11.6062C26.02 10.0741 24.778 8.83206 23.2459 8.83206C21.7138 8.83206 20.4718 10.0741 20.4718 11.6062Z"></path><path d="M2.00003 11.6062C2.00003 13.1383 3.24205 14.3803 4.77415 14.3803C6.30626 14.3803 7.54828 13.1383 7.54828 11.6062C7.54828 10.0741 6.30626 8.83206 4.77415 8.83206C3.24205 8.83206 2.00003 10.0741 2.00003 11.6062Z"></path><path d="M11.3726 20.6644C12.8292 22.1209 15.1907 22.1209 16.6473 20.6644C18.1038 19.2078 18.1038 16.8463 16.6473 15.3898C15.1907 13.9332 12.8292 13.9332 11.3726 15.3898C9.9161 16.8463 9.9161 19.2078 11.3726 20.6644Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Remove User.svg b/assets/icons/polkadot/line/Remove User.svg
new file mode 100644
index 00000000..cf37c7e7
--- /dev/null
+++ b/assets/icons/polkadot/line/Remove User.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26.0029 5.00293L20.0029 5.00293"></path><path d="M14.9827 12.7571L15.892 11.6639C17.4439 9.79815 17.3196 7.05748 15.6052 5.33986C13.7696 3.50082 10.7898 3.50082 8.95416 5.33986C7.23972 7.05748 7.11542 9.79815 8.66735 11.6639L9.57647 12.7569C10.1572 13.4551 9.82447 14.5199 8.94954 14.7632L7.71783 15.1057C4.34533 16.0436 2.01171 19.1147 2.01171 22.6152V25.9917H22.5393V22.6094C22.5393 19.1119 20.208 16.0432 16.8386 15.1055L15.6094 14.7634C14.7346 14.52 14.402 13.4552 14.9827 12.7571Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Remove.svg b/assets/icons/polkadot/line/Remove.svg
new file mode 100644
index 00000000..02e2b3d8
--- /dev/null
+++ b/assets/icons/polkadot/line/Remove.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9883 2.375C21.6157 2.375 26.9883 7.74758 26.9883 14.375C26.9883 21.0024 21.6157 26.375 14.9883 26.375C8.36086 26.375 2.98828 21.0024 2.98828 14.375C2.98828 7.74758 8.36086 2.375 14.9883 2.375Z"></path><path d="M9.79437 14.3156L20.184 14.3718"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Report.svg b/assets/icons/polkadot/line/Report.svg
new file mode 100644
index 00000000..5b2c4206
--- /dev/null
+++ b/assets/icons/polkadot/line/Report.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M20.4999 5.99969H23.9994V26H7.99969V22.0003"></path><path d="M19.9997 2V21.9994H4V2H19.9997Z"></path><path d="M4.48828 16.6885L8.59276 12.5838L11.6647 15.1438L16.2727 10.5358"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Reputation Systems.svg b/assets/icons/polkadot/line/Reputation Systems.svg
new file mode 100644
index 00000000..b48ca917
--- /dev/null
+++ b/assets/icons/polkadot/line/Reputation Systems.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.1408 12.0528L10.4136 11.6793L8.2547 8.10168L6.10812 11.6793L2 12.5922L4.78809 15.7134L4.40566 19.8586L8.26704 18.2054L10.2039 19.0258" stroke-miterlimit="10"></path><path d="M16.0756 12.0152L17.5866 11.6794L19.7332 8.10181L21.8921 11.6794L26.0002 12.5677L23.2245 15.7012L23.6193 19.8463L19.7455 18.2056L17.8149 19.0321" stroke-miterlimit="10"></path><path d="M20.2609 13.611L17.4851 16.7445L17.8799 20.8897L14.0062 19.2489L10.1448 20.902L10.5272 16.7569L7.73914 13.6357L11.8473 12.7228L13.9938 9.14514L16.1528 12.7228L20.2609 13.611Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Research.svg b/assets/icons/polkadot/line/Research.svg
new file mode 100644
index 00000000..bef29bf1
--- /dev/null
+++ b/assets/icons/polkadot/line/Research.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.772 2L24.772 26L4 25.9999L4 2L24.772 2Z"></path><path d="M20.8444 13.2181L20.8444 1.99995L14.621 1.99995L14.621 13.2236L17.7317 11.0341L20.8444 13.2181Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Reserve Back Assets.svg b/assets/icons/polkadot/line/Reserve Back Assets.svg
new file mode 100644
index 00000000..920ebd7b
--- /dev/null
+++ b/assets/icons/polkadot/line/Reserve Back Assets.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.0001 15.7966C14.9468 15.7966 15.7143 15.0245 15.7143 14.072C15.7143 13.1195 14.9468 12.3474 14.0001 12.3474C13.0533 12.3474 12.2858 13.1195 12.2858 14.072C12.2858 15.0245 13.0533 15.7966 14.0001 15.7966Z"></path><path d="M1.99983 26.0001L25.9993 26.0001L25.9993 19.9642L25.9995 11.4133L19.9996 11.4133L19.9996 19.9642L18.2497 19.9642L1.99983 19.9642L1.99983 26.0001Z"></path><path d="M25.9999 1.99988L2.00049 1.99988L2.00049 8.03579L2.00024 16.5867L8.00012 16.5867L8.00012 8.03579L9.75009 8.03579L25.9999 8.03579L25.9999 1.99988Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Restore From BackUp.svg b/assets/icons/polkadot/line/Restore From BackUp.svg
new file mode 100644
index 00000000..34b9641d
--- /dev/null
+++ b/assets/icons/polkadot/line/Restore From BackUp.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.87428 12.4629L5.97656 15.4395L3 12.5417" fill="none" data-nofill="true"></path><path d="M5.89111 14.2763C5.89111 9.15314 10.06 5 15.2025 5C20.345 5 24.5139 9.15314 24.5139 14.2763C24.5139 19.3995 20.345 23.5526 15.2025 23.5526C12.1324 23.5526 9.40941 22.0724 7.71323 19.7893" fill="none" data-nofill="true"></path><path d="M12.2654 14.6313L15.1631 11.6548L18.1396 14.5525" fill="none" data-nofill="true"></path><path d="M15.1631 12.5L15.1631 23.4966" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Retail And Ecommerce.svg b/assets/icons/polkadot/line/Retail And Ecommerce.svg
new file mode 100644
index 00000000..ff178454
--- /dev/null
+++ b/assets/icons/polkadot/line/Retail And Ecommerce.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.4217 16.7805L20.8978 21.9579C20.8978 21.9579 7.0277 21.9579 5.27405 21.9579" fill="none"></path><path d="M3.98242 5.95508H22.6752L19.4216 16.7806H7.84633L3.98242 5.95508Z"></path><path d="M22.5 6L23.7088 2.5625H26.2811"></path><circle cx="8.12782" cy="25.1373" r="1.71486" transform="rotate(-45 8.12782 25.1373)"></circle><circle cx="18.4173" cy="25.1373" r="1.71486" transform="rotate(-45 18.4173 25.1373)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Robust System.svg b/assets/icons/polkadot/line/Robust System.svg
new file mode 100644
index 00000000..2b4eb01e
--- /dev/null
+++ b/assets/icons/polkadot/line/Robust System.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M15.1328 2.56837L6.73413 10.967L12.9571 16.8913L14.4041 15.4607L21.2146 8.65016L15.1328 2.56837Z"></path><path d="M4.9223 21.1604V25.7046H22.712V21.1604H4.9223Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Rust.svg b/assets/icons/polkadot/line/Rust.svg
new file mode 100644
index 00000000..90aed145
--- /dev/null
+++ b/assets/icons/polkadot/line/Rust.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.5701 23.6137L17.078 26.4003L22.8004 23.1061L21.7057 19.5632L22.0074 18.6669L26.1742 17.8088V10.7457L22.5616 9.91973L21.7356 8.48664L22.8801 4.94373L17.1676 1.64961L14.6199 4.38642H12.9977L10.4998 1.59985L4.77736 4.89397L5.88203 8.49659L5.09582 9.86997L1.39368 10.6462V17.2544L5.06597 18.0903L5.86213 19.4637L4.68779 23.0564L10.4102 26.3605L12.948 23.6137H14.5701Z" stroke-miterlimit="10"></path><path d="M10 18.5357V14.1329M10 14.1329V9.46436H16.11C19.3918 9.46436 19.5186 14.1329 16.11 14.1329C15.1266 14.1329 15.1527 14.1329 14.3196 14.1329C12.9594 14.1329 10.8752 14.1329 10 14.1329ZM18.5812 18.5188L14.6763 14.5"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Save.svg b/assets/icons/polkadot/line/Save.svg
new file mode 100644
index 00000000..cb0a5673
--- /dev/null
+++ b/assets/icons/polkadot/line/Save.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 10.3145L26 26.9434L2 26.9434L2 2.94336L18.3436 2.94336L26 10.3145Z" stroke-miterlimit="10"></path><path d="M10.5714 3.5V11.5148H2.5" stroke-miterlimit="10"></path><path d="M16.4643 18.0862C16.4643 19.605 15.2331 20.8362 13.7143 20.8362C12.1955 20.8362 10.9643 19.605 10.9643 18.0862C10.9643 16.5675 12.1955 15.3362 13.7143 15.3362C15.2331 15.3362 16.4643 16.5675 16.4643 18.0862Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Scalability.svg b/assets/icons/polkadot/line/Scalability.svg
new file mode 100644
index 00000000..2ab3552f
--- /dev/null
+++ b/assets/icons/polkadot/line/Scalability.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M20.8572 2.01674L25.9634 2L25.9802 7.09755" fill="none" data-nofill="true"></path><path d="M7.12347 2.01674L2.01726 2L2.00049 7.09755" fill="none" data-nofill="true"></path><path d="M2.01674 20.877L2 25.9832L7.09755 26" fill="none" data-nofill="true"></path><path d="M25.964 20.877L25.9807 25.9832L20.8832 26" fill="none" data-nofill="true"></path><path d="M25.4783 2.67474L18.0904 9.96275" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M2.5026 2.67474L9.89059 9.96275" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M2.67484 25.498L9.96285 18.11" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M25.3061 25.498L18.0181 18.11" stroke-miterlimit="10" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Scale.svg b/assets/icons/polkadot/line/Scale.svg
new file mode 100644
index 00000000..a7b7f0dd
--- /dev/null
+++ b/assets/icons/polkadot/line/Scale.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.9909 22.0069C18.4194 22.0069 22.0094 18.4198 22.0094 13.9949C22.0094 9.56999 18.4194 5.98291 13.9909 5.98291C9.56233 5.98291 5.97229 9.56999 5.97229 13.9949C5.97229 18.4198 9.56233 22.0069 13.9909 22.0069Z" stroke-miterlimit="10"></path><path d="M14.0674 16.6526V10.9971" fill="none" data-nofill="true"></path><path d="M16.8975 13.8248L11.2373 13.8248" fill="none" data-nofill="true"></path><path d="M20.8724 2.01674L25.9828 2L25.9996 7.09755" fill="none" data-nofill="true"></path><path d="M25.4971 2.67468L19.7224 8.36656" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M7.12708 2.01674L2.01666 2L1.99988 7.09755" fill="none" data-nofill="true"></path><path d="M2.50257 2.67468L8.29218 8.36678" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M2.01675 20.877L2 25.9832L7.10175 25.9999" fill="none" data-nofill="true"></path><path d="M2.67505 25.498L8.39066 19.7087" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M25.9832 20.877L25.9999 25.9832L20.8982 25.9999" fill="none" data-nofill="true"></path><path d="M25.3246 25.498L19.6092 19.709" stroke-miterlimit="10" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Scaling.svg b/assets/icons/polkadot/line/Scaling.svg
new file mode 100644
index 00000000..6ad7a570
--- /dev/null
+++ b/assets/icons/polkadot/line/Scaling.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M16.4383 3.08008L25.4854 3.08009L25.4854 12.1331" fill="none" data-nofill="true"></path><path d="M16.4383 3.08008L25.4854 3.08009L25.4854 12.1331" fill="none" data-nofill="true"></path><path d="M25.3488 16.8559L25.3488 25.9029L16.2958 25.9029" fill="none" data-nofill="true"></path><path d="M2.52375 12.1301L2.52376 3.08306L11.5768 3.08306" fill="none" data-nofill="true"></path><path d="M11.5734 25.9059L2.52636 25.9059L2.52636 16.8528" fill="none" data-nofill="true"></path><path d="M24.8693 3.63065L3.12909 25.3708" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Scam Alert.svg b/assets/icons/polkadot/line/Scam Alert.svg
new file mode 100644
index 00000000..918e0335
--- /dev/null
+++ b/assets/icons/polkadot/line/Scam Alert.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.9898 3.12793L2.19775 24.872H25.7818L13.9898 3.12793Z" stroke-miterlimit="10"></path><path d="M11.2275 17.3172C11.2275 18.8504 12.4704 20.0933 14.0036 20.0933C15.5368 20.0933 16.7796 18.8504 16.7796 17.3172C16.7796 16.1286 16.0326 15.1144 14.9824 14.7186C14.4656 14.5239 14.0036 14.0934 14.0036 13.5412V4.3623"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Search.svg b/assets/icons/polkadot/line/Search.svg
new file mode 100644
index 00000000..ec0a5ec0
--- /dev/null
+++ b/assets/icons/polkadot/line/Search.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 22 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.8551 19.6652C15.7493 19.6652 19.716 15.6976 19.716 10.8043C19.716 5.91098 15.7493 1.94336 10.8551 1.94336C5.9608 1.94336 1.99414 5.91098 1.99414 10.8043C1.99414 15.6976 5.96176 19.6652 10.8551 19.6652Z" stroke-miterlimit="10"></path><path d="M16.7885 17.3718C15.6288 18.4208 14.1964 19.1721 12.6032 19.491L16.3743 26.0247L20.4296 23.683L16.7885 17.3718Z" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Second A Proposal.svg b/assets/icons/polkadot/line/Second A Proposal.svg
new file mode 100644
index 00000000..53b1f847
--- /dev/null
+++ b/assets/icons/polkadot/line/Second A Proposal.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M23.4615 8.92308V2H4.99999V26H23.4615V7.98154"></path><path d="M19.7691 5.69208L8.69221 5.69208" stroke-miterlimit="10"></path><path d="M19.7692 9.38446H8.69221" stroke-miterlimit="10"></path><path d="M20.2628 18.0844L16.963 21.3842L15.5942 20.0155"></path><path d="M13.0077 18.0844L9.70782 21.3842L8.3391 20.0155"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Secret Part Of The Derivation Path.svg b/assets/icons/polkadot/line/Secret Part Of The Derivation Path.svg
new file mode 100644
index 00000000..af0d122d
--- /dev/null
+++ b/assets/icons/polkadot/line/Secret Part Of The Derivation Path.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26L14.0001 22.8711M14.0001 5.12893L14.0001 2"></path><path d="M1.99999 14L5.12892 14.0001M22.8711 14.0001L26 14.0001"></path><path d="M14.0043 22.7311C18.7503 22.7311 22.5976 18.8837 22.5976 14.1378C22.5976 9.39189 18.7503 5.54456 14.0043 5.54456C9.25842 5.54456 5.41109 9.39189 5.41109 14.1378C5.41109 18.8837 9.25842 22.7311 14.0043 22.7311Z"></path><path d="M11.9876 13.1907L11.9876 11.6747C11.9876 11.1408 12.1997 10.6288 12.5772 10.2513C12.9547 9.87382 13.4667 9.66174 14.0005 9.66174C14.5331 9.6638 15.0431 9.87679 15.4189 10.2541C15.7947 10.6313 16.0057 11.1422 16.0057 11.6747V13.1907"></path><path d="M17.2103 13.3083H10.7906V17.6772H17.2103V13.3083Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Secure Device.svg b/assets/icons/polkadot/line/Secure Device.svg
new file mode 100644
index 00000000..88a82b00
--- /dev/null
+++ b/assets/icons/polkadot/line/Secure Device.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.5109 2H6V26H22.5109V2Z"></path><path d="M13.3055 22.7122H15.2053"></path><path d="M12.011 9.94757L12.011 8.25744C12.011 7.66224 12.2475 7.09142 12.6684 6.67055C13.0892 6.24969 13.6601 6.01324 14.2552 6.01324C14.8489 6.01554 15.4175 6.25299 15.8365 6.67361C16.2555 7.09423 16.4908 7.66374 16.4908 8.25744V9.94757"></path><path d="M16.834 10.0771H11.6768C11.1245 10.0771 10.6768 10.5248 10.6768 11.0771V13.9479C10.6768 14.5002 11.1245 14.9479 11.6768 14.9479H16.834C17.3863 14.9479 17.834 14.5002 17.834 13.9479V11.0771C17.834 10.5248 17.3863 10.0771 16.834 10.0771Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Security Check.svg b/assets/icons/polkadot/line/Security Check.svg
new file mode 100644
index 00000000..4532d5aa
--- /dev/null
+++ b/assets/icons/polkadot/line/Security Check.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M3.35229 5.23344V14.2632C3.35229 17.6625 5.07919 20.8291 7.93697 22.67L13.9277 26.529L20.065 22.5737C22.9217 20.7326 24.6478 17.5667 24.6478 14.1681V5.23344L13.9952 1.33521L3.35229 5.23344Z"></path><path d="M11.2649 12.4983V11.1572C11.2649 10.4318 11.553 9.73611 12.066 9.22319C12.5789 8.71027 13.2746 8.42212 13.9999 8.42212C14.7235 8.42491 15.4164 8.7143 15.9271 9.22691C16.4377 9.73953 16.7244 10.4336 16.7244 11.1572V12.4983"></path><path d="M18.3612 12.4983H9.63867V18H18.3612V12.4983Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Seed Phrase.svg b/assets/icons/polkadot/line/Seed Phrase.svg
new file mode 100644
index 00000000..c6e8df77
--- /dev/null
+++ b/assets/icons/polkadot/line/Seed Phrase.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 14.2622L7.99997 14.2622" stroke-miterlimit="10"></path><path d="M12 14.2622L21 14.2622" stroke-miterlimit="10"></path><path d="M25 14.2622L26 14.2622" stroke-miterlimit="10"></path><path d="M2 18.5244L6 18.5244" stroke-miterlimit="10"></path><path d="M10 18.5244L12 18.5244" stroke-miterlimit="10"></path><path d="M16 18.5244L26 18.5244" stroke-miterlimit="10"></path><path d="M2 10L3.68974 10" stroke-miterlimit="10"></path><path d="M21.6897 10L25.6897 10" stroke-miterlimit="10"></path><path d="M7.68974 10L17.6897 10" stroke-miterlimit="10"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Select List Item.svg b/assets/icons/polkadot/line/Select List Item.svg
new file mode 100644
index 00000000..66d3ad0c
--- /dev/null
+++ b/assets/icons/polkadot/line/Select List Item.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M13.9824 25.9434C20.6098 25.9434 25.9824 20.5708 25.9824 13.9434C25.9824 7.31594 20.6098 1.94336 13.9824 1.94336C7.355 1.94336 1.98242 7.31594 1.98242 13.9434C1.98242 20.5708 7.355 25.9434 13.9824 25.9434Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Session.svg b/assets/icons/polkadot/line/Session.svg
new file mode 100644
index 00000000..f89cdda7
--- /dev/null
+++ b/assets/icons/polkadot/line/Session.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.311 25.1507C19.4533 25.1507 23.6219 20.982 23.6219 15.8397C23.6219 10.6974 19.4533 6.52875 14.311 6.52875C9.16866 6.52875 5 10.6974 5 15.8397C5 20.982 9.16866 25.1507 14.311 25.1507Z"></path><path d="M14.3101 10.9698V16.6254L12.0919 19.3169"></path><path d="M14.2964 6.52924L14.2964 2.00003"></path><path d="M17.3588 2.01202L11.2617 2.01202"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Settings.svg b/assets/icons/polkadot/line/Settings.svg
new file mode 100644
index 00000000..001886a0
--- /dev/null
+++ b/assets/icons/polkadot/line/Settings.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14.7512 23.3034L17.1782 26L22.7159 22.8122L21.6565 19.3836L22.0799 18.1124L25.9807 17.4421V10.8507L22.4848 10.0514L21.6854 8.66453L22.7929 5.23596L17.2648 2.04815L14.7994 4.69663H13.2295L10.8122 2L5.27448 5.1878L6.3435 8.67416L5.58266 10.0032L2 10.7544V17.1493L5.55377 17.9583L6.32424 19.2873L5.1878 22.764L10.7255 25.9615L13.1814 23.3034H14.7512Z" stroke-miterlimit="10"></path><path d="M14 18C16.2091 18 18 16.2091 18 14C18 11.7909 16.2091 10 14 10C11.7909 10 10 11.7909 10 14C10 16.2091 11.7909 18 14 18Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Sharding.svg b/assets/icons/polkadot/line/Sharding.svg
new file mode 100644
index 00000000..216d4c0a
--- /dev/null
+++ b/assets/icons/polkadot/line/Sharding.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.955 6.49153C15.8154 6.49153 17.3236 5.48604 17.3236 4.24576C17.3236 3.00548 15.8154 2 13.955 2C12.0945 2 10.5863 3.00548 10.5863 4.24576C10.5863 5.48604 12.0945 6.49153 13.955 6.49153V6.49153Z"></path><path d="M7.10977 17.7639L10.2502 12.3701"></path><path d="M20.8012 17.7639L17.6607 12.3701"></path><path d="M5.82499 26C7.93726 26 9.64998 24.8582 9.64998 23.4503C9.64998 22.0425 7.93726 20.9006 5.82499 20.9006C3.71273 20.9006 2 22.0425 2 23.4503C2 24.8582 3.71273 26 5.82499 26Z"></path><path d="M22.2015 26C24.3137 26 26.0264 24.8582 26.0264 23.4503C26.0264 22.0425 24.3137 20.9006 22.2015 20.9006C20.0892 20.9006 18.3765 22.0425 18.3765 23.4503C18.3765 24.8582 20.0892 26 22.2015 26Z"></path><path d="M17.3236 4.24585C17.3236 5.48613 15.8154 6.49161 13.955 6.49161C12.0946 6.49161 10.5863 5.48613 10.5863 4.24585V7.65047C10.5863 8.89075 12.0946 9.75611 13.955 9.75611C15.8154 9.75611 17.3236 8.89075 17.3236 7.65047V4.24585Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Share.svg b/assets/icons/polkadot/line/Share.svg
new file mode 100644
index 00000000..52d79c68
--- /dev/null
+++ b/assets/icons/polkadot/line/Share.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 23 27" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M16.177 5.8259L8.4267 11.2527"></path><path d="M8.38375 15.455L16.3078 21.0035"></path><path d="M18.4763 7.05535C20.0072 7.05535 21.2482 5.81437 21.2482 4.28354C21.2482 2.7527 20.0072 1.51172 18.4763 1.51172C16.9455 1.51172 15.7045 2.7527 15.7045 4.28354C15.7045 5.81437 16.9455 7.05535 18.4763 7.05535Z"></path><path d="M18.4763 25.5117C20.0072 25.5117 21.2482 24.2707 21.2482 22.7399C21.2482 21.2091 20.0072 19.9681 18.4763 19.9681C16.9455 19.9681 15.7045 21.2091 15.7045 22.7399C15.7045 24.2707 16.9455 25.5117 18.4763 25.5117Z"></path><path d="M7.90533 15.9753C9.36066 14.52 9.36066 12.1604 7.90533 10.7051C6.45 9.24977 4.09044 9.24977 2.63511 10.7051C1.17978 12.1604 1.17978 14.52 2.63511 15.9753C4.09044 17.4307 6.45 17.4307 7.90533 15.9753Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Shared Security.svg b/assets/icons/polkadot/line/Shared Security.svg
new file mode 100644
index 00000000..d34e7099
--- /dev/null
+++ b/assets/icons/polkadot/line/Shared Security.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.9349 25.9999C15.4059 25.9999 16.5981 24.8077 16.5981 23.3367C16.5981 21.8657 15.4059 20.6735 13.9349 20.6735C12.4639 20.6735 11.2716 21.8657 11.2716 23.3367C11.2716 24.8077 12.4639 25.9999 13.9349 25.9999V25.9999Z"></path><path d="M23.8451 8.52062C25.3161 8.52062 26.5083 7.32839 26.5083 5.85739C26.5083 4.38639 25.3161 3.19415 23.8451 3.19415C22.3741 3.19415 21.1818 4.38639 21.1818 5.85739C21.1818 7.32839 22.3741 8.52062 23.8451 8.52062Z"></path><path d="M4.66323 8.52068C6.13423 8.52068 7.32647 7.32845 7.32647 5.85745C7.32647 4.38645 6.13423 3.19421 4.66323 3.19421C3.19223 3.19421 2 4.38645 2 5.85745C2 7.32845 3.19223 8.52068 4.66323 8.52068Z"></path><path d="M23.8451 8.52063C22.3741 8.52063 21.1818 7.32839 21.1818 5.8574C21.1818 5.43394 21.2899 5.03942 21.4654 4.68445L14.1288 2L7.00237 4.61018C7.20204 4.98348 7.32647 5.40404 7.32647 5.8574C7.32647 7.32839 6.13424 8.52063 4.66324 8.52063C4.58028 8.52063 4.50215 8.50327 4.42113 8.49651V14.0313C4.42113 16.983 5.9201 19.7311 8.40103 21.3294L11.2871 23.1882C11.3652 21.7876 12.515 20.6735 13.9349 20.6735C15.4059 20.6735 16.5981 21.8657 16.5981 23.3367V23.3483L19.8661 21.2416C22.3461 19.6433 23.8451 16.8952 23.8451 13.9445V8.52063Z"></path><path d="M11.6575 11.9555V10.2395C11.6575 9.58362 11.9179 8.95374 12.3828 8.48978C12.8468 8.02581 13.4767 7.7644 14.1326 7.7644C14.7876 7.7673 15.4145 8.0287 15.8766 8.49267C16.3386 8.95664 16.5981 9.58459 16.5981 10.2395V11.9555"></path><path d="M18.0797 12.2469H10.1865V17.2251H18.0797V12.2469Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Sign A Transaction.svg b/assets/icons/polkadot/line/Sign A Transaction.svg
new file mode 100644
index 00000000..60ebeaa0
--- /dev/null
+++ b/assets/icons/polkadot/line/Sign A Transaction.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.31907 24.7504H1.28955" stroke-miterlimit="10"></path><path d="M22.66 11.3802L26.0365 14.7567L17.6232 23.17L13.1 24.3123L14.2467 19.7935L22.66 11.3802Z"></path><path d="M12.9304 2.00269L16.2097 5.28203L12.9304 8.56689" fill="none" data-nofill="true"></path><path d="M15.3611 5.28467L1.95577 5.28468"></path><path d="M5.23512 15.1311L1.95577 11.8462L5.23512 8.56689" fill="none" data-nofill="true"></path><path d="M2.76658 11.8463L16.2054 11.8463"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Sign Specs.svg b/assets/icons/polkadot/line/Sign Specs.svg
new file mode 100644
index 00000000..49cebca8
--- /dev/null
+++ b/assets/icons/polkadot/line/Sign Specs.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26.9941 3.93292H2.99414V24.152H26.9941V3.93292Z"></path><path d="M19.4461 11.9332L14.724 16.6553L9.99401 11.9332"></path><path d="M14.7202 15.5L14.7202 4.5"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Sign.svg b/assets/icons/polkadot/line/Sign.svg
new file mode 100644
index 00000000..913191f2
--- /dev/null
+++ b/assets/icons/polkadot/line/Sign.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.74995 18.9047H2" stroke-miterlimit="10"></path><path d="M22.741 6L26 9.25894L17.5632 17.6957L13.091 18.9048L14.3043 14.4367L22.741 6Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Signal.svg b/assets/icons/polkadot/line/Signal.svg
new file mode 100644
index 00000000..85da05b7
--- /dev/null
+++ b/assets/icons/polkadot/line/Signal.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11.2222 13.5555L11.2222 26"></path><path d="M5 19.7778L5 26"></path><path d="M17.4444 8.22223L17.4444 26"></path><path d="M23.6667 2L23.6667 26"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Signature.svg b/assets/icons/polkadot/line/Signature.svg
new file mode 100644
index 00000000..60a4d6f0
--- /dev/null
+++ b/assets/icons/polkadot/line/Signature.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.7452 7L26 10.2548L17.5739 18.6809L13.1074 19.8885L14.3191 15.4261L22.7452 7Z"></path><path d="M9.77046 19.8888H9.02152C8.33752 19.8888 7.7297 19.5399 7.50598 19.0191L7.33759 18.6263C7.02251 17.9154 6.46324 17.5852 5.88964 17.5817C5.31605 17.5852 4.74795 17.9154 4.43288 18.6263L4.26448 19.0191C4.04076 19.5399 3.43294 19.8888 2.74895 19.8888H2" stroke-miterlimit="10" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Signifier Tab.svg b/assets/icons/polkadot/line/Signifier Tab.svg
new file mode 100644
index 00000000..b24ca4d2
--- /dev/null
+++ b/assets/icons/polkadot/line/Signifier Tab.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2.98828 14.5117H26.9883"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Smart Contract.svg b/assets/icons/polkadot/line/Smart Contract.svg
new file mode 100644
index 00000000..78217ea2
--- /dev/null
+++ b/assets/icons/polkadot/line/Smart Contract.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M12.4846 4.61499H26.7098V9.94946V23.1078H12.4846V4.61499Z"></path><path d="M22.9999 8.68042H16.3901" stroke-miterlimit="10"></path><path d="M20.2458 12.6602H16.3901" stroke-miterlimit="10"></path><path d="M22.9999 19.3152H16.3901" stroke-miterlimit="10"></path><path d="M4.45978 14.1587L12.4465 14.1587" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M4.45977 5.18872L7.63774 5.18872L7.63774 23L4.45972 23" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M1.26074 5.18872L1.24995 5.18872"></path><path d="M1.26074 14.1587L1.24995 14.1587"></path><path d="M1.26074 23L1.24995 23"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Social Impact & Humanitarian.svg b/assets/icons/polkadot/line/Social Impact & Humanitarian.svg
new file mode 100644
index 00000000..f6967975
--- /dev/null
+++ b/assets/icons/polkadot/line/Social Impact & Humanitarian.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Social Networking.svg b/assets/icons/polkadot/line/Social Networking.svg
new file mode 100644
index 00000000..7eb85c4c
--- /dev/null
+++ b/assets/icons/polkadot/line/Social Networking.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M16.5769 6.74188L16.9633 6.24627C17.686 5.31907 17.6009 3.99783 16.7652 3.17099C15.8613 2.27664 14.4059 2.27666 13.5019 3.171C12.6663 3.99784 12.5812 5.31907 13.3038 6.24628L13.6901 6.74177C13.9538 7.0801 13.7917 7.57778 13.3793 7.69593L12.8267 7.85426C11.2285 8.31215 10.127 9.77348 10.127 11.436V13.1056H20.1361V11.4332C20.1361 9.77209 19.0358 8.31197 17.4391 7.85417L16.8876 7.69606C16.4753 7.57784 16.3132 7.08018 16.5769 6.74188Z"></path><path d="M23.2969 20.1929L23.6832 19.6973C24.406 18.7701 24.3209 17.4489 23.4852 16.622C22.5813 15.7277 21.1258 15.7277 20.2219 16.6221C19.3862 17.4489 19.3011 18.7701 20.0238 19.6973L20.41 20.1928C20.6737 20.5311 20.5116 21.0288 20.0993 21.147L19.5466 21.3053C17.9484 21.7632 16.847 23.2245 16.847 24.887V26.5567H26.8561V24.8842C26.8561 23.2231 25.7558 21.763 24.159 21.3052L23.6075 21.1471C23.1952 21.0289 23.0332 20.5312 23.2969 20.1929Z"></path><path d="M9.84585 20.1929L10.2322 19.6973C10.9549 18.7701 10.8698 17.4489 10.0341 16.622C9.13021 15.7277 7.67479 15.7277 6.77087 16.6221C5.93519 17.4489 5.85007 18.7701 6.57277 19.6973L6.95898 20.1928C7.22268 20.5311 7.06059 21.0288 6.64823 21.147L6.09557 21.3053C4.49737 21.7632 3.39592 23.2245 3.39592 24.887V26.5567H13.405V24.8842C13.405 23.2231 12.3047 21.763 10.708 21.3052L10.1565 21.1471C9.74418 21.0289 9.58216 20.5312 9.84585 20.1929Z"></path><path d="M14.93 17.2586L19.4675 20.3067M10.5389 20.2033L14.9224 17.2586V13.1639" fill="none" data-nofill="true"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Software Development.svg b/assets/icons/polkadot/line/Software Development.svg
new file mode 100644
index 00000000..9e24365d
--- /dev/null
+++ b/assets/icons/polkadot/line/Software Development.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M1.99997 27L26.2441 27L26.2441 3L1.99997 3L1.99997 27Z"></path><path d="M26.2371 9.57935H2.00026"></path><path d="M9.32502 6.46778L9.30768 6.45044" stroke-miterlimit="10"></path><path d="M5.50117 6.46778L5.48383 6.45044" stroke-miterlimit="10"></path><path d="M10.2498 20.2866L7.39581 17.9107L10.2498 15.53"></path><path d="M18.2633 15.5205L21.1268 17.906L18.2633 20.2866"></path><path d="M15.8593 13.1421L12.6537 22.674"></path></g></svg>
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diff --git a/assets/icons/polkadot/line/Specialised.svg b/assets/icons/polkadot/line/Specialised.svg
new file mode 100644
index 00000000..772fb026
--- /dev/null
+++ b/assets/icons/polkadot/line/Specialised.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.8717 26.7691C20.9049 26.7691 26.6064 21.0676 26.6064 14.0344C26.6064 7.0013 20.9049 1.2998 13.8717 1.2998C6.83858 1.2998 1.13708 7.0013 1.13708 14.0344C1.13708 21.0676 6.83858 26.7691 13.8717 26.7691Z"></path><path d="M20.0753 12.2127L17.325 15.3174L17.7161 19.4246L13.8779 17.7988L10.0519 19.4368L10.4309 15.3297L7.66833 12.2371L11.7388 11.3326L13.8657 7.78772L16.0048 11.3326L20.0753 12.2127Z" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Stablecoin.svg b/assets/icons/polkadot/line/Stablecoin.svg
new file mode 100644
index 00000000..9f072ec4
--- /dev/null
+++ b/assets/icons/polkadot/line/Stablecoin.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><circle cx="6" cy="9" r="3"></circle><circle cx="22" cy="9" r="3"></circle><path d="M14.5 15H14.5276L19.2631 23.25H9.73682L14.5 15Z"></path><path d="M24 15L4 15"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Stake.svg b/assets/icons/polkadot/line/Stake.svg
new file mode 100644
index 00000000..d544969d
--- /dev/null
+++ b/assets/icons/polkadot/line/Stake.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.735 15.924V18.5202C24.735 22.3374 20.0933 24.9999 14.3675 24.9999C8.64169 24.9999 4 22.3374 4 18.5202V15.924"></path><path d="M14.3675 21.9761C20.0933 21.9761 24.735 18.8817 24.735 15.0644C24.735 11.2472 20.0933 8.15277 14.3675 8.15277C8.64169 8.15277 4 11.2472 4 15.0644C4 18.8817 8.64169 21.9761 14.3675 21.9761Z"></path><path d="M14.3678 2.99997L14.3678 15.3903M11.3078 13.3305L14.3676 16.3902L17.4273 13.3305"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Staking.svg b/assets/icons/polkadot/line/Staking.svg
new file mode 100644
index 00000000..45bf6ca7
--- /dev/null
+++ b/assets/icons/polkadot/line/Staking.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 12.958V16C25 20.0501 20.0751 22.875 14 22.875C7.92487 22.875 3 20.0501 3 16V12.958"></path><path d="M14 19.6667C20.0751 19.6667 25 16.3834 25 12.3333C25 8.28325 20.0751 5 14 5C7.92487 5 3 8.28325 3 12.3333C3 16.3834 7.92487 19.6667 14 19.6667Z"></path><path d="M11 13.5335L14.178 15.9725L17.356 13.5335"></path><path d="M14.1998 15.203L14.1998 9"></path></svg>
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diff --git a/assets/icons/polkadot/line/Starting Period.svg b/assets/icons/polkadot/line/Starting Period.svg
new file mode 100644
index 00000000..7e74587c
--- /dev/null
+++ b/assets/icons/polkadot/line/Starting Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M14.0002 14.0929L14.0001 5.9647"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Success.svg b/assets/icons/polkadot/line/Success.svg
new file mode 100644
index 00000000..29198d2c
--- /dev/null
+++ b/assets/icons/polkadot/line/Success.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M9.53394 13.4026L13.1421 16.7726L19.7548 10.0842"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Supply Chain.svg b/assets/icons/polkadot/line/Supply Chain.svg
new file mode 100644
index 00000000..5ce10c43
--- /dev/null
+++ b/assets/icons/polkadot/line/Supply Chain.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M10.4636 5.76844C10.4636 7.84969 12.1507 9.53687 14.232 9.53687C16.3132 9.53688 18.0004 7.84969 18.0004 5.76844C18.0004 3.68719 16.3132 2 14.232 2C12.1507 2 10.4636 3.68719 10.4636 5.76844Z"></path><path d="M10.2056 5.76839L5.38863 5.76839L5.38863 18.5M8.66691 16.2038L5.38863 19.5819L2.00021 16.2933" fill="none"></path><path d="M16.838 22.2316C16.838 20.1503 15.1508 18.4631 13.0696 18.4631C10.9883 18.4631 9.30113 20.1503 9.30113 22.2316C9.30113 24.3128 10.9883 26 13.0696 26C15.1508 26 16.838 24.3128 16.838 22.2316Z"></path><path d="M17.0962 22.2316L21.9132 22.2316L21.9132 9.5M18.6349 11.7962L21.9132 8.41809L25.3016 11.7067" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Talent.svg b/assets/icons/polkadot/line/Talent.svg
new file mode 100644
index 00000000..5455f26a
--- /dev/null
+++ b/assets/icons/polkadot/line/Talent.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.1443 24.8612H2V21.6582C2 18.3465 4.20777 15.4407 7.39797 14.553L8.56208 14.2292C9.39049 13.9981 9.70546 12.99 9.15549 12.3295L8.29451 11.2947C6.82529 9.5283 6.94279 6.93349 8.56603 5.3063C10.3038 3.56457 13.1257 3.56457 14.8635 5.3063C16.4867 6.9325 16.6042 9.52732 15.135 11.2947L14.274 12.3295C13.7241 12.991 14.039 13.9991 14.8674 14.2292L17.0308 14.8305C18.0438 15.1119 18.8278 15.7784 19.2879 16.6157"></path><path d="M22.403 17.691L26 18.4869L23.5681 21.2258L23.9137 24.8544L20.527 23.4148L17.1433 24.8623L17.4829 21.2327L15.0451 18.4987L18.6411 17.695L20.5171 14.5591L22.402 17.691H22.403Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Technical Committee.svg b/assets/icons/polkadot/line/Technical Committee.svg
new file mode 100644
index 00000000..142e320e
--- /dev/null
+++ b/assets/icons/polkadot/line/Technical Committee.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18 8.05658C21.2203 9.48819 23.4659 12.7152 23.4659 16.4666C23.4659 16.6457 23.4608 16.8235 23.4507 17M10.5337 8.05658C7.31336 9.48819 5.06775 12.7152 5.06775 16.4666C5.06775 16.6457 5.07286 16.8235 5.08295 17M8.98605 24C10.4806 25.0496 12.3018 25.6657 14.2668 25.6657C16.4348 25.6657 18.4276 24.9158 20 23.6611" stroke-miterlimit="10" fill="none" data-nofill="true"></path><circle cx="14.267" cy="7.26689" r="3.72426" transform="rotate(45 14.267 7.26689)"></circle><circle cx="6.26689" cy="21.0003" r="3.72426" transform="rotate(45 6.26689 21.0003)"></circle><circle cx="22.2669" cy="21.0003" r="3.72426" transform="rotate(45 22.2669 21.0003)"></circle></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Teleport.svg b/assets/icons/polkadot/line/Teleport.svg
new file mode 100644
index 00000000..2635f5fa
--- /dev/null
+++ b/assets/icons/polkadot/line/Teleport.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Testnet Token.svg b/assets/icons/polkadot/line/Testnet Token.svg
new file mode 100644
index 00000000..7668789e
--- /dev/null
+++ b/assets/icons/polkadot/line/Testnet Token.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 12.958V16C25 20.0501 20.0751 22.875 14 22.875C7.92487 22.875 3 20.0501 3 16V12.958"></path><path d="M14 19.6667C20.0751 19.6667 25 16.3834 25 12.3333C25 8.28325 20.0751 5 14 5C7.92487 5 3 8.28325 3 12.3333C3 16.3834 7.92487 19.6667 14 19.6667Z"></path><path d="M16.7515 9.63147L11.2514 15.1314"></path><path d="M16.7515 15.1315L11.2515 9.63143"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Thumbs Down.svg b/assets/icons/polkadot/line/Thumbs Down.svg
new file mode 100644
index 00000000..1061c5f1
--- /dev/null
+++ b/assets/icons/polkadot/line/Thumbs Down.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M16.1401 17.2978L23.2372 17.2978C24.5958 17.2978 25.6972 16.1964 25.6972 14.8378C25.6972 13.4792 24.5958 12.3778 23.2372 12.3778L22.2221 12.3778L23.894 12.3777C25.0442 12.3777 25.9766 11.2763 25.9766 9.9177C25.9766 8.5591 25.0442 7.45773 23.894 7.45773L21.7877 7.45773C22.9378 7.45773 23.8344 6.52958 23.8344 4.97169C23.8344 3.61309 22.5034 2.51172 21.3533 2.51172L18.9656 2.51172L15.3542 2.51177C11.3118 2.51187 9.69461 6.65141 9.69461 6.65141L3.97656 6.65141L3.97656 15.7957L9.69461 15.8378C9.69461 15.8378 12.1378 21.1212 14.1473 25.3328C14.7178 26.5283 16.1657 27.0065 17.3405 26.3945C18.3949 25.8453 18.8739 24.5958 18.4569 23.4825L16.1401 17.2978Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Thumbs Up.svg b/assets/icons/polkadot/line/Thumbs Up.svg
new file mode 100644
index 00000000..7230d76b
--- /dev/null
+++ b/assets/icons/polkadot/line/Thumbs Up.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Time.svg b/assets/icons/polkadot/line/Time.svg
new file mode 100644
index 00000000..510c4f18
--- /dev/null
+++ b/assets/icons/polkadot/line/Time.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M18.6157 12.1538L14.0002 14.9229L14.0001 6.34801"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Token Holders.svg b/assets/icons/polkadot/line/Token Holders.svg
new file mode 100644
index 00000000..2a8ab669
--- /dev/null
+++ b/assets/icons/polkadot/line/Token Holders.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Token.svg b/assets/icons/polkadot/line/Token.svg
new file mode 100644
index 00000000..02d2a25f
--- /dev/null
+++ b/assets/icons/polkadot/line/Token.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 12.761V16.066C26 20.4843 20.6274 23.566 14 23.566C7.37258 23.566 2 20.4843 2 16.066V12.761"></path><path d="M14 20.0801C20.627 20.0801 26 16.4981 26 12.0801C26 7.66208 20.627 4.08008 14 4.08008C7.373 4.08008 2 7.66208 2 12.0801C2 16.4981 7.373 20.0801 14 20.0801Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Tools.svg b/assets/icons/polkadot/line/Tools.svg
new file mode 100644
index 00000000..27025388
--- /dev/null
+++ b/assets/icons/polkadot/line/Tools.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11 7.00002H4M4 2L11 2V20.2857L7.5 26L4 20.2857L4 2Z"></path><path d="M20.5001 7.99993L17 7.99993M20.4998 13.9999H17M20.5001 19.6434H17M17 2L24 2V26H17V2Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Transaction.svg b/assets/icons/polkadot/line/Transaction.svg
new file mode 100644
index 00000000..e4747597
--- /dev/null
+++ b/assets/icons/polkadot/line/Transaction.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M2 8.47366L25 8.47366M20.4787 2.95239L26 8.47366L20.4787 14.0044" fill="none"></path><path d="M25.9918 19.5213H3M7.52138 25.0521L2 19.5213L7.52138 14.0001" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Translate.svg b/assets/icons/polkadot/line/Translate.svg
new file mode 100644
index 00000000..230aefd4
--- /dev/null
+++ b/assets/icons/polkadot/line/Translate.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M15.8744 21.235C15.2639 21.2887 14.6393 21.2849 14.0069 21.2184C12.7105 21.0822 11.5011 20.6953 10.4218 20.1112L4.79846 24.0642L7.47592 17.6476C5.94344 15.7325 5.13538 13.2365 5.41203 10.6044C5.69652 7.89795 7.10601 5.83942 9 4M12.8317 2.20431C13.8511 1.96766 14.9267 1.89399 16.026 2.00954C21.3304 2.56709 25.1785 7.31913 24.6209 12.6235C24.2828 15.8405 22.4716 18.3021 19.7768 19.8463" fill="none" data-nofill="true"></path><path d="M9.6192 7.73853L9.47795 3.24239L4.9818 3.38364" fill="none" data-nofill="true"></path><path d="M20.0228 15.5961L19.2373 20.0253L23.6665 20.8108" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Transparency.svg b/assets/icons/polkadot/line/Transparency.svg
new file mode 100644
index 00000000..8f986197
--- /dev/null
+++ b/assets/icons/polkadot/line/Transparency.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.2303 26C18.9647 26 20.6601 25.4857 22.1022 24.5221C23.5443 23.5586 24.6683 22.189 25.332 20.5866C25.9957 18.9842 26.1694 17.2211 25.831 15.52C25.4927 13.8189 24.6575 12.2564 23.4311 11.03C22.2047 9.8036 20.6421 8.96841 18.9411 8.63005C17.24 8.29169 15.4768 8.46535 13.8744 9.12907C12.2721 9.79279 10.9025 10.9168 9.93894 12.3589C8.97537 13.8009 8.46106 15.4964 8.46106 17.2308C8.46106 17.8296 8.52231 18.4222 8.64135 19C8.98462 20.6663 9.80841 22.2105 11.0295 23.4316C12.6741 25.0761 14.9045 26 17.2303 26Z"></path><path d="M10.7692 19.5385C12.5036 19.5385 14.1991 19.0242 15.6411 18.0606C17.0832 17.097 18.2072 15.7274 18.8709 14.1251C19.5347 12.5227 19.7083 10.7595 19.37 9.05844C19.0316 7.35738 18.1964 5.79485 16.97 4.56845C15.7436 3.34205 14.1811 2.50686 12.48 2.1685C10.779 1.83014 9.01576 2.0038 7.41339 2.66752C5.81102 3.33124 4.44146 4.45522 3.47788 5.89731C2.51431 7.3394 2 9.03484 2 10.7692C2 13.095 2.9239 15.3255 4.56845 16.97C6.213 18.6146 8.44348 19.5385 10.7692 19.5385Z"></path><path d="M18.9411 8.63005C17.24 8.29169 15.4768 8.46535 13.8744 9.12907C12.2721 9.79279 10.9025 10.9168 9.93894 12.3589C8.97537 13.8009 8.46106 15.4964 8.46106 17.2308C8.46106 17.8296 8.52231 18.4222 8.64135 19"></path><path d="M11.6923 11.2307L16.7692 16.3076"></path><path d="M14.7827 9.24402L18.6992 13.1606"></path><path d="M9.52991 14.1307L14.2306 18.3481"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Treasury.svg b/assets/icons/polkadot/line/Treasury.svg
new file mode 100644
index 00000000..cfd0eef0
--- /dev/null
+++ b/assets/icons/polkadot/line/Treasury.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M8.05532 10.5251H2.00006V10.3376L14.1049 2L26.2221 10.4352V10.5251H20.1399H8.05532Z"></path><path d="M2 26L26.222 26"></path><path d="M5.61755 11V25.5"></path><path d="M22.5933 11L22.5931 25.5"></path><path d="M15.7874 15.0547H13.5358C13.0926 15.0558 12.668 15.2277 12.3548 15.5326C12.0417 15.8375 11.8655 16.2506 11.8649 16.6815V16.701C11.8655 17.1319 12.0417 17.545 12.3548 17.8499C12.668 18.1548 13.0926 18.3267 13.5358 18.3278H14.6527C14.873 18.327 15.0912 18.3684 15.295 18.4498C15.4988 18.5311 15.684 18.6508 15.8401 18.802C15.9961 18.9531 16.12 19.1328 16.2045 19.3306C16.289 19.5284 16.3325 19.7404 16.3325 19.9546C16.3331 20.169 16.2901 20.3813 16.206 20.5795C16.1219 20.7777 15.9983 20.9577 15.8424 21.1093C15.6865 21.2609 15.5014 21.381 15.2976 21.4628C15.0938 21.5445 14.8754 21.5863 14.6549 21.5858H12.2134" fill="none" data-nofill="true"></path><path d="M14.0945 15.0107V13.8521" fill="none" data-nofill="true"></path><path d="M14.0945 22.8071V21.7383" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Twitter.svg b/assets/icons/polkadot/line/Twitter.svg
new file mode 100644
index 00000000..1f9013c2
--- /dev/null
+++ b/assets/icons/polkadot/line/Twitter.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M18.6909 4C16.0399 4 13.8909 6.2207 13.8909 8.96006C13.8909 9.34783 13.934 9.7252 14.0154 10.0874C14.0154 10.0874 10.463 9.63442 8.43636 8.62188C6.40973 7.60934 3.63636 4.90183 3.63636 4.90183C3.63636 4.90183 2.76727 6.3673 3.2 8.28369C3.63273 10.2001 5.16364 11.6656 5.16364 11.6656L2.98182 10.9892C2.98182 10.9892 3.09091 12.7414 4.18182 14.1456C5.27273 15.5497 6.90909 16.062 6.90909 16.062L4.72727 16.1747C4.72727 16.1747 5.38182 17.7589 6.58182 18.6547C7.78182 19.5506 9.30909 19.6693 9.30909 19.6693C9.30909 19.6693 7.54009 20.9234 6.25455 21.3602C4.6679 21.8994 2 21.8111 2 21.8111C2 21.8111 11.9273 27.0927 18.0364 21.2475C24.1455 15.4023 23.4909 8.96006 23.4909 8.96006C23.4909 8.96006 24.4192 8.36106 24.9091 7.83278C25.399 7.3045 26 6.25458 26 6.25458C26 6.25458 25.2234 6.64213 24.6909 6.81822C24.1584 6.99431 23.2727 7.1564 23.2727 7.1564C23.2727 7.1564 24.068 6.35395 24.4727 5.80366C24.8775 5.25337 25.3455 4.33819 25.3455 4.33819C25.3455 4.33819 24.2643 4.89081 23.6 5.12729C22.9948 5.34272 22.0973 5.46547 22.0973 5.46547C21.2277 4.56042 20.0226 4 18.6909 4Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Ui.svg b/assets/icons/polkadot/line/Ui.svg
new file mode 100644
index 00000000..eb1180c0
--- /dev/null
+++ b/assets/icons/polkadot/line/Ui.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M2 25.7584L26 25.7584L26 2.00001L2 2.00002L2 25.7584Z"></path><path d="M25.993 8.51306H2.00028"></path><path d="M21.9614 21.5035H16.3515" stroke-miterlimit="10"></path><path d="M21.9614 16.7718H16.3515" stroke-miterlimit="10"></path><path d="M21.9614 12.3423H16.3515" stroke-miterlimit="10"></path><path d="M11.6991 21.5035H6.08917" stroke-miterlimit="10"></path><path d="M11.5463 12.3423H6.24258V16.7718H11.5463V12.3423Z" stroke-miterlimit="10"></path><path d="M9.25124 5.43288L9.23407 5.41571" stroke-miterlimit="10"></path><path d="M5.4659 5.43288L5.44873 5.41571" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Unbond.svg b/assets/icons/polkadot/line/Unbond.svg
new file mode 100644
index 00000000..20178848
--- /dev/null
+++ b/assets/icons/polkadot/line/Unbond.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M20.3038 6.43753C20.3038 8.88855 17.3237 10.8756 13.6467 10.8756C10.0357 10.8756 7.10374 8.95739 7 6.56673V9.92591C7 12.3769 9.98008 14.364 13.6571 14.364C17.3341 14.364 20.3142 12.3769 20.3142 9.92591C20.3142 9.62319 20.3915 6.72328 20.3047 6.43658L20.3038 6.43753Z"></path><path d="M13.673 10.8761C17.349 10.8761 20.33 8.88907 20.33 6.43805C20.33 3.98703 17.35 2 13.673 2C9.99596 2 7.01588 3.98703 7.01588 6.43805C7.01588 8.88907 9.99596 10.8761 13.673 10.8761Z"></path><path d="M13.6119 18.4733L13.6119 24.9733M17.2399 22.3721L13.612 26L9.98407 22.3721" stroke-miterlimit="10" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Unchecked.svg b/assets/icons/polkadot/line/Unchecked.svg
new file mode 100644
index 00000000..00df8c5a
--- /dev/null
+++ b/assets/icons/polkadot/line/Unchecked.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26.9766 2.08008H2.97656V26.0801H26.9766V2.08008Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Unlock.svg b/assets/icons/polkadot/line/Unlock.svg
new file mode 100644
index 00000000..d272ef5e
--- /dev/null
+++ b/assets/icons/polkadot/line/Unlock.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.6869 6.80748C17.4115 6.12236 17.0106 5.69148 16.7695 5.41665C15.7381 4.2427 14.4559 3.93051 12.9403 4.01224C11.1395 4.11153 9.60805 5.39009 9.027 7.05031C8.7804 7.75346 8.7028 8.64953 8.71804 10.5" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M23.1735 10.8618H4V24.8062H23.1735V10.8618Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Unstake.svg b/assets/icons/polkadot/line/Unstake.svg
new file mode 100644
index 00000000..b4003b94
--- /dev/null
+++ b/assets/icons/polkadot/line/Unstake.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M24.735 16.924V19.5201C24.735 23.3374 20.0933 25.9998 14.3675 25.9998C8.64169 25.9998 4 23.3374 4 19.5201V16.924"></path><path d="M14.3675 22.9761C20.0933 22.9761 24.735 19.8816 24.735 16.0644C24.735 12.2472 20.0933 9.15271 14.3675 9.15271C8.64169 9.15271 4 12.2472 4 16.0644C4 19.8816 8.64169 22.9761 14.3675 22.9761Z"></path><path d="M14.3673 15.3902L14.3673 2.99994M17.4273 5.05973L14.3675 2L11.3078 5.05973" fill="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Upgrade.svg b/assets/icons/polkadot/line/Upgrade.svg
new file mode 100644
index 00000000..c726b1dc
--- /dev/null
+++ b/assets/icons/polkadot/line/Upgrade.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26.0002C20.6274 26.0002 26 20.6277 26 14.0002C26 7.37283 20.6274 2.00024 14 2.00024C7.37258 2.00024 2 7.37283 2 14.0002C2 20.6277 7.37258 26.0002 14 26.0002Z"></path><path d="M13.9998 21.0574L13.9998 8.00024M10.7449 10.1979L13.9998 6.94298L17.2547 10.1979"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Use Cases.svg b/assets/icons/polkadot/line/Use Cases.svg
new file mode 100644
index 00000000..c2ab4bc5
--- /dev/null
+++ b/assets/icons/polkadot/line/Use Cases.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 4H6.87515V23.1248H26V4Z"></path><path d="M16.4376 9.04315L20.953 13.5586L16.4376 18.0816"></path><path d="M20.0024 13.5624L1.99994 13.5624"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Users.svg b/assets/icons/polkadot/line/Users.svg
new file mode 100644
index 00000000..7f21daa9
--- /dev/null
+++ b/assets/icons/polkadot/line/Users.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M10.9523 11.4719L9.92866 10.2412C8.18155 8.14076 8.32148 5.05539 10.2515 3.12174C12.318 1.05141 15.6726 1.05141 17.7391 3.12174C19.6691 5.05539 19.8091 8.14076 18.062 10.2412L17.0385 11.4716C16.3847 12.2576 16.7593 13.4563 17.7443 13.7303L19.1309 14.1159C22.9276 15.1717 25.5547 18.6291 25.5547 22.5698V26.371H2.44531V22.5633C2.44531 18.6259 5.06981 15.1713 8.86305 14.1156L10.2468 13.7306C11.2316 13.4565 11.6061 12.2578 10.9523 11.4719Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Utility.svg b/assets/icons/polkadot/line/Utility.svg
new file mode 100644
index 00000000..4a399fc2
--- /dev/null
+++ b/assets/icons/polkadot/line/Utility.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M20.9399 24.3129L17.2934 26.4121L14.7854 23.6251H13.1634L10.6254 26.3721L4.90338 23.0681L6.07737 19.4751L5.28137 18.1021L1.60938 17.2661V10.6581L5.31138 9.88206L6.09737 8.50906L4.99237 4.90606L10.7144 1.61206L13.2124 4.39906H14.8344L17.3824 1.66206L23.0944 4.95606L21.9504 8.49906L22.7764 9.93206L26.3894 10.7581V18.2621L22.7564 19.0281L22.3441 19.2979"></path><path d="M16.3475 19.3776C15.5643 19.7935 14.6777 20.0435 13.736 20.0666C10.4945 20.1462 7.80311 17.5839 7.72349 14.3424C7.69987 13.3808 7.91538 12.463 8.30208 11.6501L12.212 15.3629L14.9484 12.4886L11.1299 8.86291C11.8361 8.53808 12.6148 8.34042 13.4475 8.31997C16.6889 8.24034 19.3803 10.8027 19.46 14.0442C19.4807 14.8868 19.3219 15.6941 19.0126 16.4257L26.1316 23.3577L23.3952 26.2319L16.3475 19.3776Z" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Ux.svg b/assets/icons/polkadot/line/Ux.svg
new file mode 100644
index 00000000..7d8e5045
--- /dev/null
+++ b/assets/icons/polkadot/line/Ux.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M21.5025 2L6.91705 2L6.91705 6.9637L21.5025 6.9637L21.5025 2Z"></path><path d="M13.9297 7.00257L13.9297 20.3938" fill="none" data-nofill="true"></path><path d="M13.9684 12.1343L23.396 12.1343L23.396 16.2048" fill="none" data-nofill="true"></path><path d="M13.7919 12.1343L4.46362 12.1343L4.46362 16.2048" fill="none" data-nofill="true"></path><path d="M6.91706 16.2047L2 16.2047L2 21.1024L6.91706 21.1024L6.91706 16.2047Z"></path><path d="M25.9127 16.2047L20.9956 16.2047L20.9956 21.1024L25.9127 21.1024L25.9127 16.2047Z"></path><path d="M16.3883 21.1024L11.4712 21.1024L11.4712 26L16.3883 26L16.3883 21.1024Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Validators.svg b/assets/icons/polkadot/line/Validators.svg
new file mode 100644
index 00000000..dd035752
--- /dev/null
+++ b/assets/icons/polkadot/line/Validators.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14 26C20.6274 26 26 20.6274 26 14C26 7.37258 20.6274 2 14 2C7.37258 2 2 7.37258 2 14C2 20.6274 7.37258 26 14 26Z"></path><path d="M8.03863 14.0733L13.0614 18.697L25.3774 2.42365" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Value Bearing Token.svg b/assets/icons/polkadot/line/Value Bearing Token.svg
new file mode 100644
index 00000000..6b2f8939
--- /dev/null
+++ b/assets/icons/polkadot/line/Value Bearing Token.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 13.4443V16.7493C26 21.1676 20.6274 24.2493 14 24.2493C7.37258 24.2493 2 21.1676 2 16.7493V13.4443"></path><path d="M14 20.7634C20.627 20.7634 26 17.1814 26 12.7634C26 8.34543 20.627 4.76343 14 4.76343C7.373 4.76343 2 8.34543 2 12.7634C2 17.1814 7.373 20.7634 14 20.7634Z"></path><path d="M14 4.76343C12.935 4.76343 11.908 4.86543 10.924 5.03843V15.0144L13.998 13.6994L17.075 15.0074V5.03843C16.092 4.86443 15.065 4.76343 13.999 4.76343H14Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Verified Account.svg b/assets/icons/polkadot/line/Verified Account.svg
new file mode 100644
index 00000000..6f7b1634
--- /dev/null
+++ b/assets/icons/polkadot/line/Verified Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.665 24.771H2V21.588C2 18.288 4.20059 15.3916 7.37984 14.5072L8.54142 14.1848C9.3664 13.9557 9.68037 12.9516 9.13258 12.2934L8.27554 11.2629C6.81225 9.50359 6.92916 6.92021 8.54613 5.30041C10.2772 3.56653 13.0859 3.56653 14.817 5.30041C16.433 6.92021 16.5508 9.50359 15.0876 11.2629L14.173 12.3623C13.6365 13.0072 13.9109 13.9896 14.7038 14.263L16.4703 14.7928"></path><path d="M26 19.2449C26 20.711 25.4173 22.1177 24.3811 23.1539C23.344 24.191 21.9382 24.7728 20.4721 24.7728C19.006 24.7728 17.5993 24.1901 16.5631 23.1539C15.526 22.1168 14.9433 20.711 14.9433 19.2449C14.9433 17.7788 15.526 16.3721 16.5631 15.3359C17.6002 14.2988 19.006 13.717 20.4721 13.717C21.9382 13.717 23.3449 14.2997 24.3811 15.3359C25.4182 16.373 26 17.7788 26 19.2449Z" stroke-miterlimit="10"></path><path d="M22.259 17.9769L19.7834 20.6706L18.4628 19.3491"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Verified Signed.svg b/assets/icons/polkadot/line/Verified Signed.svg
new file mode 100644
index 00000000..bf91f036
--- /dev/null
+++ b/assets/icons/polkadot/line/Verified Signed.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M22.8036 18.8845L26.5599 16.0759L23.6835 12.4389L24.674 7.90114L20.1062 6.88196L17.8667 2.73581L13.745 4.80927L9.32082 2.99604L7.57176 7.19308L3.03621 8.56006L4.48019 12.9155L1.95365 16.8249L5.91469 19.3033L6.58009 23.9244L11.2032 23.3636L14.7506 26.5351L17.8744 23.1989L22.6429 23.4364L22.8036 18.8845Z" stroke-miterlimit="10"></path><path d="M9.58301 14.3475L12.7651 17.3196L18.5969 11.421" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Verify.svg b/assets/icons/polkadot/line/Verify.svg
new file mode 100644
index 00000000..4abb7b8a
--- /dev/null
+++ b/assets/icons/polkadot/line/Verify.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M19.7397 4.99994L21.2397 6.99994L26.2397 2.99994" fill="none" data-nofill="true"></path><path d="M9.55662 12.7572L8.64731 11.664C7.09538 9.79821 7.21968 7.05754 8.93412 5.33992C10.7698 3.50088 13.7495 3.50088 15.5851 5.33992C17.2996 7.05754 17.4239 9.79821 15.872 11.664L14.9628 12.7569C14.3821 13.4551 14.7148 14.5199 15.5898 14.7632L16.8215 15.1058C20.194 16.0437 22.5276 19.1148 22.5276 22.6153V25.9918H2V22.6094C2 19.1119 4.33128 16.0433 7.70074 15.1056L8.92988 14.7635C9.80471 14.5201 10.1373 13.4553 9.55662 12.7572Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Version.svg b/assets/icons/polkadot/line/Version.svg
new file mode 100644
index 00000000..b415ffe1
--- /dev/null
+++ b/assets/icons/polkadot/line/Version.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M16.4735 3.99275C13.4795 0.873905 5.99424 2.49575 5.99424 2.49575L5.99424 14.5969C5.99424 14.5969 13.4795 12.975 16.4735 16.0939C19.4676 19.2127 25.4558 18.3394 25.4558 18.3394L25.4558 6.23832C25.4558 6.23832 19.4676 7.1116 16.4735 3.99275Z"></path><path d="M5.99414 3.61853L5.99414 26.0742"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Vesting Period.svg b/assets/icons/polkadot/line/Vesting Period.svg
new file mode 100644
index 00000000..7a99c45e
--- /dev/null
+++ b/assets/icons/polkadot/line/Vesting Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 26H2V3.88452H26V26Z" stroke-miterlimit="10"></path><path d="M9.42337 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34177V2.00006" stroke-miterlimit="10"></path><path d="M10.9154 13.364L10.9154 12.0846V12C10.9154 10.3431 12.2586 9 13.9154 9H14.0846C15.7415 9 17.0846 10.3431 17.0846 12V12.0846L17.0846 13.364"></path><path d="M20 13.3658H8V22.0931H20V13.3658Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Vesting.svg b/assets/icons/polkadot/line/Vesting.svg
new file mode 100644
index 00000000..f60491cf
--- /dev/null
+++ b/assets/icons/polkadot/line/Vesting.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11.1211 5.47856L11.1211 4.45884V4.45884C11.1211 3.10099 12.2218 2.00024 13.5797 2.00024V2.00024C14.9375 2.00024 16.0383 3.10099 16.0383 4.45884V4.45884L16.0383 5.47856" fill="none"></path><path d="M18.3618 5.48004H8.79722V12.4361H18.3618V5.48004Z"></path><path d="M8.01595 19.1049L8.00957 19.1065V19.1918C8.01117 19.1631 8.01356 19.1336 8.01595 19.1049Z"></path><path d="M19.2526 19.301C19.2526 21.3726 16.7339 23.052 13.6262 23.052C10.5743 23.052 8.09627 21.4308 8.00859 19.4102V22.2493C8.00859 24.3209 10.5273 26.0003 13.635 26.0003C16.7427 26.0003 19.2614 24.3209 19.2614 22.2493C19.2614 21.9935 19.3267 19.5425 19.2534 19.3002L19.2526 19.301Z"></path><path d="M13.6264 23.052C16.7333 23.052 19.2528 21.3726 19.2528 19.301C19.2528 17.2295 16.7341 15.5501 13.6264 15.5501C10.5187 15.5501 8 17.2295 8 19.301C8 21.3726 10.5187 23.052 13.6264 23.052Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Video Pause.svg b/assets/icons/polkadot/line/Video Pause.svg
new file mode 100644
index 00000000..f640f571
--- /dev/null
+++ b/assets/icons/polkadot/line/Video Pause.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9883 26.0742C21.6157 26.0742 26.9883 20.7016 26.9883 14.0742C26.9883 7.4468 21.6157 2.07422 14.9883 2.07422C8.36086 2.07422 2.98828 7.4468 2.98828 14.0742C2.98828 20.7016 8.36086 26.0742 14.9883 26.0742Z"></path><path d="M17.9443 18.3023L17.9443 10.1176"></path><path d="M11.9883 10.0742V18.3023"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Video Play.svg b/assets/icons/polkadot/line/Video Play.svg
new file mode 100644
index 00000000..9c3e0fca
--- /dev/null
+++ b/assets/icons/polkadot/line/Video Play.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M14.9824 26.0742C21.6098 26.0742 26.9824 20.7016 26.9824 14.0742C26.9824 7.4468 21.6098 2.07422 14.9824 2.07422C8.355 2.07422 2.98242 7.4468 2.98242 14.0742C2.98242 20.7016 8.355 26.0742 14.9824 26.0742Z"></path><path d="M19.8242 14.1882L12.9825 10.0742V18.3003L19.8242 14.1882Z"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Video.svg b/assets/icons/polkadot/line/Video.svg
new file mode 100644
index 00000000..c106a141
--- /dev/null
+++ b/assets/icons/polkadot/line/Video.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M26 2.99976H2V24.1198H26V2.99976Z" stroke-miterlimit="40"></path><path d="M18.32 15.4807L12.56 11.6398V19.3198L18.32 15.4807Z"></path><path d="M2 7.79974H26"></path><path d="M19.4972 3.55933L22.783 7.25587"></path><path d="M12 3.55933L15.2858 7.25587"></path><path d="M5 3.55933L8.28581 7.25587"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Videos.svg b/assets/icons/polkadot/line/Videos.svg
new file mode 100644
index 00000000..91cf84d1
--- /dev/null
+++ b/assets/icons/polkadot/line/Videos.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M21.8623 20.4786H26.0002V3H6.13812V6.72414" stroke-miterlimit="40"></path><path d="M21.8621 7.13794H2V24.6166H21.8621V7.13794Z" stroke-miterlimit="40"></path><path d="M15.5063 17.467L10.7394 14.2883V20.6442L15.5063 17.467Z"></path><path d="M2 11.1104H21.8621"></path><path d="M4.6192 7.77124L7.5 10.9999"></path><path d="M16.1174 7.74927L19 10.6318"></path><path d="M10.5771 7.77014L13.3915 10.5846"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Vote.svg b/assets/icons/polkadot/line/Vote.svg
new file mode 100644
index 00000000..9fd80096
--- /dev/null
+++ b/assets/icons/polkadot/line/Vote.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M16.0555 1.99997L4.49426 13.5612L10.68 19.747L15.0524 19.747L24.4274 10.3719L16.0555 1.99997Z"></path><path d="M12.6364 14.214L15.0919 14.3288L15.5422 8.03956"></path><path d="M2 26V19.7446H26.4885V26" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Voting Period.svg b/assets/icons/polkadot/line/Voting Period.svg
new file mode 100644
index 00000000..024503e8
--- /dev/null
+++ b/assets/icons/polkadot/line/Voting Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26 26H2V3.88452H26V26Z" stroke-miterlimit="10"></path><path d="M9.42337 6.34171V2" stroke-miterlimit="10"></path><path d="M18.5764 6.34177V2.00006" stroke-miterlimit="10"></path><path d="M15.2908 8.99999L6.64577 17.645L11.175 22.1742L14.6369 22.1742L21.551 15.2602L15.2908 8.99999Z"></path><path d="M21.5273 22.1729L6 22.1729" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Wallet Deposit.svg b/assets/icons/polkadot/line/Wallet Deposit.svg
new file mode 100644
index 00000000..3b58c8dd
--- /dev/null
+++ b/assets/icons/polkadot/line/Wallet Deposit.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.9449 2H5V17.9603H23.9449V2Z"></path><path d="M23.009 6.25403H17.2704C15.2125 6.25403 13.5443 7.92228 13.5443 9.98016C13.5443 12.0381 15.2125 13.7063 17.2704 13.7063H23.009C23.5317 13.7063 23.9555 13.2826 23.9555 12.7598V7.2005C23.9555 6.67778 23.5317 6.25403 23.009 6.25403Z"></path><path d="M17.213 22.741L14.0732 26L10.9388 22.741" fill="none" data-nofill="true"></path><path d="M14.0732 25L14.0732 18.3316"></path><path d="M17.0181 10.0181L17 10" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Wallet Withdraw.svg b/assets/icons/polkadot/line/Wallet Withdraw.svg
new file mode 100644
index 00000000..18dc2bbe
--- /dev/null
+++ b/assets/icons/polkadot/line/Wallet Withdraw.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M23.8458 10.1229H4.99995V25.9998H23.8458V10.1229Z"></path><path d="M22.9147 14.3546H17.2061C15.159 14.3546 13.4995 16.0141 13.4995 18.0613C13.4995 20.1084 15.159 21.7679 17.2061 21.7679H22.9147C23.4347 21.7679 23.8562 21.3464 23.8562 20.8264V15.2961C23.8562 14.7761 23.4347 14.3546 22.9147 14.3546Z"></path><path d="M14.7695 9.62805L14.7695 3M11.6461 5.24169L14.7695 1.99976L17.8874 5.24169" fill="none" data-nofill="true"></path><path d="M17.0181 18.0181L17 18" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Wallet.svg b/assets/icons/polkadot/line/Wallet.svg
new file mode 100644
index 00000000..e68fc2a8
--- /dev/null
+++ b/assets/icons/polkadot/line/Wallet.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M26.7599 3.24988H1.23975V24.7496H26.7599V3.24988Z"></path><path d="M26.7742 8.98047H17.7689C14.9968 8.98047 12.7495 11.2277 12.7495 13.9999C12.7495 16.772 14.9968 19.0192 17.7689 19.0192H26.7742V8.98047Z"></path><circle cx="18" cy="14" r="1"></circle></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Wallets.svg b/assets/icons/polkadot/line/Wallets.svg
new file mode 100644
index 00000000..40ffa30c
--- /dev/null
+++ b/assets/icons/polkadot/line/Wallets.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M6.11719 7V2.86328H26.4695V20.0093H22.8445"></path><path d="M22.4695 7.49976H2.11719V24.6457H22.4695V7.49976Z"></path><path d="M21.4808 12.0699H15.2991C13.0883 12.0699 11.2961 13.8621 11.2961 16.0729C11.2961 18.2837 13.0883 20.0758 15.2991 20.0758H21.4808C22.0331 20.0758 22.4808 19.6281 22.4808 19.0758V13.0699C22.4808 12.5177 22.0331 12.0699 21.4808 12.0699Z"></path><path d="M15.0181 16.0181L15 16" stroke-miterlimit="10"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Wasm.svg b/assets/icons/polkadot/line/Wasm.svg
new file mode 100644
index 00000000..9c1a08b8
--- /dev/null
+++ b/assets/icons/polkadot/line/Wasm.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M17.763 3.99976C17.763 6.08502 16.1319 7.85576 14 7.85576C11.9242 7.85576 10.1625 6.0858 10.237 3.99976H4V23.9998H24V3.99976H17.763Z"></path><path d="M10 12.9998L11.3333 19.3603H11.4172L14 12.9998H14.0651L16.6667 19.3603H16.7194L18 12.9998"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Web3.svg b/assets/icons/polkadot/line/Web3.svg
new file mode 100644
index 00000000..bc47f792
--- /dev/null
+++ b/assets/icons/polkadot/line/Web3.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><path d="M13.9999 1.27868C21.0256 1.27868 26.7211 6.97413 26.7211 13.9998C26.7211 21.0255 21.0256 26.7209 13.9999 26.7209C6.97425 26.7209 1.27881 21.0255 1.27881 13.9998C1.27881 6.97413 6.97425 1.27868 13.9999 1.27868Z"></path><path d="M6 11.1799L7.39339 17.5405H7.48107L10.1802 11.1799H10.2482L12.967 17.5405H13.022L14.3604 11.1799"></path><path d="M19.3003 14.18C20.1785 14.18 20.8905 14.8919 20.8905 15.7701C20.8905 16.6483 20.1785 17.3602 19.3003 17.3602H18.2402M19.3003 14.18C20.1785 14.18 20.8905 13.468 20.8905 12.5898C20.8905 11.7116 20.1785 10.9996 19.3003 10.9996H18.2402M19.3003 14.18H19.0984"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Whitepaper Download.svg b/assets/icons/polkadot/line/Whitepaper Download.svg
new file mode 100644
index 00000000..bfa896b3
--- /dev/null
+++ b/assets/icons/polkadot/line/Whitepaper Download.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.00001 26.0005V2.00049H17L23.4615 8.46203V26.0005H5.00001Z"></path><path d="M23 8.46201H17V2.50024"></path><path d="M14.462 12.0002L14.462 18.3181M17.424 16.3182L14.462 19.2802L11.5 16.3182"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Whitepaper Upload.svg b/assets/icons/polkadot/line/Whitepaper Upload.svg
new file mode 100644
index 00000000..c82da475
--- /dev/null
+++ b/assets/icons/polkadot/line/Whitepaper Upload.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/line/Whitepaper.svg b/assets/icons/polkadot/line/Whitepaper.svg
new file mode 100644
index 00000000..8c16979c
--- /dev/null
+++ b/assets/icons/polkadot/line/Whitepaper.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M5.00001 26.0005V2.00049H17L23.4615 8.46203V26.0005H5.00001Z"></path><path d="M23 8.46201H17V2.50024"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/WiFi Off.svg b/assets/icons/polkadot/line/WiFi Off.svg
new file mode 100644
index 00000000..7e9beeda
--- /dev/null
+++ b/assets/icons/polkadot/line/WiFi Off.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><circle cx="14.0003" cy="23.6787" r="1.83075"></circle><path d="M8.40405 18.0865C9.08223 17.2586 9.93545 16.5912 10.9024 16.1325C11.8693 15.6737 12.9258 15.4348 13.996 15.4332C15.0663 15.4315 16.1236 15.667 17.0919 16.1228C18.0602 16.5786 18.9155 17.2432 19.5963 18.069" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M5.18091 13.7426C6.98148 11.3968 10.2637 9.82629 14.0138 9.82629C17.7453 9.82629 21.0134 11.3814 22.8198 13.7087" fill="none" data-nofill="true"></path><path d="M2 9.56293C3.47594 7.81883 5.31446 6.41758 7.38743 5.45683C9.4604 4.49607 11.718 3.99894 14.0027 4.00006C16.2875 4.00119 18.5446 4.50055 20.6166 5.46335C22.6886 6.42614 24.5258 7.82921 26 9.57476" fill="none" data-nofill="true"></path><path d="M2.99982 2L24.9998 26" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/WiFi.svg b/assets/icons/polkadot/line/WiFi.svg
new file mode 100644
index 00000000..debd659a
--- /dev/null
+++ b/assets/icons/polkadot/line/WiFi.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><g><circle cx="14.9943" cy="23.747" r="1.83075"></circle><path d="M9.39825 18.1548C10.0764 17.3268 10.9297 16.6595 11.8966 16.2007C12.8635 15.7419 13.92 15.5031 14.9902 15.5014C16.0605 15.4997 17.1178 15.7353 18.0861 16.191C19.0544 16.6468 19.9097 17.3115 20.5905 18.1373" stroke-miterlimit="10" fill="none" data-nofill="true"></path><path d="M6.17468 13.8108C7.97526 11.465 11.2575 9.89453 15.0075 9.89453C18.7391 9.89453 22.0072 11.4497 23.8135 13.7769" fill="none" data-nofill="true"></path><path d="M2.99414 9.63123C4.47008 7.88713 6.3086 6.48588 8.38157 5.52513C10.4545 4.56437 12.7121 4.06724 14.9969 4.06836C17.2817 4.06949 19.5387 4.56885 21.6108 5.53164C23.6828 6.49444 25.5199 7.8975 26.9941 9.64305" fill="none" data-nofill="true"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Wiki.svg b/assets/icons/polkadot/line/Wiki.svg
new file mode 100644
index 00000000..5bdfba6c
--- /dev/null
+++ b/assets/icons/polkadot/line/Wiki.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M14 1.49976C20.6274 1.49976 26 6.87234 26 13.4998C26 20.1272 20.6274 25.4998 14 25.4998C7.37258 25.4998 2 20.1272 2 13.4998C2 6.87234 7.37258 1.49976 14 1.49976Z"></path><path d="M12.2975 10.4158L16.3586 17.9578L20.4196 10.4158" fill="none" data-nofill="true"></path><path d="M7.65649 10.4158L11.7176 17.9578L15.7787 10.4158" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Withdraw.svg b/assets/icons/polkadot/line/Withdraw.svg
new file mode 100644
index 00000000..c704e7fb
--- /dev/null
+++ b/assets/icons/polkadot/line/Withdraw.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M22.706 26L6 26" fill="none" data-nofill="true"></path><path d="M14.4817 21.4482L14.4817 2.94818M8.95172 7.52722L14.4817 1.99997L20.0165 7.52548" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Workshop.svg b/assets/icons/polkadot/line/Workshop.svg
new file mode 100644
index 00000000..39610ada
--- /dev/null
+++ b/assets/icons/polkadot/line/Workshop.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M9.29544 10.0459L9.80687 9.43105C10.6797 8.38166 10.6098 6.84019 9.64556 5.87413C8.61312 4.83977 6.93717 4.83977 5.90473 5.87412C4.94046 6.84019 4.87055 8.38166 5.74341 9.43105L6.25475 10.0458C6.58137 10.4385 6.39423 11.0374 5.90214 11.1742L5.20937 11.3669C3.31252 11.8944 2 13.6217 2 15.5905V17.4896H13.5456V15.5872C13.5456 13.6201 12.2344 11.8942 10.3393 11.3668L9.64794 11.1744C9.1559 11.0374 8.96883 10.4386 9.29544 10.0459Z"></path><path d="M18.7046 10.0459L18.1932 9.43105C17.3203 8.38166 17.3902 6.84019 18.3545 5.87413C19.387 4.83977 21.0629 4.83977 22.0953 5.87412C23.0596 6.84019 23.1295 8.38166 22.2567 9.43105L21.7453 10.0458C21.4187 10.4385 21.6058 11.0374 22.0979 11.1742L22.7907 11.3669C24.6876 11.8944 26.0001 13.6217 26.0001 15.5905V17.4896H14.4545V15.5872C14.4545 13.6201 15.7657 11.8942 17.6608 11.3668L18.3521 11.1744C18.8442 11.0374 19.0312 10.4386 18.7046 10.0459Z"></path><path d="M2.00025 25.1183V17.4898H25.9788V25.1183" fill="none" data-nofill="true"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/XCM (Message).svg b/assets/icons/polkadot/line/XCM (Message).svg
new file mode 100644
index 00000000..31e1c373
--- /dev/null
+++ b/assets/icons/polkadot/line/XCM (Message).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M11.2307 14.6156C11.2307 12.0666 9.16434 10.0002 6.61535 10.0002C4.06636 10.0002 2 12.0666 2 14.6156C2 17.1646 4.06636 19.2309 6.61535 19.2309C9.16434 19.2309 11.2307 17.1646 11.2307 14.6156Z"></path><path d="M26 10.0002H16.7693V19.231H26V10.0002Z"></path><path d="M11.4384 14.6184L21.3847 14.6184"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/line/Youtube.svg b/assets/icons/polkadot/line/Youtube.svg
new file mode 100644
index 00000000..9b5db360
--- /dev/null
+++ b/assets/icons/polkadot/line/Youtube.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#ffffff"><path d="M25 5.39978H3V22.9998H25V5.39978Z" stroke-miterlimit="40"></path><path d="M18.5631 14.1395L11.9631 10.2886V17.9886L18.5631 14.1395Z"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/AI & Computing.svg b/assets/icons/polkadot/solid/AI & Computing.svg
new file mode 100644
index 00000000..8929dd02
--- /dev/null
+++ b/assets/icons/polkadot/solid/AI & Computing.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M6 6C6 4.34315 7.34315 3 9 3C10.3062 3 11.4175 3.83481 11.8293 5H14C14.5523 5 15 5.44772 15 6V10H17C17.5523 10 18 10.4477 18 11V13H20.5707C20.9826 11.8348 22.0938 11 23.4 11C25.0569 11 26.4 12.3431 26.4 14C26.4 15.6569 25.0569 17 23.4 17C22.0938 17 20.9826 16.1652 20.5707 15H18V17C18 17.5523 17.5523 18 17 18H15L15 21H16.1707C16.5825 19.8348 17.6938 19 19 19C20.6569 19 22 20.3431 22 22C22 23.6569 20.6569 25 19 25C17.6938 25 16.5825 24.1652 16.1707 23H14C13.4477 23 13 22.5523 13 22L13 18H11C10.4477 18 10 17.5523 10 17V15H7.82929C7.41746 16.1652 6.30622 17 5 17C3.34315 17 2 15.6569 2 14C2 12.3431 3.34315 11 5 11C6.30622 11 7.41746 11.8348 7.82929 13H10V11C10 10.4477 10.4477 10 11 10H13V7H11.8293C11.4175 8.16519 10.3062 9 9 9C7.34315 9 6 7.65685 6 6Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Account Portability.svg b/assets/icons/polkadot/solid/Account Portability.svg
new file mode 100644
index 00000000..34f10cf8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Account Portability.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M13.8075 7.66319C15.75 5.71709 18.9032 5.71709 20.8457 7.66319C22.66 9.48082 22.7915 12.381 21.1492 14.3554L20.3805 15.2796C20.3699 15.2924 20.368 15.3001 20.3671 15.3047C20.3659 15.3115 20.3659 15.322 20.3697 15.3342C20.3735 15.3464 20.3795 15.355 20.3844 15.3599C20.3876 15.3632 20.3936 15.3684 20.4096 15.3729L21.4487 15.6621C24.7298 16.5752 27 19.5634 27 22.9692V25.8286C27 26.3809 26.5523 26.8286 26 26.8286H8.64612C8.09383 26.8286 7.64612 26.3809 7.64612 25.8286V22.9741C7.64612 19.5657 9.91833 16.5754 13.2021 15.6622L14.2434 15.3726C14.2594 15.3682 14.2654 15.3629 14.2686 15.3597C14.2735 15.3547 14.2795 15.3462 14.2833 15.3339C14.2871 15.3217 14.2871 15.3113 14.2859 15.3044C14.285 15.2999 14.2831 15.2922 14.2725 15.2794L13.5039 14.3554C11.8617 12.381 11.9932 9.48082 13.8075 7.66319ZM5.46275 15.9737C5.07223 16.3642 5.07224 16.9974 5.46277 17.3879C5.8533 17.7784 6.48647 17.7784 6.87699 17.3879L9.79324 14.4715C10.1837 14.081 10.1837 13.4478 9.79323 13.0573L6.87697 10.141C6.48645 9.75051 5.85329 9.75051 5.46276 10.141C5.07224 10.5316 5.07223 11.1647 5.46276 11.5553L6.67202 12.7645H2C1.44772 12.7645 1 13.2122 1 13.7645C1 14.3168 1.44772 14.7645 2 14.7645H6.67186L5.46275 15.9737Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Action Left.svg b/assets/icons/polkadot/solid/Action Left.svg
new file mode 100644
index 00000000..0f07205e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Action Left.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M19.7679 22.6405C19.4141 23.0646 18.7835 23.1217 18.3594 22.7679L9.35941 15.2604C9.13151 15.0703 8.99983 14.7887 8.99997 14.492C9.00012 14.1952 9.13208 13.9138 9.36017 13.7239L18.3602 6.23144C18.7846 5.87808 19.4152 5.93572 19.7685 6.36017C20.1219 6.78462 20.0642 7.41516 19.6398 7.76851L11.562 14.4932L19.6405 21.2321C20.0646 21.5858 20.1217 22.2164 19.7679 22.6405Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Action Right.svg b/assets/icons/polkadot/solid/Action Right.svg
new file mode 100644
index 00000000..3a2d7bbe
--- /dev/null
+++ b/assets/icons/polkadot/solid/Action Right.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M8.23212 5.35946C8.58589 4.93536 9.21649 4.87835 9.64059 5.23212L18.6406 12.7396C18.8685 12.9298 19.0002 13.2113 19 13.508C18.9999 13.8048 18.8679 14.0862 18.6398 14.2761L9.63983 21.7686C9.21538 22.1219 8.58484 22.0643 8.23149 21.6398C7.87813 21.2154 7.93577 20.5848 8.36022 20.2315L16.438 13.5068L8.35946 6.76793C7.93536 6.41416 7.87835 5.78356 8.23212 5.35946Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Add key pair.svg b/assets/icons/polkadot/solid/Add key pair.svg
new file mode 100644
index 00000000..011cac4c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Add key pair.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M6.13804 4.41342C5.82545 4.52717 5.53839 4.70139 5.29323 4.92613L5.28542 4.93329L5.28538 4.93325C4.78618 5.38122 4.4852 6.00924 4.44873 6.6795C4.41236 7.34783 4.64196 8.00365 5.08739 8.50363C5.31163 8.74716 5.58136 8.94446 5.88135 9.08438C6.18311 9.22514 6.50955 9.30506 6.84203 9.31964C7.17451 9.33421 7.50652 9.28314 7.8191 9.16939C8.13168 9.05564 8.41874 8.88142 8.6639 8.65668L8.67143 8.64978L8.67146 8.64982C9.1705 8.20164 9.47136 7.57356 9.50783 6.90328C9.5442 6.23499 9.31478 5.57921 8.86964 5.07906C8.64541 4.83558 8.37572 4.63832 8.07579 4.49843C7.77403 4.35767 7.44758 4.27775 7.1151 4.26317C6.78263 4.2486 6.45062 4.29966 6.13804 4.41342ZM3.94568 3.44826C4.38372 3.04765 4.89622 2.73702 5.45409 2.534C6.01361 2.33038 6.60779 2.23902 7.20268 2.26509C7.79758 2.29117 8.38153 2.43417 8.92122 2.6859C9.4609 2.93763 9.94577 3.29316 10.3482 3.73219L10.3564 3.74117L10.3563 3.74122C10.8319 4.27301 11.1708 4.90393 11.3539 5.57991L25.9989 5.58222C26.5511 5.58231 26.9988 6.03009 26.9987 6.58238C26.9986 7.13466 26.5508 7.58231 25.9985 7.58222L24.3242 7.58196L24.3229 10.5371C24.3228 10.8024 24.2172 11.0568 24.0294 11.2443C23.8416 11.4318 23.587 11.5369 23.3217 11.5366L18.4214 11.5307C17.8693 11.5301 17.4222 11.0821 17.4226 10.5299L17.4249 7.58087L11.4379 7.57992C11.2589 8.56052 10.7602 9.46061 10.0116 10.1345C9.57349 10.5351 9.06095 10.8458 8.50305 11.0488C7.94353 11.2524 7.34935 11.3438 6.75445 11.3177C6.15956 11.2916 5.57561 11.1486 5.03592 10.8969C4.49624 10.6452 4.01137 10.2897 3.60899 9.85062L3.60101 9.84193L3.60107 9.84188C2.79987 8.94674 2.38641 7.77029 2.45168 6.57084C2.51685 5.37312 3.05406 4.25024 3.94568 3.44826ZM15.7641 11.7783C15.7641 11.2261 15.3164 10.7783 14.7641 10.7783C14.2118 10.7783 13.7641 11.2261 13.7641 11.7783V13.4471H12.0954C11.5431 13.4471 11.0954 13.8948 11.0954 14.4471C11.0954 14.9993 11.5431 15.4471 12.0954 15.4471H13.7641V17.1158C13.7641 17.668 14.2118 18.1158 14.7641 18.1158C15.3164 18.1158 15.7641 17.668 15.7641 17.1158V15.4471H17.4328C17.9851 15.4471 18.4328 14.9993 18.4328 14.4471C18.4328 13.8948 17.9851 13.4471 17.4328 13.4471H15.7641V11.7783ZM6.13933 19.5418C5.82675 19.6556 5.53969 19.8298 5.29453 20.0545L5.28672 20.0617L5.28668 20.0617C4.78748 20.5096 4.48649 21.1377 4.45002 21.8079C4.41366 22.4763 4.64326 23.1321 5.08868 23.632C5.31293 23.8756 5.58266 24.0729 5.88264 24.2128C6.18441 24.3536 6.51085 24.4335 6.84333 24.4481C7.17581 24.4626 7.50781 24.4116 7.8204 24.2978C8.13298 24.1841 8.42004 24.0098 8.6652 23.7851L8.67272 23.7782L8.67276 23.7782C9.1718 23.3301 9.47266 22.702 9.50913 22.0317C9.54549 21.3634 9.31608 20.7076 8.87093 20.2075C8.64671 19.964 8.37702 19.7667 8.07709 19.6268C7.77533 19.4861 7.44888 19.4062 7.1164 19.3916C6.78392 19.377 6.45192 19.4281 6.13933 19.5418ZM3.94697 18.5767C4.38502 18.1761 4.89752 17.8654 5.45538 17.6624C6.01491 17.4588 6.60909 17.3674 7.20398 17.3935C7.79887 17.4196 8.38283 17.5626 8.92251 17.8143C9.4622 18.066 9.94707 18.4216 10.3494 18.8606L10.3577 18.8696L10.3576 18.8696C10.8332 19.4014 11.1721 20.0323 11.3552 20.7083L26.0002 20.7106C26.5524 20.7107 27.0001 21.1585 27 21.7108C26.9999 22.2631 26.5521 22.7107 25.9998 22.7106L24.3255 22.7104L24.3242 25.666C24.3241 25.9313 24.2185 26.1857 24.0307 26.3732C23.8429 26.5607 23.5883 26.6659 23.323 26.6655L18.4227 26.6596C17.8706 26.659 17.4235 26.211 17.4239 25.6588L17.4263 22.7093L11.4392 22.7083C11.2602 23.6889 10.7615 24.589 10.0128 25.2629C9.57478 25.6635 9.06225 25.9742 8.50435 26.1772C7.94482 26.3808 7.35065 26.4722 6.75575 26.4461C6.16086 26.4201 5.5769 26.2771 5.03722 26.0253C4.49753 25.7736 4.01266 25.4181 3.61028 24.979L3.60231 24.9703L3.60236 24.9703C2.80117 24.0752 2.38771 22.8987 2.45298 21.6993C2.51815 20.5015 3.05536 19.3787 3.94697 18.5767Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Add user.svg b/assets/icons/polkadot/solid/Add user.svg
new file mode 100644
index 00000000..e25f2b84
--- /dev/null
+++ b/assets/icons/polkadot/solid/Add user.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Add.svg b/assets/icons/polkadot/solid/Add.svg
new file mode 100644
index 00000000..b805ec68
--- /dev/null
+++ b/assets/icons/polkadot/solid/Add.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Address book.svg b/assets/icons/polkadot/solid/Address book.svg
new file mode 100644
index 00000000..ea216c0b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Address book.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Airplane Mode.svg b/assets/icons/polkadot/solid/Airplane Mode.svg
new file mode 100644
index 00000000..1e8b0f37
--- /dev/null
+++ b/assets/icons/polkadot/solid/Airplane Mode.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Alert.svg b/assets/icons/polkadot/solid/Alert.svg
new file mode 100644
index 00000000..1c21a678
--- /dev/null
+++ b/assets/icons/polkadot/solid/Alert.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Algorithm.svg b/assets/icons/polkadot/solid/Algorithm.svg
new file mode 100644
index 00000000..1af4b3fc
--- /dev/null
+++ b/assets/icons/polkadot/solid/Algorithm.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Alice.svg b/assets/icons/polkadot/solid/Alice.svg
new file mode 100644
index 00000000..194be375
--- /dev/null
+++ b/assets/icons/polkadot/solid/Alice.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Ambassadors.svg b/assets/icons/polkadot/solid/Ambassadors.svg
new file mode 100644
index 00000000..ac679ccf
--- /dev/null
+++ b/assets/icons/polkadot/solid/Ambassadors.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Announcement.svg b/assets/icons/polkadot/solid/Announcement.svg
new file mode 100644
index 00000000..bdf196de
--- /dev/null
+++ b/assets/icons/polkadot/solid/Announcement.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Anonymous Proxy.svg b/assets/icons/polkadot/solid/Anonymous Proxy.svg
new file mode 100644
index 00000000..d011bee5
--- /dev/null
+++ b/assets/icons/polkadot/solid/Anonymous Proxy.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M12.2739 4.77567C12.2739 3.79499 13.0689 3 14.0496 3C15.0303 3 15.8253 3.79499 15.8253 4.77567C15.8253 5.75635 15.0303 6.55134 14.0496 6.55134C13.4973 6.55134 13.0496 6.99906 13.0496 7.55134V9.38388C13.0496 9.93616 13.4973 10.3839 14.0496 10.3839C14.6019 10.3839 15.0496 9.93616 15.0496 9.38388V8.41749C16.6496 7.97917 17.8253 6.51472 17.8253 4.77567C17.8253 2.69042 16.1349 1 14.0496 1C11.9644 1 10.2739 2.69042 10.2739 4.77567C10.2739 5.32796 10.7217 5.77567 11.2739 5.77567C11.8262 5.77567 12.2739 5.32796 12.2739 4.77567ZM15.0496 12.8444C15.0496 12.2921 14.6019 11.8444 14.0496 11.8444C13.4973 11.8444 13.0496 12.2921 13.0496 12.8444V12.8545C13.0496 13.4068 13.4973 13.8545 14.0496 13.8545C14.6019 13.8545 15.0496 13.4068 15.0496 12.8545V12.8444ZM5.77571 17.2949V18.626C7.37563 19.0643 8.55134 20.5287 8.55134 22.2678C8.55134 24.353 6.86092 26.0435 4.77567 26.0435C2.69043 26.0435 1 24.353 1 22.2678C1 20.5287 2.17575 19.0643 3.77571 18.6259V16.2949C3.77571 16.0297 3.88107 15.7754 4.06861 15.5878C4.25614 15.4003 4.5105 15.2949 4.77571 15.2949H22.8386C23.3909 15.2949 23.8386 15.7426 23.8386 16.2949V18.5419C25.6317 18.8353 27 20.3918 27 22.2679C27 24.3531 25.3096 26.0436 23.2243 26.0436C21.1391 26.0436 19.4487 24.3531 19.4487 22.2679C19.4487 20.6719 20.4389 19.3071 21.8386 18.7546V17.2949L5.77571 17.2949Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Arbitrary Message.svg b/assets/icons/polkadot/solid/Arbitrary Message.svg
new file mode 100644
index 00000000..1c50ce9f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Arbitrary Message.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14.4767 9.76457C14.4767 6.89478 16.8031 4.56836 19.6729 4.56836C22.5427 4.56836 24.8691 6.89478 24.8691 9.76457C24.8691 12.6344 22.5427 14.9608 19.6729 14.9608C16.8031 14.9608 14.4767 12.6344 14.4767 9.76457ZM21.2912 16.7781V21.9624C21.2912 22.5147 20.8435 22.9624 20.2912 22.9624H11.7378L6.74312 26.7669C6.44074 26.9973 6.03391 27.0363 5.6933 26.8675C5.35268 26.6988 5.13717 26.3516 5.13717 25.9714V22.9624H2C1.44772 22.9624 1 22.5147 1 21.9624V9.30664C1 8.75436 1.44772 8.30664 2 8.30664H12.6245C13.2984 5.03126 16.198 2.56836 19.6729 2.56836C23.6472 2.56836 26.8691 5.79021 26.8691 9.76457C26.8691 13.1825 24.4863 16.0438 21.2912 16.7781ZM22.7334 7.88838C23.1089 8.29333 23.0851 8.92605 22.6801 9.30159L19.4452 12.3016C19.0728 12.647 18.5006 12.6583 18.1148 12.3279L16.3497 10.8163C15.9302 10.4571 15.8814 9.8258 16.2406 9.40631C16.5998 8.98683 17.2311 8.93799 17.6506 9.29723L18.7387 10.2291L21.3202 7.83513C21.7251 7.45959 22.3578 7.48343 22.7334 7.88838ZM7.70711 15.2929C7.31658 14.9024 6.68342 14.9024 6.29289 15.2929C5.90237 15.6834 5.90237 16.3166 6.29289 16.7071L6.31103 16.7252C6.70156 17.1158 7.33472 17.1158 7.72525 16.7252C8.11577 16.3347 8.11577 15.7016 7.72525 15.311L7.70711 15.2929ZM11.7071 15.2929C11.3166 14.9024 10.6834 14.9024 10.2929 15.2929C9.90237 15.6834 9.90237 16.3166 10.2929 16.7071L10.311 16.7252C10.7016 17.1158 11.3347 17.1158 11.7252 16.7252C12.1158 16.3347 12.1158 15.7016 11.7252 15.311L11.7071 15.2929ZM14.3291 15.2929C14.7197 14.9024 15.3528 14.9024 15.7434 15.2929L15.7615 15.311C16.152 15.7016 16.152 16.3347 15.7615 16.7252C15.371 17.1158 14.7378 17.1158 14.3473 16.7252L14.3291 16.7071C13.9386 16.3166 13.9386 15.6834 14.3291 15.2929Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Archive Node.svg b/assets/icons/polkadot/solid/Archive Node.svg
new file mode 100644
index 00000000..59db2271
--- /dev/null
+++ b/assets/icons/polkadot/solid/Archive Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M23.2282 19.4399C25.3113 19.4399 27 21.1286 27 23.2118C27 25.2949 25.3113 26.9836 23.2282 26.9836C21.1451 26.9836 19.4564 25.2949 19.4564 23.2118C19.4564 22.3414 19.7512 21.5399 20.2463 20.9017L18.226 17.9604C16.9661 18.6308 15.5281 19.0108 14.0013 19.0108C12.4801 19.0108 11.047 18.6336 9.79035 17.9676L7.74432 20.8897C8.24514 21.5298 8.54364 22.3359 8.54364 23.2118C8.54364 25.2949 6.85494 26.9836 4.77182 26.9836C2.68871 26.9836 1.00001 25.2949 1.00001 23.2118C1.00001 21.1286 2.68871 19.4399 4.77182 19.4399C5.25405 19.4399 5.71513 19.5304 6.13903 19.6954L8.13793 16.8406C6.21439 15.1891 4.99593 12.7395 4.99593 10.0054C4.99593 5.03185 9.02778 0.999999 14.0013 0.999999C18.9749 1 23.0067 5.03185 23.0067 10.0054C23.0067 12.734 21.7932 15.1792 19.8764 16.8306L21.8477 19.7006C22.2752 19.5323 22.7409 19.4399 23.2282 19.4399ZM16.8765 7.37703C17.267 7.76755 17.267 8.40072 16.8765 8.79124L15.5858 10.082L16.8764 11.3726C17.2669 11.7632 17.2669 12.3963 16.8764 12.7869C16.4859 13.1774 15.8527 13.1774 15.4622 12.7869L14.1715 11.4962L12.8807 12.787C12.4902 13.1775 11.857 13.1775 11.4665 12.787C11.076 12.3965 11.076 11.7633 11.4665 11.3728L12.7573 10.082L11.4664 8.79109C11.0759 8.40057 11.0759 7.7674 11.4664 7.37688C11.857 6.98635 12.4901 6.98635 12.8807 7.37688L14.1715 8.66776L15.4623 7.37703C15.8528 6.9865 16.486 6.9865 16.8765 7.37703Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Arrow Back.svg b/assets/icons/polkadot/solid/Arrow Back.svg
new file mode 100644
index 00000000..b3a0060e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Arrow Back.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M21.7589 26.6511C21.3993 27.0703 20.768 27.1185 20.3488 26.7589L6.34881 14.7469C6.12726 14.5568 5.99984 14.2794 5.99998 13.9875C6.00013 13.6955 6.12783 13.4182 6.34957 13.2284L20.3496 1.24041C20.7691 0.881191 21.4003 0.930067 21.7596 1.34957C22.1188 1.76908 22.0699 2.40035 21.6504 2.75957L8.53657 13.9887L21.6511 25.241C22.0703 25.6007 22.1185 26.232 21.7589 26.6511Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Arrow Down.svg b/assets/icons/polkadot/solid/Arrow Down.svg
new file mode 100644
index 00000000..a7269bda
--- /dev/null
+++ b/assets/icons/polkadot/solid/Arrow Down.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M13.9914 26C13.4391 26 12.9914 25.5523 12.9914 25L12.9914 2C12.9914 1.44772 13.4391 1 13.9914 1C14.5437 1 14.9914 1.44772 14.9914 2L14.9914 25C14.9914 25.5523 14.5437 26 13.9914 26Z" stroke="none"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3.30023 15.0859C3.69476 14.6994 4.32789 14.706 4.71437 15.1005L13.992 24.5716L23.2862 15.0999C23.6731 14.7057 24.3062 14.6997 24.7004 15.0865C25.0946 15.4733 25.1006 16.1065 24.7138 16.5007L14.7051 26.7004C14.517 26.8921 14.2596 27.0001 13.9909 27C13.7223 26.9999 13.465 26.8917 13.277 26.6998L3.28563 16.5C2.89916 16.1055 2.90569 15.4724 3.30023 15.0859Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Arrow Left.svg b/assets/icons/polkadot/solid/Arrow Left.svg
new file mode 100644
index 00000000..a5a1ce5c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Arrow Left.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M12.8995 4.71437C13.294 4.32789 13.3006 3.69476 12.9141 3.30023C12.5276 2.90569 11.8945 2.89916 11.5 3.28563L1.30023 13.277C1.10832 13.465 1.00012 13.7223 1 13.9909C0.999884 14.2596 1.10786 14.517 1.29961 14.7051L11.4993 24.7138C11.8935 25.1006 12.5267 25.0946 12.9135 24.7004C13.3003 24.3062 13.2943 23.6731 12.9001 23.2862L4.44671 14.9912L26 14.9912C26.5523 14.9912 27 14.5435 27 13.9912C27 13.4389 26.5523 12.9912 26 12.9912L4.45005 12.9912L12.8995 4.71437Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Arrow Right.svg b/assets/icons/polkadot/solid/Arrow Right.svg
new file mode 100644
index 00000000..a55a9e97
--- /dev/null
+++ b/assets/icons/polkadot/solid/Arrow Right.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M15.1005 23.2856C14.706 23.6721 14.6994 24.3052 15.0859 24.6998C15.4724 25.0943 16.1055 25.1008 16.5 24.7144L26.6998 14.723C26.8917 14.535 26.9999 14.2777 27 14.0091C27.0001 13.7404 26.8921 13.483 26.7004 13.2949L16.5007 3.28624C16.1065 2.89942 15.4733 2.90541 15.0865 3.29961C14.6997 3.69381 14.7057 4.32695 15.0999 4.71376L23.5533 13.0088L2 13.0088C1.44772 13.0088 1 13.4565 1 14.0088C1 14.5611 1.44772 15.0088 2 15.0088L23.5499 15.0088L15.1005 23.2856Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Arrow Up.svg b/assets/icons/polkadot/solid/Arrow Up.svg
new file mode 100644
index 00000000..bdd34eab
--- /dev/null
+++ b/assets/icons/polkadot/solid/Arrow Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M23.2856 12.8995C23.6721 13.294 24.3052 13.3006 24.6998 12.9141C25.0943 12.5276 25.1008 11.8945 24.7144 11.5L14.723 1.30023C14.535 1.10832 14.2777 1.00012 14.0091 1C13.7404 0.999884 13.483 1.10786 13.2949 1.29961L3.28624 11.4993C2.89943 11.8935 2.90541 12.5267 3.29961 12.9135C3.69381 13.3003 4.32695 13.2943 4.71376 12.9001L13.0086 4.4469L13.0086 26C13.0086 26.5523 13.4563 27 14.0086 27C14.5609 27 15.0086 26.5523 15.0086 26L15.0086 4.44986L23.2856 12.8995Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Article.svg b/assets/icons/polkadot/solid/Article.svg
new file mode 100644
index 00000000..62418f6a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Article.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><g><path fill-rule="evenodd" clip-rule="evenodd" d="M17 0.533203H5.19507C4.64278 0.533203 4.19507 0.980918 4.19507 1.5332V27.0057C4.19507 27.558 4.64278 28.0057 5.19507 28.0057H24.7893C25.3416 28.0057 25.7893 27.558 25.7893 27.0057V9.8155C25.6977 9.84313 25.6006 9.85798 25.5 9.85798H18C17.4477 9.85798 17 9.41027 17 8.85798V0.533203ZM25.6415 7.86791C25.6008 7.80169 25.5523 7.73992 25.4964 7.68408L19 1.18767V7.85798H25.5C25.548 7.85798 25.5953 7.86137 25.6415 7.86791ZM14.0125 4.45215C14.5647 4.45215 15.0125 4.89986 15.0125 5.45215V10.3507C15.0125 10.903 14.5647 11.3507 14.0125 11.3507H9.1139C8.56162 11.3507 8.1139 10.903 8.1139 10.3507V5.45215C8.1139 4.89986 8.56162 4.45215 9.1139 4.45215H14.0125ZM13.0125 6.45215H10.1139V9.35071H13.0125V6.45215ZM20.8704 18.209C21.4227 18.209 21.8704 17.7613 21.8704 17.209C21.8704 16.6567 21.4227 16.209 20.8704 16.209H9.11383C8.56155 16.209 8.11383 16.6567 8.11383 17.209C8.11383 17.7613 8.56155 18.209 9.11383 18.209H20.8704ZM21.8704 23.0869C21.8704 23.6392 21.4227 24.0869 20.8704 24.0869H9.11383C8.56155 24.0869 8.11383 23.6392 8.11383 23.0869C8.11383 22.5346 8.56155 22.0869 9.11383 22.0869H20.8704C21.4227 22.0869 21.8704 22.5346 21.8704 23.0869Z" stroke="none"></path></g></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Attack.svg b/assets/icons/polkadot/solid/Attack.svg
new file mode 100644
index 00000000..1a82c987
--- /dev/null
+++ b/assets/icons/polkadot/solid/Attack.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14 1C6.8203 1 1 6.8203 1 14C1 16.3662 1.63309 18.5876 2.73978 20.5007C2.91852 20.8097 3.24842 21 3.60539 21H6.32682V26C6.32682 26.5523 6.77454 27 7.32682 27H20.6602C21.2124 27 21.6602 26.5523 21.6602 26V21H24.3946C24.7516 21 25.0815 20.8097 25.2602 20.5007C26.3669 18.5876 27 16.3662 27 14C27 6.8203 21.1797 1 14 1ZM9.28605 12.1841C8.79696 12.1841 8.40047 12.5806 8.40047 13.0697C8.40047 13.5587 8.79696 13.9552 9.28605 13.9552C9.77514 13.9552 10.1716 13.5587 10.1716 13.0697C10.1716 12.5806 9.77514 12.1841 9.28605 12.1841ZM6.40047 13.0697C6.40047 11.476 7.69239 10.1841 9.28605 10.1841C10.8797 10.1841 12.1716 11.476 12.1716 13.0697C12.1716 14.6633 10.8797 15.9552 9.28605 15.9552C7.69239 15.9552 6.40047 14.6633 6.40047 13.0697ZM17.8284 13.0697C17.8284 12.5806 18.2248 12.1841 18.7139 12.1841C19.203 12.1841 19.5995 12.5806 19.5995 13.0697C19.5995 13.5587 19.203 13.9552 18.7139 13.9552C18.2248 13.9552 17.8284 13.5587 17.8284 13.0697ZM18.7139 10.1841C17.1203 10.1841 15.8284 11.476 15.8284 13.0697C15.8284 14.6633 17.1203 15.9552 18.7139 15.9552C20.3076 15.9552 21.5995 14.6633 21.5995 13.0697C21.5995 11.476 20.3076 10.1841 18.7139 10.1841Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Auctions.svg b/assets/icons/polkadot/solid/Auctions.svg
new file mode 100644
index 00000000..6f83acf1
--- /dev/null
+++ b/assets/icons/polkadot/solid/Auctions.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M5.63426 13.5843C5.24374 13.1938 5.24374 12.5606 5.63426 12.1701L16.5115 1.29289C16.902 0.902369 17.5352 0.902369 17.9257 1.29289L23.3643 6.7315C23.7548 7.12202 23.7548 7.75518 23.3643 8.14571L19.9923 11.5176L26.6905 18.2158C27.081 18.6063 27.081 19.2395 26.6905 19.63L23.9712 22.3493C23.5807 22.7398 22.9475 22.7398 22.557 22.3493L15.8588 15.6512L12.4871 19.0229C12.0966 19.4134 11.4634 19.4134 11.0729 19.0229L5.63426 13.5843ZM23.2641 20.228L17.2732 14.2371L18.5782 12.932L24.5692 18.9229L23.2641 20.228ZM1 26C1 25.4477 1.44772 25 2 25L14.4984 25C15.0507 25 15.4984 25.4477 15.4984 26C15.4984 26.5523 15.0507 27 14.4984 27L2 27C1.44772 27 1 26.5523 1 26ZM3.92285 21.6309C3.37057 21.6309 2.92285 22.0786 2.92285 22.6309C2.92285 23.1831 3.37057 23.6309 3.92285 23.6309H12.5756C13.1279 23.6309 13.5756 23.1831 13.5756 22.6309C13.5756 22.0786 13.1279 21.6309 12.5756 21.6309H3.92285Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Authority.svg b/assets/icons/polkadot/solid/Authority.svg
new file mode 100644
index 00000000..3e9d7eaf
--- /dev/null
+++ b/assets/icons/polkadot/solid/Authority.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 30 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M11.0111 3.05935C13.0856 0.642977 16.8255 0.642977 18.9001 3.05935C20.1124 4.4714 20.4774 6.42377 19.8572 8.17845L18.546 11.8878C18.3575 12.4214 18.5674 13.0141 19.0497 13.31L24.4413 16.6178C24.5796 16.7027 24.6927 16.8182 24.774 16.9526H5.14406C5.22532 16.8181 5.3384 16.7025 5.4767 16.6176L10.8619 13.3105C11.3441 13.0145 11.5538 12.4218 11.3653 11.8884L10.0539 8.17844C9.43371 6.42377 9.79874 4.4714 11.0111 3.05935ZM5 18.9526V22.4415C5 22.9938 5.44772 23.4415 6 23.4415H23.9184C24.4707 23.4415 24.9184 22.9938 24.9184 22.4415V18.9526H5Z" stroke="none"></path><path d="M22.1264 26.3618H8.25928"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Back Up.svg b/assets/icons/polkadot/solid/Back Up.svg
new file mode 100644
index 00000000..921325ff
--- /dev/null
+++ b/assets/icons/polkadot/solid/Back Up.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Balance.svg b/assets/icons/polkadot/solid/Balance.svg
new file mode 100644
index 00000000..8186b29a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Balance.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M1 4C1 3.44772 1.44772 3 2 3H26C26.5523 3 27 3.44772 27 4V24.219C27 24.7713 26.5523 25.219 26 25.219H2C1.44772 25.219 1 24.7713 1 24.219V4ZM15.0116 9.6499C15.0116 9.09762 14.5639 8.6499 14.0116 8.6499C13.4593 8.6499 13.0116 9.09762 13.0116 9.6499V9.89248C12.4865 9.98646 11.9982 10.2396 11.6163 10.6234C11.1261 11.1152 10.8514 11.7812 10.85 12.4742V12.496C10.85 13.192 11.1273 13.8584 11.6168 14.3492C12.1072 14.841 12.7725 15.1178 13.4654 15.1206H14.5519C14.6392 15.1206 14.721 15.1371 14.7945 15.1672C14.8697 15.1981 14.9385 15.244 14.9954 15.3009L14.9974 15.3029C15.0547 15.3598 15.1006 15.4281 15.1322 15.5044C15.1637 15.5803 15.18 15.6621 15.18 15.7444C15.18 15.8285 15.1638 15.9114 15.1326 15.9883C15.1011 16.064 15.0551 16.133 14.996 16.1924C14.9401 16.2486 14.8714 16.295 14.7936 16.3272C14.7202 16.3577 14.6399 16.3736 14.5577 16.3733H12.187C11.6347 16.3733 11.187 16.821 11.187 17.3733C11.187 17.9256 11.6347 18.3733 12.187 18.3733H13.0116V18.5924C13.0116 19.1447 13.4593 19.5924 14.0116 19.5924C14.5639 19.5924 15.0116 19.1447 15.0116 18.5924V18.3341C15.1989 18.3013 15.3828 18.2481 15.56 18.1746C15.877 18.0431 16.1685 17.8498 16.4142 17.6026C16.6564 17.3591 16.8497 17.0702 16.9819 16.7501L16.9833 16.7467C17.1137 16.4276 17.18 16.0871 17.18 15.7444C17.18 15.3991 17.1118 15.0569 16.9796 14.738C16.8478 14.4205 16.6548 14.131 16.4096 13.8867C16.1649 13.6419 15.8734 13.4482 15.5539 13.317C15.2327 13.1852 14.8922 13.1206 14.5519 13.1206H13.4719C13.307 13.1195 13.149 13.0533 13.033 12.937C12.9157 12.8194 12.85 12.6601 12.85 12.496V12.4774C12.8505 12.3107 12.9169 12.1516 13.033 12.0351L13.034 12.0341C13.1499 11.9176 13.3071 11.8521 13.4707 11.8516H15.6525C16.2048 11.8516 16.6525 11.4038 16.6525 10.8516C16.6525 10.2993 16.2048 9.85156 15.6525 9.85156H15.0116V9.6499Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Batch Transaction.svg b/assets/icons/polkadot/solid/Batch Transaction.svg
new file mode 100644
index 00000000..47cbb22b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Batch Transaction.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M13.2139 1.29057C13.402 1.4775 13.5082 1.73151 13.5091 1.99672L13.5272 7.54622C13.5291 8.0985 13.0828 8.54768 12.5305 8.54949C11.9782 8.5513 11.5291 8.10505 11.5273 7.55277L11.5173 4.51604L2.70711 13.3262C2.31658 13.7168 1.68342 13.7168 1.29289 13.3262C0.902369 12.9357 0.902369 12.3025 1.29289 11.912L10.1973 3.00762L6.97827 3.01822C6.42599 3.02004 5.9768 2.5738 5.97498 2.02152C5.97316 1.46924 6.4194 1.02005 6.97168 1.01823L12.5058 1.00001C12.771 0.999132 13.0257 1.10365 13.2139 1.29057ZM24.9901 4.5315L25 7.55277C25.0018 8.10505 25.451 8.5513 26.0033 8.54949C26.5556 8.54768 27.0018 8.0985 27 7.54622L26.9818 1.99672C26.981 1.73151 26.8748 1.4775 26.6866 1.29057C26.4985 1.10365 26.2438 0.999132 25.9786 1.00001L20.4445 1.01823C19.8922 1.02005 19.4459 1.46924 19.4478 2.02152C19.4496 2.5738 19.8988 3.02004 20.451 3.01822L23.6856 3.00757L1.40013 25.2931C1.00961 25.6836 1.00961 26.3168 1.40013 26.7073C1.79066 27.0978 2.42382 27.0978 2.81435 26.7073L24.9901 4.5315ZM23.6701 16.3885L20.451 16.3991C19.8988 16.4009 19.4496 15.9547 19.4478 15.4024C19.4459 14.8501 19.8922 14.4009 20.4445 14.3991L25.9786 14.3809C26.2438 14.38 26.4985 14.4845 26.6866 14.6714C26.8748 14.8584 26.981 15.1124 26.9818 15.3776L27 20.9271C27.0018 21.4794 26.5556 21.9285 26.0033 21.9303C25.451 21.9322 25.0018 21.4859 25 20.9336L24.9901 17.8969L16.1799 26.7071C15.7894 27.0976 15.1562 27.0976 14.7657 26.7071C14.3751 26.3166 14.3751 25.6834 14.7657 25.2929L23.6701 16.3885Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Bid.svg b/assets/icons/polkadot/solid/Bid.svg
new file mode 100644
index 00000000..b8c55619
--- /dev/null
+++ b/assets/icons/polkadot/solid/Bid.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M13.5053 1C8.25567 1 4 5.25567 4 10.5053C4 15.4172 7.72574 19.459 12.5054 19.9587V26C12.5054 26.5523 12.9531 27 13.5054 27C14.0577 27 14.5054 26.5523 14.5054 26V19.9587C19.285 19.4589 23.0106 15.4172 23.0106 10.5053C23.0106 5.25567 18.755 1 13.5053 1ZM17.5208 6.88008C17.957 7.21877 18.0361 7.84698 17.6974 8.28322L13.2952 13.9534C13.1099 14.192 12.8267 14.3341 12.5247 14.34C12.2227 14.3459 11.9342 14.2149 11.7398 13.9837L9.33784 11.1267C8.98243 10.704 9.03701 10.0732 9.45974 9.71774C9.88247 9.36233 10.5133 9.41691 10.8687 9.83964L12.4743 11.7494L16.1176 7.05672C16.4563 6.62047 17.0845 6.54139 17.5208 6.88008Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Block Explorer.svg b/assets/icons/polkadot/solid/Block Explorer.svg
new file mode 100644
index 00000000..8d8047ba
--- /dev/null
+++ b/assets/icons/polkadot/solid/Block Explorer.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M3 2C3 1.44772 3.44772 1 4 1H24C24.5523 1 25 1.44772 25 2V26C25 26.5523 24.5523 27 24 27H4C3.44772 27 3 26.5523 3 26V2ZM19.4584 9.33936C20.0107 9.33936 20.4584 8.89164 20.4584 8.33936C20.4584 7.78707 20.0107 7.33936 19.4584 7.33936H11.9206C11.3683 7.33936 10.9206 7.78707 10.9206 8.33936C10.9206 8.89164 11.3683 9.33936 11.9206 9.33936H19.4584ZM8.43256 9.33936C8.98484 9.33936 9.43256 8.89164 9.43256 8.33936C9.43256 7.78707 8.98484 7.33936 8.43256 7.33936H8.42177C7.86948 7.33936 7.42177 7.78707 7.42177 8.33936C7.42177 8.89164 7.86948 9.33936 8.42177 9.33936H8.43256ZM19.4584 14.75C20.0107 14.75 20.4584 14.3023 20.4584 13.75C20.4584 13.1977 20.0107 12.75 19.4584 12.75H11.9206C11.3683 12.75 10.9206 13.1977 10.9206 13.75C10.9206 14.3023 11.3683 14.75 11.9206 14.75H19.4584ZM8.43256 14.75C8.98484 14.75 9.43256 14.3023 9.43256 13.75C9.43256 13.1977 8.98484 12.75 8.43256 12.75H8.42177C7.86948 12.75 7.42177 13.1977 7.42177 13.75C7.42177 14.3023 7.86948 14.75 8.42177 14.75H8.43256ZM20.4584 19.3394C20.4584 19.8916 20.0107 20.3394 19.4584 20.3394H11.9206C11.3683 20.3394 10.9206 19.8916 10.9206 19.3394C10.9206 18.7871 11.3683 18.3394 11.9206 18.3394H19.4584C20.0107 18.3394 20.4584 18.7871 20.4584 19.3394ZM9.43256 19.3394C9.43256 19.8916 8.98484 20.3394 8.43256 20.3394H8.42177C7.86948 20.3394 7.42177 19.8916 7.42177 19.3394C7.42177 18.7871 7.86948 18.3394 8.42177 18.3394H8.43256C8.98484 18.3394 9.43256 18.7871 9.43256 19.3394Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Block Number.svg b/assets/icons/polkadot/solid/Block Number.svg
new file mode 100644
index 00000000..6efdcbee
--- /dev/null
+++ b/assets/icons/polkadot/solid/Block Number.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M3.57235 5C3.57235 4.44771 4.02006 4 4.57235 4H23.4277C23.9799 4 24.4277 4.44771 24.4277 5V13.4277H26C26.5523 13.4277 27 13.8754 27 14.4277C27 14.98 26.5523 15.4277 26 15.4277H24.4277V23.8553C24.4277 24.4076 23.9799 24.8553 23.4277 24.8553H4.57235C4.02006 24.8553 3.57235 24.4076 3.57235 23.8553V15.4277H2C1.44772 15.4277 1 14.98 1 14.4277C1 13.8754 1.44772 13.4277 2 13.4277H3.57235V5ZM11.8745 19.5992C11.3222 19.5992 10.8745 19.1515 10.8745 18.5992V17.502H9.77731C9.22503 17.502 8.77731 17.0542 8.77731 16.502C8.77731 15.9497 9.22503 15.502 9.77731 15.502H10.8745V13.2113H9.77731C9.22503 13.2113 8.77731 12.7636 8.77731 12.2113C8.77731 11.6591 9.22503 11.2113 9.77731 11.2113H10.8745V10.1143C10.8745 9.56197 11.3222 9.11426 11.8745 9.11426C12.4268 9.11426 12.8745 9.56197 12.8745 10.1143V11.2113L15.1651 11.2113V10.1143C15.1651 9.56197 15.6128 9.11426 16.1651 9.11426C16.7174 9.11426 17.1651 9.56197 17.1651 10.1143V11.2113H18.2623C18.8146 11.2113 19.2623 11.6591 19.2623 12.2113C19.2623 12.7636 18.8146 13.2113 18.2623 13.2113H17.1651V15.502H18.2623C18.8146 15.502 19.2623 15.9497 19.2623 16.502C19.2623 17.0542 18.8146 17.502 18.2623 17.502H17.1651V18.5992C17.1651 19.1515 16.7174 19.5992 16.1651 19.5992C15.6128 19.5992 15.1651 19.1515 15.1651 18.5992V17.502L12.8745 17.502V18.5992C12.8745 19.1515 12.4267 19.5992 11.8745 19.5992ZM15.1651 15.502H12.8745V13.2113H15.1651V15.502Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Block Search.svg b/assets/icons/polkadot/solid/Block Search.svg
new file mode 100644
index 00000000..889515b8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Block Search.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M13.831 1C8.40091 1 4 5.40201 4 10.831C4 16.2601 8.40194 20.662 13.831 20.662C14.2447 20.662 14.6525 20.6365 15.0527 20.5869L18.4657 26.5C18.5983 26.7297 18.8167 26.8974 19.0729 26.966C19.3291 27.0347 19.6021 26.9988 19.8318 26.8661L23.8734 24.5324C24.3516 24.2563 24.5155 23.6449 24.2395 23.1666L21.0024 17.5556C22.6519 15.7972 23.662 13.432 23.662 10.831C23.662 5.40201 19.2611 1 13.831 1ZM19.6979 24.634L17.0868 20.1101C17.9387 19.8112 18.7369 19.3984 19.4632 18.8898L22.0076 23.3002L19.6979 24.634ZM10.8704 6.93066C10.3181 6.93066 9.87037 7.37838 9.87037 7.93066V13.73C9.87037 14.2823 10.3181 14.73 10.8704 14.73H16.6735C17.2258 14.73 17.6735 14.2823 17.6735 13.73V7.93066C17.6735 7.37838 17.2258 6.93066 16.6735 6.93066H10.8704ZM11.8704 12.73V8.93066H15.6735V12.73H11.8704Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Block.svg b/assets/icons/polkadot/solid/Block.svg
new file mode 100644
index 00000000..d1433e66
--- /dev/null
+++ b/assets/icons/polkadot/solid/Block.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Blockchain.svg b/assets/icons/polkadot/solid/Blockchain.svg
new file mode 100644
index 00000000..4066afe3
--- /dev/null
+++ b/assets/icons/polkadot/solid/Blockchain.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M1 2C1 1.44772 1.44772 1 2 1H11.2309C11.7832 1 12.2309 1.44772 12.2309 2V5.70215H15.7692V2C15.7692 1.44772 16.2169 1 16.7692 1H26.0001C26.5523 1 27.0001 1.44772 27.0001 2V11.2309C27.0001 11.7832 26.5523 12.2309 26.0001 12.2309H17.1834L12.2308 17.1836V20.5342H15.7692V16.769C15.7692 16.2168 16.2169 15.769 16.7692 15.769H26C26.5523 15.769 27 16.2168 27 16.769V25.9999C27 26.5521 26.5523 26.9999 26 26.9999H16.7692C16.2169 26.9999 15.7692 26.5521 15.7692 25.9999V22.5342H12.2308V25.9998C12.2308 26.5521 11.7831 26.9998 11.2308 26.9998H2C1.44772 26.9998 1 26.5521 1 25.9998V16.769C1 16.2168 1.44772 15.769 2 15.769H10.8169L15.7692 10.8167V7.70215H12.2309V11.2309C12.2309 11.7832 11.7832 12.2309 11.2309 12.2309H2C1.44772 12.2309 1 11.7832 1 11.2309V2Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Blog Post.svg b/assets/icons/polkadot/solid/Blog Post.svg
new file mode 100644
index 00000000..870506c2
--- /dev/null
+++ b/assets/icons/polkadot/solid/Blog Post.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M23.6246 4.90601C23.6181 4.91286 23.6115 4.91963 23.6048 4.92631L16.6946 11.8365L15.9564 14.556L18.6795 13.8197L25.5889 6.91019C26.1372 6.36137 26.1367 5.47288 25.5894 4.92544M23.6246 4.90601C24.1733 4.37812 25.047 4.38404 25.5894 4.92544L23.6246 4.90601ZM22.1906 3.51116C23.5195 2.18228 25.6738 2.18279 27.0032 3.5108C28.332 4.83967 28.3319 6.99435 27.0039 8.3237L19.9051 15.4225C19.7815 15.5461 19.6277 15.6351 19.459 15.6807L14.7956 16.9417C14.4497 17.0352 14.0803 16.9365 13.8271 16.6831C13.5739 16.4296 13.4756 16.0601 13.5695 15.7143L14.8342 11.0557C14.8799 10.8873 17.3767 10.6233 17.5 10.5L22.1652 3.53748C22.1735 3.52857 22.182 3.51979 22.1906 3.51116Z" stroke="none"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M2 3C2 2.44772 2.44772 2 3 2H24.1462C24.6985 2 25.1462 2.44772 25.1462 3V3.5578C25.1462 4.03821 24.8046 4.45074 24.3326 4.54028C24.0653 4.59097 23.8122 4.71835 23.6056 4.92557L23.6046 4.92652L16.6944 11.8367L15.9562 14.5562L18.6793 13.8199L23.4391 9.06005C23.7251 8.77405 24.1552 8.6885 24.5289 8.84328C24.9026 8.99806 25.1462 9.3627 25.1462 9.76716V21.2005C25.1462 21.7528 24.6985 22.2005 24.1462 22.2005H11.919L3.50007 27.0621C3.19067 27.2408 2.80946 27.2408 2.50004 27.0622C2.19061 26.8836 2 26.5534 2 26.1962V3ZM5.98218 9.25098C5.98218 8.69869 6.42989 8.25098 6.98218 8.25098H16.8356C17.3879 8.25098 17.8356 8.69869 17.8356 9.25098C17.8356 9.80326 17.3879 10.251 16.8356 10.251H6.98218C6.42989 10.251 5.98218 9.80326 5.98218 9.25098ZM6.32574 15.9766C6.32574 15.4243 6.77346 14.9766 7.32574 14.9766H11.1708C11.7231 14.9766 12.1708 15.4243 12.1708 15.9766C12.1708 16.5288 11.7231 16.9766 11.1708 16.9766H7.32574C6.77346 16.9766 6.32574 16.5288 6.32574 15.9766Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Bob.svg b/assets/icons/polkadot/solid/Bob.svg
new file mode 100644
index 00000000..04647271
--- /dev/null
+++ b/assets/icons/polkadot/solid/Bob.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M17.8779 4.07829C15.872 2.14317 12.6941 2.14318 10.6882 4.07829C8.70956 5.98699 8.56757 9.10922 10.3647 11.1896L11.273 12.241C11.3272 12.3038 11.309 12.4008 11.2356 12.4396L9.64619 13.28C6.17287 15.1164 4.00002 18.7232 4.00005 22.6521L4.00007 25.9998C4.00007 26.5521 4.44779 26.9998 5.00007 26.9998H23.5736C23.8388 26.9998 24.0931 26.8945 24.2807 26.7069C24.4682 26.5194 24.5736 26.2651 24.5736 25.9998L24.5735 22.657C24.5735 18.7254 22.3985 15.1165 18.9222 13.28L17.3308 12.4392C17.2574 12.4004 17.2392 12.3035 17.2934 12.2407L18.2014 11.1896C19.9985 9.10922 19.8565 5.98699 17.8779 4.07829Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Bond.svg b/assets/icons/polkadot/solid/Bond.svg
new file mode 100644
index 00000000..605b4cd1
--- /dev/null
+++ b/assets/icons/polkadot/solid/Bond.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Bonded Time.svg b/assets/icons/polkadot/solid/Bonded Time.svg
new file mode 100644
index 00000000..a86d7bb9
--- /dev/null
+++ b/assets/icons/polkadot/solid/Bonded Time.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M6.55818 6.82266C6.55819 3.60689 9.16508 1 12.3808 1C15.5966 1 18.2035 3.6069 18.2035 6.82268L18.2035 7.82568H21.7615C22.3138 7.82568 22.7615 8.2734 22.7615 8.82568V12.8543C25.4227 13.9606 27.294 16.5852 27.294 19.6469C27.294 23.7078 24.0019 26.9998 19.941 26.9998C17.2806 26.9998 14.9501 25.5869 13.6591 23.4704H3C2.44772 23.4704 2 23.0227 2 22.4704V8.82568C2 8.2734 2.44772 7.82568 3 7.82568H6.55817L6.55818 6.82267V6.82266ZM16.2035 6.82267L16.2035 7.82568H8.55817L8.55818 6.82268L7.55818 6.82267H8.55818C8.55818 4.71147 10.2696 3 12.3808 3C14.4921 3 16.2035 4.71147 16.2035 6.82267ZM19.941 14.2939C16.9847 14.2939 14.5881 16.6905 14.5881 19.6469C14.5881 22.6032 16.9847 24.9998 19.941 24.9998C22.8974 24.9998 25.294 22.6032 25.294 19.6469C25.294 16.6905 22.8974 14.2939 19.941 14.2939ZM19.063 17.1426C19.063 16.5903 19.5107 16.1426 20.063 16.1426C20.6153 16.1426 21.063 16.5903 21.063 17.1426V19.8528C21.063 20.0848 20.9823 20.3097 20.8347 20.4887L19.7717 21.7786C19.4205 22.2048 18.7902 22.2655 18.364 21.9143C17.9378 21.563 17.8771 20.9328 18.2283 20.5066L19.063 19.4938V17.1426Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Boot Node.svg b/assets/icons/polkadot/solid/Boot Node.svg
new file mode 100644
index 00000000..7005e178
--- /dev/null
+++ b/assets/icons/polkadot/solid/Boot Node.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M23.2282 19.4399C25.3113 19.4399 27 21.1286 27 23.2118C27 25.2949 25.3113 26.9836 23.2282 26.9836C21.1451 26.9836 19.4564 25.2949 19.4564 23.2118C19.4564 22.3414 19.7512 21.5399 20.2463 20.9017L18.226 17.9604C16.9661 18.6308 15.5281 19.0108 14.0013 19.0108C12.4801 19.0108 11.047 18.6336 9.79042 17.9677L7.74437 20.8897C8.24516 21.5299 8.54364 22.336 8.54364 23.2118C8.54364 25.2949 6.85494 26.9836 4.77182 26.9836C2.68871 26.9836 1.00001 25.2949 1.00001 23.2118C1.00001 21.1286 2.68871 19.4399 4.77182 19.4399C5.25408 19.4399 5.71519 19.5304 6.1391 19.6954L8.13799 16.8407C6.21441 15.1891 4.99593 12.7396 4.99593 10.0054C4.99593 5.03185 9.02778 0.999999 14.0013 0.999999C18.9749 1 23.0067 5.03185 23.0067 10.0054C23.0067 12.734 21.7932 15.1792 19.8764 16.8306L21.8477 19.7006C22.2752 19.5323 22.7409 19.4399 23.2282 19.4399ZM11.715 9.739C11.3244 9.34848 10.6913 9.34849 10.3008 9.73902C9.91024 10.1295 9.91025 10.7627 10.3008 11.1532L13.2942 14.1466C13.6847 14.5371 14.3179 14.5371 14.7084 14.1466L17.7017 11.1532C18.0922 10.7627 18.0922 10.1295 17.7017 9.73901C17.3112 9.34848 16.678 9.34849 16.2875 9.73901L15.0013 11.0252L15.0013 6.57417C15.0013 6.02188 14.5536 5.57417 14.0013 5.57417C13.449 5.57417 13.0013 6.02188 13.0013 6.57417L13.0013 11.0253L11.715 9.739Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Bridge.svg b/assets/icons/polkadot/solid/Bridge.svg
new file mode 100644
index 00000000..0b42b604
--- /dev/null
+++ b/assets/icons/polkadot/solid/Bridge.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M3 7.39648C2.73478 7.39648 2.48043 7.50184 2.29289 7.68938C2.10535 7.87692 2 8.13127 2 8.39649L2.00008 20.3965C2.00009 20.9488 2.4478 21.3965 3.00008 21.3965L5.74999 21.3965C6.07721 21.3965 6.38368 21.2364 6.57063 20.9679L6.57024 20.9685L6.56973 20.9692C6.56973 20.9692 6.57039 20.9683 6.57172 20.9664L6.58767 20.9445C6.60362 20.9229 6.63016 20.8877 6.66721 20.8407C6.74138 20.7467 6.85728 20.6064 7.01438 20.435C7.32929 20.0914 7.80543 19.6279 8.43821 19.1636C9.70173 18.2366 11.5715 17.3182 14.039 17.3182C16.5055 17.3182 18.3539 18.2358 19.5954 19.1596C20.2176 19.6226 20.6835 20.0848 20.9908 20.4272C21.1441 20.598 21.2568 20.7378 21.3288 20.8313C21.3648 20.878 21.3905 20.913 21.4058 20.9344L21.4211 20.956L21.4218 20.9568L21.4218 20.9569L21.4218 20.9569C21.6078 21.2317 21.918 21.3965 22.25 21.3965L24.9986 21.3965C25.5508 21.3965 25.9985 20.9488 25.9986 20.3966L26 8.39664C26 8.1314 25.8947 7.87701 25.7071 7.68945C25.5196 7.50189 25.2652 7.39652 25 7.39652L3 7.39648ZM6.57063 20.9679L6.57087 20.9676L6.57128 20.967C6.57106 20.9673 6.57084 20.9676 6.57063 20.9679Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Bridges.svg b/assets/icons/polkadot/solid/Bridges.svg
new file mode 100644
index 00000000..5dfe5854
--- /dev/null
+++ b/assets/icons/polkadot/solid/Bridges.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Build.svg b/assets/icons/polkadot/solid/Build.svg
new file mode 100644
index 00000000..c92d599a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Build.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M15.5099 2.09714C15.2379 1.96762 14.922 1.96762 14.65 2.09714L12.5968 3.07485C12.0982 3.3123 11.8865 3.90901 12.1239 4.40765C12.3614 4.90628 12.9581 5.11802 13.4567 4.88058L15.08 4.10759L16.7032 4.88058C17.2019 5.11802 17.7986 4.90628 18.036 4.40765C18.2735 3.90901 18.0617 3.3123 17.5631 3.07485L15.5099 2.09714ZM7.68819 7.62749C8.18682 7.39004 8.39856 6.79333 8.16111 6.2947C7.92367 5.79606 7.32696 5.58432 6.82832 5.82177L4.38403 6.98572C4.03579 7.15155 3.81396 7.50287 3.81396 7.88858C3.81396 8.27429 4.03579 8.62561 4.38403 8.79144L6.82832 9.95538C7.32696 10.1928 7.92367 9.98109 8.16111 9.48246C8.39856 8.98382 8.18682 8.38711 7.68819 8.14966L7.13991 7.88858L7.68819 7.62749ZM23.3316 5.82177C22.833 5.58432 22.2363 5.79606 21.9988 6.2947C21.7614 6.79333 21.9731 7.39004 22.4718 7.62749L23.02 7.88858L22.4718 8.14966C21.9731 8.38711 21.7614 8.98382 21.9988 9.48246C22.2363 9.98109 22.833 10.1928 23.3316 9.95538L25.7759 8.79144C26.1242 8.62561 26.346 8.27429 26.346 7.88858C26.346 7.50287 26.1242 7.15155 25.7759 6.98572L23.3316 5.82177ZM13.4567 10.8966C12.9581 10.6591 12.3614 10.8709 12.1239 11.3695C11.8865 11.8681 12.0982 12.4649 12.5968 12.7023L14.65 13.68C14.922 13.8095 15.2379 13.8095 15.5099 13.68L17.5631 12.7023C18.0617 12.4649 18.2735 11.8681 18.036 11.3695C17.7986 10.8709 17.2019 10.6591 16.7032 10.8966L15.08 11.6696L13.4567 10.8966ZM3.47024 11.2148C3.76275 11.0321 4.12877 11.0131 4.4387 11.1644L13.5042 15.59C13.8476 15.7576 14.0655 16.1064 14.0655 16.4886V26.9998C14.0655 27.3447 13.8877 27.6652 13.5952 27.8479C13.3027 28.0306 12.9367 28.0497 12.6268 27.8984L3.56129 23.4727C3.21784 23.305 3 22.9563 3 22.5741V12.063C3 11.7181 3.17772 11.3976 3.47024 11.2148ZM26.6897 11.2148C26.3972 11.0321 26.0312 11.0131 25.7213 11.1644L16.6558 15.59C16.3124 15.7576 16.0945 16.1064 16.0945 16.4886V26.9998C16.0945 27.3447 16.2722 27.6652 16.5648 27.8479C16.8573 28.0306 17.2233 28.0497 17.5332 27.8984L26.5987 23.4727C26.9421 23.305 27.16 22.9563 27.16 22.5741V12.063C27.16 11.7181 26.9823 11.3976 26.6897 11.2148Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Builders _ Developers.svg b/assets/icons/polkadot/solid/Builders _ Developers.svg
new file mode 100644
index 00000000..758dfc8e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Builders _ Developers.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14 3C12.3433 3 11 4.34328 11 6H17C17 4.34328 15.6567 3 14 3ZM19.3523 8H20C20.5523 8 21 7.55228 21 7C21 6.44772 20.5523 6 20 6H19C19 3.23872 16.7613 1 14 1C11.2387 1 9 3.23872 9 6H8C7.44772 6 7 6.44772 7 7C7 7.55228 7.44772 8 8 8H8.63859C8.26587 9.43149 8.46866 10.9877 9.27732 12.2969C9.41951 12.527 9.58042 12.7496 9.76023 12.9625L10.6002 13.9565C10.6895 14.0623 10.6394 14.2256 10.5046 14.2626L9.27165 14.6006C5.56729 15.6156 2.99902 18.9814 2.99902 22.823V26C2.99902 26.5523 3.44674 27 3.99902 27H24C24.5523 27 25 26.5523 25 26V22.828C25 18.9844 22.4294 15.6154 18.7218 14.6004L17.4863 14.2626C17.3515 14.2255 17.3015 14.0621 17.3909 13.9564L18.2308 12.9625C19.4337 11.5392 19.7908 9.68353 19.3523 8Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Built-in Security.svg b/assets/icons/polkadot/solid/Built-in Security.svg
new file mode 100644
index 00000000..d15eee00
--- /dev/null
+++ b/assets/icons/polkadot/solid/Built-in Security.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M11.5568 1.33254C11.2414 0.980711 10.7228 0.897646 10.3133 1.13338L4.77558 4.32118C4.37137 4.55387 4.18168 5.03508 4.31841 5.481L5.26046 8.55326L4.93792 9.11669L1.79478 9.77574C1.33166 9.87284 1 10.2813 1 10.7545V17.1493C1 17.6161 1.32291 18.0208 1.77804 18.1244L4.90709 18.8367L5.23474 19.4019L4.23729 22.4534C4.09039 22.9028 4.27832 23.3937 4.68777 23.6301L10.2255 26.8275C10.6302 27.0612 11.1429 26.9834 11.46 26.6401L13.6189 24.3034H14.3058L16.4349 26.669C16.7505 27.0197 17.2682 27.1021 17.6771 26.8667L23.2148 23.6789C23.6197 23.4458 23.8092 22.9634 23.6713 22.517L22.7067 19.3951L22.8394 18.9965L26.1501 18.4277C26.63 18.3452 26.9807 17.929 26.9807 17.4421V10.8508C26.9807 10.3844 26.6583 9.97988 26.2036 9.87592L23.1332 9.17386L22.7734 8.54967L23.7445 5.54339C23.8895 5.09451 23.7011 4.60535 23.2925 4.36971L17.7644 1.18191C17.3609 0.949244 16.8503 1.02593 16.5329 1.36682L14.364 3.69667H13.6761L11.5568 1.33254ZM13.9936 9.19385C13.5575 9.19436 13.1394 9.3678 12.8311 9.67617C12.5222 9.985 12.3487 10.4039 12.3487 10.8406V11.9866H15.632V10.8406C15.632 10.405 15.4594 9.98705 15.152 9.67841C14.845 9.37021 14.4285 9.19604 13.9936 9.19385ZM17.632 11.9866V10.8406C17.632 9.87587 17.2498 8.95043 16.5689 8.26693C15.8881 7.58344 14.9641 7.19757 13.9994 7.19385H13.9955C13.0283 7.19385 12.1008 7.57806 11.4168 8.26196C10.7329 8.94586 10.3487 9.87343 10.3487 10.8406V11.9866H9.775C9.22272 11.9866 8.775 12.4344 8.775 12.9866V18.3108C8.775 18.8631 9.22272 19.3108 9.775 19.3108H18.216C18.7683 19.3108 19.216 18.8631 19.216 18.3108V12.9866C19.216 12.4344 18.7683 11.9866 18.216 11.9866H17.632ZM10.775 17.3108V13.9866H17.216V17.3108H10.775Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Burn.svg b/assets/icons/polkadot/solid/Burn.svg
new file mode 100644
index 00000000..922c273e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Burn.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/C++.svg b/assets/icons/polkadot/solid/C++.svg
new file mode 100644
index 00000000..6d9d7d47
--- /dev/null
+++ b/assets/icons/polkadot/solid/C++.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Calendar.svg b/assets/icons/polkadot/solid/Calendar.svg
new file mode 100644
index 00000000..6f948179
--- /dev/null
+++ b/assets/icons/polkadot/solid/Calendar.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M9.42334 1C9.97563 1 10.4233 1.44772 10.4233 2V2.88477H17.5764V6.34177C17.5764 6.89405 18.0241 7.34177 18.5764 7.34177C19.1287 7.34177 19.5764 6.89405 19.5764 6.34177V2.88477H26C26.5523 2.88477 27 3.33248 27 3.88477V10H1V3.88477C1 3.33248 1.44772 2.88477 2 2.88477H8.42334V2C8.42334 1.44772 8.87106 1 9.42334 1ZM1 12V26.0002C1 26.5525 1.44772 27.0002 2 27.0002H26C26.5523 27.0002 27 26.5525 27 26.0002V12H1ZM19.5764 2V2.88184H17.5764V2C17.5764 1.44772 18.0241 1 18.5764 1C19.1287 1 19.5764 1.44772 19.5764 2ZM9.42334 7.34156C9.97562 7.34156 10.4233 6.89384 10.4233 6.34156V2.89014H8.42334V6.34156C8.42334 6.89384 8.87106 7.34156 9.42334 7.34156Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Career.svg b/assets/icons/polkadot/solid/Career.svg
new file mode 100644
index 00000000..a198a16d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Career.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M10.3813 2C9.829 2 9.38129 2.44772 9.38129 3V6.62793H3C2.44772 6.62793 2 7.07564 2 7.62793V13.3442H28V7.62793C28 7.07564 27.5523 6.62793 27 6.62793H20.6192V3C20.6192 2.44772 20.1714 2 19.6192 2H10.3813ZM28 15.3442H2V24.2376C2 24.7899 2.44772 25.2376 3 25.2376H27C27.5523 25.2376 28 24.7899 28 24.2376V15.3442ZM11.3813 6.62793H18.6192V4H11.3813V6.62793Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Certificate.svg b/assets/icons/polkadot/solid/Certificate.svg
new file mode 100644
index 00000000..e2d6d4b6
--- /dev/null
+++ b/assets/icons/polkadot/solid/Certificate.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M24.9559 26.7227C24.9559 27.2749 24.5082 27.7227 23.9559 27.7227H4.38208C3.82979 27.7227 3.38208 27.2749 3.38208 26.7227V1.27665C3.38208 0.724361 3.82979 0.276646 4.38208 0.276646H23.9559C24.5082 0.276646 24.9559 0.724361 24.9559 1.27665V26.7227ZM13.89 4C13.6248 4 13.3705 4.10535 13.1829 4.29289C12.9954 4.48042 12.89 4.73478 12.89 5V14.3606C12.89 14.6966 13.0588 15.0102 13.3392 15.1953C13.6197 15.3803 13.9743 15.4122 14.2833 15.2801L16.9656 14.1328L19.6498 15.274C19.9587 15.4053 20.3128 15.3729 20.5928 15.1878C20.8727 15.0026 21.0411 14.6894 21.0411 14.3537V5.00011C21.0411 4.44783 20.5934 4.00012 20.0411 4.00011L13.89 4ZM14.89 12.8453V6.00002L19.0411 6.00009V12.842L17.3556 12.1254C17.1049 12.0189 16.8216 12.0192 16.5711 12.1263L14.89 12.8453ZM8.29675 21.8081C7.74447 21.8081 7.29675 22.2558 7.29675 22.8081C7.29675 23.3604 7.74447 23.8081 8.29675 23.8081H20.0411C20.5934 23.8081 21.0411 23.3604 21.0411 22.8081C21.0411 22.2558 20.5934 21.8081 20.0411 21.8081H8.29675ZM7.29675 18.8931C7.29675 19.4454 7.74447 19.8931 8.29675 19.8931H20.0411C20.5934 19.8931 21.0411 19.4454 21.0411 18.8931C21.0411 18.3408 20.5934 17.8931 20.0411 17.8931H8.29675C7.74447 17.8931 7.29675 18.3408 7.29675 18.8931Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Cex.svg b/assets/icons/polkadot/solid/Cex.svg
new file mode 100644
index 00000000..d5d6658e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Cex.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14.0019 0.75C11.9198 0.75 10.2323 2.43824 10.2323 4.52028C10.2323 6.25585 11.4049 7.71778 13.0012 8.15627V9.827C11.4827 10.1383 10.2177 11.145 9.55313 12.4997L8.53206 12.1414C8.53679 12.0641 8.53919 11.9862 8.53919 11.9076C8.53919 9.82561 6.85172 8.13736 4.7696 8.13736C2.68747 8.13736 1 9.82561 1 11.9076C1 13.9897 2.68747 15.6779 4.7696 15.6779C6.0632 15.6779 7.20447 15.0262 7.88336 14.0333L9.05498 14.4444C9.05138 14.5219 9.04956 14.5998 9.04956 14.6781C9.04956 15.8857 9.48173 16.9924 10.1999 17.8518L8.66113 19.3905C8.28795 19.2668 7.8889 19.1998 7.47419 19.1998C5.39207 19.1998 3.70459 20.888 3.70459 22.9701C3.70459 25.0521 5.39207 26.7403 7.47419 26.7403C9.55631 26.7403 11.2438 25.0521 11.2438 22.9701C11.2438 22.0401 10.9071 21.1886 10.3489 20.5311L11.7765 19.1036C12.4452 19.4404 13.2008 19.6301 14.0006 19.6301C14.7808 19.6301 15.5188 19.4497 16.1752 19.1282L17.5838 20.5367C17.0236 21.1948 16.6855 22.0478 16.6855 22.9797C16.6855 25.0618 18.373 26.75 20.4551 26.75C22.5372 26.75 24.2247 25.0618 24.2247 22.9797C24.2247 20.8977 22.5372 19.2094 20.4551 19.2094C20.0425 19.2094 19.6454 19.2757 19.2738 19.3983L17.7675 17.892C18.5059 17.027 18.9517 15.9046 18.9517 14.6781C18.9517 14.5954 18.9497 14.5132 18.9457 14.4315L20.1164 14.0288C20.7949 15.0243 21.9377 15.6779 23.2332 15.6779C25.3154 15.6779 27.0028 13.9897 27.0028 11.9076C27.0028 9.82561 25.3154 8.13736 23.2332 8.13736C21.1511 8.13736 19.4636 9.82561 19.4636 11.9076C19.4636 11.9843 19.4659 12.0605 19.4704 12.136L18.4431 12.4894C17.7774 11.1402 16.5154 10.1381 15.0012 9.82725V8.15665C16.5982 7.71862 17.7715 6.25635 17.7715 4.52028C17.7715 2.43824 16.084 0.75 14.0019 0.75Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Chain Spec.svg b/assets/icons/polkadot/solid/Chain Spec.svg
new file mode 100644
index 00000000..2a11e309
--- /dev/null
+++ b/assets/icons/polkadot/solid/Chain Spec.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M19.536 1.29289L26.1588 7.91569C26.5493 8.30621 26.5493 8.93938 26.1588 9.3299L19.5054 15.9833C19.1148 16.3739 18.4817 16.3739 18.0911 15.9833L15.4653 13.3575L13.3471 15.4757L11.9329 14.0615L14.0513 11.9432L15.4654 13.3573L18.7012 10.1215C19.0917 9.73099 19.0917 9.09783 18.7012 8.7073C18.3106 8.31678 17.6775 8.31678 17.2869 8.7073L14.051 11.9432L11.4683 9.36054C11.0778 8.97002 11.0778 8.33685 11.4683 7.94633L18.1218 1.29289C18.5123 0.902369 19.1455 0.902369 19.536 1.29289ZM8.71307 17.2812L11.9321 14.0621L9.32308 11.453C8.93256 11.0625 8.2994 11.0625 7.90887 11.453L1.29288 18.069C0.902353 18.4596 0.902354 19.0927 1.29288 19.4833L7.91568 26.1061C8.3062 26.4966 8.93936 26.4966 9.32989 26.1061L15.9459 19.4901C16.3364 19.0995 16.3364 18.4664 15.9459 18.0758L13.3464 15.4763L10.1273 18.6954C9.73676 19.0859 9.1036 19.0859 8.71307 18.6954C8.32255 18.3049 8.32255 17.6717 8.71307 17.2812Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Check.svg b/assets/icons/polkadot/solid/Check.svg
new file mode 100644
index 00000000..41064270
--- /dev/null
+++ b/assets/icons/polkadot/solid/Check.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M25.7129 6.29877C26.1002 6.69251 26.095 7.32566 25.7012 7.71293L11.4676 21.7129C11.0894 22.0849 10.4866 22.0969 10.094 21.7402L2.32766 14.6862C1.91884 14.3148 1.88844 13.6824 2.25977 13.2736C2.6311 12.8647 3.26353 12.8344 3.67236 13.2057L10.739 19.6242L24.2988 6.28707C24.6925 5.89979 25.3257 5.90503 25.7129 6.29877Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Checked.svg b/assets/icons/polkadot/solid/Checked.svg
new file mode 100644
index 00000000..70e6b6f8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Checked.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M1 2C1 1.44772 1.44772 1 2 1H26C26.5523 1 27 1.44772 27 2V26C27 26.5523 26.5523 27 26 27H2C1.44772 27 1 26.5523 1 26V2ZM19.9316 11.7031C20.3199 11.3103 20.3163 10.6772 19.9236 10.2889C19.5308 9.90059 18.8977 9.90419 18.5094 10.2969L12.58 16.2941L9.68222 13.5876C9.27861 13.2106 8.64581 13.2322 8.26883 13.6358C7.89185 14.0394 7.91344 14.6722 8.31705 15.0492L11.9252 18.4192C12.3207 18.7886 12.9384 18.7764 13.3189 18.3915L19.9316 11.7031Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Chevron Down.svg b/assets/icons/polkadot/solid/Chevron Down.svg
new file mode 100644
index 00000000..665f63c6
--- /dev/null
+++ b/assets/icons/polkadot/solid/Chevron Down.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M26.6346 7.79945C27.056 8.15641 27.1083 8.78741 26.7513 9.20884L15.7403 22.2088C15.5502 22.4333 15.2709 22.5627 14.9767 22.5625C14.6826 22.5624 14.4034 22.4327 14.2135 22.2081L3.22455 9.20808C2.86802 8.7863 2.92091 8.15535 3.3427 7.79881C3.76448 7.44228 4.39543 7.49517 4.75197 7.91696L14.978 20.0144L25.2252 7.9162C25.5821 7.49477 26.2131 7.4425 26.6346 7.79945Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Chevron Up.svg b/assets/icons/polkadot/solid/Chevron Up.svg
new file mode 100644
index 00000000..695aa064
--- /dev/null
+++ b/assets/icons/polkadot/solid/Chevron Up.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M2.3537 21.8939C1.93227 21.537 1.88 20.9059 2.23695 20.4845L13.248 7.48452C13.4381 7.26006 13.7174 7.13069 14.0115 7.13084C14.3057 7.13098 14.5849 7.26063 14.7748 7.48527L25.7637 20.4853C26.1203 20.9071 26.0674 21.538 25.6456 21.8945C25.2238 22.2511 24.5928 22.1982 24.2363 21.7764L14.0103 9.67896L3.76309 21.7772C3.40614 22.1986 2.77513 22.2509 2.3537 21.8939Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Claim.svg b/assets/icons/polkadot/solid/Claim.svg
new file mode 100644
index 00000000..4c332126
--- /dev/null
+++ b/assets/icons/polkadot/solid/Claim.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M5 1H16V8.46155C16 9.01384 16.4477 9.46155 17 9.46155H24.4615V26C24.4615 26.5523 24.0138 27 23.4615 27H5C4.44772 27 4 26.5523 4 26V2C4 1.44772 4.44772 1 5 1ZM18 7.46155H23.8758L18 1.58579V7.46155ZM15.2065 11.4595C15.2065 10.9072 14.7588 10.4595 14.2065 10.4595C13.6542 10.4595 13.2065 10.9072 13.2065 11.4595V11.8118C13.0028 11.8441 12.8031 11.8999 12.6113 11.9781C12.2822 12.1125 11.9829 12.3106 11.7306 12.5611C11.4784 12.8116 11.2782 13.1095 11.1416 13.4377C11.005 13.7659 10.9346 14.1179 10.9346 14.4734L10.9347 14.4803C10.9396 15.195 11.227 15.8787 11.7341 16.3823C12.2411 16.8859 12.9268 17.1685 13.6415 17.1685H14.8186C15.0052 17.1685 15.1843 17.2423 15.3167 17.3738C15.4491 17.5053 15.5242 17.6838 15.5254 17.8704C15.5255 17.882 15.5258 17.8937 15.5263 17.9053C15.5303 18.0022 15.5144 18.0989 15.4795 18.1894C15.4445 18.2799 15.3913 18.3622 15.3232 18.4313C15.2551 18.5003 15.1735 18.5546 15.0835 18.5908C14.9934 18.6269 14.8969 18.6441 14.8 18.6414C14.7905 18.6411 14.781 18.641 14.7715 18.641H12.2996C11.7473 18.641 11.2996 19.0887 11.2996 19.641C11.2996 20.1933 11.7473 20.641 12.2996 20.641H13.2065V20.9712C13.2065 21.5235 13.6542 21.9712 14.2065 21.9712C14.7588 21.9712 15.2065 21.5235 15.2065 20.9712V20.6139C15.4192 20.5833 15.6281 20.5273 15.8286 20.4468C16.1734 20.3083 16.4859 20.1005 16.7468 19.836C17.0077 19.5716 17.2114 19.2564 17.3452 18.9098C17.4769 18.5687 17.5381 18.2045 17.5252 17.8392C17.5158 17.1308 17.229 16.4542 16.726 15.9547C16.2189 15.4511 15.5332 15.1685 14.8186 15.1685H13.6415C13.4548 15.1685 13.2758 15.0947 13.1434 14.9632C13.0118 14.8325 12.9368 14.6553 12.9347 14.47C12.9351 14.3795 12.9532 14.2899 12.988 14.2063C13.0233 14.1216 13.0749 14.0448 13.1399 13.9802C13.205 13.9156 13.2822 13.8645 13.3671 13.8299C13.452 13.7952 13.5429 13.7777 13.6345 13.7784H15.9251C16.4774 13.7784 16.9251 13.3306 16.9251 12.7784C16.9251 12.2261 16.4774 11.7784 15.9251 11.7784H15.2065V11.4595Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Close.svg b/assets/icons/polkadot/solid/Close.svg
new file mode 100644
index 00000000..f908ffaf
--- /dev/null
+++ b/assets/icons/polkadot/solid/Close.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Cloud.svg b/assets/icons/polkadot/solid/Cloud.svg
new file mode 100644
index 00000000..4bf65ae2
--- /dev/null
+++ b/assets/icons/polkadot/solid/Cloud.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Code.svg b/assets/icons/polkadot/solid/Code.svg
new file mode 100644
index 00000000..44eac3dd
--- /dev/null
+++ b/assets/icons/polkadot/solid/Code.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Collapse.svg b/assets/icons/polkadot/solid/Collapse.svg
new file mode 100644
index 00000000..f225431a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Collapse.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Collators.svg b/assets/icons/polkadot/solid/Collators.svg
new file mode 100644
index 00000000..d471f754
--- /dev/null
+++ b/assets/icons/polkadot/solid/Collators.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Collective.svg b/assets/icons/polkadot/solid/Collective.svg
new file mode 100644
index 00000000..9292c995
--- /dev/null
+++ b/assets/icons/polkadot/solid/Collective.svg
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diff --git a/assets/icons/polkadot/solid/Communications And Media.svg b/assets/icons/polkadot/solid/Communications And Media.svg
new file mode 100644
index 00000000..1430f2d8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Communications And Media.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Community Events And Outreach.svg b/assets/icons/polkadot/solid/Community Events And Outreach.svg
new file mode 100644
index 00000000..96187925
--- /dev/null
+++ b/assets/icons/polkadot/solid/Community Events And Outreach.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Community.svg b/assets/icons/polkadot/solid/Community.svg
new file mode 100644
index 00000000..3a655499
--- /dev/null
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diff --git a/assets/icons/polkadot/solid/Companion Account (in Bridge context).svg b/assets/icons/polkadot/solid/Companion Account (in Bridge context).svg
new file mode 100644
index 00000000..00533485
--- /dev/null
+++ b/assets/icons/polkadot/solid/Companion Account (in Bridge context).svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Connect Wallet_Address.svg b/assets/icons/polkadot/solid/Connect Wallet_Address.svg
new file mode 100644
index 00000000..3cd6f674
--- /dev/null
+++ b/assets/icons/polkadot/solid/Connect Wallet_Address.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Connected.svg b/assets/icons/polkadot/solid/Connected.svg
new file mode 100644
index 00000000..68175aac
--- /dev/null
+++ b/assets/icons/polkadot/solid/Connected.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Connection Via Light Node.svg b/assets/icons/polkadot/solid/Connection Via Light Node.svg
new file mode 100644
index 00000000..dc21b069
--- /dev/null
+++ b/assets/icons/polkadot/solid/Connection Via Light Node.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Connection Via Remote Node.svg b/assets/icons/polkadot/solid/Connection Via Remote Node.svg
new file mode 100644
index 00000000..da4e1c18
--- /dev/null
+++ b/assets/icons/polkadot/solid/Connection Via Remote Node.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Consensus.svg b/assets/icons/polkadot/solid/Consensus.svg
new file mode 100644
index 00000000..02ce5ecc
--- /dev/null
+++ b/assets/icons/polkadot/solid/Consensus.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Contract.svg b/assets/icons/polkadot/solid/Contract.svg
new file mode 100644
index 00000000..0d98d07b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Contract.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Cooling Period.svg b/assets/icons/polkadot/solid/Cooling Period.svg
new file mode 100644
index 00000000..a788db3f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Cooling Period.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Copy _ Paste.svg b/assets/icons/polkadot/solid/Copy _ Paste.svg
new file mode 100644
index 00000000..c901e801
--- /dev/null
+++ b/assets/icons/polkadot/solid/Copy _ Paste.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Costly To Maintain.svg b/assets/icons/polkadot/solid/Costly To Maintain.svg
new file mode 100644
index 00000000..f7041e9f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Costly To Maintain.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Council.svg b/assets/icons/polkadot/solid/Council.svg
new file mode 100644
index 00000000..4a643df7
--- /dev/null
+++ b/assets/icons/polkadot/solid/Council.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path d="M19.6501 14.6921H23.9518C23.8887 12.3445 22.3113 10.3001 20.0372 9.6682L19.1896 9.43278C18.5879 9.26516 18.3591 8.53252 18.7583 8.05226L19.3836 7.29985C20.4515 6.01632 20.3658 4.13011 19.1859 2.94923C17.9231 1.68359 15.873 1.68359 14.6102 2.94923C13.4302 4.13105 13.3455 6.01632 14.4124 7.29985L15.0377 8.05226C15.437 8.53252 15.2082 9.26516 14.6064 9.43278L13.7608 9.6682C12.4735 10.026 11.4207 10.8463 10.7266 11.9075C10.7426 12.2607 10.9724 12.595 11.3547 12.7014L12.2004 12.9368C14.21 13.4962 15.6781 15.1583 16.035 17.1575H19.6482L19.6501 14.6921Z"></path><path d="M10.9254 11.3208L11.5506 10.5684C12.6185 9.28487 12.5328 7.39866 11.3529 6.21778C10.0901 4.95215 8.04002 4.95215 6.77721 6.21778C5.59727 7.39961 5.51251 9.28487 6.57945 10.5684L7.20474 11.3208C7.60401 11.8011 7.37518 12.5337 6.77344 12.7013L5.92592 12.9368C3.60559 13.5818 2 15.695 2 18.1038V20.427H16.1235V18.1001C16.1235 15.694 14.5198 13.5828 12.2014 12.9368L11.3557 12.7013C10.754 12.5337 10.5251 11.8011 10.9244 11.3208H10.9254Z"></path><path d="M26 25.1951V14.6924H19.6511V25.2007L22.8246 23.9087L26 25.1951Z"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Countdown.svg b/assets/icons/polkadot/solid/Countdown.svg
new file mode 100644
index 00000000..aeea2293
--- /dev/null
+++ b/assets/icons/polkadot/solid/Countdown.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Create New From Source.svg b/assets/icons/polkadot/solid/Create New From Source.svg
new file mode 100644
index 00000000..7e8f1838
--- /dev/null
+++ b/assets/icons/polkadot/solid/Create New From Source.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Cross-Chain Application.svg b/assets/icons/polkadot/solid/Cross-Chain Application.svg
new file mode 100644
index 00000000..aef4cf0c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Cross-Chain Application.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Cross-Chain Certification.svg b/assets/icons/polkadot/solid/Cross-Chain Certification.svg
new file mode 100644
index 00000000..62bcd3d3
--- /dev/null
+++ b/assets/icons/polkadot/solid/Cross-Chain Certification.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Cross-Chain Transfers.svg b/assets/icons/polkadot/solid/Cross-Chain Transfers.svg
new file mode 100644
index 00000000..8c3e8206
--- /dev/null
+++ b/assets/icons/polkadot/solid/Cross-Chain Transfers.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Cross-Chain.svg b/assets/icons/polkadot/solid/Cross-Chain.svg
new file mode 100644
index 00000000..49df5f9c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Cross-Chain.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Crowdloans.svg b/assets/icons/polkadot/solid/Crowdloans.svg
new file mode 100644
index 00000000..a4d6c856
--- /dev/null
+++ b/assets/icons/polkadot/solid/Crowdloans.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Cryptocurrency.svg b/assets/icons/polkadot/solid/Cryptocurrency.svg
new file mode 100644
index 00000000..f76dc93c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Cryptocurrency.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Customisation.svg b/assets/icons/polkadot/solid/Customisation.svg
new file mode 100644
index 00000000..c7dd2051
--- /dev/null
+++ b/assets/icons/polkadot/solid/Customisation.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/DAOs.svg b/assets/icons/polkadot/solid/DAOs.svg
new file mode 100644
index 00000000..1991860f
--- /dev/null
+++ b/assets/icons/polkadot/solid/DAOs.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/DEX.svg b/assets/icons/polkadot/solid/DEX.svg
new file mode 100644
index 00000000..bf16b733
--- /dev/null
+++ b/assets/icons/polkadot/solid/DEX.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Dapps.svg b/assets/icons/polkadot/solid/Dapps.svg
new file mode 100644
index 00000000..de79a172
--- /dev/null
+++ b/assets/icons/polkadot/solid/Dapps.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Data & Analytics.svg b/assets/icons/polkadot/solid/Data & Analytics.svg
new file mode 100644
index 00000000..64fe522b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Data & Analytics.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Day_Light Mode.svg b/assets/icons/polkadot/solid/Day_Light Mode.svg
new file mode 100644
index 00000000..a9e6819f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Day_Light Mode.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/DeFi.svg b/assets/icons/polkadot/solid/DeFi.svg
new file mode 100644
index 00000000..8c8a9b8c
--- /dev/null
+++ b/assets/icons/polkadot/solid/DeFi.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Decentralised File Storage.svg b/assets/icons/polkadot/solid/Decentralised File Storage.svg
new file mode 100644
index 00000000..cfa2e8df
--- /dev/null
+++ b/assets/icons/polkadot/solid/Decentralised File Storage.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Delete_Cancel.svg b/assets/icons/polkadot/solid/Delete_Cancel.svg
new file mode 100644
index 00000000..2590b4ac
--- /dev/null
+++ b/assets/icons/polkadot/solid/Delete_Cancel.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Democracy.svg b/assets/icons/polkadot/solid/Democracy.svg
new file mode 100644
index 00000000..d560961f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Democracy.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Deposit.svg b/assets/icons/polkadot/solid/Deposit.svg
new file mode 100644
index 00000000..97cebe83
--- /dev/null
+++ b/assets/icons/polkadot/solid/Deposit.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M20.7234 16.6282C21.114 16.2378 21.1142 15.6047 20.7238 15.214C20.3333 14.8234 19.7002 14.8233 19.3095 15.2137L15.4865 19.0348V2C15.4865 1.44772 15.0388 1 14.4865 1C13.9342 1 13.4865 1.44772 13.4865 2V19.0369L9.65823 15.215C9.26738 14.8248 8.63422 14.8253 8.24402 15.2162C7.85383 15.607 7.85436 16.2402 8.24521 16.6304L13.78 22.1559C14.1705 22.5458 14.8031 22.5456 15.1934 22.1555L20.7234 16.6282ZM22.706 25H6C5.44772 25 5 25.4477 5 26C5 26.5523 5.44772 27 6 27H22.706C23.2583 27 23.706 26.5523 23.706 26C23.706 25.4477 23.2583 25 22.706 25Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Derivation Path.svg b/assets/icons/polkadot/solid/Derivation Path.svg
new file mode 100644
index 00000000..3d368c67
--- /dev/null
+++ b/assets/icons/polkadot/solid/Derivation Path.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M18.7458 5.72424C18.7458 3.11512 16.6307 1 14.0215 1C11.4124 1 9.29729 3.11512 9.29729 5.72424C9.29729 7.99024 10.8927 9.88362 13.0215 10.3424V13.3726H5.57671C5.02443 13.3726 4.57671 13.8203 4.57671 14.3726L4.57671 17.7937C2.52212 18.3063 1 20.1642 1 22.3776C1 24.9867 3.11512 27.1018 5.72424 27.1018C8.33337 27.1018 10.4485 24.9867 10.4485 22.3776C10.4485 20.0595 8.77894 18.1314 6.57672 17.73V15.3726L21.2757 15.3726V17.7594C19.1469 18.2182 17.5515 20.1116 17.5515 22.3776C17.5515 24.9867 19.6666 27.1018 22.2758 27.1018C24.8849 27.1018 27 24.9867 27 22.3776C27 20.1115 25.4046 18.2181 23.2757 17.7594V14.3726C23.2757 13.8203 22.828 13.3726 22.2757 13.3726H15.0215V10.3425C17.1503 9.88369 18.7458 7.99028 18.7458 5.72424Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Derive An Address.svg b/assets/icons/polkadot/solid/Derive An Address.svg
new file mode 100644
index 00000000..c41605bd
--- /dev/null
+++ b/assets/icons/polkadot/solid/Derive An Address.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Derive Key Pair.svg b/assets/icons/polkadot/solid/Derive Key Pair.svg
new file mode 100644
index 00000000..fb238c57
--- /dev/null
+++ b/assets/icons/polkadot/solid/Derive Key Pair.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Disconnected.svg b/assets/icons/polkadot/solid/Disconnected.svg
new file mode 100644
index 00000000..38ead071
--- /dev/null
+++ b/assets/icons/polkadot/solid/Disconnected.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M25.7369 25.3243C26.1101 25.7314 26.0826 26.364 25.6755 26.7371C25.2684 27.1103 24.6358 27.0828 24.2626 26.6757L17.6822 19.4971H16.4965C15.9442 19.4971 15.4965 19.0494 15.4965 18.4971C15.4965 18.1337 15.6904 17.8156 15.9803 17.6405L13.3182 14.7363H7.86176C7.30947 14.7363 6.86176 14.2886 6.86176 13.7363C6.86176 13.184 7.30947 12.7363 7.86176 12.7363H11.4848L8.97645 9.99991H6.72972C4.66981 9.99991 2.99992 11.6698 2.99992 13.7297C2.99992 15.7896 4.66981 17.4595 6.72972 17.4595H11.4498C12.0021 17.4595 12.4498 17.9072 12.4498 18.4595C12.4498 19.0118 12.0021 19.4595 11.4498 19.4595H6.72972C3.56524 19.4595 0.999923 16.8942 0.999923 13.7297C0.999923 10.5652 3.56524 7.99991 6.72972 7.99991H7.14312L2.26261 2.67572C1.88942 2.2686 1.91692 1.63603 2.32404 1.26284C2.73116 0.889647 3.36372 0.91715 3.73692 1.32427L9.85625 7.99991H11.4498C12.0021 7.99991 12.4498 8.44762 12.4498 8.99991C12.4498 9.47734 12.1152 9.87662 11.6678 9.97609L14.198 12.7363H20.1081C20.6604 12.7363 21.1081 13.184 21.1081 13.7363C21.1081 14.2886 20.6604 14.7363 20.1081 14.7363H16.0313L18.562 17.4971H21.2701C23.33 17.4971 24.9999 15.8272 24.9999 13.7673C24.9999 11.7074 23.33 10.0375 21.2701 10.0375H16.4965C15.9442 10.0375 15.4965 9.58976 15.4965 9.03748C15.4965 8.48519 15.9442 8.03748 16.4965 8.03748H21.2701C24.4346 8.03748 26.9999 10.6028 26.9999 13.7673C26.9999 16.9318 24.4346 19.4971 21.2701 19.4971H20.3953L25.7369 25.3243Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Distributed File Storage.svg b/assets/icons/polkadot/solid/Distributed File Storage.svg
new file mode 100644
index 00000000..bba294ad
--- /dev/null
+++ b/assets/icons/polkadot/solid/Distributed File Storage.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M2.98242 4C2.43014 4 1.98242 4.44772 1.98242 5V23C1.98242 23.5523 2.43014 24 2.98242 24H26.9824C27.5347 24 27.9824 23.5523 27.9824 23V7.76827C27.9824 7.21599 27.5347 6.76827 26.9824 6.76827H15.7266L12.7331 4.23647C12.5526 4.08378 12.3238 4 12.0874 4H2.98242Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Documentations.svg b/assets/icons/polkadot/solid/Documentations.svg
new file mode 100644
index 00000000..a4833b19
--- /dev/null
+++ b/assets/icons/polkadot/solid/Documentations.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M20.4313 1.29289C20.2438 1.10536 19.9894 1 19.7242 1H9.22418C8.6719 1 8.22418 1.44772 8.22418 2V4H2.99994C2.44765 4 1.99994 4.44772 1.99994 5V26C1.99994 26.5523 2.44765 27 2.99994 27H19.1538C19.7061 27 20.1538 26.5523 20.1538 26V24H25.378C25.9303 24 26.378 23.5523 26.378 23V7.65385C26.378 7.38863 26.2727 7.13428 26.0851 6.94674L20.4313 1.29289ZM20.1538 22H24.378V8.65386H19.7242C19.1719 8.65386 18.7242 8.20614 18.7242 7.65386V3H10.2242V4H12.5V10.6538C12.5 11.2061 12.9477 11.6538 13.5 11.6538H20C20.0523 11.6538 20.1037 11.6498 20.1538 11.6421V22ZM20.7242 6.65386V4.41422L22.9638 6.65386H20.7242ZM14.5 4.58581L19.568 9.65384H14.5V4.58581ZM5.13055 17.9624C5.13055 18.5147 5.57827 18.9624 6.13055 18.9624H15.8128C16.3651 18.9624 16.8128 18.5147 16.8128 17.9624C16.8128 17.4101 16.3651 16.9624 15.8128 16.9624H6.13055C5.57827 16.9624 5.13055 17.4101 5.13055 17.9624ZM5.13055 21.1899C5.13055 20.6377 5.57827 20.1899 6.13055 20.1899H15.8128C16.3651 20.1899 16.8128 20.6377 16.8128 21.1899C16.8128 21.7422 16.3651 22.1899 15.8128 22.1899H6.13055C5.57827 22.1899 5.13055 21.7422 5.13055 21.1899Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Download.svg b/assets/icons/polkadot/solid/Download.svg
new file mode 100644
index 00000000..dc2f7b4b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Download.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M20.7234 16.6282C21.114 16.2378 21.1142 15.6047 20.7238 15.214C20.3333 14.8234 19.7002 14.8233 19.3095 15.2137L15.4865 19.0348V2C15.4865 1.44772 15.0388 1 14.4865 1C13.9342 1 13.4865 1.44772 13.4865 2V19.0369L9.65823 15.215C9.26738 14.8248 8.63422 14.8253 8.24402 15.2162C7.85383 15.607 7.85436 16.2402 8.24521 16.6304L13.78 22.1559C14.1705 22.5458 14.8031 22.5456 15.1934 22.1555L20.7234 16.6282ZM7 23.5C7 22.9477 6.55228 22.5 6 22.5C5.44772 22.5 5 22.9477 5 23.5V26C5 26.2652 5.10536 26.5196 5.29289 26.7071C5.48043 26.8946 5.73478 27 6 27H22.706C23.2583 27 23.706 26.5523 23.706 26V23.5C23.706 22.9477 23.2583 22.5 22.706 22.5C22.1537 22.5 21.706 22.9477 21.706 23.5V25H7V23.5Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Draw.svg b/assets/icons/polkadot/solid/Draw.svg
new file mode 100644
index 00000000..e571b4e8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Draw.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M18.1453 2.69745C18.4657 2.36818 18.5205 1.86298 18.2782 1.47267C18.0359 1.08236 17.5588 0.907349 17.1216 1.04839L3.83588 5.3341C3.31027 5.50366 3.02162 6.0672 3.19117 6.59281C3.36073 7.11843 3.92427 7.40707 4.44989 7.23752L13.9051 4.18744L1.2833 17.1599C0.996184 17.455 0.919276 17.8959 1.08953 18.2708C1.25978 18.6456 1.64239 18.8778 2.05352 18.8558L5.28848 18.6825L3.85323 24.655C3.77192 24.9934 3.87237 25.3497 4.11844 25.5957C4.36452 25.8418 4.72083 25.9423 5.05921 25.861L11.3696 24.3445C11.5488 24.3014 11.7127 24.2097 11.843 24.0793L17.9163 18.006L23.1826 17.7239L18.0527 22.2503C17.6386 22.6157 17.5991 23.2476 17.9645 23.6617C18.3299 24.0758 18.9618 24.1153 19.3759 23.7499L26.6616 17.3214C26.9808 17.0397 27.0867 16.5869 26.9256 16.193C26.7645 15.799 26.3716 15.5502 25.9465 15.573L20.0326 15.8898L20.254 15.6683L14.0459 9.46014L6.91346 16.5926L4.49993 16.7219L18.1453 2.69745ZM15.4601 8.04593L21.6683 14.2541L24.366 11.5564C24.7565 11.1658 24.7565 10.5327 24.366 10.1422L19.572 5.34822C19.1815 4.9577 18.5483 4.9577 18.1578 5.34822L15.4601 8.04593Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Drip.svg b/assets/icons/polkadot/solid/Drip.svg
new file mode 100644
index 00000000..5b1181ec
--- /dev/null
+++ b/assets/icons/polkadot/solid/Drip.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14 3L14.8009 2.40124C14.6121 2.14871 14.3153 2 14 2C13.6847 2 13.3879 2.14871 13.1991 2.40124C13.1992 2.40106 13.1991 2.40124 14 3ZM14 3L13.1991 2.40124L13.1927 2.40984L13.1763 2.43191L13.1149 2.51523C13.0617 2.58778 12.9845 2.69386 12.8867 2.83022C12.6911 3.1029 12.4129 3.49699 12.0796 3.9866C11.4137 4.96484 10.5246 6.32927 9.63399 7.87175C8.74493 9.41154 7.84468 11.1454 7.16423 12.8605C6.49003 14.5598 6 16.3178 6 17.8836C6 20.8204 6.80098 23.1207 8.27024 24.6943C9.74514 26.2738 11.7809 27 14 27C16.2191 27 18.2549 26.2738 19.7298 24.6943C21.199 23.1207 22 20.8204 22 17.8836C22 16.3178 21.51 14.5598 20.8358 12.8605C20.1553 11.1454 19.2551 9.41154 18.366 7.87175C17.4754 6.32927 16.5863 4.96484 15.9204 3.9866C15.5871 3.49699 15.3089 3.1029 15.1133 2.83022C15.0155 2.69386 14.9383 2.58778 14.8851 2.51523L14.8237 2.43191L14.8073 2.40984L14.8016 2.40211C14.8014 2.40193 14.8009 2.40124 14 3Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Dropdown Up.svg b/assets/icons/polkadot/solid/Dropdown Up.svg
new file mode 100644
index 00000000..81b52756
--- /dev/null
+++ b/assets/icons/polkadot/solid/Dropdown Up.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Dropdown.svg b/assets/icons/polkadot/solid/Dropdown.svg
new file mode 100644
index 00000000..8577c38b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Dropdown.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M13.2652 20.5949C13.4545 20.8 13.7209 20.9167 14 20.9167C14.2791 20.9167 14.5455 20.8 14.7348 20.5949L25.7348 8.67828C26.0042 8.38642 26.0753 7.96278 25.916 7.59893C25.7567 7.23508 25.3972 7 25 7H2.99996C2.60276 7 2.24322 7.23508 2.08391 7.59893C1.92461 7.96278 1.99575 8.38642 2.26515 8.67828L13.2652 20.5949Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Ecosystem Provisions.svg b/assets/icons/polkadot/solid/Ecosystem Provisions.svg
new file mode 100644
index 00000000..b789bda5
--- /dev/null
+++ b/assets/icons/polkadot/solid/Ecosystem Provisions.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Ecosystem.svg b/assets/icons/polkadot/solid/Ecosystem.svg
new file mode 100644
index 00000000..61af539e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Ecosystem.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Edit-Off.svg b/assets/icons/polkadot/solid/Edit-Off.svg
new file mode 100644
index 00000000..19aec48c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Edit-Off.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Edit-On.svg b/assets/icons/polkadot/solid/Edit-On.svg
new file mode 100644
index 00000000..0319a725
--- /dev/null
+++ b/assets/icons/polkadot/solid/Edit-On.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Elections.svg b/assets/icons/polkadot/solid/Elections.svg
new file mode 100644
index 00000000..5a05e93a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Elections.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Email.svg b/assets/icons/polkadot/solid/Email.svg
new file mode 100644
index 00000000..32f62697
--- /dev/null
+++ b/assets/icons/polkadot/solid/Email.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Encryption.svg b/assets/icons/polkadot/solid/Encryption.svg
new file mode 100644
index 00000000..fc0b09ce
--- /dev/null
+++ b/assets/icons/polkadot/solid/Encryption.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Ending Period.svg b/assets/icons/polkadot/solid/Ending Period.svg
new file mode 100644
index 00000000..e291b812
--- /dev/null
+++ b/assets/icons/polkadot/solid/Ending Period.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Energy Deficiency.svg b/assets/icons/polkadot/solid/Energy Deficiency.svg
new file mode 100644
index 00000000..96338cca
--- /dev/null
+++ b/assets/icons/polkadot/solid/Energy Deficiency.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Energy Efficiency.svg b/assets/icons/polkadot/solid/Energy Efficiency.svg
new file mode 100644
index 00000000..d6edb6dd
--- /dev/null
+++ b/assets/icons/polkadot/solid/Energy Efficiency.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Energy.svg b/assets/icons/polkadot/solid/Energy.svg
new file mode 100644
index 00000000..e1bb9d18
--- /dev/null
+++ b/assets/icons/polkadot/solid/Energy.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.02344 26.4316C6.47115 26.4316 6.02344 25.9839 6.02344 25.4316V5.30664C6.02344 4.75436 6.47115 4.30664 7.02344 4.30664L9.73844 4.30664V2.43164C9.73844 1.87936 10.1862 1.43164 10.7384 1.43164H17.2913C17.5576 1.43164 17.813 1.53789 18.0007 1.72682C18.1884 1.91576 18.293 2.17177 18.2913 2.4381L18.2792 4.30664L20.9877 4.30664C21.54 4.30664 21.9877 4.75436 21.9877 5.30664L21.9877 25.4316C21.9877 25.9839 21.54 26.4316 20.9877 26.4316H7.02344ZM14.7386 10.0197C14.9049 9.49301 14.6128 8.93125 14.0861 8.76495C13.5595 8.59864 12.9977 8.89075 12.8314 9.4174L11.1306 14.8034C11.0346 15.1072 11.0892 15.4386 11.2776 15.6956C11.466 15.9526 11.7655 16.1045 12.0842 16.1045H14.7366L13.3139 20.1594C13.131 20.6805 13.4053 21.2512 13.9264 21.4341C14.4475 21.6169 15.0182 21.3427 15.2011 20.8216L17.0909 15.4356C17.1982 15.1297 17.1506 14.7907 16.9631 14.5262C16.7756 14.2617 16.4715 14.1045 16.1473 14.1045H13.4486L14.7386 10.0197Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Enterprise.svg b/assets/icons/polkadot/solid/Enterprise.svg
new file mode 100644
index 00000000..e2ad7a85
--- /dev/null
+++ b/assets/icons/polkadot/solid/Enterprise.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Error.svg b/assets/icons/polkadot/solid/Error.svg
new file mode 100644
index 00000000..77612a00
--- /dev/null
+++ b/assets/icons/polkadot/solid/Error.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Eve.svg b/assets/icons/polkadot/solid/Eve.svg
new file mode 100644
index 00000000..f27c17cf
--- /dev/null
+++ b/assets/icons/polkadot/solid/Eve.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Events.svg b/assets/icons/polkadot/solid/Events.svg
new file mode 100644
index 00000000..0cd3740f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Events.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Existential Deposit.svg b/assets/icons/polkadot/solid/Existential Deposit.svg
new file mode 100644
index 00000000..c636eb6e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Existential Deposit.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Export (M,L).svg b/assets/icons/polkadot/solid/Export (M,L).svg
new file mode 100644
index 00000000..e3b0da12
--- /dev/null
+++ b/assets/icons/polkadot/solid/Export (M,L).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M9.43944 5.00533C9.04891 5.39586 9.04891 6.02902 9.43944 6.41955C9.82996 6.81007 10.4631 6.81007 10.8537 6.41955L12.8618 4.41138L12.8618 9.27637H6C5.44772 9.27637 5 9.72408 5 10.2764V26.0001C5 26.5524 5.44771 27.0001 6 27.0001H21.7237C22.276 27.0001 22.7237 26.5524 22.7237 26.0001V10.2764C22.7237 9.72408 22.276 9.27637 21.7237 9.27637H14.8619V17.5825C14.8619 18.1348 14.4142 18.5825 13.8619 18.5825C13.3096 18.5825 12.8619 18.1348 12.8619 17.5825L12.8619 9.26953L14.8618 9.26953L14.8618 4.41418L16.8711 6.42014C17.262 6.81034 17.8952 6.80981 18.2854 6.41896C18.6756 6.0281 18.675 5.39494 18.2842 5.00474L14.5655 1.2923C14.1749 0.902335 13.5422 0.9026 13.1519 1.29289L9.43944 5.00533Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Export (XS,S).svg b/assets/icons/polkadot/solid/Export (XS,S).svg
new file mode 100644
index 00000000..3a51009d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Export (XS,S).svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M9.43932 5.00533C9.04879 5.39586 9.04879 6.02902 9.43932 6.41955C9.82984 6.81007 10.463 6.81007 10.8535 6.41955L12.8617 4.41138L12.8617 14H6C5.44772 14 5 14.4477 5 15L5.00001 26C5.00001 26.5523 5.44772 27 6.00001 27L22 27C22.5523 27 23 26.5523 23 26V15C23 14.4477 22.5523 14 22 14H14.8617L14.8617 18.5825C14.8617 19.1348 14.414 19.5825 13.8617 19.5825C13.3095 19.5825 12.8617 19.1348 12.8617 18.5825L12.8617 14L14.8617 14L14.8617 4.41419L16.871 6.42014C17.2619 6.81034 17.895 6.80981 18.2852 6.41896C18.6754 6.0281 18.6749 5.39494 18.2841 5.00474L14.5654 1.2923C14.1748 0.902335 13.5421 0.9026 13.1518 1.29289L9.43932 5.00533Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Extension.svg b/assets/icons/polkadot/solid/Extension.svg
new file mode 100644
index 00000000..030b0ccd
--- /dev/null
+++ b/assets/icons/polkadot/solid/Extension.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M11.9311 1C10.0076 1 8.44828 2.55922 8.44828 4.48273V5.1379H2C1.44772 5.1379 1 5.58562 1 6.1379V13.5862C1 14.1385 1.44772 14.5862 2 14.5862H3.65517C4.47405 14.5862 5.13794 15.2501 5.13794 16.069C5.13794 16.8879 4.47412 17.5517 3.65517 17.5517H2C1.44772 17.5517 1 17.9994 1 18.5517V26C1 26.5523 1.44772 27 2 27H9.44828C10.0006 27 10.4483 26.5523 10.4483 26V24.3448C10.4483 23.5259 11.1121 22.8621 11.9311 22.8621C12.75 22.8621 13.4138 23.5259 13.4138 24.3448V26C13.4138 26.5523 13.8615 27 14.4138 27H21.8621C22.4144 27 22.8621 26.5523 22.8621 26V18.7241H23.5172C25.4407 18.7241 27 17.1649 27 15.2414C27 13.318 25.4408 11.7586 23.5172 11.7586H22.8621V6.1379C22.8621 5.58562 22.4144 5.1379 21.8621 5.1379H15.4138V4.48273C15.4138 2.55925 13.8545 1 11.9311 1Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Favorite To-Be.svg b/assets/icons/polkadot/solid/Favorite To-Be.svg
new file mode 100644
index 00000000..1148e01d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Favorite To-Be.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Favorite.svg b/assets/icons/polkadot/solid/Favorite.svg
new file mode 100644
index 00000000..f524f17a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Favorite.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Feeless.svg b/assets/icons/polkadot/solid/Feeless.svg
new file mode 100644
index 00000000..0e04f290
--- /dev/null
+++ b/assets/icons/polkadot/solid/Feeless.svg
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diff --git a/assets/icons/polkadot/solid/Fees.svg b/assets/icons/polkadot/solid/Fees.svg
new file mode 100644
index 00000000..087df8a8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Fees.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Fiat.svg b/assets/icons/polkadot/solid/Fiat.svg
new file mode 100644
index 00000000..dcc3b753
--- /dev/null
+++ b/assets/icons/polkadot/solid/Fiat.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Filter.svg b/assets/icons/polkadot/solid/Filter.svg
new file mode 100644
index 00000000..66b83013
--- /dev/null
+++ b/assets/icons/polkadot/solid/Filter.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Finances.svg b/assets/icons/polkadot/solid/Finances.svg
new file mode 100644
index 00000000..c6eb45f0
--- /dev/null
+++ b/assets/icons/polkadot/solid/Finances.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Fork.svg b/assets/icons/polkadot/solid/Fork.svg
new file mode 100644
index 00000000..a30adc78
--- /dev/null
+++ b/assets/icons/polkadot/solid/Fork.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/ForklessUpgrades.svg b/assets/icons/polkadot/solid/ForklessUpgrades.svg
new file mode 100644
index 00000000..e45e0d08
--- /dev/null
+++ b/assets/icons/polkadot/solid/ForklessUpgrades.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Full Node.svg b/assets/icons/polkadot/solid/Full Node.svg
new file mode 100644
index 00000000..fe02c8b8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Full Node.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Fund Account.svg b/assets/icons/polkadot/solid/Fund Account.svg
new file mode 100644
index 00000000..af3459ac
--- /dev/null
+++ b/assets/icons/polkadot/solid/Fund Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14.4351 2.17645C14.7782 1.94015 15.2318 1.94128 15.5737 2.17928L27.5715 10.5314C27.8401 10.7183 28.0002 11.0249 28.0002 11.3521V11.4411C28.0002 11.9934 27.5525 12.4411 27.0002 12.4411H24.3994V25.749H26.9834C27.5357 25.749 27.9834 26.1967 27.9834 26.749C27.9834 27.3013 27.5357 27.749 26.9834 27.749L3 27.749C2.44772 27.749 2 27.3013 2 26.749C2 26.1967 2.44772 25.749 3 25.749H5.59839L5.59839 12.4411H3.01672C2.46444 12.4411 2.01672 11.9934 2.01672 11.4411V11.2555C2.01672 10.9265 2.17854 10.6186 2.44948 10.4319L14.4351 2.17645ZM7.59839 12.4411H22.3994V25.749H22.1533C22.0249 23.353 20.3814 21.2882 18.0487 20.6395L17.7032 20.5433L17.9863 20.2029C19.2361 18.7007 19.1361 16.4937 17.7555 15.1104C16.2777 13.6299 13.8778 13.6299 12.4 15.1104C11.0194 16.4937 10.9197 18.701 12.1694 20.2032L12.4523 20.5433L12.1096 20.6386C9.77652 21.2876 8.13467 23.3535 8.0079 25.749H7.59839L7.59839 12.4411Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Fund Savings.svg b/assets/icons/polkadot/solid/Fund Savings.svg
new file mode 100644
index 00000000..8b58ad5b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Fund Savings.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Gaming.svg b/assets/icons/polkadot/solid/Gaming.svg
new file mode 100644
index 00000000..4e16f279
--- /dev/null
+++ b/assets/icons/polkadot/solid/Gaming.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Genesis.svg b/assets/icons/polkadot/solid/Genesis.svg
new file mode 100644
index 00000000..69cc474e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Genesis.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Gift.svg b/assets/icons/polkadot/solid/Gift.svg
new file mode 100644
index 00000000..b30b1d50
--- /dev/null
+++ b/assets/icons/polkadot/solid/Gift.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Glossary.svg b/assets/icons/polkadot/solid/Glossary.svg
new file mode 100644
index 00000000..30ffdc7d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Glossary.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Go.svg b/assets/icons/polkadot/solid/Go.svg
new file mode 100644
index 00000000..8390d272
--- /dev/null
+++ b/assets/icons/polkadot/solid/Go.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Governance.svg b/assets/icons/polkadot/solid/Governance.svg
new file mode 100644
index 00000000..d5a61667
--- /dev/null
+++ b/assets/icons/polkadot/solid/Governance.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14.0001 1C12.4041 1 11.1103 2.29379 11.1103 3.88976C11.1103 5.48573 12.4041 6.77952 14.0001 6.77952C15.596 6.77952 16.8898 5.48573 16.8898 3.88976C16.8898 2.29379 15.596 1 14.0001 1ZM14.0001 9.56738C11.6213 9.56738 9.69299 11.4957 9.69299 13.8745C9.69299 16.2532 11.6213 18.1815 14.0001 18.1815C16.3788 18.1815 18.3072 16.2532 18.3072 13.8745C18.3072 11.4957 16.3788 9.56738 14.0001 9.56738ZM14.0001 21.2202C12.4041 21.2202 11.1103 22.514 11.1103 24.11C11.1103 25.7059 12.4041 26.9997 14.0001 26.9997C15.596 26.9997 16.8898 25.7059 16.8898 24.11C16.8898 22.514 15.596 21.2202 14.0001 21.2202ZM21.2205 13.9999C21.2205 15.5959 22.5142 16.8896 24.1102 16.8896C25.7062 16.8896 27 15.5959 27 13.9999C27 12.4039 25.7062 11.1101 24.1102 11.1101C22.5142 11.1101 21.2205 12.4039 21.2205 13.9999ZM1 13.9999C1 15.5959 2.29379 16.8896 3.88976 16.8896C5.48573 16.8896 6.77952 15.5959 6.77952 13.9999C6.77952 12.4039 5.48573 11.1101 3.88976 11.1101C2.29379 11.1101 1 12.4039 1 13.9999ZM19.1056 19.1056C17.9771 20.2341 17.9771 22.0638 19.1056 23.1923C20.2341 24.3208 22.0638 24.3208 23.1924 23.1923C24.3209 22.0638 24.3209 20.2341 23.1924 19.1056C22.0638 17.977 20.2341 17.977 19.1056 19.1056ZM4.80771 4.80722C3.67919 5.93574 3.67919 7.76543 4.80771 8.89396C5.93624 10.0225 7.76593 10.0225 8.89445 8.89396C10.023 7.76543 10.023 5.93574 8.89445 4.80722C7.76593 3.67869 5.93624 3.67869 4.80771 4.80722ZM19.1057 8.89413C20.2342 10.0227 22.0639 10.0227 23.1924 8.89413C24.3209 7.76561 24.3209 5.93591 23.1924 4.80739C22.0639 3.67887 20.2342 3.67887 19.1057 4.80739C17.9772 5.93591 17.9772 7.76561 19.1057 8.89413ZM4.8077 23.1925C5.93623 24.321 7.76592 24.321 8.89444 23.1925C10.023 22.0639 10.023 20.2343 8.89444 19.1057C7.76592 17.9772 5.93623 17.9772 4.8077 19.1057C3.67918 20.2343 3.67918 22.0639 4.8077 23.1925Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Governments.svg b/assets/icons/polkadot/solid/Governments.svg
new file mode 100644
index 00000000..57adef7d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Governments.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Hackathon.svg b/assets/icons/polkadot/solid/Hackathon.svg
new file mode 100644
index 00000000..943159ce
--- /dev/null
+++ b/assets/icons/polkadot/solid/Hackathon.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Hash Function.svg b/assets/icons/polkadot/solid/Hash Function.svg
new file mode 100644
index 00000000..20e6a0e0
--- /dev/null
+++ b/assets/icons/polkadot/solid/Hash Function.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Healthcare.svg b/assets/icons/polkadot/solid/Healthcare.svg
new file mode 100644
index 00000000..aed5b11f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Healthcare.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Help.svg b/assets/icons/polkadot/solid/Help.svg
new file mode 100644
index 00000000..1576c9cd
--- /dev/null
+++ b/assets/icons/polkadot/solid/Help.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Heterogeneous Sharding.svg b/assets/icons/polkadot/solid/Heterogeneous Sharding.svg
new file mode 100644
index 00000000..7edb5673
--- /dev/null
+++ b/assets/icons/polkadot/solid/Heterogeneous Sharding.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Identify.svg b/assets/icons/polkadot/solid/Identify.svg
new file mode 100644
index 00000000..98b52005
--- /dev/null
+++ b/assets/icons/polkadot/solid/Identify.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Identity.svg b/assets/icons/polkadot/solid/Identity.svg
new file mode 100644
index 00000000..eafe72bb
--- /dev/null
+++ b/assets/icons/polkadot/solid/Identity.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Import Token.svg b/assets/icons/polkadot/solid/Import Token.svg
new file mode 100644
index 00000000..63ae0fed
--- /dev/null
+++ b/assets/icons/polkadot/solid/Import Token.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M3 14.9014C3 11.3748 5.6078 8.45738 9.00018 7.97223V21.8305C5.6078 21.3454 3 18.4279 3 14.9014ZM14.899 19.9014C13.8612 20.9183 12.5082 21.6147 11.0002 21.8305V19.9014H14.899ZM16.3264 17.9014H11.0002V15.9014H16.9291C16.8281 16.6075 16.6217 17.2797 16.3264 17.9014ZM16.9291 13.9014H11.0002V11.9014H16.3264C16.6217 12.5231 16.8281 13.1952 16.9291 13.9014ZM14.899 9.90137H11.0002V7.97228C12.5082 8.18803 13.8612 8.88445 14.899 9.90137ZM10 23.9014H10.0002H26.0002C26.5525 23.9014 27.0002 23.4537 27.0002 22.9014V6.90137C27.0002 6.34908 26.5525 5.90137 26.0002 5.90137H10.0002H10C5.02944 5.90137 1 9.9308 1 14.9014C1 19.8719 5.02944 23.9014 10 23.9014Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Indeterminate _ Negative.svg b/assets/icons/polkadot/solid/Indeterminate _ Negative.svg
new file mode 100644
index 00000000..bc6e3971
--- /dev/null
+++ b/assets/icons/polkadot/solid/Indeterminate _ Negative.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Informational.svg b/assets/icons/polkadot/solid/Informational.svg
new file mode 100644
index 00000000..19472f11
--- /dev/null
+++ b/assets/icons/polkadot/solid/Informational.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14.9883 1.67578C7.80858 1.67578 1.98828 7.49608 1.98828 14.6758C1.98828 21.8555 7.80858 27.6758 14.9883 27.6758C22.168 27.6758 27.9883 21.8555 27.9883 14.6758C27.9883 7.49608 22.168 1.67578 14.9883 1.67578ZM15.0089 21.2124C14.4566 21.2131 14.0083 20.766 14.0075 20.2137L13.998 13.0835C13.9973 12.5312 14.4444 12.0829 14.9967 12.0822C15.549 12.0815 15.9973 12.5286 15.998 13.0809L16.0075 20.2111C16.0083 20.7634 15.5611 21.2117 15.0089 21.2124ZM14.2992 9.40118C14.6897 9.7917 15.3228 9.7917 15.7134 9.40118C16.1039 9.01065 16.1039 8.37749 15.7134 7.98696L15.6952 7.96883C15.3047 7.5783 14.6715 7.5783 14.281 7.96883C13.8905 8.35935 13.8905 8.99251 14.281 9.38304L14.2992 9.40118Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Infrastructure.svg b/assets/icons/polkadot/solid/Infrastructure.svg
new file mode 100644
index 00000000..3e2bb941
--- /dev/null
+++ b/assets/icons/polkadot/solid/Infrastructure.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14.0332 1C11.9375 1 10.2618 2.71839 10.2618 4.80939C10.2618 6.5469 11.4188 8.02714 13.0125 8.47795V11.1182H4.7714C4.50618 11.1182 4.25183 11.2235 4.06429 11.4111C3.87675 11.5986 3.7714 11.8529 3.7714 12.1182V15.2981C2.16711 15.7419 1 17.2274 1 18.9725C1 21.0635 2.67575 22.7819 4.77144 22.7819C6.86712 22.7819 8.54287 21.0635 8.54287 18.9725C8.54287 17.2274 7.37573 15.7419 5.7714 15.2981V13.1182H13.0125V19.4951C11.3668 19.9108 10.1605 21.4166 10.1605 23.1907C10.1605 25.2817 11.8363 27.0001 13.932 27.0001C16.0276 27.0001 17.7034 25.2817 17.7034 23.1907C17.7034 21.475 16.5752 20.0101 15.0125 19.5396V13.1182H22.2534V15.2913C20.6363 15.7266 19.4572 17.2184 19.4572 18.9725C19.4572 21.0635 21.1329 22.7819 23.2286 22.7819C25.3243 22.7819 27 21.0635 27 18.9725C27 17.2364 25.8449 15.7572 24.2534 15.3051V12.1182C24.2534 11.5659 23.8057 11.1182 23.2534 11.1182H15.0125V8.48944C16.6274 8.05277 17.8046 6.56196 17.8046 4.80939C17.8046 2.71839 16.1289 1 14.0332 1Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Injected Account.svg b/assets/icons/polkadot/solid/Injected Account.svg
new file mode 100644
index 00000000..ab3f0185
--- /dev/null
+++ b/assets/icons/polkadot/solid/Injected Account.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M22.1409 7.47407C21.7522 7.86639 21.7551 8.49955 22.1475 8.88827C22.5398 9.27698 23.1729 9.27405 23.5617 8.88172L26.707 5.70718C27.0928 5.31774 27.0932 4.69025 26.7078 4.30036L23.5625 1.1183C23.1742 0.725516 22.5411 0.721837 22.1483 1.11009C21.7555 1.49834 21.7518 2.13149 22.1401 2.52428L23.6021 4.00335L20.0093 4.00336C19.457 4.00336 19.0093 4.45107 19.0093 5.00336C19.0093 5.55564 19.457 6.00336 20.0093 6.00336L23.5981 6.00335L22.1409 7.47407ZM16.313 4.63328C14.0866 2.40284 10.4727 2.40284 8.24641 4.63327C6.16708 6.71645 6.01633 10.0404 7.89855 12.3033L8.80767 13.3962C8.92443 13.5366 8.85753 13.7507 8.68162 13.7996L7.44991 14.1421C3.64473 15.2003 1.01172 18.6655 1.01172 22.6151V25.9916C1.01172 26.5439 1.45943 26.9916 2.01172 26.9916H22.5393C23.0916 26.9916 23.5393 26.5439 23.5393 25.9916V22.6092C23.5393 18.6627 20.9087 15.2001 17.1067 14.142L15.8775 13.7999C15.7016 13.751 15.6347 13.5368 15.7515 13.3965L16.6608 12.3033C18.543 10.0404 18.3923 6.71645 16.313 4.63328Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Interconnected.svg b/assets/icons/polkadot/solid/Interconnected.svg
new file mode 100644
index 00000000..b3d63510
--- /dev/null
+++ b/assets/icons/polkadot/solid/Interconnected.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M13.0001 10.8043C10.7633 10.3253 9.08618 8.33717 9.08618 5.95734C9.08618 3.21975 11.3054 1.00049 14.043 1.00049C16.7806 1.00049 18.9999 3.21975 18.9999 5.95734C18.9999 8.36753 17.2797 10.376 15.0001 10.8219V14.4713L19.3333 17.4906C20.2263 16.6216 21.4457 16.0864 22.7901 16.0864C25.5277 16.0864 27.747 18.3057 27.747 21.0433C27.747 23.7809 25.5277 26.0001 22.7901 26.0001C20.0525 26.0001 17.8333 23.7809 17.8333 21.0433C17.8333 20.3709 17.9671 19.7299 18.2096 19.1453L14.0048 16.2154L9.79226 19.1507C10.0334 19.7338 10.1664 20.373 10.1664 21.0433C10.1664 23.7809 7.94713 26.0001 5.20954 26.0001C2.47194 26.0001 0.252686 23.7809 0.252686 21.0433C0.252686 18.3057 2.47194 16.0864 5.20954 16.0864C6.55604 16.0864 7.77715 16.6233 8.67047 17.4947L13.0001 14.4779V10.8043Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Interoperability.svg b/assets/icons/polkadot/solid/Interoperability.svg
new file mode 100644
index 00000000..1ed2987c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Interoperability.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Investors.svg b/assets/icons/polkadot/solid/Investors.svg
new file mode 100644
index 00000000..dbdc8169
--- /dev/null
+++ b/assets/icons/polkadot/solid/Investors.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M8.79878 0.265625C4.06663 0.265625 0.230469 4.10179 0.230469 8.83393C0.230469 13.5661 4.06663 17.4022 8.79878 17.4022C13.5309 17.4022 17.3671 13.5661 17.3671 8.83393C17.3671 4.10179 13.5309 0.265625 8.79878 0.265625ZM8.79614 3.52441C9.34843 3.52441 9.79614 3.97213 9.79614 4.52441V4.7266H10.3476C10.8998 4.7266 11.3476 5.17432 11.3476 5.7266C11.3476 6.27888 10.8998 6.7266 10.3476 6.7266H8.25317C8.1807 6.7261 8.10884 6.73991 8.04174 6.7673C7.97464 6.79468 7.91362 6.83507 7.86219 6.88615C7.81076 6.93722 7.76995 6.99796 7.7421 7.06487C7.71469 7.13074 7.70037 7.20129 7.69992 7.27259C7.70184 7.41924 7.7612 7.55936 7.86533 7.66277C7.97028 7.76699 8.11219 7.82549 8.2601 7.82548H9.3361C10.012 7.82547 10.6606 8.09278 11.1402 8.56909C11.6157 9.04131 11.8869 9.68097 11.8961 10.3506C11.9082 10.6958 11.8503 11.0399 11.7258 11.3623C11.5993 11.69 11.4066 11.9883 11.1598 12.2383C10.9131 12.4884 10.6175 12.6851 10.2914 12.816C10.1311 12.8803 9.96517 12.9281 9.79614 12.9589V13.2191C9.79614 13.7714 9.34843 14.2191 8.79614 14.2191C8.24386 14.2191 7.79614 13.7714 7.79614 13.2191V12.9997H7.03348C6.48119 12.9997 6.03348 12.552 6.03348 11.9997C6.03348 11.4474 6.48119 10.9997 7.03348 10.9997H9.29308C9.30257 10.9997 9.31205 10.9998 9.32154 11.0001C9.39839 11.0023 9.47487 10.9886 9.54621 10.96C9.61754 10.9313 9.68222 10.8883 9.73623 10.8336C9.79024 10.7789 9.8324 10.7136 9.86008 10.6419C9.88777 10.5702 9.9004 10.4935 9.89719 10.4167C9.89671 10.4051 9.89642 10.3935 9.89634 10.3818C9.89532 10.2339 9.83585 10.0924 9.7309 9.98819C9.62595 9.88397 9.48405 9.82548 9.33614 9.82548H8.26014C7.58419 9.82549 6.93564 9.55818 6.45602 9.08187C5.97639 8.60555 5.7046 7.95888 5.69994 7.28294L5.69989 7.27606C5.69988 6.93976 5.76644 6.60679 5.89566 6.29633C6.02489 5.98585 6.21427 5.70402 6.45288 5.46705C6.69149 5.23008 6.97463 5.04266 7.28599 4.91558C7.45081 4.84832 7.62181 4.79866 7.79614 4.76717V4.52441C7.79614 3.97213 8.24386 3.52441 8.79614 3.52441ZM26.7751 9.23145C27.3274 9.22964 27.7766 9.67588 27.7784 10.2282L27.7974 15.9967C27.7992 16.549 27.3529 16.9982 26.8006 17C26.2484 17.0018 25.7992 16.5556 25.7974 16.0033L25.786 12.5473L17.2654 20.9526C16.8911 21.3218 16.3866 21.5288 15.8609 21.5288H9.65816L2.38845 26.8088C1.9416 27.1334 1.31624 27.0343 0.991685 26.5874C0.667128 26.1405 0.766272 25.5152 1.21313 25.1906L8.48284 19.9106C8.82449 19.6624 9.23591 19.5288 9.65816 19.5288H15.8609L24.2636 11.2397L21.0033 11.2504C20.451 11.2522 20.0018 10.806 20 10.2537C19.9982 9.70139 20.4444 9.25221 20.9967 9.2504L26.7751 9.23145Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/IoT And Robotics.svg b/assets/icons/polkadot/solid/IoT And Robotics.svg
new file mode 100644
index 00000000..c0fca16f
--- /dev/null
+++ b/assets/icons/polkadot/solid/IoT And Robotics.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M16.1031 7.80056C17.7842 6.30638 20.3582 6.45791 21.8524 8.13901C22.7477 9.14634 23.0522 10.4743 22.7907 11.6984C22.8838 11.768 22.9663 11.8551 23.0329 11.9587L27.6949 19.2047C27.9937 19.6692 27.8595 20.288 27.395 20.5868L24.4939 22.4533C24.2709 22.5968 24 22.6458 23.7408 22.5895C23.4816 22.5333 23.2554 22.3764 23.1119 22.1534L18.5358 15.0408C18.5069 14.9959 18.4821 14.9495 18.4612 14.9021C18.0577 14.8676 17.6591 14.7733 17.2797 14.62C17.2033 14.7152 17.108 14.7978 16.9956 14.862L14.268 16.4185C14.325 17.0826 14.2738 17.7683 14.0953 18.4496C13.2529 21.6655 9.96396 23.5892 6.74806 22.7468C5.79192 22.4964 4.95051 22.0231 4.26392 21.4151C4.02408 21.2027 3.90052 20.8883 3.93158 20.5695C3.96264 20.2506 4.14457 19.966 4.42088 19.8039L7.53555 17.9768L6.83237 16.7745L3.8131 18.5458C3.52695 18.7136 3.17616 18.7287 2.8767 18.5859C2.57724 18.4431 2.36809 18.1611 2.31838 17.8331C2.19988 17.0511 2.22544 16.2268 2.44269 15.3974C3.28504 12.1815 6.57402 10.2579 9.78993 11.1003C10.3896 11.2573 10.9476 11.5011 11.4508 11.8176L14.5116 10.1047C14.6123 10.0484 14.7184 10.0114 14.8259 9.99239C15.0006 9.17291 15.4288 8.39987 16.1031 7.80056ZM20.5755 14.5147L24.2528 20.2302L25.4719 19.4459L21.7501 13.6611C21.6751 13.7393 21.5963 13.8151 21.514 13.8883C21.2243 14.1458 20.9081 14.3544 20.5755 14.5147ZM15.6016 13.3548C15.3109 12.9841 15.0942 12.5766 14.9503 12.1511L11.8753 13.8719C11.5183 14.0717 11.0755 14.0338 10.7576 13.7764C10.3401 13.4382 9.84267 13.1815 9.28315 13.035C7.13903 12.4734 4.94655 13.7529 4.37999 15.8944L6.68403 14.5428C6.91299 14.4084 7.18596 14.3707 7.44278 14.4377C7.69961 14.5048 7.91923 14.6713 8.05324 14.9004L9.76615 17.8291C10.0447 18.3054 9.88486 18.9173 9.40893 19.1965L6.86561 20.6885C6.99209 20.7359 7.12192 20.7773 7.25483 20.8121C9.40221 21.3745 11.5981 20.0902 12.1606 17.9429C12.3233 17.3216 12.3278 16.6917 12.202 16.0937C12.1125 15.6687 12.3076 15.2345 12.6849 15.0192L15.6016 13.3548Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/IoT.svg b/assets/icons/polkadot/solid/IoT.svg
new file mode 100644
index 00000000..09d4abf1
--- /dev/null
+++ b/assets/icons/polkadot/solid/IoT.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Isolated.svg b/assets/icons/polkadot/solid/Isolated.svg
new file mode 100644
index 00000000..6a433d07
--- /dev/null
+++ b/assets/icons/polkadot/solid/Isolated.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/KeepAlive Check.svg b/assets/icons/polkadot/solid/KeepAlive Check.svg
new file mode 100644
index 00000000..0504daf5
--- /dev/null
+++ b/assets/icons/polkadot/solid/KeepAlive Check.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Key.svg b/assets/icons/polkadot/solid/Key.svg
new file mode 100644
index 00000000..6e8b237c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Key.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Language.svg b/assets/icons/polkadot/solid/Language.svg
new file mode 100644
index 00000000..d85175d8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Language.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Layer (Four).svg b/assets/icons/polkadot/solid/Layer (Four).svg
new file mode 100644
index 00000000..a9e26c9f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Layer (Four).svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Layer (One).svg b/assets/icons/polkadot/solid/Layer (One).svg
new file mode 100644
index 00000000..d7d19272
--- /dev/null
+++ b/assets/icons/polkadot/solid/Layer (One).svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Layer (Three).svg b/assets/icons/polkadot/solid/Layer (Three).svg
new file mode 100644
index 00000000..1a698978
--- /dev/null
+++ b/assets/icons/polkadot/solid/Layer (Three).svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Layer (Two).svg b/assets/icons/polkadot/solid/Layer (Two).svg
new file mode 100644
index 00000000..56c9bab0
--- /dev/null
+++ b/assets/icons/polkadot/solid/Layer (Two).svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Layer.svg b/assets/icons/polkadot/solid/Layer.svg
new file mode 100644
index 00000000..11f14910
--- /dev/null
+++ b/assets/icons/polkadot/solid/Layer.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Learn More.svg b/assets/icons/polkadot/solid/Learn More.svg
new file mode 100644
index 00000000..65023b8c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Learn More.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Learn.svg b/assets/icons/polkadot/solid/Learn.svg
new file mode 100644
index 00000000..2ffd3872
--- /dev/null
+++ b/assets/icons/polkadot/solid/Learn.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Lease Duration.svg b/assets/icons/polkadot/solid/Lease Duration.svg
new file mode 100644
index 00000000..17ad5f24
--- /dev/null
+++ b/assets/icons/polkadot/solid/Lease Duration.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Library.svg b/assets/icons/polkadot/solid/Library.svg
new file mode 100644
index 00000000..d15bdffd
--- /dev/null
+++ b/assets/icons/polkadot/solid/Library.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Light Node.svg b/assets/icons/polkadot/solid/Light Node.svg
new file mode 100644
index 00000000..f46b5572
--- /dev/null
+++ b/assets/icons/polkadot/solid/Light Node.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Lights On.svg b/assets/icons/polkadot/solid/Lights On.svg
new file mode 100644
index 00000000..499634a0
--- /dev/null
+++ b/assets/icons/polkadot/solid/Lights On.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Limited Supply.svg b/assets/icons/polkadot/solid/Limited Supply.svg
new file mode 100644
index 00000000..b965441b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Limited Supply.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/LinkedIn.svg b/assets/icons/polkadot/solid/LinkedIn.svg
new file mode 100644
index 00000000..29251287
--- /dev/null
+++ b/assets/icons/polkadot/solid/LinkedIn.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Lock.svg b/assets/icons/polkadot/solid/Lock.svg
new file mode 100644
index 00000000..f10e412d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Lock.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Maintain.svg b/assets/icons/polkadot/solid/Maintain.svg
new file mode 100644
index 00000000..44c43eb6
--- /dev/null
+++ b/assets/icons/polkadot/solid/Maintain.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Marketing.svg b/assets/icons/polkadot/solid/Marketing.svg
new file mode 100644
index 00000000..091866f8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Marketing.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Menu.svg b/assets/icons/polkadot/solid/Menu.svg
new file mode 100644
index 00000000..8b25bcad
--- /dev/null
+++ b/assets/icons/polkadot/solid/Menu.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M2.98242 6.66992C2.43014 6.66992 1.98242 7.11764 1.98242 7.66992C1.98242 8.22221 2.43014 8.66992 2.98242 8.66992H26.9824C27.5347 8.66992 27.9824 8.22221 27.9824 7.66992C27.9824 7.11764 27.5347 6.66992 26.9824 6.66992H2.98242ZM1.98242 14.9614C1.98242 14.4091 2.43014 13.9614 2.98242 13.9614H26.9824C27.5347 13.9614 27.9824 14.4091 27.9824 14.9614C27.9824 15.5137 27.5347 15.9614 26.9824 15.9614H2.98242C2.43014 15.9614 1.98242 15.5137 1.98242 14.9614ZM1.98242 22.2534C1.98242 21.7011 2.43014 21.2534 2.98242 21.2534H26.9824C27.5347 21.2534 27.9824 21.7011 27.9824 22.2534C27.9824 22.8057 27.5347 23.2534 26.9824 23.2534H2.98242C2.43014 23.2534 1.98242 22.8057 1.98242 22.2534Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Message.svg b/assets/icons/polkadot/solid/Message.svg
new file mode 100644
index 00000000..bdc57c78
--- /dev/null
+++ b/assets/icons/polkadot/solid/Message.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Metaverse.svg b/assets/icons/polkadot/solid/Metaverse.svg
new file mode 100644
index 00000000..277a8cba
--- /dev/null
+++ b/assets/icons/polkadot/solid/Metaverse.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M13.6297 1.10557C13.9112 0.964809 14.2426 0.964809 14.5241 1.10557L25.6011 6.64403C25.9398 6.81343 26.1538 7.15969 26.1538 7.53846V20.4615C26.1538 20.8403 25.9398 21.1866 25.6011 21.356L14.5241 26.8944C14.2426 27.0352 13.9112 27.0352 13.6297 26.8944L2.55279 21.356C2.214 21.1866 2 20.8403 2 20.4615V7.53846C2 7.15969 2.214 6.81343 2.55279 6.64403L13.6297 1.10557ZM10 11H18C19.6569 11 21 12.3431 21 14C21 15.251 20.234 16.3255 19.1416 16.7754C18.7234 16.9477 18.1049 16.8033 17.4054 16.2437C15.4145 14.651 12.5855 14.651 10.5946 16.2437C9.89511 16.8033 9.27663 16.9477 8.85841 16.7754C7.766 16.3255 7 15.251 7 14C7 12.3431 8.34315 11 10 11ZM18 9H10C7.23858 9 5 11.2386 5 14C5 16.0892 6.28107 17.8768 8.09667 18.6247C9.54763 19.2224 10.9649 18.5087 11.844 17.8054C13.1045 16.7971 14.8955 16.7971 16.156 17.8054C17.0351 18.5087 18.4524 19.2224 19.9033 18.6247C21.7189 17.8768 23 16.0892 23 14C23 11.2386 20.7614 9 18 9Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Mitigating Mev.svg b/assets/icons/polkadot/solid/Mitigating Mev.svg
new file mode 100644
index 00000000..7d703af6
--- /dev/null
+++ b/assets/icons/polkadot/solid/Mitigating Mev.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Mobile App.svg b/assets/icons/polkadot/solid/Mobile App.svg
new file mode 100644
index 00000000..5715361f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Mobile App.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M5 2.33008C5 1.77779 5.44772 1.33008 6 1.33008H22.5109C23.0632 1.33008 23.5109 1.77779 23.5109 2.33008V26.3301C23.5109 26.8824 23.0632 27.3301 22.5109 27.3301H6C5.44772 27.3301 5 26.8824 5 26.3301V2.33008ZM13.3052 22.0425C12.753 22.0425 12.3052 22.4902 12.3052 23.0425C12.3052 23.5948 12.753 24.0425 13.3052 24.0425H15.205C15.7573 24.0425 16.205 23.5948 16.205 23.0425C16.205 22.4902 15.7573 22.0425 15.205 22.0425H13.3052Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Monitor.svg b/assets/icons/polkadot/solid/Monitor.svg
new file mode 100644
index 00000000..2566890c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Monitor.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/More Horizontal.svg b/assets/icons/polkadot/solid/More Horizontal.svg
new file mode 100644
index 00000000..091b2efe
--- /dev/null
+++ b/assets/icons/polkadot/solid/More Horizontal.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M6.70262 11.9582C5.39245 10.648 3.26825 10.648 1.95809 11.9582C0.647922 13.2684 0.647922 15.3926 1.95809 16.7027C3.26825 18.0129 5.39245 18.0129 6.70262 16.7027C8.01278 15.3926 8.01278 13.2684 6.70262 11.9582ZM16.3721 11.9582C15.0619 10.648 12.9377 10.648 11.6276 11.9582C10.3174 13.2684 10.3174 15.3926 11.6276 16.7027C12.9377 18.0129 15.0619 18.0129 16.3721 16.7027C17.6823 15.3926 17.6823 13.2684 16.3721 11.9582ZM26.0419 11.9582C24.7317 10.648 22.6075 10.648 21.2973 11.9582C19.9872 13.2684 19.9872 15.3926 21.2973 16.7027C22.6075 18.0129 24.7317 18.0129 26.0419 16.7027C27.352 15.3926 27.352 13.2684 26.0419 11.9582Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/More Menu.svg b/assets/icons/polkadot/solid/More Menu.svg
new file mode 100644
index 00000000..31fc356f
--- /dev/null
+++ b/assets/icons/polkadot/solid/More Menu.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/More Vertical.svg b/assets/icons/polkadot/solid/More Vertical.svg
new file mode 100644
index 00000000..d57c823e
--- /dev/null
+++ b/assets/icons/polkadot/solid/More Vertical.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Multichain Smart Contracts.svg b/assets/icons/polkadot/solid/Multichain Smart Contracts.svg
new file mode 100644
index 00000000..610043ec
--- /dev/null
+++ b/assets/icons/polkadot/solid/Multichain Smart Contracts.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Multichain Treasuries.svg b/assets/icons/polkadot/solid/Multichain Treasuries.svg
new file mode 100644
index 00000000..b13a3f42
--- /dev/null
+++ b/assets/icons/polkadot/solid/Multichain Treasuries.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Multisign Account.svg b/assets/icons/polkadot/solid/Multisign Account.svg
new file mode 100644
index 00000000..223c6c69
--- /dev/null
+++ b/assets/icons/polkadot/solid/Multisign Account.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Multisign.svg b/assets/icons/polkadot/solid/Multisign.svg
new file mode 100644
index 00000000..bc217dfa
--- /dev/null
+++ b/assets/icons/polkadot/solid/Multisign.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/NFT Staking.svg b/assets/icons/polkadot/solid/NFT Staking.svg
new file mode 100644
index 00000000..8930c6da
--- /dev/null
+++ b/assets/icons/polkadot/solid/NFT Staking.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Network Is Connected.svg b/assets/icons/polkadot/solid/Network Is Connected.svg
new file mode 100644
index 00000000..c02bf3b5
--- /dev/null
+++ b/assets/icons/polkadot/solid/Network Is Connected.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Network Security Operations.svg b/assets/icons/polkadot/solid/Network Security Operations.svg
new file mode 100644
index 00000000..9b17ad39
--- /dev/null
+++ b/assets/icons/polkadot/solid/Network Security Operations.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/New Tab.svg b/assets/icons/polkadot/solid/New Tab.svg
new file mode 100644
index 00000000..224f76ed
--- /dev/null
+++ b/assets/icons/polkadot/solid/New Tab.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/News.svg b/assets/icons/polkadot/solid/News.svg
new file mode 100644
index 00000000..b7db72e3
--- /dev/null
+++ b/assets/icons/polkadot/solid/News.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Nft.svg b/assets/icons/polkadot/solid/Nft.svg
new file mode 100644
index 00000000..80f1c6b5
--- /dev/null
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diff --git a/assets/icons/polkadot/solid/Night_Dark Mode.svg b/assets/icons/polkadot/solid/Night_Dark Mode.svg
new file mode 100644
index 00000000..0df7c220
--- /dev/null
+++ b/assets/icons/polkadot/solid/Night_Dark Mode.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M17.2844 2.19404C10.5728 0.439795 3.71 4.45846 1.95575 11.17C0.201514 17.8815 4.22018 24.7443 10.9317 26.4986C17.2211 28.1425 23.6421 24.7173 25.8697 18.7568C26.0291 18.3303 25.8803 17.85 25.5077 17.5884C25.1351 17.3267 24.6328 17.3498 24.2857 17.6445C22.5566 19.1126 20.1665 19.7399 17.8092 19.1237C13.968 18.1197 11.668 14.1919 12.672 10.3508C13.487 7.2327 16.2299 5.12801 19.2905 4.98565C19.7459 4.96446 20.1294 4.63789 20.2228 4.19164C20.3162 3.74538 20.0959 3.29242 19.6873 3.09033C18.9324 2.71707 18.1292 2.41487 17.2844 2.19404Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Node.svg b/assets/icons/polkadot/solid/Node.svg
new file mode 100644
index 00000000..d7fb61ba
--- /dev/null
+++ b/assets/icons/polkadot/solid/Node.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Nominating.svg b/assets/icons/polkadot/solid/Nominating.svg
new file mode 100644
index 00000000..ab7695fc
--- /dev/null
+++ b/assets/icons/polkadot/solid/Nominating.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Nominators.svg b/assets/icons/polkadot/solid/Nominators.svg
new file mode 100644
index 00000000..03dc1766
--- /dev/null
+++ b/assets/icons/polkadot/solid/Nominators.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Not Able To Upgrade.svg b/assets/icons/polkadot/solid/Not Able To Upgrade.svg
new file mode 100644
index 00000000..56f8503e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Not Able To Upgrade.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Not Scalable.svg b/assets/icons/polkadot/solid/Not Scalable.svg
new file mode 100644
index 00000000..ba22c217
--- /dev/null
+++ b/assets/icons/polkadot/solid/Not Scalable.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Notification.svg b/assets/icons/polkadot/solid/Notification.svg
new file mode 100644
index 00000000..25f3c268
--- /dev/null
+++ b/assets/icons/polkadot/solid/Notification.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Off-Chain Computations.svg b/assets/icons/polkadot/solid/Off-Chain Computations.svg
new file mode 100644
index 00000000..ab5f9e6e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Off-Chain Computations.svg	
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diff --git a/assets/icons/polkadot/solid/Offboarding.svg b/assets/icons/polkadot/solid/Offboarding.svg
new file mode 100644
index 00000000..92dc5c1a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Offboarding.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/On-Chain Scheduling.svg b/assets/icons/polkadot/solid/On-Chain Scheduling.svg
new file mode 100644
index 00000000..56800c16
--- /dev/null
+++ b/assets/icons/polkadot/solid/On-Chain Scheduling.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Onboarding.svg b/assets/icons/polkadot/solid/Onboarding.svg
new file mode 100644
index 00000000..d234f6da
--- /dev/null
+++ b/assets/icons/polkadot/solid/Onboarding.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Oracle.svg b/assets/icons/polkadot/solid/Oracle.svg
new file mode 100644
index 00000000..a5bd15c6
--- /dev/null
+++ b/assets/icons/polkadot/solid/Oracle.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Oracles.svg b/assets/icons/polkadot/solid/Oracles.svg
new file mode 100644
index 00000000..87802687
--- /dev/null
+++ b/assets/icons/polkadot/solid/Oracles.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Overview.svg b/assets/icons/polkadot/solid/Overview.svg
new file mode 100644
index 00000000..125e4c78
--- /dev/null
+++ b/assets/icons/polkadot/solid/Overview.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Paper Money.svg b/assets/icons/polkadot/solid/Paper Money.svg
new file mode 100644
index 00000000..a7ce3421
--- /dev/null
+++ b/assets/icons/polkadot/solid/Paper Money.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Parachains.svg b/assets/icons/polkadot/solid/Parachains.svg
new file mode 100644
index 00000000..60eda3a9
--- /dev/null
+++ b/assets/icons/polkadot/solid/Parachains.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Payout.svg b/assets/icons/polkadot/solid/Payout.svg
new file mode 100644
index 00000000..cf57b92d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Payout.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Picture.svg b/assets/icons/polkadot/solid/Picture.svg
new file mode 100644
index 00000000..a1ebb7f2
--- /dev/null
+++ b/assets/icons/polkadot/solid/Picture.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Podcasts.svg b/assets/icons/polkadot/solid/Podcasts.svg
new file mode 100644
index 00000000..eb84801f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Podcasts.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Privacy.svg b/assets/icons/polkadot/solid/Privacy.svg
new file mode 100644
index 00000000..1bb88093
--- /dev/null
+++ b/assets/icons/polkadot/solid/Privacy.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Private Key.svg b/assets/icons/polkadot/solid/Private Key.svg
new file mode 100644
index 00000000..6e11e058
--- /dev/null
+++ b/assets/icons/polkadot/solid/Private Key.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Proof Of Stake.svg b/assets/icons/polkadot/solid/Proof Of Stake.svg
new file mode 100644
index 00000000..96c7712d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Proof Of Stake.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Proof Of Work.svg b/assets/icons/polkadot/solid/Proof Of Work.svg
new file mode 100644
index 00000000..783b1171
--- /dev/null
+++ b/assets/icons/polkadot/solid/Proof Of Work.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Proposal.svg b/assets/icons/polkadot/solid/Proposal.svg
new file mode 100644
index 00000000..eeac7adc
--- /dev/null
+++ b/assets/icons/polkadot/solid/Proposal.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Proxy.svg b/assets/icons/polkadot/solid/Proxy.svg
new file mode 100644
index 00000000..5a0f27fe
--- /dev/null
+++ b/assets/icons/polkadot/solid/Proxy.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/ProxyAccount.svg b/assets/icons/polkadot/solid/ProxyAccount.svg
new file mode 100644
index 00000000..a58d4a9b
--- /dev/null
+++ b/assets/icons/polkadot/solid/ProxyAccount.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Public Key.svg b/assets/icons/polkadot/solid/Public Key.svg
new file mode 100644
index 00000000..838d15ca
--- /dev/null
+++ b/assets/icons/polkadot/solid/Public Key.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/QR Code.svg b/assets/icons/polkadot/solid/QR Code.svg
new file mode 100644
index 00000000..3ae67607
--- /dev/null
+++ b/assets/icons/polkadot/solid/QR Code.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Randomness.svg b/assets/icons/polkadot/solid/Randomness.svg
new file mode 100644
index 00000000..835fd9a4
--- /dev/null
+++ b/assets/icons/polkadot/solid/Randomness.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Read Time.svg b/assets/icons/polkadot/solid/Read Time.svg
new file mode 100644
index 00000000..89b7c96f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Read Time.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Recover Keys.svg b/assets/icons/polkadot/solid/Recover Keys.svg
new file mode 100644
index 00000000..2bd063b3
--- /dev/null
+++ b/assets/icons/polkadot/solid/Recover Keys.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Recovery.svg b/assets/icons/polkadot/solid/Recovery.svg
new file mode 100644
index 00000000..cb34c6fb
--- /dev/null
+++ b/assets/icons/polkadot/solid/Recovery.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M15.2025 6C11.0596 6 7.6294 9.01656 6.99589 12.9588L8.15774 11.7653C8.54299 11.3696 9.1761 11.3611 9.57183 11.7464C9.96756 12.1316 9.97606 12.7647 9.59081 13.1604L6.6931 16.137C6.30785 16.5327 5.67474 16.5412 5.27901 16.156L2.30245 13.2583C1.90672 12.873 1.89822 12.2399 2.28347 11.8442C2.66871 11.4485 3.30182 11.44 3.69755 11.8252L4.96291 13.057C5.56807 7.95358 9.92471 4 15.2025 4C20.8938 4 25.5139 8.5973 25.5139 14.2763C25.5139 19.9553 20.8938 24.5526 15.2025 24.5526C11.8036 24.5526 8.78779 22.9126 6.91051 20.3857C6.58115 19.9424 6.67354 19.316 7.11686 18.9866C7.56019 18.6573 8.18658 18.7496 8.51594 19.193C10.031 21.2323 12.4613 22.5526 15.2025 22.5526C19.7963 22.5526 23.5139 18.8436 23.5139 14.2763C23.5139 9.70898 19.7963 6 15.2025 6ZM14.8432 10.1934C14.8432 9.64107 15.2909 9.19336 15.8432 9.19336C16.3955 9.19336 16.8432 9.64107 16.8432 10.1934V16.1934C16.8432 16.4256 16.7623 16.6507 16.6145 16.8298L13.7713 20.2752C13.4197 20.7012 12.7895 20.7616 12.3635 20.41C11.9375 20.0585 11.8772 19.4282 12.2287 19.0023L14.8432 15.834V10.1934Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Reddit.svg b/assets/icons/polkadot/solid/Reddit.svg
new file mode 100644
index 00000000..dd7c9151
--- /dev/null
+++ b/assets/icons/polkadot/solid/Reddit.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M22.1818 4C21.8304 4 21.5455 4.28491 21.5455 4.63636C21.5455 4.98782 21.8304 5.27273 22.1818 5.27273C22.5333 5.27273 22.8182 4.98782 22.8182 4.63636C22.8182 4.28491 22.5333 4 22.1818 4ZM19.8258 3.45205C20.2596 2.5908 21.1517 2 22.1818 2C23.6378 2 24.8182 3.18034 24.8182 4.63636C24.8182 6.09239 23.6378 7.27273 22.1818 7.27273C21.0165 7.27273 20.0278 6.51666 19.6794 5.4683L16.3877 4.73682L15.2464 9.68257C17.4494 9.84731 19.4874 10.4446 21.1811 11.3691C21.7773 10.9644 22.4977 10.7271 23.2727 10.7271C25.3312 10.7271 27 12.3959 27 14.4544C27 15.5308 26.5433 16.4999 25.8156 17.1794C25.8773 17.5373 25.9091 17.9022 25.9091 18.2726C25.9091 20.7972 24.4459 22.9805 22.2874 24.4916C20.1256 26.0048 17.1925 26.909 14 26.909C10.8075 26.909 7.87438 26.0048 5.71265 24.4916C3.55407 22.9805 2.09091 20.7972 2.09091 18.2726C2.09091 17.9022 2.12274 17.5373 2.18436 17.1795C1.45689 16.5002 1 15.5306 1 14.4544C1 12.3959 2.66876 10.7271 4.72727 10.7271C5.50217 10.7271 6.22268 10.9643 6.81887 11.3691C8.62646 10.3825 10.8263 9.76846 13.2001 9.65525L14.662 3.32059C14.7855 2.78554 15.3173 2.45015 15.8533 2.56927L19.8258 3.45205ZM9.31509 17.0621C9.70561 17.4526 10.3388 17.4526 10.7293 17.0621C11.1198 16.6716 11.1198 16.0384 10.7293 15.6479L10.7073 15.6259C10.3168 15.2354 9.68363 15.2354 9.29311 15.6259C8.90258 16.0164 8.90258 16.6496 9.29311 17.0401L9.31509 17.0621ZM17.315 17.0621C17.7055 17.4526 18.3387 17.4526 18.7292 17.0621C19.1197 16.6716 19.1197 16.0384 18.7292 15.6479L18.7072 15.6259C18.3167 15.2354 17.6836 15.2354 17.293 15.6259C16.9025 16.0164 16.9025 16.6496 17.293 17.0401L17.315 17.0621ZM10.1863 20.1649C9.72722 19.8626 9.1096 19.9875 8.80432 20.4454C8.49796 20.9049 8.62214 21.5258 9.08167 21.8322L9.63637 21.0001C9.08167 21.8322 9.08199 21.8324 9.08231 21.8326L9.08299 21.833L9.08448 21.834L9.08791 21.8363L9.09662 21.842L9.12142 21.8578C9.14121 21.8703 9.16751 21.8866 9.2002 21.9061C9.26556 21.945 9.35654 21.9969 9.4721 22.0571C9.70305 22.1776 10.0332 22.3324 10.4537 22.4854C11.295 22.7913 12.5018 23.091 14 23.091C15.4982 23.091 16.7051 22.7913 17.5463 22.4854C17.9668 22.3324 18.297 22.1776 18.5279 22.0571C18.6435 21.9969 18.7345 21.945 18.7998 21.9061C18.8325 21.8866 18.8588 21.8703 18.8786 21.8578L18.9034 21.842L18.9121 21.8363L18.9155 21.834L18.917 21.833L18.9177 21.8326C18.918 21.8324 18.9183 21.8322 18.3636 21.0001L18.9183 21.8322C19.3779 21.5258 19.502 20.9049 19.1957 20.4454C18.8904 19.9875 18.2728 19.8626 17.8137 20.1649L17.8106 20.1669C17.8051 20.1703 17.7936 20.1775 17.7762 20.1879C17.7414 20.2086 17.6832 20.242 17.6028 20.284C17.4417 20.368 17.1922 20.486 16.8628 20.6058C16.204 20.8453 15.2291 21.091 14 21.091C12.7709 21.091 11.796 20.8453 11.1372 20.6058C10.8078 20.486 10.5583 20.368 10.3972 20.284C10.3168 20.242 10.2586 20.2086 10.2238 20.1879C10.2064 20.1775 10.1949 20.1703 10.1894 20.1669L10.1863 20.1649L10.1863 20.1649Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Referenda.svg b/assets/icons/polkadot/solid/Referenda.svg
new file mode 100644
index 00000000..b97c7336
--- /dev/null
+++ b/assets/icons/polkadot/solid/Referenda.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M15.0813 1.29289C15.4718 0.902369 16.105 0.902369 16.4955 1.29289L24.7005 9.49781C24.888 9.68535 24.9933 9.9397 24.9933 10.2049C24.9933 10.4701 24.888 10.7245 24.7005 10.912L17.2219 18.3906H26C26.5523 18.3906 27 18.8383 27 19.3906V25.5212C27 26.0735 26.5523 26.5212 26 26.5212C25.4477 26.5212 25 26.0735 25 25.5212V20.3906H14.8737C14.851 20.3922 14.8282 20.393 14.8053 20.393H10.5202C10.4973 20.393 10.4745 20.3922 10.4518 20.3906H3V25.5212C3 26.0735 2.55228 26.5212 2 26.5212C1.44772 26.5212 1 26.0735 1 25.5212V19.3906C1 18.8383 1.44772 18.3906 2 18.3906H8.10363L3.75072 14.0377C3.56318 13.8502 3.45782 13.5958 3.45782 13.3306C3.45782 13.0654 3.56318 12.811 3.75072 12.6235L15.0813 1.29289Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Refresh _ Redo.svg b/assets/icons/polkadot/solid/Refresh _ Redo.svg
new file mode 100644
index 00000000..f204382f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Refresh _ Redo.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><g><path fill-rule="evenodd" clip-rule="evenodd" d="M24.3318 5.56919L24.5878 2.68303C24.6366 2.1329 25.1221 1.72649 25.6722 1.77528C26.2223 1.82406 26.6288 2.30958 26.58 2.8597L26.1053 8.21254C26.0565 8.76266 25.571 9.16908 25.0208 9.12029L19.668 8.64558C19.1179 8.59679 18.7115 8.11127 18.7602 7.56115C18.809 7.01102 19.2945 6.60461 19.8447 6.65339L22.8543 6.9203C18.8218 2.92134 12.3086 2.64075 7.90662 6.42722C3.27922 10.4075 2.74675 17.3664 6.7061 21.9694C10.6654 26.5724 17.6257 27.0862 22.2531 23.1059C25.0147 20.7305 26.3188 17.2939 26.078 13.9268C26.0386 13.3759 26.4532 12.8974 27.0041 12.858C27.555 12.8186 28.0335 13.2333 28.0729 13.7841C28.3571 17.757 26.8175 21.8179 23.5573 24.6222C18.0979 29.3181 9.87414 28.7194 5.18985 23.2736C0.505564 17.8278 1.143 9.60696 6.60239 4.91097C11.8217 0.421499 19.5676 0.7713 24.3318 5.56919Z" stroke="none"></path></g></svg>
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diff --git a/assets/icons/polkadot/solid/Registrars.svg b/assets/icons/polkadot/solid/Registrars.svg
new file mode 100644
index 00000000..baf93f70
--- /dev/null
+++ b/assets/icons/polkadot/solid/Registrars.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Regulators.svg b/assets/icons/polkadot/solid/Regulators.svg
new file mode 100644
index 00000000..99a9640d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Regulators.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Relay Chain.svg b/assets/icons/polkadot/solid/Relay Chain.svg
new file mode 100644
index 00000000..ab830428
--- /dev/null
+++ b/assets/icons/polkadot/solid/Relay Chain.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Remote Node.svg b/assets/icons/polkadot/solid/Remote Node.svg
new file mode 100644
index 00000000..1732d499
--- /dev/null
+++ b/assets/icons/polkadot/solid/Remote Node.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Remove User.svg b/assets/icons/polkadot/solid/Remove User.svg
new file mode 100644
index 00000000..55a2a07f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Remove User.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Remove.svg b/assets/icons/polkadot/solid/Remove.svg
new file mode 100644
index 00000000..2b51c767
--- /dev/null
+++ b/assets/icons/polkadot/solid/Remove.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Report.svg b/assets/icons/polkadot/solid/Report.svg
new file mode 100644
index 00000000..24ed86a5
--- /dev/null
+++ b/assets/icons/polkadot/solid/Report.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Reputation Systems.svg b/assets/icons/polkadot/solid/Reputation Systems.svg
new file mode 100644
index 00000000..2b02a91a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Reputation Systems.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Research.svg b/assets/icons/polkadot/solid/Research.svg
new file mode 100644
index 00000000..1e73f08e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Research.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Reserve Back Assets.svg b/assets/icons/polkadot/solid/Reserve Back Assets.svg
new file mode 100644
index 00000000..c4183710
--- /dev/null
+++ b/assets/icons/polkadot/solid/Reserve Back Assets.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M2.00051 1C1.44822 1 1.00051 1.44772 1.00051 2L1.00026 16.5868C1.00025 16.852 1.10561 17.1063 1.29314 17.2939C1.48068 17.4814 1.73504 17.5868 2.00026 17.5868L8.00014 17.5868C8.55242 17.5868 9.00014 17.1391 9.00014 16.5868L9.00014 9.03591L25.9999 9.03592C26.5522 9.03592 26.9999 8.5882 26.9999 8.03592L26.9999 2C26.9999 1.44772 26.5522 1 25.9999 1L2.00051 1ZM25.9993 27.0002C26.5516 27.0002 26.9993 26.5525 26.9993 26.0002L26.9996 11.4135C26.9996 11.1483 26.8942 10.8939 26.7067 10.7064C26.5191 10.5188 26.2648 10.4135 25.9996 10.4135H19.9997C19.4474 10.4135 18.9997 10.8612 18.9997 11.4135L18.9997 18.9643L1.99988 18.9643C1.44759 18.9643 0.999878 19.412 0.999878 19.9643V26.0002C0.999878 26.5525 1.44759 27.0002 1.99988 27.0002L25.9993 27.0002ZM14.0001 11.3475C12.4954 11.3475 11.2858 12.573 11.2858 14.0721C11.2858 15.5712 12.4954 16.7967 14.0001 16.7967C15.5048 16.7967 16.7144 15.5712 16.7144 14.0721C16.7144 12.573 15.5048 11.3475 14.0001 11.3475Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Restore From BackUp.svg b/assets/icons/polkadot/solid/Restore From BackUp.svg
new file mode 100644
index 00000000..0eb5d97f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Restore From BackUp.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M6.99589 12.9588C7.6294 9.01656 11.0596 6 15.2025 6C19.7963 6 23.5139 9.70898 23.5139 14.2763C23.5139 18.5206 20.3036 22.0237 16.1631 22.498L16.1631 14.0239L17.4421 15.269C17.8378 15.6543 18.4709 15.6458 18.8562 15.25C19.2414 14.8543 19.2329 14.2212 18.8372 13.836L15.8606 10.9383C15.4649 10.553 14.8318 10.5615 14.4466 10.9572L11.5488 13.9338C11.1636 14.3295 11.1721 14.9626 11.5678 15.3479C11.9635 15.7331 12.5967 15.7246 12.9819 15.3289L14.1631 14.1156L14.1631 22.4886C11.8522 22.2016 9.83646 20.9704 8.51594 19.193C8.18658 18.7496 7.56019 18.6573 7.11686 18.9866C6.67354 19.316 6.58115 19.9424 6.91051 20.3857C8.78779 22.9126 11.8036 24.5526 15.2025 24.5526C20.8938 24.5526 25.5139 19.9553 25.5139 14.2763C25.5139 8.5973 20.8938 4 15.2025 4C9.92471 4 5.56807 7.95358 4.96291 13.057L3.69755 11.8252C3.30182 11.44 2.66871 11.4485 2.28347 11.8442C1.89822 12.2399 1.90672 12.873 2.30245 13.2583L5.27901 16.156C5.67474 16.5412 6.30785 16.5327 6.6931 16.137L9.59081 13.1604C9.97606 12.7647 9.96756 12.1316 9.57183 11.7464C9.1761 11.3611 8.54299 11.3696 8.15774 11.7653L6.99589 12.9588Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Retail And Ecommerce.svg b/assets/icons/polkadot/solid/Retail And Ecommerce.svg
new file mode 100644
index 00000000..d249011b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Retail And Ecommerce.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Robust System.svg b/assets/icons/polkadot/solid/Robust System.svg
new file mode 100644
index 00000000..4ddcfb2a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Robust System.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Rust.svg b/assets/icons/polkadot/solid/Rust.svg
new file mode 100644
index 00000000..884a5612
--- /dev/null
+++ b/assets/icons/polkadot/solid/Rust.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Save.svg b/assets/icons/polkadot/solid/Save.svg
new file mode 100644
index 00000000..c6ac3bc8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Save.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M9.57141 1H2C1.44772 1 1 1.44771 1 2V9.57143H9.57141V1ZM1 11.5714H10.5714C11.1237 11.5714 11.5714 11.1237 11.5714 10.5714V1H18.3436C18.6023 1 18.8508 1.10021 19.0372 1.2796L26.6936 8.6507C26.8894 8.83921 27 9.0993 27 9.3711L27 26C27 26.5523 26.5523 27 26 27L2 27C1.44772 27 1 26.5523 1 26V11.5714ZM13.7143 19.1431C14.8189 19.1431 15.7143 18.2476 15.7143 17.1431C15.7143 16.0385 14.8189 15.1431 13.7143 15.1431C12.6097 15.1431 11.7143 16.0385 11.7143 17.1431C11.7143 18.2476 12.6097 19.1431 13.7143 19.1431ZM17.7143 17.1431C17.7143 19.3522 15.9234 21.1431 13.7143 21.1431C11.5052 21.1431 9.71429 19.3522 9.71429 17.1431C9.71429 14.9339 11.5052 13.1431 13.7143 13.1431C15.9234 13.1431 17.7143 14.9339 17.7143 17.1431Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Scalability.svg b/assets/icons/polkadot/solid/Scalability.svg
new file mode 100644
index 00000000..5bb71a91
--- /dev/null
+++ b/assets/icons/polkadot/solid/Scalability.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Scale.svg b/assets/icons/polkadot/solid/Scale.svg
new file mode 100644
index 00000000..5e36dd08
--- /dev/null
+++ b/assets/icons/polkadot/solid/Scale.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Scaling.svg b/assets/icons/polkadot/solid/Scaling.svg
new file mode 100644
index 00000000..190e28c6
--- /dev/null
+++ b/assets/icons/polkadot/solid/Scaling.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Scam Alert.svg b/assets/icons/polkadot/solid/Scam Alert.svg
new file mode 100644
index 00000000..0a0081a3
--- /dev/null
+++ b/assets/icons/polkadot/solid/Scam Alert.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Search.svg b/assets/icons/polkadot/solid/Search.svg
new file mode 100644
index 00000000..39324cde
--- /dev/null
+++ b/assets/icons/polkadot/solid/Search.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Second A Proposal.svg b/assets/icons/polkadot/solid/Second A Proposal.svg
new file mode 100644
index 00000000..89c25654
--- /dev/null
+++ b/assets/icons/polkadot/solid/Second A Proposal.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M24.4615 2C24.4615 1.44772 24.0138 1 23.4615 1H5C4.44772 1 4 1.44772 4 2V26C4 26.5523 4.44772 27 5 27H23.4615C24.0138 27 24.4615 26.5523 24.4615 26V2ZM7.69222 5.69189C7.69222 6.24418 8.13993 6.69189 8.69222 6.69189H19.7691C20.3214 6.69189 20.7691 6.24418 20.7691 5.69189C20.7691 5.13961 20.3214 4.69189 19.7691 4.69189H8.69222C8.13993 4.69189 7.69222 5.13961 7.69222 5.69189ZM7.69222 9.38428C7.69222 8.83199 8.13993 8.38428 8.69222 8.38428H19.7692C20.3215 8.38428 20.7692 8.83199 20.7692 9.38428C20.7692 9.93656 20.3215 10.3843 19.7692 10.3843H8.69222C8.13993 10.3843 7.69222 9.93656 7.69222 9.38428ZM20.9699 18.7916C21.3605 18.4011 21.3605 17.7679 20.9699 17.3774C20.5794 16.9868 19.9463 16.9868 19.5557 17.3774L16.963 19.9701L16.3013 19.3085C15.9108 18.9179 15.2777 18.9179 14.8871 19.3085C14.4966 19.699 14.4966 20.3322 14.8871 20.7227L16.2558 22.0914C16.6464 22.4819 17.2795 22.4819 17.6701 22.0914L20.9699 18.7916ZM13.7148 17.3774C14.1053 17.7679 14.1053 18.4011 13.7148 18.7916L10.4149 22.0914C10.0244 22.4819 9.39124 22.4819 9.00071 22.0914L7.632 20.7227C7.24147 20.3322 7.24147 19.699 7.632 19.3085C8.02252 18.9179 8.65568 18.9179 9.04621 19.3085L9.70783 19.9701L12.3006 17.3774C12.6911 16.9868 13.3243 16.9868 13.7148 17.3774Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Secret Part Of The Derivation Path.svg b/assets/icons/polkadot/solid/Secret Part Of The Derivation Path.svg
new file mode 100644
index 00000000..00033427
--- /dev/null
+++ b/assets/icons/polkadot/solid/Secret Part Of The Derivation Path.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14 27C13.4477 27 13 26.5523 13 26L13.0001 23.679C8.45668 23.2064 4.85576 19.5627 4.44931 15L1.99998 14.9999C1.4477 14.9999 0.999986 14.5522 0.999992 13.9999C0.999999 13.4476 1.44772 12.9999 2 12.9999L4.47785 13C5.00169 8.56672 8.54851 5.05945 13.0001 4.59637L13.0001 1.99999C13.0001 1.4477 13.4478 0.999994 14.0001 1C14.5524 1.00001 15.0001 1.44773 15.0001 2.00001L15.0001 4.59548C19.4557 5.05497 23.0067 8.56389 23.5308 13L26 13C26.5523 13 27 13.4477 27 14C27 14.5523 26.5523 15 26 15L23.5594 15C23.1527 19.5656 19.5475 23.211 15.0001 23.6799L15 26C15 26.5523 14.5523 27 14 27ZM13.9986 10.6616C13.7307 10.6621 13.4738 10.7688 13.2843 10.9583C13.0943 11.1483 12.9876 11.4059 12.9876 11.6746V12.3081H15.0057V11.6746C15.0057 11.4066 14.8995 11.1495 14.7104 10.9597C14.5218 10.7703 14.2659 10.6632 13.9986 10.6616ZM10.9876 11.6746V12.3081H10.7906C10.2383 12.3081 9.7906 12.7558 9.7906 13.3081V17.6771C9.7906 18.2293 10.2383 18.6771 10.7906 18.6771H17.2103C17.7626 18.6771 18.2103 18.2293 18.2103 17.6771V13.3081C18.2103 12.7558 17.7626 12.3081 17.2103 12.3081H17.0057V11.6746C17.0057 10.8775 16.6899 10.1129 16.1274 9.54821C15.5648 8.9835 14.8015 8.66471 14.0044 8.66163V8.66162H14.0005C13.2015 8.66162 12.4351 8.97905 11.8701 9.5441C11.305 10.1091 10.9876 10.8755 10.9876 11.6746ZM11.7906 14.3081V16.6771H16.2103V14.3081H11.7906Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Secure Device.svg b/assets/icons/polkadot/solid/Secure Device.svg
new file mode 100644
index 00000000..db4a168a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Secure Device.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M5 2C5 1.44772 5.44772 1 6 1H22.5109C23.0632 1 23.5109 1.44772 23.5109 2V26C23.5109 26.5523 23.0632 27 22.5109 27H6C5.44772 27 5 26.5523 5 26V2ZM13.3755 7.3776C13.6083 7.14473 13.924 7.0137 14.2533 7.01319C14.5818 7.01496 14.8962 7.14654 15.1281 7.37929C15.3603 7.61248 15.4908 7.92822 15.4908 8.25738V9.07715H13.011V8.25738C13.011 7.92739 13.1421 7.61093 13.3755 7.3776ZM17.4908 8.25738V9.18749C18.2727 9.45924 18.834 10.2027 18.834 11.0771V13.948C18.834 15.0525 17.9385 15.948 16.834 15.948H11.6768C10.5723 15.948 9.67682 15.0525 9.67682 13.948V11.0771C9.67682 10.206 10.2338 9.46494 11.011 9.19064V8.25738C11.011 7.39697 11.3528 6.57179 11.9612 5.96339C12.5697 5.35498 13.3948 5.01318 14.2552 5.01318H14.2591C15.1174 5.0165 15.9393 5.35977 16.545 5.96781C17.1507 6.57586 17.4908 7.39914 17.4908 8.25738ZM13.3055 21.7124C12.7532 21.7124 12.3055 22.1601 12.3055 22.7124C12.3055 23.2647 12.7532 23.7124 13.3055 23.7124H15.2053C15.7576 23.7124 16.2053 23.2647 16.2053 22.7124C16.2053 22.1601 15.7576 21.7124 15.2053 21.7124H13.3055ZM16.834 11.0771L11.6768 11.0771V13.948L16.834 13.948L16.834 11.0771Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Security Check.svg b/assets/icons/polkadot/solid/Security Check.svg
new file mode 100644
index 00000000..53fe793c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Security Check.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M13.6513 0.395965C13.8733 0.314661 14.1169 0.314625 14.3389 0.395865L24.9915 4.2941C25.3857 4.43835 25.6478 4.81343 25.6478 5.23319V14.1678C25.6478 17.9063 23.7491 21.3889 20.6067 23.414L14.4694 27.3693C14.1396 27.5818 13.716 27.5819 13.3862 27.3694L7.39544 23.5104C4.25188 21.4855 2.35229 18.0022 2.35229 14.2629V5.23319C2.35229 4.81354 2.61431 4.43853 3.00837 4.2942L13.6513 0.395965ZM13.998 9.42188C13.5385 9.42239 13.098 9.60513 12.7731 9.93006C12.4477 10.2554 12.2649 10.6967 12.2649 11.1569V11.498H15.7244V11.1569C15.7244 10.6979 15.5425 10.2576 15.2186 9.93241C14.8951 9.60767 14.4563 9.42415 13.998 9.42188ZM10.2649 11.1569V11.498H9.63867C9.08639 11.498 8.63867 11.9458 8.63867 12.498V17.9998C8.63867 18.5521 9.08639 18.9998 9.63867 18.9998H18.3612C18.9135 18.9998 19.3612 18.5521 19.3612 17.9998V12.498C19.3612 11.9458 18.9135 11.498 18.3612 11.498H17.7244V11.1569C17.7244 10.1688 17.3329 9.22098 16.6355 8.52093C15.9382 7.82089 14.9919 7.42569 14.0038 7.42188H13.9999C13.0093 7.42188 12.0593 7.81538 11.3589 8.51584C10.6584 9.2163 10.2649 10.1663 10.2649 11.1569ZM10.6387 13.498V16.9998H17.3612V13.498H10.6387Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Seed Phrase.svg b/assets/icons/polkadot/solid/Seed Phrase.svg
new file mode 100644
index 00000000..cf0c9698
--- /dev/null
+++ b/assets/icons/polkadot/solid/Seed Phrase.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M17.6897 11C18.242 11 18.6897 10.5523 18.6897 10C18.6897 9.44771 18.242 9 17.6897 9L7.68974 9.00002C7.13745 9.00002 6.68974 9.44774 6.68974 10C6.68974 10.5523 7.13746 11 7.68974 11L17.6897 11ZM3.68974 9.00001C4.24203 9.00001 4.68974 9.44773 4.68974 10C4.68974 10.5523 4.24203 11 3.68974 11L2 11C1.44771 11 1 10.5523 1 10C1 9.44773 1.44772 9.00001 2 9.00001L3.68974 9.00001ZM22 14.2622C22 13.7099 21.5522 13.2622 21 13.2622L12 13.2622C11.4477 13.2622 11 13.7099 11 14.2622C11 14.8145 11.4477 15.2622 12 15.2622L21 15.2622C21.5522 15.2622 22 14.8145 22 14.2622ZM8.99997 14.2622C8.99997 13.7099 8.55225 13.2622 7.99997 13.2622L2 13.2622C1.44771 13.2622 1 13.7099 1 14.2622C1 14.8145 1.44772 15.2622 2 15.2622L7.99997 15.2622C8.55225 15.2622 8.99997 14.8145 8.99997 14.2622ZM26 13.2622C26.5522 13.2622 27 13.7099 27 14.2622C27 14.8145 26.5523 15.2622 26 15.2622L25 15.2622C24.4477 15.2622 24 14.8145 24 14.2622C24 13.7099 24.4477 13.2622 25 13.2622L26 13.2622ZM7 18.5244C7 17.9721 6.55228 17.5244 6 17.5244L2 17.5244C1.44772 17.5244 1 17.9721 1 18.5244C1 19.0767 1.44771 19.5244 2 19.5244L6 19.5244C6.55228 19.5244 7 19.0767 7 18.5244ZM12 17.5244C12.5523 17.5244 13 17.9721 13 18.5244C13 19.0767 12.5523 19.5244 12 19.5244L10 19.5244C9.44771 19.5244 9 19.0767 9 18.5244C9 17.9721 9.44772 17.5244 10 17.5244L12 17.5244ZM27 18.5244C27 17.9721 26.5523 17.5244 26 17.5244L16 17.5244C15.4477 17.5244 15 17.9721 15 18.5244C15 19.0767 15.4477 19.5244 16 19.5244L26 19.5244C26.5523 19.5244 27 19.0767 27 18.5244ZM26.6897 10C26.6897 9.44774 26.242 9.00003 25.6897 9.00003L21.6897 9.00003C21.1374 9.00003 20.6897 9.44774 20.6897 10C20.6897 10.5523 21.1374 11 21.6897 11L25.6897 11C26.242 11 26.6897 10.5523 26.6897 10Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Select List Item.svg b/assets/icons/polkadot/solid/Select List Item.svg
new file mode 100644
index 00000000..76de60f2
--- /dev/null
+++ b/assets/icons/polkadot/solid/Select List Item.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14 1C6.8203 1 1 6.8203 1 14C1 21.1797 6.8203 27 14 27C21.1797 27 27 21.1797 27 14C27 6.8203 21.1797 1 14 1Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Session.svg b/assets/icons/polkadot/solid/Session.svg
new file mode 100644
index 00000000..6094fe12
--- /dev/null
+++ b/assets/icons/polkadot/solid/Session.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Settings.svg b/assets/icons/polkadot/solid/Settings.svg
new file mode 100644
index 00000000..fa1b0fcd
--- /dev/null
+++ b/assets/icons/polkadot/solid/Settings.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Sharding.svg b/assets/icons/polkadot/solid/Sharding.svg
new file mode 100644
index 00000000..0d67459c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Sharding.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Share.svg b/assets/icons/polkadot/solid/Share.svg
new file mode 100644
index 00000000..2925031b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Share.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 23 27" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M18.4764 0.511719C16.3933 0.511719 14.7046 2.20042 14.7046 4.28354C14.7046 4.70787 14.7747 5.11584 14.9039 5.49651L8.55526 9.94185C6.70529 8.15245 3.75494 8.17121 1.92803 9.99811C0.0821761 11.844 0.0821764 14.8367 1.92803 16.6826C3.74371 18.4982 6.66905 18.5279 8.52101 16.7716L14.989 21.3006C14.8057 21.7441 14.7046 22.2303 14.7046 22.7401C14.7046 24.8232 16.3933 26.5119 18.4764 26.5119C20.5595 26.5119 22.2482 24.8232 22.2482 22.7401C22.2482 20.657 20.5595 18.9683 18.4764 18.9683C17.6292 18.9683 16.8472 19.2476 16.2175 19.7192L9.65008 15.1206C10.1065 13.9965 10.1124 12.7322 9.66782 11.6044L16.0268 7.15176C16.6859 7.71514 17.5414 8.05535 18.4764 8.05535C20.5595 8.05535 22.2482 6.36665 22.2482 4.28354C22.2482 2.20042 20.5595 0.511719 18.4764 0.511719Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Shared Security.svg b/assets/icons/polkadot/solid/Shared Security.svg
new file mode 100644
index 00000000..66433765
--- /dev/null
+++ b/assets/icons/polkadot/solid/Shared Security.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Sign A Transaction.svg b/assets/icons/polkadot/solid/Sign A Transaction.svg
new file mode 100644
index 00000000..4571c6ec
--- /dev/null
+++ b/assets/icons/polkadot/solid/Sign A Transaction.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Sign Specs.svg b/assets/icons/polkadot/solid/Sign Specs.svg
new file mode 100644
index 00000000..ae2123df
--- /dev/null
+++ b/assets/icons/polkadot/solid/Sign Specs.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Sign.svg b/assets/icons/polkadot/solid/Sign.svg
new file mode 100644
index 00000000..70f956e5
--- /dev/null
+++ b/assets/icons/polkadot/solid/Sign.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Signal.svg b/assets/icons/polkadot/solid/Signal.svg
new file mode 100644
index 00000000..4c38048a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Signal.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Signature.svg b/assets/icons/polkadot/solid/Signature.svg
new file mode 100644
index 00000000..a68cef3e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Signature.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Signifier Tab.svg b/assets/icons/polkadot/solid/Signifier Tab.svg
new file mode 100644
index 00000000..8c1c9f54
--- /dev/null
+++ b/assets/icons/polkadot/solid/Signifier Tab.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M1.98828 14.5117C1.98828 13.9594 2.436 13.5117 2.98828 13.5117H26.9883C27.5406 13.5117 27.9883 13.9594 27.9883 14.5117C27.9883 15.064 27.5406 15.5117 26.9883 15.5117H2.98828C2.436 15.5117 1.98828 15.064 1.98828 14.5117Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Smart Contract.svg b/assets/icons/polkadot/solid/Smart Contract.svg
new file mode 100644
index 00000000..f354fc1f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Smart Contract.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Social Impact & Humanitarian.svg b/assets/icons/polkadot/solid/Social Impact & Humanitarian.svg
new file mode 100644
index 00000000..478c39fa
--- /dev/null
+++ b/assets/icons/polkadot/solid/Social Impact & Humanitarian.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Social Networking.svg b/assets/icons/polkadot/solid/Social Networking.svg
new file mode 100644
index 00000000..81bd9637
--- /dev/null
+++ b/assets/icons/polkadot/solid/Social Networking.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Software Development.svg b/assets/icons/polkadot/solid/Software Development.svg
new file mode 100644
index 00000000..5869c504
--- /dev/null
+++ b/assets/icons/polkadot/solid/Software Development.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Specialised.svg b/assets/icons/polkadot/solid/Specialised.svg
new file mode 100644
index 00000000..b396bbce
--- /dev/null
+++ b/assets/icons/polkadot/solid/Specialised.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Stablecoin.svg b/assets/icons/polkadot/solid/Stablecoin.svg
new file mode 100644
index 00000000..1d0e4f97
--- /dev/null
+++ b/assets/icons/polkadot/solid/Stablecoin.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Stake.svg b/assets/icons/polkadot/solid/Stake.svg
new file mode 100644
index 00000000..86041a36
--- /dev/null
+++ b/assets/icons/polkadot/solid/Stake.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Staking.svg b/assets/icons/polkadot/solid/Staking.svg
new file mode 100644
index 00000000..07aad245
--- /dev/null
+++ b/assets/icons/polkadot/solid/Staking.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Starting Period.svg b/assets/icons/polkadot/solid/Starting Period.svg
new file mode 100644
index 00000000..49ffef61
--- /dev/null
+++ b/assets/icons/polkadot/solid/Starting Period.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Success.svg b/assets/icons/polkadot/solid/Success.svg
new file mode 100644
index 00000000..3f391469
--- /dev/null
+++ b/assets/icons/polkadot/solid/Success.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Supply Chain.svg b/assets/icons/polkadot/solid/Supply Chain.svg
new file mode 100644
index 00000000..06a57235
--- /dev/null
+++ b/assets/icons/polkadot/solid/Supply Chain.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Talent.svg b/assets/icons/polkadot/solid/Talent.svg
new file mode 100644
index 00000000..55496879
--- /dev/null
+++ b/assets/icons/polkadot/solid/Talent.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Technical Committee.svg b/assets/icons/polkadot/solid/Technical Committee.svg
new file mode 100644
index 00000000..4f2b918d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Technical Committee.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Teleport.svg b/assets/icons/polkadot/solid/Teleport.svg
new file mode 100644
index 00000000..75a745a1
--- /dev/null
+++ b/assets/icons/polkadot/solid/Teleport.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Testnet Token.svg b/assets/icons/polkadot/solid/Testnet Token.svg
new file mode 100644
index 00000000..7e0d03a4
--- /dev/null
+++ b/assets/icons/polkadot/solid/Testnet Token.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Thumbs Down.svg b/assets/icons/polkadot/solid/Thumbs Down.svg
new file mode 100644
index 00000000..587e135b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Thumbs Down.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Thumbs Up.svg b/assets/icons/polkadot/solid/Thumbs Up.svg
new file mode 100644
index 00000000..ab57e5b2
--- /dev/null
+++ b/assets/icons/polkadot/solid/Thumbs Up.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Time.svg b/assets/icons/polkadot/solid/Time.svg
new file mode 100644
index 00000000..8111e271
--- /dev/null
+++ b/assets/icons/polkadot/solid/Time.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Token Holders.svg b/assets/icons/polkadot/solid/Token Holders.svg
new file mode 100644
index 00000000..e7f0f99b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Token Holders.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Token.svg b/assets/icons/polkadot/solid/Token.svg
new file mode 100644
index 00000000..1843210f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Token.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Tools.svg b/assets/icons/polkadot/solid/Tools.svg
new file mode 100644
index 00000000..9fbfe13c
--- /dev/null
+++ b/assets/icons/polkadot/solid/Tools.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Transaction.svg b/assets/icons/polkadot/solid/Transaction.svg
new file mode 100644
index 00000000..d0978ead
--- /dev/null
+++ b/assets/icons/polkadot/solid/Transaction.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Translate.svg b/assets/icons/polkadot/solid/Translate.svg
new file mode 100644
index 00000000..9be868f1
--- /dev/null
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diff --git a/assets/icons/polkadot/solid/Transparency.svg b/assets/icons/polkadot/solid/Transparency.svg
new file mode 100644
index 00000000..66baf79d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Transparency.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Treasury.svg b/assets/icons/polkadot/solid/Treasury.svg
new file mode 100644
index 00000000..3093cb09
--- /dev/null
+++ b/assets/icons/polkadot/solid/Treasury.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Twitter.svg b/assets/icons/polkadot/solid/Twitter.svg
new file mode 100644
index 00000000..029cf30b
--- /dev/null
+++ b/assets/icons/polkadot/solid/Twitter.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Ui.svg b/assets/icons/polkadot/solid/Ui.svg
new file mode 100644
index 00000000..243a8387
--- /dev/null
+++ b/assets/icons/polkadot/solid/Ui.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Unbond.svg b/assets/icons/polkadot/solid/Unbond.svg
new file mode 100644
index 00000000..62e35383
--- /dev/null
+++ b/assets/icons/polkadot/solid/Unbond.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Unchecked.svg b/assets/icons/polkadot/solid/Unchecked.svg
new file mode 100644
index 00000000..58b92d19
--- /dev/null
+++ b/assets/icons/polkadot/solid/Unchecked.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Unlock.svg b/assets/icons/polkadot/solid/Unlock.svg
new file mode 100644
index 00000000..130a1f8f
--- /dev/null
+++ b/assets/icons/polkadot/solid/Unlock.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Unstake.svg b/assets/icons/polkadot/solid/Unstake.svg
new file mode 100644
index 00000000..8e74d2de
--- /dev/null
+++ b/assets/icons/polkadot/solid/Unstake.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Upgrade.svg b/assets/icons/polkadot/solid/Upgrade.svg
new file mode 100644
index 00000000..7918ea07
--- /dev/null
+++ b/assets/icons/polkadot/solid/Upgrade.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Use Cases.svg b/assets/icons/polkadot/solid/Use Cases.svg
new file mode 100644
index 00000000..6b38e4b6
--- /dev/null
+++ b/assets/icons/polkadot/solid/Use Cases.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Users.svg b/assets/icons/polkadot/solid/Users.svg
new file mode 100644
index 00000000..edf44e2d
--- /dev/null
+++ b/assets/icons/polkadot/solid/Users.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M18.4468 2.41515C15.9897 -0.0465857 12.001 -0.0465854 9.54379 2.41515C7.24884 4.71435 7.08245 8.38301 9.15985 10.8805L10.1835 12.1112C10.3733 12.3394 10.2646 12.6874 9.97867 12.767L8.59494 13.1521C4.36911 14.3281 1.44531 18.1767 1.44531 22.5631V26.3709C1.44531 26.9232 1.89303 27.3709 2.44531 27.3709H25.5547C26.107 27.3709 26.5547 26.9232 26.5547 26.3709V22.5697C26.5547 18.1799 23.6282 14.3284 19.3988 13.1523L18.0122 12.7667C17.7263 12.6871 17.6175 12.3391 17.8073 12.111L18.8308 10.8805C20.9082 8.38301 20.7418 4.71435 18.4468 2.41515Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Utility.svg b/assets/icons/polkadot/solid/Utility.svg
new file mode 100644
index 00000000..ff4a5571
--- /dev/null
+++ b/assets/icons/polkadot/solid/Utility.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Ux.svg b/assets/icons/polkadot/solid/Ux.svg
new file mode 100644
index 00000000..d8def508
--- /dev/null
+++ b/assets/icons/polkadot/solid/Ux.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M5.91705 2C5.91705 1.44772 6.36477 1 6.91705 1H21.5025C22.0548 1 22.5025 1.44772 22.5025 2V6.9637C22.5025 7.51598 22.0548 7.9637 21.5025 7.9637H14.9297V11.1343H23.3961C23.6613 11.1343 23.9156 11.2396 24.1032 11.4272C24.2907 11.6147 24.3961 11.8691 24.3961 12.1343V15.2046H25.9127C26.465 15.2046 26.9127 15.6523 26.9127 16.2046V21.1022C26.9127 21.6545 26.465 22.1022 25.9127 22.1022H20.9956C20.4433 22.1022 19.9956 21.6545 19.9956 21.1022V16.2046C19.9956 15.6523 20.4433 15.2046 20.9956 15.2046H22.3961V13.1343H14.9297V20.1025H16.3883C16.9405 20.1025 17.3883 20.5503 17.3883 21.1025V26.0002C17.3883 26.5525 16.9405 27.0002 16.3883 27.0002H11.4712C10.9189 27.0002 10.4712 26.5525 10.4712 26.0002V21.1025C10.4712 20.5503 10.9189 20.1025 11.4712 20.1025H12.9297V13.1343L5.46361 13.1343V15.2046H6.91706C7.46935 15.2046 7.91706 15.6523 7.91706 16.2046V21.1022C7.91706 21.6545 7.46935 22.1022 6.91706 22.1022H2C1.44772 22.1022 1 21.6545 1 21.1022V16.2046C1 15.6523 1.44772 15.2046 2 15.2046H3.46361V12.1343C3.46361 11.582 3.91133 11.1343 4.46361 11.1343L12.9297 11.1343V7.9637H6.91705C6.36477 7.9637 5.91705 7.51598 5.91705 6.9637V2Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Validators.svg b/assets/icons/polkadot/solid/Validators.svg
new file mode 100644
index 00000000..adba7d49
--- /dev/null
+++ b/assets/icons/polkadot/solid/Validators.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14 1C6.8203 1 1 6.8203 1 14C1 21.1797 6.8203 27 14 27C21.1797 27 27 21.1797 27 14C27 10.8876 25.9062 8.03061 24.0821 5.79253L13.8588 19.3007C13.6886 19.5255 13.4315 19.6681 13.1507 19.6933C12.8699 19.7184 12.5915 19.6239 12.3841 19.433L7.36136 14.8093C6.95503 14.4353 6.92885 13.8026 7.3029 13.3963C7.67695 12.99 8.30957 12.9638 8.71591 13.3378L12.9285 17.2158L22.684 4.32572C23.187 4.77755 23.6546 5.26805 24.0821 5.79253L26.1748 3.02736C26.5081 2.58698 26.4213 1.95979 25.9809 1.6265C25.5405 1.29321 24.9133 1.38003 24.5801 1.82041L22.684 4.32572C20.382 2.25799 17.3379 1 14 1Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Value Bearing Token.svg b/assets/icons/polkadot/solid/Value Bearing Token.svg
new file mode 100644
index 00000000..354fc621
--- /dev/null
+++ b/assets/icons/polkadot/solid/Value Bearing Token.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14 3.76367H14.0051L13.9995 3.76377L13.994 3.76367H14ZM9.92401 15.0148V4.21024C8.05101 4.63362 6.35769 5.34319 4.96017 6.27487C2.60981 7.84178 1 10.1162 1 12.7637C1 12.9282 1.00621 13.0912 1.01843 13.2527C1.00634 13.3149 1 13.3791 1 13.4448V16.7498C1 19.4167 2.63154 21.5714 4.99452 23.0107C7.35555 24.4488 10.5453 25.2498 14 25.2498C17.4547 25.2498 20.6445 24.4488 23.0055 23.0107C25.3685 21.5714 27 19.4167 27 16.7498V13.4448C27 13.3791 26.9937 13.3149 26.9816 13.2527C26.9938 13.0912 27 12.9282 27 12.7637C27 10.1162 25.3902 7.84178 23.0398 6.27487C21.6421 5.34303 19.9484 4.63337 18.075 4.21002V15.0078C18.075 15.3434 17.9067 15.6566 17.6267 15.8418C17.3468 16.027 16.9927 16.0594 16.6838 15.9281L13.9992 14.7869L11.3173 15.9342C11.0084 16.0663 10.6537 16.0345 10.3732 15.8494C10.0928 15.6644 9.92401 15.3508 9.92401 15.0148ZM24.8932 17.7013C24.3536 18.2735 23.7285 18.7934 23.0398 19.2525C20.6824 20.8241 17.4834 21.7637 14 21.7637C10.5166 21.7637 7.31755 20.8241 4.96017 19.2525C4.27152 18.7934 3.64643 18.2735 3.10679 17.7013C3.42047 19.0763 4.4199 20.3189 6.03492 21.3026C8.01704 22.51 10.8273 23.2498 14 23.2498C17.1727 23.2498 19.983 22.51 21.9651 21.3026C23.5801 20.3189 24.5795 19.0763 24.8932 17.7013Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Verified Account.svg b/assets/icons/polkadot/solid/Verified Account.svg
new file mode 100644
index 00000000..03214a89
--- /dev/null
+++ b/assets/icons/polkadot/solid/Verified Account.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Verified Signed.svg b/assets/icons/polkadot/solid/Verified Signed.svg
new file mode 100644
index 00000000..9724e7d7
--- /dev/null
+++ b/assets/icons/polkadot/solid/Verified Signed.svg	
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Verify.svg b/assets/icons/polkadot/solid/Verify.svg
new file mode 100644
index 00000000..72cedcd4
--- /dev/null
+++ b/assets/icons/polkadot/solid/Verify.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Version.svg b/assets/icons/polkadot/solid/Version.svg
new file mode 100644
index 00000000..f21f6c8a
--- /dev/null
+++ b/assets/icons/polkadot/solid/Version.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Vesting Period.svg b/assets/icons/polkadot/solid/Vesting Period.svg
new file mode 100644
index 00000000..2f796837
--- /dev/null
+++ b/assets/icons/polkadot/solid/Vesting Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M10.4234 2C10.4234 1.44772 9.97566 1 9.42337 1C8.87109 1 8.42337 1.44772 8.42337 2V2.88477H2C1.44772 2.88477 1 3.33248 1 3.88477V26.0002C1 26.5525 1.44772 27.0002 2 27.0002H26C26.5523 27.0002 27 26.5525 27 26.0002V3.88477C27 3.33248 26.5523 2.88477 26 2.88477H19.5764V6.34177C19.5764 6.89405 19.1287 7.34177 18.5764 7.34177C18.0241 7.34177 17.5764 6.89405 17.5764 6.34177V2.88477H10.4234V2ZM17.5764 2.88184H19.5764V2C19.5764 1.44772 19.1287 1 18.5764 1C18.0241 1 17.5764 1.44772 17.5764 2V2.88184ZM10.4234 6.34156C10.4234 6.89384 9.97565 7.34156 9.42337 7.34156C8.87109 7.34156 8.42337 6.89384 8.42337 6.34156V2.89014H10.4234V6.34156ZM9.91542 12C9.91542 9.79086 11.7063 8 13.9154 8H14.0846C16.2938 8 18.0846 9.79086 18.0846 12L18.0846 12.3657H20C20.5523 12.3657 21 12.8134 21 13.3657V22.093C21 22.6453 20.5523 23.093 20 23.093H8C7.44772 23.093 7 22.6453 7 22.093V13.3657C7 12.8134 7.44772 12.3657 8 12.3657H9.91541L9.91542 12ZM16.0846 12L16.0846 12.3657H11.9154L11.9154 12C11.9154 10.8954 12.8108 10 13.9154 10H14.0846C15.1892 10 16.0846 10.8954 16.0846 12ZM9 14.3657V21.093H19V14.3657H9Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/Vesting.svg b/assets/icons/polkadot/solid/Vesting.svg
new file mode 100644
index 00000000..b5f596a3
--- /dev/null
+++ b/assets/icons/polkadot/solid/Vesting.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M10.1211 4.45859C10.1211 2.54846 11.6696 1 13.5797 1C15.4898 1 17.0383 2.54846 17.0383 4.45859V4.47998H18.3618C18.9141 4.47998 19.3618 4.9277 19.3618 5.47998V12.4361C19.3618 12.9884 18.9141 13.4361 18.3618 13.4361H8.79722C8.24493 13.4361 7.79722 12.9884 7.79722 12.4361V5.47998C7.79722 4.9277 8.24493 4.47998 8.79722 4.47998H10.1211L10.1211 4.45859ZM15.0383 4.47998V4.45859C15.0383 3.65304 14.3852 3 13.5797 3C12.7741 3 12.1211 3.65303 12.1211 4.45859V4.47998H15.0383ZM7.00859 19.5502C7.0029 19.4681 7 19.3851 7 19.3012C7 17.8271 7.89614 16.6149 9.09309 15.8169C10.297 15.0142 11.9027 14.5503 13.6264 14.5503C15.3501 14.5503 16.9558 15.0142 18.1597 15.8169C19.3288 16.5963 20.2109 17.7709 20.2513 19.1988C20.2655 19.2937 20.2703 19.3777 20.2727 19.4203L20.2731 19.4285C20.2795 19.5396 20.2833 19.6721 20.2855 19.8117C20.2899 20.0929 20.2884 20.4404 20.2848 20.7804C20.2802 21.2143 20.2725 21.618 20.2672 21.8959L20.2672 21.896C20.2638 22.0733 20.2614 22.1993 20.2614 22.2494C20.2614 23.7235 19.3652 24.9357 18.1683 25.7337C16.9644 26.5364 15.3587 27.0003 13.635 27.0003C11.9113 27.0003 10.3056 26.5364 9.10168 25.7337C7.90473 24.9357 7.00859 23.7235 7.00859 22.2494V19.5502ZM9.10792 22.7954C9.26672 23.2321 9.62139 23.6765 10.2111 24.0697C11.0435 24.6246 12.251 25.0003 13.635 25.0003C15.019 25.0003 16.2265 24.6246 17.0588 24.0697C17.6554 23.6719 18.0115 23.2218 18.1675 22.7801C18.1648 22.7819 18.1621 22.7838 18.1594 22.7856C16.9554 23.5882 15.3498 24.0521 13.6264 24.0521C11.9097 24.0521 10.3102 23.592 9.10792 22.7954Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Video Pause.svg b/assets/icons/polkadot/solid/Video Pause.svg
new file mode 100644
index 00000000..4569b218
--- /dev/null
+++ b/assets/icons/polkadot/solid/Video Pause.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M14.9883 1.07422C7.80858 1.07422 1.98828 6.89452 1.98828 14.0742C1.98828 21.2539 7.80858 27.0742 14.9883 27.0742C22.168 27.0742 27.9883 21.2539 27.9883 14.0742C27.9883 6.89452 22.168 1.07422 14.9883 1.07422ZM17.9443 19.3023C18.4966 19.3023 18.9443 18.8546 18.9443 18.3023L18.9443 10.1177C18.9443 9.56539 18.4966 9.11767 17.9443 9.11767C17.3921 9.11766 16.9443 9.56538 16.9443 10.1177L16.9443 18.3023C16.9443 18.8546 17.392 19.3023 17.9443 19.3023ZM12.9883 18.3023C12.9883 18.8546 12.5406 19.3023 11.9883 19.3023C11.436 19.3023 10.9883 18.8546 10.9883 18.3023V10.0742C10.9883 9.52193 11.436 9.07422 11.9883 9.07422C12.5406 9.07422 12.9883 9.52193 12.9883 10.0742V18.3023Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Video Play.svg b/assets/icons/polkadot/solid/Video Play.svg
new file mode 100644
index 00000000..a9fdf6db
--- /dev/null
+++ b/assets/icons/polkadot/solid/Video Play.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 29 29" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M1.98242 14.0742C1.98242 6.89452 7.80272 1.07422 14.9824 1.07422C22.1621 1.07422 27.9824 6.89452 27.9824 14.0742C27.9824 21.2539 22.1621 27.0742 14.9824 27.0742C7.80272 27.0742 1.98242 21.2539 1.98242 14.0742ZM13.4978 9.21722C13.1889 9.03148 12.804 9.02634 12.4902 9.20378C12.1765 9.38122 11.9825 9.71377 11.9825 10.0742V18.3003C11.9825 18.6607 12.1764 18.9932 12.4901 19.1707C12.8038 19.3481 13.1887 19.3431 13.4976 19.1574L20.3393 15.0453C20.6401 14.8645 20.8241 14.5393 20.8242 14.1883C20.8242 13.8374 20.6403 13.5121 20.3395 13.3312L13.4978 9.21722ZM13.9825 16.5325V11.8424L17.8833 14.188L13.9825 16.5325Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Video.svg b/assets/icons/polkadot/solid/Video.svg
new file mode 100644
index 00000000..253380f6
--- /dev/null
+++ b/assets/icons/polkadot/solid/Video.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M16.5622 2H12.284L16.7146 6.7998H20.9928L16.5622 2ZM9.56217 2H5.28399L9.71457 6.7998H13.9928L9.56217 2ZM2.56217 2H2C1.44772 2 1 2.44772 1 3V6.7998H6.99276L2.56217 2ZM1 8.7998V24.12C1 24.6723 1.44772 25.12 2 25.12H26C26.5523 25.12 27 24.6723 27 24.12V8.7998H1ZM27 6.7998V3C27 2.44772 26.5523 2 26 2H19.284L23.7146 6.7998H27ZM13.1148 10.8081C12.8079 10.6035 12.4134 10.5844 12.0882 10.7584C11.763 10.9324 11.56 11.2713 11.56 11.6401V19.3201C11.56 19.6889 11.763 20.0278 12.0881 20.2018C12.4132 20.3758 12.8077 20.3568 13.1146 20.1522L18.8746 16.3132C19.1528 16.1277 19.32 15.8155 19.32 15.4812C19.32 15.1468 19.153 14.8346 18.8748 14.6491L13.1148 10.8081ZM13.56 17.4519V13.5089L16.5172 15.4809L13.56 17.4519Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Videos.svg b/assets/icons/polkadot/solid/Videos.svg
new file mode 100644
index 00000000..afca29ef
--- /dev/null
+++ b/assets/icons/polkadot/solid/Videos.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M5.13812 3C5.13812 2.44772 5.58584 2 6.13812 2H26.0002C26.5525 2 27.0002 2.44772 27.0002 3V20.4786C27.0002 21.0309 26.5525 21.4786 26.0002 21.4786H22.8621V24.6163C22.8621 25.1686 22.4144 25.6163 21.8621 25.6163H2C1.44772 25.6163 1 25.1686 1 24.6163V12.1104H22.8621V19.4786H25.0002V4H13.9996H7.13812V6.1377H7.67284L11.2 10.1104H7.8536C7.82313 10.0606 7.78786 10.0128 7.74777 9.96763L4.34736 6.1377H5.13812V3ZM1.71059 6.18021C1.29942 6.30433 1 6.68605 1 7.1377V10.1104H5.19995L1.71059 6.18021ZM10.3474 6.1377L13.7478 9.96763C13.7879 10.0128 13.8231 10.0606 13.8536 10.1104H17.2L13.6728 6.1377H10.3474ZM16.3474 6.1377L19.7478 9.96763C19.7879 10.0128 19.8231 10.0606 19.8536 10.1104H22.8621V7.1377C22.8621 6.58541 22.4144 6.1377 21.8621 6.1377H16.3474ZM11.2942 13.4561C10.9873 13.2515 10.5928 13.2324 10.2676 13.4064C9.94239 13.5804 9.73938 13.9193 9.73938 14.2881V20.6439C9.73938 21.0127 9.94234 21.3516 10.2675 21.5256C10.5926 21.6996 10.9871 21.6806 11.294 21.4761L16.0609 18.2989C16.3391 18.1135 16.5062 17.8012 16.5063 17.4669C16.5063 17.1325 16.3392 16.8203 16.0611 16.6348L11.2942 13.4561ZM11.7394 18.7757V16.1569L13.7035 17.4666L11.7394 18.7757Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Vote.svg b/assets/icons/polkadot/solid/Vote.svg
new file mode 100644
index 00000000..87203d49
--- /dev/null
+++ b/assets/icons/polkadot/solid/Vote.svg
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M3.78712 12.8541C3.3966 13.2447 3.3966 13.8778 3.78712 14.2684L8.26325 18.7445H2C1.44772 18.7445 1 19.1922 1 19.7445V25.9998C1 26.5521 1.44772 26.9998 2 26.9998C2.55228 26.9998 3 26.5521 3 25.9998V20.7445H10.6088C10.6324 20.7462 10.6562 20.747 10.68 20.747L15.0523 20.747C15.0762 20.747 15.0999 20.7462 15.1236 20.7445H25.4885V25.9998C25.4885 26.5521 25.9363 26.9998 26.4885 26.9998C27.0408 26.9998 27.4885 26.5521 27.4885 25.9998V19.7445C27.4885 19.1922 27.0408 18.7445 26.4885 18.7445H17.4691L25.1345 11.079C25.525 10.6885 25.525 10.0554 25.1345 9.66483L16.7626 1.29289C16.3721 0.902369 15.7389 0.902369 15.3484 1.29289L3.78712 12.8541ZM14.5448 7.9683C14.5842 7.41742 15.0628 7.00283 15.6137 7.04228C16.1645 7.08173 16.5791 7.56028 16.5397 8.11115L16.0893 14.4002C16.0505 14.9415 15.5872 15.3531 15.0452 15.3277L12.5897 15.213C12.038 15.1872 11.6117 14.7191 11.6375 14.1674C11.6633 13.6157 12.1314 13.1894 12.6831 13.2152L14.1641 13.2844L14.5448 7.9683Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Voting Period.svg b/assets/icons/polkadot/solid/Voting Period.svg
new file mode 100644
index 00000000..22bc480e
--- /dev/null
+++ b/assets/icons/polkadot/solid/Voting Period.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M10.4234 2C10.4234 1.44772 9.97566 1 9.42337 1C8.87109 1 8.42337 1.44772 8.42337 2V2.88477H2C1.44772 2.88477 1 3.33248 1 3.88477V26.0002C1 26.5525 1.44772 27.0002 2 27.0002H26C26.5523 27.0002 27 26.5525 27 26.0002V3.88477C27 3.33248 26.5523 2.88477 26 2.88477H19.5764V6.34177C19.5764 6.89405 19.1287 7.34177 18.5764 7.34177C18.0241 7.34177 17.5764 6.89405 17.5764 6.34177V2.88477H10.4234V2ZM17.5764 2.88184H19.5764V2C19.5764 1.44772 19.1287 1 18.5764 1C18.0241 1 17.5764 1.44772 17.5764 2V2.88184ZM9.42337 7.34156C9.97565 7.34156 10.4234 6.89384 10.4234 6.34156V2.89014H8.42337V6.34156C8.42337 6.89384 8.87109 7.34156 9.42337 7.34156ZM5.93866 18.3521C5.54813 17.9616 5.54813 17.3284 5.93866 16.9379L14.5837 8.29291C14.9742 7.90238 15.6074 7.90238 15.9979 8.29291L22.2581 14.5531C22.6486 14.9436 22.6486 15.5768 22.2581 15.9673L17.0525 21.1729H21.5273C22.0796 21.1729 22.5273 21.6206 22.5273 22.1729C22.5273 22.7251 22.0796 23.1729 21.5273 23.1729H14.6898C14.6722 23.1738 14.6546 23.1742 14.6369 23.1742H11.175C11.1573 23.1742 11.1397 23.1738 11.1221 23.1729H6C5.44772 23.1729 5 22.7251 5 22.1729C5 21.6206 5.44772 21.1729 6 21.1729H8.75938L5.93866 18.3521ZM20.1367 15.2602L14.2241 21.1729L11.5878 21.1729L8.05998 17.645L15.2908 10.4142L20.1367 15.2602Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Wallet Deposit.svg b/assets/icons/polkadot/solid/Wallet Deposit.svg
new file mode 100644
index 00000000..6663bba7
--- /dev/null
+++ b/assets/icons/polkadot/solid/Wallet Deposit.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M4 2C4 1.44772 4.44772 1 5 1H23.9449C24.4972 1 24.9449 1.44772 24.9449 2V5.25391H17.2704C14.6602 5.25391 12.5443 7.36987 12.5443 9.98004C12.5443 12.5902 14.6602 14.7062 17.2704 14.7062H24.9449V17.9603C24.9449 18.5126 24.4972 18.9603 23.9449 18.9603H15.0732V23.5206L16.4928 22.0471C16.876 21.6494 17.509 21.6376 17.9068 22.0208C18.3045 22.404 18.3163 23.037 17.9331 23.4348L14.7933 26.6937C14.6048 26.8895 14.3446 27 14.0728 26.9999C13.8009 26.9998 13.5409 26.889 13.3524 26.6931L10.2181 23.4341C9.83524 23.0361 9.84758 22.403 10.2456 22.0202C10.6437 21.6374 11.2767 21.6497 11.6596 22.0478L13.0732 23.5176V18.9603H5C4.44772 18.9603 4 18.5126 4 17.9603V2ZM17.2704 7.25391H24.9449V12.7062H17.2704C15.7648 12.7062 14.5443 11.4856 14.5443 9.98004C14.5443 8.47444 15.7648 7.25391 17.2704 7.25391ZM17.7071 9.29289C17.3166 8.90237 16.6834 8.90237 16.2929 9.29289C15.9024 9.68342 15.9024 10.3166 16.2929 10.7071L16.311 10.7252C16.7016 11.1158 17.3347 11.1158 17.7252 10.7252C18.1158 10.3347 18.1158 9.70156 17.7252 9.31103L17.7071 9.29289Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Wallet Withdraw.svg b/assets/icons/polkadot/solid/Wallet Withdraw.svg
new file mode 100644
index 00000000..c880c6e2
--- /dev/null
+++ b/assets/icons/polkadot/solid/Wallet Withdraw.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M17.1667 5.93513C17.5495 6.33319 18.1826 6.34553 18.5806 5.96269C18.9787 5.57985 18.991 4.94681 18.6082 4.54875L15.4902 1.30681C15.3018 1.11089 15.0417 1.00012 14.7699 1C14.4981 0.999883 14.2379 1.11043 14.0493 1.30619L10.926 4.54812C10.5428 4.94585 10.5546 5.57891 10.9523 5.96209C11.35 6.34527 11.9831 6.33348 12.3663 5.93575L13.7695 4.47927V9.12305H4.99995C4.44767 9.12305 3.99995 9.57076 3.99995 10.123V25.9999C3.99995 26.5522 4.44767 26.9999 4.99995 26.9999H23.8458C24.3981 26.9999 24.8458 26.5522 24.8458 25.9999V22.7683H17.2061C14.6067 22.7683 12.4995 20.6611 12.4995 18.0616C12.4995 15.4622 14.6067 13.355 17.2061 13.355H24.8458V10.123C24.8458 9.57076 24.3981 9.12305 23.8458 9.12305H15.7695V4.48236L17.1667 5.93513ZM24.8458 15.355H17.2061C15.7113 15.355 14.4995 16.5668 14.4995 18.0616C14.4995 19.5565 15.7113 20.7683 17.2061 20.7683H24.8458V15.355ZM16.2929 17.2929C16.6834 16.9024 17.3166 16.9024 17.7071 17.2929L17.7252 17.311C18.1158 17.7016 18.1158 18.3347 17.7252 18.7252C17.3347 19.1158 16.7016 19.1158 16.311 18.7252L16.2929 18.7071C15.9024 18.3166 15.9024 17.6834 16.2929 17.2929Z" stroke="none"></path></svg>
\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Wallet.svg b/assets/icons/polkadot/solid/Wallet.svg
new file mode 100644
index 00000000..dc25cc84
--- /dev/null
+++ b/assets/icons/polkadot/solid/Wallet.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Wallets.svg b/assets/icons/polkadot/solid/Wallets.svg
new file mode 100644
index 00000000..9e738ce6
--- /dev/null
+++ b/assets/icons/polkadot/solid/Wallets.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Wasm.svg b/assets/icons/polkadot/solid/Wasm.svg
new file mode 100644
index 00000000..ca37f8ee
--- /dev/null
+++ b/assets/icons/polkadot/solid/Wasm.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Web3.svg b/assets/icons/polkadot/solid/Web3.svg
new file mode 100644
index 00000000..34454550
--- /dev/null
+++ b/assets/icons/polkadot/solid/Web3.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Whitepaper Download.svg b/assets/icons/polkadot/solid/Whitepaper Download.svg
new file mode 100644
index 00000000..64cbabf8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Whitepaper Download.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Whitepaper Upload.svg b/assets/icons/polkadot/solid/Whitepaper Upload.svg
new file mode 100644
index 00000000..57dd7bc8
--- /dev/null
+++ b/assets/icons/polkadot/solid/Whitepaper Upload.svg	
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Whitepaper.svg b/assets/icons/polkadot/solid/Whitepaper.svg
new file mode 100644
index 00000000..9ac914e9
--- /dev/null
+++ b/assets/icons/polkadot/solid/Whitepaper.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/WiFi Off.svg b/assets/icons/polkadot/solid/WiFi Off.svg
new file mode 100644
index 00000000..632cf3e0
--- /dev/null
+++ b/assets/icons/polkadot/solid/WiFi Off.svg	
@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 28 28" fill="#e6007a" xmlns="http://www.w3.org/2000/svg" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" stroke="#e6007a"><path fill-rule="evenodd" clip-rule="evenodd" d="M25.737 25.3243C26.1102 25.7314 26.0827 26.364 25.6755 26.7371C25.2684 27.1103 24.6359 27.0828 24.2627 26.6757L14.9375 16.5028C14.6272 16.456 14.3131 16.4326 13.9976 16.4331C13.0752 16.4345 12.1645 16.6404 11.3311 17.0358C10.4977 17.4313 9.76223 18.0065 9.17768 18.7201C8.82772 19.1474 8.19766 19.21 7.77041 18.86C7.34316 18.5101 7.28051 17.88 7.63048 17.4528C8.40229 16.5105 9.3733 15.751 10.4737 15.2289C11.2997 14.837 12.1831 14.5861 13.0875 14.4846L10.2804 11.4223C8.45315 12.0358 6.9503 13.0797 5.97422 14.3514C5.63794 14.7895 5.01018 14.8721 4.57207 14.5358C4.13397 14.1995 4.05142 13.5717 4.3877 13.1336C5.4715 11.7217 7.01036 10.5842 8.82393 9.83346L6.35437 7.1394C5.00293 7.96059 3.78956 8.99622 2.76337 10.2089C2.4066 10.6304 1.77562 10.683 1.35404 10.3262C0.93245 9.96945 0.879903 9.33847 1.23667 8.91688C2.31665 7.64069 3.57915 6.53707 4.9798 5.63986L2.26267 2.67572C1.88948 2.2686 1.91698 1.63603 2.3241 1.26284C2.73122 0.889647 3.36378 0.91715 3.73698 1.32427L6.77592 4.63948C6.83939 4.60909 6.90307 4.57908 6.96695 4.54947C9.17185 3.52758 11.5731 2.9988 14.0033 3C16.4334 3.0012 18.8341 3.53234 21.038 4.55641C23.2419 5.58047 25.196 7.07283 26.764 8.92946C27.1204 9.3514 27.0672 9.98233 26.6453 10.3387C26.2233 10.695 25.5924 10.6419 25.236 10.2199C23.8556 8.58546 22.1354 7.27169 20.1952 6.37016C18.2551 5.46864 16.1417 5.00106 14.0023 5C12.0052 4.99902 10.0303 5.40459 8.19752 6.19032L10.9269 9.16784C11.9121 8.94465 12.9484 8.82625 14.0138 8.82625C18.0049 8.82625 21.5857 10.4876 23.6098 13.0955C23.9484 13.5318 23.8692 14.16 23.433 14.4986C22.9967 14.8372 22.3685 14.7581 22.0298 14.3218C20.4413 12.2751 17.4858 10.8263 14.0138 10.8263C13.5072 10.8263 13.0115 10.8571 12.5295 10.9161L15.9709 14.6704C16.5019 14.8006 17.0201 14.9837 17.5178 15.2179C18.6198 15.7366 19.5932 16.4931 20.3679 17.4329C20.7192 17.859 20.6586 18.4893 20.2324 18.8406C20.1441 18.9134 20.047 18.9685 19.9455 19.0063L25.737 25.3243ZM14.0003 20.8479C12.4369 20.8479 11.1696 22.1153 11.1696 23.6787C11.1696 25.2421 12.4369 26.5094 14.0003 26.5094C15.5637 26.5094 16.8311 25.2421 16.8311 23.6787C16.8311 22.1153 15.5637 20.8479 14.0003 20.8479Z" stroke="none"></path></svg>
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diff --git a/assets/icons/polkadot/solid/WiFi.svg b/assets/icons/polkadot/solid/WiFi.svg
new file mode 100644
index 00000000..9136921c
--- /dev/null
+++ b/assets/icons/polkadot/solid/WiFi.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Wiki.svg b/assets/icons/polkadot/solid/Wiki.svg
new file mode 100644
index 00000000..8422f0a2
--- /dev/null
+++ b/assets/icons/polkadot/solid/Wiki.svg
@@ -0,0 +1 @@
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diff --git a/assets/icons/polkadot/solid/Withdraw.svg b/assets/icons/polkadot/solid/Withdraw.svg
new file mode 100644
index 00000000..1a4079b4
--- /dev/null
+++ b/assets/icons/polkadot/solid/Withdraw.svg
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/assets/icons/polkadot/solid/Workshop.svg b/assets/icons/polkadot/solid/Workshop.svg
new file mode 100644
index 00000000..3a053356
--- /dev/null
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AIzYAFAAAAQGgGLAAAAABCM2ABAAAAEJoBCwAAAIDQDFgAAAAAhGbAAgAAACA0AxYAAAAAoRmwAAAAAAjNgAUAAABAaAYsAAAAAEIzYAEAAAAQmgELAAAAgNAMWAAAAACEZsACAAAAIDQDFgAAAAChGbAAAAAACM2ABQAAAEBoBiwAAAAAQjNgAQAAABCaAQsAAACA0AxYAAAAAIRmwAIAAAAgNAMWAAAAAKEZsAAAAAAIzYAFAAAAQGgGLAAAAABCM2ABAAAAEJoBCwAAAIDQDFgAAAAAhGbAAgAAACA0AxYAAAAAoRmwAAAAAAjNgAUAAABAaAYsAAAAAEIzYAEAAAAQmgELAAAAgNAMWAAAAACEZsACAAAAIDQDFgAAAAChGbAAAAAACM2ABQAAAEBoBiwAAAAAQjNgAQAAABCaAQsAAACA0AxYAAAAAIRmwAIAAAAgNAMWAAAAAKEZsAAAAAAIzYAFAAAAQGgGLAAAAABCM2ABAAAAEJoBCwAAAIDQDFgAAAAAhGbAAgAAACA0AxYAAAAAoRmwAAAAAAjNgAUAAABAaAYsAAAAAEIzYAEAAAAQmgELAAAAgNAMWAAAAACEZsACAAAAIDQDFgAAAAChGbAAAAAACM2ABQAAAEBoBiwAAAAAQjNgAX133GubrQ++ezM9etOKuY5jyuRwfixcfqzS48fkOeuU+Y6fPfv3+lc7Pwbt2Ne4Xi9FJ7zOuQVRGbCAvstvOnfvbqnHLj3/0Y5jyuT4yDmPpj9y7aULz9zccfyYLGsPyVo7tqc/ee2vbVt37zl26fGkvy5oX4O09PrkRVs6XgtADAYsYCAefnBX+vuAFtgN12zrOJ5Mjhuu3pb+yLWXrrlya8fxY7Kc9sZN6Y9dC+iH/7yj41jSf9/4suv1Uuy2W51fEJUBCxiIb13vT+q9dvePd3YcTybHA/cadxfa7T9wEzHpLjnfOxJ76cpLjbvD8MB9rtdLsZ07W3s+Ppq+HoDRM2ABA3HZBVvS3we0wPKP06w5uPOYMv7yX4h9vHbhbd2yu7V6eedxZHKsu9Y7XHrpvSfPdxxL+uuEI1yvl3L5s7DS1wQwegYsYCDe9WYfC1lMM2/Y1HFMGX/5w6pVrLe93pcaTLKf3e8dLkXbtbPlAe5DcN7pnn+1lFv3NY9zgIgMWMBArD3Ug3kX04Xv85e/SXTV5VvTH7X2k3Nhcr3hr7zDpZfuut3HzIfhq1e6Xi/l5pq7W/VK5+sCGC0DFjAwP2n/kq3euvoKzzeZRPmDl1Ws/CYyPY5Mhvf9H+9I7CX/PgzHPXf6HWapl3/JRPq6AEbLgAUMzLVXebZJr/mGqcmTP8tpy2ZvNynaHeu922RSffbjnpXYS+ee5l2Jg5a/O3CXT7cu+T5/mbEYojFgAQNz4ZmeH9Fr85t2dxxPxtvbj/NcuF7atnV3a7UvNZhI373J58yLln/kMn+4eHos6a+z3+HdgfKt0BCRAQsYmLeunUt/F1CBTqx6ePUk+cQHH01/xFpgM8f4GMckamz0FpeiPXDvro7jSP996dOef6WfD8ZvWuF3MYjEgAUMTP7wy/k5H5nqtQ+808dEJsk3r/Nuk1676KxHO44n4+3EVf7A0Uvf+LJvRhuGO2/z/Cv9vI+c498fiMSABQzUv9ziodW99rlLtnQcT8bXww96t0mvfe0qN+2T5rzTfcS8ly440x82Bu3ow5qtHX510S+6Zd32jtcIMDoGLGCgrrzU2/B7zS9Nk+OE1zXTH68KlL8bIj2mjLcvf8a/Db3ko+WD996TPf9K/7+tW3a31h7a+ToBRsOABQzUWaf4RbDX8nfspMeT8fT37/Juk8XkQe6T57bve4tL0TZu8G/CMPjDm9LyUTN9nQCjYcACBuq4w5t7HoKp4uXH7djX+LapSeDdJotv5g0e5D4p8ucjbtnsH4ai5c/RS48l/XfbrcZV/XrXfG5rx+sEGA0DFjBwDz3g2T+99u6T/NVvEtyx3gOBF9tHzvYg3UmRf6ukivexc50Dg7b2kGzPOz6lX+3Bn3r3I0RhwAIG7qav+/a1Xrv0Q25Yxt2ag7PW9m1uiBbbtV/wIPdJkX+rl4r3tqM9/2rQTj/RuKruvXWt8w8iMGABA5ePMOqtG69x0z7u3vVmN0T9yIPcJ8fXv7Qt/fFqP21q7t7z0cv0WNJfn/7olvTQS3u67ALfDA0RGLCAgTvtTW7ge+2eH7tpH3efvMgNUT/avq21591s6fFl/OTXNRXruzd5/tUw3Hqz51+pez/47o6O1wswfAYsYODyrx/e4VOEPbWj/bt0/kyO9JgyPm7+v178/eqUYz3IfdwdNZ21dtqvCpcP4emxpL9WL89am+d93Fvdy38fO+YvfbEOjJoBCxiKu253x9JrbtrH2+wjvsSgX118jmfCjTvPGOqtd77RvwOD9o4TvDa17849bXPH6wYYLgMWMBRfu8ozT3rtorPctI+rt1Tn0h+nFlH+7KT0GDNeLr/AR2qLtnXLbh+fHQKvTe2vG672bxCMmgELGIoLztyc/h6gBXbN57Z2HE/Gw4fO8LrvZ/k7OdNjzHj51vU+Ulu09d/z7J1huGWd16b2XTbryxRg1AxYwFC8dY13ovTabbe6eRlX3nnY3/Jn6Xknynh7+Gc+Ulu0z13i+VeDlo8Sc5nnX2n/veN4H+eFUTJgAUOR/3KYfw24ipc/VNZf/MbT3b5tre+5eRhfxx3ebO32z0Dhzvjb+Y5jSX+97fX+yKaFdcUnDMowSgYsYGi+f4uvp+61/FlK6fEktqOmm75tbQBd/AHPhBtXZ50yn/44tZ/ya8jRh/nms0H7+HmPpode6tqdt/koO4ySAQsYmisv9YDUXvPNN+PnjLe6WR9EHuQ+vvwbUDw3y8PxrW94/pUWVv4u0hNeZ1SGUTFgAUPzfn9977n8xi89nsT22Y+5WR9Ed9/hhn5c3fod78It2pc/40s8hmHjBs9m08K78H3+qAijYsAChsbzT3rvn765veN4Ets/u1kfSDvah3XtoZ3Hm/g8JLt455zqRnnQTqp7/pWK9e0b/E4Go2LAAobqoZ/6K2cvbXhwV8exJK4932jlSwsG1qkneJD7uPkbI0Hh8j/45H/4SY8l/fXhszz/SsV6dPNu34gLI2LAAobqm9d5zkQv5Tcyx7qRGRsnH+VmfZB97FwPch8355+xOf0xaj/df7ePyw7DjddsSw+9tN/efZJvB4VRMGABQ3XJ+f7S2Wvv8cvS2PjI2V7ng+wbX/Eg93Fz9RVb0x+j9tN1X/Q6H4aHHvDOcBXP8+lgNAxYwFC9842b0t8BtMAuu8CD3MfF9V/xF/1Bds+PvTNl3Nyx3jPhipa/ay09jvTXG49spoddWlA/vce/QzAKBixgqNYekrW2u7fvqRu/6q/x4yL/xVaDy4Pcx8vq5Vlr6xbPhCvaiavmOo4l/eWjrVpMb6k5R2HYDFjA0N15m5v7Xrr3Ln/tGwfHvsa3bQ6jU//ag9zHxduP887bovnijuHIP6Yp9donPuh5jDBsBixg6L56pWeh9NKed50c0nk8ieX9p8ynPzoNoI+f58ZhXOQP3Vex1l3rHbfDcL93y2oR3Xrzjo7XFDBYBixg6D7kLfs9l7+TIT2exPL5ywy0w+iGq93gj4v8Z6ViXfwBA+2gHXe4d8tqcW3ftrt19GG+IRqGyYAFDN1J9bn0dwAtsA+f5aYmuvXf87DqYXTPnT5SOy7uv9u7XIp28lGerTNo557mj2lafGe/wzdEwzAZsICRmMv82bOXrrnS1zZHVq9krUc3e20Po507W62jpv3lO7rXv7rZ2mW/KtRcc/eea0l6LOmvq6/wblktvq9/ybuBYZgMWMBI3Pod71Lppdu+73kLkZ1yrIdVD7PT3ugjtdG95yTPhCvaLeu2dxxH+u/uOyyrWnwbN/jCBRgmAxYwEp+7ZEv6O4AW0OZ5f5mPLH+wuIaXb4CK71Mfca0v2uUXbOk4jvSXdwaqn80c448pMCwGLGAk3j/jr/K99paaZ6NE9c3rtqc/Lg2wG6/x0Y3obr7ROVG0U09wMzxovi1W/ezTFxudYVgMWMBIHPsa3/7Ta/mDZ9PjSQwPPbAr/XFpgN33Ew9yj+6Rh50TRdq6ZXdr9cGdx5H++sI/ev6V+tftP/B4BxgWAxYwMg/+1I1NL115qQe5R3TC65rpj0oDLv8IkAe5x+WcKN4PvutGeBjuWO85nOpfu9q/zh73Wv8WwTAYsICR8XGr3vruTR7wG5GvZB9N73qzj1tFdc6pzomiXfEJH0UatKOms9b2bemRlxbX+Wd4dzwMgwELGJlL/sEDr3vpkYd8401EX/6Mj6SMovw6kv4siOGqy50TRXv3SfMdx5H+OuOtnn+l/pf/UTZ9rQH9Z8ACRubUv96U/vuvBZQ/O+zYw71VPRofSRlNN37Vg9yjyj8Op4W3o324jj7MtX3QfAuyBtH8pt2t1cs7X29AfxmwgJFZc3D+Nn5Pcu+l/C/I6fFkdPLX8ratXsuj6P67Pcg9onola83POSeKdMd6r+VhWP89w6oGk4+0w+AZsICRuvO2nem//1pAl1/gOSmRnPYm7yYcVfnDc1//au9aieZv186lPyrtpy99yhd0DFr+DY/5Nz1Kg+gLn3QOw6AZsICRuuZKz0jppXVf87GpSC6/0EdSRtnpJ/qrdzQXnukB7v+PvbPsjuPY2uhfTJw4iYMO2ZbZMsbMFLNMkRlltmOITDIqZmZmRo0Yp98c6ea1U62Zqe5pqO7ee6396a57k1vTajh1zlNOmTOWzlq/lQ4ZAL94dI8uSkS/pYCFiKEqp7aAcx7f5yXJJM+Uc6JmmJQUE+RummU7OObNCa3Zhl/TSei3m5az2QD+IX/Hg36qtF13iOidFLAQMVR/68KYiRuamy2r4HP7emI4vnvTov5EECB0JJon4+HOYFMiGC+eJv8K/GXVPDZUEP2UAhYihm7qPXkUbhjXj7EpExz8C0XYsHn6kI9/k+SADucc2EkR1m9bDxao4roEf7lwstF27SGid1LAQsTQZUfUHcvnsMtngozBhg9B7mY5vj85Q075Y2qNbR3RW8f25boE/5FDArp3tF9/iOiNFLAQMXS3rSGTwg37t3PajQmS9WMGU4bQkWiKa/+oVX8eyMHAH8nN8duSRVyXEAyzRnMgA6JfUsBCxNCdOapaffaDBjevNNnWEoP3/i2yfkxg3eI622+D4SiZZKDPq+cttjVE7z3zN4dtQDCUMRKM6JsUsBAxdHt3SrWe3ALOqKlOt2Z6qOuJwdm9Y8pqYgLWCI4fJHfEFJ895lADJ/zNIQSBWPGOFw0IhtcvKEoj+iUFLEQ0wud88LhCTnFU1xKD8/ehdA+awrNHfDCYYK+v2JBwyvIi8gz9dkQPDtuAYJFrTr0OETF/KWAhohEycuKO+ZMI/g3TLavIbzMFKZpI8UT9jTBYp4+gqOuUYQV86PrtqnnkX0GwbFjKWDuiH1LAQkQjXL2Al0s3bC8hyD1ML5wiU8Ukpv5GcG7YUtR1Rupd2raG6L0yYgwQJDcukVOK6IcUsBDRCMcVcry1G86fIPcnLCV/rDLFrJRJrF/CjnfYnjtOocAJZ8q5hwfhm1fEFECwNDdbVp+v6QpG9FoKWIhohN06VFgN9RQDnCIv5epaYjAOLyBTxTROHKIYELbv31AocEJJMflXfjv4Z+7VEA4LpxDzgOi1FLAQ0RhvX2tWn/2gQd9v2eELw2WzGXs1DTkMQv2dMDgH/UShwClj+1bZ1hG9dcnMGnXZAQKBE0YRvZcCFiIa495t9eqzHzSYNpzcnzA8vIeDB0xDgtx7d6KgG5YLJlMocEJdTdrq+ql9HdFbj3CvhpCorEi3xg2o1yQiupcCFiIaY/HvfPy4gZNuwvHJAzoGTeT3oRR0w7J0E5sQTrh8lpDnIHz+hLFWCI8JA+iyRPRSCliIaIxDfmX8xA3HDtCiHrS9OqWsFr6JjISCbnhev9ik/hyQBTmxUV1D9Nb+P6RaOzMBwoLTohG9lQIWIhpl6j1vmk55fL/Zto7or7NGV6s/AxjCycMEuYehjMnISBzoM2UI3YJ+u3Aqnd0QLg9u846G6KUUsBDRKC+c4gh2p7Q0W1b3jva1RP+UHVUwkxdPCXIPw5E96aB1QlMj9+0gLNtJ/hWEi3QADvyx0nZtIqI7KWAholFuXV2nPvtBg3GFZCwE6dXzjEqZinws9PmaIPeg5VROZ9y6Sv5VEEqHMkDYLJ9Ta7s2EdGdFLAQ0ShnjGQ0yw3Li3g5CkoZlaplVMpoOJkzeA+V0unihF0bycXx2z7fkH8FZnD2GKPtiF5JAQsRjVLCsXnhdE7ZDoLcg3JMnyp1+cEwNi4jHDtoH9yh08UJs8ZQZPXbovHkX4EZSD5gwWf2axQRnUsBCxGN89ljjndzyq0rjKME5eoFjEqZzqkj7HYHqWQ5NTFVq42cYNq7E2Oufrt7C1mFYA7TR1C0RvRCCliIaJx/lzGK4hTZ3ZPRNnUt0XuPHeD6NJ2XzwhyD9JJg+hKdMLDu5xKFoT3btIVCOawdxtjw4heSAELEY2TDhd3DO3CKTdB+PIpHYKmI2PIfb+hwyUo1y3m8A0nMPLtvz2/TFnN1K/AIJ4/YWMF0QspYCGicY7rx26+GxZMrrGtJXprv+/IaIsKjGsE54lDjeryQxYWTuFe7bczR3EgDJjHsG5sNCLmKwUsRDTOrh0qrPo6qgRO2bGO9nS/nTeRUOCosGk5Qe5BSVeiMwZ0pjvQb3euJ/8KzKNkESdGI+YrBSxENNLb10gEdsqFkwRX+23pZj6KosLpcv4eglBGNelK1OfFU8aIgvDmFd4hwDyunufAHcR8pYCFiEYqYZfgjLev+TDyWzntEaLBqxf8PQThrNGMajnh6D7yr/y24PMKq5GzNsBAmhotq9dXdGAi5iMFLEQ00oVTGdVyg2Q0qWuJ3titQ4XVUE+rSVRoDXL/lr8Hv/1zLQHuTlg6mxEiv536G0VVMBeJIlCvWUTUlwIWIhrp4F8q1Wc+aEBwtX9OHMDhAlFjxkj+Hvz24mm6Ep3AabH+u3U1RVUwlyN76MJEzEcKWIhorO/fEgzslA1LCa72y/WL+SiKGptX8vfgt6n3dCXqUvEubVs/9N4r5yiqgrnIfaDLJ/brFhH1pICFiMZ6/gRHszvl+EGCq/1SQsEhWpz5m78HPx3yK52yTjh1lOvRb+UU47paiqpgNmP7VtmuXUTUkwIWIhrrllV0vDjlyYNm2zqiN0pIPkSL1wS5++ofZBU6Yu0f5F/57QRGvSECyJireu0iop4UsBDRWCXPCZzR0mxZ3Tva1xLzc+BPdJpEFQ428M89Wzkt1glj+tB14bcyRg9gOndvsNmI6FYKWIhorHLUcAtNL44ZX8hHktcW/06nSVSZOYogd7+8dYWsIV1qa9JW10/ta4jeSvQARAE5JbfwezZXEN1IAQsRjfbpw2b1uQ85WFHEmIrX7t9Op0lUkVFk9ffE/JViTH0dWUO6XDrdZFtD9FYJxq6u5JqEaLBkRo3tGkbE3FLAQkSjLd/XoD7zIQdlOzmi2Wvv3aKQGlXOHiM42w9lHA702byCQqrfju7NNQnR4dQRnk2IbqSAhYhGu2perfrMhxzcuspOv5d275iympiUiixvXhHk7ocruTc7YvJgRrv9VkLyAaJCTVW69dRM9TpGxOxSwEJEo5WjhsEZdTXp1lEKdS3RnVOHcphA1CkkyN1zj+yhO1aXxoa0VfC5fQ3RW08dJf8KosXU38hoRHQqBSxENFpyVtwxtGulbS3RnTL6A9Fm1hg+Erz28X3GanW5cZmu2CB8/5ZTXyBalG6ut13HiJhdCliIaLwyEgfOWDCZcFCv5FSr6LN1NflDXtrji5TVQv1Km53r+Uj122EFleqyAxjPk4fNtmsZEbNLAQsRjXfPVk6AcwofTN6Zek8HYNQ5d5ywXC+VsRfQZ+YoOgD9Vk7fBYgiQ36lYx7RiRSwENF4F06pUZ/3kIOLHNnuiezqx4O3rwly99INSxmr1UU61Xp9RQab3x4rI5MNosnqBbW26xkRM0sBCxGNd/DPFBGc8u4NH+xeuHQ2u/pxoX9nigheSVi2Pg9uMyIUhK9fkH8F0eQSG46IjqSAhYiRkHBW5/Tj5LW8PbybXf24MJsgd89885L7sS77/mSc228H/cQmF0QXOaVUcgXV6xoR25cCFiJGQoK0nTNjJB/s+cpJa/Fh2xqC3L2w8LuUurSQhfmTOFDDbxfPIGYAos2csbyvIepKAQsRI+HmlWSuOGXjMj7Y87FXp5TVQqNJbJAiuPobo3OLxhHgrks6bVmF39NZ4bd0ykLUOfhXg+26RsT2pYCFiJFw2nA+mpxy/CAf7PkoJ4dBfHhPLpwn7ljHqbC6PH/MNReEzx6z0wDR5u0r7hWIulLAQsRIKKc40Q3jjCcPCQ/Ox+0ldP3FjQEEueftlbNN6rJCBo7soavCb2WkVTrdAKLOqF5VtusbEe1SwELEyCgFGdBHjm/v3tG+jqjnlXN8qMeNOePIGcnHLp9UWNWVVAt0WTKT/Cu/XTCZ/CuIB5tXEPuAqCMFLESMjEf3kXPhlPH92dFzo3yo19bwoR43pKtO/a1R32HdOO3NCUN+rbStIXrr/u2MtEI8uHW1yXZ9I6JdCliIGBlXzqtVn/eQgxVza23riLkd3btKXUqIARdOkQuXj4um0+2iC5lrwfjwLp3ZEA8kJqPvt4y5I+aSAhYiRsYxfSgqOOXATjJY3LhqPsXSOJJ6l7b91qgv3S76nDxCsdRve3NSLMSM4mmMHSPmkgIWIkbGrp9WWPV1jHU54fY1WtLdeKyMcdW4QpC7e+/eoNtFl9UL6H712zljOSkW4gWnRyPmlgIWIkbKm1cI1nZCXW26Nc9JXUfM7vMnbOvHlaLx7HC7sVuHCquxgQ0EXUZzopjvlm6iIzAXF083Wavm1YZuHZmSWlSl0q2bteq1jogfpICFiJFy9xZeWJ0iwcvqOmJm+3Ese6zZXlJv+80xt+MLGeHWpbqKjYMgvHOdjsBcyCmN6rqF4aXTbD7qMmkQxW/EbFLAQsRIyZHZzlk41YwX2Kg4dwLXWJyRjgT1N8fcykgc6HHhJGNAftu9Y8pqoiaSk4E/mbGBtWFpnfqvBhnYtYFNFsRsUsBCxEg58EeOcXcKL0POZCwl3qTeE+TuxvL95MLpsnFZnW390FunjyD/KhdvXplzEua4fnRw6vLoXrNt/RDxgxSwEDFyyvHkoI+07qtriJklZy3+mNKVECWfPmRcS5eJAxkB8lsZBYbsnDpqTiegjNRKvhPkRiIMBvGMQswoBSxEjJxnjzWqz3vIghT81DXE9pWg6oZ6XrLjzryJjNU6sddXKauFfQMt5P5R8Jl9DdFbr19koyEX6xab1Ql47jjvbrqsnMcppoiZpICFiJFz03KyFJxS+H3Kto5od8IAxhySwM71jNU6cdpwxrV0kcKKun7orWw06DFxgFmdgCXF5Ojpcv6EOd1ziKZJAQsRI+fvQ/mYcsrMUdW2dUS7JYt4wU4Cl85QZHDi5pVsGujCKZf+O3kwGw25aGywjOsEHN2L302X+rq01b2jfQ0RkQIWIkbQnl+mrBbiWBwhXWvqOqLdU0cYcUgClSmC3J3I2LY+Ei6urh96KwXV3Ny+Zl4QuORgySEaoAcbj4jtSwELESPp4/tUsJxw4hDt6Dq+fUXQT1IY/DMhubq+4+AMLWRjRTZY1PVDb5UOSsjOnq1mdgJKsDzoUbajwbZ+iEgBCxEj6tG9HOnuBDlBTF1D/K8Df6xUlw1iDEHueg7onFKXDjJw7xb3Wb/t+mmFVVNNF08uFkw28/62aj5j+rq8esEBPIjtSQELESPpirm8BDlBThDr8QWdAdn8Y2qNumwQYwhy11MKfaDH3m1cU347rpAcJR0G/mRmh+nwAjaKnDCiu5m/I2KYUsBCxEg6ujcvsU6RE/bUdcQP7ttery4ZxJgrZwly13HXRv4udKGrz3/XLyb/KhdvXpnducNIsj4blpJfiqhKAQsRI6mEgdbVMEbghJXzam3riB+8d5NctSRRRZC7ltcukDekQ/qfx1Hhd3S5+i0HCuRGDiNR180kjx/kN9Tl+kU2WhBVKWAhYmS9cZkPKycc2EUgaCa7d0xZTVxOiWPIL4xnZFM2Csgb0uPZI7O7XuKgXI+VFVyPuShZZPZm1fIiIiB0aW62rN6dKIwjfiwFLESMrKWbGW1xwp3rBAxncupv1epyQQIwNejYFEf2IK9Gl0OlbBD47cieXI86mB4XMPgXfkcn8JxC/K8UsBAxss6fRLiwE+rr0q072Oo6YoW1aTm5KklE8p3UawE/uHQ2nRK6LJrOR6bfrl7A9ZiLxgbLKvjMvnam+foFOVi6lO+nOI74sRSwEDGycry7c+QEIHUdscI6f4JMjiRy9Tz5ItmUsWPQQ7pK1PVDbz15mPt0Lm5fi8Y9rXwf9xZdZGyWzUfED1LAQsRIy2k2zvhjKl0C7Zl6R65KEqmu4sMgm/dvcbCBDqaf+hYX377meZ+L3Vui0VW6ZAYd9E4Y39/ssVDEIKWAhYiRlhOJnMHIlN1h3cjjSDJDfqVzpj0LPq+wmri9aiGnqqnrh946tAv3aR0kWkFdOxMd+CO/pxO2l9TZ1hAxqVLAQsRIS3aRMy6dicZ4QZAumclOcJJZOCUaH3xBO3FglbpUkIFV88w+9S0OLiOPTQspDKlrZ6ovntJRp4t0w6rrh5hUKWAhYqSdOpTT45zw/i2jLqpyehgkl9JNdCW2Z0kxBQNd5LRGdf3QW8lMys2bl9F6vvPs1Sedtqz+nVO2NURMohSwEDHS9vgiZbUQ0+KI/j/wEvSxj+9zASUZgtzbV8biIDdVKXLUgvDlM7p1cnHySLRGWSWTE/SRLkR1DRGTKAUsRIy8FCCcMXNUtW0Nk2qvr1JWC99FiaaGIPd2ZbxHDznBVF079FZOHNZDuibVtTPZwu9TrZ1FoMeZv7nXIIoUsBAx8h7eQxu6EyQ3TF3DpCrFPAAJiFavjSTb52s+LHXZsJT7qd8WT6NTR4conlT35CEbkLrU1aStgs/sa4iYNClgIWLkXV5EVosTTh5mF+9f/1zLIQBgtY6yqNdGkqWwq8+EAdErGkTNg3+xSZWLxoZoFjfKdvLbOmHacDroESlgIWLkHdWL07Kc8OxRtIJe/fTK2SZ1eSCB7N5CkPvHbltDYVeH+rq01a2Dff3QW+nSyc2tq9HM8ps/ie46J+zdxrMKkQIWIkZeya+R1mrQQzKfJPxeXcekKdeN5B8BXL8YzY8/v7xwkgB3Ha5d4Lrx277fMM6qQ1SL8Py+znj+mA1IRApYiBgL5QMU9JnI2Is1ms49+B+1NQS5f2zFO74odZARZHXt0FvnTaRDRwdZJ3XtouLDu3TYOWFYNzIbMdlSwELEWPjXxnr1GQ9ZWDUvWqcV+eHKeWSnwQf4KGhz8C+V6tJABsij8V8ZmYLc9O8c3a5qfmNnRO20SUSvpYCFiLGQXVpnHCptsK1h0izfT3gsfKD49+h2MHjpwincS3VobmYUOwgf3KY7JxevX0R7rGzOOA6NcMKVc4wuY7KlgIWIsXBA55T6jIcs3L3RbFvDpClZEkmmsiLd2olH3lEbe7ZGM0PGayVLB3LDPdR/e32VslqoX+Xk5JFonyzcqxO/sxOa/nlk9/yS4jkmVwpYiBgb375KdkHCCXJ6VpIzf/p+S3DsueNtHz103LRx4xK72uLNK+QJ6hDV0OwoOWsMnTk6rI3BSNm9m1SwnDB3Ah3DmFwpYCFibDxTTieJE0Z0T27mT9F4ijabV7QFUP/WhcwjQU4yTXJRV2w90bU24ZVdTYrGkX/lt7vIttRifP/oH8pSuonf2gmH9xADgcmVAhYixsaNy+rUZzxkIcmZP4T+W9a0YR8+wCtTFC2E4QXJLeqKo3tzMqcO0r3Z9xtGePz29jW6AXPR2JC2Cj6zr13UnDmKbjsnvH/bkvgNF0yuFLAQMTZO/Y0XICdIEUddw6R443KyP4xaWv6boSGhsGBZi6Ylt6grrijiZE4dnjwg/8pvu3essBo5ZyMnt67GY/RZDkSQbCfQZ0yf6HfeIbqRAhYixkZ5ASIIVJ/LZ+Px4uvUrh0qWjPAkszj+//9AGdUpw05zl29XpLk4d1UDHQ4+BfjO34rHaKQmzhlsUkxDvTZuqotBgAxaVLAQsRY+egeFSxdKt6lbeuXBCUvJOmo+RkLJpMJJkiAuXq9JMmHd7l/6lCc8E69IPxzLZEAOsybGJ9rccc6NlKccOc6naCYTClgIWKspIPAGf1/SF6OS0kxY1LLi/57atXgXwhyFyTAPKm5It07pqxm6ldaDP452VlpQXjtAt04OvTvHJ9nOF13zpAogH7fxef3R9SVAhYixsrlcyhOOGHW6OSdpHXyCEEbo3rZszMqK5I9VvkvST2dc8oQPh51eP2ixbZ26K2MeesRt2ux4HPJPeN3d8LiGfHpwEPUlQIWIsbKkT3pJHHC5hXJy1B486pFXYZEkanLSDLRILkfBBuWMrKlw7ED5F/57aRBjHnrcPJwo23tou71izyHnCAbcuoaIsZdCliIGCvlw7ymmh08XZL28jPwRwqcMpqjrou4cz35I8K+P+MTiuzEU3QmarFi7n/Hb9F7Ny2nmKrD2uL4XYvb1vDbO6GmKt3asaiuI2KcpYCFiLGTHTx9nj2O1whCLhdOIax814b2CzQSBgyWdSuhQe6vXiS7M1GXpI6YBunF0zzDdRhfaB8Fj7qTB9N95xQZ/1bXETHOUsBCxNi5ayOdJLpICGjPL5MTArp3G9dG0fj2R+QG/kR3miDZO10/ta9PnO37bcpK07iak8pU++O36J2yvtVVXIy5kKyobjHsvJFuIhlzB31KN7W/KYUYVylgIWLsnDuBThInSN6IuoZx9e4NjlnLdvJkxTs+HISRPZLVZTNnLAHuOpw9lqyR6zAc04cOHB3i3Cl6hTxGRzx52GxbQ8Q4SwELEWNn4fcp9fkOWVi9IH45Gu0pJxw1JTzmJ9epVYzutLFkZvtdanF1ewmdiTqsX5y8Qy+CtqSYk4R1KN0c364bMtCcM+TXZG26YLKlgIWIsTTpJ8054VBpMk7VkpyIpJMrtJ9CRhv7t8f347A9OYFSj3ExzBwyzTPlCd9l0EQyC9W1i4sTBtCF55SkbEQiihSwEDGWnuYlWBsZq1PXL46yq2tZ63J0kBSNo8gn3L4W3/Gc9pRsJ8hOazZaDDOHTJMxZj36d848Ch51JYOQ06Sdcel0sp5ZmGwpYCFiLN2wlGKFLg31yQitPnecomauvDPJx4Lk/E2IQ7sS3q/DlXN8IPqtnPAIuZETQ9W1i5sXTvG8doKE+vf4Ir5FTcSPpYCFiLF0yhBa0J0wIgGh1amE7+w3NVlW9472dVF9/4bxW2FUr+zFvri4aBqHXuiwdXX27kXM35XzyL/S4cSh7KPgcXD9EjYhnSKHcajriBhHKWAhYizt3jFlNXPgnDbF0+KbpyHSZWJZ927pjYqeP8HOt7B0VjIyRfb9Se6ZDlOH8nHot8cPcu/RYe0f8b83cRqlcw7+lYw8U0QKWIgYWx/eoYKlS+mmeIdWL5lBl0nZDr2X221r2PkWdNcr6t6+xn0yF9K9yHiO/3L4ih5JOEygyycVVhXZfI54+yr+o6WIIgUsRIytcroe6HHlbLzzXWRnMuksmq7XZTd7DEHuwp3reh1rUVZCySXvC7IjRT517dBbB/9Ml6wOrfl8CTlM4OwxOvKckpTRd0y2FLAQMbYunU2ehi6VFWnb+sXJR/foMpExSnVd2rPwO4LchSR8KI7rx5iODnHvUDXBJTPpktXh5pV4bzZ9rIxKgjPktGV1HRHjJgUsRIytEkwO+sT1WO6eX6asloTXr6or060jGeraZFJGEcCyRveO9272qvl8IOpAOLL/HtlDl6wOSSqmjuzJO5xTbiWowInJlQIWIsZW+WCvqWI8RpdZY+L5kTZ9BCNxl047e6lldKONZbPjHZZcvo+iQS7S/zxC+nwdz+K+ST5/QtFch7kT9EbB46C8wyX99GCntPzzZ9T3G+5XGG8pYCFirL16vkl9vkMGNq+MZ+s5oeRW6xqo65LNratYM+HAzngHuT95mPDWRA0e3yf/ym8Lv0+1FgohN/1/SFZx4uQRNlOcUvx7coqcmEwpYCFirN25niPidTl1tNG2fnHw8lmKmDNHOeuumzWarjXh7o34Fi9aR2tpeslJ3IuYJrhwKvlXOrx6nrxT5lbOY8zZKccPxvNdDvFfKWAhYqwtGs+LsS4ywqGuX9SVEYTqhI+Rto5AORwpkBEEOiIsq7HBsrrFNMh92jCKlDr8MZVuBr8t28koqw5JLEwM60YOllOqUmmr66f2tUSMixSwEDHWymgC6CEFC+nKUNcwysqR0knn2WN3hcnXL2jPEcb0iWeQu5xWBbkZ+KPe6Z3oXhnThNysWRjvTL5MvuFQEcdMGhTP5xaiSAELEWPvm5e8/OgSt5eeFXMZP/i7zN0I1Jm/yR4RlhfF86OR3zc3L5+5K/6ivtIdSrenHuP6xev5rOuxA3ToOUXiM9R1RIyLFLAQMfZKthPosXpBvD7WOWXN/W8qof5gWQf/clcANN23dDXkpHx/PH97k2TMX4/6urTVNabjzLmU02DBGQ/vxje/EZECFiLG3vVL+BDX5fDueH2wPX/MR/rYvu527WeMJCNJuHczfh8C/TszWq3D8jnuir+o7+4tHLSiw43LTba1S4qDfyYHyynS1TjwJ8afMZ5SwELE2Dt5MDlIusTpY53RFMtqqHe/a8/6tRHHIPe5E+h60UECpNW1Q2+VZw7kpnRTskfCXpHJ6BiJUFDXETEOUsBCxNjbvWOF1dSkPtqhPRob4nN6zZxxdBDdupLfrr0c2w7uu9hMddcGul5ykXqXtq0beqscGtJM/UoLKTqr65ckj+4lDsAp508k79RKTIYUsBAxET64w1uyLiN7xKPrgI90q3U8R10XJ5If10bcdrKvnqein4sz5Xz8+e3MUWwy6NL/h3idEOzURdPpGnWK5KYVfG5fS8SoSwELEROhBDGDHoumxWOn98YlPtIXTM7vt9y0nPw44VBpfLLhunxSYdVUMRuai5LieBUtTVROSoPcSCesunZJc0BnRtrdIEVidS0Roy4FLERMhEtncYqNLqWb8+vaMUHJfZLdx6QzKM8Q12nD6ZAQ7t+KTzbciO4EIusQt7FRE715hU0GHY4fpBtQ5FAW5+zfHv33OURVCliImAj5aNPnyrn8cpNMcHwhwf3v3+a/a9+rE7vegmToFXxmX58oumQmozi5qKuJTxagqcpokxyQALlZs5BuQFE6YcEZEn6vriNi1KWAhYiJkLEZfSoroh9evLaYjruzx7zZtX/xlF1vYVxhPDpyynbyEZiLy2ejX8Q33am/0d2py7h+8bj35OvCqRTf3TC8IL9ObETTpICFiImR4GJ9JG9CXb8oefIw4eOSX6WuixtZyzZWzotHF8S9mxxokYstq7z528HMbl1Nvp4OMgovI/Hq+iXRvt/SEeyG9Uu4n2G8pICFiImRwFh9Zo+JdvDnm5d0DU0d6s1vuGEpH5rC4d3RD3KXMcgm6pE5mTLEm78dzKyMqkNublymG/BjH9+nAO+U6xe5hjBeUsBCxMQ4ZxwjC7pEuQNh4I/knbW0WFbPL73popNCGFjWgzvRD3KfOIBsuFxIga97R/vaoXdKR1FdLa00Ovy1kRDuj5VQcnBGc7Nl9e7kzfsAoglSwELExFj4XUp9rkMGTpd7k58Uhgsmk5Px6J53xRYphDG28b8g98/t6xMlyYbLza2rdCv47QQKqdoUja+xrV+SnTeR57sb5L1IXUvEqEoBCxETpZzIArmR4G517aLi3m3s0MppTeq65OMzji9vZXz/aIcpHztAgHsudtHx4ruMJevT/wc6Zz62z9ep1g5jcEb5Pm/fCRDDlAIWIibKk0cIgNFBOm68GkEL2rs3yMhYNtvbwPHjB/m7EVbN93Zdg/Y5hciczIp4/l8UPH+C+4kOL59FdyPJT2WcG5yRepduPY1bXUvEKEoBCxET5brF7PzqMnlw9LpNZMSLkGrLGtnD22Oz+btp48ie6O5iSwYKo6DZkc4OsmL8VT6iqyu5EHWQjQN1/bDC2r2FLms3jC+M3jsdYntSwELERDlpENkbuqxZGL1uEym6JZ3aGu93WuVUNrCsh3e9yxYL2hkj+Q1z8TAGQf2mO7o392hdVi+I3jM4COWUZHDOn2ujezgP4sdSwELEREmHjj6HI9htsnEZnUJXz3sfQt3ji5TVwtRG62lOUT2hbusq/jZyISecqeuG3rr2Dw4S0GVsXzpm2lPiDeReDM64d4sCPcZDCliImDjv3+LNR4covuycPUZ1cud6fz7Cnzzk70aQE9TUtYmC5A7lhpO6/PfUUa5DHerr0lbXDvb1wzbJunSOjJBzKADGQQpYiJg4D+zkJC4dGhui9wJd8Y5slTnj/AmhPlbG340Q1bGe928JcM/FgM583Pkt16EeNy5530kbJ+W0UHDOUo8PeEEMQwpYiJg4l8ysUZ/pkIGRPb0NA/fToV0q1X/9RFL4vT8f4SXFjP4IRyN4HPngn/nbyMWLp5z45rfDCrgOdZECjbp++EEy/dxxppyDATD6UsBCxMQ5nJdobRZNj85IzeIZFCZfPffvI5wDENp4fD96o7UyGgfZiWJhMmquKKIIrkuRT520cbF7xxR5pi6oq0lb3SLWWY+oSgELERMnx3jrI8dVq+tnqgd2MeJ28rB/u6sSXk5wrtUaZi8fT+r6mGzpZsZtcsFojf8yhqyHZBUVfhete0wY3rrSpC4daDBtGMVRjLYUsBAxkV45x4uPDn6caOeXD+9SXSlZ5O9HuHQfgWVNHBitIHfJ04HsyAiyum7ora9fkH+lw0vGWbXcXkJh3g17tkZnYxKxPSlgIWIi3bGOFx8dKlNp29qZqByrLZ0xSWeizyfkle+jg0JY+4e/hUIvlY5TGRuBzMjhD+q6obcO+onRfV2OHWCcVcepQ8nBcsOzxxRIMdpSwELERDpnLC8+ugz80fzOhOkj+D0lD6Tgc/vaeOmahWTYCOX7o/OBOaoX2WW5OHXUv9FbbFPyFEGPqJ50GrQFn1VY9XUU590wtKv573WImaSAhYiJtO+3qdacCcjNnAiEyW5bU6f+ayeOuzf8DxeXDi+IVpD78jkUHXMRpY66qHqolO5NXcb08beTNk5eu8B4tBvWFnPPw+hKAQsRE6uc2Aa52bq6zrZ2pnnpDC+x+7f7n2shHV4EuVtWyz+3jh5fRCNkmcJBbigY+O+zRzxvdZCOoq6cEqft1lVsXrnhytno5JsiqlLAQsTEKie2QW7OlJs9XtN6qmQV7XSLptXY1sYPCctvY9KgaBQ9Ht7h98pGTXW69R6irht6Z7/v6HjW5fpFCgtOlPswOEciByQ7VF1PxChIAQsRE6uc2Aa5Mf1EpJE9CQcWfgvoFLUje+joEaIwgtG9Ix1zubh4moKB3y6YTP6VLrs2+N9JGyelW41DKtxRND6YTS9Er6WAhYiJdeJAdu50kJ3zXp3M3albUUQhMsjTIlfNZ72Fv8vMD3KfPJh7XC42LTd/RDrq7tvOqb+6FEUgc9I0iRBwx+Hd5j/DENuTAhYiJlbJ85E2asjNlCHmjksd3UdH0IVTwY15ji+kKCI8eWh+kPv6xeTD5CIqo6BRljFWPWSzqPA7czeLTHXjMu5zbnj/toXxaYykFLAQMdHeu8WLtQ4mn9L17DHhwEEG7cvR5RR+24LcTc8QIecvO40N6dbrWV039E7p3pW/FciN6eP6psqmins4wAKjKAUsREy0ZTvp3tFBco/UtTPBPt8QDizMGBns2MmD2xR+BZM7E8WXz6gcZOPGZfKv/HbO2Gp12SEDxw6Y+Zw13a6fVlg1HOTiCjnFUV1PRNOlgIWIiXbxDMJldbh/y8xxKT6O2sZO+nwdbCfQoVIKv4IcBKGujSn2pbibk53rCcz229JN5F/psnqBufcT0z1/gm5TN9y5bua7HWI2KWAhYqId1o0T7HRobLBaT/tR1y9s5QM06Tx7FPzYyYq5BLkLJndMzB5DcTcXM0cF27mYROUDGfRgnMu968j7c4WM9/Yjdw0jJgUsREy0EmBZlaJNQYdRvcx7ub5+kdOHyvcFX0QZ14/MESGM4qGu20v4oMtGS7Nl9fqKDzc/7d4xZTVxi9aivi5t5CZRVBzdm2eSW2QSQV1PRJOlgIWIiffyWd6wdTDtJUdyL+SlP+msmhf82Em3fz60JAA76ciInqlFkEunua9lQ3Lc1DVDb50+gi5AXWQzRl0/1Fc2IysreCa54eSR4E4xRvRCCliImHjpVNBj9xaz8mLoAmojrLGTezcZDRKmDDFzDI2Puezs+9Os+1kc3V7CiLcuuzZwPebrmXJysNwgAfh0/2GUpICFiIl3FlkxWly7YNYO8do/yGEKc+zk4F8EuQvrF5t3itNvXcj2y8X8SWZ1lMZRRrz1mTPOzEJ4lJQQfHCHqRsxiO1JAQsREy+ndelRXZm2rV2YnjjEbuvNK+EVFZcX8bEgHD9o3vhF8e+crpoNud8Xfm/m6GdclDHjhnoerDrI9UiQdv6O6EHh3i1yWqi6noimSgELEfEfXz5tUZ/n0A6Dfqq0rV1Yvn7Bb1a6ObyXThldBMt6/ti8IPe92xjdyoaJv1ncnDyY+4MuL55yPXrl+ze8F7jhyQMyATE6UsBCRPxH6aKA3BQZMubQ/4eU+q+WSMIcgyJEv43WIPdOZnVP3L7G6FY2juwJ/uTOpLl5JdmSuhwr43r0ypOHeZdzy5BfzNmgRMwmBSxExH9cW8w4lA7b1piR97NgMiNSwsCQO+Lu3iDIXZg61IzCrkhhMTdLZoZX+E2Kl85QRNVl1fzgT5KNqyvm8i7nFskQU9cT0UQpYCEi/uPEAYw76HDmbzPyfvZsZUTq7evwx07KdhLkLmxYakZhVxzbl3tZLob8Gm7hN+5KEbWmmiKqLmGdJBtHh3KAhWsung4vUxPRiRSwEBH/seCzCquJzvOcvHwWftFEvHOdzh8TiolLZ7PbLcjYiro2YblqHr9JNt69MeMeFmfHFVJE1aWuNt1a8FPXEN375iU5WG5obEhbPb4waxwesT0pYCEi/s97NymK5MKEvJ+Czyv+edFS/82Sx8Zl4Xf9jOrFh6rw/Ik5RZGje/njyIZJxca4un4x+Ve6XL9I14vX/l3GPdAts8eYMw6PmEkKWIiI/7NsBy89OkwZEu4LzqRBFE2EsH8Hscsn5C0JUtjtHXJh918f36cQnw1yXvz37DHamXXZuT68k2Tj6tJZdKG65cAuDhRA86WAhYj4PxdNJxhcBwm8V9cuSCVvKOm0NFtWzy/NKJhw4l0b04aFX1CU8Q+5NiAz0jWorht6pxS1KysoausyZ2z49424KYebgDvevjKnmxgxkxSwEBH/59CuvPToICNK6toFKbv7lvXwTrNtXcJy33YC9QUTgtzlNETITHVVurXAoq4beufInjxHdZHOzX7fmbERETclrxPcIX/D6noimiQFLETEj2TnODcPbodbPHn/hhfTQ6XhFhE/dskMOheFk0fCz1aSXDTIzIWT4f9GcVdGNEEPk7Lz4ubhPURCuGXT8vA3YxCzSQELEfEjL51hHCoXclpjtw72tQvCIb+yuy/I6X/q2oTliB78JsLLp+F/jJ4ppzsxGyYcfBB3JSQf9JCwcXX90BuLp7Gx4pabVzhYAM2WAhYi4kf+uZYOBh1Gh5QjQ05ZGyO6m9PiLyNZdTV0Lso4UJ+vwx0HevOK7sRsTBwYzn0rSb59zTWoy6p55mxExM3C71Ot92RwjuQohv0sQ8wmBSxExI+cNZoMGR1kbExduyA8sJOxgJpq83J8ZMcWLGv6iPACmeWDDTLTUJ+2Cj6zrxt659AudGM6YXRvCqp++uwRxVS3/DE1nHc8RB0pYCEifqTsOrFrl5u928I5+lvCy5POlXPmtffL9QDhZocUjac7MRvXL5r3dxM3l80m/0qXutq01fVT+xqidx7YxYaXW44dYLwVzZUCFiKi4oun7NrlIoyPwZ5fplpb25POjnXhFA+zuYi8kVZOHQ0vJHzneoqI2dheYt7fTdws30fBQJdrF4J/hibNBZN5LrmlMmVepzfiv1LAQkRUPH6QENpcVFembevmt9OGM94pzBkb3phaJocXMDokvHoeXpC7dOZBZsIc70yKL5+x+aOLFJzV9UNv7fsNHfX5QGYgmioFLERExbV/MAahw+Cfgw0S37qagH15Ge/3nXnhqrJTK9lcSUd+H/loUtfHb2X9pagM7SOdm9LBqa4beueAzmSwOWH2GAqqQfj4Pm3bbqHIiqZKAQsRUXF8/yr1OQ7tIJk76tr56aXTdJhIh4O6LqYoY6UQTqfPMDrgsnLvVrNtzdBbixkj1qa10P0tBdUg3Pcno9VukcxRdT0RTZACFiKiYrcOFVZjA90Mudi2JrjAaukwqUrxm8h4q7o2prh7Cx8KwuYVwf1d/OviGRQPshHWoRNJ8uBf5F/p8vyxuRsRcZPDLdwjhdaBPwXbaY+oIwUsRMR2vHuDtvNcnD0WXDFlRA86TIS1xbW2tTHF4t/5UBDOlAf3d/GvZTsoHmRj3sRgu0WT6JOHPDN1Kd/PCW9B2btTymohms01K4rMfefA5EoBCxGxHfdtp5skF0EGVi8vIpdMmDDA3FDVoV0pMgqvXwT3d/GvFNwzI10EhQbmxsVJwrKdsWoeRYEgvX+L+6Nbzh0PfkMGMZcUsBAR25E8j9zIB4vsbqpr54dH99Jh0tRoWQWf29fGFAkSbyPofBtGnrPz9CE5Ln4rHW6gz+je5m5ExFHG291TX5c2+r0DkykFLETEdvytC90kOkz9LZjA6mePmAGQLht1XUzz2gWC3IWZo4L5uxA5dCI7h0oZ1/JbyRgDPepq01bXT+1riP45a0y1+jOAA2aMDO55hqgjBSxExAym3tPVkIuSADKZ+nzNeIogpympa2OapZv4kBW2rAouyH3NQsZrs7FoOvlXfvvgNiNaukiRX10/9NceX6SsJvZWXCORGuqaIoYpBSxExAxePM0bTy6O7vO/u2E2u6etSEi6ujamuXAKo0RCkAcc/F3GeG02Bv/CKVp+2vPLlNVC/UqbnespBoTh7WtcpG4JMu8UUUcKWIiIGdy2pk59joPCgzv+j7XJCz9Y1pBfzf8Ql39HsKw3L4N74We8NjNvXgX3OyRVxrOcIRsy6hqi//IekR/DCsx//8DkSAELETGDkmMD2ZFgcQmRVtfOS69fpBOusiJtWxdTrUwx7ykEcfJdr68Yr83G8YPBdcIl1V0bKQzo0nrAwzf+3xfQ7vQRvM/lw/rFwY3FI+aSAhYiYgblhD0+DnMzpo9/JypJ2G1dDT/ChZPR+RC/co6CozBrtP+dFnyUZWfVPP8z+pLu7Wv8vevy/DEdgWHZvaOc1qr+IqAL2W1okhSwEBGzKC+ckJ2ls/z7SBzblxPWhK0BhoLn664NdGQIQfxmEhYPmRnZg7EXPy34nKKAE8r3+58ZiZm9cZliq1skBF86ftU1RQxDCliIiFk8doC381zIEerqunklJ6y1IZ026tqY6vxJBLkLQQS5nzveqP5j4X9UpdJWl0/sa4be+ftQOgCdsJKOwFD9cy0F/3yQZ7u6pohhSAELETGLFFByIxlV6rp5pWTYJB0ZY+3VKTo7n4N/JshdeBtAgPj7N3SIZuL8Cf8LiEmXg06cMbqXf+P2mNspQyi45kMQp04j6kgBCxExi+MLGWHLRXWVfwHjr17wgf7kof8nPXpt6h25ZULh9/4VHgd0Tqn/OPiIDUv9H+FMulfPM5Kli2Q5SqajuoYYnAWfVVj1dTyb3FLxjq5WNEMKWIiIWZQT9hobeOHJxeBfvM+akY9/iOau56UzfNgKs8f4N/rJqGZ2Jgyg28VPu/7zbKyr5dmoixT71DXE4KXomh/jCrmvYvhSwEJEzOGd683qMxwU5k7wPhuBD/Q2opibsmMdQe6CjFipa+OVf21kjTMhXRay+aCuGXrnxIF0JztB7onqGmLwbl7J2Gs++PlMQ9SVAhYiYg73/cmHYi4kHFVdt3zdvYV1F0b3jt6OpxQ0wd8cJsmeg/ah28V/Ny2nEOCEWT52Y6K+FF7z497N6EUaYPykgIWImMPi3/kYz4UfJ67dvkbnm4zoRDE3ZeBPBLkL7974E+QuOSQ11YxvZYIuAf+9cIoDNnSRgzj6fuNfHh7qK89T7p3ukWu5/w9cyxiuFLAQEXM45Fc+xnMhYevquuVjweeSPab+U5LHjUvR7SSRwFf452W/s/cv+yN7ck/KxrRhdLv4qRRQ5fAO0OPZY2+fj5ifF0/TvZoPS2dFL9YA4yUFLEREDVPveVnPhuzK9fnauw/1SYNo8xdKN0U3N4UOjTbmjPW+mLJsdq36j4H/0dxsWT2+8O5ehHbH9OH+7ITyCB7EEWflhFJwz+ly7zvuEZ1IAQsRUUM+xnMzdah3H+q8YLYxb6L34fhBub2E31DwIx/u4F+0J2bi7g0yWvy2pJgCqhNWzKVjxSTH9aMAmw+1NRySgeFKAQsRUcOtq/kYz0XJIu9e0s/8TcFQGPhjpW1tomLRuGr1/04iuXDS+93qB7fJh8uEHP6grhd665ly7s9OGNUregdxxFkZga1K0VWfD4xpY5hSwEJE1HDGSD7Gc1G+37sxifdvWtT/+cTx5lW0c1Mk6BUs6/1bb39HyYdron6QESmcqmuG3kq+nT51NenWgom6hhiu545zE82HPVvZKMDwpICFiKhh706p1pwnyMzDu96M7gz5hYBqIQ45E3IKH1jWAA+D3MmHywynvfnviO7cn51w9Xx0D+KIs4zB5gcHE2CYUsBCRNRUHtiQmaYmyyr4zL5uTl00rUb9n04kkgOmrk3UPH+CXW7By64gGdWF9nnywJsiOmZ25TyuPydsL6FTxURlrBPyY2jX6EYcYLSlgIWIqOnfZQQn50JOp1LXzallO1lnYcqQ/NcybLetITtO8PIj9sQhioKZkHB7db3QW48f5PpzwqzR3hWv0TtlrJPTpfNjbbF3uaeITqSAhYio6eoF7DznYuns/F9oHtwhoLr5nyXo3jH6o1Czx5AdJ1w87d0Y0cundIJmonhadE/tjIqSzQd6yEhrH0ZajfXUUYqx+XDlrHfPNUQnUsBCRNSUo5dzs+/P/DpNenyRslqoX7UW8dS1iaL9viPIXUi9S9vWxo2S70QWX2YG/8xIi5/K+oI+zx6RE2Syq+azKZkPcphIzy8p0GLwUsBCRNS0a4cKq76Or8ds3LiU346cHM0MlnVgV3xGod7SsdHKwB/zL67IOBK0z+sXFAv8dslM8gmdcHRffO7jcXR4AQXZfCkaT9crBi8FLEREB96+1qQ+v+EjaqrzOzJ86yoykwT5UFTXJqqePcaYhjB3Qv6/KZlimTl2gGKB3x7ZQz6hE1YU5T9Sj/7KSbn5cXg3910MXgpYiIgO3LutXn1+g8KQX9x3mkhWEFitO8Pq2kRVipJt7FiX33iteOEUxcBMrJhLscBvnz/hY98JctKduoZolhxKkB9SAMxn0xLRjRSwEBEduHAqIxS5mDfRXaeJvARVpRjRrK7Kr4vNNGeOYuxNuORBkDunZmVmRPf4FH1NtPB78tecUFsTr/t4XF1eRA5Wvnhx+jSiEylgISI6cPAvZCbkYntJnW3ddJQPUIjfyT4Ej7chxSd1bZwonY3QPpUpigV+y+aNM66ej9d9PK7yTpc/W1a5e+dDdCsFLEREh75/yxhFNs4db7StmY7L57ATKmwvyX/UzDQlYBssa9BP7ruE/qCAkBHJWVPXC721bCf5V06I4308rvJ8yo/b1+JxajJGRwpYiIgOPX+CzIRsuD0NjIDgNmaNqbatTdQ9U87fjOB2vFbcs5X8vUysW0wHgN8+vt+sLjtkQU4MVdcQzbR8H+8e+dDSYll9v03Z1hXRLylgISI6lFDq7Mi4WJ9vnL/MPH3IB5KsXRxfBDev4G9G2LnefVfGrSsccJCJcYVksPhp706p1o9U0MPtMxDDcckMulvzZdF095sziE6lgIWI6NDpIwilzsXvQ53tPvf5mpwk4eVTd91rpsvfTBuXXeabdf20wqqv4w+kPepq01bXDvY1Q+8sGsffrxOamizr2oUmjIj3brJ5li8nDjHGjcFJAQsR0aG9vqLYkov1Dkd6ZGwOrNYjvdW1iYPSwcHfjNV6yqa6NjrKKU/QPlfOuSsKor67tzC+CgCZkdOT2UjAoKSAhYjowmePmKfIxt9lDbY1y+aOdXwgCWv/qLWtTVx8+Yy/GUFOvVLXJpcr5nLAQSa2rnZWLEfn0qECALmYMoRRbgxGCliIiC4s30/oZzYe3XN2Ko208YNljY9xls+pIwS5C/MnOc8KOcwBBxmZ6nBcGZ3Z88uU1Uz9CgBy8NdG9xmPiE6kgIWI6MJV8+mIyIZkgBR8Zl+39pR8n7oa5ssaG/TXLIpuXEaQu7Brg/OXfE6Aa5+mRsvq3pGwbD+dOYrxbgDIjTyn1PsHoh9SwEJEdOHYvmTS5ELWSF239iTfp43b1+L98jdtOB/CgtPMph5fpKwW6lftEve/GROUkzMBAHQY4mJEHtGpFLAQEV3IqWC5WTZbL89p9QK62YS925x35kTJXgS5t1Jd6SzIfepvFP4yUbop3n8zJnjzCuPdAKCHTCeo9xBEr6WAhYjo0ltXebHPxr7teh+XcvIeWNYfU51nI0XN508IcheG/Kq/S71hKaOXmZgzlvwrPy34vKJ1tBkAQIcLp+J5kjKaJQUsRESX7tnKaEU2blzWG5V69ZyihuDmdLqoefIwxUphwWT9YuWpo6xZe0g3X5+vyb/yU7r/AMAJjQ1pcgnRdylgISK6dOGUGvXZDR9RU522unxiX7ePLfw+pf7XEknFO2djZVGVbqI2nJzW9PoFBd72IDDYf7eu5u8VAJwxawydseivFLAQEV06+OdK9bkNCrlGpeZNpAgonD+RjLb7qUPp6BCuntfrTiz8jgJvJsp2NtjWC71VDhwAAHDCAe7N6LMUsBAR8/D9W7ojsiEFKnXNPnb3FsYwhc0r62xrE0d7fpmyWviTsaqrcncninPGUfDLxMIEZMaFadcOFVZdLacuAIAzpGtYvZ8geikFLETEPJTOGcjM9pLso1K3r7HDL0wbnpyW+2ePqWAJv3XJ3p0o7lhHgTcTA3/MvX7o3gkDqtQlBwDQYmQP7s/onxSwEBHzUDpnIDPZRuO6dZATrtjhlzDqXp2SE3rKqZNt6HQQXTlLgbc9Xj5jh99vyasDALdsXJaMrnIMRwpYiIh5KJ0zkJk3rzJ/aE4cyA6/kLQw6nWL+TAWSjdn706UEcPqSgq87VG+n4wVv6W7GADconsKNaIbKWAhIuZhr6/I9MlF32/a7y5av4RChnBkT7I+xqcMoXApXL+Y/QV/WDcOicjE8jm1tvVC76R4CgD50NJsWX2+bv/dDzFfKWAhIubpk4fN6rMbPiJTvtOZcnb4hRVFyfoY7/FFqvXlNunU5AhyXzSdEzozIcU9db3QO0f3psgMAPmhMyaP6EYKWIiIeXp0X4P63IaPkE4rdc3Ed29oXRNG96qyrU3cpejbxtCumQsx+7YT4N4eqXdp21qht65ZWKsuOwCAI46VJau7HIOTAhYiYp6unMfLfjbae4kZ/AvjUYIcU9/1U/s1FXf/LqPoKxT/nnmH+s51inztIZ2b6lqht546QncsAORHZSp7lzGiWylgISLm6Zg+jFtko72Q8uJpjEcJuXKQ4uraYoq+wu4t7Qe5c0JnZkqKkzVyG4bv39IdCwD5M3FA8jrM0X8pYCEi5ql00NTX8bGZieZmyyr4/L9rVraDDhxh18b2Cxhxd9Igir5CpgLmuELWJxNj+/JB5KccHgAAXrFjXTLfcdBfKWAhInrgzStN6nMbPmJcv/9+dD64zXiUMHdC5hGyONu9Y0VrYTPp1Na0P2KxegEdau1RV5PMkdsgXV7EtQcA3vDgjr0DHzFfKWAhInqgjAJBZj4+9r57xxTFi//Rv3Nyj5mW0VKwrGEF9iD38v10KLbH5bPtd6yhd5JPBwBekU5b1sAf7c84xHykgIWI6IELJpPplI392z+0kf8+tFr9jxPJm5cttusoSXJ6ZxuSB6euzVNOaWyXLavaP9EUvfPVC/KvAMA7pKtTvc8g5iMFLEREDxz0E7kh2ZARy3/XSj5CwWo96Uu9jpIkY3Jt7Nn634yQXl+lrBZqCO0yZUi17TpC7xzIcwwAPObssWS/66D3UsBCRPTI92/46syEZNf8m/Vz4RRHtAvrFye7m0ROJwLLunH5v2Nx04bTodgeTf/cNiQ7Tb2O0DsXTaeTGAC8RQ45Ug/yQcxHCliIiB557jiFmWz81qWytYhVmeLERkFO4lOvoSQpL7RNnH3wn+KuuHkFHYrtceujLk70x0OljPUCgPdMH0H3LHonBSxERI/kwzM78yfVWMMLGFERJMRewuzVayhpPrxD1pMwovuHkFsZtwA7uzZwHLvfPntEFzEAeM++P7l/o3dSwEJE9Mhpwxj9yca+7fXW+iUU+YQHtzlaWjyyh44PQUa3/l2Tt68pIrTHrDHs4Ptp4Xep1hPDAAC85sXTZB9ag95KAQsR0SN7fpmyWmgoAQ0O7GywXT9JdNV8gtyFvdvadqcHdE6p/xH8g4Ta9+5Ex6KfcpIuAPjJsIIPncaI+UgBCxHRQ588oIIFuVky40PHTZIdX0iQu/BvvtO8iRQR2kNGTdVrB71VOmQBAPxiXcIPrkHvpICFiOihR/cyEgW5GdaNnUix4LOK1tPlko6c0iRB7rs2UkRoj/3byU/xW/LoAMBPrp7nIA70RgpYiIgeumIuI1GQnerK/546l3QlDwws6/jBRuvVC/Kv2mPhFDoW/VTGM2VMEwDAL2SzqtdXjIJj/lLAQkT00NG9GYmC7Fw6wy7kxx4qpWsRsiPZYOp1g945ZywHkACA/8hp1Or9B9GpFLAQET1UOmvqajjKCTLz51pyID6WrkXIBqdX+W/pJkZXAcB/ju7jABvMXwpYiIgee+Nyk/rMBvh/Zo2utl0zSXZsX7oWITN88PjvneuM8QKA/1S8I0IB85cCFiKix5ZuZjcb2iedtqw+3zAO9bFdO1RYjQ10LUL7LJ1da7tm0Du7d0xZTey5AEBAjCusst2HEJ1IAQsR0WNlxh+gPZ4/ZhyqPe/dpAME2mdoF07s9NPpI8i/AoDg2LaGGAXMTwpYiIgeK4HDAO1xrIxxqPY8sIsgd7Aj4ybqtYLeur2EjmEACA7ZsFLvQ4hOpICFiOiD795wJjnYWb2Acaj2XD6HIHewc+poo+1aQW+9fpH5QQAIDolS6P8DUQroXgpYiIg+ePZYo/rMBiD7IYOjexPkDnbW/kHB10+7daiwGurJnwOAYFk6i3s7upcCFiKiD25aXqc+ryHhSFC5fDCq1wpWWF0/rbDq6/iQhv8ihU31WkHvnDyYwjEABM/pcrpr0b0UsBARfXDqUIJx4b/cutpku07wg3euE+QOH6ip4rh1v928ko0WAAie2ho29NC9FLAQEX2wxxcpq4XvcfiIPVvrbdcJfrBsB0Hu8IGLpyn4+u2lM+RfAUA4/D602nZPQtSRAhYiok8+vk8FCz6wcEqN7RrBD0omBsC/yBi2eo2gd8rYbk01Y7sAEA67t7Cph+6kgIWI6JOH99BRAh8Y/HOl7RrBD47qRR4PfGDSIPKv/FQOlAAACItnj1ps9yVEHSlgISL65IoiOkqgjYp3adv1gf9V8o7qaukIgbYDDwo+s18j6J3rF5N/BQDhMrQrG3voXApYiIg+OZqOEvgfZ49x4o6OEnQPcOMy+Vd+K/ckAIAwWftHre3ehJhLCliIiD7Z2lFSQ0cJkOej677t9erSQQLZuZ5sFD+VZ1NlBc8mAAiXy2fZrEDnUsBCRPTRG5foKAFO29F1yYwadekggcwcxd+Ln47sWakuOQBA4DQ2WK2ndqv3KMRsUsBCRPTR0k10lCSdlhbL6vklL2g6jujBh3XSaWm2rF5f8ffip6sXkM8IAGZQNI4NC3QmBSxERB+dN5GOkqTz+H6z7brA9pXRplrGbhPNg9v8vfjtycPkXwGAGRwqbbDdoxCzSQELEdFHB3ROqc9qSBiHd/Ny5sSbVxi7TTL7/iT/ym/fvm5Rlx0AIBTkfiSbV+p9CjGTFLAQEX2Wj4Vks3wOp+w4ce82xm6TzPxJNbZrAr1zaBfGdAHALEb3rrLdqxAzSQELEdFnz/zNuEaSkcBk9ZrAzC6axthtUkmnLavwe/Kv/HTZbPKvAMAsNq/kpGbUlwIWIqLPblxWpz6rISHU1aRpjXfosAI6RJLKs8cttusBvbV8X4O67AAAoXL7WpPtXoWYSQpYiIg+O/W3avVZDQnh2gVeypwqBb+aaoLck8jhPeTF+e3LZ4y0A4BZyGnNfb+l+xb1pICFiOizPb5ItR4ND8lj53oCqd14/SJB7klkyQzyr/yUQ0UAwFQkPkC9ZyG2JwUsRMQAfHSPClYSKRpXbbsWMLe7txDknkSG/EJenJ8Wky8HAIZy4lCj7Z6F2J4UsBARA/DwbnJHkkj/H2iJd+MfU/nQThrv3pB/5bcH/+I5BABmUl2Vtrp+ar9vIapSwEJEDMDlczj5KWm8esEHuVuHdiHIPWmcPMzuu98+eUgnMACYy+TBVbb7FqIqBSxExAAc2ZMP8qRx8ggf5G6VIPfqSoLck8TqBbW26wC9s+83KSvNnxQAGMyujeSGYm4pYCEiBiAnqyWPdYvrbNcB6nv1PEHuSWJUL3be/XTeRMZyAcBsHt9vtt27EFUpYCEiBiQnqyWLiQP5IM/H0k0EuScFyT6RIr96DaB37t3G3xMAmM9gDvPAHFLAQkQMSGmNhmTQ1GRZBZ/brwHUd+EUOkaSwoWTjNv67f1b5F8BgPmsmsc4OWaXAhYiYkDOncAHeVK4d5M2+Hwd8iu5cUlh4zLGbf2055cpq4X6FQBEADY0MJcUsBARA7Lw+5T6nIaYUrajwfb7o3MrU+TGJQHGbf111uhqdckBAIykvi5tde9ov48h/isFLETEAH3zqkV9VkMMWTS9xvbbo3OvnCM3Lu401Ketgs/svz16564NjK8DQHSQort6H0P8VwpYiIgBerq8UX1OQwwZ2pUQUi/kwzv+yOEW6u+O3nrrKoVgAIgOZTvpYsfMUsBCRAzQDUvr1Oc0xIzqSk5U88r5k8iNizvbS+ptvzt6pxwm0digrjoAgLm8ftFiu5ch/isFLETEAJ0yhCySuHPxNB0lXjn4Z4Lc4870EYyK+OnvQ3nmuOHsMYKk0Z3ThvM35wUjetDJju1LAQsRMUC7d0xZzZwGFWu2reFENS9NvSPIPa7IyXhyQp76m6N3yv0InMPJmOjWbh0qrNoanlv5IhML6toiihSwEBED9uFdKlhxZuYoOkq89NIZ8nviyr2bzbbfG7316nn+ftwwZQgnY6J7zx0n7zRfblyimx3blwIWImLAHiolkCSupNOW1ecbOkq8dMc6gtzjyp6t5F/5adcOFVZdLZ0gTpEuaemWVtcTUdeV82rVywocIn+Hfb7m7xDtUsBCRAzYZbN5sYkrzx4TPOq1cycQ5B5X5LdVf2/0zokDq9QlBw3u36IzEPNz0E+VrRtakB8Lp/CMQLsUsBARA3ZkD4Kp40r5fo5+9tqBP/L3Ekfk467vt+yu++mm5eRfuaFsB/dxzN8nD4iLyJe/y/hbRLsUsBARA7bLJxVWTTVbc3Fk1fxa2++N+VtBkHvseP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AIzYAFAAAAQGgGLAAAAABCM2ABAAAAEJoBCwAAAIDQDFgAAAAAhGbAAgAAACA0AxYAAAAAoRmwAAAAAAjNgAUAAABAaAYsAAAAAEIzYAEAAAAQmgELAAAAgNAMWAAAAACEZsACAAAAIDQDFgAAAAChGbAAAAAACM2ABQAAAEBoBiwAAAAAQjNgAQAAABCaAQsAAACA0AxYAAAAAIRmwAIAAAAgNAMWAAAAAKEZsAAAAAAIzYAFAAAAQGgGLAAAAABCM2ABAAAAEJoBCwAAAIDQDFgAAAAAhGbAAgAAACA0AxYAAAAAoRmwAAAAAAjNgAUAAABAaAYsAAAAAEIzYAEAAAAQmgELAAAAgNAMWAAAAACEZsACAAAAIDQDFgAAAAChGbAAAAAACM2ABQAAAEBoBiwAAAAAQjNgAQAAABCaAQsAAACA0AxYAAAAAIRmwAIAAAAgNAMWAAAAAKEZsAAAAAAIzYAFAAAAQGgGLAAAAABCM2ABAAAAEJoBCwAAAIDQDFgAAAAAhGbAAgAAACA0AxYAAAAAoRmwAAAAAAjNgAUAAABAaAYsAAAAAEIzYAEAAAAQmgELAAAAgNAMWAAAAACEZsACAAAAIDQDFgAAAAChGbAAAAAACM2ABQAAAEBoBiwAAAAAQjNgAX133GubrQ++ezM9etOKuY5jyuRwfixcfqzS48fkOeuU+Y6fPfv3+lc7Pwbt2Ne4Xi9FJ7zOuQVRGbCAvstvOnfvbqnHLj3/0Y5jyuT4yDmPpj9y7aULz9zccfyYLGsPyVo7tqc/ee2vbVt37zl26fGkvy5oX4O09PrkRVs6XgtADAYsYCAefnBX+vuAFtgN12zrOJ5Mjhuu3pb+yLWXrrlya8fxY7Kc9sZN6Y9dC+iH/7yj41jSf9/4suv1Uuy2W51fEJUBCxiIb13vT+q9dvePd3YcTybHA/cadxfa7T9wEzHpLjnfOxJ76cpLjbvD8MB9rtdLsZ07W3s+Ppq+HoDRM2ABA3HZBVvS3we0wPKP06w5uPOYMv7yX4h9vHbhbd2yu7V6eedxZHKsu9Y7XHrpvSfPdxxL+uuEI1yvl3L5s7DS1wQwegYsYCDe9WYfC1lMM2/Y1HFMGX/5w6pVrLe93pcaTLKf3e8dLkXbtbPlAe5DcN7pnn+1lFv3NY9zgIgMWMBArD3Ug3kX04Xv85e/SXTV5VvTH7X2k3Nhcr3hr7zDpZfuut3HzIfhq1e6Xi/l5pq7W/VK5+sCGC0DFjAwP2n/kq3euvoKzzeZRPmDl1Ws/CYyPY5Mhvf9H+9I7CX/PgzHPXf6HWapl3/JRPq6AEbLgAUMzLVXebZJr/mGqcmTP8tpy2ZvNynaHeu922RSffbjnpXYS+ee5l2Jg5a/O3CXT7cu+T5/mbEYojFgAQNz4ZmeH9Fr85t2dxxPxtvbj/NcuF7atnV3a7UvNZhI373J58yLln/kMn+4eHos6a+z3+HdgfKt0BCRAQsYmLeunUt/F1CBTqx6ePUk+cQHH01/xFpgM8f4GMckamz0FpeiPXDvro7jSP996dOef6WfD8ZvWuF3MYjEgAUMTP7wy/k5H5nqtQ+808dEJsk3r/Nuk1676KxHO44n4+3EVf7A0Uvf+LJvRhuGO2/z/Cv9vI+c498fiMSABQzUv9ziodW99rlLtnQcT8bXww96t0mvfe0qN+2T5rzTfcS8ly440x82Bu3ow5qtHX510S+6Zd32jtcIMDoGLGCgrrzU2/B7zS9Nk+OE1zXTH68KlL8bIj2mjLcvf8a/Db3ko+WD996TPf9K/7+tW3a31h7a+ToBRsOABQzUWaf4RbDX8nfspMeT8fT37/Juk8XkQe6T57bve4tL0TZu8G/CMPjDm9LyUTN9nQCjYcACBuq4w5t7HoKp4uXH7djX+LapSeDdJotv5g0e5D4p8ucjbtnsH4ai5c/RS48l/XfbrcZV/XrXfG5rx+sEGA0DFjBwDz3g2T+99u6T/NVvEtyx3gOBF9tHzvYg3UmRf6ukivexc50Dg7b2kGzPOz6lX+3Bn3r3I0RhwAIG7qav+/a1Xrv0Q25Yxt2ag7PW9m1uiBbbtV/wIPdJkX+rl4r3tqM9/2rQTj/RuKruvXWt8w8iMGABA5ePMOqtG69x0z7u3vVmN0T9yIPcJ8fXv7Qt/fFqP21q7t7z0cv0WNJfn/7olvTQS3u67ALfDA0RGLCAgTvtTW7ge+2eH7tpH3efvMgNUT/avq21591s6fFl/OTXNRXruzd5/tUw3Hqz51+pez/47o6O1wswfAYsYODyrx/e4VOEPbWj/bt0/kyO9JgyPm7+v178/eqUYz3IfdwdNZ21dtqvCpcP4emxpL9WL89am+d93Fvdy38fO+YvfbEOjJoBCxiKu253x9JrbtrH2+wjvsSgX118jmfCjTvPGOqtd77RvwOD9o4TvDa17849bXPH6wYYLgMWMBRfu8ozT3rtorPctI+rt1Tn0h+nFlH+7KT0GDNeLr/AR2qLtnXLbh+fHQKvTe2vG672bxCMmgELGIoLztyc/h6gBXbN57Z2HE/Gw4fO8LrvZ/k7OdNjzHj51vU+Ulu09d/z7J1huGWd16b2XTbryxRg1AxYwFC8dY13ovTabbe6eRlX3nnY3/Jn6Xknynh7+Gc+Ulu0z13i+VeDlo8Sc5nnX2n/veN4H+eFUTJgAUOR/3KYfw24ipc/VNZf/MbT3b5tre+5eRhfxx3ebO32z0Dhzvjb+Y5jSX+97fX+yKaFdcUnDMowSgYsYGi+f4uvp+61/FlK6fEktqOmm75tbQBd/AHPhBtXZ50yn/44tZ/ya8jRh/nms0H7+HmPpode6tqdt/koO4ySAQsYmisv9YDUXvPNN+PnjLe6WR9EHuQ+vvwbUDw3y8PxrW94/pUWVv4u0hNeZ1SGUTFgAUPzfn9977n8xi89nsT22Y+5WR9Ed9/hhn5c3fod78It2pc/40s8hmHjBs9m08K78H3+qAijYsAChsbzT3rvn765veN4Ets/u1kfSDvah3XtoZ3Hm/g8JLt455zqRnnQTqp7/pWK9e0b/E4Go2LAAobqoZ/6K2cvbXhwV8exJK4932jlSwsG1qkneJD7uPkbI0Hh8j/45H/4SY8l/fXhszz/SsV6dPNu34gLI2LAAobqm9d5zkQv5Tcyx7qRGRsnH+VmfZB97FwPch8355+xOf0xaj/df7ePyw7DjddsSw+9tN/efZJvB4VRMGABQ3XJ+f7S2Wvv8cvS2PjI2V7ng+wbX/Eg93Fz9RVb0x+j9tN1X/Q6H4aHHvDOcBXP8+lgNAxYwFC9842b0t8BtMAuu8CD3MfF9V/xF/1Bds+PvTNl3Nyx3jPhipa/ay09jvTXG49spoddWlA/vce/QzAKBixgqNYekrW2u7fvqRu/6q/x4yL/xVaDy4Pcx8vq5Vlr6xbPhCvaiavmOo4l/eWjrVpMb6k5R2HYDFjA0N15m5v7Xrr3Ln/tGwfHvsa3bQ6jU//ag9zHxduP887bovnijuHIP6Yp9donPuh5jDBsBixg6L56pWeh9NKed50c0nk8ieX9p8ynPzoNoI+f58ZhXOQP3Vex1l3rHbfDcL93y2oR3Xrzjo7XFDBYBixg6D7kLfs9l7+TIT2exPL5ywy0w+iGq93gj4v8Z6ViXfwBA+2gHXe4d8tqcW3ftrt19GG+IRqGyYAFDN1J9bn0dwAtsA+f5aYmuvXf87DqYXTPnT5SOy7uv9u7XIp28lGerTNo557mj2lafGe/wzdEwzAZsICRmMv82bOXrrnS1zZHVq9krUc3e20Po507W62jpv3lO7rXv7rZ2mW/KtRcc/eea0l6LOmvq6/wblktvq9/ybuBYZgMWMBI3Pod71Lppdu+73kLkZ1yrIdVD7PT3ugjtdG95yTPhCvaLeu2dxxH+u/uOyyrWnwbN/jCBRgmAxYwEp+7ZEv6O4AW0OZ5f5mPLH+wuIaXb4CK71Mfca0v2uUXbOk4jvSXdwaqn80c448pMCwGLGAk3j/jr/K99paaZ6NE9c3rtqc/Lg2wG6/x0Y3obr7ROVG0U09wMzxovi1W/ezTFxudYVgMWMBIHPsa3/7Ta/mDZ9PjSQwPPbAr/XFpgN33Ew9yj+6Rh50TRdq6ZXdr9cGdx5H++sI/ev6V+tftP/B4BxgWAxYwMg/+1I1NL115qQe5R3TC65rpj0oDLv8IkAe5x+WcKN4PvutGeBjuWO85nOpfu9q/zh73Wv8WwTAYsICR8XGr3vruTR7wG5GvZB9N73qzj1tFdc6pzomiXfEJH0UatKOms9b2bemRlxbX+Wd4dzwMgwELGJlL/sEDr3vpkYd8401EX/6Mj6SMovw6kv4siOGqy50TRXv3SfMdx5H+OuOtnn+l/pf/UTZ9rQH9Z8ACRubUv96U/vuvBZQ/O+zYw71VPRofSRlNN37Vg9yjyj8Op4W3o324jj7MtX3QfAuyBtH8pt2t1cs7X29AfxmwgJFZc3D+Nn5Pcu+l/C/I6fFkdPLX8ratXsuj6P67Pcg9onola83POSeKdMd6r+VhWP89w6oGk4+0w+AZsICRuvO2nem//1pAl1/gOSmRnPYm7yYcVfnDc1//au9aieZv186lPyrtpy99yhd0DFr+DY/5Nz1Kg+gLn3QOw6AZsICRuuZKz0jppXVf87GpSC6/0EdSRtnpJ/qrdzQXnukB7v+PvbPsjuPY2uhfTJw4iYMO2ZbZMsbMFLNMkRlltmOITDIqZmZmRo0Yp98c6ea1U62Zqe5pqO7ee6396a57k1vTajh1zlNOmTOWzlq/lQ4ZAL94dI8uSkS/pYCFiKEqp7aAcx7f5yXJJM+Uc6JmmJQUE+RummU7OObNCa3Zhl/TSei3m5az2QD+IX/Hg36qtF13iOidFLAQMVR/68KYiRuamy2r4HP7emI4vnvTov5EECB0JJon4+HOYFMiGC+eJv8K/GXVPDZUEP2UAhYihm7qPXkUbhjXj7EpExz8C0XYsHn6kI9/k+SADucc2EkR1m9bDxao4roEf7lwstF27SGid1LAQsTQZUfUHcvnsMtngozBhg9B7mY5vj85Q075Y2qNbR3RW8f25boE/5FDArp3tF9/iOiNFLAQMXS3rSGTwg37t3PajQmS9WMGU4bQkWiKa/+oVX8eyMHAH8nN8duSRVyXEAyzRnMgA6JfUsBCxNCdOapaffaDBjevNNnWEoP3/i2yfkxg3eI622+D4SiZZKDPq+cttjVE7z3zN4dtQDCUMRKM6JsUsBAxdHt3SrWe3ALOqKlOt2Z6qOuJwdm9Y8pqYgLWCI4fJHfEFJ895lADJ/zNIQSBWPGOFw0IhtcvKEoj+iUFLEQ0wud88LhCTnFU1xKD8/ehdA+awrNHfDCYYK+v2JBwyvIi8gz9dkQPDtuAYJFrTr0OETF/KWAhohEycuKO+ZMI/g3TLavIbzMFKZpI8UT9jTBYp4+gqOuUYQV86PrtqnnkX0GwbFjKWDuiH1LAQkQjXL2Al0s3bC8hyD1ML5wiU8Ukpv5GcG7YUtR1Rupd2raG6L0yYgwQJDcukVOK6IcUsBDRCMcVcry1G86fIPcnLCV/rDLFrJRJrF/CjnfYnjtOocAJZ8q5hwfhm1fEFECwNDdbVp+v6QpG9FoKWIhohN06VFgN9RQDnCIv5epaYjAOLyBTxTROHKIYELbv31AocEJJMflXfjv4Z+7VEA4LpxDzgOi1FLAQ0RhvX2tWn/2gQd9v2eELw2WzGXs1DTkMQv2dMDgH/UShwClj+1bZ1hG9dcnMGnXZAQKBE0YRvZcCFiIa495t9eqzHzSYNpzcnzA8vIeDB0xDgtx7d6KgG5YLJlMocEJdTdrq+ql9HdFbj3CvhpCorEi3xg2o1yQiupcCFiIaY/HvfPy4gZNuwvHJAzoGTeT3oRR0w7J0E5sQTrh8lpDnIHz+hLFWCI8JA+iyRPRSCliIaIxDfmX8xA3HDtCiHrS9OqWsFr6JjISCbnhev9ik/hyQBTmxUV1D9Nb+P6RaOzMBwoLTohG9lQIWIhpl6j1vmk55fL/Zto7or7NGV6s/AxjCycMEuYehjMnISBzoM2UI3YJ+u3Aqnd0QLg9u846G6KUUsBDRKC+c4gh2p7Q0W1b3jva1RP+UHVUwkxdPCXIPw5E96aB1QlMj9+0gLNtJ/hWEi3QADvyx0nZtIqI7KWAholFuXV2nPvtBg3GFZCwE6dXzjEqZinws9PmaIPeg5VROZ9y6Sv5VEEqHMkDYLJ9Ta7s2EdGdFLAQ0ShnjGQ0yw3Li3g5CkoZlaplVMpoOJkzeA+V0unihF0bycXx2z7fkH8FZnD2GKPtiF5JAQsRjVLCsXnhdE7ZDoLcg3JMnyp1+cEwNi4jHDtoH9yh08UJs8ZQZPXbovHkX4EZSD5gwWf2axQRnUsBCxGN89ljjndzyq0rjKME5eoFjEqZzqkj7HYHqWQ5NTFVq42cYNq7E2Oufrt7C1mFYA7TR1C0RvRCCliIaJx/lzGK4hTZ3ZPRNnUt0XuPHeD6NJ2XzwhyD9JJg+hKdMLDu5xKFoT3btIVCOawdxtjw4heSAELEY2TDhd3DO3CKTdB+PIpHYKmI2PIfb+hwyUo1y3m8A0nMPLtvz2/TFnN1K/AIJ4/YWMF0QspYCGicY7rx26+GxZMrrGtJXprv+/IaIsKjGsE54lDjeryQxYWTuFe7bczR3EgDJjHsG5sNCLmKwUsRDTOrh0qrPo6qgRO2bGO9nS/nTeRUOCosGk5Qe5BSVeiMwZ0pjvQb3euJ/8KzKNkESdGI+YrBSxENNLb10gEdsqFkwRX+23pZj6KosLpcv4eglBGNelK1OfFU8aIgvDmFd4hwDyunufAHcR8pYCFiEYqYZfgjLev+TDyWzntEaLBqxf8PQThrNGMajnh6D7yr/y24PMKq5GzNsBAmhotq9dXdGAi5iMFLEQ00oVTGdVyg2Q0qWuJ3titQ4XVUE+rSVRoDXL/lr8Hv/1zLQHuTlg6mxEiv536G0VVMBeJIlCvWUTUlwIWIhrp4F8q1Wc+aEBwtX9OHMDhAlFjxkj+Hvz24mm6Ep3AabH+u3U1RVUwlyN76MJEzEcKWIhorO/fEgzslA1LCa72y/WL+SiKGptX8vfgt6n3dCXqUvEubVs/9N4r5yiqgrnIfaDLJ/brFhH1pICFiMZ6/gRHszvl+EGCq/1SQsEhWpz5m78HPx3yK52yTjh1lOvRb+UU47paiqpgNmP7VtmuXUTUkwIWIhrrllV0vDjlyYNm2zqiN0pIPkSL1wS5++ofZBU6Yu0f5F/57QRGvSECyJireu0iop4UsBDRWCXPCZzR0mxZ3Tva1xLzc+BPdJpEFQ428M89Wzkt1glj+tB14bcyRg9gOndvsNmI6FYKWIhorHLUcAtNL44ZX8hHktcW/06nSVSZOYogd7+8dYWsIV1qa9JW10/ta4jeSvQARAE5JbfwezZXEN1IAQsRjfbpw2b1uQ85WFHEmIrX7t9Op0lUkVFk9ffE/JViTH0dWUO6XDrdZFtD9FYJxq6u5JqEaLBkRo3tGkbE3FLAQkSjLd/XoD7zIQdlOzmi2Wvv3aKQGlXOHiM42w9lHA702byCQqrfju7NNQnR4dQRnk2IbqSAhYhGu2perfrMhxzcuspOv5d275iympiUiixvXhHk7ocruTc7YvJgRrv9VkLyAaJCTVW69dRM9TpGxOxSwEJEo5WjhsEZdTXp1lEKdS3RnVOHcphA1CkkyN1zj+yhO1aXxoa0VfC5fQ3RW08dJf8KosXU38hoRHQqBSxENFpyVtwxtGulbS3RnTL6A9Fm1hg+Erz28X3GanW5cZmu2CB8/5ZTXyBalG6ut13HiJhdCliIaLwyEgfOWDCZcFCv5FSr6LN1NflDXtrji5TVQv1Km53r+Uj122EFleqyAxjPk4fNtmsZEbNLAQsRjXfPVk6AcwofTN6Zek8HYNQ5d5ywXC+VsRfQZ+YoOgD9Vk7fBYgiQ36lYx7RiRSwENF4F06pUZ/3kIOLHNnuiezqx4O3rwly99INSxmr1UU61Xp9RQab3x4rI5MNosnqBbW26xkRM0sBCxGNd/DPFBGc8u4NH+xeuHQ2u/pxoX9nigheSVi2Pg9uMyIUhK9fkH8F0eQSG46IjqSAhYiRkHBW5/Tj5LW8PbybXf24MJsgd89885L7sS77/mSc228H/cQmF0QXOaVUcgXV6xoR25cCFiJGQoK0nTNjJB/s+cpJa/Fh2xqC3L2w8LuUurSQhfmTOFDDbxfPIGYAos2csbyvIepKAQsRI+HmlWSuOGXjMj7Y87FXp5TVQqNJbJAiuPobo3OLxhHgrks6bVmF39NZ4bd0ykLUOfhXg+26RsT2pYCFiJFw2nA+mpxy/CAf7PkoJ4dBfHhPLpwn7ljHqbC6PH/MNReEzx6z0wDR5u0r7hWIulLAQsRIKKc40Q3jjCcPCQ/Ox+0ldP3FjQEEueftlbNN6rJCBo7soavCb2WkVTrdAKLOqF5VtusbEe1SwELEyCgFGdBHjm/v3tG+jqjnlXN8qMeNOePIGcnHLp9UWNWVVAt0WTKT/Cu/XTCZ/CuIB5tXEPuAqCMFLESMjEf3kXPhlPH92dFzo3yo19bwoR43pKtO/a1R32HdOO3NCUN+rbStIXrr/u2MtEI8uHW1yXZ9I6JdCliIGBlXzqtVn/eQgxVza23riLkd3btKXUqIARdOkQuXj4um0+2iC5lrwfjwLp3ZEA8kJqPvt4y5I+aSAhYiRsYxfSgqOOXATjJY3LhqPsXSOJJ6l7b91qgv3S76nDxCsdRve3NSLMSM4mmMHSPmkgIWIkbGrp9WWPV1jHU54fY1WtLdeKyMcdW4QpC7e+/eoNtFl9UL6H712zljOSkW4gWnRyPmlgIWIkbKm1cI1nZCXW26Nc9JXUfM7vMnbOvHlaLx7HC7sVuHCquxgQ0EXUZzopjvlm6iIzAXF083Wavm1YZuHZmSWlSl0q2bteq1jogfpICFiJFy9xZeWJ0iwcvqOmJm+3Ese6zZXlJv+80xt+MLGeHWpbqKjYMgvHOdjsBcyCmN6rqF4aXTbD7qMmkQxW/EbFLAQsRIyZHZzlk41YwX2Kg4dwLXWJyRjgT1N8fcykgc6HHhJGNAftu9Y8pqoiaSk4E/mbGBtWFpnfqvBhnYtYFNFsRsUsBCxEg58EeOcXcKL0POZCwl3qTeE+TuxvL95MLpsnFZnW390FunjyD/KhdvXplzEua4fnRw6vLoXrNt/RDxgxSwEDFyyvHkoI+07qtriJklZy3+mNKVECWfPmRcS5eJAxkB8lsZBYbsnDpqTiegjNRKvhPkRiIMBvGMQswoBSxEjJxnjzWqz3vIghT81DXE9pWg6oZ6XrLjzryJjNU6sddXKauFfQMt5P5R8Jl9DdFbr19koyEX6xab1Ql47jjvbrqsnMcppoiZpICFiJFz03KyFJxS+H3Kto5od8IAxhySwM71jNU6cdpwxrV0kcKKun7orWw06DFxgFmdgCXF5Ojpcv6EOd1ziKZJAQsRI+fvQ/mYcsrMUdW2dUS7JYt4wU4Cl85QZHDi5pVsGujCKZf+O3kwGw25aGywjOsEHN2L302X+rq01b2jfQ0RkQIWIkbQnl+mrBbiWBwhXWvqOqLdU0cYcUgClSmC3J3I2LY+Ei6urh96KwXV3Ny+Zl4QuORgySEaoAcbj4jtSwELESPp4/tUsJxw4hDt6Dq+fUXQT1IY/DMhubq+4+AMLWRjRTZY1PVDb5UOSsjOnq1mdgJKsDzoUbajwbZ+iEgBCxEj6tG9HOnuBDlBTF1D/K8Df6xUlw1iDEHueg7onFKXDjJw7xb3Wb/t+mmFVVNNF08uFkw28/62aj5j+rq8esEBPIjtSQELESPpirm8BDlBThDr8QWdAdn8Y2qNumwQYwhy11MKfaDH3m1cU347rpAcJR0G/mRmh+nwAjaKnDCiu5m/I2KYUsBCxEg6ujcvsU6RE/bUdcQP7ttery4ZxJgrZwly13HXRv4udKGrz3/XLyb/KhdvXpnducNIsj4blpJfiqhKAQsRI6mEgdbVMEbghJXzam3riB+8d5NctSRRRZC7ltcukDekQ/qfx1Hhd3S5+i0HCuRGDiNR180kjx/kN9Tl+kU2WhBVKWAhYmS9cZkPKycc2EUgaCa7d0xZTVxOiWPIL4xnZFM2Csgb0uPZI7O7XuKgXI+VFVyPuShZZPZm1fIiIiB0aW62rN6dKIwjfiwFLESMrKWbGW1xwp3rBAxncupv1epyQQIwNejYFEf2IK9Gl0OlbBD47cieXI86mB4XMPgXfkcn8JxC/K8UsBAxss6fRLiwE+rr0q072Oo6YoW1aTm5KklE8p3UawE/uHQ2nRK6LJrOR6bfrl7A9ZiLxgbLKvjMvnam+foFOVi6lO+nOI74sRSwEDGycry7c+QEIHUdscI6f4JMjiRy9Tz5ItmUsWPQQ7pK1PVDbz15mPt0Lm5fi8Y9rXwf9xZdZGyWzUfED1LAQsRIy2k2zvhjKl0C7Zl6R65KEqmu4sMgm/dvcbCBDqaf+hYX377meZ+L3Vui0VW6ZAYd9E4Y39/ssVDEIKWAhYiRlhOJnMHIlN1h3cjjSDJDfqVzpj0LPq+wmri9aiGnqqnrh946tAv3aR0kWkFdOxMd+CO/pxO2l9TZ1hAxqVLAQsRIS3aRMy6dicZ4QZAumclOcJJZOCUaH3xBO3FglbpUkIFV88w+9S0OLiOPTQspDKlrZ6ovntJRp4t0w6rrh5hUKWAhYqSdOpTT45zw/i2jLqpyehgkl9JNdCW2Z0kxBQNd5LRGdf3QW8lMys2bl9F6vvPs1Sedtqz+nVO2NURMohSwEDHS9vgiZbUQ0+KI/j/wEvSxj+9zASUZgtzbV8biIDdVKXLUgvDlM7p1cnHySLRGWSWTE/SRLkR1DRGTKAUsRIy8FCCcMXNUtW0Nk2qvr1JWC99FiaaGIPd2ZbxHDznBVF079FZOHNZDuibVtTPZwu9TrZ1FoMeZv7nXIIoUsBAx8h7eQxu6EyQ3TF3DpCrFPAAJiFavjSTb52s+LHXZsJT7qd8WT6NTR4conlT35CEbkLrU1aStgs/sa4iYNClgIWLkXV5EVosTTh5mF+9f/1zLIQBgtY6yqNdGkqWwq8+EAdErGkTNg3+xSZWLxoZoFjfKdvLbOmHacDroESlgIWLkHdWL07Kc8OxRtIJe/fTK2SZ1eSCB7N5CkPvHbltDYVeH+rq01a2Dff3QW+nSyc2tq9HM8ps/ie46J+zdxrMKkQIWIkZeya+R1mrQQzKfJPxeXcekKdeN5B8BXL8YzY8/v7xwkgB3Ha5d4Lrx277fMM6qQ1SL8Py+znj+mA1IRApYiBgL5QMU9JnI2Is1ms49+B+1NQS5f2zFO74odZARZHXt0FvnTaRDRwdZJ3XtouLDu3TYOWFYNzIbMdlSwELEWPjXxnr1GQ9ZWDUvWqcV+eHKeWSnwQf4KGhz8C+V6tJABsij8V8ZmYLc9O8c3a5qfmNnRO20SUSvpYCFiLGQXVpnHCptsK1h0izfT3gsfKD49+h2MHjpwincS3VobmYUOwgf3KY7JxevX0R7rGzOOA6NcMKVc4wuY7KlgIWIsXBA55T6jIcs3L3RbFvDpClZEkmmsiLd2olH3lEbe7ZGM0PGayVLB3LDPdR/e32VslqoX+Xk5JFonyzcqxO/sxOa/nlk9/yS4jkmVwpYiBgb375KdkHCCXJ6VpIzf/p+S3DsueNtHz103LRx4xK72uLNK+QJ6hDV0OwoOWsMnTk6rI3BSNm9m1SwnDB3Ah3DmFwpYCFibDxTTieJE0Z0T27mT9F4ijabV7QFUP/WhcwjQU4yTXJRV2w90bU24ZVdTYrGkX/lt7vIttRifP/oH8pSuonf2gmH9xADgcmVAhYixsaNy+rUZzxkIcmZP4T+W9a0YR8+wCtTFC2E4QXJLeqKo3tzMqcO0r3Z9xtGePz29jW6AXPR2JC2Cj6zr13UnDmKbjsnvH/bkvgNF0yuFLAQMTZO/Y0XICdIEUddw6R443KyP4xaWv6boSGhsGBZi6Ylt6grrijiZE4dnjwg/8pvu3essBo5ZyMnt67GY/RZDkSQbCfQZ0yf6HfeIbqRAhYixkZ5ASIIVJ/LZ+Px4uvUrh0qWjPAkszj+//9AGdUpw05zl29XpLk4d1UDHQ4+BfjO34rHaKQmzhlsUkxDvTZuqotBgAxaVLAQsRY+egeFSxdKt6lbeuXBCUvJOmo+RkLJpMJJkiAuXq9JMmHd7l/6lCc8E69IPxzLZEAOsybGJ9rccc6NlKccOc6naCYTClgIWKspIPAGf1/SF6OS0kxY1LLi/57atXgXwhyFyTAPKm5It07pqxm6ldaDP452VlpQXjtAt04OvTvHJ9nOF13zpAogH7fxef3R9SVAhYixsrlcyhOOGHW6OSdpHXyCEEbo3rZszMqK5I9VvkvST2dc8oQPh51eP2ixbZ26K2MeesRt2ux4HPJPeN3d8LiGfHpwEPUlQIWIsbKkT3pJHHC5hXJy1B486pFXYZEkanLSDLRILkfBBuWMrKlw7ED5F/57aRBjHnrcPJwo23tou71izyHnCAbcuoaIsZdCliIGCvlw7ymmh08XZL28jPwRwqcMpqjrou4cz35I8K+P+MTiuzEU3QmarFi7n/Hb9F7Ny2nmKrD2uL4XYvb1vDbO6GmKt3asaiuI2KcpYCFiLGTHTx9nj2O1whCLhdOIax814b2CzQSBgyWdSuhQe6vXiS7M1GXpI6YBunF0zzDdRhfaB8Fj7qTB9N95xQZ/1bXETHOUsBCxNi5ayOdJLpICGjPL5MTArp3G9dG0fj2R+QG/kR3miDZO10/ta9PnO37bcpK07iak8pU++O36J2yvtVVXIy5kKyobjHsvJFuIhlzB31KN7W/KYUYVylgIWLsnDuBThInSN6IuoZx9e4NjlnLdvJkxTs+HISRPZLVZTNnLAHuOpw9lqyR6zAc04cOHB3i3Cl6hTxGRzx52GxbQ8Q4SwELEWNn4fcp9fkOWVi9IH45Gu0pJxw1JTzmJ9epVYzutLFkZvtdanF1ewmdiTqsX5y8Qy+CtqSYk4R1KN0c364bMtCcM+TXZG26YLKlgIWIsTTpJ8054VBpMk7VkpyIpJMrtJ9CRhv7t8f347A9OYFSj3ExzBwyzTPlCd9l0EQyC9W1i4sTBtCF55SkbEQiihSwEDGWnuYlWBsZq1PXL46yq2tZ63J0kBSNo8gn3L4W3/Gc9pRsJ8hOazZaDDOHTJMxZj36d848Ch51JYOQ06Sdcel0sp5ZmGwpYCFiLN2wlGKFLg31yQitPnecomauvDPJx4Lk/E2IQ7sS3q/DlXN8IPqtnPAIuZETQ9W1i5sXTvG8doKE+vf4Ir5FTcSPpYCFiLF0yhBa0J0wIgGh1amE7+w3NVlW9472dVF9/4bxW2FUr+zFvri4aBqHXuiwdXX27kXM35XzyL/S4cSh7KPgcXD9EjYhnSKHcajriBhHKWAhYizt3jFlNXPgnDbF0+KbpyHSZWJZ927pjYqeP8HOt7B0VjIyRfb9Se6ZDlOH8nHot8cPcu/RYe0f8b83cRqlcw7+lYw8U0QKWIgYWx/eoYKlS+mmeIdWL5lBl0nZDr2X221r2PkWdNcr6t6+xn0yF9K9yHiO/3L4ih5JOEygyycVVhXZfI54+yr+o6WIIgUsRIytcroe6HHlbLzzXWRnMuksmq7XZTd7DEHuwp3reh1rUVZCySXvC7IjRT517dBbB/9Ml6wOrfl8CTlM4OwxOvKckpTRd0y2FLAQMbYunU2ehi6VFWnb+sXJR/foMpExSnVd2rPwO4LchSR8KI7rx5iODnHvUDXBJTPpktXh5pV4bzZ9rIxKgjPktGV1HRHjJgUsRIytEkwO+sT1WO6eX6asloTXr6or060jGeraZFJGEcCyRveO9272qvl8IOpAOLL/HtlDl6wOSSqmjuzJO5xTbiWowInJlQIWIsZW+WCvqWI8RpdZY+L5kTZ9BCNxl047e6lldKONZbPjHZZcvo+iQS7S/zxC+nwdz+K+ST5/QtFch7kT9EbB46C8wyX99GCntPzzZ9T3G+5XGG8pYCFirL16vkl9vkMGNq+MZ+s5oeRW6xqo65LNratYM+HAzngHuT95mPDWRA0e3yf/ym8Lv0+1FgohN/1/SFZx4uQRNlOcUvx7coqcmEwpYCFirN25niPidTl1tNG2fnHw8lmKmDNHOeuumzWarjXh7o34Fi9aR2tpeslJ3IuYJrhwKvlXOrx6nrxT5lbOY8zZKccPxvNdDvFfKWAhYqwtGs+LsS4ywqGuX9SVEYTqhI+Rto5AORwpkBEEOiIsq7HBsrrFNMh92jCKlDr8MZVuBr8t28koqw5JLEwM60YOllOqUmmr66f2tUSMixSwEDHWymgC6CEFC+nKUNcwysqR0knn2WN3hcnXL2jPEcb0iWeQu5xWBbkZ+KPe6Z3oXhnThNysWRjvTL5MvuFQEcdMGhTP5xaiSAELEWPvm5e8/OgSt5eeFXMZP/i7zN0I1Jm/yR4RlhfF86OR3zc3L5+5K/6ivtIdSrenHuP6xev5rOuxA3ToOUXiM9R1RIyLFLAQMfZKthPosXpBvD7WOWXN/W8qof5gWQf/clcANN23dDXkpHx/PH97k2TMX4/6urTVNabjzLmU02DBGQ/vxje/EZECFiLG3vVL+BDX5fDueH2wPX/MR/rYvu527WeMJCNJuHczfh8C/TszWq3D8jnuir+o7+4tHLSiw43LTba1S4qDfyYHyynS1TjwJ8afMZ5SwELE2Dt5MDlIusTpY53RFMtqqHe/a8/6tRHHIPe5E+h60UECpNW1Q2+VZw7kpnRTskfCXpHJ6BiJUFDXETEOUsBCxNjbvWOF1dSkPtqhPRob4nN6zZxxdBDdupLfrr0c2w7uu9hMddcGul5ykXqXtq0beqscGtJM/UoLKTqr65ckj+4lDsAp508k79RKTIYUsBAxET64w1uyLiN7xKPrgI90q3U8R10XJ5If10bcdrKvnqein4sz5Xz8+e3MUWwy6NL/h3idEOzURdPpGnWK5KYVfG5fS8SoSwELEROhBDGDHoumxWOn98YlPtIXTM7vt9y0nPw44VBpfLLhunxSYdVUMRuai5LieBUtTVROSoPcSCesunZJc0BnRtrdIEVidS0Roy4FLERMhEtncYqNLqWb8+vaMUHJfZLdx6QzKM8Q12nD6ZAQ7t+KTzbciO4EIusQt7FRE715hU0GHY4fpBtQ5FAW5+zfHv33OURVCliImAj5aNPnyrn8cpNMcHwhwf3v3+a/a9+rE7vegmToFXxmX58oumQmozi5qKuJTxagqcpokxyQALlZs5BuQFE6YcEZEn6vriNi1KWAhYiJkLEZfSoroh9evLaYjruzx7zZtX/xlF1vYVxhPDpyynbyEZiLy2ejX8Q33am/0d2py7h+8bj35OvCqRTf3TC8IL9ObETTpICFiImR4GJ9JG9CXb8oefIw4eOSX6WuixtZyzZWzotHF8S9mxxokYstq7z528HMbl1Nvp4OMgovI/Hq+iXRvt/SEeyG9Uu4n2G8pICFiImRwFh9Zo+JdvDnm5d0DU0d6s1vuGEpH5rC4d3RD3KXMcgm6pE5mTLEm78dzKyMqkNublymG/BjH9+nAO+U6xe5hjBeUsBCxMQ4ZxwjC7pEuQNh4I/knbW0WFbPL73popNCGFjWgzvRD3KfOIBsuFxIga97R/vaoXdKR1FdLa00Ovy1kRDuj5VQcnBGc7Nl9e7kzfsAoglSwELExFj4XUp9rkMGTpd7k58Uhgsmk5Px6J53xRYphDG28b8g98/t6xMlyYbLza2rdCv47QQKqdoUja+xrV+SnTeR57sb5L1IXUvEqEoBCxETpZzIArmR4G517aLi3m3s0MppTeq65OMzji9vZXz/aIcpHztAgHsudtHx4ruMJevT/wc6Zz62z9ep1g5jcEb5Pm/fCRDDlAIWIibKk0cIgNFBOm68GkEL2rs3yMhYNtvbwPHjB/m7EVbN93Zdg/Y5hciczIp4/l8UPH+C+4kOL59FdyPJT2WcG5yRepduPY1bXUvEKEoBCxET5brF7PzqMnlw9LpNZMSLkGrLGtnD22Oz+btp48ie6O5iSwYKo6DZkc4OsmL8VT6iqyu5EHWQjQN1/bDC2r2FLms3jC+M3jsdYntSwELERDlpENkbuqxZGL1uEym6JZ3aGu93WuVUNrCsh3e9yxYL2hkj+Q1z8TAGQf2mO7o392hdVi+I3jM4COWUZHDOn2ujezgP4sdSwELEREmHjj6HI9htsnEZnUJXz3sfQt3ji5TVwtRG62lOUT2hbusq/jZyISecqeuG3rr2Dw4S0GVsXzpm2lPiDeReDM64d4sCPcZDCliImDjv3+LNR4covuycPUZ1cud6fz7Cnzzk70aQE9TUtYmC5A7lhpO6/PfUUa5DHerr0lbXDvb1wzbJunSOjJBzKADGQQpYiJg4D+zkJC4dGhui9wJd8Y5slTnj/AmhPlbG340Q1bGe928JcM/FgM583Pkt16EeNy5530kbJ+W0UHDOUo8PeEEMQwpYiJg4l8ysUZ/pkIGRPb0NA/fToV0q1X/9RFL4vT8f4SXFjP4IRyN4HPngn/nbyMWLp5z45rfDCrgOdZECjbp++EEy/dxxppyDATD6UsBCxMQ5nJdobRZNj85IzeIZFCZfPffvI5wDENp4fD96o7UyGgfZiWJhMmquKKIIrkuRT520cbF7xxR5pi6oq0lb3SLWWY+oSgELERMnx3jrI8dVq+tnqgd2MeJ28rB/u6sSXk5wrtUaZi8fT+r6mGzpZsZtcsFojf8yhqyHZBUVfhete0wY3rrSpC4daDBtGMVRjLYUsBAxkV45x4uPDn6caOeXD+9SXSlZ5O9HuHQfgWVNHBitIHfJ04HsyAiyum7ora9fkH+lw0vGWbXcXkJh3g17tkZnYxKxPSlgIWIi3bGOFx8dKlNp29qZqByrLZ0xSWeizyfkle+jg0JY+4e/hUIvlY5TGRuBzMjhD+q6obcO+onRfV2OHWCcVcepQ8nBcsOzxxRIMdpSwELERDpnLC8+ugz80fzOhOkj+D0lD6Tgc/vaeOmahWTYCOX7o/OBOaoX2WW5OHXUv9FbbFPyFEGPqJ50GrQFn1VY9XUU590wtKv573WImaSAhYiJtO+3qdacCcjNnAiEyW5bU6f+ayeOuzf8DxeXDi+IVpD78jkUHXMRpY66qHqolO5NXcb08beTNk5eu8B4tBvWFnPPw+hKAQsRE6uc2Aa52bq6zrZ2pnnpDC+x+7f7n2shHV4EuVtWyz+3jh5fRCNkmcJBbigY+O+zRzxvdZCOoq6cEqft1lVsXrnhytno5JsiqlLAQsTEKie2QW7OlJs9XtN6qmQV7XSLptXY1sYPCctvY9KgaBQ9Ht7h98pGTXW69R6irht6Z7/v6HjW5fpFCgtOlPswOEciByQ7VF1PxChIAQsRE6uc2Aa5Mf1EpJE9CQcWfgvoFLUje+joEaIwgtG9Ix1zubh4moKB3y6YTP6VLrs2+N9JGyelW41DKtxRND6YTS9Er6WAhYiJdeJAdu50kJ3zXp3M3albUUQhMsjTIlfNZ72Fv8vMD3KfPJh7XC42LTd/RDrq7tvOqb+6FEUgc9I0iRBwx+Hd5j/DENuTAhYiJlbJ85E2asjNlCHmjksd3UdH0IVTwY15ji+kKCI8eWh+kPv6xeTD5CIqo6BRljFWPWSzqPA7czeLTHXjMu5zbnj/toXxaYykFLAQMdHeu8WLtQ4mn9L17DHhwEEG7cvR5RR+24LcTc8QIecvO40N6dbrWV039E7p3pW/FciN6eP6psqmins4wAKjKAUsREy0ZTvp3tFBco/UtTPBPt8QDizMGBns2MmD2xR+BZM7E8WXz6gcZOPGZfKv/HbO2Gp12SEDxw6Y+Zw13a6fVlg1HOTiCjnFUV1PRNOlgIWIiXbxDMJldbh/y8xxKT6O2sZO+nwdbCfQoVIKv4IcBKGujSn2pbibk53rCcz229JN5F/psnqBufcT0z1/gm5TN9y5bua7HWI2KWAhYqId1o0T7HRobLBaT/tR1y9s5QM06Tx7FPzYyYq5BLkLJndMzB5DcTcXM0cF27mYROUDGfRgnMu968j7c4WM9/Yjdw0jJgUsREy0EmBZlaJNQYdRvcx7ub5+kdOHyvcFX0QZ14/MESGM4qGu20v4oMtGS7Nl9fqKDzc/7d4xZTVxi9aivi5t5CZRVBzdm2eSW2QSQV1PRJOlgIWIiffyWd6wdTDtJUdyL+SlP+msmhf82Em3fz60JAA76ciInqlFkEunua9lQ3Lc1DVDb50+gi5AXWQzRl0/1Fc2IysreCa54eSR4E4xRvRCCliImHjpVNBj9xaz8mLoAmojrLGTezcZDRKmDDFzDI2Puezs+9Os+1kc3V7CiLcuuzZwPebrmXJysNwgAfh0/2GUpICFiIl3FlkxWly7YNYO8do/yGEKc+zk4F8EuQvrF5t3itNvXcj2y8X8SWZ1lMZRRrz1mTPOzEJ4lJQQfHCHqRsxiO1JAQsREy+ndelRXZm2rV2YnjjEbuvNK+EVFZcX8bEgHD9o3vhF8e+crpoNud8Xfm/m6GdclDHjhnoerDrI9UiQdv6O6EHh3i1yWqi6noimSgELEfEfXz5tUZ/n0A6Dfqq0rV1Yvn7Bb1a6ObyXThldBMt6/ti8IPe92xjdyoaJv1ncnDyY+4MuL55yPXrl+ze8F7jhyQMyATE6UsBCRPxH6aKA3BQZMubQ/4eU+q+WSMIcgyJEv43WIPdOZnVP3L7G6FY2juwJ/uTOpLl5JdmSuhwr43r0ypOHeZdzy5BfzNmgRMwmBSxExH9cW8w4lA7b1piR97NgMiNSwsCQO+Lu3iDIXZg61IzCrkhhMTdLZoZX+E2Kl85QRNVl1fzgT5KNqyvm8i7nFskQU9cT0UQpYCEi/uPEAYw76HDmbzPyfvZsZUTq7evwx07KdhLkLmxYakZhVxzbl3tZLob8Gm7hN+5KEbWmmiKqLmGdJBtHh3KAhWsung4vUxPRiRSwEBH/seCzCquJzvOcvHwWftFEvHOdzh8TiolLZ7PbLcjYiro2YblqHr9JNt69MeMeFmfHFVJE1aWuNt1a8FPXEN375iU5WG5obEhbPb4waxwesT0pYCEi/s97NymK5MKEvJ+Czyv+edFS/82Sx8Zl4Xf9jOrFh6rw/Ik5RZGje/njyIZJxca4un4x+Ve6XL9I14vX/l3GPdAts8eYMw6PmEkKWIiI/7NsBy89OkwZEu4LzqRBFE2EsH8Hscsn5C0JUtjtHXJh918f36cQnw1yXvz37DHamXXZuT68k2Tj6tJZdKG65cAuDhRA86WAhYj4PxdNJxhcBwm8V9cuSCVvKOm0NFtWzy/NKJhw4l0b04aFX1CU8Q+5NiAz0jWorht6pxS1KysoausyZ2z49424KYebgDvevjKnmxgxkxSwEBH/59CuvPToICNK6toFKbv7lvXwTrNtXcJy33YC9QUTgtzlNETITHVVurXAoq4beufInjxHdZHOzX7fmbERETclrxPcIX/D6noimiQFLETEj2TnODcPbodbPHn/hhfTQ6XhFhE/dskMOheFk0fCz1aSXDTIzIWT4f9GcVdGNEEPk7Lz4ubhPURCuGXT8vA3YxCzSQELEfEjL51hHCoXclpjtw72tQvCIb+yuy/I6X/q2oTliB78JsLLp+F/jJ4ppzsxGyYcfBB3JSQf9JCwcXX90BuLp7Gx4pabVzhYAM2WAhYi4kf+uZYOBh1Gh5QjQ05ZGyO6m9PiLyNZdTV0Lso4UJ+vwx0HevOK7sRsTBwYzn0rSb59zTWoy6p55mxExM3C71Ot92RwjuQohv0sQ8wmBSxExI+cNZoMGR1kbExduyA8sJOxgJpq83J8ZMcWLGv6iPACmeWDDTLTUJ+2Cj6zrxt659AudGM6YXRvCqp++uwRxVS3/DE1nHc8RB0pYCEifqTsOrFrl5u928I5+lvCy5POlXPmtffL9QDhZocUjac7MRvXL5r3dxM3l80m/0qXutq01fVT+xqidx7YxYaXW44dYLwVzZUCFiKi4oun7NrlIoyPwZ5fplpb25POjnXhFA+zuYi8kVZOHQ0vJHzneoqI2dheYt7fTdws30fBQJdrF4J/hibNBZN5LrmlMmVepzfiv1LAQkRUPH6QENpcVFembevmt9OGM94pzBkb3phaJocXMDokvHoeXpC7dOZBZsIc70yKL5+x+aOLFJzV9UNv7fsNHfX5QGYgmioFLERExbV/MAahw+Cfgw0S37qagH15Ge/3nXnhqrJTK9lcSUd+H/loUtfHb2X9pagM7SOdm9LBqa4beueAzmSwOWH2GAqqQfj4Pm3bbqHIiqZKAQsRUXF8/yr1OQ7tIJk76tr56aXTdJhIh4O6LqYoY6UQTqfPMDrgsnLvVrNtzdBbixkj1qa10P0tBdUg3Pcno9VukcxRdT0RTZACFiKiYrcOFVZjA90Mudi2JrjAaukwqUrxm8h4q7o2prh7Cx8KwuYVwf1d/OviGRQPshHWoRNJ8uBf5F/p8vyxuRsRcZPDLdwjhdaBPwXbaY+oIwUsRMR2vHuDtvNcnD0WXDFlRA86TIS1xbW2tTHF4t/5UBDOlAf3d/GvZTsoHmRj3sRgu0WT6JOHPDN1Kd/PCW9B2btTymohms01K4rMfefA5EoBCxGxHfdtp5skF0EGVi8vIpdMmDDA3FDVoV0pMgqvXwT3d/GvFNwzI10EhQbmxsVJwrKdsWoeRYEgvX+L+6Nbzh0PfkMGMZcUsBAR25E8j9zIB4vsbqpr54dH99Jh0tRoWQWf29fGFAkSbyPofBtGnrPz9CE5Ln4rHW6gz+je5m5ExFHG291TX5c2+r0DkykFLETEdvytC90kOkz9LZjA6mePmAGQLht1XUzz2gWC3IWZo4L5uxA5dCI7h0oZ1/JbyRgDPepq01bXT+1riP45a0y1+jOAA2aMDO55hqgjBSxExAym3tPVkIuSADKZ+nzNeIogpympa2OapZv4kBW2rAouyH3NQsZrs7FoOvlXfvvgNiNaukiRX10/9NceX6SsJvZWXCORGuqaIoYpBSxExAxePM0bTy6O7vO/u2E2u6etSEi6ujamuXAKo0RCkAcc/F3GeG02Bv/CKVp+2vPLlNVC/UqbnespBoTh7WtcpG4JMu8UUUcKWIiIGdy2pk59joPCgzv+j7XJCz9Y1pBfzf8Ql39HsKw3L4N74We8NjNvXgX3OyRVxrOcIRsy6hqi//IekR/DCsx//8DkSAELETGDkmMD2ZFgcQmRVtfOS69fpBOusiJtWxdTrUwx7ykEcfJdr68Yr83G8YPBdcIl1V0bKQzo0nrAwzf+3xfQ7vQRvM/lw/rFwY3FI+aSAhYiYgblhD0+DnMzpo9/JypJ2G1dDT/ChZPR+RC/co6CozBrtP+dFnyUZWfVPP8z+pLu7Wv8vevy/DEdgWHZvaOc1qr+IqAL2W1okhSwEBGzKC+ckJ2ls/z7SBzblxPWhK0BhoLn664NdGQIQfxmEhYPmRnZg7EXPy34nKKAE8r3+58ZiZm9cZliq1skBF86ftU1RQxDCliIiFk8doC381zIEerqunklJ6y1IZ026tqY6vxJBLkLQQS5nzveqP5j4X9UpdJWl0/sa4be+ftQOgCdsJKOwFD9cy0F/3yQZ7u6pohhSAELETGLFFByIxlV6rp5pWTYJB0ZY+3VKTo7n4N/JshdeBtAgPj7N3SIZuL8Cf8LiEmXg06cMbqXf+P2mNspQyi45kMQp04j6kgBCxExi+MLGWHLRXWVfwHjr17wgf7kof8nPXpt6h25ZULh9/4VHgd0Tqn/OPiIDUv9H+FMulfPM5Kli2Q5SqajuoYYnAWfVVj1dTyb3FLxjq5WNEMKWIiIWZQT9hobeOHJxeBfvM+akY9/iOau56UzfNgKs8f4N/rJqGZ2Jgyg28VPu/7zbKyr5dmoixT71DXE4KXomh/jCrmvYvhSwEJEzOGd683qMxwU5k7wPhuBD/Q2opibsmMdQe6CjFipa+OVf21kjTMhXRay+aCuGXrnxIF0JztB7onqGmLwbl7J2Gs++PlMQ9SVAhYiYg73/cmHYi4kHFVdt3zdvYV1F0b3jt6OpxQ0wd8cJsmeg/ah28V/Ny2nEOCEWT52Y6K+FF7z497N6EUaYPykgIWImMPi3/kYz4UfJ67dvkbnm4zoRDE3ZeBPBLkL7974E+QuOSQ11YxvZYIuAf+9cIoDNnSRgzj6fuNfHh7qK89T7p3ukWu5/w9cyxiuFLAQEXM45Fc+xnMhYevquuVjweeSPab+U5LHjUvR7SSRwFf452W/s/cv+yN7ck/KxrRhdLv4qRRQ5fAO0OPZY2+fj5ifF0/TvZoPS2dFL9YA4yUFLEREDVPveVnPhuzK9fnauw/1SYNo8xdKN0U3N4UOjTbmjPW+mLJsdq36j4H/0dxsWT2+8O5ehHbH9OH+7ITyCB7EEWflhFJwz+ly7zvuEZ1IAQsRUUM+xnMzdah3H+q8YLYxb6L34fhBub2E31DwIx/u4F+0J2bi7g0yWvy2pJgCqhNWzKVjxSTH9aMAmw+1NRySgeFKAQsRUcOtq/kYz0XJIu9e0s/8TcFQGPhjpW1tomLRuGr1/04iuXDS+93qB7fJh8uEHP6grhd665ly7s9OGNUregdxxFkZga1K0VWfD4xpY5hSwEJE1HDGSD7Gc1G+37sxifdvWtT/+cTx5lW0c1Mk6BUs6/1bb39HyYdron6QESmcqmuG3kq+nT51NenWgom6hhiu545zE82HPVvZKMDwpICFiKhh706p1pwnyMzDu96M7gz5hYBqIQ45E3IKH1jWAA+D3MmHywynvfnviO7cn51w9Xx0D+KIs4zB5gcHE2CYUsBCRNRUHtiQmaYmyyr4zL5uTl00rUb9n04kkgOmrk3UPH+CXW7By64gGdWF9nnywJsiOmZ25TyuPydsL6FTxURlrBPyY2jX6EYcYLSlgIWIqOnfZQQn50JOp1LXzallO1lnYcqQ/NcybLetITtO8PIj9sQhioKZkHB7db3QW48f5PpzwqzR3hWv0TtlrJPTpfNjbbF3uaeITqSAhYio6eoF7DznYuns/F9oHtwhoLr5nyXo3jH6o1Czx5AdJ1w87d0Y0cundIJmonhadE/tjIqSzQd6yEhrH0ZajfXUUYqx+XDlrHfPNUQnUsBCRNSUo5dzs+/P/DpNenyRslqoX7UW8dS1iaL9viPIXUi9S9vWxo2S70QWX2YG/8xIi5/K+oI+zx6RE2Syq+azKZkPcphIzy8p0GLwUsBCRNS0a4cKq76Or8ds3LiU346cHM0MlnVgV3xGod7SsdHKwB/zL67IOBK0z+sXFAv8dslM8gmdcHRffO7jcXR4AQXZfCkaT9crBi8FLEREB96+1qQ+v+EjaqrzOzJ86yoykwT5UFTXJqqePcaYhjB3Qv6/KZlimTl2gGKB3x7ZQz6hE1YU5T9Sj/7KSbn5cXg3910MXgpYiIgO3LutXn1+g8KQX9x3mkhWEFitO8Pq2kRVipJt7FiX33iteOEUxcBMrJhLscBvnz/hY98JctKduoZolhxKkB9SAMxn0xLRjRSwEBEduHAqIxS5mDfRXaeJvARVpRjRrK7Kr4vNNGeOYuxNuORBkDunZmVmRPf4FH1NtPB78tecUFsTr/t4XF1eRA5Wvnhx+jSiEylgISI6cPAvZCbkYntJnW3ddJQPUIjfyT4Ej7chxSd1bZwonY3QPpUpigV+y+aNM66ej9d9PK7yTpc/W1a5e+dDdCsFLEREh75/yxhFNs4db7StmY7L57ATKmwvyX/UzDQlYBssa9BP7ruE/qCAkBHJWVPXC721bCf5V06I4308rvJ8yo/b1+JxajJGRwpYiIgOPX+CzIRsuD0NjIDgNmaNqbatTdQ9U87fjOB2vFbcs5X8vUysW0wHgN8+vt+sLjtkQU4MVdcQzbR8H+8e+dDSYll9v03Z1hXRLylgISI6lFDq7Mi4WJ9vnL/MPH3IB5KsXRxfBDev4G9G2LnefVfGrSsccJCJcYVksPhp706p1o9U0MPtMxDDcckMulvzZdF095sziE6lgIWI6NDpIwilzsXvQ53tPvf5mpwk4eVTd91rpsvfTBuXXeabdf20wqqv4w+kPepq01bXDvY1Q+8sGsffrxOamizr2oUmjIj3brJ5li8nDjHGjcFJAQsR0aG9vqLYkov1Dkd6ZGwOrNYjvdW1iYPSwcHfjNV6yqa6NjrKKU/QPlfOuSsKor67tzC+CgCZkdOT2UjAoKSAhYjowmePmKfIxt9lDbY1y+aOdXwgCWv/qLWtTVx8+Yy/GUFOvVLXJpcr5nLAQSa2rnZWLEfn0qECALmYMoRRbgxGCliIiC4s30/oZzYe3XN2Ko208YNljY9xls+pIwS5C/MnOc8KOcwBBxmZ6nBcGZ3Z88uU1Uz9CgBy8NdG9xmPiE6kgIWI6MJV8+mIyIZkgBR8Zl+39pR8n7oa5ssaG/TXLIpuXEaQu7Brg/OXfE6Aa5+mRsvq3pGwbD+dOYrxbgDIjTyn1PsHoh9SwEJEdOHYvmTS5ELWSF239iTfp43b1+L98jdtOB/CgtPMph5fpKwW6lftEve/GROUkzMBAHQY4mJEHtGpFLAQEV3IqWC5WTZbL89p9QK62YS925x35kTJXgS5t1Jd6SzIfepvFP4yUbop3n8zJnjzCuPdAKCHTCeo9xBEr6WAhYjo0ltXebHPxr7teh+XcvIeWNYfU51nI0XN508IcheG/Kq/S71hKaOXmZgzlvwrPy34vKJ1tBkAQIcLp+J5kjKaJQUsRESX7tnKaEU2blzWG5V69ZyihuDmdLqoefIwxUphwWT9YuWpo6xZe0g3X5+vyb/yU7r/AMAJjQ1pcgnRdylgISK6dOGUGvXZDR9RU522unxiX7ePLfw+pf7XEknFO2djZVGVbqI2nJzW9PoFBd72IDDYf7eu5u8VAJwxawydseivFLAQEV06+OdK9bkNCrlGpeZNpAgonD+RjLb7qUPp6BCuntfrTiz8jgJvJsp2NtjWC71VDhwAAHDCAe7N6LMUsBAR8/D9W7ojsiEFKnXNPnb3FsYwhc0r62xrE0d7fpmyWviTsaqrcncninPGUfDLxMIEZMaFadcOFVZdLacuAIAzpGtYvZ8geikFLETEPJTOGcjM9pLso1K3r7HDL0wbnpyW+2ePqWAJv3XJ3p0o7lhHgTcTA3/MvX7o3gkDqtQlBwDQYmQP7s/onxSwEBHzUDpnIDPZRuO6dZATrtjhlzDqXp2SE3rKqZNt6HQQXTlLgbc9Xj5jh99vyasDALdsXJaMrnIMRwpYiIh5KJ0zkJk3rzJ/aE4cyA6/kLQw6nWL+TAWSjdn706UEcPqSgq87VG+n4wVv6W7GADconsKNaIbKWAhIuZhr6/I9MlF32/a7y5av4RChnBkT7I+xqcMoXApXL+Y/QV/WDcOicjE8jm1tvVC76R4CgD50NJsWX2+bv/dDzFfKWAhIubpk4fN6rMbPiJTvtOZcnb4hRVFyfoY7/FFqvXlNunU5AhyXzSdEzozIcU9db3QO0f3psgMAPmhMyaP6EYKWIiIeXp0X4P63IaPkE4rdc3Ed29oXRNG96qyrU3cpejbxtCumQsx+7YT4N4eqXdp21qht65ZWKsuOwCAI46VJau7HIOTAhYiYp6unMfLfjbae4kZ/AvjUYIcU9/1U/s1FXf/LqPoKxT/nnmH+s51inztIZ2b6lqht546QncsAORHZSp7lzGiWylgISLm6Zg+jFtko72Q8uJpjEcJuXKQ4uraYoq+wu4t7Qe5c0JnZkqKkzVyG4bv39IdCwD5M3FA8jrM0X8pYCEi5ql00NTX8bGZieZmyyr4/L9rVraDDhxh18b2Cxhxd9Igir5CpgLmuELWJxNj+/JB5KccHgAAXrFjXTLfcdBfKWAhInrgzStN6nMbPmJcv/9+dD64zXiUMHdC5hGyONu9Y0VrYTPp1Na0P2KxegEdau1RV5PMkdsgXV7EtQcA3vDgjr0DHzFfKWAhInqgjAJBZj4+9r57xxTFi//Rv3Nyj5mW0VKwrGEF9iD38v10KLbH5bPtd6yhd5JPBwBekU5b1sAf7c84xHykgIWI6IELJpPplI392z+0kf8+tFr9jxPJm5cttusoSXJ6ZxuSB6euzVNOaWyXLavaP9EUvfPVC/KvAMA7pKtTvc8g5iMFLEREDxz0E7kh2ZARy3/XSj5CwWo96Uu9jpIkY3Jt7Nn634yQXl+lrBZqCO0yZUi17TpC7xzIcwwAPObssWS/66D3UsBCRPTI92/46syEZNf8m/Vz4RRHtAvrFye7m0ROJwLLunH5v2Nx04bTodgeTf/cNiQ7Tb2O0DsXTaeTGAC8RQ45Ug/yQcxHCliIiB557jiFmWz81qWytYhVmeLERkFO4lOvoSQpL7RNnH3wn+KuuHkFHYrtceujLk70x0OljPUCgPdMH0H3LHonBSxERI/kwzM78yfVWMMLGFERJMRewuzVayhpPrxD1pMwovuHkFsZtwA7uzZwHLvfPntEFzEAeM++P7l/o3dSwEJE9Mhpwxj9yca+7fXW+iUU+YQHtzlaWjyyh44PQUa3/l2Tt68pIrTHrDHs4Ptp4Xep1hPDAAC85sXTZB9ag95KAQsR0SN7fpmyWmgoAQ0O7GywXT9JdNV8gtyFvdvadqcHdE6p/xH8g4Ta9+5Ex6KfcpIuAPjJsIIPncaI+UgBCxHRQ588oIIFuVky40PHTZIdX0iQu/BvvtO8iRQR2kNGTdVrB71VOmQBAPxiXcIPrkHvpICFiOihR/cyEgW5GdaNnUix4LOK1tPlko6c0iRB7rs2UkRoj/3byU/xW/LoAMBPrp7nIA70RgpYiIgeumIuI1GQnerK/546l3QlDwws6/jBRuvVC/Kv2mPhFDoW/VTGM2VMEwDAL2SzqtdXjIJj/lLAQkT00NG9GYmC7Fw6wy7kxx4qpWsRsiPZYOp1g945ZywHkACA/8hp1Or9B9GpFLAQET1UOmvqajjKCTLz51pyID6WrkXIBqdX+W/pJkZXAcB/ju7jABvMXwpYiIgee+Nyk/rMBvh/Zo2utl0zSXZsX7oWITN88PjvneuM8QKA/1S8I0IB85cCFiKix5ZuZjcb2iedtqw+3zAO9bFdO1RYjQ10LUL7LJ1da7tm0Du7d0xZTey5AEBAjCusst2HEJ1IAQsR0WNlxh+gPZ4/ZhyqPe/dpAME2mdoF07s9NPpI8i/AoDg2LaGGAXMTwpYiIgeK4HDAO1xrIxxqPY8sIsgd7Aj4ybqtYLeur2EjmEACA7ZsFLvQ4hOpICFiOiD795wJjnYWb2Acaj2XD6HIHewc+poo+1aQW+9fpH5QQAIDolS6P8DUQroXgpYiIg+ePZYo/rMBiD7IYOjexPkDnbW/kHB10+7daiwGurJnwOAYFk6i3s7upcCFiKiD25aXqc+ryHhSFC5fDCq1wpWWF0/rbDq6/iQhv8ihU31WkHvnDyYwjEABM/pcrpr0b0UsBARfXDqUIJx4b/cutpku07wg3euE+QOH6ip4rh1v928ko0WAAie2ho29NC9FLAQEX2wxxcpq4XvcfiIPVvrbdcJfrBsB0Hu8IGLpyn4+u2lM+RfAUA4/D602nZPQtSRAhYiok8+vk8FCz6wcEqN7RrBD0omBsC/yBi2eo2gd8rYbk01Y7sAEA67t7Cph+6kgIWI6JOH99BRAh8Y/HOl7RrBD47qRR4PfGDSIPKv/FQOlAAACItnj1ps9yVEHSlgISL65IoiOkqgjYp3adv1gf9V8o7qaukIgbYDDwo+s18j6J3rF5N/BQDhMrQrG3voXApYiIg+OZqOEvgfZ49x4o6OEnQPcOMy+Vd+K/ckAIAwWftHre3ehJhLCliIiD7Z2lFSQ0cJkOej677t9erSQQLZuZ5sFD+VZ1NlBc8mAAiXy2fZrEDnUsBCRPTRG5foKAFO29F1yYwadekggcwcxd+Ln47sWakuOQBA4DQ2WK2ndqv3KMRsUsBCRPTR0k10lCSdlhbL6vklL2g6jujBh3XSaWm2rF5f8ffip6sXkM8IAGZQNI4NC3QmBSxERB+dN5GOkqTz+H6z7brA9pXRplrGbhPNg9v8vfjtycPkXwGAGRwqbbDdoxCzSQELEdFHB3ROqc9qSBiHd/Ny5sSbVxi7TTL7/iT/ym/fvm5Rlx0AIBTkfiSbV+p9CjGTFLAQEX2Wj4Vks3wOp+w4ce82xm6TzPxJNbZrAr1zaBfGdAHALEb3rrLdqxAzSQELEdFnz/zNuEaSkcBk9ZrAzC6axthtUkmnLavwe/Kv/HTZbPKvAMAsNq/kpGbUlwIWIqLPblxWpz6rISHU1aRpjXfosAI6RJLKs8cttusBvbV8X4O67AAAoXL7WpPtXoWYSQpYiIg+O/W3avVZDQnh2gVeypwqBb+aaoLck8jhPeTF+e3LZ4y0A4BZyGnNfb+l+xb1pICFiOizPb5ItR4ND8lj53oCqd14/SJB7klkyQzyr/yUQ0UAwFQkPkC9ZyG2JwUsRMQAfHSPClYSKRpXbbsWMLe7txDknkSG/EJenJ8Wky8HAIZy4lCj7Z6F2J4UsBARA/DwbnJHkkj/H2iJd+MfU/nQThrv3pB/5bcH/+I5BABmUl2Vtrp+ar9vIapSwEJEDMDlczj5KWm8esEHuVuHdiHIPWmcPMzuu98+eUgnMACYy+TBVbb7FqIqBSxExAAc2ZMP8qRx8ggf5G6VIPfqSoLck8TqBbW26wC9s+83KSvNnxQAGMyujeSGYm4pYCEiBiAnqyWPdYvrbNcB6nv1PEHuSWJUL3be/XTeRMZyAcBsHt9vtt27EFUpYCEiBiQnqyWLiQP5IM/H0k0EuScFyT6RIr96DaB37t3G3xMAmM9gDvPAHFLAQkQMSGmNhmTQ1GRZBZ/brwHUd+EUOkaSwoWTjNv67f1b5F8BgPmsmsc4OWaXAhYiYkDOncAHeVK4d5M2+Hwd8iu5cUlh4zLGbf2055cpq4X6FQBEADY0MJcUsBARA7Lw+5T6nIaYUrajwfb7o3MrU+TGJQHGbf111uhqdckBAIykvi5tde9ov48h/isFLETEAH3zqkV9VkMMWTS9xvbbo3OvnCM3Lu401Ketgs/svz16564NjK8DQHSQort6H0P8VwpYiIgBerq8UX1OQwwZ2pUQUi/kwzv+yOEW6u+O3nrrKoVgAIgOZTvpYsfMUsBCRAzQDUvr1Oc0xIzqSk5U88r5k8iNizvbS+ptvzt6pxwm0digrjoAgLm8ftFiu5ch/isFLETEAJ0yhCySuHPxNB0lXjn4Z4Lc4870EYyK+OnvQ3nmuOHsMYKk0Z3ThvM35wUjetDJju1LAQsRMUC7d0xZzZwGFWu2reFENS9NvSPIPa7IyXhyQp76m6N3yv0InMPJmOjWbh0qrNoanlv5IhML6toiihSwEBED9uFdKlhxZuYoOkq89NIZ8nviyr2bzbbfG7316nn+ftwwZQgnY6J7zx0n7zRfblyimx3blwIWImLAHiolkCSupNOW1ecbOkq8dMc6gtzjyp6t5F/5adcOFVZdLZ0gTpEuaemWVtcTUdeV82rVywocIn+Hfb7m7xDtUsBCRAzYZbN5sYkrzx4TPOq1cycQ5B5X5LdVf2/0zokDq9QlBw3u36IzEPNz0E+VrRtakB8Lp/CMQLsUsBARA3ZkD4Kp40r5fo5+9tqBP/L3Ekfk467vt+yu++mm5eRfuaFsB/dxzN8nD4iLyJe/y/hbRLsUsBARA7bLJxVWTTVbc3Fk1fxa2++N+VtBkHvseP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/RHoQAAABNVrSNX8o5hYgyLnmgyQcfAABAi0SeY/5AzitElFGeZfw4eaClPPgAAABaJXKtwnfl3EJEdebahaPiB1iY8qADAABotaDoFD4n5xciqrGiY3zZZfgHAAD5Vi465pfkHENEI8yzjEPiB5SX8iADAADIG9e1Rn9EzjNEVGWu3fvR+IFUTHlwAQAA5NVQ0TY+IOcaIhqmob7R74kfQOtSHlQAAAB595Jvjd5HzjdEtJV8Z/S+yQMn5cEEAADQLp5zJ44eL+ccIhK5k4yx8QPm2ZQHEQAAQLt5aL1jvkXOO0S0uY1nvHWUa5uLUx48AAAAbaloGfevmTj+n+XcQ9T1qb6d/yF+kNwjHzQAAADtr3CLOmv838n5h6hrUzN7dvBs4zL9wQIAANAhHON8pXq2k3MQUdeVPBCSB4T2IAEAAOgwnl04Xc5CRF2XaxdOlA8OAACATlV0Cj+T8xBR1+RZxrHyQQEAANDhwqJd+IKci4g6Ps/pPTx+AAQpDwoAAIBOt3HILrxbzkdEHVvRMt8X3/GLKQ8GAACAbvGSd4axl5yTiDquIXuMEd/hl6Y8CABgZAb30v83AGgnjvFXPiiMOjo1uOs/xXf2h7U7PwCMlNOrIm+tijauUOUnrlSlm3+pvAsO1i8HAHnnGPOUtfvr5NxE1PapCT07xnfya7U7PQDUwL/4UJVWNLT5BcHc45U/47D4sqb2vQCQO5Yxg88IoI4rvnNP0e7sAFCj4PYT5OyfWjS0khcEANqDVThOzk9EbZtnF36q3ckBoA7hU9fKWb+qeEEAIMeiom0cKecoorbLs4xDXU73CSBLm4//z6Ko+KIKn75BBfNO4gUBgNZzjPW+3bu/nKeI2ibfGb1vckfW7twAUIetHf+fRbwgAJADy4qW2SvnKqLct2bi+H+O78CPpdypAaAu1R7/n0VR8aVXvyBwerXrAwBZ82xjgfrTqL+X8xVRblMTerYvWsZseWcGgCzUevx/JvnrVfjsXF4QAGiG6XLGIspt8R325JQ7MQDUL8Pj/zPJ38ALAgANU3QKP5NzFlHuKjrGl+M7bCTvwACQhUYe/59Jr3xBMOsI5faN1W4DAIxA4Nq9H5XzFlFuGppUODC+oxZT7rwAkInS3N/KkTvXJR9M5l/8Ce12AMAIrOBNwZTLNlijd47voM+k3GkBIDMtPf6/lsJAuZP30G4HAIzQXcra/XVy/iJqWcmbfl27cHXKnRUAspMc/++ukSN2rguX36ffDgCoQdE2bDmDEbUs1yn8Qd5JASBr/kUfl/N17gsWONrtAICaWYXvyjmMqOl5lnFIfIcsa3dQAMhYMPcEOV/nPv+Ko7TbAQB1KJYs8wA5jxE1LdcetYtnG6tT7pwAkLny4jlyvs53HP8PoDGWrHfMt8i5jKjhqdN7Xx8P/wtT7pQAkL22PP5/oX47ACADRdu4Uqme7eR8RtTQXLswIO+MANAo7Xn8f592OwAgK/GLgP+S8xlRw3Id8xvyTggAjdRu5/9P8q88WrsdLdM3VnkXHBz/d1P/GoB2FbhW4UNyTiPKPM8x93QdY33KnRAAGqYtj/8f3FO7Ha3iz/q3TdertHHTJxXffZryZx+p3P5x2mUBtJVn1p3e+2Y5rxFllho03hDf0R5KufMBQONw/H/dgr+cIq/ipkpDvCAA2t9NambPDnJuI8qkom1YKXc6AGio9jz+v1+7Ha0ULrlVXsX0tBcE47WfBSB/io7xKzm3EdVd0TK+Iu9sANAMbXn+/yu/rt2OlukfF78iKcqrWF3x94XL5lc+0IwXBECuBUXb+ICc34hqLjnff3zHWptyZwOAhmu74/+jsnIH99JuR6v4sz4rr2HtaS8IdtF+H4CWeZb3A1AmqQn7vta1zPkpdzIAaLx2PP5/RZsc/59FgcsLAiBHPNucJWc5ohHnWcYp8s4FAM3C8f/1q/r4/ywKg/gF0P0vvyAY2FW7PgAa7ptyniOqOneSeXB8Jyqn3LEAoCk4/r9OfWMrp/5sWbwgAFphndc/alc51xEN24aBUW+N70ArUu5UANA0HP9fH/+Sz8hr2Npe+YLgqm/kaq2ATuLZxoLkMG453xFts/iOc5m8MwFAc5kqclfJETLXhSsfSLkdrRPMO1FexXxVOe3obZX3KfizjuBzCIAMxbPcn+R8R7TVirZxpLwTAUCzeRd+TI6LuS9YOKjdjlYKn7lJXsV856/nVKNAdkLXKnxIznlEWq5TGOdyyk8AOVCae7wcD3Off+XR2u1omVYf/19DyRmFtNsBoB5L1/aPfZOc94i2pCb0bB/fUeam3HkAoOnKi6+R82G+y93x/5+W1zD3BfdM0m4HgDo5xlly5iPaUtEp/Ey70wBAK7Tl+f8X6bejhYI7/yivYu7zL/+KdjsA1K9oF74g5z6iHt/u3T++g3jyDgMAreBddIicDXNfcN9k7Xa0UrjkZnkV8125pNyB3bTbASATKzee8dZRcv6jLk5N6NkxvmPclXJnAYCWaMvj/5PTWqbclpZoy+P/79FvB4AsXSxnQOriXMc4PuVOAgAtw/H/9WnL4//vtbTbASBjTuHrcg6kLsy3Ru/jcugPgDxpy+P/79dvRwsF806SVzH3+Zd/VbsdADK3amjiuIKcB6mLUoMHvsazjYUpdw4AaBmO/69f253/PwyUO3kP7XYAaATzGjkTUhflWuZv9DsFALQWx//XqR2P/3/hXv12AGgcq/A1ORdSF7T5rD++docAgBbj+P/6+DM/Ja9h7uP4f6DpXuKsQF3W5kN/7ku5MwBAa7Xj8f8rH9BvRwtx/D+AKnFWoG7KtQrHpdwJAKDl2vL4/4WD2u1oJY7/B1CtolP4nJwTqQPzHHPPeIMX5R0AAPKgNPe3cjzMff5V/6HdjpZJjv/3N8irmOvCFxbotwNAsyxRp+70RjkvUgelVM92rmXcnrLxASAXyk9eLefDfJe74/8Pl9cw9wX32trtANBEljFVzozUQSUf/qBtdADIC47/r1sw70R5FXOff/nXtNsBoKlC1yp8SM6N1AFtGBj11ngDr0rZ6ACQC96F/ypnw9wXLJyi3Y5W4vh/ADV6XJ01/u/k/EhtnmuZ56ZsbADIjfY8/v+b2u1omXY8/n/5ffrtANAalvkbOT9SG+dZxiHaRgaAnCk/cZWcD/NdFCpv6r7a7WgVf8Zh8hrmvuC+Ae12AGiZomeN2U3OkdSGJX/OiTfo4ykbGUAVvHMPqnyqavjs3Mr51f1ZR1T+pVVeDnVqy+P/H9RvRwsF8/4gr2Lu8684SrsdAFrqOjlLUhsWb8gJKRsXQJVKN/1cziy8IGgAjv+vX/j0jfIq5juO/wdyqWibX5TzJLVRyZ9x4g3pyg0LoHrlRy+RY4uefEHQP077Odg2jv+vkzMmvkLr5VXMdeHyhfrtAJAHS9SfRv29nCupTYo34PUpGxXACEQbnpdzy/CVhja9ILj7NOXPPpIXBFVov/P/h8qb8jbtdrSKP6MNz/+/oE+7HQDywbPMiXKupDbI6yscJjcmgJHxzjlIziy1xQuCbWvH4/9ffEi/HS0U3PF7eRVzH8f/A7lW8q3R+8j5knLc5jf+PpmyMQGMQOnG/5QzSzbxguBV2vL4/0VTtNvRSuHTN8irmO+S4/8H99RuB4AcsYzblerZTs6ZlNNcp/C/2kYEMGLlR2fKsaUxaS8IxmvXpZO14/H/pau/pd2OlmnH4/9XcPw/0A6KtnGknDMph7mTjLHxBhuSGxDAyNV0/H8WBcWuekHQlsf/T91Hux2t4s/4pLyGuS9Y0K/dDgC5tJQ3BLdB8Ya6IGXjARgh75z3yZmldSUvCJbNj4cmp/NeEHD8f93a8vj/K7+u3Q4AufV7OW9SjnKt0R9J2WgAalC68WdyZslPHfSCwLvwY/LW5b7yoqna7Wiltjv+Pyord3Av7XYAyC3XtUftIudOykFqQs/2rmXOT9loAGpQfmSGHFvym/aCYBft9uRV6bbfyFuT+0pXf1u7HS3Tlsf/L9JvB4C8u1jOnpSDXMv4VsrGAlCjaN2zcm5pnwK3bV4QlJ+8Sl77fJe74/8Pk9cw9wX3DWi3A0D+eXbhE3L+pBamTu99fbxhnpUbCkBtvHP+Rc4s7V0YqHDF/fl7QVA5/n+1vLa5LnrxYf12tFBwx+/kVcx9/pVHa7cDQP55trEwOeJEzqHUouKNMkFuJAC1K11/rJxZOit/gwqfuUkF805S/iWfVm7fWG0NmsG74GB5zXJf+f7p2u1opfCpa+VVzHc5+wRlACPkGN+Rcyi1oGKfMSbeIEVtAwGoWfnhi+TY0tmVNqpwyc2bXgw4Y7T1aJTSrcfJa5L7Std8V7sdLdOOZ1Ba+aB+OwC0k+Xq1J3eKOdRanLxhpiesnEA1CFat0TOLd3T5sOFyoumqdKcYxp6vDvH/9fHv/gT8hrmvuC+ydrtANB2TpDzKDWxoUmFA+ONEKZsGAA18s5+r5xZurt46I1WPabKD52nSjccW/l8BLlmNWnH4/9fekS/HS0U3D5BXsXc51/1De12AGg7G4YmjivIuZSalOsYN6dsFAB1KF3/Ezmz0KuKVLT68fgFwfmbXxAcpK1hNTj+v37lxXPkVcx3HP8PdJIpci6lJuRZxqEpGwNAnbru+P8sSt5U/OxcFdx92qazDA3spq2r1Jbn/7/mO9rtaJm2PP///frtANCuAt829pbzKTWwyod+2eaDKRsDQJ2idc/IuYVGWhi8+rChs9+rrTPH/9eH4/8BtF7hajmjUgMrOsaX9Y0AoF7eWQfKmYWyqPI+gr++/ILgvA+oqPiivFSuS66/vL+0Umnu8fIq5j7/qm9qtwNAm7MKH5JzKjUgNWHf17qO8bS2AQDUrePP/081V77/TO3+0krtd/7/snIH99JuB4A2Z5nzlerZTs6rlHGebfxQW3wAmSg/fKEcW4gq5e78/95aeRVzXbjyAf12AOgI8Wz6WTmvUoapQeMN8UIvkwsPIBvRWo7/p5Qqx//vq91fWsW/+FB5DXNfsHBQux0AOoX5YPL+VDm3UkYVHeNX+qIDyIJ39nvkzEJUKXrpUe3+0krB7SfIq5j7/Kv+Q7sdADqIVfianFspg9ad3vtmzzbWaAsOIBOc/5+2Fsf/1xnn/we6wVPJ+1Tl/Ep15jrmSSmLDSAj5YcvkGMLUaXcHf/vrpFXMdeFKx/UbweAjuNZ5vfk/Ep1tN4x3+I6xnq50ACyE619Ws4tRCr55GNv2v7a/aVV/Is+Lq9g7gsWTtFuB4COtERZu79OzrFUY65T+EPKIgPICMf/09bK3fH/c0+QVzH3cf5/oHt4lnGsnGOphjZYo3eOF3SjXGAA2Sld/2M5sxBVKt8/Xbu/tFJ58Rx5FfMdx/8D3WZ5ctZKOc/SCONf/4HGSz6hliitaN0zqvzA2ZU3iXvnvE+77zSXqSJ3lbyKuS566ZGU2wGgk3l24adynqURtLZ/7JvihVwnFxZAtqI1T8m5hSg9f4MKn52rgrtPU/5V31DelL21+1OjeBcdIq9N7gsWTdFuB4CO94I6vff1cq6lKosX8ISURQWQIW/6u+TMQlR9UVlFqx6r/BWpdMOxyjvnIO0+lpXS3OPlb899pau/pd0OAJ3Ps4wfy7mWqmjNxPH/HC/gWrmgALJVuu5HcmYhqqto4woVPn2DCuadpPxZRyi3f7x2v6tFefE18lflu8onKO+j3Q4AXWEpZwSqIdcqHJeymAAyVn6Q4/+psSXn7Q+ful4Fd/xO+TMPV27fWO1+OLx2PP4/X2dQAtBcnm1+X863tI2Sd0/HC7dCLiSA7EVrFsu5haixhYEKV9yvggVO1e8jaMfj/8uLpmq3A0A3MRerCT07yjmXtlJyDlV9EQFkjeP/KRe98n0Ec45R3tT9tPtqae5v5XflvtLV39ZuB4Au45jfkHMupaQm7PvaeMGe0xYQQOZK1/1QzixEuahy+tG/vbH47Peq8pNXy4vkO47/B7DJY2pCz/Zy3iWRa5n/kbJ4ABqg/OC5cmwhyl/xMJ38laCd4vh/AH9TtAqfl/MuvaLkFVK8UI/KhQPQGNHqJ+XcQkQZVF40TXu8AehSljlfzrz0ijzb+Ky2aAAawpv+TjmzEFFGla75jvaYA9DFnMKH5dxLm4sX6C5twQA0ROnaH8iZhYiyiOP/AQhF27hSzr0U5/YZH5SLBaBxOP6fqDFFLz2iPd4AdL3InzRqPzn/dn3JK6OUxQLQINHqJ+TcQkQZVL7/TO3xBgCuY5wl59+uzreNveOFCbWFAtAQ3rS3x2NKJOcWIsqg5LMM5GMOAGLe0MRxBTkHd22uZfSnLBKABvLOPKDyKazJp7GGy+YrVfblHENEI61y/P++2uMNADYpnCjn4K5svWO+JV6Qor5AAJpqYDflzzpCBfNOUuHTN6jIXSNHGyIaJs7/D2BbPNtYrf406u/lPNx1FW3jl3JxAOSDd85BlU9iTT6RNVr1mJx1iEhUvn+69jgCgFfyLPN7ch7uqtSEnh3jhVgiFwZAPnnnvj9+QfBTVX74AhWtWSxnH6KurzTne9rjBgCEh5Xq2U7OxV1T0S58IWVRALSLwT2VP/vIl99HEAZyHiLqoiLlTdtff5wAgOA5xsflXNw1ubZ5q1wQAO0rObtQac53K4dBJMdCc6Yh6qpKQ5vOANS/i/bYAADhKjkXd0Ub+8x3pCwGgA6SnA0lOSSi/PCFKtrwvByXiDozf33lPu//+QvKdXq1xwUAxCLvDGMvOR93fK5jnJmyGAA6mHfhx1SwaIqK1j8nRyaijiy5rwf32sq74GDt8QCguxVtw5LzcUe3tn/sm+IbPiQXAkD3SAai5JSjmw4VIur8wpUPquD2Ccqb/g7t8QCgK61VfTv/g5yTO7aiZf4iZREAdCn/4kNV+aHzlSqX5MxE1HlFZRU+dZ3yrzxauc4Y7fEAoHt4tvFDOSd3ZMlpj+Ib/KRcAADwzn5P5TMHkgGJqBuKNixTwfzTK/d9+XgA0PmKlnG/nJU7Mtc2PyZvPAC8knfRISp8/i45KxF1blGowmduUqWrv63cvrHaYwJA5ypOMt4v5+WOy7WMGfKGA4DG6VXBnSfz2QLUdUUbV6jgnknKO/u9+uMCQOexzHPlvNxRDU0cV4hvaEm74QCwFcmpFJPTKhJ1XfGL3/Jjlyn/4k9ojwsAHcXbYI3eWc7NHZPrFP435UYDwDb5Mw5TkbtKjkdEXVO4dJ7yr/x6/HgwtccHgPaXnCBHzs0dkZrZs0N8A5fIGwwA1Ug+QyDy1sq5iKiritYtUaW5xyt38u7aYwRAW3syOVGOnJ/bPq+vcFjKjQWAqiX/AhqPQHImIuq6oqEVKvjLKcqb8jbtcQKgTTnmv8r5ue3znMIl2g0FgBEK7pssZyGi7q00pMqLpinvzAO0xwqAtnOBnJ/buuSNDS5v/gWQhcm7q2jjcjkGEXV1kbum8hcBd/Ie+mMGQLtw1/aPfZOco9s2zy78NOVGAkBNSjf9Qs4/RKSSFwKrVDDvD8od2E173ADIP88xfyDn6LbNs4375A0EgJr1jVXR+qVy9iGizVX+InD3acod3Et//ADIL8ucL+fotqxkmQdoNw4A6lT5kDAi2mbRxhdU6fqfKE4fCrQPv7/37XKebrs8u3C6vGEAUC/vrAPj6SaU8w4RpRSufFD5l35eexwByB/PNv4k5+m2Sg0e+Jr4hqyQNwwAshCufEDOOUS01SJVfvQS5U1/p/ZYApAry5MZWs7VbZPvGP+WcqMAIBPBfQNywiGi4QpcFSxwlDu4p/aYApAPnmV8Rs7VbRPn/gfQSKXrj5WjDRFVWeVTha/5jva4AtB6nm3MlHN1W5ScxzS+AZ68QQCQFX/WEXKmIaIRFj53p/LO+6D2+ALQUq4a3PWf5Hyd+zyncEzKjQGAzFTeCExE9ZccFpScNrR/nPY4A9AijvEdOV/nvvhK36zdEADIkjNGqTCQowwR1Vi4bL7yzjlIf6wBaL54lpbzda4rDvSa8RUPtRsCABlTZU/OMERUT/FjKph3Ujx89GqPNwBNFRYts1fO2bnNsws/TbkRAJA5XgAQNabwqWuVN3U/7TEHoHniFwC/kHN2bouv8J3yBgBAI/ACgKhxRcWXlH/5V7XHHYDm8GxjgZyzc5k7cfT4+ApH8gYAQNa8Mw9IRhQ5sxBRloWBCu78Y/yYM7XHIIDG863R+8h5O3cVHeNX8ooDQCOU5nxPjipE1KDCp29U3pS9tcchgAazjN/JeTt3xVf0Hu2KA0ADlB84W84oVE2cOYlqLFqzWHnnf0R7LAJoqEflvJ2rvL7e3VOuNAA0RLTqMTmf0DBFxReV27+L8md9VgV3/E6VF89R0dBKeTGiredvUP5V39QejwAax580aj85d+cm1yocJ68wADSCN/2dciyhKio/frm2lpvW8x3xUPcNFSxwKueCV2VffivRK4o2fXBYyn0JQENMkHN3bnI5/AdAk5TmHCMnEqqi0q3HaWuZanCvytlfkiEvXHKrUv56+aOIVLBwkM8LAJrCfFDO3bnInWSMdTn7D4Am4fj/2vIu/Ji2llWJh7zke0s3/ZcqP3KxilY/rjgDEyWVH5+t3P5x+n0GQKa8M4y95Pzd8jzb+Im8ogDQKJsGUBpJybH+mZ7KcfLuyp995Ka/Ejw7N54ES/JXUpcUPnencgf31O8jALL0P3L+bnmuY9ycckUBIHPetLcr/vV55JWfuEpbyyx5U/dVpau/pcqLpqrwxYcU26i7CpfeXnlRKO8XADJimfPl/N3SNlijd46vWFm7ogDQAKU535WzB1VR6bZfa2vZSMkLtdJ1P9x0yNCG5+XVoQ4sXHZ3/CJgD+2+ACATkesUxsk5vGXFV+ibKVcSABqi/MBZcu6gKqr5+P+MeOd/OH4R8hsVPnV95VSS1JlVDgca2FXb/gDqV3QKP5NzeMsqWsZseQUBoFE4///Iy/z4/3o5vcqfdUTltKPR6ifl1aU2L1x6R+XzJrTtDqA+jnGznMNbkjp1pzfGV8jTriAANIA3bX/FseUjr/xkY4//r4+p/JmHq+Beizd3d1CV95xwilAga+X1jvkWOY83vSHbOCLlygFAQ5Su4fj/WkoOvZFrmVfeeR9UwbyTVPTSI/JmUJsVLOjXti+A+hRt40g5jze9+IpMk1cMABqF8//XlnfBwdpatgPv7PduejGw5il5k6hNaqcXn0CbuFDO401NqZ7t4iuxLOWKAUBDRC89KucLGqbIXaVydfx/LZL3DMw+UpUfnckbiNutMFD+ZV/UtymAmni2sVpN6NlRzuVNa8gy3imvFAA0ijd1P8Xx/yOv/OTV2lq2tYHdVOm6H1VOOUntUVR8UXnT36lvSwC1sUZ/RM7lTcu1zN9oVwgAGqQ05xg5V1AVNfv8/83knfcBVV40Lb6RQ/JmU84Kly9Ubv84bRsCGDnPNv4k5/Km5TrGPHmFAKBRyvefKWcKqiLvwn/V1rLTJB86Ftx1qoo2Lpc3n3JUcK+tbTsANXlUzuVNKTkFkcun/wJoIo7/H3mRu7q7TsXYN7by6cPh8vvkUlAeikLlX/p5fbsBGDFvUu8ecj5veEXH+LK8IgDQKMm/8HL8/8irnIs9ZT27gX/JZ1T49A2K+02+ija+oLwpb9O2F4CR8RzjR3I+b3iuY5wvrwgANErpmu/IOYKqqDT3t9padpvkX5zDpfPk0lALKz90nradAIxM0TaulPN5Q1MTeraPf/EKeUUAoFEqb/SkEdcNx/9Xy7/iKA4jy02R8v/8BW0bARgBx1ivBg98jZzTG9aQY7xLuxIA0EB8KuzI67rj/6sRr0fpxp/xZuEcFK16rPKeDW0bARiB3o/KOb1hFS3jv/UrAACNwfH/tVV+snuP/x/WwG4quPu0eJFKctmoiSVnbtK2DYDqOeZJck5vWPEvvFa7AgDQIKWrvy3nBqqi0tzjtbXEq/kzP8Vfl1pZaUh509+hbRcAVbLM+XJOb0jK2v118S8c0q4AADQI5/+vLe/Cj2lriRTOGBXMO0mpsi+XkJpQ+cFz9W0CoFrhBmv0znJezzzXKXw45ZcDQMPwxs2RF7mr4rUztbXE1nkXHKzClQ/IpaRGFwbKO+cgbXsAqE7RNo6U83rmuZbxO/mLAaBRvKn7Vj48iEZWefEcbS1RhYFdVfnhi+RyUoMrP3yBvi0AVGuanNczL/4lt6X8YgBoiNI135WzAlUR5/+vT+n6HysVFOWyUqNK/gpw9nu17QCgGuZiOa9nmrLe/I/xLwr0XwwAjVFeNFWOClRF/kUf19YSI+PP+qyKhlbKpaUGFSzo17YBgCo5hXFybs8sz+k9XPuFANBAnKFl5HH8f3aSf5WO1iyWS0yNyN+gvCl7a9sAQBWcwtfl3J5ZnmWcov1CAGgQb+o+HP9fQ+FT12pridp509+lolV/lctMDSiYe4K2/gCqMkXO7ZkV//C/pPxCAGiI0tXfkvMBVRFDVPaSF6Phiw/JpaaMS/7iJ9ceQFWekHN7JqlB4w3xDy+l/EIAaIjyomlyPqAq8i46RFtL1C85PIXThDY+f8YntbUHMLziQK8p5/e6cyeZB8tfBACNxPH/I4/j/xvLm7a/ilY9JpedMqx8/3Rt3QEMr2gZX5Hze925jnG8/EUA0CjelLdx/H8NhU9dp60lsuWd9wGl/PVy6SmjoqEVynV6tXUHMAynMFnO73UX/+AbtF8EAA1Suvrbci6gKirNPV5bS2TPn/3leFIty+WnjPJn/Zu25gCG9aic3+tKTejZ0XWM9Sm/CAAagvP/1xbH/zdPcPdpcvkpo4IFfdp6AxhWtN4x3yLn+Job6hv9npRfAgANE658UM4ENEyRt5ZDJ5qpb6wKVyySm4EyKDntqrbeAIblOean5Rxfc0XH/Ln8BQDQKN7UfZMRQM4ENEzlxXO0tURjeed/KF54T24KyiDvrAO19QYwnMKJco6vOc82Z+m/AAAag/P/1xbn/2+N4M6T5aagDCpd+31trQEM63o5x9dc/MNeSPkFANAQwcIpchagKvIv/oS2lmiC/nEqWves3BxUZ8n7gLS1BrBtjrFezezZQc7yIy75UAHthwNAA/FhSyMv8tbFT/xjtLVEc5Ru+i+5SajOwhX3a+sMYHi+3bu/nOdHXNEpfE7+YABolMrx/5z/f8SFT12rrSWaKH7xFa1+Um4WqqcwqPx1RVtrANtmFb4r5/kR59rmH7UfDAAN4l/1DTkGUBUFt0/Q1hLNVbrlV3KzUJ15FxysrTOAYTjGmXKeH3EuHwAGoIk4/r+2/IsP1dYSTTZ5D6VKG+WmoToqXfsDfZ0BDOdhOc+PKKV6tvNsY3XKDwaAhuD8/yMvcldz/v+cKP91ltw8VEfB/DO0NQYwrFCdutMb5VxfdZ5j7pnyQwGgIbwpe8fTbFnOADRM4dM3aGuJ1vAv/5rcPFRH5ccu09YYQBWs0R+Rc33VuXbhKO0HAkCD+Fd9U+7/qYqC2zn/f270jVXKXy83EdVY+Pxd+hoDGFbRNv9TzvVVV3SMSfIHAkCjcPx/bXH+/3wJn7lJbiKqsWjdEm19AVTBMs+Vc33VuZZxu/YDAaBBOP//yIu8tRz/nzPBvD/IzUS1VvbjNTW1NQYwrAfkXF9VakLP9vE3b0z5gQCQvcG9OP6/hsKnb9TXEi3lX/IZuZmojpL3Bsk1BjCssvrTqL+X8/2weX29u6f8MABoCP+q/5D7faoizv+fP96Ut8nNRHXknfVubY0BDK/omAfJ+X7YinbhC/IHAUCjBAsH5X6fqojj//Mp8tbJTUU15p3/EW19AQzPc4wfyfl+2OJv/L38QQDQKBz/P/KSIdN1xmhridYLX3xIbi6qMX/G4dr6AqjKNDnfD1vRMman/CAAyB7H/9cUx//nV/LZDJRN/qWf19YXQFXukfP9sMXftCTlBwFA5vyrviH3+VRFwR2/09YS+VB+4kq5uajG/Es/p60vgKq4ambPDnLG32pr+8e+KeWHAEBDBPdNlvt8qiJ/xmHaWiIfyo/9WW4uqjF/1me19QVQHW9S7x5yzt9qyccHyx8AAI0Srrhf7vNpmDj+P9/Kj14iNxnVmD/zU9r6AqjOkG0cIef8reZZxrHyBwBAQyTH/4eB3OfTMCWfNqutJXKj/MgMucmoxngTMFAHy/yNnPO3musUJms/AAAawL/yaLm/pyoK7vi9tpbIj/Cp6+UmoxrjNKBAXS6Uc/5Wiy98W8oPAIDMBfcNyP09VZE/45PaWiI/whWL5CajGvPOfIe2vgCq9oCc87dafOEVKT8AADLHoDTyOP4//6INy+Rmoxpz+8dp6wugaiU1Yd/Xyllfa71jviXlmwEge4N7cvx/DXH8f96ZSpVLcrNRLZWGUtYXwEj41uh95LyvVXTMg+Q3AkAj+FccJXf3VEXBvBO1tUR+eOe8T24yqrFow/Pa+gIYmaJl/ruc97Vcy/iW/EYAaASO/68tzoqSb6U5x8hNRjUWLpuvrS+AkTJ/Led9Lc82TtW/EQCyF65YKPf3NEwc/59/wb2W3GxUY8kHqsn1BTBCjnGWnPe1irZxufaNAJAxb8re8TRblvt7Gqbw6Ru1tUS+hEtukZuNaix5MSXXF8CI3SHnfa34Qo+lfCMAZMq//GtyX09VFMw7SVtL5ImpouKLcrNRjZVu+VXKGgMYoRVy3n9VavDA18QXKqV8IwBkKljgyH09VZE/81PaWiI//JmHy01GdeTP/rK2xgBGTp260xvl3L8lb1LvHvIbAKAROP6/hvz1yu0bq60l8iO415ZbjerIO/MAbY0BjNzQpMKBcu7fkmcZh8pvAIDMDe7F+f9riPP/51+0+nG52ajGoqGV2voCqE3RNo6Uc/+WPNv8vvwGAMgax//XVnDnH7W1RH54575fbjKqo3Dp7doaA6iRZf5Gzv1b4hSgAJohWNAn9/VURcnx5XItkR/Bgn65yaiOgvsma2sMoGZny7l/S55TuCTlGwAgU+Fyjv8fcRz/n28Du6nIWyu3GtVR6Yaf6usMoFa3ybl/S55tLEj5BgDIDsf/1xTH/+db6aZfyE1GdeZffKi2zgBq9oyc+7cUf3FtyjcAQGb8y78q9/NURRz/n2emClfcLzcZ1VPgKrd/fMpaA6hRoGb27CBn/551p/e+OeXCAJCpYP5EuaunKvIv+Yy2lsiH0pzvyc1FdRY+d6e2zgDqU+wzxsj5vyc5P6i8IABkLVg0RYVLblbh8vtUNLRC7vcprdJGjv/Pq/5dVLRuidxiVGfB3afpaw2gPn3GB+X831O0Cp/XLggAWRrYTaly6eW9fNnfhLZZuORWfS2RC8G8E+XmogzyL/uittYA6lO0jK/I+T/5ELBj5QUBIEv+ZV+S+3mqouDOk7W1ROt5530gnlQ3yM1F9VYuKXdgV229AdTJKfyvnP/5DAAADRfcM0nu6qmK/Es+ra0lWiweUKOXHpWbijIofP4v+noDyEBhQM7/yRmALtAvCADZCZ+/S+7rabhKQxz/n0PJe1moMSUnCpDrDSALhavl/N/jOsbN+gUBICMDu3K8fw1x/H/+lK4/Nt4ykdxUlFH+xZ/Q1hxA/YqWcb+c/5O/ADwhLwgAWfFnf1nu56mKOP9/vlRO+RmV5WaijIrWPqOtOYDMrJTzf/ICoJhyQQDIBOf/ry1/1me1tURr+Jd+vvIBVdS4goVTtHUHkJlIDR74mi3D/9r+sW9KuRAAZIbj/2sr+RfR8kPnqdK131fetLdr64rmKF397Xg6LcrNQxnnX/o5be0BZKc40GtueQHgTxq1n7wAAGRm8u6vPv8/1Vy0bvMLghuOVd70d+lrjcwlH0rFMf+NL9q4QrlOr7b+ALIzZBfeveUFgGcZh8oLAEBWkg/1oQYUBip8YUHl9KqVD07q30Vbe9RhcE9VfuRiuerUoMoPnK1vAwCZ8izzU1teALiWebS8AABkJZh/htzXUyOKyipccb8KFjjKn31k/IJgvLYtUB3/qm+oaGiFXGFqYN75H9G2A4CMOcZ3trwAKFrmL7QLAEBGkg/2oeYXeetUefE1qnTrccq74OB4W5jatsGreVP3U+UHzooXL5TLSQ0sXH6fti0ANIL525f/AmAbJ+sXAIAMcPx/fioNqXDZ/Jf/QjCwq769utXgnpV14Y2+rSn5bAVtmwDIXNEynJdfAFjGVHkBAMiCf9m/y3095aXkBcHS21Vw9/9T/hVHKW/a/tr263Te1H1UMO9EFa1/Tq4ONankL1XuwG7atgGQPc8pXLLlBUD8amC2vAAAZCGYf7rc31OOi9Y9q8pPXKmCO36v/D9/ofIv43KbdgJ/5qdU+eELOK9/Dirff6a2fQA0iGPc/PJfABxjnnYBAMhA+Nydcn9P7VQUqmj14/GLgitU8JdTlH/VN5V3zkGqHd9PkLwPInlDevLZCpSTwiC+P71P21YAGqNoG4tefgFgG4/LCwBA3QZ2Varsy10+dUKljSpcvrDyr+ilucdvOoTo/A/l58xDzph44P+oKt3yS1V+7M8q2rhc3gLKQeWHL9S3HYBGWrLlBYBnG6tTLgAAdeH4/y4s+YvBhmWVMz+VH5mhgrv+T5Wu/4nyZ/1b5TSP3pkHKLdvrHZfqVVyDL930SGV03YmZzsqP3he5YwyvJm3Dar863/y1yR9uwJomA2V4V8NHvia+P+JUi4AAHXZ9AmqRCmVNlbeeBu++JAKl96hyk9epcoPnV/5lGPNX2dV3pcQPn2DCpfdraJVf1XRxhcY8tu88sMXac8ZABpPTdj3tT0bBka9VX4BALLA8f9ElFryr//n8q//QCtsPOOto3o8x9xTfgEA6jawG+f/J6LUggX9+nMGgKbw+wpv6xmyC++WXwCAevmXfVHu84mIKodvderpZYF2ULSND/S4k8yD5RcAoF6c/5+I0ipd/2Pt+QJA83iO+emeIds4Qn4BAOqVnAWGiOiVJe8LasfPkAA6ilX4Wo9rmUdrXwCAevTvolTZk/t+IurmwkD5Mw7Tny8ANJXnFI7p8Szjx/ILAFAPjv8nIlkw7w/acwWA5is65s97XKtwnPwCANSD4/+J6JWFz96mXKdXe64A0Armb3vi/3Ky/gUAqB3H/xPR34qGVihv2tu15wkAreFZxik9Rdvok18AgJpx/D8RbSlS/lXf1J8nALRM0TKc5C8AZ8svAECt/Mv+XU4ARNSlBXedqj1HAGgxxzgreQFwsfYFAKhRcPdpcgYgoi6s/NdZilN+AvnjOYVLeoqWMVt+AQBqlZznm4i6u/CFeyuHA8rnBwB5YF6T/AXgWv0LAFCD/vEc/0/U5UUblilv+jv15wcAOWHeGr8AKNyifwEARo7j/4m6u2jdM8o7+73acwOAXLkz+QvAX1K+AAAjxvH/RN1btPbpePh/j/a8ACB37unxbGNhyhcAYMQ4/p+oO4tW/VV5Z75De04AkD9F21iU/AXgUfkFABix5Pj/wJVzARF1eNFLjyrvrAP15wQAefVwj+sYT6d8AQBGxP/zF+RcQEQdXuVUn5ztB2g3TyR/AViW8gUAGBGO/yfqoqJQBfNOUpznH2hDjvF08gJghfYFABihcOkdckQgok6sNKRK1/9Yew4A0DaeT14ArEz5AgBUb2BXpcq+HBOIqMNK3ujPmX6Atreyx7WMF1O+AABV4/h/og4vfoFfmnu84pAfoP15trEm+QvAKvkFABiJ4K7/k+MCEXVI0UuPKH/m4drjHkDbWpt8DsDqlC8AQNXCpfPkzEBEbV40tFKVbjhW8a/+QGep/AUg+T/yCwBQtf5dlCp7cnYgonatXKqc1cudvIf+eAfQCVYlhwCtS/kCAFTFv/RzcnwgonYsClX58cuVd8FHtcc5gI7yUvJBYOtTvgAAVQnu/n9yjCCidioMVPmh85R3zr9oj28AHcgyXkz+ArBB+wIAVClcerscJ4ioHfLXq/IDZ/Mv/kD3WclfAADUjuP/idqsSIXPzlWlOcfEj99x+mMaQDdYzmlAAdTMn3WEnC6oipIPUwqX3KqUv0F+iaghRaufUMH805V3/ke0xzGArvNC8gJgecoXAGBYwV2nyjmDqsi/7Iub1tAZo7yLDlGlW49T5cf+rKL1S+VFiWouWrNYBfdMqtzH5GMXQFdblrwAWJryBQAYVrj0Djlz0HCVvcqhU3IttxjcS/mzj6ychjE5VEMFrvwJRKlF65ZU3sybHN7jTdtfv28BwCZLkxcAT6V8AQC2rX9cPJwW5QxCwxQ+f5e+ltsyeffKXwyST1sOn7lJRd46+SOJVLRxhfKvOEq//wCA7snkBcBjKV8AgG3yL/28nEGoiiofsJSyniPhTX9n5V95y4umqXDZ/MoHNxElhcvvq7w3R95nAOAVHkpeADyU8gUA2KbgL6fI2YOqyL/sS9pa1subuq/yrzxaBffa8QuCeyrndacuLvlAr0dmKO+sA7X7CgB4trGgJ/4/C+UXAGA4lePTaWSVS8od2E1by8zFvyN5oZGc9SU54xCnau3SgmLlTcDu4J76fQRA93KMeT2uZc7XvgAA28Lx/zUVLrtbX8tm6B+v/Es/VzlrU+WN22VfXjXq4KKNL6jS1d/W7xcAupNj3JwcAnSH9gUA2IZkmKSRl8Xx/5noG6v8GYepYN5Jm95DEIXyqlIHlryJ3DvnX/T7A4DuYhlzkhcA12lfAIBtSM5IQyPPv+zftbXMA2/qfpveVPzQeSpa/5y82tRJJYcFxS/8ks+gkPcDAN3Bs43LkvcA/Fl+AQC2JXz2NjlW0HA16/j/ejm9yp/xyU2fQ7DygfiKR/KWUAeU/OXHu+Cj+vYH0A0u6nFt87yULwBAuuT4/9KQnCdomFp2/H+dvOnvUqVbfqnCp2/kQ8k6rbKvSnOPj7ezqW13AB3t7PgFQGEg5QsAkIrj/2srOSOPXMu2k7x3YNYRKljgqGj1k/ImUpuWvDE8+WwJbXsD6EhFy3CSQ4D+JL8AAFvD+f9ry599pLaWbS05VOiSz6jy/dNVVHxR3lxqs5IzBfl//oK+nQF0Hsc8KXkT8ATtCwCwFeHS2+XsQMNV9pTbv4u2lh0jeTEw64jKJxNH7ip566ltiirbMDnMT9vGADrJ//QULeO/U74AALq+sRz/X0PJGy61texUk3dXpet/XDnlJJ9I3J4lHx6XfLq0tm0BdATPNn7Y4znmD+QXACCNP+uzclagKqp8GmvKenY6b9r+qnTbr1W4YpFcEsp50ZqnlHfu+7VtCqADWIWvJZ8EfLT2BQBIkXySLI08/7IvamvZbbzzP7TpzcPuark8lNMib11uP7sCQO08y/hMz5BtHCG/AABpwiW3yhmBhis5///k3bW17FqDe6nSLf+jopcelStFeazsqdK139e3I4D2ZY3+SI/rFD6sfQEApP7xlU8RpZEVPn+Xvpao8GccVvn04WTIpHxXeXMwnxcAdISNfeY7evxJo/aTXwAAKTnlI428bj3+fyS8s99TOTxI+evl8lGOChYOatsOQPvx+kft2lMc6DXlFwBA4vz/teVf9iVtLbEVyRmE5h5fOSc95bPyQ+dXTvuqbTsAbWP9oLFTjzq99/XyCwAghUtukbMADVcYcPx/LSbvoYI7fqeioRVyRSkHBQun6NsMQLsoqwk92/ckxf+Pm3IBANikfxzH/9cQx//XKb7flW7+JS8Eclhwr6VvLwDtYGVl+N/8AuD5lAsAQIU/69/k/p+qKJh/hraWqMHk3VUw76TKaSkpPwXzTtS3FYC8e+QVLwDMB1MuAAAVwZ1/lPt+qiJ/9pe1tUTtvOnvVOW/XhKvbCSXmlpRFKrSNd/VthOAXLvtlX8BmJtyAQCoCJ+9Te76abjKvnIHdtPWEvXzL/p45fAqykFlr/IJ4XIbAcgnzzYv3fICoGgZs+UFAKCib6xSpY1yt0/DFC67R19LZMfpVaUb/1NF7iq59NTkoo0rlHfWgfo2ApBD5uDLfwFwCpP1CwBAcvz/Z+X+nqqI4/+bw5uy96YPE+OwoJYWvfiwcgd21bYPgLwpnPjyCwDbmKBfAAA4/3+t+bOP1NYSjeNf+nkVrVksNwM1scpnBKRsGwD5UXQKP9vyAsCzze/LCwBAIlxys9zP03Bx/v/WGNxLlR+fLbcGNbHSHN4UDORb4agtLwCGbOMI/QIAuh7n/6+pcNnd+lqiaUrXH8v7VlqVv155Z71b2yYA8sFzjI9veQFQdHr/RV4AAPxLPi1371RFfEhS63kXfkxFqx+Xm4aaUPjU9dr2AJAPfl/hbVteALhOYZy8AAAkH75EI8+//CvaWqIFBvdU4TM3yc1DTah03Y/07QGg5ZT15n/c8gJAWbu/Lv4fI3khAN0tXHKr3K/TcJVLnP8/V0wV3H2a3ErU4CJ3tfKm7peyPQC0jGOs3zL8/634C6u0CwLoXsn5//0Ncr9OwxS+cK++lmi54PYT4qm0LDcXNbDyA2dr2wFACznGX+X8n7wAeES7IICu5V/yGbk/pyoK7pmkrSXyITlDTXKGJmpSUVj51Ga5HQC0zE1y/k9eAFybckEAXSq482S5O6cq8md/WVtL5Id/5deVKvtys1GDCp++UdsGAFrEMs+V83/yAmCKdkEAXYs3T9ZQ5fz/e2hriXwpzTmGvwQ0seSviXIbAGiJk+X83xO/KvhNygUBdCOO/6+p8IUF+loilyqfFaAiuQmpAYVLbtHWH0DzeZbxYzn/Jy8AjpYXBNCdOP6/tjj+v70EfzlFbkJqUMlnisj1B9BcRafwOTn/xy8ARn9EXhBAd+L4/9ri/P/tp/zgeXIzUgMqP3m1tvYAmmtjn/kOOf/3uBNHj5cXBNCdOP6/hjj+vz31j1fh8oVya1LWRWXlnfVuff0BNI0a3PWf5PzfowYPfE38xbK8MIAukxz/X9ood980TOGye/S1RFtIBtPIWys3KWUch8gBLfWSnP23FH9xaco3AOgiybG6NPIYbtpb5TMCqKFFQysq/8Ag1x5AU9wj5/4txV+8I+UbAHSRYN4f5H6bqsi//GvaWqK9lJ+4Qm5WyrjkcxjkugNoAsuYIef+LbmOcb72DQC6SrjkZrnPpuEql5Q7sJu2lmgv3tT94gl1vdy6lGHlxy7T1h1A43m2caqc+7cUvwA4Xn4DgC7C8f81xfH/nSOYd5LcvJRlQZE3ywMt4DmFY+Tcv6WiZXxFfgOA7uHPOFzurqmKggWOtpZoUwO7qWjDMrmJKcNKV39bX3cADeU5xsfl3L+lIbvwbvkNALoHx//Xln/FUdpaon2VbvyZ3MSUYeWHztPWHEBjedaY3eTcv6W1/WPfJL8BQPfg/P81xPn/O0/fWP4K0MCStdXWHEAjBcnp/uXc/6riC61M+UYAnc4Zwxsgayhcfp++lmh7wd2nyU1NGead9wFtzQE0zKNy3tdyHWNeyjcC6HD+zE/JfTRVUXCvpa0l2p83bX+lyp7c3JRRpZv/W1tzAI3h2cZlct7Xil8AnCW/EUDnC+74vdxHUxVx/H/nKj9xpdzclFHlhy/U1htAw5ws530t1yocl/KNADocx//XEMf/d7TSdT+SW5wyKlr9hLbeABrEMv9DzvtaRcf8kvaNADobx//XVLh8ob6W6BiVw4CiUG52yqSIF89Ak8Sz/UFy3tfyrdH7yG8E0Nn8mZz/v5aCe21tLdFZwhfulZudMir53BG53gCypwZ3/Sc572upCT07xhf25DcD6Fwc/19bHP/f+YL5p8vNThlVuv5Ybb0BZG6ZnPW3mmubD6b8AAAdKnz6BrlvpuFKjv8f3EtbS3SW0jXfkVueMoozaAFN4Bg3yzl/q7mWMUP7AQA6U99YpfwNct9MwxS+sEBfS3Qc7/wPy01PGVV+7DJtvQFkzClMlnP+VnMt8zfaDwDQkTj+v7aCBf3aWqID9Y+r/LWHsi98/i/6egPIlGcbP5Rz/lYrOoXPyR8AoDOVH71E7pepijj+v3tEq5+Um58yKFr3jLbWALJVtI0PyDl/q3mOuaf8AQA6j3fOv/Cvm7XE8f9dJXzuTnkPoCwqe9paA8hUpE7d6Y1yzt9qambPDvE3FVN+EIDNSjf8tHIe+OSNbP5lX1Ju/y7aZfKu/ORVcpdMVRSu4Pz/3YQPyWtc7fi8CbQPc7Gc8YetaBuL9B8E4G+iFx9+9Z4scFW49HYV3PnHynH1yYdrye/JE//yr776+lPVcfx/d+GFcuPypr1dW28A2Shaxmw53w+b6xhnyh8EYBN/9pFyP6YXFFX47FwVzDtJ+TMOi18Q9Go/p1W8cw5SkbtaXmOqMo7/7y7lv/I+mUblnfcBbb0BZOYEOd8Pm2cZP075QQBi5cVz5H5s2KKNL1TecFu64VjlTX+X9jObpn+XyqFLVGNRmeP/u0z54YvkvYAyyrvoEG29AWQjOamPnO+HrTjJeL/8QQCSfz1/X2UIrLdo9ROq/OC5qnTt95V35gHa72kEb+o+Knz+LnlVaARx/H/3KS++Rt4NKKP8iw/V1htANrz+UbvK+X7Y1KDxhviby/KHAd0uWDgo92GZFK16TJUfOEuV5nxXedP2135vvbzzP8TpDDMouG9AW1t0Nl40Ny5/xie19QaQiXVK9Wwn5/uqir/50ZQfCHSvyXvEe6z1ch/WgCIVvfSoKi+apkpXf7u+vxDE1zn4yymVNylT/flXfl1fY3S05K911JgqJ0xIWXMAdbtDzvVV59rmeSk/EOhapdt+LfdfTSta96wqP365Cub9ofImVG/6O7Xrt0XfWOXPOiJ+ATFVRe4q+aOo1jj+vyvxhvnG5V/8CW29AdTPswuny7m+6oqO+XP5A4Gu5fSqaM1iuf9qaclwH774UOVsQ3+T/OVAlYbkRSmDwhWL9PsFOtvAbvEDLZR3Bcqo5NBEbc3x/9u7EzA7yjLR4w0oOoCjLCF9vjoJuRhQiQoMOl5GHRVEAWWuI4PrCAqK2wzCxcHlzkg7rshISFV1J52wCGFN2An7JpAgIIGwBBIiYQtLICFbd9V31u9WnY4Kb1VCus9Wy///PL8H9cH0qXPqVL0n/Z0qoGmerb4o5/otzneKH5V/IJBXpXlHyXMX5azKwv7IfoFsK13yT3I3oBamz94v8pwDaJ7uL06Wc/0Wt3Zg4o7BH1KXfyiQR+FNvijfcf3//Onmsr88pGe+K/KcA2iOdtQrY/4C8J8L/qBH5R8M5I0+7yMm/GIu5TjW/+dSdfH5ck+gVlWvJf6O6UBK3SDn+VEX/CFnxfzBQK4wBFB48zS5XyD7ai89LHcFalF17+XI8w2gBdzCz+Q8P+q0Wzg28gcDORL+ipov1VLl/hmRfQMZF172t1qSuwK1qPrqJdHnHEDTtKP+Sc7zo640UHyv/IOBPKnc9St53qIcxvr//Clf9025G1ALqz07P/KcA2jeUP+4XjnPjzrT17N18Ietk384kAv9E019/bPyvEV5i/X/uVRdMlfuCdTCqksuiTznAJr2rJzlx5zvqltjfgCQeeXrvyXPWZTDaitZ/587A7t16K7f+a1yz2+jzzuApmjHulTO8WPOdwo/lz8AyIPac3fLcxblMNb/50/pssPlbkAtrnzz8ZHnHUBzPLdwvJzjx5x2rU/LHwBkXWnOofJ8RTmtdPVXIvsHsq269DK5G1CLK136z5HnHUBzhp3C++QcP+Y2TB+/q88NwZAz1cdY/0umsf5fz3xnZP9Adumz9jGmWpZ7ArU4fda+keceQFOGzOB+b5RzfFP53BAMORLent7UKvJ8RTmM9f/5U7nPkbsBtbi6vzryvANo2k1yfm863ylMj/lBQCZV7j1dnq8op1UWDkT2D2TYjMmmrtfK3YBaXG3FXdHnHkCzTpbze9N5tvpizA8CsmdgkqkPr5TnK8pppXlHRfcRZFblzj65C1Abqj54VuS5B9Ak1zpQzu9NNzx1t0LkBwEZVL7xOHmuorzG+v9c0Wfuw6U/O1T51pMizz+AppTNqeO3l/N7Swr+8GUxPxDIEMvUVz0mz1WU02orF8XsI8gqrvzTuUoXHhR5/gE0wbbulXN7ywp+wFmRHwhkSOmSz8jzFOW4ygODkX0E2VSae1jwitflLkDtqOI17rIuXwMAY+c51ulybm9ZwaeLI+UPBLKk+sS18lRFOa509ZGRfQTZo2e929TXPytffmpTfAEYaD1tq8Pk3N6yfLewm/yBQFboc/ZvrPkmahTsC/7gOyL7CTLGnWBqz9wuX31qY5WFbvR1ANCMsjlll7fIub2lBT/kmZgfDKReZWG/PE9Rjqu99FBkH0H2VO76lXzpqc2V5n0t8joAaMof5Lze8nxXnRnzg4F0m/52U/fXyPMU5bjKAzOj+wkypXzNMfzWr9M1rqz1rshrAaAJtvqpnNdbnueqL0R+MJBy5dtOkqcpynm1lx42lbt+aUpzDm0sE5H7DNItvL+DqZbly05trrbywchrAaBJbuEf5bze8ta71s7BD6tFfjiQVm7R1Ncsl+cpor9W8UztmTtMZcEvTOnigxv7TGQ/QmqUr/8Wf/PfpVj/D7TcBtM3ZVs5r7cl7ar7Yh4AkEqlK74gz1FEm60+tNJUl8w15ZuPN/rs90X2KSRX+fpvG1PV8iWlDlW66l8jrwmAZljXyjm9bQU/8FfRBwCkU+3Jm+U5imhU1dc8YaoPn2PK133D6DPeE9nHkAD9E03l/hnypaNOVvEb37eKvDYAxsyzrRPlnN62gk8bB8gHAKSRnv3BYHqrydMUURPVG3eTrj54pilf+3WjZ02J7HforPA6/7Vn75QvFHW42lO3RF4bAM0p29beck5vW+bsSW8OfqgnHwSQNuGQRtTWgg+Y9VWPmuqiWaZ8zdGNYVTuh2gXy5RvOs7UvVXyVaEuVP79j2JeIwBNeMn09Wwt5/S2Fq45inkgQGroWXs1vtxJ1Oka3yFYdrUp3/ETvlTcJqWLD2ncy4GSUt3os/eLvE4AmlE4R87nbS9ccxR9IEB6VO48WZ6hiLpSfegFU338ClP+/Y+NvuBALjvaBH3OB0z14dlc4jNhhcvi5GsFoGlfkvN529Onq3fEPBAgHYIBq77uKXmOIkpGpQ2m9uwCU7nPGVk2dNa+0X0Yr6HP/QdTffQiY2oV+WxSAqrcfWrkNQPQlMragYk7yvm8IwU/fGnMAwISL7wVPVGaqm94zlT/NM9U5v+3KV36WePPmBzZr3Onf6IpX/sNU3v6Vr7Mn/D0eR+Jvn4Axs5Wd8q5vGNpu/DbyAMCUiD821WiVFevjlx+dFnwoeDu34z8puCc/U34xVe5v2eKWzSlOZ8ylfunm/rwS/JZoQTG8h+gDezCj+Vc3rH8adbHIg8ISLhwjTVRZguXDz3/x8Y6+PJtP2z8tkCftU/kfZAm4aVUy9cda6qPzTF172W5xZTwwg+o8jUF0JxhW+0r5/KOZfp63qAdtUY+KCDJqosvkOcnouxX8Rp/E1tbfr2pPDDYuCRj6covNdbOh0tp5PukW8LLpJYuO9xU7uxrfDGa7+qkPz37Q5HXGUBTVhjTs5Wcyzta8CAuinlgQCKFw0V4N0oielW1SjBoP21qz91tqksvb3xACK+SVb7+26Z0+edM6aJPNpYX6ZnvirynRkuf8V6jLzig8eEjvEZ/5a5fBh/Kzze15+8xdf8V+cgo5YW/jZL7AICmnSHn8Y7n29aRMQ8MSKTKH34tz09ENMrqel1grakPr2z8Df1mrV/R+HdNtST/GMpB5VtPihyHATTHc63PyXm84607rbhT8GAq8sEBiTOwW+MGTERE1IHKQ8afsUf0WAygGb7pH7eDnMe7ku+qBTEPEEiU8o3/Lk9PRETUpqpL5kaOwwCaZV0r5/Cu5TnWCdEHCCRL7aWH5PmJiIjaVPj9EXkcBtAkWx0t5/Cu5buF3YIHVY88SCApwhsG3XyCqT42t7EmmYiI2ld93TONezZEjsUAmlFZ71o7yzm8qwUP6o8xDxRIJH3m3iPXFV90hqmtfDA8XcnzFxERjbHwKlLyuAugWYXb5Pzd9YIH9sPoAwXSIbw0IR8IiIhaUGm98Qf3jBxnATRH2+o4OX93PT2tuId8oEBahR8ISvOOMpWFLh8IiIhGUfWhsyPHVABNq3u2VZTzdyLybPVgzAMGUo8PBEREW1C9ZvTsD0aOoQCa9kc5dycm31U/iXnAQObo372/cRfT6qMXNW52RERExtSeuSNyvATQAnbhx3LuTkylgeJ7Iw8YyAF9xnte+xuCek2eF4mIMl/pkv8TOT4CaF6pv/AuOXcnquBBLpUPGsgbPhAQUd6qrbgrciwE0DzPUYvkvJ24WAYERPGBgIiyXumywyPHPgDN82z1H3LeTlzanvB2n5uCAZs3+A5TuuLzfCAgokzE3/4DbVP3+tUEOW8nMt8p3BOzAQA2ZXBPPhAQUWorXX5E9LgGoBXmyzk7sXlu4fiYDQCwhfRZ+5ryDd811Udmm/orf5LnWiKixMTf/gPto231b3LOTmxD/eN6gwddlRsBYIz4DQERJbF61egLDoweswC0QmWD3TtOztmJLnjQN8VsCIAW0GftY8rXf9tUHz7X1F9ZJk/JREQdqfrY3MjxCUDL3Cjn68Tn2+romA0B0A7yNwTcqZiI2l1pg9Fn7h09HgFojWCWlvN14ls7MHHH4MGXIhsDoO30ufub8q0nmerjV5q697I8bRMRNV3l3tMjxx4ALaPXnVbcSc7XqUg76vKYDQLQYfqcjR8Ilsw19aEX5HmciGhUhUsP/YFJkWMNgNbQjnWJnKtTk3atT8sNAtB9f/lAsOxqU9dr5bmdiGgz1bnpF9Bm2uk9RM7Vqcn09bwh2Ijn5UYBSBB3gildfLCpLPiFqT1zhzFVLc/2RER/qbr4guhxBEArPRPM0FvLuTpVaUedGrNhAJKqf6L4QFCW538iymn1oRcbdzKPHDcAtNKv5Dydukp2714xGwYgJfSsd5vydceOXHJ0zRNyHiCiHFW+4TuRYwSAlqpr19pTztOpzLete2M2EEAK6bP3M+WbjjO1J2+WswERZbjq0ssixwMALfcHOUenNu2o78RsIIAUq9x5spwPiCijhb/982dMjhwHALSWtq1vyjk6tW28J4AvNxJAetWWXy9nBCLKYtVy43tB8hgAoOWGzeDub5VzdKoLr2cas6EA0sgtmrr/ihwTiCiDVe75bfQYAKD1bHWxnJ9Tn7bVxyMbCiCVShceJGcEIspg1WVXBe95K3IMANAOxY/K+Tn1GdOzVbBxS6MbCyBtKnecLOcEIspYtZWLjD9998j7H0BbLJazc2byHPX9mA0GkDLVJ66TswIRZaj60AtGn7Vv5L0PoD082zpRzs2Zab1r7ezzZWAg5SxT91fLeYGIslL4pd9LPxvz3gfQJn44I8u5OVP5tnVuzIYDSAl94cfluEBEWalWMaV5R0Xe9wDa6nw5L2cuz1EfjNlwAClRvuMncmQgokxUN+Ubj4u85wG0md37ETkvZ7JgYx+KbDyAVKg+ca2cGogoA1UW/DzyfgfQdtn98q+MOwMDaWWZurdKzg3JrlaR/wsRiSoPzIx5vwNoN8+xTpBzcmZbM3XS24KNHpJPAoBk0xccKOeGxFf54zSjz3iPKV93rKk+MtvU1z0j/xWiHFdvLOuT73UAHaE32L3j5Jyc6TxH2TFPBIAEK9/xX3J6SHylK78Y2Q59zv6mfOtJprrsalPXa+X/hSgf1SqmfBNr/oGusdUsOR9nPt1fnBxsfC3yZABIrOqyeXKESHbBgOMP7hnZjtcYmGRKlx3e+E1B7cX7jalX5Z9ClL3C4f/Gf4u+HwB0Sr3k9k6R83EuCjZ+XswTAiCJ3KKp+2vkGJHoai/cF92O1zP97aZ0xedNZaFraisfDD4Q1OQfS5Tq6sMvmdLcw6L7PoBOukXOxblJu+qgmCcEQALp8z8m54jEFw7xcjtGS//u/aZ8y/811SWXNO6OSpTm6q8sM/rcf4js5wA6Szvqn+RcnKt8LgkKpEL59v+Us0TiK135pch2NEufuc+rvlD8lPyRRImt+sR1xp+xR2SfBtBxfzJ9PVvLmThXadv6ZswTAyBhwi/MpqotWf/fAvq8j5jy73808oXitF0ilfJRvWoq9/zW+O6EyP4LoPO0U/ienIdzlxlU2wVPxir55ABIEsvU/dVyrEh0Y1r/3wKNKwzddNzIbwjWr5APi6ij1dc+ZUoXHxrZTwF0zVpzyi5vkfNwLtOu+p+YJwhAQujzPyrnisRXWdgf2Y6Oc4umdOFBpnLHyabuvSwfIlFbqy2/wehZU6L7JYCu8Wzlyjk4t/nT1MTgSSnLJwlAMpRv/39ytkh8pSu/HNmOrumfaEx5SD5EorYU/uapNO+o6H4IoNtq2rX2lHNwrvNddXbMEwUgAVJ5/f8EfdmxNPfT8hEStb5gv29c+Wr62yP7IIAEsNXFcv7NfSVHvdPnxmBAAlmN64anqdqLD8RsR/dUFvxMPkSilhbu81zbH0i0etm29pbzLwV5rroq5gkD0EWpvP7/fU5kO7qp9vSt8iEStaT6qscaN66T+xyAhLHVzXLupY35duHDkScMQFeVb/uhnDkSX+mqf41sR9eE6/9L6+VDJGqq8KpclTtPNv7AbtF9DkDihDe/lXMvvSrfVQvkkwage1J5/f8krf+f8yn5CInGXP2VPzUuM8vgD6RHMPzfJ+ddEg076jPyiQPQLeH6/5VyBkl0tZWs/6fsVX/lcVO++YTGb5TkPgYg2TxHfV7OuyQypmer4MlaLJ88AJ2Xzuv/u5Ht6KbaU7fIh0i0ZZWHGjeUK118cGS/ApAay8ycnm3kvEsxabdwbMwTCKDDyrf9QI4kia909Vci29E17gTW/9Ooq730sCnf8ROjZ+0V3acApIp21L/LOZc2kembsm3wpD0tn0QAnVV9/Ao5myS7etX4g++IbEe3lC4+VD7CxFddfL4pX/sNU7nnfxr3f6iveaLxvFJ7q69eaip3/8bo2R+K7EcAUmulGVTbyTmXNhO/BQC6rz6UtvX/iyLb0E2V+f8tH2Lii72C0vTdG8tQwjXolQcGTe2Z21P33ZDEVS2Z2rPzTWXBz42+4IDocw4g9TzHOkHOt/Q6mcH93ui76kn5ZALoDH3eh+XIkvgq90+PbEc31Z68WT7EZBdeQWlwz8h2bIqe9W5TuvyIxnKV6sPnjHwwWPc0vzGIK3huww+o1UWzRj5kzZgceT4BZMrz5uxJb5bzLW1B2lHfiXlCAXRA+baT5AiT+EpXHxnZjq5J4fr/lt1BeWC3xlKWcNAt3/6fpvrgmY0vQzeWEwWDcB6qb3i+8QGwcvcppnTZ4Qz8QM54tvoPOdfSFmbsyW8KnsQV8kkF0H7VpZfLmSbZJW79/yHyESa+ysL+yHa0XP9Eo8/Z35Su+IIp33x8Y9179aHfmdryGxofQOpDL6bnNwjB46yvX2FqK+4y1cUXmsodJzd+I8KXd4HcW2lOHb+9nGtpFGmn8L2YJxZAmzUGsRTF+v/mi13/3w3uBKPP2rfxIao076jG1agq955mqg/PNtVlVzWWGoWvd33tU6burwkeeV1uSlPV9brG/l9fs9zUnr+38WXo6qIzTOWuXzZuwlW6/HNGn7s/1+QHEM8t/EjOszTKwvVTwZP5XOTJBdA24fKNtFW5f0ZkO7opnev/k/MblLHQM9814pz9GwN6+MXlzdHnf2zk3w2duXei7iANIKVs9bLpH7eDnGdpDHmOOinyBANom1Re/z8pf3sd6p8YPKAN8iEmutoLC6PbAQAYHVv9VM6xNMbCa6gGT+rzkScZQFtw/f/mlOak7/r/SbuDMgCk0Lq1AxN3lHMsNRH3BQA6xUrdNd5rK1t09ZoWCa/tnrYS9RsUAEgj1v63PjOnZxvfVUsiTzaAltLn/aOcDRNfZeFAZDu6KbzkZaoK1/+z/h0AmvECV/5pU8GT+6WYJxxAC6Xz+v9fiWxH16Rx/f+L90e3AwCwxbSrvivnVmpRpq9na+2oB+STDqB1uP5/c1j/DwB5Yz1hBvd7o5xbqYVpWx0WfeIBtEp9KG3r/xN2/X/W/wNAvtjWkXJepTbku2pB5MkH0DR93oflbJj4KvdPj2xHN7H+HwBy5ZHwe6pyVqU2pF11UMwLAKBJ5VvTuP7/yMh2dE0q1/8n6wpKAJAmnmMdIedUamPBkz5PvggAmlNdepmcD5Md6/+brrKwP7IdAIAt8gc5n1KbKw0U3xs88dWYFwPAGLH+vzmVBT+TDzHxsf4fAMbItQ6U8yl1IN+xBiMvBoAx0bM/JGfDxJe49f9P3iwfYrIL1/8P7hnZDgDA5mlHXS7nUupQG6aP3zV4EdbJFwXA6LH+v0nuhOABrZcPMdGx/h8AxqSk7Qlvl3MpdTDfVT+JeWEAjBLr/5tTujiN6/+TdQdlAEgDz1XT5DxKHc6cVvyb4MV4Rr44AEYnfev/H4xsQzelcv1/ku6gDADpsHrtwMQd5TxKXSh4MY6JeYEAbCE9+4NyNkx8lftnRLajm1K3/j9hv0EBgDTwbOtEOYdSlzJ9PW8IXpTF8kUCsGXKt/6HHA8TX2neUZHt6Jo0rv9fyfp/ABilp8zZk94s51DqYv4062MxLxSALVBdcqmcD5Ndwv72mvX/AJB93PQroYWXZJIvFoDXV9/wvJwPE13tpYci29BNrP8HgMy725iereTsSQnI61cTghdoKOZFA7AJ+tx/kLNh4qs8MBjZjm5i/T8AZFp12Fb7yrmTElTwIp0c88IB2ITyLd+X42HiK837amQ7uiaV6/+TdQdlAEg0tzBDzpuUsDZeFnR55MUDEKu65BI5Hya7hP3tdeniQ+QjTHxJu4MyACTYqnWnFXeS8yYlMM8pHB7zAgKIwfr/5lTm/7d8iIkvUXdQBoAE0476dzlnUoILXrTr5YsI4LX0ufvL2TDxVR6YGdmObqo9eZN8iMkuYb9BAYCk8mz1oJnTs42cMSnBlW1r7+DFq8gXE8BflW85UY6Hia8072uR7ega1v8DQGZpW31CzpeUgrSrfiNfTAB/VV0yV86Hya5eM3rmuyLb0S3pXP+frDsoA0ASaUfNkXMlpSRj7/S3wYu4Qr6oAEakb/3/w5Ft6KZUrv9P0h2UASCZPD0wfnc5V1KKGnbUZ2JeWCD39Dms/28W6/8BIHs82zpRzpOUwjxXXSVfXCDvyrf8XzkeJj7W/zdXbeWD0e0AAPyFdtV9fPE3I/nT1ESfOwQDr1F9jPX/zWD9PwBkTnV4WmE/OUdSivPdwo9iXmggt+obnpPzYaKrvfxIZBu6qTL/p/IhJj7W/wPApmnbmirnR0p5pm/KtsGLu1i+2EAe6XP+t5wNE19l0czIdnRTbfmN8iEmO9b/A8DmLDeDajs5P1IG8l3rwOAFrse86ECulG8+QY6Hia98zdGR7eiaNK7/T9gdlAEgSTy78Fk5N1KG8t3CDPmiA3lTWfALYyq+nBETXN3oWe+ObEe3lC76hHyAiS9pv0EBgKTQbmGunBcpY60dmLhj8GI/L198IHfcCUaf/zFTvvUkU112tan7a+TMmJhY/998pXlfjWwHAECt8/rVBDkvUgbTbvHQmB0AyLcEfyCoLpoVfbxdxPp/AMiMr8k5kTJc8IKfH7MTAPgztyg+ELwix8qOVb7mmOjj6xbW/wNANtjqOjkfUsZb71o7By/+ysjOACBetz4QhNf/n7VX9PF0Senig+UjTHxJu4MyAHSbdtQab3rRkvMh5SDPVV+QOwSALafP2f9VHwhWy7mzJdVfXhz5ud2UzvX/CbqDMgAkgHasb8m5kHJU8AnwcrlTABibdnwgYP1/kyXsDsoAkADBgbxnKzkTUo7yp6mJwY6wNmbnANCkv3wgWDLX1Dc8L0fTLYr1/81Ve+nh6HYAQH552rX2lPMg5bBgZ/hSzA4CoMVG/YEgaev/L/qkfISJj/X/APBX2lbHyTmQcpxnqyvkTgKgvV77geA5Obua+qpHI/+fbqrc2ScfYu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diff --git a/content/substrate/wasm/img/dev-4-3-full-comm.svg b/assets/img/5-Substrate/dev-4-3-full-comm.svg
similarity index 89%
rename from content/substrate/wasm/img/dev-4-3-full-comm.svg
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index dfe59f76..6eff82b9 100644
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diff --git a/content/substrate/storage/img/dev-trie-backend-16-with-size.svg b/assets/img/5-Substrate/dev-trie-backend-16-with-size.svg
similarity index 100%
rename from content/substrate/storage/img/dev-trie-backend-16-with-size.svg
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diff --git a/content/substrate/storage/img/dev-trie-backend-16.svg b/assets/img/5-Substrate/dev-trie-backend-16.svg
similarity index 100%
rename from content/substrate/storage/img/dev-trie-backend-16.svg
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diff --git a/content/substrate/storage/img/dev-trie-backend-proof-fat.svg b/assets/img/5-Substrate/dev-trie-backend-proof-fat.svg
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diff --git a/assets/img/5-Substrate/dev-trie-backend-proof.svg b/assets/img/5-Substrate/dev-trie-backend-proof.svg
new file mode 100644
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similarity index 100%
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new file mode 100644
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diff --git a/content/frame/benchmarking-2/img/rocksdb-hiccups.png b/assets/img/6-FRAME/benchmark/rocksdb-hiccups.png
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diff --git a/content/polkadot/scaling-homogeneous/img/Eigenlayer.webp b/assets/img/7-Polkadot/Blockchain_Scaling/Eigenlayer.webp
similarity index 100%
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rename to assets/img/7-Polkadot/Blockchain_Scaling/Eigenlayer.webp
diff --git a/content/polkadot/scaling-heterogeneous/img/L2Beat.png b/assets/img/7-Polkadot/Blockchain_Scaling/L2Beat.png
similarity index 100%
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+    <!-- 8&#45;&gt;2 -->
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+      <text
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+    <!-- 8&#45;&gt;13 -->
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+    <!-- 8&#45;&gt;19 -->
+    <g
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+    <!-- 10&#45;&gt;9 -->
+    <g
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+    <!-- 14&#45;&gt;9 -->
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+    <!-- 17&#45;&gt;16 -->
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+       class="edge"
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+      <text
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+         font-weight="bold"
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+       class="edge"
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+      <path
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+    <!-- 21 -->
+    <g
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+       class="node"
+       style="stroke-width:1.50039683;stroke-dasharray:none;stroke:#ffffff;stroke-opacity:1">
+      <title
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+      <ellipse
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+         stroke="black"
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+    <!-- 18&#45;&gt;9 -->
+    <g
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+    <!-- 18&#45;&gt;11 -->
+    <g
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+       class="edge"
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+      <text
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+    <!-- 18&#45;&gt;21 -->
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+    <g
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+      <ellipse
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diff --git a/content/polkadot/decisions/img/grandpa.png b/assets/img/7-Polkadot/decisions/grandpa.png
similarity index 100%
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rename from content/polkadot/decisions/img/treasury.svg
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index 00000000..588abb3c
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new file mode 100644
index 00000000..d66f42b7
--- /dev/null
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similarity index 100%
rename from content/polkadot/shared-security/img/double-spend.svg
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similarity index 100%
rename from content/polkadot/ecosystem-economy/img/collab.svg
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diff --git a/content/polkadot/ecosystem-economy/img/fellowship-manifesto.png b/assets/img/7-Polkadot/eco/fellowship-manifesto.png
similarity index 100%
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similarity index 100%
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diff --git a/content/polkadot/ecosystem-economy/img/forum.png b/assets/img/7-Polkadot/eco/forum.png
similarity index 100%
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diff --git a/content/polkadot/ecosystem-economy/img/governance.avif b/assets/img/7-Polkadot/eco/governance.avif
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+<g>
+	<g>
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new file mode 100644
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\ No newline at end of file
diff --git a/content/polkadot/zombienet/img/zombienet-env-vars.png b/assets/img/7-Polkadot/zombienet/zombienet-env-vars.png
similarity index 100%
rename from content/polkadot/zombienet/img/zombienet-env-vars.png
rename to assets/img/7-Polkadot/zombienet/zombienet-env-vars.png
diff --git a/assets/img/README.md b/assets/img/README.md
new file mode 100644
index 00000000..0565c773
--- /dev/null
+++ b/assets/img/README.md
@@ -0,0 +1,5 @@
+# PBA Graphical Assets
+
+- Please use any assets that live in any Parity of Web3 websites if possible first.
+- ALWAYS cite where you sourced an image you use! Put a note in these folders or the image title, and use that directly in your materials (citation specifics TBA, for now a link only is OK)
+- Peruse existing assets before requesting or adding another!
diff --git a/assets/ink!ubator_PBA6_2025.pdf b/assets/ink!ubator_PBA6_2025.pdf
new file mode 100644
index 00000000..af0b1956
Binary files /dev/null and b/assets/ink!ubator_PBA6_2025.pdf differ
diff --git a/assets/opengov_pba_lucerne_2025.pdf b/assets/opengov_pba_lucerne_2025.pdf
new file mode 100644
index 00000000..656544ba
Binary files /dev/null and b/assets/opengov_pba_lucerne_2025.pdf differ
diff --git a/assets/opengov_pba_lucerne_2025_fin.pdf b/assets/opengov_pba_lucerne_2025_fin.pdf
new file mode 100644
index 00000000..b1577192
Binary files /dev/null and b/assets/opengov_pba_lucerne_2025_fin.pdf differ
diff --git a/assets/plugin/chart/chart.js b/assets/plugin/chart/chart.js
new file mode 100644
index 00000000..62870bb1
--- /dev/null
+++ b/assets/plugin/chart/chart.js
@@ -0,0 +1,207 @@
+/*****************************************************************
+ ** Author: Asvin Goel, goel@telematique.eu
+ ** Fixed for Reveal4: kotborealis@awooo.ru
+ **
+ ** A plugin for reveal.js allowing to integrate Chart.js
+ **
+ ** Version: 1.3.1
+ **
+ ** License: MIT license (see LICENSE.md)
+ **
+ ******************************************************************/
+
+/**
+ * Reveal Plugin
+ * https://revealjs.com/creating-plugins/
+ */
+window.RevealChart = window.RevealChart || {
+  id: "RevealChart",
+  init: function(deck) {
+    initChart(deck);
+  },
+  update: function(canvas, idx, data) {
+    update(canvas, idx, data);
+  },
+};
+
+const initChart = function(Reveal) {
+  function parseJSON(str) {
+    var json;
+    try {
+      json = JSON.parse(str);
+    } catch (e) {
+      return null;
+    }
+    return json;
+  }
+
+  /*
+   * Recursively merge properties of two objects
+   */
+  function mergeRecursive(obj1, obj2) {
+    for (var p in obj2) {
+      try {
+        // Property in destination object set; update its value.
+        if (obj1[p] !== null && typeof obj1[p] === "object" && typeof obj2[p] === "object") {
+          obj1[p] = mergeRecursive(obj1[p], obj2[p]);
+        } else {
+          obj1[p] = obj2[p];
+        }
+      } catch (e) {
+        // Property in destination object not set; create it and set its value.
+        obj1[p] = obj2[p];
+      }
+    }
+
+    return obj1;
+  }
+
+  function createChart(canvas, CSV, comments) {
+    canvas.chart = null;
+    var ctx = canvas.getContext("2d");
+    var chartOptions = { responsive: true, maintainAspectRatio: false };
+    var chartData = { labels: null, datasets: [] };
+    if (comments !== null) {
+      for (var j = 0; j < comments.length; j++) {
+        comments[j] = comments[j].replace(/<!--/, "");
+        comments[j] = comments[j].replace(/-->/, "");
+        var config = parseJSON(comments[j]);
+        if (config) {
+          if (config.data) {
+            mergeRecursive(chartData, config.data);
+          }
+          if (config.options) {
+            mergeRecursive(chartOptions, config.options);
+          }
+        }
+      }
+    }
+
+    var lines = CSV.split("\n").filter(function(v) {
+      return v !== "";
+    });
+    // if labels are not defined, get them from first line
+    if (chartData.labels === null && lines.length > 0) {
+      chartData.labels = lines[0].split(",");
+      chartData.labels.shift();
+      lines.shift();
+    }
+    // get data values
+    for (var j = 0; j < lines.length; j++) {
+      if (chartData.datasets.length <= j) chartData.datasets[j] = {};
+      chartData.datasets[j].data = lines[j].split(","); // .filter(function(v){return v!==''});
+      chartData.datasets[j].label = chartData.datasets[j].data[0];
+      chartData.datasets[j].data.shift();
+      for (var k = 0; k < chartData.datasets[j].data.length; k++) {
+        chartData.datasets[j].data[k] = Number(chartData.datasets[j].data[k]);
+      }
+    }
+
+    // add chart options
+    var config = chartConfig[canvas.getAttribute("data-chart")];
+    if (config) {
+      for (var j = 0; j < chartData.datasets.length; j++) {
+        for (var attrname in config) {
+          if (!chartData.datasets[j][attrname]) {
+            chartData.datasets[j][attrname] = config[attrname][j % config[attrname].length];
+          }
+        }
+      }
+    }
+
+    canvas.chart = new Chart(ctx, { type: canvas.getAttribute("data-chart"), data: chartData, options: chartOptions });
+  }
+
+  function updateChart(canvas, idx, data) {
+    canvas.chart.data.datasets[idx].data = data;
+    recreateChart(canvas);
+  }
+
+  var initializeCharts = function() {
+    // Get all canvases
+    var canvases = document.querySelectorAll("canvas");
+    for (var i = 0; i < canvases.length; i++) {
+      // check if canvas has data-chart attribute
+      if (canvases[i].hasAttribute("data-chart")) {
+        var CSV = canvases[i].innerHTML.trim();
+        var comments = CSV.match(/<!--[\s\S]*?-->/g);
+        CSV = CSV.replace(/<!--[\s\S]*?-->/g, "").replace(/^\s*\n/gm, "");
+        if (!canvases[i].hasAttribute("data-chart-src")) {
+          createChart(canvases[i], CSV, comments);
+        } else {
+          var canvas = canvases[i];
+          var xhr = new XMLHttpRequest();
+          xhr.onload = function() {
+            if (xhr.readyState === 4) {
+              createChart(canvas, xhr.responseText, comments);
+            } else {
+              console.warn(
+                "Failed to get file " + canvas.getAttribute("data-chart-src") + ". ReadyState: " + xhr.readyState
+                  + ", Status: " + xhr.status,
+              );
+            }
+          };
+
+          xhr.open("GET", canvas.getAttribute("data-chart-src"), false);
+          try {
+            xhr.send();
+          } catch (error) {
+            console.warn(
+              "Failed to get file " + canvas.getAttribute("data-chart-src")
+                + ". Make sure that the presentation and the file are served by a HTTP server and the file can be found there. "
+                + error,
+            );
+          }
+        }
+      }
+    }
+  };
+
+  function recreateChart(canvas) {
+    // clear data to redraw animation
+    var data = canvas.chart.data.datasets;
+    canvas.chart.data.datasets = [];
+    canvas.chart.update();
+    canvas.style.visibility = "hidden";
+    setTimeout(
+      function(canvas, data) {
+        canvas.chart.data.datasets = data;
+        canvas.style.visibility = "visible";
+        canvas.chart.update();
+      },
+      500,
+      canvas,
+      data,
+    ); // wait for slide transition to re-add data and animation
+    /*
+  var config = canvas.chart.config;
+  canvas.chart.destroy();
+  setTimeout( function() { canvas.chart = new Chart(canvas, config);}, 500); // wait for slide transition
+    */
+  }
+
+  // check if chart option is given or not
+  var chartConfig = Reveal.getConfig().chart || {};
+
+  // set global chart options
+  var config = chartConfig.defaults;
+  if (config) {
+    mergeRecursive(Chart.defaults, config);
+  }
+
+  Reveal.addEventListener("ready", function() {
+    initializeCharts();
+    Reveal.addEventListener("slidechanged", function() {
+      var canvases = Reveal.getCurrentSlide().querySelectorAll("canvas[data-chart]");
+      for (var i = 0; i < canvases.length; i++) {
+        if (canvases[i].chart && canvases[i].chart.config.options.animation !== false) {
+          recreateChart(canvases[i]);
+        }
+      }
+    });
+  });
+
+  this.update = updateChart;
+
+  return this;
+};
diff --git a/assets/plugin/chart/chart.min.js b/assets/plugin/chart/chart.min.js
new file mode 100644
index 00000000..42006258
--- /dev/null
+++ b/assets/plugin/chart/chart.min.js
@@ -0,0 +1,8754 @@
+/*!
+ * Chart.js v3.9.0
+ * https://www.chartjs.org
+ * (c) 2022 Chart.js Contributors
+ * Released under the MIT License
+ */
+!function(t, e) {
+  "object" == typeof exports && "undefined" != typeof module
+    ? module.exports = e()
+    : "function" == typeof define && define.amd
+    ? define(e)
+    : (t = "undefined" != typeof globalThis ? globalThis : t || self).Chart = e();
+}(this, function() {
+  "use strict";
+  function t() {}
+  const e = function() {
+    let t = 0;
+    return function() {
+      return t++;
+    };
+  }();
+  function i(t) {
+    return null == t;
+  }
+  function s(t) {
+    if (Array.isArray && Array.isArray(t)) return !0;
+    const e = Object.prototype.toString.call(t);
+    return "[object" === e.slice(0, 7) && "Array]" === e.slice(-6);
+  }
+  function n(t) {
+    return null !== t && "[object Object]" === Object.prototype.toString.call(t);
+  }
+  const o = t => ("number" == typeof t || t instanceof Number) && isFinite(+t);
+  function a(t, e) {
+    return o(t) ? t : e;
+  }
+  function r(t, e) {
+    return void 0 === t ? e : t;
+  }
+  const l = (t, e) => "string" == typeof t && t.endsWith("%") ? parseFloat(t) / 100 : t / e,
+    h = (t, e) => "string" == typeof t && t.endsWith("%") ? parseFloat(t) / 100 * e : +t;
+  function c(t, e, i) {
+    if (t && "function" == typeof t.call) return t.apply(i, e);
+  }
+  function d(t, e, i, o) {
+    let a, r, l;
+    if (s(t)) {
+      if (r = t.length, o) for (a = r - 1; a >= 0; a--) e.call(i, t[a], a);
+      else for (a = 0; a < r; a++) e.call(i, t[a], a);
+    } else if (n(t)) for (l = Object.keys(t), r = l.length, a = 0; a < r; a++) e.call(i, t[l[a]], l[a]);
+  }
+  function u(t, e) {
+    let i, s, n, o;
+    if (!t || !e || t.length !== e.length) return !1;
+    for (i = 0, s = t.length; i < s; ++i) {
+      if (n = t[i], o = e[i], n.datasetIndex !== o.datasetIndex || n.index !== o.index) return !1;
+    }
+    return !0;
+  }
+  function f(t) {
+    if (s(t)) return t.map(f);
+    if (n(t)) {
+      const e = Object.create(null), i = Object.keys(t), s = i.length;
+      let n = 0;
+      for (; n < s; ++n) e[i[n]] = f(t[i[n]]);
+      return e;
+    }
+    return t;
+  }
+  function g(t) {
+    return -1 === ["__proto__", "prototype", "constructor"].indexOf(t);
+  }
+  function p(t, e, i, s) {
+    if (!g(t)) return;
+    const o = e[t], a = i[t];
+    n(o) && n(a) ? m(o, a, s) : e[t] = f(a);
+  }
+  function m(t, e, i) {
+    const o = s(e) ? e : [e], a = o.length;
+    if (!n(t)) return t;
+    const r = (i = i || {}).merger || p;
+    for (let s = 0; s < a; ++s) {
+      if (!n(e = o[s])) continue;
+      const a = Object.keys(e);
+      for (let s = 0, n = a.length; s < n; ++s) r(a[s], t, e, i);
+    }
+    return t;
+  }
+  function b(t, e) {
+    return m(t, e, { merger: x });
+  }
+  function x(t, e, i) {
+    if (!g(t)) return;
+    const s = e[t], o = i[t];
+    n(s) && n(o) ? b(s, o) : Object.prototype.hasOwnProperty.call(e, t) || (e[t] = f(o));
+  }
+  const _ = { "": t => t, x: t => t.x, y: t => t.y };
+  function y(t, e) {
+    const i = _[e] || (_[e] = function(t) {
+      const e = v(t);
+      return t => {
+        for (const i of e) {
+          if ("" === i) break;
+          t = t && t[i];
+        }
+        return t;
+      };
+    }(e));
+    return i(t);
+  }
+  function v(t) {
+    const e = t.split("."), i = [];
+    let s = "";
+    for (const t of e) s += t, s.endsWith("\\") ? s = s.slice(0, -1) + "." : (i.push(s), s = "");
+    return i;
+  }
+  function w(t) {
+    return t.charAt(0).toUpperCase() + t.slice(1);
+  }
+  const M = t => void 0 !== t,
+    k = t => "function" == typeof t,
+    S = (t, e) => {
+      if (t.size !== e.size) return !1;
+      for (const i of t) if (!e.has(i)) return !1;
+      return !0;
+    };
+  function P(t) {
+    return "mouseup" === t.type || "click" === t.type || "contextmenu" === t.type;
+  }
+  const D = Math.PI,
+    O = 2 * D,
+    C = O + D,
+    A = Number.POSITIVE_INFINITY,
+    T = D / 180,
+    L = D / 2,
+    E = D / 4,
+    R = 2 * D / 3,
+    I = Math.log10,
+    z = Math.sign;
+  function F(t) {
+    const e = Math.round(t);
+    t = N(t, e, t / 1e3) ? e : t;
+    const i = Math.pow(10, Math.floor(I(t))), s = t / i;
+    return (s <= 1 ? 1 : s <= 2 ? 2 : s <= 5 ? 5 : 10) * i;
+  }
+  function V(t) {
+    const e = [], i = Math.sqrt(t);
+    let s;
+    for (s = 1; s < i; s++) t % s == 0 && (e.push(s), e.push(t / s));
+    return i === (0 | i) && e.push(i), e.sort((t, e) => t - e).pop(), e;
+  }
+  function B(t) {
+    return !isNaN(parseFloat(t)) && isFinite(t);
+  }
+  function N(t, e, i) {
+    return Math.abs(t - e) < i;
+  }
+  function W(t, e) {
+    const i = Math.round(t);
+    return i - e <= t && i + e >= t;
+  }
+  function j(t, e, i) {
+    let s, n, o;
+    for (s = 0, n = t.length; s < n; s++) {
+      o = t[s][i], isNaN(o) || (e.min = Math.min(e.min, o), e.max = Math.max(e.max, o));
+    }
+  }
+  function H(t) {
+    return t * (D / 180);
+  }
+  function $(t) {
+    return t * (180 / D);
+  }
+  function Y(t) {
+    if (!o(t)) return;
+    let e = 1, i = 0;
+    for (; Math.round(t * e) / e !== t;) e *= 10, i++;
+    return i;
+  }
+  function U(t, e) {
+    const i = e.x - t.x, s = e.y - t.y, n = Math.sqrt(i * i + s * s);
+    let o = Math.atan2(s, i);
+    return o < -.5 * D && (o += O), { angle: o, distance: n };
+  }
+  function X(t, e) {
+    return Math.sqrt(Math.pow(e.x - t.x, 2) + Math.pow(e.y - t.y, 2));
+  }
+  function q(t, e) {
+    return (t - e + C) % O - D;
+  }
+  function K(t) {
+    return (t % O + O) % O;
+  }
+  function G(t, e, i, s) {
+    const n = K(t), o = K(e), a = K(i), r = K(o - n), l = K(a - n), h = K(n - o), c = K(n - a);
+    return n === o || n === a || s && o === a || r > l && h < c;
+  }
+  function Z(t, e, i) {
+    return Math.max(e, Math.min(i, t));
+  }
+  function J(t) {
+    return Z(t, -32768, 32767);
+  }
+  function Q(t, e, i, s = 1e-6) {
+    return t >= Math.min(e, i) - s && t <= Math.max(e, i) + s;
+  }
+  function tt(t, e, i) {
+    i = i || (i => t[i] < e);
+    let s, n = t.length - 1, o = 0;
+    for (; n - o > 1;) s = o + n >> 1, i(s) ? o = s : n = s;
+    return { lo: o, hi: n };
+  }
+  const et = (t, e, i, s) => tt(t, i, s ? s => t[s][e] <= i : s => t[s][e] < i),
+    it = (t, e, i) => tt(t, i, s => t[s][e] >= i);
+  function st(t, e, i) {
+    let s = 0, n = t.length;
+    for (; s < n && t[s] < e;) s++;
+    for (; n > s && t[n - 1] > i;) n--;
+    return s > 0 || n < t.length ? t.slice(s, n) : t;
+  }
+  const nt = ["push", "pop", "shift", "splice", "unshift"];
+  function ot(t, e) {
+    t._chartjs
+      ? t._chartjs.listeners.push(e)
+      : (Object.defineProperty(t, "_chartjs", { configurable: !0, enumerable: !1, value: { listeners: [e] } }),
+        nt.forEach(e => {
+          const i = "_onData" + w(e), s = t[e];
+          Object.defineProperty(t, e, {
+            configurable: !0,
+            enumerable: !1,
+            value(...e) {
+              const n = s.apply(this, e);
+              return t._chartjs.listeners.forEach(t => {
+                "function" == typeof t[i] && t[i](...e);
+              }),
+                n;
+            },
+          });
+        }));
+  }
+  function at(t, e) {
+    const i = t._chartjs;
+    if (!i) return;
+    const s = i.listeners, n = s.indexOf(e);
+    -1 !== n && s.splice(n, 1),
+      s.length > 0 || (nt.forEach(e => {
+        delete t[e];
+      }),
+        delete t._chartjs);
+  }
+  function rt(t) {
+    const e = new Set();
+    let i, s;
+    for (i = 0, s = t.length; i < s; ++i) e.add(t[i]);
+    return e.size === s ? t : Array.from(e);
+  }
+  const lt = "undefined" == typeof window
+    ? function(t) {
+      return t();
+    }
+    : window.requestAnimationFrame;
+  function ht(t, e, i) {
+    const s = i || (t => Array.prototype.slice.call(t));
+    let n = !1, o = [];
+    return function(...i) {
+      o = s(i),
+        n || (n = !0,
+          lt.call(window, () => {
+            n = !1, t.apply(e, o);
+          }));
+    };
+  }
+  function ct(t, e) {
+    let i;
+    return function(...s) {
+      return e ? (clearTimeout(i), i = setTimeout(t, e, s)) : t.apply(this, s), e;
+    };
+  }
+  const dt = t => "start" === t ? "left" : "end" === t ? "right" : "center",
+    ut = (t, e, i) => "start" === t ? e : "end" === t ? i : (e + i) / 2,
+    ft = (t, e, i, s) => t === (s ? "left" : "right") ? i : "center" === t ? (e + i) / 2 : e;
+  function gt(t, e, i) {
+    const s = e.length;
+    let n = 0, o = s;
+    if (t._sorted) {
+      const { iScale: a, _parsed: r } = t,
+        l = a.axis,
+        { min: h, max: c, minDefined: d, maxDefined: u } = a.getUserBounds();
+      d && (n = Z(Math.min(et(r, a.axis, h).lo, i ? s : et(e, l, a.getPixelForValue(h)).lo), 0, s - 1)),
+        o = u
+          ? Z(Math.max(et(r, a.axis, c, !0).hi + 1, i ? 0 : et(e, l, a.getPixelForValue(c), !0).hi + 1), n, s) - n
+          : s - n;
+    }
+    return { start: n, count: o };
+  }
+  function pt(t) {
+    const { xScale: e, yScale: i, _scaleRanges: s } = t, n = { xmin: e.min, xmax: e.max, ymin: i.min, ymax: i.max };
+    if (!s) return t._scaleRanges = n, !0;
+    const o = s.xmin !== e.min || s.xmax !== e.max || s.ymin !== i.min || s.ymax !== i.max;
+    return Object.assign(s, n), o;
+  }
+  var mt = new class {
+    constructor() {
+      this._request = null, this._charts = new Map(), this._running = !1, this._lastDate = void 0;
+    }
+    _notify(t, e, i, s) {
+      const n = e.listeners[s], o = e.duration;
+      n.forEach(s => s({ chart: t, initial: e.initial, numSteps: o, currentStep: Math.min(i - e.start, o) }));
+    }
+    _refresh() {
+      this._request || (this._running = !0,
+        this._request = lt.call(window, () => {
+          this._update(), this._request = null, this._running && this._refresh();
+        }));
+    }
+    _update(t = Date.now()) {
+      let e = 0;
+      this._charts.forEach((i, s) => {
+        if (!i.running || !i.items.length) return;
+        const n = i.items;
+        let o, a = n.length - 1, r = !1;
+        for (; a >= 0; --a) {
+          o = n[a],
+            o._active
+              ? (o._total > i.duration && (i.duration = o._total), o.tick(t), r = !0)
+              : (n[a] = n[n.length - 1], n.pop());
+        }
+        r && (s.draw(), this._notify(s, i, t, "progress")),
+          n.length || (i.running = !1, this._notify(s, i, t, "complete"), i.initial = !1),
+          e += n.length;
+      }),
+        this._lastDate = t,
+        0 === e && (this._running = !1);
+    }
+    _getAnims(t) {
+      const e = this._charts;
+      let i = e.get(t);
+      return i || (i = { running: !1, initial: !0, items: [], listeners: { complete: [], progress: [] } }, e.set(t, i)),
+        i;
+    }
+    listen(t, e, i) {
+      this._getAnims(t).listeners[e].push(i);
+    }
+    add(t, e) {
+      e && e.length && this._getAnims(t).items.push(...e);
+    }
+    has(t) {
+      return this._getAnims(t).items.length > 0;
+    }
+    start(t) {
+      const e = this._charts.get(t);
+      e
+        && (e.running = !0,
+          e.start = Date.now(),
+          e.duration = e.items.reduce((t, e) => Math.max(t, e._duration), 0),
+          this._refresh());
+    }
+    running(t) {
+      if (!this._running) return !1;
+      const e = this._charts.get(t);
+      return !!(e && e.running && e.items.length);
+    }
+    stop(t) {
+      const e = this._charts.get(t);
+      if (!e || !e.items.length) return;
+      const i = e.items;
+      let s = i.length - 1;
+      for (; s >= 0; --s) i[s].cancel();
+      e.items = [], this._notify(t, e, Date.now(), "complete");
+    }
+    remove(t) {
+      return this._charts.delete(t);
+    }
+  }();
+  /*!
+ * @kurkle/color v0.2.1
+ * https://github.com/kurkle/color#readme
+ * (c) 2022 Jukka Kurkela
+ * Released under the MIT License
+ */ function bt(t) {
+    return t + .5 | 0;
+  }
+  const xt = (t, e, i) => Math.max(Math.min(t, i), e);
+  function _t(t) {
+    return xt(bt(2.55 * t), 0, 255);
+  }
+  function yt(t) {
+    return xt(bt(255 * t), 0, 255);
+  }
+  function vt(t) {
+    return xt(bt(t / 2.55) / 100, 0, 1);
+  }
+  function wt(t) {
+    return xt(bt(100 * t), 0, 100);
+  }
+  const Mt = {
+      0: 0,
+      1: 1,
+      2: 2,
+      3: 3,
+      4: 4,
+      5: 5,
+      6: 6,
+      7: 7,
+      8: 8,
+      9: 9,
+      A: 10,
+      B: 11,
+      C: 12,
+      D: 13,
+      E: 14,
+      F: 15,
+      a: 10,
+      b: 11,
+      c: 12,
+      d: 13,
+      e: 14,
+      f: 15,
+    },
+    kt = [..."0123456789ABCDEF"],
+    St = t => kt[15 & t],
+    Pt = t => kt[(240 & t) >> 4] + kt[15 & t],
+    Dt = t => (240 & t) >> 4 == (15 & t);
+  function Ot(t) {
+    var e = (t => Dt(t.r) && Dt(t.g) && Dt(t.b) && Dt(t.a))(t) ? St : Pt;
+    return t ? "#" + e(t.r) + e(t.g) + e(t.b) + ((t, e) => t < 255 ? e(t) : "")(t.a, e) : void 0;
+  }
+  const Ct =
+    /^(hsla?|hwb|hsv)\(\s*([-+.e\d]+)(?:deg)?[\s,]+([-+.e\d]+)%[\s,]+([-+.e\d]+)%(?:[\s,]+([-+.e\d]+)(%)?)?\s*\)$/;
+  function At(t, e, i) {
+    const s = e * Math.min(i, 1 - i), n = (e, n = (e + t / 30) % 12) => i - s * Math.max(Math.min(n - 3, 9 - n, 1), -1);
+    return [n(0), n(8), n(4)];
+  }
+  function Tt(t, e, i) {
+    const s = (s, n = (s + t / 60) % 6) => i - i * e * Math.max(Math.min(n, 4 - n, 1), 0);
+    return [s(5), s(3), s(1)];
+  }
+  function Lt(t, e, i) {
+    const s = At(t, 1, .5);
+    let n;
+    for (e + i > 1 && (n = 1 / (e + i), e *= n, i *= n), n = 0; n < 3; n++) s[n] *= 1 - e - i, s[n] += e;
+    return s;
+  }
+  function Et(t) {
+    const e = t.r / 255, i = t.g / 255, s = t.b / 255, n = Math.max(e, i, s), o = Math.min(e, i, s), a = (n + o) / 2;
+    let r, l, h;
+    return n !== o && (h = n - o,
+      l = a > .5 ? h / (2 - n - o) : h / (n + o),
+      r = function(t, e, i, s, n) {
+        return t === n ? (e - i) / s + (e < i ? 6 : 0) : e === n ? (i - t) / s + 2 : (t - e) / s + 4;
+      }(e, i, s, h, n),
+      r = 60 * r + .5),
+      [0 | r, l || 0, a];
+  }
+  function Rt(t, e, i, s) {
+    return (Array.isArray(e) ? t(e[0], e[1], e[2]) : t(e, i, s)).map(yt);
+  }
+  function It(t, e, i) {
+    return Rt(At, t, e, i);
+  }
+  function zt(t) {
+    return (t % 360 + 360) % 360;
+  }
+  function Ft(t) {
+    const e = Ct.exec(t);
+    let i, s = 255;
+    if (!e) return;
+    e[5] !== i && (s = e[6] ? _t(+e[5]) : yt(+e[5]));
+    const n = zt(+e[2]), o = +e[3] / 100, a = +e[4] / 100;
+    return i = "hwb" === e[1]
+      ? function(t, e, i) {
+        return Rt(Lt, t, e, i);
+      }(n, o, a)
+      : "hsv" === e[1]
+      ? function(t, e, i) {
+        return Rt(Tt, t, e, i);
+      }(n, o, a)
+      : It(n, o, a),
+      { r: i[0], g: i[1], b: i[2], a: s };
+  }
+  const Vt = {
+      x: "dark",
+      Z: "light",
+      Y: "re",
+      X: "blu",
+      W: "gr",
+      V: "medium",
+      U: "slate",
+      A: "ee",
+      T: "ol",
+      S: "or",
+      B: "ra",
+      C: "lateg",
+      D: "ights",
+      R: "in",
+      Q: "turquois",
+      E: "hi",
+      P: "ro",
+      O: "al",
+      N: "le",
+      M: "de",
+      L: "yello",
+      F: "en",
+      K: "ch",
+      G: "arks",
+      H: "ea",
+      I: "ightg",
+      J: "wh",
+    },
+    Bt = {
+      OiceXe: "f0f8ff",
+      antiquewEte: "faebd7",
+      aqua: "ffff",
+      aquamarRe: "7fffd4",
+      azuY: "f0ffff",
+      beige: "f5f5dc",
+      bisque: "ffe4c4",
+      black: "0",
+      blanKedOmond: "ffebcd",
+      Xe: "ff",
+      XeviTet: "8a2be2",
+      bPwn: "a52a2a",
+      burlywood: "deb887",
+      caMtXe: "5f9ea0",
+      KartYuse: "7fff00",
+      KocTate: "d2691e",
+      cSO: "ff7f50",
+      cSnflowerXe: "6495ed",
+      cSnsilk: "fff8dc",
+      crimson: "dc143c",
+      cyan: "ffff",
+      xXe: "8b",
+      xcyan: "8b8b",
+      xgTMnPd: "b8860b",
+      xWay: "a9a9a9",
+      xgYF: "6400",
+      xgYy: "a9a9a9",
+      xkhaki: "bdb76b",
+      xmagFta: "8b008b",
+      xTivegYF: "556b2f",
+      xSange: "ff8c00",
+      xScEd: "9932cc",
+      xYd: "8b0000",
+      xsOmon: "e9967a",
+      xsHgYF: "8fbc8f",
+      xUXe: "483d8b",
+      xUWay: "2f4f4f",
+      xUgYy: "2f4f4f",
+      xQe: "ced1",
+      xviTet: "9400d3",
+      dAppRk: "ff1493",
+      dApskyXe: "bfff",
+      dimWay: "696969",
+      dimgYy: "696969",
+      dodgerXe: "1e90ff",
+      fiYbrick: "b22222",
+      flSOwEte: "fffaf0",
+      foYstWAn: "228b22",
+      fuKsia: "ff00ff",
+      gaRsbSo: "dcdcdc",
+      ghostwEte: "f8f8ff",
+      gTd: "ffd700",
+      gTMnPd: "daa520",
+      Way: "808080",
+      gYF: "8000",
+      gYFLw: "adff2f",
+      gYy: "808080",
+      honeyMw: "f0fff0",
+      hotpRk: "ff69b4",
+      RdianYd: "cd5c5c",
+      Rdigo: "4b0082",
+      ivSy: "fffff0",
+      khaki: "f0e68c",
+      lavFMr: "e6e6fa",
+      lavFMrXsh: "fff0f5",
+      lawngYF: "7cfc00",
+      NmoncEffon: "fffacd",
+      ZXe: "add8e6",
+      ZcSO: "f08080",
+      Zcyan: "e0ffff",
+      ZgTMnPdLw: "fafad2",
+      ZWay: "d3d3d3",
+      ZgYF: "90ee90",
+      ZgYy: "d3d3d3",
+      ZpRk: "ffb6c1",
+      ZsOmon: "ffa07a",
+      ZsHgYF: "20b2aa",
+      ZskyXe: "87cefa",
+      ZUWay: "778899",
+      ZUgYy: "778899",
+      ZstAlXe: "b0c4de",
+      ZLw: "ffffe0",
+      lime: "ff00",
+      limegYF: "32cd32",
+      lRF: "faf0e6",
+      magFta: "ff00ff",
+      maPon: "800000",
+      VaquamarRe: "66cdaa",
+      VXe: "cd",
+      VScEd: "ba55d3",
+      VpurpN: "9370db",
+      VsHgYF: "3cb371",
+      VUXe: "7b68ee",
+      VsprRggYF: "fa9a",
+      VQe: "48d1cc",
+      VviTetYd: "c71585",
+      midnightXe: "191970",
+      mRtcYam: "f5fffa",
+      mistyPse: "ffe4e1",
+      moccasR: "ffe4b5",
+      navajowEte: "ffdead",
+      navy: "80",
+      Tdlace: "fdf5e6",
+      Tive: "808000",
+      TivedBb: "6b8e23",
+      Sange: "ffa500",
+      SangeYd: "ff4500",
+      ScEd: "da70d6",
+      pOegTMnPd: "eee8aa",
+      pOegYF: "98fb98",
+      pOeQe: "afeeee",
+      pOeviTetYd: "db7093",
+      papayawEp: "ffefd5",
+      pHKpuff: "ffdab9",
+      peru: "cd853f",
+      pRk: "ffc0cb",
+      plum: "dda0dd",
+      powMrXe: "b0e0e6",
+      purpN: "800080",
+      YbeccapurpN: "663399",
+      Yd: "ff0000",
+      Psybrown: "bc8f8f",
+      PyOXe: "4169e1",
+      saddNbPwn: "8b4513",
+      sOmon: "fa8072",
+      sandybPwn: "f4a460",
+      sHgYF: "2e8b57",
+      sHshell: "fff5ee",
+      siFna: "a0522d",
+      silver: "c0c0c0",
+      skyXe: "87ceeb",
+      UXe: "6a5acd",
+      UWay: "708090",
+      UgYy: "708090",
+      snow: "fffafa",
+      sprRggYF: "ff7f",
+      stAlXe: "4682b4",
+      tan: "d2b48c",
+      teO: "8080",
+      tEstN: "d8bfd8",
+      tomato: "ff6347",
+      Qe: "40e0d0",
+      viTet: "ee82ee",
+      JHt: "f5deb3",
+      wEte: "ffffff",
+      wEtesmoke: "f5f5f5",
+      Lw: "ffff00",
+      LwgYF: "9acd32",
+    };
+  let Nt;
+  function Wt(t) {
+    Nt || (Nt = function() {
+      const t = {}, e = Object.keys(Bt), i = Object.keys(Vt);
+      let s, n, o, a, r;
+      for (s = 0; s < e.length; s++) {
+        for (a = r = e[s], n = 0; n < i.length; n++) o = i[n], r = r.replace(o, Vt[o]);
+        o = parseInt(Bt[a], 16), t[r] = [o >> 16 & 255, o >> 8 & 255, 255 & o];
+      }
+      return t;
+    }(),
+      Nt.transparent = [0, 0, 0, 0]);
+    const e = Nt[t.toLowerCase()];
+    return e && { r: e[0], g: e[1], b: e[2], a: 4 === e.length ? e[3] : 255 };
+  }
+  const jt = /^rgba?\(\s*([-+.\d]+)(%)?[\s,]+([-+.e\d]+)(%)?[\s,]+([-+.e\d]+)(%)?(?:[\s,/]+([-+.e\d]+)(%)?)?\s*\)$/;
+  const Ht = t => t <= .0031308 ? 12.92 * t : 1.055 * Math.pow(t, 1 / 2.4) - .055,
+    $t = t => t <= .04045 ? t / 12.92 : Math.pow((t + .055) / 1.055, 2.4);
+  function Yt(t, e, i) {
+    if (t) {
+      let s = Et(t);
+      s[e] = Math.max(0, Math.min(s[e] + s[e] * i, 0 === e ? 360 : 1)), s = It(s), t.r = s[0], t.g = s[1], t.b = s[2];
+    }
+  }
+  function Ut(t, e) {
+    return t ? Object.assign(e || {}, t) : t;
+  }
+  function Xt(t) {
+    var e = { r: 0, g: 0, b: 0, a: 255 };
+    return Array.isArray(t)
+      ? t.length >= 3 && (e = { r: t[0], g: t[1], b: t[2], a: 255 }, t.length > 3 && (e.a = yt(t[3])))
+      : (e = Ut(t, { r: 0, g: 0, b: 0, a: 1 })).a = yt(e.a),
+      e;
+  }
+  function qt(t) {
+    return "r" === t.charAt(0)
+      ? function(t) {
+        const e = jt.exec(t);
+        let i, s, n, o = 255;
+        if (e) {
+          if (e[7] !== i) {
+            const t = +e[7];
+            o = e[8] ? _t(t) : xt(255 * t, 0, 255);
+          }
+          return i = +e[1],
+            s = +e[3],
+            n = +e[5],
+            i = 255 & (e[2] ? _t(i) : xt(i, 0, 255)),
+            s = 255 & (e[4] ? _t(s) : xt(s, 0, 255)),
+            n = 255 & (e[6] ? _t(n) : xt(n, 0, 255)),
+            { r: i, g: s, b: n, a: o };
+        }
+      }(t)
+      : Ft(t);
+  }
+  class Kt {
+    constructor(t) {
+      if (t instanceof Kt) return t;
+      const e = typeof t;
+      let i;
+      var s, n, o;
+      "object" === e ? i = Xt(t) : "string" === e && (o = (s = t).length,
+        "#" === s[0]
+        && (4 === o || 5 === o
+          ? n = {
+            r: 255 & 17 * Mt[s[1]],
+            g: 255 & 17 * Mt[s[2]],
+            b: 255 & 17 * Mt[s[3]],
+            a: 5 === o ? 17 * Mt[s[4]] : 255,
+          }
+          : 7 !== o && 9 !== o
+            || (n = {
+              r: Mt[s[1]] << 4 | Mt[s[2]],
+              g: Mt[s[3]] << 4 | Mt[s[4]],
+              b: Mt[s[5]] << 4 | Mt[s[6]],
+              a: 9 === o ? Mt[s[7]] << 4 | Mt[s[8]] : 255,
+            })),
+        i = n || Wt(t) || qt(t)),
+        this._rgb = i,
+        this._valid = !!i;
+    }
+    get valid() {
+      return this._valid;
+    }
+    get rgb() {
+      var t = Ut(this._rgb);
+      return t && (t.a = vt(t.a)), t;
+    }
+    set rgb(t) {
+      this._rgb = Xt(t);
+    }
+    rgbString() {
+      return this._valid
+        ? (t = this._rgb) && (t.a < 255 ? `rgba(${t.r}, ${t.g}, ${t.b}, ${vt(t.a)})` : `rgb(${t.r}, ${t.g}, ${t.b})`)
+        : void 0;
+      var t;
+    }
+    hexString() {
+      return this._valid ? Ot(this._rgb) : void 0;
+    }
+    hslString() {
+      return this._valid
+        ? function(t) {
+          if (!t) return;
+          const e = Et(t), i = e[0], s = wt(e[1]), n = wt(e[2]);
+          return t.a < 255 ? `hsla(${i}, ${s}%, ${n}%, ${vt(t.a)})` : `hsl(${i}, ${s}%, ${n}%)`;
+        }(this._rgb)
+        : void 0;
+    }
+    mix(t, e) {
+      if (t) {
+        const i = this.rgb, s = t.rgb;
+        let n;
+        const o = e === n ? .5 : e,
+          a = 2 * o - 1,
+          r = i.a - s.a,
+          l = ((a * r == -1 ? a : (a + r) / (1 + a * r)) + 1) / 2;
+        n = 1 - l,
+          i.r = 255 & l * i.r + n * s.r + .5,
+          i.g = 255 & l * i.g + n * s.g + .5,
+          i.b = 255 & l * i.b + n * s.b + .5,
+          i.a = o * i.a + (1 - o) * s.a,
+          this.rgb = i;
+      }
+      return this;
+    }
+    interpolate(t, e) {
+      return t && (this._rgb = function(t, e, i) {
+        const s = $t(vt(t.r)), n = $t(vt(t.g)), o = $t(vt(t.b));
+        return {
+          r: yt(Ht(s + i * ($t(vt(e.r)) - s))),
+          g: yt(Ht(n + i * ($t(vt(e.g)) - n))),
+          b: yt(Ht(o + i * ($t(vt(e.b)) - o))),
+          a: t.a + i * (e.a - t.a),
+        };
+      }(this._rgb, t._rgb, e)),
+        this;
+    }
+    clone() {
+      return new Kt(this.rgb);
+    }
+    alpha(t) {
+      return this._rgb.a = yt(t), this;
+    }
+    clearer(t) {
+      return this._rgb.a *= 1 - t, this;
+    }
+    greyscale() {
+      const t = this._rgb, e = bt(.3 * t.r + .59 * t.g + .11 * t.b);
+      return t.r = t.g = t.b = e, this;
+    }
+    opaquer(t) {
+      return this._rgb.a *= 1 + t, this;
+    }
+    negate() {
+      const t = this._rgb;
+      return t.r = 255 - t.r, t.g = 255 - t.g, t.b = 255 - t.b, this;
+    }
+    lighten(t) {
+      return Yt(this._rgb, 2, t), this;
+    }
+    darken(t) {
+      return Yt(this._rgb, 2, -t), this;
+    }
+    saturate(t) {
+      return Yt(this._rgb, 1, t), this;
+    }
+    desaturate(t) {
+      return Yt(this._rgb, 1, -t), this;
+    }
+    rotate(t) {
+      return function(t, e) {
+        var i = Et(t);
+        i[0] = zt(i[0] + e), i = It(i), t.r = i[0], t.g = i[1], t.b = i[2];
+      }(this._rgb, t),
+        this;
+    }
+  }
+  function Gt(t) {
+    return new Kt(t);
+  }
+  function Zt(t) {
+    if (t && "object" == typeof t) {
+      const e = t.toString();
+      return "[object CanvasPattern]" === e || "[object CanvasGradient]" === e;
+    }
+    return !1;
+  }
+  function Jt(t) {
+    return Zt(t) ? t : Gt(t);
+  }
+  function Qt(t) {
+    return Zt(t) ? t : Gt(t).saturate(.5).darken(.1).hexString();
+  }
+  const te = Object.create(null), ee = Object.create(null);
+  function ie(t, e) {
+    if (!e) return t;
+    const i = e.split(".");
+    for (let e = 0, s = i.length; e < s; ++e) {
+      const s = i[e];
+      t = t[s] || (t[s] = Object.create(null));
+    }
+    return t;
+  }
+  function se(t, e, i) {
+    return "string" == typeof e ? m(ie(t, e), i) : m(ie(t, ""), e);
+  }
+  var ne = new class {
+    constructor(t) {
+      this.animation = void 0,
+        this.backgroundColor = "rgba(0,0,0,0.1)",
+        this.borderColor = "rgba(0,0,0,0.1)",
+        this.color = "#666",
+        this.datasets = {},
+        this.devicePixelRatio = t => t.chart.platform.getDevicePixelRatio(),
+        this.elements = {},
+        this.events = ["mousemove", "mouseout", "click", "touchstart", "touchmove"],
+        this.font = {
+          family: "'Helvetica Neue', 'Helvetica', 'Arial', sans-serif",
+          size: 12,
+          style: "normal",
+          lineHeight: 1.2,
+          weight: null,
+        },
+        this.hover = {},
+        this.hoverBackgroundColor = (t, e) => Qt(e.backgroundColor),
+        this.hoverBorderColor = (t, e) => Qt(e.borderColor),
+        this.hoverColor = (t, e) => Qt(e.color),
+        this.indexAxis = "x",
+        this.interaction = { mode: "nearest", intersect: !0, includeInvisible: !1 },
+        this.maintainAspectRatio = !0,
+        this.onHover = null,
+        this.onClick = null,
+        this.parsing = !0,
+        this.plugins = {},
+        this.responsive = !0,
+        this.scale = void 0,
+        this.scales = {},
+        this.showLine = !0,
+        this.drawActiveElementsOnTop = !0,
+        this.describe(t);
+    }
+    set(t, e) {
+      return se(this, t, e);
+    }
+    get(t) {
+      return ie(this, t);
+    }
+    describe(t, e) {
+      return se(ee, t, e);
+    }
+    override(t, e) {
+      return se(te, t, e);
+    }
+    route(t, e, i, s) {
+      const o = ie(this, t), a = ie(this, i), l = "_" + e;
+      Object.defineProperties(o, {
+        [l]: { value: o[e], writable: !0 },
+        [e]: {
+          enumerable: !0,
+          get() {
+            const t = this[l], e = a[s];
+            return n(t) ? Object.assign({}, e, t) : r(t, e);
+          },
+          set(t) {
+            this[l] = t;
+          },
+        },
+      });
+    }
+  }({
+    _scriptable: t => !t.startsWith("on"),
+    _indexable: t => "events" !== t,
+    hover: { _fallback: "interaction" },
+    interaction: { _scriptable: !1, _indexable: !1 },
+  });
+  function oe() {
+    return "undefined" != typeof window && "undefined" != typeof document;
+  }
+  function ae(t) {
+    let e = t.parentNode;
+    return e && "[object ShadowRoot]" === e.toString() && (e = e.host), e;
+  }
+  function re(t, e, i) {
+    let s;
+    return "string" == typeof t
+      ? (s = parseInt(t, 10), -1 !== t.indexOf("%") && (s = s / 100 * e.parentNode[i]))
+      : s = t,
+      s;
+  }
+  const le = t => window.getComputedStyle(t, null);
+  function he(t, e) {
+    return le(t).getPropertyValue(e);
+  }
+  const ce = ["top", "right", "bottom", "left"];
+  function de(t, e, i) {
+    const s = {};
+    i = i ? "-" + i : "";
+    for (let n = 0; n < 4; n++) {
+      const o = ce[n];
+      s[o] = parseFloat(t[e + "-" + o + i]) || 0;
+    }
+    return s.width = s.left + s.right, s.height = s.top + s.bottom, s;
+  }
+  function ue(t, e) {
+    if ("native" in t) return t;
+    const { canvas: i, currentDevicePixelRatio: s } = e,
+      n = le(i),
+      o = "border-box" === n.boxSizing,
+      a = de(n, "padding"),
+      r = de(n, "border", "width"),
+      { x: l, y: h, box: c } = function(t, e) {
+        const i = t.touches, s = i && i.length ? i[0] : t, { offsetX: n, offsetY: o } = s;
+        let a, r, l = !1;
+        if (((t, e, i) => (t > 0 || e > 0) && (!i || !i.shadowRoot))(n, o, t.target)) a = n, r = o;
+        else {
+          const t = e.getBoundingClientRect();
+          a = s.clientX - t.left, r = s.clientY - t.top, l = !0;
+        }
+        return { x: a, y: r, box: l };
+      }(t, i),
+      d = a.left + (c && r.left),
+      u = a.top + (c && r.top);
+    let { width: f, height: g } = e;
+    return o && (f -= a.width + r.width, g -= a.height + r.height),
+      { x: Math.round((l - d) / f * i.width / s), y: Math.round((h - u) / g * i.height / s) };
+  }
+  const fe = t => Math.round(10 * t) / 10;
+  function ge(t, e, i, s) {
+    const n = le(t),
+      o = de(n, "margin"),
+      a = re(n.maxWidth, t, "clientWidth") || A,
+      r = re(n.maxHeight, t, "clientHeight") || A,
+      l = function(t, e, i) {
+        let s, n;
+        if (void 0 === e || void 0 === i) {
+          const o = ae(t);
+          if (o) {
+            const t = o.getBoundingClientRect(), a = le(o), r = de(a, "border", "width"), l = de(a, "padding");
+            e = t.width - l.width - r.width,
+              i = t.height - l.height - r.height,
+              s = re(a.maxWidth, o, "clientWidth"),
+              n = re(a.maxHeight, o, "clientHeight");
+          } else e = t.clientWidth, i = t.clientHeight;
+        }
+        return { width: e, height: i, maxWidth: s || A, maxHeight: n || A };
+      }(t, e, i);
+    let { width: h, height: c } = l;
+    if ("content-box" === n.boxSizing) {
+      const t = de(n, "border", "width"), e = de(n, "padding");
+      h -= e.width + t.width, c -= e.height + t.height;
+    }
+    return h = Math.max(0, h - o.width),
+      c = Math.max(0, s ? Math.floor(h / s) : c - o.height),
+      h = fe(Math.min(h, a, l.maxWidth)),
+      c = fe(Math.min(c, r, l.maxHeight)),
+      h && !c && (c = fe(h / 2)),
+      { width: h, height: c };
+  }
+  function pe(t, e, i) {
+    const s = e || 1, n = Math.floor(t.height * s), o = Math.floor(t.width * s);
+    t.height = n / s, t.width = o / s;
+    const a = t.canvas;
+    return a.style && (i || !a.style.height && !a.style.width)
+      && (a.style.height = `${t.height}px`, a.style.width = `${t.width}px`),
+      (t.currentDevicePixelRatio !== s || a.height !== n || a.width !== o)
+      && (t.currentDevicePixelRatio = s, a.height = n, a.width = o, t.ctx.setTransform(s, 0, 0, s, 0, 0), !0);
+  }
+  const me = function() {
+    let t = !1;
+    try {
+      const e = {
+        get passive() {
+          return t = !0, !1;
+        },
+      };
+      window.addEventListener("test", null, e), window.removeEventListener("test", null, e);
+    } catch (t) {}
+    return t;
+  }();
+  function be(t, e) {
+    const i = he(t, e), s = i && i.match(/^(\d+)(\.\d+)?px$/);
+    return s ? +s[1] : void 0;
+  }
+  function xe(t) {
+    return !t || i(t.size) || i(t.family)
+      ? null
+      : (t.style ? t.style + " " : "") + (t.weight ? t.weight + " " : "") + t.size + "px " + t.family;
+  }
+  function _e(t, e, i, s, n) {
+    let o = e[n];
+    return o || (o = e[n] = t.measureText(n).width, i.push(n)), o > s && (s = o), s;
+  }
+  function ye(t, e, i, n) {
+    let o = (n = n || {}).data = n.data || {}, a = n.garbageCollect = n.garbageCollect || [];
+    n.font !== e && (o = n.data = {}, a = n.garbageCollect = [], n.font = e), t.save(), t.font = e;
+    let r = 0;
+    const l = i.length;
+    let h, c, d, u, f;
+    for (h = 0; h < l; h++) {
+      if (u = i[h], null != u && !0 !== s(u)) r = _e(t, o, a, r, u);
+      else if (s(u)) for (c = 0, d = u.length; c < d; c++) f = u[c], null == f || s(f) || (r = _e(t, o, a, r, f));
+    }
+    t.restore();
+    const g = a.length / 2;
+    if (g > i.length) {
+      for (h = 0; h < g; h++) delete o[a[h]];
+      a.splice(0, g);
+    }
+    return r;
+  }
+  function ve(t, e, i) {
+    const s = t.currentDevicePixelRatio, n = 0 !== i ? Math.max(i / 2, .5) : 0;
+    return Math.round((e - n) * s) / s + n;
+  }
+  function we(t, e) {
+    (e = e || t.getContext("2d")).save(), e.resetTransform(), e.clearRect(0, 0, t.width, t.height), e.restore();
+  }
+  function Me(t, e, i, s) {
+    ke(t, e, i, s, null);
+  }
+  function ke(t, e, i, s, n) {
+    let o, a, r, l, h, c;
+    const d = e.pointStyle, u = e.rotation, f = e.radius;
+    let g = (u || 0) * T;
+    if (
+      d && "object" == typeof d
+      && (o = d.toString(), "[object HTMLImageElement]" === o || "[object HTMLCanvasElement]" === o)
+    ) {
+      return t.save(),
+        t.translate(i, s),
+        t.rotate(g),
+        t.drawImage(d, -d.width / 2, -d.height / 2, d.width, d.height),
+        void t.restore();
+    }
+    if (!(isNaN(f) || f <= 0)) {
+      switch (t.beginPath(), d) {
+        default:
+          n ? t.ellipse(i, s, n / 2, f, 0, 0, O) : t.arc(i, s, f, 0, O), t.closePath();
+          break;
+        case "triangle":
+          t.moveTo(i + Math.sin(g) * f, s - Math.cos(g) * f),
+            g += R,
+            t.lineTo(i + Math.sin(g) * f, s - Math.cos(g) * f),
+            g += R,
+            t.lineTo(i + Math.sin(g) * f, s - Math.cos(g) * f),
+            t.closePath();
+          break;
+        case "rectRounded":
+          h = .516 * f,
+            l = f - h,
+            a = Math.cos(g + E) * l,
+            r = Math.sin(g + E) * l,
+            t.arc(i - a, s - r, h, g - D, g - L),
+            t.arc(i + r, s - a, h, g - L, g),
+            t.arc(i + a, s + r, h, g, g + L),
+            t.arc(i - r, s + a, h, g + L, g + D),
+            t.closePath();
+          break;
+        case "rect":
+          if (!u) {
+            l = Math.SQRT1_2 * f, c = n ? n / 2 : l, t.rect(i - c, s - l, 2 * c, 2 * l);
+            break;
+          }
+          g += E;
+        case "rectRot":
+          a = Math.cos(g) * f,
+            r = Math.sin(g) * f,
+            t.moveTo(i - a, s - r),
+            t.lineTo(i + r, s - a),
+            t.lineTo(i + a, s + r),
+            t.lineTo(i - r, s + a),
+            t.closePath();
+          break;
+        case "crossRot":
+          g += E;
+        case "cross":
+          a = Math.cos(g) * f,
+            r = Math.sin(g) * f,
+            t.moveTo(i - a, s - r),
+            t.lineTo(i + a, s + r),
+            t.moveTo(i + r, s - a),
+            t.lineTo(i - r, s + a);
+          break;
+        case "star":
+          a = Math.cos(g) * f,
+            r = Math.sin(g) * f,
+            t.moveTo(i - a, s - r),
+            t.lineTo(i + a, s + r),
+            t.moveTo(i + r, s - a),
+            t.lineTo(i - r, s + a),
+            g += E,
+            a = Math.cos(g) * f,
+            r = Math.sin(g) * f,
+            t.moveTo(i - a, s - r),
+            t.lineTo(i + a, s + r),
+            t.moveTo(i + r, s - a),
+            t.lineTo(i - r, s + a);
+          break;
+        case "line":
+          a = n ? n / 2 : Math.cos(g) * f, r = Math.sin(g) * f, t.moveTo(i - a, s - r), t.lineTo(i + a, s + r);
+          break;
+        case "dash":
+          t.moveTo(i, s), t.lineTo(i + Math.cos(g) * f, s + Math.sin(g) * f);
+      }
+      t.fill(), e.borderWidth > 0 && t.stroke();
+    }
+  }
+  function Se(t, e, i) {
+    return i = i || .5, !e || t && t.x > e.left - i && t.x < e.right + i && t.y > e.top - i && t.y < e.bottom + i;
+  }
+  function Pe(t, e) {
+    t.save(), t.beginPath(), t.rect(e.left, e.top, e.right - e.left, e.bottom - e.top), t.clip();
+  }
+  function De(t) {
+    t.restore();
+  }
+  function Oe(t, e, i, s, n) {
+    if (!e) return t.lineTo(i.x, i.y);
+    if ("middle" === n) {
+      const s = (e.x + i.x) / 2;
+      t.lineTo(s, e.y), t.lineTo(s, i.y);
+    } else "after" === n != !!s ? t.lineTo(e.x, i.y) : t.lineTo(i.x, e.y);
+    t.lineTo(i.x, i.y);
+  }
+  function Ce(t, e, i, s) {
+    if (!e) return t.lineTo(i.x, i.y);
+    t.bezierCurveTo(s ? e.cp1x : e.cp2x, s ? e.cp1y : e.cp2y, s ? i.cp2x : i.cp1x, s ? i.cp2y : i.cp1y, i.x, i.y);
+  }
+  function Ae(t, e, n, o, a, r = {}) {
+    const l = s(e) ? e : [e], h = r.strokeWidth > 0 && "" !== r.strokeColor;
+    let c, d;
+    for (
+      t.save(),
+        t.font = a.string,
+        function(t, e) {
+          e.translation && t.translate(e.translation[0], e.translation[1]);
+          i(e.rotation) || t.rotate(e.rotation);
+          e.color && (t.fillStyle = e.color);
+          e.textAlign && (t.textAlign = e.textAlign);
+          e.textBaseline && (t.textBaseline = e.textBaseline);
+        }(t, r),
+        c = 0;
+      c < l.length;
+      ++c
+    ) {
+      d = l[c],
+        h
+        && (r.strokeColor && (t.strokeStyle = r.strokeColor),
+          i(r.strokeWidth) || (t.lineWidth = r.strokeWidth),
+          t.strokeText(d, n, o, r.maxWidth)),
+        t.fillText(d, n, o, r.maxWidth),
+        Te(t, n, o, d, r),
+        o += a.lineHeight;
+    }
+    t.restore();
+  }
+  function Te(t, e, i, s, n) {
+    if (n.strikethrough || n.underline) {
+      const o = t.measureText(s),
+        a = e - o.actualBoundingBoxLeft,
+        r = e + o.actualBoundingBoxRight,
+        l = i - o.actualBoundingBoxAscent,
+        h = i + o.actualBoundingBoxDescent,
+        c = n.strikethrough ? (l + h) / 2 : h;
+      t.strokeStyle = t.fillStyle,
+        t.beginPath(),
+        t.lineWidth = n.decorationWidth || 2,
+        t.moveTo(a, c),
+        t.lineTo(r, c),
+        t.stroke();
+    }
+  }
+  function Le(t, e) {
+    const { x: i, y: s, w: n, h: o, radius: a } = e;
+    t.arc(i + a.topLeft, s + a.topLeft, a.topLeft, -L, D, !0),
+      t.lineTo(i, s + o - a.bottomLeft),
+      t.arc(i + a.bottomLeft, s + o - a.bottomLeft, a.bottomLeft, D, L, !0),
+      t.lineTo(i + n - a.bottomRight, s + o),
+      t.arc(i + n - a.bottomRight, s + o - a.bottomRight, a.bottomRight, L, 0, !0),
+      t.lineTo(i + n, s + a.topRight),
+      t.arc(i + n - a.topRight, s + a.topRight, a.topRight, 0, -L, !0),
+      t.lineTo(i + a.topLeft, s);
+  }
+  function Ee(t, e = [""], i = t, s, n = (() => t[0])) {
+    M(s) || (s = $e("_fallback", t));
+    const o = {
+      [Symbol.toStringTag]: "Object",
+      _cacheable: !0,
+      _scopes: t,
+      _rootScopes: i,
+      _fallback: s,
+      _getTarget: n,
+      override: n => Ee([n, ...t], e, i, s),
+    };
+    return new Proxy(o, {
+      deleteProperty: (e, i) => (delete e[i], delete e._keys, delete t[0][i], !0),
+      get: (i, s) =>
+        Ve(i, s, () =>
+          function(t, e, i, s) {
+            let n;
+            for (const o of e) if (n = $e(ze(o, t), i), M(n)) return Fe(t, n) ? je(i, s, t, n) : n;
+          }(s, e, t, i)),
+      getOwnPropertyDescriptor: (t, e) => Reflect.getOwnPropertyDescriptor(t._scopes[0], e),
+      getPrototypeOf: () => Reflect.getPrototypeOf(t[0]),
+      has: (t, e) => Ye(t).includes(e),
+      ownKeys: t => Ye(t),
+      set(t, e, i) {
+        const s = t._storage || (t._storage = n());
+        return t[e] = s[e] = i, delete t._keys, !0;
+      },
+    });
+  }
+  function Re(t, e, i, o) {
+    const a = {
+      _cacheable: !1,
+      _proxy: t,
+      _context: e,
+      _subProxy: i,
+      _stack: new Set(),
+      _descriptors: Ie(t, o),
+      setContext: e => Re(t, e, i, o),
+      override: s => Re(t.override(s), e, i, o),
+    };
+    return new Proxy(a, {
+      deleteProperty: (e, i) => (delete e[i], delete t[i], !0),
+      get: (t, e, i) =>
+        Ve(t, e, () =>
+          function(t, e, i) {
+            const { _proxy: o, _context: a, _subProxy: r, _descriptors: l } = t;
+            let h = o[e];
+            k(h) && l.isScriptable(e) && (h = function(t, e, i, s) {
+              const { _proxy: n, _context: o, _subProxy: a, _stack: r } = i;
+              if (r.has(t)) throw new Error("Recursion detected: " + Array.from(r).join("->") + "->" + t);
+              r.add(t), e = e(o, a || s), r.delete(t), Fe(t, e) && (e = je(n._scopes, n, t, e));
+              return e;
+            }(e, h, t, i));
+            s(h) && h.length && (h = function(t, e, i, s) {
+              const { _proxy: o, _context: a, _subProxy: r, _descriptors: l } = i;
+              if (M(a.index) && s(t)) e = e[a.index % e.length];
+              else if (n(e[0])) {
+                const i = e, s = o._scopes.filter(t => t !== i);
+                e = [];
+                for (const n of i) {
+                  const i = je(s, o, t, n);
+                  e.push(Re(i, a, r && r[t], l));
+                }
+              }
+              return e;
+            }(e, h, t, l.isIndexable));
+            Fe(e, h) && (h = Re(h, a, r && r[e], l));
+            return h;
+          }(t, e, i)),
+      getOwnPropertyDescriptor: (e, i) =>
+        e._descriptors.allKeys
+          ? Reflect.has(t, i) ? { enumerable: !0, configurable: !0 } : void 0
+          : Reflect.getOwnPropertyDescriptor(t, i),
+      getPrototypeOf: () => Reflect.getPrototypeOf(t),
+      has: (e, i) => Reflect.has(t, i),
+      ownKeys: () => Reflect.ownKeys(t),
+      set: (e, i, s) => (t[i] = s, delete e[i], !0),
+    });
+  }
+  function Ie(t, e = { scriptable: !0, indexable: !0 }) {
+    const { _scriptable: i = e.scriptable, _indexable: s = e.indexable, _allKeys: n = e.allKeys } = t;
+    return {
+      allKeys: n,
+      scriptable: i,
+      indexable: s,
+      isScriptable: k(i) ? i : () => i,
+      isIndexable: k(s) ? s : () => s,
+    };
+  }
+  const ze = (t, e) => t ? t + w(e) : e,
+    Fe = (t, e) => n(e) && "adapters" !== t && (null === Object.getPrototypeOf(e) || e.constructor === Object);
+  function Ve(t, e, i) {
+    if (Object.prototype.hasOwnProperty.call(t, e)) return t[e];
+    const s = i();
+    return t[e] = s, s;
+  }
+  function Be(t, e, i) {
+    return k(t) ? t(e, i) : t;
+  }
+  const Ne = (t, e) => !0 === t ? e : "string" == typeof t ? y(e, t) : void 0;
+  function We(t, e, i, s, n) {
+    for (const o of e) {
+      const e = Ne(i, o);
+      if (e) {
+        t.add(e);
+        const o = Be(e._fallback, i, n);
+        if (M(o) && o !== i && o !== s) return o;
+      } else if (!1 === e && M(s) && i !== s) return null;
+    }
+    return !1;
+  }
+  function je(t, e, i, o) {
+    const a = e._rootScopes, r = Be(e._fallback, i, o), l = [...t, ...a], h = new Set();
+    h.add(o);
+    let c = He(h, l, i, r || i, o);
+    return null !== c
+      && ((!M(r) || r === i || (c = He(h, l, r, c, o), null !== c))
+        && Ee(Array.from(h), [""], a, r, () =>
+          function(t, e, i) {
+            const o = t._getTarget();
+            e in o || (o[e] = {});
+            const a = o[e];
+            if (s(a) && n(i)) return i;
+            return a;
+          }(e, i, o)));
+  }
+  function He(t, e, i, s, n) {
+    for (; i;) i = We(t, e, i, s, n);
+    return i;
+  }
+  function $e(t, e) {
+    for (const i of e) {
+      if (!i) continue;
+      const e = i[t];
+      if (M(e)) return e;
+    }
+  }
+  function Ye(t) {
+    let e = t._keys;
+    return e || (e = t._keys = function(t) {
+      const e = new Set();
+      for (const i of t) for (const t of Object.keys(i).filter(t => !t.startsWith("_"))) e.add(t);
+      return Array.from(e);
+    }(t._scopes)),
+      e;
+  }
+  function Ue(t, e, i, s) {
+    const { iScale: n } = t, { key: o = "r" } = this._parsing, a = new Array(s);
+    let r, l, h, c;
+    for (r = 0, l = s; r < l; ++r) h = r + i, c = e[h], a[r] = { r: n.parse(y(c, o), h) };
+    return a;
+  }
+  const Xe = Number.EPSILON || 1e-14,
+    qe = (t, e) => e < t.length && !t[e].skip && t[e],
+    Ke = t => "x" === t ? "y" : "x";
+  function Ge(t, e, i, s) {
+    const n = t.skip ? e : t, o = e, a = i.skip ? e : i, r = X(o, n), l = X(a, o);
+    let h = r / (r + l), c = l / (r + l);
+    h = isNaN(h) ? 0 : h, c = isNaN(c) ? 0 : c;
+    const d = s * h, u = s * c;
+    return {
+      previous: { x: o.x - d * (a.x - n.x), y: o.y - d * (a.y - n.y) },
+      next: { x: o.x + u * (a.x - n.x), y: o.y + u * (a.y - n.y) },
+    };
+  }
+  function Ze(t, e = "x") {
+    const i = Ke(e), s = t.length, n = Array(s).fill(0), o = Array(s);
+    let a, r, l, h = qe(t, 0);
+    for (a = 0; a < s; ++a) {
+      if (r = l, l = h, h = qe(t, a + 1), l) {
+        if (h) {
+          const t = h[e] - l[e];
+          n[a] = 0 !== t ? (h[i] - l[i]) / t : 0;
+        }
+        o[a] = r ? h ? z(n[a - 1]) !== z(n[a]) ? 0 : (n[a - 1] + n[a]) / 2 : n[a - 1] : n[a];
+      }
+    }
+    !function(t, e, i) {
+      const s = t.length;
+      let n, o, a, r, l, h = qe(t, 0);
+      for (let c = 0; c < s - 1; ++c) {
+        l = h,
+          h = qe(t, c + 1),
+          l && h && (N(e[c], 0, Xe)
+            ? i[c] = i[c + 1] = 0
+            : (n = i[c] / e[c],
+              o = i[c + 1] / e[c],
+              r = Math.pow(n, 2) + Math.pow(o, 2),
+              r <= 9 || (a = 3 / Math.sqrt(r), i[c] = n * a * e[c], i[c + 1] = o * a * e[c])));
+      }
+    }(t, n, o),
+      function(t, e, i = "x") {
+        const s = Ke(i), n = t.length;
+        let o, a, r, l = qe(t, 0);
+        for (let h = 0; h < n; ++h) {
+          if (a = r, r = l, l = qe(t, h + 1), !r) continue;
+          const n = r[i], c = r[s];
+          a && (o = (n - a[i]) / 3, r[`cp1${i}`] = n - o, r[`cp1${s}`] = c - o * e[h]),
+            l && (o = (l[i] - n) / 3, r[`cp2${i}`] = n + o, r[`cp2${s}`] = c + o * e[h]);
+        }
+      }(t, o, e);
+  }
+  function Je(t, e, i) {
+    return Math.max(Math.min(t, i), e);
+  }
+  function Qe(t, e, i, s, n) {
+    let o, a, r, l;
+    if (e.spanGaps && (t = t.filter(t => !t.skip)), "monotone" === e.cubicInterpolationMode) Ze(t, n);
+    else {
+      let i = s ? t[t.length - 1] : t[0];
+      for (o = 0, a = t.length; o < a; ++o) {
+        r = t[o],
+          l = Ge(i, r, t[Math.min(o + 1, a - (s ? 0 : 1)) % a], e.tension),
+          r.cp1x = l.previous.x,
+          r.cp1y = l.previous.y,
+          r.cp2x = l.next.x,
+          r.cp2y = l.next.y,
+          i = r;
+      }
+    }
+    e.capBezierPoints && function(t, e) {
+      let i, s, n, o, a, r = Se(t[0], e);
+      for (i = 0, s = t.length; i < s; ++i) {
+        a = o,
+          o = r,
+          r = i < s - 1 && Se(t[i + 1], e),
+          o
+          && (n = t[i],
+            a && (n.cp1x = Je(n.cp1x, e.left, e.right), n.cp1y = Je(n.cp1y, e.top, e.bottom)),
+            r && (n.cp2x = Je(n.cp2x, e.left, e.right), n.cp2y = Je(n.cp2y, e.top, e.bottom)));
+      }
+    }(t, i);
+  }
+  const ti = t => 0 === t || 1 === t,
+    ei = (t, e, i) => -Math.pow(2, 10 * (t -= 1)) * Math.sin((t - e) * O / i),
+    ii = (t, e, i) => Math.pow(2, -10 * t) * Math.sin((t - e) * O / i) + 1,
+    si = {
+      linear: t => t,
+      easeInQuad: t => t * t,
+      easeOutQuad: t => -t * (t - 2),
+      easeInOutQuad: t => (t /= .5) < 1 ? .5 * t * t : -.5 * (--t * (t - 2) - 1),
+      easeInCubic: t => t * t * t,
+      easeOutCubic: t => (t -= 1) * t * t + 1,
+      easeInOutCubic: t => (t /= .5) < 1 ? .5 * t * t * t : .5 * ((t -= 2) * t * t + 2),
+      easeInQuart: t => t * t * t * t,
+      easeOutQuart: t => -((t -= 1) * t * t * t - 1),
+      easeInOutQuart: t => (t /= .5) < 1 ? .5 * t * t * t * t : -.5 * ((t -= 2) * t * t * t - 2),
+      easeInQuint: t => t * t * t * t * t,
+      easeOutQuint: t => (t -= 1) * t * t * t * t + 1,
+      easeInOutQuint: t => (t /= .5) < 1 ? .5 * t * t * t * t * t : .5 * ((t -= 2) * t * t * t * t + 2),
+      easeInSine: t => 1 - Math.cos(t * L),
+      easeOutSine: t => Math.sin(t * L),
+      easeInOutSine: t => -.5 * (Math.cos(D * t) - 1),
+      easeInExpo: t => 0 === t ? 0 : Math.pow(2, 10 * (t - 1)),
+      easeOutExpo: t => 1 === t ? 1 : 1 - Math.pow(2, -10 * t),
+      easeInOutExpo: t =>
+        ti(t) ? t : t < .5 ? .5 * Math.pow(2, 10 * (2 * t - 1)) : .5 * (2 - Math.pow(2, -10 * (2 * t - 1))),
+      easeInCirc: t => t >= 1 ? t : -(Math.sqrt(1 - t * t) - 1),
+      easeOutCirc: t => Math.sqrt(1 - (t -= 1) * t),
+      easeInOutCirc: t => (t /= .5) < 1 ? -.5 * (Math.sqrt(1 - t * t) - 1) : .5 * (Math.sqrt(1 - (t -= 2) * t) + 1),
+      easeInElastic: t => ti(t) ? t : ei(t, .075, .3),
+      easeOutElastic: t => ti(t) ? t : ii(t, .075, .3),
+      easeInOutElastic(t) {
+        const e = .1125;
+        return ti(t) ? t : t < .5 ? .5 * ei(2 * t, e, .45) : .5 + .5 * ii(2 * t - 1, e, .45);
+      },
+      easeInBack(t) {
+        const e = 1.70158;
+        return t * t * ((e + 1) * t - e);
+      },
+      easeOutBack(t) {
+        const e = 1.70158;
+        return (t -= 1) * t * ((e + 1) * t + e) + 1;
+      },
+      easeInOutBack(t) {
+        let e = 1.70158;
+        return (t /= .5) < 1
+          ? t * t * ((1 + (e *= 1.525)) * t - e) * .5
+          : .5 * ((t -= 2) * t * ((1 + (e *= 1.525)) * t + e) + 2);
+      },
+      easeInBounce: t => 1 - si.easeOutBounce(1 - t),
+      easeOutBounce(t) {
+        const e = 7.5625, i = 2.75;
+        return t < 1 / i
+          ? e * t * t
+          : t < 2 / i
+          ? e * (t -= 1.5 / i) * t + .75
+          : t < 2.5 / i
+          ? e * (t -= 2.25 / i) * t + .9375
+          : e * (t -= 2.625 / i) * t + .984375;
+      },
+      easeInOutBounce: t => t < .5 ? .5 * si.easeInBounce(2 * t) : .5 * si.easeOutBounce(2 * t - 1) + .5,
+    };
+  function ni(t, e, i, s) {
+    return { x: t.x + i * (e.x - t.x), y: t.y + i * (e.y - t.y) };
+  }
+  function oi(t, e, i, s) {
+    return {
+      x: t.x + i * (e.x - t.x),
+      y: "middle" === s ? i < .5 ? t.y : e.y : "after" === s ? i < 1 ? t.y : e.y : i > 0 ? e.y : t.y,
+    };
+  }
+  function ai(t, e, i, s) {
+    const n = { x: t.cp2x, y: t.cp2y },
+      o = { x: e.cp1x, y: e.cp1y },
+      a = ni(t, n, i),
+      r = ni(n, o, i),
+      l = ni(o, e, i),
+      h = ni(a, r, i),
+      c = ni(r, l, i);
+    return ni(h, c, i);
+  }
+  const ri = new Map();
+  function li(t, e, i) {
+    return function(t, e) {
+      e = e || {};
+      const i = t + JSON.stringify(e);
+      let s = ri.get(i);
+      return s || (s = new Intl.NumberFormat(t, e), ri.set(i, s)), s;
+    }(e, i).format(t);
+  }
+  const hi = new RegExp(/^(normal|(\d+(?:\.\d+)?)(px|em|%)?)$/),
+    ci = new RegExp(/^(normal|italic|initial|inherit|unset|(oblique( -?[0-9]?[0-9]deg)?))$/);
+  function di(t, e) {
+    const i = ("" + t).match(hi);
+    if (!i || "normal" === i[1]) return 1.2 * e;
+    switch (t = +i[2], i[3]) {
+      case "px":
+        return t;
+      case "%":
+        t /= 100;
+    }
+    return e * t;
+  }
+  function ui(t, e) {
+    const i = {}, s = n(e), o = s ? Object.keys(e) : e, a = n(t) ? s ? i => r(t[i], t[e[i]]) : e => t[e] : () => t;
+    for (const t of o) i[t] = +a(t) || 0;
+    return i;
+  }
+  function fi(t) {
+    return ui(t, { top: "y", right: "x", bottom: "y", left: "x" });
+  }
+  function gi(t) {
+    return ui(t, ["topLeft", "topRight", "bottomLeft", "bottomRight"]);
+  }
+  function pi(t) {
+    const e = fi(t);
+    return e.width = e.left + e.right, e.height = e.top + e.bottom, e;
+  }
+  function mi(t, e) {
+    t = t || {}, e = e || ne.font;
+    let i = r(t.size, e.size);
+    "string" == typeof i && (i = parseInt(i, 10));
+    let s = r(t.style, e.style);
+    s && !("" + s).match(ci) && (console.warn("Invalid font style specified: \"" + s + "\""), s = "");
+    const n = {
+      family: r(t.family, e.family),
+      lineHeight: di(r(t.lineHeight, e.lineHeight), i),
+      size: i,
+      style: s,
+      weight: r(t.weight, e.weight),
+      string: "",
+    };
+    return n.string = xe(n), n;
+  }
+  function bi(t, e, i, n) {
+    let o, a, r, l = !0;
+    for (o = 0, a = t.length; o < a; ++o) {
+      if (
+        r = t[o],
+          void 0 !== r
+          && (void 0 !== e && "function" == typeof r && (r = r(e), l = !1),
+            void 0 !== i && s(r) && (r = r[i % r.length], l = !1),
+            void 0 !== r)
+      ) return n && !l && (n.cacheable = !1), r;
+    }
+  }
+  function xi(t, e, i) {
+    const { min: s, max: n } = t, o = h(e, (n - s) / 2), a = (t, e) => i && 0 === t ? 0 : t + e;
+    return { min: a(s, -Math.abs(o)), max: a(n, o) };
+  }
+  function _i(t, e) {
+    return Object.assign(Object.create(t), e);
+  }
+  function yi(t, e, i) {
+    return t
+      ? function(t, e) {
+        return {
+          x: i => t + t + e - i,
+          setWidth(t) {
+            e = t;
+          },
+          textAlign: t => "center" === t ? t : "right" === t ? "left" : "right",
+          xPlus: (t, e) => t - e,
+          leftForLtr: (t, e) => t - e,
+        };
+      }(e, i)
+      : { x: t => t, setWidth(t) {}, textAlign: t => t, xPlus: (t, e) => t + e, leftForLtr: (t, e) => t };
+  }
+  function vi(t, e) {
+    let i, s;
+    "ltr" !== e && "rtl" !== e
+      || (i = t.canvas.style,
+        s = [i.getPropertyValue("direction"), i.getPropertyPriority("direction")],
+        i.setProperty("direction", e, "important"),
+        t.prevTextDirection = s);
+  }
+  function wi(t, e) {
+    void 0 !== e && (delete t.prevTextDirection, t.canvas.style.setProperty("direction", e[0], e[1]));
+  }
+  function Mi(t) {
+    return "angle" === t
+      ? { between: G, compare: q, normalize: K }
+      : { between: Q, compare: (t, e) => t - e, normalize: t => t };
+  }
+  function ki({ start: t, end: e, count: i, loop: s, style: n }) {
+    return { start: t % i, end: e % i, loop: s && (e - t + 1) % i == 0, style: n };
+  }
+  function Si(t, e, i) {
+    if (!i) return [t];
+    const { property: s, start: n, end: o } = i,
+      a = e.length,
+      { compare: r, between: l, normalize: h } = Mi(s),
+      { start: c, end: d, loop: u, style: f } = function(t, e, i) {
+        const { property: s, start: n, end: o } = i, { between: a, normalize: r } = Mi(s), l = e.length;
+        let h, c, { start: d, end: u, loop: f } = t;
+        if (f) {
+          for (d += l, u += l, h = 0, c = l; h < c && a(r(e[d % l][s]), n, o); ++h) d--, u--;
+          d %= l, u %= l;
+        }
+        return u < d && (u += l), { start: d, end: u, loop: f, style: t.style };
+      }(t, e, i),
+      g = [];
+    let p, m, b, x = !1, _ = null;
+    const y = () => x || l(n, b, p) && 0 !== r(n, b), v = () => !x || 0 === r(o, p) || l(o, b, p);
+    for (let t = c, i = c; t <= d; ++t) {
+      m = e[t % a],
+        m.skip
+        || (p = h(m[s]),
+          p !== b
+          && (x = l(p, n, o),
+            null === _ && y() && (_ = 0 === r(p, n) ? t : i),
+            null !== _ && v() && (g.push(ki({ start: _, end: t, loop: u, count: a, style: f })), _ = null),
+            i = t,
+            b = p));
+    }
+    return null !== _ && g.push(ki({ start: _, end: d, loop: u, count: a, style: f })), g;
+  }
+  function Pi(t, e) {
+    const i = [], s = t.segments;
+    for (let n = 0; n < s.length; n++) {
+      const o = Si(s[n], t.points, e);
+      o.length && i.push(...o);
+    }
+    return i;
+  }
+  function Di(t, e) {
+    const i = t.points, s = t.options.spanGaps, n = i.length;
+    if (!n) return [];
+    const o = !!t._loop,
+      { start: a, end: r } = function(t, e, i, s) {
+        let n = 0, o = e - 1;
+        if (i && !s) for (; n < e && !t[n].skip;) n++;
+        for (; n < e && t[n].skip;) n++;
+        for (n %= e, i && (o += n); o > n && t[o % e].skip;) o--;
+        return o %= e, { start: n, end: o };
+      }(i, n, o, s);
+    if (!0 === s) return Oi(t, [{ start: a, end: r, loop: o }], i, e);
+    return Oi(
+      t,
+      function(t, e, i, s) {
+        const n = t.length, o = [];
+        let a, r = e, l = t[e];
+        for (a = e + 1; a <= i; ++a) {
+          const i = t[a % n];
+          i.skip || i.stop
+            ? l.skip || (s = !1, o.push({ start: e % n, end: (a - 1) % n, loop: s }), e = r = i.stop ? a : null)
+            : (r = a, l.skip && (e = a)), l = i;
+        }
+        return null !== r && o.push({ start: e % n, end: r % n, loop: s }), o;
+      }(i, a, r < a ? r + n : r, !!t._fullLoop && 0 === a && r === n - 1),
+      i,
+      e,
+    );
+  }
+  function Oi(t, e, i, s) {
+    return s && s.setContext && i
+      ? function(t, e, i, s) {
+        const n = t._chart.getContext(),
+          o = Ci(t.options),
+          { _datasetIndex: a, options: { spanGaps: r } } = t,
+          l = i.length,
+          h = [];
+        let c = o, d = e[0].start, u = d;
+        function f(t, e, s, n) {
+          const o = r ? -1 : 1;
+          if (t !== e) {
+            for (t += l; i[t % l].skip;) t -= o;
+            for (; i[e % l].skip;) e += o;
+            t % l != e % l && (h.push({ start: t % l, end: e % l, loop: s, style: n }), c = n, d = e % l);
+          }
+        }
+        for (const t of e) {
+          d = r ? d : t.start;
+          let e, o = i[d % l];
+          for (u = d + 1; u <= t.end; u++) {
+            const r = i[u % l];
+            e = Ci(
+              s.setContext(
+                _i(n, { type: "segment", p0: o, p1: r, p0DataIndex: (u - 1) % l, p1DataIndex: u % l, datasetIndex: a }),
+              ),
+            ),
+              Ai(e, c) && f(d, u - 1, t.loop, c),
+              o = r,
+              c = e;
+          }
+          d < u - 1 && f(d, u - 1, t.loop, c);
+        }
+        return h;
+      }(t, e, i, s)
+      : e;
+  }
+  function Ci(t) {
+    return {
+      backgroundColor: t.backgroundColor,
+      borderCapStyle: t.borderCapStyle,
+      borderDash: t.borderDash,
+      borderDashOffset: t.borderDashOffset,
+      borderJoinStyle: t.borderJoinStyle,
+      borderWidth: t.borderWidth,
+      borderColor: t.borderColor,
+    };
+  }
+  function Ai(t, e) {
+    return e && JSON.stringify(t) !== JSON.stringify(e);
+  }
+  var Ti = Object.freeze({
+    __proto__: null,
+    easingEffects: si,
+    isPatternOrGradient: Zt,
+    color: Jt,
+    getHoverColor: Qt,
+    noop: t,
+    uid: e,
+    isNullOrUndef: i,
+    isArray: s,
+    isObject: n,
+    isFinite: o,
+    finiteOrDefault: a,
+    valueOrDefault: r,
+    toPercentage: l,
+    toDimension: h,
+    callback: c,
+    each: d,
+    _elementsEqual: u,
+    clone: f,
+    _merger: p,
+    merge: m,
+    mergeIf: b,
+    _mergerIf: x,
+    _deprecated: function(t, e, i, s) {
+      void 0 !== e && console.warn(t + ": \"" + i + "\" is deprecated. Please use \"" + s + "\" instead");
+    },
+    resolveObjectKey: y,
+    _splitKey: v,
+    _capitalize: w,
+    defined: M,
+    isFunction: k,
+    setsEqual: S,
+    _isClickEvent: P,
+    toFontString: xe,
+    _measureText: _e,
+    _longestText: ye,
+    _alignPixel: ve,
+    clearCanvas: we,
+    drawPoint: Me,
+    drawPointLegend: ke,
+    _isPointInArea: Se,
+    clipArea: Pe,
+    unclipArea: De,
+    _steppedLineTo: Oe,
+    _bezierCurveTo: Ce,
+    renderText: Ae,
+    addRoundedRectPath: Le,
+    _lookup: tt,
+    _lookupByKey: et,
+    _rlookupByKey: it,
+    _filterBetween: st,
+    listenArrayEvents: ot,
+    unlistenArrayEvents: at,
+    _arrayUnique: rt,
+    _createResolver: Ee,
+    _attachContext: Re,
+    _descriptors: Ie,
+    _parseObjectDataRadialScale: Ue,
+    splineCurve: Ge,
+    splineCurveMonotone: Ze,
+    _updateBezierControlPoints: Qe,
+    _isDomSupported: oe,
+    _getParentNode: ae,
+    getStyle: he,
+    getRelativePosition: ue,
+    getMaximumSize: ge,
+    retinaScale: pe,
+    supportsEventListenerOptions: me,
+    readUsedSize: be,
+    fontString: function(t, e, i) {
+      return e + " " + t + "px " + i;
+    },
+    requestAnimFrame: lt,
+    throttled: ht,
+    debounce: ct,
+    _toLeftRightCenter: dt,
+    _alignStartEnd: ut,
+    _textX: ft,
+    _getStartAndCountOfVisiblePoints: gt,
+    _scaleRangesChanged: pt,
+    _pointInLine: ni,
+    _steppedInterpolation: oi,
+    _bezierInterpolation: ai,
+    formatNumber: li,
+    toLineHeight: di,
+    _readValueToProps: ui,
+    toTRBL: fi,
+    toTRBLCorners: gi,
+    toPadding: pi,
+    toFont: mi,
+    resolve: bi,
+    _addGrace: xi,
+    createContext: _i,
+    PI: D,
+    TAU: O,
+    PITAU: C,
+    INFINITY: A,
+    RAD_PER_DEG: T,
+    HALF_PI: L,
+    QUARTER_PI: E,
+    TWO_THIRDS_PI: R,
+    log10: I,
+    sign: z,
+    niceNum: F,
+    _factorize: V,
+    isNumber: B,
+    almostEquals: N,
+    almostWhole: W,
+    _setMinAndMaxByKey: j,
+    toRadians: H,
+    toDegrees: $,
+    _decimalPlaces: Y,
+    getAngleFromPoint: U,
+    distanceBetweenPoints: X,
+    _angleDiff: q,
+    _normalizeAngle: K,
+    _angleBetween: G,
+    _limitValue: Z,
+    _int16Range: J,
+    _isBetween: Q,
+    getRtlAdapter: yi,
+    overrideTextDirection: vi,
+    restoreTextDirection: wi,
+    _boundSegment: Si,
+    _boundSegments: Pi,
+    _computeSegments: Di,
+  });
+  function Li(t, e, i, s) {
+    const { controller: n, data: o, _sorted: a } = t, r = n._cachedMeta.iScale;
+    if (r && e === r.axis && "r" !== e && a && o.length) {
+      const t = r._reversePixels ? it : et;
+      if (!s) return t(o, e, i);
+      if (n._sharedOptions) {
+        const s = o[0], n = "function" == typeof s.getRange && s.getRange(e);
+        if (n) {
+          const s = t(o, e, i - n), a = t(o, e, i + n);
+          return { lo: s.lo, hi: a.hi };
+        }
+      }
+    }
+    return { lo: 0, hi: o.length - 1 };
+  }
+  function Ei(t, e, i, s, n) {
+    const o = t.getSortedVisibleDatasetMetas(), a = i[e];
+    for (let t = 0, i = o.length; t < i; ++t) {
+      const { index: i, data: r } = o[t], { lo: l, hi: h } = Li(o[t], e, a, n);
+      for (let t = l; t <= h; ++t) {
+        const e = r[t];
+        e.skip || s(e, i, t);
+      }
+    }
+  }
+  function Ri(t, e, i, s, n) {
+    const o = [];
+    if (!n && !t.isPointInArea(e)) return o;
+    return Ei(t, i, e, function(i, a, r) {
+      (n || Se(i, t.chartArea, 0)) && i.inRange(e.x, e.y, s) && o.push({ element: i, datasetIndex: a, index: r });
+    }, !0),
+      o;
+  }
+  function Ii(t, e, i, s, n, o) {
+    let a = [];
+    const r = function(t) {
+      const e = -1 !== t.indexOf("x"), i = -1 !== t.indexOf("y");
+      return function(t, s) {
+        const n = e ? Math.abs(t.x - s.x) : 0, o = i ? Math.abs(t.y - s.y) : 0;
+        return Math.sqrt(Math.pow(n, 2) + Math.pow(o, 2));
+      };
+    }(i);
+    let l = Number.POSITIVE_INFINITY;
+    return Ei(t, i, e, function(i, h, c) {
+      const d = i.inRange(e.x, e.y, n);
+      if (s && !d) return;
+      const u = i.getCenterPoint(n);
+      if (!(!!o || t.isPointInArea(u)) && !d) return;
+      const f = r(e, u);
+      f < l
+        ? (a = [{ element: i, datasetIndex: h, index: c }], l = f)
+        : f === l && a.push({ element: i, datasetIndex: h, index: c });
+    }),
+      a;
+  }
+  function zi(t, e, i, s, n, o) {
+    return o || t.isPointInArea(e)
+      ? "r" !== i || s ? Ii(t, e, i, s, n, o) : function(t, e, i, s) {
+        let n = [];
+        return Ei(t, i, e, function(t, i, o) {
+          const { startAngle: a, endAngle: r } = t.getProps(["startAngle", "endAngle"], s),
+            { angle: l } = U(t, { x: e.x, y: e.y });
+          G(l, a, r) && n.push({ element: t, datasetIndex: i, index: o });
+        }),
+          n;
+      }(t, e, i, n)
+      : [];
+  }
+  function Fi(t, e, i, s, n) {
+    const o = [], a = "x" === i ? "inXRange" : "inYRange";
+    let r = !1;
+    return Ei(t, i, e, (t, s, l) => {
+      t[a](e[i], n) && (o.push({ element: t, datasetIndex: s, index: l }), r = r || t.inRange(e.x, e.y, n));
+    }),
+      s && !r ? [] : o;
+  }
+  var Vi = {
+    evaluateInteractionItems: Ei,
+    modes: {
+      index(t, e, i, s) {
+        const n = ue(e, t),
+          o = i.axis || "x",
+          a = i.includeInvisible || !1,
+          r = i.intersect ? Ri(t, n, o, s, a) : zi(t, n, o, !1, s, a),
+          l = [];
+        return r.length
+          ? (t.getSortedVisibleDatasetMetas().forEach(t => {
+            const e = r[0].index, i = t.data[e];
+            i && !i.skip && l.push({ element: i, datasetIndex: t.index, index: e });
+          }),
+            l)
+          : [];
+      },
+      dataset(t, e, i, s) {
+        const n = ue(e, t), o = i.axis || "xy", a = i.includeInvisible || !1;
+        let r = i.intersect ? Ri(t, n, o, s, a) : zi(t, n, o, !1, s, a);
+        if (r.length > 0) {
+          const e = r[0].datasetIndex, i = t.getDatasetMeta(e).data;
+          r = [];
+          for (let t = 0; t < i.length; ++t) r.push({ element: i[t], datasetIndex: e, index: t });
+        }
+        return r;
+      },
+      point: (t, e, i, s) => Ri(t, ue(e, t), i.axis || "xy", s, i.includeInvisible || !1),
+      nearest(t, e, i, s) {
+        const n = ue(e, t), o = i.axis || "xy", a = i.includeInvisible || !1;
+        return zi(t, n, o, i.intersect, s, a);
+      },
+      x: (t, e, i, s) => Fi(t, ue(e, t), "x", i.intersect, s),
+      y: (t, e, i, s) => Fi(t, ue(e, t), "y", i.intersect, s),
+    },
+  };
+  const Bi = ["left", "top", "right", "bottom"];
+  function Ni(t, e) {
+    return t.filter(t => t.pos === e);
+  }
+  function Wi(t, e) {
+    return t.filter(t => -1 === Bi.indexOf(t.pos) && t.box.axis === e);
+  }
+  function ji(t, e) {
+    return t.sort((t, i) => {
+      const s = e ? i : t, n = e ? t : i;
+      return s.weight === n.weight ? s.index - n.index : s.weight - n.weight;
+    });
+  }
+  function Hi(t, e) {
+    const i = function(t) {
+        const e = {};
+        for (const i of t) {
+          const { stack: t, pos: s, stackWeight: n } = i;
+          if (!t || !Bi.includes(s)) continue;
+          const o = e[t] || (e[t] = { count: 0, placed: 0, weight: 0, size: 0 });
+          o.count++, o.weight += n;
+        }
+        return e;
+      }(t),
+      { vBoxMaxWidth: s, hBoxMaxHeight: n } = e;
+    let o, a, r;
+    for (o = 0, a = t.length; o < a; ++o) {
+      r = t[o];
+      const { fullSize: a } = r.box, l = i[r.stack], h = l && r.stackWeight / l.weight;
+      r.horizontal
+        ? (r.width = h ? h * s : a && e.availableWidth, r.height = n)
+        : (r.width = s, r.height = h ? h * n : a && e.availableHeight);
+    }
+    return i;
+  }
+  function $i(t, e, i, s) {
+    return Math.max(t[i], e[i]) + Math.max(t[s], e[s]);
+  }
+  function Yi(t, e) {
+    t.top = Math.max(t.top, e.top),
+      t.left = Math.max(t.left, e.left),
+      t.bottom = Math.max(t.bottom, e.bottom),
+      t.right = Math.max(t.right, e.right);
+  }
+  function Ui(t, e, i, s) {
+    const { pos: o, box: a } = i, r = t.maxPadding;
+    if (!n(o)) {
+      i.size && (t[o] -= i.size);
+      const e = s[i.stack] || { size: 0, count: 1 };
+      e.size = Math.max(e.size, i.horizontal ? a.height : a.width), i.size = e.size / e.count, t[o] += i.size;
+    }
+    a.getPadding && Yi(r, a.getPadding());
+    const l = Math.max(0, e.outerWidth - $i(r, t, "left", "right")),
+      h = Math.max(0, e.outerHeight - $i(r, t, "top", "bottom")),
+      c = l !== t.w,
+      d = h !== t.h;
+    return t.w = l, t.h = h, i.horizontal ? { same: c, other: d } : { same: d, other: c };
+  }
+  function Xi(t, e) {
+    const i = e.maxPadding;
+    function s(t) {
+      const s = { left: 0, top: 0, right: 0, bottom: 0 };
+      return t.forEach(t => {
+        s[t] = Math.max(e[t], i[t]);
+      }),
+        s;
+    }
+    return s(t ? ["left", "right"] : ["top", "bottom"]);
+  }
+  function qi(t, e, i, s) {
+    const n = [];
+    let o, a, r, l, h, c;
+    for (o = 0, a = t.length, h = 0; o < a; ++o) {
+      r = t[o], l = r.box, l.update(r.width || e.w, r.height || e.h, Xi(r.horizontal, e));
+      const { same: a, other: d } = Ui(e, i, r, s);
+      h |= a && n.length, c = c || d, l.fullSize || n.push(r);
+    }
+    return h && qi(n, e, i, s) || c;
+  }
+  function Ki(t, e, i, s, n) {
+    t.top = i, t.left = e, t.right = e + s, t.bottom = i + n, t.width = s, t.height = n;
+  }
+  function Gi(t, e, i, s) {
+    const n = i.padding;
+    let { x: o, y: a } = e;
+    for (const r of t) {
+      const t = r.box, l = s[r.stack] || { count: 1, placed: 0, weight: 1 }, h = r.stackWeight / l.weight || 1;
+      if (r.horizontal) {
+        const s = e.w * h, o = l.size || t.height;
+        M(l.start) && (a = l.start),
+          t.fullSize ? Ki(t, n.left, a, i.outerWidth - n.right - n.left, o) : Ki(t, e.left + l.placed, a, s, o),
+          l.start = a,
+          l.placed += s,
+          a = t.bottom;
+      } else {
+        const s = e.h * h, a = l.size || t.width;
+        M(l.start) && (o = l.start),
+          t.fullSize ? Ki(t, o, n.top, a, i.outerHeight - n.bottom - n.top) : Ki(t, o, e.top + l.placed, a, s),
+          l.start = o,
+          l.placed += s,
+          o = t.right;
+      }
+    }
+    e.x = o, e.y = a;
+  }
+  ne.set("layout", { autoPadding: !0, padding: { top: 0, right: 0, bottom: 0, left: 0 } });
+  var Zi = {
+    addBox(t, e) {
+      t.boxes || (t.boxes = []),
+        e.fullSize = e.fullSize || !1,
+        e.position = e.position || "top",
+        e.weight = e.weight || 0,
+        e._layers = e._layers || function() {
+          return [{
+            z: 0,
+            draw(t) {
+              e.draw(t);
+            },
+          }];
+        },
+        t.boxes.push(e);
+    },
+    removeBox(t, e) {
+      const i = t.boxes ? t.boxes.indexOf(e) : -1;
+      -1 !== i && t.boxes.splice(i, 1);
+    },
+    configure(t, e, i) {
+      e.fullSize = i.fullSize, e.position = i.position, e.weight = i.weight;
+    },
+    update(t, e, i, s) {
+      if (!t) return;
+      const n = pi(t.options.layout.padding),
+        o = Math.max(e - n.width, 0),
+        a = Math.max(i - n.height, 0),
+        r = function(t) {
+          const e = function(t) {
+              const e = [];
+              let i, s, n, o, a, r;
+              for (i = 0, s = (t || []).length; i < s; ++i) {
+                n = t[i],
+                  ({ position: o, options: { stack: a, stackWeight: r = 1 } } = n),
+                  e.push({
+                    index: i,
+                    box: n,
+                    pos: o,
+                    horizontal: n.isHorizontal(),
+                    weight: n.weight,
+                    stack: a && o + a,
+                    stackWeight: r,
+                  });
+              }
+              return e;
+            }(t),
+            i = ji(e.filter(t => t.box.fullSize), !0),
+            s = ji(Ni(e, "left"), !0),
+            n = ji(Ni(e, "right")),
+            o = ji(Ni(e, "top"), !0),
+            a = ji(Ni(e, "bottom")),
+            r = Wi(e, "x"),
+            l = Wi(e, "y");
+          return {
+            fullSize: i,
+            leftAndTop: s.concat(o),
+            rightAndBottom: n.concat(l).concat(a).concat(r),
+            chartArea: Ni(e, "chartArea"),
+            vertical: s.concat(n).concat(l),
+            horizontal: o.concat(a).concat(r),
+          };
+        }(t.boxes),
+        l = r.vertical,
+        h = r.horizontal;
+      d(t.boxes, t => {
+        "function" == typeof t.beforeLayout && t.beforeLayout();
+      });
+      const c = l.reduce((t, e) => e.box.options && !1 === e.box.options.display ? t : t + 1, 0) || 1,
+        u = Object.freeze({
+          outerWidth: e,
+          outerHeight: i,
+          padding: n,
+          availableWidth: o,
+          availableHeight: a,
+          vBoxMaxWidth: o / 2 / c,
+          hBoxMaxHeight: a / 2,
+        }),
+        f = Object.assign({}, n);
+      Yi(f, pi(s));
+      const g = Object.assign({ maxPadding: f, w: o, h: a, x: n.left, y: n.top }, n), p = Hi(l.concat(h), u);
+      qi(r.fullSize, g, u, p),
+        qi(l, g, u, p),
+        qi(h, g, u, p) && qi(l, g, u, p),
+        function(t) {
+          const e = t.maxPadding;
+          function i(i) {
+            const s = Math.max(e[i] - t[i], 0);
+            return t[i] += s, s;
+          }
+          t.y += i("top"), t.x += i("left"), i("right"), i("bottom");
+        }(g),
+        Gi(r.leftAndTop, g, u, p),
+        g.x += g.w,
+        g.y += g.h,
+        Gi(r.rightAndBottom, g, u, p),
+        t.chartArea = { left: g.left, top: g.top, right: g.left + g.w, bottom: g.top + g.h, height: g.h, width: g.w },
+        d(r.chartArea, e => {
+          const i = e.box;
+          Object.assign(i, t.chartArea), i.update(g.w, g.h, { left: 0, top: 0, right: 0, bottom: 0 });
+        });
+    },
+  };
+  class Ji {
+    acquireContext(t, e) {}
+    releaseContext(t) {
+      return !1;
+    }
+    addEventListener(t, e, i) {}
+    removeEventListener(t, e, i) {}
+    getDevicePixelRatio() {
+      return 1;
+    }
+    getMaximumSize(t, e, i, s) {
+      return e = Math.max(0, e || t.width),
+        i = i || t.height,
+        { width: e, height: Math.max(0, s ? Math.floor(e / s) : i) };
+    }
+    isAttached(t) {
+      return !0;
+    }
+    updateConfig(t) {}
+  }
+  class Qi extends Ji {
+    acquireContext(t) {
+      return t && t.getContext && t.getContext("2d") || null;
+    }
+    updateConfig(t) {
+      t.options.animation = !1;
+    }
+  }
+  const ts = {
+      touchstart: "mousedown",
+      touchmove: "mousemove",
+      touchend: "mouseup",
+      pointerenter: "mouseenter",
+      pointerdown: "mousedown",
+      pointermove: "mousemove",
+      pointerup: "mouseup",
+      pointerleave: "mouseout",
+      pointerout: "mouseout",
+    },
+    es = t => null === t || "" === t;
+  const is = !!me && { passive: !0 };
+  function ss(t, e, i) {
+    t.canvas.removeEventListener(e, i, is);
+  }
+  function ns(t, e) {
+    for (const i of t) if (i === e || i.contains(e)) return !0;
+  }
+  function os(t, e, i) {
+    const s = t.canvas,
+      n = new MutationObserver(t => {
+        let e = !1;
+        for (const i of t) e = e || ns(i.addedNodes, s), e = e && !ns(i.removedNodes, s);
+        e && i();
+      });
+    return n.observe(document, { childList: !0, subtree: !0 }), n;
+  }
+  function as(t, e, i) {
+    const s = t.canvas,
+      n = new MutationObserver(t => {
+        let e = !1;
+        for (const i of t) e = e || ns(i.removedNodes, s), e = e && !ns(i.addedNodes, s);
+        e && i();
+      });
+    return n.observe(document, { childList: !0, subtree: !0 }), n;
+  }
+  const rs = new Map();
+  let ls = 0;
+  function hs() {
+    const t = window.devicePixelRatio;
+    t !== ls && (ls = t,
+      rs.forEach((e, i) => {
+        i.currentDevicePixelRatio !== t && e();
+      }));
+  }
+  function cs(t, e, i) {
+    const s = t.canvas, n = s && ae(s);
+    if (!n) return;
+    const o = ht((t, e) => {
+        const s = n.clientWidth;
+        i(t, e), s < n.clientWidth && i();
+      }, window),
+      a = new ResizeObserver(t => {
+        const e = t[0], i = e.contentRect.width, s = e.contentRect.height;
+        0 === i && 0 === s || o(i, s);
+      });
+    return a.observe(n),
+      function(t, e) {
+        rs.size || window.addEventListener("resize", hs), rs.set(t, e);
+      }(t, o),
+      a;
+  }
+  function ds(t, e, i) {
+    i && i.disconnect(),
+      "resize" === e && function(t) {
+        rs.delete(t), rs.size || window.removeEventListener("resize", hs);
+      }(t);
+  }
+  function us(t, e, i) {
+    const s = t.canvas,
+      n = ht(
+        e => {
+          null !== t.ctx && i(function(t, e) {
+            const i = ts[t.type] || t.type, { x: s, y: n } = ue(t, e);
+            return { type: i, chart: e, native: t, x: void 0 !== s ? s : null, y: void 0 !== n ? n : null };
+          }(e, t));
+        },
+        t,
+        t => {
+          const e = t[0];
+          return [e, e.offsetX, e.offsetY];
+        },
+      );
+    return function(t, e, i) {
+      t.addEventListener(e, i, is);
+    }(s, e, n),
+      n;
+  }
+  class fs extends Ji {
+    acquireContext(t, e) {
+      const i = t && t.getContext && t.getContext("2d");
+      return i && i.canvas === t
+        ? (function(t, e) {
+          const i = t.style, s = t.getAttribute("height"), n = t.getAttribute("width");
+          if (
+            t.$chartjs = {
+              initial: { height: s, width: n, style: { display: i.display, height: i.height, width: i.width } },
+            },
+              i.display = i.display || "block",
+              i.boxSizing = i.boxSizing || "border-box",
+              es(n)
+          ) {
+            const e = be(t, "width");
+            void 0 !== e && (t.width = e);
+          }
+          if (es(s)) {
+            if ("" === t.style.height) t.height = t.width / (e || 2);
+            else {
+              const e = be(t, "height");
+              void 0 !== e && (t.height = e);
+            }
+          }
+        }(t, e),
+          i)
+        : null;
+    }
+    releaseContext(t) {
+      const e = t.canvas;
+      if (!e.$chartjs) return !1;
+      const s = e.$chartjs.initial;
+      ["height", "width"].forEach(t => {
+        const n = s[t];
+        i(n) ? e.removeAttribute(t) : e.setAttribute(t, n);
+      });
+      const n = s.style || {};
+      return Object.keys(n).forEach(t => {
+        e.style[t] = n[t];
+      }),
+        e.width = e.width,
+        delete e.$chartjs,
+        !0;
+    }
+    addEventListener(t, e, i) {
+      this.removeEventListener(t, e);
+      const s = t.$proxies || (t.$proxies = {}), n = { attach: os, detach: as, resize: cs }[e] || us;
+      s[e] = n(t, e, i);
+    }
+    removeEventListener(t, e) {
+      const i = t.$proxies || (t.$proxies = {}), s = i[e];
+      if (!s) return;
+      ({ attach: ds, detach: ds, resize: ds }[e] || ss)(t, e, s), i[e] = void 0;
+    }
+    getDevicePixelRatio() {
+      return window.devicePixelRatio;
+    }
+    getMaximumSize(t, e, i, s) {
+      return ge(t, e, i, s);
+    }
+    isAttached(t) {
+      const e = ae(t);
+      return !(!e || !e.isConnected);
+    }
+  }
+  function gs(t) {
+    return !oe() || "undefined" != typeof OffscreenCanvas && t instanceof OffscreenCanvas ? Qi : fs;
+  }
+  var ps = Object.freeze({
+    __proto__: null,
+    _detectPlatform: gs,
+    BasePlatform: Ji,
+    BasicPlatform: Qi,
+    DomPlatform: fs,
+  });
+  const ms = "transparent",
+    bs = {
+      boolean: (t, e, i) => i > .5 ? e : t,
+      color(t, e, i) {
+        const s = Jt(t || ms), n = s.valid && Jt(e || ms);
+        return n && n.valid ? n.mix(s, i).hexString() : e;
+      },
+      number: (t, e, i) => t + (e - t) * i,
+    };
+  class xs {
+    constructor(t, e, i, s) {
+      const n = e[i];
+      s = bi([t.to, s, n, t.from]);
+      const o = bi([t.from, n, s]);
+      this._active = !0,
+        this._fn = t.fn || bs[t.type || typeof o],
+        this._easing = si[t.easing] || si.linear,
+        this._start = Math.floor(Date.now() + (t.delay || 0)),
+        this._duration = this._total = Math.floor(t.duration),
+        this._loop = !!t.loop,
+        this._target = e,
+        this._prop = i,
+        this._from = o,
+        this._to = s,
+        this._promises = void 0;
+    }
+    active() {
+      return this._active;
+    }
+    update(t, e, i) {
+      if (this._active) {
+        this._notify(!1);
+        const s = this._target[this._prop], n = i - this._start, o = this._duration - n;
+        this._start = i,
+          this._duration = Math.floor(Math.max(o, t.duration)),
+          this._total += n,
+          this._loop = !!t.loop,
+          this._to = bi([t.to, e, s, t.from]),
+          this._from = bi([t.from, s, e]);
+      }
+    }
+    cancel() {
+      this._active && (this.tick(Date.now()), this._active = !1, this._notify(!1));
+    }
+    tick(t) {
+      const e = t - this._start, i = this._duration, s = this._prop, n = this._from, o = this._loop, a = this._to;
+      let r;
+      if (this._active = n !== a && (o || e < i), !this._active) return this._target[s] = a, void this._notify(!0);
+      e < 0
+        ? this._target[s] = n
+        : (r = e / i % 2,
+          r = o && r > 1 ? 2 - r : r,
+          r = this._easing(Math.min(1, Math.max(0, r))),
+          this._target[s] = this._fn(n, a, r));
+    }
+    wait() {
+      const t = this._promises || (this._promises = []);
+      return new Promise((e, i) => {
+        t.push({ res: e, rej: i });
+      });
+    }
+    _notify(t) {
+      const e = t ? "res" : "rej", i = this._promises || [];
+      for (let t = 0; t < i.length; t++) i[t][e]();
+    }
+  }
+  ne.set("animation", {
+    delay: void 0,
+    duration: 1e3,
+    easing: "easeOutQuart",
+    fn: void 0,
+    from: void 0,
+    loop: void 0,
+    to: void 0,
+    type: void 0,
+  });
+  const _s = Object.keys(ne.animation);
+  ne.describe("animation", {
+    _fallback: !1,
+    _indexable: !1,
+    _scriptable: t => "onProgress" !== t && "onComplete" !== t && "fn" !== t,
+  }),
+    ne.set("animations", {
+      colors: { type: "color", properties: ["color", "borderColor", "backgroundColor"] },
+      numbers: { type: "number", properties: ["x", "y", "borderWidth", "radius", "tension"] },
+    }),
+    ne.describe("animations", { _fallback: "animation" }),
+    ne.set("transitions", {
+      active: { animation: { duration: 400 } },
+      resize: { animation: { duration: 0 } },
+      show: { animations: { colors: { from: "transparent" }, visible: { type: "boolean", duration: 0 } } },
+      hide: {
+        animations: { colors: { to: "transparent" }, visible: { type: "boolean", easing: "linear", fn: t => 0 | t } },
+      },
+    });
+  class ys {
+    constructor(t, e) {
+      this._chart = t, this._properties = new Map(), this.configure(e);
+    }
+    configure(t) {
+      if (!n(t)) return;
+      const e = this._properties;
+      Object.getOwnPropertyNames(t).forEach(i => {
+        const o = t[i];
+        if (!n(o)) return;
+        const a = {};
+        for (const t of _s) a[t] = o[t];
+        (s(o.properties) && o.properties || [i]).forEach(t => {
+          t !== i && e.has(t) || e.set(t, a);
+        });
+      });
+    }
+    _animateOptions(t, e) {
+      const i = e.options,
+        s = function(t, e) {
+          if (!e) return;
+          let i = t.options;
+          if (!i) return void (t.options = e);
+          i.$shared && (t.options = i = Object.assign({}, i, { $shared: !1, $animations: {} }));
+          return i;
+        }(t, i);
+      if (!s) return [];
+      const n = this._createAnimations(s, i);
+      return i.$shared && function(t, e) {
+        const i = [], s = Object.keys(e);
+        for (let e = 0; e < s.length; e++) {
+          const n = t[s[e]];
+          n && n.active() && i.push(n.wait());
+        }
+        return Promise.all(i);
+      }(t.options.$animations, i).then(() => {
+        t.options = i;
+      }, () => {}),
+        n;
+    }
+    _createAnimations(t, e) {
+      const i = this._properties, s = [], n = t.$animations || (t.$animations = {}), o = Object.keys(e), a = Date.now();
+      let r;
+      for (r = o.length - 1; r >= 0; --r) {
+        const l = o[r];
+        if ("$" === l.charAt(0)) continue;
+        if ("options" === l) {
+          s.push(...this._animateOptions(t, e));
+          continue;
+        }
+        const h = e[l];
+        let c = n[l];
+        const d = i.get(l);
+        if (c) {
+          if (d && c.active()) {
+            c.update(d, h, a);
+            continue;
+          }
+          c.cancel();
+        }
+        d && d.duration ? (n[l] = c = new xs(d, t, l, h), s.push(c)) : t[l] = h;
+      }
+      return s;
+    }
+    update(t, e) {
+      if (0 === this._properties.size) return void Object.assign(t, e);
+      const i = this._createAnimations(t, e);
+      return i.length ? (mt.add(this._chart, i), !0) : void 0;
+    }
+  }
+  function vs(t, e) {
+    const i = t && t.options || {}, s = i.reverse, n = void 0 === i.min ? e : 0, o = void 0 === i.max ? e : 0;
+    return { start: s ? o : n, end: s ? n : o };
+  }
+  function ws(t, e) {
+    const i = [], s = t._getSortedDatasetMetas(e);
+    let n, o;
+    for (n = 0, o = s.length; n < o; ++n) i.push(s[n].index);
+    return i;
+  }
+  function Ms(t, e, i, s = {}) {
+    const n = t.keys, a = "single" === s.mode;
+    let r, l, h, c;
+    if (null !== e) {
+      for (r = 0, l = n.length; r < l; ++r) {
+        if (h = +n[r], h === i) {
+          if (s.all) continue;
+          break;
+        }
+        c = t.values[h], o(c) && (a || 0 === e || z(e) === z(c)) && (e += c);
+      }
+      return e;
+    }
+  }
+  function ks(t, e) {
+    const i = t && t.options.stacked;
+    return i || void 0 === i && void 0 !== e.stack;
+  }
+  function Ss(t, e, i) {
+    const s = t[e] || (t[e] = {});
+    return s[i] || (s[i] = {});
+  }
+  function Ps(t, e, i, s) {
+    for (const n of e.getMatchingVisibleMetas(s).reverse()) {
+      const e = t[n.index];
+      if (i && e > 0 || !i && e < 0) return n.index;
+    }
+    return null;
+  }
+  function Ds(t, e) {
+    const { chart: i, _cachedMeta: s } = t,
+      n = i._stacks || (i._stacks = {}),
+      { iScale: o, vScale: a, index: r } = s,
+      l = o.axis,
+      h = a.axis,
+      c = function(t, e, i) {
+        return `${t.id}.${e.id}.${i.stack || i.type}`;
+      }(o, a, s),
+      d = e.length;
+    let u;
+    for (let t = 0; t < d; ++t) {
+      const i = e[t], { [l]: o, [h]: d } = i;
+      u = (i._stacks || (i._stacks = {}))[h] = Ss(n, c, o),
+        u[r] = d,
+        u._top = Ps(u, a, !0, s.type),
+        u._bottom = Ps(u, a, !1, s.type);
+    }
+  }
+  function Os(t, e) {
+    const i = t.scales;
+    return Object.keys(i).filter(t => i[t].axis === e).shift();
+  }
+  function Cs(t, e) {
+    const i = t.controller.index, s = t.vScale && t.vScale.axis;
+    if (s) {
+      e = e || t._parsed;
+      for (const t of e) {
+        const e = t._stacks;
+        if (!e || void 0 === e[s] || void 0 === e[s][i]) return;
+        delete e[s][i];
+      }
+    }
+  }
+  const As = t => "reset" === t || "none" === t, Ts = (t, e) => e ? t : Object.assign({}, t);
+  class Ls {
+    constructor(t, e) {
+      this.chart = t,
+        this._ctx = t.ctx,
+        this.index = e,
+        this._cachedDataOpts = {},
+        this._cachedMeta = this.getMeta(),
+        this._type = this._cachedMeta.type,
+        this.options = void 0,
+        this._parsing = !1,
+        this._data = void 0,
+        this._objectData = void 0,
+        this._sharedOptions = void 0,
+        this._drawStart = void 0,
+        this._drawCount = void 0,
+        this.enableOptionSharing = !1,
+        this.supportsDecimation = !1,
+        this.$context = void 0,
+        this._syncList = [],
+        this.initialize();
+    }
+    initialize() {
+      const t = this._cachedMeta;
+      this.configure(), this.linkScales(), t._stacked = ks(t.vScale, t), this.addElements();
+    }
+    updateIndex(t) {
+      this.index !== t && Cs(this._cachedMeta), this.index = t;
+    }
+    linkScales() {
+      const t = this.chart,
+        e = this._cachedMeta,
+        i = this.getDataset(),
+        s = (t, e, i, s) => "x" === t ? e : "r" === t ? s : i,
+        n = e.xAxisID = r(i.xAxisID, Os(t, "x")),
+        o = e.yAxisID = r(i.yAxisID, Os(t, "y")),
+        a = e.rAxisID = r(i.rAxisID, Os(t, "r")),
+        l = e.indexAxis,
+        h = e.iAxisID = s(l, n, o, a),
+        c = e.vAxisID = s(l, o, n, a);
+      e.xScale = this.getScaleForId(n),
+        e.yScale = this.getScaleForId(o),
+        e.rScale = this.getScaleForId(a),
+        e.iScale = this.getScaleForId(h),
+        e.vScale = this.getScaleForId(c);
+    }
+    getDataset() {
+      return this.chart.data.datasets[this.index];
+    }
+    getMeta() {
+      return this.chart.getDatasetMeta(this.index);
+    }
+    getScaleForId(t) {
+      return this.chart.scales[t];
+    }
+    _getOtherScale(t) {
+      const e = this._cachedMeta;
+      return t === e.iScale ? e.vScale : e.iScale;
+    }
+    reset() {
+      this._update("reset");
+    }
+    _destroy() {
+      const t = this._cachedMeta;
+      this._data && at(this._data, this), t._stacked && Cs(t);
+    }
+    _dataCheck() {
+      const t = this.getDataset(), e = t.data || (t.data = []), i = this._data;
+      if (n(e)) {
+        this._data = function(t) {
+          const e = Object.keys(t), i = new Array(e.length);
+          let s, n, o;
+          for (s = 0, n = e.length; s < n; ++s) o = e[s], i[s] = { x: o, y: t[o] };
+          return i;
+        }(e);
+      } else if (i !== e) {
+        if (i) {
+          at(i, this);
+          const t = this._cachedMeta;
+          Cs(t), t._parsed = [];
+        }
+        e && Object.isExtensible(e) && ot(e, this), this._syncList = [], this._data = e;
+      }
+    }
+    addElements() {
+      const t = this._cachedMeta;
+      this._dataCheck(), this.datasetElementType && (t.dataset = new this.datasetElementType());
+    }
+    buildOrUpdateElements(t) {
+      const e = this._cachedMeta, i = this.getDataset();
+      let s = !1;
+      this._dataCheck();
+      const n = e._stacked;
+      e._stacked = ks(e.vScale, e),
+        e.stack !== i.stack && (s = !0, Cs(e), e.stack = i.stack),
+        this._resyncElements(t),
+        (s || n !== e._stacked) && Ds(this, e._parsed);
+    }
+    configure() {
+      const t = this.chart.config, e = t.datasetScopeKeys(this._type), i = t.getOptionScopes(this.getDataset(), e, !0);
+      this.options = t.createResolver(i, this.getContext()),
+        this._parsing = this.options.parsing,
+        this._cachedDataOpts = {};
+    }
+    parse(t, e) {
+      const { _cachedMeta: i, _data: o } = this, { iScale: a, _stacked: r } = i, l = a.axis;
+      let h, c, d, u = 0 === t && e === o.length || i._sorted, f = t > 0 && i._parsed[t - 1];
+      if (!1 === this._parsing) i._parsed = o, i._sorted = !0, d = o;
+      else {
+        d = s(o[t])
+          ? this.parseArrayData(i, o, t, e)
+          : n(o[t])
+          ? this.parseObjectData(i, o, t, e)
+          : this.parsePrimitiveData(i, o, t, e);
+        const a = () => null === c[l] || f && c[l] < f[l];
+        for (h = 0; h < e; ++h) i._parsed[h + t] = c = d[h], u && (a() && (u = !1), f = c);
+        i._sorted = u;
+      }
+      r && Ds(this, d);
+    }
+    parsePrimitiveData(t, e, i, s) {
+      const { iScale: n, vScale: o } = t, a = n.axis, r = o.axis, l = n.getLabels(), h = n === o, c = new Array(s);
+      let d, u, f;
+      for (d = 0, u = s; d < u; ++d) f = d + i, c[d] = { [a]: h || n.parse(l[f], f), [r]: o.parse(e[f], f) };
+      return c;
+    }
+    parseArrayData(t, e, i, s) {
+      const { xScale: n, yScale: o } = t, a = new Array(s);
+      let r, l, h, c;
+      for (r = 0, l = s; r < l; ++r) h = r + i, c = e[h], a[r] = { x: n.parse(c[0], h), y: o.parse(c[1], h) };
+      return a;
+    }
+    parseObjectData(t, e, i, s) {
+      const { xScale: n, yScale: o } = t, { xAxisKey: a = "x", yAxisKey: r = "y" } = this._parsing, l = new Array(s);
+      let h, c, d, u;
+      for (h = 0, c = s; h < c; ++h) d = h + i, u = e[d], l[h] = { x: n.parse(y(u, a), d), y: o.parse(y(u, r), d) };
+      return l;
+    }
+    getParsed(t) {
+      return this._cachedMeta._parsed[t];
+    }
+    getDataElement(t) {
+      return this._cachedMeta.data[t];
+    }
+    applyStack(t, e, i) {
+      const s = this.chart, n = this._cachedMeta, o = e[t.axis];
+      return Ms({ keys: ws(s, !0), values: e._stacks[t.axis] }, o, n.index, { mode: i });
+    }
+    updateRangeFromParsed(t, e, i, s) {
+      const n = i[e.axis];
+      let o = null === n ? NaN : n;
+      const a = s && i._stacks[e.axis];
+      s && a && (s.values = a, o = Ms(s, n, this._cachedMeta.index)),
+        t.min = Math.min(t.min, o),
+        t.max = Math.max(t.max, o);
+    }
+    getMinMax(t, e) {
+      const i = this._cachedMeta,
+        s = i._parsed,
+        n = i._sorted && t === i.iScale,
+        a = s.length,
+        r = this._getOtherScale(t),
+        l = ((t, e, i) => t && !e.hidden && e._stacked && { keys: ws(i, !0), values: null })(e, i, this.chart),
+        h = { min: Number.POSITIVE_INFINITY, max: Number.NEGATIVE_INFINITY },
+        { min: c, max: d } = function(t) {
+          const { min: e, max: i, minDefined: s, maxDefined: n } = t.getUserBounds();
+          return { min: s ? e : Number.NEGATIVE_INFINITY, max: n ? i : Number.POSITIVE_INFINITY };
+        }(r);
+      let u, f;
+      function g() {
+        f = s[u];
+        const e = f[r.axis];
+        return !o(f[t.axis]) || c > e || d < e;
+      }
+      for (u = 0; u < a && (g() || (this.updateRangeFromParsed(h, t, f, l), !n)); ++u);
+      if (n) {
+        for (u = a - 1; u >= 0; --u) {
+          if (!g()) {
+            this.updateRangeFromParsed(h, t, f, l);
+            break;
+          }
+        }
+      }
+      return h;
+    }
+    getAllParsedValues(t) {
+      const e = this._cachedMeta._parsed, i = [];
+      let s, n, a;
+      for (s = 0, n = e.length; s < n; ++s) a = e[s][t.axis], o(a) && i.push(a);
+      return i;
+    }
+    getMaxOverflow() {
+      return !1;
+    }
+    getLabelAndValue(t) {
+      const e = this._cachedMeta, i = e.iScale, s = e.vScale, n = this.getParsed(t);
+      return { label: i ? "" + i.getLabelForValue(n[i.axis]) : "", value: s ? "" + s.getLabelForValue(n[s.axis]) : "" };
+    }
+    _update(t) {
+      const e = this._cachedMeta;
+      this.update(t || "default"),
+        e._clip = function(t) {
+          let e, i, s, o;
+          return n(t) ? (e = t.top, i = t.right, s = t.bottom, o = t.left) : e =
+            i =
+            s =
+            o =
+              t,
+            { top: e, right: i, bottom: s, left: o, disabled: !1 === t };
+        }(r(
+          this.options.clip,
+          function(t, e, i) {
+            if (!1 === i) return !1;
+            const s = vs(t, i), n = vs(e, i);
+            return { top: n.end, right: s.end, bottom: n.start, left: s.start };
+          }(e.xScale, e.yScale, this.getMaxOverflow()),
+        ));
+    }
+    update(t) {}
+    draw() {
+      const t = this._ctx,
+        e = this.chart,
+        i = this._cachedMeta,
+        s = i.data || [],
+        n = e.chartArea,
+        o = [],
+        a = this._drawStart || 0,
+        r = this._drawCount || s.length - a,
+        l = this.options.drawActiveElementsOnTop;
+      let h;
+      for (i.dataset && i.dataset.draw(t, n, a, r), h = a; h < a + r; ++h) {
+        const e = s[h];
+        e.hidden || (e.active && l ? o.push(e) : e.draw(t, n));
+      }
+      for (h = 0; h < o.length; ++h) o[h].draw(t, n);
+    }
+    getStyle(t, e) {
+      const i = e ? "active" : "default";
+      return void 0 === t && this._cachedMeta.dataset
+        ? this.resolveDatasetElementOptions(i)
+        : this.resolveDataElementOptions(t || 0, i);
+    }
+    getContext(t, e, i) {
+      const s = this.getDataset();
+      let n;
+      if (t >= 0 && t < this._cachedMeta.data.length) {
+        const e = this._cachedMeta.data[t];
+        n = e.$context || (e.$context = function(t, e, i) {
+          return _i(t, {
+            active: !1,
+            dataIndex: e,
+            parsed: void 0,
+            raw: void 0,
+            element: i,
+            index: e,
+            mode: "default",
+            type: "data",
+          });
+        }(this.getContext(), t, e)),
+          n.parsed = this.getParsed(t),
+          n.raw = s.data[t],
+          n.index = n.dataIndex = t;
+      } else {n = this.$context || (this.$context = function(t, e) {
+          return _i(t, { active: !1, dataset: void 0, datasetIndex: e, index: e, mode: "default", type: "dataset" });
+        }(this.chart.getContext(), this.index)),
+          n.dataset = s,
+          n.index = n.datasetIndex = this.index;}
+      return n.active = !!e, n.mode = i, n;
+    }
+    resolveDatasetElementOptions(t) {
+      return this._resolveElementOptions(this.datasetElementType.id, t);
+    }
+    resolveDataElementOptions(t, e) {
+      return this._resolveElementOptions(this.dataElementType.id, e, t);
+    }
+    _resolveElementOptions(t, e = "default", i) {
+      const s = "active" === e,
+        n = this._cachedDataOpts,
+        o = t + "-" + e,
+        a = n[o],
+        r = this.enableOptionSharing && M(i);
+      if (a) return Ts(a, r);
+      const l = this.chart.config,
+        h = l.datasetElementScopeKeys(this._type, t),
+        c = s ? [`${t}Hover`, "hover", t, ""] : [t, ""],
+        d = l.getOptionScopes(this.getDataset(), h),
+        u = Object.keys(ne.elements[t]),
+        f = l.resolveNamedOptions(d, u, () => this.getContext(i, s), c);
+      return f.$shared && (f.$shared = r, n[o] = Object.freeze(Ts(f, r))), f;
+    }
+    _resolveAnimations(t, e, i) {
+      const s = this.chart, n = this._cachedDataOpts, o = `animation-${e}`, a = n[o];
+      if (a) return a;
+      let r;
+      if (!1 !== s.options.animation) {
+        const s = this.chart.config,
+          n = s.datasetAnimationScopeKeys(this._type, e),
+          o = s.getOptionScopes(this.getDataset(), n);
+        r = s.createResolver(o, this.getContext(t, i, e));
+      }
+      const l = new ys(s, r && r.animations);
+      return r && r._cacheable && (n[o] = Object.freeze(l)), l;
+    }
+    getSharedOptions(t) {
+      if (t.$shared) return this._sharedOptions || (this._sharedOptions = Object.assign({}, t));
+    }
+    includeOptions(t, e) {
+      return !e || As(t) || this.chart._animationsDisabled;
+    }
+    _getSharedOptions(t, e) {
+      const i = this.resolveDataElementOptions(t, e),
+        s = this._sharedOptions,
+        n = this.getSharedOptions(i),
+        o = this.includeOptions(e, n) || n !== s;
+      return this.updateSharedOptions(n, e, i), { sharedOptions: n, includeOptions: o };
+    }
+    updateElement(t, e, i, s) {
+      As(s) ? Object.assign(t, i) : this._resolveAnimations(e, s).update(t, i);
+    }
+    updateSharedOptions(t, e, i) {
+      t && !As(e) && this._resolveAnimations(void 0, e).update(t, i);
+    }
+    _setStyle(t, e, i, s) {
+      t.active = s;
+      const n = this.getStyle(e, s);
+      this._resolveAnimations(e, i, s).update(t, { options: !s && this.getSharedOptions(n) || n });
+    }
+    removeHoverStyle(t, e, i) {
+      this._setStyle(t, i, "active", !1);
+    }
+    setHoverStyle(t, e, i) {
+      this._setStyle(t, i, "active", !0);
+    }
+    _removeDatasetHoverStyle() {
+      const t = this._cachedMeta.dataset;
+      t && this._setStyle(t, void 0, "active", !1);
+    }
+    _setDatasetHoverStyle() {
+      const t = this._cachedMeta.dataset;
+      t && this._setStyle(t, void 0, "active", !0);
+    }
+    _resyncElements(t) {
+      const e = this._data, i = this._cachedMeta.data;
+      for (const [t, e, i] of this._syncList) this[t](e, i);
+      this._syncList = [];
+      const s = i.length, n = e.length, o = Math.min(n, s);
+      o && this.parse(0, o), n > s ? this._insertElements(s, n - s, t) : n < s && this._removeElements(n, s - n);
+    }
+    _insertElements(t, e, i = !0) {
+      const s = this._cachedMeta, n = s.data, o = t + e;
+      let a;
+      const r = t => {
+        for (t.length += e, a = t.length - 1; a >= o; a--) t[a] = t[a - e];
+      };
+      for (r(n), a = t; a < o; ++a) n[a] = new this.dataElementType();
+      this._parsing && r(s._parsed), this.parse(t, e), i && this.updateElements(n, t, e, "reset");
+    }
+    updateElements(t, e, i, s) {}
+    _removeElements(t, e) {
+      const i = this._cachedMeta;
+      if (this._parsing) {
+        const s = i._parsed.splice(t, e);
+        i._stacked && Cs(i, s);
+      }
+      i.data.splice(t, e);
+    }
+    _sync(t) {
+      if (this._parsing) this._syncList.push(t);
+      else {
+        const [e, i, s] = t;
+        this[e](i, s);
+      }
+      this.chart._dataChanges.push([this.index, ...t]);
+    }
+    _onDataPush() {
+      const t = arguments.length;
+      this._sync(["_insertElements", this.getDataset().data.length - t, t]);
+    }
+    _onDataPop() {
+      this._sync(["_removeElements", this._cachedMeta.data.length - 1, 1]);
+    }
+    _onDataShift() {
+      this._sync(["_removeElements", 0, 1]);
+    }
+    _onDataSplice(t, e) {
+      e && this._sync(["_removeElements", t, e]);
+      const i = arguments.length - 2;
+      i && this._sync(["_insertElements", t, i]);
+    }
+    _onDataUnshift() {
+      this._sync(["_insertElements", 0, arguments.length]);
+    }
+  }
+  Ls.defaults = {}, Ls.prototype.datasetElementType = null, Ls.prototype.dataElementType = null;
+  class Es {
+    constructor() {
+      this.x = void 0, this.y = void 0, this.active = !1, this.options = void 0, this.$animations = void 0;
+    }
+    tooltipPosition(t) {
+      const { x: e, y: i } = this.getProps(["x", "y"], t);
+      return { x: e, y: i };
+    }
+    hasValue() {
+      return B(this.x) && B(this.y);
+    }
+    getProps(t, e) {
+      const i = this.$animations;
+      if (!e || !i) return this;
+      const s = {};
+      return t.forEach(t => {
+        s[t] = i[t] && i[t].active() ? i[t]._to : this[t];
+      }),
+        s;
+    }
+  }
+  Es.defaults = {}, Es.defaultRoutes = void 0;
+  const Rs = {
+    values: t => s(t) ? t : "" + t,
+    numeric(t, e, i) {
+      if (0 === t) return "0";
+      const s = this.chart.options.locale;
+      let n, o = t;
+      if (i.length > 1) {
+        const e = Math.max(Math.abs(i[0].value), Math.abs(i[i.length - 1].value));
+        (e < 1e-4 || e > 1e15) && (n = "scientific"),
+          o = function(t, e) {
+            let i = e.length > 3 ? e[2].value - e[1].value : e[1].value - e[0].value;
+            Math.abs(i) >= 1 && t !== Math.floor(t) && (i = t - Math.floor(t));
+            return i;
+          }(t, i);
+      }
+      const a = I(Math.abs(o)),
+        r = Math.max(Math.min(-1 * Math.floor(a), 20), 0),
+        l = { notation: n, minimumFractionDigits: r, maximumFractionDigits: r };
+      return Object.assign(l, this.options.ticks.format), li(t, s, l);
+    },
+    logarithmic(t, e, i) {
+      if (0 === t) return "0";
+      const s = t / Math.pow(10, Math.floor(I(t)));
+      return 1 === s || 2 === s || 5 === s ? Rs.numeric.call(this, t, e, i) : "";
+    },
+  };
+  var Is = { formatters: Rs };
+  function zs(t, e) {
+    const s = t.options.ticks,
+      n = s.maxTicksLimit || function(t) {
+        const e = t.options.offset, i = t._tickSize(), s = t._length / i + (e ? 0 : 1), n = t._maxLength / i;
+        return Math.floor(Math.min(s, n));
+      }(t),
+      o = s.major.enabled
+        ? function(t) {
+          const e = [];
+          let i, s;
+          for (i = 0, s = t.length; i < s; i++) t[i].major && e.push(i);
+          return e;
+        }(e)
+        : [],
+      a = o.length,
+      r = o[0],
+      l = o[a - 1],
+      h = [];
+    if (a > n) {
+      return function(t, e, i, s) {
+        let n, o = 0, a = i[0];
+        for (s = Math.ceil(s), n = 0; n < t.length; n++) n === a && (e.push(t[n]), o++, a = i[o * s]);
+      }(e, h, o, a / n),
+        h;
+    }
+    const c = function(t, e, i) {
+      const s = function(t) {
+          const e = t.length;
+          let i, s;
+          if (e < 2) return !1;
+          for (s = t[0], i = 1; i < e; ++i) if (t[i] - t[i - 1] !== s) return !1;
+          return s;
+        }(t),
+        n = e.length / i;
+      if (!s) return Math.max(n, 1);
+      const o = V(s);
+      for (let t = 0, e = o.length - 1; t < e; t++) {
+        const e = o[t];
+        if (e > n) return e;
+      }
+      return Math.max(n, 1);
+    }(o, e, n);
+    if (a > 0) {
+      let t, s;
+      const n = a > 1 ? Math.round((l - r) / (a - 1)) : null;
+      for (Fs(e, h, c, i(n) ? 0 : r - n, r), t = 0, s = a - 1; t < s; t++) Fs(e, h, c, o[t], o[t + 1]);
+      return Fs(e, h, c, l, i(n) ? e.length : l + n), h;
+    }
+    return Fs(e, h, c), h;
+  }
+  function Fs(t, e, i, s, n) {
+    const o = r(s, 0), a = Math.min(r(n, t.length), t.length);
+    let l, h, c, d = 0;
+    for (i = Math.ceil(i), n && (l = n - s, i = l / Math.floor(l / i)), c = o; c < 0;) d++, c = Math.round(o + d * i);
+    for (h = Math.max(o, 0); h < a; h++) h === c && (e.push(t[h]), d++, c = Math.round(o + d * i));
+  }
+  ne.set("scale", {
+    display: !0,
+    offset: !1,
+    reverse: !1,
+    beginAtZero: !1,
+    bounds: "ticks",
+    grace: 0,
+    grid: {
+      display: !0,
+      lineWidth: 1,
+      drawBorder: !0,
+      drawOnChartArea: !0,
+      drawTicks: !0,
+      tickLength: 8,
+      tickWidth: (t, e) => e.lineWidth,
+      tickColor: (t, e) => e.color,
+      offset: !1,
+      borderDash: [],
+      borderDashOffset: 0,
+      borderWidth: 1,
+    },
+    title: { display: !1, text: "", padding: { top: 4, bottom: 4 } },
+    ticks: {
+      minRotation: 0,
+      maxRotation: 50,
+      mirror: !1,
+      textStrokeWidth: 0,
+      textStrokeColor: "",
+      padding: 3,
+      display: !0,
+      autoSkip: !0,
+      autoSkipPadding: 3,
+      labelOffset: 0,
+      callback: Is.formatters.values,
+      minor: {},
+      major: {},
+      align: "center",
+      crossAlign: "near",
+      showLabelBackdrop: !1,
+      backdropColor: "rgba(255, 255, 255, 0.75)",
+      backdropPadding: 2,
+    },
+  }),
+    ne.route("scale.ticks", "color", "", "color"),
+    ne.route("scale.grid", "color", "", "borderColor"),
+    ne.route("scale.grid", "borderColor", "", "borderColor"),
+    ne.route("scale.title", "color", "", "color"),
+    ne.describe("scale", {
+      _fallback: !1,
+      _scriptable: t => !t.startsWith("before") && !t.startsWith("after") && "callback" !== t && "parser" !== t,
+      _indexable: t => "borderDash" !== t && "tickBorderDash" !== t,
+    }),
+    ne.describe("scales", { _fallback: "scale" }),
+    ne.describe("scale.ticks", {
+      _scriptable: t => "backdropPadding" !== t && "callback" !== t,
+      _indexable: t => "backdropPadding" !== t,
+    });
+  const Vs = (t, e, i) => "top" === e || "left" === e ? t[e] + i : t[e] - i;
+  function Bs(t, e) {
+    const i = [], s = t.length / e, n = t.length;
+    let o = 0;
+    for (; o < n; o += s) i.push(t[Math.floor(o)]);
+    return i;
+  }
+  function Ns(t, e, i) {
+    const s = t.ticks.length, n = Math.min(e, s - 1), o = t._startPixel, a = t._endPixel, r = 1e-6;
+    let l, h = t.getPixelForTick(n);
+    if (
+      !(i && (l = 1 === s
+        ? Math.max(h - o, a - h)
+        : 0 === e
+        ? (t.getPixelForTick(1) - h) / 2
+        : (h - t.getPixelForTick(n - 1)) / 2,
+        h += n < e ? l : -l,
+        h < o - r || h > a + r))
+    ) return h;
+  }
+  function Ws(t) {
+    return t.drawTicks ? t.tickLength : 0;
+  }
+  function js(t, e) {
+    if (!t.display) return 0;
+    const i = mi(t.font, e), n = pi(t.padding);
+    return (s(t.text) ? t.text.length : 1) * i.lineHeight + n.height;
+  }
+  function Hs(t, e, i) {
+    let s = dt(t);
+    return (i && "right" !== e || !i && "right" === e)
+      && (s = (t => "left" === t ? "right" : "right" === t ? "left" : t)(s)),
+      s;
+  }
+  class $s extends Es {
+    constructor(t) {
+      super(),
+        this.id = t.id,
+        this.type = t.type,
+        this.options = void 0,
+        this.ctx = t.ctx,
+        this.chart = t.chart,
+        this.top = void 0,
+        this.bottom = void 0,
+        this.left = void 0,
+        this.right = void 0,
+        this.width = void 0,
+        this.height = void 0,
+        this._margins = { left: 0, right: 0, top: 0, bottom: 0 },
+        this.maxWidth = void 0,
+        this.maxHeight = void 0,
+        this.paddingTop = void 0,
+        this.paddingBottom = void 0,
+        this.paddingLeft = void 0,
+        this.paddingRight = void 0,
+        this.axis = void 0,
+        this.labelRotation = void 0,
+        this.min = void 0,
+        this.max = void 0,
+        this._range = void 0,
+        this.ticks = [],
+        this._gridLineItems = null,
+        this._labelItems = null,
+        this._labelSizes = null,
+        this._length = 0,
+        this._maxLength = 0,
+        this._longestTextCache = {},
+        this._startPixel = void 0,
+        this._endPixel = void 0,
+        this._reversePixels = !1,
+        this._userMax = void 0,
+        this._userMin = void 0,
+        this._suggestedMax = void 0,
+        this._suggestedMin = void 0,
+        this._ticksLength = 0,
+        this._borderValue = 0,
+        this._cache = {},
+        this._dataLimitsCached = !1,
+        this.$context = void 0;
+    }
+    init(t) {
+      this.options = t.setContext(this.getContext()),
+        this.axis = t.axis,
+        this._userMin = this.parse(t.min),
+        this._userMax = this.parse(t.max),
+        this._suggestedMin = this.parse(t.suggestedMin),
+        this._suggestedMax = this.parse(t.suggestedMax);
+    }
+    parse(t, e) {
+      return t;
+    }
+    getUserBounds() {
+      let { _userMin: t, _userMax: e, _suggestedMin: i, _suggestedMax: s } = this;
+      return t = a(t, Number.POSITIVE_INFINITY),
+        e = a(e, Number.NEGATIVE_INFINITY),
+        i = a(i, Number.POSITIVE_INFINITY),
+        s = a(s, Number.NEGATIVE_INFINITY),
+        { min: a(t, i), max: a(e, s), minDefined: o(t), maxDefined: o(e) };
+    }
+    getMinMax(t) {
+      let e, { min: i, max: s, minDefined: n, maxDefined: o } = this.getUserBounds();
+      if (n && o) return { min: i, max: s };
+      const r = this.getMatchingVisibleMetas();
+      for (let a = 0, l = r.length; a < l; ++a) {
+        e = r[a].controller.getMinMax(this, t), n || (i = Math.min(i, e.min)), o || (s = Math.max(s, e.max));
+      }
+      return i = o && i > s ? s : i, s = n && i > s ? i : s, { min: a(i, a(s, i)), max: a(s, a(i, s)) };
+    }
+    getPadding() {
+      return {
+        left: this.paddingLeft || 0,
+        top: this.paddingTop || 0,
+        right: this.paddingRight || 0,
+        bottom: this.paddingBottom || 0,
+      };
+    }
+    getTicks() {
+      return this.ticks;
+    }
+    getLabels() {
+      const t = this.chart.data;
+      return this.options.labels || (this.isHorizontal() ? t.xLabels : t.yLabels) || t.labels || [];
+    }
+    beforeLayout() {
+      this._cache = {}, this._dataLimitsCached = !1;
+    }
+    beforeUpdate() {
+      c(this.options.beforeUpdate, [this]);
+    }
+    update(t, e, i) {
+      const { beginAtZero: s, grace: n, ticks: o } = this.options, a = o.sampleSize;
+      this.beforeUpdate(),
+        this.maxWidth = t,
+        this.maxHeight = e,
+        this._margins = i = Object.assign({ left: 0, right: 0, top: 0, bottom: 0 }, i),
+        this.ticks = null,
+        this._labelSizes = null,
+        this._gridLineItems = null,
+        this._labelItems = null,
+        this.beforeSetDimensions(),
+        this.setDimensions(),
+        this.afterSetDimensions(),
+        this._maxLength = this.isHorizontal() ? this.width + i.left + i.right : this.height + i.top + i.bottom,
+        this._dataLimitsCached
+        || (this.beforeDataLimits(),
+          this.determineDataLimits(),
+          this.afterDataLimits(),
+          this._range = xi(this, n, s),
+          this._dataLimitsCached = !0),
+        this.beforeBuildTicks(),
+        this.ticks = this.buildTicks() || [],
+        this.afterBuildTicks();
+      const r = a < this.ticks.length;
+      this._convertTicksToLabels(r ? Bs(this.ticks, a) : this.ticks),
+        this.configure(),
+        this.beforeCalculateLabelRotation(),
+        this.calculateLabelRotation(),
+        this.afterCalculateLabelRotation(),
+        o.display && (o.autoSkip || "auto" === o.source)
+        && (this.ticks = zs(this, this.ticks), this._labelSizes = null, this.afterAutoSkip()),
+        r && this._convertTicksToLabels(this.ticks),
+        this.beforeFit(),
+        this.fit(),
+        this.afterFit(),
+        this.afterUpdate();
+    }
+    configure() {
+      let t, e, i = this.options.reverse;
+      this.isHorizontal() ? (t = this.left, e = this.right) : (t = this.top, e = this.bottom, i = !i),
+        this._startPixel = t,
+        this._endPixel = e,
+        this._reversePixels = i,
+        this._length = e - t,
+        this._alignToPixels = this.options.alignToPixels;
+    }
+    afterUpdate() {
+      c(this.options.afterUpdate, [this]);
+    }
+    beforeSetDimensions() {
+      c(this.options.beforeSetDimensions, [this]);
+    }
+    setDimensions() {
+      this.isHorizontal()
+        ? (this.width = this.maxWidth, this.left = 0, this.right = this.width)
+        : (this.height = this.maxHeight, this.top = 0, this.bottom = this.height),
+        this.paddingLeft = 0,
+        this.paddingTop = 0,
+        this.paddingRight = 0,
+        this.paddingBottom = 0;
+    }
+    afterSetDimensions() {
+      c(this.options.afterSetDimensions, [this]);
+    }
+    _callHooks(t) {
+      this.chart.notifyPlugins(t, this.getContext()), c(this.options[t], [this]);
+    }
+    beforeDataLimits() {
+      this._callHooks("beforeDataLimits");
+    }
+    determineDataLimits() {}
+    afterDataLimits() {
+      this._callHooks("afterDataLimits");
+    }
+    beforeBuildTicks() {
+      this._callHooks("beforeBuildTicks");
+    }
+    buildTicks() {
+      return [];
+    }
+    afterBuildTicks() {
+      this._callHooks("afterBuildTicks");
+    }
+    beforeTickToLabelConversion() {
+      c(this.options.beforeTickToLabelConversion, [this]);
+    }
+    generateTickLabels(t) {
+      const e = this.options.ticks;
+      let i, s, n;
+      for (i = 0, s = t.length; i < s; i++) n = t[i], n.label = c(e.callback, [n.value, i, t], this);
+    }
+    afterTickToLabelConversion() {
+      c(this.options.afterTickToLabelConversion, [this]);
+    }
+    beforeCalculateLabelRotation() {
+      c(this.options.beforeCalculateLabelRotation, [this]);
+    }
+    calculateLabelRotation() {
+      const t = this.options, e = t.ticks, i = this.ticks.length, s = e.minRotation || 0, n = e.maxRotation;
+      let o, a, r, l = s;
+      if (!this._isVisible() || !e.display || s >= n || i <= 1 || !this.isHorizontal()) {
+        return void (this.labelRotation = s);
+      }
+      const h = this._getLabelSizes(),
+        c = h.widest.width,
+        d = h.highest.height,
+        u = Z(this.chart.width - c, 0, this.maxWidth);
+      o = t.offset ? this.maxWidth / i : u / (i - 1),
+        c + 6 > o
+        && (o = u / (i - (t.offset ? .5 : 1)),
+          a = this.maxHeight - Ws(t.grid) - e.padding - js(t.title, this.chart.options.font),
+          r = Math.sqrt(c * c + d * d),
+          l = $(
+            Math.min(
+              Math.asin(Z((h.highest.height + 6) / o, -1, 1)),
+              Math.asin(Z(a / r, -1, 1)) - Math.asin(Z(d / r, -1, 1)),
+            ),
+          ),
+          l = Math.max(s, Math.min(n, l))),
+        this.labelRotation = l;
+    }
+    afterCalculateLabelRotation() {
+      c(this.options.afterCalculateLabelRotation, [this]);
+    }
+    afterAutoSkip() {}
+    beforeFit() {
+      c(this.options.beforeFit, [this]);
+    }
+    fit() {
+      const t = { width: 0, height: 0 },
+        { chart: e, options: { ticks: i, title: s, grid: n } } = this,
+        o = this._isVisible(),
+        a = this.isHorizontal();
+      if (o) {
+        const o = js(s, e.options.font);
+        if (
+          a ? (t.width = this.maxWidth, t.height = Ws(n) + o) : (t.height = this.maxHeight, t.width = Ws(n) + o),
+            i.display && this.ticks.length
+        ) {
+          const { first: e, last: s, widest: n, highest: o } = this._getLabelSizes(),
+            r = 2 * i.padding,
+            l = H(this.labelRotation),
+            h = Math.cos(l),
+            c = Math.sin(l);
+          if (a) {
+            const e = i.mirror ? 0 : c * n.width + h * o.height;
+            t.height = Math.min(this.maxHeight, t.height + e + r);
+          } else {
+            const e = i.mirror ? 0 : h * n.width + c * o.height;
+            t.width = Math.min(this.maxWidth, t.width + e + r);
+          }
+          this._calculatePadding(e, s, c, h);
+        }
+      }
+      this._handleMargins(),
+        a
+          ? (this.width = this._length = e.width - this._margins.left - this._margins.right, this.height = t.height)
+          : (this.width = t.width, this.height = this._length = e.height - this._margins.top - this._margins.bottom);
+    }
+    _calculatePadding(t, e, i, s) {
+      const { ticks: { align: n, padding: o }, position: a } = this.options,
+        r = 0 !== this.labelRotation,
+        l = "top" !== a && "x" === this.axis;
+      if (this.isHorizontal()) {
+        const a = this.getPixelForTick(0) - this.left, h = this.right - this.getPixelForTick(this.ticks.length - 1);
+        let c = 0, d = 0;
+        r
+          ? l ? (c = s * t.width, d = i * e.height) : (c = i * t.height, d = s * e.width)
+          : "start" === n
+          ? d = e.width
+          : "end" === n
+          ? c = t.width
+          : "inner" !== n && (c = t.width / 2, d = e.width / 2),
+          this.paddingLeft = Math.max((c - a + o) * this.width / (this.width - a), 0),
+          this.paddingRight = Math.max((d - h + o) * this.width / (this.width - h), 0);
+      } else {
+        let i = e.height / 2, s = t.height / 2;
+        "start" === n ? (i = 0, s = t.height) : "end" === n && (i = e.height, s = 0),
+          this.paddingTop = i + o,
+          this.paddingBottom = s + o;
+      }
+    }
+    _handleMargins() {
+      this._margins
+        && (this._margins.left = Math.max(this.paddingLeft, this._margins.left),
+          this._margins.top = Math.max(this.paddingTop, this._margins.top),
+          this._margins.right = Math.max(this.paddingRight, this._margins.right),
+          this._margins.bottom = Math.max(this.paddingBottom, this._margins.bottom));
+    }
+    afterFit() {
+      c(this.options.afterFit, [this]);
+    }
+    isHorizontal() {
+      const { axis: t, position: e } = this.options;
+      return "top" === e || "bottom" === e || "x" === t;
+    }
+    isFullSize() {
+      return this.options.fullSize;
+    }
+    _convertTicksToLabels(t) {
+      let e, s;
+      for (this.beforeTickToLabelConversion(), this.generateTickLabels(t), e = 0, s = t.length; e < s; e++) {
+        i(t[e].label) && (t.splice(e, 1), s--, e--);
+      }
+      this.afterTickToLabelConversion();
+    }
+    _getLabelSizes() {
+      let t = this._labelSizes;
+      if (!t) {
+        const e = this.options.ticks.sampleSize;
+        let i = this.ticks;
+        e < i.length && (i = Bs(i, e)), this._labelSizes = t = this._computeLabelSizes(i, i.length);
+      }
+      return t;
+    }
+    _computeLabelSizes(t, e) {
+      const { ctx: n, _longestTextCache: o } = this, a = [], r = [];
+      let l, h, c, u, f, g, p, m, b, x, _, y = 0, v = 0;
+      for (l = 0; l < e; ++l) {
+        if (
+          u = t[l].label,
+            f = this._resolveTickFontOptions(l),
+            n.font = g = f.string,
+            p = o[g] = o[g] || { data: {}, gc: [] },
+            m = f.lineHeight,
+            b = x = 0,
+            i(u) || s(u)
+        ) {
+          if (s(u)) {
+            for (h = 0, c = u.length; h < c; ++h) _ = u[h], i(_) || s(_) || (b = _e(n, p.data, p.gc, b, _), x += m);
+          }
+        } else b = _e(n, p.data, p.gc, b, u), x = m;
+        a.push(b), r.push(x), y = Math.max(b, y), v = Math.max(x, v);
+      }
+      !function(t, e) {
+        d(t, t => {
+          const i = t.gc, s = i.length / 2;
+          let n;
+          if (s > e) {
+            for (n = 0; n < s; ++n) delete t.data[i[n]];
+            i.splice(0, s);
+          }
+        });
+      }(o, e);
+      const w = a.indexOf(y), M = r.indexOf(v), k = t => ({ width: a[t] || 0, height: r[t] || 0 });
+      return { first: k(0), last: k(e - 1), widest: k(w), highest: k(M), widths: a, heights: r };
+    }
+    getLabelForValue(t) {
+      return t;
+    }
+    getPixelForValue(t, e) {
+      return NaN;
+    }
+    getValueForPixel(t) {}
+    getPixelForTick(t) {
+      const e = this.ticks;
+      return t < 0 || t > e.length - 1 ? null : this.getPixelForValue(e[t].value);
+    }
+    getPixelForDecimal(t) {
+      this._reversePixels && (t = 1 - t);
+      const e = this._startPixel + t * this._length;
+      return J(this._alignToPixels ? ve(this.chart, e, 0) : e);
+    }
+    getDecimalForPixel(t) {
+      const e = (t - this._startPixel) / this._length;
+      return this._reversePixels ? 1 - e : e;
+    }
+    getBasePixel() {
+      return this.getPixelForValue(this.getBaseValue());
+    }
+    getBaseValue() {
+      const { min: t, max: e } = this;
+      return t < 0 && e < 0 ? e : t > 0 && e > 0 ? t : 0;
+    }
+    getContext(t) {
+      const e = this.ticks || [];
+      if (t >= 0 && t < e.length) {
+        const i = e[t];
+        return i.$context || (i.$context = function(t, e, i) {
+          return _i(t, { tick: i, index: e, type: "tick" });
+        }(this.getContext(), t, i));
+      }
+      return this.$context || (this.$context = _i(this.chart.getContext(), { scale: this, type: "scale" }));
+    }
+    _tickSize() {
+      const t = this.options.ticks,
+        e = H(this.labelRotation),
+        i = Math.abs(Math.cos(e)),
+        s = Math.abs(Math.sin(e)),
+        n = this._getLabelSizes(),
+        o = t.autoSkipPadding || 0,
+        a = n ? n.widest.width + o : 0,
+        r = n ? n.highest.height + o : 0;
+      return this.isHorizontal() ? r * i > a * s ? a / i : r / s : r * s < a * i ? r / i : a / s;
+    }
+    _isVisible() {
+      const t = this.options.display;
+      return "auto" !== t ? !!t : this.getMatchingVisibleMetas().length > 0;
+    }
+    _computeGridLineItems(t) {
+      const e = this.axis,
+        i = this.chart,
+        s = this.options,
+        { grid: o, position: a } = s,
+        l = o.offset,
+        h = this.isHorizontal(),
+        c = this.ticks.length + (l ? 1 : 0),
+        d = Ws(o),
+        u = [],
+        f = o.setContext(this.getContext()),
+        g = f.drawBorder ? f.borderWidth : 0,
+        p = g / 2,
+        m = function(t) {
+          return ve(i, t, g);
+        };
+      let b, x, _, y, v, w, M, k, S, P, D, O;
+      if ("top" === a) b = m(this.bottom), w = this.bottom - d, k = b - p, P = m(t.top) + p, O = t.bottom;
+      else if ("bottom" === a) b = m(this.top), P = t.top, O = m(t.bottom) - p, w = b + p, k = this.top + d;
+      else if ("left" === a) b = m(this.right), v = this.right - d, M = b - p, S = m(t.left) + p, D = t.right;
+      else if ("right" === a) b = m(this.left), S = t.left, D = m(t.right) - p, v = b + p, M = this.left + d;
+      else if ("x" === e) {
+        if ("center" === a) b = m((t.top + t.bottom) / 2 + .5);
+        else if (n(a)) {
+          const t = Object.keys(a)[0], e = a[t];
+          b = m(this.chart.scales[t].getPixelForValue(e));
+        }
+        P = t.top, O = t.bottom, w = b + p, k = w + d;
+      } else if ("y" === e) {
+        if ("center" === a) b = m((t.left + t.right) / 2);
+        else if (n(a)) {
+          const t = Object.keys(a)[0], e = a[t];
+          b = m(this.chart.scales[t].getPixelForValue(e));
+        }
+        v = b - p, M = v - d, S = t.left, D = t.right;
+      }
+      const C = r(s.ticks.maxTicksLimit, c), A = Math.max(1, Math.ceil(c / C));
+      for (x = 0; x < c; x += A) {
+        const t = o.setContext(this.getContext(x)),
+          e = t.lineWidth,
+          s = t.color,
+          n = t.borderDash || [],
+          a = t.borderDashOffset,
+          r = t.tickWidth,
+          c = t.tickColor,
+          d = t.tickBorderDash || [],
+          f = t.tickBorderDashOffset;
+        _ = Ns(this, x, l),
+          void 0 !== _ && (y = ve(i, _, e),
+            h
+              ? v =
+                M =
+                S =
+                D =
+                  y
+              : w =
+                k =
+                P =
+                O =
+                  y,
+            u.push({
+              tx1: v,
+              ty1: w,
+              tx2: M,
+              ty2: k,
+              x1: S,
+              y1: P,
+              x2: D,
+              y2: O,
+              width: e,
+              color: s,
+              borderDash: n,
+              borderDashOffset: a,
+              tickWidth: r,
+              tickColor: c,
+              tickBorderDash: d,
+              tickBorderDashOffset: f,
+            }));
+      }
+      return this._ticksLength = c, this._borderValue = b, u;
+    }
+    _computeLabelItems(t) {
+      const e = this.axis,
+        i = this.options,
+        { position: o, ticks: a } = i,
+        r = this.isHorizontal(),
+        l = this.ticks,
+        { align: h, crossAlign: c, padding: d, mirror: u } = a,
+        f = Ws(i.grid),
+        g = f + d,
+        p = u ? -d : g,
+        m = -H(this.labelRotation),
+        b = [];
+      let x, _, y, v, w, M, k, S, P, D, O, C, A = "middle";
+      if ("top" === o) M = this.bottom - p, k = this._getXAxisLabelAlignment();
+      else if ("bottom" === o) M = this.top + p, k = this._getXAxisLabelAlignment();
+      else if ("left" === o) {
+        const t = this._getYAxisLabelAlignment(f);
+        k = t.textAlign, w = t.x;
+      } else if ("right" === o) {
+        const t = this._getYAxisLabelAlignment(f);
+        k = t.textAlign, w = t.x;
+      } else if ("x" === e) {
+        if ("center" === o) M = (t.top + t.bottom) / 2 + g;
+        else if (n(o)) {
+          const t = Object.keys(o)[0], e = o[t];
+          M = this.chart.scales[t].getPixelForValue(e) + g;
+        }
+        k = this._getXAxisLabelAlignment();
+      } else if ("y" === e) {
+        if ("center" === o) w = (t.left + t.right) / 2 - g;
+        else if (n(o)) {
+          const t = Object.keys(o)[0], e = o[t];
+          w = this.chart.scales[t].getPixelForValue(e);
+        }
+        k = this._getYAxisLabelAlignment(f).textAlign;
+      }
+      "y" === e && ("start" === h ? A = "top" : "end" === h && (A = "bottom"));
+      const T = this._getLabelSizes();
+      for (x = 0, _ = l.length; x < _; ++x) {
+        y = l[x], v = y.label;
+        const t = a.setContext(this.getContext(x));
+        S = this.getPixelForTick(x) + a.labelOffset,
+          P = this._resolveTickFontOptions(x),
+          D = P.lineHeight,
+          O = s(v) ? v.length : 1;
+        const e = O / 2, i = t.color, n = t.textStrokeColor, h = t.textStrokeWidth;
+        let d, f = k;
+        if (
+          r
+            ? (w = S,
+              "inner" === k && (f = x === _ - 1
+                ? this.options.reverse ? "left" : "right"
+                : 0 === x
+                ? this.options.reverse ? "right" : "left"
+                : "center"),
+              C = "top" === o
+                ? "near" === c || 0 !== m
+                  ? -O * D + D / 2
+                  : "center" === c
+                  ? -T.highest.height / 2 - e * D + D
+                  : -T.highest.height + D / 2
+                : "near" === c || 0 !== m
+                ? D / 2
+                : "center" === c
+                ? T.highest.height / 2 - e * D
+                : T.highest.height - O * D,
+              u && (C *= -1))
+            : (M = S, C = (1 - O) * D / 2), t.showLabelBackdrop
+        ) {
+          const e = pi(t.backdropPadding), i = T.heights[x], s = T.widths[x];
+          let n = M + C - e.top, o = w - e.left;
+          switch (A) {
+            case "middle":
+              n -= i / 2;
+              break;
+            case "bottom":
+              n -= i;
+          }
+          switch (k) {
+            case "center":
+              o -= s / 2;
+              break;
+            case "right":
+              o -= s;
+          }
+          d = { left: o, top: n, width: s + e.width, height: i + e.height, color: t.backdropColor };
+        }
+        b.push({
+          rotation: m,
+          label: v,
+          font: P,
+          color: i,
+          strokeColor: n,
+          strokeWidth: h,
+          textOffset: C,
+          textAlign: f,
+          textBaseline: A,
+          translation: [w, M],
+          backdrop: d,
+        });
+      }
+      return b;
+    }
+    _getXAxisLabelAlignment() {
+      const { position: t, ticks: e } = this.options;
+      if (-H(this.labelRotation)) return "top" === t ? "left" : "right";
+      let i = "center";
+      return "start" === e.align ? i = "left" : "end" === e.align ? i = "right" : "inner" === e.align && (i = "inner"),
+        i;
+    }
+    _getYAxisLabelAlignment(t) {
+      const { position: e, ticks: { crossAlign: i, mirror: s, padding: n } } = this.options,
+        o = t + n,
+        a = this._getLabelSizes().widest.width;
+      let r, l;
+      return "left" === e
+        ? s
+          ? (l = this.right + n,
+            "near" === i ? r = "left" : "center" === i ? (r = "center", l += a / 2) : (r = "right", l += a))
+          : (l = this.right - o,
+            "near" === i ? r = "right" : "center" === i ? (r = "center", l -= a / 2) : (r = "left", l = this.left))
+        : "right" === e
+        ? s
+          ? (l = this.left + n,
+            "near" === i ? r = "right" : "center" === i ? (r = "center", l -= a / 2) : (r = "left", l -= a))
+          : (l = this.left + o,
+            "near" === i ? r = "left" : "center" === i ? (r = "center", l += a / 2) : (r = "right", l = this.right))
+        : r = "right",
+        { textAlign: r, x: l };
+    }
+    _computeLabelArea() {
+      if (this.options.ticks.mirror) return;
+      const t = this.chart, e = this.options.position;
+      return "left" === e || "right" === e
+        ? { top: 0, left: this.left, bottom: t.height, right: this.right }
+        : "top" === e || "bottom" === e
+        ? { top: this.top, left: 0, bottom: this.bottom, right: t.width }
+        : void 0;
+    }
+    drawBackground() {
+      const { ctx: t, options: { backgroundColor: e }, left: i, top: s, width: n, height: o } = this;
+      e && (t.save(), t.fillStyle = e, t.fillRect(i, s, n, o), t.restore());
+    }
+    getLineWidthForValue(t) {
+      const e = this.options.grid;
+      if (!this._isVisible() || !e.display) return 0;
+      const i = this.ticks.findIndex(e => e.value === t);
+      if (i >= 0) return e.setContext(this.getContext(i)).lineWidth;
+      return 0;
+    }
+    drawGrid(t) {
+      const e = this.options.grid,
+        i = this.ctx,
+        s = this._gridLineItems || (this._gridLineItems = this._computeGridLineItems(t));
+      let n, o;
+      const a = (t, e, s) => {
+        s.width && s.color
+          && (i.save(),
+            i.lineWidth = s.width,
+            i.strokeStyle = s.color,
+            i.setLineDash(s.borderDash || []),
+            i.lineDashOffset = s.borderDashOffset,
+            i.beginPath(),
+            i.moveTo(t.x, t.y),
+            i.lineTo(e.x, e.y),
+            i.stroke(),
+            i.restore());
+      };
+      if (e.display) {
+        for (n = 0, o = s.length; n < o; ++n) {
+          const t = s[n];
+          e.drawOnChartArea && a({ x: t.x1, y: t.y1 }, { x: t.x2, y: t.y2 }, t),
+            e.drawTicks
+            && a({ x: t.tx1, y: t.ty1 }, { x: t.tx2, y: t.ty2 }, {
+              color: t.tickColor,
+              width: t.tickWidth,
+              borderDash: t.tickBorderDash,
+              borderDashOffset: t.tickBorderDashOffset,
+            });
+        }
+      }
+    }
+    drawBorder() {
+      const { chart: t, ctx: e, options: { grid: i } } = this,
+        s = i.setContext(this.getContext()),
+        n = i.drawBorder ? s.borderWidth : 0;
+      if (!n) return;
+      const o = i.setContext(this.getContext(0)).lineWidth, a = this._borderValue;
+      let r, l, h, c;
+      this.isHorizontal()
+        ? (r = ve(t, this.left, n) - n / 2, l = ve(t, this.right, o) + o / 2, h = c = a)
+        : (h = ve(t, this.top, n) - n / 2, c = ve(t, this.bottom, o) + o / 2, r = l = a),
+        e.save(),
+        e.lineWidth = s.borderWidth,
+        e.strokeStyle = s.borderColor,
+        e.beginPath(),
+        e.moveTo(r, h),
+        e.lineTo(l, c),
+        e.stroke(),
+        e.restore();
+    }
+    drawLabels(t) {
+      if (!this.options.ticks.display) return;
+      const e = this.ctx, i = this._computeLabelArea();
+      i && Pe(e, i);
+      const s = this._labelItems || (this._labelItems = this._computeLabelItems(t));
+      let n, o;
+      for (n = 0, o = s.length; n < o; ++n) {
+        const t = s[n], i = t.font, o = t.label;
+        t.backdrop
+        && (e.fillStyle = t.backdrop.color,
+          e.fillRect(t.backdrop.left, t.backdrop.top, t.backdrop.width, t.backdrop.height)),
+          Ae(e, o, 0, t.textOffset, i, t);
+      }
+      i && De(e);
+    }
+    drawTitle() {
+      const { ctx: t, options: { position: e, title: i, reverse: o } } = this;
+      if (!i.display) return;
+      const a = mi(i.font), r = pi(i.padding), l = i.align;
+      let h = a.lineHeight / 2;
+      "bottom" === e || "center" === e || n(e)
+        ? (h += r.bottom, s(i.text) && (h += a.lineHeight * (i.text.length - 1)))
+        : h += r.top;
+      const { titleX: c, titleY: d, maxWidth: u, rotation: f } = function(t, e, i, s) {
+        const { top: o, left: a, bottom: r, right: l, chart: h } = t, { chartArea: c, scales: d } = h;
+        let u, f, g, p = 0;
+        const m = r - o, b = l - a;
+        if (t.isHorizontal()) {
+          if (f = ut(s, a, l), n(i)) {
+            const t = Object.keys(i)[0], s = i[t];
+            g = d[t].getPixelForValue(s) + m - e;
+          } else g = "center" === i ? (c.bottom + c.top) / 2 + m - e : Vs(t, i, e);
+          u = l - a;
+        } else {
+          if (n(i)) {
+            const t = Object.keys(i)[0], s = i[t];
+            f = d[t].getPixelForValue(s) - b + e;
+          } else f = "center" === i ? (c.left + c.right) / 2 - b + e : Vs(t, i, e);
+          g = ut(s, r, o), p = "left" === i ? -L : L;
+        }
+        return { titleX: f, titleY: g, maxWidth: u, rotation: p };
+      }(this, h, e, l);
+      Ae(t, i.text, 0, 0, a, {
+        color: i.color,
+        maxWidth: u,
+        rotation: f,
+        textAlign: Hs(l, e, o),
+        textBaseline: "middle",
+        translation: [c, d],
+      });
+    }
+    draw(t) {
+      this._isVisible()
+        && (this.drawBackground(), this.drawGrid(t), this.drawBorder(), this.drawTitle(), this.drawLabels(t));
+    }
+    _layers() {
+      const t = this.options, e = t.ticks && t.ticks.z || 0, i = r(t.grid && t.grid.z, -1);
+      return this._isVisible() && this.draw === $s.prototype.draw
+        ? [{
+          z: i,
+          draw: t => {
+            this.drawBackground(), this.drawGrid(t), this.drawTitle();
+          },
+        }, {
+          z: i + 1,
+          draw: () => {
+            this.drawBorder();
+          },
+        }, {
+          z: e,
+          draw: t => {
+            this.drawLabels(t);
+          },
+        }]
+        : [{
+          z: e,
+          draw: t => {
+            this.draw(t);
+          },
+        }];
+    }
+    getMatchingVisibleMetas(t) {
+      const e = this.chart.getSortedVisibleDatasetMetas(), i = this.axis + "AxisID", s = [];
+      let n, o;
+      for (n = 0, o = e.length; n < o; ++n) {
+        const o = e[n];
+        o[i] !== this.id || t && o.type !== t || s.push(o);
+      }
+      return s;
+    }
+    _resolveTickFontOptions(t) {
+      return mi(this.options.ticks.setContext(this.getContext(t)).font);
+    }
+    _maxDigits() {
+      const t = this._resolveTickFontOptions(0).lineHeight;
+      return (this.isHorizontal() ? this.width : this.height) / t;
+    }
+  }
+  class Ys {
+    constructor(t, e, i) {
+      this.type = t, this.scope = e, this.override = i, this.items = Object.create(null);
+    }
+    isForType(t) {
+      return Object.prototype.isPrototypeOf.call(this.type.prototype, t.prototype);
+    }
+    register(t) {
+      const e = Object.getPrototypeOf(t);
+      let i;
+      (function(t) {
+        return "id" in t && "defaults" in t;
+      })(e) && (i = this.register(e));
+      const s = this.items, n = t.id, o = this.scope + "." + n;
+      if (!n) throw new Error("class does not have id: " + t);
+      return n in s || (s[n] = t,
+        function(t, e, i) {
+          const s = m(Object.create(null), [i ? ne.get(i) : {}, ne.get(e), t.defaults]);
+          ne.set(e, s),
+            t.defaultRoutes && function(t, e) {
+              Object.keys(e).forEach(i => {
+                const s = i.split("."),
+                  n = s.pop(),
+                  o = [t].concat(s).join("."),
+                  a = e[i].split("."),
+                  r = a.pop(),
+                  l = a.join(".");
+                ne.route(o, n, l, r);
+              });
+            }(e, t.defaultRoutes);
+          t.descriptors && ne.describe(e, t.descriptors);
+        }(t, o, i),
+        this.override && ne.override(t.id, t.overrides)),
+        o;
+    }
+    get(t) {
+      return this.items[t];
+    }
+    unregister(t) {
+      const e = this.items, i = t.id, s = this.scope;
+      i in e && delete e[i], s && i in ne[s] && (delete ne[s][i], this.override && delete te[i]);
+    }
+  }
+  var Us = new class {
+    constructor() {
+      this.controllers = new Ys(Ls, "datasets", !0),
+        this.elements = new Ys(Es, "elements"),
+        this.plugins = new Ys(Object, "plugins"),
+        this.scales = new Ys($s, "scales"),
+        this._typedRegistries = [this.controllers, this.scales, this.elements];
+    }
+    add(...t) {
+      this._each("register", t);
+    }
+    remove(...t) {
+      this._each("unregister", t);
+    }
+    addControllers(...t) {
+      this._each("register", t, this.controllers);
+    }
+    addElements(...t) {
+      this._each("register", t, this.elements);
+    }
+    addPlugins(...t) {
+      this._each("register", t, this.plugins);
+    }
+    addScales(...t) {
+      this._each("register", t, this.scales);
+    }
+    getController(t) {
+      return this._get(t, this.controllers, "controller");
+    }
+    getElement(t) {
+      return this._get(t, this.elements, "element");
+    }
+    getPlugin(t) {
+      return this._get(t, this.plugins, "plugin");
+    }
+    getScale(t) {
+      return this._get(t, this.scales, "scale");
+    }
+    removeControllers(...t) {
+      this._each("unregister", t, this.controllers);
+    }
+    removeElements(...t) {
+      this._each("unregister", t, this.elements);
+    }
+    removePlugins(...t) {
+      this._each("unregister", t, this.plugins);
+    }
+    removeScales(...t) {
+      this._each("unregister", t, this.scales);
+    }
+    _each(t, e, i) {
+      [...e].forEach(e => {
+        const s = i || this._getRegistryForType(e);
+        i || s.isForType(e) || s === this.plugins && e.id ? this._exec(t, s, e) : d(e, e => {
+          const s = i || this._getRegistryForType(e);
+          this._exec(t, s, e);
+        });
+      });
+    }
+    _exec(t, e, i) {
+      const s = w(t);
+      c(i["before" + s], [], i), e[t](i), c(i["after" + s], [], i);
+    }
+    _getRegistryForType(t) {
+      for (let e = 0; e < this._typedRegistries.length; e++) {
+        const i = this._typedRegistries[e];
+        if (i.isForType(t)) return i;
+      }
+      return this.plugins;
+    }
+    _get(t, e, i) {
+      const s = e.get(t);
+      if (void 0 === s) throw new Error("\"" + t + "\" is not a registered " + i + ".");
+      return s;
+    }
+  }();
+  class Xs {
+    constructor() {
+      this._init = [];
+    }
+    notify(t, e, i, s) {
+      "beforeInit" === e && (this._init = this._createDescriptors(t, !0), this._notify(this._init, t, "install"));
+      const n = s ? this._descriptors(t).filter(s) : this._descriptors(t), o = this._notify(n, t, e, i);
+      return "afterDestroy" === e && (this._notify(n, t, "stop"), this._notify(this._init, t, "uninstall")), o;
+    }
+    _notify(t, e, i, s) {
+      s = s || {};
+      for (const n of t) {
+        const t = n.plugin;
+        if (!1 === c(t[i], [e, s, n.options], t) && s.cancelable) return !1;
+      }
+      return !0;
+    }
+    invalidate() {
+      i(this._cache) || (this._oldCache = this._cache, this._cache = void 0);
+    }
+    _descriptors(t) {
+      if (this._cache) return this._cache;
+      const e = this._cache = this._createDescriptors(t);
+      return this._notifyStateChanges(t), e;
+    }
+    _createDescriptors(t, e) {
+      const i = t && t.config,
+        s = r(i.options && i.options.plugins, {}),
+        n = function(t) {
+          const e = {}, i = [], s = Object.keys(Us.plugins.items);
+          for (let t = 0; t < s.length; t++) i.push(Us.getPlugin(s[t]));
+          const n = t.plugins || [];
+          for (let t = 0; t < n.length; t++) {
+            const s = n[t];
+            -1 === i.indexOf(s) && (i.push(s), e[s.id] = !0);
+          }
+          return { plugins: i, localIds: e };
+        }(i);
+      return !1 !== s || e
+        ? function(t, { plugins: e, localIds: i }, s, n) {
+          const o = [], a = t.getContext();
+          for (const r of e) {
+            const e = r.id, l = qs(s[e], n);
+            null !== l && o.push({ plugin: r, options: Ks(t.config, { plugin: r, local: i[e] }, l, a) });
+          }
+          return o;
+        }(t, n, s, e)
+        : [];
+    }
+    _notifyStateChanges(t) {
+      const e = this._oldCache || [],
+        i = this._cache,
+        s = (t, e) => t.filter(t => !e.some(e => t.plugin.id === e.plugin.id));
+      this._notify(s(e, i), t, "stop"), this._notify(s(i, e), t, "start");
+    }
+  }
+  function qs(t, e) {
+    return e || !1 !== t ? !0 === t ? {} : t : null;
+  }
+  function Ks(t, { plugin: e, local: i }, s, n) {
+    const o = t.pluginScopeKeys(e), a = t.getOptionScopes(s, o);
+    return i && e.defaults && a.push(e.defaults),
+      t.createResolver(a, n, [""], { scriptable: !1, indexable: !1, allKeys: !0 });
+  }
+  function Gs(t, e) {
+    const i = ne.datasets[t] || {};
+    return ((e.datasets || {})[t] || {}).indexAxis || e.indexAxis || i.indexAxis || "x";
+  }
+  function Zs(t, e) {
+    return "x" === t || "y" === t
+      ? t
+      : e.axis || ("top" === (i = e.position) || "bottom" === i ? "x" : "left" === i || "right" === i ? "y" : void 0)
+        || t.charAt(0).toLowerCase();
+    var i;
+  }
+  function Js(t) {
+    const e = t.options || (t.options = {});
+    e.plugins = r(e.plugins, {}),
+      e.scales = function(t, e) {
+        const i = te[t.type] || { scales: {} },
+          s = e.scales || {},
+          o = Gs(t.type, e),
+          a = Object.create(null),
+          r = Object.create(null);
+        return Object.keys(s).forEach(t => {
+          const e = s[t];
+          if (!n(e)) return console.error(`Invalid scale configuration for scale: ${t}`);
+          if (e._proxy) return console.warn(`Ignoring resolver passed as options for scale: ${t}`);
+          const l = Zs(t, e),
+            h = function(t, e) {
+              return t === e ? "_index_" : "_value_";
+            }(l, o),
+            c = i.scales || {};
+          a[l] = a[l] || t, r[t] = b(Object.create(null), [{ axis: l }, e, c[l], c[h]]);
+        }),
+          t.data.datasets.forEach(i => {
+            const n = i.type || t.type, o = i.indexAxis || Gs(n, e), l = (te[n] || {}).scales || {};
+            Object.keys(l).forEach(t => {
+              const e = function(t, e) {
+                  let i = t;
+                  return "_index_" === t ? i = e : "_value_" === t && (i = "x" === e ? "y" : "x"), i;
+                }(t, o),
+                n = i[e + "AxisID"] || a[e] || e;
+              r[n] = r[n] || Object.create(null), b(r[n], [{ axis: e }, s[n], l[t]]);
+            });
+          }),
+          Object.keys(r).forEach(t => {
+            const e = r[t];
+            b(e, [ne.scales[e.type], ne.scale]);
+          }),
+          r;
+      }(t, e);
+  }
+  function Qs(t) {
+    return (t = t || {}).datasets = t.datasets || [], t.labels = t.labels || [], t;
+  }
+  const tn = new Map(), en = new Set();
+  function sn(t, e) {
+    let i = tn.get(t);
+    return i || (i = e(), tn.set(t, i), en.add(i)), i;
+  }
+  const nn = (t, e, i) => {
+    const s = y(e, i);
+    void 0 !== s && t.add(s);
+  };
+  class on {
+    constructor(t) {
+      this._config = function(t) {
+        return (t = t || {}).data = Qs(t.data), Js(t), t;
+      }(t),
+        this._scopeCache = new Map(),
+        this._resolverCache = new Map();
+    }
+    get platform() {
+      return this._config.platform;
+    }
+    get type() {
+      return this._config.type;
+    }
+    set type(t) {
+      this._config.type = t;
+    }
+    get data() {
+      return this._config.data;
+    }
+    set data(t) {
+      this._config.data = Qs(t);
+    }
+    get options() {
+      return this._config.options;
+    }
+    set options(t) {
+      this._config.options = t;
+    }
+    get plugins() {
+      return this._config.plugins;
+    }
+    update() {
+      const t = this._config;
+      this.clearCache(), Js(t);
+    }
+    clearCache() {
+      this._scopeCache.clear(), this._resolverCache.clear();
+    }
+    datasetScopeKeys(t) {
+      return sn(t, () => [[`datasets.${t}`, ""]]);
+    }
+    datasetAnimationScopeKeys(t, e) {
+      return sn(
+        `${t}.transition.${e}`,
+        () => [[`datasets.${t}.transitions.${e}`, `transitions.${e}`], [`datasets.${t}`, ""]],
+      );
+    }
+    datasetElementScopeKeys(t, e) {
+      return sn(`${t}-${e}`, () => [[`datasets.${t}.elements.${e}`, `datasets.${t}`, `elements.${e}`, ""]]);
+    }
+    pluginScopeKeys(t) {
+      const e = t.id;
+      return sn(`${this.type}-plugin-${e}`, () => [[`plugins.${e}`, ...t.additionalOptionScopes || []]]);
+    }
+    _cachedScopes(t, e) {
+      const i = this._scopeCache;
+      let s = i.get(t);
+      return s && !e || (s = new Map(), i.set(t, s)), s;
+    }
+    getOptionScopes(t, e, i) {
+      const { options: s, type: n } = this, o = this._cachedScopes(t, i), a = o.get(e);
+      if (a) return a;
+      const r = new Set();
+      e.forEach(e => {
+        t && (r.add(t), e.forEach(e => nn(r, t, e))),
+          e.forEach(t => nn(r, s, t)),
+          e.forEach(t => nn(r, te[n] || {}, t)),
+          e.forEach(t => nn(r, ne, t)),
+          e.forEach(t => nn(r, ee, t));
+      });
+      const l = Array.from(r);
+      return 0 === l.length && l.push(Object.create(null)), en.has(e) && o.set(e, l), l;
+    }
+    chartOptionScopes() {
+      const { options: t, type: e } = this;
+      return [t, te[e] || {}, ne.datasets[e] || {}, { type: e }, ne, ee];
+    }
+    resolveNamedOptions(t, e, i, n = [""]) {
+      const o = { $shared: !0 }, { resolver: a, subPrefixes: r } = an(this._resolverCache, t, n);
+      let l = a;
+      if (
+        function(t, e) {
+          const { isScriptable: i, isIndexable: n } = Ie(t);
+          for (const o of e) {
+            const e = i(o), a = n(o), r = (a || e) && t[o];
+            if (e && (k(r) || rn(r)) || a && s(r)) return !0;
+          }
+          return !1;
+        }(a, e)
+      ) {
+        o.$shared = !1;
+        l = Re(a, i = k(i) ? i() : i, this.createResolver(t, i, r));
+      }
+      for (const t of e) o[t] = l[t];
+      return o;
+    }
+    createResolver(t, e, i = [""], s) {
+      const { resolver: o } = an(this._resolverCache, t, i);
+      return n(e) ? Re(o, e, void 0, s) : o;
+    }
+  }
+  function an(t, e, i) {
+    let s = t.get(e);
+    s || (s = new Map(), t.set(e, s));
+    const n = i.join();
+    let o = s.get(n);
+    if (!o) o = { resolver: Ee(e, i), subPrefixes: i.filter(t => !t.toLowerCase().includes("hover")) }, s.set(n, o);
+    return o;
+  }
+  const rn = t => n(t) && Object.getOwnPropertyNames(t).reduce((e, i) => e || k(t[i]), !1);
+  const ln = ["top", "bottom", "left", "right", "chartArea"];
+  function hn(t, e) {
+    return "top" === t || "bottom" === t || -1 === ln.indexOf(t) && "x" === e;
+  }
+  function cn(t, e) {
+    return function(i, s) {
+      return i[t] === s[t] ? i[e] - s[e] : i[t] - s[t];
+    };
+  }
+  function dn(t) {
+    const e = t.chart, i = e.options.animation;
+    e.notifyPlugins("afterRender"), c(i && i.onComplete, [t], e);
+  }
+  function un(t) {
+    const e = t.chart, i = e.options.animation;
+    c(i && i.onProgress, [t], e);
+  }
+  function fn(t) {
+    return oe() && "string" == typeof t ? t = document.getElementById(t) : t && t.length && (t = t[0]),
+      t && t.canvas && (t = t.canvas),
+      t;
+  }
+  const gn = {},
+    pn = t => {
+      const e = fn(t);
+      return Object.values(gn).filter(t => t.canvas === e).pop();
+    };
+  function mn(t, e, i) {
+    const s = Object.keys(t);
+    for (const n of s) {
+      const s = +n;
+      if (s >= e) {
+        const o = t[n];
+        delete t[n], (i > 0 || s > e) && (t[s + i] = o);
+      }
+    }
+  }
+  class bn {
+    constructor(t, i) {
+      const s = this.config = new on(i), n = fn(t), o = pn(n);
+      if (o) {
+        throw new Error(
+          "Canvas is already in use. Chart with ID '" + o.id + "' must be destroyed before the canvas with ID '"
+            + o.canvas.id + "' can be reused.",
+        );
+      }
+      const a = s.createResolver(s.chartOptionScopes(), this.getContext());
+      this.platform = new (s.platform || gs(n))(), this.platform.updateConfig(s);
+      const r = this.platform.acquireContext(n, a.aspectRatio), l = r && r.canvas, h = l && l.height, c = l && l.width;
+      this.id = e(),
+        this.ctx = r,
+        this.canvas = l,
+        this.width = c,
+        this.height = h,
+        this._options = a,
+        this._aspectRatio = this.aspectRatio,
+        this._layers = [],
+        this._metasets = [],
+        this._stacks = void 0,
+        this.boxes = [],
+        this.currentDevicePixelRatio = void 0,
+        this.chartArea = void 0,
+        this._active = [],
+        this._lastEvent = void 0,
+        this._listeners = {},
+        this._responsiveListeners = void 0,
+        this._sortedMetasets = [],
+        this.scales = {},
+        this._plugins = new Xs(),
+        this.$proxies = {},
+        this._hiddenIndices = {},
+        this.attached = !1,
+        this._animationsDisabled = void 0,
+        this.$context = void 0,
+        this._doResize = ct(t => this.update(t), a.resizeDelay || 0),
+        this._dataChanges = [],
+        gn[this.id] = this,
+        r && l
+          ? (mt.listen(this, "complete", dn),
+            mt.listen(this, "progress", un),
+            this._initialize(),
+            this.attached && this.update())
+          : console.error("Failed to create chart: can't acquire context from the given item");
+    }
+    get aspectRatio() {
+      const { options: { aspectRatio: t, maintainAspectRatio: e }, width: s, height: n, _aspectRatio: o } = this;
+      return i(t) ? e && o ? o : n ? s / n : null : t;
+    }
+    get data() {
+      return this.config.data;
+    }
+    set data(t) {
+      this.config.data = t;
+    }
+    get options() {
+      return this._options;
+    }
+    set options(t) {
+      this.config.options = t;
+    }
+    _initialize() {
+      return this.notifyPlugins("beforeInit"),
+        this.options.responsive ? this.resize() : pe(this, this.options.devicePixelRatio),
+        this.bindEvents(),
+        this.notifyPlugins("afterInit"),
+        this;
+    }
+    clear() {
+      return we(this.canvas, this.ctx), this;
+    }
+    stop() {
+      return mt.stop(this), this;
+    }
+    resize(t, e) {
+      mt.running(this) ? this._resizeBeforeDraw = { width: t, height: e } : this._resize(t, e);
+    }
+    _resize(t, e) {
+      const i = this.options,
+        s = this.canvas,
+        n = i.maintainAspectRatio && this.aspectRatio,
+        o = this.platform.getMaximumSize(s, t, e, n),
+        a = i.devicePixelRatio || this.platform.getDevicePixelRatio(),
+        r = this.width ? "resize" : "attach";
+      this.width = o.width,
+        this.height = o.height,
+        this._aspectRatio = this.aspectRatio,
+        pe(this, a, !0)
+        && (this.notifyPlugins("resize", { size: o }),
+          c(i.onResize, [this, o], this),
+          this.attached && this._doResize(r) && this.render());
+    }
+    ensureScalesHaveIDs() {
+      d(this.options.scales || {}, (t, e) => {
+        t.id = e;
+      });
+    }
+    buildOrUpdateScales() {
+      const t = this.options, e = t.scales, i = this.scales, s = Object.keys(i).reduce((t, e) => (t[e] = !1, t), {});
+      let n = [];
+      e && (n = n.concat(
+        Object.keys(e).map(t => {
+          const i = e[t], s = Zs(t, i), n = "r" === s, o = "x" === s;
+          return {
+            options: i,
+            dposition: n ? "chartArea" : o ? "bottom" : "left",
+            dtype: n ? "radialLinear" : o ? "category" : "linear",
+          };
+        }),
+      )),
+        d(n, e => {
+          const n = e.options, o = n.id, a = Zs(o, n), l = r(n.type, e.dtype);
+          void 0 !== n.position && hn(n.position, a) === hn(e.dposition) || (n.position = e.dposition), s[o] = !0;
+          let h = null;
+          if (o in i && i[o].type === l) h = i[o];
+          else h = new (Us.getScale(l))({ id: o, type: l, ctx: this.ctx, chart: this }), i[h.id] = h;
+          h.init(n, t);
+        }),
+        d(s, (t, e) => {
+          t || delete i[e];
+        }),
+        d(i, t => {
+          Zi.configure(this, t, t.options), Zi.addBox(this, t);
+        });
+    }
+    _updateMetasets() {
+      const t = this._metasets, e = this.data.datasets.length, i = t.length;
+      if (t.sort((t, e) => t.index - e.index), i > e) {
+        for (let t = e; t < i; ++t) this._destroyDatasetMeta(t);
+        t.splice(e, i - e);
+      }
+      this._sortedMetasets = t.slice(0).sort(cn("order", "index"));
+    }
+    _removeUnreferencedMetasets() {
+      const { _metasets: t, data: { datasets: e } } = this;
+      t.length > e.length && delete this._stacks,
+        t.forEach((t, i) => {
+          0 === e.filter(e => e === t._dataset).length && this._destroyDatasetMeta(i);
+        });
+    }
+    buildOrUpdateControllers() {
+      const t = [], e = this.data.datasets;
+      let i, s;
+      for (this._removeUnreferencedMetasets(), i = 0, s = e.length; i < s; i++) {
+        const s = e[i];
+        let n = this.getDatasetMeta(i);
+        const o = s.type || this.config.type;
+        if (
+          n.type && n.type !== o && (this._destroyDatasetMeta(i), n = this.getDatasetMeta(i)),
+            n.type = o,
+            n.indexAxis = s.indexAxis || Gs(o, this.options),
+            n.order = s.order || 0,
+            n.index = i,
+            n.label = "" + s.label,
+            n.visible = this.isDatasetVisible(i),
+            n.controller
+        ) n.controller.updateIndex(i), n.controller.linkScales();
+        else {
+          const e = Us.getController(o), { datasetElementType: s, dataElementType: a } = ne.datasets[o];
+          Object.assign(e.prototype, { dataElementType: Us.getElement(a), datasetElementType: s && Us.getElement(s) }),
+            n.controller = new e(this, i),
+            t.push(n.controller);
+        }
+      }
+      return this._updateMetasets(), t;
+    }
+    _resetElements() {
+      d(this.data.datasets, (t, e) => {
+        this.getDatasetMeta(e).controller.reset();
+      }, this);
+    }
+    reset() {
+      this._resetElements(), this.notifyPlugins("reset");
+    }
+    update(t) {
+      const e = this.config;
+      e.update();
+      const i = this._options = e.createResolver(e.chartOptionScopes(), this.getContext()),
+        s = this._animationsDisabled = !i.animation;
+      if (
+        this._updateScales(),
+          this._checkEventBindings(),
+          this._updateHiddenIndices(),
+          this._plugins.invalidate(),
+          !1 === this.notifyPlugins("beforeUpdate", { mode: t, cancelable: !0 })
+      ) return;
+      const n = this.buildOrUpdateControllers();
+      this.notifyPlugins("beforeElementsUpdate");
+      let o = 0;
+      for (let t = 0, e = this.data.datasets.length; t < e; t++) {
+        const { controller: e } = this.getDatasetMeta(t), i = !s && -1 === n.indexOf(e);
+        e.buildOrUpdateElements(i), o = Math.max(+e.getMaxOverflow(), o);
+      }
+      o = this._minPadding = i.layout.autoPadding ? o : 0,
+        this._updateLayout(o),
+        s || d(n, t => {
+          t.reset();
+        }),
+        this._updateDatasets(t),
+        this.notifyPlugins("afterUpdate", { mode: t }),
+        this._layers.sort(cn("z", "_idx"));
+      const { _active: a, _lastEvent: r } = this;
+      r ? this._eventHandler(r, !0) : a.length && this._updateHoverStyles(a, a, !0), this.render();
+    }
+    _updateScales() {
+      d(this.scales, t => {
+        Zi.removeBox(this, t);
+      }),
+        this.ensureScalesHaveIDs(),
+        this.buildOrUpdateScales();
+    }
+    _checkEventBindings() {
+      const t = this.options, e = new Set(Object.keys(this._listeners)), i = new Set(t.events);
+      S(e, i) && !!this._responsiveListeners === t.responsive || (this.unbindEvents(), this.bindEvents());
+    }
+    _updateHiddenIndices() {
+      const { _hiddenIndices: t } = this, e = this._getUniformDataChanges() || [];
+      for (const { method: i, start: s, count: n } of e) mn(t, s, "_removeElements" === i ? -n : n);
+    }
+    _getUniformDataChanges() {
+      const t = this._dataChanges;
+      if (!t || !t.length) return;
+      this._dataChanges = [];
+      const e = this.data.datasets.length,
+        i = e => new Set(t.filter(t => t[0] === e).map((t, e) => e + "," + t.splice(1).join(","))),
+        s = i(0);
+      for (let t = 1; t < e; t++) if (!S(s, i(t))) return;
+      return Array.from(s).map(t => t.split(",")).map(t => ({ method: t[1], start: +t[2], count: +t[3] }));
+    }
+    _updateLayout(t) {
+      if (!1 === this.notifyPlugins("beforeLayout", { cancelable: !0 })) return;
+      Zi.update(this, this.width, this.height, t);
+      const e = this.chartArea, i = e.width <= 0 || e.height <= 0;
+      this._layers = [],
+        d(this.boxes, t => {
+          i && "chartArea" === t.position || (t.configure && t.configure(), this._layers.push(...t._layers()));
+        }, this),
+        this._layers.forEach((t, e) => {
+          t._idx = e;
+        }),
+        this.notifyPlugins("afterLayout");
+    }
+    _updateDatasets(t) {
+      if (!1 !== this.notifyPlugins("beforeDatasetsUpdate", { mode: t, cancelable: !0 })) {
+        for (let t = 0, e = this.data.datasets.length; t < e; ++t) this.getDatasetMeta(t).controller.configure();
+        for (let e = 0, i = this.data.datasets.length; e < i; ++e) {
+          this._updateDataset(e, k(t) ? t({ datasetIndex: e }) : t);
+        }
+        this.notifyPlugins("afterDatasetsUpdate", { mode: t });
+      }
+    }
+    _updateDataset(t, e) {
+      const i = this.getDatasetMeta(t), s = { meta: i, index: t, mode: e, cancelable: !0 };
+      !1 !== this.notifyPlugins("beforeDatasetUpdate", s)
+        && (i.controller._update(e), s.cancelable = !1, this.notifyPlugins("afterDatasetUpdate", s));
+    }
+    render() {
+      !1 !== this.notifyPlugins("beforeRender", { cancelable: !0 })
+        && (mt.has(this) ? this.attached && !mt.running(this) && mt.start(this) : (this.draw(), dn({ chart: this })));
+    }
+    draw() {
+      let t;
+      if (this._resizeBeforeDraw) {
+        const { width: t, height: e } = this._resizeBeforeDraw;
+        this._resize(t, e), this._resizeBeforeDraw = null;
+      }
+      if (this.clear(), this.width <= 0 || this.height <= 0) return;
+      if (!1 === this.notifyPlugins("beforeDraw", { cancelable: !0 })) return;
+      const e = this._layers;
+      for (t = 0; t < e.length && e[t].z <= 0; ++t) e[t].draw(this.chartArea);
+      for (this._drawDatasets(); t < e.length; ++t) e[t].draw(this.chartArea);
+      this.notifyPlugins("afterDraw");
+    }
+    _getSortedDatasetMetas(t) {
+      const e = this._sortedMetasets, i = [];
+      let s, n;
+      for (s = 0, n = e.length; s < n; ++s) {
+        const n = e[s];
+        t && !n.visible || i.push(n);
+      }
+      return i;
+    }
+    getSortedVisibleDatasetMetas() {
+      return this._getSortedDatasetMetas(!0);
+    }
+    _drawDatasets() {
+      if (!1 === this.notifyPlugins("beforeDatasetsDraw", { cancelable: !0 })) return;
+      const t = this.getSortedVisibleDatasetMetas();
+      for (let e = t.length - 1; e >= 0; --e) this._drawDataset(t[e]);
+      this.notifyPlugins("afterDatasetsDraw");
+    }
+    _drawDataset(t) {
+      const e = this.ctx,
+        i = t._clip,
+        s = !i.disabled,
+        n = this.chartArea,
+        o = { meta: t, index: t.index, cancelable: !0 };
+      !1 !== this.notifyPlugins("beforeDatasetDraw", o)
+        && (s
+          && Pe(e, {
+            left: !1 === i.left ? 0 : n.left - i.left,
+            right: !1 === i.right ? this.width : n.right + i.right,
+            top: !1 === i.top ? 0 : n.top - i.top,
+            bottom: !1 === i.bottom ? this.height : n.bottom + i.bottom,
+          }),
+          t.controller.draw(),
+          s && De(e),
+          o.cancelable = !1,
+          this.notifyPlugins("afterDatasetDraw", o));
+    }
+    isPointInArea(t) {
+      return Se(t, this.chartArea, this._minPadding);
+    }
+    getElementsAtEventForMode(t, e, i, s) {
+      const n = Vi.modes[e];
+      return "function" == typeof n ? n(this, t, i, s) : [];
+    }
+    getDatasetMeta(t) {
+      const e = this.data.datasets[t], i = this._metasets;
+      let s = i.filter(t => t && t._dataset === e).pop();
+      return s
+        || (s = {
+          type: null,
+          data: [],
+          dataset: null,
+          controller: null,
+          hidden: null,
+          xAxisID: null,
+          yAxisID: null,
+          order: e && e.order || 0,
+          index: t,
+          _dataset: e,
+          _parsed: [],
+          _sorted: !1,
+        },
+          i.push(s)),
+        s;
+    }
+    getContext() {
+      return this.$context || (this.$context = _i(null, { chart: this, type: "chart" }));
+    }
+    getVisibleDatasetCount() {
+      return this.getSortedVisibleDatasetMetas().length;
+    }
+    isDatasetVisible(t) {
+      const e = this.data.datasets[t];
+      if (!e) return !1;
+      const i = this.getDatasetMeta(t);
+      return "boolean" == typeof i.hidden ? !i.hidden : !e.hidden;
+    }
+    setDatasetVisibility(t, e) {
+      this.getDatasetMeta(t).hidden = !e;
+    }
+    toggleDataVisibility(t) {
+      this._hiddenIndices[t] = !this._hiddenIndices[t];
+    }
+    getDataVisibility(t) {
+      return !this._hiddenIndices[t];
+    }
+    _updateVisibility(t, e, i) {
+      const s = i ? "show" : "hide", n = this.getDatasetMeta(t), o = n.controller._resolveAnimations(void 0, s);
+      M(e)
+        ? (n.data[e].hidden = !i, this.update())
+        : (this.setDatasetVisibility(t, i),
+          o.update(n, { visible: i }),
+          this.update(e => e.datasetIndex === t ? s : void 0));
+    }
+    hide(t, e) {
+      this._updateVisibility(t, e, !1);
+    }
+    show(t, e) {
+      this._updateVisibility(t, e, !0);
+    }
+    _destroyDatasetMeta(t) {
+      const e = this._metasets[t];
+      e && e.controller && e.controller._destroy(), delete this._metasets[t];
+    }
+    _stop() {
+      let t, e;
+      for (this.stop(), mt.remove(this), t = 0, e = this.data.datasets.length; t < e; ++t) this._destroyDatasetMeta(t);
+    }
+    destroy() {
+      this.notifyPlugins("beforeDestroy");
+      const { canvas: t, ctx: e } = this;
+      this._stop(),
+        this.config.clearCache(),
+        t && (this.unbindEvents(), we(t, e), this.platform.releaseContext(e), this.canvas = null, this.ctx = null),
+        this.notifyPlugins("destroy"),
+        delete gn[this.id],
+        this.notifyPlugins("afterDestroy");
+    }
+    toBase64Image(...t) {
+      return this.canvas.toDataURL(...t);
+    }
+    bindEvents() {
+      this.bindUserEvents(), this.options.responsive ? this.bindResponsiveEvents() : this.attached = !0;
+    }
+    bindUserEvents() {
+      const t = this._listeners,
+        e = this.platform,
+        i = (i, s) => {
+          e.addEventListener(this, i, s), t[i] = s;
+        },
+        s = (t, e, i) => {
+          t.offsetX = e, t.offsetY = i, this._eventHandler(t);
+        };
+      d(this.options.events, t => i(t, s));
+    }
+    bindResponsiveEvents() {
+      this._responsiveListeners || (this._responsiveListeners = {});
+      const t = this._responsiveListeners,
+        e = this.platform,
+        i = (i, s) => {
+          e.addEventListener(this, i, s), t[i] = s;
+        },
+        s = (i, s) => {
+          t[i] && (e.removeEventListener(this, i, s), delete t[i]);
+        },
+        n = (t, e) => {
+          this.canvas && this.resize(t, e);
+        };
+      let o;
+      const a = () => {
+        s("attach", a), this.attached = !0, this.resize(), i("resize", n), i("detach", o);
+      };
+      o = () => {
+        this.attached = !1, s("resize", n), this._stop(), this._resize(0, 0), i("attach", a);
+      }, e.isAttached(this.canvas) ? a() : o();
+    }
+    unbindEvents() {
+      d(this._listeners, (t, e) => {
+        this.platform.removeEventListener(this, e, t);
+      }),
+        this._listeners = {},
+        d(this._responsiveListeners, (t, e) => {
+          this.platform.removeEventListener(this, e, t);
+        }),
+        this._responsiveListeners = void 0;
+    }
+    updateHoverStyle(t, e, i) {
+      const s = i ? "set" : "remove";
+      let n, o, a, r;
+      for (
+        "dataset" === e && (n = this.getDatasetMeta(t[0].datasetIndex), n.controller["_" + s + "DatasetHoverStyle"]()),
+          a = 0,
+          r = t.length;
+        a < r;
+        ++a
+      ) {
+        o = t[a];
+        const e = o && this.getDatasetMeta(o.datasetIndex).controller;
+        e && e[s + "HoverStyle"](o.element, o.datasetIndex, o.index);
+      }
+    }
+    getActiveElements() {
+      return this._active || [];
+    }
+    setActiveElements(t) {
+      const e = this._active || [],
+        i = t.map(({ datasetIndex: t, index: e }) => {
+          const i = this.getDatasetMeta(t);
+          if (!i) throw new Error("No dataset found at index " + t);
+          return { datasetIndex: t, element: i.data[e], index: e };
+        });
+      !u(i, e) && (this._active = i, this._lastEvent = null, this._updateHoverStyles(i, e));
+    }
+    notifyPlugins(t, e, i) {
+      return this._plugins.notify(this, t, e, i);
+    }
+    _updateHoverStyles(t, e, i) {
+      const s = this.options.hover,
+        n = (t, e) => t.filter(t => !e.some(e => t.datasetIndex === e.datasetIndex && t.index === e.index)),
+        o = n(e, t),
+        a = i ? t : n(t, e);
+      o.length && this.updateHoverStyle(o, s.mode, !1), a.length && s.mode && this.updateHoverStyle(a, s.mode, !0);
+    }
+    _eventHandler(t, e) {
+      const i = { event: t, replay: e, cancelable: !0, inChartArea: this.isPointInArea(t) },
+        s = e => (e.options.events || this.options.events).includes(t.native.type);
+      if (!1 === this.notifyPlugins("beforeEvent", i, s)) return;
+      const n = this._handleEvent(t, e, i.inChartArea);
+      return i.cancelable = !1, this.notifyPlugins("afterEvent", i, s), (n || i.changed) && this.render(), this;
+    }
+    _handleEvent(t, e, i) {
+      const { _active: s = [], options: n } = this,
+        o = e,
+        a = this._getActiveElements(t, s, i, o),
+        r = P(t),
+        l = function(t, e, i, s) {
+          return i && "mouseout" !== t.type ? s ? e : t : null;
+        }(t, this._lastEvent, i, r);
+      i && (this._lastEvent = null, c(n.onHover, [t, a, this], this), r && c(n.onClick, [t, a, this], this));
+      const h = !u(a, s);
+      return (h || e) && (this._active = a, this._updateHoverStyles(a, s, e)), this._lastEvent = l, h;
+    }
+    _getActiveElements(t, e, i, s) {
+      if ("mouseout" === t.type) return [];
+      if (!i) return e;
+      const n = this.options.hover;
+      return this.getElementsAtEventForMode(t, n.mode, n, s);
+    }
+  }
+  const xn = () => d(bn.instances, t => t._plugins.invalidate()), _n = !0;
+  function yn() {
+    throw new Error("This method is not implemented: Check that a complete date adapter is provided.");
+  }
+  Object.defineProperties(bn, {
+    defaults: { enumerable: _n, value: ne },
+    instances: { enumerable: _n, value: gn },
+    overrides: { enumerable: _n, value: te },
+    registry: { enumerable: _n, value: Us },
+    version: { enumerable: _n, value: "3.9.0" },
+    getChart: { enumerable: _n, value: pn },
+    register: {
+      enumerable: _n,
+      value: (...t) => {
+        Us.add(...t), xn();
+      },
+    },
+    unregister: {
+      enumerable: _n,
+      value: (...t) => {
+        Us.remove(...t), xn();
+      },
+    },
+  });
+  class vn {
+    constructor(t) {
+      this.options = t || {};
+    }
+    init(t) {}
+    formats() {
+      return yn();
+    }
+    parse(t, e) {
+      return yn();
+    }
+    format(t, e) {
+      return yn();
+    }
+    add(t, e, i) {
+      return yn();
+    }
+    diff(t, e, i) {
+      return yn();
+    }
+    startOf(t, e, i) {
+      return yn();
+    }
+    endOf(t, e) {
+      return yn();
+    }
+  }
+  vn.override = function(t) {
+    Object.assign(vn.prototype, t);
+  };
+  var wn = { _date: vn };
+  function Mn(t) {
+    const e = t.iScale,
+      i = function(t, e) {
+        if (!t._cache.$bar) {
+          const i = t.getMatchingVisibleMetas(e);
+          let s = [];
+          for (let e = 0, n = i.length; e < n; e++) s = s.concat(i[e].controller.getAllParsedValues(t));
+          t._cache.$bar = rt(s.sort((t, e) => t - e));
+        }
+        return t._cache.$bar;
+      }(e, t.type);
+    let s, n, o, a, r = e._length;
+    const l = () => {
+      32767 !== o && -32768 !== o && (M(a) && (r = Math.min(r, Math.abs(o - a) || r)), a = o);
+    };
+    for (s = 0, n = i.length; s < n; ++s) o = e.getPixelForValue(i[s]), l();
+    for (a = void 0, s = 0, n = e.ticks.length; s < n; ++s) o = e.getPixelForTick(s), l();
+    return r;
+  }
+  function kn(t, e, i, n) {
+    return s(t)
+      ? function(t, e, i, s) {
+        const n = i.parse(t[0], s), o = i.parse(t[1], s), a = Math.min(n, o), r = Math.max(n, o);
+        let l = a, h = r;
+        Math.abs(a) > Math.abs(r) && (l = r, h = a),
+          e[i.axis] = h,
+          e._custom = { barStart: l, barEnd: h, start: n, end: o, min: a, max: r };
+      }(t, e, i, n)
+      : e[i.axis] = i.parse(t, n),
+      e;
+  }
+  function Sn(t, e, i, s) {
+    const n = t.iScale, o = t.vScale, a = n.getLabels(), r = n === o, l = [];
+    let h, c, d, u;
+    for (h = i, c = i + s; h < c; ++h) u = e[h], d = {}, d[n.axis] = r || n.parse(a[h], h), l.push(kn(u, d, o, h));
+    return l;
+  }
+  function Pn(t) {
+    return t && void 0 !== t.barStart && void 0 !== t.barEnd;
+  }
+  function Dn(t, e, i, s) {
+    let n = e.borderSkipped;
+    const o = {};
+    if (!n) return void (t.borderSkipped = o);
+    if (!0 === n) return void (t.borderSkipped = { top: !0, right: !0, bottom: !0, left: !0 });
+    const { start: a, end: r, reverse: l, top: h, bottom: c } = function(t) {
+      let e, i, s, n, o;
+      return t.horizontal ? (e = t.base > t.x, i = "left", s = "right") : (e = t.base < t.y, i = "bottom", s = "top"),
+        e ? (n = "end", o = "start") : (n = "start", o = "end"),
+        { start: i, end: s, reverse: e, top: n, bottom: o };
+    }(t);
+    "middle" === n && i
+    && (t.enableBorderRadius = !0,
+      (i._top || 0) === s ? n = h : (i._bottom || 0) === s ? n = c : (o[On(c, a, r, l)] = !0, n = h)),
+      o[On(n, a, r, l)] = !0,
+      t.borderSkipped = o;
+  }
+  function On(t, e, i, s) {
+    var n, o, a;
+    return s ? (a = i, t = Cn(t = (n = t) === (o = e) ? a : n === a ? o : n, i, e)) : t = Cn(t, e, i), t;
+  }
+  function Cn(t, e, i) {
+    return "start" === t ? e : "end" === t ? i : t;
+  }
+  function An(t, { inflateAmount: e }, i) {
+    t.inflateAmount = "auto" === e ? 1 === i ? .33 : 0 : e;
+  }
+  class Tn extends Ls {
+    parsePrimitiveData(t, e, i, s) {
+      return Sn(t, e, i, s);
+    }
+    parseArrayData(t, e, i, s) {
+      return Sn(t, e, i, s);
+    }
+    parseObjectData(t, e, i, s) {
+      const { iScale: n, vScale: o } = t,
+        { xAxisKey: a = "x", yAxisKey: r = "y" } = this._parsing,
+        l = "x" === n.axis ? a : r,
+        h = "x" === o.axis ? a : r,
+        c = [];
+      let d, u, f, g;
+      for (d = i, u = i + s; d < u; ++d) {
+        g = e[d], f = {}, f[n.axis] = n.parse(y(g, l), d), c.push(kn(y(g, h), f, o, d));
+      }
+      return c;
+    }
+    updateRangeFromParsed(t, e, i, s) {
+      super.updateRangeFromParsed(t, e, i, s);
+      const n = i._custom;
+      n && e === this._cachedMeta.vScale && (t.min = Math.min(t.min, n.min), t.max = Math.max(t.max, n.max));
+    }
+    getMaxOverflow() {
+      return 0;
+    }
+    getLabelAndValue(t) {
+      const e = this._cachedMeta,
+        { iScale: i, vScale: s } = e,
+        n = this.getParsed(t),
+        o = n._custom,
+        a = Pn(o) ? "[" + o.start + ", " + o.end + "]" : "" + s.getLabelForValue(n[s.axis]);
+      return { label: "" + i.getLabelForValue(n[i.axis]), value: a };
+    }
+    initialize() {
+      this.enableOptionSharing = !0, super.initialize();
+      this._cachedMeta.stack = this.getDataset().stack;
+    }
+    update(t) {
+      const e = this._cachedMeta;
+      this.updateElements(e.data, 0, e.data.length, t);
+    }
+    updateElements(t, e, s, n) {
+      const o = "reset" === n,
+        { index: a, _cachedMeta: { vScale: r } } = this,
+        l = r.getBasePixel(),
+        h = r.isHorizontal(),
+        c = this._getRuler(),
+        { sharedOptions: d, includeOptions: u } = this._getSharedOptions(e, n);
+      for (let f = e; f < e + s; f++) {
+        const e = this.getParsed(f),
+          s = o || i(e[r.axis]) ? { base: l, head: l } : this._calculateBarValuePixels(f),
+          g = this._calculateBarIndexPixels(f, c),
+          p = (e._stacks || {})[r.axis],
+          m = {
+            horizontal: h,
+            base: s.base,
+            enableBorderRadius: !p || Pn(e._custom) || a === p._top || a === p._bottom,
+            x: h ? s.head : g.center,
+            y: h ? g.center : s.head,
+            height: h ? g.size : Math.abs(s.size),
+            width: h ? Math.abs(s.size) : g.size,
+          };
+        u && (m.options = d || this.resolveDataElementOptions(f, t[f].active ? "active" : n));
+        const b = m.options || t[f].options;
+        Dn(m, b, p, a), An(m, b, c.ratio), this.updateElement(t[f], f, m, n);
+      }
+    }
+    _getStacks(t, e) {
+      const { iScale: s } = this._cachedMeta,
+        n = s.getMatchingVisibleMetas(this._type).filter(t => t.controller.options.grouped),
+        o = s.options.stacked,
+        a = [],
+        r = t => {
+          const s = t.controller.getParsed(e), n = s && s[t.vScale.axis];
+          if (i(n) || isNaN(n)) return !0;
+        };
+      for (const i of n) {
+        if (
+          (void 0 === e || !r(i))
+          && ((!1 === o || -1 === a.indexOf(i.stack) || void 0 === o && void 0 === i.stack) && a.push(i.stack),
+            i.index === t)
+        ) break;
+      }
+      return a.length || a.push(void 0), a;
+    }
+    _getStackCount(t) {
+      return this._getStacks(void 0, t).length;
+    }
+    _getStackIndex(t, e, i) {
+      const s = this._getStacks(t, i), n = void 0 !== e ? s.indexOf(e) : -1;
+      return -1 === n ? s.length - 1 : n;
+    }
+    _getRuler() {
+      const t = this.options, e = this._cachedMeta, i = e.iScale, s = [];
+      let n, o;
+      for (n = 0, o = e.data.length; n < o; ++n) s.push(i.getPixelForValue(this.getParsed(n)[i.axis], n));
+      const a = t.barThickness;
+      return {
+        min: a || Mn(e),
+        pixels: s,
+        start: i._startPixel,
+        end: i._endPixel,
+        stackCount: this._getStackCount(),
+        scale: i,
+        grouped: t.grouped,
+        ratio: a ? 1 : t.categoryPercentage * t.barPercentage,
+      };
+    }
+    _calculateBarValuePixels(t) {
+      const { _cachedMeta: { vScale: e, _stacked: s }, options: { base: n, minBarLength: o } } = this,
+        a = n || 0,
+        r = this.getParsed(t),
+        l = r._custom,
+        h = Pn(l);
+      let c, d, u = r[e.axis], f = 0, g = s ? this.applyStack(e, r, s) : u;
+      g !== u && (f = g - u, g = u),
+        h && (u = l.barStart, g = l.barEnd - l.barStart, 0 !== u && z(u) !== z(l.barEnd) && (f = 0), f += u);
+      const p = i(n) || h ? f : n;
+      let m = e.getPixelForValue(p);
+      if (c = this.chart.getDataVisibility(t) ? e.getPixelForValue(f + g) : m, d = c - m, Math.abs(d) < o) {
+        d = function(t, e, i) {
+          return 0 !== t ? z(t) : (e.isHorizontal() ? 1 : -1) * (e.min >= i ? 1 : -1);
+        }(d, e, a) * o, u === a && (m -= d / 2);
+        const t = e.getPixelForDecimal(0), i = e.getPixelForDecimal(1), s = Math.min(t, i), n = Math.max(t, i);
+        m = Math.max(Math.min(m, n), s), c = m + d;
+      }
+      if (m === e.getPixelForValue(a)) {
+        const t = z(d) * e.getLineWidthForValue(a) / 2;
+        m += t, d -= t;
+      }
+      return { size: d, base: m, head: c, center: c + d / 2 };
+    }
+    _calculateBarIndexPixels(t, e) {
+      const s = e.scale, n = this.options, o = n.skipNull, a = r(n.maxBarThickness, 1 / 0);
+      let l, h;
+      if (e.grouped) {
+        const s = o ? this._getStackCount(t) : e.stackCount,
+          r = "flex" === n.barThickness
+            ? function(t, e, i, s) {
+              const n = e.pixels, o = n[t];
+              let a = t > 0 ? n[t - 1] : null, r = t < n.length - 1 ? n[t + 1] : null;
+              const l = i.categoryPercentage;
+              null === a && (a = o - (null === r ? e.end - e.start : r - o)), null === r && (r = o + o - a);
+              const h = o - (o - Math.min(a, r)) / 2 * l;
+              return { chunk: Math.abs(r - a) / 2 * l / s, ratio: i.barPercentage, start: h };
+            }(t, e, n, s)
+            : function(t, e, s, n) {
+              const o = s.barThickness;
+              let a, r;
+              return i(o) ? (a = e.min * s.categoryPercentage, r = s.barPercentage) : (a = o * n, r = 1),
+                { chunk: a / n, ratio: r, start: e.pixels[t] - a / 2 };
+            }(t, e, n, s),
+          c = this._getStackIndex(this.index, this._cachedMeta.stack, o ? t : void 0);
+        l = r.start + r.chunk * c + r.chunk / 2, h = Math.min(a, r.chunk * r.ratio);
+      } else l = s.getPixelForValue(this.getParsed(t)[s.axis], t), h = Math.min(a, e.min * e.ratio);
+      return { base: l - h / 2, head: l + h / 2, center: l, size: h };
+    }
+    draw() {
+      const t = this._cachedMeta, e = t.vScale, i = t.data, s = i.length;
+      let n = 0;
+      for (; n < s; ++n) null !== this.getParsed(n)[e.axis] && i[n].draw(this._ctx);
+    }
+  }
+  Tn.id = "bar",
+    Tn.defaults = {
+      datasetElementType: !1,
+      dataElementType: "bar",
+      categoryPercentage: .8,
+      barPercentage: .9,
+      grouped: !0,
+      animations: { numbers: { type: "number", properties: ["x", "y", "base", "width", "height"] } },
+    },
+    Tn.overrides = {
+      scales: {
+        _index_: { type: "category", offset: !0, grid: { offset: !0 } },
+        _value_: { type: "linear", beginAtZero: !0 },
+      },
+    };
+  class Ln extends Ls {
+    initialize() {
+      this.enableOptionSharing = !0, super.initialize();
+    }
+    parsePrimitiveData(t, e, i, s) {
+      const n = super.parsePrimitiveData(t, e, i, s);
+      for (let t = 0; t < n.length; t++) n[t]._custom = this.resolveDataElementOptions(t + i).radius;
+      return n;
+    }
+    parseArrayData(t, e, i, s) {
+      const n = super.parseArrayData(t, e, i, s);
+      for (let t = 0; t < n.length; t++) {
+        const s = e[i + t];
+        n[t]._custom = r(s[2], this.resolveDataElementOptions(t + i).radius);
+      }
+      return n;
+    }
+    parseObjectData(t, e, i, s) {
+      const n = super.parseObjectData(t, e, i, s);
+      for (let t = 0; t < n.length; t++) {
+        const s = e[i + t];
+        n[t]._custom = r(s && s.r && +s.r, this.resolveDataElementOptions(t + i).radius);
+      }
+      return n;
+    }
+    getMaxOverflow() {
+      const t = this._cachedMeta.data;
+      let e = 0;
+      for (let i = t.length - 1; i >= 0; --i) e = Math.max(e, t[i].size(this.resolveDataElementOptions(i)) / 2);
+      return e > 0 && e;
+    }
+    getLabelAndValue(t) {
+      const e = this._cachedMeta,
+        { xScale: i, yScale: s } = e,
+        n = this.getParsed(t),
+        o = i.getLabelForValue(n.x),
+        a = s.getLabelForValue(n.y),
+        r = n._custom;
+      return { label: e.label, value: "(" + o + ", " + a + (r ? ", " + r : "") + ")" };
+    }
+    update(t) {
+      const e = this._cachedMeta.data;
+      this.updateElements(e, 0, e.length, t);
+    }
+    updateElements(t, e, i, s) {
+      const n = "reset" === s,
+        { iScale: o, vScale: a } = this._cachedMeta,
+        { sharedOptions: r, includeOptions: l } = this._getSharedOptions(e, s),
+        h = o.axis,
+        c = a.axis;
+      for (let d = e; d < e + i; d++) {
+        const e = t[d],
+          i = !n && this.getParsed(d),
+          u = {},
+          f = u[h] = n ? o.getPixelForDecimal(.5) : o.getPixelForValue(i[h]),
+          g = u[c] = n ? a.getBasePixel() : a.getPixelForValue(i[c]);
+        u.skip = isNaN(f) || isNaN(g),
+          l
+          && (u.options = r || this.resolveDataElementOptions(d, e.active ? "active" : s), n && (u.options.radius = 0)),
+          this.updateElement(e, d, u, s);
+      }
+    }
+    resolveDataElementOptions(t, e) {
+      const i = this.getParsed(t);
+      let s = super.resolveDataElementOptions(t, e);
+      s.$shared && (s = Object.assign({}, s, { $shared: !1 }));
+      const n = s.radius;
+      return "active" !== e && (s.radius = 0), s.radius += r(i && i._custom, n), s;
+    }
+  }
+  Ln.id = "bubble",
+    Ln.defaults = {
+      datasetElementType: !1,
+      dataElementType: "point",
+      animations: { numbers: { type: "number", properties: ["x", "y", "borderWidth", "radius"] } },
+    },
+    Ln.overrides = {
+      scales: { x: { type: "linear" }, y: { type: "linear" } },
+      plugins: { tooltip: { callbacks: { title: () => "" } } },
+    };
+  class En extends Ls {
+    constructor(t, e) {
+      super(t, e),
+        this.enableOptionSharing = !0,
+        this.innerRadius = void 0,
+        this.outerRadius = void 0,
+        this.offsetX = void 0,
+        this.offsetY = void 0;
+    }
+    linkScales() {}
+    parse(t, e) {
+      const i = this.getDataset().data, s = this._cachedMeta;
+      if (!1 === this._parsing) s._parsed = i;
+      else {
+        let o, a, r = t => +i[t];
+        if (n(i[t])) {
+          const { key: t = "value" } = this._parsing;
+          r = e => +y(i[e], t);
+        }
+        for (o = t, a = t + e; o < a; ++o) s._parsed[o] = r(o);
+      }
+    }
+    _getRotation() {
+      return H(this.options.rotation - 90);
+    }
+    _getCircumference() {
+      return H(this.options.circumference);
+    }
+    _getRotationExtents() {
+      let t = O, e = -O;
+      for (let i = 0; i < this.chart.data.datasets.length; ++i) {
+        if (this.chart.isDatasetVisible(i)) {
+          const s = this.chart.getDatasetMeta(i).controller, n = s._getRotation(), o = s._getCircumference();
+          t = Math.min(t, n), e = Math.max(e, n + o);
+        }
+      }
+      return { rotation: t, circumference: e - t };
+    }
+    update(t) {
+      const e = this.chart,
+        { chartArea: i } = e,
+        s = this._cachedMeta,
+        n = s.data,
+        o = this.getMaxBorderWidth() + this.getMaxOffset(n) + this.options.spacing,
+        a = Math.max((Math.min(i.width, i.height) - o) / 2, 0),
+        r = Math.min(l(this.options.cutout, a), 1),
+        c = this._getRingWeight(this.index),
+        { circumference: d, rotation: u } = this._getRotationExtents(),
+        { ratioX: f, ratioY: g, offsetX: p, offsetY: m } = function(t, e, i) {
+          let s = 1, n = 1, o = 0, a = 0;
+          if (e < O) {
+            const r = t,
+              l = r + e,
+              h = Math.cos(r),
+              c = Math.sin(r),
+              d = Math.cos(l),
+              u = Math.sin(l),
+              f = (t, e, s) => G(t, r, l, !0) ? 1 : Math.max(e, e * i, s, s * i),
+              g = (t, e, s) => G(t, r, l, !0) ? -1 : Math.min(e, e * i, s, s * i),
+              p = f(0, h, d),
+              m = f(L, c, u),
+              b = g(D, h, d),
+              x = g(D + L, c, u);
+            s = (p - b) / 2, n = (m - x) / 2, o = -(p + b) / 2, a = -(m + x) / 2;
+          }
+          return { ratioX: s, ratioY: n, offsetX: o, offsetY: a };
+        }(u, d, r),
+        b = (i.width - o) / f,
+        x = (i.height - o) / g,
+        _ = Math.max(Math.min(b, x) / 2, 0),
+        y = h(this.options.radius, _),
+        v = (y - Math.max(y * r, 0)) / this._getVisibleDatasetWeightTotal();
+      this.offsetX = p * y,
+        this.offsetY = m * y,
+        s.total = this.calculateTotal(),
+        this.outerRadius = y - v * this._getRingWeightOffset(this.index),
+        this.innerRadius = Math.max(this.outerRadius - v * c, 0),
+        this.updateElements(n, 0, n.length, t);
+    }
+    _circumference(t, e) {
+      const i = this.options, s = this._cachedMeta, n = this._getCircumference();
+      return e && i.animation.animateRotate || !this.chart.getDataVisibility(t) || null === s._parsed[t]
+          || s.data[t].hidden
+        ? 0
+        : this.calculateCircumference(s._parsed[t] * n / O);
+    }
+    updateElements(t, e, i, s) {
+      const n = "reset" === s,
+        o = this.chart,
+        a = o.chartArea,
+        r = o.options.animation,
+        l = (a.left + a.right) / 2,
+        h = (a.top + a.bottom) / 2,
+        c = n && r.animateScale,
+        d = c ? 0 : this.innerRadius,
+        u = c ? 0 : this.outerRadius,
+        { sharedOptions: f, includeOptions: g } = this._getSharedOptions(e, s);
+      let p, m = this._getRotation();
+      for (p = 0; p < e; ++p) m += this._circumference(p, n);
+      for (p = e; p < e + i; ++p) {
+        const e = this._circumference(p, n),
+          i = t[p],
+          o = {
+            x: l + this.offsetX,
+            y: h + this.offsetY,
+            startAngle: m,
+            endAngle: m + e,
+            circumference: e,
+            outerRadius: u,
+            innerRadius: d,
+          };
+        g && (o.options = f || this.resolveDataElementOptions(p, i.active ? "active" : s)),
+          m += e,
+          this.updateElement(i, p, o, s);
+      }
+    }
+    calculateTotal() {
+      const t = this._cachedMeta, e = t.data;
+      let i, s = 0;
+      for (i = 0; i < e.length; i++) {
+        const n = t._parsed[i];
+        null === n || isNaN(n) || !this.chart.getDataVisibility(i) || e[i].hidden || (s += Math.abs(n));
+      }
+      return s;
+    }
+    calculateCircumference(t) {
+      const e = this._cachedMeta.total;
+      return e > 0 && !isNaN(t) ? O * (Math.abs(t) / e) : 0;
+    }
+    getLabelAndValue(t) {
+      const e = this._cachedMeta, i = this.chart, s = i.data.labels || [], n = li(e._parsed[t], i.options.locale);
+      return { label: s[t] || "", value: n };
+    }
+    getMaxBorderWidth(t) {
+      let e = 0;
+      const i = this.chart;
+      let s, n, o, a, r;
+      if (!t) {
+        for (s = 0, n = i.data.datasets.length; s < n; ++s) {
+          if (i.isDatasetVisible(s)) {
+            o = i.getDatasetMeta(s), t = o.data, a = o.controller;
+            break;
+          }
+        }
+      }
+      if (!t) return 0;
+      for (s = 0, n = t.length; s < n; ++s) {
+        r = a.resolveDataElementOptions(s),
+          "inner" !== r.borderAlign && (e = Math.max(e, r.borderWidth || 0, r.hoverBorderWidth || 0));
+      }
+      return e;
+    }
+    getMaxOffset(t) {
+      let e = 0;
+      for (let i = 0, s = t.length; i < s; ++i) {
+        const t = this.resolveDataElementOptions(i);
+        e = Math.max(e, t.offset || 0, t.hoverOffset || 0);
+      }
+      return e;
+    }
+    _getRingWeightOffset(t) {
+      let e = 0;
+      for (let i = 0; i < t; ++i) this.chart.isDatasetVisible(i) && (e += this._getRingWeight(i));
+      return e;
+    }
+    _getRingWeight(t) {
+      return Math.max(r(this.chart.data.datasets[t].weight, 1), 0);
+    }
+    _getVisibleDatasetWeightTotal() {
+      return this._getRingWeightOffset(this.chart.data.datasets.length) || 1;
+    }
+  }
+  En.id = "doughnut",
+    En.defaults = {
+      datasetElementType: !1,
+      dataElementType: "arc",
+      animation: { animateRotate: !0, animateScale: !1 },
+      animations: {
+        numbers: {
+          type: "number",
+          properties: [
+            "circumference",
+            "endAngle",
+            "innerRadius",
+            "outerRadius",
+            "startAngle",
+            "x",
+            "y",
+            "offset",
+            "borderWidth",
+            "spacing",
+          ],
+        },
+      },
+      cutout: "50%",
+      rotation: 0,
+      circumference: 360,
+      radius: "100%",
+      spacing: 0,
+      indexAxis: "r",
+    },
+    En.descriptors = { _scriptable: t => "spacing" !== t, _indexable: t => "spacing" !== t },
+    En.overrides = {
+      aspectRatio: 1,
+      plugins: {
+        legend: {
+          labels: {
+            generateLabels(t) {
+              const e = t.data;
+              if (e.labels.length && e.datasets.length) {
+                const { labels: { pointStyle: i } } = t.legend.options;
+                return e.labels.map((e, s) => {
+                  const n = t.getDatasetMeta(0).controller.getStyle(s);
+                  return {
+                    text: e,
+                    fillStyle: n.backgroundColor,
+                    strokeStyle: n.borderColor,
+                    lineWidth: n.borderWidth,
+                    pointStyle: i,
+                    hidden: !t.getDataVisibility(s),
+                    index: s,
+                  };
+                });
+              }
+              return [];
+            },
+          },
+          onClick(t, e, i) {
+            i.chart.toggleDataVisibility(e.index), i.chart.update();
+          },
+        },
+        tooltip: {
+          callbacks: {
+            title: () => "",
+            label(t) {
+              let e = t.label;
+              const i = ": " + t.formattedValue;
+              return s(e) ? (e = e.slice(), e[0] += i) : e += i, e;
+            },
+          },
+        },
+      },
+    };
+  class Rn extends Ls {
+    initialize() {
+      this.enableOptionSharing = !0, this.supportsDecimation = !0, super.initialize();
+    }
+    update(t) {
+      const e = this._cachedMeta, { dataset: i, data: s = [], _dataset: n } = e, o = this.chart._animationsDisabled;
+      let { start: a, count: r } = gt(e, s, o);
+      this._drawStart = a,
+        this._drawCount = r,
+        pt(e) && (a = 0, r = s.length),
+        i._chart = this.chart,
+        i._datasetIndex = this.index,
+        i._decimated = !!n._decimated,
+        i.points = s;
+      const l = this.resolveDatasetElementOptions(t);
+      this.options.showLine || (l.borderWidth = 0),
+        l.segment = this.options.segment,
+        this.updateElement(i, void 0, { animated: !o, options: l }, t),
+        this.updateElements(s, a, r, t);
+    }
+    updateElements(t, e, s, n) {
+      const o = "reset" === n,
+        { iScale: a, vScale: r, _stacked: l, _dataset: h } = this._cachedMeta,
+        { sharedOptions: c, includeOptions: d } = this._getSharedOptions(e, n),
+        u = a.axis,
+        f = r.axis,
+        { spanGaps: g, segment: p } = this.options,
+        m = B(g) ? g : Number.POSITIVE_INFINITY,
+        b = this.chart._animationsDisabled || o || "none" === n;
+      let x = e > 0 && this.getParsed(e - 1);
+      for (let g = e; g < e + s; ++g) {
+        const e = t[g],
+          s = this.getParsed(g),
+          _ = b ? e : {},
+          y = i(s[f]),
+          v = _[u] = a.getPixelForValue(s[u], g),
+          w = _[f] = o || y ? r.getBasePixel() : r.getPixelForValue(l ? this.applyStack(r, s, l) : s[f], g);
+        _.skip = isNaN(v) || isNaN(w) || y,
+          _.stop = g > 0 && Math.abs(s[u] - x[u]) > m,
+          p && (_.parsed = s, _.raw = h.data[g]),
+          d && (_.options = c || this.resolveDataElementOptions(g, e.active ? "active" : n)),
+          b || this.updateElement(e, g, _, n),
+          x = s;
+      }
+    }
+    getMaxOverflow() {
+      const t = this._cachedMeta, e = t.dataset, i = e.options && e.options.borderWidth || 0, s = t.data || [];
+      if (!s.length) return i;
+      const n = s[0].size(this.resolveDataElementOptions(0)),
+        o = s[s.length - 1].size(this.resolveDataElementOptions(s.length - 1));
+      return Math.max(i, n, o) / 2;
+    }
+    draw() {
+      const t = this._cachedMeta;
+      t.dataset.updateControlPoints(this.chart.chartArea, t.iScale.axis), super.draw();
+    }
+  }
+  Rn.id = "line",
+    Rn.defaults = { datasetElementType: "line", dataElementType: "point", showLine: !0, spanGaps: !1 },
+    Rn.overrides = { scales: { _index_: { type: "category" }, _value_: { type: "linear" } } };
+  class In extends Ls {
+    constructor(t, e) {
+      super(t, e), this.innerRadius = void 0, this.outerRadius = void 0;
+    }
+    getLabelAndValue(t) {
+      const e = this._cachedMeta, i = this.chart, s = i.data.labels || [], n = li(e._parsed[t].r, i.options.locale);
+      return { label: s[t] || "", value: n };
+    }
+    parseObjectData(t, e, i, s) {
+      return Ue.bind(this)(t, e, i, s);
+    }
+    update(t) {
+      const e = this._cachedMeta.data;
+      this._updateRadius(), this.updateElements(e, 0, e.length, t);
+    }
+    getMinMax() {
+      const t = this._cachedMeta, e = { min: Number.POSITIVE_INFINITY, max: Number.NEGATIVE_INFINITY };
+      return t.data.forEach((t, i) => {
+        const s = this.getParsed(i).r;
+        !isNaN(s) && this.chart.getDataVisibility(i) && (s < e.min && (e.min = s), s > e.max && (e.max = s));
+      }),
+        e;
+    }
+    _updateRadius() {
+      const t = this.chart,
+        e = t.chartArea,
+        i = t.options,
+        s = Math.min(e.right - e.left, e.bottom - e.top),
+        n = Math.max(s / 2, 0),
+        o = (n - Math.max(i.cutoutPercentage ? n / 100 * i.cutoutPercentage : 1, 0)) / t.getVisibleDatasetCount();
+      this.outerRadius = n - o * this.index, this.innerRadius = this.outerRadius - o;
+    }
+    updateElements(t, e, i, s) {
+      const n = "reset" === s,
+        o = this.chart,
+        a = o.options.animation,
+        r = this._cachedMeta.rScale,
+        l = r.xCenter,
+        h = r.yCenter,
+        c = r.getIndexAngle(0) - .5 * D;
+      let d, u = c;
+      const f = 360 / this.countVisibleElements();
+      for (d = 0; d < e; ++d) u += this._computeAngle(d, s, f);
+      for (d = e; d < e + i; d++) {
+        const e = t[d];
+        let i = u,
+          g = u + this._computeAngle(d, s, f),
+          p = o.getDataVisibility(d) ? r.getDistanceFromCenterForValue(this.getParsed(d).r) : 0;
+        u = g, n && (a.animateScale && (p = 0), a.animateRotate && (i = g = c));
+        const m = {
+          x: l,
+          y: h,
+          innerRadius: 0,
+          outerRadius: p,
+          startAngle: i,
+          endAngle: g,
+          options: this.resolveDataElementOptions(d, e.active ? "active" : s),
+        };
+        this.updateElement(e, d, m, s);
+      }
+    }
+    countVisibleElements() {
+      const t = this._cachedMeta;
+      let e = 0;
+      return t.data.forEach((t, i) => {
+        !isNaN(this.getParsed(i).r) && this.chart.getDataVisibility(i) && e++;
+      }),
+        e;
+    }
+    _computeAngle(t, e, i) {
+      return this.chart.getDataVisibility(t) ? H(this.resolveDataElementOptions(t, e).angle || i) : 0;
+    }
+  }
+  In.id = "polarArea",
+    In.defaults = {
+      dataElementType: "arc",
+      animation: { animateRotate: !0, animateScale: !0 },
+      animations: {
+        numbers: { type: "number", properties: ["x", "y", "startAngle", "endAngle", "innerRadius", "outerRadius"] },
+      },
+      indexAxis: "r",
+      startAngle: 0,
+    },
+    In.overrides = {
+      aspectRatio: 1,
+      plugins: {
+        legend: {
+          labels: {
+            generateLabels(t) {
+              const e = t.data;
+              if (e.labels.length && e.datasets.length) {
+                const { labels: { pointStyle: i } } = t.legend.options;
+                return e.labels.map((e, s) => {
+                  const n = t.getDatasetMeta(0).controller.getStyle(s);
+                  return {
+                    text: e,
+                    fillStyle: n.backgroundColor,
+                    strokeStyle: n.borderColor,
+                    lineWidth: n.borderWidth,
+                    pointStyle: i,
+                    hidden: !t.getDataVisibility(s),
+                    index: s,
+                  };
+                });
+              }
+              return [];
+            },
+          },
+          onClick(t, e, i) {
+            i.chart.toggleDataVisibility(e.index), i.chart.update();
+          },
+        },
+        tooltip: {
+          callbacks: { title: () => "", label: t => t.chart.data.labels[t.dataIndex] + ": " + t.formattedValue },
+        },
+      },
+      scales: {
+        r: {
+          type: "radialLinear",
+          angleLines: { display: !1 },
+          beginAtZero: !0,
+          grid: { circular: !0 },
+          pointLabels: { display: !1 },
+          startAngle: 0,
+        },
+      },
+    };
+  class zn extends En {}
+  zn.id = "pie", zn.defaults = { cutout: 0, rotation: 0, circumference: 360, radius: "100%" };
+  class Fn extends Ls {
+    getLabelAndValue(t) {
+      const e = this._cachedMeta.vScale, i = this.getParsed(t);
+      return { label: e.getLabels()[t], value: "" + e.getLabelForValue(i[e.axis]) };
+    }
+    parseObjectData(t, e, i, s) {
+      return Ue.bind(this)(t, e, i, s);
+    }
+    update(t) {
+      const e = this._cachedMeta, i = e.dataset, s = e.data || [], n = e.iScale.getLabels();
+      if (i.points = s, "resize" !== t) {
+        const e = this.resolveDatasetElementOptions(t);
+        this.options.showLine || (e.borderWidth = 0);
+        const o = { _loop: !0, _fullLoop: n.length === s.length, options: e };
+        this.updateElement(i, void 0, o, t);
+      }
+      this.updateElements(s, 0, s.length, t);
+    }
+    updateElements(t, e, i, s) {
+      const n = this._cachedMeta.rScale, o = "reset" === s;
+      for (let a = e; a < e + i; a++) {
+        const e = t[a],
+          i = this.resolveDataElementOptions(a, e.active ? "active" : s),
+          r = n.getPointPositionForValue(a, this.getParsed(a).r),
+          l = o ? n.xCenter : r.x,
+          h = o ? n.yCenter : r.y,
+          c = { x: l, y: h, angle: r.angle, skip: isNaN(l) || isNaN(h), options: i };
+        this.updateElement(e, a, c, s);
+      }
+    }
+  }
+  Fn.id = "radar",
+    Fn.defaults = {
+      datasetElementType: "line",
+      dataElementType: "point",
+      indexAxis: "r",
+      showLine: !0,
+      elements: { line: { fill: "start" } },
+    },
+    Fn.overrides = { aspectRatio: 1, scales: { r: { type: "radialLinear" } } };
+  class Vn extends Ls {
+    update(t) {
+      const e = this._cachedMeta, { data: i = [] } = e, s = this.chart._animationsDisabled;
+      let { start: n, count: o } = gt(e, i, s);
+      if (this._drawStart = n, this._drawCount = o, pt(e) && (n = 0, o = i.length), this.options.showLine) {
+        const { dataset: n, _dataset: o } = e;
+        n._chart = this.chart, n._datasetIndex = this.index, n._decimated = !!o._decimated, n.points = i;
+        const a = this.resolveDatasetElementOptions(t);
+        a.segment = this.options.segment, this.updateElement(n, void 0, { animated: !s, options: a }, t);
+      }
+      this.updateElements(i, n, o, t);
+    }
+    addElements() {
+      const { showLine: t } = this.options;
+      !this.datasetElementType && t && (this.datasetElementType = Us.getElement("line")), super.addElements();
+    }
+    updateElements(t, e, s, n) {
+      const o = "reset" === n,
+        { iScale: a, vScale: r, _stacked: l, _dataset: h } = this._cachedMeta,
+        c = this.resolveDataElementOptions(e, n),
+        d = this.getSharedOptions(c),
+        u = this.includeOptions(n, d),
+        f = a.axis,
+        g = r.axis,
+        { spanGaps: p, segment: m } = this.options,
+        b = B(p) ? p : Number.POSITIVE_INFINITY,
+        x = this.chart._animationsDisabled || o || "none" === n;
+      let _ = e > 0 && this.getParsed(e - 1);
+      for (let c = e; c < e + s; ++c) {
+        const e = t[c],
+          s = this.getParsed(c),
+          p = x ? e : {},
+          y = i(s[g]),
+          v = p[f] = a.getPixelForValue(s[f], c),
+          w = p[g] = o || y ? r.getBasePixel() : r.getPixelForValue(l ? this.applyStack(r, s, l) : s[g], c);
+        p.skip = isNaN(v) || isNaN(w) || y,
+          p.stop = c > 0 && Math.abs(s[f] - _[f]) > b,
+          m && (p.parsed = s, p.raw = h.data[c]),
+          u && (p.options = d || this.resolveDataElementOptions(c, e.active ? "active" : n)),
+          x || this.updateElement(e, c, p, n),
+          _ = s;
+      }
+      this.updateSharedOptions(d, n, c);
+    }
+    getMaxOverflow() {
+      const t = this._cachedMeta, e = t.data || [];
+      if (!this.options.showLine) {
+        let t = 0;
+        for (let i = e.length - 1; i >= 0; --i) t = Math.max(t, e[i].size(this.resolveDataElementOptions(i)) / 2);
+        return t > 0 && t;
+      }
+      const i = t.dataset, s = i.options && i.options.borderWidth || 0;
+      if (!e.length) return s;
+      const n = e[0].size(this.resolveDataElementOptions(0)),
+        o = e[e.length - 1].size(this.resolveDataElementOptions(e.length - 1));
+      return Math.max(s, n, o) / 2;
+    }
+  }
+  Vn.id = "scatter",
+    Vn.defaults = { datasetElementType: !1, dataElementType: "point", showLine: !1, fill: !1 },
+    Vn.overrides = {
+      interaction: { mode: "point" },
+      plugins: {
+        tooltip: { callbacks: { title: () => "", label: t => "(" + t.label + ", " + t.formattedValue + ")" } },
+      },
+      scales: { x: { type: "linear" }, y: { type: "linear" } },
+    };
+  var Bn = Object.freeze({
+    __proto__: null,
+    BarController: Tn,
+    BubbleController: Ln,
+    DoughnutController: En,
+    LineController: Rn,
+    PolarAreaController: In,
+    PieController: zn,
+    RadarController: Fn,
+    ScatterController: Vn,
+  });
+  function Nn(t, e, i) {
+    const { startAngle: s, pixelMargin: n, x: o, y: a, outerRadius: r, innerRadius: l } = e;
+    let h = n / r;
+    t.beginPath(),
+      t.arc(o, a, r, s - h, i + h),
+      l > n ? (h = n / l, t.arc(o, a, l, i + h, s - h, !0)) : t.arc(o, a, n, i + L, s - L),
+      t.closePath(),
+      t.clip();
+  }
+  function Wn(t, e, i, s) {
+    const n = ui(t.options.borderRadius, ["outerStart", "outerEnd", "innerStart", "innerEnd"]);
+    const o = (i - e) / 2,
+      a = Math.min(o, s * e / 2),
+      r = t => {
+        const e = (i - Math.min(o, t)) * s / 2;
+        return Z(t, 0, Math.min(o, e));
+      };
+    return {
+      outerStart: r(n.outerStart),
+      outerEnd: r(n.outerEnd),
+      innerStart: Z(n.innerStart, 0, a),
+      innerEnd: Z(n.innerEnd, 0, a),
+    };
+  }
+  function jn(t, e, i, s) {
+    return { x: i + t * Math.cos(e), y: s + t * Math.sin(e) };
+  }
+  function Hn(t, e, i, s, n, o) {
+    const { x: a, y: r, startAngle: l, pixelMargin: h, innerRadius: c } = e,
+      d = Math.max(e.outerRadius + s + i - h, 0),
+      u = c > 0 ? c + s + i + h : 0;
+    let f = 0;
+    const g = n - l;
+    if (s) {
+      const t = ((c > 0 ? c - s : 0) + (d > 0 ? d - s : 0)) / 2;
+      f = (g - (0 !== t ? g * t / (t + s) : g)) / 2;
+    }
+    const p = (g - Math.max(.001, g * d - i / D) / d) / 2,
+      m = l + p + f,
+      b = n - p - f,
+      { outerStart: x, outerEnd: _, innerStart: y, innerEnd: v } = Wn(e, u, d, b - m),
+      w = d - x,
+      M = d - _,
+      k = m + x / w,
+      S = b - _ / M,
+      P = u + y,
+      O = u + v,
+      C = m + y / P,
+      A = b - v / O;
+    if (t.beginPath(), o) {
+      if (t.arc(a, r, d, k, S), _ > 0) {
+        const e = jn(M, S, a, r);
+        t.arc(e.x, e.y, _, S, b + L);
+      }
+      const e = jn(O, b, a, r);
+      if (t.lineTo(e.x, e.y), v > 0) {
+        const e = jn(O, A, a, r);
+        t.arc(e.x, e.y, v, b + L, A + Math.PI);
+      }
+      if (t.arc(a, r, u, b - v / u, m + y / u, !0), y > 0) {
+        const e = jn(P, C, a, r);
+        t.arc(e.x, e.y, y, C + Math.PI, m - L);
+      }
+      const i = jn(w, m, a, r);
+      if (t.lineTo(i.x, i.y), x > 0) {
+        const e = jn(w, k, a, r);
+        t.arc(e.x, e.y, x, m - L, k);
+      }
+    } else {
+      t.moveTo(a, r);
+      const e = Math.cos(k) * d + a, i = Math.sin(k) * d + r;
+      t.lineTo(e, i);
+      const s = Math.cos(S) * d + a, n = Math.sin(S) * d + r;
+      t.lineTo(s, n);
+    }
+    t.closePath();
+  }
+  function $n(t, e, i, s, n, o) {
+    const { options: a } = e, { borderWidth: r, borderJoinStyle: l } = a, h = "inner" === a.borderAlign;
+    r
+      && (h ? (t.lineWidth = 2 * r, t.lineJoin = l || "round") : (t.lineWidth = r, t.lineJoin = l || "bevel"),
+        e.fullCircles && function(t, e, i) {
+          const { x: s, y: n, startAngle: o, pixelMargin: a, fullCircles: r } = e,
+            l = Math.max(e.outerRadius - a, 0),
+            h = e.innerRadius + a;
+          let c;
+          for (i && Nn(t, e, o + O), t.beginPath(), t.arc(s, n, h, o + O, o, !0), c = 0; c < r; ++c) t.stroke();
+          for (t.beginPath(), t.arc(s, n, l, o, o + O), c = 0; c < r; ++c) t.stroke();
+        }(t, e, h),
+        h && Nn(t, e, n),
+        Hn(t, e, i, s, n, o),
+        t.stroke());
+  }
+  class Yn extends Es {
+    constructor(t) {
+      super(),
+        this.options = void 0,
+        this.circumference = void 0,
+        this.startAngle = void 0,
+        this.endAngle = void 0,
+        this.innerRadius = void 0,
+        this.outerRadius = void 0,
+        this.pixelMargin = 0,
+        this.fullCircles = 0,
+        t && Object.assign(this, t);
+    }
+    inRange(t, e, i) {
+      const s = this.getProps(["x", "y"], i),
+        { angle: n, distance: o } = U(s, { x: t, y: e }),
+        { startAngle: a, endAngle: l, innerRadius: h, outerRadius: c, circumference: d } = this.getProps([
+          "startAngle",
+          "endAngle",
+          "innerRadius",
+          "outerRadius",
+          "circumference",
+        ], i),
+        u = this.options.spacing / 2,
+        f = r(d, l - a) >= O || G(n, a, l),
+        g = Q(o, h + u, c + u);
+      return f && g;
+    }
+    getCenterPoint(t) {
+      const { x: e, y: i, startAngle: s, endAngle: n, innerRadius: o, outerRadius: a } = this.getProps([
+          "x",
+          "y",
+          "startAngle",
+          "endAngle",
+          "innerRadius",
+          "outerRadius",
+          "circumference",
+        ], t),
+        { offset: r, spacing: l } = this.options,
+        h = (s + n) / 2,
+        c = (o + a + l + r) / 2;
+      return { x: e + Math.cos(h) * c, y: i + Math.sin(h) * c };
+    }
+    tooltipPosition(t) {
+      return this.getCenterPoint(t);
+    }
+    draw(t) {
+      const { options: e, circumference: i } = this, s = (e.offset || 0) / 2, n = (e.spacing || 0) / 2, o = e.circular;
+      if (
+        this.pixelMargin = "inner" === e.borderAlign ? .33 : 0,
+          this.fullCircles = i > O ? Math.floor(i / O) : 0,
+          0 === i || this.innerRadius < 0 || this.outerRadius < 0
+      ) return;
+      t.save();
+      let a = 0;
+      if (s) {
+        a = s / 2;
+        const e = (this.startAngle + this.endAngle) / 2;
+        t.translate(Math.cos(e) * a, Math.sin(e) * a), this.circumference >= D && (a = s);
+      }
+      t.fillStyle = e.backgroundColor, t.strokeStyle = e.borderColor;
+      const r = function(t, e, i, s, n) {
+        const { fullCircles: o, startAngle: a, circumference: r } = e;
+        let l = e.endAngle;
+        if (o) {
+          Hn(t, e, i, s, a + O, n);
+          for (let e = 0; e < o; ++e) t.fill();
+          isNaN(r) || (l = a + r % O, r % O == 0 && (l += O));
+        }
+        return Hn(t, e, i, s, l, n), t.fill(), l;
+      }(t, this, a, n, o);
+      $n(t, this, a, n, r, o), t.restore();
+    }
+  }
+  function Un(t, e, i = e) {
+    t.lineCap = r(i.borderCapStyle, e.borderCapStyle),
+      t.setLineDash(r(i.borderDash, e.borderDash)),
+      t.lineDashOffset = r(i.borderDashOffset, e.borderDashOffset),
+      t.lineJoin = r(i.borderJoinStyle, e.borderJoinStyle),
+      t.lineWidth = r(i.borderWidth, e.borderWidth),
+      t.strokeStyle = r(i.borderColor, e.borderColor);
+  }
+  function Xn(t, e, i) {
+    t.lineTo(i.x, i.y);
+  }
+  function qn(t, e, i = {}) {
+    const s = t.length,
+      { start: n = 0, end: o = s - 1 } = i,
+      { start: a, end: r } = e,
+      l = Math.max(n, a),
+      h = Math.min(o, r),
+      c = n < a && o < a || n > r && o > r;
+    return { count: s, start: l, loop: e.loop, ilen: h < l && !c ? s + h - l : h - l };
+  }
+  function Kn(t, e, i, s) {
+    const { points: n, options: o } = e,
+      { count: a, start: r, loop: l, ilen: h } = qn(n, i, s),
+      c = function(t) {
+        return t.stepped ? Oe : t.tension || "monotone" === t.cubicInterpolationMode ? Ce : Xn;
+      }(o);
+    let d, u, f, { move: g = !0, reverse: p } = s || {};
+    for (d = 0; d <= h; ++d) {
+      u = n[(r + (p ? h - d : d)) % a], u.skip || (g ? (t.moveTo(u.x, u.y), g = !1) : c(t, f, u, p, o.stepped), f = u);
+    }
+    return l && (u = n[(r + (p ? h : 0)) % a], c(t, f, u, p, o.stepped)), !!l;
+  }
+  function Gn(t, e, i, s) {
+    const n = e.points, { count: o, start: a, ilen: r } = qn(n, i, s), { move: l = !0, reverse: h } = s || {};
+    let c, d, u, f, g, p, m = 0, b = 0;
+    const x = t => (a + (h ? r - t : t)) % o,
+      _ = () => {
+        f !== g && (t.lineTo(m, g), t.lineTo(m, f), t.lineTo(m, p));
+      };
+    for (l && (d = n[x(0)], t.moveTo(d.x, d.y)), c = 0; c <= r; ++c) {
+      if (d = n[x(c)], d.skip) continue;
+      const e = d.x, i = d.y, s = 0 | e;
+      s === u
+        ? (i < f ? f = i : i > g && (g = i), m = (b * m + e) / ++b)
+        : (_(), t.lineTo(e, i), u = s, b = 0, f = g = i), p = i;
+    }
+    _();
+  }
+  function Zn(t) {
+    const e = t.options, i = e.borderDash && e.borderDash.length;
+    return !(t._decimated || t._loop || e.tension || "monotone" === e.cubicInterpolationMode || e.stepped || i)
+      ? Gn
+      : Kn;
+  }
+  Yn.id = "arc",
+    Yn.defaults = {
+      borderAlign: "center",
+      borderColor: "#fff",
+      borderJoinStyle: void 0,
+      borderRadius: 0,
+      borderWidth: 2,
+      offset: 0,
+      spacing: 0,
+      angle: void 0,
+      circular: !0,
+    },
+    Yn.defaultRoutes = { backgroundColor: "backgroundColor" };
+  const Jn = "function" == typeof Path2D;
+  function Qn(t, e, i, s) {
+    Jn && !e.options.segment
+      ? function(t, e, i, s) {
+        let n = e._path;
+        n || (n = e._path = new Path2D(), e.path(n, i, s) && n.closePath()), Un(t, e.options), t.stroke(n);
+      }(t, e, i, s)
+      : function(t, e, i, s) {
+        const { segments: n, options: o } = e, a = Zn(e);
+        for (const r of n) {
+          Un(t, o, r.style), t.beginPath(), a(t, e, r, { start: i, end: i + s - 1 }) && t.closePath(), t.stroke();
+        }
+      }(t, e, i, s);
+  }
+  class to extends Es {
+    constructor(t) {
+      super(),
+        this.animated = !0,
+        this.options = void 0,
+        this._chart = void 0,
+        this._loop = void 0,
+        this._fullLoop = void 0,
+        this._path = void 0,
+        this._points = void 0,
+        this._segments = void 0,
+        this._decimated = !1,
+        this._pointsUpdated = !1,
+        this._datasetIndex = void 0,
+        t && Object.assign(this, t);
+    }
+    updateControlPoints(t, e) {
+      const i = this.options;
+      if ((i.tension || "monotone" === i.cubicInterpolationMode) && !i.stepped && !this._pointsUpdated) {
+        const s = i.spanGaps ? this._loop : this._fullLoop;
+        Qe(this._points, i, t, s, e), this._pointsUpdated = !0;
+      }
+    }
+    set points(t) {
+      this._points = t, delete this._segments, delete this._path, this._pointsUpdated = !1;
+    }
+    get points() {
+      return this._points;
+    }
+    get segments() {
+      return this._segments || (this._segments = Di(this, this.options.segment));
+    }
+    first() {
+      const t = this.segments, e = this.points;
+      return t.length && e[t[0].start];
+    }
+    last() {
+      const t = this.segments, e = this.points, i = t.length;
+      return i && e[t[i - 1].end];
+    }
+    interpolate(t, e) {
+      const i = this.options, s = t[e], n = this.points, o = Pi(this, { property: e, start: s, end: s });
+      if (!o.length) return;
+      const a = [],
+        r = function(t) {
+          return t.stepped ? oi : t.tension || "monotone" === t.cubicInterpolationMode ? ai : ni;
+        }(i);
+      let l, h;
+      for (l = 0, h = o.length; l < h; ++l) {
+        const { start: h, end: c } = o[l], d = n[h], u = n[c];
+        if (d === u) {
+          a.push(d);
+          continue;
+        }
+        const f = r(d, u, Math.abs((s - d[e]) / (u[e] - d[e])), i.stepped);
+        f[e] = t[e], a.push(f);
+      }
+      return 1 === a.length ? a[0] : a;
+    }
+    pathSegment(t, e, i) {
+      return Zn(this)(t, this, e, i);
+    }
+    path(t, e, i) {
+      const s = this.segments, n = Zn(this);
+      let o = this._loop;
+      e = e || 0, i = i || this.points.length - e;
+      for (const a of s) o &= n(t, this, a, { start: e, end: e + i - 1 });
+      return !!o;
+    }
+    draw(t, e, i, s) {
+      const n = this.options || {};
+      (this.points || []).length && n.borderWidth && (t.save(), Qn(t, this, i, s), t.restore()),
+        this.animated && (this._pointsUpdated = !1, this._path = void 0);
+    }
+  }
+  function eo(t, e, i, s) {
+    const n = t.options, { [i]: o } = t.getProps([i], s);
+    return Math.abs(e - o) < n.radius + n.hitRadius;
+  }
+  to.id = "line",
+    to.defaults = {
+      borderCapStyle: "butt",
+      borderDash: [],
+      borderDashOffset: 0,
+      borderJoinStyle: "miter",
+      borderWidth: 3,
+      capBezierPoints: !0,
+      cubicInterpolationMode: "default",
+      fill: !1,
+      spanGaps: !1,
+      stepped: !1,
+      tension: 0,
+    },
+    to.defaultRoutes = { backgroundColor: "backgroundColor", borderColor: "borderColor" },
+    to.descriptors = { _scriptable: !0, _indexable: t => "borderDash" !== t && "fill" !== t };
+  class io extends Es {
+    constructor(t) {
+      super(),
+        this.options = void 0,
+        this.parsed = void 0,
+        this.skip = void 0,
+        this.stop = void 0,
+        t && Object.assign(this, t);
+    }
+    inRange(t, e, i) {
+      const s = this.options, { x: n, y: o } = this.getProps(["x", "y"], i);
+      return Math.pow(t - n, 2) + Math.pow(e - o, 2) < Math.pow(s.hitRadius + s.radius, 2);
+    }
+    inXRange(t, e) {
+      return eo(this, t, "x", e);
+    }
+    inYRange(t, e) {
+      return eo(this, t, "y", e);
+    }
+    getCenterPoint(t) {
+      const { x: e, y: i } = this.getProps(["x", "y"], t);
+      return { x: e, y: i };
+    }
+    size(t) {
+      let e = (t = t || this.options || {}).radius || 0;
+      e = Math.max(e, e && t.hoverRadius || 0);
+      return 2 * (e + (e && t.borderWidth || 0));
+    }
+    draw(t, e) {
+      const i = this.options;
+      this.skip || i.radius < .1 || !Se(this, e, this.size(i) / 2)
+        || (t.strokeStyle = i.borderColor,
+          t.lineWidth = i.borderWidth,
+          t.fillStyle = i.backgroundColor,
+          Me(t, i, this.x, this.y));
+    }
+    getRange() {
+      const t = this.options || {};
+      return t.radius + t.hitRadius;
+    }
+  }
+  function so(t, e) {
+    const { x: i, y: s, base: n, width: o, height: a } = t.getProps(["x", "y", "base", "width", "height"], e);
+    let r, l, h, c, d;
+    return t.horizontal
+      ? (d = a / 2, r = Math.min(i, n), l = Math.max(i, n), h = s - d, c = s + d)
+      : (d = o / 2, r = i - d, l = i + d, h = Math.min(s, n), c = Math.max(s, n)),
+      { left: r, top: h, right: l, bottom: c };
+  }
+  function no(t, e, i, s) {
+    return t ? 0 : Z(e, i, s);
+  }
+  function oo(t) {
+    const e = so(t),
+      i = e.right - e.left,
+      s = e.bottom - e.top,
+      o = function(t, e, i) {
+        const s = t.options.borderWidth, n = t.borderSkipped, o = fi(s);
+        return {
+          t: no(n.top, o.top, 0, i),
+          r: no(n.right, o.right, 0, e),
+          b: no(n.bottom, o.bottom, 0, i),
+          l: no(n.left, o.left, 0, e),
+        };
+      }(t, i / 2, s / 2),
+      a = function(t, e, i) {
+        const { enableBorderRadius: s } = t.getProps(["enableBorderRadius"]),
+          o = t.options.borderRadius,
+          a = gi(o),
+          r = Math.min(e, i),
+          l = t.borderSkipped,
+          h = s || n(o);
+        return {
+          topLeft: no(!h || l.top || l.left, a.topLeft, 0, r),
+          topRight: no(!h || l.top || l.right, a.topRight, 0, r),
+          bottomLeft: no(!h || l.bottom || l.left, a.bottomLeft, 0, r),
+          bottomRight: no(!h || l.bottom || l.right, a.bottomRight, 0, r),
+        };
+      }(t, i / 2, s / 2);
+    return {
+      outer: { x: e.left, y: e.top, w: i, h: s, radius: a },
+      inner: {
+        x: e.left + o.l,
+        y: e.top + o.t,
+        w: i - o.l - o.r,
+        h: s - o.t - o.b,
+        radius: {
+          topLeft: Math.max(0, a.topLeft - Math.max(o.t, o.l)),
+          topRight: Math.max(0, a.topRight - Math.max(o.t, o.r)),
+          bottomLeft: Math.max(0, a.bottomLeft - Math.max(o.b, o.l)),
+          bottomRight: Math.max(0, a.bottomRight - Math.max(o.b, o.r)),
+        },
+      },
+    };
+  }
+  function ao(t, e, i, s) {
+    const n = null === e, o = null === i, a = t && !(n && o) && so(t, s);
+    return a && (n || Q(e, a.left, a.right)) && (o || Q(i, a.top, a.bottom));
+  }
+  function ro(t, e) {
+    t.rect(e.x, e.y, e.w, e.h);
+  }
+  function lo(t, e, i = {}) {
+    const s = t.x !== i.x ? -e : 0,
+      n = t.y !== i.y ? -e : 0,
+      o = (t.x + t.w !== i.x + i.w ? e : 0) - s,
+      a = (t.y + t.h !== i.y + i.h ? e : 0) - n;
+    return { x: t.x + s, y: t.y + n, w: t.w + o, h: t.h + a, radius: t.radius };
+  }
+  io.id = "point",
+    io.defaults = {
+      borderWidth: 1,
+      hitRadius: 1,
+      hoverBorderWidth: 1,
+      hoverRadius: 4,
+      pointStyle: "circle",
+      radius: 3,
+      rotation: 0,
+    },
+    io.defaultRoutes = { backgroundColor: "backgroundColor", borderColor: "borderColor" };
+  class ho extends Es {
+    constructor(t) {
+      super(),
+        this.options = void 0,
+        this.horizontal = void 0,
+        this.base = void 0,
+        this.width = void 0,
+        this.height = void 0,
+        this.inflateAmount = void 0,
+        t && Object.assign(this, t);
+    }
+    draw(t) {
+      const { inflateAmount: e, options: { borderColor: i, backgroundColor: s } } = this,
+        { inner: n, outer: o } = oo(this),
+        a = (r = o.radius).topLeft || r.topRight || r.bottomLeft || r.bottomRight ? Le : ro;
+      var r;
+      t.save(),
+        o.w === n.w && o.h === n.h
+        || (t.beginPath(), a(t, lo(o, e, n)), t.clip(), a(t, lo(n, -e, o)), t.fillStyle = i, t.fill("evenodd")),
+        t.beginPath(),
+        a(t, lo(n, e)),
+        t.fillStyle = s,
+        t.fill(),
+        t.restore();
+    }
+    inRange(t, e, i) {
+      return ao(this, t, e, i);
+    }
+    inXRange(t, e) {
+      return ao(this, t, null, e);
+    }
+    inYRange(t, e) {
+      return ao(this, null, t, e);
+    }
+    getCenterPoint(t) {
+      const { x: e, y: i, base: s, horizontal: n } = this.getProps(["x", "y", "base", "horizontal"], t);
+      return { x: n ? (e + s) / 2 : e, y: n ? i : (i + s) / 2 };
+    }
+    getRange(t) {
+      return "x" === t ? this.width / 2 : this.height / 2;
+    }
+  }
+  ho.id = "bar",
+    ho.defaults = {
+      borderSkipped: "start",
+      borderWidth: 0,
+      borderRadius: 0,
+      inflateAmount: "auto",
+      pointStyle: void 0,
+    },
+    ho.defaultRoutes = { backgroundColor: "backgroundColor", borderColor: "borderColor" };
+  var co = Object.freeze({ __proto__: null, ArcElement: Yn, LineElement: to, PointElement: io, BarElement: ho });
+  function uo(t) {
+    if (t._decimated) {
+      const e = t._data;
+      delete t._decimated, delete t._data, Object.defineProperty(t, "data", { value: e });
+    }
+  }
+  function fo(t) {
+    t.data.datasets.forEach(t => {
+      uo(t);
+    });
+  }
+  var go = {
+    id: "decimation",
+    defaults: { algorithm: "min-max", enabled: !1 },
+    beforeElementsUpdate: (t, e, s) => {
+      if (!s.enabled) return void fo(t);
+      const n = t.width;
+      t.data.datasets.forEach((e, o) => {
+        const { _data: a, indexAxis: r } = e, l = t.getDatasetMeta(o), h = a || e.data;
+        if ("y" === bi([r, t.options.indexAxis])) return;
+        if (!l.controller.supportsDecimation) return;
+        const c = t.scales[l.xAxisID];
+        if ("linear" !== c.type && "time" !== c.type) return;
+        if (t.options.parsing) return;
+        let { start: d, count: u } = function(t, e) {
+          const i = e.length;
+          let s, n = 0;
+          const { iScale: o } = t, { min: a, max: r, minDefined: l, maxDefined: h } = o.getUserBounds();
+          return l && (n = Z(et(e, o.axis, a).lo, 0, i - 1)),
+            s = h ? Z(et(e, o.axis, r).hi + 1, n, i) - n : i - n,
+            { start: n, count: s };
+        }(l, h);
+        if (u <= (s.threshold || 4 * n)) return void uo(e);
+        let f;
+        switch (
+          i(a)
+          && (e._data = h,
+            delete e.data,
+            Object.defineProperty(e, "data", {
+              configurable: !0,
+              enumerable: !0,
+              get: function() {
+                return this._decimated;
+              },
+              set: function(t) {
+                this._data = t;
+              },
+            })), s.algorithm
+        ) {
+          case "lttb":
+            f = function(t, e, i, s, n) {
+              const o = n.samples || s;
+              if (o >= i) return t.slice(e, e + i);
+              const a = [], r = (i - 2) / (o - 2);
+              let l = 0;
+              const h = e + i - 1;
+              let c, d, u, f, g, p = e;
+              for (a[l++] = t[p], c = 0; c < o - 2; c++) {
+                let s, n = 0, o = 0;
+                const h = Math.floor((c + 1) * r) + 1 + e, m = Math.min(Math.floor((c + 2) * r) + 1, i) + e, b = m - h;
+                for (s = h; s < m; s++) n += t[s].x, o += t[s].y;
+                n /= b, o /= b;
+                const x = Math.floor(c * r) + 1 + e,
+                  _ = Math.min(Math.floor((c + 1) * r) + 1, i) + e,
+                  { x: y, y: v } = t[p];
+                for (u = f = -1, s = x; s < _; s++) {
+                  f = .5 * Math.abs((y - n) * (t[s].y - v) - (y - t[s].x) * (o - v)), f > u && (u = f, d = t[s], g = s);
+                }
+                a[l++] = d, p = g;
+              }
+              return a[l++] = t[h], a;
+            }(h, d, u, n, s);
+            break;
+          case "min-max":
+            f = function(t, e, s, n) {
+              let o, a, r, l, h, c, d, u, f, g, p = 0, m = 0;
+              const b = [], x = e + s - 1, _ = t[e].x, y = t[x].x - _;
+              for (o = e; o < e + s; ++o) {
+                a = t[o], r = (a.x - _) / y * n, l = a.y;
+                const e = 0 | r;
+                if (e === h) l < f ? (f = l, c = o) : l > g && (g = l, d = o), p = (m * p + a.x) / ++m;
+                else {
+                  const s = o - 1;
+                  if (!i(c) && !i(d)) {
+                    const e = Math.min(c, d), i = Math.max(c, d);
+                    e !== u && e !== s && b.push({ ...t[e], x: p }), i !== u && i !== s && b.push({ ...t[i], x: p });
+                  }
+                  o > 0 && s !== u && b.push(t[s]), b.push(a), h = e, m = 0, f = g = l, c = d = u = o;
+                }
+              }
+              return b;
+            }(h, d, u, n);
+            break;
+          default:
+            throw new Error(`Unsupported decimation algorithm '${s.algorithm}'`);
+        }
+        e._decimated = f;
+      });
+    },
+    destroy(t) {
+      fo(t);
+    },
+  };
+  function po(t, e, i, s) {
+    if (s) return;
+    let n = e[t], o = i[t];
+    return "angle" === t && (n = K(n), o = K(o)), { property: t, start: n, end: o };
+  }
+  function mo(t, e, i) {
+    for (; e > t; e--) {
+      const t = i[e];
+      if (!isNaN(t.x) && !isNaN(t.y)) break;
+    }
+    return e;
+  }
+  function bo(t, e, i, s) {
+    return t && e ? s(t[i], e[i]) : t ? t[i] : e ? e[i] : 0;
+  }
+  function xo(t, e) {
+    let i = [], n = !1;
+    return s(t) ? (n = !0, i = t) : i = function(t, e) {
+      const { x: i = null, y: s = null } = t || {}, n = e.points, o = [];
+      return e.segments.forEach(({ start: t, end: e }) => {
+        e = mo(t, e, n);
+        const a = n[t], r = n[e];
+        null !== s
+          ? (o.push({ x: a.x, y: s }), o.push({ x: r.x, y: s }))
+          : null !== i && (o.push({ x: i, y: a.y }), o.push({ x: i, y: r.y }));
+      }),
+        o;
+    }(t, e),
+      i.length ? new to({ points: i, options: { tension: 0 }, _loop: n, _fullLoop: n }) : null;
+  }
+  function _o(t) {
+    return t && !1 !== t.fill;
+  }
+  function yo(t, e, i) {
+    let s = t[e].fill;
+    const n = [e];
+    let a;
+    if (!i) return s;
+    for (; !1 !== s && -1 === n.indexOf(s);) {
+      if (!o(s)) return s;
+      if (a = t[s], !a) return !1;
+      if (a.visible) return s;
+      n.push(s), s = a.fill;
+    }
+    return !1;
+  }
+  function vo(t, e, i) {
+    const s = function(t) {
+      const e = t.options, i = e.fill;
+      let s = r(i && i.target, i);
+      void 0 === s && (s = !!e.backgroundColor);
+      if (!1 === s || null === s) return !1;
+      if (!0 === s) return "origin";
+      return s;
+    }(t);
+    if (n(s)) return !isNaN(s.value) && s;
+    let a = parseFloat(s);
+    return o(a) && Math.floor(a) === a
+      ? function(t, e, i, s) {
+        "-" !== t && "+" !== t || (i = e + i);
+        if (i === e || i < 0 || i >= s) return !1;
+        return i;
+      }(s[0], e, a, i)
+      : ["origin", "start", "end", "stack", "shape"].indexOf(s) >= 0 && s;
+  }
+  function wo(t, e, i) {
+    const s = [];
+    for (let n = 0; n < i.length; n++) {
+      const o = i[n], { first: a, last: r, point: l } = Mo(o, e, "x");
+      if (!(!l || a && r)) {
+        if (a) s.unshift(l);
+        else if (t.push(l), !r) break;
+      }
+    }
+    t.push(...s);
+  }
+  function Mo(t, e, i) {
+    const s = t.interpolate(e, i);
+    if (!s) return {};
+    const n = s[i], o = t.segments, a = t.points;
+    let r = !1, l = !1;
+    for (let t = 0; t < o.length; t++) {
+      const e = o[t], s = a[e.start][i], h = a[e.end][i];
+      if (Q(n, s, h)) {
+        r = n === s, l = n === h;
+        break;
+      }
+    }
+    return { first: r, last: l, point: s };
+  }
+  class ko {
+    constructor(t) {
+      this.x = t.x, this.y = t.y, this.radius = t.radius;
+    }
+    pathSegment(t, e, i) {
+      const { x: s, y: n, radius: o } = this;
+      return e = e || { start: 0, end: O }, t.arc(s, n, o, e.end, e.start, !0), !i.bounds;
+    }
+    interpolate(t) {
+      const { x: e, y: i, radius: s } = this, n = t.angle;
+      return { x: e + Math.cos(n) * s, y: i + Math.sin(n) * s, angle: n };
+    }
+  }
+  function So(t) {
+    const { chart: e, fill: i, line: s } = t;
+    if (o(i)) {
+      return function(t, e) {
+        const i = t.getDatasetMeta(e);
+        return i && t.isDatasetVisible(e) ? i.dataset : null;
+      }(e, i);
+    }
+    if ("stack" === i) {
+      return function(t) {
+        const { scale: e, index: i, line: s } = t,
+          n = [],
+          o = s.segments,
+          a = s.points,
+          r = function(t, e) {
+            const i = [], s = t.getMatchingVisibleMetas("line");
+            for (let t = 0; t < s.length; t++) {
+              const n = s[t];
+              if (n.index === e) break;
+              n.hidden || i.unshift(n.dataset);
+            }
+            return i;
+          }(e, i);
+        r.push(xo({ x: null, y: e.bottom }, s));
+        for (let t = 0; t < o.length; t++) {
+          const e = o[t];
+          for (let t = e.start; t <= e.end; t++) wo(n, a[t], r);
+        }
+        return new to({ points: n, options: {} });
+      }(t);
+    }
+    if ("shape" === i) return !0;
+    const a = function(t) {
+      if ((t.scale || {}).getPointPositionForValue) {
+        return function(t) {
+          const { scale: e, fill: i } = t,
+            s = e.options,
+            o = e.getLabels().length,
+            a = s.reverse ? e.max : e.min,
+            r = function(t, e, i) {
+              let s;
+              return s = "start" === t
+                ? i
+                : "end" === t
+                ? e.options.reverse ? e.min : e.max
+                : n(t)
+                ? t.value
+                : e.getBaseValue(),
+                s;
+            }(i, e, a),
+            l = [];
+          if (s.grid.circular) {
+            const t = e.getPointPositionForValue(0, a);
+            return new ko({ x: t.x, y: t.y, radius: e.getDistanceFromCenterForValue(r) });
+          }
+          for (let t = 0; t < o; ++t) l.push(e.getPointPositionForValue(t, r));
+          return l;
+        }(t);
+      }
+      return function(t) {
+        const { scale: e = {}, fill: i } = t,
+          s = function(t, e) {
+            let i = null;
+            return "start" === t
+              ? i = e.bottom
+              : "end" === t
+              ? i = e.top
+              : n(t)
+              ? i = e.getPixelForValue(t.value)
+              : e.getBasePixel && (i = e.getBasePixel()),
+              i;
+          }(i, e);
+        if (o(s)) {
+          const t = e.isHorizontal();
+          return { x: t ? s : null, y: t ? null : s };
+        }
+        return null;
+      }(t);
+    }(t);
+    return a instanceof ko ? a : xo(a, s);
+  }
+  function Po(t, e, i) {
+    const s = So(e),
+      { line: n, scale: o, axis: a } = e,
+      r = n.options,
+      l = r.fill,
+      h = r.backgroundColor,
+      { above: c = h, below: d = h } = l || {};
+    s && n.points.length && (Pe(t, i),
+      function(t, e) {
+        const { line: i, target: s, above: n, below: o, area: a, scale: r } = e, l = i._loop ? "angle" : e.axis;
+        t.save(),
+          "x" === l && o !== n
+          && (Do(t, s, a.top),
+            Oo(t, { line: i, target: s, color: n, scale: r, property: l }),
+            t.restore(),
+            t.save(),
+            Do(t, s, a.bottom));
+        Oo(t, { line: i, target: s, color: o, scale: r, property: l }), t.restore();
+      }(t, { line: n, target: s, above: c, below: d, area: i, scale: o, axis: a }),
+      De(t));
+  }
+  function Do(t, e, i) {
+    const { segments: s, points: n } = e;
+    let o = !0, a = !1;
+    t.beginPath();
+    for (const r of s) {
+      const { start: s, end: l } = r, h = n[s], c = n[mo(s, l, n)];
+      o ? (t.moveTo(h.x, h.y), o = !1) : (t.lineTo(h.x, i), t.lineTo(h.x, h.y)),
+        a = !!e.pathSegment(t, r, { move: a }),
+        a ? t.closePath() : t.lineTo(c.x, i);
+    }
+    t.lineTo(e.first().x, i), t.closePath(), t.clip();
+  }
+  function Oo(t, e) {
+    const { line: i, target: s, property: n, color: o, scale: a } = e,
+      r = function(t, e, i) {
+        const s = t.segments, n = t.points, o = e.points, a = [];
+        for (const t of s) {
+          let { start: s, end: r } = t;
+          r = mo(s, r, n);
+          const l = po(i, n[s], n[r], t.loop);
+          if (!e.segments) {
+            a.push({ source: t, target: l, start: n[s], end: n[r] });
+            continue;
+          }
+          const h = Pi(e, l);
+          for (const e of h) {
+            const s = po(i, o[e.start], o[e.end], e.loop), r = Si(t, n, s);
+            for (const t of r) {
+              a.push({
+                source: t,
+                target: e,
+                start: { [i]: bo(l, s, "start", Math.max) },
+                end: { [i]: bo(l, s, "end", Math.min) },
+              });
+            }
+          }
+        }
+        return a;
+      }(i, s, n);
+    for (const { source: e, target: l, start: h, end: c } of r) {
+      const { style: { backgroundColor: r = o } = {} } = e, d = !0 !== s;
+      t.save(), t.fillStyle = r, Co(t, a, d && po(n, h, c)), t.beginPath();
+      const u = !!i.pathSegment(t, e);
+      let f;
+      if (d) {
+        u ? t.closePath() : Ao(t, s, c, n);
+        const e = !!s.pathSegment(t, l, { move: u, reverse: !0 });
+        f = u && e, f || Ao(t, s, h, n);
+      }
+      t.closePath(), t.fill(f ? "evenodd" : "nonzero"), t.restore();
+    }
+  }
+  function Co(t, e, i) {
+    const { top: s, bottom: n } = e.chart.chartArea, { property: o, start: a, end: r } = i || {};
+    "x" === o && (t.beginPath(), t.rect(a, s, r - a, n - s), t.clip());
+  }
+  function Ao(t, e, i, s) {
+    const n = e.interpolate(i, s);
+    n && t.lineTo(n.x, n.y);
+  }
+  var To = {
+    id: "filler",
+    afterDatasetsUpdate(t, e, i) {
+      const s = (t.data.datasets || []).length, n = [];
+      let o, a, r, l;
+      for (a = 0; a < s; ++a) {
+        o = t.getDatasetMeta(a),
+          r = o.dataset,
+          l = null,
+          r && r.options && r instanceof to
+          && (l = {
+            visible: t.isDatasetVisible(a),
+            index: a,
+            fill: vo(r, a, s),
+            chart: t,
+            axis: o.controller.options.indexAxis,
+            scale: o.vScale,
+            line: r,
+          }),
+          o.$filler = l,
+          n.push(l);
+      }
+      for (a = 0; a < s; ++a) l = n[a], l && !1 !== l.fill && (l.fill = yo(n, a, i.propagate));
+    },
+    beforeDraw(t, e, i) {
+      const s = "beforeDraw" === i.drawTime, n = t.getSortedVisibleDatasetMetas(), o = t.chartArea;
+      for (let e = n.length - 1; e >= 0; --e) {
+        const i = n[e].$filler;
+        i && (i.line.updateControlPoints(o, i.axis), s && i.fill && Po(t.ctx, i, o));
+      }
+    },
+    beforeDatasetsDraw(t, e, i) {
+      if ("beforeDatasetsDraw" !== i.drawTime) return;
+      const s = t.getSortedVisibleDatasetMetas();
+      for (let e = s.length - 1; e >= 0; --e) {
+        const i = s[e].$filler;
+        _o(i) && Po(t.ctx, i, t.chartArea);
+      }
+    },
+    beforeDatasetDraw(t, e, i) {
+      const s = e.meta.$filler;
+      _o(s) && "beforeDatasetDraw" === i.drawTime && Po(t.ctx, s, t.chartArea);
+    },
+    defaults: { propagate: !0, drawTime: "beforeDatasetDraw" },
+  };
+  const Lo = (t, e) => {
+    let { boxHeight: i = e, boxWidth: s = e } = t;
+    return t.usePointStyle && (i = Math.min(i, e), s = t.pointStyleWidth || Math.min(s, e)),
+      { boxWidth: s, boxHeight: i, itemHeight: Math.max(e, i) };
+  };
+  class Eo extends Es {
+    constructor(t) {
+      super(),
+        this._added = !1,
+        this.legendHitBoxes = [],
+        this._hoveredItem = null,
+        this.doughnutMode = !1,
+        this.chart = t.chart,
+        this.options = t.options,
+        this.ctx = t.ctx,
+        this.legendItems = void 0,
+        this.columnSizes = void 0,
+        this.lineWidths = void 0,
+        this.maxHeight = void 0,
+        this.maxWidth = void 0,
+        this.top = void 0,
+        this.bottom = void 0,
+        this.left = void 0,
+        this.right = void 0,
+        this.height = void 0,
+        this.width = void 0,
+        this._margins = void 0,
+        this.position = void 0,
+        this.weight = void 0,
+        this.fullSize = void 0;
+    }
+    update(t, e, i) {
+      this.maxWidth = t, this.maxHeight = e, this._margins = i, this.setDimensions(), this.buildLabels(), this.fit();
+    }
+    setDimensions() {
+      this.isHorizontal()
+        ? (this.width = this.maxWidth, this.left = this._margins.left, this.right = this.width)
+        : (this.height = this.maxHeight, this.top = this._margins.top, this.bottom = this.height);
+    }
+    buildLabels() {
+      const t = this.options.labels || {};
+      let e = c(t.generateLabels, [this.chart], this) || [];
+      t.filter && (e = e.filter(e => t.filter(e, this.chart.data))),
+        t.sort && (e = e.sort((e, i) => t.sort(e, i, this.chart.data))),
+        this.options.reverse && e.reverse(),
+        this.legendItems = e;
+    }
+    fit() {
+      const { options: t, ctx: e } = this;
+      if (!t.display) return void (this.width = this.height = 0);
+      const i = t.labels,
+        s = mi(i.font),
+        n = s.size,
+        o = this._computeTitleHeight(),
+        { boxWidth: a, itemHeight: r } = Lo(i, n);
+      let l, h;
+      e.font = s.string,
+        this.isHorizontal()
+          ? (l = this.maxWidth, h = this._fitRows(o, n, a, r) + 10)
+          : (h = this.maxHeight, l = this._fitCols(o, n, a, r) + 10),
+        this.width = Math.min(l, t.maxWidth || this.maxWidth),
+        this.height = Math.min(h, t.maxHeight || this.maxHeight);
+    }
+    _fitRows(t, e, i, s) {
+      const { ctx: n, maxWidth: o, options: { labels: { padding: a } } } = this,
+        r = this.legendHitBoxes = [],
+        l = this.lineWidths = [0],
+        h = s + a;
+      let c = t;
+      n.textAlign = "left", n.textBaseline = "middle";
+      let d = -1, u = -h;
+      return this.legendItems.forEach((t, f) => {
+        const g = i + e / 2 + n.measureText(t.text).width;
+        (0 === f || l[l.length - 1] + g + 2 * a > o) && (c += h, l[l.length - (f > 0 ? 0 : 1)] = 0, u += h, d++),
+          r[f] = { left: 0, top: u, row: d, width: g, height: s },
+          l[l.length - 1] += g + a;
+      }),
+        c;
+    }
+    _fitCols(t, e, i, s) {
+      const { ctx: n, maxHeight: o, options: { labels: { padding: a } } } = this,
+        r = this.legendHitBoxes = [],
+        l = this.columnSizes = [],
+        h = o - t;
+      let c = a, d = 0, u = 0, f = 0, g = 0;
+      return this.legendItems.forEach((t, o) => {
+        const p = i + e / 2 + n.measureText(t.text).width;
+        o > 0 && u + s + 2 * a > h && (c += d + a, l.push({ width: d, height: u }), f += d + a, g++, d = u = 0),
+          r[o] = { left: f, top: u, col: g, width: p, height: s },
+          d = Math.max(d, p),
+          u += s + a;
+      }),
+        c += d,
+        l.push({ width: d, height: u }),
+        c;
+    }
+    adjustHitBoxes() {
+      if (!this.options.display) return;
+      const t = this._computeTitleHeight(),
+        { legendHitBoxes: e, options: { align: i, labels: { padding: s }, rtl: n } } = this,
+        o = yi(n, this.left, this.width);
+      if (this.isHorizontal()) {
+        let n = 0, a = ut(i, this.left + s, this.right - this.lineWidths[n]);
+        for (const r of e) {
+          n !== r.row && (n = r.row, a = ut(i, this.left + s, this.right - this.lineWidths[n])),
+            r.top += this.top + t + s,
+            r.left = o.leftForLtr(o.x(a), r.width),
+            a += r.width + s;
+        }
+      } else {
+        let n = 0, a = ut(i, this.top + t + s, this.bottom - this.columnSizes[n].height);
+        for (const r of e) {
+          r.col !== n && (n = r.col, a = ut(i, this.top + t + s, this.bottom - this.columnSizes[n].height)),
+            r.top = a,
+            r.left += this.left + s,
+            r.left = o.leftForLtr(o.x(r.left), r.width),
+            a += r.height + s;
+        }
+      }
+    }
+    isHorizontal() {
+      return "top" === this.options.position || "bottom" === this.options.position;
+    }
+    draw() {
+      if (this.options.display) {
+        const t = this.ctx;
+        Pe(t, this), this._draw(), De(t);
+      }
+    }
+    _draw() {
+      const { options: t, columnSizes: e, lineWidths: i, ctx: s } = this,
+        { align: n, labels: o } = t,
+        a = ne.color,
+        l = yi(t.rtl, this.left, this.width),
+        h = mi(o.font),
+        { color: c, padding: d } = o,
+        u = h.size,
+        f = u / 2;
+      let g;
+      this.drawTitle(),
+        s.textAlign = l.textAlign("left"),
+        s.textBaseline = "middle",
+        s.lineWidth = .5,
+        s.font = h.string;
+      const { boxWidth: p, boxHeight: m, itemHeight: b } = Lo(o, u),
+        x = this.isHorizontal(),
+        _ = this._computeTitleHeight();
+      g = x
+        ? { x: ut(n, this.left + d, this.right - i[0]), y: this.top + d + _, line: 0 }
+        : { x: this.left + d, y: ut(n, this.top + _ + d, this.bottom - e[0].height), line: 0 },
+        vi(this.ctx, t.textDirection);
+      const y = b + d;
+      this.legendItems.forEach((v, w) => {
+        s.strokeStyle = v.fontColor || c, s.fillStyle = v.fontColor || c;
+        const M = s.measureText(v.text).width,
+          k = l.textAlign(v.textAlign || (v.textAlign = o.textAlign)),
+          S = p + f + M;
+        let P = g.x, D = g.y;
+        l.setWidth(this.width),
+          x
+            ? w > 0 && P + S + d > this.right
+              && (D = g.y += y, g.line++, P = g.x = ut(n, this.left + d, this.right - i[g.line]))
+            : w > 0 && D + y > this.bottom
+              && (P = g.x = P + e[g.line].width + d,
+                g.line++,
+                D = g.y = ut(n, this.top + _ + d, this.bottom - e[g.line].height));
+        !function(t, e, i) {
+          if (isNaN(p) || p <= 0 || isNaN(m) || m < 0) return;
+          s.save();
+          const n = r(i.lineWidth, 1);
+          if (
+            s.fillStyle = r(i.fillStyle, a),
+              s.lineCap = r(i.lineCap, "butt"),
+              s.lineDashOffset = r(i.lineDashOffset, 0),
+              s.lineJoin = r(i.lineJoin, "miter"),
+              s.lineWidth = n,
+              s.strokeStyle = r(i.strokeStyle, a),
+              s.setLineDash(r(i.lineDash, [])),
+              o.usePointStyle
+          ) {
+            const a = { radius: m * Math.SQRT2 / 2, pointStyle: i.pointStyle, rotation: i.rotation, borderWidth: n },
+              r = l.xPlus(t, p / 2);
+            ke(s, a, r, e + f, o.pointStyleWidth && p);
+          } else {
+            const o = e + Math.max((u - m) / 2, 0), a = l.leftForLtr(t, p), r = gi(i.borderRadius);
+            s.beginPath(),
+              Object.values(r).some(t => 0 !== t) ? Le(s, { x: a, y: o, w: p, h: m, radius: r }) : s.rect(a, o, p, m),
+              s.fill(),
+              0 !== n && s.stroke();
+          }
+          s.restore();
+        }(l.x(P), D, v),
+          P = ft(k, P + p + f, x ? P + S : this.right, t.rtl),
+          function(t, e, i) {
+            Ae(s, i.text, t, e + b / 2, h, { strikethrough: i.hidden, textAlign: l.textAlign(i.textAlign) });
+          }(l.x(P), D, v),
+          x ? g.x += S + d : g.y += y;
+      }), wi(this.ctx, t.textDirection);
+    }
+    drawTitle() {
+      const t = this.options, e = t.title, i = mi(e.font), s = pi(e.padding);
+      if (!e.display) return;
+      const n = yi(t.rtl, this.left, this.width), o = this.ctx, a = e.position, r = i.size / 2, l = s.top + r;
+      let h, c = this.left, d = this.width;
+      if (this.isHorizontal()) d = Math.max(...this.lineWidths), h = this.top + l, c = ut(t.align, c, this.right - d);
+      else {
+        const e = this.columnSizes.reduce((t, e) => Math.max(t, e.height), 0);
+        h = l + ut(t.align, this.top, this.bottom - e - t.labels.padding - this._computeTitleHeight());
+      }
+      const u = ut(a, c, c + d);
+      o.textAlign = n.textAlign(dt(a)),
+        o.textBaseline = "middle",
+        o.strokeStyle = e.color,
+        o.fillStyle = e.color,
+        o.font = i.string,
+        Ae(o, e.text, u, h, i);
+    }
+    _computeTitleHeight() {
+      const t = this.options.title, e = mi(t.font), i = pi(t.padding);
+      return t.display ? e.lineHeight + i.height : 0;
+    }
+    _getLegendItemAt(t, e) {
+      let i, s, n;
+      if (Q(t, this.left, this.right) && Q(e, this.top, this.bottom)) {
+        for (n = this.legendHitBoxes, i = 0; i < n.length; ++i) {
+          if (s = n[i], Q(t, s.left, s.left + s.width) && Q(e, s.top, s.top + s.height)) return this.legendItems[i];
+        }
+      }
+      return null;
+    }
+    handleEvent(t) {
+      const e = this.options;
+      if (
+        !function(t, e) {
+          if (("mousemove" === t || "mouseout" === t) && (e.onHover || e.onLeave)) return !0;
+          if (e.onClick && ("click" === t || "mouseup" === t)) return !0;
+          return !1;
+        }(t.type, e)
+      ) return;
+      const i = this._getLegendItemAt(t.x, t.y);
+      if ("mousemove" === t.type || "mouseout" === t.type) {
+        const o = this._hoveredItem,
+          a = (n = i, null !== (s = o) && null !== n && s.datasetIndex === n.datasetIndex && s.index === n.index);
+        o && !a && c(e.onLeave, [t, o, this], this), this._hoveredItem = i, i && !a && c(e.onHover, [t, i, this], this);
+      } else i && c(e.onClick, [t, i, this], this);
+      var s, n;
+    }
+  }
+  var Ro = {
+    id: "legend",
+    _element: Eo,
+    start(t, e, i) {
+      const s = t.legend = new Eo({ ctx: t.ctx, options: i, chart: t });
+      Zi.configure(t, s, i), Zi.addBox(t, s);
+    },
+    stop(t) {
+      Zi.removeBox(t, t.legend), delete t.legend;
+    },
+    beforeUpdate(t, e, i) {
+      const s = t.legend;
+      Zi.configure(t, s, i), s.options = i;
+    },
+    afterUpdate(t) {
+      const e = t.legend;
+      e.buildLabels(), e.adjustHitBoxes();
+    },
+    afterEvent(t, e) {
+      e.replay || t.legend.handleEvent(e.event);
+    },
+    defaults: {
+      display: !0,
+      position: "top",
+      align: "center",
+      fullSize: !0,
+      reverse: !1,
+      weight: 1e3,
+      onClick(t, e, i) {
+        const s = e.datasetIndex, n = i.chart;
+        n.isDatasetVisible(s) ? (n.hide(s), e.hidden = !0) : (n.show(s), e.hidden = !1);
+      },
+      onHover: null,
+      onLeave: null,
+      labels: {
+        color: t => t.chart.options.color,
+        boxWidth: 40,
+        padding: 10,
+        generateLabels(t) {
+          const e = t.data.datasets,
+            { labels: { usePointStyle: i, pointStyle: s, textAlign: n, color: o } } = t.legend.options;
+          return t._getSortedDatasetMetas().map(t => {
+            const a = t.controller.getStyle(i ? 0 : void 0), r = pi(a.borderWidth);
+            return {
+              text: e[t.index].label,
+              fillStyle: a.backgroundColor,
+              fontColor: o,
+              hidden: !t.visible,
+              lineCap: a.borderCapStyle,
+              lineDash: a.borderDash,
+              lineDashOffset: a.borderDashOffset,
+              lineJoin: a.borderJoinStyle,
+              lineWidth: (r.width + r.height) / 4,
+              strokeStyle: a.borderColor,
+              pointStyle: s || a.pointStyle,
+              rotation: a.rotation,
+              textAlign: n || a.textAlign,
+              borderRadius: 0,
+              datasetIndex: t.index,
+            };
+          }, this);
+        },
+      },
+      title: { color: t => t.chart.options.color, display: !1, position: "center", text: "" },
+    },
+    descriptors: {
+      _scriptable: t => !t.startsWith("on"),
+      labels: { _scriptable: t => !["generateLabels", "filter", "sort"].includes(t) },
+    },
+  };
+  class Io extends Es {
+    constructor(t) {
+      super(),
+        this.chart = t.chart,
+        this.options = t.options,
+        this.ctx = t.ctx,
+        this._padding = void 0,
+        this.top = void 0,
+        this.bottom = void 0,
+        this.left = void 0,
+        this.right = void 0,
+        this.width = void 0,
+        this.height = void 0,
+        this.position = void 0,
+        this.weight = void 0,
+        this.fullSize = void 0;
+    }
+    update(t, e) {
+      const i = this.options;
+      if (this.left = 0, this.top = 0, !i.display) {
+        return void (this.width =
+          this.height =
+          this.right =
+          this.bottom =
+            0);
+      }
+      this.width = this.right = t, this.height = this.bottom = e;
+      const n = s(i.text) ? i.text.length : 1;
+      this._padding = pi(i.padding);
+      const o = n * mi(i.font).lineHeight + this._padding.height;
+      this.isHorizontal() ? this.height = o : this.width = o;
+    }
+    isHorizontal() {
+      const t = this.options.position;
+      return "top" === t || "bottom" === t;
+    }
+    _drawArgs(t) {
+      const { top: e, left: i, bottom: s, right: n, options: o } = this, a = o.align;
+      let r, l, h, c = 0;
+      return this.isHorizontal()
+        ? (l = ut(a, i, n), h = e + t, r = n - i)
+        : ("left" === o.position ? (l = i + t, h = ut(a, s, e), c = -.5 * D) : (l = n - t, h = ut(a, e, s), c = .5 * D),
+          r = s - e),
+        { titleX: l, titleY: h, maxWidth: r, rotation: c };
+    }
+    draw() {
+      const t = this.ctx, e = this.options;
+      if (!e.display) return;
+      const i = mi(e.font),
+        s = i.lineHeight / 2 + this._padding.top,
+        { titleX: n, titleY: o, maxWidth: a, rotation: r } = this._drawArgs(s);
+      Ae(t, e.text, 0, 0, i, {
+        color: e.color,
+        maxWidth: a,
+        rotation: r,
+        textAlign: dt(e.align),
+        textBaseline: "middle",
+        translation: [n, o],
+      });
+    }
+  }
+  var zo = {
+    id: "title",
+    _element: Io,
+    start(t, e, i) {
+      !function(t, e) {
+        const i = new Io({ ctx: t.ctx, options: e, chart: t });
+        Zi.configure(t, i, e), Zi.addBox(t, i), t.titleBlock = i;
+      }(t, i);
+    },
+    stop(t) {
+      const e = t.titleBlock;
+      Zi.removeBox(t, e), delete t.titleBlock;
+    },
+    beforeUpdate(t, e, i) {
+      const s = t.titleBlock;
+      Zi.configure(t, s, i), s.options = i;
+    },
+    defaults: {
+      align: "center",
+      display: !1,
+      font: { weight: "bold" },
+      fullSize: !0,
+      padding: 10,
+      position: "top",
+      text: "",
+      weight: 2e3,
+    },
+    defaultRoutes: { color: "color" },
+    descriptors: { _scriptable: !0, _indexable: !1 },
+  };
+  const Fo = new WeakMap();
+  var Vo = {
+    id: "subtitle",
+    start(t, e, i) {
+      const s = new Io({ ctx: t.ctx, options: i, chart: t });
+      Zi.configure(t, s, i), Zi.addBox(t, s), Fo.set(t, s);
+    },
+    stop(t) {
+      Zi.removeBox(t, Fo.get(t)), Fo.delete(t);
+    },
+    beforeUpdate(t, e, i) {
+      const s = Fo.get(t);
+      Zi.configure(t, s, i), s.options = i;
+    },
+    defaults: {
+      align: "center",
+      display: !1,
+      font: { weight: "normal" },
+      fullSize: !0,
+      padding: 0,
+      position: "top",
+      text: "",
+      weight: 1500,
+    },
+    defaultRoutes: { color: "color" },
+    descriptors: { _scriptable: !0, _indexable: !1 },
+  };
+  const Bo = {
+    average(t) {
+      if (!t.length) return !1;
+      let e, i, s = 0, n = 0, o = 0;
+      for (e = 0, i = t.length; e < i; ++e) {
+        const i = t[e].element;
+        if (i && i.hasValue()) {
+          const t = i.tooltipPosition();
+          s += t.x, n += t.y, ++o;
+        }
+      }
+      return { x: s / o, y: n / o };
+    },
+    nearest(t, e) {
+      if (!t.length) return !1;
+      let i, s, n, o = e.x, a = e.y, r = Number.POSITIVE_INFINITY;
+      for (i = 0, s = t.length; i < s; ++i) {
+        const s = t[i].element;
+        if (s && s.hasValue()) {
+          const t = X(e, s.getCenterPoint());
+          t < r && (r = t, n = s);
+        }
+      }
+      if (n) {
+        const t = n.tooltipPosition();
+        o = t.x, a = t.y;
+      }
+      return { x: o, y: a };
+    },
+  };
+  function No(t, e) {
+    return e && (s(e) ? Array.prototype.push.apply(t, e) : t.push(e)), t;
+  }
+  function Wo(t) {
+    return ("string" == typeof t || t instanceof String) && t.indexOf("\n") > -1 ? t.split("\n") : t;
+  }
+  function jo(t, e) {
+    const { element: i, datasetIndex: s, index: n } = e,
+      o = t.getDatasetMeta(s).controller,
+      { label: a, value: r } = o.getLabelAndValue(n);
+    return {
+      chart: t,
+      label: a,
+      parsed: o.getParsed(n),
+      raw: t.data.datasets[s].data[n],
+      formattedValue: r,
+      dataset: o.getDataset(),
+      dataIndex: n,
+      datasetIndex: s,
+      element: i,
+    };
+  }
+  function Ho(t, e) {
+    const i = t.chart.ctx,
+      { body: s, footer: n, title: o } = t,
+      { boxWidth: a, boxHeight: r } = e,
+      l = mi(e.bodyFont),
+      h = mi(e.titleFont),
+      c = mi(e.footerFont),
+      u = o.length,
+      f = n.length,
+      g = s.length,
+      p = pi(e.padding);
+    let m = p.height, b = 0, x = s.reduce((t, e) => t + e.before.length + e.lines.length + e.after.length, 0);
+    if (
+      x += t.beforeBody.length + t.afterBody.length,
+        u && (m += u * h.lineHeight + (u - 1) * e.titleSpacing + e.titleMarginBottom),
+        x
+    ) {
+      m += g * (e.displayColors ? Math.max(r, l.lineHeight) : l.lineHeight) + (x - g) * l.lineHeight
+        + (x - 1) * e.bodySpacing;
+    }
+    f && (m += e.footerMarginTop + f * c.lineHeight + (f - 1) * e.footerSpacing);
+    let _ = 0;
+    const y = function(t) {
+      b = Math.max(b, i.measureText(t).width + _);
+    };
+    return i.save(),
+      i.font = h.string,
+      d(t.title, y),
+      i.font = l.string,
+      d(t.beforeBody.concat(t.afterBody), y),
+      _ = e.displayColors ? a + 2 + e.boxPadding : 0,
+      d(s, t => {
+        d(t.before, y), d(t.lines, y), d(t.after, y);
+      }),
+      _ = 0,
+      i.font = c.string,
+      d(t.footer, y),
+      i.restore(),
+      b += p.width,
+      { width: b, height: m };
+  }
+  function $o(t, e, i, s) {
+    const { x: n, width: o } = i, { width: a, chartArea: { left: r, right: l } } = t;
+    let h = "center";
+    return "center" === s
+      ? h = n <= (r + l) / 2 ? "left" : "right"
+      : n <= o / 2
+      ? h = "left"
+      : n >= a - o / 2 && (h = "right"),
+      function(t, e, i, s) {
+        const { x: n, width: o } = s, a = i.caretSize + i.caretPadding;
+        return "left" === t && n + o + a > e.width || "right" === t && n - o - a < 0 || void 0;
+      }(h, t, e, i) && (h = "center"),
+      h;
+  }
+  function Yo(t, e, i) {
+    const s = i.yAlign || e.yAlign || function(t, e) {
+      const { y: i, height: s } = e;
+      return i < s / 2 ? "top" : i > t.height - s / 2 ? "bottom" : "center";
+    }(t, i);
+    return { xAlign: i.xAlign || e.xAlign || $o(t, e, i, s), yAlign: s };
+  }
+  function Uo(t, e, i, s) {
+    const { caretSize: n, caretPadding: o, cornerRadius: a } = t,
+      { xAlign: r, yAlign: l } = i,
+      h = n + o,
+      { topLeft: c, topRight: d, bottomLeft: u, bottomRight: f } = gi(a);
+    let g = function(t, e) {
+      let { x: i, width: s } = t;
+      return "right" === e ? i -= s : "center" === e && (i -= s / 2), i;
+    }(e, r);
+    const p = function(t, e, i) {
+      let { y: s, height: n } = t;
+      return "top" === e ? s += i : s -= "bottom" === e ? n + i : n / 2, s;
+    }(e, l, h);
+    return "center" === l
+      ? "left" === r ? g += h : "right" === r && (g -= h)
+      : "left" === r
+      ? g -= Math.max(c, u) + n
+      : "right" === r && (g += Math.max(d, f) + n),
+      { x: Z(g, 0, s.width - e.width), y: Z(p, 0, s.height - e.height) };
+  }
+  function Xo(t, e, i) {
+    const s = pi(i.padding);
+    return "center" === e ? t.x + t.width / 2 : "right" === e ? t.x + t.width - s.right : t.x + s.left;
+  }
+  function qo(t) {
+    return No([], Wo(t));
+  }
+  function Ko(t, e) {
+    const i = e && e.dataset && e.dataset.tooltip && e.dataset.tooltip.callbacks;
+    return i ? t.override(i) : t;
+  }
+  class Go extends Es {
+    constructor(t) {
+      super(),
+        this.opacity = 0,
+        this._active = [],
+        this._eventPosition = void 0,
+        this._size = void 0,
+        this._cachedAnimations = void 0,
+        this._tooltipItems = [],
+        this.$animations = void 0,
+        this.$context = void 0,
+        this.chart = t.chart || t._chart,
+        this._chart = this.chart,
+        this.options = t.options,
+        this.dataPoints = void 0,
+        this.title = void 0,
+        this.beforeBody = void 0,
+        this.body = void 0,
+        this.afterBody = void 0,
+        this.footer = void 0,
+        this.xAlign = void 0,
+        this.yAlign = void 0,
+        this.x = void 0,
+        this.y = void 0,
+        this.height = void 0,
+        this.width = void 0,
+        this.caretX = void 0,
+        this.caretY = void 0,
+        this.labelColors = void 0,
+        this.labelPointStyles = void 0,
+        this.labelTextColors = void 0;
+    }
+    initialize(t) {
+      this.options = t, this._cachedAnimations = void 0, this.$context = void 0;
+    }
+    _resolveAnimations() {
+      const t = this._cachedAnimations;
+      if (t) return t;
+      const e = this.chart,
+        i = this.options.setContext(this.getContext()),
+        s = i.enabled && e.options.animation && i.animations,
+        n = new ys(this.chart, s);
+      return s._cacheable && (this._cachedAnimations = Object.freeze(n)), n;
+    }
+    getContext() {
+      return this.$context
+        || (this.$context =
+          (t = this.chart.getContext(),
+            e = this,
+            i = this._tooltipItems,
+            _i(t, { tooltip: e, tooltipItems: i, type: "tooltip" })));
+      var t, e, i;
+    }
+    getTitle(t, e) {
+      const { callbacks: i } = e,
+        s = i.beforeTitle.apply(this, [t]),
+        n = i.title.apply(this, [t]),
+        o = i.afterTitle.apply(this, [t]);
+      let a = [];
+      return a = No(a, Wo(s)), a = No(a, Wo(n)), a = No(a, Wo(o)), a;
+    }
+    getBeforeBody(t, e) {
+      return qo(e.callbacks.beforeBody.apply(this, [t]));
+    }
+    getBody(t, e) {
+      const { callbacks: i } = e, s = [];
+      return d(t, t => {
+        const e = { before: [], lines: [], after: [] }, n = Ko(i, t);
+        No(e.before, Wo(n.beforeLabel.call(this, t))),
+          No(e.lines, n.label.call(this, t)),
+          No(e.after, Wo(n.afterLabel.call(this, t))),
+          s.push(e);
+      }),
+        s;
+    }
+    getAfterBody(t, e) {
+      return qo(e.callbacks.afterBody.apply(this, [t]));
+    }
+    getFooter(t, e) {
+      const { callbacks: i } = e,
+        s = i.beforeFooter.apply(this, [t]),
+        n = i.footer.apply(this, [t]),
+        o = i.afterFooter.apply(this, [t]);
+      let a = [];
+      return a = No(a, Wo(s)), a = No(a, Wo(n)), a = No(a, Wo(o)), a;
+    }
+    _createItems(t) {
+      const e = this._active, i = this.chart.data, s = [], n = [], o = [];
+      let a, r, l = [];
+      for (a = 0, r = e.length; a < r; ++a) l.push(jo(this.chart, e[a]));
+      return t.filter && (l = l.filter((e, s, n) => t.filter(e, s, n, i))),
+        t.itemSort && (l = l.sort((e, s) => t.itemSort(e, s, i))),
+        d(l, e => {
+          const i = Ko(t.callbacks, e);
+          s.push(i.labelColor.call(this, e)),
+            n.push(i.labelPointStyle.call(this, e)),
+            o.push(i.labelTextColor.call(this, e));
+        }),
+        this.labelColors = s,
+        this.labelPointStyles = n,
+        this.labelTextColors = o,
+        this.dataPoints = l,
+        l;
+    }
+    update(t, e) {
+      const i = this.options.setContext(this.getContext()), s = this._active;
+      let n, o = [];
+      if (s.length) {
+        const t = Bo[i.position].call(this, s, this._eventPosition);
+        o = this._createItems(i),
+          this.title = this.getTitle(o, i),
+          this.beforeBody = this.getBeforeBody(o, i),
+          this.body = this.getBody(o, i),
+          this.afterBody = this.getAfterBody(o, i),
+          this.footer = this.getFooter(o, i);
+        const e = this._size = Ho(this, i),
+          a = Object.assign({}, t, e),
+          r = Yo(this.chart, i, a),
+          l = Uo(i, a, r, this.chart);
+        this.xAlign = r.xAlign,
+          this.yAlign = r.yAlign,
+          n = { opacity: 1, x: l.x, y: l.y, width: e.width, height: e.height, caretX: t.x, caretY: t.y };
+      } else 0 !== this.opacity && (n = { opacity: 0 });
+      this._tooltipItems = o,
+        this.$context = void 0,
+        n && this._resolveAnimations().update(this, n),
+        t && i.external && i.external.call(this, { chart: this.chart, tooltip: this, replay: e });
+    }
+    drawCaret(t, e, i, s) {
+      const n = this.getCaretPosition(t, i, s);
+      e.lineTo(n.x1, n.y1), e.lineTo(n.x2, n.y2), e.lineTo(n.x3, n.y3);
+    }
+    getCaretPosition(t, e, i) {
+      const { xAlign: s, yAlign: n } = this,
+        { caretSize: o, cornerRadius: a } = i,
+        { topLeft: r, topRight: l, bottomLeft: h, bottomRight: c } = gi(a),
+        { x: d, y: u } = t,
+        { width: f, height: g } = e;
+      let p, m, b, x, _, y;
+      return "center" === n
+        ? (_ = u + g / 2,
+          "left" === s ? (p = d, m = p - o, x = _ + o, y = _ - o) : (p = d + f, m = p + o, x = _ - o, y = _ + o),
+          b = p)
+        : (m = "left" === s ? d + Math.max(r, h) + o : "right" === s ? d + f - Math.max(l, c) - o : this.caretX,
+          "top" === n ? (x = u, _ = x - o, p = m - o, b = m + o) : (x = u + g, _ = x + o, p = m + o, b = m - o),
+          y = x),
+        { x1: p, x2: m, x3: b, y1: x, y2: _, y3: y };
+    }
+    drawTitle(t, e, i) {
+      const s = this.title, n = s.length;
+      let o, a, r;
+      if (n) {
+        const l = yi(i.rtl, this.x, this.width);
+        for (
+          t.x = Xo(this, i.titleAlign, i),
+            e.textAlign = l.textAlign(i.titleAlign),
+            e.textBaseline = "middle",
+            o = mi(i.titleFont),
+            a = i.titleSpacing,
+            e.fillStyle = i.titleColor,
+            e.font = o.string,
+            r = 0;
+          r < n;
+          ++r
+        ) {
+          e.fillText(s[r], l.x(t.x), t.y + o.lineHeight / 2),
+            t.y += o.lineHeight + a,
+            r + 1 === n && (t.y += i.titleMarginBottom - a);
+        }
+      }
+    }
+    _drawColorBox(t, e, i, s, o) {
+      const a = this.labelColors[i],
+        r = this.labelPointStyles[i],
+        { boxHeight: l, boxWidth: h, boxPadding: c } = o,
+        d = mi(o.bodyFont),
+        u = Xo(this, "left", o),
+        f = s.x(u),
+        g = l < d.lineHeight ? (d.lineHeight - l) / 2 : 0,
+        p = e.y + g;
+      if (o.usePointStyle) {
+        const e = { radius: Math.min(h, l) / 2, pointStyle: r.pointStyle, rotation: r.rotation, borderWidth: 1 },
+          i = s.leftForLtr(f, h) + h / 2,
+          n = p + l / 2;
+        t.strokeStyle = o.multiKeyBackground,
+          t.fillStyle = o.multiKeyBackground,
+          Me(t, e, i, n),
+          t.strokeStyle = a.borderColor,
+          t.fillStyle = a.backgroundColor,
+          Me(t, e, i, n);
+      } else {
+        t.lineWidth = n(a.borderWidth) ? Math.max(...Object.values(a.borderWidth)) : a.borderWidth || 1,
+          t.strokeStyle = a.borderColor,
+          t.setLineDash(a.borderDash || []),
+          t.lineDashOffset = a.borderDashOffset || 0;
+        const e = s.leftForLtr(f, h - c), i = s.leftForLtr(s.xPlus(f, 1), h - c - 2), r = gi(a.borderRadius);
+        Object.values(r).some(t => 0 !== t)
+          ? (t.beginPath(),
+            t.fillStyle = o.multiKeyBackground,
+            Le(t, { x: e, y: p, w: h, h: l, radius: r }),
+            t.fill(),
+            t.stroke(),
+            t.fillStyle = a.backgroundColor,
+            t.beginPath(),
+            Le(t, { x: i, y: p + 1, w: h - 2, h: l - 2, radius: r }),
+            t.fill())
+          : (t.fillStyle = o.multiKeyBackground,
+            t.fillRect(e, p, h, l),
+            t.strokeRect(e, p, h, l),
+            t.fillStyle = a.backgroundColor,
+            t.fillRect(i, p + 1, h - 2, l - 2));
+      }
+      t.fillStyle = this.labelTextColors[i];
+    }
+    drawBody(t, e, i) {
+      const { body: s } = this,
+        { bodySpacing: n, bodyAlign: o, displayColors: a, boxHeight: r, boxWidth: l, boxPadding: h } = i,
+        c = mi(i.bodyFont);
+      let u = c.lineHeight, f = 0;
+      const g = yi(i.rtl, this.x, this.width),
+        p = function(i) {
+          e.fillText(i, g.x(t.x + f), t.y + u / 2), t.y += u + n;
+        },
+        m = g.textAlign(o);
+      let b, x, _, y, v, w, M;
+      for (
+        e.textAlign = o,
+          e.textBaseline = "middle",
+          e.font = c.string,
+          t.x = Xo(this, m, i),
+          e.fillStyle = i.bodyColor,
+          d(this.beforeBody, p),
+          f = a && "right" !== m ? "center" === o ? l / 2 + h : l + 2 + h : 0,
+          y = 0,
+          w = s.length;
+        y < w;
+        ++y
+      ) {
+        for (
+          b = s[y],
+            x = this.labelTextColors[y],
+            e.fillStyle = x,
+            d(b.before, p),
+            _ = b.lines,
+            a && _.length && (this._drawColorBox(e, t, y, g, i), u = Math.max(c.lineHeight, r)),
+            v = 0,
+            M = _.length;
+          v < M;
+          ++v
+        ) p(_[v]), u = c.lineHeight;
+        d(b.after, p);
+      }
+      f = 0, u = c.lineHeight, d(this.afterBody, p), t.y -= n;
+    }
+    drawFooter(t, e, i) {
+      const s = this.footer, n = s.length;
+      let o, a;
+      if (n) {
+        const r = yi(i.rtl, this.x, this.width);
+        for (
+          t.x = Xo(this, i.footerAlign, i),
+            t.y += i.footerMarginTop,
+            e.textAlign = r.textAlign(i.footerAlign),
+            e.textBaseline = "middle",
+            o = mi(i.footerFont),
+            e.fillStyle = i.footerColor,
+            e.font = o.string,
+            a = 0;
+          a < n;
+          ++a
+        ) e.fillText(s[a], r.x(t.x), t.y + o.lineHeight / 2), t.y += o.lineHeight + i.footerSpacing;
+      }
+    }
+    drawBackground(t, e, i, s) {
+      const { xAlign: n, yAlign: o } = this,
+        { x: a, y: r } = t,
+        { width: l, height: h } = i,
+        { topLeft: c, topRight: d, bottomLeft: u, bottomRight: f } = gi(s.cornerRadius);
+      e.fillStyle = s.backgroundColor,
+        e.strokeStyle = s.borderColor,
+        e.lineWidth = s.borderWidth,
+        e.beginPath(),
+        e.moveTo(a + c, r),
+        "top" === o && this.drawCaret(t, e, i, s),
+        e.lineTo(a + l - d, r),
+        e.quadraticCurveTo(a + l, r, a + l, r + d),
+        "center" === o && "right" === n && this.drawCaret(t, e, i, s),
+        e.lineTo(a + l, r + h - f),
+        e.quadraticCurveTo(a + l, r + h, a + l - f, r + h),
+        "bottom" === o && this.drawCaret(t, e, i, s),
+        e.lineTo(a + u, r + h),
+        e.quadraticCurveTo(a, r + h, a, r + h - u),
+        "center" === o && "left" === n && this.drawCaret(t, e, i, s),
+        e.lineTo(a, r + c),
+        e.quadraticCurveTo(a, r, a + c, r),
+        e.closePath(),
+        e.fill(),
+        s.borderWidth > 0 && e.stroke();
+    }
+    _updateAnimationTarget(t) {
+      const e = this.chart, i = this.$animations, s = i && i.x, n = i && i.y;
+      if (s || n) {
+        const i = Bo[t.position].call(this, this._active, this._eventPosition);
+        if (!i) return;
+        const o = this._size = Ho(this, t), a = Object.assign({}, i, this._size), r = Yo(e, t, a), l = Uo(t, a, r, e);
+        s._to === l.x && n._to === l.y
+          || (this.xAlign = r.xAlign,
+            this.yAlign = r.yAlign,
+            this.width = o.width,
+            this.height = o.height,
+            this.caretX = i.x,
+            this.caretY = i.y,
+            this._resolveAnimations().update(this, l));
+      }
+    }
+    _willRender() {
+      return !!this.opacity;
+    }
+    draw(t) {
+      const e = this.options.setContext(this.getContext());
+      let i = this.opacity;
+      if (!i) return;
+      this._updateAnimationTarget(e);
+      const s = { width: this.width, height: this.height }, n = { x: this.x, y: this.y };
+      i = Math.abs(i) < .001 ? 0 : i;
+      const o = pi(e.padding),
+        a = this.title.length || this.beforeBody.length || this.body.length || this.afterBody.length
+          || this.footer.length;
+      e.enabled && a
+        && (t.save(),
+          t.globalAlpha = i,
+          this.drawBackground(n, t, s, e),
+          vi(t, e.textDirection),
+          n.y += o.top,
+          this.drawTitle(n, t, e),
+          this.drawBody(n, t, e),
+          this.drawFooter(n, t, e),
+          wi(t, e.textDirection),
+          t.restore());
+    }
+    getActiveElements() {
+      return this._active || [];
+    }
+    setActiveElements(t, e) {
+      const i = this._active,
+        s = t.map(({ datasetIndex: t, index: e }) => {
+          const i = this.chart.getDatasetMeta(t);
+          if (!i) throw new Error("Cannot find a dataset at index " + t);
+          return { datasetIndex: t, element: i.data[e], index: e };
+        }),
+        n = !u(i, s),
+        o = this._positionChanged(s, e);
+      (n || o) && (this._active = s, this._eventPosition = e, this._ignoreReplayEvents = !0, this.update(!0));
+    }
+    handleEvent(t, e, i = !0) {
+      if (e && this._ignoreReplayEvents) return !1;
+      this._ignoreReplayEvents = !1;
+      const s = this.options,
+        n = this._active || [],
+        o = this._getActiveElements(t, n, e, i),
+        a = this._positionChanged(o, t),
+        r = e || !u(o, n) || a;
+      return r
+        && (this._active = o,
+          (s.enabled || s.external) && (this._eventPosition = { x: t.x, y: t.y }, this.update(!0, e))),
+        r;
+    }
+    _getActiveElements(t, e, i, s) {
+      const n = this.options;
+      if ("mouseout" === t.type) return [];
+      if (!s) return e;
+      const o = this.chart.getElementsAtEventForMode(t, n.mode, n, i);
+      return n.reverse && o.reverse(), o;
+    }
+    _positionChanged(t, e) {
+      const { caretX: i, caretY: s, options: n } = this, o = Bo[n.position].call(this, t, e);
+      return !1 !== o && (i !== o.x || s !== o.y);
+    }
+  }
+  Go.positioners = Bo;
+  var Zo = {
+      id: "tooltip",
+      _element: Go,
+      positioners: Bo,
+      afterInit(t, e, i) {
+        i && (t.tooltip = new Go({ chart: t, options: i }));
+      },
+      beforeUpdate(t, e, i) {
+        t.tooltip && t.tooltip.initialize(i);
+      },
+      reset(t, e, i) {
+        t.tooltip && t.tooltip.initialize(i);
+      },
+      afterDraw(t) {
+        const e = t.tooltip;
+        if (e && e._willRender()) {
+          const i = { tooltip: e };
+          if (!1 === t.notifyPlugins("beforeTooltipDraw", i)) return;
+          e.draw(t.ctx), t.notifyPlugins("afterTooltipDraw", i);
+        }
+      },
+      afterEvent(t, e) {
+        if (t.tooltip) {
+          const i = e.replay;
+          t.tooltip.handleEvent(e.event, i, e.inChartArea) && (e.changed = !0);
+        }
+      },
+      defaults: {
+        enabled: !0,
+        external: null,
+        position: "average",
+        backgroundColor: "rgba(0,0,0,0.8)",
+        titleColor: "#fff",
+        titleFont: { weight: "bold" },
+        titleSpacing: 2,
+        titleMarginBottom: 6,
+        titleAlign: "left",
+        bodyColor: "#fff",
+        bodySpacing: 2,
+        bodyFont: {},
+        bodyAlign: "left",
+        footerColor: "#fff",
+        footerSpacing: 2,
+        footerMarginTop: 6,
+        footerFont: { weight: "bold" },
+        footerAlign: "left",
+        padding: 6,
+        caretPadding: 2,
+        caretSize: 5,
+        cornerRadius: 6,
+        boxHeight: (t, e) => e.bodyFont.size,
+        boxWidth: (t, e) => e.bodyFont.size,
+        multiKeyBackground: "#fff",
+        displayColors: !0,
+        boxPadding: 0,
+        borderColor: "rgba(0,0,0,0)",
+        borderWidth: 0,
+        animation: { duration: 400, easing: "easeOutQuart" },
+        animations: {
+          numbers: { type: "number", properties: ["x", "y", "width", "height", "caretX", "caretY"] },
+          opacity: { easing: "linear", duration: 200 },
+        },
+        callbacks: {
+          beforeTitle: t,
+          title(t) {
+            if (t.length > 0) {
+              const e = t[0], i = e.chart.data.labels, s = i ? i.length : 0;
+              if (this && this.options && "dataset" === this.options.mode) return e.dataset.label || "";
+              if (e.label) return e.label;
+              if (s > 0 && e.dataIndex < s) return i[e.dataIndex];
+            }
+            return "";
+          },
+          afterTitle: t,
+          beforeBody: t,
+          beforeLabel: t,
+          label(t) {
+            if (this && this.options && "dataset" === this.options.mode) {
+              return t.label + ": " + t.formattedValue || t.formattedValue;
+            }
+            let e = t.dataset.label || "";
+            e && (e += ": ");
+            const s = t.formattedValue;
+            return i(s) || (e += s), e;
+          },
+          labelColor(t) {
+            const e = t.chart.getDatasetMeta(t.datasetIndex).controller.getStyle(t.dataIndex);
+            return {
+              borderColor: e.borderColor,
+              backgroundColor: e.backgroundColor,
+              borderWidth: e.borderWidth,
+              borderDash: e.borderDash,
+              borderDashOffset: e.borderDashOffset,
+              borderRadius: 0,
+            };
+          },
+          labelTextColor() {
+            return this.options.bodyColor;
+          },
+          labelPointStyle(t) {
+            const e = t.chart.getDatasetMeta(t.datasetIndex).controller.getStyle(t.dataIndex);
+            return { pointStyle: e.pointStyle, rotation: e.rotation };
+          },
+          afterLabel: t,
+          afterBody: t,
+          beforeFooter: t,
+          footer: t,
+          afterFooter: t,
+        },
+      },
+      defaultRoutes: { bodyFont: "font", footerFont: "font", titleFont: "font" },
+      descriptors: {
+        _scriptable: t => "filter" !== t && "itemSort" !== t && "external" !== t,
+        _indexable: !1,
+        callbacks: { _scriptable: !1, _indexable: !1 },
+        animation: { _fallback: !1 },
+        animations: { _fallback: "animation" },
+      },
+      additionalOptionScopes: ["interaction"],
+    },
+    Jo = Object.freeze({
+      __proto__: null,
+      Decimation: go,
+      Filler: To,
+      Legend: Ro,
+      SubTitle: Vo,
+      Title: zo,
+      Tooltip: Zo,
+    });
+  function Qo(t, e, i, s) {
+    const n = t.indexOf(e);
+    if (-1 === n) {
+      return ((
+        t,
+        e,
+        i,
+        s,
+      ) => ("string" == typeof e ? (i = t.push(e) - 1, s.unshift({ index: i, label: e })) : isNaN(e) && (i = null), i))(
+        t,
+        e,
+        i,
+        s,
+      );
+    }
+    return n !== t.lastIndexOf(e) ? i : n;
+  }
+  class ta extends $s {
+    constructor(t) {
+      super(t), this._startValue = void 0, this._valueRange = 0, this._addedLabels = [];
+    }
+    init(t) {
+      const e = this._addedLabels;
+      if (e.length) {
+        const t = this.getLabels();
+        for (const { index: i, label: s } of e) t[i] === s && t.splice(i, 1);
+        this._addedLabels = [];
+      }
+      super.init(t);
+    }
+    parse(t, e) {
+      if (i(t)) return null;
+      const s = this.getLabels();
+      return ((t, e) => null === t ? null : Z(Math.round(t), 0, e))(
+        e = isFinite(e) && s[e] === t ? e : Qo(s, t, r(e, t), this._addedLabels),
+        s.length - 1,
+      );
+    }
+    determineDataLimits() {
+      const { minDefined: t, maxDefined: e } = this.getUserBounds();
+      let { min: i, max: s } = this.getMinMax(!0);
+      "ticks" === this.options.bounds && (t || (i = 0), e || (s = this.getLabels().length - 1)),
+        this.min = i,
+        this.max = s;
+    }
+    buildTicks() {
+      const t = this.min, e = this.max, i = this.options.offset, s = [];
+      let n = this.getLabels();
+      n = 0 === t && e === n.length - 1 ? n : n.slice(t, e + 1),
+        this._valueRange = Math.max(n.length - (i ? 0 : 1), 1),
+        this._startValue = this.min - (i ? .5 : 0);
+      for (let i = t; i <= e; i++) s.push({ value: i });
+      return s;
+    }
+    getLabelForValue(t) {
+      const e = this.getLabels();
+      return t >= 0 && t < e.length ? e[t] : t;
+    }
+    configure() {
+      super.configure(), this.isHorizontal() || (this._reversePixels = !this._reversePixels);
+    }
+    getPixelForValue(t) {
+      return "number" != typeof t && (t = this.parse(t)),
+        null === t ? NaN : this.getPixelForDecimal((t - this._startValue) / this._valueRange);
+    }
+    getPixelForTick(t) {
+      const e = this.ticks;
+      return t < 0 || t > e.length - 1 ? null : this.getPixelForValue(e[t].value);
+    }
+    getValueForPixel(t) {
+      return Math.round(this._startValue + this.getDecimalForPixel(t) * this._valueRange);
+    }
+    getBasePixel() {
+      return this.bottom;
+    }
+  }
+  function ea(t, e, { horizontal: i, minRotation: s }) {
+    const n = H(s), o = (i ? Math.sin(n) : Math.cos(n)) || .001, a = .75 * e * ("" + t).length;
+    return Math.min(e / o, a);
+  }
+  ta.id = "category", ta.defaults = { ticks: { callback: ta.prototype.getLabelForValue } };
+  class ia extends $s {
+    constructor(t) {
+      super(t),
+        this.start = void 0,
+        this.end = void 0,
+        this._startValue = void 0,
+        this._endValue = void 0,
+        this._valueRange = 0;
+    }
+    parse(t, e) {
+      return i(t) || ("number" == typeof t || t instanceof Number) && !isFinite(+t) ? null : +t;
+    }
+    handleTickRangeOptions() {
+      const { beginAtZero: t } = this.options, { minDefined: e, maxDefined: i } = this.getUserBounds();
+      let { min: s, max: n } = this;
+      const o = t => s = e ? s : t, a = t => n = i ? n : t;
+      if (t) {
+        const t = z(s), e = z(n);
+        t < 0 && e < 0 ? a(0) : t > 0 && e > 0 && o(0);
+      }
+      if (s === n) {
+        let e = 1;
+        (n >= Number.MAX_SAFE_INTEGER || s <= Number.MIN_SAFE_INTEGER) && (e = Math.abs(.05 * n)),
+          a(n + e),
+          t || o(s - e);
+      }
+      this.min = s, this.max = n;
+    }
+    getTickLimit() {
+      const t = this.options.ticks;
+      let e, { maxTicksLimit: i, stepSize: s } = t;
+      return s
+        ? (e = Math.ceil(this.max / s) - Math.floor(this.min / s) + 1,
+          e > 1e3
+          && (console.warn(
+            `scales.${this.id}.ticks.stepSize: ${s} would result generating up to ${e} ticks. Limiting to 1000.`,
+          ),
+            e = 1e3))
+        : (e = this.computeTickLimit(), i = i || 11),
+        i && (e = Math.min(i, e)),
+        e;
+    }
+    computeTickLimit() {
+      return Number.POSITIVE_INFINITY;
+    }
+    buildTicks() {
+      const t = this.options, e = t.ticks;
+      let s = this.getTickLimit();
+      s = Math.max(2, s);
+      const n = function(t, e) {
+        const s = [],
+          { bounds: n, step: o, min: a, max: r, precision: l, count: h, maxTicks: c, maxDigits: d, includeBounds: u } =
+            t,
+          f = o || 1,
+          g = c - 1,
+          { min: p, max: m } = e,
+          b = !i(a),
+          x = !i(r),
+          _ = !i(h),
+          y = (m - p) / (d + 1);
+        let v, w, M, k, S = F((m - p) / g / f) * f;
+        if (S < 1e-14 && !b && !x) return [{ value: p }, { value: m }];
+        k = Math.ceil(m / S) - Math.floor(p / S),
+          k > g && (S = F(k * S / g / f) * f),
+          i(l) || (v = Math.pow(10, l), S = Math.ceil(S * v) / v),
+          "ticks" === n ? (w = Math.floor(p / S) * S, M = Math.ceil(m / S) * S) : (w = p, M = m),
+          b && x && o && W((r - a) / o, S / 1e3)
+            ? (k = Math.round(Math.min((r - a) / S, c)), S = (r - a) / k, w = a, M = r)
+            : _
+            ? (w = b ? a : w, M = x ? r : M, k = h - 1, S = (M - w) / k)
+            : (k = (M - w) / S, k = N(k, Math.round(k), S / 1e3) ? Math.round(k) : Math.ceil(k));
+        const P = Math.max(Y(S), Y(w));
+        v = Math.pow(10, i(l) ? P : l), w = Math.round(w * v) / v, M = Math.round(M * v) / v;
+        let D = 0;
+        for (
+          b && (u && w !== a
+            ? (s.push({ value: a }), w < a && D++, N(Math.round((w + D * S) * v) / v, a, ea(a, y, t)) && D++)
+            : w < a && D++);
+          D < k;
+          ++D
+        ) s.push({ value: Math.round((w + D * S) * v) / v });
+        return x && u && M !== r
+          ? s.length && N(s[s.length - 1].value, r, ea(r, y, t)) ? s[s.length - 1].value = r : s.push({ value: r })
+          : x && M !== r || s.push({ value: M }),
+          s;
+      }({
+        maxTicks: s,
+        bounds: t.bounds,
+        min: t.min,
+        max: t.max,
+        precision: e.precision,
+        step: e.stepSize,
+        count: e.count,
+        maxDigits: this._maxDigits(),
+        horizontal: this.isHorizontal(),
+        minRotation: e.minRotation || 0,
+        includeBounds: !1 !== e.includeBounds,
+      }, this._range || this);
+      return "ticks" === t.bounds && j(n, this, "value"),
+        t.reverse
+          ? (n.reverse(), this.start = this.max, this.end = this.min)
+          : (this.start = this.min, this.end = this.max),
+        n;
+    }
+    configure() {
+      const t = this.ticks;
+      let e = this.min, i = this.max;
+      if (super.configure(), this.options.offset && t.length) {
+        const s = (i - e) / Math.max(t.length - 1, 1) / 2;
+        e -= s, i += s;
+      }
+      this._startValue = e, this._endValue = i, this._valueRange = i - e;
+    }
+    getLabelForValue(t) {
+      return li(t, this.chart.options.locale, this.options.ticks.format);
+    }
+  }
+  class sa extends ia {
+    determineDataLimits() {
+      const { min: t, max: e } = this.getMinMax(!0);
+      this.min = o(t) ? t : 0, this.max = o(e) ? e : 1, this.handleTickRangeOptions();
+    }
+    computeTickLimit() {
+      const t = this.isHorizontal(),
+        e = t ? this.width : this.height,
+        i = H(this.options.ticks.minRotation),
+        s = (t ? Math.sin(i) : Math.cos(i)) || .001,
+        n = this._resolveTickFontOptions(0);
+      return Math.ceil(e / Math.min(40, n.lineHeight / s));
+    }
+    getPixelForValue(t) {
+      return null === t ? NaN : this.getPixelForDecimal((t - this._startValue) / this._valueRange);
+    }
+    getValueForPixel(t) {
+      return this._startValue + this.getDecimalForPixel(t) * this._valueRange;
+    }
+  }
+  function na(t) {
+    return 1 === t / Math.pow(10, Math.floor(I(t)));
+  }
+  sa.id = "linear", sa.defaults = { ticks: { callback: Is.formatters.numeric } };
+  class oa extends $s {
+    constructor(t) {
+      super(t), this.start = void 0, this.end = void 0, this._startValue = void 0, this._valueRange = 0;
+    }
+    parse(t, e) {
+      const i = ia.prototype.parse.apply(this, [t, e]);
+      if (0 !== i) return o(i) && i > 0 ? i : null;
+      this._zero = !0;
+    }
+    determineDataLimits() {
+      const { min: t, max: e } = this.getMinMax(!0);
+      this.min = o(t) ? Math.max(0, t) : null,
+        this.max = o(e) ? Math.max(0, e) : null,
+        this.options.beginAtZero && (this._zero = !0),
+        this.handleTickRangeOptions();
+    }
+    handleTickRangeOptions() {
+      const { minDefined: t, maxDefined: e } = this.getUserBounds();
+      let i = this.min, s = this.max;
+      const n = e => i = t ? i : e, o = t => s = e ? s : t, a = (t, e) => Math.pow(10, Math.floor(I(t)) + e);
+      i === s && (i <= 0 ? (n(1), o(10)) : (n(a(i, -1)), o(a(s, 1)))),
+        i <= 0 && n(a(s, -1)),
+        s <= 0 && o(a(i, 1)),
+        this._zero && this.min !== this._suggestedMin && i === a(this.min, 0) && n(a(i, -1)),
+        this.min = i,
+        this.max = s;
+    }
+    buildTicks() {
+      const t = this.options,
+        e = function(t, e) {
+          const i = Math.floor(I(e.max)), s = Math.ceil(e.max / Math.pow(10, i)), n = [];
+          let o = a(t.min, Math.pow(10, Math.floor(I(e.min)))),
+            r = Math.floor(I(o)),
+            l = Math.floor(o / Math.pow(10, r)),
+            h = r < 0 ? Math.pow(10, Math.abs(r)) : 1;
+          do {
+            n.push({ value: o, major: na(o) }),
+              ++l,
+              10 === l && (l = 1, ++r, h = r >= 0 ? 1 : h),
+              o = Math.round(l * Math.pow(10, r) * h) / h;
+          } while (r < i || r === i && l < s);
+          const c = a(t.max, o);
+          return n.push({ value: c, major: na(o) }), n;
+        }({ min: this._userMin, max: this._userMax }, this);
+      return "ticks" === t.bounds && j(e, this, "value"),
+        t.reverse
+          ? (e.reverse(), this.start = this.max, this.end = this.min)
+          : (this.start = this.min, this.end = this.max),
+        e;
+    }
+    getLabelForValue(t) {
+      return void 0 === t ? "0" : li(t, this.chart.options.locale, this.options.ticks.format);
+    }
+    configure() {
+      const t = this.min;
+      super.configure(), this._startValue = I(t), this._valueRange = I(this.max) - I(t);
+    }
+    getPixelForValue(t) {
+      return void 0 !== t && 0 !== t || (t = this.min),
+        null === t || isNaN(t)
+          ? NaN
+          : this.getPixelForDecimal(t === this.min ? 0 : (I(t) - this._startValue) / this._valueRange);
+    }
+    getValueForPixel(t) {
+      const e = this.getDecimalForPixel(t);
+      return Math.pow(10, this._startValue + e * this._valueRange);
+    }
+  }
+  function aa(t) {
+    const e = t.ticks;
+    if (e.display && t.display) {
+      const t = pi(e.backdropPadding);
+      return r(e.font && e.font.size, ne.font.size) + t.height;
+    }
+    return 0;
+  }
+  function ra(t, e, i, s, n) {
+    return t === s || t === n
+      ? { start: e - i / 2, end: e + i / 2 }
+      : t < s || t > n
+      ? { start: e - i, end: e }
+      : { start: e, end: e + i };
+  }
+  function la(t) {
+    const e = {
+        l: t.left + t._padding.left,
+        r: t.right - t._padding.right,
+        t: t.top + t._padding.top,
+        b: t.bottom - t._padding.bottom,
+      },
+      i = Object.assign({}, e),
+      n = [],
+      o = [],
+      a = t._pointLabels.length,
+      r = t.options.pointLabels,
+      l = r.centerPointLabels ? D / a : 0;
+    for (let u = 0; u < a; u++) {
+      const a = r.setContext(t.getPointLabelContext(u));
+      o[u] = a.padding;
+      const f = t.getPointPosition(u, t.drawingArea + o[u], l),
+        g = mi(a.font),
+        p =
+          (h = t.ctx,
+            c = g,
+            d = s(d = t._pointLabels[u]) ? d : [d],
+            { w: ye(h, c.string, d), h: d.length * c.lineHeight });
+      n[u] = p;
+      const m = K(t.getIndexAngle(u) + l), b = Math.round($(m));
+      ha(i, e, m, ra(b, f.x, p.w, 0, 180), ra(b, f.y, p.h, 90, 270));
+    }
+    var h, c, d;
+    t.setCenterPoint(e.l - i.l, i.r - e.r, e.t - i.t, i.b - e.b),
+      t._pointLabelItems = function(t, e, i) {
+        const s = [],
+          n = t._pointLabels.length,
+          o = t.options,
+          a = aa(o) / 2,
+          r = t.drawingArea,
+          l = o.pointLabels.centerPointLabels ? D / n : 0;
+        for (let o = 0; o < n; o++) {
+          const n = t.getPointPosition(o, r + a + i[o], l),
+            h = Math.round($(K(n.angle + L))),
+            c = e[o],
+            d = ua(n.y, c.h, h),
+            u = ca(h),
+            f = da(n.x, c.w, u);
+          s.push({ x: n.x, y: d, textAlign: u, left: f, top: d, right: f + c.w, bottom: d + c.h });
+        }
+        return s;
+      }(t, n, o);
+  }
+  function ha(t, e, i, s, n) {
+    const o = Math.abs(Math.sin(i)), a = Math.abs(Math.cos(i));
+    let r = 0, l = 0;
+    s.start < e.l
+      ? (r = (e.l - s.start) / o, t.l = Math.min(t.l, e.l - r))
+      : s.end > e.r && (r = (s.end - e.r) / o, t.r = Math.max(t.r, e.r + r)),
+      n.start < e.t
+        ? (l = (e.t - n.start) / a, t.t = Math.min(t.t, e.t - l))
+        : n.end > e.b && (l = (n.end - e.b) / a, t.b = Math.max(t.b, e.b + l));
+  }
+  function ca(t) {
+    return 0 === t || 180 === t ? "center" : t < 180 ? "left" : "right";
+  }
+  function da(t, e, i) {
+    return "right" === i ? t -= e : "center" === i && (t -= e / 2), t;
+  }
+  function ua(t, e, i) {
+    return 90 === i || 270 === i ? t -= e / 2 : (i > 270 || i < 90) && (t -= e), t;
+  }
+  function fa(t, e, i, s) {
+    const { ctx: n } = t;
+    if (i) n.arc(t.xCenter, t.yCenter, e, 0, O);
+    else {
+      let i = t.getPointPosition(0, e);
+      n.moveTo(i.x, i.y);
+      for (let o = 1; o < s; o++) i = t.getPointPosition(o, e), n.lineTo(i.x, i.y);
+    }
+  }
+  oa.id = "logarithmic", oa.defaults = { ticks: { callback: Is.formatters.logarithmic, major: { enabled: !0 } } };
+  class ga extends ia {
+    constructor(t) {
+      super(t),
+        this.xCenter = void 0,
+        this.yCenter = void 0,
+        this.drawingArea = void 0,
+        this._pointLabels = [],
+        this._pointLabelItems = [];
+    }
+    setDimensions() {
+      const t = this._padding = pi(aa(this.options) / 2),
+        e = this.width = this.maxWidth - t.width,
+        i = this.height = this.maxHeight - t.height;
+      this.xCenter = Math.floor(this.left + e / 2 + t.left),
+        this.yCenter = Math.floor(this.top + i / 2 + t.top),
+        this.drawingArea = Math.floor(Math.min(e, i) / 2);
+    }
+    determineDataLimits() {
+      const { min: t, max: e } = this.getMinMax(!1);
+      this.min = o(t) && !isNaN(t) ? t : 0, this.max = o(e) && !isNaN(e) ? e : 0, this.handleTickRangeOptions();
+    }
+    computeTickLimit() {
+      return Math.ceil(this.drawingArea / aa(this.options));
+    }
+    generateTickLabels(t) {
+      ia.prototype.generateTickLabels.call(this, t),
+        this._pointLabels = this.getLabels().map((t, e) => {
+          const i = c(this.options.pointLabels.callback, [t, e], this);
+          return i || 0 === i ? i : "";
+        }).filter((t, e) => this.chart.getDataVisibility(e));
+    }
+    fit() {
+      const t = this.options;
+      t.display && t.pointLabels.display ? la(this) : this.setCenterPoint(0, 0, 0, 0);
+    }
+    setCenterPoint(t, e, i, s) {
+      this.xCenter += Math.floor((t - e) / 2),
+        this.yCenter += Math.floor((i - s) / 2),
+        this.drawingArea -= Math.min(this.drawingArea / 2, Math.max(t, e, i, s));
+    }
+    getIndexAngle(t) {
+      return K(t * (O / (this._pointLabels.length || 1)) + H(this.options.startAngle || 0));
+    }
+    getDistanceFromCenterForValue(t) {
+      if (i(t)) return NaN;
+      const e = this.drawingArea / (this.max - this.min);
+      return this.options.reverse ? (this.max - t) * e : (t - this.min) * e;
+    }
+    getValueForDistanceFromCenter(t) {
+      if (i(t)) return NaN;
+      const e = t / (this.drawingArea / (this.max - this.min));
+      return this.options.reverse ? this.max - e : this.min + e;
+    }
+    getPointLabelContext(t) {
+      const e = this._pointLabels || [];
+      if (t >= 0 && t < e.length) {
+        const i = e[t];
+        return function(t, e, i) {
+          return _i(t, { label: i, index: e, type: "pointLabel" });
+        }(this.getContext(), t, i);
+      }
+    }
+    getPointPosition(t, e, i = 0) {
+      const s = this.getIndexAngle(t) - L + i;
+      return { x: Math.cos(s) * e + this.xCenter, y: Math.sin(s) * e + this.yCenter, angle: s };
+    }
+    getPointPositionForValue(t, e) {
+      return this.getPointPosition(t, this.getDistanceFromCenterForValue(e));
+    }
+    getBasePosition(t) {
+      return this.getPointPositionForValue(t || 0, this.getBaseValue());
+    }
+    getPointLabelPosition(t) {
+      const { left: e, top: i, right: s, bottom: n } = this._pointLabelItems[t];
+      return { left: e, top: i, right: s, bottom: n };
+    }
+    drawBackground() {
+      const { backgroundColor: t, grid: { circular: e } } = this.options;
+      if (t) {
+        const i = this.ctx;
+        i.save(),
+          i.beginPath(),
+          fa(this, this.getDistanceFromCenterForValue(this._endValue), e, this._pointLabels.length),
+          i.closePath(),
+          i.fillStyle = t,
+          i.fill(),
+          i.restore();
+      }
+    }
+    drawGrid() {
+      const t = this.ctx, e = this.options, { angleLines: s, grid: n } = e, o = this._pointLabels.length;
+      let a, r, l;
+      if (
+        e.pointLabels.display && function(t, e) {
+          const { ctx: s, options: { pointLabels: n } } = t;
+          for (let o = e - 1; o >= 0; o--) {
+            const e = n.setContext(t.getPointLabelContext(o)),
+              a = mi(e.font),
+              { x: r, y: l, textAlign: h, left: c, top: d, right: u, bottom: f } = t._pointLabelItems[o],
+              { backdropColor: g } = e;
+            if (!i(g)) {
+              const t = gi(e.borderRadius), i = pi(e.backdropPadding);
+              s.fillStyle = g;
+              const n = c - i.left, o = d - i.top, a = u - c + i.width, r = f - d + i.height;
+              Object.values(t).some(t => 0 !== t)
+                ? (s.beginPath(), Le(s, { x: n, y: o, w: a, h: r, radius: t }), s.fill())
+                : s.fillRect(n, o, a, r);
+            }
+            Ae(s, t._pointLabels[o], r, l + a.lineHeight / 2, a, {
+              color: e.color,
+              textAlign: h,
+              textBaseline: "middle",
+            });
+          }
+        }(this, o),
+          n.display && this.ticks.forEach((t, e) => {
+            if (0 !== e) {
+              r = this.getDistanceFromCenterForValue(t.value);
+              !function(t, e, i, s) {
+                const n = t.ctx, o = e.circular, { color: a, lineWidth: r } = e;
+                !o && !s || !a || !r || i < 0
+                  || (n.save(),
+                    n.strokeStyle = a,
+                    n.lineWidth = r,
+                    n.setLineDash(e.borderDash),
+                    n.lineDashOffset = e.borderDashOffset,
+                    n.beginPath(),
+                    fa(t, i, o, s),
+                    n.closePath(),
+                    n.stroke(),
+                    n.restore());
+              }(this, n.setContext(this.getContext(e - 1)), r, o);
+            }
+          }),
+          s.display
+      ) {
+        for (t.save(), a = o - 1; a >= 0; a--) {
+          const i = s.setContext(this.getPointLabelContext(a)), { color: n, lineWidth: o } = i;
+          o && n
+            && (t.lineWidth = o,
+              t.strokeStyle = n,
+              t.setLineDash(i.borderDash),
+              t.lineDashOffset = i.borderDashOffset,
+              r = this.getDistanceFromCenterForValue(e.ticks.reverse ? this.min : this.max),
+              l = this.getPointPosition(a, r),
+              t.beginPath(),
+              t.moveTo(this.xCenter, this.yCenter),
+              t.lineTo(l.x, l.y),
+              t.stroke());
+        }
+        t.restore();
+      }
+    }
+    drawBorder() {}
+    drawLabels() {
+      const t = this.ctx, e = this.options, i = e.ticks;
+      if (!i.display) return;
+      const s = this.getIndexAngle(0);
+      let n, o;
+      t.save(),
+        t.translate(this.xCenter, this.yCenter),
+        t.rotate(s),
+        t.textAlign = "center",
+        t.textBaseline = "middle",
+        this.ticks.forEach((s, a) => {
+          if (0 === a && !e.reverse) return;
+          const r = i.setContext(this.getContext(a)), l = mi(r.font);
+          if (n = this.getDistanceFromCenterForValue(this.ticks[a].value), r.showLabelBackdrop) {
+            t.font = l.string, o = t.measureText(s.label).width, t.fillStyle = r.backdropColor;
+            const e = pi(r.backdropPadding);
+            t.fillRect(-o / 2 - e.left, -n - l.size / 2 - e.top, o + e.width, l.size + e.height);
+          }
+          Ae(t, s.label, 0, -n, l, { color: r.color });
+        }),
+        t.restore();
+    }
+    drawTitle() {}
+  }
+  ga.id = "radialLinear",
+    ga.defaults = {
+      display: !0,
+      animate: !0,
+      position: "chartArea",
+      angleLines: { display: !0, lineWidth: 1, borderDash: [], borderDashOffset: 0 },
+      grid: { circular: !1 },
+      startAngle: 0,
+      ticks: { showLabelBackdrop: !0, callback: Is.formatters.numeric },
+      pointLabels: {
+        backdropColor: void 0,
+        backdropPadding: 2,
+        display: !0,
+        font: { size: 10 },
+        callback: t => t,
+        padding: 5,
+        centerPointLabels: !1,
+      },
+    },
+    ga.defaultRoutes = { "angleLines.color": "borderColor", "pointLabels.color": "color", "ticks.color": "color" },
+    ga.descriptors = { angleLines: { _fallback: "grid" } };
+  const pa = {
+      millisecond: { common: !0, size: 1, steps: 1e3 },
+      second: { common: !0, size: 1e3, steps: 60 },
+      minute: { common: !0, size: 6e4, steps: 60 },
+      hour: { common: !0, size: 36e5, steps: 24 },
+      day: { common: !0, size: 864e5, steps: 30 },
+      week: { common: !1, size: 6048e5, steps: 4 },
+      month: { common: !0, size: 2628e6, steps: 12 },
+      quarter: { common: !1, size: 7884e6, steps: 4 },
+      year: { common: !0, size: 3154e7 },
+    },
+    ma = Object.keys(pa);
+  function ba(t, e) {
+    return t - e;
+  }
+  function xa(t, e) {
+    if (i(e)) return null;
+    const s = t._adapter, { parser: n, round: a, isoWeekday: r } = t._parseOpts;
+    let l = e;
+    return "function" == typeof n && (l = n(l)),
+      o(l) || (l = "string" == typeof n ? s.parse(l, n) : s.parse(l)),
+      null === l
+        ? null
+        : (a && (l = "week" !== a || !B(r) && !0 !== r ? s.startOf(l, a) : s.startOf(l, "isoWeek", r)), +l);
+  }
+  function _a(t, e, i, s) {
+    const n = ma.length;
+    for (let o = ma.indexOf(t); o < n - 1; ++o) {
+      const t = pa[ma[o]], n = t.steps ? t.steps : Number.MAX_SAFE_INTEGER;
+      if (t.common && Math.ceil((i - e) / (n * t.size)) <= s) return ma[o];
+    }
+    return ma[n - 1];
+  }
+  function ya(t, e, i) {
+    if (i) {
+      if (i.length) {
+        const { lo: s, hi: n } = tt(i, e);
+        t[i[s] >= e ? i[s] : i[n]] = !0;
+      }
+    } else t[e] = !0;
+  }
+  function va(t, e, i) {
+    const s = [], n = {}, o = e.length;
+    let a, r;
+    for (a = 0; a < o; ++a) r = e[a], n[r] = a, s.push({ value: r, major: !1 });
+    return 0 !== o && i
+      ? function(t, e, i, s) {
+        const n = t._adapter, o = +n.startOf(e[0].value, s), a = e[e.length - 1].value;
+        let r, l;
+        for (r = o; r <= a; r = +n.add(r, 1, s)) l = i[r], l >= 0 && (e[l].major = !0);
+        return e;
+      }(t, s, n, i)
+      : s;
+  }
+  class wa extends $s {
+    constructor(t) {
+      super(t),
+        this._cache = { data: [], labels: [], all: [] },
+        this._unit = "day",
+        this._majorUnit = void 0,
+        this._offsets = {},
+        this._normalized = !1,
+        this._parseOpts = void 0;
+    }
+    init(t, e) {
+      const i = t.time || (t.time = {}), s = this._adapter = new wn._date(t.adapters.date);
+      s.init(e),
+        b(i.displayFormats, s.formats()),
+        this._parseOpts = { parser: i.parser, round: i.round, isoWeekday: i.isoWeekday },
+        super.init(t),
+        this._normalized = e.normalized;
+    }
+    parse(t, e) {
+      return void 0 === t ? null : xa(this, t);
+    }
+    beforeLayout() {
+      super.beforeLayout(), this._cache = { data: [], labels: [], all: [] };
+    }
+    determineDataLimits() {
+      const t = this.options, e = this._adapter, i = t.time.unit || "day";
+      let { min: s, max: n, minDefined: a, maxDefined: r } = this.getUserBounds();
+      function l(t) {
+        a || isNaN(t.min) || (s = Math.min(s, t.min)), r || isNaN(t.max) || (n = Math.max(n, t.max));
+      }
+      a && r
+      || (l(this._getLabelBounds()), "ticks" === t.bounds && "labels" === t.ticks.source || l(this.getMinMax(!1))),
+        s = o(s) && !isNaN(s) ? s : +e.startOf(Date.now(), i),
+        n = o(n) && !isNaN(n) ? n : +e.endOf(Date.now(), i) + 1,
+        this.min = Math.min(s, n - 1),
+        this.max = Math.max(s + 1, n);
+    }
+    _getLabelBounds() {
+      const t = this.getLabelTimestamps();
+      let e = Number.POSITIVE_INFINITY, i = Number.NEGATIVE_INFINITY;
+      return t.length && (e = t[0], i = t[t.length - 1]), { min: e, max: i };
+    }
+    buildTicks() {
+      const t = this.options,
+        e = t.time,
+        i = t.ticks,
+        s = "labels" === i.source ? this.getLabelTimestamps() : this._generate();
+      "ticks" === t.bounds && s.length
+        && (this.min = this._userMin || s[0], this.max = this._userMax || s[s.length - 1]);
+      const n = this.min, o = st(s, n, this.max);
+      return this._unit = e.unit
+        || (i.autoSkip ? _a(e.minUnit, this.min, this.max, this._getLabelCapacity(n)) : function(t, e, i, s, n) {
+          for (let o = ma.length - 1; o >= ma.indexOf(i); o--) {
+            const i = ma[o];
+            if (pa[i].common && t._adapter.diff(n, s, i) >= e - 1) return i;
+          }
+          return ma[i ? ma.indexOf(i) : 0];
+        }(this, o.length, e.minUnit, this.min, this.max)),
+        this._majorUnit = i.major.enabled && "year" !== this._unit
+          ? function(t) {
+            for (let e = ma.indexOf(t) + 1, i = ma.length; e < i; ++e) if (pa[ma[e]].common) return ma[e];
+          }(this._unit)
+          : void 0,
+        this.initOffsets(s),
+        t.reverse && o.reverse(),
+        va(this, o, this._majorUnit);
+    }
+    afterAutoSkip() {
+      this.options.offsetAfterAutoskip && this.initOffsets(this.ticks.map(t => +t.value));
+    }
+    initOffsets(t) {
+      let e, i, s = 0, n = 0;
+      this.options.offset && t.length
+        && (e = this.getDecimalForValue(t[0]),
+          s = 1 === t.length ? 1 - e : (this.getDecimalForValue(t[1]) - e) / 2,
+          i = this.getDecimalForValue(t[t.length - 1]),
+          n = 1 === t.length ? i : (i - this.getDecimalForValue(t[t.length - 2])) / 2);
+      const o = t.length < 3 ? .5 : .25;
+      s = Z(s, 0, o), n = Z(n, 0, o), this._offsets = { start: s, end: n, factor: 1 / (s + 1 + n) };
+    }
+    _generate() {
+      const t = this._adapter,
+        e = this.min,
+        i = this.max,
+        s = this.options,
+        n = s.time,
+        o = n.unit || _a(n.minUnit, e, i, this._getLabelCapacity(e)),
+        a = r(n.stepSize, 1),
+        l = "week" === o && n.isoWeekday,
+        h = B(l) || !0 === l,
+        c = {};
+      let d, u, f = e;
+      if (h && (f = +t.startOf(f, "isoWeek", l)), f = +t.startOf(f, h ? "day" : o), t.diff(i, e, o) > 1e5 * a) {
+        throw new Error(e + " and " + i + " are too far apart with stepSize of " + a + " " + o);
+      }
+      const g = "data" === s.ticks.source && this.getDataTimestamps();
+      for (d = f, u = 0; d < i; d = +t.add(d, a, o), u++) ya(c, d, g);
+      return d !== i && "ticks" !== s.bounds && 1 !== u || ya(c, d, g),
+        Object.keys(c).sort((t, e) => t - e).map(t => +t);
+    }
+    getLabelForValue(t) {
+      const e = this._adapter, i = this.options.time;
+      return i.tooltipFormat ? e.format(t, i.tooltipFormat) : e.format(t, i.displayFormats.datetime);
+    }
+    _tickFormatFunction(t, e, i, s) {
+      const n = this.options,
+        o = n.time.displayFormats,
+        a = this._unit,
+        r = this._majorUnit,
+        l = a && o[a],
+        h = r && o[r],
+        d = i[e],
+        u = r && h && d && d.major,
+        f = this._adapter.format(t, s || (u ? h : l)),
+        g = n.ticks.callback;
+      return g ? c(g, [f, e, i], this) : f;
+    }
+    generateTickLabels(t) {
+      let e, i, s;
+      for (e = 0, i = t.length; e < i; ++e) s = t[e], s.label = this._tickFormatFunction(s.value, e, t);
+    }
+    getDecimalForValue(t) {
+      return null === t ? NaN : (t - this.min) / (this.max - this.min);
+    }
+    getPixelForValue(t) {
+      const e = this._offsets, i = this.getDecimalForValue(t);
+      return this.getPixelForDecimal((e.start + i) * e.factor);
+    }
+    getValueForPixel(t) {
+      const e = this._offsets, i = this.getDecimalForPixel(t) / e.factor - e.end;
+      return this.min + i * (this.max - this.min);
+    }
+    _getLabelSize(t) {
+      const e = this.options.ticks,
+        i = this.ctx.measureText(t).width,
+        s = H(this.isHorizontal() ? e.maxRotation : e.minRotation),
+        n = Math.cos(s),
+        o = Math.sin(s),
+        a = this._resolveTickFontOptions(0).size;
+      return { w: i * n + a * o, h: i * o + a * n };
+    }
+    _getLabelCapacity(t) {
+      const e = this.options.time,
+        i = e.displayFormats,
+        s = i[e.unit] || i.millisecond,
+        n = this._tickFormatFunction(t, 0, va(this, [t], this._majorUnit), s),
+        o = this._getLabelSize(n),
+        a = Math.floor(this.isHorizontal() ? this.width / o.w : this.height / o.h) - 1;
+      return a > 0 ? a : 1;
+    }
+    getDataTimestamps() {
+      let t, e, i = this._cache.data || [];
+      if (i.length) return i;
+      const s = this.getMatchingVisibleMetas();
+      if (this._normalized && s.length) return this._cache.data = s[0].controller.getAllParsedValues(this);
+      for (t = 0, e = s.length; t < e; ++t) i = i.concat(s[t].controller.getAllParsedValues(this));
+      return this._cache.data = this.normalize(i);
+    }
+    getLabelTimestamps() {
+      const t = this._cache.labels || [];
+      let e, i;
+      if (t.length) return t;
+      const s = this.getLabels();
+      for (e = 0, i = s.length; e < i; ++e) t.push(xa(this, s[e]));
+      return this._cache.labels = this._normalized ? t : this.normalize(t);
+    }
+    normalize(t) {
+      return rt(t.sort(ba));
+    }
+  }
+  function Ma(t, e, i) {
+    let s, n, o, a, r = 0, l = t.length - 1;
+    i
+      ? (e >= t[r].pos && e <= t[l].pos && ({ lo: r, hi: l } = et(t, "pos", e)),
+        ({ pos: s, time: o } = t[r]),
+        ({ pos: n, time: a } = t[l]))
+      : (e >= t[r].time && e <= t[l].time && ({ lo: r, hi: l } = et(t, "time", e)),
+        ({ time: s, pos: o } = t[r]),
+        ({ time: n, pos: a } = t[l]));
+    const h = n - s;
+    return h ? o + (a - o) * (e - s) / h : o;
+  }
+  wa.id = "time",
+    wa.defaults = {
+      bounds: "data",
+      adapters: {},
+      time: { parser: !1, unit: !1, round: !1, isoWeekday: !1, minUnit: "millisecond", displayFormats: {} },
+      ticks: { source: "auto", major: { enabled: !1 } },
+    };
+  class ka extends wa {
+    constructor(t) {
+      super(t), this._table = [], this._minPos = void 0, this._tableRange = void 0;
+    }
+    initOffsets() {
+      const t = this._getTimestampsForTable(), e = this._table = this.buildLookupTable(t);
+      this._minPos = Ma(e, this.min), this._tableRange = Ma(e, this.max) - this._minPos, super.initOffsets(t);
+    }
+    buildLookupTable(t) {
+      const { min: e, max: i } = this, s = [], n = [];
+      let o, a, r, l, h;
+      for (o = 0, a = t.length; o < a; ++o) l = t[o], l >= e && l <= i && s.push(l);
+      if (s.length < 2) return [{ time: e, pos: 0 }, { time: i, pos: 1 }];
+      for (o = 0, a = s.length; o < a; ++o) {
+        h = s[o + 1], r = s[o - 1], l = s[o], Math.round((h + r) / 2) !== l && n.push({ time: l, pos: o / (a - 1) });
+      }
+      return n;
+    }
+    _getTimestampsForTable() {
+      let t = this._cache.all || [];
+      if (t.length) return t;
+      const e = this.getDataTimestamps(), i = this.getLabelTimestamps();
+      return t = e.length && i.length ? this.normalize(e.concat(i)) : e.length ? e : i, t = this._cache.all = t, t;
+    }
+    getDecimalForValue(t) {
+      return (Ma(this._table, t) - this._minPos) / this._tableRange;
+    }
+    getValueForPixel(t) {
+      const e = this._offsets, i = this.getDecimalForPixel(t) / e.factor - e.end;
+      return Ma(this._table, i * this._tableRange + this._minPos, !0);
+    }
+  }
+  ka.id = "timeseries", ka.defaults = wa.defaults;
+  var Sa = Object.freeze({
+    __proto__: null,
+    CategoryScale: ta,
+    LinearScale: sa,
+    LogarithmicScale: oa,
+    RadialLinearScale: ga,
+    TimeScale: wa,
+    TimeSeriesScale: ka,
+  });
+  return bn.register(Bn, Sa, co, Jo),
+    bn.helpers = { ...Ti },
+    bn._adapters = wn,
+    bn.Animation = xs,
+    bn.Animations = ys,
+    bn.animator = mt,
+    bn.controllers = Us.controllers.items,
+    bn.DatasetController = Ls,
+    bn.Element = Es,
+    bn.elements = co,
+    bn.Interaction = Vi,
+    bn.layouts = Zi,
+    bn.platforms = ps,
+    bn.Scale = $s,
+    bn.Ticks = Is,
+    Object.assign(bn, Bn, Sa, co, Jo, ps),
+    bn.Chart = bn,
+    "undefined" != typeof window && (window.Chart = bn),
+    bn;
+});
diff --git a/assets/plugin/mermaid-theme.js b/assets/plugin/mermaid-theme.js
new file mode 100644
index 00000000..0513f2fa
--- /dev/null
+++ b/assets/plugin/mermaid-theme.js
@@ -0,0 +1,34 @@
+// Mermaid theme and functions
+const pink = "#E6007A";
+const purple = "#442299";
+const lightPurple = "#6D3AEE";
+const white = "#FFFFFF";
+
+Reveal.addEventListener("ready", event => asyncMermaidRender(event));
+
+async function asyncMermaidRender(event) {
+  var graphs = document.querySelectorAll(".mermaid");
+  graphs.forEach((item, index) => {
+    let graphCode = item.textContent.trim(); // trim() becase of gantt, class and git diagram
+    let mermaidDiv = document.createElement("div");
+    mermaidDiv.classList.add("mermaid");
+    mermaidDiv.setAttribute("data-processed", "true");
+
+    try {
+      // item.innerText ignores html elements added by revealjs highlight plugin.
+      mermaid.mermaidAPI.render("theGraph" + index, graphCode, function(svgCode) {
+        mermaidDiv.innerHTML = svgCode;
+      });
+
+      let parentDiv = document.createElement("div");
+      parentDiv.appendChild(mermaidDiv);
+      parentDiv.style.width = "100%";
+      parentDiv.style.height = "100%";
+      item.parentNode.parentNode.insertBefore(parentDiv, item.parentNode);
+      item.parentNode.remove();
+    } catch (err) {
+      console.log("Cannot render mermaid diagram " + index + "\n" + graphCode);
+      console.log(err.message);
+    }
+  });
+}
diff --git a/assets/plugin/mermaid.js b/assets/plugin/mermaid.js
new file mode 100644
index 00000000..bfa7f98a
--- /dev/null
+++ b/assets/plugin/mermaid.js
@@ -0,0 +1,40764 @@
+!function(t, e) {
+  "object" == typeof exports && "undefined" != typeof module
+    ? module.exports = e()
+    : "function" == typeof define && define.amd
+    ? define(e)
+    : (t = "undefined" != typeof globalThis ? globalThis : t || self).RevealMermaid = e();
+}(this, function() {
+  "use strict";
+  "undefined" != typeof globalThis
+    ? globalThis
+    : "undefined" != typeof window
+    ? window
+    : "undefined" != typeof global
+    ? global
+    : "undefined" != typeof self && self;
+  var t = { exports: {} };
+  !function(t, e) {
+    t.exports = function() {
+      var e;
+      function n() {
+        return e.apply(null, arguments);
+      }
+      function i(t) {
+        return t instanceof Array || "[object Array]" === Object.prototype.toString.call(t);
+      }
+      function r(t) {
+        return null != t && "[object Object]" === Object.prototype.toString.call(t);
+      }
+      function a(t, e) {
+        return Object.prototype.hasOwnProperty.call(t, e);
+      }
+      function s(t) {
+        if (Object.getOwnPropertyNames) return 0 === Object.getOwnPropertyNames(t).length;
+        for (var e in t) if (a(t, e)) return;
+        return 1;
+      }
+      function o(t) {
+        return void 0 === t;
+      }
+      function l(t) {
+        return "number" == typeof t || "[object Number]" === Object.prototype.toString.call(t);
+      }
+      function c(t) {
+        return t instanceof Date || "[object Date]" === Object.prototype.toString.call(t);
+      }
+      function h(t, e) {
+        for (var n = [], i = t.length, r = 0; r < i; ++r) n.push(e(t[r], r));
+        return n;
+      }
+      function u(t, e) {
+        for (var n in e) a(e, n) && (t[n] = e[n]);
+        return a(e, "toString") && (t.toString = e.toString), a(e, "valueOf") && (t.valueOf = e.valueOf), t;
+      }
+      function d(t, e, n, i) {
+        return De(t, e, n, i, !0).utc();
+      }
+      function p(t) {
+        return null == t._pf
+          && (t._pf = {
+            empty: !1,
+            unusedTokens: [],
+            unusedInput: [],
+            overflow: -2,
+            charsLeftOver: 0,
+            nullInput: !1,
+            invalidEra: null,
+            invalidMonth: null,
+            invalidFormat: !1,
+            userInvalidated: !1,
+            iso: !1,
+            parsedDateParts: [],
+            era: null,
+            meridiem: null,
+            rfc2822: !1,
+            weekdayMismatch: !1,
+          }),
+          t._pf;
+      }
+      function f(t) {
+        if (null == t._isValid) {
+          var e = p(t),
+            n = y.call(e.parsedDateParts, function(t) {
+              return null != t;
+            });
+          if (
+            n = !isNaN(t._d.getTime()) && e.overflow < 0 && !e.empty && !e.invalidEra && !e.invalidMonth
+              && !e.invalidWeekday && !e.weekdayMismatch && !e.nullInput && !e.invalidFormat && !e.userInvalidated
+              && (!e.meridiem || e.meridiem && n),
+              t._strict && (n = n && 0 === e.charsLeftOver && 0 === e.unusedTokens.length && void 0 === e.bigHour),
+              null != Object.isFrozen && Object.isFrozen(t)
+          ) return n;
+          t._isValid = n;
+        }
+        return t._isValid;
+      }
+      function g(t) {
+        var e = d(NaN);
+        return null != t ? u(p(e), t) : p(e).userInvalidated = !0, e;
+      }
+      var y = Array.prototype.some || function(t) {
+          for (var e = Object(this), n = e.length >>> 0, i = 0; i < n; i++) {
+            if (i in e && t.call(this, e[i], i, e)) return !0;
+          }
+          return !1;
+        },
+        m = n.momentProperties = [],
+        b = !1;
+      function _(t, e) {
+        var n, i, r, a = m.length;
+        if (
+          o(e._isAMomentObject) || (t._isAMomentObject = e._isAMomentObject),
+            o(e._i) || (t._i = e._i),
+            o(e._f) || (t._f = e._f),
+            o(e._l) || (t._l = e._l),
+            o(e._strict) || (t._strict = e._strict),
+            o(e._tzm) || (t._tzm = e._tzm),
+            o(e._isUTC) || (t._isUTC = e._isUTC),
+            o(e._offset) || (t._offset = e._offset),
+            o(e._pf) || (t._pf = p(e)),
+            o(e._locale) || (t._locale = e._locale),
+            0 < a
+        ) for (n = 0; n < a; n++) o(r = e[i = m[n]]) || (t[i] = r);
+        return t;
+      }
+      function x(t) {
+        _(this, t),
+          this._d = new Date(null != t._d ? t._d.getTime() : NaN),
+          this.isValid() || (this._d = new Date(NaN)),
+          !1 === b && (b = !0, n.updateOffset(this), b = !1);
+      }
+      function v(t) {
+        return t instanceof x || null != t && null != t._isAMomentObject;
+      }
+      function k(t) {
+        !1 === n.suppressDeprecationWarnings && "undefined" != typeof console && console.warn
+          && console.warn("Deprecation warning: " + t);
+      }
+      function w(t, e) {
+        var i = !0;
+        return u(function() {
+          if (null != n.deprecationHandler && n.deprecationHandler(null, t), i) {
+            for (var r, s, o = [], l = arguments.length, c = 0; c < l; c++) {
+              if (r = "", "object" == typeof arguments[c]) {
+                for (s in r += "\n[" + c + "] ", arguments[0]) {
+                  a(arguments[0], s) && (r += s + ": " + arguments[0][s] + ", ");
+                }
+                r = r.slice(0, -2);
+              } else r = arguments[c];
+              o.push(r);
+            }
+            k(t + "\nArguments: " + Array.prototype.slice.call(o).join("") + "\n" + (new Error()).stack), i = !1;
+          }
+          return e.apply(this, arguments);
+        }, e);
+      }
+      var T = {};
+      function C(t, e) {
+        null != n.deprecationHandler && n.deprecationHandler(t, e), T[t] || (k(e), T[t] = !0);
+      }
+      function E(t) {
+        return "undefined" != typeof Function && t instanceof Function
+          || "[object Function]" === Object.prototype.toString.call(t);
+      }
+      function S(t, e) {
+        var n, i = u({}, t);
+        for (n in e) {
+          a(e, n) && (r(t[n]) && r(e[n])
+            ? (i[n] = {}, u(i[n], t[n]), u(i[n], e[n]))
+            : null != e[n]
+            ? i[n] = e[n]
+            : delete i[n]);
+        }
+        for (n in t) a(t, n) && !a(e, n) && r(t[n]) && (i[n] = u({}, i[n]));
+        return i;
+      }
+      function A(t) {
+        null != t && this.set(t);
+      }
+      n.suppressDeprecationWarnings = !1, n.deprecationHandler = null;
+      var D = Object.keys || function(t) {
+        var e, n = [];
+        for (e in t) a(t, e) && n.push(e);
+        return n;
+      };
+      function L(t, e, n) {
+        var i = "" + Math.abs(t);
+        return (0 <= t ? n ? "+" : "" : "-") + Math.pow(10, Math.max(0, e - i.length)).toString().substr(1) + i;
+      }
+      var O =
+          /(\[[^\[]*\])|(\\)?([Hh]mm(ss)?|Mo|MM?M?M?|Do|DDDo|DD?D?D?|ddd?d?|do?|w[o|w]?|W[o|W]?|Qo?|N{1,5}|YYYYYY|YYYYY|YYYY|YY|y{2,4}|yo?|gg(ggg?)?|GG(GGG?)?|e|E|a|A|hh?|HH?|kk?|mm?|ss?|S{1,9}|x|X|zz?|ZZ?|.)/g,
+        N = /(\[[^\[]*\])|(\\)?(LTS|LT|LL?L?L?|l{1,4})/g,
+        M = {},
+        B = {};
+      function I(t, e, n, i) {
+        var r = "string" == typeof i
+          ? function() {
+            return this[i]();
+          }
+          : i;
+        t && (B[t] = r),
+          e && (B[e[0]] = function() {
+            return L(r.apply(this, arguments), e[1], e[2]);
+          }),
+          n && (B[n] = function() {
+            return this.localeData().ordinal(r.apply(this, arguments), t);
+          });
+      }
+      function F(t, e) {
+        return t.isValid()
+          ? (e = R(e, t.localeData()),
+            M[e] = M[e] || function(t) {
+              for (var e, n = t.match(O), i = 0, r = n.length; i < r; i++) {
+                B[n[i]]
+                  ? n[i] = B[n[i]]
+                  : n[i] = (e = n[i]).match(/\[[\s\S]/) ? e.replace(/^\[|\]$/g, "") : e.replace(/\\/g, "");
+              }
+              return function(e) {
+                for (var i = "", a = 0; a < r; a++) i += E(n[a]) ? n[a].call(e, t) : n[a];
+                return i;
+              };
+            }(e),
+            M[e](t))
+          : t.localeData().invalidDate();
+      }
+      function R(t, e) {
+        var n = 5;
+        function i(t) {
+          return e.longDateFormat(t) || t;
+        }
+        for (N.lastIndex = 0; 0 <= n && N.test(t);) t = t.replace(N, i), N.lastIndex = 0, --n;
+        return t;
+      }
+      var $ = {};
+      function P(t, e) {
+        var n = t.toLowerCase();
+        $[n] = $[n + "s"] = $[e] = t;
+      }
+      function Y(t) {
+        return "string" == typeof t ? $[t] || $[t.toLowerCase()] : void 0;
+      }
+      function j(t) {
+        var e, n, i = {};
+        for (n in t) a(t, n) && (e = Y(n)) && (i[e] = t[n]);
+        return i;
+      }
+      var z = {};
+      function U(t, e) {
+        z[t] = e;
+      }
+      function W(t) {
+        return t % 4 == 0 && t % 100 != 0 || t % 400 == 0;
+      }
+      function H(t) {
+        return t < 0 ? Math.ceil(t) || 0 : Math.floor(t);
+      }
+      function q(t) {
+        var e = 0;
+        return 0 != (t = +t) && isFinite(t) ? H(t) : e;
+      }
+      function V(t, e) {
+        return function(i) {
+          return null != i ? (X(this, t, i), n.updateOffset(this, e), this) : G(this, t);
+        };
+      }
+      function G(t, e) {
+        return t.isValid() ? t._d["get" + (t._isUTC ? "UTC" : "") + e]() : NaN;
+      }
+      function X(t, e, n) {
+        t.isValid() && !isNaN(n)
+          && ("FullYear" === e && W(t.year()) && 1 === t.month() && 29 === t.date()
+            ? (n = q(n), t._d["set" + (t._isUTC ? "UTC" : "") + e](n, t.month(), Dt(n, t.month())))
+            : t._d["set" + (t._isUTC ? "UTC" : "") + e](n));
+      }
+      var Z = /\d/,
+        Q = /\d\d/,
+        K = /\d{3}/,
+        J = /\d{4}/,
+        tt = /[+-]?\d{6}/,
+        et = /\d\d?/,
+        nt = /\d\d\d\d?/,
+        it = /\d\d\d\d\d\d?/,
+        rt = /\d{1,3}/,
+        at = /\d{1,4}/,
+        st = /[+-]?\d{1,6}/,
+        ot = /\d+/,
+        lt = /[+-]?\d+/,
+        ct = /Z|[+-]\d\d:?\d\d/gi,
+        ht = /Z|[+-]\d\d(?::?\d\d)?/gi,
+        ut =
+          /[0-9]{0,256}['a-z\u00A0-\u05FF\u0700-\uD7FF\uF900-\uFDCF\uFDF0-\uFF07\uFF10-\uFFEF]{1,256}|[\u0600-\u06FF\/]{1,256}(\s*?[\u0600-\u06FF]{1,256}){1,2}/i;
+      function dt(t, e, n) {
+        gt[t] = E(e) ? e : function(t, i) {
+          return t && n ? n : e;
+        };
+      }
+      function pt(t, e) {
+        return a(gt, t)
+          ? gt[t](e._strict, e._locale)
+          : new RegExp(ft(
+            t.replace("\\", "").replace(/\\(\[)|\\(\])|\[([^\]\[]*)\]|\\(.)/g, function(t, e, n, i, r) {
+              return e || n || i || r;
+            }),
+          ));
+      }
+      function ft(t) {
+        return t.replace(/[-\/\\^$*+?.()|[\]{}]/g, "\\$&");
+      }
+      var gt = {}, yt = {};
+      function mt(t, e) {
+        var n, i, r = e;
+        for (
+          "string" == typeof t && (t = [t]),
+            l(e) && (r = function(t, n) {
+              n[e] = q(t);
+            }),
+            i = t.length,
+            n = 0;
+          n < i;
+          n++
+        ) yt[t[n]] = r;
+      }
+      function bt(t, e) {
+        mt(t, function(t, n, i, r) {
+          i._w = i._w || {}, e(t, i._w, i, r);
+        });
+      }
+      var _t, xt = 0, vt = 1, kt = 2, wt = 3, Tt = 4, Ct = 5, Et = 6, St = 7, At = 8;
+      function Dt(t, e) {
+        if (isNaN(t) || isNaN(e)) return NaN;
+        var n = (e % (n = 12) + n) % n;
+        return t += (e - n) / 12, 1 == n ? W(t) ? 29 : 28 : 31 - n % 7 % 2;
+      }
+      _t = Array.prototype.indexOf || function(t) {
+        for (var e = 0; e < this.length; ++e) if (this[e] === t) return e;
+        return -1;
+      },
+        I("M", ["MM", 2], "Mo", function() {
+          return this.month() + 1;
+        }),
+        I("MMM", 0, 0, function(t) {
+          return this.localeData().monthsShort(this, t);
+        }),
+        I("MMMM", 0, 0, function(t) {
+          return this.localeData().months(this, t);
+        }),
+        P("month", "M"),
+        U("month", 8),
+        dt("M", et),
+        dt("MM", et, Q),
+        dt("MMM", function(t, e) {
+          return e.monthsShortRegex(t);
+        }),
+        dt("MMMM", function(t, e) {
+          return e.monthsRegex(t);
+        }),
+        mt(["M", "MM"], function(t, e) {
+          e[vt] = q(t) - 1;
+        }),
+        mt(["MMM", "MMMM"], function(t, e, n, i) {
+          null != (i = n._locale.monthsParse(t, i, n._strict)) ? e[vt] = i : p(n).invalidMonth = t;
+        });
+      var Lt = "January_February_March_April_May_June_July_August_September_October_November_December".split("_"),
+        Ot = "Jan_Feb_Mar_Apr_May_Jun_Jul_Aug_Sep_Oct_Nov_Dec".split("_"),
+        Nt = /D[oD]?(\[[^\[\]]*\]|\s)+MMMM?/,
+        Mt = ut,
+        Bt = ut;
+      function It(t, e) {
+        var n;
+        if (t.isValid()) {
+          if ("string" == typeof e) {
+            if (/^\d+$/.test(e)) e = q(e);
+            else if (!l(e = t.localeData().monthsParse(e))) return;
+          }
+          n = Math.min(t.date(), Dt(t.year(), e)), t._d["set" + (t._isUTC ? "UTC" : "") + "Month"](e, n);
+        }
+      }
+      function Ft(t) {
+        return null != t ? (It(this, t), n.updateOffset(this, !0), this) : G(this, "Month");
+      }
+      function Rt() {
+        function t(t, e) {
+          return e.length - t.length;
+        }
+        for (var e, n = [], i = [], r = [], a = 0; a < 12; a++) {
+          e = d([2e3, a]),
+            n.push(this.monthsShort(e, "")),
+            i.push(this.months(e, "")),
+            r.push(this.months(e, "")),
+            r.push(this.monthsShort(e, ""));
+        }
+        for (n.sort(t), i.sort(t), r.sort(t), a = 0; a < 12; a++) n[a] = ft(n[a]), i[a] = ft(i[a]);
+        for (a = 0; a < 24; a++) r[a] = ft(r[a]);
+        this._monthsRegex = new RegExp("^(" + r.join("|") + ")", "i"),
+          this._monthsShortRegex = this._monthsRegex,
+          this._monthsStrictRegex = new RegExp("^(" + i.join("|") + ")", "i"),
+          this._monthsShortStrictRegex = new RegExp("^(" + n.join("|") + ")", "i");
+      }
+      function $t(t) {
+        return W(t) ? 366 : 365;
+      }
+      I("Y", 0, 0, function() {
+        var t = this.year();
+        return t <= 9999 ? L(t, 4) : "+" + t;
+      }),
+        I(0, ["YY", 2], 0, function() {
+          return this.year() % 100;
+        }),
+        I(0, ["YYYY", 4], 0, "year"),
+        I(0, ["YYYYY", 5], 0, "year"),
+        I(0, ["YYYYYY", 6, !0], 0, "year"),
+        P("year", "y"),
+        U("year", 1),
+        dt("Y", lt),
+        dt("YY", et, Q),
+        dt("YYYY", at, J),
+        dt("YYYYY", st, tt),
+        dt("YYYYYY", st, tt),
+        mt(["YYYYY", "YYYYYY"], xt),
+        mt("YYYY", function(t, e) {
+          e[xt] = 2 === t.length ? n.parseTwoDigitYear(t) : q(t);
+        }),
+        mt("YY", function(t, e) {
+          e[xt] = n.parseTwoDigitYear(t);
+        }),
+        mt("Y", function(t, e) {
+          e[xt] = parseInt(t, 10);
+        }),
+        n.parseTwoDigitYear = function(t) {
+          return q(t) + (68 < q(t) ? 1900 : 2e3);
+        };
+      var Pt = V("FullYear", !0);
+      function Yt(t, e, n, i, r, a, s) {
+        var o;
+        return t < 100 && 0 <= t
+          ? (o = new Date(t + 400, e, n, i, r, a, s), isFinite(o.getFullYear()) && o.setFullYear(t))
+          : o = new Date(t, e, n, i, r, a, s),
+          o;
+      }
+      function jt(t) {
+        var e;
+        return t < 100 && 0 <= t
+          ? ((e = Array.prototype.slice.call(arguments))[0] = t + 400,
+            e = new Date(Date.UTC.apply(null, e)),
+            isFinite(e.getUTCFullYear()) && e.setUTCFullYear(t))
+          : e = new Date(Date.UTC.apply(null, arguments)),
+          e;
+      }
+      function zt(t, e, n) {
+        return (n = 7 + e - n) - (7 + jt(t, 0, n).getUTCDay() - e) % 7 - 1;
+      }
+      function Ut(t, e, n, i, r) {
+        var a;
+        return n = (e = 1 + 7 * (e - 1) + (7 + n - i) % 7 + zt(t, i, r)) <= 0
+          ? $t(a = t - 1) + e
+          : e > $t(t)
+          ? (a = t + 1, e - $t(t))
+          : (a = t, e),
+          { year: a, dayOfYear: n };
+      }
+      function Wt(t, e, n) {
+        var i, r, a = zt(t.year(), e, n);
+        return (a = Math.floor((t.dayOfYear() - a - 1) / 7) + 1) < 1
+          ? i = a + Ht(r = t.year() - 1, e, n)
+          : a > Ht(t.year(), e, n)
+          ? (i = a - Ht(t.year(), e, n), r = t.year() + 1)
+          : (r = t.year(), i = a),
+          { week: i, year: r };
+      }
+      function Ht(t, e, n) {
+        var i = zt(t, e, n);
+        return e = zt(t + 1, e, n), ($t(t) - i + e) / 7;
+      }
+      function qt(t, e) {
+        return t.slice(e, 7).concat(t.slice(0, e));
+      }
+      I("w", ["ww", 2], "wo", "week"),
+        I("W", ["WW", 2], "Wo", "isoWeek"),
+        P("week", "w"),
+        P("isoWeek", "W"),
+        U("week", 5),
+        U("isoWeek", 5),
+        dt("w", et),
+        dt("ww", et, Q),
+        dt("W", et),
+        dt("WW", et, Q),
+        bt(["w", "ww", "W", "WW"], function(t, e, n, i) {
+          e[i.substr(0, 1)] = q(t);
+        }),
+        I("d", 0, "do", "day"),
+        I("dd", 0, 0, function(t) {
+          return this.localeData().weekdaysMin(this, t);
+        }),
+        I("ddd", 0, 0, function(t) {
+          return this.localeData().weekdaysShort(this, t);
+        }),
+        I("dddd", 0, 0, function(t) {
+          return this.localeData().weekdays(this, t);
+        }),
+        I("e", 0, 0, "weekday"),
+        I("E", 0, 0, "isoWeekday"),
+        P("day", "d"),
+        P("weekday", "e"),
+        P("isoWeekday", "E"),
+        U("day", 11),
+        U("weekday", 11),
+        U("isoWeekday", 11),
+        dt("d", et),
+        dt("e", et),
+        dt("E", et),
+        dt("dd", function(t, e) {
+          return e.weekdaysMinRegex(t);
+        }),
+        dt("ddd", function(t, e) {
+          return e.weekdaysShortRegex(t);
+        }),
+        dt("dddd", function(t, e) {
+          return e.weekdaysRegex(t);
+        }),
+        bt(["dd", "ddd", "dddd"], function(t, e, n, i) {
+          null != (i = n._locale.weekdaysParse(t, i, n._strict)) ? e.d = i : p(n).invalidWeekday = t;
+        }),
+        bt(["d", "e", "E"], function(t, e, n, i) {
+          e[i] = q(t);
+        });
+      var Vt = "Sunday_Monday_Tuesday_Wednesday_Thursday_Friday_Saturday".split("_"),
+        Gt = "Sun_Mon_Tue_Wed_Thu_Fri_Sat".split("_"),
+        Xt = "Su_Mo_Tu_We_Th_Fr_Sa".split("_"),
+        Zt = ut,
+        Qt = ut,
+        Kt = ut;
+      function Jt() {
+        function t(t, e) {
+          return e.length - t.length;
+        }
+        for (var e, n, i, r = [], a = [], s = [], o = [], l = 0; l < 7; l++) {
+          i = d([2e3, 1]).day(l),
+            e = ft(this.weekdaysMin(i, "")),
+            n = ft(this.weekdaysShort(i, "")),
+            i = ft(this.weekdays(i, "")),
+            r.push(e),
+            a.push(n),
+            s.push(i),
+            o.push(e),
+            o.push(n),
+            o.push(i);
+        }
+        r.sort(t),
+          a.sort(t),
+          s.sort(t),
+          o.sort(t),
+          this._weekdaysRegex = new RegExp("^(" + o.join("|") + ")", "i"),
+          this._weekdaysShortRegex = this._weekdaysRegex,
+          this._weekdaysMinRegex = this._weekdaysRegex,
+          this._weekdaysStrictRegex = new RegExp("^(" + s.join("|") + ")", "i"),
+          this._weekdaysShortStrictRegex = new RegExp("^(" + a.join("|") + ")", "i"),
+          this._weekdaysMinStrictRegex = new RegExp("^(" + r.join("|") + ")", "i");
+      }
+      function te() {
+        return this.hours() % 12 || 12;
+      }
+      function ee(t, e) {
+        I(t, 0, 0, function() {
+          return this.localeData().meridiem(this.hours(), this.minutes(), e);
+        });
+      }
+      function ne(t, e) {
+        return e._meridiemParse;
+      }
+      I("H", ["HH", 2], 0, "hour"),
+        I("h", ["hh", 2], 0, te),
+        I("k", ["kk", 2], 0, function() {
+          return this.hours() || 24;
+        }),
+        I("hmm", 0, 0, function() {
+          return "" + te.apply(this) + L(this.minutes(), 2);
+        }),
+        I("hmmss", 0, 0, function() {
+          return "" + te.apply(this) + L(this.minutes(), 2) + L(this.seconds(), 2);
+        }),
+        I("Hmm", 0, 0, function() {
+          return "" + this.hours() + L(this.minutes(), 2);
+        }),
+        I("Hmmss", 0, 0, function() {
+          return "" + this.hours() + L(this.minutes(), 2) + L(this.seconds(), 2);
+        }),
+        ee("a", !0),
+        ee("A", !1),
+        P("hour", "h"),
+        U("hour", 13),
+        dt("a", ne),
+        dt("A", ne),
+        dt("H", et),
+        dt("h", et),
+        dt("k", et),
+        dt("HH", et, Q),
+        dt("hh", et, Q),
+        dt("kk", et, Q),
+        dt("hmm", nt),
+        dt("hmmss", it),
+        dt("Hmm", nt),
+        dt("Hmmss", it),
+        mt(["H", "HH"], wt),
+        mt(["k", "kk"], function(t, e, n) {
+          t = q(t), e[wt] = 24 === t ? 0 : t;
+        }),
+        mt(["a", "A"], function(t, e, n) {
+          n._isPm = n._locale.isPM(t), n._meridiem = t;
+        }),
+        mt(["h", "hh"], function(t, e, n) {
+          e[wt] = q(t), p(n).bigHour = !0;
+        }),
+        mt("hmm", function(t, e, n) {
+          var i = t.length - 2;
+          e[wt] = q(t.substr(0, i)), e[Tt] = q(t.substr(i)), p(n).bigHour = !0;
+        }),
+        mt("hmmss", function(t, e, n) {
+          var i = t.length - 4, r = t.length - 2;
+          e[wt] = q(t.substr(0, i)), e[Tt] = q(t.substr(i, 2)), e[Ct] = q(t.substr(r)), p(n).bigHour = !0;
+        }),
+        mt("Hmm", function(t, e, n) {
+          var i = t.length - 2;
+          e[wt] = q(t.substr(0, i)), e[Tt] = q(t.substr(i));
+        }),
+        mt("Hmmss", function(t, e, n) {
+          var i = t.length - 4, r = t.length - 2;
+          e[wt] = q(t.substr(0, i)), e[Tt] = q(t.substr(i, 2)), e[Ct] = q(t.substr(r));
+        }),
+        ut = V("Hours", !0);
+      var ie,
+        re = {
+          calendar: {
+            sameDay: "[Today at] LT",
+            nextDay: "[Tomorrow at] LT",
+            nextWeek: "dddd [at] LT",
+            lastDay: "[Yesterday at] LT",
+            lastWeek: "[Last] dddd [at] LT",
+            sameElse: "L",
+          },
+          longDateFormat: {
+            LTS: "h:mm:ss A",
+            LT: "h:mm A",
+            L: "MM/DD/YYYY",
+            LL: "MMMM D, YYYY",
+            LLL: "MMMM D, YYYY h:mm A",
+            LLLL: "dddd, MMMM D, YYYY h:mm A",
+          },
+          invalidDate: "Invalid date",
+          ordinal: "%d",
+          dayOfMonthOrdinalParse: /\d{1,2}/,
+          relativeTime: {
+            future: "in %s",
+            past: "%s ago",
+            s: "a few seconds",
+            ss: "%d seconds",
+            m: "a minute",
+            mm: "%d minutes",
+            h: "an hour",
+            hh: "%d hours",
+            d: "a day",
+            dd: "%d days",
+            w: "a week",
+            ww: "%d weeks",
+            M: "a month",
+            MM: "%d months",
+            y: "a year",
+            yy: "%d years",
+          },
+          months: Lt,
+          monthsShort: Ot,
+          week: { dow: 0, doy: 6 },
+          weekdays: Vt,
+          weekdaysMin: Xt,
+          weekdaysShort: Gt,
+          meridiemParse: /[ap]\.?m?\.?/i,
+        },
+        ae = {},
+        se = {};
+      function oe(t) {
+        return t && t.toLowerCase().replace("_", "-");
+      }
+      function le(t) {
+        for (var e, n, i, r, a = 0; a < t.length;) {
+          for (e = (r = oe(t[a]).split("-")).length, n = (n = oe(t[a + 1])) ? n.split("-") : null; 0 < e;) {
+            if (i = ce(r.slice(0, e).join("-"))) return i;
+            if (
+              n && n.length >= e && function(t, e) {
+                  for (var n = Math.min(t.length, e.length), i = 0; i < n; i += 1) if (t[i] !== e[i]) return i;
+                  return n;
+                }(r, n) >= e - 1
+            ) break;
+            e--;
+          }
+          a++;
+        }
+        return ie;
+      }
+      function ce(e) {
+        var n;
+        if (void 0 === ae[e] && t && t.exports && null != e.match("^[^/\\\\]*$")) {
+          try {
+            n = ie._abbr,
+              function(t) {
+                throw new Error(
+                  "Could not dynamically require \"" + t
+                    + "\". Please configure the dynamicRequireTargets or/and ignoreDynamicRequires option of @rollup/plugin-commonjs appropriately for this require call to work.",
+                );
+              }("./locale/" + e),
+              he(n);
+          } catch (n) {
+            ae[e] = null;
+          }
+        }
+        return ae[e];
+      }
+      function he(t, e) {
+        return t
+          && ((e = o(e) ? de(t) : ue(t, e))
+            ? ie = e
+            : "undefined" != typeof console && console.warn
+              && console.warn("Locale " + t + " not found. Did you forget to load it?")),
+          ie._abbr;
+      }
+      function ue(t, e) {
+        if (null === e) return delete ae[t], null;
+        var n, i = re;
+        if (e.abbr = t, null != ae[t]) {
+          C(
+            "defineLocaleOverride",
+            "use moment.updateLocale(localeName, config) to change an existing locale. moment.defineLocale(localeName, config) should only be used for creating a new locale See http://momentjs.com/guides/#/warnings/define-locale/ for more info.",
+          ), i = ae[t]._config;
+        } else if (null != e.parentLocale) {
+          if (null != ae[e.parentLocale]) i = ae[e.parentLocale]._config;
+          else {
+            if (null == (n = ce(e.parentLocale))) {
+              return se[e.parentLocale] || (se[e.parentLocale] = []),
+                se[e.parentLocale].push({ name: t, config: e }),
+                null;
+            }
+            i = n._config;
+          }
+        }
+        return ae[t] = new A(S(i, e)),
+          se[t] && se[t].forEach(function(t) {
+            ue(t.name, t.config);
+          }),
+          he(t),
+          ae[t];
+      }
+      function de(t) {
+        var e;
+        if (!(t = t && t._locale && t._locale._abbr ? t._locale._abbr : t)) return ie;
+        if (!i(t)) {
+          if (e = ce(t)) return e;
+          t = [t];
+        }
+        return le(t);
+      }
+      function pe(t) {
+        var e = t._a;
+        return e && -2 === p(t).overflow
+          && (e = e[vt] < 0 || 11 < e[vt]
+            ? vt
+            : e[kt] < 1 || e[kt] > Dt(e[xt], e[vt])
+            ? kt
+            : e[wt] < 0 || 24 < e[wt] || 24 === e[wt] && (0 !== e[Tt] || 0 !== e[Ct] || 0 !== e[Et])
+            ? wt
+            : e[Tt] < 0 || 59 < e[Tt]
+            ? Tt
+            : e[Ct] < 0 || 59 < e[Ct]
+            ? Ct
+            : e[Et] < 0 || 999 < e[Et]
+            ? Et
+            : -1,
+            p(t)._overflowDayOfYear && (e < xt || kt < e) && (e = kt),
+            p(t)._overflowWeeks && -1 === e && (e = St),
+            p(t)._overflowWeekday && -1 === e && (e = At),
+            p(t).overflow = e),
+          t;
+      }
+      var fe =
+          /^\s*((?:[+-]\d{6}|\d{4})-(?:\d\d-\d\d|W\d\d-\d|W\d\d|\d\d\d|\d\d))(?:(T| )(\d\d(?::\d\d(?::\d\d(?:[.,]\d+)?)?)?)([+-]\d\d(?::?\d\d)?|\s*Z)?)?$/,
+        ge =
+          /^\s*((?:[+-]\d{6}|\d{4})(?:\d\d\d\d|W\d\d\d|W\d\d|\d\d\d|\d\d|))(?:(T| )(\d\d(?:\d\d(?:\d\d(?:[.,]\d+)?)?)?)([+-]\d\d(?::?\d\d)?|\s*Z)?)?$/,
+        ye = /Z|[+-]\d\d(?::?\d\d)?/,
+        me = [
+          ["YYYYYY-MM-DD", /[+-]\d{6}-\d\d-\d\d/],
+          ["YYYY-MM-DD", /\d{4}-\d\d-\d\d/],
+          ["GGGG-[W]WW-E", /\d{4}-W\d\d-\d/],
+          ["GGGG-[W]WW", /\d{4}-W\d\d/, !1],
+          ["YYYY-DDD", /\d{4}-\d{3}/],
+          ["YYYY-MM", /\d{4}-\d\d/, !1],
+          ["YYYYYYMMDD", /[+-]\d{10}/],
+          ["YYYYMMDD", /\d{8}/],
+          ["GGGG[W]WWE", /\d{4}W\d{3}/],
+          ["GGGG[W]WW", /\d{4}W\d{2}/, !1],
+          ["YYYYDDD", /\d{7}/],
+          ["YYYYMM", /\d{6}/, !1],
+          ["YYYY", /\d{4}/, !1],
+        ],
+        be = [
+          ["HH:mm:ss.SSSS", /\d\d:\d\d:\d\d\.\d+/],
+          ["HH:mm:ss,SSSS", /\d\d:\d\d:\d\d,\d+/],
+          ["HH:mm:ss", /\d\d:\d\d:\d\d/],
+          ["HH:mm", /\d\d:\d\d/],
+          ["HHmmss.SSSS", /\d\d\d\d\d\d\.\d+/],
+          ["HHmmss,SSSS", /\d\d\d\d\d\d,\d+/],
+          ["HHmmss", /\d\d\d\d\d\d/],
+          ["HHmm", /\d\d\d\d/],
+          ["HH", /\d\d/],
+        ],
+        _e = /^\/?Date\((-?\d+)/i,
+        xe =
+          /^(?:(Mon|Tue|Wed|Thu|Fri|Sat|Sun),?\s)?(\d{1,2})\s(Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)\s(\d{2,4})\s(\d\d):(\d\d)(?::(\d\d))?\s(?:(UT|GMT|[ECMP][SD]T)|([Zz])|([+-]\d{4}))$/,
+        ve = { UT: 0, GMT: 0, EDT: -240, EST: -300, CDT: -300, CST: -360, MDT: -360, MST: -420, PDT: -420, PST: -480 };
+      function ke(t) {
+        var e, n, i, r, a, s, o = t._i, l = fe.exec(o) || ge.exec(o), c = (o = me.length, be.length);
+        if (l) {
+          for (p(t).iso = !0, e = 0, n = o; e < n; e++) {
+            if (me[e][1].exec(l[1])) {
+              r = me[e][0], i = !1 !== me[e][2];
+              break;
+            }
+          }
+          if (null == r) t._isValid = !1;
+          else {
+            if (l[3]) {
+              for (e = 0, n = c; e < n; e++) {
+                if (be[e][1].exec(l[3])) {
+                  a = (l[2] || " ") + be[e][0];
+                  break;
+                }
+              }
+              if (null == a) return void (t._isValid = !1);
+            }
+            if (i || null == a) {
+              if (l[4]) {
+                if (!ye.exec(l[4])) return void (t._isValid = !1);
+                s = "Z";
+              }
+              t._f = r + (a || "") + (s || ""), Se(t);
+            } else t._isValid = !1;
+          }
+        } else t._isValid = !1;
+      }
+      function we(t, e, n, i, r, a) {
+        return t = [
+          function(t) {
+            return (t = parseInt(t, 10)) <= 49 ? 2e3 + t : t <= 999 ? 1900 + t : t;
+          }(t),
+          Ot.indexOf(e),
+          parseInt(n, 10),
+          parseInt(i, 10),
+          parseInt(r, 10),
+        ],
+          a && t.push(parseInt(a, 10)),
+          t;
+      }
+      function Te(t) {
+        var e,
+          n,
+          i,
+          r,
+          a = xe.exec(
+            t._i.replace(/\([^()]*\)|[\n\t]/g, " ").replace(/(\s\s+)/g, " ").replace(/^\s\s*/, "").replace(
+              /\s\s*$/,
+              "",
+            ),
+          );
+        a
+          ? (i = e = we(a[4], a[3], a[2], a[5], a[6], a[7]),
+            r = t,
+            (n = a[1]) && Gt.indexOf(n) !== new Date(i[0], i[1], i[2]).getDay()
+              ? (p(r).weekdayMismatch = !0, r._isValid = !1)
+              : (t._a = e,
+                t._tzm =
+                  (n = a[8],
+                    i = a[9],
+                    r = a[10],
+                    n ? ve[n] : i ? 0 : ((n = parseInt(r, 10)) - (i = n % 100)) / 100 * 60 + i),
+                t._d = jt.apply(null, t._a),
+                t._d.setUTCMinutes(t._d.getUTCMinutes() - t._tzm),
+                p(t).rfc2822 = !0))
+          : t._isValid = !1;
+      }
+      function Ce(t, e, n) {
+        return null != t ? t : null != e ? e : n;
+      }
+      function Ee(t) {
+        var e, i, r, a, s, o, l, c, h, u, d, f = [];
+        if (!t._d) {
+          for (
+            r = t,
+              a = new Date(n.now()),
+              i = r._useUTC
+                ? [a.getUTCFullYear(), a.getUTCMonth(), a.getUTCDate()]
+                : [a.getFullYear(), a.getMonth(), a.getDate()],
+              t._w && null == t._a[kt] && null == t._a[vt] && (null != (a = (r = t)._w).GG || null != a.W || null != a.E
+                ? (c = 1,
+                  h = 4,
+                  s = Ce(a.GG, r._a[xt], Wt(Le(), 1, 4).year),
+                  o = Ce(a.W, 1),
+                  ((l = Ce(a.E, 1)) < 1 || 7 < l) && (u = !0))
+                : (c = r._locale._week.dow,
+                  h = r._locale._week.doy,
+                  d = Wt(Le(), c, h),
+                  s = Ce(a.gg, r._a[xt], d.year),
+                  o = Ce(a.w, d.week),
+                  null != a.d
+                    ? ((l = a.d) < 0 || 6 < l) && (u = !0)
+                    : null != a.e
+                    ? (l = a.e + c, (a.e < 0 || 6 < a.e) && (u = !0))
+                    : l = c),
+                o < 1 || o > Ht(s, c, h)
+                  ? p(r)._overflowWeeks = !0
+                  : null != u
+                  ? p(r)._overflowWeekday = !0
+                  : (d = Ut(s, o, l, c, h), r._a[xt] = d.year, r._dayOfYear = d.dayOfYear)),
+              null != t._dayOfYear
+              && (a = Ce(t._a[xt], i[xt]),
+                (t._dayOfYear > $t(a) || 0 === t._dayOfYear) && (p(t)._overflowDayOfYear = !0),
+                u = jt(a, 0, t._dayOfYear),
+                t._a[vt] = u.getUTCMonth(),
+                t._a[kt] = u.getUTCDate()),
+              e = 0;
+            e < 3 && null == t._a[e];
+            ++e
+          ) t._a[e] = f[e] = i[e];
+          for (; e < 7; e++) t._a[e] = f[e] = null == t._a[e] ? 2 === e ? 1 : 0 : t._a[e];
+          24 === t._a[wt] && 0 === t._a[Tt] && 0 === t._a[Ct] && 0 === t._a[Et] && (t._nextDay = !0, t._a[wt] = 0),
+            t._d = (t._useUTC ? jt : Yt).apply(null, f),
+            s = t._useUTC ? t._d.getUTCDay() : t._d.getDay(),
+            null != t._tzm && t._d.setUTCMinutes(t._d.getUTCMinutes() - t._tzm),
+            t._nextDay && (t._a[wt] = 24),
+            t._w && void 0 !== t._w.d && t._w.d !== s && (p(t).weekdayMismatch = !0);
+        }
+      }
+      function Se(t) {
+        if (t._f === n.ISO_8601) ke(t);
+        else if (t._f === n.RFC_2822) Te(t);
+        else {
+          t._a = [], p(t).empty = !0;
+          for (
+            var e,
+              i,
+              r,
+              s,
+              o,
+              l = "" + t._i,
+              c = l.length,
+              h = 0,
+              u = R(t._f, t._locale).match(O) || [],
+              d = u.length,
+              f = 0;
+            f < d;
+            f++
+          ) {
+            i = u[f],
+              (e = (l.match(pt(i, t)) || [])[0])
+              && (0 < (r = l.substr(0, l.indexOf(e))).length && p(t).unusedInput.push(r),
+                l = l.slice(l.indexOf(e) + e.length),
+                h += e.length),
+              B[i]
+                ? (e ? p(t).empty = !1 : p(t).unusedTokens.push(i),
+                  r = i,
+                  o = t,
+                  null != (s = e) && a(yt, r) && yt[r](s, o._a, o, r))
+                : t._strict && !e && p(t).unusedTokens.push(i);
+          }
+          p(t).charsLeftOver = c - h,
+            0 < l.length && p(t).unusedInput.push(l),
+            t._a[wt] <= 12 && !0 === p(t).bigHour && 0 < t._a[wt] && (p(t).bigHour = void 0),
+            p(t).parsedDateParts = t._a.slice(0),
+            p(t).meridiem = t._meridiem,
+            t._a[wt] = function(t, e, n) {
+              return null == n
+                ? e
+                : null != t.meridiemHour
+                ? t.meridiemHour(e, n)
+                : null != t.isPM
+                ? ((t = t.isPM(n)) && e < 12 && (e += 12), e = t || 12 !== e ? e : 0)
+                : e;
+            }(t._locale, t._a[wt], t._meridiem),
+            null !== (c = p(t).era) && (t._a[xt] = t._locale.erasConvertYear(c, t._a[xt])),
+            Ee(t),
+            pe(t);
+        }
+      }
+      function Ae(t) {
+        var e, a, s, d = t._i, y = t._f;
+        return t._locale = t._locale || de(t._l),
+          null === d || void 0 === y && "" === d
+            ? g({ nullInput: !0 })
+            : ("string" == typeof d && (t._i = d = t._locale.preparse(d)),
+              v(d) ? new x(pe(d)) : (c(d) ? t._d = d : i(y)
+                ? function(t) {
+                  var e, n, i, r, a, s, o = !1, l = t._f.length;
+                  if (0 === l) return p(t).invalidFormat = !0, t._d = new Date(NaN);
+                  for (r = 0; r < l; r++) {
+                    a = 0,
+                      s = !1,
+                      e = _({}, t),
+                      null != t._useUTC && (e._useUTC = t._useUTC),
+                      e._f = t._f[r],
+                      Se(e),
+                      f(e) && (s = !0),
+                      a = (a += p(e).charsLeftOver) + 10 * p(e).unusedTokens.length,
+                      p(e).score = a,
+                      o ? a < i && (i = a, n = e) : (null == i || a < i || s) && (i = a, n = e, s && (o = !0));
+                  }
+                  u(t, n || e);
+                }(t)
+                : y
+                ? Se(t)
+                : o(y = (d = t)._i)
+                ? d._d = new Date(n.now())
+                : c(y)
+                ? d._d = new Date(y.valueOf())
+                : "string" == typeof y
+                ? (a = d,
+                  null !== (e = _e.exec(a._i))
+                    ? a._d = new Date(+e[1])
+                    : (ke(a),
+                      !1 === a._isValid
+                      && (delete a._isValid,
+                        Te(a),
+                        !1 === a._isValid
+                        && (delete a._isValid, a._strict ? a._isValid = !1 : n.createFromInputFallback(a)))))
+                : i(y)
+                ? (d._a = h(y.slice(0), function(t) {
+                  return parseInt(t, 10);
+                }),
+                  Ee(d))
+                : r(y)
+                ? (e = d)._d
+                  || (s = void 0 === (a = j(e._i)).day ? a.date : a.day,
+                    e._a = h([a.year, a.month, s, a.hour, a.minute, a.second, a.millisecond], function(t) {
+                      return t && parseInt(t, 10);
+                    }),
+                    Ee(e))
+                : l(y)
+                ? d._d = new Date(y)
+                : n.createFromInputFallback(d),
+                f(t) || (t._d = null),
+                t));
+      }
+      function De(t, e, n, a, o) {
+        var l = {};
+        return !0 !== e && !1 !== e || (a = e, e = void 0),
+          !0 !== n && !1 !== n || (a = n, n = void 0),
+          (r(t) && s(t) || i(t) && 0 === t.length) && (t = void 0),
+          l._isAMomentObject = !0,
+          l._useUTC = l._isUTC = o,
+          l._l = n,
+          l._i = t,
+          l._f = e,
+          l._strict = a,
+          (o = new x(pe(Ae(o = l))))._nextDay && (o.add(1, "d"), o._nextDay = void 0),
+          o;
+      }
+      function Le(t, e, n, i) {
+        return De(t, e, n, i, !1);
+      }
+      function Oe(t, e) {
+        var n, r;
+        if (!(e = 1 === e.length && i(e[0]) ? e[0] : e).length) return Le();
+        for (n = e[0], r = 1; r < e.length; ++r) e[r].isValid() && !e[r][t](n) || (n = e[r]);
+        return n;
+      }
+      n.createFromInputFallback = w(
+        "value provided is not in a recognized RFC2822 or ISO format. moment construction falls back to js Date(), which is not reliable across all browsers and versions. Non RFC2822/ISO date formats are discouraged. Please refer to http://momentjs.com/guides/#/warnings/js-date/ for more info.",
+        function(t) {
+          t._d = new Date(t._i + (t._useUTC ? " UTC" : ""));
+        },
+      ),
+        n.ISO_8601 = function() {},
+        n.RFC_2822 = function() {},
+        nt = w(
+          "moment().min is deprecated, use moment.max instead. http://momentjs.com/guides/#/warnings/min-max/",
+          function() {
+            var t = Le.apply(null, arguments);
+            return this.isValid() && t.isValid() ? t < this ? this : t : g();
+          },
+        ),
+        it = w(
+          "moment().max is deprecated, use moment.min instead. http://momentjs.com/guides/#/warnings/min-max/",
+          function() {
+            var t = Le.apply(null, arguments);
+            return this.isValid() && t.isValid() ? this < t ? this : t : g();
+          },
+        );
+      var Ne = ["year", "quarter", "month", "week", "day", "hour", "minute", "second", "millisecond"];
+      function Me(t) {
+        var e = (t = j(t)).year || 0,
+          n = t.quarter || 0,
+          i = t.month || 0,
+          r = t.week || t.isoWeek || 0,
+          s = t.day || 0,
+          o = t.hour || 0,
+          l = t.minute || 0,
+          c = t.second || 0,
+          h = t.millisecond || 0;
+        this._isValid = function(t) {
+          var e, n, i = !1, r = Ne.length;
+          for (e in t) if (a(t, e) && (-1 === _t.call(Ne, e) || null != t[e] && isNaN(t[e]))) return !1;
+          for (n = 0; n < r; ++n) {
+            if (t[Ne[n]]) {
+              if (i) return !1;
+              parseFloat(t[Ne[n]]) !== q(t[Ne[n]]) && (i = !0);
+            }
+          }
+          return !0;
+        }(t),
+          this._milliseconds = +h + 1e3 * c + 6e4 * l + 1e3 * o * 60 * 60,
+          this._days = +s + 7 * r,
+          this._months = +i + 3 * n + 12 * e,
+          this._data = {},
+          this._locale = de(),
+          this._bubble();
+      }
+      function Be(t) {
+        return t instanceof Me;
+      }
+      function Ie(t) {
+        return t < 0 ? -1 * Math.round(-1 * t) : Math.round(t);
+      }
+      function Fe(t, e) {
+        I(t, 0, 0, function() {
+          var t = this.utcOffset(), n = "+";
+          return t < 0 && (t = -t, n = "-"), n + L(~~(t / 60), 2) + e + L(~~t % 60, 2);
+        });
+      }
+      Fe("Z", ":"),
+        Fe("ZZ", ""),
+        dt("Z", ht),
+        dt("ZZ", ht),
+        mt(["Z", "ZZ"], function(t, e, n) {
+          n._useUTC = !0, n._tzm = $e(ht, t);
+        });
+      var Re = /([\+\-]|\d\d)/gi;
+      function $e(t, e) {
+        return null === (e = (e || "").match(t))
+          ? null
+          : 0 === (e = 60 * (t = ((e[e.length - 1] || []) + "").match(Re) || ["-", 0, 0])[1] + q(t[2]))
+          ? 0
+          : "+" === t[0]
+          ? e
+          : -e;
+      }
+      function Pe(t, e) {
+        var i;
+        return e._isUTC
+          ? (e = e.clone(),
+            i = (v(t) || c(t) ? t : Le(t)).valueOf() - e.valueOf(),
+            e._d.setTime(e._d.valueOf() + i),
+            n.updateOffset(e, !1),
+            e)
+          : Le(t).local();
+      }
+      function Ye(t) {
+        return -Math.round(t._d.getTimezoneOffset());
+      }
+      function je() {
+        return !!this.isValid() && this._isUTC && 0 === this._offset;
+      }
+      n.updateOffset = function() {};
+      var ze = /^(-|\+)?(?:(\d*)[. ])?(\d+):(\d+)(?::(\d+)(\.\d*)?)?$/,
+        Ue =
+          /^(-|\+)?P(?:([-+]?[0-9,.]*)Y)?(?:([-+]?[0-9,.]*)M)?(?:([-+]?[0-9,.]*)W)?(?:([-+]?[0-9,.]*)D)?(?:T(?:([-+]?[0-9,.]*)H)?(?:([-+]?[0-9,.]*)M)?(?:([-+]?[0-9,.]*)S)?)?$/;
+      function We(t, e) {
+        var n, i = t, r = null;
+        return Be(t)
+          ? i = { ms: t._milliseconds, d: t._days, M: t._months }
+          : l(t) || !isNaN(+t)
+          ? (i = {}, e ? i[e] = +t : i.milliseconds = +t)
+          : (r = ze.exec(t))
+          ? (n = "-" === r[1] ? -1 : 1,
+            i = {
+              y: 0,
+              d: q(r[kt]) * n,
+              h: q(r[wt]) * n,
+              m: q(r[Tt]) * n,
+              s: q(r[Ct]) * n,
+              ms: q(Ie(1e3 * r[Et])) * n,
+            })
+          : (r = Ue.exec(t))
+          ? (n = "-" === r[1] ? -1 : 1,
+            i = {
+              y: He(r[2], n),
+              M: He(r[3], n),
+              w: He(r[4], n),
+              d: He(r[5], n),
+              h: He(r[6], n),
+              m: He(r[7], n),
+              s: He(r[8], n),
+            })
+          : null == i
+          ? i = {}
+          : "object" == typeof i && ("from" in i || "to" in i) && (e = function(t, e) {
+            var n;
+            return t.isValid() && e.isValid()
+              ? (e = Pe(e, t),
+                t.isBefore(e) ? n = qe(t, e) : ((n = qe(e, t)).milliseconds = -n.milliseconds, n.months = -n.months),
+                n)
+              : { milliseconds: 0, months: 0 };
+          }(Le(i.from), Le(i.to)),
+            (i = {}).ms = e.milliseconds,
+            i.M = e.months),
+          r = new Me(i),
+          Be(t) && a(t, "_locale") && (r._locale = t._locale),
+          Be(t) && a(t, "_isValid") && (r._isValid = t._isValid),
+          r;
+      }
+      function He(t, e) {
+        return t = t && parseFloat(t.replace(",", ".")), (isNaN(t) ? 0 : t) * e;
+      }
+      function qe(t, e) {
+        var n = {};
+        return n.months = e.month() - t.month() + 12 * (e.year() - t.year()),
+          t.clone().add(n.months, "M").isAfter(e) && --n.months,
+          n.milliseconds = +e - +t.clone().add(n.months, "M"),
+          n;
+      }
+      function Ve(t, e) {
+        return function(n, i) {
+          var r;
+          return null === i || isNaN(+i)
+            || (C(
+              e,
+              "moment()." + e + "(period, number) is deprecated. Please use moment()." + e
+                + "(number, period). See http://momentjs.com/guides/#/warnings/add-inverted-param/ for more info.",
+            ),
+              r = n,
+              n = i,
+              i = r),
+            Ge(this, We(n, i), t),
+            this;
+        };
+      }
+      function Ge(t, e, i, r) {
+        var a = e._milliseconds, s = Ie(e._days);
+        e = Ie(e._months),
+          t.isValid()
+          && (r = null == r || r,
+            e && It(t, G(t, "Month") + e * i),
+            s && X(t, "Date", G(t, "Date") + s * i),
+            a && t._d.setTime(t._d.valueOf() + a * i),
+            r && n.updateOffset(t, s || e));
+      }
+      function Xe(t) {
+        return "string" == typeof t || t instanceof String;
+      }
+      function Ze(t) {
+        return v(t) || c(t) || Xe(t) || l(t) || function(t) {
+          var e = i(t), n = !1;
+          return e && (n = 0 === t.filter(function(e) {
+            return !l(e) && Xe(t);
+          }).length),
+            e && n;
+        }(t) || function(t) {
+          var e,
+            n,
+            i = r(t) && !s(t),
+            o = !1,
+            l = [
+              "years",
+              "year",
+              "y",
+              "months",
+              "month",
+              "M",
+              "days",
+              "day",
+              "d",
+              "dates",
+              "date",
+              "D",
+              "hours",
+              "hour",
+              "h",
+              "minutes",
+              "minute",
+              "m",
+              "seconds",
+              "second",
+              "s",
+              "milliseconds",
+              "millisecond",
+              "ms",
+            ],
+            c = l.length;
+          for (e = 0; e < c; e += 1) n = l[e], o = o || a(t, n);
+          return i && o;
+        }(t) || null == t;
+      }
+      function Qe(t, e) {
+        if (t.date() < e.date()) return -Qe(e, t);
+        var n = 12 * (e.year() - t.year()) + (e.month() - t.month()), i = t.clone().add(n, "months");
+        return -(n
+          + (e = e - i < 0
+            ? (e - i) / (i - t.clone().add(n - 1, "months"))
+            : (e - i) / (t.clone().add(1 + n, "months") - i))) || 0;
+      }
+      function Ke(t) {
+        return void 0 === t ? this._locale._abbr : (null != (t = de(t)) && (this._locale = t), this);
+      }
+      function Je() {
+        return this._locale;
+      }
+      We.fn = Me.prototype,
+        We.invalid = function() {
+          return We(NaN);
+        },
+        Lt = Ve(1, "add"),
+        Vt = Ve(-1, "subtract"),
+        n.defaultFormat = "YYYY-MM-DDTHH:mm:ssZ",
+        n.defaultFormatUtc = "YYYY-MM-DDTHH:mm:ss[Z]",
+        Xt = w(
+          "moment().lang() is deprecated. Instead, use moment().localeData() to get the language configuration. Use moment().locale() to change languages.",
+          function(t) {
+            return void 0 === t ? this.localeData() : this.locale(t);
+          },
+        );
+      var tn, en = 126227808e5;
+      function nn(t, e) {
+        return (t % e + e) % e;
+      }
+      function rn(t, e, n) {
+        return t < 100 && 0 <= t ? new Date(t + 400, e, n) - en : new Date(t, e, n).valueOf();
+      }
+      function an(t, e, n) {
+        return t < 100 && 0 <= t ? Date.UTC(t + 400, e, n) - en : Date.UTC(t, e, n);
+      }
+      function sn(t, e) {
+        return e.erasAbbrRegex(t);
+      }
+      function on() {
+        for (var t = [], e = [], n = [], i = [], r = this.eras(), a = 0, s = r.length; a < s; ++a) {
+          e.push(ft(r[a].name)),
+            t.push(ft(r[a].abbr)),
+            n.push(ft(r[a].narrow)),
+            i.push(ft(r[a].name)),
+            i.push(ft(r[a].abbr)),
+            i.push(ft(r[a].narrow));
+        }
+        this._erasRegex = new RegExp("^(" + i.join("|") + ")", "i"),
+          this._erasNameRegex = new RegExp("^(" + e.join("|") + ")", "i"),
+          this._erasAbbrRegex = new RegExp("^(" + t.join("|") + ")", "i"),
+          this._erasNarrowRegex = new RegExp("^(" + n.join("|") + ")", "i");
+      }
+      function ln(t, e) {
+        I(0, [t, t.length], 0, e);
+      }
+      function cn(t, e, n, i, r) {
+        var a;
+        return null == t ? Wt(this, i, r).year : (a = Ht(t, i, r),
+          function(t, e, n, i, r) {
+            return e = jt((t = Ut(t, e, n, i, r)).year, 0, t.dayOfYear),
+              this.year(e.getUTCFullYear()),
+              this.month(e.getUTCMonth()),
+              this.date(e.getUTCDate()),
+              this;
+          }.call(this, t, e = a < e ? a : e, n, i, r));
+      }
+      for (
+        I("N", 0, 0, "eraAbbr"),
+          I("NN", 0, 0, "eraAbbr"),
+          I("NNN", 0, 0, "eraAbbr"),
+          I("NNNN", 0, 0, "eraName"),
+          I("NNNNN", 0, 0, "eraNarrow"),
+          I("y", ["y", 1], "yo", "eraYear"),
+          I("y", ["yy", 2], 0, "eraYear"),
+          I("y", ["yyy", 3], 0, "eraYear"),
+          I("y", ["yyyy", 4], 0, "eraYear"),
+          dt("N", sn),
+          dt("NN", sn),
+          dt("NNN", sn),
+          dt("NNNN", function(t, e) {
+            return e.erasNameRegex(t);
+          }),
+          dt("NNNNN", function(t, e) {
+            return e.erasNarrowRegex(t);
+          }),
+          mt(["N", "NN", "NNN", "NNNN", "NNNNN"], function(t, e, n, i) {
+            (i = n._locale.erasParse(t, i, n._strict)) ? p(n).era = i : p(n).invalidEra = t;
+          }),
+          dt("y", ot),
+          dt("yy", ot),
+          dt("yyy", ot),
+          dt("yyyy", ot),
+          dt("yo", function(t, e) {
+            return e._eraYearOrdinalRegex || ot;
+          }),
+          mt(["y", "yy", "yyy", "yyyy"], xt),
+          mt(["yo"], function(t, e, n, i) {
+            var r;
+            n._locale._eraYearOrdinalRegex && (r = t.match(n._locale._eraYearOrdinalRegex)),
+              n._locale.eraYearOrdinalParse ? e[xt] = n._locale.eraYearOrdinalParse(t, r) : e[xt] = parseInt(t, 10);
+          }),
+          I(0, ["gg", 2], 0, function() {
+            return this.weekYear() % 100;
+          }),
+          I(0, ["GG", 2], 0, function() {
+            return this.isoWeekYear() % 100;
+          }),
+          ln("gggg", "weekYear"),
+          ln("ggggg", "weekYear"),
+          ln("GGGG", "isoWeekYear"),
+          ln("GGGGG", "isoWeekYear"),
+          P("weekYear", "gg"),
+          P("isoWeekYear", "GG"),
+          U("weekYear", 1),
+          U("isoWeekYear", 1),
+          dt("G", lt),
+          dt("g", lt),
+          dt("GG", et, Q),
+          dt("gg", et, Q),
+          dt("GGGG", at, J),
+          dt("gggg", at, J),
+          dt("GGGGG", st, tt),
+          dt("ggggg", st, tt),
+          bt(["gggg", "ggggg", "GGGG", "GGGGG"], function(t, e, n, i) {
+            e[i.substr(0, 2)] = q(t);
+          }),
+          bt(["gg", "GG"], function(t, e, i, r) {
+            e[r] = n.parseTwoDigitYear(t);
+          }),
+          I("Q", 0, "Qo", "quarter"),
+          P("quarter", "Q"),
+          U("quarter", 7),
+          dt("Q", Z),
+          mt("Q", function(t, e) {
+            e[vt] = 3 * (q(t) - 1);
+          }),
+          I("D", ["DD", 2], "Do", "date"),
+          P("date", "D"),
+          U("date", 9),
+          dt("D", et),
+          dt("DD", et, Q),
+          dt("Do", function(t, e) {
+            return t ? e._dayOfMonthOrdinalParse || e._ordinalParse : e._dayOfMonthOrdinalParseLenient;
+          }),
+          mt(["D", "DD"], kt),
+          mt("Do", function(t, e) {
+            e[kt] = q(t.match(et)[0]);
+          }),
+          at = V("Date", !0),
+          I("DDD", ["DDDD", 3], "DDDo", "dayOfYear"),
+          P("dayOfYear", "DDD"),
+          U("dayOfYear", 4),
+          dt("DDD", rt),
+          dt("DDDD", K),
+          mt(["DDD", "DDDD"], function(t, e, n) {
+            n._dayOfYear = q(t);
+          }),
+          I("m", ["mm", 2], 0, "minute"),
+          P("minute", "m"),
+          U("minute", 14),
+          dt("m", et),
+          dt("mm", et, Q),
+          mt(["m", "mm"], Tt),
+          J = V("Minutes", !1),
+          I("s", ["ss", 2], 0, "second"),
+          P("second", "s"),
+          U("second", 15),
+          dt("s", et),
+          dt("ss", et, Q),
+          mt(["s", "ss"], Ct),
+          st = V("Seconds", !1),
+          I("S", 0, 0, function() {
+            return ~~(this.millisecond() / 100);
+          }),
+          I(0, ["SS", 2], 0, function() {
+            return ~~(this.millisecond() / 10);
+          }),
+          I(0, ["SSS", 3], 0, "millisecond"),
+          I(0, ["SSSS", 4], 0, function() {
+            return 10 * this.millisecond();
+          }),
+          I(0, ["SSSSS", 5], 0, function() {
+            return 100 * this.millisecond();
+          }),
+          I(0, ["SSSSSS", 6], 0, function() {
+            return 1e3 * this.millisecond();
+          }),
+          I(0, ["SSSSSSS", 7], 0, function() {
+            return 1e4 * this.millisecond();
+          }),
+          I(0, ["SSSSSSSS", 8], 0, function() {
+            return 1e5 * this.millisecond();
+          }),
+          I(0, ["SSSSSSSSS", 9], 0, function() {
+            return 1e6 * this.millisecond();
+          }),
+          P("millisecond", "ms"),
+          U("millisecond", 16),
+          dt("S", rt, Z),
+          dt("SS", rt, Q),
+          dt("SSS", rt, K),
+          tn = "SSSS";
+        tn.length <= 9;
+        tn += "S"
+      ) dt(tn, ot);
+      function hn(t, e) {
+        e[Et] = q(1e3 * ("0." + t));
+      }
+      for (tn = "S"; tn.length <= 9; tn += "S") mt(tn, hn);
+      function un(t) {
+        return t;
+      }
+      function dn(t, e, n, i) {
+        var r = de();
+        return i = d().set(i, e), r[n](i, t);
+      }
+      function pn(t, e, n) {
+        if (l(t) && (e = t, t = void 0), t = t || "", null != e) return dn(t, e, n, "month");
+        for (var i = [], r = 0; r < 12; r++) i[r] = dn(t, r, n, "month");
+        return i;
+      }
+      function fn(t, e, n, i) {
+        "boolean" == typeof t ? l(e) && (n = e, e = void 0) : (e = t, t = !1, l(n = e) && (n = e, e = void 0)),
+          e = e || "";
+        var r, a = de(), s = t ? a._week.dow : 0, o = [];
+        if (null != n) return dn(e, (n + s) % 7, i, "day");
+        for (r = 0; r < 7; r++) o[r] = dn(e, (r + s) % 7, i, "day");
+        return o;
+      }
+      tt = V("Milliseconds", !1),
+        I("z", 0, 0, "zoneAbbr"),
+        I("zz", 0, 0, "zoneName"),
+        (Z = x.prototype).add = Lt,
+        Z.calendar = function(t, e) {
+          1 === arguments.length && (arguments[0]
+            ? Ze(arguments[0]) ? (t = arguments[0], e = void 0) : function(t) {
+              for (
+                var e = r(t) && !s(t),
+                  n = !1,
+                  i = ["sameDay", "nextDay", "lastDay", "nextWeek", "lastWeek", "sameElse"],
+                  o = 0;
+                o < i.length;
+                o += 1
+              ) n = n || a(t, i[o]);
+              return e && n;
+            }(arguments[0]) && (e = arguments[0], t = void 0)
+            : e = t = void 0);
+          var i = Pe(t = t || Le(), this).startOf("day");
+          return i = n.calendarFormat(this, i) || "sameElse",
+            e = e && (E(e[i]) ? e[i].call(this, t) : e[i]),
+            this.format(e || this.localeData().calendar(i, this, Le(t)));
+        },
+        Z.clone = function() {
+          return new x(this);
+        },
+        Z.diff = function(t, e, n) {
+          var i, r, a;
+          if (!this.isValid()) return NaN;
+          if (!(i = Pe(t, this)).isValid()) return NaN;
+          switch (r = 6e4 * (i.utcOffset() - this.utcOffset()), e = Y(e)) {
+            case "year":
+              a = Qe(this, i) / 12;
+              break;
+            case "month":
+              a = Qe(this, i);
+              break;
+            case "quarter":
+              a = Qe(this, i) / 3;
+              break;
+            case "second":
+              a = (this - i) / 1e3;
+              break;
+            case "minute":
+              a = (this - i) / 6e4;
+              break;
+            case "hour":
+              a = (this - i) / 36e5;
+              break;
+            case "day":
+              a = (this - i - r) / 864e5;
+              break;
+            case "week":
+              a = (this - i - r) / 6048e5;
+              break;
+            default:
+              a = this - i;
+          }
+          return n ? a : H(a);
+        },
+        Z.endOf = function(t) {
+          var e, i;
+          if (void 0 === (t = Y(t)) || "millisecond" === t || !this.isValid()) return this;
+          switch (i = this._isUTC ? an : rn, t) {
+            case "year":
+              e = i(this.year() + 1, 0, 1) - 1;
+              break;
+            case "quarter":
+              e = i(this.year(), this.month() - this.month() % 3 + 3, 1) - 1;
+              break;
+            case "month":
+              e = i(this.year(), this.month() + 1, 1) - 1;
+              break;
+            case "week":
+              e = i(this.year(), this.month(), this.date() - this.weekday() + 7) - 1;
+              break;
+            case "isoWeek":
+              e = i(this.year(), this.month(), this.date() - (this.isoWeekday() - 1) + 7) - 1;
+              break;
+            case "day":
+            case "date":
+              e = i(this.year(), this.month(), this.date() + 1) - 1;
+              break;
+            case "hour":
+              e = this._d.valueOf(), e += 36e5 - nn(e + (this._isUTC ? 0 : 6e4 * this.utcOffset()), 36e5) - 1;
+              break;
+            case "minute":
+              e = this._d.valueOf(), e += 6e4 - nn(e, 6e4) - 1;
+              break;
+            case "second":
+              e = this._d.valueOf(), e += 1e3 - nn(e, 1e3) - 1;
+          }
+          return this._d.setTime(e), n.updateOffset(this, !0), this;
+        },
+        Z.format = function(t) {
+          return t = F(this, t = t || (this.isUtc() ? n.defaultFormatUtc : n.defaultFormat)),
+            this.localeData().postformat(t);
+        },
+        Z.from = function(t, e) {
+          return this.isValid() && (v(t) && t.isValid() || Le(t).isValid())
+            ? We({ to: this, from: t }).locale(this.locale()).humanize(!e)
+            : this.localeData().invalidDate();
+        },
+        Z.fromNow = function(t) {
+          return this.from(Le(), t);
+        },
+        Z.to = function(t, e) {
+          return this.isValid() && (v(t) && t.isValid() || Le(t).isValid())
+            ? We({ from: this, to: t }).locale(this.locale()).humanize(!e)
+            : this.localeData().invalidDate();
+        },
+        Z.toNow = function(t) {
+          return this.to(Le(), t);
+        },
+        Z.get = function(t) {
+          return E(this[t = Y(t)]) ? this[t]() : this;
+        },
+        Z.invalidAt = function() {
+          return p(this).overflow;
+        },
+        Z.isAfter = function(t, e) {
+          return t = v(t) ? t : Le(t),
+            !(!this.isValid() || !t.isValid())
+            && ("millisecond" === (e = Y(e) || "millisecond")
+              ? this.valueOf() > t.valueOf()
+              : t.valueOf() < this.clone().startOf(e).valueOf());
+        },
+        Z.isBefore = function(t, e) {
+          return t = v(t) ? t : Le(t),
+            !(!this.isValid() || !t.isValid())
+            && ("millisecond" === (e = Y(e) || "millisecond")
+              ? this.valueOf() < t.valueOf()
+              : this.clone().endOf(e).valueOf() < t.valueOf());
+        },
+        Z.isBetween = function(t, e, n, i) {
+          return t = v(t) ? t : Le(t),
+            e = v(e) ? e : Le(e),
+            !!(this.isValid() && t.isValid() && e.isValid())
+            && ("(" === (i = i || "()")[0] ? this.isAfter(t, n) : !this.isBefore(t, n))
+            && (")" === i[1] ? this.isBefore(e, n) : !this.isAfter(e, n));
+        },
+        Z.isSame = function(t, e) {
+          return t = v(t) ? t : Le(t),
+            !(!this.isValid() || !t.isValid())
+            && ("millisecond" === (e = Y(e) || "millisecond")
+              ? this.valueOf() === t.valueOf()
+              : (t = t.valueOf(), this.clone().startOf(e).valueOf() <= t && t <= this.clone().endOf(e).valueOf()));
+        },
+        Z.isSameOrAfter = function(t, e) {
+          return this.isSame(t, e) || this.isAfter(t, e);
+        },
+        Z.isSameOrBefore = function(t, e) {
+          return this.isSame(t, e) || this.isBefore(t, e);
+        },
+        Z.isValid = function() {
+          return f(this);
+        },
+        Z.lang = Xt,
+        Z.locale = Ke,
+        Z.localeData = Je,
+        Z.max = it,
+        Z.min = nt,
+        Z.parsingFlags = function() {
+          return u({}, p(this));
+        },
+        Z.set = function(t, e) {
+          if ("object" == typeof t) {
+            for (
+              var n = function(t) {
+                  var e, n = [];
+                  for (e in t) a(t, e) && n.push({ unit: e, priority: z[e] });
+                  return n.sort(function(t, e) {
+                    return t.priority - e.priority;
+                  }),
+                    n;
+                }(t = j(t)),
+                i = n.length,
+                r = 0;
+              r < i;
+              r++
+            ) this[n[r].unit](t[n[r].unit]);
+          } else if (E(this[t = Y(t)])) return this[t](e);
+          return this;
+        },
+        Z.startOf = function(t) {
+          var e, i;
+          if (void 0 === (t = Y(t)) || "millisecond" === t || !this.isValid()) return this;
+          switch (i = this._isUTC ? an : rn, t) {
+            case "year":
+              e = i(this.year(), 0, 1);
+              break;
+            case "quarter":
+              e = i(this.year(), this.month() - this.month() % 3, 1);
+              break;
+            case "month":
+              e = i(this.year(), this.month(), 1);
+              break;
+            case "week":
+              e = i(this.year(), this.month(), this.date() - this.weekday());
+              break;
+            case "isoWeek":
+              e = i(this.year(), this.month(), this.date() - (this.isoWeekday() - 1));
+              break;
+            case "day":
+            case "date":
+              e = i(this.year(), this.month(), this.date());
+              break;
+            case "hour":
+              e = this._d.valueOf(), e -= nn(e + (this._isUTC ? 0 : 6e4 * this.utcOffset()), 36e5);
+              break;
+            case "minute":
+              e = this._d.valueOf(), e -= nn(e, 6e4);
+              break;
+            case "second":
+              e = this._d.valueOf(), e -= nn(e, 1e3);
+          }
+          return this._d.setTime(e), n.updateOffset(this, !0), this;
+        },
+        Z.subtract = Vt,
+        Z.toArray = function() {
+          var t = this;
+          return [t.year(), t.month(), t.date(), t.hour(), t.minute(), t.second(), t.millisecond()];
+        },
+        Z.toObject = function() {
+          var t = this;
+          return {
+            years: t.year(),
+            months: t.month(),
+            date: t.date(),
+            hours: t.hours(),
+            minutes: t.minutes(),
+            seconds: t.seconds(),
+            milliseconds: t.milliseconds(),
+          };
+        },
+        Z.toDate = function() {
+          return new Date(this.valueOf());
+        },
+        Z.toISOString = function(t) {
+          if (!this.isValid()) return null;
+          var e = (t = !0 !== t) ? this.clone().utc() : this;
+          return e.year() < 0 || 9999 < e.year()
+            ? F(e, t ? "YYYYYY-MM-DD[T]HH:mm:ss.SSS[Z]" : "YYYYYY-MM-DD[T]HH:mm:ss.SSSZ")
+            : E(Date.prototype.toISOString)
+            ? t
+              ? this.toDate().toISOString()
+              : new Date(this.valueOf() + 60 * this.utcOffset() * 1e3).toISOString().replace("Z", F(e, "Z"))
+            : F(e, t ? "YYYY-MM-DD[T]HH:mm:ss.SSS[Z]" : "YYYY-MM-DD[T]HH:mm:ss.SSSZ");
+        },
+        Z.inspect = function() {
+          if (!this.isValid()) return "moment.invalid(/* " + this._i + " */)";
+          var t, e = "moment", n = "";
+          return this.isLocal() || (e = 0 === this.utcOffset() ? "moment.utc" : "moment.parseZone", n = "Z"),
+            e = "[" + e + "(\"]",
+            t = 0 <= this.year() && this.year() <= 9999 ? "YYYY" : "YYYYYY",
+            this.format(e + t + "-MM-DD[T]HH:mm:ss.SSS" + n + "[\")]");
+        },
+        "undefined" != typeof Symbol && null != Symbol.for
+        && (Z[Symbol.for("nodejs.util.inspect.custom")] = function() {
+          return "Moment<" + this.format() + ">";
+        }),
+        Z.toJSON = function() {
+          return this.isValid() ? this.toISOString() : null;
+        },
+        Z.toString = function() {
+          return this.clone().locale("en").format("ddd MMM DD YYYY HH:mm:ss [GMT]ZZ");
+        },
+        Z.unix = function() {
+          return Math.floor(this.valueOf() / 1e3);
+        },
+        Z.valueOf = function() {
+          return this._d.valueOf() - 6e4 * (this._offset || 0);
+        },
+        Z.creationData = function() {
+          return { input: this._i, format: this._f, locale: this._locale, isUTC: this._isUTC, strict: this._strict };
+        },
+        Z.eraName = function() {
+          for (var t, e = this.localeData().eras(), n = 0, i = e.length; n < i; ++n) {
+            if (t = this.clone().startOf("day").valueOf(), e[n].since <= t && t <= e[n].until) return e[n].name;
+            if (e[n].until <= t && t <= e[n].since) return e[n].name;
+          }
+          return "";
+        },
+        Z.eraNarrow = function() {
+          for (var t, e = this.localeData().eras(), n = 0, i = e.length; n < i; ++n) {
+            if (t = this.clone().startOf("day").valueOf(), e[n].since <= t && t <= e[n].until) return e[n].narrow;
+            if (e[n].until <= t && t <= e[n].since) return e[n].narrow;
+          }
+          return "";
+        },
+        Z.eraAbbr = function() {
+          for (var t, e = this.localeData().eras(), n = 0, i = e.length; n < i; ++n) {
+            if (t = this.clone().startOf("day").valueOf(), e[n].since <= t && t <= e[n].until) return e[n].abbr;
+            if (e[n].until <= t && t <= e[n].since) return e[n].abbr;
+          }
+          return "";
+        },
+        Z.eraYear = function() {
+          for (var t, e, i = this.localeData().eras(), r = 0, a = i.length; r < a; ++r) {
+            if (
+              t = i[r].since <= i[r].until ? 1 : -1,
+                e = this.clone().startOf("day").valueOf(),
+                i[r].since <= e && e <= i[r].until || i[r].until <= e && e <= i[r].since
+            ) return (this.year() - n(i[r].since).year()) * t + i[r].offset;
+          }
+          return this.year();
+        },
+        Z.year = Pt,
+        Z.isLeapYear = function() {
+          return W(this.year());
+        },
+        Z.weekYear = function(t) {
+          return cn.call(
+            this,
+            t,
+            this.week(),
+            this.weekday(),
+            this.localeData()._week.dow,
+            this.localeData()._week.doy,
+          );
+        },
+        Z.isoWeekYear = function(t) {
+          return cn.call(this, t, this.isoWeek(), this.isoWeekday(), 1, 4);
+        },
+        Z.quarter = Z.quarters = function(t) {
+          return null == t ? Math.ceil((this.month() + 1) / 3) : this.month(3 * (t - 1) + this.month() % 3);
+        },
+        Z.month = Ft,
+        Z.daysInMonth = function() {
+          return Dt(this.year(), this.month());
+        },
+        Z.week = Z.weeks = function(t) {
+          var e = this.localeData().week(this);
+          return null == t ? e : this.add(7 * (t - e), "d");
+        },
+        Z.isoWeek = Z.isoWeeks = function(t) {
+          var e = Wt(this, 1, 4).week;
+          return null == t ? e : this.add(7 * (t - e), "d");
+        },
+        Z.weeksInYear = function() {
+          var t = this.localeData()._week;
+          return Ht(this.year(), t.dow, t.doy);
+        },
+        Z.weeksInWeekYear = function() {
+          var t = this.localeData()._week;
+          return Ht(this.weekYear(), t.dow, t.doy);
+        },
+        Z.isoWeeksInYear = function() {
+          return Ht(this.year(), 1, 4);
+        },
+        Z.isoWeeksInISOWeekYear = function() {
+          return Ht(this.isoWeekYear(), 1, 4);
+        },
+        Z.date = at,
+        Z.day = Z.days = function(t) {
+          if (!this.isValid()) return null != t ? this : NaN;
+          var e, n, i = this._isUTC ? this._d.getUTCDay() : this._d.getDay();
+          return null != t
+            ? (e = t,
+              n = this.localeData(),
+              t = "string" != typeof e
+                ? e
+                : isNaN(e)
+                ? "number" == typeof (e = n.weekdaysParse(e)) ? e : null
+                : parseInt(e, 10),
+              this.add(t - i, "d"))
+            : i;
+        },
+        Z.weekday = function(t) {
+          if (!this.isValid()) return null != t ? this : NaN;
+          var e = (this.day() + 7 - this.localeData()._week.dow) % 7;
+          return null == t ? e : this.add(t - e, "d");
+        },
+        Z.isoWeekday = function(t) {
+          return this.isValid()
+            ? null != t
+              ? (e = t,
+                n = this.localeData(),
+                n = "string" == typeof e ? n.weekdaysParse(e) % 7 || 7 : isNaN(e) ? null : e,
+                this.day(this.day() % 7 ? n : n - 7))
+              : this.day() || 7
+            : null != t
+            ? this
+            : NaN;
+          var e, n;
+        },
+        Z.dayOfYear = function(t) {
+          var e = Math.round((this.clone().startOf("day") - this.clone().startOf("year")) / 864e5) + 1;
+          return null == t ? e : this.add(t - e, "d");
+        },
+        Z.hour = Z.hours = ut,
+        Z.minute = Z.minutes = J,
+        Z.second = Z.seconds = st,
+        Z.millisecond = Z.milliseconds = tt,
+        Z.utcOffset = function(t, e, i) {
+          var r, a = this._offset || 0;
+          if (!this.isValid()) return null != t ? this : NaN;
+          if (null == t) return this._isUTC ? a : Ye(this);
+          if ("string" == typeof t) {
+            if (null === (t = $e(ht, t))) return this;
+            else Math.abs(t) < 16 && !i && (t *= 60);
+          }
+          return !this._isUTC && e && (r = Ye(this)),
+            this._offset = t,
+            this._isUTC = !0,
+            null != r && this.add(r, "m"),
+            a !== t
+            && (!e || this._changeInProgress
+              ? Ge(this, We(t - a, "m"), 1, !1)
+              : this._changeInProgress
+                || (this._changeInProgress = !0, n.updateOffset(this, !0), this._changeInProgress = null)),
+            this;
+        },
+        Z.utc = function(t) {
+          return this.utcOffset(0, t);
+        },
+        Z.local = function(t) {
+          return this._isUTC && (this.utcOffset(0, t), this._isUTC = !1, t && this.subtract(Ye(this), "m")), this;
+        },
+        Z.parseZone = function() {
+          var t;
+          return null != this._tzm
+            ? this.utcOffset(this._tzm, !1, !0)
+            : "string" == typeof this._i && (null != (t = $e(ct, this._i)) ? this.utcOffset(t) : this.utcOffset(0, !0)),
+            this;
+        },
+        Z.hasAlignedHourOffset = function(t) {
+          return !!this.isValid() && (t = t ? Le(t).utcOffset() : 0, (this.utcOffset() - t) % 60 == 0);
+        },
+        Z.isDST = function() {
+          return this.utcOffset() > this.clone().month(0).utcOffset()
+            || this.utcOffset() > this.clone().month(5).utcOffset();
+        },
+        Z.isLocal = function() {
+          return !!this.isValid() && !this._isUTC;
+        },
+        Z.isUtcOffset = function() {
+          return !!this.isValid() && this._isUTC;
+        },
+        Z.isUtc = je,
+        Z.isUTC = je,
+        Z.zoneAbbr = function() {
+          return this._isUTC ? "UTC" : "";
+        },
+        Z.zoneName = function() {
+          return this._isUTC ? "Coordinated Universal Time" : "";
+        },
+        Z.dates = w("dates accessor is deprecated. Use date instead.", at),
+        Z.months = w("months accessor is deprecated. Use month instead", Ft),
+        Z.years = w("years accessor is deprecated. Use year instead", Pt),
+        Z.zone = w(
+          "moment().zone is deprecated, use moment().utcOffset instead. http://momentjs.com/guides/#/warnings/zone/",
+          function(t, e) {
+            return null != t ? (this.utcOffset(t = "string" != typeof t ? -t : t, e), this) : -this.utcOffset();
+          },
+        ),
+        Z.isDSTShifted = w(
+          "isDSTShifted is deprecated. See http://momentjs.com/guides/#/warnings/dst-shifted/ for more information",
+          function() {
+            if (!o(this._isDSTShifted)) return this._isDSTShifted;
+            var t, e = {};
+            return _(e, this),
+              (e = Ae(e))._a
+                ? (t = (e._isUTC ? d : Le)(e._a),
+                  this._isDSTShifted = this.isValid() && 0 < function(t, e, n) {
+                        for (
+                          var i = Math.min(t.length, e.length), r = Math.abs(t.length - e.length), a = 0, s = 0;
+                          s < i;
+                          s++
+                        ) (n && t[s] !== e[s] || !n && q(t[s]) !== q(e[s])) && a++;
+                        return a + r;
+                      }(e._a, t.toArray()))
+                : this._isDSTShifted = !1,
+              this._isDSTShifted;
+          },
+        ),
+        (Q = A.prototype).calendar = function(t, e, n) {
+          return E(t = this._calendar[t] || this._calendar.sameElse) ? t.call(e, n) : t;
+        },
+        Q.longDateFormat = function(t) {
+          var e = this._longDateFormat[t], n = this._longDateFormat[t.toUpperCase()];
+          return e || !n ? e : (this._longDateFormat[t] = n.match(O).map(function(t) {
+            return "MMMM" === t || "MM" === t || "DD" === t || "dddd" === t ? t.slice(1) : t;
+          }).join(""),
+            this._longDateFormat[t]);
+        },
+        Q.invalidDate = function() {
+          return this._invalidDate;
+        },
+        Q.ordinal = function(t) {
+          return this._ordinal.replace("%d", t);
+        },
+        Q.preparse = un,
+        Q.postformat = un,
+        Q.relativeTime = function(t, e, n, i) {
+          var r = this._relativeTime[n];
+          return E(r) ? r(t, e, n, i) : r.replace(/%d/i, t);
+        },
+        Q.pastFuture = function(t, e) {
+          return E(t = this._relativeTime[0 < t ? "future" : "past"]) ? t(e) : t.replace(/%s/i, e);
+        },
+        Q.set = function(t) {
+          var e, n;
+          for (n in t) a(t, n) && (E(e = t[n]) ? this[n] = e : this["_" + n] = e);
+          this._config = t,
+            this._dayOfMonthOrdinalParseLenient = new RegExp(
+              (this._dayOfMonthOrdinalParse.source || this._ordinalParse.source) + "|" + /\d{1,2}/.source,
+            );
+        },
+        Q.eras = function(t, e) {
+          for (var i, r = this._eras || de("en")._eras, a = 0, s = r.length; a < s; ++a) {
+            switch (
+              "string" == typeof r[a].since && (i = n(r[a].since).startOf("day"), r[a].since = i.valueOf()),
+                typeof r[a].until
+            ) {
+              case "undefined":
+                r[a].until = 1 / 0;
+                break;
+              case "string":
+                i = n(r[a].until).startOf("day").valueOf(), r[a].until = i.valueOf();
+            }
+          }
+          return r;
+        },
+        Q.erasParse = function(t, e, n) {
+          var i, r, a, s, o, l = this.eras();
+          for (t = t.toUpperCase(), i = 0, r = l.length; i < r; ++i) {
+            if (a = l[i].name.toUpperCase(), s = l[i].abbr.toUpperCase(), o = l[i].narrow.toUpperCase(), n) {
+              switch (e) {
+                case "N":
+                case "NN":
+                case "NNN":
+                  if (s === t) return l[i];
+                  break;
+                case "NNNN":
+                  if (a === t) return l[i];
+                  break;
+                case "NNNNN":
+                  if (o === t) return l[i];
+              }
+            } else if (0 <= [a, s, o].indexOf(t)) return l[i];
+          }
+        },
+        Q.erasConvertYear = function(t, e) {
+          var i = t.since <= t.until ? 1 : -1;
+          return void 0 === e ? n(t.since).year() : n(t.since).year() + (e - t.offset) * i;
+        },
+        Q.erasAbbrRegex = function(t) {
+          return a(this, "_erasAbbrRegex") || on.call(this), t ? this._erasAbbrRegex : this._erasRegex;
+        },
+        Q.erasNameRegex = function(t) {
+          return a(this, "_erasNameRegex") || on.call(this), t ? this._erasNameRegex : this._erasRegex;
+        },
+        Q.erasNarrowRegex = function(t) {
+          return a(this, "_erasNarrowRegex") || on.call(this), t ? this._erasNarrowRegex : this._erasRegex;
+        },
+        Q.months = function(t, e) {
+          return t
+            ? (i(this._months)
+              ? this._months
+              : this._months[(this._months.isFormat || Nt).test(e) ? "format" : "standalone"])[t.month()]
+            : i(this._months)
+            ? this._months
+            : this._months.standalone;
+        },
+        Q.monthsShort = function(t, e) {
+          return t
+            ? (i(this._monthsShort) ? this._monthsShort : this._monthsShort[Nt.test(e) ? "format" : "standalone"])[
+              t.month()
+            ]
+            : i(this._monthsShort)
+            ? this._monthsShort
+            : this._monthsShort.standalone;
+        },
+        Q.monthsParse = function(t, e, n) {
+          var i, r;
+          if (this._monthsParseExact) {
+            return function(t, e, n) {
+              var i, r, a;
+              if (t = t.toLocaleLowerCase(), !this._monthsParse) {
+                for (
+                  this._monthsParse = [], this._longMonthsParse = [], this._shortMonthsParse = [], i = 0;
+                  i < 12;
+                  ++i
+                ) {
+                  a = d([2e3, i]),
+                    this._shortMonthsParse[i] = this.monthsShort(a, "").toLocaleLowerCase(),
+                    this._longMonthsParse[i] = this.months(a, "").toLocaleLowerCase();
+                }
+              }
+              return n
+                ? "MMM" === e
+                  ? -1 !== (r = _t.call(this._shortMonthsParse, t)) ? r : null
+                  : -1 !== (r = _t.call(this._longMonthsParse, t))
+                  ? r
+                  : null
+                : "MMM" === e
+                ? -1 !== (r = _t.call(this._shortMonthsParse, t)) || -1 !== (r = _t.call(this._longMonthsParse, t))
+                  ? r
+                  : null
+                : -1 !== (r = _t.call(this._longMonthsParse, t)) || -1 !== (r = _t.call(this._shortMonthsParse, t))
+                ? r
+                : null;
+            }.call(this, t, e, n);
+          }
+          for (
+            this._monthsParse || (this._monthsParse = [], this._longMonthsParse = [], this._shortMonthsParse = []),
+              i = 0;
+            i < 12;
+            i++
+          ) {
+            if (
+              r = d([2e3, i]),
+                n && !this._longMonthsParse[i]
+                && (this._longMonthsParse[i] = new RegExp("^" + this.months(r, "").replace(".", "") + "$", "i"),
+                  this._shortMonthsParse[i] = new RegExp("^" + this.monthsShort(r, "").replace(".", "") + "$", "i")),
+                n || this._monthsParse[i]
+                || (r = "^" + this.months(r, "") + "|^" + this.monthsShort(r, ""),
+                  this._monthsParse[i] = new RegExp(r.replace(".", ""), "i")),
+                n && "MMMM" === e && this._longMonthsParse[i].test(t)
+            ) return i;
+            if (n && "MMM" === e && this._shortMonthsParse[i].test(t)) return i;
+            if (!n && this._monthsParse[i].test(t)) return i;
+          }
+        },
+        Q.monthsRegex = function(t) {
+          return this._monthsParseExact
+            ? (a(this, "_monthsRegex") || Rt.call(this), t ? this._monthsStrictRegex : this._monthsRegex)
+            : (a(this, "_monthsRegex") || (this._monthsRegex = Bt),
+              this._monthsStrictRegex && t ? this._monthsStrictRegex : this._monthsRegex);
+        },
+        Q.monthsShortRegex = function(t) {
+          return this._monthsParseExact
+            ? (a(this, "_monthsRegex") || Rt.call(this), t ? this._monthsShortStrictRegex : this._monthsShortRegex)
+            : (a(this, "_monthsShortRegex") || (this._monthsShortRegex = Mt),
+              this._monthsShortStrictRegex && t ? this._monthsShortStrictRegex : this._monthsShortRegex);
+        },
+        Q.week = function(t) {
+          return Wt(t, this._week.dow, this._week.doy).week;
+        },
+        Q.firstDayOfYear = function() {
+          return this._week.doy;
+        },
+        Q.firstDayOfWeek = function() {
+          return this._week.dow;
+        },
+        Q.weekdays = function(t, e) {
+          return e = i(this._weekdays)
+            ? this._weekdays
+            : this._weekdays[t && !0 !== t && this._weekdays.isFormat.test(e) ? "format" : "standalone"],
+            !0 === t ? qt(e, this._week.dow) : t ? e[t.day()] : e;
+        },
+        Q.weekdaysMin = function(t) {
+          return !0 === t ? qt(this._weekdaysMin, this._week.dow) : t ? this._weekdaysMin[t.day()] : this._weekdaysMin;
+        },
+        Q.weekdaysShort = function(t) {
+          return !0 === t
+            ? qt(this._weekdaysShort, this._week.dow)
+            : t
+            ? this._weekdaysShort[t.day()]
+            : this._weekdaysShort;
+        },
+        Q.weekdaysParse = function(t, e, n) {
+          var i, r;
+          if (this._weekdaysParseExact) {
+            return function(t, e, n) {
+              var i, r, a;
+              if (t = t.toLocaleLowerCase(), !this._weekdaysParse) {
+                for (
+                  this._weekdaysParse = [], this._shortWeekdaysParse = [], this._minWeekdaysParse = [], i = 0;
+                  i < 7;
+                  ++i
+                ) {
+                  a = d([2e3, 1]).day(i),
+                    this._minWeekdaysParse[i] = this.weekdaysMin(a, "").toLocaleLowerCase(),
+                    this._shortWeekdaysParse[i] = this.weekdaysShort(a, "").toLocaleLowerCase(),
+                    this._weekdaysParse[i] = this.weekdays(a, "").toLocaleLowerCase();
+                }
+              }
+              return n
+                ? "dddd" === e
+                  ? -1 !== (r = _t.call(this._weekdaysParse, t)) ? r : null
+                  : "ddd" === e
+                  ? -1 !== (r = _t.call(this._shortWeekdaysParse, t)) ? r : null
+                  : -1 !== (r = _t.call(this._minWeekdaysParse, t))
+                  ? r
+                  : null
+                : "dddd" === e
+                ? -1 !== (r = _t.call(this._weekdaysParse, t)) || -1 !== (r = _t.call(this._shortWeekdaysParse, t))
+                    || -1 !== (r = _t.call(this._minWeekdaysParse, t))
+                  ? r
+                  : null
+                : "ddd" === e
+                ? -1 !== (r = _t.call(this._shortWeekdaysParse, t)) || -1 !== (r = _t.call(this._weekdaysParse, t))
+                    || -1 !== (r = _t.call(this._minWeekdaysParse, t))
+                  ? r
+                  : null
+                : -1 !== (r = _t.call(this._minWeekdaysParse, t)) || -1 !== (r = _t.call(this._weekdaysParse, t))
+                    || -1 !== (r = _t.call(this._shortWeekdaysParse, t))
+                ? r
+                : null;
+            }.call(this, t, e, n);
+          }
+          for (
+            this._weekdaysParse
+            || (this._weekdaysParse = [],
+              this._minWeekdaysParse = [],
+              this._shortWeekdaysParse = [],
+              this._fullWeekdaysParse = []), i = 0;
+            i < 7;
+            i++
+          ) {
+            if (
+              r = d([2e3, 1]).day(i),
+                n && !this._fullWeekdaysParse[i]
+                && (this._fullWeekdaysParse[i] = new RegExp("^" + this.weekdays(r, "").replace(".", "\\.?") + "$", "i"),
+                  this._shortWeekdaysParse[i] = new RegExp(
+                    "^" + this.weekdaysShort(r, "").replace(".", "\\.?") + "$",
+                    "i",
+                  ),
+                  this._minWeekdaysParse[i] = new RegExp(
+                    "^" + this.weekdaysMin(r, "").replace(".", "\\.?") + "$",
+                    "i",
+                  )),
+                this._weekdaysParse[i]
+                || (r = "^" + this.weekdays(r, "") + "|^" + this.weekdaysShort(r, "") + "|^" + this.weekdaysMin(r, ""),
+                  this._weekdaysParse[i] = new RegExp(r.replace(".", ""), "i")),
+                n && "dddd" === e && this._fullWeekdaysParse[i].test(t)
+            ) return i;
+            if (n && "ddd" === e && this._shortWeekdaysParse[i].test(t)) return i;
+            if (n && "dd" === e && this._minWeekdaysParse[i].test(t)) return i;
+            if (!n && this._weekdaysParse[i].test(t)) return i;
+          }
+        },
+        Q.weekdaysRegex = function(t) {
+          return this._weekdaysParseExact
+            ? (a(this, "_weekdaysRegex") || Jt.call(this), t ? this._weekdaysStrictRegex : this._weekdaysRegex)
+            : (a(this, "_weekdaysRegex") || (this._weekdaysRegex = Zt),
+              this._weekdaysStrictRegex && t ? this._weekdaysStrictRegex : this._weekdaysRegex);
+        },
+        Q.weekdaysShortRegex = function(t) {
+          return this._weekdaysParseExact
+            ? (a(this, "_weekdaysRegex") || Jt.call(this),
+              t ? this._weekdaysShortStrictRegex : this._weekdaysShortRegex)
+            : (a(this, "_weekdaysShortRegex") || (this._weekdaysShortRegex = Qt),
+              this._weekdaysShortStrictRegex && t ? this._weekdaysShortStrictRegex : this._weekdaysShortRegex);
+        },
+        Q.weekdaysMinRegex = function(t) {
+          return this._weekdaysParseExact
+            ? (a(this, "_weekdaysRegex") || Jt.call(this), t ? this._weekdaysMinStrictRegex : this._weekdaysMinRegex)
+            : (a(this, "_weekdaysMinRegex") || (this._weekdaysMinRegex = Kt),
+              this._weekdaysMinStrictRegex && t ? this._weekdaysMinStrictRegex : this._weekdaysMinRegex);
+        },
+        Q.isPM = function(t) {
+          return "p" === (t + "").toLowerCase().charAt(0);
+        },
+        Q.meridiem = function(t, e, n) {
+          return 11 < t ? n ? "pm" : "PM" : n ? "am" : "AM";
+        },
+        he("en", {
+          eras: [{ since: "0001-01-01", until: 1 / 0, offset: 1, name: "Anno Domini", narrow: "AD", abbr: "AD" }, {
+            since: "0000-12-31",
+            until: -1 / 0,
+            offset: 1,
+            name: "Before Christ",
+            narrow: "BC",
+            abbr: "BC",
+          }],
+          dayOfMonthOrdinalParse: /\d{1,2}(th|st|nd|rd)/,
+          ordinal: function(t) {
+            var e = t % 10;
+            return t + (1 === q(t % 100 / 10) ? "th" : 1 == e ? "st" : 2 == e ? "nd" : 3 == e ? "rd" : "th");
+          },
+        }),
+        n.lang = w("moment.lang is deprecated. Use moment.locale instead.", he),
+        n.langData = w("moment.langData is deprecated. Use moment.localeData instead.", de);
+      var gn = Math.abs;
+      function yn(t, e, n, i) {
+        return e = We(e, n),
+          t._milliseconds += i * e._milliseconds,
+          t._days += i * e._days,
+          t._months += i * e._months,
+          t._bubble();
+      }
+      function mn(t) {
+        return t < 0 ? Math.floor(t) : Math.ceil(t);
+      }
+      function bn(t) {
+        return 4800 * t / 146097;
+      }
+      function _n(t) {
+        return 146097 * t / 4800;
+      }
+      function xn(t) {
+        return function() {
+          return this.as(t);
+        };
+      }
+      function vn(t) {
+        return function() {
+          return this.isValid() ? this._data[t] : NaN;
+        };
+      }
+      rt = xn("ms"),
+        K = xn("s"),
+        Lt = xn("m"),
+        it = xn("h"),
+        nt = xn("d"),
+        Vt = xn("w"),
+        ut = xn("M"),
+        J = xn("Q"),
+        st = xn("y"),
+        tt = vn("milliseconds"),
+        at = vn("seconds"),
+        Pt = vn("minutes"),
+        Q = vn("hours");
+      var kn = vn("days"),
+        wn = vn("months"),
+        Tn = vn("years"),
+        Cn = Math.round,
+        En = { ss: 44, s: 45, m: 45, h: 22, d: 26, w: null, M: 11 };
+      function Sn(t, e, n, i) {
+        var r = We(t).abs(),
+          a = Cn(r.as("s")),
+          s = Cn(r.as("m")),
+          o = Cn(r.as("h")),
+          l = Cn(r.as("d")),
+          c = Cn(r.as("M")),
+          h = Cn(r.as("w"));
+        return r = Cn(r.as("y")),
+          a = (a <= n.ss ? ["s", a] : a < n.s && ["ss", a]) || s <= 1 && ["m"] || s < n.m && ["mm", s]
+            || o <= 1 && ["h"] || o < n.h && ["hh", o] || l <= 1 && ["d"] || l < n.d && ["dd", l],
+          (a = (a = null != n.w ? a || h <= 1 && ["w"] || h < n.w && ["ww", h] : a) || c <= 1 && ["M"]
+            || c < n.M && ["MM", c] || r <= 1 && ["y"] || ["yy", r])[2] = e,
+          a[3] = 0 < +t,
+          a[4] = i,
+          function(t, e, n, i, r) {
+            return r.relativeTime(e || 1, !!n, t, i);
+          }.apply(null, a);
+      }
+      var An = Math.abs;
+      function Dn(t) {
+        return (0 < t) - (t < 0) || +t;
+      }
+      function Ln() {
+        if (!this.isValid()) return this.localeData().invalidDate();
+        var t,
+          e,
+          n,
+          i,
+          r,
+          a,
+          s,
+          o = An(this._milliseconds) / 1e3,
+          l = An(this._days),
+          c = An(this._months),
+          h = this.asSeconds();
+        return h
+          ? (t = H(o / 60),
+            e = H(t / 60),
+            o %= 60,
+            t %= 60,
+            n = H(c / 12),
+            c %= 12,
+            i = o ? o.toFixed(3).replace(/\.?0+$/, "") : "",
+            r = Dn(this._months) !== Dn(h) ? "-" : "",
+            a = Dn(this._days) !== Dn(h) ? "-" : "",
+            s = Dn(this._milliseconds) !== Dn(h) ? "-" : "",
+            (h < 0 ? "-" : "") + "P" + (n ? r + n + "Y" : "") + (c ? r + c + "M" : "") + (l ? a + l + "D" : "")
+            + (e || t || o ? "T" : "") + (e ? s + e + "H" : "") + (t ? s + t + "M" : "") + (o ? s + i + "S" : ""))
+          : "P0D";
+      }
+      var On = Me.prototype;
+      return On.isValid = function() {
+        return this._isValid;
+      },
+        On.abs = function() {
+          var t = this._data;
+          return this._milliseconds = gn(this._milliseconds),
+            this._days = gn(this._days),
+            this._months = gn(this._months),
+            t.milliseconds = gn(t.milliseconds),
+            t.seconds = gn(t.seconds),
+            t.minutes = gn(t.minutes),
+            t.hours = gn(t.hours),
+            t.months = gn(t.months),
+            t.years = gn(t.years),
+            this;
+        },
+        On.add = function(t, e) {
+          return yn(this, t, e, 1);
+        },
+        On.subtract = function(t, e) {
+          return yn(this, t, e, -1);
+        },
+        On.as = function(t) {
+          if (!this.isValid()) return NaN;
+          var e, n, i = this._milliseconds;
+          if ("month" === (t = Y(t)) || "quarter" === t || "year" === t) {
+            switch (e = this._days + i / 864e5, n = this._months + bn(e), t) {
+              case "month":
+                return n;
+              case "quarter":
+                return n / 3;
+              case "year":
+                return n / 12;
+            }
+          } else {switch (e = this._days + Math.round(_n(this._months)), t) {
+              case "week":
+                return e / 7 + i / 6048e5;
+              case "day":
+                return e + i / 864e5;
+              case "hour":
+                return 24 * e + i / 36e5;
+              case "minute":
+                return 1440 * e + i / 6e4;
+              case "second":
+                return 86400 * e + i / 1e3;
+              case "millisecond":
+                return Math.floor(864e5 * e) + i;
+              default:
+                throw new Error("Unknown unit " + t);
+            }}
+        },
+        On.asMilliseconds = rt,
+        On.asSeconds = K,
+        On.asMinutes = Lt,
+        On.asHours = it,
+        On.asDays = nt,
+        On.asWeeks = Vt,
+        On.asMonths = ut,
+        On.asQuarters = J,
+        On.asYears = st,
+        On.valueOf = function() {
+          return this.isValid()
+            ? this._milliseconds + 864e5 * this._days + this._months % 12 * 2592e6 + 31536e6 * q(this._months / 12)
+            : NaN;
+        },
+        On._bubble = function() {
+          var t = this._milliseconds, e = this._days, n = this._months, i = this._data;
+          return 0 <= t && 0 <= e && 0 <= n || t <= 0 && e <= 0 && n <= 0 || (t += 864e5 * mn(_n(n) + e), n = e = 0),
+            i.milliseconds = t % 1e3,
+            t = H(t / 1e3),
+            i.seconds = t % 60,
+            t = H(t / 60),
+            i.minutes = t % 60,
+            t = H(t / 60),
+            i.hours = t % 24,
+            e += H(t / 24),
+            n += t = H(bn(e)),
+            e -= mn(_n(t)),
+            t = H(n / 12),
+            n %= 12,
+            i.days = e,
+            i.months = n,
+            i.years = t,
+            this;
+        },
+        On.clone = function() {
+          return We(this);
+        },
+        On.get = function(t) {
+          return t = Y(t), this.isValid() ? this[t + "s"]() : NaN;
+        },
+        On.milliseconds = tt,
+        On.seconds = at,
+        On.minutes = Pt,
+        On.hours = Q,
+        On.days = kn,
+        On.weeks = function() {
+          return H(this.days() / 7);
+        },
+        On.months = wn,
+        On.years = Tn,
+        On.humanize = function(t, e) {
+          if (!this.isValid()) return this.localeData().invalidDate();
+          var n = !1, i = En;
+          return "object" == typeof t && (e = t, t = !1),
+            "boolean" == typeof t && (n = t),
+            "object" == typeof e && (i = Object.assign({}, En, e), null != e.s && null == e.ss && (i.ss = e.s - 1)),
+            e = Sn(this, !n, i, t = this.localeData()),
+            n && (e = t.pastFuture(+this, e)),
+            t.postformat(e);
+        },
+        On.toISOString = Ln,
+        On.toString = Ln,
+        On.toJSON = Ln,
+        On.locale = Ke,
+        On.localeData = Je,
+        On.toIsoString = w("toIsoString() is deprecated. Please use toISOString() instead (notice the capitals)", Ln),
+        On.lang = Xt,
+        I("X", 0, 0, "unix"),
+        I("x", 0, 0, "valueOf"),
+        dt("x", lt),
+        dt("X", /[+-]?\d+(\.\d{1,3})?/),
+        mt("X", function(t, e, n) {
+          n._d = new Date(1e3 * parseFloat(t));
+        }),
+        mt("x", function(t, e, n) {
+          n._d = new Date(q(t));
+        }),
+        n.version = "2.29.4",
+        e = Le,
+        n.fn = Z,
+        n.min = function() {
+          return Oe("isBefore", [].slice.call(arguments, 0));
+        },
+        n.max = function() {
+          return Oe("isAfter", [].slice.call(arguments, 0));
+        },
+        n.now = function() {
+          return Date.now ? Date.now() : +new Date();
+        },
+        n.utc = d,
+        n.unix = function(t) {
+          return Le(1e3 * t);
+        },
+        n.months = function(t, e) {
+          return pn(t, e, "months");
+        },
+        n.isDate = c,
+        n.locale = he,
+        n.invalid = g,
+        n.duration = We,
+        n.isMoment = v,
+        n.weekdays = function(t, e, n) {
+          return fn(t, e, n, "weekdays");
+        },
+        n.parseZone = function() {
+          return Le.apply(null, arguments).parseZone();
+        },
+        n.localeData = de,
+        n.isDuration = Be,
+        n.monthsShort = function(t, e) {
+          return pn(t, e, "monthsShort");
+        },
+        n.weekdaysMin = function(t, e, n) {
+          return fn(t, e, n, "weekdaysMin");
+        },
+        n.defineLocale = ue,
+        n.updateLocale = function(t, e) {
+          var n, i;
+          return null != e
+            ? (i = re,
+              null != ae[t] && null != ae[t].parentLocale
+                ? ae[t].set(S(ae[t]._config, e))
+                : (e = S(i = null != (n = ce(t)) ? n._config : i, e),
+                  null == n && (e.abbr = t),
+                  (i = new A(e)).parentLocale = ae[t],
+                  ae[t] = i),
+              he(t))
+            : null != ae[t]
+              && (null != ae[t].parentLocale
+                ? (ae[t] = ae[t].parentLocale, t === he() && he(t))
+                : null != ae[t] && delete ae[t]),
+            ae[t];
+        },
+        n.locales = function() {
+          return D(ae);
+        },
+        n.weekdaysShort = function(t, e, n) {
+          return fn(t, e, n, "weekdaysShort");
+        },
+        n.normalizeUnits = Y,
+        n.relativeTimeRounding = function(t) {
+          return void 0 === t ? Cn : "function" == typeof t && (Cn = t, !0);
+        },
+        n.relativeTimeThreshold = function(t, e) {
+          return void 0 !== En[t] && (void 0 === e ? En[t] : (En[t] = e, "s" === t && (En.ss = e - 1), !0));
+        },
+        n.calendarFormat = function(t, e) {
+          return (t = t.diff(e, "days", !0)) < -6
+            ? "sameElse"
+            : t < -1
+            ? "lastWeek"
+            : t < 0
+            ? "lastDay"
+            : t < 1
+            ? "sameDay"
+            : t < 2
+            ? "nextDay"
+            : t < 7
+            ? "nextWeek"
+            : "sameElse";
+        },
+        n.prototype = Z,
+        n.HTML5_FMT = {
+          DATETIME_LOCAL: "YYYY-MM-DDTHH:mm",
+          DATETIME_LOCAL_SECONDS: "YYYY-MM-DDTHH:mm:ss",
+          DATETIME_LOCAL_MS: "YYYY-MM-DDTHH:mm:ss.SSS",
+          DATE: "YYYY-MM-DD",
+          TIME: "HH:mm",
+          TIME_SECONDS: "HH:mm:ss",
+          TIME_MS: "HH:mm:ss.SSS",
+          WEEK: "GGGG-[W]WW",
+          MONTH: "YYYY-MM",
+        },
+        n;
+    }();
+  }(t);
+  var e = t.exports, n = {};
+  Object.defineProperty(n, "__esModule", { value: !0 });
+  var i = n.sanitizeUrl = void 0,
+    r = /^([^\w]*)(javascript|data|vbscript)/im,
+    a = /&#(\w+)(^\w|;)?/g,
+    s = /&(newline|tab);/gi,
+    o = /[\u0000-\u001F\u007F-\u009F\u2000-\u200D\uFEFF]/gim,
+    l = /^.+(:|&colon;)/gim,
+    h = [".", "/"];
+  function u(t, e) {
+    return null == t || null == e ? NaN : t < e ? -1 : t > e ? 1 : t >= e ? 0 : NaN;
+  }
+  function d(t, e) {
+    return null == t || null == e ? NaN : e < t ? -1 : e > t ? 1 : e >= t ? 0 : NaN;
+  }
+  function p(t) {
+    let e, n, i;
+    function r(t, i, r = 0, a = t.length) {
+      if (r < a) {
+        if (0 !== e(i, i)) return a;
+        do {
+          const e = r + a >>> 1;
+          n(t[e], i) < 0 ? r = e + 1 : a = e;
+        } while (r < a);
+      }
+      return r;
+    }
+    return 2 !== t.length
+      ? (e = u, n = (e, n) => u(t(e), n), i = (e, n) => t(e) - n)
+      : (e = t === u || t === d ? t : f, n = t, i = t),
+      {
+        left: r,
+        center: function(t, e, n = 0, a = t.length) {
+          const s = r(t, e, n, a - 1);
+          return s > n && i(t[s - 1], e) > -i(t[s], e) ? s - 1 : s;
+        },
+        right: function(t, i, r = 0, a = t.length) {
+          if (r < a) {
+            if (0 !== e(i, i)) return a;
+            do {
+              const e = r + a >>> 1;
+              n(t[e], i) <= 0 ? r = e + 1 : a = e;
+            } while (r < a);
+          }
+          return r;
+        },
+      };
+  }
+  function f() {
+    return 0;
+  }
+  i = n.sanitizeUrl = function(t) {
+    var e = function(t) {
+      return t.replace(a, function(t, e) {
+        return String.fromCharCode(e);
+      });
+    }(t || "").replace(s, "").replace(o, "").trim();
+    if (!e) return "about:blank";
+    if (
+      function(t) {
+        return h.indexOf(t[0]) > -1;
+      }(e)
+    ) return e;
+    var n = e.match(l);
+    if (!n) return e;
+    var i = n[0];
+    return r.test(i) ? "about:blank" : e;
+  };
+  const g = p(u).right;
+  p(function(t) {
+    return null === t ? NaN : +t;
+  }).center;
+  var y = g;
+  class m extends Map {
+    constructor(t, e = _) {
+      if (super(), Object.defineProperties(this, { _intern: { value: new Map() }, _key: { value: e } }), null != t) {
+        for (const [e, n] of t) this.set(e, n);
+      }
+    }
+    get(t) {
+      return super.get(b(this, t));
+    }
+    has(t) {
+      return super.has(b(this, t));
+    }
+    set(t, e) {
+      return super.set(
+        function({ _intern: t, _key: e }, n) {
+          const i = e(n);
+          return t.has(i) ? t.get(i) : (t.set(i, n), n);
+        }(this, t),
+        e,
+      );
+    }
+    delete(t) {
+      return super.delete(function({ _intern: t, _key: e }, n) {
+        const i = e(n);
+        t.has(i) && (n = t.get(i), t.delete(i));
+        return n;
+      }(this, t));
+    }
+  }
+  function b({ _intern: t, _key: e }, n) {
+    const i = e(n);
+    return t.has(i) ? t.get(i) : n;
+  }
+  function _(t) {
+    return null !== t && "object" == typeof t ? t.valueOf() : t;
+  }
+  const x = Math.sqrt(50), v = Math.sqrt(10), k = Math.sqrt(2);
+  function w(t, e, n) {
+    const i = (e - t) / Math.max(0, n),
+      r = Math.floor(Math.log10(i)),
+      a = i / Math.pow(10, r),
+      s = a >= x ? 10 : a >= v ? 5 : a >= k ? 2 : 1;
+    let o, l, c;
+    return r < 0
+      ? (c = Math.pow(10, -r) / s,
+        o = Math.round(t * c),
+        l = Math.round(e * c),
+        o / c < t && ++o,
+        l / c > e && --l,
+        c = -c)
+      : (c = Math.pow(10, r) * s, o = Math.round(t / c), l = Math.round(e / c), o * c < t && ++o, l * c > e && --l),
+      l < o && .5 <= n && n < 2 ? w(t, e, 2 * n) : [o, l, c];
+  }
+  function T(t, e, n) {
+    return w(t = +t, e = +e, n = +n)[2];
+  }
+  function C(t, e, n) {
+    n = +n;
+    const i = (e = +e) < (t = +t), r = i ? T(e, t, n) : T(t, e, n);
+    return (i ? -1 : 1) * (r < 0 ? 1 / -r : r);
+  }
+  function E(t, e) {
+    let n;
+    if (void 0 === e) for (const e of t) null != e && (n < e || void 0 === n && e >= e) && (n = e);
+    else {
+      let i = -1;
+      for (let r of t) null != (r = e(r, ++i, t)) && (n < r || void 0 === n && r >= r) && (n = r);
+    }
+    return n;
+  }
+  function S(t, e) {
+    let n;
+    if (void 0 === e) for (const e of t) null != e && (n > e || void 0 === n && e >= e) && (n = e);
+    else {
+      let i = -1;
+      for (let r of t) null != (r = e(r, ++i, t)) && (n > r || void 0 === n && r >= r) && (n = r);
+    }
+    return n;
+  }
+  function A(t) {
+    return t;
+  }
+  var D = 1, L = 2, O = 3, N = 4, M = 1e-6;
+  function B(t) {
+    return "translate(" + t + ",0)";
+  }
+  function I(t) {
+    return "translate(0," + t + ")";
+  }
+  function F(t) {
+    return e => +t(e);
+  }
+  function R(t, e) {
+    return e = Math.max(0, t.bandwidth() - 2 * e) / 2, t.round() && (e = Math.round(e)), n => +t(n) + e;
+  }
+  function $() {
+    return !this.__axis;
+  }
+  function P(t, e) {
+    var n = [],
+      i = null,
+      r = null,
+      a = 6,
+      s = 6,
+      o = 3,
+      l = "undefined" != typeof window && window.devicePixelRatio > 1 ? 0 : .5,
+      c = t === D || t === N ? -1 : 1,
+      h = t === N || t === L ? "x" : "y",
+      u = t === D || t === O ? B : I;
+    function d(d) {
+      var p = null == i ? e.ticks ? e.ticks.apply(e, n) : e.domain() : i,
+        f = null == r ? e.tickFormat ? e.tickFormat.apply(e, n) : A : r,
+        g = Math.max(a, 0) + o,
+        y = e.range(),
+        m = +y[0] + l,
+        b = +y[y.length - 1] + l,
+        _ = (e.bandwidth ? R : F)(e.copy(), l),
+        x = d.selection ? d.selection() : d,
+        v = x.selectAll(".domain").data([null]),
+        k = x.selectAll(".tick").data(p, e).order(),
+        w = k.exit(),
+        T = k.enter().append("g").attr("class", "tick"),
+        C = k.select("line"),
+        E = k.select("text");
+      v = v.merge(v.enter().insert("path", ".tick").attr("class", "domain").attr("stroke", "currentColor")),
+        k = k.merge(T),
+        C = C.merge(T.append("line").attr("stroke", "currentColor").attr(h + "2", c * a)),
+        E = E.merge(
+          T.append("text").attr("fill", "currentColor").attr(h, c * g).attr(
+            "dy",
+            t === D ? "0em" : t === O ? "0.71em" : "0.32em",
+          ),
+        ),
+        d !== x
+        && (v = v.transition(d),
+          k = k.transition(d),
+          C = C.transition(d),
+          E = E.transition(d),
+          w = w.transition(d).attr("opacity", M).attr("transform", function(t) {
+            return isFinite(t = _(t)) ? u(t + l) : this.getAttribute("transform");
+          }),
+          T.attr("opacity", M).attr("transform", function(t) {
+            var e = this.parentNode.__axis;
+            return u((e && isFinite(e = e(t)) ? e : _(t)) + l);
+          })),
+        w.remove(),
+        v.attr(
+          "d",
+          t === N || t === L
+            ? s ? "M" + c * s + "," + m + "H" + l + "V" + b + "H" + c * s : "M" + l + "," + m + "V" + b
+            : s
+            ? "M" + m + "," + c * s + "V" + l + "H" + b + "V" + c * s
+            : "M" + m + "," + l + "H" + b,
+        ),
+        k.attr("opacity", 1).attr("transform", function(t) {
+          return u(_(t) + l);
+        }),
+        C.attr(h + "2", c * a),
+        E.attr(h, c * g).text(f),
+        x.filter($).attr("fill", "none").attr("font-size", 10).attr("font-family", "sans-serif").attr(
+          "text-anchor",
+          t === L ? "start" : t === N ? "end" : "middle",
+        ),
+        x.each(function() {
+          this.__axis = _;
+        });
+    }
+    return d.scale = function(t) {
+      return arguments.length ? (e = t, d) : e;
+    },
+      d.ticks = function() {
+        return n = Array.from(arguments), d;
+      },
+      d.tickArguments = function(t) {
+        return arguments.length ? (n = null == t ? [] : Array.from(t), d) : n.slice();
+      },
+      d.tickValues = function(t) {
+        return arguments.length ? (i = null == t ? null : Array.from(t), d) : i && i.slice();
+      },
+      d.tickFormat = function(t) {
+        return arguments.length ? (r = t, d) : r;
+      },
+      d.tickSize = function(t) {
+        return arguments.length ? (a = s = +t, d) : a;
+      },
+      d.tickSizeInner = function(t) {
+        return arguments.length ? (a = +t, d) : a;
+      },
+      d.tickSizeOuter = function(t) {
+        return arguments.length ? (s = +t, d) : s;
+      },
+      d.tickPadding = function(t) {
+        return arguments.length ? (o = +t, d) : o;
+      },
+      d.offset = function(t) {
+        return arguments.length ? (l = +t, d) : l;
+      },
+      d;
+  }
+  var Y = { value: () => {} };
+  function j() {
+    for (var t, e = 0, n = arguments.length, i = {}; e < n; ++e) {
+      if (!(t = arguments[e] + "") || t in i || /[\s.]/.test(t)) throw new Error("illegal type: " + t);
+      i[t] = [];
+    }
+    return new z(i);
+  }
+  function z(t) {
+    this._ = t;
+  }
+  function U(t, e) {
+    for (var n, i = 0, r = t.length; i < r; ++i) if ((n = t[i]).name === e) return n.value;
+  }
+  function W(t, e, n) {
+    for (var i = 0, r = t.length; i < r; ++i) {
+      if (t[i].name === e) {
+        t[i] = Y, t = t.slice(0, i).concat(t.slice(i + 1));
+        break;
+      }
+    }
+    return null != n && t.push({ name: e, value: n }), t;
+  }
+  z.prototype = j.prototype = {
+    constructor: z,
+    on: function(t, e) {
+      var n,
+        i = this._,
+        r = function(t, e) {
+          return t.trim().split(/^|\s+/).map(function(t) {
+            var n = "", i = t.indexOf(".");
+            if (i >= 0 && (n = t.slice(i + 1), t = t.slice(0, i)), t && !e.hasOwnProperty(t)) {
+              throw new Error("unknown type: " + t);
+            }
+            return { type: t, name: n };
+          });
+        }(t + "", i),
+        a = -1,
+        s = r.length;
+      if (!(arguments.length < 2)) {
+        if (null != e && "function" != typeof e) throw new Error("invalid callback: " + e);
+        for (; ++a < s;) {
+          if (n = (t = r[a]).type) i[n] = W(i[n], t.name, e);
+          else if (null == e) for (n in i) i[n] = W(i[n], t.name, null);
+        }
+        return this;
+      }
+      for (; ++a < s;) if ((n = (t = r[a]).type) && (n = U(i[n], t.name))) return n;
+    },
+    copy: function() {
+      var t = {}, e = this._;
+      for (var n in e) t[n] = e[n].slice();
+      return new z(t);
+    },
+    call: function(t, e) {
+      if ((n = arguments.length - 2) > 0) for (var n, i, r = new Array(n), a = 0; a < n; ++a) r[a] = arguments[a + 2];
+      if (!this._.hasOwnProperty(t)) throw new Error("unknown type: " + t);
+      for (a = 0, n = (i = this._[t]).length; a < n; ++a) i[a].value.apply(e, r);
+    },
+    apply: function(t, e, n) {
+      if (!this._.hasOwnProperty(t)) throw new Error("unknown type: " + t);
+      for (var i = this._[t], r = 0, a = i.length; r < a; ++r) i[r].value.apply(e, n);
+    },
+  };
+  var H = "http://www.w3.org/1999/xhtml",
+    q = {
+      svg: "http://www.w3.org/2000/svg",
+      xhtml: H,
+      xlink: "http://www.w3.org/1999/xlink",
+      xml: "http://www.w3.org/XML/1998/namespace",
+      xmlns: "http://www.w3.org/2000/xmlns/",
+    };
+  function V(t) {
+    var e = t += "", n = e.indexOf(":");
+    return n >= 0 && "xmlns" !== (e = t.slice(0, n)) && (t = t.slice(n + 1)),
+      q.hasOwnProperty(e) ? { space: q[e], local: t } : t;
+  }
+  function G(t) {
+    return function() {
+      var e = this.ownerDocument, n = this.namespaceURI;
+      return n === H && e.documentElement.namespaceURI === H ? e.createElement(t) : e.createElementNS(n, t);
+    };
+  }
+  function X(t) {
+    return function() {
+      return this.ownerDocument.createElementNS(t.space, t.local);
+    };
+  }
+  function Z(t) {
+    var e = V(t);
+    return (e.local ? X : G)(e);
+  }
+  function Q() {}
+  function K(t) {
+    return null == t ? Q : function() {
+      return this.querySelector(t);
+    };
+  }
+  function J(t) {
+    return null == t ? [] : Array.isArray(t) ? t : Array.from(t);
+  }
+  function tt() {
+    return [];
+  }
+  function et(t) {
+    return null == t ? tt : function() {
+      return this.querySelectorAll(t);
+    };
+  }
+  function nt(t) {
+    return function() {
+      return this.matches(t);
+    };
+  }
+  function it(t) {
+    return function(e) {
+      return e.matches(t);
+    };
+  }
+  var rt = Array.prototype.find;
+  function at() {
+    return this.firstElementChild;
+  }
+  var st = Array.prototype.filter;
+  function ot() {
+    return Array.from(this.children);
+  }
+  function lt(t) {
+    return new Array(t.length);
+  }
+  function ct(t, e) {
+    this.ownerDocument = t.ownerDocument,
+      this.namespaceURI = t.namespaceURI,
+      this._next = null,
+      this._parent = t,
+      this.__data__ = e;
+  }
+  function ht(t, e, n, i, r, a) {
+    for (var s, o = 0, l = e.length, c = a.length; o < c; ++o) {
+      (s = e[o])
+        ? (s.__data__ = a[o], i[o] = s)
+        : n[o] = new ct(t, a[o]);
+    }
+    for (; o < l; ++o) (s = e[o]) && (r[o] = s);
+  }
+  function ut(t, e, n, i, r, a, s) {
+    var o, l, c, h = new Map(), u = e.length, d = a.length, p = new Array(u);
+    for (o = 0; o < u; ++o) {
+      (l = e[o]) && (p[o] = c = s.call(l, l.__data__, o, e) + "", h.has(c) ? r[o] = l : h.set(c, l));
+    }
+    for (o = 0; o < d; ++o) {
+      c = s.call(t, a[o], o, a) + "",
+        (l = h.get(c)) ? (i[o] = l, l.__data__ = a[o], h.delete(c)) : n[o] = new ct(t, a[o]);
+    }
+    for (o = 0; o < u; ++o) (l = e[o]) && h.get(p[o]) === l && (r[o] = l);
+  }
+  function dt(t) {
+    return t.__data__;
+  }
+  function pt(t) {
+    return "object" == typeof t && "length" in t ? t : Array.from(t);
+  }
+  function ft(t, e) {
+    return t < e ? -1 : t > e ? 1 : t >= e ? 0 : NaN;
+  }
+  function gt(t) {
+    return function() {
+      this.removeAttribute(t);
+    };
+  }
+  function yt(t) {
+    return function() {
+      this.removeAttributeNS(t.space, t.local);
+    };
+  }
+  function mt(t, e) {
+    return function() {
+      this.setAttribute(t, e);
+    };
+  }
+  function bt(t, e) {
+    return function() {
+      this.setAttributeNS(t.space, t.local, e);
+    };
+  }
+  function _t(t, e) {
+    return function() {
+      var n = e.apply(this, arguments);
+      null == n ? this.removeAttribute(t) : this.setAttribute(t, n);
+    };
+  }
+  function xt(t, e) {
+    return function() {
+      var n = e.apply(this, arguments);
+      null == n ? this.removeAttributeNS(t.space, t.local) : this.setAttributeNS(t.space, t.local, n);
+    };
+  }
+  function vt(t) {
+    return t.ownerDocument && t.ownerDocument.defaultView || t.document && t || t.defaultView;
+  }
+  function kt(t) {
+    return function() {
+      this.style.removeProperty(t);
+    };
+  }
+  function wt(t, e, n) {
+    return function() {
+      this.style.setProperty(t, e, n);
+    };
+  }
+  function Tt(t, e, n) {
+    return function() {
+      var i = e.apply(this, arguments);
+      null == i ? this.style.removeProperty(t) : this.style.setProperty(t, i, n);
+    };
+  }
+  function Ct(t, e) {
+    return t.style.getPropertyValue(e) || vt(t).getComputedStyle(t, null).getPropertyValue(e);
+  }
+  function Et(t) {
+    return function() {
+      delete this[t];
+    };
+  }
+  function St(t, e) {
+    return function() {
+      this[t] = e;
+    };
+  }
+  function At(t, e) {
+    return function() {
+      var n = e.apply(this, arguments);
+      null == n ? delete this[t] : this[t] = n;
+    };
+  }
+  function Dt(t) {
+    return t.trim().split(/^|\s+/);
+  }
+  function Lt(t) {
+    return t.classList || new Ot(t);
+  }
+  function Ot(t) {
+    this._node = t, this._names = Dt(t.getAttribute("class") || "");
+  }
+  function Nt(t, e) {
+    for (var n = Lt(t), i = -1, r = e.length; ++i < r;) n.add(e[i]);
+  }
+  function Mt(t, e) {
+    for (var n = Lt(t), i = -1, r = e.length; ++i < r;) n.remove(e[i]);
+  }
+  function Bt(t) {
+    return function() {
+      Nt(this, t);
+    };
+  }
+  function It(t) {
+    return function() {
+      Mt(this, t);
+    };
+  }
+  function Ft(t, e) {
+    return function() {
+      (e.apply(this, arguments) ? Nt : Mt)(this, t);
+    };
+  }
+  function Rt() {
+    this.textContent = "";
+  }
+  function $t(t) {
+    return function() {
+      this.textContent = t;
+    };
+  }
+  function Pt(t) {
+    return function() {
+      var e = t.apply(this, arguments);
+      this.textContent = null == e ? "" : e;
+    };
+  }
+  function Yt() {
+    this.innerHTML = "";
+  }
+  function jt(t) {
+    return function() {
+      this.innerHTML = t;
+    };
+  }
+  function zt(t) {
+    return function() {
+      var e = t.apply(this, arguments);
+      this.innerHTML = null == e ? "" : e;
+    };
+  }
+  function Ut() {
+    this.nextSibling && this.parentNode.appendChild(this);
+  }
+  function Wt() {
+    this.previousSibling && this.parentNode.insertBefore(this, this.parentNode.firstChild);
+  }
+  function Ht() {
+    return null;
+  }
+  function qt() {
+    var t = this.parentNode;
+    t && t.removeChild(this);
+  }
+  function Vt() {
+    var t = this.cloneNode(!1), e = this.parentNode;
+    return e ? e.insertBefore(t, this.nextSibling) : t;
+  }
+  function Gt() {
+    var t = this.cloneNode(!0), e = this.parentNode;
+    return e ? e.insertBefore(t, this.nextSibling) : t;
+  }
+  function Xt(t) {
+    return function() {
+      var e = this.__on;
+      if (e) {
+        for (var n, i = 0, r = -1, a = e.length; i < a; ++i) {
+          n = e[i],
+            t.type && n.type !== t.type || n.name !== t.name
+              ? e[++r] = n
+              : this.removeEventListener(n.type, n.listener, n.options);
+        }
+        ++r ? e.length = r : delete this.__on;
+      }
+    };
+  }
+  function Zt(t, e, n) {
+    return function() {
+      var i,
+        r = this.__on,
+        a = function(t) {
+          return function(e) {
+            t.call(this, e, this.__data__);
+          };
+        }(e);
+      if (r) {
+        for (var s = 0, o = r.length; s < o; ++s) {
+          if ((i = r[s]).type === t.type && i.name === t.name) {
+            return this.removeEventListener(i.type, i.listener, i.options),
+              this.addEventListener(i.type, i.listener = a, i.options = n),
+              void (i.value = e);
+          }
+        }
+      }
+      this.addEventListener(t.type, a, n),
+        i = { type: t.type, name: t.name, value: e, listener: a, options: n },
+        r ? r.push(i) : this.__on = [i];
+    };
+  }
+  function Qt(t, e, n) {
+    var i = vt(t), r = i.CustomEvent;
+    "function" == typeof r
+      ? r = new r(e, n)
+      : (r = i.document.createEvent("Event"),
+        n ? (r.initEvent(e, n.bubbles, n.cancelable), r.detail = n.detail) : r.initEvent(e, !1, !1)),
+      t.dispatchEvent(r);
+  }
+  function Kt(t, e) {
+    return function() {
+      return Qt(this, t, e);
+    };
+  }
+  function Jt(t, e) {
+    return function() {
+      return Qt(this, t, e.apply(this, arguments));
+    };
+  }
+  ct.prototype = {
+    constructor: ct,
+    appendChild: function(t) {
+      return this._parent.insertBefore(t, this._next);
+    },
+    insertBefore: function(t, e) {
+      return this._parent.insertBefore(t, e);
+    },
+    querySelector: function(t) {
+      return this._parent.querySelector(t);
+    },
+    querySelectorAll: function(t) {
+      return this._parent.querySelectorAll(t);
+    },
+  },
+    Ot.prototype = {
+      add: function(t) {
+        this._names.indexOf(t) < 0 && (this._names.push(t), this._node.setAttribute("class", this._names.join(" ")));
+      },
+      remove: function(t) {
+        var e = this._names.indexOf(t);
+        e >= 0 && (this._names.splice(e, 1), this._node.setAttribute("class", this._names.join(" ")));
+      },
+      contains: function(t) {
+        return this._names.indexOf(t) >= 0;
+      },
+    };
+  var te = [null];
+  function ee(t, e) {
+    this._groups = t, this._parents = e;
+  }
+  function ne() {
+    return new ee([[document.documentElement]], te);
+  }
+  function ie(t) {
+    return "string" == typeof t ? new ee([[document.querySelector(t)]], [document.documentElement]) : new ee([[t]], te);
+  }
+  function re(t) {
+    return "string" == typeof t
+      ? new ee([document.querySelectorAll(t)], [document.documentElement])
+      : new ee([J(t)], te);
+  }
+  function ae(t, e, n) {
+    t.prototype = e.prototype = n, n.constructor = t;
+  }
+  function se(t, e) {
+    var n = Object.create(t.prototype);
+    for (var i in e) n[i] = e[i];
+    return n;
+  }
+  function oe() {}
+  ee.prototype = ne.prototype = {
+    constructor: ee,
+    select: function(t) {
+      "function" != typeof t && (t = K(t));
+      for (var e = this._groups, n = e.length, i = new Array(n), r = 0; r < n; ++r) {
+        for (var a, s, o = e[r], l = o.length, c = i[r] = new Array(l), h = 0; h < l; ++h) {
+          (a = o[h]) && (s = t.call(a, a.__data__, h, o)) && ("__data__" in a && (s.__data__ = a.__data__), c[h] = s);
+        }
+      }
+      return new ee(i, this._parents);
+    },
+    selectAll: function(t) {
+      t = "function" == typeof t
+        ? function(t) {
+          return function() {
+            return J(t.apply(this, arguments));
+          };
+        }(t)
+        : et(t);
+      for (var e = this._groups, n = e.length, i = [], r = [], a = 0; a < n; ++a) {
+        for (var s, o = e[a], l = o.length, c = 0; c < l; ++c) {
+          (s = o[c]) && (i.push(t.call(s, s.__data__, c, o)), r.push(s));
+        }
+      }
+      return new ee(i, r);
+    },
+    selectChild: function(t) {
+      return this.select(
+        null == t ? at : function(t) {
+          return function() {
+            return rt.call(this.children, t);
+          };
+        }("function" == typeof t ? t : it(t)),
+      );
+    },
+    selectChildren: function(t) {
+      return this.selectAll(
+        null == t ? ot : function(t) {
+          return function() {
+            return st.call(this.children, t);
+          };
+        }("function" == typeof t ? t : it(t)),
+      );
+    },
+    filter: function(t) {
+      "function" != typeof t && (t = nt(t));
+      for (var e = this._groups, n = e.length, i = new Array(n), r = 0; r < n; ++r) {
+        for (var a, s = e[r], o = s.length, l = i[r] = [], c = 0; c < o; ++c) {
+          (a = s[c]) && t.call(a, a.__data__, c, s) && l.push(a);
+        }
+      }
+      return new ee(i, this._parents);
+    },
+    data: function(t, e) {
+      if (!arguments.length) return Array.from(this, dt);
+      var n = e ? ut : ht, i = this._parents, r = this._groups;
+      "function" != typeof t && (t = function(t) {
+        return function() {
+          return t;
+        };
+      }(t));
+      for (var a = r.length, s = new Array(a), o = new Array(a), l = new Array(a), c = 0; c < a; ++c) {
+        var h = i[c],
+          u = r[c],
+          d = u.length,
+          p = pt(t.call(h, h && h.__data__, c, i)),
+          f = p.length,
+          g = o[c] = new Array(f),
+          y = s[c] = new Array(f);
+        n(h, u, g, y, l[c] = new Array(d), p, e);
+        for (var m, b, _ = 0, x = 0; _ < f; ++_) {
+          if (m = g[_]) {
+            for (_ >= x && (x = _ + 1); !(b = y[x]) && ++x < f;);
+            m._next = b || null;
+          }
+        }
+      }
+      return (s = new ee(s, i))._enter = o, s._exit = l, s;
+    },
+    enter: function() {
+      return new ee(this._enter || this._groups.map(lt), this._parents);
+    },
+    exit: function() {
+      return new ee(this._exit || this._groups.map(lt), this._parents);
+    },
+    join: function(t, e, n) {
+      var i = this.enter(), r = this, a = this.exit();
+      return "function" == typeof t ? (i = t(i)) && (i = i.selection()) : i = i.append(t + ""),
+        null != e && (r = e(r)) && (r = r.selection()),
+        null == n ? a.remove() : n(a),
+        i && r ? i.merge(r).order() : r;
+    },
+    merge: function(t) {
+      for (
+        var e = t.selection ? t.selection() : t,
+          n = this._groups,
+          i = e._groups,
+          r = n.length,
+          a = i.length,
+          s = Math.min(r, a),
+          o = new Array(r),
+          l = 0;
+        l < s;
+        ++l
+      ) {
+        for (var c, h = n[l], u = i[l], d = h.length, p = o[l] = new Array(d), f = 0; f < d; ++f) {
+          (c = h[f] || u[f]) && (p[f] = c);
+        }
+      }
+      for (; l < r; ++l) o[l] = n[l];
+      return new ee(o, this._parents);
+    },
+    selection: function() {
+      return this;
+    },
+    order: function() {
+      for (var t = this._groups, e = -1, n = t.length; ++e < n;) {
+        for (var i, r = t[e], a = r.length - 1, s = r[a]; --a >= 0;) {
+          (i = r[a]) && (s && 4 ^ i.compareDocumentPosition(s) && s.parentNode.insertBefore(i, s), s = i);
+        }
+      }
+      return this;
+    },
+    sort: function(t) {
+      function e(e, n) {
+        return e && n ? t(e.__data__, n.__data__) : !e - !n;
+      }
+      t || (t = ft);
+      for (var n = this._groups, i = n.length, r = new Array(i), a = 0; a < i; ++a) {
+        for (var s, o = n[a], l = o.length, c = r[a] = new Array(l), h = 0; h < l; ++h) (s = o[h]) && (c[h] = s);
+        c.sort(e);
+      }
+      return new ee(r, this._parents).order();
+    },
+    call: function() {
+      var t = arguments[0];
+      return arguments[0] = this, t.apply(null, arguments), this;
+    },
+    nodes: function() {
+      return Array.from(this);
+    },
+    node: function() {
+      for (var t = this._groups, e = 0, n = t.length; e < n; ++e) {
+        for (var i = t[e], r = 0, a = i.length; r < a; ++r) {
+          var s = i[r];
+          if (s) return s;
+        }
+      }
+      return null;
+    },
+    size: function() {
+      let t = 0;
+      for (const e of this) ++t;
+      return t;
+    },
+    empty: function() {
+      return !this.node();
+    },
+    each: function(t) {
+      for (var e = this._groups, n = 0, i = e.length; n < i; ++n) {
+        for (var r, a = e[n], s = 0, o = a.length; s < o; ++s) {
+          (r = a[s]) && t.call(r, r.__data__, s, a);
+        }
+      }
+      return this;
+    },
+    attr: function(t, e) {
+      var n = V(t);
+      if (arguments.length < 2) {
+        var i = this.node();
+        return n.local ? i.getAttributeNS(n.space, n.local) : i.getAttribute(n);
+      }
+      return this.each(
+        (null == e ? n.local ? yt : gt : "function" == typeof e ? n.local ? xt : _t : n.local ? bt : mt)(n, e),
+      );
+    },
+    style: function(t, e, n) {
+      return arguments.length > 1
+        ? this.each((null == e ? kt : "function" == typeof e ? Tt : wt)(t, e, null == n ? "" : n))
+        : Ct(this.node(), t);
+    },
+    property: function(t, e) {
+      return arguments.length > 1
+        ? this.each((null == e ? Et : "function" == typeof e ? At : St)(t, e))
+        : this.node()[t];
+    },
+    classed: function(t, e) {
+      var n = Dt(t + "");
+      if (arguments.length < 2) {
+        for (var i = Lt(this.node()), r = -1, a = n.length; ++r < a;) if (!i.contains(n[r])) return !1;
+        return !0;
+      }
+      return this.each(("function" == typeof e ? Ft : e ? Bt : It)(n, e));
+    },
+    text: function(t) {
+      return arguments.length
+        ? this.each(null == t ? Rt : ("function" == typeof t ? Pt : $t)(t))
+        : this.node().textContent;
+    },
+    html: function(t) {
+      return arguments.length
+        ? this.each(null == t ? Yt : ("function" == typeof t ? zt : jt)(t))
+        : this.node().innerHTML;
+    },
+    raise: function() {
+      return this.each(Ut);
+    },
+    lower: function() {
+      return this.each(Wt);
+    },
+    append: function(t) {
+      var e = "function" == typeof t ? t : Z(t);
+      return this.select(function() {
+        return this.appendChild(e.apply(this, arguments));
+      });
+    },
+    insert: function(t, e) {
+      var n = "function" == typeof t ? t : Z(t), i = null == e ? Ht : "function" == typeof e ? e : K(e);
+      return this.select(function() {
+        return this.insertBefore(n.apply(this, arguments), i.apply(this, arguments) || null);
+      });
+    },
+    remove: function() {
+      return this.each(qt);
+    },
+    clone: function(t) {
+      return this.select(t ? Gt : Vt);
+    },
+    datum: function(t) {
+      return arguments.length ? this.property("__data__", t) : this.node().__data__;
+    },
+    on: function(t, e, n) {
+      var i,
+        r,
+        a = function(t) {
+          return t.trim().split(/^|\s+/).map(function(t) {
+            var e = "", n = t.indexOf(".");
+            return n >= 0 && (e = t.slice(n + 1), t = t.slice(0, n)), { type: t, name: e };
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+        }(t + ""),
+        s = a.length;
+      if (!(arguments.length < 2)) {
+        for (o = e ? Zt : Xt, i = 0; i < s; ++i) this.each(o(a[i], e, n));
+        return this;
+      }
+      var o = this.node().__on;
+      if (o) {
+        for (var l, c = 0, h = o.length; c < h; ++c) {
+          for (i = 0, l = o[c]; i < s; ++i) if ((r = a[i]).type === l.type && r.name === l.name) return l.value;
+        }
+      }
+    },
+    dispatch: function(t, e) {
+      return this.each(("function" == typeof e ? Jt : Kt)(t, e));
+    },
+    [Symbol.iterator]: function*() {
+      for (var t = this._groups, e = 0, n = t.length; e < n; ++e) {
+        for (var i, r = t[e], a = 0, s = r.length; a < s; ++a) {
+          (i = r[a]) && (yield i);
+        }
+      }
+    },
+  };
+  var le = .7,
+    ce = 1 / le,
+    he = "\\s*([+-]?\\d+)\\s*",
+    ue = "\\s*([+-]?(?:\\d*\\.)?\\d+(?:[eE][+-]?\\d+)?)\\s*",
+    de = "\\s*([+-]?(?:\\d*\\.)?\\d+(?:[eE][+-]?\\d+)?)%\\s*",
+    pe = /^#([0-9a-f]{3,8})$/,
+    fe = new RegExp(`^rgb\\(${he},${he},${he}\\)$`),
+    ge = new RegExp(`^rgb\\(${de},${de},${de}\\)$`),
+    ye = new RegExp(`^rgba\\(${he},${he},${he},${ue}\\)$`),
+    me = new RegExp(`^rgba\\(${de},${de},${de},${ue}\\)$`),
+    be = new RegExp(`^hsl\\(${ue},${de},${de}\\)$`),
+    _e = new RegExp(`^hsla\\(${ue},${de},${de},${ue}\\)$`),
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+      antiquewhite: 16444375,
+      aqua: 65535,
+      aquamarine: 8388564,
+      azure: 15794175,
+      beige: 16119260,
+      bisque: 16770244,
+      black: 0,
+      blanchedalmond: 16772045,
+      blue: 255,
+      blueviolet: 9055202,
+      brown: 10824234,
+      burlywood: 14596231,
+      cadetblue: 6266528,
+      chartreuse: 8388352,
+      chocolate: 13789470,
+      coral: 16744272,
+      cornflowerblue: 6591981,
+      cornsilk: 16775388,
+      crimson: 14423100,
+      cyan: 65535,
+      darkblue: 139,
+      darkcyan: 35723,
+      darkgoldenrod: 12092939,
+      darkgray: 11119017,
+      darkgreen: 25600,
+      darkgrey: 11119017,
+      darkkhaki: 12433259,
+      darkmagenta: 9109643,
+      darkolivegreen: 5597999,
+      darkorange: 16747520,
+      darkorchid: 10040012,
+      darkred: 9109504,
+      darksalmon: 15308410,
+      darkseagreen: 9419919,
+      darkslateblue: 4734347,
+      darkslategray: 3100495,
+      darkslategrey: 3100495,
+      darkturquoise: 52945,
+      darkviolet: 9699539,
+      deeppink: 16716947,
+      deepskyblue: 49151,
+      dimgray: 6908265,
+      dimgrey: 6908265,
+      dodgerblue: 2003199,
+      firebrick: 11674146,
+      floralwhite: 16775920,
+      forestgreen: 2263842,
+      fuchsia: 16711935,
+      gainsboro: 14474460,
+      ghostwhite: 16316671,
+      gold: 16766720,
+      goldenrod: 14329120,
+      gray: 8421504,
+      green: 32768,
+      greenyellow: 11403055,
+      grey: 8421504,
+      honeydew: 15794160,
+      hotpink: 16738740,
+      indianred: 13458524,
+      indigo: 4915330,
+      ivory: 16777200,
+      khaki: 15787660,
+      lavender: 15132410,
+      lavenderblush: 16773365,
+      lawngreen: 8190976,
+      lemonchiffon: 16775885,
+      lightblue: 11393254,
+      lightcoral: 15761536,
+      lightcyan: 14745599,
+      lightgoldenrodyellow: 16448210,
+      lightgray: 13882323,
+      lightgreen: 9498256,
+      lightgrey: 13882323,
+      lightpink: 16758465,
+      lightsalmon: 16752762,
+      lightseagreen: 2142890,
+      lightskyblue: 8900346,
+      lightslategray: 7833753,
+      lightslategrey: 7833753,
+      lightsteelblue: 11584734,
+      lightyellow: 16777184,
+      lime: 65280,
+      limegreen: 3329330,
+      linen: 16445670,
+      magenta: 16711935,
+      maroon: 8388608,
+      mediumaquamarine: 6737322,
+      mediumblue: 205,
+      mediumorchid: 12211667,
+      mediumpurple: 9662683,
+      mediumseagreen: 3978097,
+      mediumslateblue: 8087790,
+      mediumspringgreen: 64154,
+      mediumturquoise: 4772300,
+      mediumvioletred: 13047173,
+      midnightblue: 1644912,
+      mintcream: 16121850,
+      mistyrose: 16770273,
+      moccasin: 16770229,
+      navajowhite: 16768685,
+      navy: 128,
+      oldlace: 16643558,
+      olive: 8421376,
+      olivedrab: 7048739,
+      orange: 16753920,
+      orangered: 16729344,
+      orchid: 14315734,
+      palegoldenrod: 15657130,
+      palegreen: 10025880,
+      paleturquoise: 11529966,
+      palevioletred: 14381203,
+      papayawhip: 16773077,
+      peachpuff: 16767673,
+      peru: 13468991,
+      pink: 16761035,
+      plum: 14524637,
+      powderblue: 11591910,
+      purple: 8388736,
+      rebeccapurple: 6697881,
+      red: 16711680,
+      rosybrown: 12357519,
+      royalblue: 4286945,
+      saddlebrown: 9127187,
+      salmon: 16416882,
+      sandybrown: 16032864,
+      seagreen: 3050327,
+      seashell: 16774638,
+      sienna: 10506797,
+      silver: 12632256,
+      skyblue: 8900331,
+      slateblue: 6970061,
+      slategray: 7372944,
+      slategrey: 7372944,
+      snow: 16775930,
+      springgreen: 65407,
+      steelblue: 4620980,
+      tan: 13808780,
+      teal: 32896,
+      thistle: 14204888,
+      tomato: 16737095,
+      turquoise: 4251856,
+      violet: 15631086,
+      wheat: 16113331,
+      white: 16777215,
+      whitesmoke: 16119285,
+      yellow: 16776960,
+      yellowgreen: 10145074,
+    };
+  function ve() {
+    return this.rgb().formatHex();
+  }
+  function ke() {
+    return this.rgb().formatRgb();
+  }
+  function we(t) {
+    var e, n;
+    return t = (t + "").trim().toLowerCase(),
+      (e = pe.exec(t))
+        ? (n = e[1].length,
+          e = parseInt(e[1], 16),
+          6 === n
+            ? Te(e)
+            : 3 === n
+            ? new Ae(e >> 8 & 15 | e >> 4 & 240, e >> 4 & 15 | 240 & e, (15 & e) << 4 | 15 & e, 1)
+            : 8 === n
+            ? Ce(e >> 24 & 255, e >> 16 & 255, e >> 8 & 255, (255 & e) / 255)
+            : 4 === n
+            ? Ce(
+              e >> 12 & 15 | e >> 8 & 240,
+              e >> 8 & 15 | e >> 4 & 240,
+              e >> 4 & 15 | 240 & e,
+              ((15 & e) << 4 | 15 & e) / 255,
+            )
+            : null)
+        : (e = fe.exec(t))
+        ? new Ae(e[1], e[2], e[3], 1)
+        : (e = ge.exec(t))
+        ? new Ae(255 * e[1] / 100, 255 * e[2] / 100, 255 * e[3] / 100, 1)
+        : (e = ye.exec(t))
+        ? Ce(e[1], e[2], e[3], e[4])
+        : (e = me.exec(t))
+        ? Ce(255 * e[1] / 100, 255 * e[2] / 100, 255 * e[3] / 100, e[4])
+        : (e = be.exec(t))
+        ? Be(e[1], e[2] / 100, e[3] / 100, 1)
+        : (e = _e.exec(t))
+        ? Be(e[1], e[2] / 100, e[3] / 100, e[4])
+        : xe.hasOwnProperty(t)
+        ? Te(xe[t])
+        : "transparent" === t
+        ? new Ae(NaN, NaN, NaN, 0)
+        : null;
+  }
+  function Te(t) {
+    return new Ae(t >> 16 & 255, t >> 8 & 255, 255 & t, 1);
+  }
+  function Ce(t, e, n, i) {
+    return i <= 0 && (t = e = n = NaN), new Ae(t, e, n, i);
+  }
+  function Ee(t) {
+    return t instanceof oe || (t = we(t)), t ? new Ae((t = t.rgb()).r, t.g, t.b, t.opacity) : new Ae();
+  }
+  function Se(t, e, n, i) {
+    return 1 === arguments.length ? Ee(t) : new Ae(t, e, n, null == i ? 1 : i);
+  }
+  function Ae(t, e, n, i) {
+    this.r = +t, this.g = +e, this.b = +n, this.opacity = +i;
+  }
+  function De() {
+    return `#${Me(this.r)}${Me(this.g)}${Me(this.b)}`;
+  }
+  function Le() {
+    const t = Oe(this.opacity);
+    return `${1 === t ? "rgb(" : "rgba("}${Ne(this.r)}, ${Ne(this.g)}, ${Ne(this.b)}${1 === t ? ")" : `, ${t})`}`;
+  }
+  function Oe(t) {
+    return isNaN(t) ? 1 : Math.max(0, Math.min(1, t));
+  }
+  function Ne(t) {
+    return Math.max(0, Math.min(255, Math.round(t) || 0));
+  }
+  function Me(t) {
+    return ((t = Ne(t)) < 16 ? "0" : "") + t.toString(16);
+  }
+  function Be(t, e, n, i) {
+    return i <= 0 ? t = e = n = NaN : n <= 0 || n >= 1 ? t = e = NaN : e <= 0 && (t = NaN), new Fe(t, e, n, i);
+  }
+  function Ie(t) {
+    if (t instanceof Fe) return new Fe(t.h, t.s, t.l, t.opacity);
+    if (t instanceof oe || (t = we(t)), !t) return new Fe();
+    if (t instanceof Fe) return t;
+    var e = (t = t.rgb()).r / 255,
+      n = t.g / 255,
+      i = t.b / 255,
+      r = Math.min(e, n, i),
+      a = Math.max(e, n, i),
+      s = NaN,
+      o = a - r,
+      l = (a + r) / 2;
+    return o
+      ? (s = e === a ? (n - i) / o + 6 * (n < i) : n === a ? (i - e) / o + 2 : (e - n) / o + 4,
+        o /= l < .5 ? a + r : 2 - a - r,
+        s *= 60)
+      : o = l > 0 && l < 1 ? 0 : s,
+      new Fe(s, o, l, t.opacity);
+  }
+  function Fe(t, e, n, i) {
+    this.h = +t, this.s = +e, this.l = +n, this.opacity = +i;
+  }
+  function Re(t) {
+    return (t = (t || 0) % 360) < 0 ? t + 360 : t;
+  }
+  function $e(t) {
+    return Math.max(0, Math.min(1, t || 0));
+  }
+  function Pe(t, e, n) {
+    return 255 * (t < 60 ? e + (n - e) * t / 60 : t < 180 ? n : t < 240 ? e + (n - e) * (240 - t) / 60 : e);
+  }
+  ae(oe, we, {
+    copy(t) {
+      return Object.assign(new this.constructor(), this, t);
+    },
+    displayable() {
+      return this.rgb().displayable();
+    },
+    hex: ve,
+    formatHex: ve,
+    formatHex8: function() {
+      return this.rgb().formatHex8();
+    },
+    formatHsl: function() {
+      return Ie(this).formatHsl();
+    },
+    formatRgb: ke,
+    toString: ke,
+  }),
+    ae(
+      Ae,
+      Se,
+      se(oe, {
+        brighter(t) {
+          return t = null == t ? ce : Math.pow(ce, t), new Ae(this.r * t, this.g * t, this.b * t, this.opacity);
+        },
+        darker(t) {
+          return t = null == t ? le : Math.pow(le, t), new Ae(this.r * t, this.g * t, this.b * t, this.opacity);
+        },
+        rgb() {
+          return this;
+        },
+        clamp() {
+          return new Ae(Ne(this.r), Ne(this.g), Ne(this.b), Oe(this.opacity));
+        },
+        displayable() {
+          return -.5 <= this.r && this.r < 255.5 && -.5 <= this.g && this.g < 255.5 && -.5 <= this.b && this.b < 255.5
+            && 0 <= this.opacity && this.opacity <= 1;
+        },
+        hex: De,
+        formatHex: De,
+        formatHex8: function() {
+          return `#${Me(this.r)}${Me(this.g)}${Me(this.b)}${Me(255 * (isNaN(this.opacity) ? 1 : this.opacity))}`;
+        },
+        formatRgb: Le,
+        toString: Le,
+      }),
+    ),
+    ae(
+      Fe,
+      function(t, e, n, i) {
+        return 1 === arguments.length ? Ie(t) : new Fe(t, e, n, null == i ? 1 : i);
+      },
+      se(oe, {
+        brighter(t) {
+          return t = null == t ? ce : Math.pow(ce, t), new Fe(this.h, this.s, this.l * t, this.opacity);
+        },
+        darker(t) {
+          return t = null == t ? le : Math.pow(le, t), new Fe(this.h, this.s, this.l * t, this.opacity);
+        },
+        rgb() {
+          var t = this.h % 360 + 360 * (this.h < 0),
+            e = isNaN(t) || isNaN(this.s) ? 0 : this.s,
+            n = this.l,
+            i = n + (n < .5 ? n : 1 - n) * e,
+            r = 2 * n - i;
+          return new Ae(
+            Pe(t >= 240 ? t - 240 : t + 120, r, i),
+            Pe(t, r, i),
+            Pe(t < 120 ? t + 240 : t - 120, r, i),
+            this.opacity,
+          );
+        },
+        clamp() {
+          return new Fe(Re(this.h), $e(this.s), $e(this.l), Oe(this.opacity));
+        },
+        displayable() {
+          return (0 <= this.s && this.s <= 1 || isNaN(this.s)) && 0 <= this.l && this.l <= 1 && 0 <= this.opacity
+            && this.opacity <= 1;
+        },
+        formatHsl() {
+          const t = Oe(this.opacity);
+          return `${1 === t ? "hsl(" : "hsla("}${Re(this.h)}, ${100 * $e(this.s)}%, ${100 * $e(this.l)}%${
+            1 === t ? ")" : `, ${t})`
+          }`;
+        },
+      }),
+    );
+  const Ye = Math.PI / 180,
+    je = 180 / Math.PI,
+    ze = .96422,
+    Ue = 1,
+    We = .82521,
+    He = 4 / 29,
+    qe = 6 / 29,
+    Ve = 3 * qe * qe,
+    Ge = qe * qe * qe;
+  function Xe(t) {
+    if (t instanceof Ze) return new Ze(t.l, t.a, t.b, t.opacity);
+    if (t instanceof nn) return rn(t);
+    t instanceof Ae || (t = Ee(t));
+    var e, n, i = tn(t.r), r = tn(t.g), a = tn(t.b), s = Qe((.2225045 * i + .7168786 * r + .0606169 * a) / Ue);
+    return i === r && r === a
+      ? e = n = s
+      : (e = Qe((.4360747 * i + .3850649 * r + .1430804 * a) / ze),
+        n = Qe((.0139322 * i + .0971045 * r + .7141733 * a) / We)),
+      new Ze(116 * s - 16, 500 * (e - s), 200 * (s - n), t.opacity);
+  }
+  function Ze(t, e, n, i) {
+    this.l = +t, this.a = +e, this.b = +n, this.opacity = +i;
+  }
+  function Qe(t) {
+    return t > Ge ? Math.pow(t, 1 / 3) : t / Ve + He;
+  }
+  function Ke(t) {
+    return t > qe ? t * t * t : Ve * (t - He);
+  }
+  function Je(t) {
+    return 255 * (t <= .0031308 ? 12.92 * t : 1.055 * Math.pow(t, 1 / 2.4) - .055);
+  }
+  function tn(t) {
+    return (t /= 255) <= .04045 ? t / 12.92 : Math.pow((t + .055) / 1.055, 2.4);
+  }
+  function en(t, e, n, i) {
+    return 1 === arguments.length
+      ? function(t) {
+        if (t instanceof nn) return new nn(t.h, t.c, t.l, t.opacity);
+        if (t instanceof Ze || (t = Xe(t)), 0 === t.a && 0 === t.b) {
+          return new nn(NaN, 0 < t.l && t.l < 100 ? 0 : NaN, t.l, t.opacity);
+        }
+        var e = Math.atan2(t.b, t.a) * je;
+        return new nn(e < 0 ? e + 360 : e, Math.sqrt(t.a * t.a + t.b * t.b), t.l, t.opacity);
+      }(t)
+      : new nn(t, e, n, null == i ? 1 : i);
+  }
+  function nn(t, e, n, i) {
+    this.h = +t, this.c = +e, this.l = +n, this.opacity = +i;
+  }
+  function rn(t) {
+    if (isNaN(t.h)) {
+      return new Ze(t.l, 0, 0, t.opacity);
+    }
+    var e = t.h * Ye;
+    return new Ze(t.l, Math.cos(e) * t.c, Math.sin(e) * t.c, t.opacity);
+  }
+  ae(
+    Ze,
+    function(t, e, n, i) {
+      return 1 === arguments.length ? Xe(t) : new Ze(t, e, n, null == i ? 1 : i);
+    },
+    se(oe, {
+      brighter(t) {
+        return new Ze(this.l + 18 * (null == t ? 1 : t), this.a, this.b, this.opacity);
+      },
+      darker(t) {
+        return new Ze(this.l - 18 * (null == t ? 1 : t), this.a, this.b, this.opacity);
+      },
+      rgb() {
+        var t = (this.l + 16) / 116, e = isNaN(this.a) ? t : t + this.a / 500, n = isNaN(this.b) ? t : t - this.b / 200;
+        return new Ae(
+          Je(3.1338561 * (e = ze * Ke(e)) - 1.6168667 * (t = Ue * Ke(t)) - .4906146 * (n = We * Ke(n))),
+          Je(-.9787684 * e + 1.9161415 * t + .033454 * n),
+          Je(.0719453 * e - .2289914 * t + 1.4052427 * n),
+          this.opacity,
+        );
+      },
+    }),
+  ),
+    ae(
+      nn,
+      en,
+      se(oe, {
+        brighter(t) {
+          return new nn(this.h, this.c, this.l + 18 * (null == t ? 1 : t), this.opacity);
+        },
+        darker(t) {
+          return new nn(this.h, this.c, this.l - 18 * (null == t ? 1 : t), this.opacity);
+        },
+        rgb() {
+          return rn(this).rgb();
+        },
+      }),
+    );
+  var an = t => () => t;
+  function sn(t, e) {
+    return function(n) {
+      return t + n * e;
+    };
+  }
+  function on(t) {
+    return 1 == (t = +t) ? ln : function(e, n) {
+      return n - e
+        ? function(t, e, n) {
+          return t = Math.pow(t, n), e = Math.pow(e, n) - t, n = 1 / n, function(i) {
+            return Math.pow(t + i * e, n);
+          };
+        }(e, n, t)
+        : an(isNaN(e) ? n : e);
+    };
+  }
+  function ln(t, e) {
+    var n = e - t;
+    return n ? sn(t, n) : an(isNaN(t) ? e : t);
+  }
+  var cn = function t(e) {
+    var n = on(e);
+    function i(t, e) {
+      var i = n((t = Se(t)).r, (e = Se(e)).r), r = n(t.g, e.g), a = n(t.b, e.b), s = ln(t.opacity, e.opacity);
+      return function(e) {
+        return t.r = i(e), t.g = r(e), t.b = a(e), t.opacity = s(e), t + "";
+      };
+    }
+    return i.gamma = t, i;
+  }(1);
+  function hn(t, e) {
+    e || (e = []);
+    var n, i = t ? Math.min(e.length, t.length) : 0, r = e.slice();
+    return function(a) {
+      for (n = 0; n < i; ++n) r[n] = t[n] * (1 - a) + e[n] * a;
+      return r;
+    };
+  }
+  function un(t, e) {
+    var n, i = e ? e.length : 0, r = t ? Math.min(i, t.length) : 0, a = new Array(r), s = new Array(i);
+    for (n = 0; n < r; ++n) a[n] = bn(t[n], e[n]);
+    for (; n < i; ++n) s[n] = e[n];
+    return function(t) {
+      for (n = 0; n < r; ++n) s[n] = a[n](t);
+      return s;
+    };
+  }
+  function dn(t, e) {
+    var n = new Date();
+    return t = +t, e = +e, function(i) {
+      return n.setTime(t * (1 - i) + e * i), n;
+    };
+  }
+  function pn(t, e) {
+    return t = +t, e = +e, function(n) {
+      return t * (1 - n) + e * n;
+    };
+  }
+  function fn(t, e) {
+    var n, i = {}, r = {};
+    for (n in null !== t && "object" == typeof t || (t = {}), null !== e && "object" == typeof e || (e = {}), e) {
+      n in t
+        ? i[n] = bn(t[n], e[n])
+        : r[n] = e[n];
+    }
+    return function(t) {
+      for (n in i) r[n] = i[n](t);
+      return r;
+    };
+  }
+  var gn = /[-+]?(?:\d+\.?\d*|\.?\d+)(?:[eE][-+]?\d+)?/g, yn = new RegExp(gn.source, "g");
+  function mn(t, e) {
+    var n, i, r, a = gn.lastIndex = yn.lastIndex = 0, s = -1, o = [], l = [];
+    for (t += "", e += ""; (n = gn.exec(t)) && (i = yn.exec(e));) {
+      (r = i.index) > a && (r = e.slice(a, r), o[s] ? o[s] += r : o[++s] = r),
+        (n = n[0]) === (i = i[0]) ? o[s] ? o[s] += i : o[++s] = i : (o[++s] = null, l.push({ i: s, x: pn(n, i) })),
+        a = yn.lastIndex;
+    }
+    return a < e.length && (r = e.slice(a), o[s] ? o[s] += r : o[++s] = r),
+      o.length < 2
+        ? l[0]
+          ? function(t) {
+            return function(e) {
+              return t(e) + "";
+            };
+          }(l[0].x)
+          : function(t) {
+            return function() {
+              return t;
+            };
+          }(e)
+        : (e = l.length, function(t) {
+          for (var n, i = 0; i < e; ++i) o[(n = l[i]).i] = n.x(t);
+          return o.join("");
+        });
+  }
+  function bn(t, e) {
+    var n, i = typeof e;
+    return null == e || "boolean" === i
+      ? an(e)
+      : ("number" === i
+        ? pn
+        : "string" === i
+        ? (n = we(e)) ? (e = n, cn) : mn
+        : e instanceof we
+        ? cn
+        : e instanceof Date
+        ? dn
+        : (function(t) {
+            return ArrayBuffer.isView(t) && !(t instanceof DataView);
+          })(e)
+        ? hn
+        : Array.isArray(e)
+        ? un
+        : "function" != typeof e.valueOf && "function" != typeof e.toString || isNaN(e)
+        ? fn
+        : pn)(t, e);
+  }
+  function _n(t, e) {
+    return t = +t, e = +e, function(n) {
+      return Math.round(t * (1 - n) + e * n);
+    };
+  }
+  var xn, vn = 180 / Math.PI, kn = { translateX: 0, translateY: 0, rotate: 0, skewX: 0, scaleX: 1, scaleY: 1 };
+  function wn(t, e, n, i, r, a) {
+    var s, o, l;
+    return (s = Math.sqrt(t * t + e * e)) && (t /= s, e /= s),
+      (l = t * n + e * i) && (n -= t * l, i -= e * l),
+      (o = Math.sqrt(n * n + i * i)) && (n /= o, i /= o, l /= o),
+      t * i < e * n && (t = -t, e = -e, l = -l, s = -s),
+      { translateX: r, translateY: a, rotate: Math.atan2(e, t) * vn, skewX: Math.atan(l) * vn, scaleX: s, scaleY: o };
+  }
+  function Tn(t, e, n, i) {
+    function r(t) {
+      return t.length ? t.pop() + " " : "";
+    }
+    return function(a, s) {
+      var o = [], l = [];
+      return a = t(a),
+        s = t(s),
+        function(t, i, r, a, s, o) {
+          if (t !== r || i !== a) {
+            var l = s.push("translate(", null, e, null, n);
+            o.push({ i: l - 4, x: pn(t, r) }, { i: l - 2, x: pn(i, a) });
+          } else (r || a) && s.push("translate(" + r + e + a + n);
+        }(a.translateX, a.translateY, s.translateX, s.translateY, o, l),
+        function(t, e, n, a) {
+          t !== e
+            ? (t - e > 180 ? e += 360 : e - t > 180 && (t += 360),
+              a.push({ i: n.push(r(n) + "rotate(", null, i) - 2, x: pn(t, e) }))
+            : e && n.push(r(n) + "rotate(" + e + i);
+        }(a.rotate, s.rotate, o, l),
+        function(t, e, n, a) {
+          t !== e
+            ? a.push({ i: n.push(r(n) + "skewX(", null, i) - 2, x: pn(t, e) })
+            : e && n.push(r(n) + "skewX(" + e + i);
+        }(a.skewX, s.skewX, o, l),
+        function(t, e, n, i, a, s) {
+          if (t !== n || e !== i) {
+            var o = a.push(r(a) + "scale(", null, ",", null, ")");
+            s.push({ i: o - 4, x: pn(t, n) }, { i: o - 2, x: pn(e, i) });
+          } else 1 === n && 1 === i || a.push(r(a) + "scale(" + n + "," + i + ")");
+        }(a.scaleX, a.scaleY, s.scaleX, s.scaleY, o, l),
+        a = s = null,
+        function(t) {
+          for (var e, n = -1, i = l.length; ++n < i;) o[(e = l[n]).i] = e.x(t);
+          return o.join("");
+        };
+    };
+  }
+  var Cn = Tn(
+      function(t) {
+        const e = new ("function" == typeof DOMMatrix ? DOMMatrix : WebKitCSSMatrix)(t + "");
+        return e.isIdentity ? kn : wn(e.a, e.b, e.c, e.d, e.e, e.f);
+      },
+      "px, ",
+      "px)",
+      "deg)",
+    ),
+    En = Tn(
+      function(t) {
+        return null == t
+          ? kn
+          : (xn || (xn = document.createElementNS("http://www.w3.org/2000/svg", "g")),
+            xn.setAttribute("transform", t),
+            (t = xn.transform.baseVal.consolidate()) ? wn((t = t.matrix).a, t.b, t.c, t.d, t.e, t.f) : kn);
+      },
+      ", ",
+      ")",
+      ")",
+    );
+  var Sn,
+    An,
+    Dn = function(t) {
+      return function(e, n) {
+        var i = t((e = en(e)).h, (n = en(n)).h), r = ln(e.c, n.c), a = ln(e.l, n.l), s = ln(e.opacity, n.opacity);
+        return function(t) {
+          return e.h = i(t), e.c = r(t), e.l = a(t), e.opacity = s(t), e + "";
+        };
+      };
+    }(function(t, e) {
+      var n = e - t;
+      return n ? sn(t, n > 180 || n < -180 ? n - 360 * Math.round(n / 360) : n) : an(isNaN(t) ? e : t);
+    }),
+    Ln = 0,
+    On = 0,
+    Nn = 0,
+    Mn = 1e3,
+    Bn = 0,
+    In = 0,
+    Fn = 0,
+    Rn = "object" == typeof performance && performance.now ? performance : Date,
+    $n = "object" == typeof window && window.requestAnimationFrame
+      ? window.requestAnimationFrame.bind(window)
+      : function(t) {
+        setTimeout(t, 17);
+      };
+  function Pn() {
+    return In || ($n(Yn), In = Rn.now() + Fn);
+  }
+  function Yn() {
+    In = 0;
+  }
+  function jn() {
+    this._call = this._time = this._next = null;
+  }
+  function zn(t, e, n) {
+    var i = new jn();
+    return i.restart(t, e, n), i;
+  }
+  function Un() {
+    In = (Bn = Rn.now()) + Fn, Ln = On = 0;
+    try {
+      !function() {
+        Pn(), ++Ln;
+        for (var t, e = Sn; e;) (t = In - e._time) >= 0 && e._call.call(void 0, t), e = e._next;
+        --Ln;
+      }();
+    } finally {
+      Ln = 0,
+        function() {
+          var t, e, n = Sn, i = 1 / 0;
+          for (; n;) {
+            n._call
+              ? (i > n._time && (i = n._time), t = n, n = n._next)
+              : (e = n._next, n._next = null, n = t ? t._next = e : Sn = e);
+          }
+          An = t, Hn(i);
+        }(),
+        In = 0;
+    }
+  }
+  function Wn() {
+    var t = Rn.now(), e = t - Bn;
+    e > Mn && (Fn -= e, Bn = t);
+  }
+  function Hn(t) {
+    Ln
+      || (On && (On = clearTimeout(On)),
+        t - In > 24
+          ? (t < 1 / 0 && (On = setTimeout(Un, t - Rn.now() - Fn)), Nn && (Nn = clearInterval(Nn)))
+          : (Nn || (Bn = Rn.now(), Nn = setInterval(Wn, Mn)), Ln = 1, $n(Un)));
+  }
+  function qn(t, e, n) {
+    var i = new jn();
+    return e = null == e ? 0 : +e,
+      i.restart(
+        n => {
+          i.stop(), t(n + e);
+        },
+        e,
+        n,
+      ),
+      i;
+  }
+  jn.prototype = zn.prototype = {
+    constructor: jn,
+    restart: function(t, e, n) {
+      if ("function" != typeof t) throw new TypeError("callback is not a function");
+      n = (null == n ? Pn() : +n) + (null == e ? 0 : +e),
+        this._next || An === this || (An ? An._next = this : Sn = this, An = this),
+        this._call = t,
+        this._time = n,
+        Hn();
+    },
+    stop: function() {
+      this._call && (this._call = null, this._time = 1 / 0, Hn());
+    },
+  };
+  var Vn = j("start", "end", "cancel", "interrupt"), Gn = [], Xn = 0, Zn = 1, Qn = 2, Kn = 3, Jn = 4, ti = 5, ei = 6;
+  function ni(t, e, n, i, r, a) {
+    var s = t.__transition;
+    if (s) {
+      if (n in s) return;
+      else t.__transition = {};
+    }
+    !function(t, e, n) {
+      var i, r = t.__transition;
+      function a(t) {
+        n.state = Zn, n.timer.restart(s, n.delay, n.time), n.delay <= t && s(t - n.delay);
+      }
+      function s(a) {
+        var c, h, u, d;
+        if (n.state !== Zn) return l();
+        for (c in r) {
+          if ((d = r[c]).name === n.name) {
+            if (d.state === Kn) return qn(s);
+            d.state === Jn
+              ? (d.state = ei, d.timer.stop(), d.on.call("interrupt", t, t.__data__, d.index, d.group), delete r[c])
+              : +c < e
+                && (d.state = ei, d.timer.stop(), d.on.call("cancel", t, t.__data__, d.index, d.group), delete r[c]);
+          }
+        }
+        if (
+          qn(function() {
+            n.state === Kn && (n.state = Jn, n.timer.restart(o, n.delay, n.time), o(a));
+          }),
+            n.state = Qn,
+            n.on.call("start", t, t.__data__, n.index, n.group),
+            n.state === Qn
+        ) {
+          for (n.state = Kn, i = new Array(u = n.tween.length), c = 0, h = -1; c < u; ++c) {
+            (d = n.tween[c].value.call(t, t.__data__, n.index, n.group)) && (i[++h] = d);
+          }
+          i.length = h + 1;
+        }
+      }
+      function o(e) {
+        for (
+          var r = e < n.duration ? n.ease.call(null, e / n.duration) : (n.timer.restart(l), n.state = ti, 1),
+            a = -1,
+            s = i.length;
+          ++a < s;
+        ) i[a].call(t, r);
+        n.state === ti && (n.on.call("end", t, t.__data__, n.index, n.group), l());
+      }
+      function l() {
+        for (var i in n.state = ei, n.timer.stop(), delete r[e], r) return;
+        delete t.__transition;
+      }
+      r[e] = n, n.timer = zn(a, 0, n.time);
+    }(t, n, {
+      name: e,
+      index: i,
+      group: r,
+      on: Vn,
+      tween: Gn,
+      time: a.time,
+      delay: a.delay,
+      duration: a.duration,
+      ease: a.ease,
+      timer: null,
+      state: Xn,
+    });
+  }
+  function ii(t, e) {
+    var n = ai(t, e);
+    if (n.state > Xn) throw new Error("too late; already scheduled");
+    return n;
+  }
+  function ri(t, e) {
+    var n = ai(t, e);
+    if (n.state > Kn) throw new Error("too late; already running");
+    return n;
+  }
+  function ai(t, e) {
+    var n = t.__transition;
+    if (!n || !(n = n[e])) throw new Error("transition not found");
+    return n;
+  }
+  function si(t, e) {
+    var n, i;
+    return function() {
+      var r = ri(this, t), a = r.tween;
+      if (a !== n) {
+        for (var s = 0, o = (i = n = a).length; s < o; ++s) {
+          if (i[s].name === e) {
+            (i = i.slice()).splice(s, 1);
+            break;
+          }
+        }
+      }
+      r.tween = i;
+    };
+  }
+  function oi(t, e, n) {
+    var i, r;
+    if ("function" != typeof n) throw new Error();
+    return function() {
+      var a = ri(this, t), s = a.tween;
+      if (s !== i) {
+        r = (i = s).slice();
+        for (var o = { name: e, value: n }, l = 0, c = r.length; l < c; ++l) {
+          if (r[l].name === e) {
+            r[l] = o;
+            break;
+          }
+        }
+        l === c && r.push(o);
+      }
+      a.tween = r;
+    };
+  }
+  function li(t, e, n) {
+    var i = t._id;
+    return t.each(function() {
+      var t = ri(this, i);
+      (t.value || (t.value = {}))[e] = n.apply(this, arguments);
+    }),
+      function(t) {
+        return ai(t, i).value[e];
+      };
+  }
+  function ci(t, e) {
+    var n;
+    return ("number" == typeof e ? pn : e instanceof we ? cn : (n = we(e)) ? (e = n, cn) : mn)(t, e);
+  }
+  function hi(t) {
+    return function() {
+      this.removeAttribute(t);
+    };
+  }
+  function ui(t) {
+    return function() {
+      this.removeAttributeNS(t.space, t.local);
+    };
+  }
+  function di(t, e, n) {
+    var i, r, a = n + "";
+    return function() {
+      var s = this.getAttribute(t);
+      return s === a ? null : s === i ? r : r = e(i = s, n);
+    };
+  }
+  function pi(t, e, n) {
+    var i, r, a = n + "";
+    return function() {
+      var s = this.getAttributeNS(t.space, t.local);
+      return s === a ? null : s === i ? r : r = e(i = s, n);
+    };
+  }
+  function fi(t, e, n) {
+    var i, r, a;
+    return function() {
+      var s, o, l = n(this);
+      if (null != l) {
+        return (s = this.getAttribute(t)) === (o = l + "")
+          ? null
+          : s === i && o === r
+          ? a
+          : (r = o, a = e(i = s, l));
+      }
+      this.removeAttribute(t);
+    };
+  }
+  function gi(t, e, n) {
+    var i, r, a;
+    return function() {
+      var s, o, l = n(this);
+      if (null != l) {
+        return (s = this.getAttributeNS(t.space, t.local)) === (o = l + "")
+          ? null
+          : s === i && o === r
+          ? a
+          : (r = o, a = e(i = s, l));
+      }
+      this.removeAttributeNS(t.space, t.local);
+    };
+  }
+  function yi(t, e) {
+    var n, i;
+    function r() {
+      var r = e.apply(this, arguments);
+      return r !== i && (n = (i = r) && function(t, e) {
+        return function(n) {
+          this.setAttributeNS(t.space, t.local, e.call(this, n));
+        };
+      }(t, r)),
+        n;
+    }
+    return r._value = e, r;
+  }
+  function mi(t, e) {
+    var n, i;
+    function r() {
+      var r = e.apply(this, arguments);
+      return r !== i && (n = (i = r) && function(t, e) {
+        return function(n) {
+          this.setAttribute(t, e.call(this, n));
+        };
+      }(t, r)),
+        n;
+    }
+    return r._value = e, r;
+  }
+  function bi(t, e) {
+    return function() {
+      ii(this, t).delay = +e.apply(this, arguments);
+    };
+  }
+  function _i(t, e) {
+    return e = +e, function() {
+      ii(this, t).delay = e;
+    };
+  }
+  function xi(t, e) {
+    return function() {
+      ri(this, t).duration = +e.apply(this, arguments);
+    };
+  }
+  function vi(t, e) {
+    return e = +e, function() {
+      ri(this, t).duration = e;
+    };
+  }
+  var ki = ne.prototype.constructor;
+  function wi(t) {
+    return function() {
+      this.style.removeProperty(t);
+    };
+  }
+  var Ti = 0;
+  function Ci(t, e, n, i) {
+    this._groups = t, this._parents = e, this._name = n, this._id = i;
+  }
+  function Ei() {
+    return ++Ti;
+  }
+  var Si = ne.prototype;
+  Ci.prototype = {
+    constructor: Ci,
+    select: function(t) {
+      var e = this._name, n = this._id;
+      "function" != typeof t && (t = K(t));
+      for (var i = this._groups, r = i.length, a = new Array(r), s = 0; s < r; ++s) {
+        for (var o, l, c = i[s], h = c.length, u = a[s] = new Array(h), d = 0; d < h; ++d) {
+          (o = c[d]) && (l = t.call(o, o.__data__, d, c))
+            && ("__data__" in o && (l.__data__ = o.__data__), u[d] = l, ni(u[d], e, n, d, u, ai(o, n)));
+        }
+      }
+      return new Ci(a, this._parents, e, n);
+    },
+    selectAll: function(t) {
+      var e = this._name, n = this._id;
+      "function" != typeof t && (t = et(t));
+      for (var i = this._groups, r = i.length, a = [], s = [], o = 0; o < r; ++o) {
+        for (var l, c = i[o], h = c.length, u = 0; u < h; ++u) {
+          if (l = c[u]) {
+            for (var d, p = t.call(l, l.__data__, u, c), f = ai(l, n), g = 0, y = p.length; g < y; ++g) {
+              (d = p[g]) && ni(d, e, n, g, p, f);
+            }
+            a.push(p), s.push(l);
+          }
+        }
+      }
+      return new Ci(a, s, e, n);
+    },
+    selectChild: Si.selectChild,
+    selectChildren: Si.selectChildren,
+    filter: function(t) {
+      "function" != typeof t && (t = nt(t));
+      for (var e = this._groups, n = e.length, i = new Array(n), r = 0; r < n; ++r) {
+        for (var a, s = e[r], o = s.length, l = i[r] = [], c = 0; c < o; ++c) {
+          (a = s[c]) && t.call(a, a.__data__, c, s) && l.push(a);
+        }
+      }
+      return new Ci(i, this._parents, this._name, this._id);
+    },
+    merge: function(t) {
+      if (t._id !== this._id) throw new Error();
+      for (
+        var e = this._groups, n = t._groups, i = e.length, r = n.length, a = Math.min(i, r), s = new Array(i), o = 0;
+        o < a;
+        ++o
+      ) {
+        for (var l, c = e[o], h = n[o], u = c.length, d = s[o] = new Array(u), p = 0; p < u; ++p) {
+          (l = c[p] || h[p]) && (d[p] = l);
+        }
+      }
+      for (; o < i; ++o) s[o] = e[o];
+      return new Ci(s, this._parents, this._name, this._id);
+    },
+    selection: function() {
+      return new ki(this._groups, this._parents);
+    },
+    transition: function() {
+      for (var t = this._name, e = this._id, n = Ei(), i = this._groups, r = i.length, a = 0; a < r; ++a) {
+        for (var s, o = i[a], l = o.length, c = 0; c < l; ++c) {
+          if (s = o[c]) {
+            var h = ai(s, e);
+            ni(s, t, n, c, o, { time: h.time + h.delay + h.duration, delay: 0, duration: h.duration, ease: h.ease });
+          }
+        }
+      }
+      return new Ci(i, this._parents, t, n);
+    },
+    call: Si.call,
+    nodes: Si.nodes,
+    node: Si.node,
+    size: Si.size,
+    empty: Si.empty,
+    each: Si.each,
+    on: function(t, e) {
+      var n = this._id;
+      return arguments.length < 2 ? ai(this.node(), n).on.on(t) : this.each(function(t, e, n) {
+        var i,
+          r,
+          a = (function(t) {
+              return (t + "").trim().split(/^|\s+/).every(function(t) {
+                var e = t.indexOf(".");
+                return e >= 0 && (t = t.slice(0, e)), !t || "start" === t;
+              });
+            })(e)
+            ? ii
+            : ri;
+        return function() {
+          var s = a(this, t), o = s.on;
+          o !== i && (r = (i = o).copy()).on(e, n), s.on = r;
+        };
+      }(n, t, e));
+    },
+    attr: function(t, e) {
+      var n = V(t), i = "transform" === n ? En : ci;
+      return this.attrTween(
+        t,
+        "function" == typeof e
+          ? (n.local ? gi : fi)(n, i, li(this, "attr." + t, e))
+          : null == e
+          ? (n.local ? ui : hi)(n)
+          : (n.local ? pi : di)(n, i, e),
+      );
+    },
+    attrTween: function(t, e) {
+      var n = "attr." + t;
+      if (arguments.length < 2) return (n = this.tween(n)) && n._value;
+      if (null == e) return this.tween(n, null);
+      if ("function" != typeof e) throw new Error();
+      var i = V(t);
+      return this.tween(n, (i.local ? yi : mi)(i, e));
+    },
+    style: function(t, e, n) {
+      var i = "transform" == (t += "") ? Cn : ci;
+      return null == e
+        ? this.styleTween(
+          t,
+          function(t, e) {
+            var n, i, r;
+            return function() {
+              var a = Ct(this, t), s = (this.style.removeProperty(t), Ct(this, t));
+              return a === s ? null : a === n && s === i ? r : r = e(n = a, i = s);
+            };
+          }(t, i),
+        ).on("end.style." + t, wi(t))
+        : "function" == typeof e
+        ? this.styleTween(
+          t,
+          function(t, e, n) {
+            var i, r, a;
+            return function() {
+              var s = Ct(this, t), o = n(this), l = o + "";
+              return null == o && (this.style.removeProperty(t), l = o = Ct(this, t)),
+                s === l ? null : s === i && l === r ? a : (r = l, a = e(i = s, o));
+            };
+          }(t, i, li(this, "style." + t, e)),
+        ).each(function(t, e) {
+          var n, i, r, a, s = "style." + e, o = "end." + s;
+          return function() {
+            var l = ri(this, t), c = l.on, h = null == l.value[s] ? a || (a = wi(e)) : void 0;
+            c === n && r === h || (i = (n = c).copy()).on(o, r = h), l.on = i;
+          };
+        }(this._id, t))
+        : this.styleTween(
+          t,
+          function(t, e, n) {
+            var i, r, a = n + "";
+            return function() {
+              var s = Ct(this, t);
+              return s === a ? null : s === i ? r : r = e(i = s, n);
+            };
+          }(t, i, e),
+          n,
+        ).on("end.style." + t, null);
+    },
+    styleTween: function(t, e, n) {
+      var i = "style." + (t += "");
+      if (arguments.length < 2) return (i = this.tween(i)) && i._value;
+      if (null == e) return this.tween(i, null);
+      if ("function" != typeof e) throw new Error();
+      return this.tween(
+        i,
+        function(t, e, n) {
+          var i, r;
+          function a() {
+            var a = e.apply(this, arguments);
+            return a !== r && (i = (r = a) && function(t, e, n) {
+              return function(i) {
+                this.style.setProperty(t, e.call(this, i), n);
+              };
+            }(t, a, n)),
+              i;
+          }
+          return a._value = e, a;
+        }(t, e, null == n ? "" : n),
+      );
+    },
+    text: function(t) {
+      return this.tween(
+        "text",
+        "function" == typeof t
+          ? function(t) {
+            return function() {
+              var e = t(this);
+              this.textContent = null == e ? "" : e;
+            };
+          }(li(this, "text", t))
+          : function(t) {
+            return function() {
+              this.textContent = t;
+            };
+          }(null == t ? "" : t + ""),
+      );
+    },
+    textTween: function(t) {
+      var e = "text";
+      if (arguments.length < 1) return (e = this.tween(e)) && e._value;
+      if (null == t) return this.tween(e, null);
+      if ("function" != typeof t) throw new Error();
+      return this.tween(
+        e,
+        function(t) {
+          var e, n;
+          function i() {
+            var i = t.apply(this, arguments);
+            return i !== n && (e = (n = i) && function(t) {
+              return function(e) {
+                this.textContent = t.call(this, e);
+              };
+            }(i)),
+              e;
+          }
+          return i._value = t, i;
+        }(t),
+      );
+    },
+    remove: function() {
+      return this.on(
+        "end.remove",
+        function(t) {
+          return function() {
+            var e = this.parentNode;
+            for (var n in this.__transition) if (+n !== t) return;
+            e && e.removeChild(this);
+          };
+        }(this._id),
+      );
+    },
+    tween: function(t, e) {
+      var n = this._id;
+      if (t += "", arguments.length < 2) {
+        for (var i, r = ai(this.node(), n).tween, a = 0, s = r.length; a < s; ++a) {
+          if ((i = r[a]).name === t) return i.value;
+        }
+        return null;
+      }
+      return this.each((null == e ? si : oi)(n, t, e));
+    },
+    delay: function(t) {
+      var e = this._id;
+      return arguments.length ? this.each(("function" == typeof t ? bi : _i)(e, t)) : ai(this.node(), e).delay;
+    },
+    duration: function(t) {
+      var e = this._id;
+      return arguments.length ? this.each(("function" == typeof t ? xi : vi)(e, t)) : ai(this.node(), e).duration;
+    },
+    ease: function(t) {
+      var e = this._id;
+      return arguments.length
+        ? this.each(function(t, e) {
+          if ("function" != typeof e) throw new Error();
+          return function() {
+            ri(this, t).ease = e;
+          };
+        }(e, t))
+        : ai(this.node(), e).ease;
+    },
+    easeVarying: function(t) {
+      if ("function" != typeof t) throw new Error();
+      return this.each(function(t, e) {
+        return function() {
+          var n = e.apply(this, arguments);
+          if ("function" != typeof n) throw new Error();
+          ri(this, t).ease = n;
+        };
+      }(this._id, t));
+    },
+    end: function() {
+      var t, e, n = this, i = n._id, r = n.size();
+      return new Promise(function(a, s) {
+        var o = { value: s },
+          l = {
+            value: function() {
+              0 == --r && a();
+            },
+          };
+        n.each(function() {
+          var n = ri(this, i), r = n.on;
+          r !== t && ((e = (t = r).copy())._.cancel.push(o), e._.interrupt.push(o), e._.end.push(l)), n.on = e;
+        }), 0 === r && a();
+      });
+    },
+    [Symbol.iterator]: Si[Symbol.iterator],
+  };
+  var Ai = {
+    time: null,
+    delay: 0,
+    duration: 250,
+    ease: function(t) {
+      return ((t *= 2) <= 1 ? t * t * t : (t -= 2) * t * t + 2) / 2;
+    },
+  };
+  function Di(t, e) {
+    for (var n; !(n = t.__transition) || !(n = n[e]);) {
+      if (!(t = t.parentNode)) throw new Error(`transition ${e} not found`);
+    }
+    return n;
+  }
+  ne.prototype.interrupt = function(t) {
+    return this.each(function() {
+      !function(t, e) {
+        var n, i, r, a = t.__transition, s = !0;
+        if (a) {
+          for (r in e = null == e ? null : e + "", a) {
+            (n = a[r]).name === e
+              ? (i = n.state > Qn && n.state < ti,
+                n.state = ei,
+                n.timer.stop(),
+                n.on.call(i ? "interrupt" : "cancel", t, t.__data__, n.index, n.group),
+                delete a[r])
+              : s = !1;
+          }
+          s && delete t.__transition;
+        }
+      }(this, t);
+    });
+  },
+    ne.prototype.transition = function(t) {
+      var e, n;
+      t instanceof Ci ? (e = t._id, t = t._name) : (e = Ei(), (n = Ai).time = Pn(), t = null == t ? null : t + "");
+      for (var i = this._groups, r = i.length, a = 0; a < r; ++a) {
+        for (var s, o = i[a], l = o.length, c = 0; c < l; ++c) {
+          (s = o[c]) && ni(s, t, e, c, o, n || Di(s, e));
+        }
+      }
+      return new Ci(i, this._parents, t, e);
+    };
+  const Li = Math.PI, Oi = 2 * Li, Ni = 1e-6, Mi = Oi - Ni;
+  function Bi(t) {
+    this._ += t[0];
+    for (let e = 1, n = t.length; e < n; ++e) this._ += arguments[e] + t[e];
+  }
+  class Ii {
+    constructor(t) {
+      this._x0 =
+        this._y0 =
+        this._x1 =
+        this._y1 =
+          null,
+        this._ = "",
+        this._append = null == t ? Bi : function(t) {
+          let e = Math.floor(t);
+          if (!(e >= 0)) throw new Error(`invalid digits: ${t}`);
+          if (e > 15) return Bi;
+          const n = 10 ** e;
+          return function(t) {
+            this._ += t[0];
+            for (let e = 1, i = t.length; e < i; ++e) this._ += Math.round(arguments[e] * n) / n + t[e];
+          };
+        }(t);
+    }
+    moveTo(t, e) {
+      this._append`M${this._x0 = this._x1 = +t},${this._y0 = this._y1 = +e}`;
+    }
+    closePath() {
+      null !== this._x1 && (this._x1 = this._x0, this._y1 = this._y0, this._append`Z`);
+    }
+    lineTo(t, e) {
+      this._append`L${this._x1 = +t},${this._y1 = +e}`;
+    }
+    quadraticCurveTo(t, e, n, i) {
+      this._append`Q${+t},${+e},${this._x1 = +n},${this._y1 = +i}`;
+    }
+    bezierCurveTo(t, e, n, i, r, a) {
+      this._append`C${+t},${+e},${+n},${+i},${this._x1 = +r},${this._y1 = +a}`;
+    }
+    arcTo(t, e, n, i, r) {
+      if (t = +t, e = +e, n = +n, i = +i, (r = +r) < 0) throw new Error(`negative radius: ${r}`);
+      let a = this._x1, s = this._y1, o = n - t, l = i - e, c = a - t, h = s - e, u = c * c + h * h;
+      if (null === this._x1) this._append`M${this._x1 = t},${this._y1 = e}`;
+      else if (u > Ni) {
+        if (Math.abs(h * o - l * c) > Ni && r) {
+          let d = n - a,
+            p = i - s,
+            f = o * o + l * l,
+            g = d * d + p * p,
+            y = Math.sqrt(f),
+            m = Math.sqrt(u),
+            b = r * Math.tan((Li - Math.acos((f + u - g) / (2 * y * m))) / 2),
+            _ = b / m,
+            x = b / y;
+          Math.abs(_ - 1) > Ni && this._append`L${t + _ * c},${e + _ * h}`,
+            this._append`A${r},${r},0,0,${+(h * d > c * p)},${this._x1 = t + x * o},${this._y1 = e + x * l}`;
+        } else this._append`L${this._x1 = t},${this._y1 = e}`;
+      } else;
+    }
+    arc(t, e, n, i, r, a) {
+      if (t = +t, e = +e, a = !!a, (n = +n) < 0) throw new Error(`negative radius: ${n}`);
+      let s = n * Math.cos(i), o = n * Math.sin(i), l = t + s, c = e + o, h = 1 ^ a, u = a ? i - r : r - i;
+      null === this._x1
+        ? this._append`M${l},${c}`
+        : (Math.abs(this._x1 - l) > Ni || Math.abs(this._y1 - c) > Ni) && this._append`L${l},${c}`,
+        n
+        && (u < 0 && (u = u % Oi + Oi),
+          u > Mi
+            ? this._append`A${n},${n},0,1,${h},${t - s},${e - o}A${n},${n},0,1,${h},${this._x1 = l},${this._y1 = c}`
+            : u > Ni
+              && this._append`A${n},${n},0,${+(u >= Li)},${h},${this._x1 = t + n * Math.cos(r)},${this._y1 = e
+                + n * Math.sin(r)}`);
+    }
+    rect(t, e, n, i) {
+      this._append`M${this._x0 = this._x1 = +t},${this._y0 = this._y1 = +e}h${n = +n}v${+i}h${-n}Z`;
+    }
+    toString() {
+      return this._;
+    }
+  }
+  function Fi(t) {
+    if (!t.ok) throw new Error(t.status + " " + t.statusText);
+    return t.text();
+  }
+  function Ri(t, e) {
+    if ((n = (t = e ? t.toExponential(e - 1) : t.toExponential()).indexOf("e")) < 0) return null;
+    var n, i = t.slice(0, n);
+    return [i.length > 1 ? i[0] + i.slice(2) : i, +t.slice(n + 1)];
+  }
+  function $i(t) {
+    return (t = Ri(Math.abs(t))) ? t[1] : NaN;
+  }
+  var Pi, Yi = /^(?:(.)?([<>=^]))?([+\-( ])?([$#])?(0)?(\d+)?(,)?(\.\d+)?(~)?([a-z%])?$/i;
+  function ji(t) {
+    if (!(e = Yi.exec(t))) throw new Error("invalid format: " + t);
+    var e;
+    return new zi({
+      fill: e[1],
+      align: e[2],
+      sign: e[3],
+      symbol: e[4],
+      zero: e[5],
+      width: e[6],
+      comma: e[7],
+      precision: e[8] && e[8].slice(1),
+      trim: e[9],
+      type: e[10],
+    });
+  }
+  function zi(t) {
+    this.fill = void 0 === t.fill ? " " : t.fill + "",
+      this.align = void 0 === t.align ? ">" : t.align + "",
+      this.sign = void 0 === t.sign ? "-" : t.sign + "",
+      this.symbol = void 0 === t.symbol ? "" : t.symbol + "",
+      this.zero = !!t.zero,
+      this.width = void 0 === t.width ? void 0 : +t.width,
+      this.comma = !!t.comma,
+      this.precision = void 0 === t.precision ? void 0 : +t.precision,
+      this.trim = !!t.trim,
+      this.type = void 0 === t.type ? "" : t.type + "";
+  }
+  function Ui(t, e) {
+    var n = Ri(t, e);
+    if (!n) return t + "";
+    var i = n[0], r = n[1];
+    return r < 0
+      ? "0." + new Array(-r).join("0") + i
+      : i.length > r + 1
+      ? i.slice(0, r + 1) + "." + i.slice(r + 1)
+      : i + new Array(r - i.length + 2).join("0");
+  }
+  ji.prototype = zi.prototype,
+    zi.prototype.toString = function() {
+      return this.fill + this.align + this.sign + this.symbol + (this.zero ? "0" : "")
+        + (void 0 === this.width ? "" : Math.max(1, 0 | this.width)) + (this.comma ? "," : "")
+        + (void 0 === this.precision ? "" : "." + Math.max(0, 0 | this.precision)) + (this.trim ? "~" : "") + this.type;
+    };
+  var Wi = {
+    "%": (t, e) => (100 * t).toFixed(e),
+    b: t => Math.round(t).toString(2),
+    c: t => t + "",
+    d: function(t) {
+      return Math.abs(t = Math.round(t)) >= 1e21 ? t.toLocaleString("en").replace(/,/g, "") : t.toString(10);
+    },
+    e: (t, e) => t.toExponential(e),
+    f: (t, e) => t.toFixed(e),
+    g: (t, e) => t.toPrecision(e),
+    o: t => Math.round(t).toString(8),
+    p: (t, e) => Ui(100 * t, e),
+    r: Ui,
+    s: function(t, e) {
+      var n = Ri(t, e);
+      if (!n) return t + "";
+      var i = n[0], r = n[1], a = r - (Pi = 3 * Math.max(-8, Math.min(8, Math.floor(r / 3)))) + 1, s = i.length;
+      return a === s
+        ? i
+        : a > s
+        ? i + new Array(a - s + 1).join("0")
+        : a > 0
+        ? i.slice(0, a) + "." + i.slice(a)
+        : "0." + new Array(1 - a).join("0") + Ri(t, Math.max(0, e + a - 1))[0];
+    },
+    X: t => Math.round(t).toString(16).toUpperCase(),
+    x: t => Math.round(t).toString(16),
+  };
+  function Hi(t) {
+    return t;
+  }
+  var qi,
+    Vi,
+    Gi,
+    Xi = Array.prototype.map,
+    Zi = ["y", "z", "a", "f", "p", "n", "µ", "m", "", "k", "M", "G", "T", "P", "E", "Z", "Y"];
+  function Qi(t) {
+    var e,
+      n,
+      i = void 0 === t.grouping || void 0 === t.thousands
+        ? Hi
+        : (e = Xi.call(t.grouping, Number), n = t.thousands + "", function(t, i) {
+          for (
+            var r = t.length, a = [], s = 0, o = e[0], l = 0;
+            r > 0 && o > 0
+            && (l + o + 1 > i && (o = Math.max(1, i - l)), a.push(t.substring(r -= o, r + o)), !((l += o + 1) > i));
+          ) o = e[s = (s + 1) % e.length];
+          return a.reverse().join(n);
+        }),
+      r = void 0 === t.currency ? "" : t.currency[0] + "",
+      a = void 0 === t.currency ? "" : t.currency[1] + "",
+      s = void 0 === t.decimal ? "." : t.decimal + "",
+      o = void 0 === t.numerals ? Hi : function(t) {
+        return function(e) {
+          return e.replace(/[0-9]/g, function(e) {
+            return t[+e];
+          });
+        };
+      }(Xi.call(t.numerals, String)),
+      l = void 0 === t.percent ? "%" : t.percent + "",
+      c = void 0 === t.minus ? "−" : t.minus + "",
+      h = void 0 === t.nan ? "NaN" : t.nan + "";
+    function u(t) {
+      var e = (t = ji(t)).fill,
+        n = t.align,
+        u = t.sign,
+        d = t.symbol,
+        p = t.zero,
+        f = t.width,
+        g = t.comma,
+        y = t.precision,
+        m = t.trim,
+        b = t.type;
+      "n" === b ? (g = !0, b = "g") : Wi[b] || (void 0 === y && (y = 12), m = !0, b = "g"),
+        (p || "0" === e && "=" === n) && (p = !0, e = "0", n = "=");
+      var _ = "$" === d ? r : "#" === d && /[boxX]/.test(b) ? "0" + b.toLowerCase() : "",
+        x = "$" === d ? a : /[%p]/.test(b) ? l : "",
+        v = Wi[b],
+        k = /[defgprs%]/.test(b);
+      function w(t) {
+        var r, a, l, d = _, w = x;
+        if ("c" === b) w = v(t) + w, t = "";
+        else {
+          var T = (t = +t) < 0 || 1 / t < 0;
+          if (
+            t = isNaN(t) ? h : v(Math.abs(t), y),
+              m && (t = function(t) {
+                t: for (var e, n = t.length, i = 1, r = -1; i < n; ++i) {
+                  switch (t[i]) {
+                    case ".":
+                      r = e = i;
+                      break;
+                    case "0":
+                      0 === r && (r = i), e = i;
+                      break;
+                    default:
+                      if (!+t[i]) break t;
+                      r > 0 && (r = 0);
+                  }
+                }
+                return r > 0 ? t.slice(0, r) + t.slice(e + 1) : t;
+              }(t)),
+              T && 0 == +t && "+" !== u && (T = !1),
+              d = (T ? "(" === u ? u : c : "-" === u || "(" === u ? "" : u) + d,
+              w = ("s" === b ? Zi[8 + Pi / 3] : "") + w + (T && "(" === u ? ")" : ""),
+              k
+          ) {
+            for (r = -1, a = t.length; ++r < a;) {
+              if (48 > (l = t.charCodeAt(r)) || l > 57) {
+                w = (46 === l ? s + t.slice(r + 1) : t.slice(r)) + w, t = t.slice(0, r);
+                break;
+              }
+            }
+          }
+        }
+        g && !p && (t = i(t, 1 / 0));
+        var C = d.length + t.length + w.length, E = C < f ? new Array(f - C + 1).join(e) : "";
+        switch (g && p && (t = i(E + t, E.length ? f - w.length : 1 / 0), E = ""), n) {
+          case "<":
+            t = d + t + w + E;
+            break;
+          case "=":
+            t = d + E + t + w;
+            break;
+          case "^":
+            t = E.slice(0, C = E.length >> 1) + d + t + w + E.slice(C);
+            break;
+          default:
+            t = E + d + t + w;
+        }
+        return o(t);
+      }
+      return y = void 0 === y ? 6 : /[gprs]/.test(b) ? Math.max(1, Math.min(21, y)) : Math.max(0, Math.min(20, y)),
+        w.toString = function() {
+          return t + "";
+        },
+        w;
+    }
+    return {
+      format: u,
+      formatPrefix: function(t, e) {
+        var n = u(((t = ji(t)).type = "f", t)),
+          i = 3 * Math.max(-8, Math.min(8, Math.floor($i(e) / 3))),
+          r = Math.pow(10, -i),
+          a = Zi[8 + i / 3];
+        return function(t) {
+          return n(r * t) + a;
+        };
+      },
+    };
+  }
+  function Ki(t, e) {
+    switch (arguments.length) {
+      case 0:
+        break;
+      case 1:
+        this.range(t);
+        break;
+      default:
+        this.range(e).domain(t);
+    }
+    return this;
+  }
+  qi = Qi({ thousands: ",", grouping: [3], currency: ["$", ""] }), Vi = qi.format, Gi = qi.formatPrefix;
+  const Ji = Symbol("implicit");
+  function tr() {
+    var t = new m(), e = [], n = [], i = Ji;
+    function r(r) {
+      let a = t.get(r);
+      if (void 0 === a) {
+        if (i !== Ji) return i;
+        t.set(r, a = e.push(r) - 1);
+      }
+      return n[a % n.length];
+    }
+    return r.domain = function(n) {
+      if (!arguments.length) return e.slice();
+      e = [], t = new m();
+      for (const i of n) t.has(i) || t.set(i, e.push(i) - 1);
+      return r;
+    },
+      r.range = function(t) {
+        return arguments.length ? (n = Array.from(t), r) : n.slice();
+      },
+      r.unknown = function(t) {
+        return arguments.length ? (i = t, r) : i;
+      },
+      r.copy = function() {
+        return tr(e, n).unknown(i);
+      },
+      Ki.apply(r, arguments),
+      r;
+  }
+  function er(t) {
+    return +t;
+  }
+  var nr = [0, 1];
+  function ir(t) {
+    return t;
+  }
+  function rr(t, e) {
+    return (e -= t = +t)
+      ? function(n) {
+        return (n - t) / e;
+      }
+      : function(t) {
+        return function() {
+          return t;
+        };
+      }(isNaN(e) ? NaN : .5);
+  }
+  function ar(t, e, n) {
+    var i = t[0], r = t[1], a = e[0], s = e[1];
+    return r < i ? (i = rr(r, i), a = n(s, a)) : (i = rr(i, r), a = n(a, s)), function(t) {
+      return a(i(t));
+    };
+  }
+  function sr(t, e, n) {
+    var i = Math.min(t.length, e.length) - 1, r = new Array(i), a = new Array(i), s = -1;
+    for (t[i] < t[0] && (t = t.slice().reverse(), e = e.slice().reverse()); ++s < i;) {
+      r[s] = rr(t[s], t[s + 1]), a[s] = n(e[s], e[s + 1]);
+    }
+    return function(e) {
+      var n = y(t, e, 1, i) - 1;
+      return a[n](r[n](e));
+    };
+  }
+  function or(t, e) {
+    return e.domain(t.domain()).range(t.range()).interpolate(t.interpolate()).clamp(t.clamp()).unknown(t.unknown());
+  }
+  function lr() {
+    var t, e, n, i, r, a, s = nr, o = nr, l = bn, c = ir;
+    function h() {
+      var t, e, n, l = Math.min(s.length, o.length);
+      return c !== ir && (t = s[0],
+        e = s[l - 1],
+        t > e && (n = t, t = e, e = n),
+        c = function(n) {
+          return Math.max(t, Math.min(e, n));
+        }),
+        i = l > 2 ? sr : ar,
+        r = a = null,
+        u;
+    }
+    function u(e) {
+      return null == e || isNaN(e = +e) ? n : (r || (r = i(s.map(t), o, l)))(t(c(e)));
+    }
+    return u.invert = function(n) {
+      return c(e((a || (a = i(o, s.map(t), pn)))(n)));
+    },
+      u.domain = function(t) {
+        return arguments.length ? (s = Array.from(t, er), h()) : s.slice();
+      },
+      u.range = function(t) {
+        return arguments.length ? (o = Array.from(t), h()) : o.slice();
+      },
+      u.rangeRound = function(t) {
+        return o = Array.from(t), l = _n, h();
+      },
+      u.clamp = function(t) {
+        return arguments.length ? (c = !!t || ir, h()) : c !== ir;
+      },
+      u.interpolate = function(t) {
+        return arguments.length ? (l = t, h()) : l;
+      },
+      u.unknown = function(t) {
+        return arguments.length ? (n = t, u) : n;
+      },
+      function(n, i) {
+        return t = n, e = i, h();
+      };
+  }
+  function cr() {
+    return lr()(ir, ir);
+  }
+  function hr(t, e, n, i) {
+    var r, a = C(t, e, n);
+    switch ((i = ji(null == i ? ",f" : i)).type) {
+      case "s":
+        var s = Math.max(Math.abs(t), Math.abs(e));
+        return null != i.precision || isNaN(
+          r = function(t, e) {
+            return Math.max(0, 3 * Math.max(-8, Math.min(8, Math.floor($i(e) / 3))) - $i(Math.abs(t)));
+          }(a, s),
+        ) || (i.precision = r),
+          Gi(i, s);
+      case "":
+      case "e":
+      case "g":
+      case "p":
+      case "r":
+        null != i.precision || isNaN(
+          r = function(t, e) {
+            return t = Math.abs(t), e = Math.abs(e) - t, Math.max(0, $i(e) - $i(t)) + 1;
+          }(a, Math.max(Math.abs(t), Math.abs(e))),
+        ) || (i.precision = r - ("e" === i.type));
+        break;
+      case "f":
+      case "%":
+        null != i.precision || isNaN(
+          r = function(t) {
+            return Math.max(0, -$i(Math.abs(t)));
+          }(a),
+        ) || (i.precision = r - 2 * ("%" === i.type));
+    }
+    return Vi(i);
+  }
+  function ur(t) {
+    var e = t.domain;
+    return t.ticks = function(t) {
+      var n = e();
+      return function(t, e, n) {
+        if (!((n = +n) > 0)) return [];
+        if ((t = +t) == (e = +e)) return [t];
+        const i = e < t, [r, a, s] = i ? w(e, t, n) : w(t, e, n);
+        if (!(a >= r)) return [];
+        const o = a - r + 1, l = new Array(o);
+        if (i) {
+          if (s < 0) for (let t = 0; t < o; ++t) l[t] = (a - t) / -s;
+          else for (let t = 0; t < o; ++t) l[t] = (a - t) * s;
+        } else if (s < 0) for (let t = 0; t < o; ++t) l[t] = (r + t) / -s;
+        else for (let t = 0; t < o; ++t) l[t] = (r + t) * s;
+        return l;
+      }(n[0], n[n.length - 1], null == t ? 10 : t);
+    },
+      t.tickFormat = function(t, n) {
+        var i = e();
+        return hr(i[0], i[i.length - 1], null == t ? 10 : t, n);
+      },
+      t.nice = function(n) {
+        null == n && (n = 10);
+        var i, r, a = e(), s = 0, o = a.length - 1, l = a[s], c = a[o], h = 10;
+        for (c < l && (r = l, l = c, c = r, r = s, s = o, o = r); h-- > 0;) {
+          if ((r = T(l, c, n)) === i) return a[s] = l, a[o] = c, e(a);
+          if (r > 0) l = Math.floor(l / r) * r, c = Math.ceil(c / r) * r;
+          else {
+            if (!(r < 0)) break;
+            l = Math.ceil(l * r) / r, c = Math.floor(c * r) / r;
+          }
+          i = r;
+        }
+        return t;
+      },
+      t;
+  }
+  function dr() {
+    var t = cr();
+    return t.copy = function() {
+      return or(t, dr());
+    },
+      Ki.apply(t, arguments),
+      ur(t);
+  }
+  const pr = new Date(), fr = new Date();
+  function gr(t, e, n, i) {
+    function r(e) {
+      return t(e = 0 === arguments.length ? new Date() : new Date(+e)), e;
+    }
+    return r.floor = e => (t(e = new Date(+e)), e),
+      r.ceil = n => (t(n = new Date(n - 1)), e(n, 1), t(n), n),
+      r.round = t => {
+        const e = r(t), n = r.ceil(t);
+        return t - e < n - t ? e : n;
+      },
+      r.offset = (t, n) => (e(t = new Date(+t), null == n ? 1 : Math.floor(n)), t),
+      r.range = (n, i, a) => {
+        const s = [];
+        if (n = r.ceil(n), a = null == a ? 1 : Math.floor(a), !(n < i && a > 0)) return s;
+        let o;
+        do {
+          s.push(o = new Date(+n)), e(n, a), t(n);
+        } while (o < n && n < i);
+        return s;
+      },
+      r.filter = n =>
+        gr(e => {
+          if (e >= e) for (; t(e), !n(e);) e.setTime(e - 1);
+        }, (t, i) => {
+          if (t >= t) {
+            if (i < 0) for (; ++i <= 0;) for (; e(t, -1), !n(t););
+            else for (; --i >= 0;) for (; e(t, 1), !n(t););
+          }
+        }),
+      n
+      && (r.count = (e, i) => (pr.setTime(+e), fr.setTime(+i), t(pr), t(fr), Math.floor(n(pr, fr))),
+        r.every = t => (t = Math.floor(t),
+          isFinite(t) && t > 0
+            ? t > 1
+              ? r.filter(
+                i
+                  ? e => i(e) % t == 0
+                  : e => r.count(0, e) % t == 0,
+              )
+              : r
+            : null)),
+      r;
+  }
+  const yr = gr(() => {}, (t, e) => {
+    t.setTime(+t + e);
+  }, (t, e) => e - t);
+  yr.every = t => (t = Math.floor(t),
+    isFinite(t) && t > 0
+      ? t > 1
+        ? gr(e => {
+          e.setTime(Math.floor(e / t) * t);
+        }, (e, n) => {
+          e.setTime(+e + n * t);
+        }, (e, n) => (n - e) / t)
+        : yr
+      : null), yr.range;
+  const mr = 1e3,
+    br = 60 * mr,
+    _r = 60 * br,
+    xr = 24 * _r,
+    vr = 7 * xr,
+    kr = 30 * xr,
+    wr = 365 * xr,
+    Tr = gr(
+      t => {
+        t.setTime(t - t.getMilliseconds());
+      },
+      (t, e) => {
+        t.setTime(+t + e * mr);
+      },
+      (t, e) => (e - t) / mr,
+      t => t.getUTCSeconds(),
+    );
+  Tr.range;
+  const Cr = gr(
+    t => {
+      t.setTime(t - t.getMilliseconds() - t.getSeconds() * mr);
+    },
+    (t, e) => {
+      t.setTime(+t + e * br);
+    },
+    (t, e) => (e - t) / br,
+    t => t.getMinutes(),
+  );
+  Cr.range;
+  const Er = gr(
+    t => {
+      t.setUTCSeconds(0, 0);
+    },
+    (t, e) => {
+      t.setTime(+t + e * br);
+    },
+    (t, e) => (e - t) / br,
+    t => t.getUTCMinutes(),
+  );
+  Er.range;
+  const Sr = gr(
+    t => {
+      t.setTime(t - t.getMilliseconds() - t.getSeconds() * mr - t.getMinutes() * br);
+    },
+    (t, e) => {
+      t.setTime(+t + e * _r);
+    },
+    (t, e) => (e - t) / _r,
+    t => t.getHours(),
+  );
+  Sr.range;
+  const Ar = gr(
+    t => {
+      t.setUTCMinutes(0, 0, 0);
+    },
+    (t, e) => {
+      t.setTime(+t + e * _r);
+    },
+    (t, e) => (e - t) / _r,
+    t => t.getUTCHours(),
+  );
+  Ar.range;
+  const Dr = gr(
+    t => t.setHours(0, 0, 0, 0),
+    (t, e) => t.setDate(t.getDate() + e),
+    (t, e) => (e - t - (e.getTimezoneOffset() - t.getTimezoneOffset()) * br) / xr,
+    t => t.getDate() - 1,
+  );
+  Dr.range;
+  const Lr = gr(
+    t => {
+      t.setUTCHours(0, 0, 0, 0);
+    },
+    (t, e) => {
+      t.setUTCDate(t.getUTCDate() + e);
+    },
+    (t, e) => (e - t) / xr,
+    t => t.getUTCDate() - 1,
+  );
+  Lr.range;
+  const Or = gr(
+    t => {
+      t.setUTCHours(0, 0, 0, 0);
+    },
+    (t, e) => {
+      t.setUTCDate(t.getUTCDate() + e);
+    },
+    (t, e) => (e - t) / xr,
+    t => Math.floor(t / xr),
+  );
+  function Nr(t) {
+    return gr(e => {
+      e.setDate(e.getDate() - (e.getDay() + 7 - t) % 7), e.setHours(0, 0, 0, 0);
+    }, (t, e) => {
+      t.setDate(t.getDate() + 7 * e);
+    }, (t, e) => (e - t - (e.getTimezoneOffset() - t.getTimezoneOffset()) * br) / vr);
+  }
+  Or.range;
+  const Mr = Nr(0), Br = Nr(1), Ir = Nr(2), Fr = Nr(3), Rr = Nr(4), $r = Nr(5), Pr = Nr(6);
+  function Yr(t) {
+    return gr(e => {
+      e.setUTCDate(e.getUTCDate() - (e.getUTCDay() + 7 - t) % 7), e.setUTCHours(0, 0, 0, 0);
+    }, (t, e) => {
+      t.setUTCDate(t.getUTCDate() + 7 * e);
+    }, (t, e) => (e - t) / vr);
+  }
+  Mr.range, Br.range, Ir.range, Fr.range, Rr.range, $r.range, Pr.range;
+  const jr = Yr(0), zr = Yr(1), Ur = Yr(2), Wr = Yr(3), Hr = Yr(4), qr = Yr(5), Vr = Yr(6);
+  jr.range, zr.range, Ur.range, Wr.range, Hr.range, qr.range, Vr.range;
+  const Gr = gr(
+    t => {
+      t.setDate(1), t.setHours(0, 0, 0, 0);
+    },
+    (t, e) => {
+      t.setMonth(t.getMonth() + e);
+    },
+    (t, e) => e.getMonth() - t.getMonth() + 12 * (e.getFullYear() - t.getFullYear()),
+    t => t.getMonth(),
+  );
+  Gr.range;
+  const Xr = gr(
+    t => {
+      t.setUTCDate(1), t.setUTCHours(0, 0, 0, 0);
+    },
+    (t, e) => {
+      t.setUTCMonth(t.getUTCMonth() + e);
+    },
+    (t, e) => e.getUTCMonth() - t.getUTCMonth() + 12 * (e.getUTCFullYear() - t.getUTCFullYear()),
+    t => t.getUTCMonth(),
+  );
+  Xr.range;
+  const Zr = gr(
+    t => {
+      t.setMonth(0, 1), t.setHours(0, 0, 0, 0);
+    },
+    (t, e) => {
+      t.setFullYear(t.getFullYear() + e);
+    },
+    (t, e) => e.getFullYear() - t.getFullYear(),
+    t => t.getFullYear(),
+  );
+  Zr.every = t =>
+    isFinite(t = Math.floor(t)) && t > 0
+      ? gr(e => {
+        e.setFullYear(Math.floor(e.getFullYear() / t) * t), e.setMonth(0, 1), e.setHours(0, 0, 0, 0);
+      }, (e, n) => {
+        e.setFullYear(e.getFullYear() + n * t);
+      })
+      : null, Zr.range;
+  const Qr = gr(
+    t => {
+      t.setUTCMonth(0, 1), t.setUTCHours(0, 0, 0, 0);
+    },
+    (t, e) => {
+      t.setUTCFullYear(t.getUTCFullYear() + e);
+    },
+    (t, e) => e.getUTCFullYear() - t.getUTCFullYear(),
+    t => t.getUTCFullYear(),
+  );
+  function Kr(t, e, n, i, r, a) {
+    const s = [
+      [Tr, 1, mr],
+      [Tr, 5, 5 * mr],
+      [Tr, 15, 15 * mr],
+      [Tr, 30, 30 * mr],
+      [a, 1, br],
+      [a, 5, 5 * br],
+      [a, 15, 15 * br],
+      [a, 30, 30 * br],
+      [r, 1, _r],
+      [r, 3, 3 * _r],
+      [r, 6, 6 * _r],
+      [r, 12, 12 * _r],
+      [i, 1, xr],
+      [i, 2, 2 * xr],
+      [n, 1, vr],
+      [e, 1, kr],
+      [e, 3, 3 * kr],
+      [t, 1, wr],
+    ];
+    function o(e, n, i) {
+      const r = Math.abs(n - e) / i, a = p(([, , t]) => t).right(s, r);
+      if (a === s.length) return t.every(C(e / wr, n / wr, i));
+      if (0 === a) return yr.every(Math.max(C(e, n, i), 1));
+      const [o, l] = s[r / s[a - 1][2] < s[a][2] / r ? a - 1 : a];
+      return o.every(l);
+    }
+    return [function(t, e, n) {
+      const i = e < t;
+      i && ([t, e] = [e, t]);
+      const r = n && "function" == typeof n.range ? n : o(t, e, n), a = r ? r.range(t, +e + 1) : [];
+      return i ? a.reverse() : a;
+    }, o];
+  }
+  Qr.every = t =>
+    isFinite(t = Math.floor(t)) && t > 0
+      ? gr(e => {
+        e.setUTCFullYear(Math.floor(e.getUTCFullYear() / t) * t), e.setUTCMonth(0, 1), e.setUTCHours(0, 0, 0, 0);
+      }, (e, n) => {
+        e.setUTCFullYear(e.getUTCFullYear() + n * t);
+      })
+      : null,
+    Qr.range,
+    Kr(Qr, Xr, jr, Or, Ar, Er);
+  const [Jr, ta] = Kr(Zr, Gr, Mr, Dr, Sr, Cr);
+  function ea(t) {
+    if (0 <= t.y && t.y < 100) {
+      var e = new Date(-1, t.m, t.d, t.H, t.M, t.S, t.L);
+      return e.setFullYear(t.y), e;
+    }
+    return new Date(t.y, t.m, t.d, t.H, t.M, t.S, t.L);
+  }
+  function na(t) {
+    if (0 <= t.y && t.y < 100) {
+      var e = new Date(Date.UTC(-1, t.m, t.d, t.H, t.M, t.S, t.L));
+      return e.setUTCFullYear(t.y), e;
+    }
+    return new Date(Date.UTC(t.y, t.m, t.d, t.H, t.M, t.S, t.L));
+  }
+  function ia(t, e, n) {
+    return { y: t, m: e, d: n, H: 0, M: 0, S: 0, L: 0 };
+  }
+  var ra, aa, sa = { "-": "", _: " ", 0: "0" }, oa = /^\s*\d+/, la = /^%/, ca = /[\\^$*+?|[\]().{}]/g;
+  function ha(t, e, n) {
+    var i = t < 0 ? "-" : "", r = (i ? -t : t) + "", a = r.length;
+    return i + (a < n ? new Array(n - a + 1).join(e) + r : r);
+  }
+  function ua(t) {
+    return t.replace(ca, "\\$&");
+  }
+  function da(t) {
+    return new RegExp("^(?:" + t.map(ua).join("|") + ")", "i");
+  }
+  function pa(t) {
+    return new Map(t.map((t, e) => [t.toLowerCase(), e]));
+  }
+  function fa(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 1));
+    return i ? (t.w = +i[0], n + i[0].length) : -1;
+  }
+  function ga(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 1));
+    return i ? (t.u = +i[0], n + i[0].length) : -1;
+  }
+  function ya(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 2));
+    return i ? (t.U = +i[0], n + i[0].length) : -1;
+  }
+  function ma(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 2));
+    return i ? (t.V = +i[0], n + i[0].length) : -1;
+  }
+  function ba(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 2));
+    return i ? (t.W = +i[0], n + i[0].length) : -1;
+  }
+  function _a(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 4));
+    return i ? (t.y = +i[0], n + i[0].length) : -1;
+  }
+  function xa(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 2));
+    return i ? (t.y = +i[0] + (+i[0] > 68 ? 1900 : 2e3), n + i[0].length) : -1;
+  }
+  function va(t, e, n) {
+    var i = /^(Z)|([+-]\d\d)(?::?(\d\d))?/.exec(e.slice(n, n + 6));
+    return i ? (t.Z = i[1] ? 0 : -(i[2] + (i[3] || "00")), n + i[0].length) : -1;
+  }
+  function ka(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 1));
+    return i ? (t.q = 3 * i[0] - 3, n + i[0].length) : -1;
+  }
+  function wa(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 2));
+    return i ? (t.m = i[0] - 1, n + i[0].length) : -1;
+  }
+  function Ta(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 2));
+    return i ? (t.d = +i[0], n + i[0].length) : -1;
+  }
+  function Ca(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 3));
+    return i ? (t.m = 0, t.d = +i[0], n + i[0].length) : -1;
+  }
+  function Ea(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 2));
+    return i ? (t.H = +i[0], n + i[0].length) : -1;
+  }
+  function Sa(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 2));
+    return i ? (t.M = +i[0], n + i[0].length) : -1;
+  }
+  function Aa(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 2));
+    return i ? (t.S = +i[0], n + i[0].length) : -1;
+  }
+  function Da(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 3));
+    return i ? (t.L = +i[0], n + i[0].length) : -1;
+  }
+  function La(t, e, n) {
+    var i = oa.exec(e.slice(n, n + 6));
+    return i ? (t.L = Math.floor(i[0] / 1e3), n + i[0].length) : -1;
+  }
+  function Oa(t, e, n) {
+    var i = la.exec(e.slice(n, n + 1));
+    return i ? n + i[0].length : -1;
+  }
+  function Na(t, e, n) {
+    var i = oa.exec(e.slice(n));
+    return i ? (t.Q = +i[0], n + i[0].length) : -1;
+  }
+  function Ma(t, e, n) {
+    var i = oa.exec(e.slice(n));
+    return i ? (t.s = +i[0], n + i[0].length) : -1;
+  }
+  function Ba(t, e) {
+    return ha(t.getDate(), e, 2);
+  }
+  function Ia(t, e) {
+    return ha(t.getHours(), e, 2);
+  }
+  function Fa(t, e) {
+    return ha(t.getHours() % 12 || 12, e, 2);
+  }
+  function Ra(t, e) {
+    return ha(1 + Dr.count(Zr(t), t), e, 3);
+  }
+  function $a(t, e) {
+    return ha(t.getMilliseconds(), e, 3);
+  }
+  function Pa(t, e) {
+    return $a(t, e) + "000";
+  }
+  function Ya(t, e) {
+    return ha(t.getMonth() + 1, e, 2);
+  }
+  function ja(t, e) {
+    return ha(t.getMinutes(), e, 2);
+  }
+  function za(t, e) {
+    return ha(t.getSeconds(), e, 2);
+  }
+  function Ua(t) {
+    var e = t.getDay();
+    return 0 === e ? 7 : e;
+  }
+  function Wa(t, e) {
+    return ha(Mr.count(Zr(t) - 1, t), e, 2);
+  }
+  function Ha(t) {
+    var e = t.getDay();
+    return e >= 4 || 0 === e ? Rr(t) : Rr.ceil(t);
+  }
+  function qa(t, e) {
+    return t = Ha(t), ha(Rr.count(Zr(t), t) + (4 === Zr(t).getDay()), e, 2);
+  }
+  function Va(t) {
+    return t.getDay();
+  }
+  function Ga(t, e) {
+    return ha(Br.count(Zr(t) - 1, t), e, 2);
+  }
+  function Xa(t, e) {
+    return ha(t.getFullYear() % 100, e, 2);
+  }
+  function Za(t, e) {
+    return ha((t = Ha(t)).getFullYear() % 100, e, 2);
+  }
+  function Qa(t, e) {
+    return ha(t.getFullYear() % 1e4, e, 4);
+  }
+  function Ka(t, e) {
+    var n = t.getDay();
+    return ha((t = n >= 4 || 0 === n ? Rr(t) : Rr.ceil(t)).getFullYear() % 1e4, e, 4);
+  }
+  function Ja(t) {
+    var e = t.getTimezoneOffset();
+    return (e > 0 ? "-" : (e *= -1, "+")) + ha(e / 60 | 0, "0", 2) + ha(e % 60, "0", 2);
+  }
+  function ts(t, e) {
+    return ha(t.getUTCDate(), e, 2);
+  }
+  function es(t, e) {
+    return ha(t.getUTCHours(), e, 2);
+  }
+  function ns(t, e) {
+    return ha(t.getUTCHours() % 12 || 12, e, 2);
+  }
+  function is(t, e) {
+    return ha(1 + Lr.count(Qr(t), t), e, 3);
+  }
+  function rs(t, e) {
+    return ha(t.getUTCMilliseconds(), e, 3);
+  }
+  function as(t, e) {
+    return rs(t, e) + "000";
+  }
+  function ss(t, e) {
+    return ha(t.getUTCMonth() + 1, e, 2);
+  }
+  function os(t, e) {
+    return ha(t.getUTCMinutes(), e, 2);
+  }
+  function ls(t, e) {
+    return ha(t.getUTCSeconds(), e, 2);
+  }
+  function cs(t) {
+    var e = t.getUTCDay();
+    return 0 === e ? 7 : e;
+  }
+  function hs(t, e) {
+    return ha(jr.count(Qr(t) - 1, t), e, 2);
+  }
+  function us(t) {
+    var e = t.getUTCDay();
+    return e >= 4 || 0 === e ? Hr(t) : Hr.ceil(t);
+  }
+  function ds(t, e) {
+    return t = us(t), ha(Hr.count(Qr(t), t) + (4 === Qr(t).getUTCDay()), e, 2);
+  }
+  function ps(t) {
+    return t.getUTCDay();
+  }
+  function fs(t, e) {
+    return ha(zr.count(Qr(t) - 1, t), e, 2);
+  }
+  function gs(t, e) {
+    return ha(t.getUTCFullYear() % 100, e, 2);
+  }
+  function ys(t, e) {
+    return ha((t = us(t)).getUTCFullYear() % 100, e, 2);
+  }
+  function ms(t, e) {
+    return ha(t.getUTCFullYear() % 1e4, e, 4);
+  }
+  function bs(t, e) {
+    var n = t.getUTCDay();
+    return ha((t = n >= 4 || 0 === n ? Hr(t) : Hr.ceil(t)).getUTCFullYear() % 1e4, e, 4);
+  }
+  function _s() {
+    return "+0000";
+  }
+  function xs() {
+    return "%";
+  }
+  function vs(t) {
+    return +t;
+  }
+  function ks(t) {
+    return Math.floor(+t / 1e3);
+  }
+  function ws(t) {
+    return new Date(t);
+  }
+  function Ts(t) {
+    return t instanceof Date ? +t : +new Date(+t);
+  }
+  function Cs(t, e, n, i, r, a, s, o, l, c) {
+    var h = cr(),
+      u = h.invert,
+      d = h.domain,
+      p = c(".%L"),
+      f = c(":%S"),
+      g = c("%I:%M"),
+      y = c("%I %p"),
+      m = c("%a %d"),
+      b = c("%b %d"),
+      _ = c("%B"),
+      x = c("%Y");
+    function v(t) {
+      return (l(t) < t
+        ? p
+        : o(t) < t
+        ? f
+        : s(t) < t
+        ? g
+        : a(t) < t
+        ? y
+        : i(t) < t
+        ? r(t) < t ? m : b
+        : n(t) < t
+        ? _
+        : x)(t);
+    }
+    return h.invert = function(t) {
+      return new Date(u(t));
+    },
+      h.domain = function(t) {
+        return arguments.length ? d(Array.from(t, Ts)) : d().map(ws);
+      },
+      h.ticks = function(e) {
+        var n = d();
+        return t(n[0], n[n.length - 1], null == e ? 10 : e);
+      },
+      h.tickFormat = function(t, e) {
+        return null == e ? v : c(e);
+      },
+      h.nice = function(t) {
+        var n = d();
+        return t && "function" == typeof t.range || (t = e(n[0], n[n.length - 1], null == t ? 10 : t)),
+          t
+            ? d(function(t, e) {
+              var n, i = 0, r = (t = t.slice()).length - 1, a = t[i], s = t[r];
+              return s < a && (n = i, i = r, r = n, n = a, a = s, s = n), t[i] = e.floor(a), t[r] = e.ceil(s), t;
+            }(n, t))
+            : h;
+      },
+      h.copy = function() {
+        return or(h, Cs(t, e, n, i, r, a, s, o, l, c));
+      },
+      h;
+  }
+  function Es() {
+    return Ki.apply(
+      Cs(Jr, ta, Zr, Gr, Mr, Dr, Sr, Cr, Tr, aa).domain([new Date(2e3, 0, 1), new Date(2e3, 0, 2)]),
+      arguments,
+    );
+  }
+  function Ss(t) {
+    return function() {
+      return t;
+    };
+  }
+  !function(t) {
+    ra = function(t) {
+      var e = t.dateTime,
+        n = t.date,
+        i = t.time,
+        r = t.periods,
+        a = t.days,
+        s = t.shortDays,
+        o = t.months,
+        l = t.shortMonths,
+        c = da(r),
+        h = pa(r),
+        u = da(a),
+        d = pa(a),
+        p = da(s),
+        f = pa(s),
+        g = da(o),
+        y = pa(o),
+        m = da(l),
+        b = pa(l),
+        _ = {
+          a: function(t) {
+            return s[t.getDay()];
+          },
+          A: function(t) {
+            return a[t.getDay()];
+          },
+          b: function(t) {
+            return l[t.getMonth()];
+          },
+          B: function(t) {
+            return o[t.getMonth()];
+          },
+          c: null,
+          d: Ba,
+          e: Ba,
+          f: Pa,
+          g: Za,
+          G: Ka,
+          H: Ia,
+          I: Fa,
+          j: Ra,
+          L: $a,
+          m: Ya,
+          M: ja,
+          p: function(t) {
+            return r[+(t.getHours() >= 12)];
+          },
+          q: function(t) {
+            return 1 + ~~(t.getMonth() / 3);
+          },
+          Q: vs,
+          s: ks,
+          S: za,
+          u: Ua,
+          U: Wa,
+          V: qa,
+          w: Va,
+          W: Ga,
+          x: null,
+          X: null,
+          y: Xa,
+          Y: Qa,
+          Z: Ja,
+          "%": xs,
+        },
+        x = {
+          a: function(t) {
+            return s[t.getUTCDay()];
+          },
+          A: function(t) {
+            return a[t.getUTCDay()];
+          },
+          b: function(t) {
+            return l[t.getUTCMonth()];
+          },
+          B: function(t) {
+            return o[t.getUTCMonth()];
+          },
+          c: null,
+          d: ts,
+          e: ts,
+          f: as,
+          g: ys,
+          G: bs,
+          H: es,
+          I: ns,
+          j: is,
+          L: rs,
+          m: ss,
+          M: os,
+          p: function(t) {
+            return r[+(t.getUTCHours() >= 12)];
+          },
+          q: function(t) {
+            return 1 + ~~(t.getUTCMonth() / 3);
+          },
+          Q: vs,
+          s: ks,
+          S: ls,
+          u: cs,
+          U: hs,
+          V: ds,
+          w: ps,
+          W: fs,
+          x: null,
+          X: null,
+          y: gs,
+          Y: ms,
+          Z: _s,
+          "%": xs,
+        },
+        v = {
+          a: function(t, e, n) {
+            var i = p.exec(e.slice(n));
+            return i ? (t.w = f.get(i[0].toLowerCase()), n + i[0].length) : -1;
+          },
+          A: function(t, e, n) {
+            var i = u.exec(e.slice(n));
+            return i ? (t.w = d.get(i[0].toLowerCase()), n + i[0].length) : -1;
+          },
+          b: function(t, e, n) {
+            var i = m.exec(e.slice(n));
+            return i ? (t.m = b.get(i[0].toLowerCase()), n + i[0].length) : -1;
+          },
+          B: function(t, e, n) {
+            var i = g.exec(e.slice(n));
+            return i ? (t.m = y.get(i[0].toLowerCase()), n + i[0].length) : -1;
+          },
+          c: function(t, n, i) {
+            return T(t, e, n, i);
+          },
+          d: Ta,
+          e: Ta,
+          f: La,
+          g: xa,
+          G: _a,
+          H: Ea,
+          I: Ea,
+          j: Ca,
+          L: Da,
+          m: wa,
+          M: Sa,
+          p: function(t, e, n) {
+            var i = c.exec(e.slice(n));
+            return i ? (t.p = h.get(i[0].toLowerCase()), n + i[0].length) : -1;
+          },
+          q: ka,
+          Q: Na,
+          s: Ma,
+          S: Aa,
+          u: ga,
+          U: ya,
+          V: ma,
+          w: fa,
+          W: ba,
+          x: function(t, e, i) {
+            return T(t, n, e, i);
+          },
+          X: function(t, e, n) {
+            return T(t, i, e, n);
+          },
+          y: xa,
+          Y: _a,
+          Z: va,
+          "%": Oa,
+        };
+      function k(t, e) {
+        return function(n) {
+          var i, r, a, s = [], o = -1, l = 0, c = t.length;
+          for (n instanceof Date || (n = new Date(+n)); ++o < c;) {
+            37 === t.charCodeAt(o)
+              && (s.push(t.slice(l, o)),
+                null != (r = sa[i = t.charAt(++o)]) ? i = t.charAt(++o) : r = "e" === i ? " " : "0",
+                (a = e[i]) && (i = a(n, r)),
+                s.push(i),
+                l = o + 1);
+          }
+          return s.push(t.slice(l, o)), s.join("");
+        };
+      }
+      function w(t, e) {
+        return function(n) {
+          var i, r, a = ia(1900, void 0, 1);
+          if (T(a, t, n += "", 0) != n.length) return null;
+          if ("Q" in a) return new Date(a.Q);
+          if ("s" in a) return new Date(1e3 * a.s + ("L" in a ? a.L : 0));
+          if (
+            e && !("Z" in a) && (a.Z = 0),
+              "p" in a && (a.H = a.H % 12 + 12 * a.p),
+              void 0 === a.m && (a.m = "q" in a ? a.q : 0),
+              "V" in a
+          ) {
+            if (a.V < 1 || a.V > 53) return null;
+            "w" in a || (a.w = 1),
+              "Z" in a
+                ? (r = (i = na(ia(a.y, 0, 1))).getUTCDay(),
+                  i = r > 4 || 0 === r ? zr.ceil(i) : zr(i),
+                  i = Lr.offset(i, 7 * (a.V - 1)),
+                  a.y = i.getUTCFullYear(),
+                  a.m = i.getUTCMonth(),
+                  a.d = i.getUTCDate() + (a.w + 6) % 7)
+                : (r = (i = ea(ia(a.y, 0, 1))).getDay(),
+                  i = r > 4 || 0 === r ? Br.ceil(i) : Br(i),
+                  i = Dr.offset(i, 7 * (a.V - 1)),
+                  a.y = i.getFullYear(),
+                  a.m = i.getMonth(),
+                  a.d = i.getDate() + (a.w + 6) % 7);
+          } else {("W" in a || "U" in a)
+              && ("w" in a || (a.w = "u" in a ? a.u % 7 : "W" in a ? 1 : 0),
+                r = "Z" in a ? na(ia(a.y, 0, 1)).getUTCDay() : ea(ia(a.y, 0, 1)).getDay(),
+                a.m = 0,
+                a.d = "W" in a ? (a.w + 6) % 7 + 7 * a.W - (r + 5) % 7 : a.w + 7 * a.U - (r + 6) % 7);}
+          return "Z" in a ? (a.H += a.Z / 100 | 0, a.M += a.Z % 100, na(a)) : ea(a);
+        };
+      }
+      function T(t, e, n, i) {
+        for (var r, a, s = 0, o = e.length, l = n.length; s < o;) {
+          if (i >= l) return -1;
+          if (37 === (r = e.charCodeAt(s++))) {
+            if (r = e.charAt(s++), !(a = v[r in sa ? e.charAt(s++) : r]) || (i = a(t, n, i)) < 0) return -1;
+          } else if (r != n.charCodeAt(i++)) return -1;
+        }
+        return i;
+      }
+      return _.x = k(n, _), _.X = k(i, _), _.c = k(e, _), x.x = k(n, x), x.X = k(i, x), x.c = k(e, x), {
+        format: function(t) {
+          var e = k(t += "", _);
+          return e.toString = function() {
+            return t;
+          },
+            e;
+        },
+        parse: function(t) {
+          var e = w(t += "", !1);
+          return e.toString = function() {
+            return t;
+          },
+            e;
+        },
+        utcFormat: function(t) {
+          var e = k(t += "", x);
+          return e.toString = function() {
+            return t;
+          },
+            e;
+        },
+        utcParse: function(t) {
+          var e = w(t += "", !0);
+          return e.toString = function() {
+            return t;
+          },
+            e;
+        },
+      };
+    }(t),
+      aa = ra.format,
+      ra.parse,
+      ra.utcFormat,
+      ra.utcParse;
+  }({
+    dateTime: "%x, %X",
+    date: "%-m/%-d/%Y",
+    time: "%-I:%M:%S %p",
+    periods: ["AM", "PM"],
+    days: ["Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday"],
+    shortDays: ["Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat"],
+    months: [
+      "January",
+      "February",
+      "March",
+      "April",
+      "May",
+      "June",
+      "July",
+      "August",
+      "September",
+      "October",
+      "November",
+      "December",
+    ],
+    shortMonths: ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"],
+  });
+  const As = Math.abs,
+    Ds = Math.atan2,
+    Ls = Math.cos,
+    Os = Math.max,
+    Ns = Math.min,
+    Ms = Math.sin,
+    Bs = Math.sqrt,
+    Is = 1e-12,
+    Fs = Math.PI,
+    Rs = Fs / 2,
+    $s = 2 * Fs;
+  function Ps(t) {
+    return t >= 1 ? Rs : t <= -1 ? -Rs : Math.asin(t);
+  }
+  function Ys(t) {
+    let e = 3;
+    return t.digits = function(n) {
+      if (!arguments.length) return e;
+      if (null == n) e = null;
+      else {
+        const t = Math.floor(n);
+        if (!(t >= 0)) throw new RangeError(`invalid digits: ${n}`);
+        e = t;
+      }
+      return t;
+    },
+      () => new Ii(e);
+  }
+  function js(t) {
+    return t.innerRadius;
+  }
+  function zs(t) {
+    return t.outerRadius;
+  }
+  function Us(t) {
+    return t.startAngle;
+  }
+  function Ws(t) {
+    return t.endAngle;
+  }
+  function Hs(t) {
+    return t && t.padAngle;
+  }
+  function qs(t, e, n, i, r, a, s) {
+    var o = t - n,
+      l = e - i,
+      c = (s ? a : -a) / Bs(o * o + l * l),
+      h = c * l,
+      u = -c * o,
+      d = t + h,
+      p = e + u,
+      f = n + h,
+      g = i + u,
+      y = (d + f) / 2,
+      m = (p + g) / 2,
+      b = f - d,
+      _ = g - p,
+      x = b * b + _ * _,
+      v = r - a,
+      k = d * g - f * p,
+      w = (_ < 0 ? -1 : 1) * Bs(Os(0, v * v * x - k * k)),
+      T = (k * _ - b * w) / x,
+      C = (-k * b - _ * w) / x,
+      E = (k * _ + b * w) / x,
+      S = (-k * b + _ * w) / x,
+      A = T - y,
+      D = C - m,
+      L = E - y,
+      O = S - m;
+    return A * A + D * D > L * L + O * O && (T = E, C = S),
+      { cx: T, cy: C, x01: -h, y01: -u, x11: T * (r / v - 1), y11: C * (r / v - 1) };
+  }
+  function Vs() {
+    var t = js, e = zs, n = Ss(0), i = null, r = Us, a = Ws, s = Hs, o = null, l = Ys(c);
+    function c() {
+      var c,
+        h,
+        u = +t.apply(this, arguments),
+        d = +e.apply(this, arguments),
+        p = r.apply(this, arguments) - Rs,
+        f = a.apply(this, arguments) - Rs,
+        g = As(f - p),
+        y = f > p;
+      if (o || (o = c = l()), d < u && (h = d, d = u, u = h), d > Is) {
+        if (g > $s - Is) {
+          o.moveTo(d * Ls(p), d * Ms(p)),
+            o.arc(0, 0, d, p, f, !y),
+            u > Is && (o.moveTo(u * Ls(f), u * Ms(f)), o.arc(0, 0, u, f, p, y));
+        } else {
+          var m,
+            b,
+            _ = p,
+            x = f,
+            v = p,
+            k = f,
+            w = g,
+            T = g,
+            C = s.apply(this, arguments) / 2,
+            E = C > Is && (i ? +i.apply(this, arguments) : Bs(u * u + d * d)),
+            S = Ns(As(d - u) / 2, +n.apply(this, arguments)),
+            A = S,
+            D = S;
+          if (E > Is) {
+            var L = Ps(E / u * Ms(C)), O = Ps(E / d * Ms(C));
+            (w -= 2 * L) > Is ? (v += L *= y ? 1 : -1, k -= L) : (w = 0, v = k = (p + f) / 2),
+              (T -= 2 * O) > Is ? (_ += O *= y ? 1 : -1, x -= O) : (T = 0, _ = x = (p + f) / 2);
+          }
+          var N = d * Ls(_), M = d * Ms(_), B = u * Ls(k), I = u * Ms(k);
+          if (S > Is) {
+            var F, R = d * Ls(x), $ = d * Ms(x), P = u * Ls(v), Y = u * Ms(v);
+            if (g < Fs) {
+              if (
+                F = function(t, e, n, i, r, a, s, o) {
+                  var l = n - t, c = i - e, h = s - r, u = o - a, d = u * l - h * c;
+                  if (!(d * d < Is)) return [t + (d = (h * (e - a) - u * (t - r)) / d) * l, e + d * c];
+                }(N, M, P, Y, R, $, B, I)
+              ) {
+                var j = N - F[0],
+                  z = M - F[1],
+                  U = R - F[0],
+                  W = $ - F[1],
+                  H = 1 / Ms(
+                    function(t) {
+                      return t > 1 ? 0 : t < -1 ? Fs : Math.acos(t);
+                    }((j * U + z * W) / (Bs(j * j + z * z) * Bs(U * U + W * W))) / 2,
+                  ),
+                  q = Bs(F[0] * F[0] + F[1] * F[1]);
+                A = Ns(S, (u - q) / (H - 1)), D = Ns(S, (d - q) / (H + 1));
+              } else A = D = 0;
+            }
+          }
+          T > Is
+            ? D > Is
+              ? (m = qs(P, Y, N, M, d, D, y),
+                b = qs(R, $, B, I, d, D, y),
+                o.moveTo(m.cx + m.x01, m.cy + m.y01),
+                D < S
+                  ? o.arc(m.cx, m.cy, D, Ds(m.y01, m.x01), Ds(b.y01, b.x01), !y)
+                  : (o.arc(m.cx, m.cy, D, Ds(m.y01, m.x01), Ds(m.y11, m.x11), !y),
+                    o.arc(0, 0, d, Ds(m.cy + m.y11, m.cx + m.x11), Ds(b.cy + b.y11, b.cx + b.x11), !y),
+                    o.arc(b.cx, b.cy, D, Ds(b.y11, b.x11), Ds(b.y01, b.x01), !y)))
+              : (o.moveTo(N, M), o.arc(0, 0, d, _, x, !y))
+            : o.moveTo(N, M),
+            u > Is && w > Is
+              ? A > Is
+                ? (m = qs(B, I, R, $, u, -A, y),
+                  b = qs(N, M, P, Y, u, -A, y),
+                  o.lineTo(m.cx + m.x01, m.cy + m.y01),
+                  A < S
+                    ? o.arc(m.cx, m.cy, A, Ds(m.y01, m.x01), Ds(b.y01, b.x01), !y)
+                    : (o.arc(m.cx, m.cy, A, Ds(m.y01, m.x01), Ds(m.y11, m.x11), !y),
+                      o.arc(0, 0, u, Ds(m.cy + m.y11, m.cx + m.x11), Ds(b.cy + b.y11, b.cx + b.x11), y),
+                      o.arc(b.cx, b.cy, A, Ds(b.y11, b.x11), Ds(b.y01, b.x01), !y)))
+                : o.arc(0, 0, u, k, v, y)
+              : o.lineTo(B, I);
+        }
+      } else o.moveTo(0, 0);
+      if (o.closePath(), c) return o = null, c + "" || null;
+    }
+    return c.centroid = function() {
+      var n = (+t.apply(this, arguments) + +e.apply(this, arguments)) / 2,
+        i = (+r.apply(this, arguments) + +a.apply(this, arguments)) / 2 - Fs / 2;
+      return [Ls(i) * n, Ms(i) * n];
+    },
+      c.innerRadius = function(e) {
+        return arguments.length ? (t = "function" == typeof e ? e : Ss(+e), c) : t;
+      },
+      c.outerRadius = function(t) {
+        return arguments.length ? (e = "function" == typeof t ? t : Ss(+t), c) : e;
+      },
+      c.cornerRadius = function(t) {
+        return arguments.length ? (n = "function" == typeof t ? t : Ss(+t), c) : n;
+      },
+      c.padRadius = function(t) {
+        return arguments.length ? (i = null == t ? null : "function" == typeof t ? t : Ss(+t), c) : i;
+      },
+      c.startAngle = function(t) {
+        return arguments.length ? (r = "function" == typeof t ? t : Ss(+t), c) : r;
+      },
+      c.endAngle = function(t) {
+        return arguments.length ? (a = "function" == typeof t ? t : Ss(+t), c) : a;
+      },
+      c.padAngle = function(t) {
+        return arguments.length ? (s = "function" == typeof t ? t : Ss(+t), c) : s;
+      },
+      c.context = function(t) {
+        return arguments.length ? (o = null == t ? null : t, c) : o;
+      },
+      c;
+  }
+  function Gs(t) {
+    return "object" == typeof t && "length" in t ? t : Array.from(t);
+  }
+  function Xs(t) {
+    this._context = t;
+  }
+  function Zs(t) {
+    return new Xs(t);
+  }
+  function Qs(t) {
+    return t[0];
+  }
+  function Ks(t) {
+    return t[1];
+  }
+  function Js(t, e) {
+    var n = Ss(!0), i = null, r = Zs, a = null, s = Ys(o);
+    function o(o) {
+      var l, c, h, u = (o = Gs(o)).length, d = !1;
+      for (null == i && (a = r(h = s())), l = 0; l <= u; ++l) {
+        !(l < u && n(c = o[l], l, o)) === d && ((d = !d) ? a.lineStart() : a.lineEnd()),
+          d && a.point(+t(c, l, o), +e(c, l, o));
+      }
+      if (h) return a = null, h + "" || null;
+    }
+    return t = "function" == typeof t ? t : void 0 === t ? Qs : Ss(t),
+      e = "function" == typeof e ? e : void 0 === e ? Ks : Ss(e),
+      o.x = function(e) {
+        return arguments.length ? (t = "function" == typeof e ? e : Ss(+e), o) : t;
+      },
+      o.y = function(t) {
+        return arguments.length ? (e = "function" == typeof t ? t : Ss(+t), o) : e;
+      },
+      o.defined = function(t) {
+        return arguments.length ? (n = "function" == typeof t ? t : Ss(!!t), o) : n;
+      },
+      o.curve = function(t) {
+        return arguments.length ? (r = t, null != i && (a = r(i)), o) : r;
+      },
+      o.context = function(t) {
+        return arguments.length ? (null == t ? i = a = null : a = r(i = t), o) : i;
+      },
+      o;
+  }
+  function to(t, e) {
+    return e < t ? -1 : e > t ? 1 : e >= t ? 0 : NaN;
+  }
+  function eo(t) {
+    return t;
+  }
+  function no() {}
+  function io(t, e, n) {
+    t._context.bezierCurveTo(
+      (2 * t._x0 + t._x1) / 3,
+      (2 * t._y0 + t._y1) / 3,
+      (t._x0 + 2 * t._x1) / 3,
+      (t._y0 + 2 * t._y1) / 3,
+      (t._x0 + 4 * t._x1 + e) / 6,
+      (t._y0 + 4 * t._y1 + n) / 6,
+    );
+  }
+  function ro(t) {
+    this._context = t;
+  }
+  function ao(t) {
+    return new ro(t);
+  }
+  function so(t) {
+    this._context = t;
+  }
+  function oo(t) {
+    this._context = t;
+  }
+  function lo(t) {
+    this._context = t;
+  }
+  function co(t) {
+    return t < 0 ? -1 : 1;
+  }
+  function ho(t, e, n) {
+    var i = t._x1 - t._x0,
+      r = e - t._x1,
+      a = (t._y1 - t._y0) / (i || r < 0 && -0),
+      s = (n - t._y1) / (r || i < 0 && -0),
+      o = (a * r + s * i) / (i + r);
+    return (co(a) + co(s)) * Math.min(Math.abs(a), Math.abs(s), .5 * Math.abs(o)) || 0;
+  }
+  function uo(t, e) {
+    var n = t._x1 - t._x0;
+    return n ? (3 * (t._y1 - t._y0) / n - e) / 2 : e;
+  }
+  function po(t, e, n) {
+    var i = t._x0, r = t._y0, a = t._x1, s = t._y1, o = (a - i) / 3;
+    t._context.bezierCurveTo(i + o, r + o * e, a - o, s - o * n, a, s);
+  }
+  function fo(t) {
+    this._context = t;
+  }
+  function go(t) {
+    this._context = new yo(t);
+  }
+  function yo(t) {
+    this._context = t;
+  }
+  function mo(t) {
+    this._context = t;
+  }
+  function bo(t) {
+    var e, n, i = t.length - 1, r = new Array(i), a = new Array(i), s = new Array(i);
+    for (r[0] = 0, a[0] = 2, s[0] = t[0] + 2 * t[1], e = 1; e < i - 1; ++e) {
+      r[e] = 1, a[e] = 4, s[e] = 4 * t[e] + 2 * t[e + 1];
+    }
+    for (r[i - 1] = 2, a[i - 1] = 7, s[i - 1] = 8 * t[i - 1] + t[i], e = 1; e < i; ++e) {
+      n = r[e] / a[e - 1], a[e] -= n, s[e] -= n * s[e - 1];
+    }
+    for (r[i - 1] = s[i - 1] / a[i - 1], e = i - 2; e >= 0; --e) r[e] = (s[e] - r[e + 1]) / a[e];
+    for (a[i - 1] = (t[i] + r[i - 1]) / 2, e = 0; e < i - 1; ++e) a[e] = 2 * t[e + 1] - r[e + 1];
+    return [r, a];
+  }
+  function _o(t, e) {
+    this._context = t, this._t = e;
+  }
+  function xo(t, e, n) {
+    this.k = t, this.x = e, this.y = n;
+  }
+  /*! @license DOMPurify 2.4.1 | (c) Cure53 and other contributors | Released under the Apache license 2.0 and Mozilla Public License 2.0 | github.com/cure53/DOMPurify/blob/2.4.1/LICENSE */
+  function vo(t) {
+    return vo = "function" == typeof Symbol && "symbol" == typeof Symbol.iterator
+      ? function(t) {
+        return typeof t;
+      }
+      : function(t) {
+        return t && "function" == typeof Symbol && t.constructor === Symbol && t !== Symbol.prototype
+          ? "symbol"
+          : typeof t;
+      },
+      vo(t);
+  }
+  function ko(t, e) {
+    return ko = Object.setPrototypeOf || function(t, e) {
+      return t.__proto__ = e, t;
+    },
+      ko(t, e);
+  }
+  function wo(t, e, n) {
+    return wo = (function() {
+        if ("undefined" == typeof Reflect || !Reflect.construct) return !1;
+        if (Reflect.construct.sham) return !1;
+        if ("function" == typeof Proxy) return !0;
+        try {
+          return Boolean.prototype.valueOf.call(Reflect.construct(Boolean, [], function() {})), !0;
+        } catch (t) {
+          return !1;
+        }
+      })()
+      ? Reflect.construct
+      : function(t, e, n) {
+        var i = [null];
+        i.push.apply(i, e);
+        var r = new (Function.bind.apply(t, i))();
+        return n && ko(r, n.prototype), r;
+      },
+      wo.apply(null, arguments);
+  }
+  function To(t) {
+    return function(t) {
+      if (Array.isArray(t)) return Co(t);
+    }(t) || function(t) {
+      if ("undefined" != typeof Symbol && null != t[Symbol.iterator] || null != t["@@iterator"]) return Array.from(t);
+    }(t) || function(t, e) {
+      if (!t) return;
+      if ("string" == typeof t) return Co(t, e);
+      var n = Object.prototype.toString.call(t).slice(8, -1);
+      "Object" === n && t.constructor && (n = t.constructor.name);
+      if ("Map" === n || "Set" === n) return Array.from(t);
+      if ("Arguments" === n || /^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(n)) return Co(t, e);
+    }(t) || function() {
+      throw new TypeError(
+        "Invalid attempt to spread non-iterable instance.\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.",
+      );
+    }();
+  }
+  function Co(t, e) {
+    (null == e || e > t.length) && (e = t.length);
+    for (var n = 0, i = new Array(e); n < e; n++) i[n] = t[n];
+    return i;
+  }
+  Xs.prototype = {
+    areaStart: function() {
+      this._line = 0;
+    },
+    areaEnd: function() {
+      this._line = NaN;
+    },
+    lineStart: function() {
+      this._point = 0;
+    },
+    lineEnd: function() {
+      (this._line || 0 !== this._line && 1 === this._point) && this._context.closePath(), this._line = 1 - this._line;
+    },
+    point: function(t, e) {
+      switch (t = +t, e = +e, this._point) {
+        case 0:
+          this._point = 1, this._line ? this._context.lineTo(t, e) : this._context.moveTo(t, e);
+          break;
+        case 1:
+          this._point = 2;
+        default:
+          this._context.lineTo(t, e);
+      }
+    },
+  },
+    ro.prototype = {
+      areaStart: function() {
+        this._line = 0;
+      },
+      areaEnd: function() {
+        this._line = NaN;
+      },
+      lineStart: function() {
+        this._x0 =
+          this._x1 =
+          this._y0 =
+          this._y1 =
+            NaN, this._point = 0;
+      },
+      lineEnd: function() {
+        switch (this._point) {
+          case 3:
+            io(this, this._x1, this._y1);
+          case 2:
+            this._context.lineTo(this._x1, this._y1);
+        }
+        (this._line || 0 !== this._line && 1 === this._point) && this._context.closePath(), this._line = 1 - this._line;
+      },
+      point: function(t, e) {
+        switch (t = +t, e = +e, this._point) {
+          case 0:
+            this._point = 1, this._line ? this._context.lineTo(t, e) : this._context.moveTo(t, e);
+            break;
+          case 1:
+            this._point = 2;
+            break;
+          case 2:
+            this._point = 3, this._context.lineTo((5 * this._x0 + this._x1) / 6, (5 * this._y0 + this._y1) / 6);
+          default:
+            io(this, t, e);
+        }
+        this._x0 = this._x1, this._x1 = t, this._y0 = this._y1, this._y1 = e;
+      },
+    },
+    so.prototype = {
+      areaStart: no,
+      areaEnd: no,
+      lineStart: function() {
+        this._x0 =
+          this._x1 =
+          this._x2 =
+          this._x3 =
+          this._x4 =
+          this._y0 =
+          this._y1 =
+          this._y2 =
+          this._y3 =
+          this._y4 =
+            NaN, this._point = 0;
+      },
+      lineEnd: function() {
+        switch (this._point) {
+          case 1:
+            this._context.moveTo(this._x2, this._y2), this._context.closePath();
+            break;
+          case 2:
+            this._context.moveTo((this._x2 + 2 * this._x3) / 3, (this._y2 + 2 * this._y3) / 3),
+              this._context.lineTo((this._x3 + 2 * this._x2) / 3, (this._y3 + 2 * this._y2) / 3),
+              this._context.closePath();
+            break;
+          case 3:
+            this.point(this._x2, this._y2), this.point(this._x3, this._y3), this.point(this._x4, this._y4);
+        }
+      },
+      point: function(t, e) {
+        switch (t = +t, e = +e, this._point) {
+          case 0:
+            this._point = 1, this._x2 = t, this._y2 = e;
+            break;
+          case 1:
+            this._point = 2, this._x3 = t, this._y3 = e;
+            break;
+          case 2:
+            this._point = 3,
+              this._x4 = t,
+              this._y4 = e,
+              this._context.moveTo((this._x0 + 4 * this._x1 + t) / 6, (this._y0 + 4 * this._y1 + e) / 6);
+            break;
+          default:
+            io(this, t, e);
+        }
+        this._x0 = this._x1, this._x1 = t, this._y0 = this._y1, this._y1 = e;
+      },
+    },
+    oo.prototype = {
+      areaStart: function() {
+        this._line = 0;
+      },
+      areaEnd: function() {
+        this._line = NaN;
+      },
+      lineStart: function() {
+        this._x0 =
+          this._x1 =
+          this._y0 =
+          this._y1 =
+            NaN, this._point = 0;
+      },
+      lineEnd: function() {
+        (this._line || 0 !== this._line && 3 === this._point) && this._context.closePath(), this._line = 1 - this._line;
+      },
+      point: function(t, e) {
+        switch (t = +t, e = +e, this._point) {
+          case 0:
+            this._point = 1;
+            break;
+          case 1:
+            this._point = 2;
+            break;
+          case 2:
+            this._point = 3;
+            var n = (this._x0 + 4 * this._x1 + t) / 6, i = (this._y0 + 4 * this._y1 + e) / 6;
+            this._line ? this._context.lineTo(n, i) : this._context.moveTo(n, i);
+            break;
+          case 3:
+            this._point = 4;
+          default:
+            io(this, t, e);
+        }
+        this._x0 = this._x1, this._x1 = t, this._y0 = this._y1, this._y1 = e;
+      },
+    },
+    lo.prototype = {
+      areaStart: no,
+      areaEnd: no,
+      lineStart: function() {
+        this._point = 0;
+      },
+      lineEnd: function() {
+        this._point && this._context.closePath();
+      },
+      point: function(t, e) {
+        t = +t, e = +e, this._point ? this._context.lineTo(t, e) : (this._point = 1, this._context.moveTo(t, e));
+      },
+    },
+    fo.prototype = {
+      areaStart: function() {
+        this._line = 0;
+      },
+      areaEnd: function() {
+        this._line = NaN;
+      },
+      lineStart: function() {
+        this._x0 =
+          this._x1 =
+          this._y0 =
+          this._y1 =
+          this._t0 =
+            NaN, this._point = 0;
+      },
+      lineEnd: function() {
+        switch (this._point) {
+          case 2:
+            this._context.lineTo(this._x1, this._y1);
+            break;
+          case 3:
+            po(this, this._t0, uo(this, this._t0));
+        }
+        (this._line || 0 !== this._line && 1 === this._point) && this._context.closePath(), this._line = 1 - this._line;
+      },
+      point: function(t, e) {
+        var n = NaN;
+        if (e = +e, (t = +t) !== this._x1 || e !== this._y1) {
+          switch (this._point) {
+            case 0:
+              this._point = 1, this._line ? this._context.lineTo(t, e) : this._context.moveTo(t, e);
+              break;
+            case 1:
+              this._point = 2;
+              break;
+            case 2:
+              this._point = 3, po(this, uo(this, n = ho(this, t, e)), n);
+              break;
+            default:
+              po(this, this._t0, n = ho(this, t, e));
+          }
+          this._x0 = this._x1, this._x1 = t, this._y0 = this._y1, this._y1 = e, this._t0 = n;
+        }
+      },
+    },
+    (go.prototype = Object.create(fo.prototype)).point = function(t, e) {
+      fo.prototype.point.call(this, e, t);
+    },
+    yo.prototype = {
+      moveTo: function(t, e) {
+        this._context.moveTo(e, t);
+      },
+      closePath: function() {
+        this._context.closePath();
+      },
+      lineTo: function(t, e) {
+        this._context.lineTo(e, t);
+      },
+      bezierCurveTo: function(t, e, n, i, r, a) {
+        this._context.bezierCurveTo(e, t, i, n, a, r);
+      },
+    },
+    mo.prototype = {
+      areaStart: function() {
+        this._line = 0;
+      },
+      areaEnd: function() {
+        this._line = NaN;
+      },
+      lineStart: function() {
+        this._x = [], this._y = [];
+      },
+      lineEnd: function() {
+        var t = this._x, e = this._y, n = t.length;
+        if (n) {
+          if (this._line ? this._context.lineTo(t[0], e[0]) : this._context.moveTo(t[0], e[0]), 2 === n) {
+            this._context.lineTo(t[1], e[1]);
+          } else {for (var i = bo(t), r = bo(e), a = 0, s = 1; s < n; ++a, ++s) {
+              this._context.bezierCurveTo(i[0][a], r[0][a], i[1][a], r[1][a], t[s], e[s]);
+            }}
+        }
+        (this._line || 0 !== this._line && 1 === n) && this._context.closePath(),
+          this._line = 1 - this._line,
+          this._x = this._y = null;
+      },
+      point: function(t, e) {
+        this._x.push(+t), this._y.push(+e);
+      },
+    },
+    _o.prototype = {
+      areaStart: function() {
+        this._line = 0;
+      },
+      areaEnd: function() {
+        this._line = NaN;
+      },
+      lineStart: function() {
+        this._x = this._y = NaN, this._point = 0;
+      },
+      lineEnd: function() {
+        0 < this._t && this._t < 1 && 2 === this._point && this._context.lineTo(this._x, this._y),
+          (this._line || 0 !== this._line && 1 === this._point) && this._context.closePath(),
+          this._line >= 0 && (this._t = 1 - this._t, this._line = 1 - this._line);
+      },
+      point: function(t, e) {
+        switch (t = +t, e = +e, this._point) {
+          case 0:
+            this._point = 1, this._line ? this._context.lineTo(t, e) : this._context.moveTo(t, e);
+            break;
+          case 1:
+            this._point = 2;
+          default:
+            if (this._t <= 0) {
+              this._context.lineTo(this._x, e), this._context.lineTo(t, e);
+            } else {
+              var n = this._x * (1 - this._t) + t * this._t;
+              this._context.lineTo(n, this._y), this._context.lineTo(n, e);
+            }
+        }
+        this._x = t, this._y = e;
+      },
+    },
+    xo.prototype = {
+      constructor: xo,
+      scale: function(t) {
+        return 1 === t ? this : new xo(this.k * t, this.x, this.y);
+      },
+      translate: function(t, e) {
+        return 0 === t & 0 === e ? this : new xo(this.k, this.x + this.k * t, this.y + this.k * e);
+      },
+      apply: function(t) {
+        return [t[0] * this.k + this.x, t[1] * this.k + this.y];
+      },
+      applyX: function(t) {
+        return t * this.k + this.x;
+      },
+      applyY: function(t) {
+        return t * this.k + this.y;
+      },
+      invert: function(t) {
+        return [(t[0] - this.x) / this.k, (t[1] - this.y) / this.k];
+      },
+      invertX: function(t) {
+        return (t - this.x) / this.k;
+      },
+      invertY: function(t) {
+        return (t - this.y) / this.k;
+      },
+      rescaleX: function(t) {
+        return t.copy().domain(t.range().map(this.invertX, this).map(t.invert, t));
+      },
+      rescaleY: function(t) {
+        return t.copy().domain(t.range().map(this.invertY, this).map(t.invert, t));
+      },
+      toString: function() {
+        return "translate(" + this.x + "," + this.y + ") scale(" + this.k + ")";
+      },
+    },
+    new xo(1, 0, 0),
+    xo.prototype;
+  var Eo = Object.hasOwnProperty,
+    So = Object.setPrototypeOf,
+    Ao = Object.isFrozen,
+    Do = Object.getPrototypeOf,
+    Lo = Object.getOwnPropertyDescriptor,
+    Oo = Object.freeze,
+    No = Object.seal,
+    Mo = Object.create,
+    Bo = "undefined" != typeof Reflect && Reflect,
+    Io = Bo.apply,
+    Fo = Bo.construct;
+  Io || (Io = function(t, e, n) {
+    return t.apply(e, n);
+  }),
+    Oo || (Oo = function(t) {
+      return t;
+    }),
+    No || (No = function(t) {
+      return t;
+    }),
+    Fo || (Fo = function(t, e) {
+      return wo(t, To(e));
+    });
+  var Ro,
+    $o = Xo(Array.prototype.forEach),
+    Po = Xo(Array.prototype.pop),
+    Yo = Xo(Array.prototype.push),
+    jo = Xo(String.prototype.toLowerCase),
+    zo = Xo(String.prototype.toString),
+    Uo = Xo(String.prototype.match),
+    Wo = Xo(String.prototype.replace),
+    Ho = Xo(String.prototype.indexOf),
+    qo = Xo(String.prototype.trim),
+    Vo = Xo(RegExp.prototype.test),
+    Go = (Ro = TypeError, function() {
+      for (var t = arguments.length, e = new Array(t), n = 0; n < t; n++) {
+        e[n] = arguments[n];
+      }
+      return Fo(Ro, e);
+    });
+  function Xo(t) {
+    return function(e) {
+      for (var n = arguments.length, i = new Array(n > 1 ? n - 1 : 0), r = 1; r < n; r++) {
+        i[r - 1] = arguments[r];
+      }
+      return Io(t, e, i);
+    };
+  }
+  function Zo(t, e, n) {
+    n = n || jo, So && So(t, null);
+    for (var i = e.length; i--;) {
+      var r = e[i];
+      if ("string" == typeof r) {
+        var a = n(r);
+        a !== r && (Ao(e) || (e[i] = a), r = a);
+      }
+      t[r] = !0;
+    }
+    return t;
+  }
+  function Qo(t) {
+    var e, n = Mo(null);
+    for (e in t) Io(Eo, t, [e]) && (n[e] = t[e]);
+    return n;
+  }
+  function Ko(t, e) {
+    for (; null !== t;) {
+      var n = Lo(t, e);
+      if (n) {
+        if (n.get) return Xo(n.get);
+        if ("function" == typeof n.value) return Xo(n.value);
+      }
+      t = Do(t);
+    }
+    return function(t) {
+      return console.warn("fallback value for", t), null;
+    };
+  }
+  var Jo = Oo([
+      "a",
+      "abbr",
+      "acronym",
+      "address",
+      "area",
+      "article",
+      "aside",
+      "audio",
+      "b",
+      "bdi",
+      "bdo",
+      "big",
+      "blink",
+      "blockquote",
+      "body",
+      "br",
+      "button",
+      "canvas",
+      "caption",
+      "center",
+      "cite",
+      "code",
+      "col",
+      "colgroup",
+      "content",
+      "data",
+      "datalist",
+      "dd",
+      "decorator",
+      "del",
+      "details",
+      "dfn",
+      "dialog",
+      "dir",
+      "div",
+      "dl",
+      "dt",
+      "element",
+      "em",
+      "fieldset",
+      "figcaption",
+      "figure",
+      "font",
+      "footer",
+      "form",
+      "h1",
+      "h2",
+      "h3",
+      "h4",
+      "h5",
+      "h6",
+      "head",
+      "header",
+      "hgroup",
+      "hr",
+      "html",
+      "i",
+      "img",
+      "input",
+      "ins",
+      "kbd",
+      "label",
+      "legend",
+      "li",
+      "main",
+      "map",
+      "mark",
+      "marquee",
+      "menu",
+      "menuitem",
+      "meter",
+      "nav",
+      "nobr",
+      "ol",
+      "optgroup",
+      "option",
+      "output",
+      "p",
+      "picture",
+      "pre",
+      "progress",
+      "q",
+      "rp",
+      "rt",
+      "ruby",
+      "s",
+      "samp",
+      "section",
+      "select",
+      "shadow",
+      "small",
+      "source",
+      "spacer",
+      "span",
+      "strike",
+      "strong",
+      "style",
+      "sub",
+      "summary",
+      "sup",
+      "table",
+      "tbody",
+      "td",
+      "template",
+      "textarea",
+      "tfoot",
+      "th",
+      "thead",
+      "time",
+      "tr",
+      "track",
+      "tt",
+      "u",
+      "ul",
+      "var",
+      "video",
+      "wbr",
+    ]),
+    tl = Oo([
+      "svg",
+      "a",
+      "altglyph",
+      "altglyphdef",
+      "altglyphitem",
+      "animatecolor",
+      "animatemotion",
+      "animatetransform",
+      "circle",
+      "clippath",
+      "defs",
+      "desc",
+      "ellipse",
+      "filter",
+      "font",
+      "g",
+      "glyph",
+      "glyphref",
+      "hkern",
+      "image",
+      "line",
+      "lineargradient",
+      "marker",
+      "mask",
+      "metadata",
+      "mpath",
+      "path",
+      "pattern",
+      "polygon",
+      "polyline",
+      "radialgradient",
+      "rect",
+      "stop",
+      "style",
+      "switch",
+      "symbol",
+      "text",
+      "textpath",
+      "title",
+      "tref",
+      "tspan",
+      "view",
+      "vkern",
+    ]),
+    el = Oo([
+      "feBlend",
+      "feColorMatrix",
+      "feComponentTransfer",
+      "feComposite",
+      "feConvolveMatrix",
+      "feDiffuseLighting",
+      "feDisplacementMap",
+      "feDistantLight",
+      "feFlood",
+      "feFuncA",
+      "feFuncB",
+      "feFuncG",
+      "feFuncR",
+      "feGaussianBlur",
+      "feImage",
+      "feMerge",
+      "feMergeNode",
+      "feMorphology",
+      "feOffset",
+      "fePointLight",
+      "feSpecularLighting",
+      "feSpotLight",
+      "feTile",
+      "feTurbulence",
+    ]),
+    nl = Oo([
+      "animate",
+      "color-profile",
+      "cursor",
+      "discard",
+      "fedropshadow",
+      "font-face",
+      "font-face-format",
+      "font-face-name",
+      "font-face-src",
+      "font-face-uri",
+      "foreignobject",
+      "hatch",
+      "hatchpath",
+      "mesh",
+      "meshgradient",
+      "meshpatch",
+      "meshrow",
+      "missing-glyph",
+      "script",
+      "set",
+      "solidcolor",
+      "unknown",
+      "use",
+    ]),
+    il = Oo([
+      "math",
+      "menclose",
+      "merror",
+      "mfenced",
+      "mfrac",
+      "mglyph",
+      "mi",
+      "mlabeledtr",
+      "mmultiscripts",
+      "mn",
+      "mo",
+      "mover",
+      "mpadded",
+      "mphantom",
+      "mroot",
+      "mrow",
+      "ms",
+      "mspace",
+      "msqrt",
+      "mstyle",
+      "msub",
+      "msup",
+      "msubsup",
+      "mtable",
+      "mtd",
+      "mtext",
+      "mtr",
+      "munder",
+      "munderover",
+    ]),
+    rl = Oo([
+      "maction",
+      "maligngroup",
+      "malignmark",
+      "mlongdiv",
+      "mscarries",
+      "mscarry",
+      "msgroup",
+      "mstack",
+      "msline",
+      "msrow",
+      "semantics",
+      "annotation",
+      "annotation-xml",
+      "mprescripts",
+      "none",
+    ]),
+    al = Oo(["#text"]),
+    sl = Oo([
+      "accept",
+      "action",
+      "align",
+      "alt",
+      "autocapitalize",
+      "autocomplete",
+      "autopictureinpicture",
+      "autoplay",
+      "background",
+      "bgcolor",
+      "border",
+      "capture",
+      "cellpadding",
+      "cellspacing",
+      "checked",
+      "cite",
+      "class",
+      "clear",
+      "color",
+      "cols",
+      "colspan",
+      "controls",
+      "controlslist",
+      "coords",
+      "crossorigin",
+      "datetime",
+      "decoding",
+      "default",
+      "dir",
+      "disabled",
+      "disablepictureinpicture",
+      "disableremoteplayback",
+      "download",
+      "draggable",
+      "enctype",
+      "enterkeyhint",
+      "face",
+      "for",
+      "headers",
+      "height",
+      "hidden",
+      "high",
+      "href",
+      "hreflang",
+      "id",
+      "inputmode",
+      "integrity",
+      "ismap",
+      "kind",
+      "label",
+      "lang",
+      "list",
+      "loading",
+      "loop",
+      "low",
+      "max",
+      "maxlength",
+      "media",
+      "method",
+      "min",
+      "minlength",
+      "multiple",
+      "muted",
+      "name",
+      "nonce",
+      "noshade",
+      "novalidate",
+      "nowrap",
+      "open",
+      "optimum",
+      "pattern",
+      "placeholder",
+      "playsinline",
+      "poster",
+      "preload",
+      "pubdate",
+      "radiogroup",
+      "readonly",
+      "rel",
+      "required",
+      "rev",
+      "reversed",
+      "role",
+      "rows",
+      "rowspan",
+      "spellcheck",
+      "scope",
+      "selected",
+      "shape",
+      "size",
+      "sizes",
+      "span",
+      "srclang",
+      "start",
+      "src",
+      "srcset",
+      "step",
+      "style",
+      "summary",
+      "tabindex",
+      "title",
+      "translate",
+      "type",
+      "usemap",
+      "valign",
+      "value",
+      "width",
+      "xmlns",
+      "slot",
+    ]),
+    ol = Oo([
+      "accent-height",
+      "accumulate",
+      "additive",
+      "alignment-baseline",
+      "ascent",
+      "attributename",
+      "attributetype",
+      "azimuth",
+      "basefrequency",
+      "baseline-shift",
+      "begin",
+      "bias",
+      "by",
+      "class",
+      "clip",
+      "clippathunits",
+      "clip-path",
+      "clip-rule",
+      "color",
+      "color-interpolation",
+      "color-interpolation-filters",
+      "color-profile",
+      "color-rendering",
+      "cx",
+      "cy",
+      "d",
+      "dx",
+      "dy",
+      "diffuseconstant",
+      "direction",
+      "display",
+      "divisor",
+      "dur",
+      "edgemode",
+      "elevation",
+      "end",
+      "fill",
+      "fill-opacity",
+      "fill-rule",
+      "filter",
+      "filterunits",
+      "flood-color",
+      "flood-opacity",
+      "font-family",
+      "font-size",
+      "font-size-adjust",
+      "font-stretch",
+      "font-style",
+      "font-variant",
+      "font-weight",
+      "fx",
+      "fy",
+      "g1",
+      "g2",
+      "glyph-name",
+      "glyphref",
+      "gradientunits",
+      "gradienttransform",
+      "height",
+      "href",
+      "id",
+      "image-rendering",
+      "in",
+      "in2",
+      "k",
+      "k1",
+      "k2",
+      "k3",
+      "k4",
+      "kerning",
+      "keypoints",
+      "keysplines",
+      "keytimes",
+      "lang",
+      "lengthadjust",
+      "letter-spacing",
+      "kernelmatrix",
+      "kernelunitlength",
+      "lighting-color",
+      "local",
+      "marker-end",
+      "marker-mid",
+      "marker-start",
+      "markerheight",
+      "markerunits",
+      "markerwidth",
+      "maskcontentunits",
+      "maskunits",
+      "max",
+      "mask",
+      "media",
+      "method",
+      "mode",
+      "min",
+      "name",
+      "numoctaves",
+      "offset",
+      "operator",
+      "opacity",
+      "order",
+      "orient",
+      "orientation",
+      "origin",
+      "overflow",
+      "paint-order",
+      "path",
+      "pathlength",
+      "patterncontentunits",
+      "patterntransform",
+      "patternunits",
+      "points",
+      "preservealpha",
+      "preserveaspectratio",
+      "primitiveunits",
+      "r",
+      "rx",
+      "ry",
+      "radius",
+      "refx",
+      "refy",
+      "repeatcount",
+      "repeatdur",
+      "restart",
+      "result",
+      "rotate",
+      "scale",
+      "seed",
+      "shape-rendering",
+      "specularconstant",
+      "specularexponent",
+      "spreadmethod",
+      "startoffset",
+      "stddeviation",
+      "stitchtiles",
+      "stop-color",
+      "stop-opacity",
+      "stroke-dasharray",
+      "stroke-dashoffset",
+      "stroke-linecap",
+      "stroke-linejoin",
+      "stroke-miterlimit",
+      "stroke-opacity",
+      "stroke",
+      "stroke-width",
+      "style",
+      "surfacescale",
+      "systemlanguage",
+      "tabindex",
+      "targetx",
+      "targety",
+      "transform",
+      "transform-origin",
+      "text-anchor",
+      "text-decoration",
+      "text-rendering",
+      "textlength",
+      "type",
+      "u1",
+      "u2",
+      "unicode",
+      "values",
+      "viewbox",
+      "visibility",
+      "version",
+      "vert-adv-y",
+      "vert-origin-x",
+      "vert-origin-y",
+      "width",
+      "word-spacing",
+      "wrap",
+      "writing-mode",
+      "xchannelselector",
+      "ychannelselector",
+      "x",
+      "x1",
+      "x2",
+      "xmlns",
+      "y",
+      "y1",
+      "y2",
+      "z",
+      "zoomandpan",
+    ]),
+    ll = Oo([
+      "accent",
+      "accentunder",
+      "align",
+      "bevelled",
+      "close",
+      "columnsalign",
+      "columnlines",
+      "columnspan",
+      "denomalign",
+      "depth",
+      "dir",
+      "display",
+      "displaystyle",
+      "encoding",
+      "fence",
+      "frame",
+      "height",
+      "href",
+      "id",
+      "largeop",
+      "length",
+      "linethickness",
+      "lspace",
+      "lquote",
+      "mathbackground",
+      "mathcolor",
+      "mathsize",
+      "mathvariant",
+      "maxsize",
+      "minsize",
+      "movablelimits",
+      "notation",
+      "numalign",
+      "open",
+      "rowalign",
+      "rowlines",
+      "rowspacing",
+      "rowspan",
+      "rspace",
+      "rquote",
+      "scriptlevel",
+      "scriptminsize",
+      "scriptsizemultiplier",
+      "selection",
+      "separator",
+      "separators",
+      "stretchy",
+      "subscriptshift",
+      "supscriptshift",
+      "symmetric",
+      "voffset",
+      "width",
+      "xmlns",
+    ]),
+    cl = Oo(["xlink:href", "xml:id", "xlink:title", "xml:space", "xmlns:xlink"]),
+    hl = No(/\{\{[\w\W]*|[\w\W]*\}\}/gm),
+    ul = No(/<%[\w\W]*|[\w\W]*%>/gm),
+    dl = No(/\${[\w\W]*}/gm),
+    pl = No(/^data-[\-\w.\u00B7-\uFFFF]/),
+    fl = No(/^aria-[\-\w]+$/),
+    gl = No(/^(?:(?:(?:f|ht)tps?|mailto|tel|callto|cid|xmpp):|[^a-z]|[a-z+.\-]+(?:[^a-z+.\-:]|$))/i),
+    yl = No(/^(?:\w+script|data):/i),
+    ml = No(/[\u0000-\u0020\u00A0\u1680\u180E\u2000-\u2029\u205F\u3000]/g),
+    bl = No(/^html$/i),
+    _l = function() {
+      return "undefined" == typeof window ? null : window;
+    },
+    xl = function(t, e) {
+      if ("object" !== vo(t) || "function" != typeof t.createPolicy) return null;
+      var n = null, i = "data-tt-policy-suffix";
+      e.currentScript && e.currentScript.hasAttribute(i) && (n = e.currentScript.getAttribute(i));
+      var r = "dompurify" + (n ? "#" + n : "");
+      try {
+        return t.createPolicy(r, {
+          createHTML: function(t) {
+            return t;
+          },
+          createScriptURL: function(t) {
+            return t;
+          },
+        });
+      } catch (t) {
+        return console.warn("TrustedTypes policy " + r + " could not be created."), null;
+      }
+    };
+  var vl = function t() {
+    var e = arguments.length > 0 && void 0 !== arguments[0] ? arguments[0] : _l(),
+      n = function(e) {
+        return t(e);
+      };
+    if (n.version = "2.4.1", n.removed = [], !e || !e.document || 9 !== e.document.nodeType) {
+      return n.isSupported = !1, n;
+    }
+    var i = e.document,
+      r = e.document,
+      a = e.DocumentFragment,
+      s = e.HTMLTemplateElement,
+      o = e.Node,
+      l = e.Element,
+      c = e.NodeFilter,
+      h = e.NamedNodeMap,
+      u = void 0 === h ? e.NamedNodeMap || e.MozNamedAttrMap : h,
+      d = e.HTMLFormElement,
+      p = e.DOMParser,
+      f = e.trustedTypes,
+      g = l.prototype,
+      y = Ko(g, "cloneNode"),
+      m = Ko(g, "nextSibling"),
+      b = Ko(g, "childNodes"),
+      _ = Ko(g, "parentNode");
+    if ("function" == typeof s) {
+      var x = r.createElement("template");
+      x.content && x.content.ownerDocument && (r = x.content.ownerDocument);
+    }
+    var v = xl(f, i),
+      k = v ? v.createHTML("") : "",
+      w = r,
+      T = w.implementation,
+      C = w.createNodeIterator,
+      E = w.createDocumentFragment,
+      S = w.getElementsByTagName,
+      A = i.importNode,
+      D = {};
+    try {
+      D = Qo(r).documentMode ? r.documentMode : {};
+    } catch (t) {}
+    var L = {};
+    n.isSupported = "function" == typeof _ && T && void 0 !== T.createHTMLDocument && 9 !== D;
+    var O,
+      N,
+      M = hl,
+      B = ul,
+      I = dl,
+      F = pl,
+      R = fl,
+      $ = yl,
+      P = ml,
+      Y = gl,
+      j = null,
+      z = Zo({}, [].concat(To(Jo), To(tl), To(el), To(il), To(al))),
+      U = null,
+      W = Zo({}, [].concat(To(sl), To(ol), To(ll), To(cl))),
+      H = Object.seal(
+        Object.create(null, {
+          tagNameCheck: { writable: !0, configurable: !1, enumerable: !0, value: null },
+          attributeNameCheck: { writable: !0, configurable: !1, enumerable: !0, value: null },
+          allowCustomizedBuiltInElements: { writable: !0, configurable: !1, enumerable: !0, value: !1 },
+        }),
+      ),
+      q = null,
+      V = null,
+      G = !0,
+      X = !0,
+      Z = !1,
+      Q = !1,
+      K = !1,
+      J = !1,
+      tt = !1,
+      et = !1,
+      nt = !1,
+      it = !1,
+      rt = !0,
+      at = !1,
+      st = !0,
+      ot = !1,
+      lt = {},
+      ct = null,
+      ht = Zo({}, [
+        "annotation-xml",
+        "audio",
+        "colgroup",
+        "desc",
+        "foreignobject",
+        "head",
+        "iframe",
+        "math",
+        "mi",
+        "mn",
+        "mo",
+        "ms",
+        "mtext",
+        "noembed",
+        "noframes",
+        "noscript",
+        "plaintext",
+        "script",
+        "style",
+        "svg",
+        "template",
+        "thead",
+        "title",
+        "video",
+        "xmp",
+      ]),
+      ut = null,
+      dt = Zo({}, ["audio", "video", "img", "source", "image", "track"]),
+      pt = null,
+      ft = Zo({}, [
+        "alt",
+        "class",
+        "for",
+        "id",
+        "label",
+        "name",
+        "pattern",
+        "placeholder",
+        "role",
+        "summary",
+        "title",
+        "value",
+        "style",
+        "xmlns",
+      ]),
+      gt = "http://www.w3.org/1998/Math/MathML",
+      yt = "http://www.w3.org/2000/svg",
+      mt = "http://www.w3.org/1999/xhtml",
+      bt = mt,
+      _t = !1,
+      xt = null,
+      vt = Zo({}, [gt, yt, mt], zo),
+      kt = ["application/xhtml+xml", "text/html"],
+      wt = null,
+      Tt = r.createElement("form"),
+      Ct = function(t) {
+        return t instanceof RegExp || t instanceof Function;
+      },
+      Et = function(t) {
+        wt && wt === t
+          || (t && "object" === vo(t) || (t = {}),
+            t = Qo(t),
+            O = O = -1 === kt.indexOf(t.PARSER_MEDIA_TYPE) ? "text/html" : t.PARSER_MEDIA_TYPE,
+            N = "application/xhtml+xml" === O ? zo : jo,
+            j = "ALLOWED_TAGS" in t ? Zo({}, t.ALLOWED_TAGS, N) : z,
+            U = "ALLOWED_ATTR" in t ? Zo({}, t.ALLOWED_ATTR, N) : W,
+            xt = "ALLOWED_NAMESPACES" in t ? Zo({}, t.ALLOWED_NAMESPACES, zo) : vt,
+            pt = "ADD_URI_SAFE_ATTR" in t ? Zo(Qo(ft), t.ADD_URI_SAFE_ATTR, N) : ft,
+            ut = "ADD_DATA_URI_TAGS" in t ? Zo(Qo(dt), t.ADD_DATA_URI_TAGS, N) : dt,
+            ct = "FORBID_CONTENTS" in t ? Zo({}, t.FORBID_CONTENTS, N) : ht,
+            q = "FORBID_TAGS" in t ? Zo({}, t.FORBID_TAGS, N) : {},
+            V = "FORBID_ATTR" in t ? Zo({}, t.FORBID_ATTR, N) : {},
+            lt = "USE_PROFILES" in t && t.USE_PROFILES,
+            G = !1 !== t.ALLOW_ARIA_ATTR,
+            X = !1 !== t.ALLOW_DATA_ATTR,
+            Z = t.ALLOW_UNKNOWN_PROTOCOLS || !1,
+            Q = t.SAFE_FOR_TEMPLATES || !1,
+            K = t.WHOLE_DOCUMENT || !1,
+            et = t.RETURN_DOM || !1,
+            nt = t.RETURN_DOM_FRAGMENT || !1,
+            it = t.RETURN_TRUSTED_TYPE || !1,
+            tt = t.FORCE_BODY || !1,
+            rt = !1 !== t.SANITIZE_DOM,
+            at = t.SANITIZE_NAMED_PROPS || !1,
+            st = !1 !== t.KEEP_CONTENT,
+            ot = t.IN_PLACE || !1,
+            Y = t.ALLOWED_URI_REGEXP || Y,
+            bt = t.NAMESPACE || mt,
+            t.CUSTOM_ELEMENT_HANDLING && Ct(t.CUSTOM_ELEMENT_HANDLING.tagNameCheck)
+            && (H.tagNameCheck = t.CUSTOM_ELEMENT_HANDLING.tagNameCheck),
+            t.CUSTOM_ELEMENT_HANDLING && Ct(t.CUSTOM_ELEMENT_HANDLING.attributeNameCheck)
+            && (H.attributeNameCheck = t.CUSTOM_ELEMENT_HANDLING.attributeNameCheck),
+            t.CUSTOM_ELEMENT_HANDLING && "boolean" == typeof t.CUSTOM_ELEMENT_HANDLING.allowCustomizedBuiltInElements
+            && (H.allowCustomizedBuiltInElements = t.CUSTOM_ELEMENT_HANDLING.allowCustomizedBuiltInElements),
+            Q && (X = !1),
+            nt && (et = !0),
+            lt
+            && (j = Zo({}, To(al)),
+              U = [],
+              !0 === lt.html && (Zo(j, Jo), Zo(U, sl)),
+              !0 === lt.svg && (Zo(j, tl), Zo(U, ol), Zo(U, cl)),
+              !0 === lt.svgFilters && (Zo(j, el), Zo(U, ol), Zo(U, cl)),
+              !0 === lt.mathMl && (Zo(j, il), Zo(U, ll), Zo(U, cl))),
+            t.ADD_TAGS && (j === z && (j = Qo(j)), Zo(j, t.ADD_TAGS, N)),
+            t.ADD_ATTR && (U === W && (U = Qo(U)), Zo(U, t.ADD_ATTR, N)),
+            t.ADD_URI_SAFE_ATTR && Zo(pt, t.ADD_URI_SAFE_ATTR, N),
+            t.FORBID_CONTENTS && (ct === ht && (ct = Qo(ct)), Zo(ct, t.FORBID_CONTENTS, N)),
+            st && (j["#text"] = !0),
+            K && Zo(j, ["html", "head", "body"]),
+            j.table && (Zo(j, ["tbody"]), delete q.tbody),
+            Oo && Oo(t),
+            wt = t);
+      },
+      St = Zo({}, ["mi", "mo", "mn", "ms", "mtext"]),
+      At = Zo({}, ["foreignobject", "desc", "title", "annotation-xml"]),
+      Dt = Zo({}, ["title", "style", "font", "a", "script"]),
+      Lt = Zo({}, tl);
+    Zo(Lt, el), Zo(Lt, nl);
+    var Ot = Zo({}, il);
+    Zo(Ot, rl);
+    var Nt = function(t) {
+        Yo(n.removed, { element: t });
+        try {
+          t.parentNode.removeChild(t);
+        } catch (e) {
+          try {
+            t.outerHTML = k;
+          } catch (e) {
+            t.remove();
+          }
+        }
+      },
+      Mt = function(t, e) {
+        try {
+          Yo(n.removed, { attribute: e.getAttributeNode(t), from: e });
+        } catch (t) {
+          Yo(n.removed, { attribute: null, from: e });
+        }
+        if (e.removeAttribute(t), "is" === t && !U[t]) {
+          if (et || nt) {
+            try {
+              Nt(e);
+            } catch (t) {}
+          } else {try {
+              e.setAttribute(t, "");
+            } catch (t) {}}
+        }
+      },
+      Bt = function(t) {
+        var e, n;
+        if (tt) t = "<remove></remove>" + t;
+        else {
+          var i = Uo(t, /^[\r\n\t ]+/);
+          n = i && i[0];
+        }
+        "application/xhtml+xml" === O && bt === mt
+          && (t = "<html xmlns=\"http://www.w3.org/1999/xhtml\"><head></head><body>" + t + "</body></html>");
+        var a = v ? v.createHTML(t) : t;
+        if (bt === mt) {
+          try {
+            e = (new p()).parseFromString(a, O);
+          } catch (t) {}
+        }
+        if (!e || !e.documentElement) {
+          e = T.createDocument(bt, "template", null);
+          try {
+            e.documentElement.innerHTML = _t ? "" : a;
+          } catch (t) {}
+        }
+        var s = e.body || e.documentElement;
+        return t && n && s.insertBefore(r.createTextNode(n), s.childNodes[0] || null),
+          bt === mt ? S.call(e, K ? "html" : "body")[0] : K ? e.documentElement : s;
+      },
+      It = function(t) {
+        return C.call(t.ownerDocument || t, t, c.SHOW_ELEMENT | c.SHOW_COMMENT | c.SHOW_TEXT, null, !1);
+      },
+      Ft = function(t) {
+        return "object" === vo(o)
+          ? t instanceof o
+          : t && "object" === vo(t) && "number" == typeof t.nodeType && "string" == typeof t.nodeName;
+      },
+      Rt = function(t, e, i) {
+        L[t] && $o(L[t], function(t) {
+          t.call(n, e, i, wt);
+        });
+      },
+      $t = function(t) {
+        var e, i;
+        if (
+          Rt("beforeSanitizeElements", t, null),
+            (i = t) instanceof d
+            && ("string" != typeof i.nodeName || "string" != typeof i.textContent || "function" != typeof i.removeChild
+              || !(i.attributes instanceof u) || "function" != typeof i.removeAttribute
+              || "function" != typeof i.setAttribute || "string" != typeof i.namespaceURI
+              || "function" != typeof i.insertBefore || "function" != typeof i.hasChildNodes)
+        ) return Nt(t), !0;
+        if (Vo(/[\u0080-\uFFFF]/, t.nodeName)) return Nt(t), !0;
+        var r = N(t.nodeName);
+        if (
+          Rt("uponSanitizeElement", t, { tagName: r, allowedTags: j }),
+            t.hasChildNodes() && !Ft(t.firstElementChild) && (!Ft(t.content) || !Ft(t.content.firstElementChild))
+            && Vo(/<[/\w]/g, t.innerHTML) && Vo(/<[/\w]/g, t.textContent)
+        ) return Nt(t), !0;
+        if ("select" === r && Vo(/<template/i, t.innerHTML)) return Nt(t), !0;
+        if (!j[r] || q[r]) {
+          if (!q[r] && Yt(r)) {
+            if (H.tagNameCheck instanceof RegExp && Vo(H.tagNameCheck, r)) return !1;
+            if (H.tagNameCheck instanceof Function && H.tagNameCheck(r)) return !1;
+          }
+          if (st && !ct[r]) {
+            var a = _(t) || t.parentNode, s = b(t) || t.childNodes;
+            if (s && a) for (var o = s.length - 1; o >= 0; --o) a.insertBefore(y(s[o], !0), m(t));
+          }
+          return Nt(t), !0;
+        }
+        return t instanceof l && !function(t) {
+            var e = _(t);
+            e && e.tagName || (e = { namespaceURI: bt, tagName: "template" });
+            var n = jo(t.tagName), i = jo(e.tagName);
+            return !!xt[t.namespaceURI]
+              && (t.namespaceURI === yt
+                ? e.namespaceURI === mt
+                  ? "svg" === n
+                  : e.namespaceURI === gt
+                  ? "svg" === n && ("annotation-xml" === i || St[i])
+                  : Boolean(Lt[n])
+                : t.namespaceURI === gt
+                ? e.namespaceURI === mt ? "math" === n : e.namespaceURI === yt ? "math" === n && At[i] : Boolean(Ot[n])
+                : t.namespaceURI === mt
+                ? !(e.namespaceURI === yt && !At[i]) && !(e.namespaceURI === gt && !St[i]) && !Ot[n]
+                  && (Dt[n] || !Lt[n])
+                : !("application/xhtml+xml" !== O || !xt[t.namespaceURI]));
+          }(t)
+          ? (Nt(t), !0)
+          : "noscript" !== r && "noembed" !== r || !Vo(/<\/no(script|embed)/i, t.innerHTML)
+          ? (Q && 3 === t.nodeType
+            && (e = t.textContent,
+              e = Wo(e, M, " "),
+              e = Wo(e, B, " "),
+              e = Wo(e, I, " "),
+              t.textContent !== e && (Yo(n.removed, { element: t.cloneNode() }), t.textContent = e)),
+            Rt("afterSanitizeElements", t, null),
+            !1)
+          : (Nt(t), !0);
+      },
+      Pt = function(t, e, n) {
+        if (rt && ("id" === e || "name" === e) && (n in r || n in Tt)) return !1;
+        if (X && !V[e] && Vo(F, e));
+        else if (G && Vo(R, e));
+        else if (!U[e] || V[e]) {
+          if (
+            !(Yt(t)
+                && (H.tagNameCheck instanceof RegExp && Vo(H.tagNameCheck, t)
+                  || H.tagNameCheck instanceof Function && H.tagNameCheck(t))
+                && (H.attributeNameCheck instanceof RegExp && Vo(H.attributeNameCheck, e)
+                  || H.attributeNameCheck instanceof Function && H.attributeNameCheck(e))
+              || "is" === e && H.allowCustomizedBuiltInElements
+                && (H.tagNameCheck instanceof RegExp && Vo(H.tagNameCheck, n)
+                  || H.tagNameCheck instanceof Function && H.tagNameCheck(n)))
+          ) return !1;
+        } else if (pt[e]);
+        else if (Vo(Y, Wo(n, P, "")));
+        else if (
+          "src" !== e && "xlink:href" !== e && "href" !== e || "script" === t || 0 !== Ho(n, "data:") || !ut[t]
+        ) {
+          if (Z && !Vo($, Wo(n, P, "")));
+          else if (n) return !1;
+        } else;
+        return !0;
+      },
+      Yt = function(t) {
+        return t.indexOf("-") > 0;
+      },
+      jt = function(t) {
+        var e, i, r, a;
+        Rt("beforeSanitizeAttributes", t, null);
+        var s = t.attributes;
+        if (s) {
+          var o = { attrName: "", attrValue: "", keepAttr: !0, allowedAttributes: U };
+          for (a = s.length; a--;) {
+            var l = e = s[a], c = l.name, h = l.namespaceURI;
+            if (
+              i = "value" === c ? e.value : qo(e.value),
+                r = N(c),
+                o.attrName = r,
+                o.attrValue = i,
+                o.keepAttr = !0,
+                o.forceKeepAttr = void 0,
+                Rt("uponSanitizeAttribute", t, o),
+                i = o.attrValue,
+                !o.forceKeepAttr && (Mt(c, t), o.keepAttr)
+            ) {
+              if (Vo(/\/>/i, i)) Mt(c, t);
+              else {
+                Q && (i = Wo(i, M, " "), i = Wo(i, B, " "), i = Wo(i, I, " "));
+                var u = N(t.nodeName);
+                if (Pt(u, r, i)) {
+                  if (
+                    !at || "id" !== r && "name" !== r || (Mt(c, t), i = "user-content-" + i),
+                      v && "object" === vo(f) && "function" == typeof f.getAttributeType
+                  ) {
+                    if (h);
+                    else {switch (f.getAttributeType(u, r)) {
+                        case "TrustedHTML":
+                          i = v.createHTML(i);
+                          break;
+                        case "TrustedScriptURL":
+                          i = v.createScriptURL(i);
+                      }}
+                  }
+                  try {
+                    h ? t.setAttributeNS(h, c, i) : t.setAttribute(c, i), Po(n.removed);
+                  } catch (t) {}
+                }
+              }
+            }
+          }
+          Rt("afterSanitizeAttributes", t, null);
+        }
+      },
+      zt = function t(e) {
+        var n, i = It(e);
+        for (Rt("beforeSanitizeShadowDOM", e, null); n = i.nextNode();) {
+          Rt("uponSanitizeShadowNode", n, null), $t(n) || (n.content instanceof a && t(n.content), jt(n));
+        }
+        Rt("afterSanitizeShadowDOM", e, null);
+      };
+    return n.sanitize = function(t) {
+      var r, s, l, c, h, u = arguments.length > 1 && void 0 !== arguments[1] ? arguments[1] : {};
+      if ((_t = !t) && (t = "\x3c!--\x3e"), "string" != typeof t && !Ft(t)) {
+        if ("function" != typeof t.toString) throw Go("toString is not a function");
+        if ("string" != typeof (t = t.toString())) throw Go("dirty is not a string, aborting");
+      }
+      if (!n.isSupported) {
+        if ("object" === vo(e.toStaticHTML) || "function" == typeof e.toStaticHTML) {
+          if ("string" == typeof t) return e.toStaticHTML(t);
+          if (Ft(t)) return e.toStaticHTML(t.outerHTML);
+        }
+        return t;
+      }
+      if (J || Et(u), n.removed = [], "string" == typeof t && (ot = !1), ot) {
+        if (t.nodeName) {
+          var d = N(t.nodeName);
+          if (!j[d] || q[d]) throw Go("root node is forbidden and cannot be sanitized in-place");
+        }
+      } else if (t instanceof o) {
+        1 === (s = (r = Bt("\x3c!----\x3e")).ownerDocument.importNode(t, !0)).nodeType && "BODY" === s.nodeName
+          || "HTML" === s.nodeName
+          ? r = s
+          : r.appendChild(s);
+      } else {
+        if (!et && !Q && !K && -1 === t.indexOf("<")) return v && it ? v.createHTML(t) : t;
+        if (!(r = Bt(t))) return et ? null : it ? k : "";
+      }
+      r && tt && Nt(r.firstChild);
+      for (var p = It(ot ? t : r); l = p.nextNode();) {
+        3 === l.nodeType && l === c || $t(l)
+          || (l.content instanceof a && zt(l.content), jt(l), c = l);
+      }
+      if (c = null, ot) return t;
+      if (et) {
+        if (nt) for (h = E.call(r.ownerDocument); r.firstChild;) h.appendChild(r.firstChild);
+        else h = r;
+        return U.shadowroot && (h = A.call(i, h, !0)), h;
+      }
+      var f = K ? r.outerHTML : r.innerHTML;
+      return K && j["!doctype"] && r.ownerDocument && r.ownerDocument.doctype && r.ownerDocument.doctype.name
+        && Vo(bl, r.ownerDocument.doctype.name) && (f = "<!DOCTYPE " + r.ownerDocument.doctype.name + ">\n" + f),
+        Q && (f = Wo(f, M, " "), f = Wo(f, B, " "), f = Wo(f, I, " ")),
+        v && it ? v.createHTML(f) : f;
+    },
+      n.setConfig = function(t) {
+        Et(t), J = !0;
+      },
+      n.clearConfig = function() {
+        wt = null, J = !1;
+      },
+      n.isValidAttribute = function(t, e, n) {
+        wt || Et({});
+        var i = N(t), r = N(e);
+        return Pt(i, r, n);
+      },
+      n.addHook = function(t, e) {
+        "function" == typeof e && (L[t] = L[t] || [], Yo(L[t], e));
+      },
+      n.removeHook = function(t) {
+        if (L[t]) return Po(L[t]);
+      },
+      n.removeHooks = function(t) {
+        L[t] && (L[t] = []);
+      },
+      n.removeAllHooks = function() {
+        L = {};
+      },
+      n;
+  }();
+  const kl = {
+    min: { r: 0, g: 0, b: 0, s: 0, l: 0, a: 0 },
+    max: { r: 255, g: 255, b: 255, h: 360, s: 100, l: 100, a: 1 },
+    clamp: {
+      r: t => t >= 255 ? 255 : t < 0 ? 0 : t,
+      g: t => t >= 255 ? 255 : t < 0 ? 0 : t,
+      b: t => t >= 255 ? 255 : t < 0 ? 0 : t,
+      h: t => t % 360,
+      s: t => t >= 100 ? 100 : t < 0 ? 0 : t,
+      l: t => t >= 100 ? 100 : t < 0 ? 0 : t,
+      a: t => t >= 1 ? 1 : t < 0 ? 0 : t,
+    },
+    toLinear: t => {
+      const e = t / 255;
+      return t > .03928 ? Math.pow((e + .055) / 1.055, 2.4) : e / 12.92;
+    },
+    hue2rgb: (
+      t,
+      e,
+      n,
+    ) => (n < 0 && (n += 1),
+      n > 1 && (n -= 1),
+      n < 1 / 6 ? t + 6 * (e - t) * n : n < .5 ? e : n < 2 / 3 ? t + (e - t) * (2 / 3 - n) * 6 : t),
+    hsl2rgb: ({ h: t, s: e, l: n }, i) => {
+      if (!e) return 2.55 * n;
+      t /= 360, e /= 100;
+      const r = (n /= 100) < .5 ? n * (1 + e) : n + e - n * e, a = 2 * n - r;
+      switch (i) {
+        case "r":
+          return 255 * kl.hue2rgb(a, r, t + 1 / 3);
+        case "g":
+          return 255 * kl.hue2rgb(a, r, t);
+        case "b":
+          return 255 * kl.hue2rgb(a, r, t - 1 / 3);
+      }
+    },
+    rgb2hsl: ({ r: t, g: e, b: n }, i) => {
+      t /= 255, e /= 255, n /= 255;
+      const r = Math.max(t, e, n), a = Math.min(t, e, n), s = (r + a) / 2;
+      if ("l" === i) return 100 * s;
+      if (r === a) return 0;
+      const o = r - a;
+      if ("s" === i) return 100 * (s > .5 ? o / (2 - r - a) : o / (r + a));
+      switch (r) {
+        case t:
+          return 60 * ((e - n) / o + (e < n ? 6 : 0));
+        case e:
+          return 60 * ((n - t) / o + 2);
+        case n:
+          return 60 * ((t - e) / o + 4);
+        default:
+          return -1;
+      }
+    },
+  };
+  const wl = {
+    clamp: (t, e, n) => e > n ? Math.min(e, Math.max(n, t)) : Math.min(n, Math.max(e, t)),
+    round: t => Math.round(1e10 * t) / 1e10,
+  };
+  const Tl = {
+    dec2hex: t => {
+      const e = Math.round(t).toString(16);
+      return e.length > 1 ? e : `0${e}`;
+    },
+  };
+  var Cl = { channel: kl, lang: wl, unit: Tl };
+  const El = {};
+  for (let t = 0; t <= 255; t++) El[t] = Cl.unit.dec2hex(t);
+  const Sl = 0, Al = 1, Dl = 2;
+  var Ll = class {
+    constructor() {
+      this.type = Sl;
+    }
+    get() {
+      return this.type;
+    }
+    set(t) {
+      if (this.type && this.type !== t) throw new Error("Cannot change both RGB and HSL channels at the same time");
+      this.type = t;
+    }
+    reset() {
+      this.type = Sl;
+    }
+    is(t) {
+      return this.type === t;
+    }
+  };
+  var Ol = class {
+    constructor(t, e) {
+      this.color = e, this.changed = !1, this.data = t, this.type = new Ll();
+    }
+    set(t, e) {
+      return this.color = e, this.changed = !1, this.data = t, this.type.type = Sl, this;
+    }
+    _ensureHSL() {
+      const t = this.data, { h: e, s: n, l: i } = t;
+      void 0 === e && (t.h = Cl.channel.rgb2hsl(t, "h")),
+        void 0 === n && (t.s = Cl.channel.rgb2hsl(t, "s")),
+        void 0 === i && (t.l = Cl.channel.rgb2hsl(t, "l"));
+    }
+    _ensureRGB() {
+      const t = this.data, { r: e, g: n, b: i } = t;
+      void 0 === e && (t.r = Cl.channel.hsl2rgb(t, "r")),
+        void 0 === n && (t.g = Cl.channel.hsl2rgb(t, "g")),
+        void 0 === i && (t.b = Cl.channel.hsl2rgb(t, "b"));
+    }
+    get r() {
+      const t = this.data, e = t.r;
+      return this.type.is(Dl) || void 0 === e ? (this._ensureHSL(), Cl.channel.hsl2rgb(t, "r")) : e;
+    }
+    get g() {
+      const t = this.data, e = t.g;
+      return this.type.is(Dl) || void 0 === e ? (this._ensureHSL(), Cl.channel.hsl2rgb(t, "g")) : e;
+    }
+    get b() {
+      const t = this.data, e = t.b;
+      return this.type.is(Dl) || void 0 === e ? (this._ensureHSL(), Cl.channel.hsl2rgb(t, "b")) : e;
+    }
+    get h() {
+      const t = this.data, e = t.h;
+      return this.type.is(Al) || void 0 === e ? (this._ensureRGB(), Cl.channel.rgb2hsl(t, "h")) : e;
+    }
+    get s() {
+      const t = this.data, e = t.s;
+      return this.type.is(Al) || void 0 === e ? (this._ensureRGB(), Cl.channel.rgb2hsl(t, "s")) : e;
+    }
+    get l() {
+      const t = this.data, e = t.l;
+      return this.type.is(Al) || void 0 === e ? (this._ensureRGB(), Cl.channel.rgb2hsl(t, "l")) : e;
+    }
+    get a() {
+      return this.data.a;
+    }
+    set r(t) {
+      this.type.set(Al), this.changed = !0, this.data.r = t;
+    }
+    set g(t) {
+      this.type.set(Al), this.changed = !0, this.data.g = t;
+    }
+    set b(t) {
+      this.type.set(Al), this.changed = !0, this.data.b = t;
+    }
+    set h(t) {
+      this.type.set(Dl), this.changed = !0, this.data.h = t;
+    }
+    set s(t) {
+      this.type.set(Dl), this.changed = !0, this.data.s = t;
+    }
+    set l(t) {
+      this.type.set(Dl), this.changed = !0, this.data.l = t;
+    }
+    set a(t) {
+      this.changed = !0, this.data.a = t;
+    }
+  };
+  var Nl = new Ol({ r: 0, g: 0, b: 0, a: 0 }, "transparent");
+  const Ml = {
+    re: /^#((?:[a-f0-9]{2}){2,4}|[a-f0-9]{3})$/i,
+    parse: t => {
+      if (35 !== t.charCodeAt(0)) return;
+      const e = t.match(Ml.re);
+      if (!e) return;
+      const n = e[1],
+        i = parseInt(n, 16),
+        r = n.length,
+        a = r % 4 == 0,
+        s = r > 4,
+        o = s ? 1 : 17,
+        l = s ? 8 : 4,
+        c = a ? 0 : -1,
+        h = s ? 255 : 15;
+      return Nl.set({
+        r: (i >> l * (c + 3) & h) * o,
+        g: (i >> l * (c + 2) & h) * o,
+        b: (i >> l * (c + 1) & h) * o,
+        a: a ? (i & h) * o / 255 : 1,
+      }, t);
+    },
+    stringify: t => {
+      const { r: e, g: n, b: i, a: r } = t;
+      return r < 1
+        ? `#${El[Math.round(e)]}${El[Math.round(n)]}${El[Math.round(i)]}${El[Math.round(255 * r)]}`
+        : `#${El[Math.round(e)]}${El[Math.round(n)]}${El[Math.round(i)]}`;
+    },
+  };
+  var Bl = Ml;
+  const Il = {
+    re:
+      /^hsla?\(\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e-?\d+)?(?:deg|grad|rad|turn)?)\s*?(?:,|\s)\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e-?\d+)?%)\s*?(?:,|\s)\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e-?\d+)?%)(?:\s*?(?:,|\/)\s*?\+?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e-?\d+)?(%)?))?\s*?\)$/i,
+    hueRe: /^(.+?)(deg|grad|rad|turn)$/i,
+    _hue2deg: t => {
+      const e = t.match(Il.hueRe);
+      if (e) {
+        const [, t, n] = e;
+        switch (n) {
+          case "grad":
+            return Cl.channel.clamp.h(.9 * parseFloat(t));
+          case "rad":
+            return Cl.channel.clamp.h(180 * parseFloat(t) / Math.PI);
+          case "turn":
+            return Cl.channel.clamp.h(360 * parseFloat(t));
+        }
+      }
+      return Cl.channel.clamp.h(parseFloat(t));
+    },
+    parse: t => {
+      const e = t.charCodeAt(0);
+      if (104 !== e && 72 !== e) return;
+      const n = t.match(Il.re);
+      if (!n) return;
+      const [, i, r, a, s, o] = n;
+      return Nl.set({
+        h: Il._hue2deg(i),
+        s: Cl.channel.clamp.s(parseFloat(r)),
+        l: Cl.channel.clamp.l(parseFloat(a)),
+        a: s ? Cl.channel.clamp.a(o ? parseFloat(s) / 100 : parseFloat(s)) : 1,
+      }, t);
+    },
+    stringify: t => {
+      const { h: e, s: n, l: i, a: r } = t;
+      return r < 1
+        ? `hsla(${Cl.lang.round(e)}, ${Cl.lang.round(n)}%, ${Cl.lang.round(i)}%, ${r})`
+        : `hsl(${Cl.lang.round(e)}, ${Cl.lang.round(n)}%, ${Cl.lang.round(i)}%)`;
+    },
+  };
+  var Fl = Il;
+  const Rl = {
+    colors: {
+      aliceblue: "#f0f8ff",
+      antiquewhite: "#faebd7",
+      aqua: "#00ffff",
+      aquamarine: "#7fffd4",
+      azure: "#f0ffff",
+      beige: "#f5f5dc",
+      bisque: "#ffe4c4",
+      black: "#000000",
+      blanchedalmond: "#ffebcd",
+      blue: "#0000ff",
+      blueviolet: "#8a2be2",
+      brown: "#a52a2a",
+      burlywood: "#deb887",
+      cadetblue: "#5f9ea0",
+      chartreuse: "#7fff00",
+      chocolate: "#d2691e",
+      coral: "#ff7f50",
+      cornflowerblue: "#6495ed",
+      cornsilk: "#fff8dc",
+      crimson: "#dc143c",
+      cyanaqua: "#00ffff",
+      darkblue: "#00008b",
+      darkcyan: "#008b8b",
+      darkgoldenrod: "#b8860b",
+      darkgray: "#a9a9a9",
+      darkgreen: "#006400",
+      darkgrey: "#a9a9a9",
+      darkkhaki: "#bdb76b",
+      darkmagenta: "#8b008b",
+      darkolivegreen: "#556b2f",
+      darkorange: "#ff8c00",
+      darkorchid: "#9932cc",
+      darkred: "#8b0000",
+      darksalmon: "#e9967a",
+      darkseagreen: "#8fbc8f",
+      darkslateblue: "#483d8b",
+      darkslategray: "#2f4f4f",
+      darkslategrey: "#2f4f4f",
+      darkturquoise: "#00ced1",
+      darkviolet: "#9400d3",
+      deeppink: "#ff1493",
+      deepskyblue: "#00bfff",
+      dimgray: "#696969",
+      dimgrey: "#696969",
+      dodgerblue: "#1e90ff",
+      firebrick: "#b22222",
+      floralwhite: "#fffaf0",
+      forestgreen: "#228b22",
+      fuchsia: "#ff00ff",
+      gainsboro: "#dcdcdc",
+      ghostwhite: "#f8f8ff",
+      gold: "#ffd700",
+      goldenrod: "#daa520",
+      gray: "#808080",
+      green: "#008000",
+      greenyellow: "#adff2f",
+      grey: "#808080",
+      honeydew: "#f0fff0",
+      hotpink: "#ff69b4",
+      indianred: "#cd5c5c",
+      indigo: "#4b0082",
+      ivory: "#fffff0",
+      khaki: "#f0e68c",
+      lavender: "#e6e6fa",
+      lavenderblush: "#fff0f5",
+      lawngreen: "#7cfc00",
+      lemonchiffon: "#fffacd",
+      lightblue: "#add8e6",
+      lightcoral: "#f08080",
+      lightcyan: "#e0ffff",
+      lightgoldenrodyellow: "#fafad2",
+      lightgray: "#d3d3d3",
+      lightgreen: "#90ee90",
+      lightgrey: "#d3d3d3",
+      lightpink: "#ffb6c1",
+      lightsalmon: "#ffa07a",
+      lightseagreen: "#20b2aa",
+      lightskyblue: "#87cefa",
+      lightslategray: "#778899",
+      lightslategrey: "#778899",
+      lightsteelblue: "#b0c4de",
+      lightyellow: "#ffffe0",
+      lime: "#00ff00",
+      limegreen: "#32cd32",
+      linen: "#faf0e6",
+      magenta: "#ff00ff",
+      maroon: "#800000",
+      mediumaquamarine: "#66cdaa",
+      mediumblue: "#0000cd",
+      mediumorchid: "#ba55d3",
+      mediumpurple: "#9370db",
+      mediumseagreen: "#3cb371",
+      mediumslateblue: "#7b68ee",
+      mediumspringgreen: "#00fa9a",
+      mediumturquoise: "#48d1cc",
+      mediumvioletred: "#c71585",
+      midnightblue: "#191970",
+      mintcream: "#f5fffa",
+      mistyrose: "#ffe4e1",
+      moccasin: "#ffe4b5",
+      navajowhite: "#ffdead",
+      navy: "#000080",
+      oldlace: "#fdf5e6",
+      olive: "#808000",
+      olivedrab: "#6b8e23",
+      orange: "#ffa500",
+      orangered: "#ff4500",
+      orchid: "#da70d6",
+      palegoldenrod: "#eee8aa",
+      palegreen: "#98fb98",
+      paleturquoise: "#afeeee",
+      palevioletred: "#db7093",
+      papayawhip: "#ffefd5",
+      peachpuff: "#ffdab9",
+      peru: "#cd853f",
+      pink: "#ffc0cb",
+      plum: "#dda0dd",
+      powderblue: "#b0e0e6",
+      purple: "#800080",
+      rebeccapurple: "#663399",
+      red: "#ff0000",
+      rosybrown: "#bc8f8f",
+      royalblue: "#4169e1",
+      saddlebrown: "#8b4513",
+      salmon: "#fa8072",
+      sandybrown: "#f4a460",
+      seagreen: "#2e8b57",
+      seashell: "#fff5ee",
+      sienna: "#a0522d",
+      silver: "#c0c0c0",
+      skyblue: "#87ceeb",
+      slateblue: "#6a5acd",
+      slategray: "#708090",
+      slategrey: "#708090",
+      snow: "#fffafa",
+      springgreen: "#00ff7f",
+      tan: "#d2b48c",
+      teal: "#008080",
+      thistle: "#d8bfd8",
+      transparent: "#00000000",
+      turquoise: "#40e0d0",
+      violet: "#ee82ee",
+      wheat: "#f5deb3",
+      white: "#ffffff",
+      whitesmoke: "#f5f5f5",
+      yellow: "#ffff00",
+      yellowgreen: "#9acd32",
+    },
+    parse: t => {
+      t = t.toLowerCase();
+      const e = Rl.colors[t];
+      if (e) return Bl.parse(e);
+    },
+    stringify: t => {
+      const e = Bl.stringify(t);
+      for (const t in Rl.colors) if (Rl.colors[t] === e) return t;
+    },
+  };
+  var $l = Rl;
+  const Pl = {
+    re:
+      /^rgba?\(\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e\d+)?(%?))\s*?(?:,|\s)\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e\d+)?(%?))\s*?(?:,|\s)\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e\d+)?(%?))(?:\s*?(?:,|\/)\s*?\+?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e\d+)?(%?)))?\s*?\)$/i,
+    parse: t => {
+      const e = t.charCodeAt(0);
+      if (114 !== e && 82 !== e) return;
+      const n = t.match(Pl.re);
+      if (!n) return;
+      const [, i, r, a, s, o, l, c, h] = n;
+      return Nl.set({
+        r: Cl.channel.clamp.r(r ? 2.55 * parseFloat(i) : parseFloat(i)),
+        g: Cl.channel.clamp.g(s ? 2.55 * parseFloat(a) : parseFloat(a)),
+        b: Cl.channel.clamp.b(l ? 2.55 * parseFloat(o) : parseFloat(o)),
+        a: c ? Cl.channel.clamp.a(h ? parseFloat(c) / 100 : parseFloat(c)) : 1,
+      }, t);
+    },
+    stringify: t => {
+      const { r: e, g: n, b: i, a: r } = t;
+      return r < 1
+        ? `rgba(${Cl.lang.round(e)}, ${Cl.lang.round(n)}, ${Cl.lang.round(i)}, ${Cl.lang.round(r)})`
+        : `rgb(${Cl.lang.round(e)}, ${Cl.lang.round(n)}, ${Cl.lang.round(i)})`;
+    },
+  };
+  var Yl = Pl;
+  const jl = {
+    format: { keyword: $l, hex: Bl, rgb: Yl, rgba: Yl, hsl: Fl, hsla: Fl },
+    parse: t => {
+      if ("string" != typeof t) return t;
+      const e = Bl.parse(t) || Yl.parse(t) || Fl.parse(t) || $l.parse(t);
+      if (e) return e;
+      throw new Error(`Unsupported color format: "${t}"`);
+    },
+    stringify: t =>
+      !t.changed && t.color
+        ? t.color
+        : t.type.is(Dl) || void 0 === t.data.r
+        ? Fl.stringify(t)
+        : t.a < 1 || !Number.isInteger(t.r) || !Number.isInteger(t.g) || !Number.isInteger(t.b)
+        ? Yl.stringify(t)
+        : Bl.stringify(t),
+  };
+  var zl = jl;
+  var Ul = (t, e) => {
+    const n = zl.parse(t);
+    for (const t in e) n[t] = Cl.channel.clamp[t](e[t]);
+    return zl.stringify(n);
+  };
+  var Wl = (t, e, n = 0, i = 1) => {
+    if ("number" != typeof t) return Ul(t, { a: e });
+    const r = Nl.set({
+      r: Cl.channel.clamp.r(t),
+      g: Cl.channel.clamp.g(e),
+      b: Cl.channel.clamp.b(n),
+      a: Cl.channel.clamp.a(i),
+    });
+    return zl.stringify(r);
+  };
+  var Hl = (t, e, n) => {
+    const i = zl.parse(t), r = i[e], a = Cl.channel.clamp[e](r + n);
+    return r !== a && (i[e] = a), zl.stringify(i);
+  };
+  var ql = (t, e) => Hl(t, "l", e);
+  var Vl = (t, e) => Hl(t, "l", -e);
+  var Gl = (t, e) => {
+    const n = zl.parse(t), i = {};
+    for (const t in e) e[t] && (i[t] = n[t] + e[t]);
+    return Ul(t, i);
+  };
+  var Xl = (t, e, n = 50) => {
+    const { r: i, g: r, b: a, a: s } = zl.parse(t),
+      { r: o, g: l, b: c, a: h } = zl.parse(e),
+      u = n / 100,
+      d = 2 * u - 1,
+      p = s - h,
+      f = ((d * p == -1 ? d : (d + p) / (1 + d * p)) + 1) / 2,
+      g = 1 - f;
+    return Wl(i * f + o * g, r * f + l * g, a * f + c * g, s * u + h * (1 - u));
+  };
+  var Zl = (t, e = 100) => {
+      const n = zl.parse(t);
+      return n.r = 255 - n.r, n.g = 255 - n.g, n.b = 255 - n.b, Xl(n, t, e);
+    },
+    Ql = "object" == typeof global && global && global.Object === Object && global,
+    Kl = "object" == typeof self && self && self.Object === Object && self,
+    Jl = Ql || Kl || Function("return this")(),
+    tc = Jl.Symbol,
+    ec = Object.prototype,
+    nc = ec.hasOwnProperty,
+    ic = ec.toString,
+    rc = tc ? tc.toStringTag : void 0;
+  var ac = Object.prototype.toString;
+  var sc = "[object Null]", oc = "[object Undefined]", lc = tc ? tc.toStringTag : void 0;
+  function cc(t) {
+    return null == t ? void 0 === t ? oc : sc : lc && lc in Object(t)
+      ? function(t) {
+        var e = nc.call(t, rc), n = t[rc];
+        try {
+          t[rc] = void 0;
+          var i = !0;
+        } catch (t) {}
+        var r = ic.call(t);
+        return i && (e ? t[rc] = n : delete t[rc]), r;
+      }(t)
+      : function(t) {
+        return ac.call(t);
+      }(t);
+  }
+  function hc(t) {
+    var e = typeof t;
+    return null != t && ("object" == e || "function" == e);
+  }
+  var uc = "[object AsyncFunction]", dc = "[object Function]", pc = "[object GeneratorFunction]", fc = "[object Proxy]";
+  function gc(t) {
+    if (!hc(t)) return !1;
+    var e = cc(t);
+    return e == dc || e == pc || e == uc || e == fc;
+  }
+  var yc,
+    mc = Jl["__core-js_shared__"],
+    bc = (yc = /[^.]+$/.exec(mc && mc.keys && mc.keys.IE_PROTO || "")) ? "Symbol(src)_1." + yc : "";
+  var _c = Function.prototype.toString;
+  function xc(t) {
+    if (null != t) {
+      try {
+        return _c.call(t);
+      } catch (t) {}
+      try {
+        return t + "";
+      } catch (t) {}
+    }
+    return "";
+  }
+  var vc = /^\[object .+?Constructor\]$/,
+    kc = Function.prototype,
+    wc = Object.prototype,
+    Tc = kc.toString,
+    Cc = wc.hasOwnProperty,
+    Ec = RegExp(
+      "^"
+        + Tc.call(Cc).replace(/[\\^$.*+?()[\]{}|]/g, "\\$&").replace(
+          /hasOwnProperty|(function).*?(?=\\\()| for .+?(?=\\\])/g,
+          "$1.*?",
+        ) + "$",
+    );
+  function Sc(t) {
+    return !(!hc(t) || function(t) {
+      return !!bc && bc in t;
+    }(t)) && (gc(t) ? Ec : vc).test(xc(t));
+  }
+  function Ac(t, e) {
+    var n = function(t, e) {
+      return null == t ? void 0 : t[e];
+    }(t, e);
+    return Sc(n) ? n : void 0;
+  }
+  var Dc = Ac(Object, "create");
+  var Lc = "__lodash_hash_undefined__", Oc = Object.prototype.hasOwnProperty;
+  var Nc = Object.prototype.hasOwnProperty;
+  var Mc = "__lodash_hash_undefined__";
+  function Bc(t) {
+    var e = -1, n = null == t ? 0 : t.length;
+    for (this.clear(); ++e < n;) {
+      var i = t[e];
+      this.set(i[0], i[1]);
+    }
+  }
+  function Ic(t, e) {
+    return t === e || t != t && e != e;
+  }
+  function Fc(t, e) {
+    for (var n = t.length; n--;) if (Ic(t[n][0], e)) return n;
+    return -1;
+  }
+  Bc.prototype.clear = function() {
+    this.__data__ = Dc ? Dc(null) : {}, this.size = 0;
+  },
+    Bc.prototype.delete = function(t) {
+      var e = this.has(t) && delete this.__data__[t];
+      return this.size -= e ? 1 : 0, e;
+    },
+    Bc.prototype.get = function(t) {
+      var e = this.__data__;
+      if (Dc) {
+        var n = e[t];
+        return n === Lc ? void 0 : n;
+      }
+      return Oc.call(e, t) ? e[t] : void 0;
+    },
+    Bc.prototype.has = function(t) {
+      var e = this.__data__;
+      return Dc ? void 0 !== e[t] : Nc.call(e, t);
+    },
+    Bc.prototype.set = function(t, e) {
+      var n = this.__data__;
+      return this.size += this.has(t) ? 0 : 1, n[t] = Dc && void 0 === e ? Mc : e, this;
+    };
+  var Rc = Array.prototype.splice;
+  function $c(t) {
+    var e = -1, n = null == t ? 0 : t.length;
+    for (this.clear(); ++e < n;) {
+      var i = t[e];
+      this.set(i[0], i[1]);
+    }
+  }
+  $c.prototype.clear = function() {
+    this.__data__ = [], this.size = 0;
+  },
+    $c.prototype.delete = function(t) {
+      var e = this.__data__, n = Fc(e, t);
+      return !(n < 0) && (n == e.length - 1 ? e.pop() : Rc.call(e, n, 1), --this.size, !0);
+    },
+    $c.prototype.get = function(t) {
+      var e = this.__data__, n = Fc(e, t);
+      return n < 0 ? void 0 : e[n][1];
+    },
+    $c.prototype.has = function(t) {
+      return Fc(this.__data__, t) > -1;
+    },
+    $c.prototype.set = function(t, e) {
+      var n = this.__data__, i = Fc(n, t);
+      return i < 0 ? (++this.size, n.push([t, e])) : n[i][1] = e, this;
+    };
+  var Pc = Ac(Jl, "Map");
+  function Yc(t, e) {
+    var n = t.__data__;
+    return (function(t) {
+        var e = typeof t;
+        return "string" == e || "number" == e || "symbol" == e || "boolean" == e ? "__proto__" !== t : null === t;
+      })(e)
+      ? n["string" == typeof e ? "string" : "hash"]
+      : n.map;
+  }
+  function jc(t) {
+    var e = -1, n = null == t ? 0 : t.length;
+    for (this.clear(); ++e < n;) {
+      var i = t[e];
+      this.set(i[0], i[1]);
+    }
+  }
+  jc.prototype.clear = function() {
+    this.size = 0, this.__data__ = { hash: new Bc(), map: new (Pc || $c)(), string: new Bc() };
+  },
+    jc.prototype.delete = function(t) {
+      var e = Yc(this, t).delete(t);
+      return this.size -= e ? 1 : 0, e;
+    },
+    jc.prototype.get = function(t) {
+      return Yc(this, t).get(t);
+    },
+    jc.prototype.has = function(t) {
+      return Yc(this, t).has(t);
+    },
+    jc.prototype.set = function(t, e) {
+      var n = Yc(this, t), i = n.size;
+      return n.set(t, e), this.size += n.size == i ? 0 : 1, this;
+    };
+  var zc = "Expected a function";
+  function Uc(t, e) {
+    if ("function" != typeof t || null != e && "function" != typeof e) throw new TypeError(zc);
+    var n = function() {
+      var i = arguments, r = e ? e.apply(this, i) : i[0], a = n.cache;
+      if (a.has(r)) return a.get(r);
+      var s = t.apply(this, i);
+      return n.cache = a.set(r, s) || a, s;
+    };
+    return n.cache = new (Uc.Cache || jc)(), n;
+  }
+  Uc.Cache = jc;
+  var Wc = "comm", Hc = "rule", qc = "decl", Vc = "@import", Gc = "@keyframes", Xc = Math.abs, Zc = String.fromCharCode;
+  function Qc(t) {
+    return t.trim();
+  }
+  function Kc(t, e, n) {
+    return t.replace(e, n);
+  }
+  function Jc(t, e) {
+    return t.indexOf(e);
+  }
+  function th(t, e) {
+    return 0 | t.charCodeAt(e);
+  }
+  function eh(t, e, n) {
+    return t.slice(e, n);
+  }
+  function nh(t) {
+    return t.length;
+  }
+  function ih(t) {
+    return t.length;
+  }
+  function rh(t, e) {
+    return e.push(t), t;
+  }
+  var ah = 1, sh = 1, oh = 0, lh = 0, ch = 0, hh = "";
+  function uh(t, e, n, i, r, a, s) {
+    return {
+      value: t,
+      root: e,
+      parent: n,
+      type: i,
+      props: r,
+      children: a,
+      line: ah,
+      column: sh,
+      length: s,
+      return: "",
+    };
+  }
+  function dh() {
+    return ch = lh > 0 ? th(hh, --lh) : 0, sh--, 10 === ch && (sh = 1, ah--), ch;
+  }
+  function ph() {
+    return ch = lh < oh ? th(hh, lh++) : 0, sh++, 10 === ch && (sh = 1, ah++), ch;
+  }
+  function fh() {
+    return th(hh, lh);
+  }
+  function gh() {
+    return lh;
+  }
+  function yh(t, e) {
+    return eh(hh, t, e);
+  }
+  function mh(t) {
+    switch (t) {
+      case 0:
+      case 9:
+      case 10:
+      case 13:
+      case 32:
+        return 5;
+      case 33:
+      case 43:
+      case 44:
+      case 47:
+      case 62:
+      case 64:
+      case 126:
+      case 59:
+      case 123:
+      case 125:
+        return 4;
+      case 58:
+        return 3;
+      case 34:
+      case 39:
+      case 40:
+      case 91:
+        return 2;
+      case 41:
+      case 93:
+        return 1;
+    }
+    return 0;
+  }
+  function bh(t) {
+    return Qc(yh(lh - 1, vh(91 === t ? t + 2 : 40 === t ? t + 1 : t)));
+  }
+  function _h(t) {
+    for (; (ch = fh()) && ch < 33;) ph();
+    return mh(t) > 2 || mh(ch) > 3 ? "" : " ";
+  }
+  function xh(t, e) {
+    for (; --e && ph() && !(ch < 48 || ch > 102 || ch > 57 && ch < 65 || ch > 70 && ch < 97););
+    return yh(t, gh() + (e < 6 && 32 == fh() && 32 == ph()));
+  }
+  function vh(t) {
+    for (; ph();) {
+      switch (ch) {
+        case t:
+          return lh;
+        case 34:
+        case 39:
+          34 !== t && 39 !== t && vh(ch);
+          break;
+        case 40:
+          41 === t && vh(t);
+          break;
+        case 92:
+          ph();
+      }
+    }
+    return lh;
+  }
+  function kh(t, e) {
+    for (; ph() && t + ch !== 57 && (t + ch !== 84 || 47 !== fh()););
+    return "/*" + yh(e, lh - 1) + "*" + Zc(47 === t ? t : ph());
+  }
+  function wh(t) {
+    for (; !mh(fh());) ph();
+    return yh(t, lh);
+  }
+  function Th(t) {
+    return function(t) {
+      return hh = "", t;
+    }(Ch(
+      "",
+      null,
+      null,
+      null,
+      [""],
+      t = function(t) {
+        return ah = sh = 1, oh = nh(hh = t), lh = 0, [];
+      }(t),
+      0,
+      [0],
+      t,
+    ));
+  }
+  function Ch(t, e, n, i, r, a, s, o, l) {
+    for (
+      var c = 0, h = 0, u = s, d = 0, p = 0, f = 0, g = 1, y = 1, m = 1, b = 0, _ = "", x = r, v = a, k = i, w = _;
+      y;
+    ) {
+      switch (f = b, b = ph()) {
+        case 40:
+          if (108 != f && 58 == th(w, u - 1)) {
+            -1 != Jc(w += Kc(bh(b), "&", "&\f"), "&\f") && (m = -1);
+            break;
+          }
+        case 34:
+        case 39:
+        case 91:
+          w += bh(b);
+          break;
+        case 9:
+        case 10:
+        case 13:
+        case 32:
+          w += _h(f);
+          break;
+        case 92:
+          w += xh(gh() - 1, 7);
+          continue;
+        case 47:
+          switch (fh()) {
+            case 42:
+            case 47:
+              rh(Sh(kh(ph(), gh()), e, n), l);
+              break;
+            default:
+              w += "/";
+          }
+          break;
+        case 123 * g:
+          o[c++] = nh(w) * m;
+        case 125 * g:
+        case 59:
+        case 0:
+          switch (b) {
+            case 0:
+            case 125:
+              y = 0;
+            case 59 + h:
+              p > 0 && nh(w) - u && rh(p > 32 ? Ah(w + ";", i, n, u - 1) : Ah(Kc(w, " ", "") + ";", i, n, u - 2), l);
+              break;
+            case 59:
+              w += ";";
+            default:
+              if (rh(k = Eh(w, e, n, c, h, r, o, _, x = [], v = [], u), a), 123 === b) {
+                if (0 === h) Ch(w, e, k, k, x, a, u, o, v);
+                else {switch (99 === d && 110 === th(w, 3) ? 100 : d) {
+                    case 100:
+                    case 109:
+                    case 115:
+                      Ch(t, k, k, i && rh(Eh(t, k, k, 0, 0, r, o, _, r, x = [], u), v), r, v, u, o, i ? x : v);
+                      break;
+                    default:
+                      Ch(w, k, k, k, [""], v, 0, o, v);
+                  }}
+              }
+          }
+          c = h = p = 0, g = m = 1, _ = w = "", u = s;
+          break;
+        case 58:
+          u = 1 + nh(w), p = f;
+        default:
+          if (g < 1) {
+            if (123 == b) --g;
+            else if (125 == b && 0 == g++ && 125 == dh()) continue;
+          }
+          switch (w += Zc(b), b * g) {
+            case 38:
+              m = h > 0 ? 1 : (w += "\f", -1);
+              break;
+            case 44:
+              o[c++] = (nh(w) - 1) * m, m = 1;
+              break;
+            case 64:
+              45 === fh() && (w += bh(ph())), d = fh(), h = u = nh(_ = w += wh(gh())), b++;
+              break;
+            case 45:
+              45 === f && 2 == nh(w) && (g = 0);
+          }
+      }
+    }
+    return a;
+  }
+  function Eh(t, e, n, i, r, a, s, o, l, c, h) {
+    for (var u = r - 1, d = 0 === r ? a : [""], p = ih(d), f = 0, g = 0, y = 0; f < i; ++f) {
+      for (var m = 0, b = eh(t, u + 1, u = Xc(g = s[f])), _ = t; m < p; ++m) {
+        (_ = Qc(g > 0 ? d[m] + " " + b : Kc(b, /&\f/g, d[m]))) && (l[y++] = _);
+      }
+    }
+    return uh(t, e, n, 0 === r ? Hc : o, l, c, h);
+  }
+  function Sh(t, e, n) {
+    return uh(t, e, n, Wc, Zc(ch), eh(t, 2, -2), 0);
+  }
+  function Ah(t, e, n, i) {
+    return uh(t, e, n, qc, eh(t, 0, i), eh(t, i + 1, -1), i);
+  }
+  function Dh(t, e) {
+    for (var n = "", i = ih(t), r = 0; r < i; r++) n += e(t[r], r, t, e) || "";
+    return n;
+  }
+  function Lh(t, e, n, i) {
+    switch (t.type) {
+      case Vc:
+      case qc:
+        return t.return = t.return || t.value;
+      case Wc:
+        return "";
+      case Gc:
+        return t.return = t.value + "{" + Dh(t.children, i) + "}";
+      case Hc:
+        t.value = t.props.join(",");
+    }
+    return nh(n = Dh(t.children, i)) ? t.return = t.value + "{" + n + "}" : "";
+  }
+  function Oh(t) {
+    return null != t && "object" == typeof t;
+  }
+  var Nh = "[object Symbol]";
+  function Mh(t) {
+    return "symbol" == typeof t || Oh(t) && cc(t) == Nh;
+  }
+  function Bh(t, e) {
+    for (var n = -1, i = null == t ? 0 : t.length, r = Array(i); ++n < i;) r[n] = e(t[n], n, t);
+    return r;
+  }
+  var Ih = Array.isArray, Fh = 1 / 0, Rh = tc ? tc.prototype : void 0, $h = Rh ? Rh.toString : void 0;
+  function Ph(t) {
+    if ("string" == typeof t) return t;
+    if (Ih(t)) return Bh(t, Ph) + "";
+    if (Mh(t)) return $h ? $h.call(t) : "";
+    var e = t + "";
+    return "0" == e && 1 / t == -Fh ? "-0" : e;
+  }
+  var Yh = /\s/;
+  var jh = /^\s+/;
+  function zh(t) {
+    return t
+      ? t.slice(
+        0,
+        function(t) {
+          for (var e = t.length; e-- && Yh.test(t.charAt(e)););
+          return e;
+        }(t) + 1,
+      ).replace(jh, "")
+      : t;
+  }
+  var Uh = NaN, Wh = /^[-+]0x[0-9a-f]+$/i, Hh = /^0b[01]+$/i, qh = /^0o[0-7]+$/i, Vh = parseInt;
+  var Gh = 1 / 0, Xh = 17976931348623157e292;
+  function Zh(t) {
+    return t
+      ? (t = function(t) {
+        if ("number" == typeof t) return t;
+        if (Mh(t)) return Uh;
+        if (hc(t)) {
+          var e = "function" == typeof t.valueOf ? t.valueOf() : t;
+          t = hc(e) ? e + "" : e;
+        }
+        if ("string" != typeof t) return 0 === t ? t : +t;
+        t = zh(t);
+        var n = Hh.test(t);
+        return n || qh.test(t) ? Vh(t.slice(2), n ? 2 : 8) : Wh.test(t) ? Uh : +t;
+      }(t),
+        t === Gh || t === -Gh ? (t < 0 ? -1 : 1) * Xh : t == t ? t : 0)
+      : 0 === t
+      ? t
+      : 0;
+  }
+  function Qh(t) {
+    return t;
+  }
+  var Kh = Ac(Jl, "WeakMap"),
+    Jh = Object.create,
+    tu = function() {
+      function t() {}
+      return function(e) {
+        if (!hc(e)) return {};
+        if (Jh) return Jh(e);
+        t.prototype = e;
+        var n = new t();
+        return t.prototype = void 0, n;
+      };
+    }(),
+    eu = tu;
+  function nu(t, e) {
+    var n = -1, i = t.length;
+    for (e || (e = Array(i)); ++n < i;) e[n] = t[n];
+    return e;
+  }
+  var iu = 800, ru = 16, au = Date.now;
+  function su(t) {
+    return function() {
+      return t;
+    };
+  }
+  var ou = function() {
+      try {
+        var t = Ac(Object, "defineProperty");
+        return t({}, "", {}), t;
+      } catch (t) {}
+    }(),
+    lu = ou,
+    cu = lu
+      ? function(t, e) {
+        return lu(t, "toString", { configurable: !0, enumerable: !1, value: su(e), writable: !0 });
+      }
+      : Qh,
+    hu = function(t) {
+      var e = 0, n = 0;
+      return function() {
+        var i = au(), r = ru - (i - n);
+        if (n = i, r > 0) {
+          if (++e >= iu) return arguments[0];
+          else e = 0;
+        }
+        return t.apply(void 0, arguments);
+      };
+    }(cu),
+    uu = hu;
+  function du(t, e) {
+    for (var n = -1, i = null == t ? 0 : t.length; ++n < i && !1 !== e(t[n], n, t););
+    return t;
+  }
+  function pu(t, e, n, i) {
+    for (var r = t.length, a = n + (i ? 1 : -1); i ? a-- : ++a < r;) if (e(t[a], a, t)) return a;
+    return -1;
+  }
+  function fu(t) {
+    return t != t;
+  }
+  function gu(t, e) {
+    return !!(null == t ? 0 : t.length) && function(t, e, n) {
+          return e == e
+            ? function(t, e, n) {
+              for (var i = n - 1, r = t.length; ++i < r;) if (t[i] === e) return i;
+              return -1;
+            }(t, e, n)
+            : pu(t, fu, n);
+        }(t, e, 0) > -1;
+  }
+  var yu = 9007199254740991, mu = /^(?:0|[1-9]\d*)$/;
+  function bu(t, e) {
+    var n = typeof t;
+    return !!(e = null == e ? yu : e) && ("number" == n || "symbol" != n && mu.test(t)) && t > -1 && t % 1 == 0
+      && t < e;
+  }
+  function _u(t, e, n) {
+    "__proto__" == e && lu ? lu(t, e, { configurable: !0, enumerable: !0, value: n, writable: !0 }) : t[e] = n;
+  }
+  var xu = Object.prototype.hasOwnProperty;
+  function vu(t, e, n) {
+    var i = t[e];
+    xu.call(t, e) && Ic(i, n) && (void 0 !== n || e in t) || _u(t, e, n);
+  }
+  function ku(t, e, n, i) {
+    var r = !n;
+    n || (n = {});
+    for (var a = -1, s = e.length; ++a < s;) {
+      var o = e[a], l = i ? i(n[o], t[o], o, n, t) : void 0;
+      void 0 === l && (l = t[o]), r ? _u(n, o, l) : vu(n, o, l);
+    }
+    return n;
+  }
+  var wu = Math.max;
+  function Tu(t, e, n) {
+    return e = wu(void 0 === e ? t.length - 1 : e, 0), function() {
+      for (var i = arguments, r = -1, a = wu(i.length - e, 0), s = Array(a); ++r < a;) s[r] = i[e + r];
+      r = -1;
+      for (var o = Array(e + 1); ++r < e;) o[r] = i[r];
+      return o[e] = n(s),
+        function(t, e, n) {
+          switch (n.length) {
+            case 0:
+              return t.call(e);
+            case 1:
+              return t.call(e, n[0]);
+            case 2:
+              return t.call(e, n[0], n[1]);
+            case 3:
+              return t.call(e, n[0], n[1], n[2]);
+          }
+          return t.apply(e, n);
+        }(t, this, o);
+    };
+  }
+  function Cu(t, e) {
+    return uu(Tu(t, e, Qh), t + "");
+  }
+  var Eu = 9007199254740991;
+  function Su(t) {
+    return "number" == typeof t && t > -1 && t % 1 == 0 && t <= Eu;
+  }
+  function Au(t) {
+    return null != t && Su(t.length) && !gc(t);
+  }
+  function Du(t, e, n) {
+    if (!hc(n)) return !1;
+    var i = typeof e;
+    return !!("number" == i ? Au(n) && bu(e, n.length) : "string" == i && e in n) && Ic(n[e], t);
+  }
+  var Lu = Object.prototype;
+  function Ou(t) {
+    var e = t && t.constructor;
+    return t === ("function" == typeof e && e.prototype || Lu);
+  }
+  var Nu = "[object Arguments]";
+  function Mu(t) {
+    return Oh(t) && cc(t) == Nu;
+  }
+  var Bu = Object.prototype,
+    Iu = Bu.hasOwnProperty,
+    Fu = Bu.propertyIsEnumerable,
+    Ru = Mu(function() {
+        return arguments;
+      }())
+      ? Mu
+      : function(t) {
+        return Oh(t) && Iu.call(t, "callee") && !Fu.call(t, "callee");
+      },
+    $u = Ru;
+  var Pu = "object" == typeof exports && exports && !exports.nodeType && exports,
+    Yu = Pu && "object" == typeof module && module && !module.nodeType && module,
+    ju = Yu && Yu.exports === Pu ? Jl.Buffer : void 0,
+    zu = (ju ? ju.isBuffer : void 0) || function() {
+      return !1;
+    },
+    Uu = {};
+  function Wu(t) {
+    return function(e) {
+      return t(e);
+    };
+  }
+  Uu["[object Float32Array]"] =
+    Uu["[object Float64Array]"] =
+    Uu["[object Int8Array]"] =
+    Uu["[object Int16Array]"] =
+    Uu["[object Int32Array]"] =
+    Uu["[object Uint8Array]"] =
+    Uu["[object Uint8ClampedArray]"] =
+    Uu["[object Uint16Array]"] =
+    Uu["[object Uint32Array]"] =
+      !0,
+    Uu["[object Arguments]"] =
+      Uu["[object Array]"] =
+      Uu["[object ArrayBuffer]"] =
+      Uu["[object Boolean]"] =
+      Uu["[object DataView]"] =
+      Uu["[object Date]"] =
+      Uu["[object Error]"] =
+      Uu["[object Function]"] =
+      Uu["[object Map]"] =
+      Uu["[object Number]"] =
+      Uu["[object Object]"] =
+      Uu["[object RegExp]"] =
+      Uu["[object Set]"] =
+      Uu["[object String]"] =
+      Uu["[object WeakMap]"] =
+        !1;
+  var Hu = "object" == typeof exports && exports && !exports.nodeType && exports,
+    qu = Hu && "object" == typeof module && module && !module.nodeType && module,
+    Vu = qu && qu.exports === Hu && Ql.process,
+    Gu = function() {
+      try {
+        var t = qu && qu.require && qu.require("util").types;
+        return t || Vu && Vu.binding && Vu.binding("util");
+      } catch (t) {}
+    }(),
+    Xu = Gu,
+    Zu = Xu && Xu.isTypedArray,
+    Qu = Zu ? Wu(Zu) : function(t) {
+      return Oh(t) && Su(t.length) && !!Uu[cc(t)];
+    },
+    Ku = Object.prototype.hasOwnProperty;
+  function Ju(t, e) {
+    var n = Ih(t),
+      i = !n && $u(t),
+      r = !n && !i && zu(t),
+      a = !n && !i && !r && Qu(t),
+      s = n || i || r || a,
+      o = s
+        ? function(t, e) {
+          for (var n = -1, i = Array(t); ++n < t;) i[n] = e(n);
+          return i;
+        }(t.length, String)
+        : [],
+      l = o.length;
+    for (var c in t) {
+      !e && !Ku.call(t, c)
+        || s
+          && ("length" == c || r && ("offset" == c || "parent" == c)
+            || a && ("buffer" == c || "byteLength" == c || "byteOffset" == c) || bu(c, l))
+        || o.push(c);
+    }
+    return o;
+  }
+  function td(t, e) {
+    return function(n) {
+      return t(e(n));
+    };
+  }
+  var ed = td(Object.keys, Object), nd = Object.prototype.hasOwnProperty;
+  function id(t) {
+    if (!Ou(t)) return ed(t);
+    var e = [];
+    for (var n in Object(t)) nd.call(t, n) && "constructor" != n && e.push(n);
+    return e;
+  }
+  function rd(t) {
+    return Au(t) ? Ju(t) : id(t);
+  }
+  var ad = Object.prototype.hasOwnProperty;
+  function sd(t) {
+    if (!hc(t)) {
+      return function(t) {
+        var e = [];
+        if (null != t) for (var n in Object(t)) e.push(n);
+        return e;
+      }(t);
+    }
+    var e = Ou(t), n = [];
+    for (var i in t) ("constructor" != i || !e && ad.call(t, i)) && n.push(i);
+    return n;
+  }
+  function od(t) {
+    return Au(t) ? Ju(t, !0) : sd(t);
+  }
+  var ld = /\.|\[(?:[^[\]]*|(["'])(?:(?!\1)[^\\]|\\.)*?\1)\]/, cd = /^\w*$/;
+  function hd(t, e) {
+    if (Ih(t)) return !1;
+    var n = typeof t;
+    return !("number" != n && "symbol" != n && "boolean" != n && null != t && !Mh(t))
+      || (cd.test(t) || !ld.test(t) || null != e && t in Object(e));
+  }
+  var ud = 500;
+  var dd = /[^.[\]]+|\[(?:(-?\d+(?:\.\d+)?)|(["'])((?:(?!\2)[^\\]|\\.)*?)\2)\]|(?=(?:\.|\[\])(?:\.|\[\]|$))/g,
+    pd = /\\(\\)?/g,
+    fd = function(t) {
+      var e = Uc(t, function(t) {
+          return n.size === ud && n.clear(), t;
+        }),
+        n = e.cache;
+      return e;
+    }(function(t) {
+      var e = [];
+      return 46 === t.charCodeAt(0) && e.push(""),
+        t.replace(dd, function(t, n, i, r) {
+          e.push(i ? r.replace(pd, "$1") : n || t);
+        }),
+        e;
+    }),
+    gd = fd;
+  function yd(t) {
+    return null == t ? "" : Ph(t);
+  }
+  function md(t, e) {
+    return Ih(t) ? t : hd(t, e) ? [t] : gd(yd(t));
+  }
+  var bd = 1 / 0;
+  function _d(t) {
+    if ("string" == typeof t || Mh(t)) return t;
+    var e = t + "";
+    return "0" == e && 1 / t == -bd ? "-0" : e;
+  }
+  function xd(t, e) {
+    for (var n = 0, i = (e = md(e, t)).length; null != t && n < i;) t = t[_d(e[n++])];
+    return n && n == i ? t : void 0;
+  }
+  function vd(t, e) {
+    for (var n = -1, i = e.length, r = t.length; ++n < i;) t[r + n] = e[n];
+    return t;
+  }
+  var kd = tc ? tc.isConcatSpreadable : void 0;
+  function wd(t) {
+    return Ih(t) || $u(t) || !!(kd && t && t[kd]);
+  }
+  function Td(t, e, n, i, r) {
+    var a = -1, s = t.length;
+    for (n || (n = wd), r || (r = []); ++a < s;) {
+      var o = t[a];
+      e > 0 && n(o) ? e > 1 ? Td(o, e - 1, n, i, r) : vd(r, o) : i || (r[r.length] = o);
+    }
+    return r;
+  }
+  function Cd(t) {
+    return (null == t ? 0 : t.length) ? Td(t, 1) : [];
+  }
+  var Ed = td(Object.getPrototypeOf, Object),
+    Sd = "[object Object]",
+    Ad = Function.prototype,
+    Dd = Object.prototype,
+    Ld = Ad.toString,
+    Od = Dd.hasOwnProperty,
+    Nd = Ld.call(Object);
+  function Md(t) {
+    if (!Oh(t) || cc(t) != Sd) return !1;
+    var e = Ed(t);
+    if (null === e) return !0;
+    var n = Od.call(e, "constructor") && e.constructor;
+    return "function" == typeof n && n instanceof n && Ld.call(n) == Nd;
+  }
+  function Bd(t, e, n, i) {
+    var r = -1, a = null == t ? 0 : t.length;
+    for (i && a && (n = t[++r]); ++r < a;) n = e(n, t[r], r, t);
+    return n;
+  }
+  var Id = 200;
+  function Fd(t) {
+    var e = this.__data__ = new $c(t);
+    this.size = e.size;
+  }
+  Fd.prototype.clear = function() {
+    this.__data__ = new $c(), this.size = 0;
+  },
+    Fd.prototype.delete = function(t) {
+      var e = this.__data__, n = e.delete(t);
+      return this.size = e.size, n;
+    },
+    Fd.prototype.get = function(t) {
+      return this.__data__.get(t);
+    },
+    Fd.prototype.has = function(t) {
+      return this.__data__.has(t);
+    },
+    Fd.prototype.set = function(t, e) {
+      var n = this.__data__;
+      if (n instanceof $c) {
+        var i = n.__data__;
+        if (!Pc || i.length < Id - 1) return i.push([t, e]), this.size = ++n.size, this;
+        n = this.__data__ = new jc(i);
+      }
+      return n.set(t, e), this.size = n.size, this;
+    };
+  var Rd = "object" == typeof exports && exports && !exports.nodeType && exports,
+    $d = Rd && "object" == typeof module && module && !module.nodeType && module,
+    Pd = $d && $d.exports === Rd ? Jl.Buffer : void 0,
+    Yd = Pd ? Pd.allocUnsafe : void 0;
+  function jd(t, e) {
+    if (e) return t.slice();
+    var n = t.length, i = Yd ? Yd(n) : new t.constructor(n);
+    return t.copy(i), i;
+  }
+  function zd(t, e) {
+    for (var n = -1, i = null == t ? 0 : t.length, r = 0, a = []; ++n < i;) {
+      var s = t[n];
+      e(s, n, t) && (a[r++] = s);
+    }
+    return a;
+  }
+  function Ud() {
+    return [];
+  }
+  var Wd = Object.prototype.propertyIsEnumerable,
+    Hd = Object.getOwnPropertySymbols,
+    qd = Hd
+      ? function(t) {
+        return null == t ? [] : (t = Object(t),
+          zd(Hd(t), function(e) {
+            return Wd.call(t, e);
+          }));
+      }
+      : Ud,
+    Vd = qd;
+  var Gd = Object.getOwnPropertySymbols
+      ? function(t) {
+        for (var e = []; t;) vd(e, Vd(t)), t = Ed(t);
+        return e;
+      }
+      : Ud,
+    Xd = Gd;
+  function Zd(t, e, n) {
+    var i = e(t);
+    return Ih(t) ? i : vd(i, n(t));
+  }
+  function Qd(t) {
+    return Zd(t, rd, Vd);
+  }
+  function Kd(t) {
+    return Zd(t, od, Xd);
+  }
+  var Jd = Ac(Jl, "DataView"),
+    tp = Ac(Jl, "Promise"),
+    ep = Ac(Jl, "Set"),
+    np = "[object Map]",
+    ip = "[object Promise]",
+    rp = "[object Set]",
+    ap = "[object WeakMap]",
+    sp = "[object DataView]",
+    op = xc(Jd),
+    lp = xc(Pc),
+    cp = xc(tp),
+    hp = xc(ep),
+    up = xc(Kh),
+    dp = cc;
+  (Jd && dp(new Jd(new ArrayBuffer(1))) != sp || Pc && dp(new Pc()) != np || tp && dp(tp.resolve()) != ip
+    || ep && dp(new ep()) != rp || Kh && dp(new Kh()) != ap) && (dp = function(t) {
+      var e = cc(t), n = "[object Object]" == e ? t.constructor : void 0, i = n ? xc(n) : "";
+      if (i) {
+        switch (i) {
+          case op:
+            return sp;
+          case lp:
+            return np;
+          case cp:
+            return ip;
+          case hp:
+            return rp;
+          case up:
+            return ap;
+        }
+      }
+      return e;
+    });
+  var pp = dp, fp = Object.prototype.hasOwnProperty;
+  var gp = Jl.Uint8Array;
+  function yp(t) {
+    var e = new t.constructor(t.byteLength);
+    return new gp(e).set(new gp(t)), e;
+  }
+  var mp = /\w*$/;
+  var bp = tc ? tc.prototype : void 0, _p = bp ? bp.valueOf : void 0;
+  function xp(t, e) {
+    var n = e ? yp(t.buffer) : t.buffer;
+    return new t.constructor(n, t.byteOffset, t.length);
+  }
+  var vp = "[object Boolean]",
+    kp = "[object Date]",
+    wp = "[object Map]",
+    Tp = "[object Number]",
+    Cp = "[object RegExp]",
+    Ep = "[object Set]",
+    Sp = "[object String]",
+    Ap = "[object Symbol]",
+    Dp = "[object ArrayBuffer]",
+    Lp = "[object DataView]",
+    Op = "[object Float32Array]",
+    Np = "[object Float64Array]",
+    Mp = "[object Int8Array]",
+    Bp = "[object Int16Array]",
+    Ip = "[object Int32Array]",
+    Fp = "[object Uint8Array]",
+    Rp = "[object Uint8ClampedArray]",
+    $p = "[object Uint16Array]",
+    Pp = "[object Uint32Array]";
+  function Yp(t, e, n) {
+    var i, r, a, s = t.constructor;
+    switch (e) {
+      case Dp:
+        return yp(t);
+      case vp:
+      case kp:
+        return new s(+t);
+      case Lp:
+        return function(t, e) {
+          var n = e ? yp(t.buffer) : t.buffer;
+          return new t.constructor(n, t.byteOffset, t.byteLength);
+        }(t, n);
+      case Op:
+      case Np:
+      case Mp:
+      case Bp:
+      case Ip:
+      case Fp:
+      case Rp:
+      case $p:
+      case Pp:
+        return xp(t, n);
+      case wp:
+        return new s();
+      case Tp:
+      case Sp:
+        return new s(t);
+      case Cp:
+        return (a = new (r = t).constructor(r.source, mp.exec(r))).lastIndex = r.lastIndex, a;
+      case Ep:
+        return new s();
+      case Ap:
+        return i = t, _p ? Object(_p.call(i)) : {};
+    }
+  }
+  function jp(t) {
+    return "function" != typeof t.constructor || Ou(t) ? {} : eu(Ed(t));
+  }
+  var zp = "[object Map]";
+  var Up = Xu && Xu.isMap,
+    Wp = Up ? Wu(Up) : function(t) {
+      return Oh(t) && pp(t) == zp;
+    },
+    Hp = "[object Set]";
+  var qp = Xu && Xu.isSet,
+    Vp = qp ? Wu(qp) : function(t) {
+      return Oh(t) && pp(t) == Hp;
+    },
+    Gp = 1,
+    Xp = 2,
+    Zp = 4,
+    Qp = "[object Arguments]",
+    Kp = "[object Function]",
+    Jp = "[object GeneratorFunction]",
+    tf = "[object Object]",
+    ef = {};
+  function nf(t, e, n, i, r, a) {
+    var s, o = e & Gp, l = e & Xp, c = e & Zp;
+    if (n && (s = r ? n(t, i, r, a) : n(t)), void 0 !== s) return s;
+    if (!hc(t)) return t;
+    var h = Ih(t);
+    if (h) {
+      if (
+        s = function(t) {
+          var e = t.length, n = new t.constructor(e);
+          return e && "string" == typeof t[0] && fp.call(t, "index") && (n.index = t.index, n.input = t.input), n;
+        }(t), !o
+      ) return nu(t, s);
+    } else {
+      var u = pp(t), d = u == Kp || u == Jp;
+      if (zu(t)) return jd(t, o);
+      if (u == tf || u == Qp || d && !r) {
+        if (s = l || d ? {} : jp(t), !o) {
+          return l
+            ? function(t, e) {
+              return ku(t, Xd(t), e);
+            }(
+              t,
+              function(t, e) {
+                return t && ku(e, od(e), t);
+              }(s, t),
+            )
+            : function(t, e) {
+              return ku(t, Vd(t), e);
+            }(
+              t,
+              function(t, e) {
+                return t && ku(e, rd(e), t);
+              }(s, t),
+            );
+        }
+      } else {
+        if (!ef[u]) return r ? t : {};
+        s = Yp(t, u, o);
+      }
+    }
+    a || (a = new Fd());
+    var p = a.get(t);
+    if (p) return p;
+    a.set(t, s),
+      Vp(t)
+        ? t.forEach(function(i) {
+          s.add(nf(i, e, n, i, t, a));
+        })
+        : Wp(t) && t.forEach(function(i, r) {
+          s.set(r, nf(i, e, n, r, t, a));
+        });
+    var f = h ? void 0 : (c ? l ? Kd : Qd : l ? od : rd)(t);
+    return du(f || t, function(i, r) {
+      f && (i = t[r = i]), vu(s, r, nf(i, e, n, r, t, a));
+    }),
+      s;
+  }
+  ef[Qp] =
+    ef["[object Array]"] =
+    ef["[object ArrayBuffer]"] =
+    ef["[object DataView]"] =
+    ef["[object Boolean]"] =
+    ef["[object Date]"] =
+    ef["[object Float32Array]"] =
+    ef["[object Float64Array]"] =
+    ef["[object Int8Array]"] =
+    ef["[object Int16Array]"] =
+    ef["[object Int32Array]"] =
+    ef["[object Map]"] =
+    ef["[object Number]"] =
+    ef[tf] =
+    ef["[object RegExp]"] =
+    ef["[object Set]"] =
+    ef["[object String]"] =
+    ef["[object Symbol]"] =
+    ef["[object Uint8Array]"] =
+    ef["[object Uint8ClampedArray]"] =
+    ef["[object Uint16Array]"] =
+    ef["[object Uint32Array]"] =
+      !0, ef["[object Error]"] = ef[Kp] = ef["[object WeakMap]"] = !1;
+  var rf = 4;
+  var af = 1, sf = 4;
+  var of = "__lodash_hash_undefined__";
+  function lf(t) {
+    var e = -1, n = null == t ? 0 : t.length;
+    for (this.__data__ = new jc(); ++e < n;) this.add(t[e]);
+  }
+  function cf(t, e) {
+    for (var n = -1, i = null == t ? 0 : t.length; ++n < i;) if (e(t[n], n, t)) return !0;
+    return !1;
+  }
+  function hf(t, e) {
+    return t.has(e);
+  }
+  lf.prototype.add = lf.prototype.push = function(t) {
+    return this.__data__.set(t, of), this;
+  },
+    lf.prototype.has = function(t) {
+      return this.__data__.has(t);
+    };
+  var uf = 1, df = 2;
+  function pf(t, e, n, i, r, a) {
+    var s = n & uf, o = t.length, l = e.length;
+    if (o != l && !(s && l > o)) return !1;
+    var c = a.get(t), h = a.get(e);
+    if (c && h) return c == e && h == t;
+    var u = -1, d = !0, p = n & df ? new lf() : void 0;
+    for (a.set(t, e), a.set(e, t); ++u < o;) {
+      var f = t[u], g = e[u];
+      if (i) var y = s ? i(g, f, u, e, t, a) : i(f, g, u, t, e, a);
+      if (void 0 !== y) {
+        if (y) continue;
+        d = !1;
+        break;
+      }
+      if (p) {
+        if (
+          !cf(e, function(t, e) {
+            if (!hf(p, e) && (f === t || r(f, t, n, i, a))) return p.push(e);
+          })
+        ) {
+          d = !1;
+          break;
+        }
+      } else if (f !== g && !r(f, g, n, i, a)) {
+        d = !1;
+        break;
+      }
+    }
+    return a.delete(t), a.delete(e), d;
+  }
+  function ff(t) {
+    var e = -1, n = Array(t.size);
+    return t.forEach(function(t, i) {
+      n[++e] = [i, t];
+    }),
+      n;
+  }
+  function gf(t) {
+    var e = -1, n = Array(t.size);
+    return t.forEach(function(t) {
+      n[++e] = t;
+    }),
+      n;
+  }
+  var yf = 1,
+    mf = 2,
+    bf = "[object Boolean]",
+    _f = "[object Date]",
+    xf = "[object Error]",
+    vf = "[object Map]",
+    kf = "[object Number]",
+    wf = "[object RegExp]",
+    Tf = "[object Set]",
+    Cf = "[object String]",
+    Ef = "[object Symbol]",
+    Sf = "[object ArrayBuffer]",
+    Af = "[object DataView]",
+    Df = tc ? tc.prototype : void 0,
+    Lf = Df ? Df.valueOf : void 0;
+  var Of = 1, Nf = Object.prototype.hasOwnProperty;
+  var Mf = 1,
+    Bf = "[object Arguments]",
+    If = "[object Array]",
+    Ff = "[object Object]",
+    Rf = Object.prototype.hasOwnProperty;
+  function $f(t, e, n, i, r, a) {
+    var s = Ih(t),
+      o = Ih(e),
+      l = s ? If : pp(t),
+      c = o ? If : pp(e),
+      h = (l = l == Bf ? Ff : l) == Ff,
+      u = (c = c == Bf ? Ff : c) == Ff,
+      d = l == c;
+    if (d && zu(t)) {
+      if (!zu(e)) return !1;
+      s = !0, h = !1;
+    }
+    if (d && !h) {
+      return a || (a = new Fd()),
+        s || Qu(t) ? pf(t, e, n, i, r, a) : function(t, e, n, i, r, a, s) {
+          switch (n) {
+            case Af:
+              if (t.byteLength != e.byteLength || t.byteOffset != e.byteOffset) return !1;
+              t = t.buffer, e = e.buffer;
+            case Sf:
+              return !(t.byteLength != e.byteLength || !a(new gp(t), new gp(e)));
+            case bf:
+            case _f:
+            case kf:
+              return Ic(+t, +e);
+            case xf:
+              return t.name == e.name && t.message == e.message;
+            case wf:
+            case Cf:
+              return t == e + "";
+            case vf:
+              var o = ff;
+            case Tf:
+              var l = i & yf;
+              if (o || (o = gf), t.size != e.size && !l) return !1;
+              var c = s.get(t);
+              if (c) return c == e;
+              i |= mf, s.set(t, e);
+              var h = pf(o(t), o(e), i, r, a, s);
+              return s.delete(t), h;
+            case Ef:
+              if (Lf) return Lf.call(t) == Lf.call(e);
+          }
+          return !1;
+        }(t, e, l, n, i, r, a);
+    }
+    if (!(n & Mf)) {
+      var p = h && Rf.call(t, "__wrapped__"), f = u && Rf.call(e, "__wrapped__");
+      if (p || f) {
+        var g = p ? t.value() : t, y = f ? e.value() : e;
+        return a || (a = new Fd()), r(g, y, n, i, a);
+      }
+    }
+    return !!d && (a || (a = new Fd()),
+      function(t, e, n, i, r, a) {
+        var s = n & Of, o = Qd(t), l = o.length;
+        if (l != Qd(e).length && !s) return !1;
+        for (var c = l; c--;) {
+          var h = o[c];
+          if (!(s ? h in e : Nf.call(e, h))) return !1;
+        }
+        var u = a.get(t), d = a.get(e);
+        if (u && d) return u == e && d == t;
+        var p = !0;
+        a.set(t, e), a.set(e, t);
+        for (var f = s; ++c < l;) {
+          var g = t[h = o[c]], y = e[h];
+          if (i) var m = s ? i(y, g, h, e, t, a) : i(g, y, h, t, e, a);
+          if (!(void 0 === m ? g === y || r(g, y, n, i, a) : m)) {
+            p = !1;
+            break;
+          }
+          f || (f = "constructor" == h);
+        }
+        if (p && !f) {
+          var b = t.constructor, _ = e.constructor;
+          b == _ || !("constructor" in t) || !("constructor" in e)
+            || "function" == typeof b && b instanceof b && "function" == typeof _ && _ instanceof _ || (p = !1);
+        }
+        return a.delete(t), a.delete(e), p;
+      }(t, e, n, i, r, a));
+  }
+  function Pf(t, e, n, i, r) {
+    return t === e || (null == t || null == e || !Oh(t) && !Oh(e) ? t != t && e != e : $f(t, e, n, i, Pf, r));
+  }
+  var Yf = 1, jf = 2;
+  function zf(t) {
+    return t == t && !hc(t);
+  }
+  function Uf(t, e) {
+    return function(n) {
+      return null != n && (n[t] === e && (void 0 !== e || t in Object(n)));
+    };
+  }
+  function Wf(t) {
+    var e = function(t) {
+      for (var e = rd(t), n = e.length; n--;) {
+        var i = e[n], r = t[i];
+        e[n] = [i, r, zf(r)];
+      }
+      return e;
+    }(t);
+    return 1 == e.length && e[0][2] ? Uf(e[0][0], e[0][1]) : function(n) {
+      return n === t || function(t, e, n, i) {
+        var r = n.length, a = r, s = !i;
+        if (null == t) return !a;
+        for (t = Object(t); r--;) {
+          var o = n[r];
+          if (s && o[2] ? o[1] !== t[o[0]] : !(o[0] in t)) return !1;
+        }
+        for (; ++r < a;) {
+          var l = (o = n[r])[0], c = t[l], h = o[1];
+          if (s && o[2]) {
+            if (void 0 === c && !(l in t)) return !1;
+            else {
+              var u = new Fd();
+              if (i) var d = i(c, h, l, t, e, u);
+              if (!(void 0 === d ? Pf(h, c, Yf | jf, i, u) : d)) return !1;
+            }
+          }
+        }
+        return !0;
+      }(n, t, e);
+    };
+  }
+  function Hf(t, e) {
+    return null != t && e in Object(t);
+  }
+  function qf(t, e, n) {
+    for (var i = -1, r = (e = md(e, t)).length, a = !1; ++i < r;) {
+      var s = _d(e[i]);
+      if (!(a = null != t && n(t, s))) break;
+      t = t[s];
+    }
+    return a || ++i != r ? a : !!(r = null == t ? 0 : t.length) && Su(r) && bu(s, r) && (Ih(t) || $u(t));
+  }
+  function Vf(t, e) {
+    return null != t && qf(t, e, Hf);
+  }
+  var Gf = 1, Xf = 2;
+  function Zf(t, e) {
+    return hd(t) && zf(e) ? Uf(_d(t), e) : function(n) {
+      var i = function(t, e, n) {
+        var i = null == t ? void 0 : xd(t, e);
+        return void 0 === i ? n : i;
+      }(n, t);
+      return void 0 === i && i === e ? Vf(n, t) : Pf(e, i, Gf | Xf);
+    };
+  }
+  function Qf(t) {
+    return hd(t)
+      ? (e = _d(t), function(t) {
+        return null == t ? void 0 : t[e];
+      })
+      : function(t) {
+        return function(e) {
+          return xd(e, t);
+        };
+      }(t);
+    var e;
+  }
+  function Kf(t) {
+    return "function" == typeof t ? t : null == t ? Qh : "object" == typeof t ? Ih(t) ? Zf(t[0], t[1]) : Wf(t) : Qf(t);
+  }
+  var Jf,
+    tg = function(t, e, n) {
+      for (var i = -1, r = Object(t), a = n(t), s = a.length; s--;) {
+        var o = a[Jf ? s : ++i];
+        if (!1 === e(r[o], o, r)) break;
+      }
+      return t;
+    },
+    eg = tg;
+  function ng(t, e) {
+    return t && eg(t, e, rd);
+  }
+  var ig = function(t, e) {
+      return function(n, i) {
+        if (null == n) return n;
+        if (!Au(n)) return t(n, i);
+        for (var r = n.length, a = e ? r : -1, s = Object(n); (e ? a-- : ++a < r) && !1 !== i(s[a], a, s););
+        return n;
+      };
+    }(ng),
+    rg = ig,
+    ag = function() {
+      return Jl.Date.now();
+    },
+    sg = Object.prototype,
+    og = sg.hasOwnProperty,
+    lg = Cu(function(t, e) {
+      t = Object(t);
+      var n = -1, i = e.length, r = i > 2 ? e[2] : void 0;
+      for (r && Du(e[0], e[1], r) && (i = 1); ++n < i;) {
+        for (var a = e[n], s = od(a), o = -1, l = s.length; ++o < l;) {
+          var c = s[o], h = t[c];
+          (void 0 === h || Ic(h, sg[c]) && !og.call(t, c)) && (t[c] = a[c]);
+        }
+      }
+      return t;
+    }),
+    cg = lg;
+  function hg(t, e, n) {
+    (void 0 !== n && !Ic(t[e], n) || void 0 === n && !(e in t)) && _u(t, e, n);
+  }
+  function ug(t) {
+    return Oh(t) && Au(t);
+  }
+  function dg(t, e) {
+    if (("constructor" !== e || "function" != typeof t[e]) && "__proto__" != e) return t[e];
+  }
+  function pg(t, e, n, i, r, a, s) {
+    var o = dg(t, n), l = dg(e, n), c = s.get(l);
+    if (c) hg(t, n, c);
+    else {
+      var h, u = a ? a(o, l, n + "", t, e, s) : void 0, d = void 0 === u;
+      if (d) {
+        var p = Ih(l), f = !p && zu(l), g = !p && !f && Qu(l);
+        u = l,
+          p || f || g
+            ? Ih(o) ? u = o : ug(o) ? u = nu(o) : f ? (d = !1, u = jd(l, !0)) : g ? (d = !1, u = xp(l, !0)) : u = []
+            : Md(l) || $u(l)
+            ? (u = o, $u(o) ? u = ku(h = o, od(h)) : hc(o) && !gc(o) || (u = jp(l)))
+            : d = !1;
+      }
+      d && (s.set(l, u), r(u, l, i, a, s), s.delete(l)), hg(t, n, u);
+    }
+  }
+  function fg(t, e, n, i, r) {
+    t !== e && eg(e, function(a, s) {
+      if (r || (r = new Fd()), hc(a)) pg(t, e, s, n, fg, i, r);
+      else {
+        var o = i ? i(dg(t, s), a, s + "", t, e, r) : void 0;
+        void 0 === o && (o = a), hg(t, s, o);
+      }
+    }, od);
+  }
+  function gg(t, e, n) {
+    for (var i = -1, r = null == t ? 0 : t.length; ++i < r;) if (n(e, t[i])) return !0;
+    return !1;
+  }
+  function yg(t) {
+    var e = null == t ? 0 : t.length;
+    return e ? t[e - 1] : void 0;
+  }
+  function mg(t) {
+    return "function" == typeof t ? t : Qh;
+  }
+  function bg(t, e) {
+    return (Ih(t) ? du : rg)(t, mg(e));
+  }
+  function _g(t, e) {
+    var n = [];
+    return rg(t, function(t, i, r) {
+      e(t, i, r) && n.push(t);
+    }),
+      n;
+  }
+  function xg(t, e) {
+    return (Ih(t) ? zd : _g)(t, Kf(e));
+  }
+  var vg = Math.max;
+  var kg,
+    wg = (kg = function(t, e, n) {
+      var i = null == t ? 0 : t.length;
+      if (!i) return -1;
+      var r, a, s = null == n ? 0 : (r = Zh(n), a = r % 1, r == r ? a ? r - a : r : 0);
+      return s < 0 && (s = vg(i + s, 0)), pu(t, Kf(e), s);
+    },
+      function(t, e, n) {
+        var i = Object(t);
+        if (!Au(t)) {
+          var r = Kf(e);
+          t = rd(t),
+            e = function(t) {
+              return r(i[t], t, i);
+            };
+        }
+        var a = kg(t, e, n);
+        return a > -1 ? i[r ? t[a] : a] : void 0;
+      }),
+    Tg = wg;
+  function Cg(t, e) {
+    var n = -1, i = Au(t) ? Array(t.length) : [];
+    return rg(t, function(t, r, a) {
+      i[++n] = e(t, r, a);
+    }),
+      i;
+  }
+  function Eg(t, e) {
+    return (Ih(t) ? Bh : Cg)(t, Kf(e));
+  }
+  function Sg(t, e) {
+    return t > e;
+  }
+  var Ag = Object.prototype.hasOwnProperty;
+  function Dg(t, e) {
+    return null != t && Ag.call(t, e);
+  }
+  function Lg(t, e) {
+    return null != t && qf(t, e, Dg);
+  }
+  function Og(t) {
+    return null == t ? [] : function(t, e) {
+      return Bh(e, function(e) {
+        return t[e];
+      });
+    }(t, rd(t));
+  }
+  var Ng = "[object Map]", Mg = "[object Set]", Bg = Object.prototype.hasOwnProperty;
+  function Ig(t) {
+    if (null == t) return !0;
+    if (Au(t) && (Ih(t) || "string" == typeof t || "function" == typeof t.splice || zu(t) || Qu(t) || $u(t))) {
+      return !t.length;
+    }
+    var e = pp(t);
+    if (e == Ng || e == Mg) return !t.size;
+    if (Ou(t)) return !id(t).length;
+    for (var n in t) if (Bg.call(t, n)) return !1;
+    return !0;
+  }
+  function Fg(t) {
+    return void 0 === t;
+  }
+  function Rg(t, e) {
+    return t < e;
+  }
+  function $g(t, e) {
+    var n = {};
+    return e = Kf(e),
+      ng(t, function(t, i, r) {
+        _u(n, i, e(t, i, r));
+      }),
+      n;
+  }
+  function Pg(t, e, n) {
+    for (var i = -1, r = t.length; ++i < r;) {
+      var a = t[i], s = e(a);
+      if (null != s && (void 0 === o ? s == s && !Mh(s) : n(s, o))) var o = s, l = a;
+    }
+    return l;
+  }
+  function Yg(t) {
+    return t && t.length ? Pg(t, Qh, Sg) : void 0;
+  }
+  var jg,
+    zg = (jg = function(t, e, n) {
+      fg(t, e, n);
+    },
+      Cu(function(t, e) {
+        var n = -1, i = e.length, r = i > 1 ? e[i - 1] : void 0, a = i > 2 ? e[2] : void 0;
+        for (
+          r = jg.length > 3 && "function" == typeof r ? (i--, r) : void 0,
+            a && Du(e[0], e[1], a) && (r = i < 3 ? void 0 : r, i = 1),
+            t = Object(t);
+          ++n < i;
+        ) {
+          var s = e[n];
+          s && jg(t, s, n, r);
+        }
+        return t;
+      })),
+    Ug = zg;
+  function Wg(t) {
+    return t && t.length ? Pg(t, Qh, Rg) : void 0;
+  }
+  function Hg(t, e) {
+    return t && t.length ? Pg(t, Kf(e), Rg) : void 0;
+  }
+  function qg(t, e, n, i) {
+    if (!hc(t)) return t;
+    for (var r = -1, a = (e = md(e, t)).length, s = a - 1, o = t; null != o && ++r < a;) {
+      var l = _d(e[r]), c = n;
+      if ("__proto__" === l || "constructor" === l || "prototype" === l) return t;
+      if (r != s) {
+        var h = o[l];
+        void 0 === (c = i ? i(h, l, o) : void 0) && (c = hc(h) ? h : bu(e[r + 1]) ? [] : {});
+      }
+      vu(o, l, c), o = o[l];
+    }
+    return t;
+  }
+  function Vg(t, e) {
+    if (t !== e) {
+      var n = void 0 !== t,
+        i = null === t,
+        r = t == t,
+        a = Mh(t),
+        s = void 0 !== e,
+        o = null === e,
+        l = e == e,
+        c = Mh(e);
+      if (!o && !c && !a && t > e || a && s && l && !o && !c || i && s && l || !n && l || !r) return 1;
+      if (!i && !a && !c && t < e || c && n && r && !i && !a || o && n && r || !s && r || !l) return -1;
+    }
+    return 0;
+  }
+  function Gg(t, e, n) {
+    e = e.length
+      ? Bh(e, function(t) {
+        return Ih(t)
+          ? function(e) {
+            return xd(e, 1 === t.length ? t[0] : t);
+          }
+          : t;
+      })
+      : [Qh];
+    var i = -1;
+    return e = Bh(e, Wu(Kf)),
+      function(t, e) {
+        var n = t.length;
+        for (t.sort(e); n--;) t[n] = t[n].value;
+        return t;
+      }(
+        Cg(t, function(t, n, r) {
+          return {
+            criteria: Bh(e, function(e) {
+              return e(t);
+            }),
+            index: ++i,
+            value: t,
+          };
+        }),
+        function(t, e) {
+          return function(t, e, n) {
+            for (var i = -1, r = t.criteria, a = e.criteria, s = r.length, o = n.length; ++i < s;) {
+              var l = Vg(r[i], a[i]);
+              if (l) return i >= o ? l : l * ("desc" == n[i] ? -1 : 1);
+            }
+            return t.index - e.index;
+          }(t, e, n);
+        },
+      );
+  }
+  function Xg(t, e) {
+    return function(t, e, n) {
+      for (var i = -1, r = e.length, a = {}; ++i < r;) {
+        var s = e[i], o = xd(t, s);
+        n(o, s) && qg(a, md(s, t), o);
+      }
+      return a;
+    }(t, e, function(e, n) {
+      return Vf(t, n);
+    });
+  }
+  var Zg = function(t) {
+      return uu(Tu(t, void 0, Cd), t + "");
+    }(function(t, e) {
+      return null == t ? {} : Xg(t, e);
+    }),
+    Qg = Zg,
+    Kg = Math.ceil,
+    Jg = Math.max;
+  var ty = function(t) {
+      return function(e, n, i) {
+        return i && "number" != typeof i && Du(e, n, i) && (n = i = void 0),
+          e = Zh(e),
+          void 0 === n ? (n = e, e = 0) : n = Zh(n),
+          function(t, e, n, i) {
+            for (var r = -1, a = Jg(Kg((e - t) / (n || 1)), 0), s = Array(a); a--;) s[i ? a : ++r] = t, t += n;
+            return s;
+          }(e, n, i = void 0 === i ? e < n ? 1 : -1 : Zh(i), t);
+      };
+    }(),
+    ey = ty;
+  function ny(t, e, n, i, r) {
+    return r(t, function(t, r, a) {
+      n = i ? (i = !1, t) : e(n, t, r, a);
+    }),
+      n;
+  }
+  function iy(t, e, n) {
+    var i = Ih(t) ? Bd : ny, r = arguments.length < 3;
+    return i(t, Kf(e), n, r, rg);
+  }
+  var ry = Cu(function(t, e) {
+      if (null == t) return [];
+      var n = e.length;
+      return n > 1 && Du(t, e[0], e[1]) ? e = [] : n > 2 && Du(e[0], e[1], e[2]) && (e = [e[0]]), Gg(t, Td(e, 1), []);
+    }),
+    ay = ry,
+    sy = ep && 1 / gf(new ep([, -0]))[1] == 1 / 0
+      ? function(t) {
+        return new ep(t);
+      }
+      : function() {},
+    oy = sy,
+    ly = 200;
+  var cy = Cu(function(t) {
+      return function(t, e, n) {
+        var i = -1, r = gu, a = t.length, s = !0, o = [], l = o;
+        if (n) s = !1, r = gg;
+        else if (a >= ly) {
+          var c = e ? null : oy(t);
+          if (c) return gf(c);
+          s = !1, r = hf, l = new lf();
+        } else l = e ? [] : o;
+        t: for (; ++i < a;) {
+          var h = t[i], u = e ? e(h) : h;
+          if (h = n || 0 !== h ? h : 0, s && u == u) {
+            for (var d = l.length; d--;) if (l[d] === u) continue t;
+            e && l.push(u), o.push(h);
+          } else r(l, u, n) || (l !== o && l.push(u), o.push(h));
+        }
+        return o;
+      }(Td(t, 1, ug, !0));
+    }),
+    hy = cy,
+    uy = 0;
+  function dy(t) {
+    var e = ++uy;
+    return yd(t) + e;
+  }
+  var py = "\0", fy = "\0", gy = "
";
+  class yy {
+    constructor(t = {}) {
+      this._isDirected = !Lg(t, "directed") || t.directed,
+        this._isMultigraph = !!Lg(t, "multigraph") && t.multigraph,
+        this._isCompound = !!Lg(t, "compound") && t.compound,
+        this._label = void 0,
+        this._defaultNodeLabelFn = su(void 0),
+        this._defaultEdgeLabelFn = su(void 0),
+        this._nodes = {},
+        this._isCompound && (this._parent = {}, this._children = {}, this._children[fy] = {}),
+        this._in = {},
+        this._preds = {},
+        this._out = {},
+        this._sucs = {},
+        this._edgeObjs = {},
+        this._edgeLabels = {};
+    }
+    isDirected() {
+      return this._isDirected;
+    }
+    isMultigraph() {
+      return this._isMultigraph;
+    }
+    isCompound() {
+      return this._isCompound;
+    }
+    setGraph(t) {
+      return this._label = t, this;
+    }
+    graph() {
+      return this._label;
+    }
+    setDefaultNodeLabel(t) {
+      return gc(t) || (t = su(t)), this._defaultNodeLabelFn = t, this;
+    }
+    nodeCount() {
+      return this._nodeCount;
+    }
+    nodes() {
+      return rd(this._nodes);
+    }
+    sources() {
+      var t = this;
+      return xg(this.nodes(), function(e) {
+        return Ig(t._in[e]);
+      });
+    }
+    sinks() {
+      var t = this;
+      return xg(this.nodes(), function(e) {
+        return Ig(t._out[e]);
+      });
+    }
+    setNodes(t, e) {
+      var n = arguments, i = this;
+      return bg(t, function(t) {
+        n.length > 1 ? i.setNode(t, e) : i.setNode(t);
+      }),
+        this;
+    }
+    setNode(t, e) {
+      return Lg(this._nodes, t)
+        ? (arguments.length > 1 && (this._nodes[t] = e), this)
+        : (this._nodes[t] = arguments.length > 1 ? e : this._defaultNodeLabelFn(t),
+          this._isCompound && (this._parent[t] = fy, this._children[t] = {}, this._children[fy][t] = !0),
+          this._in[t] = {},
+          this._preds[t] = {},
+          this._out[t] = {},
+          this._sucs[t] = {},
+          ++this._nodeCount,
+          this);
+    }
+    node(t) {
+      return this._nodes[t];
+    }
+    hasNode(t) {
+      return Lg(this._nodes, t);
+    }
+    removeNode(t) {
+      var e = this;
+      if (Lg(this._nodes, t)) {
+        var n = function(t) {
+          e.removeEdge(e._edgeObjs[t]);
+        };
+        delete this._nodes[t],
+          this._isCompound
+          && (this._removeFromParentsChildList(t),
+            delete this._parent[t],
+            bg(this.children(t), function(t) {
+              e.setParent(t);
+            }),
+            delete this._children[t]),
+          bg(rd(this._in[t]), n),
+          delete this._in[t],
+          delete this._preds[t],
+          bg(rd(this._out[t]), n),
+          delete this._out[t],
+          delete this._sucs[t],
+          --this._nodeCount;
+      }
+      return this;
+    }
+    setParent(t, e) {
+      if (!this._isCompound) throw new Error("Cannot set parent in a non-compound graph");
+      if (Fg(e)) e = fy;
+      else {
+        for (var n = e += ""; !Fg(n); n = this.parent(n)) {
+          if (n === t) throw new Error("Setting " + e + " as parent of " + t + " would create a cycle");
+        }
+        this.setNode(e);
+      }
+      return this.setNode(t), this._removeFromParentsChildList(t), this._parent[t] = e, this._children[e][t] = !0, this;
+    }
+    _removeFromParentsChildList(t) {
+      delete this._children[this._parent[t]][t];
+    }
+    parent(t) {
+      if (this._isCompound) {
+        var e = this._parent[t];
+        if (e !== fy) return e;
+      }
+    }
+    children(t) {
+      if (Fg(t) && (t = fy), this._isCompound) {
+        var e = this._children[t];
+        if (e) return rd(e);
+      } else {
+        if (t === fy) return this.nodes();
+        if (this.hasNode(t)) return [];
+      }
+    }
+    predecessors(t) {
+      var e = this._preds[t];
+      if (e) return rd(e);
+    }
+    successors(t) {
+      var e = this._sucs[t];
+      if (e) return rd(e);
+    }
+    neighbors(t) {
+      var e = this.predecessors(t);
+      if (e) return hy(e, this.successors(t));
+    }
+    isLeaf(t) {
+      return 0 === (this.isDirected() ? this.successors(t) : this.neighbors(t)).length;
+    }
+    filterNodes(t) {
+      var e = new this.constructor({
+        directed: this._isDirected,
+        multigraph: this._isMultigraph,
+        compound: this._isCompound,
+      });
+      e.setGraph(this.graph());
+      var n = this;
+      bg(this._nodes, function(n, i) {
+        t(i) && e.setNode(i, n);
+      }),
+        bg(this._edgeObjs, function(t) {
+          e.hasNode(t.v) && e.hasNode(t.w) && e.setEdge(t, n.edge(t));
+        });
+      var i = {};
+      function r(t) {
+        var a = n.parent(t);
+        return void 0 === a || e.hasNode(a) ? (i[t] = a, a) : a in i ? i[a] : r(a);
+      }
+      return this._isCompound && bg(e.nodes(), function(t) {
+        e.setParent(t, r(t));
+      }),
+        e;
+    }
+    setDefaultEdgeLabel(t) {
+      return gc(t) || (t = su(t)), this._defaultEdgeLabelFn = t, this;
+    }
+    edgeCount() {
+      return this._edgeCount;
+    }
+    edges() {
+      return Og(this._edgeObjs);
+    }
+    setPath(t, e) {
+      var n = this, i = arguments;
+      return iy(t, function(t, r) {
+        return i.length > 1 ? n.setEdge(t, r, e) : n.setEdge(t, r), r;
+      }),
+        this;
+    }
+    setEdge() {
+      var t, e, n, i, r = !1, a = arguments[0];
+      "object" == typeof a && null !== a && "v" in a
+        ? (t = a.v, e = a.w, n = a.name, 2 === arguments.length && (i = arguments[1], r = !0))
+        : (t = a, e = arguments[1], n = arguments[3], arguments.length > 2 && (i = arguments[2], r = !0)),
+        t = "" + t,
+        e = "" + e,
+        Fg(n) || (n = "" + n);
+      var s = _y(this._isDirected, t, e, n);
+      if (Lg(this._edgeLabels, s)) return r && (this._edgeLabels[s] = i), this;
+      if (!Fg(n) && !this._isMultigraph) throw new Error("Cannot set a named edge when isMultigraph = false");
+      this.setNode(t), this.setNode(e), this._edgeLabels[s] = r ? i : this._defaultEdgeLabelFn(t, e, n);
+      var o = function(t, e, n, i) {
+        var r = "" + e, a = "" + n;
+        if (!t && r > a) {
+          var s = r;
+          r = a, a = s;
+        }
+        var o = { v: r, w: a };
+        i && (o.name = i);
+        return o;
+      }(this._isDirected, t, e, n);
+      return t = o.v,
+        e = o.w,
+        Object.freeze(o),
+        this._edgeObjs[s] = o,
+        my(this._preds[e], t),
+        my(this._sucs[t], e),
+        this._in[e][s] = o,
+        this._out[t][s] = o,
+        this._edgeCount++,
+        this;
+    }
+    edge(t, e, n) {
+      var i = 1 === arguments.length ? xy(this._isDirected, arguments[0]) : _y(this._isDirected, t, e, n);
+      return this._edgeLabels[i];
+    }
+    hasEdge(t, e, n) {
+      var i = 1 === arguments.length ? xy(this._isDirected, arguments[0]) : _y(this._isDirected, t, e, n);
+      return Lg(this._edgeLabels, i);
+    }
+    removeEdge(t, e, n) {
+      var i = 1 === arguments.length ? xy(this._isDirected, arguments[0]) : _y(this._isDirected, t, e, n),
+        r = this._edgeObjs[i];
+      return r
+        && (t = r.v,
+          e = r.w,
+          delete this._edgeLabels[i],
+          delete this._edgeObjs[i],
+          by(this._preds[e], t),
+          by(this._sucs[t], e),
+          delete this._in[e][i],
+          delete this._out[t][i],
+          this._edgeCount--),
+        this;
+    }
+    inEdges(t, e) {
+      var n = this._in[t];
+      if (n) {
+        var i = Og(n);
+        return e
+          ? xg(i, function(t) {
+            return t.v === e;
+          })
+          : i;
+      }
+    }
+    outEdges(t, e) {
+      var n = this._out[t];
+      if (n) {
+        var i = Og(n);
+        return e
+          ? xg(i, function(t) {
+            return t.w === e;
+          })
+          : i;
+      }
+    }
+    nodeEdges(t, e) {
+      var n = this.inEdges(t, e);
+      if (n) return n.concat(this.outEdges(t, e));
+    }
+  }
+  function my(t, e) {
+    t[e] ? t[e]++ : t[e] = 1;
+  }
+  function by(t, e) {
+    --t[e] || delete t[e];
+  }
+  function _y(t, e, n, i) {
+    var r = "" + e, a = "" + n;
+    if (!t && r > a) {
+      var s = r;
+      r = a, a = s;
+    }
+    return r + gy + a + gy + (Fg(i) ? py : i);
+  }
+  function xy(t, e) {
+    return _y(t, e.v, e.w, e.name);
+  }
+  yy.prototype._nodeCount = 0, yy.prototype._edgeCount = 0;
+  class vy {
+    constructor() {
+      var t = {};
+      t._next = t._prev = t, this._sentinel = t;
+    }
+    dequeue() {
+      var t = this._sentinel, e = t._prev;
+      if (e !== t) return ky(e), e;
+    }
+    enqueue(t) {
+      var e = this._sentinel;
+      t._prev && t._next && ky(t), t._next = e._next, e._next._prev = t, e._next = t, t._prev = e;
+    }
+    toString() {
+      for (var t = [], e = this._sentinel, n = e._prev; n !== e;) t.push(JSON.stringify(n, wy)), n = n._prev;
+      return "[" + t.join(", ") + "]";
+    }
+  }
+  function ky(t) {
+    t._prev._next = t._next, t._next._prev = t._prev, delete t._next, delete t._prev;
+  }
+  function wy(t, e) {
+    if ("_next" !== t && "_prev" !== t) return e;
+  }
+  var Ty = su(1);
+  function Cy(t, e) {
+    if (t.nodeCount() <= 1) return [];
+    var n = function(t, e) {
+        var n = new yy(), i = 0, r = 0;
+        bg(t.nodes(), function(t) {
+          n.setNode(t, { v: t, in: 0, out: 0 });
+        }),
+          bg(t.edges(), function(t) {
+            var a = n.edge(t.v, t.w) || 0, s = e(t), o = a + s;
+            n.setEdge(t.v, t.w, o), r = Math.max(r, n.node(t.v).out += s), i = Math.max(i, n.node(t.w).in += s);
+          });
+        var a = ey(r + i + 3).map(function() {
+            return new vy();
+          }),
+          s = i + 1;
+        return bg(n.nodes(), function(t) {
+          Sy(a, s, n.node(t));
+        }),
+          { graph: n, buckets: a, zeroIdx: s };
+      }(t, e || Ty),
+      i = function(t, e, n) {
+        var i, r = [], a = e[e.length - 1], s = e[0];
+        for (; t.nodeCount();) {
+          for (; i = s.dequeue();) Ey(t, e, n, i);
+          for (; i = a.dequeue();) Ey(t, e, n, i);
+          if (t.nodeCount()) {
+            for (var o = e.length - 2; o > 0; --o) {
+              if (i = e[o].dequeue()) {
+                r = r.concat(Ey(t, e, n, i, !0));
+                break;
+              }
+            }
+          }
+        }
+        return r;
+      }(n.graph, n.buckets, n.zeroIdx);
+    return Cd(Eg(i, function(e) {
+      return t.outEdges(e.v, e.w);
+    }));
+  }
+  function Ey(t, e, n, i, r) {
+    var a = r ? [] : void 0;
+    return bg(t.inEdges(i.v), function(i) {
+      var s = t.edge(i), o = t.node(i.v);
+      r && a.push({ v: i.v, w: i.w }), o.out -= s, Sy(e, n, o);
+    }),
+      bg(t.outEdges(i.v), function(i) {
+        var r = t.edge(i), a = i.w, s = t.node(a);
+        s.in -= r, Sy(e, n, s);
+      }),
+      t.removeNode(i.v),
+      a;
+  }
+  function Sy(t, e, n) {
+    n.out ? n.in ? t[n.out - n.in + e].enqueue(n) : t[t.length - 1].enqueue(n) : t[0].enqueue(n);
+  }
+  function Ay(t) {
+    var e = "greedy" === t.graph().acyclicer
+      ? Cy(
+        t,
+        function(t) {
+          return function(e) {
+            return t.edge(e).weight;
+          };
+        }(t),
+      )
+      : function(t) {
+        var e = [], n = {}, i = {};
+        function r(a) {
+          Lg(i, a) || (i[a] = !0,
+            n[a] = !0,
+            bg(t.outEdges(a), function(t) {
+              Lg(n, t.w) ? e.push(t) : r(t.w);
+            }),
+            delete n[a]);
+        }
+        return bg(t.nodes(), r), e;
+      }(t);
+    bg(e, function(e) {
+      var n = t.edge(e);
+      t.removeEdge(e), n.forwardName = e.name, n.reversed = !0, t.setEdge(e.w, e.v, n, dy("rev"));
+    });
+  }
+  function Dy(t, e, n, i) {
+    var r;
+    do {
+      r = dy(i);
+    } while (t.hasNode(r));
+    return n.dummy = e, t.setNode(r, n), r;
+  }
+  function Ly(t) {
+    var e = new yy({ multigraph: t.isMultigraph() }).setGraph(t.graph());
+    return bg(t.nodes(), function(n) {
+      t.children(n).length || e.setNode(n, t.node(n));
+    }),
+      bg(t.edges(), function(n) {
+        e.setEdge(n, t.edge(n));
+      }),
+      e;
+  }
+  function Oy(t, e) {
+    var n, i, r = t.x, a = t.y, s = e.x - r, o = e.y - a, l = t.width / 2, c = t.height / 2;
+    if (!s && !o) throw new Error("Not possible to find intersection inside of the rectangle");
+    return Math.abs(o) * l > Math.abs(s) * c
+      ? (o < 0 && (c = -c), n = c * s / o, i = c)
+      : (s < 0 && (l = -l), n = l, i = l * o / s),
+      { x: r + n, y: a + i };
+  }
+  function Ny(t) {
+    var e = Eg(ey(By(t) + 1), function() {
+      return [];
+    });
+    return bg(t.nodes(), function(n) {
+      var i = t.node(n), r = i.rank;
+      Fg(r) || (e[r][i.order] = n);
+    }),
+      e;
+  }
+  function My(t, e, n, i) {
+    var r = { width: 0, height: 0 };
+    return arguments.length >= 4 && (r.rank = n, r.order = i), Dy(t, "border", r, e);
+  }
+  function By(t) {
+    return Yg(Eg(t.nodes(), function(e) {
+      var n = t.node(e).rank;
+      if (!Fg(n)) return n;
+    }));
+  }
+  function Iy(t, e) {
+    var n = ag();
+    try {
+      return e();
+    } finally {
+      console.log(t + " time: " + (ag() - n) + "ms");
+    }
+  }
+  function Fy(t, e) {
+    return e();
+  }
+  function Ry(t, e, n, i, r, a) {
+    var s = { width: 0, height: 0, rank: a, borderType: e }, o = r[e][a - 1], l = Dy(t, "border", s, n);
+    r[e][a] = l, t.setParent(l, i), o && t.setEdge(o, l, { weight: 1 });
+  }
+  function $y(t) {
+    var e = t.graph().rankdir.toLowerCase();
+    "bt" !== e && "rl" !== e || function(t) {
+      bg(t.nodes(), function(e) {
+        jy(t.node(e));
+      }),
+        bg(t.edges(), function(e) {
+          var n = t.edge(e);
+          bg(n.points, jy), Lg(n, "y") && jy(n);
+        });
+    }(t),
+      "lr" !== e && "rl" !== e || (!function(t) {
+        bg(t.nodes(), function(e) {
+          zy(t.node(e));
+        }),
+          bg(t.edges(), function(e) {
+            var n = t.edge(e);
+            bg(n.points, zy), Lg(n, "x") && zy(n);
+          });
+      }(t),
+        Py(t));
+  }
+  function Py(t) {
+    bg(t.nodes(), function(e) {
+      Yy(t.node(e));
+    }),
+      bg(t.edges(), function(e) {
+        Yy(t.edge(e));
+      });
+  }
+  function Yy(t) {
+    var e = t.width;
+    t.width = t.height, t.height = e;
+  }
+  function jy(t) {
+    t.y = -t.y;
+  }
+  function zy(t) {
+    var e = t.x;
+    t.x = t.y, t.y = e;
+  }
+  function Uy(t) {
+    var e = Dy(t, "root", {}, "_root"),
+      n = function(t) {
+        var e = {};
+        function n(i, r) {
+          var a = t.children(i);
+          a && a.length && bg(a, function(t) {
+            n(t, r + 1);
+          }), e[i] = r;
+        }
+        return bg(t.children(), function(t) {
+          n(t, 1);
+        }),
+          e;
+      }(t),
+      i = Yg(Og(n)) - 1,
+      r = 2 * i + 1;
+    t.graph().nestingRoot = e,
+      bg(t.edges(), function(e) {
+        t.edge(e).minlen *= r;
+      });
+    var a = function(t) {
+      return iy(t.edges(), function(e, n) {
+        return e + t.edge(n).weight;
+      }, 0);
+    }(t) + 1;
+    bg(t.children(), function(s) {
+      Wy(t, e, r, a, i, n, s);
+    }), t.graph().nodeRankFactor = r;
+  }
+  function Wy(t, e, n, i, r, a, s) {
+    var o = t.children(s);
+    if (o.length) {
+      var l = My(t, "_bt"), c = My(t, "_bb"), h = t.node(s);
+      t.setParent(l, s),
+        h.borderTop = l,
+        t.setParent(c, s),
+        h.borderBottom = c,
+        bg(o, function(o) {
+          Wy(t, e, n, i, r, a, o);
+          var h = t.node(o),
+            u = h.borderTop ? h.borderTop : o,
+            d = h.borderBottom ? h.borderBottom : o,
+            p = h.borderTop ? i : 2 * i,
+            f = u !== d ? 1 : r - a[s] + 1;
+          t.setEdge(l, u, { weight: p, minlen: f, nestingEdge: !0 }),
+            t.setEdge(d, c, { weight: p, minlen: f, nestingEdge: !0 });
+        }),
+        t.parent(s) || t.setEdge(e, l, { weight: 0, minlen: r + a[s] });
+    } else s !== e && t.setEdge(e, s, { weight: 0, minlen: n });
+  }
+  function Hy(t, e, n) {
+    var i = function(t) {
+        var e;
+        for (; t.hasNode(e = dy("_root")););
+        return e;
+      }(t),
+      r = new yy({ compound: !0 }).setGraph({ root: i }).setDefaultNodeLabel(function(e) {
+        return t.node(e);
+      });
+    return bg(t.nodes(), function(a) {
+      var s = t.node(a), o = t.parent(a);
+      (s.rank === e || s.minRank <= e && e <= s.maxRank)
+        && (r.setNode(a),
+          r.setParent(a, o || i),
+          bg(t[n](a), function(e) {
+            var n = e.v === a ? e.w : e.v, i = r.edge(n, a), s = Fg(i) ? 0 : i.weight;
+            r.setEdge(n, a, { weight: t.edge(e).weight + s });
+          }),
+          Lg(s, "minRank") && r.setNode(a, { borderLeft: s.borderLeft[e], borderRight: s.borderRight[e] }));
+    }),
+      r;
+  }
+  function qy(t, e) {
+    for (var n = 0, i = 1; i < e.length; ++i) n += Vy(t, e[i - 1], e[i]);
+    return n;
+  }
+  function Vy(t, e, n) {
+    for (
+      var i = function(t, e) {
+          return function(t, e, n) {
+            for (var i = -1, r = t.length, a = e.length, s = {}; ++i < r;) {
+              var o = i < a ? e[i] : void 0;
+              n(s, t[i], o);
+            }
+            return s;
+          }(t || [], e || [], vu);
+        }(
+          n,
+          Eg(n, function(t, e) {
+            return e;
+          }),
+        ),
+        r = Cd(Eg(e, function(e) {
+          return ay(
+            Eg(t.outEdges(e), function(e) {
+              return { pos: i[e.w], weight: t.edge(e).weight };
+            }),
+            "pos",
+          );
+        })),
+        a = 1;
+      a < n.length;
+    ) a <<= 1;
+    var s = 2 * a - 1;
+    a -= 1;
+    var o = Eg(new Array(s), function() {
+        return 0;
+      }),
+      l = 0;
+    return bg(r.forEach(function(t) {
+      var e = t.pos + a;
+      o[e] += t.weight;
+      for (var n = 0; e > 0;) e % 2 && (n += o[e + 1]), o[e = e - 1 >> 1] += t.weight;
+      l += t.weight * n;
+    })),
+      l;
+  }
+  function Gy(t, e) {
+    var n = {};
+    return bg(t, function(t, e) {
+      var i = n[t.v] = { indegree: 0, in: [], out: [], vs: [t.v], i: e };
+      Fg(t.barycenter) || (i.barycenter = t.barycenter, i.weight = t.weight);
+    }),
+      bg(e.edges(), function(t) {
+        var e = n[t.v], i = n[t.w];
+        Fg(e) || Fg(i) || (i.indegree++, e.out.push(n[t.w]));
+      }),
+      function(t) {
+        var e = [];
+        function n(t) {
+          return function(e) {
+            e.merged || (Fg(e.barycenter) || Fg(t.barycenter) || e.barycenter >= t.barycenter) && function(t, e) {
+                  var n = 0, i = 0;
+                  t.weight && (n += t.barycenter * t.weight, i += t.weight);
+                  e.weight && (n += e.barycenter * e.weight, i += e.weight);
+                  t.vs = e.vs.concat(t.vs), t.barycenter = n / i, t.weight = i, t.i = Math.min(e.i, t.i), e.merged = !0;
+                }(t, e);
+          };
+        }
+        function i(e) {
+          return function(n) {
+            n.in.push(e), 0 == --n.indegree && t.push(n);
+          };
+        }
+        for (; t.length;) {
+          var r = t.pop();
+          e.push(r), bg(r.in.reverse(), n(r)), bg(r.out, i(r));
+        }
+        return Eg(
+          xg(e, function(t) {
+            return !t.merged;
+          }),
+          function(t) {
+            return Qg(t, ["vs", "i", "barycenter", "weight"]);
+          },
+        );
+      }(xg(n, function(t) {
+        return !t.indegree;
+      }));
+  }
+  function Xy(t, e) {
+    var n,
+      i = function(t, e) {
+        var n = { lhs: [], rhs: [] };
+        return bg(t, function(t) {
+          e(t) ? n.lhs.push(t) : n.rhs.push(t);
+        }),
+          n;
+      }(t, function(t) {
+        return Lg(t, "barycenter");
+      }),
+      r = i.lhs,
+      a = ay(i.rhs, function(t) {
+        return -t.i;
+      }),
+      s = [],
+      o = 0,
+      l = 0,
+      c = 0;
+    r.sort(
+      (n = !!e, function(t, e) {
+        return t.barycenter < e.barycenter ? -1 : t.barycenter > e.barycenter ? 1 : n ? e.i - t.i : t.i - e.i;
+      }),
+    ),
+      c = Zy(s, a, c),
+      bg(r, function(t) {
+        c += t.vs.length, s.push(t.vs), o += t.barycenter * t.weight, l += t.weight, c = Zy(s, a, c);
+      });
+    var h = { vs: Cd(s) };
+    return l && (h.barycenter = o / l, h.weight = l), h;
+  }
+  function Zy(t, e, n) {
+    for (var i; e.length && (i = yg(e)).i <= n;) e.pop(), t.push(i.vs), n++;
+    return n;
+  }
+  function Qy(t, e, n, i) {
+    var r = t.children(e), a = t.node(e), s = a ? a.borderLeft : void 0, o = a ? a.borderRight : void 0, l = {};
+    s && (r = xg(r, function(t) {
+      return t !== s && t !== o;
+    }));
+    var c = function(t, e) {
+      return Eg(e, function(e) {
+        var n = t.inEdges(e);
+        if (n.length) {
+          var i = iy(n, function(e, n) {
+            var i = t.edge(n), r = t.node(n.v);
+            return { sum: e.sum + i.weight * r.order, weight: e.weight + i.weight };
+          }, { sum: 0, weight: 0 });
+          return { v: e, barycenter: i.sum / i.weight, weight: i.weight };
+        }
+        return { v: e };
+      });
+    }(t, r);
+    bg(c, function(e) {
+      if (t.children(e.v).length) {
+        var r = Qy(t, e.v, n, i);
+        l[e.v] = r,
+          Lg(r, "barycenter")
+          && (s = r,
+            Fg((a = e).barycenter)
+              ? (a.barycenter = s.barycenter, a.weight = s.weight)
+              : (a.barycenter = (a.barycenter * a.weight + s.barycenter * s.weight) / (a.weight + s.weight),
+                a.weight += s.weight));
+      }
+      var a, s;
+    });
+    var h = Gy(c, n);
+    !function(t, e) {
+      bg(t, function(t) {
+        t.vs = Cd(t.vs.map(function(t) {
+          return e[t] ? e[t].vs : t;
+        }));
+      });
+    }(h, l);
+    var u = Xy(h, i);
+    if (s && (u.vs = Cd([s, u.vs, o]), t.predecessors(s).length)) {
+      var d = t.node(t.predecessors(s)[0]), p = t.node(t.predecessors(o)[0]);
+      Lg(u, "barycenter") || (u.barycenter = 0, u.weight = 0),
+        u.barycenter = (u.barycenter * u.weight + d.order + p.order) / (u.weight + 2),
+        u.weight += 2;
+    }
+    return u;
+  }
+  function Ky(t) {
+    var e = By(t),
+      n = Jy(t, ey(1, e + 1), "inEdges"),
+      i = Jy(t, ey(e - 1, -1, -1), "outEdges"),
+      r = function(t) {
+        var e = {},
+          n = xg(t.nodes(), function(e) {
+            return !t.children(e).length;
+          }),
+          i = Yg(Eg(n, function(e) {
+            return t.node(e).rank;
+          })),
+          r = Eg(ey(i + 1), function() {
+            return [];
+          });
+        return bg(
+          ay(n, function(e) {
+            return t.node(e).rank;
+          }),
+          function n(i) {
+            if (!Lg(e, i)) {
+              e[i] = !0;
+              var a = t.node(i);
+              r[a.rank].push(i), bg(t.successors(i), n);
+            }
+          },
+        ),
+          r;
+      }(t);
+    em(t, r);
+    for (var a, s = Number.POSITIVE_INFINITY, o = 0, l = 0; l < 4; ++o, ++l) {
+      tm(o % 2 ? n : i, o % 4 >= 2);
+      var c = qy(t, r = Ny(t));
+      c < s && (l = 0, a = nf(r, af | sf), s = c);
+    }
+    em(t, a);
+  }
+  function Jy(t, e, n) {
+    return Eg(e, function(e) {
+      return Hy(t, e, n);
+    });
+  }
+  function tm(t, e) {
+    var n = new yy();
+    bg(t, function(t) {
+      var i = t.graph().root, r = Qy(t, i, n, e);
+      bg(r.vs, function(e, n) {
+        t.node(e).order = n;
+      }),
+        function(t, e, n) {
+          var i, r = {};
+          bg(n, function(n) {
+            for (var a, s, o = t.parent(n); o;) {
+              if ((a = t.parent(o)) ? (s = r[a], r[a] = o) : (s = i, i = o), s && s !== o) return void e.setEdge(s, o);
+              o = a;
+            }
+          });
+        }(t, n, r.vs);
+    });
+  }
+  function em(t, e) {
+    bg(e, function(e) {
+      bg(e, function(e, n) {
+        t.node(e).order = n;
+      });
+    });
+  }
+  function nm(t) {
+    var e = function(t) {
+      var e = {}, n = 0;
+      function i(r) {
+        var a = n;
+        bg(t.children(r), i), e[r] = { low: a, lim: n++ };
+      }
+      return bg(t.children(), i), e;
+    }(t);
+    bg(t.graph().dummyChains, function(n) {
+      for (
+        var i = t.node(n),
+          r = i.edgeObj,
+          a = function(t, e, n, i) {
+            var r, a, s = [], o = [], l = Math.min(e[n].low, e[i].low), c = Math.max(e[n].lim, e[i].lim);
+            r = n;
+            do {
+              r = t.parent(r), s.push(r);
+            } while (r && (e[r].low > l || c > e[r].lim));
+            a = r, r = i;
+            for (; (r = t.parent(r)) !== a;) o.push(r);
+            return { path: s.concat(o.reverse()), lca: a };
+          }(t, e, r.v, r.w),
+          s = a.path,
+          o = a.lca,
+          l = 0,
+          c = s[l],
+          h = !0;
+        n !== r.w;
+      ) {
+        if (i = t.node(n), h) {
+          for (; (c = s[l]) !== o && t.node(c).maxRank < i.rank;) l++;
+          c === o && (h = !1);
+        }
+        if (!h) {
+          for (; l < s.length - 1 && t.node(c = s[l + 1]).minRank <= i.rank;) l++;
+          c = s[l];
+        }
+        t.setParent(n, c), n = t.successors(n)[0];
+      }
+    });
+  }
+  function im(t, e) {
+    var n = {};
+    return iy(e, function(e, i) {
+      var r = 0, a = 0, s = e.length, o = yg(i);
+      return bg(i, function(e, l) {
+        var c = function(t, e) {
+            if (t.node(e).dummy) {
+              return Tg(t.predecessors(e), function(e) {
+                return t.node(e).dummy;
+              });
+            }
+          }(t, e),
+          h = c ? t.node(c).order : s;
+        (c || e === o) && (bg(i.slice(a, l + 1), function(e) {
+          bg(t.predecessors(e), function(i) {
+            var a = t.node(i), s = a.order;
+            !(s < r || h < s) || a.dummy && t.node(e).dummy || rm(n, i, e);
+          });
+        }),
+          a = l + 1,
+          r = h);
+      }),
+        i;
+    }),
+      n;
+  }
+  function rm(t, e, n) {
+    if (e > n) {
+      var i = e;
+      e = n, n = i;
+    }
+    var r = t[e];
+    r || (t[e] = r = {}), r[n] = !0;
+  }
+  function am(t, e, n) {
+    if (e > n) {
+      var i = e;
+      e = n, n = i;
+    }
+    return Lg(t[e], n);
+  }
+  function sm(t, e, n, i, r) {
+    var a = {},
+      s = function(t, e, n, i) {
+        var r = new yy(),
+          a = t.graph(),
+          s = function(t, e, n) {
+            return function(i, r, a) {
+              var s, o = i.node(r), l = i.node(a), c = 0;
+              if (c += o.width / 2, Lg(o, "labelpos")) {
+                switch (o.labelpos.toLowerCase()) {
+                  case "l":
+                    s = -o.width / 2;
+                    break;
+                  case "r":
+                    s = o.width / 2;
+                }
+              }
+              if (
+                s && (c += n ? s : -s),
+                  s = 0,
+                  c += (o.dummy ? e : t) / 2,
+                  c += (l.dummy ? e : t) / 2,
+                  c += l.width / 2,
+                  Lg(l, "labelpos")
+              ) {
+                switch (l.labelpos.toLowerCase()) {
+                  case "l":
+                    s = l.width / 2;
+                    break;
+                  case "r":
+                    s = -l.width / 2;
+                }
+              }
+              return s && (c += n ? s : -s), s = 0, c;
+            };
+          }(a.nodesep, a.edgesep, i);
+        return bg(e, function(e) {
+          var i;
+          bg(e, function(e) {
+            var a = n[e];
+            if (r.setNode(a), i) {
+              var o = n[i], l = r.edge(o, a);
+              r.setEdge(o, a, Math.max(s(t, e, i), l || 0));
+            }
+            i = e;
+          });
+        }),
+          r;
+      }(t, e, n, r),
+      o = r ? "borderLeft" : "borderRight";
+    function l(t, e) {
+      for (var n = s.nodes(), i = n.pop(), r = {}; i;) {
+        r[i] ? t(i) : (r[i] = !0, n.push(i), n = n.concat(e(i))), i = n.pop();
+      }
+    }
+    return l(function(t) {
+      a[t] = s.inEdges(t).reduce(function(t, e) {
+        return Math.max(t, a[e.v] + s.edge(e));
+      }, 0);
+    }, s.predecessors.bind(s)),
+      l(function(e) {
+        var n = s.outEdges(e).reduce(function(t, e) {
+            return Math.min(t, a[e.w] - s.edge(e));
+          }, Number.POSITIVE_INFINITY),
+          i = t.node(e);
+        n !== Number.POSITIVE_INFINITY && i.borderType !== o && (a[e] = Math.max(a[e], n));
+      }, s.successors.bind(s)),
+      bg(i, function(t) {
+        a[t] = a[n[t]];
+      }),
+      a;
+  }
+  function om(t, e) {
+    return Hg(Og(e), function(e) {
+      var n = Number.NEGATIVE_INFINITY, i = Number.POSITIVE_INFINITY;
+      return function(t, e) {
+        null == t || eg(t, mg(e), od);
+      }(e, function(e, r) {
+        var a = function(t, e) {
+          return t.node(e).width;
+        }(t, r) / 2;
+        n = Math.max(e + a, n), i = Math.min(e - a, i);
+      }),
+        n - i;
+    });
+  }
+  function lm(t) {
+    var e,
+      n = Ny(t),
+      i = Ug(
+        im(t, n),
+        function(t, e) {
+          var n = {};
+          function i(e, i, r, a, s) {
+            var o;
+            bg(ey(i, r), function(i) {
+              o = e[i],
+                t.node(o).dummy && bg(t.predecessors(o), function(e) {
+                  var i = t.node(e);
+                  i.dummy && (i.order < a || i.order > s) && rm(n, e, o);
+                });
+            });
+          }
+          return iy(e, function(e, n) {
+            var r, a = -1, s = 0;
+            return bg(n, function(o, l) {
+              if ("border" === t.node(o).dummy) {
+                var c = t.predecessors(o);
+                c.length && (r = t.node(c[0]).order, i(n, s, l, a, r), s = l, a = r);
+              }
+              i(n, s, n.length, r, e.length);
+            }),
+              n;
+          }),
+            n;
+        }(t, n),
+      ),
+      r = {};
+    bg(["u", "d"], function(a) {
+      e = "u" === a ? n : Og(n).reverse(),
+        bg(["l", "r"], function(n) {
+          "r" === n && (e = Eg(e, function(t) {
+            return Og(t).reverse();
+          }));
+          var s = ("u" === a ? t.predecessors : t.successors).bind(t),
+            o = function(t, e, n, i) {
+              var r = {}, a = {}, s = {};
+              return bg(e, function(t) {
+                bg(t, function(t, e) {
+                  r[t] = t, a[t] = t, s[t] = e;
+                });
+              }),
+                bg(e, function(t) {
+                  var e = -1;
+                  bg(t, function(t) {
+                    var o = i(t);
+                    if (o.length) {
+                      o = ay(o, function(t) {
+                        return s[t];
+                      });
+                      for (var l = (o.length - 1) / 2, c = Math.floor(l), h = Math.ceil(l); c <= h; ++c) {
+                        var u = o[c];
+                        a[t] === t && e < s[u] && !am(n, t, u) && (a[u] = t, a[t] = r[t] = r[u], e = s[u]);
+                      }
+                    }
+                  });
+                }),
+                { root: r, align: a };
+            }(0, e, i, s),
+            l = sm(t, e, o.root, o.align, "r" === n);
+          "r" === n && (l = $g(l, function(t) {
+            return -t;
+          })), r[a + n] = l;
+        });
+    });
+    var a = om(t, r);
+    return function(t, e) {
+      var n = Og(e), i = Wg(n), r = Yg(n);
+      bg(["u", "d"], function(n) {
+        bg(["l", "r"], function(a) {
+          var s, o = n + a, l = t[o];
+          if (l !== e) {
+            var c = Og(l);
+            (s = "l" === a ? i - Wg(c) : r - Yg(c)) && (t[o] = $g(l, function(t) {
+              return t + s;
+            }));
+          }
+        });
+      });
+    }(r, a),
+      function(t, e) {
+        return $g(t.ul, function(n, i) {
+          if (e) return t[e.toLowerCase()][i];
+          var r = ay(Eg(t, i));
+          return (r[1] + r[2]) / 2;
+        });
+      }(r, t.graph().align);
+  }
+  function cm(t) {
+    (function(t) {
+      var e = Ny(t), n = t.graph().ranksep, i = 0;
+      bg(e, function(e) {
+        var r = Yg(Eg(e, function(e) {
+          return t.node(e).height;
+        }));
+        bg(e, function(e) {
+          t.node(e).y = i + r / 2;
+        }), i += r + n;
+      });
+    })(t = Ly(t)),
+      bg(lm(t), function(e, n) {
+        t.node(n).x = e;
+      });
+  }
+  function hm(t, e) {
+    var n = e && e.debugTiming ? Iy : Fy;
+    n("layout", function() {
+      var e = n("  buildLayoutGraph", function() {
+        return function(t) {
+          var e = new yy({ multigraph: !0, compound: !0 }), n = xm(t.graph());
+          return e.setGraph(Ug({}, dm, _m(n, um), Qg(n, pm))),
+            bg(t.nodes(), function(n) {
+              var i = xm(t.node(n));
+              e.setNode(n, cg(_m(i, fm), gm)), e.setParent(n, t.parent(n));
+            }),
+            bg(t.edges(), function(n) {
+              var i = xm(t.edge(n));
+              e.setEdge(n, Ug({}, mm, _m(i, ym), Qg(i, bm)));
+            }),
+            e;
+        }(t);
+      });
+      n("  runLayout", function() {
+        !function(t, e) {
+          e("    makeSpaceForEdgeLabels", function() {
+            !function(t) {
+              var e = t.graph();
+              e.ranksep /= 2,
+                bg(t.edges(), function(n) {
+                  var i = t.edge(n);
+                  i.minlen *= 2,
+                    "c" !== i.labelpos.toLowerCase()
+                    && ("TB" === e.rankdir || "BT" === e.rankdir
+                      ? i.width += i.labeloffset
+                      : i.height += i.labeloffset);
+                });
+            }(t);
+          }),
+            e("    removeSelfEdges", function() {
+              !function(t) {
+                bg(t.edges(), function(e) {
+                  if (e.v === e.w) {
+                    var n = t.node(e.v);
+                    n.selfEdges || (n.selfEdges = []), n.selfEdges.push({ e: e, label: t.edge(e) }), t.removeEdge(e);
+                  }
+                });
+              }(t);
+            }),
+            e("    acyclic", function() {
+              Ay(t);
+            }),
+            e("    nestingGraph.run", function() {
+              Uy(t);
+            }),
+            e("    rank", function() {
+              !function(t) {
+                switch (t.graph().ranker) {
+                  case "network-simplex":
+                  default:
+                    Pm(t);
+                    break;
+                  case "tight-tree":
+                    !function(t) {
+                      vm(t), wm(t);
+                    }(t);
+                    break;
+                  case "longest-path":
+                    $m(t);
+                }
+              }(Ly(t));
+            }),
+            e("    injectEdgeLabelProxies", function() {
+              !function(t) {
+                bg(t.edges(), function(e) {
+                  var n = t.edge(e);
+                  if (n.width && n.height) {
+                    var i = t.node(e.v), r = { rank: (t.node(e.w).rank - i.rank) / 2 + i.rank, e: e };
+                    Dy(t, "edge-proxy", r, "_ep");
+                  }
+                });
+              }(t);
+            }),
+            e("    removeEmptyRanks", function() {
+              !function(t) {
+                var e = Wg(Eg(t.nodes(), function(e) {
+                    return t.node(e).rank;
+                  })),
+                  n = [];
+                bg(t.nodes(), function(i) {
+                  var r = t.node(i).rank - e;
+                  n[r] || (n[r] = []), n[r].push(i);
+                });
+                var i = 0, r = t.graph().nodeRankFactor;
+                bg(n, function(e, n) {
+                  Fg(e) && n % r != 0 ? --i : i && bg(e, function(e) {
+                    t.node(e).rank += i;
+                  });
+                });
+              }(t);
+            }),
+            e("    nestingGraph.cleanup", function() {
+              !function(t) {
+                var e = t.graph();
+                t.removeNode(e.nestingRoot),
+                  delete e.nestingRoot,
+                  bg(t.edges(), function(e) {
+                    t.edge(e).nestingEdge && t.removeEdge(e);
+                  });
+              }(t);
+            }),
+            e("    normalizeRanks", function() {
+              !function(t) {
+                var e = Wg(Eg(t.nodes(), function(e) {
+                  return t.node(e).rank;
+                }));
+                bg(t.nodes(), function(n) {
+                  var i = t.node(n);
+                  Lg(i, "rank") && (i.rank -= e);
+                });
+              }(t);
+            }),
+            e("    assignRankMinMax", function() {
+              !function(t) {
+                var e = 0;
+                bg(t.nodes(), function(n) {
+                  var i = t.node(n);
+                  i.borderTop
+                    && (i.minRank = t.node(i.borderTop).rank,
+                      i.maxRank = t.node(i.borderBottom).rank,
+                      e = Yg(e, i.maxRank));
+                }), t.graph().maxRank = e;
+              }(t);
+            }),
+            e("    removeEdgeLabelProxies", function() {
+              !function(t) {
+                bg(t.nodes(), function(e) {
+                  var n = t.node(e);
+                  "edge-proxy" === n.dummy && (t.edge(n.e).labelRank = n.rank, t.removeNode(e));
+                });
+              }(t);
+            }),
+            e("    normalize.run", function() {
+              !function(t) {
+                t.graph().dummyChains = [],
+                  bg(t.edges(), function(e) {
+                    !function(t, e) {
+                      var n,
+                        i,
+                        r,
+                        a = e.v,
+                        s = t.node(a).rank,
+                        o = e.w,
+                        l = t.node(o).rank,
+                        c = e.name,
+                        h = t.edge(e),
+                        u = h.labelRank;
+                      if (l === s + 1) return;
+                      for (t.removeEdge(e), r = 0, ++s; s < l; ++r, ++s) {
+                        h.points = [],
+                          n = Dy(t, "edge", i = { width: 0, height: 0, edgeLabel: h, edgeObj: e, rank: s }, "_d"),
+                          s === u
+                          && (i.width = h.width, i.height = h.height, i.dummy = "edge-label", i.labelpos = h.labelpos),
+                          t.setEdge(a, n, { weight: h.weight }, c),
+                          0 === r && t.graph().dummyChains.push(n),
+                          a = n;
+                      }
+                      t.setEdge(a, o, { weight: h.weight }, c);
+                    }(t, e);
+                  });
+              }(t);
+            }),
+            e("    parentDummyChains", function() {
+              nm(t);
+            }),
+            e("    addBorderSegments", function() {
+              !function(t) {
+                bg(t.children(), function e(n) {
+                  var i = t.children(n), r = t.node(n);
+                  if (i.length && bg(i, e), Lg(r, "minRank")) {
+                    r.borderLeft = [], r.borderRight = [];
+                    for (var a = r.minRank, s = r.maxRank + 1; a < s; ++a) {
+                      Ry(t, "borderLeft", "_bl", n, r, a), Ry(t, "borderRight", "_br", n, r, a);
+                    }
+                  }
+                });
+              }(t);
+            }),
+            e("    order", function() {
+              Ky(t);
+            }),
+            e("    insertSelfEdges", function() {
+              !function(t) {
+                var e = Ny(t);
+                bg(e, function(e) {
+                  var n = 0;
+                  bg(e, function(e, i) {
+                    var r = t.node(e);
+                    r.order = i + n,
+                      bg(r.selfEdges, function(e) {
+                        Dy(t, "selfedge", {
+                          width: e.label.width,
+                          height: e.label.height,
+                          rank: r.rank,
+                          order: i + ++n,
+                          e: e.e,
+                          label: e.label,
+                        }, "_se");
+                      }),
+                      delete r.selfEdges;
+                  });
+                });
+              }(t);
+            }),
+            e("    adjustCoordinateSystem", function() {
+              !function(t) {
+                var e = t.graph().rankdir.toLowerCase();
+                "lr" !== e && "rl" !== e || Py(t);
+              }(t);
+            }),
+            e("    position", function() {
+              cm(t);
+            }),
+            e("    positionSelfEdges", function() {
+              !function(t) {
+                bg(t.nodes(), function(e) {
+                  var n = t.node(e);
+                  if ("selfedge" === n.dummy) {
+                    var i = t.node(n.e.v), r = i.x + i.width / 2, a = i.y, s = n.x - r, o = i.height / 2;
+                    t.setEdge(n.e, n.label),
+                      t.removeNode(e),
+                      n.label.points = [
+                        { x: r + 2 * s / 3, y: a - o },
+                        { x: r + 5 * s / 6, y: a - o },
+                        { x: r + s, y: a },
+                        { x: r + 5 * s / 6, y: a + o },
+                        { x: r + 2 * s / 3, y: a + o },
+                      ],
+                      n.label.x = n.x,
+                      n.label.y = n.y;
+                  }
+                });
+              }(t);
+            }),
+            e("    removeBorderNodes", function() {
+              !function(t) {
+                bg(t.nodes(), function(e) {
+                  if (t.children(e).length) {
+                    var n = t.node(e),
+                      i = t.node(n.borderTop),
+                      r = t.node(n.borderBottom),
+                      a = t.node(yg(n.borderLeft)),
+                      s = t.node(yg(n.borderRight));
+                    n.width = Math.abs(s.x - a.x),
+                      n.height = Math.abs(r.y - i.y),
+                      n.x = a.x + n.width / 2,
+                      n.y = i.y + n.height / 2;
+                  }
+                }),
+                  bg(t.nodes(), function(e) {
+                    "border" === t.node(e).dummy && t.removeNode(e);
+                  });
+              }(t);
+            }),
+            e("    normalize.undo", function() {
+              !function(t) {
+                bg(t.graph().dummyChains, function(e) {
+                  var n, i = t.node(e), r = i.edgeLabel;
+                  for (t.setEdge(i.edgeObj, r); i.dummy;) {
+                    n = t.successors(e)[0],
+                      t.removeNode(e),
+                      r.points.push({ x: i.x, y: i.y }),
+                      "edge-label" === i.dummy && (r.x = i.x, r.y = i.y, r.width = i.width, r.height = i.height),
+                      e = n,
+                      i = t.node(e);
+                  }
+                });
+              }(t);
+            }),
+            e("    fixupEdgeLabelCoords", function() {
+              !function(t) {
+                bg(t.edges(), function(e) {
+                  var n = t.edge(e);
+                  if (Lg(n, "x")) {
+                    switch ("l" !== n.labelpos && "r" !== n.labelpos || (n.width -= n.labeloffset), n.labelpos) {
+                      case "l":
+                        n.x -= n.width / 2 + n.labeloffset;
+                        break;
+                      case "r":
+                        n.x += n.width / 2 + n.labeloffset;
+                    }
+                  }
+                });
+              }(t);
+            }),
+            e("    undoCoordinateSystem", function() {
+              $y(t);
+            }),
+            e("    translateGraph", function() {
+              !function(t) {
+                var e = Number.POSITIVE_INFINITY,
+                  n = 0,
+                  i = Number.POSITIVE_INFINITY,
+                  r = 0,
+                  a = t.graph(),
+                  s = a.marginx || 0,
+                  o = a.marginy || 0;
+                function l(t) {
+                  var a = t.x, s = t.y, o = t.width, l = t.height;
+                  e = Math.min(e, a - o / 2),
+                    n = Math.max(n, a + o / 2),
+                    i = Math.min(i, s - l / 2),
+                    r = Math.max(r, s + l / 2);
+                }
+                bg(t.nodes(), function(e) {
+                  l(t.node(e));
+                }),
+                  bg(t.edges(), function(e) {
+                    var n = t.edge(e);
+                    Lg(n, "x") && l(n);
+                  }),
+                  e -= s,
+                  i -= o,
+                  bg(t.nodes(), function(n) {
+                    var r = t.node(n);
+                    r.x -= e, r.y -= i;
+                  }),
+                  bg(t.edges(), function(n) {
+                    var r = t.edge(n);
+                    bg(r.points, function(t) {
+                      t.x -= e, t.y -= i;
+                    }),
+                      Lg(r, "x") && (r.x -= e),
+                      Lg(r, "y") && (r.y -= i);
+                  }),
+                  a.width = n - e + s,
+                  a.height = r - i + o;
+              }(t);
+            }),
+            e("    assignNodeIntersects", function() {
+              !function(t) {
+                bg(t.edges(), function(e) {
+                  var n, i, r = t.edge(e), a = t.node(e.v), s = t.node(e.w);
+                  r.points ? (n = r.points[0], i = r.points[r.points.length - 1]) : (r.points = [], n = s, i = a),
+                    r.points.unshift(Oy(a, n)),
+                    r.points.push(Oy(s, i));
+                });
+              }(t);
+            }),
+            e("    reversePoints", function() {
+              !function(t) {
+                bg(t.edges(), function(e) {
+                  var n = t.edge(e);
+                  n.reversed && n.points.reverse();
+                });
+              }(t);
+            }),
+            e("    acyclic.undo", function() {
+              !function(t) {
+                bg(t.edges(), function(e) {
+                  var n = t.edge(e);
+                  if (n.reversed) {
+                    t.removeEdge(e);
+                    var i = n.forwardName;
+                    delete n.reversed, delete n.forwardName, t.setEdge(e.w, e.v, n, i);
+                  }
+                });
+              }(t);
+            });
+        }(e, n);
+      }),
+        n("  updateInputGraph", function() {
+          !function(t, e) {
+            bg(t.nodes(), function(n) {
+              var i = t.node(n), r = e.node(n);
+              i && (i.x = r.x, i.y = r.y, e.children(n).length && (i.width = r.width, i.height = r.height));
+            }),
+              bg(t.edges(), function(n) {
+                var i = t.edge(n), r = e.edge(n);
+                i.points = r.points, Lg(r, "x") && (i.x = r.x, i.y = r.y);
+              }),
+              t.graph().width = e.graph().width,
+              t.graph().height = e.graph().height;
+          }(t, e);
+        });
+    });
+  }
+  var um = ["nodesep", "edgesep", "ranksep", "marginx", "marginy"],
+    dm = { ranksep: 50, edgesep: 20, nodesep: 50, rankdir: "tb" },
+    pm = ["acyclicer", "ranker", "rankdir", "align"],
+    fm = ["width", "height"],
+    gm = { width: 0, height: 0 },
+    ym = ["minlen", "weight", "width", "height", "labeloffset"],
+    mm = { minlen: 1, weight: 1, width: 0, height: 0, labeloffset: 10, labelpos: "r" },
+    bm = ["labelpos"];
+  function _m(t, e) {
+    return $g(Qg(t, e), Number);
+  }
+  function xm(t) {
+    var e = {};
+    return bg(t, function(t, n) {
+      e[n.toLowerCase()] = t;
+    }),
+      e;
+  }
+  function vm(t) {
+    var e = {};
+    bg(t.sources(), function n(i) {
+      var r = t.node(i);
+      if (Lg(e, i)) return r.rank;
+      e[i] = !0;
+      var a = Wg(Eg(t.outEdges(i), function(e) {
+        return n(e.w) - t.edge(e).minlen;
+      }));
+      return a !== Number.POSITIVE_INFINITY && null != a || (a = 0), r.rank = a;
+    });
+  }
+  function km(t, e) {
+    return t.node(e.w).rank - t.node(e.v).rank - t.edge(e).minlen;
+  }
+  function wm(t) {
+    var e, n, i = new yy({ directed: !1 }), r = t.nodes()[0], a = t.nodeCount();
+    for (i.setNode(r, {}); Tm(i, t) < a;) e = Cm(i, t), n = i.hasNode(e.v) ? km(t, e) : -km(t, e), Em(i, t, n);
+    return i;
+  }
+  function Tm(t, e) {
+    return bg(t.nodes(), function n(i) {
+      bg(e.nodeEdges(i), function(r) {
+        var a = r.v, s = i === a ? r.w : a;
+        t.hasNode(s) || km(e, r) || (t.setNode(s, {}), t.setEdge(i, s, {}), n(s));
+      });
+    }),
+      t.nodeCount();
+  }
+  function Cm(t, e) {
+    return Hg(e.edges(), function(n) {
+      if (t.hasNode(n.v) !== t.hasNode(n.w)) return km(e, n);
+    });
+  }
+  function Em(t, e, n) {
+    bg(t.nodes(), function(t) {
+      e.node(t).rank += n;
+    });
+  }
+  function Sm(t, e, n) {
+    Ih(e) || (e = [e]);
+    var i = (t.isDirected() ? t.successors : t.neighbors).bind(t), r = [], a = {};
+    return bg(e, function(e) {
+      if (!t.hasNode(e)) throw new Error("Graph does not have node: " + e);
+      Am(t, e, "post" === n, a, i, r);
+    }),
+      r;
+  }
+  function Am(t, e, n, i, r, a) {
+    Lg(i, e) || (i[e] = !0,
+      n || a.push(e),
+      bg(r(e), function(e) {
+        Am(t, e, n, i, r, a);
+      }),
+      n && a.push(e));
+  }
+  function Dm(t) {
+    t = function(t) {
+      var e = (new yy()).setGraph(t.graph());
+      return bg(t.nodes(), function(n) {
+        e.setNode(n, t.node(n));
+      }),
+        bg(t.edges(), function(n) {
+          var i = e.edge(n.v, n.w) || { weight: 0, minlen: 1 }, r = t.edge(n);
+          e.setEdge(n.v, n.w, { weight: i.weight + r.weight, minlen: Math.max(i.minlen, r.minlen) });
+        }),
+        e;
+    }(t), vm(t);
+    var e, n = wm(t);
+    for (Nm(n), Lm(n, t); e = Bm(n);) Fm(n, t, e, Im(n, t, e));
+  }
+  function Lm(t, e) {
+    var n = function(t, e) {
+      return Sm(t, e, "post");
+    }(t, t.nodes());
+    bg(n = n.slice(0, n.length - 1), function(n) {
+      !function(t, e, n) {
+        var i = t.node(n), r = i.parent;
+        t.edge(n, r).cutvalue = Om(t, e, n);
+      }(t, e, n);
+    });
+  }
+  function Om(t, e, n) {
+    var i = t.node(n).parent, r = !0, a = e.edge(n, i), s = 0;
+    return a || (r = !1, a = e.edge(i, n)),
+      s = a.weight,
+      bg(e.nodeEdges(n), function(a) {
+        var o, l, c = a.v === n, h = c ? a.w : a.v;
+        if (h !== i) {
+          var u = c === r, d = e.edge(a).weight;
+          if (s += u ? d : -d, o = n, l = h, t.hasEdge(o, l)) {
+            var p = t.edge(n, h).cutvalue;
+            s += u ? -p : p;
+          }
+        }
+      }),
+      s;
+  }
+  function Nm(t, e) {
+    arguments.length < 2 && (e = t.nodes()[0]), Mm(t, {}, 1, e);
+  }
+  function Mm(t, e, n, i, r) {
+    var a = n, s = t.node(i);
+    return e[i] = !0,
+      bg(t.neighbors(i), function(r) {
+        Lg(e, r) || (n = Mm(t, e, n, r, i));
+      }),
+      s.low = a,
+      s.lim = n++,
+      r ? s.parent = r : delete s.parent,
+      n;
+  }
+  function Bm(t) {
+    return Tg(t.edges(), function(e) {
+      return t.edge(e).cutvalue < 0;
+    });
+  }
+  function Im(t, e, n) {
+    var i = n.v, r = n.w;
+    e.hasEdge(i, r) || (i = n.w, r = n.v);
+    var a = t.node(i), s = t.node(r), o = a, l = !1;
+    a.lim > s.lim && (o = s, l = !0);
+    var c = xg(e.edges(), function(e) {
+      return l === Rm(t, t.node(e.v), o) && l !== Rm(t, t.node(e.w), o);
+    });
+    return Hg(c, function(t) {
+      return km(e, t);
+    });
+  }
+  function Fm(t, e, n, i) {
+    var r = n.v, a = n.w;
+    t.removeEdge(r, a),
+      t.setEdge(i.v, i.w, {}),
+      Nm(t),
+      Lm(t, e),
+      function(t, e) {
+        var n = Tg(t.nodes(), function(t) {
+            return !e.node(t).parent;
+          }),
+          i = function(t, e) {
+            return Sm(t, e, "pre");
+          }(t, n);
+        bg(i = i.slice(1), function(n) {
+          var i = t.node(n).parent, r = e.edge(n, i), a = !1;
+          r || (r = e.edge(i, n), a = !0), e.node(n).rank = e.node(i).rank + (a ? r.minlen : -r.minlen);
+        });
+      }(t, e);
+  }
+  function Rm(t, e, n) {
+    return n.low <= e.lim && e.lim <= n.lim;
+  }
+  new Error(),
+    Dm.initLowLimValues = Nm,
+    Dm.initCutValues = Lm,
+    Dm.calcCutValue = Om,
+    Dm.leaveEdge = Bm,
+    Dm.enterEdge = Im,
+    Dm.exchangeEdges = Fm;
+  var $m = vm;
+  function Pm(t) {
+    Dm(t);
+  }
+  function Ym(t) {
+    var e = {
+      options: { directed: t.isDirected(), multigraph: t.isMultigraph(), compound: t.isCompound() },
+      nodes: jm(t),
+      edges: zm(t),
+    };
+    return Fg(t.graph()) || (e.value = nf(t.graph(), rf)), e;
+  }
+  function jm(t) {
+    return Eg(t.nodes(), function(e) {
+      var n = t.node(e), i = t.parent(e), r = { v: e };
+      return Fg(n) || (r.value = n), Fg(i) || (r.parent = i), r;
+    });
+  }
+  function zm(t) {
+    return Eg(t.edges(), function(e) {
+      var n = t.edge(e), i = { v: e.v, w: e.w };
+      return Fg(e.name) || (i.name = e.name), Fg(n) || (i.value = n), i;
+    });
+  }
+  let Um;
+  const Wm = new Uint8Array(16);
+  function Hm() {
+    if (
+      !Um && (Um = "undefined" != typeof crypto && crypto.getRandomValues && crypto.getRandomValues.bind(crypto), !Um)
+    ) {
+      throw new Error(
+        "crypto.getRandomValues() not supported. See https://github.com/uuidjs/uuid#getrandomvalues-not-supported",
+      );
+    }
+    return Um(Wm);
+  }
+  const qm = [];
+  for (let t = 0; t < 256; ++t) qm.push((t + 256).toString(16).slice(1));
+  var Vm = { randomUUID: "undefined" != typeof crypto && crypto.randomUUID && crypto.randomUUID.bind(crypto) };
+  function Gm(t, e, n) {
+    if (Vm.randomUUID && !e && !t) return Vm.randomUUID();
+    const i = (t = t || {}).random || (t.rng || Hm)();
+    if (i[6] = 15 & i[6] | 64, i[8] = 63 & i[8] | 128, e) {
+      n = n || 0;
+      for (let t = 0; t < 16; ++t) e[n + t] = i[t];
+      return e;
+    }
+    return function(t, e = 0) {
+      return (qm[t[e + 0]] + qm[t[e + 1]] + qm[t[e + 2]] + qm[t[e + 3]] + "-" + qm[t[e + 4]] + qm[t[e + 5]] + "-"
+        + qm[t[e + 6]] + qm[t[e + 7]] + "-" + qm[t[e + 8]] + qm[t[e + 9]] + "-" + qm[t[e + 10]] + qm[t[e + 11]]
+        + qm[t[e + 12]] + qm[t[e + 13]] + qm[t[e + 14]] + qm[t[e + 15]]).toLowerCase();
+    }(i);
+  }
+  function Xm(t, e) {
+    e && t.attr("style", e);
+  }
+  function Zm(t, e) {
+    var n = t.append("foreignObject").attr("width", "100000"), i = n.append("xhtml:div");
+    i.attr("xmlns", "http://www.w3.org/1999/xhtml");
+    var r = e.label;
+    switch (typeof r) {
+      case "function":
+        i.insert(r);
+        break;
+      case "object":
+        i.insert(function() {
+          return r;
+        });
+        break;
+      default:
+        i.html(r);
+    }
+    Xm(i, e.labelStyle), i.style("display", "inline-block"), i.style("white-space", "nowrap");
+    var a = i.node().getBoundingClientRect();
+    return n.attr("width", a.width).attr("height", a.height), n;
+  }
+  var Qm = Object.defineProperty,
+    Km = (t, e, n) => (((t, e, n) => {
+      e in t ? Qm(t, e, { enumerable: !0, configurable: !0, writable: !0, value: n }) : t[e] = n;
+    })(t, "symbol" != typeof e ? e + "" : e, n),
+      n);
+  const Jm = { trace: 0, debug: 1, info: 2, warn: 3, error: 4, fatal: 5 },
+    tb = {
+      trace: (...t) => {},
+      debug: (...t) => {},
+      info: (...t) => {},
+      warn: (...t) => {},
+      error: (...t) => {},
+      fatal: (...t) => {},
+    },
+    eb = function(t = "fatal") {
+      let e = Jm.fatal;
+      "string" == typeof t ? (t = t.toLowerCase()) in Jm && (e = Jm[t]) : "number" == typeof t && (e = t),
+        tb.trace = () => {},
+        tb.debug = () => {},
+        tb.info = () => {},
+        tb.warn = () => {},
+        tb.error = () => {},
+        tb.fatal = () => {},
+        e <= Jm.fatal
+        && (tb.fatal = console.error
+          ? console.error.bind(console, nb("FATAL"), "color: orange")
+          : console.log.bind(console, "", nb("FATAL"))),
+        e <= Jm.error
+        && (tb.error = console.error
+          ? console.error.bind(console, nb("ERROR"), "color: orange")
+          : console.log.bind(console, "", nb("ERROR"))),
+        e <= Jm.warn
+        && (tb.warn = console.warn
+          ? console.warn.bind(console, nb("WARN"), "color: orange")
+          : console.log.bind(console, "", nb("WARN"))),
+        e <= Jm.info
+        && (tb.info = console.info
+          ? console.info.bind(console, nb("INFO"), "color: lightblue")
+          : console.log.bind(console, "", nb("INFO"))),
+        e <= Jm.debug
+        && (tb.debug = console.debug
+          ? console.debug.bind(console, nb("DEBUG"), "color: lightgreen")
+          : console.log.bind(console, "", nb("DEBUG"))),
+        e <= Jm.trace
+        && (tb.trace = console.debug
+          ? console.debug.bind(console, nb("TRACE"), "color: lightgreen")
+          : console.log.bind(console, "", nb("TRACE")));
+    },
+    nb = t => `%c${e().format("ss.SSS")} : ${t} : `,
+    ib = t => vl.sanitize(t),
+    rb = (t, e) => {
+      var n;
+      if (!1 !== (null == (n = e.flowchart) ? void 0 : n.htmlLabels)) {
+        const n = e.securityLevel;
+        "antiscript" === n || "strict" === n
+          ? t = ib(t)
+          : "loose" !== n
+            && (t = (t = (t = lb(t)).replace(/</g, "&lt;").replace(/>/g, "&gt;")).replace(/=/g, "&equals;"), t = ob(t));
+      }
+      return t;
+    },
+    ab = (t, e) =>
+      t
+        ? t = e.dompurifyConfig
+          ? vl.sanitize(rb(t, e), e.dompurifyConfig).toString()
+          : vl.sanitize(rb(t, e), { FORBID_TAGS: ["style"] }).toString()
+        : t,
+    sb = /<br\s*\/?>/gi,
+    ob = t => t.replace(/#br#/g, "<br/>"),
+    lb = t => t.replace(sb, "#br#"),
+    cb = t => !1 !== t && !["false", "null", "0"].includes(String(t).trim().toLowerCase()),
+    hb = function(t) {
+      let e = t;
+      return t.includes("~") ? (e = e.replace(/~([^~].*)/, "<$1"), e = e.replace(/~([^~]*)$/, ">$1"), hb(e)) : e;
+    },
+    ub = {
+      getRows: t => {
+        if (!t) return [""];
+        return lb(t).replace(/\\n/g, "#br#").split("#br#");
+      },
+      sanitizeText: ab,
+      sanitizeTextOrArray: (t, e) => "string" == typeof t ? ab(t, e) : t.flat().map(t => ab(t, e)),
+      hasBreaks: t => sb.test(t),
+      splitBreaks: t => t.split(sb),
+      lineBreakRegex: sb,
+      removeScript: ib,
+      getUrl: t => {
+        let e = "";
+        return t
+          && (e = window.location.protocol + "//" + window.location.host + window.location.pathname
+            + window.location.search,
+            e = e.replaceAll(/\(/g, "\\("),
+            e = e.replaceAll(/\)/g, "\\)")),
+          e;
+      },
+      evaluate: cb,
+    },
+    db = (t, e) => Gl(t, e ? { s: -40, l: 10 } : { s: -40, l: -10 }),
+    pb = "#ffffff",
+    fb = "#f2f2f2";
+  class gb {
+    constructor() {
+      this.background = "#f4f4f4",
+        this.darkMode = !1,
+        this.primaryColor = "#fff4dd",
+        this.noteBkgColor = "#fff5ad",
+        this.noteTextColor = "#333",
+        this.THEME_COLOR_LIMIT = 12,
+        this.fontFamily = "\"trebuchet ms\", verdana, arial, sans-serif",
+        this.fontSize = "16px";
+    }
+    updateColors() {
+      if (
+        this.primaryTextColor = this.primaryTextColor || (this.darkMode ? "#eee" : "#333"),
+          this.secondaryColor = this.secondaryColor || Gl(this.primaryColor, { h: -120 }),
+          this.tertiaryColor = this.tertiaryColor || Gl(this.primaryColor, { h: 180, l: 5 }),
+          this.primaryBorderColor = this.primaryBorderColor || db(this.primaryColor, this.darkMode),
+          this.secondaryBorderColor = this.secondaryBorderColor || db(this.secondaryColor, this.darkMode),
+          this.tertiaryBorderColor = this.tertiaryBorderColor || db(this.tertiaryColor, this.darkMode),
+          this.noteBorderColor = this.noteBorderColor || db(this.noteBkgColor, this.darkMode),
+          this.noteBkgColor = this.noteBkgColor || "#fff5ad",
+          this.noteTextColor = this.noteTextColor || "#333",
+          this.secondaryTextColor = this.secondaryTextColor || Zl(this.secondaryColor),
+          this.tertiaryTextColor = this.tertiaryTextColor || Zl(this.tertiaryColor),
+          this.lineColor = this.lineColor || Zl(this.background),
+          this.textColor = this.textColor || this.primaryTextColor,
+          this.nodeBkg = this.nodeBkg || this.primaryColor,
+          this.mainBkg = this.mainBkg || this.primaryColor,
+          this.nodeBorder = this.nodeBorder || this.primaryBorderColor,
+          this.clusterBkg = this.clusterBkg || this.tertiaryColor,
+          this.clusterBorder = this.clusterBorder || this.tertiaryBorderColor,
+          this.defaultLinkColor = this.defaultLinkColor || this.lineColor,
+          this.titleColor = this.titleColor || this.tertiaryTextColor,
+          this.edgeLabelBackground = this.edgeLabelBackground
+            || (this.darkMode ? Vl(this.secondaryColor, 30) : this.secondaryColor),
+          this.nodeTextColor = this.nodeTextColor || this.primaryTextColor,
+          this.actorBorder = this.actorBorder || this.primaryBorderColor,
+          this.actorBkg = this.actorBkg || this.mainBkg,
+          this.actorTextColor = this.actorTextColor || this.primaryTextColor,
+          this.actorLineColor = this.actorLineColor || "grey",
+          this.labelBoxBkgColor = this.labelBoxBkgColor || this.actorBkg,
+          this.signalColor = this.signalColor || this.textColor,
+          this.signalTextColor = this.signalTextColor || this.textColor,
+          this.labelBoxBorderColor = this.labelBoxBorderColor || this.actorBorder,
+          this.labelTextColor = this.labelTextColor || this.actorTextColor,
+          this.loopTextColor = this.loopTextColor || this.actorTextColor,
+          this.activationBorderColor = this.activationBorderColor || Vl(this.secondaryColor, 10),
+          this.activationBkgColor = this.activationBkgColor || this.secondaryColor,
+          this.sequenceNumberColor = this.sequenceNumberColor || Zl(this.lineColor),
+          this.sectionBkgColor = this.sectionBkgColor || this.tertiaryColor,
+          this.altSectionBkgColor = this.altSectionBkgColor || "white",
+          this.sectionBkgColor = this.sectionBkgColor || this.secondaryColor,
+          this.sectionBkgColor2 = this.sectionBkgColor2 || this.primaryColor,
+          this.excludeBkgColor = this.excludeBkgColor || "#eeeeee",
+          this.taskBorderColor = this.taskBorderColor || this.primaryBorderColor,
+          this.taskBkgColor = this.taskBkgColor || this.primaryColor,
+          this.activeTaskBorderColor = this.activeTaskBorderColor || this.primaryColor,
+          this.activeTaskBkgColor = this.activeTaskBkgColor || ql(this.primaryColor, 23),
+          this.gridColor = this.gridColor || "lightgrey",
+          this.doneTaskBkgColor = this.doneTaskBkgColor || "lightgrey",
+          this.doneTaskBorderColor = this.doneTaskBorderColor || "grey",
+          this.critBorderColor = this.critBorderColor || "#ff8888",
+          this.critBkgColor = this.critBkgColor || "red",
+          this.todayLineColor = this.todayLineColor || "red",
+          this.taskTextColor = this.taskTextColor || this.textColor,
+          this.taskTextOutsideColor = this.taskTextOutsideColor || this.textColor,
+          this.taskTextLightColor = this.taskTextLightColor || this.textColor,
+          this.taskTextColor = this.taskTextColor || this.primaryTextColor,
+          this.taskTextDarkColor = this.taskTextDarkColor || this.textColor,
+          this.taskTextClickableColor = this.taskTextClickableColor || "#003163",
+          this.personBorder = this.personBorder || this.primaryBorderColor,
+          this.personBkg = this.personBkg || this.mainBkg,
+          this.transitionColor = this.transitionColor || this.lineColor,
+          this.transitionLabelColor = this.transitionLabelColor || this.textColor,
+          this.stateLabelColor = this.stateLabelColor || this.stateBkg || this.primaryTextColor,
+          this.stateBkg = this.stateBkg || this.mainBkg,
+          this.labelBackgroundColor = this.labelBackgroundColor || this.stateBkg,
+          this.compositeBackground = this.compositeBackground || this.background || this.tertiaryColor,
+          this.altBackground = this.altBackground || this.tertiaryColor,
+          this.compositeTitleBackground = this.compositeTitleBackground || this.mainBkg,
+          this.compositeBorder = this.compositeBorder || this.nodeBorder,
+          this.innerEndBackground = this.nodeBorder,
+          this.errorBkgColor = this.errorBkgColor || this.tertiaryColor,
+          this.errorTextColor = this.errorTextColor || this.tertiaryTextColor,
+          this.transitionColor = this.transitionColor || this.lineColor,
+          this.specialStateColor = this.lineColor,
+          this.cScale0 = this.cScale0 || this.primaryColor,
+          this.cScale1 = this.cScale1 || this.secondaryColor,
+          this.cScale2 = this.cScale2 || this.tertiaryColor,
+          this.cScale3 = this.cScale3 || Gl(this.primaryColor, { h: 30 }),
+          this.cScale4 = this.cScale4 || Gl(this.primaryColor, { h: 60 }),
+          this.cScale5 = this.cScale5 || Gl(this.primaryColor, { h: 90 }),
+          this.cScale6 = this.cScale6 || Gl(this.primaryColor, { h: 120 }),
+          this.cScale7 = this.cScale7 || Gl(this.primaryColor, { h: 150 }),
+          this.cScale8 = this.cScale8 || Gl(this.primaryColor, { h: 210, l: 150 }),
+          this.cScale9 = this.cScale9 || Gl(this.primaryColor, { h: 270 }),
+          this.cScale10 = this.cScale10 || Gl(this.primaryColor, { h: 300 }),
+          this.cScale11 = this.cScale11 || Gl(this.primaryColor, { h: 330 }),
+          this.darkMode
+      ) for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) this["cScale" + t] = Vl(this["cScale" + t], 75);
+      else for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) this["cScale" + t] = Vl(this["cScale" + t], 25);
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScaleInv" + t] = this["cScaleInv" + t] || Zl(this["cScale" + t]);
+      }
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this.darkMode
+          ? this["cScalePeer" + t] = this["cScalePeer" + t] || ql(this["cScale" + t], 10)
+          : this["cScalePeer" + t] = this["cScalePeer" + t] || Vl(this["cScale" + t], 10);
+      }
+      this.scaleLabelColor = this.scaleLabelColor || this.labelTextColor;
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScaleLabel" + t] = this["cScaleLabel" + t] || this.scaleLabelColor;
+      }
+      this.classText = this.classText || this.textColor,
+        this.fillType0 = this.fillType0 || this.primaryColor,
+        this.fillType1 = this.fillType1 || this.secondaryColor,
+        this.fillType2 = this.fillType2 || Gl(this.primaryColor, { h: 64 }),
+        this.fillType3 = this.fillType3 || Gl(this.secondaryColor, { h: 64 }),
+        this.fillType4 = this.fillType4 || Gl(this.primaryColor, { h: -64 }),
+        this.fillType5 = this.fillType5 || Gl(this.secondaryColor, { h: -64 }),
+        this.fillType6 = this.fillType6 || Gl(this.primaryColor, { h: 128 }),
+        this.fillType7 = this.fillType7 || Gl(this.secondaryColor, { h: 128 }),
+        this.pie1 = this.pie1 || this.primaryColor,
+        this.pie2 = this.pie2 || this.secondaryColor,
+        this.pie3 = this.pie3 || this.tertiaryColor,
+        this.pie4 = this.pie4 || Gl(this.primaryColor, { l: -10 }),
+        this.pie5 = this.pie5 || Gl(this.secondaryColor, { l: -10 }),
+        this.pie6 = this.pie6 || Gl(this.tertiaryColor, { l: -10 }),
+        this.pie7 = this.pie7 || Gl(this.primaryColor, { h: 60, l: -10 }),
+        this.pie8 = this.pie8 || Gl(this.primaryColor, { h: -60, l: -10 }),
+        this.pie9 = this.pie9 || Gl(this.primaryColor, { h: 120, l: 0 }),
+        this.pie10 = this.pie10 || Gl(this.primaryColor, { h: 60, l: -20 }),
+        this.pie11 = this.pie11 || Gl(this.primaryColor, { h: -60, l: -20 }),
+        this.pie12 = this.pie12 || Gl(this.primaryColor, { h: 120, l: -10 }),
+        this.pieTitleTextSize = this.pieTitleTextSize || "25px",
+        this.pieTitleTextColor = this.pieTitleTextColor || this.taskTextDarkColor,
+        this.pieSectionTextSize = this.pieSectionTextSize || "17px",
+        this.pieSectionTextColor = this.pieSectionTextColor || this.textColor,
+        this.pieLegendTextSize = this.pieLegendTextSize || "17px",
+        this.pieLegendTextColor = this.pieLegendTextColor || this.taskTextDarkColor,
+        this.pieStrokeColor = this.pieStrokeColor || "black",
+        this.pieStrokeWidth = this.pieStrokeWidth || "2px",
+        this.pieOpacity = this.pieOpacity || "0.7",
+        this.requirementBackground = this.requirementBackground || this.primaryColor,
+        this.requirementBorderColor = this.requirementBorderColor || this.primaryBorderColor,
+        this.requirementBorderSize = this.requirementBorderSize || this.primaryBorderColor,
+        this.requirementTextColor = this.requirementTextColor || this.primaryTextColor,
+        this.relationColor = this.relationColor || this.lineColor,
+        this.relationLabelBackground = this.relationLabelBackground
+          || (this.darkMode ? Vl(this.secondaryColor, 30) : this.secondaryColor),
+        this.relationLabelColor = this.relationLabelColor || this.actorTextColor,
+        this.git0 = this.git0 || this.primaryColor,
+        this.git1 = this.git1 || this.secondaryColor,
+        this.git2 = this.git2 || this.tertiaryColor,
+        this.git3 = this.git3 || Gl(this.primaryColor, { h: -30 }),
+        this.git4 = this.git4 || Gl(this.primaryColor, { h: -60 }),
+        this.git5 = this.git5 || Gl(this.primaryColor, { h: -90 }),
+        this.git6 = this.git6 || Gl(this.primaryColor, { h: 60 }),
+        this.git7 = this.git7 || Gl(this.primaryColor, { h: 120 }),
+        this.darkMode
+          ? (this.git0 = ql(this.git0, 25),
+            this.git1 = ql(this.git1, 25),
+            this.git2 = ql(this.git2, 25),
+            this.git3 = ql(this.git3, 25),
+            this.git4 = ql(this.git4, 25),
+            this.git5 = ql(this.git5, 25),
+            this.git6 = ql(this.git6, 25),
+            this.git7 = ql(this.git7, 25))
+          : (this.git0 = Vl(this.git0, 25),
+            this.git1 = Vl(this.git1, 25),
+            this.git2 = Vl(this.git2, 25),
+            this.git3 = Vl(this.git3, 25),
+            this.git4 = Vl(this.git4, 25),
+            this.git5 = Vl(this.git5, 25),
+            this.git6 = Vl(this.git6, 25),
+            this.git7 = Vl(this.git7, 25)),
+        this.gitInv0 = this.gitInv0 || Zl(this.git0),
+        this.gitInv1 = this.gitInv1 || Zl(this.git1),
+        this.gitInv2 = this.gitInv2 || Zl(this.git2),
+        this.gitInv3 = this.gitInv3 || Zl(this.git3),
+        this.gitInv4 = this.gitInv4 || Zl(this.git4),
+        this.gitInv5 = this.gitInv5 || Zl(this.git5),
+        this.gitInv6 = this.gitInv6 || Zl(this.git6),
+        this.gitInv7 = this.gitInv7 || Zl(this.git7),
+        this.branchLabelColor = this.branchLabelColor || (this.darkMode ? "black" : this.labelTextColor),
+        this.gitBranchLabel0 = this.gitBranchLabel0 || this.branchLabelColor,
+        this.gitBranchLabel1 = this.gitBranchLabel1 || this.branchLabelColor,
+        this.gitBranchLabel2 = this.gitBranchLabel2 || this.branchLabelColor,
+        this.gitBranchLabel3 = this.gitBranchLabel3 || this.branchLabelColor,
+        this.gitBranchLabel4 = this.gitBranchLabel4 || this.branchLabelColor,
+        this.gitBranchLabel5 = this.gitBranchLabel5 || this.branchLabelColor,
+        this.gitBranchLabel6 = this.gitBranchLabel6 || this.branchLabelColor,
+        this.gitBranchLabel7 = this.gitBranchLabel7 || this.branchLabelColor,
+        this.tagLabelColor = this.tagLabelColor || this.primaryTextColor,
+        this.tagLabelBackground = this.tagLabelBackground || this.primaryColor,
+        this.tagLabelBorder = this.tagBorder || this.primaryBorderColor,
+        this.tagLabelFontSize = this.tagLabelFontSize || "10px",
+        this.commitLabelColor = this.commitLabelColor || this.secondaryTextColor,
+        this.commitLabelBackground = this.commitLabelBackground || this.secondaryColor,
+        this.commitLabelFontSize = this.commitLabelFontSize || "10px",
+        this.attributeBackgroundColorOdd = this.attributeBackgroundColorOdd || pb,
+        this.attributeBackgroundColorEven = this.attributeBackgroundColorEven || fb;
+    }
+    calculate(t) {
+      if ("object" != typeof t) return void this.updateColors();
+      const e = Object.keys(t);
+      e.forEach(e => {
+        this[e] = t[e];
+      }),
+        this.updateColors(),
+        e.forEach(e => {
+          this[e] = t[e];
+        });
+    }
+  }
+  class yb {
+    constructor() {
+      this.background = "#333",
+        this.primaryColor = "#1f2020",
+        this.secondaryColor = ql(this.primaryColor, 16),
+        this.tertiaryColor = Gl(this.primaryColor, { h: -160 }),
+        this.primaryBorderColor = Zl(this.background),
+        this.secondaryBorderColor = db(this.secondaryColor, this.darkMode),
+        this.tertiaryBorderColor = db(this.tertiaryColor, this.darkMode),
+        this.primaryTextColor = Zl(this.primaryColor),
+        this.secondaryTextColor = Zl(this.secondaryColor),
+        this.tertiaryTextColor = Zl(this.tertiaryColor),
+        this.lineColor = Zl(this.background),
+        this.textColor = Zl(this.background),
+        this.mainBkg = "#1f2020",
+        this.secondBkg = "calculated",
+        this.mainContrastColor = "lightgrey",
+        this.darkTextColor = ql(Zl("#323D47"), 10),
+        this.lineColor = "calculated",
+        this.border1 = "#81B1DB",
+        this.border2 = Wl(255, 255, 255, .25),
+        this.arrowheadColor = "calculated",
+        this.fontFamily = "\"trebuchet ms\", verdana, arial, sans-serif",
+        this.fontSize = "16px",
+        this.labelBackground = "#181818",
+        this.textColor = "#ccc",
+        this.THEME_COLOR_LIMIT = 12,
+        this.nodeBkg = "calculated",
+        this.nodeBorder = "calculated",
+        this.clusterBkg = "calculated",
+        this.clusterBorder = "calculated",
+        this.defaultLinkColor = "calculated",
+        this.titleColor = "#F9FFFE",
+        this.edgeLabelBackground = "calculated",
+        this.actorBorder = "calculated",
+        this.actorBkg = "calculated",
+        this.actorTextColor = "calculated",
+        this.actorLineColor = "calculated",
+        this.signalColor = "calculated",
+        this.signalTextColor = "calculated",
+        this.labelBoxBkgColor = "calculated",
+        this.labelBoxBorderColor = "calculated",
+        this.labelTextColor = "calculated",
+        this.loopTextColor = "calculated",
+        this.noteBorderColor = "calculated",
+        this.noteBkgColor = "#fff5ad",
+        this.noteTextColor = "calculated",
+        this.activationBorderColor = "calculated",
+        this.activationBkgColor = "calculated",
+        this.sequenceNumberColor = "black",
+        this.sectionBkgColor = Vl("#EAE8D9", 30),
+        this.altSectionBkgColor = "calculated",
+        this.sectionBkgColor2 = "#EAE8D9",
+        this.taskBorderColor = Wl(255, 255, 255, 70),
+        this.taskBkgColor = "calculated",
+        this.taskTextColor = "calculated",
+        this.taskTextLightColor = "calculated",
+        this.taskTextOutsideColor = "calculated",
+        this.taskTextClickableColor = "#003163",
+        this.activeTaskBorderColor = Wl(255, 255, 255, 50),
+        this.activeTaskBkgColor = "#81B1DB",
+        this.gridColor = "calculated",
+        this.doneTaskBkgColor = "calculated",
+        this.doneTaskBorderColor = "grey",
+        this.critBorderColor = "#E83737",
+        this.critBkgColor = "#E83737",
+        this.taskTextDarkColor = "calculated",
+        this.todayLineColor = "#DB5757",
+        this.personBorder = "calculated",
+        this.personBkg = "calculated",
+        this.labelColor = "calculated",
+        this.errorBkgColor = "#a44141",
+        this.errorTextColor = "#ddd";
+    }
+    updateColors() {
+      this.secondBkg = ql(this.mainBkg, 16),
+        this.lineColor = this.mainContrastColor,
+        this.arrowheadColor = this.mainContrastColor,
+        this.nodeBkg = this.mainBkg,
+        this.nodeBorder = this.border1,
+        this.clusterBkg = this.secondBkg,
+        this.clusterBorder = this.border2,
+        this.defaultLinkColor = this.lineColor,
+        this.edgeLabelBackground = ql(this.labelBackground, 25),
+        this.actorBorder = this.border1,
+        this.actorBkg = this.mainBkg,
+        this.actorTextColor = this.mainContrastColor,
+        this.actorLineColor = this.mainContrastColor,
+        this.signalColor = this.mainContrastColor,
+        this.signalTextColor = this.mainContrastColor,
+        this.labelBoxBkgColor = this.actorBkg,
+        this.labelBoxBorderColor = this.actorBorder,
+        this.labelTextColor = this.mainContrastColor,
+        this.loopTextColor = this.mainContrastColor,
+        this.noteBorderColor = this.secondaryBorderColor,
+        this.noteBkgColor = this.secondBkg,
+        this.noteTextColor = this.secondaryTextColor,
+        this.activationBorderColor = this.border1,
+        this.activationBkgColor = this.secondBkg,
+        this.altSectionBkgColor = this.background,
+        this.taskBkgColor = ql(this.mainBkg, 23),
+        this.taskTextColor = this.darkTextColor,
+        this.taskTextLightColor = this.mainContrastColor,
+        this.taskTextOutsideColor = this.taskTextLightColor,
+        this.gridColor = this.mainContrastColor,
+        this.doneTaskBkgColor = this.mainContrastColor,
+        this.taskTextDarkColor = this.darkTextColor,
+        this.transitionColor = this.transitionColor || this.lineColor,
+        this.transitionLabelColor = this.transitionLabelColor || this.textColor,
+        this.stateLabelColor = this.stateLabelColor || this.stateBkg || this.primaryTextColor,
+        this.stateBkg = this.stateBkg || this.mainBkg,
+        this.labelBackgroundColor = this.labelBackgroundColor || this.stateBkg,
+        this.compositeBackground = this.compositeBackground || this.background || this.tertiaryColor,
+        this.altBackground = this.altBackground || "#555",
+        this.compositeTitleBackground = this.compositeTitleBackground || this.mainBkg,
+        this.compositeBorder = this.compositeBorder || this.nodeBorder,
+        this.innerEndBackground = this.primaryBorderColor,
+        this.specialStateColor = "#f4f4f4",
+        this.errorBkgColor = this.errorBkgColor || this.tertiaryColor,
+        this.errorTextColor = this.errorTextColor || this.tertiaryTextColor,
+        this.fillType0 = this.primaryColor,
+        this.fillType1 = this.secondaryColor,
+        this.fillType2 = Gl(this.primaryColor, { h: 64 }),
+        this.fillType3 = Gl(this.secondaryColor, { h: 64 }),
+        this.fillType4 = Gl(this.primaryColor, { h: -64 }),
+        this.fillType5 = Gl(this.secondaryColor, { h: -64 }),
+        this.fillType6 = Gl(this.primaryColor, { h: 128 }),
+        this.fillType7 = Gl(this.secondaryColor, { h: 128 }),
+        this.cScale1 = this.cScale1 || "#0b0000",
+        this.cScale2 = this.cScale2 || "#4d1037",
+        this.cScale3 = this.cScale3 || "#3f5258",
+        this.cScale4 = this.cScale4 || "#4f2f1b",
+        this.cScale5 = this.cScale5 || "#6e0a0a",
+        this.cScale6 = this.cScale6 || "#3b0048",
+        this.cScale7 = this.cScale7 || "#995a01",
+        this.cScale8 = this.cScale8 || "#154706",
+        this.cScale9 = this.cScale9 || "#161722",
+        this.cScale10 = this.cScale10 || "#00296f",
+        this.cScale11 = this.cScale11 || "#01629c",
+        this.cScale12 = this.cScale12 || "#010029",
+        this.cScale0 = this.cScale0 || this.primaryColor,
+        this.cScale1 = this.cScale1 || this.secondaryColor,
+        this.cScale2 = this.cScale2 || this.tertiaryColor,
+        this.cScale3 = this.cScale3 || Gl(this.primaryColor, { h: 30 }),
+        this.cScale4 = this.cScale4 || Gl(this.primaryColor, { h: 60 }),
+        this.cScale5 = this.cScale5 || Gl(this.primaryColor, { h: 90 }),
+        this.cScale6 = this.cScale6 || Gl(this.primaryColor, { h: 120 }),
+        this.cScale7 = this.cScale7 || Gl(this.primaryColor, { h: 150 }),
+        this.cScale8 = this.cScale8 || Gl(this.primaryColor, { h: 210 }),
+        this.cScale9 = this.cScale9 || Gl(this.primaryColor, { h: 270 }),
+        this.cScale10 = this.cScale10 || Gl(this.primaryColor, { h: 300 }),
+        this.cScale11 = this.cScale11 || Gl(this.primaryColor, { h: 330 });
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScaleInv" + t] = this["cScaleInv" + t] || Zl(this["cScale" + t]);
+      }
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScalePeer" + t] = this["cScalePeer" + t] || ql(this["cScale" + t], 10);
+      }
+      this.scaleLabelColor = this.scaleLabelColor || (this.darkMode ? "black" : this.labelTextColor);
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScaleLabel" + t] = this["cScaleLabel" + t] || this.scaleLabelColor;
+      }
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) this["pie" + t] = this["cScale" + t];
+      this.pieTitleTextSize = this.pieTitleTextSize || "25px",
+        this.pieTitleTextColor = this.pieTitleTextColor || this.taskTextDarkColor,
+        this.pieSectionTextSize = this.pieSectionTextSize || "17px",
+        this.pieSectionTextColor = this.pieSectionTextColor || this.textColor,
+        this.pieLegendTextSize = this.pieLegendTextSize || "17px",
+        this.pieLegendTextColor = this.pieLegendTextColor || this.taskTextDarkColor,
+        this.pieStrokeColor = this.pieStrokeColor || "black",
+        this.pieStrokeWidth = this.pieStrokeWidth || "2px",
+        this.pieOpacity = this.pieOpacity || "0.7",
+        this.classText = this.primaryTextColor,
+        this.requirementBackground = this.requirementBackground || this.primaryColor,
+        this.requirementBorderColor = this.requirementBorderColor || this.primaryBorderColor,
+        this.requirementBorderSize = this.requirementBorderSize || this.primaryBorderColor,
+        this.requirementTextColor = this.requirementTextColor || this.primaryTextColor,
+        this.relationColor = this.relationColor || this.lineColor,
+        this.relationLabelBackground = this.relationLabelBackground
+          || (this.darkMode ? Vl(this.secondaryColor, 30) : this.secondaryColor),
+        this.relationLabelColor = this.relationLabelColor || this.actorTextColor,
+        this.git0 = ql(this.secondaryColor, 20),
+        this.git1 = ql(this.pie2 || this.secondaryColor, 20),
+        this.git2 = ql(this.pie3 || this.tertiaryColor, 20),
+        this.git3 = ql(this.pie4 || Gl(this.primaryColor, { h: -30 }), 20),
+        this.git4 = ql(this.pie5 || Gl(this.primaryColor, { h: -60 }), 20),
+        this.git5 = ql(this.pie6 || Gl(this.primaryColor, { h: -90 }), 10),
+        this.git6 = ql(this.pie7 || Gl(this.primaryColor, { h: 60 }), 10),
+        this.git7 = ql(this.pie8 || Gl(this.primaryColor, { h: 120 }), 20),
+        this.gitInv0 = this.gitInv0 || Zl(this.git0),
+        this.gitInv1 = this.gitInv1 || Zl(this.git1),
+        this.gitInv2 = this.gitInv2 || Zl(this.git2),
+        this.gitInv3 = this.gitInv3 || Zl(this.git3),
+        this.gitInv4 = this.gitInv4 || Zl(this.git4),
+        this.gitInv5 = this.gitInv5 || Zl(this.git5),
+        this.gitInv6 = this.gitInv6 || Zl(this.git6),
+        this.gitInv7 = this.gitInv7 || Zl(this.git7),
+        this.tagLabelColor = this.tagLabelColor || this.primaryTextColor,
+        this.tagLabelBackground = this.tagLabelBackground || this.primaryColor,
+        this.tagLabelBorder = this.tagBorder || this.primaryBorderColor,
+        this.tagLabelFontSize = this.tagLabelFontSize || "10px",
+        this.commitLabelColor = this.commitLabelColor || this.secondaryTextColor,
+        this.commitLabelBackground = this.commitLabelBackground || this.secondaryColor,
+        this.commitLabelFontSize = this.commitLabelFontSize || "10px",
+        this.attributeBackgroundColorOdd = this.attributeBackgroundColorOdd || ql(this.background, 12),
+        this.attributeBackgroundColorEven = this.attributeBackgroundColorEven || ql(this.background, 2);
+    }
+    calculate(t) {
+      if ("object" != typeof t) return void this.updateColors();
+      const e = Object.keys(t);
+      e.forEach(e => {
+        this[e] = t[e];
+      }),
+        this.updateColors(),
+        e.forEach(e => {
+          this[e] = t[e];
+        });
+    }
+  }
+  class mb {
+    constructor() {
+      this.background = "#f4f4f4",
+        this.primaryColor = "#ECECFF",
+        this.secondaryColor = Gl(this.primaryColor, { h: 120 }),
+        this.secondaryColor = "#ffffde",
+        this.tertiaryColor = Gl(this.primaryColor, { h: -160 }),
+        this.primaryBorderColor = db(this.primaryColor, this.darkMode),
+        this.secondaryBorderColor = db(this.secondaryColor, this.darkMode),
+        this.tertiaryBorderColor = db(this.tertiaryColor, this.darkMode),
+        this.primaryTextColor = Zl(this.primaryColor),
+        this.secondaryTextColor = Zl(this.secondaryColor),
+        this.tertiaryTextColor = Zl(this.tertiaryColor),
+        this.lineColor = Zl(this.background),
+        this.textColor = Zl(this.background),
+        this.background = "white",
+        this.mainBkg = "#ECECFF",
+        this.secondBkg = "#ffffde",
+        this.lineColor = "#333333",
+        this.border1 = "#9370DB",
+        this.border2 = "#aaaa33",
+        this.arrowheadColor = "#333333",
+        this.fontFamily = "\"trebuchet ms\", verdana, arial, sans-serif",
+        this.fontSize = "16px",
+        this.labelBackground = "#e8e8e8",
+        this.textColor = "#333",
+        this.THEME_COLOR_LIMIT = 12,
+        this.nodeBkg = "calculated",
+        this.nodeBorder = "calculated",
+        this.clusterBkg = "calculated",
+        this.clusterBorder = "calculated",
+        this.defaultLinkColor = "calculated",
+        this.titleColor = "calculated",
+        this.edgeLabelBackground = "calculated",
+        this.actorBorder = "calculated",
+        this.actorBkg = "calculated",
+        this.actorTextColor = "black",
+        this.actorLineColor = "grey",
+        this.signalColor = "calculated",
+        this.signalTextColor = "calculated",
+        this.labelBoxBkgColor = "calculated",
+        this.labelBoxBorderColor = "calculated",
+        this.labelTextColor = "calculated",
+        this.loopTextColor = "calculated",
+        this.noteBorderColor = "calculated",
+        this.noteBkgColor = "#fff5ad",
+        this.noteTextColor = "calculated",
+        this.activationBorderColor = "#666",
+        this.activationBkgColor = "#f4f4f4",
+        this.sequenceNumberColor = "white",
+        this.sectionBkgColor = "calculated",
+        this.altSectionBkgColor = "calculated",
+        this.sectionBkgColor2 = "calculated",
+        this.excludeBkgColor = "#eeeeee",
+        this.taskBorderColor = "calculated",
+        this.taskBkgColor = "calculated",
+        this.taskTextLightColor = "calculated",
+        this.taskTextColor = this.taskTextLightColor,
+        this.taskTextDarkColor = "calculated",
+        this.taskTextOutsideColor = this.taskTextDarkColor,
+        this.taskTextClickableColor = "calculated",
+        this.activeTaskBorderColor = "calculated",
+        this.activeTaskBkgColor = "calculated",
+        this.gridColor = "calculated",
+        this.doneTaskBkgColor = "calculated",
+        this.doneTaskBorderColor = "calculated",
+        this.critBorderColor = "calculated",
+        this.critBkgColor = "calculated",
+        this.todayLineColor = "calculated",
+        this.sectionBkgColor = Wl(102, 102, 255, .49),
+        this.altSectionBkgColor = "white",
+        this.sectionBkgColor2 = "#fff400",
+        this.taskBorderColor = "#534fbc",
+        this.taskBkgColor = "#8a90dd",
+        this.taskTextLightColor = "white",
+        this.taskTextColor = "calculated",
+        this.taskTextDarkColor = "black",
+        this.taskTextOutsideColor = "calculated",
+        this.taskTextClickableColor = "#003163",
+        this.activeTaskBorderColor = "#534fbc",
+        this.activeTaskBkgColor = "#bfc7ff",
+        this.gridColor = "lightgrey",
+        this.doneTaskBkgColor = "lightgrey",
+        this.doneTaskBorderColor = "grey",
+        this.critBorderColor = "#ff8888",
+        this.critBkgColor = "red",
+        this.todayLineColor = "red",
+        this.personBorder = "calculated",
+        this.personBkg = "calculated",
+        this.labelColor = "black",
+        this.errorBkgColor = "#552222",
+        this.errorTextColor = "#552222",
+        this.updateColors();
+    }
+    updateColors() {
+      this.cScale0 = this.cScale0 || this.primaryColor,
+        this.cScale1 = this.cScale1 || this.secondaryColor,
+        this.cScale2 = this.cScale2 || this.tertiaryColor,
+        this.cScale3 = this.cScale3 || Gl(this.primaryColor, { h: 30 }),
+        this.cScale4 = this.cScale4 || Gl(this.primaryColor, { h: 60 }),
+        this.cScale5 = this.cScale5 || Gl(this.primaryColor, { h: 90 }),
+        this.cScale6 = this.cScale6 || Gl(this.primaryColor, { h: 120 }),
+        this.cScale7 = this.cScale7 || Gl(this.primaryColor, { h: 150 }),
+        this.cScale8 = this.cScale8 || Gl(this.primaryColor, { h: 210 }),
+        this.cScale9 = this.cScale9 || Gl(this.primaryColor, { h: 270 }),
+        this.cScale10 = this.cScale10 || Gl(this.primaryColor, { h: 300 }),
+        this.cScale11 = this.cScale11 || Gl(this.primaryColor, { h: 330 }),
+        this.cScalePeer1 = this.cScalePeer1 || Vl(this.secondaryColor, 45),
+        this.cScalePeer2 = this.cScalePeer2 || Vl(this.tertiaryColor, 40);
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScale" + t] = Vl(this["cScale" + t], 10),
+          this["cScalePeer" + t] = this["cScalePeer" + t] || Vl(this["cScale" + t], 25);
+      }
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScaleInv" + t] = this["cScaleInv" + t] || Gl(this["cScale" + t], { h: 180 });
+      }
+      if (
+        this.scaleLabelColor = "calculated" !== this.scaleLabelColor && this.scaleLabelColor
+          ? this.scaleLabelColor
+          : this.labelTextColor, "calculated" !== this.labelTextColor
+      ) {
+        this.cScaleLabel0 = this.cScaleLabel0 || Zl(this.labelTextColor),
+          this.cScaleLabel3 = this.cScaleLabel3 || Zl(this.labelTextColor);
+        for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+          this["cScaleLabel" + t] = this["cScaleLabel" + t] || this.labelTextColor;
+        }
+      }
+      this.nodeBkg = this.mainBkg,
+        this.nodeBorder = this.border1,
+        this.clusterBkg = this.secondBkg,
+        this.clusterBorder = this.border2,
+        this.defaultLinkColor = this.lineColor,
+        this.titleColor = this.textColor,
+        this.edgeLabelBackground = this.labelBackground,
+        this.actorBorder = ql(this.border1, 23),
+        this.actorBkg = this.mainBkg,
+        this.labelBoxBkgColor = this.actorBkg,
+        this.signalColor = this.textColor,
+        this.signalTextColor = this.textColor,
+        this.labelBoxBorderColor = this.actorBorder,
+        this.labelTextColor = this.actorTextColor,
+        this.loopTextColor = this.actorTextColor,
+        this.noteBorderColor = this.border2,
+        this.noteTextColor = this.actorTextColor,
+        this.taskTextColor = this.taskTextLightColor,
+        this.taskTextOutsideColor = this.taskTextDarkColor,
+        this.transitionColor = this.transitionColor || this.lineColor,
+        this.transitionLabelColor = this.transitionLabelColor || this.textColor,
+        this.stateLabelColor = this.stateLabelColor || this.stateBkg || this.primaryTextColor,
+        this.stateBkg = this.stateBkg || this.mainBkg,
+        this.labelBackgroundColor = this.labelBackgroundColor || this.stateBkg,
+        this.compositeBackground = this.compositeBackground || this.background || this.tertiaryColor,
+        this.altBackground = this.altBackground || "#f0f0f0",
+        this.compositeTitleBackground = this.compositeTitleBackground || this.mainBkg,
+        this.compositeBorder = this.compositeBorder || this.nodeBorder,
+        this.innerEndBackground = this.nodeBorder,
+        this.specialStateColor = this.lineColor,
+        this.errorBkgColor = this.errorBkgColor || this.tertiaryColor,
+        this.errorTextColor = this.errorTextColor || this.tertiaryTextColor,
+        this.transitionColor = this.transitionColor || this.lineColor,
+        this.classText = this.primaryTextColor,
+        this.fillType0 = this.primaryColor,
+        this.fillType1 = this.secondaryColor,
+        this.fillType2 = Gl(this.primaryColor, { h: 64 }),
+        this.fillType3 = Gl(this.secondaryColor, { h: 64 }),
+        this.fillType4 = Gl(this.primaryColor, { h: -64 }),
+        this.fillType5 = Gl(this.secondaryColor, { h: -64 }),
+        this.fillType6 = Gl(this.primaryColor, { h: 128 }),
+        this.fillType7 = Gl(this.secondaryColor, { h: 128 }),
+        this.pie1 = this.pie1 || this.primaryColor,
+        this.pie2 = this.pie2 || this.secondaryColor,
+        this.pie3 = this.pie3 || Gl(this.tertiaryColor, { l: -40 }),
+        this.pie4 = this.pie4 || Gl(this.primaryColor, { l: -10 }),
+        this.pie5 = this.pie5 || Gl(this.secondaryColor, { l: -30 }),
+        this.pie6 = this.pie6 || Gl(this.tertiaryColor, { l: -20 }),
+        this.pie7 = this.pie7 || Gl(this.primaryColor, { h: 60, l: -20 }),
+        this.pie8 = this.pie8 || Gl(this.primaryColor, { h: -60, l: -40 }),
+        this.pie9 = this.pie9 || Gl(this.primaryColor, { h: 120, l: -40 }),
+        this.pie10 = this.pie10 || Gl(this.primaryColor, { h: 60, l: -40 }),
+        this.pie11 = this.pie11 || Gl(this.primaryColor, { h: -90, l: -40 }),
+        this.pie12 = this.pie12 || Gl(this.primaryColor, { h: 120, l: -30 }),
+        this.pieTitleTextSize = this.pieTitleTextSize || "25px",
+        this.pieTitleTextColor = this.pieTitleTextColor || this.taskTextDarkColor,
+        this.pieSectionTextSize = this.pieSectionTextSize || "17px",
+        this.pieSectionTextColor = this.pieSectionTextColor || this.textColor,
+        this.pieLegendTextSize = this.pieLegendTextSize || "17px",
+        this.pieLegendTextColor = this.pieLegendTextColor || this.taskTextDarkColor,
+        this.pieStrokeColor = this.pieStrokeColor || "black",
+        this.pieStrokeWidth = this.pieStrokeWidth || "2px",
+        this.pieOpacity = this.pieOpacity || "0.7",
+        this.requirementBackground = this.requirementBackground || this.primaryColor,
+        this.requirementBorderColor = this.requirementBorderColor || this.primaryBorderColor,
+        this.requirementBorderSize = this.requirementBorderSize || this.primaryBorderColor,
+        this.requirementTextColor = this.requirementTextColor || this.primaryTextColor,
+        this.relationColor = this.relationColor || this.lineColor,
+        this.relationLabelBackground = this.relationLabelBackground || this.labelBackground,
+        this.relationLabelColor = this.relationLabelColor || this.actorTextColor,
+        this.git0 = this.git0 || this.primaryColor,
+        this.git1 = this.git1 || this.secondaryColor,
+        this.git2 = this.git2 || this.tertiaryColor,
+        this.git3 = this.git3 || Gl(this.primaryColor, { h: -30 }),
+        this.git4 = this.git4 || Gl(this.primaryColor, { h: -60 }),
+        this.git5 = this.git5 || Gl(this.primaryColor, { h: -90 }),
+        this.git6 = this.git6 || Gl(this.primaryColor, { h: 60 }),
+        this.git7 = this.git7 || Gl(this.primaryColor, { h: 120 }),
+        this.darkMode
+          ? (this.git0 = ql(this.git0, 25),
+            this.git1 = ql(this.git1, 25),
+            this.git2 = ql(this.git2, 25),
+            this.git3 = ql(this.git3, 25),
+            this.git4 = ql(this.git4, 25),
+            this.git5 = ql(this.git5, 25),
+            this.git6 = ql(this.git6, 25),
+            this.git7 = ql(this.git7, 25))
+          : (this.git0 = Vl(this.git0, 25),
+            this.git1 = Vl(this.git1, 25),
+            this.git2 = Vl(this.git2, 25),
+            this.git3 = Vl(this.git3, 25),
+            this.git4 = Vl(this.git4, 25),
+            this.git5 = Vl(this.git5, 25),
+            this.git6 = Vl(this.git6, 25),
+            this.git7 = Vl(this.git7, 25)),
+        this.gitInv0 = this.gitInv0 || Vl(Zl(this.git0), 25),
+        this.gitInv1 = this.gitInv1 || Zl(this.git1),
+        this.gitInv2 = this.gitInv2 || Zl(this.git2),
+        this.gitInv3 = this.gitInv3 || Zl(this.git3),
+        this.gitInv4 = this.gitInv4 || Zl(this.git4),
+        this.gitInv5 = this.gitInv5 || Zl(this.git5),
+        this.gitInv6 = this.gitInv6 || Zl(this.git6),
+        this.gitInv7 = this.gitInv7 || Zl(this.git7),
+        this.gitBranchLabel0 = this.gitBranchLabel0 || Zl(this.labelTextColor),
+        this.gitBranchLabel1 = this.gitBranchLabel1 || this.labelTextColor,
+        this.gitBranchLabel2 = this.gitBranchLabel2 || this.labelTextColor,
+        this.gitBranchLabel3 = this.gitBranchLabel3 || Zl(this.labelTextColor),
+        this.gitBranchLabel4 = this.gitBranchLabel4 || this.labelTextColor,
+        this.gitBranchLabel5 = this.gitBranchLabel5 || this.labelTextColor,
+        this.gitBranchLabel6 = this.gitBranchLabel6 || this.labelTextColor,
+        this.gitBranchLabel7 = this.gitBranchLabel7 || this.labelTextColor,
+        this.tagLabelColor = this.tagLabelColor || this.primaryTextColor,
+        this.tagLabelBackground = this.tagLabelBackground || this.primaryColor,
+        this.tagLabelBorder = this.tagBorder || this.primaryBorderColor,
+        this.tagLabelFontSize = this.tagLabelFontSize || "10px",
+        this.commitLabelColor = this.commitLabelColor || this.secondaryTextColor,
+        this.commitLabelBackground = this.commitLabelBackground || this.secondaryColor,
+        this.commitLabelFontSize = this.commitLabelFontSize || "10px",
+        this.attributeBackgroundColorOdd = this.attributeBackgroundColorOdd || pb,
+        this.attributeBackgroundColorEven = this.attributeBackgroundColorEven || fb;
+    }
+    calculate(t) {
+      if ("object" != typeof t) return void this.updateColors();
+      const e = Object.keys(t);
+      e.forEach(e => {
+        this[e] = t[e];
+      }),
+        this.updateColors(),
+        e.forEach(e => {
+          this[e] = t[e];
+        });
+    }
+  }
+  class bb {
+    constructor() {
+      this.background = "#f4f4f4",
+        this.primaryColor = "#cde498",
+        this.secondaryColor = "#cdffb2",
+        this.background = "white",
+        this.mainBkg = "#cde498",
+        this.secondBkg = "#cdffb2",
+        this.lineColor = "green",
+        this.border1 = "#13540c",
+        this.border2 = "#6eaa49",
+        this.arrowheadColor = "green",
+        this.fontFamily = "\"trebuchet ms\", verdana, arial, sans-serif",
+        this.fontSize = "16px",
+        this.tertiaryColor = ql("#cde498", 10),
+        this.primaryBorderColor = db(this.primaryColor, this.darkMode),
+        this.secondaryBorderColor = db(this.secondaryColor, this.darkMode),
+        this.tertiaryBorderColor = db(this.tertiaryColor, this.darkMode),
+        this.primaryTextColor = Zl(this.primaryColor),
+        this.secondaryTextColor = Zl(this.secondaryColor),
+        this.tertiaryTextColor = Zl(this.primaryColor),
+        this.lineColor = Zl(this.background),
+        this.textColor = Zl(this.background),
+        this.THEME_COLOR_LIMIT = 12,
+        this.nodeBkg = "calculated",
+        this.nodeBorder = "calculated",
+        this.clusterBkg = "calculated",
+        this.clusterBorder = "calculated",
+        this.defaultLinkColor = "calculated",
+        this.titleColor = "#333",
+        this.edgeLabelBackground = "#e8e8e8",
+        this.actorBorder = "calculated",
+        this.actorBkg = "calculated",
+        this.actorTextColor = "black",
+        this.actorLineColor = "grey",
+        this.signalColor = "#333",
+        this.signalTextColor = "#333",
+        this.labelBoxBkgColor = "calculated",
+        this.labelBoxBorderColor = "#326932",
+        this.labelTextColor = "calculated",
+        this.loopTextColor = "calculated",
+        this.noteBorderColor = "calculated",
+        this.noteBkgColor = "#fff5ad",
+        this.noteTextColor = "calculated",
+        this.activationBorderColor = "#666",
+        this.activationBkgColor = "#f4f4f4",
+        this.sequenceNumberColor = "white",
+        this.sectionBkgColor = "#6eaa49",
+        this.altSectionBkgColor = "white",
+        this.sectionBkgColor2 = "#6eaa49",
+        this.excludeBkgColor = "#eeeeee",
+        this.taskBorderColor = "calculated",
+        this.taskBkgColor = "#487e3a",
+        this.taskTextLightColor = "white",
+        this.taskTextColor = "calculated",
+        this.taskTextDarkColor = "black",
+        this.taskTextOutsideColor = "calculated",
+        this.taskTextClickableColor = "#003163",
+        this.activeTaskBorderColor = "calculated",
+        this.activeTaskBkgColor = "calculated",
+        this.gridColor = "lightgrey",
+        this.doneTaskBkgColor = "lightgrey",
+        this.doneTaskBorderColor = "grey",
+        this.critBorderColor = "#ff8888",
+        this.critBkgColor = "red",
+        this.todayLineColor = "red",
+        this.personBorder = "calculated",
+        this.personBkg = "calculated",
+        this.labelColor = "black",
+        this.errorBkgColor = "#552222",
+        this.errorTextColor = "#552222";
+    }
+    updateColors() {
+      this.cScale0 = this.cScale0 || this.primaryColor,
+        this.cScale1 = this.cScale1 || this.secondaryColor,
+        this.cScale2 = this.cScale2 || this.tertiaryColor,
+        this.cScale3 = this.cScale3 || Gl(this.primaryColor, { h: 30 }),
+        this.cScale4 = this.cScale4 || Gl(this.primaryColor, { h: 60 }),
+        this.cScale5 = this.cScale5 || Gl(this.primaryColor, { h: 90 }),
+        this.cScale6 = this.cScale6 || Gl(this.primaryColor, { h: 120 }),
+        this.cScale7 = this.cScale7 || Gl(this.primaryColor, { h: 150 }),
+        this.cScale8 = this.cScale8 || Gl(this.primaryColor, { h: 210 }),
+        this.cScale9 = this.cScale9 || Gl(this.primaryColor, { h: 270 }),
+        this.cScale10 = this.cScale10 || Gl(this.primaryColor, { h: 300 }),
+        this.cScale11 = this.cScale11 || Gl(this.primaryColor, { h: 330 }),
+        this.cScalePeer1 = this.cScalePeer1 || Vl(this.secondaryColor, 45),
+        this.cScalePeer2 = this.cScalePeer2 || Vl(this.tertiaryColor, 40);
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScale" + t] = Vl(this["cScale" + t], 10),
+          this["cScalePeer" + t] = this["cScalePeer" + t] || Vl(this["cScale" + t], 25);
+      }
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScaleInv" + t] = this["cScaleInv" + t] || Gl(this["cScale" + t], { h: 180 });
+      }
+      this.scaleLabelColor = "calculated" !== this.scaleLabelColor && this.scaleLabelColor
+        ? this.scaleLabelColor
+        : this.labelTextColor;
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScaleLabel" + t] = this["cScaleLabel" + t] || this.scaleLabelColor;
+      }
+      this.nodeBkg = this.mainBkg,
+        this.nodeBorder = this.border1,
+        this.clusterBkg = this.secondBkg,
+        this.clusterBorder = this.border2,
+        this.defaultLinkColor = this.lineColor,
+        this.actorBorder = Vl(this.mainBkg, 20),
+        this.actorBkg = this.mainBkg,
+        this.labelBoxBkgColor = this.actorBkg,
+        this.labelTextColor = this.actorTextColor,
+        this.loopTextColor = this.actorTextColor,
+        this.noteBorderColor = this.border2,
+        this.noteTextColor = this.actorTextColor,
+        this.taskBorderColor = this.border1,
+        this.taskTextColor = this.taskTextLightColor,
+        this.taskTextOutsideColor = this.taskTextDarkColor,
+        this.activeTaskBorderColor = this.taskBorderColor,
+        this.activeTaskBkgColor = this.mainBkg,
+        this.transitionColor = this.transitionColor || this.lineColor,
+        this.transitionLabelColor = this.transitionLabelColor || this.textColor,
+        this.stateLabelColor = this.stateLabelColor || this.stateBkg || this.primaryTextColor,
+        this.stateBkg = this.stateBkg || this.mainBkg,
+        this.labelBackgroundColor = this.labelBackgroundColor || this.stateBkg,
+        this.compositeBackground = this.compositeBackground || this.background || this.tertiaryColor,
+        this.altBackground = this.altBackground || "#f0f0f0",
+        this.compositeTitleBackground = this.compositeTitleBackground || this.mainBkg,
+        this.compositeBorder = this.compositeBorder || this.nodeBorder,
+        this.innerEndBackground = this.primaryBorderColor,
+        this.specialStateColor = this.lineColor,
+        this.errorBkgColor = this.errorBkgColor || this.tertiaryColor,
+        this.errorTextColor = this.errorTextColor || this.tertiaryTextColor,
+        this.transitionColor = this.transitionColor || this.lineColor,
+        this.classText = this.primaryTextColor,
+        this.fillType0 = this.primaryColor,
+        this.fillType1 = this.secondaryColor,
+        this.fillType2 = Gl(this.primaryColor, { h: 64 }),
+        this.fillType3 = Gl(this.secondaryColor, { h: 64 }),
+        this.fillType4 = Gl(this.primaryColor, { h: -64 }),
+        this.fillType5 = Gl(this.secondaryColor, { h: -64 }),
+        this.fillType6 = Gl(this.primaryColor, { h: 128 }),
+        this.fillType7 = Gl(this.secondaryColor, { h: 128 }),
+        this.pie1 = this.pie1 || this.primaryColor,
+        this.pie2 = this.pie2 || this.secondaryColor,
+        this.pie3 = this.pie3 || this.tertiaryColor,
+        this.pie4 = this.pie4 || Gl(this.primaryColor, { l: -30 }),
+        this.pie5 = this.pie5 || Gl(this.secondaryColor, { l: -30 }),
+        this.pie6 = this.pie6 || Gl(this.tertiaryColor, { h: 40, l: -40 }),
+        this.pie7 = this.pie7 || Gl(this.primaryColor, { h: 60, l: -10 }),
+        this.pie8 = this.pie8 || Gl(this.primaryColor, { h: -60, l: -10 }),
+        this.pie9 = this.pie9 || Gl(this.primaryColor, { h: 120, l: 0 }),
+        this.pie10 = this.pie10 || Gl(this.primaryColor, { h: 60, l: -50 }),
+        this.pie11 = this.pie11 || Gl(this.primaryColor, { h: -60, l: -50 }),
+        this.pie12 = this.pie12 || Gl(this.primaryColor, { h: 120, l: -50 }),
+        this.pieTitleTextSize = this.pieTitleTextSize || "25px",
+        this.pieTitleTextColor = this.pieTitleTextColor || this.taskTextDarkColor,
+        this.pieSectionTextSize = this.pieSectionTextSize || "17px",
+        this.pieSectionTextColor = this.pieSectionTextColor || this.textColor,
+        this.pieLegendTextSize = this.pieLegendTextSize || "17px",
+        this.pieLegendTextColor = this.pieLegendTextColor || this.taskTextDarkColor,
+        this.pieStrokeColor = this.pieStrokeColor || "black",
+        this.pieStrokeWidth = this.pieStrokeWidth || "2px",
+        this.pieOpacity = this.pieOpacity || "0.7",
+        this.requirementBackground = this.requirementBackground || this.primaryColor,
+        this.requirementBorderColor = this.requirementBorderColor || this.primaryBorderColor,
+        this.requirementBorderSize = this.requirementBorderSize || this.primaryBorderColor,
+        this.requirementTextColor = this.requirementTextColor || this.primaryTextColor,
+        this.relationColor = this.relationColor || this.lineColor,
+        this.relationLabelBackground = this.relationLabelBackground || this.edgeLabelBackground,
+        this.relationLabelColor = this.relationLabelColor || this.actorTextColor,
+        this.git0 = this.git0 || this.primaryColor,
+        this.git1 = this.git1 || this.secondaryColor,
+        this.git2 = this.git2 || this.tertiaryColor,
+        this.git3 = this.git3 || Gl(this.primaryColor, { h: -30 }),
+        this.git4 = this.git4 || Gl(this.primaryColor, { h: -60 }),
+        this.git5 = this.git5 || Gl(this.primaryColor, { h: -90 }),
+        this.git6 = this.git6 || Gl(this.primaryColor, { h: 60 }),
+        this.git7 = this.git7 || Gl(this.primaryColor, { h: 120 }),
+        this.darkMode
+          ? (this.git0 = ql(this.git0, 25),
+            this.git1 = ql(this.git1, 25),
+            this.git2 = ql(this.git2, 25),
+            this.git3 = ql(this.git3, 25),
+            this.git4 = ql(this.git4, 25),
+            this.git5 = ql(this.git5, 25),
+            this.git6 = ql(this.git6, 25),
+            this.git7 = ql(this.git7, 25))
+          : (this.git0 = Vl(this.git0, 25),
+            this.git1 = Vl(this.git1, 25),
+            this.git2 = Vl(this.git2, 25),
+            this.git3 = Vl(this.git3, 25),
+            this.git4 = Vl(this.git4, 25),
+            this.git5 = Vl(this.git5, 25),
+            this.git6 = Vl(this.git6, 25),
+            this.git7 = Vl(this.git7, 25)),
+        this.gitInv0 = this.gitInv0 || Zl(this.git0),
+        this.gitInv1 = this.gitInv1 || Zl(this.git1),
+        this.gitInv2 = this.gitInv2 || Zl(this.git2),
+        this.gitInv3 = this.gitInv3 || Zl(this.git3),
+        this.gitInv4 = this.gitInv4 || Zl(this.git4),
+        this.gitInv5 = this.gitInv5 || Zl(this.git5),
+        this.gitInv6 = this.gitInv6 || Zl(this.git6),
+        this.gitInv7 = this.gitInv7 || Zl(this.git7),
+        this.tagLabelColor = this.tagLabelColor || this.primaryTextColor,
+        this.tagLabelBackground = this.tagLabelBackground || this.primaryColor,
+        this.tagLabelBorder = this.tagBorder || this.primaryBorderColor,
+        this.tagLabelFontSize = this.tagLabelFontSize || "10px",
+        this.commitLabelColor = this.commitLabelColor || this.secondaryTextColor,
+        this.commitLabelBackground = this.commitLabelBackground || this.secondaryColor,
+        this.commitLabelFontSize = this.commitLabelFontSize || "10px",
+        this.attributeBackgroundColorOdd = this.attributeBackgroundColorOdd || pb,
+        this.attributeBackgroundColorEven = this.attributeBackgroundColorEven || fb;
+    }
+    calculate(t) {
+      if ("object" != typeof t) return void this.updateColors();
+      const e = Object.keys(t);
+      e.forEach(e => {
+        this[e] = t[e];
+      }),
+        this.updateColors(),
+        e.forEach(e => {
+          this[e] = t[e];
+        });
+    }
+  }
+  class _b {
+    constructor() {
+      this.primaryColor = "#eee",
+        this.contrast = "#707070",
+        this.secondaryColor = ql(this.contrast, 55),
+        this.background = "#ffffff",
+        this.tertiaryColor = Gl(this.primaryColor, { h: -160 }),
+        this.primaryBorderColor = db(this.primaryColor, this.darkMode),
+        this.secondaryBorderColor = db(this.secondaryColor, this.darkMode),
+        this.tertiaryBorderColor = db(this.tertiaryColor, this.darkMode),
+        this.primaryTextColor = Zl(this.primaryColor),
+        this.secondaryTextColor = Zl(this.secondaryColor),
+        this.tertiaryTextColor = Zl(this.tertiaryColor),
+        this.lineColor = Zl(this.background),
+        this.textColor = Zl(this.background),
+        this.mainBkg = "#eee",
+        this.secondBkg = "calculated",
+        this.lineColor = "#666",
+        this.border1 = "#999",
+        this.border2 = "calculated",
+        this.note = "#ffa",
+        this.text = "#333",
+        this.critical = "#d42",
+        this.done = "#bbb",
+        this.arrowheadColor = "#333333",
+        this.fontFamily = "\"trebuchet ms\", verdana, arial, sans-serif",
+        this.fontSize = "16px",
+        this.THEME_COLOR_LIMIT = 12,
+        this.nodeBkg = "calculated",
+        this.nodeBorder = "calculated",
+        this.clusterBkg = "calculated",
+        this.clusterBorder = "calculated",
+        this.defaultLinkColor = "calculated",
+        this.titleColor = "calculated",
+        this.edgeLabelBackground = "white",
+        this.actorBorder = "calculated",
+        this.actorBkg = "calculated",
+        this.actorTextColor = "calculated",
+        this.actorLineColor = "calculated",
+        this.signalColor = "calculated",
+        this.signalTextColor = "calculated",
+        this.labelBoxBkgColor = "calculated",
+        this.labelBoxBorderColor = "calculated",
+        this.labelTextColor = "calculated",
+        this.loopTextColor = "calculated",
+        this.noteBorderColor = "calculated",
+        this.noteBkgColor = "calculated",
+        this.noteTextColor = "calculated",
+        this.activationBorderColor = "#666",
+        this.activationBkgColor = "#f4f4f4",
+        this.sequenceNumberColor = "white",
+        this.sectionBkgColor = "calculated",
+        this.altSectionBkgColor = "white",
+        this.sectionBkgColor2 = "calculated",
+        this.excludeBkgColor = "#eeeeee",
+        this.taskBorderColor = "calculated",
+        this.taskBkgColor = "calculated",
+        this.taskTextLightColor = "white",
+        this.taskTextColor = "calculated",
+        this.taskTextDarkColor = "calculated",
+        this.taskTextOutsideColor = "calculated",
+        this.taskTextClickableColor = "#003163",
+        this.activeTaskBorderColor = "calculated",
+        this.activeTaskBkgColor = "calculated",
+        this.gridColor = "calculated",
+        this.doneTaskBkgColor = "calculated",
+        this.doneTaskBorderColor = "calculated",
+        this.critBkgColor = "calculated",
+        this.critBorderColor = "calculated",
+        this.todayLineColor = "calculated",
+        this.personBorder = "calculated",
+        this.personBkg = "calculated",
+        this.labelColor = "black",
+        this.errorBkgColor = "#552222",
+        this.errorTextColor = "#552222";
+    }
+    updateColors() {
+      this.secondBkg = ql(this.contrast, 55),
+        this.border2 = this.contrast,
+        this.cScale0 = this.cScale0 || "#555",
+        this.cScale1 = this.cScale1 || "#F4F4F4",
+        this.cScale2 = this.cScale2 || "#555",
+        this.cScale3 = this.cScale3 || "#BBB",
+        this.cScale4 = this.cScale4 || "#777",
+        this.cScale5 = this.cScale5 || "#999",
+        this.cScale6 = this.cScale6 || "#DDD",
+        this.cScale7 = this.cScale7 || "#FFF",
+        this.cScale8 = this.cScale8 || "#DDD",
+        this.cScale9 = this.cScale9 || "#BBB",
+        this.cScale10 = this.cScale10 || "#999",
+        this.cScale11 = this.cScale11 || "#777";
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScaleInv" + t] = this["cScaleInv" + t] || Zl(this["cScale" + t]);
+      }
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this.darkMode
+          ? this["cScalePeer" + t] = this["cScalePeer" + t] || ql(this["cScale" + t], 10)
+          : this["cScalePeer" + t] = this["cScalePeer" + t] || Vl(this["cScale" + t], 10);
+      }
+      this.scaleLabelColor = this.scaleLabelColor || (this.darkMode ? "black" : this.labelTextColor),
+        this.cScaleLabel0 = this.cScaleLabel0 || this.cScale1,
+        this.cScaleLabel2 = this.cScaleLabel2 || this.cScale1;
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) {
+        this["cScaleLabel" + t] = this["cScaleLabel" + t] || this.scaleLabelColor;
+      }
+      this.nodeBkg = this.mainBkg,
+        this.nodeBorder = this.border1,
+        this.clusterBkg = this.secondBkg,
+        this.clusterBorder = this.border2,
+        this.defaultLinkColor = this.lineColor,
+        this.titleColor = this.text,
+        this.actorBorder = ql(this.border1, 23),
+        this.actorBkg = this.mainBkg,
+        this.actorTextColor = this.text,
+        this.actorLineColor = this.lineColor,
+        this.signalColor = this.text,
+        this.signalTextColor = this.text,
+        this.labelBoxBkgColor = this.actorBkg,
+        this.labelBoxBorderColor = this.actorBorder,
+        this.labelTextColor = this.text,
+        this.loopTextColor = this.text,
+        this.noteBorderColor = "#999",
+        this.noteBkgColor = "#666",
+        this.noteTextColor = "#fff",
+        this.sectionBkgColor = ql(this.contrast, 30),
+        this.sectionBkgColor2 = ql(this.contrast, 30),
+        this.taskBorderColor = Vl(this.contrast, 10),
+        this.taskBkgColor = this.contrast,
+        this.taskTextColor = this.taskTextLightColor,
+        this.taskTextDarkColor = this.text,
+        this.taskTextOutsideColor = this.taskTextDarkColor,
+        this.activeTaskBorderColor = this.taskBorderColor,
+        this.activeTaskBkgColor = this.mainBkg,
+        this.gridColor = ql(this.border1, 30),
+        this.doneTaskBkgColor = this.done,
+        this.doneTaskBorderColor = this.lineColor,
+        this.critBkgColor = this.critical,
+        this.critBorderColor = Vl(this.critBkgColor, 10),
+        this.todayLineColor = this.critBkgColor,
+        this.transitionColor = this.transitionColor || "#000",
+        this.transitionLabelColor = this.transitionLabelColor || this.textColor,
+        this.stateLabelColor = this.stateLabelColor || this.stateBkg || this.primaryTextColor,
+        this.stateBkg = this.stateBkg || this.mainBkg,
+        this.labelBackgroundColor = this.labelBackgroundColor || this.stateBkg,
+        this.compositeBackground = this.compositeBackground || this.background || this.tertiaryColor,
+        this.altBackground = this.altBackground || "#f4f4f4",
+        this.compositeTitleBackground = this.compositeTitleBackground || this.mainBkg,
+        this.stateBorder = this.stateBorder || "#000",
+        this.innerEndBackground = this.primaryBorderColor,
+        this.specialStateColor = "#222",
+        this.errorBkgColor = this.errorBkgColor || this.tertiaryColor,
+        this.errorTextColor = this.errorTextColor || this.tertiaryTextColor,
+        this.classText = this.primaryTextColor,
+        this.fillType0 = this.primaryColor,
+        this.fillType1 = this.secondaryColor,
+        this.fillType2 = Gl(this.primaryColor, { h: 64 }),
+        this.fillType3 = Gl(this.secondaryColor, { h: 64 }),
+        this.fillType4 = Gl(this.primaryColor, { h: -64 }),
+        this.fillType5 = Gl(this.secondaryColor, { h: -64 }),
+        this.fillType6 = Gl(this.primaryColor, { h: 128 }),
+        this.fillType7 = Gl(this.secondaryColor, { h: 128 });
+      for (let t = 0; t < this.THEME_COLOR_LIMIT; t++) this["pie" + t] = this["cScale" + t];
+      this.pie12 = this.pie0,
+        this.pieTitleTextSize = this.pieTitleTextSize || "25px",
+        this.pieTitleTextColor = this.pieTitleTextColor || this.taskTextDarkColor,
+        this.pieSectionTextSize = this.pieSectionTextSize || "17px",
+        this.pieSectionTextColor = this.pieSectionTextColor || this.textColor,
+        this.pieLegendTextSize = this.pieLegendTextSize || "17px",
+        this.pieLegendTextColor = this.pieLegendTextColor || this.taskTextDarkColor,
+        this.pieStrokeColor = this.pieStrokeColor || "black",
+        this.pieStrokeWidth = this.pieStrokeWidth || "2px",
+        this.pieOpacity = this.pieOpacity || "0.7",
+        this.requirementBackground = this.requirementBackground || this.primaryColor,
+        this.requirementBorderColor = this.requirementBorderColor || this.primaryBorderColor,
+        this.requirementBorderSize = this.requirementBorderSize || this.primaryBorderColor,
+        this.requirementTextColor = this.requirementTextColor || this.primaryTextColor,
+        this.relationColor = this.relationColor || this.lineColor,
+        this.relationLabelBackground = this.relationLabelBackground || this.edgeLabelBackground,
+        this.relationLabelColor = this.relationLabelColor || this.actorTextColor,
+        this.git0 = Vl(this.pie1, 25) || this.primaryColor,
+        this.git1 = this.pie2 || this.secondaryColor,
+        this.git2 = this.pie3 || this.tertiaryColor,
+        this.git3 = this.pie4 || Gl(this.primaryColor, { h: -30 }),
+        this.git4 = this.pie5 || Gl(this.primaryColor, { h: -60 }),
+        this.git5 = this.pie6 || Gl(this.primaryColor, { h: -90 }),
+        this.git6 = this.pie7 || Gl(this.primaryColor, { h: 60 }),
+        this.git7 = this.pie8 || Gl(this.primaryColor, { h: 120 }),
+        this.gitInv0 = this.gitInv0 || Zl(this.git0),
+        this.gitInv1 = this.gitInv1 || Zl(this.git1),
+        this.gitInv2 = this.gitInv2 || Zl(this.git2),
+        this.gitInv3 = this.gitInv3 || Zl(this.git3),
+        this.gitInv4 = this.gitInv4 || Zl(this.git4),
+        this.gitInv5 = this.gitInv5 || Zl(this.git5),
+        this.gitInv6 = this.gitInv6 || Zl(this.git6),
+        this.gitInv7 = this.gitInv7 || Zl(this.git7),
+        this.branchLabelColor = this.branchLabelColor || this.labelTextColor,
+        this.gitBranchLabel0 = this.branchLabelColor,
+        this.gitBranchLabel1 = "white",
+        this.gitBranchLabel2 = this.branchLabelColor,
+        this.gitBranchLabel3 = "white",
+        this.gitBranchLabel4 = this.branchLabelColor,
+        this.gitBranchLabel5 = this.branchLabelColor,
+        this.gitBranchLabel6 = this.branchLabelColor,
+        this.gitBranchLabel7 = this.branchLabelColor,
+        this.tagLabelColor = this.tagLabelColor || this.primaryTextColor,
+        this.tagLabelBackground = this.tagLabelBackground || this.primaryColor,
+        this.tagLabelBorder = this.tagBorder || this.primaryBorderColor,
+        this.tagLabelFontSize = this.tagLabelFontSize || "10px",
+        this.commitLabelColor = this.commitLabelColor || this.secondaryTextColor,
+        this.commitLabelBackground = this.commitLabelBackground || this.secondaryColor,
+        this.commitLabelFontSize = this.commitLabelFontSize || "10px",
+        this.attributeBackgroundColorOdd = this.attributeBackgroundColorOdd || pb,
+        this.attributeBackgroundColorEven = this.attributeBackgroundColorEven || fb;
+    }
+    calculate(t) {
+      if ("object" != typeof t) return void this.updateColors();
+      const e = Object.keys(t);
+      e.forEach(e => {
+        this[e] = t[e];
+      }),
+        this.updateColors(),
+        e.forEach(e => {
+          this[e] = t[e];
+        });
+    }
+  }
+  const xb = {
+      base: {
+        getThemeVariables: t => {
+          const e = new gb();
+          return e.calculate(t), e;
+        },
+      },
+      dark: {
+        getThemeVariables: t => {
+          const e = new yb();
+          return e.calculate(t), e;
+        },
+      },
+      default: {
+        getThemeVariables: t => {
+          const e = new mb();
+          return e.calculate(t), e;
+        },
+      },
+      forest: {
+        getThemeVariables: t => {
+          const e = new bb();
+          return e.calculate(t), e;
+        },
+      },
+      neutral: {
+        getThemeVariables: t => {
+          const e = new _b();
+          return e.calculate(t), e;
+        },
+      },
+    },
+    vb = {
+      theme: "default",
+      themeVariables: xb.default.getThemeVariables(),
+      themeCSS: void 0,
+      maxTextSize: 5e4,
+      darkMode: !1,
+      fontFamily: "\"trebuchet ms\", verdana, arial, sans-serif;",
+      logLevel: 5,
+      securityLevel: "strict",
+      startOnLoad: !0,
+      arrowMarkerAbsolute: !1,
+      secure: ["secure", "securityLevel", "startOnLoad", "maxTextSize"],
+      deterministicIds: !1,
+      deterministicIDSeed: void 0,
+      flowchart: {
+        titleTopMargin: 25,
+        diagramPadding: 8,
+        htmlLabels: !0,
+        nodeSpacing: 50,
+        rankSpacing: 50,
+        curve: "basis",
+        padding: 15,
+        useMaxWidth: !0,
+        defaultRenderer: "dagre-wrapper",
+      },
+      sequence: {
+        hideUnusedParticipants: !1,
+        activationWidth: 10,
+        diagramMarginX: 50,
+        diagramMarginY: 10,
+        actorMargin: 50,
+        width: 150,
+        height: 65,
+        boxMargin: 10,
+        boxTextMargin: 5,
+        noteMargin: 10,
+        messageMargin: 35,
+        messageAlign: "center",
+        mirrorActors: !0,
+        forceMenus: !1,
+        bottomMarginAdj: 1,
+        useMaxWidth: !0,
+        rightAngles: !1,
+        showSequenceNumbers: !1,
+        actorFontSize: 14,
+        actorFontFamily: "\"Open Sans\", sans-serif",
+        actorFontWeight: 400,
+        noteFontSize: 14,
+        noteFontFamily: "\"trebuchet ms\", verdana, arial, sans-serif",
+        noteFontWeight: 400,
+        noteAlign: "center",
+        messageFontSize: 16,
+        messageFontFamily: "\"trebuchet ms\", verdana, arial, sans-serif",
+        messageFontWeight: 400,
+        wrap: !1,
+        wrapPadding: 10,
+        labelBoxWidth: 50,
+        labelBoxHeight: 20,
+        messageFont: function() {
+          return {
+            fontFamily: this.messageFontFamily,
+            fontSize: this.messageFontSize,
+            fontWeight: this.messageFontWeight,
+          };
+        },
+        noteFont: function() {
+          return { fontFamily: this.noteFontFamily, fontSize: this.noteFontSize, fontWeight: this.noteFontWeight };
+        },
+        actorFont: function() {
+          return { fontFamily: this.actorFontFamily, fontSize: this.actorFontSize, fontWeight: this.actorFontWeight };
+        },
+      },
+      gantt: {
+        titleTopMargin: 25,
+        barHeight: 20,
+        barGap: 4,
+        topPadding: 50,
+        rightPadding: 75,
+        leftPadding: 75,
+        gridLineStartPadding: 35,
+        fontSize: 11,
+        sectionFontSize: 11,
+        numberSectionStyles: 4,
+        axisFormat: "%Y-%m-%d",
+        tickInterval: void 0,
+        useMaxWidth: !0,
+        topAxis: !1,
+        useWidth: void 0,
+      },
+      journey: {
+        diagramMarginX: 50,
+        diagramMarginY: 10,
+        leftMargin: 150,
+        width: 150,
+        height: 50,
+        boxMargin: 10,
+        boxTextMargin: 5,
+        noteMargin: 10,
+        messageMargin: 35,
+        messageAlign: "center",
+        bottomMarginAdj: 1,
+        useMaxWidth: !0,
+        rightAngles: !1,
+        taskFontSize: 14,
+        taskFontFamily: "\"Open Sans\", sans-serif",
+        taskMargin: 50,
+        activationWidth: 10,
+        textPlacement: "fo",
+        actorColours: ["#8FBC8F", "#7CFC00", "#00FFFF", "#20B2AA", "#B0E0E6", "#FFFFE0"],
+        sectionFills: ["#191970", "#8B008B", "#4B0082", "#2F4F4F", "#800000", "#8B4513", "#00008B"],
+        sectionColours: ["#fff"],
+      },
+      class: {
+        titleTopMargin: 25,
+        arrowMarkerAbsolute: !1,
+        dividerMargin: 10,
+        padding: 5,
+        textHeight: 10,
+        useMaxWidth: !0,
+        defaultRenderer: "dagre-wrapper",
+      },
+      state: {
+        titleTopMargin: 25,
+        dividerMargin: 10,
+        sizeUnit: 5,
+        padding: 8,
+        textHeight: 10,
+        titleShift: -15,
+        noteMargin: 10,
+        forkWidth: 70,
+        forkHeight: 7,
+        miniPadding: 2,
+        fontSizeFactor: 5.02,
+        fontSize: 24,
+        labelHeight: 16,
+        edgeLengthFactor: "20",
+        compositTitleSize: 35,
+        radius: 5,
+        useMaxWidth: !0,
+        defaultRenderer: "dagre-wrapper",
+      },
+      er: {
+        titleTopMargin: 25,
+        diagramPadding: 20,
+        layoutDirection: "TB",
+        minEntityWidth: 100,
+        minEntityHeight: 75,
+        entityPadding: 15,
+        stroke: "gray",
+        fill: "honeydew",
+        fontSize: 12,
+        useMaxWidth: !0,
+      },
+      pie: { useWidth: void 0, useMaxWidth: !0 },
+      requirement: {
+        useWidth: void 0,
+        useMaxWidth: !0,
+        rect_fill: "#f9f9f9",
+        text_color: "#333",
+        rect_border_size: "0.5px",
+        rect_border_color: "#bbb",
+        rect_min_width: 200,
+        rect_min_height: 200,
+        fontSize: 14,
+        rect_padding: 10,
+        line_height: 20,
+      },
+      gitGraph: {
+        titleTopMargin: 25,
+        diagramPadding: 8,
+        nodeLabel: { width: 75, height: 100, x: -25, y: 0 },
+        mainBranchName: "main",
+        mainBranchOrder: 0,
+        showCommitLabel: !0,
+        showBranches: !0,
+        rotateCommitLabel: !0,
+      },
+      c4: {
+        useWidth: void 0,
+        diagramMarginX: 50,
+        diagramMarginY: 10,
+        c4ShapeMargin: 50,
+        c4ShapePadding: 20,
+        width: 216,
+        height: 60,
+        boxMargin: 10,
+        useMaxWidth: !0,
+        c4ShapeInRow: 4,
+        nextLinePaddingX: 0,
+        c4BoundaryInRow: 2,
+        personFontSize: 14,
+        personFontFamily: "\"Open Sans\", sans-serif",
+        personFontWeight: "normal",
+        external_personFontSize: 14,
+        external_personFontFamily: "\"Open Sans\", sans-serif",
+        external_personFontWeight: "normal",
+        systemFontSize: 14,
+        systemFontFamily: "\"Open Sans\", sans-serif",
+        systemFontWeight: "normal",
+        external_systemFontSize: 14,
+        external_systemFontFamily: "\"Open Sans\", sans-serif",
+        external_systemFontWeight: "normal",
+        system_dbFontSize: 14,
+        system_dbFontFamily: "\"Open Sans\", sans-serif",
+        system_dbFontWeight: "normal",
+        external_system_dbFontSize: 14,
+        external_system_dbFontFamily: "\"Open Sans\", sans-serif",
+        external_system_dbFontWeight: "normal",
+        system_queueFontSize: 14,
+        system_queueFontFamily: "\"Open Sans\", sans-serif",
+        system_queueFontWeight: "normal",
+        external_system_queueFontSize: 14,
+        external_system_queueFontFamily: "\"Open Sans\", sans-serif",
+        external_system_queueFontWeight: "normal",
+        boundaryFontSize: 14,
+        boundaryFontFamily: "\"Open Sans\", sans-serif",
+        boundaryFontWeight: "normal",
+        messageFontSize: 12,
+        messageFontFamily: "\"Open Sans\", sans-serif",
+        messageFontWeight: "normal",
+        containerFontSize: 14,
+        containerFontFamily: "\"Open Sans\", sans-serif",
+        containerFontWeight: "normal",
+        external_containerFontSize: 14,
+        external_containerFontFamily: "\"Open Sans\", sans-serif",
+        external_containerFontWeight: "normal",
+        container_dbFontSize: 14,
+        container_dbFontFamily: "\"Open Sans\", sans-serif",
+        container_dbFontWeight: "normal",
+        external_container_dbFontSize: 14,
+        external_container_dbFontFamily: "\"Open Sans\", sans-serif",
+        external_container_dbFontWeight: "normal",
+        container_queueFontSize: 14,
+        container_queueFontFamily: "\"Open Sans\", sans-serif",
+        container_queueFontWeight: "normal",
+        external_container_queueFontSize: 14,
+        external_container_queueFontFamily: "\"Open Sans\", sans-serif",
+        external_container_queueFontWeight: "normal",
+        componentFontSize: 14,
+        componentFontFamily: "\"Open Sans\", sans-serif",
+        componentFontWeight: "normal",
+        external_componentFontSize: 14,
+        external_componentFontFamily: "\"Open Sans\", sans-serif",
+        external_componentFontWeight: "normal",
+        component_dbFontSize: 14,
+        component_dbFontFamily: "\"Open Sans\", sans-serif",
+        component_dbFontWeight: "normal",
+        external_component_dbFontSize: 14,
+        external_component_dbFontFamily: "\"Open Sans\", sans-serif",
+        external_component_dbFontWeight: "normal",
+        component_queueFontSize: 14,
+        component_queueFontFamily: "\"Open Sans\", sans-serif",
+        component_queueFontWeight: "normal",
+        external_component_queueFontSize: 14,
+        external_component_queueFontFamily: "\"Open Sans\", sans-serif",
+        external_component_queueFontWeight: "normal",
+        wrap: !0,
+        wrapPadding: 10,
+        personFont: function() {
+          return {
+            fontFamily: this.personFontFamily,
+            fontSize: this.personFontSize,
+            fontWeight: this.personFontWeight,
+          };
+        },
+        external_personFont: function() {
+          return {
+            fontFamily: this.external_personFontFamily,
+            fontSize: this.external_personFontSize,
+            fontWeight: this.external_personFontWeight,
+          };
+        },
+        systemFont: function() {
+          return {
+            fontFamily: this.systemFontFamily,
+            fontSize: this.systemFontSize,
+            fontWeight: this.systemFontWeight,
+          };
+        },
+        external_systemFont: function() {
+          return {
+            fontFamily: this.external_systemFontFamily,
+            fontSize: this.external_systemFontSize,
+            fontWeight: this.external_systemFontWeight,
+          };
+        },
+        system_dbFont: function() {
+          return {
+            fontFamily: this.system_dbFontFamily,
+            fontSize: this.system_dbFontSize,
+            fontWeight: this.system_dbFontWeight,
+          };
+        },
+        external_system_dbFont: function() {
+          return {
+            fontFamily: this.external_system_dbFontFamily,
+            fontSize: this.external_system_dbFontSize,
+            fontWeight: this.external_system_dbFontWeight,
+          };
+        },
+        system_queueFont: function() {
+          return {
+            fontFamily: this.system_queueFontFamily,
+            fontSize: this.system_queueFontSize,
+            fontWeight: this.system_queueFontWeight,
+          };
+        },
+        external_system_queueFont: function() {
+          return {
+            fontFamily: this.external_system_queueFontFamily,
+            fontSize: this.external_system_queueFontSize,
+            fontWeight: this.external_system_queueFontWeight,
+          };
+        },
+        containerFont: function() {
+          return {
+            fontFamily: this.containerFontFamily,
+            fontSize: this.containerFontSize,
+            fontWeight: this.containerFontWeight,
+          };
+        },
+        external_containerFont: function() {
+          return {
+            fontFamily: this.external_containerFontFamily,
+            fontSize: this.external_containerFontSize,
+            fontWeight: this.external_containerFontWeight,
+          };
+        },
+        container_dbFont: function() {
+          return {
+            fontFamily: this.container_dbFontFamily,
+            fontSize: this.container_dbFontSize,
+            fontWeight: this.container_dbFontWeight,
+          };
+        },
+        external_container_dbFont: function() {
+          return {
+            fontFamily: this.external_container_dbFontFamily,
+            fontSize: this.external_container_dbFontSize,
+            fontWeight: this.external_container_dbFontWeight,
+          };
+        },
+        container_queueFont: function() {
+          return {
+            fontFamily: this.container_queueFontFamily,
+            fontSize: this.container_queueFontSize,
+            fontWeight: this.container_queueFontWeight,
+          };
+        },
+        external_container_queueFont: function() {
+          return {
+            fontFamily: this.external_container_queueFontFamily,
+            fontSize: this.external_container_queueFontSize,
+            fontWeight: this.external_container_queueFontWeight,
+          };
+        },
+        componentFont: function() {
+          return {
+            fontFamily: this.componentFontFamily,
+            fontSize: this.componentFontSize,
+            fontWeight: this.componentFontWeight,
+          };
+        },
+        external_componentFont: function() {
+          return {
+            fontFamily: this.external_componentFontFamily,
+            fontSize: this.external_componentFontSize,
+            fontWeight: this.external_componentFontWeight,
+          };
+        },
+        component_dbFont: function() {
+          return {
+            fontFamily: this.component_dbFontFamily,
+            fontSize: this.component_dbFontSize,
+            fontWeight: this.component_dbFontWeight,
+          };
+        },
+        external_component_dbFont: function() {
+          return {
+            fontFamily: this.external_component_dbFontFamily,
+            fontSize: this.external_component_dbFontSize,
+            fontWeight: this.external_component_dbFontWeight,
+          };
+        },
+        component_queueFont: function() {
+          return {
+            fontFamily: this.component_queueFontFamily,
+            fontSize: this.component_queueFontSize,
+            fontWeight: this.component_queueFontWeight,
+          };
+        },
+        external_component_queueFont: function() {
+          return {
+            fontFamily: this.external_component_queueFontFamily,
+            fontSize: this.external_component_queueFontSize,
+            fontWeight: this.external_component_queueFontWeight,
+          };
+        },
+        boundaryFont: function() {
+          return {
+            fontFamily: this.boundaryFontFamily,
+            fontSize: this.boundaryFontSize,
+            fontWeight: this.boundaryFontWeight,
+          };
+        },
+        messageFont: function() {
+          return {
+            fontFamily: this.messageFontFamily,
+            fontSize: this.messageFontSize,
+            fontWeight: this.messageFontWeight,
+          };
+        },
+        person_bg_color: "#08427B",
+        person_border_color: "#073B6F",
+        external_person_bg_color: "#686868",
+        external_person_border_color: "#8A8A8A",
+        system_bg_color: "#1168BD",
+        system_border_color: "#3C7FC0",
+        system_db_bg_color: "#1168BD",
+        system_db_border_color: "#3C7FC0",
+        system_queue_bg_color: "#1168BD",
+        system_queue_border_color: "#3C7FC0",
+        external_system_bg_color: "#999999",
+        external_system_border_color: "#8A8A8A",
+        external_system_db_bg_color: "#999999",
+        external_system_db_border_color: "#8A8A8A",
+        external_system_queue_bg_color: "#999999",
+        external_system_queue_border_color: "#8A8A8A",
+        container_bg_color: "#438DD5",
+        container_border_color: "#3C7FC0",
+        container_db_bg_color: "#438DD5",
+        container_db_border_color: "#3C7FC0",
+        container_queue_bg_color: "#438DD5",
+        container_queue_border_color: "#3C7FC0",
+        external_container_bg_color: "#B3B3B3",
+        external_container_border_color: "#A6A6A6",
+        external_container_db_bg_color: "#B3B3B3",
+        external_container_db_border_color: "#A6A6A6",
+        external_container_queue_bg_color: "#B3B3B3",
+        external_container_queue_border_color: "#A6A6A6",
+        component_bg_color: "#85BBF0",
+        component_border_color: "#78A8D8",
+        component_db_bg_color: "#85BBF0",
+        component_db_border_color: "#78A8D8",
+        component_queue_bg_color: "#85BBF0",
+        component_queue_border_color: "#78A8D8",
+        external_component_bg_color: "#CCCCCC",
+        external_component_border_color: "#BFBFBF",
+        external_component_db_bg_color: "#CCCCCC",
+        external_component_db_border_color: "#BFBFBF",
+        external_component_queue_bg_color: "#CCCCCC",
+        external_component_queue_border_color: "#BFBFBF",
+      },
+      mindmap: { useMaxWidth: !0, padding: 10, maxNodeWidth: 200 },
+      fontSize: 16,
+    };
+  vb.class && (vb.class.arrowMarkerAbsolute = vb.arrowMarkerAbsolute),
+    vb.gitGraph && (vb.gitGraph.arrowMarkerAbsolute = vb.arrowMarkerAbsolute);
+  const kb = (t, e = "") =>
+      Object.keys(t).reduce(
+        (n, i) =>
+          Array.isArray(t[i])
+            ? n
+            : "object" == typeof t[i] && null !== t[i]
+            ? [...n, e + i, ...kb(t[i], "")]
+            : [...n, e + i],
+        [],
+      ),
+    wb = kb(vb, ""),
+    Tb = vb;
+  /*! js-yaml 4.1.0 https://github.com/nodeca/js-yaml @license MIT */
+  function Cb(t) {
+    return null == t;
+  }
+  var Eb = function(t) {
+      return 0 === t && Number.NEGATIVE_INFINITY === 1 / t;
+    },
+    Sb = function(t, e) {
+      var n, i, r, a;
+      if (e) for (n = 0, i = (a = Object.keys(e)).length; n < i; n += 1) t[r = a[n]] = e[r];
+      return t;
+    },
+    Ab = {
+      isNothing: Cb,
+      isObject: function(t) {
+        return "object" == typeof t && null !== t;
+      },
+      toArray: function(t) {
+        return Array.isArray(t) ? t : Cb(t) ? [] : [t];
+      },
+      repeat: function(t, e) {
+        var n, i = "";
+        for (n = 0; n < e; n += 1) i += t;
+        return i;
+      },
+      isNegativeZero: Eb,
+      extend: Sb,
+    };
+  function Db(t, e) {
+    var n = "", i = t.reason || "(unknown reason)";
+    return t.mark
+      ? (t.mark.name && (n += "in \"" + t.mark.name + "\" "),
+        n += "(" + (t.mark.line + 1) + ":" + (t.mark.column + 1) + ")",
+        !e && t.mark.snippet && (n += "\n\n" + t.mark.snippet),
+        i + " " + n)
+      : i;
+  }
+  function Lb(t, e) {
+    Error.call(this),
+      this.name = "YAMLException",
+      this.reason = t,
+      this.mark = e,
+      this.message = Db(this, !1),
+      Error.captureStackTrace
+        ? Error.captureStackTrace(this, this.constructor)
+        : this.stack = (new Error()).stack || "";
+  }
+  Lb.prototype = Object.create(Error.prototype),
+    Lb.prototype.constructor = Lb,
+    Lb.prototype.toString = function(t) {
+      return this.name + ": " + Db(this, t);
+    };
+  var Ob = Lb;
+  function Nb(t, e, n, i, r) {
+    var a = "", s = "", o = Math.floor(r / 2) - 1;
+    return i - e > o && (e = i - o + (a = " ... ").length),
+      n - i > o && (n = i + o - (s = " ...").length),
+      { str: a + t.slice(e, n).replace(/\t/g, "→") + s, pos: i - e + a.length };
+  }
+  function Mb(t, e) {
+    return Ab.repeat(" ", e - t.length) + t;
+  }
+  var Bb = function(t, e) {
+      if (e = Object.create(e || null), !t.buffer) return null;
+      e.maxLength || (e.maxLength = 79),
+        "number" != typeof e.indent && (e.indent = 1),
+        "number" != typeof e.linesBefore && (e.linesBefore = 3),
+        "number" != typeof e.linesAfter && (e.linesAfter = 2);
+      for (var n, i = /\r?\n|\r|\0/g, r = [0], a = [], s = -1; n = i.exec(t.buffer);) {
+        a.push(n.index), r.push(n.index + n[0].length), t.position <= n.index && s < 0 && (s = r.length - 2);
+      }
+      s < 0 && (s = r.length - 1);
+      var o,
+        l,
+        c = "",
+        h = Math.min(t.line + e.linesAfter, a.length).toString().length,
+        u = e.maxLength - (e.indent + h + 3);
+      for (o = 1; o <= e.linesBefore && !(s - o < 0); o++) {
+        l = Nb(t.buffer, r[s - o], a[s - o], t.position - (r[s] - r[s - o]), u),
+          c = Ab.repeat(" ", e.indent) + Mb((t.line - o + 1).toString(), h) + " | " + l.str + "\n" + c;
+      }
+      for (
+        l = Nb(t.buffer, r[s], a[s], t.position, u),
+          c += Ab.repeat(" ", e.indent) + Mb((t.line + 1).toString(), h) + " | " + l.str + "\n",
+          c += Ab.repeat("-", e.indent + h + 3 + l.pos) + "^\n",
+          o = 1;
+        o <= e.linesAfter && !(s + o >= a.length);
+        o++
+      ) {
+        l = Nb(t.buffer, r[s + o], a[s + o], t.position - (r[s] - r[s + o]), u),
+          c += Ab.repeat(" ", e.indent) + Mb((t.line + o + 1).toString(), h) + " | " + l.str + "\n";
+      }
+      return c.replace(/\n$/, "");
+    },
+    Ib = [
+      "kind",
+      "multi",
+      "resolve",
+      "construct",
+      "instanceOf",
+      "predicate",
+      "represent",
+      "representName",
+      "defaultStyle",
+      "styleAliases",
+    ],
+    Fb = ["scalar", "sequence", "mapping"];
+  var Rb = function(t, e) {
+    var n, i;
+    if (
+      e = e || {},
+        Object.keys(e).forEach(function(e) {
+          if (-1 === Ib.indexOf(e)) {
+            throw new Ob("Unknown option \"" + e + "\" is met in definition of \"" + t + "\" YAML type.");
+          }
+        }),
+        this.options = e,
+        this.tag = t,
+        this.kind = e.kind || null,
+        this.resolve = e.resolve || function() {
+          return !0;
+        },
+        this.construct = e.construct || function(t) {
+          return t;
+        },
+        this.instanceOf = e.instanceOf || null,
+        this.predicate = e.predicate || null,
+        this.represent = e.represent || null,
+        this.representName = e.representName || null,
+        this.defaultStyle = e.defaultStyle || null,
+        this.multi = e.multi || !1,
+        this.styleAliases = (n = e.styleAliases || null,
+          i = {},
+          null !== n && Object.keys(n).forEach(function(t) {
+            n[t].forEach(function(e) {
+              i[String(e)] = t;
+            });
+          }),
+          i),
+        -1 === Fb.indexOf(this.kind)
+    ) throw new Ob("Unknown kind \"" + this.kind + "\" is specified for \"" + t + "\" YAML type.");
+  };
+  function $b(t, e) {
+    var n = [];
+    return t[e].forEach(function(t) {
+      var e = n.length;
+      n.forEach(function(n, i) {
+        n.tag === t.tag && n.kind === t.kind && n.multi === t.multi && (e = i);
+      }), n[e] = t;
+    }),
+      n;
+  }
+  function Pb(t) {
+    return this.extend(t);
+  }
+  Pb.prototype.extend = function(t) {
+    var e = [], n = [];
+    if (t instanceof Rb) n.push(t);
+    else if (Array.isArray(t)) n = n.concat(t);
+    else {
+      if (!t || !Array.isArray(t.implicit) && !Array.isArray(t.explicit)) {
+        throw new Ob(
+          "Schema.extend argument should be a Type, [ Type ], or a schema definition ({ implicit: [...], explicit: [...] })",
+        );
+      }
+      t.implicit && (e = e.concat(t.implicit)), t.explicit && (n = n.concat(t.explicit));
+    }
+    e.forEach(function(t) {
+      if (!(t instanceof Rb)) {
+        throw new Ob("Specified list of YAML types (or a single Type object) contains a non-Type object.");
+      }
+      if (t.loadKind && "scalar" !== t.loadKind) {
+        throw new Ob(
+          "There is a non-scalar type in the implicit list of a schema. Implicit resolving of such types is not supported.",
+        );
+      }
+      if (t.multi) {
+        throw new Ob(
+          "There is a multi type in the implicit list of a schema. Multi tags can only be listed as explicit.",
+        );
+      }
+    }),
+      n.forEach(function(t) {
+        if (!(t instanceof Rb)) {
+          throw new Ob("Specified list of YAML types (or a single Type object) contains a non-Type object.");
+        }
+      });
+    var i = Object.create(Pb.prototype);
+    return i.implicit = (this.implicit || []).concat(e),
+      i.explicit = (this.explicit || []).concat(n),
+      i.compiledImplicit = $b(i, "implicit"),
+      i.compiledExplicit = $b(i, "explicit"),
+      i.compiledTypeMap = function() {
+        var t,
+          e,
+          n = {
+            scalar: {},
+            sequence: {},
+            mapping: {},
+            fallback: {},
+            multi: { scalar: [], sequence: [], mapping: [], fallback: [] },
+          };
+        function i(t) {
+          t.multi ? (n.multi[t.kind].push(t), n.multi.fallback.push(t)) : n[t.kind][t.tag] = n.fallback[t.tag] = t;
+        }
+        for (t = 0, e = arguments.length; t < e; t += 1) arguments[t].forEach(i);
+        return n;
+      }(i.compiledImplicit, i.compiledExplicit),
+      i;
+  };
+  var Yb = new Pb({
+    explicit: [
+      new Rb("tag:yaml.org,2002:str", {
+        kind: "scalar",
+        construct: function(t) {
+          return null !== t ? t : "";
+        },
+      }),
+      new Rb("tag:yaml.org,2002:seq", {
+        kind: "sequence",
+        construct: function(t) {
+          return null !== t ? t : [];
+        },
+      }),
+      new Rb("tag:yaml.org,2002:map", {
+        kind: "mapping",
+        construct: function(t) {
+          return null !== t ? t : {};
+        },
+      }),
+    ],
+  });
+  var jb = new Rb("tag:yaml.org,2002:null", {
+    kind: "scalar",
+    resolve: function(t) {
+      if (null === t) return !0;
+      var e = t.length;
+      return 1 === e && "~" === t || 4 === e && ("null" === t || "Null" === t || "NULL" === t);
+    },
+    construct: function() {
+      return null;
+    },
+    predicate: function(t) {
+      return null === t;
+    },
+    represent: {
+      canonical: function() {
+        return "~";
+      },
+      lowercase: function() {
+        return "null";
+      },
+      uppercase: function() {
+        return "NULL";
+      },
+      camelcase: function() {
+        return "Null";
+      },
+      empty: function() {
+        return "";
+      },
+    },
+    defaultStyle: "lowercase",
+  });
+  var zb = new Rb("tag:yaml.org,2002:bool", {
+    kind: "scalar",
+    resolve: function(t) {
+      if (null === t) return !1;
+      var e = t.length;
+      return 4 === e && ("true" === t || "True" === t || "TRUE" === t)
+        || 5 === e && ("false" === t || "False" === t || "FALSE" === t);
+    },
+    construct: function(t) {
+      return "true" === t || "True" === t || "TRUE" === t;
+    },
+    predicate: function(t) {
+      return "[object Boolean]" === Object.prototype.toString.call(t);
+    },
+    represent: {
+      lowercase: function(t) {
+        return t ? "true" : "false";
+      },
+      uppercase: function(t) {
+        return t ? "TRUE" : "FALSE";
+      },
+      camelcase: function(t) {
+        return t ? "True" : "False";
+      },
+    },
+    defaultStyle: "lowercase",
+  });
+  function Ub(t) {
+    return 48 <= t && t <= 55;
+  }
+  function Wb(t) {
+    return 48 <= t && t <= 57;
+  }
+  var Hb = new Rb("tag:yaml.org,2002:int", {
+      kind: "scalar",
+      resolve: function(t) {
+        if (null === t) return !1;
+        var e, n, i = t.length, r = 0, a = !1;
+        if (!i) return !1;
+        if ("-" !== (e = t[r]) && "+" !== e || (e = t[++r]), "0" === e) {
+          if (r + 1 === i) return !0;
+          if ("b" === (e = t[++r])) {
+            for (r++; r < i; r++) {
+              if ("_" !== (e = t[r])) {
+                if ("0" !== e && "1" !== e) return !1;
+                a = !0;
+              }
+            }
+            return a && "_" !== e;
+          }
+          if ("x" === e) {
+            for (r++; r < i; r++) {
+              if ("_" !== (e = t[r])) {
+                if (!(48 <= (n = t.charCodeAt(r)) && n <= 57 || 65 <= n && n <= 70 || 97 <= n && n <= 102)) return !1;
+                a = !0;
+              }
+            }
+            return a && "_" !== e;
+          }
+          if ("o" === e) {
+            for (r++; r < i; r++) {
+              if ("_" !== (e = t[r])) {
+                if (!Ub(t.charCodeAt(r))) return !1;
+                a = !0;
+              }
+            }
+            return a && "_" !== e;
+          }
+        }
+        if ("_" === e) return !1;
+        for (; r < i; r++) {
+          if ("_" !== (e = t[r])) {
+            if (!Wb(t.charCodeAt(r))) return !1;
+            a = !0;
+          }
+        }
+        return !(!a || "_" === e);
+      },
+      construct: function(t) {
+        var e, n = t, i = 1;
+        if (
+          -1 !== n.indexOf("_") && (n = n.replace(/_/g, "")),
+            "-" !== (e = n[0]) && "+" !== e || ("-" === e && (i = -1), e = (n = n.slice(1))[0]),
+            "0" === n
+        ) return 0;
+        if ("0" === e) {
+          if ("b" === n[1]) return i * parseInt(n.slice(2), 2);
+          if ("x" === n[1]) return i * parseInt(n.slice(2), 16);
+          if ("o" === n[1]) return i * parseInt(n.slice(2), 8);
+        }
+        return i * parseInt(n, 10);
+      },
+      predicate: function(t) {
+        return "[object Number]" === Object.prototype.toString.call(t) && t % 1 == 0 && !Ab.isNegativeZero(t);
+      },
+      represent: {
+        binary: function(t) {
+          return t >= 0 ? "0b" + t.toString(2) : "-0b" + t.toString(2).slice(1);
+        },
+        octal: function(t) {
+          return t >= 0 ? "0o" + t.toString(8) : "-0o" + t.toString(8).slice(1);
+        },
+        decimal: function(t) {
+          return t.toString(10);
+        },
+        hexadecimal: function(t) {
+          return t >= 0 ? "0x" + t.toString(16).toUpperCase() : "-0x" + t.toString(16).toUpperCase().slice(1);
+        },
+      },
+      defaultStyle: "decimal",
+      styleAliases: { binary: [2, "bin"], octal: [8, "oct"], decimal: [10, "dec"], hexadecimal: [16, "hex"] },
+    }),
+    qb = new RegExp(
+      "^(?:[-+]?(?:[0-9][0-9_]*)(?:\\.[0-9_]*)?(?:[eE][-+]?[0-9]+)?|\\.[0-9_]+(?:[eE][-+]?[0-9]+)?|[-+]?\\.(?:inf|Inf|INF)|\\.(?:nan|NaN|NAN))$",
+    );
+  var Vb = /^[-+]?[0-9]+e/;
+  var Gb = new Rb("tag:yaml.org,2002:float", {
+      kind: "scalar",
+      resolve: function(t) {
+        return null !== t && !(!qb.test(t) || "_" === t[t.length - 1]);
+      },
+      construct: function(t) {
+        var e, n;
+        return n = "-" === (e = t.replace(/_/g, "").toLowerCase())[0] ? -1 : 1,
+          "+-".indexOf(e[0]) >= 0 && (e = e.slice(1)),
+          ".inf" === e
+            ? 1 === n ? Number.POSITIVE_INFINITY : Number.NEGATIVE_INFINITY
+            : ".nan" === e
+            ? NaN
+            : n * parseFloat(e, 10);
+      },
+      predicate: function(t) {
+        return "[object Number]" === Object.prototype.toString.call(t) && (t % 1 != 0 || Ab.isNegativeZero(t));
+      },
+      represent: function(t, e) {
+        var n;
+        if (isNaN(t)) {
+          switch (e) {
+            case "lowercase":
+              return ".nan";
+            case "uppercase":
+              return ".NAN";
+            case "camelcase":
+              return ".NaN";
+          }
+        } else if (Number.POSITIVE_INFINITY === t) {
+          switch (e) {
+            case "lowercase":
+              return ".inf";
+            case "uppercase":
+              return ".INF";
+            case "camelcase":
+              return ".Inf";
+          }
+        } else if (Number.NEGATIVE_INFINITY === t) {
+          switch (e) {
+            case "lowercase":
+              return "-.inf";
+            case "uppercase":
+              return "-.INF";
+            case "camelcase":
+              return "-.Inf";
+          }
+        } else if (Ab.isNegativeZero(t)) return "-0.0";
+        return n = t.toString(10), Vb.test(n) ? n.replace("e", ".e") : n;
+      },
+      defaultStyle: "lowercase",
+    }),
+    Xb = Yb.extend({ implicit: [jb, zb, Hb, Gb] }),
+    Zb = new RegExp("^([0-9][0-9][0-9][0-9])-([0-9][0-9])-([0-9][0-9])$"),
+    Qb = new RegExp(
+      "^([0-9][0-9][0-9][0-9])-([0-9][0-9]?)-([0-9][0-9]?)(?:[Tt]|[ \\t]+)([0-9][0-9]?):([0-9][0-9]):([0-9][0-9])(?:\\.([0-9]*))?(?:[ \\t]*(Z|([-+])([0-9][0-9]?)(?::([0-9][0-9]))?))?$",
+    );
+  var Kb = new Rb("tag:yaml.org,2002:timestamp", {
+    kind: "scalar",
+    resolve: function(t) {
+      return null !== t && (null !== Zb.exec(t) || null !== Qb.exec(t));
+    },
+    construct: function(t) {
+      var e, n, i, r, a, s, o, l, c = 0, h = null;
+      if (null === (e = Zb.exec(t)) && (e = Qb.exec(t)), null === e) throw new Error("Date resolve error");
+      if (n = +e[1], i = +e[2] - 1, r = +e[3], !e[4]) return new Date(Date.UTC(n, i, r));
+      if (a = +e[4], s = +e[5], o = +e[6], e[7]) {
+        for (c = e[7].slice(0, 3); c.length < 3;) c += "0";
+        c = +c;
+      }
+      return e[9] && (h = 6e4 * (60 * +e[10] + +(e[11] || 0)), "-" === e[9] && (h = -h)),
+        l = new Date(Date.UTC(n, i, r, a, s, o, c)),
+        h && l.setTime(l.getTime() - h),
+        l;
+    },
+    instanceOf: Date,
+    represent: function(t) {
+      return t.toISOString();
+    },
+  });
+  var Jb = new Rb("tag:yaml.org,2002:merge", {
+      kind: "scalar",
+      resolve: function(t) {
+        return "<<" === t || null === t;
+      },
+    }),
+    t_ = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=\n\r";
+  var e_ = new Rb("tag:yaml.org,2002:binary", {
+      kind: "scalar",
+      resolve: function(t) {
+        if (null === t) return !1;
+        var e, n, i = 0, r = t.length, a = t_;
+        for (n = 0; n < r; n++) {
+          if (!((e = a.indexOf(t.charAt(n))) > 64)) {
+            if (e < 0) return !1;
+            i += 6;
+          }
+        }
+        return i % 8 == 0;
+      },
+      construct: function(t) {
+        var e, n, i = t.replace(/[\r\n=]/g, ""), r = i.length, a = t_, s = 0, o = [];
+        for (e = 0; e < r; e++) {
+          e % 4 == 0 && e && (o.push(s >> 16 & 255), o.push(s >> 8 & 255), o.push(255 & s)),
+            s = s << 6 | a.indexOf(i.charAt(e));
+        }
+        return 0 === (n = r % 4 * 6)
+          ? (o.push(s >> 16 & 255), o.push(s >> 8 & 255), o.push(255 & s))
+          : 18 === n
+          ? (o.push(s >> 10 & 255), o.push(s >> 2 & 255))
+          : 12 === n && o.push(s >> 4 & 255),
+          new Uint8Array(o);
+      },
+      predicate: function(t) {
+        return "[object Uint8Array]" === Object.prototype.toString.call(t);
+      },
+      represent: function(t) {
+        var e, n, i = "", r = 0, a = t.length, s = t_;
+        for (e = 0; e < a; e++) {
+          e % 3 == 0 && e && (i += s[r >> 18 & 63], i += s[r >> 12 & 63], i += s[r >> 6 & 63], i += s[63 & r]),
+            r = (r << 8) + t[e];
+        }
+        return 0 === (n = a % 3)
+          ? (i += s[r >> 18 & 63], i += s[r >> 12 & 63], i += s[r >> 6 & 63], i += s[63 & r])
+          : 2 === n
+          ? (i += s[r >> 10 & 63], i += s[r >> 4 & 63], i += s[r << 2 & 63], i += s[64])
+          : 1 === n && (i += s[r >> 2 & 63], i += s[r << 4 & 63], i += s[64], i += s[64]),
+          i;
+      },
+    }),
+    n_ = Object.prototype.hasOwnProperty,
+    i_ = Object.prototype.toString;
+  var r_ = new Rb("tag:yaml.org,2002:omap", {
+      kind: "sequence",
+      resolve: function(t) {
+        if (null === t) return !0;
+        var e, n, i, r, a, s = [], o = t;
+        for (e = 0, n = o.length; e < n; e += 1) {
+          if (i = o[e], a = !1, "[object Object]" !== i_.call(i)) return !1;
+          for (r in i) {
+            if (n_.call(i, r)) {
+              if (a) return !1;
+              a = !0;
+            }
+          }
+          if (!a) return !1;
+          if (-1 !== s.indexOf(r)) return !1;
+          s.push(r);
+        }
+        return !0;
+      },
+      construct: function(t) {
+        return null !== t ? t : [];
+      },
+    }),
+    a_ = Object.prototype.toString;
+  var s_ = new Rb("tag:yaml.org,2002:pairs", {
+      kind: "sequence",
+      resolve: function(t) {
+        if (null === t) return !0;
+        var e, n, i, r, a, s = t;
+        for (a = new Array(s.length), e = 0, n = s.length; e < n; e += 1) {
+          if (i = s[e], "[object Object]" !== a_.call(i)) return !1;
+          if (1 !== (r = Object.keys(i)).length) return !1;
+          a[e] = [r[0], i[r[0]]];
+        }
+        return !0;
+      },
+      construct: function(t) {
+        if (null === t) return [];
+        var e, n, i, r, a, s = t;
+        for (a = new Array(s.length), e = 0, n = s.length; e < n; e += 1) {
+          i = s[e], r = Object.keys(i), a[e] = [r[0], i[r[0]]];
+        }
+        return a;
+      },
+    }),
+    o_ = Object.prototype.hasOwnProperty;
+  var l_ = new Rb("tag:yaml.org,2002:set", {
+      kind: "mapping",
+      resolve: function(t) {
+        if (null === t) return !0;
+        var e, n = t;
+        for (e in n) if (o_.call(n, e) && null !== n[e]) return !1;
+        return !0;
+      },
+      construct: function(t) {
+        return null !== t ? t : {};
+      },
+    }),
+    c_ = Xb.extend({ implicit: [Kb, Jb], explicit: [e_, r_, s_, l_] }),
+    h_ = Object.prototype.hasOwnProperty,
+    u_ = 1,
+    d_ = 2,
+    p_ = 3,
+    f_ = 4,
+    g_ = 1,
+    y_ = 2,
+    m_ = 3,
+    b_ =
+      /[\x00-\x08\x0B\x0C\x0E-\x1F\x7F-\x84\x86-\x9F\uFFFE\uFFFF]|[\uD800-\uDBFF](?![\uDC00-\uDFFF])|(?:[^\uD800-\uDBFF]|^)[\uDC00-\uDFFF]/,
+    __ = /[\x85\u2028\u2029]/,
+    x_ = /[,\[\]\{\}]/,
+    v_ = /^(?:!|!!|![a-z\-]+!)$/i,
+    k_ = /^(?:!|[^,\[\]\{\}])(?:%[0-9a-f]{2}|[0-9a-z\-#;\/\?:@&=\+\$,_\.!~\*'\(\)\[\]])*$/i;
+  function w_(t) {
+    return Object.prototype.toString.call(t);
+  }
+  function T_(t) {
+    return 10 === t || 13 === t;
+  }
+  function C_(t) {
+    return 9 === t || 32 === t;
+  }
+  function E_(t) {
+    return 9 === t || 32 === t || 10 === t || 13 === t;
+  }
+  function S_(t) {
+    return 44 === t || 91 === t || 93 === t || 123 === t || 125 === t;
+  }
+  function A_(t) {
+    var e;
+    return 48 <= t && t <= 57 ? t - 48 : 97 <= (e = 32 | t) && e <= 102 ? e - 97 + 10 : -1;
+  }
+  function D_(t) {
+    return 48 === t
+      ? "\0"
+      : 97 === t
+      ? ""
+      : 98 === t
+      ? "\b"
+      : 116 === t || 9 === t
+      ? "\t"
+      : 110 === t
+      ? "\n"
+      : 118 === t
+      ? "\v"
+      : 102 === t
+      ? "\f"
+      : 114 === t
+      ? "\r"
+      : 101 === t
+      ? ""
+      : 32 === t
+      ? " "
+      : 34 === t
+      ? "\""
+      : 47 === t
+      ? "/"
+      : 92 === t
+      ? "\\"
+      : 78 === t
+      ? "…"
+      : 95 === t
+      ? " "
+      : 76 === t
+      ? "\u2028"
+      : 80 === t
+      ? "\u2029"
+      : "";
+  }
+  function L_(t) {
+    return t <= 65535
+      ? String.fromCharCode(t)
+      : String.fromCharCode(55296 + (t - 65536 >> 10), 56320 + (t - 65536 & 1023));
+  }
+  for (var O_ = new Array(256), N_ = new Array(256), M_ = 0; M_ < 256; M_++) O_[M_] = D_(M_) ? 1 : 0, N_[M_] = D_(M_);
+  function B_(t, e) {
+    this.input = t,
+      this.filename = e.filename || null,
+      this.schema = e.schema || c_,
+      this.onWarning = e.onWarning || null,
+      this.legacy = e.legacy || !1,
+      this.json = e.json || !1,
+      this.listener = e.listener || null,
+      this.implicitTypes = this.schema.compiledImplicit,
+      this.typeMap = this.schema.compiledTypeMap,
+      this.length = t.length,
+      this.position = 0,
+      this.line = 0,
+      this.lineStart = 0,
+      this.lineIndent = 0,
+      this.firstTabInLine = -1,
+      this.documents = [];
+  }
+  function I_(t, e) {
+    var n = {
+      name: t.filename,
+      buffer: t.input.slice(0, -1),
+      position: t.position,
+      line: t.line,
+      column: t.position - t.lineStart,
+    };
+    return n.snippet = Bb(n), new Ob(e, n);
+  }
+  function F_(t, e) {
+    throw I_(t, e);
+  }
+  function R_(t, e) {
+    t.onWarning && t.onWarning.call(null, I_(t, e));
+  }
+  var $_ = {
+    YAML: function(t, e, n) {
+      var i, r, a;
+      null !== t.version && F_(t, "duplication of %YAML directive"),
+        1 !== n.length && F_(t, "YAML directive accepts exactly one argument"),
+        null === (i = /^([0-9]+)\.([0-9]+)$/.exec(n[0])) && F_(t, "ill-formed argument of the YAML directive"),
+        r = parseInt(i[1], 10),
+        a = parseInt(i[2], 10),
+        1 !== r && F_(t, "unacceptable YAML version of the document"),
+        t.version = n[0],
+        t.checkLineBreaks = a < 2,
+        1 !== a && 2 !== a && R_(t, "unsupported YAML version of the document");
+    },
+    TAG: function(t, e, n) {
+      var i, r;
+      2 !== n.length && F_(t, "TAG directive accepts exactly two arguments"),
+        i = n[0],
+        r = n[1],
+        v_.test(i) || F_(t, "ill-formed tag handle (first argument) of the TAG directive"),
+        h_.call(t.tagMap, i) && F_(t, "there is a previously declared suffix for \"" + i + "\" tag handle"),
+        k_.test(r) || F_(t, "ill-formed tag prefix (second argument) of the TAG directive");
+      try {
+        r = decodeURIComponent(r);
+      } catch (e) {
+        F_(t, "tag prefix is malformed: " + r);
+      }
+      t.tagMap[i] = r;
+    },
+  };
+  function P_(t, e, n, i) {
+    var r, a, s, o;
+    if (e < n) {
+      if (o = t.input.slice(e, n), i) {
+        for (r = 0, a = o.length; r < a; r += 1) {
+          9 === (s = o.charCodeAt(r)) || 32 <= s && s <= 1114111 || F_(t, "expected valid JSON character");
+        }
+      } else b_.test(o) && F_(t, "the stream contains non-printable characters");
+      t.result += o;
+    }
+  }
+  function Y_(t, e, n, i) {
+    var r, a, s, o;
+    for (
+      Ab.isObject(n) || F_(t, "cannot merge mappings; the provided source object is unacceptable"),
+        s = 0,
+        o = (r = Object.keys(n)).length;
+      s < o;
+      s += 1
+    ) a = r[s], h_.call(e, a) || (e[a] = n[a], i[a] = !0);
+  }
+  function j_(t, e, n, i, r, a, s, o, l) {
+    var c, h;
+    if (Array.isArray(r)) {
+      for (c = 0, h = (r = Array.prototype.slice.call(r)).length; c < h; c += 1) {
+        Array.isArray(r[c]) && F_(t, "nested arrays are not supported inside keys"),
+          "object" == typeof r && "[object Object]" === w_(r[c]) && (r[c] = "[object Object]");
+      }
+    }
+    if (
+      "object" == typeof r && "[object Object]" === w_(r) && (r = "[object Object]"),
+        r = String(r),
+        null === e && (e = {}),
+        "tag:yaml.org,2002:merge" === i
+    ) {
+      if (Array.isArray(a)) for (c = 0, h = a.length; c < h; c += 1) Y_(t, e, a[c], n);
+      else Y_(t, e, a, n);
+    } else {t.json || h_.call(n, r) || !h_.call(e, r)
+        || (t.line = s || t.line,
+          t.lineStart = o || t.lineStart,
+          t.position = l || t.position,
+          F_(t, "duplicated mapping key")),
+        "__proto__" === r
+          ? Object.defineProperty(e, r, { configurable: !0, enumerable: !0, writable: !0, value: a })
+          : e[r] = a,
+        delete n[r];}
+    return e;
+  }
+  function z_(t) {
+    var e;
+    10 === (e = t.input.charCodeAt(t.position))
+      ? t.position++
+      : 13 === e
+      ? (t.position++, 10 === t.input.charCodeAt(t.position) && t.position++)
+      : F_(t, "a line break is expected"),
+      t.line += 1,
+      t.lineStart = t.position,
+      t.firstTabInLine = -1;
+  }
+  function U_(t, e, n) {
+    for (var i = 0, r = t.input.charCodeAt(t.position); 0 !== r;) {
+      for (; C_(r);) {
+        9 === r && -1 === t.firstTabInLine && (t.firstTabInLine = t.position), r = t.input.charCodeAt(++t.position);
+      }
+      if (e && 35 === r) {
+        do {
+          r = t.input.charCodeAt(++t.position);
+        } while (10 !== r && 13 !== r && 0 !== r);
+      }
+      if (!T_(r)) break;
+      for (z_(t), r = t.input.charCodeAt(t.position), i++, t.lineIndent = 0; 32 === r;) {
+        t.lineIndent++, r = t.input.charCodeAt(++t.position);
+      }
+    }
+    return -1 !== n && 0 !== i && t.lineIndent < n && R_(t, "deficient indentation"), i;
+  }
+  function W_(t) {
+    var e, n = t.position;
+    return !(45 !== (e = t.input.charCodeAt(n)) && 46 !== e || e !== t.input.charCodeAt(n + 1)
+      || e !== t.input.charCodeAt(n + 2) || (n += 3, 0 !== (e = t.input.charCodeAt(n)) && !E_(e)));
+  }
+  function H_(t, e) {
+    1 === e ? t.result += " " : e > 1 && (t.result += Ab.repeat("\n", e - 1));
+  }
+  function q_(t, e) {
+    var n, i, r = t.tag, a = t.anchor, s = [], o = !1;
+    if (-1 !== t.firstTabInLine) return !1;
+    for (
+      null !== t.anchor && (t.anchorMap[t.anchor] = s), i = t.input.charCodeAt(t.position);
+      0 !== i
+      && (-1 !== t.firstTabInLine
+        && (t.position = t.firstTabInLine, F_(t, "tab characters must not be used in indentation")),
+        45 === i)
+      && E_(t.input.charCodeAt(t.position + 1));
+    ) {
+      if (o = !0, t.position++, U_(t, !0, -1) && t.lineIndent <= e) s.push(null), i = t.input.charCodeAt(t.position);
+      else if (
+        n = t.line,
+          X_(t, e, p_, !1, !0),
+          s.push(t.result),
+          U_(t, !0, -1),
+          i = t.input.charCodeAt(t.position),
+          (t.line === n || t.lineIndent > e) && 0 !== i
+      ) F_(t, "bad indentation of a sequence entry");
+      else if (t.lineIndent < e) break;
+    }
+    return !!o && (t.tag = r, t.anchor = a, t.kind = "sequence", t.result = s, !0);
+  }
+  function V_(t) {
+    var e, n, i, r, a = !1, s = !1;
+    if (33 !== (r = t.input.charCodeAt(t.position))) return !1;
+    if (
+      null !== t.tag && F_(t, "duplication of a tag property"),
+        60 === (r = t.input.charCodeAt(++t.position))
+          ? (a = !0, r = t.input.charCodeAt(++t.position))
+          : 33 === r
+          ? (s = !0, n = "!!", r = t.input.charCodeAt(++t.position))
+          : n = "!",
+        e = t.position,
+        a
+    ) {
+      do {
+        r = t.input.charCodeAt(++t.position);
+      } while (0 !== r && 62 !== r);
+      t.position < t.length
+        ? (i = t.input.slice(e, t.position), r = t.input.charCodeAt(++t.position))
+        : F_(t, "unexpected end of the stream within a verbatim tag");
+    } else {
+      for (; 0 !== r && !E_(r);) {
+        33 === r
+        && (s
+          ? F_(t, "tag suffix cannot contain exclamation marks")
+          : (n = t.input.slice(e - 1, t.position + 1),
+            v_.test(n) || F_(t, "named tag handle cannot contain such characters"),
+            s = !0,
+            e = t.position + 1)), r = t.input.charCodeAt(++t.position);
+      }
+      i = t.input.slice(e, t.position), x_.test(i) && F_(t, "tag suffix cannot contain flow indicator characters");
+    }
+    i && !k_.test(i) && F_(t, "tag name cannot contain such characters: " + i);
+    try {
+      i = decodeURIComponent(i);
+    } catch (e) {
+      F_(t, "tag name is malformed: " + i);
+    }
+    return a
+      ? t.tag = i
+      : h_.call(t.tagMap, n)
+      ? t.tag = t.tagMap[n] + i
+      : "!" === n
+      ? t.tag = "!" + i
+      : "!!" === n
+      ? t.tag = "tag:yaml.org,2002:" + i
+      : F_(t, "undeclared tag handle \"" + n + "\""),
+      !0;
+  }
+  function G_(t) {
+    var e, n;
+    if (38 !== (n = t.input.charCodeAt(t.position))) return !1;
+    for (
+      null !== t.anchor && F_(t, "duplication of an anchor property"),
+        n = t.input.charCodeAt(++t.position),
+        e = t.position;
+      0 !== n && !E_(n) && !S_(n);
+    ) n = t.input.charCodeAt(++t.position);
+    return t.position === e && F_(t, "name of an anchor node must contain at least one character"),
+      t.anchor = t.input.slice(e, t.position),
+      !0;
+  }
+  function X_(t, e, n, i, r) {
+    var a, s, o, l, c, h, u, d, p, f = 1, g = !1, y = !1;
+    if (
+      null !== t.listener && t.listener("open", t),
+        t.tag = null,
+        t.anchor = null,
+        t.kind = null,
+        t.result = null,
+        a = s = o = f_ === n || p_ === n,
+        i && U_(t, !0, -1)
+        && (g = !0, t.lineIndent > e ? f = 1 : t.lineIndent === e ? f = 0 : t.lineIndent < e && (f = -1)),
+        1 === f
+    ) {
+      for (; V_(t) || G_(t);) {
+        U_(t, !0, -1)
+          ? (g = !0, o = a, t.lineIndent > e ? f = 1 : t.lineIndent === e ? f = 0 : t.lineIndent < e && (f = -1))
+          : o = !1;
+      }
+    }
+    if (
+      o && (o = g || r),
+        1 !== f && f_ !== n || (d = u_ === n || d_ === n ? e : e + 1,
+          p = t.position - t.lineStart,
+          1 === f
+            ? o && (q_(t, p) || function(t, e, n) {
+                    var i,
+                      r,
+                      a,
+                      s,
+                      o,
+                      l,
+                      c,
+                      h = t.tag,
+                      u = t.anchor,
+                      d = {},
+                      p = Object.create(null),
+                      f = null,
+                      g = null,
+                      y = null,
+                      m = !1,
+                      b = !1;
+                    if (-1 !== t.firstTabInLine) return !1;
+                    for (
+                      null !== t.anchor && (t.anchorMap[t.anchor] = d), c = t.input.charCodeAt(t.position);
+                      0 !== c;
+                    ) {
+                      if (
+                        m || -1 === t.firstTabInLine
+                        || (t.position = t.firstTabInLine, F_(t, "tab characters must not be used in indentation")),
+                          i = t.input.charCodeAt(t.position + 1),
+                          a = t.line,
+                          63 !== c && 58 !== c || !E_(i)
+                      ) {
+                        if (s = t.line, o = t.lineStart, l = t.position, !X_(t, n, d_, !1, !0)) break;
+                        if (t.line === a) {
+                          for (c = t.input.charCodeAt(t.position); C_(c);) c = t.input.charCodeAt(++t.position);
+                          if (58 === c) {
+                            E_(c = t.input.charCodeAt(++t.position))
+                            || F_(
+                              t,
+                              "a whitespace character is expected after the key-value separator within a block mapping",
+                            ),
+                              m && (j_(t, d, p, f, g, null, s, o, l), f = g = y = null),
+                              b = !0,
+                              m = !1,
+                              r = !1,
+                              f = t.tag,
+                              g = t.result;
+                          } else {
+                            if (!b) return t.tag = h, t.anchor = u, !0;
+                            F_(t, "can not read an implicit mapping pair; a colon is missed");
+                          }
+                        } else {
+                          if (!b) return t.tag = h, t.anchor = u, !0;
+                          F_(t, "can not read a block mapping entry; a multiline key may not be an implicit key");
+                        }
+                      } else {63 === c
+                          ? (m && (j_(t, d, p, f, g, null, s, o, l), f = g = y = null), b = !0, m = !0, r = !0)
+                          : m
+                          ? (m = !1, r = !0)
+                          : F_(
+                            t,
+                            "incomplete explicit mapping pair; a key node is missed; or followed by a non-tabulated empty line",
+                          ),
+                          t.position += 1,
+                          c = i;}
+                      if (
+                        (t.line === a || t.lineIndent > e)
+                        && (m && (s = t.line, o = t.lineStart, l = t.position),
+                          X_(t, e, f_, !0, r) && (m ? g = t.result : y = t.result),
+                          m || (j_(t, d, p, f, g, y, s, o, l), f = g = y = null),
+                          U_(t, !0, -1),
+                          c = t.input.charCodeAt(t.position)), (t.line === a || t.lineIndent > e) && 0 !== c
+                      ) F_(t, "bad indentation of a mapping entry");
+                      else if (t.lineIndent < e) break;
+                    }
+                    return m && j_(t, d, p, f, g, null, s, o, l),
+                      b && (t.tag = h, t.anchor = u, t.kind = "mapping", t.result = d),
+                      b;
+                  }(t, p, d)) || function(t, e) {
+                var n, i, r, a, s, o, l, c, h, u, d, p, f = !0, g = t.tag, y = t.anchor, m = Object.create(null);
+                if (91 === (p = t.input.charCodeAt(t.position))) s = 93, c = !1, a = [];
+                else {
+                  if (123 !== p) return !1;
+                  s = 125, c = !0, a = {};
+                }
+                for (null !== t.anchor && (t.anchorMap[t.anchor] = a), p = t.input.charCodeAt(++t.position); 0 !== p;) {
+                  if (U_(t, !0, e), (p = t.input.charCodeAt(t.position)) === s) {
+                    return t.position++, t.tag = g, t.anchor = y, t.kind = c ? "mapping" : "sequence", t.result = a, !0;
+                  }
+                  f
+                    ? 44 === p && F_(t, "expected the node content, but found ','")
+                    : F_(t, "missed comma between flow collection entries"),
+                    d = null,
+                    o = l = !1,
+                    63 === p && E_(t.input.charCodeAt(t.position + 1)) && (o = l = !0, t.position++, U_(t, !0, e)),
+                    n = t.line,
+                    i = t.lineStart,
+                    r = t.position,
+                    X_(t, e, u_, !1, !0),
+                    u = t.tag,
+                    h = t.result,
+                    U_(t, !0, e),
+                    p = t.input.charCodeAt(t.position),
+                    !l && t.line !== n || 58 !== p
+                    || (o = !0, p = t.input.charCodeAt(++t.position), U_(t, !0, e), X_(t, e, u_, !1, !0), d = t.result),
+                    c ? j_(t, a, m, u, h, d, n, i, r) : o ? a.push(j_(t, null, m, u, h, d, n, i, r)) : a.push(h),
+                    U_(t, !0, e),
+                    44 === (p = t.input.charCodeAt(t.position))
+                      ? (f = !0, p = t.input.charCodeAt(++t.position))
+                      : f = !1;
+                }
+                F_(t, "unexpected end of the stream within a flow collection");
+              }(t, d)
+              ? y = !0
+              : (s && function(t, e) {
+                      var n, i, r, a, s, o = g_, l = !1, c = !1, h = e, u = 0, d = !1;
+                      if (124 === (a = t.input.charCodeAt(t.position))) i = !1;
+                      else {
+                        if (62 !== a) return !1;
+                        i = !0;
+                      }
+                      for (t.kind = "scalar", t.result = ""; 0 !== a;) {
+                        if (43 === (a = t.input.charCodeAt(++t.position)) || 45 === a) {
+                          g_ === o
+                            ? o = 43 === a ? m_ : y_
+                            : F_(t, "repeat of a chomping mode identifier");
+                        } else {
+                          if (!((r = 48 <= (s = a) && s <= 57 ? s - 48 : -1) >= 0)) break;
+                          0 === r
+                            ? F_(t, "bad explicit indentation width of a block scalar; it cannot be less than one")
+                            : c
+                            ? F_(t, "repeat of an indentation width identifier")
+                            : (h = e + r - 1, c = !0);
+                        }
+                      }
+                      if (C_(a)) {
+                        do {
+                          a = t.input.charCodeAt(++t.position);
+                        } while (C_(a));
+                        if (35 === a) {
+                          do {
+                            a = t.input.charCodeAt(++t.position);
+                          } while (!T_(a) && 0 !== a);
+                        }
+                      }
+                      for (; 0 !== a;) {
+                        for (
+                          z_(t), t.lineIndent = 0, a = t.input.charCodeAt(t.position);
+                          (!c || t.lineIndent < h) && 32 === a;
+                        ) t.lineIndent++, a = t.input.charCodeAt(++t.position);
+                        if (!c && t.lineIndent > h && (h = t.lineIndent), T_(a)) u++;
+                        else {
+                          if (t.lineIndent < h) {
+                            o === m_ ? t.result += Ab.repeat("\n", l ? 1 + u : u) : o === g_ && l && (t.result += "\n");
+                            break;
+                          }
+                          for (
+                            i
+                              ? C_(a)
+                                ? (d = !0, t.result += Ab.repeat("\n", l ? 1 + u : u))
+                                : d
+                                ? (d = !1, t.result += Ab.repeat("\n", u + 1))
+                                : 0 === u
+                                ? l && (t.result += " ")
+                                : t.result += Ab.repeat("\n", u)
+                              : t.result += Ab.repeat("\n", l ? 1 + u : u),
+                              l = !0,
+                              c = !0,
+                              u = 0,
+                              n = t.position;
+                            !T_(a) && 0 !== a;
+                          ) a = t.input.charCodeAt(++t.position);
+                          P_(t, n, t.position, !1);
+                        }
+                      }
+                      return !0;
+                    }(t, d)
+                  || function(t, e) {
+                    var n, i, r;
+                    if (39 !== (n = t.input.charCodeAt(t.position))) return !1;
+                    for (
+                      t.kind = "scalar", t.result = "", t.position++, i = r = t.position;
+                      0 !== (n = t.input.charCodeAt(t.position));
+                    ) {
+                      if (39 === n) {
+                        if (P_(t, i, t.position, !0), 39 !== (n = t.input.charCodeAt(++t.position))) return !0;
+                        i = t.position, t.position++, r = t.position;
+                      } else {T_(n)
+                          ? (P_(t, i, r, !0), H_(t, U_(t, !1, e)), i = r = t.position)
+                          : t.position === t.lineStart && W_(t)
+                          ? F_(t, "unexpected end of the document within a single quoted scalar")
+                          : (t.position++, r = t.position);}
+                    }
+                    F_(t, "unexpected end of the stream within a single quoted scalar");
+                  }(t, d) || function(t, e) {
+                  var n, i, r, a, s, o, l;
+                  if (34 !== (o = t.input.charCodeAt(t.position))) return !1;
+                  for (
+                    t.kind = "scalar", t.result = "", t.position++, n = i = t.position;
+                    0 !== (o = t.input.charCodeAt(t.position));
+                  ) {
+                    if (34 === o) return P_(t, n, t.position, !0), t.position++, !0;
+                    if (92 === o) {
+                      if (P_(t, n, t.position, !0), T_(o = t.input.charCodeAt(++t.position))) U_(t, !1, e);
+                      else if (o < 256 && O_[o]) t.result += N_[o], t.position++;
+                      else if ((s = 120 === (l = o) ? 2 : 117 === l ? 4 : 85 === l ? 8 : 0) > 0) {
+                        for (r = s, a = 0; r > 0; r--) {
+                          (s = A_(o = t.input.charCodeAt(++t.position))) >= 0
+                            ? a = (a << 4) + s
+                            : F_(t, "expected hexadecimal character");
+                        }
+                        t.result += L_(a), t.position++;
+                      } else F_(t, "unknown escape sequence");
+                      n = i = t.position;
+                    } else {T_(o)
+                        ? (P_(t, n, i, !0), H_(t, U_(t, !1, e)), n = i = t.position)
+                        : t.position === t.lineStart && W_(t)
+                        ? F_(t, "unexpected end of the document within a double quoted scalar")
+                        : (t.position++, i = t.position);}
+                  }
+                  F_(t, "unexpected end of the stream within a double quoted scalar");
+                }(t, d)
+                ? y = !0
+                : !function(t) {
+                    var e, n, i;
+                    if (42 !== (i = t.input.charCodeAt(t.position))) return !1;
+                    for (i = t.input.charCodeAt(++t.position), e = t.position; 0 !== i && !E_(i) && !S_(i);) {
+                      i = t.input.charCodeAt(++t.position);
+                    }
+                    return t.position === e && F_(t, "name of an alias node must contain at least one character"),
+                      n = t.input.slice(e, t.position),
+                      h_.call(t.anchorMap, n) || F_(t, "unidentified alias \"" + n + "\""),
+                      t.result = t.anchorMap[n],
+                      U_(t, !0, -1),
+                      !0;
+                  }(t)
+                ? function(t, e, n) {
+                  var i, r, a, s, o, l, c, h, u = t.kind, d = t.result;
+                  if (
+                    E_(h = t.input.charCodeAt(t.position)) || S_(h) || 35 === h || 38 === h || 42 === h || 33 === h
+                    || 124 === h || 62 === h || 39 === h || 34 === h || 37 === h || 64 === h || 96 === h
+                  ) return !1;
+                  if ((63 === h || 45 === h) && (E_(i = t.input.charCodeAt(t.position + 1)) || n && S_(i))) return !1;
+                  for (t.kind = "scalar", t.result = "", r = a = t.position, s = !1; 0 !== h;) {
+                    if (58 === h) {
+                      if (E_(i = t.input.charCodeAt(t.position + 1)) || n && S_(i)) break;
+                      else if (35 === h) {
+                        if (E_(t.input.charCodeAt(t.position - 1))) break;
+                        else {
+                          if (t.position === t.lineStart && W_(t) || n && S_(h)) break;
+                          if (T_(h)) {
+                            if (o = t.line, l = t.lineStart, c = t.lineIndent, U_(t, !1, -1), t.lineIndent >= e) {
+                              s = !0, h = t.input.charCodeAt(t.position);
+                              continue;
+                            }
+                            t.position = a, t.line = o, t.lineStart = l, t.lineIndent = c;
+                            break;
+                          }
+                        }
+                      }
+                    }
+                    s && (P_(t, r, a, !1), H_(t, t.line - o), r = a = t.position, s = !1),
+                      C_(h) || (a = t.position + 1),
+                      h = t.input.charCodeAt(++t.position);
+                  }
+                  return P_(t, r, a, !1), !!t.result || (t.kind = u, t.result = d, !1);
+                }(t, d, u_ === n) && (y = !0, null === t.tag && (t.tag = "?"))
+                : (y = !0, null === t.tag && null === t.anchor || F_(t, "alias node should not have any properties")),
+                null !== t.anchor && (t.anchorMap[t.anchor] = t.result))
+            : 0 === f && (y = o && q_(t, p))),
+        null === t.tag
+    ) null !== t.anchor && (t.anchorMap[t.anchor] = t.result);
+    else if ("?" === t.tag) {
+      for (
+        null !== t.result && "scalar" !== t.kind
+        && F_(t, "unacceptable node kind for !<?> tag; it should be \"scalar\", not \"" + t.kind + "\""),
+          l = 0,
+          c = t.implicitTypes.length;
+        l < c;
+        l += 1
+      ) {
+        if ((u = t.implicitTypes[l]).resolve(t.result)) {
+          t.result = u.construct(t.result), t.tag = u.tag, null !== t.anchor && (t.anchorMap[t.anchor] = t.result);
+          break;
+        }
+      }
+    } else if ("!" !== t.tag) {
+      if (h_.call(t.typeMap[t.kind || "fallback"], t.tag)) u = t.typeMap[t.kind || "fallback"][t.tag];
+      else {for (u = null, l = 0, c = (h = t.typeMap.multi[t.kind || "fallback"]).length; l < c; l += 1) {
+          if (t.tag.slice(0, h[l].tag.length) === h[l].tag) {
+            u = h[l];
+            break;
+          }
+        }}
+      u || F_(t, "unknown tag !<" + t.tag + ">"),
+        null !== t.result && u.kind !== t.kind
+        && F_(
+          t,
+          "unacceptable node kind for !<" + t.tag + "> tag; it should be \"" + u.kind + "\", not \"" + t.kind + "\"",
+        ),
+        u.resolve(t.result, t.tag)
+          ? (t.result = u.construct(t.result, t.tag), null !== t.anchor && (t.anchorMap[t.anchor] = t.result))
+          : F_(t, "cannot resolve a node with !<" + t.tag + "> explicit tag");
+    }
+    return null !== t.listener && t.listener("close", t), null !== t.tag || null !== t.anchor || y;
+  }
+  function Z_(t) {
+    var e, n, i, r, a = t.position, s = !1;
+    for (
+      t.version = null, t.checkLineBreaks = t.legacy, t.tagMap = Object.create(null), t.anchorMap = Object.create(null);
+      0 !== (r = t.input.charCodeAt(t.position))
+      && (U_(t, !0, -1), r = t.input.charCodeAt(t.position), !(t.lineIndent > 0 || 37 !== r));
+    ) {
+      for (s = !0, r = t.input.charCodeAt(++t.position), e = t.position; 0 !== r && !E_(r);) {
+        r = t.input.charCodeAt(
+          ++t.position,
+        );
+      }
+      for (
+        i = [],
+          (n = t.input.slice(e, t.position)).length < 1
+          && F_(t, "directive name must not be less than one character in length");
+        0 !== r;
+      ) {
+        for (; C_(r);) r = t.input.charCodeAt(++t.position);
+        if (35 === r) {
+          do {
+            r = t.input.charCodeAt(++t.position);
+          } while (0 !== r && !T_(r));
+          break;
+        }
+        if (T_(r)) break;
+        for (e = t.position; 0 !== r && !E_(r);) r = t.input.charCodeAt(++t.position);
+        i.push(t.input.slice(e, t.position));
+      }
+      0 !== r && z_(t), h_.call($_, n) ? $_[n](t, n, i) : R_(t, "unknown document directive \"" + n + "\"");
+    }
+    U_(t, !0, -1),
+      0 === t.lineIndent && 45 === t.input.charCodeAt(t.position) && 45 === t.input.charCodeAt(t.position + 1)
+        && 45 === t.input.charCodeAt(t.position + 2)
+        ? (t.position += 3, U_(t, !0, -1))
+        : s && F_(t, "directives end mark is expected"),
+      X_(t, t.lineIndent - 1, f_, !1, !0),
+      U_(t, !0, -1),
+      t.checkLineBreaks && __.test(t.input.slice(a, t.position))
+      && R_(t, "non-ASCII line breaks are interpreted as content"),
+      t.documents.push(t.result),
+      t.position === t.lineStart && W_(t)
+        ? 46 === t.input.charCodeAt(t.position) && (t.position += 3, U_(t, !0, -1))
+        : t.position < t.length - 1 && F_(t, "end of the stream or a document separator is expected");
+  }
+  function Q_(t, e) {
+    e = e || {},
+      0 !== (t = String(t)).length
+      && (10 !== t.charCodeAt(t.length - 1) && 13 !== t.charCodeAt(t.length - 1) && (t += "\n"),
+        65279 === t.charCodeAt(0) && (t = t.slice(1)));
+    var n = new B_(t, e), i = t.indexOf("\0");
+    for (
+      -1 !== i && (n.position = i, F_(n, "null byte is not allowed in input")), n.input += "\0";
+      32 === n.input.charCodeAt(n.position);
+    ) n.lineIndent += 1, n.position += 1;
+    for (; n.position < n.length - 1;) Z_(n);
+    return n.documents;
+  }
+  var K_ = function(t, e, n) {
+      null !== e && "object" == typeof e && void 0 === n && (n = e, e = null);
+      var i = Q_(t, n);
+      if ("function" != typeof e) return i;
+      for (var r = 0, a = i.length; r < a; r += 1) e(i[r]);
+    },
+    J_ = Yb,
+    tx = {
+      loadAll: K_,
+      load: function(t, e) {
+        var n = Q_(t, e);
+        if (0 !== n.length) {
+          if (1 === n.length) return n[0];
+          throw new Ob("expected a single document in the stream, but found more");
+        }
+      },
+    }.load;
+  const ex = /^-{3}\s*[\n\r](.*?)[\n\r]-{3}\s*[\n\r]+/s;
+  const nx = /%{2}{\s*(?:(\w+)\s*:|(\w+))\s*(?:(\w+)|((?:(?!}%{2}).|\r?\n)*))?\s*(?:}%{2})?/gi,
+    ix = /\s*%%.*\n/gm,
+    rx = {},
+    ax = function(t, e) {
+      t = t.replace(ex, "").replace(nx, "").replace(ix, "\n");
+      for (const [n, { detector: i }] of Object.entries(rx)) if (i(t, e)) return n;
+      throw new Error(`No diagram type detected for text: ${t}`);
+    },
+    sx = (t, e, n) => {
+      if (rx[t]) throw new Error(`Detector with key ${t} already exists`);
+      rx[t] = { detector: e, loader: n }, tb.debug(`Detector with key ${t} added${n ? " with loader" : ""}`);
+    },
+    ox = function(t, e, n) {
+      const { depth: i, clobber: r } = Object.assign({ depth: 2, clobber: !1 }, n);
+      return Array.isArray(e) && !Array.isArray(t)
+        ? (e.forEach(e => ox(t, e, n)), t)
+        : Array.isArray(e) && Array.isArray(t)
+        ? (e.forEach(e => {
+          t.includes(e) || t.push(e);
+        }),
+          t)
+        : void 0 === t || i <= 0
+        ? null != t && "object" == typeof t && "object" == typeof e ? Object.assign(t, e) : e
+        : (void 0 !== e && "object" == typeof t && "object" == typeof e && Object.keys(e).forEach(n => {
+          "object" != typeof e[n] || void 0 !== t[n] && "object" != typeof t[n]
+            ? (r || "object" != typeof t[n] && "object" != typeof e[n]) && (t[n] = e[n])
+            : (void 0 === t[n] && (t[n] = Array.isArray(e[n]) ? [] : {}),
+              t[n] = ox(t[n], e[n], { depth: i - 1, clobber: r }));
+        }),
+          t);
+    },
+    lx = ox,
+    cx = {
+      curveBasis: ao,
+      curveBasisClosed: function(t) {
+        return new so(t);
+      },
+      curveBasisOpen: function(t) {
+        return new oo(t);
+      },
+      curveLinear: Zs,
+      curveLinearClosed: function(t) {
+        return new lo(t);
+      },
+      curveMonotoneX: function(t) {
+        return new fo(t);
+      },
+      curveMonotoneY: function(t) {
+        return new go(t);
+      },
+      curveNatural: function(t) {
+        return new mo(t);
+      },
+      curveStep: function(t) {
+        return new _o(t, .5);
+      },
+      curveStepAfter: function(t) {
+        return new _o(t, 1);
+      },
+      curveStepBefore: function(t) {
+        return new _o(t, 0);
+      },
+    },
+    hx = /%{2}{\s*(?:(\w+)\s*:|(\w+))\s*(?:(\w+)|((?:(?!}%{2}).|\r?\n)*))?\s*(?:}%{2})?/gi,
+    ux = /\s*(?:(\w+)(?=:):|(\w+))\s*(?:(\w+)|((?:(?!}%{2}).|\r?\n)*))?\s*(?:}%{2})?/gi,
+    dx = function(t, e = null) {
+      try {
+        const n = new RegExp(`[%]{2}(?![{]${ux.source})(?=[}][%]{2}).*\n`, "ig");
+        let i;
+        t = t.trim().replace(n, "").replace(/'/gm, "\""),
+          tb.debug(`Detecting diagram directive${null !== e ? " type:" + e : ""} based on the text:${t}`);
+        const r = [];
+        for (; null !== (i = hx.exec(t));) {
+          if (
+            i.index === hx.lastIndex && hx.lastIndex++,
+              i && !e || e && i[1] && i[1].match(e) || e && i[2] && i[2].match(e)
+          ) {
+            const t = i[1] ? i[1] : i[2], e = i[3] ? i[3].trim() : i[4] ? JSON.parse(i[4].trim()) : null;
+            r.push({ type: t, args: e });
+          }
+        }
+        return 0 === r.length && r.push({ type: t, args: null }), 1 === r.length ? r[0] : r;
+      } catch (n) {
+        return tb.error(
+          `ERROR: ${n.message} - Unable to parse directive\n      ${
+            null !== e ? " type:" + e : ""
+          } based on the text:${t}`,
+        ),
+          { type: null, args: null };
+      }
+    };
+  function px(t, e) {
+    if (!t) return e;
+    const n = `curve${t.charAt(0).toUpperCase() + t.slice(1)}`;
+    return cx[n] || e;
+  }
+  function fx(t, e) {
+    return t && e ? Math.sqrt(Math.pow(e.x - t.x, 2) + Math.pow(e.y - t.y, 2)) : 0;
+  }
+  function gx(t) {
+    let e = "", n = "";
+    for (const i of t) {
+      void 0 !== i
+        && (i.startsWith("color:") || i.startsWith("text-align:") ? n = n + i + ";" : e = e + i + ";");
+    }
+    return { style: e, labelStyle: n };
+  }
+  let yx = 0;
+  const mx = () => (yx++, "id-" + Math.random().toString(36).substr(2, 12) + "-" + yx);
+  const bx = t =>
+      function(t) {
+        let e = "";
+        const n = "0123456789abcdef", i = n.length;
+        for (let r = 0; r < t; r++) e += n.charAt(Math.floor(Math.random() * i));
+        return e;
+      }(t.length),
+    _x = function(t, e) {
+      const n = e.text.replace(ub.lineBreakRegex, " "), i = t.append("text");
+      i.attr("x", e.x),
+        i.attr("y", e.y),
+        i.style("text-anchor", e.anchor),
+        i.style("font-family", e.fontFamily),
+        i.style("font-size", e.fontSize),
+        i.style("font-weight", e.fontWeight),
+        i.attr("fill", e.fill),
+        void 0 !== e.class && i.attr("class", e.class);
+      const r = i.append("tspan");
+      return r.attr("x", e.x + 2 * e.textMargin), r.attr("fill", e.fill), r.text(n), i;
+    },
+    xx = Uc((t, e, n) => {
+      if (!t) return t;
+      if (
+        n = Object.assign({ fontSize: 12, fontWeight: 400, fontFamily: "Arial", joinWith: "<br/>" }, n),
+          ub.lineBreakRegex.test(t)
+      ) return t;
+      const i = t.split(" "), r = [];
+      let a = "";
+      return i.forEach((t, s) => {
+        const o = wx(`${t} `, n), l = wx(a, n);
+        if (o > e) {
+          const { hyphenatedStrings: i, remainingWord: s } = vx(t, e, "-", n);
+          r.push(a, ...i), a = s;
+        } else l + o >= e ? (r.push(a), a = t) : a = [a, t].filter(Boolean).join(" ");
+        s + 1 === i.length && r.push(a);
+      }),
+        r.filter(t => "" !== t).join(n.joinWith);
+    }, (t, e, n) => `${t}${e}${n.fontSize}${n.fontWeight}${n.fontFamily}${n.joinWith}`),
+    vx = Uc((t, e, n = "-", i) => {
+      i = Object.assign({ fontSize: 12, fontWeight: 400, fontFamily: "Arial", margin: 0 }, i);
+      const r = [...t], a = [];
+      let s = "";
+      return r.forEach((t, o) => {
+        const l = `${s}${t}`;
+        if (wx(l, i) >= e) {
+          const t = o + 1, e = r.length === t, i = `${l}${n}`;
+          a.push(e ? l : i), s = "";
+        } else s = l;
+      }),
+        { hyphenatedStrings: a, remainingWord: s };
+    }, (t, e, n = "-", i) => `${t}${e}${n}${i.fontSize}${i.fontWeight}${i.fontFamily}`);
+  function kx(t, e) {
+    return e = Object.assign({ fontSize: 12, fontWeight: 400, fontFamily: "Arial", margin: 15 }, e), Tx(t, e).height;
+  }
+  function wx(t, e) {
+    return e = Object.assign({ fontSize: 12, fontWeight: 400, fontFamily: "Arial" }, e), Tx(t, e).width;
+  }
+  const Tx = Uc((t, e) => {
+    e = Object.assign({ fontSize: 12, fontWeight: 400, fontFamily: "Arial" }, e);
+    const { fontSize: n, fontFamily: i, fontWeight: r } = e;
+    if (!t) return { width: 0, height: 0 };
+    const a = ["sans-serif", i], s = t.split(ub.lineBreakRegex), o = [], l = ie("body");
+    if (!l.remove) return { width: 0, height: 0, lineHeight: 0 };
+    const c = l.append("svg");
+    for (const t of a) {
+      let e = 0;
+      const i = { width: 0, height: 0, lineHeight: 0 };
+      for (const a of s) {
+        const s = {
+          x: 0,
+          y: 0,
+          fill: void 0,
+          anchor: "start",
+          style: "#666",
+          width: 100,
+          height: 100,
+          textMargin: 0,
+          rx: 0,
+          ry: 0,
+          valign: void 0,
+        };
+        s.text = a;
+        const o = _x(c, s).style("font-size", n).style("font-weight", r).style("font-family", t),
+          l = (o._groups || o)[0][0].getBBox();
+        i.width = Math.round(Math.max(i.width, l.width)),
+          e = Math.round(l.height),
+          i.height += e,
+          i.lineHeight = Math.round(Math.max(i.lineHeight, e));
+      }
+      o.push(i);
+    }
+    c.remove();
+    return o[
+      isNaN(o[1].height) || isNaN(o[1].width) || isNaN(o[1].lineHeight)
+        || o[0].height > o[1].height && o[0].width > o[1].width && o[0].lineHeight > o[1].lineHeight
+        ? 0
+        : 1
+    ];
+  }, (t, e) => `${t}${e.fontSize}${e.fontWeight}${e.fontFamily}`);
+  let Cx;
+  const Ex = t => {
+      if (
+        tb.debug("directiveSanitizer called with", t),
+          "object" == typeof t && (t.length ? t.forEach(t => Ex(t)) : Object.keys(t).forEach(e => {
+            tb.debug("Checking key", e),
+              e.startsWith("__") && (tb.debug("sanitize deleting __ option", e), delete t[e]),
+              e.includes("proto") && (tb.debug("sanitize deleting proto option", e), delete t[e]),
+              e.includes("constr") && (tb.debug("sanitize deleting constr option", e), delete t[e]),
+              e.includes("themeCSS") && (tb.debug("sanitizing themeCss option"), t[e] = Sx(t[e])),
+              e.includes("fontFamily") && (tb.debug("sanitizing fontFamily option"), t[e] = Sx(t[e])),
+              e.includes("altFontFamily") && (tb.debug("sanitizing altFontFamily option"), t[e] = Sx(t[e])),
+              wb.includes(e)
+                ? "object" == typeof t[e] && (tb.debug("sanitize deleting object", e), Ex(t[e]))
+                : (tb.debug("sanitize deleting option", e), delete t[e]);
+          })),
+          t.themeVariables
+      ) {
+        const e = Object.keys(t.themeVariables);
+        for (const n of e) {
+          const e = t.themeVariables[n];
+          e && e.match && !e.match(/^[\d "#%(),.;A-Za-z]+$/) && (t.themeVariables[n] = "");
+        }
+      }
+      tb.debug("After sanitization", t);
+    },
+    Sx = t => {
+      let e = 0, n = 0;
+      for (const i of t) {
+        if (e < n) return "{ /* ERROR: Unbalanced CSS */ }";
+        "{" === i ? e++ : "}" === i && n++;
+      }
+      return e !== n ? "{ /* ERROR: Unbalanced CSS */ }" : t;
+    };
+  function Ax(t) {
+    return "str" in t;
+  }
+  const Dx = {
+      assignWithDepth: lx,
+      wrapLabel: xx,
+      calculateTextHeight: kx,
+      calculateTextWidth: wx,
+      calculateTextDimensions: Tx,
+      detectInit: function(t, e) {
+        const n = dx(t, /(?:init\b)|(?:initialize\b)/);
+        let i = {};
+        if (Array.isArray(n)) {
+          const t = n.map(t => t.args);
+          Ex(t), i = lx(i, [...t]);
+        } else i = n.args;
+        if (i) {
+          let n = ax(t, e);
+          ["config"].forEach(t => {
+            void 0 !== i[t] && ("flowchart-v2" === n && (n = "flowchart"), i[n] = i[t], delete i[t]);
+          });
+        }
+        return i;
+      },
+      detectDirective: dx,
+      isSubstringInArray: function(t, e) {
+        for (const [n, i] of e.entries()) if (i.match(t)) return n;
+        return -1;
+      },
+      interpolateToCurve: px,
+      calcLabelPosition: function(t) {
+        return 1 === t.length ? t[0] : function(t) {
+          let e, n = 0;
+          t.forEach(t => {
+            n += fx(t, e), e = t;
+          });
+          let i, r = n / 2;
+          return e = void 0,
+            t.forEach(t => {
+              if (e && !i) {
+                const n = fx(t, e);
+                if (n < r) r -= n;
+                else {
+                  const a = r / n;
+                  a <= 0 && (i = e),
+                    a >= 1 && (i = { x: t.x, y: t.y }),
+                    a > 0 && a < 1 && (i = { x: (1 - a) * e.x + a * t.x, y: (1 - a) * e.y + a * t.y });
+                }
+              }
+              e = t;
+            }),
+            i;
+        }(t);
+      },
+      calcCardinalityPosition: (t, e, n) => {
+        let i;
+        tb.info(`our points ${JSON.stringify(e)}`), e[0] !== n && (e = e.reverse());
+        let r, a = 25;
+        i = void 0,
+          e.forEach(t => {
+            if (i && !r) {
+              const e = fx(t, i);
+              if (e < a) a -= e;
+              else {
+                const n = a / e;
+                n <= 0 && (r = i),
+                  n >= 1 && (r = { x: t.x, y: t.y }),
+                  n > 0 && n < 1 && (r = { x: (1 - n) * i.x + n * t.x, y: (1 - n) * i.y + n * t.y });
+              }
+            }
+            i = t;
+          });
+        const s = t ? 10 : 5, o = Math.atan2(e[0].y - r.y, e[0].x - r.x), l = { x: 0, y: 0 };
+        return l.x = Math.sin(o) * s + (e[0].x + r.x) / 2, l.y = -Math.cos(o) * s + (e[0].y + r.y) / 2, l;
+      },
+      calcTerminalLabelPosition: function(t, e, n) {
+        let i, r = JSON.parse(JSON.stringify(n));
+        tb.info("our points", r),
+          "start_left" !== e && "start_right" !== e && (r = r.reverse()),
+          r.forEach(t => {
+            i = t;
+          });
+        let a, s = 25 + t;
+        i = void 0,
+          r.forEach(t => {
+            if (i && !a) {
+              const e = fx(t, i);
+              if (e < s) s -= e;
+              else {
+                const n = s / e;
+                n <= 0 && (a = i),
+                  n >= 1 && (a = { x: t.x, y: t.y }),
+                  n > 0 && n < 1 && (a = { x: (1 - n) * i.x + n * t.x, y: (1 - n) * i.y + n * t.y });
+              }
+            }
+            i = t;
+          });
+        const o = 10 + .5 * t, l = Math.atan2(r[0].y - a.y, r[0].x - a.x), c = { x: 0, y: 0 };
+        return c.x = Math.sin(l) * o + (r[0].x + a.x) / 2,
+          c.y = -Math.cos(l) * o + (r[0].y + a.y) / 2,
+          "start_left" === e
+          && (c.x = Math.sin(l + Math.PI) * o + (r[0].x + a.x) / 2,
+            c.y = -Math.cos(l + Math.PI) * o + (r[0].y + a.y) / 2),
+          "end_right" === e
+          && (c.x = Math.sin(l - Math.PI) * o + (r[0].x + a.x) / 2 - 5,
+            c.y = -Math.cos(l - Math.PI) * o + (r[0].y + a.y) / 2 - 5),
+          "end_left" === e
+          && (c.x = Math.sin(l) * o + (r[0].x + a.x) / 2 - 5, c.y = -Math.cos(l) * o + (r[0].y + a.y) / 2 - 5),
+          c;
+      },
+      formatUrl: function(t, e) {
+        const n = t.trim();
+        if (n) return "loose" !== e.securityLevel ? i(n) : n;
+      },
+      getStylesFromArray: gx,
+      generateId: mx,
+      random: bx,
+      runFunc: (t, ...e) => {
+        const n = t.split("."), i = n.length - 1, r = n[i];
+        let a = window;
+        for (let t = 0; t < i; t++) if (a = a[n[t]], !a) return;
+        a[r](...e);
+      },
+      entityDecode: function(t) {
+        return Cx = Cx || document.createElement("div"),
+          t = escape(t).replace(/%26/g, "&").replace(/%23/g, "#").replace(/%3B/g, ";"),
+          Cx.innerHTML = t,
+          unescape(Cx.textContent);
+      },
+      initIdGenerator: class {
+        constructor(t, e) {
+          this.deterministic = t, this.seed = e, this.count = e ? e.length : 0;
+        }
+        next() {
+          return this.deterministic ? this.count++ : Date.now();
+        }
+      },
+      directiveSanitizer: Ex,
+      sanitizeCss: Sx,
+      insertTitle: (t, e, n, i) => {
+        if (!i) return;
+        const r = t.node().getBBox();
+        t.append("text").text(i).attr("x", r.x + r.width / 2).attr("y", -n).attr("class", e);
+      },
+    },
+    Lx = "9.3.0",
+    Ox = Object.freeze(Tb);
+  let Nx, Mx = lx({}, Ox), Bx = [], Ix = lx({}, Ox);
+  const Fx = (t, e) => {
+      let n = lx({}, t), i = {};
+      for (const t of e) zx(t), i = lx(i, t);
+      if (n = lx(n, i), i.theme && i.theme in xb) {
+        const t = lx({}, Nx), e = lx(t.themeVariables || {}, i.themeVariables);
+        n.theme && n.theme in xb && (n.themeVariables = xb[n.theme].getThemeVariables(e));
+      }
+      return Ix = n, Vx(Ix), Ix;
+    },
+    Rx =
+      t => (Mx = lx({}, Ox),
+        Mx = lx(Mx, t),
+        t.theme && xb[t.theme] && (Mx.themeVariables = xb[t.theme].getThemeVariables(t.themeVariables)),
+        Fx(Mx, Bx),
+        Mx),
+    $x = t => {
+      Nx = lx({}, t);
+    },
+    Px = () => lx({}, Mx),
+    Yx = t => (Vx(t), lx(Ix, t), jx()),
+    jx = () => lx({}, Ix),
+    zx = t => {
+      var e;
+      ["secure", ...null != (e = Mx.secure) ? e : []].forEach(e => {
+        void 0 !== t[e] && (tb.debug(`Denied attempt to modify a secure key ${e}`, t[e]), delete t[e]);
+      }),
+        Object.keys(t).forEach(e => {
+          0 === e.indexOf("__") && delete t[e];
+        }),
+        Object.keys(t).forEach(e => {
+          "string" == typeof t[e] && (t[e].includes("<") || t[e].includes(">") || t[e].includes("url(data:"))
+          && delete t[e], "object" == typeof t[e] && zx(t[e]);
+        });
+    },
+    Ux = t => {
+      t.fontFamily
+      && (t.themeVariables && t.themeVariables.fontFamily || (t.themeVariables = { fontFamily: t.fontFamily })),
+        Bx.push(t),
+        Fx(Mx, Bx);
+    },
+    Wx = (t = Mx) => {
+      Bx = [], Fx(t, Bx);
+    };
+  var Hx =
+    (t => (t.LAZY_LOAD_DEPRECATED =
+      "The configuration options lazyLoadedDiagrams and loadExternalDiagramsAtStartup are deprecated. Please use registerExternalDiagrams instead.",
+      t))(Hx || {});
+  const qx = {},
+    Vx = t => {
+      var e;
+      t
+        && ((t.lazyLoadedDiagrams || t.loadExternalDiagramsAtStartup)
+          && (qx[e = "LAZY_LOAD_DEPRECATED"] || (tb.warn(Hx[e]), qx[e] = !0)));
+    },
+    Gx = function(t, e, n, i) {
+      const r = function(t, e, n) {
+        let i = new Map();
+        return n
+          ? (i.set("width", "100%"), i.set("style", `max-width: ${e}px;`))
+          : (i.set("height", t), i.set("width", e)),
+          i;
+      }(e, n, i);
+      !function(t, e) {
+        for (let n of e) t.attr(n[0], n[1]);
+      }(t, r);
+    },
+    Xx = function(t, e, n, i) {
+      const r = e.node().getBBox(), a = r.width, s = r.height;
+      tb.info(`SVG bounds: ${a}x${s}`, r);
+      let o = 0, l = 0;
+      tb.info(`Graph bounds: ${o}x${l}`, t),
+        o = a + 2 * n,
+        l = s + 2 * n,
+        tb.info(`Calculated bounds: ${o}x${l}`),
+        Gx(e, l, o, i);
+      const c = `${r.x - n} ${r.y - n} ${r.width + 2 * n} ${r.height + 2 * n}`;
+      e.attr("viewBox", c);
+    },
+    Zx = t =>
+      `g.classGroup text {\n  fill: ${t.nodeBorder};\n  fill: ${t.classText};\n  stroke: none;\n  font-family: ${t.fontFamily};\n  font-size: 10px;\n\n  .title {\n    font-weight: bolder;\n  }\n\n}\n\n.nodeLabel, .edgeLabel {\n  color: ${t.classText};\n}\n.edgeLabel .label rect {\n  fill: ${t.mainBkg};\n}\n.label text {\n  fill: ${t.classText};\n}\n.edgeLabel .label span {\n  background: ${t.mainBkg};\n}\n\n.classTitle {\n  font-weight: bolder;\n}\n.node rect,\n  .node circle,\n  .node ellipse,\n  .node polygon,\n  .node path {\n    fill: ${t.mainBkg};\n    stroke: ${t.nodeBorder};\n    stroke-width: 1px;\n  }\n\n\n.divider {\n  stroke: ${t.nodeBorder};\n  stroke: 1;\n}\n\ng.clickable {\n  cursor: pointer;\n}\n\ng.classGroup rect {\n  fill: ${t.mainBkg};\n  stroke: ${t.nodeBorder};\n}\n\ng.classGroup line {\n  stroke: ${t.nodeBorder};\n  stroke-width: 1;\n}\n\n.classLabel .box {\n  stroke: none;\n  stroke-width: 0;\n  fill: ${t.mainBkg};\n  opacity: 0.5;\n}\n\n.classLabel .label {\n  fill: ${t.nodeBorder};\n  font-size: 10px;\n}\n\n.relation {\n  stroke: ${t.lineColor};\n  stroke-width: 1;\n  fill: none;\n}\n\n.dashed-line{\n  stroke-dasharray: 3;\n}\n\n.dotted-line{\n  stroke-dasharray: 1 2;\n}\n\n#compositionStart, .composition {\n  fill: ${t.lineColor} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n#compositionEnd, .composition {\n  fill: ${t.lineColor} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n#dependencyStart, .dependency {\n  fill: ${t.lineColor} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n#dependencyStart, .dependency {\n  fill: ${t.lineColor} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n#extensionStart, .extension {\n  fill: ${t.mainBkg} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n#extensionEnd, .extension {\n  fill: ${t.mainBkg} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n#aggregationStart, .aggregation {\n  fill: ${t.mainBkg} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n#aggregationEnd, .aggregation {\n  fill: ${t.mainBkg} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n#lollipopStart, .lollipop {\n  fill: ${t.mainBkg} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n#lollipopEnd, .lollipop {\n  fill: ${t.mainBkg} !important;\n  stroke: ${t.lineColor} !important;\n  stroke-width: 1;\n}\n\n.edgeTerminals {\n  font-size: 11px;\n}\n\n.classTitleText {\n  text-anchor: middle;\n  font-size: 18px;\n  fill: ${t.textColor};\n}\n`,
+    Qx = t =>
+      `\n  .entityBox {\n    fill: ${t.mainBkg};\n    stroke: ${t.nodeBorder};\n  }\n\n  .attributeBoxOdd {\n    fill: ${t.attributeBackgroundColorOdd};\n    stroke: ${t.nodeBorder};\n  }\n\n  .attributeBoxEven {\n    fill:  ${t.attributeBackgroundColorEven};\n    stroke: ${t.nodeBorder};\n  }\n\n  .relationshipLabelBox {\n    fill: ${t.tertiaryColor};\n    opacity: 0.7;\n    background-color: ${t.tertiaryColor};\n      rect {\n        opacity: 0.5;\n      }\n  }\n\n    .relationshipLine {\n      stroke: ${t.lineColor};\n    }\n\n  .entityTitleText {\n    text-anchor: middle;\n    font-size: 18px;\n    fill: ${t.textColor};\n  }    \n`,
+    Kx = () => "",
+    Jx = t =>
+      `.label {\n    font-family: ${t.fontFamily};\n    color: ${
+        t.nodeTextColor || t.textColor
+      };\n  }\n  .cluster-label text {\n    fill: ${t.titleColor};\n  }\n  .cluster-label span {\n    color: ${t.titleColor};\n  }\n\n  .label text,span {\n    fill: ${
+        t.nodeTextColor || t.textColor
+      };\n    color: ${
+        t.nodeTextColor || t.textColor
+      };\n  }\n\n  .node rect,\n  .node circle,\n  .node ellipse,\n  .node polygon,\n  .node path {\n    fill: ${t.mainBkg};\n    stroke: ${t.nodeBorder};\n    stroke-width: 1px;\n  }\n\n  .node .label {\n    text-align: center;\n  }\n  .node.clickable {\n    cursor: pointer;\n  }\n\n  .arrowheadPath {\n    fill: ${t.arrowheadColor};\n  }\n\n  .edgePath .path {\n    stroke: ${t.lineColor};\n    stroke-width: 2.0px;\n  }\n\n  .flowchart-link {\n    stroke: ${t.lineColor};\n    fill: none;\n  }\n\n  .edgeLabel {\n    background-color: ${t.edgeLabelBackground};\n    rect {\n      opacity: 0.5;\n      background-color: ${t.edgeLabelBackground};\n      fill: ${t.edgeLabelBackground};\n    }\n    text-align: center;\n  }\n\n  .cluster rect {\n    fill: ${t.clusterBkg};\n    stroke: ${t.clusterBorder};\n    stroke-width: 1px;\n  }\n\n  .cluster text {\n    fill: ${t.titleColor};\n  }\n\n  .cluster span {\n    color: ${t.titleColor};\n  }\n  /* .cluster div {\n    color: ${t.titleColor};\n  } */\n\n  div.mermaidTooltip {\n    position: absolute;\n    text-align: center;\n    max-width: 200px;\n    padding: 2px;\n    font-family: ${t.fontFamily};\n    font-size: 12px;\n    background: ${t.tertiaryColor};\n    border: 1px solid ${t.border2};\n    border-radius: 2px;\n    pointer-events: none;\n    z-index: 100;\n  }\n\n  .flowchartTitleText {\n    text-anchor: middle;\n    font-size: 18px;\n    fill: ${t.textColor};\n  }\n`,
+    tv = t =>
+      `\n  .mermaid-main-font {\n    font-family: "trebuchet ms", verdana, arial, sans-serif;\n    font-family: var(--mermaid-font-family);\n  }\n  .exclude-range {\n    fill: ${t.excludeBkgColor};\n  }\n\n  .section {\n    stroke: none;\n    opacity: 0.2;\n  }\n\n  .section0 {\n    fill: ${t.sectionBkgColor};\n  }\n\n  .section2 {\n    fill: ${t.sectionBkgColor2};\n  }\n\n  .section1,\n  .section3 {\n    fill: ${t.altSectionBkgColor};\n    opacity: 0.2;\n  }\n\n  .sectionTitle0 {\n    fill: ${t.titleColor};\n  }\n\n  .sectionTitle1 {\n    fill: ${t.titleColor};\n  }\n\n  .sectionTitle2 {\n    fill: ${t.titleColor};\n  }\n\n  .sectionTitle3 {\n    fill: ${t.titleColor};\n  }\n\n  .sectionTitle {\n    text-anchor: start;\n    // font-size: ${t.ganttFontSize};\n    // text-height: 14px;\n    font-family: 'trebuchet ms', verdana, arial, sans-serif;\n    font-family: var(--mermaid-font-family);\n\n  }\n\n\n  /* Grid and axis */\n\n  .grid .tick {\n    stroke: ${t.gridColor};\n    opacity: 0.8;\n    shape-rendering: crispEdges;\n    text {\n      font-family: ${t.fontFamily};\n      fill: ${t.textColor};\n    }\n  }\n\n  .grid path {\n    stroke-width: 0;\n  }\n\n\n  /* Today line */\n\n  .today {\n    fill: none;\n    stroke: ${t.todayLineColor};\n    stroke-width: 2px;\n  }\n\n\n  /* Task styling */\n\n  /* Default task */\n\n  .task {\n    stroke-width: 2;\n  }\n\n  .taskText {\n    text-anchor: middle;\n    font-family: 'trebuchet ms', verdana, arial, sans-serif;\n    font-family: var(--mermaid-font-family);\n  }\n\n  // .taskText:not([font-size]) {\n  //   font-size: ${t.ganttFontSize};\n  // }\n\n  .taskTextOutsideRight {\n    fill: ${t.taskTextDarkColor};\n    text-anchor: start;\n    // font-size: ${t.ganttFontSize};\n    font-family: 'trebuchet ms', verdana, arial, sans-serif;\n    font-family: var(--mermaid-font-family);\n\n  }\n\n  .taskTextOutsideLeft {\n    fill: ${t.taskTextDarkColor};\n    text-anchor: end;\n    // font-size: ${t.ganttFontSize};\n  }\n\n  /* Special case clickable */\n  .task.clickable {\n    cursor: pointer;\n  }\n  .taskText.clickable {\n    cursor: pointer;\n    fill: ${t.taskTextClickableColor} !important;\n    font-weight: bold;\n  }\n\n  .taskTextOutsideLeft.clickable {\n    cursor: pointer;\n    fill: ${t.taskTextClickableColor} !important;\n    font-weight: bold;\n  }\n\n  .taskTextOutsideRight.clickable {\n    cursor: pointer;\n    fill: ${t.taskTextClickableColor} !important;\n    font-weight: bold;\n  }\n\n  /* Specific task settings for the sections*/\n\n  .taskText0,\n  .taskText1,\n  .taskText2,\n  .taskText3 {\n    fill: ${t.taskTextColor};\n  }\n\n  .task0,\n  .task1,\n  .task2,\n  .task3 {\n    fill: ${t.taskBkgColor};\n    stroke: ${t.taskBorderColor};\n  }\n\n  .taskTextOutside0,\n  .taskTextOutside2\n  {\n    fill: ${t.taskTextOutsideColor};\n  }\n\n  .taskTextOutside1,\n  .taskTextOutside3 {\n    fill: ${t.taskTextOutsideColor};\n  }\n\n\n  /* Active task */\n\n  .active0,\n  .active1,\n  .active2,\n  .active3 {\n    fill: ${t.activeTaskBkgColor};\n    stroke: ${t.activeTaskBorderColor};\n  }\n\n  .activeText0,\n  .activeText1,\n  .activeText2,\n  .activeText3 {\n    fill: ${t.taskTextDarkColor} !important;\n  }\n\n\n  /* Completed task */\n\n  .done0,\n  .done1,\n  .done2,\n  .done3 {\n    stroke: ${t.doneTaskBorderColor};\n    fill: ${t.doneTaskBkgColor};\n    stroke-width: 2;\n  }\n\n  .doneText0,\n  .doneText1,\n  .doneText2,\n  .doneText3 {\n    fill: ${t.taskTextDarkColor} !important;\n  }\n\n\n  /* Tasks on the critical line */\n\n  .crit0,\n  .crit1,\n  .crit2,\n  .crit3 {\n    stroke: ${t.critBorderColor};\n    fill: ${t.critBkgColor};\n    stroke-width: 2;\n  }\n\n  .activeCrit0,\n  .activeCrit1,\n  .activeCrit2,\n  .activeCrit3 {\n    stroke: ${t.critBorderColor};\n    fill: ${t.activeTaskBkgColor};\n    stroke-width: 2;\n  }\n\n  .doneCrit0,\n  .doneCrit1,\n  .doneCrit2,\n  .doneCrit3 {\n    stroke: ${t.critBorderColor};\n    fill: ${t.doneTaskBkgColor};\n    stroke-width: 2;\n    cursor: pointer;\n    shape-rendering: crispEdges;\n  }\n\n  .milestone {\n    transform: rotate(45deg) scale(0.8,0.8);\n  }\n\n  .milestoneText {\n    font-style: italic;\n  }\n  .doneCritText0,\n  .doneCritText1,\n  .doneCritText2,\n  .doneCritText3 {\n    fill: ${t.taskTextDarkColor} !important;\n  }\n\n  .activeCritText0,\n  .activeCritText1,\n  .activeCritText2,\n  .activeCritText3 {\n    fill: ${t.taskTextDarkColor} !important;\n  }\n\n  .titleText {\n    text-anchor: middle;\n    font-size: 18px;\n    fill: ${t.textColor}    ;\n    font-family: 'trebuchet ms', verdana, arial, sans-serif;\n    font-family: var(--mermaid-font-family);\n  }\n`,
+    ev = () => "",
+    nv = t =>
+      `\n  .pieCircle{\n    stroke: ${t.pieStrokeColor};\n    stroke-width : ${t.pieStrokeWidth};\n    opacity : ${t.pieOpacity};\n  }\n  .pieTitleText {\n    text-anchor: middle;\n    font-size: ${t.pieTitleTextSize};\n    fill: ${t.pieTitleTextColor};\n    font-family: ${t.fontFamily};\n  }\n  .slice {\n    font-family: ${t.fontFamily};\n    fill: ${t.pieSectionTextColor};\n    font-size:${t.pieSectionTextSize};\n    // fill: white;\n  }\n  .legend text {\n    fill: ${t.pieLegendTextColor};\n    font-family: ${t.fontFamily};\n    font-size: ${t.pieLegendTextSize};\n  }\n`,
+    iv = t =>
+      `\n\n  marker {\n    fill: ${t.relationColor};\n    stroke: ${t.relationColor};\n  }\n\n  marker.cross {\n    stroke: ${t.lineColor};\n  }\n\n  svg {\n    font-family: ${t.fontFamily};\n    font-size: ${t.fontSize};\n  }\n\n  .reqBox {\n    fill: ${t.requirementBackground};\n    fill-opacity: 100%;\n    stroke: ${t.requirementBorderColor};\n    stroke-width: ${t.requirementBorderSize};\n  }\n  \n  .reqTitle, .reqLabel{\n    fill:  ${t.requirementTextColor};\n  }\n  .reqLabelBox {\n    fill: ${t.relationLabelBackground};\n    fill-opacity: 100%;\n  }\n\n  .req-title-line {\n    stroke: ${t.requirementBorderColor};\n    stroke-width: ${t.requirementBorderSize};\n  }\n  .relationshipLine {\n    stroke: ${t.relationColor};\n    stroke-width: 1;\n  }\n  .relationshipLabel {\n    fill: ${t.relationLabelColor};\n  }\n\n`,
+    rv = t =>
+      `.actor {\n    stroke: ${t.actorBorder};\n    fill: ${t.actorBkg};\n  }\n\n  text.actor > tspan {\n    fill: ${t.actorTextColor};\n    stroke: none;\n  }\n\n  .actor-line {\n    stroke: ${t.actorLineColor};\n  }\n\n  .messageLine0 {\n    stroke-width: 1.5;\n    stroke-dasharray: none;\n    stroke: ${t.signalColor};\n  }\n\n  .messageLine1 {\n    stroke-width: 1.5;\n    stroke-dasharray: 2, 2;\n    stroke: ${t.signalColor};\n  }\n\n  #arrowhead path {\n    fill: ${t.signalColor};\n    stroke: ${t.signalColor};\n  }\n\n  .sequenceNumber {\n    fill: ${t.sequenceNumberColor};\n  }\n\n  #sequencenumber {\n    fill: ${t.signalColor};\n  }\n\n  #crosshead path {\n    fill: ${t.signalColor};\n    stroke: ${t.signalColor};\n  }\n\n  .messageText {\n    fill: ${t.signalTextColor};\n    stroke: none;\n  }\n\n  .labelBox {\n    stroke: ${t.labelBoxBorderColor};\n    fill: ${t.labelBoxBkgColor};\n  }\n\n  .labelText, .labelText > tspan {\n    fill: ${t.labelTextColor};\n    stroke: none;\n  }\n\n  .loopText, .loopText > tspan {\n    fill: ${t.loopTextColor};\n    stroke: none;\n  }\n\n  .loopLine {\n    stroke-width: 2px;\n    stroke-dasharray: 2, 2;\n    stroke: ${t.labelBoxBorderColor};\n    fill: ${t.labelBoxBorderColor};\n  }\n\n  .note {\n    //stroke: #decc93;\n    stroke: ${t.noteBorderColor};\n    fill: ${t.noteBkgColor};\n  }\n\n  .noteText, .noteText > tspan {\n    fill: ${t.noteTextColor};\n    stroke: none;\n  }\n\n  .activation0 {\n    fill: ${t.activationBkgColor};\n    stroke: ${t.activationBorderColor};\n  }\n\n  .activation1 {\n    fill: ${t.activationBkgColor};\n    stroke: ${t.activationBorderColor};\n  }\n\n  .activation2 {\n    fill: ${t.activationBkgColor};\n    stroke: ${t.activationBorderColor};\n  }\n\n  .actorPopupMenu {\n    position: absolute;\n  }\n\n  .actorPopupMenuPanel {\n    position: absolute;\n    fill: ${t.actorBkg};\n    box-shadow: 0px 8px 16px 0px rgba(0,0,0,0.2);\n    filter: drop-shadow(3px 5px 2px rgb(0 0 0 / 0.4));\n}\n  .actor-man line {\n    stroke: ${t.actorBorder};\n    fill: ${t.actorBkg};\n  }\n  .actor-man circle, line {\n    stroke: ${t.actorBorder};\n    fill: ${t.actorBkg};\n    stroke-width: 2px;\n  }\n`,
+    av = t =>
+      `\ndefs #statediagram-barbEnd {\n    fill: ${t.transitionColor};\n    stroke: ${t.transitionColor};\n  }\ng.stateGroup text {\n  fill: ${t.nodeBorder};\n  stroke: none;\n  font-size: 10px;\n}\ng.stateGroup text {\n  fill: ${t.textColor};\n  stroke: none;\n  font-size: 10px;\n\n}\ng.stateGroup .state-title {\n  font-weight: bolder;\n  fill: ${t.stateLabelColor};\n}\n\ng.stateGroup rect {\n  fill: ${t.mainBkg};\n  stroke: ${t.nodeBorder};\n}\n\ng.stateGroup line {\n  stroke: ${t.lineColor};\n  stroke-width: 1;\n}\n\n.transition {\n  stroke: ${t.transitionColor};\n  stroke-width: 1;\n  fill: none;\n}\n\n.stateGroup .composit {\n  fill: ${t.background};\n  border-bottom: 1px\n}\n\n.stateGroup .alt-composit {\n  fill: #e0e0e0;\n  border-bottom: 1px\n}\n\n.state-note {\n  stroke: ${t.noteBorderColor};\n  fill: ${t.noteBkgColor};\n\n  text {\n    fill: ${t.noteTextColor};\n    stroke: none;\n    font-size: 10px;\n  }\n}\n\n.stateLabel .box {\n  stroke: none;\n  stroke-width: 0;\n  fill: ${t.mainBkg};\n  opacity: 0.5;\n}\n\n.edgeLabel .label rect {\n  fill: ${t.labelBackgroundColor};\n  opacity: 0.5;\n}\n.edgeLabel .label text {\n  fill: ${
+        t.transitionLabelColor || t.tertiaryTextColor
+      };\n}\n.label div .edgeLabel {\n  color: ${
+        t.transitionLabelColor || t.tertiaryTextColor
+      };\n}\n\n.stateLabel text {\n  fill: ${t.stateLabelColor};\n  font-size: 10px;\n  font-weight: bold;\n}\n\n.node circle.state-start {\n  fill: ${t.specialStateColor};\n  stroke: ${t.specialStateColor};\n}\n\n.node .fork-join {\n  fill: ${t.specialStateColor};\n  stroke: ${t.specialStateColor};\n}\n\n.node circle.state-end {\n  fill: ${t.innerEndBackground};\n  stroke: ${t.background};\n  stroke-width: 1.5\n}\n.end-state-inner {\n  fill: ${
+        t.compositeBackground || t.background
+      };\n  // stroke: ${t.background};\n  stroke-width: 1.5\n}\n\n.node rect {\n  fill: ${
+        t.stateBkg || t.mainBkg
+      };\n  stroke: ${
+        t.stateBorder || t.nodeBorder
+      };\n  stroke-width: 1px;\n}\n.node polygon {\n  fill: ${t.mainBkg};\n  stroke: ${
+        t.stateBorder || t.nodeBorder
+      };;\n  stroke-width: 1px;\n}\n#statediagram-barbEnd {\n  fill: ${t.lineColor};\n}\n\n.statediagram-cluster rect {\n  fill: ${t.compositeTitleBackground};\n  stroke: ${
+        t.stateBorder || t.nodeBorder
+      };\n  stroke-width: 1px;\n}\n\n.cluster-label, .nodeLabel {\n  color: ${t.stateLabelColor};\n}\n\n.statediagram-cluster rect.outer {\n  rx: 5px;\n  ry: 5px;\n}\n.statediagram-state .divider {\n  stroke: ${
+        t.stateBorder || t.nodeBorder
+      };\n}\n\n.statediagram-state .title-state {\n  rx: 5px;\n  ry: 5px;\n}\n.statediagram-cluster.statediagram-cluster .inner {\n  fill: ${
+        t.compositeBackground || t.background
+      };\n}\n.statediagram-cluster.statediagram-cluster-alt .inner {\n  fill: ${
+        t.altBackground ? t.altBackground : "#efefef"
+      };\n}\n\n.statediagram-cluster .inner {\n  rx:0;\n  ry:0;\n}\n\n.statediagram-state rect.basic {\n  rx: 5px;\n  ry: 5px;\n}\n.statediagram-state rect.divider {\n  stroke-dasharray: 10,10;\n  fill: ${
+        t.altBackground ? t.altBackground : "#efefef"
+      };\n}\n\n.note-edge {\n  stroke-dasharray: 5;\n}\n\n.statediagram-note rect {\n  fill: ${t.noteBkgColor};\n  stroke: ${t.noteBorderColor};\n  stroke-width: 1px;\n  rx: 0;\n  ry: 0;\n}\n.statediagram-note rect {\n  fill: ${t.noteBkgColor};\n  stroke: ${t.noteBorderColor};\n  stroke-width: 1px;\n  rx: 0;\n  ry: 0;\n}\n\n.statediagram-note text {\n  fill: ${t.noteTextColor};\n}\n\n.statediagram-note .nodeLabel {\n  color: ${t.noteTextColor};\n}\n.statediagram .edgeLabel {\n  color: red; // ${t.noteTextColor};\n}\n\n#dependencyStart, #dependencyEnd {\n  fill: ${t.lineColor};\n  stroke: ${t.lineColor};\n  stroke-width: 1;\n}\n\n.statediagramTitleText {\n  text-anchor: middle;\n  font-size: 18px;\n  fill: ${t.textColor};\n}\n`,
+    sv = t =>
+      `.label {\n    font-family: 'trebuchet ms', verdana, arial, sans-serif;\n    font-family: var(--mermaid-font-family);\n    color: ${t.textColor};\n  }\n  .mouth {\n    stroke: #666;\n  }\n\n  line {\n    stroke: ${t.textColor}\n  }\n\n  .legend {\n    fill: ${t.textColor};\n  }\n\n  .label text {\n    fill: #333;\n  }\n  .label {\n    color: ${t.textColor}\n  }\n\n  .face {\n    ${
+        t.faceColor ? `fill: ${t.faceColor}` : "fill: #FFF8DC"
+      };\n    stroke: #999;\n  }\n\n  .node rect,\n  .node circle,\n  .node ellipse,\n  .node polygon,\n  .node path {\n    fill: ${t.mainBkg};\n    stroke: ${t.nodeBorder};\n    stroke-width: 1px;\n  }\n\n  .node .label {\n    text-align: center;\n  }\n  .node.clickable {\n    cursor: pointer;\n  }\n\n  .arrowheadPath {\n    fill: ${t.arrowheadColor};\n  }\n\n  .edgePath .path {\n    stroke: ${t.lineColor};\n    stroke-width: 1.5px;\n  }\n\n  .flowchart-link {\n    stroke: ${t.lineColor};\n    fill: none;\n  }\n\n  .edgeLabel {\n    background-color: ${t.edgeLabelBackground};\n    rect {\n      opacity: 0.5;\n    }\n    text-align: center;\n  }\n\n  .cluster rect {\n  }\n\n  .cluster text {\n    fill: ${t.titleColor};\n  }\n\n  div.mermaidTooltip {\n    position: absolute;\n    text-align: center;\n    max-width: 200px;\n    padding: 2px;\n    font-family: 'trebuchet ms', verdana, arial, sans-serif;\n    font-family: var(--mermaid-font-family);\n    font-size: 12px;\n    background: ${t.tertiaryColor};\n    border: 1px solid ${t.border2};\n    border-radius: 2px;\n    pointer-events: none;\n    z-index: 100;\n  }\n\n  .task-type-0, .section-type-0  {\n    ${
+        t.fillType0 ? `fill: ${t.fillType0}` : ""
+      };\n  }\n  .task-type-1, .section-type-1  {\n    ${
+        t.fillType0 ? `fill: ${t.fillType1}` : ""
+      };\n  }\n  .task-type-2, .section-type-2  {\n    ${
+        t.fillType0 ? `fill: ${t.fillType2}` : ""
+      };\n  }\n  .task-type-3, .section-type-3  {\n    ${
+        t.fillType0 ? `fill: ${t.fillType3}` : ""
+      };\n  }\n  .task-type-4, .section-type-4  {\n    ${
+        t.fillType0 ? `fill: ${t.fillType4}` : ""
+      };\n  }\n  .task-type-5, .section-type-5  {\n    ${
+        t.fillType0 ? `fill: ${t.fillType5}` : ""
+      };\n  }\n  .task-type-6, .section-type-6  {\n    ${
+        t.fillType0 ? `fill: ${t.fillType6}` : ""
+      };\n  }\n  .task-type-7, .section-type-7  {\n    ${
+        t.fillType0 ? `fill: ${t.fillType7}` : ""
+      };\n  }\n\n  .actor-0 {\n    ${t.actor0 ? `fill: ${t.actor0}` : ""};\n  }\n  .actor-1 {\n    ${
+        t.actor1 ? `fill: ${t.actor1}` : ""
+      };\n  }\n  .actor-2 {\n    ${t.actor2 ? `fill: ${t.actor2}` : ""};\n  }\n  .actor-3 {\n    ${
+        t.actor3 ? `fill: ${t.actor3}` : ""
+      };\n  }\n  .actor-4 {\n    ${t.actor4 ? `fill: ${t.actor4}` : ""};\n  }\n  .actor-5 {\n    ${
+        t.actor5 ? `fill: ${t.actor5}` : ""
+      };\n  }\n`,
+    ov = t => `.person {\n    stroke: ${t.personBorder};\n    fill: ${t.personBkg};\n  }\n`,
+    lv = {
+      flowchart: Jx,
+      "flowchart-v2": Jx,
+      sequence: rv,
+      gantt: tv,
+      classDiagram: Zx,
+      "classDiagram-v2": Zx,
+      class: Zx,
+      stateDiagram: av,
+      state: av,
+      info: ev,
+      pie: nv,
+      er: Qx,
+      error: Kx,
+      journey: sv,
+      requirement: iv,
+      c4: ov,
+    },
+    cv = (t, e, n) => {
+      let i = "";
+      return t in lv && lv[t] ? i = lv[t](n) : tb.warn(`No theme found for ${t}`),
+        ` & {\n    font-family: ${n.fontFamily};\n    font-size: ${n.fontSize};\n    fill: ${n.textColor}\n  }\n\n  /* Classes common for multiple diagrams */\n\n  & .error-icon {\n    fill: ${n.errorBkgColor};\n  }\n  & .error-text {\n    fill: ${n.errorTextColor};\n    stroke: ${n.errorTextColor};\n  }\n\n  & .edge-thickness-normal {\n    stroke-width: 2px;\n  }\n  & .edge-thickness-thick {\n    stroke-width: 3.5px\n  }\n  & .edge-pattern-solid {\n    stroke-dasharray: 0;\n  }\n\n  & .edge-pattern-dashed{\n    stroke-dasharray: 3;\n  }\n  .edge-pattern-dotted {\n    stroke-dasharray: 2;\n  }\n\n  & .marker {\n    fill: ${n.lineColor};\n    stroke: ${n.lineColor};\n  }\n  & .marker.cross {\n    stroke: ${n.lineColor};\n  }\n\n  & svg {\n    font-family: ${n.fontFamily};\n    font-size: ${n.fontSize};\n  }\n\n  ${i}\n\n  ${e}\n`;
+    },
+    hv = tb,
+    uv = eb,
+    dv = jx,
+    pv = t => ab(t, dv()),
+    fv = Xx,
+    gv = {},
+    yv = (t, e, n) => {
+      if (gv[t]) throw new Error(`Diagram ${t} already registered.`);
+      var i, r;
+      gv[t] = e, n && sx(t, n), i = t, r = e.styles, lv[i] = r, e.injectUtils && e.injectUtils(hv, uv, dv, pv, fv);
+    },
+    mv = t => {
+      if (t in gv) return gv[t];
+      throw new Error(`Diagram ${t} not found.`);
+    };
+  var bv = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [1, 4],
+      i = [1, 7],
+      r = [1, 5],
+      a = [1, 9],
+      s = [1, 6],
+      o = [2, 6],
+      l = [1, 16],
+      c = [6, 8, 14, 20, 22, 24, 25, 27, 29, 32, 37, 40, 50, 55],
+      h = [8, 14, 20, 22, 24, 25, 27, 29, 32, 37, 40],
+      u = [8, 13, 14, 20, 22, 24, 25, 27, 29, 32, 37, 40],
+      d = [1, 26],
+      p = [6, 8, 14, 50, 55],
+      f = [8, 14, 55],
+      g = [1, 53],
+      y = [1, 52],
+      m = [8, 14, 30, 33, 35, 38, 55],
+      b = [1, 67],
+      _ = [1, 68],
+      x = [1, 69],
+      v = [8, 14, 33, 35, 42, 55],
+      k = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          eol: 4,
+          directive: 5,
+          GG: 6,
+          document: 7,
+          EOF: 8,
+          ":": 9,
+          DIR: 10,
+          options: 11,
+          body: 12,
+          OPT: 13,
+          NL: 14,
+          line: 15,
+          statement: 16,
+          commitStatement: 17,
+          mergeStatement: 18,
+          cherryPickStatement: 19,
+          acc_title: 20,
+          acc_title_value: 21,
+          acc_descr: 22,
+          acc_descr_value: 23,
+          acc_descr_multiline_value: 24,
+          section: 25,
+          branchStatement: 26,
+          CHECKOUT: 27,
+          ref: 28,
+          BRANCH: 29,
+          ORDER: 30,
+          NUM: 31,
+          CHERRY_PICK: 32,
+          COMMIT_ID: 33,
+          STR: 34,
+          COMMIT_TAG: 35,
+          EMPTYSTR: 36,
+          MERGE: 37,
+          COMMIT_TYPE: 38,
+          commitType: 39,
+          COMMIT: 40,
+          commit_arg: 41,
+          COMMIT_MSG: 42,
+          NORMAL: 43,
+          REVERSE: 44,
+          HIGHLIGHT: 45,
+          openDirective: 46,
+          typeDirective: 47,
+          closeDirective: 48,
+          argDirective: 49,
+          open_directive: 50,
+          type_directive: 51,
+          arg_directive: 52,
+          close_directive: 53,
+          ID: 54,
+          ";": 55,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: {
+          2: "error",
+          6: "GG",
+          8: "EOF",
+          9: ":",
+          10: "DIR",
+          13: "OPT",
+          14: "NL",
+          20: "acc_title",
+          21: "acc_title_value",
+          22: "acc_descr",
+          23: "acc_descr_value",
+          24: "acc_descr_multiline_value",
+          25: "section",
+          27: "CHECKOUT",
+          29: "BRANCH",
+          30: "ORDER",
+          31: "NUM",
+          32: "CHERRY_PICK",
+          33: "COMMIT_ID",
+          34: "STR",
+          35: "COMMIT_TAG",
+          36: "EMPTYSTR",
+          37: "MERGE",
+          38: "COMMIT_TYPE",
+          40: "COMMIT",
+          42: "COMMIT_MSG",
+          43: "NORMAL",
+          44: "REVERSE",
+          45: "HIGHLIGHT",
+          50: "open_directive",
+          51: "type_directive",
+          52: "arg_directive",
+          53: "close_directive",
+          54: "ID",
+          55: ";",
+        },
+        productions_: [
+          0,
+          [3, 2],
+          [3, 2],
+          [3, 3],
+          [3, 4],
+          [3, 5],
+          [7, 0],
+          [7, 2],
+          [11, 2],
+          [11, 1],
+          [12, 0],
+          [12, 2],
+          [15, 2],
+          [15, 1],
+          [16, 1],
+          [16, 1],
+          [16, 1],
+          [16, 2],
+          [16, 2],
+          [16, 1],
+          [16, 1],
+          [16, 1],
+          [16, 2],
+          [26, 2],
+          [26, 4],
+          [19, 3],
+          [19, 5],
+          [19, 5],
+          [19, 5],
+          [19, 5],
+          [18, 2],
+          [18, 4],
+          [18, 4],
+          [18, 4],
+          [18, 6],
+          [18, 6],
+          [18, 6],
+          [18, 6],
+          [18, 6],
+          [18, 6],
+          [18, 8],
+          [18, 8],
+          [18, 8],
+          [18, 8],
+          [18, 8],
+          [18, 8],
+          [17, 2],
+          [17, 3],
+          [17, 3],
+          [17, 5],
+          [17, 5],
+          [17, 3],
+          [17, 5],
+          [17, 5],
+          [17, 5],
+          [17, 5],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 3],
+          [17, 5],
+          [17, 5],
+          [17, 5],
+          [17, 5],
+          [17, 5],
+          [17, 5],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 7],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [17, 9],
+          [41, 0],
+          [41, 1],
+          [39, 1],
+          [39, 1],
+          [39, 1],
+          [5, 3],
+          [5, 5],
+          [46, 1],
+          [47, 1],
+          [49, 1],
+          [48, 1],
+          [28, 1],
+          [28, 1],
+          [4, 1],
+          [4, 1],
+          [4, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 3:
+              return a[o];
+            case 4:
+              return a[o - 1];
+            case 5:
+              return i.setDirection(a[o - 3]), a[o - 1];
+            case 7:
+              i.setOptions(a[o - 1]), this.$ = a[o];
+              break;
+            case 8:
+              a[o - 1] += a[o], this.$ = a[o - 1];
+              break;
+            case 10:
+              this.$ = [];
+              break;
+            case 11:
+              a[o - 1].push(a[o]), this.$ = a[o - 1];
+              break;
+            case 12:
+              this.$ = a[o - 1];
+              break;
+            case 17:
+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 18:
+            case 19:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 20:
+              i.addSection(a[o].substr(8)), this.$ = a[o].substr(8);
+              break;
+            case 22:
+              i.checkout(a[o]);
+              break;
+            case 23:
+              i.branch(a[o]);
+              break;
+            case 24:
+              i.branch(a[o - 2], a[o]);
+              break;
+            case 25:
+              i.cherryPick(a[o], "", void 0);
+              break;
+            case 26:
+              i.cherryPick(a[o - 2], "", a[o]);
+              break;
+            case 27:
+            case 29:
+              i.cherryPick(a[o - 2], "", "");
+              break;
+            case 28:
+              i.cherryPick(a[o], "", a[o - 2]);
+              break;
+            case 30:
+              i.merge(a[o], "", "", "");
+              break;
+            case 31:
+              i.merge(a[o - 2], a[o], "", "");
+              break;
+            case 32:
+              i.merge(a[o - 2], "", a[o], "");
+              break;
+            case 33:
+              i.merge(a[o - 2], "", "", a[o]);
+              break;
+            case 34:
+              i.merge(a[o - 4], a[o], "", a[o - 2]);
+              break;
+            case 35:
+              i.merge(a[o - 4], "", a[o], a[o - 2]);
+              break;
+            case 36:
+              i.merge(a[o - 4], "", a[o - 2], a[o]);
+              break;
+            case 37:
+              i.merge(a[o - 4], a[o - 2], a[o], "");
+              break;
+            case 38:
+              i.merge(a[o - 4], a[o - 2], "", a[o]);
+              break;
+            case 39:
+              i.merge(a[o - 4], a[o], a[o - 2], "");
+              break;
+            case 40:
+              i.merge(a[o - 6], a[o - 4], a[o - 2], a[o]);
+              break;
+            case 41:
+              i.merge(a[o - 6], a[o], a[o - 4], a[o - 2]);
+              break;
+            case 42:
+              i.merge(a[o - 6], a[o - 4], a[o], a[o - 2]);
+              break;
+            case 43:
+              i.merge(a[o - 6], a[o - 2], a[o - 4], a[o]);
+              break;
+            case 44:
+              i.merge(a[o - 6], a[o], a[o - 2], a[o - 4]);
+              break;
+            case 45:
+              i.merge(a[o - 6], a[o - 2], a[o], a[o - 4]);
+              break;
+            case 46:
+              i.commit(a[o]);
+              break;
+            case 47:
+              i.commit("", "", i.commitType.NORMAL, a[o]);
+              break;
+            case 48:
+              i.commit("", "", a[o], "");
+              break;
+            case 49:
+              i.commit("", "", a[o], a[o - 2]);
+              break;
+            case 50:
+              i.commit("", "", a[o - 2], a[o]);
+              break;
+            case 51:
+              i.commit("", a[o], i.commitType.NORMAL, "");
+              break;
+            case 52:
+              i.commit("", a[o - 2], i.commitType.NORMAL, a[o]);
+              break;
+            case 53:
+              i.commit("", a[o], i.commitType.NORMAL, a[o - 2]);
+              break;
+            case 54:
+              i.commit("", a[o - 2], a[o], "");
+              break;
+            case 55:
+              i.commit("", a[o], a[o - 2], "");
+              break;
+            case 56:
+              i.commit("", a[o - 4], a[o - 2], a[o]);
+              break;
+            case 57:
+              i.commit("", a[o - 4], a[o], a[o - 2]);
+              break;
+            case 58:
+              i.commit("", a[o - 2], a[o - 4], a[o]);
+              break;
+            case 59:
+              i.commit("", a[o], a[o - 4], a[o - 2]);
+              break;
+            case 60:
+              i.commit("", a[o], a[o - 2], a[o - 4]);
+              break;
+            case 61:
+              i.commit("", a[o - 2], a[o], a[o - 4]);
+              break;
+            case 62:
+              i.commit(a[o], "", i.commitType.NORMAL, "");
+              break;
+            case 63:
+              i.commit(a[o], "", i.commitType.NORMAL, a[o - 2]);
+              break;
+            case 64:
+              i.commit(a[o - 2], "", i.commitType.NORMAL, a[o]);
+              break;
+            case 65:
+              i.commit(a[o - 2], "", a[o], "");
+              break;
+            case 66:
+              i.commit(a[o], "", a[o - 2], "");
+              break;
+            case 67:
+              i.commit(a[o], a[o - 2], i.commitType.NORMAL, "");
+              break;
+            case 68:
+              i.commit(a[o - 2], a[o], i.commitType.NORMAL, "");
+              break;
+            case 69:
+              i.commit(a[o - 4], "", a[o - 2], a[o]);
+              break;
+            case 70:
+              i.commit(a[o - 4], "", a[o], a[o - 2]);
+              break;
+            case 71:
+              i.commit(a[o - 2], "", a[o - 4], a[o]);
+              break;
+            case 72:
+              i.commit(a[o], "", a[o - 4], a[o - 2]);
+              break;
+            case 73:
+              i.commit(a[o], "", a[o - 2], a[o - 4]);
+              break;
+            case 74:
+              i.commit(a[o - 2], "", a[o], a[o - 4]);
+              break;
+            case 75:
+              i.commit(a[o - 4], a[o], a[o - 2], "");
+              break;
+            case 76:
+              i.commit(a[o - 4], a[o - 2], a[o], "");
+              break;
+            case 77:
+              i.commit(a[o - 2], a[o], a[o - 4], "");
+              break;
+            case 78:
+              i.commit(a[o], a[o - 2], a[o - 4], "");
+              break;
+            case 79:
+              i.commit(a[o], a[o - 4], a[o - 2], "");
+              break;
+            case 80:
+              i.commit(a[o - 2], a[o - 4], a[o], "");
+              break;
+            case 81:
+              i.commit(a[o - 4], a[o], i.commitType.NORMAL, a[o - 2]);
+              break;
+            case 82:
+              i.commit(a[o - 4], a[o - 2], i.commitType.NORMAL, a[o]);
+              break;
+            case 83:
+              i.commit(a[o - 2], a[o], i.commitType.NORMAL, a[o - 4]);
+              break;
+            case 84:
+              i.commit(a[o], a[o - 2], i.commitType.NORMAL, a[o - 4]);
+              break;
+            case 85:
+              i.commit(a[o], a[o - 4], i.commitType.NORMAL, a[o - 2]);
+              break;
+            case 86:
+              i.commit(a[o - 2], a[o - 4], i.commitType.NORMAL, a[o]);
+              break;
+            case 87:
+              i.commit(a[o - 6], a[o - 4], a[o - 2], a[o]);
+              break;
+            case 88:
+              i.commit(a[o - 6], a[o - 4], a[o], a[o - 2]);
+              break;
+            case 89:
+              i.commit(a[o - 6], a[o - 2], a[o - 4], a[o]);
+              break;
+            case 90:
+              i.commit(a[o - 6], a[o], a[o - 4], a[o - 2]);
+              break;
+            case 91:
+              i.commit(a[o - 6], a[o - 2], a[o], a[o - 4]);
+              break;
+            case 92:
+              i.commit(a[o - 6], a[o], a[o - 2], a[o - 4]);
+              break;
+            case 93:
+              i.commit(a[o - 4], a[o - 6], a[o - 2], a[o]);
+              break;
+            case 94:
+              i.commit(a[o - 4], a[o - 6], a[o], a[o - 2]);
+              break;
+            case 95:
+              i.commit(a[o - 2], a[o - 6], a[o - 4], a[o]);
+              break;
+            case 96:
+              i.commit(a[o], a[o - 6], a[o - 4], a[o - 2]);
+              break;
+            case 97:
+              i.commit(a[o - 2], a[o - 6], a[o], a[o - 4]);
+              break;
+            case 98:
+              i.commit(a[o], a[o - 6], a[o - 2], a[o - 4]);
+              break;
+            case 99:
+              i.commit(a[o], a[o - 4], a[o - 2], a[o - 6]);
+              break;
+            case 100:
+              i.commit(a[o - 2], a[o - 4], a[o], a[o - 6]);
+              break;
+            case 101:
+              i.commit(a[o], a[o - 2], a[o - 4], a[o - 6]);
+              break;
+            case 102:
+              i.commit(a[o - 2], a[o], a[o - 4], a[o - 6]);
+              break;
+            case 103:
+              i.commit(a[o - 4], a[o - 2], a[o], a[o - 6]);
+              break;
+            case 104:
+              i.commit(a[o - 4], a[o], a[o - 2], a[o - 6]);
+              break;
+            case 105:
+              i.commit(a[o - 2], a[o - 4], a[o - 6], a[o]);
+              break;
+            case 106:
+              i.commit(a[o], a[o - 4], a[o - 6], a[o - 2]);
+              break;
+            case 107:
+              i.commit(a[o - 2], a[o], a[o - 6], a[o - 4]);
+              break;
+            case 108:
+              i.commit(a[o], a[o - 2], a[o - 6], a[o - 4]);
+              break;
+            case 109:
+              i.commit(a[o - 4], a[o - 2], a[o - 6], a[o]);
+              break;
+            case 110:
+              i.commit(a[o - 4], a[o], a[o - 6], a[o - 2]);
+              break;
+            case 111:
+              this.$ = "";
+              break;
+            case 112:
+              this.$ = a[o];
+              break;
+            case 113:
+              this.$ = i.commitType.NORMAL;
+              break;
+            case 114:
+              this.$ = i.commitType.REVERSE;
+              break;
+            case 115:
+              this.$ = i.commitType.HIGHLIGHT;
+              break;
+            case 118:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 119:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 120:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 121:
+              i.parseDirective("}%%", "close_directive", "gitGraph");
+          }
+        },
+        table: [
+          { 3: 1, 4: 2, 5: 3, 6: n, 8: i, 14: r, 46: 8, 50: a, 55: s },
+          { 1: [3] },
+          { 3: 10, 4: 2, 5: 3, 6: n, 8: i, 14: r, 46: 8, 50: a, 55: s },
+          { 3: 11, 4: 2, 5: 3, 6: n, 8: i, 14: r, 46: 8, 50: a, 55: s },
+          { 7: 12, 8: o, 9: [1, 13], 10: [1, 14], 11: 15, 14: l },
+          e(c, [2, 124]),
+          e(c, [2, 125]),
+          e(c, [2, 126]),
+          { 47: 17, 51: [1, 18] },
+          { 51: [2, 118] },
+          { 1: [2, 1] },
+          { 1: [2, 2] },
+          { 8: [1, 19] },
+          { 7: 20, 8: o, 11: 15, 14: l },
+          { 9: [1, 21] },
+          e(h, [2, 10], { 12: 22, 13: [1, 23] }),
+          e(u, [2, 9]),
+          { 9: [1, 25], 48: 24, 53: d },
+          e([9, 53], [2, 119]),
+          { 1: [2, 3] },
+          { 8: [1, 27] },
+          { 7: 28, 8: o, 11: 15, 14: l },
+          {
+            8: [2, 7],
+            14: [1, 31],
+            15: 29,
+            16: 30,
+            17: 32,
+            18: 33,
+            19: 34,
+            20: [1, 35],
+            22: [1, 36],
+            24: [1, 37],
+            25: [1, 38],
+            26: 39,
+            27: [1, 40],
+            29: [1, 44],
+            32: [1, 43],
+            37: [1, 42],
+            40: [1, 41],
+          },
+          e(u, [2, 8]),
+          e(p, [2, 116]),
+          { 49: 45, 52: [1, 46] },
+          e(p, [2, 121]),
+          { 1: [2, 4] },
+          { 8: [1, 47] },
+          e(h, [2, 11]),
+          { 4: 48, 8: i, 14: r, 55: s },
+          e(h, [2, 13]),
+          e(f, [2, 14]),
+          e(f, [2, 15]),
+          e(f, [2, 16]),
+          { 21: [1, 49] },
+          { 23: [1, 50] },
+          e(f, [2, 19]),
+          e(f, [2, 20]),
+          e(f, [2, 21]),
+          { 28: 51, 34: g, 54: y },
+          e(f, [2, 111], { 41: 54, 33: [1, 57], 34: [1, 59], 35: [1, 55], 38: [1, 56], 42: [1, 58] }),
+          { 28: 60, 34: g, 54: y },
+          { 33: [1, 61], 35: [1, 62] },
+          { 28: 63, 34: g, 54: y },
+          { 48: 64, 53: d },
+          { 53: [2, 120] },
+          { 1: [2, 5] },
+          e(h, [2, 12]),
+          e(f, [2, 17]),
+          e(f, [2, 18]),
+          e(f, [2, 22]),
+          e(m, [2, 122]),
+          e(m, [2, 123]),
+          e(f, [2, 46]),
+          { 34: [1, 65] },
+          { 39: 66, 43: b, 44: _, 45: x },
+          { 34: [1, 70] },
+          { 34: [1, 71] },
+          e(f, [2, 112]),
+          e(f, [2, 30], { 33: [1, 72], 35: [1, 74], 38: [1, 73] }),
+          { 34: [1, 75] },
+          { 34: [1, 76], 36: [1, 77] },
+          e(f, [2, 23], { 30: [1, 78] }),
+          e(p, [2, 117]),
+          e(f, [2, 47], { 33: [1, 80], 38: [1, 79], 42: [1, 81] }),
+          e(f, [2, 48], { 33: [1, 83], 35: [1, 82], 42: [1, 84] }),
+          e(v, [2, 113]),
+          e(v, [2, 114]),
+          e(v, [2, 115]),
+          e(f, [2, 51], { 35: [1, 85], 38: [1, 86], 42: [1, 87] }),
+          e(f, [2, 62], { 33: [1, 90], 35: [1, 88], 38: [1, 89] }),
+          { 34: [1, 91] },
+          { 39: 92, 43: b, 44: _, 45: x },
+          { 34: [1, 93] },
+          e(f, [2, 25], { 35: [1, 94] }),
+          { 33: [1, 95] },
+          { 33: [1, 96] },
+          { 31: [1, 97] },
+          { 39: 98, 43: b, 44: _, 45: x },
+          { 34: [1, 99] },
+          { 34: [1, 100] },
+          { 34: [1, 101] },
+          { 34: [1, 102] },
+          { 34: [1, 103] },
+          { 34: [1, 104] },
+          { 39: 105, 43: b, 44: _, 45: x },
+          { 34: [1, 106] },
+          { 34: [1, 107] },
+          { 39: 108, 43: b, 44: _, 45: x },
+          { 34: [1, 109] },
+          e(f, [2, 31], { 35: [1, 111], 38: [1, 110] }),
+          e(f, [2, 32], { 33: [1, 113], 35: [1, 112] }),
+          e(f, [2, 33], { 33: [1, 114], 38: [1, 115] }),
+          { 34: [1, 116], 36: [1, 117] },
+          { 34: [1, 118] },
+          { 34: [1, 119] },
+          e(f, [2, 24]),
+          e(f, [2, 49], { 33: [1, 120], 42: [1, 121] }),
+          e(f, [2, 53], { 38: [1, 122], 42: [1, 123] }),
+          e(f, [2, 63], { 33: [1, 125], 38: [1, 124] }),
+          e(f, [2, 50], { 33: [1, 126], 42: [1, 127] }),
+          e(f, [2, 55], { 35: [1, 128], 42: [1, 129] }),
+          e(f, [2, 66], { 33: [1, 131], 35: [1, 130] }),
+          e(f, [2, 52], { 38: [1, 132], 42: [1, 133] }),
+          e(f, [2, 54], { 35: [1, 134], 42: [1, 135] }),
+          e(f, [2, 67], { 35: [1, 137], 38: [1, 136] }),
+          e(f, [2, 64], { 33: [1, 139], 38: [1, 138] }),
+          e(f, [2, 65], { 33: [1, 141], 35: [1, 140] }),
+          e(f, [2, 68], { 35: [1, 143], 38: [1, 142] }),
+          { 39: 144, 43: b, 44: _, 45: x },
+          { 34: [1, 145] },
+          { 34: [1, 146] },
+          { 34: [1, 147] },
+          { 34: [1, 148] },
+          { 39: 149, 43: b, 44: _, 45: x },
+          e(f, [2, 26]),
+          e(f, [2, 27]),
+          e(f, [2, 28]),
+          e(f, [2, 29]),
+          { 34: [1, 150] },
+          { 34: [1, 151] },
+          { 39: 152, 43: b, 44: _, 45: x },
+          { 34: [1, 153] },
+          { 39: 154, 43: b, 44: _, 45: x },
+          { 34: [1, 155] },
+          { 34: [1, 156] },
+          { 34: [1, 157] },
+          { 34: [1, 158] },
+          { 34: [1, 159] },
+          { 34: [1, 160] },
+          { 34: [1, 161] },
+          { 39: 162, 43: b, 44: _, 45: x },
+          { 34: [1, 163] },
+          { 34: [1, 164] },
+          { 34: [1, 165] },
+          { 39: 166, 43: b, 44: _, 45: x },
+          { 34: [1, 167] },
+          { 39: 168, 43: b, 44: _, 45: x },
+          { 34: [1, 169] },
+          { 34: [1, 170] },
+          { 34: [1, 171] },
+          { 39: 172, 43: b, 44: _, 45: x },
+          { 34: [1, 173] },
+          e(f, [2, 37], { 35: [1, 174] }),
+          e(f, [2, 38], { 38: [1, 175] }),
+          e(f, [2, 36], { 33: [1, 176] }),
+          e(f, [2, 39], { 35: [1, 177] }),
+          e(f, [2, 34], { 38: [1, 178] }),
+          e(f, [2, 35], { 33: [1, 179] }),
+          e(f, [2, 60], { 42: [1, 180] }),
+          e(f, [2, 73], { 33: [1, 181] }),
+          e(f, [2, 61], { 42: [1, 182] }),
+          e(f, [2, 84], { 38: [1, 183] }),
+          e(f, [2, 74], { 33: [1, 184] }),
+          e(f, [2, 83], { 38: [1, 185] }),
+          e(f, [2, 59], { 42: [1, 186] }),
+          e(f, [2, 72], { 33: [1, 187] }),
+          e(f, [2, 58], { 42: [1, 188] }),
+          e(f, [2, 78], { 35: [1, 189] }),
+          e(f, [2, 71], { 33: [1, 190] }),
+          e(f, [2, 77], { 35: [1, 191] }),
+          e(f, [2, 57], { 42: [1, 192] }),
+          e(f, [2, 85], { 38: [1, 193] }),
+          e(f, [2, 56], { 42: [1, 194] }),
+          e(f, [2, 79], { 35: [1, 195] }),
+          e(f, [2, 80], { 35: [1, 196] }),
+          e(f, [2, 86], { 38: [1, 197] }),
+          e(f, [2, 70], { 33: [1, 198] }),
+          e(f, [2, 81], { 38: [1, 199] }),
+          e(f, [2, 69], { 33: [1, 200] }),
+          e(f, [2, 75], { 35: [1, 201] }),
+          e(f, [2, 76], { 35: [1, 202] }),
+          e(f, [2, 82], { 38: [1, 203] }),
+          { 34: [1, 204] },
+          { 39: 205, 43: b, 44: _, 45: x },
+          { 34: [1, 206] },
+          { 34: [1, 207] },
+          { 39: 208, 43: b, 44: _, 45: x },
+          { 34: [1, 209] },
+          { 34: [1, 210] },
+          { 34: [1, 211] },
+          { 34: [1, 212] },
+          { 39: 213, 43: b, 44: _, 45: x },
+          { 34: [1, 214] },
+          { 39: 215, 43: b, 44: _, 45: x },
+          { 34: [1, 216] },
+          { 34: [1, 217] },
+          { 34: [1, 218] },
+          { 34: [1, 219] },
+          { 34: [1, 220] },
+          { 34: [1, 221] },
+          { 34: [1, 222] },
+          { 39: 223, 43: b, 44: _, 45: x },
+          { 34: [1, 224] },
+          { 34: [1, 225] },
+          { 34: [1, 226] },
+          { 39: 227, 43: b, 44: _, 45: x },
+          { 34: [1, 228] },
+          { 39: 229, 43: b, 44: _, 45: x },
+          { 34: [1, 230] },
+          { 34: [1, 231] },
+          { 34: [1, 232] },
+          { 39: 233, 43: b, 44: _, 45: x },
+          e(f, [2, 40]),
+          e(f, [2, 42]),
+          e(f, [2, 41]),
+          e(f, [2, 43]),
+          e(f, [2, 45]),
+          e(f, [2, 44]),
+          e(f, [2, 101]),
+          e(f, [2, 102]),
+          e(f, [2, 99]),
+          e(f, [2, 100]),
+          e(f, [2, 104]),
+          e(f, [2, 103]),
+          e(f, [2, 108]),
+          e(f, [2, 107]),
+          e(f, [2, 106]),
+          e(f, [2, 105]),
+          e(f, [2, 110]),
+          e(f, [2, 109]),
+          e(f, [2, 98]),
+          e(f, [2, 97]),
+          e(f, [2, 96]),
+          e(f, [2, 95]),
+          e(f, [2, 93]),
+          e(f, [2, 94]),
+          e(f, [2, 92]),
+          e(f, [2, 91]),
+          e(f, [2, 90]),
+          e(f, [2, 89]),
+          e(f, [2, 87]),
+          e(f, [2, 88]),
+        ],
+        defaultActions: { 9: [2, 118], 10: [2, 1], 11: [2, 2], 19: [2, 3], 27: [2, 4], 46: [2, 120], 47: [2, 5] },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      w = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: { "case-insensitive": !0 },
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("open_directive"), 50;
+            case 1:
+              return this.begin("type_directive"), 51;
+            case 2:
+              return this.popState(), this.begin("arg_directive"), 9;
+            case 3:
+              return this.popState(), this.popState(), 53;
+            case 4:
+              return 52;
+            case 5:
+              return this.begin("acc_title"), 20;
+            case 6:
+              return this.popState(), "acc_title_value";
+            case 7:
+              return this.begin("acc_descr"), 22;
+            case 8:
+              return this.popState(), "acc_descr_value";
+            case 9:
+              this.begin("acc_descr_multiline");
+              break;
+            case 10:
+            case 34:
+            case 38:
+              this.popState();
+              break;
+            case 11:
+              return "acc_descr_multiline_value";
+            case 12:
+              return 14;
+            case 13:
+            case 14:
+              break;
+            case 15:
+              return 6;
+            case 16:
+              return 40;
+            case 17:
+              return 33;
+            case 18:
+              return 38;
+            case 19:
+              return 42;
+            case 20:
+              return 43;
+            case 21:
+              return 44;
+            case 22:
+              return 45;
+            case 23:
+              return 35;
+            case 24:
+              return 29;
+            case 25:
+              return 30;
+            case 26:
+              return 37;
+            case 27:
+              return 32;
+            case 28:
+              return 27;
+            case 29:
+            case 30:
+              return 10;
+            case 31:
+              return 9;
+            case 32:
+              return "CARET";
+            case 33:
+              this.begin("options");
+              break;
+            case 35:
+              return 13;
+            case 36:
+              return 36;
+            case 37:
+              this.begin("string");
+              break;
+            case 39:
+              return 34;
+            case 40:
+              return 31;
+            case 41:
+              return 54;
+            case 42:
+              return 8;
+          }
+        },
+        rules: [
+          /^(?:%%\{)/i,
+          /^(?:((?:(?!\}%%)[^:.])*))/i,
+          /^(?::)/i,
+          /^(?:\}%%)/i,
+          /^(?:((?:(?!\}%%).|\n)*))/i,
+          /^(?:accTitle\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*\{\s*)/i,
+          /^(?:[\}])/i,
+          /^(?:[^\}]*)/i,
+          /^(?:(\r?\n)+)/i,
+          /^(?:#[^\n]*)/i,
+          /^(?:%[^\n]*)/i,
+          /^(?:gitGraph\b)/i,
+          /^(?:commit(?=\s|$))/i,
+          /^(?:id:)/i,
+          /^(?:type:)/i,
+          /^(?:msg:)/i,
+          /^(?:NORMAL\b)/i,
+          /^(?:REVERSE\b)/i,
+          /^(?:HIGHLIGHT\b)/i,
+          /^(?:tag:)/i,
+          /^(?:branch(?=\s|$))/i,
+          /^(?:order:)/i,
+          /^(?:merge(?=\s|$))/i,
+          /^(?:cherry-pick(?=\s|$))/i,
+          /^(?:checkout(?=\s|$))/i,
+          /^(?:LR\b)/i,
+          /^(?:BT\b)/i,
+          /^(?::)/i,
+          /^(?:\^)/i,
+          /^(?:options\r?\n)/i,
+          /^(?:[ \r\n\t]+end\b)/i,
+          /^(?:[\s\S]+(?=[ \r\n\t]+end))/i,
+          /^(?:["]["])/i,
+          /^(?:["])/i,
+          /^(?:["])/i,
+          /^(?:[^"]*)/i,
+          /^(?:[0-9]+(?=\s|$))/i,
+          /^(?:\w([-\./\w]*[-\w])?)/i,
+          /^(?:$)/i,
+          /^(?:\s+)/i,
+        ],
+        conditions: {
+          acc_descr_multiline: { rules: [10, 11], inclusive: !1 },
+          acc_descr: { rules: [8], inclusive: !1 },
+          acc_title: { rules: [6], inclusive: !1 },
+          close_directive: { rules: [], inclusive: !1 },
+          arg_directive: { rules: [3, 4], inclusive: !1 },
+          type_directive: { rules: [2, 3], inclusive: !1 },
+          open_directive: { rules: [1], inclusive: !1 },
+          options: { rules: [34, 35], inclusive: !1 },
+          string: { rules: [38, 39], inclusive: !1 },
+          INITIAL: {
+            rules: [
+              0,
+              5,
+              7,
+              9,
+              12,
+              13,
+              14,
+              15,
+              16,
+              17,
+              18,
+              19,
+              20,
+              21,
+              22,
+              23,
+              24,
+              25,
+              26,
+              27,
+              28,
+              29,
+              30,
+              31,
+              32,
+              33,
+              36,
+              37,
+              40,
+              41,
+              42,
+              43,
+            ],
+            inclusive: !0,
+          },
+        },
+      },
+        t);
+    function T() {
+      this.yy = {};
+    }
+    return k.lexer = w, T.prototype = k, k.Parser = T, new T();
+  }();
+  bv.parser = bv;
+  const _v = bv, xv = t => null !== t.match(/^\s*gitGraph/);
+  let vv = "", kv = "", wv = "";
+  const Tv = t => ab(t, jx()),
+    Cv = function() {
+      vv = "", wv = "", kv = "";
+    },
+    Ev = function(t) {
+      vv = Tv(t).replace(/^\s+/g, "");
+    },
+    Sv = function() {
+      return vv || kv;
+    },
+    Av = function(t) {
+      wv = Tv(t).replace(/\n\s+/g, "\n");
+    },
+    Dv = function() {
+      return wv;
+    },
+    Lv = function(t) {
+      kv = Tv(t);
+    },
+    Ov = function() {
+      return kv;
+    };
+  let Nv = jx().gitGraph.mainBranchName, Mv = jx().gitGraph.mainBranchOrder, Bv = {}, Iv = null, Fv = {};
+  Fv[Nv] = { name: Nv, order: Mv };
+  let Rv = {};
+  Rv[Nv] = Iv;
+  let $v = Nv, Pv = "LR", Yv = 0;
+  function jv() {
+    return bx({ length: 7 });
+  }
+  let zv = {};
+  const Uv = function(t) {
+    if (t = ub.sanitizeText(t, jx()), void 0 === Rv[t]) {
+      let e = new Error("Trying to checkout branch which is not yet created. (Help try using \"branch " + t + "\")");
+      throw e.hash = {
+        text: "checkout " + t,
+        token: "checkout " + t,
+        line: "1",
+        loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+        expected: ["\"branch " + t + "\""],
+      },
+        e;
+    }
+    {
+      $v = t;
+      const e = Rv[$v];
+      Iv = Bv[e];
+    }
+  };
+  function Wv(t, e, n) {
+    const i = t.indexOf(e);
+    -1 === i ? t.push(n) : t.splice(i, 1, n);
+  }
+  function Hv(t) {
+    const e = t.reduce((t, e) => t.seq > e.seq ? t : e, t[0]);
+    let n = "";
+    t.forEach(function(t) {
+      n += t === e ? "\t*" : "\t|";
+    });
+    const i = [n, e.id, e.seq];
+    for (let t in Rv) Rv[t] === e.id && i.push(t);
+    if (tb.debug(i.join(" ")), e.parents && 2 == e.parents.length) {
+      const n = Bv[e.parents[0]];
+      Wv(t, e, n), t.push(Bv[e.parents[1]]);
+    } else {
+      if (0 == e.parents.length) return;
+      {
+        const n = Bv[e.parents];
+        Wv(t, e, n);
+      }
+    }
+    Hv(
+      t = function(t, e) {
+        const n = Object.create(null);
+        return t.reduce((t, i) => {
+          const r = e(i);
+          return n[r] || (n[r] = !0, t.push(i)), t;
+        }, []);
+      }(t, t => t.id),
+    );
+  }
+  const qv = function() {
+      const t = Object.keys(Bv).map(function(t) {
+        return Bv[t];
+      });
+      return t.forEach(function(t) {
+        tb.debug(t.id);
+      }),
+        t.sort((t, e) => t.seq - e.seq),
+        t;
+    },
+    Vv = { NORMAL: 0, REVERSE: 1, HIGHLIGHT: 2, MERGE: 3, CHERRY_PICK: 4 },
+    Gv = {
+      parseDirective: function(t, e, n) {
+        nL.parseDirective(this, t, e, n);
+      },
+      getConfig: () => jx().gitGraph,
+      setDirection: function(t) {
+        Pv = t;
+      },
+      setOptions: function(t) {
+        tb.debug("options str", t), t = (t = t && t.trim()) || "{}";
+        try {
+          zv = JSON.parse(t);
+        } catch (t) {
+          tb.error("error while parsing gitGraph options", t.message);
+        }
+      },
+      getOptions: function() {
+        return zv;
+      },
+      commit: function(t, e, n, i) {
+        tb.debug("Entering commit:", t, e, n, i),
+          e = ub.sanitizeText(e, jx()),
+          t = ub.sanitizeText(t, jx()),
+          i = ub.sanitizeText(i, jx());
+        const r = {
+          id: e || Yv + "-" + jv(),
+          message: t,
+          seq: Yv++,
+          type: n || Vv.NORMAL,
+          tag: i || "",
+          parents: null == Iv ? [] : [Iv.id],
+          branch: $v,
+        };
+        Iv = r, Bv[r.id] = r, Rv[$v] = r.id, tb.debug("in pushCommit " + r.id);
+      },
+      branch: function(t, e) {
+        if (t = ub.sanitizeText(t, jx()), void 0 !== Rv[t]) {
+          let e = new Error(
+            "Trying to create an existing branch. (Help: Either use a new name if you want create a new branch or try using \"checkout "
+              + t + "\")",
+          );
+          throw e.hash = {
+            text: "branch " + t,
+            token: "branch " + t,
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["\"checkout " + t + "\""],
+          },
+            e;
+        }
+        Rv[t] = null != Iv ? Iv.id : null,
+          Fv[t] = { name: t, order: e ? parseInt(e, 10) : null },
+          Uv(t),
+          tb.debug("in createBranch");
+      },
+      merge: function(t, e, n, i) {
+        t = ub.sanitizeText(t, jx()), e = ub.sanitizeText(e, jx());
+        const r = Bv[Rv[$v]], a = Bv[Rv[t]];
+        if ($v === t) {
+          let e = new Error("Incorrect usage of \"merge\". Cannot merge a branch to itself");
+          throw e.hash = {
+            text: "merge " + t,
+            token: "merge " + t,
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["branch abc"],
+          },
+            e;
+        }
+        if (void 0 === r || !r) {
+          let e = new Error("Incorrect usage of \"merge\". Current branch (" + $v + ")has no commits");
+          throw e.hash = {
+            text: "merge " + t,
+            token: "merge " + t,
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["commit"],
+          },
+            e;
+        }
+        if (void 0 === Rv[t]) {
+          let e = new Error("Incorrect usage of \"merge\". Branch to be merged (" + t + ") does not exist");
+          throw e.hash = {
+            text: "merge " + t,
+            token: "merge " + t,
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["branch " + t],
+          },
+            e;
+        }
+        if (void 0 === a || !a) {
+          let e = new Error("Incorrect usage of \"merge\". Branch to be merged (" + t + ") has no commits");
+          throw e.hash = {
+            text: "merge " + t,
+            token: "merge " + t,
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["\"commit\""],
+          },
+            e;
+        }
+        if (r === a) {
+          let e = new Error("Incorrect usage of \"merge\". Both branches have same head");
+          throw e.hash = {
+            text: "merge " + t,
+            token: "merge " + t,
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["branch abc"],
+          },
+            e;
+        }
+        if (e && void 0 !== Bv[e]) {
+          let r = new Error(
+            "Incorrect usage of \"merge\". Commit with id:" + e + " already exists, use different custom Id",
+          );
+          throw r.hash = {
+            text: "merge " + t + e + n + i,
+            token: "merge " + t + e + n + i,
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["merge " + t + " " + e + "_UNIQUE " + n + " " + i],
+          },
+            r;
+        }
+        const s = {
+          id: e || Yv + "-" + jv(),
+          message: "merged branch " + t + " into " + $v,
+          seq: Yv++,
+          parents: [null == Iv ? null : Iv.id, Rv[t]],
+          branch: $v,
+          type: Vv.MERGE,
+          customType: n,
+          customId: !!e,
+          tag: i || "",
+        };
+        Iv = s, Bv[s.id] = s, Rv[$v] = s.id, tb.debug(Rv), tb.debug("in mergeBranch");
+      },
+      cherryPick: function(t, e, n) {
+        if (
+          tb.debug("Entering cherryPick:", t, e, n),
+            t = ub.sanitizeText(t, jx()),
+            e = ub.sanitizeText(e, jx()),
+            n = ub.sanitizeText(n, jx()),
+            !t || void 0 === Bv[t]
+        ) {
+          let n = new Error("Incorrect usage of \"cherryPick\". Source commit id should exist and provided");
+          throw n.hash = {
+            text: "cherryPick " + t + " " + e,
+            token: "cherryPick " + t + " " + e,
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["cherry-pick abc"],
+          },
+            n;
+        }
+        let i = Bv[t], r = i.branch;
+        if (i.type === Vv.MERGE) {
+          let n = new Error("Incorrect usage of \"cherryPick\". Source commit should not be a merge commit");
+          throw n.hash = {
+            text: "cherryPick " + t + " " + e,
+            token: "cherryPick " + t + " " + e,
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["cherry-pick abc"],
+          },
+            n;
+        }
+        if (!e || void 0 === Bv[e]) {
+          if (r === $v) {
+            let n = new Error("Incorrect usage of \"cherryPick\". Source commit is already on current branch");
+            throw n.hash = {
+              text: "cherryPick " + t + " " + e,
+              token: "cherryPick " + t + " " + e,
+              line: "1",
+              loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+              expected: ["cherry-pick abc"],
+            },
+              n;
+          }
+          const a = Bv[Rv[$v]];
+          if (void 0 === a || !a) {
+            let n = new Error("Incorrect usage of \"cherry-pick\". Current branch (" + $v + ")has no commits");
+            throw n.hash = {
+              text: "cherryPick " + t + " " + e,
+              token: "cherryPick " + t + " " + e,
+              line: "1",
+              loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+              expected: ["cherry-pick abc"],
+            },
+              n;
+          }
+          const s = {
+            id: Yv + "-" + jv(),
+            message: "cherry-picked " + i + " into " + $v,
+            seq: Yv++,
+            parents: [null == Iv ? null : Iv.id, i.id],
+            branch: $v,
+            type: Vv.CHERRY_PICK,
+            tag: null != n ? n : "cherry-pick:" + i.id,
+          };
+          Iv = s, Bv[s.id] = s, Rv[$v] = s.id, tb.debug(Rv), tb.debug("in cherryPick");
+        }
+      },
+      checkout: Uv,
+      prettyPrint: function() {
+        tb.debug(Bv);
+        Hv([qv()[0]]);
+      },
+      clear: function() {
+        Bv = {}, Iv = null;
+        let t = jx().gitGraph.mainBranchName, e = jx().gitGraph.mainBranchOrder;
+        Rv = {}, Rv[t] = null, Fv = {}, Fv[t] = { name: t, order: e }, $v = t, Yv = 0, Cv();
+      },
+      getBranchesAsObjArray: function() {
+        const t = Object.values(Fv).map((t, e) => null !== t.order ? t : { ...t, order: parseFloat(`0.${e}`, 10) })
+          .sort((t, e) => t.order - e.order).map(({ name: t }) => ({ name: t }));
+        return t;
+      },
+      getBranches: function() {
+        return Rv;
+      },
+      getCommits: function() {
+        return Bv;
+      },
+      getCommitsArray: qv,
+      getCurrentBranch: function() {
+        return $v;
+      },
+      getDirection: function() {
+        return Pv;
+      },
+      getHead: function() {
+        return Iv;
+      },
+      setAccTitle: Ev,
+      getAccTitle: Sv,
+      getAccDescription: Dv,
+      setAccDescription: Av,
+      setDiagramTitle: Lv,
+      getDiagramTitle: Ov,
+      commitType: Vv,
+    };
+  let Xv = {};
+  const Zv = 0, Qv = 1, Kv = 2, Jv = 3, tk = 4;
+  let ek = {}, nk = {}, ik = [], rk = 0;
+  const ak = (t, e, n) => {
+      const i = dv().gitGraph,
+        r = t.append("g").attr("class", "commit-bullets"),
+        a = t.append("g").attr("class", "commit-labels");
+      let s = 0;
+      Object.keys(e).sort((t, n) => e[t].seq - e[n].seq).forEach(t => {
+        const o = e[t], l = ek[o.branch].pos, c = s + 10;
+        if (n) {
+          let t, e = void 0 !== o.customType && "" !== o.customType ? o.customType : o.type;
+          switch (e) {
+            case Zv:
+              t = "commit-normal";
+              break;
+            case Qv:
+              t = "commit-reverse";
+              break;
+            case Kv:
+              t = "commit-highlight";
+              break;
+            case Jv:
+              t = "commit-merge";
+              break;
+            case tk:
+              t = "commit-cherry-pick";
+              break;
+            default:
+              t = "commit-normal";
+          }
+          if (e === Kv) {
+            const e = r.append("rect");
+            e.attr("x", c - 10),
+              e.attr("y", l - 10),
+              e.attr("height", 20),
+              e.attr("width", 20),
+              e.attr("class", `commit ${o.id} commit-highlight${ek[o.branch].index % 8} ${t}-outer`),
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+                "class",
+                `commit ${o.id} commit${ek[o.branch].index % 8} ${t}-inner`,
+              );
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+            r.append("circle").attr("cx", c).attr("cy", l).attr("r", 10).attr("class", `commit ${o.id} ${t}`),
+              r.append("circle").attr("cx", c - 3).attr("cy", l + 2).attr("r", 2.75).attr("fill", "#fff").attr(
+                "class",
+                `commit ${o.id} ${t}`,
+              ),
+              r.append("circle").attr("cx", c + 3).attr("cy", l + 2).attr("r", 2.75).attr("fill", "#fff").attr(
+                "class",
+                `commit ${o.id} ${t}`,
+              ),
+              r.append("line").attr("x1", c + 3).attr("y1", l + 1).attr("x2", c).attr("y2", l - 5).attr(
+                "stroke",
+                "#fff",
+              ).attr("class", `commit ${o.id} ${t}`),
+              r.append("line").attr("x1", c - 3).attr("y1", l + 1).attr("x2", c).attr("y2", l - 5).attr(
+                "stroke",
+                "#fff",
+              ).attr("class", `commit ${o.id} ${t}`);
+          } else {
+            const n = r.append("circle");
+            if (
+              n.attr("cx", c),
+                n.attr("cy", l),
+                n.attr("r", o.type === Jv ? 9 : 10),
+                n.attr("class", `commit ${o.id} commit${ek[o.branch].index % 8}`),
+                e === Jv
+            ) {
+              const e = r.append("circle");
+              e.attr("cx", c),
+                e.attr("cy", l),
+                e.attr("r", 6),
+                e.attr("class", `commit ${t} ${o.id} commit${ek[o.branch].index % 8}`);
+            }
+            if (e === Qv) {
+              r.append("path").attr("d", `M ${c - 5},${l - 5}L${c + 5},${l + 5}M${c - 5},${l + 5}L${c + 5},${l - 5}`)
+                .attr("class", `commit ${t} ${o.id} commit${ek[o.branch].index % 8}`);
+            }
+          }
+        }
+        if (nk[o.id] = { x: s + 10, y: l }, n) {
+          const t = 4, e = 2;
+          if (o.type !== tk && (o.customId && o.type === Jv || o.type !== Jv) && i.showCommitLabel) {
+            const t = a.append("g"),
+              n = t.insert("rect").attr("class", "commit-label-bkg"),
+              r = t.append("text").attr("x", s).attr("y", l + 25).attr("class", "commit-label").text(o.id);
+            let c = r.node().getBBox();
+            if (
+              n.attr("x", s + 10 - c.width / 2 - e).attr("y", l + 13.5).attr("width", c.width + 2 * e).attr(
+                "height",
+                c.height + 2 * e,
+              ),
+                r.attr("x", s + 10 - c.width / 2),
+                i.rotateCommitLabel
+            ) {
+              let e = -7.5 - (c.width + 10) / 25 * 9.5, n = 10 + c.width / 25 * 8.5;
+              t.attr("transform", "translate(" + e + ", " + n + ") rotate(" + "-45, " + s + ", " + l + ")");
+            }
+          }
+          if (o.tag) {
+            const n = a.insert("polygon"),
+              i = a.append("circle"),
+              r = a.append("text").attr("y", l - 16).attr("class", "tag-label").text(o.tag);
+            let c = r.node().getBBox();
+            r.attr("x", s + 10 - c.width / 2);
+            const h = c.height / 2, u = l - 19.2;
+            n.attr("class", "tag-label-bkg").attr(
+              "points",
+              `\n          ${s - c.width / 2 - t / 2},${u + e}\n          ${s - c.width / 2 - t / 2},${
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+              }\n          ${s + 10 - c.width / 2 - t},${u - h - e}\n          ${s + 10 + c.width / 2 + t},${
+                u - h - e
+              }\n          ${s + 10 + c.width / 2 + t},${u + h + e}\n          ${s + 10 - c.width / 2 - t},${
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+            ), i.attr("cx", s - c.width / 2 + t / 2).attr("cy", u).attr("r", 1.5).attr("class", "tag-hole");
+          }
+        }
+        s += 50, s > rk && (rk = s);
+      });
+    },
+    sk = (t, e, n = 0) => {
+      const i = t + Math.abs(t - e) / 2;
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+      if (ik.every(t => Math.abs(t - i) >= 10)) return ik.push(i), i;
+      const r = Math.abs(t - e);
+      return sk(t, e - r / 5, n + 1);
+    },
+    ok = (t, e, n, i) => {
+      const r = nk[e.id],
+        a = nk[n.id],
+        s = ((t, e, n) =>
+          Object.keys(n).filter(i =>
+            n[i].branch === e.branch && n[i].seq > t.seq && n[i].seq < e.seq
+          ).length > 0)(
+            e,
+            n,
+            i,
+          );
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+      if (s) {
+        l = "A 10 10, 0, 0, 0,", c = "A 10 10, 0, 0, 1,", h = 10, u = 10, d = ek[n.branch].index;
+        const t = r.y < a.y ? sk(r.y, a.y) : sk(a.y, r.y);
+        o = r.y < a.y
+          ? `M ${r.x} ${r.y} L ${r.x} ${t - h} ${l} ${r.x + u} ${t} L ${a.x - h} ${t} ${c} ${a.x} ${
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+          } L ${a.x} ${a.y}`
+          : `M ${r.x} ${r.y} L ${r.x} ${t + h} ${c} ${r.x + u} ${t} L ${a.x - h} ${t} ${l} ${a.x} ${
+            t - u
+          } L ${a.x} ${a.y}`;
+      } else {r.y < a.y
+          && (l = "A 20 20, 0, 0, 0,",
+            h = 20,
+            u = 20,
+            d = ek[n.branch].index,
+            o = `M ${r.x} ${r.y} L ${r.x} ${a.y - h} ${l} ${r.x + u} ${a.y} L ${a.x} ${a.y}`),
+          r.y > a.y
+          && (l = "A 20 20, 0, 0, 0,",
+            h = 20,
+            u = 20,
+            d = ek[e.branch].index,
+            o = `M ${r.x} ${r.y} L ${a.x - h} ${r.y} ${l} ${a.x} ${r.y - u} L ${a.x} ${a.y}`),
+          r.y === a.y
+          && (d = ek[e.branch].index,
+            o = `M ${r.x} ${r.y} L ${r.x} ${a.y - h} ${l} ${r.x + u} ${a.y} L ${a.x} ${a.y}`);}
+      t.append("path").attr("d", o).attr("class", "arrow arrow" + d % 8);
+    },
+    lk = (t, e) => {
+      const n = dv().gitGraph, i = t.append("g");
+      e.forEach((t, e) => {
+        const r = e % 8, a = ek[t.name].pos, s = i.append("line");
+        s.attr("x1", 0),
+          s.attr("y1", a),
+          s.attr("x2", rk),
+          s.attr("y2", a),
+          s.attr("class", "branch branch" + r),
+          ik.push(a);
+        const o = (t => {
+            const e = document.createElementNS("http://www.w3.org/2000/svg", "text");
+            let n = [];
+            n = "string" == typeof t ? t.split(/\\n|\n|<br\s*\/?>/gi) : Array.isArray(t) ? t : [];
+            for (const t of n) {
+              const n = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
+              n.setAttributeNS("http://www.w3.org/XML/1998/namespace", "xml:space", "preserve"),
+                n.setAttribute("dy", "1em"),
+                n.setAttribute("x", "0"),
+                n.setAttribute("class", "row"),
+                n.textContent = t.trim(),
+                e.appendChild(n);
+            }
+            return e;
+          })(t.name),
+          l = i.insert("rect"),
+          c = i.insert("g").attr("class", "branchLabel").insert("g").attr("class", "label branch-label" + r);
+        c.node().appendChild(o);
+        let h = o.getBBox();
+        l.attr("class", "branchLabelBkg label" + r).attr("rx", 4).attr("ry", 4).attr(
+          "x",
+          -h.width - 4 - (!0 === n.rotateCommitLabel ? 30 : 0),
+        ).attr("y", -h.height / 2 + 8).attr("width", h.width + 18).attr("height", h.height + 4),
+          c.attr(
+            "transform",
+            "translate(" + (-h.width - 14 - (!0 === n.rotateCommitLabel ? 30 : 0)) + ", " + (a - h.height / 2 - 1)
+              + ")",
+          ),
+          l.attr("transform", "translate(-19, " + (a - h.height / 2) + ")");
+      });
+    },
+    ck = {
+      draw: function(t, e, n, i) {
+        var r;
+        ek = {}, nk = {}, Xv = {}, rk = 0, ik = [];
+        const a = dv(), s = a.gitGraph;
+        tb.debug("in gitgraph renderer", t + "\n", "id:", e, n), Xv = i.db.getCommits();
+        const o = i.db.getBranchesAsObjArray();
+        let l = 0;
+        o.forEach((t, e) => {
+          ek[t.name] = { pos: l, index: e }, l += 50 + (s.rotateCommitLabel ? 40 : 0);
+        });
+        const c = ie(`[id="${e}"]`);
+        ak(c, Xv, !1),
+          s.showBranches && lk(c, o),
+          ((t, e) => {
+            const n = t.append("g").attr("class", "commit-arrows");
+            Object.keys(e).forEach(t => {
+              const i = e[t];
+              i.parents && i.parents.length > 0 && i.parents.forEach(t => {
+                ok(n, e[t], i, e);
+              });
+            });
+          })(c, Xv),
+          ak(c, Xv, !0),
+          Dx.insertTitle(c, "gitTitleText", s.titleTopMargin, i.db.getDiagramTitle()),
+          fv(void 0, c, s.diagramPadding, null != (r = s.useMaxWidth) ? r : a.useMaxWidth);
+      },
+    },
+    hk = t =>
+      `\n  .commit-id,\n  .commit-msg,\n  .branch-label {\n    fill: lightgrey;\n    color: lightgrey;\n    font-family: 'trebuchet ms', verdana, arial, sans-serif;\n    font-family: var(--mermaid-font-family);\n  }\n  ${
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+          `\n        .branch-label${e} { fill: ${t["gitBranchLabel" + e]}; }\n        .commit${e} { stroke: ${
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+          }; fill: ${t["git" + e]}; }\n        .commit-highlight${e} { stroke: ${t["gitInv" + e]}; fill: ${
+            t["gitInv" + e]
+          }; }\n        .label${e}  { fill: ${t["git" + e]}; }\n        .arrow${e} { stroke: ${
+            t["git" + e]
+          }; }\n        `
+        ).join("\n")
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+  var uk = function() {
+    var t,
+      e = function(t, e, n, i) {
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+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 1],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [53, 2],
+          [45, 1],
+          [45, 2],
+          [85, 1],
+          [85, 2],
+          [85, 1],
+          [85, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 4:
+              i.setDirection("TB");
+              break;
+            case 5:
+              i.setDirection("BT");
+              break;
+            case 6:
+              i.setDirection("RL");
+              break;
+            case 7:
+              i.setDirection("LR");
+              break;
+            case 11:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 12:
+              break;
+            case 13:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 14:
+              i.parseDirective("}%%", "close_directive", "c4Context");
+              break;
+            case 15:
+            case 16:
+            case 17:
+            case 18:
+            case 19:
+              i.setC4Type(a[o - 3]);
+              break;
+            case 26:
+              i.setTitle(a[o].substring(6)), this.$ = a[o].substring(6);
+              break;
+            case 27:
+              i.setAccDescription(a[o].substring(15)), this.$ = a[o].substring(15);
+              break;
+            case 28:
+              this.$ = a[o].trim(), i.setTitle(this.$);
+              break;
+            case 29:
+            case 30:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 35:
+            case 36:
+              a[o].splice(2, 0, "ENTERPRISE"), i.addPersonOrSystemBoundary(...a[o]), this.$ = a[o];
+              break;
+            case 37:
+              i.addPersonOrSystemBoundary(...a[o]), this.$ = a[o];
+              break;
+            case 38:
+              a[o].splice(2, 0, "CONTAINER"), i.addContainerBoundary(...a[o]), this.$ = a[o];
+              break;
+            case 39:
+              i.addDeploymentNode("node", ...a[o]), this.$ = a[o];
+              break;
+            case 40:
+              i.addDeploymentNode("nodeL", ...a[o]), this.$ = a[o];
+              break;
+            case 41:
+              i.addDeploymentNode("nodeR", ...a[o]), this.$ = a[o];
+              break;
+            case 42:
+              i.popBoundaryParseStack();
+              break;
+            case 46:
+              i.addPersonOrSystem("person", ...a[o]), this.$ = a[o];
+              break;
+            case 47:
+              i.addPersonOrSystem("external_person", ...a[o]), this.$ = a[o];
+              break;
+            case 48:
+              i.addPersonOrSystem("system", ...a[o]), this.$ = a[o];
+              break;
+            case 49:
+              i.addPersonOrSystem("system_db", ...a[o]), this.$ = a[o];
+              break;
+            case 50:
+              i.addPersonOrSystem("system_queue", ...a[o]), this.$ = a[o];
+              break;
+            case 51:
+              i.addPersonOrSystem("external_system", ...a[o]), this.$ = a[o];
+              break;
+            case 52:
+              i.addPersonOrSystem("external_system_db", ...a[o]), this.$ = a[o];
+              break;
+            case 53:
+              i.addPersonOrSystem("external_system_queue", ...a[o]), this.$ = a[o];
+              break;
+            case 54:
+              i.addContainer("container", ...a[o]), this.$ = a[o];
+              break;
+            case 55:
+              i.addContainer("container_db", ...a[o]), this.$ = a[o];
+              break;
+            case 56:
+              i.addContainer("container_queue", ...a[o]), this.$ = a[o];
+              break;
+            case 57:
+              i.addContainer("external_container", ...a[o]), this.$ = a[o];
+              break;
+            case 58:
+              i.addContainer("external_container_db", ...a[o]), this.$ = a[o];
+              break;
+            case 59:
+              i.addContainer("external_container_queue", ...a[o]), this.$ = a[o];
+              break;
+            case 60:
+              i.addComponent("component", ...a[o]), this.$ = a[o];
+              break;
+            case 61:
+              i.addComponent("component_db", ...a[o]), this.$ = a[o];
+              break;
+            case 62:
+              i.addComponent("component_queue", ...a[o]), this.$ = a[o];
+              break;
+            case 63:
+              i.addComponent("external_component", ...a[o]), this.$ = a[o];
+              break;
+            case 64:
+              i.addComponent("external_component_db", ...a[o]), this.$ = a[o];
+              break;
+            case 65:
+              i.addComponent("external_component_queue", ...a[o]), this.$ = a[o];
+              break;
+            case 67:
+              i.addRel("rel", ...a[o]), this.$ = a[o];
+              break;
+            case 68:
+              i.addRel("birel", ...a[o]), this.$ = a[o];
+              break;
+            case 69:
+              i.addRel("rel_u", ...a[o]), this.$ = a[o];
+              break;
+            case 70:
+              i.addRel("rel_d", ...a[o]), this.$ = a[o];
+              break;
+            case 71:
+              i.addRel("rel_l", ...a[o]), this.$ = a[o];
+              break;
+            case 72:
+              i.addRel("rel_r", ...a[o]), this.$ = a[o];
+              break;
+            case 73:
+              i.addRel("rel_b", ...a[o]), this.$ = a[o];
+              break;
+            case 74:
+              a[o].splice(0, 1), i.addRel("rel", ...a[o]), this.$ = a[o];
+              break;
+            case 75:
+              i.updateElStyle("update_el_style", ...a[o]), this.$ = a[o];
+              break;
+            case 76:
+              i.updateRelStyle("update_rel_style", ...a[o]), this.$ = a[o];
+              break;
+            case 77:
+              i.updateLayoutConfig("update_layout_config", ...a[o]), this.$ = a[o];
+              break;
+            case 78:
+              this.$ = [a[o]];
+              break;
+            case 79:
+              a[o].unshift(a[o - 1]), this.$ = a[o];
+              break;
+            case 80:
+            case 82:
+              this.$ = a[o].trim();
+              break;
+            case 81:
+              let t = {};
+              t[a[o - 1].trim()] = a[o].trim(), this.$ = t;
+              break;
+            case 83:
+              this.$ = "";
+          }
+        },
+        table: [
+          { 3: 1, 4: 2, 5: 3, 6: 4, 7: n, 8: i, 9: r, 10: a, 11: 5, 12: 10, 18: s, 22: o, 25: l, 26: h, 27: u, 28: d },
+          { 1: [3] },
+          { 1: [2, 1] },
+          { 1: [2, 2] },
+          { 3: 17, 4: 2, 5: 3, 6: 4, 7: n, 8: i, 9: r, 10: a, 11: 5, 12: 10, 18: s, 22: o, 25: l, 26: h, 27: u, 28: d },
+          { 1: [2, 8] },
+          { 1: [2, 4] },
+          { 1: [2, 5] },
+          { 1: [2, 6] },
+          { 1: [2, 7] },
+          { 13: 18, 19: [1, 19] },
+          { 15: [1, 20] },
+          { 15: [1, 21] },
+          { 15: [1, 22] },
+          { 15: [1, 23] },
+          { 15: [1, 24] },
+          { 19: [2, 11] },
+          { 1: [2, 3] },
+          { 14: 25, 16: [1, 26], 21: p },
+          e([16, 21], [2, 12]),
+          {
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+          },
+          {
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+          },
+          {
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+          },
+          {
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+          },
+          { 15: [1, 83] },
+          { 17: 84, 20: [1, 85] },
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+          { 24: [1, 86] },
+          e(it, [2, 20], {
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+          }),
+          e(it, [2, 21]),
+          e(rt, [2, 23], { 15: [1, 88] }),
+          e(it, [2, 43], { 15: [1, 89] }),
+          e(at, [2, 26]),
+          e(at, [2, 27]),
+          { 35: [1, 90] },
+          { 37: [1, 91] },
+          e(at, [2, 30]),
+          { 45: 92, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 98, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 99, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 100, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 101, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 102, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 103, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 104, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 105, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 106, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 107, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 108, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 109, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 110, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 111, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 112, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 113, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 114, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 115, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 116, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          e(ht, [2, 66]),
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+          { 45: 118, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 119, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 120, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 121, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 122, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 123, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 124, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 125, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 126, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 127, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          {
+            30: 128,
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+            81: J,
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+            83: et,
+            84: nt,
+          },
+          { 15: [1, 130], 43: [1, 129] },
+          { 45: 131, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 132, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 133, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 134, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 135, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 136, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 45: 137, 85: 93, 86: st, 87: ot, 89: lt, 90: ct },
+          { 24: [1, 138] },
+          { 24: [1, 139] },
+          { 24: [1, 140] },
+          { 24: [1, 141] },
+          e(ut, [2, 9]),
+          { 14: 142, 21: p },
+          { 21: [2, 13] },
+          { 1: [2, 15] },
+          e(it, [2, 22]),
+          e(rt, [2, 24], { 31: 31, 29: 143, 32: f, 33: g, 34: y, 36: m, 38: b }),
+          e(it, [2, 44], {
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+          }),
+          e(at, [2, 28]),
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+          e(ht, [2, 55]),
+          e(ht, [2, 56]),
+          e(ht, [2, 57]),
+          e(ht, [2, 58]),
+          e(ht, [2, 59]),
+          e(ht, [2, 60]),
+          e(ht, [2, 61]),
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+          e(ht, [2, 64]),
+          e(ht, [2, 65]),
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+          e(ht, [2, 75]),
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+          { 15: [1, 149] },
+          { 43: [1, 150] },
+          e(ft, [2, 35]),
+          e(ft, [2, 36]),
+          e(ft, [2, 37]),
+          e(ft, [2, 38]),
+          e(ft, [2, 39]),
+          e(ft, [2, 40]),
+          e(ft, [2, 41]),
+          { 1: [2, 16] },
+          { 1: [2, 17] },
+          { 1: [2, 18] },
+          { 1: [2, 19] },
+          { 15: [1, 151] },
+          e(rt, [2, 25]),
+          e(it, [2, 45]),
+          e(dt, [2, 79]),
+          e(pt, [2, 81]),
+          e(ht, [2, 31]),
+          e(ht, [2, 42]),
+          e(gt, [2, 32]),
+          e(gt, [2, 33], { 15: [1, 152] }),
+          e(ut, [2, 10]),
+          e(gt, [2, 34]),
+        ],
+        defaultActions: {
+          2: [2, 1],
+          3: [2, 2],
+          5: [2, 8],
+          6: [2, 4],
+          7: [2, 5],
+          8: [2, 6],
+          9: [2, 7],
+          16: [2, 11],
+          17: [2, 3],
+          27: [2, 14],
+          85: [2, 13],
+          86: [2, 15],
+          138: [2, 16],
+          139: [2, 17],
+          140: [2, 18],
+          141: [2, 19],
+        },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      mt = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: {},
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("open_directive"), 18;
+            case 1:
+              return 7;
+            case 2:
+              return 8;
+            case 3:
+              return 9;
+            case 4:
+              return 10;
+            case 5:
+              return this.begin("type_directive"), 19;
+            case 6:
+              return this.popState(), this.begin("arg_directive"), 16;
+            case 7:
+              return this.popState(), this.popState(), 21;
+            case 8:
+              return 20;
+            case 9:
+              return 32;
+            case 10:
+              return 33;
+            case 11:
+              return this.begin("acc_title"), 34;
+            case 12:
+              return this.popState(), "acc_title_value";
+            case 13:
+              return this.begin("acc_descr"), 36;
+            case 14:
+              return this.popState(), "acc_descr_value";
+            case 15:
+              this.begin("acc_descr_multiline");
+              break;
+            case 16:
+            case 78:
+              this.popState();
+              break;
+            case 17:
+              return "acc_descr_multiline_value";
+            case 18:
+            case 21:
+            case 75:
+              break;
+            case 19:
+              c;
+              break;
+            case 20:
+              return 15;
+            case 22:
+              return 22;
+            case 23:
+              return 25;
+            case 24:
+              return 26;
+            case 25:
+              return 27;
+            case 26:
+              return 28;
+            case 27:
+              return this.begin("person_ext"), 55;
+            case 28:
+              return this.begin("person"), 54;
+            case 29:
+              return this.begin("system_ext_queue"), 61;
+            case 30:
+              return this.begin("system_ext_db"), 60;
+            case 31:
+              return this.begin("system_ext"), 59;
+            case 32:
+              return this.begin("system_queue"), 58;
+            case 33:
+              return this.begin("system_db"), 57;
+            case 34:
+              return this.begin("system"), 56;
+            case 35:
+              return this.begin("boundary"), 47;
+            case 36:
+              return this.begin("enterprise_boundary"), 44;
+            case 37:
+              return this.begin("system_boundary"), 46;
+            case 38:
+              return this.begin("container_ext_queue"), 67;
+            case 39:
+              return this.begin("container_ext_db"), 66;
+            case 40:
+              return this.begin("container_ext"), 65;
+            case 41:
+              return this.begin("container_queue"), 64;
+            case 42:
+              return this.begin("container_db"), 63;
+            case 43:
+              return this.begin("container"), 62;
+            case 44:
+              return this.begin("container_boundary"), 48;
+            case 45:
+              return this.begin("component_ext_queue"), 73;
+            case 46:
+              return this.begin("component_ext_db"), 72;
+            case 47:
+              return this.begin("component_ext"), 71;
+            case 48:
+              return this.begin("component_queue"), 70;
+            case 49:
+              return this.begin("component_db"), 69;
+            case 50:
+              return this.begin("component"), 68;
+            case 51:
+            case 52:
+              return this.begin("node"), 49;
+            case 53:
+              return this.begin("node_l"), 50;
+            case 54:
+              return this.begin("node_r"), 51;
+            case 55:
+              return this.begin("rel"), 74;
+            case 56:
+              return this.begin("birel"), 75;
+            case 57:
+            case 58:
+              return this.begin("rel_u"), 76;
+            case 59:
+            case 60:
+              return this.begin("rel_d"), 77;
+            case 61:
+            case 62:
+              return this.begin("rel_l"), 78;
+            case 63:
+            case 64:
+              return this.begin("rel_r"), 79;
+            case 65:
+              return this.begin("rel_b"), 80;
+            case 66:
+              return this.begin("rel_index"), 81;
+            case 67:
+              return this.begin("update_el_style"), 82;
+            case 68:
+              return this.begin("update_rel_style"), 83;
+            case 69:
+              return this.begin("update_layout_config"), 84;
+            case 70:
+              return "EOF_IN_STRUCT";
+            case 71:
+              return this.begin("attribute"), "ATTRIBUTE_EMPTY";
+            case 72:
+              this.begin("attribute");
+              break;
+            case 73:
+            case 84:
+              this.popState(), this.popState();
+              break;
+            case 74:
+            case 76:
+              return 90;
+            case 77:
+              this.begin("string");
+              break;
+            case 79:
+            case 85:
+              return "STR";
+            case 80:
+              this.begin("string_kv");
+              break;
+            case 81:
+              return this.begin("string_kv_key"), "STR_KEY";
+            case 82:
+              this.popState(), this.begin("string_kv_value");
+              break;
+            case 83:
+              return "STR_VALUE";
+            case 86:
+              return "LBRACE";
+            case 87:
+              return "RBRACE";
+            case 88:
+              return "SPACE";
+            case 89:
+              return "EOL";
+            case 90:
+              return 24;
+          }
+        },
+        rules: [
+          /^(?:%%\{)/,
+          /^(?:.*direction\s+TB[^\n]*)/,
+          /^(?:.*direction\s+BT[^\n]*)/,
+          /^(?:.*direction\s+RL[^\n]*)/,
+          /^(?:.*direction\s+LR[^\n]*)/,
+          /^(?:((?:(?!\}%%)[^:.])*))/,
+          /^(?::)/,
+          /^(?:\}%%)/,
+          /^(?:((?:(?!\}%%).|\n)*))/,
+          /^(?:title\s[^#\n;]+)/,
+          /^(?:accDescription\s[^#\n;]+)/,
+          /^(?:accTitle\s*:\s*)/,
+          /^(?:(?!\n||)*[^\n]*)/,
+          /^(?:accDescr\s*:\s*)/,
+          /^(?:(?!\n||)*[^\n]*)/,
+          /^(?:accDescr\s*\{\s*)/,
+          /^(?:[\}])/,
+          /^(?:[^\}]*)/,
+          /^(?:%%(?!\{)*[^\n]*(\r?\n?)+)/,
+          /^(?:%%[^\n]*(\r?\n)*)/,
+          /^(?:\s*(\r?\n)+)/,
+          /^(?:\s+)/,
+          /^(?:C4Context\b)/,
+          /^(?:C4Container\b)/,
+          /^(?:C4Component\b)/,
+          /^(?:C4Dynamic\b)/,
+          /^(?:C4Deployment\b)/,
+          /^(?:Person_Ext\b)/,
+          /^(?:Person\b)/,
+          /^(?:SystemQueue_Ext\b)/,
+          /^(?:SystemDb_Ext\b)/,
+          /^(?:System_Ext\b)/,
+          /^(?:SystemQueue\b)/,
+          /^(?:SystemDb\b)/,
+          /^(?:System\b)/,
+          /^(?:Boundary\b)/,
+          /^(?:Enterprise_Boundary\b)/,
+          /^(?:System_Boundary\b)/,
+          /^(?:ContainerQueue_Ext\b)/,
+          /^(?:ContainerDb_Ext\b)/,
+          /^(?:Container_Ext\b)/,
+          /^(?:ContainerQueue\b)/,
+          /^(?:ContainerDb\b)/,
+          /^(?:Container\b)/,
+          /^(?:Container_Boundary\b)/,
+          /^(?:ComponentQueue_Ext\b)/,
+          /^(?:ComponentDb_Ext\b)/,
+          /^(?:Component_Ext\b)/,
+          /^(?:ComponentQueue\b)/,
+          /^(?:ComponentDb\b)/,
+          /^(?:Component\b)/,
+          /^(?:Deployment_Node\b)/,
+          /^(?:Node\b)/,
+          /^(?:Node_L\b)/,
+          /^(?:Node_R\b)/,
+          /^(?:Rel\b)/,
+          /^(?:BiRel\b)/,
+          /^(?:Rel_Up\b)/,
+          /^(?:Rel_U\b)/,
+          /^(?:Rel_Down\b)/,
+          /^(?:Rel_D\b)/,
+          /^(?:Rel_Left\b)/,
+          /^(?:Rel_L\b)/,
+          /^(?:Rel_Right\b)/,
+          /^(?:Rel_R\b)/,
+          /^(?:Rel_Back\b)/,
+          /^(?:RelIndex\b)/,
+          /^(?:UpdateElementStyle\b)/,
+          /^(?:UpdateRelStyle\b)/,
+          /^(?:UpdateLayoutConfig\b)/,
+          /^(?:$)/,
+          /^(?:[(][ ]*[,])/,
+          /^(?:[(])/,
+          /^(?:[)])/,
+          /^(?:,,)/,
+          /^(?:,)/,
+          /^(?:[ ]*["]["])/,
+          /^(?:[ ]*["])/,
+          /^(?:["])/,
+          /^(?:[^"]*)/,
+          /^(?:[ ]*[\$])/,
+          /^(?:[^=]*)/,
+          /^(?:[=][ ]*["])/,
+          /^(?:[^"]+)/,
+          /^(?:["])/,
+          /^(?:[^,]+)/,
+          /^(?:\{)/,
+          /^(?:\})/,
+          /^(?:[\s]+)/,
+          /^(?:[\n\r]+)/,
+          /^(?:$)/,
+        ],
+        conditions: {
+          acc_descr_multiline: { rules: [16, 17], inclusive: !1 },
+          acc_descr: { rules: [14], inclusive: !1 },
+          acc_title: { rules: [12], inclusive: !1 },
+          close_directive: { rules: [], inclusive: !1 },
+          arg_directive: { rules: [7, 8], inclusive: !1 },
+          type_directive: { rules: [6, 7], inclusive: !1 },
+          open_directive: { rules: [5], inclusive: !1 },
+          string_kv_value: { rules: [83, 84], inclusive: !1 },
+          string_kv_key: { rules: [82], inclusive: !1 },
+          string_kv: { rules: [81], inclusive: !1 },
+          string: { rules: [78, 79], inclusive: !1 },
+          attribute: { rules: [73, 74, 75, 76, 77, 80, 85], inclusive: !1 },
+          update_layout_config: { rules: [70, 71, 72, 73], inclusive: !1 },
+          update_rel_style: { rules: [70, 71, 72, 73], inclusive: !1 },
+          update_el_style: { rules: [70, 71, 72, 73], inclusive: !1 },
+          rel_b: { rules: [70, 71, 72, 73], inclusive: !1 },
+          rel_r: { rules: [70, 71, 72, 73], inclusive: !1 },
+          rel_l: { rules: [70, 71, 72, 73], inclusive: !1 },
+          rel_d: { rules: [70, 71, 72, 73], inclusive: !1 },
+          rel_u: { rules: [70, 71, 72, 73], inclusive: !1 },
+          rel_bi: { rules: [], inclusive: !1 },
+          rel: { rules: [70, 71, 72, 73], inclusive: !1 },
+          node_r: { rules: [70, 71, 72, 73], inclusive: !1 },
+          node_l: { rules: [70, 71, 72, 73], inclusive: !1 },
+          node: { rules: [70, 71, 72, 73], inclusive: !1 },
+          index: { rules: [], inclusive: !1 },
+          rel_index: { rules: [70, 71, 72, 73], inclusive: !1 },
+          component_ext_queue: { rules: [], inclusive: !1 },
+          component_ext_db: { rules: [70, 71, 72, 73], inclusive: !1 },
+          component_ext: { rules: [70, 71, 72, 73], inclusive: !1 },
+          component_queue: { rules: [70, 71, 72, 73], inclusive: !1 },
+          component_db: { rules: [70, 71, 72, 73], inclusive: !1 },
+          component: { rules: [70, 71, 72, 73], inclusive: !1 },
+          container_boundary: { rules: [70, 71, 72, 73], inclusive: !1 },
+          container_ext_queue: { rules: [], inclusive: !1 },
+          container_ext_db: { rules: [70, 71, 72, 73], inclusive: !1 },
+          container_ext: { rules: [70, 71, 72, 73], inclusive: !1 },
+          container_queue: { rules: [70, 71, 72, 73], inclusive: !1 },
+          container_db: { rules: [70, 71, 72, 73], inclusive: !1 },
+          container: { rules: [70, 71, 72, 73], inclusive: !1 },
+          birel: { rules: [70, 71, 72, 73], inclusive: !1 },
+          system_boundary: { rules: [70, 71, 72, 73], inclusive: !1 },
+          enterprise_boundary: { rules: [70, 71, 72, 73], inclusive: !1 },
+          boundary: { rules: [70, 71, 72, 73], inclusive: !1 },
+          system_ext_queue: { rules: [70, 71, 72, 73], inclusive: !1 },
+          system_ext_db: { rules: [70, 71, 72, 73], inclusive: !1 },
+          system_ext: { rules: [70, 71, 72, 73], inclusive: !1 },
+          system_queue: { rules: [70, 71, 72, 73], inclusive: !1 },
+          system_db: { rules: [70, 71, 72, 73], inclusive: !1 },
+          system: { rules: [70, 71, 72, 73], inclusive: !1 },
+          person_ext: { rules: [70, 71, 72, 73], inclusive: !1 },
+          person: { rules: [70, 71, 72, 73], inclusive: !1 },
+          INITIAL: {
+            rules: [
+              0,
+              1,
+              2,
+              3,
+              4,
+              9,
+              10,
+              11,
+              13,
+              15,
+              18,
+              19,
+              20,
+              21,
+              22,
+              23,
+              24,
+              25,
+              26,
+              27,
+              28,
+              29,
+              30,
+              31,
+              32,
+              33,
+              34,
+              35,
+              36,
+              37,
+              38,
+              39,
+              40,
+              41,
+              42,
+              43,
+              44,
+              45,
+              46,
+              47,
+              48,
+              49,
+              50,
+              51,
+              52,
+              53,
+              54,
+              55,
+              56,
+              57,
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+              60,
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+              66,
+              67,
+              68,
+              69,
+              86,
+              87,
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+            inclusive: !0,
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+        t);
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+      this.yy = {};
+    }
+    return yt.lexer = mt, bt.prototype = yt, yt.Parser = bt, new bt();
+  }();
+  uk.parser = uk;
+  const dk = uk, pk = t => null !== t.match(/^\s*C4Context|C4Container|C4Component|C4Dynamic|C4Deployment/);
+  let fk = [],
+    gk = [""],
+    yk = "global",
+    mk = "",
+    bk = [{
+      alias: "global",
+      label: { text: "global" },
+      type: { text: "global" },
+      tags: null,
+      link: null,
+      parentBoundary: "",
+    }],
+    _k = [],
+    xk = "",
+    vk = !1,
+    kk = 4,
+    wk = 2;
+  var Tk;
+  const Ck = function(t) {
+      return null == t ? fk : fk.filter(e => e.parentBoundary === t);
+    },
+    Ek = function() {
+      return vk;
+    },
+    Sk = {
+      addPersonOrSystem: function(t, e, n, i, r, a, s) {
+        if (null === e || null === n) return;
+        let o = {};
+        const l = fk.find(t => t.alias === e);
+        if (
+          l && e === l.alias ? o = l : (o.alias = e, fk.push(o)),
+            o.label = null == n ? { text: "" } : { text: n },
+            null == i
+        ) o.descr = { text: "" };
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+          let [t, e] = Object.entries(i)[0];
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+        if ("object" == typeof r) {
+          let [t, e] = Object.entries(r)[0];
+          o[t] = e;
+        } else o.sprite = r;
+        if ("object" == typeof a) {
+          let [t, e] = Object.entries(a)[0];
+          o[t] = e;
+        } else o.tags = a;
+        if ("object" == typeof s) {
+          let [t, e] = Object.entries(s)[0];
+          o[t] = e;
+        } else o.link = s;
+        o.typeC4Shape = { text: t }, o.parentBoundary = yk, o.wrap = Ek();
+      },
+      addPersonOrSystemBoundary: function(t, e, n, i, r) {
+        if (null === t || null === e) return;
+        let a = {};
+        const s = bk.find(e => e.alias === t);
+        if (
+          s && t === s.alias ? a = s : (a.alias = t, bk.push(a)),
+            a.label = null == e ? { text: "" } : { text: e },
+            null == n
+        ) a.type = { text: "system" };
+        else if ("object" == typeof n) {
+          let [t, e] = Object.entries(n)[0];
+          a[t] = { text: e };
+        } else a.type = { text: n };
+        if ("object" == typeof i) {
+          let [t, e] = Object.entries(i)[0];
+          a[t] = e;
+        } else a.tags = i;
+        if ("object" == typeof r) {
+          let [t, e] = Object.entries(r)[0];
+          a[t] = e;
+        } else a.link = r;
+        a.parentBoundary = yk, a.wrap = Ek(), mk = yk, yk = t, gk.push(mk);
+      },
+      addContainer: function(t, e, n, i, r, a, s, o) {
+        if (null === e || null === n) return;
+        let l = {};
+        const c = fk.find(t => t.alias === e);
+        if (
+          c && e === c.alias ? l = c : (l.alias = e, fk.push(l)),
+            l.label = null == n ? { text: "" } : { text: n },
+            null == i
+        ) l.techn = { text: "" };
+        else if ("object" == typeof i) {
+          let [t, e] = Object.entries(i)[0];
+          l[t] = { text: e };
+        } else l.techn = { text: i };
+        if (null == r) l.descr = { text: "" };
+        else if ("object" == typeof r) {
+          let [t, e] = Object.entries(r)[0];
+          l[t] = { text: e };
+        } else l.descr = { text: r };
+        if ("object" == typeof a) {
+          let [t, e] = Object.entries(a)[0];
+          l[t] = e;
+        } else l.sprite = a;
+        if ("object" == typeof s) {
+          let [t, e] = Object.entries(s)[0];
+          l[t] = e;
+        } else l.tags = s;
+        if ("object" == typeof o) {
+          let [t, e] = Object.entries(o)[0];
+          l[t] = e;
+        } else l.link = o;
+        l.wrap = Ek(), l.typeC4Shape = { text: t }, l.parentBoundary = yk;
+      },
+      addContainerBoundary: function(t, e, n, i, r) {
+        if (null === t || null === e) return;
+        let a = {};
+        const s = bk.find(e => e.alias === t);
+        if (
+          s && t === s.alias ? a = s : (a.alias = t, bk.push(a)),
+            a.label = null == e ? { text: "" } : { text: e },
+            null == n
+        ) a.type = { text: "container" };
+        else if ("object" == typeof n) {
+          let [t, e] = Object.entries(n)[0];
+          a[t] = { text: e };
+        } else a.type = { text: n };
+        if ("object" == typeof i) {
+          let [t, e] = Object.entries(i)[0];
+          a[t] = e;
+        } else a.tags = i;
+        if ("object" == typeof r) {
+          let [t, e] = Object.entries(r)[0];
+          a[t] = e;
+        } else a.link = r;
+        a.parentBoundary = yk, a.wrap = Ek(), mk = yk, yk = t, gk.push(mk);
+      },
+      addComponent: function(t, e, n, i, r, a, s, o) {
+        if (null === e || null === n) return;
+        let l = {};
+        const c = fk.find(t => t.alias === e);
+        if (
+          c && e === c.alias ? l = c : (l.alias = e, fk.push(l)),
+            l.label = null == n ? { text: "" } : { text: n },
+            null == i
+        ) l.techn = { text: "" };
+        else if ("object" == typeof i) {
+          let [t, e] = Object.entries(i)[0];
+          l[t] = { text: e };
+        } else l.techn = { text: i };
+        if (null == r) l.descr = { text: "" };
+        else if ("object" == typeof r) {
+          let [t, e] = Object.entries(r)[0];
+          l[t] = { text: e };
+        } else l.descr = { text: r };
+        if ("object" == typeof a) {
+          let [t, e] = Object.entries(a)[0];
+          l[t] = e;
+        } else l.sprite = a;
+        if ("object" == typeof s) {
+          let [t, e] = Object.entries(s)[0];
+          l[t] = e;
+        } else l.tags = s;
+        if ("object" == typeof o) {
+          let [t, e] = Object.entries(o)[0];
+          l[t] = e;
+        } else l.link = o;
+        l.wrap = Ek(), l.typeC4Shape = { text: t }, l.parentBoundary = yk;
+      },
+      addDeploymentNode: function(t, e, n, i, r, a, s, o) {
+        if (null === e || null === n) return;
+        let l = {};
+        const c = bk.find(t => t.alias === e);
+        if (
+          c && e === c.alias ? l = c : (l.alias = e, bk.push(l)),
+            l.label = null == n ? { text: "" } : { text: n },
+            null == i
+        ) l.type = { text: "node" };
+        else if ("object" == typeof i) {
+          let [t, e] = Object.entries(i)[0];
+          l[t] = { text: e };
+        } else l.type = { text: i };
+        if (null == r) l.descr = { text: "" };
+        else if ("object" == typeof r) {
+          let [t, e] = Object.entries(r)[0];
+          l[t] = { text: e };
+        } else l.descr = { text: r };
+        if ("object" == typeof s) {
+          let [t, e] = Object.entries(s)[0];
+          l[t] = e;
+        } else l.tags = s;
+        if ("object" == typeof o) {
+          let [t, e] = Object.entries(o)[0];
+          l[t] = e;
+        } else l.link = o;
+        l.nodeType = t, l.parentBoundary = yk, l.wrap = Ek(), mk = yk, yk = e, gk.push(mk);
+      },
+      popBoundaryParseStack: function() {
+        yk = mk, gk.pop(), mk = gk.pop(), gk.push(mk);
+      },
+      addRel: function(t, e, n, i, r, a, s, o, l) {
+        if (null == t || null == e || null == n || null == i) return;
+        let c = {};
+        const h = _k.find(t => t.from === e && t.to === n);
+        if (h ? c = h : _k.push(c), c.type = t, c.from = e, c.to = n, c.label = { text: i }, null == r) {
+          c.techn = { text: "" };
+        } else if ("object" == typeof r) {
+          let [t, e] = Object.entries(r)[0];
+          c[t] = { text: e };
+        } else c.techn = { text: r };
+        if (null == a) c.descr = { text: "" };
+        else if ("object" == typeof a) {
+          let [t, e] = Object.entries(a)[0];
+          c[t] = { text: e };
+        } else c.descr = { text: a };
+        if ("object" == typeof s) {
+          let [t, e] = Object.entries(s)[0];
+          c[t] = e;
+        } else c.sprite = s;
+        if ("object" == typeof o) {
+          let [t, e] = Object.entries(o)[0];
+          c[t] = e;
+        } else c.tags = o;
+        if ("object" == typeof l) {
+          let [t, e] = Object.entries(l)[0];
+          c[t] = e;
+        } else c.link = l;
+        c.wrap = Ek();
+      },
+      updateElStyle: function(t, e, n, i, r, a, s, o, l, c, h) {
+        let u = fk.find(t => t.alias === e);
+        if (void 0 !== u || (u = bk.find(t => t.alias === e), void 0 !== u)) {
+          if (null != n) {
+            if ("object" == typeof n) {
+              let [t, e] = Object.entries(n)[0];
+              u[t] = e;
+            } else u.bgColor = n;
+          }
+          if (null != i) {
+            if ("object" == typeof i) {
+              let [t, e] = Object.entries(i)[0];
+              u[t] = e;
+            } else u.fontColor = i;
+          }
+          if (null != r) {
+            if ("object" == typeof r) {
+              let [t, e] = Object.entries(r)[0];
+              u[t] = e;
+            } else u.borderColor = r;
+          }
+          if (null != a) {
+            if ("object" == typeof a) {
+              let [t, e] = Object.entries(a)[0];
+              u[t] = e;
+            } else u.shadowing = a;
+          }
+          if (null != s) {
+            if ("object" == typeof s) {
+              let [t, e] = Object.entries(s)[0];
+              u[t] = e;
+            } else u.shape = s;
+          }
+          if (null != o) {
+            if ("object" == typeof o) {
+              let [t, e] = Object.entries(o)[0];
+              u[t] = e;
+            } else u.sprite = o;
+          }
+          if (null != l) {
+            if ("object" == typeof l) {
+              let [t, e] = Object.entries(l)[0];
+              u[t] = e;
+            } else u.techn = l;
+          }
+          if (null != c) {
+            if ("object" == typeof c) {
+              let [t, e] = Object.entries(c)[0];
+              u[t] = e;
+            } else u.legendText = c;
+          }
+          if (null != h) {
+            if ("object" == typeof h) {
+              let [t, e] = Object.entries(h)[0];
+              u[t] = e;
+            } else u.legendSprite = h;
+          }
+        }
+      },
+      updateRelStyle: function(t, e, n, i, r, a, s) {
+        const o = _k.find(t => t.from === e && t.to === n);
+        if (void 0 !== o) {
+          if (null != i) {
+            if ("object" == typeof i) {
+              let [t, e] = Object.entries(i)[0];
+              o[t] = e;
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+          if (null != r) {
+            if ("object" == typeof r) {
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+              o[t] = e;
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+          if (null != a) {
+            if ("object" == typeof a) {
+              let [t, e] = Object.entries(a)[0];
+              o[t] = parseInt(e);
+            } else o.offsetX = parseInt(a);
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+          if (null != s) {
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+              let [t, e] = Object.entries(s)[0];
+              o[t] = parseInt(e);
+            } else o.offsetY = parseInt(s);
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+        }
+      },
+      updateLayoutConfig: function(t, e, n) {
+        let i = kk, r = wk;
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+          const t = Object.values(e)[0];
+          i = parseInt(t);
+        } else i = parseInt(e);
+        if ("object" == typeof n) {
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+          r = parseInt(t);
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+      autoWrap: Ek,
+      setWrap: function(t) {
+        vk = t;
+      },
+      getC4ShapeArray: Ck,
+      getC4Shape: function(t) {
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+      },
+      getC4ShapeKeys: function(t) {
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+      },
+      getBoundarys: function(t) {
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+      },
+      getCurrentBoundaryParse: function() {
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+      },
+      getParentBoundaryParse: function() {
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+      getRels: function() {
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+      getTitle: function() {
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+      getC4Type: function() {
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+      getC4ShapeInRow: function() {
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+      getC4BoundaryInRow: function() {
+        return wk;
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+      setAccTitle: Ev,
+      getAccTitle: Sv,
+      getAccDescription: Dv,
+      setAccDescription: Av,
+      parseDirective: function(t, e, n) {
+        nL.parseDirective(this, t, e, n);
+      },
+      getConfig: () => jx().c4,
+      clear: function() {
+        fk = [],
+          bk = [{
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+            label: { text: "global" },
+            type: { text: "global" },
+            tags: null,
+            link: null,
+            parentBoundary: "",
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+          mk = "",
+          yk = "global",
+          gk = [""],
+          _k = [],
+          gk = [""],
+          xk = "",
+          vk = !1,
+          kk = 4,
+          wk = 2;
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+      LINETYPE: {
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+        DOTTED: 1,
+        NOTE: 2,
+        SOLID_CROSS: 3,
+        DOTTED_CROSS: 4,
+        SOLID_OPEN: 5,
+        DOTTED_OPEN: 6,
+        LOOP_START: 10,
+        LOOP_END: 11,
+        ALT_START: 12,
+        ALT_ELSE: 13,
+        ALT_END: 14,
+        OPT_START: 15,
+        OPT_END: 16,
+        ACTIVE_START: 17,
+        ACTIVE_END: 18,
+        PAR_START: 19,
+        PAR_AND: 20,
+        PAR_END: 21,
+        RECT_START: 22,
+        RECT_END: 23,
+        SOLID_POINT: 24,
+        DOTTED_POINT: 25,
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+      ARROWTYPE: { FILLED: 0, OPEN: 1 },
+      PLACEMENT: { LEFTOF: 0, RIGHTOF: 1, OVER: 2 },
+      setTitle: function(t) {
+        let e = ab(t, jx());
+        xk = e;
+      },
+      setC4Type: function(t) {
+        let e = ab(t, jx());
+        Tk = e;
+      },
+    },
+    Ak = function(t, e) {
+      const n = t.append("rect");
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+        n.attr("x", e.x),
+          n.attr("y", e.y),
+          n.attr("fill", e.fill),
+          n.attr("stroke", e.stroke),
+          n.attr("width", e.width),
+          n.attr("height", e.height),
+          n.attr("rx", e.rx),
+          n.attr("ry", e.ry),
+          "undefined" !== e.attrs && null !== e.attrs
+      ) for (let t in e.attrs) n.attr(t, e.attrs[t]);
+      return "undefined" !== e.class && n.attr("class", e.class), n;
+    },
+    Dk = function(t, e, n, r, a, s) {
+      const o = t.append("image");
+      o.attr("width", e), o.attr("height", n), o.attr("x", r), o.attr("y", a);
+      let l = s.startsWith("data:image/png;base64") ? s : i(s);
+      o.attr("xlink:href", l);
+    },
+    Lk = function() {
+      return { x: 0, y: 0, fill: "#EDF2AE", stroke: "#666", width: 100, anchor: "start", height: 100, rx: 0, ry: 0 };
+    },
+    Ok = (t, e) => ({ fontFamily: t[e + "FontFamily"], fontSize: t[e + "FontSize"], fontWeight: t[e + "FontWeight"] }),
+    Nk = function() {
+      function t(t, e, n, r, a, s, o) {
+        i(e.append("text").attr("x", n + a / 2).attr("y", r + s / 2 + 5).style("text-anchor", "middle").text(t), o);
+      }
+      function e(t, e, n, r, a, s, o, l) {
+        const { fontSize: c, fontFamily: h, fontWeight: u } = l, d = t.split(ub.lineBreakRegex);
+        for (let t = 0; t < d.length; t++) {
+          const s = t * c - c * (d.length - 1) / 2,
+            l = e.append("text").attr("x", n + a / 2).attr("y", r).style("text-anchor", "middle").attr(
+              "dominant-baseline",
+              "middle",
+            ).style("font-size", c).style("font-weight", u).style("font-family", h);
+          l.append("tspan").attr("dy", s).text(d[t]).attr("alignment-baseline", "mathematical"), i(l, o);
+        }
+      }
+      function n(t, n, r, a, s, o, l, c) {
+        const h = n.append("switch"),
+          u = h.append("foreignObject").attr("x", r).attr("y", a).attr("width", s).attr("height", o).append("xhtml:div")
+            .style("display", "table").style("height", "100%").style("width", "100%");
+        u.append("div").style("display", "table-cell").style("text-align", "center").style("vertical-align", "middle")
+          .text(t),
+          e(t, h, r, a, s, 0, l, c),
+          i(u, l);
+      }
+      function i(t, e) {
+        for (const n in e) e.hasOwnProperty(n) && t.attr(n, e[n]);
+      }
+      return function(i) {
+        return "fo" === i.textPlacement ? n : "old" === i.textPlacement ? t : e;
+      };
+    }(),
+    Mk = function(t, e, n) {
+      const i = t.append("g");
+      let r = e.bgColor ? e.bgColor : "none",
+        a = e.borderColor ? e.borderColor : "#444444",
+        s = e.fontColor ? e.fontColor : "black",
+        o = { "stroke-width": 1, "stroke-dasharray": "7.0,7.0" };
+      e.nodeType && (o = { "stroke-width": 1 });
+      let l = { x: e.x, y: e.y, fill: r, stroke: a, width: e.width, height: e.height, rx: 2.5, ry: 2.5, attrs: o };
+      Ak(i, l);
+      let c = n.boundaryFont();
+      c.fontWeight = "bold",
+        c.fontSize = c.fontSize + 2,
+        c.fontColor = s,
+        Nk(n)(e.label.text, i, e.x, e.y + e.label.Y, e.width, e.height, { fill: "#444444" }, c),
+        e.type && "" !== e.type.text
+        && (c = n.boundaryFont(),
+          c.fontColor = s,
+          Nk(n)(e.type.text, i, e.x, e.y + e.type.Y, e.width, e.height, { fill: "#444444" }, c)),
+        e.descr && "" !== e.descr.text
+        && (c = n.boundaryFont(),
+          c.fontSize = c.fontSize - 2,
+          c.fontColor = s,
+          Nk(n)(e.descr.text, i, e.x, e.y + e.descr.Y, e.width, e.height, { fill: "#444444" }, c));
+    },
+    Bk = function(t, e, n) {
+      let i = e.bgColor ? e.bgColor : n[e.typeC4Shape.text + "_bg_color"],
+        r = e.borderColor ? e.borderColor : n[e.typeC4Shape.text + "_border_color"],
+        a = e.fontColor ? e.fontColor : "#FFFFFF",
+        s =
+          "data:image/png;base64,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";
+      switch (e.typeC4Shape.text) {
+        case "person":
+          s =
+            "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAwCAIAAADYYG7QAAACD0lEQVR4Xu2YoU4EMRCGT+4j8Ai8AhaH4QHgAUjQuFMECUgMIUgwJAgMhgQsAYUiJCiQIBBY+EITsjfTdme6V24v4c8vyGbb+ZjOtN0bNcvjQXmkH83WvYBWto6PLm6v7p7uH1/w2fXD+PBycX1Pv2l3IdDm/vn7x+dXQiAubRzoURa7gRZWd0iGRIiJbOnhnfYBQZNJjNbuyY2eJG8fkDE3bbG4ep6MHUAsgYxmE3nVs6VsBWJSGccsOlFPmLIViMzLOB7pCVO2AtHJMohH7Fh6zqitQK7m0rJvAVYgGcEpe//PLdDz65sM4pF9N7ICcXDKIB5Nv6j7tD0NoSdM2QrU9Gg0ewE1LqBhHR3BBdvj2vapnidjHxD/q6vd7Pvhr31AwcY8eXMTXAKECZZJFXuEq27aLgQK5uLMohCenGGuGewOxSjBvYBqeG6B+Nqiblggdjnc+ZXDy+FNFpFzw76O3UBAROuXh6FoiAcf5g9eTvUgzy0nWg6I8cXHRUpg5bOVBCo+KDpFajOf23GgPme7RSQ+lacIENUgJ6gg1k6HjgOlqnLqip4tEuhv0hNEMXUD0clyXE3p6pZA0S2nnvTlXwLJEZWlb7cTQH1+USgTN4VhAenm/wea1OCAOmqo6fE1WCb9WSKBah+rbUWPWAmE2Rvk0ApiB45eOyNAzU8xcTvj8KvkKEoOaIYeHNA3ZuygAvFMUO0AAAAASUVORK5CYII=";
+          break;
+        case "external_person":
+          s =
+            "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAwCAIAAADYYG7QAAAB6ElEQVR4Xu2YLY+EMBCG9+dWr0aj0Wg0Go1Go0+j8Xdv2uTCvv1gpt0ebHKPuhDaeW4605Z9mJvx4AdXUyTUdd08z+u6flmWZRnHsWkafk9DptAwDPu+f0eAYtu2PEaGWuj5fCIZrBAC2eLBAnRCsEkkxmeaJp7iDJ2QMDdHsLg8SxKFEJaAo8lAXnmuOFIhTMpxxKATebo4UiFknuNo4OniSIXQyRxEA3YsnjGCVEjVXD7yLUAqxBGUyPv/Y4W2beMgGuS7kVQIBycH0fD+oi5pezQETxdHKmQKGk1eQEYldK+jw5GxPfZ9z7Mk0Qnhf1W1m3w//EUn5BDmSZsbR44QQLBEqrBHqOrmSKaQAxdnLArCrxZcM7A7ZKs4ioRq8LFC+NpC3WCBJsvpVw5edm9iEXFuyNfxXAgSwfrFQ1c0iNda8AdejvUgnktOtJQQxmcfFzGglc5WVCj7oDgFqU18boeFSs52CUh8LE8BIVQDT1ABrB0HtgSEYlX5doJnCwv9TXocKCaKbnwhdDKPq4lf3SwU3HLq4V/+WYhHVMa/3b4IlfyikAduCkcBc7mQ3/z/Qq/cTuikhkzB12Ae/mcJC9U+Vo8Ej1gWAtgbeGgFsAMHr50BIWOLCbezvhpBFUdY6EJuJ/QDW0XoMX60zZ0AAAAASUVORK5CYII=";
+      }
+      const o = t.append("g");
+      o.attr("class", "person-man");
+      const l = Lk();
+      switch (e.typeC4Shape.text) {
+        case "person":
+        case "external_person":
+        case "system":
+        case "external_system":
+        case "container":
+        case "external_container":
+        case "component":
+        case "external_component":
+          l.x = e.x,
+            l.y = e.y,
+            l.fill = i,
+            l.width = e.width,
+            l.height = e.height,
+            l.style = "stroke:" + r + ";stroke-width:0.5;",
+            l.rx = 2.5,
+            l.ry = 2.5,
+            Ak(o, l);
+          break;
+        case "system_db":
+        case "external_system_db":
+        case "container_db":
+        case "external_container_db":
+        case "component_db":
+        case "external_component_db":
+          o.append("path").attr("fill", i).attr("stroke-width", "0.5").attr("stroke", r).attr(
+            "d",
+            "Mstartx,startyc0,-10 half,-10 half,-10c0,0 half,0 half,10l0,heightc0,10 -half,10 -half,10c0,0 -half,0 -half,-10l0,-height"
+              .replaceAll("startx", e.x).replaceAll("starty", e.y).replaceAll("half", e.width / 2).replaceAll(
+                "height",
+                e.height,
+              ),
+          ),
+            o.append("path").attr("fill", "none").attr("stroke-width", "0.5").attr("stroke", r).attr(
+              "d",
+              "Mstartx,startyc0,10 half,10 half,10c0,0 half,0 half,-10".replaceAll("startx", e.x).replaceAll(
+                "starty",
+                e.y,
+              ).replaceAll("half", e.width / 2),
+            );
+          break;
+        case "system_queue":
+        case "external_system_queue":
+        case "container_queue":
+        case "external_container_queue":
+        case "component_queue":
+        case "external_component_queue":
+          o.append("path").attr("fill", i).attr("stroke-width", "0.5").attr("stroke", r).attr(
+            "d",
+            "Mstartx,startylwidth,0c5,0 5,half 5,halfc0,0 0,half -5,halfl-width,0c-5,0 -5,-half -5,-halfc0,0 0,-half 5,-half"
+              .replaceAll("startx", e.x).replaceAll("starty", e.y).replaceAll("width", e.width).replaceAll(
+                "half",
+                e.height / 2,
+              ),
+          ),
+            o.append("path").attr("fill", "none").attr("stroke-width", "0.5").attr("stroke", r).attr(
+              "d",
+              "Mstartx,startyc-5,0 -5,half -5,halfc0,half 5,half 5,half".replaceAll("startx", e.x + e.width).replaceAll(
+                "starty",
+                e.y,
+              ).replaceAll("half", e.height / 2),
+            );
+      }
+      let c = Ok(n, e.typeC4Shape.text);
+      switch (
+        o.append("text").attr("fill", a).attr("font-family", c.fontFamily).attr("font-size", c.fontSize - 2).attr(
+          "font-style",
+          "italic",
+        ).attr("lengthAdjust", "spacing").attr("textLength", e.typeC4Shape.width).attr(
+          "x",
+          e.x + e.width / 2 - e.typeC4Shape.width / 2,
+        ).attr("y", e.y + e.typeC4Shape.Y).text("<<" + e.typeC4Shape.text + ">>"), e.typeC4Shape.text
+      ) {
+        case "person":
+        case "external_person":
+          Dk(o, 48, 48, e.x + e.width / 2 - 24, e.y + e.image.Y, s);
+      }
+      let h = n[e.typeC4Shape.text + "Font"]();
+      return h.fontWeight = "bold",
+        h.fontSize = h.fontSize + 2,
+        h.fontColor = a,
+        Nk(n)(e.label.text, o, e.x, e.y + e.label.Y, e.width, e.height, { fill: a }, h),
+        h = n[e.typeC4Shape.text + "Font"](),
+        h.fontColor = a,
+        e.thchn && "" !== e.thchn.text
+          ? Nk(n)(e.thchn.text, o, e.x, e.y + e.thchn.Y, e.width, e.height, { fill: a, "font-style": "italic" }, h)
+          : e.type && "" !== e.type.text
+            && Nk(n)(e.type.text, o, e.x, e.y + e.type.Y, e.width, e.height, { fill: a, "font-style": "italic" }, h),
+        e.descr && "" !== e.descr.text
+        && (h = n.personFont(),
+          h.fontColor = a,
+          Nk(n)(e.descr.text, o, e.x, e.y + e.descr.Y, e.width, e.height, { fill: a }, h)),
+        e.height;
+    },
+    Ik = (t, e, n) => {
+      const i = t.append("g");
+      let r = 0;
+      for (let t of e) {
+        let e = t.textColor ? t.textColor : "#444444",
+          a = t.lineColor ? t.lineColor : "#444444",
+          s = t.offsetX ? parseInt(t.offsetX) : 0,
+          o = t.offsetY ? parseInt(t.offsetY) : 0,
+          l = "";
+        if (0 === r) {
+          let e = i.append("line");
+          e.attr("x1", t.startPoint.x),
+            e.attr("y1", t.startPoint.y),
+            e.attr("x2", t.endPoint.x),
+            e.attr("y2", t.endPoint.y),
+            e.attr("stroke-width", "1"),
+            e.attr("stroke", a),
+            e.style("fill", "none"),
+            "rel_b" !== t.type && e.attr("marker-end", "url(" + l + "#arrowhead)"),
+            "birel" !== t.type && "rel_b" !== t.type || e.attr("marker-start", "url(" + l + "#arrowend)"),
+            r = -1;
+        } else {
+          let e = i.append("path");
+          e.attr("fill", "none").attr("stroke-width", "1").attr("stroke", a).attr(
+            "d",
+            "Mstartx,starty Qcontrolx,controly stopx,stopy ".replaceAll("startx", t.startPoint.x).replaceAll(
+              "starty",
+              t.startPoint.y,
+            ).replaceAll(
+              "controlx",
+              t.startPoint.x + (t.endPoint.x - t.startPoint.x) / 2 - (t.endPoint.x - t.startPoint.x) / 4,
+            ).replaceAll("controly", t.startPoint.y + (t.endPoint.y - t.startPoint.y) / 2).replaceAll(
+              "stopx",
+              t.endPoint.x,
+            ).replaceAll("stopy", t.endPoint.y),
+          ),
+            "rel_b" !== t.type && e.attr("marker-end", "url(" + l + "#arrowhead)"),
+            "birel" !== t.type && "rel_b" !== t.type || e.attr("marker-start", "url(" + l + "#arrowend)");
+        }
+        let c = n.messageFont();
+        Nk(n)(
+          t.label.text,
+          i,
+          Math.min(t.startPoint.x, t.endPoint.x) + Math.abs(t.endPoint.x - t.startPoint.x) / 2 + s,
+          Math.min(t.startPoint.y, t.endPoint.y) + Math.abs(t.endPoint.y - t.startPoint.y) / 2 + o,
+          t.label.width,
+          t.label.height,
+          { fill: e },
+          c,
+        ),
+          t.techn && "" !== t.techn.text && (c = n.messageFont(),
+            Nk(n)(
+              "[" + t.techn.text + "]",
+              i,
+              Math.min(t.startPoint.x, t.endPoint.x) + Math.abs(t.endPoint.x - t.startPoint.x) / 2 + s,
+              Math.min(t.startPoint.y, t.endPoint.y) + Math.abs(t.endPoint.y - t.startPoint.y) / 2 + n.messageFontSize
+                + 5 + o,
+              Math.max(t.label.width, t.techn.width),
+              t.techn.height,
+              { fill: e, "font-style": "italic" },
+              c,
+            ));
+      }
+    },
+    Fk = function(t) {
+      t.append("defs").append("marker").attr("id", "arrowhead").attr("refX", 9).attr("refY", 5).attr(
+        "markerUnits",
+        "userSpaceOnUse",
+      ).attr("markerWidth", 12).attr("markerHeight", 12).attr("orient", "auto").append("path").attr(
+        "d",
+        "M 0 0 L 10 5 L 0 10 z",
+      );
+    },
+    Rk = function(t) {
+      t.append("defs").append("marker").attr("id", "arrowend").attr("refX", 1).attr("refY", 5).attr(
+        "markerUnits",
+        "userSpaceOnUse",
+      ).attr("markerWidth", 12).attr("markerHeight", 12).attr("orient", "auto").append("path").attr(
+        "d",
+        "M 10 0 L 0 5 L 10 10 z",
+      );
+    },
+    $k = function(t) {
+      t.append("defs").append("marker").attr("id", "filled-head").attr("refX", 18).attr("refY", 7).attr(
+        "markerWidth",
+        20,
+      ).attr("markerHeight", 28).attr("orient", "auto").append("path").attr("d", "M 18,7 L9,13 L14,7 L9,1 Z");
+    },
+    Pk = function(t) {
+      const e = t.append("defs").append("marker").attr("id", "crosshead").attr("markerWidth", 15).attr(
+        "markerHeight",
+        8,
+      ).attr("orient", "auto").attr("refX", 16).attr("refY", 4);
+      e.append("path").attr("fill", "black").attr("stroke", "#000000").style("stroke-dasharray", "0, 0").attr(
+        "stroke-width",
+        "1px",
+      ).attr("d", "M 9,2 V 6 L16,4 Z"),
+        e.append("path").attr("fill", "none").attr("stroke", "#000000").style("stroke-dasharray", "0, 0").attr(
+          "stroke-width",
+          "1px",
+        ).attr("d", "M 0,1 L 6,7 M 6,1 L 0,7");
+    },
+    Yk = function(t) {
+      t.append("defs").append("symbol").attr("id", "database").attr("fill-rule", "evenodd").attr("clip-rule", "evenodd")
+        .append("path").attr("transform", "scale(.5)").attr(
+          "d",
+          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+        );
+    },
+    jk = function(t) {
+      t.append("defs").append("symbol").attr("id", "computer").attr("width", "24").attr("height", "24").append("path")
+        .attr("transform", "scale(.5)").attr(
+          "d",
+          "M2 2v13h20v-13h-20zm18 11h-16v-9h16v9zm-10.228 6l.466-1h3.524l.467 1h-4.457zm14.228 3h-24l2-6h2.104l-1.33 4h18.45l-1.297-4h2.073l2 6zm-5-10h-14v-7h14v7z",
+        );
+    },
+    zk = function(t) {
+      t.append("defs").append("symbol").attr("id", "clock").attr("width", "24").attr("height", "24").append("path")
+        .attr("transform", "scale(.5)").attr(
+          "d",
+          "M12 2c5.514 0 10 4.486 10 10s-4.486 10-10 10-10-4.486-10-10 4.486-10 10-10zm0-2c-6.627 0-12 5.373-12 12s5.373 12 12 12 12-5.373 12-12-5.373-12-12-12zm5.848 12.459c.202.038.202.333.001.372-1.907.361-6.045 1.111-6.547 1.111-.719 0-1.301-.582-1.301-1.301 0-.512.77-5.447 1.125-7.445.034-.192.312-.181.343.014l.985 6.238 5.394 1.011z",
+        );
+    };
+  let Uk = 0, Wk = 0, Hk = 4, qk = 2;
+  uk.yy = Sk;
+  let Vk = {};
+  class Gk {
+    constructor(t) {
+      this.name = "",
+        this.data = {},
+        this.data.startx = void 0,
+        this.data.stopx = void 0,
+        this.data.starty = void 0,
+        this.data.stopy = void 0,
+        this.data.widthLimit = void 0,
+        this.nextData = {},
+        this.nextData.startx = void 0,
+        this.nextData.stopx = void 0,
+        this.nextData.starty = void 0,
+        this.nextData.stopy = void 0,
+        this.nextData.cnt = 0,
+        Xk(t.db.getConfig());
+    }
+    setData(t, e, n, i) {
+      this.nextData.startx = this.data.startx = t,
+        this.nextData.stopx = this.data.stopx = e,
+        this.nextData.starty = this.data.starty = n,
+        this.nextData.stopy = this.data.stopy = i;
+    }
+    updateVal(t, e, n, i) {
+      void 0 === t[e] ? t[e] = n : t[e] = i(n, t[e]);
+    }
+    insert(t) {
+      this.nextData.cnt = this.nextData.cnt + 1;
+      let e = this.nextData.startx === this.nextData.stopx
+          ? this.nextData.stopx + t.margin
+          : this.nextData.stopx + 2 * t.margin,
+        n = e + t.width,
+        i = this.nextData.starty + 2 * t.margin,
+        r = i + t.height;
+      (e >= this.data.widthLimit || n >= this.data.widthLimit || this.nextData.cnt > Hk)
+      && (e = this.nextData.startx + t.margin + Vk.nextLinePaddingX,
+        i = this.nextData.stopy + 2 * t.margin,
+        this.nextData.stopx = n = e + t.width,
+        this.nextData.starty = this.nextData.stopy,
+        this.nextData.stopy = r = i + t.height,
+        this.nextData.cnt = 1),
+        t.x = e,
+        t.y = i,
+        this.updateVal(this.data, "startx", e, Math.min),
+        this.updateVal(this.data, "starty", i, Math.min),
+        this.updateVal(this.data, "stopx", n, Math.max),
+        this.updateVal(this.data, "stopy", r, Math.max),
+        this.updateVal(this.nextData, "startx", e, Math.min),
+        this.updateVal(this.nextData, "starty", i, Math.min),
+        this.updateVal(this.nextData, "stopx", n, Math.max),
+        this.updateVal(this.nextData, "stopy", r, Math.max);
+    }
+    init(t) {
+      this.name = "",
+        this.data = { startx: void 0, stopx: void 0, starty: void 0, stopy: void 0, widthLimit: void 0 },
+        this.nextData = { startx: void 0, stopx: void 0, starty: void 0, stopy: void 0, cnt: 0 },
+        Xk(t.db.getConfig());
+    }
+    bumpLastMargin(t) {
+      this.data.stopx += t, this.data.stopy += t;
+    }
+  }
+  const Xk = function(t) {
+      lx(Vk, t),
+        t.fontFamily && (Vk.personFontFamily = Vk.systemFontFamily = Vk.messageFontFamily = t.fontFamily),
+        t.fontSize && (Vk.personFontSize = Vk.systemFontSize = Vk.messageFontSize = t.fontSize),
+        t.fontWeight && (Vk.personFontWeight = Vk.systemFontWeight = Vk.messageFontWeight = t.fontWeight);
+    },
+    Zk = (t, e) => ({ fontFamily: t[e + "FontFamily"], fontSize: t[e + "FontSize"], fontWeight: t[e + "FontWeight"] }),
+    Qk = t => ({ fontFamily: t.boundaryFontFamily, fontSize: t.boundaryFontSize, fontWeight: t.boundaryFontWeight });
+  function Kk(t, e, n, i, r) {
+    if (!e[t].width) {
+      if (n) {
+        e[t].text = xx(e[t].text, r, i),
+          e[t].textLines = e[t].text.split(ub.lineBreakRegex).length,
+          e[t].width = r,
+          e[t].height = kx(e[t].text, i);
+      } else {
+        let n = e[t].text.split(ub.lineBreakRegex);
+        e[t].textLines = n.length;
+        let r = 0;
+        e[t].height = 0, e[t].width = 0;
+        for (const a of n) e[t].width = Math.max(wx(a, i), e[t].width), r = kx(a, i), e[t].height = e[t].height + r;
+      }
+    }
+  }
+  const Jk = function(t, e, n) {
+      e.x = n.data.startx,
+        e.y = n.data.starty,
+        e.width = n.data.stopx - n.data.startx,
+        e.height = n.data.stopy - n.data.starty,
+        e.label.y = Vk.c4ShapeMargin - 35;
+      let i = e.wrap && Vk.wrap, r = Qk(Vk);
+      r.fontSize = r.fontSize + 2, r.fontWeight = "bold", Kk("label", e, i, r, wx(e.label.text, r)), Mk(t, e, Vk);
+    },
+    tw = function(t, e, n, i) {
+      let r = 0;
+      for (const a of i) {
+        r = 0;
+        const i = n[a];
+        let s = Zk(Vk, i.typeC4Shape.text);
+        switch (
+          s.fontSize = s.fontSize - 2,
+            i.typeC4Shape.width = wx("<<" + i.typeC4Shape.text + ">>", s),
+            i.typeC4Shape.height = s.fontSize + 2,
+            i.typeC4Shape.Y = Vk.c4ShapePadding,
+            r = i.typeC4Shape.Y + i.typeC4Shape.height - 4,
+            i.image = { width: 0, height: 0, Y: 0 },
+            i.typeC4Shape.text
+        ) {
+          case "person":
+          case "external_person":
+            i.image.width = 48, i.image.height = 48, i.image.Y = r, r = i.image.Y + i.image.height;
+        }
+        i.sprite && (i.image.width = 48, i.image.height = 48, i.image.Y = r, r = i.image.Y + i.image.height);
+        let o = i.wrap && Vk.wrap, l = Vk.width - 2 * Vk.c4ShapePadding, c = Zk(Vk, i.typeC4Shape.text);
+        if (
+          c.fontSize = c.fontSize + 2,
+            c.fontWeight = "bold",
+            Kk("label", i, o, c, l),
+            i.label.Y = r + 8,
+            r = i.label.Y + i.label.height,
+            i.type && "" !== i.type.text
+        ) {
+          i.type.text = "[" + i.type.text + "]",
+            Kk("type", i, o, Zk(Vk, i.typeC4Shape.text), l),
+            i.type.Y = r + 5,
+            r = i.type.Y + i.type.height;
+        } else if (i.techn && "" !== i.techn.text) {
+          i.techn.text = "[" + i.techn.text + "]",
+            Kk("techn", i, o, Zk(Vk, i.techn.text), l),
+            i.techn.Y = r + 5,
+            r = i.techn.Y + i.techn.height;
+        }
+        let h = r, u = i.label.width;
+        if (i.descr && "" !== i.descr.text) {
+          Kk("descr", i, o, Zk(Vk, i.typeC4Shape.text), l),
+            i.descr.Y = r + 20,
+            r = i.descr.Y + i.descr.height,
+            u = Math.max(i.label.width, i.descr.width),
+            h = r - 5 * i.descr.textLines;
+        }
+        u += Vk.c4ShapePadding,
+          i.width = Math.max(i.width || Vk.width, u, Vk.width),
+          i.height = Math.max(i.height || Vk.height, h, Vk.height),
+          i.margin = i.margin || Vk.c4ShapeMargin,
+          t.insert(i),
+          Bk(e, i, Vk);
+      }
+      t.bumpLastMargin(Vk.c4ShapeMargin);
+    };
+  class ew {
+    constructor(t, e) {
+      this.x = t, this.y = e;
+    }
+  }
+  let nw = function(t, e) {
+      let n = t.x,
+        i = t.y,
+        r = e.x,
+        a = e.y,
+        s = n + t.width / 2,
+        o = i + t.height / 2,
+        l = Math.abs(n - r),
+        c = Math.abs(i - a),
+        h = c / l,
+        u = t.height / t.width,
+        d = null;
+      return i == a && n < r
+        ? d = new ew(n + t.width, o)
+        : i == a && n > r
+        ? d = new ew(n, o)
+        : n == r && i < a
+        ? d = new ew(s, i + t.height)
+        : n == r && i > a && (d = new ew(s, i)),
+        n > r && i < a
+          ? d = u >= h ? new ew(n, o + h * t.width / 2) : new ew(s - l / c * t.height / 2, i + t.height)
+          : n < r && i < a
+          ? d = u >= h ? new ew(n + t.width, o + h * t.width / 2) : new ew(s + l / c * t.height / 2, i + t.height)
+          : n < r && i > a
+          ? d = u >= h ? new ew(n + t.width, o - h * t.width / 2) : new ew(s + t.height / 2 * l / c, i)
+          : n > r && i > a && (d = u >= h ? new ew(n, o - t.width / 2 * h) : new ew(s - t.height / 2 * l / c, i)),
+        d;
+    },
+    iw = function(t, e) {
+      let n = { x: 0, y: 0 };
+      n.x = e.x + e.width / 2, n.y = e.y + e.height / 2;
+      let i = nw(t, n);
+      return n.x = t.x + t.width / 2, n.y = t.y + t.height / 2, { startPoint: i, endPoint: nw(e, n) };
+    };
+  function rw(t, e, n, i, r) {
+    let a = new Gk(r);
+    a.data.widthLimit = n.data.widthLimit / Math.min(qk, i.length);
+    for (let [s, o] of i.entries()) {
+      let i = 0;
+      o.image = { width: 0, height: 0, Y: 0 },
+        o.sprite && (o.image.width = 48, o.image.height = 48, o.image.Y = i, i = o.image.Y + o.image.height);
+      let l = o.wrap && Vk.wrap, c = Qk(Vk);
+      if (
+        c.fontSize = c.fontSize + 2,
+          c.fontWeight = "bold",
+          Kk("label", o, l, c, a.data.widthLimit),
+          o.label.Y = i + 8,
+          i = o.label.Y + o.label.height,
+          o.type && "" !== o.type.text
+      ) {
+        o.type.text = "[" + o.type.text + "]",
+          Kk("type", o, l, Qk(Vk), a.data.widthLimit),
+          o.type.Y = i + 5,
+          i = o.type.Y + o.type.height;
+      }
+      if (o.descr && "" !== o.descr.text) {
+        let t = Qk(Vk);
+        t.fontSize = t.fontSize - 2,
+          Kk("descr", o, l, t, a.data.widthLimit),
+          o.descr.Y = i + 20,
+          i = o.descr.Y + o.descr.height;
+      }
+      if (0 == s || s % qk == 0) {
+        let t = n.data.startx + Vk.diagramMarginX, e = n.data.stopy + Vk.diagramMarginY + i;
+        a.setData(t, t, e, e);
+      } else {
+        let t = a.data.stopx !== a.data.startx ? a.data.stopx + Vk.diagramMarginX : a.data.startx, e = a.data.starty;
+        a.setData(t, t, e, e);
+      }
+      a.name = o.alias;
+      let h = r.db.getC4ShapeArray(o.alias), u = r.db.getC4ShapeKeys(o.alias);
+      u.length > 0 && tw(a, t, h, u), e = o.alias;
+      let d = r.db.getBoundarys(e);
+      d.length > 0 && rw(t, e, a, d, r),
+        "global" !== o.alias && Jk(t, o, a),
+        n.data.stopy = Math.max(a.data.stopy + Vk.c4ShapeMargin, n.data.stopy),
+        n.data.stopx = Math.max(a.data.stopx + Vk.c4ShapeMargin, n.data.stopx),
+        Uk = Math.max(Uk, n.data.stopx),
+        Wk = Math.max(Wk, n.data.stopy);
+    }
+  }
+  const aw = {
+    drawPersonOrSystemArray: tw,
+    drawBoundary: Jk,
+    setConf: Xk,
+    draw: function(t, e, n, i) {
+      Vk = jx().c4;
+      const r = jx().securityLevel;
+      let a;
+      "sandbox" === r && (a = ie("#i" + e));
+      const s = ie("sandbox" === r ? a.nodes()[0].contentDocument.body : "body");
+      let o = i.db;
+      i.db.setWrap(Vk.wrap),
+        Hk = o.getC4ShapeInRow(),
+        qk = o.getC4BoundaryInRow(),
+        tb.debug(`C:${JSON.stringify(Vk, null, 2)}`);
+      const l = "sandbox" === r ? s.select(`[id="${e}"]`) : ie(`[id="${e}"]`);
+      jk(l), Yk(l), zk(l);
+      let c = new Gk(i);
+      c.setData(Vk.diagramMarginX, Vk.diagramMarginX, Vk.diagramMarginY, Vk.diagramMarginY),
+        c.data.widthLimit = screen.availWidth,
+        Uk = Vk.diagramMarginX,
+        Wk = Vk.diagramMarginY;
+      const h = i.db.getTitle();
+      rw(l, "", c, i.db.getBoundarys(""), i),
+        Fk(l),
+        Rk(l),
+        Pk(l),
+        $k(l),
+        function(t, e, n, i) {
+          let r = 0;
+          for (let t of e) {
+            r += 1;
+            let e = t.wrap && Vk.wrap,
+              s = {
+                fontFamily: (a = Vk).messageFontFamily,
+                fontSize: a.messageFontSize,
+                fontWeight: a.messageFontWeight,
+              };
+            "C4Dynamic" === i.db.getC4Type() && (t.label.text = r + ": " + t.label.text);
+            let o = wx(t.label.text, s);
+            Kk("label", t, e, s, o),
+              t.techn && "" !== t.techn.text && (o = wx(t.techn.text, s), Kk("techn", t, e, s, o)),
+              t.descr && "" !== t.descr.text && (o = wx(t.descr.text, s), Kk("descr", t, e, s, o));
+            let l = n(t.from), c = n(t.to), h = iw(l, c);
+            t.startPoint = h.startPoint, t.endPoint = h.endPoint;
+          }
+          var a;
+          Ik(t, e, Vk);
+        }(l, i.db.getRels(), i.db.getC4Shape, i),
+        c.data.stopx = Uk,
+        c.data.stopy = Wk;
+      const u = c.data;
+      let d = u.stopy - u.starty + 2 * Vk.diagramMarginY;
+      const p = u.stopx - u.startx + 2 * Vk.diagramMarginX;
+      h
+      && l.append("text").text(h).attr("x", (u.stopx - u.startx) / 2 - 4 * Vk.diagramMarginX).attr(
+        "y",
+        u.starty + Vk.diagramMarginY,
+      ), Gx(l, d, p, Vk.useMaxWidth);
+      const f = h ? 60 : 0;
+      l.attr("viewBox", u.startx - Vk.diagramMarginX + " -" + (Vk.diagramMarginY + f) + " " + p + " " + (d + f)),
+        tb.debug("models:", u);
+    },
+  };
+  var sw = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [1, 3],
+      i = [1, 7],
+      r = [1, 8],
+      a = [1, 9],
+      s = [1, 10],
+      o = [1, 13],
+      l = [1, 12],
+      c = [1, 16, 25],
+      h = [1, 20],
+      u = [1, 32],
+      d = [1, 33],
+      p = [1, 34],
+      f = [1, 36],
+      g = [1, 39],
+      y = [1, 37],
+      m = [1, 38],
+      b = [1, 44],
+      _ = [1, 45],
+      x = [1, 40],
+      v = [1, 41],
+      k = [1, 42],
+      w = [1, 43],
+      T = [1, 48],
+      C = [1, 49],
+      E = [1, 50],
+      S = [1, 51],
+      A = [16, 25],
+      D = [1, 65],
+      L = [1, 66],
+      O = [1, 67],
+      N = [1, 68],
+      M = [1, 69],
+      B = [1, 70],
+      I = [1, 71],
+      F = [1, 80],
+      R = [16, 25, 32, 45, 46, 54, 60, 61, 62, 63, 64, 65, 66, 71, 73],
+      $ = [16, 25, 30, 32, 45, 46, 50, 54, 60, 61, 62, 63, 64, 65, 66, 71, 73, 88, 89, 90, 91],
+      P = [5, 8, 9, 10, 11, 16, 19, 23, 25],
+      Y = [54, 88, 89, 90, 91],
+      j = [54, 65, 66, 88, 89, 90, 91],
+      z = [54, 60, 61, 62, 63, 64, 88, 89, 90, 91],
+      U = [16, 25, 32],
+      W = [1, 107],
+      H = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          mermaidDoc: 4,
+          statments: 5,
+          direction: 6,
+          directive: 7,
+          direction_tb: 8,
+          direction_bt: 9,
+          direction_rl: 10,
+          direction_lr: 11,
+          graphConfig: 12,
+          openDirective: 13,
+          typeDirective: 14,
+          closeDirective: 15,
+          NEWLINE: 16,
+          ":": 17,
+          argDirective: 18,
+          open_directive: 19,
+          type_directive: 20,
+          arg_directive: 21,
+          close_directive: 22,
+          CLASS_DIAGRAM: 23,
+          statements: 24,
+          EOF: 25,
+          statement: 26,
+          className: 27,
+          alphaNumToken: 28,
+          classLiteralName: 29,
+          GENERICTYPE: 30,
+          relationStatement: 31,
+          LABEL: 32,
+          classStatement: 33,
+          methodStatement: 34,
+          annotationStatement: 35,
+          clickStatement: 36,
+          cssClassStatement: 37,
+          noteStatement: 38,
+          acc_title: 39,
+          acc_title_value: 40,
+          acc_descr: 41,
+          acc_descr_value: 42,
+          acc_descr_multiline_value: 43,
+          CLASS: 44,
+          STYLE_SEPARATOR: 45,
+          STRUCT_START: 46,
+          members: 47,
+          STRUCT_STOP: 48,
+          ANNOTATION_START: 49,
+          ANNOTATION_END: 50,
+          MEMBER: 51,
+          SEPARATOR: 52,
+          relation: 53,
+          STR: 54,
+          NOTE_FOR: 55,
+          noteText: 56,
+          NOTE: 57,
+          relationType: 58,
+          lineType: 59,
+          AGGREGATION: 60,
+          EXTENSION: 61,
+          COMPOSITION: 62,
+          DEPENDENCY: 63,
+          LOLLIPOP: 64,
+          LINE: 65,
+          DOTTED_LINE: 66,
+          CALLBACK: 67,
+          LINK: 68,
+          LINK_TARGET: 69,
+          CLICK: 70,
+          CALLBACK_NAME: 71,
+          CALLBACK_ARGS: 72,
+          HREF: 73,
+          CSSCLASS: 74,
+          commentToken: 75,
+          textToken: 76,
+          graphCodeTokens: 77,
+          textNoTagsToken: 78,
+          TAGSTART: 79,
+          TAGEND: 80,
+          "==": 81,
+          "--": 82,
+          PCT: 83,
+          DEFAULT: 84,
+          SPACE: 85,
+          MINUS: 86,
+          keywords: 87,
+          UNICODE_TEXT: 88,
+          NUM: 89,
+          ALPHA: 90,
+          BQUOTE_STR: 91,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: {
+          2: "error",
+          5: "statments",
+          8: "direction_tb",
+          9: "direction_bt",
+          10: "direction_rl",
+          11: "direction_lr",
+          16: "NEWLINE",
+          17: ":",
+          19: "open_directive",
+          20: "type_directive",
+          21: "arg_directive",
+          22: "close_directive",
+          23: "CLASS_DIAGRAM",
+          25: "EOF",
+          30: "GENERICTYPE",
+          32: "LABEL",
+          39: "acc_title",
+          40: "acc_title_value",
+          41: "acc_descr",
+          42: "acc_descr_value",
+          43: "acc_descr_multiline_value",
+          44: "CLASS",
+          45: "STYLE_SEPARATOR",
+          46: "STRUCT_START",
+          48: "STRUCT_STOP",
+          49: "ANNOTATION_START",
+          50: "ANNOTATION_END",
+          51: "MEMBER",
+          52: "SEPARATOR",
+          54: "STR",
+          55: "NOTE_FOR",
+          57: "NOTE",
+          60: "AGGREGATION",
+          61: "EXTENSION",
+          62: "COMPOSITION",
+          63: "DEPENDENCY",
+          64: "LOLLIPOP",
+          65: "LINE",
+          66: "DOTTED_LINE",
+          67: "CALLBACK",
+          68: "LINK",
+          69: "LINK_TARGET",
+          70: "CLICK",
+          71: "CALLBACK_NAME",
+          72: "CALLBACK_ARGS",
+          73: "HREF",
+          74: "CSSCLASS",
+          77: "graphCodeTokens",
+          79: "TAGSTART",
+          80: "TAGEND",
+          81: "==",
+          82: "--",
+          83: "PCT",
+          84: "DEFAULT",
+          85: "SPACE",
+          86: "MINUS",
+          87: "keywords",
+          88: "UNICODE_TEXT",
+          89: "NUM",
+          90: "ALPHA",
+          91: "BQUOTE_STR",
+        },
+        productions_: [
+          0,
+          [3, 1],
+          [3, 1],
+          [3, 1],
+          [3, 2],
+          [6, 1],
+          [6, 1],
+          [6, 1],
+          [6, 1],
+          [4, 1],
+          [7, 4],
+          [7, 6],
+          [13, 1],
+          [14, 1],
+          [18, 1],
+          [15, 1],
+          [12, 4],
+          [24, 1],
+          [24, 2],
+          [24, 3],
+          [27, 1],
+          [27, 1],
+          [27, 2],
+          [27, 2],
+          [27, 2],
+          [26, 1],
+          [26, 2],
+          [26, 1],
+          [26, 1],
+          [26, 1],
+          [26, 1],
+          [26, 1],
+          [26, 1],
+          [26, 1],
+          [26, 1],
+          [26, 2],
+          [26, 2],
+          [26, 1],
+          [33, 2],
+          [33, 4],
+          [33, 5],
+          [33, 7],
+          [35, 4],
+          [47, 1],
+          [47, 2],
+          [34, 1],
+          [34, 2],
+          [34, 1],
+          [34, 1],
+          [31, 3],
+          [31, 4],
+          [31, 4],
+          [31, 5],
+          [38, 3],
+          [38, 2],
+          [53, 3],
+          [53, 2],
+          [53, 2],
+          [53, 1],
+          [58, 1],
+          [58, 1],
+          [58, 1],
+          [58, 1],
+          [58, 1],
+          [59, 1],
+          [59, 1],
+          [36, 3],
+          [36, 4],
+          [36, 3],
+          [36, 4],
+          [36, 4],
+          [36, 5],
+          [36, 3],
+          [36, 4],
+          [36, 4],
+          [36, 5],
+          [36, 3],
+          [36, 4],
+          [36, 4],
+          [36, 5],
+          [37, 3],
+          [75, 1],
+          [75, 1],
+          [76, 1],
+          [76, 1],
+          [76, 1],
+          [76, 1],
+          [76, 1],
+          [76, 1],
+          [76, 1],
+          [78, 1],
+          [78, 1],
+          [78, 1],
+          [78, 1],
+          [28, 1],
+          [28, 1],
+          [28, 1],
+          [29, 1],
+          [56, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 5:
+              i.setDirection("TB");
+              break;
+            case 6:
+              i.setDirection("BT");
+              break;
+            case 7:
+              i.setDirection("RL");
+              break;
+            case 8:
+              i.setDirection("LR");
+              break;
+            case 12:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 13:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 14:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 15:
+              i.parseDirective("}%%", "close_directive", "class");
+              break;
+            case 20:
+            case 21:
+              this.$ = a[o];
+              break;
+            case 22:
+              this.$ = a[o - 1] + a[o];
+              break;
+            case 23:
+            case 24:
+              this.$ = a[o - 1] + "~" + a[o];
+              break;
+            case 25:
+              i.addRelation(a[o]);
+              break;
+            case 26:
+              a[o - 1].title = i.cleanupLabel(a[o]), i.addRelation(a[o - 1]);
+              break;
+            case 35:
+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 36:
+            case 37:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 38:
+              i.addClass(a[o]);
+              break;
+            case 39:
+              i.addClass(a[o - 2]), i.setCssClass(a[o - 2], a[o]);
+              break;
+            case 40:
+              i.addClass(a[o - 3]), i.addMembers(a[o - 3], a[o - 1]);
+              break;
+            case 41:
+              i.addClass(a[o - 5]), i.setCssClass(a[o - 5], a[o - 3]), i.addMembers(a[o - 5], a[o - 1]);
+              break;
+            case 42:
+              i.addAnnotation(a[o], a[o - 2]);
+              break;
+            case 43:
+              this.$ = [a[o]];
+              break;
+            case 44:
+              a[o].push(a[o - 1]), this.$ = a[o];
+              break;
+            case 45:
+            case 47:
+            case 48:
+              break;
+            case 46:
+              i.addMember(a[o - 1], i.cleanupLabel(a[o]));
+              break;
+            case 49:
+              this.$ = { id1: a[o - 2], id2: a[o], relation: a[o - 1], relationTitle1: "none", relationTitle2: "none" };
+              break;
+            case 50:
+              this.$ = {
+                id1: a[o - 3],
+                id2: a[o],
+                relation: a[o - 1],
+                relationTitle1: a[o - 2],
+                relationTitle2: "none",
+              };
+              break;
+            case 51:
+              this.$ = {
+                id1: a[o - 3],
+                id2: a[o],
+                relation: a[o - 2],
+                relationTitle1: "none",
+                relationTitle2: a[o - 1],
+              };
+              break;
+            case 52:
+              this.$ = {
+                id1: a[o - 4],
+                id2: a[o],
+                relation: a[o - 2],
+                relationTitle1: a[o - 3],
+                relationTitle2: a[o - 1],
+              };
+              break;
+            case 53:
+              i.addNote(a[o], a[o - 1]);
+              break;
+            case 54:
+              i.addNote(a[o]);
+              break;
+            case 55:
+              this.$ = { type1: a[o - 2], type2: a[o], lineType: a[o - 1] };
+              break;
+            case 56:
+              this.$ = { type1: "none", type2: a[o], lineType: a[o - 1] };
+              break;
+            case 57:
+              this.$ = { type1: a[o - 1], type2: "none", lineType: a[o] };
+              break;
+            case 58:
+              this.$ = { type1: "none", type2: "none", lineType: a[o] };
+              break;
+            case 59:
+              this.$ = i.relationType.AGGREGATION;
+              break;
+            case 60:
+              this.$ = i.relationType.EXTENSION;
+              break;
+            case 61:
+              this.$ = i.relationType.COMPOSITION;
+              break;
+            case 62:
+              this.$ = i.relationType.DEPENDENCY;
+              break;
+            case 63:
+              this.$ = i.relationType.LOLLIPOP;
+              break;
+            case 64:
+              this.$ = i.lineType.LINE;
+              break;
+            case 65:
+              this.$ = i.lineType.DOTTED_LINE;
+              break;
+            case 66:
+            case 72:
+              this.$ = a[o - 2], i.setClickEvent(a[o - 1], a[o]);
+              break;
+            case 67:
+            case 73:
+              this.$ = a[o - 3], i.setClickEvent(a[o - 2], a[o - 1]), i.setTooltip(a[o - 2], a[o]);
+              break;
+            case 68:
+            case 76:
+              this.$ = a[o - 2], i.setLink(a[o - 1], a[o]);
+              break;
+            case 69:
+            case 77:
+              this.$ = a[o - 3], i.setLink(a[o - 2], a[o - 1], a[o]);
+              break;
+            case 70:
+            case 78:
+              this.$ = a[o - 3], i.setLink(a[o - 2], a[o - 1]), i.setTooltip(a[o - 2], a[o]);
+              break;
+            case 71:
+            case 79:
+              this.$ = a[o - 4], i.setLink(a[o - 3], a[o - 2], a[o]), i.setTooltip(a[o - 3], a[o - 1]);
+              break;
+            case 74:
+              this.$ = a[o - 3], i.setClickEvent(a[o - 2], a[o - 1], a[o]);
+              break;
+            case 75:
+              this.$ = a[o - 4], i.setClickEvent(a[o - 3], a[o - 2], a[o - 1]), i.setTooltip(a[o - 3], a[o]);
+              break;
+            case 80:
+              i.setCssClass(a[o - 1], a[o]);
+          }
+        },
+        table: [
+          { 3: 1, 4: 2, 5: n, 6: 4, 7: 5, 8: i, 9: r, 10: a, 11: s, 12: 6, 13: 11, 19: o, 23: l },
+          { 1: [3] },
+          { 1: [2, 1] },
+          { 1: [2, 2] },
+          { 1: [2, 3] },
+          { 3: 14, 4: 2, 5: n, 6: 4, 7: 5, 8: i, 9: r, 10: a, 11: s, 12: 6, 13: 11, 19: o, 23: l },
+          { 1: [2, 9] },
+          e(c, [2, 5]),
+          e(c, [2, 6]),
+          e(c, [2, 7]),
+          e(c, [2, 8]),
+          { 14: 15, 20: [1, 16] },
+          { 16: [1, 17] },
+          { 20: [2, 12] },
+          { 1: [2, 4] },
+          { 15: 18, 17: [1, 19], 22: h },
+          e([17, 22], [2, 13]),
+          {
+            6: 31,
+            7: 30,
+            8: i,
+            9: r,
+            10: a,
+            11: s,
+            13: 11,
+            19: o,
+            24: 21,
+            26: 22,
+            27: 35,
+            28: 46,
+            29: 47,
+            31: 23,
+            33: 24,
+            34: 25,
+            35: 26,
+            36: 27,
+            37: 28,
+            38: 29,
+            39: u,
+            41: d,
+            43: p,
+            44: f,
+            49: g,
+            51: y,
+            52: m,
+            55: b,
+            57: _,
+            67: x,
+            68: v,
+            70: k,
+            74: w,
+            88: T,
+            89: C,
+            90: E,
+            91: S,
+          },
+          { 16: [1, 52] },
+          { 18: 53, 21: [1, 54] },
+          { 16: [2, 15] },
+          { 25: [1, 55] },
+          { 16: [1, 56], 25: [2, 17] },
+          e(A, [2, 25], { 32: [1, 57] }),
+          e(A, [2, 27]),
+          e(A, [2, 28]),
+          e(A, [2, 29]),
+          e(A, [2, 30]),
+          e(A, [2, 31]),
+          e(A, [2, 32]),
+          e(A, [2, 33]),
+          e(A, [2, 34]),
+          { 40: [1, 58] },
+          { 42: [1, 59] },
+          e(A, [2, 37]),
+          e(A, [2, 45], {
+            53: 60,
+            58: 63,
+            59: 64,
+            32: [1, 62],
+            54: [1, 61],
+            60: D,
+            61: L,
+            62: O,
+            63: N,
+            64: M,
+            65: B,
+            66: I,
+          }),
+          { 27: 72, 28: 46, 29: 47, 88: T, 89: C, 90: E, 91: S },
+          e(A, [2, 47]),
+          e(A, [2, 48]),
+          { 28: 73, 88: T, 89: C, 90: E },
+          { 27: 74, 28: 46, 29: 47, 88: T, 89: C, 90: E, 91: S },
+          { 27: 75, 28: 46, 29: 47, 88: T, 89: C, 90: E, 91: S },
+          { 27: 76, 28: 46, 29: 47, 88: T, 89: C, 90: E, 91: S },
+          { 54: [1, 77] },
+          { 27: 78, 28: 46, 29: 47, 88: T, 89: C, 90: E, 91: S },
+          { 54: F, 56: 79 },
+          e(R, [2, 20], { 28: 46, 29: 47, 27: 81, 30: [1, 82], 88: T, 89: C, 90: E, 91: S }),
+          e(R, [2, 21], { 30: [1, 83] }),
+          e($, [2, 94]),
+          e($, [2, 95]),
+          e($, [2, 96]),
+          e([16, 25, 30, 32, 45, 46, 54, 60, 61, 62, 63, 64, 65, 66, 71, 73], [2, 97]),
+          e(P, [2, 10]),
+          { 15: 84, 22: h },
+          { 22: [2, 14] },
+          { 1: [2, 16] },
+          {
+            6: 31,
+            7: 30,
+            8: i,
+            9: r,
+            10: a,
+            11: s,
+            13: 11,
+            19: o,
+            24: 85,
+            25: [2, 18],
+            26: 22,
+            27: 35,
+            28: 46,
+            29: 47,
+            31: 23,
+            33: 24,
+            34: 25,
+            35: 26,
+            36: 27,
+            37: 28,
+            38: 29,
+            39: u,
+            41: d,
+            43: p,
+            44: f,
+            49: g,
+            51: y,
+            52: m,
+            55: b,
+            57: _,
+            67: x,
+            68: v,
+            70: k,
+            74: w,
+            88: T,
+            89: C,
+            90: E,
+            91: S,
+          },
+          e(A, [2, 26]),
+          e(A, [2, 35]),
+          e(A, [2, 36]),
+          { 27: 86, 28: 46, 29: 47, 54: [1, 87], 88: T, 89: C, 90: E, 91: S },
+          { 53: 88, 58: 63, 59: 64, 60: D, 61: L, 62: O, 63: N, 64: M, 65: B, 66: I },
+          e(A, [2, 46]),
+          { 59: 89, 65: B, 66: I },
+          e(Y, [2, 58], { 58: 90, 60: D, 61: L, 62: O, 63: N, 64: M }),
+          e(j, [2, 59]),
+          e(j, [2, 60]),
+          e(j, [2, 61]),
+          e(j, [2, 62]),
+          e(j, [2, 63]),
+          e(z, [2, 64]),
+          e(z, [2, 65]),
+          e(A, [2, 38], { 45: [1, 91], 46: [1, 92] }),
+          { 50: [1, 93] },
+          { 54: [1, 94] },
+          { 54: [1, 95] },
+          { 71: [1, 96], 73: [1, 97] },
+          { 28: 98, 88: T, 89: C, 90: E },
+          { 54: F, 56: 99 },
+          e(A, [2, 54]),
+          e(A, [2, 98]),
+          e(R, [2, 22]),
+          e(R, [2, 23]),
+          e(R, [2, 24]),
+          { 16: [1, 100] },
+          { 25: [2, 19] },
+          e(U, [2, 49]),
+          { 27: 101, 28: 46, 29: 47, 88: T, 89: C, 90: E, 91: S },
+          { 27: 102, 28: 46, 29: 47, 54: [1, 103], 88: T, 89: C, 90: E, 91: S },
+          e(Y, [2, 57], { 58: 104, 60: D, 61: L, 62: O, 63: N, 64: M }),
+          e(Y, [2, 56]),
+          { 28: 105, 88: T, 89: C, 90: E },
+          { 47: 106, 51: W },
+          { 27: 108, 28: 46, 29: 47, 88: T, 89: C, 90: E, 91: S },
+          e(A, [2, 66], { 54: [1, 109] }),
+          e(A, [2, 68], { 54: [1, 111], 69: [1, 110] }),
+          e(A, [2, 72], { 54: [1, 112], 72: [1, 113] }),
+          e(A, [2, 76], { 54: [1, 115], 69: [1, 114] }),
+          e(A, [2, 80]),
+          e(A, [2, 53]),
+          e(P, [2, 11]),
+          e(U, [2, 51]),
+          e(U, [2, 50]),
+          { 27: 116, 28: 46, 29: 47, 88: T, 89: C, 90: E, 91: S },
+          e(Y, [2, 55]),
+          e(A, [2, 39], { 46: [1, 117] }),
+          { 48: [1, 118] },
+          { 47: 119, 48: [2, 43], 51: W },
+          e(A, [2, 42]),
+          e(A, [2, 67]),
+          e(A, [2, 69]),
+          e(A, [2, 70], { 69: [1, 120] }),
+          e(A, [2, 73]),
+          e(A, [2, 74], { 54: [1, 121] }),
+          e(A, [2, 77]),
+          e(A, [2, 78], { 69: [1, 122] }),
+          e(U, [2, 52]),
+          { 47: 123, 51: W },
+          e(A, [2, 40]),
+          { 48: [2, 44] },
+          e(A, [2, 71]),
+          e(A, [2, 75]),
+          e(A, [2, 79]),
+          { 48: [1, 124] },
+          e(A, [2, 41]),
+        ],
+        defaultActions: {
+          2: [2, 1],
+          3: [2, 2],
+          4: [2, 3],
+          6: [2, 9],
+          13: [2, 12],
+          14: [2, 4],
+          20: [2, 15],
+          54: [2, 14],
+          55: [2, 16],
+          85: [2, 19],
+          119: [2, 44],
+        },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      q = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: {},
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("open_directive"), 19;
+            case 1:
+              return 8;
+            case 2:
+              return 9;
+            case 3:
+              return 10;
+            case 4:
+              return 11;
+            case 5:
+              return this.begin("type_directive"), 20;
+            case 6:
+              return this.popState(), this.begin("arg_directive"), 17;
+            case 7:
+              return this.popState(), this.popState(), 22;
+            case 8:
+              return 21;
+            case 9:
+            case 10:
+            case 19:
+            case 27:
+              break;
+            case 11:
+              return this.begin("acc_title"), 39;
+            case 12:
+              return this.popState(), "acc_title_value";
+            case 13:
+              return this.begin("acc_descr"), 41;
+            case 14:
+              return this.popState(), "acc_descr_value";
+            case 15:
+              this.begin("acc_descr_multiline");
+              break;
+            case 16:
+            case 39:
+            case 42:
+            case 45:
+            case 48:
+            case 51:
+            case 54:
+              this.popState();
+              break;
+            case 17:
+              return "acc_descr_multiline_value";
+            case 18:
+              return 16;
+            case 20:
+            case 21:
+              return 23;
+            case 22:
+              return this.begin("struct"), 46;
+            case 23:
+              return "EDGE_STATE";
+            case 24:
+              return "EOF_IN_STRUCT";
+            case 25:
+              return "OPEN_IN_STRUCT";
+            case 26:
+              return this.popState(), 48;
+            case 28:
+              return "MEMBER";
+            case 29:
+              return 44;
+            case 30:
+              return 74;
+            case 31:
+              return 67;
+            case 32:
+              return 68;
+            case 33:
+              return 70;
+            case 34:
+              return 55;
+            case 35:
+              return 57;
+            case 36:
+              return 49;
+            case 37:
+              return 50;
+            case 38:
+              this.begin("generic");
+              break;
+            case 40:
+              return "GENERICTYPE";
+            case 41:
+              this.begin("string");
+              break;
+            case 43:
+              return "STR";
+            case 44:
+              this.begin("bqstring");
+              break;
+            case 46:
+              return "BQUOTE_STR";
+            case 47:
+              this.begin("href");
+              break;
+            case 49:
+              return 73;
+            case 50:
+              this.begin("callback_name");
+              break;
+            case 52:
+              this.popState(), this.begin("callback_args");
+              break;
+            case 53:
+              return 71;
+            case 55:
+              return 72;
+            case 56:
+            case 57:
+            case 58:
+            case 59:
+              return 69;
+            case 60:
+            case 61:
+              return 61;
+            case 62:
+            case 63:
+              return 63;
+            case 64:
+              return 62;
+            case 65:
+              return 60;
+            case 66:
+              return 64;
+            case 67:
+              return 65;
+            case 68:
+              return 66;
+            case 69:
+              return 32;
+            case 70:
+              return 45;
+            case 71:
+              return 86;
+            case 72:
+              return "DOT";
+            case 73:
+              return "PLUS";
+            case 74:
+              return 83;
+            case 75:
+            case 76:
+              return "EQUALS";
+            case 77:
+              return 90;
+            case 78:
+              return "PUNCTUATION";
+            case 79:
+              return 89;
+            case 80:
+              return 88;
+            case 81:
+              return 85;
+            case 82:
+              return 25;
+          }
+        },
+        rules: [
+          /^(?:%%\{)/,
+          /^(?:.*direction\s+TB[^\n]*)/,
+          /^(?:.*direction\s+BT[^\n]*)/,
+          /^(?:.*direction\s+RL[^\n]*)/,
+          /^(?:.*direction\s+LR[^\n]*)/,
+          /^(?:((?:(?!\}%%)[^:.])*))/,
+          /^(?::)/,
+          /^(?:\}%%)/,
+          /^(?:((?:(?!\}%%).|\n)*))/,
+          /^(?:%%(?!\{)*[^\n]*(\r?\n?)+)/,
+          /^(?:%%[^\n]*(\r?\n)*)/,
+          /^(?:accTitle\s*:\s*)/,
+          /^(?:(?!\n||)*[^\n]*)/,
+          /^(?:accDescr\s*:\s*)/,
+          /^(?:(?!\n||)*[^\n]*)/,
+          /^(?:accDescr\s*\{\s*)/,
+          /^(?:[\}])/,
+          /^(?:[^\}]*)/,
+          /^(?:\s*(\r?\n)+)/,
+          /^(?:\s+)/,
+          /^(?:classDiagram-v2\b)/,
+          /^(?:classDiagram\b)/,
+          /^(?:[{])/,
+          /^(?:\[\*\])/,
+          /^(?:$)/,
+          /^(?:[{])/,
+          /^(?:[}])/,
+          /^(?:[\n])/,
+          /^(?:[^{}\n]*)/,
+          /^(?:class\b)/,
+          /^(?:cssClass\b)/,
+          /^(?:callback\b)/,
+          /^(?:link\b)/,
+          /^(?:click\b)/,
+          /^(?:note for\b)/,
+          /^(?:note\b)/,
+          /^(?:<<)/,
+          /^(?:>>)/,
+          /^(?:[~])/,
+          /^(?:[~])/,
+          /^(?:[^~]*)/,
+          /^(?:["])/,
+          /^(?:["])/,
+          /^(?:[^"]*)/,
+          /^(?:[`])/,
+          /^(?:[`])/,
+          /^(?:[^`]+)/,
+          /^(?:href[\s]+["])/,
+          /^(?:["])/,
+          /^(?:[^"]*)/,
+          /^(?:call[\s]+)/,
+          /^(?:\([\s]*\))/,
+          /^(?:\()/,
+          /^(?:[^(]*)/,
+          /^(?:\))/,
+          /^(?:[^)]*)/,
+          /^(?:_self\b)/,
+          /^(?:_blank\b)/,
+          /^(?:_parent\b)/,
+          /^(?:_top\b)/,
+          /^(?:\s*<\|)/,
+          /^(?:\s*\|>)/,
+          /^(?:\s*>)/,
+          /^(?:\s*<)/,
+          /^(?:\s*\*)/,
+          /^(?:\s*o\b)/,
+          /^(?:\s*\(\))/,
+          /^(?:--)/,
+          /^(?:\.\.)/,
+          /^(?::{1}[^:\n;]+)/,
+          /^(?::{3})/,
+          /^(?:-)/,
+          /^(?:\.)/,
+          /^(?:\+)/,
+          /^(?:%)/,
+          /^(?:=)/,
+          /^(?:=)/,
+          /^(?:\w+)/,
+          /^(?:[!"#$%&'*+,-.`?\\/])/,
+          /^(?:[0-9]+)/,
+          /^(?:[\u00AA\u00B5\u00BA\u00C0-\u00D6\u00D8-\u00F6]|[\u00F8-\u02C1\u02C6-\u02D1\u02E0-\u02E4\u02EC\u02EE\u0370-\u0374\u0376\u0377]|[\u037A-\u037D\u0386\u0388-\u038A\u038C\u038E-\u03A1\u03A3-\u03F5]|[\u03F7-\u0481\u048A-\u0527\u0531-\u0556\u0559\u0561-\u0587\u05D0-\u05EA]|[\u05F0-\u05F2\u0620-\u064A\u066E\u066F\u0671-\u06D3\u06D5\u06E5\u06E6\u06EE]|[\u06EF\u06FA-\u06FC\u06FF\u0710\u0712-\u072F\u074D-\u07A5\u07B1\u07CA-\u07EA]|[\u07F4\u07F5\u07FA\u0800-\u0815\u081A\u0824\u0828\u0840-\u0858\u08A0]|[\u08A2-\u08AC\u0904-\u0939\u093D\u0950\u0958-\u0961\u0971-\u0977]|[\u0979-\u097F\u0985-\u098C\u098F\u0990\u0993-\u09A8\u09AA-\u09B0\u09B2]|[\u09B6-\u09B9\u09BD\u09CE\u09DC\u09DD\u09DF-\u09E1\u09F0\u09F1\u0A05-\u0A0A]|[\u0A0F\u0A10\u0A13-\u0A28\u0A2A-\u0A30\u0A32\u0A33\u0A35\u0A36\u0A38\u0A39]|[\u0A59-\u0A5C\u0A5E\u0A72-\u0A74\u0A85-\u0A8D\u0A8F-\u0A91\u0A93-\u0AA8]|[\u0AAA-\u0AB0\u0AB2\u0AB3\u0AB5-\u0AB9\u0ABD\u0AD0\u0AE0\u0AE1\u0B05-\u0B0C]|[\u0B0F\u0B10\u0B13-\u0B28\u0B2A-\u0B30\u0B32\u0B33\u0B35-\u0B39\u0B3D\u0B5C]|[\u0B5D\u0B5F-\u0B61\u0B71\u0B83\u0B85-\u0B8A\u0B8E-\u0B90\u0B92-\u0B95\u0B99]|[\u0B9A\u0B9C\u0B9E\u0B9F\u0BA3\u0BA4\u0BA8-\u0BAA\u0BAE-\u0BB9\u0BD0]|[\u0C05-\u0C0C\u0C0E-\u0C10\u0C12-\u0C28\u0C2A-\u0C33\u0C35-\u0C39\u0C3D]|[\u0C58\u0C59\u0C60\u0C61\u0C85-\u0C8C\u0C8E-\u0C90\u0C92-\u0CA8\u0CAA-\u0CB3]|[\u0CB5-\u0CB9\u0CBD\u0CDE\u0CE0\u0CE1\u0CF1\u0CF2\u0D05-\u0D0C\u0D0E-\u0D10]|[\u0D12-\u0D3A\u0D3D\u0D4E\u0D60\u0D61\u0D7A-\u0D7F\u0D85-\u0D96\u0D9A-\u0DB1]|[\u0DB3-\u0DBB\u0DBD\u0DC0-\u0DC6\u0E01-\u0E30\u0E32\u0E33\u0E40-\u0E46\u0E81]|[\u0E82\u0E84\u0E87\u0E88\u0E8A\u0E8D\u0E94-\u0E97\u0E99-\u0E9F\u0EA1-\u0EA3]|[\u0EA5\u0EA7\u0EAA\u0EAB\u0EAD-\u0EB0\u0EB2\u0EB3\u0EBD\u0EC0-\u0EC4\u0EC6]|[\u0EDC-\u0EDF\u0F00\u0F40-\u0F47\u0F49-\u0F6C\u0F88-\u0F8C\u1000-\u102A]|[\u103F\u1050-\u1055\u105A-\u105D\u1061\u1065\u1066\u106E-\u1070\u1075-\u1081]|[\u108E\u10A0-\u10C5\u10C7\u10CD\u10D0-\u10FA\u10FC-\u1248\u124A-\u124D]|[\u1250-\u1256\u1258\u125A-\u125D\u1260-\u1288\u128A-\u128D\u1290-\u12B0]|[\u12B2-\u12B5\u12B8-\u12BE\u12C0\u12C2-\u12C5\u12C8-\u12D6\u12D8-\u1310]|[\u1312-\u1315\u1318-\u135A\u1380-\u138F\u13A0-\u13F4\u1401-\u166C]|[\u166F-\u167F\u1681-\u169A\u16A0-\u16EA\u1700-\u170C\u170E-\u1711]|[\u1720-\u1731\u1740-\u1751\u1760-\u176C\u176E-\u1770\u1780-\u17B3\u17D7]|[\u17DC\u1820-\u1877\u1880-\u18A8\u18AA\u18B0-\u18F5\u1900-\u191C]|[\u1950-\u196D\u1970-\u1974\u1980-\u19AB\u19C1-\u19C7\u1A00-\u1A16]|[\u1A20-\u1A54\u1AA7\u1B05-\u1B33\u1B45-\u1B4B\u1B83-\u1BA0\u1BAE\u1BAF]|[\u1BBA-\u1BE5\u1C00-\u1C23\u1C4D-\u1C4F\u1C5A-\u1C7D\u1CE9-\u1CEC]|[\u1CEE-\u1CF1\u1CF5\u1CF6\u1D00-\u1DBF\u1E00-\u1F15\u1F18-\u1F1D]|[\u1F20-\u1F45\u1F48-\u1F4D\u1F50-\u1F57\u1F59\u1F5B\u1F5D\u1F5F-\u1F7D]|[\u1F80-\u1FB4\u1FB6-\u1FBC\u1FBE\u1FC2-\u1FC4\u1FC6-\u1FCC\u1FD0-\u1FD3]|[\u1FD6-\u1FDB\u1FE0-\u1FEC\u1FF2-\u1FF4\u1FF6-\u1FFC\u2071\u207F]|[\u2090-\u209C\u2102\u2107\u210A-\u2113\u2115\u2119-\u211D\u2124\u2126\u2128]|[\u212A-\u212D\u212F-\u2139\u213C-\u213F\u2145-\u2149\u214E\u2183\u2184]|[\u2C00-\u2C2E\u2C30-\u2C5E\u2C60-\u2CE4\u2CEB-\u2CEE\u2CF2\u2CF3]|[\u2D00-\u2D25\u2D27\u2D2D\u2D30-\u2D67\u2D6F\u2D80-\u2D96\u2DA0-\u2DA6]|[\u2DA8-\u2DAE\u2DB0-\u2DB6\u2DB8-\u2DBE\u2DC0-\u2DC6\u2DC8-\u2DCE]|[\u2DD0-\u2DD6\u2DD8-\u2DDE\u2E2F\u3005\u3006\u3031-\u3035\u303B\u303C]|[\u3041-\u3096\u309D-\u309F\u30A1-\u30FA\u30FC-\u30FF\u3105-\u312D]|[\u3131-\u318E\u31A0-\u31BA\u31F0-\u31FF\u3400-\u4DB5\u4E00-\u9FCC]|[\uA000-\uA48C\uA4D0-\uA4FD\uA500-\uA60C\uA610-\uA61F\uA62A\uA62B]|[\uA640-\uA66E\uA67F-\uA697\uA6A0-\uA6E5\uA717-\uA71F\uA722-\uA788]|[\uA78B-\uA78E\uA790-\uA793\uA7A0-\uA7AA\uA7F8-\uA801\uA803-\uA805]|[\uA807-\uA80A\uA80C-\uA822\uA840-\uA873\uA882-\uA8B3\uA8F2-\uA8F7\uA8FB]|[\uA90A-\uA925\uA930-\uA946\uA960-\uA97C\uA984-\uA9B2\uA9CF\uAA00-\uAA28]|[\uAA40-\uAA42\uAA44-\uAA4B\uAA60-\uAA76\uAA7A\uAA80-\uAAAF\uAAB1\uAAB5]|[\uAAB6\uAAB9-\uAABD\uAAC0\uAAC2\uAADB-\uAADD\uAAE0-\uAAEA\uAAF2-\uAAF4]|[\uAB01-\uAB06\uAB09-\uAB0E\uAB11-\uAB16\uAB20-\uAB26\uAB28-\uAB2E]|[\uABC0-\uABE2\uAC00-\uD7A3\uD7B0-\uD7C6\uD7CB-\uD7FB\uF900-\uFA6D]|[\uFA70-\uFAD9\uFB00-\uFB06\uFB13-\uFB17\uFB1D\uFB1F-\uFB28\uFB2A-\uFB36]|[\uFB38-\uFB3C\uFB3E\uFB40\uFB41\uFB43\uFB44\uFB46-\uFBB1\uFBD3-\uFD3D]|[\uFD50-\uFD8F\uFD92-\uFDC7\uFDF0-\uFDFB\uFE70-\uFE74\uFE76-\uFEFC]|[\uFF21-\uFF3A\uFF41-\uFF5A\uFF66-\uFFBE\uFFC2-\uFFC7\uFFCA-\uFFCF]|[\uFFD2-\uFFD7\uFFDA-\uFFDC])/,
+          /^(?:\s)/,
+          /^(?:$)/,
+        ],
+        conditions: {
+          acc_descr_multiline: { rules: [16, 17], inclusive: !1 },
+          acc_descr: { rules: [14], inclusive: !1 },
+          acc_title: { rules: [12], inclusive: !1 },
+          arg_directive: { rules: [7, 8], inclusive: !1 },
+          type_directive: { rules: [6, 7], inclusive: !1 },
+          open_directive: { rules: [5], inclusive: !1 },
+          callback_args: { rules: [54, 55], inclusive: !1 },
+          callback_name: { rules: [51, 52, 53], inclusive: !1 },
+          href: { rules: [48, 49], inclusive: !1 },
+          struct: { rules: [23, 24, 25, 26, 27, 28], inclusive: !1 },
+          generic: { rules: [39, 40], inclusive: !1 },
+          bqstring: { rules: [45, 46], inclusive: !1 },
+          string: { rules: [42, 43], inclusive: !1 },
+          INITIAL: {
+            rules: [
+              0,
+              1,
+              2,
+              3,
+              4,
+              9,
+              10,
+              11,
+              13,
+              15,
+              18,
+              19,
+              20,
+              21,
+              22,
+              23,
+              29,
+              30,
+              31,
+              32,
+              33,
+              34,
+              35,
+              36,
+              37,
+              38,
+              41,
+              44,
+              47,
+              50,
+              56,
+              57,
+              58,
+              59,
+              60,
+              61,
+              62,
+              63,
+              64,
+              65,
+              66,
+              67,
+              68,
+              69,
+              70,
+              71,
+              72,
+              73,
+              74,
+              75,
+              76,
+              77,
+              78,
+              79,
+              80,
+              81,
+              82,
+            ],
+            inclusive: !0,
+          },
+        },
+      },
+        t);
+    function V() {
+      this.yy = {};
+    }
+    return H.lexer = q, V.prototype = H, H.Parser = V, new V();
+  }();
+  sw.parser = sw;
+  const ow = sw,
+    lw = (t, e) => {
+      var n;
+      return "dagre-wrapper" !== (null == (n = null == e ? void 0 : e.class) ? void 0 : n.defaultRenderer)
+        && null !== t.match(/^\s*classDiagram/);
+    },
+    cw = (t, e) => {
+      var n;
+      return null !== t.match(/^\s*classDiagram/)
+          && "dagre-wrapper" === (null == (n = null == e ? void 0 : e.class) ? void 0 : n.defaultRenderer)
+        || null !== t.match(/^\s*classDiagram-v2/);
+    },
+    hw = "classid-";
+  let uw = [], dw = {}, pw = [], fw = 0, gw = [];
+  const yw = t => ub.sanitizeText(t, jx()),
+    mw = function(t) {
+      let e = "", n = t;
+      if (t.indexOf("~") > 0) {
+        let i = t.split("~");
+        n = i[0], e = ub.sanitizeText(i[1], jx());
+      }
+      return { className: n, type: e };
+    },
+    bw = function(t) {
+      let e = mw(t);
+      void 0 === dw[e.className]
+        && (dw[e.className] = {
+          id: e.className,
+          type: e.type,
+          cssClasses: [],
+          methods: [],
+          members: [],
+          annotations: [],
+          domId: hw + e.className + "-" + fw,
+        },
+          fw++);
+    },
+    _w = function(t) {
+      const e = Object.keys(dw);
+      for (const n of e) if (dw[n].id === t) return dw[n].domId;
+    },
+    xw = function(t, e) {
+      const n = mw(t).className, i = dw[n];
+      if ("string" == typeof e) {
+        const t = e.trim();
+        t.startsWith("<<") && t.endsWith(">>")
+          ? i.annotations.push(yw(t.substring(2, t.length - 2)))
+          : t.indexOf(")") > 0
+          ? i.methods.push(yw(t))
+          : t && i.members.push(yw(t));
+      }
+    },
+    vw = function(t, e) {
+      t.split(",").forEach(function(t) {
+        let n = t;
+        t[0].match(/\d/) && (n = hw + n), void 0 !== dw[n] && dw[n].cssClasses.push(e);
+      });
+    },
+    kw = function(t, e, n) {
+      const i = jx();
+      let r = t, a = _w(r);
+      if ("loose" === i.securityLevel && void 0 !== e && void 0 !== dw[r]) {
+        let t = [];
+        if ("string" == typeof n) {
+          t = n.split(/,(?=(?:(?:[^"]*"){2})*[^"]*$)/);
+          for (let e = 0; e < t.length; e++) {
+            let n = t[e].trim();
+            "\"" === n.charAt(0) && "\"" === n.charAt(n.length - 1) && (n = n.substr(1, n.length - 2)), t[e] = n;
+          }
+        }
+        0 === t.length && t.push(a),
+          gw.push(function() {
+            const n = document.querySelector(`[id="${a}"]`);
+            null !== n && n.addEventListener("click", function() {
+              Dx.runFunc(e, ...t);
+            }, !1);
+          });
+      }
+    },
+    ww = function(t) {
+      let e = ie(".mermaidTooltip");
+      null === (e._groups || e)[0][0]
+        && (e = ie("body").append("div").attr("class", "mermaidTooltip").style("opacity", 0));
+      ie(t).select("svg").selectAll("g.node").on("mouseover", function() {
+        const t = ie(this);
+        if (null === t.attr("title")) return;
+        const n = this.getBoundingClientRect();
+        e.transition().duration(200).style("opacity", ".9"),
+          e.text(t.attr("title")).style("left", window.scrollX + n.left + (n.right - n.left) / 2 + "px").style(
+            "top",
+            window.scrollY + n.top - 14 + document.body.scrollTop + "px",
+          ),
+          e.html(e.html().replace(/&lt;br\/&gt;/g, "<br/>")),
+          t.classed("hover", !0);
+      }).on("mouseout", function() {
+        e.transition().duration(500).style("opacity", 0);
+        ie(this).classed("hover", !1);
+      });
+    };
+  gw.push(ww);
+  let Tw = "TB";
+  const Cw = {
+    parseDirective: function(t, e, n) {
+      nL.parseDirective(this, t, e, n);
+    },
+    setAccTitle: Ev,
+    getAccTitle: Sv,
+    getAccDescription: Dv,
+    setAccDescription: Av,
+    getConfig: () => jx().class,
+    addClass: bw,
+    bindFunctions: function(t) {
+      gw.forEach(function(e) {
+        e(t);
+      });
+    },
+    clear: function() {
+      uw = [], dw = {}, pw = [], gw = [], gw.push(ww), Cv();
+    },
+    getClass: function(t) {
+      return dw[t];
+    },
+    getClasses: function() {
+      return dw;
+    },
+    getNotes: function() {
+      return pw;
+    },
+    addAnnotation: function(t, e) {
+      const n = mw(t).className;
+      dw[n].annotations.push(e);
+    },
+    addNote: function(t, e) {
+      const n = { id: `note${pw.length}`, class: e, text: t };
+      pw.push(n);
+    },
+    getRelations: function() {
+      return uw;
+    },
+    addRelation: function(t) {
+      tb.debug("Adding relation: " + JSON.stringify(t)),
+        bw(t.id1),
+        bw(t.id2),
+        t.id1 = mw(t.id1).className,
+        t.id2 = mw(t.id2).className,
+        t.relationTitle1 = ub.sanitizeText(t.relationTitle1.trim(), jx()),
+        t.relationTitle2 = ub.sanitizeText(t.relationTitle2.trim(), jx()),
+        uw.push(t);
+    },
+    getDirection: () => Tw,
+    setDirection: t => {
+      Tw = t;
+    },
+    addMember: xw,
+    addMembers: function(t, e) {
+      Array.isArray(e) && (e.reverse(), e.forEach(e => xw(t, e)));
+    },
+    cleanupLabel: function(t) {
+      return ":" === t.substring(0, 1) ? ub.sanitizeText(t.substr(1).trim(), jx()) : yw(t.trim());
+    },
+    lineType: { LINE: 0, DOTTED_LINE: 1 },
+    relationType: { AGGREGATION: 0, EXTENSION: 1, COMPOSITION: 2, DEPENDENCY: 3, LOLLIPOP: 4 },
+    setClickEvent: function(t, e, n) {
+      t.split(",").forEach(function(t) {
+        kw(t, e, n), dw[t].haveCallback = !0;
+      }), vw(t, "clickable");
+    },
+    setCssClass: vw,
+    setLink: function(t, e, n) {
+      const i = jx();
+      t.split(",").forEach(function(t) {
+        let r = t;
+        t[0].match(/\d/) && (r = hw + r),
+          void 0 !== dw[r]
+          && (dw[r].link = Dx.formatUrl(e, i),
+            "sandbox" === i.securityLevel
+              ? dw[r].linkTarget = "_top"
+              : dw[r].linkTarget = "string" == typeof n ? yw(n) : "_blank");
+      }), vw(t, "clickable");
+    },
+    getTooltip: function(t) {
+      return dw[t].tooltip;
+    },
+    setTooltip: function(t, e) {
+      const n = jx();
+      t.split(",").forEach(function(t) {
+        void 0 !== e && (dw[t].tooltip = ub.sanitizeText(e, n));
+      });
+    },
+    lookUpDomId: _w,
+    setDiagramTitle: Lv,
+    getDiagramTitle: Ov,
+  };
+  let Ew = 0;
+  const Sw = function(t) {
+      let e = t.match(/^([#+~-])?(\w+)(~\w+~|\[])?\s+(\w+) *([$*])?$/),
+        n = t.match(/^([#+|~-])?(\w+) *\( *(.*)\) *([$*])? *(\w*[[\]|~]*\s*\w*~?)$/);
+      return e && !n ? Aw(e) : n ? Dw(n) : Lw(t);
+    },
+    Aw = function(t) {
+      let e = "", n = "";
+      try {
+        let i = t[1] ? t[1].trim() : "",
+          r = t[2] ? t[2].trim() : "",
+          a = t[3] ? hb(t[3].trim()) : "",
+          s = t[4] ? t[4].trim() : "",
+          o = t[5] ? t[5].trim() : "";
+        n = i + r + a + " " + s, e = Nw(o);
+      } catch (e) {
+        n = t;
+      }
+      return { displayText: n, cssStyle: e };
+    },
+    Dw = function(t) {
+      let e = "", n = "";
+      try {
+        let i = t[1] ? t[1].trim() : "",
+          r = t[2] ? t[2].trim() : "",
+          a = t[3] ? hb(t[3].trim()) : "",
+          s = t[4] ? t[4].trim() : "";
+        n = i + r + "(" + a + ")" + (t[5] ? " : " + hb(t[5]).trim() : ""), e = Nw(s);
+      } catch (e) {
+        n = t;
+      }
+      return { displayText: n, cssStyle: e };
+    },
+    Lw = function(t) {
+      let e = "", n = "", i = "", r = t.indexOf("("), a = t.indexOf(")");
+      if (r > 1 && a > r && a <= t.length) {
+        let s = "", o = "", l = t.substring(0, 1);
+        l.match(/\w/) ? o = t.substring(0, r).trim() : (l.match(/[#+~-]/) && (s = l), o = t.substring(1, r).trim());
+        const c = t.substring(r + 1, a);
+        t.substring(a + 1, 1),
+          n = Nw(t.substring(a + 1, a + 2)),
+          e = s + o + "(" + hb(c.trim()) + ")",
+          a < t.length && (i = t.substring(a + 2).trim(), "" !== i && (i = " : " + hb(i), e += i));
+      } else e = hb(t);
+      return { displayText: e, cssStyle: n };
+    },
+    Ow = function(t, e, n, i) {
+      let r = Sw(e);
+      const a = t.append("tspan").attr("x", i.padding).text(r.displayText);
+      "" !== r.cssStyle && a.attr("style", r.cssStyle), n || a.attr("dy", i.textHeight);
+    },
+    Nw = function(t) {
+      switch (t) {
+        case "*":
+          return "font-style:italic;";
+        case "$":
+          return "text-decoration:underline;";
+        default:
+          return "";
+      }
+    },
+    Mw = function(t, e, n, i) {
+      tb.debug("Rendering class ", e, n);
+      const r = e.id,
+        a = { id: r, label: e.id, width: 0, height: 0 },
+        s = t.append("g").attr("id", i.db.lookUpDomId(r)).attr("class", "classGroup");
+      let o;
+      o = e.link
+        ? s.append("svg:a").attr("xlink:href", e.link).attr("target", e.linkTarget).append("text").attr(
+          "y",
+          n.textHeight + n.padding,
+        ).attr("x", 0)
+        : s.append("text").attr("y", n.textHeight + n.padding).attr("x", 0);
+      let l = !0;
+      e.annotations.forEach(function(t) {
+        const e = o.append("tspan").text("«" + t + "»");
+        l || e.attr("dy", n.textHeight), l = !1;
+      });
+      let c = e.id;
+      void 0 !== e.type && "" !== e.type && (c += "<" + e.type + ">");
+      const h = o.append("tspan").text(c).attr("class", "title");
+      l || h.attr("dy", n.textHeight);
+      const u = o.node().getBBox().height,
+        d = s.append("line").attr("x1", 0).attr("y1", n.padding + u + n.dividerMargin / 2).attr(
+          "y2",
+          n.padding + u + n.dividerMargin / 2,
+        ),
+        p = s.append("text").attr("x", n.padding).attr("y", u + n.dividerMargin + n.textHeight).attr("fill", "white")
+          .attr("class", "classText");
+      l = !0,
+        e.members.forEach(function(t) {
+          Ow(p, t, l, n), l = !1;
+        });
+      const f = p.node().getBBox(),
+        g = s.append("line").attr("x1", 0).attr("y1", n.padding + u + n.dividerMargin + f.height).attr(
+          "y2",
+          n.padding + u + n.dividerMargin + f.height,
+        ),
+        y = s.append("text").attr("x", n.padding).attr("y", u + 2 * n.dividerMargin + f.height + n.textHeight).attr(
+          "fill",
+          "white",
+        ).attr("class", "classText");
+      l = !0,
+        e.methods.forEach(function(t) {
+          Ow(y, t, l, n), l = !1;
+        });
+      const m = s.node().getBBox();
+      var b = " ";
+      e.cssClasses.length > 0 && (b += e.cssClasses.join(" "));
+      const _ = s.insert("rect", ":first-child").attr("x", 0).attr("y", 0).attr("width", m.width + 2 * n.padding).attr(
+        "height",
+        m.height + n.padding + .5 * n.dividerMargin,
+      ).attr("class", b).node().getBBox().width;
+      return o.node().childNodes.forEach(function(t) {
+        t.setAttribute("x", (_ - t.getBBox().width) / 2);
+      }),
+        e.tooltip && o.insert("title").text(e.tooltip),
+        d.attr("x2", _),
+        g.attr("x2", _),
+        a.width = _,
+        a.height = m.height + n.padding + .5 * n.dividerMargin,
+        a;
+    },
+    Bw = function(t, e, n, i, r) {
+      const a = function(t) {
+        switch (t) {
+          case r.db.relationType.AGGREGATION:
+            return "aggregation";
+          case r.db.relationType.EXTENSION:
+            return "extension";
+          case r.db.relationType.COMPOSITION:
+            return "composition";
+          case r.db.relationType.DEPENDENCY:
+            return "dependency";
+          case r.db.relationType.LOLLIPOP:
+            return "lollipop";
+        }
+      };
+      e.points = e.points.filter(t => !Number.isNaN(t.y));
+      const s = e.points,
+        o = Js().x(function(t) {
+          return t.x;
+        }).y(function(t) {
+          return t.y;
+        }).curve(ao),
+        l = t.append("path").attr("d", o(s)).attr("id", "edge" + Ew).attr("class", "relation");
+      let c, h, u = "";
+      i.arrowMarkerAbsolute
+      && (u = window.location.protocol + "//" + window.location.host + window.location.pathname
+        + window.location.search,
+        u = u.replace(/\(/g, "\\("),
+        u = u.replace(/\)/g, "\\)")),
+        1 == n.relation.lineType && l.attr("class", "relation dashed-line"),
+        10 == n.relation.lineType && l.attr("class", "relation dotted-line"),
+        "none" !== n.relation.type1 && l.attr("marker-start", "url(" + u + "#" + a(n.relation.type1) + "Start)"),
+        "none" !== n.relation.type2 && l.attr("marker-end", "url(" + u + "#" + a(n.relation.type2) + "End)");
+      const d = e.points.length;
+      let p, f, g, y, m = Dx.calcLabelPosition(e.points);
+      if (c = m.x, h = m.y, d % 2 != 0 && d > 1) {
+        let t = Dx.calcCardinalityPosition("none" !== n.relation.type1, e.points, e.points[0]),
+          i = Dx.calcCardinalityPosition("none" !== n.relation.type2, e.points, e.points[d - 1]);
+        tb.debug("cardinality_1_point " + JSON.stringify(t)),
+          tb.debug("cardinality_2_point " + JSON.stringify(i)),
+          p = t.x,
+          f = t.y,
+          g = i.x,
+          y = i.y;
+      }
+      if (void 0 !== n.title) {
+        const e = t.append("g").attr("class", "classLabel"),
+          r = e.append("text").attr("class", "label").attr("x", c).attr("y", h).attr("fill", "red").attr(
+            "text-anchor",
+            "middle",
+          ).text(n.title);
+        window.label = r;
+        const a = r.node().getBBox();
+        e.insert("rect", ":first-child").attr("class", "box").attr("x", a.x - i.padding / 2).attr(
+          "y",
+          a.y - i.padding / 2,
+        ).attr("width", a.width + i.padding).attr("height", a.height + i.padding);
+      }
+      if (
+        tb.info("Rendering relation " + JSON.stringify(n)), void 0 !== n.relationTitle1 && "none" !== n.relationTitle1
+      ) {
+        t.append("g").attr("class", "cardinality").append("text").attr("class", "type1").attr("x", p).attr("y", f).attr(
+          "fill",
+          "black",
+        ).attr("font-size", "6").text(n.relationTitle1);
+      }
+      if (void 0 !== n.relationTitle2 && "none" !== n.relationTitle2) {
+        t.append("g").attr("class", "cardinality").append("text").attr("class", "type2").attr("x", g).attr("y", y).attr(
+          "fill",
+          "black",
+        ).attr("font-size", "6").text(n.relationTitle2);
+      }
+      Ew++;
+    },
+    Iw = function(t, e, n, i) {
+      tb.debug("Rendering note ", e, n);
+      const r = e.id,
+        a = { id: r, text: e.text, width: 0, height: 0 },
+        s = t.append("g").attr("id", r).attr("class", "classGroup");
+      let o = s.append("text").attr("y", n.textHeight + n.padding).attr("x", 0);
+      const l = JSON.parse(`"${e.text}"`).split("\n");
+      l.forEach(function(t) {
+        tb.debug(`Adding line: ${t}`), o.append("tspan").text(t).attr("class", "title").attr("dy", n.textHeight);
+      });
+      const c = s.node().getBBox(),
+        h = s.insert("rect", ":first-child").attr("x", 0).attr("y", 0).attr("width", c.width + 2 * n.padding).attr(
+          "height",
+          c.height + l.length * n.textHeight + n.padding + .5 * n.dividerMargin,
+        ).node().getBBox().width;
+      return o.node().childNodes.forEach(function(t) {
+        t.setAttribute("x", (h - t.getBBox().width) / 2);
+      }),
+        a.width = h,
+        a.height = c.height + l.length * n.textHeight + n.padding + .5 * n.dividerMargin,
+        a;
+    };
+  let Fw = {};
+  const Rw = function(t) {
+      const e = Object.entries(Fw).find(e => e[1].label === t);
+      if (e) return e[0];
+    },
+    $w = {
+      draw: function(t, e, n, i) {
+        const r = jx().class;
+        Fw = {}, tb.info("Rendering diagram " + t);
+        const a = jx().securityLevel;
+        let s;
+        "sandbox" === a && (s = ie("#i" + e));
+        const o = ie("sandbox" === a ? s.nodes()[0].contentDocument.body : "body"), l = o.select(`[id='${e}']`);
+        var c;
+        (c = l).append("defs").append("marker").attr("id", "extensionStart").attr("class", "extension").attr("refX", 0)
+          .attr("refY", 7).attr("markerWidth", 190).attr("markerHeight", 240).attr("orient", "auto").append("path")
+          .attr("d", "M 1,7 L18,13 V 1 Z"),
+          c.append("defs").append("marker").attr("id", "extensionEnd").attr("refX", 19).attr("refY", 7).attr(
+            "markerWidth",
+            20,
+          ).attr("markerHeight", 28).attr("orient", "auto").append("path").attr("d", "M 1,1 V 13 L18,7 Z"),
+          c.append("defs").append("marker").attr("id", "compositionStart").attr("class", "extension").attr("refX", 0)
+            .attr("refY", 7).attr("markerWidth", 190).attr("markerHeight", 240).attr("orient", "auto").append("path")
+            .attr("d", "M 18,7 L9,13 L1,7 L9,1 Z"),
+          c.append("defs").append("marker").attr("id", "compositionEnd").attr("refX", 19).attr("refY", 7).attr(
+            "markerWidth",
+            20,
+          ).attr("markerHeight", 28).attr("orient", "auto").append("path").attr("d", "M 18,7 L9,13 L1,7 L9,1 Z"),
+          c.append("defs").append("marker").attr("id", "aggregationStart").attr("class", "extension").attr("refX", 0)
+            .attr("refY", 7).attr("markerWidth", 190).attr("markerHeight", 240).attr("orient", "auto").append("path")
+            .attr("d", "M 18,7 L9,13 L1,7 L9,1 Z"),
+          c.append("defs").append("marker").attr("id", "aggregationEnd").attr("refX", 19).attr("refY", 7).attr(
+            "markerWidth",
+            20,
+          ).attr("markerHeight", 28).attr("orient", "auto").append("path").attr("d", "M 18,7 L9,13 L1,7 L9,1 Z"),
+          c.append("defs").append("marker").attr("id", "dependencyStart").attr("class", "extension").attr("refX", 0)
+            .attr("refY", 7).attr("markerWidth", 190).attr("markerHeight", 240).attr("orient", "auto").append("path")
+            .attr("d", "M 5,7 L9,13 L1,7 L9,1 Z"),
+          c.append("defs").append("marker").attr("id", "dependencyEnd").attr("refX", 19).attr("refY", 7).attr(
+            "markerWidth",
+            20,
+          ).attr("markerHeight", 28).attr("orient", "auto").append("path").attr("d", "M 18,7 L9,13 L14,7 L9,1 Z");
+        const h = new yy({ multigraph: !0 });
+        h.setGraph({ isMultiGraph: !0 }),
+          h.setDefaultEdgeLabel(function() {
+            return {};
+          });
+        const u = i.db.getClasses(), d = Object.keys(u);
+        for (const t of d) {
+          const e = u[t], n = Mw(l, e, r, i);
+          Fw[n.id] = n, h.setNode(n.id, n), tb.info("Org height: " + n.height);
+        }
+        i.db.getRelations().forEach(function(t) {
+          tb.info("tjoho" + Rw(t.id1) + Rw(t.id2) + JSON.stringify(t)),
+            h.setEdge(Rw(t.id1), Rw(t.id2), { relation: t }, t.title || "DEFAULT");
+        });
+        i.db.getNotes().forEach(function(t) {
+          tb.debug(`Adding note: ${JSON.stringify(t)}`);
+          const e = Iw(l, t, r, i);
+          Fw[e.id] = e,
+            h.setNode(e.id, e),
+            t.class && t.class in u
+            && h.setEdge(t.id, Rw(t.class), {
+              relation: { id1: t.id, id2: t.class, relation: { type1: "none", type2: "none", lineType: 10 } },
+            }, "DEFAULT");
+        }),
+          hm(h),
+          h.nodes().forEach(function(t) {
+            void 0 !== t && void 0 !== h.node(t)
+              && (tb.debug("Node " + t + ": " + JSON.stringify(h.node(t))),
+                o.select("#" + (i.db.lookUpDomId(t) || t)).attr(
+                  "transform",
+                  "translate(" + (h.node(t).x - h.node(t).width / 2) + "," + (h.node(t).y - h.node(t).height / 2)
+                    + " )",
+                ));
+          }),
+          h.edges().forEach(function(t) {
+            void 0 !== t && void 0 !== h.edge(t)
+              && (tb.debug("Edge " + t.v + " -> " + t.w + ": " + JSON.stringify(h.edge(t))),
+                Bw(l, h.edge(t), h.edge(t).relation, r, i));
+          });
+        const p = l.node().getBBox(), f = p.width + 40, g = p.height + 40;
+        Gx(l, g, f, r.useMaxWidth);
+        const y = `${p.x - 20} ${p.y - 20} ${f} ${g}`;
+        tb.debug(`viewBox ${y}`), l.attr("viewBox", y);
+      },
+    },
+    Pw = {
+      extension: (t, e, n) => {
+        tb.trace("Making markers for ", n),
+          t.append("defs").append("marker").attr("id", e + "-extensionStart").attr("class", "marker extension " + e)
+            .attr("refX", 0).attr("refY", 7).attr("markerWidth", 190).attr("markerHeight", 240).attr("orient", "auto")
+            .append("path").attr("d", "M 1,7 L18,13 V 1 Z"),
+          t.append("defs").append("marker").attr("id", e + "-extensionEnd").attr("class", "marker extension " + e).attr(
+            "refX",
+            19,
+          ).attr("refY", 7).attr("markerWidth", 20).attr("markerHeight", 28).attr("orient", "auto").append("path").attr(
+            "d",
+            "M 1,1 V 13 L18,7 Z",
+          );
+      },
+      composition: (t, e) => {
+        t.append("defs").append("marker").attr("id", e + "-compositionStart").attr("class", "marker composition " + e)
+          .attr("refX", 0).attr("refY", 7).attr("markerWidth", 190).attr("markerHeight", 240).attr("orient", "auto")
+          .append("path").attr("d", "M 18,7 L9,13 L1,7 L9,1 Z"),
+          t.append("defs").append("marker").attr("id", e + "-compositionEnd").attr("class", "marker composition " + e)
+            .attr("refX", 19).attr("refY", 7).attr("markerWidth", 20).attr("markerHeight", 28).attr("orient", "auto")
+            .append("path").attr("d", "M 18,7 L9,13 L1,7 L9,1 Z");
+      },
+      aggregation: (t, e) => {
+        t.append("defs").append("marker").attr("id", e + "-aggregationStart").attr("class", "marker aggregation " + e)
+          .attr("refX", 0).attr("refY", 7).attr("markerWidth", 190).attr("markerHeight", 240).attr("orient", "auto")
+          .append("path").attr("d", "M 18,7 L9,13 L1,7 L9,1 Z"),
+          t.append("defs").append("marker").attr("id", e + "-aggregationEnd").attr("class", "marker aggregation " + e)
+            .attr("refX", 19).attr("refY", 7).attr("markerWidth", 20).attr("markerHeight", 28).attr("orient", "auto")
+            .append("path").attr("d", "M 18,7 L9,13 L1,7 L9,1 Z");
+      },
+      dependency: (t, e) => {
+        t.append("defs").append("marker").attr("id", e + "-dependencyStart").attr("class", "marker dependency " + e)
+          .attr("refX", 0).attr("refY", 7).attr("markerWidth", 190).attr("markerHeight", 240).attr("orient", "auto")
+          .append("path").attr("d", "M 5,7 L9,13 L1,7 L9,1 Z"),
+          t.append("defs").append("marker").attr("id", e + "-dependencyEnd").attr("class", "marker dependency " + e)
+            .attr("refX", 19).attr("refY", 7).attr("markerWidth", 20).attr("markerHeight", 28).attr("orient", "auto")
+            .append("path").attr("d", "M 18,7 L9,13 L14,7 L9,1 Z");
+      },
+      lollipop: (t, e) => {
+        t.append("defs").append("marker").attr("id", e + "-lollipopStart").attr("class", "marker lollipop " + e).attr(
+          "refX",
+          0,
+        ).attr("refY", 7).attr("markerWidth", 190).attr("markerHeight", 240).attr("orient", "auto").append("circle")
+          .attr("stroke", "black").attr("fill", "white").attr("cx", 6).attr("cy", 7).attr("r", 6);
+      },
+      point: (t, e) => {
+        t.append("marker").attr("id", e + "-pointEnd").attr("class", "marker " + e).attr("viewBox", "0 0 10 10").attr(
+          "refX",
+          10,
+        ).attr("refY", 5).attr("markerUnits", "userSpaceOnUse").attr("markerWidth", 12).attr("markerHeight", 12).attr(
+          "orient",
+          "auto",
+        ).append("path").attr("d", "M 0 0 L 10 5 L 0 10 z").attr("class", "arrowMarkerPath").style("stroke-width", 1)
+          .style("stroke-dasharray", "1,0"),
+          t.append("marker").attr("id", e + "-pointStart").attr("class", "marker " + e).attr("viewBox", "0 0 10 10")
+            .attr("refX", 0).attr("refY", 5).attr("markerUnits", "userSpaceOnUse").attr("markerWidth", 12).attr(
+              "markerHeight",
+              12,
+            ).attr("orient", "auto").append("path").attr("d", "M 0 5 L 10 10 L 10 0 z").attr("class", "arrowMarkerPath")
+            .style("stroke-width", 1).style("stroke-dasharray", "1,0");
+      },
+      circle: (t, e) => {
+        t.append("marker").attr("id", e + "-circleEnd").attr("class", "marker " + e).attr("viewBox", "0 0 10 10").attr(
+          "refX",
+          11,
+        ).attr("refY", 5).attr("markerUnits", "userSpaceOnUse").attr("markerWidth", 11).attr("markerHeight", 11).attr(
+          "orient",
+          "auto",
+        ).append("circle").attr("cx", "5").attr("cy", "5").attr("r", "5").attr("class", "arrowMarkerPath").style(
+          "stroke-width",
+          1,
+        ).style("stroke-dasharray", "1,0"),
+          t.append("marker").attr("id", e + "-circleStart").attr("class", "marker " + e).attr("viewBox", "0 0 10 10")
+            .attr("refX", -1).attr("refY", 5).attr("markerUnits", "userSpaceOnUse").attr("markerWidth", 11).attr(
+              "markerHeight",
+              11,
+            ).attr("orient", "auto").append("circle").attr("cx", "5").attr("cy", "5").attr("r", "5").attr(
+              "class",
+              "arrowMarkerPath",
+            ).style("stroke-width", 1).style("stroke-dasharray", "1,0");
+      },
+      cross: (t, e) => {
+        t.append("marker").attr("id", e + "-crossEnd").attr("class", "marker cross " + e).attr("viewBox", "0 0 11 11")
+          .attr("refX", 12).attr("refY", 5.2).attr("markerUnits", "userSpaceOnUse").attr("markerWidth", 11).attr(
+            "markerHeight",
+            11,
+          ).attr("orient", "auto").append("path").attr("d", "M 1,1 l 9,9 M 10,1 l -9,9").attr(
+            "class",
+            "arrowMarkerPath",
+          ).style("stroke-width", 2).style("stroke-dasharray", "1,0"),
+          t.append("marker").attr("id", e + "-crossStart").attr("class", "marker cross " + e).attr(
+            "viewBox",
+            "0 0 11 11",
+          ).attr("refX", -1).attr("refY", 5.2).attr("markerUnits", "userSpaceOnUse").attr("markerWidth", 11).attr(
+            "markerHeight",
+            11,
+          ).attr("orient", "auto").append("path").attr("d", "M 1,1 l 9,9 M 10,1 l -9,9").attr(
+            "class",
+            "arrowMarkerPath",
+          ).style("stroke-width", 2).style("stroke-dasharray", "1,0");
+      },
+      barb: (t, e) => {
+        t.append("defs").append("marker").attr("id", e + "-barbEnd").attr("refX", 19).attr("refY", 7).attr(
+          "markerWidth",
+          20,
+        ).attr("markerHeight", 14).attr("markerUnits", "strokeWidth").attr("orient", "auto").append("path").attr(
+          "d",
+          "M 19,7 L9,13 L14,7 L9,1 Z",
+        );
+      },
+    },
+    Yw = (t, e, n, i) => {
+      e.forEach(e => {
+        Pw[e](t, n, i);
+      });
+    };
+  const jw = (t, e, n, i) => {
+      let r = t || "";
+      if ("object" == typeof r && (r = r[0]), cb(jx().flowchart.htmlLabels)) {
+        r = r.replace(/\\n|\n/g, "<br />"), tb.info("vertexText" + r);
+        let t = function(t) {
+          const e = ie(document.createElementNS("http://www.w3.org/2000/svg", "foreignObject")),
+            n = e.append("xhtml:div"),
+            i = t.label,
+            r = t.isNode ? "nodeLabel" : "edgeLabel";
+          var a, s;
+          return n.html(
+            "<span class=\"" + r + "\" " + (t.labelStyle ? "style=\"" + t.labelStyle + "\"" : "") + ">" + i + "</span>",
+          ),
+            a = n,
+            (s = t.labelStyle) && a.attr("style", s),
+            n.style("display", "inline-block"),
+            n.style("white-space", "nowrap"),
+            n.attr("xmlns", "http://www.w3.org/1999/xhtml"),
+            e.node();
+        }({
+          isNode: i,
+          label: HD(r).replace(/fa[blrs]?:fa-[\w-]+/g, t => `<i class='${t.replace(":", " ")}'></i>`),
+          labelStyle: e.replace("fill:", "color:"),
+        });
+        return t;
+      }
+      {
+        const t = document.createElementNS("http://www.w3.org/2000/svg", "text");
+        t.setAttribute("style", e.replace("color:", "fill:"));
+        let i = [];
+        i = "string" == typeof r ? r.split(/\\n|\n|<br\s*\/?>/gi) : Array.isArray(r) ? r : [];
+        for (const e of i) {
+          const i = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
+          i.setAttributeNS("http://www.w3.org/XML/1998/namespace", "xml:space", "preserve"),
+            i.setAttribute("dy", "1em"),
+            i.setAttribute("x", "0"),
+            n ? i.setAttribute("class", "title-row") : i.setAttribute("class", "row"),
+            i.textContent = e.trim(),
+            t.appendChild(i);
+        }
+        return t;
+      }
+    },
+    zw = (t, e, n, i) => {
+      let r;
+      r = n || "node default";
+      const a = t.insert("g").attr("class", r).attr("id", e.domId || e.id),
+        s = a.insert("g").attr("class", "label").attr("style", e.labelStyle);
+      let o;
+      o = void 0 === e.labelText ? "" : "string" == typeof e.labelText ? e.labelText : e.labelText[0];
+      const l = s.node().appendChild(jw(ab(HD(o), jx()), e.labelStyle, !1, i));
+      let c = l.getBBox();
+      if (cb(jx().flowchart.htmlLabels)) {
+        const t = l.children[0], e = ie(l);
+        c = t.getBoundingClientRect(), e.attr("width", c.width), e.attr("height", c.height);
+      }
+      const h = e.padding / 2;
+      return s.attr("transform", "translate(" + -c.width / 2 + ", " + -c.height / 2 + ")"),
+        { shapeSvg: a, bbox: c, halfPadding: h, label: s };
+    },
+    Uw = (t, e) => {
+      const n = e.node().getBBox();
+      t.width = n.width, t.height = n.height;
+    };
+  function Ww(t, e, n, i) {
+    return t.insert("polygon", ":first-child").attr(
+      "points",
+      i.map(function(t) {
+        return t.x + "," + t.y;
+      }).join(" "),
+    ).attr("class", "label-container").attr("transform", "translate(" + -e / 2 + "," + n / 2 + ")");
+  }
+  let Hw = {}, qw = {}, Vw = {};
+  const Gw = (t, e) => (tb.trace("In isDecendant", e, " ", t, " = ", qw[e].includes(t)), !!qw[e].includes(t)),
+    Xw = (t, e, n, i) => {
+      tb.warn("Copying children of ", t, "root", i, "data", e.node(t), i);
+      const r = e.children(t) || [];
+      t !== i && r.push(t),
+        tb.warn("Copying (nodes) clusterId", t, "nodes", r),
+        r.forEach(r => {
+          if (e.children(r).length > 0) Xw(r, e, n, i);
+          else {
+            const a = e.node(r);
+            tb.info("cp ", r, " to ", i, " with parent ", t),
+              n.setNode(r, a),
+              i !== e.parent(r) && (tb.warn("Setting parent", r, e.parent(r)), n.setParent(r, e.parent(r))),
+              t !== i && r !== t
+                ? (tb.debug("Setting parent", r, t), n.setParent(r, t))
+                : (tb.info("In copy ", t, "root", i, "data", e.node(t), i),
+                  tb.debug(
+                    "Not Setting parent for node=",
+                    r,
+                    "cluster!==rootId",
+                    t !== i,
+                    "node!==clusterId",
+                    r !== t,
+                  ));
+            const s = e.edges(r);
+            tb.debug("Copying Edges", s),
+              s.forEach(r => {
+                tb.info("Edge", r);
+                const a = e.edge(r.v, r.w, r.name);
+                tb.info("Edge data", a, i);
+                try {
+                  ((
+                      t,
+                      e,
+                    ) => (tb.info("Decendants of ", e, " is ", qw[e]),
+                      tb.info("Edge is ", t),
+                      t.v !== e && t.w !== e && (qw[e]
+                        ? qw[e].includes(t.v) || Gw(t.v, e) || Gw(t.w, e) || qw[e].includes(t.w)
+                        : (tb.debug("Tilt, ", e, ",not in decendants"), !1))))(r, i)
+                    ? (tb.info("Copying as ", r.v, r.w, a, r.name),
+                      n.setEdge(r.v, r.w, a, r.name),
+                      tb.info("newGraph edges ", n.edges(), n.edge(n.edges()[0])))
+                    : tb.info("Skipping copy of edge ", r.v, "--\x3e", r.w, " rootId: ", i, " clusterId:", t);
+                } catch (t) {
+                  tb.error(t);
+                }
+              });
+          }
+          tb.debug("Removing node", r), e.removeNode(r);
+        });
+    },
+    Zw = (t, e) => {
+      const n = e.children(t);
+      let i = [...n];
+      for (const r of n) Vw[r] = t, i = [...i, ...Zw(r, e)];
+      return i;
+    },
+    Qw = (t, e) => {
+      tb.trace("Searching", t);
+      const n = e.children(t);
+      if (tb.trace("Searching children of id ", t, n), n.length < 1) return tb.trace("This is a valid node", t), t;
+      for (const i of n) {
+        const n = Qw(i, e);
+        if (n) return tb.trace("Found replacement for", t, " => ", n), n;
+      }
+    },
+    Kw = t => Hw[t] && Hw[t].externalConnections && Hw[t] ? Hw[t].id : t,
+    Jw = (t, e) => {
+      if (tb.warn("extractor - ", e, Ym(t), t.children("D")), e > 10) return void tb.error("Bailing out");
+      let n = t.nodes(), i = !1;
+      for (const e of n) {
+        const n = t.children(e);
+        i = i || n.length > 0;
+      }
+      if (i) {
+        tb.debug("Nodes = ", n, e);
+        for (const i of n) {
+          if (
+            tb.debug(
+              "Extracting node",
+              i,
+              Hw,
+              Hw[i] && !Hw[i].externalConnections,
+              !t.parent(i),
+              t.node(i),
+              t.children("D"),
+              " Depth ",
+              e,
+            ), Hw[i]
+          ) {
+            if (!Hw[i].externalConnections && t.children(i) && t.children(i).length > 0) {
+              tb.warn("Cluster without external connections, without a parent and with children", i, e);
+              let n = "TB" === t.graph().rankdir ? "LR" : "TB";
+              Hw[i] && Hw[i].clusterData && Hw[i].clusterData.dir
+                && (n = Hw[i].clusterData.dir, tb.warn("Fixing dir", Hw[i].clusterData.dir, n));
+              const r = new yy({ multigraph: !0, compound: !0 }).setGraph({
+                rankdir: n,
+                nodesep: 50,
+                ranksep: 50,
+                marginx: 8,
+                marginy: 8,
+              }).setDefaultEdgeLabel(function() {
+                return {};
+              });
+              tb.warn("Old graph before copy", Ym(t)),
+                Xw(i, t, r, i),
+                t.setNode(i, {
+                  clusterNode: !0,
+                  id: i,
+                  clusterData: Hw[i].clusterData,
+                  labelText: Hw[i].labelText,
+                  graph: r,
+                }),
+                tb.warn("New graph after copy node: (", i, ")", Ym(r)),
+                tb.debug("Old graph after copy", Ym(t));
+            } else {tb.warn(
+                "Cluster ** ",
+                i,
+                " **not meeting the criteria !externalConnections:",
+                !Hw[i].externalConnections,
+                " no parent: ",
+                !t.parent(i),
+                " children ",
+                t.children(i) && t.children(i).length > 0,
+                t.children("D"),
+                e,
+              ),
+                tb.debug(Hw);}
+          } else tb.debug("Not a cluster", i, e);
+        }
+        n = t.nodes(), tb.warn("New list of nodes", n);
+        for (const i of n) {
+          const n = t.node(i);
+          tb.warn(" Now next level", i, n), n.clusterNode && Jw(n.graph, e + 1);
+        }
+      } else tb.debug("Done, no node has children", t.nodes());
+    },
+    tT = (t, e) => {
+      if (0 === e.length) return [];
+      let n = Object.assign(e);
+      return e.forEach(e => {
+        const i = t.children(e), r = tT(t, i);
+        n = [...n, ...r];
+      }),
+        n;
+    };
+  function eT(t, e, n, i) {
+    var r = t.x,
+      a = t.y,
+      s = r - i.x,
+      o = a - i.y,
+      l = Math.sqrt(e * e * o * o + n * n * s * s),
+      c = Math.abs(e * n * s / l);
+    i.x < r && (c = -c);
+    var h = Math.abs(e * n * o / l);
+    return i.y < a && (h = -h), { x: r + c, y: a + h };
+  }
+  function nT(t, e, n, i) {
+    var r, a, s, o, l, c, h, u, d, p, f, g, y;
+    if (
+      r = e.y - t.y,
+        s = t.x - e.x,
+        l = e.x * t.y - t.x * e.y,
+        d = r * n.x + s * n.y + l,
+        p = r * i.x + s * i.y + l,
+        !(0 !== d && 0 !== p && iT(d, p)
+          || (a = i.y - n.y,
+            o = n.x - i.x,
+            c = i.x * n.y - n.x * i.y,
+            h = a * t.x + o * t.y + c,
+            u = a * e.x + o * e.y + c,
+            0 !== h && 0 !== u && iT(h, u) || 0 == (f = r * o - a * s)))
+    ) {
+      return g = Math.abs(f / 2), {
+        x: (y = s * c - o * l) < 0 ? (y - g) / f : (y + g) / f,
+        y: (y = a * l - r * c) < 0 ? (y - g) / f : (y + g) / f,
+      };
+    }
+  }
+  function iT(t, e) {
+    return t * e > 0;
+  }
+  const rT = (t, e) => {
+      var n, i, r = t.x, a = t.y, s = e.x - r, o = e.y - a, l = t.width / 2, c = t.height / 2;
+      return Math.abs(o) * l > Math.abs(s) * c
+        ? (o < 0 && (c = -c), n = 0 === o ? 0 : c * s / o, i = c)
+        : (s < 0 && (l = -l), n = l, i = 0 === s ? 0 : l * o / s),
+        { x: r + n, y: a + i };
+    },
+    aT = {
+      node: function(t, e) {
+        return t.intersect(e);
+      },
+      circle: function(t, e, n) {
+        return eT(t, e, e, n);
+      },
+      ellipse: eT,
+      polygon: function(t, e, n) {
+        var i = t.x, r = t.y, a = [], s = Number.POSITIVE_INFINITY, o = Number.POSITIVE_INFINITY;
+        "function" == typeof e.forEach
+          ? e.forEach(function(t) {
+            s = Math.min(s, t.x), o = Math.min(o, t.y);
+          })
+          : (s = Math.min(s, e.x), o = Math.min(o, e.y));
+        for (var l = i - t.width / 2 - s, c = r - t.height / 2 - o, h = 0; h < e.length; h++) {
+          var u = e[h],
+            d = e[h < e.length - 1 ? h + 1 : 0],
+            p = nT(t, n, { x: l + u.x, y: c + u.y }, { x: l + d.x, y: c + d.y });
+          p && a.push(p);
+        }
+        return a.length
+          ? (a.length > 1 && a.sort(function(t, e) {
+            var i = t.x - n.x,
+              r = t.y - n.y,
+              a = Math.sqrt(i * i + r * r),
+              s = e.x - n.x,
+              o = e.y - n.y,
+              l = Math.sqrt(s * s + o * o);
+            return a < l ? -1 : a === l ? 0 : 1;
+          }),
+            a[0])
+          : t;
+      },
+      rect: rT,
+    },
+    sT = (t, e) => {
+      const { shapeSvg: n, bbox: i, halfPadding: r } = zw(t, e, "node " + e.classes, !0);
+      tb.info("Classes = ", e.classes);
+      const a = n.insert("rect", ":first-child");
+      return a.attr("rx", e.rx).attr("ry", e.ry).attr("x", -i.width / 2 - r).attr("y", -i.height / 2 - r).attr(
+        "width",
+        i.width + e.padding,
+      ).attr("height", i.height + e.padding),
+        Uw(e, a),
+        e.intersect = function(t) {
+          return aT.rect(e, t);
+        },
+        n;
+    };
+  function oT(t, e, n, i) {
+    const r = [],
+      a = t => {
+        r.push(t, 0);
+      },
+      s = t => {
+        r.push(0, t);
+      };
+    e.includes("t") ? (tb.debug("add top border"), a(n)) : s(n),
+      e.includes("r") ? (tb.debug("add right border"), a(i)) : s(i),
+      e.includes("b") ? (tb.debug("add bottom border"), a(n)) : s(n),
+      e.includes("l") ? (tb.debug("add left border"), a(i)) : s(i),
+      t.attr("stroke-dasharray", r.join(" "));
+  }
+  const lT = (t, e, n) => {
+      const i = t.insert("g").attr("class", "node default").attr("id", e.domId || e.id);
+      let r = 70, a = 10;
+      "LR" === n && (r = 10, a = 70);
+      const s = i.append("rect").attr("x", -1 * r / 2).attr("y", -1 * a / 2).attr("width", r).attr("height", a).attr(
+        "class",
+        "fork-join",
+      );
+      return Uw(e, s),
+        e.height = e.height + e.padding / 2,
+        e.width = e.width + e.padding / 2,
+        e.intersect = function(t) {
+          return aT.rect(e, t);
+        },
+        i;
+    },
+    cT = {
+      question: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.width + e.padding + (i.height + e.padding),
+          a = [{ x: r / 2, y: 0 }, { x: r, y: -r / 2 }, { x: r / 2, y: -r }, { x: 0, y: -r / 2 }];
+        tb.info("Question main (Circle)");
+        const s = Ww(n, r, r, a);
+        return s.attr("style", e.style),
+          Uw(e, s),
+          e.intersect = function(t) {
+            return tb.warn("Intersect called"), aT.polygon(e, a, t);
+          },
+          n;
+      },
+      rect: (t, e) => {
+        const { shapeSvg: n, bbox: i, halfPadding: r } = zw(t, e, "node " + e.classes, !0);
+        tb.trace("Classes = ", e.classes);
+        const a = n.insert("rect", ":first-child"), s = i.width + e.padding, o = i.height + e.padding;
+        if (
+          a.attr("class", "basic label-container").attr("style", e.style).attr("rx", e.rx).attr("ry", e.ry).attr(
+            "x",
+            -i.width / 2 - r,
+          ).attr("y", -i.height / 2 - r).attr("width", s).attr("height", o), e.props
+        ) {
+          const t = new Set(Object.keys(e.props));
+          e.props.borders && (oT(a, e.props.borders, s, o), t.delete("borders")),
+            t.forEach(t => {
+              tb.warn(`Unknown node property ${t}`);
+            });
+        }
+        return Uw(e, a),
+          e.intersect = function(t) {
+            return aT.rect(e, t);
+          },
+          n;
+      },
+      labelRect: (t, e) => {
+        const { shapeSvg: n } = zw(t, e, "label", !0);
+        tb.trace("Classes = ", e.classes);
+        const i = n.insert("rect", ":first-child");
+        if (i.attr("width", 0).attr("height", 0), n.attr("class", "label edgeLabel"), e.props) {
+          const t = new Set(Object.keys(e.props));
+          e.props.borders && (oT(i, e.props.borders, 0, 0), t.delete("borders")),
+            t.forEach(t => {
+              tb.warn(`Unknown node property ${t}`);
+            });
+        }
+        return Uw(e, i),
+          e.intersect = function(t) {
+            return aT.rect(e, t);
+          },
+          n;
+      },
+      rectWithTitle: (t, e) => {
+        let n;
+        n = e.classes ? "node " + e.classes : "node default";
+        const i = t.insert("g").attr("class", n).attr("id", e.domId || e.id),
+          r = i.insert("rect", ":first-child"),
+          a = i.insert("line"),
+          s = i.insert("g").attr("class", "label"),
+          o = e.labelText.flat ? e.labelText.flat() : e.labelText;
+        let l = "";
+        l = "object" == typeof o ? o[0] : o, tb.info("Label text abc79", l, o, "object" == typeof o);
+        const c = s.node().appendChild(jw(l, e.labelStyle, !0, !0));
+        let h = { width: 0, height: 0 };
+        if (cb(jx().flowchart.htmlLabels)) {
+          const t = c.children[0], e = ie(c);
+          h = t.getBoundingClientRect(), e.attr("width", h.width), e.attr("height", h.height);
+        }
+        tb.info("Text 2", o);
+        const u = o.slice(1, o.length);
+        let d = c.getBBox();
+        const p = s.node().appendChild(jw(u.join ? u.join("<br/>") : u, e.labelStyle, !0, !0));
+        if (cb(jx().flowchart.htmlLabels)) {
+          const t = p.children[0], e = ie(p);
+          h = t.getBoundingClientRect(), e.attr("width", h.width), e.attr("height", h.height);
+        }
+        const f = e.padding / 2;
+        return ie(p).attr(
+          "transform",
+          "translate( " + (h.width > d.width ? 0 : (d.width - h.width) / 2) + ", " + (d.height + f + 5) + ")",
+        ),
+          ie(c).attr("transform", "translate( " + (h.width < d.width ? 0 : -(d.width - h.width) / 2) + ", 0)"),
+          h = s.node().getBBox(),
+          s.attr("transform", "translate(" + -h.width / 2 + ", " + (-h.height / 2 - f + 3) + ")"),
+          r.attr("class", "outer title-state").attr("x", -h.width / 2 - f).attr("y", -h.height / 2 - f).attr(
+            "width",
+            h.width + e.padding,
+          ).attr("height", h.height + e.padding),
+          a.attr("class", "divider").attr("x1", -h.width / 2 - f).attr("x2", h.width / 2 + f).attr(
+            "y1",
+            -h.height / 2 - f + d.height + f,
+          ).attr("y2", -h.height / 2 - f + d.height + f),
+          Uw(e, r),
+          e.intersect = function(t) {
+            return aT.rect(e, t);
+          },
+          i;
+      },
+      choice: (t, e) => {
+        const n = t.insert("g").attr("class", "node default").attr("id", e.domId || e.id),
+          i = [{ x: 0, y: 14 }, { x: 14, y: 0 }, { x: 0, y: -14 }, { x: -14, y: 0 }];
+        return n.insert("polygon", ":first-child").attr(
+          "points",
+          i.map(function(t) {
+            return t.x + "," + t.y;
+          }).join(" "),
+        ).attr("class", "state-start").attr("r", 7).attr("width", 28).attr("height", 28),
+          e.width = 28,
+          e.height = 28,
+          e.intersect = function(t) {
+            return aT.circle(e, 14, t);
+          },
+          n;
+      },
+      circle: (t, e) => {
+        const { shapeSvg: n, bbox: i, halfPadding: r } = zw(t, e, void 0, !0), a = n.insert("circle", ":first-child");
+        return a.attr("style", e.style).attr("rx", e.rx).attr("ry", e.ry).attr("r", i.width / 2 + r).attr(
+          "width",
+          i.width + e.padding,
+        ).attr("height", i.height + e.padding),
+          tb.info("Circle main"),
+          Uw(e, a),
+          e.intersect = function(t) {
+            return tb.info("Circle intersect", e, i.width / 2 + r, t), aT.circle(e, i.width / 2 + r, t);
+          },
+          n;
+      },
+      doublecircle: (t, e) => {
+        const { shapeSvg: n, bbox: i, halfPadding: r } = zw(t, e, void 0, !0),
+          a = n.insert("g", ":first-child"),
+          s = a.insert("circle"),
+          o = a.insert("circle");
+        return s.attr("style", e.style).attr("rx", e.rx).attr("ry", e.ry).attr("r", i.width / 2 + r + 5).attr(
+          "width",
+          i.width + e.padding + 10,
+        ).attr("height", i.height + e.padding + 10),
+          o.attr("style", e.style).attr("rx", e.rx).attr("ry", e.ry).attr("r", i.width / 2 + r).attr(
+            "width",
+            i.width + e.padding,
+          ).attr("height", i.height + e.padding),
+          tb.info("DoubleCircle main"),
+          Uw(e, s),
+          e.intersect = function(t) {
+            return tb.info("DoubleCircle intersect", e, i.width / 2 + r + 5, t), aT.circle(e, i.width / 2 + r + 5, t);
+          },
+          n;
+      },
+      stadium: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.height + e.padding,
+          a = i.width + r / 4 + e.padding,
+          s = n.insert("rect", ":first-child").attr("style", e.style).attr("rx", r / 2).attr("ry", r / 2).attr(
+            "x",
+            -a / 2,
+          ).attr("y", -r / 2).attr("width", a).attr("height", r);
+        return Uw(e, s),
+          e.intersect = function(t) {
+            return aT.rect(e, t);
+          },
+          n;
+      },
+      hexagon: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.height + e.padding,
+          a = r / 4,
+          s = i.width + 2 * a + e.padding,
+          o = [{ x: a, y: 0 }, { x: s - a, y: 0 }, { x: s, y: -r / 2 }, { x: s - a, y: -r }, { x: a, y: -r }, {
+            x: 0,
+            y: -r / 2,
+          }],
+          l = Ww(n, s, r, o);
+        return l.attr("style", e.style),
+          Uw(e, l),
+          e.intersect = function(t) {
+            return aT.polygon(e, o, t);
+          },
+          n;
+      },
+      rect_left_inv_arrow: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.width + e.padding,
+          a = i.height + e.padding,
+          s = [{ x: -a / 2, y: 0 }, { x: r, y: 0 }, { x: r, y: -a }, { x: -a / 2, y: -a }, { x: 0, y: -a / 2 }];
+        return Ww(n, r, a, s).attr("style", e.style),
+          e.width = r + a,
+          e.height = a,
+          e.intersect = function(t) {
+            return aT.polygon(e, s, t);
+          },
+          n;
+      },
+      lean_right: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.width + e.padding,
+          a = i.height + e.padding,
+          s = [{ x: -2 * a / 6, y: 0 }, { x: r - a / 6, y: 0 }, { x: r + 2 * a / 6, y: -a }, { x: a / 6, y: -a }],
+          o = Ww(n, r, a, s);
+        return o.attr("style", e.style),
+          Uw(e, o),
+          e.intersect = function(t) {
+            return aT.polygon(e, s, t);
+          },
+          n;
+      },
+      lean_left: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.width + e.padding,
+          a = i.height + e.padding,
+          s = [{ x: 2 * a / 6, y: 0 }, { x: r + a / 6, y: 0 }, { x: r - 2 * a / 6, y: -a }, { x: -a / 6, y: -a }],
+          o = Ww(n, r, a, s);
+        return o.attr("style", e.style),
+          Uw(e, o),
+          e.intersect = function(t) {
+            return aT.polygon(e, s, t);
+          },
+          n;
+      },
+      trapezoid: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.width + e.padding,
+          a = i.height + e.padding,
+          s = [{ x: -2 * a / 6, y: 0 }, { x: r + 2 * a / 6, y: 0 }, { x: r - a / 6, y: -a }, { x: a / 6, y: -a }],
+          o = Ww(n, r, a, s);
+        return o.attr("style", e.style),
+          Uw(e, o),
+          e.intersect = function(t) {
+            return aT.polygon(e, s, t);
+          },
+          n;
+      },
+      inv_trapezoid: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.width + e.padding,
+          a = i.height + e.padding,
+          s = [{ x: a / 6, y: 0 }, { x: r - a / 6, y: 0 }, { x: r + 2 * a / 6, y: -a }, { x: -2 * a / 6, y: -a }],
+          o = Ww(n, r, a, s);
+        return o.attr("style", e.style),
+          Uw(e, o),
+          e.intersect = function(t) {
+            return aT.polygon(e, s, t);
+          },
+          n;
+      },
+      rect_right_inv_arrow: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.width + e.padding,
+          a = i.height + e.padding,
+          s = [{ x: 0, y: 0 }, { x: r + a / 2, y: 0 }, { x: r, y: -a / 2 }, { x: r + a / 2, y: -a }, { x: 0, y: -a }],
+          o = Ww(n, r, a, s);
+        return o.attr("style", e.style),
+          Uw(e, o),
+          e.intersect = function(t) {
+            return aT.polygon(e, s, t);
+          },
+          n;
+      },
+      cylinder: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.width + e.padding,
+          a = r / 2,
+          s = a / (2.5 + r / 50),
+          o = i.height + s + e.padding,
+          l = "M 0," + s + " a " + a + "," + s + " 0,0,0 " + r + " 0 a " + a + "," + s + " 0,0,0 " + -r + " 0 l 0," + o
+            + " a " + a + "," + s + " 0,0,0 " + r + " 0 l 0," + -o,
+          c = n.attr("label-offset-y", s).insert("path", ":first-child").attr("style", e.style).attr("d", l).attr(
+            "transform",
+            "translate(" + -r / 2 + "," + -(o / 2 + s) + ")",
+          );
+        return Uw(e, c),
+          e.intersect = function(t) {
+            const n = aT.rect(e, t), i = n.x - e.x;
+            if (
+              0 != a
+              && (Math.abs(i) < e.width / 2 || Math.abs(i) == e.width / 2 && Math.abs(n.y - e.y) > e.height / 2 - s)
+            ) {
+              let r = s * s * (1 - i * i / (a * a));
+              0 != r && (r = Math.sqrt(r)), r = s - r, t.y - e.y > 0 && (r = -r), n.y += r;
+            }
+            return n;
+          },
+          n;
+      },
+      start: (t, e) => {
+        const n = t.insert("g").attr("class", "node default").attr("id", e.domId || e.id),
+          i = n.insert("circle", ":first-child");
+        return i.attr("class", "state-start").attr("r", 7).attr("width", 14).attr("height", 14),
+          Uw(e, i),
+          e.intersect = function(t) {
+            return aT.circle(e, 7, t);
+          },
+          n;
+      },
+      end: (t, e) => {
+        const n = t.insert("g").attr("class", "node default").attr("id", e.domId || e.id),
+          i = n.insert("circle", ":first-child"),
+          r = n.insert("circle", ":first-child");
+        return r.attr("class", "state-start").attr("r", 7).attr("width", 14).attr("height", 14),
+          i.attr("class", "state-end").attr("r", 5).attr("width", 10).attr("height", 10),
+          Uw(e, r),
+          e.intersect = function(t) {
+            return aT.circle(e, 7, t);
+          },
+          n;
+      },
+      note: sT,
+      subroutine: (t, e) => {
+        const { shapeSvg: n, bbox: i } = zw(t, e, void 0, !0),
+          r = i.width + e.padding,
+          a = i.height + e.padding,
+          s = [
+            { x: 0, y: 0 },
+            { x: r, y: 0 },
+            { x: r, y: -a },
+            { x: 0, y: -a },
+            { x: 0, y: 0 },
+            { x: -8, y: 0 },
+            { x: r + 8, y: 0 },
+            { x: r + 8, y: -a },
+            { x: -8, y: -a },
+            { x: -8, y: 0 },
+          ],
+          o = Ww(n, r, a, s);
+        return o.attr("style", e.style),
+          Uw(e, o),
+          e.intersect = function(t) {
+            return aT.polygon(e, s, t);
+          },
+          n;
+      },
+      fork: lT,
+      join: lT,
+      class_box: (t, e) => {
+        const n = e.padding / 2;
+        let i;
+        i = e.classes ? "node " + e.classes : "node default";
+        const r = t.insert("g").attr("class", i).attr("id", e.domId || e.id),
+          a = r.insert("rect", ":first-child"),
+          s = r.insert("line"),
+          o = r.insert("line");
+        let l = 0, c = 4;
+        const h = r.insert("g").attr("class", "label");
+        let u = 0;
+        const d = e.classData.annotations && e.classData.annotations[0],
+          p = e.classData.annotations[0] ? "«" + e.classData.annotations[0] + "»" : "",
+          f = h.node().appendChild(jw(p, e.labelStyle, !0, !0));
+        let g = f.getBBox();
+        if (cb(jx().flowchart.htmlLabels)) {
+          const t = f.children[0], e = ie(f);
+          g = t.getBoundingClientRect(), e.attr("width", g.width), e.attr("height", g.height);
+        }
+        e.classData.annotations[0] && (c += g.height + 4, l += g.width);
+        let y = e.classData.id;
+        void 0 !== e.classData.type && "" !== e.classData.type
+          && (jx().flowchart.htmlLabels ? y += "&lt;" + e.classData.type + "&gt;" : y += "<" + e.classData.type + ">");
+        const m = h.node().appendChild(jw(y, e.labelStyle, !0, !0));
+        ie(m).attr("class", "classTitle");
+        let b = m.getBBox();
+        if (cb(jx().flowchart.htmlLabels)) {
+          const t = m.children[0], e = ie(m);
+          b = t.getBoundingClientRect(), e.attr("width", b.width), e.attr("height", b.height);
+        }
+        c += b.height + 4, b.width > l && (l = b.width);
+        const _ = [];
+        e.classData.members.forEach(t => {
+          const n = Sw(t);
+          let i = n.displayText;
+          jx().flowchart.htmlLabels && (i = i.replace(/</g, "&lt;").replace(/>/g, "&gt;"));
+          const r = h.node().appendChild(jw(i, n.cssStyle ? n.cssStyle : e.labelStyle, !0, !0));
+          let a = r.getBBox();
+          if (cb(jx().flowchart.htmlLabels)) {
+            const t = r.children[0], e = ie(r);
+            a = t.getBoundingClientRect(), e.attr("width", a.width), e.attr("height", a.height);
+          }
+          a.width > l && (l = a.width), c += a.height + 4, _.push(r);
+        }), c += 8;
+        const x = [];
+        if (
+          e.classData.methods.forEach(t => {
+            const n = Sw(t);
+            let i = n.displayText;
+            jx().flowchart.htmlLabels && (i = i.replace(/</g, "&lt;").replace(/>/g, "&gt;"));
+            const r = h.node().appendChild(jw(i, n.cssStyle ? n.cssStyle : e.labelStyle, !0, !0));
+            let a = r.getBBox();
+            if (cb(jx().flowchart.htmlLabels)) {
+              const t = r.children[0], e = ie(r);
+              a = t.getBoundingClientRect(), e.attr("width", a.width), e.attr("height", a.height);
+            }
+            a.width > l && (l = a.width), c += a.height + 4, x.push(r);
+          }),
+            c += 8,
+            d
+        ) {
+          let t = (l - g.width) / 2;
+          ie(f).attr("transform", "translate( " + (-1 * l / 2 + t) + ", " + -1 * c / 2 + ")"), u = g.height + 4;
+        }
+        let v = (l - b.width) / 2;
+        return ie(m).attr("transform", "translate( " + (-1 * l / 2 + v) + ", " + (-1 * c / 2 + u) + ")"),
+          u += b.height + 4,
+          s.attr("class", "divider").attr("x1", -l / 2 - n).attr("x2", l / 2 + n).attr("y1", -c / 2 - n + 8 + u).attr(
+            "y2",
+            -c / 2 - n + 8 + u,
+          ),
+          u += 8,
+          _.forEach(t => {
+            ie(t).attr("transform", "translate( " + -l / 2 + ", " + (-1 * c / 2 + u + 4) + ")"), u += b.height + 4;
+          }),
+          u += 8,
+          o.attr("class", "divider").attr("x1", -l / 2 - n).attr("x2", l / 2 + n).attr("y1", -c / 2 - n + 8 + u).attr(
+            "y2",
+            -c / 2 - n + 8 + u,
+          ),
+          u += 8,
+          x.forEach(t => {
+            ie(t).attr("transform", "translate( " + -l / 2 + ", " + (-1 * c / 2 + u) + ")"), u += b.height + 4;
+          }),
+          a.attr("class", "outer title-state").attr("x", -l / 2 - n).attr("y", -c / 2 - n).attr("width", l + e.padding)
+            .attr("height", c + e.padding),
+          Uw(e, a),
+          e.intersect = function(t) {
+            return aT.rect(e, t);
+          },
+          r;
+      },
+    };
+  let hT = {};
+  const uT = t => {
+      const e = hT[t.id];
+      tb.trace("Transforming node", t.diff, t, "translate(" + (t.x - t.width / 2 - 5) + ", " + t.width / 2 + ")");
+      const n = t.diff || 0;
+      return t.clusterNode
+        ? e.attr("transform", "translate(" + (t.x + n - t.width / 2) + ", " + (t.y - t.height / 2 - 8) + ")")
+        : e.attr("transform", "translate(" + t.x + ", " + t.y + ")"),
+        n;
+    },
+    dT = {
+      rect: (t, e) => {
+        tb.trace("Creating subgraph rect for ", e.id, e);
+        const n = t.insert("g").attr("class", "cluster" + (e.class ? " " + e.class : "")).attr("id", e.id),
+          i = n.insert("rect", ":first-child"),
+          r = n.insert("g").attr("class", "cluster-label"),
+          a = r.node().appendChild(jw(e.labelText, e.labelStyle, void 0, !0));
+        let s = a.getBBox();
+        if (cb(jx().flowchart.htmlLabels)) {
+          const t = a.children[0], e = ie(a);
+          s = t.getBoundingClientRect(), e.attr("width", s.width), e.attr("height", s.height);
+        }
+        const o = 0 * e.padding, l = o / 2, c = e.width <= s.width + o ? s.width + o : e.width;
+        e.width <= s.width + o ? e.diff = (s.width - e.width) / 2 - e.padding / 2 : e.diff = -e.padding / 2,
+          tb.trace("Data ", e, JSON.stringify(e)),
+          i.attr("style", e.style).attr("rx", e.rx).attr("ry", e.ry).attr("x", e.x - c / 2).attr(
+            "y",
+            e.y - e.height / 2 - l,
+          ).attr("width", c).attr("height", e.height + o),
+          r.attr("transform", "translate(" + (e.x - s.width / 2) + ", " + (e.y - e.height / 2) + ")");
+        const h = i.node().getBBox();
+        return e.width = h.width,
+          e.height = h.height,
+          e.intersect = function(t) {
+            return rT(e, t);
+          },
+          n;
+      },
+      roundedWithTitle: (t, e) => {
+        const n = t.insert("g").attr("class", e.classes).attr("id", e.id),
+          i = n.insert("rect", ":first-child"),
+          r = n.insert("g").attr("class", "cluster-label"),
+          a = n.append("rect"),
+          s = r.node().appendChild(jw(e.labelText, e.labelStyle, void 0, !0));
+        let o = s.getBBox();
+        if (cb(jx().flowchart.htmlLabels)) {
+          const t = s.children[0], e = ie(s);
+          o = t.getBoundingClientRect(), e.attr("width", o.width), e.attr("height", o.height);
+        }
+        o = s.getBBox();
+        const l = 0 * e.padding, c = l / 2, h = e.width <= o.width + e.padding ? o.width + e.padding : e.width;
+        e.width <= o.width + e.padding ? e.diff = (o.width + 0 * e.padding - e.width) / 2 : e.diff = -e.padding / 2,
+          i.attr("class", "outer").attr("x", e.x - h / 2 - c).attr("y", e.y - e.height / 2 - c).attr("width", h + l)
+            .attr("height", e.height + l),
+          a.attr("class", "inner").attr("x", e.x - h / 2 - c).attr("y", e.y - e.height / 2 - c + o.height - 1).attr(
+            "width",
+            h + l,
+          ).attr("height", e.height + l - o.height - 3),
+          r.attr(
+            "transform",
+            "translate(" + (e.x - o.width / 2) + ", "
+              + (e.y - e.height / 2 - e.padding / 3 + (cb(jx().flowchart.htmlLabels) ? 5 : 3)) + ")",
+          );
+        const u = i.node().getBBox();
+        return e.height = u.height,
+          e.intersect = function(t) {
+            return rT(e, t);
+          },
+          n;
+      },
+      noteGroup: (t, e) => {
+        const n = t.insert("g").attr("class", "note-cluster").attr("id", e.id),
+          i = n.insert("rect", ":first-child"),
+          r = 0 * e.padding,
+          a = r / 2;
+        i.attr("rx", e.rx).attr("ry", e.ry).attr("x", e.x - e.width / 2 - a).attr("y", e.y - e.height / 2 - a).attr(
+          "width",
+          e.width + r,
+        ).attr("height", e.height + r).attr("fill", "none");
+        const s = i.node().getBBox();
+        return e.width = s.width,
+          e.height = s.height,
+          e.intersect = function(t) {
+            return rT(e, t);
+          },
+          n;
+      },
+      divider: (t, e) => {
+        const n = t.insert("g").attr("class", e.classes).attr("id", e.id),
+          i = n.insert("rect", ":first-child"),
+          r = 0 * e.padding,
+          a = r / 2;
+        i.attr("class", "divider").attr("x", e.x - e.width / 2 - a).attr("y", e.y - e.height / 2).attr(
+          "width",
+          e.width + r,
+        ).attr("height", e.height + r);
+        const s = i.node().getBBox();
+        return e.width = s.width,
+          e.height = s.height,
+          e.diff = -e.padding / 2,
+          e.intersect = function(t) {
+            return rT(e, t);
+          },
+          n;
+      },
+    };
+  let pT = {};
+  let fT = {}, gT = {};
+  function yT(t, e) {
+    jx().flowchart.htmlLabels && t && (t.style.width = 9 * e.length + "px", t.style.height = "12px");
+  }
+  const mT = (t, e) => {
+      tb.warn("abc88 cutPathAtIntersect", t, e);
+      let n = [], i = t[0], r = !1;
+      return t.forEach(t => {
+        if (
+          tb.info("abc88 checking point", t, e),
+            ((t, e) => {
+              const n = t.x, i = t.y, r = Math.abs(e.x - n), a = Math.abs(e.y - i), s = t.width / 2, o = t.height / 2;
+              return r >= s || a >= o;
+            })(e, t) || r
+        ) tb.warn("abc88 outside", t, i), i = t, r || n.push(t);
+        else {
+          const a = ((t, e, n) => {
+            tb.warn(
+              `intersection calc abc89:\n  outsidePoint: ${JSON.stringify(e)}\n  insidePoint : ${
+                JSON.stringify(n)
+              }\n  node        : x:${t.x} y:${t.y} w:${t.width} h:${t.height}`,
+            );
+            const i = t.x, r = t.y, a = Math.abs(i - n.x), s = t.width / 2;
+            let o = n.x < e.x ? s - a : s + a;
+            const l = t.height / 2, c = Math.abs(e.y - n.y), h = Math.abs(e.x - n.x);
+            if (Math.abs(r - e.y) * s > Math.abs(i - e.x) * l) {
+              let t = n.y < e.y ? e.y - l - r : r - l - e.y;
+              o = h * t / c;
+              const i = { x: n.x < e.x ? n.x + o : n.x - h + o, y: n.y < e.y ? n.y + c - t : n.y - c + t };
+              return 0 === o && (i.x = e.x, i.y = e.y),
+                0 === h && (i.x = e.x),
+                0 === c && (i.y = e.y),
+                tb.warn(`abc89 topp/bott calc, Q ${c}, q ${t}, R ${h}, r ${o}`, i),
+                i;
+            }
+            {
+              o = n.x < e.x ? e.x - s - i : i - s - e.x;
+              let t = c * o / h, r = n.x < e.x ? n.x + h - o : n.x - h + o, a = n.y < e.y ? n.y + t : n.y - t;
+              return tb.warn(`sides calc abc89, Q ${c}, q ${t}, R ${h}, r ${o}`, { _x: r, _y: a }),
+                0 === o && (r = e.x, a = e.y),
+                0 === h && (r = e.x),
+                0 === c && (a = e.y),
+                { x: r, y: a };
+            }
+          })(e, i, t);
+          tb.warn("abc88 inside", t, i, a), tb.warn("abc88 intersection", a);
+          let s = !1;
+          n.forEach(t => {
+            s = s || t.x === a.x && t.y === a.y;
+          }),
+            n.some(t => t.x === a.x && t.y === a.y) ? tb.warn("abc88 no intersect", a, n) : n.push(a),
+            r = !0;
+        }
+      }),
+        tb.warn("abc88 returning points", n),
+        n;
+    },
+    bT = (t, e, n, i) => {
+      tb.info("Graph in recursive render: XXX", Ym(e), i);
+      const r = e.graph().rankdir;
+      tb.trace("Dir in recursive render - dir:", r);
+      const a = t.insert("g").attr("class", "root");
+      e.nodes() ? tb.info("Recursive render XXX", e.nodes()) : tb.info("No nodes found for", e),
+        e.edges().length > 0 && tb.trace("Recursive edges", e.edge(e.edges()[0]));
+      const s = a.insert("g").attr("class", "clusters"),
+        o = a.insert("g").attr("class", "edgePaths"),
+        l = a.insert("g").attr("class", "edgeLabels"),
+        c = a.insert("g").attr("class", "nodes");
+      e.nodes().forEach(function(t) {
+        const a = e.node(t);
+        if (void 0 !== i) {
+          const n = JSON.parse(JSON.stringify(i.clusterData));
+          tb.info("Setting data for cluster XXX (", t, ") ", n, i),
+            e.setNode(i.id, n),
+            e.parent(t) || (tb.trace("Setting parent", t, i.id), e.setParent(t, i.id, n));
+        }
+        if (tb.info("(Insert) Node XXX" + t + ": " + JSON.stringify(e.node(t))), a && a.clusterNode) {
+          tb.info("Cluster identified", t, a.width, e.node(t));
+          const i = bT(c, a.graph, n, e.node(t)), r = i.elem;
+          Uw(a, r),
+            a.diff = i.diff || 0,
+            tb.info("Node bounds (abc123)", t, a, a.width, a.x, a.y),
+            ((t, e) => {
+              hT[e.id] = t;
+            })(r, a),
+            tb.warn("Recursive render complete ", r, a);
+        } else {e.children(t).length > 0
+            ? (tb.info("Cluster - the non recursive path XXX", t, a.id, a, e),
+              tb.info(Qw(a.id, e)),
+              Hw[a.id] = { id: Qw(a.id, e), node: a })
+            : (tb.info("Node - the non recursive path", t, a.id, a),
+              ((t, e, n) => {
+                let i, r;
+                if (e.link) {
+                  let a;
+                  "sandbox" === jx().securityLevel ? a = "_top" : e.linkTarget && (a = e.linkTarget || "_blank"),
+                    i = t.insert("svg:a").attr("xlink:href", e.link).attr("target", a),
+                    r = cT[e.shape](i, e, n);
+                } else r = cT[e.shape](t, e, n), i = r;
+                e.tooltip && r.attr("title", e.tooltip),
+                  e.class && r.attr("class", "node default " + e.class),
+                  hT[e.id] = i,
+                  e.haveCallback && hT[e.id].attr("class", hT[e.id].attr("class") + " clickable");
+              })(c, e.node(t), r));}
+      }),
+        e.edges().forEach(function(t) {
+          const n = e.edge(t.v, t.w, t.name);
+          tb.info("Edge " + t.v + " -> " + t.w + ": " + JSON.stringify(t)),
+            tb.info("Edge " + t.v + " -> " + t.w + ": ", t, " ", JSON.stringify(e.edge(t))),
+            tb.info("Fix", Hw, "ids:", t.v, t.w, "Translateing: ", Hw[t.v], Hw[t.w]),
+            ((t, e) => {
+              const n = jw(e.label, e.labelStyle),
+                i = t.insert("g").attr("class", "edgeLabel"),
+                r = i.insert("g").attr("class", "label");
+              r.node().appendChild(n);
+              let a, s = n.getBBox();
+              if (cb(jx().flowchart.htmlLabels)) {
+                const t = n.children[0], e = ie(n);
+                s = t.getBoundingClientRect(), e.attr("width", s.width), e.attr("height", s.height);
+              }
+              if (
+                r.attr("transform", "translate(" + -s.width / 2 + ", " + -s.height / 2 + ")"),
+                  fT[e.id] = i,
+                  e.width = s.width,
+                  e.height = s.height,
+                  e.startLabelLeft
+              ) {
+                const n = jw(e.startLabelLeft, e.labelStyle),
+                  i = t.insert("g").attr("class", "edgeTerminals"),
+                  r = i.insert("g").attr("class", "inner");
+                a = r.node().appendChild(n);
+                const s = n.getBBox();
+                r.attr("transform", "translate(" + -s.width / 2 + ", " + -s.height / 2 + ")"),
+                  gT[e.id] || (gT[e.id] = {}),
+                  gT[e.id].startLeft = i,
+                  yT(a, e.startLabelLeft);
+              }
+              if (e.startLabelRight) {
+                const n = jw(e.startLabelRight, e.labelStyle),
+                  i = t.insert("g").attr("class", "edgeTerminals"),
+                  r = i.insert("g").attr("class", "inner");
+                a = i.node().appendChild(n), r.node().appendChild(n);
+                const s = n.getBBox();
+                r.attr("transform", "translate(" + -s.width / 2 + ", " + -s.height / 2 + ")"),
+                  gT[e.id] || (gT[e.id] = {}),
+                  gT[e.id].startRight = i,
+                  yT(a, e.startLabelRight);
+              }
+              if (e.endLabelLeft) {
+                const n = jw(e.endLabelLeft, e.labelStyle),
+                  i = t.insert("g").attr("class", "edgeTerminals"),
+                  r = i.insert("g").attr("class", "inner");
+                a = r.node().appendChild(n);
+                const s = n.getBBox();
+                r.attr("transform", "translate(" + -s.width / 2 + ", " + -s.height / 2 + ")"),
+                  i.node().appendChild(n),
+                  gT[e.id] || (gT[e.id] = {}),
+                  gT[e.id].endLeft = i,
+                  yT(a, e.endLabelLeft);
+              }
+              if (e.endLabelRight) {
+                const n = jw(e.endLabelRight, e.labelStyle),
+                  i = t.insert("g").attr("class", "edgeTerminals"),
+                  r = i.insert("g").attr("class", "inner");
+                a = r.node().appendChild(n);
+                const s = n.getBBox();
+                r.attr("transform", "translate(" + -s.width / 2 + ", " + -s.height / 2 + ")"),
+                  i.node().appendChild(n),
+                  gT[e.id] || (gT[e.id] = {}),
+                  gT[e.id].endRight = i,
+                  yT(a, e.endLabelRight);
+              }
+            })(l, n);
+        }),
+        e.edges().forEach(function(t) {
+          tb.info("Edge " + t.v + " -> " + t.w + ": " + JSON.stringify(t));
+        }),
+        tb.info("#############################################"),
+        tb.info("###                Layout                 ###"),
+        tb.info("#############################################"),
+        tb.info(e),
+        hm(e),
+        tb.info("Graph after layout:", Ym(e));
+      let h = 0;
+      return (t => tT(t, t.children()))(e).forEach(function(t) {
+        const n = e.node(t);
+        tb.info("Position " + t + ": " + JSON.stringify(e.node(t))),
+          tb.info("Position " + t + ": (" + n.x, "," + n.y, ") width: ", n.width, " height: ", n.height),
+          n && n.clusterNode ? uT(n) : e.children(t).length > 0
+            ? (((t, e) => {
+              tb.trace("Inserting cluster");
+              const n = e.shape || "rect";
+              pT[e.id] = dT[n](t, e);
+            })(s, n),
+              Hw[n.id].node = n)
+            : uT(n);
+      }),
+        e.edges().forEach(function(t) {
+          const i = e.edge(t);
+          tb.info("Edge " + t.v + " -> " + t.w + ": " + JSON.stringify(i), i);
+          const r = function(t, e, n, i, r, a) {
+            let s = n.points, o = !1;
+            const l = a.node(e.v);
+            var c = a.node(e.w);
+            tb.info("abc88 InsertEdge: ", n),
+              c.intersect && l.intersect
+              && (s = s.slice(1, n.points.length - 1),
+                s.unshift(l.intersect(s[0])),
+                tb.info("Last point", s[s.length - 1], c, c.intersect(s[s.length - 1])),
+                s.push(c.intersect(s[s.length - 1]))),
+              n.toCluster
+              && (tb.info("to cluster abc88", i[n.toCluster]), s = mT(n.points, i[n.toCluster].node), o = !0),
+              n.fromCluster
+              && (tb.info("from cluster abc88", i[n.fromCluster]),
+                s = mT(s.reverse(), i[n.fromCluster].node).reverse(),
+                o = !0);
+            const h = s.filter(t => !Number.isNaN(t.y));
+            let u;
+            u = ("graph" === r || "flowchart" === r) && n.curve || ao;
+            const d = Js().x(function(t) {
+              return t.x;
+            }).y(function(t) {
+              return t.y;
+            }).curve(u);
+            let p;
+            switch (n.thickness) {
+              case "normal":
+                p = "edge-thickness-normal";
+                break;
+              case "thick":
+                p = "edge-thickness-thick";
+                break;
+              default:
+                p = "";
+            }
+            switch (n.pattern) {
+              case "solid":
+                p += " edge-pattern-solid";
+                break;
+              case "dotted":
+                p += " edge-pattern-dotted";
+                break;
+              case "dashed":
+                p += " edge-pattern-dashed";
+            }
+            const f = t.append("path").attr("d", d(h)).attr("id", n.id).attr(
+              "class",
+              " " + p + (n.classes ? " " + n.classes : ""),
+            ).attr("style", n.style);
+            let g = "";
+            switch (
+              (jx().flowchart.arrowMarkerAbsolute || jx().state.arrowMarkerAbsolute)
+              && (g = window.location.protocol + "//" + window.location.host + window.location.pathname
+                + window.location.search,
+                g = g.replace(/\(/g, "\\("),
+                g = g.replace(/\)/g, "\\)")),
+                tb.info("arrowTypeStart", n.arrowTypeStart),
+                tb.info("arrowTypeEnd", n.arrowTypeEnd),
+                n.arrowTypeStart
+            ) {
+              case "arrow_cross":
+                f.attr("marker-start", "url(" + g + "#" + r + "-crossStart)");
+                break;
+              case "arrow_point":
+                f.attr("marker-start", "url(" + g + "#" + r + "-pointStart)");
+                break;
+              case "arrow_barb":
+                f.attr("marker-start", "url(" + g + "#" + r + "-barbStart)");
+                break;
+              case "arrow_circle":
+                f.attr("marker-start", "url(" + g + "#" + r + "-circleStart)");
+                break;
+              case "aggregation":
+                f.attr("marker-start", "url(" + g + "#" + r + "-aggregationStart)");
+                break;
+              case "extension":
+                f.attr("marker-start", "url(" + g + "#" + r + "-extensionStart)");
+                break;
+              case "composition":
+                f.attr("marker-start", "url(" + g + "#" + r + "-compositionStart)");
+                break;
+              case "dependency":
+                f.attr("marker-start", "url(" + g + "#" + r + "-dependencyStart)");
+                break;
+              case "lollipop":
+                f.attr("marker-start", "url(" + g + "#" + r + "-lollipopStart)");
+            }
+            switch (n.arrowTypeEnd) {
+              case "arrow_cross":
+                f.attr("marker-end", "url(" + g + "#" + r + "-crossEnd)");
+                break;
+              case "arrow_point":
+                f.attr("marker-end", "url(" + g + "#" + r + "-pointEnd)");
+                break;
+              case "arrow_barb":
+                f.attr("marker-end", "url(" + g + "#" + r + "-barbEnd)");
+                break;
+              case "arrow_circle":
+                f.attr("marker-end", "url(" + g + "#" + r + "-circleEnd)");
+                break;
+              case "aggregation":
+                f.attr("marker-end", "url(" + g + "#" + r + "-aggregationEnd)");
+                break;
+              case "extension":
+                f.attr("marker-end", "url(" + g + "#" + r + "-extensionEnd)");
+                break;
+              case "composition":
+                f.attr("marker-end", "url(" + g + "#" + r + "-compositionEnd)");
+                break;
+              case "dependency":
+                f.attr("marker-end", "url(" + g + "#" + r + "-dependencyEnd)");
+                break;
+              case "lollipop":
+                f.attr("marker-end", "url(" + g + "#" + r + "-lollipopEnd)");
+            }
+            let y = {};
+            return o && (y.updatedPath = s), y.originalPath = n.points, y;
+          }(o, t, i, Hw, n, e);
+          ((t, e) => {
+            tb.info("Moving label abc78 ", t.id, t.label, fT[t.id]);
+            let n = e.updatedPath ? e.updatedPath : e.originalPath;
+            if (t.label) {
+              const i = fT[t.id];
+              let r = t.x, a = t.y;
+              if (n) {
+                const i = Dx.calcLabelPosition(n);
+                tb.info("Moving label " + t.label + " from (", r, ",", a, ") to (", i.x, ",", i.y, ") abc78"),
+                  e.updatedPath && (r = i.x, a = i.y);
+              }
+              i.attr("transform", "translate(" + r + ", " + a + ")");
+            }
+            if (t.startLabelLeft) {
+              const e = gT[t.id].startLeft;
+              let i = t.x, r = t.y;
+              if (n) {
+                const e = Dx.calcTerminalLabelPosition(t.arrowTypeStart ? 10 : 0, "start_left", n);
+                i = e.x, r = e.y;
+              }
+              e.attr("transform", "translate(" + i + ", " + r + ")");
+            }
+            if (t.startLabelRight) {
+              const e = gT[t.id].startRight;
+              let i = t.x, r = t.y;
+              if (n) {
+                const e = Dx.calcTerminalLabelPosition(t.arrowTypeStart ? 10 : 0, "start_right", n);
+                i = e.x, r = e.y;
+              }
+              e.attr("transform", "translate(" + i + ", " + r + ")");
+            }
+            if (t.endLabelLeft) {
+              const e = gT[t.id].endLeft;
+              let i = t.x, r = t.y;
+              if (n) {
+                const e = Dx.calcTerminalLabelPosition(t.arrowTypeEnd ? 10 : 0, "end_left", n);
+                i = e.x, r = e.y;
+              }
+              e.attr("transform", "translate(" + i + ", " + r + ")");
+            }
+            if (t.endLabelRight) {
+              const e = gT[t.id].endRight;
+              let i = t.x, r = t.y;
+              if (n) {
+                const e = Dx.calcTerminalLabelPosition(t.arrowTypeEnd ? 10 : 0, "end_right", n);
+                i = e.x, r = e.y;
+              }
+              e.attr("transform", "translate(" + i + ", " + r + ")");
+            }
+          })(i, r);
+        }),
+        e.nodes().forEach(function(t) {
+          const n = e.node(t);
+          tb.info(t, n.type, n.diff), "group" === n.type && (h = n.diff);
+        }),
+        { elem: a, diff: h };
+    },
+    _T = (t, e, n, i, r) => {
+      Yw(t, n, i, r),
+        hT = {},
+        fT = {},
+        gT = {},
+        pT = {},
+        qw = {},
+        Vw = {},
+        Hw = {},
+        tb.warn("Graph at first:", Ym(e)),
+        ((t, e) => {
+          !t || e > 10
+            ? tb.debug("Opting out, no graph ")
+            : (tb.debug("Opting in, graph "),
+              t.nodes().forEach(function(e) {
+                t.children(e).length > 0
+                  && (tb.warn("Cluster identified", e, " Replacement id in edges: ", Qw(e, t)),
+                    qw[e] = Zw(e, t),
+                    Hw[e] = { id: Qw(e, t), clusterData: t.node(e) });
+              }),
+              t.nodes().forEach(function(e) {
+                const n = t.children(e), i = t.edges();
+                n.length > 0
+                  ? (tb.debug("Cluster identified", e, qw),
+                    i.forEach(t => {
+                      t.v !== e && t.w !== e && Gw(t.v, e) ^ Gw(t.w, e)
+                        && (tb.warn("Edge: ", t, " leaves cluster ", e),
+                          tb.warn("Decendants of XXX ", e, ": ", qw[e]),
+                          Hw[e].externalConnections = !0);
+                    }))
+                  : tb.debug("Not a cluster ", e, qw);
+              }),
+              t.edges().forEach(function(e) {
+                const n = t.edge(e);
+                tb.warn("Edge " + e.v + " -> " + e.w + ": " + JSON.stringify(e)),
+                  tb.warn("Edge " + e.v + " -> " + e.w + ": " + JSON.stringify(t.edge(e)));
+                let i = e.v, r = e.w;
+                if (
+                  tb.warn("Fix XXX", Hw, "ids:", e.v, e.w, "Translating: ", Hw[e.v], " --- ", Hw[e.w]),
+                    Hw[e.v] && Hw[e.w] && Hw[e.v] === Hw[e.w]
+                ) {
+                  tb.warn("Fixing and trixing link to self - removing XXX", e.v, e.w, e.name),
+                    tb.warn("Fixing and trixing - removing XXX", e.v, e.w, e.name),
+                    i = Kw(e.v),
+                    r = Kw(e.w),
+                    t.removeEdge(e.v, e.w, e.name);
+                  const a = e.w + "---" + e.v;
+                  t.setNode(a, {
+                    domId: a,
+                    id: a,
+                    labelStyle: "",
+                    labelText: n.label,
+                    padding: 0,
+                    shape: "labelRect",
+                    style: "",
+                  });
+                  const s = JSON.parse(JSON.stringify(n)), o = JSON.parse(JSON.stringify(n));
+                  s.label = "",
+                    s.arrowTypeEnd = "none",
+                    o.label = "",
+                    s.fromCluster = e.v,
+                    o.toCluster = e.v,
+                    t.setEdge(i, a, s, e.name + "-cyclic-special"),
+                    t.setEdge(a, r, o, e.name + "-cyclic-special");
+                } else {(Hw[e.v] || Hw[e.w])
+                    && (tb.warn("Fixing and trixing - removing XXX", e.v, e.w, e.name),
+                      i = Kw(e.v),
+                      r = Kw(e.w),
+                      t.removeEdge(e.v, e.w, e.name),
+                      i !== e.v && (n.fromCluster = e.v),
+                      r !== e.w && (n.toCluster = e.w),
+                      tb.warn("Fix Replacing with XXX", i, r, e.name),
+                      t.setEdge(i, r, n, e.name));}
+              }),
+              tb.warn("Adjusted Graph", Ym(t)),
+              Jw(t, 0),
+              tb.trace(Hw));
+        })(e),
+        tb.warn("Graph after:", Ym(e)),
+        bT(t, e, i);
+    },
+    xT = t => ub.sanitizeText(t, jx());
+  let vT = { dividerMargin: 10, padding: 5, textHeight: 10 };
+  function kT(t) {
+    let e;
+    switch (t) {
+      case 0:
+        e = "aggregation";
+        break;
+      case 1:
+        e = "extension";
+        break;
+      case 2:
+        e = "composition";
+        break;
+      case 3:
+        e = "dependency";
+        break;
+      case 4:
+        e = "lollipop";
+        break;
+      default:
+        e = "none";
+    }
+    return e;
+  }
+  const wT = {
+    setConf: function(t) {
+      Object.keys(t).forEach(function(e) {
+        vT[e] = t[e];
+      });
+    },
+    draw: function(t, e, n, i) {
+      tb.info("Drawing class - ", e);
+      const r = jx().flowchart, a = jx().securityLevel;
+      tb.info("config:", r);
+      const s = r.nodeSpacing || 50,
+        o = r.rankSpacing || 50,
+        l = new yy({ multigraph: !0, compound: !0 }).setGraph({
+          rankdir: i.db.getDirection(),
+          nodesep: s,
+          ranksep: o,
+          marginx: 8,
+          marginy: 8,
+        }).setDefaultEdgeLabel(function() {
+          return {};
+        }),
+        c = i.db.getClasses(),
+        h = i.db.getRelations(),
+        u = i.db.getNotes();
+      let d;
+      tb.info(h),
+        function(t, e, n, i) {
+          const r = Object.keys(t);
+          tb.info("keys:", r),
+            tb.info(t),
+            r.forEach(function(n) {
+              const r = t[n];
+              let a = "";
+              r.cssClasses.length > 0 && (a = a + " " + r.cssClasses.join(" "));
+              const s = { labelStyle: "" };
+              let o = void 0 !== r.text ? r.text : r.id, l = "";
+              r.type,
+                l = "class_box",
+                e.setNode(r.id, {
+                  labelStyle: s.labelStyle,
+                  shape: l,
+                  labelText: xT(o),
+                  classData: r,
+                  rx: 0,
+                  ry: 0,
+                  class: a,
+                  style: s.style,
+                  id: r.id,
+                  domId: r.domId,
+                  tooltip: i.db.getTooltip(r.id) || "",
+                  haveCallback: r.haveCallback,
+                  link: r.link,
+                  width: "group" === r.type ? 500 : void 0,
+                  type: r.type,
+                  padding: jx().flowchart.padding,
+                }),
+                tb.info("setNode", {
+                  labelStyle: s.labelStyle,
+                  shape: l,
+                  labelText: o,
+                  rx: 0,
+                  ry: 0,
+                  class: a,
+                  style: s.style,
+                  id: r.id,
+                  width: "group" === r.type ? 500 : void 0,
+                  type: r.type,
+                  padding: jx().flowchart.padding,
+                });
+            });
+        }(c, l, 0, i),
+        function(t, e) {
+          const n = jx().flowchart;
+          let i = 0;
+          t.forEach(function(r) {
+            i++;
+            const a = { classes: "relation" };
+            a.pattern = 1 == r.relation.lineType ? "dashed" : "solid",
+              a.id = "id" + i,
+              "arrow_open" === r.type ? a.arrowhead = "none" : a.arrowhead = "normal",
+              tb.info(a, r),
+              a.startLabelRight = "none" === r.relationTitle1 ? "" : r.relationTitle1,
+              a.endLabelLeft = "none" === r.relationTitle2 ? "" : r.relationTitle2,
+              a.arrowTypeStart = kT(r.relation.type1),
+              a.arrowTypeEnd = kT(r.relation.type2);
+            let s = "", o = "";
+            if (void 0 !== r.style) {
+              const t = gx(r.style);
+              s = t.style, o = t.labelStyle;
+            } else s = "fill:none";
+            a.style = s,
+              a.labelStyle = o,
+              void 0 !== r.interpolate
+                ? a.curve = px(r.interpolate, Zs)
+                : void 0 !== t.defaultInterpolate
+                ? a.curve = px(t.defaultInterpolate, Zs)
+                : a.curve = px(n.curve, Zs),
+              r.text = r.title,
+              void 0 === r.text
+                ? void 0 !== r.style && (a.arrowheadStyle = "fill: #333")
+                : (a.arrowheadStyle = "fill: #333",
+                  a.labelpos = "c",
+                  jx().flowchart.htmlLabels
+                    ? (a.labelType = "html", a.label = "<span class=\"edgeLabel\">" + r.text + "</span>")
+                    : (a.labelType = "text",
+                      a.label = r.text.replace(ub.lineBreakRegex, "\n"),
+                      void 0 === r.style && (a.style = a.style || "stroke: #333; stroke-width: 1.5px;fill:none"),
+                      a.labelStyle = a.labelStyle.replace("color:", "fill:"))),
+              e.setEdge(r.id1, r.id2, a, i);
+          });
+        }(h, l),
+        function(t, e, n, i) {
+          tb.info(t),
+            t.forEach(function(t, r) {
+              const a = t, s = "", o = "";
+              let l = a.text, c = "note";
+              if (
+                e.setNode(a.id, {
+                  labelStyle: s,
+                  shape: c,
+                  labelText: xT(l),
+                  noteData: a,
+                  rx: 0,
+                  ry: 0,
+                  class: "",
+                  style: o,
+                  id: a.id,
+                  domId: a.id,
+                  tooltip: "",
+                  type: "note",
+                  padding: jx().flowchart.padding,
+                }),
+                  tb.info("setNode", {
+                    labelStyle: s,
+                    shape: c,
+                    labelText: l,
+                    rx: 0,
+                    ry: 0,
+                    style: o,
+                    id: a.id,
+                    type: "note",
+                    padding: jx().flowchart.padding,
+                  }),
+                  !a.class || !(a.class in i)
+              ) return;
+              const h = n + r, u = { classes: "relation", pattern: "dotted" };
+              u.id = `edgeNote${h}`,
+                u.arrowhead = "none",
+                tb.info(`Note edge: ${JSON.stringify(u)}, ${JSON.stringify(a)}`),
+                u.startLabelRight = "",
+                u.endLabelLeft = "",
+                u.arrowTypeStart = "none",
+                u.arrowTypeEnd = "none",
+                u.style = "fill:none",
+                u.labelStyle = "",
+                u.curve = px(vT.curve, Zs),
+                e.setEdge(a.id, a.class, u, h);
+            });
+        }(u, l, h.length + 1, c),
+        "sandbox" === a && (d = ie("#i" + e));
+      const p = ie("sandbox" === a ? d.nodes()[0].contentDocument.body : "body"),
+        f = p.select(`[id="${e}"]`),
+        g = p.select("#" + e + " g");
+      if (
+        _T(g, l, ["aggregation", "extension", "composition", "dependency", "lollipop"], "classDiagram", e),
+          Dx.insertTitle(f, "classTitleText", r.titleTopMargin, i.db.getDiagramTitle()),
+          Xx(l, f, r.diagramPadding, r.useMaxWidth),
+          !r.htmlLabels
+      ) {
+        const t = "sandbox" === a ? d.nodes()[0].contentDocument : document,
+          n = t.querySelectorAll("[id=\"" + e + "\"] .edgeLabel .label");
+        for (const e of n) {
+          const n = e.getBBox(), i = t.createElementNS("http://www.w3.org/2000/svg", "rect");
+          i.setAttribute("rx", 0),
+            i.setAttribute("ry", 0),
+            i.setAttribute("width", n.width),
+            i.setAttribute("height", n.height),
+            e.insertBefore(i, e.firstChild);
+        }
+      }
+    },
+  };
+  var TT = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [1, 2],
+      i = [1, 5],
+      r = [6, 9, 11, 23, 25, 27, 29, 30, 31, 49],
+      a = [1, 17],
+      s = [1, 18],
+      o = [1, 19],
+      l = [1, 20],
+      c = [1, 21],
+      h = [1, 22],
+      u = [1, 25],
+      d = [1, 30],
+      p = [1, 31],
+      f = [1, 32],
+      g = [1, 33],
+      y = [6, 9, 11, 15, 20, 23, 25, 27, 29, 30, 31, 42, 43, 44, 45, 49],
+      m = [1, 45],
+      b = [30, 31, 46, 47],
+      _ = [4, 6, 9, 11, 23, 25, 27, 29, 30, 31, 49],
+      x = [42, 43, 44, 45],
+      v = [22, 37],
+      k = [1, 64],
+      w = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          ER_DIAGRAM: 4,
+          document: 5,
+          EOF: 6,
+          directive: 7,
+          line: 8,
+          SPACE: 9,
+          statement: 10,
+          NEWLINE: 11,
+          openDirective: 12,
+          typeDirective: 13,
+          closeDirective: 14,
+          ":": 15,
+          argDirective: 16,
+          entityName: 17,
+          relSpec: 18,
+          role: 19,
+          BLOCK_START: 20,
+          attributes: 21,
+          BLOCK_STOP: 22,
+          title: 23,
+          title_value: 24,
+          acc_title: 25,
+          acc_title_value: 26,
+          acc_descr: 27,
+          acc_descr_value: 28,
+          acc_descr_multiline_value: 29,
+          ALPHANUM: 30,
+          ENTITY_NAME: 31,
+          attribute: 32,
+          attributeType: 33,
+          attributeName: 34,
+          attributeKeyType: 35,
+          attributeComment: 36,
+          ATTRIBUTE_WORD: 37,
+          ATTRIBUTE_KEY: 38,
+          COMMENT: 39,
+          cardinality: 40,
+          relType: 41,
+          ZERO_OR_ONE: 42,
+          ZERO_OR_MORE: 43,
+          ONE_OR_MORE: 44,
+          ONLY_ONE: 45,
+          NON_IDENTIFYING: 46,
+          IDENTIFYING: 47,
+          WORD: 48,
+          open_directive: 49,
+          type_directive: 50,
+          arg_directive: 51,
+          close_directive: 52,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: {
+          2: "error",
+          4: "ER_DIAGRAM",
+          6: "EOF",
+          9: "SPACE",
+          11: "NEWLINE",
+          15: ":",
+          20: "BLOCK_START",
+          22: "BLOCK_STOP",
+          23: "title",
+          24: "title_value",
+          25: "acc_title",
+          26: "acc_title_value",
+          27: "acc_descr",
+          28: "acc_descr_value",
+          29: "acc_descr_multiline_value",
+          30: "ALPHANUM",
+          31: "ENTITY_NAME",
+          37: "ATTRIBUTE_WORD",
+          38: "ATTRIBUTE_KEY",
+          39: "COMMENT",
+          42: "ZERO_OR_ONE",
+          43: "ZERO_OR_MORE",
+          44: "ONE_OR_MORE",
+          45: "ONLY_ONE",
+          46: "NON_IDENTIFYING",
+          47: "IDENTIFYING",
+          48: "WORD",
+          49: "open_directive",
+          50: "type_directive",
+          51: "arg_directive",
+          52: "close_directive",
+        },
+        productions_: [
+          0,
+          [3, 3],
+          [3, 2],
+          [5, 0],
+          [5, 2],
+          [8, 2],
+          [8, 1],
+          [8, 1],
+          [8, 1],
+          [7, 4],
+          [7, 6],
+          [10, 1],
+          [10, 5],
+          [10, 4],
+          [10, 3],
+          [10, 1],
+          [10, 2],
+          [10, 2],
+          [10, 2],
+          [10, 1],
+          [17, 1],
+          [17, 1],
+          [21, 1],
+          [21, 2],
+          [32, 2],
+          [32, 3],
+          [32, 3],
+          [32, 4],
+          [33, 1],
+          [34, 1],
+          [35, 1],
+          [36, 1],
+          [18, 3],
+          [40, 1],
+          [40, 1],
+          [40, 1],
+          [40, 1],
+          [41, 1],
+          [41, 1],
+          [19, 1],
+          [19, 1],
+          [19, 1],
+          [12, 1],
+          [13, 1],
+          [16, 1],
+          [14, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 1:
+              break;
+            case 3:
+            case 7:
+            case 8:
+              this.$ = [];
+              break;
+            case 4:
+              a[o - 1].push(a[o]), this.$ = a[o - 1];
+              break;
+            case 5:
+            case 6:
+            case 20:
+            case 41:
+            case 28:
+            case 29:
+            case 30:
+              this.$ = a[o];
+              break;
+            case 12:
+              i.addEntity(a[o - 4]), i.addEntity(a[o - 2]), i.addRelationship(a[o - 4], a[o], a[o - 2], a[o - 3]);
+              break;
+            case 13:
+              i.addEntity(a[o - 3]), i.addAttributes(a[o - 3], a[o - 1]);
+              break;
+            case 14:
+              i.addEntity(a[o - 2]);
+              break;
+            case 15:
+              i.addEntity(a[o]);
+              break;
+            case 16:
+            case 17:
+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 18:
+            case 19:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 21:
+            case 39:
+            case 40:
+            case 31:
+              this.$ = a[o].replace(/"/g, "");
+              break;
+            case 22:
+              this.$ = [a[o]];
+              break;
+            case 23:
+              a[o].push(a[o - 1]), this.$ = a[o];
+              break;
+            case 24:
+              this.$ = { attributeType: a[o - 1], attributeName: a[o] };
+              break;
+            case 25:
+              this.$ = { attributeType: a[o - 2], attributeName: a[o - 1], attributeKeyType: a[o] };
+              break;
+            case 26:
+              this.$ = { attributeType: a[o - 2], attributeName: a[o - 1], attributeComment: a[o] };
+              break;
+            case 27:
+              this.$ = {
+                attributeType: a[o - 3],
+                attributeName: a[o - 2],
+                attributeKeyType: a[o - 1],
+                attributeComment: a[o],
+              };
+              break;
+            case 32:
+              this.$ = { cardA: a[o], relType: a[o - 1], cardB: a[o - 2] };
+              break;
+            case 33:
+              this.$ = i.Cardinality.ZERO_OR_ONE;
+              break;
+            case 34:
+              this.$ = i.Cardinality.ZERO_OR_MORE;
+              break;
+            case 35:
+              this.$ = i.Cardinality.ONE_OR_MORE;
+              break;
+            case 36:
+              this.$ = i.Cardinality.ONLY_ONE;
+              break;
+            case 37:
+              this.$ = i.Identification.NON_IDENTIFYING;
+              break;
+            case 38:
+              this.$ = i.Identification.IDENTIFYING;
+              break;
+            case 42:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 43:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 44:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 45:
+              i.parseDirective("}%%", "close_directive", "er");
+          }
+        },
+        table: [
+          { 3: 1, 4: n, 7: 3, 12: 4, 49: i },
+          { 1: [3] },
+          e(r, [2, 3], { 5: 6 }),
+          { 3: 7, 4: n, 7: 3, 12: 4, 49: i },
+          { 13: 8, 50: [1, 9] },
+          { 50: [2, 42] },
+          {
+            6: [1, 10],
+            7: 15,
+            8: 11,
+            9: [1, 12],
+            10: 13,
+            11: [1, 14],
+            12: 4,
+            17: 16,
+            23: a,
+            25: s,
+            27: o,
+            29: l,
+            30: c,
+            31: h,
+            49: i,
+          },
+          { 1: [2, 2] },
+          { 14: 23, 15: [1, 24], 52: u },
+          e([15, 52], [2, 43]),
+          e(r, [2, 8], { 1: [2, 1] }),
+          e(r, [2, 4]),
+          { 7: 15, 10: 26, 12: 4, 17: 16, 23: a, 25: s, 27: o, 29: l, 30: c, 31: h, 49: i },
+          e(r, [2, 6]),
+          e(r, [2, 7]),
+          e(r, [2, 11]),
+          e(r, [2, 15], { 18: 27, 40: 29, 20: [1, 28], 42: d, 43: p, 44: f, 45: g }),
+          { 24: [1, 34] },
+          { 26: [1, 35] },
+          { 28: [1, 36] },
+          e(r, [2, 19]),
+          e(y, [2, 20]),
+          e(y, [2, 21]),
+          { 11: [1, 37] },
+          { 16: 38, 51: [1, 39] },
+          { 11: [2, 45] },
+          e(r, [2, 5]),
+          { 17: 40, 30: c, 31: h },
+          { 21: 41, 22: [1, 42], 32: 43, 33: 44, 37: m },
+          { 41: 46, 46: [1, 47], 47: [1, 48] },
+          e(b, [2, 33]),
+          e(b, [2, 34]),
+          e(b, [2, 35]),
+          e(b, [2, 36]),
+          e(r, [2, 16]),
+          e(r, [2, 17]),
+          e(r, [2, 18]),
+          e(_, [2, 9]),
+          { 14: 49, 52: u },
+          { 52: [2, 44] },
+          { 15: [1, 50] },
+          { 22: [1, 51] },
+          e(r, [2, 14]),
+          { 21: 52, 22: [2, 22], 32: 43, 33: 44, 37: m },
+          { 34: 53, 37: [1, 54] },
+          { 37: [2, 28] },
+          { 40: 55, 42: d, 43: p, 44: f, 45: g },
+          e(x, [2, 37]),
+          e(x, [2, 38]),
+          { 11: [1, 56] },
+          { 19: 57, 30: [1, 60], 31: [1, 59], 48: [1, 58] },
+          e(r, [2, 13]),
+          { 22: [2, 23] },
+          e(v, [2, 24], { 35: 61, 36: 62, 38: [1, 63], 39: k }),
+          e([22, 37, 38, 39], [2, 29]),
+          e([30, 31], [2, 32]),
+          e(_, [2, 10]),
+          e(r, [2, 12]),
+          e(r, [2, 39]),
+          e(r, [2, 40]),
+          e(r, [2, 41]),
+          e(v, [2, 25], { 36: 65, 39: k }),
+          e(v, [2, 26]),
+          e([22, 37, 39], [2, 30]),
+          e(v, [2, 31]),
+          e(v, [2, 27]),
+        ],
+        defaultActions: { 5: [2, 42], 7: [2, 2], 25: [2, 45], 39: [2, 44], 45: [2, 28], 52: [2, 23] },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      T = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: { "case-insensitive": !0 },
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("acc_title"), 25;
+            case 1:
+              return this.popState(), "acc_title_value";
+            case 2:
+              return this.begin("acc_descr"), 27;
+            case 3:
+              return this.popState(), "acc_descr_value";
+            case 4:
+              this.begin("acc_descr_multiline");
+              break;
+            case 5:
+              this.popState();
+              break;
+            case 6:
+              return "acc_descr_multiline_value";
+            case 7:
+              return this.begin("open_directive"), 49;
+            case 8:
+              return this.begin("type_directive"), 50;
+            case 9:
+              return this.popState(), this.begin("arg_directive"), 15;
+            case 10:
+              return this.popState(), this.popState(), 52;
+            case 11:
+              return 51;
+            case 12:
+            case 13:
+            case 15:
+            case 21:
+            case 26:
+              break;
+            case 14:
+              return 11;
+            case 16:
+              return 9;
+            case 17:
+              return 31;
+            case 18:
+              return 48;
+            case 19:
+              return 4;
+            case 20:
+              return this.begin("block"), 20;
+            case 22:
+              return 38;
+            case 23:
+            case 24:
+              return 37;
+            case 25:
+              return 39;
+            case 27:
+              return this.popState(), 22;
+            case 28:
+            case 57:
+              return e.yytext[0];
+            case 29:
+            case 33:
+            case 34:
+            case 47:
+              return 42;
+            case 30:
+            case 31:
+            case 32:
+            case 40:
+            case 42:
+            case 49:
+              return 44;
+            case 35:
+            case 36:
+            case 37:
+            case 38:
+            case 39:
+            case 41:
+            case 48:
+              return 43;
+            case 43:
+            case 44:
+            case 45:
+            case 46:
+              return 45;
+            case 50:
+            case 53:
+            case 54:
+            case 55:
+              return 46;
+            case 51:
+            case 52:
+              return 47;
+            case 56:
+              return 30;
+            case 58:
+              return 6;
+          }
+        },
+        rules: [
+          /^(?:accTitle\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*\{\s*)/i,
+          /^(?:[\}])/i,
+          /^(?:[^\}]*)/i,
+          /^(?:%%\{)/i,
+          /^(?:((?:(?!\}%%)[^:.])*))/i,
+          /^(?::)/i,
+          /^(?:\}%%)/i,
+          /^(?:((?:(?!\}%%).|\n)*))/i,
+          /^(?:%(?!\{)[^\n]*)/i,
+          /^(?:[^\}]%%[^\n]*)/i,
+          /^(?:[\n]+)/i,
+          /^(?:\s+)/i,
+          /^(?:[\s]+)/i,
+          /^(?:"[^"%\r\n\v\b\\]+")/i,
+          /^(?:"[^"]*")/i,
+          /^(?:erDiagram\b)/i,
+          /^(?:\{)/i,
+          /^(?:\s+)/i,
+          /^(?:\b((?:PK)|(?:FK))\b)/i,
+          /^(?:(.*?)[~](.*?)*[~])/i,
+          /^(?:[A-Za-z][A-Za-z0-9\-_\[\]]*)/i,
+          /^(?:"[^"]*")/i,
+          /^(?:[\n]+)/i,
+          /^(?:\})/i,
+          /^(?:.)/i,
+          /^(?:one or zero\b)/i,
+          /^(?:one or more\b)/i,
+          /^(?:one or many\b)/i,
+          /^(?:1\+)/i,
+          /^(?:\|o\b)/i,
+          /^(?:zero or one\b)/i,
+          /^(?:zero or more\b)/i,
+          /^(?:zero or many\b)/i,
+          /^(?:0\+)/i,
+          /^(?:\}o\b)/i,
+          /^(?:many\(0\))/i,
+          /^(?:many\(1\))/i,
+          /^(?:many\b)/i,
+          /^(?:\}\|)/i,
+          /^(?:one\b)/i,
+          /^(?:only one\b)/i,
+          /^(?:1\b)/i,
+          /^(?:\|\|)/i,
+          /^(?:o\|)/i,
+          /^(?:o\{)/i,
+          /^(?:\|\{)/i,
+          /^(?:\.\.)/i,
+          /^(?:--)/i,
+          /^(?:to\b)/i,
+          /^(?:optionally to\b)/i,
+          /^(?:\.-)/i,
+          /^(?:-\.)/i,
+          /^(?:[A-Za-z][A-Za-z0-9\-_]*)/i,
+          /^(?:.)/i,
+          /^(?:$)/i,
+        ],
+        conditions: {
+          acc_descr_multiline: { rules: [5, 6], inclusive: !1 },
+          acc_descr: { rules: [3], inclusive: !1 },
+          acc_title: { rules: [1], inclusive: !1 },
+          open_directive: { rules: [8], inclusive: !1 },
+          type_directive: { rules: [9, 10], inclusive: !1 },
+          arg_directive: { rules: [10, 11], inclusive: !1 },
+          block: { rules: [21, 22, 23, 24, 25, 26, 27, 28], inclusive: !1 },
+          INITIAL: {
+            rules: [
+              0,
+              2,
+              4,
+              7,
+              12,
+              13,
+              14,
+              15,
+              16,
+              17,
+              18,
+              19,
+              20,
+              29,
+              30,
+              31,
+              32,
+              33,
+              34,
+              35,
+              36,
+              37,
+              38,
+              39,
+              40,
+              41,
+              42,
+              43,
+              44,
+              45,
+              46,
+              47,
+              48,
+              49,
+              50,
+              51,
+              52,
+              53,
+              54,
+              55,
+              56,
+              57,
+              58,
+            ],
+            inclusive: !0,
+          },
+        },
+      },
+        t);
+    function C() {
+      this.yy = {};
+    }
+    return w.lexer = T, C.prototype = w, w.Parser = C, new C();
+  }();
+  TT.parser = TT;
+  const CT = TT, ET = t => null !== t.match(/^\s*erDiagram/);
+  let ST = {}, AT = [];
+  const DT = function(t) {
+      return void 0 === ST[t] && (ST[t] = { attributes: [] }, tb.info("Added new entity :", t)), ST[t];
+    },
+    LT = {
+      Cardinality: {
+        ZERO_OR_ONE: "ZERO_OR_ONE",
+        ZERO_OR_MORE: "ZERO_OR_MORE",
+        ONE_OR_MORE: "ONE_OR_MORE",
+        ONLY_ONE: "ONLY_ONE",
+      },
+      Identification: { NON_IDENTIFYING: "NON_IDENTIFYING", IDENTIFYING: "IDENTIFYING" },
+      parseDirective: function(t, e, n) {
+        nL.parseDirective(this, t, e, n);
+      },
+      getConfig: () => jx().er,
+      addEntity: DT,
+      addAttributes: function(t, e) {
+        let n, i = DT(t);
+        for (n = e.length - 1; n >= 0; n--) i.attributes.push(e[n]), tb.debug("Added attribute ", e[n].attributeName);
+      },
+      getEntities: () => ST,
+      addRelationship: function(t, e, n, i) {
+        let r = { entityA: t, roleA: e, entityB: n, relSpec: i };
+        AT.push(r), tb.debug("Added new relationship :", r);
+      },
+      getRelationships: () => AT,
+      clear: function() {
+        ST = {}, AT = [], Cv();
+      },
+      setAccTitle: Ev,
+      getAccTitle: Sv,
+      setAccDescription: Av,
+      getAccDescription: Dv,
+      setDiagramTitle: Lv,
+      getDiagramTitle: Ov,
+    },
+    OT = {
+      ONLY_ONE_START: "ONLY_ONE_START",
+      ONLY_ONE_END: "ONLY_ONE_END",
+      ZERO_OR_ONE_START: "ZERO_OR_ONE_START",
+      ZERO_OR_ONE_END: "ZERO_OR_ONE_END",
+      ONE_OR_MORE_START: "ONE_OR_MORE_START",
+      ONE_OR_MORE_END: "ONE_OR_MORE_END",
+      ZERO_OR_MORE_START: "ZERO_OR_MORE_START",
+      ZERO_OR_MORE_END: "ZERO_OR_MORE_END",
+    },
+    NT = OT,
+    MT = function(t, e) {
+      let n;
+      t.append("defs").append("marker").attr("id", OT.ONLY_ONE_START).attr("refX", 0).attr("refY", 9).attr(
+        "markerWidth",
+        18,
+      ).attr("markerHeight", 18).attr("orient", "auto").append("path").attr("stroke", e.stroke).attr("fill", "none")
+        .attr("d", "M9,0 L9,18 M15,0 L15,18"),
+        t.append("defs").append("marker").attr("id", OT.ONLY_ONE_END).attr("refX", 18).attr("refY", 9).attr(
+          "markerWidth",
+          18,
+        ).attr("markerHeight", 18).attr("orient", "auto").append("path").attr("stroke", e.stroke).attr("fill", "none")
+          .attr("d", "M3,0 L3,18 M9,0 L9,18"),
+        n = t.append("defs").append("marker").attr("id", OT.ZERO_OR_ONE_START).attr("refX", 0).attr("refY", 9).attr(
+          "markerWidth",
+          30,
+        ).attr("markerHeight", 18).attr("orient", "auto"),
+        n.append("circle").attr("stroke", e.stroke).attr("fill", "white").attr("cx", 21).attr("cy", 9).attr("r", 6),
+        n.append("path").attr("stroke", e.stroke).attr("fill", "none").attr("d", "M9,0 L9,18"),
+        n = t.append("defs").append("marker").attr("id", OT.ZERO_OR_ONE_END).attr("refX", 30).attr("refY", 9).attr(
+          "markerWidth",
+          30,
+        ).attr("markerHeight", 18).attr("orient", "auto"),
+        n.append("circle").attr("stroke", e.stroke).attr("fill", "white").attr("cx", 9).attr("cy", 9).attr("r", 6),
+        n.append("path").attr("stroke", e.stroke).attr("fill", "none").attr("d", "M21,0 L21,18"),
+        t.append("defs").append("marker").attr("id", OT.ONE_OR_MORE_START).attr("refX", 18).attr("refY", 18).attr(
+          "markerWidth",
+          45,
+        ).attr("markerHeight", 36).attr("orient", "auto").append("path").attr("stroke", e.stroke).attr("fill", "none")
+          .attr("d", "M0,18 Q 18,0 36,18 Q 18,36 0,18 M42,9 L42,27"),
+        t.append("defs").append("marker").attr("id", OT.ONE_OR_MORE_END).attr("refX", 27).attr("refY", 18).attr(
+          "markerWidth",
+          45,
+        ).attr("markerHeight", 36).attr("orient", "auto").append("path").attr("stroke", e.stroke).attr("fill", "none")
+          .attr("d", "M3,9 L3,27 M9,18 Q27,0 45,18 Q27,36 9,18"),
+        n = t.append("defs").append("marker").attr("id", OT.ZERO_OR_MORE_START).attr("refX", 18).attr("refY", 18).attr(
+          "markerWidth",
+          57,
+        ).attr("markerHeight", 36).attr("orient", "auto"),
+        n.append("circle").attr("stroke", e.stroke).attr("fill", "white").attr("cx", 48).attr("cy", 18).attr("r", 6),
+        n.append("path").attr("stroke", e.stroke).attr("fill", "none").attr("d", "M0,18 Q18,0 36,18 Q18,36 0,18"),
+        n = t.append("defs").append("marker").attr("id", OT.ZERO_OR_MORE_END).attr("refX", 39).attr("refY", 18).attr(
+          "markerWidth",
+          57,
+        ).attr("markerHeight", 36).attr("orient", "auto"),
+        n.append("circle").attr("stroke", e.stroke).attr("fill", "white").attr("cx", 9).attr("cy", 18).attr("r", 6),
+        n.append("path").attr("stroke", e.stroke).attr("fill", "none").attr("d", "M21,18 Q39,0 57,18 Q39,36 21,18");
+    },
+    BT = /[^\dA-Za-z](\W)*/g;
+  let IT = {}, FT = new Map();
+  const RT = function(t, e, n) {
+      let i;
+      return Object.keys(e).forEach(function(r) {
+        const a = function(t = "", e = "") {
+          const n = t.replace(BT, "");
+          return `${YT(e)}${YT(n)}${Gm()}`;
+        }(r, "entity");
+        FT.set(r, a);
+        const s = t.append("g").attr("id", a);
+        i = void 0 === i ? a : i;
+        const o = "text-" + a,
+          l = s.append("text").classed("er entityLabel", !0).attr("id", o).attr("x", 0).attr("y", 0).style(
+            "dominant-baseline",
+            "middle",
+          ).style("text-anchor", "middle").style("font-family", jx().fontFamily).style("font-size", IT.fontSize + "px")
+            .text(r),
+          { width: c, height: h } = ((t, e, n) => {
+            const i = IT.entityPadding / 3,
+              r = IT.entityPadding / 3,
+              a = .85 * IT.fontSize,
+              s = e.node().getBBox(),
+              o = [];
+            let l = !1, c = !1, h = 0, u = 0, d = 0, p = 0, f = s.height + 2 * i, g = 1;
+            n.forEach(t => {
+              void 0 !== t.attributeKeyType && (l = !0), void 0 !== t.attributeComment && (c = !0);
+            }),
+              n.forEach(n => {
+                const r = `${e.node().id}-attr-${g}`;
+                let s = 0;
+                const y = hb(n.attributeType),
+                  m = t.append("text").classed("er entityLabel", !0).attr("id", `${r}-type`).attr("x", 0).attr("y", 0)
+                    .style("dominant-baseline", "middle").style("text-anchor", "left").style(
+                      "font-family",
+                      jx().fontFamily,
+                    ).style("font-size", a + "px").text(y),
+                  b = t.append("text").classed("er entityLabel", !0).attr("id", `${r}-name`).attr("x", 0).attr("y", 0)
+                    .style("dominant-baseline", "middle").style("text-anchor", "left").style(
+                      "font-family",
+                      jx().fontFamily,
+                    ).style("font-size", a + "px").text(n.attributeName),
+                  _ = {};
+                _.tn = m, _.nn = b;
+                const x = m.node().getBBox(), v = b.node().getBBox();
+                if (h = Math.max(h, x.width), u = Math.max(u, v.width), s = Math.max(x.height, v.height), l) {
+                  const e = t.append("text").classed("er entityLabel", !0).attr("id", `${r}-key`).attr("x", 0).attr(
+                    "y",
+                    0,
+                  ).style("dominant-baseline", "middle").style("text-anchor", "left").style(
+                    "font-family",
+                    jx().fontFamily,
+                  ).style("font-size", a + "px").text(n.attributeKeyType || "");
+                  _.kn = e;
+                  const i = e.node().getBBox();
+                  d = Math.max(d, i.width), s = Math.max(s, i.height);
+                }
+                if (c) {
+                  const e = t.append("text").classed("er entityLabel", !0).attr("id", `${r}-comment`).attr("x", 0).attr(
+                    "y",
+                    0,
+                  ).style("dominant-baseline", "middle").style("text-anchor", "left").style(
+                    "font-family",
+                    jx().fontFamily,
+                  ).style("font-size", a + "px").text(n.attributeComment || "");
+                  _.cn = e;
+                  const i = e.node().getBBox();
+                  p = Math.max(p, i.width), s = Math.max(s, i.height);
+                }
+                _.height = s, o.push(_), f += s + 2 * i, g += 1;
+              });
+            let y = 4;
+            l && (y += 2), c && (y += 2);
+            const m = h + u + d + p,
+              b = {
+                width: Math.max(IT.minEntityWidth, Math.max(s.width + 2 * IT.entityPadding, m + r * y)),
+                height: n.length > 0 ? f : Math.max(IT.minEntityHeight, s.height + 2 * IT.entityPadding),
+              };
+            if (n.length > 0) {
+              const n = Math.max(0, (b.width - m - r * y) / (y / 2));
+              e.attr("transform", "translate(" + b.width / 2 + "," + (i + s.height / 2) + ")");
+              let a = s.height + 2 * i, f = "attributeBoxOdd";
+              o.forEach(e => {
+                const s = a + i + e.height / 2;
+                e.tn.attr("transform", "translate(" + r + "," + s + ")");
+                const o = t.insert("rect", "#" + e.tn.node().id).classed(`er ${f}`, !0).attr("x", 0).attr("y", a).attr(
+                    "width",
+                    h + 2 * r + n,
+                  ).attr("height", e.height + 2 * i),
+                  g = parseFloat(o.attr("x")) + parseFloat(o.attr("width"));
+                e.nn.attr("transform", "translate(" + (g + r) + "," + s + ")");
+                const y = t.insert("rect", "#" + e.nn.node().id).classed(`er ${f}`, !0).attr("x", g).attr("y", a).attr(
+                  "width",
+                  u + 2 * r + n,
+                ).attr("height", e.height + 2 * i);
+                let m = parseFloat(y.attr("x")) + parseFloat(y.attr("width"));
+                if (l) {
+                  e.kn.attr("transform", "translate(" + (m + r) + "," + s + ")");
+                  const o = t.insert("rect", "#" + e.kn.node().id).classed(`er ${f}`, !0).attr("x", m).attr("y", a)
+                    .attr("width", d + 2 * r + n).attr("height", e.height + 2 * i);
+                  m = parseFloat(o.attr("x")) + parseFloat(o.attr("width"));
+                }
+                c
+                && (e.cn.attr("transform", "translate(" + (m + r) + "," + s + ")"),
+                  t.insert("rect", "#" + e.cn.node().id).classed(`er ${f}`, "true").attr("x", m).attr("y", a).attr(
+                    "width",
+                    p + 2 * r + n,
+                  ).attr("height", e.height + 2 * i)),
+                  a += e.height + 2 * i,
+                  f = "attributeBoxOdd" === f ? "attributeBoxEven" : "attributeBoxOdd";
+              });
+            } else {b.height = Math.max(IT.minEntityHeight, f),
+                e.attr("transform", "translate(" + b.width / 2 + "," + b.height / 2 + ")");}
+            return b;
+          })(s, l, e[r].attributes),
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+          [34, 5],
+          [34, 5],
+          [34, 9],
+          [34, 9],
+          [34, 7],
+          [34, 7],
+          [103, 1],
+          [103, 3],
+          [96, 1],
+          [96, 3],
+          [107, 1],
+          [107, 2],
+          [108, 1],
+          [108, 1],
+          [108, 1],
+          [108, 1],
+          [108, 1],
+          [108, 1],
+          [108, 1],
+          [108, 1],
+          [108, 1],
+          [108, 1],
+          [108, 1],
+          [83, 1],
+          [83, 1],
+          [83, 1],
+          [83, 1],
+          [83, 1],
+          [83, 1],
+          [94, 1],
+          [94, 1],
+          [94, 1],
+          [94, 1],
+          [54, 1],
+          [54, 2],
+          [97, 1],
+          [97, 2],
+          [117, 1],
+          [117, 1],
+          [117, 1],
+          [117, 1],
+          [43, 1],
+          [43, 1],
+          [43, 1],
+          [43, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [115, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [116, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+          [128, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 5:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 6:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 7:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 8:
+              i.parseDirective("}%%", "close_directive", "flowchart");
+              break;
+            case 10:
+            case 36:
+            case 37:
+            case 38:
+            case 39:
+            case 40:
+              this.$ = [];
+              break;
+            case 11:
+              (!Array.isArray(a[o]) || a[o].length > 0) && a[o - 1].push(a[o]), this.$ = a[o - 1];
+              break;
+            case 12:
+            case 82:
+            case 84:
+            case 96:
+            case 152:
+            case 154:
+            case 155:
+            case 78:
+            case 150:
+              this.$ = a[o];
+              break;
+            case 19:
+              i.setDirection("TB"), this.$ = "TB";
+              break;
+            case 20:
+              i.setDirection(a[o - 1]), this.$ = a[o - 1];
+              break;
+            case 35:
+              this.$ = a[o - 1].nodes;
+              break;
+            case 41:
+              this.$ = i.addSubGraph(a[o - 6], a[o - 1], a[o - 4]);
+              break;
+            case 42:
+              this.$ = i.addSubGraph(a[o - 3], a[o - 1], a[o - 3]);
+              break;
+            case 43:
+              this.$ = i.addSubGraph(void 0, a[o - 1], void 0);
+              break;
+            case 45:
+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 46:
+            case 47:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 51:
+              i.addLink(a[o - 2].stmt, a[o], a[o - 1]), this.$ = { stmt: a[o], nodes: a[o].concat(a[o - 2].nodes) };
+              break;
+            case 52:
+              i.addLink(a[o - 3].stmt, a[o - 1], a[o - 2]),
+                this.$ = { stmt: a[o - 1], nodes: a[o - 1].concat(a[o - 3].nodes) };
+              break;
+            case 53:
+              this.$ = { stmt: a[o - 1], nodes: a[o - 1] };
+              break;
+            case 54:
+              this.$ = { stmt: a[o], nodes: a[o] };
+              break;
+            case 55:
+            case 123:
+            case 125:
+              this.$ = [a[o]];
+              break;
+            case 56:
+              this.$ = a[o - 4].concat(a[o]);
+              break;
+            case 57:
+              this.$ = [a[o - 2]], i.setClass(a[o - 2], a[o]);
+              break;
+            case 58:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "square");
+              break;
+            case 59:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "doublecircle");
+              break;
+            case 60:
+              this.$ = a[o - 5], i.addVertex(a[o - 5], a[o - 2], "circle");
+              break;
+            case 61:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "ellipse");
+              break;
+            case 62:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "stadium");
+              break;
+            case 63:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "subroutine");
+              break;
+            case 64:
+              this.$ = a[o - 7],
+                i.addVertex(
+                  a[o - 7],
+                  a[o - 1],
+                  "rect",
+                  void 0,
+                  void 0,
+                  void 0,
+                  Object.fromEntries([[a[o - 5], a[o - 3]]]),
+                );
+              break;
+            case 65:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "cylinder");
+              break;
+            case 66:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "round");
+              break;
+            case 67:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "diamond");
+              break;
+            case 68:
+              this.$ = a[o - 5], i.addVertex(a[o - 5], a[o - 2], "hexagon");
+              break;
+            case 69:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "odd");
+              break;
+            case 70:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "trapezoid");
+              break;
+            case 71:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "inv_trapezoid");
+              break;
+            case 72:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "lean_right");
+              break;
+            case 73:
+              this.$ = a[o - 3], i.addVertex(a[o - 3], a[o - 1], "lean_left");
+              break;
+            case 74:
+              this.$ = a[o], i.addVertex(a[o]);
+              break;
+            case 75:
+              a[o - 1].text = a[o], this.$ = a[o - 1];
+              break;
+            case 76:
+            case 77:
+              a[o - 2].text = a[o - 1], this.$ = a[o - 2];
+              break;
+            case 79:
+              var l = i.destructLink(a[o], a[o - 2]);
+              this.$ = { type: l.type, stroke: l.stroke, length: l.length, text: a[o - 1] };
+              break;
+            case 80:
+              l = i.destructLink(a[o]);
+              this.$ = { type: l.type, stroke: l.stroke, length: l.length };
+              break;
+            case 81:
+              this.$ = a[o - 1];
+              break;
+            case 83:
+            case 97:
+            case 153:
+            case 151:
+              this.$ = a[o - 1] + "" + a[o];
+              break;
+            case 98:
+            case 99:
+              this.$ = a[o - 4], i.addClass(a[o - 2], a[o]);
+              break;
+            case 100:
+              this.$ = a[o - 4], i.setClass(a[o - 2], a[o]);
+              break;
+            case 101:
+            case 109:
+              this.$ = a[o - 1], i.setClickEvent(a[o - 1], a[o]);
+              break;
+            case 102:
+            case 110:
+              this.$ = a[o - 3], i.setClickEvent(a[o - 3], a[o - 2]), i.setTooltip(a[o - 3], a[o]);
+              break;
+            case 103:
+              this.$ = a[o - 2], i.setClickEvent(a[o - 2], a[o - 1], a[o]);
+              break;
+            case 104:
+              this.$ = a[o - 4], i.setClickEvent(a[o - 4], a[o - 3], a[o - 2]), i.setTooltip(a[o - 4], a[o]);
+              break;
+            case 105:
+            case 111:
+              this.$ = a[o - 1], i.setLink(a[o - 1], a[o]);
+              break;
+            case 106:
+            case 112:
+              this.$ = a[o - 3], i.setLink(a[o - 3], a[o - 2]), i.setTooltip(a[o - 3], a[o]);
+              break;
+            case 107:
+            case 113:
+              this.$ = a[o - 3], i.setLink(a[o - 3], a[o - 2], a[o]);
+              break;
+            case 108:
+            case 114:
+              this.$ = a[o - 5], i.setLink(a[o - 5], a[o - 4], a[o]), i.setTooltip(a[o - 5], a[o - 2]);
+              break;
+            case 115:
+              this.$ = a[o - 4], i.addVertex(a[o - 2], void 0, void 0, a[o]);
+              break;
+            case 116:
+            case 118:
+              this.$ = a[o - 4], i.updateLink(a[o - 2], a[o]);
+              break;
+            case 117:
+              this.$ = a[o - 4], i.updateLink([a[o - 2]], a[o]);
+              break;
+            case 119:
+              this.$ = a[o - 8], i.updateLinkInterpolate([a[o - 6]], a[o - 2]), i.updateLink([a[o - 6]], a[o]);
+              break;
+            case 120:
+              this.$ = a[o - 8], i.updateLinkInterpolate(a[o - 6], a[o - 2]), i.updateLink(a[o - 6], a[o]);
+              break;
+            case 121:
+              this.$ = a[o - 6], i.updateLinkInterpolate([a[o - 4]], a[o]);
+              break;
+            case 122:
+              this.$ = a[o - 6], i.updateLinkInterpolate(a[o - 4], a[o]);
+              break;
+            case 124:
+            case 126:
+              a[o - 2].push(a[o]), this.$ = a[o - 2];
+              break;
+            case 128:
+              this.$ = a[o - 1] + a[o];
+              break;
+            case 156:
+              this.$ = "v";
+              break;
+            case 157:
+              this.$ = "-";
+              break;
+            case 158:
+              this.$ = { stmt: "dir", value: "TB" };
+              break;
+            case 159:
+              this.$ = { stmt: "dir", value: "BT" };
+              break;
+            case 160:
+              this.$ = { stmt: "dir", value: "RL" };
+              break;
+            case 161:
+              this.$ = { stmt: "dir", value: "LR" };
+          }
+        },
+        table: [
+          { 3: 1, 4: 2, 5: 3, 6: 5, 12: n, 16: 4, 21: i, 22: r, 24: a },
+          { 1: [3] },
+          { 1: [2, 1] },
+          { 3: 10, 4: 2, 5: 3, 6: 5, 12: n, 16: 4, 21: i, 22: r, 24: a },
+          e(s, o, { 17: 11 }),
+          { 7: 12, 13: [1, 13] },
+          { 16: 14, 21: i, 22: r, 24: a },
+          { 16: 15, 21: i, 22: r, 24: a },
+          { 25: [1, 16], 26: [1, 17] },
+          { 13: [2, 5] },
+          { 1: [2, 2] },
+          {
+            1: [2, 9],
+            18: 18,
+            19: 19,
+            20: l,
+            21: c,
+            22: h,
+            23: u,
+            32: 24,
+            33: 25,
+            34: 26,
+            35: 27,
+            36: 28,
+            37: 29,
+            38: d,
+            43: 31,
+            44: p,
+            46: f,
+            48: g,
+            50: 35,
+            51: 45,
+            52: y,
+            54: 46,
+            66: m,
+            67: b,
+            86: _,
+            87: x,
+            88: v,
+            89: k,
+            90: w,
+            91: T,
+            95: C,
+            105: E,
+            106: S,
+            109: A,
+            111: D,
+            112: L,
+            116: 47,
+            118: O,
+            119: N,
+            120: M,
+            121: B,
+            122: I,
+            123: F,
+            124: R,
+            125: $,
+            126: P,
+            127: Y,
+          },
+          { 8: 64, 10: [1, 65], 15: j },
+          e([10, 15], [2, 6]),
+          e(s, [2, 17]),
+          e(s, [2, 18]),
+          e(s, [2, 19]),
+          { 20: [1, 68], 21: [1, 69], 22: z, 27: 67, 30: 70 },
+          e(U, [2, 11]),
+          e(U, [2, 12]),
+          e(U, [2, 13]),
+          e(U, [2, 14]),
+          e(U, [2, 15]),
+          e(U, [2, 16]),
+          { 9: 72, 20: W, 21: H, 23: q, 49: 73, 78: 77, 81: [1, 78], 82: [1, 79] },
+          { 9: 80, 20: W, 21: H, 23: q },
+          { 9: 81, 20: W, 21: H, 23: q },
+          { 9: 82, 20: W, 21: H, 23: q },
+          { 9: 83, 20: W, 21: H, 23: q },
+          { 9: 84, 20: W, 21: H, 23: q },
+          { 9: 86, 20: W, 21: H, 22: [1, 85], 23: q },
+          e(U, [2, 44]),
+          { 45: [1, 87] },
+          { 47: [1, 88] },
+          e(U, [2, 47]),
+          e(V, [2, 54], { 30: 89, 22: z }),
+          { 22: [1, 90] },
+          { 22: [1, 91] },
+          { 22: [1, 92] },
+          { 22: [1, 93] },
+          {
+            26: G,
+            52: X,
+            66: Z,
+            67: Q,
+            84: [1, 97],
+            91: K,
+            97: 96,
+            98: [1, 94],
+            100: [1, 95],
+            105: J,
+            106: tt,
+            109: et,
+            111: nt,
+            112: it,
+            115: 100,
+            117: 98,
+            122: rt,
+            123: at,
+            124: st,
+            125: ot,
+            126: lt,
+            127: ct,
+          },
+          e(U, [2, 158]),
+          e(U, [2, 159]),
+          e(U, [2, 160]),
+          e(U, [2, 161]),
+          e(ht, [2, 55], { 53: [1, 116] }),
+          e(ut, [2, 74], {
+            116: 129,
+            40: [1, 117],
+            52: y,
+            55: [1, 118],
+            57: [1, 119],
+            59: [1, 120],
+            61: [1, 121],
+            63: [1, 122],
+            65: [1, 123],
+            66: m,
+            67: b,
+            69: [1, 124],
+            71: [1, 125],
+            73: [1, 126],
+            74: [1, 127],
+            76: [1, 128],
+            91: T,
+            95: C,
+            105: E,
+            106: S,
+            109: A,
+            111: D,
+            112: L,
+            122: I,
+            123: F,
+            124: R,
+            125: $,
+            126: P,
+            127: Y,
+          }),
+          e(dt, [2, 150]),
+          e(dt, [2, 175]),
+          e(dt, [2, 176]),
+          e(dt, [2, 177]),
+          e(dt, [2, 178]),
+          e(dt, [2, 179]),
+          e(dt, [2, 180]),
+          e(dt, [2, 181]),
+          e(dt, [2, 182]),
+          e(dt, [2, 183]),
+          e(dt, [2, 184]),
+          e(dt, [2, 185]),
+          e(dt, [2, 186]),
+          e(dt, [2, 187]),
+          e(dt, [2, 188]),
+          e(dt, [2, 189]),
+          e(dt, [2, 190]),
+          { 9: 130, 20: W, 21: H, 23: q },
+          { 11: 131, 14: [1, 132] },
+          e(pt, [2, 8]),
+          e(s, [2, 20]),
+          e(s, [2, 26]),
+          e(s, [2, 27]),
+          { 21: [1, 133] },
+          e(ft, [2, 34], { 30: 134, 22: z }),
+          e(U, [2, 35]),
+          {
+            50: 135,
+            51: 45,
+            52: y,
+            54: 46,
+            66: m,
+            67: b,
+            91: T,
+            95: C,
+            105: E,
+            106: S,
+            109: A,
+            111: D,
+            112: L,
+            116: 47,
+            122: I,
+            123: F,
+            124: R,
+            125: $,
+            126: P,
+            127: Y,
+          },
+          e(gt, [2, 48]),
+          e(gt, [2, 49]),
+          e(gt, [2, 50]),
+          e(yt, [2, 78], { 79: 136, 68: [1, 138], 80: [1, 137] }),
+          {
+            22: mt,
+            24: bt,
+            26: _t,
+            38: xt,
+            39: 139,
+            42: vt,
+            52: X,
+            66: Z,
+            67: Q,
+            73: kt,
+            81: wt,
+            83: 140,
+            84: Tt,
+            85: 151,
+            86: Ct,
+            87: Et,
+            88: St,
+            89: At,
+            90: Dt,
+            91: Lt,
+            92: Ot,
+            94: 142,
+            95: Nt,
+            105: J,
+            106: tt,
+            109: Mt,
+            111: nt,
+            112: it,
+            113: Bt,
+            114: It,
+            115: 148,
+            122: rt,
+            123: at,
+            124: st,
+            125: ot,
+            126: lt,
+            127: ct,
+          },
+          e([52, 66, 67, 68, 80, 91, 95, 105, 106, 109, 111, 112, 122, 123, 124, 125, 126, 127], [2, 80]),
+          e(U, [2, 36]),
+          e(U, [2, 37]),
+          e(U, [2, 38]),
+          e(U, [2, 39]),
+          e(U, [2, 40]),
+          {
+            22: mt,
+            24: bt,
+            26: _t,
+            38: xt,
+            39: 163,
+            42: vt,
+            52: X,
+            66: Z,
+            67: Q,
+            73: kt,
+            81: wt,
+            83: 140,
+            84: Tt,
+            85: 151,
+            86: Ct,
+            87: Et,
+            88: St,
+            89: At,
+            90: Dt,
+            91: Lt,
+            92: Ot,
+            94: 142,
+            95: Nt,
+            105: J,
+            106: tt,
+            109: Mt,
+            111: nt,
+            112: it,
+            113: Bt,
+            114: It,
+            115: 148,
+            122: rt,
+            123: at,
+            124: st,
+            125: ot,
+            126: lt,
+            127: ct,
+          },
+          e(Ft, o, { 17: 164 }),
+          e(U, [2, 45]),
+          e(U, [2, 46]),
+          e(V, [2, 53], { 52: Rt }),
+          {
+            26: G,
+            52: X,
+            66: Z,
+            67: Q,
+            91: K,
+            97: 166,
+            102: [1, 167],
+            105: J,
+            106: tt,
+            109: et,
+            111: nt,
+            112: it,
+            115: 100,
+            117: 98,
+            122: rt,
+            123: at,
+            124: st,
+            125: ot,
+            126: lt,
+            127: ct,
+          },
+          { 95: [1, 168], 103: 169, 105: [1, 170] },
+          {
+            26: G,
+            52: X,
+            66: Z,
+            67: Q,
+            91: K,
+            95: [1, 171],
+            97: 172,
+            105: J,
+            106: tt,
+            109: et,
+            111: nt,
+            112: it,
+            115: 100,
+            117: 98,
+            122: rt,
+            123: at,
+            124: st,
+            125: ot,
+            126: lt,
+            127: ct,
+          },
+          {
+            26: G,
+            52: X,
+            66: Z,
+            67: Q,
+            91: K,
+            97: 173,
+            105: J,
+            106: tt,
+            109: et,
+            111: nt,
+            112: it,
+            115: 100,
+            117: 98,
+            122: rt,
+            123: at,
+            124: st,
+            125: ot,
+            126: lt,
+            127: ct,
+          },
+          e(pt, [2, 101], { 22: [1, 174], 99: [1, 175] }),
+          e(pt, [2, 105], { 22: [1, 176] }),
+          e(pt, [2, 109], {
+            115: 100,
+            117: 178,
+            22: [1, 177],
+            26: G,
+            52: X,
+            66: Z,
+            67: Q,
+            91: K,
+            105: J,
+            106: tt,
+            109: et,
+            111: nt,
+            112: it,
+            122: rt,
+            123: at,
+            124: st,
+            125: ot,
+            126: lt,
+            127: ct,
+          }),
+          e(pt, [2, 111], { 22: [1, 179] }),
+          e($t, [2, 152]),
+          e($t, [2, 154]),
+          e($t, [2, 155]),
+          e($t, [2, 156]),
+          e($t, [2, 157]),
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+            126: lt,
+            127: ct,
+          },
+          {
+            18: 18,
+            19: 19,
+            20: l,
+            21: c,
+            22: h,
+            23: u,
+            32: 24,
+            33: 25,
+            34: 26,
+            35: 27,
+            36: 28,
+            37: 29,
+            38: d,
+            42: [1, 291],
+            43: 31,
+            44: p,
+            46: f,
+            48: g,
+            50: 35,
+            51: 45,
+            52: y,
+            54: 46,
+            66: m,
+            67: b,
+            86: _,
+            87: x,
+            88: v,
+            89: k,
+            90: w,
+            91: T,
+            95: C,
+            105: E,
+            106: S,
+            109: A,
+            111: D,
+            112: L,
+            116: 47,
+            118: O,
+            119: N,
+            120: M,
+            121: B,
+            122: I,
+            123: F,
+            124: R,
+            125: $,
+            126: P,
+            127: Y,
+          },
+          {
+            22: zt,
+            66: Ut,
+            67: Wt,
+            86: Ht,
+            96: 292,
+            102: qt,
+            105: Vt,
+            107: 243,
+            108: 244,
+            109: Gt,
+            110: Xt,
+            111: Zt,
+            112: Qt,
+            113: Kt,
+          },
+          {
+            22: zt,
+            66: Ut,
+            67: Wt,
+            86: Ht,
+            96: 293,
+            102: qt,
+            105: Vt,
+            107: 243,
+            108: 244,
+            109: Gt,
+            110: Xt,
+            111: Zt,
+            112: Qt,
+            113: Kt,
+          },
+          e(ut, [2, 64]),
+          e(U, [2, 41]),
+          e(pt, [2, 119], { 106: Jt }),
+          e(pt, [2, 120], { 106: Jt }),
+        ],
+        defaultActions: { 2: [2, 1], 9: [2, 5], 10: [2, 2], 132: [2, 7] },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      ie = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: {},
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("open_directive"), 12;
+            case 1:
+              return this.begin("type_directive"), 13;
+            case 2:
+              return this.popState(), this.begin("arg_directive"), 10;
+            case 3:
+              return this.popState(), this.popState(), 15;
+            case 4:
+              return 14;
+            case 5:
+            case 6:
+              break;
+            case 7:
+              return this.begin("acc_title"), 44;
+            case 8:
+              return this.popState(), "acc_title_value";
+            case 9:
+              return this.begin("acc_descr"), 46;
+            case 10:
+              return this.popState(), "acc_descr_value";
+            case 11:
+              this.begin("acc_descr_multiline");
+              break;
+            case 12:
+            case 15:
+            case 24:
+            case 27:
+            case 30:
+            case 33:
+              this.popState();
+              break;
+            case 13:
+              return "acc_descr_multiline_value";
+            case 14:
+              this.begin("string");
+              break;
+            case 16:
+              return "STR";
+            case 17:
+              return 86;
+            case 18:
+              return 95;
+            case 19:
+              return 87;
+            case 20:
+              return 104;
+            case 21:
+              return 88;
+            case 22:
+              return 89;
+            case 23:
+              this.begin("href");
+              break;
+            case 25:
+              return 100;
+            case 26:
+              this.begin("callbackname");
+              break;
+            case 28:
+              this.popState(), this.begin("callbackargs");
+              break;
+            case 29:
+              return 98;
+            case 31:
+              return 99;
+            case 32:
+              this.begin("click");
+              break;
+            case 34:
+              return 90;
+            case 35:
+            case 36:
+              return t.lex.firstGraph() && this.begin("dir"), 24;
+            case 37:
+              return 38;
+            case 38:
+              return 42;
+            case 39:
+            case 40:
+            case 41:
+            case 42:
+              return 101;
+            case 43:
+              return this.popState(), 25;
+            case 44:
+            case 45:
+            case 46:
+            case 47:
+            case 48:
+            case 49:
+            case 50:
+            case 51:
+            case 52:
+            case 53:
+              return this.popState(), 26;
+            case 54:
+              return 118;
+            case 55:
+              return 119;
+            case 56:
+              return 120;
+            case 57:
+              return 121;
+            case 58:
+              return 105;
+            case 59:
+              return 111;
+            case 60:
+              return 53;
+            case 61:
+              return 67;
+            case 62:
+              return 52;
+            case 63:
+              return 20;
+            case 64:
+              return 106;
+            case 65:
+              return 126;
+            case 66:
+            case 67:
+            case 68:
+              return 82;
+            case 69:
+            case 70:
+            case 71:
+              return 81;
+            case 72:
+              return 59;
+            case 73:
+              return 60;
+            case 74:
+              return 61;
+            case 75:
+              return 62;
+            case 76:
+              return 63;
+            case 77:
+              return 64;
+            case 78:
+              return 65;
+            case 79:
+              return 69;
+            case 80:
+              return 70;
+            case 81:
+              return 55;
+            case 82:
+              return 56;
+            case 83:
+              return 109;
+            case 84:
+              return 112;
+            case 85:
+              return 127;
+            case 86:
+              return 124;
+            case 87:
+              return 113;
+            case 88:
+            case 89:
+              return 125;
+            case 90:
+              return 114;
+            case 91:
+              return 73;
+            case 92:
+              return 92;
+            case 93:
+              return "SEP";
+            case 94:
+              return 91;
+            case 95:
+              return 66;
+            case 96:
+              return 75;
+            case 97:
+              return 74;
+            case 98:
+              return 77;
+            case 99:
+              return 76;
+            case 100:
+              return 122;
+            case 101:
+              return 123;
+            case 102:
+              return 68;
+            case 103:
+              return 57;
+            case 104:
+              return 58;
+            case 105:
+              return 40;
+            case 106:
+              return 41;
+            case 107:
+              return 71;
+            case 108:
+              return 72;
+            case 109:
+              return 133;
+            case 110:
+              return 21;
+            case 111:
+              return 22;
+            case 112:
+              return 23;
+          }
+        },
+        rules: [
+          /^(?:%%\{)/,
+          /^(?:((?:(?!\}%%)[^:.])*))/,
+          /^(?::)/,
+          /^(?:\}%%)/,
+          /^(?:((?:(?!\}%%).|\n)*))/,
+          /^(?:%%(?!\{)[^\n]*)/,
+          /^(?:[^\}]%%[^\n]*)/,
+          /^(?:accTitle\s*:\s*)/,
+          /^(?:(?!\n||)*[^\n]*)/,
+          /^(?:accDescr\s*:\s*)/,
+          /^(?:(?!\n||)*[^\n]*)/,
+          /^(?:accDescr\s*\{\s*)/,
+          /^(?:[\}])/,
+          /^(?:[^\}]*)/,
+          /^(?:["])/,
+          /^(?:["])/,
+          /^(?:[^"]*)/,
+          /^(?:style\b)/,
+          /^(?:default\b)/,
+          /^(?:linkStyle\b)/,
+          /^(?:interpolate\b)/,
+          /^(?:classDef\b)/,
+          /^(?:class\b)/,
+          /^(?:href[\s]+["])/,
+          /^(?:["])/,
+          /^(?:[^"]*)/,
+          /^(?:call[\s]+)/,
+          /^(?:\([\s]*\))/,
+          /^(?:\()/,
+          /^(?:[^(]*)/,
+          /^(?:\))/,
+          /^(?:[^)]*)/,
+          /^(?:click[\s]+)/,
+          /^(?:[\s\n])/,
+          /^(?:[^\s\n]*)/,
+          /^(?:graph\b)/,
+          /^(?:flowchart\b)/,
+          /^(?:subgraph\b)/,
+          /^(?:end\b\s*)/,
+          /^(?:_self\b)/,
+          /^(?:_blank\b)/,
+          /^(?:_parent\b)/,
+          /^(?:_top\b)/,
+          /^(?:(\r?\n)*\s*\n)/,
+          /^(?:\s*LR\b)/,
+          /^(?:\s*RL\b)/,
+          /^(?:\s*TB\b)/,
+          /^(?:\s*BT\b)/,
+          /^(?:\s*TD\b)/,
+          /^(?:\s*BR\b)/,
+          /^(?:\s*<)/,
+          /^(?:\s*>)/,
+          /^(?:\s*\^)/,
+          /^(?:\s*v\b)/,
+          /^(?:.*direction\s+TB[^\n]*)/,
+          /^(?:.*direction\s+BT[^\n]*)/,
+          /^(?:.*direction\s+RL[^\n]*)/,
+          /^(?:.*direction\s+LR[^\n]*)/,
+          /^(?:[0-9]+)/,
+          /^(?:#)/,
+          /^(?::::)/,
+          /^(?::)/,
+          /^(?:&)/,
+          /^(?:;)/,
+          /^(?:,)/,
+          /^(?:\*)/,
+          /^(?:\s*[xo<]?--+[-xo>]\s*)/,
+          /^(?:\s*[xo<]?==+[=xo>]\s*)/,
+          /^(?:\s*[xo<]?-?\.+-[xo>]?\s*)/,
+          /^(?:\s*[xo<]?--\s*)/,
+          /^(?:\s*[xo<]?==\s*)/,
+          /^(?:\s*[xo<]?-\.\s*)/,
+          /^(?:\(-)/,
+          /^(?:-\))/,
+          /^(?:\(\[)/,
+          /^(?:\]\))/,
+          /^(?:\[\[)/,
+          /^(?:\]\])/,
+          /^(?:\[\|)/,
+          /^(?:\[\()/,
+          /^(?:\)\])/,
+          /^(?:\(\(\()/,
+          /^(?:\)\)\))/,
+          /^(?:-)/,
+          /^(?:\.)/,
+          /^(?:[\_])/,
+          /^(?:\+)/,
+          /^(?:%)/,
+          /^(?:=)/,
+          /^(?:=)/,
+          /^(?:<)/,
+          /^(?:>)/,
+          /^(?:\^)/,
+          /^(?:\\\|)/,
+          /^(?:v\b)/,
+          /^(?:[A-Za-z]+)/,
+          /^(?:\\\])/,
+          /^(?:\[\/)/,
+          /^(?:\/\])/,
+          /^(?:\[\\)/,
+          /^(?:[!"#$%&'*+,-.`?\\_/])/,
+          /^(?:[\u00AA\u00B5\u00BA\u00C0-\u00D6\u00D8-\u00F6]|[\u00F8-\u02C1\u02C6-\u02D1\u02E0-\u02E4\u02EC\u02EE\u0370-\u0374\u0376\u0377]|[\u037A-\u037D\u0386\u0388-\u038A\u038C\u038E-\u03A1\u03A3-\u03F5]|[\u03F7-\u0481\u048A-\u0527\u0531-\u0556\u0559\u0561-\u0587\u05D0-\u05EA]|[\u05F0-\u05F2\u0620-\u064A\u066E\u066F\u0671-\u06D3\u06D5\u06E5\u06E6\u06EE]|[\u06EF\u06FA-\u06FC\u06FF\u0710\u0712-\u072F\u074D-\u07A5\u07B1\u07CA-\u07EA]|[\u07F4\u07F5\u07FA\u0800-\u0815\u081A\u0824\u0828\u0840-\u0858\u08A0]|[\u08A2-\u08AC\u0904-\u0939\u093D\u0950\u0958-\u0961\u0971-\u0977]|[\u0979-\u097F\u0985-\u098C\u098F\u0990\u0993-\u09A8\u09AA-\u09B0\u09B2]|[\u09B6-\u09B9\u09BD\u09CE\u09DC\u09DD\u09DF-\u09E1\u09F0\u09F1\u0A05-\u0A0A]|[\u0A0F\u0A10\u0A13-\u0A28\u0A2A-\u0A30\u0A32\u0A33\u0A35\u0A36\u0A38\u0A39]|[\u0A59-\u0A5C\u0A5E\u0A72-\u0A74\u0A85-\u0A8D\u0A8F-\u0A91\u0A93-\u0AA8]|[\u0AAA-\u0AB0\u0AB2\u0AB3\u0AB5-\u0AB9\u0ABD\u0AD0\u0AE0\u0AE1\u0B05-\u0B0C]|[\u0B0F\u0B10\u0B13-\u0B28\u0B2A-\u0B30\u0B32\u0B33\u0B35-\u0B39\u0B3D\u0B5C]|[\u0B5D\u0B5F-\u0B61\u0B71\u0B83\u0B85-\u0B8A\u0B8E-\u0B90\u0B92-\u0B95\u0B99]|[\u0B9A\u0B9C\u0B9E\u0B9F\u0BA3\u0BA4\u0BA8-\u0BAA\u0BAE-\u0BB9\u0BD0]|[\u0C05-\u0C0C\u0C0E-\u0C10\u0C12-\u0C28\u0C2A-\u0C33\u0C35-\u0C39\u0C3D]|[\u0C58\u0C59\u0C60\u0C61\u0C85-\u0C8C\u0C8E-\u0C90\u0C92-\u0CA8\u0CAA-\u0CB3]|[\u0CB5-\u0CB9\u0CBD\u0CDE\u0CE0\u0CE1\u0CF1\u0CF2\u0D05-\u0D0C\u0D0E-\u0D10]|[\u0D12-\u0D3A\u0D3D\u0D4E\u0D60\u0D61\u0D7A-\u0D7F\u0D85-\u0D96\u0D9A-\u0DB1]|[\u0DB3-\u0DBB\u0DBD\u0DC0-\u0DC6\u0E01-\u0E30\u0E32\u0E33\u0E40-\u0E46\u0E81]|[\u0E82\u0E84\u0E87\u0E88\u0E8A\u0E8D\u0E94-\u0E97\u0E99-\u0E9F\u0EA1-\u0EA3]|[\u0EA5\u0EA7\u0EAA\u0EAB\u0EAD-\u0EB0\u0EB2\u0EB3\u0EBD\u0EC0-\u0EC4\u0EC6]|[\u0EDC-\u0EDF\u0F00\u0F40-\u0F47\u0F49-\u0F6C\u0F88-\u0F8C\u1000-\u102A]|[\u103F\u1050-\u1055\u105A-\u105D\u1061\u1065\u1066\u106E-\u1070\u1075-\u1081]|[\u108E\u10A0-\u10C5\u10C7\u10CD\u10D0-\u10FA\u10FC-\u1248\u124A-\u124D]|[\u1250-\u1256\u1258\u125A-\u125D\u1260-\u1288\u128A-\u128D\u1290-\u12B0]|[\u12B2-\u12B5\u12B8-\u12BE\u12C0\u12C2-\u12C5\u12C8-\u12D6\u12D8-\u1310]|[\u1312-\u1315\u1318-\u135A\u1380-\u138F\u13A0-\u13F4\u1401-\u166C]|[\u166F-\u167F\u1681-\u169A\u16A0-\u16EA\u1700-\u170C\u170E-\u1711]|[\u1720-\u1731\u1740-\u1751\u1760-\u176C\u176E-\u1770\u1780-\u17B3\u17D7]|[\u17DC\u1820-\u1877\u1880-\u18A8\u18AA\u18B0-\u18F5\u1900-\u191C]|[\u1950-\u196D\u1970-\u1974\u1980-\u19AB\u19C1-\u19C7\u1A00-\u1A16]|[\u1A20-\u1A54\u1AA7\u1B05-\u1B33\u1B45-\u1B4B\u1B83-\u1BA0\u1BAE\u1BAF]|[\u1BBA-\u1BE5\u1C00-\u1C23\u1C4D-\u1C4F\u1C5A-\u1C7D\u1CE9-\u1CEC]|[\u1CEE-\u1CF1\u1CF5\u1CF6\u1D00-\u1DBF\u1E00-\u1F15\u1F18-\u1F1D]|[\u1F20-\u1F45\u1F48-\u1F4D\u1F50-\u1F57\u1F59\u1F5B\u1F5D\u1F5F-\u1F7D]|[\u1F80-\u1FB4\u1FB6-\u1FBC\u1FBE\u1FC2-\u1FC4\u1FC6-\u1FCC\u1FD0-\u1FD3]|[\u1FD6-\u1FDB\u1FE0-\u1FEC\u1FF2-\u1FF4\u1FF6-\u1FFC\u2071\u207F]|[\u2090-\u209C\u2102\u2107\u210A-\u2113\u2115\u2119-\u211D\u2124\u2126\u2128]|[\u212A-\u212D\u212F-\u2139\u213C-\u213F\u2145-\u2149\u214E\u2183\u2184]|[\u2C00-\u2C2E\u2C30-\u2C5E\u2C60-\u2CE4\u2CEB-\u2CEE\u2CF2\u2CF3]|[\u2D00-\u2D25\u2D27\u2D2D\u2D30-\u2D67\u2D6F\u2D80-\u2D96\u2DA0-\u2DA6]|[\u2DA8-\u2DAE\u2DB0-\u2DB6\u2DB8-\u2DBE\u2DC0-\u2DC6\u2DC8-\u2DCE]|[\u2DD0-\u2DD6\u2DD8-\u2DDE\u2E2F\u3005\u3006\u3031-\u3035\u303B\u303C]|[\u3041-\u3096\u309D-\u309F\u30A1-\u30FA\u30FC-\u30FF\u3105-\u312D]|[\u3131-\u318E\u31A0-\u31BA\u31F0-\u31FF\u3400-\u4DB5\u4E00-\u9FCC]|[\uA000-\uA48C\uA4D0-\uA4FD\uA500-\uA60C\uA610-\uA61F\uA62A\uA62B]|[\uA640-\uA66E\uA67F-\uA697\uA6A0-\uA6E5\uA717-\uA71F\uA722-\uA788]|[\uA78B-\uA78E\uA790-\uA793\uA7A0-\uA7AA\uA7F8-\uA801\uA803-\uA805]|[\uA807-\uA80A\uA80C-\uA822\uA840-\uA873\uA882-\uA8B3\uA8F2-\uA8F7\uA8FB]|[\uA90A-\uA925\uA930-\uA946\uA960-\uA97C\uA984-\uA9B2\uA9CF\uAA00-\uAA28]|[\uAA40-\uAA42\uAA44-\uAA4B\uAA60-\uAA76\uAA7A\uAA80-\uAAAF\uAAB1\uAAB5]|[\uAAB6\uAAB9-\uAABD\uAAC0\uAAC2\uAADB-\uAADD\uAAE0-\uAAEA\uAAF2-\uAAF4]|[\uAB01-\uAB06\uAB09-\uAB0E\uAB11-\uAB16\uAB20-\uAB26\uAB28-\uAB2E]|[\uABC0-\uABE2\uAC00-\uD7A3\uD7B0-\uD7C6\uD7CB-\uD7FB\uF900-\uFA6D]|[\uFA70-\uFAD9\uFB00-\uFB06\uFB13-\uFB17\uFB1D\uFB1F-\uFB28\uFB2A-\uFB36]|[\uFB38-\uFB3C\uFB3E\uFB40\uFB41\uFB43\uFB44\uFB46-\uFBB1\uFBD3-\uFD3D]|[\uFD50-\uFD8F\uFD92-\uFDC7\uFDF0-\uFDFB\uFE70-\uFE74\uFE76-\uFEFC]|[\uFF21-\uFF3A\uFF41-\uFF5A\uFF66-\uFFBE\uFFC2-\uFFC7\uFFCA-\uFFCF]|[\uFFD2-\uFFD7\uFFDA-\uFFDC])/,
+          /^(?:\|)/,
+          /^(?:\()/,
+          /^(?:\))/,
+          /^(?:\[)/,
+          /^(?:\])/,
+          /^(?:\{)/,
+          /^(?:\})/,
+          /^(?:")/,
+          /^(?:(\r?\n)+)/,
+          /^(?:\s)/,
+          /^(?:$)/,
+        ],
+        conditions: {
+          close_directive: { rules: [], inclusive: !1 },
+          arg_directive: { rules: [3, 4], inclusive: !1 },
+          type_directive: { rules: [2, 3], inclusive: !1 },
+          open_directive: { rules: [1], inclusive: !1 },
+          callbackargs: { rules: [30, 31], inclusive: !1 },
+          callbackname: { rules: [27, 28, 29], inclusive: !1 },
+          href: { rules: [24, 25], inclusive: !1 },
+          click: { rules: [33, 34], inclusive: !1 },
+          vertex: { rules: [], inclusive: !1 },
+          dir: { rules: [43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53], inclusive: !1 },
+          acc_descr_multiline: { rules: [12, 13], inclusive: !1 },
+          acc_descr: { rules: [10], inclusive: !1 },
+          acc_title: { rules: [8], inclusive: !1 },
+          string: { rules: [15, 16], inclusive: !1 },
+          INITIAL: {
+            rules: [
+              0,
+              5,
+              6,
+              7,
+              9,
+              11,
+              14,
+              17,
+              18,
+              19,
+              20,
+              21,
+              22,
+              23,
+              26,
+              32,
+              35,
+              36,
+              37,
+              38,
+              39,
+              40,
+              41,
+              42,
+              54,
+              55,
+              56,
+              57,
+              58,
+              59,
+              60,
+              61,
+              62,
+              63,
+              64,
+              65,
+              66,
+              67,
+              68,
+              69,
+              70,
+              71,
+              72,
+              73,
+              74,
+              75,
+              76,
+              77,
+              78,
+              79,
+              80,
+              81,
+              82,
+              83,
+              84,
+              85,
+              86,
+              87,
+              88,
+              89,
+              90,
+              91,
+              92,
+              93,
+              94,
+              95,
+              96,
+              97,
+              98,
+              99,
+              100,
+              101,
+              102,
+              103,
+              104,
+              105,
+              106,
+              107,
+              108,
+              109,
+              110,
+              111,
+              112,
+            ],
+            inclusive: !0,
+          },
+        },
+      },
+        t);
+    function re() {
+      this.yy = {};
+    }
+    return ne.lexer = ie, re.prototype = ne, ne.Parser = re, new re();
+  }();
+  zT.parser = zT;
+  const UT = zT,
+    WT = (t, e) => {
+      var n;
+      return "dagre-wrapper" !== (null == (n = null == e ? void 0 : e.flowchart) ? void 0 : n.defaultRenderer)
+        && null !== t.match(/^\s*graph/);
+    },
+    HT = (t, e) => {
+      var n;
+      return "dagre-wrapper" === (null == (n = null == e ? void 0 : e.flowchart) ? void 0 : n.defaultRenderer)
+          && null !== t.match(/^\s*graph/) || null !== t.match(/^\s*flowchart/);
+    };
+  let qT, VT, GT = 0, XT = jx(), ZT = {}, QT = [], KT = {}, JT = [], tC = {}, eC = {}, nC = 0, iC = !0, rC = [];
+  const aC = t => ub.sanitizeText(t, XT),
+    sC = function(t) {
+      const e = Object.keys(ZT);
+      for (const n of e) if (ZT[n].id === t) return ZT[n].domId;
+      return t;
+    },
+    oC = function(t, e, n, i) {
+      const r = { start: t, end: e, type: void 0, text: "" };
+      void 0 !== (i = n.text)
+      && (r.text = aC(i.trim()),
+        "\"" === r.text[0] && "\"" === r.text[r.text.length - 1] && (r.text = r.text.substring(1, r.text.length - 1))),
+        void 0 !== n && (r.type = n.type, r.stroke = n.stroke, r.length = n.length),
+        QT.push(r);
+    },
+    lC = function(t, e) {
+      t.split(",").forEach(function(t) {
+        let n = t;
+        void 0 !== ZT[n] && ZT[n].classes.push(e), void 0 !== tC[n] && tC[n].classes.push(e);
+      });
+    },
+    cC = function(t) {
+      let e = ie(".mermaidTooltip");
+      null === (e._groups || e)[0][0]
+        && (e = ie("body").append("div").attr("class", "mermaidTooltip").style("opacity", 0));
+      ie(t).select("svg").selectAll("g.node").on("mouseover", function() {
+        const t = ie(this);
+        if (null === t.attr("title")) return;
+        const n = this.getBoundingClientRect();
+        e.transition().duration(200).style("opacity", ".9"),
+          e.text(t.attr("title")).style("left", window.scrollX + n.left + (n.right - n.left) / 2 + "px").style(
+            "top",
+            window.scrollY + n.top - 14 + document.body.scrollTop + "px",
+          ),
+          e.html(e.html().replace(/&lt;br\/&gt;/g, "<br/>")),
+          t.classed("hover", !0);
+      }).on("mouseout", function() {
+        e.transition().duration(500).style("opacity", 0);
+        ie(this).classed("hover", !1);
+      });
+    };
+  rC.push(cC);
+  const hC = function(t) {
+    for (const [e, n] of JT.entries()) if (n.id === t) return e;
+    return -1;
+  };
+  let uC = -1;
+  const dC = [],
+    pC = function(t, e) {
+      const n = JT[e].nodes;
+      if (uC += 1, uC > 2e3) return;
+      if (dC[uC] = e, JT[e].id === t) return { result: !0, count: 0 };
+      let i = 0, r = 1;
+      for (; i < n.length;) {
+        const e = hC(n[i]);
+        if (e >= 0) {
+          const n = pC(t, e);
+          if (n.result) return { result: !0, count: r + n.count };
+          r += n.count;
+        }
+        i += 1;
+      }
+      return { result: !1, count: r };
+    },
+    fC = (t, e) => {
+      let n = !1;
+      return t.forEach(t => {
+        t.nodes.indexOf(e) >= 0 && (n = !0);
+      }),
+        n;
+    },
+    gC = (t, e) => {
+      const n = [];
+      return t.nodes.forEach((i, r) => {
+        fC(e, i) || n.push(t.nodes[r]);
+      }),
+        { nodes: n };
+    },
+    yC = {
+      parseDirective: function(t, e, n) {
+        nL.parseDirective(this, t, e, n);
+      },
+      defaultConfig: () => Ox.flowchart,
+      setAccTitle: Ev,
+      getAccTitle: Sv,
+      getAccDescription: Dv,
+      setAccDescription: Av,
+      addVertex: function(t, e, n, i, r, a, s = {}) {
+        let o, l = t;
+        void 0 !== l && 0 !== l.trim().length
+          && (void 0 === ZT[l] && (ZT[l] = { id: l, domId: "flowchart-" + l + "-" + GT, styles: [], classes: [] }),
+            GT++,
+            void 0 !== e
+              ? (XT = jx(),
+                o = aC(e.trim()),
+                "\"" === o[0] && "\"" === o[o.length - 1] && (o = o.substring(1, o.length - 1)),
+                ZT[l].text = o)
+              : void 0 === ZT[l].text && (ZT[l].text = t),
+            void 0 !== n && (ZT[l].type = n),
+            null != i && i.forEach(function(t) {
+              ZT[l].styles.push(t);
+            }),
+            null != r && r.forEach(function(t) {
+              ZT[l].classes.push(t);
+            }),
+            void 0 !== a && (ZT[l].dir = a),
+            void 0 === ZT[l].props ? ZT[l].props = s : void 0 !== s && Object.assign(ZT[l].props, s));
+      },
+      lookUpDomId: sC,
+      addLink: function(t, e, n, i) {
+        let r, a;
+        for (r = 0; r < t.length; r++) for (a = 0; a < e.length; a++) oC(t[r], e[a], n, i);
+      },
+      updateLinkInterpolate: function(t, e) {
+        t.forEach(function(t) {
+          "default" === t ? QT.defaultInterpolate = e : QT[t].interpolate = e;
+        });
+      },
+      updateLink: function(t, e) {
+        t.forEach(function(t) {
+          "default" === t
+            ? QT.defaultStyle = e
+            : (-1 === Dx.isSubstringInArray("fill", e) && e.push("fill:none"), QT[t].style = e);
+        });
+      },
+      addClass: function(t, e) {
+        void 0 === KT[t] && (KT[t] = { id: t, styles: [], textStyles: [] }),
+          null != e && e.forEach(function(e) {
+            if (e.match("color")) {
+              const n = e.replace("fill", "bgFill").replace("color", "fill");
+              KT[t].textStyles.push(n);
+            }
+            KT[t].styles.push(e);
+          });
+      },
+      setDirection: function(t) {
+        qT = t,
+          qT.match(/.*</) && (qT = "RL"),
+          qT.match(/.*\^/) && (qT = "BT"),
+          qT.match(/.*>/) && (qT = "LR"),
+          qT.match(/.*v/) && (qT = "TB");
+      },
+      setClass: lC,
+      setTooltip: function(t, e) {
+        t.split(",").forEach(function(t) {
+          void 0 !== e && (eC["gen-1" === VT ? sC(t) : t] = aC(e));
+        });
+      },
+      getTooltip: function(t) {
+        return eC[t];
+      },
+      setClickEvent: function(t, e, n) {
+        t.split(",").forEach(function(t) {
+          !function(t, e, n) {
+            let i = sC(t);
+            if ("loose" !== jx().securityLevel) return;
+            if (void 0 === e) return;
+            let r = [];
+            if ("string" == typeof n) {
+              r = n.split(/,(?=(?:(?:[^"]*"){2})*[^"]*$)/);
+              for (let t = 0; t < r.length; t++) {
+                let e = r[t].trim();
+                "\"" === e.charAt(0) && "\"" === e.charAt(e.length - 1) && (e = e.substr(1, e.length - 2)), r[t] = e;
+              }
+            }
+            0 === r.length && r.push(t),
+              void 0 !== ZT[t] && (ZT[t].haveCallback = !0,
+                rC.push(function() {
+                  const t = document.querySelector(`[id="${i}"]`);
+                  null !== t && t.addEventListener("click", function() {
+                    Dx.runFunc(e, ...r);
+                  }, !1);
+                }));
+          }(t, e, n);
+        }), lC(t, "clickable");
+      },
+      setLink: function(t, e, n) {
+        t.split(",").forEach(function(t) {
+          void 0 !== ZT[t] && (ZT[t].link = Dx.formatUrl(e, XT), ZT[t].linkTarget = n);
+        }), lC(t, "clickable");
+      },
+      bindFunctions: function(t) {
+        rC.forEach(function(e) {
+          e(t);
+        });
+      },
+      getDirection: function() {
+        return qT.trim();
+      },
+      getVertices: function() {
+        return ZT;
+      },
+      getEdges: function() {
+        return QT;
+      },
+      getClasses: function() {
+        return KT;
+      },
+      clear: function(t = "gen-1") {
+        ZT = {}, KT = {}, QT = [], rC = [cC], JT = [], tC = {}, nC = 0, eC = [], iC = !0, VT = t, Cv();
+      },
+      setGen: t => {
+        VT = t || "gen-1";
+      },
+      defaultStyle: function() {
+        return "fill:#ffa;stroke: #f66; stroke-width: 3px; stroke-dasharray: 5, 5;fill:#ffa;stroke: #666;";
+      },
+      addSubGraph: function(t, e, n) {
+        let i = t.trim(), r = n;
+        t === n && n.match(/\s/) && (i = void 0);
+        let a = [];
+        const { nodeList: s, dir: o } = function(t) {
+          const e = { boolean: {}, number: {}, string: {} }, n = [];
+          let i;
+          return {
+            nodeList: t.filter(function(t) {
+              const r = typeof t;
+              return t.stmt && "dir" === t.stmt
+                ? (i = t.value, !1)
+                : "" !== t.trim() && (r in e ? !e[r].hasOwnProperty(t) && (e[r][t] = !0) : !n.includes(t) && n.push(t));
+            }),
+            dir: i,
+          };
+        }(a.concat.apply(a, e));
+        if (a = s, "gen-1" === VT) for (let t = 0; t < a.length; t++) a[t] = sC(a[t]);
+        i = i || "subGraph" + nC, r = r || "", r = aC(r), nC += 1;
+        const l = { id: i, nodes: a, title: r.trim(), classes: [], dir: o };
+        return tb.info("Adding", l.id, l.nodes, l.dir), l.nodes = gC(l, JT).nodes, JT.push(l), tC[i] = l, i;
+      },
+      getDepthFirstPos: function(t) {
+        return dC[t];
+      },
+      indexNodes: function() {
+        uC = -1, JT.length > 0 && pC("none", JT.length - 1);
+      },
+      getSubGraphs: function() {
+        return JT;
+      },
+      destructLink: (t, e) => {
+        const n = (t => {
+          const e = t.trim();
+          let n = e.slice(0, -1), i = "arrow_open";
+          switch (e.slice(-1)) {
+            case "x":
+              i = "arrow_cross", "x" === e[0] && (i = "double_" + i, n = n.slice(1));
+              break;
+            case ">":
+              i = "arrow_point", "<" === e[0] && (i = "double_" + i, n = n.slice(1));
+              break;
+            case "o":
+              i = "arrow_circle", "o" === e[0] && (i = "double_" + i, n = n.slice(1));
+          }
+          let r = "normal", a = n.length - 1;
+          "=" === n[0] && (r = "thick");
+          let s = ((t, e) => {
+            const n = e.length;
+            let i = 0;
+            for (let r = 0; r < n; ++r) e[r] === t && ++i;
+            return i;
+          })(".", n);
+          return s && (r = "dotted", a = s), { type: i, stroke: r, length: a };
+        })(t);
+        let i;
+        if (e) {
+          if (
+            i = (t => {
+              let e = t.trim(), n = "arrow_open";
+              switch (e[0]) {
+                case "<":
+                  n = "arrow_point", e = e.slice(1);
+                  break;
+                case "x":
+                  n = "arrow_cross", e = e.slice(1);
+                  break;
+                case "o":
+                  n = "arrow_circle", e = e.slice(1);
+              }
+              let i = "normal";
+              return e.includes("=") && (i = "thick"), e.includes(".") && (i = "dotted"), { type: n, stroke: i };
+            })(e), i.stroke !== n.stroke
+          ) return { type: "INVALID", stroke: "INVALID" };
+          if ("arrow_open" === i.type) i.type = n.type;
+          else {
+            if (i.type !== n.type) return { type: "INVALID", stroke: "INVALID" };
+            i.type = "double_" + i.type;
+          }
+          return "double_arrow" === i.type && (i.type = "double_arrow_point"), i.length = n.length, i;
+        }
+        return n;
+      },
+      lex: { firstGraph: () => !!iC && (iC = !1, !0) },
+      exists: fC,
+      makeUniq: gC,
+      setDiagramTitle: Lv,
+      getDiagramTitle: Ov,
+    };
+  const mC = {},
+    bC = function(t) {
+      const e = Object.keys(t);
+      for (const n of e) mC[n] = t[n];
+    },
+    _C = {},
+    xC = function(t, e, n, i, r, a) {
+      const s = i.select(`[id="${n}"]`);
+      Object.keys(t).forEach(function(n) {
+        const i = t[n];
+        let o = "default";
+        i.classes.length > 0 && (o = i.classes.join(" "));
+        const l = gx(i.styles);
+        let c, h = void 0 !== i.text ? i.text : i.id;
+        if (cb(jx().flowchart.htmlLabels)) {
+          const t = { label: h.replace(/fa[blrs]?:fa-[\w-]+/g, t => `<i class='${t.replace(":", " ")}'></i>`) };
+          c = Zm(s, t).node(), c.parentNode.removeChild(c);
+        } else {
+          const t = r.createElementNS("http://www.w3.org/2000/svg", "text");
+          t.setAttribute("style", l.labelStyle.replace("color:", "fill:"));
+          const e = h.split(ub.lineBreakRegex);
+          for (const n of e) {
+            const e = r.createElementNS("http://www.w3.org/2000/svg", "tspan");
+            e.setAttributeNS("http://www.w3.org/XML/1998/namespace", "xml:space", "preserve"),
+              e.setAttribute("dy", "1em"),
+              e.setAttribute("x", "1"),
+              e.textContent = n,
+              t.appendChild(e);
+          }
+          c = t;
+        }
+        let u = 0, d = "";
+        switch (i.type) {
+          case "round":
+            u = 5, d = "rect";
+            break;
+          case "square":
+          case "group":
+          default:
+            d = "rect";
+            break;
+          case "diamond":
+            d = "question";
+            break;
+          case "hexagon":
+            d = "hexagon";
+            break;
+          case "odd":
+          case "odd_right":
+            d = "rect_left_inv_arrow";
+            break;
+          case "lean_right":
+            d = "lean_right";
+            break;
+          case "lean_left":
+            d = "lean_left";
+            break;
+          case "trapezoid":
+            d = "trapezoid";
+            break;
+          case "inv_trapezoid":
+            d = "inv_trapezoid";
+            break;
+          case "circle":
+            d = "circle";
+            break;
+          case "ellipse":
+            d = "ellipse";
+            break;
+          case "stadium":
+            d = "stadium";
+            break;
+          case "subroutine":
+            d = "subroutine";
+            break;
+          case "cylinder":
+            d = "cylinder";
+            break;
+          case "doublecircle":
+            d = "doublecircle";
+        }
+        e.setNode(i.id, {
+          labelStyle: l.labelStyle,
+          shape: d,
+          labelText: h,
+          rx: u,
+          ry: u,
+          class: o,
+          style: l.style,
+          id: i.id,
+          link: i.link,
+          linkTarget: i.linkTarget,
+          tooltip: a.db.getTooltip(i.id) || "",
+          domId: a.db.lookUpDomId(i.id),
+          haveCallback: i.haveCallback,
+          width: "group" === i.type ? 500 : void 0,
+          dir: i.dir,
+          type: i.type,
+          props: i.props,
+          padding: jx().flowchart.padding,
+        }),
+          tb.info("setNode", {
+            labelStyle: l.labelStyle,
+            shape: d,
+            labelText: h,
+            rx: u,
+            ry: u,
+            class: o,
+            style: l.style,
+            id: i.id,
+            domId: a.db.lookUpDomId(i.id),
+            width: "group" === i.type ? 500 : void 0,
+            type: i.type,
+            dir: i.dir,
+            props: i.props,
+            padding: jx().flowchart.padding,
+          });
+      });
+    },
+    vC = function(t, e, n) {
+      tb.info("abc78 edges = ", t);
+      let i, r, a = 0, s = {};
+      if (void 0 !== t.defaultStyle) {
+        const e = gx(t.defaultStyle);
+        i = e.style, r = e.labelStyle;
+      }
+      t.forEach(function(n) {
+        a++;
+        var o = "L-" + n.start + "-" + n.end;
+        void 0 === s[o]
+          ? (s[o] = 0, tb.info("abc78 new entry", o, s[o]))
+          : (s[o]++, tb.info("abc78 new entry", o, s[o]));
+        let l = o + "-" + s[o];
+        tb.info("abc78 new link id to be used is", o, l, s[o]);
+        var c = "LS-" + n.start, h = "LE-" + n.end;
+        const u = { style: "", labelStyle: "" };
+        switch (
+          u.minlen = n.length || 1,
+            "arrow_open" === n.type ? u.arrowhead = "none" : u.arrowhead = "normal",
+            u.arrowTypeStart = "arrow_open",
+            u.arrowTypeEnd = "arrow_open",
+            n.type
+        ) {
+          case "double_arrow_cross":
+            u.arrowTypeStart = "arrow_cross";
+          case "arrow_cross":
+            u.arrowTypeEnd = "arrow_cross";
+            break;
+          case "double_arrow_point":
+            u.arrowTypeStart = "arrow_point";
+          case "arrow_point":
+            u.arrowTypeEnd = "arrow_point";
+            break;
+          case "double_arrow_circle":
+            u.arrowTypeStart = "arrow_circle";
+          case "arrow_circle":
+            u.arrowTypeEnd = "arrow_circle";
+        }
+        let d = "", p = "";
+        switch (n.stroke) {
+          case "normal":
+            d = "fill:none;",
+              void 0 !== i && (d = i),
+              void 0 !== r && (p = r),
+              u.thickness = "normal",
+              u.pattern = "solid";
+            break;
+          case "dotted":
+            u.thickness = "normal", u.pattern = "dotted", u.style = "fill:none;stroke-width:2px;stroke-dasharray:3;";
+            break;
+          case "thick":
+            u.thickness = "thick", u.pattern = "solid", u.style = "stroke-width: 3.5px;fill:none;";
+        }
+        if (void 0 !== n.style) {
+          const t = gx(n.style);
+          d = t.style, p = t.labelStyle;
+        }
+        u.style = u.style += d,
+          u.labelStyle = u.labelStyle += p,
+          void 0 !== n.interpolate
+            ? u.curve = px(n.interpolate, Zs)
+            : void 0 !== t.defaultInterpolate
+            ? u.curve = px(t.defaultInterpolate, Zs)
+            : u.curve = px(_C.curve, Zs),
+          void 0 === n.text
+            ? void 0 !== n.style && (u.arrowheadStyle = "fill: #333")
+            : (u.arrowheadStyle = "fill: #333", u.labelpos = "c"),
+          u.labelType = "text",
+          u.label = n.text.replace(ub.lineBreakRegex, "\n"),
+          void 0 === n.style && (u.style = u.style || "stroke: #333; stroke-width: 1.5px;fill:none;"),
+          u.labelStyle = u.labelStyle.replace("color:", "fill:"),
+          u.id = l,
+          u.classes = "flowchart-link " + c + " " + h,
+          e.setEdge(n.start, n.end, u, a);
+      });
+    },
+    kC = {
+      setConf: function(t) {
+        const e = Object.keys(t);
+        for (const n of e) _C[n] = t[n];
+      },
+      addVertices: xC,
+      addEdges: vC,
+      getClasses: function(t, e) {
+        tb.info("Extracting classes"), e.db.clear();
+        try {
+          return e.parse(t), e.db.getClasses();
+        } catch (t) {
+          return;
+        }
+      },
+      draw: function(t, e, n, i) {
+        tb.info("Drawing flowchart"), i.db.clear(), yC.setGen("gen-2"), i.parser.parse(t);
+        let r = i.db.getDirection();
+        void 0 === r && (r = "TD");
+        const { securityLevel: a, flowchart: s } = jx(), o = s.nodeSpacing || 50, l = s.rankSpacing || 50;
+        let c;
+        "sandbox" === a && (c = ie("#i" + e));
+        const h = ie("sandbox" === a ? c.nodes()[0].contentDocument.body : "body"),
+          u = "sandbox" === a ? c.nodes()[0].contentDocument : document,
+          d = new yy({ multigraph: !0, compound: !0 }).setGraph({
+            rankdir: r,
+            nodesep: o,
+            ranksep: l,
+            marginx: 0,
+            marginy: 0,
+          }).setDefaultEdgeLabel(function() {
+            return {};
+          });
+        let p;
+        const f = i.db.getSubGraphs();
+        tb.info("Subgraphs - ", f);
+        for (let t = f.length - 1; t >= 0; t--) {
+          p = f[t], tb.info("Subgraph - ", p), i.db.addVertex(p.id, p.title, "group", void 0, p.classes, p.dir);
+        }
+        const g = i.db.getVertices(), y = i.db.getEdges();
+        tb.info(y);
+        let m = 0;
+        for (m = f.length - 1; m >= 0; m--) {
+          p = f[m], re("cluster").append("text");
+          for (let t = 0; t < p.nodes.length; t++) {
+            tb.info("Setting up subgraphs", p.nodes[t], p.id), d.setParent(p.nodes[t], p.id);
+          }
+        }
+        xC(g, d, e, h, u, i), vC(y, d);
+        const b = h.select(`[id="${e}"]`), _ = h.select("#" + e + " g");
+        if (
+          _T(_, d, ["point", "circle", "cross"], "flowchart", e),
+            Dx.insertTitle(b, "flowchartTitleText", s.titleTopMargin, i.db.getDiagramTitle()),
+            Xx(d, b, s.diagramPadding, s.useMaxWidth),
+            i.db.indexNodes("subGraph" + m),
+            !s.htmlLabels
+        ) {
+          const t = u.querySelectorAll("[id=\"" + e + "\"] .edgeLabel .label");
+          for (const e of t) {
+            const t = e.getBBox(), n = u.createElementNS("http://www.w3.org/2000/svg", "rect");
+            n.setAttribute("rx", 0),
+              n.setAttribute("ry", 0),
+              n.setAttribute("width", t.width),
+              n.setAttribute("height", t.height),
+              e.insertBefore(n, e.firstChild);
+          }
+        }
+        Object.keys(g).forEach(function(t) {
+          const n = g[t];
+          if (n.link) {
+            const i = ie("#" + e + " [id=\"" + t + "\"]");
+            if (i) {
+              const t = u.createElementNS("http://www.w3.org/2000/svg", "a");
+              t.setAttributeNS("http://www.w3.org/2000/svg", "class", n.classes.join(" ")),
+                t.setAttributeNS("http://www.w3.org/2000/svg", "href", n.link),
+                t.setAttributeNS("http://www.w3.org/2000/svg", "rel", "noopener"),
+                "sandbox" === a
+                  ? t.setAttributeNS("http://www.w3.org/2000/svg", "target", "_top")
+                  : n.linkTarget && t.setAttributeNS("http://www.w3.org/2000/svg", "target", n.linkTarget);
+              const e = i.insert(function() {
+                  return t;
+                }, ":first-child"),
+                r = i.select(".label-container");
+              r && e.append(function() {
+                return r.node();
+              });
+              const s = i.select(".label");
+              s && e.append(function() {
+                return s.node();
+              });
+            }
+          }
+        });
+      },
+    };
+  var wC = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [1, 3],
+      i = [1, 5],
+      r = [7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 23, 25, 26, 28, 35, 40],
+      a = [1, 15],
+      s = [1, 16],
+      o = [1, 17],
+      l = [1, 18],
+      c = [1, 19],
+      h = [1, 20],
+      u = [1, 21],
+      d = [1, 22],
+      p = [1, 23],
+      f = [1, 24],
+      g = [1, 25],
+      y = [1, 26],
+      m = [1, 27],
+      b = [1, 29],
+      _ = [1, 31],
+      x = [1, 34],
+      v = [5, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 23, 25, 26, 28, 35, 40],
+      k = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          directive: 4,
+          gantt: 5,
+          document: 6,
+          EOF: 7,
+          line: 8,
+          SPACE: 9,
+          statement: 10,
+          NL: 11,
+          dateFormat: 12,
+          inclusiveEndDates: 13,
+          topAxis: 14,
+          axisFormat: 15,
+          tickInterval: 16,
+          excludes: 17,
+          includes: 18,
+          todayMarker: 19,
+          title: 20,
+          acc_title: 21,
+          acc_title_value: 22,
+          acc_descr: 23,
+          acc_descr_value: 24,
+          acc_descr_multiline_value: 25,
+          section: 26,
+          clickStatement: 27,
+          taskTxt: 28,
+          taskData: 29,
+          openDirective: 30,
+          typeDirective: 31,
+          closeDirective: 32,
+          ":": 33,
+          argDirective: 34,
+          click: 35,
+          callbackname: 36,
+          callbackargs: 37,
+          href: 38,
+          clickStatementDebug: 39,
+          open_directive: 40,
+          type_directive: 41,
+          arg_directive: 42,
+          close_directive: 43,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: {
+          2: "error",
+          5: "gantt",
+          7: "EOF",
+          9: "SPACE",
+          11: "NL",
+          12: "dateFormat",
+          13: "inclusiveEndDates",
+          14: "topAxis",
+          15: "axisFormat",
+          16: "tickInterval",
+          17: "excludes",
+          18: "includes",
+          19: "todayMarker",
+          20: "title",
+          21: "acc_title",
+          22: "acc_title_value",
+          23: "acc_descr",
+          24: "acc_descr_value",
+          25: "acc_descr_multiline_value",
+          26: "section",
+          28: "taskTxt",
+          29: "taskData",
+          33: ":",
+          35: "click",
+          36: "callbackname",
+          37: "callbackargs",
+          38: "href",
+          40: "open_directive",
+          41: "type_directive",
+          42: "arg_directive",
+          43: "close_directive",
+        },
+        productions_: [
+          0,
+          [3, 2],
+          [3, 3],
+          [6, 0],
+          [6, 2],
+          [8, 2],
+          [8, 1],
+          [8, 1],
+          [8, 1],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 2],
+          [10, 2],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 2],
+          [10, 1],
+          [4, 4],
+          [4, 6],
+          [27, 2],
+          [27, 3],
+          [27, 3],
+          [27, 4],
+          [27, 3],
+          [27, 4],
+          [27, 2],
+          [39, 2],
+          [39, 3],
+          [39, 3],
+          [39, 4],
+          [39, 3],
+          [39, 4],
+          [39, 2],
+          [30, 1],
+          [31, 1],
+          [34, 1],
+          [32, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 2:
+              return a[o - 1];
+            case 3:
+            case 7:
+            case 8:
+              this.$ = [];
+              break;
+            case 4:
+              a[o - 1].push(a[o]), this.$ = a[o - 1];
+              break;
+            case 5:
+            case 6:
+              this.$ = a[o];
+              break;
+            case 9:
+              i.setDateFormat(a[o].substr(11)), this.$ = a[o].substr(11);
+              break;
+            case 10:
+              i.enableInclusiveEndDates(), this.$ = a[o].substr(18);
+              break;
+            case 11:
+              i.TopAxis(), this.$ = a[o].substr(8);
+              break;
+            case 12:
+              i.setAxisFormat(a[o].substr(11)), this.$ = a[o].substr(11);
+              break;
+            case 13:
+              i.setTickInterval(a[o].substr(13)), this.$ = a[o].substr(13);
+              break;
+            case 14:
+              i.setExcludes(a[o].substr(9)), this.$ = a[o].substr(9);
+              break;
+            case 15:
+              i.setIncludes(a[o].substr(9)), this.$ = a[o].substr(9);
+              break;
+            case 16:
+              i.setTodayMarker(a[o].substr(12)), this.$ = a[o].substr(12);
+              break;
+            case 17:
+              i.setDiagramTitle(a[o].substr(6)), this.$ = a[o].substr(6);
+              break;
+            case 18:
+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 19:
+            case 20:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 21:
+              i.addSection(a[o].substr(8)), this.$ = a[o].substr(8);
+              break;
+            case 23:
+              i.addTask(a[o - 1], a[o]), this.$ = "task";
+              break;
+            case 27:
+              this.$ = a[o - 1], i.setClickEvent(a[o - 1], a[o], null);
+              break;
+            case 28:
+              this.$ = a[o - 2], i.setClickEvent(a[o - 2], a[o - 1], a[o]);
+              break;
+            case 29:
+              this.$ = a[o - 2], i.setClickEvent(a[o - 2], a[o - 1], null), i.setLink(a[o - 2], a[o]);
+              break;
+            case 30:
+              this.$ = a[o - 3], i.setClickEvent(a[o - 3], a[o - 2], a[o - 1]), i.setLink(a[o - 3], a[o]);
+              break;
+            case 31:
+              this.$ = a[o - 2], i.setClickEvent(a[o - 2], a[o], null), i.setLink(a[o - 2], a[o - 1]);
+              break;
+            case 32:
+              this.$ = a[o - 3], i.setClickEvent(a[o - 3], a[o - 1], a[o]), i.setLink(a[o - 3], a[o - 2]);
+              break;
+            case 33:
+              this.$ = a[o - 1], i.setLink(a[o - 1], a[o]);
+              break;
+            case 34:
+            case 40:
+              this.$ = a[o - 1] + " " + a[o];
+              break;
+            case 35:
+            case 36:
+            case 38:
+              this.$ = a[o - 2] + " " + a[o - 1] + " " + a[o];
+              break;
+            case 37:
+            case 39:
+              this.$ = a[o - 3] + " " + a[o - 2] + " " + a[o - 1] + " " + a[o];
+              break;
+            case 41:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 42:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 43:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 44:
+              i.parseDirective("}%%", "close_directive", "gantt");
+          }
+        },
+        table: [
+          { 3: 1, 4: 2, 5: n, 30: 4, 40: i },
+          { 1: [3] },
+          { 3: 6, 4: 2, 5: n, 30: 4, 40: i },
+          e(r, [2, 3], { 6: 7 }),
+          { 31: 8, 41: [1, 9] },
+          { 41: [2, 41] },
+          { 1: [2, 1] },
+          {
+            4: 30,
+            7: [1, 10],
+            8: 11,
+            9: [1, 12],
+            10: 13,
+            11: [1, 14],
+            12: a,
+            13: s,
+            14: o,
+            15: l,
+            16: c,
+            17: h,
+            18: u,
+            19: d,
+            20: p,
+            21: f,
+            23: g,
+            25: y,
+            26: m,
+            27: 28,
+            28: b,
+            30: 4,
+            35: _,
+            40: i,
+          },
+          { 32: 32, 33: [1, 33], 43: x },
+          e([33, 43], [2, 42]),
+          e(r, [2, 8], { 1: [2, 2] }),
+          e(r, [2, 4]),
+          {
+            4: 30,
+            10: 35,
+            12: a,
+            13: s,
+            14: o,
+            15: l,
+            16: c,
+            17: h,
+            18: u,
+            19: d,
+            20: p,
+            21: f,
+            23: g,
+            25: y,
+            26: m,
+            27: 28,
+            28: b,
+            30: 4,
+            35: _,
+            40: i,
+          },
+          e(r, [2, 6]),
+          e(r, [2, 7]),
+          e(r, [2, 9]),
+          e(r, [2, 10]),
+          e(r, [2, 11]),
+          e(r, [2, 12]),
+          e(r, [2, 13]),
+          e(r, [2, 14]),
+          e(r, [2, 15]),
+          e(r, [2, 16]),
+          e(r, [2, 17]),
+          { 22: [1, 36] },
+          { 24: [1, 37] },
+          e(r, [2, 20]),
+          e(r, [2, 21]),
+          e(r, [2, 22]),
+          { 29: [1, 38] },
+          e(r, [2, 24]),
+          { 36: [1, 39], 38: [1, 40] },
+          { 11: [1, 41] },
+          { 34: 42, 42: [1, 43] },
+          { 11: [2, 44] },
+          e(r, [2, 5]),
+          e(r, [2, 18]),
+          e(r, [2, 19]),
+          e(r, [2, 23]),
+          e(r, [2, 27], { 37: [1, 44], 38: [1, 45] }),
+          e(r, [2, 33], { 36: [1, 46] }),
+          e(v, [2, 25]),
+          { 32: 47, 43: x },
+          { 43: [2, 43] },
+          e(r, [2, 28], { 38: [1, 48] }),
+          e(r, [2, 29]),
+          e(r, [2, 31], { 37: [1, 49] }),
+          { 11: [1, 50] },
+          e(r, [2, 30]),
+          e(r, [2, 32]),
+          e(v, [2, 26]),
+        ],
+        defaultActions: { 5: [2, 41], 6: [2, 1], 34: [2, 44], 43: [2, 43] },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      w = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: { "case-insensitive": !0 },
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("open_directive"), 40;
+            case 1:
+              return this.begin("type_directive"), 41;
+            case 2:
+              return this.popState(), this.begin("arg_directive"), 33;
+            case 3:
+              return this.popState(), this.popState(), 43;
+            case 4:
+              return 42;
+            case 5:
+              return this.begin("acc_title"), 21;
+            case 6:
+              return this.popState(), "acc_title_value";
+            case 7:
+              return this.begin("acc_descr"), 23;
+            case 8:
+              return this.popState(), "acc_descr_value";
+            case 9:
+              this.begin("acc_descr_multiline");
+              break;
+            case 10:
+            case 20:
+            case 23:
+            case 26:
+            case 29:
+              this.popState();
+              break;
+            case 11:
+              return "acc_descr_multiline_value";
+            case 12:
+            case 13:
+            case 14:
+            case 16:
+            case 17:
+            case 18:
+              break;
+            case 15:
+              return 11;
+            case 19:
+              this.begin("href");
+              break;
+            case 21:
+              return 38;
+            case 22:
+              this.begin("callbackname");
+              break;
+            case 24:
+              this.popState(), this.begin("callbackargs");
+              break;
+            case 25:
+              return 36;
+            case 27:
+              return 37;
+            case 28:
+              this.begin("click");
+              break;
+            case 30:
+              return 35;
+            case 31:
+              return 5;
+            case 32:
+              return 12;
+            case 33:
+              return 13;
+            case 34:
+              return 14;
+            case 35:
+              return 15;
+            case 36:
+              return 16;
+            case 37:
+              return 18;
+            case 38:
+              return 17;
+            case 39:
+              return 19;
+            case 40:
+              return "date";
+            case 41:
+              return 20;
+            case 42:
+              return "accDescription";
+            case 43:
+              return 26;
+            case 44:
+              return 28;
+            case 45:
+              return 29;
+            case 46:
+              return 33;
+            case 47:
+              return 7;
+            case 48:
+              return "INVALID";
+          }
+        },
+        rules: [
+          /^(?:%%\{)/i,
+          /^(?:((?:(?!\}%%)[^:.])*))/i,
+          /^(?::)/i,
+          /^(?:\}%%)/i,
+          /^(?:((?:(?!\}%%).|\n)*))/i,
+          /^(?:accTitle\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*\{\s*)/i,
+          /^(?:[\}])/i,
+          /^(?:[^\}]*)/i,
+          /^(?:%%(?!\{)*[^\n]*)/i,
+          /^(?:[^\}]%%*[^\n]*)/i,
+          /^(?:%%*[^\n]*[\n]*)/i,
+          /^(?:[\n]+)/i,
+          /^(?:\s+)/i,
+          /^(?:#[^\n]*)/i,
+          /^(?:%[^\n]*)/i,
+          /^(?:href[\s]+["])/i,
+          /^(?:["])/i,
+          /^(?:[^"]*)/i,
+          /^(?:call[\s]+)/i,
+          /^(?:\([\s]*\))/i,
+          /^(?:\()/i,
+          /^(?:[^(]*)/i,
+          /^(?:\))/i,
+          /^(?:[^)]*)/i,
+          /^(?:click[\s]+)/i,
+          /^(?:[\s\n])/i,
+          /^(?:[^\s\n]*)/i,
+          /^(?:gantt\b)/i,
+          /^(?:dateFormat\s[^#\n;]+)/i,
+          /^(?:inclusiveEndDates\b)/i,
+          /^(?:topAxis\b)/i,
+          /^(?:axisFormat\s[^#\n;]+)/i,
+          /^(?:tickInterval\s[^#\n;]+)/i,
+          /^(?:includes\s[^#\n;]+)/i,
+          /^(?:excludes\s[^#\n;]+)/i,
+          /^(?:todayMarker\s[^\n;]+)/i,
+          /^(?:\d\d\d\d-\d\d-\d\d\b)/i,
+          /^(?:title\s[^#\n;]+)/i,
+          /^(?:accDescription\s[^#\n;]+)/i,
+          /^(?:section\s[^#:\n;]+)/i,
+          /^(?:[^#:\n;]+)/i,
+          /^(?::[^#\n;]+)/i,
+          /^(?::)/i,
+          /^(?:$)/i,
+          /^(?:.)/i,
+        ],
+        conditions: {
+          acc_descr_multiline: { rules: [10, 11], inclusive: !1 },
+          acc_descr: { rules: [8], inclusive: !1 },
+          acc_title: { rules: [6], inclusive: !1 },
+          close_directive: { rules: [], inclusive: !1 },
+          arg_directive: { rules: [3, 4], inclusive: !1 },
+          type_directive: { rules: [2, 3], inclusive: !1 },
+          open_directive: { rules: [1], inclusive: !1 },
+          callbackargs: { rules: [26, 27], inclusive: !1 },
+          callbackname: { rules: [23, 24, 25], inclusive: !1 },
+          href: { rules: [20, 21], inclusive: !1 },
+          click: { rules: [29, 30], inclusive: !1 },
+          INITIAL: {
+            rules: [
+              0,
+              5,
+              7,
+              9,
+              12,
+              13,
+              14,
+              15,
+              16,
+              17,
+              18,
+              19,
+              22,
+              28,
+              31,
+              32,
+              33,
+              34,
+              35,
+              36,
+              37,
+              38,
+              39,
+              40,
+              41,
+              42,
+              43,
+              44,
+              45,
+              46,
+              47,
+              48,
+            ],
+            inclusive: !0,
+          },
+        },
+      },
+        t);
+    function T() {
+      this.yy = {};
+    }
+    return k.lexer = w, T.prototype = k, k.Parser = T, new T();
+  }();
+  wC.parser = wC;
+  const TC = wC, CC = t => null !== t.match(/^\s*gantt/);
+  let EC, SC = "", AC = "", DC = "", LC = [], OC = [], NC = {}, MC = [], BC = [], IC = "";
+  const FC = ["active", "done", "crit", "milestone"];
+  let RC = [], $C = !1, PC = !1, YC = 0;
+  const jC = function(t, e, n, i) {
+      return !i.includes(t.format(e.trim()))
+        && (!!(t.isoWeekday() >= 6 && n.includes("weekends"))
+          || (!!n.includes(t.format("dddd").toLowerCase()) || n.includes(t.format(e.trim()))));
+    },
+    zC = function(t, n, i, r) {
+      if (!i.length || t.manualEndTime) return;
+      let a = e(t.startTime, n, !0);
+      a.add(1, "d");
+      let s = e(t.endTime, n, !0), o = UC(a, s, n, i, r);
+      t.endTime = s.toDate(), t.renderEndTime = o;
+    },
+    UC = function(t, e, n, i, r) {
+      let a = !1, s = null;
+      for (; t <= e;) a || (s = e.toDate()), a = jC(t, n, i, r), a && e.add(1, "d"), t.add(1, "d");
+      return s;
+    },
+    WC = function(t, n, i) {
+      i = i.trim();
+      const r = /^after\s+([\d\w- ]+)/.exec(i.trim());
+      if (null !== r) {
+        let t = null;
+        if (
+          r[1].split(" ").forEach(function(e) {
+            let n = JC(e);
+            void 0 !== n && (t ? n.endTime > t.endTime && (t = n) : t = n);
+          }), t
+        ) return t.endTime;
+        {
+          const t = new Date();
+          return t.setHours(0, 0, 0, 0), t;
+        }
+      }
+      let a = e(i, n.trim(), !0);
+      if (a.isValid()) return a.toDate();
+      {
+        tb.debug("Invalid date:" + i), tb.debug("With date format:" + n.trim());
+        const t = new Date(i);
+        if (void 0 === t || isNaN(t.getTime())) throw new Error("Invalid date:" + i);
+        return t;
+      }
+    },
+    HC = function(t) {
+      const n = /^(\d+(?:\.\d+)?)([Mdhmswy]|ms)$/.exec(t.trim());
+      return null !== n ? e.duration(Number.parseFloat(n[1]), n[2]) : e.duration.invalid();
+    },
+    qC = function(t, n, i, r = !1) {
+      i = i.trim();
+      let a = e(i, n.trim(), !0);
+      if (a.isValid()) return r && a.add(1, "d"), a.toDate();
+      const s = e(t), o = HC(i);
+      return o.isValid() && s.add(o), s.toDate();
+    };
+  let VC = 0;
+  const GC = function(t) {
+    return void 0 === t ? (VC += 1, "task" + VC) : t;
+  };
+  let XC, ZC, QC = [];
+  const KC = {},
+    JC = function(t) {
+      const e = KC[t];
+      return QC[e];
+    },
+    tE = function() {
+      const t = function(t) {
+        const n = QC[t];
+        let i = "";
+        switch (QC[t].raw.startTime.type) {
+          case "prevTaskEnd": {
+            const t = JC(n.prevTaskId);
+            n.startTime = t.endTime;
+            break;
+          }
+          case "getStartDate":
+            i = WC(0, SC, QC[t].raw.startTime.startData), i && (QC[t].startTime = i);
+        }
+        return QC[t].startTime
+          && (QC[t].endTime = qC(QC[t].startTime, SC, QC[t].raw.endTime.data, $C),
+            QC[t].endTime
+            && (QC[t].processed = !0,
+              QC[t].manualEndTime = e(QC[t].raw.endTime.data, "YYYY-MM-DD", !0).isValid(),
+              zC(QC[t], SC, OC, LC))),
+          QC[t].processed;
+      };
+      let n = !0;
+      for (const [e, i] of QC.entries()) t(e), n = n && i.processed;
+      return n;
+    },
+    eE = function(t, e) {
+      t.split(",").forEach(function(t) {
+        let n = JC(t);
+        void 0 !== n && n.classes.push(e);
+      });
+    },
+    nE = function(t, e) {
+      RC.push(function() {
+        const n = document.querySelector(`[id="${t}"]`);
+        null !== n && n.addEventListener("click", function() {
+          e();
+        });
+      }, function() {
+        const n = document.querySelector(`[id="${t}-text"]`);
+        null !== n && n.addEventListener("click", function() {
+          e();
+        });
+      });
+    },
+    iE = {
+      parseDirective: function(t, e, n) {
+        nL.parseDirective(this, t, e, n);
+      },
+      getConfig: () => jx().gantt,
+      clear: function() {
+        MC = [],
+          BC = [],
+          IC = "",
+          RC = [],
+          VC = 0,
+          XC = void 0,
+          ZC = void 0,
+          QC = [],
+          SC = "",
+          AC = "",
+          EC = void 0,
+          DC = "",
+          LC = [],
+          OC = [],
+          $C = !1,
+          PC = !1,
+          YC = 0,
+          NC = {},
+          Cv();
+      },
+      setDateFormat: function(t) {
+        SC = t;
+      },
+      getDateFormat: function() {
+        return SC;
+      },
+      enableInclusiveEndDates: function() {
+        $C = !0;
+      },
+      endDatesAreInclusive: function() {
+        return $C;
+      },
+      enableTopAxis: function() {
+        PC = !0;
+      },
+      topAxisEnabled: function() {
+        return PC;
+      },
+      setAxisFormat: function(t) {
+        AC = t;
+      },
+      getAxisFormat: function() {
+        return AC;
+      },
+      setTickInterval: function(t) {
+        EC = t;
+      },
+      getTickInterval: function() {
+        return EC;
+      },
+      setTodayMarker: function(t) {
+        DC = t;
+      },
+      getTodayMarker: function() {
+        return DC;
+      },
+      setAccTitle: Ev,
+      getAccTitle: Sv,
+      setDiagramTitle: Lv,
+      getDiagramTitle: Ov,
+      setAccDescription: Av,
+      getAccDescription: Dv,
+      addSection: function(t) {
+        IC = t, MC.push(t);
+      },
+      getSections: function() {
+        return MC;
+      },
+      getTasks: function() {
+        let t = tE();
+        let e = 0;
+        for (; !t && e < 10;) t = tE(), e++;
+        return BC = QC, BC;
+      },
+      addTask: function(t, e) {
+        const n = {
+            section: IC,
+            type: IC,
+            processed: !1,
+            manualEndTime: !1,
+            renderEndTime: null,
+            raw: { data: e },
+            task: t,
+            classes: [],
+          },
+          i = function(t, e) {
+            let n;
+            n = ":" === e.substr(0, 1) ? e.substr(1, e.length) : e;
+            const i = n.split(","), r = {};
+            rE(i, r, FC);
+            for (let t = 0; t < i.length; t++) i[t] = i[t].trim();
+            switch (i.length) {
+              case 1:
+                r.id = GC(), r.startTime = { type: "prevTaskEnd", id: t }, r.endTime = { data: i[0] };
+                break;
+              case 2:
+                r.id = GC(), r.startTime = { type: "getStartDate", startData: i[0] }, r.endTime = { data: i[1] };
+                break;
+              case 3:
+                r.id = GC(i[0]), r.startTime = { type: "getStartDate", startData: i[1] }, r.endTime = { data: i[2] };
+            }
+            return r;
+          }(ZC, e);
+        n.raw.startTime = i.startTime,
+          n.raw.endTime = i.endTime,
+          n.id = i.id,
+          n.prevTaskId = ZC,
+          n.active = i.active,
+          n.done = i.done,
+          n.crit = i.crit,
+          n.milestone = i.milestone,
+          n.order = YC,
+          YC++;
+        const r = QC.push(n);
+        ZC = n.id, KC[n.id] = r - 1;
+      },
+      findTaskById: JC,
+      addTaskOrg: function(t, n) {
+        const i = { section: IC, type: IC, description: t, task: t, classes: [] },
+          r = function(t, n) {
+            let i;
+            i = ":" === n.substr(0, 1) ? n.substr(1, n.length) : n;
+            const r = i.split(","), a = {};
+            rE(r, a, FC);
+            for (let t = 0; t < r.length; t++) r[t] = r[t].trim();
+            let s = "";
+            switch (r.length) {
+              case 1:
+                a.id = GC(), a.startTime = t.endTime, s = r[0];
+                break;
+              case 2:
+                a.id = GC(), a.startTime = WC(0, SC, r[0]), s = r[1];
+                break;
+              case 3:
+                a.id = GC(r[0]), a.startTime = WC(0, SC, r[1]), s = r[2];
+            }
+            return s
+              && (a.endTime = qC(a.startTime, SC, s, $C),
+                a.manualEndTime = e(s, "YYYY-MM-DD", !0).isValid(),
+                zC(a, SC, OC, LC)),
+              a;
+          }(XC, n);
+        i.startTime = r.startTime,
+          i.endTime = r.endTime,
+          i.id = r.id,
+          i.active = r.active,
+          i.done = r.done,
+          i.crit = r.crit,
+          i.milestone = r.milestone,
+          XC = i,
+          BC.push(i);
+      },
+      setIncludes: function(t) {
+        LC = t.toLowerCase().split(/[\s,]+/);
+      },
+      getIncludes: function() {
+        return LC;
+      },
+      setExcludes: function(t) {
+        OC = t.toLowerCase().split(/[\s,]+/);
+      },
+      getExcludes: function() {
+        return OC;
+      },
+      setClickEvent: function(t, e, n) {
+        t.split(",").forEach(function(t) {
+          !function(t, e, n) {
+            if ("loose" !== jx().securityLevel) return;
+            if (void 0 === e) return;
+            let i = [];
+            if ("string" == typeof n) {
+              i = n.split(/,(?=(?:(?:[^"]*"){2})*[^"]*$)/);
+              for (let t = 0; t < i.length; t++) {
+                let e = i[t].trim();
+                "\"" === e.charAt(0) && "\"" === e.charAt(e.length - 1) && (e = e.substr(1, e.length - 2)), i[t] = e;
+              }
+            }
+            0 === i.length && i.push(t),
+              void 0 !== JC(t) && nE(t, () => {
+                Dx.runFunc(e, ...i);
+              });
+          }(t, e, n);
+        }), eE(t, "clickable");
+      },
+      setLink: function(t, e) {
+        let n = e;
+        "loose" !== jx().securityLevel && (n = i(e)),
+          t.split(",").forEach(function(t) {
+            void 0 !== JC(t) && (nE(t, () => {
+              window.open(n, "_self");
+            }),
+              NC[t] = n);
+          }),
+          eE(t, "clickable");
+      },
+      getLinks: function() {
+        return NC;
+      },
+      bindFunctions: function(t) {
+        RC.forEach(function(e) {
+          e(t);
+        });
+      },
+      parseDuration: HC,
+      isInvalidDate: jC,
+    };
+  function rE(t, e, n) {
+    let i = !0;
+    for (; i;) {
+      i = !1,
+        n.forEach(function(n) {
+          const r = new RegExp("^\\s*" + n + "\\s*$");
+          t[0].match(r) && (e[n] = !0, t.shift(1), i = !0);
+        });
+    }
+  }
+  let aE;
+  const sE = {
+    setConf: function() {
+      tb.debug("Something is calling, setConf, remove the call");
+    },
+    draw: function(t, n, i, r) {
+      const a = jx().gantt, s = jx().securityLevel;
+      let o;
+      "sandbox" === s && (o = ie("#i" + n));
+      const l = ie("sandbox" === s ? o.nodes()[0].contentDocument.body : "body"),
+        c = "sandbox" === s ? o.nodes()[0].contentDocument : document,
+        h = c.getElementById(n);
+      aE = h.parentElement.offsetWidth, void 0 === aE && (aE = 1200), void 0 !== a.useWidth && (aE = a.useWidth);
+      const u = r.db.getTasks(), d = u.length * (a.barHeight + a.barGap) + 2 * a.topPadding;
+      h.setAttribute("viewBox", "0 0 " + aE + " " + d);
+      const p = l.select(`[id="${n}"]`),
+        f = Es().domain([
+          S(u, function(t) {
+            return t.startTime;
+          }),
+          E(u, function(t) {
+            return t.endTime;
+          }),
+        ]).rangeRound([0, aE - a.leftPadding - a.rightPadding]);
+      let g = [];
+      for (const t of u) g.push(t.type);
+      const y = g;
+      function m(t, e) {
+        return function(t) {
+          let e = t.length;
+          const n = {};
+          for (; e;) n[t[--e]] = (n[t[e]] || 0) + 1;
+          return n;
+        }(e)[t] || 0;
+      }
+      g = function(t) {
+        const e = {}, n = [];
+        for (let i = 0, r = t.length; i < r; ++i) {
+          Object.prototype.hasOwnProperty.call(e, t[i]) || (e[t[i]] = !0, n.push(t[i]));
+        }
+        return n;
+      }(g),
+        u.sort(function(t, e) {
+          const n = t.startTime, i = e.startTime;
+          let r = 0;
+          return n > i ? r = 1 : n < i && (r = -1), r;
+        }),
+        function(t, i, s) {
+          const o = a.barHeight, l = o + a.barGap, h = a.topPadding, u = a.leftPadding;
+          dr().domain([0, g.length]).range(["#00B9FA", "#F95002"]).interpolate(Dn);
+          (function(t, n, i, s, o, l, c, h) {
+            const u = l.reduce((t, { startTime: e }) => t ? Math.min(t, e) : e, 0),
+              d = l.reduce((t, { endTime: e }) => t ? Math.max(t, e) : e, 0),
+              g = r.db.getDateFormat();
+            if (!u || !d) return;
+            const y = [];
+            let m = null, b = e(u);
+            for (; b.valueOf() <= d;) {
+              r.db.isInvalidDate(b, g, c, h)
+                ? m ? m.end = b.clone() : m = { start: b.clone(), end: b.clone() }
+                : m && (y.push(m), m = null), b.add(1, "d");
+            }
+            p.append("g").selectAll("rect").data(y).enter().append("rect").attr("id", function(t) {
+              return "exclude-" + t.start.format("YYYY-MM-DD");
+            }).attr("x", function(t) {
+              return f(t.start) + i;
+            }).attr("y", a.gridLineStartPadding).attr("width", function(t) {
+              const e = t.end.clone().add(1, "day");
+              return f(e) - f(t.start);
+            }).attr("height", o - n - a.gridLineStartPadding).attr("transform-origin", function(e, n) {
+              return (f(e.start) + i + .5 * (f(e.end) - f(e.start))).toString() + "px " + (n * t + .5 * o).toString()
+                + "px";
+            }).attr("class", "exclude-range");
+          })(l, h, u, 0, s, t, r.db.getExcludes(), r.db.getIncludes()),
+            function(t, e, n, i) {
+              let s = (o = f, P(O, o)).tickSize(-i + e + a.gridLineStartPadding).tickFormat(
+                aa(r.db.getAxisFormat() || a.axisFormat || "%Y-%m-%d"),
+              );
+              var o;
+              const l = /^([1-9]\d*)(minute|hour|day|week|month)$/.exec(r.db.getTickInterval() || a.tickInterval);
+              if (null !== l) {
+                const t = l[1];
+                switch (l[2]) {
+                  case "minute":
+                    s.ticks(Cr.every(t));
+                    break;
+                  case "hour":
+                    s.ticks(Sr.every(t));
+                    break;
+                  case "day":
+                    s.ticks(Dr.every(t));
+                    break;
+                  case "week":
+                    s.ticks(Mr.every(t));
+                    break;
+                  case "month":
+                    s.ticks(Gr.every(t));
+                }
+              }
+              if (
+                p.append("g").attr("class", "grid").attr("transform", "translate(" + t + ", " + (i - 50) + ")").call(s)
+                  .selectAll("text").style("text-anchor", "middle").attr("fill", "#000").attr("stroke", "none").attr(
+                    "font-size",
+                    10,
+                  ).attr("dy", "1em"), r.db.topAxisEnabled() || a.topAxis
+              ) {
+                let n = function(t) {
+                  return P(D, t);
+                }(f).tickSize(-i + e + a.gridLineStartPadding).tickFormat(
+                  aa(r.db.getAxisFormat() || a.axisFormat || "%Y-%m-%d"),
+                );
+                if (null !== l) {
+                  const t = l[1];
+                  switch (l[2]) {
+                    case "minute":
+                      n.ticks(Cr.every(t));
+                      break;
+                    case "hour":
+                      n.ticks(Sr.every(t));
+                      break;
+                    case "day":
+                      n.ticks(Dr.every(t));
+                      break;
+                    case "week":
+                      n.ticks(Mr.every(t));
+                      break;
+                    case "month":
+                      n.ticks(Gr.every(t));
+                  }
+                }
+                p.append("g").attr("class", "grid").attr("transform", "translate(" + t + ", " + e + ")").call(n)
+                  .selectAll("text").style("text-anchor", "middle").attr("fill", "#000").attr("stroke", "none").attr(
+                    "font-size",
+                    10,
+                  );
+              }
+            }(u, h, 0, s),
+            function(t, e, i, s, o, l, c) {
+              p.append("g").selectAll("rect").data(t).enter().append("rect").attr("x", 0).attr("y", function(t, n) {
+                return t.order * e + i - 2;
+              }).attr("width", function() {
+                return c - a.rightPadding / 2;
+              }).attr("height", e).attr("class", function(t) {
+                for (const [e, n] of g.entries()) {
+                  if (t.type === n) return "section section" + e % a.numberSectionStyles;
+                }
+                return "section section0";
+              });
+              const h = p.append("g").selectAll("rect").data(t).enter(), u = r.db.getLinks();
+              h.append("rect").attr("id", function(t) {
+                return t.id;
+              }).attr("rx", 3).attr("ry", 3).attr("x", function(t) {
+                return t.milestone
+                  ? f(t.startTime) + s + .5 * (f(t.endTime) - f(t.startTime)) - .5 * o
+                  : f(t.startTime) + s;
+              }).attr("y", function(t, n) {
+                return t.order * e + i;
+              }).attr("width", function(t) {
+                return t.milestone ? o : f(t.renderEndTime || t.endTime) - f(t.startTime);
+              }).attr("height", o).attr("transform-origin", function(t, n) {
+                return n = t.order,
+                  (f(t.startTime) + s + .5 * (f(t.endTime) - f(t.startTime))).toString() + "px "
+                  + (n * e + i + .5 * o).toString() + "px";
+              }).attr("class", function(t) {
+                const e = "task";
+                let n = "";
+                t.classes.length > 0 && (n = t.classes.join(" "));
+                let i = 0;
+                for (const [e, n] of g.entries()) t.type === n && (i = e % a.numberSectionStyles);
+                let r = "";
+                return t.active
+                  ? t.crit ? r += " activeCrit" : r = " active"
+                  : t.done
+                  ? r = t.crit ? " doneCrit" : " done"
+                  : t.crit && (r += " crit"),
+                  0 === r.length && (r = " task"),
+                  t.milestone && (r = " milestone " + r),
+                  r += i,
+                  r += " " + n,
+                  e + r;
+              }),
+                h.append("text").attr("id", function(t) {
+                  return t.id + "-text";
+                }).text(function(t) {
+                  return t.task;
+                }).attr("font-size", a.fontSize).attr("x", function(t) {
+                  let e = f(t.startTime), n = f(t.renderEndTime || t.endTime);
+                  t.milestone && (e += .5 * (f(t.endTime) - f(t.startTime)) - .5 * o), t.milestone && (n = e + o);
+                  const i = this.getBBox().width;
+                  return i > n - e ? n + i + 1.5 * a.leftPadding > c ? e + s - 5 : n + s + 5 : (n - e) / 2 + e + s;
+                }).attr("y", function(t, n) {
+                  return t.order * e + a.barHeight / 2 + (a.fontSize / 2 - 2) + i;
+                }).attr("text-height", o).attr("class", function(t) {
+                  const e = f(t.startTime);
+                  let n = f(t.endTime);
+                  t.milestone && (n = e + o);
+                  const i = this.getBBox().width;
+                  let r = "";
+                  t.classes.length > 0 && (r = t.classes.join(" "));
+                  let s = 0;
+                  for (const [e, n] of g.entries()) t.type === n && (s = e % a.numberSectionStyles);
+                  let l = "";
+                  return t.active && (l = t.crit ? "activeCritText" + s : "activeText" + s),
+                    t.done
+                      ? l = t.crit ? l + " doneCritText" + s : l + " doneText" + s
+                      : t.crit && (l = l + " critText" + s),
+                    t.milestone && (l += " milestoneText"),
+                    i > n - e
+                      ? n + i + 1.5 * a.leftPadding > c
+                        ? r + " taskTextOutsideLeft taskTextOutside" + s + " " + l
+                        : r + " taskTextOutsideRight taskTextOutside" + s + " " + l + " width-" + i
+                      : r + " taskText taskText" + s + " " + l + " width-" + i;
+                });
+              if ("sandbox" === jx().securityLevel) {
+                let t;
+                t = ie("#i" + n);
+                const e = t.nodes()[0].contentDocument;
+                h.filter(function(t) {
+                  return void 0 !== u[t.id];
+                }).each(function(t) {
+                  var n = e.querySelector("#" + t.id), i = e.querySelector("#" + t.id + "-text");
+                  const r = n.parentNode;
+                  var a = e.createElement("a");
+                  a.setAttribute("xlink:href", u[t.id]),
+                    a.setAttribute("target", "_top"),
+                    r.appendChild(a),
+                    a.appendChild(n),
+                    a.appendChild(i);
+                });
+              }
+            }(t, l, h, u, o, 0, i),
+            function(t, e) {
+              const n = [];
+              let i = 0;
+              for (const [t, e] of g.entries()) n[t] = [e, m(e, y)];
+              p.append("g").selectAll("text").data(n).enter().append(function(t) {
+                const e = t[0].split(ub.lineBreakRegex),
+                  n = -(e.length - 1) / 2,
+                  i = c.createElementNS("http://www.w3.org/2000/svg", "text");
+                i.setAttribute("dy", n + "em");
+                for (const [t, n] of e.entries()) {
+                  const e = c.createElementNS("http://www.w3.org/2000/svg", "tspan");
+                  e.setAttribute("alignment-baseline", "central"),
+                    e.setAttribute("x", "10"),
+                    t > 0 && e.setAttribute("dy", "1em"),
+                    e.textContent = n,
+                    i.appendChild(e);
+                }
+                return i;
+              }).attr("x", 10).attr("y", function(r, a) {
+                if (!(a > 0)) return r[1] * t / 2 + e;
+                for (let s = 0; s < a; s++) {
+                  return i += n[a - 1][1], r[1] * t / 2 + i * t + e;
+                }
+              }).attr("font-size", a.sectionFontSize).attr("font-size", a.sectionFontSize).attr("class", function(t) {
+                for (const [e, n] of g.entries()) {
+                  if (t[0] === n) {
+                    return "sectionTitle sectionTitle" + e % a.numberSectionStyles;
+                  }
+                }
+                return "sectionTitle";
+              });
+            }(l, h),
+            function(t, e, n, i) {
+              const s = r.db.getTodayMarker();
+              if ("off" === s) {
+                return;
+              }
+              const o = p.append("g").attr("class", "today"), l = new Date(), c = o.append("line");
+              c.attr("x1", f(l) + t).attr("x2", f(l) + t).attr("y1", a.titleTopMargin).attr("y2", i - a.titleTopMargin)
+                .attr("class", "today"), "" !== s && c.attr("style", s.replace(/,/g, ";"));
+            }(u, 0, 0, s);
+        }(u, aE, d),
+        Gx(p, d, aE, a.useMaxWidth),
+        p.append("text").text(r.db.getDiagramTitle()).attr("x", aE / 2).attr("y", a.titleTopMargin).attr(
+          "class",
+          "titleText",
+        );
+    },
+  };
+  var oE = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [6, 9, 10],
+      i = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          info: 4,
+          document: 5,
+          EOF: 6,
+          line: 7,
+          statement: 8,
+          NL: 9,
+          showInfo: 10,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: { 2: "error", 4: "info", 6: "EOF", 9: "NL", 10: "showInfo" },
+        productions_: [0, [3, 3], [5, 0], [5, 2], [7, 1], [7, 1], [8, 1]],
+        performAction: function(t, e, n, i, r, a, s) {
+          switch (a.length, r) {
+            case 1:
+              return i;
+            case 4:
+              break;
+            case 6:
+              i.setInfo(!0);
+          }
+        },
+        table: [
+          { 3: 1, 4: [1, 2] },
+          { 1: [3] },
+          e(n, [2, 2], { 5: 3 }),
+          { 6: [1, 4], 7: 5, 8: 6, 9: [1, 7], 10: [1, 8] },
+          { 1: [2, 1] },
+          e(n, [2, 3]),
+          e(n, [2, 4]),
+          e(n, [2, 5]),
+          e(n, [2, 6]),
+        ],
+        defaultActions: { 4: [2, 1] },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      r = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: { "case-insensitive": !0 },
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return 4;
+            case 1:
+              return 9;
+            case 2:
+              return "space";
+            case 3:
+              return 10;
+            case 4:
+              return 6;
+            case 5:
+              return "TXT";
+          }
+        },
+        rules: [/^(?:info\b)/i, /^(?:[\s\n\r]+)/i, /^(?:[\s]+)/i, /^(?:showInfo\b)/i, /^(?:$)/i, /^(?:.)/i],
+        conditions: { INITIAL: { rules: [0, 1, 2, 3, 4, 5], inclusive: !0 } },
+      },
+        t);
+    function a() {
+      this.yy = {};
+    }
+    return i.lexer = r, a.prototype = i, i.Parser = a, new a();
+  }();
+  oE.parser = oE;
+  const lE = oE;
+  var cE = "", hE = !1;
+  const uE = {
+      setMessage: t => {
+        tb.debug("Setting message to: " + t), cE = t;
+      },
+      getMessage: () => cE,
+      setInfo: t => {
+        hE = t;
+      },
+      getInfo: () => hE,
+      clear: Cv,
+    },
+    dE = {
+      draw: (t, e, n) => {
+        try {
+          tb.debug("Rendering info diagram\n" + t);
+          const i = jx().securityLevel;
+          let r;
+          "sandbox" === i && (r = ie("#i" + e));
+          const a = ie("sandbox" === i ? r.nodes()[0].contentDocument.body : "body").select("#" + e);
+          a.append("g").append("text").attr("x", 100).attr("y", 40).attr("class", "version").attr("font-size", "32px")
+            .style("text-anchor", "middle").text("v " + n),
+            a.attr("height", 100),
+            a.attr("width", 400);
+        } catch (t) {
+          tb.error("Error while rendering info diagram"), tb.error(t.message);
+        }
+      },
+    },
+    pE = t => null !== t.match(/^\s*info/);
+  var fE = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [1, 4],
+      i = [1, 5],
+      r = [1, 6],
+      a = [1, 7],
+      s = [1, 9],
+      o = [1, 11, 13, 15, 17, 19, 20, 26, 27, 28, 29],
+      l = [2, 5],
+      c = [1, 6, 11, 13, 15, 17, 19, 20, 26, 27, 28, 29],
+      h = [26, 27, 28],
+      u = [2, 8],
+      d = [1, 18],
+      p = [1, 19],
+      f = [1, 20],
+      g = [1, 21],
+      y = [1, 22],
+      m = [1, 23],
+      b = [1, 28],
+      _ = [6, 26, 27, 28, 29],
+      x = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          eol: 4,
+          directive: 5,
+          PIE: 6,
+          document: 7,
+          showData: 8,
+          line: 9,
+          statement: 10,
+          txt: 11,
+          value: 12,
+          title: 13,
+          title_value: 14,
+          acc_title: 15,
+          acc_title_value: 16,
+          acc_descr: 17,
+          acc_descr_value: 18,
+          acc_descr_multiline_value: 19,
+          section: 20,
+          openDirective: 21,
+          typeDirective: 22,
+          closeDirective: 23,
+          ":": 24,
+          argDirective: 25,
+          NEWLINE: 26,
+          ";": 27,
+          EOF: 28,
+          open_directive: 29,
+          type_directive: 30,
+          arg_directive: 31,
+          close_directive: 32,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: {
+          2: "error",
+          6: "PIE",
+          8: "showData",
+          11: "txt",
+          12: "value",
+          13: "title",
+          14: "title_value",
+          15: "acc_title",
+          16: "acc_title_value",
+          17: "acc_descr",
+          18: "acc_descr_value",
+          19: "acc_descr_multiline_value",
+          20: "section",
+          24: ":",
+          26: "NEWLINE",
+          27: ";",
+          28: "EOF",
+          29: "open_directive",
+          30: "type_directive",
+          31: "arg_directive",
+          32: "close_directive",
+        },
+        productions_: [
+          0,
+          [3, 2],
+          [3, 2],
+          [3, 2],
+          [3, 3],
+          [7, 0],
+          [7, 2],
+          [9, 2],
+          [10, 0],
+          [10, 2],
+          [10, 2],
+          [10, 2],
+          [10, 2],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [5, 3],
+          [5, 5],
+          [4, 1],
+          [4, 1],
+          [4, 1],
+          [21, 1],
+          [22, 1],
+          [25, 1],
+          [23, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 4:
+              i.setShowData(!0);
+              break;
+            case 7:
+              this.$ = a[o - 1];
+              break;
+            case 9:
+              i.addSection(a[o - 1], i.cleanupValue(a[o]));
+              break;
+            case 10:
+              this.$ = a[o].trim(), i.setDiagramTitle(this.$);
+              break;
+            case 11:
+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 12:
+            case 13:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 14:
+              i.addSection(a[o].substr(8)), this.$ = a[o].substr(8);
+              break;
+            case 21:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 22:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 23:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 24:
+              i.parseDirective("}%%", "close_directive", "pie");
+          }
+        },
+        table: [
+          { 3: 1, 4: 2, 5: 3, 6: n, 21: 8, 26: i, 27: r, 28: a, 29: s },
+          { 1: [3] },
+          { 3: 10, 4: 2, 5: 3, 6: n, 21: 8, 26: i, 27: r, 28: a, 29: s },
+          { 3: 11, 4: 2, 5: 3, 6: n, 21: 8, 26: i, 27: r, 28: a, 29: s },
+          e(o, l, { 7: 12, 8: [1, 13] }),
+          e(c, [2, 18]),
+          e(c, [2, 19]),
+          e(c, [2, 20]),
+          { 22: 14, 30: [1, 15] },
+          { 30: [2, 21] },
+          { 1: [2, 1] },
+          { 1: [2, 2] },
+          e(h, u, { 21: 8, 9: 16, 10: 17, 5: 24, 1: [2, 3], 11: d, 13: p, 15: f, 17: g, 19: y, 20: m, 29: s }),
+          e(o, l, { 7: 25 }),
+          { 23: 26, 24: [1, 27], 32: b },
+          e([24, 32], [2, 22]),
+          e(o, [2, 6]),
+          { 4: 29, 26: i, 27: r, 28: a },
+          { 12: [1, 30] },
+          { 14: [1, 31] },
+          { 16: [1, 32] },
+          { 18: [1, 33] },
+          e(h, [2, 13]),
+          e(h, [2, 14]),
+          e(h, [2, 15]),
+          e(h, u, { 21: 8, 9: 16, 10: 17, 5: 24, 1: [2, 4], 11: d, 13: p, 15: f, 17: g, 19: y, 20: m, 29: s }),
+          e(_, [2, 16]),
+          { 25: 34, 31: [1, 35] },
+          e(_, [2, 24]),
+          e(o, [2, 7]),
+          e(h, [2, 9]),
+          e(h, [2, 10]),
+          e(h, [2, 11]),
+          e(h, [2, 12]),
+          { 23: 36, 32: b },
+          { 32: [2, 23] },
+          e(_, [2, 17]),
+        ],
+        defaultActions: { 9: [2, 21], 10: [2, 1], 11: [2, 2], 35: [2, 23] },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      v = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: { "case-insensitive": !0 },
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("open_directive"), 29;
+            case 1:
+              return this.begin("type_directive"), 30;
+            case 2:
+              return this.popState(), this.begin("arg_directive"), 24;
+            case 3:
+              return this.popState(), this.popState(), 32;
+            case 4:
+              return 31;
+            case 5:
+            case 6:
+            case 8:
+            case 9:
+              break;
+            case 7:
+              return 26;
+            case 10:
+              return this.begin("title"), 13;
+            case 11:
+              return this.popState(), "title_value";
+            case 12:
+              return this.begin("acc_title"), 15;
+            case 13:
+              return this.popState(), "acc_title_value";
+            case 14:
+              return this.begin("acc_descr"), 17;
+            case 15:
+              return this.popState(), "acc_descr_value";
+            case 16:
+              this.begin("acc_descr_multiline");
+              break;
+            case 17:
+            case 20:
+              this.popState();
+              break;
+            case 18:
+              return "acc_descr_multiline_value";
+            case 19:
+              this.begin("string");
+              break;
+            case 21:
+              return "txt";
+            case 22:
+              return 6;
+            case 23:
+              return 8;
+            case 24:
+              return "value";
+            case 25:
+              return 28;
+          }
+        },
+        rules: [
+          /^(?:%%\{)/i,
+          /^(?:((?:(?!\}%%)[^:.])*))/i,
+          /^(?::)/i,
+          /^(?:\}%%)/i,
+          /^(?:((?:(?!\}%%).|\n)*))/i,
+          /^(?:%%(?!\{)[^\n]*)/i,
+          /^(?:[^\}]%%[^\n]*)/i,
+          /^(?:[\n\r]+)/i,
+          /^(?:%%[^\n]*)/i,
+          /^(?:[\s]+)/i,
+          /^(?:title\b)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accTitle\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*\{\s*)/i,
+          /^(?:[\}])/i,
+          /^(?:[^\}]*)/i,
+          /^(?:["])/i,
+          /^(?:["])/i,
+          /^(?:[^"]*)/i,
+          /^(?:pie\b)/i,
+          /^(?:showData\b)/i,
+          /^(?::[\s]*[\d]+(?:\.[\d]+)?)/i,
+          /^(?:$)/i,
+        ],
+        conditions: {
+          acc_descr_multiline: { rules: [17, 18], inclusive: !1 },
+          acc_descr: { rules: [15], inclusive: !1 },
+          acc_title: { rules: [13], inclusive: !1 },
+          close_directive: { rules: [], inclusive: !1 },
+          arg_directive: { rules: [3, 4], inclusive: !1 },
+          type_directive: { rules: [2, 3], inclusive: !1 },
+          open_directive: { rules: [1], inclusive: !1 },
+          title: { rules: [11], inclusive: !1 },
+          string: { rules: [20, 21], inclusive: !1 },
+          INITIAL: { rules: [0, 5, 6, 7, 8, 9, 10, 12, 14, 16, 19, 22, 23, 24, 25], inclusive: !0 },
+        },
+      },
+        t);
+    function k() {
+      this.yy = {};
+    }
+    return x.lexer = v, k.prototype = x, x.Parser = k, new k();
+  }();
+  fE.parser = fE;
+  const gE = fE, yE = t => null !== t.match(/^\s*pie/) || null !== t.match(/^\s*bar/);
+  let mE = {}, bE = !1;
+  const _E = {
+    parseDirective: function(t, e, n) {
+      nL.parseDirective(this, t, e, n);
+    },
+    getConfig: () => jx().pie,
+    addSection: function(t, e) {
+      t = ub.sanitizeText(t, jx()), void 0 === mE[t] && (mE[t] = e, tb.debug("Added new section :", t));
+    },
+    getSections: () => mE,
+    cleanupValue: function(t) {
+      return ":" === t.substring(0, 1) ? (t = t.substring(1).trim(), Number(t.trim())) : Number(t.trim());
+    },
+    clear: function() {
+      mE = {}, bE = !1, Cv();
+    },
+    setAccTitle: Ev,
+    getAccTitle: Sv,
+    setDiagramTitle: Lv,
+    getDiagramTitle: Ov,
+    setShowData: function(t) {
+      bE = t;
+    },
+    getShowData: function() {
+      return bE;
+    },
+    getAccDescription: Dv,
+    setAccDescription: Av,
+  };
+  let xE, vE = jx();
+  const kE = 450,
+    wE = {
+      draw: (t, e, n, i) => {
+        try {
+          vE = jx(), tb.debug("Rendering info diagram\n" + t);
+          const n = jx().securityLevel;
+          let y;
+          "sandbox" === n && (y = ie("#i" + e));
+          const m = ie("sandbox" === n ? y.nodes()[0].contentDocument.body : "body"),
+            b = "sandbox" === n ? y.nodes()[0].contentDocument : document;
+          i.db.clear(), i.parser.parse(t), tb.debug("Parsed info diagram");
+          const _ = b.getElementById(e);
+          xE = _.parentElement.offsetWidth,
+            void 0 === xE && (xE = 1200),
+            void 0 !== vE.useWidth && (xE = vE.useWidth),
+            void 0 !== vE.pie.useWidth && (xE = vE.pie.useWidth);
+          const x = m.select("#" + e);
+          Gx(x, kE, xE, vE.pie.useMaxWidth), _.setAttribute("viewBox", "0 0 " + xE + " " + kE);
+          var r = 18,
+            a = Math.min(xE, kE) / 2 - 40,
+            s = x.append("g").attr("transform", "translate(" + xE / 2 + ",225)"),
+            o = i.db.getSections(),
+            l = 0;
+          Object.keys(o).forEach(function(t) {
+            l += o[t];
+          });
+          const v = vE.themeVariables;
+          var c = [v.pie1, v.pie2, v.pie3, v.pie4, v.pie5, v.pie6, v.pie7, v.pie8, v.pie9, v.pie10, v.pie11, v.pie12],
+            h = tr().range(c),
+            u = Object.entries(o).map(function(t, e) {
+              return { order: e, name: t[0], value: t[1] };
+            }),
+            d = function() {
+              var t = eo, e = to, n = null, i = Ss(0), r = Ss($s), a = Ss(0);
+              function s(s) {
+                var o,
+                  l,
+                  c,
+                  h,
+                  u,
+                  d = (s = Gs(s)).length,
+                  p = 0,
+                  f = new Array(d),
+                  g = new Array(d),
+                  y = +i.apply(this, arguments),
+                  m = Math.min($s, Math.max(-$s, r.apply(this, arguments) - y)),
+                  b = Math.min(Math.abs(m) / d, a.apply(this, arguments)),
+                  _ = b * (m < 0 ? -1 : 1);
+                for (o = 0; o < d; ++o) (u = g[f[o] = o] = +t(s[o], o, s)) > 0 && (p += u);
+                for (
+                  null != e
+                    ? f.sort(function(t, n) {
+                      return e(g[t], g[n]);
+                    })
+                    : null != n && f.sort(function(t, e) {
+                      return n(s[t], s[e]);
+                    }),
+                    o = 0,
+                    c = p ? (m - d * _) / p : 0;
+                  o < d;
+                  ++o, y = h
+                ) {
+                  l = f[o],
+                    h = y + ((u = g[l]) > 0 ? u * c : 0) + _,
+                    g[l] = { data: s[l], index: o, value: u, startAngle: y, endAngle: h, padAngle: b };
+                }
+                return g;
+              }
+              return s.value = function(e) {
+                return arguments.length ? (t = "function" == typeof e ? e : Ss(+e), s) : t;
+              },
+                s.sortValues = function(t) {
+                  return arguments.length ? (e = t, n = null, s) : e;
+                },
+                s.sort = function(t) {
+                  return arguments.length ? (n = t, e = null, s) : n;
+                },
+                s.startAngle = function(t) {
+                  return arguments.length ? (i = "function" == typeof t ? t : Ss(+t), s) : i;
+                },
+                s.endAngle = function(t) {
+                  return arguments.length ? (r = "function" == typeof t ? t : Ss(+t), s) : r;
+                },
+                s.padAngle = function(t) {
+                  return arguments.length ? (a = "function" == typeof t ? t : Ss(+t), s) : a;
+                },
+                s;
+            }().value(function(t) {
+              return t.value;
+            }).sort(function(t, e) {
+              return t.order - e.order;
+            }),
+            p = d(u),
+            f = Vs().innerRadius(0).outerRadius(a);
+          s.selectAll("mySlices").data(p).enter().append("path").attr("d", f).attr("fill", function(t) {
+            return h(t.data.name);
+          }).attr("class", "pieCircle"),
+            s.selectAll("mySlices").data(p).enter().append("text").text(function(t) {
+              return (t.data.value / l * 100).toFixed(0) + "%";
+            }).attr("transform", function(t) {
+              return "translate(" + f.centroid(t) + ")";
+            }).style("text-anchor", "middle").attr("class", "slice"),
+            s.append("text").text(i.db.getDiagramTitle()).attr("x", 0).attr("y", -200).attr("class", "pieTitleText");
+          var g = s.selectAll(".legend").data(h.domain()).enter().append("g").attr("class", "legend").attr(
+            "transform",
+            function(t, e) {
+              return "translate(216," + (22 * e - 22 * h.domain().length / 2) + ")";
+            },
+          );
+          g.append("rect").attr("width", r).attr("height", r).style("fill", h).style("stroke", h),
+            g.data(p).append("text").attr("x", 22).attr("y", 14).text(function(t) {
+              return i.db.getShowData() || vE.showData || vE.pie.showData
+                ? t.data.name + " [" + t.data.value + "]"
+                : t.data.name;
+            });
+        } catch (t) {
+          tb.error("Error while rendering info diagram"), tb.error(t);
+        }
+      },
+    };
+  var TE = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [1, 3],
+      i = [1, 5],
+      r = [1, 6],
+      a = [1, 7],
+      s = [1, 8],
+      o = [5, 6, 8, 14, 16, 18, 19, 40, 41, 42, 43, 44, 45, 53, 71, 72],
+      l = [1, 22],
+      c = [2, 13],
+      h = [1, 26],
+      u = [1, 27],
+      d = [1, 28],
+      p = [1, 29],
+      f = [1, 30],
+      g = [1, 31],
+      y = [1, 24],
+      m = [1, 32],
+      b = [1, 33],
+      _ = [1, 36],
+      x = [71, 72],
+      v = [5, 8, 14, 16, 18, 19, 40, 41, 42, 43, 44, 45, 53, 60, 62, 71, 72],
+      k = [1, 56],
+      w = [1, 57],
+      T = [1, 58],
+      C = [1, 59],
+      E = [1, 60],
+      S = [1, 61],
+      A = [1, 62],
+      D = [62, 63],
+      L = [1, 74],
+      O = [1, 70],
+      N = [1, 71],
+      M = [1, 72],
+      B = [1, 73],
+      I = [1, 75],
+      F = [1, 79],
+      R = [1, 80],
+      $ = [1, 77],
+      P = [1, 78],
+      Y = [5, 8, 14, 16, 18, 19, 40, 41, 42, 43, 44, 45, 53, 71, 72],
+      j = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          directive: 4,
+          NEWLINE: 5,
+          RD: 6,
+          diagram: 7,
+          EOF: 8,
+          openDirective: 9,
+          typeDirective: 10,
+          closeDirective: 11,
+          ":": 12,
+          argDirective: 13,
+          acc_title: 14,
+          acc_title_value: 15,
+          acc_descr: 16,
+          acc_descr_value: 17,
+          acc_descr_multiline_value: 18,
+          open_directive: 19,
+          type_directive: 20,
+          arg_directive: 21,
+          close_directive: 22,
+          requirementDef: 23,
+          elementDef: 24,
+          relationshipDef: 25,
+          requirementType: 26,
+          requirementName: 27,
+          STRUCT_START: 28,
+          requirementBody: 29,
+          ID: 30,
+          COLONSEP: 31,
+          id: 32,
+          TEXT: 33,
+          text: 34,
+          RISK: 35,
+          riskLevel: 36,
+          VERIFYMTHD: 37,
+          verifyType: 38,
+          STRUCT_STOP: 39,
+          REQUIREMENT: 40,
+          FUNCTIONAL_REQUIREMENT: 41,
+          INTERFACE_REQUIREMENT: 42,
+          PERFORMANCE_REQUIREMENT: 43,
+          PHYSICAL_REQUIREMENT: 44,
+          DESIGN_CONSTRAINT: 45,
+          LOW_RISK: 46,
+          MED_RISK: 47,
+          HIGH_RISK: 48,
+          VERIFY_ANALYSIS: 49,
+          VERIFY_DEMONSTRATION: 50,
+          VERIFY_INSPECTION: 51,
+          VERIFY_TEST: 52,
+          ELEMENT: 53,
+          elementName: 54,
+          elementBody: 55,
+          TYPE: 56,
+          type: 57,
+          DOCREF: 58,
+          ref: 59,
+          END_ARROW_L: 60,
+          relationship: 61,
+          LINE: 62,
+          END_ARROW_R: 63,
+          CONTAINS: 64,
+          COPIES: 65,
+          DERIVES: 66,
+          SATISFIES: 67,
+          VERIFIES: 68,
+          REFINES: 69,
+          TRACES: 70,
+          unqString: 71,
+          qString: 72,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: {
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+          5: "NEWLINE",
+          6: "RD",
+          8: "EOF",
+          12: ":",
+          14: "acc_title",
+          15: "acc_title_value",
+          16: "acc_descr",
+          17: "acc_descr_value",
+          18: "acc_descr_multiline_value",
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+          21: "arg_directive",
+          22: "close_directive",
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+          30: "ID",
+          31: "COLONSEP",
+          33: "TEXT",
+          35: "RISK",
+          37: "VERIFYMTHD",
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+          40: "REQUIREMENT",
+          41: "FUNCTIONAL_REQUIREMENT",
+          42: "INTERFACE_REQUIREMENT",
+          43: "PERFORMANCE_REQUIREMENT",
+          44: "PHYSICAL_REQUIREMENT",
+          45: "DESIGN_CONSTRAINT",
+          46: "LOW_RISK",
+          47: "MED_RISK",
+          48: "HIGH_RISK",
+          49: "VERIFY_ANALYSIS",
+          50: "VERIFY_DEMONSTRATION",
+          51: "VERIFY_INSPECTION",
+          52: "VERIFY_TEST",
+          53: "ELEMENT",
+          56: "TYPE",
+          58: "DOCREF",
+          60: "END_ARROW_L",
+          62: "LINE",
+          63: "END_ARROW_R",
+          64: "CONTAINS",
+          65: "COPIES",
+          66: "DERIVES",
+          67: "SATISFIES",
+          68: "VERIFIES",
+          69: "REFINES",
+          70: "TRACES",
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+          72: "qString",
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+          [57, 1],
+          [59, 1],
+          [59, 1],
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+          var o = a.length - 1;
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+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 7:
+            case 8:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 9:
+              i.parseDirective("%%{", "open_directive");
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+            case 10:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 11:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 12:
+              i.parseDirective("}%%", "close_directive", "pie");
+              break;
+            case 13:
+              this.$ = [];
+              break;
+            case 19:
+              i.addRequirement(a[o - 3], a[o - 4]);
+              break;
+            case 20:
+              i.setNewReqId(a[o - 2]);
+              break;
+            case 21:
+              i.setNewReqText(a[o - 2]);
+              break;
+            case 22:
+              i.setNewReqRisk(a[o - 2]);
+              break;
+            case 23:
+              i.setNewReqVerifyMethod(a[o - 2]);
+              break;
+            case 26:
+              this.$ = i.RequirementType.REQUIREMENT;
+              break;
+            case 27:
+              this.$ = i.RequirementType.FUNCTIONAL_REQUIREMENT;
+              break;
+            case 28:
+              this.$ = i.RequirementType.INTERFACE_REQUIREMENT;
+              break;
+            case 29:
+              this.$ = i.RequirementType.PERFORMANCE_REQUIREMENT;
+              break;
+            case 30:
+              this.$ = i.RequirementType.PHYSICAL_REQUIREMENT;
+              break;
+            case 31:
+              this.$ = i.RequirementType.DESIGN_CONSTRAINT;
+              break;
+            case 32:
+              this.$ = i.RiskLevel.LOW_RISK;
+              break;
+            case 33:
+              this.$ = i.RiskLevel.MED_RISK;
+              break;
+            case 34:
+              this.$ = i.RiskLevel.HIGH_RISK;
+              break;
+            case 35:
+              this.$ = i.VerifyType.VERIFY_ANALYSIS;
+              break;
+            case 36:
+              this.$ = i.VerifyType.VERIFY_DEMONSTRATION;
+              break;
+            case 37:
+              this.$ = i.VerifyType.VERIFY_INSPECTION;
+              break;
+            case 38:
+              this.$ = i.VerifyType.VERIFY_TEST;
+              break;
+            case 39:
+              i.addElement(a[o - 3]);
+              break;
+            case 40:
+              i.setNewElementType(a[o - 2]);
+              break;
+            case 41:
+              i.setNewElementDocRef(a[o - 2]);
+              break;
+            case 44:
+              i.addRelationship(a[o - 2], a[o], a[o - 4]);
+              break;
+            case 45:
+              i.addRelationship(a[o - 2], a[o - 4], a[o]);
+              break;
+            case 46:
+              this.$ = i.Relationships.CONTAINS;
+              break;
+            case 47:
+              this.$ = i.Relationships.COPIES;
+              break;
+            case 48:
+              this.$ = i.Relationships.DERIVES;
+              break;
+            case 49:
+              this.$ = i.Relationships.SATISFIES;
+              break;
+            case 50:
+              this.$ = i.Relationships.VERIFIES;
+              break;
+            case 51:
+              this.$ = i.Relationships.REFINES;
+              break;
+            case 52:
+              this.$ = i.Relationships.TRACES;
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+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: { "case-insensitive": !0 },
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("open_directive"), 19;
+            case 1:
+              return this.begin("type_directive"), 20;
+            case 2:
+              return this.popState(), this.begin("arg_directive"), 12;
+            case 3:
+              return this.popState(), this.popState(), 22;
+            case 4:
+              return 21;
+            case 5:
+              return "title";
+            case 6:
+              return this.begin("acc_title"), 14;
+            case 7:
+              return this.popState(), "acc_title_value";
+            case 8:
+              return this.begin("acc_descr"), 16;
+            case 9:
+              return this.popState(), "acc_descr_value";
+            case 10:
+              this.begin("acc_descr_multiline");
+              break;
+            case 11:
+            case 53:
+              this.popState();
+              break;
+            case 12:
+              return "acc_descr_multiline_value";
+            case 13:
+              return 5;
+            case 14:
+            case 15:
+            case 16:
+              break;
+            case 17:
+              return 8;
+            case 18:
+              return 6;
+            case 19:
+              return 28;
+            case 20:
+              return 39;
+            case 21:
+              return 31;
+            case 22:
+              return 30;
+            case 23:
+              return 33;
+            case 24:
+              return 35;
+            case 25:
+              return 37;
+            case 26:
+              return 40;
+            case 27:
+              return 41;
+            case 28:
+              return 42;
+            case 29:
+              return 43;
+            case 30:
+              return 44;
+            case 31:
+              return 45;
+            case 32:
+              return 46;
+            case 33:
+              return 47;
+            case 34:
+              return 48;
+            case 35:
+              return 49;
+            case 36:
+              return 50;
+            case 37:
+              return 51;
+            case 38:
+              return 52;
+            case 39:
+              return 53;
+            case 40:
+              return 64;
+            case 41:
+              return 65;
+            case 42:
+              return 66;
+            case 43:
+              return 67;
+            case 44:
+              return 68;
+            case 45:
+              return 69;
+            case 46:
+              return 70;
+            case 47:
+              return 56;
+            case 48:
+              return 58;
+            case 49:
+              return 60;
+            case 50:
+              return 63;
+            case 51:
+              return 62;
+            case 52:
+              this.begin("string");
+              break;
+            case 54:
+              return "qString";
+            case 55:
+              return e.yytext = e.yytext.trim(), 71;
+          }
+        },
+        rules: [
+          /^(?:%%\{)/i,
+          /^(?:((?:(?!\}%%)[^:.])*))/i,
+          /^(?::)/i,
+          /^(?:\}%%)/i,
+          /^(?:((?:(?!\}%%).|\n)*))/i,
+          /^(?:title\s[^#\n;]+)/i,
+          /^(?:accTitle\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*\{\s*)/i,
+          /^(?:[\}])/i,
+          /^(?:[^\}]*)/i,
+          /^(?:(\r?\n)+)/i,
+          /^(?:\s+)/i,
+          /^(?:#[^\n]*)/i,
+          /^(?:%[^\n]*)/i,
+          /^(?:$)/i,
+          /^(?:requirementDiagram\b)/i,
+          /^(?:\{)/i,
+          /^(?:\})/i,
+          /^(?::)/i,
+          /^(?:id\b)/i,
+          /^(?:text\b)/i,
+          /^(?:risk\b)/i,
+          /^(?:verifyMethod\b)/i,
+          /^(?:requirement\b)/i,
+          /^(?:functionalRequirement\b)/i,
+          /^(?:interfaceRequirement\b)/i,
+          /^(?:performanceRequirement\b)/i,
+          /^(?:physicalRequirement\b)/i,
+          /^(?:designConstraint\b)/i,
+          /^(?:low\b)/i,
+          /^(?:medium\b)/i,
+          /^(?:high\b)/i,
+          /^(?:analysis\b)/i,
+          /^(?:demonstration\b)/i,
+          /^(?:inspection\b)/i,
+          /^(?:test\b)/i,
+          /^(?:element\b)/i,
+          /^(?:contains\b)/i,
+          /^(?:copies\b)/i,
+          /^(?:derives\b)/i,
+          /^(?:satisfies\b)/i,
+          /^(?:verifies\b)/i,
+          /^(?:refines\b)/i,
+          /^(?:traces\b)/i,
+          /^(?:type\b)/i,
+          /^(?:docref\b)/i,
+          /^(?:<-)/i,
+          /^(?:->)/i,
+          /^(?:-)/i,
+          /^(?:["])/i,
+          /^(?:["])/i,
+          /^(?:[^"]*)/i,
+          /^(?:[\w][^\r\n\{\<\>\-\=]*)/i,
+        ],
+        conditions: {
+          acc_descr_multiline: { rules: [11, 12], inclusive: !1 },
+          acc_descr: { rules: [9], inclusive: !1 },
+          acc_title: { rules: [7], inclusive: !1 },
+          close_directive: { rules: [], inclusive: !1 },
+          arg_directive: { rules: [3, 4], inclusive: !1 },
+          type_directive: { rules: [2, 3], inclusive: !1 },
+          open_directive: { rules: [1], inclusive: !1 },
+          unqString: { rules: [], inclusive: !1 },
+          token: { rules: [], inclusive: !1 },
+          string: { rules: [53, 54], inclusive: !1 },
+          INITIAL: {
+            rules: [
+              0,
+              5,
+              6,
+              8,
+              10,
+              13,
+              14,
+              15,
+              16,
+              17,
+              18,
+              19,
+              20,
+              21,
+              22,
+              23,
+              24,
+              25,
+              26,
+              27,
+              28,
+              29,
+              30,
+              31,
+              32,
+              33,
+              34,
+              35,
+              36,
+              37,
+              38,
+              39,
+              40,
+              41,
+              42,
+              43,
+              44,
+              45,
+              46,
+              47,
+              48,
+              49,
+              50,
+              51,
+              52,
+              55,
+            ],
+            inclusive: !0,
+          },
+        },
+      },
+        t);
+    function U() {
+      this.yy = {};
+    }
+    return j.lexer = z, U.prototype = j, j.Parser = U, new U();
+  }();
+  TE.parser = TE;
+  const CE = TE, EE = t => null !== t.match(/^\s*requirement(Diagram)?/);
+  let SE = [], AE = {}, DE = {}, LE = {}, OE = {};
+  const NE = {
+      RequirementType: {
+        REQUIREMENT: "Requirement",
+        FUNCTIONAL_REQUIREMENT: "Functional Requirement",
+        INTERFACE_REQUIREMENT: "Interface Requirement",
+        PERFORMANCE_REQUIREMENT: "Performance Requirement",
+        PHYSICAL_REQUIREMENT: "Physical Requirement",
+        DESIGN_CONSTRAINT: "Design Constraint",
+      },
+      RiskLevel: { LOW_RISK: "Low", MED_RISK: "Medium", HIGH_RISK: "High" },
+      VerifyType: {
+        VERIFY_ANALYSIS: "Analysis",
+        VERIFY_DEMONSTRATION: "Demonstration",
+        VERIFY_INSPECTION: "Inspection",
+        VERIFY_TEST: "Test",
+      },
+      Relationships: {
+        CONTAINS: "contains",
+        COPIES: "copies",
+        DERIVES: "derives",
+        SATISFIES: "satisfies",
+        VERIFIES: "verifies",
+        REFINES: "refines",
+        TRACES: "traces",
+      },
+      parseDirective: function(t, e, n) {
+        nL.parseDirective(this, t, e, n);
+      },
+      getConfig: () => jx().req,
+      addRequirement: (
+        t,
+        e,
+      ) => (void 0 === DE[t]
+        && (DE[t] = { name: t, type: e, id: AE.id, text: AE.text, risk: AE.risk, verifyMethod: AE.verifyMethod }),
+        AE = {},
+        DE[t]),
+      getRequirements: () => DE,
+      setNewReqId: t => {
+        void 0 !== AE && (AE.id = t);
+      },
+      setNewReqText: t => {
+        void 0 !== AE && (AE.text = t);
+      },
+      setNewReqRisk: t => {
+        void 0 !== AE && (AE.risk = t);
+      },
+      setNewReqVerifyMethod: t => {
+        void 0 !== AE && (AE.verifyMethod = t);
+      },
+      setAccTitle: Ev,
+      getAccTitle: Sv,
+      setAccDescription: Av,
+      getAccDescription: Dv,
+      addElement: t => (void 0 === OE[t]
+        && (OE[t] = { name: t, type: LE.type, docRef: LE.docRef }, tb.info("Added new requirement: ", t)),
+        LE = {},
+        OE[t]),
+      getElements: () => OE,
+      setNewElementType: t => {
+        void 0 !== LE && (LE.type = t);
+      },
+      setNewElementDocRef: t => {
+        void 0 !== LE && (LE.docRef = t);
+      },
+      addRelationship: (t, e, n) => {
+        SE.push({ type: t, src: e, dst: n });
+      },
+      getRelationships: () => SE,
+      clear: () => {
+        SE = [], AE = {}, DE = {}, LE = {}, OE = {}, Cv();
+      },
+    },
+    ME = { CONTAINS: "contains", ARROW: "arrow" },
+    BE = ME,
+    IE = (t, e) => {
+      let n = t.append("defs").append("marker").attr("id", ME.CONTAINS + "_line_ending").attr("refX", 0).attr(
+        "refY",
+        e.line_height / 2,
+      ).attr("markerWidth", e.line_height).attr("markerHeight", e.line_height).attr("orient", "auto").append("g");
+      n.append("circle").attr("cx", e.line_height / 2).attr("cy", e.line_height / 2).attr("r", e.line_height / 2).attr(
+        "fill",
+        "none",
+      ),
+        n.append("line").attr("x1", 0).attr("x2", e.line_height).attr("y1", e.line_height / 2).attr(
+          "y2",
+          e.line_height / 2,
+        ).attr("stroke-width", 1),
+        n.append("line").attr("y1", 0).attr("y2", e.line_height).attr("x1", e.line_height / 2).attr(
+          "x2",
+          e.line_height / 2,
+        ).attr("stroke-width", 1),
+        t.append("defs").append("marker").attr("id", ME.ARROW + "_line_ending").attr("refX", e.line_height).attr(
+          "refY",
+          .5 * e.line_height,
+        ).attr("markerWidth", e.line_height).attr("markerHeight", e.line_height).attr("orient", "auto").append("path")
+          .attr(
+            "d",
+            `M0,0\n      L${e.line_height},${e.line_height / 2}\n      M${e.line_height},${
+              e.line_height / 2
+            }\n      L0,${e.line_height}`,
+          ).attr("stroke-width", 1);
+    };
+  let FE = {}, RE = 0;
+  const $E = (t, e) =>
+      t.insert("rect", "#" + e).attr("class", "req reqBox").attr("x", 0).attr("y", 0).attr(
+        "width",
+        FE.rect_min_width + "px",
+      ).attr("height", FE.rect_min_height + "px"),
+    PE = (t, e, n) => {
+      let i = FE.rect_min_width / 2,
+        r = t.append("text").attr("class", "req reqLabel reqTitle").attr("id", e).attr("x", i).attr(
+          "y",
+          FE.rect_padding,
+        ).attr("dominant-baseline", "hanging"),
+        a = 0;
+      n.forEach(t => {
+        0 == a
+          ? r.append("tspan").attr("text-anchor", "middle").attr("x", FE.rect_min_width / 2).attr("dy", 0).text(t)
+          : r.append("tspan").attr("text-anchor", "middle").attr("x", FE.rect_min_width / 2).attr(
+            "dy",
+            .75 * FE.line_height,
+          ).text(t), a++;
+      });
+      let s = 1.5 * FE.rect_padding + a * FE.line_height * .75;
+      return t.append("line").attr("class", "req-title-line").attr("x1", "0").attr("x2", FE.rect_min_width).attr(
+        "y1",
+        s,
+      ).attr("y2", s),
+        { titleNode: r, y: s };
+    },
+    YE = (t, e, n, i) => {
+      let r = t.append("text").attr("class", "req reqLabel").attr("id", e).attr("x", FE.rect_padding).attr("y", i).attr(
+          "dominant-baseline",
+          "hanging",
+        ),
+        a = 0;
+      let s = [];
+      return n.forEach(t => {
+        let e = t.length;
+        for (; e > 30 && a < 3;) {
+          let n = t.substring(0, 30);
+          e = (t = t.substring(30, t.length)).length, s[s.length] = n, a++;
+        }
+        if (3 == a) {
+          let t = s[s.length - 1];
+          s[s.length - 1] = t.substring(0, t.length - 4) + "...";
+        } else s[s.length] = t;
+        a = 0;
+      }),
+        s.forEach(t => {
+          r.append("tspan").attr("x", FE.rect_padding).attr("dy", FE.line_height).text(t);
+        }),
+        r;
+    },
+    jE = function(t, e, n, i, r) {
+      const a = n.edge(zE(e.src), zE(e.dst)),
+        s = Js().x(function(t) {
+          return t.x;
+        }).y(function(t) {
+          return t.y;
+        }),
+        o = t.insert("path", "#" + i).attr("class", "er relationshipLine").attr("d", s(a.points)).attr("fill", "none");
+      e.type == r.db.Relationships.CONTAINS
+        ? o.attr("marker-start", "url(" + ub.getUrl(FE.arrowMarkerAbsolute) + "#" + e.type + "_line_ending)")
+        : (o.attr("stroke-dasharray", "10,7"),
+          o.attr("marker-end", "url(" + ub.getUrl(FE.arrowMarkerAbsolute) + "#" + BE.ARROW + "_line_ending)")),
+        ((t, e, n, i) => {
+          const r = e.node().getTotalLength(), a = e.node().getPointAtLength(.5 * r), s = "rel" + RE;
+          RE++;
+          const o = t.append("text").attr("class", "req relationshipLabel").attr("id", s).attr("x", a.x).attr("y", a.y)
+            .attr("text-anchor", "middle").attr("dominant-baseline", "middle").text(i).node().getBBox();
+          t.insert("rect", "#" + s).attr("class", "req reqLabelBox").attr("x", a.x - o.width / 2).attr(
+            "y",
+            a.y - o.height / 2,
+          ).attr("width", o.width).attr("height", o.height).attr("fill", "white").attr("fill-opacity", "85%");
+        })(t, o, 0, `<<${e.type}>>`);
+    },
+    zE = t => t.replace(/\s/g, "").replace(/\./g, "_"),
+    UE = {
+      draw: (t, e, n, i) => {
+        FE = jx().requirement, i.db.clear(), i.parser.parse(t);
+        const r = FE.securityLevel;
+        let a;
+        "sandbox" === r && (a = ie("#i" + e));
+        const s = ie("sandbox" === r ? a.nodes()[0].contentDocument.body : "body").select(`[id='${e}']`);
+        IE(s, FE);
+        const o = new yy({ multigraph: !1, compound: !1, directed: !0 }).setGraph({
+          rankdir: FE.layoutDirection,
+          marginx: 20,
+          marginy: 20,
+          nodesep: 100,
+          edgesep: 100,
+          ranksep: 100,
+        }).setDefaultEdgeLabel(function() {
+          return {};
+        });
+        let l = i.db.getRequirements(), c = i.db.getElements(), h = i.db.getRelationships();
+        ((t, e, n) => {
+          Object.keys(t).forEach(i => {
+            let r = t[i];
+            i = zE(i), tb.info("Added new requirement: ", i);
+            const a = n.append("g").attr("id", i), s = $E(a, "req-" + i);
+            let o = PE(a, i + "_title", [`<<${r.type}>>`, `${r.name}`]);
+            YE(
+              a,
+              i + "_body",
+              [`Id: ${r.id}`, `Text: ${r.text}`, `Risk: ${r.risk}`, `Verification: ${r.verifyMethod}`],
+              o.y,
+            );
+            const l = s.node().getBBox();
+            e.setNode(i, { width: l.width, height: l.height, shape: "rect", id: i });
+          });
+        })(l, o, s),
+          ((t, e, n) => {
+            Object.keys(t).forEach(i => {
+              let r = t[i];
+              const a = zE(i), s = n.append("g").attr("id", a), o = "element-" + a, l = $E(s, o);
+              let c = PE(s, o + "_title", ["<<Element>>", `${i}`]);
+              YE(s, o + "_body", [`Type: ${r.type || "Not Specified"}`, `Doc Ref: ${r.docRef || "None"}`], c.y);
+              const h = l.node().getBBox();
+              e.setNode(a, { width: h.width, height: h.height, shape: "rect", id: a });
+            });
+          })(c, o, s),
+          ((t, e) => {
+            t.forEach(function(t) {
+              let n = zE(t.src), i = zE(t.dst);
+              e.setEdge(n, i, { relationship: t });
+            });
+          })(h, o),
+          hm(o),
+          function(t, e) {
+            e.nodes().forEach(function(n) {
+              void 0 !== n && void 0 !== e.node(n)
+                && (t.select("#" + n),
+                  t.select("#" + n).attr(
+                    "transform",
+                    "translate(" + (e.node(n).x - e.node(n).width / 2) + "," + (e.node(n).y - e.node(n).height / 2)
+                      + " )",
+                  ));
+            });
+          }(s, o),
+          h.forEach(function(t) {
+            jE(s, t, o, e, i);
+          });
+        const u = FE.rect_padding, d = s.node().getBBox(), p = d.width + 2 * u, f = d.height + 2 * u;
+        Gx(s, f, p, FE.useMaxWidth), s.attr("viewBox", `${d.x - u} ${d.y - u} ${p} ${f}`);
+      },
+    };
+  var WE = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [1, 2],
+      i = [1, 3],
+      r = [1, 5],
+      a = [1, 7],
+      s = [2, 5],
+      o = [1, 15],
+      l = [1, 17],
+      c = [1, 18],
+      h = [1, 19],
+      u = [1, 21],
+      d = [1, 22],
+      p = [1, 23],
+      f = [1, 29],
+      g = [1, 30],
+      y = [1, 31],
+      m = [1, 32],
+      b = [1, 33],
+      _ = [1, 34],
+      x = [1, 35],
+      v = [1, 36],
+      k = [1, 37],
+      w = [1, 38],
+      T = [1, 39],
+      C = [1, 40],
+      E = [1, 43],
+      S = [1, 44],
+      A = [1, 45],
+      D = [1, 46],
+      L = [1, 47],
+      O = [1, 48],
+      N = [1, 51],
+      M = [
+        1,
+        4,
+        5,
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+        51,
+        52,
+        53,
+        58,
+        59,
+        60,
+        61,
+        69,
+        79,
+      ],
+      B = [4, 5, 16, 20, 22, 25, 26, 32, 33, 34, 36, 38, 39, 40, 41, 42, 43, 45, 47, 49, 53, 58, 59, 60, 61, 69, 79],
+      I = [
+        4,
+        5,
+        16,
+        20,
+        22,
+        25,
+        26,
+        32,
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+        34,
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+        49,
+        52,
+        53,
+        58,
+        59,
+        60,
+        61,
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+        79,
+      ],
+      F = [
+        4,
+        5,
+        16,
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+        25,
+        26,
+        32,
+        33,
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+        58,
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+        79,
+      ],
+      R = [
+        4,
+        5,
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+        25,
+        26,
+        32,
+        33,
+        34,
+        36,
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+        49,
+        50,
+        53,
+        58,
+        59,
+        60,
+        61,
+        69,
+        79,
+      ],
+      $ = [67, 68, 69],
+      P = [1, 121],
+      Y = [
+        1,
+        4,
+        5,
+        7,
+        16,
+        20,
+        22,
+        25,
+        26,
+        32,
+        33,
+        34,
+        36,
+        38,
+        39,
+        40,
+        41,
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+        43,
+        45,
+        47,
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+        50,
+        51,
+        52,
+        53,
+        58,
+        59,
+        60,
+        61,
+        69,
+        79,
+      ],
+      j = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          SPACE: 4,
+          NEWLINE: 5,
+          directive: 6,
+          SD: 7,
+          document: 8,
+          line: 9,
+          statement: 10,
+          openDirective: 11,
+          typeDirective: 12,
+          closeDirective: 13,
+          ":": 14,
+          argDirective: 15,
+          participant: 16,
+          actor: 17,
+          AS: 18,
+          restOfLine: 19,
+          participant_actor: 20,
+          signal: 21,
+          autonumber: 22,
+          NUM: 23,
+          off: 24,
+          activate: 25,
+          deactivate: 26,
+          note_statement: 27,
+          links_statement: 28,
+          link_statement: 29,
+          properties_statement: 30,
+          details_statement: 31,
+          title: 32,
+          legacy_title: 33,
+          acc_title: 34,
+          acc_title_value: 35,
+          acc_descr: 36,
+          acc_descr_value: 37,
+          acc_descr_multiline_value: 38,
+          loop: 39,
+          end: 40,
+          rect: 41,
+          opt: 42,
+          alt: 43,
+          else_sections: 44,
+          par: 45,
+          par_sections: 46,
+          critical: 47,
+          option_sections: 48,
+          break: 49,
+          option: 50,
+          and: 51,
+          else: 52,
+          note: 53,
+          placement: 54,
+          text2: 55,
+          over: 56,
+          actor_pair: 57,
+          links: 58,
+          link: 59,
+          properties: 60,
+          details: 61,
+          spaceList: 62,
+          ",": 63,
+          left_of: 64,
+          right_of: 65,
+          signaltype: 66,
+          "+": 67,
+          "-": 68,
+          ACTOR: 69,
+          SOLID_OPEN_ARROW: 70,
+          DOTTED_OPEN_ARROW: 71,
+          SOLID_ARROW: 72,
+          DOTTED_ARROW: 73,
+          SOLID_CROSS: 74,
+          DOTTED_CROSS: 75,
+          SOLID_POINT: 76,
+          DOTTED_POINT: 77,
+          TXT: 78,
+          open_directive: 79,
+          type_directive: 80,
+          arg_directive: 81,
+          close_directive: 82,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: {
+          2: "error",
+          4: "SPACE",
+          5: "NEWLINE",
+          7: "SD",
+          14: ":",
+          16: "participant",
+          18: "AS",
+          19: "restOfLine",
+          20: "participant_actor",
+          22: "autonumber",
+          23: "NUM",
+          24: "off",
+          25: "activate",
+          26: "deactivate",
+          32: "title",
+          33: "legacy_title",
+          34: "acc_title",
+          35: "acc_title_value",
+          36: "acc_descr",
+          37: "acc_descr_value",
+          38: "acc_descr_multiline_value",
+          39: "loop",
+          40: "end",
+          41: "rect",
+          42: "opt",
+          43: "alt",
+          45: "par",
+          47: "critical",
+          49: "break",
+          50: "option",
+          51: "and",
+          52: "else",
+          53: "note",
+          56: "over",
+          58: "links",
+          59: "link",
+          60: "properties",
+          61: "details",
+          63: ",",
+          64: "left_of",
+          65: "right_of",
+          67: "+",
+          68: "-",
+          69: "ACTOR",
+          70: "SOLID_OPEN_ARROW",
+          71: "DOTTED_OPEN_ARROW",
+          72: "SOLID_ARROW",
+          73: "DOTTED_ARROW",
+          74: "SOLID_CROSS",
+          75: "DOTTED_CROSS",
+          76: "SOLID_POINT",
+          77: "DOTTED_POINT",
+          78: "TXT",
+          79: "open_directive",
+          80: "type_directive",
+          81: "arg_directive",
+          82: "close_directive",
+        },
+        productions_: [
+          0,
+          [3, 2],
+          [3, 2],
+          [3, 2],
+          [3, 2],
+          [8, 0],
+          [8, 2],
+          [9, 2],
+          [9, 1],
+          [9, 1],
+          [6, 4],
+          [6, 6],
+          [10, 5],
+          [10, 3],
+          [10, 5],
+          [10, 3],
+          [10, 2],
+          [10, 4],
+          [10, 3],
+          [10, 3],
+          [10, 2],
+          [10, 3],
+          [10, 3],
+          [10, 2],
+          [10, 2],
+          [10, 2],
+          [10, 2],
+          [10, 2],
+          [10, 1],
+          [10, 1],
+          [10, 2],
+          [10, 2],
+          [10, 1],
+          [10, 4],
+          [10, 4],
+          [10, 4],
+          [10, 4],
+          [10, 4],
+          [10, 4],
+          [10, 4],
+          [10, 1],
+          [48, 1],
+          [48, 4],
+          [46, 1],
+          [46, 4],
+          [44, 1],
+          [44, 4],
+          [27, 4],
+          [27, 4],
+          [28, 3],
+          [29, 3],
+          [30, 3],
+          [31, 3],
+          [62, 2],
+          [62, 1],
+          [57, 3],
+          [57, 1],
+          [54, 1],
+          [54, 1],
+          [21, 5],
+          [21, 5],
+          [21, 4],
+          [17, 1],
+          [66, 1],
+          [66, 1],
+          [66, 1],
+          [66, 1],
+          [66, 1],
+          [66, 1],
+          [66, 1],
+          [66, 1],
+          [55, 1],
+          [11, 1],
+          [12, 1],
+          [15, 1],
+          [13, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 4:
+              return i.apply(a[o]), a[o];
+            case 5:
+            case 9:
+              this.$ = [];
+              break;
+            case 6:
+              a[o - 1].push(a[o]), this.$ = a[o - 1];
+              break;
+            case 7:
+            case 8:
+            case 56:
+              this.$ = a[o];
+              break;
+            case 12:
+              a[o - 3].type = "addParticipant", a[o - 3].description = i.parseMessage(a[o - 1]), this.$ = a[o - 3];
+              break;
+            case 13:
+              a[o - 1].type = "addParticipant", this.$ = a[o - 1];
+              break;
+            case 14:
+              a[o - 3].type = "addActor", a[o - 3].description = i.parseMessage(a[o - 1]), this.$ = a[o - 3];
+              break;
+            case 15:
+              a[o - 1].type = "addActor", this.$ = a[o - 1];
+              break;
+            case 17:
+              this.$ = {
+                type: "sequenceIndex",
+                sequenceIndex: Number(a[o - 2]),
+                sequenceIndexStep: Number(a[o - 1]),
+                sequenceVisible: !0,
+                signalType: i.LINETYPE.AUTONUMBER,
+              };
+              break;
+            case 18:
+              this.$ = {
+                type: "sequenceIndex",
+                sequenceIndex: Number(a[o - 1]),
+                sequenceIndexStep: 1,
+                sequenceVisible: !0,
+                signalType: i.LINETYPE.AUTONUMBER,
+              };
+              break;
+            case 19:
+              this.$ = { type: "sequenceIndex", sequenceVisible: !1, signalType: i.LINETYPE.AUTONUMBER };
+              break;
+            case 20:
+              this.$ = { type: "sequenceIndex", sequenceVisible: !0, signalType: i.LINETYPE.AUTONUMBER };
+              break;
+            case 21:
+              this.$ = { type: "activeStart", signalType: i.LINETYPE.ACTIVE_START, actor: a[o - 1] };
+              break;
+            case 22:
+              this.$ = { type: "activeEnd", signalType: i.LINETYPE.ACTIVE_END, actor: a[o - 1] };
+              break;
+            case 28:
+              i.setDiagramTitle(a[o].substring(6)), this.$ = a[o].substring(6);
+              break;
+            case 29:
+              i.setDiagramTitle(a[o].substring(7)), this.$ = a[o].substring(7);
+              break;
+            case 30:
+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 31:
+            case 32:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 33:
+              a[o - 1].unshift({
+                type: "loopStart",
+                loopText: i.parseMessage(a[o - 2]),
+                signalType: i.LINETYPE.LOOP_START,
+              }),
+                a[o - 1].push({ type: "loopEnd", loopText: a[o - 2], signalType: i.LINETYPE.LOOP_END }),
+                this.$ = a[o - 1];
+              break;
+            case 34:
+              a[o - 1].unshift({
+                type: "rectStart",
+                color: i.parseMessage(a[o - 2]),
+                signalType: i.LINETYPE.RECT_START,
+              }),
+                a[o - 1].push({ type: "rectEnd", color: i.parseMessage(a[o - 2]), signalType: i.LINETYPE.RECT_END }),
+                this.$ = a[o - 1];
+              break;
+            case 35:
+              a[o - 1].unshift({
+                type: "optStart",
+                optText: i.parseMessage(a[o - 2]),
+                signalType: i.LINETYPE.OPT_START,
+              }),
+                a[o - 1].push({ type: "optEnd", optText: i.parseMessage(a[o - 2]), signalType: i.LINETYPE.OPT_END }),
+                this.$ = a[o - 1];
+              break;
+            case 36:
+              a[o - 1].unshift({
+                type: "altStart",
+                altText: i.parseMessage(a[o - 2]),
+                signalType: i.LINETYPE.ALT_START,
+              }),
+                a[o - 1].push({ type: "altEnd", signalType: i.LINETYPE.ALT_END }),
+                this.$ = a[o - 1];
+              break;
+            case 37:
+              a[o - 1].unshift({
+                type: "parStart",
+                parText: i.parseMessage(a[o - 2]),
+                signalType: i.LINETYPE.PAR_START,
+              }),
+                a[o - 1].push({ type: "parEnd", signalType: i.LINETYPE.PAR_END }),
+                this.$ = a[o - 1];
+              break;
+            case 38:
+              a[o - 1].unshift({
+                type: "criticalStart",
+                criticalText: i.parseMessage(a[o - 2]),
+                signalType: i.LINETYPE.CRITICAL_START,
+              }),
+                a[o - 1].push({ type: "criticalEnd", signalType: i.LINETYPE.CRITICAL_END }),
+                this.$ = a[o - 1];
+              break;
+            case 39:
+              a[o - 1].unshift({
+                type: "breakStart",
+                breakText: i.parseMessage(a[o - 2]),
+                signalType: i.LINETYPE.BREAK_START,
+              }),
+                a[o - 1].push({
+                  type: "breakEnd",
+                  optText: i.parseMessage(a[o - 2]),
+                  signalType: i.LINETYPE.BREAK_END,
+                }),
+                this.$ = a[o - 1];
+              break;
+            case 42:
+              this.$ = a[o - 3].concat([{
+                type: "option",
+                optionText: i.parseMessage(a[o - 1]),
+                signalType: i.LINETYPE.CRITICAL_OPTION,
+              }, a[o]]);
+              break;
+            case 44:
+              this.$ = a[o - 3].concat([{
+                type: "and",
+                parText: i.parseMessage(a[o - 1]),
+                signalType: i.LINETYPE.PAR_AND,
+              }, a[o]]);
+              break;
+            case 46:
+              this.$ = a[o - 3].concat([{
+                type: "else",
+                altText: i.parseMessage(a[o - 1]),
+                signalType: i.LINETYPE.ALT_ELSE,
+              }, a[o]]);
+              break;
+            case 47:
+              this.$ = [a[o - 1], { type: "addNote", placement: a[o - 2], actor: a[o - 1].actor, text: a[o] }];
+              break;
+            case 48:
+              a[o - 2] = [].concat(a[o - 1], a[o - 1]).slice(0, 2),
+                a[o - 2][0] = a[o - 2][0].actor,
+                a[o - 2][1] = a[o - 2][1].actor,
+                this.$ = [a[o - 1], {
+                  type: "addNote",
+                  placement: i.PLACEMENT.OVER,
+                  actor: a[o - 2].slice(0, 2),
+                  text: a[o],
+                }];
+              break;
+            case 49:
+              this.$ = [a[o - 1], { type: "addLinks", actor: a[o - 1].actor, text: a[o] }];
+              break;
+            case 50:
+              this.$ = [a[o - 1], { type: "addALink", actor: a[o - 1].actor, text: a[o] }];
+              break;
+            case 51:
+              this.$ = [a[o - 1], { type: "addProperties", actor: a[o - 1].actor, text: a[o] }];
+              break;
+            case 52:
+              this.$ = [a[o - 1], { type: "addDetails", actor: a[o - 1].actor, text: a[o] }];
+              break;
+            case 55:
+              this.$ = [a[o - 2], a[o]];
+              break;
+            case 57:
+              this.$ = i.PLACEMENT.LEFTOF;
+              break;
+            case 58:
+              this.$ = i.PLACEMENT.RIGHTOF;
+              break;
+            case 59:
+              this.$ = [a[o - 4], a[o - 1], {
+                type: "addMessage",
+                from: a[o - 4].actor,
+                to: a[o - 1].actor,
+                signalType: a[o - 3],
+                msg: a[o],
+              }, { type: "activeStart", signalType: i.LINETYPE.ACTIVE_START, actor: a[o - 1] }];
+              break;
+            case 60:
+              this.$ = [a[o - 4], a[o - 1], {
+                type: "addMessage",
+                from: a[o - 4].actor,
+                to: a[o - 1].actor,
+                signalType: a[o - 3],
+                msg: a[o],
+              }, { type: "activeEnd", signalType: i.LINETYPE.ACTIVE_END, actor: a[o - 4] }];
+              break;
+            case 61:
+              this.$ = [a[o - 3], a[o - 1], {
+                type: "addMessage",
+                from: a[o - 3].actor,
+                to: a[o - 1].actor,
+                signalType: a[o - 2],
+                msg: a[o],
+              }];
+              break;
+            case 62:
+              this.$ = { type: "addParticipant", actor: a[o] };
+              break;
+            case 63:
+              this.$ = i.LINETYPE.SOLID_OPEN;
+              break;
+            case 64:
+              this.$ = i.LINETYPE.DOTTED_OPEN;
+              break;
+            case 65:
+              this.$ = i.LINETYPE.SOLID;
+              break;
+            case 66:
+              this.$ = i.LINETYPE.DOTTED;
+              break;
+            case 67:
+              this.$ = i.LINETYPE.SOLID_CROSS;
+              break;
+            case 68:
+              this.$ = i.LINETYPE.DOTTED_CROSS;
+              break;
+            case 69:
+              this.$ = i.LINETYPE.SOLID_POINT;
+              break;
+            case 70:
+              this.$ = i.LINETYPE.DOTTED_POINT;
+              break;
+            case 71:
+              this.$ = i.parseMessage(a[o].trim().substring(1));
+              break;
+            case 72:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 73:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 74:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 75:
+              i.parseDirective("}%%", "close_directive", "sequence");
+          }
+        },
+        table: [
+          { 3: 1, 4: n, 5: i, 6: 4, 7: r, 11: 6, 79: a },
+          { 1: [3] },
+          { 3: 8, 4: n, 5: i, 6: 4, 7: r, 11: 6, 79: a },
+          { 3: 9, 4: n, 5: i, 6: 4, 7: r, 11: 6, 79: a },
+          { 3: 10, 4: n, 5: i, 6: 4, 7: r, 11: 6, 79: a },
+          e(
+            [1, 4, 5, 16, 20, 22, 25, 26, 32, 33, 34, 36, 38, 39, 41, 42, 43, 45, 47, 49, 53, 58, 59, 60, 61, 69, 79],
+            s,
+            { 8: 11 },
+          ),
+          { 12: 12, 80: [1, 13] },
+          { 80: [2, 72] },
+          { 1: [2, 1] },
+          { 1: [2, 2] },
+          { 1: [2, 3] },
+          {
+            1: [2, 4],
+            4: o,
+            5: l,
+            6: 41,
+            9: 14,
+            10: 16,
+            11: 6,
+            16: c,
+            17: 42,
+            20: h,
+            21: 20,
+            22: u,
+            25: d,
+            26: p,
+            27: 24,
+            28: 25,
+            29: 26,
+            30: 27,
+            31: 28,
+            32: f,
+            33: g,
+            34: y,
+            36: m,
+            38: b,
+            39: _,
+            41: x,
+            42: v,
+            43: k,
+            45: w,
+            47: T,
+            49: C,
+            53: E,
+            58: S,
+            59: A,
+            60: D,
+            61: L,
+            69: O,
+            79: a,
+          },
+          { 13: 49, 14: [1, 50], 82: N },
+          e([14, 82], [2, 73]),
+          e(M, [2, 6]),
+          {
+            6: 41,
+            10: 52,
+            11: 6,
+            16: c,
+            17: 42,
+            20: h,
+            21: 20,
+            22: u,
+            25: d,
+            26: p,
+            27: 24,
+            28: 25,
+            29: 26,
+            30: 27,
+            31: 28,
+            32: f,
+            33: g,
+            34: y,
+            36: m,
+            38: b,
+            39: _,
+            41: x,
+            42: v,
+            43: k,
+            45: w,
+            47: T,
+            49: C,
+            53: E,
+            58: S,
+            59: A,
+            60: D,
+            61: L,
+            69: O,
+            79: a,
+          },
+          e(M, [2, 8]),
+          e(M, [2, 9]),
+          { 17: 53, 69: O },
+          { 17: 54, 69: O },
+          { 5: [1, 55] },
+          { 5: [1, 58], 23: [1, 56], 24: [1, 57] },
+          { 17: 59, 69: O },
+          { 17: 60, 69: O },
+          { 5: [1, 61] },
+          { 5: [1, 62] },
+          { 5: [1, 63] },
+          { 5: [1, 64] },
+          { 5: [1, 65] },
+          e(M, [2, 28]),
+          e(M, [2, 29]),
+          { 35: [1, 66] },
+          { 37: [1, 67] },
+          e(M, [2, 32]),
+          { 19: [1, 68] },
+          { 19: [1, 69] },
+          { 19: [1, 70] },
+          { 19: [1, 71] },
+          { 19: [1, 72] },
+          { 19: [1, 73] },
+          { 19: [1, 74] },
+          e(M, [2, 40]),
+          {
+            66: 75,
+            70: [1, 76],
+            71: [1, 77],
+            72: [1, 78],
+            73: [1, 79],
+            74: [1, 80],
+            75: [1, 81],
+            76: [1, 82],
+            77: [1, 83],
+          },
+          { 54: 84, 56: [1, 85], 64: [1, 86], 65: [1, 87] },
+          { 17: 88, 69: O },
+          { 17: 89, 69: O },
+          { 17: 90, 69: O },
+          { 17: 91, 69: O },
+          e([5, 18, 63, 70, 71, 72, 73, 74, 75, 76, 77, 78], [2, 62]),
+          { 5: [1, 92] },
+          { 15: 93, 81: [1, 94] },
+          { 5: [2, 75] },
+          e(M, [2, 7]),
+          { 5: [1, 96], 18: [1, 95] },
+          { 5: [1, 98], 18: [1, 97] },
+          e(M, [2, 16]),
+          { 5: [1, 100], 23: [1, 99] },
+          { 5: [1, 101] },
+          e(M, [2, 20]),
+          { 5: [1, 102] },
+          { 5: [1, 103] },
+          e(M, [2, 23]),
+          e(M, [2, 24]),
+          e(M, [2, 25]),
+          e(M, [2, 26]),
+          e(M, [2, 27]),
+          e(M, [2, 30]),
+          e(M, [2, 31]),
+          e(B, s, { 8: 104 }),
+          e(B, s, { 8: 105 }),
+          e(B, s, { 8: 106 }),
+          e(I, s, { 44: 107, 8: 108 }),
+          e(F, s, { 46: 109, 8: 110 }),
+          e(R, s, { 48: 111, 8: 112 }),
+          e(B, s, { 8: 113 }),
+          { 17: 116, 67: [1, 114], 68: [1, 115], 69: O },
+          e($, [2, 63]),
+          e($, [2, 64]),
+          e($, [2, 65]),
+          e($, [2, 66]),
+          e($, [2, 67]),
+          e($, [2, 68]),
+          e($, [2, 69]),
+          e($, [2, 70]),
+          { 17: 117, 69: O },
+          { 17: 119, 57: 118, 69: O },
+          { 69: [2, 57] },
+          { 69: [2, 58] },
+          { 55: 120, 78: P },
+          { 55: 122, 78: P },
+          { 55: 123, 78: P },
+          { 55: 124, 78: P },
+          e(Y, [2, 10]),
+          { 13: 125, 82: N },
+          { 82: [2, 74] },
+          { 19: [1, 126] },
+          e(M, [2, 13]),
+          { 19: [1, 127] },
+          e(M, [2, 15]),
+          { 5: [1, 128] },
+          e(M, [2, 18]),
+          e(M, [2, 19]),
+          e(M, [2, 21]),
+          e(M, [2, 22]),
+          {
+            4: o,
+            5: l,
+            6: 41,
+            9: 14,
+            10: 16,
+            11: 6,
+            16: c,
+            17: 42,
+            20: h,
+            21: 20,
+            22: u,
+            25: d,
+            26: p,
+            27: 24,
+            28: 25,
+            29: 26,
+            30: 27,
+            31: 28,
+            32: f,
+            33: g,
+            34: y,
+            36: m,
+            38: b,
+            39: _,
+            40: [1, 129],
+            41: x,
+            42: v,
+            43: k,
+            45: w,
+            47: T,
+            49: C,
+            53: E,
+            58: S,
+            59: A,
+            60: D,
+            61: L,
+            69: O,
+            79: a,
+          },
+          {
+            4: o,
+            5: l,
+            6: 41,
+            9: 14,
+            10: 16,
+            11: 6,
+            16: c,
+            17: 42,
+            20: h,
+            21: 20,
+            22: u,
+            25: d,
+            26: p,
+            27: 24,
+            28: 25,
+            29: 26,
+            30: 27,
+            31: 28,
+            32: f,
+            33: g,
+            34: y,
+            36: m,
+            38: b,
+            39: _,
+            40: [1, 130],
+            41: x,
+            42: v,
+            43: k,
+            45: w,
+            47: T,
+            49: C,
+            53: E,
+            58: S,
+            59: A,
+            60: D,
+            61: L,
+            69: O,
+            79: a,
+          },
+          {
+            4: o,
+            5: l,
+            6: 41,
+            9: 14,
+            10: 16,
+            11: 6,
+            16: c,
+            17: 42,
+            20: h,
+            21: 20,
+            22: u,
+            25: d,
+            26: p,
+            27: 24,
+            28: 25,
+            29: 26,
+            30: 27,
+            31: 28,
+            32: f,
+            33: g,
+            34: y,
+            36: m,
+            38: b,
+            39: _,
+            40: [1, 131],
+            41: x,
+            42: v,
+            43: k,
+            45: w,
+            47: T,
+            49: C,
+            53: E,
+            58: S,
+            59: A,
+            60: D,
+            61: L,
+            69: O,
+            79: a,
+          },
+          { 40: [1, 132] },
+          {
+            4: o,
+            5: l,
+            6: 41,
+            9: 14,
+            10: 16,
+            11: 6,
+            16: c,
+            17: 42,
+            20: h,
+            21: 20,
+            22: u,
+            25: d,
+            26: p,
+            27: 24,
+            28: 25,
+            29: 26,
+            30: 27,
+            31: 28,
+            32: f,
+            33: g,
+            34: y,
+            36: m,
+            38: b,
+            39: _,
+            40: [2, 45],
+            41: x,
+            42: v,
+            43: k,
+            45: w,
+            47: T,
+            49: C,
+            52: [1, 133],
+            53: E,
+            58: S,
+            59: A,
+            60: D,
+            61: L,
+            69: O,
+            79: a,
+          },
+          { 40: [1, 134] },
+          {
+            4: o,
+            5: l,
+            6: 41,
+            9: 14,
+            10: 16,
+            11: 6,
+            16: c,
+            17: 42,
+            20: h,
+            21: 20,
+            22: u,
+            25: d,
+            26: p,
+            27: 24,
+            28: 25,
+            29: 26,
+            30: 27,
+            31: 28,
+            32: f,
+            33: g,
+            34: y,
+            36: m,
+            38: b,
+            39: _,
+            40: [2, 43],
+            41: x,
+            42: v,
+            43: k,
+            45: w,
+            47: T,
+            49: C,
+            51: [1, 135],
+            53: E,
+            58: S,
+            59: A,
+            60: D,
+            61: L,
+            69: O,
+            79: a,
+          },
+          { 40: [1, 136] },
+          {
+            4: o,
+            5: l,
+            6: 41,
+            9: 14,
+            10: 16,
+            11: 6,
+            16: c,
+            17: 42,
+            20: h,
+            21: 20,
+            22: u,
+            25: d,
+            26: p,
+            27: 24,
+            28: 25,
+            29: 26,
+            30: 27,
+            31: 28,
+            32: f,
+            33: g,
+            34: y,
+            36: m,
+            38: b,
+            39: _,
+            40: [2, 41],
+            41: x,
+            42: v,
+            43: k,
+            45: w,
+            47: T,
+            49: C,
+            50: [1, 137],
+            53: E,
+            58: S,
+            59: A,
+            60: D,
+            61: L,
+            69: O,
+            79: a,
+          },
+          {
+            4: o,
+            5: l,
+            6: 41,
+            9: 14,
+            10: 16,
+            11: 6,
+            16: c,
+            17: 42,
+            20: h,
+            21: 20,
+            22: u,
+            25: d,
+            26: p,
+            27: 24,
+            28: 25,
+            29: 26,
+            30: 27,
+            31: 28,
+            32: f,
+            33: g,
+            34: y,
+            36: m,
+            38: b,
+            39: _,
+            40: [1, 138],
+            41: x,
+            42: v,
+            43: k,
+            45: w,
+            47: T,
+            49: C,
+            53: E,
+            58: S,
+            59: A,
+            60: D,
+            61: L,
+            69: O,
+            79: a,
+          },
+          { 17: 139, 69: O },
+          { 17: 140, 69: O },
+          { 55: 141, 78: P },
+          { 55: 142, 78: P },
+          { 55: 143, 78: P },
+          { 63: [1, 144], 78: [2, 56] },
+          { 5: [2, 49] },
+          { 5: [2, 71] },
+          { 5: [2, 50] },
+          { 5: [2, 51] },
+          { 5: [2, 52] },
+          { 5: [1, 145] },
+          { 5: [1, 146] },
+          { 5: [1, 147] },
+          e(M, [2, 17]),
+          e(M, [2, 33]),
+          e(M, [2, 34]),
+          e(M, [2, 35]),
+          e(M, [2, 36]),
+          { 19: [1, 148] },
+          e(M, [2, 37]),
+          { 19: [1, 149] },
+          e(M, [2, 38]),
+          { 19: [1, 150] },
+          e(M, [2, 39]),
+          { 55: 151, 78: P },
+          { 55: 152, 78: P },
+          { 5: [2, 61] },
+          { 5: [2, 47] },
+          { 5: [2, 48] },
+          { 17: 153, 69: O },
+          e(Y, [2, 11]),
+          e(M, [2, 12]),
+          e(M, [2, 14]),
+          e(I, s, { 8: 108, 44: 154 }),
+          e(F, s, { 8: 110, 46: 155 }),
+          e(R, s, { 8: 112, 48: 156 }),
+          { 5: [2, 59] },
+          { 5: [2, 60] },
+          { 78: [2, 55] },
+          { 40: [2, 46] },
+          { 40: [2, 44] },
+          { 40: [2, 42] },
+        ],
+        defaultActions: {
+          7: [2, 72],
+          8: [2, 1],
+          9: [2, 2],
+          10: [2, 3],
+          51: [2, 75],
+          86: [2, 57],
+          87: [2, 58],
+          94: [2, 74],
+          120: [2, 49],
+          121: [2, 71],
+          122: [2, 50],
+          123: [2, 51],
+          124: [2, 52],
+          141: [2, 61],
+          142: [2, 47],
+          143: [2, 48],
+          151: [2, 59],
+          152: [2, 60],
+          153: [2, 55],
+          154: [2, 46],
+          155: [2, 44],
+          156: [2, 42],
+        },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      z = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: { "case-insensitive": !0 },
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("open_directive"), 79;
+            case 1:
+              return this.begin("type_directive"), 80;
+            case 2:
+              return this.popState(), this.begin("arg_directive"), 14;
+            case 3:
+              return this.popState(), this.popState(), 82;
+            case 4:
+              return 81;
+            case 5:
+            case 52:
+            case 65:
+              return 5;
+            case 6:
+            case 7:
+            case 8:
+            case 9:
+            case 10:
+              break;
+            case 11:
+              return 23;
+            case 12:
+              return this.begin("ID"), 16;
+            case 13:
+              return this.begin("ID"), 20;
+            case 14:
+              return e.yytext = e.yytext.trim(), this.begin("ALIAS"), 69;
+            case 15:
+              return this.popState(), this.popState(), this.begin("LINE"), 18;
+            case 16:
+              return this.popState(), this.popState(), 5;
+            case 17:
+              return this.begin("LINE"), 39;
+            case 18:
+              return this.begin("LINE"), 41;
+            case 19:
+              return this.begin("LINE"), 42;
+            case 20:
+              return this.begin("LINE"), 43;
+            case 21:
+              return this.begin("LINE"), 52;
+            case 22:
+              return this.begin("LINE"), 45;
+            case 23:
+              return this.begin("LINE"), 51;
+            case 24:
+              return this.begin("LINE"), 47;
+            case 25:
+              return this.begin("LINE"), 50;
+            case 26:
+              return this.begin("LINE"), 49;
+            case 27:
+              return this.popState(), 19;
+            case 28:
+              return 40;
+            case 29:
+              return 64;
+            case 30:
+              return 65;
+            case 31:
+              return 58;
+            case 32:
+              return 59;
+            case 33:
+              return 60;
+            case 34:
+              return 61;
+            case 35:
+              return 56;
+            case 36:
+              return 53;
+            case 37:
+              return this.begin("ID"), 25;
+            case 38:
+              return this.begin("ID"), 26;
+            case 39:
+              return 32;
+            case 40:
+              return 33;
+            case 41:
+              return this.begin("acc_title"), 34;
+            case 42:
+              return this.popState(), "acc_title_value";
+            case 43:
+              return this.begin("acc_descr"), 36;
+            case 44:
+              return this.popState(), "acc_descr_value";
+            case 45:
+              this.begin("acc_descr_multiline");
+              break;
+            case 46:
+              this.popState();
+              break;
+            case 47:
+              return "acc_descr_multiline_value";
+            case 48:
+              return 7;
+            case 49:
+              return 22;
+            case 50:
+              return 24;
+            case 51:
+              return 63;
+            case 53:
+              return e.yytext = e.yytext.trim(), 69;
+            case 54:
+              return 72;
+            case 55:
+              return 73;
+            case 56:
+              return 70;
+            case 57:
+              return 71;
+            case 58:
+              return 74;
+            case 59:
+              return 75;
+            case 60:
+              return 76;
+            case 61:
+              return 77;
+            case 62:
+              return 78;
+            case 63:
+              return 67;
+            case 64:
+              return 68;
+            case 66:
+              return "INVALID";
+          }
+        },
+        rules: [
+          /^(?:%%\{)/i,
+          /^(?:((?:(?!\}%%)[^:.])*))/i,
+          /^(?::)/i,
+          /^(?:\}%%)/i,
+          /^(?:((?:(?!\}%%).|\n)*))/i,
+          /^(?:[\n]+)/i,
+          /^(?:\s+)/i,
+          /^(?:((?!\n)\s)+)/i,
+          /^(?:#[^\n]*)/i,
+          /^(?:%(?!\{)[^\n]*)/i,
+          /^(?:[^\}]%%[^\n]*)/i,
+          /^(?:[0-9]+(?=[ \n]+))/i,
+          /^(?:participant\b)/i,
+          /^(?:actor\b)/i,
+          /^(?:[^\->:\n,;]+?([\-]*[^\->:\n,;]+?)*?(?=((?!\n)\s)+as(?!\n)\s|[#\n;]|$))/i,
+          /^(?:as\b)/i,
+          /^(?:(?:))/i,
+          /^(?:loop\b)/i,
+          /^(?:rect\b)/i,
+          /^(?:opt\b)/i,
+          /^(?:alt\b)/i,
+          /^(?:else\b)/i,
+          /^(?:par\b)/i,
+          /^(?:and\b)/i,
+          /^(?:critical\b)/i,
+          /^(?:option\b)/i,
+          /^(?:break\b)/i,
+          /^(?:(?:[:]?(?:no)?wrap)?[^#\n;]*)/i,
+          /^(?:end\b)/i,
+          /^(?:left of\b)/i,
+          /^(?:right of\b)/i,
+          /^(?:links\b)/i,
+          /^(?:link\b)/i,
+          /^(?:properties\b)/i,
+          /^(?:details\b)/i,
+          /^(?:over\b)/i,
+          /^(?:note\b)/i,
+          /^(?:activate\b)/i,
+          /^(?:deactivate\b)/i,
+          /^(?:title\s[^#\n;]+)/i,
+          /^(?:title:\s[^#\n;]+)/i,
+          /^(?:accTitle\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*\{\s*)/i,
+          /^(?:[\}])/i,
+          /^(?:[^\}]*)/i,
+          /^(?:sequenceDiagram\b)/i,
+          /^(?:autonumber\b)/i,
+          /^(?:off\b)/i,
+          /^(?:,)/i,
+          /^(?:;)/i,
+          /^(?:[^\+\->:\n,;]+((?!(-x|--x|-\)|--\)))[\-]*[^\+\->:\n,;]+)*)/i,
+          /^(?:->>)/i,
+          /^(?:-->>)/i,
+          /^(?:->)/i,
+          /^(?:-->)/i,
+          /^(?:-[x])/i,
+          /^(?:--[x])/i,
+          /^(?:-[\)])/i,
+          /^(?:--[\)])/i,
+          /^(?::(?:(?:no)?wrap)?[^#\n;]+)/i,
+          /^(?:\+)/i,
+          /^(?:-)/i,
+          /^(?:$)/i,
+          /^(?:.)/i,
+        ],
+        conditions: {
+          acc_descr_multiline: { rules: [46, 47], inclusive: !1 },
+          acc_descr: { rules: [44], inclusive: !1 },
+          acc_title: { rules: [42], inclusive: !1 },
+          open_directive: { rules: [1, 8], inclusive: !1 },
+          type_directive: { rules: [2, 3, 8], inclusive: !1 },
+          arg_directive: { rules: [3, 4, 8], inclusive: !1 },
+          ID: { rules: [7, 8, 14], inclusive: !1 },
+          ALIAS: { rules: [7, 8, 15, 16], inclusive: !1 },
+          LINE: { rules: [7, 8, 27], inclusive: !1 },
+          INITIAL: {
+            rules: [
+              0,
+              5,
+              6,
+              8,
+              9,
+              10,
+              11,
+              12,
+              13,
+              17,
+              18,
+              19,
+              20,
+              21,
+              22,
+              23,
+              24,
+              25,
+              26,
+              28,
+              29,
+              30,
+              31,
+              32,
+              33,
+              34,
+              35,
+              36,
+              37,
+              38,
+              39,
+              40,
+              41,
+              43,
+              45,
+              48,
+              49,
+              50,
+              51,
+              52,
+              53,
+              54,
+              55,
+              56,
+              57,
+              58,
+              59,
+              60,
+              61,
+              62,
+              63,
+              64,
+              65,
+              66,
+            ],
+            inclusive: !0,
+          },
+        },
+      },
+        t);
+    function U() {
+      this.yy = {};
+    }
+    return j.lexer = z, U.prototype = j, j.Parser = U, new U();
+  }();
+  WE.parser = WE;
+  const HE = WE, qE = t => null !== t.match(/^\s*sequenceDiagram/);
+  let VE, GE, XE = {}, ZE = [], QE = !1;
+  const KE = function(t, e, n, i) {
+      const r = XE[t];
+      r && e === r.name && null == n
+        || (null != n && null != n.text || (n = { text: e, wrap: null, type: i }),
+          null != i && null != n.text || (n = { text: e, wrap: null, type: i }),
+          XE[t] = {
+            name: e,
+            description: n.text,
+            wrap: void 0 === n.wrap && eS() || !!n.wrap,
+            prevActor: VE,
+            links: {},
+            properties: {},
+            actorCnt: null,
+            rectData: null,
+            type: i || "participant",
+          },
+          VE && XE[VE] && (XE[VE].nextActor = t),
+          VE = t);
+    },
+    JE = function(t, e, n = { text: void 0, wrap: void 0 }, i) {
+      if (i === nS.ACTIVE_END) {
+        const e = (t => {
+          let e, n = 0;
+          for (e = 0; e < ZE.length; e++) {
+            ZE[e].type === nS.ACTIVE_START && ZE[e].from.actor === t && n++,
+              ZE[e].type === nS.ACTIVE_END && ZE[e].from.actor === t && n--;
+          }
+          return n;
+        })(t.actor);
+        if (e < 1) {
+          let e = new Error("Trying to inactivate an inactive participant (" + t.actor + ")");
+          throw e.hash = {
+            text: "->>-",
+            token: "->>-",
+            line: "1",
+            loc: { first_line: 1, last_line: 1, first_column: 1, last_column: 1 },
+            expected: ["'ACTIVE_PARTICIPANT'"],
+          },
+            e;
+        }
+      }
+      return ZE.push({ from: t, to: e, message: n.text, wrap: void 0 === n.wrap && eS() || !!n.wrap, type: i }), !0;
+    },
+    tS = function(t) {
+      return XE[t];
+    },
+    eS = () => void 0 !== GE ? GE : jx().sequence.wrap,
+    nS = {
+      SOLID: 0,
+      DOTTED: 1,
+      NOTE: 2,
+      SOLID_CROSS: 3,
+      DOTTED_CROSS: 4,
+      SOLID_OPEN: 5,
+      DOTTED_OPEN: 6,
+      LOOP_START: 10,
+      LOOP_END: 11,
+      ALT_START: 12,
+      ALT_ELSE: 13,
+      ALT_END: 14,
+      OPT_START: 15,
+      OPT_END: 16,
+      ACTIVE_START: 17,
+      ACTIVE_END: 18,
+      PAR_START: 19,
+      PAR_AND: 20,
+      PAR_END: 21,
+      RECT_START: 22,
+      RECT_END: 23,
+      SOLID_POINT: 24,
+      DOTTED_POINT: 25,
+      AUTONUMBER: 26,
+      CRITICAL_START: 27,
+      CRITICAL_OPTION: 28,
+      CRITICAL_END: 29,
+      BREAK_START: 30,
+      BREAK_END: 31,
+    },
+    iS = function(t, e, n) {
+      n.text, void 0 === n.wrap && eS() || n.wrap;
+      const i = [].concat(t, t);
+      ZE.push({
+        from: i[0],
+        to: i[1],
+        message: n.text,
+        wrap: void 0 === n.wrap && eS() || !!n.wrap,
+        type: nS.NOTE,
+        placement: e,
+      });
+    },
+    rS = function(t, e) {
+      const n = tS(t);
+      try {
+        let t = ab(e.text, jx());
+        t = t.replace(/&amp;/g, "&"), t = t.replace(/&equals;/g, "=");
+        aS(n, JSON.parse(t));
+      } catch (t) {
+        tb.error("error while parsing actor link text", t);
+      }
+    };
+  function aS(t, e) {
+    if (null == t.links) t.links = e;
+    else for (let n in e) t.links[n] = e[n];
+  }
+  const sS = function(t, e) {
+    const n = tS(t);
+    try {
+      let t = ab(e.text, jx());
+      oS(n, JSON.parse(t));
+    } catch (t) {
+      tb.error("error while parsing actor properties text", t);
+    }
+  };
+  function oS(t, e) {
+    if (null == t.properties) t.properties = e;
+    else for (let n in e) t.properties[n] = e[n];
+  }
+  const lS = function(t, e) {
+      const n = tS(t), i = document.getElementById(e.text);
+      try {
+        const t = i.innerHTML, e = JSON.parse(t);
+        e.properties && oS(n, e.properties), e.links && aS(n, e.links);
+      } catch (t) {
+        tb.error("error while parsing actor details text", t);
+      }
+    },
+    cS = function(t) {
+      if (Array.isArray(t)) {
+        t.forEach(function(t) {
+          cS(t);
+        });
+      } else {switch (t.type) {
+          case "sequenceIndex":
+            ZE.push({
+              from: void 0,
+              to: void 0,
+              message: { start: t.sequenceIndex, step: t.sequenceIndexStep, visible: t.sequenceVisible },
+              wrap: !1,
+              type: t.signalType,
+            });
+            break;
+          case "addParticipant":
+            KE(t.actor, t.actor, t.description, "participant");
+            break;
+          case "addActor":
+            KE(t.actor, t.actor, t.description, "actor");
+            break;
+          case "activeStart":
+          case "activeEnd":
+            JE(t.actor, void 0, void 0, t.signalType);
+            break;
+          case "addNote":
+            iS(t.actor, t.placement, t.text);
+            break;
+          case "addLinks":
+            rS(t.actor, t.text);
+            break;
+          case "addALink":
+            !function(t, e) {
+              const n = tS(t);
+              try {
+                const t = {};
+                let s = ab(e.text, jx());
+                var i = s.indexOf("@");
+                s = s.replace(/&amp;/g, "&"), s = s.replace(/&equals;/g, "=");
+                var r = s.slice(0, i - 1).trim(), a = s.slice(i + 1).trim();
+                t[r] = a, aS(n, t);
+              } catch (t) {
+                tb.error("error while parsing actor link text", t);
+              }
+            }(t.actor, t.text);
+            break;
+          case "addProperties":
+            sS(t.actor, t.text);
+            break;
+          case "addDetails":
+            lS(t.actor, t.text);
+            break;
+          case "addMessage":
+            JE(t.from, t.to, t.msg, t.signalType);
+            break;
+          case "loopStart":
+            JE(void 0, void 0, t.loopText, t.signalType);
+            break;
+          case "loopEnd":
+          case "rectEnd":
+          case "optEnd":
+          case "altEnd":
+          case "parEnd":
+          case "criticalEnd":
+          case "breakEnd":
+            JE(void 0, void 0, void 0, t.signalType);
+            break;
+          case "rectStart":
+            JE(void 0, void 0, t.color, t.signalType);
+            break;
+          case "optStart":
+            JE(void 0, void 0, t.optText, t.signalType);
+            break;
+          case "altStart":
+          case "else":
+            JE(void 0, void 0, t.altText, t.signalType);
+            break;
+          case "setAccTitle":
+            Ev(t.text);
+            break;
+          case "parStart":
+          case "and":
+            JE(void 0, void 0, t.parText, t.signalType);
+            break;
+          case "criticalStart":
+            JE(void 0, void 0, t.criticalText, t.signalType);
+            break;
+          case "option":
+            JE(void 0, void 0, t.optionText, t.signalType);
+            break;
+          case "breakStart":
+            JE(void 0, void 0, t.breakText, t.signalType);
+        }}
+    },
+    hS = {
+      addActor: KE,
+      addMessage: function(t, e, n, i) {
+        ZE.push({ from: t, to: e, message: n.text, wrap: void 0 === n.wrap && eS() || !!n.wrap, answer: i });
+      },
+      addSignal: JE,
+      addLinks: rS,
+      addDetails: lS,
+      addProperties: sS,
+      autoWrap: eS,
+      setWrap: function(t) {
+        GE = t;
+      },
+      enableSequenceNumbers: function() {
+        QE = !0;
+      },
+      disableSequenceNumbers: function() {
+        QE = !1;
+      },
+      showSequenceNumbers: () => QE,
+      getMessages: function() {
+        return ZE;
+      },
+      getActors: function() {
+        return XE;
+      },
+      getActor: tS,
+      getActorKeys: function() {
+        return Object.keys(XE);
+      },
+      getActorProperty: function(t, e) {
+        if (void 0 !== t && void 0 !== t.properties) return t.properties[e];
+      },
+      getAccTitle: Sv,
+      getDiagramTitle: Ov,
+      setDiagramTitle: Lv,
+      parseDirective: function(t, e, n) {
+        nL.parseDirective(this, t, e, n);
+      },
+      getConfig: () => jx().sequence,
+      clear: function() {
+        XE = {}, ZE = [], QE = !1, Cv();
+      },
+      parseMessage: function(t) {
+        const e = t.trim(),
+          n = {
+            text: e.replace(/^:?(?:no)?wrap:/, "").trim(),
+            wrap: null !== e.match(/^:?wrap:/) || null === e.match(/^:?nowrap:/) && void 0,
+          };
+        return tb.debug("parseMessage:", n), n;
+      },
+      LINETYPE: nS,
+      ARROWTYPE: { FILLED: 0, OPEN: 1 },
+      PLACEMENT: { LEFTOF: 0, RIGHTOF: 1, OVER: 2 },
+      addNote: iS,
+      setAccTitle: Ev,
+      apply: cS,
+      setAccDescription: Av,
+      getAccDescription: Dv,
+    };
+  let uS = [];
+  const dS = () => {
+      uS.forEach(t => {
+        t();
+      }), uS = [];
+    },
+    pS = function(t, e) {
+      const n = t.append("rect");
+      return n.attr("x", e.x),
+        n.attr("y", e.y),
+        n.attr("fill", e.fill),
+        n.attr("stroke", e.stroke),
+        n.attr("width", e.width),
+        n.attr("height", e.height),
+        n.attr("rx", e.rx),
+        n.attr("ry", e.ry),
+        void 0 !== e.class && n.attr("class", e.class),
+        n;
+    },
+    fS = (t, e) => {
+      (t => {
+        uS.push(t);
+      })(() => {
+        const n = document.querySelectorAll(t);
+        0 !== n.length && (n[0].addEventListener("mouseover", function() {
+          mS("actor" + e + "_popup");
+        }),
+          n[0].addEventListener("mouseout", function() {
+            bS("actor" + e + "_popup");
+          }));
+      });
+    },
+    gS = function(t, e, n, r) {
+      const a = t.append("image");
+      a.attr("x", e), a.attr("y", n);
+      var s = i(r);
+      a.attr("xlink:href", s);
+    },
+    yS = function(t, e, n, r) {
+      const a = t.append("use");
+      a.attr("x", e), a.attr("y", n);
+      var s = i(r);
+      a.attr("xlink:href", "#" + s);
+    },
+    mS = function(t) {
+      var e = document.getElementById(t);
+      null != e && (e.style.display = "block");
+    },
+    bS = function(t) {
+      var e = document.getElementById(t);
+      null != e && (e.style.display = "none");
+    },
+    _S = function(t, e) {
+      let n = 0, i = 0;
+      const r = e.text.split(ub.lineBreakRegex);
+      let a = [], s = 0, o = () => e.y;
+      if (void 0 !== e.valign && void 0 !== e.textMargin && e.textMargin > 0) {
+        switch (e.valign) {
+          case "top":
+          case "start":
+            o = () => Math.round(e.y + e.textMargin);
+            break;
+          case "middle":
+          case "center":
+            o = () => Math.round(e.y + (n + i + e.textMargin) / 2);
+            break;
+          case "bottom":
+          case "end":
+            o = () => Math.round(e.y + (n + i + 2 * e.textMargin) - e.textMargin);
+        }
+      }
+      if (void 0 !== e.anchor && void 0 !== e.textMargin && void 0 !== e.width) {
+        switch (e.anchor) {
+          case "left":
+          case "start":
+            e.x = Math.round(e.x + e.textMargin),
+              e.anchor = "start",
+              e.dominantBaseline = "middle",
+              e.alignmentBaseline = "middle";
+            break;
+          case "middle":
+          case "center":
+            e.x = Math.round(e.x + e.width / 2),
+              e.anchor = "middle",
+              e.dominantBaseline = "middle",
+              e.alignmentBaseline = "middle";
+            break;
+          case "right":
+          case "end":
+            e.x = Math.round(e.x + e.width - e.textMargin),
+              e.anchor = "end",
+              e.dominantBaseline = "middle",
+              e.alignmentBaseline = "middle";
+        }
+      }
+      for (let [l, c] of r.entries()) {
+        void 0 !== e.textMargin && 0 === e.textMargin && void 0 !== e.fontSize && (s = l * e.fontSize);
+        const r = t.append("text");
+        if (
+          r.attr("x", e.x),
+            r.attr("y", o()),
+            void 0 !== e.anchor
+            && r.attr("text-anchor", e.anchor).attr("dominant-baseline", e.dominantBaseline).attr(
+              "alignment-baseline",
+              e.alignmentBaseline,
+            ),
+            void 0 !== e.fontFamily && r.style("font-family", e.fontFamily),
+            void 0 !== e.fontSize && r.style("font-size", e.fontSize),
+            void 0 !== e.fontWeight && r.style("font-weight", e.fontWeight),
+            void 0 !== e.fill && r.attr("fill", e.fill),
+            void 0 !== e.class && r.attr("class", e.class),
+            void 0 !== e.dy ? r.attr("dy", e.dy) : 0 !== s && r.attr("dy", s),
+            e.tspan
+        ) {
+          const t = r.append("tspan");
+          t.attr("x", e.x), void 0 !== e.fill && t.attr("fill", e.fill), t.text(c);
+        } else r.text(c);
+        void 0 !== e.valign && void 0 !== e.textMargin && e.textMargin > 0
+        && (i += (r._groups || r)[0][0].getBBox().height, n = i), a.push(r);
+      }
+      return a;
+    },
+    xS = function(t, e) {
+      const n = t.append("polygon");
+      return n.attr(
+        "points",
+        function(t, e, n, i, r) {
+          return t + "," + e + " " + (t + n) + "," + e + " " + (t + n) + "," + (e + i - r) + " " + (t + n - 1.2 * r)
+            + "," + (e + i) + " " + t + "," + (e + i);
+        }(e.x, e.y, e.width, e.height, 7),
+      ),
+        n.attr("class", "labelBox"),
+        e.y = e.y + e.height / 2,
+        _S(t, e),
+        n;
+    };
+  let vS = -1;
+  const kS = (t, e) => {
+      t.selectAll && t.selectAll(".actor-line").attr("class", "200").attr("y2", e - 55);
+    },
+    wS = function() {
+      return {
+        x: 0,
+        y: 0,
+        fill: void 0,
+        anchor: void 0,
+        style: "#666",
+        width: void 0,
+        height: void 0,
+        textMargin: 0,
+        rx: 0,
+        ry: 0,
+        tspan: !0,
+        valign: void 0,
+      };
+    },
+    TS = function() {
+      return { x: 0, y: 0, fill: "#EDF2AE", stroke: "#666", width: 100, anchor: "start", height: 100, rx: 0, ry: 0 };
+    },
+    CS = function() {
+      function t(t, e, n, r, a, s, o) {
+        i(e.append("text").attr("x", n + a / 2).attr("y", r + s / 2 + 5).style("text-anchor", "middle").text(t), o);
+      }
+      function e(t, e, n, r, a, s, o, l) {
+        const { actorFontSize: c, actorFontFamily: h, actorFontWeight: u } = l;
+        let d = c && c.replace ? c.replace("px", "") : c;
+        const p = t.split(ub.lineBreakRegex);
+        for (let t = 0; t < p.length; t++) {
+          const l = t * d - d * (p.length - 1) / 2,
+            f = e.append("text").attr("x", n + a / 2).attr("y", r).style("text-anchor", "middle").style("font-size", c)
+              .style("font-weight", u).style("font-family", h);
+          f.append("tspan").attr("x", n + a / 2).attr("dy", l).text(p[t]),
+            f.attr("y", r + s / 2).attr("dominant-baseline", "central").attr("alignment-baseline", "central"),
+            i(f, o);
+        }
+      }
+      function n(t, n, r, a, s, o, l, c) {
+        const h = n.append("switch"),
+          u = h.append("foreignObject").attr("x", r).attr("y", a).attr("width", s).attr("height", o).append("xhtml:div")
+            .style("display", "table").style("height", "100%").style("width", "100%");
+        u.append("div").style("display", "table-cell").style("text-align", "center").style("vertical-align", "middle")
+          .text(t),
+          e(t, h, r, a, s, o, l, c),
+          i(u, l);
+      }
+      function i(t, e) {
+        for (const n in e) e.hasOwnProperty(n) && t.attr(n, e[n]);
+      }
+      return function(i) {
+        return "fo" === i.textPlacement ? n : "old" === i.textPlacement ? t : e;
+      };
+    }(),
+    ES = function() {
+      function t(t, e, n, r, a, s, o) {
+        i(e.append("text").attr("x", n).attr("y", r).style("text-anchor", "start").text(t), o);
+      }
+      function e(t, e, n, r, a, s, o, l) {
+        const { actorFontSize: c, actorFontFamily: h, actorFontWeight: u } = l, d = t.split(ub.lineBreakRegex);
+        for (let t = 0; t < d.length; t++) {
+          const a = t * c - c * (d.length - 1) / 2,
+            l = e.append("text").attr("x", n).attr("y", r).style("text-anchor", "start").style("font-size", c).style(
+              "font-weight",
+              u,
+            ).style("font-family", h);
+          l.append("tspan").attr("x", n).attr("dy", a).text(d[t]),
+            l.attr("y", r + s / 2).attr("dominant-baseline", "central").attr("alignment-baseline", "central"),
+            i(l, o);
+        }
+      }
+      function n(t, n, r, a, s, o, l, c) {
+        const h = n.append("switch"),
+          u = h.append("foreignObject").attr("x", r).attr("y", a).attr("width", s).attr("height", o).append("xhtml:div")
+            .style("display", "table").style("height", "100%").style("width", "100%");
+        u.append("div").style("display", "table-cell").style("text-align", "center").style("vertical-align", "middle")
+          .text(t),
+          e(t, h, r, a, 0, o, l, c),
+          i(u, l);
+      }
+      function i(t, e) {
+        for (const n in e) e.hasOwnProperty(n) && t.attr(n, e[n]);
+      }
+      return function(i) {
+        return "fo" === i.textPlacement ? n : "old" === i.textPlacement ? t : e;
+      };
+    }(),
+    SS = {
+      drawRect: pS,
+      drawText: _S,
+      drawLabel: xS,
+      drawActor: function(t, e, n) {
+        switch (e.type) {
+          case "actor":
+            return function(t, e, n) {
+              const i = e.x + e.width / 2;
+              0 === e.y
+                && (vS++,
+                  t.append("line").attr("id", "actor" + vS).attr("x1", i).attr("y1", 80).attr("x2", i).attr("y2", 2e3)
+                    .attr("class", "actor-line").attr("stroke-width", "0.5px").attr("stroke", "#999"));
+              const r = t.append("g");
+              r.attr("class", "actor-man");
+              const a = TS();
+              a.x = e.x,
+                a.y = e.y,
+                a.fill = "#eaeaea",
+                a.width = e.width,
+                a.height = e.height,
+                a.class = "actor",
+                a.rx = 3,
+                a.ry = 3,
+                r.append("line").attr("id", "actor-man-torso" + vS).attr("x1", i).attr("y1", e.y + 25).attr("x2", i)
+                  .attr("y2", e.y + 45),
+                r.append("line").attr("id", "actor-man-arms" + vS).attr("x1", i - 18).attr("y1", e.y + 33).attr(
+                  "x2",
+                  i + 18,
+                ).attr("y2", e.y + 33),
+                r.append("line").attr("x1", i - 18).attr("y1", e.y + 60).attr("x2", i).attr("y2", e.y + 45),
+                r.append("line").attr("x1", i).attr("y1", e.y + 45).attr("x2", i + 16).attr("y2", e.y + 60);
+              const s = r.append("circle");
+              s.attr("cx", e.x + e.width / 2),
+                s.attr("cy", e.y + 10),
+                s.attr("r", 15),
+                s.attr("width", e.width),
+                s.attr("height", e.height);
+              const o = r.node().getBBox();
+              return e.height = o.height,
+                CS(n)(e.description, r, a.x, a.y + 35, a.width, a.height, { class: "actor" }, n),
+                e.height;
+            }(t, e, n);
+          case "participant":
+            return function(t, e, n) {
+              const i = e.x + e.width / 2, r = t.append("g");
+              var a = r;
+              0 === e.y
+                && (vS++,
+                  a.append("line").attr("id", "actor" + vS).attr("x1", i).attr("y1", 5).attr("x2", i).attr("y2", 2e3)
+                    .attr("class", "actor-line").attr("stroke-width", "0.5px").attr("stroke", "#999"),
+                  a = r.append("g"),
+                  e.actorCnt = vS,
+                  null != e.links && (a.attr("id", "root-" + vS), fS("#root-" + vS, vS)));
+              const s = TS();
+              var o = "actor";
+              null != e.properties && e.properties.class ? o = e.properties.class : s.fill = "#eaeaea",
+                s.x = e.x,
+                s.y = e.y,
+                s.width = e.width,
+                s.height = e.height,
+                s.class = o,
+                s.rx = 3,
+                s.ry = 3;
+              const l = pS(a, s);
+              if (e.rectData = s, null != e.properties && e.properties.icon) {
+                const t = e.properties.icon.trim();
+                "@" === t.charAt(0)
+                  ? yS(a, s.x + s.width - 20, s.y + 10, t.substr(1))
+                  : gS(a, s.x + s.width - 20, s.y + 10, t);
+              }
+              CS(n)(e.description, a, s.x, s.y, s.width, s.height, { class: "actor" }, n);
+              let c = e.height;
+              if (l.node) {
+                const t = l.node().getBBox();
+                e.height = t.height, c = t.height;
+              }
+              return c;
+            }(t, e, n);
+        }
+      },
+      drawPopup: function(t, e, n, r, a) {
+        if (void 0 === e.links || null === e.links || 0 === Object.keys(e.links).length) return { height: 0, width: 0 };
+        const s = e.links, o = e.actorCnt, l = e.rectData;
+        var c = "none";
+        a && (c = "block !important");
+        const h = t.append("g");
+        h.attr("id", "actor" + o + "_popup"),
+          h.attr("class", "actorPopupMenu"),
+          h.attr("display", c),
+          fS("#actor" + o + "_popup", o);
+        var u = "";
+        void 0 !== l.class && (u = " " + l.class);
+        let d = l.width > n ? l.width : n;
+        const p = h.append("rect");
+        if (
+          p.attr("class", "actorPopupMenuPanel" + u),
+            p.attr("x", l.x),
+            p.attr("y", l.height),
+            p.attr("fill", l.fill),
+            p.attr("stroke", l.stroke),
+            p.attr("width", d),
+            p.attr("height", l.height),
+            p.attr("rx", l.rx),
+            p.attr("ry", l.ry),
+            null != s
+        ) {
+          var f = 20;
+          for (let t in s) {
+            var g = h.append("a"), y = i(s[t]);
+            g.attr("xlink:href", y),
+              g.attr("target", "_blank"),
+              ES(r)(t, g, l.x + 10, l.height + f, d, 20, { class: "actor" }, r),
+              f += 30;
+          }
+        }
+        return p.attr("height", f), { height: l.height + f, width: d };
+      },
+      drawImage: gS,
+      drawEmbeddedImage: yS,
+      anchorElement: function(t) {
+        return t.append("g");
+      },
+      drawActivation: function(t, e, n, i, r) {
+        const a = TS(), s = e.anchored;
+        a.x = e.startx,
+          a.y = e.starty,
+          a.class = "activation" + r % 3,
+          a.width = e.stopx - e.startx,
+          a.height = n - e.starty,
+          pS(s, a);
+      },
+      drawLoop: function(t, e, n, i) {
+        const {
+            boxMargin: r,
+            boxTextMargin: a,
+            labelBoxHeight: s,
+            labelBoxWidth: o,
+            messageFontFamily: l,
+            messageFontSize: c,
+            messageFontWeight: h,
+          } = i,
+          u = t.append("g"),
+          d = function(t, e, n, i) {
+            return u.append("line").attr("x1", t).attr("y1", e).attr("x2", n).attr("y2", i).attr("class", "loopLine");
+          };
+        d(e.startx, e.starty, e.stopx, e.starty),
+          d(e.stopx, e.starty, e.stopx, e.stopy),
+          d(e.startx, e.stopy, e.stopx, e.stopy),
+          d(e.startx, e.starty, e.startx, e.stopy),
+          void 0 !== e.sections && e.sections.forEach(function(t) {
+            d(e.startx, t.y, e.stopx, t.y).style("stroke-dasharray", "3, 3");
+          });
+        let p = wS();
+        p.text = n,
+          p.x = e.startx,
+          p.y = e.starty,
+          p.fontFamily = l,
+          p.fontSize = c,
+          p.fontWeight = h,
+          p.anchor = "middle",
+          p.valign = "middle",
+          p.tspan = !1,
+          p.width = o || 50,
+          p.height = s || 20,
+          p.textMargin = a,
+          p.class = "labelText",
+          xS(u, p),
+          p = wS(),
+          p.text = e.title,
+          p.x = e.startx + o / 2 + (e.stopx - e.startx) / 2,
+          p.y = e.starty + r + a,
+          p.anchor = "middle",
+          p.valign = "middle",
+          p.textMargin = a,
+          p.class = "loopText",
+          p.fontFamily = l,
+          p.fontSize = c,
+          p.fontWeight = h,
+          p.wrap = !0;
+        let f = _S(u, p);
+        return void 0 !== e.sectionTitles && e.sectionTitles.forEach(function(t, n) {
+          if (t.message) {
+            p.text = t.message,
+              p.x = e.startx + (e.stopx - e.startx) / 2,
+              p.y = e.sections[n].y + r + a,
+              p.class = "loopText",
+              p.anchor = "middle",
+              p.valign = "middle",
+              p.tspan = !1,
+              p.fontFamily = l,
+              p.fontSize = c,
+              p.fontWeight = h,
+              p.wrap = e.wrap,
+              f = _S(u, p);
+            let i = Math.round(f.map(t => (t._groups || t)[0][0].getBBox().height).reduce((t, e) => t + e));
+            e.sections[n].height += i - (r + a);
+          }
+        }),
+          e.height = Math.round(e.stopy - e.starty),
+          u;
+      },
+      drawBackgroundRect: function(t, e) {
+        pS(t, {
+          x: e.startx,
+          y: e.starty,
+          width: e.stopx - e.startx,
+          height: e.stopy - e.starty,
+          fill: e.fill,
+          class: "rect",
+        }).lower();
+      },
+      insertArrowHead: function(t) {
+        t.append("defs").append("marker").attr("id", "arrowhead").attr("refX", 9).attr("refY", 5).attr(
+          "markerUnits",
+          "userSpaceOnUse",
+        ).attr("markerWidth", 12).attr("markerHeight", 12).attr("orient", "auto").append("path").attr(
+          "d",
+          "M 0 0 L 10 5 L 0 10 z",
+        );
+      },
+      insertArrowFilledHead: function(t) {
+        t.append("defs").append("marker").attr("id", "filled-head").attr("refX", 18).attr("refY", 7).attr(
+          "markerWidth",
+          20,
+        ).attr("markerHeight", 28).attr("orient", "auto").append("path").attr("d", "M 18,7 L9,13 L14,7 L9,1 Z");
+      },
+      insertSequenceNumber: function(t) {
+        t.append("defs").append("marker").attr("id", "sequencenumber").attr("refX", 15).attr("refY", 15).attr(
+          "markerWidth",
+          60,
+        ).attr("markerHeight", 40).attr("orient", "auto").append("circle").attr("cx", 15).attr("cy", 15).attr("r", 6);
+      },
+      insertArrowCrossHead: function(t) {
+        t.append("defs").append("marker").attr("id", "crosshead").attr("markerWidth", 15).attr("markerHeight", 8).attr(
+          "orient",
+          "auto",
+        ).attr("refX", 4).attr("refY", 5).append("path").attr("fill", "none").attr("stroke", "#000000").style(
+          "stroke-dasharray",
+          "0, 0",
+        ).attr("stroke-width", "1pt").attr("d", "M 1,2 L 6,7 M 6,2 L 1,7");
+      },
+      insertDatabaseIcon: function(t) {
+        t.append("defs").append("symbol").attr("id", "database").attr("fill-rule", "evenodd").attr(
+          "clip-rule",
+          "evenodd",
+        ).append("path").attr("transform", "scale(.5)").attr(
+          "d",
+          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+        );
+      },
+      insertComputerIcon: function(t) {
+        t.append("defs").append("symbol").attr("id", "computer").attr("width", "24").attr("height", "24").append("path")
+          .attr("transform", "scale(.5)").attr(
+            "d",
+            "M2 2v13h20v-13h-20zm18 11h-16v-9h16v9zm-10.228 6l.466-1h3.524l.467 1h-4.457zm14.228 3h-24l2-6h2.104l-1.33 4h18.45l-1.297-4h2.073l2 6zm-5-10h-14v-7h14v7z",
+          );
+      },
+      insertClockIcon: function(t) {
+        t.append("defs").append("symbol").attr("id", "clock").attr("width", "24").attr("height", "24").append("path")
+          .attr("transform", "scale(.5)").attr(
+            "d",
+            "M12 2c5.514 0 10 4.486 10 10s-4.486 10-10 10-10-4.486-10-10 4.486-10 10-10zm0-2c-6.627 0-12 5.373-12 12s5.373 12 12 12 12-5.373 12-12-5.373-12-12-12zm5.848 12.459c.202.038.202.333.001.372-1.907.361-6.045 1.111-6.547 1.111-.719 0-1.301-.582-1.301-1.301 0-.512.77-5.447 1.125-7.445.034-.192.312-.181.343.014l.985 6.238 5.394 1.011z",
+          );
+      },
+      getTextObj: wS,
+      getNoteRect: TS,
+      popupMenu: function(t) {
+        return "var pu = document.getElementById('" + t + "'); if (pu != null) { pu.style.display = 'block'; }";
+      },
+      popdownMenu: function(t) {
+        return "var pu = document.getElementById('" + t + "'); if (pu != null) { pu.style.display = 'none'; }";
+      },
+      fixLifeLineHeights: kS,
+      sanitizeUrl: i,
+    };
+  let AS = {};
+  const DS = {
+      data: { startx: void 0, stopx: void 0, starty: void 0, stopy: void 0 },
+      verticalPos: 0,
+      sequenceItems: [],
+      activations: [],
+      models: {
+        getHeight: function() {
+          return Math.max.apply(null, 0 === this.actors.length ? [0] : this.actors.map(t => t.height || 0))
+            + (0 === this.loops.length ? 0 : this.loops.map(t => t.height || 0).reduce((t, e) => t + e))
+            + (0 === this.messages.length ? 0 : this.messages.map(t => t.height || 0).reduce((t, e) => t + e))
+            + (0 === this.notes.length ? 0 : this.notes.map(t => t.height || 0).reduce((t, e) => t + e));
+        },
+        clear: function() {
+          this.actors = [], this.loops = [], this.messages = [], this.notes = [];
+        },
+        addActor: function(t) {
+          this.actors.push(t);
+        },
+        addLoop: function(t) {
+          this.loops.push(t);
+        },
+        addMessage: function(t) {
+          this.messages.push(t);
+        },
+        addNote: function(t) {
+          this.notes.push(t);
+        },
+        lastActor: function() {
+          return this.actors[this.actors.length - 1];
+        },
+        lastLoop: function() {
+          return this.loops[this.loops.length - 1];
+        },
+        lastMessage: function() {
+          return this.messages[this.messages.length - 1];
+        },
+        lastNote: function() {
+          return this.notes[this.notes.length - 1];
+        },
+        actors: [],
+        loops: [],
+        messages: [],
+        notes: [],
+      },
+      init: function() {
+        this.sequenceItems = [],
+          this.activations = [],
+          this.models.clear(),
+          this.data = { startx: void 0, stopx: void 0, starty: void 0, stopy: void 0 },
+          this.verticalPos = 0,
+          IS(jx());
+      },
+      updateVal: function(t, e, n, i) {
+        void 0 === t[e] ? t[e] = n : t[e] = i(n, t[e]);
+      },
+      updateBounds: function(t, e, n, i) {
+        const r = this;
+        let a = 0;
+        function s(s) {
+          return function(o) {
+            a++;
+            const l = r.sequenceItems.length - a + 1;
+            r.updateVal(o, "starty", e - l * AS.boxMargin, Math.min),
+              r.updateVal(o, "stopy", i + l * AS.boxMargin, Math.max),
+              r.updateVal(DS.data, "startx", t - l * AS.boxMargin, Math.min),
+              r.updateVal(DS.data, "stopx", n + l * AS.boxMargin, Math.max),
+              "activation" !== s
+              && (r.updateVal(o, "startx", t - l * AS.boxMargin, Math.min),
+                r.updateVal(o, "stopx", n + l * AS.boxMargin, Math.max),
+                r.updateVal(DS.data, "starty", e - l * AS.boxMargin, Math.min),
+                r.updateVal(DS.data, "stopy", i + l * AS.boxMargin, Math.max));
+          };
+        }
+        this.sequenceItems.forEach(s()), this.activations.forEach(s("activation"));
+      },
+      insert: function(t, e, n, i) {
+        const r = Math.min(t, n), a = Math.max(t, n), s = Math.min(e, i), o = Math.max(e, i);
+        this.updateVal(DS.data, "startx", r, Math.min),
+          this.updateVal(DS.data, "starty", s, Math.min),
+          this.updateVal(DS.data, "stopx", a, Math.max),
+          this.updateVal(DS.data, "stopy", o, Math.max),
+          this.updateBounds(r, s, a, o);
+      },
+      newActivation: function(t, e, n) {
+        const i = n[t.from.actor],
+          r = FS(t.from.actor).length || 0,
+          a = i.x + i.width / 2 + (r - 1) * AS.activationWidth / 2;
+        this.activations.push({
+          startx: a,
+          starty: this.verticalPos + 2,
+          stopx: a + AS.activationWidth,
+          stopy: void 0,
+          actor: t.from.actor,
+          anchored: SS.anchorElement(e),
+        });
+      },
+      endActivation: function(t) {
+        const e = this.activations.map(function(t) {
+          return t.actor;
+        }).lastIndexOf(t.from.actor);
+        return this.activations.splice(e, 1)[0];
+      },
+      createLoop: function(t = { message: void 0, wrap: !1, width: void 0 }, e) {
+        return {
+          startx: void 0,
+          starty: this.verticalPos,
+          stopx: void 0,
+          stopy: void 0,
+          title: t.message,
+          wrap: t.wrap,
+          width: t.width,
+          height: 0,
+          fill: e,
+        };
+      },
+      newLoop: function(t = { message: void 0, wrap: !1, width: void 0 }, e) {
+        this.sequenceItems.push(this.createLoop(t, e));
+      },
+      endLoop: function() {
+        return this.sequenceItems.pop();
+      },
+      addSectionToLoop: function(t) {
+        const e = this.sequenceItems.pop();
+        e.sections = e.sections || [],
+          e.sectionTitles = e.sectionTitles || [],
+          e.sections.push({ y: DS.getVerticalPos(), height: 0 }),
+          e.sectionTitles.push(t),
+          this.sequenceItems.push(e);
+      },
+      bumpVerticalPos: function(t) {
+        this.verticalPos = this.verticalPos + t, this.data.stopy = this.verticalPos;
+      },
+      getVerticalPos: function() {
+        return this.verticalPos;
+      },
+      getBounds: function() {
+        return { bounds: this.data, models: this.models };
+      },
+    },
+    LS = t => ({ fontFamily: t.messageFontFamily, fontSize: t.messageFontSize, fontWeight: t.messageFontWeight }),
+    OS = t => ({ fontFamily: t.noteFontFamily, fontSize: t.noteFontSize, fontWeight: t.noteFontWeight }),
+    NS = t => ({ fontFamily: t.actorFontFamily, fontSize: t.actorFontSize, fontWeight: t.actorFontWeight });
+  const MS = function(t, e, n, i, r, a) {
+      if (!0 === r.hideUnusedParticipants) {
+        const t = new Set();
+        a.forEach(e => {
+          t.add(e.from), t.add(e.to);
+        }), n = n.filter(e => t.has(e));
+      }
+      let s = 0, o = 0, l = 0;
+      for (const r of n) {
+        const n = e[r];
+        n.width = n.width || AS.width,
+          n.height = Math.max(n.height || AS.height, AS.height),
+          n.margin = n.margin || AS.actorMargin,
+          n.x = s + o,
+          n.y = i;
+        const a = SS.drawActor(t, n, AS);
+        l = Math.max(l, a),
+          DS.insert(n.x, i, n.x + n.width, n.height),
+          s += n.width,
+          o += n.margin,
+          DS.models.addActor(n);
+      }
+      DS.bumpVerticalPos(l);
+    },
+    BS = function(t, e, n, i) {
+      let r = 0, a = 0;
+      for (const s of n) {
+        const n = e[s], o = PS(n), l = SS.drawPopup(t, n, o, AS, AS.forceMenus, i);
+        l.height > r && (r = l.height), l.width + n.x > a && (a = l.width + n.x);
+      }
+      return { maxHeight: r, maxWidth: a };
+    },
+    IS = function(t) {
+      lx(AS, t),
+        t.fontFamily && (AS.actorFontFamily = AS.noteFontFamily = AS.messageFontFamily = t.fontFamily),
+        t.fontSize && (AS.actorFontSize = AS.noteFontSize = AS.messageFontSize = t.fontSize),
+        t.fontWeight && (AS.actorFontWeight = AS.noteFontWeight = AS.messageFontWeight = t.fontWeight);
+    },
+    FS = function(t) {
+      return DS.activations.filter(function(e) {
+        return e.actor === t;
+      });
+    },
+    RS = function(t, e) {
+      const n = e[t], i = FS(t);
+      return [
+        i.reduce(function(t, e) {
+          return Math.min(t, e.startx);
+        }, n.x + n.width / 2),
+        i.reduce(function(t, e) {
+          return Math.max(t, e.stopx);
+        }, n.x + n.width / 2),
+      ];
+    };
+  function $S(t, e, n, i, r) {
+    DS.bumpVerticalPos(n);
+    let a = i;
+    if (e.id && e.message && t[e.id]) {
+      const n = t[e.id].width, r = LS(AS);
+      e.message = Dx.wrapLabel(`[${e.message}]`, n - 2 * AS.wrapPadding, r), e.width = n, e.wrap = !0;
+      const s = Dx.calculateTextDimensions(e.message, r), o = Math.max(s.height, AS.labelBoxHeight);
+      a = i + o, tb.debug(`${o} - ${e.message}`);
+    }
+    r(e), DS.bumpVerticalPos(a);
+  }
+  const PS = function(t) {
+    let e = 0;
+    const n = NS(AS);
+    for (const i in t.links) {
+      const t = Dx.calculateTextDimensions(i, n).width + 2 * AS.wrapPadding + 2 * AS.boxMargin;
+      e < t && (e = t);
+    }
+    return e;
+  };
+  const YS = function(t, e, n, i) {
+      const r = {}, a = [];
+      let s, o, l;
+      return t.forEach(function(t) {
+        switch (t.id = Dx.random({ length: 10 }), t.type) {
+          case i.db.LINETYPE.LOOP_START:
+          case i.db.LINETYPE.ALT_START:
+          case i.db.LINETYPE.OPT_START:
+          case i.db.LINETYPE.PAR_START:
+          case i.db.LINETYPE.CRITICAL_START:
+          case i.db.LINETYPE.BREAK_START:
+            a.push({ id: t.id, msg: t.message, from: Number.MAX_SAFE_INTEGER, to: Number.MIN_SAFE_INTEGER, width: 0 });
+            break;
+          case i.db.LINETYPE.ALT_ELSE:
+          case i.db.LINETYPE.PAR_AND:
+          case i.db.LINETYPE.CRITICAL_OPTION:
+            t.message && (s = a.pop(), r[s.id] = s, r[t.id] = s, a.push(s));
+            break;
+          case i.db.LINETYPE.LOOP_END:
+          case i.db.LINETYPE.ALT_END:
+          case i.db.LINETYPE.OPT_END:
+          case i.db.LINETYPE.PAR_END:
+          case i.db.LINETYPE.CRITICAL_END:
+          case i.db.LINETYPE.BREAK_END:
+            s = a.pop(), r[s.id] = s;
+            break;
+          case i.db.LINETYPE.ACTIVE_START:
+            {
+              const n = e[t.from ? t.from.actor : t.to.actor],
+                i = FS(t.from ? t.from.actor : t.to.actor).length,
+                r = n.x + n.width / 2 + (i - 1) * AS.activationWidth / 2,
+                a = { startx: r, stopx: r + AS.activationWidth, actor: t.from.actor, enabled: !0 };
+              DS.activations.push(a);
+            }
+            break;
+          case i.db.LINETYPE.ACTIVE_END: {
+            const e = DS.activations.map(t => t.actor).lastIndexOf(t.from.actor);
+            delete DS.activations.splice(e, 1)[0];
+          }
+        }
+        void 0 !== t.placement
+          ? (o = function(t, e, n) {
+            const i = e[t.from].x, r = e[t.to].x, a = t.wrap && t.message;
+            let s = Dx.calculateTextDimensions(a ? Dx.wrapLabel(t.message, AS.width, OS(AS)) : t.message, OS(AS));
+            const o = {
+              width: a ? AS.width : Math.max(AS.width, s.width + 2 * AS.noteMargin),
+              height: 0,
+              startx: e[t.from].x,
+              stopx: 0,
+              starty: 0,
+              stopy: 0,
+              message: t.message,
+            };
+            return t.placement === n.db.PLACEMENT.RIGHTOF
+              ? (o.width = a
+                ? Math.max(AS.width, s.width)
+                : Math.max(e[t.from].width / 2 + e[t.to].width / 2, s.width + 2 * AS.noteMargin),
+                o.startx = i + (e[t.from].width + AS.actorMargin) / 2)
+              : t.placement === n.db.PLACEMENT.LEFTOF
+              ? (o.width = a
+                ? Math.max(AS.width, s.width + 2 * AS.noteMargin)
+                : Math.max(e[t.from].width / 2 + e[t.to].width / 2, s.width + 2 * AS.noteMargin),
+                o.startx = i - o.width + (e[t.from].width - AS.actorMargin) / 2)
+              : t.to === t.from
+              ? (s = Dx.calculateTextDimensions(
+                a ? Dx.wrapLabel(t.message, Math.max(AS.width, e[t.from].width), OS(AS)) : t.message,
+                OS(AS),
+              ),
+                o.width = a
+                  ? Math.max(AS.width, e[t.from].width)
+                  : Math.max(e[t.from].width, AS.width, s.width + 2 * AS.noteMargin),
+                o.startx = i + (e[t.from].width - o.width) / 2)
+              : (o.width = Math.abs(i + e[t.from].width / 2 - (r + e[t.to].width / 2)) + AS.actorMargin,
+                o.startx = i < r
+                  ? i + e[t.from].width / 2 - AS.actorMargin / 2
+                  : r + e[t.to].width / 2 - AS.actorMargin / 2),
+              a && (o.message = Dx.wrapLabel(t.message, o.width - 2 * AS.wrapPadding, OS(AS))),
+              tb.debug(`NM:[${o.startx},${o.stopx},${o.starty},${o.stopy}:${o.width},${o.height}=${t.message}]`),
+              o;
+          }(t, e, i),
+            t.noteModel = o,
+            a.forEach(t => {
+              s = t,
+                s.from = Math.min(s.from, o.startx),
+                s.to = Math.max(s.to, o.startx + o.width),
+                s.width = Math.max(s.width, Math.abs(s.from - s.to)) - AS.labelBoxWidth;
+            }))
+          : (l = function(t, e, n) {
+            let i = !1;
+            if (
+              [
+                n.db.LINETYPE.SOLID_OPEN,
+                n.db.LINETYPE.DOTTED_OPEN,
+                n.db.LINETYPE.SOLID,
+                n.db.LINETYPE.DOTTED,
+                n.db.LINETYPE.SOLID_CROSS,
+                n.db.LINETYPE.DOTTED_CROSS,
+                n.db.LINETYPE.SOLID_POINT,
+                n.db.LINETYPE.DOTTED_POINT,
+              ].includes(t.type) && (i = !0), !i
+            ) return {};
+            const r = RS(t.from, e),
+              a = RS(t.to, e),
+              s = r[0] <= a[0] ? 1 : 0,
+              o = r[0] < a[0] ? 0 : 1,
+              l = [...r, ...a],
+              c = Math.abs(a[o] - r[s]);
+            t.wrap && t.message
+              && (t.message = Dx.wrapLabel(t.message, Math.max(c + 2 * AS.wrapPadding, AS.width), LS(AS)));
+            const h = Dx.calculateTextDimensions(t.message, LS(AS));
+            return {
+              width: Math.max(t.wrap ? 0 : h.width + 2 * AS.wrapPadding, c + 2 * AS.wrapPadding, AS.width),
+              height: 0,
+              startx: r[s],
+              stopx: a[o],
+              starty: 0,
+              stopy: 0,
+              message: t.message,
+              type: t.type,
+              wrap: t.wrap,
+              fromBounds: Math.min.apply(null, l),
+              toBounds: Math.max.apply(null, l),
+            };
+          }(t, e, i),
+            t.msgModel = l,
+            l.startx && l.stopx && a.length > 0 && a.forEach(n => {
+              if (s = n, l.startx === l.stopx) {
+                const n = e[t.from], i = e[t.to];
+                s.from = Math.min(n.x - l.width / 2, n.x - n.width / 2, s.from),
+                  s.to = Math.max(i.x + l.width / 2, i.x + n.width / 2, s.to),
+                  s.width = Math.max(s.width, Math.abs(s.to - s.from)) - AS.labelBoxWidth;
+              } else {s.from = Math.min(l.startx, s.from),
+                  s.to = Math.max(l.stopx, s.to),
+                  s.width = Math.max(s.width, l.width) - AS.labelBoxWidth;}
+            }));
+      }),
+        DS.activations = [],
+        tb.debug("Loop type widths:", r),
+        r;
+    },
+    jS = {
+      bounds: DS,
+      drawActors: MS,
+      drawActorsPopup: BS,
+      setConf: IS,
+      draw: function(t, e, n, i) {
+        const { securityLevel: r, sequence: a } = jx();
+        let s;
+        AS = a, "sandbox" === r && (s = ie("#i" + e));
+        const o = ie("sandbox" === r ? s.nodes()[0].contentDocument.body : "body"),
+          l = "sandbox" === r ? s.nodes()[0].contentDocument : document;
+        DS.init(), tb.debug(i.db);
+        const c = "sandbox" === r ? o.select(`[id="${e}"]`) : ie(`[id="${e}"]`),
+          h = i.db.getActors(),
+          u = i.db.getActorKeys(),
+          d = i.db.getMessages(),
+          p = i.db.getDiagramTitle(),
+          f = function(t, e, n) {
+            const i = {};
+            return e.forEach(function(e) {
+              if (t[e.to] && t[e.from]) {
+                const r = t[e.to];
+                if (e.placement === n.db.PLACEMENT.LEFTOF && !r.prevActor) return;
+                if (e.placement === n.db.PLACEMENT.RIGHTOF && !r.nextActor) return;
+                const a = void 0 !== e.placement,
+                  s = !a,
+                  o = a ? OS(AS) : LS(AS),
+                  l = e.wrap ? Dx.wrapLabel(e.message, AS.width - 2 * AS.wrapPadding, o) : e.message,
+                  c = Dx.calculateTextDimensions(l, o).width + 2 * AS.wrapPadding;
+                s && e.from === r.nextActor
+                  ? i[e.to] = Math.max(i[e.to] || 0, c)
+                  : s && e.from === r.prevActor
+                  ? i[e.from] = Math.max(i[e.from] || 0, c)
+                  : s && e.from === e.to
+                  ? (i[e.from] = Math.max(i[e.from] || 0, c / 2), i[e.to] = Math.max(i[e.to] || 0, c / 2))
+                  : e.placement === n.db.PLACEMENT.RIGHTOF
+                  ? i[e.from] = Math.max(i[e.from] || 0, c)
+                  : e.placement === n.db.PLACEMENT.LEFTOF
+                  ? i[r.prevActor] = Math.max(i[r.prevActor] || 0, c)
+                  : e.placement === n.db.PLACEMENT.OVER
+                    && (r.prevActor && (i[r.prevActor] = Math.max(i[r.prevActor] || 0, c / 2)),
+                      r.nextActor && (i[e.from] = Math.max(i[e.from] || 0, c / 2)));
+              }
+            }),
+              tb.debug("maxMessageWidthPerActor:", i),
+              i;
+          }(h, d, i);
+        AS.height = function(t, e) {
+          let n = 0;
+          Object.keys(t).forEach(e => {
+            const i = t[e];
+            i.wrap && (i.description = Dx.wrapLabel(i.description, AS.width - 2 * AS.wrapPadding, NS(AS)));
+            const r = Dx.calculateTextDimensions(i.description, NS(AS));
+            i.width = i.wrap ? AS.width : Math.max(AS.width, r.width + 2 * AS.wrapPadding),
+              i.height = i.wrap ? Math.max(r.height, AS.height) : AS.height,
+              n = Math.max(n, i.height);
+          });
+          for (const n in e) {
+            const i = t[n];
+            if (!i) continue;
+            const r = t[i.nextActor];
+            if (!r) continue;
+            const a = e[n] + AS.actorMargin - i.width / 2 - r.width / 2;
+            i.margin = Math.max(a, AS.actorMargin);
+          }
+          return Math.max(n, AS.height);
+        }(h, f),
+          SS.insertComputerIcon(c),
+          SS.insertDatabaseIcon(c),
+          SS.insertClockIcon(c),
+          MS(c, h, u, 0, AS, d);
+        const g = YS(d, h, f, i);
+        SS.insertArrowHead(c), SS.insertArrowCrossHead(c), SS.insertArrowFilledHead(c), SS.insertSequenceNumber(c);
+        let y = 1, m = 1;
+        const b = [];
+        d.forEach(function(t) {
+          let e, n, r;
+          switch (t.type) {
+            case i.db.LINETYPE.NOTE:
+              n = t.noteModel,
+                function(t, e) {
+                  DS.bumpVerticalPos(AS.boxMargin), e.height = AS.boxMargin, e.starty = DS.getVerticalPos();
+                  const n = SS.getNoteRect();
+                  n.x = e.startx, n.y = e.starty, n.width = e.width || AS.width, n.class = "note";
+                  const i = t.append("g"), r = SS.drawRect(i, n), a = SS.getTextObj();
+                  a.x = e.startx,
+                    a.y = e.starty,
+                    a.width = n.width,
+                    a.dy = "1em",
+                    a.text = e.message,
+                    a.class = "noteText",
+                    a.fontFamily = AS.noteFontFamily,
+                    a.fontSize = AS.noteFontSize,
+                    a.fontWeight = AS.noteFontWeight,
+                    a.anchor = AS.noteAlign,
+                    a.textMargin = AS.noteMargin,
+                    a.valign = "center";
+                  const s = _S(i, a),
+                    o = Math.round(s.map(t => (t._groups || t)[0][0].getBBox().height).reduce((t, e) => t + e));
+                  r.attr("height", o + 2 * AS.noteMargin),
+                    e.height += o + 2 * AS.noteMargin,
+                    DS.bumpVerticalPos(o + 2 * AS.noteMargin),
+                    e.stopy = e.starty + o + 2 * AS.noteMargin,
+                    e.stopx = e.startx + n.width,
+                    DS.insert(e.startx, e.starty, e.stopx, e.stopy),
+                    DS.models.addNote(e);
+                }(c, n);
+              break;
+            case i.db.LINETYPE.ACTIVE_START:
+              DS.newActivation(t, c, h);
+              break;
+            case i.db.LINETYPE.ACTIVE_END:
+              !function(t, e) {
+                const n = DS.endActivation(t);
+                n.starty + 18 > e && (n.starty = e - 6, e += 12),
+                  SS.drawActivation(c, n, e, AS, FS(t.from.actor).length),
+                  DS.insert(n.startx, e - 10, n.stopx, e);
+              }(t, DS.getVerticalPos());
+              break;
+            case i.db.LINETYPE.LOOP_START:
+              $S(g, t, AS.boxMargin, AS.boxMargin + AS.boxTextMargin, t => DS.newLoop(t));
+              break;
+            case i.db.LINETYPE.LOOP_END:
+              e = DS.endLoop(),
+                SS.drawLoop(c, e, "loop", AS),
+                DS.bumpVerticalPos(e.stopy - DS.getVerticalPos()),
+                DS.models.addLoop(e);
+              break;
+            case i.db.LINETYPE.RECT_START:
+              $S(g, t, AS.boxMargin, AS.boxMargin, t => DS.newLoop(void 0, t.message));
+              break;
+            case i.db.LINETYPE.RECT_END:
+              e = DS.endLoop(),
+                SS.drawBackgroundRect(c, e),
+                DS.models.addLoop(e),
+                DS.bumpVerticalPos(e.stopy - DS.getVerticalPos());
+              break;
+            case i.db.LINETYPE.OPT_START:
+              $S(g, t, AS.boxMargin, AS.boxMargin + AS.boxTextMargin, t => DS.newLoop(t));
+              break;
+            case i.db.LINETYPE.OPT_END:
+              e = DS.endLoop(),
+                SS.drawLoop(c, e, "opt", AS),
+                DS.bumpVerticalPos(e.stopy - DS.getVerticalPos()),
+                DS.models.addLoop(e);
+              break;
+            case i.db.LINETYPE.ALT_START:
+              $S(g, t, AS.boxMargin, AS.boxMargin + AS.boxTextMargin, t => DS.newLoop(t));
+              break;
+            case i.db.LINETYPE.ALT_ELSE:
+              $S(g, t, AS.boxMargin + AS.boxTextMargin, AS.boxMargin, t => DS.addSectionToLoop(t));
+              break;
+            case i.db.LINETYPE.ALT_END:
+              e = DS.endLoop(),
+                SS.drawLoop(c, e, "alt", AS),
+                DS.bumpVerticalPos(e.stopy - DS.getVerticalPos()),
+                DS.models.addLoop(e);
+              break;
+            case i.db.LINETYPE.PAR_START:
+              $S(g, t, AS.boxMargin, AS.boxMargin + AS.boxTextMargin, t => DS.newLoop(t));
+              break;
+            case i.db.LINETYPE.PAR_AND:
+              $S(g, t, AS.boxMargin + AS.boxTextMargin, AS.boxMargin, t => DS.addSectionToLoop(t));
+              break;
+            case i.db.LINETYPE.PAR_END:
+              e = DS.endLoop(),
+                SS.drawLoop(c, e, "par", AS),
+                DS.bumpVerticalPos(e.stopy - DS.getVerticalPos()),
+                DS.models.addLoop(e);
+              break;
+            case i.db.LINETYPE.AUTONUMBER:
+              y = t.message.start || y,
+                m = t.message.step || m,
+                t.message.visible ? i.db.enableSequenceNumbers() : i.db.disableSequenceNumbers();
+              break;
+            case i.db.LINETYPE.CRITICAL_START:
+              $S(g, t, AS.boxMargin, AS.boxMargin + AS.boxTextMargin, t => DS.newLoop(t));
+              break;
+            case i.db.LINETYPE.CRITICAL_OPTION:
+              $S(g, t, AS.boxMargin + AS.boxTextMargin, AS.boxMargin, t => DS.addSectionToLoop(t));
+              break;
+            case i.db.LINETYPE.CRITICAL_END:
+              e = DS.endLoop(),
+                SS.drawLoop(c, e, "critical", AS),
+                DS.bumpVerticalPos(e.stopy - DS.getVerticalPos()),
+                DS.models.addLoop(e);
+              break;
+            case i.db.LINETYPE.BREAK_START:
+              $S(g, t, AS.boxMargin, AS.boxMargin + AS.boxTextMargin, t => DS.newLoop(t));
+              break;
+            case i.db.LINETYPE.BREAK_END:
+              e = DS.endLoop(),
+                SS.drawLoop(c, e, "break", AS),
+                DS.bumpVerticalPos(e.stopy - DS.getVerticalPos()),
+                DS.models.addLoop(e);
+              break;
+            default:
+              try {
+                r = t.msgModel,
+                  r.starty = DS.getVerticalPos(),
+                  r.sequenceIndex = y,
+                  r.sequenceVisible = i.db.showSequenceNumbers();
+                const e = function(t, e) {
+                  DS.bumpVerticalPos(10);
+                  const { startx: n, stopx: i, message: r } = e,
+                    a = ub.splitBreaks(r).length,
+                    s = Dx.calculateTextDimensions(r, LS(AS)),
+                    o = s.height / a;
+                  let l;
+                  e.height += o, DS.bumpVerticalPos(o);
+                  let c = s.height - 10;
+                  const h = s.width;
+                  if (n === i) {
+                    l = DS.getVerticalPos() + c,
+                      AS.rightAngles || (c += AS.boxMargin, l = DS.getVerticalPos() + c),
+                      c += 30;
+                    const t = Math.max(h / 2, AS.width / 2);
+                    DS.insert(n - t, DS.getVerticalPos() - 10 + c, i + t, DS.getVerticalPos() + 30 + c);
+                  } else c += AS.boxMargin, l = DS.getVerticalPos() + c, DS.insert(n, l - 10, i, l);
+                  return DS.bumpVerticalPos(c),
+                    e.height += c,
+                    e.stopy = e.starty + e.height,
+                    DS.insert(e.fromBounds, e.starty, e.toBounds, e.stopy),
+                    l;
+                }(0, r);
+                b.push({ messageModel: r, lineStartY: e }), DS.models.addMessage(r);
+              } catch (t) {
+                tb.error("error while drawing message", t);
+              }
+          }
+          [
+            i.db.LINETYPE.SOLID_OPEN,
+            i.db.LINETYPE.DOTTED_OPEN,
+            i.db.LINETYPE.SOLID,
+            i.db.LINETYPE.DOTTED,
+            i.db.LINETYPE.SOLID_CROSS,
+            i.db.LINETYPE.DOTTED_CROSS,
+            i.db.LINETYPE.SOLID_POINT,
+            i.db.LINETYPE.DOTTED_POINT,
+          ].includes(t.type) && (y += m);
+        }),
+          b.forEach(t =>
+            function(t, e, n, i) {
+              const { startx: r, stopx: a, starty: s, message: o, type: l, sequenceIndex: c, sequenceVisible: h } = e,
+                u = Dx.calculateTextDimensions(o, LS(AS)),
+                d = SS.getTextObj();
+              d.x = r,
+                d.y = s + 10,
+                d.width = a - r,
+                d.class = "messageText",
+                d.dy = "1em",
+                d.text = o,
+                d.fontFamily = AS.messageFontFamily,
+                d.fontSize = AS.messageFontSize,
+                d.fontWeight = AS.messageFontWeight,
+                d.anchor = AS.messageAlign,
+                d.valign = "center",
+                d.textMargin = AS.wrapPadding,
+                d.tspan = !1,
+                _S(t, d);
+              const p = u.width;
+              let f;
+              r === a
+                ? f = AS.rightAngles
+                  ? t.append("path").attr("d", `M  ${r},${n} H ${r + Math.max(AS.width / 2, p / 2)} V ${n + 25} H ${r}`)
+                  : t.append("path").attr(
+                    "d",
+                    "M " + r + "," + n + " C " + (r + 60) + "," + (n - 10) + " " + (r + 60) + "," + (n + 30) + " " + r
+                      + "," + (n + 20),
+                  )
+                : (f = t.append("line"), f.attr("x1", r), f.attr("y1", n), f.attr("x2", a), f.attr("y2", n)),
+                l === i.db.LINETYPE.DOTTED || l === i.db.LINETYPE.DOTTED_CROSS || l === i.db.LINETYPE.DOTTED_POINT
+                  || l === i.db.LINETYPE.DOTTED_OPEN
+                  ? (f.style("stroke-dasharray", "3, 3"), f.attr("class", "messageLine1"))
+                  : f.attr("class", "messageLine0");
+              let g = "";
+              AS.arrowMarkerAbsolute
+              && (g = window.location.protocol + "//" + window.location.host + window.location.pathname
+                + window.location.search,
+                g = g.replace(/\(/g, "\\("),
+                g = g.replace(/\)/g, "\\)")),
+                f.attr("stroke-width", 2),
+                f.attr("stroke", "none"),
+                f.style("fill", "none"),
+                l !== i.db.LINETYPE.SOLID && l !== i.db.LINETYPE.DOTTED
+                || f.attr("marker-end", "url(" + g + "#arrowhead)"),
+                l !== i.db.LINETYPE.SOLID_POINT && l !== i.db.LINETYPE.DOTTED_POINT
+                || f.attr("marker-end", "url(" + g + "#filled-head)"),
+                l !== i.db.LINETYPE.SOLID_CROSS && l !== i.db.LINETYPE.DOTTED_CROSS
+                || f.attr("marker-end", "url(" + g + "#crosshead)"),
+                (h || AS.showSequenceNumbers)
+                && (f.attr("marker-start", "url(" + g + "#sequencenumber)"),
+                  t.append("text").attr("x", r).attr("y", n + 4).attr("font-family", "sans-serif").attr(
+                    "font-size",
+                    "12px",
+                  ).attr("text-anchor", "middle").attr("class", "sequenceNumber").text(c));
+            }(c, t.messageModel, t.lineStartY, i)
+          ),
+          AS.mirrorActors
+          && (DS.bumpVerticalPos(2 * AS.boxMargin),
+            MS(c, h, u, DS.getVerticalPos(), AS, d),
+            DS.bumpVerticalPos(AS.boxMargin),
+            kS(c, DS.getVerticalPos()));
+        const _ = BS(c, h, u, l), { bounds: x } = DS.getBounds();
+        tb.debug("For line height fix Querying: #" + e + " .actor-line");
+        re("#" + e + " .actor-line").attr("y2", x.stopy);
+        let v = x.stopy - x.starty;
+        v < _.maxHeight && (v = _.maxHeight);
+        let k = v + 2 * AS.diagramMarginY;
+        AS.mirrorActors && (k = k - AS.boxMargin + AS.bottomMarginAdj);
+        let w = x.stopx - x.startx;
+        w < _.maxWidth && (w = _.maxWidth);
+        const T = w + 2 * AS.diagramMarginX;
+        p && c.append("text").text(p).attr("x", (x.stopx - x.startx) / 2 - 2 * AS.diagramMarginX).attr("y", -25),
+          Gx(c, k, T, AS.useMaxWidth);
+        const C = p ? 40 : 0;
+        c.attr("viewBox", x.startx - AS.diagramMarginX + " -" + (AS.diagramMarginY + C) + " " + T + " " + (k + C)),
+          tb.debug("models:", DS.models);
+      },
+    };
+  var zS = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [1, 2],
+      i = [1, 3],
+      r = [1, 5],
+      a = [1, 7],
+      s = [2, 5],
+      o = [1, 15],
+      l = [1, 17],
+      c = [1, 21],
+      h = [1, 22],
+      u = [1, 23],
+      d = [1, 24],
+      p = [1, 37],
+      f = [1, 25],
+      g = [1, 26],
+      y = [1, 27],
+      m = [1, 28],
+      b = [1, 29],
+      _ = [1, 32],
+      x = [1, 33],
+      v = [1, 34],
+      k = [1, 35],
+      w = [1, 36],
+      T = [1, 39],
+      C = [1, 40],
+      E = [1, 41],
+      S = [1, 42],
+      A = [1, 38],
+      D = [1, 45],
+      L = [1, 4, 5, 16, 17, 19, 21, 22, 24, 25, 26, 27, 28, 29, 33, 35, 37, 38, 42, 50, 51, 52, 53, 56, 60],
+      O = [1, 4, 5, 14, 15, 16, 17, 19, 21, 22, 24, 25, 26, 27, 28, 29, 33, 35, 37, 38, 42, 50, 51, 52, 53, 56, 60],
+      N = [1, 4, 5, 7, 16, 17, 19, 21, 22, 24, 25, 26, 27, 28, 29, 33, 35, 37, 38, 42, 50, 51, 52, 53, 56, 60],
+      M = [4, 5, 16, 17, 19, 21, 22, 24, 25, 26, 27, 28, 29, 33, 35, 37, 38, 42, 50, 51, 52, 53, 56, 60],
+      B = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          SPACE: 4,
+          NL: 5,
+          directive: 6,
+          SD: 7,
+          document: 8,
+          line: 9,
+          statement: 10,
+          classDefStatement: 11,
+          cssClassStatement: 12,
+          idStatement: 13,
+          DESCR: 14,
+          "--\x3e": 15,
+          HIDE_EMPTY: 16,
+          scale: 17,
+          WIDTH: 18,
+          COMPOSIT_STATE: 19,
+          STRUCT_START: 20,
+          STRUCT_STOP: 21,
+          STATE_DESCR: 22,
+          AS: 23,
+          ID: 24,
+          FORK: 25,
+          JOIN: 26,
+          CHOICE: 27,
+          CONCURRENT: 28,
+          note: 29,
+          notePosition: 30,
+          NOTE_TEXT: 31,
+          direction: 32,
+          acc_title: 33,
+          acc_title_value: 34,
+          acc_descr: 35,
+          acc_descr_value: 36,
+          acc_descr_multiline_value: 37,
+          classDef: 38,
+          CLASSDEF_ID: 39,
+          CLASSDEF_STYLEOPTS: 40,
+          DEFAULT: 41,
+          class: 42,
+          CLASSENTITY_IDS: 43,
+          STYLECLASS: 44,
+          openDirective: 45,
+          typeDirective: 46,
+          closeDirective: 47,
+          ":": 48,
+          argDirective: 49,
+          direction_tb: 50,
+          direction_bt: 51,
+          direction_rl: 52,
+          direction_lr: 53,
+          eol: 54,
+          ";": 55,
+          EDGE_STATE: 56,
+          STYLE_SEPARATOR: 57,
+          left_of: 58,
+          right_of: 59,
+          open_directive: 60,
+          type_directive: 61,
+          arg_directive: 62,
+          close_directive: 63,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: {
+          2: "error",
+          4: "SPACE",
+          5: "NL",
+          7: "SD",
+          14: "DESCR",
+          15: "--\x3e",
+          16: "HIDE_EMPTY",
+          17: "scale",
+          18: "WIDTH",
+          19: "COMPOSIT_STATE",
+          20: "STRUCT_START",
+          21: "STRUCT_STOP",
+          22: "STATE_DESCR",
+          23: "AS",
+          24: "ID",
+          25: "FORK",
+          26: "JOIN",
+          27: "CHOICE",
+          28: "CONCURRENT",
+          29: "note",
+          31: "NOTE_TEXT",
+          33: "acc_title",
+          34: "acc_title_value",
+          35: "acc_descr",
+          36: "acc_descr_value",
+          37: "acc_descr_multiline_value",
+          38: "classDef",
+          39: "CLASSDEF_ID",
+          40: "CLASSDEF_STYLEOPTS",
+          41: "DEFAULT",
+          42: "class",
+          43: "CLASSENTITY_IDS",
+          44: "STYLECLASS",
+          48: ":",
+          50: "direction_tb",
+          51: "direction_bt",
+          52: "direction_rl",
+          53: "direction_lr",
+          55: ";",
+          56: "EDGE_STATE",
+          57: "STYLE_SEPARATOR",
+          58: "left_of",
+          59: "right_of",
+          60: "open_directive",
+          61: "type_directive",
+          62: "arg_directive",
+          63: "close_directive",
+        },
+        productions_: [
+          0,
+          [3, 2],
+          [3, 2],
+          [3, 2],
+          [3, 2],
+          [8, 0],
+          [8, 2],
+          [9, 2],
+          [9, 1],
+          [9, 1],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 2],
+          [10, 3],
+          [10, 4],
+          [10, 1],
+          [10, 2],
+          [10, 1],
+          [10, 4],
+          [10, 3],
+          [10, 6],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 1],
+          [10, 4],
+          [10, 4],
+          [10, 1],
+          [10, 1],
+          [10, 2],
+          [10, 2],
+          [10, 1],
+          [11, 3],
+          [11, 3],
+          [12, 3],
+          [6, 3],
+          [6, 5],
+          [32, 1],
+          [32, 1],
+          [32, 1],
+          [32, 1],
+          [54, 1],
+          [54, 1],
+          [13, 1],
+          [13, 1],
+          [13, 3],
+          [13, 3],
+          [30, 1],
+          [30, 1],
+          [45, 1],
+          [46, 1],
+          [49, 1],
+          [47, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 4:
+              return i.setRootDoc(a[o]), a[o];
+            case 5:
+              this.$ = [];
+              break;
+            case 6:
+              "nl" != a[o] && (a[o - 1].push(a[o]), this.$ = a[o - 1]);
+              break;
+            case 7:
+            case 8:
+            case 12:
+              this.$ = a[o];
+              break;
+            case 9:
+              this.$ = "nl";
+              break;
+            case 13:
+              const t = a[o - 1];
+              t.description = i.trimColon(a[o]), this.$ = t;
+              break;
+            case 14:
+              this.$ = { stmt: "relation", state1: a[o - 2], state2: a[o] };
+              break;
+            case 15:
+              const e = i.trimColon(a[o]);
+              this.$ = { stmt: "relation", state1: a[o - 3], state2: a[o - 1], description: e };
+              break;
+            case 19:
+              this.$ = { stmt: "state", id: a[o - 3], type: "default", description: "", doc: a[o - 1] };
+              break;
+            case 20:
+              var l = a[o], c = a[o - 2].trim();
+              if (a[o].match(":")) {
+                var h = a[o].split(":");
+                l = h[0], c = [c, h[1]];
+              }
+              this.$ = { stmt: "state", id: l, type: "default", description: c };
+              break;
+            case 21:
+              this.$ = { stmt: "state", id: a[o - 3], type: "default", description: a[o - 5], doc: a[o - 1] };
+              break;
+            case 22:
+              this.$ = { stmt: "state", id: a[o], type: "fork" };
+              break;
+            case 23:
+              this.$ = { stmt: "state", id: a[o], type: "join" };
+              break;
+            case 24:
+              this.$ = { stmt: "state", id: a[o], type: "choice" };
+              break;
+            case 25:
+              this.$ = { stmt: "state", id: i.getDividerId(), type: "divider" };
+              break;
+            case 26:
+              this.$ = { stmt: "state", id: a[o - 1].trim(), note: { position: a[o - 2].trim(), text: a[o].trim() } };
+              break;
+            case 30:
+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 31:
+            case 32:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 33:
+            case 34:
+              this.$ = { stmt: "classDef", id: a[o - 1].trim(), classes: a[o].trim() };
+              break;
+            case 35:
+              this.$ = { stmt: "applyClass", id: a[o - 1].trim(), styleClass: a[o].trim() };
+              break;
+            case 38:
+              i.setDirection("TB"), this.$ = { stmt: "dir", value: "TB" };
+              break;
+            case 39:
+              i.setDirection("BT"), this.$ = { stmt: "dir", value: "BT" };
+              break;
+            case 40:
+              i.setDirection("RL"), this.$ = { stmt: "dir", value: "RL" };
+              break;
+            case 41:
+              i.setDirection("LR"), this.$ = { stmt: "dir", value: "LR" };
+              break;
+            case 44:
+            case 45:
+              this.$ = { stmt: "state", id: a[o].trim(), type: "default", description: "" };
+              break;
+            case 46:
+            case 47:
+              this.$ = { stmt: "state", id: a[o - 2].trim(), classes: [a[o].trim()], type: "default", description: "" };
+              break;
+            case 50:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 51:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 52:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 53:
+              i.parseDirective("}%%", "close_directive", "state");
+          }
+        },
+        table: [
+          { 3: 1, 4: n, 5: i, 6: 4, 7: r, 45: 6, 60: a },
+          { 1: [3] },
+          { 3: 8, 4: n, 5: i, 6: 4, 7: r, 45: 6, 60: a },
+          { 3: 9, 4: n, 5: i, 6: 4, 7: r, 45: 6, 60: a },
+          { 3: 10, 4: n, 5: i, 6: 4, 7: r, 45: 6, 60: a },
+          e([1, 4, 5, 16, 17, 19, 22, 24, 25, 26, 27, 28, 29, 33, 35, 37, 38, 42, 50, 51, 52, 53, 56, 60], s, {
+            8: 11,
+          }),
+          { 46: 12, 61: [1, 13] },
+          { 61: [2, 50] },
+          { 1: [2, 1] },
+          { 1: [2, 2] },
+          { 1: [2, 3] },
+          {
+            1: [2, 4],
+            4: o,
+            5: l,
+            6: 30,
+            9: 14,
+            10: 16,
+            11: 18,
+            12: 19,
+            13: 20,
+            16: c,
+            17: h,
+            19: u,
+            22: d,
+            24: p,
+            25: f,
+            26: g,
+            27: y,
+            28: m,
+            29: b,
+            32: 31,
+            33: _,
+            35: x,
+            37: v,
+            38: k,
+            42: w,
+            45: 6,
+            50: T,
+            51: C,
+            52: E,
+            53: S,
+            56: A,
+            60: a,
+          },
+          { 47: 43, 48: [1, 44], 63: D },
+          e([48, 63], [2, 51]),
+          e(L, [2, 6]),
+          {
+            6: 30,
+            10: 46,
+            11: 18,
+            12: 19,
+            13: 20,
+            16: c,
+            17: h,
+            19: u,
+            22: d,
+            24: p,
+            25: f,
+            26: g,
+            27: y,
+            28: m,
+            29: b,
+            32: 31,
+            33: _,
+            35: x,
+            37: v,
+            38: k,
+            42: w,
+            45: 6,
+            50: T,
+            51: C,
+            52: E,
+            53: S,
+            56: A,
+            60: a,
+          },
+          e(L, [2, 8]),
+          e(L, [2, 9]),
+          e(L, [2, 10]),
+          e(L, [2, 11]),
+          e(L, [2, 12], { 14: [1, 47], 15: [1, 48] }),
+          e(L, [2, 16]),
+          { 18: [1, 49] },
+          e(L, [2, 18], { 20: [1, 50] }),
+          { 23: [1, 51] },
+          e(L, [2, 22]),
+          e(L, [2, 23]),
+          e(L, [2, 24]),
+          e(L, [2, 25]),
+          { 30: 52, 31: [1, 53], 58: [1, 54], 59: [1, 55] },
+          e(L, [2, 28]),
+          e(L, [2, 29]),
+          { 34: [1, 56] },
+          { 36: [1, 57] },
+          e(L, [2, 32]),
+          { 39: [1, 58], 41: [1, 59] },
+          { 43: [1, 60] },
+          e(O, [2, 44], { 57: [1, 61] }),
+          e(O, [2, 45], { 57: [1, 62] }),
+          e(L, [2, 38]),
+          e(L, [2, 39]),
+          e(L, [2, 40]),
+          e(L, [2, 41]),
+          e(N, [2, 36]),
+          { 49: 63, 62: [1, 64] },
+          e(N, [2, 53]),
+          e(L, [2, 7]),
+          e(L, [2, 13]),
+          { 13: 65, 24: p, 56: A },
+          e(L, [2, 17]),
+          e(M, s, { 8: 66 }),
+          { 24: [1, 67] },
+          { 24: [1, 68] },
+          { 23: [1, 69] },
+          { 24: [2, 48] },
+          { 24: [2, 49] },
+          e(L, [2, 30]),
+          e(L, [2, 31]),
+          { 40: [1, 70] },
+          { 40: [1, 71] },
+          { 44: [1, 72] },
+          { 24: [1, 73] },
+          { 24: [1, 74] },
+          { 47: 75, 63: D },
+          { 63: [2, 52] },
+          e(L, [2, 14], { 14: [1, 76] }),
+          {
+            4: o,
+            5: l,
+            6: 30,
+            9: 14,
+            10: 16,
+            11: 18,
+            12: 19,
+            13: 20,
+            16: c,
+            17: h,
+            19: u,
+            21: [1, 77],
+            22: d,
+            24: p,
+            25: f,
+            26: g,
+            27: y,
+            28: m,
+            29: b,
+            32: 31,
+            33: _,
+            35: x,
+            37: v,
+            38: k,
+            42: w,
+            45: 6,
+            50: T,
+            51: C,
+            52: E,
+            53: S,
+            56: A,
+            60: a,
+          },
+          e(L, [2, 20], { 20: [1, 78] }),
+          { 31: [1, 79] },
+          { 24: [1, 80] },
+          e(L, [2, 33]),
+          e(L, [2, 34]),
+          e(L, [2, 35]),
+          e(O, [2, 46]),
+          e(O, [2, 47]),
+          e(N, [2, 37]),
+          e(L, [2, 15]),
+          e(L, [2, 19]),
+          e(M, s, { 8: 81 }),
+          e(L, [2, 26]),
+          e(L, [2, 27]),
+          {
+            4: o,
+            5: l,
+            6: 30,
+            9: 14,
+            10: 16,
+            11: 18,
+            12: 19,
+            13: 20,
+            16: c,
+            17: h,
+            19: u,
+            21: [1, 82],
+            22: d,
+            24: p,
+            25: f,
+            26: g,
+            27: y,
+            28: m,
+            29: b,
+            32: 31,
+            33: _,
+            35: x,
+            37: v,
+            38: k,
+            42: w,
+            45: 6,
+            50: T,
+            51: C,
+            52: E,
+            53: S,
+            56: A,
+            60: a,
+          },
+          e(L, [2, 21]),
+        ],
+        defaultActions: { 7: [2, 50], 8: [2, 1], 9: [2, 2], 10: [2, 3], 54: [2, 48], 55: [2, 49], 64: [2, 52] },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      I = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: { "case-insensitive": !0 },
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return 41;
+            case 1:
+            case 44:
+              return 50;
+            case 2:
+            case 45:
+              return 51;
+            case 3:
+            case 46:
+              return 52;
+            case 4:
+            case 47:
+              return 53;
+            case 5:
+              return this.begin("open_directive"), 60;
+            case 6:
+              return this.begin("type_directive"), 61;
+            case 7:
+              return this.popState(), this.begin("arg_directive"), 48;
+            case 8:
+              return this.popState(), this.popState(), 63;
+            case 9:
+              return 62;
+            case 10:
+            case 11:
+            case 13:
+            case 14:
+            case 15:
+            case 16:
+            case 56:
+            case 58:
+            case 64:
+              break;
+            case 12:
+            case 79:
+              return 5;
+            case 17:
+            case 34:
+              return this.pushState("SCALE"), 17;
+            case 18:
+            case 35:
+              return 18;
+            case 19:
+            case 25:
+            case 36:
+            case 51:
+            case 54:
+              this.popState();
+              break;
+            case 20:
+              return this.begin("acc_title"), 33;
+            case 21:
+              return this.popState(), "acc_title_value";
+            case 22:
+              return this.begin("acc_descr"), 35;
+            case 23:
+              return this.popState(), "acc_descr_value";
+            case 24:
+              this.begin("acc_descr_multiline");
+              break;
+            case 26:
+              return "acc_descr_multiline_value";
+            case 27:
+              return this.pushState("CLASSDEF"), 38;
+            case 28:
+              return this.popState(), this.pushState("CLASSDEFID"), "DEFAULT_CLASSDEF_ID";
+            case 29:
+              return this.popState(), this.pushState("CLASSDEFID"), 39;
+            case 30:
+              return this.popState(), 40;
+            case 31:
+              return this.pushState("CLASS"), 42;
+            case 32:
+              return this.popState(), this.pushState("CLASS_STYLE"), 43;
+            case 33:
+              return this.popState(), 44;
+            case 37:
+              this.pushState("STATE");
+              break;
+            case 38:
+            case 41:
+              return this.popState(), e.yytext = e.yytext.slice(0, -8).trim(), 25;
+            case 39:
+            case 42:
+              return this.popState(), e.yytext = e.yytext.slice(0, -8).trim(), 26;
+            case 40:
+            case 43:
+              return this.popState(), e.yytext = e.yytext.slice(0, -10).trim(), 27;
+            case 48:
+              this.begin("STATE_STRING");
+              break;
+            case 49:
+              return this.popState(), this.pushState("STATE_ID"), "AS";
+            case 50:
+            case 66:
+              return this.popState(), "ID";
+            case 52:
+              return "STATE_DESCR";
+            case 53:
+              return 19;
+            case 55:
+              return this.popState(), this.pushState("struct"), 20;
+            case 57:
+              return this.popState(), 21;
+            case 59:
+              return this.begin("NOTE"), 29;
+            case 60:
+              return this.popState(), this.pushState("NOTE_ID"), 58;
+            case 61:
+              return this.popState(), this.pushState("NOTE_ID"), 59;
+            case 62:
+              this.popState(), this.pushState("FLOATING_NOTE");
+              break;
+            case 63:
+              return this.popState(), this.pushState("FLOATING_NOTE_ID"), "AS";
+            case 65:
+              return "NOTE_TEXT";
+            case 67:
+              return this.popState(), this.pushState("NOTE_TEXT"), 24;
+            case 68:
+              return this.popState(), e.yytext = e.yytext.substr(2).trim(), 31;
+            case 69:
+              return this.popState(), e.yytext = e.yytext.slice(0, -8).trim(), 31;
+            case 70:
+            case 71:
+              return 7;
+            case 72:
+              return 16;
+            case 73:
+              return 56;
+            case 74:
+              return 24;
+            case 75:
+              return e.yytext = e.yytext.trim(), 14;
+            case 76:
+              return 15;
+            case 77:
+              return 28;
+            case 78:
+              return 57;
+            case 80:
+              return "INVALID";
+          }
+        },
+        rules: [
+          /^(?:default\b)/i,
+          /^(?:.*direction\s+TB[^\n]*)/i,
+          /^(?:.*direction\s+BT[^\n]*)/i,
+          /^(?:.*direction\s+RL[^\n]*)/i,
+          /^(?:.*direction\s+LR[^\n]*)/i,
+          /^(?:%%\{)/i,
+          /^(?:((?:(?!\}%%)[^:.])*))/i,
+          /^(?::)/i,
+          /^(?:\}%%)/i,
+          /^(?:((?:(?!\}%%).|\n)*))/i,
+          /^(?:%%(?!\{)[^\n]*)/i,
+          /^(?:[^\}]%%[^\n]*)/i,
+          /^(?:[\n]+)/i,
+          /^(?:[\s]+)/i,
+          /^(?:((?!\n)\s)+)/i,
+          /^(?:#[^\n]*)/i,
+          /^(?:%[^\n]*)/i,
+          /^(?:scale\s+)/i,
+          /^(?:\d+)/i,
+          /^(?:\s+width\b)/i,
+          /^(?:accTitle\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*\{\s*)/i,
+          /^(?:[\}])/i,
+          /^(?:[^\}]*)/i,
+          /^(?:classDef\s+)/i,
+          /^(?:DEFAULT\s+)/i,
+          /^(?:\w+\s+)/i,
+          /^(?:[^\n]*)/i,
+          /^(?:class\s+)/i,
+          /^(?:(\w+)+((,\s*\w+)*))/i,
+          /^(?:[^\n]*)/i,
+          /^(?:scale\s+)/i,
+          /^(?:\d+)/i,
+          /^(?:\s+width\b)/i,
+          /^(?:state\s+)/i,
+          /^(?:.*<<fork>>)/i,
+          /^(?:.*<<join>>)/i,
+          /^(?:.*<<choice>>)/i,
+          /^(?:.*\[\[fork\]\])/i,
+          /^(?:.*\[\[join\]\])/i,
+          /^(?:.*\[\[choice\]\])/i,
+          /^(?:.*direction\s+TB[^\n]*)/i,
+          /^(?:.*direction\s+BT[^\n]*)/i,
+          /^(?:.*direction\s+RL[^\n]*)/i,
+          /^(?:.*direction\s+LR[^\n]*)/i,
+          /^(?:["])/i,
+          /^(?:\s*as\s+)/i,
+          /^(?:[^\n\{]*)/i,
+          /^(?:["])/i,
+          /^(?:[^"]*)/i,
+          /^(?:[^\n\s\{]+)/i,
+          /^(?:\n)/i,
+          /^(?:\{)/i,
+          /^(?:%%(?!\{)[^\n]*)/i,
+          /^(?:\})/i,
+          /^(?:[\n])/i,
+          /^(?:note\s+)/i,
+          /^(?:left of\b)/i,
+          /^(?:right of\b)/i,
+          /^(?:")/i,
+          /^(?:\s*as\s*)/i,
+          /^(?:["])/i,
+          /^(?:[^"]*)/i,
+          /^(?:[^\n]*)/i,
+          /^(?:\s*[^:\n\s\-]+)/i,
+          /^(?:\s*:[^:\n;]+)/i,
+          /^(?:[\s\S]*?end note\b)/i,
+          /^(?:stateDiagram\s+)/i,
+          /^(?:stateDiagram-v2\s+)/i,
+          /^(?:hide empty description\b)/i,
+          /^(?:\[\*\])/i,
+          /^(?:[^:\n\s\-\{]+)/i,
+          /^(?:\s*:[^:\n;]+)/i,
+          /^(?:-->)/i,
+          /^(?:--)/i,
+          /^(?::::)/i,
+          /^(?:$)/i,
+          /^(?:.)/i,
+        ],
+        conditions: {
+          LINE: { rules: [14, 15], inclusive: !1 },
+          close_directive: { rules: [14, 15], inclusive: !1 },
+          arg_directive: { rules: [8, 9, 14, 15], inclusive: !1 },
+          type_directive: { rules: [7, 8, 14, 15], inclusive: !1 },
+          open_directive: { rules: [6, 14, 15], inclusive: !1 },
+          struct: { rules: [14, 15, 27, 31, 37, 44, 45, 46, 47, 56, 57, 58, 59, 73, 74, 75, 76, 77], inclusive: !1 },
+          FLOATING_NOTE_ID: { rules: [66], inclusive: !1 },
+          FLOATING_NOTE: { rules: [63, 64, 65], inclusive: !1 },
+          NOTE_TEXT: { rules: [68, 69], inclusive: !1 },
+          NOTE_ID: { rules: [67], inclusive: !1 },
+          NOTE: { rules: [60, 61, 62], inclusive: !1 },
+          CLASS_STYLE: { rules: [33], inclusive: !1 },
+          CLASS: { rules: [32], inclusive: !1 },
+          CLASSDEFID: { rules: [30], inclusive: !1 },
+          CLASSDEF: { rules: [28, 29], inclusive: !1 },
+          acc_descr_multiline: { rules: [25, 26], inclusive: !1 },
+          acc_descr: { rules: [23], inclusive: !1 },
+          acc_title: { rules: [21], inclusive: !1 },
+          SCALE: { rules: [18, 19, 35, 36], inclusive: !1 },
+          ALIAS: { rules: [], inclusive: !1 },
+          STATE_ID: { rules: [50], inclusive: !1 },
+          STATE_STRING: { rules: [51, 52], inclusive: !1 },
+          FORK_STATE: { rules: [], inclusive: !1 },
+          STATE: { rules: [14, 15, 38, 39, 40, 41, 42, 43, 48, 49, 53, 54, 55], inclusive: !1 },
+          ID: { rules: [14, 15], inclusive: !1 },
+          INITIAL: {
+            rules: [
+              0,
+              1,
+              2,
+              3,
+              4,
+              5,
+              10,
+              11,
+              12,
+              13,
+              15,
+              16,
+              17,
+              20,
+              22,
+              24,
+              27,
+              31,
+              34,
+              37,
+              55,
+              59,
+              70,
+              71,
+              72,
+              73,
+              74,
+              75,
+              76,
+              78,
+              79,
+              80,
+            ],
+            inclusive: !0,
+          },
+        },
+      },
+        t);
+    function F() {
+      this.yy = {};
+    }
+    return B.lexer = I, F.prototype = B, B.Parser = F, new F();
+  }();
+  zS.parser = zS;
+  const US = zS,
+    WS = (t, e) => {
+      var n;
+      return "dagre-wrapper" !== (null == (n = null == e ? void 0 : e.state) ? void 0 : n.defaultRenderer)
+        && null !== t.match(/^\s*stateDiagram/);
+    },
+    HS = (t, e) => {
+      var n;
+      return null !== t.match(/^\s*stateDiagram-v2/)
+        || !(!t.match(/^\s*stateDiagram/)
+          || "dagre-wrapper" !== (null == (n = null == e ? void 0 : e.state) ? void 0 : n.defaultRenderer));
+    },
+    qS = "state",
+    VS = "relation",
+    GS = "default",
+    XS = "divider",
+    ZS = "[*]",
+    QS = "start",
+    KS = ZS,
+    JS = "end",
+    tA = "color",
+    eA = "fill";
+  let nA = "LR", iA = [], rA = {};
+  let aA = { root: { relations: [], states: {}, documents: {} } }, sA = aA.root, oA = 0, lA = 0;
+  const cA = t => JSON.parse(JSON.stringify(t)),
+    hA = (t, e, n) => {
+      if (e.stmt === VS) hA(t, e.state1, !0), hA(t, e.state2, !1);
+      else if (e.stmt === qS && "[*]" === e.id && (e.id = n ? t.id + "_start" : t.id + "_end", e.start = n), e.doc) {
+        const t = [];
+        let n, i = [];
+        for (n = 0; n < e.doc.length; n++) {
+          if (e.doc[n].type === XS) {
+            const r = cA(e.doc[n]);
+            r.doc = cA(i), t.push(r), i = [];
+          } else i.push(e.doc[n]);
+        }
+        if (t.length > 0 && i.length > 0) {
+          const n = { stmt: qS, id: mx(), type: "divider", doc: cA(i) };
+          t.push(cA(n)), e.doc = t;
+        }
+        e.doc.forEach(t => hA(e, t, !0));
+      }
+    },
+    uA = function(t, e = GS, n = null, i = null, r = null, a = null, s = null, o = null) {
+      if (
+        void 0 === sA.states[t]
+          ? (tb.info("Adding state ", t, i),
+            sA.states[t] = {
+              id: t,
+              descriptions: [],
+              type: e,
+              doc: n,
+              note: r,
+              classes: [],
+              styles: [],
+              textStyles: [],
+            })
+          : (sA.states[t].doc || (sA.states[t].doc = n), sA.states[t].type || (sA.states[t].type = e)),
+          i
+          && (tb.info("Setting state description", t, i),
+            "string" == typeof i && mA(t, i.trim()),
+            "object" == typeof i && i.forEach(e => mA(t, e.trim()))),
+          r && (sA.states[t].note = r, sA.states[t].note.text = ub.sanitizeText(sA.states[t].note.text, jx())),
+          a
+      ) {
+        tb.info("Setting state classes", t, a);
+        ("string" == typeof a ? [a] : a).forEach(e => _A(t, e.trim()));
+      }
+      if (s) {
+        tb.info("Setting state styles", t, s);
+        ("string" == typeof s ? [s] : s).forEach(e => xA(t, e.trim()));
+      }
+      if (o) {
+        tb.info("Setting state styles", t, s);
+        ("string" == typeof o ? [o] : o).forEach(e => vA(t, e.trim()));
+      }
+    },
+    dA = function(t) {
+      aA = { root: { relations: [], states: {}, documents: {} } }, sA = aA.root, oA = 0, rA = {}, t || Cv();
+    },
+    pA = function(t) {
+      return sA.states[t];
+    };
+  function fA(t = "") {
+    let e = t;
+    return t === ZS && (oA++, e = `${QS}${oA}`), e;
+  }
+  function gA(t = "", e = GS) {
+    return t === ZS ? QS : e;
+  }
+  const yA = function(t, e, n) {
+      if ("object" == typeof t) {
+        !function(t, e, n) {
+          let i = fA(t.id), r = gA(t.id, t.type), a = fA(e.id), s = gA(e.id, e.type);
+          uA(i, r, t.doc, t.description, t.note, t.classes, t.styles, t.textStyles),
+            uA(a, s, e.doc, e.description, e.note, e.classes, e.styles, e.textStyles),
+            sA.relations.push({ id1: i, id2: a, relationTitle: ub.sanitizeText(n, jx()) });
+        }(t, e, n);
+      } else {
+        const i = fA(t),
+          r = gA(t),
+          a = function(t = "") {
+            let e = t;
+            return t === KS && (oA++, e = `${JS}${oA}`), e;
+          }(e),
+          s = function(t = "", e = GS) {
+            return t === KS ? JS : e;
+          }(e);
+        uA(i, r), uA(a, s), sA.relations.push({ id1: i, id2: a, title: ub.sanitizeText(n, jx()) });
+      }
+    },
+    mA = function(t, e) {
+      const n = sA.states[t], i = e.startsWith(":") ? e.replace(":", "").trim() : e;
+      n.descriptions.push(ub.sanitizeText(i, jx()));
+    },
+    bA = function(t, e = "") {
+      void 0 === rA[t] && (rA[t] = { id: t, styles: [], textStyles: [] });
+      const n = rA[t];
+      null != e && e.split(",").forEach(t => {
+        const e = t.replace(/([^;]*);/, "$1").trim();
+        if (t.match(tA)) {
+          const t = e.replace(eA, "bgFill").replace(tA, eA);
+          n.textStyles.push(t);
+        }
+        n.styles.push(e);
+      });
+    },
+    _A = function(t, e) {
+      t.split(",").forEach(function(t) {
+        let n = pA(t);
+        if (void 0 === n) {
+          const e = t.trim();
+          uA(e), n = pA(e);
+        }
+        n.classes.push(e);
+      });
+    },
+    xA = function(t, e) {
+      const n = pA(t);
+      void 0 !== n && n.textStyles.push(e);
+    },
+    vA = function(t, e) {
+      const n = pA(t);
+      void 0 !== n && n.textStyles.push(e);
+    },
+    kA = {
+      parseDirective: function(t, e, n) {
+        nL.parseDirective(this, t, e, n);
+      },
+      getConfig: () => jx().state,
+      addState: uA,
+      clear: dA,
+      getState: pA,
+      getStates: function() {
+        return sA.states;
+      },
+      getRelations: function() {
+        return sA.relations;
+      },
+      getClasses: function() {
+        return rA;
+      },
+      getDirection: () => nA,
+      addRelation: yA,
+      getDividerId: () => (lA++, "divider-id-" + lA),
+      setDirection: t => {
+        nA = t;
+      },
+      cleanupLabel: function(t) {
+        return ":" === t.substring(0, 1) ? t.substr(2).trim() : t.trim();
+      },
+      lineType: { LINE: 0, DOTTED_LINE: 1 },
+      relationType: { AGGREGATION: 0, EXTENSION: 1, COMPOSITION: 2, DEPENDENCY: 3 },
+      logDocuments: function() {
+        tb.info("Documents = ", aA);
+      },
+      getRootDoc: () => iA,
+      setRootDoc: t => {
+        tb.info("Setting root doc", t), iA = t;
+      },
+      getRootDocV2: () => (hA({ id: "root" }, { id: "root", doc: iA }, !0), { id: "root", doc: iA }),
+      extract: t => {
+        let e;
+        e = t.doc ? t.doc : t,
+          tb.info(e),
+          dA(!0),
+          tb.info("Extract", e),
+          e.forEach(t => {
+            switch (t.stmt) {
+              case qS:
+                uA(t.id, t.type, t.doc, t.description, t.note, t.classes, t.styles, t.textStyles);
+                break;
+              case VS:
+                yA(t.state1, t.state2, t.description);
+                break;
+              case "classDef":
+                bA(t.id, t.classes);
+                break;
+              case "applyClass":
+                _A(t.id, t.styleClass);
+            }
+          });
+      },
+      trimColon: t => t && ":" === t[0] ? t.substr(1).trim() : t.trim(),
+      getAccTitle: Sv,
+      setAccTitle: Ev,
+      getAccDescription: Dv,
+      setAccDescription: Av,
+      addStyleClass: bA,
+      setCssClass: _A,
+      addDescription: mA,
+      setDiagramTitle: Lv,
+      getDiagramTitle: Ov,
+    },
+    wA = (t, e) => {
+      const n = t.append("text").attr("x", 2 * jx().state.padding).attr(
+          "y",
+          jx().state.textHeight + 1.3 * jx().state.padding,
+        ).attr("font-size", jx().state.fontSize).attr("class", "state-title").text(e.descriptions[0]).node().getBBox(),
+        i = n.height,
+        r = t.append("text").attr("x", jx().state.padding).attr(
+          "y",
+          i + .4 * jx().state.padding + jx().state.dividerMargin + jx().state.textHeight,
+        ).attr("class", "state-description");
+      let a = !0, s = !0;
+      e.descriptions.forEach(function(t) {
+        a || (!function(t, e, n) {
+          const i = t.append("tspan").attr("x", 2 * jx().state.padding).text(e);
+          n || i.attr("dy", jx().state.textHeight);
+        }(r, t, s),
+          s = !1), a = !1;
+      });
+      const o = t.append("line").attr("x1", jx().state.padding).attr(
+          "y1",
+          jx().state.padding + i + jx().state.dividerMargin / 2,
+        ).attr("y2", jx().state.padding + i + jx().state.dividerMargin / 2).attr("class", "descr-divider"),
+        l = r.node().getBBox(),
+        c = Math.max(l.width, n.width);
+      return o.attr("x2", c + 3 * jx().state.padding),
+        t.insert("rect", ":first-child").attr("x", jx().state.padding).attr("y", jx().state.padding).attr(
+          "width",
+          c + 2 * jx().state.padding,
+        ).attr("height", l.height + i + 2 * jx().state.padding).attr("rx", jx().state.radius),
+        t;
+    },
+    TA = (t, e, n) => {
+      const i = jx().state.padding,
+        r = 2 * jx().state.padding,
+        a = t.node().getBBox(),
+        s = a.width,
+        o = a.x,
+        l = t.append("text").attr("x", 0).attr("y", jx().state.titleShift).attr("font-size", jx().state.fontSize).attr(
+          "class",
+          "state-title",
+        ).text(e.id),
+        c = l.node().getBBox().width + r;
+      let h, u = Math.max(c, s);
+      u === s && (u += r);
+      const d = t.node().getBBox();
+      e.doc, h = o - i, c > s && (h = (s - u) / 2 + i), Math.abs(o - d.x) < i && c > s && (h = o - (c - s) / 2);
+      const p = 1 - jx().state.textHeight;
+      return t.insert("rect", ":first-child").attr("x", h).attr("y", p).attr("class", n ? "alt-composit" : "composit")
+        .attr("width", u).attr("height", d.height + jx().state.textHeight + jx().state.titleShift + 1).attr("rx", "0"),
+        l.attr("x", h + i),
+        c <= s && l.attr("x", o + (u - r) / 2 - c / 2 + i),
+        t.insert("rect", ":first-child").attr("x", h).attr(
+          "y",
+          jx().state.titleShift - jx().state.textHeight - jx().state.padding,
+        ).attr("width", u).attr("height", 3 * jx().state.textHeight).attr("rx", jx().state.radius),
+        t.insert("rect", ":first-child").attr("x", h).attr(
+          "y",
+          jx().state.titleShift - jx().state.textHeight - jx().state.padding,
+        ).attr("width", u).attr("height", d.height + 3 + 2 * jx().state.textHeight).attr("rx", jx().state.radius),
+        t;
+    },
+    CA = (t, e) => {
+      e.attr("class", "state-note");
+      const n = e.append("rect").attr("x", 0).attr("y", jx().state.padding),
+        i = e.append("g"),
+        { textWidth: r, textHeight: a } = ((t, e, n, i) => {
+          let r = 0;
+          const a = i.append("text");
+          a.style("text-anchor", "start"), a.attr("class", "noteText");
+          let s = t.replace(/\r\n/g, "<br/>");
+          s = s.replace(/\n/g, "<br/>");
+          const o = s.split(ub.lineBreakRegex);
+          let l = 1.25 * jx().state.noteMargin;
+          for (const t of o) {
+            const i = t.trim();
+            if (i.length > 0) {
+              const t = a.append("tspan");
+              t.text(i),
+                0 === l && (l += t.node().getBBox().height),
+                r += l,
+                t.attr("x", e + jx().state.noteMargin),
+                t.attr("y", n + r + 1.25 * jx().state.noteMargin);
+            }
+          }
+          return { textWidth: a.node().getBBox().width, textHeight: r };
+        })(t, 0, 0, i);
+      return n.attr("height", a + 2 * jx().state.noteMargin), n.attr("width", r + 2 * jx().state.noteMargin), n;
+    },
+    EA = function(t, e) {
+      const n = e.id,
+        i = { id: n, label: e.id, width: 0, height: 0 },
+        r = t.append("g").attr("id", n).attr("class", "stateGroup");
+      "start" === e.type && (t => {
+        t.append("circle").attr("class", "start-state").attr("r", jx().state.sizeUnit).attr(
+          "cx",
+          jx().state.padding + jx().state.sizeUnit,
+        ).attr("cy", jx().state.padding + jx().state.sizeUnit);
+      })(r),
+        "end" === e.type && (t => {
+          t.append("circle").attr("class", "end-state-outer").attr("r", jx().state.sizeUnit + jx().state.miniPadding)
+            .attr("cx", jx().state.padding + jx().state.sizeUnit + jx().state.miniPadding).attr(
+              "cy",
+              jx().state.padding + jx().state.sizeUnit + jx().state.miniPadding,
+            ),
+            t.append("circle").attr("class", "end-state-inner").attr("r", jx().state.sizeUnit).attr(
+              "cx",
+              jx().state.padding + jx().state.sizeUnit + 2,
+            ).attr("cy", jx().state.padding + jx().state.sizeUnit + 2);
+        })(r),
+        "fork" !== e.type && "join" !== e.type || ((t, e) => {
+          let n = jx().state.forkWidth, i = jx().state.forkHeight;
+          if (e.parentId) {
+            let t = n;
+            n = i, i = t;
+          }
+          t.append("rect").style("stroke", "black").style("fill", "black").attr("width", n).attr("height", i).attr(
+            "x",
+            jx().state.padding,
+          ).attr("y", jx().state.padding);
+        })(r, e),
+        "note" === e.type && CA(e.note.text, r),
+        "divider" === e.type && (t => {
+          t.append("line").style("stroke", "grey").style("stroke-dasharray", "3").attr("x1", jx().state.textHeight)
+            .attr("class", "divider").attr("x2", 2 * jx().state.textHeight).attr("y1", 0).attr("y2", 0);
+        })(r),
+        "default" === e.type && 0 === e.descriptions.length && ((t, e) => {
+          const n = t.append("text").attr("x", 2 * jx().state.padding).attr(
+              "y",
+              jx().state.textHeight + 2 * jx().state.padding,
+            ).attr("font-size", jx().state.fontSize).attr("class", "state-title").text(e.id),
+            i = n.node().getBBox();
+          t.insert("rect", ":first-child").attr("x", jx().state.padding).attr("y", jx().state.padding).attr(
+            "width",
+            i.width + 2 * jx().state.padding,
+          ).attr("height", i.height + 2 * jx().state.padding).attr("rx", jx().state.radius);
+        })(r, e),
+        "default" === e.type && e.descriptions.length > 0 && wA(r, e);
+      const a = r.node().getBBox();
+      return i.width = a.width + 2 * jx().state.padding, i.height = a.height + 2 * jx().state.padding, i;
+    };
+  let SA = 0;
+  let AA;
+  const DA = {},
+    LA = t => t ? t.length * AA.fontSizeFactor : 1,
+    OA = (t, e, n, i, r, a, s) => {
+      const o = new yy({ compound: !0, multigraph: !0 });
+      let l, c = !0;
+      for (l = 0; l < t.length; l++) {
+        if ("relation" === t[l].stmt) {
+          c = !1;
+          break;
+        }
+      }
+      n
+        ? o.setGraph({
+          rankdir: "LR",
+          multigraph: !0,
+          compound: !0,
+          ranker: "tight-tree",
+          ranksep: c ? 1 : AA.edgeLengthFactor,
+          nodeSep: c ? 1 : 50,
+          isMultiGraph: !0,
+        })
+        : o.setGraph({
+          rankdir: "TB",
+          multigraph: !0,
+          compound: !0,
+          ranksep: c ? 1 : AA.edgeLengthFactor,
+          nodeSep: c ? 1 : 50,
+          ranker: "tight-tree",
+          isMultiGraph: !0,
+        }),
+        o.setDefaultEdgeLabel(function() {
+          return {};
+        }),
+        s.db.extract(t);
+      const h = s.db.getStates(), u = s.db.getRelations(), d = Object.keys(h);
+      for (const t of d) {
+        const l = h[t];
+        let c;
+        if (n && (l.parentId = n), l.doc) {
+          let t = e.append("g").attr("id", l.id).attr("class", "stateGroup");
+          c = OA(l.doc, t, l.id, !i, r, a, s);
+          {
+            t = TA(t, l, i);
+            let e = t.node().getBBox();
+            c.width = e.width, c.height = e.height + AA.padding / 2, DA[l.id] = { y: AA.compositTitleSize };
+          }
+        } else c = EA(e, l);
+        if (l.note) {
+          const t = { descriptions: [], id: l.id + "-note", note: l.note, type: "note" }, n = EA(e, t);
+          "left of" === l.note.position
+            ? (o.setNode(c.id + "-note", n), o.setNode(c.id, c))
+            : (o.setNode(c.id, c), o.setNode(c.id + "-note", n)),
+            o.setParent(c.id, c.id + "-group"),
+            o.setParent(c.id + "-note", c.id + "-group");
+        } else o.setNode(c.id, c);
+      }
+      tb.debug("Count=", o.nodeCount(), o);
+      let p = 0;
+      u.forEach(function(t) {
+        p++,
+          tb.debug("Setting edge", t),
+          o.setEdge(t.id1, t.id2, {
+            relation: t,
+            width: LA(t.title),
+            height: AA.labelHeight * ub.getRows(t.title).length,
+            labelpos: "c",
+          }, "id" + p);
+      }),
+        hm(o),
+        tb.debug("Graph after layout", o.nodes());
+      const f = e.node();
+      o.nodes().forEach(function(t) {
+        if (void 0 !== t && void 0 !== o.node(t)) {
+          tb.warn("Node " + t + ": " + JSON.stringify(o.node(t))),
+            r.select("#" + f.id + " #" + t).attr(
+              "transform",
+              "translate(" + (o.node(t).x - o.node(t).width / 2) + ","
+                + (o.node(t).y + (DA[t] ? DA[t].y : 0) - o.node(t).height / 2) + " )",
+            ),
+            r.select("#" + f.id + " #" + t).attr("data-x-shift", o.node(t).x - o.node(t).width / 2);
+          a.querySelectorAll("#" + f.id + " #" + t + " .divider").forEach(t => {
+            const e = t.parentElement;
+            let n = 0, i = 0;
+            e
+            && (e.parentElement && (n = e.parentElement.getBBox().width),
+              i = parseInt(e.getAttribute("data-x-shift"), 10),
+              Number.isNaN(i) && (i = 0)),
+              t.setAttribute("x1", 0 - i + 8),
+              t.setAttribute("x2", n - i - 8);
+          });
+        } else tb.debug("No Node " + t + ": " + JSON.stringify(o.node(t)));
+      });
+      let g = f.getBBox();
+      o.edges().forEach(function(t) {
+        void 0 !== t && void 0 !== o.edge(t)
+          && (tb.debug("Edge " + t.v + " -> " + t.w + ": " + JSON.stringify(o.edge(t))),
+            function(t, e, n) {
+              e.points = e.points.filter(t => !Number.isNaN(t.y));
+              const i = e.points,
+                r = Js().x(function(t) {
+                  return t.x;
+                }).y(function(t) {
+                  return t.y;
+                }).curve(ao),
+                a = t.append("path").attr("d", r(i)).attr("id", "edge" + SA).attr("class", "transition");
+              let s = "";
+              if (
+                jx().state.arrowMarkerAbsolute
+                && (s = window.location.protocol + "//" + window.location.host + window.location.pathname
+                  + window.location.search,
+                  s = s.replace(/\(/g, "\\("),
+                  s = s.replace(/\)/g, "\\)")),
+                  a.attr(
+                    "marker-end",
+                    "url(" + s + "#" + function(t) {
+                      switch (t) {
+                        case kA.relationType.AGGREGATION:
+                          return "aggregation";
+                        case kA.relationType.EXTENSION:
+                          return "extension";
+                        case kA.relationType.COMPOSITION:
+                          return "composition";
+                        case kA.relationType.DEPENDENCY:
+                          return "dependency";
+                      }
+                    }(kA.relationType.DEPENDENCY) + "End)",
+                  ),
+                  void 0 !== n.title
+              ) {
+                const i = t.append("g").attr("class", "stateLabel"),
+                  { x: r, y: a } = Dx.calcLabelPosition(e.points),
+                  s = ub.getRows(n.title);
+                let o = 0;
+                const l = [];
+                let c = 0, h = 0;
+                for (let t = 0; t <= s.length; t++) {
+                  const e = i.append("text").attr("text-anchor", "middle").text(s[t]).attr("x", r).attr("y", a + o),
+                    n = e.node().getBBox();
+                  if (c = Math.max(c, n.width), h = Math.min(h, n.x), tb.info(n.x, r, a + o), 0 === o) {
+                    const t = e.node().getBBox();
+                    o = t.height, tb.info("Title height", o, a);
+                  }
+                  l.push(e);
+                }
+                let u = o * s.length;
+                if (s.length > 1) {
+                  const t = (s.length - 1) * o * .5;
+                  l.forEach((e, n) => e.attr("y", a + n * o - t)), u = o * s.length;
+                }
+                const d = i.node().getBBox();
+                i.insert("rect", ":first-child").attr("class", "box").attr("x", r - c / 2 - jx().state.padding / 2)
+                  .attr("y", a - u / 2 - jx().state.padding / 2 - 3.5).attr("width", c + jx().state.padding).attr(
+                    "height",
+                    u + jx().state.padding,
+                  ), tb.info(d);
+              }
+              SA++;
+            }(e, o.edge(t), o.edge(t).relation));
+      }), g = f.getBBox();
+      const y = { id: n || "root", label: n || "root", width: 0, height: 0 };
+      return y.width = g.width + 2 * AA.padding,
+        y.height = g.height + 2 * AA.padding,
+        tb.debug("Doc rendered", y, o),
+        y;
+    },
+    NA = {
+      setConf: function() {},
+      draw: function(t, e, n, i) {
+        AA = jx().state;
+        const r = jx().securityLevel;
+        let a;
+        "sandbox" === r && (a = ie("#i" + e));
+        const s = ie("sandbox" === r ? a.nodes()[0].contentDocument.body : "body"),
+          o = "sandbox" === r ? a.nodes()[0].contentDocument : document;
+        tb.debug("Rendering diagram " + t);
+        const l = s.select(`[id='${e}']`);
+        l.append("defs").append("marker").attr("id", "dependencyEnd").attr("refX", 19).attr("refY", 7).attr(
+          "markerWidth",
+          20,
+        ).attr("markerHeight", 28).attr("orient", "auto").append("path").attr("d", "M 19,7 L9,13 L14,7 L9,1 Z");
+        new yy({ multigraph: !0, compound: !0, rankdir: "RL" }).setDefaultEdgeLabel(function() {
+          return {};
+        });
+        const c = i.db.getRootDoc();
+        OA(c, l, void 0, !1, s, o, i);
+        const h = AA.padding, u = l.node().getBBox(), d = u.width + 2 * h, p = u.height + 2 * h;
+        Gx(l, p, 1.75 * d, AA.useMaxWidth),
+          l.attr("viewBox", `${u.x - AA.padding}  ${u.y - AA.padding} ` + d + " " + p);
+      },
+    },
+    MA = "rect",
+    BA = "rectWithTitle",
+    IA = "statediagram",
+    FA = `${IA}-state`,
+    RA = "transition",
+    $A = `${RA} note-edge`,
+    PA = `${IA}-note`,
+    YA = `${IA}-cluster`,
+    jA = `${IA}-cluster-alt`,
+    zA = "parent",
+    UA = "note",
+    WA = "state",
+    HA = "----",
+    qA = `${HA}${UA}`,
+    VA = `${HA}${zA}`,
+    GA = "fill:none",
+    XA = "fill: #333",
+    ZA = "text",
+    QA = "normal";
+  let KA = {}, JA = 0;
+  function tD(t = "", e = 0, n = "", i = HA) {
+    const r = null !== n && n.length > 0 ? `${i}${n}` : "";
+    return `${WA}-${t}${r}-${e}`;
+  }
+  const eD = (t, e, n, i, r, a) => {
+      const s = n.id, o = null == (l = i[s]) ? "" : l.classes ? l.classes.join(" ") : "";
+      var l;
+      if ("root" !== s) {
+        let e = MA;
+        !0 === n.start && (e = "start"),
+          !1 === n.start && (e = "end"),
+          n.type !== GS && (e = n.type),
+          KA[s] || (KA[s] = { id: s, shape: e, description: ub.sanitizeText(s, jx()), classes: `${o} ${FA}` });
+        const i = KA[s];
+        n.description
+        && (Array.isArray(i.description)
+          ? (i.shape = BA, i.description.push(n.description))
+          : i.description.length > 0
+          ? (i.shape = BA,
+            i.description === s ? i.description = [n.description] : i.description = [i.description, n.description])
+          : (i.shape = MA, i.description = n.description),
+          i.description = ub.sanitizeTextOrArray(i.description, jx())),
+          1 === i.description.length && i.shape === BA && (i.shape = MA),
+          !i.type && n.doc
+          && (tb.info("Setting cluster for ", s, iD(n)),
+            i.type = "group",
+            i.dir = iD(n),
+            i.shape = n.type === XS ? "divider" : "roundedWithTitle",
+            i.classes = i.classes + " " + YA + " " + (a ? jA : ""));
+        const r = {
+          labelStyle: "",
+          shape: i.shape,
+          labelText: i.description,
+          classes: i.classes,
+          style: "",
+          id: s,
+          dir: i.dir,
+          domId: tD(s, JA),
+          type: i.type,
+          padding: 15,
+        };
+        if (n.note) {
+          const e = {
+              labelStyle: "",
+              shape: "note",
+              labelText: n.note.text,
+              classes: PA,
+              style: "",
+              id: s + qA + "-" + JA,
+              domId: tD(s, JA, UA),
+              type: i.type,
+              padding: 15,
+            },
+            a = {
+              labelStyle: "",
+              shape: "noteGroup",
+              labelText: n.note.text,
+              classes: i.classes,
+              style: "",
+              id: s + VA,
+              domId: tD(s, JA, zA),
+              type: "group",
+              padding: 0,
+            };
+          JA++;
+          const o = s + VA;
+          t.setNode(o, a), t.setNode(e.id, e), t.setNode(s, r), t.setParent(s, o), t.setParent(e.id, o);
+          let l = s, c = e.id;
+          "left of" === n.note.position && (l = e.id, c = s),
+            t.setEdge(l, c, {
+              arrowhead: "none",
+              arrowType: "",
+              style: GA,
+              labelStyle: "",
+              classes: $A,
+              arrowheadStyle: XA,
+              labelpos: "c",
+              labelType: ZA,
+              thickness: QA,
+            });
+        } else t.setNode(s, r);
+      }
+      e && "root" !== e.id && (tb.trace("Setting node ", s, " to be child of its parent ", e.id), t.setParent(s, e.id)),
+        n.doc && (tb.trace("Adding nodes children "), nD(t, n, n.doc, i, r, !a));
+    },
+    nD = (t, e, n, i, r, a) => {
+      tb.trace("items", n),
+        n.forEach(n => {
+          switch (n.stmt) {
+            case qS:
+            case GS:
+              eD(t, e, n, i, r, a);
+              break;
+            case VS: {
+              eD(t, e, n.state1, i, r, a), eD(t, e, n.state2, i, r, a);
+              const s = {
+                id: "edge" + JA,
+                arrowhead: "normal",
+                arrowTypeEnd: "arrow_barb",
+                style: GA,
+                labelStyle: "",
+                label: ub.sanitizeText(n.description, jx()),
+                arrowheadStyle: XA,
+                labelpos: "c",
+                labelType: ZA,
+                thickness: QA,
+                classes: RA,
+              };
+              t.setEdge(n.state1.id, n.state2.id, s, JA), JA++;
+            }
+          }
+        });
+    },
+    iD = (t, e = "TB") => {
+      let n = e;
+      if (t.doc) {
+        for (let e = 0; e < t.doc.length; e++) {
+          const i = t.doc[e];
+          "dir" === i.stmt && (n = i.value);
+        }
+      }
+      return n;
+    },
+    rD = {
+      setConf: function(t) {
+        const e = Object.keys(t);
+        for (const n of e) t[n];
+      },
+      getClasses: function(t, e) {
+        tb.trace("Extracting classes"), e.db.clear();
+        try {
+          return e.parser.parse(t), e.db.extract(e.db.getRootDocV2()), e.db.getClasses();
+        } catch (t) {
+          return t;
+        }
+      },
+      draw: function(t, e, n, i) {
+        tb.info("Drawing state diagram (v2)", e), KA = {}, i.db.getDirection();
+        const { securityLevel: r, state: a } = jx(), s = a.nodeSpacing || 50, o = a.rankSpacing || 50;
+        tb.info(i.db.getRootDocV2()), i.db.extract(i.db.getRootDocV2()), tb.info(i.db.getRootDocV2());
+        const l = i.db.getStates(),
+          c = new yy({ multigraph: !0, compound: !0 }).setGraph({
+            rankdir: iD(i.db.getRootDocV2()),
+            nodesep: s,
+            ranksep: o,
+            marginx: 8,
+            marginy: 8,
+          }).setDefaultEdgeLabel(function() {
+            return {};
+          });
+        let h;
+        eD(c, void 0, i.db.getRootDocV2(), l, i.db, !0), "sandbox" === r && (h = ie("#i" + e));
+        const u = ie("sandbox" === r ? h.nodes()[0].contentDocument.body : "body"),
+          d = u.select(`[id="${e}"]`),
+          p = u.select("#" + e + " g");
+        _T(p, c, ["barb"], IA, e);
+        Dx.insertTitle(d, "statediagramTitleText", a.titleTopMargin, i.db.getDiagramTitle());
+        const f = d.node().getBBox(), g = f.width + 16, y = f.height + 16;
+        d.attr("class", IA);
+        const m = d.node().getBBox();
+        Gx(d, y, g, a.useMaxWidth);
+        const b = `${m.x - 8} ${m.y - 8} ${g} ${y}`;
+        tb.debug(`viewBox ${b}`), d.attr("viewBox", b);
+        const _ = document.querySelectorAll("[id=\"" + e + "\"] .edgeLabel .label");
+        for (const t of _) {
+          const e = t.getBBox(), n = document.createElementNS("http://www.w3.org/2000/svg", MA);
+          n.setAttribute("rx", 0),
+            n.setAttribute("ry", 0),
+            n.setAttribute("width", e.width),
+            n.setAttribute("height", e.height),
+            t.insertBefore(n, t.firstChild);
+        }
+      },
+    };
+  var aD = function() {
+    var t,
+      e = function(t, e, n, i) {
+        for (n = n || {}, i = t.length; i--; n[t[i]] = e);
+        return n;
+      },
+      n = [1, 2],
+      i = [1, 5],
+      r = [6, 9, 11, 17, 18, 20, 22, 23, 24, 26],
+      a = [1, 15],
+      s = [1, 16],
+      o = [1, 17],
+      l = [1, 18],
+      c = [1, 19],
+      h = [1, 20],
+      u = [1, 24],
+      d = [4, 6, 9, 11, 17, 18, 20, 22, 23, 24, 26],
+      p = {
+        trace: function() {},
+        yy: {},
+        symbols_: {
+          error: 2,
+          start: 3,
+          journey: 4,
+          document: 5,
+          EOF: 6,
+          directive: 7,
+          line: 8,
+          SPACE: 9,
+          statement: 10,
+          NEWLINE: 11,
+          openDirective: 12,
+          typeDirective: 13,
+          closeDirective: 14,
+          ":": 15,
+          argDirective: 16,
+          title: 17,
+          acc_title: 18,
+          acc_title_value: 19,
+          acc_descr: 20,
+          acc_descr_value: 21,
+          acc_descr_multiline_value: 22,
+          section: 23,
+          taskName: 24,
+          taskData: 25,
+          open_directive: 26,
+          type_directive: 27,
+          arg_directive: 28,
+          close_directive: 29,
+          $accept: 0,
+          $end: 1,
+        },
+        terminals_: {
+          2: "error",
+          4: "journey",
+          6: "EOF",
+          9: "SPACE",
+          11: "NEWLINE",
+          15: ":",
+          17: "title",
+          18: "acc_title",
+          19: "acc_title_value",
+          20: "acc_descr",
+          21: "acc_descr_value",
+          22: "acc_descr_multiline_value",
+          23: "section",
+          24: "taskName",
+          25: "taskData",
+          26: "open_directive",
+          27: "type_directive",
+          28: "arg_directive",
+          29: "close_directive",
+        },
+        productions_: [
+          0,
+          [3, 3],
+          [3, 2],
+          [5, 0],
+          [5, 2],
+          [8, 2],
+          [8, 1],
+          [8, 1],
+          [8, 1],
+          [7, 4],
+          [7, 6],
+          [10, 1],
+          [10, 2],
+          [10, 2],
+          [10, 1],
+          [10, 1],
+          [10, 2],
+          [10, 1],
+          [12, 1],
+          [13, 1],
+          [16, 1],
+          [14, 1],
+        ],
+        performAction: function(t, e, n, i, r, a, s) {
+          var o = a.length - 1;
+          switch (r) {
+            case 1:
+              return a[o - 1];
+            case 3:
+            case 7:
+            case 8:
+              this.$ = [];
+              break;
+            case 4:
+              a[o - 1].push(a[o]), this.$ = a[o - 1];
+              break;
+            case 5:
+            case 6:
+              this.$ = a[o];
+              break;
+            case 11:
+              i.setDiagramTitle(a[o].substr(6)), this.$ = a[o].substr(6);
+              break;
+            case 12:
+              this.$ = a[o].trim(), i.setAccTitle(this.$);
+              break;
+            case 13:
+            case 14:
+              this.$ = a[o].trim(), i.setAccDescription(this.$);
+              break;
+            case 15:
+              i.addSection(a[o].substr(8)), this.$ = a[o].substr(8);
+              break;
+            case 16:
+              i.addTask(a[o - 1], a[o]), this.$ = "task";
+              break;
+            case 18:
+              i.parseDirective("%%{", "open_directive");
+              break;
+            case 19:
+              i.parseDirective(a[o], "type_directive");
+              break;
+            case 20:
+              a[o] = a[o].trim().replace(/'/g, "\""), i.parseDirective(a[o], "arg_directive");
+              break;
+            case 21:
+              i.parseDirective("}%%", "close_directive", "journey");
+          }
+        },
+        table: [
+          { 3: 1, 4: n, 7: 3, 12: 4, 26: i },
+          { 1: [3] },
+          e(r, [2, 3], { 5: 6 }),
+          { 3: 7, 4: n, 7: 3, 12: 4, 26: i },
+          { 13: 8, 27: [1, 9] },
+          { 27: [2, 18] },
+          {
+            6: [1, 10],
+            7: 21,
+            8: 11,
+            9: [1, 12],
+            10: 13,
+            11: [1, 14],
+            12: 4,
+            17: a,
+            18: s,
+            20: o,
+            22: l,
+            23: c,
+            24: h,
+            26: i,
+          },
+          { 1: [2, 2] },
+          { 14: 22, 15: [1, 23], 29: u },
+          e([15, 29], [2, 19]),
+          e(r, [2, 8], { 1: [2, 1] }),
+          e(r, [2, 4]),
+          { 7: 21, 10: 25, 12: 4, 17: a, 18: s, 20: o, 22: l, 23: c, 24: h, 26: i },
+          e(r, [2, 6]),
+          e(r, [2, 7]),
+          e(r, [2, 11]),
+          { 19: [1, 26] },
+          { 21: [1, 27] },
+          e(r, [2, 14]),
+          e(r, [2, 15]),
+          { 25: [1, 28] },
+          e(r, [2, 17]),
+          { 11: [1, 29] },
+          { 16: 30, 28: [1, 31] },
+          { 11: [2, 21] },
+          e(r, [2, 5]),
+          e(r, [2, 12]),
+          e(r, [2, 13]),
+          e(r, [2, 16]),
+          e(d, [2, 9]),
+          { 14: 32, 29: u },
+          { 29: [2, 20] },
+          { 11: [1, 33] },
+          e(d, [2, 10]),
+        ],
+        defaultActions: { 5: [2, 18], 7: [2, 2], 24: [2, 21], 31: [2, 20] },
+        parseError: function(t, e) {
+          if (!e.recoverable) {
+            var n = new Error(t);
+            throw n.hash = e, n;
+          }
+          this.trace(t);
+        },
+        parse: function(t) {
+          var e = this,
+            n = [0],
+            i = [],
+            r = [null],
+            a = [],
+            s = this.table,
+            o = "",
+            l = 0,
+            c = 0,
+            h = 1,
+            u = a.slice.call(arguments, 1),
+            d = Object.create(this.lexer),
+            p = { yy: {} };
+          for (var f in this.yy) Object.prototype.hasOwnProperty.call(this.yy, f) && (p.yy[f] = this.yy[f]);
+          d.setInput(t, p.yy), p.yy.lexer = d, p.yy.parser = this, void 0 === d.yylloc && (d.yylloc = {});
+          var g = d.yylloc;
+          a.push(g);
+          var y = d.options && d.options.ranges;
+          function m() {
+            var t;
+            return "number" != typeof (t = i.pop() || d.lex() || h)
+              && (t instanceof Array && (t = (i = t).pop()), t = e.symbols_[t] || t),
+              t;
+          }
+          "function" == typeof p.yy.parseError
+            ? this.parseError = p.yy.parseError
+            : this.parseError = Object.getPrototypeOf(this).parseError;
+          for (var b, _, x, v, k, w, T, C, E = {};;) {
+            if (
+              _ = n[n.length - 1],
+                this.defaultActions[_] ? x = this.defaultActions[_] : (null == b && (b = m()), x = s[_] && s[_][b]),
+                void 0 === x || !x.length || !x[0]
+            ) {
+              var S = "";
+              for (k in C = [], s[_]) this.terminals_[k] && k > 2 && C.push("'" + this.terminals_[k] + "'");
+              S = d.showPosition
+                ? "Parse error on line " + (l + 1) + ":\n" + d.showPosition() + "\nExpecting " + C.join(", ")
+                  + ", got '" + (this.terminals_[b] || b) + "'"
+                : "Parse error on line " + (l + 1) + ": Unexpected "
+                  + (b == h ? "end of input" : "'" + (this.terminals_[b] || b) + "'"),
+                this.parseError(S, {
+                  text: d.match,
+                  token: this.terminals_[b] || b,
+                  line: d.yylineno,
+                  loc: g,
+                  expected: C,
+                });
+            }
+            if (x[0] instanceof Array && x.length > 1) {
+              throw new Error("Parse Error: multiple actions possible at state: " + _ + ", token: " + b);
+            }
+            switch (x[0]) {
+              case 1:
+                n.push(b),
+                  r.push(d.yytext),
+                  a.push(d.yylloc),
+                  n.push(x[1]),
+                  b = null,
+                  c = d.yyleng,
+                  o = d.yytext,
+                  l = d.yylineno,
+                  g = d.yylloc;
+                break;
+              case 2:
+                if (
+                  w = this.productions_[x[1]][1],
+                    E.$ = r[r.length - w],
+                    E._$ = {
+                      first_line: a[a.length - (w || 1)].first_line,
+                      last_line: a[a.length - 1].last_line,
+                      first_column: a[a.length - (w || 1)].first_column,
+                      last_column: a[a.length - 1].last_column,
+                    },
+                    y && (E._$.range = [a[a.length - (w || 1)].range[0], a[a.length - 1].range[1]]),
+                    void 0 !== (v = this.performAction.apply(E, [o, c, l, p.yy, x[1], r, a].concat(u)))
+                ) return v;
+                w && (n = n.slice(0, -1 * w * 2), r = r.slice(0, -1 * w), a = a.slice(0, -1 * w)),
+                  n.push(this.productions_[x[1]][0]),
+                  r.push(E.$),
+                  a.push(E._$),
+                  T = s[n[n.length - 2]][n[n.length - 1]],
+                  n.push(T);
+                break;
+              case 3:
+                return !0;
+            }
+          }
+          return !0;
+        },
+      },
+      f = (t = {
+        EOF: 1,
+        parseError: function(t, e) {
+          if (!this.yy.parser) throw new Error(t);
+          this.yy.parser.parseError(t, e);
+        },
+        setInput: function(t, e) {
+          return this.yy = e || this.yy || {},
+            this._input = t,
+            this._more = this._backtrack = this.done = !1,
+            this.yylineno = this.yyleng = 0,
+            this.yytext = this.matched = this.match = "",
+            this.conditionStack = ["INITIAL"],
+            this.yylloc = { first_line: 1, first_column: 0, last_line: 1, last_column: 0 },
+            this.options.ranges && (this.yylloc.range = [0, 0]),
+            this.offset = 0,
+            this;
+        },
+        input: function() {
+          var t = this._input[0];
+          return this.yytext += t,
+            this.yyleng++,
+            this.offset++,
+            this.match += t,
+            this.matched += t,
+            t.match(/(?:\r\n?|\n).*/g) ? (this.yylineno++, this.yylloc.last_line++) : this.yylloc.last_column++,
+            this.options.ranges && this.yylloc.range[1]++,
+            this._input = this._input.slice(1),
+            t;
+        },
+        unput: function(t) {
+          var e = t.length, n = t.split(/(?:\r\n?|\n)/g);
+          this._input = t + this._input, this.yytext = this.yytext.substr(0, this.yytext.length - e), this.offset -= e;
+          var i = this.match.split(/(?:\r\n?|\n)/g);
+          this.match = this.match.substr(0, this.match.length - 1),
+            this.matched = this.matched.substr(0, this.matched.length - 1),
+            n.length - 1 && (this.yylineno -= n.length - 1);
+          var r = this.yylloc.range;
+          return this.yylloc = {
+            first_line: this.yylloc.first_line,
+            last_line: this.yylineno + 1,
+            first_column: this.yylloc.first_column,
+            last_column: n
+              ? (n.length === i.length ? this.yylloc.first_column : 0) + i[i.length - n.length].length - n[0].length
+              : this.yylloc.first_column - e,
+          },
+            this.options.ranges && (this.yylloc.range = [r[0], r[0] + this.yyleng - e]),
+            this.yyleng = this.yytext.length,
+            this;
+        },
+        more: function() {
+          return this._more = !0, this;
+        },
+        reject: function() {
+          return this.options.backtrack_lexer
+            ? (this._backtrack = !0, this)
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1)
+                + ". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"
+                + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        less: function(t) {
+          this.unput(this.match.slice(t));
+        },
+        pastInput: function() {
+          var t = this.matched.substr(0, this.matched.length - this.match.length);
+          return (t.length > 20 ? "..." : "") + t.substr(-20).replace(/\n/g, "");
+        },
+        upcomingInput: function() {
+          var t = this.match;
+          return t.length < 20 && (t += this._input.substr(0, 20 - t.length)),
+            (t.substr(0, 20) + (t.length > 20 ? "..." : "")).replace(/\n/g, "");
+        },
+        showPosition: function() {
+          var t = this.pastInput(), e = new Array(t.length + 1).join("-");
+          return t + this.upcomingInput() + "\n" + e + "^";
+        },
+        test_match: function(t, e) {
+          var n, i, r;
+          if (
+            this.options.backtrack_lexer && (r = {
+              yylineno: this.yylineno,
+              yylloc: {
+                first_line: this.yylloc.first_line,
+                last_line: this.last_line,
+                first_column: this.yylloc.first_column,
+                last_column: this.yylloc.last_column,
+              },
+              yytext: this.yytext,
+              match: this.match,
+              matches: this.matches,
+              matched: this.matched,
+              yyleng: this.yyleng,
+              offset: this.offset,
+              _more: this._more,
+              _input: this._input,
+              yy: this.yy,
+              conditionStack: this.conditionStack.slice(0),
+              done: this.done,
+            },
+              this.options.ranges && (r.yylloc.range = this.yylloc.range.slice(0))),
+              (i = t[0].match(/(?:\r\n?|\n).*/g)) && (this.yylineno += i.length),
+              this.yylloc = {
+                first_line: this.yylloc.last_line,
+                last_line: this.yylineno + 1,
+                first_column: this.yylloc.last_column,
+                last_column: i
+                  ? i[i.length - 1].length - i[i.length - 1].match(/\r?\n?/)[0].length
+                  : this.yylloc.last_column + t[0].length,
+              },
+              this.yytext += t[0],
+              this.match += t[0],
+              this.matches = t,
+              this.yyleng = this.yytext.length,
+              this.options.ranges && (this.yylloc.range = [this.offset, this.offset += this.yyleng]),
+              this._more = !1,
+              this._backtrack = !1,
+              this._input = this._input.slice(t[0].length),
+              this.matched += t[0],
+              n = this.performAction.call(this, this.yy, this, e, this.conditionStack[this.conditionStack.length - 1]),
+              this.done && this._input && (this.done = !1),
+              n
+          ) return n;
+          if (this._backtrack) {
+            for (var a in r) this[a] = r[a];
+            return !1;
+          }
+          return !1;
+        },
+        next: function() {
+          if (this.done) return this.EOF;
+          var t, e, n, i;
+          this._input || (this.done = !0), this._more || (this.yytext = "", this.match = "");
+          for (var r = this._currentRules(), a = 0; a < r.length; a++) {
+            if ((n = this._input.match(this.rules[r[a]])) && (!e || n[0].length > e[0].length)) {
+              if (e = n, i = a, this.options.backtrack_lexer) {
+                if (!1 !== (t = this.test_match(n, r[a]))) return t;
+                if (this._backtrack) {
+                  e = !1;
+                  continue;
+                }
+                return !1;
+              }
+              if (!this.options.flex) break;
+            }
+          }
+          return e
+            ? !1 !== (t = this.test_match(e, r[i])) && t
+            : "" === this._input
+            ? this.EOF
+            : this.parseError(
+              "Lexical error on line " + (this.yylineno + 1) + ". Unrecognized text.\n" + this.showPosition(),
+              { text: "", token: null, line: this.yylineno },
+            );
+        },
+        lex: function() {
+          var t = this.next();
+          return t || this.lex();
+        },
+        begin: function(t) {
+          this.conditionStack.push(t);
+        },
+        popState: function() {
+          return this.conditionStack.length - 1 > 0 ? this.conditionStack.pop() : this.conditionStack[0];
+        },
+        _currentRules: function() {
+          return this.conditionStack.length && this.conditionStack[this.conditionStack.length - 1]
+            ? this.conditions[this.conditionStack[this.conditionStack.length - 1]].rules
+            : this.conditions.INITIAL.rules;
+        },
+        topState: function(t) {
+          return (t = this.conditionStack.length - 1 - Math.abs(t || 0)) >= 0 ? this.conditionStack[t] : "INITIAL";
+        },
+        pushState: function(t) {
+          this.begin(t);
+        },
+        stateStackSize: function() {
+          return this.conditionStack.length;
+        },
+        options: { "case-insensitive": !0 },
+        performAction: function(t, e, n, i) {
+          switch (n) {
+            case 0:
+              return this.begin("open_directive"), 26;
+            case 1:
+              return this.begin("type_directive"), 27;
+            case 2:
+              return this.popState(), this.begin("arg_directive"), 15;
+            case 3:
+              return this.popState(), this.popState(), 29;
+            case 4:
+              return 28;
+            case 5:
+            case 6:
+            case 8:
+            case 9:
+              break;
+            case 7:
+              return 11;
+            case 10:
+              return 4;
+            case 11:
+              return 17;
+            case 12:
+              return this.begin("acc_title"), 18;
+            case 13:
+              return this.popState(), "acc_title_value";
+            case 14:
+              return this.begin("acc_descr"), 20;
+            case 15:
+              return this.popState(), "acc_descr_value";
+            case 16:
+              this.begin("acc_descr_multiline");
+              break;
+            case 17:
+              this.popState();
+              break;
+            case 18:
+              return "acc_descr_multiline_value";
+            case 19:
+              return 23;
+            case 20:
+              return 24;
+            case 21:
+              return 25;
+            case 22:
+              return 15;
+            case 23:
+              return 6;
+            case 24:
+              return "INVALID";
+          }
+        },
+        rules: [
+          /^(?:%%\{)/i,
+          /^(?:((?:(?!\}%%)[^:.])*))/i,
+          /^(?::)/i,
+          /^(?:\}%%)/i,
+          /^(?:((?:(?!\}%%).|\n)*))/i,
+          /^(?:%(?!\{)[^\n]*)/i,
+          /^(?:[^\}]%%[^\n]*)/i,
+          /^(?:[\n]+)/i,
+          /^(?:\s+)/i,
+          /^(?:#[^\n]*)/i,
+          /^(?:journey\b)/i,
+          /^(?:title\s[^#\n;]+)/i,
+          /^(?:accTitle\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*:\s*)/i,
+          /^(?:(?!\n||)*[^\n]*)/i,
+          /^(?:accDescr\s*\{\s*)/i,
+          /^(?:[\}])/i,
+          /^(?:[^\}]*)/i,
+          /^(?:section\s[^#:\n;]+)/i,
+          /^(?:[^#:\n;]+)/i,
+          /^(?::[^#\n;]+)/i,
+          /^(?::)/i,
+          /^(?:$)/i,
+          /^(?:.)/i,
+        ],
+        conditions: {
+          open_directive: { rules: [1], inclusive: !1 },
+          type_directive: { rules: [2, 3], inclusive: !1 },
+          arg_directive: { rules: [3, 4], inclusive: !1 },
+          acc_descr_multiline: { rules: [17, 18], inclusive: !1 },
+          acc_descr: { rules: [15], inclusive: !1 },
+          acc_title: { rules: [13], inclusive: !1 },
+          INITIAL: { rules: [0, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 19, 20, 21, 22, 23, 24], inclusive: !0 },
+        },
+      },
+        t);
+    function g() {
+      this.yy = {};
+    }
+    return p.lexer = f, g.prototype = p, p.Parser = g, new g();
+  }();
+  aD.parser = aD;
+  const sD = aD, oD = t => null !== t.match(/^\s*journey/);
+  let lD = "";
+  const cD = [],
+    hD = [],
+    uD = [],
+    dD = function() {
+      let t = !0;
+      for (const [e, n] of uD.entries()) uD[e].processed, t = t && n.processed;
+      return t;
+    },
+    pD = {
+      parseDirective: function(t, e, n) {
+        nL.parseDirective(this, t, e, n);
+      },
+      getConfig: () => jx().journey,
+      clear: function() {
+        cD.length = 0, hD.length = 0, lD = "", uD.length = 0, Cv();
+      },
+      setDiagramTitle: Lv,
+      getDiagramTitle: Ov,
+      setAccTitle: Ev,
+      getAccTitle: Sv,
+      setAccDescription: Av,
+      getAccDescription: Dv,
+      addSection: function(t) {
+        lD = t, cD.push(t);
+      },
+      getSections: function() {
+        return cD;
+      },
+      getTasks: function() {
+        let t = dD();
+        let e = 0;
+        for (; !t && e < 100;) t = dD(), e++;
+        return hD.push(...uD), hD;
+      },
+      addTask: function(t, e) {
+        const n = e.substr(1).split(":");
+        let i = 0, r = [];
+        1 === n.length ? (i = Number(n[0]), r = []) : (i = Number(n[0]), r = n[1].split(","));
+        const a = r.map(t => t.trim()), s = { section: lD, type: lD, people: a, task: t, score: i };
+        uD.push(s);
+      },
+      addTaskOrg: function(t) {
+        const e = { section: lD, type: lD, description: t, task: t, classes: [] };
+        hD.push(e);
+      },
+      getActors: function() {
+        return function() {
+          const t = [];
+          return hD.forEach(e => {
+            e.people && t.push(...e.people);
+          }),
+            [...new Set(t)].sort();
+        }();
+      },
+    },
+    fD = function(t, e) {
+      const n = t.append("rect");
+      return n.attr("x", e.x),
+        n.attr("y", e.y),
+        n.attr("fill", e.fill),
+        n.attr("stroke", e.stroke),
+        n.attr("width", e.width),
+        n.attr("height", e.height),
+        n.attr("rx", e.rx),
+        n.attr("ry", e.ry),
+        void 0 !== e.class && n.attr("class", e.class),
+        n;
+    },
+    gD = function(t, e) {
+      const n = t.append("circle");
+      return n.attr("cx", e.cx),
+        n.attr("cy", e.cy),
+        n.attr("class", "actor-" + e.pos),
+        n.attr("fill", e.fill),
+        n.attr("stroke", e.stroke),
+        n.attr("r", e.r),
+        void 0 !== n.class && n.attr("class", n.class),
+        void 0 !== e.title && n.append("title").text(e.title),
+        n;
+    },
+    yD = function(t, e) {
+      const n = e.text.replace(/<br\s*\/?>/gi, " "), i = t.append("text");
+      i.attr("x", e.x),
+        i.attr("y", e.y),
+        i.attr("class", "legend"),
+        i.style("text-anchor", e.anchor),
+        void 0 !== e.class && i.attr("class", e.class);
+      const r = i.append("tspan");
+      return r.attr("x", e.x + 2 * e.textMargin), r.text(n), i;
+    };
+  let mD = -1;
+  const bD = function() {
+      return { x: 0, y: 0, width: 100, anchor: "start", height: 100, rx: 0, ry: 0 };
+    },
+    _D = function() {
+      function t(t, e, n, r, a, s, o, l) {
+        i(
+          e.append("text").attr("x", n + a / 2).attr("y", r + s / 2 + 5).style("font-color", l).style(
+            "text-anchor",
+            "middle",
+          ).text(t),
+          o,
+        );
+      }
+      function e(t, e, n, r, a, s, o, l, c) {
+        const { taskFontSize: h, taskFontFamily: u } = l, d = t.split(/<br\s*\/?>/gi);
+        for (let t = 0; t < d.length; t++) {
+          const l = t * h - h * (d.length - 1) / 2,
+            p = e.append("text").attr("x", n + a / 2).attr("y", r).attr("fill", c).style("text-anchor", "middle").style(
+              "font-size",
+              h,
+            ).style("font-family", u);
+          p.append("tspan").attr("x", n + a / 2).attr("dy", l).text(d[t]),
+            p.attr("y", r + s / 2).attr("dominant-baseline", "central").attr("alignment-baseline", "central"),
+            i(p, o);
+        }
+      }
+      function n(t, n, r, a, s, o, l, c) {
+        const h = n.append("switch"),
+          u = h.append("foreignObject").attr("x", r).attr("y", a).attr("width", s).attr("height", o).attr(
+            "position",
+            "fixed",
+          ).append("xhtml:div").style("display", "table").style("height", "100%").style("width", "100%");
+        u.append("div").attr("class", "label").style("display", "table-cell").style("text-align", "center").style(
+          "vertical-align",
+          "middle",
+        ).text(t),
+          e(t, h, r, a, s, o, l, c),
+          i(u, l);
+      }
+      function i(t, e) {
+        for (const n in e) n in e && t.attr(n, e[n]);
+      }
+      return function(i) {
+        return "fo" === i.textPlacement ? n : "old" === i.textPlacement ? t : e;
+      };
+    }(),
+    xD = {
+      drawRect: fD,
+      drawCircle: gD,
+      drawSection: function(t, e, n) {
+        const i = t.append("g"), r = bD();
+        r.x = e.x,
+          r.y = e.y,
+          r.fill = e.fill,
+          r.width = n.width,
+          r.height = n.height,
+          r.class = "journey-section section-type-" + e.num,
+          r.rx = 3,
+          r.ry = 3,
+          fD(i, r),
+          _D(n)(
+            e.text,
+            i,
+            r.x,
+            r.y,
+            r.width,
+            r.height,
+            { class: "journey-section section-type-" + e.num },
+            n,
+            e.colour,
+          );
+      },
+      drawText: yD,
+      drawLabel: function(t, e) {
+        const n = t.append("polygon");
+        n.attr(
+          "points",
+          function(t, e, n, i, r) {
+            return t + "," + e + " " + (t + n) + "," + e + " " + (t + n) + "," + (e + i - r) + " " + (t + n - 1.2 * r)
+              + "," + (e + i) + " " + t + "," + (e + i);
+          }(e.x, e.y, 50, 20, 7),
+        ),
+          n.attr("class", "labelBox"),
+          e.y = e.y + e.labelMargin,
+          e.x = e.x + .5 * e.labelMargin,
+          yD(t, e);
+      },
+      drawTask: function(t, e, n) {
+        const i = e.x + n.width / 2, r = t.append("g");
+        mD++;
+        r.append("line").attr("id", "task" + mD).attr("x1", i).attr("y1", e.y).attr("x2", i).attr("y2", 450).attr(
+          "class",
+          "task-line",
+        ).attr("stroke-width", "1px").attr("stroke-dasharray", "4 2").attr("stroke", "#666"),
+          function(t, e) {
+            const n = 15,
+              i = t.append("circle").attr("cx", e.cx).attr("cy", e.cy).attr("class", "face").attr("r", n).attr(
+                "stroke-width",
+                2,
+              ).attr("overflow", "visible"),
+              r = t.append("g");
+            r.append("circle").attr("cx", e.cx - n / 3).attr("cy", e.cy - n / 3).attr("r", 1.5).attr("stroke-width", 2)
+              .attr("fill", "#666").attr("stroke", "#666"),
+              r.append("circle").attr("cx", e.cx + n / 3).attr("cy", e.cy - n / 3).attr("r", 1.5).attr(
+                "stroke-width",
+                2,
+              ).attr("fill", "#666").attr("stroke", "#666"),
+              e.score > 3
+                ? function(t) {
+                  const i = Vs().startAngle(Math.PI / 2).endAngle(Math.PI / 2 * 3).innerRadius(n / 2).outerRadius(
+                    n / 2.2,
+                  );
+                  t.append("path").attr("class", "mouth").attr("d", i).attr(
+                    "transform",
+                    "translate(" + e.cx + "," + (e.cy + 2) + ")",
+                  );
+                }(r)
+                : e.score < 3
+                ? function(t) {
+                  const i = Vs().startAngle(3 * Math.PI / 2).endAngle(Math.PI / 2 * 5).innerRadius(n / 2).outerRadius(
+                    n / 2.2,
+                  );
+                  t.append("path").attr("class", "mouth").attr("d", i).attr(
+                    "transform",
+                    "translate(" + e.cx + "," + (e.cy + 7) + ")",
+                  );
+                }(r)
+                : r.append("line").attr("class", "mouth").attr("stroke", 2).attr("x1", e.cx - 5).attr("y1", e.cy + 7)
+                  .attr("x2", e.cx + 5).attr("y2", e.cy + 7).attr("class", "mouth").attr("stroke-width", "1px").attr(
+                    "stroke",
+                    "#666",
+                  );
+          }(r, { cx: i, cy: 300 + 30 * (5 - e.score), score: e.score });
+        const a = bD();
+        a.x = e.x,
+          a.y = e.y,
+          a.fill = e.fill,
+          a.width = n.width,
+          a.height = n.height,
+          a.class = "task task-type-" + e.num,
+          a.rx = 3,
+          a.ry = 3,
+          fD(r, a);
+        let s = e.x + 14;
+        e.people.forEach(t => {
+          const n = e.actors[t].color,
+            i = { cx: s, cy: e.y, r: 7, fill: n, stroke: "#000", title: t, pos: e.actors[t].position };
+          gD(r, i), s += 10;
+        }), _D(n)(e.task, r, a.x, a.y, a.width, a.height, { class: "task" }, n, e.colour);
+      },
+      drawBackgroundRect: function(t, e) {
+        fD(t, {
+          x: e.startx,
+          y: e.starty,
+          width: e.stopx - e.startx,
+          height: e.stopy - e.starty,
+          fill: e.fill,
+          class: "rect",
+        }).lower();
+      },
+      getTextObj: function() {
+        return {
+          x: 0,
+          y: 0,
+          fill: void 0,
+          "text-anchor": "start",
+          width: 100,
+          height: 100,
+          textMargin: 0,
+          rx: 0,
+          ry: 0,
+        };
+      },
+      getNoteRect: bD,
+      initGraphics: function(t) {
+        t.append("defs").append("marker").attr("id", "arrowhead").attr("refX", 5).attr("refY", 2).attr("markerWidth", 6)
+          .attr("markerHeight", 4).attr("orient", "auto").append("path").attr("d", "M 0,0 V 4 L6,2 Z");
+      },
+    },
+    vD = {};
+  const kD = jx().journey,
+    wD = kD.leftMargin,
+    TD = {
+      data: { startx: void 0, stopx: void 0, starty: void 0, stopy: void 0 },
+      verticalPos: 0,
+      sequenceItems: [],
+      init: function() {
+        this.sequenceItems = [],
+          this.data = { startx: void 0, stopx: void 0, starty: void 0, stopy: void 0 },
+          this.verticalPos = 0;
+      },
+      updateVal: function(t, e, n, i) {
+        void 0 === t[e] ? t[e] = n : t[e] = i(n, t[e]);
+      },
+      updateBounds: function(t, e, n, i) {
+        const r = jx().journey, a = this;
+        let s = 0;
+        var o;
+        this.sequenceItems.forEach(function(l) {
+          s++;
+          const c = a.sequenceItems.length - s + 1;
+          a.updateVal(l, "starty", e - c * r.boxMargin, Math.min),
+            a.updateVal(l, "stopy", i + c * r.boxMargin, Math.max),
+            a.updateVal(TD.data, "startx", t - c * r.boxMargin, Math.min),
+            a.updateVal(TD.data, "stopx", n + c * r.boxMargin, Math.max),
+            "activation" !== o
+            && (a.updateVal(l, "startx", t - c * r.boxMargin, Math.min),
+              a.updateVal(l, "stopx", n + c * r.boxMargin, Math.max),
+              a.updateVal(TD.data, "starty", e - c * r.boxMargin, Math.min),
+              a.updateVal(TD.data, "stopy", i + c * r.boxMargin, Math.max));
+        });
+      },
+      insert: function(t, e, n, i) {
+        const r = Math.min(t, n), a = Math.max(t, n), s = Math.min(e, i), o = Math.max(e, i);
+        this.updateVal(TD.data, "startx", r, Math.min),
+          this.updateVal(TD.data, "starty", s, Math.min),
+          this.updateVal(TD.data, "stopx", a, Math.max),
+          this.updateVal(TD.data, "stopy", o, Math.max),
+          this.updateBounds(r, s, a, o);
+      },
+      bumpVerticalPos: function(t) {
+        this.verticalPos = this.verticalPos + t, this.data.stopy = this.verticalPos;
+      },
+      getVerticalPos: function() {
+        return this.verticalPos;
+      },
+      getBounds: function() {
+        return this.data;
+      },
+    },
+    CD = kD.sectionFills,
+    ED = kD.sectionColours,
+    SD = function(t, e, n) {
+      const i = jx().journey;
+      let r = "";
+      const a = n + (2 * i.height + i.diagramMarginY);
+      let s = 0, o = "#CCC", l = "black", c = 0;
+      for (const [n, h] of e.entries()) {
+        if (r !== h.section) {
+          o = CD[s % CD.length], c = s % CD.length, l = ED[s % ED.length];
+          const e = { x: n * i.taskMargin + n * i.width + wD, y: 50, text: h.section, fill: o, num: c, colour: l };
+          xD.drawSection(t, e, i), r = h.section, s++;
+        }
+        const e = h.people.reduce((t, e) => (vD[e] && (t[e] = vD[e]), t), {});
+        h.x = n * i.taskMargin + n * i.width + wD,
+          h.y = a,
+          h.width = i.diagramMarginX,
+          h.height = i.diagramMarginY,
+          h.colour = l,
+          h.fill = o,
+          h.num = c,
+          h.actors = e,
+          xD.drawTask(t, h, i),
+          TD.insert(h.x, h.y, h.x + h.width + i.taskMargin, 450);
+      }
+    },
+    AD = {
+      setConf: function(t) {
+        Object.keys(t).forEach(function(e) {
+          kD[e] = t[e];
+        });
+      },
+      draw: function(t, e, n, i) {
+        const r = jx().journey;
+        i.db.clear(), i.parser.parse(t + "\n");
+        const a = jx().securityLevel;
+        let s;
+        "sandbox" === a && (s = ie("#i" + e));
+        const o = ie("sandbox" === a ? s.nodes()[0].contentDocument.body : "body");
+        TD.init();
+        const l = o.select("#" + e);
+        xD.initGraphics(l);
+        const c = i.db.getTasks(), h = i.db.getDiagramTitle(), u = i.db.getActors();
+        for (const t in vD) delete vD[t];
+        let d = 0;
+        u.forEach(t => {
+          vD[t] = { color: r.actorColours[d % r.actorColours.length], position: d }, d++;
+        }),
+          function(t) {
+            const e = jx().journey;
+            let n = 60;
+            Object.keys(vD).forEach(i => {
+              const r = vD[i].color, a = { cx: 20, cy: n, r: 7, fill: r, stroke: "#000", pos: vD[i].position };
+              xD.drawCircle(t, a);
+              const s = { x: 40, y: n + 7, fill: "#666", text: i, textMargin: 5 | e.boxTextMargin };
+              xD.drawText(t, s), n += 20;
+            });
+          }(l),
+          TD.insert(0, 0, wD, 50 * Object.keys(vD).length),
+          SD(l, c, 0);
+        const p = TD.getBounds();
+        h && l.append("text").text(h).attr("x", wD).attr("font-size", "4ex").attr("font-weight", "bold").attr("y", 25);
+        const f = p.stopy - p.starty + 2 * r.diagramMarginY, g = wD + p.stopx + 2 * r.diagramMarginX;
+        Gx(l, f, g, r.useMaxWidth),
+          l.append("line").attr("x1", wD).attr("y1", 4 * r.height).attr("x2", g - wD - 4).attr("y2", 4 * r.height).attr(
+            "stroke-width",
+            4,
+          ).attr("stroke", "black").attr("marker-end", "url(#arrowhead)");
+        const y = h ? 70 : 0;
+        l.attr("viewBox", `${p.startx} -25 ${g} ${f + y}`),
+          l.attr("preserveAspectRatio", "xMinYMin meet"),
+          l.attr("height", f + y + 25);
+      },
+    };
+  let DD = {};
+  const LD = {
+    setConf: function(t) {
+      DD = { ...DD, ...t };
+    },
+    draw: (t, e, n) => {
+      try {
+        tb.debug("Renering svg for syntax error\n");
+        const t = ie("#" + e), i = t.append("g");
+        i.append("path").attr("class", "error-icon").attr(
+          "d",
+          "m411.313,123.313c6.25-6.25 6.25-16.375 0-22.625s-16.375-6.25-22.625,0l-32,32-9.375,9.375-20.688-20.688c-12.484-12.5-32.766-12.5-45.25,0l-16,16c-1.261,1.261-2.304,2.648-3.31,4.051-21.739-8.561-45.324-13.426-70.065-13.426-105.867,0-192,86.133-192,192s86.133,192 192,192 192-86.133 192-192c0-24.741-4.864-48.327-13.426-70.065 1.402-1.007 2.79-2.049 4.051-3.31l16-16c12.5-12.492 12.5-32.758 0-45.25l-20.688-20.688 9.375-9.375 32.001-31.999zm-219.313,100.687c-52.938,0-96,43.063-96,96 0,8.836-7.164,16-16,16s-16-7.164-16-16c0-70.578 57.422-128 128-128 8.836,0 16,7.164 16,16s-7.164,16-16,16z",
+        ),
+          i.append("path").attr("class", "error-icon").attr(
+            "d",
+            "m459.02,148.98c-6.25-6.25-16.375-6.25-22.625,0s-6.25,16.375 0,22.625l16,16c3.125,3.125 7.219,4.688 11.313,4.688 4.094,0 8.188-1.563 11.313-4.688 6.25-6.25 6.25-16.375 0-22.625l-16.001-16z",
+          ),
+          i.append("path").attr("class", "error-icon").attr(
+            "d",
+            "m340.395,75.605c3.125,3.125 7.219,4.688 11.313,4.688 4.094,0 8.188-1.563 11.313-4.688 6.25-6.25 6.25-16.375 0-22.625l-16-16c-6.25-6.25-16.375-6.25-22.625,0s-6.25,16.375 0,22.625l15.999,16z",
+          ),
+          i.append("path").attr("class", "error-icon").attr(
+            "d",
+            "m400,64c8.844,0 16-7.164 16-16v-32c0-8.836-7.156-16-16-16-8.844,0-16,7.164-16,16v32c0,8.836 7.156,16 16,16z",
+          ),
+          i.append("path").attr("class", "error-icon").attr(
+            "d",
+            "m496,96.586h-32c-8.844,0-16,7.164-16,16 0,8.836 7.156,16 16,16h32c8.844,0 16-7.164 16-16 0-8.836-7.156-16-16-16z",
+          ),
+          i.append("path").attr("class", "error-icon").attr(
+            "d",
+            "m436.98,75.605c3.125,3.125 7.219,4.688 11.313,4.688 4.094,0 8.188-1.563 11.313-4.688l32-32c6.25-6.25 6.25-16.375 0-22.625s-16.375-6.25-22.625,0l-32,32c-6.251,6.25-6.251,16.375-0.001,22.625z",
+          ),
+          i.append("text").attr("class", "error-text").attr("x", 1440).attr("y", 250).attr("font-size", "150px").style(
+            "text-anchor",
+            "middle",
+          ).text("Syntax error in graph"),
+          i.append("text").attr("class", "error-text").attr("x", 1250).attr("y", 400).attr("font-size", "100px").style(
+            "text-anchor",
+            "middle",
+          ).text("mermaid version " + n),
+          t.attr("height", 100),
+          t.attr("width", 500),
+          t.attr("viewBox", "768 0 912 512");
+      } catch (t) {
+        tb.error("Error while rendering info diagram"), tb.error((i = t) instanceof Error ? i.message : String(i));
+      }
+      var i;
+    },
+  };
+  let OD = !1;
+  const ND = () => {
+    OD || (OD = !0,
+      yv("error", {
+        db: { clear: () => {} },
+        styles: Kx,
+        renderer: LD,
+        parser: { parser: { yy: {} }, parse: () => {} },
+        init: () => {},
+      }, t => "error" === t.toLowerCase().trim()),
+      yv("c4", {
+        parser: dk,
+        db: Sk,
+        renderer: aw,
+        styles: ov,
+        init: t => {
+          aw.setConf(t.c4);
+        },
+      }, pk),
+      yv("class", {
+        parser: ow,
+        db: Cw,
+        renderer: $w,
+        styles: Zx,
+        init: t => {
+          t.class || (t.class = {}), t.class.arrowMarkerAbsolute = t.arrowMarkerAbsolute, Cw.clear();
+        },
+      }, lw),
+      yv("classDiagram", {
+        parser: ow,
+        db: Cw,
+        renderer: wT,
+        styles: Zx,
+        init: t => {
+          t.class || (t.class = {}), t.class.arrowMarkerAbsolute = t.arrowMarkerAbsolute, Cw.clear();
+        },
+      }, cw),
+      yv("er", { parser: CT, db: LT, renderer: jT, styles: Qx }, ET),
+      yv("gantt", { parser: TC, db: iE, renderer: sE, styles: tv }, CC),
+      yv("info", { parser: lE, db: uE, renderer: dE, styles: ev }, pE),
+      yv("pie", { parser: gE, db: _E, renderer: wE, styles: nv }, yE),
+      yv("requirement", { parser: CE, db: NE, renderer: UE, styles: iv }, EE),
+      yv("sequence", {
+        parser: HE,
+        db: hS,
+        renderer: jS,
+        styles: rv,
+        init: t => {
+          if (
+            t.sequence || (t.sequence = {}),
+              t.sequence.arrowMarkerAbsolute = t.arrowMarkerAbsolute,
+              "sequenceDiagram" in t
+          ) {
+            throw new Error(
+              "`mermaid config.sequenceDiagram` has been renamed to `config.sequence`. Please update your mermaid config.",
+            );
+          }
+          hS.setWrap(t.wrap), jS.setConf(t.sequence);
+        },
+      }, qE),
+      yv("state", {
+        parser: US,
+        db: kA,
+        renderer: NA,
+        styles: av,
+        init: t => {
+          t.state || (t.state = {}), t.state.arrowMarkerAbsolute = t.arrowMarkerAbsolute, kA.clear();
+        },
+      }, WS),
+      yv("stateDiagram", {
+        parser: US,
+        db: kA,
+        renderer: rD,
+        styles: av,
+        init: t => {
+          t.state || (t.state = {}), t.state.arrowMarkerAbsolute = t.arrowMarkerAbsolute, kA.clear();
+        },
+      }, HS),
+      yv("journey", {
+        parser: sD,
+        db: pD,
+        renderer: AD,
+        styles: sv,
+        init: t => {
+          AD.setConf(t.journey), pD.clear();
+        },
+      }, oD),
+      yv("flowchart", {
+        parser: UT,
+        db: yC,
+        renderer: kC,
+        styles: Jx,
+        init: t => {
+          t.flowchart || (t.flowchart = {}),
+            t.flowchart.arrowMarkerAbsolute = t.arrowMarkerAbsolute,
+            bC(t.flowchart),
+            yC.clear(),
+            yC.setGen("gen-1");
+        },
+      }, WT),
+      yv("flowchart-v2", {
+        parser: UT,
+        db: yC,
+        renderer: kC,
+        styles: Jx,
+        init: t => {
+          t.flowchart || (t.flowchart = {}),
+            t.flowchart.arrowMarkerAbsolute = t.arrowMarkerAbsolute,
+            Yx({ flowchart: { arrowMarkerAbsolute: t.arrowMarkerAbsolute } }),
+            kC.setConf(t.flowchart),
+            yC.clear(),
+            yC.setGen("gen-2");
+        },
+      }, HT),
+      yv("gitGraph", { parser: _v, db: Gv, renderer: ck, styles: hk }, xv));
+  };
+  class MD {
+    constructor(t, e) {
+      var n, i;
+      Km(this, "type", "graph"),
+        Km(this, "parser"),
+        Km(this, "renderer"),
+        Km(this, "db"),
+        Km(this, "detectTypeFailed", !1),
+        this.txt = t;
+      const r = jx();
+      this.txt = t;
+      try {
+        this.type = ax(t, r);
+      } catch (t) {
+        this.handleError(t, e), this.type = "error", this.detectTypeFailed = !0;
+      }
+      const a = mv(this.type);
+      tb.debug("Type " + this.type),
+        this.db = a.db,
+        null == (i = (n = this.db).clear) || i.call(n),
+        this.renderer = a.renderer,
+        this.parser = a.parser;
+      const s = this.parser.parse.bind(this.parser);
+      this.parser.parse = t =>
+        s(function(t, e) {
+          var n;
+          const i = t.match(ex);
+          if (i) {
+            const r = tx(i[1], { schema: J_ });
+            return (null == r ? void 0 : r.title) && (null == (n = e.setDiagramTitle) || n.call(e, r.title)),
+              t.slice(i[0].length);
+          }
+          return t;
+        }(t, this.db)),
+        this.parser.parser.yy = this.db,
+        a.init && (a.init(r), tb.debug("Initialized diagram " + this.type, r)),
+        this.txt += "\n",
+        this.parse(this.txt, e);
+    }
+    parse(t, e) {
+      var n, i;
+      if (this.detectTypeFailed) return !1;
+      try {
+        return t += "\n", null == (i = (n = this.db).clear) || i.call(n), this.parser.parse(t), !0;
+      } catch (t) {
+        this.handleError(t, e);
+      }
+      return !1;
+    }
+    handleError(t, e) {
+      if (void 0 === e) throw t;
+      Ax(t) ? e(t.str, t.hash) : e(t);
+    }
+    getParser() {
+      return this.parser;
+    }
+    getType() {
+      return this.type;
+    }
+  }
+  const BD = (t, e) => {
+      const n = ax(t, jx());
+      try {
+        mv(n);
+      } catch (i) {
+        const r = rx[n].loader;
+        if (!r) throw new Error(`Diagram ${n} not found.`);
+        return r().then(({ diagram: i }) => (yv(n, i, void 0), new MD(t, e)));
+      }
+      return new MD(t, e);
+    },
+    ID = MD;
+  const FD = ["graph", "flowchart", "flowchart-v2", "stateDiagram", "stateDiagram-v2"],
+    RD = "graph TB;a[Maximum text size in diagram exceeded];style a fill:#faa",
+    $D = "sandbox",
+    PD = "loose",
+    YD = "http://www.w3.org/1999/xlink",
+    jD = "http://www.w3.org/1999/xhtml",
+    zD = ["foreignobject"],
+    UD = ["dominant-baseline"];
+  const WD = function(t) {
+      let e = t;
+      return e = e.replace(/style.*:\S*#.*;/g, function(t) {
+        return t.substring(0, t.length - 1);
+      }),
+        e = e.replace(/classDef.*:\S*#.*;/g, function(t) {
+          return t.substring(0, t.length - 1);
+        }),
+        e = e.replace(/#\w+;/g, function(t) {
+          const e = t.substring(1, t.length - 1);
+          return /^\+?\d+$/.test(e) ? "fl°°" + e + "¶ß" : "fl°" + e + "¶ß";
+        }),
+        e;
+    },
+    HD = function(t) {
+      let e = t;
+      return e = e.replace(/fl°°/g, "&#"), e = e.replace(/fl°/g, "&"), e = e.replace(/¶ß/g, ";"), e;
+    },
+    qD = (t, e, n = []) => `\n.${t} ${e} { ${n.join(" !important; ")} !important; }`,
+    VD = (t, e, n, i) => {
+      const r = ((t, e, n = {}) => {
+        var i;
+        let r = "";
+        if (
+          void 0 !== t.themeCSS && (r += `\n${t.themeCSS}`),
+            void 0 !== t.fontFamily && (r += `\n:root { --mermaid-font-family: ${t.fontFamily}}`),
+            void 0 !== t.altFontFamily && (r += `\n:root { --mermaid-alt-font-family: ${t.altFontFamily}}`),
+            !Ig(n) && FD.includes(e)
+        ) {
+          const e = t.htmlLabels || (null == (i = t.flowchart) ? void 0 : i.htmlLabels)
+            ? ["> *", "span"]
+            : ["rect", "polygon", "ellipse", "circle", "path"];
+          for (const t in n) {
+            const i = n[t];
+            Ig(i.styles) || e.forEach(t => {
+              r += qD(i.id, t, i.styles);
+            }), Ig(i.textStyles) || (r += qD(i.id, "tspan", i.textStyles));
+          }
+        }
+        return r;
+      })(t, e, n);
+      return Dh(Th(`${i}{${cv(e, r, t.themeVariables)}}`), Lh);
+    },
+    GD = (t = "", e, n) => {
+      let i = t;
+      return n || e || (i = i.replace(/marker-end="url\(.*?#/g, "marker-end=\"url(#")),
+        i = HD(i),
+        i = i.replace(/<br>/g, "<br/>"),
+        i;
+    },
+    XD = (t = "", e) =>
+      `<iframe style="width:100%;height:${
+        e ? e.viewBox.baseVal.height + "px" : "100%"
+      };border:0;margin:0;" src="data:text/html;base64,${
+        btoa("<body style=\"margin:0\">" + t + "</body>")
+      }" sandbox="allow-top-navigation-by-user-activation allow-popups">\n  The "iframe" tag is not supported by your browser.\n</iframe>`,
+    ZD = (t, e, n, i, r) => {
+      const a = t.append("div");
+      a.attr("id", n), i && a.attr("style", i);
+      const s = a.append("svg").attr("id", e).attr("width", "100%").attr("xmlns", "http://www.w3.org/2000/svg");
+      return r && s.attr("xmlns:xlink", r), s.append("g"), t;
+    };
+  function QD(t, e) {
+    return t.append("iframe").attr("id", e).attr("style", "width: 100%; height: 100%;").attr("sandbox", "");
+  }
+  const KD = (t, e, n, i) => {
+    var r, a, s;
+    null == (r = t.getElementById(e)) || r.remove(),
+      null == (a = t.getElementById(n)) || a.remove(),
+      null == (s = t.getElementById(i)) || s.remove();
+  };
+  let JD = {};
+  const tL = function(t, e, n) {
+    switch (tb.debug(`Directive type=${e.type} with args:`, e.args), e.type) {
+      case "init":
+      case "initialize":
+        ["config"].forEach(t => {
+          void 0 !== e.args[t] && ("flowchart-v2" === n && (n = "flowchart"), e.args[n] = e.args[t], delete e.args[t]);
+        }),
+          tb.debug("sanitize in handleDirective", e.args),
+          Ex(e.args),
+          tb.debug("sanitize in handleDirective (done)", e.args),
+          Ux(e.args);
+        break;
+      case "wrap":
+      case "nowrap":
+        t && t.setWrap && t.setWrap("wrap" === e.type);
+        break;
+      case "themeCss":
+        tb.warn("themeCss encountered");
+        break;
+      default:
+        tb.warn(`Unhandled directive: source: '%%{${e.type}: ${JSON.stringify(e.args ? e.args : {})}}%%`, e);
+    }
+  };
+  function eL(t, e, n, i) {
+    !function(t, e) {
+      Ig(e) || t.attr("aria-roledescription", e);
+    }(e, t),
+      function(t, e, n, i) {
+        if (void 0 !== t.insert && (e || n)) {
+          if (n) {
+            const e = "chart-desc-" + i;
+            t.attr("aria-describedby", e), t.insert("desc", ":first-child").attr("id", e).text(n);
+          }
+          if (e) {
+            const n = "chart-title-" + i;
+            t.attr("aria-labelledby", n), t.insert("title", ":first-child").attr("id", n).text(e);
+          }
+        }
+      }(e, n, i, e.attr("id"));
+  }
+  const nL = Object.freeze({
+    render: function(t, e, n, i) {
+      var r, a, s, o, l;
+      ND(), Wx();
+      const c = Dx.detectInit(e);
+      c && (Ex(c), Ux(c));
+      const h = jx();
+      tb.debug(h),
+        e.length > (null != (r = null == h ? void 0 : h.maxTextSize) ? r : 5e4) && (e = RD),
+        e = e.replace(/\r\n?/g, "\n");
+      const u = "#" + t, d = "i" + t, p = "#" + d, f = "d" + t, g = "#" + f;
+      let y = ie("body");
+      const m = h.securityLevel === $D, b = h.securityLevel === PD, _ = h.fontFamily;
+      if (void 0 !== i) {
+        if (i && (i.innerHTML = ""), m) {
+          const t = QD(ie(i), d);
+          y = ie(t.nodes()[0].contentDocument.body), y.node().style.margin = 0;
+        } else y = ie(i);
+        ZD(y, t, f, `font-family: ${_}`, YD);
+      } else {
+        if (KD(document, t, f, d), m) {
+          const t = QD(ie("body"), d);
+          y = ie(t.nodes()[0].contentDocument.body), y.node().style.margin = 0;
+        } else y = ie("body");
+        ZD(y, t, f);
+      }
+      let x, v;
+      e = WD(e);
+      try {
+        if (x = BD(e), "then" in x) throw new Error("Diagram is a promise. Use renderAsync.");
+      } catch (t) {
+        x = new ID("error"), v = t;
+      }
+      const k = y.select(g).node(),
+        w = x.type,
+        T = k.firstChild,
+        C = T.firstChild,
+        E = FD.includes(w) ? x.renderer.getClasses(e, x) : {},
+        S = VD(h, w, E, u),
+        A = document.createElement("style");
+      A.innerHTML = S, T.insertBefore(A, C);
+      try {
+        x.renderer.draw(e, t, Lx, x);
+      } catch (n) {
+        throw LD.draw(e, t, Lx), n;
+      }
+      eL(
+        w,
+        y.select(`${g} svg`),
+        null == (s = (a = x.db).getAccTitle) ? void 0 : s.call(a),
+        null == (l = (o = x.db).getAccDescription) ? void 0 : l.call(o),
+      ), y.select(`[id="${t}"]`).selectAll("foreignobject > *").attr("xmlns", jD);
+      let D = y.select(g).node().innerHTML;
+      if (tb.debug("config.arrowMarkerAbsolute", h.arrowMarkerAbsolute), D = GD(D, m, cb(h.arrowMarkerAbsolute)), m) {
+        const t = y.select(g + " svg").node();
+        D = XD(D, t);
+      } else b || (D = vl.sanitize(D, { ADD_TAGS: zD, ADD_ATTR: UD }));
+      if (void 0 !== n) {
+        switch (w) {
+          case "flowchart":
+          case "flowchart-v2":
+            n(D, yC.bindFunctions);
+            break;
+          case "gantt":
+            n(D, iE.bindFunctions);
+            break;
+          case "class":
+          case "classDiagram":
+            n(D, Cw.bindFunctions);
+            break;
+          default:
+            n(D);
+        }
+      } else tb.debug("CB = undefined!");
+      dS();
+      const L = ie(m ? p : g).node();
+      if (L && "remove" in L && L.remove(), v) throw v;
+      return D;
+    },
+    renderAsync: async function(t, e, n, i) {
+      var r, a, s, o, l;
+      ND(), Wx();
+      const c = Dx.detectInit(e);
+      c && (Ex(c), Ux(c));
+      const h = jx();
+      tb.debug(h),
+        e.length > (null != (r = null == h ? void 0 : h.maxTextSize) ? r : 5e4) && (e = RD),
+        e = e.replace(/\r\n?/g, "\n");
+      const u = "#" + t, d = "i" + t, p = "#" + d, f = "d" + t, g = "#" + f;
+      let y = ie("body");
+      const m = h.securityLevel === $D, b = h.securityLevel === PD, _ = h.fontFamily;
+      if (void 0 !== i) {
+        if (i && (i.innerHTML = ""), m) {
+          const t = QD(ie(i), d);
+          y = ie(t.nodes()[0].contentDocument.body), y.node().style.margin = 0;
+        } else y = ie(i);
+        ZD(y, t, f, `font-family: ${_}`, YD);
+      } else {
+        if (KD(document, t, f, d), m) {
+          const t = QD(ie("body"), d);
+          y = ie(t.nodes()[0].contentDocument.body), y.node().style.margin = 0;
+        } else y = ie("body");
+        ZD(y, t, f);
+      }
+      let x, v;
+      e = WD(e);
+      try {
+        x = await BD(e);
+      } catch (t) {
+        x = new ID("error"), v = t;
+      }
+      const k = y.select(g).node(),
+        w = x.type,
+        T = k.firstChild,
+        C = T.firstChild,
+        E = FD.includes(w) ? x.renderer.getClasses(e, x) : {},
+        S = VD(h, w, E, u),
+        A = document.createElement("style");
+      A.innerHTML = S, T.insertBefore(A, C);
+      try {
+        await x.renderer.draw(e, t, Lx, x);
+      } catch (n) {
+        throw LD.draw(e, t, Lx), n;
+      }
+      eL(
+        w,
+        y.select(`${g} svg`),
+        null == (s = (a = x.db).getAccTitle) ? void 0 : s.call(a),
+        null == (l = (o = x.db).getAccDescription) ? void 0 : l.call(o),
+      ), y.select(`[id="${t}"]`).selectAll("foreignobject > *").attr("xmlns", jD);
+      let D = y.select(g).node().innerHTML;
+      if (tb.debug("config.arrowMarkerAbsolute", h.arrowMarkerAbsolute), D = GD(D, m, cb(h.arrowMarkerAbsolute)), m) {
+        const t = y.select(g + " svg").node();
+        D = XD(D, t);
+      } else b || (D = vl.sanitize(D, { ADD_TAGS: zD, ADD_ATTR: UD }));
+      if (void 0 !== n) {
+        switch (w) {
+          case "flowchart":
+          case "flowchart-v2":
+            n(D, yC.bindFunctions);
+            break;
+          case "gantt":
+            n(D, iE.bindFunctions);
+            break;
+          case "class":
+          case "classDiagram":
+            n(D, Cw.bindFunctions);
+            break;
+          default:
+            n(D);
+        }
+      } else tb.debug("CB = undefined!");
+      dS();
+      const L = ie(m ? p : g).node();
+      if (L && "remove" in L && L.remove(), v) throw v;
+      return D;
+    },
+    parse: function(t, e) {
+      return ND(), new ID(t, e).parse(t, e);
+    },
+    parseAsync: async function(t, e) {
+      return ND(), (await BD(t, e)).parse(t, e);
+    },
+    parseDirective: function(t, e, n, i) {
+      try {
+        if (void 0 !== e) {
+          switch (e = e.trim(), n) {
+            case "open_directive":
+              JD = {};
+              break;
+            case "type_directive":
+              if (!JD) throw new Error("currentDirective is undefined");
+              JD.type = e.toLowerCase();
+              break;
+            case "arg_directive":
+              if (!JD) throw new Error("currentDirective is undefined");
+              JD.args = JSON.parse(e);
+              break;
+            case "close_directive":
+              tL(t, JD, i), JD = void 0;
+          }
+        }
+      } catch (t) {
+        tb.error(`Error while rendering sequenceDiagram directive: ${e} jison context: ${n}`), tb.error(t.message);
+      }
+    },
+    initialize: function(t = {}) {
+      var e;
+      (null == t ? void 0 : t.fontFamily) && !(null == (e = t.themeVariables) ? void 0 : e.fontFamily)
+      && (t.themeVariables = { fontFamily: t.fontFamily }),
+        $x(t),
+        (null == t ? void 0 : t.theme) && t.theme in xb
+          ? t.themeVariables = xb[t.theme].getThemeVariables(t.themeVariables)
+          : t && (t.themeVariables = xb.default.getThemeVariables(t.themeVariables));
+      const n = "object" == typeof t ? Rx(t) : Px();
+      eb(n.logLevel), ND();
+    },
+    getConfig: jx,
+    setConfig: Yx,
+    getSiteConfig: Px,
+    updateSiteConfig: t => (Mx = lx(Mx, t), Fx(Mx, Bx), Mx),
+    reset: () => {
+      Wx();
+    },
+    globalReset: () => {
+      Wx(Ox);
+    },
+    defaultConfig: Ox,
+  });
+  eb(jx().logLevel), Wx(jx());
+  let iL = !1;
+  const rL = (t, e, n) => {
+      tb.warn(t),
+        Ax(t)
+          ? (n && n(t.str, t.hash), e.push({ ...t, message: t.str, error: t }))
+          : (n && n(t), t instanceof Error && e.push({ str: t.message, message: t.message, hash: t.name, error: t }));
+    },
+    aL = function(t, e, n) {
+      const i = nL.getConfig();
+      let r;
+      if (t && (uL.sequenceConfig = t), tb.debug((n ? "" : "No ") + "Callback function found"), void 0 === e) {
+        r = document.querySelectorAll(".mermaid");
+      } else if ("string" == typeof e) r = document.querySelectorAll(e);
+      else if (e instanceof HTMLElement) r = [e];
+      else {
+        if (!(e instanceof NodeList)) throw new Error("Invalid argument nodes for mermaid.init");
+        r = e;
+      }
+      tb.debug(`Found ${r.length} diagrams`),
+        void 0 !== (null == t ? void 0 : t.startOnLoad)
+        && (tb.debug("Start On Load: " + (null == t ? void 0 : t.startOnLoad)),
+          nL.updateSiteConfig({ startOnLoad: null == t ? void 0 : t.startOnLoad }));
+      const a = new Dx.initIdGenerator(i.deterministicIds, i.deterministicIDSeed);
+      let s;
+      const o = [];
+      for (const t of Array.from(r)) {
+        /*! Check if previously processed */
+        if (tb.info("Rendering diagram: " + t.id), t.getAttribute("data-processed")) continue;
+        t.setAttribute("data-processed", "true");
+        const e = `mermaid-${a.next()}`;
+        s = t.innerHTML, s = Dx.entityDecode(s).trim().replace(/<br\s*\/?>/gi, "<br/>");
+        const i = Dx.detectInit(s);
+        i && tb.debug("Detected early reinit: ", i);
+        try {
+          nL.render(e, s, (i, r) => {
+            t.innerHTML = i, void 0 !== n && n(e), r && r(t);
+          }, t);
+        } catch (t) {
+          rL(t, o, uL.parseError);
+        }
+      }
+      if (o.length > 0) throw o[0];
+    },
+    sL = async function(t, e, n) {
+      const i = nL.getConfig();
+      let r;
+      if (t && (uL.sequenceConfig = t), tb.debug((n ? "" : "No ") + "Callback function found"), void 0 === e) {
+        r = document.querySelectorAll(".mermaid");
+      } else if ("string" == typeof e) r = document.querySelectorAll(e);
+      else if (e instanceof HTMLElement) r = [e];
+      else {
+        if (!(e instanceof NodeList)) throw new Error("Invalid argument nodes for mermaid.init");
+        r = e;
+      }
+      tb.debug(`Found ${r.length} diagrams`),
+        void 0 !== (null == t ? void 0 : t.startOnLoad)
+        && (tb.debug("Start On Load: " + (null == t ? void 0 : t.startOnLoad)),
+          nL.updateSiteConfig({ startOnLoad: null == t ? void 0 : t.startOnLoad }));
+      const a = new Dx.initIdGenerator(i.deterministicIds, i.deterministicIDSeed);
+      let s;
+      const o = [];
+      for (const t of Array.from(r)) {
+        /*! Check if previously processed */
+        if (tb.info("Rendering diagram: " + t.id), t.getAttribute("data-processed")) continue;
+        t.setAttribute("data-processed", "true");
+        const e = `mermaid-${a.next()}`;
+        s = t.innerHTML, s = Dx.entityDecode(s).trim().replace(/<br\s*\/?>/gi, "<br/>");
+        const i = Dx.detectInit(s);
+        i && tb.debug("Detected early reinit: ", i);
+        try {
+          await nL.renderAsync(e, s, (i, r) => {
+            t.innerHTML = i, void 0 !== n && n(e), r && r(t);
+          }, t);
+        } catch (t) {
+          rL(t, o, uL.parseError);
+        }
+      }
+      if (o.length > 0) throw o[0];
+    },
+    oL = function() {
+      if (uL.startOnLoad) {
+        const { startOnLoad: t } = nL.getConfig();
+        t && uL.init();
+      }
+    };
+  "undefined" != typeof document
+    /*!
+	   * Wait for document loaded before starting the execution
+	   */
+    && window.addEventListener("load", oL, !1);
+  const lL = [];
+  let cL = !1;
+  const hL = async () => {
+      if (!cL) {
+        for (cL = !0; lL.length > 0;) {
+          const t = lL.shift();
+          if (t) {
+            try {
+              await t();
+            } catch (t) {
+              tb.error("Error executing queue", t);
+            }
+          }
+        }
+        cL = !1;
+      }
+    },
+    uL = {
+      startOnLoad: !0,
+      diagrams: {},
+      mermaidAPI: nL,
+      parse: t => nL.parse(t, uL.parseError),
+      parseAsync: t =>
+        new Promise((e, n) => {
+          lL.push(() =>
+            new Promise((i, r) => {
+              nL.parseAsync(t, uL.parseError).then(t => {
+                i(t), e(t);
+              }, t => {
+                tb.error("Error parsing", t), r(t), n(t);
+              });
+            })
+          ), hL();
+        }),
+      render: nL.render,
+      renderAsync: (t, e, n, i) =>
+        new Promise((r, a) => {
+          lL.push(() =>
+            new Promise((s, o) => {
+              nL.renderAsync(t, e, n, i).then(t => {
+                s(t), r(t);
+              }, t => {
+                tb.error("Error parsing", t), o(t), a(t);
+              });
+            })
+          ), hL();
+        }),
+      init: async function(t, e, n) {
+        try {
+          iL ? await sL(t, e, n) : aL(t, e, n);
+        } catch (t) {
+          tb.warn("Syntax Error rendering"), Ax(t) && tb.warn(t.str), uL.parseError && uL.parseError(t);
+        }
+      },
+      initThrowsErrors: aL,
+      initThrowsErrorsAsync: sL,
+      registerExternalDiagrams: async (t, { lazyLoad: e = !0 } = {}) => {
+        e
+          ? (t => {
+            for (const { id: e, detector: n, loader: i } of t) sx(e, n, i);
+          })(t)
+          : await (async t => {
+            tb.debug(`Loading ${t.length} external diagrams`);
+            const e = await Promise.allSettled(t.map(async ({ id: t, detector: e, loader: n }) => {
+                const { diagram: i } = await n();
+                yv(t, i, e);
+              })),
+              n = e.filter(t => "rejected" === t.status);
+            if (n.length > 0) {
+              tb.error(`Failed to load ${n.length} external diagrams`);
+              for (const t of n) tb.error(t);
+              throw new Error(`Failed to load ${n.length} external diagrams`);
+            }
+          })(t), iL = !0;
+      },
+      initialize: function(t) {
+        nL.initialize(t);
+      },
+      parseError: void 0,
+      contentLoaded: oL,
+      setParseErrorHandler: function(t) {
+        uL.parseError = t;
+      },
+    },
+    dL = {
+      id: "mermaid",
+      init: function(t) {
+        let { ...e } = t.getConfig().mermaid || {};
+        uL.mermaidAPI.initialize({ startOnLoad: !1, ...e });
+        const n = t.getRevealElement().querySelectorAll(".mermaid");
+        Array.from(n).forEach(function(t) {
+          var e = t.textContent.trim();
+          try {
+            uL.mermaidAPI.render(`mermaid-${Math.random().toString(36).substring(2)}`, e, function(e, n) {
+              t.innerHTML = e;
+            });
+          } catch (n) {
+            let i = "";
+            n?.str && (i = n.str),
+              n?.message && (i = n.message),
+              console.error(i, { error: n, graphDefinition: e, el: t }),
+              t.innerHTML = i;
+          }
+        });
+      },
+    };
+  return () => dL;
+});
diff --git a/assets/plugin/tailwindcss.min.js b/assets/plugin/tailwindcss.min.js
new file mode 100644
index 00000000..415dbc1c
--- /dev/null
+++ b/assets/plugin/tailwindcss.min.js
@@ -0,0 +1,16716 @@
+(() => {
+  var Hb = Object.create;
+  var ii = Object.defineProperty;
+  var Yb = Object.getOwnPropertyDescriptor;
+  var Qb = Object.getOwnPropertyNames;
+  var Jb = Object.getPrototypeOf, Xb = Object.prototype.hasOwnProperty;
+  var Hl = r => ii(r, "__esModule", { value: !0 });
+  var Yl = r => {
+    if (typeof require != "undefined") return require(r);
+    throw new Error("Dynamic require of \"" + r + "\" is not supported");
+  };
+  var C = (r, e) => () => (r && (e = r(r = 0)), e);
+  var v = (r, e) => () => (e || r((e = { exports: {} }).exports, e), e.exports),
+    Ce = (r, e) => {
+      Hl(r);
+      for (var t in e) ii(r, t, { get: e[t], enumerable: !0 });
+    },
+    Kb = (r, e, t) => {
+      if (e && typeof e == "object" || typeof e == "function") {
+        for (let i of Qb(e)) {
+          !Xb.call(r, i) && i !== "default"
+            && ii(r, i, { get: () => e[i], enumerable: !(t = Yb(e, i)) || t.enumerable });
+        }
+      }
+      return r;
+    },
+    K = r =>
+      Kb(
+        Hl(ii(
+          r != null ? Hb(Jb(r)) : {},
+          "default",
+          r && r.__esModule && "default" in r
+            ? { get: () => r.default, enumerable: !0 }
+            : { value: r, enumerable: !0 },
+        )),
+        r,
+      );
+  var m,
+    l = C(() => {
+      m = { platform: "", env: {}, versions: { node: "14.17.6" } };
+    });
+  var Zb,
+    ie,
+    je = C(() => {
+      l();
+      Zb = 0, ie = { readFileSync: r => self[r] || "", statSync: () => ({ mtimeMs: Zb++ }) };
+    });
+  var zn = v((pE, Jl) => {
+    l();
+    "use strict";
+    var Ql = class {
+      constructor(e = {}) {
+        if (!(e.maxSize && e.maxSize > 0)) throw new TypeError("`maxSize` must be a number greater than 0");
+        if (typeof e.maxAge == "number" && e.maxAge === 0) {
+          throw new TypeError("`maxAge` must be a number greater than 0");
+        }
+        this.maxSize = e.maxSize,
+          this.maxAge = e.maxAge || 1 / 0,
+          this.onEviction = e.onEviction,
+          this.cache = new Map(),
+          this.oldCache = new Map(),
+          this._size = 0;
+      }
+      _emitEvictions(e) {
+        if (typeof this.onEviction == "function") for (let [t, i] of e) this.onEviction(t, i.value);
+      }
+      _deleteIfExpired(e, t) {
+        return typeof t.expiry == "number" && t.expiry <= Date.now()
+          ? (typeof this.onEviction == "function" && this.onEviction(e, t.value), this.delete(e))
+          : !1;
+      }
+      _getOrDeleteIfExpired(e, t) {
+        if (this._deleteIfExpired(e, t) === !1) return t.value;
+      }
+      _getItemValue(e, t) {
+        return t.expiry ? this._getOrDeleteIfExpired(e, t) : t.value;
+      }
+      _peek(e, t) {
+        let i = t.get(e);
+        return this._getItemValue(e, i);
+      }
+      _set(e, t) {
+        this.cache.set(e, t),
+          this._size++,
+          this._size >= this.maxSize
+          && (this._size = 0, this._emitEvictions(this.oldCache), this.oldCache = this.cache, this.cache = new Map());
+      }
+      _moveToRecent(e, t) {
+        this.oldCache.delete(e), this._set(e, t);
+      }
+      *_entriesAscending() {
+        for (let e of this.oldCache) {
+          let [t, i] = e;
+          this.cache.has(t) || this._deleteIfExpired(t, i) === !1 && (yield e);
+        }
+        for (let e of this.cache) {
+          let [t, i] = e;
+          this._deleteIfExpired(t, i) === !1 && (yield e);
+        }
+      }
+      get(e) {
+        if (this.cache.has(e)) {
+          let t = this.cache.get(e);
+          return this._getItemValue(e, t);
+        }
+        if (this.oldCache.has(e)) {
+          let t = this.oldCache.get(e);
+          if (this._deleteIfExpired(e, t) === !1) return this._moveToRecent(e, t), t.value;
+        }
+      }
+      set(e, t, { maxAge: i = this.maxAge === 1 / 0 ? void 0 : Date.now() + this.maxAge } = {}) {
+        this.cache.has(e) ? this.cache.set(e, { value: t, maxAge: i }) : this._set(e, { value: t, expiry: i });
+      }
+      has(e) {
+        return this.cache.has(e)
+          ? !this._deleteIfExpired(e, this.cache.get(e))
+          : this.oldCache.has(e)
+          ? !this._deleteIfExpired(e, this.oldCache.get(e))
+          : !1;
+      }
+      peek(e) {
+        if (this.cache.has(e)) return this._peek(e, this.cache);
+        if (this.oldCache.has(e)) return this._peek(e, this.oldCache);
+      }
+      delete(e) {
+        let t = this.cache.delete(e);
+        return t && this._size--, this.oldCache.delete(e) || t;
+      }
+      clear() {
+        this.cache.clear(), this.oldCache.clear(), this._size = 0;
+      }
+      resize(e) {
+        if (!(e && e > 0)) throw new TypeError("`maxSize` must be a number greater than 0");
+        let t = [...this._entriesAscending()], i = t.length - e;
+        i < 0
+          ? (this.cache = new Map(t), this.oldCache = new Map(), this._size = t.length)
+          : (i > 0 && this._emitEvictions(t.slice(0, i)),
+            this.oldCache = new Map(t.slice(i)),
+            this.cache = new Map(),
+            this._size = 0), this.maxSize = e;
+      }
+      *keys() {
+        for (let [e] of this) yield e;
+      }
+      *values() {
+        for (let [, e] of this) yield e;
+      }
+      *[Symbol.iterator]() {
+        for (let e of this.cache) {
+          let [t, i] = e;
+          this._deleteIfExpired(t, i) === !1 && (yield [t, i.value]);
+        }
+        for (let e of this.oldCache) {
+          let [t, i] = e;
+          this.cache.has(t) || this._deleteIfExpired(t, i) === !1 && (yield [t, i.value]);
+        }
+      }
+      *entriesDescending() {
+        let e = [...this.cache];
+        for (let t = e.length - 1; t >= 0; --t) {
+          let i = e[t], [n, s] = i;
+          this._deleteIfExpired(n, s) === !1 && (yield [n, s.value]);
+        }
+        e = [...this.oldCache];
+        for (let t = e.length - 1; t >= 0; --t) {
+          let i = e[t], [n, s] = i;
+          this.cache.has(n) || this._deleteIfExpired(n, s) === !1 && (yield [n, s.value]);
+        }
+      }
+      *entriesAscending() {
+        for (let [e, t] of this._entriesAscending()) yield [e, t.value];
+      }
+      get size() {
+        if (!this._size) return this.oldCache.size;
+        let e = 0;
+        for (let t of this.oldCache.keys()) this.cache.has(t) || e++;
+        return Math.min(this._size + e, this.maxSize);
+      }
+    };
+    Jl.exports = Ql;
+  });
+  var Xl,
+    Kl = C(() => {
+      l();
+      Xl = r => r && r._hash;
+    });
+  function ni(r) {
+    return Xl(r, { ignoreUnknown: !0 });
+  }
+  var Zl = C(() => {
+    l();
+    Kl();
+  });
+  function Je(r) {
+    if (r = `${r}`, r === "0") return "0";
+    if (/^[+-]?(\d+|\d*\.\d+)(e[+-]?\d+)?(%|\w+)?$/.test(r)) return r.replace(/^[+-]?/, t => t === "-" ? "" : "-");
+    let e = ["var", "calc", "min", "max", "clamp"];
+    for (let t of e) if (r.includes(`${t}(`)) return `calc(${r} * -1)`;
+  }
+  var si = C(() => {
+    l();
+  });
+  var eu,
+    tu = C(() => {
+      l();
+      eu = [
+        "preflight",
+        "container",
+        "accessibility",
+        "pointerEvents",
+        "visibility",
+        "position",
+        "inset",
+        "isolation",
+        "zIndex",
+        "order",
+        "gridColumn",
+        "gridColumnStart",
+        "gridColumnEnd",
+        "gridRow",
+        "gridRowStart",
+        "gridRowEnd",
+        "float",
+        "clear",
+        "margin",
+        "boxSizing",
+        "lineClamp",
+        "display",
+        "aspectRatio",
+        "height",
+        "maxHeight",
+        "minHeight",
+        "width",
+        "minWidth",
+        "maxWidth",
+        "flex",
+        "flexShrink",
+        "flexGrow",
+        "flexBasis",
+        "tableLayout",
+        "captionSide",
+        "borderCollapse",
+        "borderSpacing",
+        "transformOrigin",
+        "translate",
+        "rotate",
+        "skew",
+        "scale",
+        "transform",
+        "animation",
+        "cursor",
+        "touchAction",
+        "userSelect",
+        "resize",
+        "scrollSnapType",
+        "scrollSnapAlign",
+        "scrollSnapStop",
+        "scrollMargin",
+        "scrollPadding",
+        "listStylePosition",
+        "listStyleType",
+        "listStyleImage",
+        "appearance",
+        "columns",
+        "breakBefore",
+        "breakInside",
+        "breakAfter",
+        "gridAutoColumns",
+        "gridAutoFlow",
+        "gridAutoRows",
+        "gridTemplateColumns",
+        "gridTemplateRows",
+        "flexDirection",
+        "flexWrap",
+        "placeContent",
+        "placeItems",
+        "alignContent",
+        "alignItems",
+        "justifyContent",
+        "justifyItems",
+        "gap",
+        "space",
+        "divideWidth",
+        "divideStyle",
+        "divideColor",
+        "divideOpacity",
+        "placeSelf",
+        "alignSelf",
+        "justifySelf",
+        "overflow",
+        "overscrollBehavior",
+        "scrollBehavior",
+        "textOverflow",
+        "hyphens",
+        "whitespace",
+        "wordBreak",
+        "borderRadius",
+        "borderWidth",
+        "borderStyle",
+        "borderColor",
+        "borderOpacity",
+        "backgroundColor",
+        "backgroundOpacity",
+        "backgroundImage",
+        "gradientColorStops",
+        "boxDecorationBreak",
+        "backgroundSize",
+        "backgroundAttachment",
+        "backgroundClip",
+        "backgroundPosition",
+        "backgroundRepeat",
+        "backgroundOrigin",
+        "fill",
+        "stroke",
+        "strokeWidth",
+        "objectFit",
+        "objectPosition",
+        "padding",
+        "textAlign",
+        "textIndent",
+        "verticalAlign",
+        "fontFamily",
+        "fontSize",
+        "fontWeight",
+        "textTransform",
+        "fontStyle",
+        "fontVariantNumeric",
+        "lineHeight",
+        "letterSpacing",
+        "textColor",
+        "textOpacity",
+        "textDecoration",
+        "textDecorationColor",
+        "textDecorationStyle",
+        "textDecorationThickness",
+        "textUnderlineOffset",
+        "fontSmoothing",
+        "placeholderColor",
+        "placeholderOpacity",
+        "caretColor",
+        "accentColor",
+        "opacity",
+        "backgroundBlendMode",
+        "mixBlendMode",
+        "boxShadow",
+        "boxShadowColor",
+        "outlineStyle",
+        "outlineWidth",
+        "outlineOffset",
+        "outlineColor",
+        "ringWidth",
+        "ringColor",
+        "ringOpacity",
+        "ringOffsetWidth",
+        "ringOffsetColor",
+        "blur",
+        "brightness",
+        "contrast",
+        "dropShadow",
+        "grayscale",
+        "hueRotate",
+        "invert",
+        "saturate",
+        "sepia",
+        "filter",
+        "backdropBlur",
+        "backdropBrightness",
+        "backdropContrast",
+        "backdropGrayscale",
+        "backdropHueRotate",
+        "backdropInvert",
+        "backdropOpacity",
+        "backdropSaturate",
+        "backdropSepia",
+        "backdropFilter",
+        "transitionProperty",
+        "transitionDelay",
+        "transitionDuration",
+        "transitionTimingFunction",
+        "willChange",
+        "content",
+      ];
+    });
+  function ru(r, e) {
+    return r === void 0
+      ? e
+      : Array.isArray(r)
+      ? r
+      : [...new Set(e.filter(i => r !== !1 && r[i] !== !1).concat(Object.keys(r).filter(i => r[i] !== !1)))];
+  }
+  var iu = C(() => {
+    l();
+  });
+  var nu = {};
+  Ce(nu, { default: () => Ae });
+  var Ae,
+    ai = C(() => {
+      l();
+      Ae = new Proxy({}, { get: () => String });
+    });
+  function Vn(r, e, t) {
+    typeof m != "undefined" && m.env.JEST_WORKER_ID || t && su.has(t)
+      || (t && su.add(t), console.warn(""), e.forEach(i => console.warn(r, "-", i)));
+  }
+  function Un(r) {
+    return Ae.dim(r);
+  }
+  var su,
+    N,
+    Oe = C(() => {
+      l();
+      ai();
+      su = new Set();
+      N = {
+        info(r, e) {
+          Vn(Ae.bold(Ae.cyan("info")), ...Array.isArray(r) ? [r] : [e, r]);
+        },
+        warn(r, e) {
+          Vn(Ae.bold(Ae.yellow("warn")), ...Array.isArray(r) ? [r] : [e, r]);
+        },
+        risk(r, e) {
+          Vn(Ae.bold(Ae.magenta("risk")), ...Array.isArray(r) ? [r] : [e, r]);
+        },
+      };
+    });
+  var au = {};
+  Ce(au, { default: () => Wn });
+  function rr({ version: r, from: e, to: t }) {
+    N.warn(`${e}-color-renamed`, [
+      `As of Tailwind CSS ${r}, \`${e}\` has been renamed to \`${t}\`.`,
+      "Update your configuration file to silence this warning.",
+    ]);
+  }
+  var Wn,
+    Gn = C(() => {
+      l();
+      Oe();
+      Wn = {
+        inherit: "inherit",
+        current: "currentColor",
+        transparent: "transparent",
+        black: "#000",
+        white: "#fff",
+        slate: {
+          50: "#f8fafc",
+          100: "#f1f5f9",
+          200: "#e2e8f0",
+          300: "#cbd5e1",
+          400: "#94a3b8",
+          500: "#64748b",
+          600: "#475569",
+          700: "#334155",
+          800: "#1e293b",
+          900: "#0f172a",
+          950: "#020617",
+        },
+        gray: {
+          50: "#f9fafb",
+          100: "#f3f4f6",
+          200: "#e5e7eb",
+          300: "#d1d5db",
+          400: "#9ca3af",
+          500: "#6b7280",
+          600: "#4b5563",
+          700: "#374151",
+          800: "#1f2937",
+          900: "#111827",
+          950: "#030712",
+        },
+        zinc: {
+          50: "#fafafa",
+          100: "#f4f4f5",
+          200: "#e4e4e7",
+          300: "#d4d4d8",
+          400: "#a1a1aa",
+          500: "#71717a",
+          600: "#52525b",
+          700: "#3f3f46",
+          800: "#27272a",
+          900: "#18181b",
+          950: "#09090b",
+        },
+        neutral: {
+          50: "#fafafa",
+          100: "#f5f5f5",
+          200: "#e5e5e5",
+          300: "#d4d4d4",
+          400: "#a3a3a3",
+          500: "#737373",
+          600: "#525252",
+          700: "#404040",
+          800: "#262626",
+          900: "#171717",
+          950: "#0a0a0a",
+        },
+        stone: {
+          50: "#fafaf9",
+          100: "#f5f5f4",
+          200: "#e7e5e4",
+          300: "#d6d3d1",
+          400: "#a8a29e",
+          500: "#78716c",
+          600: "#57534e",
+          700: "#44403c",
+          800: "#292524",
+          900: "#1c1917",
+          950: "#0c0a09",
+        },
+        red: {
+          50: "#fef2f2",
+          100: "#fee2e2",
+          200: "#fecaca",
+          300: "#fca5a5",
+          400: "#f87171",
+          500: "#ef4444",
+          600: "#dc2626",
+          700: "#b91c1c",
+          800: "#991b1b",
+          900: "#7f1d1d",
+          950: "#450a0a",
+        },
+        orange: {
+          50: "#fff7ed",
+          100: "#ffedd5",
+          200: "#fed7aa",
+          300: "#fdba74",
+          400: "#fb923c",
+          500: "#f97316",
+          600: "#ea580c",
+          700: "#c2410c",
+          800: "#9a3412",
+          900: "#7c2d12",
+          950: "#431407",
+        },
+        amber: {
+          50: "#fffbeb",
+          100: "#fef3c7",
+          200: "#fde68a",
+          300: "#fcd34d",
+          400: "#fbbf24",
+          500: "#f59e0b",
+          600: "#d97706",
+          700: "#b45309",
+          800: "#92400e",
+          900: "#78350f",
+          950: "#451a03",
+        },
+        yellow: {
+          50: "#fefce8",
+          100: "#fef9c3",
+          200: "#fef08a",
+          300: "#fde047",
+          400: "#facc15",
+          500: "#eab308",
+          600: "#ca8a04",
+          700: "#a16207",
+          800: "#854d0e",
+          900: "#713f12",
+          950: "#422006",
+        },
+        lime: {
+          50: "#f7fee7",
+          100: "#ecfccb",
+          200: "#d9f99d",
+          300: "#bef264",
+          400: "#a3e635",
+          500: "#84cc16",
+          600: "#65a30d",
+          700: "#4d7c0f",
+          800: "#3f6212",
+          900: "#365314",
+          950: "#1a2e05",
+        },
+        green: {
+          50: "#f0fdf4",
+          100: "#dcfce7",
+          200: "#bbf7d0",
+          300: "#86efac",
+          400: "#4ade80",
+          500: "#22c55e",
+          600: "#16a34a",
+          700: "#15803d",
+          800: "#166534",
+          900: "#14532d",
+          950: "#052e16",
+        },
+        emerald: {
+          50: "#ecfdf5",
+          100: "#d1fae5",
+          200: "#a7f3d0",
+          300: "#6ee7b7",
+          400: "#34d399",
+          500: "#10b981",
+          600: "#059669",
+          700: "#047857",
+          800: "#065f46",
+          900: "#064e3b",
+          950: "#022c22",
+        },
+        teal: {
+          50: "#f0fdfa",
+          100: "#ccfbf1",
+          200: "#99f6e4",
+          300: "#5eead4",
+          400: "#2dd4bf",
+          500: "#14b8a6",
+          600: "#0d9488",
+          700: "#0f766e",
+          800: "#115e59",
+          900: "#134e4a",
+          950: "#042f2e",
+        },
+        cyan: {
+          50: "#ecfeff",
+          100: "#cffafe",
+          200: "#a5f3fc",
+          300: "#67e8f9",
+          400: "#22d3ee",
+          500: "#06b6d4",
+          600: "#0891b2",
+          700: "#0e7490",
+          800: "#155e75",
+          900: "#164e63",
+          950: "#083344",
+        },
+        sky: {
+          50: "#f0f9ff",
+          100: "#e0f2fe",
+          200: "#bae6fd",
+          300: "#7dd3fc",
+          400: "#38bdf8",
+          500: "#0ea5e9",
+          600: "#0284c7",
+          700: "#0369a1",
+          800: "#075985",
+          900: "#0c4a6e",
+          950: "#082f49",
+        },
+        blue: {
+          50: "#eff6ff",
+          100: "#dbeafe",
+          200: "#bfdbfe",
+          300: "#93c5fd",
+          400: "#60a5fa",
+          500: "#3b82f6",
+          600: "#2563eb",
+          700: "#1d4ed8",
+          800: "#1e40af",
+          900: "#1e3a8a",
+          950: "#172554",
+        },
+        indigo: {
+          50: "#eef2ff",
+          100: "#e0e7ff",
+          200: "#c7d2fe",
+          300: "#a5b4fc",
+          400: "#818cf8",
+          500: "#6366f1",
+          600: "#4f46e5",
+          700: "#4338ca",
+          800: "#3730a3",
+          900: "#312e81",
+          950: "#1e1b4b",
+        },
+        violet: {
+          50: "#f5f3ff",
+          100: "#ede9fe",
+          200: "#ddd6fe",
+          300: "#c4b5fd",
+          400: "#a78bfa",
+          500: "#8b5cf6",
+          600: "#7c3aed",
+          700: "#6d28d9",
+          800: "#5b21b6",
+          900: "#4c1d95",
+          950: "#2e1065",
+        },
+        purple: {
+          50: "#faf5ff",
+          100: "#f3e8ff",
+          200: "#e9d5ff",
+          300: "#d8b4fe",
+          400: "#c084fc",
+          500: "#a855f7",
+          600: "#9333ea",
+          700: "#7e22ce",
+          800: "#6b21a8",
+          900: "#581c87",
+          950: "#3b0764",
+        },
+        fuchsia: {
+          50: "#fdf4ff",
+          100: "#fae8ff",
+          200: "#f5d0fe",
+          300: "#f0abfc",
+          400: "#e879f9",
+          500: "#d946ef",
+          600: "#c026d3",
+          700: "#a21caf",
+          800: "#86198f",
+          900: "#701a75",
+          950: "#4a044e",
+        },
+        pink: {
+          50: "#fdf2f8",
+          100: "#fce7f3",
+          200: "#fbcfe8",
+          300: "#f9a8d4",
+          400: "#f472b6",
+          500: "#ec4899",
+          600: "#db2777",
+          700: "#be185d",
+          800: "#9d174d",
+          900: "#831843",
+          950: "#500724",
+        },
+        rose: {
+          50: "#fff1f2",
+          100: "#ffe4e6",
+          200: "#fecdd3",
+          300: "#fda4af",
+          400: "#fb7185",
+          500: "#f43f5e",
+          600: "#e11d48",
+          700: "#be123c",
+          800: "#9f1239",
+          900: "#881337",
+          950: "#4c0519",
+        },
+        get lightBlue() {
+          return rr({ version: "v2.2", from: "lightBlue", to: "sky" }), this.sky;
+        },
+        get warmGray() {
+          return rr({ version: "v3.0", from: "warmGray", to: "stone" }), this.stone;
+        },
+        get trueGray() {
+          return rr({ version: "v3.0", from: "trueGray", to: "neutral" }), this.neutral;
+        },
+        get coolGray() {
+          return rr({ version: "v3.0", from: "coolGray", to: "gray" }), this.gray;
+        },
+        get blueGray() {
+          return rr({ version: "v3.0", from: "blueGray", to: "slate" }), this.slate;
+        },
+      };
+    });
+  function Hn(r, ...e) {
+    for (let t of e) {
+      for (let i in t) r?.hasOwnProperty?.(i) || (r[i] = t[i]);
+      for (let i of Object.getOwnPropertySymbols(t)) r?.hasOwnProperty?.(i) || (r[i] = t[i]);
+    }
+    return r;
+  }
+  var ou = C(() => {
+    l();
+  });
+  function Xe(r) {
+    if (Array.isArray(r)) return r;
+    let e = r.split("[").length - 1, t = r.split("]").length - 1;
+    if (e !== t) throw new Error(`Path is invalid. Has unbalanced brackets: ${r}`);
+    return r.split(/\.(?![^\[]*\])|[\[\]]/g).filter(Boolean);
+  }
+  var oi = C(() => {
+    l();
+  });
+  function J(r, e) {
+    return li.future.includes(e)
+      ? r.future === "all" || (r?.future?.[e] ?? lu[e] ?? !1)
+      : li.experimental.includes(e)
+      ? r.experimental === "all" || (r?.experimental?.[e] ?? lu[e] ?? !1)
+      : !1;
+  }
+  function uu(r) {
+    return r.experimental === "all"
+      ? li.experimental
+      : Object.keys(r?.experimental ?? {}).filter(e => li.experimental.includes(e) && r.experimental[e]);
+  }
+  function fu(r) {
+    if (m.env.JEST_WORKER_ID === void 0 && uu(r).length > 0) {
+      let e = uu(r).map(t => Ae.yellow(t)).join(", ");
+      N.warn("experimental-flags-enabled", [
+        `You have enabled experimental features: ${e}`,
+        "Experimental features in Tailwind CSS are not covered by semver, may introduce breaking changes, and can change at any time.",
+      ]);
+    }
+  }
+  var lu,
+    li,
+    De = C(() => {
+      l();
+      ai();
+      Oe();
+      lu = {
+        optimizeUniversalDefaults: !1,
+        generalizedModifiers: !0,
+        get disableColorOpacityUtilitiesByDefault() {
+          return !1;
+        },
+        get relativeContentPathsByDefault() {
+          return !1;
+        },
+      },
+        li = {
+          future: [
+            "hoverOnlyWhenSupported",
+            "respectDefaultRingColorOpacity",
+            "disableColorOpacityUtilitiesByDefault",
+            "relativeContentPathsByDefault",
+          ],
+          experimental: ["optimizeUniversalDefaults", "generalizedModifiers"],
+        };
+    });
+  function cu(r) {
+    (() => {
+      if (r.purge || !r.content || !Array.isArray(r.content) && !(typeof r.content == "object" && r.content !== null)) {
+        return !1;
+      }
+      if (Array.isArray(r.content)) {
+        return r.content.every(t =>
+          typeof t == "string" ? !0 : !(typeof t?.raw != "string" || t?.extension && typeof t?.extension != "string")
+        );
+      }
+      if (typeof r.content == "object" && r.content !== null) {
+        if (Object.keys(r.content).some(t => !["files", "relative", "extract", "transform"].includes(t))) return !1;
+        if (Array.isArray(r.content.files)) {
+          if (
+            !r.content.files.every(t =>
+              typeof t == "string"
+                ? !0
+                : !(typeof t?.raw != "string" || t?.extension && typeof t?.extension != "string")
+            )
+          ) return !1;
+          if (typeof r.content.extract == "object") {
+            for (let t of Object.values(r.content.extract)) if (typeof t != "function") return !1;
+          } else if (!(r.content.extract === void 0 || typeof r.content.extract == "function")) return !1;
+          if (typeof r.content.transform == "object") {
+            for (let t of Object.values(r.content.transform)) if (typeof t != "function") return !1;
+          } else if (!(r.content.transform === void 0 || typeof r.content.transform == "function")) return !1;
+          if (typeof r.content.relative != "boolean" && typeof r.content.relative != "undefined") return !1;
+        }
+        return !0;
+      }
+      return !1;
+    })()
+    || N.warn("purge-deprecation", [
+      "The `purge`/`content` options have changed in Tailwind CSS v3.0.",
+      "Update your configuration file to eliminate this warning.",
+      "https://tailwindcss.com/docs/upgrade-guide#configure-content-sources",
+    ]),
+      r.safelist = (() => {
+        let { content: t, purge: i, safelist: n } = r;
+        return Array.isArray(n)
+          ? n
+          : Array.isArray(t?.safelist)
+          ? t.safelist
+          : Array.isArray(i?.safelist)
+          ? i.safelist
+          : Array.isArray(i?.options?.safelist)
+          ? i.options.safelist
+          : [];
+      })(),
+      r.blocklist = (() => {
+        let { blocklist: t } = r;
+        if (Array.isArray(t)) {
+          if (t.every(i => typeof i == "string")) return t;
+          N.warn("blocklist-invalid", [
+            "The `blocklist` option must be an array of strings.",
+            "https://tailwindcss.com/docs/content-configuration#discarding-classes",
+          ]);
+        }
+        return [];
+      })(),
+      typeof r.prefix == "function"
+        ? (N.warn("prefix-function", [
+          "As of Tailwind CSS v3.0, `prefix` cannot be a function.",
+          "Update `prefix` in your configuration to be a string to eliminate this warning.",
+          "https://tailwindcss.com/docs/upgrade-guide#prefix-cannot-be-a-function",
+        ]),
+          r.prefix = "")
+        : r.prefix = r.prefix ?? "",
+      r.content = {
+        relative: (() => {
+          let { content: t } = r;
+          return t?.relative ? t.relative : J(r, "relativeContentPathsByDefault");
+        })(),
+        files: (() => {
+          let { content: t, purge: i } = r;
+          return Array.isArray(i)
+            ? i
+            : Array.isArray(i?.content)
+            ? i.content
+            : Array.isArray(t)
+            ? t
+            : Array.isArray(t?.content)
+            ? t.content
+            : Array.isArray(t?.files)
+            ? t.files
+            : [];
+        })(),
+        extract: (() => {
+          let t = (() =>
+              r.purge?.extract
+                ? r.purge.extract
+                : r.content?.extract
+                ? r.content.extract
+                : r.purge?.extract?.DEFAULT
+                ? r.purge.extract.DEFAULT
+                : r.content?.extract?.DEFAULT
+                ? r.content.extract.DEFAULT
+                : r.purge?.options?.extractors
+                ? r.purge.options.extractors
+                : r.content?.options?.extractors
+                ? r.content.options.extractors
+                : {})(),
+            i = {},
+            n = (() => {
+              if (r.purge?.options?.defaultExtractor) return r.purge.options.defaultExtractor;
+              if (r.content?.options?.defaultExtractor) return r.content.options.defaultExtractor;
+            })();
+          if (n !== void 0 && (i.DEFAULT = n), typeof t == "function") i.DEFAULT = t;
+          else if (Array.isArray(t)) for (let { extensions: s, extractor: a } of t ?? []) for (let o of s) i[o] = a;
+          else typeof t == "object" && t !== null && Object.assign(i, t);
+          return i;
+        })(),
+        transform: (() => {
+          let t = (() =>
+              r.purge?.transform
+                ? r.purge.transform
+                : r.content?.transform
+                ? r.content.transform
+                : r.purge?.transform?.DEFAULT
+                ? r.purge.transform.DEFAULT
+                : r.content?.transform?.DEFAULT
+                ? r.content.transform.DEFAULT
+                : {})(),
+            i = {};
+          return typeof t == "function" && (i.DEFAULT = t),
+            typeof t == "object" && t !== null && Object.assign(i, t),
+            i;
+        })(),
+      };
+    for (let t of r.content.files) {
+      if (typeof t == "string" && /{([^,]*?)}/g.test(t)) {
+        N.warn("invalid-glob-braces", [
+          `The glob pattern ${Un(t)} in your Tailwind CSS configuration is invalid.`,
+          `Update it to ${Un(t.replace(/{([^,]*?)}/g, "$1"))} to silence this warning.`,
+        ]);
+        break;
+      }
+    }
+    return r;
+  }
+  var pu = C(() => {
+    l();
+    De();
+    Oe();
+  });
+  function se(r) {
+    if (Object.prototype.toString.call(r) !== "[object Object]") return !1;
+    let e = Object.getPrototypeOf(r);
+    return e === null || e === Object.prototype;
+  }
+  var vt = C(() => {
+    l();
+  });
+  function Ke(r) {
+    return Array.isArray(r)
+      ? r.map(e => Ke(e))
+      : typeof r == "object" && r !== null
+      ? Object.fromEntries(Object.entries(r).map(([e, t]) => [e, Ke(t)]))
+      : r;
+  }
+  var ui = C(() => {
+    l();
+  });
+  function pt(r) {
+    return r.replace(/\\,/g, "\\2c ");
+  }
+  var fi = C(() => {
+    l();
+  });
+  var Yn,
+    du = C(() => {
+      l();
+      Yn = {
+        aliceblue: [240, 248, 255],
+        antiquewhite: [250, 235, 215],
+        aqua: [0, 255, 255],
+        aquamarine: [127, 255, 212],
+        azure: [240, 255, 255],
+        beige: [245, 245, 220],
+        bisque: [255, 228, 196],
+        black: [0, 0, 0],
+        blanchedalmond: [255, 235, 205],
+        blue: [0, 0, 255],
+        blueviolet: [138, 43, 226],
+        brown: [165, 42, 42],
+        burlywood: [222, 184, 135],
+        cadetblue: [95, 158, 160],
+        chartreuse: [127, 255, 0],
+        chocolate: [210, 105, 30],
+        coral: [255, 127, 80],
+        cornflowerblue: [100, 149, 237],
+        cornsilk: [255, 248, 220],
+        crimson: [220, 20, 60],
+        cyan: [0, 255, 255],
+        darkblue: [0, 0, 139],
+        darkcyan: [0, 139, 139],
+        darkgoldenrod: [184, 134, 11],
+        darkgray: [169, 169, 169],
+        darkgreen: [0, 100, 0],
+        darkgrey: [169, 169, 169],
+        darkkhaki: [189, 183, 107],
+        darkmagenta: [139, 0, 139],
+        darkolivegreen: [85, 107, 47],
+        darkorange: [255, 140, 0],
+        darkorchid: [153, 50, 204],
+        darkred: [139, 0, 0],
+        darksalmon: [233, 150, 122],
+        darkseagreen: [143, 188, 143],
+        darkslateblue: [72, 61, 139],
+        darkslategray: [47, 79, 79],
+        darkslategrey: [47, 79, 79],
+        darkturquoise: [0, 206, 209],
+        darkviolet: [148, 0, 211],
+        deeppink: [255, 20, 147],
+        deepskyblue: [0, 191, 255],
+        dimgray: [105, 105, 105],
+        dimgrey: [105, 105, 105],
+        dodgerblue: [30, 144, 255],
+        firebrick: [178, 34, 34],
+        floralwhite: [255, 250, 240],
+        forestgreen: [34, 139, 34],
+        fuchsia: [255, 0, 255],
+        gainsboro: [220, 220, 220],
+        ghostwhite: [248, 248, 255],
+        gold: [255, 215, 0],
+        goldenrod: [218, 165, 32],
+        gray: [128, 128, 128],
+        green: [0, 128, 0],
+        greenyellow: [173, 255, 47],
+        grey: [128, 128, 128],
+        honeydew: [240, 255, 240],
+        hotpink: [255, 105, 180],
+        indianred: [205, 92, 92],
+        indigo: [75, 0, 130],
+        ivory: [255, 255, 240],
+        khaki: [240, 230, 140],
+        lavender: [230, 230, 250],
+        lavenderblush: [255, 240, 245],
+        lawngreen: [124, 252, 0],
+        lemonchiffon: [255, 250, 205],
+        lightblue: [173, 216, 230],
+        lightcoral: [240, 128, 128],
+        lightcyan: [224, 255, 255],
+        lightgoldenrodyellow: [250, 250, 210],
+        lightgray: [211, 211, 211],
+        lightgreen: [144, 238, 144],
+        lightgrey: [211, 211, 211],
+        lightpink: [255, 182, 193],
+        lightsalmon: [255, 160, 122],
+        lightseagreen: [32, 178, 170],
+        lightskyblue: [135, 206, 250],
+        lightslategray: [119, 136, 153],
+        lightslategrey: [119, 136, 153],
+        lightsteelblue: [176, 196, 222],
+        lightyellow: [255, 255, 224],
+        lime: [0, 255, 0],
+        limegreen: [50, 205, 50],
+        linen: [250, 240, 230],
+        magenta: [255, 0, 255],
+        maroon: [128, 0, 0],
+        mediumaquamarine: [102, 205, 170],
+        mediumblue: [0, 0, 205],
+        mediumorchid: [186, 85, 211],
+        mediumpurple: [147, 112, 219],
+        mediumseagreen: [60, 179, 113],
+        mediumslateblue: [123, 104, 238],
+        mediumspringgreen: [0, 250, 154],
+        mediumturquoise: [72, 209, 204],
+        mediumvioletred: [199, 21, 133],
+        midnightblue: [25, 25, 112],
+        mintcream: [245, 255, 250],
+        mistyrose: [255, 228, 225],
+        moccasin: [255, 228, 181],
+        navajowhite: [255, 222, 173],
+        navy: [0, 0, 128],
+        oldlace: [253, 245, 230],
+        olive: [128, 128, 0],
+        olivedrab: [107, 142, 35],
+        orange: [255, 165, 0],
+        orangered: [255, 69, 0],
+        orchid: [218, 112, 214],
+        palegoldenrod: [238, 232, 170],
+        palegreen: [152, 251, 152],
+        paleturquoise: [175, 238, 238],
+        palevioletred: [219, 112, 147],
+        papayawhip: [255, 239, 213],
+        peachpuff: [255, 218, 185],
+        peru: [205, 133, 63],
+        pink: [255, 192, 203],
+        plum: [221, 160, 221],
+        powderblue: [176, 224, 230],
+        purple: [128, 0, 128],
+        rebeccapurple: [102, 51, 153],
+        red: [255, 0, 0],
+        rosybrown: [188, 143, 143],
+        royalblue: [65, 105, 225],
+        saddlebrown: [139, 69, 19],
+        salmon: [250, 128, 114],
+        sandybrown: [244, 164, 96],
+        seagreen: [46, 139, 87],
+        seashell: [255, 245, 238],
+        sienna: [160, 82, 45],
+        silver: [192, 192, 192],
+        skyblue: [135, 206, 235],
+        slateblue: [106, 90, 205],
+        slategray: [112, 128, 144],
+        slategrey: [112, 128, 144],
+        snow: [255, 250, 250],
+        springgreen: [0, 255, 127],
+        steelblue: [70, 130, 180],
+        tan: [210, 180, 140],
+        teal: [0, 128, 128],
+        thistle: [216, 191, 216],
+        tomato: [255, 99, 71],
+        turquoise: [64, 224, 208],
+        violet: [238, 130, 238],
+        wheat: [245, 222, 179],
+        white: [255, 255, 255],
+        whitesmoke: [245, 245, 245],
+        yellow: [255, 255, 0],
+        yellowgreen: [154, 205, 50],
+      };
+    });
+  function ir(r, { loose: e = !1 } = {}) {
+    if (typeof r != "string") return null;
+    if (r = r.trim(), r === "transparent") return { mode: "rgb", color: ["0", "0", "0"], alpha: "0" };
+    if (r in Yn) return { mode: "rgb", color: Yn[r].map(s => s.toString()) };
+    let t = r.replace(tw, (s, a, o, u, c) => ["#", a, a, o, o, u, u, c ? c + c : ""].join("")).match(ew);
+    if (t !== null) {
+      return {
+        mode: "rgb",
+        color: [parseInt(t[1], 16), parseInt(t[2], 16), parseInt(t[3], 16)].map(s => s.toString()),
+        alpha: t[4] ? (parseInt(t[4], 16) / 255).toString() : void 0,
+      };
+    }
+    let i = r.match(rw) ?? r.match(iw);
+    if (i === null) return null;
+    let n = [i[2], i[3], i[4]].filter(Boolean).map(s => s.toString());
+    return n.length === 2 && n[0].startsWith("var(")
+      ? { mode: i[1], color: [n[0]], alpha: n[1] }
+      : !e && n.length !== 3 || n.length < 3 && !n.some(s => /^var\(.*?\)$/.test(s))
+      ? null
+      : { mode: i[1], color: n, alpha: i[5]?.toString?.() };
+  }
+  function Qn({ mode: r, color: e, alpha: t }) {
+    let i = t !== void 0;
+    return r === "rgba" || r === "hsla"
+      ? `${r}(${e.join(", ")}${i ? `, ${t}` : ""})`
+      : `${r}(${e.join(" ")}${i ? ` / ${t}` : ""})`;
+  }
+  var ew,
+    tw,
+    Ze,
+    ci,
+    hu,
+    et,
+    rw,
+    iw,
+    Jn = C(() => {
+      l();
+      du();
+      ew = /^#([a-f\d]{2})([a-f\d]{2})([a-f\d]{2})([a-f\d]{2})?$/i,
+        tw = /^#([a-f\d])([a-f\d])([a-f\d])([a-f\d])?$/i,
+        Ze = /(?:\d+|\d*\.\d+)%?/,
+        ci = /(?:\s*,\s*|\s+)/,
+        hu = /\s*[,/]\s*/,
+        et = /var\(--(?:[^ )]*?)\)/,
+        rw = new RegExp(
+          `^(rgba?)\\(\\s*(${Ze.source}|${et.source})(?:${ci.source}(${Ze.source}|${et.source}))?(?:${ci.source}(${Ze.source}|${et.source}))?(?:${hu.source}(${Ze.source}|${et.source}))?\\s*\\)$`,
+        ),
+        iw = new RegExp(
+          `^(hsla?)\\(\\s*((?:${Ze.source})(?:deg|rad|grad|turn)?|${et.source})(?:${ci.source}(${Ze.source}|${et.source}))?(?:${ci.source}(${Ze.source}|${et.source}))?(?:${hu.source}(${Ze.source}|${et.source}))?\\s*\\)$`,
+        );
+    });
+  function Ie(r, e, t) {
+    if (typeof r == "function") return r({ opacityValue: e });
+    let i = ir(r, { loose: !0 });
+    return i === null ? t : Qn({ ...i, alpha: e });
+  }
+  function oe({ color: r, property: e, variable: t }) {
+    let i = [].concat(e);
+    if (typeof r == "function") {
+      return { [t]: "1", ...Object.fromEntries(i.map(s => [s, r({ opacityVariable: t, opacityValue: `var(${t})` })])) };
+    }
+    let n = ir(r);
+    return n === null
+      ? Object.fromEntries(i.map(s => [s, r]))
+      : n.alpha !== void 0
+      ? Object.fromEntries(i.map(s => [s, r]))
+      : { [t]: "1", ...Object.fromEntries(i.map(s => [s, Qn({ ...n, alpha: `var(${t})` })])) };
+  }
+  var nr = C(() => {
+    l();
+    Jn();
+  });
+  function le(r, e) {
+    let t = [], i = [], n = 0, s = !1;
+    for (let a = 0; a < r.length; a++) {
+      let o = r[a];
+      t.length === 0 && o === e[0] && !s && (e.length === 1 || r.slice(a, a + e.length) === e)
+      && (i.push(r.slice(n, a)), n = a + e.length),
+        s ? s = !1 : o === "\\" && (s = !0),
+        o === "(" || o === "[" || o === "{"
+          ? t.push(o)
+          : (o === ")" && t[t.length - 1] === "(" || o === "]" && t[t.length - 1] === "["
+            || o === "}" && t[t.length - 1] === "{") && t.pop();
+    }
+    return i.push(r.slice(n)), i;
+  }
+  var sr = C(() => {
+    l();
+  });
+  function pi(r) {
+    return le(r, ",").map(t => {
+      let i = t.trim(), n = { raw: i }, s = i.split(sw), a = new Set();
+      for (let o of s) {
+        mu.lastIndex = 0,
+          !a.has("KEYWORD") && nw.has(o)
+            ? (n.keyword = o, a.add("KEYWORD"))
+            : mu.test(o)
+            ? a.has("X")
+              ? a.has("Y")
+                ? a.has("BLUR") ? a.has("SPREAD") || (n.spread = o, a.add("SPREAD")) : (n.blur = o, a.add("BLUR"))
+                : (n.y = o, a.add("Y"))
+              : (n.x = o, a.add("X"))
+            : n.color
+            ? (n.unknown || (n.unknown = []), n.unknown.push(o))
+            : n.color = o;
+      }
+      return n.valid = n.x !== void 0 && n.y !== void 0, n;
+    });
+  }
+  function gu(r) {
+    return r.map(e => e.valid ? [e.keyword, e.x, e.y, e.blur, e.spread, e.color].filter(Boolean).join(" ") : e.raw)
+      .join(", ");
+  }
+  var nw,
+    sw,
+    mu,
+    Xn = C(() => {
+      l();
+      sr();
+      nw = new Set(["inset", "inherit", "initial", "revert", "unset"]),
+        sw = /\ +(?![^(]*\))/g,
+        mu = /^-?(\d+|\.\d+)(.*?)$/g;
+    });
+  function Kn(r) {
+    return aw.some(e => new RegExp(`^${e}\\(.*\\)`).test(r));
+  }
+  function V(r, e = !0) {
+    return r.startsWith("--")
+      ? `var(${r})`
+      : r.includes("url(")
+      ? r.split(/(url\(.*?\))/g).filter(Boolean).map(t => /^url\(.*?\)$/.test(t) ? t : V(t, !1)).join("")
+      : (r = r.replace(/([^\\])_+/g, (t, i) => i + " ".repeat(t.length - 1)).replace(/^_/g, " ").replace(/\\_/g, "_"),
+        e && (r = r.trim()),
+        r = r.replace(/(calc|min|max|clamp)\(.+\)/g, t => {
+          let i = [];
+          return t.replace(/var\((--.+?)[,)]/g, (n, s) => (i.push(s), n.replace(s, yu))).replace(
+            /(-?\d*\.?\d(?!\b-\d.+[,)](?![^+\-/*])\D)(?:%|[a-z]+)?|\))([+\-/*])/g,
+            "$1 $2 ",
+          ).replace(ow, () => i.shift());
+        }),
+        r);
+  }
+  function Zn(r) {
+    return r.startsWith("url(");
+  }
+  function es(r) {
+    return !isNaN(Number(r)) || Kn(r);
+  }
+  function ar(r) {
+    return r.endsWith("%") && es(r.slice(0, -1)) || Kn(r);
+  }
+  function or(r) {
+    return r === "0" || new RegExp(`^[+-]?[0-9]*.?[0-9]+(?:[eE][+-]?[0-9]+)?${uw}$`).test(r) || Kn(r);
+  }
+  function bu(r) {
+    return fw.has(r);
+  }
+  function wu(r) {
+    let e = pi(V(r));
+    for (let t of e) if (!t.valid) return !1;
+    return !0;
+  }
+  function vu(r) {
+    let e = 0;
+    return le(r, "_").every(i => (i = V(i), i.startsWith("var(") ? !0 : ir(i, { loose: !0 }) !== null ? (e++, !0) : !1))
+      ? e > 0
+      : !1;
+  }
+  function xu(r) {
+    let e = 0;
+    return le(r, ",").every(
+        i => (i = V(i),
+          i.startsWith("var(")
+            ? !0
+            : Zn(i) || pw(i) || ["element(", "image(", "cross-fade(", "image-set("].some(n => i.startsWith(n))
+            ? (e++, !0)
+            : !1),
+      )
+      ? e > 0
+      : !1;
+  }
+  function pw(r) {
+    r = V(r);
+    for (let e of cw) if (r.startsWith(`${e}(`)) return !0;
+    return !1;
+  }
+  function ku(r) {
+    let e = 0;
+    return le(r, "_").every(i => (i = V(i), i.startsWith("var(") ? !0 : dw.has(i) || or(i) || ar(i) ? (e++, !0) : !1))
+      ? e > 0
+      : !1;
+  }
+  function Su(r) {
+    let e = 0;
+    return le(r, ",").every(
+        i => (i = V(i),
+          i.startsWith("var(")
+            ? !0
+            : i.includes(" ") && !/(['"])([^"']+)\1/g.test(i) || /^\d/g.test(i)
+            ? !1
+            : (e++, !0)),
+      )
+      ? e > 0
+      : !1;
+  }
+  function _u(r) {
+    return hw.has(r);
+  }
+  function Cu(r) {
+    return mw.has(r);
+  }
+  function Au(r) {
+    return gw.has(r);
+  }
+  var aw,
+    yu,
+    ow,
+    lw,
+    uw,
+    fw,
+    cw,
+    dw,
+    hw,
+    mw,
+    gw,
+    lr = C(() => {
+      l();
+      Jn();
+      Xn();
+      sr();
+      aw = ["min", "max", "clamp", "calc"];
+      yu = "--tw-placeholder", ow = new RegExp(yu, "g");
+      lw = [
+        "cm",
+        "mm",
+        "Q",
+        "in",
+        "pc",
+        "pt",
+        "px",
+        "em",
+        "ex",
+        "ch",
+        "rem",
+        "lh",
+        "rlh",
+        "vw",
+        "vh",
+        "vmin",
+        "vmax",
+        "vb",
+        "vi",
+        "svw",
+        "svh",
+        "lvw",
+        "lvh",
+        "dvw",
+        "dvh",
+        "cqw",
+        "cqh",
+        "cqi",
+        "cqb",
+        "cqmin",
+        "cqmax",
+      ], uw = `(?:${lw.join("|")})`;
+      fw = new Set(["thin", "medium", "thick"]);
+      cw = new Set([
+        "linear-gradient",
+        "radial-gradient",
+        "repeating-linear-gradient",
+        "repeating-radial-gradient",
+        "conic-gradient",
+      ]);
+      dw = new Set(["center", "top", "right", "bottom", "left"]);
+      hw = new Set([
+        "serif",
+        "sans-serif",
+        "monospace",
+        "cursive",
+        "fantasy",
+        "system-ui",
+        "ui-serif",
+        "ui-sans-serif",
+        "ui-monospace",
+        "ui-rounded",
+        "math",
+        "emoji",
+        "fangsong",
+      ]);
+      mw = new Set(["xx-small", "x-small", "small", "medium", "large", "x-large", "x-large", "xxx-large"]);
+      gw = new Set(["larger", "smaller"]);
+    });
+  function Ou(r) {
+    let e = ["cover", "contain"];
+    return le(r, ",").every(t => {
+      let i = le(t, "_").filter(Boolean);
+      return i.length === 1 && e.includes(i[0])
+        ? !0
+        : i.length !== 1 && i.length !== 2
+        ? !1
+        : i.every(n => or(n) || ar(n) || n === "auto");
+    });
+  }
+  var Eu = C(() => {
+    l();
+    lr();
+    sr();
+  });
+  function Tu(r, e) {
+    r.walkClasses(t => {
+      t.value = e(t.value), t.raws && t.raws.value && (t.raws.value = pt(t.raws.value));
+    });
+  }
+  function Pu(r, e) {
+    if (!tt(r)) return;
+    let t = r.slice(1, -1);
+    if (!!e(t)) return V(t);
+  }
+  function yw(r, e = {}, t) {
+    let i = e[r];
+    if (i !== void 0) return Je(i);
+    if (tt(r)) {
+      let n = Pu(r, t);
+      return n === void 0 ? void 0 : Je(n);
+    }
+  }
+  function di(r, e = {}, { validate: t = () => !0 } = {}) {
+    let i = e.values?.[r];
+    return i !== void 0 ? i : e.supportsNegativeValues && r.startsWith("-") ? yw(r.slice(1), e.values, t) : Pu(r, t);
+  }
+  function tt(r) {
+    return r.startsWith("[") && r.endsWith("]");
+  }
+  function Du(r) {
+    let e = r.lastIndexOf("/");
+    return e === -1 || e === r.length - 1
+      ? [r, void 0]
+      : tt(r) && !r.includes("]/[")
+      ? [r, void 0]
+      : [r.slice(0, e), r.slice(e + 1)];
+  }
+  function xt(r) {
+    if (typeof r == "string" && r.includes("<alpha-value>")) {
+      let e = r;
+      return ({ opacityValue: t = 1 }) => e.replace("<alpha-value>", t);
+    }
+    return r;
+  }
+  function Iu(r) {
+    return V(r.slice(1, -1));
+  }
+  function bw(r, e = {}, { tailwindConfig: t = {} } = {}) {
+    if (e.values?.[r] !== void 0) return xt(e.values?.[r]);
+    let [i, n] = Du(r);
+    if (n !== void 0) {
+      let s = e.values?.[i] ?? (tt(i) ? i.slice(1, -1) : void 0);
+      return s === void 0
+        ? void 0
+        : (s = xt(s), tt(n) ? Ie(s, Iu(n)) : t.theme?.opacity?.[n] === void 0 ? void 0 : Ie(s, t.theme.opacity[n]));
+    }
+    return di(r, e, { validate: vu });
+  }
+  function ww(r, e = {}) {
+    return e.values?.[r];
+  }
+  function he(r) {
+    return (e, t) => di(e, t, { validate: r });
+  }
+  function vw(r, e) {
+    let t = r.indexOf(e);
+    return t === -1 ? [void 0, r] : [r.slice(0, t), r.slice(t + 1)];
+  }
+  function rs(r, e, t, i) {
+    if (t.values && e in t.values) {
+      for (let { type: s } of r ?? []) {
+        let a = ts[s](e, t, { tailwindConfig: i });
+        if (a !== void 0) return [a, s, null];
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+    }
+    if (tt(e)) {
+      let s = e.slice(1, -1), [a, o] = vw(s, ":");
+      if (!/^[\w-_]+$/g.test(a)) o = s;
+      else if (a !== void 0 && !qu.includes(a)) return [];
+      if (o.length > 0 && qu.includes(a)) return [di(`[${o}]`, t), a, null];
+    }
+    let n = is(r, e, t, i);
+    for (let s of n) return s;
+    return [];
+  }
+  function* is(r, e, t, i) {
+    let n = J(i, "generalizedModifiers"), [s, a] = Du(e);
+    if (
+      n && t.modifiers != null
+        && (t.modifiers === "any" || typeof t.modifiers == "object" && (a && tt(a) || a in t.modifiers))
+      || (s = e, a = void 0),
+        a !== void 0 && s === "" && (s = "DEFAULT"),
+        a !== void 0 && typeof t.modifiers == "object"
+    ) {
+      let u = t.modifiers?.[a] ?? null;
+      u !== null ? a = u : tt(a) && (a = Iu(a));
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+      let c = ts[u](s, t, { tailwindConfig: i });
+      c !== void 0 && (yield [c, u, a ?? null]);
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+  var ts,
+    qu,
+    ur = C(() => {
+      l();
+      fi();
+      nr();
+      lr();
+      si();
+      Eu();
+      De();
+      ts = {
+        any: di,
+        color: bw,
+        url: he(Zn),
+        image: he(xu),
+        length: he(or),
+        percentage: he(ar),
+        position: he(ku),
+        lookup: ww,
+        "generic-name": he(_u),
+        "family-name": he(Su),
+        number: he(es),
+        "line-width": he(bu),
+        "absolute-size": he(Cu),
+        "relative-size": he(Au),
+        shadow: he(wu),
+        size: he(Ou),
+      }, qu = Object.keys(ts);
+    });
+  function L(r) {
+    return typeof r == "function" ? r({}) : r;
+  }
+  var ns = C(() => {
+    l();
+  });
+  function kt(r) {
+    return typeof r == "function";
+  }
+  function fr(r, ...e) {
+    let t = e.pop();
+    for (let i of e) {
+      for (let n in i) {
+        let s = t(r[n], i[n]);
+        s === void 0 ? se(r[n]) && se(i[n]) ? r[n] = fr({}, r[n], i[n], t) : r[n] = i[n] : r[n] = s;
+      }
+    }
+    return r;
+  }
+  function xw(r, ...e) {
+    return kt(r) ? r(...e) : r;
+  }
+  function kw(r) {
+    return r.reduce(
+      (e, { extend: t }) => fr(e, t, (i, n) => i === void 0 ? [n] : Array.isArray(i) ? [n, ...i] : [n, i]),
+      {},
+    );
+  }
+  function Sw(r) {
+    return { ...r.reduce((e, t) => Hn(e, t), {}), extend: kw(r) };
+  }
+  function Ru(r, e) {
+    if (Array.isArray(r) && se(r[0])) return r.concat(e);
+    if (Array.isArray(e) && se(e[0]) && se(r)) return [r, ...e];
+    if (Array.isArray(e)) return e;
+  }
+  function _w({ extend: r, ...e }) {
+    return fr(
+      e,
+      r,
+      (t, i) => !kt(t) && !i.some(kt) ? fr({}, t, ...i, Ru) : (n, s) => fr({}, ...[t, ...i].map(a => xw(a, n, s)), Ru),
+    );
+  }
+  function* Cw(r) {
+    let e = Xe(r);
+    if (e.length === 0 || (yield e, Array.isArray(r))) return;
+    let t = /^(.*?)\s*\/\s*([^/]+)$/, i = r.match(t);
+    if (i !== null) {
+      let [, n, s] = i, a = Xe(n);
+      a.alpha = s, yield a;
+    }
+  }
+  function Aw(r) {
+    let e = (t, i) => {
+      for (let n of Cw(t)) {
+        let s = 0, a = r;
+        for (; a != null && s < n.length;) {
+          a = a[n[s++]], a = kt(a) && (n.alpha === void 0 || s <= n.length - 1) ? a(e, ss) : a;
+        }
+        if (a !== void 0) {
+          if (n.alpha !== void 0) {
+            let o = xt(a);
+            return Ie(o, n.alpha, L(o));
+          }
+          return se(a) ? Ke(a) : a;
+        }
+      }
+      return i;
+    };
+    return Object.assign(e, { theme: e, ...ss }),
+      Object.keys(r).reduce((t, i) => (t[i] = kt(r[i]) ? r[i](e, ss) : r[i], t), {});
+  }
+  function Mu(r) {
+    let e = [];
+    return r.forEach(t => {
+      e = [...e, t];
+      let i = t?.plugins ?? [];
+      i.length !== 0 && i.forEach(n => {
+        n.__isOptionsFunction && (n = n()), e = [...e, ...Mu([n?.config ?? {}])];
+      });
+    }),
+      e;
+  }
+  function Ow(r) {
+    return [...r].reduceRight((t, i) => kt(i) ? i({ corePlugins: t }) : ru(i, t), eu);
+  }
+  function Ew(r) {
+    return [...r].reduceRight((t, i) => [...t, ...i], []);
+  }
+  function as(r) {
+    let e = [...Mu(r), { prefix: "", important: !1, separator: ":" }];
+    return cu(
+      Hn({
+        theme: Aw(_w(Sw(e.map(t => t?.theme ?? {})))),
+        corePlugins: Ow(e.map(t => t.corePlugins)),
+        plugins: Ew(r.map(t => t?.plugins ?? [])),
+      }, ...e),
+    );
+  }
+  var ss,
+    Fu = C(() => {
+      l();
+      si();
+      tu();
+      iu();
+      Gn();
+      ou();
+      oi();
+      pu();
+      vt();
+      ui();
+      ur();
+      nr();
+      ns();
+      ss = {
+        colors: Wn,
+        negative(r) {
+          return Object.keys(r).filter(e => r[e] !== "0").reduce((e, t) => {
+            let i = Je(r[t]);
+            return i !== void 0 && (e[`-${t}`] = i), e;
+          }, {});
+        },
+        breakpoints(r) {
+          return Object.keys(r).filter(e => typeof r[e] == "string").reduce(
+            (e, t) => ({ ...e, [`screen-${t}`]: r[t] }),
+            {},
+          );
+        },
+      };
+    });
+  var hi = v((m5, Nu) => {
+    l();
+    Nu.exports = {
+      content: [],
+      presets: [],
+      darkMode: "media",
+      theme: {
+        accentColor: ({ theme: r }) => ({ ...r("colors"), auto: "auto" }),
+        animation: {
+          none: "none",
+          spin: "spin 1s linear infinite",
+          ping: "ping 1s cubic-bezier(0, 0, 0.2, 1) infinite",
+          pulse: "pulse 2s cubic-bezier(0.4, 0, 0.6, 1) infinite",
+          bounce: "bounce 1s infinite",
+        },
+        aria: {
+          checked: "checked=\"true\"",
+          disabled: "disabled=\"true\"",
+          expanded: "expanded=\"true\"",
+          hidden: "hidden=\"true\"",
+          pressed: "pressed=\"true\"",
+          readonly: "readonly=\"true\"",
+          required: "required=\"true\"",
+          selected: "selected=\"true\"",
+        },
+        aspectRatio: { auto: "auto", square: "1 / 1", video: "16 / 9" },
+        backdropBlur: ({ theme: r }) => r("blur"),
+        backdropBrightness: ({ theme: r }) => r("brightness"),
+        backdropContrast: ({ theme: r }) => r("contrast"),
+        backdropGrayscale: ({ theme: r }) => r("grayscale"),
+        backdropHueRotate: ({ theme: r }) => r("hueRotate"),
+        backdropInvert: ({ theme: r }) => r("invert"),
+        backdropOpacity: ({ theme: r }) => r("opacity"),
+        backdropSaturate: ({ theme: r }) => r("saturate"),
+        backdropSepia: ({ theme: r }) => r("sepia"),
+        backgroundColor: ({ theme: r }) => r("colors"),
+        backgroundImage: {
+          none: "none",
+          "gradient-to-t": "linear-gradient(to top, var(--tw-gradient-stops))",
+          "gradient-to-tr": "linear-gradient(to top right, var(--tw-gradient-stops))",
+          "gradient-to-r": "linear-gradient(to right, var(--tw-gradient-stops))",
+          "gradient-to-br": "linear-gradient(to bottom right, var(--tw-gradient-stops))",
+          "gradient-to-b": "linear-gradient(to bottom, var(--tw-gradient-stops))",
+          "gradient-to-bl": "linear-gradient(to bottom left, var(--tw-gradient-stops))",
+          "gradient-to-l": "linear-gradient(to left, var(--tw-gradient-stops))",
+          "gradient-to-tl": "linear-gradient(to top left, var(--tw-gradient-stops))",
+        },
+        backgroundOpacity: ({ theme: r }) => r("opacity"),
+        backgroundPosition: {
+          bottom: "bottom",
+          center: "center",
+          left: "left",
+          "left-bottom": "left bottom",
+          "left-top": "left top",
+          right: "right",
+          "right-bottom": "right bottom",
+          "right-top": "right top",
+          top: "top",
+        },
+        backgroundSize: { auto: "auto", cover: "cover", contain: "contain" },
+        blur: {
+          0: "0",
+          none: "0",
+          sm: "4px",
+          DEFAULT: "8px",
+          md: "12px",
+          lg: "16px",
+          xl: "24px",
+          "2xl": "40px",
+          "3xl": "64px",
+        },
+        borderColor: ({ theme: r }) => ({ ...r("colors"), DEFAULT: r("colors.gray.200", "currentColor") }),
+        borderOpacity: ({ theme: r }) => r("opacity"),
+        borderRadius: {
+          none: "0px",
+          sm: "0.125rem",
+          DEFAULT: "0.25rem",
+          md: "0.375rem",
+          lg: "0.5rem",
+          xl: "0.75rem",
+          "2xl": "1rem",
+          "3xl": "1.5rem",
+          full: "9999px",
+        },
+        borderSpacing: ({ theme: r }) => ({ ...r("spacing") }),
+        borderWidth: { DEFAULT: "1px", 0: "0px", 2: "2px", 4: "4px", 8: "8px" },
+        boxShadow: {
+          sm: "0 1px 2px 0 rgb(0 0 0 / 0.05)",
+          DEFAULT: "0 1px 3px 0 rgb(0 0 0 / 0.1), 0 1px 2px -1px rgb(0 0 0 / 0.1)",
+          md: "0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1)",
+          lg: "0 10px 15px -3px rgb(0 0 0 / 0.1), 0 4px 6px -4px rgb(0 0 0 / 0.1)",
+          xl: "0 20px 25px -5px rgb(0 0 0 / 0.1), 0 8px 10px -6px rgb(0 0 0 / 0.1)",
+          "2xl": "0 25px 50px -12px rgb(0 0 0 / 0.25)",
+          inner: "inset 0 2px 4px 0 rgb(0 0 0 / 0.05)",
+          none: "none",
+        },
+        boxShadowColor: ({ theme: r }) => r("colors"),
+        brightness: {
+          0: "0",
+          50: ".5",
+          75: ".75",
+          90: ".9",
+          95: ".95",
+          100: "1",
+          105: "1.05",
+          110: "1.1",
+          125: "1.25",
+          150: "1.5",
+          200: "2",
+        },
+        caretColor: ({ theme: r }) => r("colors"),
+        colors: ({ colors: r }) => ({
+          inherit: r.inherit,
+          current: r.current,
+          transparent: r.transparent,
+          black: r.black,
+          white: r.white,
+          slate: r.slate,
+          gray: r.gray,
+          zinc: r.zinc,
+          neutral: r.neutral,
+          stone: r.stone,
+          red: r.red,
+          orange: r.orange,
+          amber: r.amber,
+          yellow: r.yellow,
+          lime: r.lime,
+          green: r.green,
+          emerald: r.emerald,
+          teal: r.teal,
+          cyan: r.cyan,
+          sky: r.sky,
+          blue: r.blue,
+          indigo: r.indigo,
+          violet: r.violet,
+          purple: r.purple,
+          fuchsia: r.fuchsia,
+          pink: r.pink,
+          rose: r.rose,
+        }),
+        columns: {
+          auto: "auto",
+          1: "1",
+          2: "2",
+          3: "3",
+          4: "4",
+          5: "5",
+          6: "6",
+          7: "7",
+          8: "8",
+          9: "9",
+          10: "10",
+          11: "11",
+          12: "12",
+          "3xs": "16rem",
+          "2xs": "18rem",
+          xs: "20rem",
+          sm: "24rem",
+          md: "28rem",
+          lg: "32rem",
+          xl: "36rem",
+          "2xl": "42rem",
+          "3xl": "48rem",
+          "4xl": "56rem",
+          "5xl": "64rem",
+          "6xl": "72rem",
+          "7xl": "80rem",
+        },
+        container: {},
+        content: { none: "none" },
+        contrast: { 0: "0", 50: ".5", 75: ".75", 100: "1", 125: "1.25", 150: "1.5", 200: "2" },
+        cursor: {
+          auto: "auto",
+          default: "default",
+          pointer: "pointer",
+          wait: "wait",
+          text: "text",
+          move: "move",
+          help: "help",
+          "not-allowed": "not-allowed",
+          none: "none",
+          "context-menu": "context-menu",
+          progress: "progress",
+          cell: "cell",
+          crosshair: "crosshair",
+          "vertical-text": "vertical-text",
+          alias: "alias",
+          copy: "copy",
+          "no-drop": "no-drop",
+          grab: "grab",
+          grabbing: "grabbing",
+          "all-scroll": "all-scroll",
+          "col-resize": "col-resize",
+          "row-resize": "row-resize",
+          "n-resize": "n-resize",
+          "e-resize": "e-resize",
+          "s-resize": "s-resize",
+          "w-resize": "w-resize",
+          "ne-resize": "ne-resize",
+          "nw-resize": "nw-resize",
+          "se-resize": "se-resize",
+          "sw-resize": "sw-resize",
+          "ew-resize": "ew-resize",
+          "ns-resize": "ns-resize",
+          "nesw-resize": "nesw-resize",
+          "nwse-resize": "nwse-resize",
+          "zoom-in": "zoom-in",
+          "zoom-out": "zoom-out",
+        },
+        divideColor: ({ theme: r }) => r("borderColor"),
+        divideOpacity: ({ theme: r }) => r("borderOpacity"),
+        divideWidth: ({ theme: r }) => r("borderWidth"),
+        dropShadow: {
+          sm: "0 1px 1px rgb(0 0 0 / 0.05)",
+          DEFAULT: ["0 1px 2px rgb(0 0 0 / 0.1)", "0 1px 1px rgb(0 0 0 / 0.06)"],
+          md: ["0 4px 3px rgb(0 0 0 / 0.07)", "0 2px 2px rgb(0 0 0 / 0.06)"],
+          lg: ["0 10px 8px rgb(0 0 0 / 0.04)", "0 4px 3px rgb(0 0 0 / 0.1)"],
+          xl: ["0 20px 13px rgb(0 0 0 / 0.03)", "0 8px 5px rgb(0 0 0 / 0.08)"],
+          "2xl": "0 25px 25px rgb(0 0 0 / 0.15)",
+          none: "0 0 #0000",
+        },
+        fill: ({ theme: r }) => ({ none: "none", ...r("colors") }),
+        flex: { 1: "1 1 0%", auto: "1 1 auto", initial: "0 1 auto", none: "none" },
+        flexBasis: ({ theme: r }) => ({
+          auto: "auto",
+          ...r("spacing"),
+          "1/2": "50%",
+          "1/3": "33.333333%",
+          "2/3": "66.666667%",
+          "1/4": "25%",
+          "2/4": "50%",
+          "3/4": "75%",
+          "1/5": "20%",
+          "2/5": "40%",
+          "3/5": "60%",
+          "4/5": "80%",
+          "1/6": "16.666667%",
+          "2/6": "33.333333%",
+          "3/6": "50%",
+          "4/6": "66.666667%",
+          "5/6": "83.333333%",
+          "1/12": "8.333333%",
+          "2/12": "16.666667%",
+          "3/12": "25%",
+          "4/12": "33.333333%",
+          "5/12": "41.666667%",
+          "6/12": "50%",
+          "7/12": "58.333333%",
+          "8/12": "66.666667%",
+          "9/12": "75%",
+          "10/12": "83.333333%",
+          "11/12": "91.666667%",
+          full: "100%",
+        }),
+        flexGrow: { 0: "0", DEFAULT: "1" },
+        flexShrink: { 0: "0", DEFAULT: "1" },
+        fontFamily: {
+          sans: [
+            "ui-sans-serif",
+            "system-ui",
+            "-apple-system",
+            "BlinkMacSystemFont",
+            "\"Segoe UI\"",
+            "Roboto",
+            "\"Helvetica Neue\"",
+            "Arial",
+            "\"Noto Sans\"",
+            "sans-serif",
+            "\"Apple Color Emoji\"",
+            "\"Segoe UI Emoji\"",
+            "\"Segoe UI Symbol\"",
+            "\"Noto Color Emoji\"",
+          ],
+          serif: ["ui-serif", "Georgia", "Cambria", "\"Times New Roman\"", "Times", "serif"],
+          mono: [
+            "ui-monospace",
+            "SFMono-Regular",
+            "Menlo",
+            "Monaco",
+            "Consolas",
+            "\"Liberation Mono\"",
+            "\"Courier New\"",
+            "monospace",
+          ],
+        },
+        fontSize: {
+          xs: ["0.75rem", { lineHeight: "1rem" }],
+          sm: ["0.875rem", { lineHeight: "1.25rem" }],
+          base: ["1rem", { lineHeight: "1.5rem" }],
+          lg: ["1.125rem", { lineHeight: "1.75rem" }],
+          xl: ["1.25rem", { lineHeight: "1.75rem" }],
+          "2xl": ["1.5rem", { lineHeight: "2rem" }],
+          "3xl": ["1.875rem", { lineHeight: "2.25rem" }],
+          "4xl": ["2.25rem", { lineHeight: "2.5rem" }],
+          "5xl": ["3rem", { lineHeight: "1" }],
+          "6xl": ["3.75rem", { lineHeight: "1" }],
+          "7xl": ["4.5rem", { lineHeight: "1" }],
+          "8xl": ["6rem", { lineHeight: "1" }],
+          "9xl": ["8rem", { lineHeight: "1" }],
+        },
+        fontWeight: {
+          thin: "100",
+          extralight: "200",
+          light: "300",
+          normal: "400",
+          medium: "500",
+          semibold: "600",
+          bold: "700",
+          extrabold: "800",
+          black: "900",
+        },
+        gap: ({ theme: r }) => r("spacing"),
+        gradientColorStops: ({ theme: r }) => r("colors"),
+        gradientColorStopPositions: {
+          "0%": "0%",
+          "5%": "5%",
+          "10%": "10%",
+          "15%": "15%",
+          "20%": "20%",
+          "25%": "25%",
+          "30%": "30%",
+          "35%": "35%",
+          "40%": "40%",
+          "45%": "45%",
+          "50%": "50%",
+          "55%": "55%",
+          "60%": "60%",
+          "65%": "65%",
+          "70%": "70%",
+          "75%": "75%",
+          "80%": "80%",
+          "85%": "85%",
+          "90%": "90%",
+          "95%": "95%",
+          "100%": "100%",
+        },
+        grayscale: { 0: "0", DEFAULT: "100%" },
+        gridAutoColumns: { auto: "auto", min: "min-content", max: "max-content", fr: "minmax(0, 1fr)" },
+        gridAutoRows: { auto: "auto", min: "min-content", max: "max-content", fr: "minmax(0, 1fr)" },
+        gridColumn: {
+          auto: "auto",
+          "span-1": "span 1 / span 1",
+          "span-2": "span 2 / span 2",
+          "span-3": "span 3 / span 3",
+          "span-4": "span 4 / span 4",
+          "span-5": "span 5 / span 5",
+          "span-6": "span 6 / span 6",
+          "span-7": "span 7 / span 7",
+          "span-8": "span 8 / span 8",
+          "span-9": "span 9 / span 9",
+          "span-10": "span 10 / span 10",
+          "span-11": "span 11 / span 11",
+          "span-12": "span 12 / span 12",
+          "span-full": "1 / -1",
+        },
+        gridColumnEnd: {
+          auto: "auto",
+          1: "1",
+          2: "2",
+          3: "3",
+          4: "4",
+          5: "5",
+          6: "6",
+          7: "7",
+          8: "8",
+          9: "9",
+          10: "10",
+          11: "11",
+          12: "12",
+          13: "13",
+        },
+        gridColumnStart: {
+          auto: "auto",
+          1: "1",
+          2: "2",
+          3: "3",
+          4: "4",
+          5: "5",
+          6: "6",
+          7: "7",
+          8: "8",
+          9: "9",
+          10: "10",
+          11: "11",
+          12: "12",
+          13: "13",
+        },
+        gridRow: {
+          auto: "auto",
+          "span-1": "span 1 / span 1",
+          "span-2": "span 2 / span 2",
+          "span-3": "span 3 / span 3",
+          "span-4": "span 4 / span 4",
+          "span-5": "span 5 / span 5",
+          "span-6": "span 6 / span 6",
+          "span-full": "1 / -1",
+        },
+        gridRowEnd: { auto: "auto", 1: "1", 2: "2", 3: "3", 4: "4", 5: "5", 6: "6", 7: "7" },
+        gridRowStart: { auto: "auto", 1: "1", 2: "2", 3: "3", 4: "4", 5: "5", 6: "6", 7: "7" },
+        gridTemplateColumns: {
+          none: "none",
+          1: "repeat(1, minmax(0, 1fr))",
+          2: "repeat(2, minmax(0, 1fr))",
+          3: "repeat(3, minmax(0, 1fr))",
+          4: "repeat(4, minmax(0, 1fr))",
+          5: "repeat(5, minmax(0, 1fr))",
+          6: "repeat(6, minmax(0, 1fr))",
+          7: "repeat(7, minmax(0, 1fr))",
+          8: "repeat(8, minmax(0, 1fr))",
+          9: "repeat(9, minmax(0, 1fr))",
+          10: "repeat(10, minmax(0, 1fr))",
+          11: "repeat(11, minmax(0, 1fr))",
+          12: "repeat(12, minmax(0, 1fr))",
+        },
+        gridTemplateRows: {
+          none: "none",
+          1: "repeat(1, minmax(0, 1fr))",
+          2: "repeat(2, minmax(0, 1fr))",
+          3: "repeat(3, minmax(0, 1fr))",
+          4: "repeat(4, minmax(0, 1fr))",
+          5: "repeat(5, minmax(0, 1fr))",
+          6: "repeat(6, minmax(0, 1fr))",
+        },
+        height: ({ theme: r }) => ({
+          auto: "auto",
+          ...r("spacing"),
+          "1/2": "50%",
+          "1/3": "33.333333%",
+          "2/3": "66.666667%",
+          "1/4": "25%",
+          "2/4": "50%",
+          "3/4": "75%",
+          "1/5": "20%",
+          "2/5": "40%",
+          "3/5": "60%",
+          "4/5": "80%",
+          "1/6": "16.666667%",
+          "2/6": "33.333333%",
+          "3/6": "50%",
+          "4/6": "66.666667%",
+          "5/6": "83.333333%",
+          full: "100%",
+          screen: "100vh",
+          min: "min-content",
+          max: "max-content",
+          fit: "fit-content",
+        }),
+        hueRotate: { 0: "0deg", 15: "15deg", 30: "30deg", 60: "60deg", 90: "90deg", 180: "180deg" },
+        inset: ({ theme: r }) => ({
+          auto: "auto",
+          ...r("spacing"),
+          "1/2": "50%",
+          "1/3": "33.333333%",
+          "2/3": "66.666667%",
+          "1/4": "25%",
+          "2/4": "50%",
+          "3/4": "75%",
+          full: "100%",
+        }),
+        invert: { 0: "0", DEFAULT: "100%" },
+        keyframes: {
+          spin: { to: { transform: "rotate(360deg)" } },
+          ping: { "75%, 100%": { transform: "scale(2)", opacity: "0" } },
+          pulse: { "50%": { opacity: ".5" } },
+          bounce: {
+            "0%, 100%": { transform: "translateY(-25%)", animationTimingFunction: "cubic-bezier(0.8,0,1,1)" },
+            "50%": { transform: "none", animationTimingFunction: "cubic-bezier(0,0,0.2,1)" },
+          },
+        },
+        letterSpacing: {
+          tighter: "-0.05em",
+          tight: "-0.025em",
+          normal: "0em",
+          wide: "0.025em",
+          wider: "0.05em",
+          widest: "0.1em",
+        },
+        lineHeight: {
+          none: "1",
+          tight: "1.25",
+          snug: "1.375",
+          normal: "1.5",
+          relaxed: "1.625",
+          loose: "2",
+          3: ".75rem",
+          4: "1rem",
+          5: "1.25rem",
+          6: "1.5rem",
+          7: "1.75rem",
+          8: "2rem",
+          9: "2.25rem",
+          10: "2.5rem",
+        },
+        listStyleType: { none: "none", disc: "disc", decimal: "decimal" },
+        listStyleImage: { none: "none" },
+        margin: ({ theme: r }) => ({ auto: "auto", ...r("spacing") }),
+        lineClamp: { 1: "1", 2: "2", 3: "3", 4: "4", 5: "5", 6: "6" },
+        maxHeight: ({ theme: r }) => ({
+          ...r("spacing"),
+          none: "none",
+          full: "100%",
+          screen: "100vh",
+          min: "min-content",
+          max: "max-content",
+          fit: "fit-content",
+        }),
+        maxWidth: ({ theme: r, breakpoints: e }) => ({
+          none: "none",
+          0: "0rem",
+          xs: "20rem",
+          sm: "24rem",
+          md: "28rem",
+          lg: "32rem",
+          xl: "36rem",
+          "2xl": "42rem",
+          "3xl": "48rem",
+          "4xl": "56rem",
+          "5xl": "64rem",
+          "6xl": "72rem",
+          "7xl": "80rem",
+          full: "100%",
+          min: "min-content",
+          max: "max-content",
+          fit: "fit-content",
+          prose: "65ch",
+          ...e(r("screens")),
+        }),
+        minHeight: {
+          0: "0px",
+          full: "100%",
+          screen: "100vh",
+          min: "min-content",
+          max: "max-content",
+          fit: "fit-content",
+        },
+        minWidth: { 0: "0px", full: "100%", min: "min-content", max: "max-content", fit: "fit-content" },
+        objectPosition: {
+          bottom: "bottom",
+          center: "center",
+          left: "left",
+          "left-bottom": "left bottom",
+          "left-top": "left top",
+          right: "right",
+          "right-bottom": "right bottom",
+          "right-top": "right top",
+          top: "top",
+        },
+        opacity: {
+          0: "0",
+          5: "0.05",
+          10: "0.1",
+          20: "0.2",
+          25: "0.25",
+          30: "0.3",
+          40: "0.4",
+          50: "0.5",
+          60: "0.6",
+          70: "0.7",
+          75: "0.75",
+          80: "0.8",
+          90: "0.9",
+          95: "0.95",
+          100: "1",
+        },
+        order: {
+          first: "-9999",
+          last: "9999",
+          none: "0",
+          1: "1",
+          2: "2",
+          3: "3",
+          4: "4",
+          5: "5",
+          6: "6",
+          7: "7",
+          8: "8",
+          9: "9",
+          10: "10",
+          11: "11",
+          12: "12",
+        },
+        outlineColor: ({ theme: r }) => r("colors"),
+        outlineOffset: { 0: "0px", 1: "1px", 2: "2px", 4: "4px", 8: "8px" },
+        outlineWidth: { 0: "0px", 1: "1px", 2: "2px", 4: "4px", 8: "8px" },
+        padding: ({ theme: r }) => r("spacing"),
+        placeholderColor: ({ theme: r }) => r("colors"),
+        placeholderOpacity: ({ theme: r }) => r("opacity"),
+        ringColor: ({ theme: r }) => ({ DEFAULT: r("colors.blue.500", "#3b82f6"), ...r("colors") }),
+        ringOffsetColor: ({ theme: r }) => r("colors"),
+        ringOffsetWidth: { 0: "0px", 1: "1px", 2: "2px", 4: "4px", 8: "8px" },
+        ringOpacity: ({ theme: r }) => ({ DEFAULT: "0.5", ...r("opacity") }),
+        ringWidth: { DEFAULT: "3px", 0: "0px", 1: "1px", 2: "2px", 4: "4px", 8: "8px" },
+        rotate: {
+          0: "0deg",
+          1: "1deg",
+          2: "2deg",
+          3: "3deg",
+          6: "6deg",
+          12: "12deg",
+          45: "45deg",
+          90: "90deg",
+          180: "180deg",
+        },
+        saturate: { 0: "0", 50: ".5", 100: "1", 150: "1.5", 200: "2" },
+        scale: {
+          0: "0",
+          50: ".5",
+          75: ".75",
+          90: ".9",
+          95: ".95",
+          100: "1",
+          105: "1.05",
+          110: "1.1",
+          125: "1.25",
+          150: "1.5",
+        },
+        screens: { sm: "640px", md: "768px", lg: "1024px", xl: "1280px", "2xl": "1536px" },
+        scrollMargin: ({ theme: r }) => ({ ...r("spacing") }),
+        scrollPadding: ({ theme: r }) => r("spacing"),
+        sepia: { 0: "0", DEFAULT: "100%" },
+        skew: { 0: "0deg", 1: "1deg", 2: "2deg", 3: "3deg", 6: "6deg", 12: "12deg" },
+        space: ({ theme: r }) => ({ ...r("spacing") }),
+        spacing: {
+          px: "1px",
+          0: "0px",
+          .5: "0.125rem",
+          1: "0.25rem",
+          1.5: "0.375rem",
+          2: "0.5rem",
+          2.5: "0.625rem",
+          3: "0.75rem",
+          3.5: "0.875rem",
+          4: "1rem",
+          5: "1.25rem",
+          6: "1.5rem",
+          7: "1.75rem",
+          8: "2rem",
+          9: "2.25rem",
+          10: "2.5rem",
+          11: "2.75rem",
+          12: "3rem",
+          14: "3.5rem",
+          16: "4rem",
+          20: "5rem",
+          24: "6rem",
+          28: "7rem",
+          32: "8rem",
+          36: "9rem",
+          40: "10rem",
+          44: "11rem",
+          48: "12rem",
+          52: "13rem",
+          56: "14rem",
+          60: "15rem",
+          64: "16rem",
+          72: "18rem",
+          80: "20rem",
+          96: "24rem",
+        },
+        stroke: ({ theme: r }) => ({ none: "none", ...r("colors") }),
+        strokeWidth: { 0: "0", 1: "1", 2: "2" },
+        supports: {},
+        data: {},
+        textColor: ({ theme: r }) => r("colors"),
+        textDecorationColor: ({ theme: r }) => r("colors"),
+        textDecorationThickness: {
+          auto: "auto",
+          "from-font": "from-font",
+          0: "0px",
+          1: "1px",
+          2: "2px",
+          4: "4px",
+          8: "8px",
+        },
+        textIndent: ({ theme: r }) => ({ ...r("spacing") }),
+        textOpacity: ({ theme: r }) => r("opacity"),
+        textUnderlineOffset: { auto: "auto", 0: "0px", 1: "1px", 2: "2px", 4: "4px", 8: "8px" },
+        transformOrigin: {
+          center: "center",
+          top: "top",
+          "top-right": "top right",
+          right: "right",
+          "bottom-right": "bottom right",
+          bottom: "bottom",
+          "bottom-left": "bottom left",
+          left: "left",
+          "top-left": "top left",
+        },
+        transitionDelay: {
+          0: "0s",
+          75: "75ms",
+          100: "100ms",
+          150: "150ms",
+          200: "200ms",
+          300: "300ms",
+          500: "500ms",
+          700: "700ms",
+          1e3: "1000ms",
+        },
+        transitionDuration: {
+          DEFAULT: "150ms",
+          0: "0s",
+          75: "75ms",
+          100: "100ms",
+          150: "150ms",
+          200: "200ms",
+          300: "300ms",
+          500: "500ms",
+          700: "700ms",
+          1e3: "1000ms",
+        },
+        transitionProperty: {
+          none: "none",
+          all: "all",
+          DEFAULT:
+            "color, background-color, border-color, text-decoration-color, fill, stroke, opacity, box-shadow, transform, filter, backdrop-filter",
+          colors: "color, background-color, border-color, text-decoration-color, fill, stroke",
+          opacity: "opacity",
+          shadow: "box-shadow",
+          transform: "transform",
+        },
+        transitionTimingFunction: {
+          DEFAULT: "cubic-bezier(0.4, 0, 0.2, 1)",
+          linear: "linear",
+          in: "cubic-bezier(0.4, 0, 1, 1)",
+          out: "cubic-bezier(0, 0, 0.2, 1)",
+          "in-out": "cubic-bezier(0.4, 0, 0.2, 1)",
+        },
+        translate: ({ theme: r }) => ({
+          ...r("spacing"),
+          "1/2": "50%",
+          "1/3": "33.333333%",
+          "2/3": "66.666667%",
+          "1/4": "25%",
+          "2/4": "50%",
+          "3/4": "75%",
+          full: "100%",
+        }),
+        width: ({ theme: r }) => ({
+          auto: "auto",
+          ...r("spacing"),
+          "1/2": "50%",
+          "1/3": "33.333333%",
+          "2/3": "66.666667%",
+          "1/4": "25%",
+          "2/4": "50%",
+          "3/4": "75%",
+          "1/5": "20%",
+          "2/5": "40%",
+          "3/5": "60%",
+          "4/5": "80%",
+          "1/6": "16.666667%",
+          "2/6": "33.333333%",
+          "3/6": "50%",
+          "4/6": "66.666667%",
+          "5/6": "83.333333%",
+          "1/12": "8.333333%",
+          "2/12": "16.666667%",
+          "3/12": "25%",
+          "4/12": "33.333333%",
+          "5/12": "41.666667%",
+          "6/12": "50%",
+          "7/12": "58.333333%",
+          "8/12": "66.666667%",
+          "9/12": "75%",
+          "10/12": "83.333333%",
+          "11/12": "91.666667%",
+          full: "100%",
+          screen: "100vw",
+          min: "min-content",
+          max: "max-content",
+          fit: "fit-content",
+        }),
+        willChange: { auto: "auto", scroll: "scroll-position", contents: "contents", transform: "transform" },
+        zIndex: { auto: "auto", 0: "0", 10: "10", 20: "20", 30: "30", 40: "40", 50: "50" },
+      },
+      plugins: [],
+    };
+  });
+  function mi(r) {
+    let e = (r?.presets ?? [Lu.default]).slice().reverse().flatMap(n => mi(n instanceof Function ? n() : n)),
+      t = {
+        respectDefaultRingColorOpacity: {
+          theme: { ringColor: ({ theme: n }) => ({ DEFAULT: "#3b82f67f", ...n("colors") }) },
+        },
+        disableColorOpacityUtilitiesByDefault: {
+          corePlugins: {
+            backgroundOpacity: !1,
+            borderOpacity: !1,
+            divideOpacity: !1,
+            placeholderOpacity: !1,
+            ringOpacity: !1,
+            textOpacity: !1,
+          },
+        },
+      },
+      i = Object.keys(t).filter(n => J(r, n)).map(n => t[n]);
+    return [r, ...i, ...e];
+  }
+  var Lu,
+    Bu = C(() => {
+      l();
+      Lu = K(hi());
+      De();
+    });
+  var $u = {};
+  Ce($u, { default: () => cr });
+  function cr(...r) {
+    let [, ...e] = mi(r[0]);
+    return as([...r, ...e]);
+  }
+  var os = C(() => {
+    l();
+    Fu();
+    Bu();
+  });
+  var ju = {};
+  Ce(ju, { default: () => te });
+  var te,
+    dt = C(() => {
+      l();
+      te = { resolve: r => r, extname: r => "." + r.split(".").pop() };
+    });
+  function gi(r) {
+    return typeof r == "object" && r !== null;
+  }
+  function Pw(r) {
+    return Object.keys(r).length === 0;
+  }
+  function zu(r) {
+    return typeof r == "string" || r instanceof String;
+  }
+  function ls(r) {
+    return gi(r) && r.config === void 0 && !Pw(r)
+      ? null
+      : gi(r) && r.config !== void 0 && zu(r.config)
+      ? te.resolve(r.config)
+      : gi(r) && r.config !== void 0 && gi(r.config)
+      ? null
+      : zu(r)
+      ? te.resolve(r)
+      : Dw();
+  }
+  function Dw() {
+    for (let r of Tw) {
+      try {
+        let e = te.resolve(r);
+        return ie.accessSync(e), e;
+      } catch (e) {}
+    }
+    return null;
+  }
+  var Tw,
+    Vu = C(() => {
+      l();
+      je();
+      dt();
+      Tw = ["./tailwind.config.js", "./tailwind.config.cjs", "./tailwind.config.mjs", "./tailwind.config.ts"];
+    });
+  var Uu = {};
+  Ce(Uu, { default: () => us });
+  var us,
+    fs = C(() => {
+      l();
+      us = { parse: r => ({ href: r }) };
+    });
+  var cs = v(() => {
+    l();
+  });
+  var yi = v((C5, Hu) => {
+    l();
+    "use strict";
+    var Wu = (ai(), nu),
+      Gu = cs(),
+      St = class extends Error {
+        constructor(e, t, i, n, s, a) {
+          super(e);
+          this.name = "CssSyntaxError",
+            this.reason = e,
+            s && (this.file = s),
+            n && (this.source = n),
+            a && (this.plugin = a),
+            typeof t != "undefined" && typeof i != "undefined"
+            && (typeof t == "number"
+              ? (this.line = t, this.column = i)
+              : (this.line = t.line, this.column = t.column, this.endLine = i.line, this.endColumn = i.column)),
+            this.setMessage(),
+            Error.captureStackTrace && Error.captureStackTrace(this, St);
+        }
+        setMessage() {
+          this.message = this.plugin ? this.plugin + ": " : "",
+            this.message += this.file ? this.file : "<css input>",
+            typeof this.line != "undefined" && (this.message += ":" + this.line + ":" + this.column),
+            this.message += ": " + this.reason;
+        }
+        showSourceCode(e) {
+          if (!this.source) return "";
+          let t = this.source;
+          e == null && (e = Wu.isColorSupported), Gu && e && (t = Gu(t));
+          let i = t.split(/\r?\n/),
+            n = Math.max(this.line - 3, 0),
+            s = Math.min(this.line + 2, i.length),
+            a = String(s).length,
+            o,
+            u;
+          if (e) {
+            let { bold: c, red: f, gray: p } = Wu.createColors(!0);
+            o = d => c(f(d)), u = d => p(d);
+          } else o = u = c => c;
+          return i.slice(n, s).map((c, f) => {
+            let p = n + 1 + f, d = " " + (" " + p).slice(-a) + " | ";
+            if (p === this.line) {
+              let h = u(d.replace(/\d/g, " ")) + c.slice(0, this.column - 1).replace(/[^\t]/g, " ");
+              return o(">") + u(d) + c + `
+ ` + h + o("^");
+            }
+            return " " + u(d) + c;
+          }).join(`
+`);
+        }
+        toString() {
+          let e = this.showSourceCode();
+          return e && (e = `
+
+` + e + `
+`),
+            this.name + ": " + this.message + e;
+        }
+      };
+    Hu.exports = St;
+    St.default = St;
+  });
+  var bi = v((A5, ps) => {
+    l();
+    "use strict";
+    ps.exports.isClean = Symbol("isClean");
+    ps.exports.my = Symbol("my");
+  });
+  var ds = v((O5, Qu) => {
+    l();
+    "use strict";
+    var Yu = {
+      colon: ": ",
+      indent: "    ",
+      beforeDecl: `
+`,
+      beforeRule: `
+`,
+      beforeOpen: " ",
+      beforeClose: `
+`,
+      beforeComment: `
+`,
+      after: `
+`,
+      emptyBody: "",
+      commentLeft: " ",
+      commentRight: " ",
+      semicolon: !1,
+    };
+    function Iw(r) {
+      return r[0].toUpperCase() + r.slice(1);
+    }
+    var wi = class {
+      constructor(e) {
+        this.builder = e;
+      }
+      stringify(e, t) {
+        if (!this[e.type]) {
+          throw new Error("Unknown AST node type " + e.type + ". Maybe you need to change PostCSS stringifier.");
+        }
+        this[e.type](e, t);
+      }
+      document(e) {
+        this.body(e);
+      }
+      root(e) {
+        this.body(e), e.raws.after && this.builder(e.raws.after);
+      }
+      comment(e) {
+        let t = this.raw(e, "left", "commentLeft"), i = this.raw(e, "right", "commentRight");
+        this.builder("/*" + t + e.text + i + "*/", e);
+      }
+      decl(e, t) {
+        let i = this.raw(e, "between", "colon"), n = e.prop + i + this.rawValue(e, "value");
+        e.important && (n += e.raws.important || " !important"), t && (n += ";"), this.builder(n, e);
+      }
+      rule(e) {
+        this.block(e, this.rawValue(e, "selector")), e.raws.ownSemicolon && this.builder(e.raws.ownSemicolon, e, "end");
+      }
+      atrule(e, t) {
+        let i = "@" + e.name, n = e.params ? this.rawValue(e, "params") : "";
+        if (typeof e.raws.afterName != "undefined" ? i += e.raws.afterName : n && (i += " "), e.nodes) {
+          this.block(e, i + n);
+        } else {
+          let s = (e.raws.between || "") + (t ? ";" : "");
+          this.builder(i + n + s, e);
+        }
+      }
+      body(e) {
+        let t = e.nodes.length - 1;
+        for (; t > 0 && e.nodes[t].type === "comment";) t -= 1;
+        let i = this.raw(e, "semicolon");
+        for (let n = 0; n < e.nodes.length; n++) {
+          let s = e.nodes[n], a = this.raw(s, "before");
+          a && this.builder(a), this.stringify(s, t !== n || i);
+        }
+      }
+      block(e, t) {
+        let i = this.raw(e, "between", "beforeOpen");
+        this.builder(t + i + "{", e, "start");
+        let n;
+        e.nodes && e.nodes.length ? (this.body(e), n = this.raw(e, "after")) : n = this.raw(e, "after", "emptyBody"),
+          n && this.builder(n),
+          this.builder("}", e, "end");
+      }
+      raw(e, t, i) {
+        let n;
+        if (i || (i = t), t && (n = e.raws[t], typeof n != "undefined")) return n;
+        let s = e.parent;
+        if (i === "before" && (!s || s.type === "root" && s.first === e || s && s.type === "document")) return "";
+        if (!s) return Yu[i];
+        let a = e.root();
+        if (a.rawCache || (a.rawCache = {}), typeof a.rawCache[i] != "undefined") return a.rawCache[i];
+        if (i === "before" || i === "after") return this.beforeAfter(e, i);
+        {
+          let o = "raw" + Iw(i);
+          this[o] ? n = this[o](a, e) : a.walk(u => {
+            if (n = u.raws[t], typeof n != "undefined") return !1;
+          });
+        }
+        return typeof n == "undefined" && (n = Yu[i]), a.rawCache[i] = n, n;
+      }
+      rawSemicolon(e) {
+        let t;
+        return e.walk(i => {
+          if (i.nodes && i.nodes.length && i.last.type === "decl" && (t = i.raws.semicolon, typeof t != "undefined")) {
+            return !1;
+          }
+        }),
+          t;
+      }
+      rawEmptyBody(e) {
+        let t;
+        return e.walk(i => {
+          if (i.nodes && i.nodes.length === 0 && (t = i.raws.after, typeof t != "undefined")) return !1;
+        }),
+          t;
+      }
+      rawIndent(e) {
+        if (e.raws.indent) return e.raws.indent;
+        let t;
+        return e.walk(i => {
+          let n = i.parent;
+          if (n && n !== e && n.parent && n.parent === e && typeof i.raws.before != "undefined") {
+            let s = i.raws.before.split(`
+`);
+            return t = s[s.length - 1], t = t.replace(/\S/g, ""), !1;
+          }
+        }),
+          t;
+      }
+      rawBeforeComment(e, t) {
+        let i;
+        return e.walkComments(n => {
+          if (typeof n.raws.before != "undefined") {
+            return i = n.raws.before,
+              i.includes(`
+`) && (i = i.replace(/[^\n]+$/, "")),
+              !1;
+          }
+        }),
+          typeof i == "undefined" ? i = this.raw(t, null, "beforeDecl") : i && (i = i.replace(/\S/g, "")),
+          i;
+      }
+      rawBeforeDecl(e, t) {
+        let i;
+        return e.walkDecls(n => {
+          if (typeof n.raws.before != "undefined") {
+            return i = n.raws.before,
+              i.includes(`
+`) && (i = i.replace(/[^\n]+$/, "")),
+              !1;
+          }
+        }),
+          typeof i == "undefined" ? i = this.raw(t, null, "beforeRule") : i && (i = i.replace(/\S/g, "")),
+          i;
+      }
+      rawBeforeRule(e) {
+        let t;
+        return e.walk(i => {
+          if (i.nodes && (i.parent !== e || e.first !== i) && typeof i.raws.before != "undefined") {
+            return t = i.raws.before,
+              t.includes(`
+`) && (t = t.replace(/[^\n]+$/, "")),
+              !1;
+          }
+        }),
+          t && (t = t.replace(/\S/g, "")),
+          t;
+      }
+      rawBeforeClose(e) {
+        let t;
+        return e.walk(i => {
+          if (i.nodes && i.nodes.length > 0 && typeof i.raws.after != "undefined") {
+            return t = i.raws.after,
+              t.includes(`
+`) && (t = t.replace(/[^\n]+$/, "")),
+              !1;
+          }
+        }),
+          t && (t = t.replace(/\S/g, "")),
+          t;
+      }
+      rawBeforeOpen(e) {
+        let t;
+        return e.walk(i => {
+          if (i.type !== "decl" && (t = i.raws.between, typeof t != "undefined")) return !1;
+        }),
+          t;
+      }
+      rawColon(e) {
+        let t;
+        return e.walkDecls(i => {
+          if (typeof i.raws.between != "undefined") return t = i.raws.between.replace(/[^\s:]/g, ""), !1;
+        }),
+          t;
+      }
+      beforeAfter(e, t) {
+        let i;
+        e.type === "decl"
+          ? i = this.raw(e, null, "beforeDecl")
+          : e.type === "comment"
+          ? i = this.raw(e, null, "beforeComment")
+          : t === "before"
+          ? i = this.raw(e, null, "beforeRule")
+          : i = this.raw(e, null, "beforeClose");
+        let n = e.parent, s = 0;
+        for (; n && n.type !== "root";) s += 1, n = n.parent;
+        if (
+          i.includes(`
+`)
+        ) {
+          let a = this.raw(e, null, "indent");
+          if (a.length) for (let o = 0; o < s; o++) i += a;
+        }
+        return i;
+      }
+      rawValue(e, t) {
+        let i = e[t], n = e.raws[t];
+        return n && n.value === i ? n.raw : i;
+      }
+    };
+    Qu.exports = wi;
+    wi.default = wi;
+  });
+  var pr = v((E5, Ju) => {
+    l();
+    "use strict";
+    var qw = ds();
+    function hs(r, e) {
+      new qw(e).stringify(r);
+    }
+    Ju.exports = hs;
+    hs.default = hs;
+  });
+  var dr = v((T5, Xu) => {
+    l();
+    "use strict";
+    var { isClean: vi, my: Rw } = bi(), Mw = yi(), Fw = ds(), Nw = pr();
+    function ms(r, e) {
+      let t = new r.constructor();
+      for (let i in r) {
+        if (!Object.prototype.hasOwnProperty.call(r, i) || i === "proxyCache") continue;
+        let n = r[i], s = typeof n;
+        i === "parent" && s === "object"
+          ? e && (t[i] = e)
+          : i === "source"
+          ? t[i] = n
+          : Array.isArray(n)
+          ? t[i] = n.map(a => ms(a, t))
+          : (s === "object" && n !== null && (n = ms(n)), t[i] = n);
+      }
+      return t;
+    }
+    var xi = class {
+      constructor(e = {}) {
+        this.raws = {}, this[vi] = !1, this[Rw] = !0;
+        for (let t in e) {
+          if (t === "nodes") {
+            this.nodes = [];
+            for (let i of e[t]) typeof i.clone == "function" ? this.append(i.clone()) : this.append(i);
+          } else this[t] = e[t];
+        }
+      }
+      error(e, t = {}) {
+        if (this.source) {
+          let { start: i, end: n } = this.rangeBy(t);
+          return this.source.input.error(e, { line: i.line, column: i.column }, { line: n.line, column: n.column }, t);
+        }
+        return new Mw(e);
+      }
+      warn(e, t, i) {
+        let n = { node: this };
+        for (let s in i) n[s] = i[s];
+        return e.warn(t, n);
+      }
+      remove() {
+        return this.parent && this.parent.removeChild(this), this.parent = void 0, this;
+      }
+      toString(e = Nw) {
+        e.stringify && (e = e.stringify);
+        let t = "";
+        return e(this, i => {
+          t += i;
+        }),
+          t;
+      }
+      assign(e = {}) {
+        for (let t in e) this[t] = e[t];
+        return this;
+      }
+      clone(e = {}) {
+        let t = ms(this);
+        for (let i in e) t[i] = e[i];
+        return t;
+      }
+      cloneBefore(e = {}) {
+        let t = this.clone(e);
+        return this.parent.insertBefore(this, t), t;
+      }
+      cloneAfter(e = {}) {
+        let t = this.clone(e);
+        return this.parent.insertAfter(this, t), t;
+      }
+      replaceWith(...e) {
+        if (this.parent) {
+          let t = this, i = !1;
+          for (let n of e) {
+            n === this
+              ? i = !0
+              : i
+              ? (this.parent.insertAfter(t, n), t = n)
+              : this.parent.insertBefore(t, n);
+          }
+          i || this.remove();
+        }
+        return this;
+      }
+      next() {
+        if (!this.parent) return;
+        let e = this.parent.index(this);
+        return this.parent.nodes[e + 1];
+      }
+      prev() {
+        if (!this.parent) return;
+        let e = this.parent.index(this);
+        return this.parent.nodes[e - 1];
+      }
+      before(e) {
+        return this.parent.insertBefore(this, e), this;
+      }
+      after(e) {
+        return this.parent.insertAfter(this, e), this;
+      }
+      root() {
+        let e = this;
+        for (; e.parent && e.parent.type !== "document";) e = e.parent;
+        return e;
+      }
+      raw(e, t) {
+        return new Fw().raw(this, e, t);
+      }
+      cleanRaws(e) {
+        delete this.raws.before, delete this.raws.after, e || delete this.raws.between;
+      }
+      toJSON(e, t) {
+        let i = {}, n = t == null;
+        t = t || new Map();
+        let s = 0;
+        for (let a in this) {
+          if (!Object.prototype.hasOwnProperty.call(this, a) || a === "parent" || a === "proxyCache") continue;
+          let o = this[a];
+          if (Array.isArray(o)) i[a] = o.map(u => typeof u == "object" && u.toJSON ? u.toJSON(null, t) : u);
+          else if (typeof o == "object" && o.toJSON) i[a] = o.toJSON(null, t);
+          else if (a === "source") {
+            let u = t.get(o.input);
+            u == null && (u = s, t.set(o.input, s), s++), i[a] = { inputId: u, start: o.start, end: o.end };
+          } else i[a] = o;
+        }
+        return n && (i.inputs = [...t.keys()].map(a => a.toJSON())), i;
+      }
+      positionInside(e) {
+        let t = this.toString(), i = this.source.start.column, n = this.source.start.line;
+        for (let s = 0; s < e; s++) {
+          t[s] === `
+`
+            ? (i = 1, n += 1)
+            : i += 1;
+        }
+        return { line: n, column: i };
+      }
+      positionBy(e) {
+        let t = this.source.start;
+        if (e.index) t = this.positionInside(e.index);
+        else if (e.word) {
+          let i = this.toString().indexOf(e.word);
+          i !== -1 && (t = this.positionInside(i));
+        }
+        return t;
+      }
+      rangeBy(e) {
+        let t = { line: this.source.start.line, column: this.source.start.column },
+          i = this.source.end
+            ? { line: this.source.end.line, column: this.source.end.column + 1 }
+            : { line: t.line, column: t.column + 1 };
+        if (e.word) {
+          let n = this.toString().indexOf(e.word);
+          n !== -1 && (t = this.positionInside(n), i = this.positionInside(n + e.word.length));
+        } else {e.start
+            ? t = { line: e.start.line, column: e.start.column }
+            : e.index && (t = this.positionInside(e.index)),
+            e.end
+              ? i = { line: e.end.line, column: e.end.column }
+              : e.endIndex
+              ? i = this.positionInside(e.endIndex)
+              : e.index && (i = this.positionInside(e.index + 1));}
+        return (i.line < t.line || i.line === t.line && i.column <= t.column)
+          && (i = { line: t.line, column: t.column + 1 }),
+          { start: t, end: i };
+      }
+      getProxyProcessor() {
+        return {
+          set(e, t, i) {
+            return e[t] === i
+              || (e[t] = i,
+                (t === "prop" || t === "value" || t === "name" || t === "params" || t === "important" || t === "text")
+                && e.markDirty()),
+              !0;
+          },
+          get(e, t) {
+            return t === "proxyOf" ? e : t === "root" ? () => e.root().toProxy() : e[t];
+          },
+        };
+      }
+      toProxy() {
+        return this.proxyCache || (this.proxyCache = new Proxy(this, this.getProxyProcessor())), this.proxyCache;
+      }
+      addToError(e) {
+        if (e.postcssNode = this, e.stack && this.source && /\n\s{4}at /.test(e.stack)) {
+          let t = this.source;
+          e.stack = e.stack.replace(/\n\s{4}at /, `$&${t.input.from}:${t.start.line}:${t.start.column}$&`);
+        }
+        return e;
+      }
+      markDirty() {
+        if (this[vi]) {
+          this[vi] = !1;
+          let e = this;
+          for (; e = e.parent;) e[vi] = !1;
+        }
+      }
+      get proxyOf() {
+        return this;
+      }
+    };
+    Xu.exports = xi;
+    xi.default = xi;
+  });
+  var hr = v((P5, Ku) => {
+    l();
+    "use strict";
+    var Lw = dr(),
+      ki = class extends Lw {
+        constructor(e) {
+          e && typeof e.value != "undefined" && typeof e.value != "string" && (e = { ...e, value: String(e.value) });
+          super(e);
+          this.type = "decl";
+        }
+        get variable() {
+          return this.prop.startsWith("--") || this.prop[0] === "$";
+        }
+      };
+    Ku.exports = ki;
+    ki.default = ki;
+  });
+  var gs = v((D5, Zu) => {
+    l();
+    Zu.exports = function(r, e) {
+      return {
+        generate: () => {
+          let t = "";
+          return r(e, i => {
+            t += i;
+          }),
+            [t];
+        },
+      };
+    };
+  });
+  var mr = v((I5, ef) => {
+    l();
+    "use strict";
+    var Bw = dr(),
+      Si = class extends Bw {
+        constructor(e) {
+          super(e);
+          this.type = "comment";
+        }
+      };
+    ef.exports = Si;
+    Si.default = Si;
+  });
+  var rt = v((q5, ff) => {
+    l();
+    "use strict";
+    var { isClean: tf, my: rf } = bi(), nf = hr(), sf = mr(), $w = dr(), af, ys, bs, of;
+    function lf(r) {
+      return r.map(e => (e.nodes && (e.nodes = lf(e.nodes)), delete e.source, e));
+    }
+    function uf(r) {
+      if (r[tf] = !1, r.proxyOf.nodes) for (let e of r.proxyOf.nodes) uf(e);
+    }
+    var ye = class extends $w {
+      push(e) {
+        return e.parent = this, this.proxyOf.nodes.push(e), this;
+      }
+      each(e) {
+        if (!this.proxyOf.nodes) return;
+        let t = this.getIterator(), i, n;
+        for (
+          ;
+          this.indexes[t] < this.proxyOf.nodes.length
+          && (i = this.indexes[t], n = e(this.proxyOf.nodes[i], i), n !== !1);
+        ) this.indexes[t] += 1;
+        return delete this.indexes[t], n;
+      }
+      walk(e) {
+        return this.each((t, i) => {
+          let n;
+          try {
+            n = e(t, i);
+          } catch (s) {
+            throw t.addToError(s);
+          }
+          return n !== !1 && t.walk && (n = t.walk(e)), n;
+        });
+      }
+      walkDecls(e, t) {
+        return t
+          ? e instanceof RegExp
+            ? this.walk((i, n) => {
+              if (i.type === "decl" && e.test(i.prop)) return t(i, n);
+            })
+            : this.walk((i, n) => {
+              if (i.type === "decl" && i.prop === e) return t(i, n);
+            })
+          : (t = e,
+            this.walk((i, n) => {
+              if (i.type === "decl") return t(i, n);
+            }));
+      }
+      walkRules(e, t) {
+        return t
+          ? e instanceof RegExp
+            ? this.walk((i, n) => {
+              if (i.type === "rule" && e.test(i.selector)) return t(i, n);
+            })
+            : this.walk((i, n) => {
+              if (i.type === "rule" && i.selector === e) return t(i, n);
+            })
+          : (t = e,
+            this.walk((i, n) => {
+              if (i.type === "rule") return t(i, n);
+            }));
+      }
+      walkAtRules(e, t) {
+        return t
+          ? e instanceof RegExp
+            ? this.walk((i, n) => {
+              if (i.type === "atrule" && e.test(i.name)) return t(i, n);
+            })
+            : this.walk((i, n) => {
+              if (i.type === "atrule" && i.name === e) return t(i, n);
+            })
+          : (t = e,
+            this.walk((i, n) => {
+              if (i.type === "atrule") return t(i, n);
+            }));
+      }
+      walkComments(e) {
+        return this.walk((t, i) => {
+          if (t.type === "comment") return e(t, i);
+        });
+      }
+      append(...e) {
+        for (let t of e) {
+          let i = this.normalize(t, this.last);
+          for (let n of i) this.proxyOf.nodes.push(n);
+        }
+        return this.markDirty(), this;
+      }
+      prepend(...e) {
+        e = e.reverse();
+        for (let t of e) {
+          let i = this.normalize(t, this.first, "prepend").reverse();
+          for (let n of i) this.proxyOf.nodes.unshift(n);
+          for (let n in this.indexes) this.indexes[n] = this.indexes[n] + i.length;
+        }
+        return this.markDirty(), this;
+      }
+      cleanRaws(e) {
+        if (super.cleanRaws(e), this.nodes) for (let t of this.nodes) t.cleanRaws(e);
+      }
+      insertBefore(e, t) {
+        let i = this.index(e), n = i === 0 ? "prepend" : !1, s = this.normalize(t, this.proxyOf.nodes[i], n).reverse();
+        i = this.index(e);
+        for (let o of s) this.proxyOf.nodes.splice(i, 0, o);
+        let a;
+        for (let o in this.indexes) a = this.indexes[o], i <= a && (this.indexes[o] = a + s.length);
+        return this.markDirty(), this;
+      }
+      insertAfter(e, t) {
+        let i = this.index(e), n = this.normalize(t, this.proxyOf.nodes[i]).reverse();
+        i = this.index(e);
+        for (let a of n) this.proxyOf.nodes.splice(i + 1, 0, a);
+        let s;
+        for (let a in this.indexes) s = this.indexes[a], i < s && (this.indexes[a] = s + n.length);
+        return this.markDirty(), this;
+      }
+      removeChild(e) {
+        e = this.index(e), this.proxyOf.nodes[e].parent = void 0, this.proxyOf.nodes.splice(e, 1);
+        let t;
+        for (let i in this.indexes) t = this.indexes[i], t >= e && (this.indexes[i] = t - 1);
+        return this.markDirty(), this;
+      }
+      removeAll() {
+        for (let e of this.proxyOf.nodes) e.parent = void 0;
+        return this.proxyOf.nodes = [], this.markDirty(), this;
+      }
+      replaceValues(e, t, i) {
+        return i || (i = t, t = {}),
+          this.walkDecls(n => {
+            t.props && !t.props.includes(n.prop) || t.fast && !n.value.includes(t.fast)
+              || (n.value = n.value.replace(e, i));
+          }),
+          this.markDirty(),
+          this;
+      }
+      every(e) {
+        return this.nodes.every(e);
+      }
+      some(e) {
+        return this.nodes.some(e);
+      }
+      index(e) {
+        return typeof e == "number" ? e : (e.proxyOf && (e = e.proxyOf), this.proxyOf.nodes.indexOf(e));
+      }
+      get first() {
+        if (!!this.proxyOf.nodes) return this.proxyOf.nodes[0];
+      }
+      get last() {
+        if (!!this.proxyOf.nodes) return this.proxyOf.nodes[this.proxyOf.nodes.length - 1];
+      }
+      normalize(e, t) {
+        if (typeof e == "string") e = lf(af(e).nodes);
+        else if (Array.isArray(e)) {
+          e = e.slice(0);
+          for (let n of e) n.parent && n.parent.removeChild(n, "ignore");
+        } else if (e.type === "root" && this.type !== "document") {
+          e = e.nodes.slice(0);
+          for (let n of e) n.parent && n.parent.removeChild(n, "ignore");
+        } else if (e.type) e = [e];
+        else if (e.prop) {
+          if (typeof e.value == "undefined") throw new Error("Value field is missed in node creation");
+          typeof e.value != "string" && (e.value = String(e.value)), e = [new nf(e)];
+        } else if (e.selector) e = [new ys(e)];
+        else if (e.name) e = [new bs(e)];
+        else if (e.text) e = [new sf(e)];
+        else throw new Error("Unknown node type in node creation");
+        return e.map(
+          n => (n[rf] || ye.rebuild(n),
+            n = n.proxyOf,
+            n.parent && n.parent.removeChild(n),
+            n[tf] && uf(n),
+            typeof n.raws.before == "undefined" && t && typeof t.raws.before != "undefined"
+            && (n.raws.before = t.raws.before.replace(/\S/g, "")),
+            n.parent = this.proxyOf,
+            n),
+        );
+      }
+      getProxyProcessor() {
+        return {
+          set(e, t, i) {
+            return e[t] === i || (e[t] = i, (t === "name" || t === "params" || t === "selector") && e.markDirty()), !0;
+          },
+          get(e, t) {
+            return t === "proxyOf"
+              ? e
+              : e[t]
+              ? t === "each" || typeof t == "string" && t.startsWith("walk")
+                ? (...i) => e[t](...i.map(n => typeof n == "function" ? (s, a) => n(s.toProxy(), a) : n))
+                : t === "every" || t === "some"
+                ? i => e[t]((n, ...s) => i(n.toProxy(), ...s))
+                : t === "root"
+                ? () => e.root().toProxy()
+                : t === "nodes"
+                ? e.nodes.map(i => i.toProxy())
+                : t === "first" || t === "last"
+                ? e[t].toProxy()
+                : e[t]
+              : e[t];
+          },
+        };
+      }
+      getIterator() {
+        this.lastEach || (this.lastEach = 0), this.indexes || (this.indexes = {}), this.lastEach += 1;
+        let e = this.lastEach;
+        return this.indexes[e] = 0, e;
+      }
+    };
+    ye.registerParse = r => {
+      af = r;
+    };
+    ye.registerRule = r => {
+      ys = r;
+    };
+    ye.registerAtRule = r => {
+      bs = r;
+    };
+    ye.registerRoot = r => {
+      of = r;
+    };
+    ff.exports = ye;
+    ye.default = ye;
+    ye.rebuild = r => {
+      r.type === "atrule"
+        ? Object.setPrototypeOf(r, bs.prototype)
+        : r.type === "rule"
+        ? Object.setPrototypeOf(r, ys.prototype)
+        : r.type === "decl"
+        ? Object.setPrototypeOf(r, nf.prototype)
+        : r.type === "comment"
+        ? Object.setPrototypeOf(r, sf.prototype)
+        : r.type === "root" && Object.setPrototypeOf(r, of.prototype),
+        r[rf] = !0,
+        r.nodes && r.nodes.forEach(e => {
+          ye.rebuild(e);
+        });
+    };
+  });
+  var _i = v((R5, df) => {
+    l();
+    "use strict";
+    var jw = rt(),
+      cf,
+      pf,
+      _t = class extends jw {
+        constructor(e) {
+          super({ type: "document", ...e });
+          this.nodes || (this.nodes = []);
+        }
+        toResult(e = {}) {
+          return new cf(new pf(), this, e).stringify();
+        }
+      };
+    _t.registerLazyResult = r => {
+      cf = r;
+    };
+    _t.registerProcessor = r => {
+      pf = r;
+    };
+    df.exports = _t;
+    _t.default = _t;
+  });
+  var ws = v((M5, mf) => {
+    l();
+    "use strict";
+    var hf = {};
+    mf.exports = function(e) {
+      hf[e] || (hf[e] = !0, typeof console != "undefined" && console.warn && console.warn(e));
+    };
+  });
+  var vs = v((F5, gf) => {
+    l();
+    "use strict";
+    var Ci = class {
+      constructor(e, t = {}) {
+        if (this.type = "warning", this.text = e, t.node && t.node.source) {
+          let i = t.node.rangeBy(t);
+          this.line = i.start.line,
+            this.column = i.start.column,
+            this.endLine = i.end.line,
+            this.endColumn = i.end.column;
+        }
+        for (let i in t) this[i] = t[i];
+      }
+      toString() {
+        return this.node
+          ? this.node.error(this.text, { plugin: this.plugin, index: this.index, word: this.word }).message
+          : this.plugin
+          ? this.plugin + ": " + this.text
+          : this.text;
+      }
+    };
+    gf.exports = Ci;
+    Ci.default = Ci;
+  });
+  var Oi = v((N5, yf) => {
+    l();
+    "use strict";
+    var zw = vs(),
+      Ai = class {
+        constructor(e, t, i) {
+          this.processor = e, this.messages = [], this.root = t, this.opts = i, this.css = void 0, this.map = void 0;
+        }
+        toString() {
+          return this.css;
+        }
+        warn(e, t = {}) {
+          t.plugin || this.lastPlugin && this.lastPlugin.postcssPlugin && (t.plugin = this.lastPlugin.postcssPlugin);
+          let i = new zw(e, t);
+          return this.messages.push(i), i;
+        }
+        warnings() {
+          return this.messages.filter(e => e.type === "warning");
+        }
+        get content() {
+          return this.css;
+        }
+      };
+    yf.exports = Ai;
+    Ai.default = Ai;
+  });
+  var kf = v((L5, xf) => {
+    l();
+    "use strict";
+    var xs = "'".charCodeAt(0),
+      bf = "\"".charCodeAt(0),
+      Ei = "\\".charCodeAt(0),
+      wf = "/".charCodeAt(0),
+      Ti = `
+`.charCodeAt(0),
+      gr = " ".charCodeAt(0),
+      Pi = "\f".charCodeAt(0),
+      Di = "	".charCodeAt(0),
+      Ii = "\r".charCodeAt(0),
+      Vw = "[".charCodeAt(0),
+      Uw = "]".charCodeAt(0),
+      Ww = "(".charCodeAt(0),
+      Gw = ")".charCodeAt(0),
+      Hw = "{".charCodeAt(0),
+      Yw = "}".charCodeAt(0),
+      Qw = ";".charCodeAt(0),
+      Jw = "*".charCodeAt(0),
+      Xw = ":".charCodeAt(0),
+      Kw = "@".charCodeAt(0),
+      qi = /[\t\n\f\r "#'()/;[\\\]{}]/g,
+      Ri = /[\t\n\f\r !"#'():;@[\\\]{}]|\/(?=\*)/g,
+      Zw = /.[\n"'(/\\]/,
+      vf = /[\da-f]/i;
+    xf.exports = function(e, t = {}) {
+      let i = e.css.valueOf(), n = t.ignoreErrors, s, a, o, u, c, f, p, d, h, y, x = i.length, b = 0, w = [], k = [];
+      function S() {
+        return b;
+      }
+      function _(I) {
+        throw e.error("Unclosed " + I, b);
+      }
+      function P() {
+        return k.length === 0 && b >= x;
+      }
+      function M(I) {
+        if (k.length) return k.pop();
+        if (b >= x) return;
+        let X = I ? I.ignoreUnclosed : !1;
+        switch (s = i.charCodeAt(b), s) {
+          case Ti:
+          case gr:
+          case Di:
+          case Ii:
+          case Pi: {
+            a = b;
+            do a += 1, s = i.charCodeAt(a); while (s === gr || s === Ti || s === Di || s === Ii || s === Pi);
+            y = ["space", i.slice(b, a)], b = a - 1;
+            break;
+          }
+          case Vw:
+          case Uw:
+          case Hw:
+          case Yw:
+          case Xw:
+          case Qw:
+          case Gw: {
+            let ge = String.fromCharCode(s);
+            y = [ge, ge, b];
+            break;
+          }
+          case Ww: {
+            if (
+              d = w.length ? w.pop()[1] : "",
+                h = i.charCodeAt(b + 1),
+                d === "url" && h !== xs && h !== bf && h !== gr && h !== Ti && h !== Di && h !== Pi && h !== Ii
+            ) {
+              a = b;
+              do {
+                if (f = !1, a = i.indexOf(")", a + 1), a === -1) {
+                  if (n || X) {
+                    a = b;
+                    break;
+                  } else _("bracket");
+                }
+                for (p = a; i.charCodeAt(p - 1) === Ei;) p -= 1, f = !f;
+              } while (f);
+              y = ["brackets", i.slice(b, a + 1), b, a], b = a;
+            } else {a = i.indexOf(")", b + 1),
+                u = i.slice(b, a + 1),
+                a === -1 || Zw.test(u) ? y = ["(", "(", b] : (y = ["brackets", u, b, a], b = a);}
+            break;
+          }
+          case xs:
+          case bf: {
+            o = s === xs ? "'" : "\"", a = b;
+            do {
+              if (f = !1, a = i.indexOf(o, a + 1), a === -1) {
+                if (n || X) {
+                  a = b + 1;
+                  break;
+                } else _("string");
+              }
+              for (p = a; i.charCodeAt(p - 1) === Ei;) p -= 1, f = !f;
+            } while (f);
+            y = ["string", i.slice(b, a + 1), b, a], b = a;
+            break;
+          }
+          case Kw: {
+            qi.lastIndex = b + 1,
+              qi.test(i),
+              qi.lastIndex === 0 ? a = i.length - 1 : a = qi.lastIndex - 2,
+              y = ["at-word", i.slice(b, a + 1), b, a],
+              b = a;
+            break;
+          }
+          case Ei: {
+            for (a = b, c = !0; i.charCodeAt(a + 1) === Ei;) a += 1, c = !c;
+            if (
+              s = i.charCodeAt(a + 1),
+                c && s !== wf && s !== gr && s !== Ti && s !== Di && s !== Ii && s !== Pi
+                && (a += 1, vf.test(i.charAt(a)))
+            ) {
+              for (; vf.test(i.charAt(a + 1));) a += 1;
+              i.charCodeAt(a + 1) === gr && (a += 1);
+            }
+            y = ["word", i.slice(b, a + 1), b, a], b = a;
+            break;
+          }
+          default: {
+            s === wf && i.charCodeAt(b + 1) === Jw
+              ? (a = i.indexOf("*/", b + 2) + 1,
+                a === 0 && (n || X ? a = i.length : _("comment")),
+                y = ["comment", i.slice(b, a + 1), b, a],
+                b = a)
+              : (Ri.lastIndex = b + 1,
+                Ri.test(i),
+                Ri.lastIndex === 0 ? a = i.length - 1 : a = Ri.lastIndex - 2,
+                y = ["word", i.slice(b, a + 1), b, a],
+                w.push(y),
+                b = a);
+            break;
+          }
+        }
+        return b++, y;
+      }
+      function F(I) {
+        k.push(I);
+      }
+      return { back: F, nextToken: M, endOfFile: P, position: S };
+    };
+  });
+  var Mi = v((B5, _f) => {
+    l();
+    "use strict";
+    var Sf = rt(),
+      yr = class extends Sf {
+        constructor(e) {
+          super(e);
+          this.type = "atrule";
+        }
+        append(...e) {
+          return this.proxyOf.nodes || (this.nodes = []), super.append(...e);
+        }
+        prepend(...e) {
+          return this.proxyOf.nodes || (this.nodes = []), super.prepend(...e);
+        }
+      };
+    _f.exports = yr;
+    yr.default = yr;
+    Sf.registerAtRule(yr);
+  });
+  var Ct = v(($5, Ef) => {
+    l();
+    "use strict";
+    var Cf = rt(),
+      Af,
+      Of,
+      ht = class extends Cf {
+        constructor(e) {
+          super(e);
+          this.type = "root", this.nodes || (this.nodes = []);
+        }
+        removeChild(e, t) {
+          let i = this.index(e);
+          return !t && i === 0 && this.nodes.length > 1 && (this.nodes[1].raws.before = this.nodes[i].raws.before),
+            super.removeChild(e);
+        }
+        normalize(e, t, i) {
+          let n = super.normalize(e);
+          if (t) {
+            if (i === "prepend") {
+              this.nodes.length > 1
+                ? t.raws.before = this.nodes[1].raws.before
+                : delete t.raws.before;
+            } else if (this.first !== t) for (let s of n) s.raws.before = t.raws.before;
+          }
+          return n;
+        }
+        toResult(e = {}) {
+          return new Af(new Of(), this, e).stringify();
+        }
+      };
+    ht.registerLazyResult = r => {
+      Af = r;
+    };
+    ht.registerProcessor = r => {
+      Of = r;
+    };
+    Ef.exports = ht;
+    ht.default = ht;
+    Cf.registerRoot(ht);
+  });
+  var ks = v((j5, Tf) => {
+    l();
+    "use strict";
+    var br = {
+      split(r, e, t) {
+        let i = [], n = "", s = !1, a = 0, o = !1, u = "", c = !1;
+        for (let f of r) {
+          c
+            ? c = !1
+            : f === "\\"
+            ? c = !0
+            : o
+            ? f === u && (o = !1)
+            : f === "\"" || f === "'"
+            ? (o = !0, u = f)
+            : f === "("
+            ? a += 1
+            : f === ")"
+            ? a > 0 && (a -= 1)
+            : a === 0 && e.includes(f) && (s = !0), s ? (n !== "" && i.push(n.trim()), n = "", s = !1) : n += f;
+        }
+        return (t || n !== "") && i.push(n.trim()), i;
+      },
+      space(r) {
+        let e = [
+          " ",
+          `
+`,
+          "	",
+        ];
+        return br.split(r, e);
+      },
+      comma(r) {
+        return br.split(r, [","], !0);
+      },
+    };
+    Tf.exports = br;
+    br.default = br;
+  });
+  var Fi = v((z5, Df) => {
+    l();
+    "use strict";
+    var Pf = rt(),
+      e0 = ks(),
+      wr = class extends Pf {
+        constructor(e) {
+          super(e);
+          this.type = "rule", this.nodes || (this.nodes = []);
+        }
+        get selectors() {
+          return e0.comma(this.selector);
+        }
+        set selectors(e) {
+          let t = this.selector ? this.selector.match(/,\s*/) : null,
+            i = t ? t[0] : "," + this.raw("between", "beforeOpen");
+          this.selector = e.join(i);
+        }
+      };
+    Df.exports = wr;
+    wr.default = wr;
+    Pf.registerRule(wr);
+  });
+  var Ff = v((V5, Mf) => {
+    l();
+    "use strict";
+    var t0 = hr(), r0 = kf(), i0 = mr(), n0 = Mi(), s0 = Ct(), If = Fi(), qf = { empty: !0, space: !0 };
+    function a0(r) {
+      for (let e = r.length - 1; e >= 0; e--) {
+        let t = r[e], i = t[3] || t[2];
+        if (i) return i;
+      }
+    }
+    var Rf = class {
+      constructor(e) {
+        this.input = e,
+          this.root = new s0(),
+          this.current = this.root,
+          this.spaces = "",
+          this.semicolon = !1,
+          this.customProperty = !1,
+          this.createTokenizer(),
+          this.root.source = { input: e, start: { offset: 0, line: 1, column: 1 } };
+      }
+      createTokenizer() {
+        this.tokenizer = r0(this.input);
+      }
+      parse() {
+        let e;
+        for (; !this.tokenizer.endOfFile();) {
+          switch (e = this.tokenizer.nextToken(), e[0]) {
+            case "space":
+              this.spaces += e[1];
+              break;
+            case ";":
+              this.freeSemicolon(e);
+              break;
+            case "}":
+              this.end(e);
+              break;
+            case "comment":
+              this.comment(e);
+              break;
+            case "at-word":
+              this.atrule(e);
+              break;
+            case "{":
+              this.emptyRule(e);
+              break;
+            default:
+              this.other(e);
+              break;
+          }
+        }
+        this.endFile();
+      }
+      comment(e) {
+        let t = new i0();
+        this.init(t, e[2]), t.source.end = this.getPosition(e[3] || e[2]);
+        let i = e[1].slice(2, -2);
+        if (/^\s*$/.test(i)) t.text = "", t.raws.left = i, t.raws.right = "";
+        else {
+          let n = i.match(/^(\s*)([^]*\S)(\s*)$/);
+          t.text = n[2], t.raws.left = n[1], t.raws.right = n[3];
+        }
+      }
+      emptyRule(e) {
+        let t = new If();
+        this.init(t, e[2]), t.selector = "", t.raws.between = "", this.current = t;
+      }
+      other(e) {
+        let t = !1, i = null, n = !1, s = null, a = [], o = e[1].startsWith("--"), u = [], c = e;
+        for (; c;) {
+          if (i = c[0], u.push(c), i === "(" || i === "[") s || (s = c), a.push(i === "(" ? ")" : "]");
+          else if (o && n && i === "{") s || (s = c), a.push("}");
+          else if (a.length === 0) {
+            if (i === ";") {
+              if (n) {
+                this.decl(u, o);
+                return;
+              } else break;
+            } else if (i === "{") {
+              this.rule(u);
+              return;
+            } else if (i === "}") {
+              this.tokenizer.back(u.pop()), t = !0;
+              break;
+            } else i === ":" && (n = !0);
+          } else i === a[a.length - 1] && (a.pop(), a.length === 0 && (s = null));
+          c = this.tokenizer.nextToken();
+        }
+        if (this.tokenizer.endOfFile() && (t = !0), a.length > 0 && this.unclosedBracket(s), t && n) {
+          if (!o) {
+            for (; u.length && (c = u[u.length - 1][0], !(c !== "space" && c !== "comment"));) {
+              this.tokenizer.back(u.pop());
+            }
+          }
+          this.decl(u, o);
+        } else this.unknownWord(u);
+      }
+      rule(e) {
+        e.pop();
+        let t = new If();
+        this.init(t, e[0][2]),
+          t.raws.between = this.spacesAndCommentsFromEnd(e),
+          this.raw(t, "selector", e),
+          this.current = t;
+      }
+      decl(e, t) {
+        let i = new t0();
+        this.init(i, e[0][2]);
+        let n = e[e.length - 1];
+        for (
+          n[0] === ";" && (this.semicolon = !0, e.pop()), i.source.end = this.getPosition(n[3] || n[2] || a0(e));
+          e[0][0] !== "word";
+        ) e.length === 1 && this.unknownWord(e), i.raws.before += e.shift()[1];
+        for (i.source.start = this.getPosition(e[0][2]), i.prop = ""; e.length;) {
+          let c = e[0][0];
+          if (c === ":" || c === "space" || c === "comment") break;
+          i.prop += e.shift()[1];
+        }
+        i.raws.between = "";
+        let s;
+        for (; e.length;) {
+          if (s = e.shift(), s[0] === ":") {
+            i.raws.between += s[1];
+            break;
+          } else s[0] === "word" && /\w/.test(s[1]) && this.unknownWord([s]), i.raws.between += s[1];
+        }
+        (i.prop[0] === "_" || i.prop[0] === "*") && (i.raws.before += i.prop[0], i.prop = i.prop.slice(1));
+        let a = [], o;
+        for (; e.length && (o = e[0][0], !(o !== "space" && o !== "comment"));) a.push(e.shift());
+        this.precheckMissedSemicolon(e);
+        for (let c = e.length - 1; c >= 0; c--) {
+          if (s = e[c], s[1].toLowerCase() === "!important") {
+            i.important = !0;
+            let f = this.stringFrom(e, c);
+            f = this.spacesFromEnd(e) + f, f !== " !important" && (i.raws.important = f);
+            break;
+          } else if (s[1].toLowerCase() === "important") {
+            let f = e.slice(0), p = "";
+            for (let d = c; d > 0; d--) {
+              let h = f[d][0];
+              if (p.trim().indexOf("!") === 0 && h !== "space") break;
+              p = f.pop()[1] + p;
+            }
+            p.trim().indexOf("!") === 0 && (i.important = !0, i.raws.important = p, e = f);
+          }
+          if (s[0] !== "space" && s[0] !== "comment") break;
+        }
+        e.some(c => c[0] !== "space" && c[0] !== "comment") && (i.raws.between += a.map(c => c[1]).join(""), a = []),
+          this.raw(i, "value", a.concat(e), t),
+          i.value.includes(":") && !t && this.checkMissedSemicolon(e);
+      }
+      atrule(e) {
+        let t = new n0();
+        t.name = e[1].slice(1), t.name === "" && this.unnamedAtrule(t, e), this.init(t, e[2]);
+        let i, n, s, a = !1, o = !1, u = [], c = [];
+        for (; !this.tokenizer.endOfFile();) {
+          if (
+            e = this.tokenizer.nextToken(),
+              i = e[0],
+              i === "(" || i === "["
+                ? c.push(i === "(" ? ")" : "]")
+                : i === "{" && c.length > 0
+                ? c.push("}")
+                : i === c[c.length - 1] && c.pop(),
+              c.length === 0
+          ) {
+            if (i === ";") {
+              t.source.end = this.getPosition(e[2]), this.semicolon = !0;
+              break;
+            } else if (i === "{") {
+              o = !0;
+              break;
+            } else if (i === "}") {
+              if (u.length > 0) {
+                for (s = u.length - 1, n = u[s]; n && n[0] === "space";) n = u[--s];
+                n && (t.source.end = this.getPosition(n[3] || n[2]));
+              }
+              this.end(e);
+              break;
+            } else u.push(e);
+          } else u.push(e);
+          if (this.tokenizer.endOfFile()) {
+            a = !0;
+            break;
+          }
+        }
+        t.raws.between = this.spacesAndCommentsFromEnd(u),
+          u.length
+            ? (t.raws.afterName = this.spacesAndCommentsFromStart(u),
+              this.raw(t, "params", u),
+              a
+              && (e = u[u.length - 1],
+                t.source.end = this.getPosition(e[3] || e[2]),
+                this.spaces = t.raws.between,
+                t.raws.between = ""))
+            : (t.raws.afterName = "", t.params = ""),
+          o && (t.nodes = [], this.current = t);
+      }
+      end(e) {
+        this.current.nodes && this.current.nodes.length && (this.current.raws.semicolon = this.semicolon),
+          this.semicolon = !1,
+          this.current.raws.after = (this.current.raws.after || "") + this.spaces,
+          this.spaces = "",
+          this.current.parent
+            ? (this.current.source.end = this.getPosition(e[2]), this.current = this.current.parent)
+            : this.unexpectedClose(e);
+      }
+      endFile() {
+        this.current.parent && this.unclosedBlock(),
+          this.current.nodes && this.current.nodes.length && (this.current.raws.semicolon = this.semicolon),
+          this.current.raws.after = (this.current.raws.after || "") + this.spaces;
+      }
+      freeSemicolon(e) {
+        if (this.spaces += e[1], this.current.nodes) {
+          let t = this.current.nodes[this.current.nodes.length - 1];
+          t && t.type === "rule" && !t.raws.ownSemicolon && (t.raws.ownSemicolon = this.spaces, this.spaces = "");
+        }
+      }
+      getPosition(e) {
+        let t = this.input.fromOffset(e);
+        return { offset: e, line: t.line, column: t.col };
+      }
+      init(e, t) {
+        this.current.push(e),
+          e.source = { start: this.getPosition(t), input: this.input },
+          e.raws.before = this.spaces,
+          this.spaces = "",
+          e.type !== "comment" && (this.semicolon = !1);
+      }
+      raw(e, t, i, n) {
+        let s, a, o = i.length, u = "", c = !0, f, p;
+        for (let d = 0; d < o; d += 1) {
+          s = i[d],
+            a = s[0],
+            a === "space" && d === o - 1 && !n
+              ? c = !1
+              : a === "comment"
+              ? (p = i[d - 1] ? i[d - 1][0] : "empty",
+                f = i[d + 1] ? i[d + 1][0] : "empty",
+                !qf[p] && !qf[f] ? u.slice(-1) === "," ? c = !1 : u += s[1] : c = !1)
+              : u += s[1];
+        }
+        if (!c) {
+          let d = i.reduce((h, y) => h + y[1], "");
+          e.raws[t] = { value: u, raw: d };
+        }
+        e[t] = u;
+      }
+      spacesAndCommentsFromEnd(e) {
+        let t, i = "";
+        for (; e.length && (t = e[e.length - 1][0], !(t !== "space" && t !== "comment"));) i = e.pop()[1] + i;
+        return i;
+      }
+      spacesAndCommentsFromStart(e) {
+        let t, i = "";
+        for (; e.length && (t = e[0][0], !(t !== "space" && t !== "comment"));) i += e.shift()[1];
+        return i;
+      }
+      spacesFromEnd(e) {
+        let t, i = "";
+        for (; e.length && (t = e[e.length - 1][0], t === "space");) i = e.pop()[1] + i;
+        return i;
+      }
+      stringFrom(e, t) {
+        let i = "";
+        for (let n = t; n < e.length; n++) i += e[n][1];
+        return e.splice(t, e.length - t), i;
+      }
+      colon(e) {
+        let t = 0, i, n, s;
+        for (let [a, o] of e.entries()) {
+          if (i = o, n = i[0], n === "(" && (t += 1), n === ")" && (t -= 1), t === 0 && n === ":") {
+            if (!s) this.doubleColon(i);
+            else {
+              if (s[0] === "word" && s[1] === "progid") continue;
+              return a;
+            }
+          }
+          s = i;
+        }
+        return !1;
+      }
+      unclosedBracket(e) {
+        throw this.input.error("Unclosed bracket", { offset: e[2] }, { offset: e[2] + 1 });
+      }
+      unknownWord(e) {
+        throw this.input.error("Unknown word", { offset: e[0][2] }, { offset: e[0][2] + e[0][1].length });
+      }
+      unexpectedClose(e) {
+        throw this.input.error("Unexpected }", { offset: e[2] }, { offset: e[2] + 1 });
+      }
+      unclosedBlock() {
+        let e = this.current.source.start;
+        throw this.input.error("Unclosed block", e.line, e.column);
+      }
+      doubleColon(e) {
+        throw this.input.error("Double colon", { offset: e[2] }, { offset: e[2] + e[1].length });
+      }
+      unnamedAtrule(e, t) {
+        throw this.input.error("At-rule without name", { offset: t[2] }, { offset: t[2] + t[1].length });
+      }
+      precheckMissedSemicolon() {}
+      checkMissedSemicolon(e) {
+        let t = this.colon(e);
+        if (t === !1) return;
+        let i = 0, n;
+        for (let s = t - 1; s >= 0 && (n = e[s], !(n[0] !== "space" && (i += 1, i === 2))); s--);
+        throw this.input.error("Missed semicolon", n[0] === "word" ? n[3] + 1 : n[2]);
+      }
+    };
+    Mf.exports = Rf;
+  });
+  var Nf = v(() => {
+    l();
+  });
+  var Bf = v((G5, Lf) => {
+    l();
+    var o0 = "useandom-26T198340PX75pxJACKVERYMINDBUSHWOLF_GQZbfghjklqvwyzrict",
+      l0 = (r, e = 21) => (t = e) => {
+        let i = "", n = t;
+        for (; n--;) i += r[Math.random() * r.length | 0];
+        return i;
+      },
+      u0 = (r = 21) => {
+        let e = "", t = r;
+        for (; t--;) e += o0[Math.random() * 64 | 0];
+        return e;
+      };
+    Lf.exports = { nanoid: u0, customAlphabet: l0 };
+  });
+  var Ss = v((H5, $f) => {
+    l();
+    $f.exports = {};
+  });
+  var Li = v((Y5, Uf) => {
+    l();
+    "use strict";
+    var { SourceMapConsumer: f0, SourceMapGenerator: c0 } = Nf(),
+      { fileURLToPath: jf, pathToFileURL: Ni } = (fs(), Uu),
+      { resolve: _s, isAbsolute: Cs } = (dt(), ju),
+      { nanoid: p0 } = Bf(),
+      As = cs(),
+      zf = yi(),
+      d0 = Ss(),
+      Os = Symbol("fromOffsetCache"),
+      h0 = Boolean(f0 && c0),
+      Vf = Boolean(_s && Cs),
+      vr = class {
+        constructor(e, t = {}) {
+          if (e === null || typeof e == "undefined" || typeof e == "object" && !e.toString) {
+            throw new Error(`PostCSS received ${e} instead of CSS string`);
+          }
+          if (
+            this.css = e.toString(),
+              this.css[0] === "\uFEFF" || this.css[0] === "\uFFFE"
+                ? (this.hasBOM = !0, this.css = this.css.slice(1))
+                : this.hasBOM = !1,
+              t.from && (!Vf || /^\w+:\/\//.test(t.from) || Cs(t.from) ? this.file = t.from : this.file = _s(t.from)),
+              Vf && h0
+          ) {
+            let i = new d0(this.css, t);
+            if (i.text) {
+              this.map = i;
+              let n = i.consumer().file;
+              !this.file && n && (this.file = this.mapResolve(n));
+            }
+          }
+          this.file || (this.id = "<input css " + p0(6) + ">"), this.map && (this.map.file = this.from);
+        }
+        fromOffset(e) {
+          let t, i;
+          if (this[Os]) i = this[Os];
+          else {
+            let s = this.css.split(`
+`);
+            i = new Array(s.length);
+            let a = 0;
+            for (let o = 0, u = s.length; o < u; o++) i[o] = a, a += s[o].length + 1;
+            this[Os] = i;
+          }
+          t = i[i.length - 1];
+          let n = 0;
+          if (e >= t) n = i.length - 1;
+          else {
+            let s = i.length - 2, a;
+            for (; n < s;) {
+              if (a = n + (s - n >> 1), e < i[a]) s = a - 1;
+              else if (e >= i[a + 1]) n = a + 1;
+              else {
+                n = a;
+                break;
+              }
+            }
+          }
+          return { line: n + 1, col: e - i[n] + 1 };
+        }
+        error(e, t, i, n = {}) {
+          let s, a, o;
+          if (t && typeof t == "object") {
+            let c = t, f = i;
+            if (typeof c.offset == "number") {
+              let p = this.fromOffset(c.offset);
+              t = p.line, i = p.col;
+            } else t = c.line, i = c.column;
+            if (typeof f.offset == "number") {
+              let p = this.fromOffset(f.offset);
+              a = p.line, o = p.col;
+            } else a = f.line, o = f.column;
+          } else if (!i) {
+            let c = this.fromOffset(t);
+            t = c.line, i = c.col;
+          }
+          let u = this.origin(t, i, a, o);
+          return u
+            ? s = new zf(
+              e,
+              u.endLine === void 0 ? u.line : { line: u.line, column: u.column },
+              u.endLine === void 0 ? u.column : { line: u.endLine, column: u.endColumn },
+              u.source,
+              u.file,
+              n.plugin,
+            )
+            : s = new zf(
+              e,
+              a === void 0 ? t : { line: t, column: i },
+              a === void 0 ? i : { line: a, column: o },
+              this.css,
+              this.file,
+              n.plugin,
+            ),
+            s.input = { line: t, column: i, endLine: a, endColumn: o, source: this.css },
+            this.file && (Ni && (s.input.url = Ni(this.file).toString()), s.input.file = this.file),
+            s;
+        }
+        origin(e, t, i, n) {
+          if (!this.map) return !1;
+          let s = this.map.consumer(), a = s.originalPositionFor({ line: e, column: t });
+          if (!a.source) return !1;
+          let o;
+          typeof i == "number" && (o = s.originalPositionFor({ line: i, column: n }));
+          let u;
+          Cs(a.source)
+            ? u = Ni(a.source)
+            : u = new URL(a.source, this.map.consumer().sourceRoot || Ni(this.map.mapFile));
+          let c = { url: u.toString(), line: a.line, column: a.column, endLine: o && o.line, endColumn: o && o.column };
+          if (u.protocol === "file:") {
+            if (jf) c.file = jf(u);
+            else throw new Error("file: protocol is not available in this PostCSS build");
+          }
+          let f = s.sourceContentFor(a.source);
+          return f && (c.source = f), c;
+        }
+        mapResolve(e) {
+          return /^\w+:\/\//.test(e) ? e : _s(this.map.consumer().sourceRoot || this.map.root || ".", e);
+        }
+        get from() {
+          return this.file || this.id;
+        }
+        toJSON() {
+          let e = {};
+          for (let t of ["hasBOM", "css", "file", "id"]) this[t] != null && (e[t] = this[t]);
+          return this.map && (e.map = { ...this.map }, e.map.consumerCache && (e.map.consumerCache = void 0)), e;
+        }
+      };
+    Uf.exports = vr;
+    vr.default = vr;
+    As && As.registerInput && As.registerInput(vr);
+  });
+  var $i = v((Q5, Wf) => {
+    l();
+    "use strict";
+    var m0 = rt(), g0 = Ff(), y0 = Li();
+    function Bi(r, e) {
+      let t = new y0(r, e), i = new g0(t);
+      try {
+        i.parse();
+      } catch (n) {
+        throw n;
+      }
+      return i.root;
+    }
+    Wf.exports = Bi;
+    Bi.default = Bi;
+    m0.registerParse(Bi);
+  });
+  var Ps = v((X5, Qf) => {
+    l();
+    "use strict";
+    var { isClean: qe, my: b0 } = bi(),
+      w0 = gs(),
+      v0 = pr(),
+      x0 = rt(),
+      k0 = _i(),
+      J5 = ws(),
+      Gf = Oi(),
+      S0 = $i(),
+      _0 = Ct(),
+      C0 = {
+        document: "Document",
+        root: "Root",
+        atrule: "AtRule",
+        rule: "Rule",
+        decl: "Declaration",
+        comment: "Comment",
+      },
+      A0 = {
+        postcssPlugin: !0,
+        prepare: !0,
+        Once: !0,
+        Document: !0,
+        Root: !0,
+        Declaration: !0,
+        Rule: !0,
+        AtRule: !0,
+        Comment: !0,
+        DeclarationExit: !0,
+        RuleExit: !0,
+        AtRuleExit: !0,
+        CommentExit: !0,
+        RootExit: !0,
+        DocumentExit: !0,
+        OnceExit: !0,
+      },
+      O0 = { postcssPlugin: !0, prepare: !0, Once: !0 },
+      At = 0;
+    function xr(r) {
+      return typeof r == "object" && typeof r.then == "function";
+    }
+    function Hf(r) {
+      let e = !1, t = C0[r.type];
+      return r.type === "decl" ? e = r.prop.toLowerCase() : r.type === "atrule" && (e = r.name.toLowerCase()),
+        e && r.append
+          ? [t, t + "-" + e, At, t + "Exit", t + "Exit-" + e]
+          : e
+          ? [t, t + "-" + e, t + "Exit", t + "Exit-" + e]
+          : r.append
+          ? [t, At, t + "Exit"]
+          : [t, t + "Exit"];
+    }
+    function Yf(r) {
+      let e;
+      return r.type === "document"
+        ? e = ["Document", At, "DocumentExit"]
+        : r.type === "root"
+        ? e = ["Root", At, "RootExit"]
+        : e = Hf(r),
+        { node: r, events: e, eventIndex: 0, visitors: [], visitorIndex: 0, iterator: 0 };
+    }
+    function Es(r) {
+      return r[qe] = !1, r.nodes && r.nodes.forEach(e => Es(e)), r;
+    }
+    var Ts = {},
+      ze = class {
+        constructor(e, t, i) {
+          this.stringified = !1, this.processed = !1;
+          let n;
+          if (typeof t == "object" && t !== null && (t.type === "root" || t.type === "document")) n = Es(t);
+          else if (t instanceof ze || t instanceof Gf) {
+            n = Es(t.root),
+              t.map
+              && (typeof i.map == "undefined" && (i.map = {}), i.map.inline || (i.map.inline = !1), i.map.prev = t.map);
+          } else {
+            let s = S0;
+            i.syntax && (s = i.syntax.parse), i.parser && (s = i.parser), s.parse && (s = s.parse);
+            try {
+              n = s(t, i);
+            } catch (a) {
+              this.processed = !0, this.error = a;
+            }
+            n && !n[b0] && x0.rebuild(n);
+          }
+          this.result = new Gf(e, n, i),
+            this.helpers = { ...Ts, result: this.result, postcss: Ts },
+            this.plugins = this.processor.plugins.map(s =>
+              typeof s == "object" && s.prepare ? { ...s, ...s.prepare(this.result) } : s
+            );
+        }
+        get [Symbol.toStringTag]() {
+          return "LazyResult";
+        }
+        get processor() {
+          return this.result.processor;
+        }
+        get opts() {
+          return this.result.opts;
+        }
+        get css() {
+          return this.stringify().css;
+        }
+        get content() {
+          return this.stringify().content;
+        }
+        get map() {
+          return this.stringify().map;
+        }
+        get root() {
+          return this.sync().root;
+        }
+        get messages() {
+          return this.sync().messages;
+        }
+        warnings() {
+          return this.sync().warnings();
+        }
+        toString() {
+          return this.css;
+        }
+        then(e, t) {
+          return this.async().then(e, t);
+        }
+        catch(e) {
+          return this.async().catch(e);
+        }
+        finally(e) {
+          return this.async().then(e, e);
+        }
+        async() {
+          return this.error
+            ? Promise.reject(this.error)
+            : this.processed
+            ? Promise.resolve(this.result)
+            : (this.processing || (this.processing = this.runAsync()), this.processing);
+        }
+        sync() {
+          if (this.error) throw this.error;
+          if (this.processed) return this.result;
+          if (this.processed = !0, this.processing) throw this.getAsyncError();
+          for (let e of this.plugins) {
+            let t = this.runOnRoot(e);
+            if (xr(t)) throw this.getAsyncError();
+          }
+          if (this.prepareVisitors(), this.hasListener) {
+            let e = this.result.root;
+            for (; !e[qe];) e[qe] = !0, this.walkSync(e);
+            if (this.listeners.OnceExit) {
+              if (e.type === "document") for (let t of e.nodes) this.visitSync(this.listeners.OnceExit, t);
+              else this.visitSync(this.listeners.OnceExit, e);
+            }
+          }
+          return this.result;
+        }
+        stringify() {
+          if (this.error) throw this.error;
+          if (this.stringified) return this.result;
+          this.stringified = !0, this.sync();
+          let e = this.result.opts, t = v0;
+          e.syntax && (t = e.syntax.stringify), e.stringifier && (t = e.stringifier), t.stringify && (t = t.stringify);
+          let n = new w0(t, this.result.root, this.result.opts).generate();
+          return this.result.css = n[0], this.result.map = n[1], this.result;
+        }
+        walkSync(e) {
+          e[qe] = !0;
+          let t = Hf(e);
+          for (let i of t) {
+            if (i === At) {
+              e.nodes && e.each(n => {
+                n[qe] || this.walkSync(n);
+              });
+            } else {
+              let n = this.listeners[i];
+              if (n && this.visitSync(n, e.toProxy())) return;
+            }
+          }
+        }
+        visitSync(e, t) {
+          for (let [i, n] of e) {
+            this.result.lastPlugin = i;
+            let s;
+            try {
+              s = n(t, this.helpers);
+            } catch (a) {
+              throw this.handleError(a, t.proxyOf);
+            }
+            if (t.type !== "root" && t.type !== "document" && !t.parent) return !0;
+            if (xr(s)) throw this.getAsyncError();
+          }
+        }
+        runOnRoot(e) {
+          this.result.lastPlugin = e;
+          try {
+            if (typeof e == "object" && e.Once) {
+              if (this.result.root.type === "document") {
+                let t = this.result.root.nodes.map(i => e.Once(i, this.helpers));
+                return xr(t[0]) ? Promise.all(t) : t;
+              }
+              return e.Once(this.result.root, this.helpers);
+            } else if (typeof e == "function") return e(this.result.root, this.result);
+          } catch (t) {
+            throw this.handleError(t);
+          }
+        }
+        getAsyncError() {
+          throw new Error("Use process(css).then(cb) to work with async plugins");
+        }
+        handleError(e, t) {
+          let i = this.result.lastPlugin;
+          try {
+            t && t.addToError(e),
+              this.error = e,
+              e.name === "CssSyntaxError" && !e.plugin
+                ? (e.plugin = i.postcssPlugin, e.setMessage())
+                : i.postcssVersion;
+          } catch (n) {
+            console && console.error && console.error(n);
+          }
+          return e;
+        }
+        async runAsync() {
+          this.plugin = 0;
+          for (let e = 0; e < this.plugins.length; e++) {
+            let t = this.plugins[e], i = this.runOnRoot(t);
+            if (xr(i)) {
+              try {
+                await i;
+              } catch (n) {
+                throw this.handleError(n);
+              }
+            }
+          }
+          if (this.prepareVisitors(), this.hasListener) {
+            let e = this.result.root;
+            for (; !e[qe];) {
+              e[qe] = !0;
+              let t = [Yf(e)];
+              for (; t.length > 0;) {
+                let i = this.visitTick(t);
+                if (xr(i)) {
+                  try {
+                    await i;
+                  } catch (n) {
+                    let s = t[t.length - 1].node;
+                    throw this.handleError(n, s);
+                  }
+                }
+              }
+            }
+            if (this.listeners.OnceExit) {
+              for (let [t, i] of this.listeners.OnceExit) {
+                this.result.lastPlugin = t;
+                try {
+                  if (e.type === "document") {
+                    let n = e.nodes.map(s => i(s, this.helpers));
+                    await Promise.all(n);
+                  } else await i(e, this.helpers);
+                } catch (n) {
+                  throw this.handleError(n);
+                }
+              }
+            }
+          }
+          return this.processed = !0, this.stringify();
+        }
+        prepareVisitors() {
+          this.listeners = {};
+          let e = (t, i, n) => {
+            this.listeners[i] || (this.listeners[i] = []), this.listeners[i].push([t, n]);
+          };
+          for (let t of this.plugins) {
+            if (typeof t == "object") {
+              for (let i in t) {
+                if (!A0[i] && /^[A-Z]/.test(i)) {
+                  throw new Error(
+                    `Unknown event ${i} in ${t.postcssPlugin}. Try to update PostCSS (${this.processor.version} now).`,
+                  );
+                }
+                if (!O0[i]) {
+                  if (typeof t[i] == "object") {
+                    for (let n in t[i]) {
+                      n === "*"
+                        ? e(t, i, t[i][n])
+                        : e(t, i + "-" + n.toLowerCase(), t[i][n]);
+                    }
+                  } else typeof t[i] == "function" && e(t, i, t[i]);
+                }
+              }
+            }
+          }
+          this.hasListener = Object.keys(this.listeners).length > 0;
+        }
+        visitTick(e) {
+          let t = e[e.length - 1], { node: i, visitors: n } = t;
+          if (i.type !== "root" && i.type !== "document" && !i.parent) {
+            e.pop();
+            return;
+          }
+          if (n.length > 0 && t.visitorIndex < n.length) {
+            let [a, o] = n[t.visitorIndex];
+            t.visitorIndex += 1,
+              t.visitorIndex === n.length && (t.visitors = [], t.visitorIndex = 0),
+              this.result.lastPlugin = a;
+            try {
+              return o(i.toProxy(), this.helpers);
+            } catch (u) {
+              throw this.handleError(u, i);
+            }
+          }
+          if (t.iterator !== 0) {
+            let a = t.iterator, o;
+            for (; o = i.nodes[i.indexes[a]];) {
+              if (i.indexes[a] += 1, !o[qe]) {
+                o[qe] = !0, e.push(Yf(o));
+                return;
+              }
+            }
+            t.iterator = 0, delete i.indexes[a];
+          }
+          let s = t.events;
+          for (; t.eventIndex < s.length;) {
+            let a = s[t.eventIndex];
+            if (t.eventIndex += 1, a === At) {
+              i.nodes && i.nodes.length && (i[qe] = !0, t.iterator = i.getIterator());
+              return;
+            } else if (this.listeners[a]) {
+              t.visitors = this.listeners[a];
+              return;
+            }
+          }
+          e.pop();
+        }
+      };
+    ze.registerPostcss = r => {
+      Ts = r;
+    };
+    Qf.exports = ze;
+    ze.default = ze;
+    _0.registerLazyResult(ze);
+    k0.registerLazyResult(ze);
+  });
+  var Xf = v((Z5, Jf) => {
+    l();
+    "use strict";
+    var E0 = gs(),
+      T0 = pr(),
+      K5 = ws(),
+      P0 = $i(),
+      D0 = Oi(),
+      ji = class {
+        constructor(e, t, i) {
+          t = t.toString(),
+            this.stringified = !1,
+            this._processor = e,
+            this._css = t,
+            this._opts = i,
+            this._map = void 0;
+          let n, s = T0;
+          this.result = new D0(this._processor, n, this._opts), this.result.css = t;
+          let a = this;
+          Object.defineProperty(this.result, "root", {
+            get() {
+              return a.root;
+            },
+          });
+          let o = new E0(s, n, this._opts, t);
+          if (o.isMap()) {
+            let [u, c] = o.generate();
+            u && (this.result.css = u), c && (this.result.map = c);
+          }
+        }
+        get [Symbol.toStringTag]() {
+          return "NoWorkResult";
+        }
+        get processor() {
+          return this.result.processor;
+        }
+        get opts() {
+          return this.result.opts;
+        }
+        get css() {
+          return this.result.css;
+        }
+        get content() {
+          return this.result.css;
+        }
+        get map() {
+          return this.result.map;
+        }
+        get root() {
+          if (this._root) return this._root;
+          let e, t = P0;
+          try {
+            e = t(this._css, this._opts);
+          } catch (i) {
+            this.error = i;
+          }
+          if (this.error) throw this.error;
+          return this._root = e, e;
+        }
+        get messages() {
+          return [];
+        }
+        warnings() {
+          return [];
+        }
+        toString() {
+          return this._css;
+        }
+        then(e, t) {
+          return this.async().then(e, t);
+        }
+        catch(e) {
+          return this.async().catch(e);
+        }
+        finally(e) {
+          return this.async().then(e, e);
+        }
+        async() {
+          return this.error ? Promise.reject(this.error) : Promise.resolve(this.result);
+        }
+        sync() {
+          if (this.error) throw this.error;
+          return this.result;
+        }
+      };
+    Jf.exports = ji;
+    ji.default = ji;
+  });
+  var Zf = v((eT, Kf) => {
+    l();
+    "use strict";
+    var I0 = Xf(),
+      q0 = Ps(),
+      R0 = _i(),
+      M0 = Ct(),
+      Ot = class {
+        constructor(e = []) {
+          this.version = "8.4.24", this.plugins = this.normalize(e);
+        }
+        use(e) {
+          return this.plugins = this.plugins.concat(this.normalize([e])), this;
+        }
+        process(e, t = {}) {
+          return this.plugins.length === 0 && typeof t.parser == "undefined" && typeof t.stringifier == "undefined"
+              && typeof t.syntax == "undefined"
+            ? new I0(this, e, t)
+            : new q0(this, e, t);
+        }
+        normalize(e) {
+          let t = [];
+          for (let i of e) {
+            if (
+              i.postcss === !0 ? i = i() : i.postcss && (i = i.postcss),
+                typeof i == "object" && Array.isArray(i.plugins)
+            ) t = t.concat(i.plugins);
+            else if (typeof i == "object" && i.postcssPlugin) t.push(i);
+            else if (typeof i == "function") t.push(i);
+            else if (!(typeof i == "object" && (i.parse || i.stringify))) {
+              throw new Error(i + " is not a PostCSS plugin");
+            }
+          }
+          return t;
+        }
+      };
+    Kf.exports = Ot;
+    Ot.default = Ot;
+    M0.registerProcessor(Ot);
+    R0.registerProcessor(Ot);
+  });
+  var tc = v((tT, ec) => {
+    l();
+    "use strict";
+    var F0 = hr(), N0 = Ss(), L0 = mr(), B0 = Mi(), $0 = Li(), j0 = Ct(), z0 = Fi();
+    function kr(r, e) {
+      if (Array.isArray(r)) return r.map(n => kr(n));
+      let { inputs: t, ...i } = r;
+      if (t) {
+        e = [];
+        for (let n of t) {
+          let s = { ...n, __proto__: $0.prototype };
+          s.map && (s.map = { ...s.map, __proto__: N0.prototype }), e.push(s);
+        }
+      }
+      if (i.nodes && (i.nodes = r.nodes.map(n => kr(n, e))), i.source) {
+        let { inputId: n, ...s } = i.source;
+        i.source = s, n != null && (i.source.input = e[n]);
+      }
+      if (i.type === "root") return new j0(i);
+      if (i.type === "decl") return new F0(i);
+      if (i.type === "rule") return new z0(i);
+      if (i.type === "comment") return new L0(i);
+      if (i.type === "atrule") return new B0(i);
+      throw new Error("Unknown node type: " + r.type);
+    }
+    ec.exports = kr;
+    kr.default = kr;
+  });
+  var me = v((rT, lc) => {
+    l();
+    "use strict";
+    var V0 = yi(),
+      rc = hr(),
+      U0 = Ps(),
+      W0 = rt(),
+      Ds = Zf(),
+      G0 = pr(),
+      H0 = tc(),
+      ic = _i(),
+      Y0 = vs(),
+      nc = mr(),
+      sc = Mi(),
+      Q0 = Oi(),
+      J0 = Li(),
+      X0 = $i(),
+      K0 = ks(),
+      ac = Fi(),
+      oc = Ct(),
+      Z0 = dr();
+    function $(...r) {
+      return r.length === 1 && Array.isArray(r[0]) && (r = r[0]), new Ds(r);
+    }
+    $.plugin = function(e, t) {
+      let i = !1;
+      function n(...a) {
+        console && console.warn && !i && (i = !0,
+          console.warn(
+            e + `: postcss.plugin was deprecated. Migration guide:
+https://evilmartians.com/chronicles/postcss-8-plugin-migration`,
+          ),
+          m.env.LANG && m.env.LANG.startsWith("cn")
+          && console.warn(
+            e + `: \u91CC\u9762 postcss.plugin \u88AB\u5F03\u7528. \u8FC1\u79FB\u6307\u5357:
+https://www.w3ctech.com/topic/2226`,
+          ));
+        let o = t(...a);
+        return o.postcssPlugin = e, o.postcssVersion = new Ds().version, o;
+      }
+      let s;
+      return Object.defineProperty(n, "postcss", {
+        get() {
+          return s || (s = n()), s;
+        },
+      }),
+        n.process = function(a, o, u) {
+          return $([n(u)]).process(a, o);
+        },
+        n;
+    };
+    $.stringify = G0;
+    $.parse = X0;
+    $.fromJSON = H0;
+    $.list = K0;
+    $.comment = r => new nc(r);
+    $.atRule = r => new sc(r);
+    $.decl = r => new rc(r);
+    $.rule = r => new ac(r);
+    $.root = r => new oc(r);
+    $.document = r => new ic(r);
+    $.CssSyntaxError = V0;
+    $.Declaration = rc;
+    $.Container = W0;
+    $.Processor = Ds;
+    $.Document = ic;
+    $.Comment = nc;
+    $.Warning = Y0;
+    $.AtRule = sc;
+    $.Result = Q0;
+    $.Input = J0;
+    $.Rule = ac;
+    $.Root = oc;
+    $.Node = Z0;
+    U0.registerPostcss($);
+    lc.exports = $;
+    $.default = $;
+  });
+  var U,
+    j,
+    iT,
+    nT,
+    sT,
+    aT,
+    oT,
+    lT,
+    uT,
+    fT,
+    cT,
+    pT,
+    dT,
+    hT,
+    mT,
+    gT,
+    yT,
+    bT,
+    wT,
+    vT,
+    xT,
+    kT,
+    ST,
+    _T,
+    CT,
+    AT,
+    it = C(() => {
+      l();
+      U = K(me()),
+        j = U.default,
+        iT = U.default.stringify,
+        nT = U.default.fromJSON,
+        sT = U.default.plugin,
+        aT = U.default.parse,
+        oT = U.default.list,
+        lT = U.default.document,
+        uT = U.default.comment,
+        fT = U.default.atRule,
+        cT = U.default.rule,
+        pT = U.default.decl,
+        dT = U.default.root,
+        hT = U.default.CssSyntaxError,
+        mT = U.default.Declaration,
+        gT = U.default.Container,
+        yT = U.default.Processor,
+        bT = U.default.Document,
+        wT = U.default.Comment,
+        vT = U.default.Warning,
+        xT = U.default.AtRule,
+        kT = U.default.Result,
+        ST = U.default.Input,
+        _T = U.default.Rule,
+        CT = U.default.Root,
+        AT = U.default.Node;
+    });
+  var Is = v((ET, uc) => {
+    l();
+    uc.exports = function(r, e, t, i, n) {
+      for (e = e.split ? e.split(".") : e, i = 0; i < e.length; i++) r = r ? r[e[i]] : n;
+      return r === n ? t : r;
+    };
+  });
+  var Vi = v((zi, fc) => {
+    l();
+    "use strict";
+    zi.__esModule = !0;
+    zi.default = rv;
+    function ev(r) {
+      for (var e = r.toLowerCase(), t = "", i = !1, n = 0; n < 6 && e[n] !== void 0; n++) {
+        var s = e.charCodeAt(n), a = s >= 97 && s <= 102 || s >= 48 && s <= 57;
+        if (i = s === 32, !a) break;
+        t += e[n];
+      }
+      if (t.length !== 0) {
+        var o = parseInt(t, 16), u = o >= 55296 && o <= 57343;
+        return u || o === 0 || o > 1114111
+          ? ["\uFFFD", t.length + (i ? 1 : 0)]
+          : [String.fromCodePoint(o), t.length + (i ? 1 : 0)];
+      }
+    }
+    var tv = /\\/;
+    function rv(r) {
+      var e = tv.test(r);
+      if (!e) return r;
+      for (var t = "", i = 0; i < r.length; i++) {
+        if (r[i] === "\\") {
+          var n = ev(r.slice(i + 1, i + 7));
+          if (n !== void 0) {
+            t += n[0], i += n[1];
+            continue;
+          }
+          if (r[i + 1] === "\\") {
+            t += "\\", i++;
+            continue;
+          }
+          r.length === i + 1 && (t += r[i]);
+          continue;
+        }
+        t += r[i];
+      }
+      return t;
+    }
+    fc.exports = zi.default;
+  });
+  var pc = v((Ui, cc) => {
+    l();
+    "use strict";
+    Ui.__esModule = !0;
+    Ui.default = iv;
+    function iv(r) {
+      for (var e = arguments.length, t = new Array(e > 1 ? e - 1 : 0), i = 1; i < e; i++) t[i - 1] = arguments[i];
+      for (; t.length > 0;) {
+        var n = t.shift();
+        if (!r[n]) return;
+        r = r[n];
+      }
+      return r;
+    }
+    cc.exports = Ui.default;
+  });
+  var hc = v((Wi, dc) => {
+    l();
+    "use strict";
+    Wi.__esModule = !0;
+    Wi.default = nv;
+    function nv(r) {
+      for (var e = arguments.length, t = new Array(e > 1 ? e - 1 : 0), i = 1; i < e; i++) t[i - 1] = arguments[i];
+      for (; t.length > 0;) {
+        var n = t.shift();
+        r[n] || (r[n] = {}), r = r[n];
+      }
+    }
+    dc.exports = Wi.default;
+  });
+  var gc = v((Gi, mc) => {
+    l();
+    "use strict";
+    Gi.__esModule = !0;
+    Gi.default = sv;
+    function sv(r) {
+      for (var e = "", t = r.indexOf("/*"), i = 0; t >= 0;) {
+        e = e + r.slice(i, t);
+        var n = r.indexOf("*/", t + 2);
+        if (n < 0) return e;
+        i = n + 2, t = r.indexOf("/*", i);
+      }
+      return e = e + r.slice(i), e;
+    }
+    mc.exports = Gi.default;
+  });
+  var Sr = v(Re => {
+    l();
+    "use strict";
+    Re.__esModule = !0;
+    Re.unesc =
+      Re.stripComments =
+      Re.getProp =
+      Re.ensureObject =
+        void 0;
+    var av = Hi(Vi());
+    Re.unesc = av.default;
+    var ov = Hi(pc());
+    Re.getProp = ov.default;
+    var lv = Hi(hc());
+    Re.ensureObject = lv.default;
+    var uv = Hi(gc());
+    Re.stripComments = uv.default;
+    function Hi(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+  });
+  var Ve = v((_r, wc) => {
+    l();
+    "use strict";
+    _r.__esModule = !0;
+    _r.default = void 0;
+    var yc = Sr();
+    function bc(r, e) {
+      for (var t = 0; t < e.length; t++) {
+        var i = e[t];
+        i.enumerable = i.enumerable || !1,
+          i.configurable = !0,
+          "value" in i && (i.writable = !0),
+          Object.defineProperty(r, i.key, i);
+      }
+    }
+    function fv(r, e, t) {
+      return e && bc(r.prototype, e), t && bc(r, t), Object.defineProperty(r, "prototype", { writable: !1 }), r;
+    }
+    var cv = function r(e, t) {
+        if (typeof e != "object" || e === null) return e;
+        var i = new e.constructor();
+        for (var n in e) {
+          if (!!e.hasOwnProperty(n)) {
+            var s = e[n], a = typeof s;
+            n === "parent" && a === "object" ? t && (i[n] = t) : s instanceof Array
+              ? i[n] = s.map(function(o) {
+                return r(o, i);
+              })
+              : i[n] = r(s, i);
+          }
+        }
+        return i;
+      },
+      pv = function() {
+        function r(t) {
+          t === void 0 && (t = {}),
+            Object.assign(this, t),
+            this.spaces = this.spaces || {},
+            this.spaces.before = this.spaces.before || "",
+            this.spaces.after = this.spaces.after || "";
+        }
+        var e = r.prototype;
+        return e.remove = function() {
+          return this.parent && this.parent.removeChild(this), this.parent = void 0, this;
+        },
+          e.replaceWith = function() {
+            if (this.parent) {
+              for (var i in arguments) this.parent.insertBefore(this, arguments[i]);
+              this.remove();
+            }
+            return this;
+          },
+          e.next = function() {
+            return this.parent.at(this.parent.index(this) + 1);
+          },
+          e.prev = function() {
+            return this.parent.at(this.parent.index(this) - 1);
+          },
+          e.clone = function(i) {
+            i === void 0 && (i = {});
+            var n = cv(this);
+            for (var s in i) n[s] = i[s];
+            return n;
+          },
+          e.appendToPropertyAndEscape = function(i, n, s) {
+            this.raws || (this.raws = {});
+            var a = this[i], o = this.raws[i];
+            this[i] = a + n, o || s !== n ? this.raws[i] = (o || a) + s : delete this.raws[i];
+          },
+          e.setPropertyAndEscape = function(i, n, s) {
+            this.raws || (this.raws = {}), this[i] = n, this.raws[i] = s;
+          },
+          e.setPropertyWithoutEscape = function(i, n) {
+            this[i] = n, this.raws && delete this.raws[i];
+          },
+          e.isAtPosition = function(i, n) {
+            if (this.source && this.source.start && this.source.end) {
+              return !(this.source.start.line > i || this.source.end.line < i
+                || this.source.start.line === i && this.source.start.column > n
+                || this.source.end.line === i && this.source.end.column < n);
+            }
+          },
+          e.stringifyProperty = function(i) {
+            return this.raws && this.raws[i] || this[i];
+          },
+          e.valueToString = function() {
+            return String(this.stringifyProperty("value"));
+          },
+          e.toString = function() {
+            return [this.rawSpaceBefore, this.valueToString(), this.rawSpaceAfter].join("");
+          },
+          fv(r, [{
+            key: "rawSpaceBefore",
+            get: function() {
+              var i = this.raws && this.raws.spaces && this.raws.spaces.before;
+              return i === void 0 && (i = this.spaces && this.spaces.before), i || "";
+            },
+            set: function(i) {
+              (0, yc.ensureObject)(this, "raws", "spaces"), this.raws.spaces.before = i;
+            },
+          }, {
+            key: "rawSpaceAfter",
+            get: function() {
+              var i = this.raws && this.raws.spaces && this.raws.spaces.after;
+              return i === void 0 && (i = this.spaces.after), i || "";
+            },
+            set: function(i) {
+              (0, yc.ensureObject)(this, "raws", "spaces"), this.raws.spaces.after = i;
+            },
+          }]),
+          r;
+      }();
+    _r.default = pv;
+    wc.exports = _r.default;
+  });
+  var ae = v(W => {
+    l();
+    "use strict";
+    W.__esModule = !0;
+    W.UNIVERSAL =
+      W.TAG =
+      W.STRING =
+      W.SELECTOR =
+      W.ROOT =
+      W.PSEUDO =
+      W.NESTING =
+      W.ID =
+      W.COMMENT =
+      W.COMBINATOR =
+      W.CLASS =
+      W.ATTRIBUTE =
+        void 0;
+    var dv = "tag";
+    W.TAG = dv;
+    var hv = "string";
+    W.STRING = hv;
+    var mv = "selector";
+    W.SELECTOR = mv;
+    var gv = "root";
+    W.ROOT = gv;
+    var yv = "pseudo";
+    W.PSEUDO = yv;
+    var bv = "nesting";
+    W.NESTING = bv;
+    var wv = "id";
+    W.ID = wv;
+    var vv = "comment";
+    W.COMMENT = vv;
+    var xv = "combinator";
+    W.COMBINATOR = xv;
+    var kv = "class";
+    W.CLASS = kv;
+    var Sv = "attribute";
+    W.ATTRIBUTE = Sv;
+    var _v = "universal";
+    W.UNIVERSAL = _v;
+  });
+  var Yi = v((Cr, Sc) => {
+    l();
+    "use strict";
+    Cr.__esModule = !0;
+    Cr.default = void 0;
+    var Cv = Ov(Ve()), Ue = Av(ae());
+    function vc(r) {
+      if (typeof WeakMap != "function") return null;
+      var e = new WeakMap(), t = new WeakMap();
+      return (vc = function(n) {
+        return n ? t : e;
+      })(r);
+    }
+    function Av(r, e) {
+      if (!e && r && r.__esModule) return r;
+      if (r === null || typeof r != "object" && typeof r != "function") return { default: r };
+      var t = vc(e);
+      if (t && t.has(r)) return t.get(r);
+      var i = {}, n = Object.defineProperty && Object.getOwnPropertyDescriptor;
+      for (var s in r) {
+        if (s !== "default" && Object.prototype.hasOwnProperty.call(r, s)) {
+          var a = n ? Object.getOwnPropertyDescriptor(r, s) : null;
+          a && (a.get || a.set) ? Object.defineProperty(i, s, a) : i[s] = r[s];
+        }
+      }
+      return i.default = r, t && t.set(r, i), i;
+    }
+    function Ov(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function Ev(r, e) {
+      var t = typeof Symbol != "undefined" && r[Symbol.iterator] || r["@@iterator"];
+      if (t) return (t = t.call(r)).next.bind(t);
+      if (Array.isArray(r) || (t = Tv(r)) || e && r && typeof r.length == "number") {
+        t && (r = t);
+        var i = 0;
+        return function() {
+          return i >= r.length ? { done: !0 } : { done: !1, value: r[i++] };
+        };
+      }
+      throw new TypeError(`Invalid attempt to iterate non-iterable instance.
+In order to be iterable, non-array objects must have a [Symbol.iterator]() method.`);
+    }
+    function Tv(r, e) {
+      if (!!r) {
+        if (typeof r == "string") return xc(r, e);
+        var t = Object.prototype.toString.call(r).slice(8, -1);
+        if (t === "Object" && r.constructor && (t = r.constructor.name), t === "Map" || t === "Set") {
+          return Array.from(r);
+        }
+        if (t === "Arguments" || /^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(t)) return xc(r, e);
+      }
+    }
+    function xc(r, e) {
+      (e == null || e > r.length) && (e = r.length);
+      for (var t = 0, i = new Array(e); t < e; t++) i[t] = r[t];
+      return i;
+    }
+    function kc(r, e) {
+      for (var t = 0; t < e.length; t++) {
+        var i = e[t];
+        i.enumerable = i.enumerable || !1,
+          i.configurable = !0,
+          "value" in i && (i.writable = !0),
+          Object.defineProperty(r, i.key, i);
+      }
+    }
+    function Pv(r, e, t) {
+      return e && kc(r.prototype, e), t && kc(r, t), Object.defineProperty(r, "prototype", { writable: !1 }), r;
+    }
+    function Dv(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, qs(r, e);
+    }
+    function qs(r, e) {
+      return qs = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        qs(r, e);
+    }
+    var Iv = function(r) {
+      Dv(e, r);
+      function e(i) {
+        var n;
+        return n = r.call(this, i) || this, n.nodes || (n.nodes = []), n;
+      }
+      var t = e.prototype;
+      return t.append = function(n) {
+        return n.parent = this, this.nodes.push(n), this;
+      },
+        t.prepend = function(n) {
+          return n.parent = this, this.nodes.unshift(n), this;
+        },
+        t.at = function(n) {
+          return this.nodes[n];
+        },
+        t.index = function(n) {
+          return typeof n == "number" ? n : this.nodes.indexOf(n);
+        },
+        t.removeChild = function(n) {
+          n = this.index(n), this.at(n).parent = void 0, this.nodes.splice(n, 1);
+          var s;
+          for (var a in this.indexes) s = this.indexes[a], s >= n && (this.indexes[a] = s - 1);
+          return this;
+        },
+        t.removeAll = function() {
+          for (var n = Ev(this.nodes), s; !(s = n()).done;) {
+            var a = s.value;
+            a.parent = void 0;
+          }
+          return this.nodes = [], this;
+        },
+        t.empty = function() {
+          return this.removeAll();
+        },
+        t.insertAfter = function(n, s) {
+          s.parent = this;
+          var a = this.index(n);
+          this.nodes.splice(a + 1, 0, s), s.parent = this;
+          var o;
+          for (var u in this.indexes) o = this.indexes[u], a <= o && (this.indexes[u] = o + 1);
+          return this;
+        },
+        t.insertBefore = function(n, s) {
+          s.parent = this;
+          var a = this.index(n);
+          this.nodes.splice(a, 0, s), s.parent = this;
+          var o;
+          for (var u in this.indexes) o = this.indexes[u], o <= a && (this.indexes[u] = o + 1);
+          return this;
+        },
+        t._findChildAtPosition = function(n, s) {
+          var a = void 0;
+          return this.each(function(o) {
+            if (o.atPosition) {
+              var u = o.atPosition(n, s);
+              if (u) return a = u, !1;
+            } else if (o.isAtPosition(n, s)) return a = o, !1;
+          }),
+            a;
+        },
+        t.atPosition = function(n, s) {
+          if (this.isAtPosition(n, s)) return this._findChildAtPosition(n, s) || this;
+        },
+        t._inferEndPosition = function() {
+          this.last && this.last.source && this.last.source.end
+            && (this.source = this.source || {},
+              this.source.end = this.source.end || {},
+              Object.assign(this.source.end, this.last.source.end));
+        },
+        t.each = function(n) {
+          this.lastEach || (this.lastEach = 0), this.indexes || (this.indexes = {}), this.lastEach++;
+          var s = this.lastEach;
+          if (this.indexes[s] = 0, !!this.length) {
+            for (var a, o; this.indexes[s] < this.length && (a = this.indexes[s], o = n(this.at(a), a), o !== !1);) {
+              this.indexes[s] += 1;
+            }
+            if (delete this.indexes[s], o === !1) return !1;
+          }
+        },
+        t.walk = function(n) {
+          return this.each(function(s, a) {
+            var o = n(s, a);
+            if (o !== !1 && s.length && (o = s.walk(n)), o === !1) return !1;
+          });
+        },
+        t.walkAttributes = function(n) {
+          var s = this;
+          return this.walk(function(a) {
+            if (a.type === Ue.ATTRIBUTE) return n.call(s, a);
+          });
+        },
+        t.walkClasses = function(n) {
+          var s = this;
+          return this.walk(function(a) {
+            if (a.type === Ue.CLASS) return n.call(s, a);
+          });
+        },
+        t.walkCombinators = function(n) {
+          var s = this;
+          return this.walk(function(a) {
+            if (a.type === Ue.COMBINATOR) return n.call(s, a);
+          });
+        },
+        t.walkComments = function(n) {
+          var s = this;
+          return this.walk(function(a) {
+            if (a.type === Ue.COMMENT) return n.call(s, a);
+          });
+        },
+        t.walkIds = function(n) {
+          var s = this;
+          return this.walk(function(a) {
+            if (a.type === Ue.ID) return n.call(s, a);
+          });
+        },
+        t.walkNesting = function(n) {
+          var s = this;
+          return this.walk(function(a) {
+            if (a.type === Ue.NESTING) return n.call(s, a);
+          });
+        },
+        t.walkPseudos = function(n) {
+          var s = this;
+          return this.walk(function(a) {
+            if (a.type === Ue.PSEUDO) return n.call(s, a);
+          });
+        },
+        t.walkTags = function(n) {
+          var s = this;
+          return this.walk(function(a) {
+            if (a.type === Ue.TAG) return n.call(s, a);
+          });
+        },
+        t.walkUniversals = function(n) {
+          var s = this;
+          return this.walk(function(a) {
+            if (a.type === Ue.UNIVERSAL) return n.call(s, a);
+          });
+        },
+        t.split = function(n) {
+          var s = this, a = [];
+          return this.reduce(function(o, u, c) {
+            var f = n.call(s, u);
+            return a.push(u), f ? (o.push(a), a = []) : c === s.length - 1 && o.push(a), o;
+          }, []);
+        },
+        t.map = function(n) {
+          return this.nodes.map(n);
+        },
+        t.reduce = function(n, s) {
+          return this.nodes.reduce(n, s);
+        },
+        t.every = function(n) {
+          return this.nodes.every(n);
+        },
+        t.some = function(n) {
+          return this.nodes.some(n);
+        },
+        t.filter = function(n) {
+          return this.nodes.filter(n);
+        },
+        t.sort = function(n) {
+          return this.nodes.sort(n);
+        },
+        t.toString = function() {
+          return this.map(String).join("");
+        },
+        Pv(e, [{
+          key: "first",
+          get: function() {
+            return this.at(0);
+          },
+        }, {
+          key: "last",
+          get: function() {
+            return this.at(this.length - 1);
+          },
+        }, {
+          key: "length",
+          get: function() {
+            return this.nodes.length;
+          },
+        }]),
+        e;
+    }(Cv.default);
+    Cr.default = Iv;
+    Sc.exports = Cr.default;
+  });
+  var Ms = v((Ar, Cc) => {
+    l();
+    "use strict";
+    Ar.__esModule = !0;
+    Ar.default = void 0;
+    var qv = Mv(Yi()), Rv = ae();
+    function Mv(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function _c(r, e) {
+      for (var t = 0; t < e.length; t++) {
+        var i = e[t];
+        i.enumerable = i.enumerable || !1,
+          i.configurable = !0,
+          "value" in i && (i.writable = !0),
+          Object.defineProperty(r, i.key, i);
+      }
+    }
+    function Fv(r, e, t) {
+      return e && _c(r.prototype, e), t && _c(r, t), Object.defineProperty(r, "prototype", { writable: !1 }), r;
+    }
+    function Nv(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, Rs(r, e);
+    }
+    function Rs(r, e) {
+      return Rs = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        Rs(r, e);
+    }
+    var Lv = function(r) {
+      Nv(e, r);
+      function e(i) {
+        var n;
+        return n = r.call(this, i) || this, n.type = Rv.ROOT, n;
+      }
+      var t = e.prototype;
+      return t.toString = function() {
+        var n = this.reduce(function(s, a) {
+          return s.push(String(a)), s;
+        }, []).join(",");
+        return this.trailingComma ? n + "," : n;
+      },
+        t.error = function(n, s) {
+          return this._error ? this._error(n, s) : new Error(n);
+        },
+        Fv(e, [{
+          key: "errorGenerator",
+          set: function(n) {
+            this._error = n;
+          },
+        }]),
+        e;
+    }(qv.default);
+    Ar.default = Lv;
+    Cc.exports = Ar.default;
+  });
+  var Ns = v((Or, Ac) => {
+    l();
+    "use strict";
+    Or.__esModule = !0;
+    Or.default = void 0;
+    var Bv = jv(Yi()), $v = ae();
+    function jv(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function zv(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, Fs(r, e);
+    }
+    function Fs(r, e) {
+      return Fs = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        Fs(r, e);
+    }
+    var Vv = function(r) {
+      zv(e, r);
+      function e(t) {
+        var i;
+        return i = r.call(this, t) || this, i.type = $v.SELECTOR, i;
+      }
+      return e;
+    }(Bv.default);
+    Or.default = Vv;
+    Ac.exports = Or.default;
+  });
+  var Qi = v((DT, Oc) => {
+    l();
+    "use strict";
+    var Uv = {},
+      Wv = Uv.hasOwnProperty,
+      Gv = function(e, t) {
+        if (!e) return t;
+        var i = {};
+        for (var n in t) i[n] = Wv.call(e, n) ? e[n] : t[n];
+        return i;
+      },
+      Hv = /[ -,\.\/:-@\[-\^`\{-~]/,
+      Yv = /[ -,\.\/:-@\[\]\^`\{-~]/,
+      Qv = /(^|\\+)?(\\[A-F0-9]{1,6})\x20(?![a-fA-F0-9\x20])/g,
+      Ls = function r(e, t) {
+        t = Gv(t, r.options), t.quotes != "single" && t.quotes != "double" && (t.quotes = "single");
+        for (
+          var i = t.quotes == "double" ? "\"" : "'", n = t.isIdentifier, s = e.charAt(0), a = "", o = 0, u = e.length;
+          o < u;
+        ) {
+          var c = e.charAt(o++), f = c.charCodeAt(), p = void 0;
+          if (f < 32 || f > 126) {
+            if (f >= 55296 && f <= 56319 && o < u) {
+              var d = e.charCodeAt(o++);
+              (d & 64512) == 56320 ? f = ((f & 1023) << 10) + (d & 1023) + 65536 : o--;
+            }
+            p = "\\" + f.toString(16).toUpperCase() + " ";
+          } else {t.escapeEverything
+              ? Hv.test(c) ? p = "\\" + c : p = "\\" + f.toString(16).toUpperCase() + " "
+              : /[\t\n\f\r\x0B]/.test(c)
+              ? p = "\\" + f.toString(16).toUpperCase() + " "
+              : c == "\\" || !n && (c == "\"" && i == c || c == "'" && i == c) || n && Yv.test(c)
+              ? p = "\\" + c
+              : p = c;}
+          a += p;
+        }
+        return n && (/^-[-\d]/.test(a) ? a = "\\-" + a.slice(1) : /\d/.test(s) && (a = "\\3" + s + " " + a.slice(1))),
+          a = a.replace(Qv, function(h, y, x) {
+            return y && y.length % 2 ? h : (y || "") + x;
+          }),
+          !n && t.wrap ? i + a + i : a;
+      };
+    Ls.options = { escapeEverything: !1, isIdentifier: !1, quotes: "single", wrap: !1 };
+    Ls.version = "3.0.0";
+    Oc.exports = Ls;
+  });
+  var $s = v((Er, Pc) => {
+    l();
+    "use strict";
+    Er.__esModule = !0;
+    Er.default = void 0;
+    var Jv = Ec(Qi()), Xv = Sr(), Kv = Ec(Ve()), Zv = ae();
+    function Ec(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function Tc(r, e) {
+      for (var t = 0; t < e.length; t++) {
+        var i = e[t];
+        i.enumerable = i.enumerable || !1,
+          i.configurable = !0,
+          "value" in i && (i.writable = !0),
+          Object.defineProperty(r, i.key, i);
+      }
+    }
+    function ex(r, e, t) {
+      return e && Tc(r.prototype, e), t && Tc(r, t), Object.defineProperty(r, "prototype", { writable: !1 }), r;
+    }
+    function tx(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, Bs(r, e);
+    }
+    function Bs(r, e) {
+      return Bs = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        Bs(r, e);
+    }
+    var rx = function(r) {
+      tx(e, r);
+      function e(i) {
+        var n;
+        return n = r.call(this, i) || this, n.type = Zv.CLASS, n._constructed = !0, n;
+      }
+      var t = e.prototype;
+      return t.valueToString = function() {
+        return "." + r.prototype.valueToString.call(this);
+      },
+        ex(e, [{
+          key: "value",
+          get: function() {
+            return this._value;
+          },
+          set: function(n) {
+            if (this._constructed) {
+              var s = (0, Jv.default)(n, { isIdentifier: !0 });
+              s !== n ? ((0, Xv.ensureObject)(this, "raws"), this.raws.value = s) : this.raws && delete this.raws.value;
+            }
+            this._value = n;
+          },
+        }]),
+        e;
+    }(Kv.default);
+    Er.default = rx;
+    Pc.exports = Er.default;
+  });
+  var zs = v((Tr, Dc) => {
+    l();
+    "use strict";
+    Tr.__esModule = !0;
+    Tr.default = void 0;
+    var ix = sx(Ve()), nx = ae();
+    function sx(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function ax(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, js(r, e);
+    }
+    function js(r, e) {
+      return js = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        js(r, e);
+    }
+    var ox = function(r) {
+      ax(e, r);
+      function e(t) {
+        var i;
+        return i = r.call(this, t) || this, i.type = nx.COMMENT, i;
+      }
+      return e;
+    }(ix.default);
+    Tr.default = ox;
+    Dc.exports = Tr.default;
+  });
+  var Us = v((Pr, Ic) => {
+    l();
+    "use strict";
+    Pr.__esModule = !0;
+    Pr.default = void 0;
+    var lx = fx(Ve()), ux = ae();
+    function fx(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function cx(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, Vs(r, e);
+    }
+    function Vs(r, e) {
+      return Vs = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        Vs(r, e);
+    }
+    var px = function(r) {
+      cx(e, r);
+      function e(i) {
+        var n;
+        return n = r.call(this, i) || this, n.type = ux.ID, n;
+      }
+      var t = e.prototype;
+      return t.valueToString = function() {
+        return "#" + r.prototype.valueToString.call(this);
+      },
+        e;
+    }(lx.default);
+    Pr.default = px;
+    Ic.exports = Pr.default;
+  });
+  var Ji = v((Dr, Mc) => {
+    l();
+    "use strict";
+    Dr.__esModule = !0;
+    Dr.default = void 0;
+    var dx = qc(Qi()), hx = Sr(), mx = qc(Ve());
+    function qc(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function Rc(r, e) {
+      for (var t = 0; t < e.length; t++) {
+        var i = e[t];
+        i.enumerable = i.enumerable || !1,
+          i.configurable = !0,
+          "value" in i && (i.writable = !0),
+          Object.defineProperty(r, i.key, i);
+      }
+    }
+    function gx(r, e, t) {
+      return e && Rc(r.prototype, e), t && Rc(r, t), Object.defineProperty(r, "prototype", { writable: !1 }), r;
+    }
+    function yx(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, Ws(r, e);
+    }
+    function Ws(r, e) {
+      return Ws = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        Ws(r, e);
+    }
+    var bx = function(r) {
+      yx(e, r);
+      function e() {
+        return r.apply(this, arguments) || this;
+      }
+      var t = e.prototype;
+      return t.qualifiedName = function(n) {
+        return this.namespace ? this.namespaceString + "|" + n : n;
+      },
+        t.valueToString = function() {
+          return this.qualifiedName(r.prototype.valueToString.call(this));
+        },
+        gx(e, [{
+          key: "namespace",
+          get: function() {
+            return this._namespace;
+          },
+          set: function(n) {
+            if (n === !0 || n === "*" || n === "&") {
+              this._namespace = n, this.raws && delete this.raws.namespace;
+              return;
+            }
+            var s = (0, dx.default)(n, { isIdentifier: !0 });
+            this._namespace = n,
+              s !== n
+                ? ((0, hx.ensureObject)(this, "raws"), this.raws.namespace = s)
+                : this.raws && delete this.raws.namespace;
+          },
+        }, {
+          key: "ns",
+          get: function() {
+            return this._namespace;
+          },
+          set: function(n) {
+            this.namespace = n;
+          },
+        }, {
+          key: "namespaceString",
+          get: function() {
+            if (this.namespace) {
+              var n = this.stringifyProperty("namespace");
+              return n === !0 ? "" : n;
+            } else return "";
+          },
+        }]),
+        e;
+    }(mx.default);
+    Dr.default = bx;
+    Mc.exports = Dr.default;
+  });
+  var Hs = v((Ir, Fc) => {
+    l();
+    "use strict";
+    Ir.__esModule = !0;
+    Ir.default = void 0;
+    var wx = xx(Ji()), vx = ae();
+    function xx(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function kx(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, Gs(r, e);
+    }
+    function Gs(r, e) {
+      return Gs = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        Gs(r, e);
+    }
+    var Sx = function(r) {
+      kx(e, r);
+      function e(t) {
+        var i;
+        return i = r.call(this, t) || this, i.type = vx.TAG, i;
+      }
+      return e;
+    }(wx.default);
+    Ir.default = Sx;
+    Fc.exports = Ir.default;
+  });
+  var Qs = v((qr, Nc) => {
+    l();
+    "use strict";
+    qr.__esModule = !0;
+    qr.default = void 0;
+    var _x = Ax(Ve()), Cx = ae();
+    function Ax(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function Ox(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, Ys(r, e);
+    }
+    function Ys(r, e) {
+      return Ys = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        Ys(r, e);
+    }
+    var Ex = function(r) {
+      Ox(e, r);
+      function e(t) {
+        var i;
+        return i = r.call(this, t) || this, i.type = Cx.STRING, i;
+      }
+      return e;
+    }(_x.default);
+    qr.default = Ex;
+    Nc.exports = qr.default;
+  });
+  var Xs = v((Rr, Lc) => {
+    l();
+    "use strict";
+    Rr.__esModule = !0;
+    Rr.default = void 0;
+    var Tx = Dx(Yi()), Px = ae();
+    function Dx(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function Ix(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, Js(r, e);
+    }
+    function Js(r, e) {
+      return Js = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        Js(r, e);
+    }
+    var qx = function(r) {
+      Ix(e, r);
+      function e(i) {
+        var n;
+        return n = r.call(this, i) || this, n.type = Px.PSEUDO, n;
+      }
+      var t = e.prototype;
+      return t.toString = function() {
+        var n = this.length ? "(" + this.map(String).join(",") + ")" : "";
+        return [this.rawSpaceBefore, this.stringifyProperty("value"), n, this.rawSpaceAfter].join("");
+      },
+        e;
+    }(Tx.default);
+    Rr.default = qx;
+    Lc.exports = Rr.default;
+  });
+  var Bc = {};
+  Ce(Bc, { deprecate: () => Rx });
+  function Rx(r) {
+    return r;
+  }
+  var $c = C(() => {
+    l();
+  });
+  var zc = v((IT, jc) => {
+    l();
+    jc.exports = ($c(), Bc).deprecate;
+  });
+  var ia = v(Nr => {
+    l();
+    "use strict";
+    Nr.__esModule = !0;
+    Nr.default = void 0;
+    Nr.unescapeValue = ta;
+    var Mr = Zs(Qi()), Mx = Zs(Vi()), Fx = Zs(Ji()), Nx = ae(), Ks;
+    function Zs(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function Vc(r, e) {
+      for (var t = 0; t < e.length; t++) {
+        var i = e[t];
+        i.enumerable = i.enumerable || !1,
+          i.configurable = !0,
+          "value" in i && (i.writable = !0),
+          Object.defineProperty(r, i.key, i);
+      }
+    }
+    function Lx(r, e, t) {
+      return e && Vc(r.prototype, e), t && Vc(r, t), Object.defineProperty(r, "prototype", { writable: !1 }), r;
+    }
+    function Bx(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, ea(r, e);
+    }
+    function ea(r, e) {
+      return ea = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        ea(r, e);
+    }
+    var Fr = zc(),
+      $x = /^('|")([^]*)\1$/,
+      jx = Fr(
+        function() {},
+        "Assigning an attribute a value containing characters that might need to be escaped is deprecated. Call attribute.setValue() instead.",
+      ),
+      zx = Fr(
+        function() {},
+        "Assigning attr.quoted is deprecated and has no effect. Assign to attr.quoteMark instead.",
+      ),
+      Vx = Fr(
+        function() {},
+        "Constructing an Attribute selector with a value without specifying quoteMark is deprecated. Note: The value should be unescaped now.",
+      );
+    function ta(r) {
+      var e = !1, t = null, i = r, n = i.match($x);
+      return n && (t = n[1], i = n[2]),
+        i = (0, Mx.default)(i),
+        i !== r && (e = !0),
+        { deprecatedUsage: e, unescaped: i, quoteMark: t };
+    }
+    function Ux(r) {
+      if (r.quoteMark !== void 0 || r.value === void 0) return r;
+      Vx();
+      var e = ta(r.value), t = e.quoteMark, i = e.unescaped;
+      return r.raws || (r.raws = {}),
+        r.raws.value === void 0 && (r.raws.value = r.value),
+        r.value = i,
+        r.quoteMark = t,
+        r;
+    }
+    var Xi = function(r) {
+      Bx(e, r);
+      function e(i) {
+        var n;
+        return i === void 0 && (i = {}),
+          n = r.call(this, Ux(i)) || this,
+          n.type = Nx.ATTRIBUTE,
+          n.raws = n.raws || {},
+          Object.defineProperty(n.raws, "unquoted", {
+            get: Fr(function() {
+              return n.value;
+            }, "attr.raws.unquoted is deprecated. Call attr.value instead."),
+            set: Fr(function() {
+              return n.value;
+            }, "Setting attr.raws.unquoted is deprecated and has no effect. attr.value is unescaped by default now."),
+          }),
+          n._constructed = !0,
+          n;
+      }
+      var t = e.prototype;
+      return t.getQuotedValue = function(n) {
+        n === void 0 && (n = {});
+        var s = this._determineQuoteMark(n), a = ra[s], o = (0, Mr.default)(this._value, a);
+        return o;
+      },
+        t._determineQuoteMark = function(n) {
+          return n.smart ? this.smartQuoteMark(n) : this.preferredQuoteMark(n);
+        },
+        t.setValue = function(n, s) {
+          s === void 0 && (s = {}),
+            this._value = n,
+            this._quoteMark = this._determineQuoteMark(s),
+            this._syncRawValue();
+        },
+        t.smartQuoteMark = function(n) {
+          var s = this.value, a = s.replace(/[^']/g, "").length, o = s.replace(/[^"]/g, "").length;
+          if (a + o === 0) {
+            var u = (0, Mr.default)(s, { isIdentifier: !0 });
+            if (u === s) return e.NO_QUOTE;
+            var c = this.preferredQuoteMark(n);
+            if (c === e.NO_QUOTE) {
+              var f = this.quoteMark || n.quoteMark || e.DOUBLE_QUOTE, p = ra[f], d = (0, Mr.default)(s, p);
+              if (d.length < u.length) return f;
+            }
+            return c;
+          } else return o === a ? this.preferredQuoteMark(n) : o < a ? e.DOUBLE_QUOTE : e.SINGLE_QUOTE;
+        },
+        t.preferredQuoteMark = function(n) {
+          var s = n.preferCurrentQuoteMark ? this.quoteMark : n.quoteMark;
+          return s === void 0 && (s = n.preferCurrentQuoteMark ? n.quoteMark : this.quoteMark),
+            s === void 0 && (s = e.DOUBLE_QUOTE),
+            s;
+        },
+        t._syncRawValue = function() {
+          var n = (0, Mr.default)(this._value, ra[this.quoteMark]);
+          n === this._value ? this.raws && delete this.raws.value : this.raws.value = n;
+        },
+        t._handleEscapes = function(n, s) {
+          if (this._constructed) {
+            var a = (0, Mr.default)(s, { isIdentifier: !0 });
+            a !== s ? this.raws[n] = a : delete this.raws[n];
+          }
+        },
+        t._spacesFor = function(n) {
+          var s = { before: "", after: "" },
+            a = this.spaces[n] || {},
+            o = this.raws.spaces && this.raws.spaces[n] || {};
+          return Object.assign(s, a, o);
+        },
+        t._stringFor = function(n, s, a) {
+          s === void 0 && (s = n), a === void 0 && (a = Uc);
+          var o = this._spacesFor(s);
+          return a(this.stringifyProperty(n), o);
+        },
+        t.offsetOf = function(n) {
+          var s = 1, a = this._spacesFor("attribute");
+          if (s += a.before.length, n === "namespace" || n === "ns") return this.namespace ? s : -1;
+          if (
+            n === "attributeNS" || (s += this.namespaceString.length, this.namespace && (s += 1), n === "attribute")
+          ) return s;
+          s += this.stringifyProperty("attribute").length, s += a.after.length;
+          var o = this._spacesFor("operator");
+          s += o.before.length;
+          var u = this.stringifyProperty("operator");
+          if (n === "operator") return u ? s : -1;
+          s += u.length, s += o.after.length;
+          var c = this._spacesFor("value");
+          s += c.before.length;
+          var f = this.stringifyProperty("value");
+          if (n === "value") return f ? s : -1;
+          s += f.length, s += c.after.length;
+          var p = this._spacesFor("insensitive");
+          return s += p.before.length, n === "insensitive" && this.insensitive ? s : -1;
+        },
+        t.toString = function() {
+          var n = this, s = [this.rawSpaceBefore, "["];
+          return s.push(this._stringFor("qualifiedAttribute", "attribute")),
+            this.operator && (this.value || this.value === "")
+            && (s.push(this._stringFor("operator")),
+              s.push(this._stringFor("value")),
+              s.push(this._stringFor("insensitiveFlag", "insensitive", function(a, o) {
+                return a.length > 0 && !n.quoted && o.before.length === 0 && !(n.spaces.value && n.spaces.value.after)
+                  && (o.before = " "),
+                  Uc(a, o);
+              }))),
+            s.push("]"),
+            s.push(this.rawSpaceAfter),
+            s.join("");
+        },
+        Lx(e, [{
+          key: "quoted",
+          get: function() {
+            var n = this.quoteMark;
+            return n === "'" || n === "\"";
+          },
+          set: function(n) {
+            zx();
+          },
+        }, {
+          key: "quoteMark",
+          get: function() {
+            return this._quoteMark;
+          },
+          set: function(n) {
+            if (!this._constructed) {
+              this._quoteMark = n;
+              return;
+            }
+            this._quoteMark !== n && (this._quoteMark = n, this._syncRawValue());
+          },
+        }, {
+          key: "qualifiedAttribute",
+          get: function() {
+            return this.qualifiedName(this.raws.attribute || this.attribute);
+          },
+        }, {
+          key: "insensitiveFlag",
+          get: function() {
+            return this.insensitive ? "i" : "";
+          },
+        }, {
+          key: "value",
+          get: function() {
+            return this._value;
+          },
+          set: function(n) {
+            if (this._constructed) {
+              var s = ta(n), a = s.deprecatedUsage, o = s.unescaped, u = s.quoteMark;
+              if (a && jx(), o === this._value && u === this._quoteMark) return;
+              this._value = o, this._quoteMark = u, this._syncRawValue();
+            } else this._value = n;
+          },
+        }, {
+          key: "insensitive",
+          get: function() {
+            return this._insensitive;
+          },
+          set: function(n) {
+            n
+            || (this._insensitive = !1,
+              this.raws && (this.raws.insensitiveFlag === "I" || this.raws.insensitiveFlag === "i")
+              && (this.raws.insensitiveFlag = void 0)), this._insensitive = n;
+          },
+        }, {
+          key: "attribute",
+          get: function() {
+            return this._attribute;
+          },
+          set: function(n) {
+            this._handleEscapes("attribute", n), this._attribute = n;
+          },
+        }]),
+        e;
+    }(Fx.default);
+    Nr.default = Xi;
+    Xi.NO_QUOTE = null;
+    Xi.SINGLE_QUOTE = "'";
+    Xi.DOUBLE_QUOTE = "\"";
+    var ra =
+      (Ks = { "'": { quotes: "single", wrap: !0 }, "\"": { quotes: "double", wrap: !0 } },
+        Ks[null] = { isIdentifier: !0 },
+        Ks);
+    function Uc(r, e) {
+      return "" + e.before + r + e.after;
+    }
+  });
+  var sa = v((Lr, Wc) => {
+    l();
+    "use strict";
+    Lr.__esModule = !0;
+    Lr.default = void 0;
+    var Wx = Hx(Ji()), Gx = ae();
+    function Hx(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function Yx(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, na(r, e);
+    }
+    function na(r, e) {
+      return na = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        na(r, e);
+    }
+    var Qx = function(r) {
+      Yx(e, r);
+      function e(t) {
+        var i;
+        return i = r.call(this, t) || this, i.type = Gx.UNIVERSAL, i.value = "*", i;
+      }
+      return e;
+    }(Wx.default);
+    Lr.default = Qx;
+    Wc.exports = Lr.default;
+  });
+  var oa = v((Br, Gc) => {
+    l();
+    "use strict";
+    Br.__esModule = !0;
+    Br.default = void 0;
+    var Jx = Kx(Ve()), Xx = ae();
+    function Kx(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function Zx(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, aa(r, e);
+    }
+    function aa(r, e) {
+      return aa = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        aa(r, e);
+    }
+    var e1 = function(r) {
+      Zx(e, r);
+      function e(t) {
+        var i;
+        return i = r.call(this, t) || this, i.type = Xx.COMBINATOR, i;
+      }
+      return e;
+    }(Jx.default);
+    Br.default = e1;
+    Gc.exports = Br.default;
+  });
+  var ua = v(($r, Hc) => {
+    l();
+    "use strict";
+    $r.__esModule = !0;
+    $r.default = void 0;
+    var t1 = i1(Ve()), r1 = ae();
+    function i1(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function n1(r, e) {
+      r.prototype = Object.create(e.prototype), r.prototype.constructor = r, la(r, e);
+    }
+    function la(r, e) {
+      return la = Object.setPrototypeOf ? Object.setPrototypeOf.bind() : function(i, n) {
+        return i.__proto__ = n, i;
+      },
+        la(r, e);
+    }
+    var s1 = function(r) {
+      n1(e, r);
+      function e(t) {
+        var i;
+        return i = r.call(this, t) || this, i.type = r1.NESTING, i.value = "&", i;
+      }
+      return e;
+    }(t1.default);
+    $r.default = s1;
+    Hc.exports = $r.default;
+  });
+  var Qc = v((Ki, Yc) => {
+    l();
+    "use strict";
+    Ki.__esModule = !0;
+    Ki.default = a1;
+    function a1(r) {
+      return r.sort(function(e, t) {
+        return e - t;
+      });
+    }
+    Yc.exports = Ki.default;
+  });
+  var fa = v(D => {
+    l();
+    "use strict";
+    D.__esModule = !0;
+    D.word =
+      D.tilde =
+      D.tab =
+      D.str =
+      D.space =
+      D.slash =
+      D.singleQuote =
+      D.semicolon =
+      D.plus =
+      D.pipe =
+      D.openSquare =
+      D.openParenthesis =
+      D.newline =
+      D.greaterThan =
+      D.feed =
+      D.equals =
+      D.doubleQuote =
+      D.dollar =
+      D.cr =
+      D.comment =
+      D.comma =
+      D.combinator =
+      D.colon =
+      D.closeSquare =
+      D.closeParenthesis =
+      D.caret =
+      D.bang =
+      D.backslash =
+      D.at =
+      D.asterisk =
+      D.ampersand =
+        void 0;
+    var o1 = 38;
+    D.ampersand = o1;
+    var l1 = 42;
+    D.asterisk = l1;
+    var u1 = 64;
+    D.at = u1;
+    var f1 = 44;
+    D.comma = f1;
+    var c1 = 58;
+    D.colon = c1;
+    var p1 = 59;
+    D.semicolon = p1;
+    var d1 = 40;
+    D.openParenthesis = d1;
+    var h1 = 41;
+    D.closeParenthesis = h1;
+    var m1 = 91;
+    D.openSquare = m1;
+    var g1 = 93;
+    D.closeSquare = g1;
+    var y1 = 36;
+    D.dollar = y1;
+    var b1 = 126;
+    D.tilde = b1;
+    var w1 = 94;
+    D.caret = w1;
+    var v1 = 43;
+    D.plus = v1;
+    var x1 = 61;
+    D.equals = x1;
+    var k1 = 124;
+    D.pipe = k1;
+    var S1 = 62;
+    D.greaterThan = S1;
+    var _1 = 32;
+    D.space = _1;
+    var Jc = 39;
+    D.singleQuote = Jc;
+    var C1 = 34;
+    D.doubleQuote = C1;
+    var A1 = 47;
+    D.slash = A1;
+    var O1 = 33;
+    D.bang = O1;
+    var E1 = 92;
+    D.backslash = E1;
+    var T1 = 13;
+    D.cr = T1;
+    var P1 = 12;
+    D.feed = P1;
+    var D1 = 10;
+    D.newline = D1;
+    var I1 = 9;
+    D.tab = I1;
+    var q1 = Jc;
+    D.str = q1;
+    var R1 = -1;
+    D.comment = R1;
+    var M1 = -2;
+    D.word = M1;
+    var F1 = -3;
+    D.combinator = F1;
+  });
+  var Zc = v(jr => {
+    l();
+    "use strict";
+    jr.__esModule = !0;
+    jr.FIELDS = void 0;
+    jr.default = V1;
+    var O = N1(fa()), Et, z;
+    function Xc(r) {
+      if (typeof WeakMap != "function") return null;
+      var e = new WeakMap(), t = new WeakMap();
+      return (Xc = function(n) {
+        return n ? t : e;
+      })(r);
+    }
+    function N1(r, e) {
+      if (!e && r && r.__esModule) return r;
+      if (r === null || typeof r != "object" && typeof r != "function") return { default: r };
+      var t = Xc(e);
+      if (t && t.has(r)) return t.get(r);
+      var i = {}, n = Object.defineProperty && Object.getOwnPropertyDescriptor;
+      for (var s in r) {
+        if (s !== "default" && Object.prototype.hasOwnProperty.call(r, s)) {
+          var a = n ? Object.getOwnPropertyDescriptor(r, s) : null;
+          a && (a.get || a.set) ? Object.defineProperty(i, s, a) : i[s] = r[s];
+        }
+      }
+      return i.default = r, t && t.set(r, i), i;
+    }
+    var L1 = (Et = {}, Et[O.tab] = !0, Et[O.newline] = !0, Et[O.cr] = !0, Et[O.feed] = !0, Et),
+      B1 =
+        (z = {},
+          z[O.space] = !0,
+          z[O.tab] = !0,
+          z[O.newline] = !0,
+          z[O.cr] = !0,
+          z[O.feed] = !0,
+          z[O.ampersand] = !0,
+          z[O.asterisk] = !0,
+          z[O.bang] = !0,
+          z[O.comma] = !0,
+          z[O.colon] = !0,
+          z[O.semicolon] = !0,
+          z[O.openParenthesis] = !0,
+          z[O.closeParenthesis] = !0,
+          z[O.openSquare] = !0,
+          z[O.closeSquare] = !0,
+          z[O.singleQuote] = !0,
+          z[O.doubleQuote] = !0,
+          z[O.plus] = !0,
+          z[O.pipe] = !0,
+          z[O.tilde] = !0,
+          z[O.greaterThan] = !0,
+          z[O.equals] = !0,
+          z[O.dollar] = !0,
+          z[O.caret] = !0,
+          z[O.slash] = !0,
+          z),
+      ca = {},
+      Kc = "0123456789abcdefABCDEF";
+    for (Zi = 0; Zi < Kc.length; Zi++) ca[Kc.charCodeAt(Zi)] = !0;
+    var Zi;
+    function $1(r, e) {
+      var t = e, i;
+      do {
+        if (i = r.charCodeAt(t), B1[i]) return t - 1;
+        i === O.backslash ? t = j1(r, t) + 1 : t++;
+      } while (t < r.length);
+      return t - 1;
+    }
+    function j1(r, e) {
+      var t = e, i = r.charCodeAt(t + 1);
+      if (!L1[i]) {
+        if (ca[i]) {
+          var n = 0;
+          do t++, n++, i = r.charCodeAt(t + 1); while (ca[i] && n < 6);
+          n < 6 && i === O.space && t++;
+        } else t++;
+      }
+      return t;
+    }
+    var z1 = { TYPE: 0, START_LINE: 1, START_COL: 2, END_LINE: 3, END_COL: 4, START_POS: 5, END_POS: 6 };
+    jr.FIELDS = z1;
+    function V1(r) {
+      var e = [],
+        t = r.css.valueOf(),
+        i = t,
+        n = i.length,
+        s = -1,
+        a = 1,
+        o = 0,
+        u = 0,
+        c,
+        f,
+        p,
+        d,
+        h,
+        y,
+        x,
+        b,
+        w,
+        k,
+        S,
+        _,
+        P;
+      function M(F, I) {
+        if (r.safe) t += I, w = t.length - 1;
+        else throw r.error("Unclosed " + F, a, o - s, o);
+      }
+      for (; o < n;) {
+        switch (c = t.charCodeAt(o), c === O.newline && (s = o, a += 1), c) {
+          case O.space:
+          case O.tab:
+          case O.newline:
+          case O.cr:
+          case O.feed:
+            w = o;
+            do w += 1, c = t.charCodeAt(w), c === O.newline && (s = w, a += 1); while (
+              c === O.space || c === O.newline || c === O.tab || c === O.cr || c === O.feed
+            );
+            P = O.space, d = a, p = w - s - 1, u = w;
+            break;
+          case O.plus:
+          case O.greaterThan:
+          case O.tilde:
+          case O.pipe:
+            w = o;
+            do w += 1, c = t.charCodeAt(w); while (
+              c === O.plus || c === O.greaterThan || c === O.tilde || c === O.pipe
+            );
+            P = O.combinator, d = a, p = o - s, u = w;
+            break;
+          case O.asterisk:
+          case O.ampersand:
+          case O.bang:
+          case O.comma:
+          case O.equals:
+          case O.dollar:
+          case O.caret:
+          case O.openSquare:
+          case O.closeSquare:
+          case O.colon:
+          case O.semicolon:
+          case O.openParenthesis:
+          case O.closeParenthesis:
+            w = o, P = c, d = a, p = o - s, u = w + 1;
+            break;
+          case O.singleQuote:
+          case O.doubleQuote:
+            _ = c === O.singleQuote ? "'" : "\"", w = o;
+            do for (
+              h = !1, w = t.indexOf(_, w + 1), w === -1 && M("quote", _), y = w;
+              t.charCodeAt(y - 1) === O.backslash;
+            ) y -= 1, h = !h; while (h);
+            P = O.str, d = a, p = o - s, u = w + 1;
+            break;
+          default:
+            c === O.slash && t.charCodeAt(o + 1) === O.asterisk
+              ? (w = t.indexOf("*/", o + 2) + 1,
+                w === 0 && M("comment", "*/"),
+                f = t.slice(o, w + 1),
+                b = f.split(`
+`),
+                x = b.length - 1,
+                x > 0 ? (k = a + x, S = w - b[x].length) : (k = a, S = s),
+                P = O.comment,
+                a = k,
+                d = k,
+                p = w - S)
+              : c === O.slash
+              ? (w = o, P = c, d = a, p = o - s, u = w + 1)
+              : (w = $1(t, o), P = O.word, d = a, p = w - s), u = w + 1;
+            break;
+        }
+        e.push([P, a, o - s, d, p, o, u]), S && (s = S, S = null), o = u;
+      }
+      return e;
+    }
+  });
+  var op = v((zr, ap) => {
+    l();
+    "use strict";
+    zr.__esModule = !0;
+    zr.default = void 0;
+    var U1 = be(Ms()),
+      pa = be(Ns()),
+      W1 = be($s()),
+      ep = be(zs()),
+      G1 = be(Us()),
+      H1 = be(Hs()),
+      da = be(Qs()),
+      Y1 = be(Xs()),
+      tp = en(ia()),
+      Q1 = be(sa()),
+      ha = be(oa()),
+      J1 = be(ua()),
+      X1 = be(Qc()),
+      A = en(Zc()),
+      E = en(fa()),
+      K1 = en(ae()),
+      H = Sr(),
+      mt,
+      ma;
+    function rp(r) {
+      if (typeof WeakMap != "function") return null;
+      var e = new WeakMap(), t = new WeakMap();
+      return (rp = function(n) {
+        return n ? t : e;
+      })(r);
+    }
+    function en(r, e) {
+      if (!e && r && r.__esModule) return r;
+      if (r === null || typeof r != "object" && typeof r != "function") return { default: r };
+      var t = rp(e);
+      if (t && t.has(r)) return t.get(r);
+      var i = {}, n = Object.defineProperty && Object.getOwnPropertyDescriptor;
+      for (var s in r) {
+        if (s !== "default" && Object.prototype.hasOwnProperty.call(r, s)) {
+          var a = n ? Object.getOwnPropertyDescriptor(r, s) : null;
+          a && (a.get || a.set) ? Object.defineProperty(i, s, a) : i[s] = r[s];
+        }
+      }
+      return i.default = r, t && t.set(r, i), i;
+    }
+    function be(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    function ip(r, e) {
+      for (var t = 0; t < e.length; t++) {
+        var i = e[t];
+        i.enumerable = i.enumerable || !1,
+          i.configurable = !0,
+          "value" in i && (i.writable = !0),
+          Object.defineProperty(r, i.key, i);
+      }
+    }
+    function Z1(r, e, t) {
+      return e && ip(r.prototype, e), t && ip(r, t), Object.defineProperty(r, "prototype", { writable: !1 }), r;
+    }
+    var ga = (mt = {}, mt[E.space] = !0, mt[E.cr] = !0, mt[E.feed] = !0, mt[E.newline] = !0, mt[E.tab] = !0, mt),
+      ek = Object.assign({}, ga, (ma = {}, ma[E.comment] = !0, ma));
+    function np(r) {
+      return { line: r[A.FIELDS.START_LINE], column: r[A.FIELDS.START_COL] };
+    }
+    function sp(r) {
+      return { line: r[A.FIELDS.END_LINE], column: r[A.FIELDS.END_COL] };
+    }
+    function gt(r, e, t, i) {
+      return { start: { line: r, column: e }, end: { line: t, column: i } };
+    }
+    function Tt(r) {
+      return gt(r[A.FIELDS.START_LINE], r[A.FIELDS.START_COL], r[A.FIELDS.END_LINE], r[A.FIELDS.END_COL]);
+    }
+    function ya(r, e) {
+      if (!!r) return gt(r[A.FIELDS.START_LINE], r[A.FIELDS.START_COL], e[A.FIELDS.END_LINE], e[A.FIELDS.END_COL]);
+    }
+    function Pt(r, e) {
+      var t = r[e];
+      if (typeof t == "string") {
+        return t.indexOf("\\") !== -1
+          && ((0, H.ensureObject)(r, "raws"), r[e] = (0, H.unesc)(t), r.raws[e] === void 0 && (r.raws[e] = t)),
+          r;
+      }
+    }
+    function ba(r, e) {
+      for (var t = -1, i = []; (t = r.indexOf(e, t + 1)) !== -1;) i.push(t);
+      return i;
+    }
+    function tk() {
+      var r = Array.prototype.concat.apply([], arguments);
+      return r.filter(function(e, t) {
+        return t === r.indexOf(e);
+      });
+    }
+    var rk = function() {
+      function r(t, i) {
+        i === void 0 && (i = {}),
+          this.rule = t,
+          this.options = Object.assign({ lossy: !1, safe: !1 }, i),
+          this.position = 0,
+          this.css = typeof this.rule == "string" ? this.rule : this.rule.selector,
+          this.tokens = (0, A.default)({ css: this.css, error: this._errorGenerator(), safe: this.options.safe });
+        var n = ya(this.tokens[0], this.tokens[this.tokens.length - 1]);
+        this.root = new U1.default({ source: n }), this.root.errorGenerator = this._errorGenerator();
+        var s = new pa.default({ source: { start: { line: 1, column: 1 } } });
+        this.root.append(s), this.current = s, this.loop();
+      }
+      var e = r.prototype;
+      return e._errorGenerator = function() {
+        var i = this;
+        return function(n, s) {
+          return typeof i.rule == "string" ? new Error(n) : i.rule.error(n, s);
+        };
+      },
+        e.attribute = function() {
+          var i = [], n = this.currToken;
+          for (
+            this.position++;
+            this.position < this.tokens.length && this.currToken[A.FIELDS.TYPE] !== E.closeSquare;
+          ) i.push(this.currToken), this.position++;
+          if (this.currToken[A.FIELDS.TYPE] !== E.closeSquare) {
+            return this.expected("closing square bracket", this.currToken[A.FIELDS.START_POS]);
+          }
+          var s = i.length,
+            a = { source: gt(n[1], n[2], this.currToken[3], this.currToken[4]), sourceIndex: n[A.FIELDS.START_POS] };
+          if (s === 1 && !~[E.word].indexOf(i[0][A.FIELDS.TYPE])) {
+            return this.expected("attribute", i[0][A.FIELDS.START_POS]);
+          }
+          for (var o = 0, u = "", c = "", f = null, p = !1; o < s;) {
+            var d = i[o], h = this.content(d), y = i[o + 1];
+            switch (d[A.FIELDS.TYPE]) {
+              case E.space:
+                if (p = !0, this.options.lossy) break;
+                if (f) {
+                  (0, H.ensureObject)(a, "spaces", f);
+                  var x = a.spaces[f].after || "";
+                  a.spaces[f].after = x + h;
+                  var b = (0, H.getProp)(a, "raws", "spaces", f, "after") || null;
+                  b && (a.raws.spaces[f].after = b + h);
+                } else u = u + h, c = c + h;
+                break;
+              case E.asterisk:
+                if (y[A.FIELDS.TYPE] === E.equals) a.operator = h, f = "operator";
+                else if ((!a.namespace || f === "namespace" && !p) && y) {
+                  u && ((0, H.ensureObject)(a, "spaces", "attribute"), a.spaces.attribute.before = u, u = ""),
+                    c
+                    && ((0, H.ensureObject)(a, "raws", "spaces", "attribute"),
+                      a.raws.spaces.attribute.before = u,
+                      c = ""),
+                    a.namespace = (a.namespace || "") + h;
+                  var w = (0, H.getProp)(a, "raws", "namespace") || null;
+                  w && (a.raws.namespace += h), f = "namespace";
+                }
+                p = !1;
+                break;
+              case E.dollar:
+                if (f === "value") {
+                  var k = (0, H.getProp)(a, "raws", "value");
+                  a.value += "$", k && (a.raws.value = k + "$");
+                  break;
+                }
+              case E.caret:
+                y[A.FIELDS.TYPE] === E.equals && (a.operator = h, f = "operator"), p = !1;
+                break;
+              case E.combinator:
+                if (h === "~" && y[A.FIELDS.TYPE] === E.equals && (a.operator = h, f = "operator"), h !== "|") {
+                  p = !1;
+                  break;
+                }
+                y[A.FIELDS.TYPE] === E.equals
+                  ? (a.operator = h, f = "operator")
+                  : !a.namespace && !a.attribute && (a.namespace = !0), p = !1;
+                break;
+              case E.word:
+                if (
+                  y && this.content(y) === "|" && i[o + 2] && i[o + 2][A.FIELDS.TYPE] !== E.equals && !a.operator
+                  && !a.namespace
+                ) a.namespace = h, f = "namespace";
+                else if (!a.attribute || f === "attribute" && !p) {
+                  u && ((0, H.ensureObject)(a, "spaces", "attribute"), a.spaces.attribute.before = u, u = ""),
+                    c
+                    && ((0, H.ensureObject)(a, "raws", "spaces", "attribute"),
+                      a.raws.spaces.attribute.before = c,
+                      c = ""),
+                    a.attribute = (a.attribute || "") + h;
+                  var S = (0, H.getProp)(a, "raws", "attribute") || null;
+                  S && (a.raws.attribute += h), f = "attribute";
+                } else if (!a.value && a.value !== "" || f === "value" && !(p || a.quoteMark)) {
+                  var _ = (0, H.unesc)(h), P = (0, H.getProp)(a, "raws", "value") || "", M = a.value || "";
+                  a.value = M + _,
+                    a.quoteMark = null,
+                    (_ !== h || P) && ((0, H.ensureObject)(a, "raws"), a.raws.value = (P || M) + h),
+                    f = "value";
+                } else {
+                  var F = h === "i" || h === "I";
+                  (a.value || a.value === "") && (a.quoteMark || p)
+                    ? (a.insensitive = F,
+                      (!F || h === "I") && ((0, H.ensureObject)(a, "raws"), a.raws.insensitiveFlag = h),
+                      f = "insensitive",
+                      u && ((0, H.ensureObject)(a, "spaces", "insensitive"), a.spaces.insensitive.before = u, u = ""),
+                      c
+                      && ((0, H.ensureObject)(a, "raws", "spaces", "insensitive"),
+                        a.raws.spaces.insensitive.before = c,
+                        c = ""))
+                    : (a.value || a.value === "") && (f = "value", a.value += h, a.raws.value && (a.raws.value += h));
+                }
+                p = !1;
+                break;
+              case E.str:
+                if (!a.attribute || !a.operator) {
+                  return this.error("Expected an attribute followed by an operator preceding the string.", {
+                    index: d[A.FIELDS.START_POS],
+                  });
+                }
+                var I = (0, tp.unescapeValue)(h), X = I.unescaped, ge = I.quoteMark;
+                a.value = X, a.quoteMark = ge, f = "value", (0, H.ensureObject)(a, "raws"), a.raws.value = h, p = !1;
+                break;
+              case E.equals:
+                if (!a.attribute) return this.expected("attribute", d[A.FIELDS.START_POS], h);
+                if (a.value) {
+                  return this.error("Unexpected \"=\" found; an operator was already defined.", {
+                    index: d[A.FIELDS.START_POS],
+                  });
+                }
+                a.operator = a.operator ? a.operator + h : h, f = "operator", p = !1;
+                break;
+              case E.comment:
+                if (f) {
+                  if (p || y && y[A.FIELDS.TYPE] === E.space || f === "insensitive") {
+                    var Q = (0, H.getProp)(a, "spaces", f, "after") || "",
+                      Z = (0, H.getProp)(a, "raws", "spaces", f, "after") || Q;
+                    (0, H.ensureObject)(a, "raws", "spaces", f), a.raws.spaces[f].after = Z + h;
+                  } else {
+                    var ee = a[f] || "", wt = (0, H.getProp)(a, "raws", f) || ee;
+                    (0, H.ensureObject)(a, "raws"), a.raws[f] = wt + h;
+                  }
+                } else c = c + h;
+                break;
+              default:
+                return this.error("Unexpected \"" + h + "\" found.", { index: d[A.FIELDS.START_POS] });
+            }
+            o++;
+          }
+          Pt(a, "attribute"), Pt(a, "namespace"), this.newNode(new tp.default(a)), this.position++;
+        },
+        e.parseWhitespaceEquivalentTokens = function(i) {
+          i < 0 && (i = this.tokens.length);
+          var n = this.position, s = [], a = "", o = void 0;
+          do if (ga[this.currToken[A.FIELDS.TYPE]]) this.options.lossy || (a += this.content());
+          else if (this.currToken[A.FIELDS.TYPE] === E.comment) {
+            var u = {};
+            a && (u.before = a, a = ""),
+              o = new ep.default({
+                value: this.content(),
+                source: Tt(this.currToken),
+                sourceIndex: this.currToken[A.FIELDS.START_POS],
+                spaces: u,
+              }),
+              s.push(o);
+          } while (++this.position < i);
+          if (a) {
+            if (o) o.spaces.after = a;
+            else if (!this.options.lossy) {
+              var c = this.tokens[n], f = this.tokens[this.position - 1];
+              s.push(
+                new da.default({
+                  value: "",
+                  source: gt(c[A.FIELDS.START_LINE], c[A.FIELDS.START_COL], f[A.FIELDS.END_LINE], f[A.FIELDS.END_COL]),
+                  sourceIndex: c[A.FIELDS.START_POS],
+                  spaces: { before: a, after: "" },
+                }),
+              );
+            }
+          }
+          return s;
+        },
+        e.convertWhitespaceNodesToSpace = function(i, n) {
+          var s = this;
+          n === void 0 && (n = !1);
+          var a = "", o = "";
+          i.forEach(function(c) {
+            var f = s.lossySpace(c.spaces.before, n), p = s.lossySpace(c.rawSpaceBefore, n);
+            a += f + s.lossySpace(c.spaces.after, n && f.length === 0),
+              o += f + c.value + s.lossySpace(c.rawSpaceAfter, n && p.length === 0);
+          }), o === a && (o = void 0);
+          var u = { space: a, rawSpace: o };
+          return u;
+        },
+        e.isNamedCombinator = function(i) {
+          return i === void 0 && (i = this.position),
+            this.tokens[i + 0] && this.tokens[i + 0][A.FIELDS.TYPE] === E.slash && this.tokens[i + 1]
+            && this.tokens[i + 1][A.FIELDS.TYPE] === E.word && this.tokens[i + 2]
+            && this.tokens[i + 2][A.FIELDS.TYPE] === E.slash;
+        },
+        e.namedCombinator = function() {
+          if (this.isNamedCombinator()) {
+            var i = this.content(this.tokens[this.position + 1]), n = (0, H.unesc)(i).toLowerCase(), s = {};
+            n !== i && (s.value = "/" + i + "/");
+            var a = new ha.default({
+              value: "/" + n + "/",
+              source: gt(
+                this.currToken[A.FIELDS.START_LINE],
+                this.currToken[A.FIELDS.START_COL],
+                this.tokens[this.position + 2][A.FIELDS.END_LINE],
+                this.tokens[this.position + 2][A.FIELDS.END_COL],
+              ),
+              sourceIndex: this.currToken[A.FIELDS.START_POS],
+              raws: s,
+            });
+            return this.position = this.position + 3, a;
+          } else this.unexpected();
+        },
+        e.combinator = function() {
+          var i = this;
+          if (this.content() === "|") return this.namespace();
+          var n = this.locateNextMeaningfulToken(this.position);
+          if (n < 0 || this.tokens[n][A.FIELDS.TYPE] === E.comma) {
+            var s = this.parseWhitespaceEquivalentTokens(n);
+            if (s.length > 0) {
+              var a = this.current.last;
+              if (a) {
+                var o = this.convertWhitespaceNodesToSpace(s), u = o.space, c = o.rawSpace;
+                c !== void 0 && (a.rawSpaceAfter += c), a.spaces.after += u;
+              } else {s.forEach(function(P) {
+                  return i.newNode(P);
+                });}
+            }
+            return;
+          }
+          var f = this.currToken, p = void 0;
+          n > this.position && (p = this.parseWhitespaceEquivalentTokens(n));
+          var d;
+          if (
+            this.isNamedCombinator()
+              ? d = this.namedCombinator()
+              : this.currToken[A.FIELDS.TYPE] === E.combinator
+              ? (d = new ha.default({
+                value: this.content(),
+                source: Tt(this.currToken),
+                sourceIndex: this.currToken[A.FIELDS.START_POS],
+              }),
+                this.position++)
+              : ga[this.currToken[A.FIELDS.TYPE]] || p || this.unexpected(), d
+          ) {
+            if (p) {
+              var h = this.convertWhitespaceNodesToSpace(p), y = h.space, x = h.rawSpace;
+              d.spaces.before = y, d.rawSpaceBefore = x;
+            }
+          } else {
+            var b = this.convertWhitespaceNodesToSpace(p, !0), w = b.space, k = b.rawSpace;
+            k || (k = w);
+            var S = {}, _ = { spaces: {} };
+            w.endsWith(" ") && k.endsWith(" ")
+              ? (S.before = w.slice(0, w.length - 1), _.spaces.before = k.slice(0, k.length - 1))
+              : w.startsWith(" ") && k.startsWith(" ")
+              ? (S.after = w.slice(1), _.spaces.after = k.slice(1))
+              : _.value = k,
+              d = new ha.default({
+                value: " ",
+                source: ya(f, this.tokens[this.position - 1]),
+                sourceIndex: f[A.FIELDS.START_POS],
+                spaces: S,
+                raws: _,
+              });
+          }
+          return this.currToken && this.currToken[A.FIELDS.TYPE] === E.space
+            && (d.spaces.after = this.optionalSpace(this.content()), this.position++),
+            this.newNode(d);
+        },
+        e.comma = function() {
+          if (this.position === this.tokens.length - 1) {
+            this.root.trailingComma = !0, this.position++;
+            return;
+          }
+          this.current._inferEndPosition();
+          var i = new pa.default({ source: { start: np(this.tokens[this.position + 1]) } });
+          this.current.parent.append(i), this.current = i, this.position++;
+        },
+        e.comment = function() {
+          var i = this.currToken;
+          this.newNode(new ep.default({ value: this.content(), source: Tt(i), sourceIndex: i[A.FIELDS.START_POS] })),
+            this.position++;
+        },
+        e.error = function(i, n) {
+          throw this.root.error(i, n);
+        },
+        e.missingBackslash = function() {
+          return this.error("Expected a backslash preceding the semicolon.", {
+            index: this.currToken[A.FIELDS.START_POS],
+          });
+        },
+        e.missingParenthesis = function() {
+          return this.expected("opening parenthesis", this.currToken[A.FIELDS.START_POS]);
+        },
+        e.missingSquareBracket = function() {
+          return this.expected("opening square bracket", this.currToken[A.FIELDS.START_POS]);
+        },
+        e.unexpected = function() {
+          return this.error(
+            "Unexpected '" + this.content() + "'. Escaping special characters with \\ may help.",
+            this.currToken[A.FIELDS.START_POS],
+          );
+        },
+        e.unexpectedPipe = function() {
+          return this.error("Unexpected '|'.", this.currToken[A.FIELDS.START_POS]);
+        },
+        e.namespace = function() {
+          var i = this.prevToken && this.content(this.prevToken) || !0;
+          if (this.nextToken[A.FIELDS.TYPE] === E.word) return this.position++, this.word(i);
+          if (this.nextToken[A.FIELDS.TYPE] === E.asterisk) return this.position++, this.universal(i);
+          this.unexpectedPipe();
+        },
+        e.nesting = function() {
+          if (this.nextToken) {
+            var i = this.content(this.nextToken);
+            if (i === "|") {
+              this.position++;
+              return;
+            }
+          }
+          var n = this.currToken;
+          this.newNode(new J1.default({ value: this.content(), source: Tt(n), sourceIndex: n[A.FIELDS.START_POS] })),
+            this.position++;
+        },
+        e.parentheses = function() {
+          var i = this.current.last, n = 1;
+          if (this.position++, i && i.type === K1.PSEUDO) {
+            var s = new pa.default({ source: { start: np(this.tokens[this.position - 1]) } }), a = this.current;
+            for (i.append(s), this.current = s; this.position < this.tokens.length && n;) {
+              this.currToken[A.FIELDS.TYPE] === E.openParenthesis && n++,
+                this.currToken[A.FIELDS.TYPE] === E.closeParenthesis && n--,
+                n
+                  ? this.parse()
+                  : (this.current.source.end = sp(this.currToken),
+                    this.current.parent.source.end = sp(this.currToken),
+                    this.position++);
+            }
+            this.current = a;
+          } else {
+            for (var o = this.currToken, u = "(", c; this.position < this.tokens.length && n;) {
+              this.currToken[A.FIELDS.TYPE] === E.openParenthesis && n++,
+                this.currToken[A.FIELDS.TYPE] === E.closeParenthesis && n--,
+                c = this.currToken,
+                u += this.parseParenthesisToken(this.currToken),
+                this.position++;
+            }
+            i
+              ? i.appendToPropertyAndEscape("value", u, u)
+              : this.newNode(
+                new da.default({
+                  value: u,
+                  source: gt(o[A.FIELDS.START_LINE], o[A.FIELDS.START_COL], c[A.FIELDS.END_LINE], c[A.FIELDS.END_COL]),
+                  sourceIndex: o[A.FIELDS.START_POS],
+                }),
+              );
+          }
+          if (n) return this.expected("closing parenthesis", this.currToken[A.FIELDS.START_POS]);
+        },
+        e.pseudo = function() {
+          for (var i = this, n = "", s = this.currToken; this.currToken && this.currToken[A.FIELDS.TYPE] === E.colon;) {
+            n += this.content(), this.position++;
+          }
+          if (!this.currToken) return this.expected(["pseudo-class", "pseudo-element"], this.position - 1);
+          if (this.currToken[A.FIELDS.TYPE] === E.word) {
+            this.splitWord(!1, function(a, o) {
+              n += a,
+                i.newNode(new Y1.default({ value: n, source: ya(s, i.currToken), sourceIndex: s[A.FIELDS.START_POS] })),
+                o > 1 && i.nextToken && i.nextToken[A.FIELDS.TYPE] === E.openParenthesis
+                && i.error("Misplaced parenthesis.", { index: i.nextToken[A.FIELDS.START_POS] });
+            });
+          } else return this.expected(["pseudo-class", "pseudo-element"], this.currToken[A.FIELDS.START_POS]);
+        },
+        e.space = function() {
+          var i = this.content();
+          this.position === 0 || this.prevToken[A.FIELDS.TYPE] === E.comma
+            || this.prevToken[A.FIELDS.TYPE] === E.openParenthesis || this.current.nodes.every(function(n) {
+              return n.type === "comment";
+            })
+            ? (this.spaces = this.optionalSpace(i), this.position++)
+            : this.position === this.tokens.length - 1 || this.nextToken[A.FIELDS.TYPE] === E.comma
+                || this.nextToken[A.FIELDS.TYPE] === E.closeParenthesis
+            ? (this.current.last.spaces.after = this.optionalSpace(i), this.position++)
+            : this.combinator();
+        },
+        e.string = function() {
+          var i = this.currToken;
+          this.newNode(new da.default({ value: this.content(), source: Tt(i), sourceIndex: i[A.FIELDS.START_POS] })),
+            this.position++;
+        },
+        e.universal = function(i) {
+          var n = this.nextToken;
+          if (n && this.content(n) === "|") return this.position++, this.namespace();
+          var s = this.currToken;
+          this.newNode(new Q1.default({ value: this.content(), source: Tt(s), sourceIndex: s[A.FIELDS.START_POS] }), i),
+            this.position++;
+        },
+        e.splitWord = function(i, n) {
+          for (
+            var s = this, a = this.nextToken, o = this.content();
+            a && ~[E.dollar, E.caret, E.equals, E.word].indexOf(a[A.FIELDS.TYPE]);
+          ) {
+            this.position++;
+            var u = this.content();
+            if (o += u, u.lastIndexOf("\\") === u.length - 1) {
+              var c = this.nextToken;
+              c && c[A.FIELDS.TYPE] === E.space && (o += this.requiredSpace(this.content(c)), this.position++);
+            }
+            a = this.nextToken;
+          }
+          var f = ba(o, ".").filter(function(y) {
+              var x = o[y - 1] === "\\", b = /^\d+\.\d+%$/.test(o);
+              return !x && !b;
+            }),
+            p = ba(o, "#").filter(function(y) {
+              return o[y - 1] !== "\\";
+            }),
+            d = ba(o, "#{");
+          d.length && (p = p.filter(function(y) {
+            return !~d.indexOf(y);
+          }));
+          var h = (0, X1.default)(tk([0].concat(f, p)));
+          h.forEach(function(y, x) {
+            var b = h[x + 1] || o.length, w = o.slice(y, b);
+            if (x === 0 && n) return n.call(s, w, h.length);
+            var k, S = s.currToken, _ = S[A.FIELDS.START_POS] + h[x], P = gt(S[1], S[2] + y, S[3], S[2] + (b - 1));
+            if (~f.indexOf(y)) {
+              var M = { value: w.slice(1), source: P, sourceIndex: _ };
+              k = new W1.default(Pt(M, "value"));
+            } else if (~p.indexOf(y)) {
+              var F = { value: w.slice(1), source: P, sourceIndex: _ };
+              k = new G1.default(Pt(F, "value"));
+            } else {
+              var I = { value: w, source: P, sourceIndex: _ };
+              Pt(I, "value"), k = new H1.default(I);
+            }
+            s.newNode(k, i), i = null;
+          }), this.position++;
+        },
+        e.word = function(i) {
+          var n = this.nextToken;
+          return n && this.content(n) === "|" ? (this.position++, this.namespace()) : this.splitWord(i);
+        },
+        e.loop = function() {
+          for (; this.position < this.tokens.length;) this.parse(!0);
+          return this.current._inferEndPosition(), this.root;
+        },
+        e.parse = function(i) {
+          switch (this.currToken[A.FIELDS.TYPE]) {
+            case E.space:
+              this.space();
+              break;
+            case E.comment:
+              this.comment();
+              break;
+            case E.openParenthesis:
+              this.parentheses();
+              break;
+            case E.closeParenthesis:
+              i && this.missingParenthesis();
+              break;
+            case E.openSquare:
+              this.attribute();
+              break;
+            case E.dollar:
+            case E.caret:
+            case E.equals:
+            case E.word:
+              this.word();
+              break;
+            case E.colon:
+              this.pseudo();
+              break;
+            case E.comma:
+              this.comma();
+              break;
+            case E.asterisk:
+              this.universal();
+              break;
+            case E.ampersand:
+              this.nesting();
+              break;
+            case E.slash:
+            case E.combinator:
+              this.combinator();
+              break;
+            case E.str:
+              this.string();
+              break;
+            case E.closeSquare:
+              this.missingSquareBracket();
+            case E.semicolon:
+              this.missingBackslash();
+            default:
+              this.unexpected();
+          }
+        },
+        e.expected = function(i, n, s) {
+          if (Array.isArray(i)) {
+            var a = i.pop();
+            i = i.join(", ") + " or " + a;
+          }
+          var o = /^[aeiou]/.test(i[0]) ? "an" : "a";
+          return s
+            ? this.error("Expected " + o + " " + i + ", found \"" + s + "\" instead.", { index: n })
+            : this.error("Expected " + o + " " + i + ".", { index: n });
+        },
+        e.requiredSpace = function(i) {
+          return this.options.lossy ? " " : i;
+        },
+        e.optionalSpace = function(i) {
+          return this.options.lossy ? "" : i;
+        },
+        e.lossySpace = function(i, n) {
+          return this.options.lossy ? n ? " " : "" : i;
+        },
+        e.parseParenthesisToken = function(i) {
+          var n = this.content(i);
+          return i[A.FIELDS.TYPE] === E.space ? this.requiredSpace(n) : n;
+        },
+        e.newNode = function(i, n) {
+          return n
+            && (/^ +$/.test(n) && (this.options.lossy || (this.spaces = (this.spaces || "") + n), n = !0),
+              i.namespace = n,
+              Pt(i, "namespace")),
+            this.spaces && (i.spaces.before = this.spaces, this.spaces = ""),
+            this.current.append(i);
+        },
+        e.content = function(i) {
+          return i === void 0 && (i = this.currToken), this.css.slice(i[A.FIELDS.START_POS], i[A.FIELDS.END_POS]);
+        },
+        e.locateNextMeaningfulToken = function(i) {
+          i === void 0 && (i = this.position + 1);
+          for (var n = i; n < this.tokens.length;) {
+            if (ek[this.tokens[n][A.FIELDS.TYPE]]) {
+              n++;
+              continue;
+            } else return n;
+          }
+          return -1;
+        },
+        Z1(r, [{
+          key: "currToken",
+          get: function() {
+            return this.tokens[this.position];
+          },
+        }, {
+          key: "nextToken",
+          get: function() {
+            return this.tokens[this.position + 1];
+          },
+        }, {
+          key: "prevToken",
+          get: function() {
+            return this.tokens[this.position - 1];
+          },
+        }]),
+        r;
+    }();
+    zr.default = rk;
+    ap.exports = zr.default;
+  });
+  var up = v((Vr, lp) => {
+    l();
+    "use strict";
+    Vr.__esModule = !0;
+    Vr.default = void 0;
+    var ik = nk(op());
+    function nk(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    var sk = function() {
+      function r(t, i) {
+        this.func = t || function() {}, this.funcRes = null, this.options = i;
+      }
+      var e = r.prototype;
+      return e._shouldUpdateSelector = function(i, n) {
+        n === void 0 && (n = {});
+        var s = Object.assign({}, this.options, n);
+        return s.updateSelector === !1 ? !1 : typeof i != "string";
+      },
+        e._isLossy = function(i) {
+          i === void 0 && (i = {});
+          var n = Object.assign({}, this.options, i);
+          return n.lossless === !1;
+        },
+        e._root = function(i, n) {
+          n === void 0 && (n = {});
+          var s = new ik.default(i, this._parseOptions(n));
+          return s.root;
+        },
+        e._parseOptions = function(i) {
+          return { lossy: this._isLossy(i) };
+        },
+        e._run = function(i, n) {
+          var s = this;
+          return n === void 0 && (n = {}),
+            new Promise(function(a, o) {
+              try {
+                var u = s._root(i, n);
+                Promise.resolve(s.func(u)).then(function(c) {
+                  var f = void 0;
+                  return s._shouldUpdateSelector(i, n) && (f = u.toString(), i.selector = f),
+                    { transform: c, root: u, string: f };
+                }).then(a, o);
+              } catch (c) {
+                o(c);
+                return;
+              }
+            });
+        },
+        e._runSync = function(i, n) {
+          n === void 0 && (n = {});
+          var s = this._root(i, n), a = this.func(s);
+          if (a && typeof a.then == "function") {
+            throw new Error("Selector processor returned a promise to a synchronous call.");
+          }
+          var o = void 0;
+          return n.updateSelector && typeof i != "string" && (o = s.toString(), i.selector = o),
+            { transform: a, root: s, string: o };
+        },
+        e.ast = function(i, n) {
+          return this._run(i, n).then(function(s) {
+            return s.root;
+          });
+        },
+        e.astSync = function(i, n) {
+          return this._runSync(i, n).root;
+        },
+        e.transform = function(i, n) {
+          return this._run(i, n).then(function(s) {
+            return s.transform;
+          });
+        },
+        e.transformSync = function(i, n) {
+          return this._runSync(i, n).transform;
+        },
+        e.process = function(i, n) {
+          return this._run(i, n).then(function(s) {
+            return s.string || s.root.toString();
+          });
+        },
+        e.processSync = function(i, n) {
+          var s = this._runSync(i, n);
+          return s.string || s.root.toString();
+        },
+        r;
+    }();
+    Vr.default = sk;
+    lp.exports = Vr.default;
+  });
+  var fp = v(G => {
+    l();
+    "use strict";
+    G.__esModule = !0;
+    G.universal =
+      G.tag =
+      G.string =
+      G.selector =
+      G.root =
+      G.pseudo =
+      G.nesting =
+      G.id =
+      G.comment =
+      G.combinator =
+      G.className =
+      G.attribute =
+        void 0;
+    var ak = we(ia()),
+      ok = we($s()),
+      lk = we(oa()),
+      uk = we(zs()),
+      fk = we(Us()),
+      ck = we(ua()),
+      pk = we(Xs()),
+      dk = we(Ms()),
+      hk = we(Ns()),
+      mk = we(Qs()),
+      gk = we(Hs()),
+      yk = we(sa());
+    function we(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    var bk = function(e) {
+      return new ak.default(e);
+    };
+    G.attribute = bk;
+    var wk = function(e) {
+      return new ok.default(e);
+    };
+    G.className = wk;
+    var vk = function(e) {
+      return new lk.default(e);
+    };
+    G.combinator = vk;
+    var xk = function(e) {
+      return new uk.default(e);
+    };
+    G.comment = xk;
+    var kk = function(e) {
+      return new fk.default(e);
+    };
+    G.id = kk;
+    var Sk = function(e) {
+      return new ck.default(e);
+    };
+    G.nesting = Sk;
+    var _k = function(e) {
+      return new pk.default(e);
+    };
+    G.pseudo = _k;
+    var Ck = function(e) {
+      return new dk.default(e);
+    };
+    G.root = Ck;
+    var Ak = function(e) {
+      return new hk.default(e);
+    };
+    G.selector = Ak;
+    var Ok = function(e) {
+      return new mk.default(e);
+    };
+    G.string = Ok;
+    var Ek = function(e) {
+      return new gk.default(e);
+    };
+    G.tag = Ek;
+    var Tk = function(e) {
+      return new yk.default(e);
+    };
+    G.universal = Tk;
+  });
+  var hp = v(B => {
+    l();
+    "use strict";
+    B.__esModule = !0;
+    B.isComment =
+      B.isCombinator =
+      B.isClassName =
+      B.isAttribute =
+        void 0;
+    B.isContainer = jk;
+    B.isIdentifier = void 0;
+    B.isNamespace = zk;
+    B.isNesting = void 0;
+    B.isNode = wa;
+    B.isPseudo = void 0;
+    B.isPseudoClass = $k;
+    B.isPseudoElement = dp;
+    B.isUniversal =
+      B.isTag =
+      B.isString =
+      B.isSelector =
+      B.isRoot =
+        void 0;
+    var Y = ae(),
+      fe,
+      Pk =
+        (fe = {},
+          fe[Y.ATTRIBUTE] = !0,
+          fe[Y.CLASS] = !0,
+          fe[Y.COMBINATOR] = !0,
+          fe[Y.COMMENT] = !0,
+          fe[Y.ID] = !0,
+          fe[Y.NESTING] = !0,
+          fe[Y.PSEUDO] = !0,
+          fe[Y.ROOT] = !0,
+          fe[Y.SELECTOR] = !0,
+          fe[Y.STRING] = !0,
+          fe[Y.TAG] = !0,
+          fe[Y.UNIVERSAL] = !0,
+          fe);
+    function wa(r) {
+      return typeof r == "object" && Pk[r.type];
+    }
+    function ve(r, e) {
+      return wa(e) && e.type === r;
+    }
+    var cp = ve.bind(null, Y.ATTRIBUTE);
+    B.isAttribute = cp;
+    var Dk = ve.bind(null, Y.CLASS);
+    B.isClassName = Dk;
+    var Ik = ve.bind(null, Y.COMBINATOR);
+    B.isCombinator = Ik;
+    var qk = ve.bind(null, Y.COMMENT);
+    B.isComment = qk;
+    var Rk = ve.bind(null, Y.ID);
+    B.isIdentifier = Rk;
+    var Mk = ve.bind(null, Y.NESTING);
+    B.isNesting = Mk;
+    var va = ve.bind(null, Y.PSEUDO);
+    B.isPseudo = va;
+    var Fk = ve.bind(null, Y.ROOT);
+    B.isRoot = Fk;
+    var Nk = ve.bind(null, Y.SELECTOR);
+    B.isSelector = Nk;
+    var Lk = ve.bind(null, Y.STRING);
+    B.isString = Lk;
+    var pp = ve.bind(null, Y.TAG);
+    B.isTag = pp;
+    var Bk = ve.bind(null, Y.UNIVERSAL);
+    B.isUniversal = Bk;
+    function dp(r) {
+      return va(r) && r.value
+        && (r.value.startsWith("::") || r.value.toLowerCase() === ":before" || r.value.toLowerCase() === ":after"
+          || r.value.toLowerCase() === ":first-letter" || r.value.toLowerCase() === ":first-line");
+    }
+    function $k(r) {
+      return va(r) && !dp(r);
+    }
+    function jk(r) {
+      return !!(wa(r) && r.walk);
+    }
+    function zk(r) {
+      return cp(r) || pp(r);
+    }
+  });
+  var mp = v(Ee => {
+    l();
+    "use strict";
+    Ee.__esModule = !0;
+    var xa = ae();
+    Object.keys(xa).forEach(function(r) {
+      r === "default" || r === "__esModule" || r in Ee && Ee[r] === xa[r] || (Ee[r] = xa[r]);
+    });
+    var ka = fp();
+    Object.keys(ka).forEach(function(r) {
+      r === "default" || r === "__esModule" || r in Ee && Ee[r] === ka[r] || (Ee[r] = ka[r]);
+    });
+    var Sa = hp();
+    Object.keys(Sa).forEach(function(r) {
+      r === "default" || r === "__esModule" || r in Ee && Ee[r] === Sa[r] || (Ee[r] = Sa[r]);
+    });
+  });
+  var Me = v((Ur, yp) => {
+    l();
+    "use strict";
+    Ur.__esModule = !0;
+    Ur.default = void 0;
+    var Vk = Gk(up()), Uk = Wk(mp());
+    function gp(r) {
+      if (typeof WeakMap != "function") return null;
+      var e = new WeakMap(), t = new WeakMap();
+      return (gp = function(n) {
+        return n ? t : e;
+      })(r);
+    }
+    function Wk(r, e) {
+      if (!e && r && r.__esModule) return r;
+      if (r === null || typeof r != "object" && typeof r != "function") return { default: r };
+      var t = gp(e);
+      if (t && t.has(r)) return t.get(r);
+      var i = {}, n = Object.defineProperty && Object.getOwnPropertyDescriptor;
+      for (var s in r) {
+        if (s !== "default" && Object.prototype.hasOwnProperty.call(r, s)) {
+          var a = n ? Object.getOwnPropertyDescriptor(r, s) : null;
+          a && (a.get || a.set) ? Object.defineProperty(i, s, a) : i[s] = r[s];
+        }
+      }
+      return i.default = r, t && t.set(r, i), i;
+    }
+    function Gk(r) {
+      return r && r.__esModule ? r : { default: r };
+    }
+    var _a = function(e) {
+      return new Vk.default(e);
+    };
+    Object.assign(_a, Uk);
+    delete _a.__esModule;
+    var Hk = _a;
+    Ur.default = Hk;
+    yp.exports = Ur.default;
+  });
+  function We(r) {
+    return ["fontSize", "outline"].includes(r)
+      ? e => (typeof e == "function" && (e = e({})), Array.isArray(e) && (e = e[0]), e)
+      : r === "fontFamily"
+      ? e => {
+        typeof e == "function" && (e = e({}));
+        let t = Array.isArray(e) && se(e[1]) ? e[0] : e;
+        return Array.isArray(t) ? t.join(", ") : t;
+      }
+      : [
+          "boxShadow",
+          "transitionProperty",
+          "transitionDuration",
+          "transitionDelay",
+          "transitionTimingFunction",
+          "backgroundImage",
+          "backgroundSize",
+          "backgroundColor",
+          "cursor",
+          "animation",
+        ].includes(r)
+      ? e => (typeof e == "function" && (e = e({})), Array.isArray(e) && (e = e.join(", ")), e)
+      : ["gridTemplateColumns", "gridTemplateRows", "objectPosition"].includes(r)
+      ? e => (typeof e == "function" && (e = e({})), typeof e == "string" && (e = j.list.comma(e).join(" ")), e)
+      : (e, t = {}) => (typeof e == "function" && (e = e(t)), e);
+  }
+  var Wr = C(() => {
+    l();
+    it();
+    vt();
+  });
+  var _p = v((zT, Ta) => {
+    l();
+    var { Rule: bp, AtRule: Yk } = me(), wp = Me();
+    function Ca(r, e) {
+      let t;
+      try {
+        wp(i => {
+          t = i;
+        }).processSync(r);
+      } catch (i) {
+        throw r.includes(":") ? e ? e.error("Missed semicolon") : i : e ? e.error(i.message) : i;
+      }
+      return t.at(0);
+    }
+    function vp(r, e) {
+      let t = !1;
+      return r.each(i => {
+        if (i.type === "nesting") {
+          let n = e.clone({});
+          i.value !== "&" ? i.replaceWith(Ca(i.value.replace("&", n.toString()))) : i.replaceWith(n), t = !0;
+        } else "nodes" in i && i.nodes && vp(i, e) && (t = !0);
+      }),
+        t;
+    }
+    function xp(r, e) {
+      let t = [];
+      return r.selectors.forEach(i => {
+        let n = Ca(i, r);
+        e.selectors.forEach(s => {
+          if (!s) return;
+          let a = Ca(s, e);
+          vp(a, n) || (a.prepend(wp.combinator({ value: " " })), a.prepend(n.clone({}))), t.push(a.toString());
+        });
+      }),
+        t;
+    }
+    function tn(r, e) {
+      let t = r.prev();
+      for (e.after(r); t && t.type === "comment";) {
+        let i = t.prev();
+        e.after(t), t = i;
+      }
+      return r;
+    }
+    function Qk(r) {
+      return function e(t, i, n, s = n) {
+        let a = [];
+        if (
+          i.each(o => {
+            o.type === "rule" && n
+              ? s && (o.selectors = xp(t, o))
+              : o.type === "atrule" && o.nodes
+              ? r[o.name] ? e(t, o, s) : i[Oa] !== !1 && a.push(o)
+              : a.push(o);
+          }), n && a.length
+        ) {
+          let o = t.clone({ nodes: [] });
+          for (let u of a) o.append(u);
+          i.prepend(o);
+        }
+      };
+    }
+    function Aa(r, e, t) {
+      let i = new bp({ selector: r, nodes: [] });
+      return i.append(e), t.after(i), i;
+    }
+    function kp(r, e) {
+      let t = {};
+      for (let i of r) t[i] = !0;
+      if (e) for (let i of e) t[i.replace(/^@/, "")] = !0;
+      return t;
+    }
+    function Jk(r) {
+      r = r.trim();
+      let e = r.match(/^\((.*)\)$/);
+      if (!e) return { type: "basic", selector: r };
+      let t = e[1].match(/^(with(?:out)?):(.+)$/);
+      if (t) {
+        let i = t[1] === "with", n = Object.fromEntries(t[2].trim().split(/\s+/).map(a => [a, !0]));
+        if (i && n.all) return { type: "noop" };
+        let s = a => !!n[a];
+        return n.all ? s = () => !0 : i && (s = a => a === "all" ? !1 : !n[a]), { type: "withrules", escapes: s };
+      }
+      return { type: "unknown" };
+    }
+    function Xk(r) {
+      let e = [], t = r.parent;
+      for (; t && t instanceof Yk;) e.push(t), t = t.parent;
+      return e;
+    }
+    function Kk(r) {
+      let e = r[Sp];
+      if (!e) r.after(r.nodes);
+      else {
+        let t = r.nodes, i, n = -1, s, a, o, u = Xk(r);
+        if (
+          u.forEach((c, f) => {
+            if (e(c.name)) i = c, n = f, a = o;
+            else {
+              let p = o;
+              o = c.clone({ nodes: [] }), p && o.append(p), s = s || o;
+            }
+          }),
+            i ? a ? (s.append(t), i.after(a)) : i.after(t) : r.after(t),
+            r.next() && i
+        ) {
+          let c;
+          u.slice(0, n + 1).forEach((f, p, d) => {
+            let h = c;
+            c = f.clone({ nodes: [] }), h && c.append(h);
+            let y = [], b = (d[p - 1] || r).next();
+            for (; b;) y.push(b), b = b.next();
+            c.append(y);
+          }), c && (a || t[t.length - 1]).after(c);
+        }
+      }
+      r.remove();
+    }
+    var Oa = Symbol("rootRuleMergeSel"), Sp = Symbol("rootRuleEscapes");
+    function Zk(r) {
+      let { params: e } = r, { type: t, selector: i, escapes: n } = Jk(e);
+      if (t === "unknown") throw r.error(`Unknown @${r.name} parameter ${JSON.stringify(e)}`);
+      if (t === "basic" && i) {
+        let s = new bp({ selector: i, nodes: r.nodes });
+        r.removeAll(), r.append(s);
+      }
+      r[Sp] = n, r[Oa] = n ? !n("all") : t === "noop";
+    }
+    var Ea = Symbol("hasRootRule");
+    Ta.exports = (r = {}) => {
+      let e = kp(["media", "supports", "layer", "container"], r.bubble),
+        t = Qk(e),
+        i = kp(["document", "font-face", "keyframes", "-webkit-keyframes", "-moz-keyframes"], r.unwrap),
+        n = (r.rootRuleName || "at-root").replace(/^@/, ""),
+        s = r.preserveEmpty;
+      return {
+        postcssPlugin: "postcss-nested",
+        Once(a) {
+          a.walkAtRules(n, o => {
+            Zk(o), a[Ea] = !0;
+          });
+        },
+        Rule(a) {
+          let o = !1, u = a, c = !1, f = [];
+          a.each(p => {
+            p.type === "rule"
+              ? (f.length && (u = Aa(a.selector, f, u), f = []), c = !0, o = !0, p.selectors = xp(a, p), u = tn(p, u))
+              : p.type === "atrule"
+              ? (f.length && (u = Aa(a.selector, f, u), f = []),
+                p.name === n
+                  ? (o = !0, t(a, p, !0, p[Oa]), u = tn(p, u))
+                  : e[p.name]
+                  ? (c = !0, o = !0, t(a, p, !0), u = tn(p, u))
+                  : i[p.name]
+                  ? (c = !0, o = !0, t(a, p, !1), u = tn(p, u))
+                  : c && f.push(p))
+              : p.type === "decl" && c && f.push(p);
+          }),
+            f.length && (u = Aa(a.selector, f, u)),
+            o && s !== !0 && (a.raws.semicolon = !0, a.nodes.length === 0 && a.remove());
+        },
+        RootExit(a) {
+          a[Ea] && (a.walkAtRules(n, Kk), a[Ea] = !1);
+        },
+      };
+    };
+    Ta.exports.postcss = !0;
+  });
+  var Ep = v((VT, Op) => {
+    l();
+    "use strict";
+    var Cp = /-(\w|$)/g,
+      Ap = (r, e) => e.toUpperCase(),
+      eS =
+        r => (r = r.toLowerCase(),
+          r === "float" ? "cssFloat" : r.startsWith("-ms-") ? r.substr(1).replace(Cp, Ap) : r.replace(Cp, Ap));
+    Op.exports = eS;
+  });
+  var Ia = v((UT, Tp) => {
+    l();
+    var tS = Ep(),
+      rS = {
+        boxFlex: !0,
+        boxFlexGroup: !0,
+        columnCount: !0,
+        flex: !0,
+        flexGrow: !0,
+        flexPositive: !0,
+        flexShrink: !0,
+        flexNegative: !0,
+        fontWeight: !0,
+        lineClamp: !0,
+        lineHeight: !0,
+        opacity: !0,
+        order: !0,
+        orphans: !0,
+        tabSize: !0,
+        widows: !0,
+        zIndex: !0,
+        zoom: !0,
+        fillOpacity: !0,
+        strokeDashoffset: !0,
+        strokeOpacity: !0,
+        strokeWidth: !0,
+      };
+    function Pa(r) {
+      return typeof r.nodes == "undefined" ? !0 : Da(r);
+    }
+    function Da(r) {
+      let e, t = {};
+      return r.each(i => {
+        if (i.type === "atrule") {
+          e = "@" + i.name,
+            i.params && (e += " " + i.params),
+            typeof t[e] == "undefined" ? t[e] = Pa(i) : Array.isArray(t[e]) ? t[e].push(Pa(i)) : t[e] = [t[e], Pa(i)];
+        } else if (i.type === "rule") {
+          let n = Da(i);
+          if (t[i.selector]) for (let s in n) t[i.selector][s] = n[s];
+          else t[i.selector] = n;
+        } else if (i.type === "decl") {
+          i.prop[0] === "-" && i.prop[1] === "-" || i.parent && i.parent.selector === ":export"
+            ? e = i.prop
+            : e = tS(i.prop);
+          let n = i.value;
+          !isNaN(i.value) && rS[e] && (n = parseFloat(i.value)),
+            i.important && (n += " !important"),
+            typeof t[e] == "undefined" ? t[e] = n : Array.isArray(t[e]) ? t[e].push(n) : t[e] = [t[e], n];
+        }
+      }),
+        t;
+    }
+    Tp.exports = Da;
+  });
+  var rn = v((WT, qp) => {
+    l();
+    var Gr = me(),
+      Pp = /\s*!important\s*$/i,
+      iS = {
+        "box-flex": !0,
+        "box-flex-group": !0,
+        "column-count": !0,
+        flex: !0,
+        "flex-grow": !0,
+        "flex-positive": !0,
+        "flex-shrink": !0,
+        "flex-negative": !0,
+        "font-weight": !0,
+        "line-clamp": !0,
+        "line-height": !0,
+        opacity: !0,
+        order: !0,
+        orphans: !0,
+        "tab-size": !0,
+        widows: !0,
+        "z-index": !0,
+        zoom: !0,
+        "fill-opacity": !0,
+        "stroke-dashoffset": !0,
+        "stroke-opacity": !0,
+        "stroke-width": !0,
+      };
+    function nS(r) {
+      return r.replace(/([A-Z])/g, "-$1").replace(/^ms-/, "-ms-").toLowerCase();
+    }
+    function Dp(r, e, t) {
+      t === !1 || t === null
+        || (e.startsWith("--") || (e = nS(e)),
+          typeof t == "number" && (t === 0 || iS[e] ? t = t.toString() : t += "px"),
+          e === "css-float" && (e = "float"),
+          Pp.test(t)
+            ? (t = t.replace(Pp, ""), r.push(Gr.decl({ prop: e, value: t, important: !0 })))
+            : r.push(Gr.decl({ prop: e, value: t })));
+    }
+    function Ip(r, e, t) {
+      let i = Gr.atRule({ name: e[1], params: e[3] || "" });
+      typeof t == "object" && (i.nodes = [], qa(t, i)), r.push(i);
+    }
+    function qa(r, e) {
+      let t, i, n;
+      for (t in r) {
+        if (i = r[t], !(i === null || typeof i == "undefined")) {
+          if (t[0] === "@") {
+            let s = t.match(/@(\S+)(\s+([\W\w]*)\s*)?/);
+            if (Array.isArray(i)) for (let a of i) Ip(e, s, a);
+            else Ip(e, s, i);
+          } else if (Array.isArray(i)) for (let s of i) Dp(e, t, s);
+          else typeof i == "object" ? (n = Gr.rule({ selector: t }), qa(i, n), e.push(n)) : Dp(e, t, i);
+        }
+      }
+    }
+    qp.exports = function(r) {
+      let e = Gr.root();
+      return qa(r, e), e;
+    };
+  });
+  var Ra = v((GT, Rp) => {
+    l();
+    var sS = Ia();
+    Rp.exports = function(e) {
+      return console && console.warn && e.warnings().forEach(t => {
+        let i = t.plugin || "PostCSS";
+        console.warn(i + ": " + t.text);
+      }),
+        sS(e.root);
+    };
+  });
+  var Fp = v((HT, Mp) => {
+    l();
+    var aS = me(), oS = Ra(), lS = rn();
+    Mp.exports = function(e) {
+      let t = aS(e);
+      return async i => {
+        let n = await t.process(i, { parser: lS, from: void 0 });
+        return oS(n);
+      };
+    };
+  });
+  var Lp = v((YT, Np) => {
+    l();
+    var uS = me(), fS = Ra(), cS = rn();
+    Np.exports = function(r) {
+      let e = uS(r);
+      return t => {
+        let i = e.process(t, { parser: cS, from: void 0 });
+        return fS(i);
+      };
+    };
+  });
+  var $p = v((QT, Bp) => {
+    l();
+    var pS = Ia(), dS = rn(), hS = Fp(), mS = Lp();
+    Bp.exports = { objectify: pS, parse: dS, async: hS, sync: mS };
+  });
+  var Dt,
+    jp,
+    JT,
+    XT,
+    KT,
+    ZT,
+    zp = C(() => {
+      l();
+      Dt = K($p()),
+        jp = Dt.default,
+        JT = Dt.default.objectify,
+        XT = Dt.default.parse,
+        KT = Dt.default.async,
+        ZT = Dt.default.sync;
+    });
+  function It(r) {
+    return Array.isArray(r)
+      ? r.flatMap(e => j([(0, Vp.default)({ bubble: ["screen"] })]).process(e, { parser: jp }).root.nodes)
+      : It([r]);
+  }
+  var Vp,
+    Ma = C(() => {
+      l();
+      it();
+      Vp = K(_p());
+      zp();
+    });
+  function qt(r, e, t = !1) {
+    if (r === "") return e;
+    let i = typeof e == "string" ? (0, Up.default)().astSync(e) : e;
+    return i.walkClasses(n => {
+      let s = n.value, a = t && s.startsWith("-");
+      n.value = a ? `-${r}${s.slice(1)}` : `${r}${s}`;
+    }),
+      typeof e == "string" ? i.toString() : i;
+  }
+  var Up,
+    nn = C(() => {
+      l();
+      Up = K(Me());
+    });
+  function ce(r) {
+    let e = Wp.default.className();
+    return e.value = r, pt(e?.raws?.value ?? e.value);
+  }
+  var Wp,
+    Rt = C(() => {
+      l();
+      Wp = K(Me());
+      fi();
+    });
+  function Fa(r) {
+    return pt(`.${ce(r)}`);
+  }
+  function sn(r, e) {
+    return Fa(Hr(r, e));
+  }
+  function Hr(r, e) {
+    return e === "DEFAULT"
+      ? r
+      : e === "-" || e === "-DEFAULT"
+      ? `-${r}`
+      : e.startsWith("-")
+      ? `-${r}${e}`
+      : e.startsWith("/")
+      ? `${r}${e}`
+      : `${r}-${e}`;
+  }
+  var Na = C(() => {
+    l();
+    Rt();
+    fi();
+  });
+  function T(r, e = [[r, [r]]], { filterDefault: t = !1, ...i } = {}) {
+    let n = We(r);
+    return function({ matchUtilities: s, theme: a }) {
+      for (let o of e) {
+        let u = Array.isArray(o[0]) ? o : [o];
+        s(
+          u.reduce((c, [f, p]) =>
+            Object.assign(c, {
+              [f]: d =>
+                p.reduce(
+                  (h, y) => Array.isArray(y) ? Object.assign(h, { [y[0]]: y[1] }) : Object.assign(h, { [y]: n(d) }),
+                  {},
+                ),
+            }), {}),
+          {
+            ...i,
+            values: t
+              ? Object.fromEntries(Object.entries(a(r) ?? {}).filter(([c]) => c !== "DEFAULT"))
+              : a(r),
+          },
+        );
+      }
+    };
+  }
+  var Gp = C(() => {
+    l();
+    Wr();
+  });
+  function nt(r) {
+    return r = Array.isArray(r) ? r : [r],
+      r.map(e => {
+        let t = e.values.map(i =>
+          i.raw !== void 0
+            ? i.raw
+            : [i.min && `(min-width: ${i.min})`, i.max && `(max-width: ${i.max})`].filter(Boolean).join(" and ")
+        );
+        return e.not ? `not all and ${t}` : t;
+      }).join(", ");
+  }
+  var an = C(() => {
+    l();
+  });
+  function La(r) {
+    return r.split(kS).map(t => {
+      let i = t.trim(), n = { value: i }, s = i.split(SS), a = new Set();
+      for (let o of s) {
+        !a.has("DIRECTIONS") && gS.has(o)
+          ? (n.direction = o, a.add("DIRECTIONS"))
+          : !a.has("PLAY_STATES") && yS.has(o)
+          ? (n.playState = o, a.add("PLAY_STATES"))
+          : !a.has("FILL_MODES") && bS.has(o)
+          ? (n.fillMode = o, a.add("FILL_MODES"))
+          : !a.has("ITERATION_COUNTS") && (wS.has(o) || _S.test(o))
+          ? (n.iterationCount = o, a.add("ITERATION_COUNTS"))
+          : !a.has("TIMING_FUNCTION") && vS.has(o) || !a.has("TIMING_FUNCTION") && xS.some(u => o.startsWith(`${u}(`))
+          ? (n.timingFunction = o, a.add("TIMING_FUNCTION"))
+          : !a.has("DURATION") && Hp.test(o)
+          ? (n.duration = o, a.add("DURATION"))
+          : !a.has("DELAY") && Hp.test(o)
+          ? (n.delay = o, a.add("DELAY"))
+          : a.has("NAME")
+          ? (n.unknown || (n.unknown = []), n.unknown.push(o))
+          : (n.name = o, a.add("NAME"));
+      }
+      return n;
+    });
+  }
+  var gS,
+    yS,
+    bS,
+    wS,
+    vS,
+    xS,
+    kS,
+    SS,
+    Hp,
+    _S,
+    Yp = C(() => {
+      l();
+      gS = new Set(["normal", "reverse", "alternate", "alternate-reverse"]),
+        yS = new Set(["running", "paused"]),
+        bS = new Set(["none", "forwards", "backwards", "both"]),
+        wS = new Set(["infinite"]),
+        vS = new Set(["linear", "ease", "ease-in", "ease-out", "ease-in-out", "step-start", "step-end"]),
+        xS = ["cubic-bezier", "steps"],
+        kS = /\,(?![^(]*\))/g,
+        SS = /\ +(?![^(]*\))/g,
+        Hp = /^(-?[\d.]+m?s)$/,
+        _S = /^(\d+)$/;
+    });
+  var Qp,
+    ne,
+    Jp = C(() => {
+      l();
+      Qp = r =>
+        Object.assign(
+          {},
+          ...Object.entries(r ?? {}).flatMap(([e, t]) =>
+            typeof t == "object"
+              ? Object.entries(Qp(t)).map(([i, n]) => ({ [e + (i === "DEFAULT" ? "" : `-${i}`)]: n }))
+              : [{ [`${e}`]: t }]
+          ),
+        ), ne = Qp;
+    });
+  var CS,
+    $a,
+    AS,
+    OS,
+    ES,
+    TS,
+    PS,
+    DS,
+    IS,
+    qS,
+    RS,
+    MS,
+    FS,
+    NS,
+    LS,
+    BS,
+    $S,
+    jS,
+    ja,
+    Ba = C(() => {
+      CS = "tailwindcss",
+        $a = "3.3.2",
+        AS = "A utility-first CSS framework for rapidly building custom user interfaces.",
+        OS = "MIT",
+        ES = "lib/index.js",
+        TS = "types/index.d.ts",
+        PS = "https://github.com/tailwindlabs/tailwindcss.git",
+        DS = "https://github.com/tailwindlabs/tailwindcss/issues",
+        IS = "https://tailwindcss.com",
+        qS = { tailwind: "lib/cli.js", tailwindcss: "lib/cli.js" },
+        RS = { engine: "stable" },
+        MS = {
+          prebuild: "npm run generate && rimraf lib",
+          build: `swc src --out-dir lib --copy-files --config jsc.transform.optimizer.globals.vars.__OXIDE__='"false"'`,
+          postbuild:
+            "esbuild lib/cli-peer-dependencies.js --bundle --platform=node --outfile=peers/index.js --define:process.env.CSS_TRANSFORMER_WASM=false",
+          "rebuild-fixtures": "npm run build && node -r @swc/register scripts/rebuildFixtures.js",
+          style: "eslint .",
+          pretest: "npm run generate",
+          test: "jest",
+          "test:integrations": "npm run test --prefix ./integrations",
+          "install:integrations": "node scripts/install-integrations.js",
+          "generate:plugin-list": "node -r @swc/register scripts/create-plugin-list.js",
+          "generate:types": "node -r @swc/register scripts/generate-types.js",
+          generate: "npm run generate:plugin-list && npm run generate:types",
+          "release-channel": "node ./scripts/release-channel.js",
+          "release-notes": "node ./scripts/release-notes.js",
+          prepublishOnly: "npm install --force && npm run build",
+        },
+        FS = [
+          "src/*",
+          "cli/*",
+          "lib/*",
+          "peers/*",
+          "scripts/*.js",
+          "stubs/*",
+          "nesting/*",
+          "types/**/*",
+          "*.d.ts",
+          "*.css",
+          "*.js",
+        ],
+        NS = {
+          "@swc/cli": "^0.1.62",
+          "@swc/core": "^1.3.55",
+          "@swc/jest": "^0.2.26",
+          "@swc/register": "^0.1.10",
+          autoprefixer: "^10.4.14",
+          browserslist: "^4.21.5",
+          concurrently: "^8.0.1",
+          cssnano: "^6.0.0",
+          esbuild: "^0.17.18",
+          eslint: "^8.39.0",
+          "eslint-config-prettier": "^8.8.0",
+          "eslint-plugin-prettier": "^4.2.1",
+          jest: "^29.5.0",
+          "jest-diff": "^29.5.0",
+          lightningcss: "1.18.0",
+          prettier: "^2.8.8",
+          rimraf: "^5.0.0",
+          "source-map-js": "^1.0.2",
+          turbo: "^1.9.3",
+        },
+        LS = {
+          "@alloc/quick-lru": "^5.2.0",
+          arg: "^5.0.2",
+          chokidar: "^3.5.3",
+          didyoumean: "^1.2.2",
+          dlv: "^1.1.3",
+          "fast-glob": "^3.2.12",
+          "glob-parent": "^6.0.2",
+          "is-glob": "^4.0.3",
+          jiti: "^1.18.2",
+          lilconfig: "^2.1.0",
+          micromatch: "^4.0.5",
+          "normalize-path": "^3.0.0",
+          "object-hash": "^3.0.0",
+          picocolors: "^1.0.0",
+          postcss: "^8.4.23",
+          "postcss-import": "^15.1.0",
+          "postcss-js": "^4.0.1",
+          "postcss-load-config": "^4.0.1",
+          "postcss-nested": "^6.0.1",
+          "postcss-selector-parser": "^6.0.11",
+          "postcss-value-parser": "^4.2.0",
+          resolve: "^1.22.2",
+          sucrase: "^3.32.0",
+        },
+        BS = ["> 1%", "not edge <= 18", "not ie 11", "not op_mini all"],
+        $S = {
+          testTimeout: 3e4,
+          setupFilesAfterEnv: ["<rootDir>/jest/customMatchers.js"],
+          testPathIgnorePatterns: ["/node_modules/", "/integrations/", "/standalone-cli/", "\\.test\\.skip\\.js$"],
+          transformIgnorePatterns: ["node_modules/(?!lightningcss)"],
+          transform: { "\\.js$": "@swc/jest", "\\.ts$": "@swc/jest" },
+        },
+        jS = { node: ">=14.0.0" },
+        ja = {
+          name: CS,
+          version: $a,
+          description: AS,
+          license: OS,
+          main: ES,
+          types: TS,
+          repository: PS,
+          bugs: DS,
+          homepage: IS,
+          bin: qS,
+          tailwindcss: RS,
+          scripts: MS,
+          files: FS,
+          devDependencies: NS,
+          dependencies: LS,
+          browserslist: BS,
+          jest: $S,
+          engines: jS,
+        };
+    });
+  function st(r, e = !0) {
+    return Array.isArray(r)
+      ? r.map(t => {
+        if (e && Array.isArray(t)) throw new Error("The tuple syntax is not supported for `screens`.");
+        if (typeof t == "string") return { name: t.toString(), not: !1, values: [{ min: t, max: void 0 }] };
+        let [i, n] = t;
+        return i = i.toString(),
+          typeof n == "string"
+            ? { name: i, not: !1, values: [{ min: n, max: void 0 }] }
+            : Array.isArray(n)
+            ? { name: i, not: !1, values: n.map(s => Kp(s)) }
+            : { name: i, not: !1, values: [Kp(n)] };
+      })
+      : st(Object.entries(r ?? {}), !1);
+  }
+  function on(r) {
+    return r.values.length !== 1
+      ? { result: !1, reason: "multiple-values" }
+      : r.values[0].raw !== void 0
+      ? { result: !1, reason: "raw-values" }
+      : r.values[0].min !== void 0 && r.values[0].max !== void 0
+      ? { result: !1, reason: "min-and-max" }
+      : { result: !0, reason: null };
+  }
+  function Xp(r, e, t) {
+    let i = ln(e, r), n = ln(t, r), s = on(i), a = on(n);
+    if (s.reason === "multiple-values" || a.reason === "multiple-values") {
+      throw new Error(
+        "Attempted to sort a screen with multiple values. This should never happen. Please open a bug report.",
+      );
+    }
+    if (s.reason === "raw-values" || a.reason === "raw-values") {
+      throw new Error(
+        "Attempted to sort a screen with raw values. This should never happen. Please open a bug report.",
+      );
+    }
+    if (s.reason === "min-and-max" || a.reason === "min-and-max") {
+      throw new Error(
+        "Attempted to sort a screen with both min and max values. This should never happen. Please open a bug report.",
+      );
+    }
+    let { min: o, max: u } = i.values[0], { min: c, max: f } = n.values[0];
+    e.not && ([o, u] = [u, o]),
+      t.not && ([c, f] = [f, c]),
+      o = o === void 0 ? o : parseFloat(o),
+      u = u === void 0 ? u : parseFloat(u),
+      c = c === void 0 ? c : parseFloat(c),
+      f = f === void 0 ? f : parseFloat(f);
+    let [p, d] = r === "min" ? [o, c] : [f, u];
+    return p - d;
+  }
+  function ln(r, e) {
+    return typeof r == "object" ? r : { name: "arbitrary-screen", values: [{ [e]: r }] };
+  }
+  function Kp({ "min-width": r, min: e = r, max: t, raw: i } = {}) {
+    return { min: e, max: t, raw: i };
+  }
+  var un = C(() => {
+    l();
+  });
+  function fn(r, e) {
+    r.walkDecls(t => {
+      if (e.includes(t.prop)) {
+        t.remove();
+        return;
+      }
+      for (let i of e) t.value.includes(`/ var(${i})`) && (t.value = t.value.replace(`/ var(${i})`, ""));
+    });
+  }
+  var Zp = C(() => {
+    l();
+  });
+  var pe,
+    Te,
+    Fe,
+    Ne,
+    ed,
+    td = C(() => {
+      l();
+      je();
+      dt();
+      it();
+      Gp();
+      an();
+      Rt();
+      Yp();
+      Jp();
+      nr();
+      ns();
+      vt();
+      Wr();
+      Ba();
+      Oe();
+      un();
+      Xn();
+      Zp();
+      De();
+      lr();
+      pe = {
+        pseudoElementVariants: ({ addVariant: r }) => {
+          r("first-letter", "&::first-letter"),
+            r("first-line", "&::first-line"),
+            r("marker", [
+              ({ container: e }) => (fn(e, ["--tw-text-opacity"]), "& *::marker"),
+              ({ container: e }) => (fn(e, ["--tw-text-opacity"]), "&::marker"),
+            ]),
+            r("selection", ["& *::selection", "&::selection"]),
+            r("file", "&::file-selector-button"),
+            r("placeholder", "&::placeholder"),
+            r("backdrop", "&::backdrop"),
+            r("before", ({ container: e }) => (e.walkRules(t => {
+              let i = !1;
+              t.walkDecls("content", () => {
+                i = !0;
+              }), i || t.prepend(j.decl({ prop: "content", value: "var(--tw-content)" }));
+            }),
+              "&::before")),
+            r("after", ({ container: e }) => (e.walkRules(t => {
+              let i = !1;
+              t.walkDecls("content", () => {
+                i = !0;
+              }), i || t.prepend(j.decl({ prop: "content", value: "var(--tw-content)" }));
+            }),
+              "&::after"));
+        },
+        pseudoClassVariants: ({ addVariant: r, matchVariant: e, config: t }) => {
+          let i = [
+            ["first", "&:first-child"],
+            ["last", "&:last-child"],
+            ["only", "&:only-child"],
+            ["odd", "&:nth-child(odd)"],
+            ["even", "&:nth-child(even)"],
+            "first-of-type",
+            "last-of-type",
+            "only-of-type",
+            [
+              "visited",
+              (
+                { container: s },
+              ) => (fn(s, ["--tw-text-opacity", "--tw-border-opacity", "--tw-bg-opacity"]), "&:visited"),
+            ],
+            "target",
+            ["open", "&[open]"],
+            "default",
+            "checked",
+            "indeterminate",
+            "placeholder-shown",
+            "autofill",
+            "optional",
+            "required",
+            "valid",
+            "invalid",
+            "in-range",
+            "out-of-range",
+            "read-only",
+            "empty",
+            "focus-within",
+            [
+              "hover",
+              J(t(), "hoverOnlyWhenSupported") ? "@media (hover: hover) and (pointer: fine) { &:hover }" : "&:hover",
+            ],
+            "focus",
+            "focus-visible",
+            "active",
+            "enabled",
+            "disabled",
+          ].map(s => Array.isArray(s) ? s : [s, `&:${s}`]);
+          for (let [s, a] of i) r(s, o => typeof a == "function" ? a(o) : a);
+          let n = {
+            group: (s, { modifier: a }) => a ? [`:merge(.group\\/${ce(a)})`, " &"] : [":merge(.group)", " &"],
+            peer: (s, { modifier: a }) => a ? [`:merge(.peer\\/${ce(a)})`, " ~ &"] : [":merge(.peer)", " ~ &"],
+          };
+          for (let [s, a] of Object.entries(n)) {
+            e(s, (o = "", u) => {
+              let c = V(typeof o == "function" ? o(u) : o);
+              c.includes("&") || (c = "&" + c);
+              let [f, p] = a("", u), d = null, h = null, y = 0;
+              for (let x = 0; x < c.length; ++x) {
+                let b = c[x];
+                b === "&" ? d = x : b === "'" || b === "\"" ? y += 1 : d !== null && b === " " && !y && (h = x);
+              }
+              return d !== null && h === null && (h = c.length), c.slice(0, d) + f + c.slice(d + 1, h) + p + c.slice(h);
+            }, { values: Object.fromEntries(i) });
+          }
+        },
+        directionVariants: ({ addVariant: r }) => {
+          r("ltr", ":is([dir=\"ltr\"] &)"), r("rtl", ":is([dir=\"rtl\"] &)");
+        },
+        reducedMotionVariants: ({ addVariant: r }) => {
+          r("motion-safe", "@media (prefers-reduced-motion: no-preference)"),
+            r("motion-reduce", "@media (prefers-reduced-motion: reduce)");
+        },
+        darkVariants: ({ config: r, addVariant: e }) => {
+          let [t, i = ".dark"] = [].concat(r("darkMode", "media"));
+          t === !1 && (t = "media",
+            N.warn("darkmode-false", [
+              "The `darkMode` option in your Tailwind CSS configuration is set to `false`, which now behaves the same as `media`.",
+              "Change `darkMode` to `media` or remove it entirely.",
+              "https://tailwindcss.com/docs/upgrade-guide#remove-dark-mode-configuration",
+            ])),
+            t === "class"
+              ? e("dark", `:is(${i} &)`)
+              : t === "media" && e("dark", "@media (prefers-color-scheme: dark)");
+        },
+        printVariant: ({ addVariant: r }) => {
+          r("print", "@media print");
+        },
+        screenVariants: ({ theme: r, addVariant: e, matchVariant: t }) => {
+          let i = r("screens") ?? {},
+            n = Object.values(i).every(w => typeof w == "string"),
+            s = st(r("screens")),
+            a = new Set([]);
+          function o(w) {
+            return w.match(/(\D+)$/)?.[1] ?? "(none)";
+          }
+          function u(w) {
+            w !== void 0 && a.add(o(w));
+          }
+          function c(w) {
+            return u(w), a.size === 1;
+          }
+          for (let w of s) for (let k of w.values) u(k.min), u(k.max);
+          let f = a.size <= 1;
+          function p(w) {
+            return Object.fromEntries(
+              s.filter(k => on(k).result).map(k => {
+                let { min: S, max: _ } = k.values[0];
+                if (w === "min" && S !== void 0) return k;
+                if (w === "min" && _ !== void 0) return { ...k, not: !k.not };
+                if (w === "max" && _ !== void 0) return k;
+                if (w === "max" && S !== void 0) return { ...k, not: !k.not };
+              }).map(k => [k.name, k]),
+            );
+          }
+          function d(w) {
+            return (k, S) => Xp(w, k.value, S.value);
+          }
+          let h = d("max"), y = d("min");
+          function x(w) {
+            return k => {
+              if (n) {
+                if (f) {
+                  if (typeof k == "string" && !c(k)) {
+                    return N.warn("minmax-have-mixed-units", [
+                      "The `min-*` and `max-*` variants are not supported with a `screens` configuration containing mixed units.",
+                    ]),
+                      [];
+                  }
+                } else {return N.warn("mixed-screen-units", [
+                    "The `min-*` and `max-*` variants are not supported with a `screens` configuration containing mixed units.",
+                  ]),
+                    [];}
+              } else {return N.warn("complex-screen-config", [
+                  "The `min-*` and `max-*` variants are not supported with a `screens` configuration containing objects.",
+                ]),
+                  [];}
+              return [`@media ${nt(ln(k, w))}`];
+            };
+          }
+          t("max", x("max"), { sort: h, values: n ? p("max") : {} });
+          let b = "min-screens";
+          for (let w of s) e(w.name, `@media ${nt(w)}`, { id: b, sort: n && f ? y : void 0, value: w });
+          t("min", x("min"), { id: b, sort: y });
+        },
+        supportsVariants: ({ matchVariant: r, theme: e }) => {
+          r("supports", (t = "") => {
+            let i = V(t), n = /^\w*\s*\(/.test(i);
+            return i = n ? i.replace(/\b(and|or|not)\b/g, " $1 ") : i,
+              n
+                ? `@supports ${i}`
+                : (i.includes(":") || (i = `${i}: var(--tw)`),
+                  i.startsWith("(") && i.endsWith(")") || (i = `(${i})`),
+                  `@supports ${i}`);
+          }, { values: e("supports") ?? {} });
+        },
+        ariaVariants: ({ matchVariant: r, theme: e }) => {
+          r("aria", t => `&[aria-${V(t)}]`, { values: e("aria") ?? {} }),
+            r(
+              "group-aria",
+              (t, { modifier: i }) => i ? `:merge(.group\\/${i})[aria-${V(t)}] &` : `:merge(.group)[aria-${V(t)}] &`,
+              { values: e("aria") ?? {} },
+            ),
+            r(
+              "peer-aria",
+              (t, { modifier: i }) => i ? `:merge(.peer\\/${i})[aria-${V(t)}] ~ &` : `:merge(.peer)[aria-${V(t)}] ~ &`,
+              { values: e("aria") ?? {} },
+            );
+        },
+        dataVariants: ({ matchVariant: r, theme: e }) => {
+          r("data", t => `&[data-${V(t)}]`, { values: e("data") ?? {} }),
+            r(
+              "group-data",
+              (t, { modifier: i }) => i ? `:merge(.group\\/${i})[data-${V(t)}] &` : `:merge(.group)[data-${V(t)}] &`,
+              { values: e("data") ?? {} },
+            ),
+            r(
+              "peer-data",
+              (t, { modifier: i }) => i ? `:merge(.peer\\/${i})[data-${V(t)}] ~ &` : `:merge(.peer)[data-${V(t)}] ~ &`,
+              { values: e("data") ?? {} },
+            );
+        },
+        orientationVariants: ({ addVariant: r }) => {
+          r("portrait", "@media (orientation: portrait)"), r("landscape", "@media (orientation: landscape)");
+        },
+        prefersContrastVariants: ({ addVariant: r }) => {
+          r("contrast-more", "@media (prefers-contrast: more)"), r("contrast-less", "@media (prefers-contrast: less)");
+        },
+      },
+        Te = [
+          "translate(var(--tw-translate-x), var(--tw-translate-y))",
+          "rotate(var(--tw-rotate))",
+          "skewX(var(--tw-skew-x))",
+          "skewY(var(--tw-skew-y))",
+          "scaleX(var(--tw-scale-x))",
+          "scaleY(var(--tw-scale-y))",
+        ].join(" "),
+        Fe = [
+          "var(--tw-blur)",
+          "var(--tw-brightness)",
+          "var(--tw-contrast)",
+          "var(--tw-grayscale)",
+          "var(--tw-hue-rotate)",
+          "var(--tw-invert)",
+          "var(--tw-saturate)",
+          "var(--tw-sepia)",
+          "var(--tw-drop-shadow)",
+        ].join(" "),
+        Ne = [
+          "var(--tw-backdrop-blur)",
+          "var(--tw-backdrop-brightness)",
+          "var(--tw-backdrop-contrast)",
+          "var(--tw-backdrop-grayscale)",
+          "var(--tw-backdrop-hue-rotate)",
+          "var(--tw-backdrop-invert)",
+          "var(--tw-backdrop-opacity)",
+          "var(--tw-backdrop-saturate)",
+          "var(--tw-backdrop-sepia)",
+        ].join(" "),
+        ed = {
+          preflight: ({ addBase: r }) => {
+            let e = j.parse(
+              `*,::after,::before{box-sizing:border-box;border-width:0;border-style:solid;border-color:theme('borderColor.DEFAULT', currentColor)}::after,::before{--tw-content:''}html{line-height:1.5;-webkit-text-size-adjust:100%;-moz-tab-size:4;tab-size:4;font-family:theme('fontFamily.sans', ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji");font-feature-settings:theme('fontFamily.sans[1].fontFeatureSettings', normal);font-variation-settings:theme('fontFamily.sans[1].fontVariationSettings', normal)}body{margin:0;line-height:inherit}hr{height:0;color:inherit;border-top-width:1px}abbr:where([title]){text-decoration:underline dotted}h1,h2,h3,h4,h5,h6{font-size:inherit;font-weight:inherit}a{color:inherit;text-decoration:inherit}b,strong{font-weight:bolder}code,kbd,pre,samp{font-family:theme('fontFamily.mono', ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace);font-size:1em}small{font-size:80%}sub,sup{font-size:75%;line-height:0;position:relative;vertical-align:baseline}sub{bottom:-.25em}sup{top:-.5em}table{text-indent:0;border-color:inherit;border-collapse:collapse}button,input,optgroup,select,textarea{font-family:inherit;font-size:100%;font-weight:inherit;line-height:inherit;color:inherit;margin:0;padding:0}button,select{text-transform:none}[type=button],[type=reset],[type=submit],button{-webkit-appearance:button;background-color:transparent;background-image:none}:-moz-focusring{outline:auto}:-moz-ui-invalid{box-shadow:none}progress{vertical-align:baseline}::-webkit-inner-spin-button,::-webkit-outer-spin-button{height:auto}[type=search]{-webkit-appearance:textfield;outline-offset:-2px}::-webkit-search-decoration{-webkit-appearance:none}::-webkit-file-upload-button{-webkit-appearance:button;font:inherit}summary{display:list-item}blockquote,dd,dl,figure,h1,h2,h3,h4,h5,h6,hr,p,pre{margin:0}fieldset{margin:0;padding:0}legend{padding:0}menu,ol,ul{list-style:none;margin:0;padding:0}textarea{resize:vertical}input::placeholder,textarea::placeholder{opacity:1;color:theme('colors.gray.4', #9ca3af)}[role=button],button{cursor:pointer}:disabled{cursor:default}audio,canvas,embed,iframe,img,object,svg,video{display:block;vertical-align:middle}img,video{max-width:100%;height:auto}[hidden]{display:none}`,
+            );
+            r([j.comment({ text: `! tailwindcss v${$a} | MIT License | https://tailwindcss.com` }), ...e.nodes]);
+          },
+          container: (() => {
+            function r(t = []) {
+              return t.flatMap(i => i.values.map(n => n.min)).filter(i => i !== void 0);
+            }
+            function e(t, i, n) {
+              if (typeof n == "undefined") return [];
+              if (!(typeof n == "object" && n !== null)) return [{ screen: "DEFAULT", minWidth: 0, padding: n }];
+              let s = [];
+              n.DEFAULT && s.push({ screen: "DEFAULT", minWidth: 0, padding: n.DEFAULT });
+              for (let a of t) {
+                for (let o of i) {
+                  for (let { min: u } of o.values) u === a && s.push({ minWidth: a, padding: n[o.name] });
+                }
+              }
+              return s;
+            }
+            return function({ addComponents: t, theme: i }) {
+              let n = st(i("container.screens", i("screens"))),
+                s = r(n),
+                a = e(s, n, i("container.padding")),
+                o = c => {
+                  let f = a.find(p => p.minWidth === c);
+                  return f ? { paddingRight: f.padding, paddingLeft: f.padding } : {};
+                },
+                u = Array.from(new Set(s.slice().sort((c, f) => parseInt(c) - parseInt(f)))).map(c => ({
+                  [`@media (min-width: ${c})`]: { ".container": { "max-width": c, ...o(c) } },
+                }));
+              t([{
+                ".container": Object.assign(
+                  { width: "100%" },
+                  i("container.center", !1) ? { marginRight: "auto", marginLeft: "auto" } : {},
+                  o(0),
+                ),
+              }, ...u]);
+            };
+          })(),
+          accessibility: ({ addUtilities: r }) => {
+            r({
+              ".sr-only": {
+                position: "absolute",
+                width: "1px",
+                height: "1px",
+                padding: "0",
+                margin: "-1px",
+                overflow: "hidden",
+                clip: "rect(0, 0, 0, 0)",
+                whiteSpace: "nowrap",
+                borderWidth: "0",
+              },
+              ".not-sr-only": {
+                position: "static",
+                width: "auto",
+                height: "auto",
+                padding: "0",
+                margin: "0",
+                overflow: "visible",
+                clip: "auto",
+                whiteSpace: "normal",
+              },
+            });
+          },
+          pointerEvents: ({ addUtilities: r }) => {
+            r({
+              ".pointer-events-none": { "pointer-events": "none" },
+              ".pointer-events-auto": { "pointer-events": "auto" },
+            });
+          },
+          visibility: ({ addUtilities: r }) => {
+            r({
+              ".visible": { visibility: "visible" },
+              ".invisible": { visibility: "hidden" },
+              ".collapse": { visibility: "collapse" },
+            });
+          },
+          position: ({ addUtilities: r }) => {
+            r({
+              ".static": { position: "static" },
+              ".fixed": { position: "fixed" },
+              ".absolute": { position: "absolute" },
+              ".relative": { position: "relative" },
+              ".sticky": { position: "sticky" },
+            });
+          },
+          inset: T("inset", [["inset", ["inset"]], [["inset-x", ["left", "right"]], ["inset-y", ["top", "bottom"]]], [
+            ["start", ["inset-inline-start"]],
+            ["end", ["inset-inline-end"]],
+            ["top", ["top"]],
+            ["right", ["right"]],
+            ["bottom", ["bottom"]],
+            ["left", ["left"]],
+          ]], { supportsNegativeValues: !0 }),
+          isolation: ({ addUtilities: r }) => {
+            r({ ".isolate": { isolation: "isolate" }, ".isolation-auto": { isolation: "auto" } });
+          },
+          zIndex: T("zIndex", [["z", ["zIndex"]]], { supportsNegativeValues: !0 }),
+          order: T("order", void 0, { supportsNegativeValues: !0 }),
+          gridColumn: T("gridColumn", [["col", ["gridColumn"]]]),
+          gridColumnStart: T("gridColumnStart", [["col-start", ["gridColumnStart"]]]),
+          gridColumnEnd: T("gridColumnEnd", [["col-end", ["gridColumnEnd"]]]),
+          gridRow: T("gridRow", [["row", ["gridRow"]]]),
+          gridRowStart: T("gridRowStart", [["row-start", ["gridRowStart"]]]),
+          gridRowEnd: T("gridRowEnd", [["row-end", ["gridRowEnd"]]]),
+          float: ({ addUtilities: r }) => {
+            r({
+              ".float-right": { float: "right" },
+              ".float-left": { float: "left" },
+              ".float-none": { float: "none" },
+            });
+          },
+          clear: ({ addUtilities: r }) => {
+            r({
+              ".clear-left": { clear: "left" },
+              ".clear-right": { clear: "right" },
+              ".clear-both": { clear: "both" },
+              ".clear-none": { clear: "none" },
+            });
+          },
+          margin: T("margin", [["m", ["margin"]], [["mx", ["margin-left", "margin-right"]], ["my", [
+            "margin-top",
+            "margin-bottom",
+          ]]], [
+            ["ms", ["margin-inline-start"]],
+            ["me", ["margin-inline-end"]],
+            ["mt", ["margin-top"]],
+            ["mr", ["margin-right"]],
+            ["mb", ["margin-bottom"]],
+            ["ml", ["margin-left"]],
+          ]], { supportsNegativeValues: !0 }),
+          boxSizing: ({ addUtilities: r }) => {
+            r({ ".box-border": { "box-sizing": "border-box" }, ".box-content": { "box-sizing": "content-box" } });
+          },
+          lineClamp: ({ matchUtilities: r, addUtilities: e, theme: t }) => {
+            r({
+              "line-clamp": i => ({
+                overflow: "hidden",
+                display: "-webkit-box",
+                "-webkit-box-orient": "vertical",
+                "-webkit-line-clamp": `${i}`,
+              }),
+            }, { values: t("lineClamp") }),
+              e({
+                ".line-clamp-none": {
+                  overflow: "visible",
+                  display: "block",
+                  "-webkit-box-orient": "horizontal",
+                  "-webkit-line-clamp": "none",
+                },
+              });
+          },
+          display: ({ addUtilities: r }) => {
+            r({
+              ".block": { display: "block" },
+              ".inline-block": { display: "inline-block" },
+              ".inline": { display: "inline" },
+              ".flex": { display: "flex" },
+              ".inline-flex": { display: "inline-flex" },
+              ".table": { display: "table" },
+              ".inline-table": { display: "inline-table" },
+              ".table-caption": { display: "table-caption" },
+              ".table-cell": { display: "table-cell" },
+              ".table-column": { display: "table-column" },
+              ".table-column-group": { display: "table-column-group" },
+              ".table-footer-group": { display: "table-footer-group" },
+              ".table-header-group": { display: "table-header-group" },
+              ".table-row-group": { display: "table-row-group" },
+              ".table-row": { display: "table-row" },
+              ".flow-root": { display: "flow-root" },
+              ".grid": { display: "grid" },
+              ".inline-grid": { display: "inline-grid" },
+              ".contents": { display: "contents" },
+              ".list-item": { display: "list-item" },
+              ".hidden": { display: "none" },
+            });
+          },
+          aspectRatio: T("aspectRatio", [["aspect", ["aspect-ratio"]]]),
+          height: T("height", [["h", ["height"]]]),
+          maxHeight: T("maxHeight", [["max-h", ["maxHeight"]]]),
+          minHeight: T("minHeight", [["min-h", ["minHeight"]]]),
+          width: T("width", [["w", ["width"]]]),
+          minWidth: T("minWidth", [["min-w", ["minWidth"]]]),
+          maxWidth: T("maxWidth", [["max-w", ["maxWidth"]]]),
+          flex: T("flex"),
+          flexShrink: T("flexShrink", [["flex-shrink", ["flex-shrink"]], ["shrink", ["flex-shrink"]]]),
+          flexGrow: T("flexGrow", [["flex-grow", ["flex-grow"]], ["grow", ["flex-grow"]]]),
+          flexBasis: T("flexBasis", [["basis", ["flex-basis"]]]),
+          tableLayout: ({ addUtilities: r }) => {
+            r({ ".table-auto": { "table-layout": "auto" }, ".table-fixed": { "table-layout": "fixed" } });
+          },
+          captionSide: ({ addUtilities: r }) => {
+            r({ ".caption-top": { "caption-side": "top" }, ".caption-bottom": { "caption-side": "bottom" } });
+          },
+          borderCollapse: ({ addUtilities: r }) => {
+            r({
+              ".border-collapse": { "border-collapse": "collapse" },
+              ".border-separate": { "border-collapse": "separate" },
+            });
+          },
+          borderSpacing: ({ addDefaults: r, matchUtilities: e, theme: t }) => {
+            r("border-spacing", { "--tw-border-spacing-x": 0, "--tw-border-spacing-y": 0 }),
+              e({
+                "border-spacing": i => ({
+                  "--tw-border-spacing-x": i,
+                  "--tw-border-spacing-y": i,
+                  "@defaults border-spacing": {},
+                  "border-spacing": "var(--tw-border-spacing-x) var(--tw-border-spacing-y)",
+                }),
+                "border-spacing-x": i => ({
+                  "--tw-border-spacing-x": i,
+                  "@defaults border-spacing": {},
+                  "border-spacing": "var(--tw-border-spacing-x) var(--tw-border-spacing-y)",
+                }),
+                "border-spacing-y": i => ({
+                  "--tw-border-spacing-y": i,
+                  "@defaults border-spacing": {},
+                  "border-spacing": "var(--tw-border-spacing-x) var(--tw-border-spacing-y)",
+                }),
+              }, { values: t("borderSpacing") });
+          },
+          transformOrigin: T("transformOrigin", [["origin", ["transformOrigin"]]]),
+          translate: T("translate", [[["translate-x", [["@defaults transform", {}], "--tw-translate-x", [
+            "transform",
+            Te,
+          ]]], ["translate-y", [["@defaults transform", {}], "--tw-translate-y", ["transform", Te]]]]], {
+            supportsNegativeValues: !0,
+          }),
+          rotate: T("rotate", [["rotate", [["@defaults transform", {}], "--tw-rotate", ["transform", Te]]]], {
+            supportsNegativeValues: !0,
+          }),
+          skew: T("skew", [[["skew-x", [["@defaults transform", {}], "--tw-skew-x", ["transform", Te]]], ["skew-y", [
+            ["@defaults transform", {}],
+            "--tw-skew-y",
+            ["transform", Te],
+          ]]]], { supportsNegativeValues: !0 }),
+          scale: T("scale", [["scale", [["@defaults transform", {}], "--tw-scale-x", "--tw-scale-y", [
+            "transform",
+            Te,
+          ]]], [["scale-x", [["@defaults transform", {}], "--tw-scale-x", ["transform", Te]]], ["scale-y", [
+            ["@defaults transform", {}],
+            "--tw-scale-y",
+            ["transform", Te],
+          ]]]], { supportsNegativeValues: !0 }),
+          transform: ({ addDefaults: r, addUtilities: e }) => {
+            r("transform", {
+              "--tw-translate-x": "0",
+              "--tw-translate-y": "0",
+              "--tw-rotate": "0",
+              "--tw-skew-x": "0",
+              "--tw-skew-y": "0",
+              "--tw-scale-x": "1",
+              "--tw-scale-y": "1",
+            }),
+              e({
+                ".transform": { "@defaults transform": {}, transform: Te },
+                ".transform-cpu": { transform: Te },
+                ".transform-gpu": {
+                  transform: Te.replace(
+                    "translate(var(--tw-translate-x), var(--tw-translate-y))",
+                    "translate3d(var(--tw-translate-x), var(--tw-translate-y), 0)",
+                  ),
+                },
+                ".transform-none": { transform: "none" },
+              });
+          },
+          animation: ({ matchUtilities: r, theme: e, config: t }) => {
+            let i = s => `${t("prefix")}${ce(s)}`,
+              n = Object.fromEntries(
+                Object.entries(e("keyframes") ?? {}).map(([s, a]) => [s, { [`@keyframes ${i(s)}`]: a }]),
+              );
+            r({
+              animate: s => {
+                let a = La(s);
+                return [...a.flatMap(o => n[o.name]), {
+                  animation: a.map(({ name: o, value: u }) => o === void 0 || n[o] === void 0 ? u : u.replace(o, i(o)))
+                    .join(", "),
+                }];
+              },
+            }, { values: e("animation") });
+          },
+          cursor: T("cursor"),
+          touchAction: ({ addDefaults: r, addUtilities: e }) => {
+            r("touch-action", { "--tw-pan-x": " ", "--tw-pan-y": " ", "--tw-pinch-zoom": " " });
+            let t = "var(--tw-pan-x) var(--tw-pan-y) var(--tw-pinch-zoom)";
+            e({
+              ".touch-auto": { "touch-action": "auto" },
+              ".touch-none": { "touch-action": "none" },
+              ".touch-pan-x": { "@defaults touch-action": {}, "--tw-pan-x": "pan-x", "touch-action": t },
+              ".touch-pan-left": { "@defaults touch-action": {}, "--tw-pan-x": "pan-left", "touch-action": t },
+              ".touch-pan-right": { "@defaults touch-action": {}, "--tw-pan-x": "pan-right", "touch-action": t },
+              ".touch-pan-y": { "@defaults touch-action": {}, "--tw-pan-y": "pan-y", "touch-action": t },
+              ".touch-pan-up": { "@defaults touch-action": {}, "--tw-pan-y": "pan-up", "touch-action": t },
+              ".touch-pan-down": { "@defaults touch-action": {}, "--tw-pan-y": "pan-down", "touch-action": t },
+              ".touch-pinch-zoom": { "@defaults touch-action": {}, "--tw-pinch-zoom": "pinch-zoom", "touch-action": t },
+              ".touch-manipulation": { "touch-action": "manipulation" },
+            });
+          },
+          userSelect: ({ addUtilities: r }) => {
+            r({
+              ".select-none": { "user-select": "none" },
+              ".select-text": { "user-select": "text" },
+              ".select-all": { "user-select": "all" },
+              ".select-auto": { "user-select": "auto" },
+            });
+          },
+          resize: ({ addUtilities: r }) => {
+            r({
+              ".resize-none": { resize: "none" },
+              ".resize-y": { resize: "vertical" },
+              ".resize-x": { resize: "horizontal" },
+              ".resize": { resize: "both" },
+            });
+          },
+          scrollSnapType: ({ addDefaults: r, addUtilities: e }) => {
+            r("scroll-snap-type", { "--tw-scroll-snap-strictness": "proximity" }),
+              e({
+                ".snap-none": { "scroll-snap-type": "none" },
+                ".snap-x": {
+                  "@defaults scroll-snap-type": {},
+                  "scroll-snap-type": "x var(--tw-scroll-snap-strictness)",
+                },
+                ".snap-y": {
+                  "@defaults scroll-snap-type": {},
+                  "scroll-snap-type": "y var(--tw-scroll-snap-strictness)",
+                },
+                ".snap-both": {
+                  "@defaults scroll-snap-type": {},
+                  "scroll-snap-type": "both var(--tw-scroll-snap-strictness)",
+                },
+                ".snap-mandatory": { "--tw-scroll-snap-strictness": "mandatory" },
+                ".snap-proximity": { "--tw-scroll-snap-strictness": "proximity" },
+              });
+          },
+          scrollSnapAlign: ({ addUtilities: r }) => {
+            r({
+              ".snap-start": { "scroll-snap-align": "start" },
+              ".snap-end": { "scroll-snap-align": "end" },
+              ".snap-center": { "scroll-snap-align": "center" },
+              ".snap-align-none": { "scroll-snap-align": "none" },
+            });
+          },
+          scrollSnapStop: ({ addUtilities: r }) => {
+            r({ ".snap-normal": { "scroll-snap-stop": "normal" }, ".snap-always": { "scroll-snap-stop": "always" } });
+          },
+          scrollMargin: T("scrollMargin", [["scroll-m", ["scroll-margin"]], [["scroll-mx", [
+            "scroll-margin-left",
+            "scroll-margin-right",
+          ]], ["scroll-my", ["scroll-margin-top", "scroll-margin-bottom"]]], [
+            ["scroll-ms", ["scroll-margin-inline-start"]],
+            ["scroll-me", ["scroll-margin-inline-end"]],
+            ["scroll-mt", ["scroll-margin-top"]],
+            ["scroll-mr", ["scroll-margin-right"]],
+            ["scroll-mb", ["scroll-margin-bottom"]],
+            ["scroll-ml", ["scroll-margin-left"]],
+          ]], { supportsNegativeValues: !0 }),
+          scrollPadding: T("scrollPadding", [["scroll-p", ["scroll-padding"]], [["scroll-px", [
+            "scroll-padding-left",
+            "scroll-padding-right",
+          ]], ["scroll-py", ["scroll-padding-top", "scroll-padding-bottom"]]], [
+            ["scroll-ps", ["scroll-padding-inline-start"]],
+            ["scroll-pe", ["scroll-padding-inline-end"]],
+            ["scroll-pt", ["scroll-padding-top"]],
+            ["scroll-pr", ["scroll-padding-right"]],
+            ["scroll-pb", ["scroll-padding-bottom"]],
+            ["scroll-pl", ["scroll-padding-left"]],
+          ]]),
+          listStylePosition: ({ addUtilities: r }) => {
+            r({
+              ".list-inside": { "list-style-position": "inside" },
+              ".list-outside": { "list-style-position": "outside" },
+            });
+          },
+          listStyleType: T("listStyleType", [["list", ["listStyleType"]]]),
+          listStyleImage: T("listStyleImage", [["list-image", ["listStyleImage"]]]),
+          appearance: ({ addUtilities: r }) => {
+            r({ ".appearance-none": { appearance: "none" } });
+          },
+          columns: T("columns", [["columns", ["columns"]]]),
+          breakBefore: ({ addUtilities: r }) => {
+            r({
+              ".break-before-auto": { "break-before": "auto" },
+              ".break-before-avoid": { "break-before": "avoid" },
+              ".break-before-all": { "break-before": "all" },
+              ".break-before-avoid-page": { "break-before": "avoid-page" },
+              ".break-before-page": { "break-before": "page" },
+              ".break-before-left": { "break-before": "left" },
+              ".break-before-right": { "break-before": "right" },
+              ".break-before-column": { "break-before": "column" },
+            });
+          },
+          breakInside: ({ addUtilities: r }) => {
+            r({
+              ".break-inside-auto": { "break-inside": "auto" },
+              ".break-inside-avoid": { "break-inside": "avoid" },
+              ".break-inside-avoid-page": { "break-inside": "avoid-page" },
+              ".break-inside-avoid-column": { "break-inside": "avoid-column" },
+            });
+          },
+          breakAfter: ({ addUtilities: r }) => {
+            r({
+              ".break-after-auto": { "break-after": "auto" },
+              ".break-after-avoid": { "break-after": "avoid" },
+              ".break-after-all": { "break-after": "all" },
+              ".break-after-avoid-page": { "break-after": "avoid-page" },
+              ".break-after-page": { "break-after": "page" },
+              ".break-after-left": { "break-after": "left" },
+              ".break-after-right": { "break-after": "right" },
+              ".break-after-column": { "break-after": "column" },
+            });
+          },
+          gridAutoColumns: T("gridAutoColumns", [["auto-cols", ["gridAutoColumns"]]]),
+          gridAutoFlow: ({ addUtilities: r }) => {
+            r({
+              ".grid-flow-row": { gridAutoFlow: "row" },
+              ".grid-flow-col": { gridAutoFlow: "column" },
+              ".grid-flow-dense": { gridAutoFlow: "dense" },
+              ".grid-flow-row-dense": { gridAutoFlow: "row dense" },
+              ".grid-flow-col-dense": { gridAutoFlow: "column dense" },
+            });
+          },
+          gridAutoRows: T("gridAutoRows", [["auto-rows", ["gridAutoRows"]]]),
+          gridTemplateColumns: T("gridTemplateColumns", [["grid-cols", ["gridTemplateColumns"]]]),
+          gridTemplateRows: T("gridTemplateRows", [["grid-rows", ["gridTemplateRows"]]]),
+          flexDirection: ({ addUtilities: r }) => {
+            r({
+              ".flex-row": { "flex-direction": "row" },
+              ".flex-row-reverse": { "flex-direction": "row-reverse" },
+              ".flex-col": { "flex-direction": "column" },
+              ".flex-col-reverse": { "flex-direction": "column-reverse" },
+            });
+          },
+          flexWrap: ({ addUtilities: r }) => {
+            r({
+              ".flex-wrap": { "flex-wrap": "wrap" },
+              ".flex-wrap-reverse": { "flex-wrap": "wrap-reverse" },
+              ".flex-nowrap": { "flex-wrap": "nowrap" },
+            });
+          },
+          placeContent: ({ addUtilities: r }) => {
+            r({
+              ".place-content-center": { "place-content": "center" },
+              ".place-content-start": { "place-content": "start" },
+              ".place-content-end": { "place-content": "end" },
+              ".place-content-between": { "place-content": "space-between" },
+              ".place-content-around": { "place-content": "space-around" },
+              ".place-content-evenly": { "place-content": "space-evenly" },
+              ".place-content-baseline": { "place-content": "baseline" },
+              ".place-content-stretch": { "place-content": "stretch" },
+            });
+          },
+          placeItems: ({ addUtilities: r }) => {
+            r({
+              ".place-items-start": { "place-items": "start" },
+              ".place-items-end": { "place-items": "end" },
+              ".place-items-center": { "place-items": "center" },
+              ".place-items-baseline": { "place-items": "baseline" },
+              ".place-items-stretch": { "place-items": "stretch" },
+            });
+          },
+          alignContent: ({ addUtilities: r }) => {
+            r({
+              ".content-normal": { "align-content": "normal" },
+              ".content-center": { "align-content": "center" },
+              ".content-start": { "align-content": "flex-start" },
+              ".content-end": { "align-content": "flex-end" },
+              ".content-between": { "align-content": "space-between" },
+              ".content-around": { "align-content": "space-around" },
+              ".content-evenly": { "align-content": "space-evenly" },
+              ".content-baseline": { "align-content": "baseline" },
+              ".content-stretch": { "align-content": "stretch" },
+            });
+          },
+          alignItems: ({ addUtilities: r }) => {
+            r({
+              ".items-start": { "align-items": "flex-start" },
+              ".items-end": { "align-items": "flex-end" },
+              ".items-center": { "align-items": "center" },
+              ".items-baseline": { "align-items": "baseline" },
+              ".items-stretch": { "align-items": "stretch" },
+            });
+          },
+          justifyContent: ({ addUtilities: r }) => {
+            r({
+              ".justify-normal": { "justify-content": "normal" },
+              ".justify-start": { "justify-content": "flex-start" },
+              ".justify-end": { "justify-content": "flex-end" },
+              ".justify-center": { "justify-content": "center" },
+              ".justify-between": { "justify-content": "space-between" },
+              ".justify-around": { "justify-content": "space-around" },
+              ".justify-evenly": { "justify-content": "space-evenly" },
+              ".justify-stretch": { "justify-content": "stretch" },
+            });
+          },
+          justifyItems: ({ addUtilities: r }) => {
+            r({
+              ".justify-items-start": { "justify-items": "start" },
+              ".justify-items-end": { "justify-items": "end" },
+              ".justify-items-center": { "justify-items": "center" },
+              ".justify-items-stretch": { "justify-items": "stretch" },
+            });
+          },
+          gap: T("gap", [["gap", ["gap"]], [["gap-x", ["columnGap"]], ["gap-y", ["rowGap"]]]]),
+          space: ({ matchUtilities: r, addUtilities: e, theme: t }) => {
+            r({
+              "space-x": i => (i = i === "0" ? "0px" : i, {
+                "& > :not([hidden]) ~ :not([hidden])": {
+                  "--tw-space-x-reverse": "0",
+                  "margin-right": `calc(${i} * var(--tw-space-x-reverse))`,
+                  "margin-left": `calc(${i} * calc(1 - var(--tw-space-x-reverse)))`,
+                },
+              }),
+              "space-y": i => (i = i === "0" ? "0px" : i, {
+                "& > :not([hidden]) ~ :not([hidden])": {
+                  "--tw-space-y-reverse": "0",
+                  "margin-top": `calc(${i} * calc(1 - var(--tw-space-y-reverse)))`,
+                  "margin-bottom": `calc(${i} * var(--tw-space-y-reverse))`,
+                },
+              }),
+            }, { values: t("space"), supportsNegativeValues: !0 }),
+              e({
+                ".space-y-reverse > :not([hidden]) ~ :not([hidden])": { "--tw-space-y-reverse": "1" },
+                ".space-x-reverse > :not([hidden]) ~ :not([hidden])": { "--tw-space-x-reverse": "1" },
+              });
+          },
+          divideWidth: ({ matchUtilities: r, addUtilities: e, theme: t }) => {
+            r({
+              "divide-x": i => (i = i === "0" ? "0px" : i, {
+                "& > :not([hidden]) ~ :not([hidden])": {
+                  "@defaults border-width": {},
+                  "--tw-divide-x-reverse": "0",
+                  "border-right-width": `calc(${i} * var(--tw-divide-x-reverse))`,
+                  "border-left-width": `calc(${i} * calc(1 - var(--tw-divide-x-reverse)))`,
+                },
+              }),
+              "divide-y": i => (i = i === "0" ? "0px" : i, {
+                "& > :not([hidden]) ~ :not([hidden])": {
+                  "@defaults border-width": {},
+                  "--tw-divide-y-reverse": "0",
+                  "border-top-width": `calc(${i} * calc(1 - var(--tw-divide-y-reverse)))`,
+                  "border-bottom-width": `calc(${i} * var(--tw-divide-y-reverse))`,
+                },
+              }),
+            }, { values: t("divideWidth"), type: ["line-width", "length", "any"] }),
+              e({
+                ".divide-y-reverse > :not([hidden]) ~ :not([hidden])": {
+                  "@defaults border-width": {},
+                  "--tw-divide-y-reverse": "1",
+                },
+                ".divide-x-reverse > :not([hidden]) ~ :not([hidden])": {
+                  "@defaults border-width": {},
+                  "--tw-divide-x-reverse": "1",
+                },
+              });
+          },
+          divideStyle: ({ addUtilities: r }) => {
+            r({
+              ".divide-solid > :not([hidden]) ~ :not([hidden])": { "border-style": "solid" },
+              ".divide-dashed > :not([hidden]) ~ :not([hidden])": { "border-style": "dashed" },
+              ".divide-dotted > :not([hidden]) ~ :not([hidden])": { "border-style": "dotted" },
+              ".divide-double > :not([hidden]) ~ :not([hidden])": { "border-style": "double" },
+              ".divide-none > :not([hidden]) ~ :not([hidden])": { "border-style": "none" },
+            });
+          },
+          divideColor: ({ matchUtilities: r, theme: e, corePlugins: t }) => {
+            r({
+              divide: i =>
+                t("divideOpacity")
+                  ? {
+                    ["& > :not([hidden]) ~ :not([hidden])"]: oe({
+                      color: i,
+                      property: "border-color",
+                      variable: "--tw-divide-opacity",
+                    }),
+                  }
+                  : { ["& > :not([hidden]) ~ :not([hidden])"]: { "border-color": L(i) } },
+            }, { values: (({ DEFAULT: i, ...n }) => n)(ne(e("divideColor"))), type: ["color", "any"] });
+          },
+          divideOpacity: ({ matchUtilities: r, theme: e }) => {
+            r({ "divide-opacity": t => ({ ["& > :not([hidden]) ~ :not([hidden])"]: { "--tw-divide-opacity": t } }) }, {
+              values: e("divideOpacity"),
+            });
+          },
+          placeSelf: ({ addUtilities: r }) => {
+            r({
+              ".place-self-auto": { "place-self": "auto" },
+              ".place-self-start": { "place-self": "start" },
+              ".place-self-end": { "place-self": "end" },
+              ".place-self-center": { "place-self": "center" },
+              ".place-self-stretch": { "place-self": "stretch" },
+            });
+          },
+          alignSelf: ({ addUtilities: r }) => {
+            r({
+              ".self-auto": { "align-self": "auto" },
+              ".self-start": { "align-self": "flex-start" },
+              ".self-end": { "align-self": "flex-end" },
+              ".self-center": { "align-self": "center" },
+              ".self-stretch": { "align-self": "stretch" },
+              ".self-baseline": { "align-self": "baseline" },
+            });
+          },
+          justifySelf: ({ addUtilities: r }) => {
+            r({
+              ".justify-self-auto": { "justify-self": "auto" },
+              ".justify-self-start": { "justify-self": "start" },
+              ".justify-self-end": { "justify-self": "end" },
+              ".justify-self-center": { "justify-self": "center" },
+              ".justify-self-stretch": { "justify-self": "stretch" },
+            });
+          },
+          overflow: ({ addUtilities: r }) => {
+            r({
+              ".overflow-auto": { overflow: "auto" },
+              ".overflow-hidden": { overflow: "hidden" },
+              ".overflow-clip": { overflow: "clip" },
+              ".overflow-visible": { overflow: "visible" },
+              ".overflow-scroll": { overflow: "scroll" },
+              ".overflow-x-auto": { "overflow-x": "auto" },
+              ".overflow-y-auto": { "overflow-y": "auto" },
+              ".overflow-x-hidden": { "overflow-x": "hidden" },
+              ".overflow-y-hidden": { "overflow-y": "hidden" },
+              ".overflow-x-clip": { "overflow-x": "clip" },
+              ".overflow-y-clip": { "overflow-y": "clip" },
+              ".overflow-x-visible": { "overflow-x": "visible" },
+              ".overflow-y-visible": { "overflow-y": "visible" },
+              ".overflow-x-scroll": { "overflow-x": "scroll" },
+              ".overflow-y-scroll": { "overflow-y": "scroll" },
+            });
+          },
+          overscrollBehavior: ({ addUtilities: r }) => {
+            r({
+              ".overscroll-auto": { "overscroll-behavior": "auto" },
+              ".overscroll-contain": { "overscroll-behavior": "contain" },
+              ".overscroll-none": { "overscroll-behavior": "none" },
+              ".overscroll-y-auto": { "overscroll-behavior-y": "auto" },
+              ".overscroll-y-contain": { "overscroll-behavior-y": "contain" },
+              ".overscroll-y-none": { "overscroll-behavior-y": "none" },
+              ".overscroll-x-auto": { "overscroll-behavior-x": "auto" },
+              ".overscroll-x-contain": { "overscroll-behavior-x": "contain" },
+              ".overscroll-x-none": { "overscroll-behavior-x": "none" },
+            });
+          },
+          scrollBehavior: ({ addUtilities: r }) => {
+            r({ ".scroll-auto": { "scroll-behavior": "auto" }, ".scroll-smooth": { "scroll-behavior": "smooth" } });
+          },
+          textOverflow: ({ addUtilities: r }) => {
+            r({
+              ".truncate": { overflow: "hidden", "text-overflow": "ellipsis", "white-space": "nowrap" },
+              ".overflow-ellipsis": { "text-overflow": "ellipsis" },
+              ".text-ellipsis": { "text-overflow": "ellipsis" },
+              ".text-clip": { "text-overflow": "clip" },
+            });
+          },
+          hyphens: ({ addUtilities: r }) => {
+            r({
+              ".hyphens-none": { hyphens: "none" },
+              ".hyphens-manual": { hyphens: "manual" },
+              ".hyphens-auto": { hyphens: "auto" },
+            });
+          },
+          whitespace: ({ addUtilities: r }) => {
+            r({
+              ".whitespace-normal": { "white-space": "normal" },
+              ".whitespace-nowrap": { "white-space": "nowrap" },
+              ".whitespace-pre": { "white-space": "pre" },
+              ".whitespace-pre-line": { "white-space": "pre-line" },
+              ".whitespace-pre-wrap": { "white-space": "pre-wrap" },
+              ".whitespace-break-spaces": { "white-space": "break-spaces" },
+            });
+          },
+          wordBreak: ({ addUtilities: r }) => {
+            r({
+              ".break-normal": { "overflow-wrap": "normal", "word-break": "normal" },
+              ".break-words": { "overflow-wrap": "break-word" },
+              ".break-all": { "word-break": "break-all" },
+              ".break-keep": { "word-break": "keep-all" },
+            });
+          },
+          borderRadius: T("borderRadius", [["rounded", ["border-radius"]], [
+            ["rounded-s", ["border-start-start-radius", "border-end-start-radius"]],
+            ["rounded-e", ["border-start-end-radius", "border-end-end-radius"]],
+            ["rounded-t", ["border-top-left-radius", "border-top-right-radius"]],
+            ["rounded-r", ["border-top-right-radius", "border-bottom-right-radius"]],
+            ["rounded-b", ["border-bottom-right-radius", "border-bottom-left-radius"]],
+            ["rounded-l", ["border-top-left-radius", "border-bottom-left-radius"]],
+          ], [
+            ["rounded-ss", ["border-start-start-radius"]],
+            ["rounded-se", ["border-start-end-radius"]],
+            ["rounded-ee", ["border-end-end-radius"]],
+            ["rounded-es", ["border-end-start-radius"]],
+            ["rounded-tl", ["border-top-left-radius"]],
+            ["rounded-tr", ["border-top-right-radius"]],
+            ["rounded-br", ["border-bottom-right-radius"]],
+            ["rounded-bl", ["border-bottom-left-radius"]],
+          ]]),
+          borderWidth: T("borderWidth", [["border", [["@defaults border-width", {}], "border-width"]], [["border-x", [
+            ["@defaults border-width", {}],
+            "border-left-width",
+            "border-right-width",
+          ]], ["border-y", [["@defaults border-width", {}], "border-top-width", "border-bottom-width"]]], [
+            ["border-s", [["@defaults border-width", {}], "border-inline-start-width"]],
+            ["border-e", [["@defaults border-width", {}], "border-inline-end-width"]],
+            ["border-t", [["@defaults border-width", {}], "border-top-width"]],
+            ["border-r", [["@defaults border-width", {}], "border-right-width"]],
+            ["border-b", [["@defaults border-width", {}], "border-bottom-width"]],
+            ["border-l", [["@defaults border-width", {}], "border-left-width"]],
+          ]], { type: ["line-width", "length"] }),
+          borderStyle: ({ addUtilities: r }) => {
+            r({
+              ".border-solid": { "border-style": "solid" },
+              ".border-dashed": { "border-style": "dashed" },
+              ".border-dotted": { "border-style": "dotted" },
+              ".border-double": { "border-style": "double" },
+              ".border-hidden": { "border-style": "hidden" },
+              ".border-none": { "border-style": "none" },
+            });
+          },
+          borderColor: ({ matchUtilities: r, theme: e, corePlugins: t }) => {
+            r({
+              border: i =>
+                t("borderOpacity")
+                  ? oe({ color: i, property: "border-color", variable: "--tw-border-opacity" })
+                  : { "border-color": L(i) },
+            }, { values: (({ DEFAULT: i, ...n }) => n)(ne(e("borderColor"))), type: ["color", "any"] }),
+              r({
+                "border-x": i =>
+                  t("borderOpacity")
+                    ? oe({
+                      color: i,
+                      property: ["border-left-color", "border-right-color"],
+                      variable: "--tw-border-opacity",
+                    })
+                    : { "border-left-color": L(i), "border-right-color": L(i) },
+                "border-y": i =>
+                  t("borderOpacity")
+                    ? oe({
+                      color: i,
+                      property: ["border-top-color", "border-bottom-color"],
+                      variable: "--tw-border-opacity",
+                    })
+                    : { "border-top-color": L(i), "border-bottom-color": L(i) },
+              }, { values: (({ DEFAULT: i, ...n }) => n)(ne(e("borderColor"))), type: ["color", "any"] }),
+              r({
+                "border-s": i =>
+                  t("borderOpacity")
+                    ? oe({ color: i, property: "border-inline-start-color", variable: "--tw-border-opacity" })
+                    : { "border-inline-start-color": L(i) },
+                "border-e": i =>
+                  t("borderOpacity")
+                    ? oe({ color: i, property: "border-inline-end-color", variable: "--tw-border-opacity" })
+                    : { "border-inline-end-color": L(i) },
+                "border-t": i =>
+                  t("borderOpacity")
+                    ? oe({ color: i, property: "border-top-color", variable: "--tw-border-opacity" })
+                    : { "border-top-color": L(i) },
+                "border-r": i =>
+                  t("borderOpacity")
+                    ? oe({ color: i, property: "border-right-color", variable: "--tw-border-opacity" })
+                    : { "border-right-color": L(i) },
+                "border-b": i =>
+                  t("borderOpacity")
+                    ? oe({ color: i, property: "border-bottom-color", variable: "--tw-border-opacity" })
+                    : { "border-bottom-color": L(i) },
+                "border-l": i =>
+                  t("borderOpacity")
+                    ? oe({ color: i, property: "border-left-color", variable: "--tw-border-opacity" })
+                    : { "border-left-color": L(i) },
+              }, { values: (({ DEFAULT: i, ...n }) => n)(ne(e("borderColor"))), type: ["color", "any"] });
+          },
+          borderOpacity: T("borderOpacity", [["border-opacity", ["--tw-border-opacity"]]]),
+          backgroundColor: ({ matchUtilities: r, theme: e, corePlugins: t }) => {
+            r({
+              bg: i =>
+                t("backgroundOpacity")
+                  ? oe({ color: i, property: "background-color", variable: "--tw-bg-opacity" })
+                  : { "background-color": L(i) },
+            }, { values: ne(e("backgroundColor")), type: ["color", "any"] });
+          },
+          backgroundOpacity: T("backgroundOpacity", [["bg-opacity", ["--tw-bg-opacity"]]]),
+          backgroundImage: T("backgroundImage", [["bg", ["background-image"]]], { type: ["lookup", "image", "url"] }),
+          gradientColorStops: (() => {
+            function r(e) {
+              return Ie(e, 0, "rgb(255 255 255 / 0)");
+            }
+            return function({ matchUtilities: e, theme: t, addDefaults: i }) {
+              i("gradient-color-stops", {
+                "--tw-gradient-from-position": " ",
+                "--tw-gradient-via-position": " ",
+                "--tw-gradient-to-position": " ",
+              });
+              let n = { values: ne(t("gradientColorStops")), type: ["color", "any"] },
+                s = { values: t("gradientColorStopPositions"), type: ["length", "percentage"] };
+              e({
+                from: a => {
+                  let o = r(a);
+                  return {
+                    "@defaults gradient-color-stops": {},
+                    "--tw-gradient-from": `${L(a)} var(--tw-gradient-from-position)`,
+                    "--tw-gradient-to": `${o} var(--tw-gradient-to-position)`,
+                    "--tw-gradient-stops": "var(--tw-gradient-from), var(--tw-gradient-to)",
+                  };
+                },
+              }, n),
+                e({ from: a => ({ "--tw-gradient-from-position": a }) }, s),
+                e({
+                  via: a => {
+                    let o = r(a);
+                    return {
+                      "@defaults gradient-color-stops": {},
+                      "--tw-gradient-to": `${o}  var(--tw-gradient-to-position)`,
+                      "--tw-gradient-stops": `var(--tw-gradient-from), ${
+                        L(a)
+                      } var(--tw-gradient-via-position), var(--tw-gradient-to)`,
+                    };
+                  },
+                }, n),
+                e({ via: a => ({ "--tw-gradient-via-position": a }) }, s),
+                e({
+                  to: a => ({
+                    "@defaults gradient-color-stops": {},
+                    "--tw-gradient-to": `${L(a)} var(--tw-gradient-to-position)`,
+                  }),
+                }, n),
+                e({ to: a => ({ "--tw-gradient-to-position": a }) }, s);
+            };
+          })(),
+          boxDecorationBreak: ({ addUtilities: r }) => {
+            r({
+              ".decoration-slice": { "box-decoration-break": "slice" },
+              ".decoration-clone": { "box-decoration-break": "clone" },
+              ".box-decoration-slice": { "box-decoration-break": "slice" },
+              ".box-decoration-clone": { "box-decoration-break": "clone" },
+            });
+          },
+          backgroundSize: T("backgroundSize", [["bg", ["background-size"]]], {
+            type: ["lookup", "length", "percentage", "size"],
+          }),
+          backgroundAttachment: ({ addUtilities: r }) => {
+            r({
+              ".bg-fixed": { "background-attachment": "fixed" },
+              ".bg-local": { "background-attachment": "local" },
+              ".bg-scroll": { "background-attachment": "scroll" },
+            });
+          },
+          backgroundClip: ({ addUtilities: r }) => {
+            r({
+              ".bg-clip-border": { "background-clip": "border-box" },
+              ".bg-clip-padding": { "background-clip": "padding-box" },
+              ".bg-clip-content": { "background-clip": "content-box" },
+              ".bg-clip-text": { "background-clip": "text" },
+            });
+          },
+          backgroundPosition: T("backgroundPosition", [["bg", ["background-position"]]], {
+            type: ["lookup", ["position", { preferOnConflict: !0 }]],
+          }),
+          backgroundRepeat: ({ addUtilities: r }) => {
+            r({
+              ".bg-repeat": { "background-repeat": "repeat" },
+              ".bg-no-repeat": { "background-repeat": "no-repeat" },
+              ".bg-repeat-x": { "background-repeat": "repeat-x" },
+              ".bg-repeat-y": { "background-repeat": "repeat-y" },
+              ".bg-repeat-round": { "background-repeat": "round" },
+              ".bg-repeat-space": { "background-repeat": "space" },
+            });
+          },
+          backgroundOrigin: ({ addUtilities: r }) => {
+            r({
+              ".bg-origin-border": { "background-origin": "border-box" },
+              ".bg-origin-padding": { "background-origin": "padding-box" },
+              ".bg-origin-content": { "background-origin": "content-box" },
+            });
+          },
+          fill: ({ matchUtilities: r, theme: e }) => {
+            r({ fill: t => ({ fill: L(t) }) }, { values: ne(e("fill")), type: ["color", "any"] });
+          },
+          stroke: ({ matchUtilities: r, theme: e }) => {
+            r({ stroke: t => ({ stroke: L(t) }) }, { values: ne(e("stroke")), type: ["color", "url", "any"] });
+          },
+          strokeWidth: T("strokeWidth", [["stroke", ["stroke-width"]]], { type: ["length", "number", "percentage"] }),
+          objectFit: ({ addUtilities: r }) => {
+            r({
+              ".object-contain": { "object-fit": "contain" },
+              ".object-cover": { "object-fit": "cover" },
+              ".object-fill": { "object-fit": "fill" },
+              ".object-none": { "object-fit": "none" },
+              ".object-scale-down": { "object-fit": "scale-down" },
+            });
+          },
+          objectPosition: T("objectPosition", [["object", ["object-position"]]]),
+          padding: T("padding", [["p", ["padding"]], [["px", ["padding-left", "padding-right"]], ["py", [
+            "padding-top",
+            "padding-bottom",
+          ]]], [
+            ["ps", ["padding-inline-start"]],
+            ["pe", ["padding-inline-end"]],
+            ["pt", ["padding-top"]],
+            ["pr", ["padding-right"]],
+            ["pb", ["padding-bottom"]],
+            ["pl", ["padding-left"]],
+          ]]),
+          textAlign: ({ addUtilities: r }) => {
+            r({
+              ".text-left": { "text-align": "left" },
+              ".text-center": { "text-align": "center" },
+              ".text-right": { "text-align": "right" },
+              ".text-justify": { "text-align": "justify" },
+              ".text-start": { "text-align": "start" },
+              ".text-end": { "text-align": "end" },
+            });
+          },
+          textIndent: T("textIndent", [["indent", ["text-indent"]]], { supportsNegativeValues: !0 }),
+          verticalAlign: ({ addUtilities: r, matchUtilities: e }) => {
+            r({
+              ".align-baseline": { "vertical-align": "baseline" },
+              ".align-top": { "vertical-align": "top" },
+              ".align-middle": { "vertical-align": "middle" },
+              ".align-bottom": { "vertical-align": "bottom" },
+              ".align-text-top": { "vertical-align": "text-top" },
+              ".align-text-bottom": { "vertical-align": "text-bottom" },
+              ".align-sub": { "vertical-align": "sub" },
+              ".align-super": { "vertical-align": "super" },
+            }), e({ align: t => ({ "vertical-align": t }) });
+          },
+          fontFamily: ({ matchUtilities: r, theme: e }) => {
+            r({
+              font: t => {
+                let [i, n = {}] = Array.isArray(t) && se(t[1]) ? t : [t],
+                  { fontFeatureSettings: s, fontVariationSettings: a } = n;
+                return {
+                  "font-family": Array.isArray(i) ? i.join(", ") : i,
+                  ...s === void 0 ? {} : { "font-feature-settings": s },
+                  ...a === void 0 ? {} : { "font-variation-settings": a },
+                };
+              },
+            }, { values: e("fontFamily"), type: ["lookup", "generic-name", "family-name"] });
+          },
+          fontSize: ({ matchUtilities: r, theme: e }) => {
+            r({
+              text: (t, { modifier: i }) => {
+                let [n, s] = Array.isArray(t) ? t : [t];
+                if (i) return { "font-size": n, "line-height": i };
+                let { lineHeight: a, letterSpacing: o, fontWeight: u } = se(s) ? s : { lineHeight: s };
+                return {
+                  "font-size": n,
+                  ...a === void 0 ? {} : { "line-height": a },
+                  ...o === void 0 ? {} : { "letter-spacing": o },
+                  ...u === void 0 ? {} : { "font-weight": u },
+                };
+              },
+            }, {
+              values: e("fontSize"),
+              modifiers: e("lineHeight"),
+              type: ["absolute-size", "relative-size", "length", "percentage"],
+            });
+          },
+          fontWeight: T("fontWeight", [["font", ["fontWeight"]]], { type: ["lookup", "number", "any"] }),
+          textTransform: ({ addUtilities: r }) => {
+            r({
+              ".uppercase": { "text-transform": "uppercase" },
+              ".lowercase": { "text-transform": "lowercase" },
+              ".capitalize": { "text-transform": "capitalize" },
+              ".normal-case": { "text-transform": "none" },
+            });
+          },
+          fontStyle: ({ addUtilities: r }) => {
+            r({ ".italic": { "font-style": "italic" }, ".not-italic": { "font-style": "normal" } });
+          },
+          fontVariantNumeric: ({ addDefaults: r, addUtilities: e }) => {
+            let t =
+              "var(--tw-ordinal) var(--tw-slashed-zero) var(--tw-numeric-figure) var(--tw-numeric-spacing) var(--tw-numeric-fraction)";
+            r("font-variant-numeric", {
+              "--tw-ordinal": " ",
+              "--tw-slashed-zero": " ",
+              "--tw-numeric-figure": " ",
+              "--tw-numeric-spacing": " ",
+              "--tw-numeric-fraction": " ",
+            }),
+              e({
+                ".normal-nums": { "font-variant-numeric": "normal" },
+                ".ordinal": {
+                  "@defaults font-variant-numeric": {},
+                  "--tw-ordinal": "ordinal",
+                  "font-variant-numeric": t,
+                },
+                ".slashed-zero": {
+                  "@defaults font-variant-numeric": {},
+                  "--tw-slashed-zero": "slashed-zero",
+                  "font-variant-numeric": t,
+                },
+                ".lining-nums": {
+                  "@defaults font-variant-numeric": {},
+                  "--tw-numeric-figure": "lining-nums",
+                  "font-variant-numeric": t,
+                },
+                ".oldstyle-nums": {
+                  "@defaults font-variant-numeric": {},
+                  "--tw-numeric-figure": "oldstyle-nums",
+                  "font-variant-numeric": t,
+                },
+                ".proportional-nums": {
+                  "@defaults font-variant-numeric": {},
+                  "--tw-numeric-spacing": "proportional-nums",
+                  "font-variant-numeric": t,
+                },
+                ".tabular-nums": {
+                  "@defaults font-variant-numeric": {},
+                  "--tw-numeric-spacing": "tabular-nums",
+                  "font-variant-numeric": t,
+                },
+                ".diagonal-fractions": {
+                  "@defaults font-variant-numeric": {},
+                  "--tw-numeric-fraction": "diagonal-fractions",
+                  "font-variant-numeric": t,
+                },
+                ".stacked-fractions": {
+                  "@defaults font-variant-numeric": {},
+                  "--tw-numeric-fraction": "stacked-fractions",
+                  "font-variant-numeric": t,
+                },
+              });
+          },
+          lineHeight: T("lineHeight", [["leading", ["lineHeight"]]]),
+          letterSpacing: T("letterSpacing", [["tracking", ["letterSpacing"]]], { supportsNegativeValues: !0 }),
+          textColor: ({ matchUtilities: r, theme: e, corePlugins: t }) => {
+            r({
+              text: i =>
+                t("textOpacity") ? oe({ color: i, property: "color", variable: "--tw-text-opacity" }) : { color: L(i) },
+            }, { values: ne(e("textColor")), type: ["color", "any"] });
+          },
+          textOpacity: T("textOpacity", [["text-opacity", ["--tw-text-opacity"]]]),
+          textDecoration: ({ addUtilities: r }) => {
+            r({
+              ".underline": { "text-decoration-line": "underline" },
+              ".overline": { "text-decoration-line": "overline" },
+              ".line-through": { "text-decoration-line": "line-through" },
+              ".no-underline": { "text-decoration-line": "none" },
+            });
+          },
+          textDecorationColor: ({ matchUtilities: r, theme: e }) => {
+            r({ decoration: t => ({ "text-decoration-color": L(t) }) }, {
+              values: ne(e("textDecorationColor")),
+              type: ["color", "any"],
+            });
+          },
+          textDecorationStyle: ({ addUtilities: r }) => {
+            r({
+              ".decoration-solid": { "text-decoration-style": "solid" },
+              ".decoration-double": { "text-decoration-style": "double" },
+              ".decoration-dotted": { "text-decoration-style": "dotted" },
+              ".decoration-dashed": { "text-decoration-style": "dashed" },
+              ".decoration-wavy": { "text-decoration-style": "wavy" },
+            });
+          },
+          textDecorationThickness: T("textDecorationThickness", [["decoration", ["text-decoration-thickness"]]], {
+            type: ["length", "percentage"],
+          }),
+          textUnderlineOffset: T("textUnderlineOffset", [["underline-offset", ["text-underline-offset"]]], {
+            type: ["length", "percentage", "any"],
+          }),
+          fontSmoothing: ({ addUtilities: r }) => {
+            r({
+              ".antialiased": { "-webkit-font-smoothing": "antialiased", "-moz-osx-font-smoothing": "grayscale" },
+              ".subpixel-antialiased": { "-webkit-font-smoothing": "auto", "-moz-osx-font-smoothing": "auto" },
+            });
+          },
+          placeholderColor: ({ matchUtilities: r, theme: e, corePlugins: t }) => {
+            r({
+              placeholder: i =>
+                t("placeholderOpacity")
+                  ? { "&::placeholder": oe({ color: i, property: "color", variable: "--tw-placeholder-opacity" }) }
+                  : { "&::placeholder": { color: L(i) } },
+            }, { values: ne(e("placeholderColor")), type: ["color", "any"] });
+          },
+          placeholderOpacity: ({ matchUtilities: r, theme: e }) => {
+            r({ "placeholder-opacity": t => ({ ["&::placeholder"]: { "--tw-placeholder-opacity": t } }) }, {
+              values: e("placeholderOpacity"),
+            });
+          },
+          caretColor: ({ matchUtilities: r, theme: e }) => {
+            r({ caret: t => ({ "caret-color": L(t) }) }, { values: ne(e("caretColor")), type: ["color", "any"] });
+          },
+          accentColor: ({ matchUtilities: r, theme: e }) => {
+            r({ accent: t => ({ "accent-color": L(t) }) }, { values: ne(e("accentColor")), type: ["color", "any"] });
+          },
+          opacity: T("opacity", [["opacity", ["opacity"]]]),
+          backgroundBlendMode: ({ addUtilities: r }) => {
+            r({
+              ".bg-blend-normal": { "background-blend-mode": "normal" },
+              ".bg-blend-multiply": { "background-blend-mode": "multiply" },
+              ".bg-blend-screen": { "background-blend-mode": "screen" },
+              ".bg-blend-overlay": { "background-blend-mode": "overlay" },
+              ".bg-blend-darken": { "background-blend-mode": "darken" },
+              ".bg-blend-lighten": { "background-blend-mode": "lighten" },
+              ".bg-blend-color-dodge": { "background-blend-mode": "color-dodge" },
+              ".bg-blend-color-burn": { "background-blend-mode": "color-burn" },
+              ".bg-blend-hard-light": { "background-blend-mode": "hard-light" },
+              ".bg-blend-soft-light": { "background-blend-mode": "soft-light" },
+              ".bg-blend-difference": { "background-blend-mode": "difference" },
+              ".bg-blend-exclusion": { "background-blend-mode": "exclusion" },
+              ".bg-blend-hue": { "background-blend-mode": "hue" },
+              ".bg-blend-saturation": { "background-blend-mode": "saturation" },
+              ".bg-blend-color": { "background-blend-mode": "color" },
+              ".bg-blend-luminosity": { "background-blend-mode": "luminosity" },
+            });
+          },
+          mixBlendMode: ({ addUtilities: r }) => {
+            r({
+              ".mix-blend-normal": { "mix-blend-mode": "normal" },
+              ".mix-blend-multiply": { "mix-blend-mode": "multiply" },
+              ".mix-blend-screen": { "mix-blend-mode": "screen" },
+              ".mix-blend-overlay": { "mix-blend-mode": "overlay" },
+              ".mix-blend-darken": { "mix-blend-mode": "darken" },
+              ".mix-blend-lighten": { "mix-blend-mode": "lighten" },
+              ".mix-blend-color-dodge": { "mix-blend-mode": "color-dodge" },
+              ".mix-blend-color-burn": { "mix-blend-mode": "color-burn" },
+              ".mix-blend-hard-light": { "mix-blend-mode": "hard-light" },
+              ".mix-blend-soft-light": { "mix-blend-mode": "soft-light" },
+              ".mix-blend-difference": { "mix-blend-mode": "difference" },
+              ".mix-blend-exclusion": { "mix-blend-mode": "exclusion" },
+              ".mix-blend-hue": { "mix-blend-mode": "hue" },
+              ".mix-blend-saturation": { "mix-blend-mode": "saturation" },
+              ".mix-blend-color": { "mix-blend-mode": "color" },
+              ".mix-blend-luminosity": { "mix-blend-mode": "luminosity" },
+              ".mix-blend-plus-lighter": { "mix-blend-mode": "plus-lighter" },
+            });
+          },
+          boxShadow: (() => {
+            let r = We("boxShadow"),
+              e = ["var(--tw-ring-offset-shadow, 0 0 #0000)", "var(--tw-ring-shadow, 0 0 #0000)", "var(--tw-shadow)"]
+                .join(", ");
+            return function({ matchUtilities: t, addDefaults: i, theme: n }) {
+              i(" box-shadow", {
+                "--tw-ring-offset-shadow": "0 0 #0000",
+                "--tw-ring-shadow": "0 0 #0000",
+                "--tw-shadow": "0 0 #0000",
+                "--tw-shadow-colored": "0 0 #0000",
+              }),
+                t({
+                  shadow: s => {
+                    s = r(s);
+                    let a = pi(s);
+                    for (let o of a) !o.valid || (o.color = "var(--tw-shadow-color)");
+                    return {
+                      "@defaults box-shadow": {},
+                      "--tw-shadow": s === "none" ? "0 0 #0000" : s,
+                      "--tw-shadow-colored": s === "none" ? "0 0 #0000" : gu(a),
+                      "box-shadow": e,
+                    };
+                  },
+                }, { values: n("boxShadow"), type: ["shadow"] });
+            };
+          })(),
+          boxShadowColor: ({ matchUtilities: r, theme: e }) => {
+            r({ shadow: t => ({ "--tw-shadow-color": L(t), "--tw-shadow": "var(--tw-shadow-colored)" }) }, {
+              values: ne(e("boxShadowColor")),
+              type: ["color", "any"],
+            });
+          },
+          outlineStyle: ({ addUtilities: r }) => {
+            r({
+              ".outline-none": { outline: "2px solid transparent", "outline-offset": "2px" },
+              ".outline": { "outline-style": "solid" },
+              ".outline-dashed": { "outline-style": "dashed" },
+              ".outline-dotted": { "outline-style": "dotted" },
+              ".outline-double": { "outline-style": "double" },
+            });
+          },
+          outlineWidth: T("outlineWidth", [["outline", ["outline-width"]]], {
+            type: ["length", "number", "percentage"],
+          }),
+          outlineOffset: T("outlineOffset", [["outline-offset", ["outline-offset"]]], {
+            type: ["length", "number", "percentage", "any"],
+            supportsNegativeValues: !0,
+          }),
+          outlineColor: ({ matchUtilities: r, theme: e }) => {
+            r({ outline: t => ({ "outline-color": L(t) }) }, { values: ne(e("outlineColor")), type: ["color", "any"] });
+          },
+          ringWidth: ({ matchUtilities: r, addDefaults: e, addUtilities: t, theme: i, config: n }) => {
+            let s = (() => {
+              if (J(n(), "respectDefaultRingColorOpacity")) return i("ringColor.DEFAULT");
+              let a = i("ringOpacity.DEFAULT", "0.5");
+              return i("ringColor")?.DEFAULT
+                ? Ie(i("ringColor")?.DEFAULT, a, `rgb(147 197 253 / ${a})`)
+                : `rgb(147 197 253 / ${a})`;
+            })();
+            e("ring-width", {
+              "--tw-ring-inset": " ",
+              "--tw-ring-offset-width": i("ringOffsetWidth.DEFAULT", "0px"),
+              "--tw-ring-offset-color": i("ringOffsetColor.DEFAULT", "#fff"),
+              "--tw-ring-color": s,
+              "--tw-ring-offset-shadow": "0 0 #0000",
+              "--tw-ring-shadow": "0 0 #0000",
+              "--tw-shadow": "0 0 #0000",
+              "--tw-shadow-colored": "0 0 #0000",
+            }),
+              r({
+                ring: a => ({
+                  "@defaults ring-width": {},
+                  "--tw-ring-offset-shadow":
+                    "var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color)",
+                  "--tw-ring-shadow":
+                    `var(--tw-ring-inset) 0 0 0 calc(${a} + var(--tw-ring-offset-width)) var(--tw-ring-color)`,
+                  "box-shadow": ["var(--tw-ring-offset-shadow)", "var(--tw-ring-shadow)", "var(--tw-shadow, 0 0 #0000)"]
+                    .join(", "),
+                }),
+              }, { values: i("ringWidth"), type: "length" }),
+              t({ ".ring-inset": { "@defaults ring-width": {}, "--tw-ring-inset": "inset" } });
+          },
+          ringColor: ({ matchUtilities: r, theme: e, corePlugins: t }) => {
+            r({
+              ring: i =>
+                t("ringOpacity")
+                  ? oe({ color: i, property: "--tw-ring-color", variable: "--tw-ring-opacity" })
+                  : { "--tw-ring-color": L(i) },
+            }, {
+              values: Object.fromEntries(Object.entries(ne(e("ringColor"))).filter(([i]) => i !== "DEFAULT")),
+              type: ["color", "any"],
+            });
+          },
+          ringOpacity: r => {
+            let { config: e } = r;
+            return T("ringOpacity", [["ring-opacity", ["--tw-ring-opacity"]]], {
+              filterDefault: !J(e(), "respectDefaultRingColorOpacity"),
+            })(r);
+          },
+          ringOffsetWidth: T("ringOffsetWidth", [["ring-offset", ["--tw-ring-offset-width"]]], { type: "length" }),
+          ringOffsetColor: ({ matchUtilities: r, theme: e }) => {
+            r({ "ring-offset": t => ({ "--tw-ring-offset-color": L(t) }) }, {
+              values: ne(e("ringOffsetColor")),
+              type: ["color", "any"],
+            });
+          },
+          blur: ({ matchUtilities: r, theme: e }) => {
+            r({ blur: t => ({ "--tw-blur": `blur(${t})`, "@defaults filter": {}, filter: Fe }) }, {
+              values: e("blur"),
+            });
+          },
+          brightness: ({ matchUtilities: r, theme: e }) => {
+            r({ brightness: t => ({ "--tw-brightness": `brightness(${t})`, "@defaults filter": {}, filter: Fe }) }, {
+              values: e("brightness"),
+            });
+          },
+          contrast: ({ matchUtilities: r, theme: e }) => {
+            r({ contrast: t => ({ "--tw-contrast": `contrast(${t})`, "@defaults filter": {}, filter: Fe }) }, {
+              values: e("contrast"),
+            });
+          },
+          dropShadow: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "drop-shadow": t => ({
+                "--tw-drop-shadow": Array.isArray(t)
+                  ? t.map(i => `drop-shadow(${i})`).join(" ")
+                  : `drop-shadow(${t})`,
+                "@defaults filter": {},
+                filter: Fe,
+              }),
+            }, { values: e("dropShadow") });
+          },
+          grayscale: ({ matchUtilities: r, theme: e }) => {
+            r({ grayscale: t => ({ "--tw-grayscale": `grayscale(${t})`, "@defaults filter": {}, filter: Fe }) }, {
+              values: e("grayscale"),
+            });
+          },
+          hueRotate: ({ matchUtilities: r, theme: e }) => {
+            r({ "hue-rotate": t => ({ "--tw-hue-rotate": `hue-rotate(${t})`, "@defaults filter": {}, filter: Fe }) }, {
+              values: e("hueRotate"),
+              supportsNegativeValues: !0,
+            });
+          },
+          invert: ({ matchUtilities: r, theme: e }) => {
+            r({ invert: t => ({ "--tw-invert": `invert(${t})`, "@defaults filter": {}, filter: Fe }) }, {
+              values: e("invert"),
+            });
+          },
+          saturate: ({ matchUtilities: r, theme: e }) => {
+            r({ saturate: t => ({ "--tw-saturate": `saturate(${t})`, "@defaults filter": {}, filter: Fe }) }, {
+              values: e("saturate"),
+            });
+          },
+          sepia: ({ matchUtilities: r, theme: e }) => {
+            r({ sepia: t => ({ "--tw-sepia": `sepia(${t})`, "@defaults filter": {}, filter: Fe }) }, {
+              values: e("sepia"),
+            });
+          },
+          filter: ({ addDefaults: r, addUtilities: e }) => {
+            r("filter", {
+              "--tw-blur": " ",
+              "--tw-brightness": " ",
+              "--tw-contrast": " ",
+              "--tw-grayscale": " ",
+              "--tw-hue-rotate": " ",
+              "--tw-invert": " ",
+              "--tw-saturate": " ",
+              "--tw-sepia": " ",
+              "--tw-drop-shadow": " ",
+            }), e({ ".filter": { "@defaults filter": {}, filter: Fe }, ".filter-none": { filter: "none" } });
+          },
+          backdropBlur: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "backdrop-blur": t => ({
+                "--tw-backdrop-blur": `blur(${t})`,
+                "@defaults backdrop-filter": {},
+                "backdrop-filter": Ne,
+              }),
+            }, { values: e("backdropBlur") });
+          },
+          backdropBrightness: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "backdrop-brightness": t => ({
+                "--tw-backdrop-brightness": `brightness(${t})`,
+                "@defaults backdrop-filter": {},
+                "backdrop-filter": Ne,
+              }),
+            }, { values: e("backdropBrightness") });
+          },
+          backdropContrast: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "backdrop-contrast": t => ({
+                "--tw-backdrop-contrast": `contrast(${t})`,
+                "@defaults backdrop-filter": {},
+                "backdrop-filter": Ne,
+              }),
+            }, { values: e("backdropContrast") });
+          },
+          backdropGrayscale: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "backdrop-grayscale": t => ({
+                "--tw-backdrop-grayscale": `grayscale(${t})`,
+                "@defaults backdrop-filter": {},
+                "backdrop-filter": Ne,
+              }),
+            }, { values: e("backdropGrayscale") });
+          },
+          backdropHueRotate: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "backdrop-hue-rotate": t => ({
+                "--tw-backdrop-hue-rotate": `hue-rotate(${t})`,
+                "@defaults backdrop-filter": {},
+                "backdrop-filter": Ne,
+              }),
+            }, { values: e("backdropHueRotate"), supportsNegativeValues: !0 });
+          },
+          backdropInvert: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "backdrop-invert": t => ({
+                "--tw-backdrop-invert": `invert(${t})`,
+                "@defaults backdrop-filter": {},
+                "backdrop-filter": Ne,
+              }),
+            }, { values: e("backdropInvert") });
+          },
+          backdropOpacity: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "backdrop-opacity": t => ({
+                "--tw-backdrop-opacity": `opacity(${t})`,
+                "@defaults backdrop-filter": {},
+                "backdrop-filter": Ne,
+              }),
+            }, { values: e("backdropOpacity") });
+          },
+          backdropSaturate: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "backdrop-saturate": t => ({
+                "--tw-backdrop-saturate": `saturate(${t})`,
+                "@defaults backdrop-filter": {},
+                "backdrop-filter": Ne,
+              }),
+            }, { values: e("backdropSaturate") });
+          },
+          backdropSepia: ({ matchUtilities: r, theme: e }) => {
+            r({
+              "backdrop-sepia": t => ({
+                "--tw-backdrop-sepia": `sepia(${t})`,
+                "@defaults backdrop-filter": {},
+                "backdrop-filter": Ne,
+              }),
+            }, { values: e("backdropSepia") });
+          },
+          backdropFilter: ({ addDefaults: r, addUtilities: e }) => {
+            r("backdrop-filter", {
+              "--tw-backdrop-blur": " ",
+              "--tw-backdrop-brightness": " ",
+              "--tw-backdrop-contrast": " ",
+              "--tw-backdrop-grayscale": " ",
+              "--tw-backdrop-hue-rotate": " ",
+              "--tw-backdrop-invert": " ",
+              "--tw-backdrop-opacity": " ",
+              "--tw-backdrop-saturate": " ",
+              "--tw-backdrop-sepia": " ",
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+              e({
+                ".backdrop-filter": { "@defaults backdrop-filter": {}, "backdrop-filter": Ne },
+                ".backdrop-filter-none": { "backdrop-filter": "none" },
+              });
+          },
+          transitionProperty: ({ matchUtilities: r, theme: e }) => {
+            let t = e("transitionTimingFunction.DEFAULT"), i = e("transitionDuration.DEFAULT");
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+              transition: n => ({
+                "transition-property": n,
+                ...n === "none" ? {} : { "transition-timing-function": t, "transition-duration": i },
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+          },
+          transitionDelay: T("transitionDelay", [["delay", ["transitionDelay"]]]),
+          transitionDuration: T("transitionDuration", [["duration", ["transitionDuration"]]], { filterDefault: !0 }),
+          transitionTimingFunction: T("transitionTimingFunction", [["ease", ["transitionTimingFunction"]]], {
+            filterDefault: !0,
+          }),
+          willChange: T("willChange", [["will-change", ["will-change"]]]),
+          content: T("content", [["content", ["--tw-content", ["content", "var(--tw-content)"]]]]),
+        };
+    });
+  function zS(r) {
+    if (r === void 0) return !1;
+    if (r === "true" || r === "1") return !0;
+    if (r === "false" || r === "0") return !1;
+    if (r === "*") return !0;
+    let e = r.split(",").map(t => t.split(":")[0]);
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+    id,
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+        id = new Map(),
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+        za = new Map(),
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+  function Mt(r) {
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+      if (VS.has(n) && r[i - 1] !== "\\" && (t = !t), !t && r[i - 1] !== "\\") {
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+          let s = sd.get(n);
+          if (e.length <= 0 || e.pop() !== s) return !1;
+        }
+      }
+    }
+    return !(e.length > 0);
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+  var nd,
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+      l();
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+        VS = new Set(["\"", "'", "`"]);
+    });
+  function Ft(r) {
+    let [e] = ad(r);
+    return e.forEach(([t, i]) => t.removeChild(i)), r.nodes.push(...e.map(([, t]) => t)), r;
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+  function US(r) {
+    return od(r) && Wa(r).includes("terminal");
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+  function Wa(r) {
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+        "::backdrop": ["terminal"],
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+        ":after": ["terminal", "jumpable"],
+        ":before": ["terminal", "jumpable"],
+        ":first-letter": ["terminal", "jumpable"],
+        ":first-line": ["terminal", "jumpable"],
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+      };
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+      s = Le.default.root({ nodes: [Le.default.selector({ nodes: [Le.default.className({ value: ce(t) })] })] });
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+    return s;
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+  function ud(r) {
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+        ? -1
+        : e.type === "class" && t.type === "tag"
+        ? 1
+        : e.type === "class" && t.type === "pseudo" && t.value.startsWith("::")
+        ? -1
+        : e.type === "pseudo" && e.value.startsWith("::") && t.type === "class"
+        ? 1
+        : r.index(e) - r.index(t)
+    ),
+      r;
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+  function Ha(r, e) {
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+      if (i.type === "class" && i.value === e) return t = !0, !1;
+    }), t || r.remove();
+  }
+  function dn(r, e, { context: t, candidate: i, base: n }) {
+    let s = t?.tailwindConfig?.separator ?? ":";
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+    let o = Array.isArray(e) ? Nt(e, { context: t, candidate: i }) : e;
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+      a.each(f => Ft(f)),
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+      e.walkPseudos(i => {
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+    Ja = C(() => {
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+      Qa = K(Me());
+      pn();
+    });
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+  }
+  function* QS(r) {
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+      if (e === 1 / 0 && r.endsWith("]")) {
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+    return t;
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+          else {
+            let w = u.map(S => new Set([...c.get(S) ?? []]));
+            for (let S of w) {
+              for (let _ of S) {
+                let P = !1;
+                for (let M of w) S !== M && M.has(_) && (M.delete(_), P = !0);
+                P && S.delete(_);
+              }
+            }
+            let k = [];
+            for (let [S, _] of w.entries()) {
+              for (let P of _) {
+                let M = u[S].map(([, F]) => F).flat().map(F =>
+                  F.toString().split(`
+`).slice(1, -1).map(I => I.trim()).map(I => `      ${I}`).join(`
+`)
+                ).join(`
+
+`);
+                k.push(`  Use \`${r.replace("[", `[${P}:`)}\` for \`${M.trim()}\``);
+                break;
+              }
+            }
+            N.warn([
+              `The class \`${r}\` is ambiguous and matches multiple utilities.`,
+              ...k,
+              `If this is content and not a class, replace it with \`${
+                r.replace("[", "&lsqb;").replace("]", "&rsqb;")
+              }\` to silence this warning.`,
+            ]);
+            continue;
+          }
+        }
+        u = u.map(h => h.filter(y => fd(y[1])));
+      }
+      u = u.flat(), u = Array.from(s2(u, n)), u = JS(u, e), a && (u = XS(u, n));
+      for (let h of s) u = KS(h, u, e);
+      for (let h of u) {
+        h[1].raws.tailwind = { ...h[1].raws.tailwind, candidate: r },
+          h = a2(h, { context: e, candidate: r, original: t }),
+          h !== null && (yield h);
+      }
+    }
+  }
+  function a2(r, { context: e, candidate: t, original: i }) {
+    if (!r[0].collectedFormats) return r;
+    let n = !0, s;
+    try {
+      s = Nt(r[0].collectedFormats, { context: e, candidate: t });
+    } catch {
+      return null;
+    }
+    let a = j.root({ nodes: [r[1].clone()] });
+    return a.walkRules(o => {
+      if (!yn(o)) {
+        try {
+          o.selector = dn(o.selector, s, { candidate: i, context: e });
+        } catch {
+          return n = !1, !1;
+        }
+      }
+    }),
+      n ? (r[1] = a.nodes[0], r) : null;
+  }
+  function yn(r) {
+    return r.parent && r.parent.type === "atrule" && r.parent.name === "keyframes";
+  }
+  function o2(r) {
+    if (r === !0) {
+      return e => {
+        yn(e) || e.walkDecls(t => {
+          t.parent.type === "rule" && !yn(t.parent) && (t.important = !0);
+        });
+      };
+    }
+    if (typeof r == "string") {
+      return e => {
+        yn(e) || (e.selectors = e.selectors.map(t => hn(t, r)));
+      };
+    }
+  }
+  function bn(r, e) {
+    let t = [], i = o2(e.tailwindConfig.important);
+    for (let n of r) {
+      if (e.notClassCache.has(n)) continue;
+      if (e.candidateRuleCache.has(n)) {
+        t = t.concat(Array.from(e.candidateRuleCache.get(n)));
+        continue;
+      }
+      let s = Array.from(gn(n, e));
+      if (s.length === 0) {
+        e.notClassCache.add(n);
+        continue;
+      }
+      e.classCache.set(n, s);
+      let a = e.candidateRuleCache.get(n) ?? new Set();
+      e.candidateRuleCache.set(n, a);
+      for (let o of s) {
+        let [{ sort: u, options: c }, f] = o;
+        if (c.respectImportant && i) {
+          let d = j.root({ nodes: [f.clone()] });
+          d.walkRules(i), f = d.nodes[0];
+        }
+        let p = [u, f];
+        a.add(p), e.ruleCache.add(p), t.push(p);
+      }
+    }
+    return t;
+  }
+  function Za(r) {
+    return r.startsWith("[") && r.endsWith("]");
+  }
+  var mn,
+    YS,
+    ZS,
+    wn = C(() => {
+      l();
+      it();
+      mn = K(Me());
+      Ma();
+      vt();
+      nn();
+      ur();
+      Oe();
+      at();
+      Ya();
+      Na();
+      lr();
+      xn();
+      Va();
+      sr();
+      De();
+      Ja();
+      YS = (0, mn.default)(r => r.first.filter(({ type: e }) => e === "class").pop().value);
+      ZS = /^[a-z_-]/;
+    });
+  var pd,
+    dd = C(() => {
+      l();
+      pd = {};
+    });
+  function l2(r) {
+    try {
+      return pd.createHash("md5").update(r, "utf-8").digest("binary");
+    } catch (e) {
+      return "";
+    }
+  }
+  function hd(r, e) {
+    let t = e.toString();
+    if (!t.includes("@tailwind")) return !1;
+    let i = za.get(r), n = l2(t), s = i !== n;
+    return za.set(r, n), s;
+  }
+  var md = C(() => {
+    l();
+    dd();
+    at();
+  });
+  function kn(r) {
+    return (r > 0n) - (r < 0n);
+  }
+  var gd = C(() => {
+    l();
+  });
+  function yd(r, e) {
+    let t = 0n, i = 0n;
+    for (let [n, s] of e) r & n && (t = t | n, i = i | s);
+    return r & ~t | i;
+  }
+  var bd = C(() => {
+    l();
+  });
+  function wd(r) {
+    let e = null;
+    for (let t of r) e = e ?? t, e = e > t ? e : t;
+    return e;
+  }
+  function u2(r, e) {
+    let t = r.length, i = e.length, n = t < i ? t : i;
+    for (let s = 0; s < n; s++) {
+      let a = r.charCodeAt(s) - e.charCodeAt(s);
+      if (a !== 0) return a;
+    }
+    return t - i;
+  }
+  var eo,
+    vd = C(() => {
+      l();
+      gd();
+      bd();
+      eo = class {
+        constructor() {
+          this.offsets = { defaults: 0n, base: 0n, components: 0n, utilities: 0n, variants: 0n, user: 0n },
+            this.layerPositions = { defaults: 0n, base: 1n, components: 2n, utilities: 3n, user: 4n, variants: 5n },
+            this.reservedVariantBits = 0n,
+            this.variantOffsets = new Map();
+        }
+        create(e) {
+          return {
+            layer: e,
+            parentLayer: e,
+            arbitrary: 0n,
+            variants: 0n,
+            parallelIndex: 0n,
+            index: this.offsets[e]++,
+            options: [],
+          };
+        }
+        arbitraryProperty() {
+          return { ...this.create("utilities"), arbitrary: 1n };
+        }
+        forVariant(e, t = 0) {
+          let i = this.variantOffsets.get(e);
+          if (i === void 0) throw new Error(`Cannot find offset for unknown variant ${e}`);
+          return { ...this.create("variants"), variants: i << BigInt(t) };
+        }
+        applyVariantOffset(e, t, i) {
+          return i.variant = t.variants, {
+            ...e,
+            layer: "variants",
+            parentLayer: e.layer === "variants" ? e.parentLayer : e.layer,
+            variants: e.variants | t.variants,
+            options: i.sort ? [].concat(i, e.options) : e.options,
+            parallelIndex: wd([e.parallelIndex, t.parallelIndex]),
+          };
+        }
+        applyParallelOffset(e, t) {
+          return { ...e, parallelIndex: BigInt(t) };
+        }
+        recordVariants(e, t) {
+          for (let i of e) this.recordVariant(i, t(i));
+        }
+        recordVariant(e, t = 1) {
+          return this.variantOffsets.set(e, 1n << this.reservedVariantBits),
+            this.reservedVariantBits += BigInt(t),
+            { ...this.create("variants"), variants: this.variantOffsets.get(e) };
+        }
+        compare(e, t) {
+          if (e.layer !== t.layer) return this.layerPositions[e.layer] - this.layerPositions[t.layer];
+          if (e.parentLayer !== t.parentLayer) {
+            return this.layerPositions[e.parentLayer] - this.layerPositions[t.parentLayer];
+          }
+          for (let i of e.options) {
+            for (let n of t.options) {
+              if (i.id !== n.id || !i.sort || !n.sort) continue;
+              let s = wd([i.variant, n.variant]) ?? 0n, a = ~(s | s - 1n), o = e.variants & a, u = t.variants & a;
+              if (o !== u) continue;
+              let c = i.sort({ value: i.value, modifier: i.modifier }, { value: n.value, modifier: n.modifier });
+              if (c !== 0) return c;
+            }
+          }
+          return e.variants !== t.variants
+            ? e.variants - t.variants
+            : e.parallelIndex !== t.parallelIndex
+            ? e.parallelIndex - t.parallelIndex
+            : e.arbitrary !== t.arbitrary
+            ? e.arbitrary - t.arbitrary
+            : e.index - t.index;
+        }
+        recalculateVariantOffsets() {
+          let e = Array.from(this.variantOffsets.entries()).filter(([n]) => n.startsWith("[")).sort(([n], [s]) =>
+              u2(n, s)
+            ),
+            t = e.map(([, n]) => n).sort((n, s) => kn(n - s));
+          return e.map(([, n], s) => [n, t[s]]).filter(([n, s]) => n !== s);
+        }
+        remapArbitraryVariantOffsets(e) {
+          let t = this.recalculateVariantOffsets();
+          return t.length === 0 ? e : e.map(i => {
+            let [n, s] = i;
+            return n = { ...n, variants: yd(n.variants, t) }, [n, s];
+          });
+        }
+        sort(e) {
+          return e = this.remapArbitraryVariantOffsets(e), e.sort(([t], [i]) => kn(this.compare(t, i)));
+        }
+      };
+    });
+  function no(r, e) {
+    let t = r.tailwindConfig.prefix;
+    return typeof t == "function" ? t(e) : t + e;
+  }
+  function kd({ type: r = "any", ...e }) {
+    let t = [].concat(r);
+    return { ...e, types: t.map(i => Array.isArray(i) ? { type: i[0], ...i[1] } : { type: i, preferOnConflict: !1 }) };
+  }
+  function f2(r) {
+    let e = [], t = "", i = 0;
+    for (let n = 0; n < r.length; n++) {
+      let s = r[n];
+      if (s === "\\") t += "\\" + r[++n];
+      else if (s === "{") ++i, e.push(t.trim()), t = "";
+      else if (s === "}") {
+        if (--i < 0) throw new Error("Your { and } are unbalanced.");
+        e.push(t.trim()), t = "";
+      } else t += s;
+    }
+    return t.length > 0 && e.push(t.trim()), e = e.filter(n => n !== ""), e;
+  }
+  function c2(r, e, { before: t = [] } = {}) {
+    if (t = [].concat(t), t.length <= 0) {
+      r.push(e);
+      return;
+    }
+    let i = r.length - 1;
+    for (let n of t) {
+      let s = r.indexOf(n);
+      s !== -1 && (i = Math.min(i, s));
+    }
+    r.splice(i, 0, e);
+  }
+  function Sd(r) {
+    return Array.isArray(r) ? r.flatMap(e => !Array.isArray(e) && !se(e) ? e : It(e)) : Sd([r]);
+  }
+  function _d(r, e) {
+    return (0, to.default)(i => {
+      let n = [];
+      return e && e(i),
+        i.walkClasses(s => {
+          n.push(s.value);
+        }),
+        n;
+    }).transformSync(r);
+  }
+  function p2(r, e = { containsNonOnDemandable: !1 }, t = 0) {
+    let i = [];
+    if (r.type === "rule") {
+      let n = function(s) {
+        s.walkPseudos(a => {
+          a.value === ":not" && a.remove();
+        });
+      };
+      for (let s of r.selectors) {
+        let a = _d(s, n);
+        a.length === 0 && (e.containsNonOnDemandable = !0);
+        for (let o of a) i.push(o);
+      }
+    } else {r.type === "atrule" && r.walkRules(n => {
+        for (let s of n.selectors.flatMap(a => _d(a))) i.push(s);
+      });}
+    return t === 0 ? [e.containsNonOnDemandable || i.length === 0, i] : i;
+  }
+  function Sn(r) {
+    return Sd(r).flatMap(e => {
+      let t = new Map(), [i, n] = p2(e);
+      return i && n.unshift(Ge), n.map(s => (t.has(e) || t.set(e, e), [s, t.get(e)]));
+    });
+  }
+  function vn(r) {
+    return r.startsWith("@") || r.includes("&");
+  }
+  function Qr(r) {
+    r = r.replace(/\n+/g, "").replace(/\s{1,}/g, " ").trim();
+    let e = f2(r).map(t => {
+      if (!t.startsWith("@")) return ({ format: s }) => s(t);
+      let [, i, n] = /@(.*?)( .+|[({].*)/g.exec(t);
+      return ({ wrap: s }) => s(j.atRule({ name: i, params: n.trim() }));
+    }).reverse();
+    return t => {
+      for (let i of e) i(t);
+    };
+  }
+  function d2(r, e, { variantList: t, variantMap: i, offsets: n, classList: s }) {
+    function a(d, h) {
+      return d ? (0, xd.default)(r, d, h) : r;
+    }
+    function o(d) {
+      return qt(r.prefix, d);
+    }
+    function u(d, h) {
+      return d === Ge ? Ge : h.respectPrefix ? e.tailwindConfig.prefix + d : d;
+    }
+    function c(d, h, y = {}) {
+      let x = Xe(d), b = a(["theme", ...x], h);
+      return We(x[0])(b, y);
+    }
+    let f = 0,
+      p = {
+        postcss: j,
+        prefix: o,
+        e: ce,
+        config: a,
+        theme: c,
+        corePlugins: d => Array.isArray(r.corePlugins) ? r.corePlugins.includes(d) : a(["corePlugins", d], !0),
+        variants: () => [],
+        addBase(d) {
+          for (let [h, y] of Sn(d)) {
+            let x = u(h, {}), b = n.create("base");
+            e.candidateRuleMap.has(x) || e.candidateRuleMap.set(x, []),
+              e.candidateRuleMap.get(x).push([{ sort: b, layer: "base" }, y]);
+          }
+        },
+        addDefaults(d, h) {
+          let y = { [`@defaults ${d}`]: h };
+          for (let [x, b] of Sn(y)) {
+            let w = u(x, {});
+            e.candidateRuleMap.has(w) || e.candidateRuleMap.set(w, []),
+              e.candidateRuleMap.get(w).push([{ sort: n.create("defaults"), layer: "defaults" }, b]);
+          }
+        },
+        addComponents(d, h) {
+          h = Object.assign(
+            {},
+            { preserveSource: !1, respectPrefix: !0, respectImportant: !1 },
+            Array.isArray(h) ? {} : h,
+          );
+          for (let [x, b] of Sn(d)) {
+            let w = u(x, h);
+            s.add(w),
+              e.candidateRuleMap.has(w) || e.candidateRuleMap.set(w, []),
+              e.candidateRuleMap.get(w).push([{ sort: n.create("components"), layer: "components", options: h }, b]);
+          }
+        },
+        addUtilities(d, h) {
+          h = Object.assign(
+            {},
+            { preserveSource: !1, respectPrefix: !0, respectImportant: !0 },
+            Array.isArray(h) ? {} : h,
+          );
+          for (let [x, b] of Sn(d)) {
+            let w = u(x, h);
+            s.add(w),
+              e.candidateRuleMap.has(w) || e.candidateRuleMap.set(w, []),
+              e.candidateRuleMap.get(w).push([{ sort: n.create("utilities"), layer: "utilities", options: h }, b]);
+          }
+        },
+        matchUtilities: function(d, h) {
+          h = kd({ ...{ respectPrefix: !0, respectImportant: !0, modifiers: !1 }, ...h });
+          let x = n.create("utilities");
+          for (let b in d) {
+            let S = function(P, { isOnlyPlugin: M }) {
+                let [F, I, X] = rs(h.types, P, h, r);
+                if (F === void 0) return [];
+                if (!h.types.some(({ type: ee }) => ee === I)) {
+                  if (M) {
+                    N.warn([
+                      `Unnecessary typehint \`${I}\` in \`${b}-${P}\`.`,
+                      `You can safely update it to \`${b}-${P.replace(I + ":", "")}\`.`,
+                    ]);
+                  } else return [];
+                }
+                if (!Mt(F)) return [];
+                let ge = {
+                    get modifier() {
+                      return h.modifiers
+                        || N.warn(`modifier-used-without-options-for-${b}`, [
+                          "Your plugin must set `modifiers: true` in its options to support modifiers.",
+                        ]),
+                        X;
+                    },
+                  },
+                  Q = J(r, "generalizedModifiers");
+                return [].concat(Q ? k(F, ge) : k(F)).filter(Boolean).map(ee => ({ [sn(b, P)]: ee }));
+              },
+              w = u(b, h),
+              k = d[b];
+            s.add([w, h]);
+            let _ = [{ sort: x, layer: "utilities", options: h }, S];
+            e.candidateRuleMap.has(w) || e.candidateRuleMap.set(w, []), e.candidateRuleMap.get(w).push(_);
+          }
+        },
+        matchComponents: function(d, h) {
+          h = kd({ ...{ respectPrefix: !0, respectImportant: !1, modifiers: !1 }, ...h });
+          let x = n.create("components");
+          for (let b in d) {
+            let S = function(P, { isOnlyPlugin: M }) {
+                let [F, I, X] = rs(h.types, P, h, r);
+                if (F === void 0) return [];
+                if (!h.types.some(({ type: ee }) => ee === I)) {
+                  if (M) {
+                    N.warn([
+                      `Unnecessary typehint \`${I}\` in \`${b}-${P}\`.`,
+                      `You can safely update it to \`${b}-${P.replace(I + ":", "")}\`.`,
+                    ]);
+                  } else return [];
+                }
+                if (!Mt(F)) return [];
+                let ge = {
+                    get modifier() {
+                      return h.modifiers
+                        || N.warn(`modifier-used-without-options-for-${b}`, [
+                          "Your plugin must set `modifiers: true` in its options to support modifiers.",
+                        ]),
+                        X;
+                    },
+                  },
+                  Q = J(r, "generalizedModifiers");
+                return [].concat(Q ? k(F, ge) : k(F)).filter(Boolean).map(ee => ({ [sn(b, P)]: ee }));
+              },
+              w = u(b, h),
+              k = d[b];
+            s.add([w, h]);
+            let _ = [{ sort: x, layer: "components", options: h }, S];
+            e.candidateRuleMap.has(w) || e.candidateRuleMap.set(w, []), e.candidateRuleMap.get(w).push(_);
+          }
+        },
+        addVariant(d, h, y = {}) {
+          h = [].concat(h).map(x => {
+            if (typeof x != "string") {
+              return (b = {}) => {
+                let { args: w, modifySelectors: k, container: S, separator: _, wrap: P, format: M } = b,
+                  F = x(
+                    Object.assign(
+                      { modifySelectors: k, container: S, separator: _ },
+                      y.type === ro.MatchVariant && { args: w, wrap: P, format: M },
+                    ),
+                  );
+                if (typeof F == "string" && !vn(F)) {
+                  throw new Error(
+                    `Your custom variant \`${d}\` has an invalid format string. Make sure it's an at-rule or contains a \`&\` placeholder.`,
+                  );
+                }
+                return Array.isArray(F)
+                  ? F.filter(I => typeof I == "string").map(I => Qr(I))
+                  : F && typeof F == "string" && Qr(F)(b);
+              };
+            }
+            if (!vn(x)) {
+              throw new Error(
+                `Your custom variant \`${d}\` has an invalid format string. Make sure it's an at-rule or contains a \`&\` placeholder.`,
+              );
+            }
+            return Qr(x);
+          }),
+            c2(t, d, y),
+            i.set(d, h),
+            e.variantOptions.set(d, y);
+        },
+        matchVariant(d, h, y) {
+          let x = y?.id ?? ++f, b = d === "@", w = J(r, "generalizedModifiers");
+          for (let [S, _] of Object.entries(y?.values ?? {})) {
+            S !== "DEFAULT"
+              && p.addVariant(
+                b ? `${d}${S}` : `${d}-${S}`,
+                ({ args: P, container: M }) => h(_, w ? { modifier: P?.modifier, container: M } : { container: M }),
+                {
+                  ...y,
+                  value: _,
+                  id: x,
+                  type: ro.MatchVariant,
+                  variantInfo: io.Base,
+                },
+              );
+          }
+          let k = "DEFAULT" in (y?.values ?? {});
+          p.addVariant(
+            d,
+            ({ args: S, container: _ }) =>
+              S?.value === Yr && !k
+                ? null
+                : h(
+                  S?.value === Yr ? y.values.DEFAULT : S?.value ?? (typeof S == "string" ? S : ""),
+                  w ? { modifier: S?.modifier, container: _ } : { container: _ },
+                ),
+            { ...y, id: x, type: ro.MatchVariant, variantInfo: io.Dynamic },
+          );
+        },
+      };
+    return p;
+  }
+  function _n(r) {
+    return so.has(r) || so.set(r, new Map()), so.get(r);
+  }
+  function Cd(r, e) {
+    let t = !1, i = new Map();
+    for (let n of r) {
+      if (!n) continue;
+      let s = us.parse(n), a = s.hash ? s.href.replace(s.hash, "") : s.href;
+      a = s.search ? a.replace(s.search, "") : a;
+      let o = ie.statSync(decodeURIComponent(a), { throwIfNoEntry: !1 })?.mtimeMs;
+      !o || ((!e.has(n) || o > e.get(n)) && (t = !0), i.set(n, o));
+    }
+    return [t, i];
+  }
+  function Ad(r) {
+    r.walkAtRules(e => {
+      ["responsive", "variants"].includes(e.name) && (Ad(e), e.before(e.nodes), e.remove());
+    });
+  }
+  function h2(r) {
+    let e = [];
+    return r.each(t => {
+      t.type === "atrule" && ["responsive", "variants"].includes(t.name) && (t.name = "layer", t.params = "utilities");
+    }),
+      r.walkAtRules("layer", t => {
+        if (Ad(t), t.params === "base") {
+          for (let i of t.nodes) {
+            e.push(function({ addBase: n }) {
+              n(i, { respectPrefix: !1 });
+            });
+          }
+          t.remove();
+        } else if (t.params === "components") {
+          for (let i of t.nodes) {
+            e.push(function({ addComponents: n }) {
+              n(i, { respectPrefix: !1, preserveSource: !0 });
+            });
+          }
+          t.remove();
+        } else if (t.params === "utilities") {
+          for (let i of t.nodes) {
+            e.push(function({ addUtilities: n }) {
+              n(i, { respectPrefix: !1, preserveSource: !0 });
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+          t.remove();
+        }
+      }),
+      e;
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+  function m2(r, e) {
+    let t = Object.entries({ ...pe, ...ed }).map(([o, u]) => r.tailwindConfig.corePlugins.includes(o) ? u : null)
+        .filter(Boolean),
+      i = r.tailwindConfig.plugins.map(
+        o => (o.__isOptionsFunction && (o = o()), typeof o == "function" ? o : o.handler),
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+      n = h2(e),
+      s = [pe.pseudoElementVariants, pe.pseudoClassVariants, pe.ariaVariants, pe.dataVariants],
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+        pe.directionVariants,
+        pe.reducedMotionVariants,
+        pe.prefersContrastVariants,
+        pe.darkVariants,
+        pe.printVariant,
+        pe.screenVariants,
+        pe.orientationVariants,
+      ];
+    return [...t, ...s, ...i, ...a, ...n];
+  }
+  function g2(r, e) {
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+    e.variantMap = i;
+    let n = new eo();
+    e.offsets = n;
+    let s = new Set(), a = d2(e.tailwindConfig, e, { variantList: t, variantMap: i, offsets: n, classList: s });
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+      for (let p of o) {
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+          e.changedContent.push({ content: p, extension: "html" });
+          continue;
+        }
+        if (p instanceof RegExp) {
+          N.warn("root-regex", [
+            "Regular expressions in `safelist` work differently in Tailwind CSS v3.0.",
+            "Update your `safelist` configuration to eliminate this warning.",
+            "https://tailwindcss.com/docs/content-configuration#safelisting-classes",
+          ]);
+          continue;
+        }
+        f.push(p);
+      }
+      if (f.length > 0) {
+        let p = new Map(), d = e.tailwindConfig.prefix.length, h = f.some(y => y.pattern.source.includes("!"));
+        for (let y of s) {
+          let x = Array.isArray(y)
+            ? (() => {
+              let [b, w] = y, S = Object.keys(w?.values ?? {}).map(_ => Hr(b, _));
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+                w.types.some(({ type: _ }) => _ === "color")
+                && (S = [...S, ...S.flatMap(_ => Object.keys(e.tailwindConfig.theme.opacity).map(P => `${_}/${P}`))]),
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+            for (let { pattern: w, variants: k = [] } of f) {
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+                p.set(w, p.get(w) + 1), e.changedContent.push({ content: b, extension: "html" });
+                for (let S of k) {
+                  e.changedContent.push({ content: S + e.tailwindConfig.separator + b, extension: "html" });
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+              }
+            }
+          }
+        }
+        for (let [y, x] of p.entries()) {
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+            && N.warn([
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+              "Fix this pattern or remove it from your `safelist` configuration.",
+              "https://tailwindcss.com/docs/content-configuration#safelisting-classes",
+            ]);
+        }
+      }
+    }
+    let u = [].concat(e.tailwindConfig.darkMode ?? "media")[1] ?? "dark", c = [no(e, u), no(e, "group"), no(e, "peer")];
+    e.getClassOrder = function(p) {
+      let d = [...p].sort((b, w) => b === w ? 0 : b < w ? -1 : 1),
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+        y = bn(new Set(d), e);
+      y = e.offsets.sort(y);
+      let x = BigInt(c.length);
+      for (let [, b] of y) h.set(b.raws.tailwind.candidate, x++);
+      return p.map(b => {
+        let w = h.get(b) ?? null, k = c.indexOf(b);
+        return w === null && k !== -1 && (w = BigInt(k)), [b, w];
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+    },
+      e.getClassList = function(p = {}) {
+        let d = [];
+        for (let h of s) {
+          if (Array.isArray(h)) {
+            let [y, x] = h, b = [], w = Object.keys(x?.modifiers ?? {});
+            x?.types?.some(({ type: _ }) => _ === "color")
+              && w.push(...Object.keys(e.tailwindConfig.theme.opacity ?? {}));
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+                b.push(S ? [F, k] : F);
+              }
+            }
+            d.push(...b);
+          } else d.push(h);
+        }
+        return d;
+      },
+      e.getVariants = function() {
+        let p = [];
+        for (let [d, h] of e.variantOptions.entries()) {
+          h.variantInfo !== io.Base && p.push({
+            name: d,
+            isArbitrary: h.type === Symbol.for("MATCH_VARIANT"),
+            values: Object.keys(h.values ?? {}),
+            hasDash: d !== "@",
+            selectors({ modifier: y, value: x } = {}) {
+              let b = "__TAILWIND_PLACEHOLDER__",
+                w = j.rule({ selector: `.${b}` }),
+                k = j.root({ nodes: [w.clone()] }),
+                S = k.toString(),
+                _ = (e.variantMap.get(d) ?? []).flatMap(([Q, Z]) => Z),
+                P = [];
+              for (let Q of _) {
+                let Z = [],
+                  ee = {
+                    args: { modifier: y, value: h.values?.[x] ?? x },
+                    separator: e.tailwindConfig.separator,
+                    modifySelectors(_e) {
+                      return k.each(jn => {
+                        jn.type === "rule" && (jn.selectors = jn.selectors.map(Gl =>
+                          _e({
+                            get className() {
+                              return Xa(Gl);
+                            },
+                            selector: Gl,
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+                        ));
+                      }),
+                        k;
+                    },
+                    format(_e) {
+                      Z.push(_e);
+                    },
+                    wrap(_e) {
+                      Z.push(`@${_e.name} ${_e.params} { & }`);
+                    },
+                    container: k,
+                  },
+                  wt = Q(ee);
+                if (Z.length > 0 && P.push(Z), Array.isArray(wt)) for (let _e of wt) Z = [], _e(ee), P.push(Z);
+              }
+              let M = [], F = k.toString();
+              S !== F && (k.walkRules(Q => {
+                let Z = Q.selector,
+                  ee = (0, to.default)(wt => {
+                    wt.walkClasses(_e => {
+                      _e.value = `${d}${e.tailwindConfig.separator}${_e.value}`;
+                    });
+                  }).processSync(Z);
+                M.push(Z.replace(ee, "&").replace(b, "&"));
+              }),
+                k.walkAtRules(Q => {
+                  M.push(`@${Q.name} (${Q.params}) { & }`);
+                }));
+              let I = !(x in (h.values ?? {}));
+              P = P.map(Q => Q.map(Z => ({ format: Z, isArbitraryVariant: I }))),
+                M = M.map(Q => ({ format: Q, isArbitraryVariant: I }));
+              let X = { candidate: b, context: e },
+                ge = P.map(Q => dn(`.${b}`, Nt(Q, X), X).replace(`.${b}`, "&").replace("{ & }", "").trim());
+              return M.length > 0 && ge.push(Nt(M, X).toString().replace(`.${b}`, "&")), ge;
+            },
+          });
+        }
+        return p;
+      };
+  }
+  function Od(r, e) {
+    !r.classCache.has(e)
+      || (r.notClassCache.add(e),
+        r.classCache.delete(e),
+        r.applyClassCache.delete(e),
+        r.candidateRuleMap.delete(e),
+        r.candidateRuleCache.delete(e),
+        r.stylesheetCache = null);
+  }
+  function y2(r, e) {
+    let t = e.raws.tailwind.candidate;
+    if (!!t) {
+      for (let i of r.ruleCache) i[1].raws.tailwind.candidate === t && r.ruleCache.delete(i);
+      Od(r, t);
+    }
+  }
+  function ao(r, e = [], t = j.root()) {
+    let i = {
+        disposables: [],
+        ruleCache: new Set(),
+        candidateRuleCache: new Map(),
+        classCache: new Map(),
+        applyClassCache: new Map(),
+        notClassCache: new Set(r.blocklist ?? []),
+        postCssNodeCache: new Map(),
+        candidateRuleMap: new Map(),
+        tailwindConfig: r,
+        changedContent: e,
+        variantMap: new Map(),
+        stylesheetCache: null,
+        variantOptions: new Map(),
+        markInvalidUtilityCandidate: s => Od(i, s),
+        markInvalidUtilityNode: s => y2(i, s),
+      },
+      n = m2(i, t);
+    return g2(n, i), i;
+  }
+  function Ed(r, e, t, i, n, s) {
+    let a = e.opts.from, o = i !== null;
+    Pe.DEBUG && console.log("Source path:", a);
+    let u;
+    if (o && Lt.has(a)) u = Lt.get(a);
+    else if (Jr.has(n)) {
+      let d = Jr.get(n);
+      ot.get(d).add(a), Lt.set(a, d), u = d;
+    }
+    let c = hd(a, r);
+    if (u) {
+      let [d, h] = Cd([...s], _n(u));
+      if (!d && !c) return [u, !1, h];
+    }
+    if (Lt.has(a)) {
+      let d = Lt.get(a);
+      if (ot.has(d) && (ot.get(d).delete(a), ot.get(d).size === 0)) {
+        ot.delete(d);
+        for (let [h, y] of Jr) y === d && Jr.delete(h);
+        for (let h of d.disposables.splice(0)) h(d);
+      }
+    }
+    Pe.DEBUG && console.log("Setting up new context...");
+    let f = ao(t, [], r);
+    Object.assign(f, { userConfigPath: i });
+    let [, p] = Cd([...s], _n(f));
+    return Jr.set(n, f), Lt.set(a, f), ot.has(f) || ot.set(f, new Set()), ot.get(f).add(a), [f, !0, p];
+  }
+  var xd,
+    to,
+    ro,
+    io,
+    so,
+    Lt,
+    Jr,
+    ot,
+    xn = C(() => {
+      l();
+      je();
+      fs();
+      it();
+      xd = K(Is()), to = K(Me());
+      Wr();
+      Ma();
+      nn();
+      vt();
+      Rt();
+      Na();
+      ur();
+      td();
+      at();
+      at();
+      oi();
+      Oe();
+      si();
+      Va();
+      wn();
+      md();
+      vd();
+      De();
+      Ya();
+      ro = { AddVariant: Symbol.for("ADD_VARIANT"), MatchVariant: Symbol.for("MATCH_VARIANT") },
+        io = { Base: 1 << 0, Dynamic: 1 << 1 };
+      so = new WeakMap();
+      Lt = rd, Jr = id, ot = cn;
+    });
+  function oo(r) {
+    return r.ignore
+      ? []
+      : r.glob
+      ? m.env.ROLLUP_WATCH === "true"
+        ? [{ type: "dependency", file: r.base }]
+        : [{ type: "dir-dependency", dir: r.base, glob: r.glob }]
+      : [{ type: "dependency", file: r.base }];
+  }
+  var Td = C(() => {
+    l();
+  });
+  function Pd(r, e) {
+    return { handler: r, config: e };
+  }
+  var Dd,
+    Id = C(() => {
+      l();
+      Pd.withOptions = function(r, e = () => ({})) {
+        let t = function(i) {
+          return { __options: i, handler: r(i), config: e(i) };
+        };
+        return t.__isOptionsFunction = !0, t.__pluginFunction = r, t.__configFunction = e, t;
+      };
+      Dd = Pd;
+    });
+  var lo = {};
+  Ce(lo, { default: () => b2 });
+  var b2,
+    uo = C(() => {
+      l();
+      Id();
+      b2 = Dd;
+    });
+  var Rd = v((GP, qd) => {
+    l();
+    var w2 = (uo(), lo).default,
+      v2 = { overflow: "hidden", display: "-webkit-box", "-webkit-box-orient": "vertical" },
+      x2 = w2(function({ matchUtilities: r, addUtilities: e, theme: t, variants: i }) {
+        let n = t("lineClamp");
+        r({ "line-clamp": s => ({ ...v2, "-webkit-line-clamp": `${s}` }) }, { values: n }),
+          e([{ ".line-clamp-none": { "-webkit-line-clamp": "unset" } }], i("lineClamp"));
+      }, {
+        theme: { lineClamp: { 1: "1", 2: "2", 3: "3", 4: "4", 5: "5", 6: "6" } },
+        variants: { lineClamp: ["responsive"] },
+      });
+    qd.exports = x2;
+  });
+  function fo(r) {
+    r.content.files.length === 0
+      && N.warn("content-problems", [
+        "The `content` option in your Tailwind CSS configuration is missing or empty.",
+        "Configure your content sources or your generated CSS will be missing styles.",
+        "https://tailwindcss.com/docs/content-configuration",
+      ]);
+    try {
+      let e = Rd();
+      r.plugins.includes(e)
+        && (N.warn("line-clamp-in-core", [
+          "As of Tailwind CSS v3.3, the `@tailwindcss/line-clamp` plugin is now included by default.",
+          "Remove it from the `plugins` array in your configuration to eliminate this warning.",
+        ]),
+          r.plugins = r.plugins.filter(t => t !== e));
+    } catch {}
+    return r;
+  }
+  var Md = C(() => {
+    l();
+    Oe();
+  });
+  var Fd,
+    Nd = C(() => {
+      l();
+      Fd = () => !1;
+    });
+  var Cn,
+    Ld = C(() => {
+      l();
+      Cn = {
+        sync: r => [].concat(r),
+        generateTasks: r => [{ dynamic: !1, base: ".", negative: [], positive: [].concat(r), patterns: [].concat(r) }],
+        escapePath: r => r,
+      };
+    });
+  var co,
+    Bd = C(() => {
+      l();
+      co = r => r;
+    });
+  var $d,
+    jd = C(() => {
+      l();
+      $d = () => "";
+    });
+  function zd(r) {
+    let e = r, t = $d(r);
+    return t !== "." && (e = r.substr(t.length), e.charAt(0) === "/" && (e = e.substr(1))),
+      e.substr(0, 2) === "./" && (e = e.substr(2)),
+      e.charAt(0) === "/" && (e = e.substr(1)),
+      { base: t, glob: e };
+  }
+  var Vd = C(() => {
+    l();
+    jd();
+  });
+  function Ud(r, e) {
+    let t = e.content.files;
+    t = t.filter(o => typeof o == "string"), t = t.map(co);
+    let i = Cn.generateTasks(t), n = [], s = [];
+    for (let o of i) n.push(...o.positive.map(u => Wd(u, !1))), s.push(...o.negative.map(u => Wd(u, !0)));
+    let a = [...n, ...s];
+    return a = S2(r, a), a = a.flatMap(_2), a = a.map(k2), a;
+  }
+  function Wd(r, e) {
+    let t = { original: r, base: r, ignore: e, pattern: r, glob: null };
+    return Fd(r) && Object.assign(t, zd(r)), t;
+  }
+  function k2(r) {
+    let e = co(r.base);
+    return e = Cn.escapePath(e),
+      r.pattern = r.glob ? `${e}/${r.glob}` : e,
+      r.pattern = r.ignore ? `!${r.pattern}` : r.pattern,
+      r;
+  }
+  function S2(r, e) {
+    let t = [];
+    return r.userConfigPath && r.tailwindConfig.content.relative && (t = [te.dirname(r.userConfigPath)]),
+      e.map(i => (i.base = te.resolve(...t, i.base), i));
+  }
+  function _2(r) {
+    let e = [r];
+    try {
+      let t = ie.realpathSync(r.base);
+      t !== r.base && e.push({ ...r, base: t });
+    } catch {}
+    return e;
+  }
+  function Gd(r, e, t) {
+    let i = r.tailwindConfig.content.files.filter(a => typeof a.raw == "string").map((
+        { raw: a, extension: o = "html" },
+      ) => ({ content: a, extension: o })
+      ),
+      [n, s] = C2(e, t);
+    for (let a of n) {
+      let o = te.extname(a).slice(1);
+      i.push({ file: a, extension: o });
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+    return [i, s];
+  }
+  function C2(r, e) {
+    let t = r.map(a => a.pattern), i = new Map(), n = new Set();
+    Pe.DEBUG && console.time("Finding changed files");
+    let s = Cn.sync(t, { absolute: !0 });
+    for (let a of s) {
+      let o = e.get(a) || -1 / 0, u = ie.statSync(a).mtimeMs;
+      u > o && (n.add(a), i.set(a, u));
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+    return Pe.DEBUG && console.timeEnd("Finding changed files"), [n, i];
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+  var Hd = C(() => {
+    l();
+    je();
+    dt();
+    Nd();
+    Ld();
+    Bd();
+    Vd();
+    at();
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+  function Yd() {}
+  var Qd = C(() => {
+    l();
+  });
+  function T2(r, e) {
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+      let i = `${r}${t}`;
+      if (ie.existsSync(i) && ie.statSync(i).isFile()) return i;
+    }
+    for (let t of e) {
+      let i = `${r}/index${t}`;
+      if (ie.existsSync(i)) return i;
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+    return null;
+  }
+  function* Jd(r, e, t, i = te.extname(r)) {
+    let n = T2(te.resolve(e, r), A2.includes(i) ? O2 : E2);
+    if (n === null || t.has(n)) return;
+    t.add(n), yield n, e = te.dirname(n), i = te.extname(n);
+    let s = ie.readFileSync(n, "utf-8");
+    for (
+      let a of [
+        ...s.matchAll(/import[\s\S]*?['"](.{3,}?)['"]/gi),
+        ...s.matchAll(/import[\s\S]*from[\s\S]*?['"](.{3,}?)['"]/gi),
+        ...s.matchAll(/require\(['"`](.+)['"`]\)/gi),
+      ]
+    ) !a[1].startsWith(".") || (yield* Jd(a[1], e, t, i));
+  }
+  function po(r) {
+    return r === null ? new Set() : new Set(Jd(r, te.dirname(r), new Set()));
+  }
+  var A2,
+    O2,
+    E2,
+    Xd = C(() => {
+      l();
+      je();
+      dt();
+      A2 = [".js", ".cjs", ".mjs"],
+        O2 = ["", ".js", ".cjs", ".mjs", ".ts", ".cts", ".mts", ".jsx", ".tsx"],
+        E2 = ["", ".ts", ".cts", ".mts", ".tsx", ".js", ".cjs", ".mjs", ".jsx"];
+    });
+  function P2(r, e) {
+    if (ho.has(r)) return ho.get(r);
+    let t = Ud(r, e);
+    return ho.set(r, t).get(r);
+  }
+  function D2(r) {
+    let e = ls(r);
+    if (e !== null) {
+      let [i, n, s, a] = Zd.get(e) || [], o = po(e), u = !1, c = new Map();
+      for (let d of o) {
+        let h = ie.statSync(d).mtimeMs;
+        c.set(d, h), (!a || !a.has(d) || h > a.get(d)) && (u = !0);
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+      if (!u) return [i, e, n, s];
+      for (let d of o) delete Yl.cache[d];
+      let f = fo(cr(Yd(e))), p = ni(f);
+      return Zd.set(e, [f, p, o, c]), [f, e, p, o];
+    }
+    let t = cr(r.config === void 0 ? r : r.config);
+    return t = fo(t), [t, null, ni(t), []];
+  }
+  function mo(r) {
+    return ({ tailwindDirectives: e, registerDependency: t }) => (i, n) => {
+      let [s, a, o, u] = D2(r), c = new Set(u);
+      if (e.size > 0) {
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+        for (let y of n.messages) y.type === "dependency" && c.add(y.file);
+      }
+      let [f, , p] = Ed(i, n, s, a, o, c), d = _n(f), h = P2(f, s);
+      if (e.size > 0) {
+        for (let b of h) for (let w of oo(b)) t(w);
+        let [y, x] = Gd(f, h, d);
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+        for (let [b, w] of x.entries()) p.set(b, w);
+      }
+      for (let y of u) t({ type: "dependency", file: y });
+      for (let [y, x] of p.entries()) d.set(y, x);
+      return f;
+    };
+  }
+  var Kd,
+    Zd,
+    ho,
+    eh = C(() => {
+      l();
+      je();
+      Kd = K(zn());
+      Zl();
+      os();
+      Vu();
+      xn();
+      Td();
+      Md();
+      Hd();
+      Qd();
+      Xd();
+      Zd = new Kd.default({ maxSize: 100 }), ho = new WeakMap();
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+  function go(r) {
+    let e = new Set(), t = new Set(), i = new Set();
+    if (
+      r.walkAtRules(n => {
+        n.name === "apply" && i.add(n),
+          n.name === "import" && (n.params === "\"tailwindcss/base\"" || n.params === "'tailwindcss/base'"
+            ? (n.name = "tailwind", n.params = "base")
+            : n.params === "\"tailwindcss/components\"" || n.params === "'tailwindcss/components'"
+            ? (n.name = "tailwind", n.params = "components")
+            : n.params === "\"tailwindcss/utilities\"" || n.params === "'tailwindcss/utilities'"
+            ? (n.name = "tailwind", n.params = "utilities")
+            : (n.params === "\"tailwindcss/screens\"" || n.params === "'tailwindcss/screens'"
+              || n.params === "\"tailwindcss/variants\"" || n.params === "'tailwindcss/variants'")
+              && (n.name = "tailwind", n.params = "variants")),
+          n.name === "tailwind" && (n.params === "screens" && (n.params = "variants"), e.add(n.params)),
+          ["layer", "responsive", "variants"].includes(n.name)
+          && (["responsive", "variants"].includes(n.name)
+            && N.warn(`${n.name}-at-rule-deprecated`, [
+              `The \`@${n.name}\` directive has been deprecated in Tailwind CSS v3.0.`,
+              "Use `@layer utilities` or `@layer components` instead.",
+              "https://tailwindcss.com/docs/upgrade-guide#replace-variants-with-layer",
+            ]),
+            t.add(n));
+      }), !e.has("base") || !e.has("components") || !e.has("utilities")
+    ) {
+      for (let n of t) {
+        if (n.name === "layer" && ["base", "components", "utilities"].includes(n.params)) {
+          if (!e.has(n.params)) {
+            throw n.error(
+              `\`@layer ${n.params}\` is used but no matching \`@tailwind ${n.params}\` directive is present.`,
+            );
+          }
+        } else if (n.name === "responsive") {
+          if (!e.has("utilities")) throw n.error("`@responsive` is used but `@tailwind utilities` is missing.");
+        } else if (n.name === "variants" && !e.has("utilities")) {
+          throw n.error("`@variants` is used but `@tailwind utilities` is missing.");
+        }
+      }
+    }
+    return { tailwindDirectives: e, applyDirectives: i };
+  }
+  var th = C(() => {
+    l();
+    Oe();
+  });
+  function yt(r, e = void 0, t = void 0) {
+    return r.map(i => {
+      let n = i.clone(), s = i.raws.tailwind?.preserveSource !== !0 || !n.source;
+      return e !== void 0 && s && (n.source = e,
+        "walk" in n && n.walk(a => {
+          a.source = e;
+        })),
+        t !== void 0 && (n.raws.tailwind = { ...n.raws.tailwind, ...t }),
+        n;
+    });
+  }
+  var rh = C(() => {
+    l();
+  });
+  function An(r) {
+    return r = Array.isArray(r) ? r : [r], r = r.map(e => e instanceof RegExp ? e.source : e), r.join("");
+  }
+  function xe(r) {
+    return new RegExp(An(r), "g");
+  }
+  function Bt(r) {
+    return `(?:${r.map(An).join("|")})`;
+  }
+  function yo(r) {
+    return `(?:${An(r)})?`;
+  }
+  function nh(r) {
+    return `(?:${An(r)})*`;
+  }
+  function sh(r) {
+    return r && I2.test(r) ? r.replace(ih, "\\$&") : r || "";
+  }
+  var ih,
+    I2,
+    ah = C(() => {
+      l();
+      ih = /[\\^$.*+?()[\]{}|]/g, I2 = RegExp(ih.source);
+    });
+  function oh(r) {
+    let e = Array.from(q2(r));
+    return t => {
+      let i = [];
+      for (let n of e) i = [...i, ...t.match(n) ?? []];
+      return i.filter(n => n !== void 0).map(F2);
+    };
+  }
+  function* q2(r) {
+    let e = r.tailwindConfig.separator,
+      t = J(r.tailwindConfig, "variantGrouping"),
+      i = r.tailwindConfig.prefix !== "" ? yo(xe([/-?/, sh(r.tailwindConfig.prefix)])) : "",
+      n = Bt([
+        /\[[^\s:'"`]+:[^\s\[\]]+\]/,
+        /\[[^\s:'"`]+:[^\s]+?\[[^\s]+\][^\s]+?\]/,
+        xe([
+          /-?(?:\w+)/,
+          yo(
+            Bt([
+              xe([/-(?:\w+-)*\[[^\s:]+\]/, /(?![{([]])/, /(?:\/[^\s'"`\\><$]*)?/]),
+              xe([/-(?:\w+-)*\[[^\s]+\]/, /(?![{([]])/, /(?:\/[^\s'"`\\$]*)?/]),
+              /[-\/][^\s'"`\\$={><]*/,
+            ]),
+          ),
+        ]),
+      ]),
+      s = [
+        Bt([
+          xe([/@\[[^\s"'`]+\](\/[^\s"'`]+)?/, e]),
+          xe([/([^\s"'`\[\\]+-)?\[[^\s"'`]+\]/, e]),
+          xe([/[^\s"'`\[\\]+/, e]),
+        ]),
+        Bt([xe([/([^\s"'`\[\\]+-)?\[[^\s`]+\]/, e]), xe([/[^\s`\[\\]+/, e])]),
+      ];
+    for (let a of s) yield xe(["((?=((", a, ")+))\\2)?", /!?/, i, t ? Bt([xe([/\(/, n, nh([/,/, n]), /\)/]), n]) : n]);
+    yield /[^<>"'`\s.(){}[\]#=%$]*[^<>"'`\s.(){}[\]#=%:$]/g;
+  }
+  function F2(r) {
+    if (!r.includes("-[")) return r;
+    let e = 0, t = [], i = r.matchAll(R2);
+    i = Array.from(i).flatMap(n => {
+      let [, ...s] = n;
+      return s.map((a, o) => Object.assign([], n, { index: n.index + o, 0: a }));
+    });
+    for (let n of i) {
+      let s = n[0], a = t[t.length - 1];
+      if (s === a ? t.pop() : (s === "'" || s === "\"" || s === "`") && t.push(s), !a) {
+        if (s === "[") {
+          e++;
+          continue;
+        } else if (s === "]") {
+          e--;
+          continue;
+        }
+        if (e < 0) return r.substring(0, n.index - 1);
+        if (e === 0 && !M2.test(s)) return r.substring(0, n.index);
+      }
+    }
+    return r;
+  }
+  var R2,
+    M2,
+    lh = C(() => {
+      l();
+      De();
+      ah();
+      R2 = /([\[\]'"`])([^\[\]'"`])?/g, M2 = /[^"'`\s<>\]]+/;
+    });
+  function N2(r, e) {
+    let t = r.tailwindConfig.content.extract;
+    return t[e] || t.DEFAULT || fh[e] || fh.DEFAULT(r);
+  }
+  function L2(r, e) {
+    let t = r.content.transform;
+    return t[e] || t.DEFAULT || ch[e] || ch.DEFAULT;
+  }
+  function B2(r, e, t, i) {
+    Xr.has(e) || Xr.set(e, new uh.default({ maxSize: 25e3 }));
+    for (
+      let n of r.split(`
+`)
+    ) {
+      if (n = n.trim(), !i.has(n)) {
+        if (i.add(n), Xr.get(e).has(n)) for (let s of Xr.get(e).get(n)) t.add(s);
+        else {
+          let s = e(n).filter(o => o !== "!*"), a = new Set(s);
+          for (let o of a) t.add(o);
+          Xr.get(e).set(n, a);
+        }
+      }
+    }
+  }
+  function $2(r, e) {
+    let t = e.offsets.sort(r),
+      i = { base: new Set(), defaults: new Set(), components: new Set(), utilities: new Set(), variants: new Set() };
+    for (let [n, s] of t) i[n.layer].add(s);
+    return i;
+  }
+  function bo(r) {
+    return e => {
+      let t = { base: null, components: null, utilities: null, variants: null };
+      if (
+        e.walkAtRules(y => {
+          y.name === "tailwind" && Object.keys(t).includes(y.params) && (t[y.params] = y);
+        }), Object.values(t).every(y => y === null)
+      ) return e;
+      let i = new Set([...r.candidates ?? [], Ge]), n = new Set();
+      He.DEBUG && console.time("Reading changed files");
+      for (let { file: y, content: x, extension: b } of r.changedContent) {
+        let w = L2(r.tailwindConfig, b), k = N2(r, b);
+        x = y ? ie.readFileSync(y, "utf8") : x, B2(w(x), k, i, n);
+      }
+      He.DEBUG && console.timeEnd("Reading changed files");
+      let s = r.classCache.size;
+      He.DEBUG && console.time("Generate rules"), He.DEBUG && console.time("Sorting candidates");
+      let a = new Set([...i].sort((y, x) => y === x ? 0 : y < x ? -1 : 1));
+      He.DEBUG && console.timeEnd("Sorting candidates"),
+        bn(a, r),
+        He.DEBUG && console.timeEnd("Generate rules"),
+        He.DEBUG && console.time("Build stylesheet"),
+        (r.stylesheetCache === null || r.classCache.size !== s) && (r.stylesheetCache = $2([...r.ruleCache], r)),
+        He.DEBUG && console.timeEnd("Build stylesheet");
+      let { defaults: o, base: u, components: c, utilities: f, variants: p } = r.stylesheetCache;
+      t.base && (t.base.before(yt([...u, ...o], t.base.source, { layer: "base" })), t.base.remove()),
+        t.components
+        && (t.components.before(yt([...c], t.components.source, { layer: "components" })), t.components.remove()),
+        t.utilities
+        && (t.utilities.before(yt([...f], t.utilities.source, { layer: "utilities" })), t.utilities.remove());
+      let d = Array.from(p).filter(y => {
+        let x = y.raws.tailwind?.parentLayer;
+        return x === "components" ? t.components !== null : x === "utilities" ? t.utilities !== null : !0;
+      });
+      t.variants
+        ? (t.variants.before(yt(d, t.variants.source, { layer: "variants" })), t.variants.remove())
+        : d.length > 0 && e.append(yt(d, e.source, { layer: "variants" }));
+      let h = d.some(y => y.raws.tailwind?.parentLayer === "utilities");
+      t.utilities && f.size === 0 && !h
+      && N.warn("content-problems", [
+        "No utility classes were detected in your source files. If this is unexpected, double-check the `content` option in your Tailwind CSS configuration.",
+        "https://tailwindcss.com/docs/content-configuration",
+      ]),
+        He.DEBUG && (console.log("Potential classes: ", i.size), console.log("Active contexts: ", cn.size)),
+        r.changedContent = [],
+        e.walkAtRules("layer", y => {
+          Object.keys(t).includes(y.params) && y.remove();
+        });
+    };
+  }
+  var uh,
+    He,
+    fh,
+    ch,
+    Xr,
+    ph = C(() => {
+      l();
+      je();
+      uh = K(zn());
+      at();
+      wn();
+      Oe();
+      rh();
+      lh();
+      He = Pe, fh = { DEFAULT: oh }, ch = { DEFAULT: r => r, svelte: r => r.replace(/(?:^|\s)class:/g, " ") };
+      Xr = new WeakMap();
+    });
+  function En(r) {
+    let e = new Map();
+    j.root({ nodes: [r.clone()] }).walkRules(s => {
+      (0, On.default)(a => {
+        a.walkClasses(o => {
+          let u = o.parent.toString(), c = e.get(u);
+          c || e.set(u, c = new Set()), c.add(o.value);
+        });
+      }).processSync(s.selector);
+    });
+    let i = Array.from(e.values(), s => Array.from(s)), n = i.flat();
+    return Object.assign(n, { groups: i });
+  }
+  function wo(r) {
+    return j2.astSync(r);
+  }
+  function dh(r, e) {
+    let t = new Set();
+    for (let i of r) t.add(i.split(e).pop());
+    return Array.from(t);
+  }
+  function hh(r, e) {
+    let t = r.tailwindConfig.prefix;
+    return typeof t == "function" ? t(e) : t + e;
+  }
+  function* mh(r) {
+    for (yield r; r.parent;) yield r.parent, r = r.parent;
+  }
+  function z2(r, e = {}) {
+    let t = r.nodes;
+    r.nodes = [];
+    let i = r.clone(e);
+    return r.nodes = t, i;
+  }
+  function V2(r) {
+    for (let e of mh(r)) {
+      if (r !== e) {
+        if (e.type === "root") break;
+        r = z2(e, { nodes: [r] });
+      }
+    }
+    return r;
+  }
+  function U2(r, e) {
+    let t = new Map();
+    return r.walkRules(i => {
+      for (let a of mh(i)) if (a.raws.tailwind?.layer !== void 0) return;
+      let n = V2(i), s = e.offsets.create("user");
+      for (let a of En(i)) {
+        let o = t.get(a) || [];
+        t.set(a, o), o.push([{ layer: "user", sort: s, important: !1 }, n]);
+      }
+    }),
+      t;
+  }
+  function W2(r, e) {
+    for (let t of r) {
+      if (e.notClassCache.has(t) || e.applyClassCache.has(t)) continue;
+      if (e.classCache.has(t)) {
+        e.applyClassCache.set(t, e.classCache.get(t).map(([n, s]) => [n, s.clone()]));
+        continue;
+      }
+      let i = Array.from(gn(t, e));
+      if (i.length === 0) {
+        e.notClassCache.add(t);
+        continue;
+      }
+      e.applyClassCache.set(t, i);
+    }
+    return e.applyClassCache;
+  }
+  function G2(r) {
+    let e = null;
+    return { get: t => (e = e || r(), e.get(t)), has: t => (e = e || r(), e.has(t)) };
+  }
+  function H2(r) {
+    return { get: e => r.flatMap(t => t.get(e) || []), has: e => r.some(t => t.has(e)) };
+  }
+  function gh(r) {
+    let e = r.split(/[\s\t\n]+/g);
+    return e[e.length - 1] === "!important" ? [e.slice(0, -1), !0] : [e, !1];
+  }
+  function yh(r, e, t) {
+    let i = new Set(), n = [];
+    if (
+      r.walkAtRules("apply", u => {
+        let [c] = gh(u.params);
+        for (let f of c) i.add(f);
+        n.push(u);
+      }), n.length === 0
+    ) return;
+    let s = H2([t, W2(i, e)]);
+    function a(u, c, f) {
+      let p = wo(u), d = wo(c), y = wo(`.${ce(f)}`).nodes[0].nodes[0];
+      return p.each(x => {
+        let b = new Set();
+        d.each(w => {
+          let k = !1;
+          w = w.clone(),
+            w.walkClasses(S => {
+              S.value === y.value && (k || (S.replaceWith(...x.nodes.map(_ => _.clone())), b.add(w), k = !0));
+            });
+        });
+        for (let w of b) {
+          let k = [[]];
+          for (let S of w.nodes) S.type === "combinator" ? (k.push(S), k.push([])) : k[k.length - 1].push(S);
+          w.nodes = [];
+          for (let S of k) {
+            Array.isArray(S)
+            && S.sort((_, P) =>
+              _.type === "tag" && P.type === "class"
+                ? -1
+                : _.type === "class" && P.type === "tag"
+                ? 1
+                : _.type === "class" && P.type === "pseudo" && P.value.startsWith("::")
+                ? -1
+                : _.type === "pseudo" && _.value.startsWith("::") && P.type === "class"
+                ? 1
+                : 0
+            ), w.nodes = w.nodes.concat(S);
+          }
+        }
+        x.replaceWith(...b);
+      }),
+        p.toString();
+    }
+    let o = new Map();
+    for (let u of n) {
+      let [c] = o.get(u.parent) || [[], u.source];
+      o.set(u.parent, [c, u.source]);
+      let [f, p] = gh(u.params);
+      if (u.parent.type === "atrule") {
+        if (u.parent.name === "screen") {
+          let d = u.parent.params;
+          throw u.error(
+            `@apply is not supported within nested at-rules like @screen. We suggest you write this as @apply ${
+              f.map(h => `${d}:${h}`).join(" ")
+            } instead.`,
+          );
+        }
+        throw u.error(
+          `@apply is not supported within nested at-rules like @${u.parent.name}. You can fix this by un-nesting @${u.parent.name}.`,
+        );
+      }
+      for (let d of f) {
+        if ([hh(e, "group"), hh(e, "peer")].includes(d)) {
+          throw u.error(`@apply should not be used with the '${d}' utility`);
+        }
+        if (!s.has(d)) {
+          throw u.error(
+            `The \`${d}\` class does not exist. If \`${d}\` is a custom class, make sure it is defined within a \`@layer\` directive.`,
+          );
+        }
+        let h = s.get(d);
+        c.push([d, p, h]);
+      }
+    }
+    for (let [u, [c, f]] of o) {
+      let p = [];
+      for (let [h, y, x] of c) {
+        let b = [h, ...dh([h], e.tailwindConfig.separator)];
+        for (let [w, k] of x) {
+          let S = En(u), _ = En(k);
+          if (
+            _ = _.groups.filter(I => I.some(X => b.includes(X))).flat(),
+              _ = _.concat(dh(_, e.tailwindConfig.separator)),
+              S.some(I => _.includes(I))
+          ) throw k.error(`You cannot \`@apply\` the \`${h}\` utility here because it creates a circular dependency.`);
+          let M = j.root({ nodes: [k.clone()] });
+          M.walk(I => {
+            I.source = f;
+          }),
+            (k.type !== "atrule" || k.type === "atrule" && k.name !== "keyframes") && M.walkRules(I => {
+              if (!En(I).some(ee => ee === h)) {
+                I.remove();
+                return;
+              }
+              let X = typeof e.tailwindConfig.important == "string" ? e.tailwindConfig.important : null,
+                Q = u.raws.tailwind !== void 0 && X && u.selector.indexOf(X) === 0
+                  ? u.selector.slice(X.length)
+                  : u.selector;
+              I.selector = a(Q, I.selector, h),
+                X && Q !== u.selector && (I.selector = hn(I.selector, X)),
+                I.walkDecls(ee => {
+                  ee.important = w.important || y;
+                });
+              let Z = (0, On.default)().astSync(I.selector);
+              Z.each(ee => Ft(ee)), I.selector = Z.toString();
+            }),
+            !!M.nodes[0] && p.push([w.sort, M.nodes[0]]);
+        }
+      }
+      let d = e.offsets.sort(p).map(h => h[1]);
+      u.after(d);
+    }
+    for (let u of n) u.parent.nodes.length > 1 ? u.remove() : u.parent.remove();
+    yh(r, e, t);
+  }
+  function vo(r) {
+    return e => {
+      let t = G2(() => U2(e, r));
+      yh(e, r, t);
+    };
+  }
+  var On,
+    j2,
+    bh = C(() => {
+      l();
+      it();
+      On = K(Me());
+      wn();
+      Rt();
+      Ja();
+      pn();
+      j2 = (0, On.default)();
+    });
+  var wh = v((U3, Tn) => {
+    l();
+    (function() {
+      "use strict";
+      function r(i, n, s) {
+        if (!i) return null;
+        r.caseSensitive || (i = i.toLowerCase());
+        var a = r.threshold === null ? null : r.threshold * i.length, o = r.thresholdAbsolute, u;
+        a !== null && o !== null ? u = Math.min(a, o) : a !== null ? u = a : o !== null ? u = o : u = null;
+        var c, f, p, d, h, y = n.length;
+        for (h = 0; h < y; h++) {
+          if (
+            f = n[h],
+              s && (f = f[s]),
+              !!f
+              && (r.caseSensitive ? p = f : p = f.toLowerCase(),
+                d = t(i, p, u),
+                (u === null || d < u) && (u = d, s && r.returnWinningObject ? c = n[h] : c = f, r.returnFirstMatch))
+          ) return c;
+        }
+        return c || r.nullResultValue;
+      }
+      r.threshold = .4,
+        r.thresholdAbsolute = 20,
+        r.caseSensitive = !1,
+        r.nullResultValue = null,
+        r.returnWinningObject = null,
+        r.returnFirstMatch = !1,
+        typeof Tn != "undefined" && Tn.exports ? Tn.exports = r : window.didYouMean = r;
+      var e = Math.pow(2, 32) - 1;
+      function t(i, n, s) {
+        s = s || s === 0 ? s : e;
+        var a = i.length, o = n.length;
+        if (a === 0) return Math.min(s + 1, o);
+        if (o === 0) return Math.min(s + 1, a);
+        if (Math.abs(a - o) > s) return s + 1;
+        var u = [], c, f, p, d, h;
+        for (c = 0; c <= o; c++) u[c] = [c];
+        for (f = 0; f <= a; f++) u[0][f] = f;
+        for (c = 1; c <= o; c++) {
+          for (p = e, d = 1, c > s && (d = c - s), h = o + 1, h > s + c && (h = s + c), f = 1; f <= a; f++) {
+            f < d || f > h
+              ? u[c][f] = s + 1
+              : n.charAt(c - 1) === i.charAt(f - 1)
+              ? u[c][f] = u[c - 1][f - 1]
+              : u[c][f] = Math.min(u[c - 1][f - 1] + 1, Math.min(u[c][f - 1] + 1, u[c - 1][f] + 1)),
+              u[c][f] < p && (p = u[c][f]);
+          }
+          if (p > s) return s + 1;
+        }
+        return u[o][a];
+      }
+    })();
+  });
+  var xh = v((W3, vh) => {
+    l();
+    var xo = "(".charCodeAt(0),
+      ko = ")".charCodeAt(0),
+      Pn = "'".charCodeAt(0),
+      So = "\"".charCodeAt(0),
+      _o = "\\".charCodeAt(0),
+      $t = "/".charCodeAt(0),
+      Co = ",".charCodeAt(0),
+      Ao = ":".charCodeAt(0),
+      Dn = "*".charCodeAt(0),
+      Y2 = "u".charCodeAt(0),
+      Q2 = "U".charCodeAt(0),
+      J2 = "+".charCodeAt(0),
+      X2 = /^[a-f0-9?-]+$/i;
+    vh.exports = function(r) {
+      for (
+        var e = [],
+          t = r,
+          i,
+          n,
+          s,
+          a,
+          o,
+          u,
+          c,
+          f,
+          p = 0,
+          d = t.charCodeAt(p),
+          h = t.length,
+          y = [{ nodes: e }],
+          x = 0,
+          b,
+          w = "",
+          k = "",
+          S = "";
+        p < h;
+      ) {
+        if (d <= 32) {
+          i = p;
+          do i += 1, d = t.charCodeAt(i); while (d <= 32);
+          a = t.slice(p, i),
+            s = e[e.length - 1],
+            d === ko && x
+              ? S = a
+              : s && s.type === "div"
+              ? (s.after = a, s.sourceEndIndex += a.length)
+              : d === Co || d === Ao
+                  || d === $t && t.charCodeAt(i + 1) !== Dn && (!b || b && b.type === "function" && b.value !== "calc")
+              ? k = a
+              : e.push({ type: "space", sourceIndex: p, sourceEndIndex: i, value: a }),
+            p = i;
+        } else if (d === Pn || d === So) {
+          i = p, n = d === Pn ? "'" : "\"", a = { type: "string", sourceIndex: p, quote: n };
+          do if (o = !1, i = t.indexOf(n, i + 1), ~i) for (u = i; t.charCodeAt(u - 1) === _o;) u -= 1, o = !o;
+          else t += n, i = t.length - 1, a.unclosed = !0; while (o);
+          a.value = t.slice(p + 1, i),
+            a.sourceEndIndex = a.unclosed ? i : i + 1,
+            e.push(a),
+            p = i + 1,
+            d = t.charCodeAt(p);
+        } else if (d === $t && t.charCodeAt(p + 1) === Dn) {
+          i = t.indexOf("*/", p),
+            a = { type: "comment", sourceIndex: p, sourceEndIndex: i + 2 },
+            i === -1 && (a.unclosed = !0, i = t.length, a.sourceEndIndex = i),
+            a.value = t.slice(p + 2, i),
+            e.push(a),
+            p = i + 2,
+            d = t.charCodeAt(p);
+        } else if ((d === $t || d === Dn) && b && b.type === "function" && b.value === "calc") {
+          a = t[p],
+            e.push({ type: "word", sourceIndex: p - k.length, sourceEndIndex: p + a.length, value: a }),
+            p += 1,
+            d = t.charCodeAt(p);
+        } else if (d === $t || d === Co || d === Ao) {
+          a = t[p],
+            e.push({
+              type: "div",
+              sourceIndex: p - k.length,
+              sourceEndIndex: p + a.length,
+              value: a,
+              before: k,
+              after: "",
+            }),
+            k = "",
+            p += 1,
+            d = t.charCodeAt(p);
+        } else if (xo === d) {
+          i = p;
+          do i += 1, d = t.charCodeAt(i); while (d <= 32);
+          if (
+            f = p,
+              a = { type: "function", sourceIndex: p - w.length, value: w, before: t.slice(f + 1, i) },
+              p = i,
+              w === "url" && d !== Pn && d !== So
+          ) {
+            i -= 1;
+            do if (o = !1, i = t.indexOf(")", i + 1), ~i) for (u = i; t.charCodeAt(u - 1) === _o;) u -= 1, o = !o;
+            else t += ")", i = t.length - 1, a.unclosed = !0; while (o);
+            c = i;
+            do c -= 1, d = t.charCodeAt(c); while (d <= 32);
+            f < c
+              ? (p !== c + 1
+                ? a.nodes = [{ type: "word", sourceIndex: p, sourceEndIndex: c + 1, value: t.slice(p, c + 1) }]
+                : a.nodes = [],
+                a.unclosed && c + 1 !== i
+                  ? (a.after = "",
+                    a.nodes.push({ type: "space", sourceIndex: c + 1, sourceEndIndex: i, value: t.slice(c + 1, i) }))
+                  : (a.after = t.slice(c + 1, i), a.sourceEndIndex = i))
+              : (a.after = "", a.nodes = []),
+              p = i + 1,
+              a.sourceEndIndex = a.unclosed ? i : p,
+              d = t.charCodeAt(p),
+              e.push(a);
+          } else x += 1, a.after = "", a.sourceEndIndex = p + 1, e.push(a), y.push(a), e = a.nodes = [], b = a;
+          w = "";
+        } else if (ko === d && x) {
+          p += 1,
+            d = t.charCodeAt(p),
+            b.after = S,
+            b.sourceEndIndex += S.length,
+            S = "",
+            x -= 1,
+            y[y.length - 1].sourceEndIndex = p,
+            y.pop(),
+            b = y[x],
+            e = b.nodes;
+        } else {
+          i = p;
+          do d === _o && (i += 1), i += 1, d = t.charCodeAt(i); while (
+            i < h
+            && !(d <= 32 || d === Pn || d === So || d === Co || d === Ao || d === $t || d === xo
+              || d === Dn && b && b.type === "function" && b.value === "calc"
+              || d === $t && b.type === "function" && b.value === "calc" || d === ko && x)
+          );
+          a = t.slice(p, i),
+            xo === d
+              ? w = a
+              : (Y2 === a.charCodeAt(0) || Q2 === a.charCodeAt(0)) && J2 === a.charCodeAt(1) && X2.test(a.slice(2))
+              ? e.push({ type: "unicode-range", sourceIndex: p, sourceEndIndex: i, value: a })
+              : e.push({ type: "word", sourceIndex: p, sourceEndIndex: i, value: a }),
+            p = i;
+        }
+      }
+      for (p = y.length - 1; p; p -= 1) y[p].unclosed = !0, y[p].sourceEndIndex = t.length;
+      return y[0].nodes;
+    };
+  });
+  var Sh = v((G3, kh) => {
+    l();
+    kh.exports = function r(e, t, i) {
+      var n, s, a, o;
+      for (n = 0, s = e.length; n < s; n += 1) {
+        a = e[n],
+          i || (o = t(a, n, e)),
+          o !== !1 && a.type === "function" && Array.isArray(a.nodes) && r(a.nodes, t, i),
+          i && t(a, n, e);
+      }
+    };
+  });
+  var Oh = v((H3, Ah) => {
+    l();
+    function _h(r, e) {
+      var t = r.type, i = r.value, n, s;
+      return e && (s = e(r)) !== void 0
+        ? s
+        : t === "word" || t === "space"
+        ? i
+        : t === "string"
+        ? (n = r.quote || "", n + i + (r.unclosed ? "" : n))
+        : t === "comment"
+        ? "/*" + i + (r.unclosed ? "" : "*/")
+        : t === "div"
+        ? (r.before || "") + i + (r.after || "")
+        : Array.isArray(r.nodes)
+        ? (n = Ch(r.nodes, e),
+          t !== "function" ? n : i + "(" + (r.before || "") + n + (r.after || "") + (r.unclosed ? "" : ")"))
+        : i;
+    }
+    function Ch(r, e) {
+      var t, i;
+      if (Array.isArray(r)) {
+        for (t = "", i = r.length - 1; ~i; i -= 1) t = _h(r[i], e) + t;
+        return t;
+      }
+      return _h(r, e);
+    }
+    Ah.exports = Ch;
+  });
+  var Th = v((Y3, Eh) => {
+    l();
+    var In = "-".charCodeAt(0),
+      qn = "+".charCodeAt(0),
+      Oo = ".".charCodeAt(0),
+      K2 = "e".charCodeAt(0),
+      Z2 = "E".charCodeAt(0);
+    function e_(r) {
+      var e = r.charCodeAt(0), t;
+      if (e === qn || e === In) {
+        if (t = r.charCodeAt(1), t >= 48 && t <= 57) return !0;
+        var i = r.charCodeAt(2);
+        return t === Oo && i >= 48 && i <= 57;
+      }
+      return e === Oo ? (t = r.charCodeAt(1), t >= 48 && t <= 57) : e >= 48 && e <= 57;
+    }
+    Eh.exports = function(r) {
+      var e = 0, t = r.length, i, n, s;
+      if (t === 0 || !e_(r)) return !1;
+      for (i = r.charCodeAt(e), (i === qn || i === In) && e++; e < t && (i = r.charCodeAt(e), !(i < 48 || i > 57));) {
+        e += 1;
+      }
+      if (i = r.charCodeAt(e), n = r.charCodeAt(e + 1), i === Oo && n >= 48 && n <= 57) {
+        for (e += 2; e < t && (i = r.charCodeAt(e), !(i < 48 || i > 57));) {
+          e += 1;
+        }
+      }
+      if (
+        i = r.charCodeAt(e),
+          n = r.charCodeAt(e + 1),
+          s = r.charCodeAt(e + 2),
+          (i === K2 || i === Z2) && (n >= 48 && n <= 57 || (n === qn || n === In) && s >= 48 && s <= 57)
+      ) for (e += n === qn || n === In ? 3 : 2; e < t && (i = r.charCodeAt(e), !(i < 48 || i > 57));) e += 1;
+      return { number: r.slice(0, e), unit: r.slice(e) };
+    };
+  });
+  var Kr = v((Q3, Ih) => {
+    l();
+    var t_ = xh(), Ph = Sh(), Dh = Oh();
+    function lt(r) {
+      return this instanceof lt ? (this.nodes = t_(r), this) : new lt(r);
+    }
+    lt.prototype.toString = function() {
+      return Array.isArray(this.nodes) ? Dh(this.nodes) : "";
+    };
+    lt.prototype.walk = function(r, e) {
+      return Ph(this.nodes, r, e), this;
+    };
+    lt.unit = Th();
+    lt.walk = Ph;
+    lt.stringify = Dh;
+    Ih.exports = lt;
+  });
+  function To(r) {
+    return typeof r == "object" && r !== null;
+  }
+  function r_(r, e) {
+    let t = Xe(e);
+    do if (t.pop(), (0, Zr.default)(r, t) !== void 0) break; while (t.length);
+    return t.length ? t : void 0;
+  }
+  function jt(r) {
+    return typeof r == "string"
+      ? r
+      : r.reduce((e, t, i) => t.includes(".") ? `${e}[${t}]` : i === 0 ? t : `${e}.${t}`, "");
+  }
+  function Rh(r) {
+    return r.map(e => `'${e}'`).join(", ");
+  }
+  function Mh(r) {
+    return Rh(Object.keys(r));
+  }
+  function Po(r, e, t, i = {}) {
+    let n = Array.isArray(e) ? jt(e) : e.replace(/^['"]+|['"]+$/g, ""),
+      s = Array.isArray(e) ? e : Xe(n),
+      a = (0, Zr.default)(r.theme, s, t);
+    if (a === void 0) {
+      let u = `'${n}' does not exist in your theme config.`, c = s.slice(0, -1), f = (0, Zr.default)(r.theme, c);
+      if (To(f)) {
+        let p = Object.keys(f).filter(h => Po(r, [...c, h]).isValid), d = (0, qh.default)(s[s.length - 1], p);
+        d
+          ? u += ` Did you mean '${jt([...c, d])}'?`
+          : p.length > 0 && (u += ` '${jt(c)}' has the following valid keys: ${Rh(p)}`);
+      } else {
+        let p = r_(r.theme, n);
+        if (p) {
+          let d = (0, Zr.default)(r.theme, p);
+          To(d) ? u += ` '${jt(p)}' has the following keys: ${Mh(d)}` : u += ` '${jt(p)}' is not an object.`;
+        } else u += ` Your theme has the following top-level keys: ${Mh(r.theme)}`;
+      }
+      return { isValid: !1, error: u };
+    }
+    if (
+      !(typeof a == "string" || typeof a == "number" || typeof a == "function" || a instanceof String
+        || a instanceof Number || Array.isArray(a))
+    ) {
+      let u = `'${n}' was found but does not resolve to a string.`;
+      if (To(a)) {
+        let c = Object.keys(a).filter(f => Po(r, [...s, f]).isValid);
+        c.length && (u += ` Did you mean something like '${jt([...s, c[0]])}'?`);
+      }
+      return { isValid: !1, error: u };
+    }
+    let [o] = s;
+    return { isValid: !0, value: We(o)(a, i) };
+  }
+  function i_(r, e, t) {
+    e = e.map(n => Fh(r, n, t));
+    let i = [""];
+    for (let n of e) n.type === "div" && n.value === "," ? i.push("") : i[i.length - 1] += Eo.default.stringify(n);
+    return i;
+  }
+  function Fh(r, e, t) {
+    if (e.type === "function" && t[e.value] !== void 0) {
+      let i = i_(r, e.nodes, t);
+      e.type = "word", e.value = t[e.value](r, ...i);
+    }
+    return e;
+  }
+  function n_(r, e, t) {
+    return (0, Eo.default)(e).walk(i => {
+      Fh(r, i, t);
+    }).toString();
+  }
+  function* a_(r) {
+    r = r.replace(/^['"]+|['"]+$/g, "");
+    let e = r.match(/^([^\s]+)(?![^\[]*\])(?:\s*\/\s*([^\/\s]+))$/), t;
+    yield [r, void 0], e && (r = e[1], t = e[2], yield [r, t]);
+  }
+  function o_(r, e, t) {
+    let i = Array.from(a_(e)).map(([n, s]) =>
+      Object.assign(Po(r, n, t, { opacityValue: s }), { resolvedPath: n, alpha: s })
+    );
+    return i.find(n => n.isValid) ?? i[0];
+  }
+  function Nh(r) {
+    let e = r.tailwindConfig,
+      t = {
+        theme: (i, n, ...s) => {
+          let { isValid: a, value: o, error: u, alpha: c } = o_(e, n, s.length ? s : void 0);
+          if (!a) {
+            let d = i.parent, h = d?.raws.tailwind?.candidate;
+            if (d && h !== void 0) {
+              r.markInvalidUtilityNode(d),
+                d.remove(),
+                N.warn("invalid-theme-key-in-class", [
+                  `The utility \`${h}\` contains an invalid theme value and was not generated.`,
+                ]);
+              return;
+            }
+            throw i.error(u);
+          }
+          let f = xt(o), p = f !== void 0 && typeof f == "function";
+          return (c !== void 0 || p) && (c === void 0 && (c = 1), o = Ie(f, c, f)), o;
+        },
+        screen: (i, n) => {
+          n = n.replace(/^['"]+/g, "").replace(/['"]+$/g, "");
+          let a = st(e.theme.screens).find(({ name: o }) => o === n);
+          if (!a) throw i.error(`The '${n}' screen does not exist in your theme.`);
+          return nt(a);
+        },
+      };
+    return i => {
+      i.walk(n => {
+        let s = s_[n.type];
+        s !== void 0 && (n[s] = n_(n, n[s], t));
+      });
+    };
+  }
+  var Zr,
+    qh,
+    Eo,
+    s_,
+    Lh = C(() => {
+      l();
+      Zr = K(Is()), qh = K(wh());
+      Wr();
+      Eo = K(Kr());
+      un();
+      an();
+      oi();
+      nr();
+      ur();
+      Oe();
+      s_ = { atrule: "params", decl: "value" };
+    });
+  function Bh({ tailwindConfig: { theme: r } }) {
+    return function(e) {
+      e.walkAtRules("screen", t => {
+        let i = t.params, s = st(r.screens).find(({ name: a }) => a === i);
+        if (!s) throw t.error(`No \`${i}\` screen found.`);
+        t.name = "media", t.params = nt(s);
+      });
+    };
+  }
+  var $h = C(() => {
+    l();
+    un();
+    an();
+  });
+  function l_(r) {
+    let e = r.filter(o =>
+        o.type !== "pseudo" || o.nodes.length > 0
+          ? !0
+          : o.value.startsWith("::") || [":before", ":after", ":first-line", ":first-letter"].includes(o.value)
+      ).reverse(),
+      t = new Set(["tag", "class", "id", "attribute"]),
+      i = e.findIndex(o => t.has(o.type));
+    if (i === -1) return e.reverse().join("").trim();
+    let n = e[i], s = jh[n.type] ? jh[n.type](n) : n;
+    e = e.slice(0, i);
+    let a = e.findIndex(o => o.type === "combinator" && o.value === ">");
+    return a !== -1 && (e.splice(0, a), e.unshift(Rn.default.universal())), [s, ...e.reverse()].join("").trim();
+  }
+  function f_(r) {
+    return Do.has(r) || Do.set(r, u_.transformSync(r)), Do.get(r);
+  }
+  function Io({ tailwindConfig: r }) {
+    return e => {
+      let t = new Map(), i = new Set();
+      if (
+        e.walkAtRules("defaults", n => {
+          if (n.nodes && n.nodes.length > 0) {
+            i.add(n);
+            return;
+          }
+          let s = n.params;
+          t.has(s) || t.set(s, new Set()), t.get(s).add(n.parent), n.remove();
+        }), J(r, "optimizeUniversalDefaults")
+      ) {
+        for (let n of i) {
+          let s = new Map(), a = t.get(n.params) ?? [];
+          for (let o of a) {
+            for (let u of f_(o.selector)) {
+              let c = u.includes(":-") || u.includes("::-") ? u : "__DEFAULT__", f = s.get(c) ?? new Set();
+              s.set(c, f), f.add(u);
+            }
+          }
+          if (J(r, "optimizeUniversalDefaults")) {
+            if (s.size === 0) {
+              n.remove();
+              continue;
+            }
+            for (let [, o] of s) {
+              let u = j.rule({ source: n.source });
+              u.selectors = [...o], u.append(n.nodes.map(c => c.clone())), n.before(u);
+            }
+          }
+          n.remove();
+        }
+      } else if (i.size) {
+        let n = j.rule({ selectors: ["*", "::before", "::after"] });
+        for (let a of i) n.append(a.nodes), n.parent || a.before(n), n.source || (n.source = a.source), a.remove();
+        let s = n.clone({ selectors: ["::backdrop"] });
+        n.after(s);
+      }
+    };
+  }
+  var Rn,
+    jh,
+    u_,
+    Do,
+    zh = C(() => {
+      l();
+      it();
+      Rn = K(Me());
+      De();
+      jh = {
+        id(r) {
+          return Rn.default.attribute({ attribute: "id", operator: "=", value: r.value, quoteMark: "\"" });
+        },
+      };
+      u_ = (0, Rn.default)(r =>
+        r.map(e => {
+          let t = e.split(i => i.type === "combinator" && i.value === " ").pop();
+          return l_(t);
+        })
+      ), Do = new Map();
+    });
+  function qo() {
+    function r(e) {
+      let t = null;
+      e.each(i => {
+        if (!c_.has(i.type)) {
+          t = null;
+          return;
+        }
+        if (t === null) {
+          t = i;
+          return;
+        }
+        let n = Vh[i.type];
+        i.type === "atrule" && i.name === "font-face"
+          ? t = i
+          : n.every(s => (i[s] ?? "").replace(/\s+/g, " ") === (t[s] ?? "").replace(/\s+/g, " "))
+          ? (i.nodes && t.append(i.nodes), i.remove())
+          : t = i;
+      }),
+        e.each(i => {
+          i.type === "atrule" && r(i);
+        });
+    }
+    return e => {
+      r(e);
+    };
+  }
+  var Vh,
+    c_,
+    Uh = C(() => {
+      l();
+      Vh = { atrule: ["name", "params"], rule: ["selector"] }, c_ = new Set(Object.keys(Vh));
+    });
+  function Ro() {
+    return r => {
+      r.walkRules(e => {
+        let t = new Map(), i = new Set([]), n = new Map();
+        e.walkDecls(s => {
+          if (s.parent === e) {
+            if (t.has(s.prop)) {
+              if (t.get(s.prop).value === s.value) {
+                i.add(t.get(s.prop)), t.set(s.prop, s);
+                return;
+              }
+              n.has(s.prop) || n.set(s.prop, new Set()), n.get(s.prop).add(t.get(s.prop)), n.get(s.prop).add(s);
+            }
+            t.set(s.prop, s);
+          }
+        });
+        for (let s of i) s.remove();
+        for (let s of n.values()) {
+          let a = new Map();
+          for (let o of s) {
+            let u = d_(o.value);
+            u !== null && (a.has(u) || a.set(u, new Set()), a.get(u).add(o));
+          }
+          for (let o of a.values()) {
+            let u = Array.from(o).slice(0, -1);
+            for (let c of u) c.remove();
+          }
+        }
+      });
+    };
+  }
+  function d_(r) {
+    let e = /^-?\d*.?\d+([\w%]+)?$/g.exec(r);
+    return e ? e[1] ?? p_ : null;
+  }
+  var p_,
+    Wh = C(() => {
+      l();
+      p_ = Symbol("unitless-number");
+    });
+  function h_(r) {
+    if (!r.walkAtRules) return;
+    let e = new Set();
+    if (
+      r.walkAtRules("apply", t => {
+        e.add(t.parent);
+      }), e.size !== 0
+    ) {
+      for (let t of e) {
+        let i = [], n = [];
+        for (let s of t.nodes) {
+          s.type === "atrule" && s.name === "apply"
+            ? (n.length > 0 && (i.push(n), n = []), i.push([s]))
+            : n.push(s);
+        }
+        if (n.length > 0 && i.push(n), i.length !== 1) {
+          for (let s of [...i].reverse()) {
+            let a = t.clone({ nodes: [] });
+            a.append(s), t.after(a);
+          }
+          t.remove();
+        }
+      }
+    }
+  }
+  function Mn() {
+    return r => {
+      h_(r);
+    };
+  }
+  var Gh = C(() => {
+    l();
+  });
+  function m_(r) {
+    return r.type === "root";
+  }
+  function g_(r) {
+    return r.type === "atrule" && r.name === "layer";
+  }
+  function Hh(r) {
+    return (e, t) => {
+      let i = !1;
+      e.walkAtRules("tailwind", n => {
+        if (i) return !1;
+        if (n.parent && !(m_(n.parent) || g_(n.parent))) {
+          return i = !0,
+            n.warn(
+              t,
+              [
+                "Nested @tailwind rules were detected, but are not supported.",
+                "Consider using a prefix to scope Tailwind's classes: https://tailwindcss.com/docs/configuration#prefix",
+                "Alternatively, use the important selector strategy: https://tailwindcss.com/docs/configuration#selector-strategy",
+              ].join(`
+`),
+            ),
+            !1;
+        }
+      }),
+        e.walkRules(n => {
+          if (i) return !1;
+          n.walkRules(
+            s => (i = !0,
+              s.warn(
+                t,
+                [
+                  "Nested CSS was detected, but CSS nesting has not been configured correctly.",
+                  "Please enable a CSS nesting plugin *before* Tailwind in your configuration.",
+                  "See how here: https://tailwindcss.com/docs/using-with-preprocessors#nesting",
+                ].join(`
+`),
+              ),
+              !1),
+          );
+        });
+    };
+  }
+  var Yh = C(() => {
+    l();
+  });
+  function Fn(r) {
+    return function(e, t) {
+      let { tailwindDirectives: i, applyDirectives: n } = go(e);
+      Hh()(e, t), Mn()(e, t);
+      let s = r({
+        tailwindDirectives: i,
+        applyDirectives: n,
+        registerDependency(a) {
+          t.messages.push({ plugin: "tailwindcss", parent: t.opts.from, ...a });
+        },
+        createContext(a, o) {
+          return ao(a, o, e);
+        },
+      })(e, t);
+      if (s.tailwindConfig.separator === "-") {
+        throw new Error(
+          "The '-' character cannot be used as a custom separator in JIT mode due to parsing ambiguity. Please use another character like '_' instead.",
+        );
+      }
+      fu(s.tailwindConfig),
+        bo(s)(e, t),
+        Mn()(e, t),
+        vo(s)(e, t),
+        Nh(s)(e, t),
+        Bh(s)(e, t),
+        Io(s)(e, t),
+        qo(s)(e, t),
+        Ro(s)(e, t);
+    };
+  }
+  var Qh = C(() => {
+    l();
+    th();
+    ph();
+    bh();
+    Lh();
+    $h();
+    zh();
+    Uh();
+    Wh();
+    Gh();
+    Yh();
+    xn();
+    De();
+  });
+  function Jh(r, e) {
+    let t = null, i = null;
+    return r.walkAtRules("config", n => {
+      if (i = n.source?.input.file ?? e.opts.from ?? null, i === null) {
+        throw n.error("The `@config` directive cannot be used without setting `from` in your PostCSS config.");
+      }
+      if (t) throw n.error("Only one `@config` directive is allowed per file.");
+      let s = n.params.match(/(['"])(.*?)\1/);
+      if (!s) throw n.error("A path is required when using the `@config` directive.");
+      let a = s[2];
+      if (te.isAbsolute(a)) throw n.error("The `@config` directive cannot be used with an absolute path.");
+      if (t = te.resolve(te.dirname(i), a), !ie.existsSync(t)) {
+        throw n.error(`The config file at "${a}" does not exist. Make sure the path is correct and the file exists.`);
+      }
+      n.remove();
+    }),
+      t || null;
+  }
+  var Xh = C(() => {
+    l();
+    je();
+    dt();
+  });
+  var Kh = v((RD, Mo) => {
+    l();
+    eh();
+    Qh();
+    at();
+    Xh();
+    Mo.exports = function(e) {
+      return {
+        postcssPlugin: "tailwindcss",
+        plugins: [
+          Pe.DEBUG && function(t) {
+            return console.log(`
+`),
+              console.time("JIT TOTAL"),
+              t;
+          },
+          function(t, i) {
+            e = Jh(t, i) ?? e;
+            let n = mo(e);
+            if (t.type === "document") {
+              let s = t.nodes.filter(a => a.type === "root");
+              for (let a of s) a.type === "root" && Fn(n)(a, i);
+              return;
+            }
+            Fn(n)(t, i);
+          },
+          !1,
+          Pe.DEBUG && function(t) {
+            return console.timeEnd("JIT TOTAL"),
+              console.log(`
+`),
+              t;
+          },
+        ].filter(Boolean),
+      };
+    };
+    Mo.exports.postcss = !0;
+  });
+  var em = v((MD, Zh) => {
+    l();
+    Zh.exports = Kh();
+  });
+  var Fo = v((FD, tm) => {
+    l();
+    tm.exports = () => [
+      "and_chr 92",
+      "and_uc 12.12",
+      "chrome 92",
+      "chrome 91",
+      "edge 91",
+      "firefox 89",
+      "ios_saf 14.5-14.7",
+      "ios_saf 14.0-14.4",
+      "safari 14.1",
+      "samsung 14.0",
+    ];
+  });
+  var Nn = {};
+  Ce(Nn, { agents: () => y_, feature: () => b_ });
+  function b_() {
+    return {
+      status: "cr",
+      title: "CSS Feature Queries",
+      stats: {
+        ie: { "6": "n", "7": "n", "8": "n", "9": "n", "10": "n", "11": "n", "5.5": "n" },
+        edge: {
+          "12": "y",
+          "13": "y",
+          "14": "y",
+          "15": "y",
+          "16": "y",
+          "17": "y",
+          "18": "y",
+          "79": "y",
+          "80": "y",
+          "81": "y",
+          "83": "y",
+          "84": "y",
+          "85": "y",
+          "86": "y",
+          "87": "y",
+          "88": "y",
+          "89": "y",
+          "90": "y",
+          "91": "y",
+          "92": "y",
+        },
+        firefox: {
+          "2": "n",
+          "3": "n",
+          "4": "n",
+          "5": "n",
+          "6": "n",
+          "7": "n",
+          "8": "n",
+          "9": "n",
+          "10": "n",
+          "11": "n",
+          "12": "n",
+          "13": "n",
+          "14": "n",
+          "15": "n",
+          "16": "n",
+          "17": "n",
+          "18": "n",
+          "19": "n",
+          "20": "n",
+          "21": "n",
+          "22": "y",
+          "23": "y",
+          "24": "y",
+          "25": "y",
+          "26": "y",
+          "27": "y",
+          "28": "y",
+          "29": "y",
+          "30": "y",
+          "31": "y",
+          "32": "y",
+          "33": "y",
+          "34": "y",
+          "35": "y",
+          "36": "y",
+          "37": "y",
+          "38": "y",
+          "39": "y",
+          "40": "y",
+          "41": "y",
+          "42": "y",
+          "43": "y",
+          "44": "y",
+          "45": "y",
+          "46": "y",
+          "47": "y",
+          "48": "y",
+          "49": "y",
+          "50": "y",
+          "51": "y",
+          "52": "y",
+          "53": "y",
+          "54": "y",
+          "55": "y",
+          "56": "y",
+          "57": "y",
+          "58": "y",
+          "59": "y",
+          "60": "y",
+          "61": "y",
+          "62": "y",
+          "63": "y",
+          "64": "y",
+          "65": "y",
+          "66": "y",
+          "67": "y",
+          "68": "y",
+          "69": "y",
+          "70": "y",
+          "71": "y",
+          "72": "y",
+          "73": "y",
+          "74": "y",
+          "75": "y",
+          "76": "y",
+          "77": "y",
+          "78": "y",
+          "79": "y",
+          "80": "y",
+          "81": "y",
+          "82": "y",
+          "83": "y",
+          "84": "y",
+          "85": "y",
+          "86": "y",
+          "87": "y",
+          "88": "y",
+          "89": "y",
+          "90": "y",
+          "91": "y",
+          "92": "y",
+          "93": "y",
+          "3.5": "n",
+          "3.6": "n",
+        },
+        chrome: {
+          "4": "n",
+          "5": "n",
+          "6": "n",
+          "7": "n",
+          "8": "n",
+          "9": "n",
+          "10": "n",
+          "11": "n",
+          "12": "n",
+          "13": "n",
+          "14": "n",
+          "15": "n",
+          "16": "n",
+          "17": "n",
+          "18": "n",
+          "19": "n",
+          "20": "n",
+          "21": "n",
+          "22": "n",
+          "23": "n",
+          "24": "n",
+          "25": "n",
+          "26": "n",
+          "27": "n",
+          "28": "y",
+          "29": "y",
+          "30": "y",
+          "31": "y",
+          "32": "y",
+          "33": "y",
+          "34": "y",
+          "35": "y",
+          "36": "y",
+          "37": "y",
+          "38": "y",
+          "39": "y",
+          "40": "y",
+          "41": "y",
+          "42": "y",
+          "43": "y",
+          "44": "y",
+          "45": "y",
+          "46": "y",
+          "47": "y",
+          "48": "y",
+          "49": "y",
+          "50": "y",
+          "51": "y",
+          "52": "y",
+          "53": "y",
+          "54": "y",
+          "55": "y",
+          "56": "y",
+          "57": "y",
+          "58": "y",
+          "59": "y",
+          "60": "y",
+          "61": "y",
+          "62": "y",
+          "63": "y",
+          "64": "y",
+          "65": "y",
+          "66": "y",
+          "67": "y",
+          "68": "y",
+          "69": "y",
+          "70": "y",
+          "71": "y",
+          "72": "y",
+          "73": "y",
+          "74": "y",
+          "75": "y",
+          "76": "y",
+          "77": "y",
+          "78": "y",
+          "79": "y",
+          "80": "y",
+          "81": "y",
+          "83": "y",
+          "84": "y",
+          "85": "y",
+          "86": "y",
+          "87": "y",
+          "88": "y",
+          "89": "y",
+          "90": "y",
+          "91": "y",
+          "92": "y",
+          "93": "y",
+          "94": "y",
+          "95": "y",
+        },
+        safari: {
+          "4": "n",
+          "5": "n",
+          "6": "n",
+          "7": "n",
+          "8": "n",
+          "9": "y",
+          "10": "y",
+          "11": "y",
+          "12": "y",
+          "13": "y",
+          "14": "y",
+          "15": "y",
+          "9.1": "y",
+          "10.1": "y",
+          "11.1": "y",
+          "12.1": "y",
+          "13.1": "y",
+          "14.1": "y",
+          TP: "y",
+          "3.1": "n",
+          "3.2": "n",
+          "5.1": "n",
+          "6.1": "n",
+          "7.1": "n",
+        },
+        opera: {
+          "9": "n",
+          "11": "n",
+          "12": "n",
+          "15": "y",
+          "16": "y",
+          "17": "y",
+          "18": "y",
+          "19": "y",
+          "20": "y",
+          "21": "y",
+          "22": "y",
+          "23": "y",
+          "24": "y",
+          "25": "y",
+          "26": "y",
+          "27": "y",
+          "28": "y",
+          "29": "y",
+          "30": "y",
+          "31": "y",
+          "32": "y",
+          "33": "y",
+          "34": "y",
+          "35": "y",
+          "36": "y",
+          "37": "y",
+          "38": "y",
+          "39": "y",
+          "40": "y",
+          "41": "y",
+          "42": "y",
+          "43": "y",
+          "44": "y",
+          "45": "y",
+          "46": "y",
+          "47": "y",
+          "48": "y",
+          "49": "y",
+          "50": "y",
+          "51": "y",
+          "52": "y",
+          "53": "y",
+          "54": "y",
+          "55": "y",
+          "56": "y",
+          "57": "y",
+          "58": "y",
+          "60": "y",
+          "62": "y",
+          "63": "y",
+          "64": "y",
+          "65": "y",
+          "66": "y",
+          "67": "y",
+          "68": "y",
+          "69": "y",
+          "70": "y",
+          "71": "y",
+          "72": "y",
+          "73": "y",
+          "74": "y",
+          "75": "y",
+          "76": "y",
+          "77": "y",
+          "78": "y",
+          "12.1": "y",
+          "9.5-9.6": "n",
+          "10.0-10.1": "n",
+          "10.5": "n",
+          "10.6": "n",
+          "11.1": "n",
+          "11.5": "n",
+          "11.6": "n",
+        },
+        ios_saf: {
+          "8": "n",
+          "9.0-9.2": "y",
+          "9.3": "y",
+          "10.0-10.2": "y",
+          "10.3": "y",
+          "11.0-11.2": "y",
+          "11.3-11.4": "y",
+          "12.0-12.1": "y",
+          "12.2-12.4": "y",
+          "13.0-13.1": "y",
+          "13.2": "y",
+          "13.3": "y",
+          "13.4-13.7": "y",
+          "14.0-14.4": "y",
+          "14.5-14.7": "y",
+          "3.2": "n",
+          "4.0-4.1": "n",
+          "4.2-4.3": "n",
+          "5.0-5.1": "n",
+          "6.0-6.1": "n",
+          "7.0-7.1": "n",
+          "8.1-8.4": "n",
+        },
+        op_mini: { all: "y" },
+        android: {
+          "3": "n",
+          "4": "n",
+          "92": "y",
+          "4.4": "y",
+          "4.4.3-4.4.4": "y",
+          "2.1": "n",
+          "2.2": "n",
+          "2.3": "n",
+          "4.1": "n",
+          "4.2-4.3": "n",
+        },
+        bb: { "7": "n", "10": "n" },
+        op_mob: { "10": "n", "11": "n", "12": "n", "64": "y", "11.1": "n", "11.5": "n", "12.1": "n" },
+        and_chr: { "92": "y" },
+        and_ff: { "90": "y" },
+        ie_mob: { "10": "n", "11": "n" },
+        and_uc: { "12.12": "y" },
+        samsung: {
+          "4": "y",
+          "5.0-5.4": "y",
+          "6.2-6.4": "y",
+          "7.2-7.4": "y",
+          "8.2": "y",
+          "9.2": "y",
+          "10.1": "y",
+          "11.1-11.2": "y",
+          "12.0": "y",
+          "13.0": "y",
+          "14.0": "y",
+        },
+        and_qq: { "10.4": "y" },
+        baidu: { "7.12": "y" },
+        kaios: { "2.5": "y" },
+      },
+    };
+  }
+  var y_,
+    Ln = C(() => {
+      l();
+      y_ = {
+        ie: { prefix: "ms" },
+        edge: {
+          prefix: "webkit",
+          prefix_exceptions: { "12": "ms", "13": "ms", "14": "ms", "15": "ms", "16": "ms", "17": "ms", "18": "ms" },
+        },
+        firefox: { prefix: "moz" },
+        chrome: { prefix: "webkit" },
+        safari: { prefix: "webkit" },
+        opera: {
+          prefix: "webkit",
+          prefix_exceptions: {
+            "9": "o",
+            "11": "o",
+            "12": "o",
+            "9.5-9.6": "o",
+            "10.0-10.1": "o",
+            "10.5": "o",
+            "10.6": "o",
+            "11.1": "o",
+            "11.5": "o",
+            "11.6": "o",
+            "12.1": "o",
+          },
+        },
+        ios_saf: { prefix: "webkit" },
+        op_mini: { prefix: "o" },
+        android: { prefix: "webkit" },
+        bb: { prefix: "webkit" },
+        op_mob: { prefix: "o", prefix_exceptions: { "64": "webkit" } },
+        and_chr: { prefix: "webkit" },
+        and_ff: { prefix: "moz" },
+        ie_mob: { prefix: "ms" },
+        and_uc: { prefix: "webkit", prefix_exceptions: { "12.12": "webkit" } },
+        samsung: { prefix: "webkit" },
+        and_qq: { prefix: "webkit" },
+        baidu: { prefix: "webkit" },
+        kaios: { prefix: "moz" },
+      };
+    });
+  var rm = v(() => {
+    l();
+  });
+  var ue = v((BD, ut) => {
+    l();
+    var { list: No } = me();
+    ut.exports.error = function(r) {
+      let e = new Error(r);
+      throw e.autoprefixer = !0, e;
+    };
+    ut.exports.uniq = function(r) {
+      return [...new Set(r)];
+    };
+    ut.exports.removeNote = function(r) {
+      return r.includes(" ") ? r.split(" ")[0] : r;
+    };
+    ut.exports.escapeRegexp = function(r) {
+      return r.replace(/[$()*+-.?[\\\]^{|}]/g, "\\$&");
+    };
+    ut.exports.regexp = function(r, e = !0) {
+      return e && (r = this.escapeRegexp(r)), new RegExp(`(^|[\\s,(])(${r}($|[\\s(,]))`, "gi");
+    };
+    ut.exports.editList = function(r, e) {
+      let t = No.comma(r), i = e(t, []);
+      if (t === i) return r;
+      let n = r.match(/,\s*/);
+      return n = n ? n[0] : ", ", i.join(n);
+    };
+    ut.exports.splitSelector = function(r) {
+      return No.comma(r).map(e => No.space(e).map(t => t.split(/(?=\.|#)/g)));
+    };
+  });
+  var ft = v(($D, sm) => {
+    l();
+    var w_ = Fo(),
+      im = (Ln(), Nn).agents,
+      v_ = ue(),
+      nm = class {
+        static prefixes() {
+          if (this.prefixesCache) return this.prefixesCache;
+          this.prefixesCache = [];
+          for (let e in im) this.prefixesCache.push(`-${im[e].prefix}-`);
+          return this.prefixesCache = v_.uniq(this.prefixesCache).sort((e, t) => t.length - e.length),
+            this.prefixesCache;
+        }
+        static withPrefix(e) {
+          return this.prefixesRegexp || (this.prefixesRegexp = new RegExp(this.prefixes().join("|"))),
+            this.prefixesRegexp.test(e);
+        }
+        constructor(e, t, i, n) {
+          this.data = e, this.options = i || {}, this.browserslistOpts = n || {}, this.selected = this.parse(t);
+        }
+        parse(e) {
+          let t = {};
+          for (let i in this.browserslistOpts) t[i] = this.browserslistOpts[i];
+          return t.path = this.options.from, w_(e, t);
+        }
+        prefix(e) {
+          let [t, i] = e.split(" "), n = this.data[t], s = n.prefix_exceptions && n.prefix_exceptions[i];
+          return s || (s = n.prefix), `-${s}-`;
+        }
+        isSelected(e) {
+          return this.selected.includes(e);
+        }
+      };
+    sm.exports = nm;
+  });
+  var ei = v((jD, am) => {
+    l();
+    am.exports = {
+      prefix(r) {
+        let e = r.match(/^(-\w+-)/);
+        return e ? e[0] : "";
+      },
+      unprefixed(r) {
+        return r.replace(/^-\w+-/, "");
+      },
+    };
+  });
+  var zt = v((zD, lm) => {
+    l();
+    var x_ = ft(), om = ei(), k_ = ue();
+    function Lo(r, e) {
+      let t = new r.constructor();
+      for (let i of Object.keys(r || {})) {
+        let n = r[i];
+        i === "parent" && typeof n == "object"
+          ? e && (t[i] = e)
+          : i === "source" || i === null
+          ? t[i] = n
+          : Array.isArray(n)
+          ? t[i] = n.map(s => Lo(s, t))
+          : i !== "_autoprefixerPrefix" && i !== "_autoprefixerValues" && i !== "proxyCache"
+            && (typeof n == "object" && n !== null && (n = Lo(n, t)), t[i] = n);
+      }
+      return t;
+    }
+    var Bn = class {
+      static hack(e) {
+        return this.hacks || (this.hacks = {}), e.names.map(t => (this.hacks[t] = e, this.hacks[t]));
+      }
+      static load(e, t, i) {
+        let n = this.hacks && this.hacks[e];
+        return n ? new n(e, t, i) : new this(e, t, i);
+      }
+      static clone(e, t) {
+        let i = Lo(e);
+        for (let n in t) i[n] = t[n];
+        return i;
+      }
+      constructor(e, t, i) {
+        this.prefixes = t, this.name = e, this.all = i;
+      }
+      parentPrefix(e) {
+        let t;
+        return typeof e._autoprefixerPrefix != "undefined"
+          ? t = e._autoprefixerPrefix
+          : e.type === "decl" && e.prop[0] === "-"
+          ? t = om.prefix(e.prop)
+          : e.type === "root"
+          ? t = !1
+          : e.type === "rule" && e.selector.includes(":-") && /:(-\w+-)/.test(e.selector)
+          ? t = e.selector.match(/:(-\w+-)/)[1]
+          : e.type === "atrule" && e.name[0] === "-"
+          ? t = om.prefix(e.name)
+          : t = this.parentPrefix(e.parent),
+          x_.prefixes().includes(t) || (t = !1),
+          e._autoprefixerPrefix = t,
+          e._autoprefixerPrefix;
+      }
+      process(e, t) {
+        if (!this.check(e)) return;
+        let i = this.parentPrefix(e), n = this.prefixes.filter(a => !i || i === k_.removeNote(a)), s = [];
+        for (let a of n) this.add(e, a, s.concat([a]), t) && s.push(a);
+        return s;
+      }
+      clone(e, t) {
+        return Bn.clone(e, t);
+      }
+    };
+    lm.exports = Bn;
+  });
+  var q = v((VD, cm) => {
+    l();
+    var S_ = zt(),
+      __ = ft(),
+      um = ue(),
+      fm = class extends S_ {
+        check() {
+          return !0;
+        }
+        prefixed(e, t) {
+          return t + e;
+        }
+        normalize(e) {
+          return e;
+        }
+        otherPrefixes(e, t) {
+          for (let i of __.prefixes()) if (i !== t && e.includes(i)) return !0;
+          return !1;
+        }
+        set(e, t) {
+          return e.prop = this.prefixed(e.prop, t), e;
+        }
+        needCascade(e) {
+          return e._autoprefixerCascade
+            || (e._autoprefixerCascade = this.all.options.cascade !== !1 && e.raw("before").includes(`
+`)),
+            e._autoprefixerCascade;
+        }
+        maxPrefixed(e, t) {
+          if (t._autoprefixerMax) return t._autoprefixerMax;
+          let i = 0;
+          for (let n of e) n = um.removeNote(n), n.length > i && (i = n.length);
+          return t._autoprefixerMax = i, t._autoprefixerMax;
+        }
+        calcBefore(e, t, i = "") {
+          let s = this.maxPrefixed(e, t) - um.removeNote(i).length, a = t.raw("before");
+          return s > 0 && (a += Array(s).fill(" ").join("")), a;
+        }
+        restoreBefore(e) {
+          let t = e.raw("before").split(`
+`),
+            i = t[t.length - 1];
+          this.all.group(e).up(n => {
+            let s = n.raw("before").split(`
+`),
+              a = s[s.length - 1];
+            a.length < i.length && (i = a);
+          }),
+            t[t.length - 1] = i,
+            e.raws.before = t.join(`
+`);
+        }
+        insert(e, t, i) {
+          let n = this.set(this.clone(e), t);
+          if (!(!n || e.parent.some(a => a.prop === n.prop && a.value === n.value))) {
+            return this.needCascade(e) && (n.raws.before = this.calcBefore(i, e, t)), e.parent.insertBefore(e, n);
+          }
+        }
+        isAlready(e, t) {
+          let i = this.all.group(e).up(n => n.prop === t);
+          return i || (i = this.all.group(e).down(n => n.prop === t)), i;
+        }
+        add(e, t, i, n) {
+          let s = this.prefixed(e.prop, t);
+          if (!(this.isAlready(e, s) || this.otherPrefixes(e.value, t))) return this.insert(e, t, i, n);
+        }
+        process(e, t) {
+          if (!this.needCascade(e)) {
+            super.process(e, t);
+            return;
+          }
+          let i = super.process(e, t);
+          !i || !i.length || (this.restoreBefore(e), e.raws.before = this.calcBefore(i, e));
+        }
+        old(e, t) {
+          return [this.prefixed(e, t)];
+        }
+      };
+    cm.exports = fm;
+  });
+  var dm = v((UD, pm) => {
+    l();
+    pm.exports = function r(e) {
+      return { mul: t => new r(e * t), div: t => new r(e / t), simplify: () => new r(e), toString: () => e.toString() };
+    };
+  });
+  var gm = v((WD, mm) => {
+    l();
+    var C_ = dm(),
+      A_ = zt(),
+      Bo = ue(),
+      O_ = /(min|max)-resolution\s*:\s*\d*\.?\d+(dppx|dpcm|dpi|x)/gi,
+      E_ = /(min|max)-resolution(\s*:\s*)(\d*\.?\d+)(dppx|dpcm|dpi|x)/i,
+      hm = class extends A_ {
+        prefixName(e, t) {
+          return e === "-moz-" ? t + "--moz-device-pixel-ratio" : e + t + "-device-pixel-ratio";
+        }
+        prefixQuery(e, t, i, n, s) {
+          return n = new C_(n),
+            s === "dpi" ? n = n.div(96) : s === "dpcm" && (n = n.mul(2.54).div(96)),
+            n = n.simplify(),
+            e === "-o-" && (n = n.n + "/" + n.d),
+            this.prefixName(e, t) + i + n;
+        }
+        clean(e) {
+          if (!this.bad) {
+            this.bad = [];
+            for (let t of this.prefixes) {
+              this.bad.push(this.prefixName(t, "min")), this.bad.push(this.prefixName(t, "max"));
+            }
+          }
+          e.params = Bo.editList(e.params, t => t.filter(i => this.bad.every(n => !i.includes(n))));
+        }
+        process(e) {
+          let t = this.parentPrefix(e), i = t ? [t] : this.prefixes;
+          e.params = Bo.editList(e.params, (n, s) => {
+            for (let a of n) {
+              if (!a.includes("min-resolution") && !a.includes("max-resolution")) {
+                s.push(a);
+                continue;
+              }
+              for (let o of i) {
+                let u = a.replace(O_, c => {
+                  let f = c.match(E_);
+                  return this.prefixQuery(o, f[1], f[2], f[3], f[4]);
+                });
+                s.push(u);
+              }
+              s.push(a);
+            }
+            return Bo.uniq(s);
+          });
+        }
+      };
+    mm.exports = hm;
+  });
+  var xm = v((GD, vm) => {
+    l();
+    var { list: T_ } = me(),
+      ym = Kr(),
+      P_ = ft(),
+      bm = ei(),
+      wm = class {
+        constructor(e) {
+          this.props = ["transition", "transition-property"], this.prefixes = e;
+        }
+        add(e, t) {
+          let i,
+            n,
+            s = this.prefixes.add[e.prop],
+            a = this.ruleVendorPrefixes(e),
+            o = a || s && s.prefixes || [],
+            u = this.parse(e.value),
+            c = u.map(h => this.findProp(h)),
+            f = [];
+          if (c.some(h => h[0] === "-")) return;
+          for (let h of u) {
+            if (n = this.findProp(h), n[0] === "-") continue;
+            let y = this.prefixes.add[n];
+            if (!(!y || !y.prefixes)) {
+              for (i of y.prefixes) {
+                if (a && !a.some(b => i.includes(b))) continue;
+                let x = this.prefixes.prefixed(n, i);
+                x !== "-ms-transform" && !c.includes(x) && (this.disabled(n, i) || f.push(this.clone(n, x, h)));
+              }
+            }
+          }
+          u = u.concat(f);
+          let p = this.stringify(u), d = this.stringify(this.cleanFromUnprefixed(u, "-webkit-"));
+          if (
+            o.includes("-webkit-") && this.cloneBefore(e, `-webkit-${e.prop}`, d),
+              this.cloneBefore(e, e.prop, d),
+              o.includes("-o-")
+          ) {
+            let h = this.stringify(this.cleanFromUnprefixed(u, "-o-"));
+            this.cloneBefore(e, `-o-${e.prop}`, h);
+          }
+          for (i of o) {
+            if (i !== "-webkit-" && i !== "-o-") {
+              let h = this.stringify(this.cleanOtherPrefixes(u, i));
+              this.cloneBefore(e, i + e.prop, h);
+            }
+          }
+          p !== e.value && !this.already(e, e.prop, p) && (this.checkForWarning(t, e), e.cloneBefore(), e.value = p);
+        }
+        findProp(e) {
+          let t = e[0].value;
+          if (/^\d/.test(t)) for (let [i, n] of e.entries()) if (i !== 0 && n.type === "word") return n.value;
+          return t;
+        }
+        already(e, t, i) {
+          return e.parent.some(n => n.prop === t && n.value === i);
+        }
+        cloneBefore(e, t, i) {
+          this.already(e, t, i) || e.cloneBefore({ prop: t, value: i });
+        }
+        checkForWarning(e, t) {
+          if (t.prop !== "transition-property") return;
+          let i = !1, n = !1;
+          t.parent.each(s => {
+            if (s.type !== "decl" || s.prop.indexOf("transition-") !== 0) return;
+            let a = T_.comma(s.value);
+            if (s.prop === "transition-property") {
+              a.forEach(o => {
+                let u = this.prefixes.add[o];
+                u && u.prefixes && u.prefixes.length > 0 && (i = !0);
+              });
+              return;
+            }
+            return n = n || a.length > 1, !1;
+          }),
+            i && n
+            && t.warn(
+              e,
+              "Replace transition-property to transition, because Autoprefixer could not support any cases of transition-property and other transition-*",
+            );
+        }
+        remove(e) {
+          let t = this.parse(e.value);
+          t = t.filter(a => {
+            let o = this.prefixes.remove[this.findProp(a)];
+            return !o || !o.remove;
+          });
+          let i = this.stringify(t);
+          if (e.value === i) return;
+          if (t.length === 0) {
+            e.remove();
+            return;
+          }
+          let n = e.parent.some(a => a.prop === e.prop && a.value === i),
+            s = e.parent.some(a => a !== e && a.prop === e.prop && a.value.length > i.length);
+          if (n || s) {
+            e.remove();
+            return;
+          }
+          e.value = i;
+        }
+        parse(e) {
+          let t = ym(e), i = [], n = [];
+          for (let s of t.nodes) n.push(s), s.type === "div" && s.value === "," && (i.push(n), n = []);
+          return i.push(n), i.filter(s => s.length > 0);
+        }
+        stringify(e) {
+          if (e.length === 0) return "";
+          let t = [];
+          for (let i of e) i[i.length - 1].type !== "div" && i.push(this.div(e)), t = t.concat(i);
+          return t[0].type === "div" && (t = t.slice(1)),
+            t[t.length - 1].type === "div" && (t = t.slice(0, -2 + 1 || void 0)),
+            ym.stringify({ nodes: t });
+        }
+        clone(e, t, i) {
+          let n = [], s = !1;
+          for (let a of i) {
+            !s && a.type === "word" && a.value === e
+              ? (n.push({ type: "word", value: t }), s = !0)
+              : n.push(a);
+          }
+          return n;
+        }
+        div(e) {
+          for (let t of e) for (let i of t) if (i.type === "div" && i.value === ",") return i;
+          return { type: "div", value: ",", after: " " };
+        }
+        cleanOtherPrefixes(e, t) {
+          return e.filter(i => {
+            let n = bm.prefix(this.findProp(i));
+            return n === "" || n === t;
+          });
+        }
+        cleanFromUnprefixed(e, t) {
+          let i = e.map(s => this.findProp(s)).filter(s => s.slice(0, t.length) === t).map(s =>
+              this.prefixes.unprefixed(s)
+            ),
+            n = [];
+          for (let s of e) {
+            let a = this.findProp(s), o = bm.prefix(a);
+            !i.includes(a) && (o === t || o === "") && n.push(s);
+          }
+          return n;
+        }
+        disabled(e, t) {
+          let i = ["order", "justify-content", "align-self", "align-content"];
+          if (e.includes("flex") || i.includes(e)) {
+            if (this.prefixes.options.flexbox === !1) return !0;
+            if (this.prefixes.options.flexbox === "no-2009") return t.includes("2009");
+          }
+        }
+        ruleVendorPrefixes(e) {
+          let { parent: t } = e;
+          if (t.type !== "rule") return !1;
+          if (!t.selector.includes(":-")) return !1;
+          let i = P_.prefixes().filter(n => t.selector.includes(":" + n));
+          return i.length > 0 ? i : !1;
+        }
+      };
+    vm.exports = wm;
+  });
+  var Vt = v((HD, Sm) => {
+    l();
+    var D_ = ue(),
+      km = class {
+        constructor(e, t, i, n) {
+          this.unprefixed = e, this.prefixed = t, this.string = i || t, this.regexp = n || D_.regexp(t);
+        }
+        check(e) {
+          return e.includes(this.string) ? !!e.match(this.regexp) : !1;
+        }
+      };
+    Sm.exports = km;
+  });
+  var ke = v((YD, Cm) => {
+    l();
+    var I_ = zt(),
+      q_ = Vt(),
+      R_ = ei(),
+      M_ = ue(),
+      _m = class extends I_ {
+        static save(e, t) {
+          let i = t.prop, n = [];
+          for (let s in t._autoprefixerValues) {
+            let a = t._autoprefixerValues[s];
+            if (a === t.value) continue;
+            let o, u = R_.prefix(i);
+            if (u === "-pie-") continue;
+            if (u === s) {
+              o = t.value = a, n.push(o);
+              continue;
+            }
+            let c = e.prefixed(i, s), f = t.parent;
+            if (!f.every(y => y.prop !== c)) {
+              n.push(o);
+              continue;
+            }
+            let p = a.replace(/\s+/, " ");
+            if (f.some(y => y.prop === t.prop && y.value.replace(/\s+/, " ") === p)) {
+              n.push(o);
+              continue;
+            }
+            let h = this.clone(t, { value: a });
+            o = t.parent.insertBefore(t, h), n.push(o);
+          }
+          return n;
+        }
+        check(e) {
+          let t = e.value;
+          return t.includes(this.name) ? !!t.match(this.regexp()) : !1;
+        }
+        regexp() {
+          return this.regexpCache || (this.regexpCache = M_.regexp(this.name));
+        }
+        replace(e, t) {
+          return e.replace(this.regexp(), `$1${t}$2`);
+        }
+        value(e) {
+          return e.raws.value && e.raws.value.value === e.value ? e.raws.value.raw : e.value;
+        }
+        add(e, t) {
+          e._autoprefixerValues || (e._autoprefixerValues = {});
+          let i = e._autoprefixerValues[t] || this.value(e), n;
+          do if (n = i, i = this.replace(i, t), i === !1) return; while (i !== n);
+          e._autoprefixerValues[t] = i;
+        }
+        old(e) {
+          return new q_(this.name, e + this.name);
+        }
+      };
+    Cm.exports = _m;
+  });
+  var ct = v((QD, Am) => {
+    l();
+    Am.exports = {};
+  });
+  var jo = v((JD, Tm) => {
+    l();
+    var Om = Kr(),
+      F_ = ke(),
+      N_ = ct().insertAreas,
+      L_ = /(^|[^-])linear-gradient\(\s*(top|left|right|bottom)/i,
+      B_ = /(^|[^-])radial-gradient\(\s*\d+(\w*|%)\s+\d+(\w*|%)\s*,/i,
+      $_ = /(!\s*)?autoprefixer:\s*ignore\s+next/i,
+      j_ = /(!\s*)?autoprefixer\s*grid:\s*(on|off|(no-)?autoplace)/i,
+      z_ = [
+        "width",
+        "height",
+        "min-width",
+        "max-width",
+        "min-height",
+        "max-height",
+        "inline-size",
+        "min-inline-size",
+        "max-inline-size",
+        "block-size",
+        "min-block-size",
+        "max-block-size",
+      ];
+    function $o(r) {
+      return r.parent.some(e => e.prop === "grid-template" || e.prop === "grid-template-areas");
+    }
+    function V_(r) {
+      let e = r.parent.some(i => i.prop === "grid-template-rows"),
+        t = r.parent.some(i => i.prop === "grid-template-columns");
+      return e && t;
+    }
+    var Em = class {
+      constructor(e) {
+        this.prefixes = e;
+      }
+      add(e, t) {
+        let i = this.prefixes.add["@resolution"],
+          n = this.prefixes.add["@keyframes"],
+          s = this.prefixes.add["@viewport"],
+          a = this.prefixes.add["@supports"];
+        e.walkAtRules(f => {
+          if (f.name === "keyframes") {
+            if (!this.disabled(f, t)) return n && n.process(f);
+            else if (f.name === "viewport") {
+              if (!this.disabled(f, t)) return s && s.process(f);
+              else if (f.name === "supports") {
+                if (this.prefixes.options.supports !== !1 && !this.disabled(f, t)) return a.process(f);
+              } else if (f.name === "media" && f.params.includes("-resolution") && !this.disabled(f, t)) {
+                return i && i.process(f);
+              }
+            }
+          }
+        }),
+          e.walkRules(f => {
+            if (!this.disabled(f, t)) return this.prefixes.add.selectors.map(p => p.process(f, t));
+          });
+        function o(f) {
+          return f.parent.nodes.some(p => {
+            if (p.type !== "decl") return !1;
+            let d = p.prop === "display" && /(inline-)?grid/.test(p.value),
+              h = p.prop.startsWith("grid-template"),
+              y = /^grid-([A-z]+-)?gap/.test(p.prop);
+            return d || h || y;
+          });
+        }
+        function u(f) {
+          return f.parent.some(p => p.prop === "display" && /(inline-)?flex/.test(p.value));
+        }
+        let c = this.gridStatus(e, t) && this.prefixes.add["grid-area"] && this.prefixes.add["grid-area"].prefixes;
+        return e.walkDecls(f => {
+          if (this.disabledDecl(f, t)) return;
+          let p = f.parent, d = f.prop, h = f.value;
+          if (d === "grid-row-span") {
+            t.warn("grid-row-span is not part of final Grid Layout. Use grid-row.", { node: f });
+            return;
+          } else if (d === "grid-column-span") {
+            t.warn("grid-column-span is not part of final Grid Layout. Use grid-column.", { node: f });
+            return;
+          } else if (d === "display" && h === "box") {
+            t.warn("You should write display: flex by final spec instead of display: box", { node: f });
+            return;
+          } else if (d === "text-emphasis-position") {
+            (h === "under" || h === "over")
+              && t.warn(
+                "You should use 2 values for text-emphasis-position For example, `under left` instead of just `under`.",
+                { node: f },
+              );
+          } else if (/^(align|justify|place)-(items|content)$/.test(d) && u(f)) {
+            (h === "start" || h === "end")
+              && t.warn(`${h} value has mixed support, consider using flex-${h} instead`, { node: f });
+          } else if (d === "text-decoration-skip" && h === "ink") {
+            t.warn(
+              "Replace text-decoration-skip: ink to text-decoration-skip-ink: auto, because spec had been changed",
+              { node: f },
+            );
+          } else {
+            if (c && this.gridStatus(f, t)) {
+              if (
+                f.value === "subgrid" && t.warn("IE does not support subgrid", { node: f }),
+                  /^(align|justify|place)-items$/.test(d) && o(f)
+              ) {
+                let x = d.replace("-items", "-self");
+                t.warn(
+                  `IE does not support ${d} on grid containers. Try using ${x} on child elements instead: ${f.parent.selector} > * { ${x}: ${f.value} }`,
+                  { node: f },
+                );
+              } else if (/^(align|justify|place)-content$/.test(d) && o(f)) {
+                t.warn(`IE does not support ${f.prop} on grid containers`, { node: f });
+              } else if (d === "display" && f.value === "contents") {
+                t.warn("Please do not use display: contents; if you have grid setting enabled", { node: f });
+                return;
+              } else if (f.prop === "grid-gap") {
+                let x = this.gridStatus(f, t);
+                x === "autoplace" && !V_(f) && !$o(f)
+                  ? t.warn(
+                    "grid-gap only works if grid-template(-areas) is being used or both rows and columns have been declared and cells have not been manually placed inside the explicit grid",
+                    { node: f },
+                  )
+                  : (x === !0 || x === "no-autoplace") && !$o(f)
+                    && t.warn("grid-gap only works if grid-template(-areas) is being used", { node: f });
+              } else if (d === "grid-auto-columns") {
+                t.warn("grid-auto-columns is not supported by IE", { node: f });
+                return;
+              } else if (d === "grid-auto-rows") {
+                t.warn("grid-auto-rows is not supported by IE", { node: f });
+                return;
+              } else if (d === "grid-auto-flow") {
+                let x = p.some(w => w.prop === "grid-template-rows"),
+                  b = p.some(w => w.prop === "grid-template-columns");
+                $o(f)
+                  ? t.warn("grid-auto-flow is not supported by IE", { node: f })
+                  : h.includes("dense")
+                  ? t.warn("grid-auto-flow: dense is not supported by IE", { node: f })
+                  : !x && !b
+                    && t.warn(
+                      "grid-auto-flow works only if grid-template-rows and grid-template-columns are present in the same rule",
+                      { node: f },
+                    );
+                return;
+              } else if (h.includes("auto-fit")) {
+                t.warn("auto-fit value is not supported by IE", { node: f, word: "auto-fit" });
+                return;
+              } else if (h.includes("auto-fill")) {
+                t.warn("auto-fill value is not supported by IE", { node: f, word: "auto-fill" });
+                return;
+              } else {d.startsWith("grid-template") && h.includes("[")
+                  && t.warn(
+                    "Autoprefixer currently does not support line names. Try using grid-template-areas instead.",
+                    { node: f, word: "[" },
+                  );}
+            }
+            if (h.includes("radial-gradient")) {
+              if (B_.test(f.value)) {
+                t.warn(
+                  "Gradient has outdated direction syntax. New syntax is like `closest-side at 0 0` instead of `0 0, closest-side`.",
+                  { node: f },
+                );
+              } else {
+                let x = Om(h);
+                for (let b of x.nodes) {
+                  if (b.type === "function" && b.value === "radial-gradient") {
+                    for (let w of b.nodes) {
+                      w.type === "word" && (w.value === "cover"
+                        ? t.warn("Gradient has outdated direction syntax. Replace `cover` to `farthest-corner`.", {
+                          node: f,
+                        })
+                        : w.value === "contain"
+                          && t.warn("Gradient has outdated direction syntax. Replace `contain` to `closest-side`.", {
+                            node: f,
+                          }));
+                    }
+                  }
+                }
+              }
+            }
+            h.includes("linear-gradient") && L_.test(h)
+              && t.warn("Gradient has outdated direction syntax. New syntax is like `to left` instead of `right`.", {
+                node: f,
+              });
+          }
+          z_.includes(f.prop)
+            && (f.value.includes("-fill-available")
+              || (f.value.includes("fill-available")
+                ? t.warn("Replace fill-available to stretch, because spec had been changed", { node: f })
+                : f.value.includes("fill") && Om(h).nodes.some(b => b.type === "word" && b.value === "fill")
+                  && t.warn("Replace fill to stretch, because spec had been changed", { node: f })));
+          let y;
+          if (f.prop === "transition" || f.prop === "transition-property") return this.prefixes.transition.add(f, t);
+          if (f.prop === "align-self") {
+            if (
+              this.displayType(f) !== "grid" && this.prefixes.options.flexbox !== !1
+              && (y = this.prefixes.add["align-self"], y && y.prefixes && y.process(f)),
+                this.gridStatus(f, t) !== !1 && (y = this.prefixes.add["grid-row-align"], y && y.prefixes)
+            ) return y.process(f, t);
+          } else if (f.prop === "justify-self") {
+            if (this.gridStatus(f, t) !== !1 && (y = this.prefixes.add["grid-column-align"], y && y.prefixes)) {
+              return y.process(f, t);
+            }
+          } else if (f.prop === "place-self") {
+            if (y = this.prefixes.add["place-self"], y && y.prefixes && this.gridStatus(f, t) !== !1) {
+              return y.process(f, t);
+            }
+          } else if (y = this.prefixes.add[f.prop], y && y.prefixes) return y.process(f, t);
+        }),
+          this.gridStatus(e, t) && N_(e, this.disabled),
+          e.walkDecls(f => {
+            if (this.disabledValue(f, t)) return;
+            let p = this.prefixes.unprefixed(f.prop), d = this.prefixes.values("add", p);
+            if (Array.isArray(d)) for (let h of d) h.process && h.process(f, t);
+            F_.save(this.prefixes, f);
+          });
+      }
+      remove(e, t) {
+        let i = this.prefixes.remove["@resolution"];
+        e.walkAtRules((n, s) => {
+          this.prefixes.remove[`@${n.name}`]
+            ? this.disabled(n, t) || n.parent.removeChild(s)
+            : n.name === "media" && n.params.includes("-resolution") && i && i.clean(n);
+        });
+        for (let n of this.prefixes.remove.selectors) {
+          e.walkRules((s, a) => {
+            n.check(s) && (this.disabled(s, t) || s.parent.removeChild(a));
+          });
+        }
+        return e.walkDecls((n, s) => {
+          if (this.disabled(n, t)) return;
+          let a = n.parent, o = this.prefixes.unprefixed(n.prop);
+          if (
+            (n.prop === "transition" || n.prop === "transition-property") && this.prefixes.transition.remove(n),
+              this.prefixes.remove[n.prop] && this.prefixes.remove[n.prop].remove
+          ) {
+            let u = this.prefixes.group(n).down(c => this.prefixes.normalize(c.prop) === o);
+            if (o === "flex-flow" && (u = !0), n.prop === "-webkit-box-orient") {
+              let c = { "flex-direction": !0, "flex-flow": !0 };
+              if (!n.parent.some(f => c[f.prop])) return;
+            }
+            if (u && !this.withHackValue(n)) {
+              n.raw("before").includes(`
+`) && this.reduceSpaces(n), a.removeChild(s);
+              return;
+            }
+          }
+          for (let u of this.prefixes.values("remove", o)) {
+            if (!u.check || !u.check(n.value)) continue;
+            if (o = u.unprefixed, this.prefixes.group(n).down(f => f.value.includes(o))) {
+              a.removeChild(s);
+              return;
+            }
+          }
+        });
+      }
+      withHackValue(e) {
+        return e.prop === "-webkit-background-clip" && e.value === "text";
+      }
+      disabledValue(e, t) {
+        return this.gridStatus(e, t) === !1 && e.type === "decl" && e.prop === "display" && e.value.includes("grid")
+            || this.prefixes.options.flexbox === !1 && e.type === "decl" && e.prop === "display"
+              && e.value.includes("flex")
+            || e.type === "decl" && e.prop === "content"
+          ? !0
+          : this.disabled(e, t);
+      }
+      disabledDecl(e, t) {
+        if (
+          this.gridStatus(e, t) === !1 && e.type === "decl" && (e.prop.includes("grid") || e.prop === "justify-items")
+        ) return !0;
+        if (this.prefixes.options.flexbox === !1 && e.type === "decl") {
+          let i = ["order", "justify-content", "align-items", "align-content"];
+          if (e.prop.includes("flex") || i.includes(e.prop)) return !0;
+        }
+        return this.disabled(e, t);
+      }
+      disabled(e, t) {
+        if (!e) return !1;
+        if (e._autoprefixerDisabled !== void 0) return e._autoprefixerDisabled;
+        if (e.parent) {
+          let n = e.prev();
+          if (n && n.type === "comment" && $_.test(n.text)) {
+            return e._autoprefixerDisabled = !0, e._autoprefixerSelfDisabled = !0, !0;
+          }
+        }
+        let i = null;
+        if (e.nodes) {
+          let n;
+          e.each(s => {
+            s.type === "comment" && /(!\s*)?autoprefixer:\s*(off|on)/i.test(s.text)
+              && (typeof n != "undefined"
+                ? t.warn(
+                  "Second Autoprefixer control comment was ignored. Autoprefixer applies control comment to whole block, not to next rules.",
+                  { node: s },
+                )
+                : n = /on/i.test(s.text));
+          }), n !== void 0 && (i = !n);
+        }
+        if (!e.nodes || i === null) {
+          if (e.parent) {
+            let n = this.disabled(e.parent, t);
+            e.parent._autoprefixerSelfDisabled === !0 ? i = !1 : i = n;
+          } else i = !1;
+        }
+        return e._autoprefixerDisabled = i, i;
+      }
+      reduceSpaces(e) {
+        let t = !1;
+        if (this.prefixes.group(e).up(() => (t = !0, !0)), t) return;
+        let i = e.raw("before").split(`
+`),
+          n = i[i.length - 1].length,
+          s = !1;
+        this.prefixes.group(e).down(a => {
+          i = a.raw("before").split(`
+`);
+          let o = i.length - 1;
+          i[o].length > n && (s === !1 && (s = i[o].length - n),
+            i[o] = i[o].slice(0, -s),
+            a.raws.before = i.join(`
+`));
+        });
+      }
+      displayType(e) {
+        for (let t of e.parent.nodes) {
+          if (t.prop === "display") {
+            if (t.value.includes("flex")) return "flex";
+            if (t.value.includes("grid")) return "grid";
+          }
+        }
+        return !1;
+      }
+      gridStatus(e, t) {
+        if (!e) return !1;
+        if (e._autoprefixerGridStatus !== void 0) return e._autoprefixerGridStatus;
+        let i = null;
+        if (e.nodes) {
+          let n;
+          e.each(s => {
+            if (s.type === "comment" && j_.test(s.text)) {
+              let a = /:\s*autoplace/i.test(s.text), o = /no-autoplace/i.test(s.text);
+              typeof n != "undefined"
+                ? t.warn(
+                  "Second Autoprefixer grid control comment was ignored. Autoprefixer applies control comments to the whole block, not to the next rules.",
+                  { node: s },
+                )
+                : a
+                ? n = "autoplace"
+                : o
+                ? n = !0
+                : n = /on/i.test(s.text);
+            }
+          }), n !== void 0 && (i = n);
+        }
+        if (e.type === "atrule" && e.name === "supports") {
+          let n = e.params;
+          n.includes("grid") && n.includes("auto") && (i = !1);
+        }
+        if (!e.nodes || i === null) {
+          if (e.parent) {
+            let n = this.gridStatus(e.parent, t);
+            e.parent._autoprefixerSelfDisabled === !0 ? i = !1 : i = n;
+          } else {typeof this.prefixes.options.grid != "undefined"
+              ? i = this.prefixes.options.grid
+              : typeof m.env.AUTOPREFIXER_GRID != "undefined"
+              ? m.env.AUTOPREFIXER_GRID === "autoplace" ? i = "autoplace" : i = !0
+              : i = !1;}
+        }
+        return e._autoprefixerGridStatus = i, i;
+      }
+    };
+    Tm.exports = Em;
+  });
+  var Dm = v((XD, Pm) => {
+    l();
+    Pm.exports = {
+      A: {
+        A: { "2": "J D E F A B iB" },
+        B: { "1": "C K L G M N O R S T U V W X Y Z a P b H" },
+        C: {
+          "1":
+            "0 1 2 3 4 5 6 7 8 9 g h i j k l m n o p q r s t u v w x y z AB BB CB DB EB FB GB bB HB cB IB JB Q KB LB MB NB OB PB QB RB SB TB UB VB WB XB R S T kB U V W X Y Z a P b H dB",
+          "2": "jB aB I c J D E F A B C K L G M N O d e f lB mB",
+        },
+        D: {
+          "1":
+            "0 1 2 3 4 5 6 7 8 9 m n o p q r s t u v w x y z AB BB CB DB EB FB GB bB HB cB IB JB Q KB LB MB NB OB PB QB RB SB TB UB VB WB XB R S T U V W X Y Z a P b H dB nB oB",
+          "2": "I c J D E F A B C K L G M N O d e f g h i j k l",
+        },
+        E: { "1": "F A B C K L G tB fB YB ZB uB vB wB", "2": "I c J D E pB eB qB rB sB" },
+        F: {
+          "1":
+            "0 1 2 3 4 5 6 7 8 9 G M N O d e f g h i j k l m n o p q r s t u v w x y z AB BB CB DB EB FB GB HB IB JB Q KB LB MB NB OB PB QB RB SB TB UB VB WB XB ZB",
+          "2": "F B C xB yB zB 0B YB gB 1B",
+        },
+        G: { "1": "7B 8B 9B AC BC CC DC EC FC GC HC IC JC KC", "2": "E eB 2B hB 3B 4B 5B 6B" },
+        H: { "1": "LC" },
+        I: { "1": "H QC RC", "2": "aB I MC NC OC PC hB" },
+        J: { "2": "D A" },
+        K: { "1": "Q", "2": "A B C YB gB ZB" },
+        L: { "1": "H" },
+        M: { "1": "P" },
+        N: { "2": "A B" },
+        O: { "1": "SC" },
+        P: { "1": "I TC UC VC WC XC fB YC ZC aC bC" },
+        Q: { "1": "cC" },
+        R: { "1": "dC" },
+        S: { "1": "eC" },
+      },
+      B: 4,
+      C: "CSS Feature Queries",
+    };
+  });
+  var Mm = v((KD, Rm) => {
+    l();
+    function Im(r) {
+      return r[r.length - 1];
+    }
+    var qm = {
+      parse(r) {
+        let e = [""], t = [e];
+        for (let i of r) {
+          if (i === "(") {
+            e = [""], Im(t).push(e), t.push(e);
+            continue;
+          }
+          if (i === ")") {
+            t.pop(), e = Im(t), e.push("");
+            continue;
+          }
+          e[e.length - 1] += i;
+        }
+        return t[0];
+      },
+      stringify(r) {
+        let e = "";
+        for (let t of r) {
+          if (typeof t == "object") {
+            e += `(${qm.stringify(t)})`;
+            continue;
+          }
+          e += t;
+        }
+        return e;
+      },
+    };
+    Rm.exports = qm;
+  });
+  var $m = v((ZD, Bm) => {
+    l();
+    var U_ = Dm(),
+      { feature: W_ } = (Ln(), Nn),
+      { parse: G_ } = me(),
+      H_ = ft(),
+      zo = Mm(),
+      Y_ = ke(),
+      Q_ = ue(),
+      Fm = W_(U_),
+      Nm = [];
+    for (let r in Fm.stats) {
+      let e = Fm.stats[r];
+      for (let t in e) {
+        let i = e[t];
+        /y/.test(i) && Nm.push(r + " " + t);
+      }
+    }
+    var Lm = class {
+      constructor(e, t) {
+        this.Prefixes = e, this.all = t;
+      }
+      prefixer() {
+        if (this.prefixerCache) return this.prefixerCache;
+        let e = this.all.browsers.selected.filter(i => Nm.includes(i)),
+          t = new H_(this.all.browsers.data, e, this.all.options);
+        return this.prefixerCache = new this.Prefixes(this.all.data, t, this.all.options), this.prefixerCache;
+      }
+      parse(e) {
+        let t = e.split(":"), i = t[0], n = t[1];
+        return n || (n = ""), [i.trim(), n.trim()];
+      }
+      virtual(e) {
+        let [t, i] = this.parse(e), n = G_("a{}").first;
+        return n.append({ prop: t, value: i, raws: { before: "" } }), n;
+      }
+      prefixed(e) {
+        let t = this.virtual(e);
+        if (this.disabled(t.first)) return t.nodes;
+        let i = { warn: () => null }, n = this.prefixer().add[t.first.prop];
+        n && n.process && n.process(t.first, i);
+        for (let s of t.nodes) {
+          for (let a of this.prefixer().values("add", t.first.prop)) a.process(s);
+          Y_.save(this.all, s);
+        }
+        return t.nodes;
+      }
+      isNot(e) {
+        return typeof e == "string" && /not\s*/i.test(e);
+      }
+      isOr(e) {
+        return typeof e == "string" && /\s*or\s*/i.test(e);
+      }
+      isProp(e) {
+        return typeof e == "object" && e.length === 1 && typeof e[0] == "string";
+      }
+      isHack(e, t) {
+        return !new RegExp(`(\\(|\\s)${Q_.escapeRegexp(t)}:`).test(e);
+      }
+      toRemove(e, t) {
+        let [i, n] = this.parse(e), s = this.all.unprefixed(i), a = this.all.cleaner();
+        if (a.remove[i] && a.remove[i].remove && !this.isHack(t, s)) return !0;
+        for (let o of a.values("remove", s)) if (o.check(n)) return !0;
+        return !1;
+      }
+      remove(e, t) {
+        let i = 0;
+        for (; i < e.length;) {
+          if (!this.isNot(e[i - 1]) && this.isProp(e[i]) && this.isOr(e[i + 1])) {
+            if (this.toRemove(e[i][0], t)) {
+              e.splice(i, 2);
+              continue;
+            }
+            i += 2;
+            continue;
+          }
+          typeof e[i] == "object" && (e[i] = this.remove(e[i], t)), i += 1;
+        }
+        return e;
+      }
+      cleanBrackets(e) {
+        return e.map(t =>
+          typeof t != "object"
+            ? t
+            : t.length === 1 && typeof t[0] == "object"
+            ? this.cleanBrackets(t[0])
+            : this.cleanBrackets(t)
+        );
+      }
+      convert(e) {
+        let t = [""];
+        for (let i of e) t.push([`${i.prop}: ${i.value}`]), t.push(" or ");
+        return t[t.length - 1] = "", t;
+      }
+      normalize(e) {
+        if (typeof e != "object") return e;
+        if (e = e.filter(t => t !== ""), typeof e[0] == "string") {
+          let t = e[0].trim();
+          if (t.includes(":") || t === "selector" || t === "not selector") return [zo.stringify(e)];
+        }
+        return e.map(t => this.normalize(t));
+      }
+      add(e, t) {
+        return e.map(i => {
+          if (this.isProp(i)) {
+            let n = this.prefixed(i[0]);
+            return n.length > 1 ? this.convert(n) : i;
+          }
+          return typeof i == "object" ? this.add(i, t) : i;
+        });
+      }
+      process(e) {
+        let t = zo.parse(e.params);
+        t = this.normalize(t),
+          t = this.remove(t, e.params),
+          t = this.add(t, e.params),
+          t = this.cleanBrackets(t),
+          e.params = zo.stringify(t);
+      }
+      disabled(e) {
+        if (
+          !this.all.options.grid
+          && (e.prop === "display" && e.value.includes("grid") || e.prop.includes("grid") || e.prop === "justify-items")
+        ) return !0;
+        if (this.all.options.flexbox === !1) {
+          if (e.prop === "display" && e.value.includes("flex")) return !0;
+          let t = ["order", "justify-content", "align-items", "align-content"];
+          if (e.prop.includes("flex") || t.includes(e.prop)) return !0;
+        }
+        return !1;
+      }
+    };
+    Bm.exports = Lm;
+  });
+  var Vm = v((eI, zm) => {
+    l();
+    var jm = class {
+      constructor(e, t) {
+        this.prefix = t,
+          this.prefixed = e.prefixed(this.prefix),
+          this.regexp = e.regexp(this.prefix),
+          this.prefixeds = e.possible().map(i => [e.prefixed(i), e.regexp(i)]),
+          this.unprefixed = e.name,
+          this.nameRegexp = e.regexp();
+      }
+      isHack(e) {
+        let t = e.parent.index(e) + 1, i = e.parent.nodes;
+        for (; t < i.length;) {
+          let n = i[t].selector;
+          if (!n) return !0;
+          if (n.includes(this.unprefixed) && n.match(this.nameRegexp)) return !1;
+          let s = !1;
+          for (let [a, o] of this.prefixeds) {
+            if (n.includes(a) && n.match(o)) {
+              s = !0;
+              break;
+            }
+          }
+          if (!s) return !0;
+          t += 1;
+        }
+        return !0;
+      }
+      check(e) {
+        return !(!e.selector.includes(this.prefixed) || !e.selector.match(this.regexp) || this.isHack(e));
+      }
+    };
+    zm.exports = jm;
+  });
+  var Ut = v((tI, Wm) => {
+    l();
+    var { list: J_ } = me(),
+      X_ = Vm(),
+      K_ = zt(),
+      Z_ = ft(),
+      eC = ue(),
+      Um = class extends K_ {
+        constructor(e, t, i) {
+          super(e, t, i);
+          this.regexpCache = new Map();
+        }
+        check(e) {
+          return e.selector.includes(this.name) ? !!e.selector.match(this.regexp()) : !1;
+        }
+        prefixed(e) {
+          return this.name.replace(/^(\W*)/, `$1${e}`);
+        }
+        regexp(e) {
+          if (!this.regexpCache.has(e)) {
+            let t = e ? this.prefixed(e) : this.name;
+            this.regexpCache.set(e, new RegExp(`(^|[^:"'=])${eC.escapeRegexp(t)}`, "gi"));
+          }
+          return this.regexpCache.get(e);
+        }
+        possible() {
+          return Z_.prefixes();
+        }
+        prefixeds(e) {
+          if (e._autoprefixerPrefixeds) {
+            if (e._autoprefixerPrefixeds[this.name]) return e._autoprefixerPrefixeds;
+            else e._autoprefixerPrefixeds = {};
+          }
+          let t = {};
+          if (e.selector.includes(",")) {
+            let n = J_.comma(e.selector).filter(s => s.includes(this.name));
+            for (let s of this.possible()) t[s] = n.map(a => this.replace(a, s)).join(", ");
+          } else for (let i of this.possible()) t[i] = this.replace(e.selector, i);
+          return e._autoprefixerPrefixeds[this.name] = t, e._autoprefixerPrefixeds;
+        }
+        already(e, t, i) {
+          let n = e.parent.index(e) - 1;
+          for (; n >= 0;) {
+            let s = e.parent.nodes[n];
+            if (s.type !== "rule") return !1;
+            let a = !1;
+            for (let o in t[this.name]) {
+              let u = t[this.name][o];
+              if (s.selector === u) {
+                if (i === o) return !0;
+                a = !0;
+                break;
+              }
+            }
+            if (!a) return !1;
+            n -= 1;
+          }
+          return !1;
+        }
+        replace(e, t) {
+          return e.replace(this.regexp(), `$1${this.prefixed(t)}`);
+        }
+        add(e, t) {
+          let i = this.prefixeds(e);
+          if (this.already(e, i, t)) return;
+          let n = this.clone(e, { selector: i[this.name][t] });
+          e.parent.insertBefore(e, n);
+        }
+        old(e) {
+          return new X_(this, e);
+        }
+      };
+    Wm.exports = Um;
+  });
+  var Ym = v((rI, Hm) => {
+    l();
+    var tC = zt(),
+      Gm = class extends tC {
+        add(e, t) {
+          let i = t + e.name;
+          if (e.parent.some(a => a.name === i && a.params === e.params)) return;
+          let s = this.clone(e, { name: i });
+          return e.parent.insertBefore(e, s);
+        }
+        process(e) {
+          let t = this.parentPrefix(e);
+          for (let i of this.prefixes) (!t || t === i) && this.add(e, i);
+        }
+      };
+    Hm.exports = Gm;
+  });
+  var Jm = v((iI, Qm) => {
+    l();
+    var rC = Ut(),
+      Vo = class extends rC {
+        prefixed(e) {
+          return e === "-webkit-" ? ":-webkit-full-screen" : e === "-moz-" ? ":-moz-full-screen" : `:${e}fullscreen`;
+        }
+      };
+    Vo.names = [":fullscreen"];
+    Qm.exports = Vo;
+  });
+  var Km = v((nI, Xm) => {
+    l();
+    var iC = Ut(),
+      Uo = class extends iC {
+        possible() {
+          return super.possible().concat(["-moz- old", "-ms- old"]);
+        }
+        prefixed(e) {
+          return e === "-webkit-"
+            ? "::-webkit-input-placeholder"
+            : e === "-ms-"
+            ? "::-ms-input-placeholder"
+            : e === "-ms- old"
+            ? ":-ms-input-placeholder"
+            : e === "-moz- old"
+            ? ":-moz-placeholder"
+            : `::${e}placeholder`;
+        }
+      };
+    Uo.names = ["::placeholder"];
+    Xm.exports = Uo;
+  });
+  var eg = v((sI, Zm) => {
+    l();
+    var nC = Ut(),
+      Wo = class extends nC {
+        prefixed(e) {
+          return e === "-ms-" ? ":-ms-input-placeholder" : `:${e}placeholder-shown`;
+        }
+      };
+    Wo.names = [":placeholder-shown"];
+    Zm.exports = Wo;
+  });
+  var rg = v((aI, tg) => {
+    l();
+    var sC = Ut(),
+      aC = ue(),
+      Go = class extends sC {
+        constructor(e, t, i) {
+          super(e, t, i);
+          this.prefixes && (this.prefixes = aC.uniq(this.prefixes.map(n => "-webkit-")));
+        }
+        prefixed(e) {
+          return e === "-webkit-" ? "::-webkit-file-upload-button" : `::${e}file-selector-button`;
+        }
+      };
+    Go.names = ["::file-selector-button"];
+    tg.exports = Go;
+  });
+  var de = v((oI, ig) => {
+    l();
+    ig.exports = function(r) {
+      let e;
+      return r === "-webkit- 2009" || r === "-moz-"
+        ? e = 2009
+        : r === "-ms-"
+        ? e = 2012
+        : r === "-webkit-" && (e = "final"),
+        r === "-webkit- 2009" && (r = "-webkit-"),
+        [e, r];
+    };
+  });
+  var og = v((lI, ag) => {
+    l();
+    var ng = me().list,
+      sg = de(),
+      oC = q(),
+      Wt = class extends oC {
+        prefixed(e, t) {
+          let i;
+          return [i, t] = sg(t), i === 2009 ? t + "box-flex" : super.prefixed(e, t);
+        }
+        normalize() {
+          return "flex";
+        }
+        set(e, t) {
+          let i = sg(t)[0];
+          if (i === 2009) {
+            return e.value = ng.space(e.value)[0], e.value = Wt.oldValues[e.value] || e.value, super.set(e, t);
+          }
+          if (i === 2012) {
+            let n = ng.space(e.value);
+            n.length === 3 && n[2] === "0" && (e.value = n.slice(0, 2).concat("0px").join(" "));
+          }
+          return super.set(e, t);
+        }
+      };
+    Wt.names = ["flex", "box-flex"];
+    Wt.oldValues = { auto: "1", none: "0" };
+    ag.exports = Wt;
+  });
+  var fg = v((uI, ug) => {
+    l();
+    var lg = de(),
+      lC = q(),
+      Ho = class extends lC {
+        prefixed(e, t) {
+          let i;
+          return [i, t] = lg(t),
+            i === 2009 ? t + "box-ordinal-group" : i === 2012 ? t + "flex-order" : super.prefixed(e, t);
+        }
+        normalize() {
+          return "order";
+        }
+        set(e, t) {
+          return lg(t)[0] === 2009 && /\d/.test(e.value)
+            ? (e.value = (parseInt(e.value) + 1).toString(), super.set(e, t))
+            : super.set(e, t);
+        }
+      };
+    Ho.names = ["order", "flex-order", "box-ordinal-group"];
+    ug.exports = Ho;
+  });
+  var pg = v((fI, cg) => {
+    l();
+    var uC = q(),
+      Yo = class extends uC {
+        check(e) {
+          let t = e.value;
+          return !t.toLowerCase().includes("alpha(") && !t.includes("DXImageTransform.Microsoft")
+            && !t.includes("data:image/svg+xml");
+        }
+      };
+    Yo.names = ["filter"];
+    cg.exports = Yo;
+  });
+  var hg = v((cI, dg) => {
+    l();
+    var fC = q(),
+      Qo = class extends fC {
+        insert(e, t, i, n) {
+          if (t !== "-ms-") return super.insert(e, t, i);
+          let s = this.clone(e), a = e.prop.replace(/end$/, "start"), o = t + e.prop.replace(/end$/, "span");
+          if (!e.parent.some(u => u.prop === o)) {
+            if (s.prop = o, e.value.includes("span")) s.value = e.value.replace(/span\s/i, "");
+            else {
+              let u;
+              if (
+                e.parent.walkDecls(a, c => {
+                  u = c;
+                }), u
+              ) {
+                let c = Number(e.value) - Number(u.value) + "";
+                s.value = c;
+              } else e.warn(n, `Can not prefix ${e.prop} (${a} is not found)`);
+            }
+            e.cloneBefore(s);
+          }
+        }
+      };
+    Qo.names = ["grid-row-end", "grid-column-end"];
+    dg.exports = Qo;
+  });
+  var gg = v((pI, mg) => {
+    l();
+    var cC = q(),
+      Jo = class extends cC {
+        check(e) {
+          return !e.value.split(/\s+/).some(t => {
+            let i = t.toLowerCase();
+            return i === "reverse" || i === "alternate-reverse";
+          });
+        }
+      };
+    Jo.names = ["animation", "animation-direction"];
+    mg.exports = Jo;
+  });
+  var bg = v((dI, yg) => {
+    l();
+    var pC = de(),
+      dC = q(),
+      Xo = class extends dC {
+        insert(e, t, i) {
+          let n;
+          if ([n, t] = pC(t), n !== 2009) return super.insert(e, t, i);
+          let s = e.value.split(/\s+/).filter(p => p !== "wrap" && p !== "nowrap" && "wrap-reverse");
+          if (s.length === 0 || e.parent.some(p => p.prop === t + "box-orient" || p.prop === t + "box-direction")) {
+            return;
+          }
+          let o = s[0],
+            u = o.includes("row") ? "horizontal" : "vertical",
+            c = o.includes("reverse") ? "reverse" : "normal",
+            f = this.clone(e);
+          return f.prop = t + "box-orient",
+            f.value = u,
+            this.needCascade(e) && (f.raws.before = this.calcBefore(i, e, t)),
+            e.parent.insertBefore(e, f),
+            f = this.clone(e),
+            f.prop = t + "box-direction",
+            f.value = c,
+            this.needCascade(e) && (f.raws.before = this.calcBefore(i, e, t)),
+            e.parent.insertBefore(e, f);
+        }
+      };
+    Xo.names = ["flex-flow", "box-direction", "box-orient"];
+    yg.exports = Xo;
+  });
+  var vg = v((hI, wg) => {
+    l();
+    var hC = de(),
+      mC = q(),
+      Ko = class extends mC {
+        normalize() {
+          return "flex";
+        }
+        prefixed(e, t) {
+          let i;
+          return [i, t] = hC(t), i === 2009 ? t + "box-flex" : i === 2012 ? t + "flex-positive" : super.prefixed(e, t);
+        }
+      };
+    Ko.names = ["flex-grow", "flex-positive"];
+    wg.exports = Ko;
+  });
+  var kg = v((mI, xg) => {
+    l();
+    var gC = de(),
+      yC = q(),
+      Zo = class extends yC {
+        set(e, t) {
+          if (gC(t)[0] !== 2009) return super.set(e, t);
+        }
+      };
+    Zo.names = ["flex-wrap"];
+    xg.exports = Zo;
+  });
+  var _g = v((gI, Sg) => {
+    l();
+    var bC = q(),
+      Gt = ct(),
+      el = class extends bC {
+        insert(e, t, i, n) {
+          if (t !== "-ms-") return super.insert(e, t, i);
+          let s = Gt.parse(e), [a, o] = Gt.translate(s, 0, 2), [u, c] = Gt.translate(s, 1, 3);
+          [["grid-row", a], ["grid-row-span", o], ["grid-column", u], ["grid-column-span", c]].forEach(([f, p]) => {
+            Gt.insertDecl(e, f, p);
+          }),
+            Gt.warnTemplateSelectorNotFound(e, n),
+            Gt.warnIfGridRowColumnExists(e, n);
+        }
+      };
+    el.names = ["grid-area"];
+    Sg.exports = el;
+  });
+  var Ag = v((yI, Cg) => {
+    l();
+    var wC = q(),
+      ti = ct(),
+      tl = class extends wC {
+        insert(e, t, i) {
+          if (t !== "-ms-") return super.insert(e, t, i);
+          if (e.parent.some(a => a.prop === "-ms-grid-row-align")) return;
+          let [[n, s]] = ti.parse(e);
+          s
+            ? (ti.insertDecl(e, "grid-row-align", n), ti.insertDecl(e, "grid-column-align", s))
+            : (ti.insertDecl(e, "grid-row-align", n), ti.insertDecl(e, "grid-column-align", n));
+        }
+      };
+    tl.names = ["place-self"];
+    Cg.exports = tl;
+  });
+  var Eg = v((bI, Og) => {
+    l();
+    var vC = q(),
+      rl = class extends vC {
+        check(e) {
+          let t = e.value;
+          return !t.includes("/") || t.includes("span");
+        }
+        normalize(e) {
+          return e.replace("-start", "");
+        }
+        prefixed(e, t) {
+          let i = super.prefixed(e, t);
+          return t === "-ms-" && (i = i.replace("-start", "")), i;
+        }
+      };
+    rl.names = ["grid-row-start", "grid-column-start"];
+    Og.exports = rl;
+  });
+  var Dg = v((wI, Pg) => {
+    l();
+    var Tg = de(),
+      xC = q(),
+      Ht = class extends xC {
+        check(e) {
+          return e.parent && !e.parent.some(t => t.prop && t.prop.startsWith("grid-"));
+        }
+        prefixed(e, t) {
+          let i;
+          return [i, t] = Tg(t), i === 2012 ? t + "flex-item-align" : super.prefixed(e, t);
+        }
+        normalize() {
+          return "align-self";
+        }
+        set(e, t) {
+          let i = Tg(t)[0];
+          if (i === 2012) return e.value = Ht.oldValues[e.value] || e.value, super.set(e, t);
+          if (i === "final") return super.set(e, t);
+        }
+      };
+    Ht.names = ["align-self", "flex-item-align"];
+    Ht.oldValues = { "flex-end": "end", "flex-start": "start" };
+    Pg.exports = Ht;
+  });
+  var qg = v((vI, Ig) => {
+    l();
+    var kC = q(),
+      SC = ue(),
+      il = class extends kC {
+        constructor(e, t, i) {
+          super(e, t, i);
+          this.prefixes && (this.prefixes = SC.uniq(this.prefixes.map(n => n === "-ms-" ? "-webkit-" : n)));
+        }
+      };
+    il.names = ["appearance"];
+    Ig.exports = il;
+  });
+  var Fg = v((xI, Mg) => {
+    l();
+    var Rg = de(),
+      _C = q(),
+      nl = class extends _C {
+        normalize() {
+          return "flex-basis";
+        }
+        prefixed(e, t) {
+          let i;
+          return [i, t] = Rg(t), i === 2012 ? t + "flex-preferred-size" : super.prefixed(e, t);
+        }
+        set(e, t) {
+          let i;
+          if ([i, t] = Rg(t), i === 2012 || i === "final") return super.set(e, t);
+        }
+      };
+    nl.names = ["flex-basis", "flex-preferred-size"];
+    Mg.exports = nl;
+  });
+  var Lg = v((kI, Ng) => {
+    l();
+    var CC = q(),
+      sl = class extends CC {
+        normalize() {
+          return this.name.replace("box-image", "border");
+        }
+        prefixed(e, t) {
+          let i = super.prefixed(e, t);
+          return t === "-webkit-" && (i = i.replace("border", "box-image")), i;
+        }
+      };
+    sl.names = [
+      "mask-border",
+      "mask-border-source",
+      "mask-border-slice",
+      "mask-border-width",
+      "mask-border-outset",
+      "mask-border-repeat",
+      "mask-box-image",
+      "mask-box-image-source",
+      "mask-box-image-slice",
+      "mask-box-image-width",
+      "mask-box-image-outset",
+      "mask-box-image-repeat",
+    ];
+    Ng.exports = sl;
+  });
+  var $g = v((SI, Bg) => {
+    l();
+    var AC = q(),
+      Be = class extends AC {
+        insert(e, t, i) {
+          let n = e.prop === "mask-composite", s;
+          n ? s = e.value.split(",") : s = e.value.match(Be.regexp) || [], s = s.map(c => c.trim()).filter(c => c);
+          let a = s.length, o;
+          if (
+            a
+            && (o = this.clone(e),
+              o.value = s.map(c => Be.oldValues[c] || c).join(", "),
+              s.includes("intersect") && (o.value += ", xor"),
+              o.prop = t + "mask-composite"), n
+          ) {
+            return a
+              ? (this.needCascade(e) && (o.raws.before = this.calcBefore(i, e, t)), e.parent.insertBefore(e, o))
+              : void 0;
+          }
+          let u = this.clone(e);
+          return u.prop = t + u.prop,
+            a && (u.value = u.value.replace(Be.regexp, "")),
+            this.needCascade(e) && (u.raws.before = this.calcBefore(i, e, t)),
+            e.parent.insertBefore(e, u),
+            a ? (this.needCascade(e) && (o.raws.before = this.calcBefore(i, e, t)), e.parent.insertBefore(e, o)) : e;
+        }
+      };
+    Be.names = ["mask", "mask-composite"];
+    Be.oldValues = { add: "source-over", subtract: "source-out", intersect: "source-in", exclude: "xor" };
+    Be.regexp = new RegExp(`\\s+(${Object.keys(Be.oldValues).join("|")})\\b(?!\\))\\s*(?=[,])`, "ig");
+    Bg.exports = Be;
+  });
+  var Vg = v((_I, zg) => {
+    l();
+    var jg = de(),
+      OC = q(),
+      Yt = class extends OC {
+        prefixed(e, t) {
+          let i;
+          return [i, t] = jg(t), i === 2009 ? t + "box-align" : i === 2012 ? t + "flex-align" : super.prefixed(e, t);
+        }
+        normalize() {
+          return "align-items";
+        }
+        set(e, t) {
+          let i = jg(t)[0];
+          return (i === 2009 || i === 2012) && (e.value = Yt.oldValues[e.value] || e.value), super.set(e, t);
+        }
+      };
+    Yt.names = ["align-items", "flex-align", "box-align"];
+    Yt.oldValues = { "flex-end": "end", "flex-start": "start" };
+    zg.exports = Yt;
+  });
+  var Wg = v((CI, Ug) => {
+    l();
+    var EC = q(),
+      al = class extends EC {
+        set(e, t) {
+          return t === "-ms-" && e.value === "contain" && (e.value = "element"), super.set(e, t);
+        }
+        insert(e, t, i) {
+          if (!(e.value === "all" && t === "-ms-")) return super.insert(e, t, i);
+        }
+      };
+    al.names = ["user-select"];
+    Ug.exports = al;
+  });
+  var Yg = v((AI, Hg) => {
+    l();
+    var Gg = de(),
+      TC = q(),
+      ol = class extends TC {
+        normalize() {
+          return "flex-shrink";
+        }
+        prefixed(e, t) {
+          let i;
+          return [i, t] = Gg(t), i === 2012 ? t + "flex-negative" : super.prefixed(e, t);
+        }
+        set(e, t) {
+          let i;
+          if ([i, t] = Gg(t), i === 2012 || i === "final") return super.set(e, t);
+        }
+      };
+    ol.names = ["flex-shrink", "flex-negative"];
+    Hg.exports = ol;
+  });
+  var Jg = v((OI, Qg) => {
+    l();
+    var PC = q(),
+      ll = class extends PC {
+        prefixed(e, t) {
+          return `${t}column-${e}`;
+        }
+        normalize(e) {
+          return e.includes("inside") ? "break-inside" : e.includes("before") ? "break-before" : "break-after";
+        }
+        set(e, t) {
+          return (e.prop === "break-inside" && e.value === "avoid-column" || e.value === "avoid-page")
+            && (e.value = "avoid"),
+            super.set(e, t);
+        }
+        insert(e, t, i) {
+          if (e.prop !== "break-inside") return super.insert(e, t, i);
+          if (!(/region/i.test(e.value) || /page/i.test(e.value))) return super.insert(e, t, i);
+        }
+      };
+    ll.names = [
+      "break-inside",
+      "page-break-inside",
+      "column-break-inside",
+      "break-before",
+      "page-break-before",
+      "column-break-before",
+      "break-after",
+      "page-break-after",
+      "column-break-after",
+    ];
+    Qg.exports = ll;
+  });
+  var Kg = v((EI, Xg) => {
+    l();
+    var DC = q(),
+      ul = class extends DC {
+        prefixed(e, t) {
+          return t + "print-color-adjust";
+        }
+        normalize() {
+          return "color-adjust";
+        }
+      };
+    ul.names = ["color-adjust", "print-color-adjust"];
+    Xg.exports = ul;
+  });
+  var ey = v((TI, Zg) => {
+    l();
+    var IC = q(),
+      Qt = class extends IC {
+        insert(e, t, i) {
+          if (t === "-ms-") {
+            let n = this.set(this.clone(e), t);
+            this.needCascade(e) && (n.raws.before = this.calcBefore(i, e, t));
+            let s = "ltr";
+            return e.parent.nodes.forEach(a => {
+              a.prop === "direction" && (a.value === "rtl" || a.value === "ltr") && (s = a.value);
+            }),
+              n.value = Qt.msValues[s][e.value] || e.value,
+              e.parent.insertBefore(e, n);
+          }
+          return super.insert(e, t, i);
+        }
+      };
+    Qt.names = ["writing-mode"];
+    Qt.msValues = {
+      ltr: { "horizontal-tb": "lr-tb", "vertical-rl": "tb-rl", "vertical-lr": "tb-lr" },
+      rtl: { "horizontal-tb": "rl-tb", "vertical-rl": "bt-rl", "vertical-lr": "bt-lr" },
+    };
+    Zg.exports = Qt;
+  });
+  var ry = v((PI, ty) => {
+    l();
+    var qC = q(),
+      fl = class extends qC {
+        set(e, t) {
+          return e.value = e.value.replace(/\s+fill(\s)/, "$1"), super.set(e, t);
+        }
+      };
+    fl.names = ["border-image"];
+    ty.exports = fl;
+  });
+  var sy = v((DI, ny) => {
+    l();
+    var iy = de(),
+      RC = q(),
+      Jt = class extends RC {
+        prefixed(e, t) {
+          let i;
+          return [i, t] = iy(t), i === 2012 ? t + "flex-line-pack" : super.prefixed(e, t);
+        }
+        normalize() {
+          return "align-content";
+        }
+        set(e, t) {
+          let i = iy(t)[0];
+          if (i === 2012) return e.value = Jt.oldValues[e.value] || e.value, super.set(e, t);
+          if (i === "final") return super.set(e, t);
+        }
+      };
+    Jt.names = ["align-content", "flex-line-pack"];
+    Jt.oldValues = {
+      "flex-end": "end",
+      "flex-start": "start",
+      "space-between": "justify",
+      "space-around": "distribute",
+    };
+    ny.exports = Jt;
+  });
+  var oy = v((II, ay) => {
+    l();
+    var MC = q(),
+      Se = class extends MC {
+        prefixed(e, t) {
+          return t === "-moz-" ? t + (Se.toMozilla[e] || e) : super.prefixed(e, t);
+        }
+        normalize(e) {
+          return Se.toNormal[e] || e;
+        }
+      };
+    Se.names = ["border-radius"];
+    Se.toMozilla = {};
+    Se.toNormal = {};
+    for (let r of ["top", "bottom"]) {
+      for (let e of ["left", "right"]) {
+        let t = `border-${r}-${e}-radius`, i = `border-radius-${r}${e}`;
+        Se.names.push(t), Se.names.push(i), Se.toMozilla[t] = i, Se.toNormal[i] = t;
+      }
+    }
+    ay.exports = Se;
+  });
+  var uy = v((qI, ly) => {
+    l();
+    var FC = q(),
+      cl = class extends FC {
+        prefixed(e, t) {
+          return e.includes("-start")
+            ? t + e.replace("-block-start", "-before")
+            : t + e.replace("-block-end", "-after");
+        }
+        normalize(e) {
+          return e.includes("-before") ? e.replace("-before", "-block-start") : e.replace("-after", "-block-end");
+        }
+      };
+    cl.names = [
+      "border-block-start",
+      "border-block-end",
+      "margin-block-start",
+      "margin-block-end",
+      "padding-block-start",
+      "padding-block-end",
+      "border-before",
+      "border-after",
+      "margin-before",
+      "margin-after",
+      "padding-before",
+      "padding-after",
+    ];
+    ly.exports = cl;
+  });
+  var cy = v((RI, fy) => {
+    l();
+    var NC = q(),
+      { parseTemplate: LC, warnMissedAreas: BC, getGridGap: $C, warnGridGap: jC, inheritGridGap: zC } = ct(),
+      pl = class extends NC {
+        insert(e, t, i, n) {
+          if (t !== "-ms-") return super.insert(e, t, i);
+          if (e.parent.some(h => h.prop === "-ms-grid-rows")) return;
+          let s = $C(e),
+            a = zC(e, s),
+            { rows: o, columns: u, areas: c } = LC({ decl: e, gap: a || s }),
+            f = Object.keys(c).length > 0,
+            p = Boolean(o),
+            d = Boolean(u);
+          return jC({ gap: s, hasColumns: d, decl: e, result: n }),
+            BC(c, e, n),
+            (p && d || f) && e.cloneBefore({ prop: "-ms-grid-rows", value: o, raws: {} }),
+            d && e.cloneBefore({ prop: "-ms-grid-columns", value: u, raws: {} }),
+            e;
+        }
+      };
+    pl.names = ["grid-template"];
+    fy.exports = pl;
+  });
+  var dy = v((MI, py) => {
+    l();
+    var VC = q(),
+      dl = class extends VC {
+        prefixed(e, t) {
+          return t + e.replace("-inline", "");
+        }
+        normalize(e) {
+          return e.replace(/(margin|padding|border)-(start|end)/, "$1-inline-$2");
+        }
+      };
+    dl.names = [
+      "border-inline-start",
+      "border-inline-end",
+      "margin-inline-start",
+      "margin-inline-end",
+      "padding-inline-start",
+      "padding-inline-end",
+      "border-start",
+      "border-end",
+      "margin-start",
+      "margin-end",
+      "padding-start",
+      "padding-end",
+    ];
+    py.exports = dl;
+  });
+  var my = v((FI, hy) => {
+    l();
+    var UC = q(),
+      hl = class extends UC {
+        check(e) {
+          return !e.value.includes("flex-") && e.value !== "baseline";
+        }
+        prefixed(e, t) {
+          return t + "grid-row-align";
+        }
+        normalize() {
+          return "align-self";
+        }
+      };
+    hl.names = ["grid-row-align"];
+    hy.exports = hl;
+  });
+  var yy = v((NI, gy) => {
+    l();
+    var WC = q(),
+      Xt = class extends WC {
+        keyframeParents(e) {
+          let { parent: t } = e;
+          for (; t;) {
+            if (t.type === "atrule" && t.name === "keyframes") return !0;
+            ({ parent: t } = t);
+          }
+          return !1;
+        }
+        contain3d(e) {
+          if (e.prop === "transform-origin") return !1;
+          for (let t of Xt.functions3d) if (e.value.includes(`${t}(`)) return !0;
+          return !1;
+        }
+        set(e, t) {
+          return e = super.set(e, t), t === "-ms-" && (e.value = e.value.replace(/rotatez/gi, "rotate")), e;
+        }
+        insert(e, t, i) {
+          if (t === "-ms-") {
+            if (!this.contain3d(e) && !this.keyframeParents(e)) return super.insert(e, t, i);
+            else if (t === "-o-") {
+              if (!this.contain3d(e)) return super.insert(e, t, i);
+              else return super.insert(e, t, i);
+            }
+          }
+        }
+      };
+    Xt.names = ["transform", "transform-origin"];
+    Xt.functions3d = [
+      "matrix3d",
+      "translate3d",
+      "translateZ",
+      "scale3d",
+      "scaleZ",
+      "rotate3d",
+      "rotateX",
+      "rotateY",
+      "perspective",
+    ];
+    gy.exports = Xt;
+  });
+  var vy = v((LI, wy) => {
+    l();
+    var by = de(),
+      GC = q(),
+      ml = class extends GC {
+        normalize() {
+          return "flex-direction";
+        }
+        insert(e, t, i) {
+          let n;
+          if ([n, t] = by(t), n !== 2009) return super.insert(e, t, i);
+          if (e.parent.some(f => f.prop === t + "box-orient" || f.prop === t + "box-direction")) return;
+          let a = e.value, o, u;
+          a === "inherit" || a === "initial" || a === "unset"
+            ? (o = a, u = a)
+            : (o = a.includes("row") ? "horizontal" : "vertical", u = a.includes("reverse") ? "reverse" : "normal");
+          let c = this.clone(e);
+          return c.prop = t + "box-orient",
+            c.value = o,
+            this.needCascade(e) && (c.raws.before = this.calcBefore(i, e, t)),
+            e.parent.insertBefore(e, c),
+            c = this.clone(e),
+            c.prop = t + "box-direction",
+            c.value = u,
+            this.needCascade(e) && (c.raws.before = this.calcBefore(i, e, t)),
+            e.parent.insertBefore(e, c);
+        }
+        old(e, t) {
+          let i;
+          return [i, t] = by(t), i === 2009 ? [t + "box-orient", t + "box-direction"] : super.old(e, t);
+        }
+      };
+    ml.names = ["flex-direction", "box-direction", "box-orient"];
+    wy.exports = ml;
+  });
+  var ky = v((BI, xy) => {
+    l();
+    var HC = q(),
+      gl = class extends HC {
+        check(e) {
+          return e.value === "pixelated";
+        }
+        prefixed(e, t) {
+          return t === "-ms-" ? "-ms-interpolation-mode" : super.prefixed(e, t);
+        }
+        set(e, t) {
+          return t !== "-ms-" ? super.set(e, t) : (e.prop = "-ms-interpolation-mode", e.value = "nearest-neighbor", e);
+        }
+        normalize() {
+          return "image-rendering";
+        }
+        process(e, t) {
+          return super.process(e, t);
+        }
+      };
+    gl.names = ["image-rendering", "interpolation-mode"];
+    xy.exports = gl;
+  });
+  var _y = v(($I, Sy) => {
+    l();
+    var YC = q(),
+      QC = ue(),
+      yl = class extends YC {
+        constructor(e, t, i) {
+          super(e, t, i);
+          this.prefixes && (this.prefixes = QC.uniq(this.prefixes.map(n => n === "-ms-" ? "-webkit-" : n)));
+        }
+      };
+    yl.names = ["backdrop-filter"];
+    Sy.exports = yl;
+  });
+  var Ay = v((jI, Cy) => {
+    l();
+    var JC = q(),
+      XC = ue(),
+      bl = class extends JC {
+        constructor(e, t, i) {
+          super(e, t, i);
+          this.prefixes && (this.prefixes = XC.uniq(this.prefixes.map(n => n === "-ms-" ? "-webkit-" : n)));
+        }
+        check(e) {
+          return e.value.toLowerCase() === "text";
+        }
+      };
+    bl.names = ["background-clip"];
+    Cy.exports = bl;
+  });
+  var Ey = v((zI, Oy) => {
+    l();
+    var KC = q(),
+      ZC = ["none", "underline", "overline", "line-through", "blink", "inherit", "initial", "unset"],
+      wl = class extends KC {
+        check(e) {
+          return e.value.split(/\s+/).some(t => !ZC.includes(t));
+        }
+      };
+    wl.names = ["text-decoration"];
+    Oy.exports = wl;
+  });
+  var Dy = v((VI, Py) => {
+    l();
+    var Ty = de(),
+      eA = q(),
+      Kt = class extends eA {
+        prefixed(e, t) {
+          let i;
+          return [i, t] = Ty(t), i === 2009 ? t + "box-pack" : i === 2012 ? t + "flex-pack" : super.prefixed(e, t);
+        }
+        normalize() {
+          return "justify-content";
+        }
+        set(e, t) {
+          let i = Ty(t)[0];
+          if (i === 2009 || i === 2012) {
+            let n = Kt.oldValues[e.value] || e.value;
+            if (e.value = n, i !== 2009 || n !== "distribute") return super.set(e, t);
+          } else if (i === "final") return super.set(e, t);
+        }
+      };
+    Kt.names = ["justify-content", "flex-pack", "box-pack"];
+    Kt.oldValues = {
+      "flex-end": "end",
+      "flex-start": "start",
+      "space-between": "justify",
+      "space-around": "distribute",
+    };
+    Py.exports = Kt;
+  });
+  var qy = v((UI, Iy) => {
+    l();
+    var tA = q(),
+      vl = class extends tA {
+        set(e, t) {
+          let i = e.value.toLowerCase();
+          return t === "-webkit-" && !i.includes(" ") && i !== "contain" && i !== "cover"
+            && (e.value = e.value + " " + e.value),
+            super.set(e, t);
+        }
+      };
+    vl.names = ["background-size"];
+    Iy.exports = vl;
+  });
+  var My = v((WI, Ry) => {
+    l();
+    var rA = q(),
+      xl = ct(),
+      kl = class extends rA {
+        insert(e, t, i) {
+          if (t !== "-ms-") return super.insert(e, t, i);
+          let n = xl.parse(e), [s, a] = xl.translate(n, 0, 1);
+          n[0] && n[0].includes("span") && (a = n[0].join("").replace(/\D/g, "")),
+            [[e.prop, s], [`${e.prop}-span`, a]].forEach(([u, c]) => {
+              xl.insertDecl(e, u, c);
+            });
+        }
+      };
+    kl.names = ["grid-row", "grid-column"];
+    Ry.exports = kl;
+  });
+  var Ly = v((GI, Ny) => {
+    l();
+    var iA = q(),
+      { prefixTrackProp: Fy, prefixTrackValue: nA, autoplaceGridItems: sA, getGridGap: aA, inheritGridGap: oA } = ct(),
+      lA = jo(),
+      Sl = class extends iA {
+        prefixed(e, t) {
+          return t === "-ms-" ? Fy({ prop: e, prefix: t }) : super.prefixed(e, t);
+        }
+        normalize(e) {
+          return e.replace(/^grid-(rows|columns)/, "grid-template-$1");
+        }
+        insert(e, t, i, n) {
+          if (t !== "-ms-") return super.insert(e, t, i);
+          let { parent: s, prop: a, value: o } = e,
+            u = a.includes("rows"),
+            c = a.includes("columns"),
+            f = s.some(k => k.prop === "grid-template" || k.prop === "grid-template-areas");
+          if (f && u) return !1;
+          let p = new lA({ options: {} }), d = p.gridStatus(s, n), h = aA(e);
+          h = oA(e, h) || h;
+          let y = u ? h.row : h.column;
+          (d === "no-autoplace" || d === !0) && !f && (y = null);
+          let x = nA({ value: o, gap: y });
+          e.cloneBefore({ prop: Fy({ prop: a, prefix: t }), value: x });
+          let b = s.nodes.find(k => k.prop === "grid-auto-flow"), w = "row";
+          if (b && !p.disabled(b, n) && (w = b.value.trim()), d === "autoplace") {
+            let k = s.nodes.find(_ => _.prop === "grid-template-rows");
+            if (!k && f) return;
+            if (!k && !f) {
+              e.warn(n, "Autoplacement does not work without grid-template-rows property");
+              return;
+            }
+            !s.nodes.find(_ => _.prop === "grid-template-columns") && !f
+            && e.warn(n, "Autoplacement does not work without grid-template-columns property"),
+              c && !f && sA(e, n, h, w);
+          }
+        }
+      };
+    Sl.names = ["grid-template-rows", "grid-template-columns", "grid-rows", "grid-columns"];
+    Ny.exports = Sl;
+  });
+  var $y = v((HI, By) => {
+    l();
+    var uA = q(),
+      _l = class extends uA {
+        check(e) {
+          return !e.value.includes("flex-") && e.value !== "baseline";
+        }
+        prefixed(e, t) {
+          return t + "grid-column-align";
+        }
+        normalize() {
+          return "justify-self";
+        }
+      };
+    _l.names = ["grid-column-align"];
+    By.exports = _l;
+  });
+  var zy = v((YI, jy) => {
+    l();
+    var fA = q(),
+      Cl = class extends fA {
+        prefixed(e, t) {
+          return t + "scroll-chaining";
+        }
+        normalize() {
+          return "overscroll-behavior";
+        }
+        set(e, t) {
+          return e.value === "auto"
+            ? e.value = "chained"
+            : (e.value === "none" || e.value === "contain") && (e.value = "none"),
+            super.set(e, t);
+        }
+      };
+    Cl.names = ["overscroll-behavior", "scroll-chaining"];
+    jy.exports = Cl;
+  });
+  var Wy = v((QI, Uy) => {
+    l();
+    var cA = q(),
+      {
+        parseGridAreas: pA,
+        warnMissedAreas: dA,
+        prefixTrackProp: hA,
+        prefixTrackValue: Vy,
+        getGridGap: mA,
+        warnGridGap: gA,
+        inheritGridGap: yA,
+      } = ct();
+    function bA(r) {
+      return r.trim().slice(1, -1).split(/["']\s*["']?/g);
+    }
+    var Al = class extends cA {
+      insert(e, t, i, n) {
+        if (t !== "-ms-") return super.insert(e, t, i);
+        let s = !1, a = !1, o = e.parent, u = mA(e);
+        u = yA(e, u) || u,
+          o.walkDecls(/-ms-grid-rows/, p => p.remove()),
+          o.walkDecls(/grid-template-(rows|columns)/, p => {
+            if (p.prop === "grid-template-rows") {
+              a = !0;
+              let { prop: d, value: h } = p;
+              p.cloneBefore({ prop: hA({ prop: d, prefix: t }), value: Vy({ value: h, gap: u.row }) });
+            } else s = !0;
+          });
+        let c = bA(e.value);
+        s && !a && u.row && c.length > 1
+        && e.cloneBefore({
+          prop: "-ms-grid-rows",
+          value: Vy({ value: `repeat(${c.length}, auto)`, gap: u.row }),
+          raws: {},
+        }), gA({ gap: u, hasColumns: s, decl: e, result: n });
+        let f = pA({ rows: c, gap: u });
+        return dA(f, e, n), e;
+      }
+    };
+    Al.names = ["grid-template-areas"];
+    Uy.exports = Al;
+  });
+  var Hy = v((JI, Gy) => {
+    l();
+    var wA = q(),
+      Ol = class extends wA {
+        set(e, t) {
+          return t === "-webkit-" && (e.value = e.value.replace(/\s*(right|left)\s*/i, "")), super.set(e, t);
+        }
+      };
+    Ol.names = ["text-emphasis-position"];
+    Gy.exports = Ol;
+  });
+  var Qy = v((XI, Yy) => {
+    l();
+    var vA = q(),
+      El = class extends vA {
+        set(e, t) {
+          return e.prop === "text-decoration-skip-ink" && e.value === "auto"
+            ? (e.prop = t + "text-decoration-skip", e.value = "ink", e)
+            : super.set(e, t);
+        }
+      };
+    El.names = ["text-decoration-skip-ink", "text-decoration-skip"];
+    Yy.exports = El;
+  });
+  var tb = v((KI, eb) => {
+    l();
+    "use strict";
+    eb.exports = { wrap: Jy, limit: Xy, validate: Ky, test: Tl, curry: xA, name: Zy };
+    function Jy(r, e, t) {
+      var i = e - r;
+      return ((t - r) % i + i) % i + r;
+    }
+    function Xy(r, e, t) {
+      return Math.max(r, Math.min(e, t));
+    }
+    function Ky(r, e, t, i, n) {
+      if (!Tl(r, e, t, i, n)) throw new Error(t + " is outside of range [" + r + "," + e + ")");
+      return t;
+    }
+    function Tl(r, e, t, i, n) {
+      return !(t < r || t > e || n && t === e || i && t === r);
+    }
+    function Zy(r, e, t, i) {
+      return (t ? "(" : "[") + r + "," + e + (i ? ")" : "]");
+    }
+    function xA(r, e, t, i) {
+      var n = Zy.bind(null, r, e, t, i);
+      return {
+        wrap: Jy.bind(null, r, e),
+        limit: Xy.bind(null, r, e),
+        validate: function(s) {
+          return Ky(r, e, s, t, i);
+        },
+        test: function(s) {
+          return Tl(r, e, s, t, i);
+        },
+        toString: n,
+        name: n,
+      };
+    }
+  });
+  var nb = v((ZI, ib) => {
+    l();
+    var Pl = Kr(),
+      kA = tb(),
+      SA = Vt(),
+      _A = ke(),
+      CA = ue(),
+      rb = /top|left|right|bottom/gi,
+      Ye = class extends _A {
+        replace(e, t) {
+          let i = Pl(e);
+          for (let n of i.nodes) {
+            if (n.type === "function" && n.value === this.name) {
+              if (n.nodes = this.newDirection(n.nodes), n.nodes = this.normalize(n.nodes), t === "-webkit- old") {
+                if (!this.oldWebkit(n)) {
+                  return !1;
+                }
+              } else n.nodes = this.convertDirection(n.nodes), n.value = t + n.value;
+            }
+          }
+          return i.toString();
+        }
+        replaceFirst(e, ...t) {
+          return t.map(n => n === " " ? { type: "space", value: n } : { type: "word", value: n }).concat(e.slice(1));
+        }
+        normalizeUnit(e, t) {
+          return `${parseFloat(e) / t * 360}deg`;
+        }
+        normalize(e) {
+          if (!e[0]) return e;
+          if (/-?\d+(.\d+)?grad/.test(e[0].value)) e[0].value = this.normalizeUnit(e[0].value, 400);
+          else if (/-?\d+(.\d+)?rad/.test(e[0].value)) e[0].value = this.normalizeUnit(e[0].value, 2 * Math.PI);
+          else if (/-?\d+(.\d+)?turn/.test(e[0].value)) e[0].value = this.normalizeUnit(e[0].value, 1);
+          else if (e[0].value.includes("deg")) {
+            let t = parseFloat(e[0].value);
+            t = kA.wrap(0, 360, t), e[0].value = `${t}deg`;
+          }
+          return e[0].value === "0deg"
+            ? e = this.replaceFirst(e, "to", " ", "top")
+            : e[0].value === "90deg"
+            ? e = this.replaceFirst(e, "to", " ", "right")
+            : e[0].value === "180deg"
+            ? e = this.replaceFirst(e, "to", " ", "bottom")
+            : e[0].value === "270deg" && (e = this.replaceFirst(e, "to", " ", "left")),
+            e;
+        }
+        newDirection(e) {
+          if (e[0].value === "to" || (rb.lastIndex = 0, !rb.test(e[0].value))) return e;
+          e.unshift({ type: "word", value: "to" }, { type: "space", value: " " });
+          for (let t = 2; t < e.length && e[t].type !== "div"; t++) {
+            e[t].type === "word" && (e[t].value = this.revertDirection(e[t].value));
+          }
+          return e;
+        }
+        isRadial(e) {
+          let t = "before";
+          for (let i of e) {
+            if (t === "before" && i.type === "space") t = "at";
+            else if (t === "at" && i.value === "at") t = "after";
+            else {
+              if (t === "after" && i.type === "space") return !0;
+              if (i.type === "div") break;
+              t = "before";
+            }
+          }
+          return !1;
+        }
+        convertDirection(e) {
+          return e.length > 0
+            && (e[0].value === "to"
+              ? this.fixDirection(e)
+              : e[0].value.includes("deg")
+              ? this.fixAngle(e)
+              : this.isRadial(e) && this.fixRadial(e)),
+            e;
+        }
+        fixDirection(e) {
+          e.splice(0, 2);
+          for (let t of e) {
+            if (t.type === "div") break;
+            t.type === "word" && (t.value = this.revertDirection(t.value));
+          }
+        }
+        fixAngle(e) {
+          let t = e[0].value;
+          t = parseFloat(t), t = Math.abs(450 - t) % 360, t = this.roundFloat(t, 3), e[0].value = `${t}deg`;
+        }
+        fixRadial(e) {
+          let t = [], i = [], n, s, a, o, u;
+          for (o = 0; o < e.length - 2; o++) {
+            if (n = e[o], s = e[o + 1], a = e[o + 2], n.type === "space" && s.value === "at" && a.type === "space") {
+              u = o + 3;
+              break;
+            } else t.push(n);
+          }
+          let c;
+          for (o = u; o < e.length; o++) {
+            if (e[o].type === "div") {
+              c = e[o];
+              break;
+            } else i.push(e[o]);
+          }
+          e.splice(0, o, ...i, c, ...t);
+        }
+        revertDirection(e) {
+          return Ye.directions[e.toLowerCase()] || e;
+        }
+        roundFloat(e, t) {
+          return parseFloat(e.toFixed(t));
+        }
+        oldWebkit(e) {
+          let { nodes: t } = e, i = Pl.stringify(e.nodes);
+          if (
+            this.name !== "linear-gradient" || t[0] && t[0].value.includes("deg") || i.includes("px")
+            || i.includes("-corner") || i.includes("-side")
+          ) return !1;
+          let n = [[]];
+          for (let s of t) n[n.length - 1].push(s), s.type === "div" && s.value === "," && n.push([]);
+          this.oldDirection(n), this.colorStops(n), e.nodes = [];
+          for (let s of n) e.nodes = e.nodes.concat(s);
+          return e.nodes.unshift({ type: "word", value: "linear" }, this.cloneDiv(e.nodes)),
+            e.value = "-webkit-gradient",
+            !0;
+        }
+        oldDirection(e) {
+          let t = this.cloneDiv(e[0]);
+          if (e[0][0].value !== "to") return e.unshift([{ type: "word", value: Ye.oldDirections.bottom }, t]);
+          {
+            let i = [];
+            for (let s of e[0].slice(2)) s.type === "word" && i.push(s.value.toLowerCase());
+            i = i.join(" ");
+            let n = Ye.oldDirections[i] || i;
+            return e[0] = [{ type: "word", value: n }, t], e[0];
+          }
+        }
+        cloneDiv(e) {
+          for (let t of e) if (t.type === "div" && t.value === ",") return t;
+          return { type: "div", value: ",", after: " " };
+        }
+        colorStops(e) {
+          let t = [];
+          for (let i = 0; i < e.length; i++) {
+            let n, s = e[i], a;
+            if (i === 0) continue;
+            let o = Pl.stringify(s[0]);
+            s[1] && s[1].type === "word" ? n = s[1].value : s[2] && s[2].type === "word" && (n = s[2].value);
+            let u;
+            i === 1 && (!n || n === "0%")
+              ? u = `from(${o})`
+              : i === e.length - 1 && (!n || n === "100%")
+              ? u = `to(${o})`
+              : n
+              ? u = `color-stop(${n}, ${o})`
+              : u = `color-stop(${o})`;
+            let c = s[s.length - 1];
+            e[i] = [{ type: "word", value: u }], c.type === "div" && c.value === "," && (a = e[i].push(c)), t.push(a);
+          }
+          return t;
+        }
+        old(e) {
+          if (e === "-webkit-") {
+            let t = this.name === "linear-gradient" ? "linear" : "radial",
+              i = "-gradient",
+              n = CA.regexp(`-webkit-(${t}-gradient|gradient\\(\\s*${t})`, !1);
+            return new SA(this.name, e + this.name, i, n);
+          } else return super.old(e);
+        }
+        add(e, t) {
+          let i = e.prop;
+          if (i.includes("mask")) {
+            if (t === "-webkit-" || t === "-webkit- old") return super.add(e, t);
+            else if (i === "list-style" || i === "list-style-image" || i === "content") {
+              if (t === "-webkit-" || t === "-webkit- old") return super.add(e, t);
+            } else return super.add(e, t);
+          }
+        }
+      };
+    Ye.names = ["linear-gradient", "repeating-linear-gradient", "radial-gradient", "repeating-radial-gradient"];
+    Ye.directions = { top: "bottom", left: "right", bottom: "top", right: "left" };
+    Ye.oldDirections = {
+      top: "left bottom, left top",
+      left: "right top, left top",
+      bottom: "left top, left bottom",
+      right: "left top, right top",
+      "top right": "left bottom, right top",
+      "top left": "right bottom, left top",
+      "right top": "left bottom, right top",
+      "right bottom": "left top, right bottom",
+      "bottom right": "left top, right bottom",
+      "bottom left": "right top, left bottom",
+      "left top": "right bottom, left top",
+      "left bottom": "right top, left bottom",
+    };
+    ib.exports = Ye;
+  });
+  var ob = v((eq, ab) => {
+    l();
+    var AA = Vt(), OA = ke();
+    function sb(r) {
+      return new RegExp(`(^|[\\s,(])(${r}($|[\\s),]))`, "gi");
+    }
+    var Dl = class extends OA {
+      regexp() {
+        return this.regexpCache || (this.regexpCache = sb(this.name)), this.regexpCache;
+      }
+      isStretch() {
+        return this.name === "stretch" || this.name === "fill" || this.name === "fill-available";
+      }
+      replace(e, t) {
+        return t === "-moz-" && this.isStretch()
+          ? e.replace(this.regexp(), "$1-moz-available$3")
+          : t === "-webkit-" && this.isStretch()
+          ? e.replace(this.regexp(), "$1-webkit-fill-available$3")
+          : super.replace(e, t);
+      }
+      old(e) {
+        let t = e + this.name;
+        return this.isStretch()
+          && (e === "-moz-" ? t = "-moz-available" : e === "-webkit-" && (t = "-webkit-fill-available")),
+          new AA(this.name, t, t, sb(t));
+      }
+      add(e, t) {
+        if (!(e.prop.includes("grid") && t !== "-webkit-")) return super.add(e, t);
+      }
+    };
+    Dl.names = ["max-content", "min-content", "fit-content", "fill", "fill-available", "stretch"];
+    ab.exports = Dl;
+  });
+  var fb = v((tq, ub) => {
+    l();
+    var lb = Vt(),
+      EA = ke(),
+      Il = class extends EA {
+        replace(e, t) {
+          return t === "-webkit-"
+            ? e.replace(this.regexp(), "$1-webkit-optimize-contrast")
+            : t === "-moz-"
+            ? e.replace(this.regexp(), "$1-moz-crisp-edges")
+            : super.replace(e, t);
+        }
+        old(e) {
+          return e === "-webkit-"
+            ? new lb(this.name, "-webkit-optimize-contrast")
+            : e === "-moz-"
+            ? new lb(this.name, "-moz-crisp-edges")
+            : super.old(e);
+        }
+      };
+    Il.names = ["pixelated"];
+    ub.exports = Il;
+  });
+  var pb = v((rq, cb) => {
+    l();
+    var TA = ke(),
+      ql = class extends TA {
+        replace(e, t) {
+          let i = super.replace(e, t);
+          return t === "-webkit-" && (i = i.replace(/("[^"]+"|'[^']+')(\s+\d+\w)/gi, "url($1)$2")), i;
+        }
+      };
+    ql.names = ["image-set"];
+    cb.exports = ql;
+  });
+  var hb = v((iq, db) => {
+    l();
+    var PA = me().list,
+      DA = ke(),
+      Rl = class extends DA {
+        replace(e, t) {
+          return PA.space(e).map(i => {
+            if (i.slice(0, +this.name.length + 1) !== this.name + "(") return i;
+            let n = i.lastIndexOf(")"), s = i.slice(n + 1), a = i.slice(this.name.length + 1, n);
+            if (t === "-webkit-") {
+              let o = a.match(/\d*.?\d+%?/);
+              o ? (a = a.slice(o[0].length).trim(), a += `, ${o[0]}`) : a += ", 0.5";
+            }
+            return t + this.name + "(" + a + ")" + s;
+          }).join(" ");
+        }
+      };
+    Rl.names = ["cross-fade"];
+    db.exports = Rl;
+  });
+  var gb = v((nq, mb) => {
+    l();
+    var IA = de(),
+      qA = Vt(),
+      RA = ke(),
+      Ml = class extends RA {
+        constructor(e, t) {
+          super(e, t);
+          e === "display-flex" && (this.name = "flex");
+        }
+        check(e) {
+          return e.prop === "display" && e.value === this.name;
+        }
+        prefixed(e) {
+          let t, i;
+          return [t, e] = IA(e),
+            t === 2009
+              ? this.name === "flex" ? i = "box" : i = "inline-box"
+              : t === 2012
+              ? this.name === "flex" ? i = "flexbox" : i = "inline-flexbox"
+              : t === "final" && (i = this.name),
+            e + i;
+        }
+        replace(e, t) {
+          return this.prefixed(t);
+        }
+        old(e) {
+          let t = this.prefixed(e);
+          if (!!t) return new qA(this.name, t);
+        }
+      };
+    Ml.names = ["display-flex", "inline-flex"];
+    mb.exports = Ml;
+  });
+  var bb = v((sq, yb) => {
+    l();
+    var MA = ke(),
+      Fl = class extends MA {
+        constructor(e, t) {
+          super(e, t);
+          e === "display-grid" && (this.name = "grid");
+        }
+        check(e) {
+          return e.prop === "display" && e.value === this.name;
+        }
+      };
+    Fl.names = ["display-grid", "inline-grid"];
+    yb.exports = Fl;
+  });
+  var vb = v((aq, wb) => {
+    l();
+    var FA = ke(),
+      Nl = class extends FA {
+        constructor(e, t) {
+          super(e, t);
+          e === "filter-function" && (this.name = "filter");
+        }
+      };
+    Nl.names = ["filter", "filter-function"];
+    wb.exports = Nl;
+  });
+  var _b = v((oq, Sb) => {
+    l();
+    var xb = ei(),
+      R = q(),
+      kb = gm(),
+      NA = xm(),
+      LA = jo(),
+      BA = $m(),
+      Ll = ft(),
+      Zt = Ut(),
+      $A = Ym(),
+      $e = ke(),
+      er = ue(),
+      jA = Jm(),
+      zA = Km(),
+      VA = eg(),
+      UA = rg(),
+      WA = og(),
+      GA = fg(),
+      HA = pg(),
+      YA = hg(),
+      QA = gg(),
+      JA = bg(),
+      XA = vg(),
+      KA = kg(),
+      ZA = _g(),
+      eO = Ag(),
+      tO = Eg(),
+      rO = Dg(),
+      iO = qg(),
+      nO = Fg(),
+      sO = Lg(),
+      aO = $g(),
+      oO = Vg(),
+      lO = Wg(),
+      uO = Yg(),
+      fO = Jg(),
+      cO = Kg(),
+      pO = ey(),
+      dO = ry(),
+      hO = sy(),
+      mO = oy(),
+      gO = uy(),
+      yO = cy(),
+      bO = dy(),
+      wO = my(),
+      vO = yy(),
+      xO = vy(),
+      kO = ky(),
+      SO = _y(),
+      _O = Ay(),
+      CO = Ey(),
+      AO = Dy(),
+      OO = qy(),
+      EO = My(),
+      TO = Ly(),
+      PO = $y(),
+      DO = zy(),
+      IO = Wy(),
+      qO = Hy(),
+      RO = Qy(),
+      MO = nb(),
+      FO = ob(),
+      NO = fb(),
+      LO = pb(),
+      BO = hb(),
+      $O = gb(),
+      jO = bb(),
+      zO = vb();
+    Zt.hack(jA);
+    Zt.hack(zA);
+    Zt.hack(VA);
+    Zt.hack(UA);
+    R.hack(WA);
+    R.hack(GA);
+    R.hack(HA);
+    R.hack(YA);
+    R.hack(QA);
+    R.hack(JA);
+    R.hack(XA);
+    R.hack(KA);
+    R.hack(ZA);
+    R.hack(eO);
+    R.hack(tO);
+    R.hack(rO);
+    R.hack(iO);
+    R.hack(nO);
+    R.hack(sO);
+    R.hack(aO);
+    R.hack(oO);
+    R.hack(lO);
+    R.hack(uO);
+    R.hack(fO);
+    R.hack(cO);
+    R.hack(pO);
+    R.hack(dO);
+    R.hack(hO);
+    R.hack(mO);
+    R.hack(gO);
+    R.hack(yO);
+    R.hack(bO);
+    R.hack(wO);
+    R.hack(vO);
+    R.hack(xO);
+    R.hack(kO);
+    R.hack(SO);
+    R.hack(_O);
+    R.hack(CO);
+    R.hack(AO);
+    R.hack(OO);
+    R.hack(EO);
+    R.hack(TO);
+    R.hack(PO);
+    R.hack(DO);
+    R.hack(IO);
+    R.hack(qO);
+    R.hack(RO);
+    $e.hack(MO);
+    $e.hack(FO);
+    $e.hack(NO);
+    $e.hack(LO);
+    $e.hack(BO);
+    $e.hack($O);
+    $e.hack(jO);
+    $e.hack(zO);
+    var Bl = new Map(),
+      ri = class {
+        constructor(e, t, i = {}) {
+          this.data = e,
+            this.browsers = t,
+            this.options = i,
+            [this.add, this.remove] = this.preprocess(this.select(this.data)),
+            this.transition = new NA(this),
+            this.processor = new LA(this);
+        }
+        cleaner() {
+          if (this.cleanerCache) return this.cleanerCache;
+          if (this.browsers.selected.length) {
+            let e = new Ll(this.browsers.data, []);
+            this.cleanerCache = new ri(this.data, e, this.options);
+          } else return this;
+          return this.cleanerCache;
+        }
+        select(e) {
+          let t = { add: {}, remove: {} };
+          for (let i in e) {
+            let n = e[i],
+              s = n.browsers.map(u => {
+                let c = u.split(" ");
+                return { browser: `${c[0]} ${c[1]}`, note: c[2] };
+              }),
+              a = s.filter(u => u.note).map(u => `${this.browsers.prefix(u.browser)} ${u.note}`);
+            a = er.uniq(a),
+              s = s.filter(u => this.browsers.isSelected(u.browser)).map(u => {
+                let c = this.browsers.prefix(u.browser);
+                return u.note ? `${c} ${u.note}` : c;
+              }),
+              s = this.sort(er.uniq(s)),
+              this.options.flexbox === "no-2009" && (s = s.filter(u => !u.includes("2009")));
+            let o = n.browsers.map(u => this.browsers.prefix(u));
+            n.mistakes && (o = o.concat(n.mistakes)),
+              o = o.concat(a),
+              o = er.uniq(o),
+              s.length
+                ? (t.add[i] = s, s.length < o.length && (t.remove[i] = o.filter(u => !s.includes(u))))
+                : t.remove[i] = o;
+          }
+          return t;
+        }
+        sort(e) {
+          return e.sort((t, i) => {
+            let n = er.removeNote(t).length, s = er.removeNote(i).length;
+            return n === s ? i.length - t.length : s - n;
+          });
+        }
+        preprocess(e) {
+          let t = { selectors: [], "@supports": new BA(ri, this) };
+          for (let n in e.add) {
+            let s = e.add[n];
+            if (n === "@keyframes" || n === "@viewport") t[n] = new $A(n, s, this);
+            else if (n === "@resolution") t[n] = new kb(n, s, this);
+            else if (this.data[n].selector) t.selectors.push(Zt.load(n, s, this));
+            else {
+              let a = this.data[n].props;
+              if (a) {
+                let o = $e.load(n, s, this);
+                for (let u of a) t[u] || (t[u] = { values: [] }), t[u].values.push(o);
+              } else {
+                let o = t[n] && t[n].values || [];
+                t[n] = R.load(n, s, this), t[n].values = o;
+              }
+            }
+          }
+          let i = { selectors: [] };
+          for (let n in e.remove) {
+            let s = e.remove[n];
+            if (this.data[n].selector) {
+              let a = Zt.load(n, s);
+              for (let o of s) i.selectors.push(a.old(o));
+            } else if (n === "@keyframes" || n === "@viewport") {
+              for (let a of s) {
+                let o = `@${a}${n.slice(1)}`;
+                i[o] = { remove: !0 };
+              }
+            } else if (n === "@resolution") i[n] = new kb(n, s, this);
+            else {
+              let a = this.data[n].props;
+              if (a) {
+                let o = $e.load(n, [], this);
+                for (let u of s) {
+                  let c = o.old(u);
+                  if (c) for (let f of a) i[f] || (i[f] = {}), i[f].values || (i[f].values = []), i[f].values.push(c);
+                }
+              } else {for (let o of s) {
+                  let u = this.decl(n).old(n, o);
+                  if (n === "align-self") {
+                    let c = t[n] && t[n].prefixes;
+                    if (c) {
+                      if (o === "-webkit- 2009" && c.includes("-webkit-")) continue;
+                      if (o === "-webkit-" && c.includes("-webkit- 2009")) continue;
+                    }
+                  }
+                  for (let c of u) i[c] || (i[c] = {}), i[c].remove = !0;
+                }}
+            }
+          }
+          return [t, i];
+        }
+        decl(e) {
+          return Bl.has(e) || Bl.set(e, R.load(e)), Bl.get(e);
+        }
+        unprefixed(e) {
+          let t = this.normalize(xb.unprefixed(e));
+          return t === "flex-direction" && (t = "flex-flow"), t;
+        }
+        normalize(e) {
+          return this.decl(e).normalize(e);
+        }
+        prefixed(e, t) {
+          return e = xb.unprefixed(e), this.decl(e).prefixed(e, t);
+        }
+        values(e, t) {
+          let i = this[e], n = i["*"] && i["*"].values, s = i[t] && i[t].values;
+          return n && s ? er.uniq(n.concat(s)) : n || s || [];
+        }
+        group(e) {
+          let t = e.parent,
+            i = t.index(e),
+            { length: n } = t.nodes,
+            s = this.unprefixed(e.prop),
+            a = (o, u) => {
+              for (i += o; i >= 0 && i < n;) {
+                let c = t.nodes[i];
+                if (c.type === "decl") {
+                  if (o === -1 && c.prop === s && !Ll.withPrefix(c.value) || this.unprefixed(c.prop) !== s) break;
+                  if (u(c) === !0) return !0;
+                  if (o === 1 && c.prop === s && !Ll.withPrefix(c.value)) break;
+                }
+                i += o;
+              }
+              return !1;
+            };
+          return {
+            up(o) {
+              return a(-1, o);
+            },
+            down(o) {
+              return a(1, o);
+            },
+          };
+        }
+      };
+    Sb.exports = ri;
+  });
+  var Ab = v((lq, Cb) => {
+    l();
+    Cb.exports = {
+      "backface-visibility": {
+        mistakes: ["-ms-", "-o-"],
+        feature: "transforms3d",
+        browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7", "safari 14.1"],
+      },
+      "backdrop-filter": {
+        feature: "css-backdrop-filter",
+        browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7", "safari 14.1"],
+      },
+      element: {
+        props: [
+          "background",
+          "background-image",
+          "border-image",
+          "mask",
+          "list-style",
+          "list-style-image",
+          "content",
+          "mask-image",
+        ],
+        feature: "css-element-function",
+        browsers: ["firefox 89"],
+      },
+      "user-select": {
+        mistakes: ["-khtml-"],
+        feature: "user-select-none",
+        browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7", "safari 14.1"],
+      },
+      "background-clip": {
+        feature: "background-clip-text",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      hyphens: { feature: "css-hyphens", browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7", "safari 14.1"] },
+      ":fullscreen": { selector: !0, feature: "fullscreen", browsers: ["and_chr 92", "and_uc 12.12", "safari 14.1"] },
+      "::backdrop": { selector: !0, feature: "fullscreen", browsers: ["and_chr 92", "and_uc 12.12", "safari 14.1"] },
+      "::file-selector-button": { selector: !0, feature: "fullscreen", browsers: ["safari 14.1"] },
+      "tab-size": { feature: "css3-tabsize", browsers: ["firefox 89"] },
+      fill: {
+        props: [
+          "width",
+          "min-width",
+          "max-width",
+          "height",
+          "min-height",
+          "max-height",
+          "inline-size",
+          "min-inline-size",
+          "max-inline-size",
+          "block-size",
+          "min-block-size",
+          "max-block-size",
+          "grid",
+          "grid-template",
+          "grid-template-rows",
+          "grid-template-columns",
+          "grid-auto-columns",
+          "grid-auto-rows",
+        ],
+        feature: "intrinsic-width",
+        browsers: ["and_chr 92", "chrome 91", "chrome 92", "edge 91", "samsung 14.0"],
+      },
+      "fill-available": {
+        props: [
+          "width",
+          "min-width",
+          "max-width",
+          "height",
+          "min-height",
+          "max-height",
+          "inline-size",
+          "min-inline-size",
+          "max-inline-size",
+          "block-size",
+          "min-block-size",
+          "max-block-size",
+          "grid",
+          "grid-template",
+          "grid-template-rows",
+          "grid-template-columns",
+          "grid-auto-columns",
+          "grid-auto-rows",
+        ],
+        feature: "intrinsic-width",
+        browsers: ["and_chr 92", "chrome 91", "chrome 92", "edge 91", "samsung 14.0"],
+      },
+      stretch: {
+        props: [
+          "width",
+          "min-width",
+          "max-width",
+          "height",
+          "min-height",
+          "max-height",
+          "inline-size",
+          "min-inline-size",
+          "max-inline-size",
+          "block-size",
+          "min-block-size",
+          "max-block-size",
+          "grid",
+          "grid-template",
+          "grid-template-rows",
+          "grid-template-columns",
+          "grid-auto-columns",
+          "grid-auto-rows",
+        ],
+        feature: "intrinsic-width",
+        browsers: ["firefox 89"],
+      },
+      "fit-content": {
+        props: [
+          "width",
+          "min-width",
+          "max-width",
+          "height",
+          "min-height",
+          "max-height",
+          "inline-size",
+          "min-inline-size",
+          "max-inline-size",
+          "block-size",
+          "min-block-size",
+          "max-block-size",
+          "grid",
+          "grid-template",
+          "grid-template-rows",
+          "grid-template-columns",
+          "grid-auto-columns",
+          "grid-auto-rows",
+        ],
+        feature: "intrinsic-width",
+        browsers: ["firefox 89"],
+      },
+      "text-decoration-style": { feature: "text-decoration", browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7"] },
+      "text-decoration-color": { feature: "text-decoration", browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7"] },
+      "text-decoration-line": { feature: "text-decoration", browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7"] },
+      "text-decoration": { feature: "text-decoration", browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7"] },
+      "text-decoration-skip": { feature: "text-decoration", browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7"] },
+      "text-decoration-skip-ink": { feature: "text-decoration", browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7"] },
+      "text-size-adjust": { feature: "text-size-adjust", browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7"] },
+      "mask-clip": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-composite": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-image": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-origin": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-repeat": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-border-repeat": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-border-source": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      mask: {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-position": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-size": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-border": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-border-outset": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-border-width": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "mask-border-slice": {
+        feature: "css-masks",
+        browsers: [
+          "and_chr 92",
+          "and_uc 12.12",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "clip-path": {
+        feature: "css-clip-path",
+        browsers: ["and_uc 12.12", "ios_saf 14.0-14.4", "ios_saf 14.5-14.7", "safari 14.1", "samsung 14.0"],
+      },
+      "box-decoration-break": {
+        feature: "css-boxdecorationbreak",
+        browsers: [
+          "and_chr 92",
+          "chrome 91",
+          "chrome 92",
+          "edge 91",
+          "ios_saf 14.0-14.4",
+          "ios_saf 14.5-14.7",
+          "safari 14.1",
+          "samsung 14.0",
+        ],
+      },
+      "@resolution": {
+        feature: "css-media-resolution",
+        browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7", "safari 14.1"],
+      },
+      "border-inline-start": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "border-inline-end": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "margin-inline-start": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "margin-inline-end": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "padding-inline-start": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "padding-inline-end": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "border-block-start": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "border-block-end": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "margin-block-start": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "margin-block-end": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "padding-block-start": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      "padding-block-end": { feature: "css-logical-props", browsers: ["and_uc 12.12"] },
+      appearance: {
+        feature: "css-appearance",
+        browsers: ["and_uc 12.12", "ios_saf 14.0-14.4", "ios_saf 14.5-14.7", "safari 14.1", "samsung 14.0"],
+      },
+      "image-set": {
+        props: [
+          "background",
+          "background-image",
+          "border-image",
+          "cursor",
+          "mask",
+          "mask-image",
+          "list-style",
+          "list-style-image",
+          "content",
+        ],
+        feature: "css-image-set",
+        browsers: ["and_chr 92", "and_uc 12.12", "chrome 91", "chrome 92", "edge 91", "samsung 14.0"],
+      },
+      "cross-fade": {
+        props: [
+          "background",
+          "background-image",
+          "border-image",
+          "mask",
+          "list-style",
+          "list-style-image",
+          "content",
+          "mask-image",
+        ],
+        feature: "css-cross-fade",
+        browsers: ["and_chr 92", "and_uc 12.12", "chrome 91", "chrome 92", "edge 91", "samsung 14.0"],
+      },
+      "text-emphasis": {
+        feature: "text-emphasis",
+        browsers: ["and_chr 92", "and_uc 12.12", "chrome 91", "chrome 92", "edge 91", "samsung 14.0"],
+      },
+      "text-emphasis-position": {
+        feature: "text-emphasis",
+        browsers: ["and_chr 92", "and_uc 12.12", "chrome 91", "chrome 92", "edge 91", "samsung 14.0"],
+      },
+      "text-emphasis-style": {
+        feature: "text-emphasis",
+        browsers: ["and_chr 92", "and_uc 12.12", "chrome 91", "chrome 92", "edge 91", "samsung 14.0"],
+      },
+      "text-emphasis-color": {
+        feature: "text-emphasis",
+        browsers: ["and_chr 92", "and_uc 12.12", "chrome 91", "chrome 92", "edge 91", "samsung 14.0"],
+      },
+      ":any-link": { selector: !0, feature: "css-any-link", browsers: ["and_uc 12.12"] },
+      isolate: {
+        props: ["unicode-bidi"],
+        feature: "css-unicode-bidi",
+        browsers: ["ios_saf 14.0-14.4", "ios_saf 14.5-14.7", "safari 14.1"],
+      },
+      "color-adjust": { feature: "css-color-adjust", browsers: ["chrome 91", "chrome 92", "edge 91", "safari 14.1"] },
+    };
+  });
+  var Eb = v((uq, Ob) => {
+    l();
+    Ob.exports = {};
+  });
+  var Ib = v((fq, Db) => {
+    l();
+    var VO = Fo(),
+      { agents: UO } = (Ln(), Nn),
+      $l = rm(),
+      WO = ft(),
+      GO = _b(),
+      HO = Ab(),
+      YO = Eb(),
+      Tb = { browsers: UO, prefixes: HO },
+      Pb = `
+  Replace Autoprefixer \`browsers\` option to Browserslist config.
+  Use \`browserslist\` key in \`package.json\` or \`.browserslistrc\` file.
+
+  Using \`browsers\` option can cause errors. Browserslist config can
+  be used for Babel, Autoprefixer, postcss-normalize and other tools.
+
+  If you really need to use option, rename it to \`overrideBrowserslist\`.
+
+  Learn more at:
+  https://github.com/browserslist/browserslist#readme
+  https://twitter.com/browserslist
+
+`;
+    function QO(r) {
+      return Object.prototype.toString.apply(r) === "[object Object]";
+    }
+    var jl = new Map();
+    function JO(r, e) {
+      e.browsers.selected.length !== 0
+        && (e.add.selectors.length > 0 || Object.keys(e.add).length > 2
+          || r.warn(`Autoprefixer target browsers do not need any prefixes.You do not need Autoprefixer anymore.
+Check your Browserslist config to be sure that your targets are set up correctly.
+
+  Learn more at:
+  https://github.com/postcss/autoprefixer#readme
+  https://github.com/browserslist/browserslist#readme
+
+`));
+    }
+    Db.exports = tr;
+    function tr(...r) {
+      let e;
+      if (
+        r.length === 1 && QO(r[0])
+          ? (e = r[0], r = void 0)
+          : r.length === 0 || r.length === 1 && !r[0]
+          ? r = void 0
+          : r.length <= 2 && (Array.isArray(r[0]) || !r[0])
+          ? (e = r[1], r = r[0])
+          : typeof r[r.length - 1] == "object" && (e = r.pop()),
+          e || (e = {}),
+          e.browser
+      ) throw new Error("Change `browser` option to `overrideBrowserslist` in Autoprefixer");
+      if (e.browserslist) throw new Error("Change `browserslist` option to `overrideBrowserslist` in Autoprefixer");
+      e.overrideBrowserslist
+        ? r = e.overrideBrowserslist
+        : e.browsers && (typeof console != "undefined" && console.warn && ($l.red
+          ? console.warn($l.red(Pb.replace(/`[^`]+`/g, n => $l.yellow(n.slice(1, -1)))))
+          : console.warn(Pb)),
+          r = e.browsers);
+      let t = { ignoreUnknownVersions: e.ignoreUnknownVersions, stats: e.stats, env: e.env };
+      function i(n) {
+        let s = Tb, a = new WO(s.browsers, r, n, t), o = a.selected.join(", ") + JSON.stringify(e);
+        return jl.has(o) || jl.set(o, new GO(s.prefixes, a, e)), jl.get(o);
+      }
+      return {
+        postcssPlugin: "autoprefixer",
+        prepare(n) {
+          let s = i({ from: n.opts.from, env: e.env });
+          return {
+            OnceExit(a) {
+              JO(n, s), e.remove !== !1 && s.processor.remove(a, n), e.add !== !1 && s.processor.add(a, n);
+            },
+          };
+        },
+        info(n) {
+          return n = n || {}, n.from = n.from || m.cwd(), YO(i(n));
+        },
+        options: e,
+        browsers: r,
+      };
+    }
+    tr.postcss = !0;
+    tr.data = Tb;
+    tr.defaults = VO.defaults;
+    tr.info = () => tr().info();
+  });
+  var qb = {};
+  Ce(qb, { default: () => XO });
+  var XO,
+    Rb = C(() => {
+      l();
+      XO = [];
+    });
+  var Fb = {};
+  Ce(Fb, { default: () => KO });
+  var Mb,
+    KO,
+    Nb = C(() => {
+      l();
+      ui();
+      Mb = K(hi()), KO = Ke(Mb.default.theme);
+    });
+  var Bb = {};
+  Ce(Bb, { default: () => ZO });
+  var Lb,
+    ZO,
+    $b = C(() => {
+      l();
+      ui();
+      Lb = K(hi()), ZO = Ke(Lb.default);
+    });
+  l();
+  "use strict";
+  var eE = Qe(em()),
+    tE = Qe(me()),
+    rE = Qe(Ib()),
+    iE = Qe((Rb(), qb)),
+    nE = Qe((Nb(), Fb)),
+    sE = Qe(($b(), Bb)),
+    aE = Qe((Gn(), au)),
+    oE = Qe((uo(), lo)),
+    lE = Qe((os(), $u));
+  function Qe(r) {
+    return r && r.__esModule ? r : { default: r };
+  }
+  console.warn(
+    "cdn.tailwindcss.com should not be used in production. To use Tailwind CSS in production, install it as a PostCSS plugin or use the Tailwind CLI: https://tailwindcss.com/docs/installation",
+  );
+  var $n = "tailwind",
+    zl = "text/tailwindcss",
+    jb = "/template.html",
+    bt,
+    zb = !0,
+    Vb = 0,
+    Vl = new Set(),
+    Ul,
+    Ub = "",
+    Wb = (r = !1) => ({
+      get(e, t) {
+        return (!r || t === "config") && typeof e[t] == "object" && e[t] !== null ? new Proxy(e[t], Wb()) : e[t];
+      },
+      set(e, t, i) {
+        return e[t] = i, (!r || t === "config") && Wl(!0), !0;
+      },
+    });
+  window[$n] = new Proxy({
+    config: {},
+    defaultTheme: nE.default,
+    defaultConfig: sE.default,
+    colors: aE.default,
+    plugin: oE.default,
+    resolveConfig: lE.default,
+  }, Wb(!0));
+  function Gb(r) {
+    Ul.observe(r, { attributes: !0, attributeFilter: ["type"], characterData: !0, subtree: !0, childList: !0 });
+  }
+  new MutationObserver(async r => {
+    let e = !1;
+    if (!Ul) {
+      Ul = new MutationObserver(async () => await Wl(!0));
+      for (let t of document.querySelectorAll(`style[type="${zl}"]`)) Gb(t);
+    }
+    for (let t of r) {
+      for (let i of t.addedNodes) {
+        i.nodeType === 1 && i.tagName === "STYLE" && i.getAttribute("type") === zl && (Gb(i), e = !0);
+      }
+    }
+    await Wl(e);
+  }).observe(document.documentElement, { attributes: !0, attributeFilter: ["class"], childList: !0, subtree: !0 });
+  async function Wl(r = !1) {
+    r && (Vb++, Vl.clear());
+    let e = "";
+    for (let i of document.querySelectorAll(`style[type="${zl}"]`)) e += i.textContent;
+    let t = new Set();
+    for (let i of document.querySelectorAll("[class]")) for (let n of i.classList) Vl.has(n) || t.add(n);
+    if (document.body && (zb || t.size > 0 || e !== Ub || !bt || !bt.isConnected)) {
+      for (let n of t) Vl.add(n);
+      zb = !1, Ub = e, self[jb] = Array.from(t).join(" ");
+      let i = (0, tE.default)([
+        (0, eE.default)({
+          ...window[$n].config,
+          _hash: Vb,
+          content: [jb],
+          plugins: [...iE.default, ...Array.isArray(window[$n].config.plugins) ? window[$n].config.plugins : []],
+        }),
+        (0, rE.default)({ remove: !1 }),
+      ]).process(`@tailwind base;@tailwind components;@tailwind utilities;${e}`).css;
+      (!bt || !bt.isConnected) && (bt = document.createElement("style"), document.head.append(bt)), bt.textContent = i;
+    }
+  }
+})();
+/*! https://mths.be/cssesc v3.0.0 by @mathias */
diff --git a/assets/styles/PBA-theme.css b/assets/styles/PBA-theme.css
new file mode 100644
index 00000000..d9b3d8f6
--- /dev/null
+++ b/assets/styles/PBA-theme.css
@@ -0,0 +1,684 @@
+/**
+ * PBA slide theme
+ * Derived from the night theme in reveal.js
+ * More info https://github.com/webpro/reveal-md#theme & https://revealjs.com/themes/
+**/
+
+/*********************************************
+	 * NAVIGATION CONTROLS
+	 *********************************************/
+.reveal .controls {
+	color: var(--r-color-controls);
+}
+
+/*********************************************
+     * PROGRESS BAR
+     *********************************************/
+.reveal .progress {
+	background: rgba(0, 0, 0, 0.2);
+	color: var(--r-color-controls);
+	height: 0.15em;
+}
+
+/*********************************************
+     * PRINT BACKGROUND
+     *********************************************/
+@media print {
+	.backgrounds {
+		background-color: var(--r-background-color);
+	}
+}
+
+/*********************************************
+   * FONTS
+   *********************************************/
+/* font: unbounded https://unbounded.polkadot.network/ */
+@font-face {
+	font-family: 'Unbounded';
+	font-style: normal;
+	font-weight: 300;
+	src: url('./fonts/unbounded/Unbounded-Light.woff2');
+	src: local(''),
+		url('./fonts/unbounded/Unbounded-Light.woff2') format('woff2'),
+		/* Super Modern Browsers */
+		url('./fonts/unbounded/Unbounded-Light.ttf') format('truetype'),
+		/* Safari, Android, iOS */
+}
+
+@font-face {
+	font-family: 'Unbounded';
+	font-style: normal;
+	font-weight: 400;
+	src: url('./fonts/unbounded/Unbounded-Regular.woff2');
+	src: local(''),
+		url('./fonts/unbounded/Unbounded-Regular.woff2') format('woff2'),
+		/* Super Modern Browsers */
+		url('./fonts/unbounded/Unbounded-Regular.ttf') format('truetype'),
+		/* Safari, Android, iOS */
+}
+
+@font-face {
+	font-family: 'Unbounded';
+	font-style: normal;
+	font-weight: 700;
+	src: url('./fonts/unbounded/Unbounded-Bold.woff2');
+	src: local(''),
+		url('./fonts/unbounded/Unbounded-Bold.woff2') format('woff2'),
+		/* Super Modern Browsers */
+		url('./fonts/unbounded/Unbounded-Bold.ttf') format('truetype'),
+		/* Safari, Android, iOS */
+}
+
+/* fonts: work-sans-regular - latin	https://google-webfonts-helper.herokuapp.com/fonts/work-sans/work-sans?subsets=latin */
+@font-face {
+	font-family: 'Work Sans';
+	font-style: normal;
+	font-weight: 400;
+	src: local(''),
+		url('./fonts/work-sans/work-sans-v17-latin-regular.eot?#iefix') format('embedded-opentype'),
+		/* IE6-IE8 */
+		url('./fonts/work-sans/work-sans-v17-latin-regular.woff2') format('woff2'),
+		/* Super Modern Browsers */
+		url('./fonts/work-sans/work-sans-v17-latin-regular.woff') format('woff'),
+		/* Modern Browsers */
+		url('./fonts/work-sans/work-sans-v17-latin-regular.ttf') format('truetype'),
+		/* Safari, Android, iOS */
+		url('./fonts/work-sans/work-sans-v17-latin-regular.svg#WorkSans') format('svg');
+	/* Legacy iOS */
+}
+
+/* work-sans-800 - latin */
+@font-face {
+	font-family: 'Work Sans';
+	font-style: normal;
+	font-weight: 800;
+	src: url('./fonts/work-sans/work-sans-v17-latin-800.eot');
+	/* IE9 Compat Modes */
+	src: local(''),
+		url('./fonts/work-sans/work-sans-v17-latin-800.eot?#iefix') format('embedded-opentype'),
+		/* IE6-IE8 */
+		url('./fonts/work-sans/work-sans-v17-latin-800.woff2') format('woff2'),
+		/* Super Modern Browsers */
+		url('./fonts/work-sans/work-sans-v17-latin-800.woff') format('woff'),
+		/* Modern Browsers */
+		url('./fonts/work-sans/work-sans-v17-latin-800.ttf') format('truetype'),
+		/* Safari, Android, iOS */
+		url('./fonts/work-sans/work-sans-v17-latin-800.svg#WorkSans') format('svg');
+	/* Legacy iOS */
+}
+
+/* work-sans-italic - latin */
+@font-face {
+	font-family: 'Work Sans';
+	font-style: italic;
+	font-weight: 400;
+	src: url('./fonts/work-sans/work-sans-v17-latin-italic.eot');
+	/* IE9 Compat Modes */
+	src: local(''),
+		url('./fonts/work-sans/work-sans-v17-latin-italic.eot?#iefix') format('embedded-opentype'),
+		/* IE6-IE8 */
+		url('./fonts/work-sans/work-sans-v17-latin-italic.woff2') format('woff2'),
+		/* Super Modern Browsers */
+		url('./fonts/work-sans/work-sans-v17-latin-italic.woff') format('woff'),
+		/* Modern Browsers */
+		url('./fonts/work-sans/work-sans-v17-latin-italic.ttf') format('truetype'),
+		/* Safari, Android, iOS */
+		url('./fonts/work-sans/work-sans-v17-latin-italic.svg#WorkSans') format('svg');
+	/* Legacy iOS */
+}
+
+/* work-sans-800italic - latin */
+@font-face {
+	font-family: 'Work Sans';
+	font-style: italic;
+	font-weight: 800;
+	src: url('./fonts/work-sans/work-sans-v17-latin-800italic.eot');
+	/* IE9 Compat Modes */
+	src: local(''),
+		url('./fonts/work-sans/work-sans-v17-latin-800italic.eot?#iefix') format('embedded-opentype'),
+		/* IE6-IE8 */
+		url('./fonts/work-sans/work-sans-v17-latin-800italic.woff2') format('woff2'),
+		/* Super Modern Browsers */
+		url('./fonts/work-sans/work-sans-v17-latin-800italic.woff') format('woff'),
+		/* Modern Browsers */
+		url('./fonts/work-sans/work-sans-v17-latin-800italic.ttf') format('truetype'),
+		/* Safari, Android, iOS */
+		url('./fonts/work-sans/work-sans-v17-latin-800italic.svg#WorkSans') format('svg');
+	/* Legacy iOS */
+}
+
+/*********************************************
+ * GLOBAL STYLES
+ *********************************************/
+
+:root {
+	--r-main-font-size: 35px;
+	--r-main-font: "Work Sans";
+	--r-main-color: #fff;
+	--r-background-color: #140526;
+	--r-code-background-color: #000000;
+	--r-block-margin: 0em 30px 15px 30px;
+	--r-heading-margin: 0em 0em 20px 0em;
+	--r-heading-font: "Unbounded";
+	--r-heading-color: #d92f78;
+	--r-heading-line-height: 1.5em;
+	--r-heading-letter-spacing: 0.02em;
+	--r-heading-text-transform: none;
+	--r-heading-text-shadow: none;
+	--r-heading-font-weight: normal;
+	--r-heading1-text-shadow: none;
+	--r-heading1-size: 2em;
+	--r-heading2-size: 1.35em;
+	--r-heading3-size: 1.25em;
+	--r-heading4-size: 1.15em;
+	--r-code-font: monospace;
+	/* custom PBA var */
+	--r-code-font-size: 0.75em;
+	--r-link-color: #ccc;
+	--r-link-color-decoration: #d92f78;
+	--r-color-controls: #d92f78;
+	--r-link-color-dark: #;
+	--r-link-color-hover: #8d3aed;
+	--r-selection-background-color: #8d3aed;
+	--r-selection-color: #fff;
+	--r-padding: 24px;
+
+	/* POLKADOT MAIN COLORS */
+	--r-hub-cyan: #00B2FF;
+	--r-hub-purple: #552BBF;
+	--r-hub-pink: #E6007A;
+	--r-hub-lime: #D3FF33;
+	--r-hub-green: #56F39A;
+
+	/* Colors used in the Polkadot-SDK Lectures */
+	--substrate-green: #25cc85ff;
+	--substrate-runtime: #bb8ba6;
+	--substrate-host: #8d3aed;
+}
+
+/* box sizing;
+	https://css-tricks.com/box-sizing/#aa-universal-box-sizing-with-inheritance */
+html {
+	box-sizing: border-box;
+}
+
+*,
+*:before,
+*:after {
+	box-sizing: inherit;
+}
+
+.reveal-viewport {
+	background: #111;
+	background-color: var(--r-background-color);
+}
+
+section.has-light-background,
+section.has-light-background p,
+section.has-light-background h1,
+section.has-light-background h2,
+section.has-light-background h3,
+section.has-light-background h4,
+section.has-light-background h5,
+section.has-light-background h6 {
+	color: #222;
+}
+
+.reveal {
+	font-family: var(--r-main-font);
+	font-size: var(--r-main-font-size);
+	font-weight: normal;
+	color: var(--r-main-color);
+}
+
+.reveal ::selection {
+	color: var(--r-selection-color);
+	background: var(--r-selection-background-color);
+	text-shadow: none;
+}
+
+.reveal ::-moz-selection {
+	color: var(--r-selection-color);
+	background: var(--r-selection-background-color);
+	text-shadow: none;
+}
+
+.reveal .slides section,
+.reveal .slides section>section {
+	/* line-height: 1.3; */
+	font-weight: inherit;
+}
+
+/*
+  custom-elements
+*/
+/* columns:  a widget to display columns of things */
+
+.site-header {
+	position: fixed;
+	top: 0;
+	left: 0;
+	right: 0;
+	z-index: 99;
+	display: flex;
+	justify-content: space-between;
+	align-items: center;
+	padding: 3%;
+}
+
+.site-header--small {
+	padding: var(--size);
+}
+
+.reveal section {
+	left: 0;
+	padding: var(--r-padding);
+}
+
+pba-cols {
+	margin: var(--r-block-margin);
+	display: flex;
+	align-items: center;
+	gap: calc(var(--r-padding) * 2);
+}
+
+/* TODO: Columns hard coded in style for 2 only, for best results 3 and more need more styling calculated on total columns in slide... Seems to overflow slide on  right side...*/
+pba-col {
+	display: flex;
+	flex: 1;
+}
+
+pba-col {
+	display: block;
+}
+
+pba-col:nth-of-type(2) {
+	padding-right: 0;
+}
+
+pba-col[left] {
+	display: flex;
+	flex-direction: column;
+	align-items: left;
+	text-align: left;
+}
+
+pba-col[center] {
+	display: flex;
+	flex-direction: column;
+	align-items: center;
+	text-align: center;
+}
+
+pba-col[right] {
+	display: flex;
+	flex-direction: column;
+	align-items: right;
+	text-align: right;
+}
+
+pba-flex[left] {
+	display: flex;
+	flex-direction: column;
+	align-items: left;
+	text-align: left;
+}
+
+pba-flex[center] {
+	display: flex;
+	flex-direction: column;
+	align-items: center;
+	text-align: center;
+}
+
+pba-flex[right] {
+	display: flex;
+	flex-direction: column;
+	align-items: right;
+	text-align: right;
+}
+
+
+/*********************************************
+	 * HEADERS
+	 *********************************************/
+.reveal h1,
+.reveal h2,
+.reveal h3,
+.reveal h4,
+.reveal h5,
+.reveal h6 {
+	margin: var(--r-heading-margin);
+	color: var(--r-heading-color);
+	font-family: var(--r-heading-font);
+	font-weight: var(--r-heading-font-weight);
+	line-height: var(--r-heading-line-height);
+	letter-spacing: var(--r-heading-letter-spacing);
+	text-transform: var(--r-heading-text-transform);
+	text-shadow: var(--r-heading-text-shadow);
+	word-wrap: break-word;
+}
+
+.reveal h1 {
+	font-size: var(--r-heading1-size);
+	text-shadow: var(--r-heading1-text-shadow);
+}
+
+.reveal h2 {
+	font-size: var(--r-heading2-size);
+}
+
+.reveal h3 {
+	font-size: var(--r-heading3-size);
+}
+
+.reveal h4 {
+	font-size: var(--r-heading4-size);
+}
+
+/*********************************************
+	 * OTHER
+	 *********************************************/
+.reveal p {
+	margin: var(--r-block-margin);
+	line-height: 1.3;
+}
+
+.mermaid svg {
+	margin-left: auto;
+	margin-right: auto;
+	max-width: 70% !important;
+}
+
+.mermaid.limit {
+	display: block;
+	margin: auto;
+}
+
+.mermaid.size-10 {
+	width: 10%;
+}
+
+.mermaid.size-20 {
+	width: 20%;
+}
+
+.mermaid.size-30 {
+	width: 30%;
+}
+
+.mermaid.size-40 {
+	width: 40%;
+}
+
+.mermaid.size-50 {
+	width: 50%;
+}
+
+.mermaid.size-60 {
+	width: 60%;
+}
+
+.mermaid.size-70 {
+	width: 70%;
+}
+
+.mermaid.size-80 {
+	width: 80%;
+}
+
+.mermaid.size-90 {
+	width: 90%;
+}
+
+/* Ensure certain elements are never larger than the slide itself */
+/* Set in ./reveal.json -> "width": 1400, "height": 900, */
+.reveal img,
+.reveal video,
+.reveal iframe {
+	margin-left: auto;
+	margin-right: auto;
+	max-width: 1300px;
+	max-height: 800px;
+	margin-top: 10px;
+	margin-bottom: 10px;
+}
+
+.reveal img[rounded],
+.reveal video[rounded],
+.reveal iframe[rounded] {
+	border-radius: 0.6em;
+}
+
+.reveal strong,
+.reveal b {
+	font-weight: bold;
+}
+
+.reveal em {
+	font-style: italic;
+}
+
+.reveal ol,
+.reveal dl,
+.reveal ul {
+	position: relative;
+	text-align: left;
+	line-height: 1.2;
+}
+
+.reveal ol {
+	margin-left: -2em;
+}
+
+.reveal ul~ol {
+	margin-left: 0;
+}
+
+
+.reveal ol li,
+.reveal dl li,
+.reveal ul li {
+	margin: var(--r-block-margin);
+	margin-left: 1em;
+}
+
+.reveal * li ol,
+.reveal * li dl,
+.reveal * li ul {
+	margin-top: 0.3em;
+	margin-left: -1em;
+}
+
+.reveal ul,
+.reveal ol {
+	/* Remove default bullets/numbers on lists */
+	list-style: none !important;
+	padding-left: 2em;
+}
+
+.reveal ol>li {
+	counter-increment: count-ol;
+}
+
+.reveal * li ol>li {
+	counter-increment: count-ol-ol;
+}
+
+.reveal ul>li::before {
+	font-family: "Unbounded";
+	font-size: 0.8em;
+	line-height: 1.5em;
+	position: absolute;
+	padding-left: 3em;
+	left: -0.5em;
+	font-family: monospace;
+	/* CSS Code/unicode, hex: https://www.w3schools.com/charsets/ref_utf_symbols.asp */
+	content: "\2688";
+	color: var(--r-hub-cyan);
+}
+
+.reveal ol>li::before {
+	font-family: "Unbounded";
+	font-size: 0.75em;
+	position: relative;
+	font-family: monospace;
+	/* Custom numbers and list item delimiter */
+	/* CSS Code/unicode, hex: https://www.w3schools.com/charsets/ref_utf_symbols.asp */
+	/* Change the color */
+	color: var(--r-hub-cyan);
+	font-weight: bold;
+}
+
+.reveal ol>li::before {
+	content: counters(count-ol, ".") ": ";
+}
+
+.reveal * li ol>li::before {
+	content: counters(count-ol-ol, ".") ": ";
+}
+
+.reveal blockquote {
+	display: inline-block;
+	padding: 0.7em;
+	font-style: italic;
+	background: rgba(255, 255, 255, 0.1);
+	border-radius: 0.6em;
+	margin: var(--r-block-margin);
+}
+
+.reveal blockquote * {
+	margin: 0em !important;
+}
+
+.reveal q {
+	font-style: italic;
+}
+
+.reveal pre {
+	font-size: var(--r-code-font-size);
+	font-family: var(--r-code-font);
+	display: block;
+	position: relative;
+	margin: var(--r-block-margin) auto;
+	line-height: 1.2em;
+	word-wrap: break-word;
+	text-align: left;
+}
+
+.reveal code {
+	font-family: var(--r-code-font);
+	text-transform: none;
+	tab-size: 2;
+	background-color: var(--r-code-background-color);
+}
+
+.reveal pre code {
+	display: block;
+	overflow: auto;
+	max-height: 650px;
+	word-wrap: break-word;
+}
+
+.reveal .code-wrapper {
+	white-space: normal;
+}
+
+.reveal .code-wrapper code {
+	white-space: pre;
+}
+
+.reveal table {
+	margin: auto;
+	border-collapse: collapse;
+	border-spacing: 0;
+}
+
+.reveal table th {
+	font-weight: bold;
+}
+
+.reveal table th,
+.reveal table td {
+	text-align: left;
+	padding: 0.2em 0.5em 0.2em 0.5em;
+	border-bottom: 1px solid;
+}
+
+.reveal table th[align="center"],
+.reveal table td[align="center"] {
+	text-align: center;
+}
+
+.reveal table th[align="right"],
+.reveal table td[align="right"] {
+	text-align: right;
+}
+
+.reveal table tbody tr:last-child th,
+.reveal table tbody tr:last-child td {
+	border-bottom: none;
+}
+
+.reveal sup {
+	vertical-align: super;
+	font-size: smaller;
+}
+
+.reveal sub {
+	vertical-align: sub;
+	font-size: smaller;
+}
+
+.reveal small {
+	display: inline-block;
+	font-size: 0.6em;
+	line-height: 1.2em;
+	vertical-align: top;
+}
+
+.reveal small * {
+	vertical-align: top;
+}
+
+/*********************************************
+	 * LINKS
+	 *********************************************/
+
+/* default elements, used in slide temple */
+a {
+	color: var(--r-link-color);
+	text-decoration: underline dotted;
+	text-decoration-color: var(--r-link-color-decoration);
+	text-underline-offset: 0.25em;
+	transition: color 0.15s ease;
+	font-weight: bolder;
+}
+
+.reveal a:hover {
+	color: var(--r-link-color-hover);
+	text-shadow: none;
+	border: none;
+}
+
+.reveal .roll span:after {
+	color: #fff;
+	background: var(--r-link-color-dark);
+}
+
+/*********************************************
+	 * Frame helper
+	 *********************************************/
+.reveal .r-frame {
+	border: 4px solid var(--r-main-color);
+	box-shadow: 0 0 10px rgba(0, 0, 0, 0.15);
+}
+
+.reveal a .r-frame {
+	transition: all 0.15s linear;
+}
+
+.reveal a:hover .r-frame {
+	border-color: var(--r-link-color);
+	box-shadow: 0 0 20px rgba(0, 0, 0, 0.55);
+}
\ No newline at end of file
diff --git a/assets/styles/custom-classes.css b/assets/styles/custom-classes.css
new file mode 100644
index 00000000..369096ed
--- /dev/null
+++ b/assets/styles/custom-classes.css
@@ -0,0 +1,203 @@
+/*********************************************
+  * CUSTOM CLASSES
+  *********************************************/
+
+.flex-container {
+	/* We first create a flex layout context */
+	display: flex;
+
+	/* Then we define the flow direction
+	   and if we allow the items to wrap
+	 * Remember this is the same as:
+	 * flex-direction: row;
+	 * flex-wrap: wrap;
+	 */
+	flex-flow: row nowrap;
+
+	/* Then we define how is distributed the remaining space */
+	justify-content: space-around;
+}
+
+.flex-container>* {
+	flex: 1 100%;
+}
+
+.left {
+	order: 1;
+}
+
+.left-small {
+	order: 1;
+	flex-shrink: 2;
+}
+
+.left-large {
+	order: 1;
+	flex-grow: 2;
+}
+
+.right {
+	order: 2;
+}
+
+.centered * {
+	position: relative;
+	left: 50%;
+	transform: translate(-50%, 0%);
+}
+
+.text-center>* {
+	text-align: center !important;
+}
+
+.text-right>* {
+	text-align: right !important;
+}
+
+.text-left>* {
+	text-align: left !important;
+}
+
+/* Classes for Table in 4.5*/
+
+.storage-layer-table {
+	position: fixed;
+	top: 50%;
+	transform: translate(0%, -50%);
+}
+
+.storage-layer-table td {
+	padding: 20px !important;
+	background-color: white;
+	color: black;
+}
+
+.storage-layer-table .active {
+	background-color: pink;
+	color: black;
+}
+
+.storage-layer-table .ends {
+	background-color: transparent;
+	color: white;
+}
+
+th {
+	font-weight: 400;
+}
+
+/* positioning within a container */
+.image-container {
+	position: relative;
+	text-align: center;
+}
+
+.bottom-left {
+	position: absolute;
+	bottom: 8px;
+	left: 16px;
+}
+
+.top-left {
+	position: absolute;
+	top: 8px;
+	left: 16px;
+}
+
+.top-right {
+	position: absolute;
+	top: 8px;
+	right: 16px;
+}
+
+.bottom-right {
+	position: absolute;
+	bottom: 8px;
+	right: 16px;
+}
+
+.center-right {
+	position: absolute;
+	top: 50%;
+	right: 16px;
+}
+
+.centered {
+	position: absolute;
+	top: 50%;
+	left: 50%;
+	transform: translate(-50%, -50%);
+}
+
+.black-box {
+	background-color: black;
+	color: white;
+	padding: 30px;
+}
+
+.black-box ol,
+.black-box ul {
+	margin-top: 0px !important;
+	margin-left: 24px;
+}
+
+.text-small * {
+	font-size: 24px !important;
+}
+
+.text-smaller * {
+	font-size: 18px !important;
+}
+
+.overlay-table {
+	width: 800px;
+}
+
+.overlay-table,
+.overlay-table tr,
+.overlay-table td {
+	border: 2px solid;
+	border-color: white;
+	border-collapse: separate;
+	text-align: center !important;
+}
+
+.overlay-table td {
+	width: 200px;
+}
+
+.layers-table,
+.layers-table tr,
+.layers-table td {
+	border: 2px solid;
+	border-color: white;
+	border-collapse: separate;
+	text-align: center !important;
+	background-color: lightgray;
+	color: black;
+}
+
+.layers-table td {
+	min-width: 200px;
+	height: 100px;
+}
+
+.spec-block {
+	width: 100px;
+	height: 100px;
+	color: white;
+	display: block;
+	font-size: 24px;
+	float: left;
+	margin: 10px;
+	text-align: center;
+	line-height: 100px;
+}
+
+.no-bullet-padding ul,
+.no-bullet-padding ul>li::before {
+	padding: 0 !important;
+	/* Remove padding */
+	margin: 0 !important;
+	/* Remove margins */
+}
diff --git a/assets/styles/fonts/unbounded/Unbounded-Bold.ttf b/assets/styles/fonts/unbounded/Unbounded-Bold.ttf
new file mode 100644
index 00000000..f872248c
Binary files /dev/null and b/assets/styles/fonts/unbounded/Unbounded-Bold.ttf differ
diff --git a/assets/styles/fonts/unbounded/Unbounded-Bold.woff2 b/assets/styles/fonts/unbounded/Unbounded-Bold.woff2
new file mode 100644
index 00000000..add77ee4
Binary files /dev/null and b/assets/styles/fonts/unbounded/Unbounded-Bold.woff2 differ
diff --git a/assets/styles/fonts/unbounded/Unbounded-Light.ttf b/assets/styles/fonts/unbounded/Unbounded-Light.ttf
new file mode 100644
index 00000000..10350df2
Binary files /dev/null and b/assets/styles/fonts/unbounded/Unbounded-Light.ttf differ
diff --git a/assets/styles/fonts/unbounded/Unbounded-Light.woff2 b/assets/styles/fonts/unbounded/Unbounded-Light.woff2
new file mode 100644
index 00000000..f9989034
Binary files /dev/null and b/assets/styles/fonts/unbounded/Unbounded-Light.woff2 differ
diff --git a/assets/styles/fonts/unbounded/Unbounded-Regular.ttf b/assets/styles/fonts/unbounded/Unbounded-Regular.ttf
new file mode 100644
index 00000000..14a7d8ae
Binary files /dev/null and b/assets/styles/fonts/unbounded/Unbounded-Regular.ttf differ
diff --git a/assets/styles/fonts/unbounded/Unbounded-Regular.woff2 b/assets/styles/fonts/unbounded/Unbounded-Regular.woff2
new file mode 100644
index 00000000..5db9542d
Binary files /dev/null and b/assets/styles/fonts/unbounded/Unbounded-Regular.woff2 differ
diff --git a/assets/styles/fonts/work-sans/work-sans-v17-latin-800.eot b/assets/styles/fonts/work-sans/work-sans-v17-latin-800.eot
new file mode 100644
index 00000000..98186695
Binary files /dev/null and b/assets/styles/fonts/work-sans/work-sans-v17-latin-800.eot differ
diff --git a/assets/styles/fonts/work-sans/work-sans-v17-latin-800.svg b/assets/styles/fonts/work-sans/work-sans-v17-latin-800.svg
new file mode 100644
index 00000000..d1d4b62b
--- /dev/null
+++ b/assets/styles/fonts/work-sans/work-sans-v17-latin-800.svg
@@ -0,0 +1,336 @@
+<?xml version="1.0" standalone="no"?>
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg xmlns="http://www.w3.org/2000/svg">
+<defs >
+<font id="WorkSans" horiz-adv-x="597" ><font-face
+    font-family="Work Sans ExtraBold"
+    units-per-em="1000"
+    panose-1="0 0 0 0 0 0 0 0 0 0"
+    ascent="930"
+    descent="-243"
+    alphabetic="0" />
+<glyph unicode=" " horiz-adv-x="267" />
+<glyph unicode="!" horiz-adv-x="312" d="M261 660V473L239 218H72L50 473V660H261ZM156 173Q206 173 234 149T263 83Q263 40 235 16T156 -8Q105 -8 77 16T48 83Q48 125 76 149T156 173Z" />
+<glyph unicode="&quot;" horiz-adv-x="463" d="M426 674L395 386H264V674H426ZM218 674L187 386H56V674H218Z" />
+<glyph unicode="#" horiz-adv-x="706" d="M589 660L483 0H351L456 660H589ZM635 266V150H28V266H635ZM340 660L235 0H102L207 660H340ZM678 510V394H71V510H678Z" />
+<glyph unicode="$" horiz-adv-x="647" d="M330 0Q268 0 209 13T99 49T14 106L99 237Q125 205 167 184T255 153T342 142Q387 142 412 154T437 191Q437 209 420 219T363 238L234 269Q182 281 138 303T69 360T43 446Q43 509 77 557T176 633T333 660Q423 660 494 635T619
+561L537 441Q493 478 441 499T323 521Q288 521 266 515T233 498T222 472Q222 460 229 451T257 433T319 416L418 394Q515 372 562 333T610 219Q610 146 573 97T473 24T330 0ZM273 -84V744H392V-84H273Z" />
+<glyph unicode="%" horiz-adv-x="967" d="M173 0L646 661H796L322 0H173ZM223 670Q281 670 325 647T393 580T418 480Q418 422 394 380T325 314T223 290Q164 290 120 313T52 380T27 480Q27 537 51 580T120 646T223 670ZM222 538Q207 538 196 532T179 512T173 480Q173
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diff --git a/assets/templates/listing-template.html b/assets/templates/listing-template.html
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index 00000000..906b0822
--- /dev/null
+++ b/assets/templates/listing-template.html
@@ -0,0 +1,198 @@
+<!doctype html>
+<html lang="en">
+
+<head>
+  <meta charset="utf-8" />
+  <title>{{pageTitle}}</title>
+  <link rel="stylesheet" href="{{{themeUrl}}}" id="theme" />
+  <link rel="icon" href="./assets/favicon.svg" />
+  <link rel="shortcut icon" href="./assets/favicon.png" />
+  <style>
+    /* local variables */
+    html {
+      --font-size: 16px;
+      --container: 100em;
+      --size: 1.5rem;
+    }
+
+    /* general layout elements */
+    html,
+    body,
+    .site {
+      display: flex;
+      flex-direction: column;
+      margin: 0;
+    }
+
+    html {
+      align-items: center;
+      font-size: var(--font-size);
+      color: var(--r-main-color);
+      background-color: var(--r-background-color);
+    }
+
+    ul {
+      margin: 0;
+    }
+
+    /* site layout */
+    .site {
+      max-width: var(--container);
+    }
+
+    .site-header {
+      position: sticky;
+      top: 0;
+      background-color: var(--r-selection-background-color);
+    }
+
+    .site-footer {
+      position: sticky;
+      bottom: 0;
+      background-color: var(--r-selection-background-color);
+    }
+
+    a:hover {
+      color: var(--r-link-color-dark) !important;
+    }
+
+    a span:first-of-type {
+      color: var(--r-heading-color);
+    }
+
+    h1 {
+      margin: 0;
+      text-transform: uppercase;
+      letter-spacing: var(--r-heading-letter-spacing);
+      font-family: var(--r-heading-font);
+      font-size: calc(var(--font-size) * 1.5);
+      text-shadow: var(--r-heading1-text-shadow);
+    }
+
+    .site-logo {
+      width: calc(var(--size) * 10);
+      margin-left: calc(var(--size) / 2);
+    }
+
+    .slide-list li::before {
+      color: var(--r-link-color);
+    }
+
+    .slide-list li {
+      /* Replacing the link-color-hover with the CYAN #00B2FF */
+      /* color: var(--r-link-color-hover); */
+      color: var(--r-hub-cyan);
+      display: flex;
+      align-items: center;
+    }
+
+    .slide-list li::before {
+      font-size: calc(var(--font-size) * 2);
+      content: "";
+      display: list-item;
+      line-height: 0;
+      color: var(--r-link-color-dark);
+    }
+
+    .slide-card-name {
+      font-family: var(--r-heading-font);
+      letter-spacing: var(--r-heading-letter-spacing);
+    }
+
+    .slide-card-path {
+      font-style: italic;
+      color: var(--r-link-color);
+      font-size: 0.7em;
+    }
+
+    a:hover .slide-card-path {
+      color: var(--r-hub-cyan);
+      transition: color 200ms ease-in-out;
+    }
+
+    .slide-list li a {
+      padding-top: calc(var(--size) / 3);
+      padding-bottom: calc(var(--size) / 3);
+      font-size: calc(var(--font-size) * 1.2);
+      color: var(--r-main-color);
+      text-decoration: none;
+      word-break: break-word;
+    }
+
+    .slide-list li a:hover {
+      color: var(--r-hub-cyan);
+    }
+
+    /* menu navigation bar, sticky */
+    .menu {
+      display: flex;
+      list-style: none;
+      margin: 0;
+      padding: 0;
+    }
+
+    .menu--header {
+      flex-grow: 1;
+      justify-content: space-between;
+    }
+
+    .menu--footer {
+      justify-content: center;
+      padding: calc(var(--font-size) * 0.5);
+    }
+
+    .menu-item {
+      display: flex;
+      align-items: center;
+    }
+
+    .menu--footer .menu-item {
+      font-size: var(--font-size);
+      font-family: var(--r-heading-font);
+    }
+  </style>
+
+
+<body class="site">
+  <header class="site-header site-header--small">
+    <menu class="menu menu--header">
+      <li class="menu-item">
+        <img class="site-logo" src="./assets/img/0-Shared/logo/pba-logo-white.svg" />
+      </li>
+      <li class="menu-item">
+        <h1>PBA Slides</h1>
+      </li>
+    </menu>
+  </header>
+
+  <main class="site-main">
+    <ul class="slide-list">
+      {{#files}}
+      <li {{#filePath}}data-template="{{filePath}}" {{/filePath}}>
+        <a href="{{filePath}}" title="{{title}}" class="slide-card">
+          {{#title}}
+          <span class="slide-card-name">{{.}}</span>
+          <span class="slide-card-path"><br />&nbsp;&nbsp;&nbsp;&nbsp;{{filePath}}</span>
+          {{/title}}
+          {{^title}}
+          {{filePath}}
+          {{/title}}
+        </a>
+      </li>
+      {{/files}}
+    </ul>
+  </main>
+
+  {{#watch}}
+  <footer class="site-footer">
+    <menu class="menu menu--footer">
+      <li class="menu-item">
+        <a class="menu-link" href="https://github.com/Polkadot-Blockchain-Academy/pba-content/">PBA Content on
+          GitHub</a>
+      </li>
+    </menu>
+  </footer>
+  {{/watch}}
+</body>
+
+</html>
diff --git a/assets/templates/slide-template.html b/assets/templates/slide-template.html
new file mode 100644
index 00000000..ee1f4585
--- /dev/null
+++ b/assets/templates/slide-template.html
@@ -0,0 +1,141 @@
+<!DOCTYPE html>
+<html lang="en">
+
+<head>
+  <meta charset="utf-8" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
+
+  <title>{{{title}}}</title>
+  {{#absoluteUrl}}
+  <meta property="og:title" content="{{{title}}}" />
+  <meta property="og:type" content="website" />
+  <meta property="og:image" content="{{{absoluteUrl}}}/featured-slide.jpg" />
+  <meta property="og:url" content="{{{absoluteUrl}}}" />
+  {{/absoluteUrl}}
+  <link rel="icon" href="{{{base}}}/assets/favicon.svg" />
+  <link rel="shortcut icon" href="{{{base}}}/assets/favicon.png" />
+  <link rel="stylesheet" href="{{{base}}}/dist/reset.css" />
+  <link rel="stylesheet" href="{{{base}}}/dist/reveal.css" />
+  <link rel="stylesheet" href="{{{themeUrl}}}" id="theme" />
+  <link rel="stylesheet" href="{{{base}}}{{{highlightThemeUrl}}}" />
+
+  {{#cssPaths}}
+  <link rel="stylesheet" href="{{{.}}}" />
+  {{/cssPaths}}
+
+  {{#watch}}
+  <script>
+    document.write(
+      '<script src="http://' +
+      (location.host || 'localhost').split(':')[0] +
+      ':35729/livereload.js?snipver=1"></' +
+      'script>'
+    );
+  </script>
+  {{/watch}}
+</head>
+
+<body class="site">
+  <header class="site-header">
+    <!-- This logo is a link only on the watching server, not the production build -->
+    <a href="{{{absoluteUrl}}}">
+      <img style="height: 2.5vw;" class="watermark-logo" src="{{{base}}}/assets/img/0-Shared/logo/pba-logo-white.svg"
+        alt="PBA Logo">
+    </a>
+  </header>
+  <main class="reveal">
+    <article class="slides">
+      {{{slides}}}
+    </article>
+  </main>
+
+  <script src="{{{base}}}/dist/reveal.js"></script>
+
+  <script src="{{{base}}}/plugin/markdown/markdown.js"></script>
+  <script src="{{{base}}}/plugin/highlight/highlight.js"></script>
+  <script src="{{{base}}}/plugin/zoom/zoom.js"></script>
+  <script src="{{{base}}}/plugin/notes/notes.js"></script>
+  <script src="{{{base}}}/plugin/math/math.js"></script>
+
+  <script src="{{{base}}}/assets/plugin/mermaid.js"></script>
+  <script src="{{{base}}}/assets/plugin/mermaid-theme.js"></script>
+
+  <script src="{{{base}}}/assets/plugin/chart/chart.js"></script>
+  <script src="{{{base}}}/assets/plugin/chart/chart.min.js"></script>
+
+  <script src="{{{base}}}/assets/plugin/tailwindcss.min.js"></script>
+
+  <script>
+    function extend() {
+      var target = {};
+      for (var i = 0; i < arguments.length; i++) {
+        var source = arguments[i];
+        for (var key in source) {
+          if (source.hasOwnProperty(key)) {
+            target[key] = source[key];
+          }
+        }
+      }
+      return target;
+    }
+
+    // default options to init reveal.js
+    var defaultOptions = {
+      controls: true,
+      progress: true,
+      history: true,
+      center: true,
+      transition: 'default', // none/fade/slide/convex/concave/zoom
+      slideNumber: true,
+      mermaid: {
+        startOnLoad: false,
+        logLevel: 3,
+        theme: 'base',
+        themeVariables: {
+          primaryColor: purple,
+          primaryTextColor: white,
+          primaryBorderColor: pink,
+          lineColor: pink,
+          secondaryColor: lightPurple,
+          tertiaryColor: lightPurple,
+        },
+      },
+      chart: {
+        defaults: {
+          color: 'lightgray', // color of labels
+          scale: {
+            beginAtZero: true,
+            ticks: { stepSize: 1 },
+            grid: { color: "lightgray" }, // color of grid lines
+          },
+        },
+        line: { borderColor: ["#ccc", "#E6007A", "#6D3AEE"], "borderDash": [[5, 10], [0, 0]] },
+        bar: { backgroundColor: ["#ccc", "#E6007A", "#6D3AEE"] },
+      },
+      plugins: [
+        RevealMarkdown,
+        RevealHighlight,
+        RevealZoom,
+        RevealNotes,
+        RevealMath,
+        RevealMermaid,
+        RevealChart
+      ]
+    };
+
+    // options from URL query string
+    var queryOptions = Reveal().getQueryHash() || {};
+
+    var options = extend(defaultOptions, {{{ revealOptionsStr }}}, queryOptions);
+  </script>
+
+  {{#scriptPaths}}
+  <script src="{{{.}}}"></script>
+  {{/scriptPaths}}
+
+  <script>
+    Reveal.initialize(options);
+  </script>
+</body>
+
+</html>
diff --git a/bun.lockb b/bun.lockb
index 7d13a3e6..68506726 100755
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diff --git a/content/1-Cryptography/1-Intro-slides.md b/content/1-Cryptography/1-Intro-slides.md
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+++ b/content/1-Cryptography/1-Intro-slides.md
@@ -0,0 +1,476 @@
+---
+title: Introduction to Cryptography
+description: Cryptographic primitives for Web3 engineers
+duration: 1 hour
+---
+
+# Cryptography Day I
+
+<pba-flex center>
+
+- Introduction to cryptography<!-- .element: class="fragment" data-fragment-index="0" -->
+- Addresses and Keys<!-- .element: class="fragment" data-fragment-index="1" -->
+- Many time pad activity<!-- .element: class="fragment" data-fragment-index="2" -->
+
+</pba-flex>
+
+---
+
+# Introduction to Cryptography
+
+---
+
+## Some Useful Equations
+
+<img rounded style="height: 600px" src="./img/scary-equations.png" />
+
+Notes:
+
+Just kidding!
+
+---
+
+## Goals for this lesson
+
+<pba-flex center>
+
+- Understand the goals of cryptography<!-- .element: class="fragment" data-fragment-index="0" -->
+- Understand security guarantees for resources<!-- .element: class="fragment" data-fragment-index="1" -->
+- Learn the primitives<!-- .element: class="fragment" data-fragment-index="2" -->
+
+</pba-flex>
+
+Notes:
+
+In this first lesson,
+
+---
+
+## Cryptography Landscape
+
+<img style="height: 700px; padding-left:100px" src="./img/crypto-mind-map.svg" />
+
+Notes:
+
+What is covered in this course is all connected subjects.
+We will not cover any details for hybrid or interactive protocols in the course.
+
+---
+
+## Operating Context
+
+##### _Protocols use resources and cryptography ensures that they provide security guarantees_
+
+- **Network, storage, computation, etc.**: We want to specify guarantees on what the resources provide.
+
+<pba-flex center>
+
+- Stored/transmitted data is untampered,<!-- .element: class="fragment" data-fragment-index="1" -->
+- Transmitted data comes from a specific sender,<!-- .element: class="fragment" data-fragment-index="2" -->
+- A computation over data has been performed correctly,<!-- .element: class="fragment" data-fragment-index="3" -->
+- Sensitive data does not get leaked,<!-- .element: class="fragment" data-fragment-index="4" -->
+- and many more...<!-- .element: class="fragment" data-fragment-index="5" -->
+
+</pba-flex>
+
+---
+
+## Operating Context: Example
+
+##### _The internet is a public space_
+
+We communicate over public channels.
+Adversaries may want to:
+
+<pba-flex center>
+
+- Read messages not intended for them<!-- .element: class="fragment" data-fragment-index="0" -->
+- Impersonate others<!-- .element: class="fragment" data-fragment-index="1" -->
+- Tamper with messages<!-- .element: class="fragment" data-fragment-index="2" -->
+
+</pba-flex>
+
+Notes:
+
+Use e-mail as an example of an flawed system.
+
+Some examples include:
+
+- An attacker may impersonate your boss, trying to get you to send them money<!-- .element: class="fragment" data-fragment-index="0" -->
+- An attacker may change a message sent over a network, e.g. an instruction to transfer 100 EUR to 10000 EUR<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Probably best for the teacher to ask students to participate with examples of application messages,
+not just person-to-person messages.
+
+---
+
+## Public vs. Private Systems
+
+_Cryptography based on public systems is more sound_
+
+**Kerckhoff's Principle:** Security should not rely on secret _methods_,<br/>but rather on secret _information_
+
+Notes:
+
+There is no such thing as a "closed channel" :)
+
+- Methods can be reverse engineered.
+  After that, the communication channel is completely insecure.
+  For example, CSS protection for DVDs.
+- We always work with public, open protocols.
+
+---
+
+## Security Guarantees\*
+
+<pba-flex center>
+
+- Data confidentiality<!-- .element: class="fragment" data-fragm ent-index="0" -->
+- Data authenticity<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Data integrity<!-- .element: class="fragment" data-fragm ent-index="2" -->
+- Non-repudiation<!-- .element: class="fragment" data-fragm ent-index="3" -->
+- Data availability<!-- .element: class="fragment" data-fragm ent-index="4" -->
+- Data verifiability<!-- .element: class="fragment" data-fragm ent-index="5" -->
+- ...<!-- .element: class="fragment" data-fragm ent-index="6" -->
+  </pba-flex>
+
+Notes:
+
+Cryptography is one of the (most important) tools we have to build tools that are _guaranteed_ to work correctly.
+This is regardless of who (human, machine, or otherwise) is using them and their intentions (good or bad).
+
+Why an asterisk?
+There generally are no perfect & absolute guarantees here, but for most practical purposes the bounds on where these fail are good enough to serve our needs as engineers and users.
+Do note the assumptions and monitor their validity over time (like quantum tech).
+
+---
+
+## Data Confidentiality
+
+A party may gain access to information<br/>if and only if they know some secret (a key).
+
+<br/>
+
+Confidentiality ensures that a third party cannot read my confidential data.
+
+Notes:
+
+The ability to decrypt some data and reveal its underlying information directly implies knowledge of some secret, potentially unknown to the originator of the information.
+Supplying the original information (aka plain text message) can be used in a "challenge game" mechanism as one means of proving knowledge of the secret without compromising it.
+
+Mention use of the term "plaintext".
+
+Allegory: A private document stored on server where sysadmin has _access_ can be subpoenaed, violating assumed Attorney-Client Privilege on the document.
+
+---v
+
+<!-- This slide should potentially be pushed into the lecture on encryption. I can see it in either spot. Alternately, could be cut entirely, as encrypted communication is not an emphasized topic. -->
+
+## Confidentiality in Communication Channels
+
+Suppose Alice and Bob are sending confidential messages back and forth. There are some subtypes of confidentiality here:
+
+- **Forward Secrecy**: Even if an adversary temporarily learns Alice's secret, it cannot read future messages after some point.
+- **Backwards Secrecy**: Even if an adversary temporarily learns Alice's secret, it cannot read past messages beyond some previous point.
+
+---
+
+## Data Authenticity
+
+Users can have the **credible** expectation that the stated origin of a message is authentic.
+
+<br/>
+
+Authenticity ensures that a third party cannot pretend I created some data.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+
+Notes:
+
+- Digital signatures should be difficult (practically speaking: impossible) to forge.
+- Digital signatures should verify that the signer knows some secret, without revealing the secret itself.
+
+---
+
+## Data Integrity
+
+If data is tampered with, it is detectable. In other words, it possible to check if the current state of some data is the consistent with when it was created.
+
+<br/>
+
+Integrity ensures that if data I create is corrupted, it can be detected.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+---v
+
+## Physical Signatures
+
+Physical signatures provide weak authenticity guarantees<br/>(i.e. they are quite easy to forge), and no integrity guarantees.
+
+---v
+
+## An Ideal Signature
+
+<img style="width: 900px;" src="./img/Data-Integrity.png" />
+
+Notes:
+
+For example, if you change the year on your university diploma, the dean's signature is still valid.
+Digital signatures provide a guarantee that the signed information has not been tampered with.
+
+---
+
+## Non-repudiation
+
+The sender of a message cannot deny that they sent it.
+
+<br/>
+
+Non-repudiation ensures if Bob sends me some data, I can prove to a third party that they sent it.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+
+---
+
+## Data availability
+
+Not always considered a cryptographic guarantee, but in many contexts we would like that data is available to people when they want to access it.
+
+Notes:
+
+Cryptography alone cannot make strong guarantees that data is available to people when they want to access it.
+
+There are many schemes to get around this, and this topic will come up later in the course.
+We will touch on erasure coding, which makes data availability more efficient.
+
+---
+
+## Data Verifiability
+
+In some contexts we want to show that (possibly sensitive) data satisfies certain properties.
+
+Notes:
+
+Proving without showing --> we will see that zero-knowledge proofs will allow us to show that a data satisfies certain properties. For example, that I know the key that corresponds to the ciphertext data that I have sent you. Or that the data I have sent you is indeed the correct result of a computation.
+
+---
+
+## One-Way Functions
+
+One-way functions form the basis of cryptographic primitives. A function $f$ is one way if:
+
+- it is reasonably fast to compute<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- it is very, very slow to undo<!-- .element: class="fragment" data-fragm ent-index="2" -->
+
+Notes:
+
+There are a lot of assumptions about why these functions are hard to invert, but we cannot rigorously prove it.
+We often express inversion problems in terms of mathematical games or oracles.
+
+---
+
+## Hash Functions
+
+**Motivation:** We often want a succinct, yet unique representation of some (potentially large) data.
+
+</br>
+
+A fingerprint, which is much smaller than a person, yet uniquely identifies an individual.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+
+Notes:
+
+The following slides serve as an intro.
+Many terms may be glossed over, and covered in detail later.
+There are lessons later in this module dedicated to hashes and hash-based data structures.
+
+---v
+
+## Hash Function Applications
+
+Hashes can be useful for many applications:
+
+<pba-flex center>
+
+- Representation of larger data object<br/>(history, commitment, file)<!-- .element: class="fragment" data-fragm ent-index="0" -->
+- Keys in a database<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Digital signatures<!-- .element: class="fragment" data-fragm ent-index="2" -->
+- Key derivation<!-- .element: class="fragment" data-fragm ent-index="3" -->
+- Pseudorandom functions<!-- .element: class="fragment" data-fragm ent-index="4" -->
+
+</pba-flex>
+
+---
+
+## Symmetric Cryptography
+
+<pba-flex center>
+
+- Symmetric cryptography assumes all parties begin with some shared secret information.
+- This is a potentially very difficult requirement.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- The shared secret can then be used to protect further communications from others who do not know this secret.<!-- .element: class="fragment" data-fragm ent-index="2" -->
+- In essence, it gives a way of "extending" a shared secret over time.<!-- .element: class="fragment" data-fragm ent-index="3" -->
+
+</pba-flex>
+
+Notes:
+
+Remember that these communications are over an _open channel_, as we assumed that all channels can be monitored.
+
+---
+
+## Symmetric Encryption
+
+For example, the Enigma cipher in WW2. A _channel_ was initiated by sharing a secret ("key") between two participants. Using the cipher, those participants could then exchange information securely.
+
+However, since the key contained only limited "entropy" ("information"), enough usage of it eventually compromised the secret and allowed the allies to decode messages. Even altering it once per day was not enough.<!-- .element: class="fragment" data-fragm ent-index="0" -->
+
+Notes:
+
+When communicating over a channel that is protected with only a certain amount of entropy, it is still possible to extend messages basically indefinitely by introducing _new entropy_ that is used to protect the channel sufficiently often.
+
+---
+
+## Asymmetric Cryptography
+
+- In asymmetric cryptography, we devise a means to transform one value (the "secret") into some corresponding counterpart (the "public" key), preserving certain properties.
+- We believe that this is a one-way function (that there is no easy/fast inverse of this function).<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Aside from preserving certain properties, we believe this counterpart (the "public key") reveals no information about the secret.<!-- .element: class="fragment" data-fragm ent-index="2" -->
+
+---
+
+## Asymmetric Encryption
+
+_Using only the public key_, information can be transformed ("encrypted") such that only those with knowledge of the secret are able to inverse and regain the original information.
+
+---
+
+## Digital Signatures
+
+- _Using the secret key_, information can be transformed ("signed") such that anyone with knowledge of the information and the counterpart public key is able to affirm the operation.
+- Digital signatures provide message authenticity and integrity guarantees.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- There are two lessons dedicated to digital signatures,<br/>this is strictly an intro.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+
+---
+
+## Digital Signatures
+
+**Signing function**: a function which operates on some<br/> _message data_ and some _secret_ to yield a _signature_.
+
+A **signature** _proves_ that the signer had knowledge of the secret,<br/>without revealing the secret itself.
+
+The signature cannot be used to create other signatures, and is unique to the message.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+
+Notes:
+
+A **signing function** is a pure function which operates on some _message data_ (which may or may not be small, depending on the function) and some _secret_ (a small piece of information known only to the operator).
+The result of this function is a small piece of data called a _signature_.
+
+Pure means that it has no side effects.
+
+It has a special property: it proves (beyond reasonable doubt) that the signer (i.e. operator of the signing function) had knowledge of the secret and utilized this knowledge with the specific _message_ data, yet it does not reveal the secret itself, nor can knowledge of the signature be used to create other signatures (e.g. for alternative message data).
+
+---
+
+## Non-repudiation for Cryptographic Signatures
+
+There is cryptographic proof that the secret was known to the producer of the signature.
+
+<br/>
+
+The signer cannot claim that the signature was forged, unless they can defend a claim that the secret was compromised prior to signing.<br/><!-- .element: class="fragment" data-fragm ent-index="1" -->
+
+---
+
+## Practical Considerations
+
+**Symmetric cryptography** is much faster, but requires more setup (key establishment) and trust (someone else knows the secret).
+
+**Asymmetric cryptography** is slow, but typically preserves specific algebraic relationships, which then permit more diverse if fragile protocols.
+
+---
+
+## Hybrid Cryptography
+
+Hybrid cryptography composes new mechanisms from different cryptographic primitives.
+
+For example:
+
+- Symmetric encryption can provide speed, and often confidentiality,<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Hash functions can reduce the size of data while preserving identity,<!-- .element: class="fragment" data-fragm ent-index="2" -->
+- Asymmetric cryptography can dictate relations among the participants.<!-- .element: class="fragment" data-fragm ent-index="3" -->
+
+---
+
+## Certifications
+
+Certifications are used to make attestations about public key relationships.
+
+Typically in the form of a _signature_ on:
+
+- One or more cryptographically strong identifiers (e.g. public keys, hashes).
+- Information about its ownership, its use and any other properties that the signer is capable of attesting/authorizing/witnessing.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- "(Meta-)information" about this information itself, such as how long it is valid for and external considerations which would invalidate it.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+
+Notes:
+
+- Real application is the hierarchy of SSL certs.
+  - Root keys -> State level entities -> Smaller entities.
+- Web of Trust & GPG cross-signing
+- In the case of signature-based certificates, as long as you have the signature, data, and originating public key, you can trust a certificate no matter where it came from. It could be posted on a public message board, sent to you privately, or etched into stone.
+
+---
+
+## Entropy, Randomness, and Key Size
+
+- Entropy: Amount of non-redundant information contained within some data.
+- Randomness: Unpredictability of some information. Less random implies lower entropy.<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Key size: Upper limit of possible entropy contained in a key. Keys with less random (more predictable) data have less entropy than this upper bound.<!-- .element: class="fragment" data-fragm ent-index="2" -->
+- One-time pad: A key of effectively infinite size. If it is perfectly random (i.e. has maximal entropy), then the cipher is theoretically unbreakable.<!-- .element: class="fragment" data-fragm ent-index="3" -->
+
+Notes:
+
+Mention the upcoming "many time pad" activity, that exploits using a one time pad multiple times.
+
+---
+
+## Randomness Generation
+
+```rust
+fn roll_die() -> u32 {
+  // Guaranteed random: it was achieved through a real-life die-roll.
+  4u32
+}
+```
+
+- Pseudo-random sequences<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Physical data collection (e.g. cursor movement, LSB of microphone)<!-- .element: class="fragment" data-fragm ent-index="2" -->
+- Specialised hardware (e.g. low-level noise on silicon gates, quantum-amplifiers)<!-- .element: class="fragment" data-fragm ent-index="3" -->
+
+Notes:
+
+LSB := Least Significant Bit
+
+---
+
+## Summary
+
+Cryptography is much more than encryption.
+
+<pba-flex center>
+
+- Communicate on public networks, in the open<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Access information<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Have expectations about a message's authenticity and integrity<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Prove knowledge of some secret information<!-- .element: class="fragment" data-fragm ent-index="1" -->
+- Represent large amounts of data succinctly<!-- .element: class="fragment" data-fragm ent-index="1" -->
+
+</pba-flex>
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
+
+<img style="height: 600px" src="./img/crypto-mind-map.svg" />
+
+##### _What insights did you gain?_
+
+Notes:
+
+Class discussion.
+Last slide.
diff --git a/content/1-Cryptography/10-Advanced_ZK_proofs-slides.md b/content/1-Cryptography/10-Advanced_ZK_proofs-slides.md
new file mode 100644
index 00000000..cfa6c32b
--- /dev/null
+++ b/content/1-Cryptography/10-Advanced_ZK_proofs-slides.md
@@ -0,0 +1,302 @@
+---
+title: Advanced ZK Proofs
+description: Introduction to zero-knowledge proofs and zk-SNARKS
+duration: 2 hour
+---
+
+# Cryptography Day IV
+
+<pba-flex center>
+
+- Quiz
+- Advanced ZK Proofs<!-- .element: class="fragment" data-fragment-index="0" -->
+- ZKP Activity<!-- .element: class="fragment" data-fragment-index="1" -->
+- Cryptography in Context<!-- .element: class="fragment" data-fragment-index="2" -->
+
+</pba-flex>
+
+---
+
+# Advanced ZK Proofs
+
+---
+
+# Outline
+
+<pba-flex center>
+
+1. [Under the hood of zk-SNARKs](#zk-practice) <!-- .element: class="fragment" data-fragment-index="1" -->
+1. [Introduction to Plonk](#plonk) <!-- .element: class="fragment" data-fragment-index="2" -->
+1. [Polynomial commitment](#polynomial-commitment) <!-- .element: class="fragment" data-fragment-index="3" -->
+1. [Generating ZK-proofs using Circom and snarkjs](#circom-snarkjs) <!-- .element: class="fragment" data-fragment-index="4" -->
+
+</pba-flex>
+
+---
+
+## Circuit to SNARK Strategy
+
+- To represent the circuit as a univariate polynomial called the "All Gate Polynomial".<!-- .element: class="fragment" data-fragment-index="1" -->
+- The all-gate polynomial is equal to zero at each "gate" of the circuit if the solution satisfies the gate relation.<!-- .element: class="fragment" data-fragment-index="2" -->
+- Then the verifier should be able to test if the polynomial actually has a root for every gate.<!-- .element: class="fragment" data-fragment-index="3" -->
+- ... without knowing the polynomial: This is done using "polynomial commitment".<!-- .element: class="fragment" data-fragment-index="4" -->
+
+---
+
+## Universal PLONK Gate
+
+<img style="height: 200px; padding-left:100px" src="./img/factorization-circuit.png" />
+
+- Supppose we have a left input $a$ and a right input $b$ and we are doing some addition and multiplication with them and the output is $c$.<!-- .element: class="fragment" data-fragment-index="1" -->
+- Then we could encode all of these operations as:<!-- .element: class="fragment" data-fragment-index="2" -->
+  $Q_l\times a + Q_r \times b + Q_o \times c + Q_m \times a\times b + Q_c = 0$<!-- .element: class="fragment" data-fragment-index="3" -->
+- for some constant $Q_l$ $Q_r$ $Q_o$ $Q_m$ and $Q_c$<!-- .element: class="fragment" data-fragment-index="4" -->
+- In fact all the operation we discussed can be written using one of these gates.<!-- .element: class="fragment" data-fragment-index="5" -->
+
+---
+
+## Gate table for factorization
+
+$r \times s = N$
+
+$Q_l\times a + Q_r\times b + Q_o\times c + Q_m\times a\times b + Q_c = 0$
+
+<img style="height: 200px; padding-left:100px" src="./img/gate-table-factorization.png" />
+
+---
+
+## Gate table for left input to be small and not 1
+
+$r_{01} = r_{0} + 2r_{1}$
+
+$r = r_{01} + 4r_{2}$
+
+$r_{i} \times (r_{i} - 1) = 0 \Rightarrow r_{i}^2 - r_{i} = 0$
+
+$(r-1)\times\frac{1}{r - 1} = 1 \Rightarrow r\frac{1}{r - 1} - \frac{1}{r - 1} = 1$
+
+$Q_l\times a + Q_r\times b + Q_o\times c + Q_m\times a\times b + Q_c = 0$
+
+<img style="height: 500px; padding-left:100px" src="./img/gate-table-left-input-less-than-8-and-not-1.png" />
+
+---
+
+## Gate table for the right input to be an integer and not 1
+
+$Q_l\times a + Q_r\times b + Q_o\times c + Q_m\times a\times b + Q_c = 0$
+<img style="height: 500px; padding-left:100px" src="./img/gate-table-right-input-less-than-8-and-not-1.png" />
+
+---
+
+## Encode all gate values as a polynomial G
+
+- You can always encode a column of a table into a polynomial.<!-- .element: class="fragment" data-fragment-index="1" -->
+- $Q_l(x)$ such that $Q_l(1) = 0, Q_l(2) = 1, Q_l(3) = 1, Q_l(4) = -1 ,...$<!-- .element: class="fragment" data-fragment-index="2" -->
+  <img style="height: 300px; padding-left:100px" src="./img/gate-table-left-input-less-than-8-and-not-1.png" /><!-- .element: class="fragment" data-fragment-index="2" -->
+- When you have one polynomial for each column then you can turn the whole table into a polynomial:<!-- .element: class="fragment" data-fragment-index="3" -->
+  $Q_l(x)\times a(x) + Q_r(x)\times b(x) + Q_o(x)\times c(x) + Q_m(x)\times a(x)\times b(x) + Q_c(x)$<!-- .element: class="fragment" data-fragment-index="4" -->
+  $= 0$<!-- .element: class="fragment" data-fragment-index="4" -->
+
+---
+
+## Compute the all-gate polynomial from the gate table
+
+SAGE demo
+
+---
+
+## Prove the Validity of G
+
+- G encode every gate is evaluated correctly: Zero test.
+
+---
+
+# Zero test
+
+- if f(x) = 0 for x = 1,..,13 then
+- $f(x) = q(x) \times (x-1)\times ...\times (x-13)$
+- $f(x)/q(x) = (x-1)...(x-13)$
+- How to verifier this.
+
+---
+
+# Zero test on the resulting polynomial.
+
+SAGE demo
+
+---
+
+# Proving the correctness of the wiring
+
+- So far we have proven that the we have a solution which satisfies each round of PLONK gate.<!-- .element: class="fragment" data-fragment-index="1" -->
+- However we have not proven that we are using the outputs from previous rounds in correct places in each round.<!-- .element: class="fragment" data-fragment-index="2" -->
+- So the prover could cheat and use the values.<!-- .element: class="fragment" data-fragment-index="3" -->
+- The verifier need enforce equality of reused values in different rounds.<!-- .element: class="fragment" data-fragment-index="4" -->
+- This is actually the hard creative bit in PLONK and that is what P stands for in PLONK.<!-- .element: class="fragment" data-fragment-index="5" -->
+
+---
+
+# The Wiring in a Glance
+
+## <img style="height: 700px; padding-left:100px" src="./img/wiring-fans-with-constraints.png" />
+
+# The Trace polynomial
+
+<img style="height: 700px; padding-left:100px" src="./img/trace-polynomial-known-points.png" />
+
+---
+
+# The Trace poly with Wiring
+
+<img style="height: 700px; padding-left:100px" src="./img/trace-polynomial-known-points-with-wiring.png" />
+
+---
+
+# The wiring permutation: $T(i)=T(\psi(i))$
+
+<img style="height: 700px; padding-left:100px" src="./img/psi-with-wirings.png" />
+
+---
+
+# Naive Permutation check wtih zero test
+
+- We could find polynomial $\psi$. <!-- .element: class="fragment" data-fragment-index="1" -->
+- Then compute $T(\psi(x))$. <!-- .element: class="fragment" data-fragment-index="2" -->
+- Then compute $T(\psi(x)) - T(x)$. <!-- .element: class="fragment" data-fragment-index="3" -->
+- Run Zero-test to erify that $T(\psi(x)) - T(x)/((x - 1)...(x - 39))$ is a polynomial. <!-- .element: class="fragment" data-fragment-index="4" -->
+- We will end up with a degree $38\times38 = 1444$ polynomial. <!-- .element: class="fragment" data-fragment-index="5" -->
+- It is impractical. <!-- .element: class="fragment" data-fragment-index="6" -->
+
+---
+
+# SAGE demo: Computing the trace and the wiring
+
+SAGE demo
+
+---
+
+# Developing a wiring enforcement gadget/polynomial
+
+- We take a step back and develop some tools to tackle this. <!-- .element: class="fragment" data-fragment-index="1" -->
+- They sound random and irrelevant at first but it all makes sense at the end. <!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+# Product check
+
+- We have a polynomial $f(x)$ and we want to prove that:<!-- .element: class="fragment" data-fragment-index="1" -->
+- $\prod_{i \in \{1..39\}}f(i) = 1$.<!-- .element: class="fragment" data-fragment-index="2" -->
+- We could perform a a zero test $\prod_{i \in \{1..39\}}f(i)$ but the degree is huge. <!-- .element: class="fragment" data-fragment-index="3" -->
+- Instead we introduce a new polynomial: <!-- .element: class="fragment" data-fragment-index="4" -->
+- $t(x) = \prod_{i \in \{1..x+1}}f(i)$ <!-- .element: class="fragment" data-fragment-index="5" -->.
+- We have a nice recursion: $t(x + 1) = t(x)f(x+1)$ for $x \in \{1..39}$ <!-- .element: class="fragment" data-fragment-index="6" -->
+
+---
+
+# Product check
+
+- The observeration is that if you have the recursion: <!-- .element: class="fragment" data-fragment-index="1" -->
+- $t(x + 1) = t(x)f(x+1)$ for $x \in \{1..39}$ <!-- .element: class="fragment" data-fragment-index="2" -->
+- And you know $ t(39) = 1 $ then you know that: <!-- .element: class="fragment" data-fragment-index="3" -->
+- $\prod\_{i \in \{1..39}}f(i) = 1$ . <!-- .element: class="fragment" data-fragment-index="4" -->
+- We intepolate $t$ and it will have degree 38 (vs $38 \times 38$) <!-- .element: class="fragment" data-fragment-index="5" -->
+- We run a zero test on $t(x + 1) - t(x)f(x+1) = 0$ for $\{1,...,39\}$. <!-- .element: class="fragment" data-fragment-index="6" -->
+
+---
+
+# Ratio check
+
+- We can run the product check to prove $\prod_{i \in \{1..39\}}f(i)/g(i) = 1$.<!-- .element: class="fragment" data-fragment-index="1" -->
+- $t(x + 1) = t(x)f(x+1)/g(x + 1)$ <!-- .element: class="fragment" data-fragment-index="2" -->
+- We can only run a zero test polynomials. <!-- .element: class="fragment" data-fragment-index="3" -->
+- Run zero test on $t(x + 1)g(x + 1) - t(x)f(x+1)$. <!-- .element: class="fragment" data-fragment-index="4" -->
+
+---
+
+# Permutation check
+
+- Now we want to use the ratio check to enforce our wiring. <!-- .element: class="fragment" data-fragment-index="1" -->
+- We have $T(a) = T(\psi(a))$ then <!-- .element: class="fragment" data-fragment-index="2" -->
+- $\{ (a, T(a))| \textrm{ for all } a \in \{1,..,39\}\} == {(\psi(a), T(a))| \textrm{ for all } a \in \{1,...,39\}\}$ <!-- .element: class="fragment" data-fragment-index="3" -->
+- Then for any random $u_1, u_2$ <!-- .element: class="fragment" data-fragment-index="4" -->
+- $\prod_{a\in\{1,..,39\}}\frac{u_1 - u_2 \times a - T(a)}{u_1 - u_2 \times \psi(a) - T(\psi(a))} = 1$. <!-- .element: class="fragment" data-fragment-index="5" -->
+
+---
+
+# Proof of wiring being correct
+
+- The verifier runs a zero test on $T(x) - N$.
+- The verifier runs a zero test on $T(3x) - a(x)$, $T(3x+1) - b(x)$, $T(3x+2) - c(x)$
+- A Permutation check on $T(x)$ and $T(\psi(x))$
+
+---
+
+# SAGE demo: Proof of correctness of the wiring on the trace polynomial.
+
+SAGE Demo
+
+Zero test on:
+$t(x + 1)(u_1 - u_2 \times (x+1) - T(x + 1)) - t(x)(u_1 - u_2 \times (\psi(x)+1) - T(\psi(x)+1) = 0$
+
+---
+
+# Zero test without knowing the polynomial: Polynomial commitment
+
+- When the prover tells the $f(x)$ at some point $u$ ($f(u)$) without revealing $f(x)$.<!-- .element: class="fragment" data-fragment-index="1" -->
+- It is a tool to convince the verifier which it has done so honestly.<!-- .element: class="fragment" data-fragment-index="2" -->
+- The prover first commit to the polynomial $f(x)$ so later on, they can't back off and cheat (and use another polynomial).<!-- .element: class="fragment" data-fragment-index="3" -->
+- Then the verifier is going to ask the prover to evaluate the polynomials in random point $u$.<!-- .element: class="fragment" data-fragment-index="4" -->
+- The verifier is able to be confident that $f(u) = v$.<!-- .element: class="fragment" data-fragment-index="5" -->
+
+---
+
+# Zero test using polynomial commitment
+
+- The prover claims it has $f(x)$ passing the zero test.<!-- .element: class="fragment" data-fragment-index="1" -->
+- The prover is also able to compute $q(x)$ such that <!-- .element: class="fragment" data-fragment-index="2" -->
+- $f(x) = q(x) \times \prod(x-1)..(x-13)$<!-- .element: class="fragment" data-fragment-index="3" -->
+- The prover commit to $f$ and $q$.<!-- .element: class="fragment" data-fragment-index="4" -->
+- The verifier ask the prover to provide them with $f(u)$ and $q(u)$ for some random point $u$<!-- .element: class="fragment" data-fragment-index="5" -->
+- It is very unlikely that the prover is able to lie about $f(u)$ and $q(u)$ given he has commited to $f$ and $q$. <!-- .element: class="fragment" data-fragment-index="6" -->
+- The verifier computes $\prod(u-1)...(u-13)$<!-- .element: class="fragment" data-fragment-index="7" -->
+- The verifier verifies that $f(u) = q(u)\times \prod(u-1)...(u-13)$ and if so believes that the prover has a solution.<!-- .element: class="fragment" data-fragment-index="8" -->
+
+---
+
+# KZG Polynomial-commitment
+
+- Is one of the most space efficient polynomial commitment.<!-- .element: class="fragment" data-fragment-index="1" -->
+- Uses elliptic curve cryptography.<!-- .element: class="fragment" data-fragment-index="2" -->
+- It requires trusted setup: a pre-computation with toxic waste which needs to be discarded to keep the scheme secure.<!-- .element: class="fragment" data-fragment-index="3" -->
+
+---
+
+## Making ZK non-interactive
+
+- The only interactive step is when verifier is quizzing prover with a random value $r$.<!-- .element: class="fragment" data-fragment-index="1" -->
+- We replace that with asking the prover to apply a secure hash function to his commitment to generate $r$.<!-- .element: class="fragment" data-fragment-index="2" -->
+- That way if the prover changes his commitment his point also changes without his control. <!-- .element: class="fragment" data-fragment-index="3" -->
+
+---
+
+## Use Circom to generate trace polynomials.
+
+Circom demo
+
+---
+
+## Use snarkjs to generate proofs
+
+Generate proof demo with snarkjs
+
+---
+
+## Use snarkjs to verify the proofs
+
+Verify the proof snarkjs
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/1-Cryptography/11-Cryptography_In_Context-slides.md b/content/1-Cryptography/11-Cryptography_In_Context-slides.md
new file mode 100644
index 00000000..c4ac2fe8
--- /dev/null
+++ b/content/1-Cryptography/11-Cryptography_In_Context-slides.md
@@ -0,0 +1,498 @@
+---
+title: Cryptography In Context
+description: Real-world considerations around cryptography
+duration: 1 hour
+---
+
+# Cryptography in Context
+
+---
+
+# Outline
+
+<pba-flex center>
+
+1. Keeping Secrets Secret <!-- .element: class="fragment" data-fragment-index="1" -->
+1. Security and Usability <!-- .element: class="fragment" data-fragment-index="2" -->
+
+</pba-flex>
+
+---
+
+## Secrets
+
+- What is a secret in cryptography?
+- Data that you know, that nobody else knows.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+## How Secrets Stay Secret
+
+In order for a cryptographic secret to stay secret, the _only_ thing about it that can be revealed is the output of known, secured cryptographic operations.
+
+- A (sufficiently random) secret can be hashed, and the hash revealed.<!-- .element: class="fragment" data-fragment-index="0" -->
+- A private key can be used to generate a public key, and the public key revealed.<!-- .element: class="fragment" data-fragment-index="1" -->
+- A private key can be used to generate a signature, and the signature revealed.<!-- .element: class="fragment" data-fragment-index="3" -->
+
+---
+
+## How Secrets Get Leaked
+
+1. Inadvertently leaking information about the secret during normal operation.<!-- .element: class="fragment" data-fragment-index="0" -->
+1. Compromised digital or physical security leading to private key loss.<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+Let's go over each of these in order.
+
+---
+
+## Bad Randomness
+
+Some algorithms require randomness. If the randomness is compromised, the private key or encrypted message can possibly be exposed.
+
+Notes:
+
+[one source](https://learn.saylor.org/mod/book/view.php?id=36341&chapterid=18921)
+
+---
+
+## Side Channel Attacks
+
+A side channel attack is when a cryptographic system is attacked, and the attacker has another source of information outputted by the system.
+
+---
+
+## Timing Attacks
+
+A timing attack can be possible if any of the following<br/> depend on the contents of a secret:
+
+<pba-flex center>
+
+- Which instructions execute<!-- .element: class="fragment" data-fragment-index="0" -->
+- Branching (if statements)<!-- .element: class="fragment" data-fragment-index="1" -->
+- Memory access patterns<!-- .element: class="fragment" data-fragment-index="2" -->
+
+</pba-flex>
+
+Notes:
+
+There are many crazy forms of side channel attack, but the primary one is timing. Timing is also the only one that gets reliably sent back over a long distance.
+
+---
+
+## An Example
+
+Imagine this is the source code for a password checker:
+
+```rust
+fn verify_password(actual: &[u8], entered: &[u8]) -> bool {
+ if actual.len() != entered.len() {
+    return false;
+ }
+
+ for i in 0..actual.len() {
+  if entered.get(i) != actual.get(i) {
+   return false;
+  }
+ }
+ true
+}
+```
+
+What's the problem?
+
+Notes:
+
+Imagine you compile this into a little binary, and you are able to hit it repeatedly. When sending a guess into this, what information do you get back?
+
+A boolean, and the amount of time from sending the password to getting back a response.
+
+The problem is that the amount of time for a response reveals information about the password. An attacker can send in guesses repeatedly, and if it takes a longer amount of time to respond, that means more of the guess is correct.
+
+---
+
+## Example (Cont)
+
+What if we changed the code to look like this?
+
+```rust
+fn verify_password(actual: &[u8], entered: &[u8]) -> bool {
+ actual == entered
+}
+```
+
+Is this safe?
+
+Notes:
+
+Now, we don't see any difference in the amount of lines of code or loops, right?
+
+---
+
+## Example (Cont)
+
+What does the source code look like?
+
+```rust[0|1|7-9|15]
+// Use memcmp for bytewise equality when the types allow
+impl<A, B> SlicePartialEq<B> for [A]
+where
+    A: BytewiseEq<B>,
+{
+    fn equal(&self, other: &[B]) -> bool {
+        if self.len() != other.len() {
+            return false;
+        }
+
+        // SAFETY: `self` and `other` are references and are thus guaranteed to be valid.
+        // The two slices have been checked to have the same size above.
+        unsafe {
+            let size = mem::size_of_val(self);
+            memcmp(self.as_ptr() as *const u8, other.as_ptr() as *const u8, size) == 0
+        }
+    }
+}
+```
+
+Is this safe?
+
+Notes:
+
+Ok, still no. It looks like now the attacker can still figure out if the length of the password based on an early return. But what if we make sure all passwords are 16 bytes long. Now we are just using a single syscall. Is is safe then?
+
+---
+
+## Example (Cont)
+
+Let's check on `memcmp`.
+
+```text
+memcmp(3) — Linux manual page
+
+/* snip */
+
+NOTES
+       Do not use memcmp() to compare security critical data, such as
+       cryptographic secrets, because the required CPU time depends on
+       the number of equal bytes.  Instead, a function that performs
+       comparisons in constant time is required.  Some operating systems
+       provide such a function (e.g., NetBSD's consttime_memequal()),
+       but no such function is specified in POSIX.  On Linux, it may be
+       necessary to implement such a function oneself.
+```
+
+---
+
+## So how could we do it?
+
+This is from the `subtle` crate, which provides constant time equality.
+
+```rust[0|14-15|20-28]
+impl<T: ConstantTimeEq> ConstantTimeEq for [T] {
+    /// Check whether two slices of `ConstantTimeEq` types are equal.
+    ///
+    /// # Note
+    ///
+    /// This function short-circuits if the lengths of the input slices
+    /// are different.  Otherwise, it should execute in time independent
+    /// of the slice contents.
+    /* snip */
+    #[inline]
+    fn ct_eq(&self, _rhs: &[T]) -> Choice {
+        let len = self.len();
+
+        // Short-circuit on the *lengths* of the slices, not their
+        // contents.
+        if len != _rhs.len() {
+            return Choice::from(0);
+        }
+
+        // This loop shouldn't be shortcircuitable, since the compiler
+        // shouldn't be able to reason about the value of the `u8`
+        // unwrapped from the `ct_eq` result.
+        let mut x = 1u8;
+        for (ai, bi) in self.iter().zip(_rhs.iter()) {
+            x &= ai.ct_eq(bi).unwrap_u8();
+        }
+
+        x.into()
+    }
+}
+```
+
+Notes:
+
+Now we've seen how hard it can be just to stop a very simple leak of timing information. Let's see what an actual cryptographic library concerns itself with.
+
+---
+
+## Ed25519's Guarantees
+
+This is an excerpt from the [ed25519](https://ed25519.cr.yp.to/) description.
+
+- **Foolproof session keys**. Signatures are generated deterministically; key generation consumes new randomness but new signatures do not. This is not only a speed feature but also a security feature.
+- **Collision resilience**. Hash-function collisions do not break this system. This adds a layer of defense against the possibility of weakness in the selected hash function.
+
+---
+
+## Ed25519's Guarantees (Cont.)
+
+- **No secret array indices**. The software never reads or writes data from secret addresses in RAM; the pattern of addresses is completely predictable. The software is therefore immune to cache-timing attacks, hyperthreading attacks, and other side-channel attacks that rely on leakage of addresses through the CPU cache.
+- **No secret branch conditions**. The software never performs conditional branches based on secret data; the pattern of jumps is completely predictable. The software is therefore immune to side-channel attacks that rely on leakage of information through the branch-prediction unit.
+
+---
+
+## Takeway: DO NOT ROLL YOUR OWN CRYPTO
+
+Preventing side channel attacks is _hard_! Noticing sidechannel attacks is even harder!
+
+<img style="width: 800px;" src="./img/we_rolled_our_own_crypto.png" />
+
+### 
+
+Notes:
+
+Be very, very careful whenever you do _anything_ that touches a secret. That includes any operation involving the secret, or reading/writing it somewhere.
+
+When necessary, talk to a security expert or cryptographer.
+
+---
+
+## Using Cryptographic Libraries Safely
+
+- Stay "above" the abstraction barrier<!-- .element: class="fragment" data-fragment-index="0" -->
+- Validate each primitive's assumptions when combining primitives<!-- .element: class="fragment" data-fragment-index="1" -->
+- Use the most reputable library you can<!-- .element: class="fragment" data-fragment-index="2" -->
+- Realize when things need serious consideration<!-- .element: class="fragment" data-fragment-index="3" -->
+- Some potentially scary terms: Curve point, padding schemes, IV, twisted curve, pairings, ElGamal<!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+Reputableness of a library is some combination of:
+
+- used by many people
+- audited for security
+- reliable cryptographic literature
+- minimal external dependencies
+- recommended by cryptographers
+
+If you get low-level enough in cryptography libraries to see these terms referenced in more than just a description, you're probably too low level.
+
+---
+
+# Horror Stories
+
+Notes:
+
+Only go through a few of these based on interest and remaining time.
+
+---v
+
+## PS3 Secret Key Leak
+
+**Problem**: Bad randomness
+
+**Description**: The ps3 developers didn't use randomness when signing with an algorithm that required randomness.
+
+**Consequence**: Every PS3 was hardcoded to trust that key. When hackers got the key, they were then able to pretend to be Sony and write any software that ran on the PS3. In practice, it made running pirated games trivial.
+
+Notes:
+
+[source](https://www.engadget.com/2010-12-29-hackers-obtain-ps3-private-cryptography-key-due-to-epic-programm.html)
+
+---v
+
+## IOTA's Novel Hash Function
+
+**Problem**: Rolling your own crypto
+
+**Description**: IOTA was a cryptocurrency with a value of 1.9B at the time. They wrote their own hash function, and researchers found severe vulnerabilities.
+
+**Consequence**: Kind security researchers reported the flaw directly to devs. They had to pause the blockchain for 3 days, generate new address for _all_ accounts, and swap to KECCAK.
+
+Notes:
+
+IOTA originally rolled their own hash function in an effort to be quantum-proof.
+
+Some hash function weaknesses are weak. This was not. The proof of concept exploit literally found two hashes that correspond to a message for the blockchain sending a small amount of currency, and another that corresponded to a message sending a huge amount of money.
+
+[exploit POC](https://github.com/mit-dci/tangled-curl/blob/master/vuln-iota.md)
+[shutdown source](https://www.bitfinex.com/posts/215)
+
+---v
+
+## How the NSA wiretapped all cellphone calls for years
+
+**Problem**: Small key space / secret technique
+
+**Description**: The standard for cellphone calls up until the mid-late 2000s (GSM A5/1) used 54-bit keys, and the method was meant to be secret. It did not stay secret, and became extremely easily crackable.
+
+**Consequence**: Intelligence agencies could and did easily wiretap calls. There were many brute-force attacks against the key space.
+
+Notes:
+
+When the standardization process started, professors proposed 128-bit keys. Western european (british especially) intelligence agencies wanted weaker security. Snowden eventually came out and said the NSA could easily read A5/1 calls.
+
+[article source](http://goodenoughsecurity.blogspot.com/2011/10/gsm-a51-substandard-security-pt2.html)
+[source on weakening](https://www.aftenposten.no/verden/i/Olkl/sources-we-were-pressured-to-weaken-the-mobile-security-in-the-80s)
+
+---v
+
+## Why HTTPS isn't as secure as you'd hope
+
+**Problem**: Cryptographic primitive assumptions not upheld
+
+**Description**: Encryption _does not_ generally hide the length of the underlying message. HTTPS often uses compression before encryption. The compression makes duplicated strings smaller.
+
+**Consequence**: An exploit called BREACH can reveal a secret from an HTTPS-protected website in under 30 seconds. All websites have had to add mitigation to offset this attack.
+
+Notes:
+
+Mitigation looks like:
+
+- randomizing size of response content after compression
+- separating secrest from user input
+- disabling HTTP compression (this is expensive though)
+- randomizing secrets per request
+
+[source](https://arstechnica.com/information-technology/2013/08/gone-in-30-seconds-new-attack-plucks-secrets-from-https-protected-pages/)
+
+---
+
+## Physical Security
+
+<img style="width: 900px;" src="./img/xkcd-physical-security.png" />
+
+Notes:
+
+Source is a classic XKCD comic.
+
+---
+
+## Physical Security
+
+Full physical access to a running computer can usually let an attacker have full access to your secrets with enough effort.
+
+Some possible means:
+
+- Scanning all disk storage
+- Take out the RAM and swap it into a different computer to read (cold boot attack)
+- Proximate side-channel attacks
+  - RF emissions
+  - Power consumption
+  - Sound of a computer running
+
+Notes:
+
+Sources for exotic attacks:
+
+- [general survey of EM side channel attacks](https://arxiv.org/abs/1903.07703)
+- [sound-based attack](https://www.iacr.org/archive/crypto2014/86160149/86160149.pdf)
+- [EM side channel attack from 15m with 500 traces only](https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A1648290&dswid=6646)
+
+---
+
+## HSMs
+
+An HSM is a **h**ardware **s**ecurity **m**odule. HSMs can make it much harder to impossible to steal cryptographic keys. An HSM will hold cryptographic keys, and perform operations on them.
+
+Notes:
+
+We don't go into this much, as there are many available resources around physical security and HSMs. This is just bringing up the ideas, in the context of what makes a cryptographic secret actually _secret_.
+
+---
+
+## Security and Usability
+
+The accessibility of a secret is typically inversely proportional to the security.
+
+Making a secret more secure is often impractical, depending on the usage.
+
+Notes:
+
+This is not explicitly true in all cases, but it is a good rule of thumb. Additionally, note that impractical != impossible.
+
+---
+
+## Thought Experiment
+
+Suppose I give you a secret that's too long to memorize.
+
+At the end of a year, if nobody else knows the secret, I'll give you a million dollars.
+
+What do you do?
+
+---
+
+## Thought Experiment
+
+Suppose I give you a secret that's too long to memorize.
+
+At the end of a year, if nobody else knows the secret, I'll give you a million dollars.
+
+What do you do?
+
+### Destroy it
+
+---
+
+## Thought Experiment
+
+Suppose I give you a secret that's too long to memorize.
+
+At the end of a year, if nobody else knows the secret **and you present me the secret**, I'll give you a million dollars.
+
+What do you do?
+
+---
+
+## Thought Experiment
+
+Suppose I give you a secret that's too long to memorize.
+
+At the end of a year, if nobody else knows the secret **and you present me the secret**, I'll give you a million dollars.
+
+What do you do?
+
+### Hide it somewhere secure
+
+Notes:
+
+Like a bank vault, box buried in the woods, etc
+
+---
+
+## Thought Experiment
+
+Suppose I give you a secret that's too long to memorize.
+
+At the end of a year, if nobody else knows the secret **and you present me the secret once per month**, I'll give you a million dollars.
+
+What do you do?
+
+---
+
+## Thought Experiment
+
+Suppose I give you a secret that's too long to memorize.
+
+At the end of a year, if nobody else knows the secret **and you present me the secret every day**, I'll give you a million dollars.
+
+What do you do?
+
+---
+
+## Application to Cryptographic Secrets
+
+Cryptographic secrets are easy to have multiple of.
+
+So don't make users use the same one for everything!
+
+As much as possible, one root secret shouldn't be _both_ used regularly, and extremely valuable.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/1-Cryptography/2-Addresses-slides.md b/content/1-Cryptography/2-Addresses-slides.md
new file mode 100644
index 00000000..73070818
--- /dev/null
+++ b/content/1-Cryptography/2-Addresses-slides.md
@@ -0,0 +1,342 @@
+---
+title: Addresses and Keys
+description: Addresses and keys in cryptography
+duration: 30 min
+---
+
+# Addresses and Keys
+
+---
+
+# Outline
+
+<pba-flex center>
+
+1. Binary Formats<!-- .element: class="fragment" data-fragment-index="1" -->
+1. Seed Creation<!-- .element: class="fragment" data-fragment-index="2" -->
+1. Hierarchical Deterministic Key Derivation<!-- .element: class="fragment" data-fragment-index="3" -->
+
+</pba-flex>
+
+---
+
+## Binary Display Formats
+
+When representing binary data, there are a few different display formats you should be familiar with.
+
+Hex: 0-9, a-f<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Base64: A-Z, a-z, 0-9, +, /<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Base58: Base64 without 0/O, I/l, +, and /<!-- .element: class="fragment" data-fragment-index="3" -->
+
+Notes:
+
+Be very clear that this is a display format that we use to _transmit binary data through text_. The same data can be encoded with any of these formats, it's just important to know which one you're using to decode. Data is not typically stored in these formats unless it has to be transmitted through text.
+
+---
+
+## Binary Display Formats Example
+
+Every hex character is 4 bits.</br>
+Every base64 character is 6 bits.</br>
+base58 characters are usually _about_ 6 bits.</br>
+
+```text
+binary: 10011111 00001010 10011110 10011000 01001100 11010011 10110010 00000101
+hex:    9   f    0   a    9   e    9   8    4    c   d   3    b   2    0   5
+base64: n     w      q      e      m     E      z      T      s     g      U=
+base58: T     b      u      H      z     e      3      c      t     k      c
+
+hex:    9f0a9e984cd3b205
+base64: nwqemEzTsgU=
+base58: TbuHze3ctkc
+```
+
+Notes:
+
+It turns out that converting from hex/base64 to base58 can in theory take n^2 time!
+
+The number of bits of a character is log2(Base) so for base58 it is log2(58) ~ 5.8
+
+---
+
+# Mnemonics and Seed Creation
+
+Notes:
+
+These are all different _representation_ of a secret. Fundamentally doesn't really change anything.
+
+---
+
+## Seeds are secrets
+
+Recall, both symmetric and asymmetric cryptography require a secret.
+
+---
+
+## Mnemonics
+
+Many wallets use a dictionary of words and give people phrases,<br />often 12 or 24 words, as these are easier to back up/recover than byte arrays.
+
+Notes:
+
+High entropy needed.
+People are _bad_ at being random.
+Some people create their own phrases... this is usually stupid.
+
+---
+
+## Dictionaries
+
+<pba-cols>
+<pba-col>
+
+There are some standard dictionaries to define which words (and character sets) are included in the generation of a phrase. Substrate uses the dictionary from BIP39.
+
+</pba-col>
+<pba-col>
+
+| No. | word    |
+| --- | ------- |
+| 1   | abandon |
+| 2   | ability |
+| 3   | able    |
+| 4   | about   |
+| 5   | above   |
+
+<pba-flex style="font-size: .6em;" center>
+
+_The first 5 words of the [BIP39 English dictionary](https://github.com/bitcoin/bips/blob/master/bip-0039/english.txt)_
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Question to ask:
+Does anyone know what a BIP is?
+
+---
+
+## Mnemonic to Secret Key
+
+For the Math peoples, what is a secret key?<!-- .element: class="fragment" data-fragment-index="0" -->
+
+Mathematically, the secret key is usually an element of some huge finite field. <!-- .element: class="fragment" data-fragment-index="1" -->
+
+In common asymmetric cryptographic systems, it is an element of the scalar field of an elliptic curve. <!-- .element: class="fragment" data-fragment-index="2" -->
+
+In that regard, it not just a phrase! <!-- .element: class="fragment" data-fragment-index="3" -->
+
+BIP39 applies 2,048 rounds of the SHA-512 hash function<br /> to the mnemonic to derive a 64 byte key.<!-- .element: class="fragment" data-fragment-index="4" -->
+
+---
+
+## Portability
+
+Different key derivation functions affect the ability to use the same mnemonic in multiple wallets as different wallets may use different functions to derive the secret from the mnemonic.
+
+Notes:
+i.e. May hash to a different scalar field because of a different elliptic curve
+
+---
+
+## Cryptography Types
+
+In common (modernish) cryptosystems, generally you will encounter 3 different modern types of cryptography across most systems you use.
+
+- Ed25519
+- Sr25519
+- ECDSA (over secp256k1)
+
+We will go more in depth in future lectures!
+
+Notes:
+
+These are digital signature schemes. ECDSA can use any elliptic curve but
+in the case of bitcoin it use secp256k1
+
+Sr25519 and Ed25519 uses the same which is Curve25519
+
+You may have learned RSA in school. It is outdated now, and requires _huge_ keys.
+RSA-4096: A 4096-bit RSA key 512 bytes
+sr25519 is 32 bytes
+
+There is also BLS12-381 curves but it is less user facing.
+
+---
+
+## What is an address?
+
+An address is a representation of a public key, potentially with additional contextual information.
+
+Notes:
+
+A public key is a point on a defined elliptic curve more specifically
+the secret scalar value multiplied times a fixed base point on some curve G
+
+Having an address for a symmetric cryptography doesn't actually make any sense, because there is no
+public information about a symmetric key.
+
+---
+
+## Address Formats
+
+Addresses often include a checksum so that a typo cannot change one valid address to another.
+
+```text
+Valid address:   5GEkFD1WxzmfasT7yMUERDprkEueFEDrSojE3ajwxXvfYYaF
+Invalid address: 5GEkFD1WxzmfasT7yMUERDprk3ueFEDrSojE3ajwxXvfYYaF
+                                          ^
+                                          E changed to 3
+```
+
+Notes:
+
+It hasn't been covered yet, but some addresses even go _extra fancy_ and include an error correcting code in the address.
+
+Question for class:
+What is a checksum?
+
+---
+
+## SS58 Address Format
+
+SS58 is the format used in Substrate.
+
+It is base58 encoded, and includes a checksum and some context information.
+Almost always, it is 2 bytes of context and 2 bytes of checksum.
+
+```text
+base58Encode( context | public key | checksum )
+```
+
+Notes:
+`|` here stands for concatenation.
+
+For ECDSA, the public key is 33 bytes, so we use the hash of it in place of the public key.
+
+There are a lot more variants here, but this is by far the most common one.
+
+[reference](https://docs.substrate.io/reference/address-formats/)
+
+---
+
+## HDKD
+
+Hierarchical Deterministic Key Derivation
+
+<img style="width: 1100px;" src="./img/HD-Deterministic-Wallet.png" />
+
+---
+
+## Hard vs. Soft
+
+Key derivation allows one to derive (virtually limitless)<br />child keys from one "parent".
+
+Derivations can either be "hard" or "soft".
+
+---
+
+## Hard vs. Soft
+
+<img style="width: 1200px;" src="./img/soft-vs-hard-derivation.png" />
+
+---
+
+## Hard Derivation
+
+Hard derivation requires the secret key and derives new child secret keys.<!-- .element: class="fragment" data-fragment-index="0" -->
+
+Always do hard paths first, then conclude in soft paths.<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+Typical "operational security" usages should favor hard derivation over soft derivation because hard derivations avoid leaking the sibling keys, unless the original secret is compromised.
+
+    DONT MENTION THIS BUT FOR NOTES!!
+    - Because you cannot derive a parent key from a child key with hard derivation but with soft you can
+
+---
+
+## Hard Derivation in Wallets
+
+Wallets can derive keys for use in different consensus systems while only needing to back up one secret plus a pattern for child derivation.
+
+<img style="width: 1000px;" src="./img/Hard-Derivation-in-Wallets.png" />
+
+---
+
+## Hard Derivation in Wallets
+
+Let's imagine we want to use this key on multiple networks, but we don't want the public keys to be connected to each other.
+
+<img style="width: 1000px;" src="./img/Hard-Derivation-in-Wallets.png" />
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Subkey Demo
+
+## Hard Derivation
+
+Notes:
+
+Hard keys: Take a _path_ (data like a name/index), concatenate with the original key, and hash it for a new key.
+They reveal nothing about keys above them, and only with the _path_ between it and children could they be recovered.
+
+- use `sha3sum -N 256` for a 32byte output and hash type in two things and press ctrl D
+- use inspect on the two private keys see that they are completely different public keys non-linkable
+
+---
+
+## Soft Derivation
+
+Soft derivation allows one to create derived addresses from only the public key.
+Contrary to hard derivation, _all_ keys are related.
+
+Notes:
+
+- With any key and the paths to children and. or parents, the public _and_ private keys can be recovered.
+- Soft derivations can break some niche advanced protocols, but our sr25519 crate avoids supporting protocols that conflict with soft derivations.
+
+---
+
+## Soft Derivation
+
+- Note that these generate new addresses, but use the same secret seed.
+
+---
+
+## Soft Derivation in Wallets
+
+Wallets can use soft derivation to link all payments controlled by a single private key, without the need to expose the private key for the address derivation.
+
+**Use case:** _A business wants to generate a new address for each payment, but should be able to automatically give customers an address without the secret key owner deriving a new child._
+
+Notes:
+
+On the use case, taking each payment at a different address could help make the association between payment and customer.
+
+See: <https://wiki.polkadot.network/docs/learn-accounts#soft-vs-hard-derivation>
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Subkey Demo
+
+## Soft Derivation
+
+Notes:
+
+See the Jupyter notebook and/or HackMD cheat sheet for this lesson.
+
+Mention that these derivations create entirely new secret seeds.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/1-Cryptography/3-Hashes-slides.md b/content/1-Cryptography/3-Hashes-slides.md
new file mode 100644
index 00000000..9ebff9e3
--- /dev/null
+++ b/content/1-Cryptography/3-Hashes-slides.md
@@ -0,0 +1,514 @@
+---
+title: Hash Functions
+description: Hash functions in Substrate
+duration: 1 hour
+---
+
+# Cryptography Day II
+
+<pba-flex center>
+
+- Quiz<!-- .element: class="fragment" data-fragment-index="-1" -->
+- Hash functions<!-- .element: class="fragment" data-fragment-index="0" -->
+- Encryption<!-- .element: class="fragment" data-fragment-index="1" -->
+- Basic Digital Signatures<!-- .element: class="fragment" data-fragment-index="2" -->
+- Advanced Digital Signatures<!-- .element: class="fragment" data-fragment-index="3" -->
+- AES Mods activity<!-- .element: class="fragment" data-fragment-index="4" -->
+
+</pba-flex>
+
+---
+
+# Hash Functions
+
+---
+
+## Introduction
+
+We often want a succinct representation of some data<br />with the expectation that we are referring to the same data.
+
+##### A "fingerprint"
+
+---
+
+## Hash Function Properties
+
+- Accept unbounded size input <!-- .element: class="fragment" data-fragment-index="0" -->
+- Map to a bounded output <!-- .element: class="fragment" data-fragment-index="1" -->
+- Be fast to compute <!-- .element: class="fragment" data-fragment-index="2" -->
+- Resist pre-image attacks:<br />Given an output, it is hard to compute a pre-image <!-- .element: class="fragment" data-fragment-index="3" -->
+- Second pre-image resistance: <br />Given an input (and its hashed output), it is hard to compute another input with the same hash<br /><!-- .element: class="fragment" data-fragment-index="4" -->
+- Resist collisions:<br />It is hard to compute two inputs that have the same hash<!-- .element: class="fragment" data-fragment-index="5" -->
+
+Notes:
+
+1. one way meaning for a given output difficult to get the input
+1. attacker has the value 5 and from that can find a preimage that hashes to 5 (5 just an example value)
+1. attacker has input and output and cant find a another input which maps to the output
+1. More generally the attacker has the entire input space and cant find two inputs which hash to the same value
+
+---
+
+## Hash Function API
+
+A hash function should:
+
+- Accept an unbounded input size (`[u8]` byte array)
+- Return a fixed-length output (here, a 32 byte array).
+
+```rust
+fn hash(s: &[u8]) -> [u8; 32];
+```
+
+---
+
+## Example
+
+**Short input (5 bytes):**
+
+```text
+hash('hello') =
+ 0x1c8aff950685c2ed4bc3174f3472287b56d9517b9c948127319a09a7a36deac8
+```
+
+**Large input (1.2 MB):**
+
+```text
+hash(Harry_Potter_series_as_string) u
+ 0xc4d194054f03dc7155ccb080f1e6d8519d9d6a83e916960de973c93231aca8f4
+```
+
+---
+
+## Input Sensitivity
+
+Changing even 1 bit of a hash function _completely_ scrambles the output.
+
+```text
+hash('hello') =
+ 0x1c8aff950685c2ed4bc3174f3472287b56d9517b9c948127319a09a7a36deac8
+```
+
+```text
+hash('hellp') =
+ 0x7bc9c272894216442e0ad9df694c50b6a0e12f6f4b3d9267904239c63a7a0807
+```
+
+---
+
+## Speed
+
+- Some hash functions are designed to be slow. <!-- .element: class="fragment" data-fragment-index="0" -->
+- Does anyone know why someone would want a hash function to be slow? <!-- .element: class="fragment" data-fragment-index="1" -->
+- These have applications like password hashing, which would slow down brute-force attackers. <!-- .element: class="fragment" data-fragment-index="2" -->
+- For our purposes, we generally want them to be fast. <!-- .element: class="fragment" data-fragment-index="3" -->
+
+---
+
+## Famous Hash Algorithms
+
+<pba-flex center>
+
+- xxHash a.k.a TwoX (non-cryptographic)
+- MD5
+- SHA1
+- RIPEMD-160
+- SHA2-256 (aka SHA256) &c.
+- SHA3
+- Keccak
+- Blake2
+
+xxHash64 is about 20x faster than Blake2.
+
+</pba-flex>
+
+---
+
+## Hash Functions in Blockchains
+
+<pba-flex center>
+
+- Bitcoin: SHA2-256 & RIPMD-160
+- Ethereum: Keccak-256 (though others supported via EVM)
+- Polkadot: Blake2 & xxHash (though others supported via host functions)
+
+</pba-flex>
+
+Notes:
+
+Substrate also implements traits that provide 160, 256, and 512 bit outputs for each hasher.
+
+Exercise: Write your own benchmarking script that compares the performance of these algorithms with various input sizes.
+
+---
+
+### Hashing Benchmarks
+
+<img rounded style="height: 650px" src="./img/crypto-bench.png" />
+
+Notes:
+
+Benchmarks for the _cryptographic_ hashing algorithms.
+Source: <https://www.blake2.net/>
+
+---
+
+#### XXHash - _Fast_ hashing algorithm
+
+<img rounded style="height: 600px" src="./img/Benchmark-XXHash.png" />
+
+Notes:
+
+Benchmarks for the XX-hash algorithms.
+Source: <https://github.com/Cyan4973/xxHash#benchmarks>
+
+---
+
+## Non-Cryptographic Hash Functions
+
+Non-cryptographic hash functions provide weaker<br />guarantees in exchange for performance.
+
+They are OK to use when you know that the input is not malicious.
+
+**If in doubt, use a cryptographic hash function.**
+
+---
+
+## One Way
+
+Given a hash, it should be difficult to find an input value (pre-image)<br />that would produce the given hash.
+
+That is, given `H(x)`, it should be difficult to find `x`.
+
+Notes:
+
+We sometimes add random bytes to pre-images to prevent guesses based on context (e.g., if you are hashing "rock, paper, scissors", then finding a pre-image is trivial without some added randomness.)
+
+---
+
+## Second Pre-Image Attacks
+
+Given a hash and a pre-image, it should be difficult to find _another_<br />pre-image that would produce the same hash.
+
+Given `H(x)`, it should be difficult to find any `x'`
+
+such that `H(x) == H(x')`.
+
+Notes:
+
+Since most signature schemes perform some internal hashing, this second pre-image would also pass signature verification.
+
+---
+
+## Collision Resistance
+
+It should be difficult for someone to find two messages that<br />hash to the same value.
+
+It should be difficult to find an `x` and `y`
+
+such that `H(x) == H(y)`.
+
+---
+
+## Collision Resistance
+
+**Difference from second pre-image attack:**
+
+In a second pre-image attack, the attacker only controls one input.
+
+In a collision, the attacker controls both inputs.
+
+Notes:
+
+Attacker has intention to impersonate the signer with the other. Generally speaking, even finding a
+single hash collision often results in the hash function being considered unsafe.
+
+---
+
+## Birthday Problem
+
+<pba-cols>
+<pba-col style="font-size:smaller">
+
+> With 23 people, there is a 6% chance that someone will be born on a specific date, but a 50% chance that two share a birthday.
+
+- Must compare each birthday with every other, not with a single one.<br /> <!-- .element: class="fragment" data-fragment-index="0" -->
+- Number of possible "hits" increases exponentially for more attempts, reducing the expected success to the square-root of what a specific target would be. <!-- .element: class="fragment" data-fragment-index="1" -->
+
+</pba-col>
+<pba-col>
+
+<img style="width: 700px; border-radius: 0;" src="./img/birthday-problem.svg" />
+
+</pba-col>
+</pba-cols>
+
+---
+
+## Birthday Attack
+
+Thus, with a birthday attack, it is possible to find a collision of a hash function in $\sqrt {2^{n}}=2^{^{\frac{n}{2}}}$, with $\cdot 2^{^{\frac{n}{2}}}$ being the classical preimage resistance security.
+
+So, hash function security is only half of the bit space.
+
+Notes:
+
+e.g., a 256 bit hash output yields 2^128 security
+
+- <https://en.wikipedia.org/wiki/Birthday_attack>
+
+- <https://en.wikipedia.org/wiki/Birthday_problem>
+
+---
+
+## Partial Resistance
+
+It should be difficult for someone to partially (for a substring of the hash output) find a collision or "second" pre-image.
+
+- Bitcoin PoW is a partial pre-image attack. <!-- .element: class="fragment" data-fragment-index="0" -->
+- Can anyone explain how? <!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+This is a technique used to trick users into thinking they are interacting with a trusted entity (like a account or piece of data) when they are actually interacting with a malicious actor. This can be done by creating a fraudulent address that looks similar to a legitimate one.
+example AEVXZ AEVYZ
+
+---
+
+## Hash Function Selection
+
+<pba-flex center>
+
+When users (i.e. attackers) have control of the input, cryptographic hash functions must be used.
+
+When input is not controllable (e.g. a system-assigned index), a non-cryptographic hash function can be used and is faster.
+
+Notes:
+
+Only safe when the users cannot select the pre-image, e.g. a system-assigned index.
+
+Keccak is available for Ethereum compatibility.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Applications
+
+---
+
+## Cryptographic Guarantees
+
+Let's see which cryptographic properties apply to hashes.
+
+---v
+
+## Confidentiality
+
+- Sending or publicly posting a hash of some data $D$ keeps $D$ confidential, as only those who already knew $D$ recognize $H(D)$ as representing $D$.
+- Both cryptographic and non-cryptographic hashes work for this, _only if the input space is large enough_.
+
+---v
+
+## Confidentiality Bad Example
+
+Imagine playing rock, paper, scissors by posting hashes and then revealing. However, if the message is either "rock", "paper", or "scissors", the output will always be either:
+
+```text
+hash('rock') = 0x10977e4d68108d418408bc9310b60fc6d0a750c63ccef42cfb0ead23ab73d102
+hash('paper') = 0xea923ca2cdda6b54f4fb2bf6a063e5a59a6369ca4c4ae2c4ce02a147b3036a21
+hash('scissors') = 0x389a2d4e358d901bfdf22245f32b4b0a401cc16a4b92155a2ee5da98273dad9a
+```
+
+The other player doesn't need to undo the hash function to know what you played!
+
+Notes:
+
+Question:
+How can we fix this issue?
+
+The data space has to be _sufficiently large_.
+Adding some randomness to input of the hash fixes this. Add x bits of randomness to make it x bits of security on that hash.
+
+---v
+
+## Authenticity
+
+Anyone can make a hash, so hashes provide no authenticity guarantees.
+
+---v
+
+## Integrity
+
+A hash changes if the data changes, so it does provide integrity.
+
+---v
+
+## Non-Repudiation
+
+Hashes on their own cannot provide authenticity, and as such cannot provide non-repudiation.
+
+However, if used in another cryptographic primitive that _does_ provide non-repudiation, $H(D)$ provides the same non-repudation as $D$ itself.
+
+Notes:
+
+- The hash alone doesnt give one the ability to authenticate or identify the originator of the data because anyone with access to the data can produce the same hash.
+
+This is key in digital signatures. However, it's important to realize that if $D$ is kept secret, $H(D)$ is basically meaningless.
+
+---
+
+## Content-Derived Indexing
+
+Hash functions can be used to generate deterministic<br />and unique lookup keys for databases.
+
+Notes:
+
+Given some fixed property, like an ID and other metadata the user knows beforehand, they can always find the database entry with all of the content they are looking for.
+
+---
+
+## Data Integrity Checks
+
+Members of a peer-to-peer network may host and share<br />file chunks rather than large files.
+
+In [Bittorrent](https://en.wikipedia.org/wiki/BitTorrent), each file chunk is hash identified so peers can<br /> _request and verify_ the chunk is a member of the larger,<br /> _content addressed_ file.
+
+Notes:
+
+- Content addressed file is when a file is identified based on the content of the file.
+
+- The hash of the large file can also serve as a signal to the protocol that transmission is complete.
+
+---
+
+## Account Abstractions
+
+Public keys can be used to authorize actions by signing of instructions.
+
+The properties of hash functions allow other kinds of representations.
+
+---
+
+## Public Key Representation
+
+Because hashes serve as unique representations of other data,<br />that other data could include public keys.<br />
+A system can map a plurality of key sizes to a fixed length<br />(e.g. for use as a database key).
+
+For example, the ECDSA public key is 33 bytes:
+
+```text
+Public key (hex):
+  0x02d82cdc83a966aaabf660c4496021918466e61455d2bc403c34bde8148b227d7a
+
+Hash of pub key:
+  0x8fea32b38ed87b4739378aa48f73ea5d0333b973ee72c5cb7578b143f82cf7e9
+                                                                    ^^
+```
+
+---
+
+## Commitment Schemes
+
+It is often useful to commit to some information<br /> without storing or revealing it:
+
+- A prediction market would want to reveal predictions only after the confirming/refuting event occurred.<!-- .element: class="fragment" data-fragment-index="0" -->
+- Users of a system may want to discuss proposals without storing the proposal on the system.<!-- .element: class="fragment" data-fragment-index="1" -->
+- However, participants should not be able to modify their predictions or proposals.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+What is an example of an application would use an application like this?
+
+---
+
+## Commit-Reveal
+
+<pba-flex center>
+
+1. Share a hash of data as a commitment ($c$)
+1. Reveal the data itself ($d$)
+
+<pba-flex>
+
+It is normal to add some randomness to the message<br />to expand the input set size:
+
+$$ hash(message + randomness) => commitment $$
+
+<pba-flex style="font-size: smaller;">
+
+Commitment: `0x97c9b8d5019e51b227b7a13cd2c753cae2df9d3b435e4122787aff968e666b0b`
+
+---
+
+## Reveal
+
+Message with some added randomness:
+
+<pba-flex style="font-size: smaller;">
+
+> "I predict Boris Johnson will resign on 7 July 2022. facc8d3303c61ec1808f00ba612c680f"
+
+---
+
+## Data Identifiers
+
+Sometimes people want to store information in one place and reference it in another. For reference, they need some "fingerprint" or digest.
+
+As an example, they may vote on executing some privileged instructions within the system.
+
+The hash of the information can succinctly represent the information and commit its creator to not altering it.
+
+---
+
+## Data Structures (in Brief)
+
+This is the focus of a later lesson.
+
+Notes:
+For now, just a brief introduction.
+
+---
+
+## Pointer-Based Linked Lists
+
+Pointer-based linked lists are a foundation of programming.
+
+But pointers are independent from the data they reference,<br />so the data can be modified while maintaining the list.
+
+That is, pointer-based linked lists are not tamper evident.
+
+<img src="./img/Hash-Chains.png" />
+
+---
+
+## Hash-Based Linked Lists
+
+Hash-based lists make the reference related to the data they are referencing.<br />
+The properties of hash functions make them a good choice for this application.
+
+Any change at any point in the list would create downstream changes to all hashes.
+
+---
+
+## Merkle Trees
+
+<img  src="./img/Merkle-Tree.png" />
+
+Notes:
+
+Each leaf is the hash of some data object and each node is the hash of its children.
+
+---
+
+## Proofs
+
+Merkle trees allow many proofs relevant to the rest of this course,<br />e.g. that some data object is a member of the tree<br />without passing the entire tree.
+
+**_More info in a later lesson._**
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
+
+---
diff --git a/content/1-Cryptography/4-Encryption-slides.md b/content/1-Cryptography/4-Encryption-slides.md
new file mode 100644
index 00000000..b7deaa2a
--- /dev/null
+++ b/content/1-Cryptography/4-Encryption-slides.md
@@ -0,0 +1,294 @@
+---
+title: Encryption
+description: A lesson on symmetric and asymmetric encryption.
+duration: 1 hour
+---
+
+# Encryption
+
+---
+
+## Goals for this lesson
+
+<pba-flex center>
+
+- Learn about the differences between symmetric and asymmetric encryption.
+
+</pba-flex>
+
+---
+
+## Symmetric Cryptography
+
+Symmetric encryption assumes all parties begin with some shared secret information, a potentially very difficult requirement.<br/>The shared secret can then be used to protect further communications from others who do not know this secret.
+
+In essence, it gives a way of _extending_ a shared secret over time.
+
+---
+
+## Symmetric Encryption
+
+<img style="width: 1100px" src="./img/Symmetric-Cryptography.png" />
+
+Examples: ChaCha20, Twofish, Serpent, Blowfish, XOR, DES, AES<!-- .element: class="fragment" data-fragment-index="0" -->
+
+---
+
+## Symmetric Encryption API
+
+Symmetric encryption libraries should generally all expose some basic functions:
+
+- `fn generate_key(r) -> k;` <br/> Generate a `k` (secret key) from some input `r`.
+- `fn encrypt(k, msg) -> ciphertext;` <br/> Takes `k` and a message; returns the ciphertext.
+- `fn decrypt(k, ciphertext) -> msg;` <br/> Takes `k` and a ciphertext; returns the original message.
+
+It always holds that `decrypt(k, encrypt(k, msg)) == msg`.
+
+Notes:
+
+The input `r` is typically a source of randomness, for example the movement pattern of a mouse.
+
+---
+
+## Symmetric Encryption Guarantees
+
+Provides:
+
+- Confidentiality
+
+Does not provide:
+
+- Authenticity
+- Integrity
+- Non-Repudiation
+
+Notes:
+
+- Authenticity: The message could only be sent by someone who knows the shared secret key. In most cases, this is functionally authentication to the receiving party.
+- Integrity: There is no proper integrity check, however the changed section of the message will be gibberish if it has been changed. Detection of gibberish could function as a form of integrity-checking.
+
+---
+
+## Symmetric Encryption
+
+#### _Example: XOR Cipher_
+
+<pba-cols>
+<pba-col>
+
+The encryption and decryption functions are identical: applying a bitwise XOR operation with a key.
+
+</pba-col>
+<pba-col style="padding-right: 100px">
+
+```text
+Plain: 1010  -->Cipher: 0110
+Key:   1100  |          1100
+       ----  |          ----
+       0110--^          1010
+```
+
+Notes:
+
+A plaintext can be converted to ciphertext, and vice versa, by applying a bitwise XOR operation with a key known to both parties.
+
+</pba-col>
+</pba-cols>
+
+---
+
+## Symmetric Encryption
+
+#### ⚠ Warning ⚠
+
+We typically expect symmetric encryption to preserve little about the original plaintext.
+We caution however that constructing these protocols remains delicate, even given secure primitives, with two classical examples being unsalted passwords and the [ECB penguin](https://tonybox.net/posts/ecb-penguin/).
+
+---
+
+### ECB penguin
+
+<pba-cols>
+<pba-col>
+
+<img style="width: 300px" src="./img/ECB-Penguin.png" />
+
+_Original image_
+
+</pba-col>
+<pba-col>
+
+<img style="width: 300px" src="./img/ECB-Penguin-Encrypted.png" />
+
+_Encrypted image_
+
+(by blocks)
+
+</pba-col>
+<pba-col>
+
+<img style="width: 300px" src="./img/ECB-Penguin-Secure.png" />
+
+_Encrypted image_
+
+(all at once)
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+The ECB penguin shows what can go wrong when you encrypt a small piece of data, and do this many times with the same key, instead of encrypting data all at once.
+
+Image sources: <https://github.com/robertdavidgraham/ecb-penguin/blob/master/Tux.png> and <https://github.com/robertdavidgraham/ecb-penguin/blob/master/Tux.ecb.png> and <https://upload.wikimedia.org/wikipedia/commons/5/58/Tux_secure.png>
+
+---
+
+## Asymmetric Encryption
+
+- Assumes the sender does not know the recipient's secret "key" 🎉😎
+- Sender only knows a special identifier of this secret<!-- .element: class="fragment" data-fragment-index="0" -->
+- Messages encrypted with the special identifier can only be decrypted with knowledge of the secret.<!-- .element: class="fragment" data-fragment-index="1" -->
+- Knowledge of this identifier does not imply knowledge of the secret, and thus cannot be used to decrypt messages encrypted with it.<!-- .element: class="fragment" data-fragment-index="2" -->
+- For this reason, the identifier may be shared publicly and is known as the "public key".<!-- .element: class="fragment" data-fragment-index="3" -->
+
+---
+
+## Asymmetric Encryption
+
+<img style="height: 600px" src="./img/asymmetric-crypto-flow.svg" />
+
+---
+
+## Why "Asymmetric"?
+
+_Using only the public key_, information can be transformed ("encrypted") such that only those with knowledge of the secret are able to inverse and regain the original information.
+
+i.e. Public key is used to encrypt but a different, _secret_, key must be used to decrypt.
+
+---
+
+## Asymmetric Encryption API
+
+Asymmetric encryption libraries should generally all expose some basic functions:
+
+- `fn generate_key(r) -> sk;` <br/> Generate a `sk` (secret key) from some input `r`.
+- `fn public_key(sk) -> pk;` <br/> Generate a `pk` (public key) from the private key `sk`.
+- `fn encrypt(pk, msg) -> ciphertext;` <br/> Takes the public key and a message; returns the ciphertext.
+- `fn decrypt(sk, ciphertext) -> msg;` <br/> For the inputs `sk` and a ciphertext; returns the original message.
+
+It always holds that `decrypt(sk, encrypt(public_key(sk), msg)) == msg`.
+
+Notes:
+
+The input `r` is typically a source of randomness, for example the movement pattern of a mouse.
+
+---
+
+## Asymmetric Encryption Guarantees
+
+Provides:
+
+- Confidentiality
+
+Does not provide:
+
+- Integrity
+- Authenticity
+- Non-Repudiation
+
+Notes:
+
+- Authenticity: The message could only be sent by someone who knows the shared secret key. In most cases, this is functionally authentication to the receiving party.
+- Integrity: There is no proper integrity check, however the changed section of the message will be gibberish if it has been changed. Detection of gibberish could function as a form of integrity-checking.
+
+---
+
+## Diffie-Hellman Key Exchange
+
+<img style="height: 500px" src="./img/Diffie-Hellman_Key_Exchange_horizontal.svg" />
+
+Mixing Paint Visualization
+
+Notes:
+
+Mixing paint example.
+Image Source: <https://upload.wikimedia.org/wikipedia/commons/4/46/Diffie-Hellman_Key_Exchange.svg>
+
+---
+
+## Authenticated Encryption
+
+Authenticated encryption adds a **M**essage **A**uthentication **C**ode to additionally provide an _authenticity_ and _integrity_ guarantee to encrypted data.
+
+A reader can check the MAC to ensure the message was constructed by someone knowing the secret.
+
+<img style="height: 500px" src="./img/Authenticated_Encryption_EtM.png" />
+
+Notes:
+
+Specifically, this authenticity says that _anyone who does not know the sender's secret_ could not construct the message.
+
+Generally, this adds ~16-32 bytes of overhead per encrypted message.
+
+The image only shows only of of many possible constructions of authenticated encryption.
+
+Explain that the Key2 in the image, could be derived from Key1.
+
+---
+
+## AEAD (**A**uthenticated **E**ncryption **A**ssociated **D**ata)
+
+AEAD is authenticated with some extra data which is unencrypted, but does have integrity and authenticity guarantees.
+
+Notes:
+
+Authenticated encryption and AEAD can work with both symmetric and asymmetric cryptography.
+
+---
+
+## AEAD Example
+
+Imagine a table with encrypted medical records stored in a table, where the data is stored using AEAD. What are the advantages of such a scheme?
+
+```text
+UserID -> Data (encrypted), UserID (associated data)
+```
+
+Notes:
+
+By using this scheme, the data is always associated with the userID. An attacker could not put that entry into another user's entry.
+
+---
+
+## Hybrid Encryption
+
+Hybrid encryption combines the best of all worlds in encryption. Asymmetric encryption establishes a shared secret between the sender and a specific public key, and then uses symmetric encryption to encrypt the actual message. It can also be authenticated.
+
+Notes:
+
+In practice, asymmetric encryption is _almost always_ hybrid encryption.
+
+---
+
+## Cryptographic Properties
+
+| Property        | Symmetric | Asymmetric | Authenticated | Hybrid + Authenticated |
+| --------------- | --------- | ---------- | ------------- | ---------------------- |
+| Confidentiality | Yes       | Yes        | Yes           | Yes                    |
+| Authenticity    | No        | No         | Yes           | Yes                    |
+| Integrity       | No        | No         | Yes           | Yes                    |
+| Non-repudiation | No        | No         | No            | No                     |
+
+Notes:
+
+- Symmetric-Authentication and Authenticated-Authenticity: The message could only be sent by someone who knows the shared secret key. In most cases, this is functionally authentication to the receiving party.
+- Symmetric-Integrity and Asymmetric-Integrity: There is no proper integrity check, however the message will be gibberish if it has been changed. Detection of gibberish could function as a form of integrity-checking.
+- Non-Repudation: Even though none of these primitives provide non-repudiation on their own, it's very possible to add non-repudation to asymmetric and hybrid schemes via signatures.
+- Note that encryption also, most importantly, makes the data _available_ to everyone who should have access.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/1-Cryptography/5-Basic_Signatures-slides.md b/content/1-Cryptography/5-Basic_Signatures-slides.md
new file mode 100644
index 00000000..d3b931f0
--- /dev/null
+++ b/content/1-Cryptography/5-Basic_Signatures-slides.md
@@ -0,0 +1,236 @@
+---
+title: Digital Signature Basics
+description: Hands-on application of digital signature
+duration: 1 hour
+---
+
+# Cryptography Day II
+
+<pba-flex center>
+
+- Quiz
+- Hash functions
+- Encryption
+- Basic Digital Signatures<!-- .element: class="fragment" data-fragment-index="2" -->
+- Advanced Digital Signatures<!-- .element: class="fragment" data-fragment-index="3" -->
+- AES Mods activity<!-- .element: class="fragment" data-fragment-index="4" -->
+
+</pba-flex>
+
+---
+
+# Digital Signatures Basics
+
+---
+
+## Signature API
+
+Signature libraries should generally all expose some basic functions:
+
+<ul>
+<li class="fragment"><code>fn generate_key(r) -> sk;</code> <br />Generate a <code>sk</code> (secret key) from some input <code>r</code>.</li>
+<li class="fragment"><code>fn public_key(sk) -> pk;</code> <br /> Return the <code>pk</code> (public key) from a <code>sk</code>.</li>
+<li class="fragment"><code>fn sign(sk, msg) -> signature;</code> <br /> Takes <code>sk</code> and a message; returns a digital signature.</li>
+<li class="fragment"><code>fn verify(pk, msg, signature) -> bool;</code> <br /> For the inputs <code>pk</code>, a message, and a signature; returns whether the signature is valid.</li>
+</ul>
+
+Notes:
+
+The input `r` could be anything, for example the movement pattern of a mouse.
+
+For some cryptographies (ECDSA), the verify might not take in the public key as an input. It takes in the message and signature, and returns the public key if it is valid.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Subkey Demo
+
+## Key Generation and Signing
+
+Notes:
+
+See the Jupyter notebook and/or HackMD cheat sheet for this lesson.
+
+1. Generate a secret key
+1. Sign a message
+1. Verify the signature
+1. Attempt to alter the message
+
+---
+
+<!-- ##  Hash Functions -->
+
+<!-- There are two lessons dedicated to hash functions.<br />But they are used as part of all signing processes. -->
+
+<!-- For now, we only concern ourselves with using Blake2. -->
+
+<!-- --- -->
+
+## Signing Hashed Messages
+
+As mentioned in the introduction,<br />it's often more practical to sign the hash of a message.
+
+Therefore, the sign/verify API may be _used_ like:
+
+- `fn sign(sk, H(msg)) -> signature;` <!-- .element: class="fragment" data-fragment-index="0" -->
+- `fn verify(pk, H(msg), signature) -> bool;` <!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+Where `H` is a hash function (for our purposes, Blake2).<br />
+This means the verifier will need to run the correct hash function on the message.
+
+---
+
+## Cryptographic Guarantees
+
+Signatures provide many useful properties:
+
+<ul>
+<li class="fragment"><strong>Confidentiality: </strong> Weak, the same as a hash</li>
+<li class="fragment"><strong>Authenticity: </strong> Yes</li>
+<li class="fragment"><strong>Integrity: </strong> Yes</li>
+<li class="fragment"><strong>Non-repudiation: </strong> Yes</li>
+</ul>
+
+Notes:
+
+Question what do each of these mean?
+
+- Confidentiality - If a hash is signed, you can prove a signature is valid _without_ telling anyone the actual message that was signed, just the hash.
+- Authenticity: Authenticity assures that the data comes from a verified source.
+- Integrity assures that the data has not been changed in an unauthorized manner.
+- Non-Repudiation provides evidence that can be used to prove the involvement of parties in a communication, preventing them from denying their actions.
+
+---
+
+## Signing Payloads
+
+<ul>
+<li class="fragment">Signing payloads are an important part of system design.</li>
+<li class="fragment">Users should have credible expectations about how their messages are used.</li>
+<li class="fragment">For example, when a user authorizes a transfer, they almost always mean just one time.</li>
+</ul>
+
+Notes:
+
+There need to be explicit rules about how a message is interpreted. If the same signature can be used in multiple contexts, there is the possibility that it will be maliciously resubmitted.
+
+In an application, this typically looks like namespacing in the signature payload.
+
+---
+
+## Signing and Verifying
+
+<img style="height: 600px" src="./img/sig-verify-flow.svg" />
+
+Notes:
+
+Note that signing and encryption are _not_ inverses.
+
+---
+
+## Replay Attacks
+
+Replay attacks occur when someone intercepts and resends a valid message.<br />
+The receiver will carry out the instructions since the message contains a valid signature.
+
+<pba-flex center>
+
+- Since we assume that channels are insecure, all messages should be considered intercepted.
+- The "receiver", for blockchain purposes, is actually an automated system.
+
+</pba-flex>
+
+Notes:
+
+Lack of _context_ is the problem.
+Solve by embedding the context and intent \_within the message being signed.
+Tell the story of Ethereum Classic replays.
+
+---
+
+## Replay Attack Prevention
+
+Signing payloads should be designed so that they can<br />only be used _one time_ and in _one context_.<br />
+Examples:
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Monotonically increasing account nonces</li>
+<li class="fragment">Timestamps (or previous blocks)</li>
+<li class="fragment">Context identifiers like genesis hash and spec versions</li>
+</ul>
+
+---
+
+# Signature Schemes
+
+---
+
+## ECDSA
+
+<ul>
+<li class="fragment">Commonly uses Secp256k1 elliptic curve.</li>
+<li class="fragment">ECDSA (used initially in Bitcoin/Ethereum) was developed to work around the patent on Schnorr signatures.</li>
+<li class="fragment">ECDSA complicates more advanced cryptographic techniques, like threshold signatures.</li>
+<li class="fragment">Non-Deterministic</li>
+</ul>
+
+Notes:
+
+inverted nonce to get from all signing parties
+is difficult
+
+Setup is difficult secret sharing and setup
+
+Show image of ECDSA vs schnorr to demonstrate this
+
+---
+
+## Ed25519
+
+<ul>
+<li class="fragment">Schnorr signature designed to reduce mistakes in implementation and usage in classical applications, like TLS certificates.</li>
+<li class="fragment">Signing is 20-30x faster than ECDSA signatures.</li>
+<li class="fragment">Deterministic</li>
+</ul>
+
+---
+
+## Schnorr Signature
+
+- To Sign: <!-- .element: class="fragment" data-fragment-index="0" -->
+  - $r \leftarrow kG$ <!-- .element: class="fragment" data-fragment-index="1" -->
+  - $e \leftarrow H(r | M)$<!-- .element: class="fragment" data-fragment-index="2" --> (<s>Verify sends random $e$</s>) <!-- .element: class="fragment" data-fragment-index="2" -->
+  - $s \leftarrow k - xe$ ($x$ is signer's secret key). <!-- .element: class="fragment" data-fragment-index="3" -->
+  - Send $(s, e)$. <!-- .element: class="fragment" data-fragment-index="4" -->
+- To Verify : <!-- .element: class="fragment" data-fragment-index="5" -->
+  - recover $r = sG + e Pub_{Signer}.$ <!-- .element: class="fragment" data-fragment-index="6" -->
+  - Verify $e \stackrel{?}{=} H(r | M)$ <!-- .element: class="fragment" data-fragment-index="7" -->
+
+---
+
+## Sr25519
+
+Sr25519 addresses several small risk factors that emerged<br />from Ed25519 usage by blockchains.
+
+Notes:
+
+Can be Deterministic but in Substrate is implemented as non-deterministic
+
+---
+
+## Use in Substrate
+
+- Sr25519 is the default key type in most Substrate-based applications.
+- Its public key is 32 bytes and generally used to identify key holders (likewise for ed25519).
+- Secp256k1 public keys are _33_ bytes, so their _hash_ is used to represent their holders.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/1-Cryptography/6-Advanced_Signatures-slides.md b/content/1-Cryptography/6-Advanced_Signatures-slides.md
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+---
+title: Advanced Digital Signatures
+description: More exotic digital signature methods
+duration: 1 hour
+---
+
+# Advanced Digital Signatures
+
+---
+
+### Certificates
+
+A certificate is essentially a witness statement concerning one or more public keys. It is a common usage of digital signatures, but _it is not a cryptographic primitive_!
+
+Notes:
+
+A certificate is one issuing key signing a message containing another certified key, which attests to some properties or relationship about the certified key.
+
+We must already trust the issuing key to give this attestation any significance, traditionally provided under "Certificate Authority" or "Web of Trust" schemes.
+
+---
+
+### Certificates
+
+A certification system specified conventions on who is allowed to issue certificates, the rules over their issuance (e.g. time limits and revocation) as well as their format and semantics.
+
+For example, the certificate transparency protocol for TLS certificates helps protect against compromised Certificate Authorities.<!-- .element: class="fragment" data-fragment-index="0" -->
+
+Notes:
+
+Certificate transparency: [explanation](https://certificate.transparency.dev/howctworks/) and [dashboard](https://ct.cloudflare.com/)
+
+- Maybe mention PGP web-of-trust style schemes
+
+---
+
+### Certificates in Web3
+
+We are building systems that do not have a centralized "Certificate Authority".<br/>
+But we can still use certificates to transfer some power from one key to another.
+
+Notes:
+
+Potential example to give verbally:
+
+- Session keys are a set of keys that generally run in online infrastructure.
+  An account, whose keys are protected, can sign a transaction to certify all the keys in the set.
+- Session keys are used to sign operational messages, but also in challenge-response type games to prove availability by signing a message.
+- Registrar.
+- Identity chains.
+
+---
+
+### Multi-Signatures
+
+We often want signatures that must be signed<br/>by multiple parties to become valid.
+
+<pba-flex center>
+
+- Require some threshold of members to<br/>agree to a message<!-- .element: class="fragment" data-fragment-index="0" -->
+- Protect against key loss<!-- .element: class="fragment" data-fragment-index="1" -->
+
+</pba-flex>
+
+---
+
+### Types of Multi-Signature
+
+<pba-flex center>
+
+- Trivial: Sending all individual signatures together.<!-- .element: class="fragment" data-fragment-index="0" -->
+- Cryptographically Aggregated.<!-- .element: class="fragment" data-fragment-index="1" -->
+- Cryptographically Threshold.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+### Trivial Multiple Signatures
+
+- We assume that there is some verifier, who can check that some threshold of individual keys have provided valid signatures.
+- This could be a trusted company or third party.<!-- .element: class="fragment" data-fragment-index="1" -->
+- For our purposes, "it's a blockchain."<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+### Trivial Multiple Signatures
+
+Trivial multiple signatures generally provide a good user experience, as no interaction is required from the participants.
+
+Notes:
+
+This good experience comes at the cost of using state and more user interactions with the system, but is generally low.
+
+Even in a web3 system, the verifier can be _distinct_ from the blockchain. 5 people can entrust a verifier with the identity of "all 5 signed this" associated to a verifier-owned private key.
+
+---
+
+### Cryptographic Multi-Sigs
+
+We want a succinct way to demonstrate that everyone from some set of parties have signed a message. This could be achieved purely on the signer side (without support from the verifier).
+
+<pba-flex center>
+
+_Example: "The five key holders have signed this message."_
+
+---
+
+### Key Generation for Multi-Sigs
+
+In cryptographic multi-signatures,<br/>signatures from individual public keys are aggregated.
+.
+
+Each participant can choose their own key to use for the multi-signature.<!-- .element: class="fragment" data-fragment-index="0" -->
+
+Notes:
+
+In some cases, a security requirement of these systems is that every participant demonstrates ownership of the public key submitted for the multi-signature, otherwise security can be compromised.
+
+---
+
+### Cryptographic Threshold Multi-Sigs
+
+- Makes more compact signatures compatible with legacy systems.
+- The public key is associated with a "threshold" number of signing parties.<!-- .element: class="fragment" data-fragment-index="0" -->
+- Not all parties are needed to take part in the signing process to create a valid signature.<!-- .element: class="fragment" data-fragment-index="1" -->
+- This requires MPC protocols and may need multiple rounds of interaction to generate the final signature.<!-- .element: class="fragment" data-fragment-index="2" -->
+- They may be vulnerable to DoS from a malfunctioning (or malicious) key-holder.<!-- .element: class="fragment" data-fragment-index="3" -->
+
+<pba-flex center>
+
+Example: "5 of 7 key holders have signed this message.".<!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+These require multi-party computation (MPC) protocols, which add some complexity for the signing users.
+
+---
+
+### Key Generation - Threshold
+
+- Threshold multi-signature schemes require that all signers run a distributed key generation (DKG) protocol that constructs key "shares".
+  <img style="height: 500px" src="./img/11-simplex_graph.png" /><!-- .element: class="fragment" data-fragment-index="0" -->
+- The secret encodes the threshold behavior, and signing demands some threshold of signature "fragments".<!-- .element: class="fragment" data-fragment-index="1" -->
+- This DKG protocol breaks other useful things, like hard key derivation.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+DKG requires MPC which adds a lot of communication overhead.
+
+---
+
+### Schnorr Multi-Sigs
+
+Schnorr signatures are primarily used for threshold multi-sig.
+
+- Fit legacy systems nicely, and can reduce fees on blockchains.<!-- .element: class="fragment" data-fragment-index="0" -->
+- Reduce verifier costs in bandwidth & CPU time, so great for certificates.<!-- .element: class="fragment" data-fragment-index="1" -->
+- Could support soft key derivations.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+### Schnorr Multi-Sigs - Downside
+
+- However, automation becomes tricky.
+- We need agreement upon the final signer list and two random nonce contributions from each prospective signer, before constructing the signature fragments.<!-- .element: class="fragment" data-fragment-index="0" -->
+
+---
+
+### BLS Signatures
+
+- BLS signatures are especially useful for aggregated multi-signatures (but can be used for threshold as well).<!-- .element: class="fragment" data-fragment-index="0" -->
+- Signatures can be aggregated without advance agreement upon the signer list.<!-- .element: class="fragment" data-fragment-index="1" -->
+- This simplifies automation and makes them useful in consensus.<!-- .element: class="fragment" data-fragment-index="2" -->
+- Verifying individual signatures is slow, but verifying aggregated ones is relatively fast.<!-- .element: class="fragment" data-fragment-index="3" -->
+- (Coming to Substrate soonish.)<!-- .element: class="fragment" data-fragment-index="4" -->
+
+---
+
+### BLS Signatures
+
+Allows multiple signatures generated under multiple public keys for multiple messages to be aggregated into a single signature.
+
+<pba-flex center>
+
+- Uses heavier pairing friendly elliptic curves than ECDSA/Schnorr.<!-- .element: class="fragment" data-fragment-index="0" -->
+- Very popular for consensus.<!-- .element: class="fragment" data-fragment-index="1" -->
+
+<pba-flex>
+
+---
+
+### BLS Signatures - Downside
+
+- DKGs remain tricky (for threshold).<!-- .element: class="fragment" data-fragment-index="0" -->
+- Soft key derivations are typically insecure for BLS.<!-- .element: class="fragment" data-fragment-index="1" -->
+- Verifiers are significantly slower than Schnorr, due to using pairings, for a single signature.<!-- .element: class="fragment" data-fragment-index="2" -->
+- But for hundreds or thousands of signatures on the same message, aggregated signature verification can be much faster than Schnorr.<!-- .element: class="fragment" data-fragment-index="3" -->
+
+---
+
+### Schnorr and BLS Summary
+
+Schnorr & BLS multi-signatures avoid complicating verifier logic,<br/>but introduce user experience costs such as:
+
+- DKG protocols<!-- .element: class="fragment" data-fragment-index="0" -->
+- Reduced key derivation ability<!-- .element: class="fragment" data-fragment-index="1" -->
+- Verification speed<!-- .element: class="fragment" data-fragment-index="2" -->
+- Proof of possession verification.<!-- .element: class="fragment" data-fragment-index="3" -->
+
+---
+
+### Ring Signatures
+
+- Ring signatures prove the signer lies within some "anonymity set" of signing keys, but hide which key actually signed.
+  <img style="height: 300px" src="./img/Ring-signature.png" /><!-- .element: class="fragment" data-fragment-index="1" -->
+- Ring signatures come in many sizes, with many ways of presenting their anonymity sets.<!-- .element: class="fragment" data-fragment-index="2" -->
+- Anonymous blockchain transactions typically employ ring signatures (Monero, ZCash).<!-- .element: class="fragment" data-fragment-index="3" -->
+
+Notes:
+
+- ZCash uses a ring signature based upon Groth16 zkSNARKs which makes the entire chain history be the anonymity set.
+- Monero uses ring signatures with smaller signer sets.
+- Ring signatures trade some _non-repudation_ for _privacy_.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/1-Cryptography/7-Hash_Based_Data_Structures-slides.md b/content/1-Cryptography/7-Hash_Based_Data_Structures-slides.md
new file mode 100644
index 00000000..9d53ecc8
--- /dev/null
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@@ -0,0 +1,268 @@
+---
+title: Hash Based Data Structures
+description: Hash functions in Substrate
+duration: 1 hour
+---
+
+# Cryptography Day III
+
+<pba-flex center>
+
+- Quiz<!-- .element: class="fragment" data-fragment-index="0" -->
+- Hash Based Data Structures<!-- .element: class="fragment" data-fragment-index="1" -->
+- Exotic Primitives<!-- .element: class="fragment" data-fragment-index="2" -->
+- Merkle Tree Activity<!-- .element: class="fragment" data-fragment-index="3" -->
+- Zero-Knowledge Proofs Intro<!-- .element: class="fragment" data-fragment-index="4" -->
+- VRF Poker Activity<!-- .element: class="fragment" data-fragment-index="5" -->
+
+</pba-flex>
+
+---
+
+# Hash Based Data Structures
+
+---
+
+## Comparison to<br />Pointer Based Data Structures
+
+- A hash references the<!-- .element: class="fragment" data-fragment-index="0" --> **content**<!-- .element: class="fragment" data-fragment-index="0" --> of some data;<!-- .element: class="fragment" data-fragment-index="0" -->
+- A pointer tells you where to find it;<!-- .element: class="fragment" data-fragment-index="1" -->
+- We can not have cycles of hashes.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+## Hash Chains
+
+<img style="width: 800px" src="./img/Hash-Chains.png" />
+
+A hash chain is a linked list using hashes to connect nodes.
+
+Notes:
+
+Each block has the hash of the previous one.
+
+---
+
+## Merkle Trees
+
+<img style="width: 800px" src="./img/Merkle-tree-all-purple.png" />
+
+A binary Merkle tree is a binary tree using hashes to connect nodes.
+
+---
+
+## Proofs
+
+<ul>
+<li class="fragment">The root or head hash is a commitment to the entire data structure.</li>
+<li class="fragment">Generate a proof by expanding some but not all hashes.</li>
+<li class="fragment"><i>Crucial for the trustless nature of decentralised cryptographic data systems!</i></li>
+</ul>
+
+---
+
+## Proofs: Merkle Copaths
+
+<img style="width: 800px" src="./img/Merkle-Copaths.png" />
+
+Notes:
+
+Given the children of a node, we can compute a node
+Given the purple nodes and the white leaf, we can compute the white nodes bottom to top.
+If we compute the correct root, this proves that the leaf was in the tree
+
+---
+
+## Security
+
+- Collision resistance: we reasonably assume only one preimage for each hash,<!-- .element: class="fragment" data-fragment-index="0" -->
+- therefore making the data structure's linkage persistent and enduring<!-- .element: class="fragment" data-fragment-index="1" -->
+- (until the cryptography becomes compromised 😥).<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+Explain what could happen when this fails.
+
+---
+
+## Proof Sizes
+
+Proof of a leaf has size $O(\log n)$<br />and so do proofs of updates of a leaf
+
+---
+
+## Key-Value Databases and Tries
+
+---
+
+## Key-value database
+
+The data structure stores a map `key -> value`.<br />
+We should be able to:
+
+<pba-flex center>
+
+- `put(key, value)`<!-- .element: class="fragment" data-fragment-index="1" -->
+- `get(key)`<!-- .element: class="fragment" data-fragment-index="2" -->
+- `delete(key)`<!-- .element: class="fragment" data-fragment-index="3" -->
+
+</pba-flex>
+
+---
+
+## Provability in key-value databases
+
+We should also be able to perform the following operations for a provable key-value database:
+
+1. For any key, if <!-- .element: class="fragment" data-fragment-index="1" --> `<key,value>`<!-- .element: class="fragment" data-fragment-index="1" --> is in the database, we can prove it.<!-- .element: class="fragment" data-fragment-index="1" -->
+1. If no value is associated to a key, we need to be able to prove that as well.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+## Types of Data Structures
+
+- _**Trees**_ are rooted, directed acyclic graphs where each child has only one parent.
+- _**Merkle Trees**_ are _trees_ which use hashes as links.
+- _**Tries**_ are a particular class of _trees_ where:
+  - Given a particular piece of data, it will always be on a particular path.
+- _**Radix Tries**_ are a particular class of a trie where:
+  - The location of a value is determined the path constructed one chunk of digits (represented in the chosen radix) at a time.
+  - are optimized to ensure lonely node-paths are consolidated into a single node.
+- _**Patricia Tries**_ are _radix-2 tries_
+
+Notes:
+
+Just a selection we'll cover in this course.
+
+---
+
+## Trie
+
+_Words:_ to, tea, ted, ten, inn, A.
+
+<img style="width: 800px" src="./img/Trie.png" />
+
+Each node splits on the next digit in base $r$
+
+Notes:
+
+In this image, $r$ is 52 (26 lowercase + 26 uppercase).
+
+---
+
+## Radix Trie
+
+_Words:_ to, tea, ted, ten, inn, A.
+
+<img style="width: 700px" src="./img/Patricia-Trie.png" />
+
+If only one option for a sequence we merge them.
+
+<!-- TODO maybe some code stuff with extension nodes etc. -->
+
+---
+
+## Radix Trie Structures
+
+```rust
+pub enum Node {
+  Leaf {
+    partial_path: Slice<RADIX>,
+    value: Value
+  },
+  Branch {
+    partial_path: Slice<RADIX>,
+    children: [Option<Hash>; RADIX],
+    value: Option<Value>,
+  },
+}
+```
+
+Notes:
+
+The old implementation actually made use of dedicated "extension" nodes instead of branch nodes that hold a partial path. There's a good explanation of them [here](https://ethereum.stackexchange.com/questions/39915/ethereum-merkle-patricia-trie-extension-node).
+
+Additionally, if the size of a value is particularly large, it is replaced with the hash of its value.
+
+<!-- TODO: Add a nice illustration similar to Shawn's dev-trie-backend-walk here. -->
+
+---
+
+## Hash Trie
+
+- Inserting arbitrary (or worse, user-determined) keys into the Radix/Patricia tree can lead to highly unbalanced branches, enlarging proof-sizes and lookup times.<!-- .element: class="fragment" data-fragment-index="1" -->
+- Solution: pre-hash the data before inserting it to make keys random.<!-- .element: class="fragment" data-fragment-index="2" -->
+- Resistance against partial collision is important.<!-- .element: class="fragment" data-fragment-index="3" -->
+- Could be a Merkle trie or regular.<!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+- Q: Why would pre-hashing the data make the keys random? A: Because each piece of data should be unique! it is a good selection scheme.
+  Talk about how to determine keys in bitcoin state tree
+
+---
+
+## Computational and Storage <br />Trade-offs
+
+What radix $r$ is best?
+
+- Proof size of a leaf is $r \log_r n$
+  - $r=2$ gives the smallest proof for one leaf
+
+...but:
+
+- Higher branching at high levels of the tree can give smaller batch proofs. <!-- .element: class="fragment" data-fragment-index="0" -->
+- For storage, it is best to read consecutive data so high $r$ is better. <!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+Q: Why would higher branching at high levels of the tree give smaller batch proofs?
+A: Less nodes are needed in order to prove various parts of the tree
+
+---
+
+## Merkle Mountain Ranges
+
+- Efficient proofs and updates for a hash chain
+- Append only data structure
+- Lookup elements by number
+
+---
+
+## Merkle Mountain Ranges
+
+<img style="width: 800px" src="./img/U-MMR-13.png" />
+
+Notes:
+
+we have several Merkle trees of sizes that are powers of two.
+The trees that are here correspond to the binary digits of 13 that are 1.
+
+---
+
+## Merkle Mountain Ranges
+
+<img style="width: 800px" src="./img/U-MMR-14.png" />
+
+---
+
+## Merkle Mountain Ranges
+
+<img style="width: 800px" src="./img/MMR-13.png" />
+
+Notes:
+
+- Not as balanced as a binary tree but close
+- Can update the peak nodes alone on-chain
+
+Applications:
+
+- Stateless Client can very efficiently prove the end parts of the tree allowing for a client which doesnt need to store the whole blockchain just a few latest nodes.
+- Look at the structure if each leaf is a block then if previous stuff is pruned that is fine because you still carry around the hash or peak of a selection of blocks
+- Lightclients, efficiently see whether a transaction is included in a block without needing the entire the entire blockchain history
+  We use this in polkadot for our bridging!!
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/1-Cryptography/8-Exotic_Primitives-slides.md b/content/1-Cryptography/8-Exotic_Primitives-slides.md
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+---
+title: Exotic Primitives
+description: More cutting edge cryptography used in blockchain
+duration: 1 hour
+---
+
+# Exotic Primitives
+
+---
+
+# Outline
+
+<pba-flex center>
+
+1. [Verifiable Random Functions (VRFs)](#verifiable-random-functionsvrfs)
+1. [Erasure coding](#erasure-coding)
+1. [Shamir Secret Sharing](#shamir-secret-sharing)
+1. [Proxy Re-Encryption](#proxy-reencryption)
+
+</pba-flex>
+
+---
+
+## Verifiable Random Functions<br/>(VRFs)
+
+<widget-center>
+
+- Used to obtain <ins>private randomness</ins>, that is <ins>publicly verifiable</ins>
+
+- A variation on a signature scheme:
+  - still have private/public key pairs, input as message
+  - in addition to signature, we get an output
+
+---
+
+## VRF Interface
+
+- `eval(sk,input) -> output`
+
+- `sign(sk, input) -> signature`
+
+- `verify(pk, input, signature) -> option output`
+
+Notes:
+
+The output of verification being an option represents the possibility of an invalid signature
+
+---
+
+## VRF Output properties
+
+- Output is a deterministic function of _key_ and _input_
+  - i.e. eval should be deterministic
+- It should be pseudo-random
+- But until the VRF proof is revealed, only the holder<br/>of the secret key knows the output
+- Revealing output does not leak secret key
+
+---
+
+## VRF Usage
+
+- Choose input after key, then the key holder cannot influence the output
+- The output then is effectively a random number known only to the key holder
+- But they can later reveal it, by publishing the VRF proof (signature)
+
+Notes:
+
+The signature proves that this is the output associated to their input and public key.
+
+---
+
+## VRF Example
+
+- Playing a card game in a distributed and trustless way
+- For player A to draw a card, the players agree on a new random number x
+- A's card is determined by `eval(sk_A,x) mod 52`
+- To play the card, A publishes the VRF proof (signature)
+
+---
+
+## VRF Example
+
+_Lottery_
+
+- Lottery organizer generate $pk$,$sk$ for VRF;
+- Each participants choose their own tickets $t_i$;
+
+<img style="width: 500px;" src="./img/vrf1.png" />
+
+---
+
+## VRF Example
+
+_Lottery_
+
+- Lottery organizer computes `eval(sk,$t_i$)-> $y_i$` for each participants;
+- $y_i$ determines wining or not;
+- `sign(sk, $t_i$) -> $\sigma_i$` published for verification.
+  <img style="width: 500px;" src="./img/vrf1.png" />
+
+---
+
+## Recall Signature Interface
+
+- `sign(sk, msg) -> signature;`
+
+- `verify(pk, msg, signature) -> bool;`
+
+---
+
+## BLS-based VRF
+
+- `sign(sk,input)`: run `BLS.sign(sk, input)->signature`, return `signature`
+
+- `eval(sk,input)`： return `Hash(signature)`
+
+- `verify(pk,input,signature)`: `BLS.verify(pk, input, signature)?=1`, if holds, output `Hash(signature)`
+
+---
+
+## VRF Extensions
+
+- Threshold VRFs / Common coin
+
+  - Generate the same random number if $t$ out of $n$ people participate
+
+- RingVRFs
+
+  - The VRF output could be from any one of a group of public keys.
+
+Notes:
+
+Common coins were used in consensus before blockchains were a thing.
+Dfinity based their consensus on this.
+But this needs a DKG, and it's unclear if a decentralized protocol can do those easily.
+A participant in a RingVRF could still only reveal _one_ random number.
+
+---
+
+## Threshold VRFs
+
+- Also called Distributed VRFs;
+- Each of the $n$ users get their public/secret key $(pk_i,sk_i)$;
+- $t$ participants generate `output_i`, `signature_i` using their key on the same `input`;
+- Combine $t$ `output_i`, `signature_i` to get `output`, `signature`.
+
+---
+
+## Ring Signature and Ring VRFs
+
+- Ring Signature: Sign on behalf of a group people without revealing the true identity of the signer;
+
+- Ring VRFs: generate `output` and `signature` on behalf of a group of people without revealing the true identity of the signer.
+
+<img style="height: 300px" src="./img/ring.png" />
+
+---
+
+## Erasure Coding
+
+_Magical data expansion_
+
+- A type of Error Correction Code </br>Detect and correct errors occur in data transmission without the need for retransmission
+
+- Turn data into pieces (with some redundancy) so it can be reconstructed even if some pieces are missing
+
+- A message of $k$ symbols is turned into a coded message of $n$ symbols and can be recovered from any $k$ of these $n$ symbols
+
+---
+
+## Erasure Coding Intuition
+
+Erasure coding relies on both parties sharing an understanding of what possible messages are valid. This lets mistakes be noticed and corrected.
+
+Imagine you are receiving a message, and you know ahead of time that the only two possible messages you would receive are `file` and `ruin`.
+
+Notes:
+
+This concept of a subset of messages being valid is super common in real life, and occurs all over the place.
+At a restaurant, when they ask you if you want soup or salad, even if you mumble they will probably understand you.
+
+---v
+
+## Erasure Coding Intuition
+
+How would you classify each of the following words?
+
+<span style="color: red;">file</span> pile pale tale tall rule tail rail rain <span style="color: blue;">ruin</span>
+
+---v
+
+## Erasure Coding Intuition
+
+How would you classify each of the following words?
+
+<span style="color: red;">file pile pale tale tall</span> <span style="color: purple;">rule</span> <span style="color: blue;"> tail rail rain ruin</span>
+
+You can classify them based on how close they are to a valid input. This also means we can find the errors in these messages.
+
+Notes:
+
+There is no perfect way to separate these, but one very reasonable one is to do it based on the edit distance of the received word with any valid messsage you could receive.
+
+---v
+
+## Erasure Coding Intuition
+
+Now, you are receiving messages that could be `msg1` or `msg2`. Can you apply the same technique? Is it as easy to separate received messages?
+
+What if you receive `msg3`?
+
+Notes:
+
+If the messages are not far apart, it is impossible to distinguish in many cases. There is not enough "distance" between the two possibilities.
+
+---v
+
+## Erasure Coding Intuition
+
+With erasure coding, we extend each message magically so they are different enough. The sender and receiver know the same encoding procedure. These extensions will be very different, even if the messages are similar.
+
+`msg1`<span style="color: red;"> `jdf`</span> and `msg2`<span style="color: red;"> `ajk`</span>
+
+Notes:
+
+It is actually always possible to make the extra magic only appended to the message. This is called a _systematic encoding_.
+
+For those curious about how the "magic" works:
+
+The magic here is polynomials, and the fact that a polynomial of degree $n$ is completely determined by $n+1$ points. There are many good explanations online.
+
+---
+
+## Erasure Coding
+
+<img style="width: 1000px;" src="./img/erasure-code.svg" />
+
+---
+
+## Example for 1 Bit Erasuring
+
+Parity Check: $n=k+1$
+
+- Codeword length $(x_1,\cdots,x_k)$: $k$
+- Add a sum of the codeword
+
+<img style="width: 1000px;" src="./img/ECC1.png" />
+
+- What if one element gets erasured during transmission?
+
+---
+
+## Erasure Coding Classical use
+
+- Used for noisy channels
+- If a few bits of the coded data are randomly flipped,<br/> we can still recover the original data
+- Typically $n$ is not much bigger than $k$
+
+---
+
+## Use in Decentralized Systems
+
+<img style="width: 600px;" src="./img/ECC2.png" />
+
+---
+
+## Use in Decentralized Systems
+
+- We have data we want to keep publicly available
+
+  - but not have everyone store
+  - but we don't trust everyone who is storing pieces
+
+---
+
+## Shamir Secret Sharing
+
+_Redundancy for your secrets_
+
+- Turn data (typically a secret) into pieces so it can be reconstructed from some subset of the pieces.
+
+- A secret is turned into $n$ shares, and be recovered by any $k$ of the shares. $k-1$ shares together reveals nothing about the secret.
+
+---
+
+## Shamir Secret Sharing
+
+<img style="height: 600px" src="./img/shamir-secret-sharing.png" />
+
+Notes:
+
+Image credit here: https://medium.com/clavestone/bitcoin-multisig-vs-shamirs-secret-sharing-scheme-ea83a888f033
+
+---
+
+## How to Share Secrets?
+
+- A polynomial of degree $t$ is completely determined by $t+1$ points.
+- We can reconstruct the $t$ polynomial from any of its $t+1$ points (use Lagrange interpolation).
+- With point less than $t+1$, the polynomial cannot be uncovered.
+- $y=x^3+4x^2+2$
+  <img style="width:500px " src="./img/secshare1.png" />
+
+---
+
+## How to Share Secrets?
+
+- Assume we want to share a secret value $a$ among $n$ people
+- We expect that with any $k$ secret shares we are able to reconstruct $a$;
+
+---
+
+## Share Secret Value $a$
+
+- Construct polynomial $f(X)=a_0+a_1X+a_2X^2+\cdots+a_{k-1}X^{k-1}$ with degree $k-1$;
+
+- **$a_0=a$**;
+- $a_1$,$\cdots$, $a_{k-1}$ are all randomly picked;
+
+- The $n$ secret shares are $f(1)$, $f(2)$,$\cdots$, $f(n)$;
+
+- With any $k$ of the $n$ secret shares, we are able to recover $f(x)$.
+
+---
+
+## Example:$a=12, n=5, k=4$
+
+- Construct a polynomial $f(x)=12-13x-7x^2+2x^3$
+
+<img style="width:600px " src="./img/secshare2.png" />
+
+---
+
+## Example:$a=12, n=5, k=4$
+
+- Evaluate on $f(1)$, $f(2)$, $f(3)$, $f(4)$, $f(5)$
+
+  <img style="width:600px " src="./img/secshare3.png" />
+
+---
+
+## Distributed Private Key Storage
+
+- The management and protection of private keys is important;
+
+- There are wallet introduced Shamir secret sharing to help share private key into multiple pieces;
+
+- Shares are stored in different locations.
+
+---
+
+## Pros and Cons
+
+- Can reconstruct a secret if you lose it.
+- So can other people who collect enough shares.
+
+---
+
+## Recall Asymmetric (Public Key) Encryption
+
+- `fn generate_key(r) -> sk;` <br/> Generate a `sk` (secret key) from some input `r`.
+- `fn public_key(sk) -> pk;` <br/> Generate a `pk` (public key) from the private key `sk`.
+- `fn encrypt(pk, msg) -> ciphertext;` <br/> Takes the public key and a message; returns the ciphertext.
+- `fn decrypt(sk, ciphertext) -> msg;` <br/> For the inputs `sk` and a ciphertext; returns the original message.
+
+---
+
+## Proxy Reencryption Intuition
+
+<img rounded style="height: 400px" src="./img/proxy1.png" />
+
+- Directly give Email Server $sk_A$?
+- $A$ encrypt the email using $pk_B$ by itself and send the ciphertext to server?
+
+---
+
+## Proxy Reencryption
+
+- A varient of asymmetric encrytion schemes
+- Generate keys to allow a third party to transform encrypted data so someone else can read it
+- Keep the data secret to the third party
+
+---
+
+## Proxy Reencryption
+
+<img rounded style="height: 600px" src="./img/proxy-reencryption.png" />
+
+Notes:
+
+[img source](https://scrapbox.io/layerx/Proxy_Re-Encryption%28PRE%29%E3%81%A8NuCypher)
+
+---
+
+## Proxy Reencryption API
+
+- `fn encrypt(pk, msg) -> ciphertext;` <br/> Takes your public key and a message; returns ciphertext.
+- `fn decrypt(sk, ciphertext) -> msg;` <br/> Takes your private key and a ciphertext; returns the message.
+- `fn get_reencryption_key(sk, pk) -> rk;` <br/> Takes your private key, and the recipient's public key; returns a reencryption key.
+- `fn reencrypt(rk, old_ciphertext) -> new_ciphertext;` <br/> Take a reencryption key, and transform ciphertext to be decrypted by new party.
+
+---
+
+## Requirements for Proxy Reencryption
+
+- Bob (delegatee) should be able to correctly decrypt new ciphertext with his $pk$;
+
+- With $rk$, Proxy can not get Alice's (delegator) secret key.
+
+- The ciphertext is secure even $rk$ leaked;
+
+---
+
+## Summary
+
+- VRF: Private randomness that is later publicly verifiable
+- Erasure Coding: Making data robust against losses with redundancy
+- Shamir Secret Sharing: Redundancy for your secrets.
+- Proxy Re-encryption: Allow access to your data _with cryptography_.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/1-Cryptography/9-ZK_Proofs-slides.md b/content/1-Cryptography/9-ZK_Proofs-slides.md
new file mode 100644
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+---
+title: ZK proofs
+description: Introduction to zero-knowledge proofs and zk-SNARKS
+duration: 2 hour
+---
+
+# Cryptography Day III
+
+<pba-flex center>
+
+- Quiz
+- Hash Based Data Structures
+- Exotic Primitives
+- Merkle Tree Activity
+- Zero-Knowledge Proofs (Part I)<!-- .element: class="fragment" data-fragment-index="3" -->
+- Crypto in Context <!-- .element: class="fragment" data-fragment-index="4" -->
+- VRF Poker Activity<!-- .element: class="fragment" data-fragment-index="5" -->
+
+</pba-flex>
+
+---
+
+# ZK Proofs
+
+---
+
+# Outline
+
+<pba-flex center>
+
+1. [ZK Proofs overview](#zk-proofs)<!-- .element: class="fragment" data-fragment-index="0" -->
+2. [Examples](#simple-zk-example)<!-- .element: class="fragment" data-fragment-index="1" -->
+3. [zk-SNARKs](#zk-snarks)<!-- .element: class="fragment" data-fragment-index="2" -->
+4. [Applications of zk-SNARKs](#zk-application)<!-- .element: class="fragment" data-fragment-index="3" -->
+
+</pba-flex>
+
+---
+
+## ZK Proofs
+
+How do we do private operations on a public blockchain<br />and have everyone know that they were done correctly?
+
+Notes:
+
+(we are working on substrate support for these and will use them for protocols)
+
+---
+
+## What is a ZK Proof?
+
+- A prover wants to convince a verifier that something is true without revealing why it is true.
+
+- They are mostly interactive protocols, but mostly we'll turn them non-interactive and deal with their non-interactive variety.
+
+Notes:
+
+- Interactive means multiple back and forthes between parties. It requires that the parties to be online at the same time.
+- Non-interactive means one party post their contribution and the other party could use the data at the time of their convinience.
+  This does not require the praties to be online at the same time.
+
+---
+
+## What can we show?
+
+- NP relation: `function(statement, witness) -> bool`
+
+- Prover knows a witness for a statement:
+
+  - They want to show that they know it (_a proof of knowledge_)
+
+  - ... Without revealing anything about the witness (_ZK_)
+
+Notes:
+NP problems are problems that might be hard to solve but are relatively easy to verify. Easy as in "polynomial time".
+
+---
+
+## ZK Proof Interface
+
+- NP relation: `function(statement, witness) -> bool`
+
+- `prove(statement, witness) -> proof`
+
+- `verify(statement, proof) -> bool`
+
+---
+
+## Examples
+
+---
+
+## ZK Proof Example
+
+_Example:_ Schnorr signatures are ZK Proofs
+
+- $(s, e)$ such that $s = (\textrm{Random blinding factor }r) - \\ \textrm{Private Key} \times e$<!-- .element: class="fragment" data-fragment-index="0" -->
+- They show that the prover knows the private key such that $\textrm{private key} \times G = \textrm{Public Key}$ without revealing anything about it.<!-- .element: class="fragment" data-fragment-index="1" -->
+- The statement is the public key and the witness the private key.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+## The ZK Proof Example we study in this module
+
+_Example:_ Prover knows a non-trivial factorization of N
+
+- Prover wants to prove that they know $N = r \times s$ without revealing $r$ or $s$.<!-- .element: class="fragment" data-fragment-index="0" -->
+- The Prover should convince us they know the two non-trivial integer $r$ and $s$ that is $r,s \neq 1$ such that:<!-- .element: class="fragment" data-fragment-index="1" -->
+
+$r\times s = N$ <!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Without revealing any other information about $r$ or $s$.<!-- .element: class="fragment" data-fragment-index="2" -->
+- The statement is $N$ and the witnesses are $r$ and $s$.<!-- .element: class="fragment" data-fragment-index="3" -->
+
+---
+
+## ZK Proof properties
+
+- Completeness: If the claim is true, then it _must_ pass `verify(statement, proof) == true`
+- Statistical Knowledge Soundness: If the prover does not know the witness then `verify(statement, proof) == false` with high probability
+- Zero Knowledge: the proof reveals nothing about the witness that was not revealed by the statement itself<!-- .element: class="fragment" data-fragment-index="0" -->
+- The common way of implementing zero knowledge protocol is by means of zk-SNARK<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+- We prove Zero knowldege by showing a party without any knowledge of the witness, could fool an external party who was not been part of the interaction that they interacted with the prover and got a valid proof form the prover.
+
+---
+
+## zk-SNARKs
+
+---
+
+## zk-SNARK
+
+**Z**ero-**K**nowledge **S**uccinct **N**on-interactive **Ar**gument of **K**nowledge
+
+- **Zero knowledge** - the proof reveals nothing about the witness that was not revealed by the statement itself.
+- **Succinct** - the proof is small
+- **Non-interactive** - Does not require live interaction between the prover and verifier.
+- **Proof of knowledge** - if you can compute correct proofs of a statement, you should be able to compute a witness for it.
+
+---
+
+## What can we show?
+
+- NP relation: `function(statement, witness) -> bool`
+
+  - They want to show that they know it (_a proof of knowledge_)
+
+  - ... Without revealing anything about the witness (_ZK_)
+
+- With a small proof even if the witness is large (_succinctness_)
+
+---
+
+## What can we show?
+
+- There are many SNARK schemes to produce succinct ZK proofs of knowledge (_ZK-SNARKs_) for every NP relation. We concentrate on PLONK in this course.
+
+---
+
+## How do (polynomial-based) SNARKs prove of knowledge
+
+- Translate our problem into an arithmetic circuit which should output zero if we know the solution.<!-- .element: class="fragment" data-fragment-index="0" -->
+- Make a polynomials which have roots in specific values using the solutions.<!-- .element: class="fragment" data-fragment-index="1" -->
+- Prove that we know the polynomial by evaluating it at random values and provig that we have evaluated it correctly.<!-- .element: class="fragment" data-fragment-index="2" -->
+- We talk about each step in detail in next lecture<!-- .element: class="fragment" data-fragment-index="3" -->
+- Most popular SNARKs uses polynomials, other SNARKs could use other mathematical structures such as vectors, etc<!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+- We can not send the polynomial as a proof: 1. it is too big (so not succinct) 2. reveals the secret solution.
+
+---
+
+# SNARK = PIOP + commitment + Fiat-Shamir
+
+- PIOP => ARK
+- PIOP + Commitment => SARK
+- PIOP + Commitment + Fiat-Shamir => SNARK
+
+---
+
+# SARK → SNARK
+
+- Everytime the prover need the verifier to provide them with a random value... <!-- .element: class="fragment" data-fragment-index="1" -->
+- The prover apply a hash function to all it has already provided to the verifier. <!-- .element: class="fragment" data-fragment-index="2" -->
+- This way the prover is unable to cheat and control the value and break the systemc. <!-- .element: class="fragment" data-fragment-index="3" -->
+- This is know Fiat-Shamir Transform <!-- .element: class="fragment" data-fragment-index="4" -->
+
+---
+
+## Applications of zk-SNARKs
+
+---
+
+## ZK Proof Scaling
+
+- A small amount of data, a ZK proof, and execution time can be used to show properties of a much larger dataset which the verifier doesn't need to know.
+- "doesn't need/want to" know as opposed to "is not supposed to" know.<!-- .element: class="fragment" data-fragment-index="1" -->
+
+---
+
+## Scaling via ZK Proofs in Blockchain
+
+- Large amount of data - a blockchain
+- Verifier is e.g. an app on a mobile phone
+
+Notes:
+
+e.g. Mina do a blockchain with a constant size proof (of correctness of execution and consensus) using recursive SNARKs.
+
+---
+
+## Scaling via ZK Proofs in Blockchain
+
+- The verifier is a blockchain: very expensive data and computation costs.
+- Layer 2s using ZK rollups
+
+Notes:
+
+Of which Ethereum has many, ZKsync, ZKEVM etc.
+Polkadot already scales better!
+
+---
+
+## Privacy
+
+<pba-flex center>
+
+A user has private data, but we can show<br />publicly that this private data is correctly used.<br />
+An example would a private cryptocurrency:
+
+- Keep who pays who secret
+- Keep amounts secret, <br /> _But show they are positive!_
+
+</pba-flex>
+
+Notes:
+
+You can do some of keeping amounts secret without ZK-SNARKs, but the positive part is difficult.
+To do everything well, ZK-SNARKs are needed in e.g. ZCash and its many derivatives e.g. Manta.
+
+---
+
+## Practical Considerations
+
+- Very powerful primitive<!-- .element: class="fragment" data-fragment-index="0" -->
+- Useful for both scaling and privacy<!-- .element: class="fragment" data-fragment-index="1" -->
+- One can design many protocols with ZK Proofs that wouldn't otherwise be possible<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+## Downside
+
+- Slow prover time for general computation<!-- .element: class="fragment" data-fragment-index="1" -->
+- To be fast, need to hand optimize<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+Very weird computation model?
+Weird as in binary arithmetic is hard, condition is hard.
+taking square-root of an element mod p is easy.
+Non-deterministic arithmetic circuits
+
+---
+
+## Under the hood of zk-SNARKs
+
+- We are going to talk about the elementary math behind zk-SNARKs.<!-- .element: class="fragment" data-fragment-index="0" -->
+- The goal is to familiarize you with the magic behind the zk-SNARKs.<!-- .element: class="fragment" data-fragment-index="1" -->
+- But we are not aming at making you zk-Proof expert in one lecture.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+## Recall steps to SNARKify your problem
+
+- Turn the problem into an arithmetic circuit (describe it only with +, -, x). <!-- .element: class="fragment" data-fragment-index="0" -->
+- Make polynomials from the circuit and your secret solution.<!-- .element: class="fragment" data-fragment-index="1" -->
+- But we are not aming at making you zk-Proof expert in one lecture.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+## Making a SNARK out of the factorization problem
+
+- The trick is to transform our problem of proving the knowledge of factors (witnesses) into:<!-- .element: class="fragment" data-fragment-index="0" -->
+- A problem of knowledge of certain polynomials.<!-- .element: class="fragment" data-fragment-index="1" -->
+- $x^n + a_{n-1} x^{n-1} + \dots + a_1x + a_0$ <!-- .element: class="fragment" data-fragment-index="2" -->
+- Then verifier could ask me questions about those polynomials, and if the prover answers correctly,<!-- .element: class="fragment" data-fragment-index="3" -->
+- The verifier could be fairly confident that the prover knows that polynomial hence also the witness.<!-- .element: class="fragment" data-fragment-index="4" -->
+
+---
+
+## Making an SNARK for knowledge of factors problem
+
+- A routine way of to turning the problem into a polynomial is:
+
+1. To represents our problem into an arithmetic circuit.<!-- .element: class="fragment" data-fragment-index="1" -->
+2. Then there are algorithms such as PLONK for representing the circuit as few univariate polynomials.<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+- Mathematically circuit is a n-variate polynomials, with some of the variables are public and some are not.
+
+---
+
+## The conditions the prover's solution must satisfy
+
+- $r \times s = N$<!-- .element: class="fragment" data-fragment-index="0" -->
+- We also need to make sure that prover doesn't fool us with trivial factors.<!-- .element: class="fragment" data-fragment-index="1" -->
+- prevent them from using $r = 1$ or $s = 1$ only using polynomial equations.<!-- .element: class="fragment" data-fragment-index="2" -->
+- $r \neq 1$ is not a polynomial equation.<!-- .element: class="fragment" data-fragment-index="3" -->
+- So we ask them to invert $r - 1$ and $s-1$:<!-- .element: class="fragment" data-fragment-index="4" -->
+  - $(r-1)\times \frac{1}{r - 1} = 1$<!-- .element: class="fragment" data-fragment-index="5" -->
+  - $(s-1)\times \frac{1}{s - 1} = 1$<!-- .element: class="fragment" data-fragment-index="6" -->
+
+---
+
+## Overflow prevention
+
+- Our polynomials are all defined modulo some prime $p$<!-- .element: class="fragment" data-fragment-index="0" -->
+- We need to prevent the prover from fooling us with a factorization like<!-- .element: class="fragment" data-fragment-index="1" -->
+  $r \times s = N' = N + q\times p$ where $q \neq 0$.<!-- .element: class="fragment" data-fragment-index="2" -->
+- This happens if $r$ and $s$ are too big and $r \times s$ overflows over $p$<!-- .element: class="fragment" data-fragment-index="3" -->
+- We should make sure that $r < \sqrt{p}$ and $s < \sqrt{p}$ are small.<!-- .element: class="fragment" data-fragment-index="4" -->
+- We use binary decomposition instead.<!-- .element: class="fragment" data-fragment-index="5" -->
+- $r = r_{0} + 2r_{1} + 4r_{2}$ where<!-- .element: class="fragment" data-fragment-index="6" -->
+- We should only allow them to use 0 or 1 for $r_{i}$'s so they need to satisfy:<!-- .element: class="fragment" data-fragment-index="7" -->
+- $r_{i} \times (r_{i} - 1) = 0$<!-- .element: class="fragment" data-fragment-index="8" -->
+
+---
+
+## Factorization Circuit
+
+$r \times s = N$
+
+<img style="height: 500px; padding-left:100px" src="./img/factorization-circuit.png" />
+
+---
+
+## Prevent Factor 1 Circuit
+
+$(r-1)(\frac{1}{r - 1}) = 1$
+
+<img style="height: 500px; padding-left:100px" src="./img/inhibit-1-circuit.png" />
+
+---
+
+## Prevent Big Factors: Binary decompostion circuit
+
+$r = r_{0} + 2r_{1} + 4r_{2} \Rightarrow$
+
+$r_{01} = r_{0} + 2r_{1}$
+
+$r = r_{01} + 4r_{2}$
+
+<img style="height: 500px; padding-left:100px" src="./img/binary-decomposition-circuit.png" />
+
+---
+
+## Prevent Big Factors: only allow 0 or 1 in binary decomposition
+
+$r_{i} \times (r_{i} - 1) = 0$
+
+<img style="height: 500px; padding-left:100px" src="./img/enforce-0-or-1-circuit.png" />
+
+---
+
+## Writing our circuit in Circom
+
+Circom demo.
+
+---
+
+## Summary
+
+- We discussed the general idea of ZK-Proofs.
+- Their application for scalability and privacy.
+- We looked how a sample ZK Proof is generated.
+- We generate and verify the proof using modern ZK tools.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/1-Cryptography/README.md b/content/1-Cryptography/README.md
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+# Module 1: Cryptography
+
+> “Cryptography rearranges power: it configures who can do what, from what”
+>
+> Phillip Rogaway, [The Moral Character of Cryptographic Work](https://eprint.iacr.org/2015/1162.pdf)
+
+## Lessons Plan
+
+This module consists of a combination of lectures, activities, and sections of the accompanying exercises to to students at what time.
+As there is a large amount of variance in student experience around cryptography, we want to make sure that we have a variety of content for students of different experience levels.
+
+### Graded Assignment
+
+> **All graded assignments and solutions must remain private to the Academy staff, faculty, and enrolled students!**
+
+There is a private to the Academy graded exercise, in a _template repository_ titled `pba-cryptography--master` that should be introduced after the first lectures are complete.
+Instructors should \_create a per cohort, **private**, derived from the master copy, make it a template repo, and configure the cohort Github Classroom to use this new repo as an assignment.
+
+The '`px...` assignment problem' sections indicates that students are now capable of completing them with the content so far covered.
+They should be encouraged to start working on them as time allows _outside of class time!_
+They should not zone-out of class to complete this during class time, they should prioritize in-class activities and exercises over working on the assignment!
+
+## Schedule
+
+### Day 1 (0.5 day)
+
+#### Afternoon
+
+1. [1-Intro](1-Intro-slides.md)
+1. [2-Addresses](2-Addresses-slides.md)
+   - 🪄 [`subkey` demo](./materials/subkey-demo.md)
+1. 💻 [Many time pad](many-time-pad.md) activity
+
+Release:
+
+1. `p2_addresses` assignment problem
+
+### Day 2
+
+#### Morning
+
+1. Quiz 1
+1. [3-Hashes](3-Hashes-slides.md)
+   - 🪄 [hashing demo](./materials/hash-rust-repl-demo.md)
+1. [4-Encryption](4-Encryption-slides.md)
+
+#### Afternoon
+
+1. [5-Basic_Signatures](5-Basic_Signatures-slides.md)
+   - 🪄 [signature demo](./materials/signature-demo.ipynb)
+1. [6-Advanced_Signatures](6-Advanced_Signatures-slides.md)
+1. 💻 [AES Modes](./materials/aes-modes-activity/) activity
+
+Release:
+
+1. `p1_hashing` assignment problem.
+1. `p9_attacks::low_entropy_hash` assignment problem.
+1. `p3_encryption assignment` problem.
+1. `p8_aes_modes assignment` problem for advanced students.
+1. `p4_signing assignment` problem.
+
+### Day 3
+
+#### Morning
+
+1. Quiz 2.
+1. [7-Hash_Based_Data_Structures-slides](./7-Hash_Based_Data_Structures-slides.md)
+1. [8-Exotic_Primitives](8-Exotic_Primitives-slides.md)
+1. 💻 [Merkle Tree](./materials/merkle-tree-activity/) activity
+
+#### Afternoon
+
+1. [9-ZK Proofs](9-ZK_Proofs-slides.md)
+1. 💻 [VRF poker](./materials/vrf_card_activity.rs)
+
+Release:
+
+1. `p6_merkle assignment` problem.
+1. `p5_data_integrity_and_recovery` assignment problem.
+1. `p7_exotics` assignment problem if it exists.
+
+### Day 4 (0.5 day)
+
+#### Morning
+
+1. Quiz 3
+1. [10-Advanced ZK proofs](10-Advanced_ZK_proofs-slides.md)
+1. [11-Cryptography_In_Context](11-Cryptography_In_Context-slides.md)
+1. ZKP activity.
+
+Release:
+
+1. `p9_attacks::timing_attacks` assignment problem.
+1. `p10_zkp assignment.`
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diff --git a/content/cryptography/in-context/img/xkcd-physical-security.png b/content/1-Cryptography/img/xkcd-physical-security.png
similarity index 100%
rename from content/cryptography/in-context/img/xkcd-physical-security.png
rename to content/1-Cryptography/img/xkcd-physical-security.png
diff --git a/content/1-Cryptography/img/xx-hash-benchmarks.png b/content/1-Cryptography/img/xx-hash-benchmarks.png
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diff --git a/content/1-Cryptography/index.md b/content/1-Cryptography/index.md
new file mode 100644
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--- /dev/null
+++ b/content/1-Cryptography/index.md
@@ -0,0 +1,7 @@
+# Cryptography
+
+> “Cryptography rearranges power: it configures who can do what, from what”
+>
+> Phillip Rogaway, [The Moral Character of Cryptographic Work](https://eprint.iacr.org/2015/1162.pdf)
+
+_Applied_ cryptography concepts and introduction to many common tools of the trade for web3 builders.
diff --git a/content/1-Cryptography/materials/Exotic_Primitives_VRF_Activity.md b/content/1-Cryptography/materials/Exotic_Primitives_VRF_Activity.md
new file mode 100644
index 00000000..08462415
--- /dev/null
+++ b/content/1-Cryptography/materials/Exotic_Primitives_VRF_Activity.md
@@ -0,0 +1,44 @@
+# Activity: Infinite deck poker using VRFs
+
+As we learnt in class, VRFs are a way of providing private randomness that can later be publicly revealed.
+
+A card game also has randomness, for instance, drawing a random card, which can be kept a secret until the card is played.
+
+We can use a VRF output mod 52 to determine a card.
+
+## Challenge
+
+Your task is to create a poker game or a simplification of one that uses VRFs to determine a players' card.
+
+### Possible simplifications
+
+Card-less poker - There are no hands.
+The player with the highest VRF revealed at the end should win the game but with the usual poker bidding rules.
+
+Or we can simplify bidding etc.
+
+## Guidelines
+
+- Players need to have keypairs - their own secret and public keys.
+  When a player or players draw a card, we need to choose an input for the VRFs of players who draw cards.
+- One good way to get an input is for all players to do a commit-reveal and combine the results, however you could choose whatever technique you'd like.
+- Players know their own VRF output (i.e. the cards in their hand), but other players don't until the game calls for them to reveal their card, by publishing a VRF output.
+
+You can choose what VRF library you want to use, though we recommend the [`schnorrkel` Rust crate](https://github.com/w3f/schnorrkel).
+
+## Ways this protocol fails to simulate actual card drawing
+
+There is a complication: normally in card games you can't draw the same card twice or have two people draw the same card.
+But imagine we shuffle many decks together then the same card can be drawn twice.
+By "Infinite deck", we mean that card counting is useless: we always have a 1/52 probability of drawing a card, no matter who has already drawn what.
+
+Another complication is that if games require cards to be drawn and played at different times, we can tell when a card that is revealed was drawn.
+Not a problem for e.g. Poker, when we reveal once of at all.
+
+## Instructions
+
+1. Find some 2-3 other teammates you haven't worked with before.
+1. Solve the challenge.
+
+Don't hesitate to ask for help if needed.
+The target duration for this activity is about 1.5 hours.
diff --git a/content/1-Cryptography/materials/aes-modes-activity/Cargo.lock b/content/1-Cryptography/materials/aes-modes-activity/Cargo.lock
new file mode 100644
index 00000000..67d465cb
--- /dev/null
+++ b/content/1-Cryptography/materials/aes-modes-activity/Cargo.lock
@@ -0,0 +1,93 @@
+# This file is automatically @generated by Cargo.
+# It is not intended for manual editing.
+version = 3
+
+[[package]]
+name = "aes"
+version = "0.8.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "bfe0133578c0986e1fe3dfcd4af1cc5b2dd6c3dbf534d69916ce16a2701d40ba"
+dependencies = [
+ "cfg-if",
+ "cipher",
+ "cpufeatures",
+]
+
+[[package]]
+name = "aes-modes"
+version = "0.1.0"
+dependencies = [
+ "aes",
+]
+
+[[package]]
+name = "cfg-if"
+version = "1.0.0"
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+
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+dependencies = [
+ "crypto-common",
+ "inout",
+]
+
+[[package]]
+name = "cpufeatures"
+version = "0.2.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
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+dependencies = [
+ "libc",
+]
+
+[[package]]
+name = "crypto-common"
+version = "0.1.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "1bfb12502f3fc46cca1bb51ac28df9d618d813cdc3d2f25b9fe775a34af26bb3"
+dependencies = [
+ "generic-array",
+ "typenum",
+]
+
+[[package]]
+name = "generic-array"
+version = "0.14.5"
+source = "registry+https://github.com/rust-lang/crates.io-index"
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+dependencies = [
+ "typenum",
+ "version_check",
+]
+
+[[package]]
+name = "inout"
+version = "0.1.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "a0c10553d664a4d0bcff9f4215d0aac67a639cc68ef660840afe309b807bc9f5"
+dependencies = [
+ "generic-array",
+]
+
+[[package]]
+name = "libc"
+version = "0.2.126"
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+checksum = "349d5a591cd28b49e1d1037471617a32ddcda5731b99419008085f72d5a53836"
+
+[[package]]
+name = "typenum"
+version = "1.15.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "dcf81ac59edc17cc8697ff311e8f5ef2d99fcbd9817b34cec66f90b6c3dfd987"
+
+[[package]]
+name = "version_check"
+version = "0.9.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "49874b5167b65d7193b8aba1567f5c7d93d001cafc34600cee003eda787e483f"
diff --git a/content/1-Cryptography/materials/aes-modes-activity/Cargo.toml b/content/1-Cryptography/materials/aes-modes-activity/Cargo.toml
new file mode 100644
index 00000000..ee1170b9
--- /dev/null
+++ b/content/1-Cryptography/materials/aes-modes-activity/Cargo.toml
@@ -0,0 +1,9 @@
+[package]
+name = "aes-modes"
+version = "0.1.0"
+edition = "2021"
+
+# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
+
+[dependencies]
+aes = "0.8.1"
diff --git a/content/1-Cryptography/materials/aes-modes-activity/src/main.rs b/content/1-Cryptography/materials/aes-modes-activity/src/main.rs
new file mode 100644
index 00000000..25111df6
--- /dev/null
+++ b/content/1-Cryptography/materials/aes-modes-activity/src/main.rs
@@ -0,0 +1,167 @@
+//! In Module 1, we discussed Block ciphers like AES. Block ciphers have a fixed length input.
+//! Real wold data that we wish to encrypt _may_ be exactly the right length, but is probably not.
+//! When your data is too short, you can simply pad it up to the correct length.
+//! When your data is too long, you have some options.
+//!
+//! In this exercise, we will explore a few of the common ways that large pieces of data can be
+//! broken up and combined in order to encrypt it with a fixed-length block cipher.
+//!
+//! WARNING: ECB MODE IS NOT SECURE.
+//! Seriously, ECB is NOT secure. Don't use it irl. We are implementing it here to understand _why_
+//! it is not secure and make the point that the most straight-forward approach isn't always the
+//! best, and can sometimes be trivially broken.
+
+use aes::{
+	cipher::{generic_array::GenericArray, BlockCipher, BlockDecrypt, BlockEncrypt, KeyInit},
+	Aes128,
+};
+
+///We're using AES 128 which has 16-byte (128 bit) blocks.
+const BLOCK_SIZE: usize = 16;
+
+fn main() {
+	todo!("Maybe this should be a library crate. TBD");
+}
+
+/// Simple AES encryption
+/// Helper function to make the core AES block cipher easier to understand.
+fn aes_encrypt(data: [u8; BLOCK_SIZE], key: &[u8; BLOCK_SIZE]) -> [u8; BLOCK_SIZE] {
+	// Convert the inputs to the necessary data type
+	let mut block = GenericArray::from(data);
+	let key = GenericArray::from(*key);
+
+	let cipher = Aes128::new(&key);
+
+	cipher.encrypt_block(&mut block);
+
+	block.into()
+}
+
+/// Simple AES encryption
+/// Helper function to make the core AES block cipher easier to understand.
+fn aes_decrypt(data: [u8; BLOCK_SIZE], key: &[u8; BLOCK_SIZE]) -> [u8; BLOCK_SIZE] {
+	// Convert the inputs to the necessary data type
+	let mut block = GenericArray::from(data);
+	let key = GenericArray::from(*key);
+
+	let cipher = Aes128::new(&key);
+
+	cipher.decrypt_block(&mut block);
+
+	block.into()
+}
+
+/// Before we can begin encrypting our raw data, we need it to be a multiple of the
+/// block length which is 16 bytes (128 bits) in AES128.
+///
+/// The padding algorithm here is actually not trivial. The trouble is that if we just
+/// naively throw a bunch of zeros on the end, there is no way to know, later, whether
+/// those zeros are padding, or part of the message, or some of each.
+///
+/// The scheme works like this. If the data is not a multiple of the block length,  we
+/// compute how many pad bytes we need, and then write that number into the last several bytes.
+/// Later we look at the last byte, and remove that number of bytes.
+///
+/// But if the data _is_ a multiple of the block length, then we have a problem. We don't want
+/// to later look at the last byte and remove part of the data. Instead, in this case, we add
+/// another entire block containing the block length in each byte. In our case,
+/// [16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16]
+fn pad(mut data: Vec<u8>) -> Vec<u8> {
+	// When twe have a multiple the second term is 0
+	let number_pad_bytes = BLOCK_SIZE - data.len() % BLOCK_SIZE;
+
+	for _ in 0..number_pad_bytes {
+		data.push(number_pad_bytes as u8);
+	}
+
+	data
+}
+
+/// Groups the data into BLOCK_SIZE blocks. Assumes the data is already
+/// a multiple of the block size. If this is not the case, call `pad` first.
+fn group(data: Vec<u8>) -> Vec<[u8; BLOCK_SIZE]> {
+	let mut blocks = Vec::new();
+	let mut i = 0;
+	while i < data.len() {
+		let mut block: [u8; BLOCK_SIZE] = Default::default();
+		block.copy_from_slice(&data[i..i + BLOCK_SIZE]);
+		blocks.push(block);
+
+		i += BLOCK_SIZE;
+	}
+
+	blocks
+}
+
+/// Does the opposite of the group function
+fn un_group(blocks: Vec<[u8; BLOCK_SIZE]>) -> Vec<u8> {
+	todo!()
+}
+
+/// Does the opposite of the pad function.
+fn un_pad(data: Vec<u8>) -> Vec<u8> {
+	todo!()
+}
+
+/// The first mode we will implement is the Electronic Code Book, or ECB mode.
+/// Warning: THIS MODE IS NOT SECURE!!!!
+///
+/// This is probably the first thing you think of when considering how to encrypt
+/// large data. In this mode we simply encrypt each block of data under the same key.
+/// One good thing about this mode is that it is parallelizable. But to see why it is
+/// insecure look at: https://www.ubiqsecurity.com/wp-content/uploads/2022/02/ECB2.png
+fn ecb_encrypt(plain_text: Vec<u8>, key: [u8; 16]) -> Vec<u8> {
+	todo!()
+}
+
+/// Opposite of ecb_encrypt.
+fn ecb_decrypt(cipher_text: Vec<u8>, key: [u8; BLOCK_SIZE]) -> Vec<u8> {
+	todo!()
+}
+
+/// The next mode, which you can implement on your own is cipherblock chaining.
+/// This mode actually is secure, and it often used in real world applications.
+///
+/// In this mode, the ciphertext from the first block is XORed with the
+/// plaintext of the next block before it is encrypted.
+///
+/// For more information, and a very clear diagram,
+/// see https://de.wikipedia.org/wiki/Cipher_Block_Chaining_Mode
+///
+/// You will need to generate a random initialization vector (IV) to encrypt the
+/// very first block because it doesn't have a previous block. Typically this IV
+/// is inserted as the first block of ciphertext.
+fn cbc_encrypt(plain_text: Vec<u8>, key: [u8; BLOCK_SIZE]) -> Vec<u8> {
+	// Remember to generate a random initialization vector for the first block.
+
+	todo!()
+}
+
+fn cbc_decrypt(cipher_text: Vec<u8>, key: [u8; BLOCK_SIZE]) -> Vec<u8> {
+	todo!()
+}
+
+/// Another mode which you can implement on your own is counter mode.
+/// This mode is secure as well, and is used in real world applications.
+/// It allows parallelized encryption and decryption, as well as random read access when decrypting.
+///
+/// In this mode, there is an index for each block being encrypted (the "counter"), as well as a random nonce.
+/// For a 128-bit cipher, the nonce is 64 bits long.
+///
+/// For the ith block, the 128-bit value V of `nonce | counter` is constructed, where | denotes
+/// concatenation. Then, V is encrypted with the key using ECB mode. Finally, the encrypted V is
+/// XOR'd with the plaintext to produce the ciphertext.
+///
+/// A very clear diagram is present here:
+/// https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Counter_(CTR)
+///
+/// Once again, you will need to generate a random nonce which is 64 bits long. This should be
+/// inserted as the first block of the ciphertext.
+fn ctr_encrypt(plain_text: Vec<u8>, key: [u8; BLOCK_SIZE]) -> Vec<u8> {
+	// Remember to generate a random nonce
+	todo!()
+}
+
+fn ctr_decrypt(cipher_text: Vec<u8>, key: [u8; BLOCK_SIZE]) -> Vec<u8> {
+	todo!()
+}
diff --git a/content/1-Cryptography/materials/hash-rust-repl-demo.md b/content/1-Cryptography/materials/hash-rust-repl-demo.md
new file mode 100644
index 00000000..ece028a7
--- /dev/null
+++ b/content/1-Cryptography/materials/hash-rust-repl-demo.md
@@ -0,0 +1,166 @@
+# Rust Demo for Hashes
+
+---
+
+## Preamble
+
+Run this ASAP to get our deps built before you need them.
+
+```rust
+:dep sp-core = { version = "6.0.0", git = "https://github.com/paritytech/substrate.git", branch = "polkadot-v0.9.25" }
+:dep rand = { version = "0.8.5", features = ["small_rng"] }
+use sp_core::*;
+
+/// Helper function to compare a subset of bytes from an array.
+fn sized_compare<H:std::cmp::PartialEq+?Sized>(a: &H, b: &H) -> bool {
+	a == b
+}
+```
+
+---
+
+## Fixed-Size Outputs
+
+```rust
+let short_input_hash = blake2_256(&b"abcd"[..]);
+let long_input_hash = blake2_256(&[0u8; 1024][..]);
+assert_eq!(short_input_hash.len(), long_input_hash.len());
+```
+
+```rust
+HexDisplay::from(&short_input_hash)
+```
+
+```rust
+HexDisplay::from(&long_input_hash)
+```
+
+---
+
+## Computation Speed Properties
+
+```rust
+use std::time::{Instant};
+// Let's give the function 1kb of data to hash
+let value_to_hash = [0u8; 1024];
+```
+
+```rust
+// Blake2
+let blake2_start = Instant::now();
+for _ in 0..1000 {
+	let _ = blake2_256(&value_to_hash[..]);
+}
+let blake2_elapsed_time = blake2_start.elapsed().as_micros();
+```
+
+```rust
+// TwoX
+let twox_start = Instant::now();
+for _ in 0..1000 {
+	let _ = twox_256(&value_to_hash[..]);
+}
+let twox_elapsed_time = twox_start.elapsed().as_micros();
+```
+
+```rust
+// Compare times for the 1000 rounds we did for each.
+// We expect TwoX to be about 10x faster.
+// Note this is native hardware, Wasm may be different.
+blake2_elapsed_time
+```
+
+```rust
+twox_elapsed_time
+```
+
+---
+
+## Pre-Image Attacks
+
+```rust
+use rand::prelude::*;
+
+// We want to find some other pre-image that will give the same hash as "blockchain".
+let attack_target: [u8; 32] = blake2_256(b"blockchain");
+
+// Hopefully we could not actually succeed in this! So let's cheat, and truncate the hash to just
+// its first few bytes. We'll look for a collision on this truncated hash.
+let difficulty = 2;
+let mut count = 0u32;
+loop {
+	count += 1;
+	// Generate some random array.
+	let x: [u8; 16] = random();
+	let x_hash: [u8; 32] = blake2_256(&x[..]);
+	if sized_compare(&attack_target[0..difficulty], &x_hash[0..difficulty]) {
+		println!("\nSecond pre-image found in {:?} attempts! {:?}", count, x);
+		println!("{:?}", &x_hash[0..difficulty]);
+		println!("{:?}", &attack_target[0..difficulty]);
+		break;
+	}
+
+	// Let's not let our CPU run forever and bail. Usually takes about 200k.
+	if count == 500_000 {
+		println!("\nGiving up on pre-image attack");
+		break;
+	}
+}
+```
+
+---
+
+## Collisions
+
+```rust
+use rand::prelude::*;
+
+// Here there is no "attack target". The attacker controls both inputs. This should find a collision
+// much faster than a second pre-image, and demonstrate the birthday paradox.
+
+// Store the previous hashes to check new ones against.
+//                     hash,     value
+let mut previous: Vec<([u8; 32], [u8; 16])> = Vec::new();
+
+let mut count = 0u32;
+let mut break_loop = false;
+let difficulty = 2; // number of bytes to call it a "collision"
+loop {
+	count += 1;
+
+	// Generate a new value and hash it.
+	let x: [u8; 16] = random();
+	let x_hash: [u8; 32] = blake2_256(&x[..]);
+
+	// for all previous...
+	/*
+	Looping through this vec every time and checking each value is obviously really
+	inefficient. After the hash-based data structure lesson, perhaps students could code up a
+	better solution, like a sorted list with binary search.
+	*/
+	for hh in &previous {
+		// check if the new one matches
+		if sized_compare(&x_hash[0..difficulty], &hh.0[0..difficulty]) {
+			println!("\nCollision found in {:?} attempts!", count);
+			println!("pre-image 1: {:?}", &hh.1);
+			println!("pre-image 2: {:?}", x);
+			println!("{:?}", &hh.0[0..difficulty]);
+			println!("{:?}", &x_hash[0..difficulty]);
+			break_loop = true;
+			break;
+		}
+	}
+	if break_loop {
+		break;
+	}
+
+	// if not, add the new one to previous
+	previous.push((x_hash, x));
+
+	// bail if it's taking too long
+	if count == 100_000 {
+		println!("\nGiving up on collision");
+		break;
+	}
+}
+```
diff --git a/content/cryptography/_materials/many-time-pad.md b/content/1-Cryptography/materials/many-time-pad.md
similarity index 100%
rename from content/cryptography/_materials/many-time-pad.md
rename to content/1-Cryptography/materials/many-time-pad.md
diff --git a/content/1-Cryptography/materials/merkle-tree-activity/Cargo.lock b/content/1-Cryptography/materials/merkle-tree-activity/Cargo.lock
new file mode 100644
index 00000000..189b6318
--- /dev/null
+++ b/content/1-Cryptography/materials/merkle-tree-activity/Cargo.lock
@@ -0,0 +1,7 @@
+# This file is automatically @generated by Cargo.
+# It is not intended for manual editing.
+version = 3
+
+[[package]]
+name = "merkle-tree"
+version = "0.1.0"
diff --git a/content/1-Cryptography/materials/merkle-tree-activity/Cargo.toml b/content/1-Cryptography/materials/merkle-tree-activity/Cargo.toml
new file mode 100644
index 00000000..bbba1ff1
--- /dev/null
+++ b/content/1-Cryptography/materials/merkle-tree-activity/Cargo.toml
@@ -0,0 +1,8 @@
+[package]
+name = "merkle-tree"
+version = "0.1.0"
+edition = "2021"
+
+# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
+
+[dependencies]
diff --git a/content/1-Cryptography/materials/merkle-tree-activity/src/main.rs b/content/1-Cryptography/materials/merkle-tree-activity/src/main.rs
new file mode 100644
index 00000000..0f89ac54
--- /dev/null
+++ b/content/1-Cryptography/materials/merkle-tree-activity/src/main.rs
@@ -0,0 +1,83 @@
+//! This is minimal Merkle tree implementation with proof checking
+
+use std::{
+	collections::hash_map::DefaultHasher,
+	hash::{Hash, Hasher},
+};
+
+fn main() {
+	let s = "";
+	let h = hash(&s);
+	println!("{}", h);
+}
+
+/// We'll use Rust's built-in hashing which returns a u64 type.
+/// This alias just helps us understand when we're treating the number as a hash
+type HashValue = u64;
+
+/// Helper function that makes the hashing interface easier to understand.
+fn hash<T: Hash>(t: &T) -> HashValue {
+	let mut s = DefaultHasher::new();
+	t.hash(&mut s);
+	s.finish()
+}
+
+/// Given a vector of data blocks this function adds padding blocks to the end
+/// until the length is a power of two which is needed for Merkle trees.
+fn pad_base_layer(blocks: &mut Vec<&str>) {
+	todo!()
+}
+
+/// Helper function to combine two hashes and compute the hash of the combination.
+/// This will be useful when building the intermediate nodes in the Merkle tree.
+///
+/// There are many correct ways to do this, but the easiest one and the one that I recommend
+/// is to convert the hashes to strings and concatenate them.
+fn concatenate_hash_values(left: HashValue, right: HashValue) -> HashValue {
+	todo!()
+}
+
+/// Calculates the Merkle root of a sentence. We consider each word in the sentence to
+/// be one block. Words are separated by one or more spaces.
+///
+/// Example:
+/// Sentence: "Trust me, bro!"
+/// "Trust", "me," "bro!"
+/// Notice that the punctuation like the comma and exclamation point are included in the words
+/// but the spaces are not.
+fn calculate_merkle_root(sentence: &str) -> HashValue {
+	todo!()
+}
+
+/// A representation of a sibling node along the Merkle path from the data
+/// to the root. It is necessary to specify which side the sibling is on
+/// so that the hash values can be combined in the same order.
+enum SiblingNode {
+	Left(HashValue),
+	Right(HashValue),
+}
+
+/// Generates a Merkle proof that one particular word is contained
+/// in the given sentence. You provide the sentence and the index of the word
+/// which you want a proof.
+///
+/// Panics if the index is beyond the length of the word.
+///
+/// Example: I want to prove that the word "Trust" is in the sentence "Trust me, bro!"
+/// So I call generate_proof("Trust me, bro!", 0)
+/// And I get back the merkle root and list of intermediate nodes from which the
+/// root can be reconstructed.
+fn generate_proof(sentence: &str, index: usize) -> (HashValue, Vec<SiblingNode>) {
+	todo!()
+}
+
+/// Checks whether the given word is contained in a sentence, without knowing the whole sentence.
+/// Rather we only know the merkle root of the sentence and a proof.
+fn validate_proof(root: &str, word: &str, proof: Vec<SiblingNode>) -> bool {
+	todo!()
+}
+
+#[test]
+fn we_should_probably_have_some_tests() {
+	todo!()
+}
diff --git a/content/1-Cryptography/materials/plonk-activity/.github/workflows/pythonpackage.yml b/content/1-Cryptography/materials/plonk-activity/.github/workflows/pythonpackage.yml
new file mode 100644
index 00000000..dd84f306
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/.github/workflows/pythonpackage.yml
@@ -0,0 +1,35 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+name: Python package
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    branches: [ master ]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.6, 3.7, 3.8]
+
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install .[lint,test,tutorial]
+    - name: Lint with black
+      run: |
+        black plonk --check
+    - name: Test with pytest
+      run: |
+        pytest --nbval
diff --git a/content/1-Cryptography/materials/plonk-activity/.gitignore b/content/1-Cryptography/materials/plonk-activity/.gitignore
new file mode 100644
index 00000000..ae0eca5f
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/.gitignore
@@ -0,0 +1,7 @@
+__pycache__/
+.ipynb_checkpoints/
+.pytest_cache/
+.python-version
+.vscode/
+build/
+*.egg-info/
diff --git a/content/1-Cryptography/materials/plonk-activity/LICENSE b/content/1-Cryptography/materials/plonk-activity/LICENSE
new file mode 100644
index 00000000..f288702d
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/LICENSE
@@ -0,0 +1,674 @@
+                    GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
+
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diff --git a/content/1-Cryptography/materials/plonk-activity/README.md b/content/1-Cryptography/materials/plonk-activity/README.md
new file mode 100644
index 00000000..fb12d48f
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/README.md
@@ -0,0 +1,35 @@
+# Plonk
+
+A Python tutorial of the paper [PLONK: Permutations over Lagrange-bases for Oecumenical Noninteractive arguments of Knowledge](https://eprint.iacr.org/2019/953) it is incomplete WIP, not secure, not correct just to help people learn.
+
+# Activity
+
+Change the [notbook content](./plonk.ipynb) so it proves that you know the solution (3,4,5) to Pythagoras equation $x^2 + y^2 = z^2$ instead of proving the knowledge of solution to $x^3 + x + 5 = 35$ (as currently does). You only need to update the tutorial up to Part x FFT, until you generate the permutations successfully.
+
+You should _not_ import the `gen_copy_constraints` from `plonk.sample_problem` instead, you should create the `copy_constraints` array similar to $\psi$ array we built in the course.
+
+## Getting Started
+
+```bash
+pip install -e .
+```
+
+See [./plonk.ipynb](./plonk.ipynb) for the tutorial.
+
+## Testing
+
+```bash
+pip install -e .[test]
+```
+
+```bash
+pytest --nbval
+```
+
+## Community
+
+https://t.me/plonk_tutorial
+
+## Citation
+
+The original tutorial is from https://github.com/barryWhiteHat/plonk_tutorial
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk.ipynb b/content/1-Cryptography/materials/plonk-activity/plonk.ipynb
new file mode 100644
index 00000000..88540dc5
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/plonk.ipynb
@@ -0,0 +1,1170 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## What does our ZKP look like \n",
+    "\n",
+    "We have a bunch of stuff \n",
+    "\n",
+    "1. A witness which is information that lets us make the proof in our case this is knowledge of a variable x that satisfies our eqation. It also includes the intermediate values that are zkp uses. This is secret to the user they want to prove this information.\n",
+    "2. A set of gate constraints. Basically that all the multiplicaions and addition we do are correct. \n",
+    "3. A copy constriant check\n",
+    "4. Input / output checks"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Plonk Tutorial\n",
+    "This tutorial is based upon https://www.vitalik.ca/general/2019/09/22/plonk.html it expands upon the ideas described there and teaches the user to build their own plonk implemenation in python.\n",
+    "\n",
+    "This tutorial takes to forum of a series of challenges where the user eventually build a plonk implmentation of a single proof. \n",
+    "\n",
+    "Plonk allows us to make arbitary zero knoledge proofs. For the purposes of this tutorial we will prove that we know an x such that  $P(x) = x^3 + x + 5 = 35$ this is a toy problem\n",
+    "\n",
+    "![](https://vitalik.ca/files/posts_files/plonk-files/Circuit.png)\n",
+    "\n",
+    "You can see we have two kinds of constraints gate constraints and copy constraints. A constraint is like an assertion from python. The program can only continue running if this assertion is true.\n",
+    "\n",
+    "We will first handle the gate constraints and then tackle the copy constraints. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Gen witness"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So lets first find a satisfying solution to the probelm we are trying to make proofs about $x^3 + x + 5 = 35$\n",
+    "\n",
+    "The variables a, b and c will be the checking of additions / multiplicaions operatirons. Where we define `a + b == c` or `a * b == c`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def gen_witness(x):\n",
+    "    a = [x , x*x, x*x*x, 1,  1, x*x*x + x]\n",
+    "    b = [x , x, x, 5, 35, 5]\n",
+    "    c = [x*x, x*x*x , x + x*x*x ,5, 35, 35]\n",
+    "    return(a,b,c)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Right so now that we have a, b , c we are ready to test. `is_satisfied` tests that our witness matches the constraints we are planing to add. \n",
+    "\n",
+    "Basically a[0] * b[0] = c[0] check this is a multiplicaion\n",
+    "a[2] + b[2] = c[2] check this is an addition."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def is_satisfied_witness(a, b, c):\n",
+    "    assert(a[0] * b[0] == c[0])\n",
+    "    assert(a[1] * b[1] == c[1])\n",
+    "    assert(a[2] + b[2] == c[2])\n",
+    "    assert(a[3] * b[3] == c[3])\n",
+    "    assert(a[4] * b[4] == c[4])\n",
+    "    assert(a[5] + b[5] == c[5])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plonk.sample_problem import gen_witness, is_satisfied_witness\n",
+    "\n",
+    "a, b , c = gen_witness(1)\n",
+    "\n",
+    "# Uncomment the next line and run\n",
+    "# is_satisfied_witness(a,b,c)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Reader should investigate why this fails and why the next passes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "a, b , c = gen_witness(3)\n",
+    "is_satisfied_witness(a,b,c)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## In plonk everything is a polynomial\n",
+    "\n",
+    "In the previous section we generated our witness. A witness is a valid solution to our constraints. Where here our constraints are $x^3 + x + 5 == 35$\n",
+    "\n",
+    "Next we want to define the actual constraints. They will be defined as a polynomial. Lets start out by creating a function eval_poly which takes a polynomial and evaluates it at a given point. Take the polynomial $1 + x + x^2 = y$ which is defined by this list [1,1,1] from lowest degree (ie starting at the $1*x^0$ ) to highest (1*x^2) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## User input here. \n",
+    "def eval_poly(coef, x):\n",
+    "    res = []\n",
+    "    power = 1\n",
+    "    for i in coef:\n",
+    "        res.append(i * power)\n",
+    "        power = power * x\n",
+    "    return(round(sum(res)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert(eval_poly([1,1,1], 2) == 7 )\n",
+    "assert(eval_poly([-2, 7, -5, 1], 0) == -2)\n",
+    "assert(eval_poly([-2, 7, -5, 1], 1) == 1)\n",
+    "assert(eval_poly([-2, 7, -5, 1], 2) == 0)\n",
+    "assert(eval_poly([-2, 7, -5, 1], 3) == 1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay now it seems out polynomial evaluations are working :)\n",
+    "\n",
+    "Our mul / add constraint is defined by $\\left(Q_{L_{i}}\\right) a_{i}+\\left(Q_{R_{i}}\\right) b_{i}+\\left(Q_{O_{i}}\\right) c_{i}+\\left(Q_{M_{i}}\\right) a_{i} b_{i}+Q_{C_{i}}=0$ we can use this to check additions and multiplications. Define the constraint polynomial.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def constraint_polynomial(Qli, Qri, Qmi, Qoi, Qci, ai, bi, ci):\n",
+    "    return(Qli*ai + Qri*bi + Qoi*ci + Qmi*ai*bi + Qci == 0)\n",
+    "\n",
+    "def validate_native(Ql, Qr, Qm, Qo, Qc, a, b, c):\n",
+    "    for Qli,Qri,Qmi,Qoi,Qci,ai,bi,ci in zip (Ql,Qr,Qm,Qo,Qc,a,b,c):\n",
+    "        if (constraint_polynomial(Qli,Qri,Qmi,Qoi,Qci,ai,bi,ci) == False):\n",
+    "            return(False)\n",
+    "    return(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def test_addition():\n",
+    "    # constraints\n",
+    "    Ql = [1]\n",
+    "    Qr = [1]\n",
+    "    Qm = [0]\n",
+    "    Qo = [-1]\n",
+    "    Qc = [0]\n",
+    "\n",
+    "    # witness\n",
+    "    a = [0]\n",
+    "    b = [1]\n",
+    "    c = [1]\n",
+    "\n",
+    "    assert ( validate_native(Ql, Qr, Qm, Qo, Qc, a, b, c) == True)\n",
+    "\n",
+    "\n",
+    "def test_mul():\n",
+    "\n",
+    "    # constraints\n",
+    "    Ql = [0]\n",
+    "    Qr = [0]\n",
+    "    Qm = [1]\n",
+    "    Qo = [-1]\n",
+    "    Qc = [0]\n",
+    "\n",
+    "    # witness\n",
+    "    a = [1]\n",
+    "    b = [1]\n",
+    "    c = [1]\n",
+    "\n",
+    "    assert ( validate_native(Ql, Qr, Qm, Qo, Qc, a, b, c) == True)\n",
+    "\n",
+    "    \n",
+    "\n",
+    "def test_constant():\n",
+    "    # constraints\n",
+    "    Ql = [1]\n",
+    "    Qr = [1]\n",
+    "    Qm = [0]\n",
+    "    Qo = [0]\n",
+    "    Qc = [-10]\n",
+    "\n",
+    "    # witness\n",
+    "    a = [10]\n",
+    "    b = [0]\n",
+    "    c = [10]\n",
+    "\n",
+    "    assert ( validate_native(Ql, Qr, Qm, Qo, Qc, a, b, c) == True)\n",
+    "    \n",
+    "test_addition()\n",
+    "test_mul()\n",
+    "test_constant()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay so now we are doing multiplicaions and additions. We can validate manually that all of these are being done correctly. Right so this is working we can make constraints. So lets make all the constraints for our system. First lets make some helpers that drop the constraints where we need then make sure they pass the tests :)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plonk.constraint import add_add_constarint, add_mul_constarint, add_constant_constraint"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay now lets add the actual constraints. By setting Ql, Qr, Qm , Qo and Qc such that it evaluates to a multipicion constaint at Ql[0] and an addition at Ql[2]. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def gen_constraints():\n",
+    "    # Prove that I know an X such that X*x*x + x +5 == 35\n",
+    "\n",
+    "    # init constraints \n",
+    "    Ql = []\n",
+    "    Qr = []\n",
+    "    Qm = []\n",
+    "    Qo = []\n",
+    "    Qc = []\n",
+    "\n",
+    "    # set constraints \n",
+    "    Ql, Qr, Qm, Qo, Qc = add_mul_constarint(Ql, Qr, Qm, Qo, Qc)\n",
+    "    Ql, Qr, Qm, Qo, Qc = add_mul_constarint(Ql, Qr, Qm, Qo, Qc)\n",
+    "    Ql, Qr, Qm, Qo, Qc = add_add_constarint(Ql, Qr, Qm, Qo, Qc)\n",
+    "    Ql, Qr, Qm, Qo, Qc = add_constant_constraint(Ql, Qr, Qm, Qo, Qc, 5)\n",
+    "    Ql, Qr, Qm, Qo, Qc = add_constant_constraint(Ql, Qr, Qm, Qo, Qc, 35)\n",
+    "    # todo add a constant constraint for 1\n",
+    "    Ql, Qr, Qm, Qo, Qc = add_add_constarint(Ql, Qr, Qm, Qo, Qc)\n",
+    "    return(Ql, Qr, Qm, Qo, Qc)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Copy constraints \n",
+    "So at the moment the system is not secure. Basically we are checking that the variables at location \n",
+    "\n",
+    "1. `a[0] * b[0] == c[0]` \n",
+    "2. `a[1] * b[1] == c[1]`\n",
+    "3. `a[2] + b[2] == c[2]`\n",
+    "\n",
+    "\n",
+    "But we are just hoping that `a[1] == c[0]` we need to add constraints to make sure that we copy c[0] to a[1] these are called copy constraints you may also have heard of them refered to as permutation arguments. \n",
+    "\n",
+    "TODO: Do the actual attack\n",
+    "\n",
+    "The naive thing to do is to do these checks manually. Basically make sure that each variable is equal to the other. The probelm with this is that it means that we need to check every variable which breaks privacy and succintness. Instead we will find a way to do this check using polynomials. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Right now we have our witness which is `witness = a + b + c` and we want to prove that the value at `witness[0] == witness[8] == witness[7] == witness[6]` all of these values corresponding to our initial x. \n",
+    "\n",
+    "So now we need to make 3 polynomials the first to return the index of witness we want to look up, `witness_x_1`. The second `witness_x_2` to return the index after the permutation has been applied. And the third witness_y which returns the actual value of that witness at a given index. \n",
+    "\n",
+    "Write code that returns all of these. \n",
+    "\n",
+    "hint: use `from scipy.interpolate import lagrange` to interpolate a polynomial that passes through several points. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Lets do the first. write fird permutation yourself \n",
+    "from plonk.copy_constraint import find_permutation\n",
+    "from plonk.poly import polynomial_eval\n",
+    "\n",
+    "witness = a + b + c\n",
+    "eval_domain = range(0,len(witness))\n",
+    "witness_x_a = find_permutation(range(0,len(a)), range(0,len(a)))\n",
+    "witness_x_b = find_permutation(range(len(a),len(b)*2), range(len(a),len(b)*2))\n",
+    "witness_x_c = find_permutation(range(len(b)*2, len(c)*3), range(len(a)*2,len(a)*3))\n",
+    "\n",
+    "witness_y = find_permutation(witness, eval_domain)\n",
+    "\n",
+    "for i, val in enumerate(witness):\n",
+    "    assert(val == polynomial_eval(witness_y, i))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The test code below checks that witness_y returns the same results when we use the permutated indexes or the non permuated version. This means that each value there matches. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Okay now lets rearrange it so that the values get swapped when they match\n",
+    "from plonk.sample_problem import gen_copy_constraints\n",
+    "\n",
+    "witness_x_a_perm, witness_x_b_perm, witness_x_c_perm, copy_constraints = gen_copy_constraints()\n",
+    "\n",
+    "for i in range(0,len(a)):\n",
+    "    assert(polynomial_eval(witness_y , polynomial_eval(witness_x_a, i)) == \n",
+    "           polynomial_eval (witness_y ,polynomial_eval(witness_x_a_perm, i)))\n",
+    "\n",
+    "for i in range(len(a), len(a)*2):\n",
+    "    assert(polynomial_eval(witness_y , polynomial_eval(witness_x_b, i)) == \n",
+    "           polynomial_eval (witness_y ,polynomial_eval(witness_x_b_perm, i)))\n",
+    "    \n",
+    "for i in range(len(a)*2, len(a)*3):\n",
+    "    assert(polynomial_eval(witness_y , polynomial_eval(witness_x_c, i)) == \n",
+    "           polynomial_eval (witness_y ,polynomial_eval(witness_x_c_perm, i)))\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So now we have a way of checking permutations with polynomials. But we still need to check every variable which means we have not really gained anything. So next we will embed these three polynomials in a third such that we can check batches of permutations at once. \n",
+    "\n",
+    "To do this we take a random linear combination of witness_x_1 and witness_y. $rlc = v1 + wintess_x_1 + v2*witness_y$\n",
+    "\n",
+    "Then we calculate P(x) where P(0) = 1 and $P(x+1) = p(x)* rlc$\n",
+    "\n",
+    "Then we do the same for witness_x_2 calculating P_2(x). Because v1 and v2 are random numbers we know that P_1(i) == P_2(i) if and only if witness_Y gives the same results when evaluated on witness_x_1(0:i) and witness_x_2(0:i)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "from plonk.copy_constraint import copy_constraint_simple \n",
+    "\n",
+    "# we have to generate v1 and v2 after a, b and c have been fixed.\n",
+    "v1 = hash(str(a + b + c))\n",
+    "v2 = hash(str(c + a + b))\n",
+    "\n",
+    "eval_domain = range(0, len(a)*3)\n",
+    "\n",
+    "\n",
+    "x, Y , Px_a, rlc = copy_constraint_simple(range(0,len(a)), witness_x_a, witness_y, v1, v2)\n",
+    "x, Y , Px_b, rlc = copy_constraint_simple(range(len(a),len(a)*2), witness_x_b, witness_y, v1, v2)\n",
+    "x, Y , Px_c, rlc = copy_constraint_simple(range(len(a)*2,len(a)*3), witness_x_c, witness_y, v1, v2)\n",
+    "\n",
+    "# calcualte permutated polynomial    \n",
+    "x_1, Y_1 , Px_a_prime, rlc_1 = copy_constraint_simple(range(0,len(a)), witness_x_a_perm, witness_y, v1, v2)\n",
+    "x_1, Y_1 , Px_b_prime, rlc_1 = copy_constraint_simple(range(len(a),len(a)*2), witness_x_b_perm, witness_y, v1, v2)\n",
+    "x_1, Y_1 , Px_c_prime, rlc_1 = copy_constraint_simple(range(len(a)*2,len(a)*3), witness_x_c_perm, witness_y, v1, v2)\n",
+    "\n",
+    "assert(Px_a[-1] * Px_b[-1] * Px_c[-1] == Px_a_prime[-1] * Px_b_prime[-1] * Px_c_prime[-1])\n",
+    "assert(Px_a[0] == Px_b[0] == Px_c[0] == Px_a_prime[0] == Px_b_prime[0] == Px_c_prime[0] == 1 )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So now we can evaluate many copy constraints by simply checking a single point. But the problem is that the verifier needs to compute the Px_a ... Px_c_prime. We want to come up with a way so that they don't need to evaluate these instead letting the prover produce an argument that they have evaluated them correctly and minimize the verifiers work. We will do that in after the next section. In the next section we will make a quick fft sidetrack cos we need that to make a performant prover. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part x: FFT\n",
+    "\n",
+    "So you can see that it takes about 1.5 seconds for 100 points. In reality we will want to make proofs for systems that constain orders of magnatudes more variables in less than that time. So lets use FFT to speed it up. \n",
+    "\n",
+    "So this is based upon https://vitalik.ca/general/2019/05/12/fft.html which is good to read before you continue. \n",
+    "\n",
+    "TODO: possibly break this into a seperate tutorial\n",
+    "\n",
+    "Firstly fft stands for fast foruier transform. A foruier transform is basically evaluating a polynomial. There are two ways to represent polynomials \n",
+    "\n",
+    "1. Is via coefficients [1,0,3] is $1 + x^2$ where its represented by coefficients \n",
+    "2. Is with evaulations calculate the foruier space (evaulation space) values. \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plonk.poly import polynomial_eval\n",
+    "\n",
+    "poly = [1,0,3]\n",
+    "fs = []\n",
+    "fs.append(polynomial_eval(poly,0))\n",
+    "fs.append(polynomial_eval(poly,1))\n",
+    "fs.append(polynomial_eval(poly,2))\n",
+    "print(fs)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Both coefficient space and evaluation space uniquely identify the polynomial as long as it has been evaluated at a few positions. So what we did by evaluating the polynomial is a fourier transform. It is also possible to do an inverse foruier transform by basically interpolating the polynomial to find the coefficient form. \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy.interpolate import lagrange\n",
+    "x = [0,1,2]\n",
+    "res = lagrange(x,fs)\n",
+    "res = [float(x) for x in reversed(res.coefficients)]\n",
+    "assert(res == poly)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay so we have gone to foruier space and back to coefficient space. But why? \n",
+    "\n",
+    "Well turns out in evaluation space it is easier to do things like multiplicaion and division. So lets do that now. Lets take the polynomial $1 + 3 x^2$ and multiply it by itself. Lets do it both ways in fourier space and in coordinate space. \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "res = [0]*len(poly)**2\n",
+    "expected_result = [1,0,6,0,9,0,0,0,0]\n",
+    "for i, coef1 in enumerate(poly):\n",
+    "    for j, coef2 in enumerate(poly):\n",
+    "        res[i+j] += coef1*coef2\n",
+    "assert(res == expected_result)\n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay so this took len(poly) ^ 2 operations. Lets try the fft version now. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plonk.poly import polynomial_eval\n",
+    "\n",
+    "poly = [1,0,3]\n",
+    "fs = []\n",
+    "for i in range(0,9):\n",
+    "    fs.append(polynomial_eval(poly,i))\n",
+    "\n",
+    "\n",
+    "fs_res = [x*y for x,y in zip(fs,fs)]\n",
+    "x = range(0,9)\n",
+    "res = lagrange(x,fs_res)\n",
+    "res = [int(x) for x in reversed(res.coefficients)]\n",
+    "assert(res == expected_result)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay so this tool len(poly)*2 operations to do the multiplicaions. But there is still a problem. Because the transform and inverse both cost more than the saving in operations we need to find a faster way to do this fourier transform. That is where the fast in fast fourier transform comes in. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay so firstly lets evaluate a polynomial over prime feild. You just have to take the result % p."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plonk.fft.fft import polynomial_eval_prime\n",
+    "# this evaluations 3 + x**2 at position 0 % 5\n",
+    "assert(polynomial_eval_prime([3,0,1], 0, 5) == 3)\n",
+    "# this evaluations 3 + x**2 at position 1 % 5\n",
+    "assert(polynomial_eval_prime([3,0,1], 1, 5) == 4)\n",
+    "# this evaluations 3 + x**2 at position 2 % 5\n",
+    "assert(polynomial_eval_prime([3,0,1], 2, 5) == 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Every prime feild has something called roots of unity. Which is a number x such that $x^n == 1$. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# this evaluations 3 + x**2 at position 1\n",
+    "from py_ecc.bn128.bn128_field_elements import FQ as GF\n",
+    "\n",
+    "from ethsnarks import field\n",
+    "\n",
+    "def roots_of_unity(order):\n",
+    "     a = field.FQ(5)\n",
+    "     p = field.FQ(field.SNARK_SCALAR_FIELD)\n",
+    "     return [a**(i*(p-1)/order) for i in range(order)]\n",
+    "\n",
+    "roots_2 = roots_of_unity(2)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So lets take these roots and square them see what happens. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#assert(roots[0]**2 == roots[0])\n",
+    "assert(roots_2[1]**2 == 1 )\n",
+    "assert(roots_2[1]**3 == roots_2[1]) \n",
+    "assert(roots_2[1]**4 == 1)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We see that they stay the same. Lets say that we have a polynomial above $3 + x  + x^2 + x^3 +  x^4$. If we want to evaluate it at a point $x^n = 1$ where $n = 2$. \n",
+    "\n",
+    "Lets say that we want to evaluate this polynomial at two points the naive thing to do is to  hen we can simply the above equation because we know that $x , x^3 == roots_2[1]$ and  \n",
+    "\n",
+    "Now lets use the roots of unity to accelerate the evaluation of the polynomial above. \n",
+    "\n",
+    "So we can save doing the squaring above because x^2 == x^4 for these roots. That lets us do the evaluation by summing 3 + roots[0] + roots[0] and 3 + root[1] + root[1]. \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p = field.SNARK_SCALAR_FIELD\n",
+    "eval1 = 3 + roots_2[0] + roots_2[0] + roots_2[0] + roots_2[0] \n",
+    "eval2 = 3 + roots_2[1] + roots_2[0] + roots_2[1] + roots_2[0]\n",
+    "\n",
+    "assert(polynomial_eval_prime([3,1,1,1,1], roots_2[0].n, p) == eval1)\n",
+    "assert(polynomial_eval_prime([3,1,1,1,1], roots_2[1].n, p) == eval2)\n",
+    "print(eval2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So the last part is a bit strange. Since eval2 == 3 even tho roots[1] = a pretty big number. The reason for this is that roots[0] == -roots[1] read about negative numbers in finite fields https://vitalik.ca/general/2017/11/22/starks_part_2.html\n",
+    "\n",
+    "So because a negative number squared is a positive number we only have to worry about half the domain for even powers. Check out the rest of https://vitalik.ca/general/2019/05/12/fft.html to fill in the details. \n",
+    "\n",
+    "Then write an fft that validates the testcase below"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plonk.fft.fft import fft\n",
+    "p = field.SNARK_SCALAR_FIELD\n",
+    "domain = roots_of_unity(8)\n",
+    "poly = [3,1,4,1,5,9,2,6]\n",
+    "result = []\n",
+    "\n",
+    "p_x = fft(p, domain, poly)\n",
+    "\n",
+    "for x in domain:\n",
+    "    result.append(polynomial_eval_prime(poly, x.n, p, 1, 0))\n",
+    "    \n",
+    "assert(p_x == result)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And the same for ifft"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plonk.fft.fft import ifft, fft\n",
+    "\n",
+    "p = field.SNARK_SCALAR_FIELD\n",
+    "domain = roots_of_unity(8)\n",
+    "poly = [3,1,4,1,5,9,2,6]\n",
+    "result = []\n",
+    "\n",
+    "p_x = fft(p, domain, poly)\n",
+    "\n",
+    "result = ifft(p, domain, p_x)\n",
+    "\n",
+    "assert(result == poly)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay thats fft done. We can do fast evaluations of polynomials. Do multiplicaion and stuff in fourier space and then convert back to coefficient space.\n",
+    "\n",
+    "TODO: do this better"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part x: Divison of polynomials \n",
+    "\n",
+    "Okay the next thing we need to do is find how to divide polynomials efficiently. We can work out a basic algorithm that does this but lets do it in fourier space since that will work out as being a bit faster. \n",
+    "\n",
+    "Take the polynomial $1 + x$ and square it using fft."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "poly1 = [1,1,0,0,0,0,0,0]\n",
+    "poly2 = [1,1,0,0,0,0,0,0]\n",
+    "\n",
+    "\n",
+    "domain = roots_of_unity(8)\n",
+    "\n",
+    "poly1_fs = fft(p,domain, poly1)\n",
+    "poly2_fs = fft(p,domain, poly2)\n",
+    "\n",
+    "res = [x*y for x,y in zip(poly1_fs, poly2_fs)]\n",
+    "\n",
+    "res = ifft(p,domain,res)\n",
+    "\n",
+    "assert(res  == [1, 2, 1, 0, 0, 0, 0, 0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Good now divide \n",
+    "hint: remember to use field.FQ for it the division"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "poly1 = [1,2,1,0]\n",
+    "poly2 = [1,1,0,0]\n",
+    "\n",
+    "\n",
+    "domain = roots_of_unity(4)\n",
+    "\n",
+    "poly1_fs = fft(p,domain, poly1)\n",
+    "poly2_fs = fft(p,domain, poly2)\n",
+    "res = []\n",
+    "for x,y in zip(poly1_fs, poly2_fs):\n",
+    "    x = field.FQ(x)\n",
+    "    y = field.FQ(y)\n",
+    "    res.append((x/y).n)\n",
+    "res = ifft(p,domain,res)\n",
+    "assert(res  == [1, 1, 0, 0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay we can mutiply and divide in fft form which is cool. But what happens when we try and divide a polynomial by one that does not have a root? "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "poly1 = [1,1,1,0]\n",
+    "poly2 = [1,1,0,0]\n",
+    "\n",
+    "\n",
+    "domain = roots_of_unity(8)\n",
+    "\n",
+    "poly1_fs = fft(p,domain, poly1)\n",
+    "poly2_fs = fft(p,domain, poly2)\n",
+    "res = []\n",
+    "for x,y in zip(poly1_fs, poly2_fs):\n",
+    "    x = field.FQ(x)\n",
+    "    y = field.FQ(y)\n",
+    "    res.append((x/y).n)\n",
+    "res = ifft(p,domain,res)\n",
+    "print(res)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "TODO: find out the meaning of this polynomial\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay so now we are able to quickly divide polynomials using fft what do we want this for?\n",
+    "\n",
+    "\n",
+    "Earlier we had polynomials that the verifier needed to multiply together in order to make sure they matched the data the prover sent. This work was square in the size of the polynomials which meant that our proof were not succinct. In order to make our proofs succinct we need to turn the verification into a bunch of polynomial evaluations. \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part x: is zero check\n",
+    "\n",
+    "So we are working with polynomials and we want to be sure that a polynomial equals zero everywhere inside a domain that we care about. So what we do is make it so that the roots of an equation are equal to zero everywhere we care about. \n",
+    "    \n",
+    "So we have a polynomial f(x) =  and we want to prove that it is zero at a bunch of places we care about say (x=1, x=2)\n",
+    "    \n",
+    "This is easy to do all we need to do is come up with a list of places that we care about (1,2,3) and rewrite our polynomial as the product of $z(x)*h(x) == f(x)$ where $z(x) = (x-1)(x-2)$\n",
+    "\n",
+    "So we have the polynomial $f(x) = x^4-10x^3+35x^2-50x+24$ and we have the polynomial $(x-2)(x-3) = x^2 -5x + 6$\n",
+    "\n",
+    "Use the polynomial division from above to calculate $h(x)$\n",
+    "\n",
+    "\n",
+    "    \n",
+    "    \n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fx = [24 , -50, 35, -10, 1,0,0,0]\n",
+    "zx = [6, -5, 1,0,0,0,0,0]\n",
+    "\n",
+    "domain = roots_of_unity(8)\n",
+    "fx_fs = fft(p,domain, fx)\n",
+    "zx_fs = fft(p,domain, zx)\n",
+    "res = []\n",
+    "for x,y in zip(fx_fs, zx_fs):\n",
+    "    x = field.FQ(x)\n",
+    "    y = field.FQ(y)\n",
+    "    res.append((x/y).n)\n",
+    "res = ifft(p,domain,res)\n",
+    "\n",
+    "#convert to negitive represtaionation \n",
+    "\n",
+    "hx = []\n",
+    "for i in res:\n",
+    "    if i > p / 2:\n",
+    "        i = -(p - i)\n",
+    "    hx.append(i)\n",
+    "\n",
+    "assert (hx == [4, -5, 1, 0,0,0,0,0])\n",
+    "# [4, -5, 1] == (x-1)(x-4)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "todo: for some reason when i divide by x-1 it fails check this out.\n",
+    "\n",
+    "Okay so now we have a way of checking that a poylnomial == 0 at every point. That we define. Next what we want to do is remove the requirement for the verifier to multiply two polynomials together and check that the results are equal. \n",
+    "\n",
+    "So we avoid this by instead of checking the polynomial at every point we check it at a single random point. So the verifier has polynomial \n",
+    "\n",
+    "$f(x)$ and $h(x)*z(x)$ so what we do is generate a random number (rand) and evaluate $f(x)$ and $h(x)$ , $z(x)$ at rant then we assert that $f(rand) == h(rand) * z(rand)$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rand = hash(str(fx))\n",
+    "assert(polynomial_eval_prime(fx,rand,p) == polynomial_eval_prime(zx, rand, p) * polynomial_eval_prime(hx, rand, p))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Turns out that this is the case for the majority of points on fx , zx and hx. Becuase we generate the rand point to evaluate fx we will only know that after it is created. So an attacker would have to spend a very long time to try and generate a random number that passes the test. So the the thinking is that this is enough to secure plonk and only check a single point. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part x: Polynomial commitments\n",
+    "\n",
+    "Okay so now we have succinct verification but these polynomials are really big. Here we will use polynomial commitments so that povers only need to commmit to their polynomials and open them at random points in order to convince a verifier. \n",
+    "\n",
+    "So we have a polynomial p = [5, 0, 2, 1] which is the same as $x^3 + 2x^2 + 0x + 5$ and we want to commit to it such that the commiter can open it at any point and convince a verifier that this is correct opening. \n",
+    "\n",
+    "So the first thing we are going to do is find a secret point that we will evaluate all our polynomials at. This secret point will be generated using a trusted setup. \n",
+    "\n",
+    "So to evaluate a polynomial we need to have a list of points x such that $(x , x^2, x^3, x^4 ... x^n)$\n",
+    "\n",
+    "So we can easily evaluate these by taking a point in g_1 and multiplying it by $secret^n$ for n in range(1,n) where n is the length of the polynomial we want to commit to."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from py_ecc.bn128.bn128_curve import multiply, add, G1, G2 , FQ, neg\n",
+    "from py_ecc.bn128.bn128_pairing import pairing\n",
+    "\n",
+    "from plonk.poly_commit import powers_of_tau\n",
+    "poly = [5,0,2,1]\n",
+    "secret = 1234\n",
+    "g1, g2 = powers_of_tau(secret, len(poly))\n",
+    "\n",
+    "assert(g1 == [(1, 2), (5240721337203810155063577104887775964429040310352786870634285698927658009894, 8895618777946819312582035270689922760507554319433213576472857911545059134563), (6948375176493266981514273412529490307784532661099513628234608095184316458902, 18216600908385678342586247701838651916221324115124034844476606797464062286560), (13938208764793520230672803096399331546637544056917425701048277721869383690071, 17643137528866430994062863932942240127918427471357794446875411188797842000191), (11205499023060593757170025183462743313595252573361076357571209373922074319500, 10574276079570991118618272977314811771918167997289361521559698253334912778879)])\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay so now we need to evaluate our polynomial at this point "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plonk.poly_commit import poly_commit\n",
+    "p_commit = poly_commit(poly, g1)\n",
+    "\n",
+    "assert(p_commit == (12751843803001521458487166996489945844735054316365547347615166726833607096115, 2774159934330533841376375186873158845895081394785984945802820943066298465301))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay so now we have evaluated our polynomial at a secret point. This we call the polynomial commitment. But how do we evaluate it at an arbitary point? \n",
+    "\n",
+    "So we use a subtract and divide trick to do this we say \n",
+    "\n",
+    "$\\frac{p(secret) - a}{secret - z} = q(secret)$\n",
+    "\n",
+    "Where a is the result when we evaluate p at z. Two problems present themselves \n",
+    "1. Secret is secret so how can't we evaluate the denomiator \n",
+    "2. We have to ensure that q(x) is a polynomial with no remainder.\n",
+    "\n",
+    "We can easily solve 2 by using the commit and open trick from above. Where we commit to all polynomials and then AFTER that evaluate it at a single point. This means that if the points match with overwhelming probability the two polynomials are the same. \n",
+    "\n",
+    "We can solve 1 by doing the evaluation in the exponent of the pairing. So when we did our trusted setup we evaluated g1 which is the powers of all the x terms in the polynomial. So lets take a look at what we can do with pairings. First we can do homomorphic operations\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from py_ecc.bn128.bn128_curve import multiply, add, G1, G2 , FQ, neg\n",
+    "from py_ecc.bn128.bn128_pairing import pairing\n",
+    "\n",
+    "\n",
+    "secret_1 = 1232\n",
+    "secret_2 = 123123\n",
+    "g_1 = multiply(G1,secret_1)\n",
+    "g_2 = multiply(G2,secret_2)\n",
+    "\n",
+    "res = pairing(g_2, g_1)\n",
+    "\n",
+    "g_1 = multiply(G1,secret_2)\n",
+    "g_2 = multiply(G2,secret_1)\n",
+    "\n",
+    "# we flip it and it still equals its homomorphic. \n",
+    "assert(res == pairing(g_2, g_1))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Secondly we can encrypt variables such that you don't need to know them to compute with them. So what I can do is take g_2 and share that with someone. Everyone can then calculate g_1 time g_2 but they will never know what secret_2 is. That is what we need to do here. So during our trusted setup we calculate `g_2` which is a `g_2` generator times a secret and once we throw away the secret there is not way to find the secret again. \n",
+    "\n",
+    "Okay lets evaluate the polynomial `p` at a randome x using the polynomial commitment to check it. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "\n",
+    "g1, g2 = powers_of_tau(1234, len(poly))\n",
+    "\n",
+    "poly = [5,0,2,1]\n",
+    "p_commit = poly_commit(poly, g1)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We want to evaluate this where z = 6 so lets evaluate the result of the polynomial at that point. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plonk.fft.fft import polynomial_eval_prime\n",
+    "\n",
+    "z = [6]\n",
+    "z_commit = poly_commit(z,g2)\n",
+    "print(p)\n",
+    "a = polynomial_eval_prime(poly, 6, p)\n",
+    "a = [a]\n",
+    "a_commit = poly_commit(a, g1)\n",
+    "\n",
+    "# q = p /  [-a,1]\n",
+    "# todo use fft division from above to do this\n",
+    "\n",
+    "q = [48,8,1]\n",
+    "q_commit = poly_commit(q, g1)\n",
+    "\n",
+    "# this is the polynomial 0 + x\n",
+    "x = [0, 1]\n",
+    "x_commit = poly_commit(x, g2)\n",
+    "\n",
+    "\n",
+    "# evaluate the polynomials\n",
+    "# p - a = q*(x-z)\n",
+    "p = field.SNARK_SCALAR_FIELD\n",
+    "\n",
+    "lhs = polynomial_eval_prime(poly,z[0],p) - polynomial_eval_prime(a,z[0],p)\n",
+    "rhs =  polynomial_eval_prime(q,z[0],p) * (polynomial_eval_prime(x,z[0],p) - z[0])\n",
+    "\n",
+    "assert(lhs == rhs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay when we evaluate the polynomial it works but lets use the pairing check."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lhs = pairing(G2, add(p_commit,neg(a_commit)))\n",
+    "rhs = pairing(add(x_commit,neg(z_commit)), q_commit)\n",
+    "\n",
+    "assert(lhs == rhs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "TODO: Go a little slower here for the last step. Possibly break it out into calculating a, q, x , z and then do the pairing check. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part x: Putting it all together\n",
+    "Okay lets list the prover work , the verifier work and the setup work.\n",
+    "\n",
+    "### SETUP: \n",
+    "\n",
+    "#### Gate constraint\n",
+    "\n",
+    "#### Copy constraint\n",
+    "\n",
+    "### Prover:\n",
+    "\n",
+    "#### Gate constaints\n",
+    "a, b ,c polynomial\n",
+    "\n",
+    "#### copy constraints\n",
+    "\n",
+    "#### polynomial commitment openings\n",
+    "\n",
+    "### Verifier:\n",
+    "\n",
+    "TODO: change zx to be the roots of unity version and not the naive (x-1)(x-2) this will make the zx polynoiail small and easy to verifiy. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Part x: Bounties\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here are a bunch fo follow on ideas, the bounty is to add another section to this tutorial explaining the following\n",
+    "\n",
+    "1. Fix some TODOs\n",
+    "2. Implement plookup\n",
+    "3. Implement range proofs for plonk\n",
+    "4. Implement build programming language on top of this\n",
+    "5. Explore custom constraints \n",
+    "6. There are a few security bugs in what we have implemented so far. Can you find them / fix them?\n",
+    "7. Build semaphore on top of this\n",
+    "\n",
+    "TODO: Find out about adding bounties or rewards to these tasks. "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk/__init__.py b/content/1-Cryptography/materials/plonk-activity/plonk/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk/constraint.py b/content/1-Cryptography/materials/plonk-activity/plonk/constraint.py
new file mode 100644
index 00000000..74a2edc9
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/plonk/constraint.py
@@ -0,0 +1,40 @@
+def constraint_polynomial(Qli, Qri, Qmi, Qoi, Qci, ai, bi, ci):
+    return Qli * ai + Qri * bi + Qoi * ci + Qmi * ai * bi + Qci == 0
+
+
+def is_satisfied(Ql, Qr, Qm, Qo, Qc, a, b, c):
+    for Qli, Qri, Qmi, Qoi, Qci, ai, bi, ci in zip(Ql, Qr, Qm, Qo, Qc, a, b, c):
+        if constraint_polynomial(Qli, Qri, Qmi, Qoi, Qci, ai, bi, ci) == False:
+            return False
+    return True
+
+
+def add_add_constarint(Ql, Qr, Qm, Qo, Qc):
+    Ql.append(1)
+    Qr.append(1)
+    Qm.append(0)
+    Qo.append(-1)
+    Qc.append(0)
+    return (Ql, Qr, Qm, Qo, Qc)
+
+
+def add_mul_constarint(Ql, Qr, Qm, Qo, Qc):
+
+    Ql.append(0)
+    Qr.append(0)
+    Qm.append(1)
+    Qo.append(-1)
+    Qc.append(0)
+
+    return (Ql, Qr, Qm, Qo, Qc)
+
+
+def add_constant_constraint(Ql, Qr, Qm, Qo, Qc, const):
+
+    Ql.append(0)
+    Qr.append(0)
+    Qm.append(1)
+    Qo.append(0)
+    Qc.append(-const)
+
+    return (Ql, Qr, Qm, Qo, Qc)
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk/copy_constraint.py b/content/1-Cryptography/materials/plonk-activity/plonk/copy_constraint.py
new file mode 100644
index 00000000..2ac274a2
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/plonk/copy_constraint.py
@@ -0,0 +1,24 @@
+from .poly import lagrange, polynomial_eval
+
+
+def copy_constraint_simple(eval_domain, Xcoef, Ycoef, v1, v2):
+    Px = [1]
+    Y = []
+    rlc = []
+    x = []
+
+    for i in range(0, len(eval_domain)):
+        x.append(polynomial_eval(Xcoef, eval_domain[i]))
+        Y.append(polynomial_eval(Ycoef, x[i]))
+
+        rlc.append(v1 + x[i] + v2 * Y[i])
+        Px.append(Px[i] * (v1 + x[i] + v2 * Y[i]))
+
+    return (x, Y, Px, rlc)
+
+
+def find_permutation(copies, eval_domain):
+
+    perm = lagrange(eval_domain, copies)
+    perm = [float(x) for x in reversed(perm.coefficients)]
+    return perm
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk/fft/__init__.py b/content/1-Cryptography/materials/plonk-activity/plonk/fft/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk/fft/fft.py b/content/1-Cryptography/materials/plonk-activity/plonk/fft/fft.py
new file mode 100644
index 00000000..02d127ed
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/plonk/fft/fft.py
@@ -0,0 +1,80 @@
+#!/usr/bin/env sage -python
+
+import pdb
+from ethsnarks.numbertheory import inverse_mod
+
+from ethsnarks import field
+
+p = field.FQ(field.SNARK_SCALAR_FIELD).n
+
+
+def roots_of_unity(order):
+    a = field.FQ(5)
+    p = field.FQ(field.SNARK_SCALAR_FIELD)
+    return [a ** (i * (p - 1) / order) for i in range(order)]
+
+
+def polynomial_eval_prime(coef, x, p, step_size=1, start_power=0):
+    res = []
+    power = x ** start_power
+    for i in coef:
+        res.append((i * power))
+        power = power * x ** step_size
+    return sum(res) % p
+
+
+def sub_group(p, g):
+    domain = [1]
+    g_ = g
+    while g_ != 1:
+        g_ = g_ * g % p
+        domain.append(g_)
+
+
+def fft(p, domain, poly):
+
+    if len(poly) == 1:
+        return poly
+
+    p_even = poly[::2]
+    p_odd = poly[1::2]
+    domain_positive = domain[::2]
+
+    L = fft(p, domain_positive, p_even)
+
+    R = fft(p, domain_positive, p_odd)
+
+    p_x = []
+    p_x_minus_1 = []
+
+    for i, (x, y) in enumerate(zip(L, R)):
+
+        y_times_root = y * domain[i].n
+
+        p_x.append((x + y_times_root) % p)
+        p_x_minus_1.append((x - y_times_root) % p)
+
+    result = [str(x) + str(y) for x, y in zip(p_x, p_x_minus_1)]
+
+    return p_x + p_x_minus_1
+
+
+def ifft(p, domain, evaluation):
+    vals = fft(p, domain, evaluation)
+
+    return [x * inverse_mod(len(vals), p) % p for x in [vals[0]] + vals[1:][::-1]]
+
+
+def fft_div(poly1, poly2):
+    domain = roots_of_unity(4)
+    print(max(len(poly1), len(poly2)))
+    print(domain)
+    poly1_fs = fft(p, domain, poly1)
+    poly2_fs = fft(p, domain, poly2)
+    res = []
+    for x, y in zip(poly1_fs, poly2_fs):
+        x = field.FQ(x)
+        y = field.FQ(y)
+        res.append((x / y).n)
+    res = ifft(p, domain, res)
+    return res
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk/plonk.py b/content/1-Cryptography/materials/plonk-activity/plonk/plonk.py
new file mode 100644
index 00000000..dcde1cec
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/plonk/plonk.py
@@ -0,0 +1,62 @@
+from .poly import gen_poly
+from .constraint import is_satisfied
+from .copy_constraint import copy_constraint_simple
+import pdb
+
+
+def verify_naieve(Ql, Qr, Qm, Qo, Qc, a, b, c, witness_y, perm_a, perm_b, perm_c):
+
+    # make sure constarints + witness is statisfied
+    assert is_satisfied(Ql, Qr, Qm, Qo, Qc, a, b, c) == True
+
+    # original polynomial
+
+    Xcoef = [0, 1]
+
+    # todo: replace with random
+
+    v1 = hash(str(a + b + c))
+    v2 = hash(str(c + a + b))
+
+    eval_domain = range(0, len(a) * 3)
+
+    x, Y, Px_a, rlc = copy_constraint_simple(range(0, len(a)), Xcoef, witness_y, v1, v2)
+    x, Y, Px_b, rlc = copy_constraint_simple(
+        range(len(a), len(a) * 2), Xcoef, witness_y, v1, v2
+    )
+    x, Y, Px_c, rlc = copy_constraint_simple(
+        range(len(a) * 2, len(a) * 3), Xcoef, witness_y, v1, v2
+    )
+
+    # calcualte permutated polynomial
+    x_1, Y_1, Px_a_prime, rlc_1 = copy_constraint_simple(
+        range(0, len(a)), perm_a, witness_y, v1, v2
+    )
+    x_1, Y_1, Px_b_prime, rlc_1 = copy_constraint_simple(
+        range(len(a), len(a) * 2), perm_b, witness_y, v1, v2
+    )
+    x_1, Y_1, Px_c_prime, rlc_1 = copy_constraint_simple(
+        range(len(a) * 2, len(a) * 3), perm_c, witness_y, v1, v2
+    )
+
+    assert (
+        Px_a[-1] * Px_b[-1] * Px_c[-1]
+        == Px_a_prime[-1] * Px_b_prime[-1] * Px_c_prime[-1]
+    )
+    assert (
+        Px_a[0]
+        == Px_b[0]
+        == Px_c[0]
+        == Px_a_prime[0]
+        == Px_b_prime[0]
+        == Px_c_prime[0]
+        == 1
+    )
+    # todo public input check
+
+
+def create_proof(a, b, c):
+
+    poly = gen_poly(a + b + c)
+
+    return (a, b, c, poly)
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk/poly.py b/content/1-Cryptography/materials/plonk-activity/plonk/poly.py
new file mode 100644
index 00000000..c73b3389
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/plonk/poly.py
@@ -0,0 +1,29 @@
+from scipy.interpolate import lagrange
+
+
+def polynomial_eval(coef, x):
+    res = []
+    power = 1
+    for i in coef:
+        res.append(i * power)
+        power = power * x
+    return round(sum(res))
+
+
+def polynomial_division(poly, q):
+    result = []
+    for i in reversed(range(0, len(poly))):
+        factor = poly[i] / q[-1]
+        result.append(factor)
+        poly[i] = poly[i] - (factor * q[-1])
+        poly[i - 1] = poly[i - 1] - (q[0] * factor)
+        if sum(poly) == 0:
+            return (True, result)
+    return (False, result)
+
+
+def gen_poly(y):
+    x = range(0, len(y))
+    poly = lagrange(x, y)
+    poly = [float(x) for x in reversed(poly.coefficients)]
+    return poly
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk/poly_commit.py b/content/1-Cryptography/materials/plonk-activity/plonk/poly_commit.py
new file mode 100644
index 00000000..55298da8
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/plonk/poly_commit.py
@@ -0,0 +1,24 @@
+from py_ecc.bn128.bn128_curve import multiply, add, G1, G2, FQ, neg
+from py_ecc.bn128.bn128_pairing import pairing
+
+
+def powers_of_tau(_secret, depth):
+    g_1 = [G1]
+    g_2 = [G2, multiply(G2, _secret)]
+    secret = _secret
+    for i in range(0, depth):
+        g_1.append(multiply(G1, secret))
+        secret = secret * _secret
+    return (g_1, g_2)
+
+
+def poly_commit(poly, g):
+    res = None
+    for i, x in enumerate(poly):
+        # deal with negitive numbers
+        if (x) < 0:
+            x = x * -1
+            res = add(res, neg(multiply(g[i], x)))
+        else:
+            res = add(res, multiply(g[i], x))
+    return res
diff --git a/content/1-Cryptography/materials/plonk-activity/plonk/sample_problem.py b/content/1-Cryptography/materials/plonk-activity/plonk/sample_problem.py
new file mode 100644
index 00000000..b124198d
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/plonk/sample_problem.py
@@ -0,0 +1,67 @@
+from .copy_constraint import find_permutation
+from .constraint import add_mul_constarint, add_add_constarint, add_constant_constraint
+
+
+def gen_witness(x):
+    a = [x, x * x, x * x * x, 1, 1, x * x * x + x]
+    b = [x, x, x, 5, 35, 5]
+    c = [x * x, x * x * x, x + x * x * x, 5, 35, 35]
+
+    return (a, b, c)
+
+
+def is_satisfied_witness(a, b, c):
+    assert a[0] * b[0] == c[0]
+    assert a[1] * b[1] == c[1]
+    assert a[2] + b[2] == c[2]
+    assert a[3] * b[3] == c[3]
+    assert a[4] * b[4] == c[4]
+    assert a[5] + b[5] == c[5]
+
+
+def gen_constraints():
+    # Prove that I know an X such that X*x*x + x +5 == 35
+
+    # init constraints
+    Ql = []
+    Qr = []
+    Qm = []
+    Qo = []
+    Qc = []
+
+    # set constraints
+    Ql, Qr, Qm, Qo, Qc = add_mul_constarint(Ql, Qr, Qm, Qo, Qc)
+    Ql, Qr, Qm, Qo, Qc = add_mul_constarint(Ql, Qr, Qm, Qo, Qc)
+    Ql, Qr, Qm, Qo, Qc = add_add_constarint(Ql, Qr, Qm, Qo, Qc)
+    Ql, Qr, Qm, Qo, Qc = add_constant_constraint(Ql, Qr, Qm, Qo, Qc, 5)
+    Ql, Qr, Qm, Qo, Qc = add_constant_constraint(Ql, Qr, Qm, Qo, Qc, 35)
+    # todo add a constant constraint for 1
+    Ql, Qr, Qm, Qo, Qc = add_add_constarint(Ql, Qr, Qm, Qo, Qc)
+    return (Ql, Qr, Qm, Qo, Qc)
+
+
+def gen_copy_constraints():
+    # copy constraints
+    # a = [x , x*x, x*x*x, 1,  1, x*x*x + x]
+    # b = [x , x, x, 5, 35, 5]
+    # c = [x*x, x*x*x , x + x*x*x ,5, 35, 35]
+    # inputs  = [x , x*x, x*x*x, 1,  1,
+    #           x*x*x + x, x , x, x, 5, 35, 5
+    #           x*x, x*x*x , x + x*x*x ,5, 35, 35]
+
+    copy_constraints = [8, 12, 13, 3, 4, 14, 0, 6, 7, 15, 17, 9, 1, 2, 5, 11, 10, 16]
+
+    eval_domain = range(0, len(copy_constraints))
+
+    x_a_prime = find_permutation(copy_constraints[0:6], eval_domain[0:6])
+    x_b_prime = find_permutation(copy_constraints[6:12], eval_domain[6:12])
+    x_c_prime = find_permutation(copy_constraints[12:18], eval_domain[12:18])
+
+    return (x_a_prime, x_b_prime, x_c_prime, copy_constraints)
+
+
+def setup():
+    Ql, Qr, Qm, Qo, Qc = gen_constraints()
+    perm_x, perm_y, perm_z, copy_constraints = gen_copy_constraints()
+
+    return (Ql, Qr, Qm, Qo, Qc, perm_x, perm_y, perm_z, copy_constraints)
diff --git a/content/1-Cryptography/materials/plonk-activity/setup.py b/content/1-Cryptography/materials/plonk-activity/setup.py
new file mode 100644
index 00000000..aa845689
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/setup.py
@@ -0,0 +1,25 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+from setuptools import setup, find_packages
+
+
+setup(
+    name="plonk",
+    version="0.0.1",
+    description="Python implementation for PLONK",
+    python_requires=">=3.6,<4",
+    install_requires=["py_ecc==1.4.0", "ethsnarks==0.0.1", "scipy>=1.4.1",],
+    extras_require={
+        "test": ["pytest>=5,<6", "nbval>=0.9.5"],
+        "lint": ["black>=19.10b0"],
+        "tutorial": ["jupyter>=1.0.0"],
+    },
+    packages=find_packages(exclude=["tests", "*.ipynb"]),
+    classifiers=[
+        "Development Status :: 3 - Alpha",
+        "Intended Audience :: Developers",
+        "License :: OSI Approved :: MIT License",
+        "Natural Language :: English",
+        "Programming Language :: Python :: 3.6",
+    ],
+)
diff --git a/content/1-Cryptography/materials/plonk-activity/tests/test_constraint.py b/content/1-Cryptography/materials/plonk-activity/tests/test_constraint.py
new file mode 100644
index 00000000..701c93de
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/tests/test_constraint.py
@@ -0,0 +1,142 @@
+from plonk.constraint import add_add_constarint, is_satisfied, add_mul_constarint
+from plonk.copy_constraint import copy_constraint_simple, find_permutation
+from plonk.sample_problem import gen_witness, setup
+from plonk.plonk import create_proof, verify_naieve
+from plonk.poly import polynomial_division, polynomial_eval
+
+
+def test_addition():
+    # constraints
+    Ql = []
+    Qr = []
+    Qm = []
+    Qo = []
+    Qc = []
+
+    Ql, Qr, Qm, Qo, Qc = add_add_constarint(Ql, Qr, Qm, Qo, Qc)
+
+    # witness
+    a = [0]
+    b = [1]
+    c = [1]
+
+    assert is_satisfied(Ql, Qr, Qm, Qo, Qc, a, b, c) == True
+
+
+def test_mul():
+
+    # constraints
+    Ql = []
+    Qr = []
+    Qm = []
+    Qo = []
+    Qc = []
+
+    Ql, Qr, Qm, Qo, Qc = add_mul_constarint(Ql, Qr, Qm, Qo, Qc)
+
+    # witness
+    a = [1]
+    b = [1]
+    c = [1]
+
+    assert is_satisfied(Ql, Qr, Qm, Qo, Qc, a, b, c) == True
+
+
+def test_constant_mul():
+
+    # constraints
+    Ql = [0]
+    Qr = [0]
+    Qm = [1]
+    Qo = [0]
+    Qc = [-10]
+
+    # witness
+    a = [10]
+    b = [1]
+    c = [10]
+
+    assert is_satisfied(Ql, Qr, Qm, Qo, Qc, a, b, c) == True
+
+
+def test_constant_add():
+    # constraints
+    Ql = [1]
+    Qr = [1]
+    Qm = [0]
+    Qo = [0]
+    Qc = [-10]
+
+    # witness
+    a = [10]
+    b = [0]
+    c = [10]
+
+    assert is_satisfied(Ql, Qr, Qm, Qo, Qc, a, b, c) == True
+
+
+def test_polynomial_eval():
+    x = [1]
+    assert polynomial_eval([1, 1, 1], 2) == 7
+    assert polynomial_eval([-2, 7, -5, 1], 0) == -2
+    assert polynomial_eval([-2, 7, -5, 1], 1) == 1
+    assert polynomial_eval([-2, 7, -5, 1], 2) == 0
+    assert polynomial_eval([-2, 7, -5, 1], 3) == 1
+
+
+def test_copy_constraint_simple():
+    Ycoef = [-2, 7, -5, 1]
+    eval_domain = [0, 1, 2, 3]
+    # y =     0 + 1x
+    Xcoef = [0, 1]
+
+    v1 = 3
+    v2 = 2
+
+    x, Y, Px_1, rlc = copy_constraint_simple(eval_domain, Xcoef, Ycoef, v1, v2)
+
+    copies = [0, 3, 2, 1]
+
+    Xcoef = find_permutation(copies, eval_domain)
+
+    eval_domain = [0, 1, 2, 3]
+
+    x, Y, Px, rlc = copy_constraint_simple(eval_domain, Xcoef, Ycoef, v1, v2)
+
+    assert Px_1[4] == Px[4]
+
+
+def test_setup_prove_verify():
+    Ql, Qr, Qm, Qo, Qc, perm_a, perm_b, perm_c, copy_constraints = setup()
+    a, b, c = gen_witness(3)
+    assert is_satisfied(Ql, Qr, Qm, Qo, Qc, a, b, c)
+
+    x, x, x, poly = create_proof(a, b, c)
+
+    verify_naieve(Ql, Qr, Qm, Qo, Qc, a, b, c, poly, perm_a, perm_b, perm_c)
+
+
+def test_polynomial_division():
+    poly = [5 - 293, 0, 2, 1]
+    q = [-6, 1]
+
+    for i in range(0, 1000):
+        if polynomial_eval(poly, i) == 293:
+            print(i)
+            break
+
+    flag, result = polynomial_division(poly, q)
+    assert flag
+    assert result == [1.0, 8.0, 48.0]
+
+
+def test_permutation():
+
+    witness = [3, 9, 27, 1, 1, 30, 3, 3, 3, 5, 35, 5, 9, 27, 30, 5, 35, 35]
+    eval_domain = [i for i in range(0, len(witness))]
+    witness_x_1 = find_permutation(eval_domain, eval_domain)
+
+    witness_y = find_permutation(witness, eval_domain)
+
+    for i, val in enumerate(witness):
+        assert val == polynomial_eval(witness_y, i)
diff --git a/content/1-Cryptography/materials/plonk-activity/tests/test_fft.py b/content/1-Cryptography/materials/plonk-activity/tests/test_fft.py
new file mode 100644
index 00000000..7940a7c7
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/tests/test_fft.py
@@ -0,0 +1,121 @@
+from plonk.fft.fft import polynomial_eval_prime, fft, ifft
+from ethsnarks.field import FQ
+
+
+def test_polynomial_eval_prime():
+    assert polynomial_eval_prime([3, 0, 1], 0, 5) == 3
+    assert polynomial_eval_prime([3, 0, 1], 1, 5) == 4
+    assert polynomial_eval_prime([3, 0, 1], 2, 5) == 2
+
+
+def test_mul_poly():
+    # (x + 1) **2
+    a = [1, 1, 0, 0, 0, 0, 0, 0]
+    b = [1, 1, 0, 0, 0, 0, 0, 0]
+    domain = [FQ(i) for i in [1, 85, 148, 111, 336, 252, 189, 226]]
+    p = 337
+
+    a_fft = fft(p, domain, a)
+    b_fft = fft(p, domain, b)
+    c = [a * b for a, b in zip(a_fft, b_fft)]
+
+    res = ifft(p, domain, c)
+    assert res == [1, 2, 1, 0, 0, 0, 0, 0]
+
+
+def test_mul():
+    a = [3, 5, 2, 1, 0, 0, 0, 0]
+    b = [5, 9, 8, 1, 0, 0, 0, 0]
+    domain = [FQ(i) for i in [1, 85, 148, 111, 336, 252, 189, 226]]
+    p = 337
+
+    a_fft = fft(p, domain, a)
+    b_fft = fft(p, domain, b)
+
+    a_b_fft = [a * b for a, b in zip(a_fft, b_fft)]
+    res = ifft(p, domain, a_b_fft)
+    for i, x in enumerate(res):
+        res[i] = x % 10
+        if int(x / 10) != 0:
+            res[i + 1] += int(x / 10)
+
+    assert res == [5, 3, 4, 4, 7, 3, 2, 0]
+
+
+def test_fft():
+    p = 337
+    _domain = [1, 85, 148, 111, 336, 252, 189, 226]
+    domain = [FQ(i) for i in _domain]
+    poly = [3, 1, 4, 1, 5, 9, 2, 6]
+    result = []
+
+    p_x = fft(p, domain, poly)
+
+    for x in _domain:
+        result.append(polynomial_eval_prime(poly, x, p, 1, 0))
+
+    assert p_x == result
+
+
+def test_ifft():
+    p = 337
+    domain = [FQ(i) for i in [1, 85, 148, 111, 336, 252, 189, 226]]
+    poly = [3, 1, 4, 1, 5, 9, 2, 6]
+    result = []
+
+    p_x = fft(p, domain, poly)
+
+    result = ifft(p, domain, p_x)
+
+    assert result == poly
+
+
+def test_constant_add():
+    a = [1, 1, 0, 0, 0, 0, 0, 0]
+    b = [1, 1, 0, 0, 0, 0, 0, 0]
+    domain = [FQ(i) for i in [1, 85, 148, 111, 336, 252, 189, 226]]
+    p = 337
+
+    constant = 330
+
+    a_fft = fft(p, domain, a)
+    b_fft = fft(p, domain, b)
+    c = [a * b for a, b in zip(a_fft, b_fft)]
+
+    c = [a + constant for a in c]
+
+    res = ifft(p, domain, c)
+
+    assert res == [331, 2, 1, 0, 0, 0, 0, 0]
+
+
+def test_poly_add():
+    a = [1, 1, 0, 0, 0, 0, 0, 0]
+    b = [1, 1, 0, 0, 0, 0, 0, 0]
+    domain = [FQ(i) for i in [1, 85, 148, 111, 336, 252, 189, 226]]
+    p = 337
+
+    a_fft = fft(p, domain, a)
+    b_fft = fft(p, domain, b)
+    c = [a * b for a, b in zip(a_fft, b_fft)]
+
+    c = [a + b for a, b in zip(c, a_fft)]
+
+    res = ifft(p, domain, c)
+
+    assert res == [2, 3, 1, 0, 0, 0, 0, 0]
+
+
+def test_degree_reduction():
+    a = [1, 0, 0, 0, 0, 0, 0, 1]
+    b = [0, 1, 0, 0, 0, 0, 0, 0]
+    domain = [FQ(i) for i in [1, 85, 148, 111, 336, 252, 189, 226]]
+    p = 337
+
+    a_fft = fft(p, domain, a)
+    b_fft = fft(p, domain, b)
+    c = [a * b for a, b in zip(a_fft, b_fft)]
+
+    res = ifft(p, domain, c)
+
+    assert res == [1, 1, 0, 0, 0, 0, 0, 0]
diff --git a/content/1-Cryptography/materials/plonk-activity/tests/test_ploy_commit.py b/content/1-Cryptography/materials/plonk-activity/tests/test_ploy_commit.py
new file mode 100644
index 00000000..f0d1140c
--- /dev/null
+++ b/content/1-Cryptography/materials/plonk-activity/tests/test_ploy_commit.py
@@ -0,0 +1,71 @@
+from plonk.poly_commit import poly_commit, powers_of_tau
+from plonk.poly import polynomial_eval
+from py_ecc.bn128.bn128_curve import multiply, add, G1, G2, FQ, neg
+from py_ecc.bn128.bn128_pairing import pairing
+
+
+def test_poly_commit():
+
+    p = [5, 0, 2, 1]
+
+    g1, g2 = powers_of_tau(1234, len(p))
+
+    a = [293]
+    a_commit = poly_commit(a, g1)
+
+    p_commit = poly_commit(p, g1)
+    q = [48, 8, 1]
+
+    q_commit = poly_commit(q, g1)
+
+    x = [0, 1]
+
+    x_commit = poly_commit(x, g2)
+
+    z = [6]
+    z_commit = poly_commit(z, g2)
+
+    # evaluate the polynomials
+    # p - a = q*(x-z)
+
+    lhs = polynomial_eval(p, z[0]) - polynomial_eval(a, z[0])
+    rhs = polynomial_eval(q, z[0]) * (polynomial_eval(x, z[0]) - z[0])
+
+    assert lhs == rhs
+
+    lhs = pairing(G2, add(p_commit, neg(a_commit)))
+    rhs = pairing(add(x_commit, neg(z_commit)), q_commit)
+
+    assert lhs == rhs
+
+
+def test_mul():
+    secret_1 = 1232
+    secret_2 = 123123
+
+    a = multiply(G1, secret_1)
+    a = multiply(a, secret_2)
+
+    b = multiply(G1, secret_2)
+    b = multiply(b, secret_1)
+
+    ## its homomorphic
+    assert a == b
+
+
+def test_pairing():
+    secret_1 = 1232
+    secret_2 = 123123
+
+    g_1 = multiply(G1, secret_1)
+
+    g_2 = multiply(G2, secret_2)
+
+    res = pairing(g_2, g_1)
+
+    g_1 = multiply(G1, secret_2)
+
+    g_2 = multiply(G2, secret_1)
+
+    # we flip it and it still equals its homomorphic.
+    assert res == pairing(g_2, g_1)
diff --git a/content/1-Cryptography/materials/signature-demo.ipynb b/content/1-Cryptography/materials/signature-demo.ipynb
new file mode 100644
index 00000000..7d7acd40
--- /dev/null
+++ b/content/1-Cryptography/materials/signature-demo.ipynb
@@ -0,0 +1,583 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    },
+    "tags": []
+   },
+   "source": [
+    "# Signing Demo for Web3 Engineers"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## \\[Note on use\\] Reset, keeping build artifacts\n",
+    "\n",
+    "Run the below cell or commands in a shell to \"reset\" the kernel, keeping build artifacts:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"/tmp/.tmp3GYuJy\"\n"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    ":clear // Clear all state, **keeping compilation cache**, use this over a kernel restart when possible. You will need to re-run the :deps to have them loaded into state. \n",
+    ":last_compile_dir // Show where the target is for cargo for this kernel, in case you want to recover these"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Set the env var `EVCXR_TMPDIR=<the output of :last_compile_dir>` to get the REPL to use this dir.\n",
+    "\n",
+    "```sh\n",
+    "# Launching jupyter-lab\n",
+    "EVCXR_TMPDIR=<dir from :last_compile_dir> jupyter-lab\n",
+    "\n",
+    "# Using Evcxr in a shell\n",
+    "EVCXR_TMPDIR=<dir from :last_compile_dir> evcxr\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Notebook Kernel & REPL Environment Setup\n",
+    "\n",
+    "The below should be run at kernel startup before you start.\n",
+    "All dependencies that we need to build _before_ anything else in this notebook will work.\n",
+    "\n",
+    "Instead of rebuilding see the `Reset, keeping build artifacts` section to clear REPL state only.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    ":dep sp-core = { version = \"7.0.0\", git = \"https://github.com/paritytech/substrate.git\", branch = \"polkadot-v0.9.36\" }\n",
+    "\n",
+    "// Loading & building dependencies crates here takes *a while*! \n",
+    "// Run this while you move on to the readings below.\n",
+    "// NOTE: A kernel restart removes all target artifacts!\n",
+    "// ONLY restart only if explicitly needed."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Digital Signatures\n",
+    "\n",
+    "Here we demonstrate a few parts of the [Substrate Primitives (`sp_core`)](https://paritytech.github.io/substrate/master/sp_core/index.html) library for interacting with keys and signatures."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "use sp_core::{\n",
+    "\tblake2_256,\n",
+    "\tcrypto::{Derive, Ss58Codec, Ss58AddressFormatRegistry},\n",
+    "\tDeriveJunction,\n",
+    "\thexdisplay::HexDisplay,\n",
+    "\tPair as _,\n",
+    "\tsr25519::{Pair, Public},\n",
+    "};"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Key Generation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Generate a secret key.\n",
+    "let (pair, mnemonic, _) = Pair::generate_with_phrase(None);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"hawk false thought wife devote close night pizza cabin novel across melt\""
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Reveal your Secret Seed Phrase\n",
+    "mnemonic"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Derive the public key.\n",
+    "let pk = pair.public();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[38, 16, 19, 15, 113, 123, 87, 121, 148, 236, 175, 26, 71, 48, 211, 188, 209, 16, 136, 10, 144, 136, 122, 166, 43, 172, 47, 201, 201, 42, 162, 38]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Print public key as raw bytes\n",
+    "pk.0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2610130f717b577994ecaf1a4730d3bcd110880a90887aa62bac2fc9c92aa226"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Print public key hex encoded \n",
+    "<HexDisplay>::from(&pk.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Signatures"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Sign a message.\n",
+    "let msg = b\"Welcome to Polkadot Blockchain Academy!\";\n",
+    "let sig = pair.sign(&msg[..]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"Welcome to Polkadot Blockchain Academy!\""
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Message:\n",
+    "std::str::from_utf8(&msg[..]).unwrap()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "c6ff39639ec55a975391e222254bac992b2d95cc5393c75444c45bdcb812af04468b549b81c1edbb9c4b06c683353dd23636e2199096553ddb40573c8cd2508d"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Signature, hex encoded:\n",
+    "&sig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Verify the sig. `assert!` will not panic here with a valid sig\n",
+    "assert!(Pair::verify(&sig, &msg[..], &pk));"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Alter the message. `assert!` will panic on msg, here we assert it's fails.\n",
+    "let tampered = b\"Welcome-to-Polkadot-Blockchain-Academy!\";\n",
+    "assert!(!Pair::verify(&sig, &tampered[..], &pk));"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Signing & Hashes\n",
+    "\n",
+    "The signature process can be resource intensive with large data. We can use a *cryptographic hash function* of the data, which is generally a fixed small size and then sign that hash. This signature, the hashing protocol, and the original data is then used to be as valid to us as the signature on the original data without as much resource use.  \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Signing a message hash example, instead of the full msg.\n",
+    "let long_msg =\n",
+    "\tb\"The term \\\"Web3\\\" (AKA Web 3.0) was coined in 2014 by Ethereum co-founder Gavin Wood, is an idea for a new iteration of the World Wide Web which incorporates concepts such as decentralization, blockchain technologies, and token-based economics.\";\n",
+    "let lm_hash = blake2_256(&long_msg[..]);\n",
+    "\n",
+    "let sig_lm_hash = pair.sign(&lm_hash[..]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "652c97cbbae2caeb52556680c55096c6a9e9aca8318461f1cb4e74019833ed32"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Hex print hash & signature\n",
+    "<HexDisplay>::from(&lm_hash)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Verify the signature from the same hash of the original message.\n",
+    "assert!(Pair::verify(&sig_lm_hash, blake2_256(&long_msg[..]), &pk));"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Hard Derivation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Derive new key pairs from the original mnemonic using `//polkadot`.\n",
+    "let pair_polkadot = Pair::from_string(&format!(\"{}//polkadot\", &mnemonic), None);\n",
+    "let pk_polkadot = pair_polkadot.unwrap().public();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "8a780f44284e9b2137ffa1ab94b05ba91cb903976995298e7aab04ed54219956"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Polkadot Public Key, Hex\n",
+    "<HexDisplay>::from(&pk_polkadot.0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"148ZGrDNoUxCXk1SzL8SspRsxqW5Xtb7W9AxkhdhTFgQ7QEy\""
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Polkadot Public Key, SS58 for Polkadot\n",
+    "&pk_polkadot.to_ss58check_with_version(Ss58AddressFormatRegistry::PolkadotAccount.into())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Derive new key pairs from the original mnemonic using `//kusama`.\n",
+    "let pair_kusama = Pair::from_string(&format!(\"{}//kusama\", &mnemonic), None);\n",
+    "let pk_kusama = pair_kusama.unwrap().public();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "fc760ea0f7e45b2c4e1b0624cf953b8de471811a57e73db7514e387e6c78e573"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Kusama Public Key, Hex\n",
+    "<HexDisplay>::from(&pk_kusama.0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"JHLewmVTEEzXwARwCKyFh4syXK98SFUPNQg6YDorRMP3ELx\""
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Kusama Public Key, SS58 for Polkadot\n",
+    "&pk_kusama.to_ss58check_with_version(Ss58AddressFormatRegistry::KusamaAccount.into())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## SS58 Tool\n",
+    "\n",
+    "https://polkadot.subscan.io/tools/ss58_transform\n",
+    "\n",
+    "This handy tool can be used to cross check a raw hex encoded pubkey, and see all SS58 variants for them."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Soft Derivation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Derive a soft path on the Polkadot key.\n",
+    "let pair_polkadot_zero = Pair::from_string(&format!(\"{}//polkadot/0\", &mnemonic), None);\n",
+    "let pk0_from_secret = pair_polkadot_zero.unwrap().public();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"123MSN6RKzp8Ha16LmajgeUKJ58YAhPV2UBhAhR5Yswjv2zg\""
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Polkadot Soft-Derived Public Key (from secret)\n",
+    "&pk0_from_secret.to_ss58check_with_version(Ss58AddressFormatRegistry::PolkadotAccount.into())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Derive a soft path only using the _public key_ of the //polkadot pair.\n",
+    "let pk_polkadot: Public = Public(pk_polkadot.0);\n",
+    "let path0 = vec![DeriveJunction::soft(0u8)];\n",
+    "let pk0_from_public = pk_polkadot.derive(path0.into_iter()).unwrap();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"123MSN6RKzp8Ha16LmajgeUKJ58YAhPV2UBhAhR5Yswjv2zg\""
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Polkadot Soft-Derived Public Key (from public only)\n",
+    "&pk0_from_public.to_ss58check_with_version(Ss58AddressFormatRegistry::PolkadotAccount.into())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "()"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "// Keys are identical.\n",
+    "assert_eq!(pk0_from_secret, pk0_from_public)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Rust",
+   "language": "rust",
+   "name": "rust"
+  },
+  "language_info": {
+   "codemirror_mode": "rust",
+   "file_extension": ".rs",
+   "mimetype": "text/rust",
+   "name": "rust",
+   "pygment_lexer": "rust",
+   "version": ""
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/content/1-Cryptography/materials/subkey-demo.md b/content/1-Cryptography/materials/subkey-demo.md
new file mode 100644
index 00000000..ea17db52
--- /dev/null
+++ b/content/1-Cryptography/materials/subkey-demo.md
@@ -0,0 +1,122 @@
+# Subkey Signature and HDKD (Hierarchical Deterministic Key Derivation) Demo
+
+All the subkey examples also exist in [a jupyter notebook](./signature-demo.ipynb) for reference.
+As an alternative, here are subkey examples to compliment/replace using the REPL.
+
+## Key Generation
+
+```sh
+subkey generate
+
+Secret phrase: s      desert piano add owner tuition tail melt rally height faint thunder immune
+  Network ID:        substrate
+  Secret seed:       0x6a0ea68072cfd0ffbabb40801570fa5e9f3a88966eaed9dedaeb0cf140b9cd8d
+  Public key (hex):  0x7acdc47530002fbc50f413859093b7df90c27874aee732dca940ea4842751d58
+  Account ID:        0x7acdc47530002fbc50f413859093b7df90c27874aee732dca940ea4842751d58
+  Public key (SS58): 5Eqipnpt5asTm7sCFWQeJjsNJX5cYVJMid3zjKHjDUGKBJTo
+  SS58 Address:      5Eqipnpt5asTm7sCFWQeJjsNJX5cYVJMid3zjKHjDUGKBJTo
+```
+
+## Sign
+
+```sh
+echo -n 'Hello Polkadot Blockchain Academy' | subkey sign --suri 'desert piano add owner tuition tail melt rally height faint thunder immune'
+```
+
+> Note, this changes each execution, this is one viable signature: `f261d56b80e4b53c70dd2ba1de6b9384d85a8f4c6d912fd86acab3439a47992aa85ded04ac55c7525082dcbc815001cd5cc94ec1a907bbd8e3138cfc8a382683`
+
+## Verify
+
+```sh
+echo -n 'Hello Polkadot Blockchain Academy' | subkey verify  '0xf261d56b80e4b53c70dd2ba1de6b9384d85a8f4c6d912fd86acab3439a47992aa85ded04ac55c7525082dcbc815001cd5cc94ec1a907bbd8e3138cfc8a382683' \
+    '0x7acdc47530002fbc50f413859093b7df90c27874aee732dca940ea4842751d58'
+```
+
+> Expect `Signature verifies correctly.`
+
+## Tamper with the Message
+
+> Last char in `Public key (hex)` - AKA URI - is changed:
+
+```sh
+echo -n 'Hello Polkadot Blockchain Academy' | subkey verify \
+ '0xf261d56b80e4b53c70dd2ba1de6b9384d85a8f4c6d912fd86acab3439a47992aa85ded04ac55c7525082dcbc815001cd5cc94ec1a907bbd8e3138cfc8a382683' \
+    '0x7acdc47530002fbc50f413859093b7df90c27874aee732dca940ea4842751d59'
+Error: SignatureInvalid
+```
+
+## Hard Derivation
+
+```sh
+subkey inspect 'desert piano add owner tuition tail melt rally height faint thunder immune//polkadot'
+
+Secret Key URI `desert piano add owner tuition tail melt rally height faint thunder immune//polkadot` is account:
+  Network ID:        substrate
+ Secret seed:       0x3d764056127d0c1b4934725cb9faecf00ed0996daa84d24a903b906f319e06bf
+  Public key (hex):  0xce6ccb0af417ade10062ac9b553d506b67d16c61cd2b6ce85330bc023db7e906
+  Account ID:        0xce6ccb0af417ade10062ac9b553d506b67d16c61cd2b6ce85330bc023db7e906
+  Public key (SS58): 5GjN3FsnqTCFZD2b1wbvJAWsVaneHbqz9HJoWeQuLFLBnwwj
+  SS58 Address:      5GjN3FsnqTCFZD2b1wbvJAWsVaneHbqz9HJoWeQuLFLBnwwj
+```
+
+```sh
+subkey inspect 'desert piano add owner tuition tail melt rally height faint thunder immune//kusama'
+
+Secret Key URI `desert piano add owner tuition tail melt rally height faint thunder immune//kusama` is account:
+  Network ID:        substrate
+ Secret seed:       0xabd92064a63df86174acfd29ab3204897974f0a39f5d61efdd30099aa5f90bd9
+  Public key (hex):  0xf62e5d444f89e704bb9b412adc472f990e9a9f40725ac6ff3abee1c9b7625a63
+  Account ID:        0xf62e5d444f89e704bb9b412adc472f990e9a9f40725ac6ff3abee1c9b7625a63
+  Public key (SS58): 5HdVQj5uqGYNsEFyzYb3nJ8dArhcS5BNVYhioFPQ3EptS9Yo
+  SS58 Address:      5HdVQj5uqGYNsEFyzYb3nJ8dArhcS5BNVYhioFPQ3EptS9Yo
+```
+
+## Soft Derivation from Secret
+
+```sh
+subkey inspect 'desert piano add owner tuition tail melt rally height faint thunder immune//polkadot/0'
+
+Secret Key URI `desert piano add owner tuition tail melt rally height faint thunder immune//polkadot/0` is account:
+  Network ID:        substrate
+ Secret seed:       n/a
+  Public key (hex):  0x4e8dfdd8a386ae37b8731dba5480d5cc65739023ea24f1a09d88be1bd9dff86b
+  Account ID:        0x4e8dfdd8a386ae37b8731dba5480d5cc65739023ea24f1a09d88be1bd9dff86b
+  Public key (SS58): 5DqhmkscaMJRbBE7vRGtcjDySwSgGwtc611SjPZMFV2WBw51
+  SS58 Address:      5DqhmkscaMJRbBE7vRGtcjDySwSgGwtc611SjPZMFV2WBw51
+```
+
+```sh
+subkey inspect 'desert piano add owner tuition tail melt rally height faint thunder immune//polkadot/1'
+
+Secret Key URI `desert piano add owner tuition tail melt rally height faint thunder immune//polkadot/1` is account:
+  Network ID:        substrate
+ Secret seed:       n/a
+  Public key (hex):  0x2e8b3090b17b12ea63029f03d852af71570e8e526690cc271491318a45785e33
+  Account ID:        0x2e8b3090b17b12ea63029f03d852af71570e8e526690cc271491318a45785e33
+  Public key (SS58): 5D7jQcDVQQ8ed4skUdaSNv3noPiwy9248vHPgifNe4Hspqa4
+  SS58 Address:      5D7jQcDVQQ8ed4skUdaSNv3noPiwy9248vHPgifNe4Hspqa4
+```
+
+## Soft Derivation from Public
+
+We use addresses here because Subkey does not derive paths from a raw public key (AFAIK).
+
+```sh
+subkey inspect 5Eqipnpt5asTm7sCFWQeJjsNJX5cYVJMid3zjKHjDUGKBJTo/0
+
+Public Key URI `5Eqipnpt5asTm7sCFWQeJjsNJX5cYVJMid3zjKHjDUGKBJTo/0` is account:
+  Network ID/Version: substrate
+  Public key (hex):   0xc4f4c8ee96476b56222b7fd10849f09893d4f1f7f41128d0109e3c86bd10d338
+  Account ID:         0xc4f4c8ee96476b56222b7fd10849f09893d4f1f7f41128d0109e3c86bd10d338
+  Public key (SS58):  5GWwxZsVJCwVuTsJP99X6Y6txonmMK3s73C4JB3DoY6UEwXq
+  SS58 Address:       5GWwxZsVJCwVuTsJP99X6Y6txonmMK3s73C4JB3DoY6UEwXq
+```
+
+```sh
+Public Key URI `5Eqipnpt5asTm7sCFWQeJjsNJX5cYVJMid3zjKHjDUGKBJTo/1` is account:
+  Network ID/Version: substrate
+  Public key (hex):   0x96450b4deeaf79aaae878c96d83b31b90375467439914c2b3a360842eba0c476
+  Account ID:         0x96450b4deeaf79aaae878c96d83b31b90375467439914c2b3a360842eba0c476
+  Public key (SS58):  5FTjYsLzGV2u7pudhPUpyV9A6u3ZiBKBAcuRJdeS4ZgyTYoS
+  SS58 Address:       5FTjYsLzGV2u7pudhPUpyV9A6u3ZiBKBAcuRJdeS4ZgyTYoS
+```
diff --git a/content/1-Cryptography/materials/zk-factorization-example/all-constraints-for-wiring.png b/content/1-Cryptography/materials/zk-factorization-example/all-constraints-for-wiring.png
new file mode 100644
index 00000000..971920b1
Binary files /dev/null and b/content/1-Cryptography/materials/zk-factorization-example/all-constraints-for-wiring.png differ
diff --git a/content/1-Cryptography/materials/zk-factorization-example/circuit-images.tm b/content/1-Cryptography/materials/zk-factorization-example/circuit-images.tm
new file mode 100644
index 00000000..b08f2968
--- /dev/null
+++ b/content/1-Cryptography/materials/zk-factorization-example/circuit-images.tm
@@ -0,0 +1,121 @@
+<TeXmacs|2.1>
+
+<style|generic>
+
+<\body>
+  <\session|xypic|default>
+    <\output>
+      TeXmacs interface to XYpic (high level 2-dimensional graphics)
+    </output>
+
+    <\unfolded-io>
+      xypic]\ 
+    <|unfolded-io>
+      \ 
+
+      \\xymatrix{
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ *+[o][F-]{r}\\ar@{-\<gtr\>}[dr]&&*+[o][F-]{s}\\ar@{-\<gtr\>}[dl]\\\\
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ &*+[o][F-]{\\times}\\ar@{-\<gtr\>}[d]&\\\\
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ &*+[o][F-]{N}&
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }
+
+      \;
+
+      \ \ \ \ \ \ \ \ 
+    <|unfolded-io>
+      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+    </unfolded-io>
+
+    <\input>
+      xypic]\ 
+    <|input>
+      \;
+    </input>
+  </session>
+
+  \;
+
+  <\session|xypic|default>
+    <\unfolded-io>
+      xypic]\ 
+    <|unfolded-io>
+      \\xymatrix{
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ *+[o][F-]{r}\\ar@{-\<gtr\>}[dr]&&*+[o][F-]{-1}\\ar@{-\<gtr\>}[dl]&*+[o][F-]{\\frac{1}{r-1}}\\ar@{-\<gtr\>}[ddl]\\\\
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ &*+[o][F-]{+}\\ar@{-\<gtr\>}[dr]&&\\\\
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ &&*+[o][F-]{\\times}\\ar@{-\<gtr\>}[d]&\\\\
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ &&*+[o][F-]{1}&
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }
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+    </unfolded-io>
+
+    <\input>
+      xypic]\ 
+    <|input>
+      \;
+    </input>
+  </session>
+
+  <\session|xypic|default>
+    <\unfolded-io>
+      xypic]\ 
+    <|unfolded-io>
+      \\xymatrix{
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ *+[o][F-]{r_0}\\ar@{-\<gtr\>}[dr]&&*+[o][F-]{2
+      r_1}\\ar@{-\<gtr\>}[dl]&*+[o][F-]{4 r_2}\\ar@{-\<gtr\>}[ddl]\\\\
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ &*+[o][F-]{+}\\ar@{-\<gtr\>}[dr]&&\\\\
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ &&*+[o][F-]{+}\\ar@{-\<gtr\>}[d]&\\\\
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ &&*+[o][F-]{r}&
+
+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }
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+      \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }
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>|ps>|0.618par|||>
+    </unfolded-io>
+
+    <\input>
+      xypic]\ 
+    <|input>
+      \;
+    </input>
+  </session>
+</body>
+
+<\initial>
+  <\collection>
+    <associate|page-height|auto>
+    <associate|page-medium|paper>
+    <associate|page-type|letter>
+    <associate|page-width|auto>
+  </collection>
+</initial>
\ No newline at end of file
diff --git a/content/1-Cryptography/materials/zk-factorization-example/circuit.circom b/content/1-Cryptography/materials/zk-factorization-example/circuit.circom
new file mode 100644
index 00000000..c5736f21
--- /dev/null
+++ b/content/1-Cryptography/materials/zk-factorization-example/circuit.circom
@@ -0,0 +1,67 @@
+pragma circom 2.0.0;
+/*This circuit template checks that r * s is a non-trivial interger factorization of c  */
+
+/*
+ * check if the input is not equal to 1
+ */
+template NotEqualToOne() {
+    signal input in;
+    signal output out;
+
+    signal inv;
+
+    inv <-- 1/(in - 1);
+
+    1 === (in - 1)*inv;
+}
+
+/*
+ * Decomposes `in` into `b` bits, given by `bits`.
+ * Least significant bit in `bits[0]`.
+ * Enforces that `in` is at most `b` bits long.
+ */
+template Num2Bits(b) {
+    signal input in;
+    signal output bits[b];
+
+    //log("numbit bits:", b);
+    for (var i = 0; i < b; i++) {
+        bits[i] <-- (in >> i) & 1;
+        bits[i] * (1 - bits[i]) === 0;
+    }
+    var sum_of_bits = 0;
+    for (var i = 0; i < b; i++) {
+        sum_of_bits += (2 ** i) * bits[i];
+    }
+    sum_of_bits === in;
+}
+
+template CheckFactorization () {  
+
+   // Declaration of signals.  
+   signal input r;  
+   signal input s;  
+   
+   component r_is_not_1;
+   component s_is_not_1;
+   component r_integer_less_than_8;
+   component s_integer_less_than_8;
+
+   // Constraints.  
+   21 === r * s;
+
+   r_is_not_1 = NotEqualToOne();
+   r_is_not_1.in <== r;
+
+   r_integer_less_than_8 = Num2Bits(3);
+   r_integer_less_than_8.in <== r;
+
+   s_is_not_1 = NotEqualToOne();
+   s_is_not_1.in <== s;
+
+   s_integer_less_than_8 = Num2Bits(3);
+   s_integer_less_than_8.in <== s;
+
+}
+
+component main = CheckFactorization();
diff --git a/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/bad_input.json b/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/bad_input.json
new file mode 100644
index 00000000..c4503445
--- /dev/null
+++ b/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/bad_input.json
@@ -0,0 +1 @@
+{ "r": 2, "s": 10944121435919637611123202872628637544274182200208017171849102093287904247819 }
diff --git a/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/input.json b/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/input.json
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@@ -0,0 +1 @@
+{ "r": 3, "s": 7 }
diff --git a/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/powers_of_tau/pot10_0000.ptau b/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/powers_of_tau/pot10_0000.ptau
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diff --git a/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/powers_of_tau/pot10_final.ptau b/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/powers_of_tau/pot10_final.ptau
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diff --git a/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/snarkjs_README.md b/content/1-Cryptography/materials/zk-factorization-example/circuit_example_playground/snarkjs_README.md
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@@ -0,0 +1,633 @@
+# snarkjs
+
+This is a **JavaScript and Pure Web Assembly implementation of zkSNARK and PLONK schemes.** It uses the Groth16 Protocol (3 point only and 3 pairings), PLONK and FFLONK.
+
+This library includes all the tools required to perform trusted setup multi-party ceremonies: including the universal [_powers of tau_](https://medium.com/coinmonks/announcing-the-perpetual-powers-of-tau-ceremony-to-benefit-all-zk-snark-projects-c3da86af8377) ceremony, and the second phase circuit specific ceremonies.
+
+> Any zk-snark project can pick a round from the common phase 1 to start their circuit-specific phase 2 ceremony.
+
+The formats used in this library for the multi-party computation are compatible with the ones used in [Semaphore's Perpetual Powers of Tau](https://github.com/weijiekoh/perpetualpowersoftau) and [other implementations](https://github.com/kobigurk/phase2-bn254).
+
+This library uses the compiled circuits generated by the [circom](https://github.com/iden3/circom) compiler.
+
+It works in [`node.js`](#using-node) as well as directly in the [browser](#in-the-browser).
+
+It's an [ES module](https://hacks.mozilla.org/2018/03/es-modules-a-cartoon-deep-dive/), so it can be directly imported into bigger projects using [Rollup](https://rollupjs.org/guide/en/) or [Webpack](https://webpack.js.org/).
+
+The low-level cryptography is performed directly in `wasm`, and uses worker threads to parallelize the computations. The result is a high performance library with benchmarks comparable to host implementations.
+
+## Preliminaries
+
+### Install node
+
+First off, make sure you have a recent version of `Node.js` installed. While any version after `v12` should work fine, we recommend you install `v16` or later.
+
+If you’re not sure which version of Node you have installed, you can run:
+
+```sh
+node -v
+```
+
+To download the latest version of Node, see [here](https://nodejs.org/en/download/).
+
+### Install snarkjs
+
+To install `snarkjs` run:
+
+```sh
+npm install -g snarkjs@latest
+```
+
+If you're seeing an error, try prefixing both commands with `sudo` and running them again.
+
+### Understand the `help` command
+
+To see a list of all `snarkjs` commands, as well as descriptions about their inputs and outputs, run:
+
+```sh
+snarkjs --help
+```
+
+You can also use the `--help` option with specific commands:
+
+```sh
+snarkjs groth16 prove --help
+```
+
+Most of the commands have an alternative shorter alias (which you can discover using `--help`).
+
+For example, the previous command can also be invoked with:
+
+```sh
+snarkjs g16p --help
+```
+
+### Debugging tip
+
+If you a feel a command is taking longer than it should, re-run it with a `-v` or `--verbose` option to see more details about how it's progressing and where it's getting blocked.
+
+### Install circom
+
+To install `circom`, follow the instructions at [installing circom](https://docs.circom.io/getting-started/installation).
+
+## Guide
+
+### 0. Create and move into a new directory
+
+```sh
+mkdir snarkjs_example
+cd snarkjs_example
+```
+
+### 1. Start a new powers of tau ceremony
+
+```sh
+snarkjs powersoftau new bn128 14 pot14_0000.ptau -v
+```
+
+The `new` command is used to start a powers of tau ceremony.
+
+The first parameter after `new` refers to the type of curve you wish to use. At the moment, we support both `bn128` and `bls12-381`.
+
+The second parameter, in this case `14`, is the power of two of the maximum number of constraints that the ceremony can accept: in this case, the number of constraints is `2 ^ 14 = 16,384`. The maximum value supported here is `28`, which means you can use `snarkjs` to securely generate zk-snark parameters for circuits with up to `2 ^ 28` (≈268 million) constraints.
+
+### 2. Contribute to the ceremony
+
+```sh
+snarkjs powersoftau contribute pot14_0000.ptau pot14_0001.ptau --name="First contribution" -v
+```
+
+The `contribute` command creates a ptau file with a new contribution.
+
+You'll be prompted to enter some random text to provide an extra source of entropy.
+
+`contribute` takes as input the transcript of the protocol so far, in this case `pot14_0000.ptau`, and outputs a new transcript, in this case `pot14_0001.ptau`, which includes the computation carried out by the new contributor (`ptau` files contain a history of all the challenges and responses that have taken place so far).
+
+`name` can be anything you want, and is just included for reference (it will be printed when you verify the file (step 5).
+
+### 3. Provide a second contribution
+
+```sh
+snarkjs powersoftau contribute pot14_0001.ptau pot14_0002.ptau --name="Second contribution" -v -e="some random text"
+```
+
+By letting you write the random text as part of the command, the `-e` parameter allows `contribute` to be non-interactive.
+
+### 4. Provide a third contribution using third party software
+
+```sh
+snarkjs powersoftau export challenge pot14_0002.ptau challenge_0003
+snarkjs powersoftau challenge contribute bn128 challenge_0003 response_0003 -e="some random text"
+snarkjs powersoftau import response pot14_0002.ptau response_0003 pot14_0003.ptau -n="Third contribution name"
+```
+
+The challenge and response files are compatible with [this software](https://github.com/kobigurk/phase2-bn254).
+
+This allows you to use different types of software in a single ceremony.
+
+### 5. Verify the protocol so far
+
+```sh
+snarkjs powersoftau verify pot14_0003.ptau
+```
+
+The `verify` command verifies a `ptau` (powers of tau) file. Which means it checks all the contributions to the multi-party computation (MPC) up to that point. It also prints the hashes of all the intermediate results to the console.
+
+If everything checks out, you should see the following at the top of the output:
+
+```sh
+[INFO]  snarkJS: Powers Of tau file OK!
+```
+
+In sum, whenever a new zk-snark project needs to perform a trusted setup, you can just pick the latest `ptau` file, and run the `verify` command to verify the entire chain of challenges and responses so far.
+
+### 6. Apply a random beacon
+
+```sh
+snarkjs powersoftau beacon pot14_0003.ptau pot14_beacon.ptau 0102030405060708090a0b0c0d0e0f101112131415161718191a1b1c1d1e1f 10 -n="Final Beacon"
+```
+
+The `beacon` command creates a `ptau` file with a contribution applied in the form of a random beacon.
+
+We need to apply a random beacon in order to finalise phase 1 of the trusted setup.
+
+> To paraphrase Sean Bowe and Ariel Gabizon, a random beacon is a source of public randomness that is not available before a fixed time. The beacon itself can be a delayed hash function (e.g. 2^40 iterations of SHA256) evaluated on some high entropy and publicly available data. Possible sources of data include: the closing value of the stock market on a certain date in the future, the output of a selected set of national lotteries, or the value of a block at a particular height in one or more blockchains. E.g. the hash of the 11 millionth Ethereum block (which as of this writing is some 3 months in the future). See [here](https://eprint.iacr.org/2017/1050.pdf) for more on the importance of a random beacon.
+
+For the purposes of this tutorial, the beacon is essentially a delayed hash function evaluated on `0102030405060708090a0b0c0d0e0f101112131415161718191a1b1c1d1e1f` (in practice this value will be some form of high entropy and publicly available data of your choice). The next input -- in our case `10` -- just tells `snarkjs` to perform `2 ^ 10` iterations of this hash function.
+
+> Note that [security holds](https://eprint.iacr.org/2017/1050) even if an adversary has limited influence on the beacon.
+
+### 7. Prepare phase 2
+
+```sh
+snarkjs powersoftau prepare phase2 pot14_beacon.ptau pot14_final.ptau -v
+```
+
+We're now ready to prepare phase 2 of the setup (the circuit-specific phase).
+
+Under the hood, the `prepare phase2` command calculates the encrypted evaluation of the Lagrange polynomials at tau for `tau`, `alpha*tau` and `beta*tau`. It takes the beacon `ptau` file we generated in the previous step, and outputs a final `ptau` file which will be used to generate the circuit proving and verification keys.
+
+---
+
+**NOTE**
+
+Ptau files for bn128 with the peraperPhase2 54 contributions and a beacon, can be found here:
+
+| power | maxConstraints | file                                                                                                         | hash                                                                                                                             |
+| ----- | -------------- | ------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------- |
+| 8     | 256            | [powersOfTau28_hez_final_08.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_08.ptau) | d6a8fb3a04feb600096c3b791f936a578c4e664d262e4aa24beed1b7a9a96aa5eb72864d628db247e9293384b74b36ffb52ca8d148d6e1b8b51e279fdf57b583 |
+| 9     | 512            | [powersOfTau28_hez_final_09.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_09.ptau) | 94f108a80e81b5d932d8e8c9e8fd7f46cf32457e31462deeeef37af1b71c2c1b3c71fb0d9b59c654ec266b042735f50311f9fd1d4cadce47ab234ad163157cb5 |
+| 10    | 1k             | [powersOfTau28_hez_final_10.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_10.ptau) | 6cfeb8cda92453099d20120bdd0e8a5c4e7706c2da9a8f09ccc157ed2464d921fd0437fb70db42104769efd7d6f3c1f964bcf448c455eab6f6c7d863e88a5849 |
+| 11    | 2k             | [powersOfTau28_hez_final_11.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_11.ptau) | 47c282116b892e5ac92ca238578006e31a47e7c7e70f0baa8b687f0a5203e28ea07bbbec765a98dcd654bad618475d4661bfaec3bd9ad2ed12e7abc251d94d33 |
+| 12    | 4k             | [powersOfTau28_hez_final_12.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_12.ptau) | ded2694169b7b08e898f736d5de95af87c3f1a64594013351b1a796dbee393bd825f88f9468c84505ddd11eb0b1465ac9b43b9064aa8ec97f2b73e04758b8a4a |
+| 13    | 8k             | [powersOfTau28_hez_final_13.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_13.ptau) | 58efc8bf2834d04768a3d7ffcd8e1e23d461561729beaac4e3e7a47829a1c9066d5320241e124a1a8e8aa6c75be0ba66f65bc8239a0542ed38e11276f6fdb4d9 |
+| 14    | 16k            | [powersOfTau28_hez_final_14.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_14.ptau) | eeefbcf7c3803b523c94112023c7ff89558f9b8e0cf5d6cdcba3ade60f168af4a181c9c21774b94fbae6c90411995f7d854d02ebd93fb66043dbb06f17a831c1 |
+| 15    | 32k            | [powersOfTau28_hez_final_15.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_15.ptau) | 982372c867d229c236091f767e703253249a9b432c1710b4f326306bfa2428a17b06240359606cfe4d580b10a5a1f63fbed499527069c18ae17060472969ae6e |
+| 16    | 64k            | [powersOfTau28_hez_final_16.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_16.ptau) | 6a6277a2f74e1073601b4f9fed6e1e55226917efb0f0db8a07d98ab01df1ccf43eb0e8c3159432acd4960e2f29fe84a4198501fa54c8dad9e43297453efec125 |
+| 17    | 128k           | [powersOfTau28_hez_final_17.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_17.ptau) | 6247a3433948b35fbfae414fa5a9355bfb45f56efa7ab4929e669264a0258976741dfbe3288bfb49828e5df02c2e633df38d2245e30162ae7e3bcca5b8b49345 |
+| 18    | 256k           | [powersOfTau28_hez_final_18.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_18.ptau) | 7e6a9c2e5f05179ddfc923f38f917c9e6831d16922a902b0b4758b8e79c2ab8a81bb5f29952e16ee6c5067ed044d7857b5de120a90704c1d3b637fd94b95b13e |
+| 19    | 512k           | [powersOfTau28_hez_final_19.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_19.ptau) | bca9d8b04242f175189872c42ceaa21e2951e0f0f272a0cc54fc37193ff6648600eaf1c555c70cdedfaf9fb74927de7aa1d33dc1e2a7f1a50619484989da0887 |
+| 20    | 1M             | [powersOfTau28_hez_final_20.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_20.ptau) | 89a66eb5590a1c94e3f1ee0e72acf49b1669e050bb5f93c73b066b564dca4e0c7556a52b323178269d64af325d8fdddb33da3a27c34409b821de82aa2bf1a27b |
+| 21    | 2M             | [powersOfTau28_hez_final_21.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_21.ptau) | 9aef0573cef4ded9c4a75f148709056bf989f80dad96876aadeb6f1c6d062391f07a394a9e756d16f7eb233198d5b69407cca44594c763ab4a5b67ae73254678 |
+| 22    | 4M             | [powersOfTau28_hez_final_22.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_22.ptau) | 0d64f63dba1a6f11139df765cb690da69d9b2f469a1ddd0de5e4aa628abb28f787f04c6a5fb84a235ec5ea7f41d0548746653ecab0559add658a83502d1cb21b |
+| 23    | 8M             | [powersOfTau28_hez_final_23.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_23.ptau) | 3063a0bd81d68711197c8820a92466d51aeac93e915f5136d74f63c394ee6d88c5e8016231ea6580bec02e25d491f319d92e77f5c7f46a9caa8f3b53c0ea544f |
+| 24    | 16M            | [powersOfTau28_hez_final_24.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_24.ptau) | fa404d140d5819d39984833ca5ec3632cd4995f81e82db402371a4de7c2eae8687c62bc632a95b0c6aadba3fb02680a94e09174b7233ccd26d78baca2647c733 |
+| 25    | 32M            | [powersOfTau28_hez_final_25.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_25.ptau) | 0377d860cdb09a8a31ea1b0b8c04335614c8206357181573bf294c25d5ca7dff72387224fbd868897e6769f7805b3dab02854aec6d69d7492883b5e4e5f35eeb |
+| 26    | 64M            | [powersOfTau28_hez_final_26.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_26.ptau) | 418dee4a74b9592198bd8fd02ad1aea76f9cf3085f206dfd7d594c9e264ae919611b1459a1cc920c2f143417744ba9edd7b8d51e44be9452344a225ff7eead19 |
+| 27    | 128M           | [powersOfTau28_hez_final_27.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final_27.ptau) | 10ffd99837c512ef99752436a54b9810d1ac8878d368fb4b806267bdd664b4abf276c9cd3c4b9039a1fa4315a0c326c0e8e9e8fe0eb588ffd4f9021bf7eae1a1 |
+| 28    | 256M           | [powersOfTau28_hez_final.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final.ptau)       | 55c77ce8562366c91e7cda394cf7b7c15a06c12d8c905e8b36ba9cf5e13eb37d1a429c589e8eaba4c591bc4b88a0e2828745a53e170eac300236f5c1a326f41a |
+
+There is a file truncated for each power of two.
+
+The complete file is [powersOfTau28_hez_final.ptau](https://storage.googleapis.com/zkevm/ptau/powersOfTau28_hez_final.ptau) which includes 2\*\*28 powers.
+
+And it's blake2b hash is:
+
+55c77ce8562366c91e7cda394cf7b7c15a06c12d8c905e8b36ba9cf5e13eb37d1a429c589e8eaba4c591bc4b88a0e2828745a53e170eac300236f5c1a326f41a
+
+You can find more information about the ceremony [here](https://github.com/weijiekoh/perpetualpowersoftau)
+
+---
+
+### 8. Verify the final `ptau`
+
+```sh
+snarkjs powersoftau verify pot14_final.ptau
+```
+
+The `verify` command verifies a powers of tau file.
+
+Before we go ahead and create the circuit, we perform a final check and verify the final protocol transcript.
+
+> Notice there is no longer a warning informing you that the file does not contain phase 2 precalculated values.
+
+### 9. Create the circuit
+
+```sh
+cat <<EOT > circuit.circom
+pragma circom 2.0.0;
+
+template Multiplier(n) {
+    signal input a;
+    signal input b;
+    signal output c;
+
+    signal int[n];
+
+    int[0] <== a*a + b;
+    for (var i=1; i<n; i++) {
+    int[i] <== int[i-1]*int[i-1] + b;
+    }
+
+    c <== int[n-1];
+}
+
+component main = Multiplier(1000);
+EOT
+```
+
+We create a circom file that allows us to easily test the system with a different number of constraints.
+
+In this case, we've chosen `1000`, but we can change this to anything we want (as long as the value we choose is below the number we defined in step 1).
+
+### 10. Compile the circuit
+
+```sh
+circom circuit.circom --r1cs --wasm --sym
+```
+
+The `circom` command takes one input (the circuit to compile, in our case `circuit.circom`) and three options:
+
+- `r1cs`: generates `circuit.r1cs` (the r1cs constraint system of the circuit in binary format).
+
+- `wasm`: generates `circuit.wasm` (the wasm code to generate the witness – more on that later).
+
+- `sym`: generates `circuit.sym` (a symbols file required for debugging and printing the constraint system in an annotated mode).
+
+### 11. View information about the circuit
+
+```sh
+snarkjs r1cs info circuit.r1cs
+```
+
+The `info` command is used to print circuit stats.
+
+You should see the following output:
+
+```
+[INFO]  snarkJS: Curve: bn-128
+[INFO]  snarkJS: # of Wires: 1003
+[INFO]  snarkJS: # of Constraints: 1000
+[INFO]  snarkJS: # of Private Inputs: 2
+[INFO]  snarkJS: # of Public Inputs: 0
+[INFO]  snarkJS: # of Outputs: 1
+```
+
+This information fits with our mental map of the circuit we created: we had two private inputs `a` and `b`, one output `c`, and a thousand constraints of the form `a * b = c.`
+
+### 12. Print the constraints
+
+```sh
+snarkjs r1cs print circuit.r1cs circuit.sym
+```
+
+To double check, we print the constraints of the circuit.
+
+You should see a thousand constraints of the form:
+
+```
+[ -main.int[i] ] * [ main.int[i] ] - [ main.b -main.int[i+1] ] = 0
+```
+
+### 13. Export r1cs to json
+
+```sh
+snarkjs r1cs export json circuit.r1cs circuit.r1cs.json
+cat circuit.r1cs.json
+```
+
+We export `r1cs` to `json` format to make it human readable.
+
+### 14. Calculate the witness
+
+First, we create a file with the inputs for our circuit:
+
+```sh
+cat <<EOT > input.json
+{"a": 3, "b": 11}
+EOT
+```
+
+Now, we use the Javascript/WASM program created by `circom` in the directory _circuit_js_ to create the witness (values of all the wires) for our inputs:
+
+```sh
+circuit_js$ node generate_witness.js circuit.wasm ../input.json ../witness.wtns
+```
+
+We can check if the generated witness complies with the `r1cs` file with the following command:
+
+```sh
+snarkjs wtns check circuit.r1cs witness.wtns
+```
+
+### 15. Setup
+
+Currently, snarkjs supports 3 proving systems: Groth16, PLONK and FFLONK (Beta version).
+
+Groth16 requires a trusted ceremony for each circuit. PLONK and FFLONK do not require it, it's enough with the powers of tau ceremony which is universal.
+
+#### Plonk
+
+```sh
+snarkjs plonk setup circuit.r1cs pot14_final.ptau circuit_final.zkey
+```
+
+#### Fflonk
+
+```sh
+snarkjs fflonk setup circuit.r1cs pot14_final.ptau circuit.zkey
+```
+
+You can jump directly to Section 21 as PLONK or FFLONK does not require a specific trusted ceremony.
+
+#### Groth16
+
+```sh
+snarkjs groth16 setup circuit.r1cs pot14_final.ptau circuit_0000.zkey
+```
+
+This generates the reference `zkey` without phase 2 contributions
+
+IMPORTANT: Do not use this zkey in production, as it's not safe. It requires at least a contribution,
+
+The `zkey new` command creates an initial `zkey` file with zero contributions.
+
+The `zkey` is a zero-knowledge key that includes both the proving and verification keys as well as phase 2 contributions.
+
+Importantly, one can verify whether a `zkey` belongs to a specific circuit or not.
+
+Note that `circuit_0000.zkey` (the output of the `zkey` command above) does not include any contributions yet, so it cannot be used in a final circuit.
+
+_The following steps (15-20) are similar to the equivalent phase 1 steps, except we use `zkey` instead of `powersoftau` as the main command, and we generate `zkey` rather that `ptau` files._
+
+### 16. Contribute to the phase 2 ceremony
+
+```sh
+snarkjs zkey contribute circuit_0000.zkey circuit_0001.zkey --name="1st Contributor Name" -v
+```
+
+The `zkey contribute` command creates a `zkey` file with a new contribution.
+
+As in phase 1, you'll be prompted to enter some random text to provide an extra source of entropy.
+
+### 17. Provide a second contribution
+
+```sh
+snarkjs zkey contribute circuit_0001.zkey circuit_0002.zkey --name="Second contribution Name" -v -e="Another random entropy"
+```
+
+We provide a second contribution.
+
+### 18. Provide a third contribution using third party software
+
+```sh
+snarkjs zkey export bellman circuit_0002.zkey  challenge_phase2_0003
+snarkjs zkey bellman contribute bn128 challenge_phase2_0003 response_phase2_0003 -e="some random text"
+snarkjs zkey import bellman circuit_0002.zkey response_phase2_0003 circuit_0003.zkey -n="Third contribution name"
+```
+
+And a third using [third-party software](https://github.com/kobigurk/phase2-bn254).
+
+### 19. Verify the latest `zkey`
+
+```sh
+snarkjs zkey verify circuit.r1cs pot14_final.ptau circuit_0003.zkey
+```
+
+The `zkey verify` command verifies a `zkey` file. It also prints the hashes of all the intermediary results to the console.
+
+We verify the `zkey` file we created in the previous step. Which means we check all the contributions to the second phase of the multi-party computation (MPC) up to that point.
+
+This command also checks that the `zkey` file matches the circuit.
+
+If everything checks out, you should see the following:
+
+```
+[INFO]  snarkJS: ZKey Ok!
+```
+
+### 20. Apply a random beacon
+
+```sh
+snarkjs zkey beacon circuit_0003.zkey circuit_final.zkey 0102030405060708090a0b0c0d0e0f101112131415161718191a1b1c1d1e1f 10 -n="Final Beacon phase2"
+```
+
+The `zkey beacon` command creates a `zkey` file with a contribution applied in the form of a random beacon.
+
+We use it to apply a random beacon to the latest `zkey` after the final contribution has been made (this is necessary in order to generate a final `zkey` file and finalise phase 2 of the trusted setup).
+
+### 21. Verify the final `zkey`
+
+```sh
+snarkjs zkey verify circuit.r1cs pot14_final.ptau circuit_final.zkey
+```
+
+Before we go ahead and export the verification key as a `json`, we perform a final check and verify the final protocol transcript (`zkey`).
+
+### 22. Export the verification key
+
+```sh
+snarkjs zkey export verificationkey circuit_final.zkey verification_key.json
+```
+
+We export the verification key from `circuit_final.zkey` into `verification_key.json`.
+
+### 23. Create the proof
+
+#### PLONK
+
+```sh
+snarkjs plonk prove circuit_final.zkey witness.wtns proof.json public.json
+```
+
+#### FFLONK
+
+```sh
+snarkjs fflonk prove circuit.zkey witness.wtns proof.json public.json
+```
+
+#### Groth16
+
+```sh
+snarkjs groth16 prove circuit_final.zkey witness.wtns proof.json public.json
+```
+
+We create the proof. this command generates the files `proof.json` and `public.json`: `proof.json` contains the actual proof, whereas `public.json` contains the values of the public inputs and output.
+
+> Note that it's also possible to create the proof and calculate the witness in the same command by running:
+>
+> ````sh
+> snarkjs groth16 fullprove input.json circuit.wasm circuit_final.zkey proof.json public.json
+> or
+> snarkjs plonk fullprove witness.json circuit.wasm circuit_final.zkey proof.json public.json
+> or
+> snarkjs fflonk fullprove witness.json circuit.wasm circuit_final.zkey proof.json public.json
+> > ```
+> ````
+
+### 24. Verify the proof
+
+#### PLONK
+
+```sh
+snarkjs plonk verify verification_key.json public.json proof.json
+```
+
+#### FFLONK
+
+```sh
+snarkjs fflonk verify verification_key.json public.json proof.json
+```
+
+#### Groth16
+
+```sh
+snarkjs groth16 verify verification_key.json public.json proof.json
+```
+
+We use the this command to verify the proof, passing in the `verification_key` we exported earlier.
+
+If all is well, you should see that `OK` has been outputted to your console. This signifies the proof is valid.
+
+### 25. Turn the verifier into a smart contract
+
+```sh
+snarkjs zkey export solidityverifier circuit_final.zkey verifier.sol
+```
+
+Finally, we export the verifier as a Solidity smart-contract so that we can publish it on-chain -- using [remix](https://remix.ethereum.org/) for example. For the details on how to do this, refer to section 4 of [this tutorial](https://blog.iden3.io/first-zk-proof.html).
+
+### 26. Simulate a verification call
+
+```sh
+snarkjs zkey export soliditycalldata public.json proof.json
+```
+
+We use `soliditycalldata` to simulate a verification call, and cut and paste the result directly in the verifyProof field in the deployed smart contract in the remix environment.
+
+And voila! That's all there is to it :)
+
+## Using Node
+
+```sh
+npm init
+npm install snarkjs
+```
+
+```js
+const snarkjs = require("snarkjs");
+const fs = require("fs");
+
+async function run() {
+  const { proof, publicSignals } = await snarkjs.groth16.fullProve(
+    { a: 10, b: 21 },
+    "circuit.wasm",
+    "circuit_final.zkey",
+  );
+
+  console.log("Proof: ");
+  console.log(JSON.stringify(proof, null, 1));
+
+  const vKey = JSON.parse(fs.readFileSync("verification_key.json"));
+
+  const res = await snarkjs.groth16.verify(vKey, publicSignals, proof);
+
+  if (res === true) {
+    console.log("Verification OK");
+  } else {
+    console.log("Invalid proof");
+  }
+}
+
+run().then(() => {
+  process.exit(0);
+});
+```
+
+## In the browser
+
+Load `snarkjs.min.js` and start using it as usual.
+
+```
+cp node_modules/snarkjs/build/snarkjs.min.js .
+```
+
+```html
+<!DOCTYPE html>
+<html>
+  <head>
+    <title>Snarkjs client example</title>
+  </head>
+  <body>
+    <h1>Snarkjs client example</h1>
+    <button id="bGenProof">Create proof</button>
+
+    <!-- JS-generated output will be added here. -->
+    <pre class="proof"> Proof: <code id="proof"></code></pre>
+
+    <pre class="proof"> Result: <code id="result"></code></pre>
+
+    <script src="snarkjs.min.js"></script>
+
+    <!-- This is the bundle generated by rollup.js -->
+    <script>
+      const proofComponent = document.getElementById("proof");
+      const resultComponent = document.getElementById("result");
+      const bGenProof = document.getElementById("bGenProof");
+
+      bGenProof.addEventListener("click", calculateProof);
+
+      async function calculateProof() {
+        const { proof, publicSignals } = await snarkjs.groth16.fullProve(
+          { a: 3, b: 11 },
+          "circuit.wasm",
+          "circuit_final.zkey"
+        );
+
+        proofComponent.innerHTML = JSON.stringify(proof, null, 1);
+
+        const vkey = await fetch("verification_key.json").then(function (res) {
+          return res.json();
+        });
+
+        const res = await snarkjs.groth16.verify(vkey, publicSignals, proof);
+
+        resultComponent.innerHTML = res;
+      }
+    </script>
+  </body>
+</html>
+```
+
+## Security
+
+Avoid using versions before v0.4.16. They contain bugs that may affect the security.
+
+## Further resources
+
+- [Announcing the Perpetual Powers of Tau Ceremony to benefit all zk-SNARK projects](https://medium.com/coinmonks/announcing-the-perpetual-powers-of-tau-ceremony-to-benefit-all-zk-snark-projects-c3da86af8377)
+- [Scalable Multi-party Computation for zk-SNARK Parameters in
+  the Random Beacon Model](https://eprint.iacr.org/2017/1050.pdf)
+- [phase2-bn254](https://github.com/kobigurk/phase2-bn254)
+- [Perpetual Powers of Tau](https://github.com/weijiekoh/perpetualpowersoftau)
+- [Powers of Tau](https://github.com/ebfull/powersoftau)
+- [Trusted setup ceremonies explored](https://www.zeroknowledge.fm/133)
+- [Simple react projct using snarkjs](https://github.com/LHerskind/snarkjs-react)
+
+## Final note
+
+We hope you enjoyed this quick walk-through. Please address any questions you may have to our [telegram group](https://t.me/iden3io) (it’s also a great way to join the community and stay up-to-date with the latest circom and snarkjs developments) 💙
+
+## License
+
+snarkjs is part of the iden3 project copyright 2018 0KIMS association and published with GPL-3 license. Please check the COPYING file for more details.
diff --git a/content/1-Cryptography/materials/zk-factorization-example/gate-constrains.org b/content/1-Cryptography/materials/zk-factorization-example/gate-constrains.org
new file mode 100644
index 00000000..b4a8f838
--- /dev/null
+++ b/content/1-Cryptography/materials/zk-factorization-example/gate-constrains.org
@@ -0,0 +1,164 @@
+#+OPTIONS: toc:nil
+
+* Gate constrains:
+
+** Multiplication constrain:
+
+  - $r * s = n$
+
+** constraining $r \neq 1$
+  - Making sure that the prover doesn't fool the verifier by using 1 as a factor.
+  - We force them to use r-1's inverse. 
+  - $(r-1)(r-1)^{-1} = 1 \Rightarrow  r * (r-1)^{-1} - (r-1)^{-1} = 1$
+
+** constraining $0< r < 8$:
+ We need to make sure r % p = r
+ otherwise prover can cheat because everything has an inverse in $FF_p$
+ We use Binary decomposition:
+  - $r0 + 2 * r1 = r01$
+  - $r01 + 4 * r2 = r$ 
+  - $r0 * r0 - r0 = 0$
+  - $r1 * r1 - r1 = 0$
+  - $r2 * r2 - r2 = 0$
+
+** similarly constraining $b$:
+
+  - $s0 + 2 * s1 = s01$
+  - $s01 + 4 * s2 = s$ 
+  - $s0 * s0 - s0 = 0$
+  - $s1 * s1 - s1 = 0$
+  - $s2 * s2 - s2 = 0$
+  - $s * (s-1)^{-1} - (s-1)^{-1} = 1$
+
+* Universal way of summerizing constrains:
+ $Q_l*a + Q_r*b + Q_o*c + Q_m*a*b + Q_c = 0$
+
+* Constrain for factorization:
+ $Q_l*a + Q_r*b + Q_o*c + Q_m*a*b + Q_c = 0$
+ 
+ | Gate No | Q_l | Q_r | Q_o | Q_m | Q_c | a | b | c |
+ |---------+-----+-----+-----+-----+-----+---+---+---|
+ |       1 |   0 |   0 |   0 |   1 | -n  | r | s | 0 |
+
+* Constrain table $a$
+ $Q_l*a + Q_r*b + Q_o*c + Q_m*a*b + Q_c = 0$
+
+ | Gate No | Q_l | Q_r | Q_o | Q_m | Q_c | a   | b        |   c |
+ |---------+-----+-----+-----+-----+-----+-----+----------+-----|
+ |       2 |   1 |   2 |  -1 |   0 |   0 | r0  | r1       | r01 |
+ |       3 |   1 |   4 |  -1 |   0 |   0 | r01 | r2       |   r |
+ |       4 |  -1 |   0 |   0 |   1 |   0 | r0  | r0       |   0 |
+ |       5 |  -1 |   0 |   0 |   1 |   0 | r1  | r1       |   0 |
+ |       6 |  -1 |   0 |   0 |   1 |   0 | r2  | r2       |   0 |
+ |       7 |   0 |  -1 |   0 |   1 |  -1 | r   | (r-1)^-1 |   0 |
+ |---------+-----+-----+-----+-----+-----+-----+----------+-----|
+
+* Constrain table  $b$
+ $Q_l*a + Q_r*b + Q_o*c + Q_m*a*b + Q_c = 0$
+
+ | Gate No | Q_l | Q_r | Q_o | Q_m | Q_c | a   | b        |   c |
+ |---------+-----+-----+-----+-----+-----+-----+----------+-----|
+ |       8 |   1 |   2 |  -1 |   0 |   0 | s0  | s1       | s01 |
+ |       9 |   1 |   4 |  -1 |   0 |   0 | s01 | s2       |   s |
+ |      10 |  -1 |   0 |   0 |   1 |   0 | s0  | s0       |   0 |
+ |      11 |  -1 |   0 |   0 |   1 |   0 | s1  | s1       |   0 |
+ |      12 |  -1 |   0 |   0 |   1 |   0 | s2  | s2       |   0 |
+ |      13 |   0 |  -1 |   0 |   1 |  -1 | s   | (s-1)^-1 |   0 |
+ |---------+-----+-----+-----+-----+-----+-----+----------+-----|
+
+* all constraints for wiring
+ | Gate No | Q_l | Q_r | Q_o | Q_m | Q_c | a   | b        |   c |
+ |---------+-----+-----+-----+-----+-----+-----+----------+-----|
+ |       1 |   0 |   0 |   0 |   1 |  -n | r   | s        |   0 |
+ |       2 |   1 |   2 |  -1 |   0 |   0 | r0  | r1       | r01 |
+ |       3 |   1 |   4 |  -1 |   0 |   0 | r01 | r2       |   r |
+ |       4 |  -1 |   0 |   0 |   1 |   0 | r0  | r0       |   0 |
+ |       5 |  -1 |   0 |   0 |   1 |   0 | r1  | r1       |   0 |
+ |       6 |  -1 |   0 |   0 |   1 |   0 | r2  | r2       |   0 |
+ |       7 |   0 |  -1 |   0 |   1 |  -1 | r   | (r-1)^-1 |   0 |
+ |       8 |   1 |   2 |  -1 |   0 |   0 | s0  | s1       | s01 |
+ |       9 |   1 |   4 |  -1 |   0 |   0 | s01 | s2       |   s |
+ |      10 |  -1 |   0 |   0 |   1 |   0 | s0  | s0       |   0 |
+ |      11 |  -1 |   0 |   0 |   1 |   0 | s1  | s1       |   0 |
+ |      12 |  -1 |   0 |   0 |   1 |   0 | s2  | s2       |   0 |
+ |      13 |   0 |  -1 |   0 |   1 |  -1 | s   | (s-1)^-1 |   0 |
+ |---------+-----+-----+-----+-----+-----+-----+----------+-----|
+
+* Trace polynomial for wiring with omega
+ | Gate | a                       | b                            | c                       |
+ |------+-------------------------+------------------------------+-------------------------|
+ |    1 | $T(\omega^1) := r$      | $T(\omega^2):=s$             | $T(\omega^3) :=  0$     |
+ |    2 | $T(\omega^4) := r0$     | $T(\omega^5):=r1$            | $T(\omega^6) := r01$    |
+ |    3 | $T(\omega^7) := r01$    | $T(\omega^8) := r2$          | $T(\omega^9) := r$      |
+ |    4 | $T(\omega^{10}) := r0$  | $T(\omega^{11}) := r0$       | $T(\omega^{12}) := 0$   |
+ |    5 | $T(\omega^{13}) := r1$  | $T(\omega^{14}) := r1$       | $T(\omega^{15}) := 0$   |
+ |    6 | $T(\omega^{16}) := r2$  | $T(\omega^{17}) := r2$       | $T(\omega^{18}) := 0$   |
+ |    7 | $T(\omega^{19}) := r$   | $T(\omega^{20}) := (r-1)^-1$ | $T(\omega^{21}) := 0$   |
+ |    8 | $T(\omega^{22}) := s0$  | $T(\omega^{23}) := s1$       | $T(\omega^{24}) := s01$ |
+ |    9 | $T(\omega^{25}) := s01$ | $T(\omega^{26}) := s2$       | $T(\omega^{27}) := s$   |
+ |   10 | $T(\omega^{28}) := s0$  | $T(\omega^{29}) := s0$       | $T(\omega^{30}) := 0$   |
+ |   11 | $T(\omega^{31}) := s1$  | $T(\omega^{32}) := s1$       | $T(\omega^{33}) := 0$   |
+ |   12 | $T(\omega^{34}) := s2$  | $T(\omega^{35}) := s2$       | $T(\omega^{36}) := 0$   |
+ |   13 | $T(\omega^{37}) := s$   | $T(\omega^{38}) := (s-1)^-1$ | $T(\omega^{39}) := 0$   |
+ |------+-------------------------+------------------------------+-------------------------|
+
+ 
+* Permutation Psi with omega
+  | Gate | a                                  | b                                  | c                                  |
+  |------+------------------------------------+------------------------------------+------------------------------------|
+  |    1 | $\Psi(\omega^1) := \omega^9$       | $\Psi(\omega^2):=\omega^{27}$      | $\Psi(\omega^3) := \omega^3$       |
+  |    2 | $\Psi(\omega^4) := \omega^{10}$    | $\Psi(\omega^5):=\omega^{13}$      | $\Psi(\omega^6) := \omega^7$       |
+  |    3 | $\Psi(\omega^7) := \omega^6$       | $\Psi(\omega^8) := \omega^{16}$    | $\Psi(\omega^9) := \omega^{19}$    |
+  |    4 | $\Psi(\omega^{10}) := \omega^{11}$ | $\Psi(\omega^{11}) := \omega^4$    | $\Psi(\omega^{12}) := \omega^{12}$ |
+  |    5 | $\Psi(\omega^{13}) := \omega^{14}$ | $\Psi(\omega^{14}) := \omega^{5}$  | $\Psi(\omega^{15}) := \omega^{15}$ |
+  |    6 | $\Psi(\omega^{16}) := \omega^{17}$ | $\Psi(\omega^{17}) := \omega^{8}$  | $\Psi(\omega^{18}) := \omega^{18}$ |
+  |    7 | $\Psi(\omega^{19}) := \omega^{1}$  | $\Psi(\omega^{20}) := \omega^{20}$ | $\Psi(\omega^{21}) := \omega^{21}$ |
+  |    8 | $\Psi(\omega^{22}) := \omega^{28}$ | $\Psi(\omega^{23}) := \omega^{31}$ | $\Psi(\omega^{24}) := \omega^{25}$ |
+  |    9 | $\Psi(\omega^{25}) := \omega^{24}$ | $\Psi(\omega^{26}) := \omega^{34}$ | $\Psi(\omega^{27}) := \omega^{37}$ |
+  |   10 | $\Psi(\omega^{28}) := \omega^{29}$ | $\Psi(\omega^{29}) := \omega^{22}$ | $\Psi(\omega^{30}) := \omega^{30}$ |
+  |   11 | $\Psi(\omega^{31}) := \omega^{31}$ | $\Psi(\omega^{32}) := \omega^{31}$ | $\Psi(\omega^{33}) := \omega^{33}$ |
+  |   12 | $\Psi(\omega^{34}) := \omega^{35}$ | $\Psi(\omega^{35}) := \omega^{35}$ | $\Psi(\omega^{36}) := \omega^{36}$ |
+  |   13 | $\Psi(\omega^{37}) := \omega^{2}$  | $\Psi(\omega^{38}) := \omega^{38}$ | $\Psi(\omega^{39}) := \omega^{39}$ |
+  |------+------------------------------------+------------------------------------+------------------------------------|
+
+* Trace polynomial for wiring
+ | Gate | a                | b                     | c                |
+ |------+------------------+-----------------------+------------------|
+ |    1 | $T(1) := r$      | $T(2):=s$             | $T(3) :=  0$     |
+ |    2 | $T(4) := r0$     | $T(5):=r1$            | $T(6) := r01$    |
+ |    3 | $T(7) := r01$    | $T(8) := r2$          | $T(9) := r$      |
+ |    4 | $T({10}) := r0$  | $T({11}) := r0$       | $T({12}) := 0$   |
+ |    5 | $T({13}) := r1$  | $T({14}) := r1$       | $T({15}) := 0$   |
+ |    6 | $T({16}) := r2$  | $T({17}) := r2$       | $T({18}) := 0$   |
+ |    7 | $T({19}) := r$   | $T({20}) := (r-1)^-1$ | $T({21}) := 0$   |
+ |    8 | $T({22}) := s0$  | $T({23}) := s1$       | $T({24}) := s01$ |
+ |    9 | $T({25}) := s01$ | $T({26}) := s2$       | $T({27}) := s$   |
+ |   10 | $T({28}) := s0$  | $T({29}) := s0$       | $T({30}) := 0$   |
+ |   11 | $T({31}) := s1$  | $T({32}) := s1$       | $T({33}) := 0$   |
+ |   12 | $T({34}) := s2$  | $T({35}) := s2$       | $T({36}) := 0$   |
+ |   13 | $T({37}) := s$   | $T({38}) := (s-1)^-1$ | $T({39}) := 0$   |
+ |------+------------------+-----------------------+------------------|
+ 
+* Permutation Psi
+  | Gate | a                    | b                    | c                    |
+  |------+----------------------+----------------------+----------------------|
+  |    1 | $\Psi(1) := 9$       | $\Psi(2):={27}$      | $\Psi(3) := 3$       |
+  |    2 | $\Psi(4) := {10}$    | $\Psi(5):={13}$      | $\Psi(6) := 7$       |
+  |    3 | $\Psi(7) := 6$       | $\Psi(8) := {16}$    | $\Psi(9) := {19}$    |
+  |    4 | $\Psi({10}) := {11}$ | $\Psi({11}) := 4$    | $\Psi({12}) := {12}$ |
+  |    5 | $\Psi({13}) := {14}$ | $\Psi({14}) := {5}$  | $\Psi({15}) := {15}$ |
+  |    6 | $\Psi({16}) := {17}$ | $\Psi({17}) := {8}$  | $\Psi({18}) := {18}$ |
+  |    7 | $\Psi({19}) := {1}$  | $\Psi({20}) := {20}$ | $\Psi({21}) := {21}$ |
+  |    8 | $\Psi({22}) := {28}$ | $\Psi({23}) := {31}$ | $\Psi({24}) := {25}$ |
+  |    9 | $\Psi({25}) := {24}$ | $\Psi({26}) := {34}$ | $\Psi({27}) := {37}$ |
+  |   10 | $\Psi({28}) := {29}$ | $\Psi({29}) := {22}$ | $\Psi({30}) := {30}$ |
+  |   11 | $\Psi({31}) := {31}$ | $\Psi({32}) := {31}$ | $\Psi({33}) := {33}$ |
+  |   12 | $\Psi({34}) := {35}$ | $\Psi({35}) := {35}$ | $\Psi({36}) := {36}$ |
+  |   13 | $\Psi({37}) := {2}$  | $\Psi({38}) := {38}$ | $\Psi({39}) := {39}$ |
+  |------+----------------------+----------------------+----------------------|
+
+* Gate Polynomial
+Summerizing all of our constrains in one polynomial:
+
+$Q_l(x)*a(x) + Q_r(x)*b(x) + Q_o(x)* c(x) + Q_m(x)*a(x)*b(x) + Q_c(x) = 0$
+
diff --git a/content/1-Cryptography/materials/zk-factorization-example/gate-constrains.tex b/content/1-Cryptography/materials/zk-factorization-example/gate-constrains.tex
new file mode 100644
index 00000000..0a9969b3
--- /dev/null
+++ b/content/1-Cryptography/materials/zk-factorization-example/gate-constrains.tex
@@ -0,0 +1,243 @@
+% Created 2024-05-22 Wed 06:20
+% Intended LaTeX compiler: pdflatex
+\documentclass[11pt]{article}
+\usepackage[utf8]{inputenc}
+\usepackage[T1]{fontenc}
+\usepackage{graphicx}
+\usepackage{longtable}
+\usepackage{wrapfig}
+\usepackage{rotating}
+\usepackage[normalem]{ulem}
+\usepackage{amsmath}
+\usepackage{amssymb}
+\usepackage{capt-of}
+\usepackage{hyperref}
+\date{\today}
+\title{}
+\hypersetup{
+ pdfauthor={},
+ pdftitle={},
+ pdfkeywords={},
+ pdfsubject={},
+ pdfcreator={Emacs 29.3 (Org mode 9.6.15)}, 
+ pdflang={English}}
+\begin{document}
+
+
+\section{Gate constrains:}
+\label{sec:org949341d}
+
+\subsection{Multiplication constrain:}
+\label{sec:org23a6312}
+
+\begin{itemize}
+\item \(r * s = n\)
+\end{itemize}
+
+\subsection{constraining \(r \neq 1\)}
+\label{sec:org60688ab}
+\begin{itemize}
+\item Making sure that the prover doesn't fool the verifier by using 1 as a factor.
+\item We force them to use r-1's inverse.
+\item \((r-1)(r-1)^{-1} = 1 \Rightarrow  r * (r-1)^{-1} - (r-1)^{-1} = 1\)
+\end{itemize}
+
+\subsection{constraining \(0< r < 8\):}
+\label{sec:orgd3ea1d2}
+We need to make sure r \% p = r
+otherwise prover can cheat because everything has an inverse in \(FF_p\)
+We use Binary decomposition:
+\begin{itemize}
+\item \(r0 + 2 * r1 = r01\)
+\item \(r01 + 4 * r2 = r\)
+\item \(r0 * r0 - r0 = 0\)
+\item \(r1 * r1 - r1 = 0\)
+\item \(r2 * r2 - r2 = 0\)
+\end{itemize}
+
+\subsection{similarly constraining \(b\):}
+\label{sec:org3a9fab7}
+
+\begin{itemize}
+\item \(s0 + 2 * s1 = s01\)
+\item \(s01 + 4 * s2 = s\)
+\item \(s0 * s0 - s0 = 0\)
+\item \(s1 * s1 - s1 = 0\)
+\item \(s2 * s2 - s2 = 0\)
+\item \(s * (s-1)^{-1} - (s-1)^{-1} = 1\)
+\end{itemize}
+
+\section{Universal way of summerizing constrains:}
+\label{sec:org9c3240b}
+\(Q_l*a + Q_r*b + Q_o*c + Q_m*a*b + Q_c = 0\)
+
+\section{Constrain for factorization:}
+\label{sec:orgea626c6}
+\(Q_l*a + Q_r*b + Q_o*c + Q_m*a*b + Q_c = 0\)
+
+\begin{center}
+\begin{tabular}{rrrrrlllr}
+Gate No & Q\textsubscript{l} & Q\textsubscript{r} & Q\textsubscript{o} & Q\textsubscript{m} & Q\textsubscript{c} & a & b & c\\[0pt]
+\hline
+1 & 0 & 0 & 0 & 1 & -n & r & s & 0\\[0pt]
+\end{tabular}
+\end{center}
+
+\section{Constrain table \(a\)}
+\label{sec:orgfa4de93}
+\(Q_l*a + Q_r*b + Q_o*c + Q_m*a*b + Q_c = 0\)
+
+\begin{center}
+\begin{tabular}{rrrrrrllr}
+Gate No & Q\textsubscript{l} & Q\textsubscript{r} & Q\textsubscript{o} & Q\textsubscript{m} & Q\textsubscript{c} & a & b & c\\[0pt]
+\hline
+2 & 1 & 2 & -1 & 0 & 0 & r0 & r1 & r01\\[0pt]
+3 & 1 & 4 & -1 & 0 & 0 & r01 & r2 & r\\[0pt]
+4 & -1 & 0 & 0 & 1 & 0 & r0 & r0 & 0\\[0pt]
+5 & -1 & 0 & 0 & 1 & 0 & r1 & r1 & 0\\[0pt]
+6 & -1 & 0 & 0 & 1 & 0 & r2 & r2 & 0\\[0pt]
+7 & 0 & -1 & 0 & 1 & -1 & r & (r-1)\textsuperscript{-1} & 0\\[0pt]
+\hline
+\end{tabular}
+\end{center}
+
+\section{Constrain table  \(b\)}
+\label{sec:orgcce3822}
+\(Q_l*a + Q_r*b + Q_o*c + Q_m*a*b + Q_c = 0\)
+
+\begin{center}
+\begin{tabular}{rrrrrrllr}
+Gate No & Q\textsubscript{l} & Q\textsubscript{r} & Q\textsubscript{o} & Q\textsubscript{m} & Q\textsubscript{c} & a & b & c\\[0pt]
+\hline
+8 & 1 & 2 & -1 & 0 & 0 & s0 & s1 & s01\\[0pt]
+9 & 1 & 4 & -1 & 0 & 0 & s01 & s2 & s\\[0pt]
+10 & -1 & 0 & 0 & 1 & 0 & s0 & s0 & 0\\[0pt]
+11 & -1 & 0 & 0 & 1 & 0 & s1 & s1 & 0\\[0pt]
+12 & -1 & 0 & 0 & 1 & 0 & s2 & s2 & 0\\[0pt]
+13 & 0 & -1 & 0 & 1 & -1 & s & (s-1)\textsuperscript{-1} & 0\\[0pt]
+\hline
+\end{tabular}
+\end{center}
+
+\section{all constraints for wiring}
+\label{sec:org582ca25}
+\begin{center}
+\begin{tabular}{rrrrrrllr}
+Gate No & Q\textsubscript{l} & Q\textsubscript{r} & Q\textsubscript{o} & Q\textsubscript{m} & Q\textsubscript{c} & a & b & c\\[0pt]
+\hline
+1 & 0 & 0 & 0 & 1 & -n & r & s & 0\\[0pt]
+2 & 1 & 2 & -1 & 0 & 0 & r0 & r1 & r01\\[0pt]
+3 & 1 & 4 & -1 & 0 & 0 & r01 & r2 & r\\[0pt]
+4 & -1 & 0 & 0 & 1 & 0 & r0 & r0 & 0\\[0pt]
+5 & -1 & 0 & 0 & 1 & 0 & r1 & r1 & 0\\[0pt]
+6 & -1 & 0 & 0 & 1 & 0 & r2 & r2 & 0\\[0pt]
+7 & 0 & -1 & 0 & 1 & -1 & r & (r-1)\textsuperscript{-1} & 0\\[0pt]
+8 & 1 & 2 & -1 & 0 & 0 & s0 & s1 & s01\\[0pt]
+9 & 1 & 4 & -1 & 0 & 0 & s01 & s2 & s\\[0pt]
+10 & -1 & 0 & 0 & 1 & 0 & s0 & s0 & 0\\[0pt]
+11 & -1 & 0 & 0 & 1 & 0 & s1 & s1 & 0\\[0pt]
+12 & -1 & 0 & 0 & 1 & 0 & s2 & s2 & 0\\[0pt]
+13 & 0 & -1 & 0 & 1 & -1 & s & (s-1)\textsuperscript{-1} & 0\\[0pt]
+\hline
+\end{tabular}
+\end{center}
+
+\section{Trace polynomial for wiring with omega}
+\label{sec:org836884f}
+\begin{center}
+\begin{tabular}{rlll}
+Gate & a & b & c\\[0pt]
+\hline
+1 & \(T(\omega^1) := r\) & \(T(\omega^2):=s\) & \(T(\omega^3) :=  0\)\\[0pt]
+2 & \(T(\omega^4) := r0\) & \(T(\omega^5):=r1\) & \(T(\omega^6) := r01\)\\[0pt]
+3 & \(T(\omega^7) := r01\) & \(T(\omega^8) := r2\) & \(T(\omega^9) := r\)\\[0pt]
+4 & \(T(\omega^{10}) := r0\) & \(T(\omega^{11}) := r0\) & \(T(\omega^{12}) := 0\)\\[0pt]
+5 & \(T(\omega^{13}) := r1\) & \(T(\omega^{14}) := r1\) & \(T(\omega^{15}) := 0\)\\[0pt]
+6 & \(T(\omega^{16}) := r2\) & \(T(\omega^{17}) := r2\) & \(T(\omega^{18}) := 0\)\\[0pt]
+7 & \(T(\omega^{19}) := r\) & \(T(\omega^{20}) := (r-1)^-1\) & \(T(\omega^{21}) := 0\)\\[0pt]
+8 & \(T(\omega^{22}) := s0\) & \(T(\omega^{23}) := s1\) & \(T(\omega^{24}) := s01\)\\[0pt]
+9 & \(T(\omega^{25}) := s01\) & \(T(\omega^{26}) := s2\) & \(T(\omega^{27}) := s\)\\[0pt]
+10 & \(T(\omega^{28}) := s0\) & \(T(\omega^{29}) := s0\) & \(T(\omega^{30}) := 0\)\\[0pt]
+11 & \(T(\omega^{31}) := s1\) & \(T(\omega^{32}) := s1\) & \(T(\omega^{33}) := 0\)\\[0pt]
+12 & \(T(\omega^{34}) := s2\) & \(T(\omega^{35}) := s2\) & \(T(\omega^{36}) := 0\)\\[0pt]
+13 & \(T(\omega^{37}) := s\) & \(T(\omega^{38}) := (s-1)^-1\) & \(T(\omega^{39}) := 0\)\\[0pt]
+\hline
+\end{tabular}
+\end{center}
+
+
+\section{Permutation Psi with omega}
+\label{sec:org35f2b9a}
+\begin{center}
+\begin{tabular}{rlll}
+Gate & a & b & c\\[0pt]
+\hline
+1 & \(\Psi(\omega^1) := \omega^9\) & \(\Psi(\omega^2):=\omega^{27}\) & \(\Psi(\omega^3) := \omega^3\)\\[0pt]
+2 & \(\Psi(\omega^4) := \omega^{10}\) & \(\Psi(\omega^5):=\omega^{13}\) & \(\Psi(\omega^6) := \omega^7\)\\[0pt]
+3 & \(\Psi(\omega^7) := \omega^6\) & \(\Psi(\omega^8) := \omega^{16}\) & \(\Psi(\omega^9) := \omega^{19}\)\\[0pt]
+4 & \(\Psi(\omega^{10}) := \omega^{11}\) & \(\Psi(\omega^{11}) := \omega^4\) & \(\Psi(\omega^{12}) := \omega^{12}\)\\[0pt]
+5 & \(\Psi(\omega^{13}) := \omega^{14}\) & \(\Psi(\omega^{14}) := \omega^{5}\) & \(\Psi(\omega^{15}) := \omega^{15}\)\\[0pt]
+6 & \(\Psi(\omega^{16}) := \omega^{17}\) & \(\Psi(\omega^{17}) := \omega^{8}\) & \(\Psi(\omega^{18}) := \omega^{18}\)\\[0pt]
+7 & \(\Psi(\omega^{19}) := \omega^{1}\) & \(\Psi(\omega^{20}) := \omega^{20}\) & \(\Psi(\omega^{21}) := \omega^{21}\)\\[0pt]
+8 & \(\Psi(\omega^{22}) := \omega^{28}\) & \(\Psi(\omega^{23}) := \omega^{31}\) & \(\Psi(\omega^{24}) := \omega^{25}\)\\[0pt]
+9 & \(\Psi(\omega^{25}) := \omega^{24}\) & \(\Psi(\omega^{26}) := \omega^{34}\) & \(\Psi(\omega^{27}) := \omega^{37}\)\\[0pt]
+10 & \(\Psi(\omega^{28}) := \omega^{29}\) & \(\Psi(\omega^{29}) := \omega^{22}\) & \(\Psi(\omega^{30}) := \omega^{30}\)\\[0pt]
+11 & \(\Psi(\omega^{31}) := \omega^{31}\) & \(\Psi(\omega^{32}) := \omega^{31}\) & \(\Psi(\omega^{33}) := \omega^{33}\)\\[0pt]
+12 & \(\Psi(\omega^{34}) := \omega^{35}\) & \(\Psi(\omega^{35}) := \omega^{35}\) & \(\Psi(\omega^{36}) := \omega^{36}\)\\[0pt]
+13 & \(\Psi(\omega^{37}) := \omega^{2}\) & \(\Psi(\omega^{38}) := \omega^{38}\) & \(\Psi(\omega^{39}) := \omega^{39}\)\\[0pt]
+\hline
+\end{tabular}
+\end{center}
+
+\section{Trace polynomial for wiring}
+\label{sec:org232436d}
+\begin{center}
+\begin{tabular}{rlll}
+Gate & a & b & c\\[0pt]
+\hline
+1 & \(T(1) := r\) & \(T(2):=s\) & \(T(3) :=  0\)\\[0pt]
+2 & \(T(4) := r0\) & \(T(5):=r1\) & \(T(6) := r01\)\\[0pt]
+3 & \(T(7) := r01\) & \(T(8) := r2\) & \(T(9) := r\)\\[0pt]
+4 & \(T({10}) := r0\) & \(T({11}) := r0\) & \(T({12}) := 0\)\\[0pt]
+5 & \(T({13}) := r1\) & \(T({14}) := r1\) & \(T({15}) := 0\)\\[0pt]
+6 & \(T({16}) := r2\) & \(T({17}) := r2\) & \(T({18}) := 0\)\\[0pt]
+7 & \(T({19}) := r\) & \(T({20}) := (r-1)^-1\) & \(T({21}) := 0\)\\[0pt]
+8 & \(T({22}) := s0\) & \(T({23}) := s1\) & \(T({24}) := s01\)\\[0pt]
+9 & \(T({25}) := s01\) & \(T({26}) := s2\) & \(T({27}) := s\)\\[0pt]
+10 & \(T({28}) := s0\) & \(T({29}) := s0\) & \(T({30}) := 0\)\\[0pt]
+11 & \(T({31}) := s1\) & \(T({32}) := s1\) & \(T({33}) := 0\)\\[0pt]
+12 & \(T({34}) := s2\) & \(T({35}) := s2\) & \(T({36}) := 0\)\\[0pt]
+13 & \(T({37}) := s\) & \(T({38}) := (s-1)^-1\) & \(T({39}) := 0\)\\[0pt]
+\hline
+\end{tabular}
+\end{center}
+
+\section{Permutation Psi}
+\label{sec:org8d7dfb9}
+\begin{center}
+\begin{tabular}{rlll}
+Gate & a & b & c\\[0pt]
+\hline
+1 & \(\Psi(1) := 9\) & \(\Psi(2):={27}\) & \(\Psi(3) := 3\)\\[0pt]
+2 & \(\Psi(4) := {10}\) & \(\Psi(5):={13}\) & \(\Psi(6) := 7\)\\[0pt]
+3 & \(\Psi(7) := 6\) & \(\Psi(8) := {16}\) & \(\Psi(9) := {19}\)\\[0pt]
+4 & \(\Psi({10}) := {11}\) & \(\Psi({11}) := 4\) & \(\Psi({12}) := {12}\)\\[0pt]
+5 & \(\Psi({13}) := {14}\) & \(\Psi({14}) := {5}\) & \(\Psi({15}) := {15}\)\\[0pt]
+6 & \(\Psi({16}) := {17}\) & \(\Psi({17}) := {8}\) & \(\Psi({18}) := {18}\)\\[0pt]
+7 & \(\Psi({19}) := {1}\) & \(\Psi({20}) := {20}\) & \(\Psi({21}) := {21}\)\\[0pt]
+8 & \(\Psi({22}) := {28}\) & \(\Psi({23}) := {31}\) & \(\Psi({24}) := {25}\)\\[0pt]
+9 & \(\Psi({25}) := {24}\) & \(\Psi({26}) := {34}\) & \(\Psi({27}) := {37}\)\\[0pt]
+10 & \(\Psi({28}) := {29}\) & \(\Psi({29}) := {22}\) & \(\Psi({30}) := {30}\)\\[0pt]
+11 & \(\Psi({31}) := {31}\) & \(\Psi({32}) := {31}\) & \(\Psi({33}) := {33}\)\\[0pt]
+12 & \(\Psi({34}) := {35}\) & \(\Psi({35}) := {35}\) & \(\Psi({36}) := {36}\)\\[0pt]
+13 & \(\Psi({37}) := {2}\) & \(\Psi({38}) := {38}\) & \(\Psi({39}) := {39}\)\\[0pt]
+\hline
+\end{tabular}
+\end{center}
+
+\section{Gate Polynomial}
+\label{sec:org5caea92}
+Summerizing all of our constrains in one polynomial:
+
+\(Q_l(x)*a(x) + Q_r(x)*b(x) + Q_o(x)* c(x) + Q_m(x)*a(x)*b(x) + Q_c(x) = 0\)
+\end{document}
diff --git a/content/1-Cryptography/materials/zk-factorization-example/how_to_generate_proof_for_circuit.md b/content/1-Cryptography/materials/zk-factorization-example/how_to_generate_proof_for_circuit.md
new file mode 100644
index 00000000..140107fb
--- /dev/null
+++ b/content/1-Cryptography/materials/zk-factorization-example/how_to_generate_proof_for_circuit.md
@@ -0,0 +1,24 @@
+cd pba-content/syllabus/1-Cryptography/zk-proofs/circuit_example_playground
+
+# compile circuit
+
+circom ../circuit.circom --r1cs --wasm --sym
+
+# generate proving and verification keys for the circuit
+
+snarkjs plonk setup circuit.r1cs powers_of_tau/pot10_final.ptau circuit_final.zkey
+snarkjs zkey export verificationkey circuit_final.zkey verification_key.json
+
+# generate witness trace
+
+cd circuit_js
+node generate_witness.js circuit.wasm ../input.json ../witness.wtns
+cd ..
+
+# generate proof for the witness
+
+snarkjs plonk prove circuit_final.zkey witness.wtns proof.json public.json
+
+# verify the proof
+
+snarkjs plonk verify verification_key.json public.json proof.json
diff --git a/content/1-Cryptography/materials/zk-factorization-example/interpolation.sage b/content/1-Cryptography/materials/zk-factorization-example/interpolation.sage
new file mode 100644
index 00000000..cc27f389
--- /dev/null
+++ b/content/1-Cryptography/materials/zk-factorization-example/interpolation.sage
@@ -0,0 +1,152 @@
+from hashlib import sha256
+
+circom_p = 21888242871839275222246405745257275088548364400416034343698204186575808495617
+our_p = 89
+ZKField = FiniteField(our_p)
+#59 | 71^10-1
+
+n = 21
+
+q_l_values = [ 0,  1,  1, -1, -1, -1,  0,  1,  1, -1, -1, -1,  0 ]
+q_r_values = [ 0,  2,  4,  0,  0,  0, -1,  2,  4,  0,  0,  0, -1 ]
+q_o_values = [ 0, -1, -1,  0,  0,  0,  0, -1, -1,  0,  0,  0,  0 ]
+q_m_values = [ 1,  0,  0,  1,  1,  1,  1,  0,  0,  1,  1,  1,  1 ]
+q_c_values = [-n,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0, -1 ]
+
+r = 7
+s = 3
+
+
+def compute_input_output_poly_values(secret_factor):
+   r0 = secret_factor % 2
+   r1 = (secret_factor // 2) % 2
+   r2 = (secret_factor // 4) % 2
+   
+   r01 = r0 + r1*2
+
+   secret_factor_minus_1_inverse = ZKField(secret_factor - 1)^(-1)
+   
+   return ([r0, r01, r0, r1, r2, secret_factor], [r1, r2, r0, r1, r2, secret_factor_minus_1_inverse] , [r01, secret_factor, 0,0,0,0] )
+
+r_input_output_values = compute_input_output_poly_values(r)
+s_input_output_values = compute_input_output_poly_values(s)
+left_input_values = [r] + r_input_output_values[0] + s_input_output_values[0]
+right_input_values = [s] + r_input_output_values[1] + s_input_output_values[1]
+
+c_output_values = [0] + r_input_output_values[2] + s_input_output_values[2]
+
+x_values = range(1, 14)
+
+PolysOnZKField.<x> = PolynomialRing(ZKField)
+
+Qlx = PolysOnZKField.lagrange_polynomial(zip(x_values,q_l_values))
+Qrx = PolysOnZKField.lagrange_polynomial(zip(x_values,q_r_values))
+Qox = PolysOnZKField.lagrange_polynomial(zip(x_values,q_o_values))
+Qmx = PolysOnZKField.lagrange_polynomial(zip(x_values,q_m_values))
+Qcx = PolysOnZKField.lagrange_polynomial(zip(x_values,q_c_values))
+
+ax  = PolysOnZKField.lagrange_polynomial(zip(x_values,left_input_values))
+bx  = PolysOnZKField.lagrange_polynomial(zip(x_values,right_input_values))
+cx  = PolysOnZKField.lagrange_polynomial(zip(x_values,c_output_values))
+
+#Q_l(x)*a(x) + Q_r(x)*b(x) + Q_o(x)* c(x) + Q_m(x)*a(x)*b(x) + Q_c(x) = 0
+gate_poly =  Qlx * ax + Qrx*bx+ Qox * cx + Qmx*ax*bx + Qcx  
+
+zero_test_poly = prod(list(map(lambda x_val: x - x_val,x_values)))
+
+print("All Gate polynomial: ", gate_poly)
+print("Zero test polynomial:", zero_test_poly)
+print("The remainder of gatepoly/zerotest: ",gate_poly % zero_test_poly)
+
+qx = gate_poly / zero_test_poly
+print("q(x):",qx)
+
+# bulid the trace polynomial T
+T = [0]*39
+for i in range(0,13):
+   T[i*3] = left_input_values[i]
+   T[i*3 + 1 ] = right_input_values[i]
+   T[i*3 + 2 ] = c_output_values[i]
+
+psi = [ 9, 27,  3,
+        10, 13, 7,
+        6, 16, 19,
+        11, 4, 12,
+        14, 5, 15,
+        17,8,18,
+        1,20, 21,
+        28, 31, 25,
+        24, 34, 37,
+        29, 22, 30,
+        32, 23, 33,
+        35, 26, 36,
+        2, 38, 39,
+        ]
+
+#check the permutation 
+for i in range(0,39):
+   if (T[i] != T[psi[i]-1]):
+      print("T's wiring doesn't match at index ", i)
+
+#naive wire test
+x_values = range(1, 40)
+
+Tx = PolysOnZKField.lagrange_polynomial(zip(x_values, T))
+psix = PolysOnZKField.lagrange_polynomial(zip(x_values, psi))
+
+zero_test_poly = prod(list(map(lambda x_val: x - x_val,x_values)))
+
+naive_wire_poly = Tx(psix(x)) - Tx(x)
+
+print("Naive wire  polynomial: ", naive_wire_poly)
+print("Zero test polynomial:", zero_test_poly)
+print("The remainder of wirepoly/zerotest: ",naive_wire_poly % zero_test_poly)
+
+u1 = ZKField('0x'+hashlib.sha256("Hello, PBA! I'm u1".encode()).hexdigest())
+u2 = ZKField('0x'+hashlib.sha256("Hello, PBA! I'm u2".encode()).hexdigest())
+
+#$\prod_{a\in\{1,..,39\}}\frac{u_1 - u_1 \times a - T(a)}{u_1 - u_2 \times \psi(a) - T(\psi(a))}
+f_numerator = [0]*40
+g_denominator = [0]*40
+for i in range(0, 39):
+   f_numerator[i] = u1 - u2 * psi[i] - T[psi[i]-1]
+   g_denominator[i] = u1 - u2 * (i + 1) - T[i]
+
+#because our group is not cyclic of size 39 we need to deal with t(40)
+f_numerator[39] = f_numerator[0] 
+g_denominator[39] = g_denominator[0]
+
+for i in range(0, 39):
+   if (f_numerator[i] != g_denominator[psi[i]-1]):
+      print("perm wiring doesn't match at index ", i)
+
+p_acc = ZKField(1)
+for i in range(0, 39):
+   p_acc *= f_numerator[i]/g_denominator[psi[i]-1]
+
+assert(p_acc == 1)
+
+t = [0]*40
+t[0] = f_numerator[0]/g_denominator[0]
+for i in range(1,40):
+   t[i] = t[i-1] * f_numerator[i]/g_denominator[i]
+
+x_values = range(1, 41)
+fx = PolysOnZKField.lagrange_polynomial(zip(x_values,f_numerator))
+gx = PolysOnZKField.lagrange_polynomial(zip(x_values,g_denominator))
+tx = PolysOnZKField.lagrange_polynomial(zip(x_values,t))
+
+perm_poly = tx(x+1) * gx(x+1) - tx(x) * fx(x+1)
+for i in range(1,40):
+   assert(perm_poly(i) == 0)
+
+print("Perm check polynomial: ", perm_poly)
+print("Zero test polynomial:", zero_test_poly)
+print("The remainder of permpoly/zerotest: ", perm_poly % zero_test_poly)
+
+qx = perm_poly / zero_test_poly
+print("q(x):",qx)
+
+# y^2 = x^3 + 8*x + 10 embeding degree 8 on 101 order 89
+# (trace_poly(r) - trace_poly(tau)) / (r - tau)
+
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diff --git a/content/1-Cryptography/materials/zk-factorization-example/trace-polynomial-known-points-with-wirings.xopp b/content/1-Cryptography/materials/zk-factorization-example/trace-polynomial-known-points-with-wirings.xopp
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+---
+title: Economics Basics
+description: Economics Basics for Web3 engineers
+duration: 2 hour
+---
+
+# Economics Module
+
+---
+
+# Overview
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Economics Basics</li>
+<li class="fragment">Game Theory Basics</li>
+<li class="fragment">Price Finding Mechanisms</li>
+<li class="fragment">The Economics of Polkadot</li>
+</ul>
+
+</pba-flex>
+
+---
+
+# Grading
+
+- Focus on the pure economic concepts and not diving into blockchain yet.
+- That is covered by another lecture.
+- Economics of Polkadot
+- Interactive: Ask questions!
+
+---
+
+# Grading
+
+- Exam for onsite students at Saturday.
+- Coding Assignment for onsite and remote students.
+
+---
+
+# Economics Basics
+
+---
+
+<pba-cols>
+<pba-col>
+<pba-flex center>
+
+#### Cryptography
+
+- Provides assurances about the conduct of machines
+- Objective in nature
+- Promotes (mostly) deterministic actions
+- Serves as a toolbox to secure certain actions in the digital world.
+
+</pba-flex>
+</pba-col>
+<pba-col>
+<pba-flex center>
+
+#### Economics
+
+- Offers predictions about the actions of people
+- Intrinsically subjective
+- Driven by individual preferences
+- Serves as a toolbox to understand which actions humans are likely to undertake.
+
+</pba-flex>
+</pba-col>
+</pba-cols>
+
+🤖$~~~$ 🤝 $~~~$👪
+
+Notes:
+
+- Cryptography would be meaningless without humans using it.
+- Crypto & Econ pair well! Together they are the toolbox to design unstoppable systems.
+- They have a great symphony: where cryptography's has boundaries, economics offers solutions and vice versa.
+- Example from crypto module: Commit-reveal scheme is cryptographically secure. But how can we make sure entities reveal if it is to their disadvantage?
+
+---
+
+## Why are economic concepts<br/>important?
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">help make better decisions in daily- and professional life.</li>
+<li class="fragment">model & reason about how others make decisions.</li>
+<li class="fragment">better understand (crypto-)economic protocols.</li>
+<li class="fragment">understand the broader context of Web3/blockchain.</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- It is also important to understand the limits of these economic concepts and when they might not work as intended.
+
+---
+
+## Outline
+
+<pba-flex center>
+
+<ul>
+<li class="fragment"><strong>Lesson</strong>
+    <ul>
+    <li class="fragment">Incentives: What motivates others to do things?</li>
+    <li class="fragment">Demand & Supply: Market Equilibrium, Influences, and Elasticity.</li>
+    <li class="fragment">Market Forms: Monopoly, Oligopoly, and Perfect Competition.</li>
+    <li class="fragment">Economics of Specialization: Comparative Advantage, Opportunity Costs, Gains from Trade.</li>
+    <li class="fragment">Time as Ultimate Resource: The interaction between Time and Value.</li>
+    <li class="fragment">Behavioral Biases: Where human decision making might be different than traditional economic theories predict.</li>
+    </ul>
+</li>
+<li class="fragment"><strong>Discussion & Workshop</strong>
+    <ul>
+    <li class="fragment">Discussions to foster and apply concepts we learned.</li>
+    <li class="fragment">Hands-on applications.</li>
+    </ul>
+</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Guiding Human Behavior
+
+> An incentive is a bullet, a key:<br/>an often tiny object with astonishing power to change a situation.<br/>-- Steven Levitt --
+
+Notes:
+
+- Human behavior is driven by incentives.
+- The aggregation of these behaviors lead to societies.
+- Carefully designing incentives lays the ground for functioning systems.
+- You might be asked to implement certain protocols, which you have to judge if they make sense / can be improved.
+
+---
+
+## Understanding Incentives
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Motivate individuals or groups to perform certain actions.</li>
+<li class="fragment">Historically, incentives were designed to influence human behavior both on a macroeconomic and microeconomic level.</li>
+<li class="fragment">Most commonly, people refer to money, that fall under the umbrella of extrinsic incentives.</li>
+<li class="fragment">But not all incentives are monetary!</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Different Types of Economic Incentives
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">In a workplace setting (microeconomic level), employees are often motivated by various forms of economic incentives:
+    <ul>
+    <li class="fragment">Flat Rate: A fixed amount of salary irrespective of performance.</li>
+    <li class="fragment">Piece Rate: Pay based on the quantity of output produced.</li>
+    <li class="fragment">Bonus: Additional rewards for excellent performance.</li>
+    <li class="fragment">Relative Incentives: Rewards relative to the performance of others (competitive incentives).</li>
+    </ul>
+</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- **Question: What are the advantages / disadvantages of those incentives?**
+
+---
+
+## Rationality in Economics
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Economic theories often assume rationality, implying that actors:
+    <ul>
+    <li class="fragment">Are primarily driven by monetary gains (payoff maximization).</li>
+    <li class="fragment">Act in self-interest.</li>
+    <li class="fragment">Have unlimited cognitive resources.</li>
+    </ul>
+</li>
+<li class="fragment">Remark: In this, all factors can be translated into monetary terms.</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- For example: should you do a vacation at the beach in Spain for two weeks or travel through France for two weeks?
+- A rational agent would compile all the factors into a single dimension (utility or value) and maximizes for payout.
+
+---
+
+## Incentives often work well
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Interest rates set by central banks.</li>
+<li class="fragment">Lower rates: Encourage borrowing and investing.</li>
+<li class="fragment">Higher rates: Slow down inflation and stabilize the economy.</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Incentives can Backfire
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">In India during British rule, the British Government was concerned about the large number of venomous Cobras.
+    <ul>
+    <li class="fragment">They offered a bounty for every dead cobra.</li>
+    <li class="fragment">People started to breed cobras at home to sell them.</li>
+    <li class="fragment">Once the government stopped the program, breeders released the cobras causing larger numbers than before.</li>
+    </ul>
+</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Goodhart's Law
+
+> When a measure becomes a target, it ceases to be a good measure
+
+---
+
+## Crowding Out
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">In Haifa (Israel) parents often got their kids late from day care.</li>
+    <ul>
+    <li class="fragment">This caused childcare workers frustration.</li>
+    <li class="fragment">Idea: fine parents for getting their kids late.</li>
+    <li class="fragment">The program was rolled out in some day cares and not others.</li>
+    </ul>
+<li class="fragment">Traditional economic theory:</li>
+    <ul>
+    <li class="fragment">Less or at least equally many late parents.</li>
+    <li class="fragment">BUT: The opposite happened, the number of late parents even increased.</li>
+    <li class="fragment">After the fine was abolished, parents still were more late.</li>
+    </ul>
+</li>
+<li class="fragment">Extrinsic motivation can crowd out intrinsic motivation.</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- **Question: Why did that happen?**
+- Gneezy & Rustichini (2000): A fine is a price.
+
+---
+
+## The Power of Intrinsic Incentives
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Beyond monetary gain, people are also motivated by intrinsic factors.</li>
+    <ul>
+    <li class="fragment">Social preferences (Reciprocity, Fairness, Social Norms, Inequality Aversion, Altruism).</li>
+    <li class="fragment">Personal morals, and deeply-held beliefs.</li>
+    </ul>
+<li class="fragment">Economic models often fail to account for these motivations, leading to unexpected outcomes in real-world applications.</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## From Humans to Automated Agents
+
+<pba-flex center>
+<ul>
+<li class="fragment">The digital age emphasizes the importance of automated actors in our economic systems.</li>
+<li class="fragment">Algorithms and bots, respond to incentives, often financial ones, automatically.</li>
+<li class="fragment">This shifts the application of incentives beyond a human context and into the realm of digital systems and automated processes.</li>
+</ul>
+</pba-flex>
+
+Notes:
+
+- Still, not always financial incentives - reputation scores
+- While automated agents existed for a while, they become much more accessible for everybody due to blockchain technology
+- Your electric car might soon have a wallet that automatically pays for charging at a red light.
+- Or you might be able to pay for priority green lights.
+
+---
+
+## Conclusion
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Incentives continue to be fundamental to interactions in society, whether among humans or between automated systems.</li>
+<li class="fragment">As we understand more about incentives in different contexts, we can better design them to influence behavior effectively.</li>
+<li class="fragment">Intrinsic motivations remain important, but in certain contexts, like automated systems, monetary incentives also play a significant role.</li>
+<li class="fragment">The challenge is to balance these factors to achieve the desired outcomes.</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Demand & Supply: The Pillars of Market Equilibrium
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">A common model to help predict and rationalize the price<br/>which emerges from a market.</li>
+<li class="fragment">Can be used to (gu)estimate the quantity<br/>of produced goods vs. their market prices.</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- A famous artist dies and her art increases in price.
+- An unusually nice summer reduces hotel prices in popular vacations destinations.
+
+---
+
+## Law of Demand: A Basic Principle
+
+- When prices increase, quantity demanded of a good (generally) decreases.
+
+Notes:
+
+- **Question: Anybody know exceptions?**
+- Exception are "Veblen goods" where demand increases when price increases.
+  These are typically luxury goods that signal something (e.g. status, reputation) in addition to being useful to consumption.
+  Examples are jewelry, luxury cars, etc.
+- This is not a contradiction to the law of demand because the good's social value depends on the price; i.e., the good "changes" and becomes more desirable as the price increases.
+
+---
+
+## Visualizing Demand: The Demand Curve
+
+<img rounded style="width:900px" src="./img/2.1-market-demand.png" />
+
+Notes:
+
+- **Question: What influences the aggregate market demand?**
+- The market demand is the sum of all individual curves.
+
+---
+
+## Influences on demand?
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Price (Demand moves along the curve)</li>
+<li class="fragment">Size of consumer base</li>
+<li class="fragment">Average disposable income of consumer base</li>
+<li class="fragment">Price of substitution goods</li>
+<li class="fragment">Preferences prevalent within consumer base</li>
+<li class="fragment">Expectations prevalent within consumer base</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- In the ice cream example, a substitution good could be frozen yoghurt: if its price goes down, the demand for ice cream will decrease.
+- If people's appetite for ice cream increases (perhaps via advertisement), the demand will increase.
+- In people expect a shortage of ice cream in the near future, the demand will increase immediately.
+
+---
+
+## Moving the demand curve
+
+<img rounded style="width:1100px" src="./img/2.1-demand-curve.png" />
+
+---
+
+## Law of Supply: The Other Side of the Coin
+
+- If the price of a good increases, the quantity supplied also increases
+
+(because suppliers can make more profit!).
+
+Notes:
+
+- That is, assuming that suppliers manage to sell all produced goods at said price.
+- For example, if the ice cream price increases the store will hire a second employee to sell more scoops per hour.
+- As another example, some petroleum deposits are easier and cheaper to extract than others, so some deposits will be extracted only if the oil price is above a certain threshold.
+
+---
+
+## Demand and Supply Interplay: Market Equilibrium
+
+<img rounded style="width: 600px;" src="./img/2.1-supply-and-demand.png" />
+
+- What happens when Price is higher than the Eq. Price?
+- What if the Quantity is lower than the Eq. Quantity?
+- Moving either supply or demand leads to new Eq.
+
+Notes:
+
+- Where the curves meet we obtain a point of equilibrium, which establishes a market quantity and a market price.
+- If price is higher than equilibrium price -> more supply than demand -> some goods remain unsold -> sellers will be forced to reduce the price to get rid of their stock.
+- If price is lower than equilibrium price -> more demand than supply -> shortages of the good -> sellers will increase the price to marke more profit.
+- Hence, we always converge to the equilibrium price.
+- If the quantity supplied is too low -> business opportunity to supply more unit of the good and make a profit -> eventually someone will increase the supply quantity.
+
+---
+
+## Elasticity
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Measures how much buyers and sellers respond to changes in market conditions.</li>
+<li class="fragment">Sensitivity of quantity demanded or supplied to changes in price.</li>
+    <ul>
+    <li class="fragment">High elasticity: small price changes have large impact on quantity demanded or supplied.</li>
+    <li class="fragment">Low elasticity (== inelasticity): price changes do not affect quantity demanded or supplied.</li>
+    </ul>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- **Question**: Examples for each?
+  - High elasticity: luxury goods or with high substitutes, where buyers can easily adjust their consumption. Butter / Magerine
+  - Low elasticity: essential goods such as energy.
+
+---
+
+<div style="text-align: center;">
+    <img rounded style="width: 1200px; margin-right: 10px;" src="./img/2.1-elasticity-1.png" />
+</div>
+
+Notes:
+
+- Which one represents low / high elasticity?
+
+---
+
+<div style="text-align: center;">
+    <img rounded style="width: 1200px; margin-right: 10px;" src="./img/2.1-elasticity-2.png" />
+</div>
+
+Notes:
+
+- Inelastic: A rather big price change leads to little change in quantity.
+- Elastic: A rather big price change leads to a large change in quantity.
+
+---
+
+<div style="text-align: center;">
+    <img rounded style="width: 1200px; margin-right: 10px;" src="./img/2.1-elasticity-3.png" />
+</div>
+
+Notes:
+
+- What are some examples?
+- Perfectly Elastic: Ice-Tea
+- Perfectly Inelastic: Insulin
+
+---
+
+## Conclusion: The Dynamics of Demand and Supply
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Demand/supply model forces in markets and can be used to estimate equilibrium quantity/price.</li>
+<li class="fragment">All other things being equal:
+    <ul>
+    <li class="fragment">demand decreases with increasing price.</li>
+    <li class="fragment">supply increases with increasing price.</li>
+    </ul>
+</li>
+<li class="fragment">There are different factors influencing supply & demand curves.
+    <ul>
+    <li class="fragment">Elasticity.</li>
+    <li class="fragment">Some shift the equilibrium on the curve.</li>
+    <li class="fragment">Others move the entire curves.</li>
+    </ul>
+</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Market forms
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Typically, economists distinguish between three market forms.
+    <ul>
+    <li class="fragment">Perfect competition: Many firms, many consumers.</li>
+    <li class="fragment">Oligopoly: Few firms, many consumers.</li>
+    <li class="fragment">Monopoly: One firm, many consumers.</li>
+    </ul>
+</li>
+<li class="fragment">The more competition a firm faces, the less market power it has.</li>
+<li class="fragment">Market power: ability to affect the price (through choosing a certain production level).</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- Special form of Oligopoly is the Duopoly with two firms, something that we see later.
+
+---
+
+## Market Form Examples
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Monopoly:
+    <ul>
+    <li class="fragment">Postal services in many European countries.</li>
+    <li class="fragment">Railway services in many European countries.</li>
+    </ul>
+</li>
+<li class="fragment">Oligopoly:
+    <ul>
+    <li class="fragment">Cloud provider (AWS, Google, ...)</li>
+    <li class="fragment">Mobile phone service.</li>
+    <li class="fragment">Smartphone OS.</li>
+    </ul>
+</li>
+<li class="fragment">Perfect Competition:
+    <ul>
+    <li class="fragment">Consumer products with low barrier to entry (e.g., kebab stand in Berlin, espresso bar in Italy)</li>
+    </ul>
+</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- A monopoly is if only one seller exists
+- A monopolistic market is if there might be more sellers but one is dominant.
+
+---
+
+## Why discuss this?
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Current web2 landscape consists of several firms with a lot of market power in their respective market segment.</li>
+<li class="fragment">We want to understand, from an economic perspective, why too much market power is not a good thing.</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Perfect Competition
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Under perfect competition ...
+    <ul>
+    <li class="fragment">there are so many firms that a single firm's production quantity does not affect market price.</li>
+    <li class="fragment">the marginal costs (cost of one additional unit) of production equals the market price.</li>
+    <li class="fragment">firms have 0 profit.</li>
+    </ul>
+</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- This makes sense: The firm produces up to the point where an additional unit costs exactly what it gets for it on the market.
+- Notice that having the market price be equal to the marginal production costs is pretty surprising, as it is ideal from a point of view of society welfare, even though every firm is acting selfishly.
+- In this perfect world, firms will have zero economic profit, meaning they make just enough money to cover production costs and keep the company running.
+
+---
+
+## Formation of a Monopoly
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Lack of competition: single seller of the good or service, serves the entire market.</li>
+<li class="fragment">Lack of substitutes: there are no similar products that provide the same utility.</li>
+<li class="fragment">Market characterized by a high barrier of entry (e.g. big investment, legal restrictions).</li>
+<li class="fragment">Monopolist is therefore sole price-setter and serves only to maximize their own profits.</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- Monopolies often form when large entities engage in price wars and undercut smaller businesses until they go bankrupt.
+- There are different types of monopolies:
+  - Natural (high barrier of entry, e.g. railroads)
+  - Geographic
+  - Technological
+  - Licensed
+
+---
+
+## Is the Government a Monopoly?
+
+Notes:
+
+- Legitimate use of Force
+- Provider of Public Goods
+- Regulation
+
+---
+
+## Monopoly: Disadvantages
+
+<pba-flex center>
+<ul>
+<li class="fragment">Higher Prices: they are free to set prices arbitrarily.</li>
+<li class="fragment">Inferior Products: there is little incentive to improve the product offered.</li>
+<li class="fragment">Price Discrimination: different prices can be charged for different customers (based on their elasticity).</li>
+<li class="fragment">This leads to sub-optimal pricing and sub-optimal society welfare: consumers either pay more than they should ("monopolist tax") or are excluded from market.</li>
+
+Notes:
+
+- There are three conditions for price discrimination to work:
+  - The company needs to have sufficient market power
+  - The company needs to be able to identify differences in demand.
+  - The company needs to be able to restrict secondary markets.
+- This is a "problem" for the consumers, because it reduces their welfare, i.e., they pay more than they would in a competitive market.
+- It also sometimes even prevents some groups from purchasing.
+
+---
+
+## Example: Antitrust case against Microsoft in 1990s
+
+<pba-flex center>
+<ul>
+<li class="fragment">Microsoft engaged in anti-competitive practices where they intertwined Windows OS with Internet Explorer.</li>
+<li class="fragment">A removal of the IE would lead to a "Blue Screen of Death".</li>
+
+---
+
+## Monopoly: Advantages?
+
+Notes:
+
+- Economies of scale (specialisation)
+- Price stability
+- Potentially higher investments like R&D that benefit customers down the line.
+
+---
+
+## Oligopolies
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Oligopolies are somewhere between monopolies and perfect competition.</li>
+<li class="fragment">Because of the competition between firms
+    <ul>
+    <li class="fragment">prices are lower, and</li>
+    <li class="fragment">overall market participation is higher.</li>
+    </ul>
+</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## What did we learn?
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Markets differ in how much market power the firms possess.</li>
+<li class="fragment">Economics typically distinguishes between three forms (ordered by increasing market power):
+    <ul>
+    <li class="fragment">Perfect competition: many firms in the market.</li>
+    <li class="fragment">Oligopoly: few firms in the market.</li>
+    <li class="fragment">Monopoly: one firm in the market.</li>
+    </ul>
+</li>
+<li class="fragment">The monopoly is generally viewed to cause inefficiencies for consumers and for welfare by economists.</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Economics of Specialization
+
+#### _(or: why bother trading at all?)_
+
+> It is the maxim of every prudent master of a family, never to attempt to make at home what it will cost him more to make than to buy.<br/>-- Adam Smith, 1776 --
+
+Notes:
+
+- In this part, we take a closer look at the following concepts:
+  - Comparative advantage.
+  - Opportunity costs.
+  - Gains from trade.
+
+---
+
+## The economic question
+
+<pba-flex center>
+
+<ul>
+    <li class="fragment">Empirical puzzle: many countries trade even though one has an absolute advantage in producing many of the traded goods.</li>
+    <li class="fragment">E.g., the US is well-equipped to cheaply produce both
+        <ul>
+            <li class="fragment">complex computer chips, and</li>
+            <li class="fragment">agricultural goods (e.g., potatoes).</li>
+        </ul>
+    </li>
+    <li class="fragment">However, the US specializes in producing the former and importing many agricultural goods.</li>
+    <li class="fragment">Question: Why do countries specialize; why do they trade?</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Comparative advantage
+
+<pba-flex center>
+
+<ul>
+    <li class="fragment">Consider the following example:
+        <ul>
+            <li class="fragment">Suppose Alice can produce 10kg of meat and 20kg of potatoes per hour.</li>
+            <li class="fragment">Suppose Bob can produce 2kg of meat and 10kg of potatoes per hour.</li>
+        </ul>
+    </li>
+    <li class="fragment">Alice has an <em>absolute</em> advantage over Bob at producing both goods.
+    <li class="fragment">BUT, Alice has only a <em>comparative</em> advantage over Bob at producing meat.
+        <ul>
+            <li class="fragment">Alice has lower <em>opportunity</em> costs of producing meat (in terms of foregone potatoes).</li>
+            <li class="fragment">That is, to produce one kg of meat Alice gives up much less produced potatoes than Bob would.</li>
+        </ul>
+    </li>
+    <li class="fragment">By the same observation, Bob has a comparative advantage at producing potatoes.</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- Comparative advantage of meat:
+  - Opp. cost Alice: **1kg meat = 2kg potatoes**
+  - Opp. cost Bob: 1kg meat = 5kg potatoes
+- Comparative advantage of potatoes:
+  - Opp. cost Alice: 1kg potatoes = 1/2kg meat
+  - Opp. cost Bob: **1kg potatoes = 1/5kg meat**
+
+---
+
+## Comparative advantage II
+
+<pba-flex center>
+
+<ul>
+    <li class="fragment">If both focus on their comparative advantage, then total welfare is higher than in a situation of autarky!</li>
+    <li class="fragment">Why? Specialization!
+        <ul>
+            <li class="fragment">Suppose both require both meat and potatoes.</li>
+            <li class="fragment">Situation A - Autarky: both divide their time equally between producing meat and producing potatoes.</li>
+            <li class="fragment">Situation B - Trade: Alice focuses most of her time to produce meat and some to produce potatoes, while Bob focuses only on producing potatoes.</li>
+            <li class="fragment">Total production of meat and potatoes is higher in Situation B!</li>
+        </ul>
+    </li>
+    <li class="fragment"><strong>Specialization result</strong>: With trade, both are better off than in Situation A.</li>
+</ul>
+</pba-flex>
+
+Notes:
+
+- Assume one working day with one worker (8 hrs).
+- Autarky:
+  - Alice: 4hrs X 10 meat, 4hrs X 20 potatoes = 40 meat, 80 potatoes
+  - Bob: 4hrs X 2 meat, 4hrs X 10 potatoes = 8 meat, 40 potatoes
+- Trade:
+
+  - Alice: 5hrs X 10 meat, 3hrs X 20 potatoes = 50 meat, 60 potatoes
+  - Bob: 0hrs X 2 meat, 8hrs X 10 potatoes = 0 meat, 80 potatoes
+  - Alice could trade 9 meat for 30 potatoes:
+    - Alice: 41 meat, 90 potatoes
+    - Bob: 9 meat, 50 potatoes
+
+---
+
+## Absolute vs Comparative Advantage
+
+<pba-flex center>
+<ul>
+    <li class="fragment">Alice can produce both meat and potatoes more efficiently than Bob - this is an absolute advantage.</li>
+    <li class="fragment">However, the choice to specialize isn't just about absolute production efficiency.</li>
+    <li class="fragment">What matters for trade is which good Alice can produce at a lower opportunity cost - this is comparative advantage.</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- What does that tell us about daily life?
+  - **Stick with what you are good at**: It's often good to stick things where you have a comparative advantage: For example, assume you are a great software engineer with a job that has a high salary, but you also want to help clean up the ocean. Instead of giving up your job and go clean the ocean, you might want to allocate some of your salary to ocean cleanup, having a larger effect.
+  - **Realize that absolute advantage is not all**Only because one co-worker has a total advantage in two dimensions of the job, another co worker can still have the comparative advantage in one of the tasks.
+  - **Question**: What are your opportunity costs of being here?
+
+---
+
+## Time: The Ultimate Resource
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Time is the one resource that is uniformly distributed and yet cannot be accumulated or saved for later.</li>
+<li class="fragment">It's always moving, never at rest.</li>
+<li class="fragment">This unique property of time lends it incredible implications.</li>
+<li class="fragment">This concept has big impact in the context of money and finance.</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## The Relationship of Time and Money
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Money now is worth more than the same amount in the future.</li>
+<li class="fragment">Why?
+    <ul>
+    <li class="fragment">Again, opportunity costs: The money at hand now could be invested, potentially earning more money.</li>
+    <li class="fragment">This potential earning capacity bestows more value to present money over future money.</li>
+    </ul>
+</ul>
+
+</pba-flex>
+
+---
+
+## Present Value: The Value of Now
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Present Value brings some future value back to the present moment.</li>
+<li class="fragment">It estimates what value would make you indifferent between getting some value now vs. later.</li>
+<li class="fragment">It reflects the worth of a future promise in today's terms, based on the potential earnings we could achieve now.</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- There are formulas to calculate how much a future payout in the future is worth today.
+- You need to make assumptions about your rate of return in the meantime.
+- Often risk free rate is used.
+- **Question: What is 1000$ worth to you now?**
+
+---
+
+## Time Value of Money: A Guiding Principle
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">It underlines the importance of wise decisions today for a brighter tomorrow.</li>
+<li class="fragment">It shows that nothing is for free. You always give up something.</li>
+<li class="fragment">It's a fundamental cornerstone guiding personal savings, investments, and wide-ranging financial decisions.</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Behavioral Biases
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Behavioral biases are systematic errors in decision-making when people use mental shortcuts (heuristics) to process information and make judgments.</li>
+<li class="fragment">For a long time economic theory was built on the assumption that all actors are <em>rational</em>.
+    <ul>
+    <li class="fragment">No regard for fairness, altruism, equality.</li>
+    <li class="fragment">All available information is considered.</li>
+    <li class="fragment">No influence of emotions.</li>
+    </ul>
+</li>
+<li class="fragment">This works well in many circumstances (e.g., on an aggregate level or assuming highly rational actors like firms executives) but in many it doesn't.</li>
+<li class="fragment">Most humans are prone to behavioral biases and are influenced by social preferences.</li>
+</ul>
+
+</pba-flex>
+
+---
+
+## Behavioral Economics
+
+<pba-flex center>
+
+<ul>
+<li class="fragment">Behavioral economics is mainly concerned with the bounds of rationality of economic agents.</li>
+<li class="fragment">Influenced by psychological aspects such as emotions, cognition as well as cultural and societal factors.</li>
+<li class="fragment">Psychologist Daniel Kahnemann received the 2002 Nobel Prize for <em>Prospect Theory</em>, a fundamental theory in Behavioral Economics.</li>
+<li class="fragment">PT models the fact that individuals assess their losses differently than their gains.</li>
+</ul>
+</pba-flex>
+
+---
+
+## Behavioral Economics
+
+<pba-flex center>
+
+<ul>
+<li class="fragment"><strong><em>Behavior is not random!</em></strong></li>
+<li class="fragment">Key behavioral biases include:
+    <ul>
+    <li class="fragment"><strong>Confirmation Bias</strong> - Decision makers focus on information that cater to their prior belief / opinion and neglect other information.</li>
+    <li class="fragment"><strong>Sunk Cost Fallacy</strong> - Instead of cutting losses, decision makers continue to pour resources into a failed endeavour.</li>
+    <li class="fragment"><strong>Herding Effect</strong> - People follow the crowd without making their own informed decision.</li>
+    <li class="fragment"><strong>Gambler's Fallacy</strong> - In many situations probabilities of repeated events are independent from each other. Often decision makers fail to understand this.</li>
+    <li class="fragment"><strong>Default Effect</strong> - People tend to stick with pre-selected choices.</li>
+    <li class="fragment"><strong>Overconfidence</strong> - People overestimate their abilities.</li>
+    </ul>
+</li>
+<li class="fragment">Any other biases you know?</li>
+</ul>
+
+</pba-flex>
+
+Notes:
+
+- Confirmation bias especially pronounced in todays time where people get trapped in echo chambers fostered by algorithms that keep feeding you information that you want to hear.
+- Overconfidence: If asked, more than 50% of people think they drive above average.
+  BUT has also positive effects.
+  Sometimes overconfident people are better than others and statistically perform better in practice.
+- Anchoring Effect
+- Endowment Effect: This bias occurs when we overvalue something simply because we own it.
+- Hindsight Bias - This is the tendency to believe, after an outcome is already known, that you would have predicted or could have foreseen the outcome.
+  It is often referred to as the "I knew it all along" effect.
+- Availability Bias - People make decisions based on the information that is readily available to them, rather than the complete data set.
+  This bias can often lead to inaccurate conclusions.
+
+---
+
+## Behavioral Economics
+
+> Simply put, the stock market is a creation of man and therefore reflects human idiosyncrasy.<br/>-- Ralph Nelson Elliott --
+
+---
+
+<!-- .slide: data-background-color="#000" -->
+
+# Break (10 minutes)
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Classroom Discussions
+
+Notes:
+
+- Roughly 20 minutes
+
+---
+
+## Behavioral Biases
+
+- Which biases might be responsible for the following situations?
+- How can we mitigate the impact of those biases?
+
+---
+
+## Situation 1:
+
+> Warren Buffett announces that he increased his exposure to Apple by buying more stocks.
+> The price of AAPL goes up.
+
+Notes:
+
+- Herding effect
+- Cannot be in the hope of a price response by Buffett's trade because it already happened.
+- Self-fulfilling prophecy
+- Maybe still rational?
+
+---
+
+## Situation 2:
+
+> A stock investor bought a big position in Disney at around 100 USD per share.
+> Then, the scandal unfolds and the price plummets.
+> The investor keeps buying in at 80 USD, 50 USD and finally at 5 USD, 3 USD and 1 USD.
+> When a friend asks him to stop he keeps arguing to recover the losses by "buying the dip" and to "further reducing the average buying price".
+
+Notes:
+
+- Sunk Cost Fallacy
+- Learn to accept losses
+
+---
+
+## Situation 3:
+
+> Peter wants to buy a new smartphone and fancies the new iPhone.
+> Mentally, he is already looking forward to finally buy it, but a friend urges him to do some more research.
+> He agrees and is reading through articles that pop up after googling "Why you should buy the new iPhone".
+
+Notes:
+
+- Confirmation Bias
+- Mitigating by actively looking outside the echo-chamber that is just catering to your opinion.
+
+---
+
+## Situation 4:
+
+> A Swiss energy company could increase the number of new renewable electricity contracts from 3% to 80-90% by pre-selecting the green option when customers were renewing their energy contracts.
+
+Notes:
+
+- Default effect
+- Is it always good?
+  People might consume more energy because they feel better about their contract, companies can exploit this effect "default to accept all cookies".
+- https://www.bbc.com/news/science-environment-56361970
+- [Paper](https://www.nature.com/articles/s41562-021-01070-3.epdf?sharing_token=4HCcx-Aouj5gOGkD37i319RgN0jAjWel9jnR3ZoTv0MsXRMaQ2nk_xsjwawpA_drZ4p8HWONsx-i-1PN3ZRN0hxsKmhDtSpN5xn5qXXWcPCTjRQxPpY5yovJQehlrDn56a7Ff3-f5ESorQLlggQObIrxTOC9Y4nefV5OGXZRww9iZyuuvAOwV0kRLk12-rKINRixIpE45bF2ZtQQdPcWuA%3D%3D&tracking_referrer=www.bbc.com)
+
+---
+
+## Situation 5
+
+> Andrew had 50 Microsoft stocks. He decided to sell 40 of them at a price of 350 USD, still keeping 10. He used his earnings to pay some bills and does not plan to buy any stocks back. In the following days he caught himself looking at the charts hoping the price would go down to less than 350 USD.
+
+Notes:
+
+- Not rational.
+- Regret aversion?
+- Sunk cost fallacy?
+
+---
+
+## Titan Submersible Incident
+
+<ul>
+    <li class="fragment">On 18 June 2023, Titan, a submersible operated by American tourism company OceanGate, imploded during an expedition to the Titanic wreck.</li>
+</ul>
+<span style="display:flex; justify-content:center; align-items:center;">
+<img rounded style="width:600px" class="fragment" src="./img/2.1-ocean-gate.png" />
+</span>
+
+---
+
+## Titan Submersible Incident
+
+<ul>
+    <li class="fragment">On board were Stockton Rush (OceanGate CEO), Paul-Henri Nargeolet (deep sea explorer), Hamish Harding and Shahzada Dawood (billionaire businessmen), and Suleman Dawood (Shahzada's son).</li>
+    <li class="fragment">Communication was lost 1 hour and 45 minutes into the dive and the vessel failed to resurface later that day.</li>
+    <li class="fragment">Four days later, a debris field containing parts of Titan was discovered near the Titanic.</li>
+</ul>
+
+---
+
+## Prior Safety Concerns
+
+<ul>
+    <li class="fragment">Many industry experts had expressed safety concerns about Titan.</li>
+    <li class="fragment">OceanGate, including CEO Rush, had not sought certification for Titan.</li>
+    <li class="fragment">They published the following blog post to give reasoning:</li>
+</ul>
+<span style="display:flex; justify-content:center; align-items:center;">
+<img rounded style="width:600px" src="./img/2.1-ocean-gate-blog-post.png" class="fragment" />
+</span>
+
+Notes:
+
+- What biases could be happening here?
+- **Survivor bias**: is the logical error of concentrating on entities that passed a selection process while overlooking those that did not.
+  This can lead to incorrect conclusions because of incomplete data.
+- Of course most accidents happen because of operator error, because most vessels underwent certification!
+- What bias are we facing maybe? **Hindsight Bias**: is the common tendency for people to perceive past events as having been more predictable than they were.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+## Where do you see yourself or others suffer from behavioral biases?
+
+Notes:
+
+Open class discussion.
+
+---
+
+## Monopoly
+
+- We have seen: Monopolists' market power leads to inefficient outcomes.
+- Web 2.0 is full of firms that have a monopoly-like position in their respective domain:
+  - Google
+  - Uber
+  - AirBnb
+  - ...
+- How do these firms exert their market power, if not over price-setting?
+
+Notes:
+
+- transparency? (stealing tips!)
+- fees (uber, airbnb)
+- surge pricing (uber)
+- opaque auction mechanism (google in the case of online ads)
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Activities
+
+---
+
+# Academy Games
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+---
+
+## Activities Today & Tomorrow
+
+- You can earn points by applying the concepts presented in this course to similar situations when playing with/against your colleagues.
+- In session 2.1, 2.2 and 2.3, you can increase your budget (starting at 0) during several economic games.
+- We have a total budget of **$4200** for this.
+- The budget is split between all the games that we play and total points earned by all of you are dynamically adjusted to correspond to the budget.
+- In 2.3, there is a big finale: You can use your earnings to bid for amazing NFTs by a professional artist in an experimental auction setting.
+
+---
+
+## Sign-in & Games
+
+- Your behavior and payouts in the games are linked to your Polkadot address.
+- You need to sign a message to prove ownership to join the games.
+- If you do not clear your cache, you should be able to continue without signing in again.
+- Make sure not to forget your wallet credentials, because your final payout / NFT will be tied to that wallet.
+- Please do not use a VPN, this can cause connection issues.
+- Make sure you are on a stable internet connection.
+- If something doesn't work, it's good to try to refresh the browser.
+
+---
+
+## Disclaimer
+
+1. If a bug occurs and the reward points are messed up or something else goes wrong, we may intervene.
+1. We cannot help you recovering your account, if you lose access you lose your rewards.
+
+---
+
+## Tracking your payoff
+
+- Your balance is tracked in a wallet app.
+- The points are translated to USD after each game.
+- You can constantly check your balance by opening the wallet app link and sign in with your wallet.
+
+---
+
+# Everybody set up?
+
+---
+
+## Game 1: Ultimatum game
+
+- You are randomly matched with another student in the classroom.
+- The interaction is anonymous.
+- Player 1 gets an endowment of 100 points.
+- Player 1 can offer Player 2 between 0 and 100 points.
+- Player 2 sees the offer and can decide to accept or reject the offer.
+- If the offer is accepted, the endowment is split according to the offer.
+- If the offer is rejected, both get 0 points.
+- **Budget for the game $938.**
+- There is no right or wrong here.
+  It is your choice how to behave in this context!
+
+---
+
+## Game 1: Examples
+
+In the Ultimatum Game, Player 1 can offer between 0 and 100 points, and Player 2 can either accept or reject the offer. The outcomes are as follows:
+
+- If Player 2 accepts, the points are split accordingly.
+- If Player 2 rejects, both players get 0 points.
+
+| Example | Player 1's Offer | Player 2's Decision | Player 1's Points | Player 2's Points |
+| ------- | ---------------- | ------------------- | ----------------- | ----------------- |
+| 1       | 0                | Reject              | 0                 | 0                 |
+| 2       | 30               | Reject              | 0                 | 0                 |
+| 3       | 80               | Accept              | 20                | 80                |
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Game 1: Questions?
+
+## Don't ask about strategies!
+
+---
+
+## Let's start!
+
+Link will be distributed!
+
+---
+
+## Game 1: Discussion
+
+- What were your strategies here?
+- What do you think we would expect from rational players?
+- Why did people offer something?
+- What did we measure here?
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Game 1: Results!
+
+---
+
+## Game 2: Cournot Competition
+
+- Economic model
+- Firms compete by setting quantities
+- Identical product
+- Demand always meets supply
+- Named after French mathematician Augustin Cournot.
+
+---
+
+## Game 2: Overview
+
+- Cournot competition (Duopoly!)
+- 2 firms (you play 1 firm!)
+- Each of you individually set a quantity to produce.
+- All units are sold, but the price decreases in the quantity.
+- Repeated over 10 rounds **with the same participant**
+- Points accumulate and are added to your budget.
+- **Budget for the game: $938**
+
+---
+
+## Game 2: Rules
+
+<img rounded style="width:1200px" src="./img/2.1-cournot-1-instructions.png" />
+
+---
+
+## Game 2: Examples
+
+In this game, the unit price is calculated as follows:
+
+Unit price = 60 - sum of both goods produced
+
+Your profit is calculated as:
+Profit = Unit Price \* your amount produced
+
+| Example | Goods Produced (Each) | Unit Price Calculation | Your Profit Calculation |
+| ------- | --------------------- | ---------------------- | ----------------------- |
+| 1       | 15                    | 60 - (15 + 15) = 30    | 30 \* 15 = 450          |
+| 2       | 30                    | 60 - (30 + 30) = 0     | 0 \* 30 = 0             |
+| 3       | 0                     | 60 - (0 + 0) = 60      | 60 \* 0 = 0             |
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Game 2: Questions?
+
+## Don't ask about strategies!
+
+---
+
+## Let's start!
+
+Link will be distributed!
+
+---
+
+## Game 2: Discussions
+
+- What strategy did you employ?
+- Did your behavior change over the rounds?
+- What was the best choice for each firm?
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Game 2: Results!
+
+---
+
+## Conclusion
+
+We learned:
+
+- fundamental economic concepts that are important to navigate in private- and professional life.
+- the notion of rationality and what to expect from actors that behave this way.
+- that especially human individuals deviate from rationality and behave differently.
+- the importance of time on value.
+- to engage in economic situations with other human actors.
diff --git a/content/2-Economics/2-Game_Theory-slides.md b/content/2-Economics/2-Game_Theory-slides.md
new file mode 100644
index 00000000..ac32af1e
--- /dev/null
+++ b/content/2-Economics/2-Game_Theory-slides.md
@@ -0,0 +1,1094 @@
+---
+title: Game Theory Basics
+description: Game Theory Basics for Web3 engineers
+duration: 1 hour lesson + 2 hours activities
+---
+
+# Game Theory Basics
+
+---
+
+# Outline
+
+<ul>
+    <li class="fragment">Lesson
+        <ul>
+            <li class="fragment">What is Game Theory?</li>
+            <li class="fragment">What is a Game?</li>
+            <li class="fragment">Types of Games</li>
+            <li class="fragment">Common Games</li>
+            <li class="fragment">Nash Equilibrium</li>
+            <li class="fragment">Equilibrium Selection</li>
+        </ul>
+    </li>
+    <li class="fragment">Workshop & Activities
+        <ul>
+            <li class="fragment">Discussions & more games</li>
+        </ul>
+    </li>
+</ul>
+
+---
+
+## What is Game Theory?
+
+> Game theory studies strategic situations where the outcome for each participant or 'player' depends on the actions of all others. It formulates models to represent these scenarios and predicts the most likely or optimal outcomes.
+
+Notes:
+
+- Game theory is all about the power of incentives.
+- Helps you understand and design systems and guide behavior of participants.
+
+---
+
+## Game Theory in Web3
+
+In the context of blockchains, game theoretic reasoning is used for <span style="font-style: italic;">modelling</span> and <span style="font-style: italic;">understanding</span>.
+
+Notes:
+
+- The term is heavily over-used.
+- 9/10 times people using the term they simply mean there is some economic structure behind their protocols.
+- Rarely real game theoretic analysis is done.
+
+---
+
+## Modelling
+
+<ul>
+<li class="fragment"><strong>Tokenomics:</strong> Macroeconomic design of a token (inflation, utility, etc.).</li>
+<li class="fragment"><strong>Business Logic:</strong> Interaction of the token with different modules of a protocol.</li>
+<li class="fragment"><strong>Consensus:</strong> Providing sufficient incentives to guarantee that participating nodes agree on a distributed state of the network.</li>
+<li class="fragment"><strong>Collaboration:</strong> Nudging (aggregated) human behavior and their interaction with the protocol.</li>
+</ul>
+
+---
+
+## Understanding
+
+<ul>
+<li class="fragment"><strong>Economics:</strong> Interaction between different protocols and how finite resources are allocated among all of them.</li>
+<li class="fragment"><strong>Security:</strong> Testing economic security of protocols against various types of attacks.</li>
+</ul>
+
+---
+
+## History of Game Theory
+
+<ul>
+<li class="fragment">Early “game theoretic” considerations going back to ancient times.</li>
+<li class="fragment">“Game theoretic” research early 19th century, still relevant.</li>
+<li class="fragment">The systematic study of games with mathematically and logically sound frameworks started in the 20th century.</li>
+<li class="fragment">Modern game theory is used in economics, biology, sociology, political science, psychology, among others.</li>
+<li class="fragment">In economics, game theory is used to analyze many different strategic situations like auctions, industrial economics, and business administration.</li>
+</ul>
+
+Notes:
+
+- In Plato's texts, Socrates recalls the following considerations of a commentator of the Battle of Delium:
+  - An example is a soldier considering his options in battle: if his side is likely to win, his personal contribution might not be essential, but he risks injury or death.
+    If his side is likely to lose, his risk of injury or death increases, and his contribution becomes pointless.
+  - This reasoning might suggest the soldier is better off fleeing, regardless of the likely outcome of the battle.
+  - If all soldiers think this way, the battle is certain to be lost.
+  - The soldiers' anticipation of each other's reasoning can lead to a self-fulfilling prophecy: they might panic and retreat before the enemy even engages, resulting in a defeat.
+- Spanish conqueror Cortez, when landing in Mexico with a small force who had good reason to fear their capacity to repel attack from the far more numerous Aztecs, removed the risk that his troops might think their way into a retreat by burning the ships on which they had landed
+- Antoine Augustin Cournot, a french mathematician, already described a duopoly game with respective solution in 1844.
+  - We will see this later.
+- Examples:
+  - Biology: Animals fight for resources or are peaceful, why cooperation evolved
+  - Political science: Art of conflict, escalation and de-escalation between nations.
+
+---
+
+## Game theory is <span style="font-style: italic;">abstract</span>
+
+<ul>
+<li class="fragment">Game theoretic models aim to get at the essence of a given strategic problem.</li>
+<li class="fragment">This often requires many simplifying assumptions.</li>
+<li class="fragment">Pro: <em>Abstraction</em> makes the problem amenable to analysis and helps to identify the key incentives at work.</li>
+<li class="fragment">Con: A certain lack of realism.</li>
+<li class="fragment">In any case: Modeling a strategic situation always entails a tradeoff between tractability and realism.</li>
+</ul>
+
+Notes:
+
+- Need to explain what we mean by lack of realism:
+- Often people have more choices than we model.
+- Often people take other things into consideration when making choices than the model allows.
+- Often people know more/less than we assume.
+- How to resolve the tradeoff between tractability and realism is often subjective and depends on the taste of the modeler.
+
+---
+
+# What is a Game?
+
+---
+
+## Definition: (Economic) Game
+
+<ul>
+<li class="fragment">A game is a strategic interaction among several players, that defines <em>common knowledge</em> about the following properties:</li>
+<li class="fragment">all the possible <em>actions</em> of the players</li>
+<li class="fragment">all the possible <em>outcomes</em></li>
+<li class="fragment">how each combination of actions affects the outcome</li>
+<li class="fragment">how the players value the different outcomes</li>
+</ul>
+
+---
+
+## Definition: Common Knowledge
+
+<ul>
+<li class="fragment">An event $X$ is common knowledge if:</li>
+<ul>
+<li class="fragment">everyone knows $X$,</li>
+<li class="fragment">everyone knows that everyone knows $X$,</li>
+<li class="fragment">everyone knows that everyone knows that everyone knows $X$,</li>
+<li class="fragment">... and so on ad infinitum.</li>
+</ul>
+</ul>
+
+---
+
+### Examples: Common Knowledge
+
+<pba-cols>
+<pba-col>
+
+##### Auctions
+
+- Actions: Bids.
+- Outcome: Winner and Payment.
+
+</pba-col>
+<pba-col>
+
+##### Price-competition<br/>between firms
+
+- Actions: Price charged.
+- Outcome: Demand for each firm, profit of each firm.
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Crucial feature of a game: outcome not only depends on own actions but also on the actions of the other players.
+
+---
+
+## Types of games
+
+Game theory distinguishes between:
+
+<ul>
+<li class="fragment">static & dynamic games</li>
+<li class="fragment">complete & incomplete information games</li>
+</ul>
+
+---
+
+## Static and Dynamic Games
+
+|                  | Static Game                                                          | Dynamic Game                                                                                           |
+| ---------------- | -------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------ |
+| Definition       | All players take their actions at the same time                      | Players move sequentially and possibly multiple times, (at least partially) observing previous actions |
+| Simple Example   | Rock-Paper-Scissors                                                  | Tic-Tac-Toe                                                                                            |
+| Economic Example | Sealed-bid auction.                                                  | English Auction.                                                                                       |
+|                  | All bidders submit their bids simultaneously (in a sealed envelope). | Auctioneer publicly raises price if at least one bidder accepts the price.                             |
+| Representation   | Payoff Matrix                                                        | Decision Tree                                                                                          |
+
+Notes:
+
+- Also referred to as simultaneous or sequential games
+
+---
+
+## Completeness of Information in Games
+
+|                       | Game of Complete Information                          | Game of Incomplete Information                             |
+| --------------------- | ----------------------------------------------------- | ---------------------------------------------------------- |
+| Information available | All information relevant to decision-making is known. | Not all information relevant to decision-making is known.  |
+| Simple Example        | Chess                                                 | Poker                                                      |
+| Economic Example      | Sealed auction for seized Bitcoin.                    | Used-car market: the resale value of a used car is opaque. |
+
+---
+
+### Three firms want to hire an engineer...
+
+<pba-cols>
+<pba-col>
+
+- The engineer brings added value to each firm of 300,000 USD per year.
+- The payoff of the firm is known by everyone to be 300,000 USD minus the salary.
+- The payoff to the engineer is salary minus cost of working, which is known to everyone.
+- All firms make a salary offer at the same time.
+
+</pba-col>
+<pba-col>
+
+### Quiz Questions:
+
+1. Is this game static or dynamic?
+   What would need to change in the description of the game such that it would fall in the other category?
+1. Is this game of complete or incomplete information?
+   What would need to change in the description of the game such that it would fall in the other category?
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+1. The game is static.
+   For it to be dynamic, firms would need to make offers sequentially, _knowing what the firms before had offered_.
+
+2. The game is of complete information.
+   To make information incomplete, we would need to have that the value of hiring the engineer differs between firms and is unknown between firms.
+   Or that the cost of working for the engineer is not known to the firms.
+   The point is that we need to have uncertainty over payoffs.
+
+- This lesson focuses on static games of complete information.
+- When we look at auctions in lesson Price finding mechanisms, we will also consider games of incomplete information, both dynamic and static.
+
+---
+
+## Utility
+
+<ul>
+    <li class="fragment">Core concept of Game Theory.</li>
+    <li class="fragment">Can transform any outcome to some value that is comparable.
+        <ul>
+            <li class="fragment">For example: What is better? Scenario A: Going for a vacation to France and drink Wine, or Scenario B: going to Germany and drink Beer?</li>
+            <li class="fragment">Those dimensions are only comparable if we give both some value like U(A) = 5, U(B) = 3.</li>
+        </ul>
+    </li>
+    <li class="fragment">Essential assumption: Agents are utility maximizers.</li>
+    <li class="fragment">Monetary payouts can also be transformed to utility.
+        <ul>
+            <li class="fragment">Simplest assumption U(x) = x.</li>
+            <li class="fragment">But that is likely not true in reality.</li>
+        </ul>
+    </li>
+    <li class="fragment">Most things have <strong>diminishing rates of returns</strong>.</li>
+</ul>
+
+Notes:
+
+- Expected Utility is the average utility we get from comparing several outcomes and weigh them with the probability they occur.
+- In the following, we won't need that, because either we deal with money or other dimensions that are comparable.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Common Games
+
+---
+
+## Prisoners' Dilemma
+
+A fundamental problem:
+
+> Even though everyone knows there is a socially optimal course of actions, no one will take it because they are rational utility maximizers.
+
+It's a static game of complete information.
+
+Notes:
+
+One of the most famous games studied in game theory.
+
+- Static because both players take their action at the same time.
+- Complete because everybody is aware of all the payouts.
+
+---
+
+## Bonnie and Clyde
+
+Bonnie and Clyde are accused of robbing two banks:
+
+<ul>
+<li class="fragment">The evidence for the first robbery is overwhelming and will certainly lead to a conviction with two years of jail.</li>
+<li class="fragment">The evidence for the second robbery is not sufficient and they will be convicted only if at least one of them confesses to it.</li>
+</ul>
+
+---
+
+## Bonnie and Clyde
+
+In the interrogation they both are offered the following:
+
+<ul>
+<li class="fragment">If you both confess you both go to jail for 4 years.</li>
+<li class="fragment">If you do not confess but your partner does, you go to jail for 5 years: 1 extra year for obstruction of justice.</li>
+<li class="fragment">However, if you confess but your partner does not, we reduce your jail time to one year.</li>
+</ul>
+
+Notes:
+
+They are interrogated in different rooms, apart from each other.
+
+---
+
+## Bonnie and Clyde
+
+- **Cooperate** ($C$) with each other and not say anything
+- **Defect** ($D$) and confess their crime
+
+<div style="text-align: center;">
+    <img style="width: 700px; margin: auto; display: block;" src="./img/Bonnie-clyde-1.png" />
+</div>
+
+Notes:
+
+- They can either cooperate or defect
+- Second payoff is Clyde, first is Bonnie
+
+---
+
+## Nash-Equilibrium
+
+<ul>
+<li class="fragment">Fundamental concept in Game Theory</li>
+<li class="fragment">A NE is a set of strategies, one for each player, such that no player can unilaterally improve their outcome by changing their strategy, assuming that the other player's strategy remains the same.</li>
+</ul>
+
+---
+
+## Finding the NE
+
+<div style="text-align: center;">
+    <img style="width: 1200px; margin: auto; display: block;" src="./img/2.2-PD-NE-1.png" />
+</div>
+
+---
+
+## Finding the NE
+
+<div style="text-align: center;">
+    <img style="width: 1200px; margin: auto; display: block;" src="./img/2.2-PD-NE-2.png" />
+</div>
+
+---
+
+## Finding the NE
+
+<div style="text-align: center;">
+    <img style="width: 1200px; margin: auto; display: block;" src="./img/2.2-PD-NE-3.png" />
+</div>
+
+---
+
+## Finding the NE
+
+<div style="text-align: center;">
+    <img style="width: 1200px; margin: auto; display: block;" src="./img/2.2-PD-NE-4.png" />
+</div>
+
+---
+
+## Finding the NE
+
+<div style="text-align: center;">
+    <img style="width: 1200px; margin: auto; display: block;" src="./img/2.2-PD-NE-5.png" />
+</div>
+
+---
+
+## Finding the NE
+
+<div style="text-align: center;">
+    <img style="width: 1200px; margin: auto; display: block;" src="./img/2.2-PD-NE-6.png" />
+</div>
+
+---
+
+## Nash Equilibrium
+
+- Remember: a Nash Equilibrium describes a set of strategies such that no player can unilaterally increase their payout assuming the other player's strategy is fixed.
+- A Nash Equilibrium **does not mean** that payouts of players are maximized (either individually or collectively)!
+
+---
+
+## Dominant Strategy
+
+<img rounded style="width: 800px; margin-right: 250px;" src="./img/Bonnie-clyde-2.png" />
+
+Choosing D is a <span style="font-style: italic;">dominant strategy</span>: a strategy that is always optimal for a player, regardless of what the other players do.
+
+Notes:
+
+No matter what Clyde does, D is always the best choice.
+So, they end up both defecting, resulting in 4 years each.
+It would be in their best interest to cooperate and not to say anything.
+This would minimize the total jail time for the two.
+However, both Bonnie and Clyde are rational utility maximizers.
+So, they end up in a situation where they not only fare worse _individually_ (4 instead of 2) but also _jointly_ (the total jail time is 8 years rather than 4 years).
+
+---
+
+## Prisoners' Dilemma IRL
+
+<ul>
+<li class="fragment"><strong>Nuclear Arms Race:</strong> <a href="https://www.history.com/topics/cold-war/arms-race">NATO and Russia</a> prefer no arms race to an arms race. Yet, having some arms is preferable to having no arms, irrespective of whether the other one is armed.</li>
+<li class="fragment"><strong>OPEC:</strong> <a href="https://www.opec.org/opec_web/en/">Limiting oil supply</a> is in the best interest of all. However, given the high price that thus results, everyone has an incentive to increase individual oil supply to maximize profits.</li>
+</ul>
+
+Notes:
+
+OPEC: Organization of the Petroleum Exporting Countries.
+It is something like a cartel that agree on limiting the global oil production and keep the oil price artificially high.
+
+OPEC and Cartels generally seems to overcome the Prisoners' Dilemma...
+More on that later.
+
+---
+
+## Ultimatum Game
+
+<ul>
+    <li class="fragment">We played it before.</li>
+    <li class="fragment">Sequential game.</li>
+    <li class="fragment">The Nash Equilibrium can be reasoned by <strong>backwards induction.</strong></li>
+    <li class="fragment">The proposer has the following considerations:
+    <ul>
+        <li class="fragment">What would the recipient accept?</li>
+        <li class="fragment">Answer: every payoff (larger than 0).</li>
+        <li class="fragment">Therefore, I should offer, since I want to maximize my payout, something equal or slightly higher than 0.</li>
+    </ul>
+    </li>
+    <li class="fragment">That means, the proposer offering something small and the recipient always accepting is the only NE.</li>
+</ul>
+
+Notes:
+
+- We saw that empirically that is not the case.
+- Fairness concerns are too strong in that setting.
+
+---
+
+## Coordination Game
+
+<ul>
+<li class="fragment">The prediction of play in the Prisoner's Dilemma was easy: both will defect.
+  <ul>
+  <li class="fragment">This is the optimal thing to do no matter what the other player does.</li>
+  </ul>
+</li>
+<li class="fragment">In other games, predictions of play are not so clear.
+  <ul>
+  <li class="fragment">One instance is the coordination game.</li>
+  </ul>
+</li>
+</ul>
+
+---
+
+## Coordination Game
+
+> A coordination game is a type of static game in which a player will earn a higher payoff when they select the same course of action as another player.
+
+---
+
+## Coordination Game Example
+
+<pba-cols>
+<pba-col>
+
+- Choose $L$ or $R$.
+- The numbers represent the payoffs a player receives.
+- The players only obtain utility if they coordinate their actions.
+
+</pba-col>
+<pba-col>
+
+<img rounded style="width: 550px;" src="./img/Players.png" />
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Examples:
+
+- Driving on the right/left side of the road.
+- Money adoption.
+- Standard adoption.
+
+---
+
+## Coordination Game Example
+
+<pba-cols>
+<pba-col>
+
+- The coordination game has two outcomes $(L,L)$ and $(R,R)$ that stand out.
+- Clearly, if the other player chooses $L$ ($R$), then it is optimal for the other to do so also.
+- So, in the outcomes $(L,L)$ and $(R,R)$ the players choose mutually optimal actions.
+
+</pba-col>
+<pba-col>
+
+<img rounded style="width: 550px;" src="./img/Players.png" />
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+- That is, for both players it holds:
+  - Playing $L$ is a _best response_ to the other player playing $L$.
+  - Playing $R$ is a _best response_ to the other player playing $R$.
+
+---
+
+## Coordination Game Example
+
+<pba-cols>
+<pba-col>
+
+- Both $(L,L)$ and $(R,R)$ are instances of Nash equilibrium.
+- By their very nature, coordination games always have multiple equilibria.
+- The outcome $(D,D)$ in the Prisoner's dilemma is the unique Nash equilibrium.
+
+</pba-col>
+<pba-col>
+
+<img rounded style="width: 550px;" src="./img/Players.png" />
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Nash equilibrium: If other players follows the recommended strategy, then the best response for you is to do the same.
+As the same logic is true for other players, it's reasonable to assume that everybody will indeed follow the recommended strategy.
+
+However, a Nash equilibrium is a weaker notion than a dominant strategy, because if the other players don't follow the recommended strategy, it is not clear what your best response should be.
+
+---
+
+## Equilibrium selection
+
+<ul>
+    <li class="fragment">So, which outcome does the theory of Nash equilibrium predict in the coordination game?</li>
+      <ul>
+      <li class="fragment">None? Both?</li>
+      </ul>
+    <li class="fragment">Sometimes people switch between equilibria (if they are made to)...</li>
+</ul>
+<div class="fragment">
+    <img rounded style="width: 550px;" src="./img/2.2-sweden-1967.jpg" /><br/>
+    <p>Sweden, 1967.</p>
+</div>
+
+Notes:
+
+- The NE does not predict any outcome.
+- Sweden switched from left-side driving to right-side.
+
+---
+
+## Schelling Points
+
+<ul>
+<li class="fragment">Nash equilibrium <span style="font-style: italic;">does not</span> predict which strategies the players actually take.</li>
+<li class="fragment">This is especially pronounced in games with multiple equilibria (e.g., coordination games).</li>
+<li class="fragment">There are theories that offer insights into which strategies players actually take.</li>
+</ul>
+
+Notes:
+
+- In the 1950s American economist Thomas Schelling ran a couple of informal experiments in which he asked his students (quote on slide)
+
+---
+
+## Schelling Points
+
+> If you are to meet a stranger in New York City, but you cannot communicate with the person, then when and where will you choose to meet?
+
+<ul>
+<li class="fragment">Literally any point and time is a Nash equilibrium...</li>
+<ul>
+<li class="fragment">However, most people responded: noon at (the information booth at) Grand Central Terminal.</li>
+</ul>
+<li class="fragment">Basic idea: in case of multiple equilibria, social norms may help to choose one.</li>
+</ul>
+
+Notes:
+
+- Imagine you are held in prison.
+- You and your significant other is asked to guess a number.
+- If you both guess the same number, you are set free.
+- You have the following options: 0.231, 1, or 0.823
+- Guessing both the same number is a NE every time.
+- It's highly likely you will walk free.
+
+---
+
+# Summary (so far...)
+
+<ul>
+<li class="fragment">Typology of games: static/dynamic, complete/incomplete information.</li>
+<li class="fragment">Three canonical games: Prisoner's Dilemma, Ultimatum-, and Coordination Game.</li>
+<li class="fragment">The Prisoner's Dilemma has a unique Nash equilibrium, which is dominant, whereas the Coordination game has two Nash equilibria.</li>
+<li class="fragment">To select among multiple equilibria, the concept of a <span style="font-style: italic;">Schelling Point</span> is sometimes used.</li>
+</ul>
+
+---
+
+## Why are theories of equilibrium important?
+
+<ul>
+<li class="fragment">Nash Equilibria are used to predict the behavior of others in a closed system.</li>
+<li class="fragment">If you can identify a unique Nash Equilibrium or the Schelling point in a system, you have a strong prediction of user behavior.</li>
+<li class="fragment">So, you can begin to drive user behavior by designing incentives accordingly.</li>
+</ul>
+
+---
+
+## Public Goods
+
+<ul>
+<li class="fragment"><strong>Non-excludable</strong> No-one can be excluded from consumption</li>
+<li class="fragment"><strong>Non-rivalrous</strong> My consumption does not affect yours</li>
+<li class="fragment">e.g., fireworks, street-lighting.</li>
+</ul>
+
+Notes:
+
+- We will now talk about public goods and common goods, which are goods enjoyed by everyone.
+- This is, of course, a very important and very tricky class of goods in a collective.
+
+---
+
+## Common Goods
+
+<ul>
+<li class="fragment"><strong>Non-excludable</strong> No-one can be excluded from consumption</li>
+<li class="fragment"><strong>Rivalrous</strong> My consumption reduces your possibility to consume</li>
+<li class="fragment">i.e., a public park, an office coffee machine.</li>
+</ul>
+
+Notes:
+
+- Recall: Public good was _non_-rivalrous.
+
+Examples:
+
+- Public park: anyone can go; too many people spoil the experience or kills the grass.
+- Coffee machine in the office: anyone can use it; too many users may cause congestion or the amount of coffee may be limited.
+
+---
+
+## Public vs. Common Good
+
+<ul>
+<li class="fragment">Main difference is that in a <span style="font-style: italic;">common good</span> your consumption reduces the value of the good to others.</li>
+<li class="fragment">This is called a <span style="font-style: italic;">consumption externality</span> that you impose on others (and others impose on you.)</li>
+<li class="fragment"> The <span style="font-style: italic;">tragedy of the commons</span> is that, because you do not take this externality into account, consumption is higher than would be socially optimal. </li>
+</ul>
+
+---
+
+## Stylized Public Good Game:
+
+<ul>
+<li class="fragment">$N$ players have 10 US dollars each, say, $N=4$.</li>
+<li class="fragment">Each player can choose how much to place into a project.</li>
+<li class="fragment">Funds in the project are magically multiplied by a factor $\alpha$, say, $\alpha=2$.</li>
+<li class="fragment">Finally, the funds in the project are split equally among all players.</li>
+<ul>
+  <li class="fragment">What would be best for the individual?</li>
+  <li class="fragment">What would be best for the collective?</li>
+<ul>
+</ul>
+
+Notes:
+
+- As long as $\alpha>1$, it's best for the collective to contribute as much money as possible, because the money in the project increases magically, so we end up with more money that we started with.
+- However, the problem is that everyone benefits from the project funds regardless of their individual contribution (it is a common good). If a player decreases their initial contribution by one dollar, their individual payoff decreases by $\alpha/N$ dollars, so as long as $\alpha<N$, it is best for each individual to contribute zero.
+- As a result, we can expect that no one will contribute anything, and the money-multiplying powers of the project will be unused. This opportunity cost is a tragedy of the commons.
+- Finally, if $\alpha\geq N$ then it would be individually better to contribute everything, and we would not have a tragedy of the commons.
+
+---
+
+## Overfishing
+
+<ul>
+<li class="fragment">Fishing gives private benefit but might destroy the broader ecosystem, which has its own value for everyone (e.g., due to tourism).</li>
+<li class="fragment">Because individual fishermen do not pay for the damage they cause to the broader ecosystem, they will fish too much.</li>
+</ul>
+
+---
+
+## Air pollution
+
+<ul>
+<li class="fragment">Producing a good yields private profit but reduces air quality for everyone.</li>
+<li class="fragment">Because there is no price attached to air quality, the firms do not have to pay for its reduction and, hence, will produce too much.</li>
+</ul>
+
+---
+
+## But...
+
+<ul>
+<li class="fragment">There should be fishing/production/mining! After all, there are always benefits to these activities.</li>
+<li class="fragment">The tragedy of the commons is that the externality is not priced into these activities, driving them to inefficiently high levels.</li>
+</ul>
+
+Notes:
+
+To be precise, in the last example the so-called "tragedy" is not that producing a good leads to air pollution; after all, this may be unavoidable if we want to consume the good.
+The tragedy is that even if we agree on the level of production and air pollution that is economically ideal for the collective, we will end up with more pollution.
+
+---
+
+<!-- .slide: data-background-color="#000" -->
+
+# Break (10 minutes)
+
+Notes:
+
+- Next up class activities.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Open Source
+
+> Providing open-source software is like contributing to a public good and the community will therefore sooner or later collapse!
+
+Notes:
+
+- Why it might not fail:
+  - Other incentives:
+    - Intrinsic motivation
+    - Reputation concerns (your github history is part of your CV)
+    - Reciprocity
+    - Direct benefit: Some contributors also use the software and benefit from improvements.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Design a 2x2 game
+
+> Jack and Christine are rivals and keep taunting each other in front of others.
+> At one time, Jack challenges Christine to a game of chicken.
+> He proposes that they both get in their cars and drive towards each other on a road.
+> In the middle of the distance between each other, there is a small bridge with a single lane.
+> Whoever swerves away before the bridge <span style="font-style: italic;">chickened out</span>.
+> If both keep straight, there is no way to avoid a strong collision between the two cars.
+> All friends will be present to see the result.
+
+Design this game in a 2x2 matrix and assign payoffs to the different outcomes.
+
+Notes:
+
+- Need a white board!
+- Give Class about 5 minuets to discuss in small groups on this
+- Then have 10 minutes to ask the class you solve the 2x2 matrix and discuss (on next slide).
+
+---
+
+## Design a 2x2 game
+
+- What is/are the Nash Equilibrium/Equilibria here?
+- Which type of games does this remind you of?
+- How would you translate this game to real scenarios?
+
+Notes:
+
+- Game of chicken or Hawk-Dove Game
+- |              | Swerve | Straight     |
+  | ------------ | ------ | ------------ |
+  | **Swerve**   | 0, 0   | -1, +1       |
+  | **Straight** | +1, -1 | -1000, -1000 |
+- "Anti-Coordination Game" with the tension between competition and mutual benefit of compromise.
+- Real-world situations of conflict, where both would prefer not to fight but would actually like to intimidate, leading to a real conflict.
+- Two businesses would be better off not to engage in price war, but it would be good to be the only one to reduce the price to grab some market share.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Workshop: Games
+
+Notes:
+
+- roughly 70 minutes
+
+---
+
+## Game 1: Guessing Game
+
+- We divide the classroom into three groups and play a guessing game.
+- **The budget for this game is: $448**.
+- The game is simple: each player enters a number from 1 to 100.
+- The player who guessed closest to 2/3 of the average number wins.
+- You can only choose integer values.
+- If multiple people win, the payoff is split equally.
+- The game is repeated for ten rounds.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+## Game 1: Questions?
+
+### Don't ask about strategies!
+
+---
+
+## Game 1: Guessing Game
+
+Link will be distributed!
+
+---
+
+## Game 1: Discussion
+
+- What number did you choose / what was your strategy?
+  (which group were you in?)
+- Did your strategy change over time?
+
+Notes:
+
+- A number above 2/3\*100 does not make sense
+- If everybody believes that, choosing a number above 2/3\*2/3\*100 does not make sense
+- ... it goes to 0
+- But does 0 Win? No!
+- **Question: Who made these considerations?**
+- Empirical results:
+  - Financial Times asked their readers to submit their solution: Winning number was 13 (~1500 participants)
+  - Other news magazine: ~3700 subjects, winning number 16.99, ~2800 subjects, winning number 14.7
+  - There were spikes at 33 (response to randomness), 22 (response to that), and 0 (rationality)
+- Level-k-thinking: 1 or 2 steps most prevalent, seldom more than that.
+- **Question: What would be the NE for multiplication of 1 of the mean?**
+  - It becomes a coordination game where all players choose the same value.
+
+---
+
+## Game 1: Results!
+
+---
+
+## Game 2: Prisoner's Dilemma
+
+- You play a Prisoner's Dilemma (groups of 2) over 10 rounds.
+- You will be randomly matched to another student in the class.
+- **Budget for this game: $938**
+- You have the option to chat between rounds.
+- Important: Keep the chat civil and do not reveal any identifying information about yourself.
+- We will read the chat.
+
+---
+
+## Game 2: Payoffs
+
+|           |             | **_The other participant_** |                        |
+| --------- | ----------- | --------------------------- | ---------------------- |
+|           |             | _Cooperate_                 | _Defect_               |
+| **_You_** | _Cooperate_ | 200 points, 200 points      | 0 points, 300 points   |
+|           | _Defect_    | 300 points, 0 points        | 100 points, 100 points |
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+## Game 2: Questions?
+
+### Don't ask about strategies!
+
+---
+
+## Game 2: Let's go!
+
+Link will be distributed!
+
+---
+
+## Game 2: Results!
+
+---
+
+## Repeated Prisonner's Dilemma
+
+<ul>
+    <li class="fragment">Prof. Robert Axelrod held a tournament in the 1980s to find out which computer program ("strategy") would perform best against others.</li>
+    <li class="fragment">In the first tournament, 14 strategies were submitted by leading Game Theorists and others in the field.</li>
+    <li class="fragment">The game would be repeated 200 times.</li>
+    <li class="fragment">Each strategy would play against every other strategy and against itself.</li>
+</ul>
+
+Notes:
+
+- Based on https://ve42.co/Axelrod1980a and https://www.youtube.com/watch?v=mScpHTIi-kM
+
+---
+
+## Repeated Prisonner's Dilemma
+
+<ul>
+    Some famous strategies were:
+    <li class="fragment">Being sneaky: Cooperate but smuggle in some defections.</li>
+    <li class="fragment">Grim trigger: Always cooperate but retaliate and defect forever, if the other defect once.</li>
+    <li class="fragment">Tit-For-Tat: Start with cooperate and copy the opponent's strategy of the last round.</li>
+</ul>
+
+---
+
+## Repeated Prisonner's Dilemma
+
+<ul>
+    <li class="fragment">Tit-for-Tat was the best-performing strategy.</li>
+    <li class="fragment">Prof. Axelrod was able to deduce four main aspects of well-performing strategies:
+        <ul>
+            <li class="fragment">First: Be nice (do not defect first).</li>
+            <li class="fragment">Second: Be forgiving (retaliate but do not hold a grudge).</li>
+            <li class="fragment">Third: Be retaliatory (strike back).</li>
+            <li class="fragment">Fourth: Be clear (signal a simple strategy so the other knows who they are playing against).</li>
+        </ul>
+    </li>
+</ul>
+
+Notes:
+
+- This was rather big surprise, especially since dominant strategy is being nasty.
+- A lot of it is what we can observe in today's politics.
+
+---
+
+## Repeated Prisonner's Dilemma
+
+<ul>
+    <li class="fragment">There is no single best strategy.</li>
+    <li class="fragment">It always depends on who you are playing against.</li>
+    <li class="fragment">Simulations in a later study show that a cluster of tit-for-tat players within a defecting population can grow and overtake defecting types.</li>
+</ul>
+
+---
+
+## Game 3: Public Good Game
+
+- We will play a public good game as presented in the lesson.
+- **Budget for this game: $938**
+- Groups of 4 over 10 periods.
+- Points in the project is multiplied by factor $1.6$.
+- With one additional mechanism: After each round each player sees the contributions of the other players and can decide to deduct points from them (at own costs).
+
+---
+
+## Game 3: Instructions
+
+<img rounded style="width: 1000px;" src="./img/2.2-pgg-instructions.png" />
+
+---
+
+## Game 3: Contribution
+
+<img rounded style="width: 1000px;" src="./img/2.2-pgg-contribution.png" />
+
+---
+
+## Game 3: Punishment
+
+<img rounded style="width: 900px;" src="./img/2.2-pgg-punishment.png" />
+
+---
+
+## Game 3: Payout
+
+<img rounded style="width: 1000px;" src="./img/2.2-pgg-result.png" />
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+## Game 3: Questions?
+
+### Don't ask about strategies!
+
+---
+
+## Game 3: Let's go!
+
+Link will be distributed!
+
+---
+
+## Game 3: Discussion
+
+- What was your strategy?
+- Were your groups able to sustain cooperation?
+- Did you cooperate?
+- Did you punish?
+
+Notes:
+
+- Additional free rider problem: Punishment was fixed to 100% of the other's points.
+  That means, it was better to hope for other players to punish a player.
+- They cooperate maybe because they did not understand the game.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+## Game 3: Results!
+
+---
+
+## Game 3: Discussion
+
+<ul>
+    <li class="fragment">How could we characterize players to types?
+     <ul>
+            <li class="fragment">Freerider</li>
+            <li class="fragment">Cooperators</li>
+            <li class="fragment">Altruists</li>
+        </ul>
+    <li class="fragment">What do you think happens when playing this ...
+        <ul>
+            <li class="fragment">... for one round?</li>
+            <li class="fragment">... for many rounds?</li>
+            <li class="fragment">... when allowing for communication?</li>
+            <li class="fragment">... with different group sizes?</li>
+        </ul>
+    </li>
+</ul>
+
+Notes:
+
+What about empirical evidence?
+
+- One Round: Little contribution.
+- Many Rounds: Some little contribution but quickly to 0.
+- Some longer and stronger contribution but eventually going to 0 quickly
+- Different group sizes: Larger groups are more prone to freeriding, i.e., cooperation collapses more quickly.
+- **Question: How can we distinguish freerider from those that only freeride because they expect others to freeride?**
+  - Answer: Ask them to provide a "conditional cooperation table" - i.e., they should state how much they contribute given other's /(average) contributions.
+  - Real freeriders have 0 even if others contribute.
+
+---
+
+## Summary
+
+- the basics of game theoretic concepts.
+- different types of games.
+- how games can be modeled.
+- how to apply game theoretic thinking in our decision making in certain games.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
+
+---
+
+## Further Reading
+
+- [Comprehensive introduction to Game Theory](https://plato.stanford.edu/entries/game-theory/)
+- [Great video about the Prisonner's Dilemma](https://www.youtube.com/watch?v=mScpHTIi-kM)
diff --git a/content/2-Economics/3-Price_Finding_Mechanisms-slides.md b/content/2-Economics/3-Price_Finding_Mechanisms-slides.md
new file mode 100644
index 00000000..27b2f6f9
--- /dev/null
+++ b/content/2-Economics/3-Price_Finding_Mechanisms-slides.md
@@ -0,0 +1,894 @@
+---
+title: Price Finding Mechanisms
+description: Auction Basics for Web3 engineers
+duration: 1 hour
+---
+
+# Price Finding Mechanisms
+
+---
+
+## Introduction
+
+- A central topic of economics is _price finding_ in markets.
+- How does a buyer and a seller agree on the price of a good?
+
+---
+
+## Supply / demand for BIG markets
+
+<img rounded style="width: 800px; margin-right: 200px;" src="./img/2.1-supply-and-demand.png" />
+
+Notes:
+
+- As we saw yesterday, a market price must balance supply and demand.
+- Demand: number of items bought by consumers at a given price.
+- Supply: number of items produced and sold at a given price.
+
+---
+
+## Supply-demand for BIG markets
+
+- Supply-demand model works well for _big_ markets.
+- We have lots of buyers, sellers, lots of info.
+- Predictable _market price_, balancing supply and demand.
+- Only sensible price at which a buyer and seller can trade.
+
+Notes:
+
+- When a particular good has a large number of buyers and sellers, and we have a well established market with lots of real-life trading data, we can develop a supply-demand model.
+- It allows us to accurately predict the price at which the market will converge to for a good, which is the point at which supply and demand balance out.
+- It only makes sense to trade at market price: if lower, the seller can easily find another buyer willing to pay more, if higher, the buyer can easily find another seller willing to charge less.
+
+---
+
+## What about _difficult_ markets?
+
+<img rounded style="width: 900px;" src="./img/2.3-auction-platform.png" />
+
+Notes:
+
+Image source: https://funkypriceguide.com/collectible/512-gold-hopper-2018-sdcc-fundays/
+
+---
+
+## What about _difficult_ markets?
+
+Today we focus on markets with few buyers or sellers,
+few trades, or non-standardized goods.
+
+<pba-flex center>
+
+- Gov't sells radio frequencies to broadcasters.
+- A painting by a famous artist trades hands.
+- An oil well goes on sale with unknown amount of oil.
+
+</pba-flex>
+
+Notes:
+
+- The supply-demand model does not work in these examples
+- First example: there is a single buyer
+- Second example: very few buyers and sellers, trades are very infrequent, and goods are not standardized
+- Third example: not enough public data about the good.
+- In second and third cases, buyers may have wildly different personal valuations of the good.
+- A standardized good could be a liter of milk.
+  A less standardized good is a wedding ring, or a painting
+
+---
+
+## A simple model
+
+<pba-flex center>
+
+- Selena wants to sell one item of a good.
+- Two buyers, Alice and Bob.
+- Each buyer has a secret _valuation_ $v_A$ and $v_B$:<br/>
+  how much they are willing to pay for the item.
+
+</pba-flex>
+
+How does Selena _optimally_ sell the item?
+
+Notes:
+
+- We consider the limit case of one single seller and two buyers, to keep things simple.
+- Throughout the talk we assume that a buyer will purchase the item if the price is below or equal to their valuation.
+
+---
+
+## Let's assume...
+
+<pba-flex center>
+
+- All of Selena's income is profit.
+- Alice and Bob each have random valuations between 0 and 1.
+- The valuations are secret but their distribution is well-known.
+
+</pba-flex>
+
+Notes:
+
+- We saw the notion of an abstraction already in game theory class: we lose a bit in realism, but gain in structure which allows us to make precise statements, and develop a richer theory.
+  The intuition and conclusions still apply in real life.
+- In particular, we are assuming that each of the three characters has a certain amount of information about the valuations of the other players, namely the distribution they are sampled from, and they can use this info to strategize their actions.
+- Assuming that each valuation $v_i$ follows a uniform distribution between 0 and 1 simplifies Selena's life, because she knows that for any value $x\in [0,1]$, the probability that a bidder's valuation is below $x$ is exactly $x$, i.e., $P[v_i\leq x]=x$.
+- However, assuming a uniform distribution is just for pedagogical reasons: most results in auction theory can be extended to more general distributions.
+
+---
+
+## Price posting
+
+- Simplest solution: Selena posts a price $p$, sells item to first taker.
+- What is her _optimal price_ $p$?
+  One maximizing her _expected revenue_.
+- Expected revenue: price $\times$ prob. of making a sale.
+- For price $p$, prob. of making a sale is $(1-p^2)$.
+- Hence her expected revenue is $p \cdot ( 1-p^2)$.
+
+---
+
+## Price posting
+
+<pba-cols>
+<pba-col>
+
+- At the optimum point, expected revenue is $\approx 0.38$.
+- We will see that **an auction can do better**.
+
+</pba-col>
+
+<pba-col>
+
+<img rounded style="width: 600px; margin-right: 10px;" src="./img/2.3-price-posting.png" />
+
+</pba-col>
+</pba-cols>
+
+---
+
+## Auctions
+
+<img rounded style="width: 500px;" src="./img/2.3-auctioneer.gif" />
+
+---
+
+## Lesson summary
+
+<pba-flex center>
+
+- Auctions can be superior to posting a price.
+- We discuss four important auction formats.
+- How to make buyers reveal their secret valuations.
+- Bid shilling.
+- The revenue-equivalence theorem.
+- Guides on what auction format to use in practice.
+
+</pba-flex>
+
+Notes:
+
+- Auctions can provide more revenue to the seller, as we will see.
+- In a market with a posted price, buyers never need to reveal their valuation (i.e., how much they would actually be willing to pay for an item).
+  In auctions, the same is generally true, as they may bid values much lower than their valuations, but there is an auction format where they tend to bid their actual valuations (called truthful bidding).
+- There is a specific sense in which, in theory, all four auction formats provide the same revenue for Selena.
+- However, in practice, some formats may be better suited than others, and we will see some such examples.
+
+---
+
+## Auctions
+
+- Alice and Bob (bidders) submit bids based on own valuations.
+- Selena (auctioneer) selects winner to allocate the item to.
+- The winner's payment is a function of the bids.
+
+_An auction is a competitive game for buyers, where the seller makes the rules._
+
+Notes:
+
+- Bidders submit bids to auctioneer, which are a declaration of how much they are willing to pay for the item.
+  In an ideal world, a bid equals the bidder's valuation (this is called a truthful bid), but of course depending on the bidder's strategy they may choose to underbid or overbid.
+- In this lesson we will have some fun analyzing the bidders' best strategies as well as the auctioneer's best strategies.
+- Both the winner and the winner's payment will dependent on the bids and the auction rules.
+  The payment cannot be higher than the winner's bid, but it could be lower.
+- Auctions yield a higher revenue because they create competition among buyers.
+
+---
+
+## Auction formats
+
+<pba-flex center>
+
+1. There are two broad classes:
+   1. _Static Auctions:_ bidders submit their bids at the same time.
+   1. _Dynamic Auctions:_ bidders submit bids over time.
+
+- The difference is whether or not bidders can react to the bids of others and adjust their own.
+- Static auctions are also called _sealed-bid auctions_.
+
+</pba-flex>
+
+Notes:
+
+- In static auctions, bidders give their bids simultaneously and cannot change it later.
+- Static auctions are also called sealed-bid auctions, as many times in practice the bids are submitted in sealed envelopes to the auctioneer.
+
+---
+
+## Auction formats
+
+Four auction formats we discuss today:
+
+<pba-flex center>
+
+- Static auctions
+  - with a first-price payment rule
+  - with a second-price payment rule
+- Dynamic Auctions
+  - with ascending price (a.k.a. English auctions)
+  - with descending price (a.k.a. Dutch auction)
+
+</pba-flex>
+
+Notes:
+
+- Example, Selena auctions off a painting.
+  Suppose in a static auction, Alice bids 1000 and Bob bids 2000.
+  In a first-price format, Bob wins and pays 2000.
+  In a second-price format, Bob still wins but only pays 1000.
+- The English format became popular in England.
+  Selena continuously raises the price as long as at least 2 bidders accept it.
+  As soon as only one bidder remains, they win and pay the current price.
+- The Dutch format became popular in the Netherlands, particularly in the tulip market.
+  Selena starts at a high price and continuously lowers it as long as there are no takers.
+  As soon as a bidder accepts the price, they win and pay the current price.
+- We are gonna analyze each of these four formats, and take the opportunity to discuss relevant notions in auction theory along the way.
+- For me, the second-price auction is the least intuitive format.
+  But it turns out to be one of the nicest and easiest to analyze, so we will start there.
+
+---
+
+## Second-price auction
+
+- Why make the winner pay the second highest bid?
+- Least intuitive format, but strategically simplest for bidders.
+- Simply bid your valuation truthfully!
+- A bidder wants to maximize their _expected profit_:
+  - own valuation - price paid, in case they win
+  - zero, otherwise
+
+Notes:
+
+- Out of the four formats, we start our analysis with second-price static auctions, i.e., Alice and Bob give their bids in sealed envelopes to Selena, and she declares the winner to be the one with the highest bid, but the price to pay is only second highest bid.
+- To analyze the bidders' best strategy, we assume that each bidder wants to maximize their expected profit.
+  Again, this is a sensible but strong assumption, as they could have some other equally sensible objectives.
+  By the end of the lesson we will highlight how this assumption can be a bit unrealistic in practice.
+
+---
+
+## Second-price auction
+
+- **Truthful equilibrium**: a _dominant strategy_ to bid truthfully.
+- **Dominant strategy**: outcome is at least as good as the outcome of any other strategy, _no matter what the other bidder bids_.
+
+<img rounded style="width: 1300px;" src="./img/second-price-auction.svg" />
+
+Notes:
+
+- We can immediately say that you should never overbid (i.e., bid above your valuation), because in that case your profit can only be zero (if you lose) or sometimes negative (if you win).
+  So the key question is whether you should ever underbid.
+- In the case that Bob's bid is higher than your valuation, bidding truthfully or underbidding both lead to losing and having a revenue of zero.
+- But if Bob's bid is lower than your valuation, any bid between these two values leads to you winning and having the same profit (namely the difference of these values), hence there is no gain in underbidding.
+  However if you underbid too much, you run the risk of losing and having zero profit.
+- Hence in both cases we see that underbidding does not increase your profit, and can only decrease your chance of winning.
+  So it is better to bid exactly your valuation.
+- The proof can be easily generalized to any number of bidders (to obtain that in a second-price auction, it is a dominant strategy for each bidder to bid truthfully.
+
+TIP: use arrow chars in unicode for style: https://www.htmlsymbols.xyz/arrow-symbols
+
+---
+
+## Second-price auction
+
+**Expected revenue**
+
+- Selena's expected revenue is expected value of 2nd highest valuation.
+- For two independent variables uniformly sampled from $[0,1]$,
+  the expected value of the minimum is $1/3\approx 0.33$.
+- This is not quite as good as posting a price
+  (which provided expected revenue $0.38$).
+  Why not?
+
+Notes:
+
+- Let $F(x)$ be the cumulative density function (CDF) of the lowest of Alice and Bob's valuations, $\min\{v_A, v_B\}$, where $v_A$ and $v_B$ are independent variables sampled uniformly from $[0,1]$.
+- By definition, for any $x$ in $[0,1]$, $F(x)$ is the probability that the lower valuation is below $x$, or equivalently, $g(x):=1-F(x)$ is the probability that both valuations are above $x$; clearly $g(x)=(1-x)^2$, and hence $F(x)=1-(1-x)^2$.
+- From the CDF, we can compute the probability density function (PDF) by derivation: $f(x)=\frac{d}{dx}F(x)=2(1-x)$.
+- Finally, the expected value is computed from the PDF with the integral formula
+  $$\int_0^1 x\cdot f(x) dx = 2\int_0^1 (x-x^2)dx=2\cdot \left(\frac{1}{2}-\frac{1}{3}\right)=\frac{1}{3}.$$
+
+---
+
+## Reserve price
+
+- Because the format we considered is not optimal for the auctioneer!
+- The optimal auction involves a _reserve price_ $r>0$:
+  - If no bid is above $r$, nobody wins.
+  - If one bid is above $r$, the payment is $r$.
+  - If both bids are above $r$, the payment is the second-highest bid.
+
+---
+
+## Reserve price
+
+**Fact:** Under any reserve price $r$, it is still optimal to bid truthfully, and if Selena sets $r=0.5$, her expected revenue is $\approx 0.42$, so it is better than posted price (where expected revenue was $\approx 0.38$).
+
+---
+
+## Reserve price
+
+<img rounded style="width: 1400px;" src="./img/reserve-price.svg" />
+
+Notes:
+
+- The proof idea is that if $r=0.5$, half of the time one valuation is above it and the other is below it, and the reserve price increases the paying price.
+  On the other hand, if both valuations are below $r$ then there is no sale, which decreases Selena's revenue, but this case only happens one quarter of the time.
+  Finally, if both valuations are above $r$, the presence of a reserve price does no affect the result.
+  Overall, there is a positive net gain in Selena's expected revenue.
+  Below we present the formal proof.
+- The probability that both valuations are below $r$ is $r^2$, the prob. that $r$ is in between the valuations is $2r(1-r)$, and the prob.that both valuations are above $r$ is $(1-r)^2$.
+  You can check that these probabilities sum up to one.
+- In the first case Selena's revenue is zero, and in the second case it is $r$.
+  Hence the expected revenue for the first two cases is $2r^2(1-r)$.
+- To compute the expected revenue of the third case, we simply copy the integral formula for the expected value (from a couple of slides ago), but we restrict the integration limits to $[r, 1]$:
+  \begin{align}
+  \int_r^1 x\cdot f(x) dx &= 2\int_r^1 (x-x^2)dx\\
+  &=2\cdot \left[\frac{x^2}{2}-\frac{x^3} {3}\right]\_r^1 \\&=\frac{1}{3} - r^2 + \frac{2}{3}r^3.
+  \end{align}
+- Putting all terms together, we obtain that the expected revenue is
+  $$R(r)=0+2r^2(1-r)+\left(\frac{1}{3} - r^2 + \frac{2}{3}r^3\right)=\frac{1}{3}+r^2-\frac{4}{3}r^3.$$
+- To maximize the auctioneer's expected revenue function $R(r)$ above:
+  - We evaluate the function at all the local extrema (minima and maxima).
+  - Since the function is continuous and differentiable, the local extrema are found at the borders $r=0$ and $r=1$, and at the roots of the derivative $R'(r)=2r-4r^2=0$.
+    These roots are $r=0$ and $r=1/2$.
+  - By inspecting all these points, we find that the global maximum is found at $r=1/2$, with a value of $R(1/2)=5/12\approx 0.42$.
+- Literature: Myerson, Roger B. "Optimal auction design." Mathematics of Operations Research 6, No. 1 (1981): 58-73.
+
+---
+
+## English auction
+
+Recall the rules:
+
+<pba-flex center>
+
+- Selena continually raises the price.
+- At any price, you decide whether to stay or leave.
+- If you leave, you may not return.
+- If you are the last one in the auction you win<br/>
+  and pay the price at which the second-to-last<br/> bidder left.
+
+</pba-flex>
+
+Notes:
+
+- Next we move to English auctions, which have a very similar analysis.
+- Notice it has a flavor of a second-price auction: the price you pay is decided by another bidder, not you.
+- In a sense, these two auction formats are strategically equivalent!
+
+---
+
+## English auction
+
+- English auction is **strategically equivalent** to static second-price auction.
+- It is a dominant strategy to stay until the price reaches one's valuation.
+- The expected revenue for Selena is the also the same!
+- Consequently, these two formats are also **revenue equivalent**.
+
+Notes:
+
+- Why is staying until the price reaches your valuation a dominant strategy?
+  - If you leave you get zero utility.
+  - If you stay while the price is below your valuation, your eventual utility may be zero or positive, so there is no incentive to leave.
+  - If you stay while the price is above your valuation, your utility is zero or negative, so you should leave immediately.
+
+---
+
+## Shill bidding
+
+- Second-price and English auctions popular among theorists, not so popular among practitioners.
+- One reason is that they are prone to _shill-bidding_: bidder that acts on behalf of the auctioneer to drive up the price.
+
+Notes:
+
+- Both second-price auctions and English auctions have the truthful bidding property, which is very satisfactory for theorists.
+  However, as you can probably tell, they are not so popular in practice.
+- A shill bidder has no intention of winning, but just increasing the price that the winner must pay.
+  They do it to benefit the auctioneer.
+- Shill bidding is frowned upon, sometimes illegal, but it is usually hard or impossible to prove and to prevent.
+
+---
+
+## First-price auction
+
+<pba-flex center>
+
+- The winning bidder pays her bid.
+- Other rules same as in the second-price auction; i.e.,
+  - all bidders submit their bids simultaneously,
+  - the highest bid wins.
+
+</pba-flex>
+
+Notes:
+
+- New topic, time to wake up!
+- We move on to first-price auction, which as you recall, is a type of sealed auction.
+- Its analysis is more involved, and the resulting optimal bidding strategy is quite different from before.
+
+---
+
+## First-price auction
+
+Bidding in the first-price auction is **not** truthful.
+
+- Bidding truthfully can never be optimal:
+  if you win, you earn nothing.
+- Underbidding is strictly better, you win sometimes
+  and when you do you have a positive utility.
+
+---
+
+## First-price auction
+
+**Equilibrium strategy:** It is a _Nash equilibrium_ for each bidder to bid **half** their own valuation.
+
+_Nash equilibrium:_ A set of strategies, one per player, where no one has an incentive to change their strategy.
+
+Notes:
+
+- Recall Nash equilibrium we already covered.
+- A Nash equilibrium is a "recommended strategy per player", such that if you assume that the other bidder will follow their recommendation, then the best you can do is to follow yours.
+- As the same is true for the other players, it is indeed a reasonable assumption to think the other players will follow their recommendation.
+- However, if the other players picks an unexpected strategy, your recommended strategy may be suboptimal.
+  In this sense, a Nash equilibrium is a weaker concept than a dominant strategy, in which the strategy of the other players is irrelevant.
+
+---
+
+## First-price auction
+
+**Intuition:** suppose you are Alice
+
+- If you bid 0, winning prob. is zero.
+- If you bid your valuation, profit is zero.
+- Hence, there is a sweet spot between 0 and your valuation
+  where your expected profit is maximal.
+- It turns out this is bidding half your valuation,
+  at which point you and Bob each wins _half of the time_.
+
+Notes:
+
+- Unfortunately, the full proof is outside the scope of the presentation, but we provide it here in the lesson notes.
+- Assume you are Alice, with valuation $v_A$ and bid $b_A$.
+- Assuming that Bob's bid $b_B$ equals half his valuation $v_B$, that $v_B$ is sampled uniformly at random between 0 and 1, and that your bid $b_A$ is at most $1/2$, your winning probability is:
+  \begin{align}
+  Pr[winning] &= Pr[b_B\leq b_A] \\
+  &= Pr[v_B/2 \leq b_A] \\
+  &= Pr[v_B \leq 2b_A] \\
+  &= 2b_A.
+  \end{align}
+- Your profit in case of winning is $(v_A-b_A)$, hence your expected profit is $2b_A(v_A-b_A)$.
+- It can be checked that this expression is maximized for $b_A=v_A/2$.
+- In summary, if Bob bids half his valuation, it is optimal for Alice to bid has her valuation, and vice versa.
+  Together we have a Nash equilibrium.
+
+---
+
+## First-price auction
+
+**Expected revenue**
+
+- Reasonable to assume each bidder bids half their valuation.
+- Hence, Selena's revenue is $\frac{1}{2}\max\{v_A, v_B\}$.
+- The expected value of $\max\{v_A, v_B\}$ is $2/3$.
+- Hence, her expected revenue is $1/3$.
+
+The same as in second-price auction!
+
+Notes:
+
+- I find this result fascinating.
+  The optimal strategies are so different, but somehow the fact that you underbid is exactly compensated by the fact that you pay more when you win.
+- Is there a deeper connection going on here?
+  Or is it just a coincidence that the expected revenues are all the same so far?
+- Formal proof of the expected revenue: recall that the valuations $v_A$ and $v_B$ are assumed to be independent variables uniformly drawn from $[0,1]$.
+- The cumulative density function (CDF) of the higher valuation, $\max\{v_A, v_B\}$, is $F(x)=x^2$.
+  This is because $F(x)$ is lower than $x$ only if both valuations are below $x$, and these are two independent events each happening with probability $x$.
+- Then, the probability density function (PDF) is $f(x)=F'(x)=2x$.
+- And the formula for the expected value of $\max\{v_A, v_B\}$ is
+  $$R = \int\limits_0^1 x\cdot f(x)\mathrm d x = \int\limits_0^1 2x^2 \mathrm d v = \frac{2}{3}.$$
+
+---
+
+## Revenue Equivalence
+
+**Fact:** When valuations are secret and independent,
+there is no reserve price, and item goes to highest bidder,
+then _all auction mechanisms_ are _revenue equivalent_.
+
+Notes:
+
+- This is a theorem established by Myerson in 1981.
+- Notice all auction formats are **not** strategically equivalent (namely, you should bid truthfully in some formats but not in others), yet they are still _revenue equivalent_ for the auctioneer.
+- This result is very surprising to me, and one of the coolest results in game theory.
+
+---
+
+## Dutch auctions
+
+<pba-flex center>
+
+- Selena continually lowers the price.
+- As soon as a bidder accepts the price,<br/>
+  they are declared winners and auction is over.
+- Winner pays the price they accepted.
+
+</pba-flex>
+
+Notes:
+
+- We finally say a few words about the fourth and last auction format.
+- Notice it has a flavor of a first-price auction: you pick the price you pay.
+  So you definitely **do not** want to bid truthfully, but rather underbid.
+
+---
+
+## Dutch Auction
+
+Recall the rules:
+
+- The auctioneer continually lowers the price.
+- At any price, you can decide whether or not to accept the price.
+- If you are the first to accept the price, you win and pay the price you just accepted.
+
+---
+
+## Dutch Auction
+
+- It turns out that the Dutch auction is strategically equivalent and revenue equivalent to the static first-price auction.
+- The price that you accept in the Dutch auction corresponds to the price that you'd bid in a static first-price auction.
+- The tradeoffs that the bidders face are very similar: take the current price or wait a bit at the risk of another bidder accepting first.
+  It is an equilibrium to wait till the price is half your valuation.
+
+---
+
+## Recap
+
+<pba-cols>
+<pba-col>
+
+**Analyzed important auction formats:**
+
+- Static first-price auction.
+- Static second-price auction.
+- English auction.
+- Dutch auction.
+
+</pba-col>
+<pba-col>
+
+**Learned under standard assumptions:**
+
+- First-price and Dutch auctions are strategy equivalent.
+- Second-price and English auctions are strategy equivalent.
+- All four auctions are revenue equivalent.
+- Having a reserve price increases the expected revenue,
+  and it beats posting a price.
+
+</pba-col>
+</pba-cols>
+
+---
+
+<!-- .slide: data-background-color="#000" -->
+
+## Break (10 minutes)
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+## Discussion
+
+---
+
+## Independence of valuations
+
+In our analysis, it was important to assume that
+bidders' valuations are independent from one another.
+
+_Can you think of examples where this assumption isn't sensible?_
+
+---
+
+## Independence of valuations
+
+_Answer:_
+
+**Sensible:** - a piece of art, where the bidders are final clients.
+
+**Not sensible:** drilling rights to an oil well.
+Bidders will have similar estimates of amount of oil,
+hence valuations are highly correlated.
+
+---
+
+## Common value auctions
+
+Special scenario: there is a unique valuation of item,
+but each bidder only has a private estimate of it.
+
+In these cases, it is observed that sealed-bid auctions
+tend to give higher revenue than dynamic auctions.
+
+_Why do you think this is the case?_
+
+---
+
+## Common value auctions
+
+_The auction may be used as a means of gathering information from other participants to triangulate a price_
+
+_Answer_: In a dynamic auction, a bidder can use the bids of others as additional signals of the correct valuation.
+If bids so far seem high, my initial estimate must be low, and vice versa, so I can adjust my personal estimate.
+Hence estimates converge.
+
+In a static auction, there is no convergence of estimates, so it is more likely that some bidders keep unusually high estimates.
+As a result, there is a higher chance that the winner ends up paying more than the correct valuation.
+This is known as the _winner's curse_.
+
+---
+
+## Equivalence of revenues
+
+It is observed in practice that first-price auctions lead to higher revenue than second-price auctions.
+
+This _violates_ the equivalence of revenues, so an assumption in our analysis fails consistently.
+
+_What do you think it is?_
+
+---
+
+## Equivalence of revenues
+
+_Answer:_ **Risk aversion.** People prefer lower uncertainty games, even if this means lower expected profits.
+
+_Would you rather win a million dollars with a 50% chance, or 300 thousand with a 90% chance?_
+
+In Nash equilibrium analysis for first-price auctions, we claimed that if Bob bids half his valuation, then Alice should bid half hers, so each wins 50% of time.
+But we implicitly assumed that Alice is risk neutral.
+Yet she might prefer to bid more and win more often.
+
+Notes:
+
+- Of course, Bob may react the same way and also bid more in an attempt to bid more often.
+  As a result, they may still win about 50% of the time each, but both end up bidding too much due to their risk aversion.
+- In contrast, in our analysis for second-price auctions, the bidders' aversion to risk is not a factor.
+- Important: If you want to maximize the auctioneer's revenue and don't mind playing psychological games with the bidders, you should choose first price auctions over second-price auctions.
+
+---
+
+## Front Running
+
+Computer systems may have _front runners_: special nodes can see an incoming bid, react by creating their own bid, and make it look like their bid was created first.
+
+If you run an auction on a system with front runners, which of the four auctions would you use?
+Why?
+
+Notes:
+
+- Front runners are a known problem in eBay, trading platforms, and blockchain networks, etc.
+- Front runners have a special, faster setup that allows them to see an incoming message from a bidder, react to it by creating their own message, and make their message get registered first in the system.
+
+---
+
+## Front Running
+
+_Answer:_ Meet front runner _Fred_.
+
+In a Dutch auction, if Fred is a bidder he waits for first bidder to signal accepting the price, and Fred makes the signal first.
+He's guaranteed to win with least possible price.
+
+In second-price auction, if Fred is auctioneer he can shill bid successfully: when a highest bid arrives, he creates bid slightly under it and makes it appear as if it was created first.
+
+---
+
+## Front Running
+
+_Answer:_ Meet front runner _Fred_.
+
+In a first-price auction, if Fred is bidder and if he can "open the seals" he can win by slightly outbidding highest bid.
+(Poor data privacy, a common issue in computer systems)
+
+Hence, it might be best to run an English auction.
+
+---
+
+## Sniping
+
+In a dynamic auction with a fixed bidding time window, _sniping_ is placing a highest bid as late as possible, so other bidders can't react and overbid you.
+The practice leads to low revenue.
+Particularly bad when done by a front runner (microseconds).
+
+How to protect an auction from snipers?
+
+Notes:
+
+- eBay uses such types of auctions, and is infamous for having snipers.
+
+---
+
+## Sniping
+
+_Answer:_ **candle auctions.**<br/>
+Dynamic first-price auction with _random ending time._
+
+<img rounded style="width: 600px;" src="./img/2.3-candle-auction-photo.jpg" />
+
+---
+
+## Sniping
+
+_Answer:_ **candle auctions.**<br/>
+Dynamic first-price auction with _random ending time._
+
+- Similar to first-price auction
+- except that ending time is unpredictable.
+- At ending time, current highest bidder wins, pays own bid.
+- Sniping protection: the longer you wait to bid, the higher the chances the auction ends.
+
+Notes:
+
+- Fun fact: candle auctions were popular in England in the 17th and 18th centuries.
+- They would use a candle (hence the name).
+  When the flame extinguishes, the auction is over.
+- Fun fact: Polkadot implemented a candle auction for assigning block space to applications.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Workshop: Auction Games
+
+---
+
+## NFT Auction
+
+- You have the chance to bid on one professionally created NFTs by an experienced artist.
+- There are 46 unique NFTs.
+- Use your budget that you accumulated throughout Academy Games.
+- Everything that you will not use for bidding (or if your bid was lower than your budget), you will receive at the end of the Academy.
+- **100% of the revenue of the auctions goes to the artist.**
+- You are randomly assigned to one of three auction formats.
+
+---
+
+# The Artist & NFTs!
+
+---
+
+## Tsung-yu Lu
+
+**Photography & generative artist, Taiwan**
+
+Tsung-yu Lu is a photography and generative artist from Taiwan. He has been creating photography since 2013. He is interested in thinking about the essence of photography and exploring the possibilities of images through special techniques.
+
+As a professional software engineer, he has immersed himself in generative art creation since 2022, to create subjects that are difficult to represent through photography.
+
+The themes of his creations mostly focus on exploring the relationship between rationality and sensibility.
+
+[https://linktr.ee/luyotw](https://linktr.ee/luyotw)
+
+---
+
+## Collection: Freak
+
+> I know there lives a freak inside your body, but if your behavior looks normal on the outside, then you’ll be fine. Just pretend and show everyone that we can connect to the world very well.
+
+> This project revolves around a misshapen gear as its protagonist. No matter how peculiar its deformities may be, it manages to seamlessly synchronize with the outside world through its "normal" layer of gears.
+
+> As we encounter more people, we gradually realize that everyone harbors some behaviors or traits that may appear peculiar to others. Yet, as long as we know how to interact with the world in a "normal" manner, what does it matter? As long as we respect others, we can believe that they will reciprocate that respect.
+
+---
+
+<img rounded style="width:600px" src="./img/2.3-nft.jpeg" />
+
+---
+
+## The NFTs
+
+- The digital assets are generated with an algorithm.
+- We capture and unify three of your freaky souls and use them as input for one asset.
+- It will remain a mystery with which colleagues you are unified and in which asset you'll be captured.
+
+---
+
+### Format 1: Activity Rule Auction
+
+- The initial bidding phase lasts 30 seconds.
+- Every valid bid resets the timer.
+- You need to bid at least 30 cents more than the previous highest bid.
+- Whoever has the highest bid at the end, wins.
+  Winners pay their bids.
+
+---
+
+### Format 2: Candle Auction
+
+- Auction Format from the 16th Century.
+- The auction lasts for exactly 4 minutes.
+- A “candle mechanism” randomly determines, after the auction, when the auction ended
+- Grace-period of 1 minute.
+- Candle Phase of 3 minutes.
+- Whoever had the highest bid when the auction actually ended, wins.
+
+---
+
+### Format 3: Hard Close Auction
+
+- Similar to eBay auctions.
+- Auction lasts for 4 minutes.
+- Whoever has the highest bid at the end of the auction, wins.
+- Winners pay their bids.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+## Auction 2: Questions?
+
+---
+
+## Auction 2: NFT Auction
+
+Link will be distributed!
+
+---
+
+## Auction 2: Discussion
+
+---
+
+## Auction 2: Results!
+
+---
+
+## Further Reading
+
+Polkadot & Kusama Auctions<br/>Data & Background information:
+
+<pba-flex center>
+
+- [Kusama Auctions 1-5](https://polkadot.network/blog/making-history-an-overview-of-the-first-five-parachain-slot-auctions-on-kusama/)
+- [Kusama Auctions 6-10](https://polkadot.network/blog/kusama-batch-2-auctions-report/)
+- [Polkadot Auctions 1-5](https://polkadot.network/blog/making-history-again-polkadot-auctions-1-5/)
+
+</pba-flex>
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions?
+
+---
+
+# Assignment
+
+- We will play our own version of the Axelrod Tournament
+- Every student will hand in a strategy for a 2x3 Game (2 players, 3 strategies).
+- More details in the announcement!
+
+---
+
+# Thank you!
diff --git a/content/2-Economics/4-Economics_of_Polkadot-slides.md b/content/2-Economics/4-Economics_of_Polkadot-slides.md
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@@ -0,0 +1,554 @@
+---
+title: The Economics of Polkadot
+description: Tokenomics of Relay Chains and more
+duration: 2 hour
+---
+
+# The Economics of Polkadot
+
+Note:
+
+- First: Lecture
+- Then we will see the tournament results and discuss
+
+---
+
+## The Economics of Polkadot
+
+<ul>
+<li class="fragment">Which economic pieces build the the Polkadot Network?</li>
+<li class="fragment">What are their mechanisms and incentives?</li>
+<li class="fragment">How are those pieces interrelated?</li>
+</ul>
+
+<p class="fragment">Remark: There are currently many changes planned</p>
+
+Note:
+
+- It was a bit challenging to find a good structure for this.
+- Because most of the "old" system is still fully in place and important, but a lot is about to change very soon.
+- I focus on the system as it is now (also conceptually things do not change) and reference to upcoming changes.
+
+---
+
+<img rounded style="width: 1200px; margin-right: 50px;" src="./img/2.4-polkadot_pieces.svg" />
+
+---
+
+# Token Economics
+
+---
+
+## DOT Token
+
+<!-- FIXME https://github.com/Polkadot-Blockchain-Academy/pba-content/issues/684 to render math for offline use -->
+
+<ul>
+<li class="fragment">Native token of the Polkadot network.</li>
+<li class="fragment">1 DOT = \(1\mathrm{e}{10}\) Plancks</li>
+<li class="fragment">
+    Planck = smallest unit of account.
+    <ul>
+        <li class="fragment">Reference to Planck Length = the smallest possible distance in Physics.</li>
+    </ul>
+</li>
+<li class="fragment">
+    <strong>Utility Token</strong> with several use-cases:
+    <ul>
+        <li class="fragment">Governance (decentralization)</li>
+        <li class="fragment">Bonding in slot auctions (utility)</li>
+        <li class="fragment">Staking (security)</li>
+        <li class="fragment">Message passing (e.g., transfers)</li>
+    </ul>
+</li>
+</ul>
+
+---
+
+## Inflation Model
+
+<ul>
+<li class="fragment">Expansion in token supply.</li>
+<li class="fragment">Token minted from thin air.
+  <ul>
+  <li class="fragment">Used to pay staking rewards for validators and nominators.</li>
+  <li class="fragment">(Indirectly) fund Treasury.</li>
+  </ul>
+</li>
+<li class="fragment">Central economic variables of the model are:</li>
+<li class="fragment"><strong>Exogenous</strong>:
+  <ul>
+  <li class="fragment">Staking rate (Total amount of staked DOT / Total amount of DOT).</li>
+  </ul>
+</li>
+<li class="fragment"><strong>Endogenous</strong>:
+  <ul>
+  <li class="fragment">Optimal staking rate (a sufficient backing for validators to provide reasonable security).</li>
+  </ul>
+</li>
+<li class="fragment">Total inflation rate (10%).</li>
+</ul>
+
+---
+
+## Inflation Model
+
+<ul>
+<li class="fragment">Different <strong>states</strong> of DOT:
+  <ul>
+  <li class="fragment"><strong>Liquid</strong>: Used for messaging and liquidity on markets.</li>
+  <li class="fragment"><strong>Bonded (Staking)</strong>: Economic mass that guarantees the security of the network.</li>
+  <li class="fragment"><strong>Bonded (Parachains)</strong>: The demand for DOT tokens by parachains.</li>
+  </ul>
+</li>
+<li class="fragment">The goal is to obtain (some) <strong>sensible ratio</strong> between those three token states.</li>
+</ul>
+
+---
+
+## Inflation Model
+
+<div style="display: flex; justify-content: center; align-items: center;">
+    <div style="flex: 1; text-align: center;">
+        <img rounded style="width: 650px; margin-right: 50px;" src="./img/2.4-current_inflation_model_polkadot.png" />
+    </div>
+    <div style="flex: 1;">
+        <ul>
+            <li class="fragment"><strong>Green</strong>: Yearly interest rate in staking, <strong>Blue</strong>: Inflation stakers</li>
+            <li class="fragment"><strong>Central variable</strong>: Ideal staking rate (currently ~59.3%).</li>
+            <li class="fragment">Highest staking rewards at the ideal staking rate.</li>
+            <li class="fragment">Incentives to (increase) decrease the staking rate it is (below) above the optimal.</li>
+            <li class="fragment">Staking inefficiencies -> Treasury.</li>
+            <li class="fragment">Ideal staking rate scales with number of active parachains (0.5% less with each parachain).</li>
+        </ul>
+    </div>
+</div>
+
+Notes:
+
+- current staking rate 56.7%
+- Assume we have 100 token in the whole network. The yearly inflation rate is 10%. Now assume that we have an ideal staking rate of 50% and we actually have 50% of the token staked the whole year (i.e., all inflation goes to stakers). That means, of the 100 token, we have 50 in the staking system. Let’s also make a simplifying assumption that staking rewards are only distributed once after one year.
+
+- At the end of the year, 10 token (100\*0.1) are minted from inflation and distributed to those 50 token (equally). Only those get the rewards, because only they are part of the staking system.
+
+- Let’s say I had 1 token in the staking system at the beginning of the year, then I will have 1.2 token after (because I get 1/50th of the 10 token). As you can see, my staking APY (yield) is 20%.
+
+---
+
+# Adjusted Ideal Rate
+
+<ul>
+<li class="fragment">Referendum 166 proposed to change the calculation of the ideal rate.</li>
+<li class="fragment">Got accepted by community with overwhelming approval and support.</li>
+<li class="fragment">Without it, the ideal rate would be 51.5% now!</li>
+<li class="fragment">That would lead to large reduction of staking rewards to stakers.</li>
+</ul>
+
+Note:
+
+- before: auction_proportion <- min(auctioned_slots, 60) / 200 , ideal_stake <- 75 / 100 - auction_proportion
+- now: auction_proportion <- min(auctioned_slots, 60) / 300 , ideal_stake <- 75 / 100 - auction_proportion
+
+---
+
+## Inflation
+
+<ul>
+    <li class="fragment">In the fiat-world, inflation has a negative connotation.</li>
+    <li class="fragment">This is a general discussion in economics.</li>
+    <li class="fragment">My take on this:</li>
+    <ul>
+        <li class="fragment">Predictable (maximum) inflation is good.</li>
+        <li class="fragment">It incentivizes to work with the tokens (i.e., bond for good parachains, use for message passing).</li>
+        <li class="fragment">Deflation can cause a halt of economic activity, because people start hoarding tokens.</li>
+    </ul>
+    <li class="fragment">Polkadot is paying validators to do their job and be resilient from inflation!</li>
+
+</ul>
+
+---
+
+## Staking: Concept
+
+<ul>
+    <li class="fragment"><strong>Nominated Proof-Of-Stake (NPoS)</strong>.</li>
+    <li class="fragment">Economic incentives of <strong>validators</strong> and <strong>nominators</strong> are aligned with those of the network.</li>
+    <ul>
+        <li class="fragment">Good behavior is rewarded with staking rewards.</li>
+        <li class="fragment">Malicious / Neglecting behavior is punished (slashed).</li>
+    </ul>
+    <li class="fragment">Currently, minimum total stake is ~2.4M DOTs.</li>
+    <li class="fragment">The total stake in the system directly translates to the <strong>economic security</strong> that it provides.</li>
+    <li class="fragment">Total stake is pooled from validators (self-stake) and their nominators (nominated stake)</li>
+    <ul>
+        <li class="fragment">High degree of inclusion</li>
+        <li class="fragment">High security</li>
+        <li class="fragment">The goal is to get as much <strong>skin-in-the-game</strong> as possible.</li>
+    </ul>
+</ul>
+
+---
+
+## Validators
+
+<ul>
+    <li class="fragment">What makes Validators resilient:</li>
+    <ul>
+        <li class="fragment">Self-stake</li>
+        <li class="fragment">Reputation (identity)</li>
+        <li class="fragment">High future rewards (self-stake + commission)</li>
+    </ul>
+</ul>
+
+---
+
+## Nominators
+
+<ul>
+    <li class="fragment">Bond tokens for up to 16 validators that they deem trustworthy.</li>
+    <li class="fragment">They have an incentive to find the best ones that match their preferences.</li>
+    <li class="fragment">They are tasked to collectively curate the set of active validators.</li>
+</ul>
+
+---
+
+## Rewards
+
+<pba-cols>
+<pba-col>
+<pba-flex center>
+
+<img rounded style="width: 700px;" src="./img/2.4-rewards_flow.png" />
+
+</pba-flex>
+</pba-col>
+<pba-col>
+
+<ul>
+    <li class="fragment"><em>What are staking rewards for?</em></li>
+    <li class="fragment"><strong>Validators</strong>: Hardware, networking, and maintenance costs, <strong>resilience</strong>.</li>
+    <li class="fragment"><strong>Nominators</strong>: Curation of the active set of validators, sort out the good from the bad ones (Invisible Hand).</li>
+</ul>
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+- Talk about economic security of validators (self-stake + NPV of future rewards (moderated by commission)).
+
+---
+
+## Validator Selection
+
+<ul>
+    <li class="fragment">The job of nominators is to find and select suitable validators.</li>
+    <li class="fragment">Nominators face several trade-offs when selecting validators:</li>
+    <ul>
+        <li class="fragment">Security, Performance, Decentralization</li>
+        <li class="fragment">Ideally those variables in their historic time-series.</li>
+    </ul>
+    <li class="fragment">Economic Background:</li>
+    <ul>
+        <li class="fragment">Self-stake as main indicator of skin-in-the-game.</li>
+        <li class="fragment">Higher commission, ceteris paribus, leaves a validator with more incentives to behave.</li>
+    </ul>
+    <li class="fragment">Various sources of trust</li>
+    <li class="fragment">Efficient validator recommendation is one of my research topics.</li>
+</ul>
+
+---
+
+# Parachains / Cores
+
+---
+
+## What are Parachains?
+
+<ul>
+    <li class="fragment">Parachains (or cores) are the layer-1 part of the protocol.</li>
+    <li class="fragment">Blockchains of their own that run in parallel.</li>
+    <ul>
+        <li class="fragment">Highly domain specific and have high degree of flexibility in their architecture.</li>
+        <li class="fragment">Share same messaging standard to be interoperable and exchange messages through the Relay Chain.</li>
+    </ul>
+    <li class="fragment">Polkadot: 50 Parachains, Kusama: 45 Parachains.</li>
+    <li class="fragment">Their state transition function (STF) is registered on the Relay Chain.</li>
+    <ul>
+        <li class="fragment">Validators can validate state transitions without knowing all the data on the Parachain.</li>
+        <li class="fragment">Collators keep the parachain alive (but are not needed for security).</li>
+    </ul>
+    <li class="fragment">Offer their utility to the network.</li>
+</ul>
+
+---
+
+## Parachain Slots
+
+<ul>
+    <li class="fragment">The access to the network is abstracted into the notion of “slots”.</li>
+    <ul>
+        <li class="fragment">Leases for ~2 years on Polkadot (~1 year on Kusama).</li>
+        <li class="fragment">Only limited amount of slots available (networking).</li>
+        <li class="fragment">The slots are allocated through a candle auction.</li>
+    </ul>
+    <li class="fragment">Bonded tokens held (trustlessly) in custody on the Relay Chain.</li>
+    <li class="fragment">The tokens will be refunded after the slot expires.</li>
+</ul>
+
+<p class="fragment">This will change in favor of agile coretime markets likely in August 2024.</p>
+
+---
+
+## Economic Intuition
+
+<ul>
+    <li class="fragment">Tokens cannot be used for anything (staking, transacting, liquidity, governance).</li>
+    <ul>
+        <li class="fragment">That means, tokens locked cause opportunity costs.</li>
+        <li class="fragment">An approximation is the trust-free rate of return from staking.</li>
+    </ul>
+    <li class="fragment">Parachains need to compete with those costs and generate benefits that exceed those opportunity costs.</li>
+    <ul>
+        <li class="fragment">Sufficient crowdloan rewards.</li>
+        <li class="fragment">Sufficient economic activity on-chain that justifies renewal.</li>
+    </ul>
+    <li class="fragment">Slot mechanism creates constant demand for DOT token.</li>
+    <li class="fragment">It is costly to be and remain a parachain.</li>
+    <ul>
+        <li class="fragment">Natural selection mechanism to select useful parachains.</li>
+        <li class="fragment">Continuous pressure to gather funds for extending slots.</li>
+    </ul>
+</ul>
+
+---
+
+## What do Parachains get?
+
+<ul>
+    <li class="fragment"><strong>Parachains pay for security</strong>.</li>
+    <ul>
+        <li class="fragment">Every parachain is as secure as the Relay Chain.</li>
+        <li class="fragment">Polkadot is a security alliance with network effects.</li>
+        <li class="fragment">Not only scaling number of transactions, but it also scaling of security.</li>
+    </ul>
+    <li class="fragment">Security is a pie of limited size, because financial resources are limited.</li>
+    <li class="fragment">Every chain that secures itself need cut a piece of the cake, which leaves less to others (zero-sum).</li>
+    <li class="fragment">Shared security protocols allow to keep the cake whole and entail it to all participants.</li>
+    <li class="fragment">Shared security is a scaling device, because the amount of stake you need to pay stakers to secure 100 shards is less than you need to pay stakers to secure 100 individual chains.</li>
+</ul>
+
+---
+
+## Outlook: Polkadot
+
+<ul>
+    <li class="fragment">Based on Gav’s Keynote at Polkadot Decoded 2023 and RFC-1.</li>
+    <li class="fragment">Blockspace: A current narrative in the Polkadot system.</li>
+    <li class="fragment">Polkadot is moving away from regarding Parachains as a distinct entity but rather regard the whole network as global distributed computer.</li>
+    <li class="fragment">It's spaces and apps rather than chains.</li>
+    <li class="fragment">This computer has computation cores that can be allocated flexible to applications that need it.</li>
+    <li class="fragment">Cores can be much easier be acquired, shared, and resold.</li>
+</ul>
+
+---
+
+## Core Attributes of Blockspace
+
+<ul>
+    <li class="fragment"><strong>Security</strong>: The scarcest resource in blockchain, crucial in preventing consensus faults or 51% attacks that could compromise transactions.</li>
+    <li class="fragment"><strong>Availability</strong>: Ensuring blockspace is available without long waiting times or uncertain costs for a smooth, seamless interaction within the decentralized ecosystem.</li>
+    <li class="fragment"><strong>Flexibility</strong>: The ability of blockspace to be fine-tuned by the consumer for specific use-cases.</li>
+</ul>
+
+---
+
+## Blockspace Ecosystem
+
+<ul>
+    <li class="fragment">A networked collection of individual blockspace producers (blockchains) offering secured, fit-for-purpose, efficiently-allocated, and cost-effective blockspace.</li>
+    <li class="fragment">A valuable aspect of a blockspace ecosystem is its connective tissue of shared security and composability.</li>
+    <li class="fragment">Dapp developers or blockspace providers can focus on their unique features, reusing existing capabilities within the ecosystem.</li>
+    <li class="fragment">For example, a supply chain traceability application could use different types of blockspace for identity verification, asset tokenization, and source traceability.</li>
+</ul>
+
+---
+
+## Agile Coretime
+
+<ul>
+    <li class="fragment">The final design is not yet determined.</li>
+    <ul>
+        <li class="fragment">Cores are sold for 4 weeks as NFT by a broker.</li>
+        <li class="fragment">Unrented cores go to the instantaneous market.</li>
+        <li class="fragment">Price de-/increases relative to demand.</li>
+        <ul>
+            <li class="fragment">Dutch auction.</li>
+        </ul>
+        <li class="fragment">Current tenants have a priority buy right for their core(s).</li>
+        <ul>
+            <li class="fragment">One goal is to offer price predictability for existing teams.</li>
+            <li class="fragment">Challenging Task.</li>
+        </ul>
+    </ul>
+</ul>
+
+---
+
+## Agile Coretime
+
+<ul>
+    <li class="fragment">The first three cores are already being sold on Kusama</li>
+    <ul>
+        <li class="fragment">First renewals are already happening.</li>
+        <li class="fragment">There is some discussion about adjusting the market structure.</li>
+        <li class="fragment">In RFC17, I proposed some design for the market.</li>
+        <li class="fragment">Launch on Polkadot in August 2024!</li>
+    </ul>
+</ul>
+
+---
+
+## RFC 10
+
+<ul>
+    <li class="fragment">Proposed to burn coretime revenues.</li>
+    <li class="fragment">Got accepted by the fellowship.</li>
+    <li class="fragment"><strong>Clear incentives:</strong> Coretime is clearly a cost.</li>
+    <ul>
+        <li class="fragment">Some actors might asymmetrically benefit from Treasury.</li>
+    </ul>
+    <li class="fragment"><strong>Balancing Inflation:</strong> Deflationary pressure in the system.</li>
+    <ul>
+        <li class="fragment">Initially rather low.</li>
+    </ul>
+    <li class="fragment"><strong>Collective Value Accrual:</strong></li>
+    <ul>
+        <li class="fragment">Burning one DOT benefits all other DOTs equally.</li>
+    </ul>
+</ul>
+
+---
+
+## Why Agile Coretime?
+
+<ul>
+    <li class="fragment">This allows for low barriers of entry for people to simply deploy their code to a core and test stuff</li>
+    <li class="fragment">It makes blockspace more efficient, because not all teams can/want to have a full block every 6/12 seconds.</li>
+    <li class="fragment">Secondary markets increase efficiency and improve resource allocation.</li>
+
+</ul>
+
+---
+
+# Treasury
+
+<ul>
+    <li class="fragment">The treasury is an on-chain fund that holds DOT token and is governed by all token holders of the network.</li>
+    <li class="fragment">Those funds come from:</li>
+    <ul>
+        <li class="fragment">Transactions</li>
+        <li class="fragment">Slashes</li>
+        <li class="fragment">Staking inefficiencies (deviations from optimal staking rate)</li>
+    </ul>
+    <li class="fragment">Through governance, everybody can submit proposals to initiate treasury spending.</li>
+    <li class="fragment">It currently holds around 28M DOT.</li>
+    <li class="fragment">Spending is incentivized by a burn mechanism (1% every 24 days).</li>
+</ul>
+
+---
+
+## Treasury as DAO
+
+<ul>
+    <li class="fragment">A DAO (decentralized autonomous organization) that has access to funds and can make funding decisions directed by the collective (that have vested interest in the network).</li>
+    <li class="fragment">This has huge potential that might not yet have been fully recognized by the people.</li>
+    <li class="fragment">This provides the chain the power to fund its own existence and improves the utility in the future. It will pay…</li>
+    <ul>
+        <li class="fragment">… <strong>core developers</strong> to improve the protocol (fellowship).</li>
+        <li class="fragment">… <strong>researchers</strong> to explore new directions, solve problems and conduct studies that are beneficial for the network.</li>
+        <li class="fragment">… for campaigns <strong>educating people</strong> about the protocol.</li>
+        <li class="fragment">… for <strong>systems-parachains</strong> (development & collators).</li>
+    </ul>
+    <li class="fragment">A truly decentralized and self-sustaining organization.</li>
+</ul>
+
+---
+
+# How does it all fit together?
+
+---
+
+<div style="display: flex; justify-content: center; align-items: center;">
+    <img src="./img/Polkadot-Economics-Cycle.svg" style="width: 1200px;" />
+</div>
+
+---
+
+## Takeaways
+
+<ul>
+    <li class="fragment">Polkadot is a system that offers shared security and cross-chain messaging.</li>
+    <li class="fragment">Security scales, i.e., it takes less stake to secure 100 parachains than 100 individual chains.</li>
+    <li class="fragment">The DOT token captures the utility that the parachains provide and converts it to security.</li>
+    <li class="fragment">The slot mechanics (renewal, auctions) creates a market where parachains need to outcompete opportunity costs to be sustainable (i.e., they need to be useful).</li>
+    <li class="fragment">Polkadot is a DAO that will be able to fund its own preservation and evolution.</li>
+    <li class="fragment">There are many changes to come to Polkadot creating a much more agile system.</li>
+</ul>
+
+---
+
+# Potential Changes to the Economics
+
+---
+
+## Independent Treasury Inflow
+
+<ul>
+    <li class="fragment">The current system incentivizes to move the staking rate to the ideal rate.</li>
+    <li class="fragment">Then, Treasury inflow would be 0 DOT.</li>
+    <li class="fragment">That is not sustainable.</li>
+    <li class="fragment">Proposed change: Detach inflation to stakers from total inflation and divert the rest to Treasury directly.</li>
+</ul>
+
+---
+
+## Fixed Ideal Staking Rate
+
+<ul>
+    <li class="fragment">Ideal staking rate scales with number of parachains.</li>
+    <li class="fragment">The notion of parachain in its original form is being deprecated.</li>
+    <li class="fragment">It might be much more reasonable to aim for a static ideal staking rate. </li>
+</ul>
+
+---
+
+## Lowered inflation?
+
+<ul>
+    <li class="fragment">Voices become louder that demand lowering inflation.</li>
+    <li class="fragment">This will be a highly debated topic.</li>
+    <li class="fragment">Inflation is used to pay validators and nominators to do their job.</li>
+    <li class="fragment">Interesting how many people "wake up" to the debate trying to block lowering of inflation.</li>
+</ul>
+
+Notes:
+
+- Validator rewards are a major contributor to the economic security of Polkadot.
+- Lowering inflation leads to lowered rewards.
+- We could increase minimum commission, but that would further disadvantage nominators.
+
+---
+
+## Further Resources
+
+- [Agile Coretime RFC](https://github.com/polkadot-fellows/RFCs/pull/1)
+- [Updates on Coretime Sales](https://forum.polkadot.network/t/agile-coretime-launch-status-report/8347)
+- [Discussion on Changing Inflation Model](https://forum.polkadot.network/t/adjusting-the-current-inflation-model-to-sustain-treasury-inflow/3301)
+- [Talk about Agile Polkadot](https://www.youtube.com/watch?v=GIB1WeVuJD0)
+- [Nominating and Validator Selection On Polkadot](https://polkadot.network/blog/nominating-and-validator-selection-on-polkadot/)
+- [(Journal Version) Paper on Validator Selection](https://www.sciencedirect.com/science/article/abs/pii/S0305048323000336)
+- [(Open Source Version) Paper on Validator Selection)](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4253515)
+- [Referendum 166](https://polkadot.polkassembly.io/referenda/166)
+- [Discussing on adjusting ideal rate](https://forum.polkadot.network/t/adjusting-polkadots-ideal-staking-rate-calculation/3897)
+- [RFC17](https://github.com/polkadot-fellows/RFCs/pull/17)
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+# Module 2: Economics and Game Theory
+
+#### Prerequisites:
+
+## Learning Outcomes
+
+Completing this module will enable participants to:
+
+- Understand and discuss the basic principles of economics, including the influence of incentives on human behavior, supply and demand, the value of time, and the role of prices in allocating resources.
+- Analyze and comprehend the principles of game theory, including strategic games, Nash equilibrium, and the role of incentives in shaping outcomes.
+- Understand and apply the concepts of price discovery mechanisms and their implications in various market settings.
+- Understand the principles of collective decision-making, including voting systems, group decision-making processes, and the role of consensus in collective decisions.
+
+## Hands on activities
+
+#### Academy Games
+
+The Web3 Foundation is needed to run their proprietary Academy Games that provide a fun and interactive way to play with auctions and more in real time as a class.
+These are played with **real money on the line** and ends in an auction with those funds for NFTs specially generated per-cohort that typically feature a local to the area NFT artist with art inspired by the region.
+
+## Schedule
+
+### Day 1 (0.5 day)
+
+#### Afternoon
+
+1. [Economics Basics](1-Economics_Basics-slides.md) (1.5hr)
+1. Classroom discussions (0.5hr)
+1. Academy Games (1.5hr)
+   - Ultimatum Game
+   - Cournot Competition
+
+### Day 2
+
+#### Morning
+
+1. [Game Theory](2-Game_Theory-slides.md) (1.5hr)
+1. Classroom discussions (0.5hr)
+1. Academy Games 2 (1.5hr)
+   - Guessing Game
+   - Prisoner's Dilemma
+   - Public Goods Game
+
+#### Afternoon
+
+- [Price Finding Mechanisms](3-Price_Finding_Mechanisms-slides.md) (1.5hr)
+- Classroom discussions (1hr)
+- Academy Games NFT Auction (0.5hr)
+
+### Day 3 (0.25 day)
+
+#### Morning
+
+- Quiz
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+# Economics and Game Theory
+
+_Applied_ economics and game theory fundamental to the architecture and operation of web3 applications.
+
+## Learning Outcomes
+
+Completing this module will enable you to:
+
+- Understand and discuss the basic principles of economics, including the influence of incentives on human behavior, supply and demand, the value of time, and the role of prices in allocating resources.
+- Analyze and comprehend the principles of game theory, including strategic games, Nash equilibrium, and the role of incentives in shaping outcomes.
+- Understand and apply the concepts of price discovery mechanisms and their implications in various market settings.
+- Understand the principles of collective decision-making, including voting systems, group decision-making processes, and the role of consensus in collective decisions.
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+---
+title: Coordination and Centralization - Past Present and Future
+description: For 200k years humans have been learning how to coordinate better. The Blockchain is our generation's contribution.
+duration: 30 - 45 minutes
+---
+
+# Coordination and Centralization
+
+## Past Present and Future
+
+Notes:
+
+Introduce instructors, tell about background, glad to be here.
+Let's all learn together.
+Shoot the shit until the initial nervousness starts to wear off, or at least peaks.
+
+Lets get started.
+
+For 100ks of year, humans have been on this earth.
+During this time we have been working on better and better ways to understand each other, and coordinate with each other.
+Sometimes we coordinate to do great things like build skyscrapers, or win sports tournaments.
+Other times we just coordinate enough to not anger each other.
+
+I believe that blcokchain is our generation's contribution to this endeavor that human kind is on.
+
+---
+
+## Goals
+
+- Trustless provisioning of infrastructure. <!-- .element: class="fragment" -->
+- Ways to coordinate with people we don't trust. <!-- .element: class="fragment" -->
+
+Notes:
+
+So. What are we doing here? What are our goals?
+
+First:
+Something kind of like a server, that doesn't rely on a server operator, and has strong guarantees like Cryptography has to offer.
+
+Next: Coming to a shared understanding of a common history, and therefore a common state, of a system.
+
+---v
+
+## Comparison with Cryptography
+
+Cryptography provides strong guarantees about _messages_ without a trusted party, regardless of the conduit over which a message was transported.
+
+Notes:
+
+Crypto guarantees:
+
+- No tampering
+- No eavesdropping
+- Authenticity of the author
+
+We want these same _kinds_ of guarantees, not just about messages, but about entire systems.
+
+---
+
+## A Shared History
+
+<img style="height: 500px;" src="./img/overview/sapiens.jpg" />
+
+Notes:
+
+So now we understand the goals of web3. How do we achieve them? The key is allowing users to agree on a shared history. The simplest blockchains do nothing more than timestamp and attest to a stream of historical records. In Web 2, and indeed often in governmental bureaucracies, users have no visibility into the history of the app. They must trust the provider to accurately represent the current state. By giving the service provider the power to change the story, we give them the power to shape our understanding of reality and consequently our behavior.
+
+---v
+
+## A Shared History
+
+> Any large-scale operation - whether a modern state, a medieval church, or an archaic tribe - is rooted in common stories that exist only in people's collective imaginations.
+
+> Telling effective stories is not easy. The difficulty lies ... in convincing everyone else to believe it. Much of history revolves around this question: How does one convince millions of people to believe particular stories about gods, nations, or LLCs?
+
+<!-- .element: class="fragment" -->
+
+_-- Yuval Noah Harari, Sapiens --_
+
+Notes:
+
+Knowing and believing shared stories is important because it helps bootstrap trust.
+
+---
+
+## Let's Tell Some Stories
+
+- Enuma Elish<!-- .element: class="fragment" -->
+- Cherokee Creation Story<!-- .element: class="fragment" -->
+- Big Bang<!-- .element: class="fragment" -->
+- Genesis Creation Stor(ies)<!-- .element: class="fragment" -->
+
+Notes:
+
+Tell them or let students tell them.
+
+These stories have really stood the test of time. They span cultures. They are the bedrock of much of modern humanity's understanding of who they are.
+
+---v
+
+## Newer Stories
+
+<img style="height: 500px;" src="./img/overview/DeclarationOfIndependance.png" />
+
+Notes:
+
+I'm not only a human. I'm also an American. This story is also important to me.
+
+I bet some of you have other similar stories.
+
+---v
+
+## Modern Stories
+
+Chancellor on Brink of second bailout for banks
+
+<img style="height: 500px;" src="./img/overview/ChancellorOnBrink.jpeg" />
+
+Notes:
+
+---
+
+## Storytelling Technology
+
+<img style="height: 500px;" src="./img/overview/StorytellingTechnology.png" />
+
+---
+
+## Who Writes the Story?
+
+A Dictator?
+
+<blockquote>Dictator (n) - One who dictates, speaks, or narrates.
+
+Notes:
+
+This is how we used to understand how much grain was in the grainery.
+
+This is how we used to understand what the holy scriptures told us to do.
+
+This is dangerous.
+
+---v
+
+## Tell the Story Together
+
+<img style="height: 500px;" src="./img/overview/campfire1.png" />
+
+---v
+
+## Tell the Story Together
+
+<img style="height: 500px;" src="./img/overview/campfire3.png" />
+
+---v
+
+## Tell the Story Together
+
+<img style="height: 500px;" src="./img/overview/campfire4.png" />
+
+---
+
+# The 21st Century Rumor Mill
+
+Notes:
+
+Shifting gears a little bit, let's take a look at what oral tradition, communication, and gossip have looked like in more recent times.
+
+---
+
+## Web 0
+
+Telegraph, Telephone
+
+Users transmit information peer-to-peer.
+
+Crypto not typically used except by military, but upheld guarantees when used.
+
+<img src="./img/overview/Web0.png" />
+
+---
+
+## Web 1
+
+Introduction of always-on servers.
+
+Still mostly peer-to-peer.
+
+Cryptography more often, but still not ubiquitous.
+
+<img style="width: 300px;" src="./img/overview/Web1.png" />
+
+---
+
+## Web 2
+
+Introduction of **Digital Services** with **Rich State**.
+
+Administered by service providers: "Send _us_ your information."
+
+However, users must place faith in the service provider.
+
+Cryptographic guarantees are about interactions with the service provider, not peers.
+
+<img style="width: 300px;" src="./img/overview/Web2.png" />
+
+---v
+
+## Digital Services
+
+People rely on digital services every day.
+They are inescapable and valuable.
+
+- Twitter, Instagram, Facebook, etc.
+- Journalism and sources
+- Banks
+- Lawyers, notaries, regulators
+
+Notes:
+
+- Ask class for more examples
+- Digital services are not bad in and of themselves. They are very valuable. We use all of these every day. We are even using some to administer this course. But they are also hard to escape.
+
+---v
+
+## Trust Example
+
+Two users on Twitter:
+
+- Trust that we are seeing information from the same database\*
+- Trust that if a tweet is from X, then X wrote that tweet\*
+- Trust that others see our messages as from us\*
+- Trust that the messages we see are the messages the users wrote\*
+- Trust that we're interacting with the application as equals
+
+Notes:
+
+- Cryptography actually provides a lot of these guarantees, but not when an intermediary has stepped in between users.
+- This is one example, but class should discuss.
+
+---v
+
+## God Mode Enabled
+
+In web 2, service providers can perform abuses:
+
+- Censoring user interaction
+- Restricting users interaction
+- Failing to produce requested data
+- Mutating state opaquely
+
+---v
+
+## Thought experiment: Digital Currency
+
+Bitcoin's application was digital currency - a trivially simple application.
+
+Could this be built with Web2 technology?
+
+Notes:
+
+Yep it could. This is the kind of simple app you might build in a Freshman year course
+on modern web interfaces. It just needs to maintain a set of bank notes and their owners (or alternatively a set of accounts and their balances.) So why didn't this exist in web 2? Because the provider could print money. Or steal money. Or freeze funds.
+Side thought. How different is this from fiat currencies?
+
+---v
+
+## Distributed Applications in Web 2
+
+Providers run redundant data centers to prevents accidents.
+
+But it still assumes benevolent participants and some trusted leader.
+
+Notes:
+
+Even in web2 we start to see the idea of redundancy to prevent accidents from natural disasters, sabotage, hardware failure etc.
+But we do not yet see disintermediation. In web 2, the masses become beholden to the service providers who were free to extract value and manipulate the users.
+
+In fact redundant systems were widely studied even before web 2. Consider a flight computer that has sensors for things like air speed and altitude. If one sensor fails we want the plane to keep flying.
+
+---
+
+## Web3
+
+- <span>A provision of digital services without the need to trust a service _provider_.</span> <!-- .element: class="fragment" -->
+- Providers do not need to be trusted; they are economically incentivized to behave honestly. <!-- .element: class="fragment" -->
+- Allow users to interact with a common system without trusting any intermediaries. <!-- .element: class="fragment" -->
+
+Notes:
+
+We want to maintain the value, versatility, and richness of Web2, but remove the trust, and possibility of extractive behavior.
+
+---
+
+# Desired Properties
+
+---v
+
+## Permissionless access
+
+Anyone should be able to access and interact with the system.
+
+---v
+
+## Privacy
+
+Users should have credible expectations about what information they give up about themselves.
+
+---v
+
+## Authenticity
+
+Users should have credible expectations about the messages they see, regardless of the platform the messages are on.
+
+---v
+
+## Finality
+
+Users should be able to form credible expectations about when a state transition is final.
+
+---v
+
+## Behavior
+
+The system should behave as expected, even if system operators do not.
+
+---v
+
+## Unstoppability
+
+No individual actor, company, state, or coalition should be able to degrade any of these properties.
+
+---
+
+# Coordination and Centralization
+
+## Past Present and Future
diff --git a/content/3-Blockchain/2-P2P_Networks-slides.md b/content/3-Blockchain/2-P2P_Networks-slides.md
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+---
+title: Peer-to-Peer (P2P) Networking
+description: Peer-to-Peer (P2P) networking for Web3 engineers
+---
+
+# Peer-to-Peer Networking
+
+---
+
+## From Circuit Switching to **Packet Switching**
+
+- Mode of data transmission in which a message is broken into a number of parts (packets) that are sent independently <!-- .element: class="fragment" data-fragment-index="2" -->
+- Packets are sent over whatever route is optimal <!-- .element: class="fragment" data-fragment-index="3" -->
+- Packets are reassembled at the destination <!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+Standard telephone networks used circuit switching, where a physical wire connected two communicating ends.
+
+Packet-switching, on the other hand, is a more decentralized approach that can divide data, send it across the network, and reconstruct it.
+
+The network is now able to survive partial destruction because there is no longer a single physical circuit between machines.
+
+It was the first step toward a distributed and resilient network
+
+---v
+
+## Packets
+
+<img style="width: 600px" src="./img/message_packet.svg" />
+
+Notes:
+
+Mention that headers contain addressing, destination information, and ordering, typically depending on the context
+
+---v
+
+## Routing
+
+<img style="width: 600px" src="./img/packet_switching_1.svg"  />
+
+Notes:
+
+We have a message that needs to be sent between two nodes.
+
+---v
+
+## Routing
+
+<img  style="width: 600px" src="./img/packet_switching_2.svg" />
+
+Notes:
+
+A Route is composed of all the nodes that will be traversed before reaching the ends.
+
+Not all packets need to traverse the same route
+
+---v
+
+## What if a node goes down?
+
+<img style="width: 600px" src="./img/packet_switching_3.svg" />
+
+---v
+
+## Another Route is Used
+
+<img style="width: 600px" src="./img/packet_switching_4.svg" />
+
+Notes:
+
+That's the strength of Packet Switching Networks, they are resilient and can survive a partial shutdown of the network
+
+As said before, not all packets need to be routed in the same way
+
+---v
+
+## ARPANET
+
+- First operational packet-switching network <!-- .element: class="fragment" data-fragment-index="2" -->
+- Developed in the late 1960s by DARPA(The Defense Advanced Research Projects Agency) <!-- .element: class="fragment" data-fragment-index="3" -->
+- Laid the foundation for the modern internet <!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+Arpanet followed a more Client-Server structure, where people were asking for papers, documents, and other information
+
+---
+
+## Peer-to-Peer (P2P) Networks
+
+- Unlike client-server model, all nodes (peers) are equal participants <!-- .element: class="fragment" data-fragment-index="2" -->
+- P2P is a decentralized form of network structure <!-- .element: class="fragment" data-fragment-index="3" -->
+- Data is shared directly between systems without a central server <!-- .element: class="fragment" data-fragment-index="4" -->
+- Peers contribute resources, including bandwidth, storage space, and processing power <!-- .element: class="fragment" data-fragment-index="5" -->
+
+Notes:
+
+As opposed to client-server structures, p2p structures are a different type of network in which all nodes are at the same level
+
+---
+
+## Historical P2P applications
+
+Notes:
+
+Napster, Limewire, BitTorrent
+
+---
+
+## Napster
+
+- Launched in 1999, first P2P sharing platform <!-- .element: class="fragment" data-fragment-index="2" -->
+- Central server for indexing, P2P for transfers <!-- .element: class="fragment" data-fragment-index="3" -->
+- Shutdown in 2001 due to legal issues <!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+Napster's story is closely tied with the band Metallica.
+In 2000, Metallica discovered that a demo of their song "I Disappear" was being circulated via Napster before its official release.
+This led to Metallica filing a lawsuit against Napster for copyright infringement.
+Napster had to comply by banning hundreds of thousands of users from their platform who were sharing Metallica's music.
+This was a turning point in digital copyright law and played a significant role in Napster's eventual shutdown in 2001.
+
+---v
+
+## Napster Setup
+
+<img style="width: 600px" src="./img/napster_1.svg" />
+
+---v
+
+## Napster Setup
+
+<img style="width: 600px" src="./img/napster_2.svg" />
+
+---v
+
+## Napster Setup
+
+<img style="width: 600px" src="./img/napster_3.svg" />
+
+---v
+
+## Napster Setup
+
+<img style="width: 600px" src="./img/napster_4.svg" />
+
+---
+
+## Limewire
+
+- Free Software p2p file sharing client <!-- .element: class="fragment" data-fragment-index="2" -->
+- In its history, it has mainly used two protocols: <!-- .element: class="fragment" data-fragment-index="3" -->
+  - Gnutella <!-- .element: class="fragment" data-fragment-index="3" -->
+  - BitTorrent <!-- .element: class="fragment" data-fragment-index="3" -->
+
+---v
+
+## Gnutella
+
+- Each node serves as both a client and a server <!-- .element: class="fragment" data-fragment-index="2" -->
+- Query recursively all connected nodes for files <!-- .element: class="fragment" data-fragment-index="3" -->
+- It does not just flood the network, it does it intelligently using concepts such as:
+  <!-- .element: class="fragment" data-fragment-index="4" -->
+  - Infection Factor
+  <!-- .element: class="fragment" data-fragment-index="5" -->
+  - TTL (Time To Live)
+  <!-- .element: class="fragment" data-fragment-index="5" -->
+
+<img style="width: 400px" src="./img/gnutella.gif" />
+<!-- .element: class="fragment" data-fragment-index="5" -->
+
+Notes:
+
+- Check local filestore for file and if it is not available, forward the request to all connected peers.
+
+- Gnutella generates a significant amount of network traffic
+
+Deep explanation of gossiping and how Gnutella gossiping works: https://nakamoto.com/gnutella/
+
+---v
+
+## BitTorrent
+
+First launched using Trackers: <!-- .element: class="fragment" data-fragment-index="2" -->
+
+- Files are split into multiple pieces <!-- .element: class="fragment" data-fragment-index="3" -->
+- .torrent files contain the hash of the pieces <!-- .element: class="fragment" data-fragment-index="4" -->
+- Trackers saves which peers in the network have which file
+
+<!-- .element: class="fragment" data-fragment-index="5" -->
+
+```rust
+HashMap<FileId, Vec<Peer>>
+```
+
+<!-- .element: class="fragment" data-fragment-index="5" -->
+
+- You can download different pieces by different peers in parallel <!-- .element: class="fragment" data-fragment-index="6" -->
+
+Notes:
+
+More efficient peer-to-peer (p2p) file sharing networks than Gnutella (but more centralized).
+
+Each data was split into multiple packets.
+
+You could request from each peer in the swarm a piece of the file you wanted to download to really take advantage of the increased bandwidth offered by the p2p network
+
+---v
+
+<img style="width: 600px" src="./img/bittorrent.svg" />
+
+---v
+
+## BitTorrent
+
+Later introduced, **Trackerless** mode:
+
+<!-- .element: class="fragment" data-fragment-index="7" -->
+
+- Does not require Tracker nodes
+
+<!-- .element: class="fragment" data-fragment-index="8" -->
+
+- How does it achieve that? How is the knowledge of who has what is shared across the network?
+
+<!-- .element: class="fragment" data-fragment-index="9" -->
+
+Notes:
+
+Trackerless was added later to support fully decentralized networks. It uses something called Distributed Hash Table (DHT), particularly Kademlia (a specific type of DHT)
+
+---v
+
+### Distributed Hash Table - DHT
+
+Same `HashMap` as before, but distributed:
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- key: hash of the .torrent file (=FileId)
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+- value: list of peers who own the file <!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+Instead of going directly to the tracker node, a single peer who knows the info hash could use the DHT to ask the network for the list of needed peers
+
+---v
+
+### Kademlia
+
+- Each node in the network has a NodeId <!-- .element: class="fragment" data-fragment-index="2" -->
+- Keys are the same length of NodeIds <!-- .element: class="fragment" data-fragment-index="3" -->
+- NodeIds and Keys live in the same Key Space <!-- .element: class="fragment" data-fragment-index="4" -->
+- XOR is used as distance metric between NodeIds and Keys <!-- .element: class="fragment" data-fragment-index="5" -->
+- The knowledge of distance is used for: <!-- .element: class="fragment" data-fragment-index="6" -->
+  - save known peers and values <!-- .element: class="fragment" data-fragment-index="7" -->
+  - understand were to ask for new key-value pairs <!-- .element: class="fragment" data-fragment-index="8" -->
+
+Notes:
+
+The Kademlia specification is not very extensive, but here we will provide an overview of how effectively the nodes know where to ask for key-value pairs not owned by them.
+
+The distance metric makes it possible to understand the distance between you and the key you are looking for. This enables knowing where to ask for the key: the closest node to the key you know of!
+
+---
+
+<section>
+    <h2>Client-Server vs Peer-to-Peer (P2P) Networks</h2>
+    <table>
+        <thead>
+            <tr>
+                <th></th>
+                <th>Client-Server Network</th>
+                <th>P2P Network</th>
+            </tr>
+        </thead>
+        <tbody>
+            <tr class="fragment">
+                <td>Structure</td>
+                <td>Centralized: One or more central servers control the network</td>
+                <td>Decentralized: All nodes (peers) participate equally</td>
+            </tr>
+            <tr class="fragment">
+                <td>Data Flow</td>
+                <td>Server provides data to clients</td>
+                <td>Peers directly share data with each other</td>
+            </tr>
+            <tr class="fragment">
+                <td>Resource Management</td>
+                <td>Servers manage resources and control access</td>
+                <td>Peers contribute resources including bandwidth, storage space, and processing power</td>
+            </tr>
+            <tr class="fragment">
+                <td>Scalability</td>
+                <td>Can be limited by server capacity</td>
+                <td>Highly scalable due to the distribution of resources</td>
+            </tr>
+            <tr class="fragment">
+                <td>Security</td>
+                <td>Centralized security measures, single point of failure</td>
+                <td>Potential attack vector to the network from the outside, but also sensible to malicious actors
+            </tr>
+        </tbody>
+    </table>
+</section>
+
+---
+
+### Single Point of failure - Centralized Networks
+
+<img style="width: 600px" src="./img/client_server_1.svg" />
+
+---v
+
+### Single Point of failure - Centralized Networks
+
+<img style="width: 600px" src="./img/client_server_2.svg" />
+
+---v
+
+### Single Point of failure - Decentralized Networks
+
+<img style="width: 600px" src="./img/p2p_topology_1.svg" />
+
+Notes:
+
+1. No single node or nodes (CDN) have access to all of the content or files or is critical for operating the network. Each node has a copy of the data.
+2. No central node carrying all of the load of traffic.
+
+---v
+
+### Single Point of failure - Decentralized Networks
+
+<img style="width: 600px" src="./img/p2p_topology_2.svg" />
+
+Notes:
+
+4. Difficult to overload the network or DOS (No single node is privileged).
+5. Although many nodes are run on Centralized cloud compute platforms, they don't have to be (Typically).
+
+Mention to block production ans block peering/importing. Generally there is no one single node carrying all the block production locic and not transactions and blocks fly in the same direction to a single node, but they are gossiped around.
+
+---
+
+## Overlay Network
+
+<img style="width: 600px" src="./img/overlay.svg" />
+
+Notes:
+
+This is how you can imagine the p2p network, lines represent the knowledge of other nodes.
+
+But...
+
+---v
+
+## Underlay Network
+
+<img style="width: 600px" src="./img/underlay.svg" />
+
+Notes:
+
+This could be the real physical connection, and something like a transatlantic cable could be connecting two completely separate sets of nodes.
+
+There could be logical connections that are not physical but also the opposite
+
+---v
+
+## The Underlay Network breaks
+
+<img style="width: 600px" src="./img/underlay_2.svg" />
+
+---v
+
+## What's happen to the overlay?
+
+<img style="width: 600px" src="./img/overlay_2.svg" />
+
+Notes:
+
+There are two disjointed networks that will continue working on their behalf. You will learn in later lectures what could happen if this network were running a blockchain
+
+---
+
+## Difficulties or Disadvantages
+
+- Since it is permissionless, a node can share malicious resources <!-- .element: class="fragment" data-fragment-index="2" -->
+- Latency <!-- .element: class="fragment" data-fragment-index="3" -->
+- Difficult to regulate illicit activity <!-- .element: class="fragment" data-fragment-index="4" -->
+- The network is limited by nodes with the weakest hardware <!-- .element: class="fragment" data-fragment-index="5" -->
+
+Notes:
+
+1. eg. wrong blocks making other nodes wasting time discarting them
+2. Latency may be an issue if we need to wait for many peers to receive the data produced from a single node since everyone may not have a direct connection.
+   Mention finality time!
+3. No central point to go and snoop all users data (for better or for worse).
+4. Why we have hardware requirements for blockchain networks.
+
+---
+
+<section>
+    <h2>Structured vs Unstructured P2P Networks</h2>
+    <table>
+        <thead>
+            <tr>
+                <th></th>
+                <th>Structured P2P Networks</th>
+                <th>Unstructured P2P Networks</th>
+            </tr>
+        </thead>
+        <tbody>
+            <tr class="fragment">
+                <td>Organization</td>
+                <td>Nodes are organized following specific protocols and structures (like Distributed Hash Tables)</td>
+                <td>Nodes are connected without any particular organization</td>
+            </tr>
+            <tr class="fragment">
+                <td>Search Efficiency</td>
+                <td>Efficient search operations due to structured nature</td>
+                <td>Search operations may be less efficient and can involve flooding the network</td>
+            </tr>
+            <tr class="fragment">
+                <td>Flexibility</td>
+                <td>Less flexible as changes in topology require restructuring</td>
+                <td>Highly flexible as nodes can freely join, leave, and reorganize</td>
+            </tr>
+            <tr class="fragment">
+                <td>Privacy</td>
+                <td>Data location is predictable due to structured organization</td>
+                <td>Greater potential for anonymity</td>
+            </tr>
+        </tbody>
+    </table>
+</section>
+
+---
+
+## Gossip Protocol
+
+<img style="width: 500px" src="./img/3.7-p2p-gossip-1.svg" />
+
+Notes:
+
+Given structured or unstructured networks, messages still have to be transmitted to other nodes
+
+In blockchain, nodes could gossip blocks that have been produced or received by someone else. Now it's time for that node to decide how it should be gossiped
+
+---v
+
+## Gossip Protocol
+
+<img style="width: 85s0px" src="./img/3.7-p2p-gossip-2.svg" />
+
+Notes:
+
+Bitcoin floods the network with requests, gossiping the block to all the known nodes, because the want share the last produced block as fast as possible.
+
+Less consuming strategies could be applied, as Gnutella did, or even using advertising. Asking for more context before sending the data.
+
+There are multiple ways to gossip information/blocks, and it depends on why you're sharing that information.
+
+---
+
+## Discovery
+
+1. Connect to a peer <!-- .element: class="fragment" data-fragment-index="2" -->
+2. Ask peer for a list of their known nodes <!-- .element: class="fragment" data-fragment-index="3" -->
+3. Connect to random subset of peers from the list <!-- .element: class="fragment" data-fragment-index="4" -->
+4. Repeat steps 2 and 3 <!-- .element: class="fragment" data-fragment-index="5" -->
+
+Notes:
+
+We talked about how the network works, how it can be used, but not how to join it
+
+---v
+
+## Initial Discovery
+
+requires bootnodes (More on this later in Substrate)
+
+Notes:
+
+Must know someone who is participating in the network initially(Bootnode)
+
+---
+
+## Attacks
+
+<img style="width: 600px" src="./img/eclipse_attack_1.svg"/>
+
+Notes:
+
+- Can anyone think of a way to exploit some of these networks?
+- What would be some things to try to take advantage of?
+
+There are multiple ways to attack an open network like the one we described because you can actively participate in it and behave maliciously.
+
+1. Distorts view of the healthy normal honest state of the network
+2. Transaction confirmations can be fictions
+3. Sybil Attack
+4. Data Poisoning
+5. Content Pollution
+
+---v
+
+## Eclipse Attack
+
+<img style="width: 600px" src="./img/eclipse_attack_2.svg"/>
+
+---v
+
+## Eclipse Attack Execution
+
+1. Flood a target node with a bunch of malicious peer addresses <!-- .element: class="fragment" data-fragment-index="2" -->
+1. The targeted node then stores these malicious peers and utilizes them when re-syncing on next bootup <!-- .element: class="fragment" data-fragment-index="3" -->
+1. DOS targeted node to take it offline to force a resync with these new malicious peers <!-- .element: class="fragment" data-fragment-index="4" -->
+
+---v
+
+## Preventing Attacks
+
+- Restrict inbound connections in some way <!-- .element: class="fragment" data-fragment-index="2" -->
+- Random selection of peers to connect with <!-- .element: class="fragment" data-fragment-index="3" -->
+- Deterministic node selection (Bootnodes) <!-- .element: class="fragment" data-fragment-index="4" -->
+- Restricting new nodes (Probably not what we want...) <!-- .element: class="fragment" data-fragment-index="5" -->
+
+Notes:
+
+1. Be wary of new connections with other nodes
+1. Don't just take the most recent request for connections to avoid the flooding
+1. Bootnodes with higher credibility and trust (Can be a bottleneck) - Rotate bootnodes as they are also subject to attacks
+
+---
+
+## libp2p
+
+- Created during the development of IPFS (InterPlanetary File System)
+- Modular system of protocols, specifications and libraries that enable the development of peer-to-peer network applications
+- Used in Substrate
+
+Notes:
+
+Libp2p aims to be a modular, general-purpose toolkit for any peer-to-peer application.
+
+Not reinventing the wheel
+
+---
+
+## Conclusion
+
+P2P networks offer us a path forward towards applications which are more decentralized and censorship resilient
diff --git a/content/3-Blockchain/2.5-State_Machines-slides.md b/content/3-Blockchain/2.5-State_Machines-slides.md
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+---
+title: State Machines
+description: State machines, labelled transition systems, and their role in blockchain systems.
+duration: 30 - 45 minutes
+---
+
+# State Machines
+
+---
+
+## State Machines
+
+We can formalize this notion of shared story with state machine model.
+
+<img width="800px" src="./img/state-machine/state-machine-general.svg" />
+
+Notes:
+
+Most systems that we care about can be modeled as state machines. A state machine is not a real machine that you can touch. It is a model comprised of a set of states and a set of rules about how to transition between the states.
+
+---v
+
+## Labelled Transition Systems
+
+Sometimes you can map the entire state space as an LTS.
+
+Other times it is too big.
+
+<img src="./img/state-machine/state-machine-arbitrary-history.png" />
+
+Notes:
+
+Consider if we tried to map all possible states of a social media app or a digital currency. Sometimes an LTS drawing like this is useful, other times it would be too large or even infinite. Even still, sometimes drawing part of it can help you think about what the states and transitions might be.
+
+Example: Audio Amplifier
+
+There are three buttons (louder, quieter, mute). The amplifier's volume output can be one of four levels: Silent, Quiet, Normal, Loud. Volume up and down should be pretty clear. When you mute the output immediately goes silent, and when you unmute it goes back to whatever it was before.
+
+Q: How should we model the states?
+A: We could make the states directly be the volume levels. Let's try that.
+
+Q: Is this enough? How do we unmute?
+A: Gonna need to store the "previous_volume"
+
+---v
+
+## Example: Light Switch
+
+Simple Switch: 2 States, 1 Transition
+
+**Labelled Transition System** <!-- .element: class="fragment" data-fragment-index="2" -->
+
+<img src="./img/state-machine/light-switch-lts.svg" /> <!-- .element: class="fragment" data-fragment-index="2" -->
+
+**History** <!-- .element: class="fragment" data-fragment-index="3" -->
+
+<img src="./img/state-machine/light-switch-history.svg" /> <!-- .element: class="fragment" data-fragment-index="3" -->
+
+---v
+
+## State Machine Example: Digital Cash
+
+Each state is a set of bank notes. Where a bank note has an amount and an owner.
+A transition involves a user consuming (spending) some bank notes and creating new ones.
+
+<img width="800px" src="./img/state-machine/state-machine-cash.svg" />
+
+Notes:
+
+Not all conceivable transitions are valid. Imagine a user consuming a bank note worth 5 coins, and creating two new ones each worth 3 coins.
+
+---v
+
+## Sate Machine Example: Social Media
+
+Each state is a set of posts and their associated comments and emoji reaction counts.
+A transition involves, making a new post, or reacting to someone elses, or commenting
+
+<img src="./img/state-machine/state-machine-social.svg" />
+
+Notes:
+
+There is not a single model here. Some state machines will allow deleting or editing posts, while others will not. Some will allow disliking posts while others only allow liking.
+
+---v
+
+## More State Machine Examples:
+
+<pba-flex center>
+
+- Light Control in this room
+- A Car-style Transmission vs a Motorcycle-style Transmission
+- Hotel Elevator
+- Roulette table
+
+</pba-flex>
+
+Notes:
+
+Let's brainstorm what the state and the transitions might be for each of these.
+
+Feel free to simplify these as necessary.
+
+---v
+
+## Shared Story of a State Machine
+
+<pba-cols>
+<pba-col>
+<pba-flex center>
+
+If we agree on:
+
+- The starting state<br/>(aka genesis state)
+- The history of transitions
+
+</pba-col>
+<pba-col>
+</pba-flex>
+
+Then we _MUST_ agree on:
+
+<pba-flex center>
+
+- The current state
+
+</pba-flex>
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Now that we have a formal math-y model of systems that we care about, we can see that the notion of shared stories being powerful is more than slick language of philosophical mumbo jumbo. Even the term genesis state (or genesis block) is taken straight from mythology. We aren't newly discovering or inventing the idea that having a shared understanding of our past is important. It dates back to pre-history. We are just formalizing it and applying it to digital services.
+
+I have a talk from 2020 that goes into more detail and philosophy about this shared history idea and its relation to blockchain:
+https://www.youtube.com/watch?v=FZXk3_RTvfc
+
+It is one of my favorite talks I've ever given.
+
+---
+
+## Blockchains (Finally)
+
+A blockchain can be thought of in three parts
+
+<pba-cols>
+<pba-col>
+<pba-flex center>
+
+**State Machine**
+
+What does the state hold?
+
+What are the _rules_ to change it?
+
+</pba-flex>
+</pba-col>
+<pba-col>
+<pba-flex center>
+
+**Shared History** (data structure)
+
+Which potential histories exist?
+
+</pba-flex>
+</pba-col>
+<pba-col>
+
+<pba-flex center>
+
+**Consensus**
+
+Which history is the real one?
+
+What part of history is final?
+
+</pba-flex>
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Let's end this lesson with a little history of what we have seen in the blockchain space so far.
+
+First, each blockchain tracks some state machine. We've discussed several examples of what that might be already, we'll code some simple examples shortly, and we'll spend all of module 5 digging into how to create a blockchain-friendly production-ready state machine.
+
+Next is the Blockchain Data structure. This data structure is basically a linked list of state transitions. But unlike the linked lists you studied in your data structures course, it isn't just linked by memory addresses or any other malleable thing. Instead it is cryptographically linked so that if anyone presents a different history, you can tell right away that you don't agree on a shared history. We'll dive into this data structure in the next lesson.
+
+Finally, is a consensus mechanism. Defining a state machine alone does not uniquely define a history. There are many possible valid histories. Just like the many worlds interpretation of quantum mechanics. To really agree on the current state, we need to agree on which of the possible histories is the real one.
+
+---v
+
+## Short History of Blockchains
+
+---v
+
+## Bitcoin
+
+<img rounded style="width: 500px;" src="./img/state-machine/bitcoin-transaction.png" />
+
+Uses an unspent transaction output (UTXO) model & Proof of Work (PoW) consensus. <!-- .element: class="fragment" -->
+
+Notes:
+
+Who knows where the figure is from?
+
+CLICK
+
+Bitcoin was first.
+It was a money app.
+The first app chain.
+It hosts a smart contract in the broad definition.
+
+It was the first time most people considered a digital service that was not run by a particular person.
+
+Figure source: [Bitcoin white paper](https://bitcoin.org/en/bitcoin-paper)
+
+---v
+
+## Litecoin, Monero, Dogecoin
+
+<img src="./img/state-machine/altcoins.png" />
+
+Notes:
+
+Only a few year later people realized they could fork the code and make small changed and improvements.
+Some changes were trivial.
+Some were interesting: monero and privacy.
+
+For me personally, this was a small crisis.
+I thought bitcoin was the one global one.
+Aren't these other coins undermining the narrative?
+NO! The point is that anytime you don't like the system or have an idea for a better one, you can do it!
+If you don't like bitcoin, build your own coin and make it better.
+Let the market decide.
+
+---v
+
+## Ethereum and Smart Contracts
+
+- Generalization of Bitcoin: provides a quasi-Turing-complete VM
+- Uses an account-based system
+- Accounts can store balances, but can also store executable code (smart contracts)
+- Each contract can have its own internal state and API
+
+---v
+
+## Polkadot, Cosmos, Avalanche, Near, ...
+
+Notes:
+
+Iterations on Ethereum's general computing platform. Strive for scalability interoperability etc. Experiment with different consensus models.
diff --git a/content/3-Blockchain/3-Blockchain_Structure-slides.md b/content/3-Blockchain/3-Blockchain_Structure-slides.md
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+---
+title: Blockchain Structure
+description: The Blockchain data structure including hash-linking, forks, header vs body, and extrinsics.
+duration: 30 min
+---
+
+# Blockchain Structure
+
+![An opaque blockchain structure](./img/opaque-blockchain.svg)
+
+---
+
+## Shared Story
+
+A Blockchain **cryptographically guarantees** that a history of events has not been tampered with.
+This allows interested parties to have a **shared history**.
+
+Notes:
+
+And it allows them to know whether they have identical histories in O(1) by just comparing the tip of the chain.
+
+---
+
+## Hash Linked List
+
+<img src="./img/hash-linked-1.svg" width="1000px" />
+
+Notes:
+
+This is a simplified blockchain. Each block has a pointer to the parent block as well as a payload.
+
+---v
+
+## Hash Linked List
+
+<img src="./img/hash-linked-2.svg" width="1000px" />
+
+Notes:
+
+The pointer is a cryptographic hash of the parent block.
+
+---v
+
+## Hash Linked List
+
+<img src="./img/hash-linked-3.svg" width="1000px" />
+
+Notes:
+
+This ensures data integrity throughout the entire history of the chain. This is the simplest form that a blockchain could take and indeed it allows us to agree on a shared history.
+
+---v
+
+### Genesis Block
+
+![Beginning of blockchain. Genesis block's "parent" is 0x0000](./img/hash-linked-genesis.svg)
+
+Notes:
+
+The first block in the chain is typically called a the "Genesis block" named after the first book in the judaeo-christian mythology - The beginning of our shared story. The parent hash is chosen to be some specific value. Typically we use the all-zero hash, although any fixed widely agreed-upon value would also do.
+
+---
+
+## State Machines (Again)
+
+A state machine defines:
+
+<pba-flex center>
+
+- Set of valid states
+- Rules for transitioning between states
+
+</pba-flex>
+
+<img style="width: 900px;" src="./img/state-machine/state-machine-general.svg" />
+
+<!-- FIXME - do you want to use shared img assets? Breaks the module specific intention of folders per mod... @joshy -Nuke
+Let's see how the hybrid contracts/blockchain thing goes first; then sort this. -Joshy
+-->
+
+---v
+
+### Blockchain meet State Machine
+
+![Blockchain where payload is state machine transition](./img/blockchain-meet-state-machine.svg)
+
+Notes:
+
+The simplest way to join a blockchain to a state machine is to to make the blockchain's payload a state machine transition.
+By doing so, we effectively track the history of a state machine in a cryptographically guaranteed way.
+
+---v
+
+### Where do the States Live?
+
+Somewhere else!
+
+![Blockchain with state shown outside of the blocks](./img/blockchain-with-state-outside.svg)
+
+Notes:
+
+There is a state associated with each block. But typically the state is NOT stored in the block. This state information is redundant because it can always be obtained by just re-executing the history of the transitions.
+It is possible to store the state in the blocks, but the redundancy is undesirable. It wastes disk space for anyone who wants to store the history of the chain. Storing the state in the block is not done by any moderately popular blockchain today.
+If you _want_ to store the states, you are welcome to do so. Software that does this is known as an Archive node or an indexer. But it is stored separately from the block
+...Pause...
+One more time to make sure it sinks in: The state is NOT in the block.
+
+---v
+
+### State Roots
+
+A cryptographic anchor to the state
+
+![State roots cryptographically tie the block to its state](./img/blockchain-with-state-roots.svg)
+
+Notes:
+
+Some data redundancy can be good to help avoid corruption etc. It is common for a block to contain a cryptographic fingerprint of
+the state. This is known as a state root. You think of it as a hash of the state. In practice, the state is typically built into a Merkle tree like structure and the tree root is included. Not all blockchains do this. Notably bitcoin doesn't. But most do. We'll go into details about exactly how this state root is calculated for Substrate in the next two modules, but for now we just consider the state root to be some kind of cryptographic fingerprint.
+
+---
+
+## Forks
+
+![forks represent alternate histories](./img/forks.svg)
+
+A state machine can have different possible histories. These are called forks.
+
+Notes:
+
+You can think of them like alternate realities. We need to decide which of the many possible forks is ultimately the "real" one. This is the core job of consensus and we will talk about it in two upcoming lessons in this module.
+
+---v
+
+## Invalid Transitions
+
+![Not all transitions are valid. Forks containing them need not be considered](./img/forks-some-invalid.svg)
+
+Notes:
+
+Before we even get to hardcore consensus, we can rule out _some_ possibilities based on the state machine itself
+
+---
+
+## Realistic Blockchain Structure
+
+<img width="600px" src="./img/header-body.svg" />
+
+- Header: Summary of minimal important information about this block
+- Body: A batched list of state transitions
+
+Notes:
+
+The header is a minimal amount of information. In some ways it is like metadata.
+The body contains the real "payload". It is almost always a batch of state transitions.
+There are many name aliases for what is included in the body:
+
+- Transitions
+- Transactions
+- Extrinsics
+
+---v
+
+## Blocks in Substrate
+
+```rust
+/// Abstraction over a Substrate block.
+pub struct Block<Header, Extrinsic: MaybeSerialize> {
+	/// The block header.
+	pub header: Header,
+	/// The accompanying extrinsics.
+	pub extrinsics: Vec<Extrinsic>,
+}
+```
+
+Notes:
+
+This example is from Substrate and as such it strives to be a general and flexible format, we will cover Substrate in more depth in the next module. This is representative of nearly all real-world blockchains
+
+---
+
+## Headers
+
+Exact content varies per blockchain.
+Always contains the parent hash.
+Headers are the _actual_ hash-linked list, not entire blocks.
+
+Notes:
+
+The parent hash links blocks together (cryptographically linked list). The other info is handy for other infrastructure and applications (more on that later).
+
+---v
+
+## Header Examples
+
+<pba-cols>
+<pba-col>
+
+<pba-flex center>
+
+**Bitcoin**
+
+</pba-flex>
+
+- Previous Hash
+- Time
+- Version
+- Tx Merkle Root
+- N_Bits
+- Nonce
+
+</pba-col>
+<pba-col>
+
+<pba-flex center>
+
+**Ethereum (PoW)**
+
+</pba-flex>
+
+- Parent Hash
+- Time
+- Block Number
+- Transactions root
+- State Root
+- Difficulty
+- Nonce
+- ... even more
+
+</pba-col>
+</pba-cols>
+
+---v
+
+## Substrate Header
+
+- Parent hash
+- Block Number (aka height)
+- State root
+- Extrinsics root
+- Consensus Digest
+
+Notes:
+
+Extrinsics root is a crypto link to the body of the block. It is very similar to the state root.
+Consensus Digest is information necessary for the consensus algorithm to determine a block's validity. It varies widely with the consensus algorithm used and we will discuss it in two upcoming lectures.
+
+---v
+
+## Substrate Header (Full Picture)
+
+![Header is cryptographically linked to parent, body, and state](./img/headers-link-state-body.svg)
+
+---
+
+## Extrinsics
+
+Packets from the outside world with _zero_ or more signatures attached.
+
+- Function calls to the STF
+- Some functions require signatures (e.g., transfer some tokens)
+- Others don't, but usually have some validation means
+
+---
+
+## DAGS
+
+**Directed Acyclic Graphs**
+
+<img style="margin-left: 215px;" src="./img/forks.svg" />
+
+Notes:
+
+In math there is a notion of a Directed Acyclic Graph.
+Define graph, than directed, than acyclic.
+Blockchains are examples of DAGs.
+Actually blockchains are a specific kind of a DAG called a tree.
+Sometimes you will hear me talk about the "block tree" which really means all the histories of the chain.
+
+But there are more kinds of DAGs than just trees.
+Consider if someone authored a block that looks like this.
+
+CLICK
+
+---v
+
+## DAGS
+
+**Directed Acyclic Graphs**
+
+![forks represent alternate histories](./img/dag.svg)
+
+Notes:
+
+What if a block could have more than one parent!?
+It could allow parallelization and increased throughput!
+But it also leads to problems.
+What if there are conflicting transactions in the two parent histories?
+How do you even know if there are conflicting histories?
+
+---
+
+<!-- FIXME
+
+This might be a good place to split the lesson.
+The part before this is about a data structure.
+The part after this is about a P2P network of nodes that track this data structure.
+-->
+
+## Blockchain 💒 P2P Networks
+
+<img style="width: 900px;" src="./img/blockchain_p2p.svg" />
+
+Notes:
+
+So hopefully some parts of this figure look familiar.
+What do you see here?
+
+- Diverse servers.
+- In a p2p network.
+- Each with their own view of the blockchain.
+
+---v
+
+## Nodes
+
+Software agents that participate in blockchain network.<br/>
+May perform these jobs:
+
+<pba-cols>
+<pba-col>
+<pba-flex center>
+
+- Gossip blocks
+- Execute and Validate blocks
+- Store blocks
+- Store states
+- Gossip transactions
+
+</pba-flex>
+</pba-col>
+<pba-col>
+<pba-flex center>
+
+- Maintain a transaction pool
+- Author blocks
+- Store block headers
+- Answer user requests for data (RPC)
+
+</pba-flex>
+</pba-col>
+</pba-cols>
+Notes:
+
+Many nodes only perform a subset of these tasks
+
+---v
+
+## Types of Nodes
+
+<pba-flex center>
+
+- Full Nodes
+- Light Nodes (aka Light clients)
+- Authoring nodes
+- Archive nodes
+- RPC nodes
+
+</pba-flex>
+
+---
+
+## Blockspace
+
+A resource created, and often sold, by a decentralized blockchain network.
+
+<img style="width: 700px;" src="./img/Web2Web3Stacks.png" />
+
+#### Learn more:
+
+- Article: https://a16zcrypto.com/blockspace-explained/
+- Article: https://www.rob.tech/blog/polkadot-blockspace-over-blockchains/
+- Podcast: https://youtu.be/jezH_7qEk50?t=5330
+
+Notes:
+
+A Blockchain network is a replacement for a centralized server.
+It sells a product to application deployers.
+The state machine is the application layer, and the blockchain is the server replacement.
+In the same way that applications pay data centers for server resources like cpu time, disk space, bandwidth etc.
+Applications (maybe via their developers or users) pay for the privilege of having their history attested to and their state tracked by a trustless unstoppable consensus layer.
+
+---v
+
+## Transaction Pool
+
+- Contains transactions that are not yet in blocks.
+- Constantly prioritizing and re-prioritizing transactions.
+- Operates as a blockspace market.
+
+Notes:
+
+Sometimes known as mempool (thanks bitcoin 🙄)
+Authoring nodes determine the order of upcoming transactions. In some sense they can see the future.
+
+Foreshadow forks where players disagree on the rules
+History: dao fork bch fork
+foreshadow consensus: arbitrary additional constraints for a block to be valid
+
+---
+
+# Let's #BUIDL It
diff --git a/content/3-Blockchain/4-Accounts_and_UTXOs-slides.md b/content/3-Blockchain/4-Accounts_and_UTXOs-slides.md
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+---
+title: Accounting Models & User Abstractions in Blockchains
+---
+
+# Accounting Models & User Abstractions in Blockchains
+
+---
+
+## Multi-User State Machines
+
+- We can model simple state machines.
+- But now we want a multi-user state machine where users can interact.
+
+Notes:
+
+We have a lot of practice modeling simple state machines like a single audio amplifier
+We can generalize this a little bit by giving every user their own machine. Their own amplifier.
+But we can get even more rich, by having cross over effects between the amplifiers.
+Imagine you plug the output of your amp into the input of my amp
+
+---
+
+## Multiple Models
+
+- Unspent Transaction Output
+- Accounts
+
+Notes:
+
+There are two popular methods for doing this in blockchain.
+There amy very well be more viable way to do it as well.
+For example I've heard of the actor model.
+We will focus on these two because they are by far the most common.
+
+---
+
+## UTXO Model
+
+![State User Model](img/utxo_state_1.svg)
+
+---
+
+## UTXO Model
+
+![State User Model](img/utxo_state_2.svg)
+
+---
+
+## How to represent Joshy and Andrew?
+
+![Representation](img/utxo_state_1.svg)
+
+---
+
+## User Representation
+
+![User Representation](img/utxo_state_3.svg)
+
+---
+
+## Addresses
+
+How to send from Joshy to Andrew? What do you need?
+
+![Transfer](img/utxo_state_4.svg)
+
+Notes:
+
+We can use cryptographic identifiers. Perhaps a public key.
+In practice it os often a hash of a public key.
+
+---
+
+## Inputs
+
+What if we want to spend this?
+
+![Spend](img/utxo_state_5.svg)
+
+Notes:
+
+Why do we say spend here and not modify?
+
+---
+
+## Input
+
+![Input](img/utxo_transaction_1.svg)
+
+---
+
+## Transaction
+
+![Transaction](img/utxo_transaction_2.svg)
+
+Notes:
+
+Why do we not send all of the 70 to Andrew?
+
+---
+
+## How to verify this state change is valid?
+
+- We can actually spend this thing signature verification!
+- Sum of the inputs is >= sum of the outputs
+- No coins are worth 0
+- Has this already been spent before?
+
+Notes:
+
+Which did I forget??
+
+---
+
+## Our new state
+
+![New State](img/utxo_state_6.svg)
+
+---
+
+## How do we generalize beyond money?
+
+![Generalization](img/utxo_state_7.svg)
+
+---
+
+## How do we generalize beyond money?
+
+![Generalization](img/utxo_state_8.svg)
+
+Notes:
+
+How are we going to verify now that the state transition is valid?
+
+---
+
+## Transaction
+
+![Transaction](img/utxo_transaction_3.svg)
+
+---
+
+## Transaction
+
+![Transaction](img/utxo_transaction_4.svg)
+
+---
+
+## Is this a good model? Why or why not? Let's discuss
+
+- Scalability
+- Privacy
+- General Computation
+
+---
+
+## Is there a different way?
+
+![Different Way](img/utxo_state_7.svg)
+
+Notes:
+
+Now ease them to the solution of Accounts
+
+---
+
+## Accounts
+
+![Accounts](img/accounts_state_1.svg)
+
+Notes:
+
+Now ease them to the solution of Accounts
+
+---
+
+## State Transition Accounts
+
+![State Transition Accounts](img/accounts_transaction_1.svg)
+
+---
+
+## State Transition Accounts
+
+![State Transition Accounts](img/accounts_transaction_2.svg)
+
+---
+
+## How do we verify and handle this transaction?
+
+- Verify enough funds are in Joshy's account
+- Verify this amount + Andrews amount don't exceed the max value
+- Check the nonce of the transaction
+- Do the actual computation of output values
+
+Notes:
+
+Did I forget any?
+
+---
+
+## State Transition Accounts
+
+![State Transition Accounts](img/accounts_transaction_3.svg)
+
+---
+
+## What did we do differently in Accounts vs UTXO model?
+
+Notes:
+
+Verify as opposed to determining the outcome. Not submitting output state in transaction
+
+---
+
+## Account Arbitrary Data
+
+![Account Arbitrary Data](img/accounts_state_2.svg)
+
+---
+
+## Is this a good model? Why or why not? Lets Discuss
+
+- Scalability
+- Privacy
+- General Computation
+
+Notes:
+
+Parallelization? Storage space, privacy solutions?
diff --git a/content/3-Blockchain/5-Consensus-Authoring-slides.md b/content/3-Blockchain/5-Consensus-Authoring-slides.md
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+---
+title: Consensus Authoring
+description: Authoring restrictions related to consensus
+duration: 30min
+---
+
+# Consensus: Authoring
+
+---v
+
+### Consensus is...
+
+...a decision making process that strives to achieve acceptance of a decision by all participants.
+
+---v
+
+## Blockchain Consensus is...
+
+...a decentralized consensus system to reach agreement over a shared history of a state machine.
+
+---v
+
+## Blockspace
+
+![Blockspace machine](./img/blockspace-machine.svg)
+
+Blockchain consensus systems produce a resource called blockspace.
+
+Strong incentive alignments and strong guarantees make for high quality blockspace.
+
+Notes:
+
+As we discussed blockspace represents the right to contribute to the shared history. This is a valuable resource that is offered to users as a product. We will discuss the selling of this resource in a later lecture on allocation and fees. The consensus system used plays a large role in determining the quality of the blockspace.
+
+---
+
+## Forks Review
+
+<img style="width: 500px" src="./img/forks-some-invalid.svg" />
+
+There are going to be forks. We need to decide which one is the real one.
+
+We can rule some forks out to reduce the problem space. Then we are left to decide which is canonical.
+
+Notes:
+
+Forks represent alternate courses that history could take. They arise every time there is a difference of opinion.
+
+You can think of them at a social level. Court cases, arguments, wars. Ideally we can resolve them peacefully
+
+You can think of them at a very low physics-y level. Every time an electron encounters a potential barrier it either reflects of tunnels. When consensus is high-quality, the result is as objective as the outcome of a physical process.
+
+---
+
+## Five Aspects of Consensus
+
+<pba-flex center>
+
+- State machine validity
+- Arbitrary / Political validity
+- Authorship throttling
+- Fork choice heuristic
+- Finality
+
+</pba-flex>
+
+Notes:
+
+The first two aspects are relatively simple and I'll discuss them briefly right now. The third and fourth are the main topic of this lecture. The fifth is covered in detail two lectures from now in great detail.
+
+The first three aspects are about ruling possibilities out. The fourth and fifth are about deciding between any remaining possibilities.
+
+---v
+
+## State Machine Validity
+
+Some forks can be ruled out simply because they contain invalid state transitions.
+
+![Invalid state transition](./img/invalid-state-transition.svg)
+
+Notes:
+
+Example spending more money than you have. Noting your present location such that you would have traveled faster than speed of light since last record. Calling a smart contract with invalid parameters.
+
+---v
+
+## Arbitrary / Political Validity
+
+Similar to state machine validity.<br/>
+Examples:
+
+<pba-flex>
+
+- Blocks that are too big
+- Blocks that have "hack" transactions
+- Empty blocks
+- Block with Even state roots
+
+</pba-flex>
+
+![Invalid state transition](./img/politically-invalid-state-transition.svg)
+
+Notes:
+
+This concept is similar to the previous slide. In some sense this is even the same. This allows us to rule out some forks just for not having properties that we like. Or for having properties that we dislike.
+
+Not everyone will agree on these properties ad that leads to long-term network splits.
+
+---
+
+## Authorship Throttling
+
+Real-world blockchains impose additional restrictions on who can author blocks. Why?
+
+![Unthrottled authoring leads to fork chaos](./img/fork-chaos.svg)
+
+Notes:
+
+These blockchains are supposed to be permissionless right? At least many of them are. Some are even very hardcore about that goal. So why would we want to restrict the authoring.
+Answer: So the nodes are not overwhelmed. Unthrottled authoring leads to fork chaos. If anyone authored at any moment there would be blocks raining down left and right. It would be impossible to check them all. It would be DOS central. So we need some organization / order to the process.
+
+---v
+
+## Leader Election
+
+We need to elect a small set (or ideally a single) entity who are allowed to author next.
+
+In pre-blockchain consensus this was called the "leader", and still often is.
+
+Notes:
+
+By electing a few leaders, we are able to throttle the authoring.
+
+---v
+
+## Liveness
+
+The ability of the system to keep authoring new blocks
+
+Notes:
+
+Before we go on, I want to introduce the concept of liveness. It is a desireable property that consensus systems want to have. Systems that have better liveness properties offer higher quality blockspace. Chains without liveness guarantees become stalled.
+
+---
+
+## Proof of Work
+
+Satoshi's Big invention.
+
+Solve a Pre-image search - earn the right to author.
+
+---v
+
+## Proof of Work: Pros
+
+<pba-flex center>
+
+- Permissionless (or so we thought)
+- Requires an external scarce resource: Energy
+- Blind: Nobody knows the next author until the moment they publish their block
+- Expensive to author competing forks - Clear incentive
+
+</pba-flex>
+
+Notes:
+
+On the surface one big strength of PoW is that anyone can spin up a node and join at any time without anyone's permission. This is clearly how it was described in the whitepaper. In practice, many systems now have such a high hashrate that your home computer is useless. It is now permissioned by who can afford and acquire the right hardware.
+
+The reliance on an external resource is good in some sense because it is an objective measure of the market's valuation of the consensus system. This helps valuate the blockspace.
+
+The blindness is a good property because it makes it impossible to perform a targeted attack (DOS or physical) on the next leader to stall the network.
+
+Some attacks rely on the leader authoring two competing forks and gossiping them to different parts of the network. With PoW, it costs energy for every block you author. This makes it expensive to perform such attacks. This provides an economic incentive for authors to only author blocks on the "correct" fork.
+
+---v
+
+## Proof of Work: Cons
+
+<pba-flex center>
+
+- Energy Intensive
+- Irregular block time
+- Not so permissionless
+
+</pba-flex>
+
+Notes:
+
+Energy consumption is more often considered a negative property. Sometimes called proof of _waste_. I won't go that far, but in a world where climate change is a reality, it is certainly not ideal to be spending so much energy if we can get away with far less.
+
+Worth noting that some PoW schemes (eg Monero's) strive to minimize the energy impact by choosing algorithms that are "asic resistant". While these are decidedly better than Bitcoin's, they do not fundamentally solve the problem. Just alleviate it somewhat in practice.
+
+Secondly, the block time is only probabilistically known. When waiting for block to be authored, there are sometimes spurts of blocks followed by long stretches without any.
+
+Although it seems permissionless on its face, in practice, to be a bitcoin miner you need to have expensive specialized hardware.
+
+---v
+
+## Why Author at All?
+
+- Altruism - You feel good about making the world a better place
+- Your Transitions - Because you want to get your own transitions in
+- Explicit incentives - Eg block reward
+
+Notes:
+
+If it costs energy to author blocks, why would anyone want to author to begin with?
+
+Mining only when you want to get your transaction in seems like a good idea to me. People who don't want to self author, can pay other a fee to do it for them. This is the purpose of transaction fees. Most chains have transaction fees specified in the transactions themselves which go to the author
+
+Some networks also add an explicit incentives such as a 50BTC reward per block.
+
+---
+
+## Proof of Authority
+
+Traditional class of solutions.
+
+Divide time into slots.
+
+Certain identities are allowed to author in each slot.
+
+Prove your identity with a signature.
+
+---v
+
+## Proof of Authority: Pros
+
+<pba-flex center>
+
+- Low energy consumption
+- Stable block time
+
+</pba-flex>
+
+Notes:
+
+Stable block time is a property of high-quality block space. It allows applications that consume the blockspace to have expectations about throughput. In PoW you will occasionally have long periods without a block which can negatively affect applications.
+
+---v
+
+## Proof of Authority: Cons
+
+<pba-flex center>
+
+- Permissioned
+- No external resource to aid valuation
+- Incentives for honesty are not always clear
+
+</pba-flex>
+
+Notes:
+
+Does anything bad happen if they misbehave? Not inherently. We will need an incentive for that.
+
+---
+
+# Some PoA Schemes
+
+Reminder: PoA is a family of leader election schemes
+
+---v
+
+## Aura
+
+The simple one.
+
+Everyone takes turns in order.
+
+```rust
+authority(slot) = authorities[slot % authorities.len()];
+```
+
+Notes:
+
+Pros:
+
+- Simple
+- Single leader elected in each slot
+
+Cons:
+
+- Not blind - welcome targeted attacks
+
+---v
+
+## Babe
+
+**B**lind **A**ssignment for **B**lockchain **E**xtension
+
+- In each slot, compute a VRF output.
+- If it is below a threshold, you are eligible to author.
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- If eligible, author a block showing VRF proof
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+- If NOT eligible, do nothing
+
+<!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+Pros:
+
+- No fixed order helps alleviate DOS attacks
+
+Cons:
+
+- Some slots have no authors - There is a workaround for this
+- Other slots have multiple authors which leads to forks. There is no workaround for this
+
+---v
+
+## Sassafras
+
+<pba-cols>
+<pba-col>
+<img style="width: 500px" src="./img/Sassafras-albidum.jpg" />
+</pba-col>
+<pba-col>
+
+Single blind VRF-based leader election
+
+🙈TBH, IDK how it works internally. <!-- .element: class="fragment" data-fragment-index="2" -->
+
+But Jeff does! <!-- .element: class="fragment" data-fragment-index="3" -->
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+- Has most of the Pros of PoW (except for the external resource based valuation hint)
+- Has all the Pros of PoA
+
+<!-- TODO style: fix rounded img css issue here -->
+
+---v
+
+## Sassafras Analogy
+
+<pba-cols>
+<pba-col>
+<img src="./img/jeff.jpeg" />
+</pba-col>
+<pba-col>
+
+> Sassafras is kinda cards against humanity
+
+</pba-col>
+</pba-cols>
+---v
+
+## Sassafras Analogy
+
+<img width="400px" style="float: left; padding: 1px;" src="./img/caa_black.png" />
+<img width="400px" style="float: left; padding: 1px;" src="./img/caa_white_1.png" />
+<!-- .element: class="fragment" data-fragment-index="2" -->
+<img width="400px" style="float: left; padding: 1px;" src="./img/caa_white_2.png" />
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+---v
+
+## Sassafras Analogy
+
+<pba-cols>
+<pba-col>
+<img src="./img/jeff.jpeg" />
+</pba-col>
+<pba-col>
+<blockquote style="font-size: 80%">Ring VRF outputs are "cards".  You anonymously "play" the best aka smallest cards in your hand.</blockquote>
+<!-- .element: class="fragment" data-fragment-index="2" -->
+<blockquote style="font-size: 80%">Those cards are sorted, not by funniness since they're just numbers, but by the number.</blockquote>
+<!-- .element: class="fragment" data-fragment-index="3" -->
+<blockquote style="font-size: 80%">The order in which they wind up is the block production order.</blockquote>
+<!-- .element: class="fragment" data-fragment-index="4" -->
+<blockquote style="font-size: 80%">You claim the ones that're yours by doing a non-ring VRF with identical outputs.</blockquote>
+<!-- .element: class="fragment" data-fragment-index="5" -->
+</pba-col>
+</pba-cols>
+
+---v
+
+# Proof of Stake
+
+It's just PoA in disguise 🤯
+
+Uses an economic staking game to select the authorities.
+
+Restores the permissionlessness to at least PoW levels.
+
+Restores clear economic incentives
+
+Notes:
+
+There is an economic game called staking as part of the state machine that allows selecting the authorities who will participate in the PoA scheme. Actually there isn't just _one_ way to do it, there are many. Kian will talk a lot more about this and about the way it is done in Polkadot later. I'll just give the flavor now.
+
+The basic idea is that anyone can lock up some tokens on chain (in the state machine). The participants with the most tokens staked are elected as the authorities. There is a state transition that allows reporting authority misbehavior (eg authoring competing blocks at the same height), and the authority loses their tokens. There are often block rewards too like PoW.
+
+---v
+
+## 💒 Consensus 🪢 State Machine
+
+- Loose coupling between consensus and state machine is common
+- Eg Block rewards, slashing, authority election
+- In PoW there is a difficulty adjustment algorithm
+
+In Substrate there is a concept of a **Runtime API** - Consensus can read information from state machine.
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+So far I've presented consensus as orthogonal to the state machine. This is mostly true. But in practice it is extremely common for there to be some loose coupling. We already saw an example when we talked about block rewards. The consensus authors are rewarded with tokens (in the state machine) for authoring blocks. Now we see that they can have tokens slashed (in state machine) for breaking consensus protocol. And we see that even the very authorities can be elected in the state machine.
+
+---
+
+# Fork Choice Heuristics
+
+Each node's preference for which fork is best
+
+<pba-flex center>
+
+- Longest chain rule
+- Most accumulated work
+- Most blocks authored by Alice
+- Most total transactions (or most gas)
+
+<img style="width: 500px" src="./img/reorgs-1.svg" />
+
+</pba-flex>
+
+Notes:
+
+The fork choice allows you, as a network participant, to decide which fork you consider best for now. It is not binding. Your opinion can change as you see more blocks appear on the network
+
+---v
+
+## Reorganizations
+
+<img style="width: 500px" src="./img/reorgs-1.svg" />
+
+<img style="width: 500px" src="./img/reorgs-2.svg" /> <!-- .element: class="fragment" data-fragment-index="2" -->
+
+Dropped transactions re-enter tx pool and re-appear in new blocks shortly <!-- .element: class="fragment" data-fragment-index="3" -->
+
+Notes:
+
+Having seen more blocks appear, we now have a different opinion about what chain is best. This is known as a reorg. Re-orgs are nearly inevitable. There area ways to make sure they don't happen at all, but there are significant costs to preventing them entirely. Typically short reorgs are not a big problem, but deep reorgs are.
+
+You can experience this in a social way too.
+
+- Imagine that you are waiting for a colleague to submit a paper. You believe they have submitted it yesterday, but it turns out that they didn't submit it until today or won't submit it until tomorrow. Might be annoying, but not world shattering (usually)
+- Imagine that you believe the colleague submitted the paper months ago and the paper has been published. You have applied on a job having listed the publication
+
+---v
+
+## Double Spends
+
+<img style="width: 800px" src="./img/double-spend-1.svg" />
+
+Notes:
+
+The name comes from bitcoin, but the attack generalizes. It exploits the existence of forks. Attacker has to get two conflicting transactions into two forks. And convince a counterparty to believe one chain long enough to take an off-chain action before they see the reorg.
+
+---v
+
+## Double Spends
+
+<img style="width: 800px" src="./img/double-spend-2.svg" />
+
+---
+
+## Five Aspects of Consensus
+
+<pba-flex center>
+
+- State machine validity
+- Arbitrary / Political validity
+- Authorship throttling
+- Fork choice heuristic
+- Finality
+
+</pba-flex>
+
+Notes:
+
+We just discussed the first four aspects. Finality will be discussed in an upcoming lesson
diff --git a/content/3-Blockchain/6-Econ_and_Game_Theory_in_Blockchain-slides.md b/content/3-Blockchain/6-Econ_and_Game_Theory_in_Blockchain-slides.md
new file mode 100644
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--- /dev/null
+++ b/content/3-Blockchain/6-Econ_and_Game_Theory_in_Blockchain-slides.md
@@ -0,0 +1,2408 @@
+---
+title: Econ & Game Theory in Blockchain # Also update the h1 header on the first slide to the same name
+description: Blockchain applications of Econ & Game Theory
+duration: 60 minutes
+# PBA has a theme: "reveal-md/PBA-theme.css", alternatively, you can use a named default like "night" from this list: https://github.com/hakimel/reveal.js/tree/master/css/theme/source
+# Add custom css files for your slides here, comma separated:
+separator: "\r?\n---\r?\n"
+verticalSeparator: "\r?\n---v\r?\n"
+# Below can be any of these: https://revealjs.com/config/
+revealOptions:
+  transition: "none" # animation between slides = none/fade/slide/convex/concave/zoom
+  backgroundTransition: "fade" # background swap between slides = none/fade/slide/convex/concave/zoom
+  slideNumber: true
+  controls: true
+  progress: true
+---
+
+# **Econ & Game Theory in Blockchain**
+
+Notes:
+
+- Presenter Introduction
+- Timeline clarification (after mod 2 and 3)
+- Today we'll be going through a brand new lecture on Econ & Game Theory in Blockchain
+
+---
+
+# What's the goal?
+
+Notes:
+
+What's the goal of this lecture?
+---v
+
+## What's the goal?
+
+<pba-cols>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/Econ_Box_Open.svg" alt="Econ Box Open" />
+    </pba-col>
+    <pba-col>
+        <ul>
+            <li> Demand & Supply </li>
+            <li> Markets </li>
+            <li> Nash Equilibrium </li>
+            <li> Schelling Point </li>
+            <li> <strong>...</strong> </li>
+        </ul>
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+By now you all should be familiar with all the terms and techniques from the Economy and Game Theory module like the Demand & Supply or Nash equilibrium.
+
+---v
+
+## What's the goal?
+
+<pba-cols>
+    <pba-col>
+        <img style="width: 280px; margin-top: 190px" src="./img/econ-game-theory/Econ_Box_Closed.svg"
+            alt="Econ Box" />
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/Blockchain_Box_Open.svg" alt="Blockchain Box Open" />
+    </pba-col>
+    <pba-col>
+        <ul>
+            <li> Consensus </li>
+            <li> Protocol </li>
+            <li> Tokens </li>
+            <li> State Transition Functions </li>
+            <li> <strong>...</strong> </li>
+        </ul>
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+And you also just finished covering the basics of Blockchains so you all should be familiar with state transition functions as well as have some understanding of consensus protocols.
+
+---v
+
+## What's the goal?
+
+<img style="width: 800px; margin-top: 130px" src="./img/econ-game-theory/Econ_Handshake_Blockchain.svg"
+    alt="Econ and Blockchain Handshake" />
+
+Notes:
+
+Having all that in mind, the goal of this lecture is to combine the two and see how the economy and game theory can be applied to blockchain.
+To do that we'll provide some exemplary use-cases and case studies.
+
+---
+
+# Landscape
+
+Notes:
+
+But first let's start with a quick summary of how we'll be approaching to bridge the gap between the two modules.
+
+---v
+
+## Landscape
+
+<pba-cols>
+    <pba-col>
+        <ul>
+            <li> Systems as Games </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/game.svg" alt="Game Pad" />
+    </pba-col>
+
+Notes:
+
+Firstly, we'll be looking at various blockchain systems as isolated games.
+
+---v
+
+## Landscape
+
+<pba-cols>
+    <pba-col>
+        <ul>
+            <li> Systems as Games </li>
+            <li> Nodes/Miners/Validators as Players </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/player.svg" alt="Laptop user cheering" />
+    </pba-col>
+
+Notes:
+
+Participants in those games will be for instance the miners, like in the Bitcoin protocol, maybe the validators in the Polkadot protocol or just some users of your smart contract.
+
+---v
+
+## Landscape
+
+<pba-cols>
+    <pba-col>
+        <ul>
+            <li> Systems as Games </li>
+            <li> Nodes/Miners/Validators as Players </li>
+            <li> Protocols as Game Rules</li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 300px" src="./img/econ-game-theory/assumptions.drawio.svg" alt="Checklist with points" />
+    </pba-col>
+
+Notes:
+
+The protocol is essentially a set of rules that will define the game itself.
+The one we will be analyzing.
+
+---v
+
+## Landscape
+
+<pba-cols>
+    <pba-col>
+        <ul>
+            <li> Systems as Games </li>
+            <li> Nodes/Miners/Validators as Players </li>
+            <li> Protocols as Game Rules</li>
+            <li> Cryptocurrencies as Points </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 400px" src="./img/econ-game-theory/bitcoin.svg" alt="BTC symbol" />
+    </pba-col>
+
+Notes:
+
+And to properly analyze those games we need to have some value representation, which in our case will be usually cryptocurrencies.
+
+---v
+
+## Landscape
+
+<pba-cols>
+    <pba-col>
+        <ul>
+            <li> Systems as Games </li>
+            <li> Nodes/Miners/Validators as Players </li>
+            <li> Protocols as Game Rules</li>
+            <li> Cryptocurrencies as Points </li>
+            <li> Rewards & Punishments as Incentives</li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/gavel.svg" alt="Gavel Hammer" />
+    </pba-col>
+
+Notes:
+
+And finally we'll be having various reward and punishment schemes that will shape the incentives of the players.
+
+Now that we have all the elements defining our blockchain games we can look for further parallels.
+
+---v
+
+# Market Emergence
+
+Notes:
+
+And first let's take a look at something that hopefully very familiar: Markets
+
+---v
+
+## Market Emergence
+
+_"A market is a composition of systems, institutions, procedures, social relations or infrastructures whereby parties engage in exchange."_
+
+Notes:
+
+So a market is a composition of systems where ppl exchange stuff.
+This is the simplest way of putting it.
+
+And Markets are the cornerstone of our economy and they are everywhere which also means they are thoroughly studied.
+Which is very fortunate for us.
+
+Now let's look at something that might also be pretty familiar to many...
+
+---v
+
+## Market Emergence
+
+#### _Fee Market_
+
+<img style="width: 1200px" src="./img/econ-game-theory/fees.png"
+    alt="Chart of Bitcoin fees over time" />
+
+Notes:
+
+The fee market.
+That's a chart of the average transaction fees in the Bitcoin network over time.
+As you can see the price is constantly fluctuating.
+
+---v
+
+## Market Emergence
+
+#### _Fee Market_
+
+<pba-cols>
+    <pba-col>
+        <strong> Fees/Tips </strong>
+        <ul>
+            <li> Users bid with the fees </li>
+            <li> Miners select highest fee transactions </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/scales.svg" alt="Scales Icon" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Let's dive a bit deeper.
+So the users are bidding with how much they are willing to pay and miners are choosing the most lucrative transactions.
+If miners already included all the best transactions and there are not many new ones coming in they need to start accepting lower fees, so the price drops.
+But wait...?
+
+---v
+
+## Market Emergence
+
+#### _Fee Market_
+
+<pba-cols>
+    <pba-col>
+        <strong> What is the product? </strong>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/blockspace.drawio.png" alt="Blockspace in Polkadot" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+What is the actual product being exchanged here? When you have the crude oil market the goods being exchanged are clearly defined.
+It's crude oil barrels.
+What is actually being traded in here?
+
+Anyone has an idea what it might be?
+
+---v
+
+## Market Emergence
+
+#### _Fee Market_
+
+<pba-cols>
+    <pba-col>
+        <strong> What is the product? </strong>
+        <ul>
+            <li> What is being exchanged is the blockspace </li>
+            <li> Miners produce blockspace and effectively auction it to users </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/blockspace.drawio.png" alt="Blockspace in Polkadot" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+It's the BLOCKSPACE.
+Miners secure and produce blockspace and sell it in an auction to various users.
+Blockspace as a product is actually a pretty new way of thinking about blockchains so I highly suggest checking out the article linked in the notes.
+
+- https://polkadot.network/blog/blockspace-blockspace-ecosystems-how-polkadot-is-unlocking-the-full-potential-of-web3/
+
+---v
+
+## Market Emergence
+
+#### _Fee Market_
+
+<pba-cols>
+    <pba-col>
+        <strong> Market Equilibrium </strong>
+        <ul>
+            <li> The transactions that manage to get into the blocks have fees representative of the current market equilibrium </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/market_eq.drawio.svg" alt="Chart showing a market equilibrium" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+The price of blockspace is determined by the market equilibrium of supply and demand.
+Demand force is the users willing to transact and supply is the miners producing the blockspace.
+Transactions that are actually included represent the current equilibrium.
+
+---v
+
+## Market Emergence
+
+#### _Fee Market_
+
+<pba-cols>
+    <pba-col>
+        <strong> Supply & Demand </strong>
+        <ul>
+            <li> In extreme cases the demand can raise so much that the fees overwhelm the network </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/rising.svg" alt="Rising graph icon" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+We all know that the transaction fees can sometimes get outrageous.
+In cases where many users want to transact the demand can skyrocket.
+And what we see is the price equilibrium following suit.
+
+---v
+
+## Market Emergence
+
+#### _Fee Market_
+
+<pba-cols>
+    <pba-col>
+        <strong> Supply & Demand </strong>
+        <ul>
+            <li> In extreme cases the demand can raise so much that the fees overwhelm the network </li>
+            <li> Most economic markets can react to growing demand with increased supply, but that is not directly possible in most blockchains </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 300px" src="./img/econ-game-theory/goods.svg" alt="Stack of goods on a conveyor belt" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+And now let's think of what normal markets do.
+If our demand and price go extremely high the suppliers would have an incentive to produce more.
+But in blockchains that's not directly possible.
+More miners often don't mean more blockspace but MORE SECURE blockspace.
+That means a better quality blockspace.
+
+So the supply is often fixed and the demand is fluctuating.
+This is often the cause for the very volatile fee market.
+
+---v
+
+## Market Emergence
+
+#### _Fee Market_
+
+<pba-cols>
+    <pba-col>
+        <strong> Supply & Demand </strong>
+        <ul>
+            <li> In extreme cases the demand can raise so much that the fees overwhelm the network </li>
+            <li> Most economic markets can react to growing demand with increased supply, but that is not directly possible in most blockchains </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/kitty.png" alt="CryptoKitties Logo" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+And according to that theory some large blockchains actually tried implementing variable size blocks to react to the demand, but it's a pretty complex task and a big tradeoff.
+
+Some of you maybe recognize this image as the CryptoKitties game on Ethereum.
+It's a game where you can buy and breed digital cats.
+It was so popular that it actually clogged the Ethereum network and made normal transactions nearly unfeasible.
+And maybe now you have some additional insights into what actually happened there.
+
+=5 sec pause=
+
+---
+
+# Nash Equilibrium
+
+Notes:
+
+Now let's look at something a bit different that allows us to predict what users would do...
+a Nash Equilibrium.
+
+---v
+
+## Nash Equilibrium
+
+- Strategy from which no player wants to deviate
+- But what's the strategy for BTC mining?
+
+Notes:
+
+Nash Equilibrium is strategy from which no player wants to deviate.
+Pretty simple but what's the strategy for BTC mining? How can we leverage that knowledge?
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 500px" src="./img/econ-game-theory/honest_mining_meme.jpg" alt="Honest Mining Meme"/>
+
+Notes:
+
+And more importantly...
+being honestly is the answer, right?
+
+---v
+
+## Nash Equilibrium
+
+#### _Bitcoin Mining_
+
+<img style="width: 400px" src="./img/econ-game-theory/bitcoin.svg" alt="Bitcoin Logo" />
+
+Notes:
+
+Let's dive in and actually see what's the answer.
+What's the Nash Equilibrium of Bitcoin mining? Is it being honest or dishonest?
+
+---v
+
+## Nash Equilibrium
+
+<pba-cols>
+    <pba-col>
+        <strong>Assumptions:</strong>
+        <ul>
+            <li> Only 2 miners </li>
+            <li> Block reward = 2 </li>
+            <li> Difficulty scales with number of honest miners </li>
+            <li> Miners are rational actors </li>
+            <li> Dishonest miners do not cooperate </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/nash.drawio.svg" alt="Payoff Table" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Here we have a few assumptions, but the main ones are:
+
+- imagine we have only 2 miners
+- the block rewards is 2
+- miners can be honestly following the protocol or try to cheat and push invalid blocks (for instance one where they get 999 bitcoins)
+
+Let's figure out how many bitcoins each one of them will mine on average.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (1).svg" alt="Payoff Table" />
+
+Notes:
+
+If both miners are not mining honestly, none of them produce valid bitcoin blocks...
+then there are no ACTUAL bitcoins being mined.
+Remember that they don't cooperate but for instance try and push blocks with 9999 BTC in their account.
+So the reward is 0 for both.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (2).svg" alt="Payoff Table" />
+
+Notes:
+
+If both are working honestly and making valid blocks they have an equal chance to mine a block and reap the rewards.
+Rest of the nodes will accept those blocks but the two miners compete for the same resource so each one will get a single BTC on average (as the mining reward is 2).
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (3).svg" alt="Payoff Table" />
+
+Notes:
+
+If one of them is dishonest the other one can still keep working honestly and reap greater rewards as there is no competition.
+In that case the honest party gains 2 BTC.
+
+Now that we know who earns how many bitcoins in each scenario we need to shift out attention to another important force.
+Things like Twitter, Facebook or Bitcoin are often deemed as valuable because of their Network Effect.
+
+---v
+
+## Nash Equilibrium
+
+<br/>
+
+#### _Network Effect_
+
+_"The network effect is a business principle that illustrates the idea that when more people use a product or service,
+its value increases."_
+
+Notes:
+
+Generally the more ppl use some platform or believe in something the more valuable it is.
+It's a pretty simple concept but it's very important in the blockchain space.
+Bitcoin is precious to many because many people believe in it and mine it and exchange it.
+In blockchains if more people use your chain it's more valuable.
+
+---v
+
+## Nash Equilibrium
+
+<br/>
+
+#### _Network Effect_
+
+<br/>
+<strong>Assumptions revisited:</strong>
+<ul>
+    <li style="color: grey;"> Only 2 miners </li>
+    <li style="color: grey;"> Block reward = 2 </li>
+    <li style="color: grey;"> Difficulty scales linearly with number of honest miners </li>
+    <li style="color: grey;"> Miners are rational actors </li>
+    <li style="color: grey;"> Dishonest miners do not cooperate </li>
+    <li> Token price scales quadratically with the number of honest miners
+        <ul>
+            <li>1 honest miner -> 1$</li>
+            <li>2 honest miners -> 4$</li>
+    </li>
+</ul>
+
+Notes:
+
+Let's add this extra assumption into our model.
+If there are more miners securing the network the coins itself are more valuable.
+We will use a super simple model here where the price of a coin is a square of the number of miners.
+We will be investigating small systems so it is a good enough approximation.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (4).svg" alt="Payoff Table" />
+
+Notes:
+
+We can apply the changes by changing the evaluations of the miners coins.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (4b).svg" alt="Payoff Table" />
+
+Notes:
+
+If both miners honestly secure the network the coin price is 4 and in case of single honest miner the price is 1.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (5).svg" alt="Payoff Table" />
+
+Notes:
+
+Now we can actually focus on finding the Nash Equilibrium
+so let's used the simplest method.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (6).svg" alt="Payoff Table" />
+
+Notes:
+
+Assuming Miner B is honest the Miner A needs to choose between a payoff of 4 or 0.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (7).svg" alt="Payoff Table" />
+
+Notes:
+
+He ofc chooses 4 as it's higher.
+We temporarily mark it with the red circle.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (8).svg" alt="Payoff Table" />
+
+Notes:
+
+Same reasoning for B being dishonest and A chooses 2 over 0.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (9).svg" alt="Payoff Table" />
+
+Notes:
+
+Now we reverse the assumptions and assume A is honest and then B chooses between 4 and 0.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (10).svg" alt="Payoff Table" />
+
+Notes:
+
+Similarly as before he should choose 4 as it's higher.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (10b).svg" alt="Payoff Table" />
+
+Notes:
+
+And the last remaining options will result in the circled 2.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (12).svg" alt="Payoff Table" />
+
+Notes:
+
+Now the square with all the options circled is the Nash Equilibrium.
+In our case it seems to be being honest.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (13).svg" alt="Payoff Table" />
+
+Notes:
+
+Not a big surprise, and being dishonest lands you with zero coins so it was too be expected.
+But what if we change the assumptions a bit?
+
+---v
+
+## Nash Equilibrium
+
+<br/>
+What does it mean exactly to be <strong>dishonest</strong>?
+<br/>
+<br/>
+
+<div>
+    There are some mainstream rules (the protocol) and if an individual miner breaks them it seems like an isolated
+    mistake or an attempt at cheating.
+</div>
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+<br/>
+<br/>
+
+If multiple miners break the protocol <strong>in the same way</strong>, it can be seen as a new protocol deviating from
+the main one.
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+We were assuming that miners are either honest or dishonest, but what does being DISHONEST actually mean?
+
+=fragment=
+
+There are some mainstream rules (the protocol) and if an individual miner breaks them it seems like an isolated mistake or an attempt at cheating.
+This is what we were analyzing before.
+
+=fragment=
+
+But what if multiple miners break the protocol in the same way? It can be seen as a new protocol deviating from the main one.
+And that's what we'll be looking at next.
+The dishonest miners are cooperating.
+
+---v
+
+## Nash Equilibrium
+
+<pba-cols>
+    <pba-col>
+        <strong>Assumptions:</strong>
+        <ul>
+            <li> Only 2 miners </li>
+            <li> Block reward = 2 </li>
+            <li> Difficulty scales with number of honest miners </li>
+            <li> Token price scales quadratically wih the number of honest miners </li>
+            <li> Miners are rational actors </li>
+            <li> Decision between which protocol to follow </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/nash.drawio (14).svg" alt="Payoff Table" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Assumptions are pretty much the same but this time around the dishonest miners will cooperate.
+Effectively they will be following a different modified protocol.
+
+So we will no longer consider them dishonest but they simply follow a different set of rules.
+Now miners choose to mine for the bitcoin BTC protocol or the bitcoin cash BCH protocol.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (15).svg" alt="Payoff Table" />
+
+Notes:
+
+Let's quickly fill up this table with the same rules as before.
+Only this time of both miners follow BCH they ofc get the rewards in the BCH token.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (16).svg" alt="Payoff Table" />
+
+Notes:
+
+Just as before we take the extra step and apply the network effect.
+If both miners secure the network price is 4 and if only 1 the price is 1.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (17).svg" alt="Payoff Table" />
+
+Notes:
+
+Here we have all the prices adjusted.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (18).svg" alt="Payoff Table" />
+
+Notes:
+
+Now let's take a look at what happens if Miner B miners BTC.
+Miner A would prefer to also mine bitcoin.
+So they are both mining the same thing.
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (19).svg" alt="Payoff Table" />
+
+Notes:
+
+On the other hand if miner B mines BCH then it seems that Miner A prefers to mine BCH...
+
+---v
+
+## Nash Equilibrium
+
+<img style="width: 700px" src="./img/econ-game-theory/nash.drawio (20).svg" alt="Payoff Table" />
+
+Notes:
+
+And in fact what we have in here is two distinct Nash Equilibria!
+
+---v
+
+## Nash Equilibrium
+
+So is being honest the best strategy?
+
+<br/>
+<br/>
+
+Not always.
+If the majority of people are honest then honesty pays off.
+If the majority of people are _dishonest_ in the
+same way then be _dishonest_ with them.
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+<br/>
+<br/>
+<div>
+    In fact it was proven that in PoW following the majority is the true Nash Equilibrium no matter what
+    strategy/protocol they are using as long as it's consistent.
+</div>
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+So is being honest the best strategy?
+
+=fragment=
+
+Not always.
+If the majority of people are honest then honesty pays off.
+If the majority of people are _dishonest_ in the same way then be _dishonest_ with them.
+
+=fragment=
+
+In fact it was proven that in PoW following the majority is the true Nash Equilibrium no matter what strategy/protocol they are using as long as it's consistent.
+So Bitcoin mining is in fact a huge coordination game and this is why honesty AKA following the BTC protocol usually pays off.
+
+- More complex examples will be explored later in the forks lecture on Friday
+- Paper investigating PoW Nash Equilibrium and following the majority:
+  https://typeset.io/pdf/mining-pool-game-model-and-nash-equilibrium-analysis-for-pow-2lckzso542.pdf
+
+---
+
+# Schelling Point
+
+Notes:
+
+On that topic...
+What if we have multiple Nash Equilibria? Schelling point often comes to the rescue.
+
+---v
+
+## Schelling Point
+
+- A solution that people tend to choose (easiest to coordinate on)
+- Generally it is also a Nash Equilibrium
+- How in the world can it be useful in Blockchain?
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+So first a Schelling point is a strategy people tend to choose.
+It is generally a Nash Equilibrium
+
+=fragment=
+
+But how in the world is it useful to us in Blockchain?
+
+---v
+
+## Schelling Point
+
+#### Detective game
+
+<pba-cols>
+    <pba-col>
+        <ul>
+            <li> Two partners in crime</li>
+            <li> Detective interrogates them individually </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 700px" src="./img/econ-game-theory/detective.drawio.png" alt="Detective and 2 robbers" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+But before we can fully answer that let's explore a different game that can show you how Schelling points work.
+And I promise it will be applicable to Blockchain.
+
+So the story goes like that.
+We have to bank robbers and a detective.
+The detective interrogates he robbers and tries to make them confess or catch them lying.
+
+---v
+
+## Schelling Point
+
+#### _Detective game_
+
+<img style="width: 550px" src="./img/econ-game-theory/interrogation_small.drawio.svg" alt="Interrogation Game Payoff Table" />
+
+Notes:
+
+If any of the robbers spill the beans and tell the truth they both loose the game and go to prison.
+If both of them lie they get away with it.
+Seems super simple and it should be pretty straightforward that they both simply need to lie.
+
+Seems like a safe strategy, right? But remember than both of them witnessed the same real events of the robbery...
+
+---v
+
+## Schelling Point
+
+#### _Detective game_
+
+<img style="width: 700px" src="./img/econ-game-theory/interrogation_large.drawio.svg" alt="Interrogation Game Large Payoff Table" />
+
+Notes:
+
+But there are multiple lies they can construct.
+If they have inconsistent stories the detective will catch them.
+So now they need to coordinate on a specific lie and have all the details exactly the same or they are screwed.
+
+Contrast it with how easy it would be to just tell the truth.
+They both witnessed the truth so talking about it in a consistent way is trivial.
+
+---v
+
+## Schelling Point
+
+#### _Detective game_
+
+Truthful answers are one of the easiest strategies coordinate on, so they are the Schelling Points.
+
+Notes:
+
+That's why we can say that Truthful answers are one of the easiest strategies coordinate on, so they are the Schelling Points.
+The truth itself is a Schelling point.
+
+And this concept is vital to something in blockchain called...
+
+---v
+
+## Schelling Point
+
+#### _Oracles_
+
+Oracles are blockchain entities that provide information from the outside world to the blockchain.
+<br>
+<br>
+<img style="width: 700px" src="./img/econ-game-theory/oracles.drawio.svg" alt="Oracle getting information from real world" />
+
+Notes:
+
+Oracles.
+Firstly who in the room heard of oracles? Raise your hands.
+Oracles are super interesting because what they are trying to achieve is to provide information from the outside world to the blockchain.
+And that's a very very hard task.
+
+---v
+
+## Schelling Point
+
+#### _Oracles_
+
+Oracles are blockchain entities that provide information from the outside world to the blockchain.
+<br/>
+<br/>
+
+<div>
+    <strong>External Information Examples:</strong>
+    <ul>
+        <li> What's the temperature in Berkeley? </li>
+        <li> Who won the election? </li>
+        <li> What's the exchange rate of USD to BTC? </li>
+    </ul>
+</div>
+
+Notes:
+
+Some examples of the information they can provide are for instance what's the current temperature in Berkeley? Who won the election? What's the exchange rate of USD to BTC? and may others.
+
+Let's actually see how they might work is a slightly simplified version with the temperate example.
+
+---v
+
+## Schelling Point
+
+#### _Oracles_
+
+<br>
+<br>
+<img style="width: 900px" src="./img/econ-game-theory/temp1.drawio.svg" alt="Temperature Line" />
+
+Notes:
+
+So what's the temperature in Berkeley? Imagine you have a garden in Berkeley and you have on chain insurance that if the temperature is too high you get a payout.
+So you want to know the temperature in Berkeley.
+
+We know the answer lies somewhere on this axis.
+But what it is exactly?
+
+---v
+
+## Schelling Point
+
+#### _Oracles_
+
+<br>
+<br>
+<img style="width: 900px" src="./img/econ-game-theory/temp2.drawio.svg" alt="Temperature Line with Some Measurements" />
+
+Notes:
+
+We can ask some users to submit what they think the temperature is.
+Some of them will check it themselves, some will use weather apps and some will just guess.
+
+---v
+
+## Schelling Point
+
+#### _Oracles_
+
+<img style="width: 900px" src="./img/econ-game-theory/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
+
+Notes:
+
+What we are hoping for is that the cluster of votes you can see here will be around the actual temperature.
+The best approach would be to check the median.
+And why is that?
+
+---v
+
+## Schelling Point
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <ul>
+            <li> Honest participants are naturally coordinated </li>
+            <li> Attackers could try to coordinate and lie </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Honest voters are naturally coordinated.
+They will check the temperature and vote honestly all within some small margin of error.
+
+People that would lie to skew the results and would submit random values generally wouldn't cluster like the honest voters.
+To make a more dangerous attack they would need to strategically coordinate on a specific value and all lie about it.
+It's much harder to pull of than simply checking the temperature outside.
+
+Submitting the truth is the Schelling Point in here and it makes it easy to be honest.
+
+---v
+
+## Schelling Point
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        What to do with attackers?
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+But what if there are some attackers? What can we do about them?
+
+---v
+
+## Schelling Point
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        What to do with attackers?
+        <br/><br/>
+        If they go unpunished they can repeat the attack until successful
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+If we never punish them they can repeat the attack until they are successful.
+And that's not good.
+
+---v
+
+## Schelling Point
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        What to do with attackers?
+        <br/><br/>
+        If they go unpunished they can repeat the attack until successful
+        <br/><br/>
+        Or even worse, they can make a million fake identities and spam incorrect votes
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Or even worse, they can make a million fake identities and spam incorrect votes.
+So we need to punish them.
+
+But this is no longer a problem of a Schelling Point.
+The Schelling point did its job already.
+What we are talking about right now are...
+
+---
+
+# Incentives
+
+Notes:
+
+Incentives.
+Incentives are the next big topic we will be exploring.
+And they are vital to the blockchain space.
+
+---v
+
+## Incentives
+
+_"Something that encourages a person to do something."_
+<br/><br/>
+
+<div>In our case we want to shape incentives that motivate the users to submit honest values.</div>
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+Incentives are things that encourage people to do something.
+
+=fragment=
+
+In our case we want to shape incentives that motivate the users to submit honest values.
+We need to build out incentives in a way that shapes the expected behavior of the users to honesty.
+
+---v
+
+## Incentives
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        What to do with attackers?
+        <br/><br/>
+        If they go unpunished they can repeat the attack until successful
+        <br/><br/>
+        Or even worse, they can make a million fake identities and spam incorrect votes
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+So going back to our oracle problem how can we deal with attackers?
+
+---v
+
+## Incentives
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <div style="color: grey;">What to do with attackers?
+        <br/><br/>
+        If they go unpunished they can repeat the attack until successful
+        <br/><br/></div>
+        <strong>Or even worse, they can make a million fake identities and spam incorrect votes</strong>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/mask.svg" alt="Mask" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Let's focus on the second issue of fake identities.
+How can we prevent that?
+
+---v
+
+## Incentives
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <strong> Sybil Attacks </strong>
+        <br/><br/>
+        Common problem in blockchain.
+        <br/><br/>
+        <div>If deploying on a chain, an easy solution is to make users lock some funds.</div>
+        <!-- .element: class="fragment" data-fragment-index="1" -->
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/mask.svg" alt="Mask" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+An attack where a single entity creates multiple fake identities is called a sybil attack and is super common in blockchain.
+This is one of the things you always will need to ask yourself when you deploy things in blockchain.
+Is whatever I built safe from Sybil Attacks?
+
+=fragment=
+
+One easy ready solution that is often used is making users lock some funds.
+Only a user with some funds locked can vote.
+The strength of the vote is proportional to the stake so making a million accounts makes no sense.
+This is a very simple solution but it's not always applicable.
+
+---v
+
+## Incentives
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <div style="color: grey;">What to do with attackers? </div>
+        <br/>
+        <strong>If they go unpunished they can repeat the attack until successful</strong>
+        <br/><br/>
+        <div style="color: grey;">Or even worse, they can make a million fake identities and spam incorrect votes </div>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/gavel.svg" alt="Gavel Hammer" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Now let's go back to the first issue of unpunished attackers.
+How can we deal with them so they don't continue attacking us?
+
+---v
+
+## Incentives
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <strong> Punishments </strong>
+        <br/><br/>
+        We already laid out the foundation for punishments.
+        <br/><br/>
+        <div> Our solution for de-sybiling users makes them lock funds.
+        <br/><br/>
+        If such a user would vote incorrectly, we can slash their funds.
+        </div>
+        <!-- .element: class="fragment" data-fragment-index="1" -->
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/gavel.svg" alt="Gavel Hammer" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Interestingly we already laid out the foundation for the defense.
+Voters have some funds locked in the system so they have Skin in the game.
+
+=fragment=
+
+If they vote incorrectly we can slash their funds.
+This is a very common solution in blockchain.
+Incorrect in that case would be very far from the median.
+
+We have designed some protective incentives and now the system seems safe.
+
+---v
+
+## Incentives
+
+#### _Oracles_
+
+<br/>
+Did we forget about something?
+
+<br/><br/>
+
+**Why would anyone participate in this system?**
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+But did we forget about something? Anyone has any idea what it might be? What we are missing?
+
+=fragment=
+
+Why would anyone participate in this system? Why would anyone vote? Why would anyone lock their funds and take the risk?
+
+---v
+
+## Incentives
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <strong> Ghost Town </strong>
+        <br/><br/>
+        No user wants to participate
+        <br/><br/>
+        Getting information from the real world is an effort and they voters are doing the protocol a service
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/ghost.svg" alt="Ghost" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Getting information from the real world is an effort and they voters are doing the protocol a service.
+So we need to incentivize them to participate.
+We need a rewards scheme or otherwise the network will be a ghost town.
+
+---v
+
+## Incentives
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <strong> Reward Scheme </strong>
+        <br/><br/>
+        If users are doing the protocol a service they need to be rewarded
+        <br/><br/>
+        <div> One way to do it is to mint some token rewards for well-behaved voters </div>
+        <!-- .element: class="fragment" data-fragment-index="1" -->
+        <br/>
+        <div> Or distribute them from a previously acquired pool of rewards </div>
+        <!-- .element: class="fragment" data-fragment-index="2" -->
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/rewards.svg" alt="Hand receiving some money" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+If users are doing the protocol a service they need to be rewarded.
+
+=fragment=
+
+One way to do it is to mint some token rewards for well-behaved voters.
+
+=fragment=
+
+Or distribute them from a previously acquired pool of rewards.
+
+But what is crucial here the protocol is safe and dependable only if there is enough voters so the incentives need to be designed in a way that encourages participation.
+
+More precisely, incentives need to be roughly proportional to the value an attacker could gain by compromising the system.
+Low-stakes oracles don't need to have super aggressive incentives.
+
+---v
+
+## Incentives
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <strong> Reward Scheme Question</strong>
+        <br/><br/>
+        Can we distribute fixed value rewards for correct votes?
+        <br/>Correct vote = 10$ </div>
+        <br/><br/>
+        <div>
+         No.
+         We should base rewards on the size of the voter's stake.
+        </div>
+        <!-- .element: class="fragment" data-fragment-index="1" -->
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/questions.svg" alt="Raised Hands" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Let's do a quick question.
+Can we distribute fixed value rewards for correct votes? As an example each Correct vote = 10$
+
+=question time=
+
+=fragment=
+
+No.
+We should base rewards on the size of the voter's stake.
+Otherwise the system is vulnerable to sybil attacks.
+If you have a million fake identities you can vote a million times and get a million times the reward.
+So the reward should be proportional to the stake.
+
+---v
+
+## Incentives
+
+**In summary:**
+
+- Make it easy to honest users and hard for attackers
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Service to the protocol needs to be rewarded
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- Destructive or interfering actions need to be punished
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+- De-Sybiling the users can help defend against spam
+
+<!-- .element: class="fragment" data-fragment-index="4" -->
+
+Notes:
+
+Now let's summarize the main points.
+
+We need to make it easy for honest nodes and hard for attackers.
+The Schelling Point as the foundational part of the design handles that for us.
+
+=fragment=
+
+Service to the protocol needs to be rewarded.
+We need to incentivize participation to guarantee reliable results.
+
+=fragment=
+
+Destructive or interfering actions need to be punished.
+We need to disincentivize bad behavior.
+In our case we did the slashes.
+
+=fragment=
+
+De-Sybiling the users can help defend against spam.
+
+We we have all of that our systems should be properly incentivized and safe...
+and on that note what happens when the incentives are...
+
+---
+
+# Misaligned Incentives
+
+Notes:
+
+Misaligned.
+When they promote some behavior that is not good for the network.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<img style="width: 200px" src="./img/econ-game-theory/eth.svg" alt="Ethereum Logo" />
+
+Notes:
+
+Let's take a look at Ethereum.
+Ethereum is a blockchain that has a lot of smart contracts.
+And smart contracts are basically programs that run on the blockchain.
+They are stored on chain and they can be executed by anyone.
+For them to work a bunch of code needs to be deployed on the chain.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> State Storage Replication </strong>
+        <br/><br/>
+        Whenever we store something on chain (like a smart contract) it needs to be at least partially replicated among the nodes.
+        <br/><br/>
+        <div> Multiple nodes store the same data.</div>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/replication.drawio.svg" alt="Data Replication Diagram" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+And moreover whenever we store something on chain (like a smart contract) it needs to be at least partially replicated among the nodes.
+Thousands of nodes store the same data which is not super efficient.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> State Storage Replication Costs </strong>
+        <br/><br/>
+        Ethereum deals with the burden of replication by charging more gas for submitting bulky data.
+        <br/><br/>
+        All of that is ON TOP OF any computation gas costs.
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/storage_costs.drawio.svg" alt="Stacks of coins next to data blobs" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Ethereum attempts to deal with it by introducing scaling fees.
+The more data you put in the state the more you need to pay.
+And that's on top of any computation costs.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> State Storage Duration</strong>
+        <br/><br/>
+        This particular part of the state might be relevant for future state transitions so nodes cannot simply discard it.
+        <br/><br/>
+        <div> Full nodes need to keep ALL the data.</div>
+    </pba-col>
+    <pba-col>
+        <img style="width: 500px" src="./img/econ-game-theory/data_no_changes.drawio.svg" alt="Data same over time" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Note that once we put something in state it has to stay there pretty much indefinitely until we use it again.
+Because who knows, it might be relevant to some future state transitions.
+So nodes cannot simply discard it.
+
+Now let's explore an example.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> Meet Bob </strong>
+        <br/><br/>
+        Bob happily deploys his awesome smart contract in Ethereum.
+        He paid a hefty gas fee but so be it.
+        <br/><br/>
+    </pba-col>
+    <pba-col>
+        <img style="width: 600px" src="./img/econ-game-theory/smart_contract.drawio.svg" alt="Deploying a smart contract on chain" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+So let's meet Bob.
+Bob is a developer and he happily deploys his awesome smart contract in Ethereum.
+He paid a hefty gas fee but so be it.
+His code was added to the state and now many nodes hold a copy of it.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> The Problem </strong>
+        <br/><br/>
+        Bob decided to become a musician or just no longer likes programming.
+        <br/><br/>
+        He doesn't care about his smart contract anymore.
+    </pba-col>
+    <pba-col>
+        <img style="width: 600px" src="./img/econ-game-theory/smart_contract_deployed.drawio.svg" alt="Smart contract deployed on chain" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+But imagine that one day Bob decides to become a musician or he just no longer likes programming.
+He doesn't care about his smart contract anymore.
+But the chain doesn't know about it.
+His code still lives in the state and has to be continuously replicated and maintained.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> The Problem Made Worse </strong>
+        <br/><br/>
+        Many others like Bob follow suit.
+        <br/><br/>
+        Some of them continue developing but, <strong>why bother</strong> removing old data? They already paid for it.
+    </pba-col>
+    <pba-col>
+        <img style="width: 600px" src="./img/econ-game-theory/smart_contract_many.drawio.svg" alt="Many smart contracts deployed on chain" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Now imagine there are hundreds of people like Bob.
+Some of them even continue developing but, WHY BOTHER removing old data? They already paid for it.
+And some of them just don't care anymore.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> "Why Bother?" </strong>
+        <br/><br/>
+        Getting data on chain is expensive, but there is no incentive to clean it up.
+        <br/><br/>
+        This is a core misalignment of incentives that lead to Ethereum state size growing out of control.
+    </pba-col>
+    <pba-col>
+        <img style="width: 600px" src="./img/econ-game-theory/smart_contract_many.drawio.svg" alt="Many smart contracts deployed on chain" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+We need to focus on this "why bother" part.
+This is a core example of a misalignment of incentives that lead to Ethereum state size growing out of control.
+
+Getting the data to state is indeed expensive but once we do...
+why clean it? There is no incentive to do so.
+So the chain was getting overwhelmed in junk.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> The Goal </strong>
+        <br/><br/>
+        Design new protocol rules that shape the behavior of the users in a way that they start cleaning up the state.
+    </pba-col>
+    <pba-col>
+        <img style="width: 600px" src="./img/econ-game-theory/smart_contract_clean.drawio.svg" alt="Cleaned smart contracts on chain" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+So what can we do about it? What's the goal? We need to design new protocol rules that shape the behavior of the users in a way that they start cleaning up the state.
+Hopefully without any side effects.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> The Solution </strong>
+        <br/><br/>
+        State Storage Gas Refunds
+        <br/><br/>
+        Pay a hefty fee when deploying data to state, but get some of it refunded when removing it.
+    </pba-col>
+    <pba-col>
+        <img style="width: 600px" src="./img/econ-game-theory/smart_contract_burn.drawio.svg" alt="Burning a smart contract" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+One of the proposed solutions was the introduction of a Gas Refund.
+You pay a hefty fee when deploying data to state, but get some of it refunded when removing it.
+So now there is an incentive to clean up the state.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<br/><br/>
+<strong>behavior Before</strong>
+
+<img style="width: 900px" src="./img/econ-game-theory/developer_musician.drawio.svg" alt="Developer becoming a musician" />
+
+Notes:
+
+So what we had originally is Bob paid for his smart contract and then simply went away to play a guitar.
+
+---v
+
+## Misaligned Incentives
+
+#### _Ethereum State Storage Issue_
+
+<br/><br/>
+<strong>behavior After</strong>
+
+<img style="width: 900px" src="./img/econ-game-theory/developer_musician2.drawio.svg" alt="Developer removing his contract and becoming a musician" />
+
+Notes:
+
+Afterwards Bob deploys his contract in the same way but before running of to play a guitar he removes it from the state and gets some of the gas back.
+He likes the extra money so he has an incentive to clean.
+In here we're presenting the version where he recovers the full value for educational purposes but Ethereum only refunds a portion of the gas.
+
+But wait...
+So what is the actual cost if he paid 10 and got 10 back? Anyone has any idea? Cost might not be obvious but it is an...
+
+---
+
+# Opportunity Cost
+
+Notes:
+
+Opportunity Cost.
+It's a very important concept in economics and it's also crucial in blockchain.
+
+---v
+
+## Opportunity Cost
+
+_"The loss of other alternatives when one option is chosen."_
+
+<img style="width: 400px" src="./img/econ-game-theory/opp_cost.drawio.svg" alt="Multiple alternatives with opportunity cost" />
+
+Notes:
+
+d
+Generally opportunity cost is the loss of other alternatives when making a choice.
+When choosing between 10 and 30$ the opportunity cost of picking 30 is 10, the other option you are forgoing.
+
+---v
+
+## Opportunity Cost
+
+#### _Ethereum State Storage_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> The Real Cost </strong>
+        <br/><br/>
+        Instead of having the funds locked in the storage deposit/refund scheme, Bob could have invested them somewhere else and gain some profit.
+        <br/><br/>
+        <div>Just locking your funds is sort of a punishment by itself.</div><!-- .element: class="fragment" data-fragment-index="1" -->
+    </pba-col>
+    <pba-col>
+        <img style="width: 600px" src="./img/econ-game-theory/opp_cost_locking.drawio.svg" alt="Locking Funds vs Investing" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Going back to the topic of Ethereum the real cost for Bob is not the 10$ he paid for storage as he regains it later.
+The cost is in losing the opportunity of investing the money elsewhere.
+
+=fragment=
+
+Just locking your funds is sort of a punishment by itself.
+Even if you regain them later.
+This is especially true in inflationary systems, and spoiler alert that most of them.
+
+The opportunity cost is a clever mechanism that allows us to include costs without directly charging them, and we also need to be super aware so we don't accidentally punish the users by not thinking of some external opportunity costs.
+
+---v
+
+## Opportunity Cost
+
+#### _Extra Examples_
+
+- Creating invalid blocks in Bitcoin never gets directly punished even if the block is rejected by the network.
+  The real cost is the opportunity cost, as the miner could have mined a valid block instead.
+- Polkadot native token DOT is inflationary (\~7.5% per year) but it can be staked to earn rewards (~15% per year).
+  Not staking DOT has an opportunity cost which incentives staking to secure the network.
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+There is a lot of awesome examples of opportunity costs in blockchain.
+For instance Creating invalid blocks in Bitcoin never gets directly punished even if the block is rejected by the network.
+The real cost is the opportunity cost, as the miner could have mined a valid block instead.
+
+=fragment=
+
+and the Polkadot native token DOT is inflationary (\~7.5% per year) but it can be staked to earn rewards (~15% per year).
+Not staking DOT has an opportunity cost which incentives staking to secure the network.
+
+And there are also many other staking and DeFi examples out there.
+
+---
+
+# Externalities
+
+Notes:
+
+Now to actually appreciate what the we did in the previous section we need to talk about externalities.
+
+---v
+
+## Externalities
+
+_"A consequence of an economic activity that is experienced by unrelated third parties."_
+
+Notes:
+
+An externality is a consequence of an economic activity that is experienced by some third parties.
+
+As an example, think of the pollution you emit when driving a car.
+It's a negative externality that affects all the people around you.
+Alternatively imagine planting a tree in your garden simply because you like how it looks and gives you some shade.
+The tree improves the quality of air in the neighborhood and that's a positive externality for the people around you.
+
+---v
+
+## Externalities
+
+#### _Ethereum State Storage_
+
+The clogging of the chain with useless data is a negative externality that affects all the users of the chain.
+
+As protocol designers we need to be aware of such externalities and we can try and limit their effects by **pricing them in**.
+
+Notes:
+
+In the Ethereum example you could argue that the network getting clogged is the externality of the single developer not cleaning after himself.
+And it affects all the users of the chain.
+The chain is an example of a common good.
+
+As protocol engineers or system designers you need to identify those externality costs and price them in.
+
+---v
+
+## Externalities
+
+#### _Ethereum State Storage_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> Negative Externality Cost </strong>
+        <br/><br/>
+        In the Ethereum State Storage problem we priced in the negative externality as the opportunity cost of locking your funds.
+    </pba-col>
+    <pba-col>
+        <img style="width: 700px" src="./img/econ-game-theory/opp_cost_locking.drawio.svg" alt="Lucking Funds vs Investing" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+That's what we did with the opportunity cost in Ethereum.
+We made it so burdening the chain is actually expensive for the perpetrator.
+We aligned his incentives with the incentives of the chain.
+
+---v
+
+## Externalities
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> Positive Externality </strong>
+        <br/><br/>
+        Providing the voting services in the Oracle scheme can be seen as a positive externality for the network that can further use this extra information.
+        <br/><br/>
+        The voters are providing a valuable service to the protocol.
+    </pba-col>
+    <pba-col>
+        <img style="width: 700px" src="./img/econ-game-theory/oracles.drawio.svg" alt="Information from the external world entering Blockchain" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+But not all externalities are negative.
+
+For example the whole oracle scheme makes it so the chain can get information from the real world.
+This is a positive externality for the network that can further use this extra information.
+
+---v
+
+## Externalities
+
+#### _Oracles_
+
+The voters are providing a valuable service to the protocol.
+
+So if they submit the vote on chain through a transaction, should they pay any fees? <!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+The honest voters are providing a valuable service to the protocol.
+
+=fragment=
+
+So having that mind should they pay any transaction fees when submitting votes?
+
+---v
+
+## Externalities
+
+#### _Oracles_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> Beneficial Transactions </strong>
+        <br/><br/>
+        Such a transaction can be totally free.
+        <br/><br/>
+        <div>But make sure it cannot be spammed!</div><!-- .element: class="fragment" data-fragment-index="1" -->
+    </pba-col>
+    <pba-col>
+        <img style="width: 300px" src="./img/econ-game-theory/free.svg" alt="Sticker with Free on it" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+And contrary to the common belief such a transaction can be totally free.
+
+=fragment=
+
+But make sure it cannot be spammed! And it's super important, because if it is free it can be trivial.
+In our oracle system we can make sure there is only ONE vote per stake.
+This way we remain safe and can make the transaction free to further incentivize participation.
+
+---v
+
+## Free Transactions
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        There are other free transactions that are not necessarily positive externalities.
+        <br/><br/>
+        <strong> Inherent Transactions </strong>
+        <ul>
+            <li> Block rewards in BTC </li>
+            <li> Any logic that needs to be executed for every block (is inherent to the block) </li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 300px" src="./img/econ-game-theory/free.svg" alt="Sticker with Free on it" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+There are other free transactions that are not necessarily positive externalities.
+For instance in Bitcoin after mining a block you get a reward.
+This is a free transaction that is not a positive externality.
+It's just inherent to the block.
+Usually any logic that needs to be executed for every block (is inherent to the block) is free.
+
+---
+
+# Complete vs Partial Information Games
+
+Notes:
+
+Now let's look at something totally different.
+We will talk about a concept crucial to game theory and that is information.
+
+---v
+
+## Complete vs Incomplete Information Games
+
+_Do players know everything about the game state?_
+
+_Do players **NEED** to know everything about the game state?_
+
+Notes:
+
+We'll be looking at questions like do players know everything about the game state? Do they NEED to know everything about the game state? And how does it affect the game?
+
+---v
+
+## Complete vs Incomplete Information Games
+
+#### _Polkadot Approval Voting (Simplified)_
+
+<img style="width: 900px" src="./img/econ-game-theory/Approval_checkers.drawio.svg" alt="Five validators and three approval checkers among them" />
+
+Notes:
+
+To investigate this topic we'll dive deeper into Polkadot and particularly the Approval Voting subsystem.
+This is something I personally work on at Parity and you will learn a lot more about it in the later modules.
+
+What you need to understand now is that there are some special nodes called validators.
+They as they name suggests validate if the new blocks in the network are valid and correct.
+
+---v
+
+## Complete vs Incomplete Information Games
+
+#### _Polkadot Approval Voting (Simplified)_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> Approval Checkers </strong>
+        <br/><br/>
+        In Polkadot when new blocks are validated, not everyone does the work.
+        Only some randomly chosen validators - called <strong>Approval Checkers</strong> - are selected to validate candidate blocks.
+    </pba-col>
+    <pba-col>
+        <img style="width: 700px" src="./img/econ-game-theory/Approval_checkers.drawio.svg" alt="Five validators and three approval checkers among them" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+But in Polkadot not every validator does all the work.
+They share the work and each block is checked only by a subset of validators.
+They are called Approval Checkers.
+
+---v
+
+## Complete vs Incomplete Information Games
+
+#### _Polkadot Approval Voting (Simplified)_
+
+<pba-cols>
+    <pba-col>
+        <br/>
+        <strong> Attackers </strong>
+        <br/><br/>
+        We assume that attackers can DDoS some but not ALL Validators.
+        <br/><br/>
+        Being DDoS'ed makes them unable to vote in time.
+    </pba-col>
+    <pba-col>
+        <img style="width: 700px" src="./img/econ-game-theory/validators_attack.drawio.svg" alt="Attackers eliminated some validators" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+We also need to make some assumptions about the attackers willing to disrupt the network.
+We assume that attackers can DDoS some but not ALL Validators.
+Being DDoS'ed makes them unable to vote in time.
+
+---v
+
+## Complete vs Incomplete Information Games
+
+#### _Polkadot Approval Voting_
+
+**Default Scenario**
+
+- Randomly select 3 Approval Checkers and announce them
+- Approval Checkers publish votes if they are selected
+- If all the votes received confirm the block is fine it passes
+
+<img style="width: 600px" src="./img/econ-game-theory/Approval_checkers.drawio.svg" alt="Five validators and three approval checkers among them" />
+
+Notes:
+
+A default validation scenario would go like that.
+We randomly select 3 Approval Checkers and announce them.
+Approval Checkers publish votes if they are selected.
+If all the votes received confirm the block is fine it passes.
+
+But there is a problem with it? Does anyone know what it is?
+
+---v
+
+## Complete vs Incomplete Information Games
+
+#### _Polkadot Approval Voting_
+
+**Default Scenario**
+
+- Randomly select 3 Approval Checkers and announce them
+- Approval Checkers publish votes if they are selected
+- **Attackers use the information and DDoS the selected before they publish the vote** (except their insider)
+- If all the votes received confirm the block is fine it passes
+
+<img style="width: 600px" src="./img/econ-game-theory/validators_target_attack.drawio.svg" alt="Eliminated approval checkers" />
+
+Notes:
+
+If the attackers learn who the designated approval checkers are they can focus their attack.
+And only eliminate the relevant targets thus compromising the network.
+
+---v
+
+## Complete vs Incomplete Information Games
+
+#### _Polkadot Approval Voting_
+
+**What was the Problem?**
+
+- Attackers learned everything about the game
+- Attackers could use this information before the validators could respond
+
+**How do we fix it?**
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Limit the information the attackers have access to so they cannot plan ahead
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+So let's ask ourselves what was the problem? The attackers learned everything about the game and could use this information before the validators could respond.
+The information is the weapon.
+
+=fragment=
+If we could somehow limit the information the game would change in our favour.
+We need to make this a game of incomplete information, where some things are hidden.
+
+---v
+
+## Complete vs Incomplete Information Games
+
+#### _Polkadot Approval Voting_
+
+**Improved Scenario**
+
+- Each validator uses a VRF to generate a random number
+- Validators with a sufficiently small number will have the right to be Approval Checkers
+- Approval Checkers reveal themselves by showing their low numbers and publish a vote at the same time <!-- .element: class="fragment" data-fragment-index="2" -->
+- If all the votes received confirm the block is fine it passes <!-- .element: class="fragment" data-fragment-index="2" -->
+
+<br/>
+
+Notes:
+
+- Let's imagine this new improved scenario.
+  Each validator uses a VRF to generate a random number.
+- There is some threshold and validators with a sufficiently small number will have the right to be Approval Checkers.
+
+=fragment=
+
+- Approval Checkers reveal themselves by showing their low numbers (with a vrf proof attached) and publish a vote at the same time.
+  If all the votes received confirm the block is fine it passes.
+
+This method has this nice property that attackers don't learn who the approval checkers are until they reveal themselves.
+So they cannot plan ahead.
+
+---v
+
+## Complete vs Incomplete Information Games
+
+#### _Polkadot Approval Voting_
+
+**What can the Attackers do?**
+
+- They no longer know who the Approval Checkers are so they have to guess
+- If they don't guess correctly they get heavily slashed
+
+<img style="width: 700px" src="./img/econ-game-theory/validators_random_attack.drawio.svg" alt="Some validators are eliminated" />
+
+Notes:
+
+So what can the attackers do? If they can no longer target DDoS they only can attack at random.
+This vastly reduces their chances of success and makes thm vulnerable to punishment if they fail.
+
+This is pretty much the method used in Polkadot and it's called a VRF based random assignment.
+It's a game of incomplete information.
+
+---v
+
+## Complete vs Incomplete Information Games
+
+#### _Extra Examples_
+
+- BABE is a Polkadot mechanism for selecting new block producers (further covered in Polkadot module).
+  It also uses a similar VRF scheme to generate random assignments
+
+Notes:
+
+Some other notable examples you will learn about in later modules are connected to BABE the Polkadot mechanism for selecting new block producers.
+It also uses a similar VRF scheme to generate random assignments.
+
+---
+
+# Shifting Assumptions
+
+Notes:
+
+By now you might have noticed a pattern that usually we have a list of assumptions.
+
+---v
+
+## Shifting Assumptions
+
+<pba-cols>
+    <pba-col>
+        Every game has some assumptions that need to be made before reasoning about them.
+        <ul>
+            <li>Number of players</li>
+            <li>Available actions</li>
+            <li>Access to information</li>
+            <li>etc</li>
+        </ul>
+    </pba-col>
+    <pba-col>
+        <img style="width: 200px" src="./img/econ-game-theory/assumptions.drawio.svg" alt="Board with assumptions" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Some of the assumptions are connected to the number of players or maybe the access to information.
+And they are usually pretty stable.
+
+---v
+
+## Shifting Assumptions
+
+<pba-cols>
+    <pba-col>
+        If any of the assumptions change the game changes as well.
+        Old incentives that were previously sensible may now motivate a vastly different behavior.
+    </pba-col>
+    <pba-col>
+        <img style="width: 300px" src="./img/econ-game-theory/assumptions_change.drawio.svg" alt="Some of the assumptions on the board change" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+What happens when for some reason the assumptions evolve and change?
+The game changes as well.
+Old incentives that were previously sensible may now motivate a vastly different behavior.
+
+---v
+
+## Shifting Assumptions
+
+#### _Restaking_
+
+<pba-cols>
+    <pba-col>
+        Restaking through EigenLayer incentives Ethereum stakers to stake the same funds for multiple apps at the same time.
+        <br/><br/>
+        The incentive game will be vastly different and the capital will effectively be leveraged (double risk and double rewards).
+    </pba-col>
+    <pba-col>
+        <img style="width: 600px" src="./img/econ-game-theory/eigen.drawio.png" alt="EigenLayer Logo" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+A super good example of that is what is very recently happening in Ethereum.
+And I mean literally this month.
+There is a new layer 2 protocol called EigenLayer that allows stakers to stake the same funds for multiple apps at the same time.
+This is called restaking.
+
+This is not something natively available in Ethereum and it wasn't taken into consideration when slashes/rewards were designed.
+
+---v
+
+## Shifting Assumptions
+
+#### _Restaking_
+
+<pba-cols>
+    <pba-col>
+        <strong> Consequences </strong>
+        <br/><br/>
+        Restaking consequences are still not fully understood and the research is ongoing.
+        <br/><br/>
+        Speaker Notes ("S") for further reading.
+    </pba-col>
+    <pba-col>
+        <img style="width: 600px" src="./img/econ-game-theory/eigen.drawio.png" alt="EigenLayer Logo" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+The consequences of restaking are still not fully understood and the research is ongoing.
+I encourage you to read the speaker notes for further reading.
+The whole field of blockchain incentivization and protocol design is still developing so there are many unknowns but overall I hope all the methods shown today help you in making more informed decisions later down the line.
+Thats it...
+
+- Podcast: https://www.youtube.com/watch?v=aP9f_1v9Ulc
+- Whitepaper: https://2039955362-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FPy2Kmkwju3mPSo9jrKKt%2Fuploads%2F9tExk4U2OdiRKGEsUWqW%2FEigenLayer_WhitePaper.pdf?alt=media&token=c20ac4bd-badd-4826-9fb6-492923741c9e <!-- markdown-link-check-disable-line -->
+
+---
+
+## Summary
+
+- Markets - Fee Markets
+- Nash Equilibrium - BTC Mining
+- Schelling Point - Oracles
+- Incentivization - Oracles
+- Opportunity cost - Ethereum State Storage Refunds
+- Externalities - Ethereum State Storage and Oracles
+- Complete vs Incomplete Information Games - Polkadot Approval Voting
+- Assumptions - Restaking
+
+Notes:
+
+So to summarize we talked about:
+
+---
+
+# Thanks everyone!
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+---
+title: Blockchain Forks # Also update the h1 header on the first slide to the same name
+description: Detailed Classification for Blockchain Forks Types
+duration: 60 minutes
+# PBA has a theme: "reveal-md/PBA-theme.css", alternatively, you can use a named default like "night" from this list: https://github.com/hakimel/reveal.js/tree/master/css/theme/source
+# Add custom css files for your slides here, comma separated:
+separator: "\r?\n---\r?\n"
+verticalSeparator: "\r?\n---v\r?\n"
+# Below can be any of these: https://revealjs.com/config/
+revealOptions:
+  transition: "none" # animation between slides = none/fade/slide/convex/concave/zoom
+	backgroundTransition: "fade" # background swap between slides = none/fade/slide/convex/concave/zoom
+	slideNumber: true
+	controls: true
+	progress: true
+---
+
+# Blockchain Forks
+
+---
+
+# Landscape
+
+---v
+
+## Landscape
+
+#### Ideal World
+
+In an ideal world blockchains would look like this:
+<br/><br/>
+
+<img style="width: 800px" src="./img/forks/no_fork.drawio.svg" />
+
+---v
+
+## Landscape
+
+#### Real World
+
+Things don't always go according to plan:
+
+<br/>
+
+<img style="width: 800px" src="./img/forks/fork_small.drawio.svg" />
+
+---v
+
+## Landscape
+
+#### Chaotic Real World
+
+And sometimes they get extra messy:
+
+<br/>
+
+<img style="width: 800px" src="./img/forks/fork_chaos.drawio.svg" />
+
+---
+
+# What's the goal?
+
+---v
+
+## What's the goal?
+
+#### _Fork Identification_
+
+<img style="width: 500px" src="./img/forks/forks_and_boxes.drawio.svg" />
+
+Notes:
+
+There are different forks, they can have different shapes and reasons.
+We'll try to identify some examples.
+
+---v
+
+## What's the goal?
+
+#### _Fork Categorization_
+
+<img style="width: 800px" src="./img/forks/forks_in_boxes.drawio.svg" />
+
+Notes:
+
+Why?
+Forks in the same category will exhibit similar behavior and will require similar handling.
+Then when making changes we can easily figure out to which box the change belongs and react accordingly.
+
+It's also worth pointing out that the whole web3 space is still very young and we are still figuring out how to name things appropriately.
+There is definitely still a lot of confusion about the fork types and the convention I will be using here today is based on the naming proposed by the MIT Digital Currencies Initiative.
+It will cover most of the common terms and hopefully will not be as self-contradictory as some of the terms used within the community.
+
+---v
+
+## What's the goal?
+
+#### _Fork Confusion_
+
+<br/>
+BABE (sometimes):
+<br/><br/>
+<img style="width: 800px" src="./img/forks/transitory_fork_unresolved.drawio.svg" />
+
+Notes:
+
+To demonstrate the confusion think of BABE.
+BABE can have multiple block authors create blocks at the same time and then the chain forks.
+What type of a fork is it?
+Some of you might have heard about soft forks and hard forks, any idea which one it is?
+
+---
+
+# Fork Categorization
+
+---v
+
+## Fork Categorization
+
+#### _Forks Family Tree_
+
+<br>
+<img style="width: 800px" src="./img/forks/fork_family.drawio.svg" />
+
+Notes:
+
+This is the core categorization of forks we'll be waking you through today.
+You don't need to understand the whole tree as we'll be going step by step.
+For now let's actually go back to the example from BABE and let's place it on the map.
+
+---
+
+# Transitory Forks
+
+Notes:
+
+For that we'll talk about transitory forks.
+
+---v
+
+## Fork Categorization
+
+#### _Transitory Forks_
+
+<br>
+<img style="width: 800px" src="./img/forks/fork_family_transitory.drawio.svg" />
+
+Notes:
+
+One of the simplest forks that is rarely talked about so the name might not sound familiar.
+They are often also called short-lived forks or temporary forks.
+
+---v
+
+## Transitory Forks
+
+<br>
+<img style="width: 800px" src="./img/forks/transitory_forks.drawio.svg" />
+
+Notes:
+
+They usually arise from the fundamental protocol uncertainty or networking lag, but luckily they are usually resolved quickly by the network itself.
+For instance in BABE even if all the nodes are running the same software those forks can still happen when two nodes roll low enough numbers.
+In Bitcoin two miners might mine a block at roughly the same time.
+Over time one of the blocks wins due to some heuristics like the longest chain.
+Those forks are generally not a problem and only live on short timescales.
+
+---
+
+# Consensus Forks
+
+Notes:
+
+So now let's move to something more interesting.
+Consensus forks.
+
+---v
+
+## Fork Categorization
+
+#### _Consensus Forks_
+
+<br>
+<img style="width: 800px" src="./img/forks/fork_family_consensus.drawio.svg" />
+
+Notes:
+
+Usually when you hear about forks you hear about those guys.
+They are the other branch and they also come in many flavours we'll discuss in a minute.
+
+---v
+
+# Consensus Forks
+
+## _Validity Set_
+
+Notes:
+
+But first before we understand the intricacies of consensus forks we need to understand the concept of the validity set and how it connects to the protocol.
+
+---v
+
+## Consensus Forks
+
+#### _Validity Set_
+
+<br>
+<img style="width: 800px" src="./img/forks/BTC_block.drawio.svg" />
+
+Notes:
+
+It's best to see it through an example so let's look at the BTC block.
+You don't need to understand all the fields that are in it but for now take a look at the blocksize field as well as the block header itself.
+
+#### _Validity Set_
+
+<br>
+<img style="width: 300px" src="./img/forks/BTC_header.drawio.svg" />
+
+---v
+
+## Consensus Forks
+
+#### _Validity Set_
+
+<br>
+<img style="width: 500px" src="./img/forks/BTC_header_constraints.drawio.svg" />
+
+---v
+
+## Consensus Forks
+
+#### _Validity Set_
+
+<br>
+<img style="width: 500px" src="./img/forks/validity_set.drawio.svg" />
+
+Notes:
+
+So the validity set is a set of all hypothetical blocks that could be produced by the protocol.
+It's a set of all valid blocks under those rules.
+
+So if there is a block D that for instance is too big, it's blocksize is bigger than the allowed one...
+
+---v
+
+## Consensus Forks
+
+#### _Validity Set_
+
+<br>
+<img style="width: 500px" src="./img/forks/universal_set.drawio.svg" />
+
+Notes:
+
+Then it falls out of the validity set into the universal set of all possible data blobs.
+Only some of those data blobs are valid blocks.
+
+---v
+
+## Consensus Forks
+
+#### _Validity Set_
+
+<br>
+<img style="width: 500px" src="./img/forks/validity_set_old.drawio.svg" />
+
+Notes:
+
+Let's actually look at an example.
+Imagine this is Bitcoins validity set and here we see a few blocks from it.
+The numbers at the top are initial few digits from the hashes representing those blocks.
+
+Imagine all the Bitcoin nodes suddenly decide they really dislike when the first hash digit is odd.
+They only like when it's even so they band together and change the protocol to only accept hashes with an even first digit.
+
+---v
+
+## Consensus Forks
+
+#### _Validity Set_
+
+<br>
+<img style="width: 500px" src="./img/forks/validity_set_new.drawio.svg" />
+
+Notes:
+
+This change in the protocol would reduce the validity set.
+It would be more constrained then before.
+Some of the previously valid blocks would no longer be valid under the new rules.
+What happens in that case?
+Can we predict that?
+
+---v
+
+## Consensus Forks
+
+#### _Validity Set_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 500px" src="./img/forks/validity_set_new.drawio.svg" />
+    </pba-col>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_soft.drawio.svg" />
+		<div style="font-size: 50px;">N ⊆ O</div>
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+To generally represent the same idea we'll be using the simpler representation on the right.
+Where the new set N is contained within the old set O.
+The fancy notion at the bottom says the same N is contained in O.
+
+---
+
+# Soft Forks
+
+To understand the example from a second ago we'll dive into soft forks.
+
+---v
+
+## Fork Categorization
+
+#### _Soft Forks_
+
+<br>
+<img style="width: 800px" src="./img/forks/fork_family_soft.drawio.svg" />
+
+Notes:
+
+Firstly soft forks are a type of a consensus fork and they are results of a change in the protocol and thus the validity set.
+
+---v
+
+## Fork Categorization
+
+#### _Soft Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_soft.drawio.svg" />
+		<div style="font-size: 50px;">N ⊆ O</div>
+    </pba-col>
+    <pba-col>
+		<ul>
+			<li>Backwards Compatible</li>
+			<li>By making the consensus rules more restrictive the set of valid blocks gets smaller.</li>
+			<li>Not every (and often none) of the blocks produced under old rules will get accepted by new nodes.</li>
+		</ul>
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+So based on the venn diagram we have on the side we can see that the new consensus rules are more restrictive as the validity set shrinks.
+
+New nodes produce blocks that are always accepted by old nodes.
+Old nodes generally don't produce blocks accepted by the new nodes.
+
+Before we jump into demonstration is decreasing or increasing blocksize a soft fork?
+
+---v
+
+## Fork Categorization
+
+#### _Soft Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_soft.drawio.svg" />
+		<div style="font-size: 50px;">N ⊆ O</div>
+    </pba-col>
+    <pba-col>
+		<strong>Examples:</strong>
+		<br/><br/>
+		<ul>
+			<li>Decreasing blocksize</li>
+			<li>Accepting only even/odd hashes</li>
+			<li>Disallowing some transaction types</li>
+		</ul>
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Decreasing the block size restricts how many different blocks can be constructed so it makes the set smaller.
+It is a soft fork.
+The example we had a moment ago with the even hashes is also a soft fork as it adds another constraint on the previous protocol rules restricting them even further.
+Another good example would be banning some transaction types from use.
+
+Now let's take a look at how forks work in practice and how they vary based on the hash power or staking power in favour of the protocol change.
+
+---v
+
+## Fork Categorization
+
+#### _Soft Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_soft.drawio.svg" />
+		<div style="font-size: 50px;">N ⊆ O</div>
+    </pba-col>
+    <pba-col>
+		<img style="width: 800px" src="./img/forks/soft_forks_s50.drawio.svg" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+So in this scenario we'll be looking at what happens if nodes with less than 50% hash power or stake want to soft fork.
+Remember that soft forking is simply making the consensus stricter.
+
+In that case the blocks produced by new nodes are marked with N and they are accepted by the old chain but the old chain mines faster so they don't care about the new nodes.
+Blocks produced by old nodes are NOT accepted by the new nodes so the longest chain for new nodes is the short chain with only the N blocks.
+This is effectively a permanent fork.
+
+---v
+
+## Fork Categorization
+
+#### _Soft Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_soft.drawio.svg" />
+		<div style="font-size: 50px;">N ⊆ O</div>
+    </pba-col>
+    <pba-col>
+		<img style="width: 800px" src="./img/forks/soft_forks_g50.drawio.svg" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+In the similar example when the new nodes control more than 50% power the situation changes drastically.
+The new nodes mine faster and are the longest chain.
+But remember that old nodes accept the new blocks so if they new nodes mine faster the old nodes blocks get constantly reorged out.
+They are forced to update the software if they want their blocks to get accepted at all otherwise they loose all the rewards.
+
+---
+
+# Hidden Forks
+
+Notes:
+
+Now let's take a look at something a bit less known.
+Hidden forks.
+
+---v
+
+## Fork Categorization
+
+#### _Hidden Forks_
+
+<br>
+<img style="width: 800px" src="./img/forks/fork_family_hidden.drawio.svg" />
+
+Notes:
+
+An edge case of soft forks.
+
+---v
+
+## Fork Categorization
+
+#### _Hidden Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_hidden.drawio.svg" />
+		<div style="font-size: 50px;">N ⊆ O</div>
+    </pba-col>
+    <pba-col>
+		<ul>
+			<li>Conflict-less</li>
+			<li>The old, now excluded blocks were allowed but never used in practice.</li>
+			<li>New nodes are theoretically stricter but practically accept all old blocks.</li>
+			<li>Old nodes accept new blocks.</li>
+		</ul>
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+So the venn diagram is exactly the same as in the normal soft fork case.
+But imagine that the the orange crescent, this is the part we're excluding from the old protocol when shifting to the new one... was never actually used.
+So for instance the block had an empty field that could have some arbitrary data inside, but everyone left it empty and never checked what was inside.
+The new protocol puts something meaningful in the empty field but doesn't require it.
+Because old nodes never used this field pretty much all old blocks will be accepted under the new rules.
+
+TL;DR the stuff we removed from the validity set wasn't even used despite being technically valid.
+
+---v
+
+## Fork Categorization
+
+#### _Hidden Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_hidden.drawio.svg" />
+		<div style="font-size: 50px;">N ⊆ O</div>
+    </pba-col>
+    <pba-col>
+		<strong>Examples:</strong>
+		<br/><br/>
+		<ul>
+			<li>Assigning non-conflicting uses to empty opcodes.</li>
+			<li>BTC Ordinals using empty opcodes to implement BTC NFTs.</li>
+		</ul>
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+A good example of that assigning new optional use-cases for previously unused opcodes as with the example of the recent Bitcoin Ordinals update.
+
+---v
+
+## Fork Categorization
+
+#### _Hidden Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_hidden.drawio.svg" />
+		<div style="font-size: 50px;">N ⊆ O</div>
+    </pba-col>
+    <pba-col>
+		<img style="width: 800px" src="./img/forks/soft_forks_hidden.drawio.svg" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+And the reason why they are hidden... is they are not even manifesting as forks despite the consensus change.
+All nodes effectively accept each others blocks so there is no conflict.
+
+---
+
+# Hard Forks
+
+Notes:
+
+---v
+
+## Fork Categorization
+
+#### _Hard Forks_
+
+<br>
+<img style="width: 800px" src="./img/forks/fork_family_hard.drawio.svg" />
+
+---v
+
+## Fork Categorization
+
+#### _Hard Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_hard.drawio.svg" />
+		<div style="font-size: 50px;">O ⊆ N</div>
+    </pba-col>
+    <pba-col>
+		<ul>
+			<li>Forwards Compatible</li>
+			<li>By making the consensus rules less restrictive the set of valid blocks gets bigger.</li>
+			<li>Not every (and often none) of the blocks produced under new rules will be accepted by the old nodes.</li>
+			<li>Every block produced under old rules will get accepted by new nodes.</li>
+		</ul>
+    </pba-col>
+</pba-cols>
+
+---v
+
+## Fork Categorization
+
+#### _Hard Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_hard.drawio.svg" />
+		<div style="font-size: 50px;">O ⊆ N</div>
+    </pba-col>
+    <pba-col>
+		<strong>Examples:</strong>
+		<br/><br/>
+		<ul>
+			<li>Increasing blocksize</li>
+			<li>BTC Cash fork at first*</li>
+			<li>Adding new transaction types</li>
+			<li>Increasing max nonce value</li>
+		</ul>
+    </pba-col>
+</pba-cols>
+
+---v
+
+## Fork Categorization
+
+#### _Hard Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_hard.drawio.svg" />
+		<div style="font-size: 50px;">O ⊆ N</div>
+    </pba-col>
+    <pba-col>
+			<img style="width: 800px" src="./img/forks/hard_forks_s50.drawio.svg" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+First let's go through the scenario of a hard fork with less than 50% support.
+Remember that the rules were loosened this time.
+If new guys accept old blocks so because they have less than 50% power they get constantly reorged out.
+There is no permanent fork in this scenario and the change will not go through if if it has this limited support.
+
+---v
+
+## Fork Categorization
+
+#### _Hard Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 300px" src="./img/forks/venn_hard.drawio.svg" />
+		<div style="font-size: 50px;">O ⊆ N</div>
+    </pba-col>
+    <pba-col>
+			<img style="width: 800px" src="./img/forks/hard_forks_g50.drawio.svg" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+In the case of more than 50% support the new guys miner faster but they are no accepted by the old nodes so they go ahead.
+Old nodes maintain the old chain and the community is split.
+So if there is a major change that most people accept but not everyone it will always fork the chain.
+
+---
+
+## Small Summary
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 400px" src="./img/forks/soft_forks_s50.drawio.svg" />
+		<br/>
+		<img style="width: 400px" src="./img/forks/soft_forks_g50.drawio.svg" />
+    </pba-col>
+	<pba-col>
+		<img style="width: 400px" src="./img/forks/hard_forks_s50.drawio.svg" />
+		<br/>
+		<img style="width: 400px" src="./img/forks/hard_forks_g50.drawio.svg" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+Now that we've seen both soft and hard forks...
+If we'd manually increase the difficulty of mining in the BTC network would that be a soft or hard fork?
+Hard.
+
+Also let's reiterate.
+We only have permanent forks in soft forks with under 50% support and in hard forks with over 50% support.
+
+---
+
+# Full Forks
+
+---v
+
+## Fork Categorization
+
+#### _Full Forks_
+
+<br>
+<img style="width: 800px" src="./img/forks/fork_family_full.drawio.svg" />
+
+---v
+
+## Fork Categorization
+
+#### _Full Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 200px" src="./img/forks/venn_full.drawio.svg" />
+		<div style="font-size: 50px;">O ∩ N = ∅</div>
+    </pba-col>
+    <pba-col>
+		<ul>
+			<li>Fully Incompatible</li>
+			<li>Soft + Hard</li>
+			<li>By changing the consensus rules the sets can become disjoint or overlapping.</li>
+			<li>Most (and often all) blocks produced under one ruleset are not accepted under the other.</li>
+		</ul>
+    </pba-col>
+</pba-cols>
+
+---v
+
+## Fork Categorization
+
+#### _Full Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 200px" src="./img/forks/venn_full.drawio.svg" />
+		<div style="font-size: 50px;">O ∩ N = ∅</div>
+    </pba-col>
+    <pba-col>
+		<strong>Examples:</strong>
+		<br/><br/>
+		<ul>
+			<li>Changing the hashing function</li>
+			<li>Changing the signature scheme</li>
+			<li>Specific combinations of soft and hard forks</li>
+			<li>BTC Cash fork in the end*</li>
+		</ul>
+    </pba-col>
+</pba-cols>
+
+---v
+
+## Fork Categorization
+
+#### _Full Forks_
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 200px" src="./img/forks/venn_full.drawio.svg" />
+		<div style="font-size: 50px;">O ∩ N = ∅</div>
+    </pba-col>
+    <pba-col>
+		<img style="width: 600px" src="./img/forks/full_forks__&_50.drawio.svg" />
+    </pba-col>
+</pba-cols>
+
+---
+
+## Summary
+
+<pba-cols>
+    <pba-col>
+		<img style="width: 400px" src="./img/forks/soft_forks_s50.drawio.svg" />
+		<br>
+		<img style="width: 400px" src="./img/forks/soft_forks_g50.drawio.svg" />
+    </pba-col>
+	<pba-col>
+		<img style="width: 400px" src="./img/forks/hard_forks_s50.drawio.svg" />
+		<br>
+		<img style="width: 400px" src="./img/forks/hard_forks_g50.drawio.svg" />
+    </pba-col>
+    <pba-col>
+		<img style="width: 400px" src="./img/forks/full_forks__&_50.drawio.svg" />
+    </pba-col>
+</pba-cols>
+
+Notes:
+
+- Bitcoin cash pivot from hard to full because they didn't have enough HP.
+- Soft are often preferred for changes because with >50%HP they do not fracture the community (BTC community logic)
+- Hard can be preferred as they seem to better represent minorities.
+  If some people don't agree with the majority they naturally fork off and are not peer pressured to follow (ETH community logic)
+
+---
+
+# Thank you!
+
+---
+
+<img style="width: 1800px" src="./img/forks/forks.drawio.svg" />
diff --git a/content/3-Blockchain/8-Consensus_Finality-slides.md b/content/3-Blockchain/8-Consensus_Finality-slides.md
new file mode 100644
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@@ -0,0 +1,805 @@
+---
+title: Consensus Finality
+description: Finality providing methods and mechanisms for blockchains
+duration: 45min
+---
+
+# Consensus: Finality
+
+---
+
+## Consensus is...
+
+...a decision making process that strives to achieve acceptance of a decision by all participants.
+
+Notes:
+
+If we have external factors like trust relationships or Social hierarchy it can be quite easy.
+
+Trust example: If everyone trusts each other, then any one person can propose an outcome, and all the others will trust that it is in the community's best interest.
+
+Social Hierarchy example: If a community has an executive (President, Queen, CEO), the executive can propose her preference and everyone will accept it based on the external mechanism that keeps her as the executive.
+
+But these conditions are not interesting, and are often not realistic. It gets interesting when we don't make these simplifying assumption.
+
+---v
+
+## Five Aspects of Blockchain Consensus
+
+<pba-flex center>
+
+- State machine validity
+- Arbitrary / Political validity
+- Authorship throttling
+- Fork choice heuristic
+- Finality
+
+</pba-flex>
+
+---
+
+## What do these things have in common?
+
+<img style="width: 600px" src="./img/roller_coaster.jpg" />
+
+---v
+
+## What do these things have in common?
+
+<img style="width: 600px" src="./img/slackline.jpg" />
+
+---v
+
+## What do these things have in common?
+
+<img style="width: 600px" src="./img/wheel.jpg" />
+
+---v
+
+## What do these things have in common?
+
+<img style="width: 600px" src="./img/ratchet.jpg" />
+
+---
+
+## Adversarial Conditions
+
+- The participants want to agree on _something_
+- They don't trust each other
+- Some could be faulty, or make mistakes
+- Some could be straight up malicious (aka Byzantine)
+
+---
+
+# One Shot Consensus
+
+A single decision to make.
+
+Once it is made, we are done.
+
+---v
+
+## Desired Properties
+
+All honest participants...
+
+- **Termination** - Eventually reach some decision
+- **Agreement** - Reach the same decision
+- **Integrity** - Reach at most one decision, which was proposed by at least one participant.
+
+---v
+
+## Also Validity
+
+If all participants unanimously propose the same decision, all honest participants reach that decision.
+
+Notes:
+
+Another desireable property that is sometimes too obvious to say.
+
+---
+
+## Example: Where to go for dinner
+
+<pba-cols>
+<pba-col>
+
+<img rounded style="width: 20em" src="./img/south-park-consensus.png" />
+
+</pba-col>
+
+<pba-col>
+
+- Termination - Stan, Kyle, and Kenny will each eventually decide where to eat.
+- Agreement - Stan, Kyle, and Kenny will each decide to eat at the same place.
+- Integrity - Stan, Kyle, and Kenny will eat at either Whistlin' Willies or Casa Bonita.
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Stan, Kyle, Kenny, and Cartman are trying to decide where to have dinner.
+Stan, Kyle, and Kenny want to have something yummy and spend time together.
+Cartman is secretly pursuing his own goals and doesn't care whether dinner is yummy.
+In fact he secretly hopes they won't decide at all so he can go home and eat KFC with his mom.
+
+Stan and Kyle both propose Whistlin' Willie's for dinner.
+Kenny and Cartman propose Casa Bonita.
+
+In the end Kenny may not agree that Whistlin' Willie's is the best option for dinner, but he will agree that it is the legitimate group decision.
+
+---v
+
+## Mistakes vs Malice
+
+**Crash Tolerance** - A system can keep operating normally when some actors crash or go offline.
+
+**Byzantine Fault Tolerance** - A system can keep operating normally when some actors are intentionally malicious. Byzantine actors may:
+
+- Crash - Or pretend to have crashed - Byzantine faults are a superset of crash faults
+- Lie - Sending false information to peers
+- Equivocate - Send inconsistent information to different peers
+
+Notes:
+
+These examples and many others are _instances_ of the Byzantine Generals Problem
+
+---v
+
+## Mistake or Malice?
+
+<pba-cols>
+<pba-col>
+
+<img rounded style="width: 600px" src="https://thepointsguy.global.ssl.fastly.net/uk/originals/2020/12/pitot-ice-scaled.jpg" />
+
+</pba-col>
+
+<pba-col>
+
+- Consider an Airplane flight computer.
+- The pilot _must_ know the airspeed at all times.
+- Airspeed sensors can fail.
+- Sensors can be buggy.
+- Are these malicious?
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Consider an Airplane flight computer. It is critical that the pilot (human or automated) knows the aircraft's airspeed at all times.
+Airspeed sensors can fail due to extreme temperatures, icing, solar radiation, and other reasons.
+For this reason, there are redundant sensors, and they run a consensus protocol.
+
+Imagine that one of the sensors has an overflow _bug_ such that when the airspeed exceeds a certain threshold, maybe `u8::max_value()`, it actually reports a much lower speed.
+
+Are these crash faults or byzantine?
+
+In a blockchain system, bugs in the code may cause nodes whose operators are intending to be honest, to deviate from the protocol anyway. This is why client diversity is important.
+
+---
+
+## Byzantine Generals Problem
+
+<pba-cols>
+<pba-col>
+
+<img rounded style="width: 700px" src="./img/byzantine-generals.png" />
+
+</pba-col>
+
+<pba-col>
+
+- Divisions plan to attack
+- Must make coordinated attack to succeed
+- Some generals might be traitors and behave maliciously
+
+</pba-col>
+</pba-cols>
+
+[Cornell Lecture Slides](https://www.cs.cornell.edu/courses/cs6410/2018fa/slides/18-distributed-systems-byzantine-agreement.pdf)
+
+Notes:
+
+Several divisions of the Byzantine army are camped around an enemy city.
+They plan to attack the city, but have not yet decided when to attack.
+If the attack is coordinated, they will probably be successful, but if it is uncoordinated, they will probably be defeated.
+What do our three properties mean in this scenario?
+
+- Termination - every honest general will eventually decide when to attack
+- Agreement - honest general will all agree to attack ta the same time
+- Integrity - the attack time will have been proposed by at least one honest general
+
+Leslie Lamport proposed this problem in the form of a story as a typical representative of the distributed consensus problem.
+
+This is a big moment for us, so let's stop and savor it.
+Two days ago Lauren kicked us off by talking about human coordination.
+How it can achieve long railroads and the great pyramids and sports teams and dancing, and even this academic program.
+Since then we've looked through so many layers of abstraction (contracts, smart contracts, state machines, dags) and so many technical implementation details (P2P networking, platform agnostic bytecodes, blockchain headers, merkle proofs).
+We've taken a huge class of problems - human coordination problems - and distilled them down to their absolute essence.
+Human coordinate at global scale reduced to this one cute, carefully stated problem.
+
+---v
+
+## Byzantine Generals: Solved
+
+<img height="600px" src="./img/pbft-cover.png" />
+
+_Miguel Castro and Barbara Liskov, 1999_
+
+Notes:
+
+_Image = Cover page: Practical Byzantine Fault Tolerance_
+
+And great news.
+The problem is solved!
+At least under some conditions.
+And also great news.
+We have a pretty good understanding of under what circumstances it is solvable.
+
+Before I can tell you exactly how and where it can be solved, we have to understand networks a little bit.
+
+---
+
+# History Lesson
+
+---
+
+## Synchrony
+
+A network is one of:
+
+- **Synchronous** - When sent, a message is received immediately by all.
+- **Asynchronous** - When a message is sent it may be received after some delay, or not at all. The sender doe not know whether it is received. Messages may be received in different orders by different parties.
+- **Partially Synchronous** - When a message is sent, it may be received after some delay up to a maximum delay, $T$. It may not be dropped entirely. Messages may be received in different orders by different parties.
+
+Roughly analogous to real-time (async) vs. turn-based (sync) games.
+
+---v
+
+## Sync or Async?
+
+Classify each of these:
+
+<pba-flex center>
+
+- Telephone call
+- Mail communication
+- Text message
+- Jitsi video call
+- Element chat
+
+</pba-flex>
+
+Notes:
+
+- Telephone call is sync. You say something and wait for the other party to reply
+- Mail is async. You send a letter, then go do other stuff for several days
+- Jitsi video call is basically sync just like the phone call.
+- The others can be either. Sometimes you text back and forth quickly and wait for replies. Other times you send and come back later like mail.
+
+---
+
+## Determinism
+
+A system is one of:
+
+- **Deterministic** - The same inputs give the same outputs every time.
+- **Probabilistic** - The same inputs may not give the same outputs.<br/>
+  $~~~~~~~~~~~~~~~~~~~~~~~~~$ Requires a source of entropy. eg coin flipping. <!-- $~~~$ is a hack to put in white space chars -->
+
+---
+
+## FLP Impossibility
+
+<img style="padding: 0 200px 0 0" src="./img/FLP-impossible.png" />
+
+[Excellent Podcast with Ethan Buchman](https://www.youtube.com/watch?v=t0T-5QOXvrQ)
+
+Notes:
+
+Once it was shown that deterministic consensus is impossible in an async network, the field split into two major parts. Either you:
+
+- Assume the network is (at least partially) synchronous
+- Introduce non-determinism
+
+One interesting thing about Nakamoto pow consensus is that it does _both_.
+
+- Nondeterminism because you don't know who will solve the pow first
+- Partial synchrony because it only works if the time to download and execute the block is much less than the time to solve the PoW
+
+---
+
+## Ongoing Consensus
+
+We want to continue agreeing on<br/>an every-growing history of events
+
+Notes:
+
+Blockchains are intended to keep processing and finalizing transactions forever. This is more like deciding where to go to dinner every night over and over.
+
+---v
+
+## Desireable Properties
+
+<pba-flex center>
+
+- **Safety** aka **Finality** - Nothing bad will happen
+- **Liveness** - Something good will eventually happen
+
+</pba-flex>
+
+Notes:
+
+Traditional literature typically uses the term safety. Blockchain folks typically talk about finality. They basically mean the same thing.
+
+Finality can be proved to entities that are not involved in consensus.
+
+We spoke about liveness previously in the authoring system. There it means that more blocks will be authored, more blockspace will be created and put up for sale. Here, in finality, it means that more blocks will be finalized. Of course liveness in the finality depends on liveness in the authoring.
+
+These two decisions can be entirely orthogonal to one another, or wrapped up together.
+
+---v
+
+## Liveness vs Termination
+
+Earlier I described Termination as desireable,<br/>now I'm saying Liveness is desireable.
+
+Are these at odds with each other?
+
+Notes:
+
+Termination guarantees that, for a given decision, each honest participant will eventually decide something. This concept is relevant when there is a single decision to be made. In the blockchain context, it guarantees that we will eventually know which block is final at height n.
+
+Liveness guarantees that a system that is intended to continue making progress, will indeed eventually make progress. In the context of the blockchain, liveness means that once we've decided what block is final at height n, we will eventually go on to decide what block is final at height n + 1.
+
+---
+
+## Finality in Nakamoto Consensus
+
+<pba-flex center>
+
+- Longest chain rule
+- Longest chain is "best"... for now
+- Someone could always start mining a chain<br/>and,with low but non-zero probability,<br/> end up with it longer.
+- There could _already_ be a longer chain<br/>that you just haven't heard of.
+
+<pba-flex>
+
+The finality is only probabilistic.<br/>
+Nakamoto consensus in only safe in a synchronous network.
+
+Notes:
+
+This is to say that Nakamoto consensus is NOT safe on the real asynchronous internet. In practice, as long as
+blocks can be downloaded and executed much more quickly than the target block time, it is usually good enough.
+
+- Longest could also mean most accumulated work
+
+---
+
+## Deterministic Finality
+
+<pba-flex center>
+
+- Based on traditional methods (BFT)
+- Requires an honest-majority finite authority set
+
+</pba-flex>
+
+<!-- two flexes needed so the next bullet points don't show too early, margin hack... TODO -->
+
+<pba-flex center style="margin-left: 48px">
+
+- Consensus protocol that assumes honest majority
+- Economic game that keeps them honest
+
+</pba-flex>
+<!-- .element: class="fragment"-->
+
+Notes:
+
+If you want deterministic finality, it basically means employing BFT agreement protocols that we talked about in the history lesson. This means we need a finite authority set with an honest majority. And that means we need incentives to keep them honest.
+
+---v
+
+## Incentives: Game Theory!
+
+Abstractly: You behave honestly<br/>when the utility of doing so exceeds the cost.
+
+Incentive designers may potentially:
+
+<pba-flex center>
+
+- Reward honest behavior
+- Punish (aka slash) dishonest behavior
+
+</pba-flex>
+
+Notes:
+
+Many systems use both of these, but doing so is not strictly necessary. Even without slashes, the opportunity cost of staking and the missed rewards from authoring invalid blocks may be sufficient.
+
+It is often the case that blockchain systems give rewards in the authorship and punishments in the finality. There is no fundamental reason for this; it is just a little more straightforward to implement.
+
+---v
+
+## What is potentially punishable?
+
+<pba-flex center>
+
+- Authoring when you aren't supposed to
+- Failing to author when you are supposed to
+- Casting finality votes for conflicting blocks
+- Casting a finality vote for a block (or chain)<br/> that includes an invalid state transition.
+
+> How severe are each of these offenses?<br/>
+> Do they all warrant a slash?<br/>
+> A full slash?
+
+Notes:
+
+PoW has inherent punishment through wasted energy. BFT based system's don't.
+
+Instead, aspiring participants will typically lock up a security deposit which can be slashed in part or in whole.
+
+---v
+
+### Concrete Punishment Example
+
+Let's say a slash is 100 units, and the reporter gets 10%.<br/>I plan to attack.
+
+If my attack is successful,<br/>I expect to gain roughly 200 units worth of utility.
+
+I ask another authority to cooperate with me:<br/>"I'll pay you 20 units to _not_ rat me out for my attack".
+
+> How would you respond?
+
+Notes:
+
+"I don't believe you can carry out the attack because _someone else_ will report you and take the 10 units, leaving me with 0."
+
+---
+
+## Case Study: Tendermint
+
+<pba-flex center>
+
+- Authorship is like Aura - simple round robin
+- Naive but **simple** BFT implementation
+- If the block has enough votes<br/>by the end of the slot, it is finalized.<br/>
+  Otherwise, it is rejected via timeout.
+- "Instant finality"
+- Forkless - Forks are disallowed<br/>because blocks can only be authored<br/>on finalized parents.
+
+</pba-flex>
+
+Notes:
+
+Tendermint assumes a partially synchronous network, like all the BFT based systems - That is to say that messages may not arrive immediately, but will arrive within a finite time bound. In practice this means it is slot-based just like so many of the authoring schemes.
+
+Tendermint is often touted as "instant finality". It is instant in the sense that finality is tied to authorship. In practice this means that authorship, which is inherently O(n), is slowed down to stay in sync with finality which is O(n^2). They sacrifice liveness to guarantee absolute safety at all times.
+
+---v
+
+## Tendermint Deep Dive
+
+<pba-flex center>
+<ol>
+<li class="fragment">Wait for a block (or author one if it is your turn)</li>
+<li class="fragment">Prevote
+  <ul>
+    <li>If the block is valid, Prevote for it.</li>
+    <li>If the block is invalid, Prevote `Nil`</li>
+  </ul>
+</li>
+<li class="fragment">Precommit
+  <ul>
+    <li>Wait for 2/3 prevotes then Precommit</li>
+    <li>If you don't get 2/3 prevotes, Precommit `Nil`</li>
+  </ul>
+</li>
+<li class="fragment">Complete
+  <ul>
+  <li>Wait for 2/3 Precommits them finalize</li>
+  <li>If you don't get it, throw the block away</li>
+  </ul>
+</li>
+</ol>
+
+[Very useful blog post](https://medium.com/softblocks/explaining-how-tendermint-consensus-works-433066cbc465) <!-- .element: class="fragment" -->
+
+</pba-flex>
+
+---
+
+## Hybrid Consensus
+
+<pba-cols>
+<pba-col>
+
+<img rounded style="width: 900px;" src="./img/grandpa-abstract.png" />
+
+</pba-col>
+<pba-col>
+<pba-flex center style="font-size: 0.7em; margin-left:-50px">
+
+- Separates block production from finality.
+- Block production stays live even if finality lags.
+- Allows lower overhead in the finality layer.
+- Used in Substrate.
+
+</pba-flex>
+</pba-col>
+</pba-cols>
+
+---v
+
+## What About Re-Orgs
+
+<img style="width: 500px; margin-right: 150px;" src="./img/reorgs-1.svg" />
+<br/>
+<img style="width: 650px;" src="./img/reorgs-2.svg" />
+
+Notes:
+
+Previously we talked about how a node's view of the best block can change, and that is called a re-org.
+
+---v
+
+## Modified Fork Choice Rule
+
+<img style="width: 500px; margin-right: 150px;" src="./img/reorgs-finality-1.svg" />
+<br/>
+<img style="width: 650px" src="./img/reorgs-finality-2.svg" />
+
+Only extend best finalized chain
+Notes:
+
+Once you have a finality gadget installed, you have to make sure you only ever author on top of finalized blocks. Even if another chain is longer.
+
+---
+
+## Case Study: Grandpa
+
+<pba-flex center>
+
+- Deterministic finality _only_
+- Requires an external block authoring scheme<br/> with its own liveness proof.
+- Kind of like Tendermint but better.
+- Finalizes chains, not blocks.
+
+</pba-flex>
+
+---v
+
+## Vote on Chains, not Blocks
+
+<img style="width: 1000px" src="./img/grandpa-round/4.6-validators-vote-on-chain.png"/>
+
+Notes:
+
+BFT finality with $n$ authorities is in $O(n^2)$.
+Tendermint does this at **every block**.
+This bounds the size of the authority set.
+
+With separated, we treat each vote as a vote not only for one block,but also for each ancestor block.
+This significantly reduces the number of total messages sent.
+Allows the chain to stay live even when many validators are offline
+
+---
+
+## A GRANDPA Round
+
+Each validator **broadcasts** a **prevote** for the **highest block** that it thinks **should** be **finalized**
+
+- For **honest** validators, this block **must include** the chain that was previously finalized
+- This **new chain** could be **several blocks** longer than the **last finalized** chain
+
+A **validator** that is designated as the **primary** broadcasts the highest block that it thinks could be final from the previous round
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-1.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-2.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+Each validator **computes** the **highest block** that can be **finalized based** on the set of **prevotes**
+
+- i.e. we find the **common ancestor** of all votes that has **support** from **more** than $\frac{2}{3}N + 1$ validators
+- We refer to this block as the **prevote GHOST**
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-3.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+We define the round **estimate** as the **highest ancestor** of the **prevote GHOST** for which it is **still possible** to **precommit**
+
+- i.e. when **no precommit** votes have been **sent** out yet, then:
+
+`estimate == prevote GHOST`
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-4.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+If the **estimate** extends the **last finalized** chain, then each validator will cast a **precommit** for that chain.
+
+Each validator **waits** to receive **enough precommits** to be able to finalize
+
+- We again find the **common ancestor** of the **estimate** which has **threshold precommits**
+- We declare that **block** as **finalized**
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-5.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-6.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+The **round** is deemed **completable**:
+
+- if the **estimate** is **lower** than the **prevote GHOST**
+- or if it's **impossible** to have a **supermajority** on any **block higher** than the current **estimate**
+
+Validators **start** a **new round** after it becomes **completable**.
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-6.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-7.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-8.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round (Alt)
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-6.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round (Alt)
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-7-alternative.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round (Alt)
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-8-alternative.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round (Alt)
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-9-alternative.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## Summary
+
+<pba-flex center>
+
+- Networks can be {Synchronous, Asynchronous}
+- Consensus systems can be {Deterministic, Probabilistic}
+- Consensus systems can be {Open participation, Finite participation}
+- There is always an assumption that at least {1/2, 2/3} participants are honest
+- In decentralized systems, we use Economics and Game Theory<br/>to incentivize honest execution of the consensus protocol
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Game Time
+
+> I want to play a game...<br/>a board game!
diff --git a/content/3-Blockchain/9-Light_Clients_and_Bridges-slides.md b/content/3-Blockchain/9-Light_Clients_and_Bridges-slides.md
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+---
+title: Light Clients and Bridges
+description: Light clients principles and application in bridges
+---
+
+# Light Clients
+
+<pba-cols>
+<pba-col>
+
+<img rounded style="width:400px" src="./img/tomaka.png" />
+
+</pba-col>
+<pba-col>
+
+> <div> What can I say?</div> <!-- .element: class="fragment" -->
+> <div> It's a client but light.</div>  <!-- .element: class="fragment" -->
+
+</pba-col>
+</pba-cols>
+
+---
+
+## 😢 Running a Node is Hard 😭
+
+<pba-cols>
+<pba-col>
+<pba-flex center>
+
+Ideally:
+
+- Everyone runs their own node.
+
+</pba-flex>
+</pba-col>
+<pba-col>
+
+<pba-flex center>
+
+<div>
+Reality:
+
+- It takes a lot of disk, memory, etc
+- It takes some know-how
+- I don't need it _all the time_
+
+</div>
+<!-- .element: class="fragment" -->
+
+</pba-flex>
+</pba-col>
+</pba-cols>
+
+Notes:
+
+The bitcoin whitepaper clearly assumes that users will run their own nodes.
+This is the most trustless and decentralized way to operate, and you should do it whenever you can.
+If you think you can't you're probably wrong.
+Just ask the Monero community.
+
+There are _some_ reasons not to run a full node and the reality is that not everyone will.
+So even though we should always run our own nodes, let's look at some alternatives and ways we can make node running more accessible.
+
+---v
+
+## RPC Nodes
+
+AKA, trust somebody else's node.
+
+<pba-flex center>
+
+<ul>
+<li>🕵️ Spy on you (<a href="https://decrypt.co/115486/infura-collect-metamask-users-ip-ethereum-addresses-after-privacy-policy-update">like infura</a>).</li> <!-- .element: class="fragment" -->
+
+<li>🔞 Censor you <!-- .element: class="fragment" -->
+<li>🤥 Lie to you <!-- .element: class="fragment" -->
+<li>💔 Steal your boyfriend <!-- .element: class="fragment" -->
+</ul>
+
+</pba-flex>
+
+Notes:
+
+The easiest thing to do is just trust some expert to run a node for you.
+Very web2.
+Lot's of things can go wrong.
+
+So this is definitely not the best option.
+Let's see if we can do better.
+
+---v
+
+## Lighten the Load
+
+For resource constrained systems and people in a hurry
+
+<pba-flex center>
+
+- Phone
+- Raspberry pi
+- Microcontroller
+- Inside Web Browser
+
+</pba-flex>
+
+Notes:
+
+One of the complaints was that the node takes too much resources.
+This is especially true if we want people to be able to run the node in all kinds of exotic environments.
+And we do want that because we want people to run their own node even when they're just paying the bill at dinner from their phone or liking social posts while scrolling on the bus.
+Let's make the client lighter so it doesn't require as much resources.
+
+---v
+
+## Light Client Duties
+
+<pba-flex center>
+
+- ❌ Sync blocks
+- ❌ Execute blocks
+- ✅ Sync headers
+- ❔ Maintain Transaction Pool
+- ✅ Checks consensus
+- ❌ Maintains state
+
+</pba-flex>
+
+Notes:
+
+This is what a typical light client does.
+There is not a single definition of light client.
+There are varying degrees of lightness to suit your needs.
+
+---v
+
+## Trustless
+
+<img rounded style="width:900px; margin-top:-30px" src="./img/bitcoin-spv.png" />
+
+<pba-flex center>
+
+- Relies on full node for data
+- Does not have to trust data
+- State root helps a lot
+
+</pba-flex>
+
+Notes:
+
+The figure is from the Bitcoin whitepaper.
+The concept of light clients has been around since bitcoin.
+At that time it was known as Simplified Payment Verification.
+You could confirm that a payment was sent or received.
+But you couldn't confirm that the tokens in question still existed or anything else about the state.
+
+Chains with state roots can have much more powerful light clients
+
+---v
+
+## Syncing Strategies
+
+<pba-flex center>
+
+- Full header sync
+- Checkpoints in code
+- Warp sync
+
+</pba-flex>
+
+Notes:
+
+We also need to address the use case of clients that are not always on.
+For example if you only need your node on your phone, or when using a specific web page, that means it will have some syncing to do.
+
+Doing a full sync is already a lot faster than on a full client because you aren't downloading or executing the blocks.
+But by the time you have a few million headers, it does still take some time.
+
+The naive solution is to just have relatively recent headers hard-coded in the client.
+This works pretty well.
+You already have to trust the client developers for the entire implementation so you aren't trusting a new party at least.
+
+Warp sync is possible when you have deterministic finality.
+In dead simple PoA you just check that the authorities have signed the latest block and you are good.
+If you have authority hand-offs, there is more work to be done.
+You have to check that each authority set signs the transition to the next authority set.
+But this is still only even N blocks instead of every block.
+
+---v
+
+## Self Defense
+
+Stay in the gossip protocol or you might get got.
+
+<img rounded width="500px" src="./img/wanka.jpg" />
+<!-- .element: class="fragment" -->
+
+Notes:
+
+In the main gossip protocol, if authorities finalize two conflicting blocks, then we can prove that they have broken the rules and slash them.
+If we don't watch the gossip and only peer with a single full node, then our view is entirely defined by that node.
+They may gossip us an attack chain and we won't know.
+So it is important to communicate with many different full nodes.
+
+---
+
+## Bridges
+
+Transport layers between independent consensus systems
+
+<img rounded width="700px" src="./img/basic-bridge.svg" />
+
+Notes:
+
+Generally speaking bridges move arbitrary data between unrelated consensus systems.
+Basically between different blockchains, and those messages can evoke arbitrary side effects on the target chain.
+To keep it concrete, we'll mostly talk about moving tokens.
+
+---v
+
+## Source and Target Chain
+
+<img rounded width="700px" src="./img/bridge-source-target.svg" />
+
+Notes:
+
+By convention we speak of bridges as being one-directional.
+When we talk about trustless bridge design this is a core concept in the design.
+It is less critical but still useful for trusted bridges.
+
+A two-way bridge is really just two one-way bridge.
+Think of a two-way
+street.
+There is a dedicated lane for each direction.
+
+---v
+
+## Source Chain Re-Orgs
+
+<img rounded width="900px" src="./img/bridge-reorg.png" />
+
+Notes:
+
+On PoW chains this is truly just a judgement call and a prayer.
+If the source chain has deterministic finality we can do better.
+We need to wait for finality.
+But even this isn't foolproof.
+More on this after we cover the basic design.
+
+---v
+
+## Bridge Models
+
+<pba-cols>
+<pba-col>
+
+### Trust-based
+
+Trusted intermediary makes a transfer manually.<br/>
+Eg. Wrapped bitcoin on ethereum (WBTC)
+
+</pba-col>
+<pba-col>
+
+### Trustless
+
+Trustless is the goal,<br/>like almost everything in web3.
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+The trust based bridges are not at all ideal.
+You have to entirely trust an intermediary.
+You send the intermediary tokens on the source chain.
+Once the intermediary is satisfied that they really own the source tokens, they send you some target tokens on the target chain.
+Or they don't whatever, not their problem.
+
+You can make they trust properties slightly better by using a multisig or a group of people so you only have to trust some subset of them.
+But this does not fundamentally eliminate the trust agreement.
+One classic example is the WBTC foundation.
+You send them bitcoin, they wait for "enough" block confirmations, and then they mint you an ERC20 token on Ethereum.
+And they provide the same service in reverse too.
+
+A lot of the trusted bridge design can be improved and we'll talk about that in detail in the next few slides.
+But it's worth observing here that we will never be able to eliminate the part about "Once the intermediary is satisfied that they really own the source tokens".
+The bridge can never be stronger than the consensus on the source chain
+
+---
+
+## Trustless bridge design
+
+<pba-flex center>
+
+- Most trustless way to interact with blockchain<br/>is to run a node
+- This is true for individuals _and_ other blockchains
+- A blockchain is extremely resource constrained.
+- Run a source chain light client on the target chain
+
+</pba-flex>
+
+Notes:
+
+---v
+
+## BTC Relay
+
+<img rounded width="1000px" src="./img/btc-relay.svg" />
+
+---
+
+## Bridge Design Challenges
+
+<img rounded width="1100px" src="./img/bridge-collapse.webp" />
+
+Notes:
+
+Bridges present their own set of design challenges beyond what we encounter in regular stand-alone light clients.
+
+---v
+
+## Peers?
+
+<pba-flex center>
+
+- How can we peer without networking?
+- Enter the **Relayer** - a permissionless and trustless role
+- Need at least one honest relayer
+
+</pba-flex>
+
+Notes:
+
+On-chain logic doesn't have network IO, so how do we peer?
+There is a role known as a relayer.
+It is an off-chain agent who watches the source chain, and submits headers and finality proofs from the source chain to the target chain through transactions.
+Anyone can start a relayer.
+It is typically a little piece of software that you run.
+But there is nothing magic about it.
+You could perform the relayer task manually by copying header data from an explorer into metamask for example.
+
+You do need at least one honest relayer for the chain to get the correct header info.
+For this reason a large decentralized relayer group is nice.
+But even if you don't trust any relayer out there, you can always run your own.
+
+---v
+
+## Finality and Equivocation
+
+<section class="!flex">
+  <img rounded width="500px" src="./img/bridge-incentives-achiles.jpg" />
+  <img rounded width="700px" src="./img/bridge-double-finalized.svg" />
+</section>
+
+Notes:
+
+It is not safe to accept headers as finalized immediately even if there is a deterministic finality proof.
+Let that sink in.
+Even if there is a valid finality proof, it is not safe to accept them as finalized.
+Why not?
+
+Because the validators may be equivocating.
+They don't send equivocations to real nodes on the network because those equivocations will be gossiped around and reported on the source chain and the validators will be slashed accordingly.
+But remember a light client on the target chain has no way to report such equivocations back to the source chain.
+
+---v
+
+## Equivocation Incentives
+
+<pba-flex center>
+
+- Add a **Challenge Period** and
+- Add Fishermen - reverse of relayers
+
+<div>
+
+**OR**
+
+- Stake Relayers
+  so they can be slashed
+
+</div>
+<!-- .element: class="fragment" -->
+
+</pba-flex>
+
+Notes:
+
+There are basically two classes of solutions.
+Both of them require a waiting period aka challenge period before accepting a header with a finality proof as final.
+
+One is to add a role of fishermen.
+They are responsible for noticing when the header candidate on the target chain is different from the one in the main source chain protocol and reporting this behavior back to the source chain so the validators can be slashed there.
+Two problems:
+
+1. Fishermen have weak incentives.
+   If they do a good job there will be no equivocations and they will not get paid.
+1. Target chain is relying on the foreign source chain to keep the bridge secure instead of owning that security itself.
+
+The other is to have the relayer role require a security deposit.
+If it turns out that a relayer relays an attack header, that relayer is slashed and the relayer who reports it gets a reward.
+Relayers will expect to earn some reward for the opportunity cost of their stake which makes the bridge operation more expensive.
+
+---
+
+## Multichain Apps
+
+<img rounded width="800px" src="./img/bridge-multichain-stack.svg" />
+
+---v
+
+## We have a header, now what?
+
+<pba-flex center>
+
+- App users submit proofs
+- Need a source chain transaction?<br/>
+  Submit an spv-style transaction proof
+- Need some source chain state?<br/>
+  Submit a state proof
+
+</pba-flex>
+
+Notes:
+
+The header sync is just the foundation.
+Now Applications can build on top of it with the best possible trust guarantees.
+
+If you need some source chain transaction, your app needs to require an spv-style transaction proof to check against the header's extrinsics root.
+
+If you need some source chain state, your app needs to require a state proof to check against the header's state root.
+
+---v
+
+## Multichain Security
+
+<img rounded style="width: 500px; margin-top:-30px" src="./img/strong-and-weak-.png" />
+
+Notes:
+
+This kind of trustless bridge _with proper incentives_ gets us information about the source chain to the target chain with security about as high as it was on the source chain.
+If you are building an app that spans multiple chains consider the security guarantees on both chains.
+The weaker security of the two is the security your app has.
+More abstractly, your app consumes two different kinds of blockspace that may be of different qualities.
+Your app is only as quality as the lower of the blockspaces.
+
+---v
+
+## Example: Depository Mint Model
+
+- Send tokens to a contract on source chain
+- Message is relayed to destination chain
+  - Offchain relay and transaction
+  - XCM
+  - "Somehow"
+- New "wrapped" tokens are minted on the destination chain
+
+<!-- TODO really needs a figure -->
+
+Notes:
+
+The same process works in reverse to get the original tokens back.
+This can get get complex when there are multiple bridges.
+Are their wrapped tokens interchangeable?
+What if one of the bridges gets hacked?
diff --git a/content/3-Blockchain/Manual_Consenus_Activity.md b/content/3-Blockchain/Manual_Consenus_Activity.md
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+# Hands-on Consensus games
+
+In this activity students will encounter and explore blockchain consensus mechanisms such as PoW, PoA, and PoS by acting them out manually.
+
+Students will collaborate in telling a shared story. The shared story is represented by a blockchain with one word in each block. To add a word to the story, a student must create a valid block, and draw that block on the community whiteboard\*
+
+<pba-flex center>
+
+<img src="./img/bitStoryLive.jpg" alt="Photo of bitstory content on whiteboard" style="width:700px;" />
+
+</pba-flex>
+
+- If no whiteboard is available, you may be able to substitute; a paper, online drawing tool, or even a chalkboard if you are desperate.
+
+## Proof of Work
+
+The PoW phase is the original, and a working hasher tool is available here: https://joshorndorff.github.io/BitStory/bitStoryLive.html
+
+To begin we'll explore the Nakamoto style Proof of Work. To add a block a student must:
+
+- Choose a parent block hash to build on
+- Choose a word to add to the story
+- Find a nonce so that the block's hash meets the required difficulty
+
+The process of finding a nonce is accomplished by entering the parent hash and word into [the hasher](https://joshorndorff.github.io/BitStory/bitStoryLive.html) and repeatedly mashing the `increment nonce` button until you find a valid one. In this way students are manually performing the preimage search.
+
+The game ends at a pre-determined time. The winner is the person who authors the most blocks in the longest chain at the end of the game.
+
+### Attacks
+
+The instructor can encourage student groups to perform various attacks on the PoW network.
+
+- Censor specific words or plot points by forking around them.
+- Publish invaild blocks to trick other miners into wasting their hash rate on invalid chains.
+- Perform a hard fork where your block start to have two words each. Some students will like the two-words-per-block rule and keep building on them. Other students (ideally ones who don't know the instructor is in on the shenanigans) may think the two-word blocks are not following the rules, and choose to ignore them. Welcome to bitstory cash.
+
+## Formalize the Language
+
+Our previous story had basically no structure. Let's change it to specifically allow a small set of "transaction types". From here on each block will contain a very short sentence (can be abbreviated on the whiteboard) The following is an _example_ and your group is encouraged to make modifications if you like. The degree of formalization is up to you. The more formal it gets, the more it starts to look like real world blockchains.
+
+- Choose a fixed cast of max 3 or 4 characters
+- Choose a fixed set of a few locations
+- Allow one simple action in each block (a character moves, or does one simple thing)
+- Consider letting your characters affect your "real world" by letting them change the difficulty necessary for a block to be valid. You now have a difficulty adjustment algorithm.
+
+Play a few more games. This time each miner write down a few goals that they want to accomplish in-story (eg, bob and alice have a fight, charlie is elected mayor). This time the winners are whoever best accomplishes their in-story goals. Notice that in some cases the goals may al lbe mutually compatible, and in other cases they may not. In subsequent rounds, establish goals together. Try to play at least one round where there are incompatible goals. Miners may choose to form alliances (pools) and censor blocks that don't build on their allies' in-story goals.
+
+## Proof of Authority (Aura)
+
+In this phase, students will choose some authorities to act as block authors and a slot duration and they will take turns authoring in order. They should observe that this method is much simpler and less chaotic. It does indeed take less work.
+
+## Attacks
+
+- You can skip your slots to slow the progress of the story once it isn't going your way.
+- Censor plot points.
+- Publish blocks in slots in which they are not valid to try to trick other miners. This may be particularly convincing when the correct author is skipping their slot.
+- Polarize the authorities to work on two different forks
+
+## Discussion
+
+What attacks worked best in PoW vs PoA. What strengths and weaknesses does each have.
+
+## Proof of Stake
+
+One weakness of PoA is that only some of the participants are authors. We can improve this situation by allowing the authority set to rotate.
+Challenge the students to consider ways in which the authority set might change. What if the story itself is about who is elected as authorities?
+
+Notice that this is the foundation of proof of stake. The on-chain story is about people bonding and unbonding their security deposits. Formalize a new language around this story.
+
+### Mixed PoW PoA
+
+Some early PoS designs envisioned interleaving PoS and PoW blocks. Invent such a scheme, and try it out.
+
+## Grandpa and finality
+
+This one is a little different. Here we assume an external block production method. At first this can just be one student who is not playing grandpa, but instead being the sole block producer.
+
+The other students use a shared whiteboard to post their pre-votes and pre-commits and personal paper to track which blocks they have finalized.
+
+## Hybrid Consensus
+
+If there is time in the activity slot, we can combine any of the block production methods with grandpa. My personal favorite is PoW + Grandpa.
diff --git a/content/3-Blockchain/README.md b/content/3-Blockchain/README.md
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+# Module 3: Blockchain Fundamentals
+
+#### Prerequisites:
+
+Latest stable rust compiler. You can install [the entire substrate developer environment](https://docs.substrate.io/install/).
+
+## Learning Outcomes
+
+This module introduces students to the shortcomings of centralized infrastructure including censorship, equity, reliability, and trustworthiness. It then demonstrates through lectures, coding activities, and games, how a peer to peer network can achieve consensus on a shared history that is recorded in the blockchain data structure.
+
+The module is designed to 3 days of contact time lasting about 6-8 hours each day. Some out-of-class study is expected, and a graded assignment is recommended.
+
+## Learning Outcomes
+
+- Students will understand the goals of decentralized systems, the tradeoffs made to achieve those goals, and the place for centralized alternatives.
+- Understand the importance of agreeing on history to agree on a notion of a present state.
+- Students will understand the fundamentals of distributed consensus.
+- Students will understand the blockchain datastructure, why each piece of data is in it, and how it tracks the history of a shared state machine.
+- Students will be able to start a blockchain on their own.
+- Students will be able to write blockchain related code.
+- Students will be able to demonstrate how the grandpa finality gadget works.
+- Students will understand how to grandpa finality gadget work.
+
+## Hands on Activities
+
+- The primary coding activity is [Blockchain From Scratch](https://github.com/JoshOrndorff/blockchain-from-scratch/). Each student should close this repository to work through it in and after class. This will occupy 8-10 hours of class time.
+
+- Grandpa Board Game - TODO find the repo, it may have gotten deleted. For now the content was copied into https://polkadot-blockchain-academy.github.io/pba-book/blockchain-contracts/_materials/grandpa-board-game.html
+
+- Start a Blockchain and Fork Off - This activity is written up in [its own repo](https://github.com/Polkadot-Blockchain-Academy/Academy-PoW).
+
+## Schedule
+
+### Day 1
+
+#### Morning
+
+- 🗣️ [Coordination and Centralization: Past, Present, Future](./1-Coordination_And_Centralization-slides.md)
+- 🗣️ [P2P Networks](./2-P2P_Networks-slides.md)
+- ☕ Break
+- 🗣️ [State Machines](./2.5-State_Machines-slides.md)
+- ⌨️ Begin working on [Blockchain from Scratch](https://github.com/JoshOrndorff/blockchain-from-scratch/)
+
+#### Afternoon
+
+- 🗣️ [Blockchain Datastructure](./3-Blockchain_Structure-slides.md)
+- ⌨️ Continue BFS
+- ☕ Break
+- 🗣️ [Accounts vs UTXOs](./4-Accounts_and_UTXOs-slides.md)
+- ⌨️ Continue BFS
+
+### Day 2
+
+#### Morning
+
+- 🗣️ [Consensus Part 1 - Author Selection](./5-Consensus-Authoring-slides.md)
+- ⌨️ Continue BFS
+- ☕ Break
+- 🗣️ [Economics and Game Theory in Blockchain](./6-Econ_and_Game_Theory_in_Blockchain-slides.md)
+- ⌨️ Continue BFS
+
+#### Afternoon
+
+- ⌨️ Start A Blockchain and Perform Forks ([Repo](https://github.com/Polkadot-Blockchain-Academy/Academy-PoW))
+- 🗣️ [Types of Forks](./7-Forks-slides.md)
+- ☕ Break
+- 🗣️ Randomness in Blockchain
+- ⌨️ Continue BFS
+
+### Day 3
+
+- 🗣️ [Consensus Part 2 - Finality](./8-Consensus_Finality-slides.md)
+- ☕ Break
+- 🎲 [Grandpa Board Game](https://polkadot-blockchain-academy.github.io/pba-book/blockchain-contracts/_materials/grandpa-board-game.html) TODO Find proper repo
+
+### Day 3
+
+#### Morning
+
+- 🗣️ Maybe Rollups, and Blockspace vs Blobspace
+- ⌨️ Continue BFS
+
+#### Afternoon
+
+- 🗣️ [Light Clients Bridges](./9-Light_Clients_and_Bridges-slides.md)
+- ⌨️ Continue BFS
+- ☕ Break
+- 🗣️ Guest Speaker (Jonas - Economics of Polkadot)
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 125px; height: 1px; padding-top: 116px; margin-left: 609px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: #A45CF6; "><div style="display: inline-block; font-size: 15px; font-family: Helvetica; color: rgb(164, 92, 246); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><p style="line-height: 120%; font-size: 23px;"><font style="font-size: 23px;">Transition</font></p></div></div></div></foreignObject><text x="671" y="121" fill="#A45CF6" font-family="Helvetica" font-size="15px" text-anchor="middle">Transition</text></switch></g><rect x="602.07" y="62" width="104" height="38" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; 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\ No newline at end of file
diff --git a/content/3-Blockchain/img/blockchain-with-state-roots.svg b/content/3-Blockchain/img/blockchain-with-state-roots.svg
new file mode 100644
index 00000000..aa004c4f
--- /dev/null
+++ b/content/3-Blockchain/img/blockchain-with-state-roots.svg
@@ -0,0 +1,4 @@
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similarity index 100%
rename from content/blockchain-contracts/forks/img/BTC_header_constraints.drawio.svg
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wRFx8fP0JEAAACAAr//AHyArwACQAoAAAFIjQzNjIWFAYiAyI1NDc2NzY1NCciDgEjIiYnNjMyFxYVFAcGBxcVBgEWJCQHERISEQWdBIYpgmkrgkQiCxsEfnNTN21wPGJzGAJGAhUgFQEVMggKShpSNS8ZFwseDykUJklDUiwsIRcDAAIAG//7BBICqgBGAFUAAAEGIyInJjQ3Njc2MzI2Mh4CFxYzMjUmJyYnIg4CFRYXFhc+ATc2NzYyFhcGBwYHBiInIicmJyY1ND4CMzIXHgEUBwYiJyYjIgcGBwYUFxYyNjc2AlBrTSQUFw4eYTBCBAwZGRAHBw8iUQlaUWBUmnVGIHNBb1SZRZVoBw8bAgKUdqpYXQyKZ1YmE1GHr1+IYTJAHi6SQAQeIiRDEwYEBhYiIE4BVlsVFzkdQyIQAQ0aIA4hOlA5NAc9bZZZXy0ZDQcTFS1tAwsQUT4yGA0EJR4/IS1hrYJLOh9hdBwscBQRICULEQgIBA4kAAACABr/8QJ+AroALgA4AAABMzIWFRYnLgEGFx4BFxYXDgEiJwMFBwYHBicmNTQ+Bjc2Mx4DFx4BJw4CBzI3NjcmAiUcER8HNg8ZEAEKFw4kIBEtAwGN/u8KHSQGEyAqKy8qIg4FBQooKy8hIBsJJOwIOCIMRGMZFy8BbgYTKAEBAgEFHUgkWScVHAEBKUMqcy0KCAwIAnBzfnJbKR8LFxhNWFolDgLYPYBHHigLCckAAAMAHv/5AsQCqAAhACsAOwAAEzYyFhcWFxYVFAcGBxYXFhUUBwYHBiMiJyYnJjQ3IiY1NBM+AjU0JyYiBxMjIg8BMjc2NzY0LgInJkFKhGc0bhoHTTNf6VMuTFOBd2ZOOAIDCAcLEn2hzls8QdeOdRlSCgpagVQnFB0tNxooApgQCg4fNQsPLDMiIw03HSc2Oj4pJhdARJfPcAURGP2qCTtFICoZGh0BPBHJKx0jEiYZEAkCAwAAAQAW//8CwAKZACYAAAEmIyIHBgcGFBcUFxYzNjc2NzIWFQYHBiMiIyInJjU0PgIzMhcWAgpBT0tFVyEMAkM/YoZ7IiYOHWNEfmYHBm9PVDtnjVFFFRoCK0A5SHIpNg9jNTELXBoYCBNWJkRFSW1SlnNEExcAAAIAJgAGAn8CgAAUACIAABM2MzIXFhUWFRQHBgcGIyInETMyFgUmJyYjBwYHETI3Njc2aUp631IgAXVrnWhEHBQOFxwB1AlaQ2USX0VGabZEGAJmGm4qQQkJZGdhOygIAnAP0FkrIAECHP4jM1p3KgABAB4AAAJKAn4AIgAAATIXFQ4BBwYHBhYXFhUyPgEzFQUXMj4BMxQHBicGBAcTFjMBYWQhG141lDYRAgEERK9gM/6BBmPPazwMGBOw/uswBBpGAnsNMQQBAQMMUDoQJzUYCzcwpBMJFBIgDRMWBAJ+CAABACb/+AK7AnoAOQAANyY1NDY3NC4BNDYyHgIXFjM+ATc2MhceARUUJwQVFB4BMzI+AjMyFAcGMwYHDgEHBg8BBiMnIiNeOCYTJBAVKAwEAQMFGkOGQoRrHwEGIf31EgkGOXV1djkBAQMDK3ExZitjEAsLDiUFBaYIEg0iEjyVUkQSCxASCBMBFQsWAxMcCREFEztBXRgUFxQPCRgYDwcMBw4XxAsDAAABABb/wAKuAowAOwAABTUGBwYjIicmNTY3Njc2MzIzNzIHDgMUFjMyNzY3Nj0BIgYHLgEnJjc+AjcWNhcWDwEGFRcUFQYiAfBfJVZBTjg5BR08i0VaAgIbLgRQjGc7UD82YD0eDx7bEQUOAQIuC/JCFgoeDSACUxMCHjgxt0EVLzk7TFBSrlEpASQEQm+UmkQvHiYSFJQuAwMHBw8fBiMKAwIFAQEiIj2plRQRDwABABX/+gJKAtsALAAAEwYUFwcDJjU0PgU1Njc2FwMyNxE2MzIXFB4CFxYXFhcGIyYnJiIHBpsDE08kIyEQAwYFBRYKGQkG9zIGMgsHAwMEAgMCByotNi4DQjAePgEaIn1ZKAEQBRMOJhkfUFpQEBYFDRf+xSABPBEBE01ibTFmMHhKEnK5AgMEAAABABr//wBpAkYADQAANxQjIicmNDY3NjU2MhVpGBIZDAQCBh0mEBERG8yFOHoHEREAAAEACQAEAgYCdgAeAAABJzQ2OwEUHgEUBgcGBwYnJicmJzQ3NjMWFxYzMjc2Aa0DBQxDBgICCRU7LWJjS1gNDxsWAR5GmxoZMQFHvS1FEFxdQmk/kSIZDQ4sM0UXESA5JVQDGgABACsAAAJhAtAANQAANzQ+BTc2NzYzMDMUBgc+AzMyFRQOBBUeAxcWFRQHBisBIi4CJxUGBwYiKwUFAwMDBAQJDwguDhEBQXlpVhUjQGBxYEASU2dvLmgRBwcKMFRfeFUCEBc0DwQQQl1vdG8uZBMXJvQXIU1BKxsVMzc4NS4RCyUvNRs7Jw0FAi5ARRfIBAUHAAEANwAOArQCrgANAAATJxcDBRYUBwYjIiclNlACUAkCDxAPHSUJCv3nGQG1+QP9tg8FGA0aAgVdAAABABwAAgMsAqoAPQAANxcUDgEiJyI1NBI+Azc2MxYXHgEXEzYzMh4DFx4BFAYiLgYnNC4BBgcGBwYnJicDBgMGBwZ7BAEXIQkhLAwJBAgIDytITDYkEcgVCyAiFxENBg4PEiAgBwcKCgoIAgIOHRo4ag4XGxO4GBQDAQWnSQYgGQEdGAFTYkMgIAoTJKh4QAwBXA86U2RtNH1AGxkZJTxLU0w7DxQiCBspV84ZDg8+AYcw/vIhFxkAAQAZ//gCYALMACQAAAEQBycmJy4BJwYRFAcGIiY0PgE3NjQnPgEeARcWFxM+ATMyFQcCYBlJN4IzZSoUBBMtEgUHAwgCFhgeLyuTjhMLFhIjAQFh/tA0Bl+sRIZCWf71ZkYSCRUtajua30gUEhM/PtG3AfIUD0AlAAACABYADgKOAl8ADgAcAAA3JjQ2NzYzMhcWFRQGIyIDFDMyNzY1NCcmIyIHBi4YLylXg4lZZJmi4QrudUlJV0pxWkVEqDaScSlVP0iGpp4BLexGRXBpNzBBQQACACb//gJ9AmYAFgAsAAAXJzU+Azc2MzIWFxYUDgIHBiMHFBMUMzI+Azc2NSYnJiIOAgcGBwZTLQUGECQkQa5LaBk5OVtyOWZeBAMrBh5LVFUiTQ9oHzFDWDwDAQQMAgLpS3RUOREgHQ0cZFE7JgwU4AwBXTIBBQ8YEipBQRIGBRosHQwQMwAAAgAbABYCtQJ6ACAAQwAANzQ+AjM2MzIXFhUUBwYUHgIUBw4BLgEnJicGBwYnJgUyNzY3JyY9ATQ2Mh4CFzY3NjUmJyYnJiIjIgcGBwYVFBYbLFZ+UgwMgkpDRAEdKx4BCyYNFgobFCZPyH5RATI8GTYVtwEcKTEuLRgzAQEFDBhhL1QIPjQpHRl29ECRcEQBTkd0cmEFFRYSFBEFCAkDDwkVAyQaP2pFRQULI6YBAgUSCSArLg5OXBwjJB09Ewo6L1NDOWhZAAACAC7/9AKrAocALwBBAAATNjMyHgEVFAcOAQcGBxQeAhcWFx4BFA4BKwEiLgEnJicVFCsBIicmNTc0JzYXFgUnIgcGFBcWFxYyPgI3NjU0djeQWno9gBOhHD0UCB48NZ6nCBoQFgwUFH9dMHFCIgsVCg4DDRgjCAFXQeIiCgIFEgMPKUVOJHECUjUkKBg3Ngk3ChcNBQcRHx1WYgYVGQoFVkAeSRblFBUgVsmUcCksChMBNA4rECkSAQgVHhAzIBIAAAEAD///AnACYAAzAAA+AjcWMzI3Njc2NCclJicmNTQ3Njc2Nx4BFxYHFAcOAgcUHgEXFhcWFRQHBgcGIyIuAQ8fEQMFdl18WB4KA/5hEhEfYmy1KRQGGQ0fBYKoUyUBLkAzfLQKPkZ8Zz0zXC5qHQsDWzooKg0RBV0EDRYSRTg9HwcBAgMDBxMiFBkiJBkFDBEOIjQWEzUxNyYfJCIAAQAAAAACfgJEABwAAAEnIgcGBwYUFwcTJyImNDYzFhcWMzc2NxYXFhUGAepZIy4CBhUCXh/VCAkSDElKiWA+SUgQBAFCAesCByc+3IMbBwHuDBoWGgMHDAICDgMvCgYTAAABABT//gIWAmMAMgAAJRQjIiYnNwYHBiMiJyY1NDc2NzYzMDM2MzIVFAcGFRQXFhcyMzI3Njc2NzYzMhcWFQMUAg4fDxkDClwqQkUNDpIoDQQDCgwFBCANKCIWLwYGozMeBQMCCxMTFwMKEBIJA4BPFCEBEKtOuzowAQEwITGhPkElGAWdXII8Ox4ROjj+gikAAAEAC//8AnICoAAYAAAlJgInJjU0Nx4BFxYXNj8BNjc2MzIVAQYiAQUbkhg1MyM9HkctEDhSQhMjGBj+5BE1EEgBHS9tEw0UQYE5izUQeK2MKyoq/ZELAAABAA4AAAOzAvYAOAAAJTYTMhceAQ4CBwYHBicuAScuAicmJwYHDgEHJwMmNDY3NjIeBhcWFxI2NzYzMhcWFxYC+zJCPwMBAQgPFg4iJCQUCQ4JDUYrFC4fJFwQGgk++gIHCREiDwkGESEmJhEkCXQ2BwsGK2YcGDumogGuJwwKO2qMTLN7GREJHxQRklYlUw44+yxLFwMCQgUKCgQGDRQYJkpSUSJLCQEeawwRwDMvcgAAAQAbAAECTwJ3ACEAACUOAyImND8BLgQnNDc2HwETFwMeAxUGBwYiJwEqGi0vND0YAb40Ry4ZCwIbFxHA7zrwIldMMwMSBBQU4RVIRDIRGwjhQFo6IQ8EFAgHCegBGi/+4y5BOTonFwgCDwAAAQAc/+4CEgKZAB0AAAUiJyY3Nj8BNjcBJjQ3NjIWFxYXPgMWFw4BBwYBFhASIwcMExsODv71BwgNJScdOYI7NB8ZEgQfOR5PEgoVEBU/Wis0ARAJDgQGDBgwm6xjHQIEDEKnWewAAQAc//0DAgJXAB4AACUGIyA1NDcBJiIGBwYHIiYnNiUyFhUGBwYHFjI+ATcDAvfP/uAKAbAoM0AykzgPBwLfAR4OGhylwh83lJikShATJQgIAeICAQQMAxIhGAoIEU6wzikLCQ4FAAABAB//rAGWA0IAGgAAEz4BNzYzFBYHDgEHBgcGFB4CFSUUHgEUBwUfIU8pZy8FCxJEJFgZAQwUEgD/BQQF/rADCwUSCRcNHAYFDQkUEiBckrCwXSMFFhkUATUAAAEAAP/+Ae4CWAAQAAAFAgMmNTQXNDYzHgMXFAYBuvKsHAodDzpmZ29CIgIBEAEOLQIBDxMIOZSakTYUGAAAAQAA/58BywMzACkAAAEQEw4DBwYjIjU2MxcyNzY0JicmJyYiBgcGIyInJjQ3ND4BPwEWFwYBoygJOk1YJ00cAzIuFG0pGAcHDRYLJj0jYTADCBQJ/EcaHh4FBAKS/sr+XwEFBwYDBjcDATAbh6dVrZoBDAkZBQ4gCwIkCQQCARJCAAEAEgH+ASwCrwAXAAASJjQ2NzY3FhcWFxYUBwYnLgInBgcGBykXFRMqPjMRHCQGBAsZJQ0YHz0WBwYB/gomJBQsHSEOGTgMFQYQDxsMGh4qJAwOAAEAIAAAApgAdQAMAAAzJzU2NzY3MhYVFAcEIQFZwttbDhkR/qsSFCQLDBQIDxUXCQAAAQAvAe4AlwJoAAoAABM0MzIfAQcmJy4BLw8JDUMRQgwEBQJMHA5BKy0UCBAAAAIAEgAGAfUBxgAeADAAACUGBwYiLgEnJjUmND4BNzY3NjIXMhceAhcjLgEnJic0IyYjIgcGBwYVFBc2NzY3NgGkS30dLx8mECUEFDUmT1wbLRI6FA0FBQo7BAQCBQs5BwdJUSYbKERaUiMXIKZ2HAYBCAkVJhItSlYkTBYGA08ys2EoGyoSKro6AUYgKDktOwsCUCMpNwAAAgAeAAcCKwLnABwALgAAEyc0NjIWBxM2NzYzMhcWFA4CBwYHJgYjIicmNRcUMj4BNzY3JiMiBwYHBhUcASEDFiAaAwc/a1lDOyAYJTxOKExKBhwUNikKVik8VStkMw1BO0ppLRMCRIEQEhEP/lBUOTAmHmNJQzoXLB0CAg1fwtwLECcfR2A5LD9dJSYKDAAAAQAWAAACbQG/AC8AACQ2MhUUDgMHBiImJyY1PAE+ATc2NzYyHgEXFhUUBwYHLgEjBgcGFRQXFBcWMjYB2E5HBTFHVChTRlEjUR48KFRcICscHgsaIgkHBRAbdlVgATEldVZ6HBYFFR0aFggREBIqUgYkQ0McPBIHAQMGDSYYFwYFFyAZMjk/BwhAGxQbAAIACf//AfQDIwAhADUAAAAOARQXFAYjIj0BBiMiJicmND4BNzYzMhc0Njc+Ajc2MwEUMzI3Mjc2NzU0IyYiDgEHBgcGAfQLCQ4RFC+OYidRJAUTOypcay4qBQMGBAcHDyX+XjkJCyk8chk5BxcwPB09FwkCw7evxW4XFE4haiY6GDJHTB0+DhJaMoIvIQwZ/XpPAhgtIYUjAQoaEyk3FQACABQABgIJAdMAIQAvAAA3MjcyFhUOAScmJyY0PgIzMhceARUUBwYHBiMnIgcGBxYAJiIGBwYVFjMyNzY1NOdYsQsOKOJibxgCIVBsPTpIIigBAjkZIZBIJhYJGQEDMCBIHEVQKG8nGEZQDwpETBkdYBNAaV42KBMwGQcHPRAHBh8RIlsBRQ4VDSAjBxMKDxIAAAEADgAGAmADPgAmAAABMhQXBRcnNCcHIicmNTcmND4BMh4CFRQHJicmIyIHBhQWFzI3NgJZBQL+qRJRFIINCRCYFCRFTlFKNAUoOUQ8ORMJCBQ+TZQBTjYKKt4EWnQyDxoVNqzXeCkiNEEfGAo4LDRRKpl/QAsXAAIAF/5RAfsBrwAmADkAAAEnIgcjIicmNTc2NTwBNRM0JwYjIiciNT4CNzYzMhcWFA4CBwYDJiIOAQcGFRQXFjI+Ajc2NTQBPA4eIiY8IhLmagUBopYNDUMCMk8yTUhUNhAGFSIXJgkMK0Q+G0IJBxUoRUoeRv5UAQQXDBgLA28EEyABQhELlwE7Lm9nKT9Z7siAaj4OFgMSBCQ5I1YzEAgEBx0uHEA9JQAAAQAX//0B8QKcACYAACUGIjU0JyYnJiIOAQcjNjQmJyY0NzYzMhYXBxQXNjMyFxYXHgEXFgHxCUsFCR1IWzsfB00CBAMFCAoTFxoBBQlaYB8jSxcLBgEGDhEbdixhBw43f3M5YodQXH81EyENpV0uPAUnLBc0IXIAAgAYAAYAiwKBAAgAEwAAExYXBiMiJicRJzQzMhcWFAcGIiZ1DQkGKgsXAx4pGxEDCAggIAHWu/YfCQgBv4gjDAsVCgoPAAL/jv6RAK0CwwAiAC0AABcUIyIuAScmJzQ3NjUeATMyNzY1NCcmNDcmNzYzBhQeARcWAxYVFAcqASc0NzatWAkbNRtBEgUJIUwrHREQDhQCAxkTFwkBCwcRPxASAQ0PDwbIpwEHCRYqAwsUAxksKiQkYZvpfygYDAk+SE2USqEDKAsYGAUNIA4FAAEAHv/7AmQC2wAtAAA3FxQHBiInEzQmNTQ7ATIXFhcWFz4CNzYzMhcGBw4BBx4BFxYXFAcGByMmJyZ+BSYIFg8BEyIIBwIPBQsJEXZIIEsTEAkyby1ZJUN4OIFdBQkcCD1lx7ZXUBEDBQF2UaNRIAE+WMNDCVQzFjETP00fPSESJxAmBRsIDgIRFSkAAQAW//8AgAKqABAAABIuASc+ATMyExYVFCMnNC4BKwQBEAkRECMTCkAIBgMBulUpUAwW/tmrqy4BNKJ4AAABABr//QMWAcsAOwAANwYiJic0PgE0JzQzMh4BFzY3NjIeARU2NzYzMgcTFAcGNSY1NzQnDgIHBhUGIyImNzY1NCYnIgcOARRuKRsKBgUEBisKCwUCGk0pSDcnGltTQl8CFR04AQUWQkc2FS8GIRYcAxMTDpAyFgUQEQYLIWRydDAgSCgJLxsNES0lMSclSP6MBQIEDhQUoXFCBSExKVyYFQ8GajsvVTdzM1k/AAABACL/+gHjAfMAKAAAJTQnNiMiBgcGBxEjJjU0Njc2MzIVFAYVNjMyFxYVBxQXBiMuAScuATUBoQ0IICJsIlEJQw0LAxoQGQWiWWUOBgECCgYDFBAKAtt3OA8iEScl/vAinYyECRE7FysId6M5ZU8sKQYBBAEoUyMAAAIANP//AjABwQASACMAADc0NzY3OgEXFhcWFAcUBwYjIiY3FBcWMjY3NjU0JyYjDgEHBjRmUXIGLCVSHgwBX1iEX2FFIRl2WiNLICM5J08jTL52SDkMDRxHHCcIfUhCWE8+FhASFjBlPCYpBxAXMQACAD7+ggIhAcAAHAAsAAATNjMyFxYVFAYHBgcUHgIXHgEVFAYjIiMDNh4BBSYiBwYHBhUUHQE2NzY1NHuIY34qEz80ea0BAQEBAwMgGgUFEAkeEgEoIUslVCgSzlYyAZEvQh8kMmorYxgLMTxEH00WBxkZAyQNAg41EQcQNxomBAStLlIvMjUAAgAk/p0B9AGQABgAJwAAAQcjAwYHBiMiLgI1ND4COwEyFhcUEhcDNCMiBwYVFBc6ATY3NjUB5RsXDydPSDkuPR0BOGh9Ow4dMBACC2QUZVFWNg8xRhxC/p4BAbUlGRcaHyIKOm5YLioarv6urgKALztBYTACDRElSwABABv/9QIiAeIAKQAAASYjIgcGBwYVHAEWFQ4BIiYnLgMnJic0MzIeAhc2MzIXNjIXFhUUAgYqQj41ZCUQFBUaEg0IAQYJCwULBiMVGA4FAoTEFhgGEgkLAW0eFypCHiIGN10wAQgQFwY4UF8uZC8YIy0sCXYBAQwOFDIAAQAW/+MB3wHKACgAAAEyFRQHBgciLgEnNjc2NCIHJicmND4BNzYzMhcyFhUmIyIHBgcUMzc2AXFuPVuaBxEJAnNKMnZyNCYhJDwoYmkfHRgIO0pcPD4CKUleAQI4KjhTMhwPAiY2JC4cAiMfPzUuEy8GKjAbJSQ6HAgUAAEAEP/xAZMCqAAdAAA/ATQnIyczETY3NjIWFxYVFBc2MzAzMjcHJxMGIyKyAgebApYDCQ4TDggQAyAgNBMQA5IFEg0yYKAmG0UBAgkJDgQMQoUhIAQCSAT+pwgAAQAN//8B6QG5AC4AADc0LgE0NzYzHgEUBwYVFBcWMzI3Njc2NC4BJzYyHgMUFwYjIicGBwYHBiIuARYFBAYNKRwTCSEDEF4xLFQeCQUHAQ0ZGxMGAQQMCygTDR9CWhEqPziFEDlERh1BCBgjGldGFxpDER8qLkU2QScGGkhhaGEjC1ALECQMAhA6AAABACL//gIEAeYAGwAAEyY0PgEWFxM+Azc2MzIWFBUOAgcGIiYnJiQCChMXB6gIIy0xFTAJFRM4Xx8MFSg0IToBgwUNFhABDv7IDEFSWSVVHxADes49Eh8/NWAAAAEALv/rAxABxwA1AAABDgEHBiMiJyYnJjU0NhcWFxYfARYXNj8BNjc2FxYXMj4BNzYzMhYUFQ4DBwYHBicuAScmAZcWHQ4WHA8TLlRSFg4iDgcKGSopFhQfKCAZfTUNCRkTDiErDgsMGh0dDiEWESYRJhUzARRJfCk7DjGopCkSCQQKFQoZPmlXIjZWcQIQwVIQeFMkVBMMAyJXW1kkTgYILxY8IFAAAAEAEv/9Ad8B4AAvAAA3PgE3Jy4CLwE3HgEXFhc2NzY3MhYVBgcOAQcWFxYXFAcGBy4DJwYHBgcGJyYaMWQLVBAeGAcHOi0rDRYqDiQ8JBccGjESHgk9VRMICxENEykuMRsXKUsZEyMJHjF+FVwRIhoJCD43OREcKRQ0WSsgDjg+FikYK2cXDAcOGAYJLzg4EhoxWhIEFgUAAQAW/lgCIAHXACAAABMGIyImNz4BNyYnJjU0PwEWFxYXPgI3Njc2MzIXFhQH7hUdDg0GFlMOI0uaASZPfyATFRgPDSI8CQoZCwQC/ocvGRFd7ikjadgVAQEmSa8sHio9JR9TgAQNBQ0GAAEAE//8AfQBsQAuAAAXIjU0PgE3NjcqAQYHBiI1NDYyPgI3NjcWFRQHDgEHFjM3MhYXFhUUByYiBgcGimRYQh5HLQkkRSZnQCcRCRYpI0WTMEY+jRwnHaQmPgcQBBk2WD5VBCwcWjkbQTcFBAsOERwCAwUDBwwGHSVHPn4eAwcHAwkZCgwDBgUGAAEANP92AbMD8gAzAAAADgEUFxQOAhUGFBcWFxYyMwYUHgMyFwcmJy4BJy4BJyYnPgM3JicmNDY3NjMVJgEHFwwKHyYfAgsaMhUJAQYJIS8vKQoEqCsWCgUGJhU5CQUgJSQKAgQGCxMqaikDoDRdknEVGxcYEwUREicgDTtNWUwjDQNIC30/mC4MHBEuKiUpGxkXJjA8YFkmVDYDAAEANP+6AG8D1AAHAAAXIyIHAzMRFGcaEgQDO0QCBBr76gIAAAEAGP8mAakDjgA1AAAXJzYyNjc2NTQnOgE3Njc2NCc0LgI2NC4EJzUyFxYXFhQHHgMXBgcOAQcOAwcGHAQKKzAZRQYBChU1GwkCIScgAQ0fKiomC24/MBEJAQooKiADAj8YLAYFBg4bGznaSAMNEjGgLjsNHyoPEAUTGBYbNlp0WzIbCAQ2Uj50NWcZFyEfIhcyMRMZBy1bVUocPQAAAQAaAeYBsAKOAB4AABMiByImJz4BNzYyHgIyPgI3Mh4BFAYHBiMiJy4BlCA2BhsDDzwhCBQdJCYrGRUZFwYXARASM0AuGxQcAjdRCA0wSg0DFSYiDhomGA8PFiUTMh4SF///ABf/TwB9Ad8QRwAEAAIB2T9Y0eQAAgAV/7oCbQI6AC0AOQAABSMiBycGIiYnJjUmNTQ3Njc1Mwc2MzIVFAcGByYnJgcRPgE3NjIVFAYHBgcVFCcyNwMGBwYUFxQXFgFaGxMCARwyUSNRAVFRcTsBIxRZIgkHCRYNMh88HURPOydMXWQZEgGQKAsBMSVEAkoEEBIqUgYHSkxNIop9BD8YFwYFLQcEDP7aCRkMGhYZIQ4aEFACggMBIThGEx0HQBsUAAH/6gAAAhgCVwA9AAA3IjU0PgI3PgM3NjMyHgEUIicmJyYiDgEPARcyFxYGDwI+AjIXFhceAQcOASYnJiIOAQcGIyIjNjcdMxgcLhEDBxMiHk87SF8tIyMZKzg8MzIOD1MpDAQMEm8bKDwzLxoqVgYGAwgrHxM3SRwXCytJCgsPBfYZDgoEBQM/XD8mChouPCYjGg4SDy8sfAEXCRQGAcAHCwYEBxsCDQcQBgcFDgUIBRBDtwAAAv////sCWAJEADQARQAAJQYjIicOAQcGIiYnJic3JjQ3JzcWFzY3OgEXPgI3MhYVBg8BBgcWFRQHFAcWFxQHBgcuASUUFxYyNjc2NTQnJiMOAQcGAcNVgC0iCC0KDwoVDR8HVyhAUEg0HkVaBy0jCikVBx0hBxAZCAUtASkvKA0WDxcx/o0hGnVaI0sgIzknTyJNbz0JCCQJCwQFCg9LLLpAT0M4IiUJDQ0wGQcjDwwZJQwHMjsHB00/LDAJDhoHCS99PhURExYwZTsmKQYQFzMAAf/2/+4B9QLGAEgAADc2NzUHIgYnJic3Nj8BASY0Njc2Mx4DFxYXNjc+ARYXDgEHBg8BPgE3Nh4BBg8CNjcyFhQHBg8BBgcGJyYnNjcGIyI1NDZ5XS9vBQ8IEwIUAooB/vUFCAwZDRAZGR4XIWVSMBAZGAUQKBU1GgIXKBIQEQMJCWUDOj4XDAJSSQgDCxoWDAIIAks7GA26DgUrDgEBAw4kAg8tAREHCg0GDwwRFB0ZI3jwKQ0CHQwiTCprSBkDBQMFChMWBg4tBw0YEggCEaIHCBMNBhYPfA8jBA0AAgAcAAgAbgI2AAYADwAANxMzAwYHBgM2NyY2MhYXBxwIQggCGhoDAwQCFBkTBAgQARL/ABIIBwE5dWUWDAQO6gAAAgAKABgB7gK/ADYARQAAATIVFAcGBx4BFRQGBwYHIicmJzY3NjQiByYnJjU0Ny4BNTQ3Njc2MhcyFhUmIyIHBgcUFjM3Nhc0IyIGBwYHFDMyNzY3NgF9cUEjMD8xQDBviAkTBAKCXUh3bDQmIWIhJUJkkQ4tHRgIO0qMOhEBGRBJWUQvJlsjTwkoCwxdRUoB9zcsOh8dBicXHUEbPgskBwIWLSMnEwIjHyNDOg80GjMzTAwBBiowG04XHxEKCBRaHCAVMDYaAR4tLwAAAgBCAlUBKQKYAAoAFAAAEyI1NDcyFhQGBwYzIjU0NzIVFAcGWhgyFQ8MCQxzGDMkKgsCVSIMFRIcDQMFIg0UIh8BAQADACb//gJnAmcAEgAlAFAAADcuATQ+Ajc2MzIXFhUUBwYjIicUMzI2NTQ1NCYjKgEjIgcGBwY3NDU0PgIzMh4BFAYHLgEjBgcGFRQeARcWMj4CMhYUDgMHBiImJyZ0JCoYJTUiS1+ARD9fXZpZV8CKi3JjCxEHNTQxIyBDKERJHgcaHRUIAgoQQTM3AQ8NFEQxLi0eCwMcKTAXMCcuFC8sF0VQbl5YIkleVX6VU1C5h46DBARzekhCZ14PBgYqWUkmARE2GAkUHBMuMjcGJiUKEhcdFwcPFBkWEwcPDg8l//8ACgB/AOABcxBGAEQDfBwsIrAAAgBUADsCmQHqABoANAAANz4BNzY3MhcWFA8BHgEXFhcOAQcGIy4CJyY3PgE3NjcWFxYPAR4BFxYXDgEHBiMuAicmVCBWLGwvDQYDBOsPOCJRPQEGBAkCHnBEHUTYIFUtaTENBwYH6w83IlwzAQYECQMecEMeROUZRCJVGhYJEgazCBkRKCgBDggVEycbDiI7GUUjUR0CFRMOswgZES4hAg4IFBMnGg8iAAABAEkAeAJLAWAAEwAAAQYdARQHBiInJjU3BTcWMj8BNjICSwUJDhYJEQP+RwMQPTx/UncBVTcXISNKAQIFKmgHQQEFCwYAAwAm//4CZwJnABIASwBbAAA3LgE0PgI3NjMyFxYVFAcGIyInFDMyNwYrASImJyYnFRQGIyImNTc0JzYXNjMyFxYVFAcGBxQWFx4CFzY1NDU0JiMqASMiBwYHBiUiBwYUFxYXFjI2Nz4BNCd0JCoYJTUiS1+ARD9fXZpZV8CeRgYHCgk3JF4vFAMRBwIGDRcdSi0lO2BrDQsZWX0KAiZyYwsRBzU0MSMgARVuEwUBAwkCCiMaPTIYLBdFUG5eWCJJXlV+lVNQuYdfASIWPBBuCAEpIHEvNBkjGgoOGR4fIwcDBgwsQwcEQGAEBHN6SEJnXsIYBxQIEwkBCAkUHhEEAAEAHgIWASsCYwANAAATIjU0PgI3MhcWFAYHUDIXOVcwKgsBCRICFhkOCggPBRcECQ8GAAACABkBDgDFAbUADQAbAAASJjQ3NjMyFxYXFAYjIjcmIyIHHAEXHgEyNzY0KxIMFSc0Hw4DKSoeQhcaHwYMEhQRCg8BLB42FCEqEhczIWQYHgMTFA8CCAohAAABABL/+wIFAfUAMgAAFyI1ND4CNy4BJyYnIgcGByImNTc1NDMyHgQVNxQOAgcGFBYXFhc2NzIXFhQGB3ozFx5KLAIEBAkNGyVLHAwNwCMRCgYGBQW7BCJNSQMDBQwBUUYpCwMJEgUaDQoFDAgVNBo7JwsWAR0PKKYTDR4mKiYHFRcWDAoNDhcfGUQfDgoXBAkQBgD//wAJAK8BZQHeEEcAFQAAAKon+iGj//8ACwCqATAB7hBHABYABgCsJkMkxQABABkB8gCPAnAACgAAEzYzMhYOAQcGBydeDhAKCgIICRE0HwJdExMSEAsTKxwAAQAh/5IBygG+ADkAADc0MzIXBgcGFBYXFhcWMjY3NjU0JjQ3NjcWFxYUBwYHBiInJjU0BwYjIicmJwYVFxQHBiInNjQmJyYhKw8WAQQHAQgZQS9YMAcIDwEDGxcNCAEBGgMOEAMCLD88OTMQAQQYBhQMAQICBuLcFCYfPzgnJygbFCUcLhwwaxsIFgYXWjtnG5MHAQkCEyUCIxoXGwsKWD8NBAQFFy4ujAABABL//wFtAeIAHAAAASciAhUHIgYnJjc2NzY3JicmNDc2MhcDJyI1EzQBOQsGBAEGFAkWAgIBAgFdNU5GMY5WDygCBgGoAv6XHyABAwcdGi9gCxIgMW4fFhv+OAMgAWYgAAEADwDIAGYBGQAMAAA3PgEyHgEXFAYiJicmDwUYDhIYAhQaEAgR8BgRAxcQGA8FBQwAAQAr/xcA9QAcACUAADc0MzIWBxQWMzYyFxYVFAcGIyInIjQ+AScWMj4BNzYnJiIHIjUmLwwMEgQCEhYzGygvKTUbHwMBAQILIDQwDBo4DCogIgEIFBsDGyoCChAlKCAdCgoODQIBCRMLGAgCA2wJ//8AGgCSAFsBtRBHABQABQCOMbQhTf//ABcAkwEAAYIQRwBSAAAAlB0uIegAAgAyADACjgHZABQAJwAANyYnNDU0Nz4BNyU3HgMXDgMXJjc+ATc2NyU3HgMXDgN2LQVHaUAG/vgyMVNNTCkaT1dVxFhBIV8ZOwj+9zIxU05LKhpPV1UwERMEAx8qPTEXYzEjHBEXHx8/QkQHIjMaNhEmHWMxIxwRFx8fP0JEAP//AA3/+AIYAqkQZwAUACsAlS1bHhIQJgAS+PgQRgAXehcm3yRF//8AFwAAAh8CsRBnABQABQCNMRYePxAmABICABBHABUAtwAJKFUl4v//AAn/7ALLAp0QZwAWAAIAkC0NJ28QJwASALX/7BBHABcBCwAYKigpHP///+IADQF9AtoQRwAiAYUC1co7vv3//wAV/+wCeQNjEiYAJPv7EAcAQwDOAPv//wAa//ECfgNvEiYAJAAAEAcAdAC1AP///wAa//ECfgNVEiYAJAAAEAcBOgCMAKb//wAa//ECfgN1EiYAJAAAEAcBQABqAOf//wAa//ECfgMvEiYAJAAAEAcAaQCMAJf//wAa//ECfgNDEiYAJAAAEAcBPgCsAPgAAgAeAAADdAKoADwARwAAASciBwYWFxYVMjc2MxUFFzI3NjMWFAcGBw4BBzUmLwEHDgEHBgcGLgE0PgI3Njc2NzYzMhceATMyFxUGBTc0JwYHMjc2NyYC24tFLhMEAQNIPXhA/ssFc0eBVgQHEyFv3GEgAhmwBA0JFhsGJA8UJC0XNhsVGB0XLhcgaDiRKhb+ZAQIfRgsHDUfAwIvAwpYMhAyKggQNiakBgsCDgkZBwwOCAMFAvIaDzUdRyIIDQoaTWdzNn8qLhccKggCEDIDzH84MLdlBgwBDv//ABb/HgLAApkSJgAmAAAQBwB4AN0AB///AB4AAAJKAxwSJgAoAAAQBwBDAIwAtP//AB4AAAJKAycSJgAoAAAQBwB0ALsAt///AB4AAAJKA1USJgAoAAAQBwE6AH0Apv//AB4AAAJKAuQSJgAoAAAQBgBpZEz//wAI//8AcAL5EiYALAAAEAcAQ//ZAJH//wAM//8AggLaEiYALAAAEAYAdPNq////x///AOEDExImACwAABAGATq1ZP///9H//wC4ArcSJgAsAAAQBgBpjx8AAgAKAAcCogKAAB4AMwAANyI1ND4CNxEzMhYXNjMyFxYVFhQOAwcGIyInNRMRNjcyFxYGDwEVMjc2NzY1JicmIjwyFxMNCA0YGwJKeuBTHwEhQ1xmNHpXGxNUISMqCwQMEl9GabZEGAtZQ9DCGQ4KAwECAYUPCRpuKkEILE5QRzwWNQe0AWL+4gYDFwkTBguEM1p3KipaKiAA//8AGf/4AmADihImADEAABAHAUAAYAD8//8AFgAOAo4DBhImADIAABAHAEMA6wCe//8AFgAOAo4DBRImADIAABAHAHQBCQCV//8AFgAOAo4DGRImADIAABAHAToAugBq//8AFgAOAo4DHxImADIAABAHAUAAkgCR//8AFgAOAo4CyRImADIAABAHAGkAogAxAAEATABJAZoBqQApAAA3BgciJic+ATcuAjU3HgEXFhc+ATc2NzIWFQ4CBxYXFhcUBgcuAScm+WAXFRgDK0EIIzEmKiEfChEdChgOHxsRExMwFQYuOg4GGQQOHhEr0XMTEgUrUw8mOCkBLigqDRcbDSUULiEXCyk9HRIhSREJChkCByIUNgD//wAW/98CjgKQEiYAMgAAEAYAElrf//8AFP/+AhYC0xImADgAABAHAEMAtABr//8AFP/+AhYC/hImADgAABAHAHQA3wCO//8AFP/+AhYDLhImADgAABAHAToAkAB///8AFP/+AhYCzxImADgAABAGAGl0N///ABz/7gISAxISJgA8AAAQBwB0AOMAogACACEAAQH4As8AHQAuAAA3FCMnJicDJjQ2MhYHFzY3NjMyFxYUDgEHBgcGIic3FDMyNjc2NyYjIgcGBwYcAWodEQoFCwEXHxoDBT9eQjU+HxQmPylUWBwnDQgdIlolWDIOQy8xYScPGRgEBQsCkAQUEhEP+VMxIzEgY01GHTsUBgJQDycbP18/HTlYIy8OAAABAEn/bwKkAqMAMgAAEyIHEyM2NC4BPQE0Nz4BMh4CFRQGBxYXFhUUBwYHBgcnPgI1NCcmIyIHJzY1NCcmI99SCg9ECwcJIBJXSl9yO3d351UuSlN/Pj8Hc5E9MER2O0oE8VU5QQJnEf0ZRsO9xikzHBUMDwcmOB0sWSkNNh0oNjc+KhUKThA4OholFyEJaTJDLxYPAP//ABIABgH1AmgSJgBEAAAQBwBDAKMAAP//ABIABgH1AnASJgBEAAAQBwB0ALAAAP//ABIABgH1Aq8SJgBEAAAQBgE6YAD//wASAAYB9QKOEiYARAAAEAYBQB0A//8AEgAGAfUCmBImAEQAABAGAGlOAP//ABIABgH1AiISJgBEAAAQBwE+AJr/1///ABL/9gOrAcYQJgBEAAAQBwBIAaL/8P//ABb/FwJtAb8SJgBGAAAQBgB4fwD//wAUAAYCCQJoEiYASAAAEAcAQwCzAAD//wAUAAYCCQJwEiYASAAAEAcAdADAAAD//wAUAAYCCQKvEiYASAAAEAYBOnEA//8AFAAGAgkCmBImAEgAABAGAGlfAAACABwABgCLApwACQAUAAA3DgIiJicRMxYDNDMyHwEHJicuAYsDGhAOFwM/DWYPCQ1DEUILBQUlEA4BCQgBv7sBZRwOQSstFAgQAAIAIQAGAJcCkgAIABMAABMWFwYjIiYnETc2MzIWDgEHBgcndQ0JBioLFwMwDhAKCgIICRE0HwHWu/YfCQgBv6kTExIQCxMrHAAAAv+8AAYA1gKvAAgAIAAAExYXBiMiJicRLgE0Njc2NxYXFhcWFAcGJy4CJwYHBgd1DQkGKgsXA2MXFRMqPjMRHCQGBAsZJQ0YHz0WBwYB1rv2HwkIAb8oCiYkFCwdIQ4ZOAwVBhAPGwwaHiokDA4AAAP/2gAGAMECmAAIABMAHQAAExYXBiMiJicRJyI1NDcyFhQGBwYzIjU0NzIVFAcGdQ0JBioLFwNEGDIVDwwJDHMYMyQqCwHWu/YfCQgBv38iDBUSHA0DBSINFCIfAQEAAAIAMwAGAikCbgAmADIAAAEWFRQHBgcGIi4BJyYnJjQ3PgEyHgEXJicHJzcmJzQ2NxYXFhc3FwEUFxYzNjc2NCcmIgHjOkcgMRAkPFUnVBACDidUMjhvPQgwTylEK00dDT4TJyZJKv5pRThfOhoRBGaoAdJzcXdBHQ4FDCYcOzsJHRMoGgIZDElFLUIiRB0SFQMgDRkmNDH+41QqIQQpGjMRKAD//wAi//oB4wLIEiYAUQAAEAYBQCI6//8ANP//AjACaBImAFIAABAHAEMAvgAA//8ANP//AjACcBImAFIAABAHAHQAywAA//8ANP//AjACrxImAFIAABAGATp8AP//ADT//wIwAo4SJgBSAAAQBgFAOAD//wA0//8CMAKYEiYAUgAAEAYAaWoA//8AOgBvAUcBexAmAB1eChAGAVscAP//ADT/2gIwAgYSJgBSAAAQRgASXNo4IjOV//8ADf//AekCaBImAFgAABAHAEMAogAA//8ADf//AekCcBImAFgAABAHAHQArwAA//8ADf//AekCrxImAFgAABAGATpgAP//AA3//wHpApgSJgBYAAAQBgBpTgD//wAW/lgCIAJwEiYAXAAAEAcAdADEAAAAAgAY/3EB/gJPABsAKwAANwcUFxYVFAYiJwM2MhcWFzYzMhcWFRQGBwYHFgEmIgcGBwYVFBUXNjc2NTRyAQQBHx4HGhcXBw4EhGB+KhM8M3WpAQESIkslVCgSBcxXMB0vHR8IBhoZAQLUCQ8agig8GyEtWyZVERIBVw0HEDcaJgQEeS5FJycr//8AFv5YAiACmBImAFwAABAGAGljAP//ABr/8QJ+Ax0SJgAkAAAQBwBvAIgAuv//ABIABgH1AmMSJgBEAAAQBgBvVQD//wAh//EChQNPEiYAJAcAEAcBPACKARH//wASAAYB9QI+EiYARAAAEAcBPACAAAD//wAa/0oCmAK6EiYAJAAAEAcBPwG+AAP//wAS/1ECGAHGEiYARAAAEAcBPwE+AAr//wAW//8CwAM1EiYAJgAAEAcAdADtAMX//wAWAAACbQJwEiYARgAAEAcAdADvAAD//wAW//8CwAOJEiYAJgAAEAcBOgCrANr//wAWAAACbQKvEiYARgAAEAcBOgCgAAD//wAW//8CwAMaEiYAJgAAEAcBPQEIAPL//wAWAAACbQIoEiYARgAAEAcBPQD2AAD//wAW//8CwANBEiYAJgAAEAcBOwCzAQP//wAWAAACbQJTEiYARgAAEAcBOwCRABX//wAmAAYCfwMpEiYAJwAAEAcBOwCSAOv//wAeAAACSgLjEiYAKAAAEAcAbwBuAID//wAUAAYCCQJjEiYASAAAEAYAb2YA//8AHgAAAkoDBhImACgAABAHATwArgDI//8AFAAGAgkCWhImAEgAABAHATwAjgAc//8AHgAAAkoC9BImACgAABAHAT0AwgDM//8AFAAGAgkCThImAEgAABAHAT0AxwAm//8AHv9wAkoCfhImACgAABAHAT8BYAAp//8AFP9KAgkB0xImAEgAABAHAT8AngAD//8AHgAAAkoDIRImACgAABAHATsAkADj//8AFAAGAgkCcRImAEgAABAGATtvM///ABb/wAKuA3QSJgAqAAAQBwE6AMkAxf//ABf+UQH7Aq8SJgBKAAAQBgE6ZAD//wAW/8ACrgMQEiYAKgAAEAcBPADYANL//wAX/lEB+wI+EiYASgAAEAcBPACEAAD//wAW/8ACrgMFEiYAKgAAEAcBPQDnAN3//wAX/lEB+wIoEiYASgAAEAcBPQC6AAD//wAW/wUCrgKMEiYAKgAAEAcBXgCeAAD//wAX/lEB+wJrEiYASgAAEAcBTACmAAD//wAV//oCSgPNEiYAKwAAEAcBOgBvAR7//wAX//0B8QMdEiYASwAAEAYBOnlu//8AFf/6AkoC2xImACsAABBGAG/sr38fR0H////x//0B8QKcEiYASwAAEAYAb9Od////k///AR8DChImACwAABAHAUD/eQB8AAL/hAAGARACsAAIACcAABMWFwYjIiYnESciByImJz4BNzYyHgIyPgI3Mh4BFAYHBiMiJy4BdQ0JBioLFwM4IDYGGwMPPCEIFB0kJisZFRkXBg0BDxEsPi4cFBwB1rv2HwkIAb+DUQgNMEoNAxUmIg4aJhgVDxYkEi8fEhcAAAL/vAAGAMkCYwAIABYAABMWFwYjIiYnESciNTQ+AjcyFxYUBgd1DQkGKgsXA0gyFzlXMCoLAQkSAda79h8JCAG/QBkOCggPBRcECQ8G////3///AKAC0hImACwAABAHATz/wACU////1f9NAIkCRhImACwAABAGAT+vBv////T/VQCoAoESJgBMAAAQBgE/zg7//wAa//8AeQLEEiYALAAAEAcBPQAAAJwAAQA2AAYAiwHWAAgAABMWFwYjIiYnEXUNCQYqCxcDAda79h8JCAG///8ACQAEAgYDjBImAC0AABAHAToAfADdAAL/hP6RANkCrwAiADoAABcUIyIuAScmJzQ2NR4BMzI3NjU0JicmNDcmNzYzBhQeARcWAiY0Njc2NxYXFhcWFAcGJy4CJwYHBgejWAkbNRtBEg4hTCscEg8NBg4CAxkTFwkBCwcRzRcVEyo+MxEcJAYFChklDRgfPRUIBsinAQcJFioFHwEZLCokJFWhUKV5KBgMCT5ITZRKoQJjCiYkFCwdIQ4ZOAwVBhAPGwwaHiokDA4A//8AK/8FAmEC0BImAC4AABAGAV5yAP//AB7/BQJkAtsSJgBOAAAQBgFedgD//wA3AA4CtANYEiYALwAAEAcAdAEHAOj//wAQ//8AhgM8EiYATwAAEAcAdP/3AMz//wA3/wUCtAKuEiYALwAAEAcBXgCeAAD//wAI/wUAkwKqEiYATwAAEAYBXo0A//8ANwAOArQCrhImAC8AABAHAU0BAAAA//8ANwAOArQCrhImAC8AABAHAHcBKAAA//8AFv//AQcCqhAmAE8AABAHAHcAoQAA//8ACQAOArQCrhImAC8AABAGAUrrHP///8H//wDOAqoSJgBPAAAQBgFKowD//wAZ//gCYANlEiYAMQAAEAcAdADwAPX//wAi//oB4wJwEiYAUQAAEAcAdACrAAD//wAZ/wUCYALMEiYAMQAAEAYBXn0A//8AIv8FAeMB8xImAFEAABAGAV47AP//ABn/+AJgA3ESJgAxAAAQBwE7AKkBM///ACL/+gHjAoASJgBRAAAQBgE7aEL//wAi//oB4wMNEiYAUQAAEAcBXv+wA0v//wAWAA4CjgLZEiYAMgAAEAcAbwCoAHb//wA0//8CMAJjEiYAUgAAEAYAb3EA//8AFgAOAo4C9RImADIAABAHATwAzAC3//8ANP//AjACPhImAFIAABAHATwAnAAA//8AFgAOAo4DFRImADIAABAHAUEAvgCD//8ANP//AjACkhImAFIAABAHAUEAkQAAAAIAFv/yBDQCewAwAEAAAAEyFxUGBwYHBhYXFhUyPgEzFQUXMjc2MxQOAScGBTUGBwYiJicmNTQ+AjMyFzcWMwQGFBYXFjI3Nj8BJicmIgYDV1UkHGS5PxECAQQ9tmAy/oIFdV+vVxoTCn7+iS1NHWdyKlgxVXFBdEkBG1L+FicdHTzmMA4HARtXH1RUAm4NMgQBAg5OPBAnNBcLNjCkCRIUIgoHDh9YORMIJydTlEV6WzZtYwilW2lgIkheHB7EdSMMLAADABj/6gOWAd4AMQBEAEsAADc0NzY3MjMyFhc2NzY6ARcWFxYUBw4CBwYHBhQXFjMyNzY3MhYVBgcGIyImJwYjIiYkPgE3NTQnJiMOAQcGBxQXFjI2ASYjIgcGFRhmUXIGBzJCDjxtISYVIEwlDwIhVVkqXR4NAhlnOTtITQoPJGJMTEdgGDylX2EBaB0DAhwPHidPI0wXIRlzRQG6FzUmHDmpdkg5DC4pYh4JCBEtEx4JGBEHAwcuEysNWxQaIw8LPiUdLyRwWBA2NgxBPxwPBxAWMoU+FREJAUgkCxYj//8ALv/0AqsDLhImADUAABAHAHQA0AC+//8AG//1AiICcBImAFUAABAHAHQAxgAA//8ALv8FAqsChxImADUAABAHAV4AqQAA//8AG/8FAiIB4hImAFUAABAGAV5WAP//AC7/9AKrAykSJgA1AAAQBwE7AI0A6///ABv/9QIiAnkSJgBVAAAQBwE7AIIAO///AA///wJwAtsSJgA2AAAQBwB0APUAa///ABb/4wHfAnASJgBWAAAQBwB0AK0AAP//AA///wJwAz0SJgA2AAAQBwE6AJoAjv//ABb/4wHfAq8SJgBWAAAQBgE6XQD//wAP/xcCcAJgEiYANgAAEAcAeADGAAD//wAW/xoB3wHKEiYAVgAAEAcAeAC2AAP//wAP//8CcALZEiYANgAAEAcBOwCWAJv//wAW/+MB3wJTEiYAVgAAEAYBO2YV//8AAP8eAn4CRBImADcAABAGAV4aGf//ABD/BQGTAqgSJgBXAAAQBgFeCgD//wAAAAACfgLnEiYANwAAEAcBOwCKAKn//wAAAAACfgJEEiYANwAAEAcAbwBp/zb////1//EBkwKoEiYAVwAAEEcAb//I/ehhO03a//8AFP/+AhYDIxImADgAABAHAUAAQgCV//8ADf//AekCjhImAFgAABAGAUAcAP//ABT//gIWArkSJgA4AAAQBgBvd1b//wAN//8B6QJjEiYAWAAAEAYAb1UA//8AFP/+AhYCvhImADgAABAHATwAlwCA//8ADf//AekCPhImAFgAABAHATwAgAAA//8AFP/+AhYC/hImADgAABAHAT4ApgCz//8ADf//AekCSxImAFgAABAHAT4AjgAA//8AFP/+AhYDERImADgAABAHAUEAqQB///8ADf//AekCkhImAFgAABAGAUF1AP//ABT/YAIkAmMSJgA4AAAQBwE/AUoAGf//AA3/YwINAbkSJgBYAAAQBwE/ATMAHP//AA4AAAOzA3ASJgA6AAAQBwE6AT4Awf//AC7/6wMQAq8SJgBaAAAQBwE6APoAAP//ABz/7gISA1USJgA8AAAQBwE6AG4Apv//ABb+WAIgAq8SJgBcAAAQBgE6dQD//wAc/+4CEgK+EiYAPAAAEAYAaVgm//8AHP/9AwIDCxImAD0AABAHAHQBIgCb//8AE//8AfQCcBImAF0AABAHAHQAqQAA//8AHP/9AwIC2xImAD0AABAHAT0A9QCz//8AE//8AfQCKBImAF0AABAHAT0AsAAA//8AHP/9AwIDFBImAD0AABAHATsAuQDW//8AE//8AfQCPhImAF0AABAGATtiAAABAA7+XgJgAz4AKwAAATIUFwUTBz8BNCYnJicHIicmNTcmND4BMh4CFRQHJicmIyIHBhQWFzI3NgJZBQL+qRXcApAOAwcGgg0JEJgUJEVOUUo0BSg5RDw5EwkIFD5NlAFONgoq/Y8VVQNZ9jd4JDIPGhU2rNd4KSI0QR8YCjgsNFEqmX9ACxf//wAd//oDcwLXEiYAhv/6EEcAdAE/AOk2HjKf//8AEv/2A6sCcBAmAEQAABAnAEgBov/wEAcAdAGEAAD//wAWAAACjgMLEiYAMgAAECYAEl0AEAcAdADuAJv//wA0/9ICMAJwEiYAUgAAEGYAEl7SNrIzXBAHAHQAywAA//8AD/8FAnACYBImADYAABAHAV4AqQAA//8AFv8FAd8ByhImAFYAABAGAV49AAABABIB/gEsAq8AFwAAEiY0Njc2NxYXFhcWFAcGJy4CJwYHBgcpFxUTKj4zERwkBgQLGSUNGB89FgcGAf4KJiQULB0hDhk4DBUGEA8bDBoeKiQMDgABAB8BxwEOAj4AFgAAEiY0NjMeARc+Azc2FxYUBwYHBgcmMRIUDwshJRsUCw0TFQgEBR0SFykzAgYYGgYTHhQUEQgHCwoKBQ0JJQwQFRMAAAEAHwHaAOACPgASAAASNDYzHgEyPgE3NjIWFAcOASMiHxQPBCATGCUICg8JBhw2DywCDSsGIBQDGRAFCg0JKxYAAAEAIgHXAHkCKAAMAAATPgEyHgEXFAYiJicmIgUYDhIYAhQaEAcSAf8YEQMXEBgPBQYMAAACAB8BpQDLAksADQAbAAASJjQ3NjMyFxYXFAYjIjcmIyIHHAEXFjMyNzwBMRIMFCgaFy8EKigfQhYbHwYMFREjBwHDHjUUIQwZLjIhZBceAxMTER4FEAAAAQAm/0cA2gAiABUAABcGIyInJjU0NjcXIiMiBwYVFBcWMjfPGRAuGzchJEcCAyAUHhUbNRqtDBgtPB4xCxkNFB8gEhcLAAEAGgHmAaYCjgAeAAATIgciJic+ATc2Mh4CMj4CNzIeARQGBwYjIicuAZQgNgYbAw88IQgUHSQmKxkVGRcGDQEPESw+LhwUHAI3UQgNMEoNAxUmIg4aJhgVDxYkEi8fEhcAAgAsAf4A8gKSAAoAEwAAEzYzMhYXFAcGByc3FAcGByc3NjJhDBEIDAIKECklxgoNLSQ0DCMCeRkOCRIRGzUWUhERFjoWWhn//wAOAAADswNIEiYAOgAAEAcAQwGVAOD//wAu/+sDEAJoEiYAWgAAEAcAQwE9AAD//wAOAAADswNXEiYAOgAAEAcAdAGQAOf//wAu/+sDEAJwEiYAWgAAEAcAdAFKAAD//wAOAAADswNjEiYAOgAAEAcAaQElAMv//wAu/+sDEAKYEiYAWgAAEAcAaQDoAAD//wAc/+4CEgMwEiYAPAAAEAcAQwDFAMj//wAW/lgCIAJoEiYAXAAAEAcAQwC3AAAAAQAeANgBKwEmAA4AADciNTQ+AjcyFxYVFAYHUDIXOVcwFA4UCRLYGg0KCBAFBwoOBRAGAAEAHgDYAYIBJQAQAAA3IjU0PgQ3MhcWFRQGB1AyFyJITUkXFA4UCRLYGg0KBQcHBgMHCg4FEAYAAQAbAbYAgAJrAAkAABMyFRQHBg8BNzZoGCIKCTA4DAJrIylDFA4EsAUAAQAbAbYAgAJrAAkAABMyFRQHBg8BNzZoGCIKCTA4DAJrIylDFA4EsAUAAQAjAAoAiAC/AAkAADcyFRQHBg8BNzZwGCIKCTA4DL8jKUMUDgSwBQAAAgA2AeoA1wL7AAsAFwAAEzcnNDcXFRcOASMiJzcnNDcXFRcOASMikgEBJBEQAxkFJFwBASQQEQQYBSQCUhwpUxEQxyIDDVcdKlMREMciBA0AAAIANgHqANcC+wALABcAABM3JzQ3FxUXDgEjIic3JzQ3FxUXDgEjIpIBASQREAMZBSRcAQEkEBEEGAUkAlIcKVMREMciAw1XHSpTERDHIgQNAAACAFUAHwD+AS0ACwAXAAA/ASc0NxcVFw4BIyInNyc0NxcVFw4BIyK5AQEkERADGQUkZAEBJBEQAxkFJH8cKFIUEcciBAxkHCpRExHHIQUMAAEAF//9AYIDWAAcAAAzFCsBIgcDByInJjU0Nz4BNwMzEzY3MhcWFAYPAeUZJAwCBDsqEwcvFScUClAJCEs5DgMNGHgCAQIHBg4FCxQGAgUCARn+8gEHGAQKEQcKAAABABf//QGEA1gALQAAMxQrASIHAwcuATY3Njc1ByInJjU0Nz4BNwMzEzY3MhcWBg8BFT4BNzYWFRQPAeUZJAwCA0ggFQMVBGA7KhMHLxUnFApQCQhLOQ4GEBh4IUEaEBMSjQIBAZkJBA0TEQQJNQYOBQsUBgIFAgEZ/vIBBxgKFQcKMgQHBQULChcNEwAAAQAhAMIApQFBAAwAABM+ATMyFhcUBiImJyYhCCULISgDHigZCxoBASUbKBolGAgIFQADABb//wGNAEIACgAVAB4AADc0NjcyFhQGBwYiNzQ2NzIWFAYHBiIzIjU0PwEyFRQWJA4VDwwJDzKQJA4VDwwJDzKoGBkaJCIIEQcRHA4DBSMIEQcRHA4DBSMIDAwhIgABAFQAOwGvAdMAGgAANz4BNzY3MhcWFA8BHgEXFhcOAQcGIy4CJyZUIFYsbC8NBgME6w84IlE9AQYECQIecEQdROUZRCJVGhYJEgazCBkRKCgBDggVEycbDiIAAAEAMgAwAaoBvQAUAAA3Jic0NTQ3PgE3JTceAxcOA3YtBUdpQAb++DIxU01MKRpPV1UwERMEAx8qPTEXYzEjHBEXHx8/QkQAAAEAFQAAAcUCtQASAAAzIj0BNBM2NzYzNjIUDgMHBicSx3NOFAUGCSU6Rk8mTyAKJAE1sWQZBBhRanh9OXcAAQAd//4DCQKZAE8AADciNTQ2MzY3NTQ3ByIGJyYnNz4BNzY3NjMyFxYVJiIOAQc+ATc2HgEGDwEGFBcVPgE3NjcyFRQHIgcGBx4BMzY3NjcyFhUOASMiLgEnJicGOxgNBCkSBCUFDwgTAhQCLCElY2aBRRYZRYVuTw8mTSAQEQMJCbACAhYqFzI7IgJQWBgYF3VMiiVCRw4dULRlDztUJEoaHq8jAw0HAw4eHgQBAQMOJAIFBIBSVRMXRCc4Yz0FCQUFChMWBhgOHA0UAwQDBwwiCAgWBgVBPgwJEC0HE0c0ARkYMVEDAAEAAP+8BMoCZQBUAAABJyIHBgcGFBcHEyciJjQ2MxYXFjI3PgEyHgQXEzYzMhcWFx4BFAYiLgQvASYnNC4BBgcGBwYnJicDBiMGBwYHBhUXFA4BIi4BPgUB+F8pMAIGFQJeH9UICRIMPDzBfS4GHkY4LiYiHhDIGBM7HQkMFQ0SICAHBwkLBQkEAgIOHBo1bQ4YHBKvDAUQEgQCBAQCFyEaEgUKCwwMCgHrAgcnPtyDGwcB7gwaFhoDBQ4EGxgxTV5ZSRIBXBa4O2q/OhsaGSU8TFMlRB4OFSEIGyhR1RkOED4BcwM61zAfGBdHCCIZARIrUFxjXE8AAQAeANgBKwEmAA4AADciNTQ+AjcyFxYVFAYHUDIXOVcwFA4UCRLYGg0KCBAFBwoOBRAG//8ADv/pApUDPhAmAEkAABAHAEwCCv/j//8ADgAGAp4DPhAmAEkAABAHAE8CHgAOAAEAe/8FAQb/wgAPAAAXPgEyFxYVFAcOAQcGIyInwgYPEgcWNwoJBxcXBgZPDQQCBhEQVRAPBxkCAAABAAABXwBcAAUAbAAFAAIAAAABAAEAAABAAAAAAwABAAAAAAAAAAAAAAAkAE0AvQEhAYwCBQIaAkICbgK+Av4DHgM4A1IDbgOlA8IECARLBIQE3AUrBWAFxwYSBjgGWQaHBrkG3QcaB5cH7whKCIUIvQj2CUoJoQnmCf8KMQp6CpcK8wswC10LoQwFDGYMtQzmDS8NWw20DeoOHQ5RDn8Ong7fDwkPIg85D4UPzRAUEGQQrRDpET4RehGdEeISKBJHEp4S2xMTE1cTlBPSFBAUPhSEFLIVBhVSFYcVzBYaFiwWexasFrcXDRdoF9EYQBhhGMcY6RlZGWMZuBnbGlsadRqiGuwa9xsCGxkbbhufG7gb8Bv7HAYcRhxZHG0cghyNHJkcpRyxHL0cyRzVHUIdTh1aHWYdch19HYkdlB2fHaod9x4DHg8eGx4nHjMePx6CHo0emR6lHrEevB7IHxAfWx9nH3Mffh+JH5QfoB+sH7cfwx/PH9of5SAKIC8gZyCXIOkg9CEAIQwhFyEiIS0hOCFFIVEhXSFoIXMhfyHDIc4h2iHlIfEh/SIJIhUiISItIjkiRSJRIl0iaSJ1IoEijSKYIqQisCK8Isgi1CLgIuwi9yMDIw4jGiMmIzIjPiNKI1YjYiNtI3ojhSORI9Aj9yQDJA4kGSQlJDkkRSSfJKoktSTBJM0k2STkJPAk/CUIJRMlHiUqJTYlQSVMJVglYyVvJXslhiWSJZ4lqiW2JhgmiCaUJqAmrCa3JsMmzybbJucm8yb+JwonFiciJy0nOCdDJ08nWydpJ3UngCeLJ5YnoieuJ7onxifSJ90n6Sf1KAEoDSgZKCQoLyg7KEcoUyhfKGsodii6KMgo2CjnKPgpBCkPKTkpYSmCKZwpyCnrKhwqQCpMKlgqZCpwKnwqiCqUKqAquirWKusrACsVKz4rZyuPK74sBSweLE4sfCygLL8tMy2vLckt1S3hLf4AAQAAAAEAxeCvFTNfDzz1AAsEAAAAAADKM4upAAAAANUxCX7/hP5RBMoD8gAAAAgAAgAAAAAAAAK0AAAAAAAAArQAAAGaAAAAigAWAPIANgKNADgCOgAJAhMAHwKuAAUApgAbATEADwFoABoCCAAnAhkACgC2/+oBPgAeAJAAFwHSABUChgAmAIMAHAJKABACCQAKArkASQLVABsCggAWAnYACgKYABYCRwAeAKsAHwB//+oB5wBUAfgAQAHjADICBgAKBCwAGwKQABoC2AAeAtUAFgKYACYCXgAeAsUAJgLFABYCbAAVAJsAGgIeAAkCbAArAsUANwNPABwCggAZAq4AFgKNACYC2gAbAtoALgKSAA8CfgAAAj8AFAKCAAsDwwAOAmYAGwIjABwDIwAcAbMAHwICAAACKgAAAToAEgK/ACAAsAAvAgkAEgI/AB4CiAAWAg0ACQIqABQCYAAOAhAAFwH7ABcAmwAYALb/jgJ1AB4AoQAWAx0AGgIAACICQAA0AjoAPgIOACQCNQAbAgIAFgGeABACCAANAhMAIgM8AC4B4gASAjIAFgH7ABMBaQA0AJUANAHqABgBxwAaAIoAFwKIABUCKP/qAkD//wIj//YAgwAcAgIACgF8AEIChgAmAP8ACgLOAFQCZgBJAoYAJgE+AB4A4QAZAhkAEgGAAAkBUAALALAAGQH2ACEBhAASAJAADwERACsAcwAaARYAFwKeADICewANApgAFwNzAAkB8P/jApAAFQKQABoCkAAaApAAGgKQABoCkAAaA4IAHgLVABYCXgAeAl4AHgJeAB4CXgAeAJsACACbAAwAm//HAJv/0QK6AAoCggAZAq4AFgKuABYCrgAWAq4AFgKuABYB4gBMAq4AFgI/ABQCPwAUAj8AFAI/ABQCIwAcAgYAIQLYAEkCCQASAgkAEgIJABICCQASAgkAEgIJABIDsgASAogAFgIqABQCKgAUAioAFAIqABQAmwAcAJsAIQCb/7wAm//aAlIAMwIAACICQAA0AkAANAJAADQCQAA0AkAANAFgADoCQAA0AggADQIIAA0CCAANAggADQIyABYCEwAYAjIAFgKQABoCCQASApAAIQIJABICkAAaAgkAEgLVABYCiAAWAtUAFgKIABYC1QAWAogAFgLVABYCiAAWApgAJgJeAB4CKgAUAl4AHgIqABQCXgAeAioAFAJeAB4CKgAUAl4AHgIqABQCxQAWAhAAFwLFABYCEAAXAsUAFgIQABcCxQAWAhAAFwJsABUB+wAXAmwAFQH7//EAm/+TAJv/hACb/7wAm//fAJv/1QCb//QAmwAaAJsANgIeAAkArP+EAmwAKwJ1AB4CxQA3AKEAEALFADcAoQAIAsUANwLFADcBMQAWAsUACQCh/8ECggAZAgAAIgKCABkCAAAiAoIAGQIAACICAAAiAq4AFgJAADQCrgAWAkAANAKuABYCQAA0BDwAFgOnABgC2gAuAjUAGwLaAC4CNQAbAtoALgI1ABsCkgAPAgIAFgKSAA8CAgAWApIADwICABYCkgAPAgIAFgJ+AAABngAQAn4AAAJ+AAABnv/2Aj8AFAIIAA0CPwAUAggADQI/ABQCCAANAj8AFAIIAA0CPwAUAggADQI/ABQCCAANA8MADgM8AC4CIwAcAjIAFgIjABwDIwAcAfsAEwMjABwB+wATAyMAHAH7ABMCYAAOA4IAHQOyABICrgAWAkAANAKSAA8CAgAWAToAEgE6AB8A/AAfAJAAIgDhAB8A/AAmAccAGgEXACwDwwAOAzwALgPDAA4DPAAuA8MADgM8AC4CIwAcAjIAFgE+AB4BpQAeAKYAGwCmABsApgAjAPIANgDyADYBHwBVAZoAFwGaABcAxQAhAbEAFgHnAFQB4wAyAdIAFQMuAB0E1wAAAT4AHgK9AA4CzgAOAZoAewABAAAD8v5jAAAE1/+E/3wEygABAAAAAAAAAAAAAAAAAAABXwADAhgBkAAFAAACzQKaAAAAjwLNApoAAAHoADMBAAAAAAAAAAAAAAAAAKAAAC9AAABKAAAAAAAAAABweXJzAEAAIPsCA/L+YwAAA/IBnQAAABEAAAAAAbcCowAAACAAAQAAAAIAAAADAAAAFAADAAEAAAAUAAQBCAAAAD4AIAAEAB4AfgCgAKwBDgEpASwBMQE3AT0BSQFkAX4BkgH/AhkCxwLdHoUe8yAUIBogHiAiICYgOiBEIKwhIiIS+wL//wAAACAAoAChAK4BEgErAS4BNAE5AT8BTAFmAZIB/AIYAsYC2B6AHvIgEyAYIBwgICAmIDkgRCCsISIiEvsB////4/9j/8H/wP+9/7z/u/+5/7j/t/+1/7T/of84/yD+dP5k4sLiVuE34TThM+Ey4S/hHeEU4K3gON9JBlsAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAuAH/hbAEjQAAAAAMAJYAAwABBAkAAAB0AAAAAwABBAkAAQAmAHQAAwABBAkAAgAOAJoAAwABBAkAAwBKAKgAAwABBAkABAA2APIAAwABBAkABQAkASgAAwABBAkABgA0AUwAAwABBAkACAAgAYAAAwABBAkACQAgAYAAAwABBAkADAA0AaAAAwABBAkADSJwAdQAAwABBAkADgA2JEQAQwBvAHAAeQByAGkAZwBoAHQAIAAoAGMAKQAgADIAMAAxADAALAAgAEsAaQBtAGIAZQByAGwAeQAgAEcAZQBzAHcAZQBpAG4AIAAoAGsAaQBtAGIAZQByAGwAeQBnAGUAcwB3AGUAaQBuAC4AYwBvAG0AKQBBAHIAYwBoAGkAdABlAGMAdABzACAARABhAHUAZwBoAHQAZQByAFIAZQBnAHUAbABhAHIAMQAuADAAMAAzADsAVQBLAFcATgA7AEEAcgBjAGgAaQB0AGUAYwB0AHMARABhAHUAZwBoAHQAZQByAC0AUgBlAGcAdQBsAGEAcgBBAHIAYwBoAGkAdABlAGMAdABzACAARABhAHUAZwBoAHQAZQByACAAUgBlAGcAdQBsAGEAcgBWAGUAcgBzAGkAbwBuACAAMQAuADAAMAAzACAAMgAwADEAMABBAHIAYwBoAGkAdABlAGMAdABzAEQAYQB1AGcAaAB0AGUAcgAtAFIAZQBnAHUAbABhAHIASwBpAG0AYgBlAHIAbAB5ACAARwBlAHMAdwBlAGkAbgBoAHQAdABwADoALwAvAGsAaQBtAGIAZQByAGwAeQBnAGUAcwB3AGUAaQBuAC4AYwBvAG0AQwBvAHAAeQByAGkAZwBoAHQAIAAoAGMAKQAgADIAMAAxADAALAAgAEsAaQBtAGIAZQByAGwAeQAgAEcAZQBzAHcAZQBpAG4AIAAoAGsAaQBtAGIAZQByAGwAeQBnAGUAcwB3AGUAaQBuAC4AYwBvAG0AKQANAAoADQAKAFQAaABpAHMAIABGAG8AbgB0ACAAUwBvAGYAdAB3AGEAcgBlACAAaQBzACAAbABpAGMAZQBuAHMAZQBkACAAdQBuAGQAZQByACAAdABoAGUAIABTAEkATAAgAE8AcABlAG4AIABGAG8AbgB0ACAATABpAGMAZQBuAHMAZQAsACAAVgBlAHIAcwBpAG8AbgAgADEALgAxAC4AIAAgAFQAaABpAHMAIABsAGkAYwBlAG4AcwBlACAAaQBzACAAYwBvAHAAaQBlAGQAIABiAGUAbABvAHcALAAgAGEAbgBkACAAaQBzACAAYQBsAHMAbwAgAGEAdgBhAGkAbABhAGIAbABlACAAdwBpAHQAaAAgAGEAIABGAEEAUQAgAGEAdAA6ACAAIABoAHQAdABwADoALwAvAHMAYwByAGkAcAB0AHMALgBzAGkAbAAuAG8AcgBnAC8ATwBGAEwADQAKAA0ACgANAAoALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAA0ACgBTAEkATAAgAE8AUABFAE4AIABGAE8ATgBUACAATABJAEMARQBOAFMARQAgAFYAZQByAHMAaQBvAG4AIAAxAC4AMQAgAC0AIAAyADYAIABGAGUAYgByAHUAYQByAHkAIAAyADAAMAA3AA0ACgAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ALQAtAC0ADQAKAA0ACgBQAFIARQBBAE0AQgBMAEUADQAKAFQAaABlACAAZwBvAGEAbABzACAAbwBmACAAdABoAGUAIABPAHAAZQBuACAARgBvAG4AdAAgAEwAaQBjAGUAbgBzAGUAIAAoAE8ARgBMACkAIABhAHIAZQAgAHQAbwAgAHMAdABpAG0AdQBsAGEAdABlACAAdwBvAHIAbABkAHcAaQBkAGUAIABkAGUAdgBlAGwAbwBwAG0AZQBuAHQAIABvAGYAIABjAG8AbABsAGEAYgBvAHIAYQB0AGkAdgBlACAAZgBvAG4AdAAgAHAAcgBvAGoAZQBjAHQAcwAsACAAdABvACAAcwB1AHAAcABvAHIAdAAgAHQAaABlACAAZgBvAG4AdAAgAGMAcgBlAGEAdABpAG8AbgAgAGUAZgBmAG8AcgB0AHMAIABvAGYAIABhAGMAYQBkAGUAbQBpAGMAIABhAG4AZAAgAGwAaQBuAGcAdQBpAHMAdABpAGMAIABjAG8AbQBtAHUAbgBpAHQAaQBlAHMALAAgAGEAbgBkACAAdABvACAAcAByAG8AdgBpAGQAZQAgAGEAIABmAHIAZQBlACAAYQBuAGQAIABvAHAAZQBuACAAZgByAGEAbQBlAHcAbwByAGsAIABpAG4AIAB3AGgAaQBjAGgAIABmAG8AbgB0AHMAIABtAGEAeQAgAGIAZQAgAHMAaABhAHIAZQBkACAAYQBuAGQAIABpAG0AcAByAG8AdgBlAGQAIABpAG4AIABwAGEAcgB0AG4AZQByAHMAaABpAHAADQAKAHcAaQB0AGgAIABvAHQAaABlAHIAcwAuAA0ACgANAAoAVABoAGUAIABPAEYATAAgAGEAbABsAG8AdwBzACAAdABoAGUAIABsAGkAYwBlAG4AcwBlAGQAIABmAG8AbgB0AHMAIAB0AG8AIABiAGUAIAB1AHMAZQBkACwAIABzAHQAdQBkAGkAZQBkACwAIABtAG8AZABpAGYAaQBlAGQAIABhAG4AZAAgAHIAZQBkAGkAcwB0AHIAaQBiAHUAdABlAGQAIABmAHIAZQBlAGwAeQAgAGEAcwAgAGwAbwBuAGcAIABhAHMAIAB0AGgAZQB5ACAAYQByAGUAIABuAG8AdAAgAHMAbwBsAGQAIABiAHkAIAB0AGgAZQBtAHMAZQBsAHYAZQBzAC4AIABUAGgAZQAgAGYAbwBuAHQAcwAsACAAaQBuAGMAbAB1AGQAaQBuAGcAIABhAG4AeQAgAGQAZQByAGkAdgBhAHQAaQB2AGUAIAB3AG8AcgBrAHMALAAgAGMAYQBuACAAYgBlACAAYgB1AG4AZABsAGUAZAAsACAAZQBtAGIAZQBkAGQAZQBkACwAIAByAGUAZABpAHMAdAByAGkAYgB1AHQAZQBkACAAYQBuAGQALwBvAHIAIABzAG8AbABkACAAdwBpAHQAaAAgAGEAbgB5ACAAcwBvAGYAdAB3AGEAcgBlACAAcAByAG8AdgBpAGQAZQBkACAAdABoAGEAdAAgAGEAbgB5ACAAcgBlAHMAZQByAHYAZQBkACAAbgBhAG0AZQBzACAAYQByAGUAIABuAG8AdAAgAHUAcwBlAGQAIABiAHkAIABkAGUAcgBpAHYAYQB0AGkAdgBlACAAdwBvAHIAawBzAC4AIABUAGgAZQAgAGYAbwBuAHQAcwAgAGEAbgBkACAAZABlAHIAaQB2AGEAdABpAHYAZQBzACwAIABoAG8AdwBlAHYAZQByACwAIABjAGEAbgBuAG8AdAAgAGIAZQAgAHIAZQBsAGUAYQBzAGUAZAAgAHUAbgBkAGUAcgAgAGEAbgB5ACAAbwB0AGgAZQByACAAdAB5AHAAZQAgAG8AZgAgAGwAaQBjAGUAbgBzAGUALgAgAFQAaABlACAAcgBlAHEAdQBpAHIAZQBtAGUAbgB0ACAAZgBvAHIAIABmAG8AbgB0AHMAIAB0AG8AIAByAGUAbQBhAGkAbgAgAHUAbgBkAGUAcgAgAHQAaABpAHMAIABsAGkAYwBlAG4AcwBlACAAZABvAGUAcwAgAG4AbwB0ACAAYQBwAHAAbAB5ACAAdABvACAAYQBuAHkAIABkAG8AYwB1AG0AZQBuAHQAIABjAHIAZQBhAHQAZQBkACAAdQBzAGkAbgBnACAAdABoAGUAIABmAG8AbgB0AHMAIABvAHIAIAB0AGgAZQBpAHIAIABkAGUAcgBpAHYAYQB0AGkAdgBlAHMALgANAAoADQAKAEQARQBGAEkATgBJAFQASQBPAE4AUwANAAoAIgBGAG8AbgB0ACAAUwBvAGYAdAB3AGEAcgBlACIAIAByAGUAZgBlAHIAcwAgAHQAbwAgAHQAaABlACAAcwBlAHQAIABvAGYAIABmAGkAbABlAHMAIAByAGUAbABlAGEAcwBlAGQAIABiAHkAIAB0AGgAZQAgAEMAbwBwAHkAcgBpAGcAaAB0ACAASABvAGwAZABlAHIAKABzACkAIAB1AG4AZABlAHIAIAB0AGgAaQBzACAAbABpAGMAZQBuAHMAZQAgAGEAbgBkACAAYwBsAGUAYQByAGwAeQAgAG0AYQByAGsAZQBkACAAYQBzACAAcwB1AGMAaAAuACAAVABoAGkAcwAgAG0AYQB5ACAAaQBuAGMAbAB1AGQAZQAgAHMAbwB1AHIAYwBlACAAZgBpAGwAZQBzACwAIABiAHUAaQBsAGQAIABzAGMAcgBpAHAAdABzACAAYQBuAGQAIABkAG8AYwB1AG0AZQBuAHQAYQB0AGkAbwBuAC4ADQAKAA0ACgAiAFIAZQBzAGUAcgB2AGUAZAAgAE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diff --git a/content/blockchain-contracts/accounting/img/utxo_state_4.svg b/content/3-Blockchain/img/utxo_state_4.svg
similarity index 100%
rename from content/blockchain-contracts/accounting/img/utxo_state_4.svg
rename to content/3-Blockchain/img/utxo_state_4.svg
diff --git a/content/blockchain-contracts/accounting/img/utxo_state_5.svg b/content/3-Blockchain/img/utxo_state_5.svg
similarity index 100%
rename from content/blockchain-contracts/accounting/img/utxo_state_5.svg
rename to content/3-Blockchain/img/utxo_state_5.svg
diff --git a/content/blockchain-contracts/accounting/img/utxo_state_6.svg b/content/3-Blockchain/img/utxo_state_6.svg
similarity index 99%
rename from content/blockchain-contracts/accounting/img/utxo_state_6.svg
rename to content/3-Blockchain/img/utxo_state_6.svg
index 84c88814..b7ed2b0d 100644
--- a/content/blockchain-contracts/accounting/img/utxo_state_6.svg
+++ b/content/3-Blockchain/img/utxo_state_6.svg
@@ -1,4 +1,4 @@
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 2px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#48cc81">0x0123</font><br />Value: 30<br />Id: 1<br /></font></div></div></div></foreignObject><text x="78" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x0123...</text></switch></g><rect x="175" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 176px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br />Value: 42</font><br /><font style="font-size: 20px;">Id: 2</font></div></div></div></foreignObject><text x="252" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="348" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 349px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#d3ff33">0x02</font><br />Value: 97</font><br /><font style="font-size: 20px;">Id: 3</font></div></div></div></foreignObject><text x="425" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x02...</text></switch></g><rect x="518" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 519px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#6d3aee">0x068</font><br /></font><div><font style="font-size: 20px;">Value: 30<br />Id: 4<br /></font></div></div></div></div></foreignObject><text x="595" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x068...</text></switch></g><rect x="348" y="132" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 186px; margin-left: 349px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#48cc81">0x0123</font><br />Value: 50<br />Id: 8<br /></font></div></div></div></foreignObject><text x="425" y="189" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x0123...</text></switch></g><rect x="1" y="129" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 183px; margin-left: 2px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br /></font><div><font style="font-size: 20px;">Value: 20<br />Id: 5<br /></font></div></div></div></div></foreignObject><text x="78" y="186" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="175" y="129" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 183px; margin-left: 176px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br /></font><div><font style="font-size: 20px;">Value: 32<br />Id: 7<br /></font></div></div></div></div></foreignObject><text x="252" y="186" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="26" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 27px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#48cc81">Joshy == 0x0123</font></div></div></div></foreignObject><text x="125" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Joshy == 0x0123</text></switch></g><rect x="226" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 227px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#00a6ed">Andrew == 0x042</font></div></div></div></foreignObject><text x="325" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Andrew == 0x042</text></switch></g><rect x="426" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 427px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#d3ff33">Pauline == 0x02</font></div></div></div></foreignObject><text x="525" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Pauline == 0x02</text></switch></g><rect x="29" y="337" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 364px; margin-left: 30px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#6d3aee">Cartman == 0x068</font></div></div></div></foreignObject><text x="128" y="368" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Cartman == 0x068</text></switch></g><rect x="518" y="132" width="153" height="107" fill="none" stroke="#48cc81" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 186px; margin-left: 519px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042 <br /></font></font><div><font style="font-size: 20px;">Value: 70<br />Id: 9<br /></font></div></div></div></div></foreignObject><text x="595" y="189" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 2px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#48cc81">0x0123</font><br />Value: 30<br />Id: 1<br /></font></div></div></div></foreignObject><text x="78" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x0123...</text></switch></g><rect x="175" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 176px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br />Value: 42</font><br /><font style="font-size: 20px;">Id: 2</font></div></div></div></foreignObject><text x="252" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="348" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 349px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#d3ff33">0x02</font><br />Value: 97</font><br /><font style="font-size: 20px;">Id: 3</font></div></div></div></foreignObject><text x="425" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x02...</text></switch></g><rect x="518" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 519px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#6d3aee">0x068</font><br /></font><div><font style="font-size: 20px;">Value: 30<br />Id: 4<br /></font></div></div></div></div></foreignObject><text x="595" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x068...</text></switch></g><rect x="348" y="132" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 186px; margin-left: 349px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#48cc81">0x0123</font><br />Value: 50<br />Id: 8<br /></font></div></div></div></foreignObject><text x="425" y="189" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x0123...</text></switch></g><rect x="1" y="129" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 183px; margin-left: 2px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br /></font><div><font style="font-size: 20px;">Value: 20<br />Id: 5<br /></font></div></div></div></div></foreignObject><text x="78" y="186" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="175" y="129" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 183px; margin-left: 176px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br /></font><div><font style="font-size: 20px;">Value: 32<br />Id: 7<br /></font></div></div></div></div></foreignObject><text x="252" y="186" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="26" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 27px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#48cc81">Joshy == 0x0123</font></div></div></div></foreignObject><text x="125" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Joshy == 0x0123</text></switch></g><rect x="226" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 227px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#00a6ed">Andrew == 0x042</font></div></div></div></foreignObject><text x="325" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Andrew == 0x042</text></switch></g><rect x="426" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 427px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#d3ff33">Pauline == 0x02</font></div></div></div></foreignObject><text x="525" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Pauline == 0x02</text></switch></g><rect x="29" y="337" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 364px; margin-left: 30px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#6d3aee">Cartman == 0x068</font></div></div></div></foreignObject><text x="128" y="368" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Cartman == 0x068</text></switch></g><rect x="518" y="132" width="153" height="107" fill="none" stroke="#48cc81" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 186px; margin-left: 519px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042 <br /></font></font><div><font style="font-size: 20px;">Value: 65<br />Id: 9<br /></font></div></div></div></div></foreignObject><text x="595" y="189" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
diff --git a/content/blockchain-contracts/accounting/img/utxo_state_7.svg b/content/3-Blockchain/img/utxo_state_7.svg
similarity index 99%
rename from content/blockchain-contracts/accounting/img/utxo_state_7.svg
rename to content/3-Blockchain/img/utxo_state_7.svg
index ab54ae69..868dee53 100644
--- a/content/blockchain-contracts/accounting/img/utxo_state_7.svg
+++ b/content/3-Blockchain/img/utxo_state_7.svg
@@ -1,4 +1,4 @@
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 2px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#48cc81">0x0123</font><br />Value: 30<br />Id: 1<br /></font></div></div></div></foreignObject><text x="78" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x0123...</text></switch></g><rect x="175" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 176px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br />Value: 42</font><br /><font style="font-size: 20px;">Id: 2</font></div></div></div></foreignObject><text x="252" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="348" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 349px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#d3ff33">0x02</font><br />Value: 97</font><br /><font style="font-size: 20px;">Id: 3</font></div></div></div></foreignObject><text x="425" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x02...</text></switch></g><rect x="518" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 519px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#6d3aee">0x068</font><br /></font><div><font style="font-size: 20px;">Value: 30<br />Id: 4<br /></font></div></div></div></div></foreignObject><text x="595" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x068...</text></switch></g><rect x="348" y="132" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 186px; margin-left: 349px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#48cc81">0x0123</font><br />Value: 50<br />Id: 8<br /></font></div></div></div></foreignObject><text x="425" y="189" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x0123...</text></switch></g><rect x="1" y="129" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 183px; margin-left: 2px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br /></font><div><font style="font-size: 20px;">Value: 20<br />Id: 5<br /></font></div></div></div></div></foreignObject><text x="78" y="186" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="175" y="129" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 183px; margin-left: 176px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br /></font><div><font style="font-size: 20px;">Value: 32<br />Id: 7<br /></font></div></div></div></div></foreignObject><text x="252" y="186" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="26" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 27px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#48cc81">Joshy == 0x0123</font></div></div></div></foreignObject><text x="125" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Joshy == 0x0123</text></switch></g><rect x="226" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 227px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#00a6ed">Andrew == 0x042</font></div></div></div></foreignObject><text x="325" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Andrew == 0x042</text></switch></g><rect x="426" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 427px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#d3ff33">Pauline == 0x02</font></div></div></div></foreignObject><text x="525" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Pauline == 0x02</text></switch></g><rect x="518" y="132" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 186px; margin-left: 519px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042 <br /></font></font><div><font style="font-size: 20px;">Value: 70<br />Id: 9<br /></font></div></div></div></div></foreignObject><text x="595" y="189" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
+<svg xmlns="http://www.w3.org/2000/svg" style="background-color: rgb(22, 5, 39);" xmlns:xlink="http://www.w3.org/1999/xlink" version="1.1" width="673px" height="330px" viewBox="-0.5 -0.5 673 330" content="&lt;mxfile host=&quot;app.diagrams.net&quot; modified=&quot;2023-07-17T23:01:55.037Z&quot; agent=&quot;Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:109.0) Gecko/20100101 Firefox/115.0&quot; etag=&quot;1Kqfdhc-LsqygoXBrPfG&quot; version=&quot;21.3.4&quot;&gt;&lt;diagram name=&quot;Page-1&quot; id=&quot;zSu6oKl2VEFmGxWaPKrN&quot;&gt;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&lt;/diagram&gt;&lt;/mxfile&gt;"><defs/><g><rect x="1" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 2px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#48cc81">0x0123</font><br />Value: 30<br />Id: 1<br /></font></div></div></div></foreignObject><text x="78" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x0123...</text></switch></g><rect x="175" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 176px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br />Value: 42</font><br /><font style="font-size: 20px;">Id: 2</font></div></div></div></foreignObject><text x="252" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="348" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 349px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#d3ff33">0x02</font><br />Value: 97</font><br /><font style="font-size: 20px;">Id: 3</font></div></div></div></foreignObject><text x="425" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x02...</text></switch></g><rect x="518" y="1" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 55px; margin-left: 519px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#6d3aee">0x068</font><br /></font><div><font style="font-size: 20px;">Value: 30<br />Id: 4<br /></font></div></div></div></div></foreignObject><text x="595" y="58" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x068...</text></switch></g><rect x="348" y="132" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 186px; margin-left: 349px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#48cc81">0x0123</font><br />Value: 50<br />Id: 8<br /></font></div></div></div></foreignObject><text x="425" y="189" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x0123...</text></switch></g><rect x="1" y="129" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 183px; margin-left: 2px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br /></font><div><font style="font-size: 20px;">Value: 20<br />Id: 5<br /></font></div></div></div></div></foreignObject><text x="78" y="186" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="175" y="129" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 183px; margin-left: 176px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042</font><br /></font><div><font style="font-size: 20px;">Value: 32<br />Id: 7<br /></font></div></div></div></div></foreignObject><text x="252" y="186" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g><rect x="26" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 27px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#48cc81">Joshy == 0x0123</font></div></div></div></foreignObject><text x="125" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Joshy == 0x0123</text></switch></g><rect x="226" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 227px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#00a6ed">Andrew == 0x042</font></div></div></div></foreignObject><text x="325" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Andrew == 0x042</text></switch></g><rect x="426" y="275" width="197" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 195px; height: 1px; padding-top: 302px; margin-left: 427px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#d3ff33">Pauline == 0x02</font></div></div></div></foreignObject><text x="525" y="306" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Pauline == 0x02</text></switch></g><rect x="518" y="132" width="153" height="107" fill="none" stroke="#e6007a" stroke-width="3" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 151px; height: 1px; padding-top: 186px; margin-left: 519px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;">Owner: <font color="#00a6ed">0x042 <br /></font></font><div><font style="font-size: 20px;">Value: 65<br />Id: 9<br /></font></div></div></div></div></foreignObject><text x="595" y="189" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Owner: 0x042...</text></switch></g></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
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diff --git a/content/3-Blockchain/index.md b/content/3-Blockchain/index.md
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+# Blockchain
diff --git a/content/4-Core_and_Basics/2-JSON-RPC-slides.md b/content/4-Core_and_Basics/2-JSON-RPC-slides.md
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+---
+title: JSON-RPC Spec
+description: JSON-RPC Spec
+---
+
+# JSON-RPC Spec
+
+---
+
+# JSON-RPC Spec
+
+## What you will learn:
+
+- What is JSON-RPC (v2)<!-- .element: class="fragment" -->
+  - Its stateless design<!-- .element: class="fragment" -->
+  - Conventions to make it stateful<!-- .element: class="fragment" -->
+- (Substrate) JSON-RPC Spec<!-- .element: class="fragment" -->
+  - Objectives<!-- .element: class="fragment" -->
+  - Versioning<!-- .element: class="fragment" -->
+  - Groups of functions<!-- .element: class="fragment" -->
+  - Overview<!-- .element: class="fragment" -->
+
+---
+
+## JSON-RPC 2.0
+
+- JSON-RPC is a stateless, transport agnostic, light-weight remote procedure call (RPC) protocol.<!-- .element: class="fragment" -->
+- Defines basic data-structures and the rules around their processing. It is transport agnostic.<!-- .element: class="fragment" -->
+
+---
+
+## JSON-RPC 2.0 - Request Object
+
+- Must have an `id` property
+
+<!-- .element: class="fragment" -->
+
+- Must have a `method`
+
+<!-- .element: class="fragment" -->
+
+- May have `params`
+
+<!-- .element: class="fragment" -->
+
+---
+
+## JSON-RPC 2.0 - Notification Object
+
+- Like `Request` but without an `id`
+
+---
+
+## JSON-RPC 2.0 - Response
+
+- Must have an `id`
+
+<!-- .element: class="fragment" -->
+
+- Must have either a `result` or an `error`
+
+<!-- .element: class="fragment" -->
+
+- If it has an `error`, it must have the following properties:
+  - `code`: number that indicates the type of error. Error codes from -32768 to -32000 are reserved for pre-defined errors.
+  - `message`: string providing a short description.
+  - `data`: optional data structure with additional information.
+
+<!-- .element: class="fragment" -->
+
+---
+
+## JSON-RPC 2.0 Examples
+
+https://www.jsonrpc.org/specification#examples
+
+---
+
+## JSON-RPC 2.0 For stateful connections and subscriptions
+
+- The client acts as a server<!-- .element: class="fragment" -->
+- The server acts as a client<!-- .element: class="fragment" -->
+- Use opaque ids that are only relevant in the context of their connection<!-- .element: class="fragment" -->
+
+---
+
+# Why a New JSON-RPC API?
+
+- Standardizing JSON-RPC requests across the Polkadot ecosystem<!-- .element: class="fragment" -->
+- Removing inconsistencies<!-- .element: class="fragment" -->
+- Providing better support for light clients and alternative runtimes<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- The previous JSON-RPC implementation had inconsistencies that made it harder for developers to maintain compatibility across parachains.
+- A key motivation was to improve support for lightweight clients, which require a more optimized and reliable data-fetching mechanism.
+
+---
+
+# JSON-RPC API Objectives
+
+- Accommodate multiple audiences<!-- .element: class="fragment" -->
+- Ensure clarity, efficiency, and scalability<!-- .element: class="fragment" -->
+- Address needs for security, reliability, and flexibility<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- The JSON-RPC API is designed to cater to a diverse range of audiences, from application developers to node operators.
+- It aims to provide a robust and efficient interface for blockchain interaction while maintaining security and clarity.
+- The interface emphasizes performance and standardization, ensuring efficient communication across various use cases.
+
+---
+
+# Key Changes & Improvements
+
+- **Groups of functions:** Based on node capabilities
+
+<!-- .element: class="fragment" -->
+
+- **Stability and versioning:** Allowing improvements without breaking contracts.
+
+<!-- .element: class="fragment" -->
+
+- **Better Error Handling:** Clearer and documented errors.
+
+<!-- .element: class="fragment" -->
+
+- **Load Balancer Friendly:** A load balancer can move a client from one server to another (and thus shut down servers that it doesn’t need anymore).
+
+<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- Method names have been changed to be more descriptive and standardized.
+
+- Errors are now structured in a way that makes debugging and handling failures easier.
+
+- The API reduces redundant calls, leading to lower latency and better efficiency.
+
+---
+
+# Grouping Functions & Node Capabilities
+
+- Functions are grouped using a prefix with a version number (e.g., `chainHead_v1_follow`)
+
+<!-- .element: class="fragment" -->
+
+- Node types: Full, Light, Archive, Plain databases
+
+<!-- .element: class="fragment" -->
+
+- Capability detection via the `rpc_methods` function
+
+<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- Grouping functions using prefixes with versioning ensures clear evolution and compatibility.
+- Each node type supports functions based on its capabilities, ensuring efficient and relevant operations.
+- Clients should always use `rpc_methods` to verify supported functions on a given node.
+
+---
+
+# Upgradability & Versioning
+
+- Groups are versioned and self-contained (e.g., `foo_v1`, `foo_v2`)
+
+<!-- .element: class="fragment" -->
+
+- Higher versions indicate preferred methods, while older versions become soft-deprecated
+
+<!-- .element: class="fragment" -->
+
+- Functions in newer versions don't overlap with older versions
+
+<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- Upgrading function groups ensures that newer functions are clearly distinct from older ones.
+- This separation simplifies development and reduces confusion when interacting with nodes of different capabilities.
+- Developers can choose which version to rely on, knowing the functional boundaries.
+
+---
+
+# Unstable Functions
+
+- Marked with the `unstable` version prefix
+
+<!-- .element: class="fragment" -->
+
+- No stability guarantees—functions can change without warning
+
+<!-- .element: class="fragment" -->
+
+- Useful for experimental or debugging utilities
+
+<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- Unstable functions are meant for experimental use and may evolve or be removed at any time.
+- They are helpful for developers needing temporary functions for debugging or testing.
+- Applications should avoid relying on unstable functions for critical features.
+
+---
+
+# Audience:
+
+## End-User Applications
+
+- Focus on reading storage and submitting transactions<!-- .element: class="fragment" -->
+- Encourage and support for light-clients<!-- .element: class="fragment" -->
+- Minimize DoS attack vectors<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- End-user applications, like wallets, should prioritize using locally-run nodes to enhance security and decentralization.
+- Light clients, which don't hold full blockchain storage, are encouraged for better usability.
+- The API design mitigates potential DoS vulnerabilities while ensuring precise and efficient operations.
+
+---
+
+# Audience:
+
+## Node Operators
+
+- Focus on monitoring and administrative operations
+
+<!-- .element: class="fragment" -->
+
+- Stable functions for scripting and automation
+
+<!-- .element: class="fragment" -->
+
+- CLI-friendly tools (e.g., `websocat`)
+
+<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- Node operators require tools to monitor and manage nodes efficiently.
+- Stability in API functions is essential for reliable scripting and automation.
+- Tools like `websocat` facilitate interaction with JSON-RPC through WebSockets.
+
+---
+
+# Audience:
+
+## Oracles & Bridges
+
+- Automated interaction with the blockchain<!-- .element: class="fragment" -->
+- Similar requirements as end-user applications<!-- .element: class="fragment" -->
+- Focus on stability and reliability<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- Oracles and bridges require reliable and automated blockchain interaction.
+- Although automated, their operational needs align with those of end-user-facing applications.
+- Ensuring security and stability is paramount.
+
+---
+
+# Audience:
+
+## Archivers / Indexers
+
+- Access to historical blockchain data<!-- .element: class="fragment" -->
+- Focus on finalized blocks<!-- .element: class="fragment" -->
+- Stable and easy-to-use functions<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- Archivers need to access and analyze past blockchain states, focusing on finalized data.
+- The API ensures stability and ease of use, simplifying data retrieval for archival purposes.
+- Performance is less critical, but stability and reliability are key.
+
+---
+
+# Overview:
+
+- chainhead<!-- .element: class="fragment" -->
+- archive<!-- .element: class="fragment" -->
+- chainSpec<!-- .element: class="fragment" -->
+- sudo\_\*<!-- .element: class="fragment" -->
+- transaction<!-- .element: class="fragment" -->
+- transactionWatch<!-- .element: class="fragment" -->
+
+---
+
+# Questions & Discussion
+
+- Feel free to ask any questions!
+
+<!-- .element: class="fragment" -->
+
+- Check the full objectives: [Parity Spec Link](https://paritytech.github.io/json-rpc-interface-spec/objectives.html)
+
+<!-- .element: class="fragment" -->
+
+- Further reading: [New JSON-RPC API mega Q&A](https://forum.polkadot.network/t/new-json-rpc-api-mega-q-a/3048)
+
+<!-- .element: class="fragment" -->
+
+**Notes:**
+
+- Encourage the audience to ask questions about their specific use cases or integration concerns.
+- Refer to the full objectives document for detailed insights and ongoing updates.
diff --git a/content/4-Core_and_Basics/2-Metadata-slides.md b/content/4-Core_and_Basics/2-Metadata-slides.md
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+---
+title: FRAME Metadata
+description: FRAME Metadata
+---
+
+# FRAME Metadata
+
+---
+
+# FRAME Metadata
+
+## What you will learn:
+
+- What is it? What's on it?<!-- .element: class="fragment" -->
+- What is it used for?<!-- .element: class="fragment" -->
+- How does it work?<!-- .element: class="fragment" -->
+- What's in it?<!-- .element: class="fragment" -->
+- What are its shortcomings?<!-- .element: class="fragment" -->
+- Evolution of Metadata (V14, V15, V16)<!-- .element: class="fragment" -->
+- Hands on.<!-- .element: class="fragment" -->
+
+---
+
+# FRAME Metadata: Introduction
+
+## FRAME Metadata: What is it?
+
+It's an opaque blob of bytes, that when decoded provides:
+
+- The necessary context to encode/decode different chain interaction.<!-- .element: class="fragment" -->
+- Documentation about certain chain interactions.<!-- .element: class="fragment" -->
+- The value of all Pallet constants.<!-- .element: class="fragment" -->
+
+---
+
+## FRAME Metadata: What is it used for?
+
+- Creating types for other languages (eg: PAPI TS types).<!-- .element: class="fragment" -->
+- Creating codecs on the fly.<!-- .element: class="fragment" -->
+- Displaying rich information about what the user is about to sign. I.e: prevent blind-signing.<!-- .element: class="fragment" -->
+- Creating docs for the chain.<!-- .element: class="fragment" -->
+- Detecting compatibility changes.<!-- .element: class="fragment" -->
+
+---
+
+## FRAME Metadata: How does it work?
+
+- Autogenerated by FRAME<!-- .element: class="fragment" -->
+- Available via a Runtime-API.<!-- .element: class="fragment" -->
+
+---
+
+## FRAME Metadata: What's in it?
+
+### Type Registry
+
+- A normalized data-structure containing all the type information used for a given chain.<!-- .element: class="fragment" -->
+- Its codec looks like this:<!-- .element: class="fragment" -->
+
+Notes:
+
+- Use dev.papi.how to navigate a decoded version of the metadata.
+
+---
+
+## FRAME Metadata: What's in it?
+
+```js
+Vector(
+  Struct({
+    id: compact,
+    path: Vector(str),
+    params: Vector(Struct({ name: str, type: Option(compact) })),
+    def: Enum({
+      composite: Vector(field),
+      variant: Vector(
+        Struct({
+          name: str,
+          fields: Vector(field),
+          index: u8,
+          docs,
+        }),
+      ),
+      sequence: compact,
+      array: Struct({
+        len: u32,
+        type: compact,
+      }),
+      tuple: Vector(compact),
+      primitive,
+      compact: compact,
+      bitSequence,
+    }),
+    docs: Vector(str),
+  }),
+);
+
+const field = Struct({
+  name: str,
+  type: compact,
+  typeName: str,
+  docs: Vector(str),
+});
+```
+
+Notes:
+
+- Use dev.papi.how to navigate a decoded version of the metadata.
+
+---
+
+## FRAME Metadata: What's in it?
+
+- Pallets: Storage, Calls, Events, Constants, Errors<!-- .element: class="fragment" -->
+- Extrinsic<!-- .element: class="fragment" -->
+- Runtime-APIs<!-- .element: class="fragment" -->
+
+Notes:
+
+- Use dev.papi.how to highliht this
+
+---
+
+## FRAME Metadata: What are its shortcomings?
+
+- Autogenerated => leaks implementation details. Examples:<!-- .element: class="fragment" -->
+  - Referenda vote.
+  - Identity types.
+- Native token is not a first class citizen. (Neither the symbol, nor the decimals are part of the metadata).<!-- .element: class="fragment" -->
+- It requires a certain level of heuristics to use it properly. Eg: AccountId, AccountId20, etc.<!-- .element: class="fragment" -->
+
+---
+
+## FRAME Metadata: How it evolved?
+
+- Prior to v14: It was not self-describing and incomplete.<!-- .element: class="fragment" -->
+- v14 was the first self-describing version. However its still missing things: runtime APIs, outters, certain extrinsic<!-- .element: class="fragment" -->
+  information. `metadata_metadata` runtime API will always return metadata v14.
+- Metadata v15: exposes runtime-apis, outters, and better types for extrinsic.<!-- .element: class="fragment" -->
+- Metadata v16: is able to highlight deprecated methods, supports extrinsic v5 and versioned transaction-extensions.<!-- .element: class="fragment" -->
diff --git a/content/4-Core_and_Basics/2-Runtime-slides.md b/content/4-Core_and_Basics/2-Runtime-slides.md
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+---
+title: Runtime
+description: Runtime (AKA State Transition Function(s))
+---
+
+# Runtime
+
+---
+
+# Runtime
+
+## What you will learn:
+
+- What is the Runtime?<!-- .element: class="fragment" -->
+- Where is located?<!-- .element: class="fragment" -->
+- How does it work?<!-- .element: class="fragment" -->
+- Tradeoffs of having a dynamic STF.<!-- .element: class="fragment" -->
+- Who does it cather to?<!-- .element: class="fragment" -->
+- Types of Runtime APIs.<!-- .element: class="fragment" -->
+
+---
+
+# Runtime: Introduction
+
+## Runtime: What is it?
+
+- It's the logic of the State Transition Fuctions that defines the business logic of the chain.<!-- .element: class="fragment" -->
+- It currently is WASM code that's stored on the state of the chain.<!-- .element: class="fragment" -->
+- It's part of the state, and it also determines how this state changes 🤯.<!-- .element: class="fragment" -->
+
+---
+
+## Runtime: part of the state of the chain.
+
+- Why?
+  - In an ideal world it allows for forkless upgrades.<!-- .element: class="fragment" -->
+
+---
+
+## Runtime: part of the state of the chain.
+
+- How does it work<!-- .element: class="fragment" -->
+
+  - Every time that the WASM changes, the node instantiates the new WASM.<!-- .element: class="fragment" -->
+
+- Host Functions:<!-- .element: class="fragment" -->
+
+  - When the WASM is instaniated, the node provides an environment so that the WASM can interact with the node.<!-- .element: class="fragment" -->
+  - Eg: Access storage, Expensive cryptografic functions, etc.<!-- .element: class="fragment" -->
+
+- Can a new WASM version require newer/different host functions?<!-- .element: class="fragment" -->
+
+Notes:
+
+- Discuss implications of changing host functions.
+
+---
+
+## Tradeoffs of having a dynamic runtime.
+
+- The good: enables forkless upgrades.<!-- .element: class="fragment" -->
+- The not so good:<!-- .element: class="fragment" -->
+  - State migrations are complicated.<!-- .element: class="fragment" -->
+  - Transactions become invalid.<!-- .element: class="fragment" -->
+  - Makes DApps and tooling more complicated.<!-- .element: class="fragment" -->
+
+---
+
+## Tradeoffs of having a dynamic runtime.
+
+- The good: enables forkless upgrades.
+- The not so good:
+  - State migrations are complicated.
+  - Transactions can:
+    - Become invalid.
+    - Have a different outcome.
+  - Makes DApps and tooling more complicated.
+
+---
+
+## Runtime functions:
+
+| How it started                              |            How it's going            |
+| ------------------------------------------- | :----------------------------------: |
+| Core_initialize_block                       |        DryRunApi_dry_run_call        |
+| Core_execute_block                          |          Metadata_metadata           |
+| Block_builder_apply_extrinsic               | NominationPoolsApi_points_to_balance |
+| TaggedTransactionQueue_validate_transaction | Inflation_inflation_prediction_info  |
+
+Notes:
+
+- Discuss why it's a good idea to expose via runtime-apis functions that
+  prevent DApps from re-implementing on-chain logic.
+
+---
+
+## Runtime: who does it cather to?
+
+Runtime functions can be divided in 3 different groups:
+
+- Functions that cather the node: applying extrinsics, handling blocks, etc.<!-- .element: class="fragment" -->
+- Functions that cather DApps: by exposing logic that otherwise would have to be duplicated offchain.<!-- .element: class="fragment" -->
+- Functions that cather both: transaction validation transactions, calculating fees, etc.<!-- .element: class="fragment" -->
+
+---
+
+## Non Host-specific runtime-apis:
+
+- Metadata<!-- .element: class="fragment" -->
+- Fees<!-- .element: class="fragment" -->
+- Dry-Runs<!-- .element: class="fragment" -->
+- View Functions<!-- .element: class="fragment" -->
diff --git a/content/4-Core_and_Basics/2-scale-slides.md b/content/4-Core_and_Basics/2-scale-slides.md
new file mode 100644
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@@ -0,0 +1,443 @@
+---
+title: SCALE
+description: SCALE Codec
+---
+
+# SCALE
+
+---
+
+# SCALE
+
+## Serialization
+
+- The process of translating a data structure or object state into a format that can be stored.<!-- .element: class="fragment" -->
+- Types of Serialization: Self-Describing vs Non Self-Describing<!-- .element: class="fragment" -->
+- Codecs: Encoders/Decoders<!-- .element: class="fragment" -->
+
+---
+
+### Binary Data Recap
+
+- What is a byte? <!-- .element: class="fragment" -->
+- 8 bits => 0 - 255 => u8 <!-- .element: class="fragment" -->
+- The smallest addressable unit of memory <!-- .element: class="fragment" -->
+
+Hexadecimal representation: <!-- .element: class="fragment" -->
+
+- Base-16 number representation <!-- .element: class="fragment" -->
+- (0..15) => 0123456789abcdef <!-- .element: class="fragment" -->
+- The "0x" prefix is commonly used to denote hexadecimal notation <!-- .element: class="fragment" -->
+- Each hexadecimal symbol => 4 bits => 1 "nibble" => 1/2 byte <!-- .element: class="fragment" -->
+- 0110 1010 => 0x6a <!-- .element: class="fragment" -->
+
+---
+
+## SCALE
+
+## Stands for...
+
+- Simple<!-- .element: class="fragment" -->
+- Concatenated<!-- .element: class="fragment" -->
+- Aggregate<!-- .element: class="fragment" -->
+- Litte-Endian<!-- .element: class="fragment" -->
+
+---
+
+## SCALE
+
+Designed for high-performance, copy-free data encoding and decoding in resource-constrained environments.
+
+- Non Self describing: the definitions must be known to decode.<!-- .element: class="fragment" -->
+- Little-Endian: has some performance benefits, like free casting.<!-- .element: class="fragment" -->
+
+---
+
+### Little-Endian
+
+<img src="./endian.png" />
+
+---
+
+## Little-Endian vs Big-Endian Example:
+
+- How to encode the `255` decimal value as a `u32`:
+
+  - Big-Endian: &nbsp;&nbsp; `0x 00 00 00 ff`
+
+  <!-- .element: class="fragment" -->
+
+  - Little-Endian: `0x ff 00 00 00`
+
+  <!-- .element: class="fragment" -->
+
+---
+
+## SCALE Basic Primitives
+
+<ul>
+<li class="fragment">
+u8, u16, u32, u64, u128, u256
+
+```sh
+20  u8  0x 14
+20  u16 0x 14 00
+256 u16 0x 00 01
+```
+
+</li>
+
+<li class="fragment">
+i8, i16, i32, i64, i128, i256
+
+```sh
+1    i8  0x 01
+-1   i8  0x ff
+-1   i16 0x ff ff
+-256 i16 0x 00 ff
+```
+
+</li>
+<li class="fragment">
+boolean (specialized u8)
+
+```sh
+true  0x01
+false 0x00
+```
+
+</li>
+
+Notes:
+
+Nothing fancy here
+
+---
+
+## SCALE: Compact
+
+- It can optimally store any integer from `0` to `2^536` without wasting memory.
+
+<!-- .element: class="fragment" -->
+
+- The least significant 2 **bits** of the **first byte** indicate the number of bytes that are used.
+
+<!-- .element: class="fragment" -->
+
+- `0b 00` => 1 byte, from 0 to 63 (2^6 - 1)
+
+<!-- .element: class="fragment" -->
+
+- `0b 01` => 2 bytes, from 64 to 16383 (2^14 - 1)
+
+<!-- .element: class="fragment" -->
+
+- `0b 10` => 4 bytes, from 16384 to 1073741823 (2^30 - 1)
+
+<!-- .element: class="fragment" -->
+
+- `0b 11` => The remaing bits of the first byte indicate the length (+4)
+
+<!-- .element: class="fragment" -->
+
+---
+
+## SCALE: Compact Examples
+
+- `1` &nbsp; -> `0b 000001 00` &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; -> `0x04`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- `2` &nbsp; -> `0b 000010 00` &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; -> `0x08`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- `3` &nbsp; -> `0b 000011 00` &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; -> `0x0c`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- `63` -> `0b 111111 00` &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;-> `0xfc`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- `64` -> `0b 000000 01 00000001` -> `0x0101`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- `65` -> `0b 000001 01 00000001` -> `0x0501`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+---
+
+## SCALE: Compact
+
+- Exercise:
+  - Manually decode `0x01ff` and `0x05`
+
+---
+
+## SCALE Complex types
+
+A "complex" type is a codec that references other types.
+
+- Tuples: Simply the concatenation of different types of codecs.<!-- .element: class="fragment" -->
+- Structs: Same as tuples, but the values are named.<!-- .element: class="fragment" -->
+- Vectors: A collection of a dynamic size of any other type.<!-- .element: class="fragment" -->
+- Arrays: A collection of static size of any other type.<!-- .element: class="fragment" -->
+- Enum: Discriminated unions (AKA variants, tagged unions...).<!-- .element: class="fragment" -->
+
+<li class="fragment">Specialized Enums:
+<ul>
+  <li>Option: The first byte indicates whether there is a value or not.</li>
+  <li>Result: An Enum which always has 2 different tags, one for success and one for error.</li>
+</ul></li>
+- Specialized Vector: String -> Vector(u8)<!-- .element: class="fragment" -->
+- Opaque: A "meta-type" which is a de-facto standard (an specialized Vector of bytes).<!-- .element: class="fragment" -->
+
+---
+
+# SCALE Complex types: Enum
+
+- The first byte indicates the index of the "tag".
+- Example:
+
+```js
+Enum({
+  foo: u16,
+  bar: boolean,
+  baz: _void,
+});
+```
+
+- `0x000100` => `foo(1)`
+
+<!-- .element: class="fragment" -->
+
+- `0x0100` => `bar(false)`
+
+<!-- .element: class="fragment" -->
+
+- `0x02` => `baz()`
+
+<!-- .element: class="fragment" -->
+
+---
+
+# SCALE Complex types: Enum
+
+## Observations
+
+- Enums make it possible to have circular Codec definitions.
+
+<!-- .element: class="fragment" -->
+
+- `Result` and `Option` are specialized Enums.
+
+<!-- .element: class="fragment" -->
+
+- There can't be more than 256 options.
+
+<!-- .element: class="fragment" -->
+
+---
+
+# SCALE Complex types: Option
+
+- `0x00`: there is no value
+
+<!-- .element: class="fragment" -->
+
+- `0x01`: there is a value.
+
+<!-- .element: class="fragment" -->
+
+- Option(u16) `0x00` -> `null / undefined / void / nil`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- Option(u16) `0x010001` -> `256`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+---
+
+# SCALE Complex types: Result
+
+- `0x00`: Ok
+
+<!-- .element: class="fragment" -->
+
+- `0x01`: Error
+
+<!-- .element: class="fragment" -->
+
+- Result({ Ok: bool, Error: u8 }) `0x0101` -> `Error(1)`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- Result({ Ok: bool, error: u8 }) `0x0000` -> `Ok(false)`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+---
+
+# SCALE Complex types
+
+## Structs and Tuples
+
+- Structs and Tuples are conceptually the same thing, but Structs have named values in its definitions.
+
+<!-- .element: class="fragment" -->
+
+- Example:
+
+<!-- .element: class="fragment" -->
+
+```js
+Tuple(Tuple(u8, u8, u8), boolean, Option(u16));
+```
+
+<!-- .element: class="fragment" -->
+
+```js
+Struct({
+  color: Struct({ red: u8, green: u8, blue: u8 }),
+  isReady: boolean,
+  price: Option(u16),
+});
+```
+
+<!-- .element: class="fragment" -->
+
+---
+
+# SCALE Complex types
+
+## Structs and Tuples
+
+```js
+Struct({
+  color: Struct({ red: u8, green: u8, blue: u8 }),
+  isReady: boolean,
+  price: Option(u16),
+});
+```
+
+### Exercise:
+
+Let's decode:
+
+- `0xff001001010001` -> `{color: {red:255, green:0, blue:16}, isReady:false, price:256}}`<!-- .element: class="fragment" -->
+- `0x0f10000000` -> `{color: {red:15, green:16, blue:0}, isReady:false, price:null}`<!-- .element: class="fragment" -->
+
+---
+
+# SCALE: Complex types:
+
+## Vectors
+
+- A compact encoded value denotes the number of instances.
+
+<!-- .element: class="fragment" -->
+
+- Example:
+
+<!-- .element: class="fragment" -->
+
+```js
+Vector(u8);
+```
+
+<!-- .element: class="fragment" -->
+
+- `[]` => `0x00`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- `[1]` => `0x04 01`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- `[1, 0]` => `0x08 01 00`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+```js
+Vector(compact);
+```
+
+<!-- .element: class="fragment" -->
+
+- `[1, 0]` => `0x08 04 00`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+- `[1, 0, 64]` => `0x0c 04 00 0101`<!-- .element: class="fragment" -->
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+Mention specialized vectors: string, bytes
+
+---
+
+# SCALE: Complex types:
+
+## Arrays
+
+Exactly the same as `Vectors`, with the difference that their size is part of the codec definition, and thus is not
+encoded.
+
+```sh
+Array<u8,4> # [u8;4]
+[2,1,3,0] => 0x 02 01 03 00
+
+Array<u16,2> # [u16;2]
+[258,3]   => 0x 0201 0300
+
+Array<u16,4> # [u16;4]
+[2,1,3,0] => 0x 0200 0100 0300 0000
+```
+
+---
+
+# SCALE
+
+## "Opaque"
+
+- Sometimes its convenient to use a Vector of bytes, so that we don't have to decode everything.
+
+<!-- .element: class="fragment" -->
+
+- Example: The body of a block is: `Vector(Opaque(Extrinsic))` => `Vector(Vector(u8))`
+
+<!-- .element: class="fragment" -->
+
+```sh
+# Vector<Extrinsic>
+{length}{ext_1}{ext_2}{ext_3}{…}
+
+# Vector<Opaque<Extrinsic>> => Vector<Vector<u8>>
+{length}{length_ext_1}{ext_1}{length_ext_2}{ext_2}{…}
+```
+
+<!-- .element: class="fragment" -->
+
+---
+
+### Implementations
+
+SCALE Codec has been many languages, including:
+
+- Rust: [`parity-scale-codec`](https://github.com/paritytech/parity-scale-codec)
+- TypeScript: [`scale-ts`](https://github.com/unstoppablejs/unstoppablejs/tree/main/packages/scale-ts#scale-ts)
+- Python: [`polkascan/py-scale-codec`](https://github.com/polkascan/py-scale-codec)
+- Golang: [`itering/scale.go`](https://github.com/itering/scale.go)
+- C: [`MatthewDarnell/cScale`](https://github.com/MatthewDarnell/cScale)
+- C++: [`soramitsu/scale-codec-cpp`](https://github.com/soramitsu/scale-codec-cpp)
+- AssemblyScript: [`LimeChain/as-scale-codec`](https://github.com/LimeChain/as-scale-codec)
+- Haskell: [`airalab/hs-web3`](https://github.com/airalab/hs-web3/tree/master/packages/scale)
+- Java: [`emeraldpay/polkaj`](https://github.com/emeraldpay/polkaj)
+- Ruby: [`wuminzhe/scale_rb`](https://github.com/wuminzhe/scale_rb)
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+# Core and Basics
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/1-Polkadot_Architecture-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/1-Polkadot_Architecture-slides.md
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+---
+title: Polkadot Architecture
+description: Comprehensive overview of Polkadot’s blockchain scaling architecture, parachain model, coretime resource allocation, interoperability (XCM), including realistic comparisons to traditional distributed systems and web2 vertical scaling limits.
+duration: 30 minutes
+---
+
+# Polkadot Architecture
+
+Notes:
+
+Intro\
+Today we'll explore Polkadot’s blockchain architecture in depth. We'll cover blockchain scalability, parachain and relay chain design, coretime resource allocation, cross-chain interoperability (XCM), and contextualize with comparisons to web2 distributed systems and common scaling limits faced historically by vertical architectures.
+
+---
+
+# The Blockchain Scalability Challenge
+
+Early blockchains (Ethereum L1, Bitcoin) have faced scalability issues:
+
+- Ethereum: ~15–30 TPS
+- Bitcoin: ~7 TPS
+
+High demand quickly congests these blockchains, causing increased costs and poor UX.
+
+Current-gen blockchains like Solana and Ethereum L2s/rollups) achieve higher TPS but introduce notable trade-offs:
+
+- Solana: Thousands of TPS (uhh.. kinda), but higher node hardware requirements.
+- Rollups (Base, Optimism): Lower fees, but sequencer centralization and delayed finality (still not that many TPS).
+
+Notes:
+
+- Explain TPS (transactions per second) clearly.
+- Highlight practical examples of network congestion (CryptoKitties, NFT events, hyped launches).
+
+---
+
+## Web2 Vertical Scaling: History
+
+Traditional web2 applications initially used vertical scaling (scale-up):
+
+- Single powerful servers (monolithic databases, Oracle DB, SQL Server).
+- Upgrade hardware (CPU, RAM) to improve capacity.
+
+Vertical scaling limits:
+
+- Diminishing returns quickly encountered (hardware upgrades increasingly expensive, minimal performance gains).
+- Centralization risks (single points of failure, limited redundancy).
+
+These limits motivated widespread adoption of horizontal scaling (scale-out) strategies in web2:
+
+- Apache Cassandra, MongoDB (distributed databases).
+- Kubernetes, AWS EC2 auto-scaling (cloud infrastructure).
+
+Notes:
+
+- Clearly illustrate historical progression from vertical to horizontal scaling in web2.
+
+---
+
+# Scaling Architectures Compared: Horizontal vs Vertical
+
+## Horizontal Scaling
+
+Multiple parallel nodes increase throughput capacity.
+
+- Analogy: Multiple lanes on a highway.
+- Examples: Kubernetes clusters, Cassandra database nodes.
+- Complexity: Coordinating node communication, state synchronization.
+
+## Vertical Scaling
+
+Single node improved through hardware/software optimization.
+
+- Analogy: Upgrading a single-lane road.
+- Examples: Large Oracle DB instances on powerful hardware.
+- Limitations: Increasingly costly hardware upgrades, inherent physical constraints, centralization risks.
+
+Blockchain analogies clearly evident in Solana's vertical optimization versus Polkadot/Ethereum sharding horizontal strategies.
+
+Notes:
+
+- Clearly contrast horizontal and vertical scaling principles.
+
+---
+
+# Sharding
+
+Sharding partitions data/workloads into smaller subsets ("shards"), processed in parallel:
+
+- Web2 distributed databases (MongoDB, Cassandra) extensively utilize sharding.
+- Blockchain equivalents: Ethereum Blobspace, Polkadot parachains.
+
+Sharding complexity: cross-shard communication, liquidity fragmentation, transaction atomicity/synchronicity.
+
+Notes:
+
+- Clearly explain traditional sharding concepts and connect to blockchain sharding.
+
+---
+
+# Polkadot's Horizontal Scaling
+
+Polkadot implements sharding horizontally via parachains:
+
+- Relay chain: Central minimal chain handling consensus/security ONLY - no execution!
+- Parachains: Independent specialized blockchains handling transactions simultaneously.
+
+Parachains closely resemble microservices architectures - specialized, isolated components with clear roles.
+
+Notes:
+
+- Clearly differentiate relay chain versus parachain roles.
+
+---
+
+## Relay chain: Minimalism & Security
+
+Relay chain principles:
+
+- Security via validators/nominators.
+- BABE (block production) & GRANDPA (finality) consensus.
+- No complex application logic, maximizing efficiency and scalability.
+
+In Web2: Kubernetes control plane—manages orchestration/coordination without running direct user workloads.
+
+Notes:
+
+- Clearly explain minimalist approach benefits.
+- Mention Kubernetes analogy explicitly.
+
+---
+
+## Coretime: Efficient Blockspace
+
+Coretime resource allocation:
+
+- Parachains buy processing resources ("blockspace/coretime") via a marketplace.
+- Efficient, fair allocation prevents resource underutilization (dutch auction model).
+
+In Web2: Cloud computing resource allocation (AWS spot instances) - allocating finite compute resources efficiently via dynamic pricing mechanisms.
+
+Notes:
+
+- Talk more about the concept of blockspace in the industry.
+
+---
+
+## Appchains: Specialization Benefits
+
+Each parachain specialized for particular functions:
+
+- DeFi parachains: Optimized security, settlement assurance.
+- Gaming parachains: Optimized low latency, rapid interactions, low cost.
+
+In web2: Microservices - specialized, optimized services with clearly defined responsibilities, avoiding monolithic inefficiencies.
+
+Notes:
+
+- Clearly connect appchains to relatable web2 concepts.
+
+---
+
+## System Parachains: Infrastructure Foundations
+
+System parachains provide foundational ecosystem infrastructure:
+
+- Asset Hub (asset issuance), bridge parachains (external ecosystem interaction), identity parachains.
+- Critical shared services analogous to DNS, authentication, load balancing in web2 infrastructure.
+
+Notes:
+
+- Clearly explain practical value of system parachains and relatable web2 parallels.
+
+---
+
+# Cross-Chain Interoperability (XCM)
+
+XCM enables secure communication between independent parachains:
+
+- Asset/token transfers.
+- Cross-chain smart contract interactions.
+
+In web2: Message-passing systems like Kafka, RabbitMQ, RPC protocols - enabling communication among independent services.
+
+Notes:
+
+---
+
+## XCM Practical Examples
+
+- Cross-chain decentralized finance (DeFi): aggregating liquidity across financial parachains.
+- Multi-chain governance: synchronized voting, decisions across ecosystem.
+- Shared identity verification across multiple parachains.
+
+Notes:
+
+- Clearly illustrate practical XCM benefits.
+
+---
+
+# Polkadot vs Ethereum Blobspace: Scaling Strategy Comparison
+
+Ethereum and Polkadot employ different scaling strategies:
+
+- Ethereum Blobspace:
+  - Optimized data availability layer supporting rollups.
+  - Off-chain computation focus, minimal state on-chain.
+- Polkadot Coretime/Parachains:
+  - Optimized compute resource allocation via coretime purchases.
+  - Specialized application chains (parachains).
+  - Built-in interoperability via XCM.
+
+Tradeoffs clearly evident: Ethereum emphasizes general rollup-driven scalability, Polkadot emphasizes specialized interoperable shards.
+
+Notes:
+
+- Blobspace vs coretime economic approaches differ wildly, explain this.
+
+---
+
+# Summary: Polkadot’s Architectural Strengths
+
+Polkadot uniquely combines:
+
+- Effective horizontal scalability (parachains).
+- Minimalist central security via relay chain.
+- Efficient resource allocation via Coretime.
+- Specialized chains tailored per use-case (appchain model).
+- Native, standardized cross-chain interoperability (XCM).
+
+Together these design choices enable practical blockchain scalability solutions.
+
+Notes:
+
+- Clearly summarize key strengths succinctly.
+
+---
+
+# The Future
+
+Polkadot represents a mature, realistic scaling solution acknowledging trade-offs inherent in any distributed system. Its architecture—parachains, relay chain minimalism, coretime allocation, and XCM interoperability—positions it well for the next phase of blockchain scaling (JAM).
+
+Future roadmap includes increased parachain capacity, enhanced interoperability, and ever-increasing DevEx.
+
+Notes:
+
+- Basically tease JAM :).
+
+---
+
+# Q&A Session
+
+Open session for questions.
+
+Notes:
+
+---
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/11-inkubator-presentation-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/11-inkubator-presentation-slides.md
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+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/11-inkubator-presentation-slides.md
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+---
+title: ink!ubator
+description: Take your ink! projects to new depths
+---
+
+<p>All presentations can be found in different formats at the links below:</p>
+<p><a href="https://github.com/Polkadot-Blockchain-Academy/pba-content/blob/main/assets/ink!ubator_PBA6_2025.pdf" target="_blank">PDF format</a></p>
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/2-Smart-Contracts-101-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/2-Smart-Contracts-101-slides.md
new file mode 100644
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+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/2-Smart-Contracts-101-slides.md
@@ -0,0 +1,622 @@
+---
+title: Smart contracts fundamentals
+description: Introduction to fundamentals smart conctracts concepts
+duration: 45min
+url: http://localhost:1948/syllabus/3-PVM-Polkadot-Architecture-and-Smart-Contracts/2-Smart-Contracts-101-slides.md
+---
+
+<style>
+    code {
+        overflow: hidden!important;
+        width: 120%!important;
+    }
+</style>
+
+## Smart contracts fundamentals
+
+Notes:
+The goal of the lecture is to define the basic definition of what a SC is
+and explain the advantage and trade off of a smart contract chain
+
+---
+
+# WHY?
+
+Notes:
+
+- Always start with the why!
+- 2 things to answers here:
+  - One, The benefits of smart contracts as a technology: Smart Contracts are a huge improvement over traditional legal contracts, that are slow, expensive, and error-prone.
+    With smart contracts, you can automate the execution of agreements, enforce them automatically, and remove the need for intermediaries. E.g crop insurance.
+  - Two, For the Polkadot ecosystem, it's important to embrace a technology that is widely adopted by the Ethereum
+    community, so that we can leverage the tooling, and easily onramp existing dapps, but also users and developers.
+
+---v
+
+## Crop Insurance contract
+
+<img style="width: 80%"  src="img/smart-contracts-101/crop-insurance.png" />
+
+Notes:
+See <https://www.owlexplains.com/en/podcast/ep-8-how-lemonade-is-using-smart-contracts-to-revolutionize-crop-insurance/>
+
+---v
+
+## Ecosystem
+
+<img style="width: 80%"  src="img/smart-contracts-101/ecosystem.png" />
+
+---
+
+## Blockchain
+
+<img style="width: 90%"  src="img/smart-contracts-101/stf.png" />
+
+Notes:
+
+Before defining what a smart contract (SC) is, we need to understand the environment in which it operates: the blockchain.
+We won’t dive deep into what a blockchain is, that will be covered in detail during the PBA. For now, it's enough to define a blockchain as:
+A distributed system where all participants (nodes) execute a common set of transactions contained in a block.
+These transactions are processed using a state transition function, which updates the blockchain’s state from block n to block n+1.
+
+---v
+
+### Bitcoin
+
+<img style="width: 90%"  src="img/smart-contracts-101/stf-btc.png" />
+
+Notes:
+
+In Bitcoin, the state transition function primarily processes transactions, which are mostly transfer transactions.
+
+---v
+
+### Polkadot
+
+<img style="width: 90%"  src="img/smart-contracts-101/stf-dot.png" />
+
+Notes:
+
+Blockchains built with Substrate run a WebAssembly (Wasm) runtime, which defines how the blockchain's state is updated.
+This runtime is built using Rust modules, called pallets, each defining specific transaction types.
+
+Different pallets allow developers to introduce specialized logic into their blockchain:
+Assets & NFT pallets → Define fungible and non-fungible tokens and their operations.
+Democracy pallet → Enables on-chain governance, allowing proposals to be submitted, voted on, and enacted when approved.
+Other pallets can introduce staking mechanisms, cross-chain messaging, DAOs, and more.
+
+Polkadot's state transition function can execute any business logic defined in the runtime.
+However, the runtime itself is not permissionless—it must be explicitly defined and deployed by the chain’s developers or governance
+To allow arbitrary logic execution, a Smart Contracts module must be embedded in the runtime.
+Otherwise, only predefined transaction types (e.g., assets, governance, staking) can be executed.
+
+---v
+
+### Smart contracts chain
+
+<img style="width: 90%"  src="img/smart-contracts-101/stf-evm.png" />
+
+Notes:
+
+Now, we can finally define what a smart contract is.
+A smart contract is a special type of account that is not controlled by a keypair, but instead by the code it defines.
+A smart contract blockchain allows users to do essentially 3 things:
+
+- Transfer value between accounts.
+- Deploy contracts on-chain.
+- Call these contracts to execute their logic.
+
+You can think of smart contracts as dormant programs stored on the blockchain at a specific address.
+These programs can access and store data on the blockchain, and execute logic based on the transactions they receive.
+
+For example, the USDC smart contract, is an ERC-20 token that maintains a mapping of balances, associating each user’s address with the amount of USDC they hold. When a user transfers USDC, the contract updates the sender’s balance by subtracting the amount, adds the same amount to the recipient’s balance, and stores the new state on-chain to ensure all nodes remain synchronized
+
+---
+
+## Bytecode & Virtual Machines
+
+<img style="width: 100%; " src="img/smart-contracts-101/bytecode-vm.png" />
+
+Notes:
+
+When we deploy a smart contract on-chain, we first compile it into bytecode, which can be executed by a virtual machine.
+Different smart contract blockchains use different bytecode formats.
+
+The state transition function of the blockchain runs the Virtual Machine to execute the instructions in this compiled bytecode, and update the state of the chain.
+
+---
+
+### A simple Example
+
+```solidity[4-9|11-15|18-24]
+// SPDX-License-Identifier: MIT
+pragma solidity ^0.8.0;
+
+contract PiggyBank {
+    address public immutable owner;
+
+    constructor() {
+        owner = msg.sender;
+    }
+
+    function getBalance() public view returns (uint256) {
+      return address(this).balance;
+    }
+
+    function deposit() public payable {}
+
+
+    function withdraw(uint256 withdrawAmount) public {
+        require(msg.sender == owner, "You are not the owner");
+        require(address(this).balance >= withdrawAmount, "Insufficient balance");
+
+        (bool success, ) = payable(msg.sender).call{value: withdrawAmount}("");
+        require(success, "Transfer failed");
+    }
+}
+```
+
+Notes:
+On EVM-compatible chains, the most widely used language is Solidity, that is compiled to bytecode using the `solc` compiler.
+Let's go through a simple `PiggyBank` solidity contract to illustrate it.
+
+- When a contract is deployed, the constructor code is executed
+- The owner can call the deposit function to deposit some balance
+- The view function `GetBalance` is a 'readonly' function that can be queried through a JSON-RPC call
+- If you send ETH directly to the contract (without calling a function like deposit), it will fail unless the contract has a receive or fallback function.
+  Without one of these, any direct transfer (e.g., sendTransaction from a wallet) will be rejected with an error.
+
+---
+
+## Core Features of Smart Contracts
+
+---v
+
+### Gas
+
+<pba-flex center>
+
+<img rounded style="width: 400px"  src="img/smart-contracts-101/gas.jpg" />
+
+```solidity
+    while (true) {
+        // ...
+        // This loop will consume all gas and revert
+    }
+}
+```
+
+<!-- .element: class="fragment" -->
+</pba-flex>
+
+Notes:
+
+You might be wondering—if a smart contract can execute any arbitrary logic, what prevents it from defining an infinite loop that could stall the entire blockchain?
+To prevent this and to protect the network from spam, virtual machines are metered. Every instruction executed by the VM has an associated gas cost, which represents the computational resources required to process it.
+
+When you submit a transaction or when a contract calls another contract, you must specify the maximum amount of gas you’re willing to pay for execution. The contract’s code will either:
+
+- Run to completion if there is enough gas.
+- Run out of gas and revert, undoing any changes made to the contract storage, but you will still pay for the gas that was consumed before the failure.
+
+Additionally, the blockchain itself imposes limits on gas usage:
+It defines a block gas limit, which sets the maximum amount of gas that can be used across all transactions in a single block.
+It also defines a gas price, which determines how much fees will be paid for a given amount of gas.
+blockchains usually adjust gas prices dynamically based on network demand, ensuring fees reflect current congestion levels
+This system ensures that no contract can consume unlimited resources, execution remains bounded, and transaction fees dynamically adjust based on network demand.
+
+---v
+
+#### Metered calls in EVM
+
+<diagram class="mermaid">
+%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
+flowchart LR
+    Start --> FetchNextOpcode[Fetch next opcode]
+    FetchNextOpcode --> LookupCost[Look up opcode cost]
+    LookupCost --> CheckGas{Enough gas?}
+    CheckGas -- No --> OutOfGas[Throw Out of Gas]
+    CheckGas -- Yes --> DeductGas[Deduct gas]
+    DeductGas --> ExecuteOpcode[Execute Opcode]
+    ExecuteOpcode --> FetchNextOpcode
+</diagram>
+
+Notes:
+
+- In pallet-revive the graph is slightly different, regular opcode are not metered but the VM injects gas metering
+  instructions per basic block
+- Checks before each opcode to make sure gas can be paid
+- Safe: prevents unpaid work from being done
+- Deterministic: results are unambiguous
+- Very inefficient: lots of branching and extra work
+
+---v
+
+#### Weighted calls in substrate
+
+```rust[1-8]
+#[pallet::weight(T::WeightInfo::set_metadata(name.len(), symbol.len()))]
+pub fn set_metadata(
+    origin: OriginFor<T>,
+    id: T::AssetIdParameter,
+    name: Vec<u8>,
+    symbol: Vec<u8>,
+    decimals: u8,
+) -> DispatchResult {
+    let origin = ensure_signed(origin)?;
+    let id: T::AssetId = id.into();
+    Self::do_set_metadata(id, &origin, name, symbol, decimals)
+}
+```
+
+Notes:
+In Substrate, each call defines a pre-dispatch weight, which can depend on the input parameters. Accounts must pay the estimated execution fee upfront, and any excess is refunded after execution.
+
+---v
+
+#### Metered VM Execution vs. Weighted Calls in Substrate
+
+| Feature             | EVM                            | Substrate                                |
+| ------------------- | ------------------------------ | ---------------------------------------- |
+| **Execution Model** | Metered                        | Pre-dispatch weights                     |
+| **Cost**            | Dynamic                        | Static, determined pre-dispatch          |
+| **Performance**     | Runtime overhead               | Optimized execution                      |
+| **Flexibility**     | Supports arbitrary computation | Requires (benchmnarked) weights per call |
+
+Notes:
+
+In VM-based blockchains, execution is metered using gas.
+This makes execution flexible but introduces runtime overhead due to dynamic metering.
+
+Contract execution performance is **less predictable**, as total costs depend on actual execution flow.
+Wallet usually need to dry-run the execution to define how much gas is required for the execution.
+
+In Substrate-based chains, execution is handled differently
+
+- Instead of metering each instruction at runtime, calls have predefined weights based on computational complexity.
+- This approach enables more efficient execution compared to metered VM, as the chain doesn’t need to meter each instruction dynamically, reducing runtime overhead.
+
+---
+
+### Composability
+
+<img rounded style="width: 500px"  src="img/smart-contracts-101/composability.jpg" />
+
+Notes:
+Smart contracts are highly composable, meaning they can interact with each other to execute complex workflows. A contract call is always initiated by an Externally Owned Account (EOA) through a transaction.
+
+---v
+
+### Call types
+
+- Normal Call: Contract A calls Contract B
+- Static Call: Contract A reads data from Contract B
+- Delegate Call: Contract A executes Contract B in its execution context
+
+Notes:
+Methods for contract interaction include:
+
+- **Normal Call**:
+
+  - Contract A calls Contract B.
+  - Contract B is pushed to the call stack, executes, potentially updates its state, and may call other contracts.
+  - Contract B returns control to Contract A along with the result and status (reverted or successful).
+    An example for this would be a contract that calls another contract to transfer tokens.
+
+- **Static Call**:
+
+  - Contract A calls Contract B.
+  - Contract B executes but cannot make state changes.
+    An example for this would be a contract that reads data from another contract, e.g a price feed.
+
+- **Delegate Call**:
+  - Contract A calls Contract B in its execution context. (Storage reads/writes affect A, not B)
+  - Contract B can read and write to A's storage, akin to a library executing within A.
+    An example for this would be to use a Math library to perform calculations.
+
+A good mental model is to think of smart contracts as the API layer of web3. Your contract can tap into other contracts
+to access their functionality, read and write data and execute complex workflows. A good example of that are flash loans
+on the Aave protocol, where a contract can borrow funds from the protocol, execute a series of transactions and repay
+the loan in the same transaction.
+
+---
+
+### Call types
+
+<img style="height: 90%"  src="img/smart-contracts-101/call-stack-1.png" />
+
+---v
+
+### Call types
+
+<img style="height: 90%"  src="img/smart-contracts-101/call-stack-2.png" />
+
+---v
+
+### Call types
+
+<img style="height: 90%"  src="img/smart-contracts-101/call-stack-3.png" />
+
+---v
+
+### Precompiled Contracts
+
+<img rounded style="width: 500px"  src="img/smart-contracts-101/precompiles.jpg" />
+
+Notes:
+
+Another important feature of smart contracts is the ability to interact with precompiled contracts.
+A precompile contract is a contract whose code is defined in the client software directly.
+On Ethereum, that has a slow VM, it's used to perform computation intensive operations like elliptic curve cryptography,
+outside the EVM, to improve performance.
+In Substrate, a Smart-Contract pallet, can leverage this to expose other features of the runtime (like staking, xcm, governance, assets) to smart contracts
+
+---v
+
+### Immutability
+
+<img rounded style="width: 500px"  src="img/smart-contracts-101/Immutability.jpg" />
+
+Notes:
+Contracts are immutable by design, however in some circumstances, you might want to upgrade to fix a bug or add or
+improve existing features. There are several patterns to achieve this, one of the most common is the Proxy pattern.
+Essentially, the proxy pattern involves creating a proxy contract that delegates calls to an implementation contract.
+When you want to upgrade the contract, you deploy a new implementation contract and update the proxy to point to the new implementation.
+
+---v
+
+#### Smart Contract vs. Substrate Upgrades
+
+|                   | Smart Contracts                       | Substrate                              |
+| ----------------- | ------------------------------------- | -------------------------------------- |
+| **Upgradability** | Immutable (requires proxy)            | Yes through Runtime Upgrade            |
+| **Governance**    | Contract owner / DAO                  | Sudo / On-chain OpenGov                |
+| **Overhead**      | Gas costs for proxy & state migration | No gas cost (protocol-level execution) |
+
+---
+
+## Security
+
+<img rounded style="width: 500px"  src="img/smart-contracts-101/security.jpg" />
+
+Notes:
+
+Permissionless Deployment is Risky
+
+Anyone can deploy a smart contract, but if "code is law," any bug or vulnerability can be exploited.
+Attackers actively search for vulnerabilities in deployed contracts.
+Even small logic errors or gas inefficiencies can be exploited for financial gain.
+
+- Security audits are essential before deploying contracts that manage funds.
+- Use battle-tested smart contract libraries (e.g., OpenZeppelin).
+- Follow established design patterns to avoid common vulnerabilities (e.g., reentrancy).
+- Implement proper access control to prevent unauthorized actions.
+
+---v
+
+### Reentrency bug
+
+```solidity[1-2|4-12]
+contract Vulnerable {
+    mapping(address => uint256) public balances;
+
+    function withdraw() external {
+        uint256 amount = balances[msg.sender];
+
+        //❗ Sends ETH before updating balance
+        (bool success, ) = msg.sender.call.value(amount)("");
+        require(success, "Transfer failed.");
+
+        //❗ Balance Update after Transfer - Allows Reentrancy!
+        balances[msg.sender] = 0;
+    }
+}
+```
+
+Note:
+see <https://blog.chain.link/reentrancy-attacks-and-the-dao-hack/>
+
+---v
+
+### Activity: Reproduce the DAO hack
+
+> Deploy and execute the DAO hack on a local chain
+
+Note:
+see <https://github.com/paritytech/contracts-boilerplate>
+
+---
+
+## JSON-RPC
+
+- JSON-RPC is a **remote procedure call (RPC) protocol** using JSON for encoding requests and responses.
+- It allows **external applications, wallets, and scripts** to interact with blockchain nodes.
+- Most chains expose a **JSON-RPC API** for querying blockchain data and sending transactions.
+
+---v
+
+### Common Ethereum JSON-RPC Methods
+
+| Method                      | Description                                     |
+| --------------------------- | ----------------------------------------------- |
+| `eth_call`                  | Executes a read-only contract call.             |
+| `eth_estimateGas`           | Estimates the gas required for a transaction.   |
+| `eth_sendRawTransaction`    | Sends a raw, signed transaction to the network. |
+| `eth_getTransactionReceipt` | Retrieves transaction execution details.        |
+
+Note:
+
+- There are two types of transactions: read-only and state-changing transactions.
+  When you want to read data from a contract, you use `eth_call` to execute a read-only contract call.
+
+- When you want to send a transaction to the network, you will usually follow this flow:
+- Estimate the gas required for the transaction using `eth_estimateGas`.
+- Sign and submit the transaction using `eth_sendRawTransaction`.
+- Finally, you can poll `eth_getTransactionReceipt` with the transaction hash to retrieve the transaction execution details.
+
+The receipt is an important object, used by wallet and JS libraries, it will contain
+
+- The transaction status
+- Gas used, and logs generated during execution.
+
+---v
+
+### Common Substrate JSON-RPC Methods
+
+| Method                   | Description                              |
+| ------------------------ | ---------------------------------------- |
+| `state_call`             | Calls a runtime API exposed by a pallet. |
+| `author_submitExtrinsic` | Submits a signed transaction             |
+
+---v
+
+### Example sending a raw transaction
+
+```json
+curl https://westend-asset-hub-eth-rpc.polkadot.io \
+-H 'content-type: application/json' \
+-d '{
+  "method":"eth_sendRawTransaction",
+  "params" ["0x02f8b3018313c1..."],
+  "id":2
+  ,"jsonrpc":"2.0"
+}'
+```
+
+---v
+
+## Structure of a Transaction
+
+```sh
+> cast decode-tx 0x02f8b3018313c17...
+```
+
+<!--https://etherscan.io/getRawTx?tx=0xcd58fbee0f90c4b7136a5af85876090dd1593e4580f840bcf0a7b9219772a5d4-->
+
+```json
+{
+  "type": "0x2",
+  "chainId": "0x1",
+  "nonce": "0x13c174",
+  "gas": "0x249f0",
+  "maxFeePerGas": "0x746a528800",
+  "maxPriorityFeePerGas": "0x878415",
+  "to": "0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48",
+  "value": "0x0",
+  "input": "0x...",
+  "r": "0xc330502a046982553df56842433dfb1f318c980724bfd30be53e6461cea620ac",
+  "s": "0x25217d80ae9538009b3b24ab83fdac6df67982b433f74488d2c14fee41ca2d79",
+  "yParity": "0x0",
+  "v": "0x0"
+}
+```
+
+<a target="_blank" href="https://etherscan.io/tx/0xcd58fbee0f90c4b7136a5af85876090dd1593e4580f840bcf0a7b9219772a5d4">Etherscan</a>
+
+Notes:
+A few things to note in the transaction:
+
+- First of all the transaction is encoded using RLP (Recursive Length Prefix) encoding, the first byte is the type of the
+  transaction, and defines the format of the transaction, that can be decoded using rlp-decode.
+- The type here is 0x2, which means it is an EIP-1559 transaction introduced by the London fork, new fork can sometimes introduce new transaction type
+  to define new transaction format, this type field is used to distinguish between them.
+- The chainId defines the network on which the transaction is being sent, this makes sure that the transaction is not replayed on another network.
+- The nonce is a very important component of the transaction, it is used to prevent replay attacks, it is incremented for each transaction sent by an account, your transaction will only be executed if the nonce is the next in line.
+- gas, maxFeePerGas, maxPriorityFeePerGas are used to define the cost and fees generated for the transaction.
+- value is the amount of ether being sent in the transaction.
+- input is the ABI encoded data of the function being called, in this case, it is the transfer function of an ERC20 token, we will see how to decode this later.
+- r, s, v are the signature of the transaction, used to verify the transaction was signed by the sender.
+
+You will notice that the transaction does not have a 'from' field, this is because the origin can be recovered from the signature.
+
+---v
+
+### ABI decoding
+
+```sh[1-7|8-13]
+INPUT="0xa9059cbb000000000000000000000000ba04f1c1e4577165dd2297d3fbedf956b0e4c8a70000000000000000000000000000000000000000000000000000000004cc7c30"
+
+# Get the selector for a function
+> cast keccak "transfer(address,uint256)" | cut -c 1-10 # or cast sig "..."
+
+0xa9059cbb
+
+# Lookup the function signature and input data
+> cast 4byte-decode $INPUT
+
+1) "transfer(address,uint256)"
+0xBA04f1c1E4577165dD2297D3FbEdF956B0e4C8a7
+80510000 [8.051e7]
+```
+
+Notes:
+Now that we have decoded the transaction, let's look at how the input data is encoded
+
+- The first 4 bytes of the input data are the function selector
+- They are derived from the first 4 bytes of the keccak hash of the function signature.
+- The VM use the selector to lookup the address of the function being called (here the transfer function), and jump to it.
+- The rest of the input are the ABI encoded parameter of the function
+
+---v
+
+### Encoding ABI parameters
+
+```sh
+cast abi-encode \
+  "test(bool, string, address)" \
+  "true"  "hello" "0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48" \
+| xxd -r -p | xxd -c 32
+```
+
+```hexdump[1 | 2 | 4 | 5 | 3]
+00: 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0001
+20: 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0060
+40: 0000 0000 0000 0000 0000 0000 a0b8 6991 c621 8b36 c1d1 9d4a 2e9e b0ce 3606 eb48
+60: 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0005
+80: 6865 6c6c 6f00 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000
+```
+
+Notes:
+
+Let's look at how the parameters are encoded using EVM ABI encoding standard.
+The ABI defines the standard way to interact with contracts both from outside the blockchain and for contract-to-contract interaction
+
+The EVM operates on 32-byte words, meaning that all storage, memory, and stack operations use 32-byte slots.
+Arguments are padded and aligned to 32 bytes, to make it easy to read or load them from memory during execution.
+
+For this example signature the data is encoded as follows:
+
+- The first element is a bool. Even though a bool is just 1 byte, like everything in the EVM, it is padded to 32 bytes.
+- The string is dynamic type, so instead of being stored inline, its offset (0x60) is stored next.
+- The address is a fixed-size type, so it’s stored inline immediately after the offsets.
+- At offset 0x60, we find the length of the string, and right after that, the string content itself.
+
+See <https://docs.soliditylang.org/en/latest/abi-spec.html>
+
+---
+
+## Beyond Smart Contracts
+
+- 🔎 Block Explorers (e.g., Etherscan, Subscan)
+- 🔮 Oracles (e.g., Chainlink, Redstone)
+- 📊 Indexers (e.g., The Graph, Subsquid)
+
+Notes:
+Bock explorers:
+
+- Track transactions and smart contract states
+- Enable transparency & debugging tools for developers
+- Examples: Etherscan, Subscan, Blockscout
+  Orcales:
+- Enable hybrid on-chain/off-chain contracts
+- Examples: Chainlink, Redstone
+- Deliver real-world data on-chain for smart contracts (e.g., price feeds, weather, events)
+- Two models
+  - Push: Data is pushed by node operators at specific interval and made available to contracts
+  - Pull: Signed data package is attached to the transaction and verified by a contract on chain
+    Indexers:
+- Blockchain are write optimized, and querying data can be slow
+- Indexers subscribe to the blockchain and store the data in a more queryable format
+- Allow fast and structured access to blockchain records
+- Improve UX for dApps by reducing raw node queries
+- Examples: The Graph, Subsquid
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/3-Platform_Agnostic_Bytecode-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/3-Platform_Agnostic_Bytecode-slides.md
new file mode 100644
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+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/3-Platform_Agnostic_Bytecode-slides.md
@@ -0,0 +1,552 @@
+---
+title: Platform Agnostic Bytecode
+description: What are PABs and why they exist?
+duration: 20 minutes
+---
+
+# Platform Agnostic Bytecode
+
+---
+
+## Review of Compilers
+
+<img src="./img/pab/compiling.png" />
+
+🤯 Fun Side Reading: <!-- .element: class="fragment" data-fragment-index="1" -->
+[Reflections on Trusting Trust](https://www.cs.cmu.edu/~rdriley/487/papers/Thompson_1984_ReflectionsonTrustingTrust.pdf) <!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+Just a very quick reminder of how compilers work.
+Humans write programs in some human readable language like Lauren talked about.
+Then the compiler translates the semantics of that program into an equivalent program in a much lower more machine-readable language called a bytecode.
+
+CLICK
+
+Whenever I show this diagram or talk about compilers, I always like to mention one of my favorite essays ever.
+Ken Thompson's 1984 Turing Award lecture.
+
+---
+
+## Definition
+
+A PAB is a bytecode that follows two main principles:
+
+- Turing Completeness, as a standard bytecode would respect
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Support for tooling that makes it executable on every machine
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+Ideally a bytecode like this is designed to be executed on a virtual machine that follows general known patterns.
+
+---
+
+<pba-cols>
+<pba-col left>
+
+<pba-flex center>
+
+###### High Level Languages
+
+<img style="width: 30%" src="./img/pab/rust_logo.png" />
+
+<img style="width: 30%" src="./img/pab/c_logo.png" />
+
+<img style="width: 30%" src="./img/pab/c++_logo.png" />
+
+</pba-flex>
+</pba-col>
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+<pba-col center>
+<pba-flex center>
+
+###### PABs
+
+<img style="width: 30%" src="./img/pab/jvm_logo.png" />
+<img style="width: 30%" src="./img/pab/wasm_logo.png" />
+<img style="width: 20%" src="./img/pab/eth_logo.png" />
+<img style="width: 30%" src="./img/pab/risc-v_logo.png" />
+
+</pba-flex>
+</pba-col>
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+<pba-col right>
+<pba-flex center>
+
+###### Architecture's bytecode
+
+<img style="width: 30%" src="./img/pab/intel_logo.png" />
+<img style="width: 30%" src="./img/pab/arm_logo.png" />
+<img style="width: 30%" src="./img/pab/risc-v_logo.png" />
+
+</pba-flex>
+</pba-col>
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+</pba-cols>
+
+Notes:
+
+From left to right you can see different levels of abstraction over the program that will ultimately be run on some machine.
+Generally, from a high level language you need two compilation step if you want to pass through a PAB.
+
+Other examples of PABs used right now:
+
+- Inside the Linux Kernel -> eBPF
+- Inside browsers -> Wasm
+- Inside Blockchains -> Wasm
+  - Full nodes
+  - Light nodes (Wasm inside Wasm)
+- LLVM Toolchain -> LLVM IR
+
+---v
+
+## Compiling in a PAB
+
+<img src="./img/pab/compiling_twice.png" />
+
+Notes:
+
+So when we are using a PAB, we need to compile twice.
+This is, of course, the cost to using a PAB.
+In this lesson we'll also explore the advantages.
+
+---
+
+#### What a PAB allows is:
+
+<pba-flex center>
+
+- Portability
+  <!-- .element: class="fragment" data-fragment-index="1" -->
+      - Avoid Hardware Centralization
+  <!-- .element: class="fragment" data-fragment-index="3" -->
+- Determinism
+  <!-- .element: class="fragment" data-fragment-index="2" -->
+      - Make consensus possible
+  <!-- .element: class="fragment" data-fragment-index="4" -->
+
+</pba-flex>
+
+Notes:
+
+The main goal of a PAB is to make the code **portable**, you should be able to compile it once and then share it around without caring about the architecture on which will be executed. Of course in a decentralized network we want that different nodes, with different architectures came up to the same result if the input are the same, that's called **determinism**, if a PAB would not have determinism then reaching consensus is impossible.
+
+---v
+
+##### That's why PABs are so important
+
+---
+
+## Desireable Features
+
+- Hardware Independence
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Efficiency: minimize overhead vs. native
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- Tool Simplicity
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+- Support as Compilation Target
+
+<!-- .element: class="fragment" data-fragment-index="4" -->
+
+- Sandboxing
+
+<!-- .element: class="fragment" data-fragment-index="5" -->
+
+- Deterministic execution
+
+<!-- .element: class="fragment" data-fragment-index="5" -->
+
+Notes:
+
+- Hardware Independence: It should not be tightly related to a specific architecture, otherwise the execution on different machine could be convoluted
+- Efficiency: the execution and compilation of a PAB should be efficient, the problem for a PAB is that in the execution time is also considered the "translation" to the machine's bytecode or the interpretation
+- Support as Compilation Target: The PAB should be possible to be compiled by as many as possible High Level languages
+- Tool Simplicity: If the tools that makes the PAB executable are extremely complex then nobody will use it
+- Deterministic execution: Same execution (always) on any platform
+
+---v
+
+### Sandboxing?
+
+An environment for running untrusted code without affecting the host.
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+<img style="height: 300px" src="./img/pab/sandbox.jpg" />
+
+A SmartContract is _Arbitrary Code_ that may be executed on other people's infrastructure, we don't want SmartContracts capable of destroying the nodes on which they are executed
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+CLICK read definition
+
+The term sandbox is an analogy to kids playing in a sandbox.
+The parent puts the kid in the sandbox and tells them they can play in the sandbox and they are safe as long as they stay in.
+Don't go in the woods and get bitten by a snake or in the road and get hit by a car.
+Just stay in the sandbox.
+
+Of course the analogy isn't perfect.
+The children in the sandbox stay there because the parent asked them to.
+They could leave anytime they wanted to.
+For actual untrusted code, a better analogy would be a walled garden or a Jail
+
+---v
+
+### Sandboxing?
+
+<img src="./img/pab/jail.jpg" /> <!-- .element: class="fragment" data-fragment-index="1" -->
+
+A sandboxed environment must be created by the executor of the PAB.
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+Of course the security can be seen by various point of view and some examples are:
+
+- Compilation takes too much time -> "compiler bomb"
+- Access to the environment -> "buffer overflow" techniques
+
+Those things can't be addressed by the PAB itself but they can give good guidelines and code design to make an 100% secure implementation of the executor possible.
+
+---
+
+## PAB's lifecycle example
+
+<div class="r-stack">
+<img style="width: 70%" src="./img/pab/pab_path_1.svg" />
+<img style="width: 70%" src="./img/pab/pab_path_2.svg"/>
+<!-- .element: class="fragment" data-fragment-index="1" -->
+<img style="width: 70%" src="./img/pab/pab_path_3.svg"/>
+<!-- .element: class="fragment" data-fragment-index="2" -->
+<img style="width: 70%" src="./img/pab/pab_path_4.svg"/>
+<!-- .element: class="fragment" data-fragment-index="3" -->
+<img style="width: 70%" src="./img/pab/pab_path_5.svg"/>
+<!-- .element: class="fragment" data-fragment-index="4" -->
+<img style="width: 70%" src="./img/pab/pab_path_6.svg"/>
+<!-- .element: class="fragment" data-fragment-index="5" -->
+</div>
+
+---
+
+<pba-cols>
+<pba-col center>
+
+# WebAssembly
+
+- Parachain validation function
+- Contracts (so far)
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+</pba-col>
+<pba-col center>
+
+<img style="width: 70%" src="https://upload.wikimedia.org/wikipedia/commons/thumb/1/1f/WebAssembly_Logo.svg/1200px-WebAssembly_Logo.svg.png" />
+
+</pba-col>
+</pba-cols>
+
+---
+
+## WebAssembly and Polkadot
+
+<img style="width: 70%" src="img/wasm/polkadot.png" />
+
+---
+
+## Wasm's key points
+
+<pba-flex center>
+
+- Hardware independent
+  <!-- .element: class="fragment" data-fragment-index="1" -->
+  - Binary instruction format for a stack-based virtual machine
+  - Altough with "locals" (registers) and higher level control flow elements
+  <!-- .element: class="fragment" data-fragment-index="1" -->
+- Supported as compilation target by many languages
+  <!-- .element: class="fragment" data-fragment-index="2" -->
+  - Rust, C, C++ and many others
+  <!-- .element: class="fragment" data-fragment-index="2" -->
+- Fast (with near-native performance when compiled - more later)
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+- Safe (executed in a sandboxed environment)
+
+<!-- .element: class="fragment" data-fragment-index="4" -->
+
+</pba-flex>
+
+Notes:
+
+Wasm seems to respect every rating points we defined before
+
+---
+
+## Stack-Based Virtual Machine Example
+
+<pba-cols>
+<pba-col center>
+
+Adding two number in wasm text representation (.wat)
+
+<!-- .element: class="fragment fade-out" data-fragment-index="1" -->
+
+```wasm [1-12|5|6|8]
+(module
+  (import "console" "log" (func $log (param i32)))
+  (func $main
+    ;; load `10` and `3` onto the stack
+    i32.const 10
+    i32.const 3
+
+    i32.add ;; add up both numbers
+    call $log ;; log the result
+  )
+  (start $main)
+)
+```
+
+<!-- .element: class="fragment" data-fragment-index="0" -->
+
+</pba-col>
+<pba-col center>
+
+<div class="r-stack">
+<img src="./img/pab/stack_1.svg" style="width: 100%">
+<!-- .element: class="fragment" data-fragment-index="1" -->
+<img src="./img/pab/stack_2.svg" style="width: 100%">
+<!-- .element: class="fragment" data-fragment-index="2" -->
+<img src="./img/pab/stack_3.svg" style="width: 100%">
+<!-- .element: class="fragment" data-fragment-index="3" -->
+<img src="./img/pab/stack_4.svg" style="width: 100%">
+<!-- .element: class="fragment" data-fragment-index="4" -->
+<img src="./img/pab/stack_5.svg" style="width: 100%">
+<!-- .element: class="fragment" data-fragment-index="5" -->
+<img src="./img/pab/stack_6.svg" style="width: 100%">
+<!-- .element: class="fragment" data-fragment-index="6" -->
+</div>
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Wasm has also a text representation,
+Wat has some features that allow for better readability:
+
+- Stack push operations can be grouped to its consuming instruction.
+- Labels can be applied to elements.
+- Blocks can enclosed with parenthesis instead of explicit start/end instructions.
+
+Instructions push results to the stack and use values on the stack as arguments, the compilation process generally translate this stack-based bytecode to register based, where registers are used to pass values to instructions as a primary mechanism. The compilation will try to elide the wasm stack and work with only the architecture registers.
+
+There is another type of stack used in wasm and that's called: shadow stack, resource to learn more: https://hackmd.io/RNp7oBzKQmmaGvssJDHxrw
+
+---
+
+## How Wasm is executed
+
+<pba-flex left>
+
+There are multiple ways to execute wasm:
+
+- Ahead Of Time Compilation
+  - Program is stored in executable format on disk
+  - Thus it can be executed directly (after linking and loading)
+- Just in Time Compilation
+  - Program isn't stored in executable format
+  - Instead it's compiled into an executable format just before it is executed
+- Single Pass Compilation
+  - Same as JIT but tries to minimize work done during compilation
+  - Used in situations when JIT can't spend much time
+- Interpretation
+  - Program isn't store in executable format and never compiled into such
+  - Instead, the programs instruction are _interpreted_ one by one
+- ...
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+</pba-flex >
+
+Notes:
+
+AOT: Compile all the code at the beginning, this allows to makes a lot of improvement to the final code efficiency
+JIT: The code is compiled only when needed, examples are functions that are compiled only when called, this leave space only to partials improvements
+SPC: This is a specific technique of compilation that is made in linear time, the compilation is done only passing once on the code
+Interpretation: The wasm blob is treated as any other interpreted language and executed in a Virtual Machine
+
+---
+
+### Wasmtime
+
+- Stand alone, sandboxed Wasm environment
+- Wasmtime is compiling Wasm code
+- Built on the optimizing Cranelift code generator to (quickly) generate high-quality machine code either at runtime (JIT) or ahead-of-time (AOT)
+
+<!--TODO: graphics-->
+
+Notes:
+
+- wasmtime book: https://docs.wasmtime.dev/
+- Used in substrate as embedder for the blockchain logic
+
+Cranelift is a fast, secure, relatively simple and innovative compiler backend. It takes an intermediate representation of a program generated by some frontend and compiles it to executable machine code
+
+---
+
+#### Wasm lifecycle in Wasmtime
+
+<div class="r-stack">
+<img style="width: 70%" src="./img/pab/wasmtime_exec_1.svg" />
+<img style="width: 70%" src="./img/pab/wasmtime_exec_2.svg"/>
+<!-- .element: class="fragment" data-fragment-index="1" -->
+<img style="width: 70%" src="./img/pab/wasmtime_exec_3.svg"/>
+<!-- .element: class="fragment" data-fragment-index="2" -->
+<img style="width: 70%" src="./img/pab/wasmtime_exec_4.svg"/>
+<!-- .element: class="fragment" data-fragment-index="3" -->
+</div>
+
+---
+
+### Wasmi
+
+- Wasm interpreter
+- Minimal compilation work but the interpreter is still very fast
+  - The wasm code is transpiled to WasmI IR, another stack-based bytecode
+  - The WasmI IR is then interpreted by a Virtual Machine
+- First approach for contracts on Polkadot (pallet-contracts)
+
+<!--TODO: graphics-->
+
+Notes:
+
+proposal to switch from a stack based ir to registry based ir https://github.com/paritytech/wasmi/issues/361
+
+paper explaining the efficiency of translating wasm to registry based code https://www.intel.com/content/www/us/en/developer/articles/technical/webassembly-interpreter-design-wasm-micro-runtime.html <!-- markdown-link-check-disable-line -->
+
+Due to it's characteristics it is mainly used to execute SmartContracts on chain
+
+---
+
+#### Wasm lifecycle in Wasmi
+
+<div class="r-stack">
+<img style="width: 70%" src="./img/pab/wasmi_exec_1.svg" />
+<img style="width: 70%" src="./img/pab/wasmi_exec_2.svg"/>
+<!-- .element: class="fragment" data-fragment-index="1" -->
+<img style="width: 70%" src="./img/pab/wasmi_exec_3.svg"/>
+<!-- .element: class="fragment" data-fragment-index="2" -->
+<img style="width: 70%" src="./img/pab/wasmi_exec_4.svg"/>
+<!-- .element: class="fragment" data-fragment-index="3" -->
+</div>
+
+<!-- Really nice slide but there's not enough knowledge about substrate
+
+There are also light clients, where both Runtime and Client are implemented in wasm, so we have:
+
+- A browser as embedder of the node's client
+  - the node's client as embedder for the node's runtime
+    - the node's runtime as embedder for the SmartContract
+
+<img style="height: 30vh" src="./img/pab/mind-blown-explosion.gif" />
+
+We have a double recursion of a PAB that embed itself
+
+-->
+
+---
+
+### Wasmi
+
+- Why use something different for contracts? Why not use Wasmtime?
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Mainly because compilation is too slow and resulting code isn't deterministic.
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- We'll investigate this in the next lecture.
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+# Alternatives
+
+---
+
+## EVM
+
+- The **Ethereum Virtual Machine** executes a stack machine
+- See previous lecture
+
+---
+
+## Solana
+
+- Berkeley Packet Filter
+- eBPF used in Linux
+  - Allows untrusted code execution in kernel space
+  - Bytecode verifier prevents attacks
+  - For example: No unbounded loops allowed
+- Solana uses a eBPF variant for contracts (rBPF / Solana VM)
+
+Notes:
+
+https://forum.polkadot.network/t/ebpf-contracts-hackathon/1084
+
+## PolkaVM
+
+More to be said about that very soon!
+
+---
+
+## Additional Resources! 😋
+
+> Check speaker notes (click "s" 😉)
+
+Notes:
+
+- More on PAB:
+
+  - https://github.com/gabriele-0201/IPABDN/blob/main/thesis/IPABDN.pdf
+
+- More on Rust target spec:
+
+  - https://rust-lang.github.io/rfcs/0131-target-specification.html
+
+- Lin Clark's awesome talks on WASI (not super relevant to our work though):
+
+  - https://www.youtube.com/watch?v=fh9WXPu0hw8
+  - https://www.youtube.com/watch?v=HktWin_LPf4
+
+- `wasm-unknown` vs `wasm-wasi`:
+
+  - https://users.rust-lang.org/t/wasm32-unknown-unknown-vs-wasm32-wasi/78325/5
+
+- `extern "C"`:
+
+  - https://doc.rust-lang.org/std/keyword.extern.html
+  - https://doc.rust-lang.org/book/ch19-01-unsafe-rust.html#using-extern-functions-to-call-external-code
+
+- Chapter 11 of this book is a great read: https://nostarch.com/rust-rustaceans
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/4-PVM-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/4-PVM-slides.md
new file mode 100644
index 00000000..1a4e2657
--- /dev/null
+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/4-PVM-slides.md
@@ -0,0 +1,965 @@
+---
+title: PolkaVM
+description: PVM architecture
+duration: 45 minutes
+---
+
+# PolkaVM
+
+## From the past (Wasm) to the future (PVM)
+
+> "the next generation virtual machine for Polkadot and PolkaJam"
+
+-- Jan Bujak, author of the first PolkaVM implementation
+
+---
+
+# Wasm
+
+Polkadot is abandoning Wasm: Here's why!
+
+Notes:
+
+Click-baity introduction slide
+
+---
+
+# Wasm: The obvious choice?
+
+- Open standard
+- Mature and widely adopted
+- Many production-grade implementation available
+- Faster than EVM
+
+Notes:
+
+On a first glance Wasm seems like an obvious choice for blockchains.
+For the reasons listened.
+
+---
+
+# Wasm: The obvious choice **for blockchains**?
+
+1. Indeterministic execution
+2. Compiling Wasm to machine code
+
+Notes:
+
+However, the way Wasm is designed, in practice it's actually not the ideal choice.
+As it turns out, deterministic execution of Wasm code is implementation dependent.
+Additionally, compiling Wasm to efficient machine code is a hard problem,
+not ideal for a decentralized network that does a lot of code re-execution across nodes.
+
+---
+
+## Problem #1: Indeterministic execution
+
+Executing Wasm code is not actually deterministic
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Example: Unbounded stack
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+We analyze why Wasm code execution isn't deterministic based how it's stack works.
+
+---
+
+## Indeterministic execution
+
+What is the problem with the below snippet?
+
+Hint: Think about the differences between how function arguments are passed in stack vs. register machines.
+
+```wasm
+(func (param i32) (param i32) (param i32) (param i32) (param i32) (param i32) (param i32) (param i32) (param i32)
+    local.get 0
+    local.get 1
+    ;; ...
+    local.get 8
+
+    call $other
+)
+```
+
+Notes:
+
+https://forum.polkadot.network/t/deterministic-pvf-executor/4204
+https://hackmd.io/@Ww6uNnIISmqGwXufqPYPOw/SklLYwb-T
+
+---
+
+## Indeterministic execution
+
+```wasm
+(func (param i32) (param i32) (param i32) (param i32) (param i32) (param i32) (param i32) (param i32) (param i32)
+    local.get 0
+    local.get 1
+    ;; ...
+    ;;
+    ;; general purpose registers and ABI of the target platform and architecture?
+    ;;
+    ;; x86_64:  6 argument registers (rdi, rsi, rcx, rdx, r8, r9)
+    ;; aarch64: 8 argument registers (r0..r7)
+    ;; x86_64:  may eventually spill to stack
+    ;; x86_64:  will eventually stack overflow
+    ;; aarch64: probably fine?
+    ;;
+    ;; => indeterministic behavior!
+    ;;
+    local.get 8
+
+    call $other
+)
+```
+
+Notes:
+
+The number of arguments is unbounded. The number of registers per platform is limited.
+As a consequence a combination of the Wasm compiler and CPU architecture used
+dictates the overflow behavior.
+
+---
+
+## Problem #2: Compiling Wasm to machine code
+
+Wasm knows many "high level" control flow elements!
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Wasm doesn't know about register allocation or target architecture specific optimizations!
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Not ideal for us because compilation is expensive :(
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+Notes:
+
+Compiling higher level control flow elements to efficient machine code
+involves multiple costly algorithms.
+
+Which is inefficient for short-lived contracts compiled on every node.
+
+---
+
+### High level control flow
+
+Compilers use (expensive) algorithms to:
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- lower "high level" control flow statements
+  - `loop`
+  - `if`
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- Into a bunch of "low level" control flow instructions
+  - (conditional) branch instructions
+  - location labels
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+Notes:
+
+Some examples of code lowering.
+
+---
+
+### High level control flow
+
+Let's use ChatGPT for a little experiment
+
+Notes:
+
+We illustrate the cost of compiling Wasm to machine code.
+
+---
+
+### High level control flow
+
+Prompt: _Write me fibonacci in webassembly text_
+
+```wasm
+  (func $fibonacci (param $n i32) (result i32)
+    (local $a i32)
+    (local $b i32)
+    (local $temp i32)
+    (local.set $a (i32.const 0))
+    (local.set $b (i32.const 1))
+
+    (loop $loop
+      ;; if n <= 1, return n
+      (if (i32.le_s (local.get $n) (i32.const 1))
+        (then
+          (return (local.get $n))
+        )
+      )
+      ..
+```
+
+---
+
+### High level control flow
+
+Prompt: _Write me fibonacci in x86_64 assembly_
+
+```asm
+fibonacci:
+    cmp rdi, 1          ; If n <= 1, return n
+    jle .base_case
+    mov rax, 0          ; a = 0
+    mov rbx, 1          ; b = 1
+    mov rcx, rdi        ; counter = n
+.loop:
+    add rax, rbx        ; temp = a + b
+    xchg rax, rbx       ; a = b, b = temp
+    dec rcx             ; counter--
+    jg .loop            ; If counter > 0, repeat loop
+    mov rax, rbx        ; Result is in b
+    ret
+.base_case:
+    mov rax, rdi        ; Return n if n <= 1
+    ret
+```
+
+---
+
+<section>
+  <h3>High level control flow</h3>
+  <table>
+  <thead>
+    <tr>
+      <th>Wasm</th>
+      <th>x86_64</th>
+    </tr>
+  </thead>
+    <tr>
+      <td>
+        <pre><code data-trim data-noescape>
+        (loop $loop
+          (if (i32.le_s (local.get $n) (i32.const 1))
+            (then
+              (return (local.get $n))
+            )
+          )
+          ..
+        )
+        </code></pre>
+      </td>
+      <td>
+        <pre><code data-trim data-noescape>
+        fibonacci:
+            cmp rdi, 1
+            jle .base_case
+            mov rax, 0
+            mov rbx, 1
+            mov rcx, rdi
+        .loop:
+            add rax, rbx
+            xchg rax, rbx
+            dec rcx
+            jg .loop
+            mov rax, rbx
+            ret
+        </code></pre>
+      </td>
+    </tr>
+  </table>
+</section>
+
+---
+
+<section>
+  <h3>High level control flow</h3>
+  <table>
+  <thead>
+    <tr>
+      <th>Wasm</th>
+      <th>x86_64</th>
+    </tr>
+  </thead>
+    <tr>
+      <td>
+        <pre><code data-trim data-noescape>
+        (loop $loop
+          (if (i32.le_s (local.get $n) (i32.const 1))
+        </code></pre>
+      </td>
+      <td>
+        <pre><code data-trim data-noescape>
+            cmp rdi, 1
+            jle .base_case
+            jg .loop
+        </code></pre>
+      </td>
+    </tr>
+  </table>
+</section>
+
+---
+
+## Register allocation
+
+Executing Wasm requires us to do register allocation
+
+Notes:
+
+A major issue for compiling stack machine code like Wasm code to
+register machine code.
+
+---
+
+### Register allocation
+
+> In compiler optimization, register allocation is the process of assigning local automatic variables and expression results to a limited number of processor registers.
+
+https://en.wikipedia.org/wiki/Register_allocation
+
+```wasm
+(func (param i32) (param i32) (param i32) (param i32) (param i32) (param i32) (param i32) (param i32) (param i32)
+    local.get 0
+    local.get 1
+    ;; ..
+    local.get 8
+    ;; Informally:
+    ;;   Compiler needs to figure out which variable goes to which register
+    ;;
+    ;; For example adding two variables here requires them to be in
+    ;; in registers on a real computer
+)
+```
+
+---
+
+### Register allocation
+
+> **NP-Problem**
+>
+> Chaitin et al. showed that register allocation is an NP-complete problem.
+
+https://en.wikipedia.org/wiki/Register_allocation#Common_problems_raised_in_register_allocation
+
+Notes:
+
+The class of nondeterministic polynomial time (NP) problems are a set of decision problems
+where the answer is yes or no and this can be verified in polynomial time.
+
+Informally, finding a solution to such a problem is hard, requires a lot of computational work.
+Verifying a proof is little work.
+
+Example: Integer factorization (finding factors is hard for large numbers - proofing that two numbers are
+factors however is just a matter of a single multiplication).
+
+NP-Complete problems can simulate every other NP problem.
+They are considered the hardest of the NP problems: It follows that if they can simulate any other NP problem, solving them is at least as difficult as solving the most difficult NP problem.
+
+---
+
+### Register allocation
+
+If you aren't familiar with the theory of computation, just read:
+
+_Register allocation is a difficult problem_
+
+---
+
+## Compiling Wasm to machine code
+
+- Wasm is almost a high level langauge (despite _assembly_ in the name)
+- What compilers do is computationally expensive
+- Can take literal hours on cheaper laptops
+  - `polkadot-sdk`
+  - `LLVM` framework
+- There is a blog post somewhere, telling the story of a web dev rewriting everything to Wasm, only to end up with even greater load times :)
+
+Notes:
+
+As we can see, compiling Wasm code to machine code is annoying.
+
+---
+
+## Compiling Wasm to machine code
+
+Not really a problem for long-living application like web apps
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+<img src="./img/pvm/this-is-fine.jpg">
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+In the context of web2 however this isn't usually a big problem.
+
+---
+
+## Compiling Wasm to machine code
+
+- Every contract needs to be compiled on every node executing it!
+- Transactions often involving multiple contracts amplifies the problem
+- This doesn't look good from a theoretical perspective
+- Caching?
+  - Harder than it seems on first glance
+  - Doesn't entirely solve the problem
+
+Notes:
+
+For us it is a problem! Contracts are short-lived and compiled on every node.
+
+---
+
+## Wasm compilation: Take-aways
+
+**Theory:** Wasm is faster than EVM
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+**Practice:** By the time Wasm has finished compiling, EVM executed a token swap literally dozens to hundreds of times
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+## Some more problems with Wasm
+
+- Complexity of the Wasm spec
+  - Tailored towards web2
+  - Spec is open but our request were turned down in the past
+- Compiler bombs:
+  - Optimizing compilers are not executing in linear time
+  - Which is bad because it opens a DOS attack vector
+  - Metered compilation slows down work that is already expensive
+
+Notes:
+
+A few more complaints about Wasm as contracts or blockchain runtime bytecode format.
+
+---
+
+# PolkaVM (PVM)
+
+# Let's do better!
+
+---
+
+# PolkaVM
+
+PolkaVM is based on RISC-V.
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+<img src="./img/pvm/RISC-V.svg" style="width: 100%">
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+---
+
+# RISC-V
+
+Wait a minute!
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+RISC-V isn't a platform agnostic bytecode.
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+But a real CPU?
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+Notes:
+
+I thought we are using PAB bytecodes? Let's explore why RISC-V can be used for that just fine.
+
+---
+
+## RISC-V
+
+<img src="./img/pvm/risc-v-microcontroller.jpg">
+
+Notes:
+
+This is an early example of a real hardware RISC-V based microcontroller.
+It's CPU is a RISC-V chip.
+
+This looks like fairly simple microcontroller and CPU. Keep this in mind!
+
+---
+
+## RISC-V
+
+<img src="./img/pvm/risc-v-ledcube.png">
+
+Notes:
+
+This LED cube is controlled by that RISC-V microcontroller on the previous slide.
+
+---
+
+## RISC-V as PAB solves many Wasm problems
+
+- Determinism
+  - We are not dictated by web2
+  - Instead we can have our own requirements
+  - => Solved simply because we can define it as requirement
+- Compilation
+  - It follows that RISC-V bytecode is (much!) simpler to compile
+  - => Minimze the work done on-chain!
+
+Notes:
+
+The main take-away is that if we have a PAB in the form of register machine code and
+without high level control flow elements, compilation get's a lot easier.
+
+---
+
+## RISC-V
+
+Realizations:
+
+- RISC-V is simple
+- Practically a common denominator of widely used _real_ CPUs
+  - x86_64
+  - aarch64
+
+Notes:
+
+RISC-V is close to either x86_64 and arm. Much closer than Wasm code anyways.
+
+---
+
+## RISC-V compilation
+
+<img src="./img/pvm/on-off-chain-compilation-1.svg">
+
+Notes:
+
+Let's look at what happens when we execute contract code.
+
+---
+
+## RISC-V compilation
+
+<img src="./img/pvm/on-off-chain-compilation-2.svg">
+
+Notes:
+
+Compilation is a lossy process. It's not ideal to compile into
+Wasm, it is a lossy translation from source code into some also high level IR.
+
+This moves compilation workloads on-chain. We should avoid this at all costs!
+
+---
+
+## RISC-V compilation vs. Wasm
+
+Prompt: _Write me a fibonacci in RISC-V_
+
+```
+fibonacci:
+    li t0, 1          # Load constant 1 into t0
+    ble a0, t0, .base_case # If n <= 1, return n
+    li t1, 0          # a = 0
+    li t2, 1          # b = 1
+.loop:
+    add t3, t1, t2    # temp = a + b
+    mv t1, t2         # a = b
+    mv t2, t3         # b = temp
+    addi a0, a0, -1   # n = n - 1
+    bgt a0, t0, .loop # If n > 1, continue loop
+    mv a0, t2         # Return b (Fibonacci(n))
+    ret
+.base_case:
+    ret
+```
+
+Notes:
+
+Back to our experiment.
+
+---
+
+<section>
+  <h3>Intuitively: What's less work to compile to x86?</h3>
+  <h3>Wasm or RISC-V?</h3>
+  <table width="100%">
+  <thead>
+    <tr>
+      <th>Wasm</th>
+      <th>x86_64</th>
+      <th>RISC-V</th>
+    </tr>
+  </thead>
+    <tr>
+      <td>
+        <pre><code data-trim data-noescape>
+        (loop $loop
+          (if (i32.le_s ..)
+            (then
+              (return (local.get $n))
+            )
+          )
+        ..
+        )
+        </code></pre>
+      </td>
+      <td>
+        <pre><code data-trim data-noescape>
+        fibonacci:
+            cmp rdi, 1
+            jle .base_case
+            mov rax, 0
+            mov rbx, 1
+            mov rcx, rdi
+        .loop:
+            add rax, rbx
+            xchg rax, rbx
+            dec rcx
+            jg .loop
+            mov rax, rbx
+            ret
+        .base_case:
+            mov rax, rdi
+            ret
+        </code></pre>
+      </td>
+      <td>
+        <pre><code data-trim data-noescape>
+        fibonacci:
+            li t0, 1
+            ble a0, t0, .base_case
+            li t1, 0
+            li t2, 1
+        .loop:
+            add t3, t1, t2
+            mv t1, t2
+            mv t2, t3
+            addi a0, a0, -1
+            bgt a0, t0, .loop
+            mv a0, t2
+            ret
+        .base_case:
+            ret
+        </code></pre>
+      </td>
+    </tr>
+  </table>
+</section>
+
+Notes:
+
+It should be obvious just from looking at this from a distance which one
+is easier to compile to a validator hardware CPU.
+
+---
+
+## The last puzzle piece
+
+- PVM is based on the rv64**e**mac (_embedded_) ISA
+  - The _embedded_ ISA is very similar to the standard ISA;
+  - Reduces the general purpose register (GPA) count to 16
+- Any computer will have 16 or more GPR (for the forseeable future)
+  - x86_64 has 16 GPRs
+  - aarch64 has 31 GPRs
+- What this allows:
+  - Instead of doing register allocation;
+  - Compiling PVM bytecode is mostly a linear mapping of registers and instructions!
+
+Notes:
+
+Non-embedded RISC-V would give us 32 GPRs. Which would require a lot of stack spilling
+on x86_64. We avoid that by using the embedded RISC-V ISA.
+
+---
+
+## This slide is important to understand
+
+<pba-cols>
+<pba-col center>
+
+<img src="./img/pvm/pvm-compilation-meme.jpg">
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+</pba-col>
+<pba-col center>
+
+PVM bytecode is
+
+- very close to machine code
+- cheap to compile **on-chain**
+- efficient to execute
+- heavily optimized **off-chain**
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+With our observation made thus fur it get's obvious why RISC-V is a better
+choice for us than Wasm.
+
+---
+
+# PolkaVM `fibonacci` example
+
+```rust
+#![no_std]
+#![no_main]
+
+#[polkavm_derive::polkavm_export]
+extern "C" fn fibonacci(n: u64) -> u64 {
+    if n < 2 {
+        return n;
+    }
+
+    let mut last = 1;
+    let mut current = 1;
+
+    for _ in 2..n {
+        let last_temp = current;
+        current = current + last;
+        last = last_temp;
+    }
+
+    current
+}
+
+#[panic_handler]
+fn panic(_info: &core::panic::PanicInfo) -> ! {
+    unsafe {
+        core::arch::asm!("unimp", options(noreturn));
+    }
+}
+```
+
+Notes:
+
+Simple example of our beloved Fibonacci program.
+We can compile this down to PVM.
+
+---
+
+# PolkaVM `fibonacci` example
+
+<pba-cols>
+<pba-col center>
+
+```
+: @0 [export #0: 'fibonacci']
+ 0: a2 = a0 <u 0x2
+ 3: a2 = 0 if a1 != 0
+ 5: jump @2 if a2 == 0
+  : @1
+ 8: ret
+  : @2
+10: a2 = a0 ^ 0x2
+13: a2 = a2 | a1
+16: jump @4 if a2 != 0
+  : @3
+19: t0 = 0
+21: a4 = 0x1
+24: a0 = 0x1
+27: a1 = 0
+29: ret
+```
+
+</pba-col>
+<pba-col center>
+
+```
+  : @4
+31: sp = sp + 0xfffffff8
+34: u32 [sp + 0x4] = s0
+37: u32 [sp] = s1
+39: t1 = 0
+41: t2 = 0
+43: a5 = 0
+45: a3 = 0x2
+48: s0 = 0x1
+51: a2 = 0x1
+54: fallthrough
+  : @5
+55: a3 = a3 + 0x1
+58: a4 = a3 <u 0x1
+61: a5 = a5 + a4
+64: a4 = a2 + s0
+67: t0 = a4 <u a2
+```
+
+</pba-col>
+<pba-col center>
+
+```
+ 70: t1 = t1 + t2
+ 73: t0 = t0 + t1
+ 76: t1 = a3 <u a0
+ 79: s0 = a5 ^ a1
+ 82: s1 = a5 <u a1
+ 85: s1 = t1 if s0 == 0
+ 88: s0 = a2
+ 90: t1 = t2
+ 92: a2 = a4
+ 94: t2 = t0
+ 96: jump @5 if s1 != 0
+   : @6
+ 99: s0 = i32 [sp + 0x4]
+102: s1 = i32 [sp]
+104: sp = sp + 0x8
+107: a0 = a4
+109: a1 = t0
+111: ret
+```
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+The PVM bytecode looks like this. As said, close to RISC-V.
+But most importantly, it is simple and close to real CPU assembly.
+No high level control flow, variables already allocated to registers.
+
+---
+
+## PolkaVM interpreter vs. JIT compiler
+
+- The PVM JIT compiler is fast!
+- Compiling a PVM blob is faster than hashing it using `blake2b`.
+- But.. for contracts it is still a significant overhead!
+- Idea: Instead of compiling the PVM blob to native code, interpret it!
+  - Pro: Nearly instant code execution
+  - Con: Much slower than compiled code
+
+Notes:
+
+The PVM compiler is very fast. Hashing a code blob using one of the fastest (but still
+cryptographically secure hash algorithms is slower than compiling it!
+
+But even with the fastest possible JIT compiler, compilation overhead is still significant
+and for some workloads still slower than just interpreting it.
+
+The PVM solution: It can do both!
+
+---
+
+## PVM bytecode interpreter vs. JIT compiler
+
+<img src="./img/pvm/interpret-vs-compile-1.svg">
+
+Notes:
+
+Consider some imaginary contract workload. For example calulating Fibonacci numbers.
+
+Horizontal axis is the time it takes to execute the contract.
+
+Vertical axis is the parameter, the amount of iterations, the contract
+will calculate Fibonacci numbers.
+
+---
+
+## PVM bytecode interpreter vs. JIT compiler
+
+<img src="./img/pvm/interpret-vs-compile-2.svg">
+
+Notes:
+
+As we can see, the compiler has a fixed base cost (fixed non-zero y-intercept).
+
+This means we essentially have an optimization problem.
+
+If the user wants to calculate only a few Fibonacci numbers => use interpreter.
+For calculating many numbers => Paying the upfront cost for the compiler is amortized.
+
+Example:
+
+For a simple token swap, prefer the interpreter.
+
+For a cryptographic computation, for example verifying a ZK proof, use the compiler.
+
+---
+
+# PVM Benchmarks
+
+<img src="./img/pvm/benchmarks-1.png" style="width: 100%">
+
+Notes:
+
+Pinky is a NES emulator. The benchmark shows executing the emulator in various VMs.
+
+---
+
+# PVM Benchmarks
+
+<img src="./img/pvm/benchmarks-2.png" style="width: 100%">
+
+Notes:
+
+There's nothing missing for the interpreter. It's just very fast because it has so little
+work to do in order to start executing.
+
+Conclusion is: PVM offers very fast execution (JIT compiler) but also very fast
+compilation (interpreter).
+
+Moreover, interpreter performance is still competitive and JIT compilation
+is still the fastest of all.
+
+In other words, PolkaVM easily crushes other existing solutions.
+
+Also note that we still have optimizations to implement in PVM.
+
+# EVM vs. PVM
+
+- EVM is slower because it has to interpreted
+- EVM isn't a general purpose VM
+  - Pinky benchmarks not possible on EVM
+  - EVM doesn't run contracts written other languages, e.g. Rust
+
+---
+
+# PVM beyond contracts
+
+- Parachain Validation Function (PVF)
+- Join-accumulate-machine (JAM)
+  - https://github.com/gavofyork/graypaper
+  - https://graypaper.fluffylabs.dev/
+
+Notes:
+
+Deterministic compilation also benefits PVF.
+
+PolkaVM will be powering JAM, a major protocol overhaul over Polkadot.
+
+---
+
+# PVM Demo
+
+## Doom
+
+Notes:
+
+If we have enough time for it
+
+---
+
+# Summary
+
+- PoklaVM solves blockchain specific pain points of Wasm
+  - Inderministic execution
+  - Compilation heavy-liftings moved off-chain
+- Fast
+- General purpose
+
+Notes:
+
+We decided to turn away from Wasm and fix the problems we discovered it with a new
+VM and bytecode format. Benchmarks for both execution and compilation perforamnce
+seem confirm our theoretical assumptions.
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/5-History_of_Contracts_on_Polkadot-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/5-History_of_Contracts_on_Polkadot-slides.md
new file mode 100644
index 00000000..b8ca9137
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+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/5-History_of_Contracts_on_Polkadot-slides.md
@@ -0,0 +1,102 @@
+---
+title: The history of contracts on Polkadot
+description: Historical evolution of smart contracts and runtime modules (pallets) on Polkadot, including Frontier, ink!, and pallet-revive.
+duration: 15 minutes
+---
+
+# dAppChains vs. Contracts
+
+Notes:
+
+Intro\
+We'll trace the historical evolution of execution environments on Polkadot, focusing explicitly on smart contract and pallet development. Specifically: Frontier (initial EVM compatibility), ink! (WASM-based contracts), and recent developments like pallet-revive (RISC-V compatible VM with Solidity compilation).
+
+---
+
+# Early Polkadot Execution Models
+
+Initially, Polkadot had two primary approaches to application execution:
+
+- **Runtime modules (pallets)**:
+
+  - Native Substrate-based execution.
+  - Maximum efficiency, full runtime customization.
+  - Integrated directly into parachain runtime.
+  - Rust, steep developer learning curve.
+
+- **Smart contracts (ink!, WASM-based)**:
+  - Flexible, easier developer onboarding compared to pallets.
+  - Permissionless deployments without runtime upgrades.
+  - Limited initial adoption: lacked mature tooling, smaller developer community compared to Solidity.
+
+Notes:
+
+---
+
+# Frontier: Naive Solidity Compatibility
+
+- A Substrate pallet providing EVM compatibility.
+- Enabled direct deployment of Solidity smart contracts on Substrate-based chains (e.g., Moonbeam).
+- Immediately leveraged existing Ethereum developer tooling (MetaMask, Remix, Truffle).
+- Dramatically accelerated adoption by tapping into Solidity's mature ecosystem.
+
+Limitations:
+
+- Frontier initially naïve: straightforward EVM compatibility layer, limited deeper runtime integration.
+- Efficiency less than native pallets or pure WASM execution.
+
+Notes:
+
+---
+
+# ink!: WASM Smart Contracts
+
+ink! aimed to provide native WASM smart contracts on Polkadot/Substrate:
+
+- Technically powerful: WASM flexibility, theoretically superior performance.
+- Designed explicitly for Substrate: deep runtime integration possible.
+
+Adoption limited in practice:
+
+- Ethereum’s Solidity community strongly entrenched.
+- Limited initial tooling, smaller community engagement than Solidity.
+- Despite technical advantages, ink! struggled with widespread real-world adoption.
+
+Notes:
+
+---
+
+# Pallet-Revive: A RISC-V Compatible VM with Solidity Compiler Support
+
+Recent evolution: pallet-revive introduces a new VM approach:
+
+- RISC-V compatible VM integrated as a Substrate pallet.
+- Direct compilation path from Solidity.
+- Combines Solidity ecosystem advantage with native runtime efficiency improvements.
+
+Advantages of pallet-revive:
+
+- Improved efficiency over traditional EVM implementations (Frontier).
+- Leverages existing Solidity ecosystem (tooling, community).
+- Deeper integration into runtime than traditional smart contracts.
+
+Notes:
+
+---
+
+# Pallets vs. Contracts: Historical Context
+
+Throughout Polkadot’s evolution:
+
+- **Pallets** have always represented maximum performance and customization but required steep learning curves, explicit runtime upgrades, and parachain integration.
+- **Smart contracts** prioritized simplicity, ease of onboarding, and permissionless deployment but sacrificed deep customization and efficiency.
+
+Historical lessons learned:
+
+- Developer tooling and community adoption critically important.
+- Technically superior solutions (WASM-based ink!) struggled against entrenched ecosystems (Solidity).
+- Practicality and familiarity often outweighed theoretical technical advantages in developer adoption.
+
+Notes:
+
+---
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-0-smart-contracts-polkadot-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-0-smart-contracts-polkadot-slides.md
new file mode 100644
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+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-0-smart-contracts-polkadot-slides.md
@@ -0,0 +1,13 @@
+---
+title: revive
+description: Solidity compatible contracts on Polkadot
+duration: 5 minutes
+---
+
+# The revive contracts stack
+
+<img src="./img/resolc/stack.png">
+
+Notes:
+
+---
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-1-Revive-compiler-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-1-Revive-compiler-slides.md
new file mode 100644
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--- /dev/null
+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-1-Revive-compiler-slides.md
@@ -0,0 +1,136 @@
+---
+title: Revive compiler
+description: Supporting Solidity contracts on PolkaVM
+duration: 10 minutes
+---
+
+# The revive Solidity compiler
+
+- Compiles Solidity to PVM bytecode
+- Ethereum Solidity solc compiler is the Solidity frontend
+- State-of-the-art LLVM compiler framework is the backend
+- Emits PVM blobs and ETH metadata
+- resolc executable + Wasm version
+
+Notes:
+
+The incumbent smart contract languages is Solidity.
+The Ethereum Solidity compiler can only emit EVM bytecode.
+Instead of interpreting it as EVM bytecode, we can speed Solidity code up by
+compiling Solidity contracts to PVM bytecode.
+
+---
+
+## Compilation process
+
+<img src="img/resolc/compilation.svg">
+
+Notes:
+
+- solc is used to lower the Solidity source code into YUL intermediate representation.
+- revive lowers the YUL IR into LLVM IR.
+- LLVM optimizes the code and emits a RISC-V ELF shared object (through LLD).
+- The PolkaVM linker finally links the ELF shared object into a PolkaVM blob.
+
+---
+
+## YUL frontend
+
+<pba-cols>
+<pba-col center>
+
+- Solidity is a moving target
+- Spec still being worked on
+- Still no stable version 1.0
+- `YUL` IR is a lot simpler and has a formal spec
+- `solc` can parse Solidity and lower it YUL for us
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+</pba-col>
+<pba-col center>
+
+<img src="img/resolc/solidity.png">
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+The revive resolc frontend executable is almost a drop-in replacement for solc.
+
+---
+
+## YUL IR
+
+Solidity example:
+
+```solidity
+contract Flipper {
+    bool coin;
+
+    constructor(bool _coin) {
+        coin = _coin;
+    }
+
+    function flip() public {
+        coin = !coin;
+    }
+}
+```
+
+Notes:
+
+We will show what YUL IR is with a simple Solidity example.
+
+---
+
+## YUL IR
+
+YUL (harder for humans but easier for compilers):
+
+```yul
+object "Flipper_23" {
+    code {
+        {
+            /// @src 0:952:1104  "contract Flipper {..."
+            let _1 := memoryguard(0x80)
+            if callvalue() { revert(0, 0) }
+            let programSize := datasize("Flipper_23")
+            let argSize := sub(codesize(), programSize)
+            let newFreePtr := add(_1, and(add(argSize, 31), not(31)))
+            if or(gt(newFreePtr, sub(shl(64, 1), 1)), lt(newFreePtr, _1))
+            {
+                mstore(/** @src -1:-1:-1 */ 0, /** @src 0:952:1104  "contract Flipper {..." */ shl(224, 0x4e487b71))
+                mstore(4, 0x41)
+                revert(/** @src -1:-1:-1 */ 0, /** @src 0:952:1104  "contract Flipper {..." */ 0x24)
+            }
+    // ..
+    }
+}
+```
+
+Our simple flipper example looks like this in YUL IR (EVM dialiect).
+
+The revive compiler lowers this into LLVM IR.
+
+---
+
+## LLVM backend
+
+<pba-cols>
+<pba-col center>
+
+- Powerful and mature compiler framework
+- Does the heavy lifting in terms of optimizations
+- Supports the RISC-V `rv64e` target
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+</pba-col>
+<pba-col center>
+
+<img src="img/resolc/llvm.png">
+
+</pba-col>
+</pba-cols>
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+---
+title: pallet-revive architecture
+description: Architecture of the pallet-revive smart contract module
+duration: 30min
+url: http://localhost:1948/syllabus/3-PVM-Polkadot-Architecture-and-Smart-Contracts/6-2-pallet-revive-runtime-slides.md
+---
+
+# pallet-revive architecture
+
+Notes:
+
+In this lecture we will cover the architecture of pallet-revive,
+We will look at how the module works inside the substrate chain, as well as the EVM compatibility layer, that we built on top of it.
+
+---
+
+## Architecture overview
+
+<img style="width: 75%" src="img/pallet-revive/node-architecture.png" />
+
+Notes:
+Before we dive int the details of how our pallet works, let's step back and look at the overall architecture of a substrate node
+
+A node is essentially composed of 2 parts. The client and the runtime.
+
+The runtime defines the business logic of our chain, it is compiled to WASM and it's code is stored on chain and can
+get upgraded via runtime upgrade. The runtime is where we find our smart contracts module among other useful pallets.
+
+The client is the Rust program that runs natively on your computer and handle all the general purpose blockchain administration tasks:
+communicating on the p2p network, answering JSON-RPC requests, ordering, prioritizing and validating the transaction pool and managing the database
+
+---
+
+## ETH-RPC compatibility layer
+
+<img style="height: 90%; " src="img/pallet-revive/eth-rpc-architecture.png" />
+
+Notes:
+To enable Ethereum compatibility, we need to speak the language of Ethereum.
+This means implementing the Ethereum JSON-RPC API, which is the standard interface used by all Ethereum clients to interact with the chain.
+
+To achieve this, we built a proxy server that sits between the Ethereum client and the Substrate node.
+The proxy connects to the Substrate node via its JSON-RPC interface, subscribes to new blocks, and relays queries.
+
+Additionally, it:
+
+- Caches recent blocks to improve response time.
+- Maintains a lightweight database with indexes to track mappings between Ethereum transactions and their corresponding Substrate transactions.
+
+There have been multiple efforts to bring EVM compatibility to Substrate.
+
+- Frontier integrates the Ethereum API directly inside the Substrate node.
+- Our approach decouples the Eth API by building it as a separate proxy layer, independent of the node.
+
+This present a few benefits:
+
+- We can use the Omninode or any Substrate node implementation, if a Node operator decide to use a different Node
+  implementation they can do so as this approach require no modification to the Node.
+- We can iterate quickly on the compatibility layer, without having to wait for the Node to be updated.
+
+---
+
+## EVM flow
+
+<img style="height: 90%; " src="img/pallet-revive/eth-rpc-flow.png" />
+
+Notes:
+
+Now, let’s examine the flow of a transaction from an Ethereum client to the Substrate node.
+
+- A user signs and submits a transaction from an Ethereum wallet like MetaMask.
+- The proxy layer intercepts the transaction and wraps it into a pallet-revive runtime call, specifically an eth_transact call.
+  Different types of transactions in Substrate:
+  - Inherents – Unsigned transactions included by the block author.
+  - Signed and unsigned transactions – Regular transactions submitted by users.
+
+In our case, we submit the Ethereum transaction as an unsigned transaction.
+
+- We define a custom implementation of the Checkable trait in Substrate, that recover the signer of the transaction
+  from the payload, and create a regular pallet_revive extrinsic out of it, with a signed origin and either an
+  instantiate_with_code or a call dispatch call
+
+---
+
+# pallet-revive
+
+Notes:
+
+- pallet-revive is the runtime module, that handle smart contracts transactions, and manage the storage used by these contracts.
+
+---
+
+## pallet-revive Config
+
+```rust[0|32-48|69-87|104-122]
+pub trait Config: frame_system::Config {
+  /// The time implementation used to supply timestamps to contracts through `seal_now`.
+  type Time: Time;
+
+  /// The fungible in which fees are paid and contract balances are held.
+  type Currency: Inspect<Self::AccountId>
+    + Mutate<Self::AccountId>
+    + MutateHold<Self::AccountId, Reason = Self::RuntimeHoldReason>;
+
+  /// The overarching event type.
+  type RuntimeEvent: From<Event<Self>> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
+
+  /// The overarching call type.
+  type RuntimeCall: Parameter
+    + Dispatchable<RuntimeOrigin = Self::RuntimeOrigin, PostInfo = PostDispatchInfo>
+    + GetDispatchInfo;
+
+  /// Overarching hold reason.
+  type RuntimeHoldReason: From<HoldReason>;
+
+  /// Used to answer contracts' queries regarding the current weight price. This is **not**
+  /// used to calculate the actual fee and is only for informational purposes.
+  type WeightPrice: Convert<Weight, BalanceOf<Self>>;
+
+  /// Describes the weights of the dispatchables of this module and is also used to
+  /// construct a default cost schedule.
+  type WeightInfo: WeightInfo;
+
+  /// Find the author of the current block.
+  type FindAuthor: FindAuthor<Self::AccountId>;
+
+  /// The amount of balance a caller has to pay for each byte of storage.
+  ///
+  /// # Note
+  ///
+  /// It is safe to change this value on a live chain as all refunds are pro rata.
+  #[pallet::constant]
+  #[pallet::no_default_bounds]
+  type DepositPerByte: Get<BalanceOf<Self>>;
+
+  /// The amount of balance a caller has to pay for each storage item.
+  ///
+  /// # Note
+  ///
+  /// It is safe to change this value on a live chain as all refunds are pro rata.
+  #[pallet::constant]
+  #[pallet::no_default_bounds]
+  type DepositPerItem: Get<BalanceOf<Self>>;
+
+  /// The percentage of the storage deposit that should be held for using a code hash.
+  /// Instantiating a contract, protects the code from being removed. In order to prevent
+  /// abuse these actions are protected with a percentage of the code deposit.
+  #[pallet::constant]
+  type CodeHashLockupDepositPercent: Get<Perbill>;
+
+
+  /// Make contract callable functions marked as `#[unstable]` available.
+  ///
+  /// Contracts that use `#[unstable]` functions won't be able to be uploaded unless
+  /// this is set to `true`. This is only meant for testnets and dev nodes in order to
+  /// experiment with new features.
+  ///
+  /// # Warning
+  ///
+  /// Do **not** set to `true` on productions chains.
+  #[pallet::constant]
+  type UnsafeUnstableInterface: Get<bool>;
+
+  /// Origin allowed to upload code.
+  ///
+  /// By default, it is safe to set this to `EnsureSigned`, allowing anyone to upload contract
+  /// code.
+  #[pallet::no_default_bounds]
+  type UploadOrigin: EnsureOrigin<Self::RuntimeOrigin, Success = Self::AccountId>;
+
+  /// Origin allowed to instantiate code.
+  ///
+  /// # Note
+  ///
+  /// This is not enforced when a contract instantiates another contract. The
+  /// [`Self::UploadOrigin`] should make sure that no code is deployed that does unwanted
+  /// instantiations.
+  ///
+  /// By default, it is safe to set this to `EnsureSigned`, allowing anyone to instantiate
+  /// contract code.
+  #[pallet::no_default_bounds]
+  type InstantiateOrigin: EnsureOrigin<Self::RuntimeOrigin, Success = Self::AccountId>;
+
+  /// The amount of memory in bytes that parachain nodes allocate to the runtime.
+  ///
+  /// This is used in [`Pallet::integrity_test`] to make sure that the runtime has enough
+  /// memory to support this pallet if set to the correct value.
+  type RuntimeMemory: Get<u32>;
+
+  /// The amount of memory in bytes that relay chain validators allocate to the PoV.
+  ///
+  /// This is used in [`Pallet::integrity_test`] to make sure that the runtime has enough
+  /// memory to support this pallet if set to the correct value.
+  ///
+  /// This value is usually higher than [`Self::RuntimeMemory`] to account for the fact
+  /// that validators have to hold all storage items in PvF memory.
+  type PVFMemory: Get<u32>;
+
+  /// The [EIP-155](https://eips.ethereum.org/EIPS/eip-155) chain ID.
+  ///
+  /// This is a unique identifier assigned to each blockchain network,
+  /// preventing replay attacks.
+  #[pallet::constant]
+  type ChainId: Get<u64>;
+
+  /// Use either valid type is [`address::AccountId32Mapper`] or [`address::H160Mapper`].
+  #[pallet::no_default]
+  type AddressMapper: AddressMapper<Self>;
+
+  /// The ratio between the decimal representation of the native token and the ETH token.
+  #[pallet::constant]
+  type NativeToEthRatio: Get<u32>;
+
+  /// Encode and decode Ethereum gas values.
+  /// Only valid value is `()`. See [`GasEncoder`].
+  #[pallet::no_default_bounds]
+  type EthGasEncoder: GasEncoder<BalanceOf<Self>>;
+}
+```
+
+Notes:
+
+Let's take a quick peek at the config of pallet-revive.
+We won't go in depth on all types defined in the config, but let's look at a few interesting ones
+
+- As for any pallet, we depends on types from the runtime, like the `Time` type, the `Currency` type, the `FindAuthor` type, etc.
+- Then we have some specific types for pallet-revive
+- `DepositPerItem` and `DepositPerByte` are the cost of storing data in the contract storage.
+- `CodeHashLockupDepositPercent` is the percentage of the deposit that is deposited when a contract with this hash is
+  instantiated.
+- `WeightInfo` is the trait that define the weights for all the functions of the pallet.
+- `RuntimeMemory` and `PVFMemory` are constants that we use in our integrity tests to make sure that the runtime has enough memory
+- UnsafeUnstableInterface is used in development to enable unstable features
+- UploadOrigin and InstantiateOrigin allow to constrain who can upload and instantiate a contract
+- Finally we have Ethereum specific types, like the `ChainId`, the `AddressMapper`, the `NativeToEthRatio` and the `EthGasEncoder`, to work with Ethereum.
+
+---
+
+## Dispatch functions
+
+```rust[0|3|4-11]
+/// Makes a call to an account, optionally transferring some balance.
+#[pallet::call_index(1)]
+#[pallet::weight(T::WeightInfo::call().saturating_add(*gas_limit))]
+pub fn call(
+    origin: OriginFor<T>,
+    dest: H160,
+    #[pallet::compact] value: BalanceOf<T>,
+    gas_limit: Weight,
+    #[pallet::compact] storage_deposit_limit: BalanceOf<T>,
+    data: Vec<u8>,
+) -> DispatchResultWithPostInfo { /* ... */  }
+```
+
+Notes:
+Like any pallet, pallet-revive define a set of dispatch functions, that can be called by the users to submit transactions to the chain.
+Usually the weight of a dispatchable is fixed, but in pallet-revive, the weight is dynamic, and depend on the gas limit of the transaction.
+Antother interesting fact is that we return `DispatchResultWithPostInfo`, instead of `DispatchResult` to return the excess weight of the transaction.
+
+---v
+
+## Dispatch functions
+
+| pallet call                    | Description                                                                |
+| ------------------------------ | -------------------------------------------------------------------------- |
+| `upload_code`                  | Uploads new code without instantiating a contract from it.                 |
+| `remove_code`                  | Removes the code stored under a hash and refunds the deposit to its owner. |
+| `instantiate`                  | Instantiates a contract from a previously deployed binary.                 |
+| `instantiate_with_code`        | Instantiates a new contract from the supplied code.                        |
+| `call`                         | Makes a call to an account, optionally transferring some balance.          |
+| `map_account`                  | Registers the caller's account ID for use in contract interactions.        |
+| `unmap_account`                | Unregisters the caller's account ID and frees the deposit.                 |
+| `dispatch_as_fallback_account` | Dispatches a call with the origin set to the caller's fallback account.    |
+
+---
+
+## VM API
+
+<img style="height: 90%;" src="img/pallet-revive/vm-architecture.png" />
+
+Notes:
+
+- Discuss how the VM interacts with the runtime
+
+---v
+
+## Host & Guest
+
+<pba-cols>
+<pba-col>
+
+```rust
+// Runtime Host implementation
+
+#[define_env]
+pub mod env {
+ #[stable]
+ #[mutating]
+ fn set_storage(
+  &mut self,
+  memory: &mut M,
+  flags: u32,
+  key_ptr: u32,
+  key_len: u32,
+  value_ptr: u32,
+  value_len: u32,
+ ) -> Result<u32, TrapReason> {
+  // implementation
+ }
+```
+
+</pba-col>
+<pba-col center>
+
+```rust
+// Contract foreign function definition
+
+#[polkavm_import(abi = self::abi)]
+extern "C" {
+  pub fn set_storage(
+    flags: u32,
+    key_ptr: *const u8,
+    key_len: u32,
+    value_ptr: *const u8,
+    value_len: u32,
+  ) -> ReturnCode;
+```
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+`#[define_env]` defines the list of system calls that the VM can make to the runtime.
+
+- It generates the syscall dispatching logic, handling input and output passing through registers.
+- It synchronizes the VM’s gas meter with the runtime’s gas meter, ensuring that execution cost is properly accounted for before and after each system call.
+
+In the same way, to define Rust guest polkavm contracts, we need to define the list of foreign functions that the
+contracts can call. They are defined in a dedicated crate `pallet-revive-uapi`.
+
+- it exposes all the foreign functions that a contract can import.
+- The #[polkavm_import] macro take care of converting the arguments and return values between the VM and the Rust runtime, by setting the registers A0 to A5
+
+---v
+
+## Activity: Build and deploy a Rust contract
+
+> Build the fibonacci contract using Rust and `pallet-revive-uapi`
+
+Notes:
+https://github.com/paritytech/rust-contract-template
+
+---
+
+## Design Differences
+
+### Substrate & pallet-revive vs Ethereum
+
+Notes:
+In this section we will highlight some of the key differences between Substrate and Ethereum, and how we designed pallet-revive to be as compatible as possible with Ethereum.
+
+---v
+
+## 1. Transaction hashes
+
+<img style="width: 60%; padding: 20px 0" src="img/pallet-revive/tx-hash.png" />
+
+> ‼️ The transaction hash is a unique identifier on Ethereum not Substrate
+
+---
+
+## 1. Transaction hashes
+
+| Index | Hash | Origin | Nonce | Call                | Results               |
+| ----- | ---- | ------ | ----- | ------------------- | --------------------- |
+| 0     | 0x01 | A      | 0     | Transfer 5 DOT to B | A reaped              |
+| 1     | 0x02 | B      | 4     | Transfer 7 DOT to A | A created (nonce = 0) |
+| 2     | 0x01 | A      | 0     | Transfer 5 DOT to B |                       |
+
+Notes:
+Imagine this contrived example with a reaped account. The first and last
+transactions are identical, and both valid.
+See <https://wiki.polkadot.network/docs/build-protocol-info#unique-identifiers-for-extrinsics>
+
+---v
+
+## 2. Existential Deposit
+
+- Every Ethereum RPC / EVM opcode that returns a balance will subtract the existential deposit.
+- When sending balance `x` to a **new account**, we actually send `x + ed`.
+
+Notes:
+On Polkadot, an account must hold a minimum balance to exist. When it drops below this minimum amount, the account is deleted.
+We call this minimum amount the "existential deposit" (`ed`). It exists to prevent unused accounts from bloating the state. This is not the case on Ethereum, where
+accounts are never deleted once created, and there is no minimum balance an account must hold to retain its associated data structures (e.g., nonce) in state.
+Since contracts are accounts (more precisely, code that controls an account), they are also affected by this.
+
+This leads to a situation where every account on Polkadot has some portion of its currency that it cannot spend. This may confuse contracts and off-chain
+tools (e.g., wallets) written for Ethereum.
+
+Luckily, we can hide this fact from all participants so everything keeps working as expected. It's just something to be aware of:
+
+- Every Ethereum RPC that returns a balance will subtract the existential deposit. This means that all returned balance is actually spendable, just as on Ethereum.
+- Every EVM opcode that returns the balance of an account will do the same.
+- When sending balance `x` to a new account, we actually send `x + ed`. This ensures that balance transfers of any amount will succeed and the receiver has `x` as available
+  balance. The downside is that it might be unexpected for the sender to send more than `x`. To prevent confusion, we add the `ed` to the transaction fee if it needs to
+  be paid. This way, the user is always aware of the total cost of a transaction. \* This is also true when a contract sends balance to another contract. In this case, we always take the `ed` from the signer of the transaction and not the sending contract.
+  This makes the additional send balance transparent to contracts. This is important since contract code is free to assume that exactly `x` is sent.
+  If a call to a contract funds multiple new accounts, this will be reflected in the transaction fee, just like any other deposit made to cover storage costs
+  (see `storage_deposit_limit` above).
+
+---v
+
+## 3. Code deployment (Ethereum)
+
+<pba-flex>
+
+- The EVM executes the init code, which:
+  - runs the constructor with the passed arguments
+  - returns the runtime code, which gets stored on-chain
+  - The compiler will modify the contract’s runtime code before it is returned by replacing all references to immutables with the values assigned to them
+
+</pba-flex>
+
+<pba-flex>
+
+```sh
+❯ solc Hello.sol --combined-json bin,bin-runtime | jq ".contracts"
+```
+
+```json
+{
+  "Hello.sol:Hello": {
+    "bin": "6080604052348015600e575f5ffd5b50603e80601a5f395ff3fe60806040525f5ffdfea26469706673582212208e040e5268feafa994012e9cb5d525195f19af6c7241997e2ea91601f98f10d064736f6c634300081d0033",
+    "bin-runtime": "60806040525f5ffdfea26469706673582212208e040e5268feafa994012e9cb5d525195f19af6c7241997e2ea91601f98f10d064736f6c634300081d0033"
+  }
+}
+```
+
+</pba-flex>
+<!-- .element: class="fragment" -->
+
+---v
+
+## 3. Code deployment (pallet-revive)
+
+In pallet-revive, the code is uploaded and stored on-chain
+
+- The constructor doesn't return the runtime code.
+- The immutable variables are stored in a pallet storage map and read when the contract is called.
+- Multiple contracts can be instantiated by referencing the same code hash.
+
+---
+
+## 3. Code deployment (pallet-revive)
+
+```rust
+pub trait Config: frame_system::Config {
+  // ...
+
+  /// The percentage of the storage deposit that should be held for using a code hash.
+  /// Instantiating a contract, protects the code from being removed. In order to prevent
+  /// abuse these actions are protected with a percentage of the code deposit.
+  #[pallet::constant]
+  type CodeHashLockupDepositPercent: Get<Perbill>;
+}
+```
+
+</pba-col>
+</pba-cols>
+
+---v
+
+## 4. Balance Decimals
+
+- In EVM, the smallest unit of value is 1 wei, which is $10^{-18}$ETH.
+- In Substrate, the smallest unit of value is 1 Planck, which is $10^{-12}$ KSM or $10^{-10}$ DOT.
+
+```rust
+pub trait Config: frame_system::Config {
+    //...
+    #[pallet::constant]
+    type NativeToEthRatio: Get<u32>;
+}
+```
+
+Notes:
+In theory, EVM wallets are configurable, and should let you define the number of decimals you want to use.
+In practice, most wallets use 18 decimals, and we have to play nicely with them.
+Also everything that is passed by the contract as argument to any opcode is assumed to use 18 decimals.
+A transaction that attempt to use a value that can't be translated to a substrate value without a rounding error, will be rejected.
+
+---v
+
+## 5. Address mapping
+
+- Most Substrate chain, including Asset Hub, use a 32 byte (AccountId32) address usually encoded in SS58 format.
+- EVM uses a 20 byte address (H160), usually encoded in hex format.
+
+```rust
+use sp_core::{crypto::AccountId32, H160};
+
+fn main() {
+    println!("Substrate: {}", AccountId32::new([1u8; 32]));
+    // Substrate: 5C62Ck4UrFPiBtoCmeSrgF7x9yv9mn38446dhCpsi2mLHiFT
+
+    println!("EVM: {:?}", H160([1u8; 20]));
+    // EVM: 0x0101010101010101010101010101010101010101
+}
+```
+
+Note:
+Substrate uses 32 bytes address, while EVM uses 20 bytes address.
+Everything that is executed in the VM expect a 20 bytes address, we need to map the 32 bytes address to a 20 bytes address.
+
+---v
+
+## 5. Address mapping
+
+```rust[0|4-9|16-20|11-12]
+#[frame_support::pallet]
+pub mod pallet {
+  pub trait Config: frame_system::Config {
+    /// Use either valid type is [`address::AccountId32Mapper`] or [`address::H160Mapper`].
+    #[pallet::no_default]
+    type AddressMapper: AddressMapper<Self>;
+    // ...
+  }
+
+  #[pallet::storage]
+  pub(crate) type OriginalAccount<T: Config> = StorageMap<_, Identity, H160, AccountId32>;
+  // ...
+}
+
+pub trait AddressMapper<T: Config> {
+ fn to_address(account_id: &T::AccountId) -> H160;
+ fn to_account_id(address: &H160) -> T::AccountId;
+ fn map(account_id: &T::AccountId) -> DispatchResult;
+  // ...
+}
+```
+
+---v
+
+## 5. Address mapping
+
+```rust[1-10| 12-21 | 14-18,23-27]
+// H160 -> AccountId32 -> H160
+
+//  alice_eth: 0x0101010101010101010101010101010101010101
+let alice_eth = H160([1u8; 20]);
+
+// alice_sub: 0101010101010101010101010101010101010101eeeeeeeeeeeeeeeeeeeeeeee (5C62Ck4U...)
+let alice_sub = <Runtime as Config>::AddressMapper::to_account_id(&alice_eth);
+
+// 👍 Convert back
+assert_eq!(alice_eth, <Runtime as Config>::AddressMapper::to_address(&alice_sub));
+
+// AccountId32 -> H160 -> AccountId32
+
+// bob_sub: 0202020202020202020202020202020202020202020202020202020202020202 (5C7LYpP2 ...)
+let bob_sub = AccountId32::from([2u8; 32]);
+
+//  bob_eth: 0xaf32a8053c2d446446d7019359e210b82e53b8ba
+let bob_eth = <Runtime as Config>::AddressMapper::to_address(&bob_sub);
+
+// ❗ Original substrate accounts need a stateful mapping
+assert_ne!(bob_sub, <Runtime as Config>::AddressMapper::to_account_id(&bob_eth));
+
+// Map the account (this is a stateful operation)
+<Runtime as Config>::AddressMapper::map(&bob_sub).unwrap();
+
+// 👍 Convert back
+assert_eq!(bob_sub, <Runtime as Config>::AddressMapper::to_account_id(&bob_eth));
+```
+
+---v
+
+## 6. Gas Model
+
+**Ethereum**
+
+- ⛽ Single dimensional `gas`
+- 📜 Gas costs are defined in the yellow paper and EIPs
+- 📈 Quadratic memory expansion cost
+
+**Polkadot**
+
+- 🚦 Multi dimensional: `ref_time`, `proof_size`, `storage_deposit`
+- 📏 Gas cost are measured in benchmarks, and updated frequently
+- 📊 Fixed memory expansion cost, with hard limits
+
+Notes:
+In Ethereum, there is one dimensional resource: `gas`. The yellow paper, and the EIPs define the cost of each opcode and
+precompile in gas. The gas cost is a measure of the computational effort required to execute an operation or a contract.
+
+in pallet-revive, we have a multi-dimensional gas model, that includes the `ref_time`, the `proof_size`, and the `storage_deposit`.
+
+- `ref_time` measure the reference time of an operation
+- `proof_size` measure the size of the proof required to execute the operation, every time we load a contract for
+  example, we need to add this contract to the proof, so that validators that are stateless can verify the execution of
+  the block.
+- `storage_deposit`: To address state bloat, we charge a deposit from a transaction signer every time a contract it calls adds data to the blockchain's state. This deposit is transferred to the contract and held there. Otherwise, the contract cannot spend or use it. Whoever signs a transaction that removes storage will receive a refund proportional to the amount of storage removed.
+
+In Ethereum the gas costs are defined in the yellow paper and EIPs, they are not updated frequently, and each change require a hard fork.
+In pallet-revive, the gas costs are measured in benchmarks, they reflect the actual performance of the reference hardware. These benchmark are run and updated every time we make a new runtime.
+
+Finally, to avoid an OOM attack, Ethereum uses a quadratic memory expansion cost. This is calculated so limit the
+maximum amount of memory that can be allocated in a transaction given the block gas limit. This means that they are
+overchariing for memory to make sure the memory consumption is bounded.
+
+In pallet-revive, we have a fixed memory expansion cost, with hard limits. This is a more realistic model. The downside
+is that these limits can be too constraining, but this is something that we will adjust over time.
+
+---v
+
+### Current limits
+
+| Limit                                      | Maximum           |
+| ------------------------------------------ | ----------------- |
+| Call stack depth                           | 5                 |
+| Event topics                               | 4                 |
+| Event data payload size (including topics) | 416 bytes         |
+| Storage value size                         | 416 bytes         |
+| Transient storage variables                | 128 `uint` values |
+| Immutable variables                        | 16 `uint` values  |
+| Contract code blob size                    | ~100 kilobytes    |
+
+Notes:
+
+Limits might be increased in the future. To guarantee existing contracts working as expected we will _never decrease_ the limits.
+
+---
+
+## 7. Gas estimation and encoding in lower digits
+
+- When sending tokens, wallets automatically retrieves the correct gas parameters by calling `eth_estimateGas`
+- The estimate encodes the gas limit, the gas price, and the storage deposit in a single value.
+
+```rust
+pub trait Config: frame_system::Config {
+  /// Encode and decode Ethereum gas values.
+  /// Only valid value is `()`. See [`GasEncoder`].
+  type EthGasEncoder: GasEncoder<BalanceOf<Self>>;
+}
+```
+
+Notes:
+
+On a Substrate chain, the gas estimation is 2 dimensional (ref_time, pov), this is not a single value like in EVM.
+n pallet-revive, we also use a deposit for the storage used, to make sure that the chain isn't bloated with unused storage.
+
+To be compatible with EVM though, we need to fit these 3 numbers in a single value, the `gas_limit` of the transaction.
+To achieve that, we compress the ref_time, pv and storage deposit on the lowest digits of the gas_limit, using the
+binary square root of these values, and storing on the lowest 6 digits.
+
+This what the `EthGasEncoder` trait does, it encode and decode the gas values in a single value.
+The only valid value here is the unit `()` where the trait is implemented. We could very well not add it to the config,
+but adding it here make it easier to use, without clutttering the call site where it is used with extra implementation
+bound
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-3-Blockchain_Asset-Hub-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-3-Blockchain_Asset-Hub-slides.md
new file mode 100644
index 00000000..b68af11d
--- /dev/null
+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-3-Blockchain_Asset-Hub-slides.md
@@ -0,0 +1,5 @@
+---
+title: The AssetHub Blockchain
+description: Central Hub aka Plaza
+duration: 15 minutes
+---
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/8-Hackathon-slides.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/8-Hackathon-slides.md
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--- /dev/null
+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/8-Hackathon-slides.md
@@ -0,0 +1,65 @@
+---
+title: Polkadot contracts Hackathon
+description: The Polkadot contracts Hackathon instructions
+duration: 30 minutes
+---
+
+---
+
+# Contracts Competition
+
+A half-day hackathon where students build hands on experience interacting with smart contracts on Polkadot.
+
+---
+
+## Goal
+
+That was a lot of theory! Too much to take in at once.
+
+- This hackathon will help everyone strengthening their understanding of the Polkadot Hub architecture.
+- Explore possibilities and limitations of Polkadots brand new contracts stack.
+- apply the knowledge from the theoretical part and gain hands-on experience with PVM contracts on Polkadot.
+
+---
+
+## Conditions
+
+Teams of up to 3 people (can also work alone).
+Pick an exciting project idea, start researching on it and even start developeing some PoC code.
+
+- Your project needs to be connected to PVM contracts on Polkadot.
+  This doesn't necessarily mean that you'll have to write and deploy a dApp (see inspiration ideas below).
+- The project needs to have a business case behind (a way to generate revenue off of it).
+- You are working on a new idea; any submitted work must be developed during the hackathon exclusively.
+- You will submit the following:
+  - Short project description
+  - Any research done and conclusions found
+  - Some PoC code (doesn't need to be much more than template code but you should get hands on)
+
+---
+
+## Example Project Ideas
+
+- Anonymous voting for openGov
+- Liquid staking protocols
+- Oracle protocol with economic security mechanisms
+- New Smart contract language targeting PVM
+- Generative art platform with on-chain algorithms fully on-chain.
+- A dex router across parachains
+- DAO with anonymous voting (ZK proofing participation)
+- STARK verifier contract (for example risc0)
+- Smart contract fuzzer
+- Formal verification framework for PVM contracts
+- Flashloans a la https://eips.ethereum.org/EIPS/eip-3156
+- A fun on-chain game to teach contracts (example https://github.com/use-ink/ink-workshop)
+- pump.fun style coin casino with bonding curves (please consider ethical and legal aspects of gambling)
+
+---
+
+## Timeline
+
+TODO: should be more fine grained
+
+- introduction ideally in the morning so over lunch they can already think about ideas and team forming
+- hackathon in the afternoon
+- selection of winners and presentation at the end
diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/README.md b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/README.md
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+# Module 3: Polkadot Architecture, PVM and smart contracts
+
+#### Prerequisites:
+
+Install:
+
+- https://github.com/paritytech/revive/releases
+- https://github.com/ethereum/solidity/
+
+## Learning Outcomes
+
+TODO
+
+## Hands on activities
+
+- Hackathon
+
+## Schedule
+
+### Morning
+
+1. Polkadot Architecture [erin]
+2. Smart Contracts general introduction [pg]
+3. EVM contracts [pg]
+4. Platform agnostic Bytecode [cyrill]
+5. PVM [cyrill]
+6. History of Contracts on Polkadot, Plaza, Hub [erin]
+7. revive stack [pg: pallet] [cyrill: compiler]
+
+### Afternoon
+
+- Hackathon
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diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/img/pvm/interpret-vs-compile-2.svg b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/img/pvm/interpret-vs-compile-2.svg
new file mode 100644
index 00000000..668c7708
--- /dev/null
+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/img/pvm/interpret-vs-compile-2.svg
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diff --git a/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/img/pvm/on-off-chain-compilation-1.svg b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/img/pvm/on-off-chain-compilation-1.svg
new file mode 100644
index 00000000..aa446c59
--- /dev/null
+++ b/content/5-PVM-Polkadot-Architecture-and-Smart-Contracts/img/pvm/on-off-chain-compilation-1.svg
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new file mode 100644
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+<?xml version="1.0" encoding="UTF-8"?>
+<svg width="1180px" height="473px" viewBox="0 0 1180 473" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
+    <title>bytecode-vm</title>
+    <g id="Page-1" stroke="none" stroke-width="1" fill="none" fill-rule="evenodd">
+        <g id="Artboard" transform="translate(-25, -55)">
+            <g id="bytecode-vm" transform="translate(25, 55)">
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+                    <g id="src" transform="translate(0, 75.4069)">
+                        <rect id="bg" fill="#7916F3" x="0" y="0" width="128.289655" height="66.5931034" rx="9"></rect>
+                        <text id="Source-code-(.sol,-." font-family="Helvetica" font-size="16" font-weight="normal" fill="#FFFFFF">
+                            <tspan x="15.1310345" y="31.5931034">Source code</tspan>
+                            <tspan x="15.1310345" y="50.6931034" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.681080638">(.sol, .rs)</tspan>
+                        </text>
+                    </g>
+                    <g id="bytecode-copy" transform="translate(248.131, 0)">
+                        <rect id="Rectangle" fill="#7916F3" x="0" y="0" width="118" height="107" rx="9"></rect>
+                        <text id="[{-name:-“…”,-inputs" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="12" font-weight="normal" fill="#FFFFFF" fill-opacity="0.711456512">
+                            <tspan x="2" y="45">[{ name: “…”,</tspan>
+                            <tspan x="2" y="61">   inputs: […],</tspan>
+                            <tspan x="2" y="77.1">   outputs: […]</tspan>
+                            <tspan x="2" y="93.2">  }, …]</tspan>
+                        </text>
+                        <text id="ABI" font-family="Helvetica" font-size="16" font-weight="normal" fill="#FFFFFF">
+                            <tspan x="48" y="24">ABI</tspan>
+                        </text>
+                    </g>
+                    <g id="bytecode-copy-2" transform="translate(241.131, 121)">
+                        <rect id="Rectangle" fill="#7916F3" x="0" y="0" width="125" height="137" rx="9"></rect>
+                        <text id="001101001010-0011010" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="12" font-weight="normal" fill="#FFFFFF">
+                            <tspan x="19" y="59" fill-opacity="0.702906469">001101001010</tspan>
+                            <tspan x="19" y="75.1" fill-opacity="0.702906469">001101001010</tspan>
+                            <tspan x="19" y="91.2" fill-opacity="0.702906469">010101101010</tspan>
+                            <tspan x="19" y="107.3" fill-opacity="0.702906469">001101001010</tspan>
+                            <tspan x="19" y="123.4" fill-opacity="0.702906469">001101001010</tspan>
+                            <tspan x="105.4" y="123.4">  </tspan>
+                        </text>
+                        <text id="Bye-code" font-family="Helvetica" font-size="16" font-weight="normal" fill="#FFFFFF">
+                            <tspan x="30" y="24">Bye code</tspan>
+                        </text>
+                    </g>
+                    <g id="Group-9" transform="translate(157.131, 90)" fill="#FFFFFF">
+                        <text id="Compile" font-family="Helvetica" font-size="12" font-weight="normal">
+                            <tspan x="0" y="11">Compile</tspan>
+                        </text>
+                        <path id="Line" d="M36.5852161,19.6078473 L45.5708264,24.1365123 L36.5565282,28.6078016 L36.569,24.607 L1.99840623,24.4976252 L1.49840877,24.4960314 L1.50159631,23.4960365 L2.00159377,23.4976303 L36.572,23.607 L36.5852161,19.6078473 Z" fill-rule="nonzero"></path>
+                    </g>
+                </g>
+                <text id="Off-chain" font-family="Helvetica" font-size="18" font-weight="normal" fill="#FFFFFF">
+                    <tspan x="147.140625" y="18">Off chain </tspan>
+                </text>
+                <text id="On-chain" font-family="Helvetica" font-size="18" font-weight="normal" fill="#FFFFFF">
+                    <tspan x="851.978027" y="18">On chain </tspan>
+                </text>
+                <line x1="492.5" y1="25.5" x2="492.5" y2="472.5" id="Line-7" stroke="#979797" stroke-linecap="square" stroke-dasharray="9"></line>
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+                        <rect id="bg" fill="#7916F3" x="0" y="0" width="264" height="167" rx="9"></rect>
+                        <text id="JSON-RPC---eth_call" font-family="Helvetica" font-size="16" font-weight="normal" fill="#FFFFFF">
+                            <tspan x="13.3220842" y="31.8649362">JSON RPC</tspan>
+                            <tspan x="13.3220842" y="50.9649362"></tspan>
+                            <tspan x="13.3220842" y="70.0649362" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.681080638">- eth_call</tspan>
+                            <tspan x="13.3220842" y="88.1649362" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.681080638">- eth_estimateGas</tspan>
+                            <tspan x="13.3220842" y="106.264936" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.681080638">- eth_sendRawTransaction</tspan>
+                            <tspan x="13.3220842" y="124.364936" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.681080638">- eth_getTransactionReceipt</tspan>
+                            <tspan x="13.3220842" y="142.364936" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.681080638">… </tspan>
+                        </text>
+                    </g>
+                    <g id="pallet-revive-copy" transform="translate(12, 254)">
+                        <rect id="bg" fill="#7916F3" x="0" y="0" width="555" height="169" rx="9"></rect>
+                        <text id="KV-Store---...---add" font-family="Helvetica" font-size="16" font-weight="normal" fill="#FFFFFF">
+                            <tspan x="28" y="25">KV Store</tspan>
+                            <tspan x="28" y="44.1"></tspan>
+                            <tspan x="28" y="63.2" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.696596372">- ...	</tspan>
+                            <tspan x="28" y="81.3" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.696596372">- address:   0x12345</tspan>
+                            <tspan x="28" y="99.4" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.696596372">- balance    1ETH </tspan>
+                            <tspan x="28" y="117.5" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.696596372">- bytecode   0x...</tspan>
+                            <tspan x="28" y="135.6" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.696596372">- key1       value1  </tspan>
+                            <tspan x="28" y="153.7" font-family="JetBrainsMono-Regular, JetBrains Mono" font-size="14" fill-opacity="0.696596372">- key2       value2</tspan>
+                            <tspan x="187.6" y="153.7" font-family="JetBrainsMono-Regular, JetBrains Mono" fill-opacity="0.696596372">  </tspan>
+                            <tspan x="206.8" y="153.7" font-family="JetBrainsMono-Regular, JetBrains Mono"></tspan>
+                            <tspan x="28" y="174.8"></tspan>
+                        </text>
+                    </g>
+                </g>
+                <text id="Node" font-family="Helvetica" font-size="18" font-weight="normal" fill="#FFFFFF">
+                    <tspan x="874.079148" y="62.1129808">Node </tspan>
+                </text>
+                <text id="--Instantiate-new-co" font-family="Helvetica" font-size="12" font-weight="normal" fill="#FFFFFF">
+                    <tspan x="878.991335" y="148.956413">- Instantiate new contract</tspan>
+                    <tspan x="878.991335" y="163.056413">- Call existing contract</tspan>
+                </text>
+                <text id="Execute-and-update" font-family="Helvetica" font-size="12" font-weight="normal" fill="#FFFFFF">
+                    <tspan x="970.991335" y="265.956413">Execute and update</tspan>
+                </text>
+                <text id="Submit-tx-/-read-sta" font-family="Helvetica" font-size="12" font-weight="normal" fill="#FFFFFF">
+                    <tspan x="418.991335" y="203.956413">Submit tx / read state</tspan>
+                </text>
+                <path id="Line" d="M983.005572,169.989491 L992,174.500618 L982.994441,178.989484 L982.999,174.989 L880.491905,174.862709 L879.991906,174.86209 L879.993142,173.862091 L880.493142,173.86271 L983,173.989 L983.005572,169.989491 Z" fill="#FFFFFF" fill-rule="nonzero"></path>
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+# PVM, Polkadot Architecture and Smart Contracts
diff --git a/content/6-Protocol_On-Chain/FRAME/1-Intro_to_FRAME/Intro_to_FRAME-slides.md b/content/6-Protocol_On-Chain/FRAME/1-Intro_to_FRAME/Intro_to_FRAME-slides.md
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+---
+title: Introduction to FRAME
+description: An introduction into FRAME, a framework for building Substrate runtimes.
+duration: 1 hour
+---
+
+<!-- ## Lesson Plan
+
+<table class="no-bullet-padding">
+<tr>
+  <td>Monday</td>
+  <td>Tuesday</td>
+  <td>Wednesday</td>
+  <td>Thursday</td>
+  <td>Friday</td>
+  <td>Weekend</td>
+</tr>
+<tr class="text-small">
+<td>
+
+- Introduction to FRAME
+- 👩‍💻 Exercise: Proof of Existence Runtime
+- Assignment 3 Feedback
+- FRAME Tips and Tricks
+- Announce FRAME Assignment
+
+</td>
+<td>
+
+- Pallet Coupling
+- FRAME Common Knowledge (Pallets & Traits)
+- FRAME Storage
+- Live Coding
+
+</td>
+<td>
+
+- Events & Errors
+- Calls
+- Origins
+- Outer Enum
+- Hooks
+- Live Coding
+
+</td>
+<td>
+
+- Construct Runtime + Tests
+- 👨‍💻 Exercise: Tests
+- FRAME Benchmarking
+- 👨🏾‍💻 Exercise: Benchmarking
+- Live Coding
+
+</td>
+<td>
+
+- FRAME Under the Hood
+  - Deep Dive
+  - Executive
+- Signed Extensions
+- Migrations & Try Runtime
+- Frame Updates
+- Live Coding
+
+</td>
+<td>
+
+- Complete FRAME Assignment
+
+</td>
+</tr>
+</table> -->
+
+# Introduction to FRAME
+
+---
+
+## What is FRAME?
+
+FRAME is a Rust framework for more easily building Substrate runtimes.
+
+---
+
+## Explaining FRAME Concisely
+
+<pba-flex center>
+
+- Writing the Sudo Pallet:
+- Without FRAME: up to 3268 lines of code.
+- With FRAME: 318 lines of code.
+- ~10x Smaller.
+
+</pba-flex>
+
+Notes:
+Without FRAME number is based on expanded FRAME-based code.
+A fair comparison would be a frameless sudo pallet that might be shorter (but potentially less featurefull).
+
+---
+
+## Goals of FRAME
+
+- Make it easy and concise for developers to do development.
+- Provide maximum flexibility and compatibility for pallet developers.
+- Provide maximum modularity for runtime developers.
+- Be as similar to vanilla Rust as possible.
+
+---
+
+## Building Blocks of FRAME
+
+- FRAME Development
+  - Pallets
+  - Macros
+- FRAME Coordination
+  - FRAME System
+  - FRAME Executive
+  - Construct Runtime
+
+---
+
+## Pallets
+
+FRAME takes the opinion that the blockchain runtime should be composed of individual modules. We call these Pallets.
+
+<img style="height: 600px" src="../../../../assets/img/6-FRAME/frame1.svg" />
+
+---
+
+## Building Blocks of Pallets
+
+Pallets are composed of multiple parts common for runtime development:
+
+- Dispatchable extrinsics
+- Storage items
+- Hooks for:
+  - Block initialization,
+  - Finalizing block (_!= block finality i.e. GRANDPA_)
+
+---
+
+## More Building Blocks of Pallets
+
+And some less important ones:
+
+- Events
+- Errors
+- Custom validation/communication with tx-pool
+- Offchain workers
+- A lot more! but you will learn about them later.
+
+---
+
+### "Shell" Pallet
+
+```rust
+#[frame_support::pallet]
+pub mod pallet {
+  #[pallet::pallet]
+  pub struct Pallet<T>(_);
+
+  #[pallet::config]
+  pub trait Config: frame_system::Config { ... }
+
+  #[pallet::event]
+  pub enum Event { .. }
+
+  #[pallet::error]
+  pub enum Error { .. }
+
+  #[pallet::storage]
+  // snip
+
+  #[pallet::call]
+  impl Pallet { .. }
+}
+```
+
+---
+
+## FRAME Macros
+
+Rust allows you to write Macros, which is code that generates code.
+
+FRAME uses Macros to simplify the development of Pallets, while keeping all of the benefits of using Rust.
+
+We will look more closely at each attribute throughout this module.
+
+---
+
+## See For Yourself
+
+- `tokei -f` will show the number of lines of a file.
+- `cargo expand` will expand the macros to "pure" Rust.
+
+```sh
+➜  polkadot-sdk git:(master) ✗ tokei -f substrate/frame/sudo/src/{lib.rs,extension.rs,weights.rs}
+    Total 318
+
+➜  polkadot-sdk git:(master) ✗ cargo expand -p pallet-sudo > sudo.rs; tokei -f sudo.rs
+    Total 3268
+```
+
+---
+
+## FRAME System
+
+The FRAME System is a Pallet which is assumed to always exist when using FRAME. You can see that in the `Config` of every Pallet:
+
+```rust
+#[pallet::config]
+pub trait Config: frame_system::Config { ... }
+```
+
+---
+
+## FRAME System
+
+It contains all the most basic functions and types needed for a blockchain system. Also contains many low level extrinsics to manage your chain directly.
+
+<div class="flex-container">
+<div class="left-small">
+
+- Block Number
+- Accounts
+- Hash
+- etc...
+
+</div>
+<div class="right text-small">
+
+- `BlockNumberFor<T>`
+- `frame_system::Pallet::<T>::block_number()`
+- `T::AccountId`
+- `T::Hash`
+- `T::Hashing::hash(&bytes)`
+
+</div>
+</div>
+
+---
+
+## FRAME Executive
+
+The FRAME Executive is a "coordinator", defining the order that your FRAME based runtime executes.
+
+```rust
+/// Actually execute all transitions for `block`.
+pub fn execute_block(block: Block) { ... }
+```
+
+- Initialize Block
+  - `on_runtime_upgrade` and `on_initialize` hooks
+- Initial Checks
+- Signature Verification
+- Execute Extrinsics
+- `on_idle` and `on_finalize` hooks
+- Final Checks
+
+---
+
+## Construct Runtime
+
+Your final runtime is composed of Pallets, which are brought together with the `construct_runtime!` macro.
+
+```rust
+// Create the runtime by composing the FRAME pallets that were previously configured.
+construct_runtime! {
+	pub struct Runtime {
+		System: frame_system,
+
+		Timestamp: pallet_timestamp,
+		Balances: pallet_balances,
+		TransactionPayment: pallet_transaction_payment,
+		Sudo: pallet_sudo,
+	}
+};
+```
+
+---
+
+## Construct Runtime
+
+New syntax
+
+```rust
+// Composes the runtime by adding all the used pallets and deriving necessary types.
+#[runtime]
+mod runtime {
+  /// The main runtime type.
+  #[runtime::runtime]
+  #[runtime::derive(RuntimeCall, RuntimeEvent, RuntimeError, RuntimeOrigin, RuntimeTask)]
+  pub struct Runtime;
+
+  pub type System = frame_system;
+  pub type Timestamp = pallet_timestamp;
+  pub type Balances = pallet_balances;
+  pub type TransactionPayment = pallet_transaction_payment;
+  pub type Sudo = pallet_sudo;
+}
+```
+
+---
+
+## Pallet Configuration
+
+Before you can add a Pallet to the final runtime, it needs to be configured as defined in the `Config`.
+
+<div class="flex-container text-small">
+<div class="left" style="max-width: 50%;">
+
+In the Pallet:
+
+```rust
+/// The timestamp pallet configuration trait.
+#[pallet::config]
+pub trait Config: frame_system::Config {
+  type Moment: Parameter + Default + AtLeast32Bit + Scale<Self::BlockNumber, Output = Self::Moment> + Copy + MaxEncodedLen + scale_info::StaticTypeInfo;
+
+  type OnTimestampSet: OnTimestampSet<Self::Moment>;
+
+  #[pallet::constant]
+  type MinimumPeriod: Get<Self::Moment>;
+
+  type WeightInfo: WeightInfo;
+}
+```
+
+</div>
+
+<div class="right" style="max-width: 50%; padding-left: 10px;">
+
+In the Runtime:
+
+```rust
+/// The timestamp pallet configuration.
+
+impl pallet_timestamp::Config for Runtime {
+  type Moment = u64;
+
+  type OnTimestampSet = Aura;
+
+
+  type MinimumPeriod = ConstU64<{ SLOT_DURATION / 2 }>;
+
+  type WeightInfo = ();
+}
+```
+
+</div>
+</div>
+
+---
+
+## Summary
+
+- **FRAME**: A Rust framework that simplifies Substrate runtime development.
+- **Goals**: Improve modularity, flexibility & developer ergonomics while maintaining safety.
+- Core components:
+  - **Pallets**: Modular runtime components with storage, extrinsics, events, errors, and hooks.
+  - **FRAME System**: Foundational pallet providing basic blockchain types and functions.
+  - **FRAME Executive**: Coordinates runtime execution (initialization, checks, extrinsic processing).
+  - **Construct Runtime**: Combines pallets into a complete runtime
+- **Development approach**: Uses Rust macros to generate boilerplate code while keeping the developer interface clean.
diff --git a/content/6-Protocol_On-Chain/FRAME/1-Intro_to_FRAME/Pallet_Coupling-slides.md b/content/6-Protocol_On-Chain/FRAME/1-Intro_to_FRAME/Pallet_Coupling-slides.md
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+---
+title: FRAME Pallet Coupling
+description: A look into how multiple pallets interact.
+duration: 1 hour
+---
+
+# 🤝 Pallet Coupling 🤝
+
+([Reference in `polkadot-sdk-docs`](https://paritytech.github.io/polkadot-sdk/master/polkadot_sdk_docs/reference_docs/frame_pallet_coupling/index.html))
+
+---
+
+## Overview
+
+Substrate believes in building modular and composable blockchain runtimes.
+
+The building blocks of a FRAME runtime are Pallets.
+
+Pallet coupling will teach you how to configure multiple pallets to interact with each other.
+
+---
+
+## Types of Coupling
+
+- Tightly Coupled Pallets
+
+  - Pallets which are directly connected to one another.
+  - You must construct a runtime using exactly the pallets which are tightly coupled.
+
+- Loosely Coupled Pallets
+
+  - Pallets which are connected "loosely" with a trait / interface.
+  - You can construct a runtime using any pallets which satisfy the required interfaces.
+
+Notes:
+
+- Tightly Coupled Pallets: Somewhat like inheritance
+- Loosely Coupled Pallets: Composition
+
+---
+
+## Tightly Coupled Pallets
+
+Tightly coupling is often an easier, but less flexible way to have two pallets interact with each other.
+
+It looks like this:
+
+```rust [2]
+#[pallet::config]
+pub trait Config: frame_system::Config + pallet_treasury::Config {
+	// -- snip --
+}
+```
+
+Note that everything is tightly coupled to `frame_system`!
+
+---
+
+## What Does It Mean?
+
+If Pallet A is tightly coupled to Pallet B, then it basically means:
+
+> This Pallet A requires a runtime which is also configured with Pallet B.
+
+You do not necessarily need Pallet A to use Pallet B, but you will always need Pallet B if you use Pallet A.
+
+---
+
+## Example: Treasury Pallet
+
+The Treasury Pallet is a standalone pallet which controls a pot of funds that can be distributed by the governance of the chain.
+
+There are two other pallets which are tightly coupled with the Treasury Pallet: Tips and Bounties.
+
+You can think of these like "Pallet Extensions".
+
+---
+
+## Treasury, Tips, Bounties
+
+`pallet_treasury`
+
+```rust
+#[pallet::config]
+pub trait Config<I: 'static = ()>: frame_system::Config { ... }
+```
+
+`pallet_tips` & `pallet_bounties`
+
+```rust
+#[pallet::config]
+pub trait Config<I: 'static = ()>: frame_system::Config + pallet_treasury::Config<I> { ... }
+```
+
+---
+
+## Tight Coupling Error
+
+Here is the kind of error you will see when you try to use a tightly coupled pallet without the appropriate pallet dependencies configured:
+
+```rust
+error[E0277]: the trait bound `Test: pallet_treasury::Config` is not satisfied
+   --> frame/sudo/src/mock.rs:149:17
+    |
+149 | impl Config for Test {
+    |                 ^^^^ the trait `pallet_treasury::Config` is not implemented for `Test`
+    |
+n o t e: required by a bound in `pallet::Config`
+   --> frame/sudo/src/lib.rs:125:43
+    |
+125 |     pub trait Config: frame_system::Config + pallet_treasury::Config{
+    |                                              ^^^^^^^^^^^^^^^^^^^^^^^ required by this bound in `Config`
+
+For more information about this error, try `rustc --explain E0277`.
+error: could not compile `pallet-sudo` due to previous error
+warning: build failed, waiting for other jobs to finish...
+```
+
+---
+
+## Advantage of Tight Coupling
+
+With tight coupling, you have direct access to all public functions and interfaces of another pallet. Just like directly using a crate / module.
+
+Examples:
+
+```rust
+// Get the block number from `frame_system`
+frame_system::Pallet::<T>::block_number()
+```
+
+```rust
+// Use type configurations defined in another pallets.
+let who: T::AccountId = ensure_signed(origin)?;
+```
+
+```rust
+// Dispatch an error defined in another pallet.
+ensure!(
+	bounty.value <= max_amount,
+	pallet_treasury::Error::<T, I>::InsufficientPermission
+);
+```
+
+---
+
+## When To Use Tight Coupling
+
+Tight coupling can make a lot of sense when trying to break apart a single "large" pallet into smaller, yet fully dependant pieces.
+
+As mentioned before, you can think of these as "extensions".
+
+Since there is less flexibility in how you can configure tightly coupled pallets, there is also less chance for error in configuring them.
+
+---
+
+## Loosely Coupled Pallets
+
+Loose coupling is the "preferred" way to build Pallets, as it emphasizes the modular nature of Pallet development.
+
+It looks like this:
+
+```rust [3]
+#[pallet::config]
+pub trait Config<I: 'static = ()>: frame_system::Config {
+	type NativeBalance: fungible::Inspect<Self::AccountId> + fungible::Mutate<Self::AccountId>;
+
+	// -- snip --
+}
+```
+
+Here you can see that this pallet requires some associated type `NativeBalance` to be configured which implements some traits `fungible::Inspect` and `fungible::Mutate`, however there is no requirements on how or where that type is configured.
+
+---
+
+## Trait Definition
+
+To begin loose coupling, you need to define a trait / interface that can be provided and depended on. A very common example is the `fungible::*` traits, which e.g. is implemented by `pallet_balances`.
+
+```rust
+/// Trait for providing balance-inspection access to a fungible asset.
+pub trait Inspect<AccountId>: Sized {
+	/// Scalar type for representing balance of an account.
+	type Balance: Balance;
+
+	/// The total amount of issuance in the system.
+	fn total_issuance() -> Self::Balance;
+
+	/// The total amount of issuance in the system excluding those which are controlled by the
+	/// system.
+	fn active_issuance() -> Self::Balance {
+		Self::total_issuance()
+	}
+
+	// -- snip --
+}
+```
+
+`frame/support/src/traits/tokens/fungible/regular.rs`
+
+---
+
+## Trait Implementation
+
+This trait can then be implemented by a Pallet, for example `pallet_balances`.
+
+```rust
+impl<T: Config<I>, I: 'static> fungible::Inspect<T::AccountId> for Pallet<T, I> {
+	type Balance = T::Balance;
+
+	fn total_issuance() -> Self::Balance {
+		TotalIssuance::<T, I>::get()
+	}
+	fn active_issuance() -> Self::Balance {
+		TotalIssuance::<T, I>::get().saturating_sub(InactiveIssuance::<T, I>::get())
+
+	// -- snip --
+}
+```
+
+`frame/balances/src/impl_fungible.rs`
+
+Any pallet, even one you write, could implement this trait.
+
+---
+
+## Trait Dependency
+
+Another pallet can then, separately, depend on this trait.
+
+```rust [3]
+#[pallet::config]
+pub trait Config: frame_system::Config {
+	type NativeBalance: fungible::Inspect<Self::AccountId> + fungible::Mutate<Self::AccountId>;
+}
+```
+
+And can use this trait throughout their pallet:
+
+```rust [4-5]
+#[pallet::weight(0)]
+pub fn transfer_all(origin: OriginFor<T>, to: T::AccountId) -> DispatchResult {
+	let from = ensure_signed(origin)?;
+	let amount = T::NativeBalance::balance(&from);
+	T::NativeBalance::transfer(&from, &to, amount, Expendable)
+}
+```
+
+---
+
+## Runtime Implementation
+
+Finally, in the runtime configuration, we concretely define which pallet implements the trait.
+
+```rust
+/// Configuration of a pallet using the `fungible::*` traits.
+impl pallet_voting::Config for Runtime {
+	type RuntimeEvent = RuntimeEvent;
+	type NativeBalance = pallet_balances::Pallet<Runtime>;
+}
+```
+
+This is the place where things are no longer "loosely" defined.
+
+Notes:
+
+- What new flexibility do you notice when remembering that we just define a trait implementation here?
+- Note that we're basically following the dependency injection pattern here.
+
+---
+
+## Time of Coupling
+
+Another way to distinguish loose vs tight is via the time of coupling:
+
+- Loose: dependency concretely specified when configuring the runtime
+- Tight: dependency concretely specified when coding the pallet
+
+So one question that will help you decide which to use:
+
+When do you need to drop down to know the exact types etc.?
+
+---
+
+## Challenges of Loose Coupling
+
+Loose coupling is more difficult because you need to think ahead of time about developing a flexible API that makes sense for potentially multiple implementations.
+
+You need to try to not let implementation details affect the API, providing maximum flexibility to users and providers of those traits.
+
+When done right, it can be very powerful; like the ERC20 token format.
+
+---
+
+## Challenges of Generic Types
+
+Many new pallet developers also find loose coupling challenging because associated types are not concretely defined... on purpose.
+
+For example, note that the `fungible::*` trait has a generic `Balance` type.
+
+This allows pallet developers to configure most unsigned integer types (`u32`, `u64`, `u128`) as the `Balance` type for their chain, however, this also means that you need to be more clever when doing math or other operations with those generic types.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
+
+Next we will look over common pallets and traits, and will see many of the pallet coupling patterns first hand.
diff --git a/content/6-Protocol_On-Chain/FRAME/1-Intro_to_FRAME/Pallets_Traits-slides.md b/content/6-Protocol_On-Chain/FRAME/1-Intro_to_FRAME/Pallets_Traits-slides.md
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+---
+title: FRAME Pallets & Traits
+description: A review of common Pallets & Traits.
+duration: 1 hour
+---
+
+# FRAME Pallets & Traits
+
+---
+
+## Overview
+
+We will walk through the codebase and touch on various commonly used pallets and traits.
+
+The goal is to learn by example, and show how you can use the Substrate codebase to self-educate and solve problems.
+
+---
+
+## System Pallet
+
+---
+
+## Utility Pallet
+
+---
+
+## Proxy Pallet
+
+---
+
+## Multisig Pallet
+
+---
+
+## Held vs Frozen Balance
+
+- Reserved -> Held
+- Locked -> Frozen
+- Both states belong to the user... but cannot be spent / transferred.
+- Held balances stack on top of one another.
+  - Useful for user deposits, or other use cases where there is sybil concerns.
+  - Ex: Deposit for storing data on-chain,
+- Frozen balances can overlap each other.
+  - Useful when you want to use the same tokens for multiple use cases.
+  - Ex: Using the same tokens for both staking and voting in governance.
+
+---
+
+## Held Balances
+
+```text
+  Total Balance
+┌─────────────────────────────────────────────────────────┐
+┌────────────────────────────────┼────────────────────────┐
+│┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼                     |ED│
+└────────────────────────────────┼────────────────────────┘
+   Held Balance                      Transferable Balance
+
+┌───────────┐
+│┼┼┼┼┼┼┼┼┼┼┼│  Various Storage Deposits
+└───────────┤
+            ├──────┐
+            │┼┼┼┼┼┼│  Treasury Proposal Deposit
+            └──────┤
+                   ├──────────┐
+                   │┼┼┼┼┼┼┼┼┼┼│  Multisig Deposit
+                   └──────────┤
+                              ├──┐
+                              │┼┼│  Proxy Deposit
+                              └──┘
+```
+
+---
+
+## New Holds Example
+
+```text
+  Total Balance
+┌─────────────────────────────────────────────────────────┐
+┌────────────────────────────────┼────────────────────────┐
+│┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼                     |ED│
+└────────────────────────────────┼────────────────────────┘
+   Held Balance                      Transferable Balance
+
+
+                                     ┌────────────────────┐
+              New Hold Successful!   │┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼│
+                                     └────────────────────┘
+
+                         ┌────────────────────────────────┐
+    New Hold Failed :(   │┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼│
+                         └────────────────────────────────┘
+```
+
+---
+
+## Frozen Balances
+
+```text
+  Total Balance
+┌─────────────────────────────────────────────────────────┐
+┌────────────────────────────────┼────────────────────────┐
+│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX                     |ED│
+└────────────────────────────────┼────────────────────────┘
+   Frozen Balance                    Transferable Balance
+
+┌───────────────────────┐
+│XXXXXXXXXXXXXXXXXXXXXXX│  Vesting Balance
+└───────────────────────┘
+
+┌────────────────────────────────┐
+│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX│  Staking Bond Freeze
+└────────────────────────────────┘
+
+┌─────────────────┐
+│XXXXXXXXXXXXXXXXX│  Governance Vote Freeze
+└─────────────────┘
+```
+
+---
+
+## New Freeze Example
+
+```text
+  Total Balance
+┌─────────────────────────────────────────────────┐
+┌────────────────────────────────┼────────────────┐
+│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX             |ED│
+└────────────────────────────────┼────────────────┘
+   Frozen Balance                    Transferable Balance
+
+┌───────────────────────┐
+│XXXXXXXXXXXXXXXXXXXXXXX│  New Freeze Successful!
+└───────────────────────┘
+
+┌─────────────────────────────────────────────────┐
+│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX│  New Freeze Successful!
+└─────────────────────────────────────────────────┘
+
+┌─────────────────────────────────────────────────────────┐
+│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX│  New Freeze Successful!
+└─────────────────────────────────────────────────────────┘
+```
+
+---
+
+## Freeze and Hold Overlap
+
+```text
+  Total Balance
+┌──────────────────────────────────────────────────────────────┐
+   Held Balance
+┌────────────────────────────────┼─────────────────────────────┐
+│┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼                                | E │
+│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX                         | D │
+└────────────────────────────────┼─────────────────────────────┘
+   Frozen Balance                    Transferable Balance
+```
+
+---
+
+## Balances Pallet & Fungible Traits
+
+---
+
+## Assets Pallet & Fungibles Traits
+
+---
+
+## NFT Pallet & Non-Fungibles Traits
+
+---
+
+## Transaction Payment Pallet
+
+---
+
+## Sudo Pallet
+
+---
+
+## Conviction Voting + Referenda Pallet
+
+(Open Governance)
+
+---
+
+## Ranked Collectives + Whitelist Pallet
+
+(Technical Fellowship)
+
+---
+
+## Scheduler Pallet
+
+---
+
+## Polkadot Deep Dives
+
+<img style="height: 500px" src="../../../../assets/img/6-FRAME/polkadot-deep-dive.png" />
+
+https://www.youtube.com/watch?v=_FwqB4FwWXk&list=PLOyWqupZ-WGsfnlpkk0KWX3uS4yg6ZztG
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Calls-slides.md b/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Calls-slides.md
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+---
+title: FRAME Calls
+description: FRAME Calls for Web3 engineers.
+duration: 1 hour
+---
+
+# FRAME Calls
+
+---
+
+## Overview
+
+Calls allow users to interact with your state transition function.
+
+In this lecture, you will learn how to create calls for your Pallet with FRAME.
+
+---
+
+## Terminology
+
+The term "call", "extrinsic", and "dispatchable" all get mixed together.
+
+Here is a sentence which should help clarify their relationship, and why they are such similar terms:
+
+> Users submit an **extrinsic** to the blockchain, which is **dispatched** to a Pallet **call**.
+
+---
+
+## Call Definition
+
+Here is a simple pallet call. Let's break it down.
+
+```rust
+#[pallet::call(weight(<T as Config>::WeightInfo))]
+impl<T: Config> Pallet<T> {
+	#[pallet::call_index(0)]
+	pub fn transfer(
+		origin: OriginFor<T>,
+		dest: AccountIdLookupOf<T>,
+		#[pallet::compact] value: T::Balance,
+	) -> DispatchResult {
+		let source = ensure_signed(origin)?;
+		let dest = T::Lookup::lookup(dest)?;
+		<Self as fungible::Mutate<_>>::transfer(&source, &dest, value, Expendable)?;
+		Ok(())
+	}
+}
+```
+
+---
+
+## Call Implementation
+
+Calls are just functions which are implemented on top of the `Pallet` struct.
+
+You can do this with any kind of function, however, "FRAME magic" turns these into dispatchable calls through the `#[pallet::call]` macro.
+
+---
+
+## Call Origin
+
+Every pallet call must have an `origin` parameter, which uses the `OriginFor<T>` type, which comes from `frame_system`.
+
+```rust
+/// Type alias for the `Origin` associated type of system config.
+pub type OriginFor<T> = <T as crate::Config>::RuntimeOrigin;
+```
+
+---
+
+## Origin
+
+The basic origins available in frame are:
+
+```rust
+/// Origin for the System pallet.
+#[derive(PartialEq, Eq, Clone, RuntimeDebug, Encode, Decode, TypeInfo, MaxEncodedLen)]
+pub enum RawOrigin<AccountId> {
+	/// The system itself ordained this dispatch to happen: this is the highest privilege level.
+	Root,
+	/// It is signed by some public key and we provide the `AccountId`.
+	Signed(AccountId),
+	/// It is signed by nobody, can be either:
+	/// * included and agreed upon by the validators anyway,
+	/// * or unsigned transaction validated by a pallet.
+	None,
+}
+```
+
+We will have another presentation diving deeper into Origins.
+
+---
+
+## Origin Checking
+
+Normally, the first thing you do in a call is check that the origin of the caller is what you expect.
+
+Most often, this is checking that the extrinsic is `Signed`, which is a transaction from a user account.
+
+```rust
+let caller: T::AccountId = ensure_signed(origin)?;
+```
+
+---
+
+## Call Parameters
+
+Pallet calls can have additional parameters beyond `origin` allowing you to submit relevant data about what the caller would like to do.
+
+All call parameters need to satisfy the `Parameter` trait:
+
+```rust
+/// A type that can be used as a parameter in a dispatchable function.
+pub trait Parameter: Codec + EncodeLike + Clone + Eq + fmt::Debug + scale_info::TypeInfo {}
+impl<T> Parameter for T where T: Codec + EncodeLike + Clone + Eq + fmt::Debug + scale_info::TypeInfo {}
+```
+
+---
+
+## Parameter Limits
+
+Most everything can be used as a call parameter, even a normal `Vec`, however, FRAME ensures that encoded blocks are smaller than a maximum block size, which inherently limits the extrinsic length.
+
+In Polkadot this is currently 5 MB.
+
+---
+
+## Compact Parameters
+
+Parameters that are compact encoded can be used in calls.
+
+```rust
+pub fn transfer(
+	origin: OriginFor<T>,
+	dest: AccountIdLookupOf<T>,
+	#[pallet::compact] value: T::Balance,
+) -> DispatchResult { ... }
+```
+
+This can help save lots of bytes, especially in cases like balances as shown above.
+
+---
+
+## Call Logic
+
+The most relevant part of a call is the "call logic".
+
+There is really nothing magical happening here, just normal Rust.
+
+However, you must follow one important rule...
+
+---
+
+## Calls MUST NOT Panic
+
+Under no circumstances (save when a state is reached that should never lead to a produced block) must this function panic.
+
+Allowing callers to trigger a panic from a call can allow users to attack your chain by bypassing fees or other costs associated with executing logic on the blockchain.
+
+---
+
+## Call Return
+
+Every call returns a `DispatchResult`:
+
+```rust
+pub type DispatchResult = Result<(), sp_runtime::DispatchError>;
+```
+
+This allows you to handle errors in your runtime, and NEVER PANIC!
+
+---
+
+## Returning an Error
+
+At any point in your call logic, you can return a `DispatchError`.
+
+```rust
+ensure!(new_balance >= min_balance, Error::<T, I>::LiquidityRestrictions);
+```
+
+When you do - thanks to transactional storage layers - all modified state will be reverted.
+
+---
+
+## Returning Success
+
+If everything in your call completed successfully, you simply return `Ok(())`, and all your state changes are committed, and the extrinsic is considered to have executed successfully.
+
+---
+
+## Call Index
+
+It is best practice to explicitly label your calls with a `call_index`.
+
+```rust
+#[pallet::call_index(0)]
+```
+
+This can help ensure that changes to your pallet do not lead to breaking changes to the transaction format.
+
+---
+
+## Call Encoding
+
+At a high level, a call is encoded as two bytes (plus any parameters):
+
+1. The Pallet Index
+1. The Call Index
+
+Pallet Index comes from the order / explicit numbering of the `construct_runtime!`. If things change order, without explicit labeling, a transaction generated by a wallet (like a ledger) could be incorrect!
+
+Notes:
+
+Note that this also implies there can only be 256 calls per pallet due to the 1 byte encoding.
+
+---
+
+## Weight
+
+Each call must also specify a call `weight`.
+
+We have another lecture on Weights and Benchmarking, but the high level idea is that this weight function tells us how complex the execution of the call is, and thus the fees that should be charged to the user.
+
+---
+
+## Weight Per Call
+
+This can be done per call:
+
+```rust [3]
+#[pallet::call]
+impl<T: Config> Pallet<T> {
+	#[pallet::weight(T::WeightInfo::transfer())]
+	#[pallet::call_index(0)]
+	pub fn transfer(
+		origin: OriginFor<T>,
+		dest: AccountIdLookupOf<T>,
+		#[pallet::compact] value: T::Balance,
+	) -> DispatchResult {
+		let source = ensure_signed(origin)?;
+		let dest = T::Lookup::lookup(dest)?;
+		<Self as fungible::Mutate<_>>::transfer(&source, &dest, value, Expendable)?;
+		Ok(())
+	}
+}
+```
+
+---
+
+## Weight for the Pallet
+
+Or for all calls in the pallet:
+
+```rust [1]
+#[pallet::call(weight(<T as Config>::WeightInfo))]
+impl<T: Config> Pallet<T> {
+	#[pallet::call_index(0)]
+	pub fn transfer(
+		origin: OriginFor<T>,
+		dest: AccountIdLookupOf<T>,
+		#[pallet::compact] value: T::Balance,
+	) -> DispatchResult {
+		let source = ensure_signed(origin)?;
+		let dest = T::Lookup::lookup(dest)?;
+		<Self as fungible::Mutate<_>>::transfer(&source, &dest, value, Expendable)?;
+		Ok(())
+	}
+}
+```
+
+In this case, the weight function name is assumed to match the call name for all calls.
+
+Notes:
+
+https://github.com/paritytech/substrate/pull/13932
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Events_and_Errors-slides.md b/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Events_and_Errors-slides.md
new file mode 100644
index 00000000..d0bbf791
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Events_and_Errors-slides.md
@@ -0,0 +1,603 @@
+---
+title: Events and Errors
+description: FRAME Events and Errors for Web3 Engineers.
+duration: 1 hour
+---
+
+# Events and Errors
+
+---
+
+## Events and Errors
+
+In this presentation, we will go over two of the tools you have access to when developing FRAME Pallets to express how your runtime calls are executing.
+
+---
+
+# Errors
+
+---
+
+## Intro to Errors
+
+Not all extrinsics are valid. It could be for a number of reasons:
+
+- The extrinsic itself is badly formatted. (wrong parameters, encoding, etc...)
+- The state transition function does not allow it.
+  - Maybe a timing problem.
+  - User might be lacking resources.
+  - State transition might be waiting for other data or processes.
+  - etc...
+
+---
+
+## Dispatch Result
+
+All pallet calls return a `DispatchResult` at the end.
+
+From: `substrate/frame/support/src/dispatch.rs`
+
+```rust
+pub type DispatchResult = Result<(), sp_runtime::DispatchError>;
+```
+
+So a function can either return `Ok(())` or some `DispatchError`.
+
+---
+
+## Dispatch Error
+
+From: `substrate/primitives/runtime/src/lib.rs`
+
+```rust [0|6-10|13-14|15-16]
+/// Reason why a dispatch call failed.
+#[derive(Eq, Clone, Copy, Encode, Decode, Debug, TypeInfo, PartialEq, MaxEncodedLen)]
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+pub enum DispatchError {
+	/// Some error occurred.
+	Other(
+		#[codec(skip)]
+		#[cfg_attr(feature = "serde", serde(skip_deserializing))]
+		&'static str,
+	),
+	/// Failed to lookup some data.
+	CannotLookup,
+	/// A bad origin.
+	BadOrigin,
+	/// A custom error in a module.
+	Module(ModuleError),
+	/// At least one consumer is remaining so the account cannot be destroyed.
+	ConsumerRemaining,
+	/// There are no providers so the account cannot be created.
+	NoProviders,
+	/// There are too many consumers so the account cannot be created.
+	TooManyConsumers,
+	/// An error to do with tokens.
+	Token(TokenError),
+	/// An arithmetic error.
+	Arithmetic(ArithmeticError),
+	/// The number of transactional layers has been reached, or we are not in a transactional
+	/// layer.
+	Transactional(TransactionalError),
+	/// Resources exhausted, e.g. attempt to read/write data which is too large to manipulate.
+	Exhausted,
+	/// The state is corrupt; this is generally not going to fix itself.
+	Corruption,
+	/// Some resource (e.g. a preimage) is unavailable right now. This might fix itself later.
+	Unavailable,
+	/// Root origin is not allowed.
+	RootNotAllowed,
+}
+```
+
+---
+
+## Module Errors
+
+From: `substrate/primitives/runtime/src/lib.rs`
+
+```rust
+/// The number of bytes of the module-specific `error` field defined in [`ModuleError`].
+/// In FRAME, this is the maximum encoded size of a pallet error type.
+pub const MAX_MODULE_ERROR_ENCODED_SIZE: usize = 4;
+
+/// Reason why a pallet call failed.
+#[derive(Eq, Clone, Copy, Encode, Decode, Debug, TypeInfo, MaxEncodedLen)]
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+pub struct ModuleError {
+	/// Module index, matching the metadata module index.
+	pub index: u8,
+	/// Module specific error value.
+	pub error: [u8; MAX_MODULE_ERROR_ENCODED_SIZE],
+	/// Optional error message.
+	#[codec(skip)]
+	#[cfg_attr(feature = "serde", serde(skip_deserializing))]
+	pub message: Option<&'static str>,
+}
+```
+
+So an error is at most just 5 bytes.
+
+---
+
+## Declaring Errors
+
+```rust [0|23-30|47-49]
+#![cfg_attr(not(feature = "std"), no_std)]
+
+pub use pallet::*;
+
+#[frame_support::pallet]
+pub mod pallet {
+	use frame_support::pallet_prelude::*;
+	use frame_system::pallet_prelude::*;
+
+	/// Configure the pallet by specifying the parameters and types on which it depends.
+	#[pallet::config]
+	pub trait Config: frame_system::Config {
+		/// Because this pallet emits events, it depends on the runtime's definition of an event.
+		type RuntimeEvent: From<Event<Self>> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
+	}
+
+	#[pallet::pallet]
+	pub struct Pallet<T>(_);
+
+	#[pallet::storage]
+	pub type CurrentOwner<T: Config> = StorageValue<_, T::AccountId>;
+
+	// Errors inform users that something went wrong.
+	#[pallet::error]
+	pub enum Error<T> {
+		/// There is currently no owner set.
+		NoOwner,
+		/// The calling user is not authorized to make this call.
+		NotAuthorized,
+	}
+
+	#[pallet::event]
+	#[pallet::generate_deposit(pub(super) fn deposit_event)]
+	pub enum Event<T: Config> {
+		/// The owner has been updated.
+		OwnerChanged,
+	}
+
+	#[pallet::call]
+	impl<T: Config> Pallet<T> {
+		/// This function allows the current owner to set a new owner.
+		/// If there is no owner, this function will return an error.
+		#[pallet::weight(u64::default())]
+		#[pallet::call_index(0)]
+		pub fn change_ownership(origin: OriginFor<T>, new: T::AccountId) -> DispatchResult {
+			let who = ensure_signed(origin)?;
+			let current_owner = CurrentOwner::<T>::get()
+				.ok_or(Error::<T>::NoOwner)?;
+			ensure!(current_owner == who, Error::<T>::NotAuthorized);
+			CurrentOwner::<T>::put(new);
+			Self::deposit_event(Event::<T>::OwnerChanged);
+			Ok(())
+		}
+	}
+}
+```
+
+---
+
+## Using Errors
+
+When writing tests, you can use errors to make sure that your functions execute exactly as expected.
+
+```rust
+#[test]
+fn errors_example() {
+	new_test_ext().execute_with(|| {
+		assert_noop!(TemplateModule::change_ownership(
+			Origin::signed(1), 2), Error::<T>::NoOwner);
+		CurrentOwner::<T>::put(1);
+		assert_ok!(TemplateModule::change_ownership(Origin::signed(1), 2));
+		assert_noop!(TemplateModule::change_ownership(
+			Origin::signed(1), 2), Error::<T>::NotAuthorized);
+	});
+}
+```
+
+---
+
+## Encoding Errors
+
+All errors ultimately become a `DispatchError`, which is the final type returned by the runtime.
+
+```rust
+println!("{:?}", Error::<T>::NoOwner.encode());
+println!("{:?}", Error::<T>::NotAuthorized.encode());
+let dispatch_error1: DispatchError = Error::<T>::NoOwner.into();
+let dispatch_error2: DispatchError = Error::<T>::NotAuthorized.into();
+println!("{:?}", dispatch_error1.encode());
+println!("{:?}", dispatch_error2.encode());
+```
+
+```sh
+[0]
+[1]
+[3, 1, 0, 0, 0, 0]
+[3, 1, 1, 0, 0, 0]
+```
+
+---
+
+## Dispatch Error Encoding
+
+<table>
+<tr>
+	<td>3</td>
+	<td>1</td>
+	<td>1</td>
+	<td>0</td>
+	<td>0</td>
+	<td>0</td>
+</tr>
+<tr>
+	<td>DispatchError::Module</td>
+	<td>Pallet #2</td>
+	<td>Error #2</td>
+	<td>(unused)</td>
+	<td>(unused)</td>
+	<td>(unused)</td>
+</tr>
+</table>
+
+Encoding based on configuration:
+
+<div class="flex-container">
+<div class="left" style="max-width: 700px;">
+
+```rust
+// Configure a mock runtime to test the pallet.
+frame_support::construct_runtime!(
+	pub struct Test {
+		System: frame_system::{Pallet, Call, Config, Storage, Event<T>},
+		TemplateModule: pallet_template,
+	}
+);
+```
+
+</div>
+<div class="right" style="margin-left: 10px; max-width: 700px;">
+
+```rust
+// Errors inform users that something went wrong.
+#[pallet::error]
+pub enum Error<T> {
+	/// There is currently no owner set.
+	NoOwner,
+	/// The calling user is not authorized to make this call.
+	NotAuthorized,
+}
+```
+
+</div>
+</div>
+---
+
+## Nested Errors
+
+Errors support up to 4 bytes, which allows you to create nested errors, or insert other minimal data with the `PalletError` derive macro.
+
+```rust
+#[derive(Encode, Decode, PalletError, TypeInfo)]
+pub enum SubError {
+	SubError1,
+	SubError2,
+	SubError3,
+}
+
+use frame_system::pallet::Error as SystemError;
+
+// Errors inform users that something went wrong.
+#[pallet::error]
+pub enum Error<T> {
+	/// There is currently no owner set.
+	NoOwner,
+	/// The calling user is not authorized to make this call.
+	NotAuthorized,
+	/// Errors coming from another place.
+	SubError(SubError),
+	/// Errors coming from another place.
+	SystemError(SystemError<T>),
+	/// Some Error with minimal data
+	DataError(u16),
+}
+```
+
+Notes:
+
+https://github.com/paritytech/substrate/pull/10242
+
+---
+
+# Events
+
+---
+
+## Intro to Events
+
+When an extrinsic completes successfully, there is often some metadata you would like to expose to the outside world about what exactly happened during the execution.
+
+For example, there may be multiple different ways an extrinsic completes successfully, and you want the user to know which exact way completed.
+
+Or maybe there is some significant state transition that you know users will want to be notified about, e.g. the amount of locked balance.
+
+For this you can use events.
+
+---
+
+## Declaring and Emitting Events
+
+```rust [10-17|34-39|53]
+#![cfg_attr(not(feature = "std"), no_std)]
+
+pub use pallet::*;
+
+#[frame_support::pallet]
+pub mod pallet {
+	use frame_support::pallet_prelude::*;
+	use frame_system::pallet_prelude::*;
+
+	/// Configure the pallet by specifying the parameters and types on which it depends.
+	#[pallet::config]
+	pub trait Config: frame_system::Config {
+		/// Because this pallet emits events,
+		/// it depends on the runtime's definition of an event.
+		type RuntimeEvent: From<Event<Self>>
+			+ IsType<<Self as frame_system::Config>::RuntimeEvent>;
+	}
+
+	#[pallet::pallet]
+	pub struct Pallet<T>(_);
+
+	#[pallet::storage]
+	pub type CurrentOwner<T: Config> = StorageValue<_, T::AccountId>;
+
+	// Errors inform users that something went wrong.
+	#[pallet::error]
+	pub enum Error<T> {
+		/// There is currently no owner set.
+		NoOwner,
+		/// The calling user is not authorized to make this call.
+		NotAuthorized,
+	}
+
+	#[pallet::event]
+	#[pallet::generate_deposit(pub(super) fn deposit_event)]
+	pub enum Event<T: Config> {
+		/// The owner has been updated.
+		OwnerChanged,
+	}
+
+	#[pallet::call]
+	impl<T: Config> Pallet<T> {
+		/// This function allows the current owner to set a new owner.
+		/// If there is no owner, this function will return an error.
+		#[pallet::weight(u64::default())]
+		#[pallet::call_index(0)]
+		pub fn change_ownership(origin: OriginFor<T>, new: T::AccountId) -> DispatchResult {
+			let who = ensure_signed(origin)?;
+			let current_owner = CurrentOwner::<T>::get()
+				.ok_or(Error::<T>::NoOwner)?;
+			ensure!(current_owner == who, Error::<T>::NotAuthorized);
+			CurrentOwner::<T>::put(new);
+			Self::deposit_event(Event::<T>::OwnerChanged);
+			Ok(())
+		}
+	}
+}
+```
+
+---
+
+## Deposit Event
+
+```rust
+#[pallet::generate_deposit(pub(super) fn deposit_event)]
+```
+
+Simply generates:
+
+```rust
+impl<T: Config> Pallet<T> {
+	pub(super) fn deposit_event(event: Event<T>) {
+		let event = <<T as Config>::Event as From<Event<T>>>::from(event);
+		let event =
+			<<T as Config>::Event as Into<<T as frame_system::Config>::Event>>::into(event);
+		<frame_system::Pallet<T>>::deposit_event(event)
+	}
+}
+```
+
+<br />
+
+`frame/support/procedural/src/pallet/expand/event.rs`
+
+---
+
+## Deposit Event in System
+
+Events are just a storage item in FRAME System.
+
+`frame/system/src/lib.rs`
+
+```rust
+/// Events deposited for the current block.
+///
+/// N O T E: The item is unbound and should therefore never be read on chain.
+/// It could otherwise inflate the PoV size of a block.
+///
+/// Events have a large in-memory size. Box the events to not go out-of-memory
+/// just in case someone still reads them from within the runtime.
+#[pallet::storage]
+pub(super) type Events<T: Config> =
+	StorageValue<_, Vec<Box<EventRecord<T::RuntimeEvent, T::Hash>>>, ValueQuery>;
+
+/// The number of events in the `Events<T>` list.
+#[pallet::storage]
+#[pallet::getter(fn event_count)]
+pub(super) type EventCount<T: Config> = StorageValue<_, EventIndex, ValueQuery>;
+```
+
+---
+
+## Deposit Events in System
+
+Depositing events ultimately just appends a new event to this storage.
+
+`frame/system/src/lib.rs`
+
+```rust [0|1-4|34|13-16]
+/// Deposits an event into this block's event record.
+pub fn deposit_event(event: impl Into<T::RuntimeEvent>) {
+	Self::deposit_event_indexed(&[], event.into());
+}
+
+/// Deposits an event into this block's event record adding this event
+/// to the corresponding topic indexes.
+///
+/// This will update storage entries that correspond to the specified topics.
+/// It is expected that light-clients could subscribe to this topics.
+pub fn deposit_event_indexed(topics: &[T::Hash], event: T::RuntimeEvent) {
+	let block_number = Self::block_number();
+	// Don't populate events on genesis.
+	if block_number.is_zero() {
+		return
+	}
+
+	let phase = ExecutionPhase::<T>::get().unwrap_or_default();
+	let event = EventRecord { phase, event, topics: topics.to_vec() };
+
+	// Index of the to be added event.
+	let event_idx = {
+		let old_event_count = EventCount::<T>::get();
+		let new_event_count = match old_event_count.checked_add(1) {
+			// We've reached the maximum number of events at this block, just
+			// don't do anything and leave the event_count unaltered.
+			None => return,
+			Some(nc) => nc,
+		};
+		EventCount::<T>::put(new_event_count);
+		old_event_count
+	};
+
+	Events::<T>::append(event);
+
+	for topic in topics {
+		<EventTopics<T>>::append(topic, &(block_number, event_idx));
+	}
+}
+```
+
+---
+
+## You Should Not Read Events
+
+- Events are meant for the outside world.
+- The events storage are an unbounded vector of individual events emitted by your pallets.
+- If you ever read this storage, you will introduce the whole thing into your storage proof!
+- **Never write runtime logic which reads from or depends on events.**
+- Tests are okay.
+
+---
+
+## You Should Not Read Events
+
+`frame/system/src/lib.rs`
+
+```rust
+/// Get the current events deposited by the runtime.
+///
+/// Should only be called if you know what you are doing and outside of the runtime block
+/// execution else it can have a large impact on the PoV size of a block.
+pub fn read_events_no_consensus(
+) -> impl sp_std::iter::Iterator<Item = Box<EventRecord<T::RuntimeEvent, T::Hash>>> {
+	Events::<T>::stream_iter()
+}
+
+/// Get the current events deposited by the runtime.
+///
+/// NOTE: This should only be used in tests. Reading events from the runtime can have a large
+/// impact on the PoV size of a block. Users should use alternative and well bounded storage
+/// items for any behavior like this.
+///
+/// NOTE: Events not registered at the genesis block and quietly omitted.
+#[cfg(any(feature = "std", feature = "runtime-benchmarks", test))]
+pub fn events() -> Vec<EventRecord<T::RuntimeEvent, T::Hash>> {
+	debug_assert!(
+		!Self::block_number().is_zero(),
+		"events not registered at the genesis block"
+	);
+	// Dereferencing the events here is fine since we are not in the
+	// memory-restricted runtime.
+	Self::read_events_no_consensus().map(|e| *e).collect()
+}
+```
+
+---
+
+## Testing Events
+
+Remember to set the block number to greater than zero!
+
+Some tools in FRAME System for you:
+
+`frame/system/src/lib.rs`
+
+```rust
+/// Set the block number to something in particular. Can be used as an alternative to
+/// `initialize` for tests that don't need to bother with the other environment entries.
+#[cfg(any(feature = "std", feature = "runtime-benchmarks", test))]
+pub fn set_block_number(n: BlockNumberFor<T>) {
+	<Number<T>>::put(n);
+}
+
+/// Assert the given `event` exists.
+#[cfg(any(feature = "std", feature = "runtime-benchmarks", test))]
+pub fn assert_has_event(event: T::RuntimeEvent) {
+	assert!(Self::events().iter().any(|record| record.event == event))
+}
+
+/// Assert the last event equal to the given `event`.
+#[cfg(any(feature = "std", feature = "runtime-benchmarks", test))]
+pub fn assert_last_event(event: T::RuntimeEvent) {
+	assert_eq!(Self::events().last().expect("events expected").event, event);
+}
+```
+
+---
+
+## Using Events in Tests
+
+```rust
+#[test]
+fn events_example() {
+	new_test_ext().execute_with(|| {
+		frame_system::Pallet::<T>::set_block_number(1);
+		CurrentOwner::<T>::put(1);
+		assert_ok!(TemplateModule::change_ownership(Origin::signed(1), 2));
+		assert_ok!(TemplateModule::change_ownership(Origin::signed(2), 3));
+		assert_ok!(TemplateModule::change_ownership(Origin::signed(3), 4));
+
+		let events = frame_system::Pallet::<T>::events();
+		assert_eq!(events.len(), 3);
+		frame_system::Pallet::<T>::assert_has_event(crate::Event::<T>::OwnerChanged { old: 1, new: 2}.into());
+		frame_system::Pallet::<T>::assert_last_event(crate::Event::<T>::OwnerChanged { old: 3, new: 4}.into());
+	});
+}
+```
+
+Remember other pallets can deposit events, too!
+
+---
+
+## Summary
+
+- Events and Errors are two ways you can signal to users what is happening when they dispatch an extrinsic.
+- Events usually signify some successful thing happening.
+- Errors signify when something has gone bad (and all changes are reverted).
+- Both are accessible by and intended for the end user when they occur.
diff --git a/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/FRAME_Storage-slides.md b/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/FRAME_Storage-slides.md
new file mode 100644
index 00000000..3608d64c
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/FRAME_Storage-slides.md
@@ -0,0 +1,1529 @@
+---
+title: FRAME Storage
+description: Deep dive into FRAME Storage
+duration: 1 hour
+---
+
+# FRAME Storage
+
+---
+
+## FRAME Storage
+
+In this presentation, we will go even deeper into the concepts of Substrate storage, and see what kind of storage primitives FRAME provides you with to make Pallet development easy.
+
+---
+
+<div class="flex-container">
+
+<div class="left-small">
+	<table class="storage-layer-table">
+	<tr><td class="ends">Developer</td></tr>
+	<tr><td style="background-color: pink;">Runtime Storage API</td></tr>
+	<tr><td style="background-color: pink;">Storage Overlays</td></tr>
+	<tr><td>Patricia-Merkle Trie</td></tr>
+	<tr><td>Key-Value Database</td></tr>
+	<tr><td class="ends">Computer</td></tr>
+	</table>
+</div>
+<div class="right">
+
+### Storage layers
+
+As we have learned, there are four core layers to Substrate's storage system.
+
+Today we will focus on the top two layers: Runtime Storage APIs and Storage Overlays, which FRAME uses to improve developer experience.
+
+</div>
+</div>
+
+---
+
+### Overlay Deep Dive
+
+<br/>
+<div class="flex-container">
+<div class="left-small" style="font-size:0.9em">
+
+The overlay stages changes to the underlying database.
+
+</div>
+
+<div class="right">
+
+<table class="overlay-table">
+<tr><td style="background-color: red;">Runtime Logic</td></tr>
+<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: green;">
+<tr><td>Runtime Storage API</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Overlay Change Set</td></tr>
+<tr>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+</tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: blue;">
+<tr><td>Memory / Database Interface</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Database</td></tr>
+<tr>
+	<td>Alice: 10</td>
+	<td>Bob: 20</td>
+	<td>Cindy: 30</td>
+	<td>Dave: 40</td>
+</tr>
+</table>
+
+</div>
+
+---
+
+### Overlay: Balance Transfer
+
+<div class="flex-container">
+<div class="left-small" style="font-size:0.9em">
+
+1. Runtime Logic Initiates.
+1. Calls the Runtime Storage API.
+1. First we query the Overlay Change Set.
+   - Unfortunately it's not there.
+1. Then we query the underlying Database.
+   - Very slow as you have learned so far.
+
+</div>
+
+<div class="right">
+
+<table class="overlay-table">
+<tr><td style="background-color: red;">Runtime Logic</td></tr>
+<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: green;">
+<tr><td>Runtime Storage API</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Overlay Change Set</td></tr>
+<tr>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+</tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: blue;">
+<tr><td>Memory / Database Interface</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Database</td></tr>
+<tr>
+	<td>Alice: 10</td>
+	<td>Bob: 20</td>
+	<td>Cindy: 30</td>
+	<td>Dave: 40</td>
+</tr>
+</table>
+
+</div>
+
+---
+
+### Overlay: Balance Transfer
+
+<br/>
+<div class="flex-container">
+<div class="left-small">
+
+- As we return the data back to the runtime, we cache the values in the overlay.
+- Subsequent reads and writes happen in the overlay, since the data is there.
+
+</div>
+<div class="right">
+
+<table class="overlay-table">
+<tr><td style="background-color: red;">Runtime Logic</td></tr>
+<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: green;">
+<tr><td>Runtime Storage API</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Overlay Change Set</td></tr>
+<tr>
+	<td>Alice: 10</td>
+	<td>Bob: 20</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+</tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: blue;">
+<tr><td>Memory / Database Interface</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Database</td></tr>
+<tr>
+	<td>Alice: 10</td>
+	<td>Bob: 20</td>
+	<td>Cindy: 30</td>
+	<td>Dave: 40</td>
+</tr>
+</table>
+
+</div>
+
+---
+
+### Overlay: Balance Transfer
+
+<br/>
+<div class="flex-container">
+<div class="left-small">
+
+- The actual transfer logic happens in the runtime memory.
+- At some point, the runtime logic writes the new balances to storage, this updates the overlay cache.
+- The underlying database is not updated yet.
+
+</div>
+<div class="right">
+
+<table class="overlay-table">
+<tr><td style="background-color: red;">Runtime Logic</td></tr>
+<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: green;">
+<tr><td>Runtime Storage API</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Overlay Change Set</td></tr>
+<tr>
+	<td style="color: yellow;">Alice: 15</td>
+	<td style="color: yellow;">Bob: 15</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+</tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: blue;">
+<tr><td>Memory / Database Interface</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Database</td></tr>
+<tr>
+	<td>Alice: 10</td>
+	<td>Bob: 20</td>
+	<td>Cindy: 30</td>
+	<td>Dave: 40</td>
+</tr>
+</table>
+
+</div>
+
+---
+
+### Overlay: Balance Transfer
+
+<br/>
+<div class="flex-container">
+<div class="left-small">
+
+- At the end of the block, staged changes are committed to the database all at once.
+- Then storage root is recomputed a single time for the final block state.
+
+</div>
+<div class="right">
+
+<table class="overlay-table">
+<tr><td style="background-color: red;">Runtime Logic</td></tr>
+<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: green;">
+<tr><td>Runtime Storage API</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Overlay Change Set</td></tr>
+<tr>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+</tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: blue;">
+<tr><td>Memory / Database Interface</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Database</td></tr>
+<tr>
+	<td style="color: lightgreen;">Alice: 15</td>
+	<td style="color: lightgreen;">Bob: 15</td>
+	<td>Cindy: 30</td>
+	<td>Dave: 40</td>
+</tr>
+</table>
+
+</div>
+
+---
+
+### Overlay: Implications
+
+<br/>
+<div class="flex-container">
+<div class="left-small">
+
+- Reading the same storage a second or more time is faster (not free) than the initial read.
+- Writing the same value multiple times is fast (not free), and only results in a single final Database write.
+
+</div>
+<div class="right">
+
+<table class="overlay-table">
+<tr><td style="background-color: red;">Runtime Logic</td></tr>
+<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: green;">
+<tr><td>Runtime Storage API</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Overlay Change Set</td></tr>
+<tr>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+	<td>&nbsp;</td>
+</tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: blue;">
+<tr><td>Memory / Database Interface</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Database</td></tr>
+<tr>
+	<td>Alice: 15</td>
+	<td>Bob: 15</td>
+	<td>Cindy: 30</td>
+	<td>Dave: 40</td>
+</tr>
+</table>
+
+</div>
+
+Notes:
+
+also this means that cross implementation of substrate/polkadot can be tricky to ensure determinism (also true for next slide).
+
+---
+
+### Additional Storage Overlays (Transactional)
+
+<br/>
+<div class="flex-container">
+<div class="left-small text-small">
+
+- The runtime has the ability to spawn additional storage layers, called "transactional layers".
+- This can allow you to commit changes through the Runtime Storage API, but then drop the changes if you want before they get to the overlay change set.
+- The runtime can spawn multiple transactional layers, each at different times, allowing the runtime developer to logically separate when they want to commit or rollback changes.
+
+</div>
+<div class="right text-small">
+
+<table class="overlay-table">
+<tr><td style="background-color: red;">Runtime Logic</td></tr>
+<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: green;">
+<tr><td>Runtime Storage API</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Transactional Layer</td></tr>
+<tr>
+	<td style="color: yellow;">Alice: 25</td>
+	<td>&nbsp;</td>
+	<td style="color: yellow;">Cindy: 20</td>
+	<td>&nbsp;</td>
+</tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Overlay Change Set</td></tr>
+<tr>
+	<td>Alice: 15</td>
+	<td>&nbsp;</td>
+	<td>Cindy: 30</td>
+	<td>&nbsp;</td>
+</tr>
+</table>
+
+<br/>
+<table class="overlay-table" style="background-color: blue;">
+<tr><td>Memory / Database Interface</td></tr>
+</table>
+
+<br/>
+<table class="overlay-table">
+<tr><td colspan=4>Database</td></tr>
+<tr>
+	<td>Alice: 15</td>
+	<td>Bob: 15</td>
+	<td>Cindy: 30</td>
+	<td>Dave: 40</td>
+</tr>
+</table>
+
+</div>
+
+---
+
+### Transactional Implementation Details
+
+- Non-Zero Overhead (but quite small)
+  - 0.15% overhead per key written, per storage layer.
+- Values are not copied between layers.
+  - Values are stored in heap, and we just move pointers around.
+  - So overhead has nothing to do with storage size, just the number of storage items in a layer.
+- Storage layers use client memory, so practically no upper limit.
+
+Notes:
+
+For more details see:
+
+https://github.com/paritytech/substrate/issues/10806
+
+https://github.com/paritytech/substrate/pull/10809
+
+In module 6, we can take a closer look at how this functionality is exposed in FRAME.
+
+See: https://github.com/paritytech/substrate/pull/11431
+
+---
+
+## Storage Layer by Default
+
+All extrinsics execute within a transactional storage layer.
+
+This means that if you return an `Error` from your extrinsic, all changes to storage caused by that extrinsic are reverted.
+
+This is the same behavior as you would expect from smart contract environments like Ethereum.
+
+---
+
+### Transactional Layer Attack
+
+Transactional layers can be used to attack your chain:
+
+<br/>
+
+- Allow a user to spawn a lot of transactional layers.
+- On the top layer, make a bunch of changes.
+- All of those changes will need to propagate down each time.
+
+**Solution:**
+
+- Do not allow the user to create an unbounded number of layers within your runtime logic.
+
+---
+
+# Runtime Storage APIs
+
+---
+
+## Patricia Trie
+
+<img style="height: 500px;" src="../../../../assets/img/6-FRAME/patricia-trie.svg" />
+
+---
+
+## Storage Keys
+
+<img style="height: 500px;" src="../../../../assets/img/6-FRAME/navigate-storage-2.svg" />
+
+---
+
+## FRAME Storage Keys
+
+We follow a simple pattern:
+
+```
+hash(name) ++ hash(name2) ++ hash(name3) ++ hash(name4) ...
+```
+
+For example:
+
+```
+twox128(pallet_name) ++ twox128(storage_name) ++ ...
+```
+
+We will get into more details as we look at the specific storage primitives.
+
+---
+
+## Pallet Name
+
+The pallet name comes from the `construct_runtime!`.
+
+```rust
+// Configure a mock runtime to test the pallet.
+frame_support::construct_runtime!(
+	pub enum Test {
+		System: frame_system::{Pallet, Call, Config, Storage, Event<T>},
+		Example: pallet_template,
+	}
+);
+```
+
+This means that changing the name of your pallet here is a **BREAKING** change, since it will change your storage keys.
+
+---
+
+## FRAME Storage Primitives
+
+- `StorageValue`
+- `StorageMap`
+- `CountedStorageMap`
+- `StorageDoubleMap`
+- `StorageNMap`
+
+We will go over all of them, and many important and subtle details along the way.
+
+---
+
+## Storage Value
+
+Place a single item into the runtime storage.
+
+```rust
+pub struct StorageValue<Prefix, Value, QueryKind = OptionQuery, OnEmpty = GetDefault>(_);
+```
+
+Storage Key:
+
+```rust
+Twox128(Prefix::pallet_prefix()) ++ Twox128(Prefix::STORAGE_PREFIX)
+```
+
+---
+
+## Storage Value: Example
+
+```rust
+#[pallet::storage]
+pub type Item1<T> = StorageValue<_, u32>;
+```
+
+```rust
+#[test]
+fn storage_value() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		assert_eq!(Item1::<T>::get(), None);
+		Item1::<T>::put(10u32);
+		assert_eq!(Item1::<T>::get(), Some(10u32));
+	});
+}
+```
+
+---
+
+## Storage "Prefix"
+
+The first generic parameter in any FRAME storage is the `Prefix`, which is used to generate the storage key.
+
+`Prefix` implements `StorageInstance` which has:
+
+```rust
+pub trait StorageInstance {
+	const STORAGE_PREFIX: &'static str;
+
+	fn pallet_prefix() -> &'static str;
+}
+```
+
+`STORAGE_PREFIX` is the name of the storage, and `pallet_prefix()` is the name of the pallet that this storage is in.
+
+This is populated thanks to FRAME's macro magic.
+
+Notes:
+
+https://substrate.stackexchange.com/questions/476/storage-definition-syntax/478#478
+
+---
+
+## Storage Value Key
+
+```rust
+use sp_core::hexdisplay::HexDisplay;
+println!("{}", HexDisplay::from(&Item1::<T>::hashed_key()));
+```
+
+This will depend on your pallet's name of course...
+
+```sh
+e375d60f814d02157aaaa18f3639a254c64445c290236a18189385ed9853fb1e
+```
+
+```sh
+e375d60f814d02157aaaa18f3639a254 ++ c64445c290236a18189385ed9853fb1e
+```
+
+```sh
+twox128("Example") = e375d60f814d02157aaaa18f3639a254
+twox128("Item1") = c64445c290236a18189385ed9853fb1e
+```
+
+---
+
+## Demystifying FRAME Storage
+
+This shows _basically_ what is going on when you use pallet storage. NOT accurate, but should be informative. As you can see, it is really not that complex.
+
+```rust
+struct Prefix;
+impl StorageInstance for Prefix {
+	const STORAGE_PREFIX: &'static str = "MyStorage";
+
+	fn pallet_prefix() -> &'static str {
+		"MyPallet"
+	};
+
+	fn prefix() -> Vec<u8> {
+		twox_128(Self::pallet_prefix()) ++ twox_128(STORAGE_PREFIX)
+	}
+}
+
+type MyStorage = StorageValue<Prefix, Type>;
+trait StorageValue<Prefix, Type> {
+    fn get() -> Option<Type> {
+        sp_io::storage::get(Prefix::prefix())
+    }
+
+    fn set(value: Type) {
+        sp_io::storage::set(Prefix::prefix(), value)
+    }
+
+    fn kill() {
+        sp_io::storage::clear(Prefix::prefix())
+    }
+
+    // etc...
+}
+```
+
+---
+
+## All Storage is an Option
+
+- At the Runtime Storage API level, a storage key will either have a value or not have a value.
+- If there is no value, any query from the backend will be `None`.
+- If there is a value, the query will be `Some(value)`.
+- However, we can also hide this with a `Default` value.
+
+---
+
+## Query If Storage Actually Exists
+
+There are APIs which expose to you whether the value actually exists in the database.
+
+```rust
+#[pallet::storage]
+pub type Item1<T> = StorageValue<_, u32>;
+```
+
+```rust
+#[test]
+fn storage_value() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// Nothing is actually there yet.
+		assert_eq!(Item1::<T>::exists(), false);
+		assert_eq!(Item1::<T>::try_get().ok(), None);
+	});
+}
+```
+
+---
+
+## Query Kind
+
+- `OptionQuery`: Default choice, represents the actual DB state.
+- `ValueQuery`: Return a value when `None`. (`Default` or configurable)
+
+```rust
+#[pallet::storage]
+pub type Item2<T> = StorageValue<_, u32, ValueQuery>;
+```
+
+```rust
+#[test]
+fn value_query() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// `0u32` is the default value of `u32`
+		assert_eq!(Item2::<T>::get(), 0u32);
+		Item2::<T>::put(10u32);
+		assert_eq!(Item2::<T>::get(), 10u32);
+	});
+}
+```
+
+Remember that 0 is not actually in storage when doing the first query.
+
+---
+
+## On Empty
+
+You can control the `OnEmpty` value with:
+
+```rust
+#[pallet::type_value]
+pub fn MyDefault<T: Config>() -> u32 { 42u32 }
+
+#[pallet::storage]
+pub type Item3<T> = StorageValue<_, u32, ValueQuery, MyDefault<T>>;
+```
+
+```rust
+#[test]
+fn my_default() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// `42u32` is the configured `OnEmpty` value.
+		assert_eq!(Item3::<T>::get(), 42u32);
+		Item3::<T>::put(10u32);
+		assert_eq!(Item3::<T>::get(), 10u32);
+	});
+}
+```
+
+Remember that 42 is not actually in storage when doing the first query.
+
+---
+
+## Not Magic
+
+These "extra features" are just ways to simplify your code.
+
+You can get the same effect without any magic:
+
+```rust
+let value = Item1::<T>::try_get().unwrap_or(42u32);
+```
+
+But you wouldn't want to do this every time.
+
+---
+
+## Set vs Put
+
+- `pub fn set(val: QueryKind::Query)`
+- `pub fn put<Arg: EncodeLike<Value>>(val: Arg)`
+
+For Example:
+
+```rust
+#[pallet::storage]
+pub type Item1<T> = StorageValue<_, u32>;
+```
+
+```rust
+Item1::<T>::set(Some(42u32));
+Item1::<T>::put(42u32);
+```
+
+---
+
+## Don't Put The Option AS the Storage Value
+
+This is basically an anti-pattern, and it doesn't really make sense to do.
+
+```rust
+#[pallet::storage]
+pub type Item4<T> = StorageValue<_, Option<u32>>;
+
+#[pallet::storage]
+pub type Item5<T> = StorageValue<_, Option<u32>, ValueQuery>;
+```
+
+```rust
+#[test]
+fn nonsense() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		assert_eq!(Item4::<T>::exists(), false);
+		assert_eq!(Item5::<T>::exists(), false);
+		Item4::<T>::put(None::<u32>);
+		Item5::<T>::put(None::<u32>);
+		assert_eq!(Item4::<T>::exists(), true);
+		assert_eq!(Item5::<T>::exists(), true);
+	});
+}
+```
+
+---
+
+## Unit Type Instead of Bool
+
+You might want to simply signify some true or false value in storage...
+
+Save some bytes! Use the unit type.
+
+```rust
+#[pallet::storage]
+pub type Item6<T> = StorageValue<_, ()>;
+```
+
+```rust
+#[test]
+fn better_bool() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// false case
+		assert_eq!(Item6::<T>::exists(), false);
+		Item6::<T>::put(());
+		// true case
+		assert_eq!(Item6::<T>::exists(), true);
+	});
+}
+```
+
+---
+
+## Kill Storage
+
+Remove the item from the database using `kill()` or `take()`.
+
+```rust
+#[pallet::type_value]
+pub fn MyDefault<T: Config>() -> u32 { 42u32 }
+
+#[pallet::storage]
+pub type Item3<T> = StorageValue<_, u32, ValueQuery, MyDefault<T>>;
+```
+
+```rust
+#[test]
+fn kill() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		assert_eq!(Item3::<T>::get(), 42u32);
+		Item3::<T>::put(10u32);
+		assert_eq!(Item3::<T>::get(), 10u32);
+		//Item3::<T>::kill();
+		let old_value = Item3::<T>::take();
+		assert_eq!(Item3::<T>::get(), 42u32);
+		assert_eq!(old_value, 10u32);
+	});
+}
+```
+
+---
+
+## Mutate
+
+Execute a closure on a storage item.
+
+```rust
+#[test]
+fn mutate() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		Item2::<T>::put(42u32);
+		Item2::<T>::mutate(|x| {
+			if *x % 2 == 0 {
+				*x = *x / 2;
+			}
+		});
+		assert_eq!(Item2::<T>::get(), 21);
+	});
+}
+```
+
+---
+
+## Try Mutate
+
+Execute a closure on a storage item, but only write if the closure returns `Ok`.
+
+```rust
+#[test]
+fn try_mutate() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		Item2::<T>::put(42u32);
+		assert_noop!(Item2::<T>::try_mutate(|x| -> Result<(), ()> {
+			*x = *x / 2;
+			if *x % 2 == 0 {
+				Ok(())
+			} else {
+				Err(())
+			}
+		}), ());
+		// Nothing written
+		assert_eq!(Item2::<T>::get(), 42);
+	});
+}
+```
+
+---
+
+## Assert Noop
+
+You may have noticed we just used `assert_noop!` instead of `assert_err!`.
+
+```rust
+/// Evaluate an expression, assert it returns an expected `Err` value and that
+/// runtime storage has not been mutated (i.e. expression is a no-operation).
+#[macro_export]
+macro_rules! assert_noop {
+	(
+		$x:expr,
+		$y:expr $(,)?
+	) => {
+		let h = $crate::storage_root($crate::StateVersion::V1);
+		$crate::assert_err!($x, $y);
+		assert_eq!(h, $crate::storage_root($crate::StateVersion::V1),
+			"storage has been mutated");
+	};
+}
+```
+
+There is also `assert_storage_noop!` which does not care what is returned, just that storage is not changed.
+
+---
+
+## Vec Tricks
+
+You can use `decode_len()` and `append()` to work with a `Vec` without decoding all the items.
+
+```rust
+#[pallet::storage]
+#[pallet::unbounded]
+pub type Item7<T> = StorageValue<_, Vec<u8>, ValueQuery>;
+```
+
+```rust
+#[test]
+fn vec_tricks() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		assert_eq!(Item7::<T>::decode_len(), None);
+		Item7::<T>::put(vec![0u8]);
+		assert_eq!(Item7::<T>::decode_len(), Some(1));
+		Item7::<T>::append(1u8);
+		Item7::<T>::append(2u8);
+		assert_eq!(Item7::<T>::get(), vec![0u8, 1u8, 2u8]);
+		assert_eq!(Item7::<T>::decode_len(), Some(3));
+	});
+}
+```
+
+---
+
+## Bounded Storage
+
+You may have noticed `#[pallet::unbounded]` on the storage item in the previous slide.
+
+Remember that blockchains are limited by:
+
+- Computation Time
+- Memory Limits
+- Storage Size / Proof Size
+
+In general, every storage item in FRAME should be **bounded** in size.
+
+We will talk about this more when we discuss benchmarking.
+
+---
+
+## Bounded Vector
+
+We have bounded versions of unbounded items like `Vec`, `BTreeSet`, etc...
+
+```rust
+#[pallet::storage]
+pub type Item8<T> = StorageValue<_, BoundedVec<u8, ConstU32<100>>, ValueQuery>;
+```
+
+A second `Get<u32>` type is used to give a maximum number of values.
+
+```rust
+#[test]
+fn bounded_vec() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		for i in 0u8..100u8 {
+			assert_ok!(Item8::<T>::try_append(i));
+		}
+		// Only supports at most 100 items.
+		assert_noop!(Item8::<T>::try_append(100), ());
+	});
+}
+```
+
+---
+
+## Storage Map
+
+Store items in storage as a key and value map.
+
+```rust
+pub struct StorageMap<Prefix, Hasher, Key, Value,
+	QueryKind = OptionQuery,
+	OnEmpty = GetDefault,
+	MaxValues = GetDefault>(_);
+```
+
+Storage Key:
+
+```rust
+Twox128(Prefix::pallet_prefix())
+	++ Twox128(Prefix::STORAGE_PREFIX)
+	++ Hasher1(encode(key))
+```
+
+---
+
+## Storage Map: Example
+
+```rust
+#[pallet::storage]
+pub type Item9<T: Config> = StorageMap<
+	_,          // Infer prefix from name
+	Blake2_128, // Hasher
+	u32,        // Key
+	i32         // Value
+>;
+```
+
+```rust
+#[test]
+fn storage_map() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		Item9::<T>::insert(0, -100);
+		assert_eq!(Item9::<T>::get(0), Some(-100));
+		assert_eq!(Item9::<T>::get(1), None);
+	});
+}
+```
+
+---
+
+## Storage Map Key
+
+With a storage map, you can introduce a "key" and "value" of arbitrary type.
+
+```rust
+pub struct StorageMap<Prefix, Hasher, Key, Value, ...>(_);
+```
+
+The storage key for a map uses the hash of the key. You can choose the storage hasher, these are the ones currently implemented:
+
+- Identity (no hash at all)
+- Blake2_128 (cryptographic)
+- Blake2_256
+- Twox128 (fast, but not cryptographic)
+- Twox256
+- Twox64Concat (special)
+- Blake2_128Concat (special)
+
+---
+
+## Value Query: Balances
+
+<!-- unclear what the aim is, showing a more complex example? -->
+
+```rust
+#[pallet::storage]
+pub type Item10<T: Config> = StorageMap<_, Blake2_128, T::AccountId, Balance, ValueQuery>;
+```
+
+```rust
+#[test]
+fn balance_map() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		let (alice, bob) = (0u64, 1u64); // these would normally be 32 byte addresses
+		Item10::<T>::insert(alice, 100);
+
+		let transfer = |from: u64, to: u64, amount: u128| -> Result<(), &'static str> {
+			Item10::<T>::try_mutate(from, |from_balance| -> Result<(), &'static str> {
+				Item10::<T>::try_mutate(to, |to_balance| -> Result<(), &'static str> {
+					*to_balance = to_balance.checked_add(amount).ok_or("overflow")?;
+					*from_balance = from_balance.checked_sub(amount).ok_or("not enough balance")?;
+					Ok(())
+				})
+			})
+		};
+
+		assert_noop!(transfer(bob, alice, 10), "not enough balance");
+		assert_ok!(transfer(alice, bob, 10));
+		assert_noop!(transfer(alice, bob, 100), "not enough balance");
+
+		assert_eq!(Item10::<T>::get(alice), 90);
+		assert_eq!(Item10::<T>::get(bob), 10);
+	});
+}
+```
+
+---
+
+## Prefix Tries
+
+All pallets and storage items naturally form "prefix tries".
+
+<img style="height: 500px;" src="../../../../assets/img/6-FRAME/balance-trie.svg" />
+
+In this diagram, a pallet "Balances" has a storage value "Total Issuance" and a map of "Accounts" with balances as the value.
+
+---
+
+## Prefix Trie Keys
+
+Let's now look at the keys of these storage items:
+
+```rust
+use sp_core::hexdisplay::HexDisplay;
+println!("{}", HexDisplay::from(&Item2::<T>::hashed_key()));
+println!("{}", HexDisplay::from(&Item10::<T>::hashed_key_for(0)));
+println!("{}", HexDisplay::from(&Item10::<T>::hashed_key_for(1)));
+```
+
+```sh
+e375d60f814d02157aaaa18f3639a2546fe5a43b77d7334acfb711a021a514b8
+e375d60f814d02157aaaa18f3639a254ca79d14bc48854f664528f3a696b6c27c804ce198ec337e3dc762bdd1a09aece
+e375d60f814d02157aaaa18f3639a254ca79d14bc48854f664528f3a696b6c279ea2d098b5f70192f96c06f38d3fbc97
+```
+
+<table style="font-size: 24px">
+<tr>
+	<td><span style="color: red;">e375d60f814d02157aaaa18f3639a254</span></td>
+	<td><span style="color: lightblue;">6fe5a43b77d7334acfb711a021a514b8</span></td>
+	<td>&nbsp;</td>
+</tr>
+<tr>
+	<td><span style="color: red;">e375d60f814d02157aaaa18f3639a254</span></td>
+	<td><span style="color: lightgreen;">ca79d14bc48854f664528f3a696b6c27</span></td>
+	<td><span style="color: pink;">c804ce198ec337e3dc762bdd1a09aece</span></td>
+</tr>
+<tr>
+	<td><span style="color: red;">e375d60f814d02157aaaa18f3639a254</span></td>
+	<td><span style="color: lightgreen;">ca79d14bc48854f664528f3a696b6c27</span></td>
+	<td><span style="color: orange;">9ea2d098b5f70192f96c06f38d3fbc97</span></td>
+</tr>
+</table>
+
+---
+
+## Storage Iteration
+
+Because all storage items form a prefix trie, you can iterate the content starting with any prefix:
+
+```rust [0|6-7]
+impl<T: Decode + Sized> Iterator for StorageIterator<T> {
+	type Item = (Vec<u8>, T);
+
+	fn next(&mut self) -> Option<(Vec<u8>, T)> {
+		loop {
+			let maybe_next = sp_io::storage::next_key(&self.previous_key)
+				.filter(|n| n.starts_with(&self.prefix));
+			break match maybe_next {
+				Some(next) => {
+					self.previous_key = next.clone();
+					let maybe_value = frame_support::storage::unhashed::get::<T>(&next);
+					match maybe_value {
+						Some(value) => {
+							if self.drain {
+								frame_support::storage::unhashed::kill(&next);
+							}
+							Some((self.previous_key[self.prefix.len()..].to_vec(), value))
+						},
+						None => continue,
+					}
+				},
+				None => None,
+			}
+		}
+	}
+}
+```
+
+---
+
+## You can...
+
+- Iterate all storage on the blockchain using prefix `&[]`
+- Iterate all storage for a pallet using prefix `hash(pallet_name)`
+- Iterate all balances of users using prefix `hash("Balances") ++ hash("Accounts")`
+
+This is not an inherit property!
+
+This is only because we "cleverly" chose this pattern for generating keys.
+
+Note that iteration has no "proper" order. All keys are hashed, and we just go in the order of the resulting hash.
+
+---
+
+## Opaque Storage Keys
+
+But there is a problem...
+
+Let's say I iterate over all users' balances...
+
+- I will get all the balance values.
+- I will get all the storage keys.
+  - Which are all hashed.
+- I will NOT get the actual accounts which hold these balances!
+
+For this, we need **transparent storage keys**.
+
+---
+
+## Transparent Hashes
+
+- Twox64Concat
+- Blake2_128Concat
+
+Basically:
+
+```sh
+final_hash = hash(preimage) ++ preimage
+```
+
+From this kind of hash, we can always extract the preimage:
+
+```sh
+"hello" = 0x68656c6c6f
+blake2_128("hello") = 0x46fb7408d4f285228f4af516ea25851b
+blake2_128concat("hello") = 0x46fb7408d4f285228f4af516ea25851b68656c6c6f
+```
+
+```sh
+"world" = 0x776f726c64
+twox64("world") = 0xef51ee66fefb78e7
+twox64concat("world") = 0xef51ee66fefb78e7776f726c64
+```
+
+---
+
+## Better Balance Map
+
+<div class="text-small">
+
+We should use `Blake2_128Concat`!
+
+```rust
+#[pallet::storage]
+pub type Item11<T: Config> = StorageMap<_, Blake2_128Concat, T::AccountId, Balance, ValueQuery>;
+```
+
+```rust
+#[test]
+fn better_balance_map() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		for i in 0u64..10u64 {
+			Item10::<T>::insert(i, u128::from(i * 100u64));
+			Item11::<T>::insert(i, u128::from(i * 100u64));
+		}
+		// cannot call iter for 10 because it cannot return the keys
+		let all_10: Vec<_> = Item10::<T>::iter_values().collect();
+		let all_11: Vec<_> = Item11::<T>::iter().collect();
+		println!("{:?}\n{:?}", all_10, all_11);
+
+		assert!(false)
+	});
+}
+```
+
+```sh
+[600, 500, 300, 100, 800, 400, 700, 900, 0, 200]
+[(6, 600), (5, 500), (3, 300), (1, 100), (8, 800), (4, 400), (7, 700), (9, 900), (0, 0), (2, 200)]
+```
+
+</div>
+
+---
+
+## Which Hasher to Use?
+
+Now that we know that transparent hashers are extremely useful, there are really just 3 choices:
+
+- `Identity` - No Hash at all
+- `Twox64Concat` - Non-Cryptographic and Transparent Hash
+- `Blake2_128Concat` - Cryptographic and Transparent Hash
+
+---
+
+## Unbalanced Trie
+
+<div class="flex-container">
+<div class="left">
+
+<img src="../../../../assets/img/5-Substrate/unbalanced-tree.svg" />
+
+</div>
+<div class="right">
+
+- We mentioned that unbalanced tries can be good at times...
+- But in this case, we must select a hasher which prevents a user from manipulating the balance of our prefix trie.
+
+</div>
+</div>
+
+---
+
+## Which Hasher to Use?
+
+Basically, you should just always use `Blake2_128Concat` since it is hardest for a user to influence. The difference in time to execute is probably nominal (but not properly benchmarked afaik).
+
+Some reasonable exceptions:
+
+- If the key is already an uncontrollable cryptographic hash, you can use `Identity`.
+- If the key is simple and controlled by runtime (like an incremented count), `Twox64Concat` is good enough.
+
+More info in the docs...
+
+---
+
+### Read the StorageMap Docs for API
+
+https://crates.parity.io/frame_support/pallet_prelude/struct.StorageMap.html
+
+---
+
+### StorageDoubleMap and StorageNMap
+
+Basically the same idea as `StorageMap`, but with more keys:
+
+```rust
+pub struct StorageDoubleMap<Prefix, Hasher1, Key1, Hasher2, Key2, Value, QueryKind = OptionQuery, OnEmpty = GetDefault, MaxValues = GetDefault>(_);
+```
+
+```sh
+Twox128(Prefix::pallet_prefix()) ++ Twox128(Prefix::STORAGE_PREFIX) ++ Hasher1(encode(key1)) ++ Hasher2(encode(key2))
+```
+
+```rust
+pub struct StorageNMap<Prefix, Key, Value, QueryKind = OptionQuery, OnEmpty = GetDefault, MaxValues = GetDefault>(_);
+```
+
+```sh
+Twox128(Prefix::pallet_prefix())
+		++ Twox128(Prefix::STORAGE_PREFIX)
+		++ Hasher1(encode(key1))
+		++ Hasher2(encode(key2))
+	++ ...
+	++ HasherN(encode(keyN))
+```
+
+---
+
+## StorageNMap: Example
+
+```rust
+#[pallet::storage]
+pub type Item12<T: Config> = StorageNMap<
+	_,
+	(
+		NMapKey<Blake2_128Concat, u8>,
+		NMapKey<Blake2_128Concat, u16>,
+		NMapKey<Blake2_128Concat, u32>,
+	),
+	u128,
+>;
+```
+
+Treat the key as a tuple of the composite keys.
+
+```rust
+#[test]
+fn storage_n_map() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		Item12::<T>::insert((1u8, 1u16, 1u32), 1u128);
+		assert_eq!(Item12::<T>::get((1u8, 1u16, 1u32)), Some(1u128));
+	});
+}
+```
+
+---
+
+## Map Iteration Complexity
+
+- Iterating over a map is extremely expensive for computational and storage proof resources.
+- Requires `N` trie reads which is really `N * log(N)` database reads.
+- Takes up `32 bytes per hash * 16 hashes per node * N * log(N)` proof size.
+
+Generally you should not iterate on a map. If you do, make sure it is bounded!
+
+---
+
+## Remove All
+
+Implemented on Storage Maps:
+
+```rust
+// Remove all value of the storage.
+pub fn remove_all(limit: Option<u32>) -> KillStorageResult
+```
+
+Where:
+
+```rust
+pub enum KillStorageResult {
+    AllRemoved(u32),
+    SomeRemaining(u32),
+}
+```
+
+Rather than trying to delete all items at once, you can "freeze" the state machine, and have a user call `remove_all` multiple times using a limit.
+
+---
+
+## Counted Storage Map
+
+A wrapper around a `StorageMap` and a `StorageValue<Value=u32>` to keep track of how many items are in a map, without needing to iterate all the values.
+
+```rust
+pub struct CountedStorageMap<Prefix, Hasher, Key, Value, QueryKind = OptionQuery, OnEmpty = GetDefault, MaxValues = GetDefault>(_);
+```
+
+This storage item has additional storage read and write overhead when manipulating values compared to a regular storage map.
+
+---
+
+## Counted Storage Map Demystified
+
+```rust
+#[pallet::storage]
+pub type Item13<T: Config> = CountedStorageMap<_, Blake2_128Concat, T::AccountId, Balance>;
+```
+
+This `CountedStorageMap` is exactly the same as:
+
+```rust
+#[pallet::storage]
+pub type Item13<T: Config> = StorageMap<_, Blake2_128Concat, T::AccountId, Balance>;
+
+/// Counter is always prefixed with "CounterFor"
+#[pallet::storage]
+pub type CounterForItem13<T: Config> = StorageValue<_, u32>;
+```
+
+With some additional logic to keep these two in check.
+
+---
+
+## Architecture Considerations
+
+- You know that accessing very large items from the database is not efficient:
+  - Databases like ParityDB are optimized for items under 32 KB.
+  - Decoding is non-zero overhead.
+- You know that accessing lots of storage items in a map is also very bad!
+  - Lots of overhead constantly calling host functions.
+  - Lots of overhead from the merkle trie lookup, and database reads.
+  - Lots of **additional** overhead in the storage proof
+
+So what do you pick?
+
+---
+
+## It depends! Sometimes both!
+
+The choice of storage depends on how your logic will access it.
+
+Let's look at some scenarios.
+
+---
+
+## Scenario A
+
+We need to manage millions of users, and support balance transfers.
+
+---
+
+## Scenario A
+
+We need to manage millions of users, and support balance transfers.
+
+-> We should obviously use a map! Balance transfers touch only 2 accounts at a time. 2 map reads is way more efficient than reading all million users to move the balance.
+
+---
+
+## Scenario B
+
+We need to get the 1,000 validators for the next era.
+
+---
+
+## Scenario B
+
+We need to get the 1,000 validators for the next era.
+
+-> We should obviously use a bounded vector! We know there is an upper limit of validators, and we will need to read them all for our logic!
+
+---
+
+## Scenario C
+
+We need to store some metadata about the configuration of each validator.
+
+---
+
+## Scenario C
+
+We need to store some metadata about the configuration of each validator.
+
+-> We should probably use a map. We will be duplicating some data from the vector mentioned in B, but the way we access configuration usually is on a per-validator basis. So updating one validator's configuration does not have
+to touch the others.
+
+---
+
+## Summary
+
+- FRAME Storage is just simple macros which wrap the underlying Substrate Storage APIs.
+- The principles of Substrate Storage directly inform what kinds of behaviors you can do in FRAME.
+- Just because something does not exist in FRAME does not mean you cannot do it!
+- Just because something does exist in FRAME does not mean you can use it without thinking!
diff --git a/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Pallet_Hooks-slides.md b/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Pallet_Hooks-slides.md
new file mode 100644
index 00000000..b3fae61e
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Pallet_Hooks-slides.md
@@ -0,0 +1,512 @@
+---
+title: FRAME/Pallet Hooks
+description: FRAME/Pallet Hooks
+duration: 1 hour
+---
+
+# 🪝 FRAME/Pallet Hooks 🪝
+
+You can not just execute logic in calls, but regularly on events.
+
+Notes:
+One of the distinctions from contracts that always need to be called.
+
+---
+
+## Hooks: All In One
+
+- Onchain / STF
+  - `on_runtime_upgrade`
+  - `on_initialize`
+  - `on_poll`
+  - `on_idle`
+  - `on_finalize`
+- Offchain:
+  - `genesis_build`
+  - `offchain_worker`
+  - `integrity_test`
+  - `try_state`
+
+Notes:
+
+https://paritytech.github.io/substrate/master/frame_support/traits/trait.Hooks.html
+
+---v
+
+### Hooks: All In One
+
+```rust
+#[pallet::hooks]
+impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
+  fn on_runtime_upgrade() -> Weight {}
+  fn on_initialize() -> Weight {}
+  fn on_finalize() {}
+  fn on_idle(remaining_weight: Weight) -> Weight {}
+  fn on_poll(weight: &mut WeightMeter) {}
+  fn offchain_worker() {}
+  fn integrity_test() {}
+  #[cfg(feature = "try-runtime")]
+  fn try_state() -> Result<(), &'static str> {}
+}
+
+#[pallet::genesis_build]
+impl<T: Config> BuildGenesisConfig for GenesisConfig<T> {
+	fn build(&self) {}
+}
+```
+
+Notes:
+
+Many of these functions receive the block number as an argument, but that can easily be fetched from
+`frame_system::Pallet::<T>::block_number()`
+
+---
+
+## Hooks: `on_runtime_upgrade`
+
+- Called every time the `spec_version`/`spec_name` is bumped.
+- Why might you be interested in implementing this?
+  - &shy;<!-- .element: class="fragment" --> **State Migration**, see dedicated lecture
+- &shy;<!-- .element: class="fragment" --> _Note_: Called before `on_initialize`, so the state might be subtly different from an extrinsic.
+
+Notes:
+
+Because very often runtime upgrades need to be accompanied by some kind of state migration.
+Has its own lecture, more over there.
+
+---
+
+## Hooks: `on_initialize`
+
+- Useful for any kind of **automatic** and **necessary** operation.
+- The weight you return is interpreted as `DispatchClass::Mandatory`.
+
+---v
+
+### Hooks: `on_initialize`
+
+- `Mandatory` Hooks should really be lightweight and predictable, with a bounded complexity.
+
+```rust
+fn on_initialize() -> Weight {
+  // any user can create one entry in `MyMap` 😱🔫.
+  <MyMap<T>>::iter().for_each(do_stuff);
+}
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Hooks: `on_initialize`
+
+- &shy;<!-- .element: class="fragment" --> Question: If you have 3 pallets, in which order are their `on_initialize` hooks called?
+- &shy;<!-- .element: class="fragment" --> Question: If your runtime panics `on_initialize`, how can you recover from it?
+- &shy;<!-- .element: class="fragment" --> Question: If your `on_initialize` consumes more than the maximum block weight?
+
+Notes:
+
+- The order comes from `construct_runtime!` macro.
+- Panic in mandatory hooks is fatal error. You are pretty much done. Most likely need to fork the chain.
+- Overweight blocks using mandatory hooks are possible, ONLY in the context of solo-chains. Such a
+  block will take longer to produce, but it eventually will. If you have your eyes set on being a
+  parachain developer, you should treat overweight blocks as fatal as well.
+
+---
+
+## Hooks: `on_poll`
+
+```rust
+fn on_poll(_n: BlockNumber, _weight: &mut WeightMeter)
+```
+
+- The non-mandatory version of `on_initialize`, i.e. it is not guaranteed to execute every block.
+- Runs after inherents.
+- Comes with a weight meter that needs to be adhered to. More on weights in the dedicated lecture.
+
+Notes:
+
+See https://github.com/paritytech/substrate/pull/14279 , https://github.com/paritytech/polkadot-sdk/pull/1781 and related PRs
+
+---
+
+## Hooks: `on_finalize`
+
+- Extension of `on_initialize`, but at the end of the block.
+- Its weight needs to be known in advance. Therefore, less preferred compared to `on_initialize`.
+
+```rust
+fn on_finalize() {} // ✅
+fn on_finalize() -> Weight {} // ❌
+```
+
+<!-- .element: class="fragment" -->
+
+- Nothing to do with _finality_ in the consensus context.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Hooks: `on_finalize`
+
+> Generally, avoid using it unless if something REALLY needs to happen at the end of the block.
+
+&shy;<!-- .element: class="fragment" --> _Tip_: Sometimes, rather than thinking "at the end of block N", consider writing code "at the beginning of block N+1".
+
+Notes:
+
+Sometimes, rather than thinking "at the end of block N", consider writing code "at the beginning of block N+1"
+
+---
+
+## Hooks: `on_idle`
+
+- **_Optional_** variant of `on_finalize`, also executed at the end of the block, that uses left-over weight.
+- Small semantic difference: executes pallets' hooks randomly, rather than in `construct_runtime` order, and only
+  if there is weight left.
+
+---v
+
+## The Future: Moving Away From Mandatory Hooks
+
+- `on_initialize` -> `on_poll`
+- `on_finalize` -> `on_idle`
+- New primitives for multi-block migrations
+- New primitives for optional service work via extrinsics.
+
+Notes:
+
+This is all in the agenda of the FRAME team at Parity for 2023.
+
+https://github.com/paritytech/substrate/issues/13530
+https://github.com/paritytech/substrate/issues/13690
+
+---
+
+## Recap: Onchain/STF Hooks
+
+<diagram class="mermaid">
+%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
+graph LR
+    subgraph AfterTransactions
+        direction LR
+        OnIdle --> OnFinalize
+    end
+
+    subgraph OnChain
+        direction LR
+        Optional --> BeforeExtrinsics
+        BeforeExtrinsics --> Inherents
+        Inherents --> Poll
+        Poll --> Transactions
+        Transactions --> AfterTransactions
+    end
+
+    subgraph Optional
+
+OnRuntimeUpgrade
+end
+
+    subgraph BeforeExtrinsics
+        OnInitialize
+    end
+
+    subgraph Transactions
+        Transaction1 --> UnsignedTransaction2 --> Transaction3
+    end
+
+    subgraph Inherents
+        Inherent1 --> Inherent2
+    end
+
+</diagram>
+
+Notes:
+
+implicit in this:
+
+Inherents are only first, which is being discussed RIGHT NOW: https://github.com/polkadot-fellows/RFCs/pull/13
+
+---
+
+## Hooks: `genesis_build`
+
+- Means for each pallet to specify a $f(input): state$ at genesis.
+- This is called only once, by the client, when you **create a new chain**.
+  - &shy;<!-- .element: class="fragment" --> Is this invoked every time you run `cargo run`?
+- `#[pallet::genesis_build]`.
+
+---v
+
+### Hooks: `genesis_build`
+
+```rust
+#[pallet::genesis_build]
+pub struct GenesisConfig<T: Config> {
+  pub foo: Option<u32>,
+  pub bar: Vec<u8>,
+}
+```
+
+<!-- .element: class="fragment" -->
+
+```rust
+impl<T: Config> Default for GenesisConfig<T> {
+  fn default() -> Self {
+    // snip
+  }
+}
+```
+
+<!-- .element: class="fragment" -->
+
+```rust
+#[pallet::genesis_build]
+impl<T: Config> GenesisBuild<T> for GenesisConfig<T> {
+  fn build(&self) {
+    // use self.foo, self.bar etc.
+  }
+}
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Hooks: `genesis_build`
+
+- `GenesisConfig` is a composite/amalgamated item at the top level runtime.
+
+```rust
+construct_runtime!(
+  pub enum Runtime where {
+    System: frame_system,
+    Balances: pallet_balances,
+  }
+);
+```
+
+```rust
+struct RuntimeGenesisConfig {
+  SystemConfig: pallet_system::GenesisConfig,
+  PalletAConfig: pallet_a::GenesisConfig,
+}
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+https://paritytech.github.io/substrate/master/node_template_runtime/struct.RuntimeGenesisConfig.html
+
+---v
+
+### Hooks: `genesis_build`
+
+<!-- check what the state of this is -->
+
+- Recent changes moving `genesis_build` to be used over a runtime API, rather than native runtime.
+- `#[cfg(feature = "std")]` in pallets will go away.
+
+Notes:
+
+https://github.com/paritytech/substrate/issues/13334
+
+---
+
+## Hooks: `offchain_worker`
+
+**Fully offchain application**:
+
+- Read chain state via RPC.
+- submit desired side effects back to the chain as transactions.
+
+**Runtime Offchain Worker**:
+
+- &shy;<!-- .element: class="fragment" --> Code lives onchain, upgradable only in synchrony with the whole runtime 👎
+- &shy;<!-- .element: class="fragment" --> Ergonomic and fast state access 👍
+- &shy;<!-- .element: class="fragment" --> State writes are ignored 🤷
+- &shy;<!-- .element: class="fragment" --> Can submit transactions back to the chain as well ✅
+- &shy;<!-- .element: class="fragment" --> Source of many confusions!
+
+Notes:
+
+People have often thought that they can do magic with things with OCW, please don't. BIG warning to
+founders to be careful with this!
+
+https://paritytech.github.io/substrate/master/pallet_examples/index.html
+
+---v
+
+### Hooks: `offchain_worker`
+
+- Execution entirely up to the client.
+- Has a totally separate thread pool than the normal execution.
+
+```
+--offchain-worker <ENABLED>
+    Possible values:
+    - always:
+    - never:
+    - when-authority
+
+--execution-offchain-worker <STRATEGY>
+    Possible values:
+    - native:
+    - wasm:
+    - both:
+    - native-else-wasm:
+```
+
+---v
+
+### Hooks: `offchain_worker`
+
+- Threads can **overlap**, each is reading the state of its corresponding block
+
+<img style="height: 500px" src="../../../../assets/img//6-FRAME/ocw.svg" />
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+https://paritytech.github.io/substrate/master/sp_runtime/offchain/storage_lock/index.html
+
+---v
+
+### Hooks: `offchain_worker`
+
+- &shy;<!-- .element: class="fragment" -->Offchain workers have their own **special host
+  functions**: http, dedicated storage, time, etc.
+- &shy;<!-- .element: class="fragment" -->Offchain workers have the same **execution limits** as
+  Wasm (limited memory, custom allocator).
+
+- &shy;<!-- .element: class="fragment" -->Source of confusion, why OCWs cannot write to state.
+
+Notes:
+
+These are the source of the confusion.
+
+Word on allocator limit in Substrate Wasm execution (subject to change).
+
+- Max single allocation limited
+- Max total allocation limited.
+
+---
+
+## Hooks: `integrity_test`
+
+- Put into a test by `construct_runtime!`.
+
+```rust
+__construct_runtime_integrity_test::runtime_integrity_tests
+```
+
+<!-- .element: class="fragment" -->
+
+```rust
+fn integrity_test() {
+  assert!(
+    T::MyConfig::get() > 0,
+    "Are all of the generic types I have sensible?"
+  );
+  // notice that this is for tests, std is available.
+  assert!(std::mem::size_of::<T::Balance>() > 4);
+}
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+I am in fan of renaming this. If you are too, please comment here
+
+---
+
+## Hooks: `try_state`
+
+- A means for you to ensure correctness of your $STF$, after each transition.
+- &shy;<!-- .element: class="fragment" -->Entirely offchain, custom runtime-apis, conditional
+  compilation.
+  - &shy;<!-- .element: class="fragment" -->Called from `try-runtime-cli`, which you will learn about in another lecture.
+- &shy;<!-- .element: class="fragment" -->Examples from your assignment?
+
+Notes:
+
+What is a transition? Either a block, or single extrinsic
+
+---
+
+## Hooks: Recap
+
+<diagram class="mermaid">
+%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
+graph LR
+    subgraph Offchain
+        OffchainWorker
+        TryState
+    end
+
+    subgraph Genesis
+        GenesisBuild
+    end
+
+    subgraph AfterTransactions
+        direction LR
+        OnIdle --> OnFinalize
+    end
+
+    subgraph OnChain
+        direction LR
+        Optional --> BeforeExtrinsics
+        BeforeExtrinsics --> Inherents
+        Inherents --> Poll
+        Poll --> Transactions
+        Transactions --> AfterTransactions
+    end
+
+    subgraph Optional
+
+OnRuntimeUpgrade
+end
+
+    subgraph BeforeExtrinsics
+        OnInitialize
+    end
+
+    subgraph Transactions
+        Transaction1 --> UnsignedTransaction2 --> Transaction3
+    end
+
+    subgraph Inherents
+        Inherent1 --> Inherent2
+    end
+
+</diagram>
+
+- What other hooks can you think of?
+
+Notes:
+
+What other ideas you can think of?
+
+- a hook called once a pallet is first initialized.
+  https://github.com/paritytech/substrate/issues/14098
+- Local on Post/Pre dispatch: https://github.com/paritytech/substrate/issues/12047
+- Global on Post/Pre dispatch is in fact a signed extension. It has to live in the runtime, because you have to specify order.
+
+---
+
+## Additional Resources! 😋
+
+> Check speaker notes (click "s" 😉)
+
+Notes:
+
+## Post lecture Notes
+
+Regarding this drawback to offchain workers that you can only upgrade in cadence with the network.
+Offchain worker, like tx-pool api, is only called from an offchain context. Node operators can
+easily use the runtime overrides feature to change the behavior of their offchain worker anytime
+they want.
diff --git a/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/index.md b/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/index.md
new file mode 100644
index 00000000..25dcc520
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/2-FRAME_Basics/index.md
@@ -0,0 +1 @@
+# Basics
diff --git a/content/6-Protocol_On-Chain/FRAME/3-FRAME_Runtime/Construct_Runtime-slides.md b/content/6-Protocol_On-Chain/FRAME/3-FRAME_Runtime/Construct_Runtime-slides.md
new file mode 100644
index 00000000..d5fabe8c
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/3-FRAME_Runtime/Construct_Runtime-slides.md
@@ -0,0 +1,618 @@
+---
+title: Construct Runtime
+description: Deep dive into the Construct Runtime macro
+duration: 1 hour
+instructors: ["Kian Paimani"]
+---
+
+# `construct_runtime!` and Testing 🔨
+
+---
+
+# Part 1: Runtime Construction
+
+---
+
+<img style="height: 600px" src="../../../../assets/img/6-FRAME/frame1.svg" />
+
+---
+
+## Pallet <=> Runtime
+
+A runtime is really ✌️ things:
+
+1. A struct that implements `Config` of all pallets.
+2. A type that helps `Executive` implement `RuntimeApis`.
+
+---v
+
+### Pallet <=> Runtime
+
+We build a runtime, using `construct_runtime`|`#[runtime]`, typically twice:
+
+1. Per pallet, there is a mock runtime.
+2. A real runtime elsewhere.
+
+Note:
+
+Benchmarking can then use both of these runtimes.
+
+---
+
+## `construct_runtime`: `Runtime` type
+
+<div class="flex-container text-small">
+<div class="left" style="max-width: 50%;">
+
+Legacy syntax:
+
+```rust [1-100|2]
+frame_support::construct_runtime!(
+  pub struct Runtime {
+    System: frame_system,
+    Timestamp: pallet_timestamp,
+    Balances: pallet_balances,
+    Aura: pallet_aura,
+    Dpos: pallet_dpos,
+  }
+);
+```
+
+</div>
+<div class="right" style="max-width: 50%; padding-left: 10px;">
+
+New syntax:
+
+```rust [1-100|5]
+#[frame_support::runtime]
+mod runtime {
+  #[runtime::runtime]
+  #[runtime::derive(RuntimeCall, RuntimeEvent, ...)]
+  pub struct Runtime;
+  #[runtime::pallet_index(0)]
+  pub type System = frame_system;
+  #[runtime::pallet_index(1)]
+  pub type Timestamp = pallet_timestamp;
+  #[runtime::pallet_index(2)]
+  pub type Balances = pallet_balances;
+  #[runtime::pallet_index(5)]
+  pub type <NameYouChoose> = path_to_crate;
+}
+```
+
+</div>
+</div>
+
+---v
+
+### `Runtime` type
+
+- It implements [A LOT OF STUFF](https://paritytech.github.io/substrate/master/kitchensink_runtime/struct.Runtime.html)!
+- But most importantly, the `Config` trait of all of your pallets 🫵🏻.
+
+```rust
+impl frame_system::Config for Runtime { .. }
+impl pallet_timestamp::Config for Runtime { .. }
+impl pallet_dpos::Config for Runtime { .. }
+```
+
+---v
+
+### `<T: Config>` ==> `Runtime`
+
+> Anywhere in your pallet code that you have `<T: Config>` can now be replaced with `Runtime`.
+
+```rust[1-2|3-4|5-6]
+// a normal pub function defined in
+frame_system::Pallet::<Runtime>::block_number();
+// a storage getter of a map.
+frame_system::Pallet::<Runtime>::account(42u32);
+// A storage type.
+frame_system::Account::<Runtime>::get(42u32);
+```
+
+---
+
+## `construct_runtime`: Pallet List
+
+<div class="flex-container text-small">
+<div class="left" style="max-width: 50%;">
+
+Legacy syntax:
+
+```rust [3-7|8]
+frame_support::construct_runtime!(
+  pub struct Runtime {
+    System: frame_system = 0,
+    Timestamp: pallet_timestamp = 1,
+    Balances: pallet_balances,
+    Aura: pallet_aura,
+    Dpos: pallet_dpos = 42,
+    <NameYouChoose>: path_to_crate,
+  }
+);
+```
+
+</div>
+<div class="right" style="max-width: 50%; padding-left: 10px;">
+
+New syntax:
+
+```rust [6-11|12-13]
+#[frame_support::runtime]
+mod runtime {
+  #[runtime::runtime]
+  #[runtime::derive(RuntimeCall, RuntimeEvent, ...)]
+  pub struct Runtime;
+  #[runtime::pallet_index(0)]
+  pub type System = frame_system;
+  #[runtime::pallet_index(1)]
+  pub type Timestamp = pallet_timestamp;
+  #[runtime::pallet_index(2)]
+  pub type Balances = pallet_balances;
+  #[runtime::pallet_index(5)]
+  pub type <NameYouChoose> = path_to_crate;
+}
+```
+
+</div>
+</div>
+
+---v
+
+### Pallet List
+
+- Crucially, under the hood, this generates:
+
+```rust
+type System = frame_system::Pallet<Runtime>;
+type Balances = pallet_balances::Pallet<Runtime>;
+..
+type DPos = pallet_dpos::Pallet<Runtime>;
+```
+
+- Recall that `Runtime` implements `<T: Config>` of all pallets.
+
+---v
+
+### Pallet List
+
+```rust
+frame_system::Pallet::<Runtime>::block_number(); // 🤮
+System::block_number(); // 🥳
+
+frame_system::Pallet::<Runtime>::account(42u32); // 🤮
+System::account(42u32); // 🥳
+```
+
+---v
+
+### Pallet List
+
+- Next crucial piece of information that is generated is:
+
+```rust
+type AllPalletsWithSystem = (System, Balances, ..., Dpos);
+```
+
+</div>
+
+- This is used in `Executive` to dispatch pallet hooks.
+
+```rust
+<AllPallets as OnInitialize>::on_initialize();
+<AllPallets as OnInitialize>::on_finalize();
+```
+
+</div>
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+Question: What will be the order of `fn on_initialize()`?
+There's also `type AllPalletsWithoutSystem` and some other variants that are no longer
+
+---v
+
+### Pallet List + Outer Enums
+
+- Generates some outer types:
+
+  - `RuntimeCall`
+  - `RuntimeEvent`
+  - `RuntimeOrigin`
+  - `RuntimeGenesisConfig`
+
+Notes:
+
+See the lecture on individual item, and the "Outer Enum" lecture.
+
+---v
+
+### Pallet List: `RuntimeCall` Example
+
+```rust
+// somewhere in your pallet, called `my_pallet`
+#[pallet::call]
+impl<T: Config> Pallet<T> {
+  fn transfer(origin: OriginFor<T>, from: T::AccountId, to: T::AccountId, amount: u128);
+  fn update_runtime(origin: OriginFor<T>, new_code: Vec<u8>);
+}
+```
+
+```rust
+// expanded in your pallet
+enum Call {
+  transfer { from: T::AccountId, to: T::AccountId, amount: u128 },
+  update_runtime { new_code: Vec<u8> },
+}
+```
+
+<!-- .element: class="fragment" -->
+
+```rust
+// in your outer runtime
+enum RuntimeCall {
+  System(frame_system::Call),
+  MyPallet(my_pallet::Call),
+}
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Pallet List: Pallet Parts
+
+```rust [1-100|3-5]
+frame_support::construct_runtime!(
+  pub struct Runtime {
+    System: frame_system::{Pallet, Call, Config, Storage, Event<T>},
+    Balances: pallet_balances::{Pallet, Call, Storage, Config<T>, Event<T>},
+    Dpos: pallet_dpos,
+  }
+);
+```
+
+- Omitting them will exclude them from the metadata, or the "outer/runtime types"
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Pallet List: Pallet Parts
+
+New syntax doesn't have parts in the same way but offers customization:
+
+```rust [2-3|6-7]
+#[runtime::pallet_index(1)]
+// can be optionally attached to a pallet to disable unsigned calls
+#[runtime::disable_unsigned]
+pub type Timestamp = pallet_timestamp;
+#[runtime::pallet_index(2)]
+// can be optionally attached to a pallet to disable its calls
+#[runtime::disable_call]
+pub type Balances = pallet_balances;
+```
+
+---
+
+## `construct_runtime`: Final Thoughts
+
+- Order in the `construct_runtime` matters! (but not in `#[runtime]`)
+- Recall `integrity_test()` is called upon `construct_runtime`.
+
+```sh
+test mock::__construct_runtime_integrity_test::runtime_integrity_tests ... ok
+```
+
+---
+
+# Part 2: Testing
+
+---
+
+## Testing and Mocks
+
+A test requires a mock runtime, so we need to do a full `construct_runtime` 😱
+
+.. but luckily, most types can be mocked 😮‍💨
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Testing and Mocks
+
+- `u32` account id.
+- `u128` balance.
+- `u32` block number.
+- ...
+
+---
+
+## Testing: `Get<_>`
+
+- Next, we want to supply some value to those `Get<_>` associated types.
+
+```rust
+#[pallet::config]
+pub trait Config: frame_system::Config {
+  type MaxVoters: Get<u32>;
+}
+```
+
+---v
+
+### Testing: `Get<_>`
+
+```rust
+parameter_types! {
+  pub const MyMaxVoters: u32 = 16;
+}
+```
+
+```rust
+impl pallet_template::Config for Runtime {
+  type MaxVoters = MyMaxVoters;
+}
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Testing: `Get<_>`
+
+- Or, if your value is always constant:
+
+```rust
+impl pallet_dpos::Config for Runtime {
+  type MaxVoters = frame_support::traits::ConstU32<16>;
+}
+```
+
+---v
+
+### Testing: `Get<_>`
+
+- Or, if you want to torture yourself:
+
+```rust
+pub struct MyMaxVoters;
+impl Get<u32> for MyMaxVoters {
+  fn get() -> u32 {
+    100
+  }
+}
+
+impl pallet_dpos::Config for Runtime {
+  type MaxVoters = MyMaxVoters;
+}
+```
+
+---
+
+## Testing: Genesis and Builder
+
+- Next, if you want to feed some data into your pallet's genesis state, we must first setup the
+  genesis config correctly.
+
+```rust
+#[pallet::genesis_config]
+#[derive(frame_support::DefaultNoBound)]
+pub struct GenesisConfig<T: Config> {
+	pub voters: Vec<(T::AccountId, Option<Vote>)>,
+}
+
+#[pallet::genesis_build]
+impl<T: Config> BuildGenesisConfig for GenesisConfig<T> {
+  fn build(&self) {
+    for (voter, maybe_vote) in &self.voters {
+      // do stuff.
+    }
+  }
+}
+```
+
+---v
+
+### Testing and Mocks: Genesis and Builder
+
+- Then, we build a builder pattern to construct the genesis config.
+
+```rust
+#[derive(Default)]
+pub struct Builder {
+  pub voters: Vec<(u64, Option<Vote>)>,
+}
+```
+
+```rust
+impl Builder {
+  pub fn add_voter(mut self, who: u64) -> Self {
+    self.voters.push((who, None));
+    self
+  }
+}
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Testing and Mocks: Genesis and Builder
+
+- Finally:
+
+```rust
+impl Builder {
+  pub fn build(self) -> TestExternalities {
+    let system = frame_system::GenesisConfig::<Runtime>::default();
+    let template_module = crate::GenesisConfig { voters: self.voters, ..Default::default() };
+    RuntimeGenesisConfig { system, template_module }.build_storage().unwrap().into()
+  }
+
+  pub fn build_and_execute(self, f: impl FnOnce()) {
+    let mut ext = self.build();
+    ext.execute_with(f);
+    // any post checks can come here.
+  }
+}
+```
+
+---v
+
+### Testing and Mocks
+
+- Finally, this allows you to write a test like this:
+
+```rust
+#[test]
+fn test_stuff() {
+  let mut ext = Builder::default()
+    .add_voter_with_vote(2, Vote::Aye)
+    .add_voter(3)
+    build_and_execute(|| {
+      // do stuff
+    });
+}
+```
+
+---
+
+## Testing: static `parameter_types!`
+
+- What if you want to change that `MyMaxVoters`?
+
+<div>
+
+```rust
+parameter_types! {
+  pub static MyMaxVoters: u32 = 100;
+}
+```
+
+```rust
+MyMaxVoters::set(200);
+MyMaxVoters::get();
+```
+
+<!-- .element: class="fragment" -->
+
+</div>
+
+---
+
+## Test ing: Progressing Blocks
+
+- Often times, in your test, you want mimic the progression of an empty block.
+- De-nada! We can fake everything in tests 🤠
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Progressing Blocks
+
+```rust
+pub fn next_block() {
+  let now = System::block_number();
+  Dpos::on_finalize(now);
+  System::on_finalize(now);
+
+  System::set_block_number(now + 1);
+
+  System::on_initialize(now + 1)
+  Dpos::on_initialize(now + 1);
+}
+```
+
+---v
+
+### Progressing Blocks
+
+```rust
+pub fn next_block() {
+  let now = System::block_number();
+  AllPallets::on_finalize(now);
+
+  System::set_block_number(now + 1);
+
+  AllPallets::on_initialize(now + 1)
+}
+```
+
+---v
+
+### Progressing Blocks
+
+````rust
+```rust
+#[test]
+fn test() {
+  let mut ext = Builder::default()
+    .add_validator(1)
+    .set_minimum_delegation(200)
+    .build();
+  ext.execute_with(|| {
+    // initial stuff
+    next_block();
+
+    // dispatch some call
+    assert!(some_condition);
+
+    next_block();
+
+    // repeat..
+  });
+}
+````
+
+```
+---
+
+## Additional Resources 😋
+
+> Check speaker notes (click "s" 😉)
+
+Notes:
+
+- This PR was actually an outcome Cambridge PBA: https://github.com/paritytech/substrate/pull/11932
+- https://github.com/paritytech/substrate/pull/11818
+- https://github.com/paritytech/substrate/pull/10043
+- On usage of macros un Substrate: https://github.com/paritytech/substrate/issues/12331
+- Disscussion on advance testing: https://forum.polkadot.network/t/testing-complex-frame-pallets-discussion-tools/356
+- Reserve topic: Reading events.
+- Reserve-topic: try-state.
+
+### Original Lecture Script
+
+this is your bridge from a pallet into a runtime.
+
+a runtime amalgamator is composed of the following:
+
+1. all pallet's `Config` implemented by a `struct Runtime`;
+1. construct `Executive` and use it to implement all the runtime APIs
+1. Optionally, some boilerplate to setup benchmarking.
+1. invoke `construct_runtime!`.
+1. Alias for each pallet.
+
+The `construct_runtime!` itself does a few things under the hood:
+
+1. crate `struct Runtime`.
+1. amalgamate `enum RuntimeCall`; // passed inwards to some pallets that want to store calls.
+1. amalgamate `enum RuntimeEvent`; // passed inwards to all pallets.
+1. amalgamate `enum RuntimeOrigin` (this is a fixed struct, not an amalgamation);
+1. Create a very important type alias:
+
+- `type AllPallets` / `type AllPalletsWithoutSystem`
+
+1. run `integrity_test()`.
+
+> Note that there is no such thing as `RuntimeError`. Errors are not amalgamated, they just are. This should be in the error lecture.
+
+- Ordering in `construct_runtime` matters.
+- Pallet parts can be optional in `construct_runtime!`.
+```
diff --git a/content/6-Protocol_On-Chain/FRAME/3-FRAME_Runtime/Origins-slides.md b/content/6-Protocol_On-Chain/FRAME/3-FRAME_Runtime/Origins-slides.md
new file mode 100644
index 00000000..b20bfa0c
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/3-FRAME_Runtime/Origins-slides.md
@@ -0,0 +1,375 @@
+---
+title: FRAME Origin
+description: Deep dive into FRAME Origins
+duration: 1 hour
+---
+
+# Origin
+
+---
+
+## Origin
+
+This presentation will cover the use of Origin in FRAME, and how you can customize and extend this abstractions.
+
+([Reference in `polkadot-sdk-docs`](https://paritytech.github.io/polkadot-sdk/master/polkadot_sdk_docs/reference_docs/frame_origin/index.html))
+
+---
+
+## What is Origin?
+
+All dispatchable calls have an `Origin` that describes where the call originates from.
+
+```rust
+/// Make some on-chain remark.
+#[pallet::weight(T::SystemWeightInfo::remark(_remark.len() as u32))]
+pub fn remark(origin: OriginFor<T>, _remark: Vec<u8>) -> DispatchResultWithPostInfo {
+	ensure_signed_or_root(origin)?;
+	Ok(().into())
+}
+```
+
+---
+
+## FRAME System `RawOrigin`
+
+These are origins which are included with FRAME by default.
+
+```rust
+/// Origin for the System pallet.
+#[derive(PartialEq, Eq, Clone, RuntimeDebug, Encode, Decode, TypeInfo, MaxEncodedLen)]
+pub enum RawOrigin<AccountId> {
+	/// The system itself ordained this dispatch to happen: this is the highest privilege level.
+	Root,
+	/// It is signed by some public key and we provide the `AccountId`.
+	Signed(AccountId),
+	/// It is signed by nobody, can be either:
+	/// * included and agreed upon by the validators anyway,
+	/// * or unsigned transaction validated by a pallet.
+	None,
+}
+```
+
+---
+
+## How is it used?
+
+The Runtime Origin is used by dispatchable functions to check where a call has come from.
+
+This is similar to `msg.sender` in Solidity, but FRAME is more powerful, and so is `Origin`.
+
+---
+
+## Origin Checks
+
+```rust
+/// Ensure that the origin `o` represents the root. Returns `Ok` or an `Err` otherwise.
+pub fn ensure_root<OuterOrigin, AccountId>(o: OuterOrigin) -> Result<(), BadOrigin>
+```
+
+```rust
+/// Ensure that the origin `o` represents a signed extrinsic (i.e. transaction).
+/// Returns `Ok` with the account that signed the extrinsic or an `Err` otherwise.
+pub fn ensure_signed<OuterOrigin, AccountId>(o: OuterOrigin) -> Result<AccountId, BadOrigin>
+```
+
+```rust
+/// Ensure that the origin `o` represents an unsigned extrinsic. Returns `Ok` or an `Err` otherwise.
+pub fn ensure_none<OuterOrigin, AccountId>(o: OuterOrigin) -> Result<(), BadOrigin>
+```
+
+```rust
+/// Ensure that the origin `o` represents either a signed extrinsic (i.e. transaction) or the root.
+/// Returns `Ok` with the account that signed the extrinsic, `None` if it was root,  or an `Err`
+/// otherwise.
+pub fn ensure_signed_or_root<OuterOrigin, AccountId>(o: OuterOrigin) -> Result<Option<AccountId>, BadOrigin>
+```
+
+---
+
+## Examples: Signed Origin
+
+A Simple Balance Transfer.
+
+```rust
+#[pallet::call_index(0)]
+#[pallet::weight(T::WeightInfo::transfer())]
+pub fn transfer(
+	origin: OriginFor<T>,
+	dest: AccountIdLookupOf<T>,
+	#[pallet::compact] value: T::Balance,
+) -> DispatchResultWithPostInfo {
+	let transactor = ensure_signed(origin)?;
+	// -- snip --
+}
+```
+
+Most extrinsics use a `Signed` origin.
+
+---
+
+## Examples: Root Origin
+
+The extrinsic to upgrade a chain.
+
+```rust
+/// Set the new runtime code.
+#[pallet::call_index(2)]
+#[pallet::weight((T::BlockWeights::get().max_block, DispatchClass::Operational))]
+pub fn set_code(origin: OriginFor<T>, code: Vec<u8>) -> DispatchResultWithPostInfo {
+	ensure_root(origin)?;
+	Self::can_set_code(&code)?;
+	T::OnSetCode::set_code(code)?;
+	Ok(().into())
+}
+```
+
+`Root` has access to many functions which can directly modify your blockchain. Assume Root access can do anything.
+
+---
+
+## Examples: None Origin
+
+Setting the timestamp of the block.
+
+```rust
+	/// Set the current time.
+	#[pallet::call_index(0)]
+	#[pallet::weight((T::WeightInfo::set(), DispatchClass::Mandatory))]
+	pub fn set(origin: OriginFor<T>, #[pallet::compact] now: T::Moment) -> DispatchResult {
+		ensure_none(origin)?;
+		// -- snip --
+	}
+}
+```
+
+`None` origin is not very straight forward. More details next...
+
+---
+
+## None for Inherents
+
+`None` origin can be used to represents extrinsics which are specifically included by the block author, also known as an inherent.
+
+In those cases, it includes inherent checking logic with `ProvideInherent`.
+
+```rust
+#[pallet::inherent]
+impl<T: Config> ProvideInherent for Pallet<T> {
+	type Call = Call<T>;
+	type Error = InherentError;
+	const INHERENT_IDENTIFIER: InherentIdentifier = INHERENT_IDENTIFIER;
+
+	// -- snip --
+```
+
+---
+
+## None for Unsigned
+
+`None` can also be used to represent "unsigned extrinsics", which are intended to be submitted by anyone without a key.
+
+In those cases, it includes unsigned validation logic with `ValidateUnsigned`.
+
+```rust
+#[pallet::validate_unsigned]
+impl<T: Config> ValidateUnsigned for Pallet<T> {
+	type Call = Call<T>;
+	fn validate_unsigned(source: TransactionSource, call: &Self::Call) -> TransactionValidity {
+		Self::validate_unsigned(source, call)
+	}
+
+	fn pre_dispatch(call: &Self::Call) -> Result<(), TransactionValidityError> {
+		Self::pre_dispatch(call)
+	}
+}
+```
+
+---
+
+## Custom Origins
+
+Origins are extensible and customizable.
+
+Each pallet can introduce new Origins which can be used throughout the runtime.
+
+```rust
+/// The `#[pallet::origin]` attribute allows you to define some origin for the pallet.
+#[pallet::origin]
+pub struct Origin<T>(PhantomData<(T)>);
+```
+
+---
+
+## Example: Collective Pallet
+
+```rust
+/// Origin for the collective module.
+pub enum RawOrigin<AccountId, I> {
+	/// It has been condoned by a given number of members of the collective from a given total.
+	Members(MemberCount, MemberCount),
+	/// It has been condoned by a single member of the collective.
+	Member(AccountId),
+	/// Dummy to manage the fact we have instancing.
+	_Phantom(PhantomData<I>),
+}
+```
+
+This custom origin allows us to represent a collection of users, rather than a single account.
+For example: `Members(5, 9)` represents that 5 out of 9 members agree on something as controlled by the collective pallet logic.
+
+---
+
+## Example: Parachain Origin
+
+```rust
+/// Origin for the parachains.
+#[pallet::origin]
+pub enum Origin {
+	/// It comes from a parachain.
+	Parachain(ParaId),
+}
+```
+
+This is a custom origin which allows us to represent a message that comes from a parachain.
+
+---
+
+## Re-Dispatching
+
+You can actually dispatch a call within a call with an origin of your choice.
+
+```rust [11]
+#[pallet::call_index(0)]
+#[pallet::weight({ let dispatch_info = call.get_dispatch_info(); (dispatch_info.weight, dispatch_info.class) })]
+pub fn sudo(
+	origin: OriginFor<T>,
+	call: Box<<T as Config>::RuntimeCall>,
+) -> DispatchResultWithPostInfo {
+	// This is a public call, so we ensure that the origin is some signed account.
+	let sender = ensure_signed(origin)?;
+	ensure!(Self::key().map_or(false, |k| sender == k), Error::<T>::RequireSudo);
+
+	let res = call.dispatch_bypass_filter(frame_system::RawOrigin::Root.into());
+	Self::deposit_event(Event::Sudid { sudo_result: res.map(|_| ()).map_err(|e| e.error) });
+	// Sudo user does not pay a fee.
+	Ok(Pays::No.into())
+}
+```
+
+Here, Sudo Pallet allows a `Signed` origin to elevate itself to a `Root` origin, if the logic allows.
+
+---
+
+## Example: Collective Pallet
+
+Here you can see the Collective Pallet creating, and dispatching with the `Members` origin we showed previously.
+
+```rust [5-6]
+	fn do_approve_proposal(seats: MemberCount, yes_votes: MemberCount, proposal_hash: T::Hash, proposal: <T as Config<I>>::Proposal) -> (Weight, u32) {
+		Self::deposit_event(Event::Approved { proposal_hash });
+
+		let dispatch_weight = proposal.get_dispatch_info().weight;
+		let origin = RawOrigin::Members(yes_votes, seats).into();
+		let result = proposal.dispatch(origin);
+		Self::deposit_event(Event::Executed { proposal_hash, result: result.map(|_| ()).map_err(|e| e.error) });
+		// default to the dispatch info weight for safety
+		let proposal_weight = get_result_weight(result).unwrap_or(dispatch_weight); // P1
+
+		let proposal_count = Self::remove_proposal(proposal_hash);
+		(proposal_weight, proposal_count)
+	}
+```
+
+---
+
+## Custom Origin Checks
+
+You can then write logic which is only accessible with custom origins by implementing the `EnsureOrigin` trait.
+
+```rust
+/// Some sort of check on the origin is performed by this object.
+pub trait EnsureOrigin<OuterOrigin> { ... }
+```
+
+These need to be configured in the Runtime, where all custom origins for your runtime are known.
+
+---
+
+## Example: Alliance Pallet
+
+Pallet's can allow for various origins to be configured by the Runtime.
+
+```rust
+#[pallet::config]
+pub trait Config<I: 'static = ()>: frame_system::Config {
+	/// Origin for admin-level operations, like setting the Alliance's rules.
+	type AdminOrigin: EnsureOrigin<Self::RuntimeOrigin>;
+	/// Origin that manages entry and forcible discharge from the Alliance.
+	type MembershipManager: EnsureOrigin<Self::RuntimeOrigin>;
+	/// Origin for making announcements and adding/removing unscrupulous items.
+	type AnnouncementOrigin: EnsureOrigin<Self::RuntimeOrigin>;
+	// -- snip --
+}
+```
+
+---
+
+## Example: Alliance Pallet
+
+Pallet calls can then use these custom origins to gate access to the logic.
+
+```rust [5]
+/// Set a new IPFS CID to the alliance rule.
+#[pallet::call_index(5)]
+#[pallet::weight(T::WeightInfo::set_rule())]
+pub fn set_rule(origin: OriginFor<T>, rule: Cid) -> DispatchResult {
+	T::AdminOrigin::ensure_origin(origin)?;
+
+	Rule::<T, I>::put(&rule);
+
+	Self::deposit_event(Event::NewRuleSet { rule });
+	Ok(())
+}
+```
+
+---
+
+## Example: Alliance Pallet
+
+Finally, the Runtime itself is where you configure what those Origins are.
+
+```rust
+impl pallet_alliance::Config for Runtime {
+	type AdminOrigin = EitherOfDiverse<
+		EnsureRoot<AccountId>,
+		EnsureProportionAtLeast<AccountId, AllianceCollective, 1, 1>,
+	>;
+	type MembershipManager = EitherOfDiverse<
+		EnsureRoot<AccountId>,
+		EnsureProportionMoreThan<AccountId, AllianceCollective, 2, 3>,
+	>;
+	type AnnouncementOrigin = EitherOfDiverse<
+		EnsureRoot<AccountId>,
+		EnsureProportionMoreThan<AccountId, AllianceCollective, 1, 3>,
+	>;
+}
+```
+
+As you can see, they can even support multiple different origins!
+
+---
+
+## Fees
+
+Fees are usually handled by some pallet like the Transaction Payments Pallet.
+
+However, if there is no `Signed` origin, you can't really take a fee.
+
+You should assume any transaction which is not from the `Signed` origin is feeless, unless you explicitly write code to handle it.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/6-Protocol_On-Chain/FRAME/4-FRAME_Production/Benchmarking-slides.md b/content/6-Protocol_On-Chain/FRAME/4-FRAME_Production/Benchmarking-slides.md
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+---
+title: FRAME Benchmarking
+description: How to benchmark Pallets in FRAME.
+duration: 2 hours
+---
+
+# FRAME Benchmarking
+
+## Lesson 1
+
+---
+
+## Overview
+
+- Quick Recap of Weights
+- Deep Dive Into Benchmarking
+
+---
+
+## Blockchains are Limited
+
+Blockchain systems are extremely limited environments.
+
+Limited in:
+
+- Execution Time / Block Time
+- Available Storage
+- Available Memory
+- Network Bandwidth
+- etc...
+
+---
+
+## Performance vs Centralization
+
+Nodes are expected to be decentralized and distributed.
+
+Increasing the system requirements can potentially lead to centralization in who can afford to run that hardware, and where such hardware may be available.
+
+---
+
+## Why do we need benchmarking?
+
+Benchmarking ensures that when users interact with our Blockchain, they are not using resources beyond what is available and expected for our network.
+
+---
+
+## What is Weight?
+
+Weight is a general concept used to track consumption of limited blockchain resources.
+
+---
+
+## What is Weight in Substrate?
+
+We currently track just two main limitations:
+
+- Execution Time on "Reference Hardware"
+- Size of Data Required to Create a Merkle Proof
+
+```rust
+pub struct Weight {
+	/// The weight of computational time used based on some reference hardware.
+	ref_time: u64,
+	/// The weight of storage space used by proof of validity.
+	proof_size: u64,
+}
+```
+
+This was already expanded once, and could be expanded in the future.
+
+---
+
+## Weight limits are specific to each blockchain.
+
+- 1 second of compute on different computers allows for different amounts of computation.
+- Weights of your blockchain will evolve over time.
+- Higher hardware requirements will result in a more performant blockchain (i.e. TXs per second), but will limit the kinds of validators that can safely participate in your network.
+- Proof size limitations can be relevant for parachains, but ignored for solo-chains.
+
+---
+
+## What can affect relative Weight?
+
+<pba-cols>
+
+<pba-col>
+
+- Processor
+- Memory
+- Hard Drive
+  - HDD vs. SSD vs. NVME
+- Operating System
+- Drivers
+- Rust Compiler
+
+</pba-col>
+<pba-col>
+
+- Runtime Execution Engine
+  - compiled vs. interpreted
+- Database
+  - RocksDB vs. ParityDB vs. ?
+- Merkle trie / storage format
+- and more!
+
+</pba-col>
+</pba-cols>
+
+---
+
+## Block Import Weight Breakdown
+
+<img style="height: 500px;" src="../../../../assets/img/6-FRAME/benchmark/block-import.svg" />
+
+---
+
+# The Benchmarking Framework
+
+---
+
+## The Benchmarking Plan
+
+<div class="flex-container">
+<div class="left-large">
+
+- Use empirical measurements of the runtime to determine the time and space it takes to execute extrinsics and other runtime logic.
+- Run benchmarks using worst case scenario conditions.
+  - Primary goal is to keep the runtime safe.
+  - Secondary goal is to be as accurate as possible to maximize throughput.
+
+</div>
+<div class="right">
+
+<img style="height: 600px;" src="../../../../assets/img/6-FRAME/benchmark/benchmarking.svg" />
+
+</div>
+</div>
+
+---
+
+## The `#[benchmarks]` Macro
+
+```rust
+#[benchmarks]
+mod benchmarks {
+	use super::*;
+
+	#[benchmark]
+	fn benchmark_name() {
+		/* setup initial state */
+
+		/* execute extrinsic or function */
+		#[extrinsic_call]
+		extrinsic_name();
+
+		/* verify final state */
+		assert!(true)
+	}
+}
+```
+
+---
+
+## Multiple Linear Regression Analysis
+
+<div class="flex-container">
+<div class="left-small">
+
+<img style="height: 600px;" src="../../../../assets/img/6-FRAME/benchmark/linear-regression.svg" />
+
+</div>
+<div class="right">
+
+- We require that no functions in Substrate have superlinear complexity.
+- Ordinary least squared linear regression.
+  - linregress crate
+- Supports multiple linear coefficients.
+  - `Y = Ax + By + Cz + k`
+- For constant time functions, we simply use the median value.
+
+</div>
+</div>
+
+---
+
+## The `benchmark` CLI
+
+Compile your node with `--features runtime-benchmarks`.
+
+```sh
+➜  ~ substrate benchmark --help
+Sub-commands concerned with benchmarking.
+The pallet benchmarking moved to the `pallet` sub-command
+
+Usage: polkadot benchmark <COMMAND>
+
+Commands:
+  pallet     Benchmark the extrinsic weight of FRAME Pallets
+  storage    Benchmark the storage speed of a chain snapshot
+  overhead   Benchmark the execution overhead per-block and per-extrinsic
+  block      Benchmark the execution time of historic blocks
+  machine    Command to benchmark the hardware
+  extrinsic  Benchmark the execution time of different extrinsics
+  help       Print this message or the help of the given subcommand(s)
+
+Options:
+  -h, --help     Print help information
+  -V, --version  Print version information
+```
+
+---
+
+## `pallet` Subcommand
+
+- Benchmark the weight of functions within pallets.
+  - Any arbitrary code can be benchmarked.
+- Outputs Autogenerated Weight files.
+
+```rust
+pub trait WeightInfo {
+   fn transfer() -> Weight;
+   fn transfer_keep_alive() -> Weight;
+   fn set_balance_creating() -> Weight;
+   fn set_balance_killing() -> Weight;
+   fn force_transfer() -> Weight;
+}
+```
+
+---
+
+# Deep Dive
+
+So let’s walk through the steps of a benchmark!
+
+Reference: `frame/benchmarking/src/lib.rs`
+
+```rust
+-> fn run_benchmark(...)
+```
+
+---
+
+## The Benchmarking Process
+
+For each component and repeat:
+
+1. Select component to benchmark
+1. Generate range of values to test (steps)
+1. Whitelist known DB keys
+1. Setup benchmarking state
+1. Commit state to the DB, clearing cache
+1. Get system time (start)
+1. Execute extrinsic / benchmark function
+1. Get system time (end)
+1. Count DB reads and writes
+1. Record Data
+
+---
+
+## Benchmarking Components
+
+- Imagine a function with 3 components
+  - let x in 1..2;
+  - let y in 0..5;
+  - let z in 0..10;
+- We set number of steps to 3.
+- Vary one component at a time, select high value for the others.
+
+|   | Δx | Δy | Δy | Δz | Δz | max |
+| - | -- | -- | -- | -- | -- | --- |
+| x | 1  | 2  | 2  | 2  | 2  | 2   |
+| y | 5  | 0  | 2  | 5  | 5  | 5   |
+| z | 10 | 10 | 10 | 0  | 5  | 10  |
+
+---
+
+## Benchmarks Evaluated Over Components
+
+<img style="height: 600px;" src="../../../../assets/img/6-FRAME/benchmark/components.svg" />
+
+---
+
+## Whitelisted DB Keys
+
+```rust [3]
+/// The current block number being processed. Set by `execute_block`.
+#[pallet::storage]
+#[pallet::whitelist_storage]
+#[pallet::getter(fn block_number)]
+pub(super) type Number<T: Config> = StorageValue<_, BlockNumberFor<T>, ValueQuery>;
+```
+
+- Some keys are accessed every block:
+  - Block Number
+  - Events
+  - Total Issuance
+  - etc…
+- We don’t want to count these reads and writes in our benchmarking results.
+- Applied to all benchmarks being run.
+- This includes a “whitelisted account” provided by FRAME.
+
+---
+
+## Example Benchmark
+
+The Identity Pallet
+
+<img style="height: 500px;" src="../../../../assets/img/6-FRAME/benchmark/identity-icon.svg" />
+
+---
+
+## Identity Pallet
+
+- Identity can have variable amount of information
+  - Name
+  - Email
+  - Twitter
+  - etc…
+- Identity can be judged by a variable amount of registrars.
+- Identity can have a two-way link to “sub-identities”
+  - Other accounts that inherit the identity status of the “super-identity”
+
+---
+
+## Extrinsic: Kill Identity
+
+```rust
+pub fn kill_identity(
+	origin: OriginFor<T>,
+	target: AccountIdLookupOf<T>,
+) -> DispatchResultWithPostInfo {
+	T::ForceOrigin::ensure_origin(origin)?;
+
+	// Figure out who we're meant to be clearing.
+	let target = T::Lookup::lookup(target)?;
+
+	// Grab their deposit (and check that they have one).
+	let (subs_deposit, sub_ids) = <SubsOf<T>>::take(&target);
+	let id = <IdentityOf<T>>::take(&target).ok_or(Error::<T>::NotNamed)?;
+	let deposit = id.total_deposit() + subs_deposit;
+	for sub in sub_ids.iter() { <SuperOf<T>>::remove(sub); }
+
+	// Slash their deposit from them.
+	T::Slashed::on_unbalanced(T::Currency::slash_reserved(&target, deposit).0);
+	Self::deposit_event(Event::IdentityKilled { who: target, deposit });
+	Ok(())
+}
+```
+
+---
+
+## Handling Configurations
+
+- `kill_identity` will only execute if the `ForceOrigin` is calling.
+
+```rust
+T::ForceOrigin::ensure_origin(origin)?;
+```
+
+- However, this is configurable by the pallet developer.
+- Our benchmark needs to always work independent of the configuration.
+- We added a special function behind a feature flag:
+
+```rust
+/// Returns an outer origin capable of passing `try_origin` check.
+///
+/// ** Should be used for benchmarking only!!! **
+#[cfg(feature = "runtime-benchmarks")]
+fn successful_origin() -> OuterOrigin;
+```
+
+---
+
+## External Logic / Hooks
+
+```rust
+// Figure out who we're meant to be clearing.
+let target = T::Lookup::lookup(target)?;
+```
+
+- In general, hooks like these are configurable in the runtime.
+- Each blockchain will have their own logic, and thus their own weight.
+- We run benchmarks against the real runtime, so we get the real results.
+- **IMPORTANT!** You need to be careful that the limitations of these hooks are well understood by the pallet developer and users of your pallet, otherwise, your benchmark will not be accurate.
+
+---
+
+## External Logic / Hooks
+
+```rust
+T::Slashed::on_unbalanced(T::Currency::slash_reserved(&target, deposit).0);
+```
+
+Here you adjust the balance.
+
+- What happens with slashed funds is configurable too!
+
+---
+
+## Deterministic Storage Reads / Writes
+
+```rust
+// Grab their deposit (and check that they have one).
+let (subs_deposit, sub_ids) = <SubsOf<T>>::take(&target);
+let id = <IdentityOf<T>>::take(&target).ok_or(Error::<T>::NotNamed)?;
+```
+
+- 2 storage reads and writes.
+- The size of these storage items will depends on:
+  - Number of Registrars
+  - Number of Additional Fields
+
+---
+
+## Variable Storage Reads / Writes
+
+```rust
+for sub in sub_ids.iter() { <SuperOf<T>>::remove(sub); }
+```
+
+- There will be more or fewer writes depending on the number of subs.
+
+---
+
+## Whitelisted Storage
+
+```rust
+Self::deposit_event(Event::IdentityKilled { who: target, deposit });
+```
+
+- We whitelist changes to the Events storage item, so generally this is “free” beyond computation and in-memory DB weight.
+
+---
+
+## Preparing to Write Your Benchmark
+
+- 3 Components
+
+  - `R` - number of registrars
+  - `S` - number of sub-accounts
+  - `X` - number of additional fields
+
+- Need to:
+  - Set up account with funds.
+  - Register an identity with additional fields.
+  - Set up worst case scenario for registrars and sub-accounts.
+  - Take into account `ForceOrigin` to make the call.
+
+---
+
+## Kill Identity Benchmark
+
+```rust
+#[benchmark]
+fn kill_identity(
+	r: Linear<1, T::MaxRegistrars::get()>,
+	s: Linear<0, T::MaxSubAccounts::get()>,
+	x: Linear<0, T::MaxAdditionalFields::get()>,
+) -> Result<(), BenchmarkError> {
+	add_registrars::<T>(r)?;
+
+	let target: T::AccountId = account("target", 0, SEED);
+	let target_origin: <T as frame_system::Config>::RuntimeOrigin = RawOrigin::Signed(target.clone()).into();
+	let target_lookup = T::Lookup::unlookup(target.clone());
+	let _ = T::Currency::make_free_balance_be(&target, BalanceOf::<T>::max_value());
+
+	let info = create_identity_info::<T>(x);
+	Identity::<T>::set_identity(target_origin.clone(), Box::new(info.clone()))?;
+	let _ = add_sub_accounts::<T>(&target, s)?;
+
+	// User requests judgement from all the registrars, and they approve
+	for i in 0..r {
+		let registrar: T::AccountId = account("registrar", i, SEED);
+		let balance_to_use =  T::Currency::minimum_balance() * 10u32.into();
+		let _ = T::Currency::make_free_balance_be(&registrar, balance_to_use);
+
+		Identity::<T>::request_judgement(target_origin.clone(), i, 10u32.into())?;
+		Identity::<T>::provide_judgement( RawOrigin::Signed(registrar).into(), i, target_lookup.clone(), Judgement::Reasonable, T::Hashing::hash_of(&info),
+		)?;
+	}
+	ensure!(IdentityOf::<T>::contains_key(&target), "Identity not set");
+	let origin = T::ForceOrigin::successful_origin();
+
+	#[extrinsic_call]
+	kill_identity<T::RuntimeOrigin>(origin, target_lookup)
+
+	ensure!(!IdentityOf::<T>::contains_key(&target), "Identity not removed");
+	Ok(())
+}
+```
+
+---
+
+## Benchmarking Components
+
+```rust
+fn kill_identity(
+	r: Linear<1, T::MaxRegistrars::get()>,
+	s: Linear<0, T::MaxSubAccounts::get()>,
+	x: Linear<0, T::MaxAdditionalFields::get()>,
+) -> Result<(), BenchmarkError> { ... }
+```
+
+- Our components.
+  - R = Number of Registrars
+  - S = Number of Sub-Accounts
+  - X = Number of Additional Fields on the Identity.
+- Note all of these have configurable, known at compile time maxima.
+  - Part of the pallet configuration trait.
+  - Runtime logic should enforce these limits.
+
+---
+
+## Set Up Logic
+
+```rust
+add_registrars::<T>(r)?;
+
+let target: T::AccountId = account("target", 0, SEED);
+let target_origin: <T as frame_system::Config>::RuntimeOrigin = RawOrigin::Signed(target.clone()).into();
+let target_lookup = T::Lookup::unlookup(target.clone());
+let _ = T::Currency::make_free_balance_be(&target, BalanceOf::<T>::max_value());
+```
+
+- Adds registrars to the runtime storage.
+- Set up an account with the appropriate funds.
+- Note this is just like writing runtime tests.
+
+---
+
+## Reusable Setup Functions
+
+```rust
+let info = create_identity_info::<T>(x);
+Identity::<T>::set_identity(target_origin.clone(), Box::new(info.clone()))?;
+let _ = add_sub_accounts::<T>(&target, s)?;
+```
+
+- Using some custom functions defined in the benchmarking file:
+- Give that account an Identity with x additional fields.
+- Give that Identity `s` sub-accounts.
+
+---
+
+## Set Up Worst Case Scenario
+
+```rust
+// User requests judgement from all the registrars, and they approve
+for i in 0..r {
+	let registrar: T::AccountId = account("registrar", i, SEED);
+	let balance_to_use =  T::Currency::minimum_balance() * 10u32.into();
+	let _ = T::Currency::make_free_balance_be(&registrar, balance_to_use);
+
+	Identity::<T>::request_judgement(target_origin.clone(), i, 10u32.into())?;
+	Identity::<T>::provide_judgement( RawOrigin::Signed(registrar).into(), i, target_lookup.clone(), Judgement::Reasonable, T::Hashing::hash_of(&info),
+	)?;
+}
+```
+
+- Add r registrars.
+- Have all of them give a judgement to this identity.
+
+---
+
+## Execute and Verify the Benchmark:
+
+```rust
+ensure!(IdentityOf::<T>::contains_key(&target), "Identity not set");
+let origin = T::ForceOrigin::successful_origin();
+
+#[extrinsic_call]
+kill_identity<T::RuntimeOrigin>(origin, target_lookup)
+
+ensure!(!IdentityOf::<T>::contains_key(&target), "Identity not removed");
+Ok(())
+```
+
+- First ensure statement verifies the “before” state is as we expect.
+- We need to use our custom origin.
+- Verify block ensures our “final” state is as we expect.
+
+---
+
+## Executing the Benchmark
+
+Build the runtime.
+
+```sh
+cargo build -p my-runtime --release --features runtime-benchmarks
+```
+
+Run the omni-bencher with the built runtime.
+
+```sh
+frame-omni-bencher v1 benchmark pallet
+	--runtime runtime.wasm \       # Specify runtime wasm path
+	--pallet "pallet_identity" \   # Specify pallet to benchmark
+	--extrinsic ""                 # Specify extrinsics to benchmark
+	--output "identity_weights.rs" # Output results into a Rust file
+	--header=./HEADER-APACHE2 \    # Custom header file to include with template
+	--template=./.maintain/frame-weight-template.hbs # Handlebar template
+```
+
+Notes:
+`--extrinsic ""` runs the benchmarks for all extrinsics in the pallet.
+
+---
+
+# Looking at Raw Benchmarking Data
+
+---
+
+## Results: Extrinsic Time vs. # of Registrars
+
+<img style="height: 500px;" src="../../../../assets/img/6-FRAME/benchmark/identity-raw-registrars.png" />
+
+Notes:
+
+Source of graph: https://www.shawntabrizi.com/substrate-graph-benchmarks/old/
+
+---
+
+## Results: Extrinsic Time vs. # of Sub-Accounts
+
+<img style="height: 500px;" src="../../../../assets/img/6-FRAME/benchmark/identity-raw-sub.png" />
+
+Notes:
+
+Source of graph: https://www.shawntabrizi.com/substrate-graph-benchmarks/old/
+
+---
+
+## Results: Extrinsic Time vs. Additional Fields
+
+<img style="height: 500px;" src="../../../../assets/img/6-FRAME/benchmark/identity-raw-fields.png" />
+
+Notes:
+
+Source of graph: https://www.shawntabrizi.com/substrate-graph-benchmarks/old/
+
+---
+
+## Result: DB Operations vs. Sub Accounts
+
+<img style="height: 500px;" src="../../../../assets/img/6-FRAME/benchmark/identity-db-sub.png" />
+
+Notes:
+
+Source of graph: https://www.shawntabrizi.com/substrate-graph-benchmarks/old/
+
+---
+
+## Final Weight
+
+```rust
+// Storage: Identity SubsOf (r:1 w:1)
+// Storage: Identity IdentityOf (r:1 w:1)
+// Storage: System Account (r:1 w:1)
+// Storage: Identity SuperOf (r:0 w:100)
+/// The range of component `r` is `[1, 20]`.
+/// The range of component `s` is `[0, 100]`.
+/// The range of component `x` is `[0, 100]`.
+fn kill_identity(r: u32, s: u32, x: u32, ) -> Weight {
+	// Minimum execution time: 68_794 nanoseconds.
+	Weight::from_parts(6_000_000, 1554)
+		// Standard Error: 4_808
+		.saturating_add(Weight::from_parts(153_462, 0).saturating_mul(r as u64))
+		// Standard Error: 939
+		.saturating_add(Weight::from_parts(1_084_612, 0).saturating_mul(s as u64))
+		// Standard Error: 939
+		.saturating_add(Weight::from_parts(170_112, 0).saturating_mul(x as u64))
+		.saturating_add(T::DbWeight::get().reads(3 as u64))
+		.saturating_add(T::DbWeight::get().writes(3 as u64))
+		.saturating_add(T::DbWeight::get().writes((1 as u64).saturating_mul(s as u64)))
+}
+```
+
+---
+
+## WeightInfo Generation
+
+```rust
+/// Weight functions needed for pallet_identity.
+pub trait WeightInfo {
+	fn add_registrar(r: u32, ) -> Weight;
+	fn set_identity(r: u32, x: u32, ) -> Weight;
+	fn set_subs_new(s: u32, ) -> Weight;
+	fn set_subs_old(p: u32, ) -> Weight;
+	fn clear_identity(r: u32, s: u32, x: u32, ) -> Weight;
+	fn request_judgement(r: u32, x: u32, ) -> Weight;
+	fn cancel_request(r: u32, x: u32, ) -> Weight;
+	fn set_fee(r: u32, ) -> Weight;
+	fn set_account_id(r: u32, ) -> Weight;
+	fn set_fields(r: u32, ) -> Weight;
+	fn provide_judgement(r: u32, x: u32, ) -> Weight;
+	fn kill_identity(r: u32, s: u32, x: u32, ) -> Weight;
+	fn add_sub(s: u32, ) -> Weight;
+	fn rename_sub(s: u32, ) -> Weight;
+	fn remove_sub(s: u32, ) -> Weight;
+	fn quit_sub(s: u32, ) -> Weight;
+}
+```
+
+---
+
+## WeightInfo Integration
+
+```rust
+#[pallet::weight(T::WeightInfo::kill_identity(
+	T::MaxRegistrars::get(), // R
+	T::MaxSubAccounts::get(), // S
+	T::MaxAdditionalFields::get(), // X
+))]
+pub fn kill_identity(
+	origin: OriginFor<T>,
+	target: AccountIdLookupOf<T>,
+) -> DispatchResultWithPostInfo {
+
+	// -- snip --
+
+	Ok(Some(T::WeightInfo::kill_identity(
+		id.judgements.len() as u32,      // R
+		sub_ids.len() as u32,            // S
+		id.info.additional.len() as u32, // X
+	))
+	.into())
+}
+```
+
+---
+
+## Initial Weight
+
+```rust
+#[pallet::weight(T::WeightInfo::kill_identity(
+	T::MaxRegistrars::get(), // R
+	T::MaxSubAccounts::get(), // S
+	T::MaxAdditionalFields::get(), // X
+))]
+```
+
+- Use the WeightInfo function as the weight definition for your function.
+- Note that we assume absolute worst case scenario to begin since we cannot know these specific values until we query storage.
+
+---
+
+## Final Weight (Refund)
+
+```rust
+pub fn kill_identity(...) -> DispatchResultWithPostInfo { ... }
+```
+
+```rust
+Ok(Some(T::WeightInfo::kill_identity(
+	id.judgements.len() as u32,      // R
+	sub_ids.len() as u32,            // S
+	id.info.additional.len() as u32, // X
+))
+.into())
+```
+
+- Then we return the actual weight used at the end!
+- We use the same WeightInfo formula, but using the values that we queried from storage as part of executing the extrinsic.
+- This only allows you to **decrease** the final weight. Nothing will happen if you return a bigger weight than the initial weight.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
+
+In another presentation we will cover some of the things we learned while benchmarking, and best practices.
+
+---
+
+# Benchmarking Exercise
+
+---
+
+# FRAME Benchmarking
+
+## Lesson 2
+
+---
+
+## Overview
+
+- Databases
+- Our Learnings Throughout Development
+- Best Practices and Common Patterns
+
+---
+
+# Databases
+
+---
+
+### RocksDB
+
+A Persistent Key-Value Store for Flash and RAM Storage.
+
+- Keys and values are arbitrary byte arrays.
+- Fast for a general database.
+
+See http://rocksdb.org/.
+
+Big project, can be very tricky to configure properly.
+
+Notes:
+
+(also a big part of substrate compilation time).
+
+---
+
+### ParityDB
+
+An Embedded Persistent Key-Value Store Optimized for Blockchain Applications.
+
+- Keys and values are arbitrary byte arrays.
+- Designed for efficiently storing Patricia-Merkle trie nodes.
+  - Mostly Fixed Size Keys.
+  - Mostly Small Values.
+  - Uniform Distribution.
+- Optimized for read performance.
+
+Notes:
+
+See: https://github.com/paritytech/parity-db/issues/82
+
+Main point is that paritydb suit the triedb model.
+Indeed triedb store encoded key by their hash.
+So we don't need rocksdb indexing, no need to order data.
+Parity db index its content by hash of key (by default), which makes access faster (hitting entry of two file generally instead of possibly multiple btree indexing node).
+Iteration on state value is done over the trie structure: having a KVDB with iteration support isn't needed.
+
+Both rocksdb and paritydb uses "Transactions" as "writes done in batches".
+We typically run a transaction per block (all in memory before), things are fast (that's probably what you meant).
+In blockchains, writes are typically performed in large batches, when the new block is imported and must be done atomically.
+See: https://github.com/paritytech/parity-db
+
+Concurrency does not matter in this, paritydb lock access to single writer (no concurrency).
+Similarly code strive at being simple and avoid redundant feature: no cache in parity db (there is plenty in substrate).
+
+'Quick commit' : all changes are stored in memory on commit , and actual writing in the WriteAheadLog is done in an asynchronous way.
+
+TODO merge with content from https://github.com/paritytech/parity-db/issues/82
+
+---
+
+### ParityDB: Probing Hash Table
+
+ParityDB is implemented as a probing hash table.
+
+- As opposed to a log-structured merge (LSM) tree.
+  - Used in Apache AsterixDB, Bigtable, HBase, LevelDB, Apache Accumulo, SQLite4, Tarantool, RocksDB, WiredTiger, Apache Cassandra, InfluxDB, ScyllaDB, etc...
+- Because we do not require key ordering or iterations for trie operations.
+- This means read performance is constant time, versus $O(\log{n})$.
+
+---
+
+### ParityDB: Fixed Size Value Tables
+
+- Each column stores data in a set of 256 value tables, with 255 tables containing entries of certain size range up to 32 KB limit.
+
+<div class="text-smaller">
+
+```rust
+const SIZES: [u16; SIZE_TIERS - 1] = [
+	32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 50, 51, 52, 54, 55, 57, 58, 60,
+	62, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 88, 90, 93, 95, 98, 101, 103, 106, 109,
+	112, 115, 119, 122, 125, 129, 132, 136, 140, 144, 148, 152, 156, 160, 165, 169, 174, 179, 183,
+	189, 194, 199, 205, 210, 216, 222, 228, 235, 241, 248, 255, 262, 269, 276, 284, 292, 300, 308,
+	317, 325, 334, 344, 353, 363, 373, 383, 394, 405, 416, 428, 439, 452, 464, 477, 490, 504, 518,
+	532, 547, 562, 577, 593, 610, 627, 644, 662, 680, 699, 718, 738, 758, 779, 801, 823, 846, 869,
+	893, 918, 943, 969, 996, 1024, 1052, 1081, 1111, 1142, 1174, 1206, 1239, 1274, 1309, 1345,
+	1382, 1421, 1460, 1500, 1542, 1584, 1628, 1673, 1720, 1767, 1816, 1866, 1918, 1971, 2025, 2082,
+	2139, 2198, 2259, 2322, 2386, 2452, 2520, 2589, 2661, 2735, 2810, 2888, 2968, 3050, 3134, 3221,
+	3310, 3402, 3496, 3593, 3692, 3794, 3899, 4007, 4118, 4232, 4349, 4469, 4593, 4720, 4850, 4984,
+	5122, 5264, 5410, 5559, 5713, 5871, 6034, 6200, 6372, 6548, 6729, 6916, 7107, 7303, 7506, 7713,
+	7927, 8146, 8371, 8603, 8841, 9085, 9337, 9595, 9860, 10133, 10413, 10702, 10998, 11302, 11614,
+	11936, 12266, 12605, 12954, 13312, 13681, 14059, 14448, 14848, 15258, 15681, 16114, 16560,
+	17018, 17489, 17973, 18470, 18981, 19506, 20046, 20600, 21170, 21756, 22358, 22976, 23612,
+	24265, 24936, 25626, 26335, 27064, 27812, 28582, 29372, 30185, 31020, 31878, 32760,
+];
+```
+
+</div>
+
+- The last 256th value table size stores entries that are over 32 KB split into multiple parts.
+
+---
+
+### ParityDB: Fixed Size Value Tables
+
+- More than 99% of trie nodes are less than 32kb in size.
+- Small values only require 2 reads: One index lookup and one value table lookup.
+- Values over 32kb may require multiple value table reads, but these are rare.
+- Helps minimize unused disk space.
+- For example, if you store a 670 byte value, it won't fit into 662 bucket, but will into 680 bucket, wasting only 10 bytes of space.
+
+Notes:
+
+That fact that most values are small allows us to address each value by its index and have a simple mechanism for reusing the space of deleted values without fragmentation and periodic garbage collection.
+
+---
+
+### ParityDB: Asynchronous Writes
+
+- Parity DB API exposes synchronous functions, but underlying IO is async.
+- The `commit` function adds the database transaction to the write queue, updates the commit overlay, and returns as quickly as possible.
+- The actual writing happens in the background.
+- The commit overlay allows the block import pipeline to start executing the next block while the database is still writing changes for the previous block.
+
+---
+
+### Practical Benchmarks and Considerations
+
+Let's now step away from concepts and talk about cold hard data.
+
+---
+
+### Common Runtime Data Size and Performance
+
+<br/>
+
+<div class="flex-container">
+<div class="left">
+
+- Most runtime values are 80 bytes, which are user accounts.
+- Of course, this would depend on your chain's logic.
+
+</div>
+<div class="right" style="padding-left: 10px;">
+
+<div class="r-stack">
+	<img style="height: 500px;" src="../../../../assets/img/6-FRAME/benchmark/polkadot-size-histogram.png" />
+	<img style="height: 500px;" class="fragment" src="../../../../assets/img/6-FRAME/benchmark/polkadot-size-histogram-alpha.png" />
+</div>
+</div>
+
+Notes:
+
+Impact of keys size is slightly bigger encoded node.
+Since eth scaling issue, we usually focus on state nodes.
+Other content access can be interesting to audit enhance though (with paritydb).
+
+See more details here:
+
+https://substrate.stackexchange.com/questions/525/how-expensive-is-it-to-access-storage-items/526#526
+
+---
+
+### RocksDB vs ParityDB Performance
+
+At 32 KB, performance decreases for each additional 4 KB.
+
+<img style="height: 500px" src="../../../../assets/img/6-FRAME/benchmark/paritydb-vs-rocksdb-read.png" />
+
+---
+
+### RocksDB Inconsistency
+
+<img style="width: 1200px;" src="../../../../assets/img/6-FRAME/benchmark/rocksdb-hiccups.png" />
+
+When doing benchmarking, we saw some really bizarre, but reproducible problems with RocksDB.
+
+---
+
+## Things we tried
+
+## Things we learned
+
+---
+
+## Isolating DB Benchmarks (PR #5586)
+
+<pba-cols>
+<pba-col>
+
+### We tried…
+
+To benchmark the entire extrinsic, including the weight of DB operations directly in the benchmark. We wanted to:
+
+- Populate the DB to be “full”
+- Flush the DB cache
+- Run the benchmark
+
+</pba-col>
+<pba-col>
+
+### We learned…
+
+RocksDB was too inconsistent to give reproducible results, and really slow to populate.
+So we use an in-memory DB for benchmarking.
+
+<img style="height: 200px;" src="../../../../assets/img/6-FRAME/benchmark/rocksdb-hiccups.png" />
+
+</pba-col>
+</pba-cols>
+
+---
+
+## Fixing Nonlinear Events (PR #5795)
+
+<pba-cols>
+<pba-col>
+
+### We tried…
+
+Executing a whole block, increasing the number of txs in each block. We expected to get linear growth of execution time, but in fact it was superlinear!
+
+<img style="height: 250px;" src="../../../../assets/img/6-FRAME/benchmark/nonlinear-events.png" />
+
+</pba-col>
+<pba-col>
+
+### We learned…
+
+Each time we appended a new event, we were passing the growing event object over the Wasm barrier.
+
+We updated the append api so only new data is pushed.
+
+<img style="height: 200px;" src="../../../../assets/img/6-FRAME/benchmark/event-fix.png" />
+
+</pba-col>
+</pba-cols>
+
+---
+
+## Enabling Weight Refunds (PR #5584)
+
+<pba-cols>
+<pba-col>
+
+### We tried…
+
+To assign weights to all extrinsics for the absolute worst case scenario in order to be safe.
+
+In many cases, we cannot know accurately what the weight of the extrinsic will be without reading storage… and this is not allowed!
+
+</pba-col>
+<pba-col>
+
+### We learned…
+
+That many extrinsics have a worst case weight much different than their average weight.
+
+So we allow extrinsics to return the actual weight consumed and refund that weight and any weight fees.
+
+</pba-col>
+</pba-cols>
+
+---
+
+## Customizable Weight Info (PR #6575)
+
+<pba-cols>
+<pba-col>
+
+### We tried…
+
+To record weight information and benchmarking results directly in the pallet.
+
+</pba-col>
+<pba-col>
+
+### We learned…
+
+This was hard to update, not customizable, and not accurate for custom pallet configurations.
+
+</pba-col>
+</pba-cols>
+
+So we moved the weight definition into customizable associated types configured in the runtime trait.
+
+```rust
+#[weight = 45_000_000 + T::DbWeight::get().reads_writes(1,1)]
+```
+
+turned into...
+
+```rust
+#[weight = T::WeightInfo::transfer()]
+```
+
+---
+
+## Inherited Call Weight Syntax (PR #13932)
+
+```rust
+#[pallet::call(weight(<T as Config>::WeightInfo))]
+impl<T: Config> Pallet<T> {
+
+	pub fn create(
+		...
+```
+
+---
+
+## Custom Benchmark Returns / Errors (PR #9517)
+
+```rust
+override_benchmark {
+	let b in 1 .. 1000;
+	let caller = account::<T::AccountId>("caller", 0, 0);
+}: {
+	Err(BenchmarkError::Override(
+		BenchmarkResult {
+			extrinsic_time: 1_234_567_890,
+			reads: 1337,
+			writes: 420,
+			..Default::default()
+		}
+	))?;
+}
+```
+
+---
+
+## Negative Y Intercept Handling (PR #11806)
+
+---
+
+## Multi-Dimensional Weight (Issue #12176)
+
+```rust
+#[derive(
+	Encode, Decode, MaxEncodedLen, TypeInfo, Eq, PartialEq, Copy, Clone, RuntimeDebug, Default,
+)]
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+pub struct Weight {
+	#[codec(compact)]
+	/// The weight of computational time used based on some reference hardware.
+	ref_time: u64,
+	#[codec(compact)]
+	/// The weight of storage space used by proof of validity.
+	proof_size: u64,
+}
+```
+
+---
+
+# Best Practices & Common Patterns
+
+---
+
+## Initial Weight Calculation Must Be Lightweight
+
+- In the TX queue, we need to know the weight to see if it would fit in the block.
+- This weight calculation must be lightweight!
+- No storage reads!
+
+Example:
+
+- Transfer Base: ~50 µs
+- Storage Read: ~25 µs
+
+---
+
+## Set Bounds and Assume the Worst!
+
+- Add a configuration trait that sets an upper bound to some item, and in weights, initially assume this worst case scenario.
+- During the extrinsic, find the actual length/size of the item, and refund the weight to be the actual amount used.
+
+---
+
+## Separate Benchmarks Per Logical Path
+
+- It may not be clear which logical path in a function is the “worst case scenario”.
+- Create a benchmark for each logical path your function could take.
+- Ensure each benchmark is testing the worst case scenario of that path.
+
+---
+
+## Comparison Operators in the Weight Definition
+
+```rust
+#[pallet::weight(
+   T::WeightInfo::path_a()
+   .max(T::WeightInfo::path_b())
+   .max(T::WeightInfo::path_c())
+)]
+```
+
+---
+
+## Keep Extrinsics Simple
+
+- The more complex your extrinsic logic, the harder it will be to accurately weigh.
+- This leads to larger up-front weights, potentially higher tx fees, and less efficient block packing.
+
+---
+
+## Use Multiple Simple Extrinsics
+
+- Take advantage of UI/UX, batch calls, and similar downstream tools to simplify extrinsic logic.
+
+Example:
+
+- Vote and Close Vote (“last vote”) are separate extrinsics.
+
+---
+
+## Minimize Usage of On Finalize
+
+- `on_finalize` is the last thing to happen in a block, and must execute for the block to be successful.
+- Variable weight needs at can lead to overweight blocks.
+
+<img style="height: 200px;" src="../../../../assets/img/6-FRAME/benchmark/on-finalize.svg" />
+
+---
+
+## Transition Logic and Weights to On Initialize
+
+- `on_initialize` happens at the beginning of the block, before extrinsics.
+- The number of extrinsics can be adjusted to support what is available.
+- Weight for `on_finalize` should be wrapped into on_initialize weight or extrinsic weight.
+
+---
+
+## Understand Limitations of Pallet Hooks
+
+- A powerful feature of Substrate is to allow the runtime configuration to implement pallet configuration traits.
+- However, it is easy for this feature to be abused and make benchmarking inaccurate.
+
+---
+
+## Keep Hooks Constant Time
+
+- Example: Balances hook for account creation and account killed.
+- Benchmarking has no idea how to properly set up your state to test for any arbitrary hook.
+- So you must keep hooks constant time, unless specified by the pallet otherwise.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/6-Protocol_On-Chain/FRAME/4-FRAME_Production/Migrations_and_try_runtime-slides.md b/content/6-Protocol_On-Chain/FRAME/4-FRAME_Production/Migrations_and_try_runtime-slides.md
new file mode 100644
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--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/4-FRAME_Production/Migrations_and_try_runtime-slides.md
@@ -0,0 +1,599 @@
+---
+title: Migrations and Try Runtime
+description: Runtime upgrades and how to survive them
+instructors: ["Kian Paimani"]
+teaching-assistants: [".."]
+---
+
+# Migrations and Try Runtime
+
+---
+
+## Runtime upgrades...
+
+### _and how to survive them_
+
+---
+
+### _At the end of this lecture, you will be able to:_
+
+- Justify when runtime migrations are needed.
+- Write a the full a runtime upgrade that includes migrations, end-to-end.
+- Test runtime upgrades before executing on a network using `try-runtime` and `remote-externalities`.
+
+---
+
+## When is a Migration Required?
+
+---v
+
+### When is a Migration Required?
+
+- In a typical runtime upgrade, you typically only replace `:code:`. This is _**Runtime Upgrade**_.
+- If you change the _storage layout_, then this is also a _**Runtime Migration**_.
+
+> Anything that changes **encoding** is a migration!
+
+---v
+
+### When is a Migration Required?
+
+```rust
+#[pallet::storage]
+pub type FooValue = StorageValue<_, Foo>;
+```
+
+```rust
+// old
+pub struct Foo(u32)
+// new
+pub struct Foo(u64)
+```
+
+- A clear migration.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### When is a Migration Required?
+
+```rust
+#[pallet::storage]
+pub type FooValue = StorageValue<_, Foo>;
+```
+
+```rust
+// old
+pub struct Foo(u32)
+// new
+pub struct Foo(i32)
+// or
+pub struct Foo(u16, u16)
+```
+
+- The data still _fits_, but the _interpretations_ is almost certainly different!
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### When is a Migration Required?
+
+```rust
+#[pallet::storage]
+pub type FooValue = StorageValue<_, Foo>;
+```
+
+```rust
+// old
+pub struct Foo { a: u32, b: u32 }
+// new
+pub struct Foo { a: u32, b: u32, c: u32 }
+```
+
+- This is still a migration, because `Foo`'s decoding changed.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### When is a Migration Required?
+
+```rust
+#[pallet::storage]
+pub type FooValue = StorageValue<_, Foo>;
+```
+
+```rust
+// old
+pub struct Foo { a: u32, b: u32 }
+// new
+pub struct Foo { a: u32, b: u32, c: PhantomData<_> }
+```
+
+- If for whatever reason `c` has a type that its encoding is like `()`, then this would work.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### When is a Migration Required?
+
+```rust
+#[pallet::storage]
+pub type FooValue = StorageValue<_, Foo>;
+```
+
+```rust
+// old
+pub enum Foo { A(u32), B(u32) }
+// new
+pub enum Foo { A(u32), B(u32), C(u128) }
+```
+
+- Extending an enum is even more interesting, because if you add the variant to the end, no migration is needed.
+
+<!-- .element: class="fragment" -->
+
+- Assuming that no value is initialized with `C`, this is _not_ a migration.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### When is a Migration Required?
+
+```rust
+#[pallet::storage]
+pub type FooValue = StorageValue<_, Foo>;
+```
+
+```rust
+// old
+pub enum Foo { A(u32), B(u32) }
+// new
+pub enum Foo { A(u32), C(u128), B(u32) }
+```
+
+- You probably _never_ want to do this, but it is a migration.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### 🦀 Rust Recall 🦀
+
+Enums are encoded as the variant enum, followed by the inner data:
+
+- The order matters! Both in `struct` and `enum`.
+- Enums that implement `Encode` cannot have more than 255 variants.
+
+---v
+
+### When is a Migration Required?
+
+```rust
+#[pallet::storage]
+pub type FooValue = StorageValue<_, u32>;
+```
+
+```rust
+// new
+#[pallet::storage]
+pub type BarValue = StorageValue<_, u32>;
+```
+
+- So far everything is changing the _value_ format.<br/>
+
+<div>
+
+- The _key_ changing is also a migration!
+
+</div>
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### When is a Migration Required?
+
+```rust
+#[pallet::storage]
+pub type FooValue = StorageValue<_, u32>;
+```
+
+```rust
+// new
+#[pallet::storage_prefix = "FooValue"]
+#[pallet::storage]
+pub type I_can_NOW_BE_renamEd_hahAA = StorageValue<_, u32>;
+```
+
+- Handy macro if you must rename a storage type.<br/>
+- This does _not_ require a migration.
+
+<!-- .element: class="fragment" -->
+
+---
+
+## Writing Runtime Migrations
+
+- Now that we know how to detect if a storage change is a **migration**, let's see how we write one.
+
+---v
+
+### Writing Runtime Migrations
+
+- Once you upgrade a runtime, the code is expecting the data to be in a new format.
+- Any `on_initialize` or transaction might fail decoding data, and potentially `panic!`
+
+---v
+
+### Writing Runtime Migrations
+
+- We need a **_hook_** that is executed **ONCE** as a part of the new runtime...
+- But before **ANY** other code (on_initialize, any transaction) with the new runtime is migrated.
+
+> This is `OnRuntimeUpgrade`.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Writing Runtime Migrations
+
+- Optional activity: Go into `executive` and `system`, and find out how `OnRuntimeUpgrade` is called only when the code changes!
+
+---
+
+## Pallet Internal Migrations
+
+---v
+
+### Pallet Internal Migrations
+
+One way to write a migration is to write it inside the pallet.
+
+```rust
+#[pallet::hooks]
+impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
+  fn on_runtime_upgrade() -> Weight {
+    migrate_stuff_and_things_here_and_there<T>();
+  }
+}
+```
+
+> This approach is likely to be deprecated and is no longer practiced within Parity either.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Pallet Internal Migrations
+
+```rust [4-8]
+#[pallet::hooks]
+impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
+  fn on_runtime_upgrade() -> Weight {
+    if guard_that_stuff_has_not_been_migrated() {
+      migrate_stuff_and_things_here_and_there<T>();
+    } else {
+      // nada
+    }
+  }
+}
+```
+
+- If you execute `migrate_stuff_and_things_here_and_there` twice as well, then you are doomed 😫.
+
+---v
+
+### Pallet Internal Migrations
+
+**Historically**, something like this was used:
+
+```rust [1-7|9-19]
+#[derive(Encode, Decode, ...)]
+enum StorageVersion {
+  V1, V2, V3, // add a new variant with each version
+}
+
+#[pallet::storage]
+pub type Version = StorageValue<_, StorageVersion>;
+
+#[pallet::hooks]
+impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
+  fn on_runtime_upgrade() -> Weight {
+    if let StorageVersion::V2 = Version::<T>::get() {
+      // do migration
+      Version::<T>::put(StorageVersion::V3);
+    } else {
+      // nada
+    }
+  }
+}
+```
+
+---v
+
+### Pallet Internal Migrations
+
+- FRAME introduced macros to manage migrations: `#[pallet::storage_version]`.
+
+```rust
+// your current storage version.
+const STORAGE_VERSION: StorageVersion = StorageVersion::new(2);
+
+#[pallet::pallet]
+#[pallet::storage_version(STORAGE_VERSION)]
+pub struct Pallet<T>(_);
+```
+
+- This adds two function to the `Pallet<_>` struct:
+
+```rust
+// read the current version, encoded in the code.
+let current = Pallet::<T>::current_storage_version();
+// read the version encoded onchain.
+Pallet::<T>::on_chain_storage_version();
+// synchronize the two.
+current.put::<Pallet<T>>();
+```
+
+---v
+
+### Pallet Internal Migrations
+
+```rust
+#[pallet::hooks]
+impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
+  fn on_runtime_upgrade() -> Weight {
+    let current = Pallet::<T>::current_storage_version();
+    let onchain = Pallet::<T>::on_chain_storage_version();
+
+    if current == 1 && onchain == 0 {
+      // do stuff
+      current.put::<Pallet<T>>();
+    } else {
+    }
+  }
+}
+```
+
+Stores the version as u16 in [`twox(pallet_name) ++ twox(:__STORAGE_VERSION__:)`](https://github.com/paritytech/substrate/blob/6d84315348d1fca9ca59454b9f37411c80e05ab4/frame/support/src/traits/metadata.rs#L155).
+
+---
+
+## External Migrations
+
+---v
+
+### External Migrations
+
+- Managing migrations within a pallet could be hard.
+- Especially for those that want to use external pallets.
+
+Alternative:
+
+- Every runtime can explicitly pass anything that implements `OnRuntimeUpgrade` to `Executive`.
+- End of the day, Executive does:
+  - `<(COnRuntimeUpgrade, AllPalletsWithSystem) as OnRuntimeUpgrade>::on_runtime_upgrade()`.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### External Migrations
+
+- The main point of external migrations is making it more clear:
+- "_What migrations did exactly execute on upgrade to spec_version xxx_"
+
+---v
+
+### External Migrations
+
+- Expose your migration as a standalone function or struct implementing `OnRuntimeUpgrade` inside a `pub mod v<version_number>`.
+
+```rust
+pub mod v3 {
+  pub struct Migration;
+  impl OnRuntimeUpgrade for Migration {
+    fn on_runtime_upgrade() -> Weight {
+      // do stuff
+    }
+  }
+}
+```
+
+---v
+
+### External Migrations
+
+- Guard the code of the migration with `pallet::storage_version`
+- Don't forget to write the new version!
+
+```rust
+pub mod v3 {
+  pub struct Migration;
+  impl OnRuntimeUpgrade for Migration {
+    fn on_runtime_upgrade() -> Weight {
+      let current = Pallet::<T>::current_storage_version();
+      let onchain = Pallet::<T>::on_chain_storage_version();
+
+      if current == 1 && onchain == 0 {
+        // do stuff
+        current.put::<Pallet<T>>();
+      } else {
+      }
+    }
+  }
+}
+```
+
+---v
+
+### External Migrations
+
+- Pass it to the runtime per-release.
+
+```rust
+pub type Executive = Executive<
+  _,
+  _,
+  _,
+  _,
+  _,
+  (v3::Migration, ...)
+>;
+```
+
+---v
+
+### External Migrations
+
+- Discussion: Can the runtime upgrade scripts live forever? Or should they be removed after a few releases?
+
+Notes:
+
+Short answer is, yes, but it is a LOT of work. See here: https://github.com/paritytech/substrate/issues/10308
+
+---
+
+### Utilities in `frame-support`.
+
+- `translate` methods:
+  - For `StorageValue`, `StorageMap`, etc.
+- https://paritytech.github.io/substrate/master/frame_support/storage/migration/index.html
+
+* `#[storage_alias]` macro to create storage types for removed for those that are being removed.
+
+Notes:
+
+Imagine you want to remove a storage map and in a migration you want to iterate it and delete all items. You want to remove this storage item, but it would be handy to be able to access it one last time in the migration code. This is where `#[storage_alias]` comes into play.
+
+---
+
+## Case Studies
+
+1. The day we destroyed all balances in Polkadot.
+1. First ever migration ([`pallet-elections-phragmen`](https://github.com/paritytech/substrate/pull/3948)).
+1. Fairly independent migrations in `pallet-elections-phragmen`.
+
+---
+
+## Testing Upgrades
+
+---v
+
+### Testing Upgrades
+
+- `try-runtime` + `RemoteExternalities` allow you to examine and test a runtime in detail with a high degree of control over the environment.
+
+- It is meant to try things out, and inspired by traits like `TryFrom`, the name `TryRuntime` was chosen.
+
+---v
+
+### Testing Upgrades
+
+Recall:
+
+- The runtime communicates with the client via host functions.
+- Moreover, the client communicates with the runtime via runtime APIs.
+- An environment that provides these host functions is called `Externalities`.
+- One example of which is `TestExternalities`, which you have already seen.
+
+---v
+
+### Testing Upgrades: `remote-externalities`
+
+`remote-externalities` ia a builder pattern that loads the state of a live chain inside `TestExternalities`.
+
+```rust
+let mut ext = Builder::<Block>::new()
+  .mode(Mode::Online(OnlineConfig {
+  	transport: "wss://rpc.polkadot.io",
+  	pallets: vec!["PalletA", "PalletB", "PalletC", "RandomPrefix"],
+  	..Default::default()
+  }))
+  .build()
+  .await
+  .unwrap();
+```
+
+Reading all this data over RPC can be slow!
+
+---v
+
+### Testing Upgrades: `remote-externalities`
+
+`remote-externalities` supports:
+
+- Custom prefixes -> Read a specific pallet
+- Injecting custom keys -> Read `:code:` as well.
+- Injecting custom key-values -> Overwrite `:code:` with `0x00`!
+- Reading child-tree data -> Relevant for crowdloan pallet etc.
+- Caching everything in disk for repeated use.
+
+---v
+
+### Testing Upgrades: `remote-externalities`
+
+`remote-externalities` is in itself a very useful tool to:
+
+- Go back in time and re-running some code.
+- Write unit tests that work on the real-chain's state.
+
+---
+
+## Testing Upgrades: `try-runtime`
+
+- `try-runtime` is a CLI and a set of custom runtime APIs integrated in substrate that allows you to do detailed testing..
+
+- .. including running `OnRuntimeUpgrade` code of a new runtime, on top of a real chain's data.
+
+---v
+
+### Testing Upgrades: `try-runtime`
+
+- A lot can be said about it, the best resource is the [rust-docs](https://paritytech.github.io/substrate/master/try_runtime_cli/index.html).
+
+---v
+
+### Testing Upgrades: `try-runtime`
+
+- You might find some code in your runtime that is featured gated with `#[cfg(feature = "try-runtime")]`. These are always for testing.
+- `pre_upgrade` and `post_upgrade`: Hooks executed before and after `on_runtime_upgrade`.
+- `try_state`: called in various other places, used to check the invariants the pallet.
+
+---v
+
+### Testing Upgrades: `try-runtime`: Live Demo.
+
+- Let's craft a migration on top of poor node-template 😈..
+- and migrate the balance type from u128 to u64.
+
+---
+
+## Additional Resources 😋
+
+> Check speaker notes (click "s" 😉)
+
+Notes:
+
+- additional work on automatic version upgrades: https://github.com/paritytech/substrate/issues/13107
+- a Great talk about try-runtime and further testing of your runtime: https://www.youtube.com/watch?v=a_u3KMG-n-I
+
+#### Reference material:
+
+https://docs.google.com/presentation/d/1hr3fiqOI0JlXw0ISs8uV9BXiDQ5mGOQLc3b_yWK6cxU/edit#slide=id.g43d9ae013f_0_82
+https://www.crowdcast.io/e/substrate-seminar/41
+
+#### Exercise ideas:
+
+- Find the storage version of nomination pools pallet in Kusama.
+- Give them a poorly written migration code, and try and fix it. Things they need to fix:
+  - The migration depends on `<T: Config>`
+  - Does not manage version properly
+  - is hardcoded in the pallet.
+- Re-execute the block at which the runtime went OOM in May 25th 2021 Polkadot.
diff --git a/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/FRAME-Deep-Dive-slides.md b/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/FRAME-Deep-Dive-slides.md
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--- /dev/null
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@@ -0,0 +1,213 @@
+---
+title: FRAME Deep Dive
+description: FRAME, Pallets, System Pallet, Executive, Runtime Amalgamator.
+duration: 1 hour
+---
+
+# FRAME Deep Dive
+
+---v
+
+## Agenda
+
+Recall the following figure:
+
+<img style="height: 600px" src="../../../../assets/img/6-FRAME/frame0.svg" />
+
+Notes:
+
+Without frame, there is the runtime and there is the client, and an API that sits in between.
+
+---v
+
+## Agenda
+
+By the end of this lecture, you will fully understand this figure.
+
+<img style="height: 600px" src="../../../../assets/img/6-FRAME/frame1.svg" />
+
+---
+
+## Expanding A Pallet
+
+- Grab a simple pallet code, and expand it.
+
+- `Pallet` implements the transactions as public functions.
+- `Pallet` implements `Hooks`, and some equivalents like `OnInitialize`.
+- `enum Call` that has in itself is just an encoding of the transaction's data
+
+- and implements `UnfilteredDispatchable` (which just forward the call back to `Pallet`)
+
+---v
+
+### Expanding A Pallet
+
+- Make sure you understand why these 3 are the same!
+
+```rust
+let origin = ..;
+
+// function call
+Pallet::<T>::set_value(origin, 10);
+
+// dispatch
+Call::<T>::set_value(10).dispatch_bypass_filter(origin);
+
+// fully qualified syntax.
+<Call<T> as UnfilteredDispatch>::dispatch_bypass_filter(Call::<T>::set_value(10), origin);
+```
+
+---
+
+## `construct_runtime!` and Runtime Amalgamator.
+
+- Now, let's look at a minimal runtime amalgamator.
+
+---v
+
+### `construct_runtime!` and Runtime Amalgamator.
+
+- struct `Runtime`
+- implements the `Config` trait of all pallets.
+- implements all of the runtime APIs as functions.
+- `type System`, `type SimplePallet`.
+- `AllPalletsWithSystem` etc.
+  - and recall that all pallets implement things like `Hooks`, `OnInitialize`, and all of these traits are tuple-able.
+- enum `RuntimeCall`
+- enum `RuntimeEvent`, `GenesisConfig`, etc. but we don't have them here.
+
+---
+
+## Executive
+
+- This part is somewhat optional to know in advance, but I want you to re-visit it in a week and then understand it all.
+
+- I present to you, Executive struct:
+
+```rust
+pub struct Executive<
+  System,
+  Block,
+  Context,
+  UnsignedValidator,
+  AllPalletsWithSystem,
+  OnRuntimeUpgrade = (),
+>(..);
+```
+
+---v
+
+#### Expanding The Generic Types.
+
+```rust
+impl<
+    // System config, we know this now.
+    System: frame_system::Config,
+    // The block type.
+    Block: sp_runtime::traits::Block<Header = System::Header, Hash = System::Hash>,
+    // Something that has all the hooks. We don't know anything else about pallets here.
+    AllPalletsWithSystem: OnRuntimeUpgrade
+      + OnInitialize<System::BlockNumber>
+      + OnIdle<System::BlockNumber>
+      + OnFinalize<System::BlockNumber>
+      + OffchainWorker<System::BlockNumber>,
+    COnRuntimeUpgrade: OnRuntimeUpgrade,
+  > Executive<System, Block, Context, UnsignedValidator, AllPalletsWithSystem, COnRuntimeUpgrade>
+where
+  // This is the juicy party, and we have to learn more sp_runtime traits to follow.
+  Block::Extrinsic: Checkable,
+  <Block::Extrinsic as Checkable>::Checked: Applyable
+  <<Block::Extrinsic as Checkable>::Checked as Applyable>::Call: Dispatchable<_>,
+{...}
+```
+
+---v
+
+#### `Block::Extrinsic: Checkable`
+
+- Who implements `Checkable`?
+- That's right, the `generic::UncheckedExtrinsic` that we indeed used as `Block::Extrinsic` in the
+  top level runtime. Recall:
+
+```rust
+type UncheckedExtrinsic = generic::UncheckedExtrinsic<_, _, _, _>;
+type Header = ..
+type Block = generic::Block<Header, UncheckedExtrinsic>;
+type Executive = frame_executive::Executive<_, Block, ...>;
+```
+
+---v
+
+#### What Does `Checkable<_>` Do?
+
+- Signature verification!
+
+```rust
+impl Checkable<_> for UncheckedExtrinsic<_, _, _, _> {
+  // this is the output type.
+  type Checked = CheckedExtrinsic<AccountId, Call, Extra>;
+
+  fn check(self, lookup: &Lookup) -> Result<Self::Checked, TransactionValidityError> {
+    ..
+  }
+}
+```
+
+---v
+
+#### `<Block::Extrinsic as Checkable>::Checked: Applyable`
+
+- `UncheckedExtrinsic::Checked` is `CheckedExtrinsic`.
+- And it surely does implement `Applyable`.
+
+---v
+
+#### What Does `Applyable<_>` Do?
+
+- TLDR: `Ok(self.call.dispatch(maybe_who.into()))`
+
+---v
+
+#### Lastly: `<<Block::Extrinsic as Checkable>::Checked as Applyable>::Call: Dispatchable`
+
+- And guess who implemented `Dispatchable`, which we already looked at!
+- The `enum Call` that we had in our expanded file!
+
+---v
+
+### Circling Back..
+
+So, to recap:
+
+```rust
+struct Runtime;
+
+impl frame_system::Config for Runtime {}
+impl simple_pallet::Config for Runtime {}
+
+enum Call {
+  System(frame_system::Call<Runtime>),
+  SimplePallet(simple_pallet::Call<Runtime>),
+}
+
+impl Dispatchable for Call {
+  fn dispatch(self, origin: _) -> Result<_, _> {
+    match self {
+      Call::System(system_call) => system_call.dispatch(),
+      Call::SimplePallet(simple_pallet_call) => system_pallet_call.dispatch(),
+    }
+  }
+}
+
+struct UncheckedExtrinsic {
+  function: Call,
+  signature: Option<_>,
+}
+
+type Executive = Executive<_, UncheckedExtrinsic, ...>;
+
+//
+let unchecked = UncheckedExtrinsic::new();
+let checked = unchecked.check();
+let _ = checked.apply();
+```
diff --git a/content/frame/extras/slides.md b/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/FRAME-Extras-slides.md
similarity index 100%
rename from content/frame/extras/slides.md
rename to content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/FRAME-Extras-slides.md
diff --git a/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/FRAME-Miscellaneous-slides.md b/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/FRAME-Miscellaneous-slides.md
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+---
+title: Frame Miscellaneous
+description: Signed Extensions and Pallet Tasks.
+---
+
+# Frame Miscellaneous
+
+---
+
+## Pre-Dispatch logic
+
+- How is nonce and tip function implemented in polkadot?
+
+<!-- .element: class="fragment" -->
+
+- How do we add more pre-dispatch logic to our runtime?
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+- See what is signed in the extrinsic.
+- Looked at Signed Extension.
+
+---
+
+## Extending pre-dispatch checks
+
+<img rounded src="../../../../assets//img/5-Substrate/dev-5-x-signed-extensions.svg" />
+
+---
+
+## Signed Extension
+
+- Generic way to **extend** the transaction.
+- Similar to middleware.
+- Tips and Fees (ChargeTransactionPayment).
+- Nonce (CheckNonce).
+
+---
+
+## Grouping Signed Extension
+
+- Is also a signed extension itself!
+
+- You can look at the implementation yourself.. but the TLDR is:
+
+- Main takeaways:
+  - `type AdditionalSigned = (SE1::AdditionalSigned, SE2::AdditionalSigned)`,
+  - all of hooks:
+    - Executes each individually, combines results
+
+Notes:
+
+TODO: how `TransactionValidity` is `combined_with` is super important here, but probably something to cover more in 4.3 and recap here.
+
+---
+
+## Usage In The Runtime
+
+- Each runtime has a bunch of signed extensions. They can be grouped as a tuple
+
+```rust
+pub type SignedExtra = (
+	frame_system::CheckNonZeroSender<Runtime>,
+	frame_system::CheckSpecVersion<Runtime>,
+	frame_system::CheckTxVersion<Runtime>,
+	frame_system::CheckGenesis<Runtime>,
+	pallet_asset_tx_payment::ChargeAssetTxPayment<Runtime>,
+);
+
+type UncheckedExtrinsic = generic::UncheckedExtrinsic<Address, Call, Signature, SignedExtra>;
+```
+
+- Signed extensions might originate from a pallet, but are applied to ALL EXTRINSICS 😮‍💨!
+
+Notes:
+
+We will get to this later as well, but recall that SignedExtensions are not a _FRAME/Pallet_
+concept per se. FRAME just implements them. This also implies that everything regarding signed
+extensions is applied to **all transactions**, throughout the runtime.
+
+---
+
+### `ChargeTransactionPayment`
+
+Charge payments, refund if `Pays::Yes`.
+
+```rust
+type Pre = (
+  // tip
+  BalanceOf<T>,
+  // who paid the fee - this is an option to allow for a Default impl.
+  Self::AccountId,
+  // imbalance resulting from withdrawing the fee
+  <<T as Config>::OnChargeTransaction as OnChargeTransaction<T>>::LiquidityInfo,
+);
+```
+
+<!-- .element: class="fragment" -->
+
+---
+
+## Feeless Signed Extension
+
+- If some condition meets, do not charge any fee.
+- Every pallet/extrinsic needs to define a new Signed Extension.
+
+---
+
+## Feeless Signed Extension
+
+```rust
+#[pallet::feeless_if(|origin: &OriginFor<T>, ticket: &Ticket| -> bool {
+    let account = ensure_signed(origin.clone())?;
+    some_conditions_here(&account, &ticket)
+})]
+```
+
+- [Issue #1725](https://github.com/paritytech/polkadot-sdk/issues/1725)
+
+---
+
+## Admin tasks
+
+- You have accumulating rewards, and user needs to claim it.
+- Voting period is over, user needs to unfreeze to get back their locked tokens.
+
+<br/>
+
+- Standard means of determining what work can be executed via an off-chain worker or script.
+
+## <!-- .element: class="fragment" -->
+
+## Off-chain worker and pallet::Tasks
+
+```rust [0-7|8-17|18-100]
+#[pallet::task]
+pub enum Task<T: Config> {
+    AddNumberIntoTotal {
+        i: u32,
+    }
+}
+
+/// Some running total.
+#[pallet::storage]
+pub(super) type Total<T: Config<I>, I: 'static = ()> =
+StorageValue<_, (u32, u32), ValueQuery>;
+
+/// Numbers to be added into the total.
+#[pallet::storage]
+pub(super) type Numbers<T: Config<I>, I: 'static = ()> =
+StorageMap<_, Twox64Concat, u32, u32, OptionQuery>;
+
+#[pallet::tasks_experimental]
+impl<T: Config<I>, I: 'static> Pallet<T, I> {
+	/// Add a pair of numbers into the totals and remove them.
+	#[pallet::task_list(Numbers::<T, I>::iter_keys())]
+	#[pallet::task_condition(|i| Numbers::<T, I>::contains_key(i))]
+	#[pallet::task_index(0)]
+	pub fn add_number_into_total(i: u32) -> DispatchResult {
+		let v = Numbers::<T, I>::take(i).ok_or(Error::<T, I>::NotFound)?;
+		Total::<T, I>::mutate(|(total_keys, total_values)| {
+			*total_keys += i;
+			*total_values += v;
+		});
+		Ok(())
+	}
+}
+```
+
+Notes:
+PR: https://github.com/paritytech/polkadot-sdk/pull/1343
diff --git a/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Outer_Enum-slides.md b/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Outer_Enum-slides.md
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+---
+title: Outer Enum
+description: FRAME Outer Enum Web3 Engineers.
+duration: 1 hour
+---
+
+# Outer Enum
+
+([Reference in `polkadot-sdk-docs`](https://paritytech.github.io/polkadot-sdk/master/polkadot_sdk_docs/reference_docs/frame_runtime_types/index.html#composite-enums))
+
+---
+
+## Outer Enum
+
+In this presentation, you will learn about a common pattern used throughout FRAME, which abstracts many separate types into a single unified type that is used by the Runtime.
+
+This is also known as "aggregate" types.
+
+---
+
+## Enums in FRAME
+
+There are 4 main Enums which you will encounter throughout your FRAME development:
+
+- The Call Enum
+- The Event Enum
+- The Error Enum
+- The Origin Enum
+
+All of these enums have some representation within individual pallets, but also the final FRAME runtime you develop.
+
+---
+
+### Breaking It Down (Without Substrate)
+
+```rust [0|10-30|32-52|54-80|82-97|99|102-107|109-114|116-140]
+#![allow(non_camel_case_types)]
+#![allow(dead_code)]
+
+use parity_scale_codec::Encode;
+
+pub type AccountId = u16;
+pub type Balance = u32;
+pub type Hash = [u8; 32];
+
+mod balances {
+	use crate::*;
+
+	#[derive(Encode)]
+	pub enum Call {
+		transfer { to: AccountId, amount: Balance },
+		transfer_all { to: AccountId },
+	}
+
+	#[derive(Encode)]
+	pub enum Error {
+		InsufficientBalance,
+		ExistentialDeposit,
+		KeepAlive,
+	}
+
+	#[derive(Encode)]
+	pub enum Event {
+		Transfer { from: AccountId, to: AccountId, amount: Balance },
+	}
+}
+
+mod democracy {
+	use crate::*;
+
+	#[derive(Encode)]
+	pub enum Call {
+		propose { proposal_hash: Hash },
+		vote { proposal_id: u32, aye: bool },
+	}
+
+	#[derive(Encode)]
+	pub enum Error {
+		DuplicateProposal,
+	}
+
+	#[derive(Encode)]
+	pub enum Event {
+		Proposed { proposal_index: Hash },
+		Passed { proposal_index: Hash },
+		NotPassed { proposal_index: Hash },
+	}
+}
+
+mod staking {
+	use crate::*;
+
+	#[derive(Encode)]
+	pub enum Call {
+		unstake,
+		stake { nominate: Vec<AccountId>, amount: Balance },
+	}
+
+	#[derive(Encode)]
+	pub enum Error {
+		TooManyTargets,
+		EmptyTargets,
+		AlreadyBonded,
+	}
+
+	impl Into<DispatchError> for Error {
+		fn into(self) -> DispatchError {
+			DispatchError::Module(
+				ModuleError {
+					pallet: runtime::Runtime::Staking as u8,
+					error: self as u8,
+				}
+			)
+		}
+	}
+}
+
+// Similar to `sp-runtime`
+mod runtime_primitives {
+	use crate::*;
+
+	#[derive(Encode)]
+	pub struct ModuleError {
+		pub pallet: u8,
+		pub error: u8,
+	}
+
+	#[derive(Encode)]
+	pub enum DispatchError {
+		BadOrigin,
+		Module(ModuleError),
+	}
+}
+
+mod runtime {
+	use crate::*;
+
+	#[derive(Encode)]
+	pub enum PalletIndex {
+		Balances = 0,
+		Democracy = 1,
+		Staking = 2,
+	}
+
+	#[derive(Encode)]
+	pub enum RuntimeCall {
+		BalancesCall(balances::Call),
+		DemocracyCall(democracy::Call),
+		StakingCall(staking::Call),
+	}
+
+	#[derive(Encode)]
+	pub enum RuntimeEvent {
+		BalancesEvent(balances::Event),
+		DemocracyEvent(democracy::Event),
+		// No staking events... not even in the enum.
+	}
+
+	// Imagine this for all of the possible types above...
+	impl Into<RuntimeEvent> for balances::Event {
+		fn into(self) -> RuntimeEvent {
+			RuntimeEvent::BalancesEvent(self)
+		}
+	}
+
+	// Imagine this for all of the possible types above...
+	impl TryFrom<RuntimeEvent> for balances::Event {
+		type Error = ();
+
+		fn try_from(outer: RuntimeEvent) -> Result<Self, ()> {
+			match outer {
+				Event::BalancesEvent(event) => Ok(event),
+				_ => Err(())
+			}
+		}
+	}
+}
+
+use runtime_primitives::*;
+
+fn main() {
+	let democracy_call = democracy::Call::propose { proposal_hash: [7u8; 32] };
+	println!("Pallet Call:   {:?}", democracy_call.encode());
+	let runtime_call = runtime::RuntimeCall::Democracy(democracy_call);
+	println!("Runtime Call:  {:?}", runtime_call.encode());
+	let staking_error = staking::Error::AlreadyBonded;
+	println!("Pallet Error:  {:?}", staking_error.encode());
+	let runtime_error: DispatchError = staking_error.into();
+	println!("Runtime Error: {:?}", runtime_error.encode());
+	let balances_event = balances::Event::Transfer { from: 1, to: 2, amount: 3 };
+	println!("Pallet Event:  {:?}", balances_event.encode());
+	let runtime_event: runtime::RuntimeEvent = balances_event.into();
+	println!("Runtime Event: {:?}", runtime_event.encode());
+}
+```
+
+---
+
+## Outer Enum Encoding
+
+This now explains how all the different runtime types are generally encoded!
+
+```rust [2,4,6,8,10,12]
+fn main() {
+	let democracy_call = democracy::Call::propose { proposal_hash: [7u8; 32] };
+	println!("Pallet Call:   {:?}", democracy_call.encode());
+	let runtime_call = runtime::RuntimeCall::Democracy(democracy_call);
+	println!("Runtime Call:  {:?}", runtime_call.encode());
+	let staking_error = staking::Error::AlreadyBonded;
+	println!("Pallet Error:  {:?}", staking_error.encode());
+	let runtime_error: DispatchError = staking_error.into();
+	println!("Runtime Error: {:?}", runtime_error.encode());
+	let balances_event = balances::Event::Transfer { from: 1, to: 2, amount: 3 };
+	println!("Pallet Event:  {:?}", balances_event.encode());
+	let runtime_event: runtime::RuntimeEvent = balances_event.into();
+	println!("Runtime Event: {:?}", runtime_event.encode());
+}
+```
+
+```sh
+Pallet Call:   [0, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]
+Runtime Call:  [1, 0, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]
+Pallet Error:  [2]
+Runtime Error: [1, 2, 2]
+Pallet Event:  [0, 1, 0, 2, 0, 3, 0, 0, 0]
+Runtime Event: [0, 0, 1, 0, 2, 0, 3, 0, 0, 0]
+```
+
+---
+
+## Real Runtime
+
+This was directly added to `substrate/bin/node-template/runtime/src/lib.rs`:
+
+```rust [7,9,11,13,15,17]
+#[test]
+fn outer_enum_tests() {
+	use sp_runtime::{DispatchError, MultiAddress};
+	use sp_core::crypto::AccountId32;
+	use codec::Encode;
+
+	let balances_call = pallet_balances::Call::<Runtime>::transfer { dest: MultiAddress::Address32([1u8; 32]), value: 12345 };
+	println!("Pallet Call:   {:?}", balances_call.encode());
+	let runtime_call = crate::RuntimeCall::Balances(balances_call);
+	println!("Runtime Call:  {:?}", runtime_call.encode());
+	let balances_error = pallet_balances::Error::<Runtime>::InsufficientBalance;
+	println!("Pallet Error:  {:?}", balances_error.encode());
+	let runtime_error: DispatchError = balances_error.into();
+	println!("Runtime Error: {:?}", runtime_error.encode());
+	let balances_event = pallet_balances::Event::<Runtime>::Transfer { from: AccountId32::new([2u8; 32]), to: AccountId32::new([3u8; 32]), amount: 12345 };
+	println!("Pallet Event:  {:?}", balances_event.encode());
+	let runtime_event: crate::RuntimeEvent = balances_event.into();
+	println!("Runtime Event: {:?}", runtime_event.encode());
+}
+```
+
+---
+
+## Real Runtime Output
+
+```sh
+Pallet Call:   [0, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 229, 192]
+Runtime Call:  [5, 0, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 229, 192]
+Pallet Error:  [2]
+Runtime Error: [3, 5, 2, 0, 0, 0]
+Pallet Event:  [2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 57, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+Runtime Event: [5, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 57, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+```
+
+Everything is just like our FRAME-less mock, but the types are more complex.
+
+---
+
+## Using Outer Enums
+
+The path for using outer enums can be a bit confusing.
+
+- The types which compose the outer enum come from pallets.
+
+- They are aggregated in the runtime.
+
+- They can be passed BACK to the pallets and used in pallet logic through associated types.
+
+---
+
+### System Aggregated Associated Types
+
+You can see these "aggregate" types are associated types in FRAME System.
+
+```rust
+/// System configuration trait. Implemented by runtime.
+#[pallet::config]
+#[pallet::disable_frame_system_supertrait_check]
+pub trait Config: 'static + Eq + Clone {
+	/// The `RuntimeOrigin` type used by dispatchable calls.
+	type RuntimeOrigin: Into<Result<RawOrigin<Self::AccountId>, Self::RuntimeOrigin>> + From<RawOrigin<Self::AccountId>> + Clone + OriginTrait<Call = Self::RuntimeCall>;
+
+	/// The aggregated `RuntimeCall` type.
+	type RuntimeCall: Parameter + Dispatchable<RuntimeOrigin = Self::RuntimeOrigin> + Debug + From<Call<Self>>;
+
+	/// The aggregated event type of the runtime.
+	type RuntimeEvent: Parameter + Member + From<Event<Self>> + Debug + IsType<<Self as frame_system::Config>::RuntimeEvent>;
+
+	// -- snip --
+}
+```
+
+---
+
+## Pallet Event
+
+You can now see why we need to add an `Event` associated type to each pallet which uses events:
+
+```rust
+/// Configure the pallet by specifying the parameters and types on which it depends.
+#[pallet::config]
+pub trait Config: frame_system::Config {
+	/// Because this pallet emits events, it depends on the runtime's definition of an event.
+	type RuntimeEvent: From<Event<Self>> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
+}
+```
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Signed_Extensions-slides.md b/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Signed_Extensions-slides.md
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+++ b/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Signed_Extensions-slides.md
@@ -0,0 +1,342 @@
+---
+title: Signed Extensions
+description: Signed Extensions, Transaction Priority.
+---
+
+# Signed Extensions
+
+---v
+
+- In this lecture you will learn above one of the most advance FRAME concepts, _Signed Extensions_.
+
+* They allow for a multitude of custom features to be added to FRAME transactions.
+
+---
+
+## History
+
+- Signed Extensions originally where added to implement tipping in a reasonable way.
+
+* Originally, your dumb instructor (@kianenigma) had the idea of hard-coding it into the `UncheckedExtrinsic`, until @gavofyork jumped in with the idea of signed extensions.
+
+> [Tipped Transaction Type. by kianenigma · Pull Request #2930 · paritytech/substrate](https://github.com/paritytech/substrate/pull/2930/files) > [Extensible transactions (and tips) by gavofyork · Pull Request #3102 · paritytech/substrate](https://github.com/paritytech/substrate/pull/3102/files)
+
+---v
+
+### History
+
+- In essence, they are a generic way to **extend** the transaction. Moreover, if they have additional payload, it is signed, therefore _`SignedExtension`_.
+
+---
+
+## Anatomy
+
+A signed extension can be either combination of the following things:
+
+- Some additional data that is attached to the transaction.
+  - The tip!
+
+<!-- .element: class="fragment" -->
+
+- Some hooks that are executed before and after the transaction is executed.
+  - Before each transaction is executed, it must pay its fee upfront.
+  - Perhaps refund the fee partially 🤑.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Anatomy
+
+- Some additional validation logic that is used to validate the transaction, and give feedback to the pool.
+  - Set priority of transaction priority based on some metric!
+
+<!-- .element: class="fragment" -->
+
+- Some additional data that must be present in the signed payload of each transaction.
+  - Data that the sender has, the chain also has, it is not communicated itself, but it is part of the signature payload.
+  - Spec version and genesis hash is part of all transaction's signature payload!
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Anatomy: Let's Peek at the Trait
+
+```rust [1-100|4|6-7|9-10|12]
+pub trait SignedExtension:
+	Codec + Debug + Sync + Send + Clone + Eq + PartialEq + StaticTypeInfo
+{
+	fn additional_signed(&self) -> Result<Self::AdditionalSigned, TransactionValidityError>;
+
+	fn validate(..) -> TransactionValidity;
+	fn validate_unsigned(..) -> TransactionValidity;
+
+	fn pre_dispatch() -> Result<Self::Pre, TransactionValidityError>;
+	fn pre_dispatch_unsigned() -> Result<(), TransactionValidityError>;
+
+	fn post_dispatch() -> Result<(), TransactionValidityError>;
+}
+```
+
+---
+
+## Grouping Signed Extension
+
+- Is also a signed extension itself!
+
+- You can look at the implementation yourself.. but the TLDR is:
+
+- Main takeaways:
+  - `type AdditionalSigned = (SE1::AdditionalSigned, SE2::AdditionalSigned)`,
+  - all of hooks:
+    - Executes each individually, combines results
+
+Notes:
+
+TODO: how `TransactionValidity` is `combined_with` is super important here, but probably something to cover more in 4.3 and recap here.
+
+---v
+
+## Usage In The Runtime
+
+- Each runtime has a bunch of signed extensions. They can be grouped as a tuple
+
+```rust
+pub type SignedExtra = (
+	frame_system::CheckNonZeroSender<Runtime>,
+	frame_system::CheckSpecVersion<Runtime>,
+	frame_system::CheckTxVersion<Runtime>,
+	frame_system::CheckGenesis<Runtime>,
+	pallet_asset_tx_payment::ChargeAssetTxPayment<Runtime>,
+);
+
+type UncheckedExtrinsic = generic::UncheckedExtrinsic<Address, Call, Signature, SignedExtra>;
+```
+
+- Signed extensions might originate from a pallet, but are applied to ALL EXTRINSICS 😮‍💨!
+
+Notes:
+
+We will get to this later as well, but recall that SignedExtensions are not a _FRAME/Pallet_
+concept per se. FRAME just implements them. This also implies that everything regarding signed
+extensions is applied to **all transactions**, throughout the runtime.
+
+---
+
+## Encoding
+
+```rust
+struct Foo(u32, u32);
+impl SignedExtension for Foo {
+  type AdditionalSigned = u32;
+  fn additional_signed(&self) -> Result<Self::AdditionalSigned, TransactionValidityError> {
+    Ok(42u32)
+  }
+}
+
+pub struct UncheckedExtrinsic<Address, Call, Signature, (Foo)>
+{
+	pub signature: Option<(Address, Signature, Extra)>,
+	pub function: Call,
+}
+```
+
+- 2 u32 are decoded as, `42u32` is expected to be in the signature payload.
+
+Notes:
+
+Here's the `check` function of `CheckedExtrinsic` extensively documented to demonstrate this:
+
+```rust
+// SignedPayload::new
+pub fn new(call: Call, extra: Extra) -> Result<Self, TransactionValidityError> {
+	// asks all signed extensions to give their additional signed data..
+	let additional_signed = extra.additional_signed()?;
+	// this essentially means: what needs to be signed in the signature of the transaction is:
+	// 1. call
+	// 2. signed extension data itself
+	// 3. any additional signed data.
+	let raw_payload = (call, extra, additional_signed);
+	Ok(Self(raw_payload))
+}
+
+// UncheckedExtrinsic::check
+fn check(self, lookup: &Lookup) -> Result<Self::Checked, TransactionValidityError> {
+	Ok(match self.signature {
+		Some((signed, signature, extra)) => {
+			let signed = lookup.lookup(signed)?;
+			// this is the payload that we expect to be signed, as explained above.
+			let raw_payload = SignedPayload::new(self.function, extra)?;
+			// encode the signed payload, and check it against the signature.
+			if !raw_payload.using_encoded(|payload| signature.verify(payload, &signed)) {
+				return Err(InvalidTransaction::BadProof.into())
+			}
+
+			// the extra is passed again to `CheckedExtrinsic`, see in the next section.
+			let (function, extra, _) = raw_payload.deconstruct();
+			CheckedExtrinsic { signed: Some((signed, extra)), function }
+		},
+		// we don't care about signed extensions at all.
+		None => CheckedExtrinsic { signed: None, function: self.function },
+	})
+}
+```
+
+---
+
+## Transaction Pool Validation
+
+- Each pallet also has `#[pallet::validate_unsigned]`.
+- This kind of overlaps with creating a signed extension and implementing `validate_unsigned`.
+
+Notes:
+
+https://github.com/paritytech/substrate/issues/6102
+https://github.com/paritytech/substrate/issues/4419
+
+---v
+
+### Transaction Pool Validation
+
+- Recall that transaction pool validation should be minimum effort and static.
+- In `executive`, we only do the following:
+  - check signature.
+  - call `Extra::validate`/`Extra::validate_unsigned`
+  - call `ValidateUnsigned::validate`, if unsigned.
+  - NOTE dispatching ✅!
+
+Notes:
+
+> Transaction queue is not part of the consensus system. Validation of transaction are _free_. Doing
+> too much work in validation of transactions is essentially opening a door to be DOS-ed.
+
+---v
+
+### Transaction Pool Validation
+
+- Crucially, you should make sure that you re-execute anything that you do in transaction pool validation in dispatch as well:
+
+```rust
+/// Do any pre-flight stuff for a signed transaction.
+///
+/// Make sure to perform the same checks as in [`Self::validate`].
+fn pre_dispatch() -> Result<Self::Pre, TransactionValidityError>;
+```
+
+- Because conditions that are not stateless might change over time!
+
+---
+
+## Post Dispatch
+
+- The dispatch result, plus generic type (`type Pre`) returned from `pre_dispatch` is passed to `post_dispatch`.
+- See [`impl Applyable for CheckedExtrinsic`](https://github.com/paritytech/substrate/blob/a47f200eebeb88a5bde6f1ed2be9728b82536dde/primitives/runtime/src/generic/checked_extrinsic.rs#L69) for more info.
+
+---
+
+## Notable Signed Extensions
+
+- These are some of the default signed extensions that come in FRAME.
+- See if you can predict how they are made!
+
+---v
+
+### `ChargeTransactionPayment`
+
+Charge payments, refund if `Pays::Yes`.
+
+```rust
+type Pre = (
+  // tip
+  BalanceOf<T>,
+  // who paid the fee - this is an option to allow for a Default impl.
+  Self::AccountId,
+  // imbalance resulting from withdrawing the fee
+  <<T as Config>::OnChargeTransaction as OnChargeTransaction<T>>::LiquidityInfo,
+);
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### `check_genesis`
+
+Wants to make sure you are signing against the right chain.
+
+Put the genesis hash in `additional_signed`.
+
+<!-- .element: class="fragment" -->
+
+`check_spec_version` and `check_tx_version` work very similarly.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### `check_non_zero_sender`
+
+- interesting story: any account can sign on behalf of the `0x00` account.
+- discovered by [@xlc](https://github.com/xlc).
+- uses `pre_dispatch` and `validate` to ensure the signing account is not `0x00`.
+
+Notes:
+
+https://github.com/paritytech/substrate/issues/10413
+
+---v
+
+### `check_nonce`
+
+- `pre_dispatch`: check nonce and actually update it.
+- `validate`: check the nonce, DO NOT WRITE ANYTHING, set `provides` and `requires`.
+
+<!-- .element: class="fragment" -->
+
+<div>
+
+- remember that:
+  - `validate` is only for lightweight checks, no read/write.
+  - anything you write to storage is reverted anyhow.
+
+</div>
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### `check_weight`
+
+- Check there is enough weight in `validate`.
+- Check there is enough weight, and update the consumed weight in `pre_dispatch`.
+- Updated consumed weight in `post_dispatch`.
+
+<!-- .element: class="fragment" -->
+
+---
+
+## Big Picture: Pipeline of Extension
+
+- Signed extensions (or at least the `pre_dispatch` and `validate` part) remind me of the extension
+  system of `express.js`, if any of you know what that is
+
+---v
+
+## Big Picture: Pipeline of Extension
+
+<img rounded src="../../../../assets/img/5-Substrate/dev-5-x-signed-extensions.svg" />
+
+---
+
+## Exercises
+
+- Walk over the notable signed extensions above and riddle each other about how they work.
+- SignedExtensions are an important part of the transaction encoding. Try and encode a correct
+  transaction against a template runtime in any language that you want, using only a scale-codec
+  library.
+- SignedExtensions that logs something on each transaction
+- SignedExtension that keeps a counter of all transactions
+- SignedExtensions that keeps a counter of all successful/failed transactions
+- SignedExtension that tries to refund the transaction from each account as long as they submit less
+  than 1tx/day.
diff --git a/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Transaction_Extensions-slides.md b/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Transaction_Extensions-slides.md
new file mode 100644
index 00000000..dfb3d705
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Transaction_Extensions-slides.md
@@ -0,0 +1,336 @@
+---
+title: Transaction Extensions
+description: Transaction Extensions, Transaction Priority.
+---
+
+# Transaction Extensions
+
+---v
+
+- In this lecture you will learn above one of the more advanced FRAME concepts, _Transaction Extensions_.
+
+* They allow for a multitude of custom features to be added to FRAME transactions.
+
+---
+
+## History
+
+- Transaction Extensions are an evolution of Signed Extensions.
+- See [the introducing PR](https://github.com/paritytech/polkadot-sdk/pull/3685)
+- In essence, they are a generic way to **extend** the transaction.
+
+---
+
+## Anatomy
+
+A transaction extension can either or both of the following things:
+
+- Some additional data that is attached to the transaction.
+  - The tip!
+
+<!-- .element: class="fragment" -->
+
+- Some hooks that are executed before and after the transaction is executed.
+  - Before each transaction is executed, it must pay its fee upfront.
+  - Perhaps refund the fee partially 🤑.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Anatomy
+
+- Some additional validation logic that is used to validate the transaction, and give feedback to the pool.
+  - Set priority of transaction priority based on some metric!
+
+<!-- .element: class="fragment" -->
+
+- Some additional data that must be present in the signed payload of each transaction.
+  - Data that the sender has, the chain also has, it is not communicated itself, but it is part of the signature payload.
+  - Spec version and genesis hash is part of all transaction's signature payload!
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Anatomy: Let's Peek at the Trait
+
+```rust [1-100|4-6|11|12-21|22-29|32-38]
+pub trait TransactionExtension<Call>: /* snip required traits */
+where Call: Dispatchable,
+{
+    type Implicit: Codec + StaticTypeInfo;
+    type Val;
+    type Pre;
+
+    const IDENTIFIER: &'static str;
+
+    // Required methods
+    fn weight(&self, call: &Call) -> Weight;
+    fn validate(
+        &self,
+        origin: <Call as Dispatchable>::RuntimeOrigin,
+        call: &Call,
+        info: &<Call as Dispatchable>::Info,
+        len: usize,
+        self_implicit: Self::Implicit,
+        inherited_implication: &impl Implication,
+        source: TransactionSource,
+    ) -> Result<(ValidTransaction, Self::Val, <Call as Dispatchable>::RuntimeOrigin), TransactionValidityError>;
+    fn prepare(
+        self,
+        val: Self::Val,
+        origin: &<Call as Dispatchable>::RuntimeOrigin,
+        call: &Call,
+        info: &<Call as Dispatchable>::Info,
+        len: usize,
+    ) -> Result<Self::Pre, TransactionValidityError>;
+
+	// Provided (but might implement)
+	fn post_dispatch(
+        pre: Self::Pre,
+        info: &<Call as Dispatchable>::Info,
+        post_info: &mut <Call as Dispatchable>::PostInfo,
+        len: usize,
+        result: &Result<(), DispatchError>,
+    ) -> Result<(), TransactionValidityError> { ... }
+
+    // Provided methods
+    fn implicit(&self) -> Result<Self::Implicit, TransactionValidityError> { ... }
+    fn metadata() -> Vec<TransactionExtensionMetadata> { ... }
+    /* snip */
+}
+```
+
+---
+
+## Grouping Transaction Extension
+
+- Is also a transaction extension itself!
+- You can look at the implementation yourself.. but the TLDR is:
+  - Executes each individually
+  - Passes resulting `Origin` from one to the next
+  - Combines results
+
+Notes:
+
+TODO: how `TransactionValidity` is `combined_with` is super important here, but probably something to cover more somewhere else and recap here.
+
+---v
+
+## Usage In The Runtime
+
+- Each runtime has a bunch of signed extensions. They can be grouped as a tuple
+
+```rust
+pub type TxExtension = (
+	frame_system::CheckNonZeroSender<Runtime>,
+	frame_system::CheckSpecVersion<Runtime>,
+	frame_system::CheckTxVersion<Runtime>,
+	frame_system::CheckGenesis<Runtime>,
+	pallet_asset_tx_payment::ChargeAssetTxPayment<Runtime>,
+);
+
+type UncheckedExtrinsic = generic::UncheckedExtrinsic<Address, Call, Signature, TxExtension>;
+```
+
+- Transaction extensions might originate from a pallet, but are applied to ALL EXTRINSICS 😮‍💨!
+
+Notes:
+
+We will get to this later as well, but recall that TransactionExtensions are not a _FRAME/Pallet_
+concept per se. FRAME just implements them. This also implies that everything regarding signed
+extensions is applied to **all transactions**, throughout the runtime.
+
+---
+
+## Encoding
+
+```rust
+struct Foo(u32, u32);
+impl TransactionExtension for Foo {
+  type Implicit = u32;
+  fn implicit(&self) -> Result<Self::Implicit, TransactionValidityError> {
+    Ok(42u32)
+  }
+  /* snip */
+}
+
+pub struct UncheckedExtrinsic<Address, Call, Signature, (Foo)>
+{
+	pub preamble: Preamble<(Address, Signature, Extension)>,
+	pub function: Call,
+}
+```
+
+- Two `u32` are decoded as `self`, `42u32` is expected to be in the signature payload.
+
+---v
+
+## Encoding
+
+Here's the `check` function of `CheckedExtrinsic` to hint at this:
+
+```rust
+// UncheckedExtrinsic::check
+fn check(self, lookup: &Lookup) -> Result<Self::Checked, TransactionValidityError> {
+  Ok(match self.preamble {
+    Preamble::Signed(signed, signature, tx_ext) => {
+      let signed = lookup.lookup(signed)?;
+      // The `Implicit` is "implicitly" included in the payload.
+      let raw_payload = SignedPayload::new(self.function, tx_ext)?;
+      if !raw_payload.using_encoded(|payload| signature.verify(payload, &signed)) {
+        return Err(InvalidTransaction::BadProof.into())
+      }
+      let (function, tx_ext, _) = raw_payload.deconstruct();
+      CheckedExtrinsic { format: ExtrinsicFormat::Signed(signed, tx_ext), function }
+    },
+    /* snip */
+  })
+}
+```
+
+---
+
+## Transaction Pool Validation
+
+- Each pallet also has `#[pallet::validate_unsigned]`.
+- This kind of overlaps with creating a transaction extension and implementing `bare_validate`.
+- Substrate is in the process of migrating to transaction extensions.
+
+Notes:
+
+https://github.com/paritytech/substrate/issues/6102
+https://github.com/paritytech/substrate/issues/4419
+
+---v
+
+### Transaction Pool Validation
+
+- Recall that transaction pool validation should be minimum effort and static.
+- In `executive`, we only do the following:
+  - check signature.
+  - call `TransactionExtension::validate`/`TransactionExtension::bare_validate`
+  - call `ValidateUnsigned::validate`, if unsigned.
+
+Notes:
+
+> Transaction queue is not part of the consensus system. Validation of transaction are _free_. Doing
+> too much work in validation of transactions is essentially opening a door to be DOS-ed.
+
+---
+
+## Post Dispatch
+
+- The dispatch result, plus generic type (`type Pre`) returned from `prepare` is passed to `post_dispatch`.
+
+---
+
+## Notable Transaction Extensions
+
+- These are some of the default transaction extensions that come in FRAME.
+- See if you can predict how they are made!
+
+---v
+
+### `ChargeAssetTxPayment`
+
+Charge payments, refund if `Pays::No`.
+
+```rust
+pub enum Pre<T: Config> {
+	Charge {
+		tip: BalanceOf<T>,
+		// who paid the fee
+		who: T::AccountId,
+		// imbalance resulting from withdrawing the fee
+		initial_payment: InitialPayment<T>,
+		// asset_id for the transaction payment
+		asset_id: Option<ChargeAssetIdOf<T>>,
+		// weight used by the extension
+		weight: Weight,
+	},
+	NoCharge {
+		// weight initially estimated by the extension, to be refunded
+		refund: Weight,
+	},
+}
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### `CheckGenesis`
+
+Wants to make sure you are signing against the right chain.
+
+Put the genesis hash in `implicit`.
+
+<!-- .element: class="fragment" -->
+
+`CheckSpecVersion` and `CheckTxVersion` work very similarly.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### `CheckNonZeroSender`
+
+- interesting story: any account can sign on behalf of the `0x00` account.
+- discovered by [@xlc](https://github.com/xlc).
+- uses `validate` to ensure the signing account is not `0x00`.
+  - Note: used to check in both `validate` and `pre_dispatch` in the old `SignedExtension`.
+
+Notes:
+
+https://github.com/paritytech/substrate/issues/10413
+
+---v
+
+### `CheckNonce`
+
+- `validate`: check the nonce, DO NOT WRITE ANYTHING, returns `provides` and `requires`.
+- `prepare`: check nonce and actually update it.
+
+<!-- .element: class="fragment" -->
+
+<div>
+
+- remember that:
+  - `validate` is only for lightweight checks, no read/write.
+  - anything you write to storage is reverted anyhow.
+
+</div>
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### `CheckWeight`
+
+- Check there is enough weight in `validate`.
+- Calculate and update the consumed weight in `prepare`.
+- Adjust consumed weight in `post_dispatch` based on unspent weight.
+
+<!-- .element: class="fragment" -->
+
+---
+
+## Big Picture: Pipeline of Extension
+
+- Transaction extensions remind me of other pipelines in computer graphics or data processing where you pass data from one stage to another.
+
+---
+
+## Exercises
+
+- Walk over the notable transaction extensions above and riddle each other about how they work.
+- TransactionExtensions are an important part of the transaction encoding. Try and encode a correct
+  transaction against a template runtime in any language that you want, using only a scale-codec
+  library.
+- TransactionExtension that logs something on each transaction
+- TransactionExtension that keeps a counter of all transactions
+- TransactionExtension that keeps a counter of all successful/failed transactions
+- TransactionExtension that tries to refund the transaction from each account as long as they submit less
+  than 1tx/day.
diff --git a/content/6-Protocol_On-Chain/FRAME/README.md b/content/6-Protocol_On-Chain/FRAME/README.md
new file mode 100644
index 00000000..303c01f4
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/README.md
@@ -0,0 +1,82 @@
+# Lesson Plan
+
+## Day 1 - Wed
+
+### Morning
+
+- Finish Substrate Module
+
+### Afternoon
+
+- Introduction To FRAME
+- Exercise: Proof of Existence Runtime
+- FRAME Assignment (1.5 weeks - deadline weekend after Polkadot module)
+
+## Day 2 - Thurs
+
+### Morning
+
+- Pallet Coupling
+- FRAME Common Knowledge (Pallets & Traits)
+
+### Afternoon
+
+- Storage
+
+## Day 3 - Friday
+
+### Morning
+
+- Events & Errors
+- Calls
+- Hooks
+
+### Afternoon
+
+- Origins
+- Outer Enum
+- Live Coding
+
+## Weekend
+
+- Complete FRAMEless Exercise
+
+## Day 4 - Monday
+
+### Morning
+
+- Construct Runtime + Tests
+- (MAYBE TODO, Tests Example)
+
+### Afternoon
+
+- FRAME Benchmarking
+- Exercise: Benchmarking Example
+
+## Day 5 - Tuesday
+
+### Morning
+
+- FRAME Under the Hood
+  - Deep Dive
+  - Executive
+- Signed Extensions
+
+### Afternoon
+
+- Migration & Try Runtime
+- Live Coding
+
+## Day 6 - Wed
+
+### Morning
+
+- TBD? Maybe not needed
+
+### Afternoon
+
+- Start Polkadot Module
+
+## Weekend
+
+- Complete FRAME Assignment
diff --git a/content/6-Protocol_On-Chain/FRAME/frame-storage-activity/lib.rs b/content/6-Protocol_On-Chain/FRAME/frame-storage-activity/lib.rs
new file mode 100644
index 00000000..bbc2a2fe
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/frame-storage-activity/lib.rs
@@ -0,0 +1,83 @@
+#![cfg_attr(not(feature = "std"), no_std)]
+
+/// Edit this file to define custom logic or remove it if it is not needed.
+/// Learn more about FRAME and the core library of Substrate FRAME pallets:
+/// <https://docs.substrate.io/v3/runtime/frame>
+pub use pallet::*;
+
+#[cfg(test)]
+mod mock;
+
+#[cfg(test)]
+mod tests;
+
+#[cfg(feature = "runtime-benchmarks")]
+mod benchmarking;
+
+#[frame_support::pallet]
+pub mod pallet {
+	use frame_support::pallet_prelude::*;
+
+	/// Configure the pallet by specifying the parameters and types on which it depends.
+	#[pallet::config]
+	pub trait Config: frame_system::Config {}
+
+	#[pallet::pallet]
+	pub struct Pallet<T>(_);
+
+	#[pallet::storage]
+	pub type Item1<T> = StorageValue<_, u32>;
+
+	#[pallet::storage]
+	pub type Item2<T> = StorageValue<_, u32, ValueQuery>;
+
+	#[pallet::type_value]
+	pub fn MyDefault<T: Config>() -> u32 {
+		42u32
+	}
+
+	#[pallet::storage]
+	pub type Item3<T> = StorageValue<_, u32, ValueQuery, MyDefault<T>>;
+
+	#[pallet::storage]
+	pub type Item4<T> = StorageValue<_, Option<u32>>;
+
+	#[pallet::storage]
+	pub type Item5<T> = StorageValue<_, Option<u32>, ValueQuery>;
+
+	#[pallet::storage]
+	pub type Item6<T> = StorageValue<_, ()>;
+
+	#[pallet::storage]
+	#[pallet::unbounded]
+	pub type Item7<T> = StorageValue<_, Vec<u8>, ValueQuery>;
+
+	#[pallet::storage]
+	pub type Item8<T> = StorageValue<_, BoundedVec<u8, ConstU32<100>>, ValueQuery>;
+
+	#[pallet::storage]
+	pub type Item9<T: Config> = StorageMap<_, Blake2_128, u32, u32>;
+
+	type Balance = u128;
+
+	#[pallet::storage]
+	pub type Item10<T: Config> = StorageMap<_, Blake2_128, T::AccountId, Balance, ValueQuery>;
+
+	#[pallet::storage]
+	pub type Item11<T: Config> = StorageMap<_, Blake2_128Concat, T::AccountId, Balance, ValueQuery>;
+
+	#[pallet::storage]
+	pub type Item12<T: Config> = StorageNMap<
+		_,
+		(
+			NMapKey<Blake2_128Concat, u8>,
+			NMapKey<Blake2_128Concat, u16>,
+			NMapKey<Blake2_128Concat, u32>,
+		),
+		u128,
+	>;
+
+	#[pallet::storage]
+	pub type Item13<T: Config> =
+		CountedStorageMap<_, Blake2_128Concat, T::AccountId, Balance, ValueQuery>;
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/frame-storage-activity/mock.rs b/content/6-Protocol_On-Chain/FRAME/frame-storage-activity/mock.rs
new file mode 100644
index 00000000..cafa448b
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/frame-storage-activity/mock.rs
@@ -0,0 +1,52 @@
+use crate as pallet_template;
+use frame_support::traits::{ConstU16, ConstU64};
+use frame_system as system;
+use sp_core::H256;
+use sp_runtime::{
+	testing::Header,
+	traits::{BlakeTwo256, IdentityLookup},
+};
+
+type UncheckedExtrinsic = frame_system::mocking::MockUncheckedExtrinsic<Test>;
+type Block = frame_system::mocking::MockBlock<Test>;
+
+// Configure a mock runtime to test the pallet.
+frame_support::construct_runtime!(
+	pub enum Test where
+		Block = Block,
+		NodeBlock = Block,
+		UncheckedExtrinsic = UncheckedExtrinsic,
+	{
+		System: frame_system::{Pallet, Call, Config, Storage, Event<T>},
+		Example: pallet_template,
+	}
+);
+
+impl system::Config for Test {
+	type BaseCallFilter = frame_support::traits::Everything;
+	type BlockWeights = ();
+	type BlockLength = ();
+	type DbWeight = ();
+	type RuntimeOrigin = RuntimeOrigin;
+	type RuntimeCall = RuntimeCall;
+	type Index = u64;
+	type BlockNumber = u64;
+	type Hash = H256;
+	type Hashing = BlakeTwo256;
+	type AccountId = u64;
+	type Lookup = IdentityLookup<Self::AccountId>;
+	type Header = Header;
+	type RuntimeEvent = RuntimeEvent;
+	type BlockHashCount = ConstU64<250>;
+	type Version = ();
+	type PalletInfo = PalletInfo;
+	type AccountData = ();
+	type OnNewAccount = ();
+	type OnKilledAccount = ();
+	type SystemWeightInfo = ();
+	type SS58Prefix = ConstU16<42>;
+	type OnSetCode = ();
+	type MaxConsumers = frame_support::traits::ConstU32<16>;
+}
+
+impl pallet_template::Config for Test {}
diff --git a/content/6-Protocol_On-Chain/FRAME/frame-storage-activity/tests.rs b/content/6-Protocol_On-Chain/FRAME/frame-storage-activity/tests.rs
new file mode 100644
index 00000000..a2739f70
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/frame-storage-activity/tests.rs
@@ -0,0 +1,233 @@
+use codec::Encode;
+use frame_support::{assert_err, assert_noop, assert_ok};
+
+use crate::{mock::Test as T, *};
+
+fn give_balance_to_bob(who: &[u8]) -> Result<(), ()> {
+	sp_io::storage::set(who, &100u32.encode());
+	if who != b"bob" {
+		// Too late to return an error, change is already made.
+		return Err(())
+	}
+
+	Ok(())
+}
+
+#[test]
+fn verify_first_write_last() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		assert_err!(give_balance_to_bob(b"alice"), ());
+		let balance = sp_io::storage::get(b"alice").unwrap();
+		assert_eq!(balance, 100u32.encode());
+	});
+}
+
+#[test]
+fn storage_value_key() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		use sp_core::hexdisplay::HexDisplay;
+		println!("{}", HexDisplay::from(&Item1::<T>::hashed_key()));
+		//assert!(false)
+	});
+}
+
+#[test]
+fn storage_value_exists() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// Nothing is actually there yet.
+		assert_eq!(Item1::<T>::exists(), false);
+		assert_eq!(Item1::<T>::try_get().ok(), None);
+	});
+}
+
+#[test]
+fn storage_value() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// Nothing is actually there yet.
+		assert_eq!(Item1::<T>::exists(), false);
+		assert_eq!(Item1::<T>::try_get().ok(), None);
+	});
+}
+
+#[test]
+fn value_query() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// `0u32` is the default value of `u32`
+		assert_eq!(Item2::<T>::get(), 0u32);
+		Item2::<T>::put(10u32);
+		assert_eq!(Item2::<T>::get(), 10u32);
+	});
+}
+
+#[test]
+fn my_default() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// `42u32` is the configured `OnEmpty` value.
+		assert_eq!(Item3::<T>::get(), 42u32);
+		Item3::<T>::put(10u32);
+		assert_eq!(Item3::<T>::get(), 10u32);
+	});
+}
+
+#[test]
+fn nonsense() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		assert_eq!(Item4::<T>::exists(), false);
+		assert_eq!(Item5::<T>::exists(), false);
+		Item4::<T>::put(None::<u32>);
+		Item5::<T>::put(None::<u32>);
+		assert_eq!(Item4::<T>::exists(), true);
+		assert_eq!(Item5::<T>::exists(), true);
+	});
+}
+
+#[test]
+fn better_bool() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// false case
+		assert_eq!(Item6::<T>::exists(), false);
+		Item6::<T>::put(());
+		// true case
+		assert_eq!(Item6::<T>::exists(), true);
+	});
+}
+
+#[test]
+fn kill() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		assert_eq!(Item3::<T>::get(), 42u32);
+		Item3::<T>::put(10u32);
+		assert_eq!(Item3::<T>::get(), 10u32);
+		//Item3::<T>::kill();
+		let old_value = Item3::<T>::take();
+		assert_eq!(Item3::<T>::get(), 42u32);
+		assert_eq!(old_value, 10u32);
+	});
+}
+
+#[test]
+fn mutate() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		Item2::<T>::put(42u32);
+		Item2::<T>::mutate(|x| {
+			if *x % 2 == 0 {
+				*x = *x / 2;
+			}
+		});
+		assert_eq!(Item2::<T>::get(), 21);
+	});
+}
+
+#[test]
+fn try_mutate() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		Item2::<T>::put(42u32);
+		assert_noop!(
+			Item2::<T>::try_mutate(|x| -> Result<(), ()> {
+				*x = *x / 2;
+				if *x % 2 == 0 {
+					Ok(())
+				} else {
+					Err(())
+				}
+			}),
+			()
+		);
+		assert_eq!(Item2::<T>::get(), 42);
+	});
+}
+
+#[test]
+fn vec_tricks() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		assert_eq!(Item7::<T>::decode_len(), None);
+		Item7::<T>::put(vec![0u8]);
+		assert_eq!(Item7::<T>::decode_len(), Some(1));
+		Item7::<T>::append(1u8);
+		Item7::<T>::append(2u8);
+		assert_eq!(Item7::<T>::get(), vec![0u8, 1u8, 2u8]);
+		assert_eq!(Item7::<T>::decode_len(), Some(3));
+	});
+}
+
+#[test]
+fn bounded_vec() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		for i in 0u8..100u8 {
+			assert_ok!(Item8::<T>::try_append(i));
+		}
+		assert_noop!(Item8::<T>::try_append(100), ());
+	});
+}
+
+#[test]
+fn storage_map() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		Item9::<T>::insert(0, 100);
+		assert_eq!(Item9::<T>::get(0), Some(100));
+		assert_eq!(Item9::<T>::get(1), None);
+	});
+}
+
+#[test]
+fn balance_map() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		// these would normally would be 32 byte addresses
+		let alice = 0u64;
+		let bob = 1u64;
+		Item10::<T>::insert(alice, 100);
+
+		let transfer = |from: u64, to: u64, amount: u128| -> Result<(), &'static str> {
+			Item10::<T>::try_mutate(from, |from_balance| -> Result<(), &'static str> {
+				Item10::<T>::try_mutate(to, |to_balance| -> Result<(), &'static str> {
+					*to_balance = to_balance.checked_add(amount).ok_or("overflow")?;
+					*from_balance = from_balance.checked_sub(amount).ok_or("not enough balance")?;
+					Ok(())
+				})
+			})
+		};
+
+		assert_noop!(transfer(bob, alice, 10), "not enough balance");
+		assert_ok!(transfer(alice, bob, 10));
+		assert_noop!(transfer(alice, bob, 100), "not enough balance");
+
+		assert_eq!(Item10::<T>::get(alice), 90);
+		assert_eq!(Item10::<T>::get(bob), 10);
+	});
+}
+
+#[test]
+fn prefix_keys() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		use sp_core::hexdisplay::HexDisplay;
+		println!("{}", HexDisplay::from(&Item2::<T>::hashed_key()));
+		println!("{}", HexDisplay::from(&Item10::<T>::hashed_key_for(0)));
+		println!("{}", HexDisplay::from(&Item10::<T>::hashed_key_for(1)));
+
+		//assert!(false)
+	});
+}
+
+#[test]
+fn better_balance_map() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		for i in 0u64..10u64 {
+			Item10::<T>::insert(i, u128::from(i * 100u64));
+			Item11::<T>::insert(i, u128::from(i * 100u64));
+		}
+		// cannot call iter for 10 because it cannot returns the keys
+		let all_10: Vec<_> = Item10::<T>::iter_values().collect();
+		let all_11: Vec<_> = Item11::<T>::iter().collect();
+		println!("{:?}\n{:?}", all_10, all_11);
+
+		//assert!(false)
+	});
+}
+
+#[test]
+fn storage_n_map() {
+	sp_io::TestExternalities::new_empty().execute_with(|| {
+		Item12::<T>::insert((1u8, 1u16, 1u32), 1u128);
+		assert_eq!(Item12::<T>::get((1u8, 1u16, 1u32)), Some(1u128));
+	});
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/lectures.md b/content/6-Protocol_On-Chain/FRAME/lectures.md
new file mode 100644
index 00000000..7bd5c2cb
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/lectures.md
@@ -0,0 +1,106 @@
+# New Frame Lectures List
+
+## Pre-requisite:
+
+- sp_runtime stuff
+
+## FRAME Lectures
+
+> Ordering constraint: things that I think should come before one another.
+
+- Error and call refund >> weight. Because of this, weight is explained broadly as a part of
+  transactions (quite early), and then there is a separate lecture toward the end about the details
+  and benchmarking.
+
+### Essentials
+
+- Intro to FRAME (Kian)
+
+  - simple-pallet
+  - breeze over system, covers
+    - Transient Storage Items
+    - Some of the types
+  - simple-runtime
+  - executive
+
+- Dispatchable, Calls and Transactions
+
+  - Call Encoding (indices)
+  - Weight basics
+
+- Frame Storage (Shawn)
+
+- Pallet Hooks
+
+- Error
+
+  - nested errors
+  - sp_runtime DispatchError
+  - PostInfo and WeightRefund
+
+- Events
+
+  - Phases,
+
+- Origin
+  - filtering
+  - custom origins (system)
+  - collective origin
+  - example
+
+---
+
+### Slightly Less Important.
+
+- Inherents
+
+- Metadata
+
+- Benchmarking (Shawn)
+
+  - Weight classes
+
+- Frame System: Revisiting and Leftover
+
+  - PalletInfoAccess
+  - Account Details: consumers, providers, sufficiency, etc
+  - ChainContext, whatever the fuck it is.
+
+- Frame Executive: Revisiting and Leftover
+
+- Testing a Pallet (Kian)
+  - How to write tests for a pallet.
+  - ExtBuilder patter
+  - `sp_io::TestExternalities`
+
+### Advance Topics
+
+- Pallets that receive/store calls + Dispatch Them
+
+  - `type Call` and how to deal with it.
+
+- Parity Patterns + Best-Practices
+
+  - sanity-checks by Kian
+  - ...
+
+- Transactional layers/dispatch (Shawn)
+- Signed Extensions, ValidateUnsigned TransactionValidity (priority) (Kian)
+- Digests
+- Migration + Try-Runtime (Kian)
+- Custom RPCs + Runtime APIs (maybe, we will probably deprecate it)
+- Pallet Instancing
+
+### Pallet Gallery!
+
+- Common Pallets: High level, no detail, as they might be subject to change.
+  - Balances
+  - Transaction Payment
+  - Timestamp
+  - Utility
+  - MultiSig + Proxy
+  - Babe + Aura + Grandpa
+
+### Part 4: Interesting Case Studies (for Q&A Sessions and such)
+
+- Staking, Offchain Workers etc.
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/.gitignore b/content/6-Protocol_On-Chain/FRAME/simple-runtime/.gitignore
new file mode 100644
index 00000000..eb5a316c
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/.gitignore
@@ -0,0 +1 @@
+target
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/Cargo.lock b/content/6-Protocol_On-Chain/FRAME/simple-runtime/Cargo.lock
new file mode 100644
index 00000000..24d1aee5
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/Cargo.lock
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new file mode 100644
index 00000000..78d986a5
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/Cargo.toml
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+transfer-pallet = { path = "./transfer-pallet", default-features = false }
+
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+
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+  "dispatch-pallet/std",
+  "transfer-pallet/std",
+
+  "frame-system/std",
+  "frame-system/std",
+  "frame-executive/std",
+
+  "sp-io/std",
+  "sp-runtime/std",
+  "sp-std/std",
+  "sp-api/std",
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+  "sp-version/std",
+  "sp-block-builder/std",
+  "sp-inherents/std",
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diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/build.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/build.rs
new file mode 100644
index 00000000..6018c194
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/build.rs
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+
+fn main() {
+  WasmBuilder::new()
+    .with_current_project()
+    .export_heap_base()
+    .import_memory()
+    .build()
+}
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index 00000000..eb5a316c
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index 00000000..3354ef81
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+]
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+ "windows_i686_gnu",
+ "windows_i686_msvc",
+ "windows_x86_64_gnu",
+ "windows_x86_64_msvc",
+]
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+]
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+ "syn",
+ "synstructure",
+]
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch-pallet/Cargo.toml b/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch-pallet/Cargo.toml
new file mode 100644
index 00000000..701c6499
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch-pallet/Cargo.toml
@@ -0,0 +1,31 @@
+[package]
+name = "dispatch-pallet"
+version = "0.1.0"
+edition = "2021"
+
+[dependencies]
+codec = { package = "parity-scale-codec", version = "3.0.0", default-features = false }
+log = { version = "0.4.17", default-features = false }
+scale-info = { version = "2.1.1", default-features = false, features = ["derive"] }
+
+frame-support = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+frame-system = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+
+sp-io = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+sp-runtime = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+sp-std = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+
+[features]
+default = ["std"]
+std = [
+  "codec/std",
+  "scale-info/std",
+  "log/std",
+
+  "frame-support/std",
+  "frame-system/std",
+
+  "sp-io/std",
+  "sp-runtime/std",
+  "sp-std/std",
+]
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch-pallet/expanded.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch-pallet/expanded.rs
new file mode 100644
index 00000000..1fb53b1d
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch-pallet/expanded.rs
@@ -0,0 +1,1040 @@
+#![feature(prelude_import)]
+#[prelude_import]
+use std::prelude::rust_2021::*;
+#[macro_use]
+extern crate std;
+pub use pallet::*;
+pub struct WithDebug {
+    foo: u32,
+    bar: u32,
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::fmt::Debug for WithDebug {
+    fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
+        ::core::fmt::Formatter::debug_struct_field2_finish(
+            f,
+            "WithDebug",
+            "foo",
+            &&self.foo,
+            "bar",
+            &&self.bar,
+        )
+    }
+}
+pub struct WithRuntimeDebug {
+    foo: u32,
+    bar: u32,
+}
+impl core::fmt::Debug for WithRuntimeDebug {
+    fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+        fmt.debug_struct("WithRuntimeDebug")
+            .field("foo", &self.foo)
+            .field("bar", &self.bar)
+            .finish()
+    }
+}
+///
+///			The module that hosts all the
+///			[FRAME](https://docs.substrate.io/v3/runtime/frame)
+///			types needed to add this pallet to a
+///			runtime.
+///
+pub mod pallet {
+    use codec::{Encode, Decode};
+    use frame_support::{
+        pallet_prelude::*,
+        dispatch::{DispatchResultWithPostInfo, PostDispatchInfo},
+        weights::Pays,
+    };
+    use frame_system::pallet_prelude::*;
+    ///
+    ///			Configuration trait of this pallet.
+    ///
+    ///			Implement this type for a runtime in order to customize this pallet.
+    ///
+    pub trait Config: frame_system::Config {}
+    ///
+    ///			The [pallet](https://docs.substrate.io/v3/runtime/frame#pallets) implementing
+    ///			the on-chain logic.
+    ///
+    pub struct Pallet<T>(PhantomData<T>);
+    const _: () = {
+        impl<T> core::clone::Clone for Pallet<T> {
+            fn clone(&self) -> Self {
+                Self(core::clone::Clone::clone(&self.0))
+            }
+        }
+    };
+    const _: () = {
+        impl<T> core::cmp::Eq for Pallet<T> {}
+    };
+    const _: () = {
+        impl<T> core::cmp::PartialEq for Pallet<T> {
+            fn eq(&self, other: &Self) -> bool {
+                true && self.0 == other.0
+            }
+        }
+    };
+    const _: () = {
+        impl<T> core::fmt::Debug for Pallet<T> {
+            fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+                fmt.debug_tuple("Pallet").field(&self.0).finish()
+            }
+        }
+    };
+    pub struct TransferConfig<AccountId> {
+        from: AccountId,
+        to: AccountId,
+        amount: u64,
+    }
+    #[allow(deprecated)]
+    const _: () = {
+        #[automatically_derived]
+        impl<AccountId> ::codec::Encode for TransferConfig<AccountId>
+        where
+            AccountId: ::codec::Encode,
+            AccountId: ::codec::Encode,
+            AccountId: ::codec::Encode,
+            AccountId: ::codec::Encode,
+        {
+            fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+                &self,
+                __codec_dest_edqy: &mut __CodecOutputEdqy,
+            ) {
+                ::codec::Encode::encode_to(&self.from, __codec_dest_edqy);
+                ::codec::Encode::encode_to(&self.to, __codec_dest_edqy);
+                ::codec::Encode::encode_to(&self.amount, __codec_dest_edqy);
+            }
+        }
+        #[automatically_derived]
+        impl<AccountId> ::codec::EncodeLike for TransferConfig<AccountId>
+        where
+            AccountId: ::codec::Encode,
+            AccountId: ::codec::Encode,
+            AccountId: ::codec::Encode,
+            AccountId: ::codec::Encode,
+        {
+        }
+    };
+    #[allow(deprecated)]
+    const _: () = {
+        #[automatically_derived]
+        impl<AccountId> ::codec::Decode for TransferConfig<AccountId>
+        where
+            AccountId: ::codec::Decode,
+            AccountId: ::codec::Decode,
+            AccountId: ::codec::Decode,
+            AccountId: ::codec::Decode,
+        {
+            fn decode<__CodecInputEdqy: ::codec::Input>(
+                __codec_input_edqy: &mut __CodecInputEdqy,
+            ) -> ::core::result::Result<Self, ::codec::Error> {
+                ::core::result::Result::Ok(TransferConfig::<AccountId> {
+                    from: {
+                        let __codec_res_edqy =
+                            <AccountId as ::codec::Decode>::decode(__codec_input_edqy);
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `TransferConfig::from`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    },
+                    to: {
+                        let __codec_res_edqy =
+                            <AccountId as ::codec::Decode>::decode(__codec_input_edqy);
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `TransferConfig::to`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    },
+                    amount: {
+                        let __codec_res_edqy = <u64 as ::codec::Decode>::decode(__codec_input_edqy);
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `TransferConfig::amount`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    },
+                })
+            }
+        }
+    };
+    #[automatically_derived]
+    #[allow(unused_qualifications)]
+    impl<AccountId: ::core::fmt::Debug> ::core::fmt::Debug for TransferConfig<AccountId> {
+        fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
+            ::core::fmt::Formatter::debug_struct_field3_finish(
+                f,
+                "TransferConfig",
+                "from",
+                &&self.from,
+                "to",
+                &&self.to,
+                "amount",
+                &&self.amount,
+            )
+        }
+    }
+    impl<AccountId> ::core::marker::StructuralPartialEq for TransferConfig<AccountId> {}
+    #[automatically_derived]
+    #[allow(unused_qualifications)]
+    impl<AccountId: ::core::cmp::PartialEq> ::core::cmp::PartialEq for TransferConfig<AccountId> {
+        #[inline]
+        fn eq(&self, other: &TransferConfig<AccountId>) -> bool {
+            self.from == other.from && self.to == other.to && self.amount == other.amount
+        }
+        #[inline]
+        fn ne(&self, other: &TransferConfig<AccountId>) -> bool {
+            self.from != other.from || self.to != other.to || self.amount != other.amount
+        }
+    }
+    impl<AccountId> ::core::marker::StructuralEq for TransferConfig<AccountId> {}
+    #[automatically_derived]
+    #[allow(unused_qualifications)]
+    impl<AccountId: ::core::cmp::Eq> ::core::cmp::Eq for TransferConfig<AccountId> {
+        #[inline]
+        #[doc(hidden)]
+        #[no_coverage]
+        fn assert_receiver_is_total_eq(&self) -> () {
+            {
+                let _: ::core::cmp::AssertParamIsEq<AccountId>;
+                let _: ::core::cmp::AssertParamIsEq<AccountId>;
+                let _: ::core::cmp::AssertParamIsEq<u64>;
+            }
+        }
+    }
+    #[automatically_derived]
+    #[allow(unused_qualifications)]
+    impl<AccountId: ::core::clone::Clone> ::core::clone::Clone for TransferConfig<AccountId> {
+        #[inline]
+        fn clone(&self) -> TransferConfig<AccountId> {
+            TransferConfig {
+                from: ::core::clone::Clone::clone(&self.from),
+                to: ::core::clone::Clone::clone(&self.to),
+                amount: ::core::clone::Clone::clone(&self.amount),
+            }
+        }
+    }
+    #[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+    const _: () = {
+        impl<AccountId> ::scale_info::TypeInfo for TransferConfig<AccountId>
+        where
+            AccountId: ::scale_info::TypeInfo + 'static,
+            AccountId: ::scale_info::TypeInfo + 'static,
+            AccountId: ::scale_info::TypeInfo + 'static,
+        {
+            type Identity = Self;
+            fn type_info() -> ::scale_info::Type {
+                ::scale_info::Type::builder()
+                    .path(::scale_info::Path::new(
+                        "TransferConfig",
+                        "dispatch_pallet::pallet",
+                    ))
+                    .type_params(<[_]>::into_vec(
+                        #[rustc_box]
+                        ::alloc::boxed::Box::new([::scale_info::TypeParameter::new(
+                            "AccountId",
+                            ::core::option::Option::Some(::scale_info::meta_type::<AccountId>()),
+                        )]),
+                    ))
+                    .docs(&[])
+                    .composite(
+                        ::scale_info::build::Fields::named()
+                            .field(|f| {
+                                f.ty::<AccountId>()
+                                    .name("from")
+                                    .type_name("AccountId")
+                                    .docs(&[])
+                            })
+                            .field(|f| {
+                                f.ty::<AccountId>()
+                                    .name("to")
+                                    .type_name("AccountId")
+                                    .docs(&[])
+                            })
+                            .field(|f| f.ty::<u64>().name("amount").type_name("u64").docs(&[])),
+                    )
+            }
+        };
+    };
+    impl<T: Config> Pallet<T> {
+        pub fn first_transaction(_origin: OriginFor<T>, _inc: u32) -> DispatchResult {
+            Ok(())
+        }
+        pub fn transfer(
+            _origin: OriginFor<T>,
+            config: TransferConfig<T::AccountId>,
+        ) -> DispatchResultWithPostInfo {
+            if config.amount == 42 {
+                Ok(PostDispatchInfo {
+                    actual_weight: Some(0),
+                    pays_fee: Pays::No,
+                })
+            } else {
+                Ok(None.into())
+            }
+        }
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn pallet_constants_metadata(
+        ) -> frame_support::sp_std::vec::Vec<frame_support::metadata::PalletConstantMetadata>
+        {
+            ::alloc::vec::Vec::new()
+        }
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn error_metadata() -> Option<frame_support::metadata::PalletErrorMetadata> {
+            None
+        }
+    }
+    /// Type alias to `Pallet`, to be used by `construct_runtime`.
+    ///
+    /// Generated by `pallet` attribute macro.
+    #[deprecated(note = "use `Pallet` instead")]
+    #[allow(dead_code)]
+    pub type Module<T> = Pallet<T>;
+    impl<T: Config> frame_support::traits::GetStorageVersion for Pallet<T> {
+        fn current_storage_version() -> frame_support::traits::StorageVersion {
+            frame_support::traits::StorageVersion::default()
+        }
+        fn on_chain_storage_version() -> frame_support::traits::StorageVersion {
+            frame_support::traits::StorageVersion::get::<Self>()
+        }
+    }
+    impl<T: Config> frame_support::traits::OnGenesis for Pallet<T> {
+        fn on_genesis() {
+            let storage_version = frame_support::traits::StorageVersion::default();
+            storage_version.put::<Self>();
+        }
+    }
+    impl<T: Config> frame_support::traits::PalletInfoAccess for Pallet<T> {
+        fn index() -> usize {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::index::<
+                Self,
+            >()
+            .expect(
+                "Pallet is part of the runtime because pallet `Config` trait is \
+						implemented by the runtime",
+            )
+        }
+        fn name() -> &'static str {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::name::<
+                Self,
+            >()
+            .expect(
+                "Pallet is part of the runtime because pallet `Config` trait is \
+						implemented by the runtime",
+            )
+        }
+        fn module_name() -> &'static str {
+            < < T as frame_system :: Config > :: PalletInfo as frame_support :: traits :: PalletInfo > :: module_name :: < Self > () . expect ("Pallet is part of the runtime because pallet `Config` trait is \
+						implemented by the runtime")
+        }
+        fn crate_version() -> frame_support::traits::CrateVersion {
+            frame_support::traits::CrateVersion {
+                major: 0u16,
+                minor: 1u8,
+                patch: 0u8,
+            }
+        }
+    }
+    impl<T: Config> frame_support::traits::PalletsInfoAccess for Pallet<T> {
+        fn count() -> usize {
+            1
+        }
+        fn accumulate(
+            acc: &mut frame_support::sp_std::vec::Vec<frame_support::traits::PalletInfoData>,
+        ) {
+            use frame_support::traits::PalletInfoAccess;
+            let item = frame_support::traits::PalletInfoData {
+                index: Self::index(),
+                name: Self::name(),
+                module_name: Self::module_name(),
+                crate_version: Self::crate_version(),
+            };
+            acc.push(item);
+        }
+    }
+    impl<T: Config> frame_support::traits::StorageInfoTrait for Pallet<T> {
+        fn storage_info() -> frame_support::sp_std::vec::Vec<frame_support::traits::StorageInfo> {
+            #[allow(unused_mut)]
+            let mut res = ::alloc::vec::Vec::new();
+            res
+        }
+    }
+    #[doc(hidden)]
+    pub mod __substrate_call_check {
+        #[doc(hidden)]
+        pub use __is_call_part_defined_0 as is_call_part_defined;
+    }
+    ///Contains one variant per dispatchable that can be called by an extrinsic.
+    #[codec(encode_bound())]
+    #[codec(decode_bound())]
+    #[scale_info(skip_type_params(T), capture_docs = "always")]
+    #[allow(non_camel_case_types)]
+    pub enum Call<T: Config> {
+        #[doc(hidden)]
+        #[codec(skip)]
+        __Ignore(
+            frame_support::sp_std::marker::PhantomData<(T,)>,
+            frame_support::Never,
+        ),
+        #[codec(index = 0u8)]
+        first_transaction {
+            #[allow(missing_docs)]
+            inc: u32,
+        },
+        #[codec(index = 1u8)]
+        transfer {
+            #[allow(missing_docs)]
+            config: TransferConfig<T::AccountId>,
+        },
+    }
+    const _: () = {
+        impl<T: Config> core::fmt::Debug for Call<T> {
+            fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+                match *self {
+                    Self::__Ignore(ref _0, ref _1) => fmt
+                        .debug_tuple("Call::__Ignore")
+                        .field(&_0)
+                        .field(&_1)
+                        .finish(),
+                    Self::first_transaction { ref inc } => fmt
+                        .debug_struct("Call::first_transaction")
+                        .field("inc", &inc)
+                        .finish(),
+                    Self::transfer { ref config } => fmt
+                        .debug_struct("Call::transfer")
+                        .field("config", &config)
+                        .finish(),
+                }
+            }
+        }
+    };
+    const _: () = {
+        impl<T: Config> core::clone::Clone for Call<T> {
+            fn clone(&self) -> Self {
+                match self {
+                    Self::__Ignore(ref _0, ref _1) => {
+                        Self::__Ignore(core::clone::Clone::clone(_0), core::clone::Clone::clone(_1))
+                    }
+                    Self::first_transaction { ref inc } => Self::first_transaction {
+                        inc: core::clone::Clone::clone(inc),
+                    },
+                    Self::transfer { ref config } => Self::transfer {
+                        config: core::clone::Clone::clone(config),
+                    },
+                }
+            }
+        }
+    };
+    const _: () = {
+        impl<T: Config> core::cmp::Eq for Call<T> {}
+    };
+    const _: () = {
+        impl<T: Config> core::cmp::PartialEq for Call<T> {
+            fn eq(&self, other: &Self) -> bool {
+                match (self, other) {
+                    (Self::__Ignore(_0, _1), Self::__Ignore(_0_other, _1_other)) => {
+                        true && _0 == _0_other && _1 == _1_other
+                    }
+                    (Self::first_transaction { inc }, Self::first_transaction { inc: _0 }) => {
+                        true && inc == _0
+                    }
+                    (Self::transfer { config }, Self::transfer { config: _0 }) => {
+                        true && config == _0
+                    }
+                    (Self::__Ignore { .. }, Self::first_transaction { .. }) => false,
+                    (Self::__Ignore { .. }, Self::transfer { .. }) => false,
+                    (Self::first_transaction { .. }, Self::__Ignore { .. }) => false,
+                    (Self::first_transaction { .. }, Self::transfer { .. }) => false,
+                    (Self::transfer { .. }, Self::__Ignore { .. }) => false,
+                    (Self::transfer { .. }, Self::first_transaction { .. }) => false,
+                }
+            }
+        }
+    };
+    #[allow(deprecated)]
+    const _: () = {
+        #[allow(non_camel_case_types)]
+        #[automatically_derived]
+        impl<T: Config> ::codec::Encode for Call<T> {
+            fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+                &self,
+                __codec_dest_edqy: &mut __CodecOutputEdqy,
+            ) {
+                match *self {
+                    Call::first_transaction { ref inc } => {
+                        __codec_dest_edqy.push_byte(0u8 as ::core::primitive::u8);
+                        ::codec::Encode::encode_to(inc, __codec_dest_edqy);
+                    }
+                    Call::transfer { ref config } => {
+                        __codec_dest_edqy.push_byte(1u8 as ::core::primitive::u8);
+                        ::codec::Encode::encode_to(config, __codec_dest_edqy);
+                    }
+                    _ => (),
+                }
+            }
+        }
+        #[automatically_derived]
+        impl<T: Config> ::codec::EncodeLike for Call<T> {}
+    };
+    #[allow(deprecated)]
+    const _: () = {
+        #[allow(non_camel_case_types)]
+        #[automatically_derived]
+        impl<T: Config> ::codec::Decode for Call<T> {
+            fn decode<__CodecInputEdqy: ::codec::Input>(
+                __codec_input_edqy: &mut __CodecInputEdqy,
+            ) -> ::core::result::Result<Self, ::codec::Error> {
+                match __codec_input_edqy
+                    .read_byte()
+                    .map_err(|e| e.chain("Could not decode `Call`, failed to read variant byte"))?
+                {
+                    __codec_x_edqy if __codec_x_edqy == 0u8 as ::core::primitive::u8 => {
+                        ::core::result::Result::Ok(Call::<T>::first_transaction {
+                            inc: {
+                                let __codec_res_edqy =
+                                    <u32 as ::codec::Decode>::decode(__codec_input_edqy);
+                                match __codec_res_edqy {
+                                    ::core::result::Result::Err(e) => {
+                                        return ::core::result::Result::Err(e.chain(
+                                            "Could not decode `Call::first_transaction::inc`",
+                                        ))
+                                    }
+                                    ::core::result::Result::Ok(__codec_res_edqy) => {
+                                        __codec_res_edqy
+                                    }
+                                }
+                            },
+                        })
+                    }
+                    __codec_x_edqy if __codec_x_edqy == 1u8 as ::core::primitive::u8 => {
+                        ::core::result::Result::Ok(Call::<T>::transfer {
+                            config: {
+                                let __codec_res_edqy =
+                                    <TransferConfig<T::AccountId> as ::codec::Decode>::decode(
+                                        __codec_input_edqy,
+                                    );
+                                match __codec_res_edqy {
+                                    ::core::result::Result::Err(e) => {
+                                        return ::core::result::Result::Err(
+                                            e.chain("Could not decode `Call::transfer::config`"),
+                                        )
+                                    }
+                                    ::core::result::Result::Ok(__codec_res_edqy) => {
+                                        __codec_res_edqy
+                                    }
+                                }
+                            },
+                        })
+                    }
+                    _ => ::core::result::Result::Err(<_ as ::core::convert::Into<_>>::into(
+                        "Could not decode `Call`, variant doesn't exist",
+                    )),
+                }
+            }
+        }
+    };
+    #[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+    const _: () = {
+        impl<T: Config> ::scale_info::TypeInfo for Call<T>
+        where
+            frame_support::sp_std::marker::PhantomData<(T,)>: ::scale_info::TypeInfo + 'static,
+            TransferConfig<T::AccountId>: ::scale_info::TypeInfo + 'static,
+            T: Config + 'static,
+        {
+            type Identity = Self;
+            fn type_info() -> ::scale_info::Type {
+                ::scale_info::Type::builder()
+                    .path(::scale_info::Path::new("Call", "dispatch_pallet::pallet"))
+                    .type_params(<[_]>::into_vec(
+                        #[rustc_box]
+                        ::alloc::boxed::Box::new([::scale_info::TypeParameter::new(
+                            "T",
+                            ::core::option::Option::None,
+                        )]),
+                    ))
+                    .docs_always(&[
+                        "Contains one variant per dispatchable that can be called by an extrinsic.",
+                    ])
+                    .variant(
+                        ::scale_info::build::Variants::new()
+                            .variant("first_transaction", |v| {
+                                v.index(0u8 as ::core::primitive::u8)
+                                    .fields(::scale_info::build::Fields::named().field(|f| {
+                                        f.ty::<u32>().name("inc").type_name("u32").docs_always(&[])
+                                    }))
+                                    .docs_always(&[])
+                            })
+                            .variant("transfer", |v| {
+                                v.index(1u8 as ::core::primitive::u8)
+                                    .fields(::scale_info::build::Fields::named().field(|f| {
+                                        f.ty::<TransferConfig<T::AccountId>>()
+                                            .name("config")
+                                            .type_name("TransferConfig<T::AccountId>")
+                                            .docs_always(&[])
+                                    }))
+                                    .docs_always(&[])
+                            }),
+                    )
+            }
+        };
+    };
+    impl<T: Config> Call<T> {
+        ///Create a call with the variant `first_transaction`.
+        pub fn new_call_variant_first_transaction(inc: u32) -> Self {
+            Self::first_transaction { inc }
+        }
+        ///Create a call with the variant `transfer`.
+        pub fn new_call_variant_transfer(config: TransferConfig<T::AccountId>) -> Self {
+            Self::transfer { config }
+        }
+    }
+    impl<T: Config> frame_support::dispatch::GetDispatchInfo for Call<T> {
+        fn get_dispatch_info(&self) -> frame_support::dispatch::DispatchInfo {
+            match *self {
+                Self::first_transaction { inc: ref _inc } => {
+                    let __pallet_base_weight = 42;
+                    let __pallet_weight =
+                        <dyn frame_support::dispatch::WeighData<(&u32,)>>::weigh_data(
+                            &__pallet_base_weight,
+                            (_inc,),
+                        );
+                    let __pallet_class =
+                        <dyn frame_support::dispatch::ClassifyDispatch<(&u32,)>>::classify_dispatch(
+                            &__pallet_base_weight,
+                            (_inc,),
+                        );
+                    let __pallet_pays_fee =
+                        <dyn frame_support::dispatch::PaysFee<(&u32,)>>::pays_fee(
+                            &__pallet_base_weight,
+                            (_inc,),
+                        );
+                    frame_support::dispatch::DispatchInfo {
+                        weight: __pallet_weight,
+                        class: __pallet_class,
+                        pays_fee: __pallet_pays_fee,
+                    }
+                }
+                Self::transfer { ref config } => {
+                    let __pallet_base_weight = 42;
+                    let __pallet_weight = <dyn frame_support::dispatch::WeighData<(
+                        &TransferConfig<T::AccountId>,
+                    )>>::weigh_data(
+                        &__pallet_base_weight, (config,)
+                    );
+                    let __pallet_class = <dyn frame_support::dispatch::ClassifyDispatch<(
+                        &TransferConfig<T::AccountId>,
+                    )>>::classify_dispatch(
+                        &__pallet_base_weight, (config,)
+                    );
+                    let __pallet_pays_fee = <dyn frame_support::dispatch::PaysFee<(
+                        &TransferConfig<T::AccountId>,
+                    )>>::pays_fee(
+                        &__pallet_base_weight, (config,)
+                    );
+                    frame_support::dispatch::DispatchInfo {
+                        weight: __pallet_weight,
+                        class: __pallet_class,
+                        pays_fee: __pallet_pays_fee,
+                    }
+                }
+                Self::__Ignore(_, _) => {
+                    ::core::panicking::panic_fmt(::core::fmt::Arguments::new_v1(
+                        &["internal error: entered unreachable code: "],
+                        &[::core::fmt::ArgumentV1::new_display(
+                            &::core::fmt::Arguments::new_v1(&["__Ignore cannot be used"], &[]),
+                        )],
+                    ))
+                }
+            }
+        }
+    }
+    impl<T: Config> frame_support::dispatch::GetCallName for Call<T> {
+        fn get_call_name(&self) -> &'static str {
+            match *self {
+                Self::first_transaction { .. } => "first_transaction",
+                Self::transfer { .. } => "transfer",
+                Self::__Ignore(_, _) => {
+                    ::core::panicking::panic_fmt(::core::fmt::Arguments::new_v1(
+                        &["internal error: entered unreachable code: "],
+                        &[::core::fmt::ArgumentV1::new_display(
+                            &::core::fmt::Arguments::new_v1(
+                                &["__PhantomItem cannot be used."],
+                                &[],
+                            ),
+                        )],
+                    ))
+                }
+            }
+        }
+        fn get_call_names() -> &'static [&'static str] {
+            &["first_transaction", "transfer"]
+        }
+    }
+    impl<T: Config> frame_support::traits::UnfilteredDispatchable for Call<T> {
+        type Origin = frame_system::pallet_prelude::OriginFor<T>;
+        fn dispatch_bypass_filter(
+            self,
+            origin: Self::Origin,
+        ) -> frame_support::dispatch::DispatchResultWithPostInfo {
+            match self {
+                Self::first_transaction { inc: _inc } => {
+                    let __within_span__ = {
+                        use ::tracing::__macro_support::Callsite as _;
+                        static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                            static META: ::tracing::Metadata<'static> = {
+                                ::tracing_core::metadata::Metadata::new(
+                                    "first_transaction",
+                                    "dispatch_pallet::pallet",
+                                    ::tracing::Level::TRACE,
+                                    Some("src/lib.rs"),
+                                    Some(11u32),
+                                    Some("dispatch_pallet::pallet"),
+                                    ::tracing_core::field::FieldSet::new(
+                                        &[],
+                                        ::tracing_core::callsite::Identifier(&CALLSITE),
+                                    ),
+                                    ::tracing::metadata::Kind::SPAN,
+                                )
+                            };
+                            ::tracing::callsite::DefaultCallsite::new(&META)
+                        };
+                        let mut interest = ::tracing::subscriber::Interest::never();
+                        if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                            && ::tracing::Level::TRACE
+                                <= ::tracing::level_filters::LevelFilter::current()
+                            && {
+                                interest = CALLSITE.interest();
+                                !interest.is_never()
+                            }
+                            && ::tracing::__macro_support::__is_enabled(
+                                CALLSITE.metadata(),
+                                interest,
+                            )
+                        {
+                            let meta = CALLSITE.metadata();
+                            ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                        } else {
+                            let span =
+                                ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                            {};
+                            span
+                        }
+                    };
+                    let __tracing_guard__ = __within_span__.enter();
+                    frame_support::storage::in_storage_layer(|| {
+                        <Pallet<T>>::first_transaction(origin, _inc)
+                            .map(Into::into)
+                            .map_err(Into::into)
+                    })
+                }
+                Self::transfer { config } => {
+                    let __within_span__ = {
+                        use ::tracing::__macro_support::Callsite as _;
+                        static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                            static META: ::tracing::Metadata<'static> = {
+                                ::tracing_core::metadata::Metadata::new(
+                                    "transfer",
+                                    "dispatch_pallet::pallet",
+                                    ::tracing::Level::TRACE,
+                                    Some("src/lib.rs"),
+                                    Some(11u32),
+                                    Some("dispatch_pallet::pallet"),
+                                    ::tracing_core::field::FieldSet::new(
+                                        &[],
+                                        ::tracing_core::callsite::Identifier(&CALLSITE),
+                                    ),
+                                    ::tracing::metadata::Kind::SPAN,
+                                )
+                            };
+                            ::tracing::callsite::DefaultCallsite::new(&META)
+                        };
+                        let mut interest = ::tracing::subscriber::Interest::never();
+                        if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                            && ::tracing::Level::TRACE
+                                <= ::tracing::level_filters::LevelFilter::current()
+                            && {
+                                interest = CALLSITE.interest();
+                                !interest.is_never()
+                            }
+                            && ::tracing::__macro_support::__is_enabled(
+                                CALLSITE.metadata(),
+                                interest,
+                            )
+                        {
+                            let meta = CALLSITE.metadata();
+                            ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                        } else {
+                            let span =
+                                ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                            {};
+                            span
+                        }
+                    };
+                    let __tracing_guard__ = __within_span__.enter();
+                    frame_support::storage::in_storage_layer(|| {
+                        <Pallet<T>>::transfer(origin, config)
+                            .map(Into::into)
+                            .map_err(Into::into)
+                    })
+                }
+                Self::__Ignore(_, _) => {
+                    let _ = origin;
+                    ::core::panicking::panic_fmt(::core::fmt::Arguments::new_v1(
+                        &["internal error: entered unreachable code: "],
+                        &[::core::fmt::ArgumentV1::new_display(
+                            &::core::fmt::Arguments::new_v1(
+                                &["__PhantomItem cannot be used."],
+                                &[],
+                            ),
+                        )],
+                    ));
+                }
+            }
+        }
+    }
+    impl<T: Config> frame_support::dispatch::Callable<T> for Pallet<T> {
+        type Call = Call<T>;
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn call_functions() -> frame_support::metadata::PalletCallMetadata {
+            frame_support::scale_info::meta_type::<Call<T>>().into()
+        }
+    }
+    pub use __tt_error_token_1 as tt_error_token;
+    #[doc(hidden)]
+    pub mod __substrate_event_check {
+        #[doc(hidden)]
+        pub use __is_event_part_defined_2 as is_event_part_defined;
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn storage_metadata() -> frame_support::metadata::PalletStorageMetadata {
+            frame_support :: metadata :: PalletStorageMetadata { prefix : < < T as frame_system :: Config > :: PalletInfo as frame_support :: traits :: PalletInfo > :: name :: < Pallet < T > > () . expect ("Every active pallet has a name in the runtime; qed") , entries : { # [allow (unused_mut)] let mut entries = :: alloc :: vec :: Vec :: new () ; entries } , }
+        }
+    }
+    #[doc(hidden)]
+    pub mod __substrate_inherent_check {
+        #[doc(hidden)]
+        pub use __is_inherent_part_defined_3 as is_inherent_part_defined;
+    }
+    /// Hidden instance generated to be internally used when module is used without
+    /// instance.
+    #[doc(hidden)]
+    pub type __InherentHiddenInstance = ();
+    impl<T: Config> frame_support::traits::Hooks<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+    }
+    impl<T: Config> frame_support::traits::OnFinalize<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn on_finalize(n: <T as frame_system::Config>::BlockNumber) {
+            let __within_span__ = {
+                use ::tracing::__macro_support::Callsite as _;
+                static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                    static META: ::tracing::Metadata<'static> = {
+                        ::tracing_core::metadata::Metadata::new(
+                            "on_finalize",
+                            "dispatch_pallet::pallet",
+                            ::tracing::Level::TRACE,
+                            Some("src/lib.rs"),
+                            Some(11u32),
+                            Some("dispatch_pallet::pallet"),
+                            ::tracing_core::field::FieldSet::new(
+                                &[],
+                                ::tracing_core::callsite::Identifier(&CALLSITE),
+                            ),
+                            ::tracing::metadata::Kind::SPAN,
+                        )
+                    };
+                    ::tracing::callsite::DefaultCallsite::new(&META)
+                };
+                let mut interest = ::tracing::subscriber::Interest::never();
+                if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                    && ::tracing::Level::TRACE <= ::tracing::level_filters::LevelFilter::current()
+                    && {
+                        interest = CALLSITE.interest();
+                        !interest.is_never()
+                    }
+                    && ::tracing::__macro_support::__is_enabled(CALLSITE.metadata(), interest)
+                {
+                    let meta = CALLSITE.metadata();
+                    ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                } else {
+                    let span = ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                    {};
+                    span
+                }
+            };
+            let __tracing_guard__ = __within_span__.enter();
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_finalize (n)
+        }
+    }
+    impl<T: Config> frame_support::traits::OnIdle<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn on_idle(
+            n: <T as frame_system::Config>::BlockNumber,
+            remaining_weight: frame_support::weights::Weight,
+        ) -> frame_support::weights::Weight {
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_idle (n , remaining_weight)
+        }
+    }
+    impl<T: Config> frame_support::traits::OnInitialize<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn on_initialize(
+            n: <T as frame_system::Config>::BlockNumber,
+        ) -> frame_support::weights::Weight {
+            let __within_span__ = {
+                use ::tracing::__macro_support::Callsite as _;
+                static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                    static META: ::tracing::Metadata<'static> = {
+                        ::tracing_core::metadata::Metadata::new(
+                            "on_initialize",
+                            "dispatch_pallet::pallet",
+                            ::tracing::Level::TRACE,
+                            Some("src/lib.rs"),
+                            Some(11u32),
+                            Some("dispatch_pallet::pallet"),
+                            ::tracing_core::field::FieldSet::new(
+                                &[],
+                                ::tracing_core::callsite::Identifier(&CALLSITE),
+                            ),
+                            ::tracing::metadata::Kind::SPAN,
+                        )
+                    };
+                    ::tracing::callsite::DefaultCallsite::new(&META)
+                };
+                let mut interest = ::tracing::subscriber::Interest::never();
+                if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                    && ::tracing::Level::TRACE <= ::tracing::level_filters::LevelFilter::current()
+                    && {
+                        interest = CALLSITE.interest();
+                        !interest.is_never()
+                    }
+                    && ::tracing::__macro_support::__is_enabled(CALLSITE.metadata(), interest)
+                {
+                    let meta = CALLSITE.metadata();
+                    ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                } else {
+                    let span = ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                    {};
+                    span
+                }
+            };
+            let __tracing_guard__ = __within_span__.enter();
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_initialize (n)
+        }
+    }
+    impl<T: Config> frame_support::traits::OnRuntimeUpgrade for Pallet<T> {
+        fn on_runtime_upgrade() -> frame_support::weights::Weight {
+            let __within_span__ = {
+                use ::tracing::__macro_support::Callsite as _;
+                static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                    static META: ::tracing::Metadata<'static> = {
+                        ::tracing_core::metadata::Metadata::new(
+                            "on_runtime_update",
+                            "dispatch_pallet::pallet",
+                            ::tracing::Level::TRACE,
+                            Some("src/lib.rs"),
+                            Some(11u32),
+                            Some("dispatch_pallet::pallet"),
+                            ::tracing_core::field::FieldSet::new(
+                                &[],
+                                ::tracing_core::callsite::Identifier(&CALLSITE),
+                            ),
+                            ::tracing::metadata::Kind::SPAN,
+                        )
+                    };
+                    ::tracing::callsite::DefaultCallsite::new(&META)
+                };
+                let mut interest = ::tracing::subscriber::Interest::never();
+                if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                    && ::tracing::Level::TRACE <= ::tracing::level_filters::LevelFilter::current()
+                    && {
+                        interest = CALLSITE.interest();
+                        !interest.is_never()
+                    }
+                    && ::tracing::__macro_support::__is_enabled(CALLSITE.metadata(), interest)
+                {
+                    let meta = CALLSITE.metadata();
+                    ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                } else {
+                    let span = ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                    {};
+                    span
+                }
+            };
+            let __tracing_guard__ = __within_span__.enter();
+            let pallet_name = < < T as frame_system :: Config > :: PalletInfo as frame_support :: traits :: PalletInfo > :: name :: < Self > () . unwrap_or ("<unknown pallet name>") ;
+            {
+                let lvl = ::log::Level::Info;
+                if lvl <= ::log::STATIC_MAX_LEVEL && lvl <= ::log::max_level() {
+                    ::log::__private_api_log(
+                        ::core::fmt::Arguments::new_v1(
+                            &["\u{2705} no migration for "],
+                            &[::core::fmt::ArgumentV1::new_display(&pallet_name)],
+                        ),
+                        lvl,
+                        &(
+                            frame_support::LOG_TARGET,
+                            "dispatch_pallet::pallet",
+                            "src/lib.rs",
+                            11u32,
+                        ),
+                        ::log::__private_api::Option::None,
+                    );
+                }
+            };
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_runtime_upgrade ()
+        }
+    }
+    impl<T: Config> frame_support::traits::OffchainWorker<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn offchain_worker(n: <T as frame_system::Config>::BlockNumber) {
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: offchain_worker (n)
+        }
+    }
+    impl<T: Config> frame_support::traits::IntegrityTest for Pallet<T> {
+        fn integrity_test() {
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: integrity_test ()
+        }
+    }
+    #[doc(hidden)]
+    pub mod __substrate_genesis_config_check {
+        #[doc(hidden)]
+        pub use __is_genesis_config_defined_4 as is_genesis_config_defined;
+        #[doc(hidden)]
+        pub use __is_std_enabled_for_genesis_4 as is_std_enabled_for_genesis;
+    }
+    #[doc(hidden)]
+    pub mod __substrate_origin_check {
+        #[doc(hidden)]
+        pub use __is_origin_part_defined_5 as is_origin_part_defined;
+    }
+    #[doc(hidden)]
+    pub mod __substrate_validate_unsigned_check {
+        #[doc(hidden)]
+        pub use __is_validate_unsigned_part_defined_6 as is_validate_unsigned_part_defined;
+    }
+    pub use __tt_default_parts_7 as tt_default_parts;
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch-pallet/src/lib.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch-pallet/src/lib.rs
new file mode 100644
index 00000000..f27bdfef
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch-pallet/src/lib.rs
@@ -0,0 +1,44 @@
+#![cfg_attr(not(feature = "std"), no_std)]
+pub use pallet::*;
+
+#[frame_support::pallet]
+pub mod pallet {
+  use codec::{Encode, Decode};
+  // TODO: maybe look into these preludes.
+  use frame_support::{pallet_prelude::*, dispatch::{DispatchResultWithPostInfo, PostDispatchInfo}, weights::Pays};
+  use frame_system::pallet_prelude::*;
+
+  #[pallet::config]
+  pub trait Config: frame_system::Config {}
+
+  #[pallet::pallet]
+  #[pallet::without_storage_info]
+  pub struct Pallet<T>(PhantomData<T>);
+
+  #[derive(Encode, Decode, Debug, PartialEq, Eq, Clone, TypeInfo)]
+  pub struct TransferConfig<AccountId> {
+    from: AccountId,
+    to: AccountId,
+    amount: u64
+  }
+
+  #[pallet::call]
+  impl<T: Config> Pallet<T> {
+    #[pallet::weight(42)]
+    pub fn first_transaction(_origin: OriginFor<T>, _inc: u32) -> DispatchResult {
+      Ok(())
+    }
+
+    #[pallet::weight(42)]
+    pub fn transfer(_origin: OriginFor<T>, config: TransferConfig<T::AccountId>) -> DispatchResultWithPostInfo {
+      if config.amount == 42 {
+        Ok(PostDispatchInfo {
+          actual_weight: Some(0),
+          pays_fee: Pays::No,
+        })
+      } else {
+        Ok(None.into())
+      }
+    }
+  }
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch.rs
new file mode 100644
index 00000000..2cbc8595
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/dispatch.rs
@@ -0,0 +1,23 @@
+impl ::Dispatchable for Call
+{
+    type Origin = Origin;
+    type Config = Call;
+    type Info = ::DispatchInfo;
+    type PostInfo = PostDispatchInfo;
+    fn dispatch (self, origin : Origin) -> dispatch::DispatchResultWithPostInfo {
+        if ! <Self::Origin as OriginTrait>::filter_call(&origin, &self) {
+          return Result :: Err (frame_system :: Error :: < Runtime > :: CallFiltered . into ()) ;
+        }
+        UnfilteredDispatchable::dispatch_bypass_filter(self, origin)
+    }
+}
+impl UnfilteredDispatchable for Call
+{
+    type Origin = Origin;
+    fn dispatch_bypass_filter (self , origin: Origin) -> DispatchResultWithPostInfo {
+        match self {
+          Call :: System (call) => UnfilteredDispatchable :: dispatch_bypass_filter (call , origin) ,
+          Call :: SimplePallet (call) => UnfilteredDispatchable :: dispatch_bypass_filter (call , origin) ,
+        }
+    }
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/expanded.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/expanded.rs
new file mode 100644
index 00000000..770914ca
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/expanded.rs
@@ -0,0 +1,2282 @@
+#![feature(prelude_import)]
+#![recursion_limit = "256"]
+#[prelude_import]
+use std::prelude::rust_2021::*;
+#[macro_use]
+extern crate std;
+pub use frame_support::{
+    construct_runtime, parameter_types,
+    traits::{
+        ConstU128, ConstU32, ConstU64, ConstU8, KeyOwnerProofSystem, Randomness, StorageInfo,
+    },
+    weights::{
+        constants::{BlockExecutionWeight, ExtrinsicBaseWeight, RocksDbWeight, WEIGHT_PER_SECOND},
+        IdentityFee, Weight,
+    },
+    StorageValue,
+};
+use sp_api::impl_runtime_apis;
+#[cfg(any(feature = "std", test))]
+pub use sp_runtime::BuildStorage;
+use sp_runtime::{
+    create_runtime_str, generic,
+    traits::{AccountIdLookup, BlakeTwo256, Block as BlockT, IdentifyAccount, Verify},
+    transaction_validity::{TransactionSource, TransactionValidity},
+    ApplyExtrinsicResult, MultiSignature,
+};
+pub use sp_runtime::{Perbill, Permill};
+use sp_std::prelude::*;
+use sp_version::RuntimeVersion;
+pub type Signature = MultiSignature;
+pub type AccountId = <<Signature as Verify>::Signer as IdentifyAccount>::AccountId;
+pub type Hash = sp_core::H256;
+pub type BlockNumber = u32;
+pub type Balance = u128;
+pub type Index = u32;
+pub const VERSION: RuntimeVersion = RuntimeVersion {
+    spec_name: { ::sp_runtime::RuntimeString::Borrowed("simple-runtime") },
+    impl_name: { ::sp_runtime::RuntimeString::Borrowed("simple-runtime") },
+    authoring_version: 1,
+    spec_version: 100,
+    impl_version: 1,
+    apis: RUNTIME_API_VERSIONS,
+    transaction_version: 1,
+    state_version: 1,
+};
+const _: () = {};
+const NORMAL_DISPATCH_RATIO: Perbill = Perbill::one();
+pub struct Version;
+impl Version {
+    /// Returns the value of this parameter type.
+    pub const fn get() -> RuntimeVersion {
+        VERSION
+    }
+}
+impl<I: From<RuntimeVersion>> ::frame_support::traits::Get<I> for Version {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for Version {
+    type Type = RuntimeVersion;
+    fn get() -> RuntimeVersion {
+        Self::get()
+    }
+}
+pub struct BlockHashCount;
+impl BlockHashCount {
+    /// Returns the value of this parameter type.
+    pub const fn get() -> BlockNumber {
+        2400
+    }
+}
+impl<I: From<BlockNumber>> ::frame_support::traits::Get<I> for BlockHashCount {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for BlockHashCount {
+    type Type = BlockNumber;
+    fn get() -> BlockNumber {
+        Self::get()
+    }
+}
+pub struct BlockWeights;
+impl BlockWeights {
+    /// Returns the value of this parameter type.
+    pub fn get() -> frame_system::limits::BlockWeights {
+        frame_system::limits::BlockWeights::with_sensible_defaults(
+            2 * WEIGHT_PER_SECOND,
+            NORMAL_DISPATCH_RATIO,
+        )
+    }
+}
+impl<I: From<frame_system::limits::BlockWeights>> ::frame_support::traits::Get<I> for BlockWeights {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for BlockWeights {
+    type Type = frame_system::limits::BlockWeights;
+    fn get() -> frame_system::limits::BlockWeights {
+        Self::get()
+    }
+}
+pub struct BlockLength;
+impl BlockLength {
+    /// Returns the value of this parameter type.
+    pub fn get() -> frame_system::limits::BlockLength {
+        frame_system::limits::BlockLength::max_with_normal_ratio(
+            5 * 1024 * 1024,
+            NORMAL_DISPATCH_RATIO,
+        )
+    }
+}
+impl<I: From<frame_system::limits::BlockLength>> ::frame_support::traits::Get<I> for BlockLength {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for BlockLength {
+    type Type = frame_system::limits::BlockLength;
+    fn get() -> frame_system::limits::BlockLength {
+        Self::get()
+    }
+}
+pub struct SS58Prefix;
+impl SS58Prefix {
+    /// Returns the value of this parameter type.
+    pub const fn get() -> u8 {
+        42
+    }
+}
+impl<I: From<u8>> ::frame_support::traits::Get<I> for SS58Prefix {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for SS58Prefix {
+    type Type = u8;
+    fn get() -> u8 {
+        Self::get()
+    }
+}
+impl frame_system::Config for Runtime {
+    type AccountId = AccountId;
+    type Index = Index;
+    type Hash = Hash;
+    type Hashing = BlakeTwo256;
+    type Version = Version;
+    type Call = Call;
+    type Origin = Origin;
+    type BaseCallFilter = frame_support::traits::Everything;
+    type BlockWeights = BlockWeights;
+    type BlockLength = BlockLength;
+    type Lookup = AccountIdLookup<AccountId, ()>;
+    type BlockNumber = BlockNumber;
+    type Header = generic::Header<BlockNumber, BlakeTwo256>;
+    type Event = Event;
+    type BlockHashCount = BlockHashCount;
+    type DbWeight = RocksDbWeight;
+    type PalletInfo = PalletInfo;
+    type OnNewAccount = ();
+    type OnKilledAccount = ();
+    type AccountData = ();
+    type SystemWeightInfo = ();
+    type SS58Prefix = SS58Prefix;
+    type OnSetCode = ();
+    type MaxConsumers = frame_support::traits::ConstU32<16>;
+}
+impl simple_pallet::pallet::Config for Runtime {
+    type ValueType = u64;
+    const MAX_VALUE: u32 = 1000;
+    fn on_value_update(_: Self::ValueType) {
+        ::core::panicking::panic("not yet implemented");
+    }
+}
+impl transfer_pallet::Config for Runtime {
+    type MinimumBalance = frame_support::traits::ConstU128<100>;
+}
+pub mod opaque {
+    use super::BlockNumber;
+    pub use sp_runtime::OpaqueExtrinsic;
+    use sp_runtime::{generic, traits::BlakeTwo256};
+    pub type Header = generic::Header<BlockNumber, BlakeTwo256>;
+    pub type Block = generic::Block<Header, OpaqueExtrinsic>;
+    pub type BlockId = generic::BlockId<Block>;
+}
+#[doc(hidden)]
+mod sp_api_hidden_includes_construct_runtime {
+    pub extern crate frame_support as hidden_include;
+}
+const _: () = {
+    #[allow(unused)]
+    type __hidden_use_of_unchecked_extrinsic = UncheckedExtrinsic;
+};
+pub struct Runtime;
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::clone::Clone for Runtime {
+    #[inline]
+    fn clone(&self) -> Runtime {
+        {
+            *self
+        }
+    }
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::marker::Copy for Runtime {}
+impl ::core::marker::StructuralPartialEq for Runtime {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::cmp::PartialEq for Runtime {
+    #[inline]
+    fn eq(&self, other: &Runtime) -> bool {
+        true
+    }
+}
+impl ::core::marker::StructuralEq for Runtime {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::cmp::Eq for Runtime {
+    #[inline]
+    #[doc(hidden)]
+    #[no_coverage]
+    fn assert_receiver_is_total_eq(&self) -> () {
+        {}
+    }
+}
+impl core::fmt::Debug for Runtime {
+    fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+        fmt.debug_tuple("Runtime").finish()
+    }
+}
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    impl ::scale_info::TypeInfo for Runtime {
+        type Identity = Self;
+        fn type_info() -> ::scale_info::Type {
+            ::scale_info::Type::builder()
+                .path(::scale_info::Path::new("Runtime", "simple_runtime"))
+                .type_params(::alloc::vec::Vec::new())
+                .docs(&[])
+                .composite(::scale_info::build::Fields::unit())
+        }
+    };
+};
+impl self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: GetNodeBlockType for Runtime { type NodeBlock = opaque :: Block ; }
+impl self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: GetRuntimeBlockType for Runtime { type RuntimeBlock = Block ; }
+#[allow(non_camel_case_types)]
+pub enum Event {
+    #[codec(index = 0u8)]
+    System(frame_system::Event<Runtime>),
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::clone::Clone for Event {
+    #[inline]
+    fn clone(&self) -> Event {
+        match (&*self,) {
+            (&Event::System(ref __self_0),) => {
+                Event::System(::core::clone::Clone::clone(&*__self_0))
+            }
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+impl ::core::marker::StructuralPartialEq for Event {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::cmp::PartialEq for Event {
+    #[inline]
+    fn eq(&self, other: &Event) -> bool {
+        match (&*self, &*other) {
+            (&Event::System(ref __self_0), &Event::System(ref __arg_1_0)) => {
+                *__self_0 == *__arg_1_0
+            }
+        }
+    }
+    #[inline]
+    fn ne(&self, other: &Event) -> bool {
+        match (&*self, &*other) {
+            (&Event::System(ref __self_0), &Event::System(ref __arg_1_0)) => {
+                *__self_0 != *__arg_1_0
+            }
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+impl ::core::marker::StructuralEq for Event {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::cmp::Eq for Event {
+    #[inline]
+    #[doc(hidden)]
+    #[no_coverage]
+    fn assert_receiver_is_total_eq(&self) -> () {
+        {
+            let _: ::core::cmp::AssertParamIsEq<frame_system::Event<Runtime>>;
+        }
+    }
+}
+#[allow(deprecated)]
+const _: () = {
+    #[allow(non_camel_case_types)]
+    #[automatically_derived]
+    impl ::codec::Encode for Event {
+        fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+            &self,
+            __codec_dest_edqy: &mut __CodecOutputEdqy,
+        ) {
+            match *self {
+                Event::System(ref aa) => {
+                    __codec_dest_edqy.push_byte(0u8 as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                _ => (),
+            }
+        }
+    }
+    #[automatically_derived]
+    impl ::codec::EncodeLike for Event {}
+};
+#[allow(deprecated)]
+const _: () = {
+    #[allow(non_camel_case_types)]
+    #[automatically_derived]
+    impl ::codec::Decode for Event {
+        fn decode<__CodecInputEdqy: ::codec::Input>(
+            __codec_input_edqy: &mut __CodecInputEdqy,
+        ) -> ::core::result::Result<Self, ::codec::Error> {
+            match __codec_input_edqy
+                .read_byte()
+                .map_err(|e| e.chain("Could not decode `Event`, failed to read variant byte"))?
+            {
+                __codec_x_edqy if __codec_x_edqy == 0u8 as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(Event::System({
+                        let __codec_res_edqy =
+                            <frame_system::Event<Runtime> as ::codec::Decode>::decode(
+                                __codec_input_edqy,
+                            );
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `Event::System.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                _ => ::core::result::Result::Err(<_ as ::core::convert::Into<_>>::into(
+                    "Could not decode `Event`, variant doesn't exist",
+                )),
+            }
+        }
+    }
+};
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    impl ::scale_info::TypeInfo for Event {
+        type Identity = Self;
+        fn type_info() -> ::scale_info::Type {
+            ::scale_info::Type::builder()
+                .path(::scale_info::Path::new("Event", "simple_runtime"))
+                .type_params(::alloc::vec::Vec::new())
+                .docs(&[])
+                .variant(::scale_info::build::Variants::new().variant("System", |v| {
+                    v.index(0u8 as ::core::primitive::u8)
+                        .fields(::scale_info::build::Fields::unnamed().field(|f| {
+                            f.ty::<frame_system::Event<Runtime>>()
+                                .type_name("frame_system::Event<Runtime>")
+                                .docs(&[])
+                        }))
+                        .docs(&[])
+                }))
+        }
+    };
+};
+impl core::fmt::Debug for Event {
+    fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+        match self {
+            Self::System(ref a0) => fmt.debug_tuple("Event::System").field(a0).finish(),
+            _ => Ok(()),
+        }
+    }
+}
+impl From<frame_system::Event<Runtime>> for Event {
+    fn from(x: frame_system::Event<Runtime>) -> Self {
+        Event::System(x)
+    }
+}
+impl TryInto<frame_system::Event<Runtime>> for Event {
+    type Error = ();
+    fn try_into(
+        self,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::result::Result<
+        frame_system::Event<Runtime>,
+        Self::Error,
+    > {
+        match self {
+            Self::System(evt) => Ok(evt),
+            _ => Err(()),
+        }
+    }
+}
+/// The runtime origin type representing the origin of a call.
+///
+/// Origin is always created with the base filter configured in [`frame_system::Config::BaseCallFilter`].
+pub struct Origin {
+    caller: OriginCaller,
+    filter: self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::rc::Rc<
+        Box<dyn Fn(&<Runtime as frame_system::Config>::Call) -> bool>,
+    >,
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::clone::Clone for Origin {
+    #[inline]
+    fn clone(&self) -> Origin {
+        Origin {
+            caller: ::core::clone::Clone::clone(&self.caller),
+            filter: ::core::clone::Clone::clone(&self.filter),
+        }
+    }
+}
+#[cfg(feature = "std")]
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::fmt::Debug for Origin {
+    fn fmt(
+        &self,
+        fmt : & mut self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: fmt :: Formatter,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::result::Result<
+        (),
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::fmt::Error,
+    > {
+        fmt.debug_struct("Origin")
+            .field("caller", &self.caller)
+            .field("filter", &"[function ptr]")
+            .finish()
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::OriginTrait
+    for Origin
+{
+    type Call = <Runtime as frame_system::Config>::Call;
+    type PalletsOrigin = OriginCaller;
+    type AccountId = <Runtime as frame_system::Config>::AccountId;
+    fn add_filter(&mut self, filter: impl Fn(&Self::Call) -> bool + 'static) {
+        let f = self.filter.clone();
+        self.filter =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::rc::Rc::new(
+                Box::new(move |call| f(call) && filter(call)),
+            );
+    }
+    fn reset_filter(&mut self) {
+        let filter = < < Runtime as frame_system :: Config > :: BaseCallFilter as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: Contains < < Runtime as frame_system :: Config > :: Call > > :: contains ;
+        self.filter =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::rc::Rc::new(
+                Box::new(filter),
+            );
+    }
+    fn set_caller_from(&mut self, other: impl Into<Self>) {
+        self.caller = other.into().caller;
+    }
+    fn filter_call(&self, call: &Self::Call) -> bool {
+        match self.caller {
+            OriginCaller::system(frame_system::Origin::<Runtime>::Root) => true,
+            _ => (self.filter)(call),
+        }
+    }
+    fn caller(&self) -> &Self::PalletsOrigin {
+        &self.caller
+    }
+    fn try_with_caller<R>(
+        mut self,
+        f: impl FnOnce(Self::PalletsOrigin) -> Result<R, Self::PalletsOrigin>,
+    ) -> Result<R, Self> {
+        match f(self.caller) {
+            Ok(r) => Ok(r),
+            Err(caller) => {
+                self.caller = caller;
+                Err(self)
+            }
+        }
+    }
+    fn none() -> Self {
+        frame_system::RawOrigin::None.into()
+    }
+    fn root() -> Self {
+        frame_system::RawOrigin::Root.into()
+    }
+    fn signed(by: Self::AccountId) -> Self {
+        frame_system::RawOrigin::Signed(by).into()
+    }
+    fn as_signed(self) -> Option<Self::AccountId> {
+        match self.caller {
+            OriginCaller::system(frame_system::RawOrigin::Signed(by)) => Some(by),
+            _ => None,
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+pub enum OriginCaller {
+    #[codec(index = 0u8)]
+    system(frame_system::Origin<Runtime>),
+    #[allow(dead_code)]
+    Void(self::sp_api_hidden_includes_construct_runtime::hidden_include::Void),
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::clone::Clone for OriginCaller {
+    #[inline]
+    fn clone(&self) -> OriginCaller {
+        match (&*self,) {
+            (&OriginCaller::system(ref __self_0),) => {
+                OriginCaller::system(::core::clone::Clone::clone(&*__self_0))
+            }
+            (&OriginCaller::Void(ref __self_0),) => {
+                OriginCaller::Void(::core::clone::Clone::clone(&*__self_0))
+            }
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+impl ::core::marker::StructuralPartialEq for OriginCaller {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::cmp::PartialEq for OriginCaller {
+    #[inline]
+    fn eq(&self, other: &OriginCaller) -> bool {
+        {
+            let __self_vi = ::core::intrinsics::discriminant_value(&*self);
+            let __arg_1_vi = ::core::intrinsics::discriminant_value(&*other);
+            if __self_vi == __arg_1_vi {
+                match (&*self, &*other) {
+                    (&OriginCaller::system(ref __self_0), &OriginCaller::system(ref __arg_1_0)) => {
+                        *__self_0 == *__arg_1_0
+                    }
+                    (&OriginCaller::Void(ref __self_0), &OriginCaller::Void(ref __arg_1_0)) => {
+                        *__self_0 == *__arg_1_0
+                    }
+                    _ => unsafe { ::core::intrinsics::unreachable() },
+                }
+            } else {
+                false
+            }
+        }
+    }
+    #[inline]
+    fn ne(&self, other: &OriginCaller) -> bool {
+        {
+            let __self_vi = ::core::intrinsics::discriminant_value(&*self);
+            let __arg_1_vi = ::core::intrinsics::discriminant_value(&*other);
+            if __self_vi == __arg_1_vi {
+                match (&*self, &*other) {
+                    (&OriginCaller::system(ref __self_0), &OriginCaller::system(ref __arg_1_0)) => {
+                        *__self_0 != *__arg_1_0
+                    }
+                    (&OriginCaller::Void(ref __self_0), &OriginCaller::Void(ref __arg_1_0)) => {
+                        *__self_0 != *__arg_1_0
+                    }
+                    _ => unsafe { ::core::intrinsics::unreachable() },
+                }
+            } else {
+                true
+            }
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+impl ::core::marker::StructuralEq for OriginCaller {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::cmp::Eq for OriginCaller {
+    #[inline]
+    #[doc(hidden)]
+    #[no_coverage]
+    fn assert_receiver_is_total_eq(&self) -> () {
+        {
+            let _: ::core::cmp::AssertParamIsEq<frame_system::Origin<Runtime>>;
+            let _: ::core::cmp::AssertParamIsEq<
+                self::sp_api_hidden_includes_construct_runtime::hidden_include::Void,
+            >;
+        }
+    }
+}
+impl core::fmt::Debug for OriginCaller {
+    fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+        match self {
+            Self::system(ref a0) => fmt.debug_tuple("OriginCaller::system").field(a0).finish(),
+            Self::Void(ref a0) => fmt.debug_tuple("OriginCaller::Void").field(a0).finish(),
+            _ => Ok(()),
+        }
+    }
+}
+#[allow(deprecated)]
+const _: () = {
+    #[allow(non_camel_case_types)]
+    #[automatically_derived]
+    impl ::codec::Encode for OriginCaller {
+        fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+            &self,
+            __codec_dest_edqy: &mut __CodecOutputEdqy,
+        ) {
+            match *self {
+                OriginCaller::system(ref aa) => {
+                    __codec_dest_edqy.push_byte(0u8 as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                OriginCaller::Void(ref aa) => {
+                    __codec_dest_edqy.push_byte(1usize as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                _ => (),
+            }
+        }
+    }
+    #[automatically_derived]
+    impl ::codec::EncodeLike for OriginCaller {}
+};
+#[allow(deprecated)]
+const _: () = {
+    #[allow(non_camel_case_types)]
+    #[automatically_derived]
+    impl ::codec::Decode for OriginCaller {
+        fn decode<__CodecInputEdqy: ::codec::Input>(
+            __codec_input_edqy: &mut __CodecInputEdqy,
+        ) -> ::core::result::Result<Self, ::codec::Error> {
+            match __codec_input_edqy.read_byte().map_err(|e| {
+                e.chain("Could not decode `OriginCaller`, failed to read variant byte")
+            })? {
+                __codec_x_edqy if __codec_x_edqy == 0u8 as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(OriginCaller::system({
+                        let __codec_res_edqy =
+                            <frame_system::Origin<Runtime> as ::codec::Decode>::decode(
+                                __codec_input_edqy,
+                            );
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `OriginCaller::system.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                __codec_x_edqy if __codec_x_edqy == 1usize as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(OriginCaller::Void({
+                        let __codec_res_edqy = < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: Void as :: codec :: Decode > :: decode (__codec_input_edqy) ;
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `OriginCaller::Void.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                _ => ::core::result::Result::Err(<_ as ::core::convert::Into<_>>::into(
+                    "Could not decode `OriginCaller`, variant doesn't exist",
+                )),
+            }
+        }
+    }
+};
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    impl ::scale_info::TypeInfo for OriginCaller {
+        type Identity = Self;
+        fn type_info() -> ::scale_info::Type {
+            :: scale_info :: Type :: builder () . path (:: scale_info :: Path :: new ("OriginCaller" , "simple_runtime")) . type_params (:: alloc :: vec :: Vec :: new ()) . docs (& []) . variant (:: scale_info :: build :: Variants :: new () . variant ("system" , | v | v . index (0u8 as :: core :: primitive :: u8) . fields (:: scale_info :: build :: Fields :: unnamed () . field (| f | f . ty :: < frame_system :: Origin < Runtime > > () . type_name ("frame_system::Origin<Runtime>") . docs (& []))) . docs (& [])) . variant ("Void" , | v | v . index (1usize as :: core :: primitive :: u8) . fields (:: scale_info :: build :: Fields :: unnamed () . field (| f | f . ty :: < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: Void > () . type_name ("self::sp_api_hidden_includes_construct_runtime::hidden_include::Void") . docs (& []))) . docs (& [])))
+        }
+    };
+};
+const _: () = {
+    impl ::codec::MaxEncodedLen for OriginCaller {
+        fn max_encoded_len() -> ::core::primitive::usize {
+            0_usize . max (0_usize . saturating_add (< frame_system :: Origin < Runtime > > :: max_encoded_len ())) . max (0_usize . saturating_add (< self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: Void > :: max_encoded_len ())) . saturating_add (1)
+        }
+    }
+};
+#[allow(dead_code)]
+impl Origin {
+    /// Create with system none origin and [`frame_system::Config::BaseCallFilter`].
+    pub fn none() -> Self {
+        < Origin as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait > :: none ()
+    }
+    /// Create with system root origin and [`frame_system::Config::BaseCallFilter`].
+    pub fn root() -> Self {
+        < Origin as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait > :: root ()
+    }
+    /// Create with system signed origin and [`frame_system::Config::BaseCallFilter`].
+    pub fn signed(by: <Runtime as frame_system::Config>::AccountId) -> Self {
+        < Origin as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait > :: signed (by)
+    }
+}
+impl From<frame_system::Origin<Runtime>> for OriginCaller {
+    fn from(x: frame_system::Origin<Runtime>) -> Self {
+        OriginCaller::system(x)
+    }
+}
+impl TryFrom<OriginCaller> for frame_system::Origin<Runtime> {
+    type Error = OriginCaller;
+    fn try_from(
+        x: OriginCaller,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::result::Result<
+        frame_system::Origin<Runtime>,
+        OriginCaller,
+    > {
+        if let OriginCaller::system(l) = x {
+            Ok(l)
+        } else {
+            Err(x)
+        }
+    }
+}
+impl From<frame_system::Origin<Runtime>> for Origin {
+    /// Convert to runtime origin, using as filter: [`frame_system::Config::BaseCallFilter`].
+    fn from(x: frame_system::Origin<Runtime>) -> Self {
+        let o: OriginCaller = x.into();
+        o.into()
+    }
+}
+impl From<OriginCaller> for Origin {
+    fn from(x: OriginCaller) -> Self {
+        let mut o = Origin {
+            caller: x,
+            filter:
+                self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::rc::Rc::new(
+                    Box::new(|_| true),
+                ),
+        };
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait :: reset_filter (& mut o) ;
+        o
+    }
+}
+impl From<Origin>
+    for self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::result::Result<
+        frame_system::Origin<Runtime>,
+        Origin,
+    >
+{
+    /// NOTE: converting to pallet origin loses the origin filter information.
+    fn from(val: Origin) -> Self {
+        if let OriginCaller::system(l) = val.caller {
+            Ok(l)
+        } else {
+            Err(val)
+        }
+    }
+}
+impl From<Option<<Runtime as frame_system::Config>::AccountId>> for Origin {
+    /// Convert to runtime origin with caller being system signed or none and use filter [`frame_system::Config::BaseCallFilter`].
+    fn from(x: Option<<Runtime as frame_system::Config>::AccountId>) -> Self {
+        <frame_system::Origin<Runtime>>::from(x).into()
+    }
+}
+pub type System = frame_system::Pallet<Runtime>;
+pub type SimplePallet = simple_pallet::Pallet<Runtime>;
+pub type TransferPallet = transfer_pallet::Pallet<Runtime>;
+/// All pallets included in the runtime as a nested tuple of types.
+#[deprecated(
+    note = "The type definition has changed from representing all pallets \
+			excluding system, in reversed order to become the representation of all pallets \
+			including system pallet in regular order. For this reason it is encouraged to use \
+			explicitly one of `AllPalletsWithSystem`, `AllPalletsWithoutSystem`, \
+			`AllPalletsWithSystemReversed`, `AllPalletsWithoutSystemReversed`. \
+			Note that the type `frame_executive::Executive` expects one of `AllPalletsWithSystem` \
+			, `AllPalletsWithSystemReversed`, `AllPalletsReversedWithSystemFirst`. More details in \
+			https://github.com/paritytech/substrate/pull/10043"
+)]
+pub type AllPallets = AllPalletsWithSystem;
+/// All pallets included in the runtime as a nested tuple of types.
+pub type AllPalletsWithSystem = (System, SimplePallet, TransferPallet,);
+/// All pallets included in the runtime as a nested tuple of types.
+/// Excludes the System pallet.
+pub type AllPalletsWithoutSystem = ((SimplePallet, (TransferPallet,)));
+/// All pallets included in the runtime as a nested tuple of types in reversed order.
+/// Excludes the System pallet.
+pub type AllPalletsWithoutSystemReversed = ((TransferPallet, (SimplePallet,)));
+/// All pallets included in the runtime as a nested tuple of types in reversed order.
+pub type AllPalletsWithSystemReversed = ((TransferPallet, (SimplePallet, (System,))));
+/// All pallets included in the runtime as a nested tuple of types in reversed order.
+/// With the system pallet first.
+pub type AllPalletsReversedWithSystemFirst = (System, AllPalletsWithoutSystemReversed);
+/// Provides an implementation of `PalletInfo` to provide information
+/// about the pallet setup in the runtime.
+pub struct PalletInfo;
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::PalletInfo
+    for PalletInfo
+{
+    fn index<P: 'static>() -> Option<usize> {
+        let type_id =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::any::TypeId::of::<
+                P,
+            >();
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < System > () { return Some (0usize) }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < SimplePallet > () { return Some (1usize) }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < TransferPallet > () { return Some (2usize) }
+        None
+    }
+    fn name<P: 'static>() -> Option<&'static str> {
+        let type_id =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::any::TypeId::of::<
+                P,
+            >();
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < System > () { return Some ("System") }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < SimplePallet > () { return Some ("SimplePallet") }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < TransferPallet > () { return Some ("TransferPallet") }
+        None
+    }
+    fn module_name<P: 'static>() -> Option<&'static str> {
+        let type_id =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::any::TypeId::of::<
+                P,
+            >();
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < System > () { return Some ("frame_system") }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < SimplePallet > () { return Some ("simple_pallet") }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < TransferPallet > () { return Some ("transfer_pallet") }
+        None
+    }
+    fn crate_version<P: 'static>(
+    ) -> Option<self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::CrateVersion>
+    {
+        let type_id =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::any::TypeId::of::<
+                P,
+            >();
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < System > () { return Some (< frame_system :: Pallet < Runtime > as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: PalletInfoAccess > :: crate_version ()) }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < SimplePallet > () { return Some (< simple_pallet :: Pallet < Runtime > as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: PalletInfoAccess > :: crate_version ()) }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < TransferPallet > () { return Some (< transfer_pallet :: Pallet < Runtime > as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: PalletInfoAccess > :: crate_version ()) }
+        None
+    }
+}
+pub enum Call {
+    #[codec(index = 0u8)]
+    System(
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            System,
+            Runtime,
+        >,
+    ),
+    #[codec(index = 1u8)]
+    SimplePallet(
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            SimplePallet,
+            Runtime,
+        >,
+    ),
+    #[codec(index = 2u8)]
+    TransferPallet(
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            TransferPallet,
+            Runtime,
+        >,
+    ),
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::clone::Clone for Call {
+    #[inline]
+    fn clone(&self) -> Call {
+        match (&*self,) {
+            (&Call::System(ref __self_0),) => Call::System(::core::clone::Clone::clone(&*__self_0)),
+            (&Call::SimplePallet(ref __self_0),) => {
+                Call::SimplePallet(::core::clone::Clone::clone(&*__self_0))
+            }
+            (&Call::TransferPallet(ref __self_0),) => {
+                Call::TransferPallet(::core::clone::Clone::clone(&*__self_0))
+            }
+        }
+    }
+}
+impl ::core::marker::StructuralPartialEq for Call {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::cmp::PartialEq for Call {
+    #[inline]
+    fn eq(&self, other: &Call) -> bool {
+        {
+            let __self_vi = ::core::intrinsics::discriminant_value(&*self);
+            let __arg_1_vi = ::core::intrinsics::discriminant_value(&*other);
+            if __self_vi == __arg_1_vi {
+                match (&*self, &*other) {
+                    (&Call::System(ref __self_0), &Call::System(ref __arg_1_0)) => {
+                        *__self_0 == *__arg_1_0
+                    }
+                    (&Call::SimplePallet(ref __self_0), &Call::SimplePallet(ref __arg_1_0)) => {
+                        *__self_0 == *__arg_1_0
+                    }
+                    (&Call::TransferPallet(ref __self_0), &Call::TransferPallet(ref __arg_1_0)) => {
+                        *__self_0 == *__arg_1_0
+                    }
+                    _ => unsafe { ::core::intrinsics::unreachable() },
+                }
+            } else {
+                false
+            }
+        }
+    }
+    #[inline]
+    fn ne(&self, other: &Call) -> bool {
+        {
+            let __self_vi = ::core::intrinsics::discriminant_value(&*self);
+            let __arg_1_vi = ::core::intrinsics::discriminant_value(&*other);
+            if __self_vi == __arg_1_vi {
+                match (&*self, &*other) {
+                    (&Call::System(ref __self_0), &Call::System(ref __arg_1_0)) => {
+                        *__self_0 != *__arg_1_0
+                    }
+                    (&Call::SimplePallet(ref __self_0), &Call::SimplePallet(ref __arg_1_0)) => {
+                        *__self_0 != *__arg_1_0
+                    }
+                    (&Call::TransferPallet(ref __self_0), &Call::TransferPallet(ref __arg_1_0)) => {
+                        *__self_0 != *__arg_1_0
+                    }
+                    _ => unsafe { ::core::intrinsics::unreachable() },
+                }
+            } else {
+                true
+            }
+        }
+    }
+}
+impl ::core::marker::StructuralEq for Call {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::cmp::Eq for Call {
+    #[inline]
+    #[doc(hidden)]
+    #[no_coverage]
+    fn assert_receiver_is_total_eq(&self) -> () {
+        {
+            let _ : :: core :: cmp :: AssertParamIsEq < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < System , Runtime > > ;
+            let _ : :: core :: cmp :: AssertParamIsEq < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < SimplePallet , Runtime > > ;
+            let _ : :: core :: cmp :: AssertParamIsEq < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < TransferPallet , Runtime > > ;
+        }
+    }
+}
+#[allow(deprecated)]
+const _: () = {
+    #[automatically_derived]
+    impl ::codec::Encode for Call {
+        fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+            &self,
+            __codec_dest_edqy: &mut __CodecOutputEdqy,
+        ) {
+            match *self {
+                Call::System(ref aa) => {
+                    __codec_dest_edqy.push_byte(0u8 as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                Call::SimplePallet(ref aa) => {
+                    __codec_dest_edqy.push_byte(1u8 as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                Call::TransferPallet(ref aa) => {
+                    __codec_dest_edqy.push_byte(2u8 as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                _ => (),
+            }
+        }
+    }
+    #[automatically_derived]
+    impl ::codec::EncodeLike for Call {}
+};
+#[allow(deprecated)]
+const _: () = {
+    #[automatically_derived]
+    impl ::codec::Decode for Call {
+        fn decode<__CodecInputEdqy: ::codec::Input>(
+            __codec_input_edqy: &mut __CodecInputEdqy,
+        ) -> ::core::result::Result<Self, ::codec::Error> {
+            match __codec_input_edqy
+                .read_byte()
+                .map_err(|e| e.chain("Could not decode `Call`, failed to read variant byte"))?
+            {
+                __codec_x_edqy if __codec_x_edqy == 0u8 as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(Call::System({
+                        let __codec_res_edqy = < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < System , Runtime > as :: codec :: Decode > :: decode (__codec_input_edqy) ;
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `Call::System.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                __codec_x_edqy if __codec_x_edqy == 1u8 as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(Call::SimplePallet({
+                        let __codec_res_edqy = < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < SimplePallet , Runtime > as :: codec :: Decode > :: decode (__codec_input_edqy) ;
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `Call::SimplePallet.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                __codec_x_edqy if __codec_x_edqy == 2u8 as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(Call::TransferPallet({
+                        let __codec_res_edqy = < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < TransferPallet , Runtime > as :: codec :: Decode > :: decode (__codec_input_edqy) ;
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `Call::TransferPallet.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                _ => ::core::result::Result::Err(<_ as ::core::convert::Into<_>>::into(
+                    "Could not decode `Call`, variant doesn't exist",
+                )),
+            }
+        }
+    }
+};
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    impl ::scale_info::TypeInfo for Call {
+        type Identity = Self;
+        fn type_info() -> ::scale_info::Type {
+            :: scale_info :: Type :: builder () . path (:: scale_info :: Path :: new ("Call" , "simple_runtime")) . type_params (:: alloc :: vec :: Vec :: new ()) . docs (& []) . variant (:: scale_info :: build :: Variants :: new () . variant ("System" , | v | v . index (0u8 as :: core :: primitive :: u8) . fields (:: scale_info :: build :: Fields :: unnamed () . field (| f | f . ty :: < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < System , Runtime > > () . type_name ("self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch\n::CallableCallFor<System, Runtime>") . docs (& []))) . docs (& [])) . variant ("SimplePallet" , | v | v . index (1u8 as :: core :: primitive :: u8) . fields (:: scale_info :: build :: Fields :: unnamed () . field (| f | f . ty :: < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < SimplePallet , Runtime > > () . type_name ("self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch\n::CallableCallFor<SimplePallet, Runtime>") . docs (& []))) . docs (& [])) . variant ("TransferPallet" , | v | v . index (2u8 as :: core :: primitive :: u8) . fields (:: scale_info :: build :: Fields :: unnamed () . field (| f | f . ty :: < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < TransferPallet , Runtime > > () . type_name ("self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch\n::CallableCallFor<TransferPallet, Runtime>") . docs (& []))) . docs (& [])))
+        }
+    };
+};
+impl core::fmt::Debug for Call {
+    fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+        match self {
+            Self::System(ref a0) => fmt.debug_tuple("Call::System").field(a0).finish(),
+            Self::SimplePallet(ref a0) => fmt.debug_tuple("Call::SimplePallet").field(a0).finish(),
+            Self::TransferPallet(ref a0) => {
+                fmt.debug_tuple("Call::TransferPallet").field(a0).finish()
+            }
+            _ => Ok(()),
+        }
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::GetDispatchInfo
+    for Call
+{
+    fn get_dispatch_info(
+        &self,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::DispatchInfo
+    {
+        match self {
+            Call::System(call) => call.get_dispatch_info(),
+            Call::SimplePallet(call) => call.get_dispatch_info(),
+            Call::TransferPallet(call) => call.get_dispatch_info(),
+        }
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::GetCallMetadata
+    for Call
+{
+    fn get_call_metadata(
+        &self,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallMetadata
+    {
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::GetCallName;
+        match self {
+            Call::System(call) => {
+                let function_name = call.get_call_name();
+                let pallet_name = "System";
+                self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallMetadata { function_name , pallet_name , }
+            }
+            Call::SimplePallet(call) => {
+                let function_name = call.get_call_name();
+                let pallet_name = "SimplePallet";
+                self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallMetadata { function_name , pallet_name , }
+            }
+            Call::TransferPallet(call) => {
+                let function_name = call.get_call_name();
+                let pallet_name = "TransferPallet";
+                self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallMetadata { function_name , pallet_name , }
+            }
+        }
+    }
+    fn get_module_names() -> &'static [&'static str] {
+        &["System", "SimplePallet", "TransferPallet"]
+    }
+    fn get_call_names(module: &str) -> &'static [&'static str] {
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::{
+            Callable, GetCallName,
+        };
+        match module {
+            "System" => <<System as Callable<Runtime>>::Call as GetCallName>::get_call_names(),
+            "SimplePallet" => {
+                <<SimplePallet as Callable<Runtime>>::Call as GetCallName>::get_call_names()
+            }
+            "TransferPallet" => {
+                <<TransferPallet as Callable<Runtime>>::Call as GetCallName>::get_call_names()
+            }
+            _ => ::core::panicking::panic("internal error: entered unreachable code"),
+        }
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::Dispatchable
+    for Call
+{
+    type Origin = Origin;
+    type Config = Call;
+    type Info =
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::weights::DispatchInfo;
+    type PostInfo =
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::weights::PostDispatchInfo;    fn dispatch (self , origin : Origin) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: DispatchResultWithPostInfo{
+        if ! < Self :: Origin as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait > :: filter_call (& origin , & self) { return self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: result :: Result :: Err (frame_system :: Error :: < Runtime > :: CallFiltered . into ()) ; }
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: UnfilteredDispatchable :: dispatch_bypass_filter (self , origin)
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::UnfilteredDispatchable
+    for Call
+{
+    type Origin = Origin;    fn dispatch_bypass_filter (self , origin : Origin) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: DispatchResultWithPostInfo{
+        match self { Call :: System (call) => self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: UnfilteredDispatchable :: dispatch_bypass_filter (call , origin) , Call :: SimplePallet (call) => self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: UnfilteredDispatchable :: dispatch_bypass_filter (call , origin) , Call :: TransferPallet (call) => self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: UnfilteredDispatchable :: dispatch_bypass_filter (call , origin) , }
+    }
+}
+impl self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: DispatchableWithStorageLayer for Call { type Origin = Origin ; fn dispatch_with_storage_layer (self , origin : Origin) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: DispatchResultWithPostInfo { self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: storage :: with_storage_layer (| | { self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: Dispatchable :: dispatch (self , origin) }) } fn dispatch_bypass_filter_with_storage_layer (self , origin : Origin) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: DispatchResultWithPostInfo { self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: storage :: with_storage_layer (| | { self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: UnfilteredDispatchable :: dispatch_bypass_filter (self , origin) }) } }
+impl
+    self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::IsSubType<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            System,
+            Runtime,
+        >,
+    > for Call
+{
+    #[allow(unreachable_patterns)]
+    fn is_sub_type(
+        &self,
+    ) -> Option<
+        &self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            System,
+            Runtime,
+        >,
+    > {
+        match self {
+            Call::System(call) => Some(call),
+            _ => None,
+        }
+    }
+}
+impl
+    From<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            System,
+            Runtime,
+        >,
+    > for Call
+{
+    fn from(
+        call : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < System , Runtime >,
+    ) -> Self {
+        Call::System(call)
+    }
+}
+impl
+    self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::IsSubType<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            SimplePallet,
+            Runtime,
+        >,
+    > for Call
+{
+    #[allow(unreachable_patterns)]
+    fn is_sub_type(
+        &self,
+    ) -> Option<
+        &self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            SimplePallet,
+            Runtime,
+        >,
+    > {
+        match self {
+            Call::SimplePallet(call) => Some(call),
+            _ => None,
+        }
+    }
+}
+impl
+    From<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            SimplePallet,
+            Runtime,
+        >,
+    > for Call
+{
+    fn from(
+        call : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < SimplePallet , Runtime >,
+    ) -> Self {
+        Call::SimplePallet(call)
+    }
+}
+impl
+    self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::IsSubType<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            TransferPallet,
+            Runtime,
+        >,
+    > for Call
+{
+    #[allow(unreachable_patterns)]
+    fn is_sub_type(
+        &self,
+    ) -> Option<
+        &self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            TransferPallet,
+            Runtime,
+        >,
+    > {
+        match self {
+            Call::TransferPallet(call) => Some(call),
+            _ => None,
+        }
+    }
+}
+impl
+    From<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            TransferPallet,
+            Runtime,
+        >,
+    > for Call
+{
+    fn from(
+        call : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < TransferPallet , Runtime >,
+    ) -> Self {
+        Call::TransferPallet(call)
+    }
+}
+impl Runtime {
+    pub fn metadata () -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: RuntimeMetadataPrefixed{
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: RuntimeMetadataLastVersion :: new (< [_] > :: into_vec (# [rustc_box] :: alloc :: boxed :: Box :: new ([self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: PalletMetadata { name : "System" , index : 0u8 , storage : Some (frame_system :: Pallet :: < Runtime > :: storage_metadata ()) , calls : Some (frame_system :: Pallet :: < Runtime > :: call_functions ()) , event : Some (self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: PalletEventMetadata { ty : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: scale_info :: meta_type :: < frame_system :: Event < Runtime > > () , }) , constants : frame_system :: Pallet :: < Runtime > :: pallet_constants_metadata () , error : frame_system :: Pallet :: < Runtime > :: error_metadata () , } , self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: PalletMetadata { name : "SimplePallet" , index : 1u8 , storage : Some (simple_pallet :: Pallet :: < Runtime > :: storage_metadata ()) , calls : Some (simple_pallet :: Pallet :: < Runtime > :: call_functions ()) , event : None , constants : simple_pallet :: Pallet :: < Runtime > :: pallet_constants_metadata () , error : simple_pallet :: Pallet :: < Runtime > :: error_metadata () , } , self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: PalletMetadata { name : "TransferPallet" , index : 2u8 , storage : Some (transfer_pallet :: Pallet :: < Runtime > :: storage_metadata ()) , calls : Some (transfer_pallet :: Pallet :: < Runtime > :: call_functions ()) , event : None , constants : transfer_pallet :: Pallet :: < Runtime > :: pallet_constants_metadata () , error : transfer_pallet :: Pallet :: < Runtime > :: error_metadata () , }])) , self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: ExtrinsicMetadata { ty : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: scale_info :: meta_type :: < UncheckedExtrinsic > () , version : < UncheckedExtrinsic as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: ExtrinsicMetadata > :: VERSION , signed_extensions : < < UncheckedExtrinsic as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: ExtrinsicMetadata > :: SignedExtensions as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: SignedExtension > :: metadata () . into_iter () . map (| meta | self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: SignedExtensionMetadata { identifier : meta . identifier , ty : meta . ty , additional_signed : meta . additional_signed , }) . collect () , } , self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: scale_info :: meta_type :: < Runtime > ()) . into ()
+    }
+}
+#[cfg(any(feature = "std", test))]
+pub type SystemConfig = frame_system::GenesisConfig;
+#[cfg(any(feature = "std", test))]
+pub type TransferPalletConfig = transfer_pallet::GenesisConfig<Runtime>;
+#[cfg(any(feature = "std", test))]
+use self::sp_api_hidden_includes_construct_runtime::hidden_include::serde as __genesis_config_serde_import__;
+#[cfg(any(feature = "std", test))]
+#[serde(rename_all = "camelCase")]
+#[serde(deny_unknown_fields)]
+#[serde(crate = "__genesis_config_serde_import__")]
+pub struct GenesisConfig {
+    pub system: SystemConfig,
+    pub transfer_pallet: TransferPalletConfig,
+}
+#[doc(hidden)]
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    use __genesis_config_serde_import__ as _serde;
+    #[automatically_derived]
+    impl __genesis_config_serde_import__::Serialize for GenesisConfig {
+        fn serialize<__S>(
+            &self,
+            __serializer: __S,
+        ) -> __genesis_config_serde_import__::__private::Result<__S::Ok, __S::Error>
+        where
+            __S: __genesis_config_serde_import__::Serializer,
+        {
+            let mut __serde_state = match _serde::Serializer::serialize_struct(
+                __serializer,
+                "GenesisConfig",
+                false as usize + 1 + 1,
+            ) {
+                _serde::__private::Ok(__val) => __val,
+                _serde::__private::Err(__err) => {
+                    return _serde::__private::Err(__err);
+                }
+            };
+            match _serde::ser::SerializeStruct::serialize_field(
+                &mut __serde_state,
+                "system",
+                &self.system,
+            ) {
+                _serde::__private::Ok(__val) => __val,
+                _serde::__private::Err(__err) => {
+                    return _serde::__private::Err(__err);
+                }
+            };
+            match _serde::ser::SerializeStruct::serialize_field(
+                &mut __serde_state,
+                "transferPallet",
+                &self.transfer_pallet,
+            ) {
+                _serde::__private::Ok(__val) => __val,
+                _serde::__private::Err(__err) => {
+                    return _serde::__private::Err(__err);
+                }
+            };
+            _serde::ser::SerializeStruct::end(__serde_state)
+        }
+    }
+};
+#[doc(hidden)]
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    use __genesis_config_serde_import__ as _serde;
+    #[automatically_derived]
+    impl<'de> __genesis_config_serde_import__::Deserialize<'de> for GenesisConfig {
+        fn deserialize<__D>(
+            __deserializer: __D,
+        ) -> __genesis_config_serde_import__::__private::Result<Self, __D::Error>
+        where
+            __D: __genesis_config_serde_import__::Deserializer<'de>,
+        {
+            #[allow(non_camel_case_types)]
+            enum __Field {
+                __field0,
+                __field1,
+            }
+            struct __FieldVisitor;
+            impl<'de> _serde::de::Visitor<'de> for __FieldVisitor {
+                type Value = __Field;
+                fn expecting(
+                    &self,
+                    __formatter: &mut _serde::__private::Formatter,
+                ) -> _serde::__private::fmt::Result {
+                    _serde::__private::Formatter::write_str(__formatter, "field identifier")
+                }
+                fn visit_u64<__E>(self, __value: u64) -> _serde::__private::Result<Self::Value, __E>
+                where
+                    __E: _serde::de::Error,
+                {
+                    match __value {
+                        0u64 => _serde::__private::Ok(__Field::__field0),
+                        1u64 => _serde::__private::Ok(__Field::__field1),
+                        _ => _serde::__private::Err(_serde::de::Error::invalid_value(
+                            _serde::de::Unexpected::Unsigned(__value),
+                            &"field index 0 <= i < 2",
+                        )),
+                    }
+                }
+                fn visit_str<__E>(
+                    self,
+                    __value: &str,
+                ) -> _serde::__private::Result<Self::Value, __E>
+                where
+                    __E: _serde::de::Error,
+                {
+                    match __value {
+                        "system" => _serde::__private::Ok(__Field::__field0),
+                        "transferPallet" => _serde::__private::Ok(__Field::__field1),
+                        _ => _serde::__private::Err(_serde::de::Error::unknown_field(
+                            __value, FIELDS,
+                        )),
+                    }
+                }
+                fn visit_bytes<__E>(
+                    self,
+                    __value: &[u8],
+                ) -> _serde::__private::Result<Self::Value, __E>
+                where
+                    __E: _serde::de::Error,
+                {
+                    match __value {
+                        b"system" => _serde::__private::Ok(__Field::__field0),
+                        b"transferPallet" => _serde::__private::Ok(__Field::__field1),
+                        _ => {
+                            let __value = &_serde::__private::from_utf8_lossy(__value);
+                            _serde::__private::Err(_serde::de::Error::unknown_field(
+                                __value, FIELDS,
+                            ))
+                        }
+                    }
+                }
+            }
+            impl<'de> _serde::Deserialize<'de> for __Field {
+                #[inline]
+                fn deserialize<__D>(
+                    __deserializer: __D,
+                ) -> _serde::__private::Result<Self, __D::Error>
+                where
+                    __D: _serde::Deserializer<'de>,
+                {
+                    _serde::Deserializer::deserialize_identifier(__deserializer, __FieldVisitor)
+                }
+            }
+            struct __Visitor<'de> {
+                marker: _serde::__private::PhantomData<GenesisConfig>,
+                lifetime: _serde::__private::PhantomData<&'de ()>,
+            }
+            impl<'de> _serde::de::Visitor<'de> for __Visitor<'de> {
+                type Value = GenesisConfig;
+                fn expecting(
+                    &self,
+                    __formatter: &mut _serde::__private::Formatter,
+                ) -> _serde::__private::fmt::Result {
+                    _serde::__private::Formatter::write_str(__formatter, "struct GenesisConfig")
+                }
+                #[inline]
+                fn visit_seq<__A>(
+                    self,
+                    mut __seq: __A,
+                ) -> _serde::__private::Result<Self::Value, __A::Error>
+                where
+                    __A: _serde::de::SeqAccess<'de>,
+                {
+                    let __field0 =
+                        match match _serde::de::SeqAccess::next_element::<SystemConfig>(&mut __seq)
+                        {
+                            _serde::__private::Ok(__val) => __val,
+                            _serde::__private::Err(__err) => {
+                                return _serde::__private::Err(__err);
+                            }
+                        } {
+                            _serde::__private::Some(__value) => __value,
+                            _serde::__private::None => {
+                                return _serde::__private::Err(_serde::de::Error::invalid_length(
+                                    0usize,
+                                    &"struct GenesisConfig with 2 elements",
+                                ));
+                            }
+                        };
+                    let __field1 = match match _serde::de::SeqAccess::next_element::<
+                        TransferPalletConfig,
+                    >(&mut __seq)
+                    {
+                        _serde::__private::Ok(__val) => __val,
+                        _serde::__private::Err(__err) => {
+                            return _serde::__private::Err(__err);
+                        }
+                    } {
+                        _serde::__private::Some(__value) => __value,
+                        _serde::__private::None => {
+                            return _serde::__private::Err(_serde::de::Error::invalid_length(
+                                1usize,
+                                &"struct GenesisConfig with 2 elements",
+                            ));
+                        }
+                    };
+                    _serde::__private::Ok(GenesisConfig {
+                        system: __field0,
+                        transfer_pallet: __field1,
+                    })
+                }
+                #[inline]
+                fn visit_map<__A>(
+                    self,
+                    mut __map: __A,
+                ) -> _serde::__private::Result<Self::Value, __A::Error>
+                where
+                    __A: _serde::de::MapAccess<'de>,
+                {
+                    let mut __field0: _serde::__private::Option<SystemConfig> =
+                        _serde::__private::None;
+                    let mut __field1: _serde::__private::Option<TransferPalletConfig> =
+                        _serde::__private::None;
+                    while let _serde::__private::Some(__key) =
+                        match _serde::de::MapAccess::next_key::<__Field>(&mut __map) {
+                            _serde::__private::Ok(__val) => __val,
+                            _serde::__private::Err(__err) => {
+                                return _serde::__private::Err(__err);
+                            }
+                        }
+                    {
+                        match __key {
+                            __Field::__field0 => {
+                                if _serde::__private::Option::is_some(&__field0) {
+                                    return _serde::__private::Err(
+                                        <__A::Error as _serde::de::Error>::duplicate_field(
+                                            "system",
+                                        ),
+                                    );
+                                }
+                                __field0 = _serde::__private::Some(
+                                    match _serde::de::MapAccess::next_value::<SystemConfig>(
+                                        &mut __map,
+                                    ) {
+                                        _serde::__private::Ok(__val) => __val,
+                                        _serde::__private::Err(__err) => {
+                                            return _serde::__private::Err(__err);
+                                        }
+                                    },
+                                );
+                            }
+                            __Field::__field1 => {
+                                if _serde::__private::Option::is_some(&__field1) {
+                                    return _serde::__private::Err(
+                                        <__A::Error as _serde::de::Error>::duplicate_field(
+                                            "transferPallet",
+                                        ),
+                                    );
+                                }
+                                __field1 = _serde::__private::Some(
+                                    match _serde::de::MapAccess::next_value::<TransferPalletConfig>(
+                                        &mut __map,
+                                    ) {
+                                        _serde::__private::Ok(__val) => __val,
+                                        _serde::__private::Err(__err) => {
+                                            return _serde::__private::Err(__err);
+                                        }
+                                    },
+                                );
+                            }
+                        }
+                    }
+                    let __field0 = match __field0 {
+                        _serde::__private::Some(__field0) => __field0,
+                        _serde::__private::None => {
+                            match _serde::__private::de::missing_field("system") {
+                                _serde::__private::Ok(__val) => __val,
+                                _serde::__private::Err(__err) => {
+                                    return _serde::__private::Err(__err);
+                                }
+                            }
+                        }
+                    };
+                    let __field1 = match __field1 {
+                        _serde::__private::Some(__field1) => __field1,
+                        _serde::__private::None => {
+                            match _serde::__private::de::missing_field("transferPallet") {
+                                _serde::__private::Ok(__val) => __val,
+                                _serde::__private::Err(__err) => {
+                                    return _serde::__private::Err(__err);
+                                }
+                            }
+                        }
+                    };
+                    _serde::__private::Ok(GenesisConfig {
+                        system: __field0,
+                        transfer_pallet: __field1,
+                    })
+                }
+            }
+            const FIELDS: &'static [&'static str] = &["system", "transferPallet"];
+            _serde::Deserializer::deserialize_struct(
+                __deserializer,
+                "GenesisConfig",
+                FIELDS,
+                __Visitor {
+                    marker: _serde::__private::PhantomData::<GenesisConfig>,
+                    lifetime: _serde::__private::PhantomData,
+                },
+            )
+        }
+    }
+};
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::default::Default for GenesisConfig {
+    #[inline]
+    fn default() -> GenesisConfig {
+        GenesisConfig {
+            system: ::core::default::Default::default(),
+            transfer_pallet: ::core::default::Default::default(),
+        }
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_runtime::BuildStorage
+    for GenesisConfig
+{
+    fn assimilate_storage(
+        &self,
+        storage : & mut self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: Storage,
+    ) -> std::result::Result<(), String> {
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: BuildModuleGenesisStorage :: < Runtime , frame_system :: __InherentHiddenInstance > :: build_module_genesis_storage (& self . system , storage) ? ;
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: BuildModuleGenesisStorage :: < Runtime , transfer_pallet :: __InherentHiddenInstance > :: build_module_genesis_storage (& self . transfer_pallet , storage) ? ;
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: BasicExternalities :: execute_with_storage (storage , | | { < AllPalletsWithSystem as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OnGenesis > :: on_genesis () ; }) ;
+        Ok(())
+    }
+}
+trait InherentDataExt {
+    fn create_extrinsics (& self) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: Vec < < Block as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: BlockT > :: Extrinsic > ;
+    fn check_extrinsics (& self , block : & Block) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: CheckInherentsResult ;
+}
+impl InherentDataExt
+    for self::sp_api_hidden_includes_construct_runtime::hidden_include::inherent::InherentData
+{
+    fn create_extrinsics (& self) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: Vec < < Block as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: BlockT > :: Extrinsic >{
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::inherent::ProvideInherent;
+        let mut inherents = Vec::new();
+        inherents
+    }    fn check_extrinsics (& self , block : & Block) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: CheckInherentsResult{
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::inherent::{
+            ProvideInherent, IsFatalError,
+        };
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::{
+            IsSubType, ExtrinsicCall,
+        };
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_runtime::traits::Block as _;
+        let mut result = self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: CheckInherentsResult :: new () ;
+        for xt in block.extrinsics() {
+            if self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: Extrinsic :: is_signed (xt) . unwrap_or (false) { break }
+            let mut is_inherent = false;
+            if !is_inherent {
+                break;
+            }
+        }
+        result
+    }
+}
+impl
+    self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::EnsureInherentsAreFirst<
+        Block,
+    > for Runtime
+{
+    fn ensure_inherents_are_first(block: &Block) -> Result<(), u32> {
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::inherent::ProvideInherent;
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::{
+            IsSubType, ExtrinsicCall,
+        };
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_runtime::traits::Block as _;
+        let mut first_signed_observed = false;
+        for (i, xt) in block.extrinsics().iter().enumerate() {
+            let is_signed = self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: Extrinsic :: is_signed (xt) . unwrap_or (false) ;
+            let is_inherent = if is_signed {
+                false
+            } else {
+                let mut is_inherent = false;
+                is_inherent
+            };
+            if !is_inherent {
+                first_signed_observed = true;
+            }
+            if first_signed_observed && is_inherent {
+                return Err(i as u32);
+            }
+        }
+        Ok(())
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::unsigned::ValidateUnsigned
+    for Runtime
+{
+    type Call = Call;    fn pre_dispatch (call : & Self :: Call) -> Result < () , self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: unsigned :: TransactionValidityError >{
+        #[allow(unreachable_patterns)]
+        match call {
+            _ => Ok(()),
+        }
+    }
+    fn validate_unsigned(
+        # [allow (unused_variables)] source : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: unsigned :: TransactionSource,
+        call: &Self::Call,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::unsigned::TransactionValidity
+    {
+        # [allow (unreachable_patterns)] match call { _ => self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: unsigned :: UnknownTransaction :: NoUnsignedValidator . into () , }
+    }
+}
+const _: () =
+    if !(<frame_system::Error<Runtime> as ::frame_support::traits::PalletError>::MAX_ENCODED_SIZE
+        <= ::frame_support::MAX_MODULE_ERROR_ENCODED_SIZE)
+    {
+        :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["The maximum encoded size of the error type in the `System` pallet exceeds `MAX_MODULE_ERROR_ENCODED_SIZE`"] , & []))
+    };
+pub type Address = sp_runtime::MultiAddress<AccountId, ()>;
+pub type Header = generic::Header<BlockNumber, BlakeTwo256>;
+pub type Block = generic::Block<Header, UncheckedExtrinsic>;
+pub type SignedExtra = (
+    frame_system::CheckGenesis<Runtime>,
+    frame_system::CheckNonce<Runtime>,
+);
+pub type UncheckedExtrinsic = generic::UncheckedExtrinsic<Address, Call, Signature, SignedExtra>;
+pub type SignedPayload = generic::SignedPayload<Call, SignedExtra>;
+pub type Executive = frame_executive::Executive<
+    Runtime,
+    Block,
+    frame_system::ChainContext<Runtime>,
+    Runtime,
+    AllPalletsWithSystem,
+>;
+#[doc(hidden)]
+mod sp_api_hidden_includes_IMPL_RUNTIME_APIS {
+    pub extern crate sp_api as sp_api;
+}
+pub struct RuntimeApi {}
+/// Implements all runtime apis for the client side.
+#[cfg(any(feature = "std", test))]
+pub struct RuntimeApiImpl<
+    Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+    C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block> + 'static,
+> {
+    call: &'static C,
+    commit_on_success: std::cell::RefCell<bool>,
+    changes: std::cell::RefCell<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::OverlayedChanges,
+    >,
+    storage_transaction_cache: std::cell::RefCell<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StorageTransactionCache<
+            Block,
+            C::StateBackend,
+        >,
+    >,
+    recorder: std::option::Option<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ProofRecorder<Block>,
+    >,
+}
+#[cfg(any(feature = "std", test))]
+unsafe impl<
+        Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+        C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block>,
+    > Send for RuntimeApiImpl<Block, C>
+{
+}
+#[cfg(any(feature = "std", test))]
+unsafe impl<
+        Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+        C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block>,
+    > Sync for RuntimeApiImpl<Block, C>
+{
+}
+#[cfg(any(feature = "std", test))]
+impl<
+        Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+        C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block>,
+    > self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiExt<Block>
+    for RuntimeApiImpl<Block, C>
+{
+    type StateBackend = C::StateBackend;
+    fn execute_in_transaction<
+        F: FnOnce(
+            &Self,
+        )
+            -> self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::TransactionOutcome<R>,
+        R,
+    >(
+        &self,
+        call: F,
+    ) -> R
+    where
+        Self: Sized,
+    {
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::OverlayedChanges::start_transaction(
+            &mut std::cell::RefCell::borrow_mut(&self.changes),
+        );
+        *std::cell::RefCell::borrow_mut(&self.commit_on_success) = false;
+        let res = call(self);
+        *std::cell::RefCell::borrow_mut(&self.commit_on_success) = true;
+        self.commit_or_rollback(match res {
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::TransactionOutcome::Commit(
+                _,
+            ) => true,
+            _ => false,
+        });
+        res.into_inner()
+    }
+    fn has_api<A: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::RuntimeApiInfo + ?Sized>(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<Block>,
+    ) -> std::result::Result<bool, self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError>
+    where
+        Self: Sized,
+    {
+        self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: CallApiAt :: < Block > :: runtime_version_at (self . call , at) . map (| v | self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: RuntimeVersion :: has_api_with (& v , & A :: ID , | v | v == A :: VERSION))
+    }
+    fn has_api_with<
+        A: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::RuntimeApiInfo + ?Sized,
+        P: Fn(u32) -> bool,
+    >(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<Block>,
+        pred: P,
+    ) -> std::result::Result<bool, self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError>
+    where
+        Self: Sized,
+    {
+        self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: CallApiAt :: < Block > :: runtime_version_at (self . call , at) . map (| v | self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: RuntimeVersion :: has_api_with (& v , & A :: ID , pred))
+    }
+    fn api_version<
+        A: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::RuntimeApiInfo + ?Sized,
+    >(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<Block>,
+    ) -> std::result::Result<
+        Option<u32>,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    >
+    where
+        Self: Sized,
+    {
+        self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: CallApiAt :: < Block > :: runtime_version_at (self . call , at) . map (| v | self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: RuntimeVersion :: api_version (& v , & A :: ID))
+    }
+    fn record_proof(&mut self) {
+        self.recorder = std::option::Option::Some(std::default::Default::default());
+    }
+    fn proof_recorder(
+        &self,
+    ) -> std::option::Option<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ProofRecorder<Block>,
+    > {
+        std::clone::Clone::clone(&self.recorder)
+    }
+    fn extract_proof(
+        &mut self,
+    ) -> std::option::Option<self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StorageProof>
+    {
+        std :: option :: Option :: take (& mut self . recorder) . map (| recorder | self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: ProofRecorder :: < Block > :: to_storage_proof (& recorder))
+    }
+    fn into_storage_changes(
+        &self,
+        backend: &Self::StateBackend,
+        parent_hash: Block::Hash,
+    ) -> core::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StorageChanges<
+            C::StateBackend,
+            Block,
+        >,
+        String,
+    >
+    where
+        Self: Sized,
+    {
+        let at = self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId::Hash(
+            std::clone::Clone::clone(&parent_hash),
+        );
+        let state_version = self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt::<
+            Block,
+        >::runtime_version_at(self.call, &at)
+        .map(|v| {
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::RuntimeVersion::state_version(
+                &v,
+            )
+        })
+        .map_err(|e| {
+            let res = ::alloc::fmt::format(::core::fmt::Arguments::new_v1(
+                &["Failed to get state version: "],
+                &[::core::fmt::ArgumentV1::new_display(&e)],
+            ));
+            res
+        })?;
+        self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: OverlayedChanges :: into_storage_changes (std :: cell :: RefCell :: take (& self . changes) , backend , core :: cell :: RefCell :: take (& self . storage_transaction_cache) , state_version)
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl<Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT, C>
+    self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ConstructRuntimeApi<Block, C>
+    for RuntimeApi
+where
+    C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block> + 'static,
+{
+    type RuntimeApi = RuntimeApiImpl<Block, C>;
+    fn construct_runtime_api<'a>(
+        call: &'a C,
+    ) -> self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiRef<'a, Self::RuntimeApi> {
+        RuntimeApiImpl {
+            call: unsafe { std::mem::transmute(call) },
+            commit_on_success: true.into(),
+            changes: std::default::Default::default(),
+            recorder: std::default::Default::default(),
+            storage_transaction_cache: std::default::Default::default(),
+        }
+        .into()
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl<
+        Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+        C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block>,
+    > RuntimeApiImpl<Block, C>
+{
+    fn call_api_at<
+        R: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode
+            + self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Decode
+            + std::cmp::PartialEq,
+        F: FnOnce(
+            &C,
+            &std::cell::RefCell<
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::OverlayedChanges,
+            >,
+            &std::cell::RefCell<
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StorageTransactionCache<
+                    Block,
+                    C::StateBackend,
+                >,
+            >,
+            &std::option::Option<
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ProofRecorder<Block>,
+            >,
+        ) -> std::result::Result<
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<R>,
+            E,
+        >,
+        E,
+    >(
+        &self,
+        call_api_at: F,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<R>,
+        E,
+    > {
+        if *std::cell::RefCell::borrow(&self.commit_on_success) {
+            self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: OverlayedChanges :: start_transaction (& mut std :: cell :: RefCell :: borrow_mut (& self . changes)) ;
+        }
+        let res = call_api_at(
+            &self.call,
+            &self.changes,
+            &self.storage_transaction_cache,
+            &self.recorder,
+        );
+        self.commit_or_rollback(std::result::Result::is_ok(&res));
+        res
+    }
+    fn commit_or_rollback(&self, commit: bool) {
+        let proof = "\
+					We only close a transaction when we opened one ourself.
+					Other parts of the runtime that make use of transactions (state-machine)
+					also balance their transactions. The runtime cannot close client initiated
+					transactions; qed";
+        if *std::cell::RefCell::borrow(&self.commit_on_success) {
+            let res = if commit {
+                self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: OverlayedChanges :: commit_transaction (& mut std :: cell :: RefCell :: borrow_mut (& self . changes))
+            } else {
+                self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: OverlayedChanges :: rollback_transaction (& mut std :: cell :: RefCell :: borrow_mut (& self . changes))
+            };
+            std::result::Result::expect(res, proof);
+        }
+    }
+}
+impl sp_api::runtime_decl_for_Core::Core<Block> for Runtime {
+    fn version() -> RuntimeVersion {
+        VERSION
+    }
+    fn execute_block(block: Block) {
+        Executive::execute_block(block);
+    }
+    fn initialize_block(header: &<Block as BlockT>::Header) {
+        Executive::initialize_block(header)
+    }
+}
+impl sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<Block> for Runtime {
+    fn apply_extrinsic(extrinsic: <Block as BlockT>::Extrinsic) -> ApplyExtrinsicResult {
+        Executive::apply_extrinsic(extrinsic)
+    }
+    fn finalize_block() -> <Block as BlockT>::Header {
+        Executive::finalize_block()
+    }
+    fn inherent_extrinsics(_: sp_inherents::InherentData) -> Vec<<Block as BlockT>::Extrinsic> {
+        ::core::panicking::panic("not implemented")
+    }
+    fn check_inherents(
+        _: Block,
+        _: sp_inherents::InherentData,
+    ) -> sp_inherents::CheckInherentsResult {
+        ::core::panicking::panic("not implemented")
+    }
+}
+impl sp_transaction_pool :: runtime_api :: runtime_decl_for_TaggedTransactionQueue :: TaggedTransactionQueue < Block > for Runtime { fn validate_transaction (source : TransactionSource , tx : < Block as BlockT > :: Extrinsic , block_hash : < Block as BlockT > :: Hash) -> TransactionValidity { Executive :: validate_transaction (source , tx , block_hash) } }
+#[cfg(any(feature = "std", test))]
+impl<
+        __SR_API_BLOCK__: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT
+            + std::panic::UnwindSafe
+            + std::panic::RefUnwindSafe,
+        RuntimeApiImplCall: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<__SR_API_BLOCK__>
+            + 'static,
+    > sp_api::Core<__SR_API_BLOCK__> for RuntimeApiImpl<__SR_API_BLOCK__, RuntimeApiImplCall>
+where
+    RuntimeApiImplCall::StateBackend:
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StateBackend<
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::HashFor<__SR_API_BLOCK__>,
+        >,
+    RuntimeVersion: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    <__SR_API_BLOCK__ as BlockT>::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+{
+    fn Core_version_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<()>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<RuntimeVersion>,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self.call_api_at(
+            |call_runtime_at, changes, storage_transaction_cache, recorder| {
+                sp_api::runtime_decl_for_Core::version_call_api_at(
+                    call_runtime_at,
+                    at,
+                    params_encoded,
+                    changes,
+                    storage_transaction_cache,
+                    params.map(|p| {
+                        sp_api::runtime_decl_for_Core::version_native_call_generator::<
+                            Runtime,
+                            __SR_API_BLOCK__,
+                            Block,
+                        >()
+                    }),
+                    context,
+                    recorder,
+                )
+            },
+        )
+    }
+    fn Core_execute_block_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(__SR_API_BLOCK__)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<()>,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self.call_api_at(
+            |call_runtime_at, changes, storage_transaction_cache, recorder| {
+                sp_api::runtime_decl_for_Core::execute_block_call_api_at(
+                    call_runtime_at,
+                    at,
+                    params_encoded,
+                    changes,
+                    storage_transaction_cache,
+                    params.map(|p| {
+                        sp_api::runtime_decl_for_Core::execute_block_native_call_generator::<
+                            Runtime,
+                            __SR_API_BLOCK__,
+                            Block,
+                        >(p)
+                    }),
+                    context,
+                    recorder,
+                )
+            },
+        )
+    }
+    fn Core_initialize_block_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(&<__SR_API_BLOCK__ as BlockT>::Header)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<()>,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self.call_api_at(
+            |call_runtime_at, changes, storage_transaction_cache, recorder| {
+                sp_api::runtime_decl_for_Core::initialize_block_call_api_at(
+                    call_runtime_at,
+                    at,
+                    params_encoded,
+                    changes,
+                    storage_transaction_cache,
+                    params.map(|p| {
+                        sp_api::runtime_decl_for_Core::initialize_block_native_call_generator::<
+                            Runtime,
+                            __SR_API_BLOCK__,
+                            Block,
+                        >(p)
+                    }),
+                    context,
+                    recorder,
+                )
+            },
+        )
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl<
+        __SR_API_BLOCK__: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT
+            + std::panic::UnwindSafe
+            + std::panic::RefUnwindSafe,
+        RuntimeApiImplCall: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<__SR_API_BLOCK__>
+            + 'static,
+    > sp_block_builder::BlockBuilder<__SR_API_BLOCK__>
+    for RuntimeApiImpl<__SR_API_BLOCK__, RuntimeApiImplCall>
+where
+    RuntimeApiImplCall::StateBackend:
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StateBackend<
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::HashFor<__SR_API_BLOCK__>,
+        >,
+    <__SR_API_BLOCK__ as BlockT>::Extrinsic: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    ApplyExtrinsicResult: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    <__SR_API_BLOCK__ as BlockT>::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    sp_inherents::InherentData: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    Vec<<__SR_API_BLOCK__ as BlockT>::Extrinsic>:
+        std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    sp_inherents::InherentData: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    sp_inherents::CheckInherentsResult: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+{
+    fn BlockBuilder_apply_extrinsic_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(<__SR_API_BLOCK__ as BlockT>::Extrinsic)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            ApplyExtrinsicResult,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_block_builder :: runtime_decl_for_BlockBuilder :: apply_extrinsic_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_block_builder :: runtime_decl_for_BlockBuilder :: apply_extrinsic_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > (p) }) , context , recorder) })
+    }
+    fn BlockBuilder_finalize_block_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<()>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            <__SR_API_BLOCK__ as BlockT>::Header,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_block_builder :: runtime_decl_for_BlockBuilder :: finalize_block_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_block_builder :: runtime_decl_for_BlockBuilder :: finalize_block_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > () }) , context , recorder) })
+    }
+    fn BlockBuilder_inherent_extrinsics_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(sp_inherents::InherentData)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            Vec<<__SR_API_BLOCK__ as BlockT>::Extrinsic>,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_block_builder :: runtime_decl_for_BlockBuilder :: inherent_extrinsics_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_block_builder :: runtime_decl_for_BlockBuilder :: inherent_extrinsics_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > (p) }) , context , recorder) })
+    }
+    fn BlockBuilder_check_inherents_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(__SR_API_BLOCK__, sp_inherents::InherentData)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            sp_inherents::CheckInherentsResult,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_block_builder :: runtime_decl_for_BlockBuilder :: check_inherents_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_block_builder :: runtime_decl_for_BlockBuilder :: check_inherents_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > (p . 0 , p . 1) }) , context , recorder) })
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl<
+        __SR_API_BLOCK__: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT
+            + std::panic::UnwindSafe
+            + std::panic::RefUnwindSafe,
+        RuntimeApiImplCall: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<__SR_API_BLOCK__>
+            + 'static,
+    > sp_transaction_pool::runtime_api::TaggedTransactionQueue<__SR_API_BLOCK__>
+    for RuntimeApiImpl<__SR_API_BLOCK__, RuntimeApiImplCall>
+where
+    RuntimeApiImplCall::StateBackend:
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StateBackend<
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::HashFor<__SR_API_BLOCK__>,
+        >,
+    TransactionSource: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    <__SR_API_BLOCK__ as BlockT>::Extrinsic: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    <__SR_API_BLOCK__ as BlockT>::Hash: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    TransactionValidity: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+{
+    fn TaggedTransactionQueue_validate_transaction_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(
+            TransactionSource,
+            <__SR_API_BLOCK__ as BlockT>::Extrinsic,
+            <__SR_API_BLOCK__ as BlockT>::Hash,
+        )>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            TransactionValidity,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_transaction_pool :: runtime_api :: runtime_decl_for_TaggedTransactionQueue :: validate_transaction_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_transaction_pool :: runtime_api :: runtime_decl_for_TaggedTransactionQueue :: validate_transaction_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > (p . 0 , p . 1 , p . 2) }) , context , recorder) })
+    }
+}
+const RUNTIME_API_VERSIONS: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApisVec =
+    ::sp_version::sp_std::borrow::Cow::Borrowed(&[
+        (
+            sp_api::runtime_decl_for_Core::ID,
+            sp_api::runtime_decl_for_Core::VERSION,
+        ),
+        (
+            sp_block_builder::runtime_decl_for_BlockBuilder::ID,
+            sp_block_builder::runtime_decl_for_BlockBuilder::VERSION,
+        ),
+        (
+            sp_transaction_pool::runtime_api::runtime_decl_for_TaggedTransactionQueue::ID,
+            sp_transaction_pool::runtime_api::runtime_decl_for_TaggedTransactionQueue::VERSION,
+        ),
+    ]);
+const _: () = {};
+const _: () = {};
+const _: () = {};
+pub mod api {
+    use super::*;
+    #[cfg(feature = "std")]
+    pub fn dispatch(method: &str, mut __sp_api__input_data: &[u8]) -> Option<Vec<u8>> {
+        match method {
+            "Core_version" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let () : () = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "version") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_api::runtime_decl_for_Core::Core<Block>>::version()
+                }),
+            ),
+            "Core_execute_block" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (block) : (Block) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "execute_block") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_api::runtime_decl_for_Core::Core<Block>>::execute_block(block)
+                }),
+            ),
+            "Core_initialize_block" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (header) : (< Block as BlockT > :: Header) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "initialize_block") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_api::runtime_decl_for_Core::Core<Block>>::initialize_block(
+                        &header,
+                    )
+                }),
+            ),
+            "BlockBuilder_apply_extrinsic" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (extrinsic) : (< Block as BlockT > :: Extrinsic) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "apply_extrinsic") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<
+                        Block,
+                    >>::apply_extrinsic(extrinsic)
+                }),
+            ),
+            "BlockBuilder_finalize_block" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let () : () = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "finalize_block") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<
+                        Block,
+                    >>::finalize_block()
+                }),
+            ),
+            "BlockBuilder_inherent_extrinsics" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (__runtime_api_generated_name_0__) : (sp_inherents :: InherentData) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "inherent_extrinsics") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<
+                        Block,
+                    >>::inherent_extrinsics(__runtime_api_generated_name_0__)
+                }),
+            ),
+            "BlockBuilder_check_inherents" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (__runtime_api_generated_name_0__ , __runtime_api_generated_name_1__) : (Block , sp_inherents :: InherentData) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "check_inherents") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<
+                        Block,
+                    >>::check_inherents(
+                        __runtime_api_generated_name_0__,
+                        __runtime_api_generated_name_1__,
+                    )
+                }),
+            ),
+            "TaggedTransactionQueue_validate_transaction" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (source , tx , block_hash) : (TransactionSource , < Block as BlockT > :: Extrinsic , < Block as BlockT > :: Hash) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "validate_transaction") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    # [allow (deprecated)] < Runtime as sp_transaction_pool :: runtime_api :: runtime_decl_for_TaggedTransactionQueue :: TaggedTransactionQueue < Block > > :: validate_transaction (source , tx , block_hash)
+                }),
+            ),
+            _ => None,
+        }
+    }
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/lib.expanded.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/lib.expanded.rs
new file mode 100644
index 00000000..57f69d3d
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/lib.expanded.rs
@@ -0,0 +1,2138 @@
+#![feature(prelude_import)]
+#![recursion_limit = "256"]
+#[prelude_import]
+use std::prelude::rust_2021::*;
+#[macro_use]
+extern crate std;
+use sp_api::impl_runtime_apis;
+use sp_runtime::{
+    create_runtime_str, generic,
+    traits::{AccountIdLookup, BlakeTwo256, Block as BlockT, IdentifyAccount, NumberFor, Verify},
+    transaction_validity::{TransactionSource, TransactionValidity},
+    ApplyExtrinsicResult, MultiSignature,
+};
+use sp_std::prelude::*;
+#[cfg(feature = "std")]
+use sp_version::NativeVersion;
+use sp_version::RuntimeVersion;
+pub use frame_support::{
+    construct_runtime, parameter_types,
+    traits::{
+        ConstU128, ConstU32, ConstU64, ConstU8, KeyOwnerProofSystem, Randomness, StorageInfo,
+    },
+    weights::{
+        constants::{BlockExecutionWeight, ExtrinsicBaseWeight, RocksDbWeight, WEIGHT_PER_SECOND},
+        IdentityFee, Weight,
+    },
+    StorageValue,
+};
+#[cfg(any(feature = "std", test))]
+pub use sp_runtime::BuildStorage;
+pub use sp_runtime::{Perbill, Permill};
+pub type BlockNumber = u32;
+pub type Signature = MultiSignature;
+pub type AccountId = <<Signature as Verify>::Signer as IdentifyAccount>::AccountId;
+pub type Hash = sp_core::H256;
+pub type Balance = u128;
+pub type Index = u32;
+/// Opaque types. These are used by the CLI to instantiate machinery that don't need to know
+/// the specifics of the runtime. They can then be made to be agnostic over specific formats
+/// of data like extrinsics, allowing for them to continue syncing the network through upgrades
+/// to even the core data structures.
+pub mod opaque {
+    use super::*;
+    pub use sp_runtime::OpaqueExtrinsic as UncheckedExtrinsic;
+    /// Opaque block header type.
+    pub type Header = generic::Header<BlockNumber, BlakeTwo256>;
+    /// Opaque block type.
+    pub type Block = generic::Block<Header, UncheckedExtrinsic>;
+    /// Opaque block identifier type.
+    pub type BlockId = generic::BlockId<Block>;
+}
+pub const VERSION: RuntimeVersion = RuntimeVersion {
+    spec_name: { ::sp_runtime::RuntimeString::Borrowed("simple-runtime") },
+    impl_name: { ::sp_runtime::RuntimeString::Borrowed("simple-runtime") },
+    authoring_version: 1,
+    spec_version: 100,
+    impl_version: 1,
+    apis: RUNTIME_API_VERSIONS,
+    transaction_version: 1,
+    state_version: 1,
+};
+const _: () = {};
+pub const MILLISECS_PER_BLOCK: u64 = 6000;
+pub const SLOT_DURATION: u64 = MILLISECS_PER_BLOCK;
+pub const MINUTES: BlockNumber = 60_000 / (MILLISECS_PER_BLOCK as BlockNumber);
+pub const HOURS: BlockNumber = MINUTES * 60;
+pub const DAYS: BlockNumber = HOURS * 24;
+/// The version information used to identify this runtime when compiled natively.
+#[cfg(feature = "std")]
+pub fn native_version() -> NativeVersion {
+    NativeVersion {
+        runtime_version: VERSION,
+        can_author_with: Default::default(),
+    }
+}
+const NORMAL_DISPATCH_RATIO: Perbill = Perbill::from_percent(75);
+pub struct BlockHashCount;
+impl BlockHashCount {
+    /// Returns the value of this parameter type.
+    pub const fn get() -> BlockNumber {
+        2400
+    }
+}
+impl<I: From<BlockNumber>> ::frame_support::traits::Get<I> for BlockHashCount {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for BlockHashCount {
+    type Type = BlockNumber;
+    fn get() -> BlockNumber {
+        Self::get()
+    }
+}
+pub struct Version;
+impl Version {
+    /// Returns the value of this parameter type.
+    pub const fn get() -> RuntimeVersion {
+        VERSION
+    }
+}
+impl<I: From<RuntimeVersion>> ::frame_support::traits::Get<I> for Version {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for Version {
+    type Type = RuntimeVersion;
+    fn get() -> RuntimeVersion {
+        Self::get()
+    }
+}
+pub struct BlockWeights;
+impl BlockWeights {
+    /// Returns the value of this parameter type.
+    pub fn get() -> frame_system::limits::BlockWeights {
+        frame_system::limits::BlockWeights::with_sensible_defaults(
+            2 * WEIGHT_PER_SECOND,
+            NORMAL_DISPATCH_RATIO,
+        )
+    }
+}
+impl<I: From<frame_system::limits::BlockWeights>> ::frame_support::traits::Get<I> for BlockWeights {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for BlockWeights {
+    type Type = frame_system::limits::BlockWeights;
+    fn get() -> frame_system::limits::BlockWeights {
+        Self::get()
+    }
+}
+pub struct BlockLength;
+impl BlockLength {
+    /// Returns the value of this parameter type.
+    pub fn get() -> frame_system::limits::BlockLength {
+        frame_system::limits::BlockLength::max_with_normal_ratio(
+            5 * 1024 * 1024,
+            NORMAL_DISPATCH_RATIO,
+        )
+    }
+}
+impl<I: From<frame_system::limits::BlockLength>> ::frame_support::traits::Get<I> for BlockLength {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for BlockLength {
+    type Type = frame_system::limits::BlockLength;
+    fn get() -> frame_system::limits::BlockLength {
+        Self::get()
+    }
+}
+pub struct SS58Prefix;
+impl SS58Prefix {
+    /// Returns the value of this parameter type.
+    pub const fn get() -> u8 {
+        42
+    }
+}
+impl<I: From<u8>> ::frame_support::traits::Get<I> for SS58Prefix {
+    fn get() -> I {
+        I::from(Self::get())
+    }
+}
+impl ::frame_support::traits::TypedGet for SS58Prefix {
+    type Type = u8;
+    fn get() -> u8 {
+        Self::get()
+    }
+}
+impl frame_system::Config for Runtime {
+    type BaseCallFilter = frame_support::traits::Everything;
+    type BlockWeights = BlockWeights;
+    type BlockLength = BlockLength;
+    type AccountId = AccountId;
+    type Call = Call;
+    type Lookup = AccountIdLookup<AccountId, ()>;
+    type Index = Index;
+    type BlockNumber = BlockNumber;
+    type Hash = Hash;
+    type Hashing = BlakeTwo256;
+    type Header = generic::Header<BlockNumber, BlakeTwo256>;
+    type Event = Event;
+    type Origin = Origin;
+    type BlockHashCount = BlockHashCount;
+    type DbWeight = RocksDbWeight;
+    type Version = Version;
+    type PalletInfo = PalletInfo;
+    type OnNewAccount = ();
+    type OnKilledAccount = ();
+    type AccountData = ();
+    type SystemWeightInfo = ();
+    type SS58Prefix = SS58Prefix;
+    type OnSetCode = ();
+    type MaxConsumers = frame_support::traits::ConstU32<16>;
+}
+impl simple_pallet::pallet::Config for Runtime {
+    type ValueType = u64;
+    const MAX_VALUE: u32 = 1000;
+    fn on_value_update(new_value: Self::ValueType) {
+        ::core::panicking::panic("not yet implemented");
+    }
+}
+#[doc(hidden)]
+mod sp_api_hidden_includes_construct_runtime {
+    pub extern crate frame_support as hidden_include;
+}
+const _: () = {
+    #[allow(unused)]
+    type __hidden_use_of_unchecked_extrinsic = UncheckedExtrinsic;
+};
+pub struct Runtime;
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::clone::Clone for Runtime {
+    #[inline]
+    fn clone(&self) -> Runtime {
+        {
+            *self
+        }
+    }
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::marker::Copy for Runtime {}
+impl ::core::marker::StructuralPartialEq for Runtime {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::cmp::PartialEq for Runtime {
+    #[inline]
+    fn eq(&self, other: &Runtime) -> bool {
+        true
+    }
+}
+impl ::core::marker::StructuralEq for Runtime {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::cmp::Eq for Runtime {
+    #[inline]
+    #[doc(hidden)]
+    #[no_coverage]
+    fn assert_receiver_is_total_eq(&self) -> () {
+        {}
+    }
+}
+impl core::fmt::Debug for Runtime {
+    fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+        fmt.debug_tuple("Runtime").finish()
+    }
+}
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    impl ::scale_info::TypeInfo for Runtime {
+        type Identity = Self;
+        fn type_info() -> ::scale_info::Type {
+            ::scale_info::Type::builder()
+                .path(::scale_info::Path::new("Runtime", "simple_runtime"))
+                .type_params(::alloc::vec::Vec::new())
+                .docs(&[])
+                .composite(::scale_info::build::Fields::unit())
+        }
+    };
+};
+impl self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: GetNodeBlockType for Runtime { type NodeBlock = opaque :: Block ; }
+impl self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: GetRuntimeBlockType for Runtime { type RuntimeBlock = Block ; }
+#[allow(non_camel_case_types)]
+pub enum Event {
+    #[codec(index = 0u8)]
+    System(frame_system::Event<Runtime>),
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::clone::Clone for Event {
+    #[inline]
+    fn clone(&self) -> Event {
+        match (&*self,) {
+            (&Event::System(ref __self_0),) => {
+                Event::System(::core::clone::Clone::clone(&*__self_0))
+            }
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+impl ::core::marker::StructuralPartialEq for Event {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::cmp::PartialEq for Event {
+    #[inline]
+    fn eq(&self, other: &Event) -> bool {
+        match (&*self, &*other) {
+            (&Event::System(ref __self_0), &Event::System(ref __arg_1_0)) => {
+                *__self_0 == *__arg_1_0
+            }
+        }
+    }
+    #[inline]
+    fn ne(&self, other: &Event) -> bool {
+        match (&*self, &*other) {
+            (&Event::System(ref __self_0), &Event::System(ref __arg_1_0)) => {
+                *__self_0 != *__arg_1_0
+            }
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+impl ::core::marker::StructuralEq for Event {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::cmp::Eq for Event {
+    #[inline]
+    #[doc(hidden)]
+    #[no_coverage]
+    fn assert_receiver_is_total_eq(&self) -> () {
+        {
+            let _: ::core::cmp::AssertParamIsEq<frame_system::Event<Runtime>>;
+        }
+    }
+}
+#[allow(deprecated)]
+const _: () = {
+    #[allow(non_camel_case_types)]
+    #[automatically_derived]
+    impl ::codec::Encode for Event {
+        fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+            &self,
+            __codec_dest_edqy: &mut __CodecOutputEdqy,
+        ) {
+            match *self {
+                Event::System(ref aa) => {
+                    __codec_dest_edqy.push_byte(0u8 as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                _ => (),
+            }
+        }
+    }
+    #[automatically_derived]
+    impl ::codec::EncodeLike for Event {}
+};
+#[allow(deprecated)]
+const _: () = {
+    #[allow(non_camel_case_types)]
+    #[automatically_derived]
+    impl ::codec::Decode for Event {
+        fn decode<__CodecInputEdqy: ::codec::Input>(
+            __codec_input_edqy: &mut __CodecInputEdqy,
+        ) -> ::core::result::Result<Self, ::codec::Error> {
+            match __codec_input_edqy
+                .read_byte()
+                .map_err(|e| e.chain("Could not decode `Event`, failed to read variant byte"))?
+            {
+                __codec_x_edqy if __codec_x_edqy == 0u8 as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(Event::System({
+                        let __codec_res_edqy =
+                            <frame_system::Event<Runtime> as ::codec::Decode>::decode(
+                                __codec_input_edqy,
+                            );
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `Event::System.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                _ => ::core::result::Result::Err(<_ as ::core::convert::Into<_>>::into(
+                    "Could not decode `Event`, variant doesn't exist",
+                )),
+            }
+        }
+    }
+};
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    impl ::scale_info::TypeInfo for Event {
+        type Identity = Self;
+        fn type_info() -> ::scale_info::Type {
+            ::scale_info::Type::builder()
+                .path(::scale_info::Path::new("Event", "simple_runtime"))
+                .type_params(::alloc::vec::Vec::new())
+                .docs(&[])
+                .variant(::scale_info::build::Variants::new().variant("System", |v| {
+                    v.index(0u8 as ::core::primitive::u8)
+                        .fields(::scale_info::build::Fields::unnamed().field(|f| {
+                            f.ty::<frame_system::Event<Runtime>>()
+                                .type_name("frame_system::Event<Runtime>")
+                                .docs(&[])
+                        }))
+                        .docs(&[])
+                }))
+        }
+    };
+};
+impl core::fmt::Debug for Event {
+    fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+        match self {
+            Self::System(ref a0) => fmt.debug_tuple("Event::System").field(a0).finish(),
+            _ => Ok(()),
+        }
+    }
+}
+impl From<frame_system::Event<Runtime>> for Event {
+    fn from(x: frame_system::Event<Runtime>) -> Self {
+        Event::System(x)
+    }
+}
+impl TryInto<frame_system::Event<Runtime>> for Event {
+    type Error = ();
+    fn try_into(
+        self,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::result::Result<
+        frame_system::Event<Runtime>,
+        Self::Error,
+    > {
+        match self {
+            Self::System(evt) => Ok(evt),
+            _ => Err(()),
+        }
+    }
+}
+/// The runtime origin type representing the origin of a call.
+///
+/// Origin is always created with the base filter configured in [`frame_system::Config::BaseCallFilter`].
+pub struct Origin {
+    caller: OriginCaller,
+    filter: self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::rc::Rc<
+        Box<dyn Fn(&<Runtime as frame_system::Config>::Call) -> bool>,
+    >,
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::clone::Clone for Origin {
+    #[inline]
+    fn clone(&self) -> Origin {
+        Origin {
+            caller: ::core::clone::Clone::clone(&self.caller),
+            filter: ::core::clone::Clone::clone(&self.filter),
+        }
+    }
+}
+#[cfg(feature = "std")]
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::fmt::Debug for Origin {
+    fn fmt(
+        &self,
+        fmt : & mut self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: fmt :: Formatter,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::result::Result<
+        (),
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::fmt::Error,
+    > {
+        fmt.debug_struct("Origin")
+            .field("caller", &self.caller)
+            .field("filter", &"[function ptr]")
+            .finish()
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::OriginTrait
+    for Origin
+{
+    type Call = <Runtime as frame_system::Config>::Call;
+    type PalletsOrigin = OriginCaller;
+    type AccountId = <Runtime as frame_system::Config>::AccountId;
+    fn add_filter(&mut self, filter: impl Fn(&Self::Call) -> bool + 'static) {
+        let f = self.filter.clone();
+        self.filter =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::rc::Rc::new(
+                Box::new(move |call| f(call) && filter(call)),
+            );
+    }
+    fn reset_filter(&mut self) {
+        let filter = < < Runtime as frame_system :: Config > :: BaseCallFilter as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: Contains < < Runtime as frame_system :: Config > :: Call > > :: contains ;
+        self.filter =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::rc::Rc::new(
+                Box::new(filter),
+            );
+    }
+    fn set_caller_from(&mut self, other: impl Into<Self>) {
+        self.caller = other.into().caller;
+    }
+    fn filter_call(&self, call: &Self::Call) -> bool {
+        match self.caller {
+            OriginCaller::system(frame_system::Origin::<Runtime>::Root) => true,
+            _ => (self.filter)(call),
+        }
+    }
+    fn caller(&self) -> &Self::PalletsOrigin {
+        &self.caller
+    }
+    fn try_with_caller<R>(
+        mut self,
+        f: impl FnOnce(Self::PalletsOrigin) -> Result<R, Self::PalletsOrigin>,
+    ) -> Result<R, Self> {
+        match f(self.caller) {
+            Ok(r) => Ok(r),
+            Err(caller) => {
+                self.caller = caller;
+                Err(self)
+            }
+        }
+    }
+    fn none() -> Self {
+        frame_system::RawOrigin::None.into()
+    }
+    fn root() -> Self {
+        frame_system::RawOrigin::Root.into()
+    }
+    fn signed(by: Self::AccountId) -> Self {
+        frame_system::RawOrigin::Signed(by).into()
+    }
+    fn as_signed(self) -> Option<Self::AccountId> {
+        match self.caller {
+            OriginCaller::system(frame_system::RawOrigin::Signed(by)) => Some(by),
+            _ => None,
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+pub enum OriginCaller {
+    #[codec(index = 0u8)]
+    system(frame_system::Origin<Runtime>),
+    #[allow(dead_code)]
+    Void(self::sp_api_hidden_includes_construct_runtime::hidden_include::Void),
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::clone::Clone for OriginCaller {
+    #[inline]
+    fn clone(&self) -> OriginCaller {
+        match (&*self,) {
+            (&OriginCaller::system(ref __self_0),) => {
+                OriginCaller::system(::core::clone::Clone::clone(&*__self_0))
+            }
+            (&OriginCaller::Void(ref __self_0),) => {
+                OriginCaller::Void(::core::clone::Clone::clone(&*__self_0))
+            }
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+impl ::core::marker::StructuralPartialEq for OriginCaller {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::cmp::PartialEq for OriginCaller {
+    #[inline]
+    fn eq(&self, other: &OriginCaller) -> bool {
+        {
+            let __self_vi = ::core::intrinsics::discriminant_value(&*self);
+            let __arg_1_vi = ::core::intrinsics::discriminant_value(&*other);
+            if __self_vi == __arg_1_vi {
+                match (&*self, &*other) {
+                    (&OriginCaller::system(ref __self_0), &OriginCaller::system(ref __arg_1_0)) => {
+                        *__self_0 == *__arg_1_0
+                    }
+                    (&OriginCaller::Void(ref __self_0), &OriginCaller::Void(ref __arg_1_0)) => {
+                        *__self_0 == *__arg_1_0
+                    }
+                    _ => unsafe { ::core::intrinsics::unreachable() },
+                }
+            } else {
+                false
+            }
+        }
+    }
+    #[inline]
+    fn ne(&self, other: &OriginCaller) -> bool {
+        {
+            let __self_vi = ::core::intrinsics::discriminant_value(&*self);
+            let __arg_1_vi = ::core::intrinsics::discriminant_value(&*other);
+            if __self_vi == __arg_1_vi {
+                match (&*self, &*other) {
+                    (&OriginCaller::system(ref __self_0), &OriginCaller::system(ref __arg_1_0)) => {
+                        *__self_0 != *__arg_1_0
+                    }
+                    (&OriginCaller::Void(ref __self_0), &OriginCaller::Void(ref __arg_1_0)) => {
+                        *__self_0 != *__arg_1_0
+                    }
+                    _ => unsafe { ::core::intrinsics::unreachable() },
+                }
+            } else {
+                true
+            }
+        }
+    }
+}
+#[allow(non_camel_case_types)]
+impl ::core::marker::StructuralEq for OriginCaller {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+#[allow(non_camel_case_types)]
+impl ::core::cmp::Eq for OriginCaller {
+    #[inline]
+    #[doc(hidden)]
+    #[no_coverage]
+    fn assert_receiver_is_total_eq(&self) -> () {
+        {
+            let _: ::core::cmp::AssertParamIsEq<frame_system::Origin<Runtime>>;
+            let _: ::core::cmp::AssertParamIsEq<
+                self::sp_api_hidden_includes_construct_runtime::hidden_include::Void,
+            >;
+        }
+    }
+}
+impl core::fmt::Debug for OriginCaller {
+    fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+        match self {
+            Self::system(ref a0) => fmt.debug_tuple("OriginCaller::system").field(a0).finish(),
+            Self::Void(ref a0) => fmt.debug_tuple("OriginCaller::Void").field(a0).finish(),
+            _ => Ok(()),
+        }
+    }
+}
+#[allow(deprecated)]
+const _: () = {
+    #[allow(non_camel_case_types)]
+    #[automatically_derived]
+    impl ::codec::Encode for OriginCaller {
+        fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+            &self,
+            __codec_dest_edqy: &mut __CodecOutputEdqy,
+        ) {
+            match *self {
+                OriginCaller::system(ref aa) => {
+                    __codec_dest_edqy.push_byte(0u8 as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                OriginCaller::Void(ref aa) => {
+                    __codec_dest_edqy.push_byte(1usize as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                _ => (),
+            }
+        }
+    }
+    #[automatically_derived]
+    impl ::codec::EncodeLike for OriginCaller {}
+};
+#[allow(deprecated)]
+const _: () = {
+    #[allow(non_camel_case_types)]
+    #[automatically_derived]
+    impl ::codec::Decode for OriginCaller {
+        fn decode<__CodecInputEdqy: ::codec::Input>(
+            __codec_input_edqy: &mut __CodecInputEdqy,
+        ) -> ::core::result::Result<Self, ::codec::Error> {
+            match __codec_input_edqy.read_byte().map_err(|e| {
+                e.chain("Could not decode `OriginCaller`, failed to read variant byte")
+            })? {
+                __codec_x_edqy if __codec_x_edqy == 0u8 as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(OriginCaller::system({
+                        let __codec_res_edqy =
+                            <frame_system::Origin<Runtime> as ::codec::Decode>::decode(
+                                __codec_input_edqy,
+                            );
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `OriginCaller::system.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                __codec_x_edqy if __codec_x_edqy == 1usize as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(OriginCaller::Void({
+                        let __codec_res_edqy = < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: Void as :: codec :: Decode > :: decode (__codec_input_edqy) ;
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `OriginCaller::Void.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                _ => ::core::result::Result::Err(<_ as ::core::convert::Into<_>>::into(
+                    "Could not decode `OriginCaller`, variant doesn't exist",
+                )),
+            }
+        }
+    }
+};
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    impl ::scale_info::TypeInfo for OriginCaller {
+        type Identity = Self;
+        fn type_info() -> ::scale_info::Type {
+            :: scale_info :: Type :: builder () . path (:: scale_info :: Path :: new ("OriginCaller" , "simple_runtime")) . type_params (:: alloc :: vec :: Vec :: new ()) . docs (& []) . variant (:: scale_info :: build :: Variants :: new () . variant ("system" , | v | v . index (0u8 as :: core :: primitive :: u8) . fields (:: scale_info :: build :: Fields :: unnamed () . field (| f | f . ty :: < frame_system :: Origin < Runtime > > () . type_name ("frame_system::Origin<Runtime>") . docs (& []))) . docs (& [])) . variant ("Void" , | v | v . index (1usize as :: core :: primitive :: u8) . fields (:: scale_info :: build :: Fields :: unnamed () . field (| f | f . ty :: < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: Void > () . type_name ("self::sp_api_hidden_includes_construct_runtime::hidden_include::Void") . docs (& []))) . docs (& [])))
+        }
+    };
+};
+const _: () = {
+    impl ::codec::MaxEncodedLen for OriginCaller {
+        fn max_encoded_len() -> ::core::primitive::usize {
+            0_usize . max (0_usize . saturating_add (< frame_system :: Origin < Runtime > > :: max_encoded_len ())) . max (0_usize . saturating_add (< self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: Void > :: max_encoded_len ())) . saturating_add (1)
+        }
+    }
+};
+#[allow(dead_code)]
+impl Origin {
+    /// Create with system none origin and [`frame_system::Config::BaseCallFilter`].
+    pub fn none() -> Self {
+        < Origin as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait > :: none ()
+    }
+    /// Create with system root origin and [`frame_system::Config::BaseCallFilter`].
+    pub fn root() -> Self {
+        < Origin as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait > :: root ()
+    }
+    /// Create with system signed origin and [`frame_system::Config::BaseCallFilter`].
+    pub fn signed(by: <Runtime as frame_system::Config>::AccountId) -> Self {
+        < Origin as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait > :: signed (by)
+    }
+}
+impl From<frame_system::Origin<Runtime>> for OriginCaller {
+    fn from(x: frame_system::Origin<Runtime>) -> Self {
+        OriginCaller::system(x)
+    }
+}
+impl TryFrom<OriginCaller> for frame_system::Origin<Runtime> {
+    type Error = OriginCaller;
+    fn try_from(
+        x: OriginCaller,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::result::Result<
+        frame_system::Origin<Runtime>,
+        OriginCaller,
+    > {
+        if let OriginCaller::system(l) = x {
+            Ok(l)
+        } else {
+            Err(x)
+        }
+    }
+}
+impl From<frame_system::Origin<Runtime>> for Origin {
+    /// Convert to runtime origin, using as filter: [`frame_system::Config::BaseCallFilter`].
+    fn from(x: frame_system::Origin<Runtime>) -> Self {
+        let o: OriginCaller = x.into();
+        o.into()
+    }
+}
+impl From<OriginCaller> for Origin {
+    fn from(x: OriginCaller) -> Self {
+        let mut o = Origin {
+            caller: x,
+            filter:
+                self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::rc::Rc::new(
+                    Box::new(|_| true),
+                ),
+        };
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait :: reset_filter (& mut o) ;
+        o
+    }
+}
+impl From<Origin>
+    for self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::result::Result<
+        frame_system::Origin<Runtime>,
+        Origin,
+    >
+{
+    /// NOTE: converting to pallet origin loses the origin filter information.
+    fn from(val: Origin) -> Self {
+        if let OriginCaller::system(l) = val.caller {
+            Ok(l)
+        } else {
+            Err(val)
+        }
+    }
+}
+impl From<Option<<Runtime as frame_system::Config>::AccountId>> for Origin {
+    /// Convert to runtime origin with caller being system signed or none and use filter [`frame_system::Config::BaseCallFilter`].
+    fn from(x: Option<<Runtime as frame_system::Config>::AccountId>) -> Self {
+        <frame_system::Origin<Runtime>>::from(x).into()
+    }
+}
+pub type System = frame_system::Pallet<Runtime>;
+pub type SimplePallet = simple_pallet::Pallet<Runtime>;
+/// All pallets included in the runtime as a nested tuple of types.
+#[deprecated(
+    note = "The type definition has changed from representing all pallets \
+			excluding system, in reversed order to become the representation of all pallets \
+			including system pallet in regular order. For this reason it is encouraged to use \
+			explicitly one of `AllPalletsWithSystem`, `AllPalletsWithoutSystem`, \
+			`AllPalletsWithSystemReversed`, `AllPalletsWithoutSystemReversed`. \
+			Note that the type `frame_executive::Executive` expects one of `AllPalletsWithSystem` \
+			, `AllPalletsWithSystemReversed`, `AllPalletsReversedWithSystemFirst`. More details in \
+			https://github.com/paritytech/substrate/pull/10043"
+)]
+pub type AllPallets = AllPalletsWithSystem;
+/// All pallets included in the runtime as a nested tuple of types.
+pub type AllPalletsWithSystem = ((System, (SimplePallet,)));
+/// All pallets included in the runtime as a nested tuple of types.
+/// Excludes the System pallet.
+pub type AllPalletsWithoutSystem = ((SimplePallet,));
+/// All pallets included in the runtime as a nested tuple of types in reversed order.
+/// Excludes the System pallet.
+pub type AllPalletsWithoutSystemReversed = ((SimplePallet,));
+/// All pallets included in the runtime as a nested tuple of types in reversed order.
+pub type AllPalletsWithSystemReversed = ((SimplePallet, (System,)));
+/// All pallets included in the runtime as a nested tuple of types in reversed order.
+/// With the system pallet first.
+pub type AllPalletsReversedWithSystemFirst = (System, AllPalletsWithoutSystemReversed);
+/// Provides an implementation of `PalletInfo` to provide information
+/// about the pallet setup in the runtime.
+pub struct PalletInfo;
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::PalletInfo
+    for PalletInfo
+{
+    fn index<P: 'static>() -> Option<usize> {
+        let type_id =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::any::TypeId::of::<
+                P,
+            >();
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < System > () { return Some (0usize) }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < SimplePallet > () { return Some (1usize) }
+        None
+    }
+    fn name<P: 'static>() -> Option<&'static str> {
+        let type_id =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::any::TypeId::of::<
+                P,
+            >();
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < System > () { return Some ("System") }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < SimplePallet > () { return Some ("SimplePallet") }
+        None
+    }
+    fn module_name<P: 'static>() -> Option<&'static str> {
+        let type_id =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::any::TypeId::of::<
+                P,
+            >();
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < System > () { return Some ("frame_system") }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < SimplePallet > () { return Some ("simple_pallet") }
+        None
+    }
+    fn crate_version<P: 'static>(
+    ) -> Option<self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::CrateVersion>
+    {
+        let type_id =
+            self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_std::any::TypeId::of::<
+                P,
+            >();
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < System > () { return Some (< frame_system :: Pallet < Runtime > as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: PalletInfoAccess > :: crate_version ()) }
+        if type_id == self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: any :: TypeId :: of :: < SimplePallet > () { return Some (< simple_pallet :: Pallet < Runtime > as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: PalletInfoAccess > :: crate_version ()) }
+        None
+    }
+}
+pub enum Call {
+    #[codec(index = 0u8)]
+    System(
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            System,
+            Runtime,
+        >,
+    ),
+    #[codec(index = 1u8)]
+    SimplePallet(
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            SimplePallet,
+            Runtime,
+        >,
+    ),
+}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::clone::Clone for Call {
+    #[inline]
+    fn clone(&self) -> Call {
+        match (&*self,) {
+            (&Call::System(ref __self_0),) => Call::System(::core::clone::Clone::clone(&*__self_0)),
+            (&Call::SimplePallet(ref __self_0),) => {
+                Call::SimplePallet(::core::clone::Clone::clone(&*__self_0))
+            }
+        }
+    }
+}
+impl ::core::marker::StructuralPartialEq for Call {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::cmp::PartialEq for Call {
+    #[inline]
+    fn eq(&self, other: &Call) -> bool {
+        {
+            let __self_vi = ::core::intrinsics::discriminant_value(&*self);
+            let __arg_1_vi = ::core::intrinsics::discriminant_value(&*other);
+            if __self_vi == __arg_1_vi {
+                match (&*self, &*other) {
+                    (&Call::System(ref __self_0), &Call::System(ref __arg_1_0)) => {
+                        *__self_0 == *__arg_1_0
+                    }
+                    (&Call::SimplePallet(ref __self_0), &Call::SimplePallet(ref __arg_1_0)) => {
+                        *__self_0 == *__arg_1_0
+                    }
+                    _ => unsafe { ::core::intrinsics::unreachable() },
+                }
+            } else {
+                false
+            }
+        }
+    }
+    #[inline]
+    fn ne(&self, other: &Call) -> bool {
+        {
+            let __self_vi = ::core::intrinsics::discriminant_value(&*self);
+            let __arg_1_vi = ::core::intrinsics::discriminant_value(&*other);
+            if __self_vi == __arg_1_vi {
+                match (&*self, &*other) {
+                    (&Call::System(ref __self_0), &Call::System(ref __arg_1_0)) => {
+                        *__self_0 != *__arg_1_0
+                    }
+                    (&Call::SimplePallet(ref __self_0), &Call::SimplePallet(ref __arg_1_0)) => {
+                        *__self_0 != *__arg_1_0
+                    }
+                    _ => unsafe { ::core::intrinsics::unreachable() },
+                }
+            } else {
+                true
+            }
+        }
+    }
+}
+impl ::core::marker::StructuralEq for Call {}
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::cmp::Eq for Call {
+    #[inline]
+    #[doc(hidden)]
+    #[no_coverage]
+    fn assert_receiver_is_total_eq(&self) -> () {
+        {
+            let _ : :: core :: cmp :: AssertParamIsEq < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < System , Runtime > > ;
+            let _ : :: core :: cmp :: AssertParamIsEq < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < SimplePallet , Runtime > > ;
+        }
+    }
+}
+#[allow(deprecated)]
+const _: () = {
+    #[automatically_derived]
+    impl ::codec::Encode for Call {
+        fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+            &self,
+            __codec_dest_edqy: &mut __CodecOutputEdqy,
+        ) {
+            match *self {
+                Call::System(ref aa) => {
+                    __codec_dest_edqy.push_byte(0u8 as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                Call::SimplePallet(ref aa) => {
+                    __codec_dest_edqy.push_byte(1u8 as ::core::primitive::u8);
+                    ::codec::Encode::encode_to(aa, __codec_dest_edqy);
+                }
+                _ => (),
+            }
+        }
+    }
+    #[automatically_derived]
+    impl ::codec::EncodeLike for Call {}
+};
+#[allow(deprecated)]
+const _: () = {
+    #[automatically_derived]
+    impl ::codec::Decode for Call {
+        fn decode<__CodecInputEdqy: ::codec::Input>(
+            __codec_input_edqy: &mut __CodecInputEdqy,
+        ) -> ::core::result::Result<Self, ::codec::Error> {
+            match __codec_input_edqy
+                .read_byte()
+                .map_err(|e| e.chain("Could not decode `Call`, failed to read variant byte"))?
+            {
+                __codec_x_edqy if __codec_x_edqy == 0u8 as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(Call::System({
+                        let __codec_res_edqy = < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < System , Runtime > as :: codec :: Decode > :: decode (__codec_input_edqy) ;
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `Call::System.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                __codec_x_edqy if __codec_x_edqy == 1u8 as ::core::primitive::u8 => {
+                    ::core::result::Result::Ok(Call::SimplePallet({
+                        let __codec_res_edqy = < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < SimplePallet , Runtime > as :: codec :: Decode > :: decode (__codec_input_edqy) ;
+                        match __codec_res_edqy {
+                            ::core::result::Result::Err(e) => {
+                                return ::core::result::Result::Err(
+                                    e.chain("Could not decode `Call::SimplePallet.0`"),
+                                )
+                            }
+                            ::core::result::Result::Ok(__codec_res_edqy) => __codec_res_edqy,
+                        }
+                    }))
+                }
+                _ => ::core::result::Result::Err(<_ as ::core::convert::Into<_>>::into(
+                    "Could not decode `Call`, variant doesn't exist",
+                )),
+            }
+        }
+    }
+};
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    impl ::scale_info::TypeInfo for Call {
+        type Identity = Self;
+        fn type_info() -> ::scale_info::Type {
+            :: scale_info :: Type :: builder () . path (:: scale_info :: Path :: new ("Call" , "simple_runtime")) . type_params (:: alloc :: vec :: Vec :: new ()) . docs (& []) . variant (:: scale_info :: build :: Variants :: new () . variant ("System" , | v | v . index (0u8 as :: core :: primitive :: u8) . fields (:: scale_info :: build :: Fields :: unnamed () . field (| f | f . ty :: < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < System , Runtime > > () . type_name ("self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch\n::CallableCallFor<System, Runtime>") . docs (& []))) . docs (& [])) . variant ("SimplePallet" , | v | v . index (1u8 as :: core :: primitive :: u8) . fields (:: scale_info :: build :: Fields :: unnamed () . field (| f | f . ty :: < self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < SimplePallet , Runtime > > () . type_name ("self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch\n::CallableCallFor<SimplePallet, Runtime>") . docs (& []))) . docs (& [])))
+        }
+    };
+};
+impl core::fmt::Debug for Call {
+    fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+        match self {
+            Self::System(ref a0) => fmt.debug_tuple("Call::System").field(a0).finish(),
+            Self::SimplePallet(ref a0) => fmt.debug_tuple("Call::SimplePallet").field(a0).finish(),
+            _ => Ok(()),
+        }
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::GetDispatchInfo
+    for Call
+{
+    fn get_dispatch_info(
+        &self,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::DispatchInfo
+    {
+        match self {
+            Call::System(call) => call.get_dispatch_info(),
+            Call::SimplePallet(call) => call.get_dispatch_info(),
+        }
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::GetCallMetadata
+    for Call
+{
+    fn get_call_metadata(
+        &self,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallMetadata
+    {
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::GetCallName;
+        match self {
+            Call::System(call) => {
+                let function_name = call.get_call_name();
+                let pallet_name = "System";
+                self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallMetadata { function_name , pallet_name , }
+            }
+            Call::SimplePallet(call) => {
+                let function_name = call.get_call_name();
+                let pallet_name = "SimplePallet";
+                self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallMetadata { function_name , pallet_name , }
+            }
+        }
+    }
+    fn get_module_names() -> &'static [&'static str] {
+        &["System", "SimplePallet"]
+    }
+    fn get_call_names(module: &str) -> &'static [&'static str] {
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::{
+            Callable, GetCallName,
+        };
+        match module {
+            "System" => <<System as Callable<Runtime>>::Call as GetCallName>::get_call_names(),
+            "SimplePallet" => {
+                <<SimplePallet as Callable<Runtime>>::Call as GetCallName>::get_call_names()
+            }
+            _ => ::core::panicking::panic("internal error: entered unreachable code"),
+        }
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::Dispatchable
+    for Call
+{
+    type Origin = Origin;
+    type Config = Call;
+    type Info =
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::weights::DispatchInfo;
+    type PostInfo =
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::weights::PostDispatchInfo;    fn dispatch (self , origin : Origin) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: DispatchResultWithPostInfo{
+        if ! < Self :: Origin as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OriginTrait > :: filter_call (& origin , & self) { return self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_std :: result :: Result :: Err (frame_system :: Error :: < Runtime > :: CallFiltered . into ()) ; }
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: UnfilteredDispatchable :: dispatch_bypass_filter (self , origin)
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::UnfilteredDispatchable
+    for Call
+{
+    type Origin = Origin;    fn dispatch_bypass_filter (self , origin : Origin) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: DispatchResultWithPostInfo{
+        match self { Call :: System (call) => self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: UnfilteredDispatchable :: dispatch_bypass_filter (call , origin) , Call :: SimplePallet (call) => self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: UnfilteredDispatchable :: dispatch_bypass_filter (call , origin) , }
+    }
+}
+impl self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: DispatchableWithStorageLayer for Call { type Origin = Origin ; fn dispatch_with_storage_layer (self , origin : Origin) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: DispatchResultWithPostInfo { self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: storage :: with_storage_layer (| | { self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: Dispatchable :: dispatch (self , origin) }) } fn dispatch_bypass_filter_with_storage_layer (self , origin : Origin) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: DispatchResultWithPostInfo { self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: storage :: with_storage_layer (| | { self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: UnfilteredDispatchable :: dispatch_bypass_filter (self , origin) }) } }
+impl
+    self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::IsSubType<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            System,
+            Runtime,
+        >,
+    > for Call
+{
+    #[allow(unreachable_patterns)]
+    fn is_sub_type(
+        &self,
+    ) -> Option<
+        &self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            System,
+            Runtime,
+        >,
+    > {
+        match self {
+            Call::System(call) => Some(call),
+            _ => None,
+        }
+    }
+}
+impl
+    From<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            System,
+            Runtime,
+        >,
+    > for Call
+{
+    fn from(
+        call : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < System , Runtime >,
+    ) -> Self {
+        Call::System(call)
+    }
+}
+impl
+    self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::IsSubType<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            SimplePallet,
+            Runtime,
+        >,
+    > for Call
+{
+    #[allow(unreachable_patterns)]
+    fn is_sub_type(
+        &self,
+    ) -> Option<
+        &self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            SimplePallet,
+            Runtime,
+        >,
+    > {
+        match self {
+            Call::SimplePallet(call) => Some(call),
+            _ => None,
+        }
+    }
+}
+impl
+    From<
+        self::sp_api_hidden_includes_construct_runtime::hidden_include::dispatch::CallableCallFor<
+            SimplePallet,
+            Runtime,
+        >,
+    > for Call
+{
+    fn from(
+        call : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: dispatch :: CallableCallFor < SimplePallet , Runtime >,
+    ) -> Self {
+        Call::SimplePallet(call)
+    }
+}
+impl Runtime {
+    pub fn metadata () -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: RuntimeMetadataPrefixed{
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: RuntimeMetadataLastVersion :: new (< [_] > :: into_vec (# [rustc_box] :: alloc :: boxed :: Box :: new ([self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: PalletMetadata { name : "System" , index : 0u8 , storage : Some (frame_system :: Pallet :: < Runtime > :: storage_metadata ()) , calls : Some (frame_system :: Pallet :: < Runtime > :: call_functions ()) , event : Some (self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: PalletEventMetadata { ty : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: scale_info :: meta_type :: < frame_system :: Event < Runtime > > () , }) , constants : frame_system :: Pallet :: < Runtime > :: pallet_constants_metadata () , error : frame_system :: Pallet :: < Runtime > :: error_metadata () , } , self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: PalletMetadata { name : "SimplePallet" , index : 1u8 , storage : Some (simple_pallet :: Pallet :: < Runtime > :: storage_metadata ()) , calls : Some (simple_pallet :: Pallet :: < Runtime > :: call_functions ()) , event : None , constants : simple_pallet :: Pallet :: < Runtime > :: pallet_constants_metadata () , error : simple_pallet :: Pallet :: < Runtime > :: error_metadata () , }])) , self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: ExtrinsicMetadata { ty : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: scale_info :: meta_type :: < UncheckedExtrinsic > () , version : < UncheckedExtrinsic as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: ExtrinsicMetadata > :: VERSION , signed_extensions : < < UncheckedExtrinsic as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: ExtrinsicMetadata > :: SignedExtensions as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: traits :: SignedExtension > :: metadata () . into_iter () . map (| meta | self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: metadata :: SignedExtensionMetadata { identifier : meta . identifier , ty : meta . ty , additional_signed : meta . additional_signed , }) . collect () , } , self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: scale_info :: meta_type :: < Runtime > ()) . into ()
+    }
+}
+#[cfg(any(feature = "std", test))]
+pub type SystemConfig = frame_system::GenesisConfig;
+#[cfg(any(feature = "std", test))]
+use self::sp_api_hidden_includes_construct_runtime::hidden_include::serde as __genesis_config_serde_import__;
+#[cfg(any(feature = "std", test))]
+#[serde(rename_all = "camelCase")]
+#[serde(deny_unknown_fields)]
+#[serde(crate = "__genesis_config_serde_import__")]
+pub struct GenesisConfig {
+    pub system: SystemConfig,
+}
+#[doc(hidden)]
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    use __genesis_config_serde_import__ as _serde;
+    #[automatically_derived]
+    impl __genesis_config_serde_import__::Serialize for GenesisConfig {
+        fn serialize<__S>(
+            &self,
+            __serializer: __S,
+        ) -> __genesis_config_serde_import__::__private::Result<__S::Ok, __S::Error>
+        where
+            __S: __genesis_config_serde_import__::Serializer,
+        {
+            let mut __serde_state = match _serde::Serializer::serialize_struct(
+                __serializer,
+                "GenesisConfig",
+                false as usize + 1,
+            ) {
+                _serde::__private::Ok(__val) => __val,
+                _serde::__private::Err(__err) => {
+                    return _serde::__private::Err(__err);
+                }
+            };
+            match _serde::ser::SerializeStruct::serialize_field(
+                &mut __serde_state,
+                "system",
+                &self.system,
+            ) {
+                _serde::__private::Ok(__val) => __val,
+                _serde::__private::Err(__err) => {
+                    return _serde::__private::Err(__err);
+                }
+            };
+            _serde::ser::SerializeStruct::end(__serde_state)
+        }
+    }
+};
+#[doc(hidden)]
+#[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+const _: () = {
+    use __genesis_config_serde_import__ as _serde;
+    #[automatically_derived]
+    impl<'de> __genesis_config_serde_import__::Deserialize<'de> for GenesisConfig {
+        fn deserialize<__D>(
+            __deserializer: __D,
+        ) -> __genesis_config_serde_import__::__private::Result<Self, __D::Error>
+        where
+            __D: __genesis_config_serde_import__::Deserializer<'de>,
+        {
+            #[allow(non_camel_case_types)]
+            enum __Field {
+                __field0,
+            }
+            struct __FieldVisitor;
+            impl<'de> _serde::de::Visitor<'de> for __FieldVisitor {
+                type Value = __Field;
+                fn expecting(
+                    &self,
+                    __formatter: &mut _serde::__private::Formatter,
+                ) -> _serde::__private::fmt::Result {
+                    _serde::__private::Formatter::write_str(__formatter, "field identifier")
+                }
+                fn visit_u64<__E>(self, __value: u64) -> _serde::__private::Result<Self::Value, __E>
+                where
+                    __E: _serde::de::Error,
+                {
+                    match __value {
+                        0u64 => _serde::__private::Ok(__Field::__field0),
+                        _ => _serde::__private::Err(_serde::de::Error::invalid_value(
+                            _serde::de::Unexpected::Unsigned(__value),
+                            &"field index 0 <= i < 1",
+                        )),
+                    }
+                }
+                fn visit_str<__E>(
+                    self,
+                    __value: &str,
+                ) -> _serde::__private::Result<Self::Value, __E>
+                where
+                    __E: _serde::de::Error,
+                {
+                    match __value {
+                        "system" => _serde::__private::Ok(__Field::__field0),
+                        _ => _serde::__private::Err(_serde::de::Error::unknown_field(
+                            __value, FIELDS,
+                        )),
+                    }
+                }
+                fn visit_bytes<__E>(
+                    self,
+                    __value: &[u8],
+                ) -> _serde::__private::Result<Self::Value, __E>
+                where
+                    __E: _serde::de::Error,
+                {
+                    match __value {
+                        b"system" => _serde::__private::Ok(__Field::__field0),
+                        _ => {
+                            let __value = &_serde::__private::from_utf8_lossy(__value);
+                            _serde::__private::Err(_serde::de::Error::unknown_field(
+                                __value, FIELDS,
+                            ))
+                        }
+                    }
+                }
+            }
+            impl<'de> _serde::Deserialize<'de> for __Field {
+                #[inline]
+                fn deserialize<__D>(
+                    __deserializer: __D,
+                ) -> _serde::__private::Result<Self, __D::Error>
+                where
+                    __D: _serde::Deserializer<'de>,
+                {
+                    _serde::Deserializer::deserialize_identifier(__deserializer, __FieldVisitor)
+                }
+            }
+            struct __Visitor<'de> {
+                marker: _serde::__private::PhantomData<GenesisConfig>,
+                lifetime: _serde::__private::PhantomData<&'de ()>,
+            }
+            impl<'de> _serde::de::Visitor<'de> for __Visitor<'de> {
+                type Value = GenesisConfig;
+                fn expecting(
+                    &self,
+                    __formatter: &mut _serde::__private::Formatter,
+                ) -> _serde::__private::fmt::Result {
+                    _serde::__private::Formatter::write_str(__formatter, "struct GenesisConfig")
+                }
+                #[inline]
+                fn visit_seq<__A>(
+                    self,
+                    mut __seq: __A,
+                ) -> _serde::__private::Result<Self::Value, __A::Error>
+                where
+                    __A: _serde::de::SeqAccess<'de>,
+                {
+                    let __field0 =
+                        match match _serde::de::SeqAccess::next_element::<SystemConfig>(&mut __seq)
+                        {
+                            _serde::__private::Ok(__val) => __val,
+                            _serde::__private::Err(__err) => {
+                                return _serde::__private::Err(__err);
+                            }
+                        } {
+                            _serde::__private::Some(__value) => __value,
+                            _serde::__private::None => {
+                                return _serde::__private::Err(_serde::de::Error::invalid_length(
+                                    0usize,
+                                    &"struct GenesisConfig with 1 element",
+                                ));
+                            }
+                        };
+                    _serde::__private::Ok(GenesisConfig { system: __field0 })
+                }
+                #[inline]
+                fn visit_map<__A>(
+                    self,
+                    mut __map: __A,
+                ) -> _serde::__private::Result<Self::Value, __A::Error>
+                where
+                    __A: _serde::de::MapAccess<'de>,
+                {
+                    let mut __field0: _serde::__private::Option<SystemConfig> =
+                        _serde::__private::None;
+                    while let _serde::__private::Some(__key) =
+                        match _serde::de::MapAccess::next_key::<__Field>(&mut __map) {
+                            _serde::__private::Ok(__val) => __val,
+                            _serde::__private::Err(__err) => {
+                                return _serde::__private::Err(__err);
+                            }
+                        }
+                    {
+                        match __key {
+                            __Field::__field0 => {
+                                if _serde::__private::Option::is_some(&__field0) {
+                                    return _serde::__private::Err(
+                                        <__A::Error as _serde::de::Error>::duplicate_field(
+                                            "system",
+                                        ),
+                                    );
+                                }
+                                __field0 = _serde::__private::Some(
+                                    match _serde::de::MapAccess::next_value::<SystemConfig>(
+                                        &mut __map,
+                                    ) {
+                                        _serde::__private::Ok(__val) => __val,
+                                        _serde::__private::Err(__err) => {
+                                            return _serde::__private::Err(__err);
+                                        }
+                                    },
+                                );
+                            }
+                        }
+                    }
+                    let __field0 = match __field0 {
+                        _serde::__private::Some(__field0) => __field0,
+                        _serde::__private::None => {
+                            match _serde::__private::de::missing_field("system") {
+                                _serde::__private::Ok(__val) => __val,
+                                _serde::__private::Err(__err) => {
+                                    return _serde::__private::Err(__err);
+                                }
+                            }
+                        }
+                    };
+                    _serde::__private::Ok(GenesisConfig { system: __field0 })
+                }
+            }
+            const FIELDS: &'static [&'static str] = &["system"];
+            _serde::Deserializer::deserialize_struct(
+                __deserializer,
+                "GenesisConfig",
+                FIELDS,
+                __Visitor {
+                    marker: _serde::__private::PhantomData::<GenesisConfig>,
+                    lifetime: _serde::__private::PhantomData,
+                },
+            )
+        }
+    }
+};
+#[automatically_derived]
+#[allow(unused_qualifications)]
+impl ::core::default::Default for GenesisConfig {
+    #[inline]
+    fn default() -> GenesisConfig {
+        GenesisConfig {
+            system: ::core::default::Default::default(),
+        }
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_runtime::BuildStorage
+    for GenesisConfig
+{
+    fn assimilate_storage(
+        &self,
+        storage : & mut self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: Storage,
+    ) -> std::result::Result<(), String> {
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: sp_runtime :: BuildModuleGenesisStorage :: < Runtime , frame_system :: __InherentHiddenInstance > :: build_module_genesis_storage (& self . system , storage) ? ;
+        self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: BasicExternalities :: execute_with_storage (storage , | | { < AllPalletsWithSystem as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: traits :: OnGenesis > :: on_genesis () ; }) ;
+        Ok(())
+    }
+}
+trait InherentDataExt {
+    fn create_extrinsics (& self) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: Vec < < Block as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: BlockT > :: Extrinsic > ;
+    fn check_extrinsics (& self , block : & Block) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: CheckInherentsResult ;
+}
+impl InherentDataExt
+    for self::sp_api_hidden_includes_construct_runtime::hidden_include::inherent::InherentData
+{
+    fn create_extrinsics (& self) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: Vec < < Block as self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: BlockT > :: Extrinsic >{
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::inherent::ProvideInherent;
+        let mut inherents = Vec::new();
+        inherents
+    }    fn check_extrinsics (& self , block : & Block) -> self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: CheckInherentsResult{
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::inherent::{
+            ProvideInherent, IsFatalError,
+        };
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::{
+            IsSubType, ExtrinsicCall,
+        };
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_runtime::traits::Block as _;
+        let mut result = self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: CheckInherentsResult :: new () ;
+        for xt in block.extrinsics() {
+            if self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: Extrinsic :: is_signed (xt) . unwrap_or (false) { break }
+            let mut is_inherent = false;
+            if !is_inherent {
+                break;
+            }
+        }
+        result
+    }
+}
+impl
+    self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::EnsureInherentsAreFirst<
+        Block,
+    > for Runtime
+{
+    fn ensure_inherents_are_first(block: &Block) -> Result<(), u32> {
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::inherent::ProvideInherent;
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::traits::{
+            IsSubType, ExtrinsicCall,
+        };
+        use self::sp_api_hidden_includes_construct_runtime::hidden_include::sp_runtime::traits::Block as _;
+        let mut first_signed_observed = false;
+        for (i, xt) in block.extrinsics().iter().enumerate() {
+            let is_signed = self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: inherent :: Extrinsic :: is_signed (xt) . unwrap_or (false) ;
+            let is_inherent = if is_signed {
+                false
+            } else {
+                let mut is_inherent = false;
+                is_inherent
+            };
+            if !is_inherent {
+                first_signed_observed = true;
+            }
+            if first_signed_observed && is_inherent {
+                return Err(i as u32);
+            }
+        }
+        Ok(())
+    }
+}
+impl self::sp_api_hidden_includes_construct_runtime::hidden_include::unsigned::ValidateUnsigned
+    for Runtime
+{
+    type Call = Call;    fn pre_dispatch (call : & Self :: Call) -> Result < () , self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: unsigned :: TransactionValidityError >{
+        #[allow(unreachable_patterns)]
+        match call {
+            _ => Ok(()),
+        }
+    }
+    fn validate_unsigned(
+        # [allow (unused_variables)] source : self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: unsigned :: TransactionSource,
+        call: &Self::Call,
+    ) -> self::sp_api_hidden_includes_construct_runtime::hidden_include::unsigned::TransactionValidity
+    {
+        # [allow (unreachable_patterns)] match call { _ => self :: sp_api_hidden_includes_construct_runtime :: hidden_include :: unsigned :: UnknownTransaction :: NoUnsignedValidator . into () , }
+    }
+}
+const _: () =
+    if !(<frame_system::Error<Runtime> as ::frame_support::traits::PalletError>::MAX_ENCODED_SIZE
+        <= ::frame_support::MAX_MODULE_ERROR_ENCODED_SIZE)
+    {
+        :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["The maximum encoded size of the error type in the `System` pallet exceeds `MAX_MODULE_ERROR_ENCODED_SIZE`"] , & []))
+    };
+pub type Address = sp_runtime::MultiAddress<AccountId, ()>;
+pub type Header = generic::Header<BlockNumber, BlakeTwo256>;
+pub type Block = generic::Block<Header, UncheckedExtrinsic>;
+pub type SignedExtra = (
+    frame_system::CheckGenesis<Runtime>,
+    frame_system::CheckNonce<Runtime>,
+);
+pub type UncheckedExtrinsic = generic::UncheckedExtrinsic<Address, Call, Signature, SignedExtra>;
+pub type SignedPayload = generic::SignedPayload<Call, SignedExtra>;
+pub type Executive = frame_executive::Executive<
+    Runtime,
+    Block,
+    frame_system::ChainContext<Runtime>,
+    Runtime,
+    AllPalletsWithSystem,
+>;
+#[doc(hidden)]
+mod sp_api_hidden_includes_IMPL_RUNTIME_APIS {
+    pub extern crate sp_api as sp_api;
+}
+pub struct RuntimeApi {}
+/// Implements all runtime apis for the client side.
+#[cfg(any(feature = "std", test))]
+pub struct RuntimeApiImpl<
+    Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+    C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block> + 'static,
+> {
+    call: &'static C,
+    commit_on_success: std::cell::RefCell<bool>,
+    changes: std::cell::RefCell<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::OverlayedChanges,
+    >,
+    storage_transaction_cache: std::cell::RefCell<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StorageTransactionCache<
+            Block,
+            C::StateBackend,
+        >,
+    >,
+    recorder: std::option::Option<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ProofRecorder<Block>,
+    >,
+}
+#[cfg(any(feature = "std", test))]
+unsafe impl<
+        Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+        C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block>,
+    > Send for RuntimeApiImpl<Block, C>
+{
+}
+#[cfg(any(feature = "std", test))]
+unsafe impl<
+        Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+        C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block>,
+    > Sync for RuntimeApiImpl<Block, C>
+{
+}
+#[cfg(any(feature = "std", test))]
+impl<
+        Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+        C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block>,
+    > self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiExt<Block>
+    for RuntimeApiImpl<Block, C>
+{
+    type StateBackend = C::StateBackend;
+    fn execute_in_transaction<
+        F: FnOnce(
+            &Self,
+        )
+            -> self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::TransactionOutcome<R>,
+        R,
+    >(
+        &self,
+        call: F,
+    ) -> R
+    where
+        Self: Sized,
+    {
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::OverlayedChanges::start_transaction(
+            &mut std::cell::RefCell::borrow_mut(&self.changes),
+        );
+        *std::cell::RefCell::borrow_mut(&self.commit_on_success) = false;
+        let res = call(self);
+        *std::cell::RefCell::borrow_mut(&self.commit_on_success) = true;
+        self.commit_or_rollback(match res {
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::TransactionOutcome::Commit(
+                _,
+            ) => true,
+            _ => false,
+        });
+        res.into_inner()
+    }
+    fn has_api<A: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::RuntimeApiInfo + ?Sized>(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<Block>,
+    ) -> std::result::Result<bool, self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError>
+    where
+        Self: Sized,
+    {
+        self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: CallApiAt :: < Block > :: runtime_version_at (self . call , at) . map (| v | self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: RuntimeVersion :: has_api_with (& v , & A :: ID , | v | v == A :: VERSION))
+    }
+    fn has_api_with<
+        A: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::RuntimeApiInfo + ?Sized,
+        P: Fn(u32) -> bool,
+    >(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<Block>,
+        pred: P,
+    ) -> std::result::Result<bool, self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError>
+    where
+        Self: Sized,
+    {
+        self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: CallApiAt :: < Block > :: runtime_version_at (self . call , at) . map (| v | self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: RuntimeVersion :: has_api_with (& v , & A :: ID , pred))
+    }
+    fn api_version<
+        A: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::RuntimeApiInfo + ?Sized,
+    >(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<Block>,
+    ) -> std::result::Result<
+        Option<u32>,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    >
+    where
+        Self: Sized,
+    {
+        self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: CallApiAt :: < Block > :: runtime_version_at (self . call , at) . map (| v | self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: RuntimeVersion :: api_version (& v , & A :: ID))
+    }
+    fn record_proof(&mut self) {
+        self.recorder = std::option::Option::Some(std::default::Default::default());
+    }
+    fn proof_recorder(
+        &self,
+    ) -> std::option::Option<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ProofRecorder<Block>,
+    > {
+        std::clone::Clone::clone(&self.recorder)
+    }
+    fn extract_proof(
+        &mut self,
+    ) -> std::option::Option<self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StorageProof>
+    {
+        std :: option :: Option :: take (& mut self . recorder) . map (| recorder | self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: ProofRecorder :: < Block > :: to_storage_proof (& recorder))
+    }
+    fn into_storage_changes(
+        &self,
+        backend: &Self::StateBackend,
+        parent_hash: Block::Hash,
+    ) -> core::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StorageChanges<
+            C::StateBackend,
+            Block,
+        >,
+        String,
+    >
+    where
+        Self: Sized,
+    {
+        let at = self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId::Hash(
+            std::clone::Clone::clone(&parent_hash),
+        );
+        let state_version = self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt::<
+            Block,
+        >::runtime_version_at(self.call, &at)
+        .map(|v| {
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::RuntimeVersion::state_version(
+                &v,
+            )
+        })
+        .map_err(|e| {
+            let res = ::alloc::fmt::format(::core::fmt::Arguments::new_v1(
+                &["Failed to get state version: "],
+                &[::core::fmt::ArgumentV1::new_display(&e)],
+            ));
+            res
+        })?;
+        self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: OverlayedChanges :: into_storage_changes (std :: cell :: RefCell :: take (& self . changes) , backend , core :: cell :: RefCell :: take (& self . storage_transaction_cache) , state_version)
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl<Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT, C>
+    self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ConstructRuntimeApi<Block, C>
+    for RuntimeApi
+where
+    C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block> + 'static,
+{
+    type RuntimeApi = RuntimeApiImpl<Block, C>;
+    fn construct_runtime_api<'a>(
+        call: &'a C,
+    ) -> self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiRef<'a, Self::RuntimeApi> {
+        RuntimeApiImpl {
+            call: unsafe { std::mem::transmute(call) },
+            commit_on_success: true.into(),
+            changes: std::default::Default::default(),
+            recorder: std::default::Default::default(),
+            storage_transaction_cache: std::default::Default::default(),
+        }
+        .into()
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl<
+        Block: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT,
+        C: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<Block>,
+    > RuntimeApiImpl<Block, C>
+{
+    fn call_api_at<
+        R: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode
+            + self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Decode
+            + std::cmp::PartialEq,
+        F: FnOnce(
+            &C,
+            &std::cell::RefCell<
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::OverlayedChanges,
+            >,
+            &std::cell::RefCell<
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StorageTransactionCache<
+                    Block,
+                    C::StateBackend,
+                >,
+            >,
+            &std::option::Option<
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ProofRecorder<Block>,
+            >,
+        ) -> std::result::Result<
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<R>,
+            E,
+        >,
+        E,
+    >(
+        &self,
+        call_api_at: F,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<R>,
+        E,
+    > {
+        if *std::cell::RefCell::borrow(&self.commit_on_success) {
+            self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: OverlayedChanges :: start_transaction (& mut std :: cell :: RefCell :: borrow_mut (& self . changes)) ;
+        }
+        let res = call_api_at(
+            &self.call,
+            &self.changes,
+            &self.storage_transaction_cache,
+            &self.recorder,
+        );
+        self.commit_or_rollback(std::result::Result::is_ok(&res));
+        res
+    }
+    fn commit_or_rollback(&self, commit: bool) {
+        let proof = "\
+					We only close a transaction when we opened one ourself.
+					Other parts of the runtime that make use of transactions (state-machine)
+					also balance their transactions. The runtime cannot close client initiated
+					transactions; qed";
+        if *std::cell::RefCell::borrow(&self.commit_on_success) {
+            let res = if commit {
+                self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: OverlayedChanges :: commit_transaction (& mut std :: cell :: RefCell :: borrow_mut (& self . changes))
+            } else {
+                self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: OverlayedChanges :: rollback_transaction (& mut std :: cell :: RefCell :: borrow_mut (& self . changes))
+            };
+            std::result::Result::expect(res, proof);
+        }
+    }
+}
+impl sp_api::runtime_decl_for_Core::Core<Block> for Runtime {
+    fn version() -> RuntimeVersion {
+        VERSION
+    }
+    fn execute_block(block: Block) {
+        Executive::execute_block(block);
+    }
+    fn initialize_block(header: &<Block as BlockT>::Header) {
+        Executive::initialize_block(header)
+    }
+}
+impl sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<Block> for Runtime {
+    fn apply_extrinsic(extrinsic: <Block as BlockT>::Extrinsic) -> ApplyExtrinsicResult {
+        Executive::apply_extrinsic(extrinsic)
+    }
+    fn finalize_block() -> <Block as BlockT>::Header {
+        Executive::finalize_block()
+    }
+    fn inherent_extrinsics(_: sp_inherents::InherentData) -> Vec<<Block as BlockT>::Extrinsic> {
+        ::core::panicking::panic("not implemented")
+    }
+    fn check_inherents(
+        _: Block,
+        _: sp_inherents::InherentData,
+    ) -> sp_inherents::CheckInherentsResult {
+        ::core::panicking::panic("not implemented")
+    }
+}
+impl sp_transaction_pool :: runtime_api :: runtime_decl_for_TaggedTransactionQueue :: TaggedTransactionQueue < Block > for Runtime { fn validate_transaction (source : TransactionSource , tx : < Block as BlockT > :: Extrinsic , block_hash : < Block as BlockT > :: Hash) -> TransactionValidity { Executive :: validate_transaction (source , tx , block_hash) } }
+#[cfg(any(feature = "std", test))]
+impl<
+        __SR_API_BLOCK__: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT
+            + std::panic::UnwindSafe
+            + std::panic::RefUnwindSafe,
+        RuntimeApiImplCall: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<__SR_API_BLOCK__>
+            + 'static,
+    > sp_api::Core<__SR_API_BLOCK__> for RuntimeApiImpl<__SR_API_BLOCK__, RuntimeApiImplCall>
+where
+    RuntimeApiImplCall::StateBackend:
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StateBackend<
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::HashFor<__SR_API_BLOCK__>,
+        >,
+    RuntimeVersion: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    <__SR_API_BLOCK__ as BlockT>::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+{
+    fn Core_version_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<()>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<RuntimeVersion>,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self.call_api_at(
+            |call_runtime_at, changes, storage_transaction_cache, recorder| {
+                sp_api::runtime_decl_for_Core::version_call_api_at(
+                    call_runtime_at,
+                    at,
+                    params_encoded,
+                    changes,
+                    storage_transaction_cache,
+                    params.map(|p| {
+                        sp_api::runtime_decl_for_Core::version_native_call_generator::<
+                            Runtime,
+                            __SR_API_BLOCK__,
+                            Block,
+                        >()
+                    }),
+                    context,
+                    recorder,
+                )
+            },
+        )
+    }
+    fn Core_execute_block_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(__SR_API_BLOCK__)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<()>,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self.call_api_at(
+            |call_runtime_at, changes, storage_transaction_cache, recorder| {
+                sp_api::runtime_decl_for_Core::execute_block_call_api_at(
+                    call_runtime_at,
+                    at,
+                    params_encoded,
+                    changes,
+                    storage_transaction_cache,
+                    params.map(|p| {
+                        sp_api::runtime_decl_for_Core::execute_block_native_call_generator::<
+                            Runtime,
+                            __SR_API_BLOCK__,
+                            Block,
+                        >(p)
+                    }),
+                    context,
+                    recorder,
+                )
+            },
+        )
+    }
+    fn Core_initialize_block_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(&<__SR_API_BLOCK__ as BlockT>::Header)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<()>,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self.call_api_at(
+            |call_runtime_at, changes, storage_transaction_cache, recorder| {
+                sp_api::runtime_decl_for_Core::initialize_block_call_api_at(
+                    call_runtime_at,
+                    at,
+                    params_encoded,
+                    changes,
+                    storage_transaction_cache,
+                    params.map(|p| {
+                        sp_api::runtime_decl_for_Core::initialize_block_native_call_generator::<
+                            Runtime,
+                            __SR_API_BLOCK__,
+                            Block,
+                        >(p)
+                    }),
+                    context,
+                    recorder,
+                )
+            },
+        )
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl<
+        __SR_API_BLOCK__: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT
+            + std::panic::UnwindSafe
+            + std::panic::RefUnwindSafe,
+        RuntimeApiImplCall: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<__SR_API_BLOCK__>
+            + 'static,
+    > sp_block_builder::BlockBuilder<__SR_API_BLOCK__>
+    for RuntimeApiImpl<__SR_API_BLOCK__, RuntimeApiImplCall>
+where
+    RuntimeApiImplCall::StateBackend:
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StateBackend<
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::HashFor<__SR_API_BLOCK__>,
+        >,
+    <__SR_API_BLOCK__ as BlockT>::Extrinsic: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    ApplyExtrinsicResult: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    <__SR_API_BLOCK__ as BlockT>::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    sp_inherents::InherentData: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    Vec<<__SR_API_BLOCK__ as BlockT>::Extrinsic>:
+        std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    sp_inherents::InherentData: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    sp_inherents::CheckInherentsResult: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+{
+    fn BlockBuilder_apply_extrinsic_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(<__SR_API_BLOCK__ as BlockT>::Extrinsic)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            ApplyExtrinsicResult,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_block_builder :: runtime_decl_for_BlockBuilder :: apply_extrinsic_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_block_builder :: runtime_decl_for_BlockBuilder :: apply_extrinsic_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > (p) }) , context , recorder) })
+    }
+    fn BlockBuilder_finalize_block_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<()>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            <__SR_API_BLOCK__ as BlockT>::Header,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_block_builder :: runtime_decl_for_BlockBuilder :: finalize_block_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_block_builder :: runtime_decl_for_BlockBuilder :: finalize_block_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > () }) , context , recorder) })
+    }
+    fn BlockBuilder_inherent_extrinsics_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(sp_inherents::InherentData)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            Vec<<__SR_API_BLOCK__ as BlockT>::Extrinsic>,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_block_builder :: runtime_decl_for_BlockBuilder :: inherent_extrinsics_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_block_builder :: runtime_decl_for_BlockBuilder :: inherent_extrinsics_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > (p) }) , context , recorder) })
+    }
+    fn BlockBuilder_check_inherents_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(__SR_API_BLOCK__, sp_inherents::InherentData)>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            sp_inherents::CheckInherentsResult,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_block_builder :: runtime_decl_for_BlockBuilder :: check_inherents_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_block_builder :: runtime_decl_for_BlockBuilder :: check_inherents_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > (p . 0 , p . 1) }) , context , recorder) })
+    }
+}
+#[cfg(any(feature = "std", test))]
+impl<
+        __SR_API_BLOCK__: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockT
+            + std::panic::UnwindSafe
+            + std::panic::RefUnwindSafe,
+        RuntimeApiImplCall: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::CallApiAt<__SR_API_BLOCK__>
+            + 'static,
+    > sp_transaction_pool::runtime_api::TaggedTransactionQueue<__SR_API_BLOCK__>
+    for RuntimeApiImpl<__SR_API_BLOCK__, RuntimeApiImplCall>
+where
+    RuntimeApiImplCall::StateBackend:
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::StateBackend<
+            self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::HashFor<__SR_API_BLOCK__>,
+        >,
+    TransactionSource: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    <__SR_API_BLOCK__ as BlockT>::Extrinsic: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    <__SR_API_BLOCK__ as BlockT>::Hash: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    TransactionValidity: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+    __SR_API_BLOCK__::Header: std::panic::UnwindSafe + std::panic::RefUnwindSafe,
+{
+    fn TaggedTransactionQueue_validate_transaction_runtime_api_impl(
+        &self,
+        at: &self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::BlockId<__SR_API_BLOCK__>,
+        context: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ExecutionContext,
+        params: Option<(
+            TransactionSource,
+            <__SR_API_BLOCK__ as BlockT>::Extrinsic,
+            <__SR_API_BLOCK__ as BlockT>::Hash,
+        )>,
+        params_encoded: Vec<u8>,
+    ) -> std::result::Result<
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::NativeOrEncoded<
+            TransactionValidity,
+        >,
+        self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApiError,
+    > {
+        self . call_api_at (| call_runtime_at , changes , storage_transaction_cache , recorder | { sp_transaction_pool :: runtime_api :: runtime_decl_for_TaggedTransactionQueue :: validate_transaction_call_api_at (call_runtime_at , at , params_encoded , changes , storage_transaction_cache , params . map (| p | { sp_transaction_pool :: runtime_api :: runtime_decl_for_TaggedTransactionQueue :: validate_transaction_native_call_generator :: < Runtime , __SR_API_BLOCK__ , Block > (p . 0 , p . 1 , p . 2) }) , context , recorder) })
+    }
+}
+const RUNTIME_API_VERSIONS: self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::ApisVec =
+    ::sp_version::sp_std::borrow::Cow::Borrowed(&[
+        (
+            sp_api::runtime_decl_for_Core::ID,
+            sp_api::runtime_decl_for_Core::VERSION,
+        ),
+        (
+            sp_block_builder::runtime_decl_for_BlockBuilder::ID,
+            sp_block_builder::runtime_decl_for_BlockBuilder::VERSION,
+        ),
+        (
+            sp_transaction_pool::runtime_api::runtime_decl_for_TaggedTransactionQueue::ID,
+            sp_transaction_pool::runtime_api::runtime_decl_for_TaggedTransactionQueue::VERSION,
+        ),
+    ]);
+const _: () = {};
+const _: () = {};
+const _: () = {};
+pub mod api {
+    use super::*;
+    #[cfg(feature = "std")]
+    pub fn dispatch(method: &str, mut __sp_api__input_data: &[u8]) -> Option<Vec<u8>> {
+        match method {
+            "Core_version" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let () : () = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "version") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_api::runtime_decl_for_Core::Core<Block>>::version()
+                }),
+            ),
+            "Core_execute_block" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (block) : (Block) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "execute_block") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_api::runtime_decl_for_Core::Core<Block>>::execute_block(block)
+                }),
+            ),
+            "Core_initialize_block" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (header) : (< Block as BlockT > :: Header) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "initialize_block") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_api::runtime_decl_for_Core::Core<Block>>::initialize_block(
+                        &header,
+                    )
+                }),
+            ),
+            "BlockBuilder_apply_extrinsic" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (extrinsic) : (< Block as BlockT > :: Extrinsic) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "apply_extrinsic") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<
+                        Block,
+                    >>::apply_extrinsic(extrinsic)
+                }),
+            ),
+            "BlockBuilder_finalize_block" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let () : () = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "finalize_block") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<
+                        Block,
+                    >>::finalize_block()
+                }),
+            ),
+            "BlockBuilder_inherent_extrinsics" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (__runtime_api_generated_name_0__) : (sp_inherents :: InherentData) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "inherent_extrinsics") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<
+                        Block,
+                    >>::inherent_extrinsics(__runtime_api_generated_name_0__)
+                }),
+            ),
+            "BlockBuilder_check_inherents" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (__runtime_api_generated_name_0__ , __runtime_api_generated_name_1__) : (Block , sp_inherents :: InherentData) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "check_inherents") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    #[allow(deprecated)]
+                    <Runtime as sp_block_builder::runtime_decl_for_BlockBuilder::BlockBuilder<
+                        Block,
+                    >>::check_inherents(
+                        __runtime_api_generated_name_0__,
+                        __runtime_api_generated_name_1__,
+                    )
+                }),
+            ),
+            "TaggedTransactionQueue_validate_transaction" => Some(
+                self::sp_api_hidden_includes_IMPL_RUNTIME_APIS::sp_api::Encode::encode(&{
+                    let (source , tx , block_hash) : (TransactionSource , < Block as BlockT > :: Extrinsic , < Block as BlockT > :: Hash) = match self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: DecodeLimit :: decode_all_with_depth_limit (self :: sp_api_hidden_includes_IMPL_RUNTIME_APIS :: sp_api :: MAX_EXTRINSIC_DEPTH , & mut __sp_api__input_data) { Ok (res) => res , Err (e) => :: core :: panicking :: panic_fmt (:: core :: fmt :: Arguments :: new_v1 (& ["Bad input data provided to " , ": "] , & [:: core :: fmt :: ArgumentV1 :: new_display (& "validate_transaction") , :: core :: fmt :: ArgumentV1 :: new_display (& e)])) , } ;
+                    # [allow (deprecated)] < Runtime as sp_transaction_pool :: runtime_api :: runtime_decl_for_TaggedTransactionQueue :: TaggedTransactionQueue < Block > > :: validate_transaction (source , tx , block_hash)
+                }),
+            ),
+            _ => None,
+        }
+    }
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/rustfmt.toml b/content/6-Protocol_On-Chain/FRAME/simple-runtime/rustfmt.toml
new file mode 100644
index 00000000..4be5bd75
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/rustfmt.toml
@@ -0,0 +1,25 @@
+# Basic
+hard_tabs = false
+tab_spaces = 2
+max_width = 100
+use_small_heuristics = "Max"
+# Imports
+imports_granularity = "Crate"
+reorder_imports = true
+# Consistency
+newline_style = "Unix"
+# Format comments
+comment_width = 100
+wrap_comments = true
+# Misc
+chain_width = 80
+spaces_around_ranges = false
+binop_separator = "Back"
+reorder_impl_items = false
+match_arm_leading_pipes = "Preserve"
+match_arm_blocks = false
+match_block_trailing_comma = true
+trailing_comma = "Vertical"
+trailing_semicolon = false
+use_field_init_shorthand = true
+edition = "2021"
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/.gitignore b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/.gitignore
new file mode 100644
index 00000000..eb5a316c
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/.gitignore
@@ -0,0 +1 @@
+target
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/Cargo.lock b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/Cargo.lock
new file mode 100644
index 00000000..8a006508
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/Cargo.lock
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+
+[[package]]
+name = "wasm-bindgen-shared"
+version = "0.2.81"
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+checksum = "6a89911bd99e5f3659ec4acf9c4d93b0a90fe4a2a11f15328472058edc5261be"
+
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+checksum = "ca00c5147c319a8ec91ec1a0edbec31e566ce2c9cc93b3f9bb86a9efd0eb795d"
+dependencies = [
+ "downcast-rs",
+ "libc",
+ "memory_units",
+ "num-rational",
+ "num-traits",
+ "parity-wasm",
+ "wasmi-validation",
+]
+
+[[package]]
+name = "wasmi-validation"
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+dependencies = [
+ "parity-wasm",
+]
+
+[[package]]
+name = "winapi"
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+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5c839a674fcd7a98952e593242ea400abe93992746761e38641405d28b00f419"
+dependencies = [
+ "winapi-i686-pc-windows-gnu",
+ "winapi-x86_64-pc-windows-gnu",
+]
+
+[[package]]
+name = "winapi-i686-pc-windows-gnu"
+version = "0.4.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
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+
+[[package]]
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+
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+checksum = "ea04155a16a59f9eab786fe12a4a450e75cdb175f9e0d80da1e17db09f55b8d2"
+dependencies = [
+ "windows_aarch64_msvc",
+ "windows_i686_gnu",
+ "windows_i686_msvc",
+ "windows_x86_64_gnu",
+ "windows_x86_64_msvc",
+]
+
+[[package]]
+name = "windows_aarch64_msvc"
+version = "0.36.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9bb8c3fd39ade2d67e9874ac4f3db21f0d710bee00fe7cab16949ec184eeaa47"
+
+[[package]]
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+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "180e6ccf01daf4c426b846dfc66db1fc518f074baa793aa7d9b9aaeffad6a3b6"
+
+[[package]]
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+version = "0.36.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e2e7917148b2812d1eeafaeb22a97e4813dfa60a3f8f78ebe204bcc88f12f024"
+
+[[package]]
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+source = "registry+https://github.com/rust-lang/crates.io-index"
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+
+[[package]]
+name = "windows_x86_64_msvc"
+version = "0.36.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
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+
+[[package]]
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+checksum = "30b31594f29d27036c383b53b59ed3476874d518f0efb151b27a4c275141390e"
+dependencies = [
+ "tap",
+]
+
+[[package]]
+name = "zeroize"
+version = "1.5.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "20b578acffd8516a6c3f2a1bdefc1ec37e547bb4e0fb8b6b01a4cafc886b4442"
+dependencies = [
+ "zeroize_derive",
+]
+
+[[package]]
+name = "zeroize_derive"
+version = "1.3.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3f8f187641dad4f680d25c4bfc4225b418165984179f26ca76ec4fb6441d3a17"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn",
+ "synstructure",
+]
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/Cargo.toml b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/Cargo.toml
new file mode 100644
index 00000000..fe7f3c40
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/Cargo.toml
@@ -0,0 +1,31 @@
+[package]
+name = "simple-pallet"
+version = "0.1.0"
+edition = "2021"
+
+[dependencies]
+codec = { package = "parity-scale-codec", version = "3.0.0", default-features = false }
+log = { version = "0.4.17", default-features = false }
+scale-info = { version = "2.1.1", default-features = false, features = ["derive"] }
+
+frame-support = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+frame-system = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+
+sp-io = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+sp-runtime = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+sp-std = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+
+[features]
+default = ["std"]
+std = [
+  "codec/std",
+  "scale-info/std",
+  "log/std",
+
+  "frame-support/std",
+  "frame-system/std",
+
+  "sp-io/std",
+  "sp-runtime/std",
+  "sp-std/std",
+]
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/expanded.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/expanded.rs
new file mode 100644
index 00000000..983ba99f
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/expanded.rs
@@ -0,0 +1,868 @@
+#![feature(prelude_import)]
+#[prelude_import]
+use std::prelude::rust_2021::*;
+#[macro_use]
+extern crate std;
+pub use pallet::*;
+///
+///			The module that hosts all the
+///			[FRAME](https://docs.substrate.io/v3/runtime/frame)
+///			types needed to add this pallet to a
+///			runtime.
+///
+pub mod pallet {
+    use codec::{Codec, FullEncode};
+    use frame_support::pallet_prelude::*;
+    use frame_system::pallet_prelude::*;
+    ///
+    ///			Configuration trait of this pallet.
+    ///
+    ///			Implement this type for a runtime in order to customize this pallet.
+    ///
+    pub trait Config: frame_system::Config {
+        fn on_value_update(new_value: Self::ValueType);
+        type ValueType: From<u32>
+            + Codec
+            + Default
+            + TypeInfo
+            + FullEncode
+            + sp_std::ops::AddAssign
+            + PartialOrd
+            + Copy;
+        const MAX_VALUE: u32;
+    }
+    #[allow(type_alias_bounds)]
+    pub type Values<T: Config> = StorageMap<
+        _GeneratedPrefixForStorageValues<T>,
+        Twox64Concat,
+        T::AccountId,
+        T::ValueType,
+        ValueQuery,
+    >;
+    #[allow(type_alias_bounds)]
+    pub type Counter<T: Config> =
+        StorageValue<_GeneratedPrefixForStorageCounter<T>, u32, ValueQuery>;
+    ///
+    ///			The [pallet](https://docs.substrate.io/v3/runtime/frame#pallets) implementing
+    ///			the on-chain logic.
+    ///
+    pub struct Pallet<T>(PhantomData<T>);
+    const _: () = {
+        impl<T> core::clone::Clone for Pallet<T> {
+            fn clone(&self) -> Self {
+                Self(core::clone::Clone::clone(&self.0))
+            }
+        }
+    };
+    const _: () = {
+        impl<T> core::cmp::Eq for Pallet<T> {}
+    };
+    const _: () = {
+        impl<T> core::cmp::PartialEq for Pallet<T> {
+            fn eq(&self, other: &Self) -> bool {
+                true && self.0 == other.0
+            }
+        }
+    };
+    const _: () = {
+        impl<T> core::fmt::Debug for Pallet<T> {
+            fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+                fmt.debug_tuple("Pallet").field(&self.0).finish()
+            }
+        }
+    };
+    impl<T: Config> Pallet<T> {
+        pub fn set_value(origin: OriginFor<T>, value: u32) -> DispatchResult {
+            let who = ensure_signed(origin)?;
+            if !<Values<T>>::contains_key(&who) {
+                if value > T::MAX_VALUE.into() {
+                    return Err("failed".into());
+                }
+                Counter::<T>::mutate(|x| *x += 1);
+                let value: T::ValueType = value.into();
+                <Values<T>>::insert(who, value);
+                T::on_value_update(value);
+            } else {
+                return Err("already submitted".into());
+            }
+            Ok(())
+        }
+        pub fn other_signed_extrinsic(origin: OriginFor<T>) -> DispatchResult {
+            let _ = ensure_signed(origin)?;
+            Ok(())
+        }
+    }
+    impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
+        fn on_initialize(n: T::BlockNumber) -> Weight {
+            if n % 10u32.into() == sp_runtime::traits::Zero::zero() {
+                {
+                    let lvl = ::log::Level::Info;
+                    if lvl <= ::log::STATIC_MAX_LEVEL && lvl <= ::log::max_level() {
+                        ::log::__private_api_log(
+                            ::core::fmt::Arguments::new_v1(
+                                &["count of users is "],
+                                &[::core::fmt::ArgumentV1::new_display(&Counter::<T>::get())],
+                            ),
+                            lvl,
+                            &(
+                                "simple_pallet::pallet",
+                                "simple_pallet::pallet",
+                                "src/lib.rs",
+                                75u32,
+                            ),
+                            ::log::__private_api::Option::None,
+                        );
+                    }
+                };
+            }
+            0
+        }
+        fn on_finalize(_n: T::BlockNumber) {}
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn pallet_constants_metadata(
+        ) -> frame_support::sp_std::vec::Vec<frame_support::metadata::PalletConstantMetadata>
+        {
+            ::alloc::vec::Vec::new()
+        }
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn error_metadata() -> Option<frame_support::metadata::PalletErrorMetadata> {
+            None
+        }
+    }
+    /// Type alias to `Pallet`, to be used by `construct_runtime`.
+    ///
+    /// Generated by `pallet` attribute macro.
+    #[deprecated(note = "use `Pallet` instead")]
+    #[allow(dead_code)]
+    pub type Module<T> = Pallet<T>;
+    impl<T: Config> frame_support::traits::GetStorageVersion for Pallet<T> {
+        fn current_storage_version() -> frame_support::traits::StorageVersion {
+            frame_support::traits::StorageVersion::default()
+        }
+        fn on_chain_storage_version() -> frame_support::traits::StorageVersion {
+            frame_support::traits::StorageVersion::get::<Self>()
+        }
+    }
+    impl<T: Config> frame_support::traits::OnGenesis for Pallet<T> {
+        fn on_genesis() {
+            let storage_version = frame_support::traits::StorageVersion::default();
+            storage_version.put::<Self>();
+        }
+    }
+    impl<T: Config> frame_support::traits::PalletInfoAccess for Pallet<T> {
+        fn index() -> usize {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::index::<
+                Self,
+            >()
+            .expect(
+                "Pallet is part of the runtime because pallet `Config` trait is \
+						implemented by the runtime",
+            )
+        }
+        fn name() -> &'static str {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::name::<
+                Self,
+            >()
+            .expect(
+                "Pallet is part of the runtime because pallet `Config` trait is \
+						implemented by the runtime",
+            )
+        }
+        fn module_name() -> &'static str {
+            < < T as frame_system :: Config > :: PalletInfo as frame_support :: traits :: PalletInfo > :: module_name :: < Self > () . expect ("Pallet is part of the runtime because pallet `Config` trait is \
+						implemented by the runtime")
+        }
+        fn crate_version() -> frame_support::traits::CrateVersion {
+            frame_support::traits::CrateVersion {
+                major: 0u16,
+                minor: 1u8,
+                patch: 0u8,
+            }
+        }
+    }
+    impl<T: Config> frame_support::traits::PalletsInfoAccess for Pallet<T> {
+        fn count() -> usize {
+            1
+        }
+        fn accumulate(
+            acc: &mut frame_support::sp_std::vec::Vec<frame_support::traits::PalletInfoData>,
+        ) {
+            use frame_support::traits::PalletInfoAccess;
+            let item = frame_support::traits::PalletInfoData {
+                index: Self::index(),
+                name: Self::name(),
+                module_name: Self::module_name(),
+                crate_version: Self::crate_version(),
+            };
+            acc.push(item);
+        }
+    }
+    impl<T: Config> frame_support::traits::StorageInfoTrait for Pallet<T> {
+        fn storage_info() -> frame_support::sp_std::vec::Vec<frame_support::traits::StorageInfo> {
+            #[allow(unused_mut)]
+            let mut res = ::alloc::vec::Vec::new();
+            {
+                let mut storage_info = < Values < T > as frame_support :: traits :: PartialStorageInfoTrait > :: partial_storage_info () ;
+                res.append(&mut storage_info);
+            }
+            {
+                let mut storage_info = < Counter < T > as frame_support :: traits :: PartialStorageInfoTrait > :: partial_storage_info () ;
+                res.append(&mut storage_info);
+            }
+            res
+        }
+    }
+    #[doc(hidden)]
+    pub mod __substrate_call_check {
+        #[doc(hidden)]
+        pub use __is_call_part_defined_0 as is_call_part_defined;
+    }
+    ///Contains one variant per dispatchable that can be called by an extrinsic.
+    #[codec(encode_bound())]
+    #[codec(decode_bound())]
+    #[scale_info(skip_type_params(T), capture_docs = "always")]
+    #[allow(non_camel_case_types)]
+    pub enum Call<T: Config> {
+        #[doc(hidden)]
+        #[codec(skip)]
+        __Ignore(
+            frame_support::sp_std::marker::PhantomData<(T,)>,
+            frame_support::Never,
+        ),
+        #[codec(index = 0u8)]
+        set_value {
+            #[allow(missing_docs)]
+            value: u32,
+        },
+        #[codec(index = 1u8)]
+        other_signed_extrinsic {},
+    }
+    const _: () = {
+        impl<T: Config> core::fmt::Debug for Call<T> {
+            fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+                match *self {
+                    Self::__Ignore(ref _0, ref _1) => fmt
+                        .debug_tuple("Call::__Ignore")
+                        .field(&_0)
+                        .field(&_1)
+                        .finish(),
+                    Self::set_value { ref value } => fmt
+                        .debug_struct("Call::set_value")
+                        .field("value", &value)
+                        .finish(),
+                    Self::other_signed_extrinsic {} => {
+                        fmt.debug_struct("Call::other_signed_extrinsic").finish()
+                    }
+                }
+            }
+        }
+    };
+    const _: () = {
+        impl<T: Config> core::clone::Clone for Call<T> {
+            fn clone(&self) -> Self {
+                match self {
+                    Self::__Ignore(ref _0, ref _1) => {
+                        Self::__Ignore(core::clone::Clone::clone(_0), core::clone::Clone::clone(_1))
+                    }
+                    Self::set_value { ref value } => Self::set_value {
+                        value: core::clone::Clone::clone(value),
+                    },
+                    Self::other_signed_extrinsic {} => Self::other_signed_extrinsic {},
+                }
+            }
+        }
+    };
+    const _: () = {
+        impl<T: Config> core::cmp::Eq for Call<T> {}
+    };
+    const _: () = {
+        impl<T: Config> core::cmp::PartialEq for Call<T> {
+            fn eq(&self, other: &Self) -> bool {
+                match (self, other) {
+                    (Self::__Ignore(_0, _1), Self::__Ignore(_0_other, _1_other)) => {
+                        true && _0 == _0_other && _1 == _1_other
+                    }
+                    (Self::set_value { value }, Self::set_value { value: _0 }) => {
+                        true && value == _0
+                    }
+                    (Self::other_signed_extrinsic {}, Self::other_signed_extrinsic {}) => true,
+                    (Self::__Ignore { .. }, Self::set_value { .. }) => false,
+                    (Self::__Ignore { .. }, Self::other_signed_extrinsic { .. }) => false,
+                    (Self::set_value { .. }, Self::__Ignore { .. }) => false,
+                    (Self::set_value { .. }, Self::other_signed_extrinsic { .. }) => false,
+                    (Self::other_signed_extrinsic { .. }, Self::__Ignore { .. }) => false,
+                    (Self::other_signed_extrinsic { .. }, Self::set_value { .. }) => false,
+                }
+            }
+        }
+    };
+    #[allow(deprecated)]
+    const _: () = {
+        #[allow(non_camel_case_types)]
+        #[automatically_derived]
+        impl<T: Config> ::codec::Encode for Call<T> {
+            fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+                &self,
+                __codec_dest_edqy: &mut __CodecOutputEdqy,
+            ) {
+                match *self {
+                    Call::set_value { ref value } => {
+                        __codec_dest_edqy.push_byte(0u8 as ::core::primitive::u8);
+                        ::codec::Encode::encode_to(value, __codec_dest_edqy);
+                    }
+                    Call::other_signed_extrinsic {} => {
+                        __codec_dest_edqy.push_byte(1u8 as ::core::primitive::u8);
+                    }
+                    _ => (),
+                }
+            }
+        }
+        #[automatically_derived]
+        impl<T: Config> ::codec::EncodeLike for Call<T> {}
+    };
+    #[allow(deprecated)]
+    const _: () = {
+        #[allow(non_camel_case_types)]
+        #[automatically_derived]
+        impl<T: Config> ::codec::Decode for Call<T> {
+            fn decode<__CodecInputEdqy: ::codec::Input>(
+                __codec_input_edqy: &mut __CodecInputEdqy,
+            ) -> ::core::result::Result<Self, ::codec::Error> {
+                match __codec_input_edqy
+                    .read_byte()
+                    .map_err(|e| e.chain("Could not decode `Call`, failed to read variant byte"))?
+                {
+                    __codec_x_edqy if __codec_x_edqy == 0u8 as ::core::primitive::u8 => {
+                        ::core::result::Result::Ok(Call::<T>::set_value {
+                            value: {
+                                let __codec_res_edqy =
+                                    <u32 as ::codec::Decode>::decode(__codec_input_edqy);
+                                match __codec_res_edqy {
+                                    ::core::result::Result::Err(e) => {
+                                        return ::core::result::Result::Err(
+                                            e.chain("Could not decode `Call::set_value::value`"),
+                                        )
+                                    }
+                                    ::core::result::Result::Ok(__codec_res_edqy) => {
+                                        __codec_res_edqy
+                                    }
+                                }
+                            },
+                        })
+                    }
+                    __codec_x_edqy if __codec_x_edqy == 1u8 as ::core::primitive::u8 => {
+                        ::core::result::Result::Ok(Call::<T>::other_signed_extrinsic {})
+                    }
+                    _ => ::core::result::Result::Err(<_ as ::core::convert::Into<_>>::into(
+                        "Could not decode `Call`, variant doesn't exist",
+                    )),
+                }
+            }
+        }
+    };
+    #[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+    const _: () = {
+        impl<T: Config> ::scale_info::TypeInfo for Call<T>
+        where
+            frame_support::sp_std::marker::PhantomData<(T,)>: ::scale_info::TypeInfo + 'static,
+            T: Config + 'static,
+        {
+            type Identity = Self;
+            fn type_info() -> ::scale_info::Type {
+                ::scale_info::Type::builder()
+                    .path(::scale_info::Path::new("Call", "simple_pallet::pallet"))
+                    .type_params(<[_]>::into_vec(
+                        #[rustc_box]
+                        ::alloc::boxed::Box::new([::scale_info::TypeParameter::new(
+                            "T",
+                            ::core::option::Option::None,
+                        )]),
+                    ))
+                    .docs_always(&[
+                        "Contains one variant per dispatchable that can be called by an extrinsic.",
+                    ])
+                    .variant(
+                        ::scale_info::build::Variants::new()
+                            .variant("set_value", |v| {
+                                v.index(0u8 as ::core::primitive::u8)
+                                    .fields(::scale_info::build::Fields::named().field(|f| {
+                                        f.ty::<u32>()
+                                            .name("value")
+                                            .type_name("u32")
+                                            .docs_always(&[])
+                                    }))
+                                    .docs_always(&[])
+                            })
+                            .variant("other_signed_extrinsic", |v| {
+                                v.index(1u8 as ::core::primitive::u8)
+                                    .fields(::scale_info::build::Fields::named())
+                                    .docs_always(&[])
+                            }),
+                    )
+            }
+        };
+    };
+    impl<T: Config> Call<T> {
+        ///Create a call with the variant `set_value`.
+        pub fn new_call_variant_set_value(value: u32) -> Self {
+            Self::set_value { value }
+        }
+        ///Create a call with the variant `other_signed_extrinsic`.
+        pub fn new_call_variant_other_signed_extrinsic() -> Self {
+            Self::other_signed_extrinsic {}
+        }
+    }
+    impl<T: Config> frame_support::dispatch::GetDispatchInfo for Call<T> {
+        fn get_dispatch_info(&self) -> frame_support::dispatch::DispatchInfo {
+            match *self {
+                Self::set_value { ref value } => {
+                    let __pallet_base_weight = 0;
+                    let __pallet_weight =
+                        <dyn frame_support::dispatch::WeighData<(&u32,)>>::weigh_data(
+                            &__pallet_base_weight,
+                            (value,),
+                        );
+                    let __pallet_class =
+                        <dyn frame_support::dispatch::ClassifyDispatch<(&u32,)>>::classify_dispatch(
+                            &__pallet_base_weight,
+                            (value,),
+                        );
+                    let __pallet_pays_fee =
+                        <dyn frame_support::dispatch::PaysFee<(&u32,)>>::pays_fee(
+                            &__pallet_base_weight,
+                            (value,),
+                        );
+                    frame_support::dispatch::DispatchInfo {
+                        weight: __pallet_weight,
+                        class: __pallet_class,
+                        pays_fee: __pallet_pays_fee,
+                    }
+                }
+                Self::other_signed_extrinsic {} => {
+                    let __pallet_base_weight = 0;
+                    let __pallet_weight = <dyn frame_support::dispatch::WeighData<()>>::weigh_data(
+                        &__pallet_base_weight,
+                        (),
+                    );
+                    let __pallet_class =
+                        <dyn frame_support::dispatch::ClassifyDispatch<()>>::classify_dispatch(
+                            &__pallet_base_weight,
+                            (),
+                        );
+                    let __pallet_pays_fee = <dyn frame_support::dispatch::PaysFee<()>>::pays_fee(
+                        &__pallet_base_weight,
+                        (),
+                    );
+                    frame_support::dispatch::DispatchInfo {
+                        weight: __pallet_weight,
+                        class: __pallet_class,
+                        pays_fee: __pallet_pays_fee,
+                    }
+                }
+                Self::__Ignore(_, _) => {
+                    ::core::panicking::panic_fmt(::core::fmt::Arguments::new_v1(
+                        &["internal error: entered unreachable code: "],
+                        &[::core::fmt::ArgumentV1::new_display(
+                            &::core::fmt::Arguments::new_v1(&["__Ignore cannot be used"], &[]),
+                        )],
+                    ))
+                }
+            }
+        }
+    }
+    impl<T: Config> frame_support::dispatch::GetCallName for Call<T> {
+        fn get_call_name(&self) -> &'static str {
+            match *self {
+                Self::set_value { .. } => "set_value",
+                Self::other_signed_extrinsic { .. } => "other_signed_extrinsic",
+                Self::__Ignore(_, _) => {
+                    ::core::panicking::panic_fmt(::core::fmt::Arguments::new_v1(
+                        &["internal error: entered unreachable code: "],
+                        &[::core::fmt::ArgumentV1::new_display(
+                            &::core::fmt::Arguments::new_v1(
+                                &["__PhantomItem cannot be used."],
+                                &[],
+                            ),
+                        )],
+                    ))
+                }
+            }
+        }
+        fn get_call_names() -> &'static [&'static str] {
+            &["set_value", "other_signed_extrinsic"]
+        }
+    }
+    impl<T: Config> frame_support::traits::UnfilteredDispatchable for Call<T> {
+        type Origin = frame_system::pallet_prelude::OriginFor<T>;
+        fn dispatch_bypass_filter(
+            self,
+            origin: Self::Origin,
+        ) -> frame_support::dispatch::DispatchResultWithPostInfo {
+            match self {
+                Self::set_value { value } => {
+                    let __within_span__ = {
+                        use ::tracing::__macro_support::Callsite as _;
+                        static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                            static META: ::tracing::Metadata<'static> = {
+                                ::tracing_core::metadata::Metadata::new(
+                                    "set_value",
+                                    "simple_pallet::pallet",
+                                    ::tracing::Level::TRACE,
+                                    Some("src/lib.rs"),
+                                    Some(4u32),
+                                    Some("simple_pallet::pallet"),
+                                    ::tracing_core::field::FieldSet::new(
+                                        &[],
+                                        ::tracing_core::callsite::Identifier(&CALLSITE),
+                                    ),
+                                    ::tracing::metadata::Kind::SPAN,
+                                )
+                            };
+                            ::tracing::callsite::DefaultCallsite::new(&META)
+                        };
+                        let mut interest = ::tracing::subscriber::Interest::never();
+                        if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                            && ::tracing::Level::TRACE
+                                <= ::tracing::level_filters::LevelFilter::current()
+                            && {
+                                interest = CALLSITE.interest();
+                                !interest.is_never()
+                            }
+                            && ::tracing::__macro_support::__is_enabled(
+                                CALLSITE.metadata(),
+                                interest,
+                            )
+                        {
+                            let meta = CALLSITE.metadata();
+                            ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                        } else {
+                            let span =
+                                ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                            {};
+                            span
+                        }
+                    };
+                    let __tracing_guard__ = __within_span__.enter();
+                    frame_support::storage::in_storage_layer(|| {
+                        <Pallet<T>>::set_value(origin, value)
+                            .map(Into::into)
+                            .map_err(Into::into)
+                    })
+                }
+                Self::other_signed_extrinsic {} => {
+                    let __within_span__ = {
+                        use ::tracing::__macro_support::Callsite as _;
+                        static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                            static META: ::tracing::Metadata<'static> = {
+                                ::tracing_core::metadata::Metadata::new(
+                                    "other_signed_extrinsic",
+                                    "simple_pallet::pallet",
+                                    ::tracing::Level::TRACE,
+                                    Some("src/lib.rs"),
+                                    Some(4u32),
+                                    Some("simple_pallet::pallet"),
+                                    ::tracing_core::field::FieldSet::new(
+                                        &[],
+                                        ::tracing_core::callsite::Identifier(&CALLSITE),
+                                    ),
+                                    ::tracing::metadata::Kind::SPAN,
+                                )
+                            };
+                            ::tracing::callsite::DefaultCallsite::new(&META)
+                        };
+                        let mut interest = ::tracing::subscriber::Interest::never();
+                        if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                            && ::tracing::Level::TRACE
+                                <= ::tracing::level_filters::LevelFilter::current()
+                            && {
+                                interest = CALLSITE.interest();
+                                !interest.is_never()
+                            }
+                            && ::tracing::__macro_support::__is_enabled(
+                                CALLSITE.metadata(),
+                                interest,
+                            )
+                        {
+                            let meta = CALLSITE.metadata();
+                            ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                        } else {
+                            let span =
+                                ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                            {};
+                            span
+                        }
+                    };
+                    let __tracing_guard__ = __within_span__.enter();
+                    frame_support::storage::in_storage_layer(|| {
+                        <Pallet<T>>::other_signed_extrinsic(origin)
+                            .map(Into::into)
+                            .map_err(Into::into)
+                    })
+                }
+                Self::__Ignore(_, _) => {
+                    let _ = origin;
+                    ::core::panicking::panic_fmt(::core::fmt::Arguments::new_v1(
+                        &["internal error: entered unreachable code: "],
+                        &[::core::fmt::ArgumentV1::new_display(
+                            &::core::fmt::Arguments::new_v1(
+                                &["__PhantomItem cannot be used."],
+                                &[],
+                            ),
+                        )],
+                    ));
+                }
+            }
+        }
+    }
+    impl<T: Config> frame_support::dispatch::Callable<T> for Pallet<T> {
+        type Call = Call<T>;
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn call_functions() -> frame_support::metadata::PalletCallMetadata {
+            frame_support::scale_info::meta_type::<Call<T>>().into()
+        }
+    }
+    pub use __tt_error_token_1 as tt_error_token;
+    #[doc(hidden)]
+    pub mod __substrate_event_check {
+        #[doc(hidden)]
+        pub use __is_event_part_defined_2 as is_event_part_defined;
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn storage_metadata() -> frame_support::metadata::PalletStorageMetadata {
+            frame_support :: metadata :: PalletStorageMetadata { prefix : < < T as frame_system :: Config > :: PalletInfo as frame_support :: traits :: PalletInfo > :: name :: < Pallet < T > > () . expect ("Every active pallet has a name in the runtime; qed") , entries : { # [allow (unused_mut)] let mut entries = :: alloc :: vec :: Vec :: new () ; { < Values < T > as frame_support :: storage :: StorageEntryMetadataBuilder > :: build_metadata (:: alloc :: vec :: Vec :: new () , & mut entries) ; } { < Counter < T > as frame_support :: storage :: StorageEntryMetadataBuilder > :: build_metadata (:: alloc :: vec :: Vec :: new () , & mut entries) ; } entries } , }
+        }
+    }
+    #[doc(hidden)]
+    pub struct _GeneratedPrefixForStorageValues<T>(core::marker::PhantomData<(T,)>);
+    impl<T: Config> frame_support::traits::StorageInstance for _GeneratedPrefixForStorageValues<T> {
+        fn pallet_prefix() -> &'static str {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::name::<
+                Pallet<T>,
+            >()
+            .expect("Every active pallet has a name in the runtime; qed")
+        }
+        const STORAGE_PREFIX: &'static str = "Values";
+    }
+    #[doc(hidden)]
+    pub struct _GeneratedPrefixForStorageCounter<T>(core::marker::PhantomData<(T,)>);
+    impl<T: Config> frame_support::traits::StorageInstance for _GeneratedPrefixForStorageCounter<T> {
+        fn pallet_prefix() -> &'static str {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::name::<
+                Pallet<T>,
+            >()
+            .expect("Every active pallet has a name in the runtime; qed")
+        }
+        const STORAGE_PREFIX: &'static str = "Counter";
+    }
+    #[doc(hidden)]
+    pub mod __substrate_inherent_check {
+        #[doc(hidden)]
+        pub use __is_inherent_part_defined_3 as is_inherent_part_defined;
+    }
+    /// Hidden instance generated to be internally used when module is used without
+    /// instance.
+    #[doc(hidden)]
+    pub type __InherentHiddenInstance = ();
+    impl<T: Config> frame_support::traits::OnFinalize<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn on_finalize(n: <T as frame_system::Config>::BlockNumber) {
+            let __within_span__ = {
+                use ::tracing::__macro_support::Callsite as _;
+                static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                    static META: ::tracing::Metadata<'static> = {
+                        ::tracing_core::metadata::Metadata::new(
+                            "on_finalize",
+                            "simple_pallet::pallet",
+                            ::tracing::Level::TRACE,
+                            Some("src/lib.rs"),
+                            Some(4u32),
+                            Some("simple_pallet::pallet"),
+                            ::tracing_core::field::FieldSet::new(
+                                &[],
+                                ::tracing_core::callsite::Identifier(&CALLSITE),
+                            ),
+                            ::tracing::metadata::Kind::SPAN,
+                        )
+                    };
+                    ::tracing::callsite::DefaultCallsite::new(&META)
+                };
+                let mut interest = ::tracing::subscriber::Interest::never();
+                if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                    && ::tracing::Level::TRACE <= ::tracing::level_filters::LevelFilter::current()
+                    && {
+                        interest = CALLSITE.interest();
+                        !interest.is_never()
+                    }
+                    && ::tracing::__macro_support::__is_enabled(CALLSITE.metadata(), interest)
+                {
+                    let meta = CALLSITE.metadata();
+                    ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                } else {
+                    let span = ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                    {};
+                    span
+                }
+            };
+            let __tracing_guard__ = __within_span__.enter();
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_finalize (n)
+        }
+    }
+    impl<T: Config> frame_support::traits::OnIdle<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn on_idle(
+            n: <T as frame_system::Config>::BlockNumber,
+            remaining_weight: frame_support::weights::Weight,
+        ) -> frame_support::weights::Weight {
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_idle (n , remaining_weight)
+        }
+    }
+    impl<T: Config> frame_support::traits::OnInitialize<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn on_initialize(
+            n: <T as frame_system::Config>::BlockNumber,
+        ) -> frame_support::weights::Weight {
+            let __within_span__ = {
+                use ::tracing::__macro_support::Callsite as _;
+                static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                    static META: ::tracing::Metadata<'static> = {
+                        ::tracing_core::metadata::Metadata::new(
+                            "on_initialize",
+                            "simple_pallet::pallet",
+                            ::tracing::Level::TRACE,
+                            Some("src/lib.rs"),
+                            Some(4u32),
+                            Some("simple_pallet::pallet"),
+                            ::tracing_core::field::FieldSet::new(
+                                &[],
+                                ::tracing_core::callsite::Identifier(&CALLSITE),
+                            ),
+                            ::tracing::metadata::Kind::SPAN,
+                        )
+                    };
+                    ::tracing::callsite::DefaultCallsite::new(&META)
+                };
+                let mut interest = ::tracing::subscriber::Interest::never();
+                if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                    && ::tracing::Level::TRACE <= ::tracing::level_filters::LevelFilter::current()
+                    && {
+                        interest = CALLSITE.interest();
+                        !interest.is_never()
+                    }
+                    && ::tracing::__macro_support::__is_enabled(CALLSITE.metadata(), interest)
+                {
+                    let meta = CALLSITE.metadata();
+                    ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                } else {
+                    let span = ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                    {};
+                    span
+                }
+            };
+            let __tracing_guard__ = __within_span__.enter();
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_initialize (n)
+        }
+    }
+    impl<T: Config> frame_support::traits::OnRuntimeUpgrade for Pallet<T> {
+        fn on_runtime_upgrade() -> frame_support::weights::Weight {
+            let __within_span__ = {
+                use ::tracing::__macro_support::Callsite as _;
+                static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                    static META: ::tracing::Metadata<'static> = {
+                        ::tracing_core::metadata::Metadata::new(
+                            "on_runtime_update",
+                            "simple_pallet::pallet",
+                            ::tracing::Level::TRACE,
+                            Some("src/lib.rs"),
+                            Some(4u32),
+                            Some("simple_pallet::pallet"),
+                            ::tracing_core::field::FieldSet::new(
+                                &[],
+                                ::tracing_core::callsite::Identifier(&CALLSITE),
+                            ),
+                            ::tracing::metadata::Kind::SPAN,
+                        )
+                    };
+                    ::tracing::callsite::DefaultCallsite::new(&META)
+                };
+                let mut interest = ::tracing::subscriber::Interest::never();
+                if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                    && ::tracing::Level::TRACE <= ::tracing::level_filters::LevelFilter::current()
+                    && {
+                        interest = CALLSITE.interest();
+                        !interest.is_never()
+                    }
+                    && ::tracing::__macro_support::__is_enabled(CALLSITE.metadata(), interest)
+                {
+                    let meta = CALLSITE.metadata();
+                    ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                } else {
+                    let span = ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                    {};
+                    span
+                }
+            };
+            let __tracing_guard__ = __within_span__.enter();
+            let pallet_name = < < T as frame_system :: Config > :: PalletInfo as frame_support :: traits :: PalletInfo > :: name :: < Self > () . unwrap_or ("<unknown pallet name>") ;
+            {
+                let lvl = ::log::Level::Info;
+                if lvl <= ::log::STATIC_MAX_LEVEL && lvl <= ::log::max_level() {
+                    ::log::__private_api_log(
+                        ::core::fmt::Arguments::new_v1(
+                            &["\u{2705} no migration for "],
+                            &[::core::fmt::ArgumentV1::new_display(&pallet_name)],
+                        ),
+                        lvl,
+                        &(
+                            frame_support::LOG_TARGET,
+                            "simple_pallet::pallet",
+                            "src/lib.rs",
+                            4u32,
+                        ),
+                        ::log::__private_api::Option::None,
+                    );
+                }
+            };
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_runtime_upgrade ()
+        }
+    }
+    impl<T: Config> frame_support::traits::OffchainWorker<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn offchain_worker(n: <T as frame_system::Config>::BlockNumber) {
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: offchain_worker (n)
+        }
+    }
+    impl<T: Config> frame_support::traits::IntegrityTest for Pallet<T> {
+        fn integrity_test() {
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: integrity_test ()
+        }
+    }
+    #[doc(hidden)]
+    pub mod __substrate_genesis_config_check {
+        #[doc(hidden)]
+        pub use __is_genesis_config_defined_4 as is_genesis_config_defined;
+        #[doc(hidden)]
+        pub use __is_std_enabled_for_genesis_4 as is_std_enabled_for_genesis;
+    }
+    #[doc(hidden)]
+    pub mod __substrate_origin_check {
+        #[doc(hidden)]
+        pub use __is_origin_part_defined_5 as is_origin_part_defined;
+    }
+    #[doc(hidden)]
+    pub mod __substrate_validate_unsigned_check {
+        #[doc(hidden)]
+        pub use __is_validate_unsigned_part_defined_6 as is_validate_unsigned_part_defined;
+    }
+    pub use __tt_default_parts_7 as tt_default_parts;
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/src/lib.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/src/lib.rs
new file mode 100644
index 00000000..b3342e56
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/simple-pallet/src/lib.rs
@@ -0,0 +1,84 @@
+#![cfg_attr(not(feature = "std"), no_std)]
+pub use pallet::*;
+
+#[frame_support::pallet]
+pub mod pallet {
+  use codec::{Codec, FullEncode};
+  use frame_support::{pallet_prelude::*};
+  use frame_system::pallet_prelude::*;
+
+  // Every pallet has a `Config` trait. It contains everything configuration-related. A
+  // non-exhaustive list of examples below. In general, anything that you can do with a trait, you
+  // can do in your config.
+  //
+  // Note that we inherit from everything system!
+  #[pallet::config]
+  pub trait Config: frame_system::Config {
+    // A hook about what to do.
+    fn on_value_update(new_value: Self::ValueType);
+    // An example of receiving an input type.
+    type ValueType: From<u32> + Codec + Default + TypeInfo + FullEncode + sp_std::ops::AddAssign + PartialOrd + Copy;
+    // An example of receiving a const.
+    const MAX_VALUE: u32;
+  }
+
+  // T::AccountId comes from system, T::ValueType comes form us.
+  #[pallet::storage]
+  pub type Values<T: Config> = StorageMap<_, Twox64Concat, T::AccountId, T::ValueType, ValueQuery>;
+  // A simpler storage item.
+  #[pallet::storage]
+  pub type Counter<T: Config> = StorageValue<_, u32, ValueQuery>;
+
+  #[pallet::pallet]
+  #[pallet::without_storage_info]
+  pub struct Pallet<T>(PhantomData<T>);
+
+  #[pallet::call]
+  impl<T: Config> Pallet<T> {
+    // this a dummy transaction that allows any user to submit a number (that is converted to
+    // `ValueType`) exactly once. It already increments a counter every time someone submits something
+    // new. A maximum of `Config::MAX_VALUE` is allowed, and the associated hooks are called.
+    #[pallet::weight(0)]
+    pub fn set_value(origin: OriginFor<T>, value: u32) -> DispatchResult {
+      // checks the origin to be signed -- more on this later.
+      let who = ensure_signed(origin)?;
+
+      // check that this user has not submitted already.
+      if !<Values<T>>::contains_key(&who) {
+        if value > T::MAX_VALUE.into() {
+          return Err("failed".into())
+        }
+
+        // increment the counter .
+        Counter::<T>::mutate(|x| *x += 1);
+        let value: T::ValueType = value.into();
+        <Values<T>>::insert(who, value);
+        T::on_value_update(value);
+      } else {
+        return Err("already submitted".into())
+      }
+
+      Ok(())
+    }
+
+    #[pallet::weight(0)]
+    pub fn other_signed_extrinsic(origin: OriginFor<T>) -> DispatchResult {
+      let _ = ensure_signed(origin)?;
+      Ok(())
+    }
+  }
+
+  #[pallet::hooks]
+  impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
+    fn on_initialize(n: T::BlockNumber) -> Weight {
+      if n % 10u32.into() == sp_runtime::traits::Zero::zero() {
+        log::info!("count of users is {}", Counter ::<T>::get());
+      }
+      0
+    }
+
+    fn on_finalize(_n: T::BlockNumber) {
+      // other stuff..
+    }
+  }
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/src/lib.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/src/lib.rs
new file mode 100644
index 00000000..7c431b73
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/src/lib.rs
@@ -0,0 +1,206 @@
+#![cfg_attr(not(feature = "std"), no_std)]
+#![recursion_limit = "256"]
+
+pub use frame_support::{
+  construct_runtime, parameter_types,
+  traits::{ConstU128, ConstU32, ConstU64, ConstU8, KeyOwnerProofSystem, Randomness, StorageInfo},
+  weights::{
+    constants::{BlockExecutionWeight, ExtrinsicBaseWeight, RocksDbWeight, WEIGHT_PER_SECOND},
+    IdentityFee, Weight,
+  },
+  StorageValue,
+};
+use sp_api::impl_runtime_apis;
+#[cfg(any(feature = "std", test))]
+pub use sp_runtime::BuildStorage;
+use sp_runtime::{
+  create_runtime_str, generic,
+  traits::{AccountIdLookup, BlakeTwo256, Block as BlockT, IdentifyAccount, Verify},
+  transaction_validity::{TransactionSource, TransactionValidity},
+  ApplyExtrinsicResult, MultiSignature,
+};
+pub use sp_runtime::{Perbill, Permill};
+use sp_std::prelude::*;
+use sp_version::RuntimeVersion;
+
+pub type Signature = MultiSignature;
+// TODO: exercise: let's decrypt this line! AccountId32
+pub type AccountId = <<Signature as Verify>::Signer as IdentifyAccount>::AccountId;
+
+// pub type Signature = sp_core::sr25519::Signature;
+// pub type AccountId = sp_core::sr25519::Public;
+
+pub type Hash = sp_core::H256;
+pub type BlockNumber = u32;
+pub type Balance = u128;
+pub type Index = u32;
+
+// One of apis that the runtime needs to implement requires it to know its version!
+#[sp_version::runtime_version]
+pub const VERSION: RuntimeVersion = RuntimeVersion {
+  spec_name: create_runtime_str!("simple-runtime"),
+  impl_name: create_runtime_str!("simple-runtime"),
+  authoring_version: 1,
+  spec_version: 100,
+  impl_version: 1,
+  apis: RUNTIME_API_VERSIONS,
+  transaction_version: 1,
+  state_version: 1,
+};
+
+const NORMAL_DISPATCH_RATIO: Perbill = Perbill::one();
+parameter_types! {
+  pub const Version: RuntimeVersion = VERSION;
+  pub const BlockHashCount: BlockNumber = 2400;
+
+  pub BlockWeights: frame_system::limits::BlockWeights = frame_system::limits::BlockWeights
+  ::with_sensible_defaults(2 * WEIGHT_PER_SECOND, NORMAL_DISPATCH_RATIO);
+  pub BlockLength: frame_system::limits::BlockLength = frame_system::limits::BlockLength
+  ::max_with_normal_ratio(5 * 1024 * 1024, NORMAL_DISPATCH_RATIO);
+
+  pub const SS58Prefix: u8 = 42;
+}
+
+impl frame_system::Config for Runtime {
+  // these might ring bell for you now.
+  type AccountId = AccountId;
+  type Index = Index;
+  type Hash = Hash;
+  type Hashing = BlakeTwo256;
+  type Version = Version;
+
+  // we will look into what this in the expanded version.
+  type Call = Call;
+
+  // this one's more important, keep this also in mind!
+  type Origin = Origin;
+
+  // the rest probably won't and no worries for now!
+  type BaseCallFilter = frame_support::traits::Everything;
+  type BlockWeights = BlockWeights;
+  type BlockLength = BlockLength;
+  type Lookup = AccountIdLookup<AccountId, ()>;
+  type BlockNumber = BlockNumber;
+  type Header = generic::Header<BlockNumber, BlakeTwo256>;
+  type Event = Event;
+  type BlockHashCount = BlockHashCount;
+  type DbWeight = RocksDbWeight;
+  type PalletInfo = PalletInfo;
+  type OnNewAccount = ();
+  type OnKilledAccount = ();
+  type AccountData = ();
+  type SystemWeightInfo = ();
+  type SS58Prefix = SS58Prefix;
+  type OnSetCode = ();
+  type MaxConsumers = frame_support::traits::ConstU32<16>;
+}
+
+impl simple_pallet::pallet::Config for Runtime {
+  // recall that we wanted a type here that's From<u32>.
+  type ValueType = u64;
+  const MAX_VALUE: u32 = 1000;
+  fn on_value_update(_: Self::ValueType) {
+    todo!();
+  }
+}
+
+impl transfer_pallet::Config for Runtime {
+  type MinimumBalance = frame_support::traits::ConstU128<100>;
+}
+
+pub mod opaque {
+  use super::BlockNumber;
+  pub use sp_runtime::OpaqueExtrinsic;
+  use sp_runtime::{generic, traits::BlakeTwo256};
+  pub type Header = generic::Header<BlockNumber, BlakeTwo256>;
+  pub type Block = generic::Block<Header, OpaqueExtrinsic>;
+  pub type BlockId = generic::BlockId<Block>;
+}
+
+// This is the marco that amalgamates all of our types together, and creates some important types
+// such as:
+// - struct Runtime, which you already see in this file
+// - implements the Config trait of all pallets.
+// - `type System`, `type SimplePallet`.
+// - AllPalletsWithSystem
+//   - and recall that all pallets implement things like `Hooks`, `OnInitialize`, and all of these
+//     traits are tuple-able.
+// - enum Call
+// - enum Event, GenesisConfig, Error etc. but we don't have them here.
+//
+// This macro's kinda old, and will hopefully be transformed into a better version soon (enum
+// Runtime: faceplam).
+construct_runtime!(
+  pub enum Runtime where
+  Block = Block,
+  NodeBlock = opaque::Block,
+  UncheckedExtrinsic = UncheckedExtrinsic
+  {
+    System: frame_system = 2,
+    SimplePallet: simple_pallet = 1,
+    TransferPallet: transfer_pallet = 0,
+  }
+);
+
+// we visit these in the last part and transition into executive
+pub type Address = sp_runtime::MultiAddress<AccountId, ()>;
+pub type Header = generic::Header<BlockNumber, BlakeTwo256>;
+pub type Block = generic::Block<Header, UncheckedExtrinsic>;
+pub type SignedExtra = (frame_system::CheckGenesis<Runtime>, frame_system::CheckNonce<Runtime>);
+pub type UncheckedExtrinsic = generic::UncheckedExtrinsic<Address, Call, Signature, SignedExtra>;
+pub type SignedPayload = generic::SignedPayload<Call, SignedExtra>;
+pub type Executive = frame_executive::Executive<
+  Runtime,
+  Block,
+  frame_system::ChainContext<Runtime>,
+  Runtime,
+  AllPalletsWithSystem,
+>;
+
+// this is the juicy part! all implementations seem to come from Executive!
+impl_runtime_apis! {
+  impl sp_api::Core<Block> for Runtime {
+    fn version() -> RuntimeVersion {
+      VERSION
+    }
+
+    fn execute_block(block: Block) {
+      Executive::execute_block(block);
+    }
+
+    fn initialize_block(header: &<Block as BlockT>::Header) {
+      Executive::initialize_block(header)
+    }
+  }
+
+  impl sp_block_builder::BlockBuilder<Block> for Runtime {
+    fn apply_extrinsic(extrinsic: <Block as BlockT>::Extrinsic) -> ApplyExtrinsicResult {
+      Executive::apply_extrinsic(extrinsic)
+    }
+
+    fn finalize_block() -> <Block as BlockT>::Header {
+      Executive::finalize_block()
+    }
+
+    fn inherent_extrinsics(_: sp_inherents::InherentData) -> Vec<<Block as BlockT>::Extrinsic> {
+      unimplemented!()
+    }
+
+    fn check_inherents(
+      _: Block,
+      _: sp_inherents::InherentData,
+    ) -> sp_inherents::CheckInherentsResult {
+      unimplemented!()
+    }
+  }
+
+  impl sp_transaction_pool::runtime_api::TaggedTransactionQueue<Block> for Runtime {
+    fn validate_transaction(
+      source: TransactionSource,
+      tx: <Block as BlockT>::Extrinsic,
+      block_hash: <Block as BlockT>::Hash,
+    ) -> TransactionValidity {
+      Executive::validate_transaction(source, tx, block_hash)
+    }
+  }
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/.gitignore b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/.gitignore
new file mode 100644
index 00000000..eb5a316c
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/.gitignore
@@ -0,0 +1 @@
+target
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/Cargo.lock b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/Cargo.lock
new file mode 100644
index 00000000..8a006508
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/Cargo.lock
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+ "memory_units",
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+ "windows_aarch64_msvc",
+ "windows_i686_gnu",
+ "windows_i686_msvc",
+ "windows_x86_64_gnu",
+ "windows_x86_64_msvc",
+]
+
+[[package]]
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+]
+
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+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn",
+ "synstructure",
+]
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/Cargo.toml b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/Cargo.toml
new file mode 100644
index 00000000..bdf177c4
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/Cargo.toml
@@ -0,0 +1,31 @@
+[package]
+name = "transfer-pallet"
+version = "0.1.0"
+edition = "2021"
+
+[dependencies]
+codec = { package = "parity-scale-codec", version = "3.0.0", default-features = false }
+log = { version = "0.4.17", default-features = false }
+scale-info = { version = "2.1.1", default-features = false, features = ["derive"] }
+
+frame-support = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+frame-system = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+
+sp-io = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+sp-runtime = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+sp-std = { git = "https://github.com/paritytech/substrate", branch = "master", default-features = false }
+
+[features]
+default = ["std"]
+std = [
+  "codec/std",
+  "scale-info/std",
+  "log/std",
+
+  "frame-support/std",
+  "frame-system/std",
+
+  "sp-io/std",
+  "sp-runtime/std",
+  "sp-std/std",
+]
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/expanded.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/expanded.rs
new file mode 100644
index 00000000..8c9f116b
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/expanded.rs
@@ -0,0 +1,766 @@
+#![feature(prelude_import)]
+#[prelude_import]
+use std::prelude::rust_2021::*;
+#[macro_use]
+extern crate std;
+pub use pallet::*;
+///
+///			The module that hosts all the
+///			[FRAME](https://docs.substrate.io/v3/runtime/frame)
+///			types needed to add this pallet to a
+///			runtime.
+///
+pub mod pallet {
+    use codec::{Codec, FullEncode};
+    use frame_support::pallet_prelude::*;
+    use frame_system::pallet_prelude::*;
+    ///
+    ///			Configuration trait of this pallet.
+    ///
+    ///			Implement this type for a runtime in order to customize this pallet.
+    ///
+    pub trait Config: frame_system::Config {
+        fn on_value_update(new_value: Self::ValueType);
+        type ValueType: From<u32>
+            + Codec
+            + Default
+            + TypeInfo
+            + FullEncode
+            + sp_std::ops::AddAssign
+            + PartialOrd
+            + Copy;
+        const MAX_VALUE: u32;
+    }
+    #[allow(type_alias_bounds)]
+    pub type Accumulators<T: Config> = StorageMap<
+        _GeneratedPrefixForStorageAccumulators<T>,
+        Twox64Concat,
+        T::AccountId,
+        T::ValueType,
+        ValueQuery,
+    >;
+    #[allow(type_alias_bounds)]
+    pub type Counter<T: Config> =
+        StorageValue<_GeneratedPrefixForStorageCounter<T>, u32, ValueQuery>;
+    ///
+    ///			The [pallet](https://docs.substrate.io/v3/runtime/frame#pallets) implementing
+    ///			the on-chain logic.
+    ///
+    pub struct Pallet<T>(PhantomData<T>);
+    const _: () = {
+        impl<T> core::clone::Clone for Pallet<T> {
+            fn clone(&self) -> Self {
+                Self(core::clone::Clone::clone(&self.0))
+            }
+        }
+    };
+    const _: () = {
+        impl<T> core::cmp::Eq for Pallet<T> {}
+    };
+    const _: () = {
+        impl<T> core::cmp::PartialEq for Pallet<T> {
+            fn eq(&self, other: &Self) -> bool {
+                true && self.0 == other.0
+            }
+        }
+    };
+    const _: () = {
+        impl<T> core::fmt::Debug for Pallet<T> {
+            fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+                fmt.debug_tuple("Pallet").field(&self.0).finish()
+            }
+        }
+    };
+    impl<T: Config> Pallet<T> {
+        pub fn inc_user_counter(origin: OriginFor<T>, inc: u32) -> DispatchResult {
+            let who = ensure_signed(origin)?;
+            if !<Accumulators<T>>::contains_key(&who) {
+                Counter::<T>::mutate(|x| *x += 1);
+                let mut current = Accumulators::<T>::get(&who);
+                current += inc.into();
+                if current > T::MAX_VALUE.into() {
+                    return Err("failed".into());
+                }
+                T::on_value_update(current);
+                Accumulators::<T>::insert(who, current);
+            } else {
+                return Err("already submitted".into());
+            }
+            Ok(())
+        }
+    }
+    impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
+        fn on_initialize(n: T::BlockNumber) -> Weight {
+            if n % 10u32.into() == sp_runtime::traits::Zero::zero() {
+                {
+                    let lvl = ::log::Level::Info;
+                    if lvl <= ::log::STATIC_MAX_LEVEL && lvl <= ::log::max_level() {
+                        ::log::__private_api_log(
+                            ::core::fmt::Arguments::new_v1(
+                                &["count of users is "],
+                                &[::core::fmt::ArgumentV1::new_display(&Counter::<T>::get())],
+                            ),
+                            lvl,
+                            &(
+                                "simple_pallet::pallet",
+                                "simple_pallet::pallet",
+                                "src/lib.rs",
+                                75u32,
+                            ),
+                            ::log::__private_api::Option::None,
+                        );
+                    }
+                };
+            }
+            0
+        }
+        fn on_finalize(_n: T::BlockNumber) {}
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn pallet_constants_metadata(
+        ) -> frame_support::sp_std::vec::Vec<frame_support::metadata::PalletConstantMetadata>
+        {
+            ::alloc::vec::Vec::new()
+        }
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn error_metadata() -> Option<frame_support::metadata::PalletErrorMetadata> {
+            None
+        }
+    }
+    /// Type alias to `Pallet`, to be used by `construct_runtime`.
+    ///
+    /// Generated by `pallet` attribute macro.
+    #[deprecated(note = "use `Pallet` instead")]
+    #[allow(dead_code)]
+    pub type Module<T> = Pallet<T>;
+    impl<T: Config> frame_support::traits::GetStorageVersion for Pallet<T> {
+        fn current_storage_version() -> frame_support::traits::StorageVersion {
+            frame_support::traits::StorageVersion::default()
+        }
+        fn on_chain_storage_version() -> frame_support::traits::StorageVersion {
+            frame_support::traits::StorageVersion::get::<Self>()
+        }
+    }
+    impl<T: Config> frame_support::traits::OnGenesis for Pallet<T> {
+        fn on_genesis() {
+            let storage_version = frame_support::traits::StorageVersion::default();
+            storage_version.put::<Self>();
+        }
+    }
+    impl<T: Config> frame_support::traits::PalletInfoAccess for Pallet<T> {
+        fn index() -> usize {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::index::<
+                Self,
+            >()
+            .expect(
+                "Pallet is part of the runtime because pallet `Config` trait is \
+						implemented by the runtime",
+            )
+        }
+        fn name() -> &'static str {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::name::<
+                Self,
+            >()
+            .expect(
+                "Pallet is part of the runtime because pallet `Config` trait is \
+						implemented by the runtime",
+            )
+        }
+        fn module_name() -> &'static str {
+            < < T as frame_system :: Config > :: PalletInfo as frame_support :: traits :: PalletInfo > :: module_name :: < Self > () . expect ("Pallet is part of the runtime because pallet `Config` trait is \
+						implemented by the runtime")
+        }
+        fn crate_version() -> frame_support::traits::CrateVersion {
+            frame_support::traits::CrateVersion {
+                major: 0u16,
+                minor: 1u8,
+                patch: 0u8,
+            }
+        }
+    }
+    impl<T: Config> frame_support::traits::PalletsInfoAccess for Pallet<T> {
+        fn count() -> usize {
+            1
+        }
+        fn accumulate(
+            acc: &mut frame_support::sp_std::vec::Vec<frame_support::traits::PalletInfoData>,
+        ) {
+            use frame_support::traits::PalletInfoAccess;
+            let item = frame_support::traits::PalletInfoData {
+                index: Self::index(),
+                name: Self::name(),
+                module_name: Self::module_name(),
+                crate_version: Self::crate_version(),
+            };
+            acc.push(item);
+        }
+    }
+    impl<T: Config> frame_support::traits::StorageInfoTrait for Pallet<T> {
+        fn storage_info() -> frame_support::sp_std::vec::Vec<frame_support::traits::StorageInfo> {
+            #[allow(unused_mut)]
+            let mut res = ::alloc::vec::Vec::new();
+            {
+                let mut storage_info = < Accumulators < T > as frame_support :: traits :: PartialStorageInfoTrait > :: partial_storage_info () ;
+                res.append(&mut storage_info);
+            }
+            {
+                let mut storage_info = < Counter < T > as frame_support :: traits :: PartialStorageInfoTrait > :: partial_storage_info () ;
+                res.append(&mut storage_info);
+            }
+            res
+        }
+    }
+    #[doc(hidden)]
+    pub mod __substrate_call_check {
+        #[doc(hidden)]
+        pub use __is_call_part_defined_0 as is_call_part_defined;
+    }
+    ///Contains one variant per dispatchable that can be called by an extrinsic.
+    #[codec(encode_bound())]
+    #[codec(decode_bound())]
+    #[scale_info(skip_type_params(T), capture_docs = "always")]
+    #[allow(non_camel_case_types)]
+    pub enum Call<T: Config> {
+        #[doc(hidden)]
+        #[codec(skip)]
+        __Ignore(
+            frame_support::sp_std::marker::PhantomData<(T,)>,
+            frame_support::Never,
+        ),
+        #[codec(index = 0u8)]
+        inc_user_counter {
+            #[allow(missing_docs)]
+            inc: u32,
+        },
+    }
+    const _: () = {
+        impl<T: Config> core::fmt::Debug for Call<T> {
+            fn fmt(&self, fmt: &mut core::fmt::Formatter) -> core::fmt::Result {
+                match *self {
+                    Self::__Ignore(ref _0, ref _1) => fmt
+                        .debug_tuple("Call::__Ignore")
+                        .field(&_0)
+                        .field(&_1)
+                        .finish(),
+                    Self::inc_user_counter { ref inc } => fmt
+                        .debug_struct("Call::inc_user_counter")
+                        .field("inc", &inc)
+                        .finish(),
+                }
+            }
+        }
+    };
+    const _: () = {
+        impl<T: Config> core::clone::Clone for Call<T> {
+            fn clone(&self) -> Self {
+                match self {
+                    Self::__Ignore(ref _0, ref _1) => {
+                        Self::__Ignore(core::clone::Clone::clone(_0), core::clone::Clone::clone(_1))
+                    }
+                    Self::inc_user_counter { ref inc } => Self::inc_user_counter {
+                        inc: core::clone::Clone::clone(inc),
+                    },
+                }
+            }
+        }
+    };
+    const _: () = {
+        impl<T: Config> core::cmp::Eq for Call<T> {}
+    };
+    const _: () = {
+        impl<T: Config> core::cmp::PartialEq for Call<T> {
+            fn eq(&self, other: &Self) -> bool {
+                match (self, other) {
+                    (Self::__Ignore(_0, _1), Self::__Ignore(_0_other, _1_other)) => {
+                        true && _0 == _0_other && _1 == _1_other
+                    }
+                    (Self::inc_user_counter { inc }, Self::inc_user_counter { inc: _0 }) => {
+                        true && inc == _0
+                    }
+                    (Self::__Ignore { .. }, Self::inc_user_counter { .. }) => false,
+                    (Self::inc_user_counter { .. }, Self::__Ignore { .. }) => false,
+                }
+            }
+        }
+    };
+    #[allow(deprecated)]
+    const _: () = {
+        #[allow(non_camel_case_types)]
+        #[automatically_derived]
+        impl<T: Config> ::codec::Encode for Call<T> {
+            fn encode_to<__CodecOutputEdqy: ::codec::Output + ?::core::marker::Sized>(
+                &self,
+                __codec_dest_edqy: &mut __CodecOutputEdqy,
+            ) {
+                match *self {
+                    Call::inc_user_counter { ref inc } => {
+                        __codec_dest_edqy.push_byte(0u8 as ::core::primitive::u8);
+                        ::codec::Encode::encode_to(inc, __codec_dest_edqy);
+                    }
+                    _ => (),
+                }
+            }
+        }
+        #[automatically_derived]
+        impl<T: Config> ::codec::EncodeLike for Call<T> {}
+    };
+    #[allow(deprecated)]
+    const _: () = {
+        #[allow(non_camel_case_types)]
+        #[automatically_derived]
+        impl<T: Config> ::codec::Decode for Call<T> {
+            fn decode<__CodecInputEdqy: ::codec::Input>(
+                __codec_input_edqy: &mut __CodecInputEdqy,
+            ) -> ::core::result::Result<Self, ::codec::Error> {
+                match __codec_input_edqy
+                    .read_byte()
+                    .map_err(|e| e.chain("Could not decode `Call`, failed to read variant byte"))?
+                {
+                    __codec_x_edqy if __codec_x_edqy == 0u8 as ::core::primitive::u8 => {
+                        ::core::result::Result::Ok(Call::<T>::inc_user_counter {
+                            inc: {
+                                let __codec_res_edqy =
+                                    <u32 as ::codec::Decode>::decode(__codec_input_edqy);
+                                match __codec_res_edqy {
+                                    ::core::result::Result::Err(e) => {
+                                        return ::core::result::Result::Err(e.chain(
+                                            "Could not decode `Call::inc_user_counter::inc`",
+                                        ))
+                                    }
+                                    ::core::result::Result::Ok(__codec_res_edqy) => {
+                                        __codec_res_edqy
+                                    }
+                                }
+                            },
+                        })
+                    }
+                    _ => ::core::result::Result::Err(<_ as ::core::convert::Into<_>>::into(
+                        "Could not decode `Call`, variant doesn't exist",
+                    )),
+                }
+            }
+        }
+    };
+    #[allow(non_upper_case_globals, unused_attributes, unused_qualifications)]
+    const _: () = {
+        impl<T: Config> ::scale_info::TypeInfo for Call<T>
+        where
+            frame_support::sp_std::marker::PhantomData<(T,)>: ::scale_info::TypeInfo + 'static,
+            T: Config + 'static,
+        {
+            type Identity = Self;
+            fn type_info() -> ::scale_info::Type {
+                ::scale_info::Type::builder()
+                    .path(::scale_info::Path::new("Call", "simple_pallet::pallet"))
+                    .type_params(<[_]>::into_vec(
+                        #[rustc_box]
+                        ::alloc::boxed::Box::new([::scale_info::TypeParameter::new(
+                            "T",
+                            ::core::option::Option::None,
+                        )]),
+                    ))
+                    .docs_always(&[
+                        "Contains one variant per dispatchable that can be called by an extrinsic.",
+                    ])
+                    .variant(::scale_info::build::Variants::new().variant(
+                        "inc_user_counter",
+                        |v| {
+                            v.index(0u8 as ::core::primitive::u8)
+                                .fields(::scale_info::build::Fields::named().field(|f| {
+                                    f.ty::<u32>().name("inc").type_name("u32").docs_always(&[])
+                                }))
+                                .docs_always(&[])
+                        },
+                    ))
+            }
+        };
+    };
+    impl<T: Config> Call<T> {
+        ///Create a call with the variant `inc_user_counter`.
+        pub fn new_call_variant_inc_user_counter(inc: u32) -> Self {
+            Self::inc_user_counter { inc }
+        }
+    }
+    impl<T: Config> frame_support::dispatch::GetDispatchInfo for Call<T> {
+        fn get_dispatch_info(&self) -> frame_support::dispatch::DispatchInfo {
+            match *self {
+                Self::inc_user_counter { ref inc } => {
+                    let __pallet_base_weight = 0;
+                    let __pallet_weight =
+                        <dyn frame_support::dispatch::WeighData<(&u32,)>>::weigh_data(
+                            &__pallet_base_weight,
+                            (inc,),
+                        );
+                    let __pallet_class =
+                        <dyn frame_support::dispatch::ClassifyDispatch<(&u32,)>>::classify_dispatch(
+                            &__pallet_base_weight,
+                            (inc,),
+                        );
+                    let __pallet_pays_fee =
+                        <dyn frame_support::dispatch::PaysFee<(&u32,)>>::pays_fee(
+                            &__pallet_base_weight,
+                            (inc,),
+                        );
+                    frame_support::dispatch::DispatchInfo {
+                        weight: __pallet_weight,
+                        class: __pallet_class,
+                        pays_fee: __pallet_pays_fee,
+                    }
+                }
+                Self::__Ignore(_, _) => {
+                    ::core::panicking::panic_fmt(::core::fmt::Arguments::new_v1(
+                        &["internal error: entered unreachable code: "],
+                        &[::core::fmt::ArgumentV1::new_display(
+                            &::core::fmt::Arguments::new_v1(&["__Ignore cannot be used"], &[]),
+                        )],
+                    ))
+                }
+            }
+        }
+    }
+    impl<T: Config> frame_support::dispatch::GetCallName for Call<T> {
+        fn get_call_name(&self) -> &'static str {
+            match *self {
+                Self::inc_user_counter { .. } => "inc_user_counter",
+                Self::__Ignore(_, _) => {
+                    ::core::panicking::panic_fmt(::core::fmt::Arguments::new_v1(
+                        &["internal error: entered unreachable code: "],
+                        &[::core::fmt::ArgumentV1::new_display(
+                            &::core::fmt::Arguments::new_v1(
+                                &["__PhantomItem cannot be used."],
+                                &[],
+                            ),
+                        )],
+                    ))
+                }
+            }
+        }
+        fn get_call_names() -> &'static [&'static str] {
+            &["inc_user_counter"]
+        }
+    }
+    impl<T: Config> frame_support::traits::UnfilteredDispatchable for Call<T> {
+        type Origin = frame_system::pallet_prelude::OriginFor<T>;
+        fn dispatch_bypass_filter(
+            self,
+            origin: Self::Origin,
+        ) -> frame_support::dispatch::DispatchResultWithPostInfo {
+            match self {
+                Self::inc_user_counter { inc } => {
+                    let __within_span__ = {
+                        use ::tracing::__macro_support::Callsite as _;
+                        static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                            static META: ::tracing::Metadata<'static> = {
+                                ::tracing_core::metadata::Metadata::new(
+                                    "inc_user_counter",
+                                    "simple_pallet::pallet",
+                                    ::tracing::Level::TRACE,
+                                    Some("src/lib.rs"),
+                                    Some(3u32),
+                                    Some("simple_pallet::pallet"),
+                                    ::tracing_core::field::FieldSet::new(
+                                        &[],
+                                        ::tracing_core::callsite::Identifier(&CALLSITE),
+                                    ),
+                                    ::tracing::metadata::Kind::SPAN,
+                                )
+                            };
+                            ::tracing::callsite::DefaultCallsite::new(&META)
+                        };
+                        let mut interest = ::tracing::subscriber::Interest::never();
+                        if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                            && ::tracing::Level::TRACE
+                                <= ::tracing::level_filters::LevelFilter::current()
+                            && {
+                                interest = CALLSITE.interest();
+                                !interest.is_never()
+                            }
+                            && ::tracing::__macro_support::__is_enabled(
+                                CALLSITE.metadata(),
+                                interest,
+                            )
+                        {
+                            let meta = CALLSITE.metadata();
+                            ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                        } else {
+                            let span =
+                                ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                            {};
+                            span
+                        }
+                    };
+                    let __tracing_guard__ = __within_span__.enter();
+                    frame_support::storage::in_storage_layer(|| {
+                        <Pallet<T>>::inc_user_counter(origin, inc)
+                            .map(Into::into)
+                            .map_err(Into::into)
+                    })
+                }
+                Self::__Ignore(_, _) => {
+                    let _ = origin;
+                    ::core::panicking::panic_fmt(::core::fmt::Arguments::new_v1(
+                        &["internal error: entered unreachable code: "],
+                        &[::core::fmt::ArgumentV1::new_display(
+                            &::core::fmt::Arguments::new_v1(
+                                &["__PhantomItem cannot be used."],
+                                &[],
+                            ),
+                        )],
+                    ));
+                }
+            }
+        }
+    }
+    impl<T: Config> frame_support::dispatch::Callable<T> for Pallet<T> {
+        type Call = Call<T>;
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn call_functions() -> frame_support::metadata::PalletCallMetadata {
+            frame_support::scale_info::meta_type::<Call<T>>().into()
+        }
+    }
+    pub use __tt_error_token_1 as tt_error_token;
+    #[doc(hidden)]
+    pub mod __substrate_event_check {
+        #[doc(hidden)]
+        pub use __is_event_part_defined_2 as is_event_part_defined;
+    }
+    impl<T: Config> Pallet<T> {
+        #[doc(hidden)]
+        pub fn storage_metadata() -> frame_support::metadata::PalletStorageMetadata {
+            frame_support :: metadata :: PalletStorageMetadata { prefix : < < T as frame_system :: Config > :: PalletInfo as frame_support :: traits :: PalletInfo > :: name :: < Pallet < T > > () . expect ("Every active pallet has a name in the runtime; qed") , entries : { # [allow (unused_mut)] let mut entries = :: alloc :: vec :: Vec :: new () ; { < Accumulators < T > as frame_support :: storage :: StorageEntryMetadataBuilder > :: build_metadata (:: alloc :: vec :: Vec :: new () , & mut entries) ; } { < Counter < T > as frame_support :: storage :: StorageEntryMetadataBuilder > :: build_metadata (:: alloc :: vec :: Vec :: new () , & mut entries) ; } entries } , }
+        }
+    }
+    #[doc(hidden)]
+    pub struct _GeneratedPrefixForStorageAccumulators<T>(core::marker::PhantomData<(T,)>);
+    impl<T: Config> frame_support::traits::StorageInstance
+        for _GeneratedPrefixForStorageAccumulators<T>
+    {
+        fn pallet_prefix() -> &'static str {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::name::<
+                Pallet<T>,
+            >()
+            .expect("Every active pallet has a name in the runtime; qed")
+        }
+        const STORAGE_PREFIX: &'static str = "Accumulators";
+    }
+    #[doc(hidden)]
+    pub struct _GeneratedPrefixForStorageCounter<T>(core::marker::PhantomData<(T,)>);
+    impl<T: Config> frame_support::traits::StorageInstance for _GeneratedPrefixForStorageCounter<T> {
+        fn pallet_prefix() -> &'static str {
+            <<T as frame_system::Config>::PalletInfo as frame_support::traits::PalletInfo>::name::<
+                Pallet<T>,
+            >()
+            .expect("Every active pallet has a name in the runtime; qed")
+        }
+        const STORAGE_PREFIX: &'static str = "Counter";
+    }
+    #[doc(hidden)]
+    pub mod __substrate_inherent_check {
+        #[doc(hidden)]
+        pub use __is_inherent_part_defined_3 as is_inherent_part_defined;
+    }
+    /// Hidden instance generated to be internally used when module is used without
+    /// instance.
+    #[doc(hidden)]
+    pub type __InherentHiddenInstance = ();
+    impl<T: Config> frame_support::traits::OnFinalize<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn on_finalize(n: <T as frame_system::Config>::BlockNumber) {
+            let __within_span__ = {
+                use ::tracing::__macro_support::Callsite as _;
+                static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                    static META: ::tracing::Metadata<'static> = {
+                        ::tracing_core::metadata::Metadata::new(
+                            "on_finalize",
+                            "simple_pallet::pallet",
+                            ::tracing::Level::TRACE,
+                            Some("src/lib.rs"),
+                            Some(3u32),
+                            Some("simple_pallet::pallet"),
+                            ::tracing_core::field::FieldSet::new(
+                                &[],
+                                ::tracing_core::callsite::Identifier(&CALLSITE),
+                            ),
+                            ::tracing::metadata::Kind::SPAN,
+                        )
+                    };
+                    ::tracing::callsite::DefaultCallsite::new(&META)
+                };
+                let mut interest = ::tracing::subscriber::Interest::never();
+                if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                    && ::tracing::Level::TRACE <= ::tracing::level_filters::LevelFilter::current()
+                    && {
+                        interest = CALLSITE.interest();
+                        !interest.is_never()
+                    }
+                    && ::tracing::__macro_support::__is_enabled(CALLSITE.metadata(), interest)
+                {
+                    let meta = CALLSITE.metadata();
+                    ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                } else {
+                    let span = ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                    {};
+                    span
+                }
+            };
+            let __tracing_guard__ = __within_span__.enter();
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_finalize (n)
+        }
+    }
+    impl<T: Config> frame_support::traits::OnIdle<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn on_idle(
+            n: <T as frame_system::Config>::BlockNumber,
+            remaining_weight: frame_support::weights::Weight,
+        ) -> frame_support::weights::Weight {
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_idle (n , remaining_weight)
+        }
+    }
+    impl<T: Config> frame_support::traits::OnInitialize<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn on_initialize(
+            n: <T as frame_system::Config>::BlockNumber,
+        ) -> frame_support::weights::Weight {
+            let __within_span__ = {
+                use ::tracing::__macro_support::Callsite as _;
+                static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                    static META: ::tracing::Metadata<'static> = {
+                        ::tracing_core::metadata::Metadata::new(
+                            "on_initialize",
+                            "simple_pallet::pallet",
+                            ::tracing::Level::TRACE,
+                            Some("src/lib.rs"),
+                            Some(3u32),
+                            Some("simple_pallet::pallet"),
+                            ::tracing_core::field::FieldSet::new(
+                                &[],
+                                ::tracing_core::callsite::Identifier(&CALLSITE),
+                            ),
+                            ::tracing::metadata::Kind::SPAN,
+                        )
+                    };
+                    ::tracing::callsite::DefaultCallsite::new(&META)
+                };
+                let mut interest = ::tracing::subscriber::Interest::never();
+                if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                    && ::tracing::Level::TRACE <= ::tracing::level_filters::LevelFilter::current()
+                    && {
+                        interest = CALLSITE.interest();
+                        !interest.is_never()
+                    }
+                    && ::tracing::__macro_support::__is_enabled(CALLSITE.metadata(), interest)
+                {
+                    let meta = CALLSITE.metadata();
+                    ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                } else {
+                    let span = ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                    {};
+                    span
+                }
+            };
+            let __tracing_guard__ = __within_span__.enter();
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_initialize (n)
+        }
+    }
+    impl<T: Config> frame_support::traits::OnRuntimeUpgrade for Pallet<T> {
+        fn on_runtime_upgrade() -> frame_support::weights::Weight {
+            let __within_span__ = {
+                use ::tracing::__macro_support::Callsite as _;
+                static CALLSITE: ::tracing::callsite::DefaultCallsite = {
+                    static META: ::tracing::Metadata<'static> = {
+                        ::tracing_core::metadata::Metadata::new(
+                            "on_runtime_update",
+                            "simple_pallet::pallet",
+                            ::tracing::Level::TRACE,
+                            Some("src/lib.rs"),
+                            Some(3u32),
+                            Some("simple_pallet::pallet"),
+                            ::tracing_core::field::FieldSet::new(
+                                &[],
+                                ::tracing_core::callsite::Identifier(&CALLSITE),
+                            ),
+                            ::tracing::metadata::Kind::SPAN,
+                        )
+                    };
+                    ::tracing::callsite::DefaultCallsite::new(&META)
+                };
+                let mut interest = ::tracing::subscriber::Interest::never();
+                if ::tracing::Level::TRACE <= ::tracing::level_filters::STATIC_MAX_LEVEL
+                    && ::tracing::Level::TRACE <= ::tracing::level_filters::LevelFilter::current()
+                    && {
+                        interest = CALLSITE.interest();
+                        !interest.is_never()
+                    }
+                    && ::tracing::__macro_support::__is_enabled(CALLSITE.metadata(), interest)
+                {
+                    let meta = CALLSITE.metadata();
+                    ::tracing::Span::new(meta, &{ meta.fields().value_set(&[]) })
+                } else {
+                    let span = ::tracing::__macro_support::__disabled_span(CALLSITE.metadata());
+                    {};
+                    span
+                }
+            };
+            let __tracing_guard__ = __within_span__.enter();
+            let pallet_name = < < T as frame_system :: Config > :: PalletInfo as frame_support :: traits :: PalletInfo > :: name :: < Self > () . unwrap_or ("<unknown pallet name>") ;
+            {
+                let lvl = ::log::Level::Info;
+                if lvl <= ::log::STATIC_MAX_LEVEL && lvl <= ::log::max_level() {
+                    ::log::__private_api_log(
+                        ::core::fmt::Arguments::new_v1(
+                            &["\u{2705} no migration for "],
+                            &[::core::fmt::ArgumentV1::new_display(&pallet_name)],
+                        ),
+                        lvl,
+                        &(
+                            frame_support::LOG_TARGET,
+                            "simple_pallet::pallet",
+                            "src/lib.rs",
+                            3u32,
+                        ),
+                        ::log::__private_api::Option::None,
+                    );
+                }
+            };
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: on_runtime_upgrade ()
+        }
+    }
+    impl<T: Config> frame_support::traits::OffchainWorker<<T as frame_system::Config>::BlockNumber>
+        for Pallet<T>
+    {
+        fn offchain_worker(n: <T as frame_system::Config>::BlockNumber) {
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: offchain_worker (n)
+        }
+    }
+    impl<T: Config> frame_support::traits::IntegrityTest for Pallet<T> {
+        fn integrity_test() {
+            < Self as frame_support :: traits :: Hooks < < T as frame_system :: Config > :: BlockNumber > > :: integrity_test ()
+        }
+    }
+    #[doc(hidden)]
+    pub mod __substrate_genesis_config_check {
+        #[doc(hidden)]
+        pub use __is_genesis_config_defined_4 as is_genesis_config_defined;
+        #[doc(hidden)]
+        pub use __is_std_enabled_for_genesis_4 as is_std_enabled_for_genesis;
+    }
+    #[doc(hidden)]
+    pub mod __substrate_origin_check {
+        #[doc(hidden)]
+        pub use __is_origin_part_defined_5 as is_origin_part_defined;
+    }
+    #[doc(hidden)]
+    pub mod __substrate_validate_unsigned_check {
+        #[doc(hidden)]
+        pub use __is_validate_unsigned_part_defined_6 as is_validate_unsigned_part_defined;
+    }
+    pub use __tt_default_parts_7 as tt_default_parts;
+}
diff --git a/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/src/lib.rs b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/src/lib.rs
new file mode 100644
index 00000000..30642b86
--- /dev/null
+++ b/content/6-Protocol_On-Chain/FRAME/simple-runtime/transfer-pallet/src/lib.rs
@@ -0,0 +1,40 @@
+#![cfg_attr(not(feature = "std"), no_std)]
+pub use pallet::*;
+
+#[frame_support::pallet]
+pub mod pallet {
+  use codec::{Codec, FullEncode};
+  use frame_support::{pallet_prelude::*};
+  use frame_system::pallet_prelude::*;
+
+  #[pallet::config]
+  pub trait Config: frame_system::Config {
+    type MinimumBalance: Get<u128>;
+  }
+
+  #[pallet::storage]
+  pub type Balances<T: Config> = StorageMap<_, Twox64Concat, T::AccountId, u128>;
+
+  #[pallet::pallet]
+  #[pallet::without_storage_info]
+  pub struct Pallet<T>(PhantomData<T>);
+
+  #[pallet::genesis_config]
+  #[cfg_attr(feature = "std", derive(frame_support::DefaultNoBound))]
+  pub struct GenesisConfig<T: Config> {
+    pub balances: Vec<(T::AccountId, u128)>,
+  }
+
+  #[pallet::genesis_build]
+  impl<T: Config> GenesisBuild<T> for GenesisConfig<T> {
+    fn build(&self) {
+      for (who, initial_balance) in &self.balances {
+        assert!(*initial_balance > T::MinimumBalance::get(), "initial balance too low");
+        Balances::<T>::insert(who, initial_balance);
+      }
+		}
+	}
+
+  #[pallet::call]
+  impl<T: Config> Pallet<T> {}
+}
diff --git a/content/6-Protocol_On-Chain/README.md b/content/6-Protocol_On-Chain/README.md
new file mode 100644
index 00000000..89755d5b
--- /dev/null
+++ b/content/6-Protocol_On-Chain/README.md
@@ -0,0 +1,110 @@
+# Module 6: Polkadot SDK
+
+## Substrate
+
+### Learning Outcomes
+
+### Hands on activities
+
+## Frame
+
+### Learning Outcomes
+
+### Hands on activities
+
+## Cross Consensus Messaging (XCM)
+
+<!-- TODO Break down the following in the schedule below -->
+
+Day 1:
+
+- Intro to XCM
+- Most Important XCM Scenarios (reserve transfer, teleport transfer, governance, upgrades, transact)
+- XCM Instructions (and specifically how these instructions map to these most important scenarios)
+- XCM Executor (dive into the logic of how instructions are executed and all the base types surrounding the executor)
+- Workshop: Build and test all of the important end to end scenarios with XCM simulator
+
+Goal: avoid talking about or touching the XCM config at all at this point. Just make them work with the base tools needed to build an XCM.
+
+Day 2:
+
+- XCM Config
+- Workshop: Modify XCM Simulator with some custom configurations and write end to end tests
+- XCMP, HRMP, UMP, Connections, Queues
+- XCM Version
+- Zombienet, and setting up a local environment
+- Workshop: building end to end XCM on a live test net using either JavaScript or Rust as a CLI or Front-End
+- EXTRA: XCM specific scenario for polkadot-sdk project they work on
+
+Goal, finally expose users to all that they can configure, have them make configurations for different scenarios and test they work.
+
+### Learning Outcomes
+
+Goal for Day 1: Building an example end to end XCM Simulator
+Goal for Day 2: Building an example end to end with JavaScript / Rust front end / CLI
+
+### Hands on activities
+
+---
+
+## Schedule
+
+### Day 1
+
+#### Morning
+
+#### Afternoon
+
+### Day 2
+
+#### Morning
+
+#### Afternoon
+
+### Day 3
+
+#### Morning
+
+#### Afternoon
+
+### Day 4
+
+#### Morning
+
+#### Afternoon
+
+### Day 5
+
+#### Morning
+
+#### Afternoon
+
+### Day 6
+
+#### Morning
+
+#### Afternoon
+
+### Day 7
+
+#### Morning
+
+#### Afternoon
+
+### Day 8
+
+#### Morning
+
+#### Afternoon
+
+### Day 9
+
+#### Morning
+
+#### Afternoon
+
+### Day 10
+
+#### Morning
+
+#### Afternoon
diff --git a/content/6-Protocol_On-Chain/Substrate/1-Intro-to-Substrate-slides.md b/content/6-Protocol_On-Chain/Substrate/1-Intro-to-Substrate-slides.md
new file mode 100644
index 00000000..1967bfd0
--- /dev/null
+++ b/content/6-Protocol_On-Chain/Substrate/1-Intro-to-Substrate-slides.md
@@ -0,0 +1,1253 @@
+---
+title: Introduction to Substrate
+description: Substrate Overview for Web3 engineers
+duration: 60 minutes
+---
+
+# Introduction to Substrate
+
+---
+
+## What is Substrate?
+
+Substrate is a **Rust framework** for **building blockchains**.
+
+Note:
+
+like a blockchain making factory.
+
+---v
+
+### Why Substrate?
+
+<img rounded width="1000px" src="../../../assets/img/5-Substrate/dev-4-1-substrate-website.gif" />
+
+Notes:
+
+Highlight the multi-chain part.
+
+---v
+
+### Why Substrate?
+
+- ⛓️ Future is multi-chain.
+- 😭 Building a blockchain is hard. Upgrading it even harder.
+
+<!-- .element: class="fragment" -->
+
+- 💡 Framework!
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Why Substrate?
+
+<img rounded width="1000px" src="../../../assets/img/5-Substrate/dev-4.1-maximalism.png" />
+
+Notes:
+
+Substrate is a pure technological investment against chain maximalism, even outside of Polkadot. You
+can create sovereign chains with substrate, or Polkadot Parachains, or more hybrid things. More on
+this when you learn about Substrate's role in the Polkadot ecosystem.
+
+Figure: https://www.youtube.com/watch?v=0IoUZdDi5Is
+
+---v
+
+### Why Substrate?
+
+#### 💭 An update in 2024 💭
+
+🧐 Multi-chain vs. Multi-shard 🧐
+
+Note:
+
+Polkadot led the way since 2016 to convince the world that the future is multi-chain.
+
+Cosmos tried to replicate the same without shared security.
+
+ETH is now doing something similar, with a Rollup-Centric roadmap.
+
+Interestingly, Polkadot is now arguing that the future is not necessarily multi-chain, but rather
+multi-shard. In that, there needs to be a sharded system, with a high degree of flexibility to
+schedule those shards. "Multi-chain" is merely one manifestation of a multi-shard system, which is
+actually not so flexible. We are now striving to make the multi-chain Polkadot more flexible, which
+is what JAM is going to be.
+
+---
+
+## Core Philosophies of Substrate 💭
+
+The **pre-substrate** way of thinking:
+
+- 😭 _Building a blockchain is hard. Upgrading it even harder_.
+- 💪🏻 We are going to spend maximal resources at making sure we get it right.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Core Philosophies of Substrate 💭
+
+But has this worked?
+
+- 😭 Bitcoin block size debate
+
+<!-- .element: class="fragment" -->
+
+- 2️⃣ L2s and beyond
+
+<!-- .element: class="fragment" -->
+
+- 📈 Ethereum gas price
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+Bitcoin block size has never been and is an ongoing debate.
+
+I am not against L2s per se, but it is truth that they mostly exist because the underlying protocol
+is too hard/slow to upgrade itself. ETH Gas prices is also shows that the underlying protocol cannot
+meet the demands of today.
+
+https://en.wikipedia.org/wiki/Bitcoin_scalability_problem
+https://ycharts.com/indicators/ethereum_average_gas_price
+
+It is interesting to checkout some projects that are now trying to be "Substrate for L2s":
+https://github.com/Sovereign-Labs/sovereign-sdk / https://arbitrum.io/orbit
+
+---v
+
+### Core Philosophies of Substrate 💭
+
+The **Substrate** way of thinking:
+
+- ☯️ Society and technology evolve
+
+<!-- .element: class="fragment" -->
+
+- 🦸 Humans are fallible
+
+<!-- .element: class="fragment" -->
+
+- 🧠 Best decision of today -> mistake of tomorrow
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Core Philosophies of Substrate 💭
+
+Outcomes of this:
+
+- 🦀 Rust
+- 🤩 Generic, Modular and Extensible Design
+- 🏦 Governance + Upgradeability
+
+Notes:
+
+Think about how each of these links back to "whatever you decide today will be a mistake soon".
+
+---
+
+## 🦀 Rust
+
+- First line of defense: prevent human error when possible.
+- Safe language, no memory safety issues.
+
+Notes:
+
+So at least we don't want to deal with human error, and only deal with the fact that we cannot
+predict the future.
+
+Memory safety is a fundamental issue in most major system-level programming languages.
+
+Some such mistakes are impossible to make in Rust.
+
+---v
+
+### 🦀 Rust
+
+<img rounded src="../img/rust-meme.png" />
+
+Note:
+
+```c
+int main() {
+    int* x = malloc(sizeof(int));
+    *x = 10;
+    int* y = x;
+    free(x);
+    printf("%d\n", *y);  // Accessing memory after it's been freed
+}
+```
+
+<br/>
+
+```rust
+fn main() {
+    let x = Box::new(10);
+    let y = x;
+    println!("{}", *y); // ❌
+}
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+another one:
+
+```c
+int* foo() {
+    int x = 10;
+    return &x;
+}
+
+int main() {
+    int* y = foo();
+    printf("%d\n", *y); // Accessing memory out of its scope
+}
+```
+
+<br/>
+
+```rust
+fn foo() -> &'static i32 {
+    let x = 10;
+    &x
+}
+
+fn main() {
+    let y = foo();
+    println!("{}", y); // ❌
+}
+```
+
+---v
+
+### 🦀 Rust
+
+> Microsoft and Google have each stated that software memory safety issues are behind around 70 percent of their vulnerabilities.
+
+Notes:
+
+https://www.nsa.gov/Press-Room/News-Highlights/Article/Article/3215760/nsa-releases-guidance-on-how-to-protect-against-software-memory-safety-issues/#:~:text=Microsoft%20and%20Google%20have%20each,70%20percent%20of%20their%20vulnerabilities.
+
+---v
+
+### 🦀 Rust
+
+- 🏎️ Most Rust abstractions are **zero-cost**.
+- ⏰ Rust has (almost) no "runtime".
+
+<br/>
+
+<img rounded width="900px" src="../../../assets/img/5-Substrate/dev-4-1-speed.png" />
+
+Notes:
+
+this is not 100% accurate though, rust has a small runtime that is the panic handler etc. Rust for Rustacean's chapter on `no_std` covers this very well.
+
+Also, this is a good time to talk about how we use "Runtime" in a different way.
+
+---
+
+## 🤩 Generic, Modular and Extensible Design
+
+- Second line of defense.
+- Whatever code we write is (thanks to Rust) perfectly executed, _but what should we write_?
+
+Notes:
+
+this is where a module, generic design is useful. You can change components easily based on the
+needs of the future.
+
+---v
+
+### 🤩 Generic, Modular and Extensible Design
+
+- Multiple consensus engines (BABE/Grandpa/AURA/PoW/Sassafras)
+
+<!-- .element: class="fragment" -->
+
+- Multiple network protocols (QUIC, TCP)
+
+<!-- .element: class="fragment" -->
+
+- Multiple database implementations (ParityDB, RocksDB)
+
+<!-- .element: class="fragment" -->
+
+- Highly configurable, graph-based transaction-pool.
+
+<!-- .element: class="fragment" -->
+
+- Easy to change primitives: AccountId, Signature, BlockNumber, Header, Hash, and many more.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+FRAME takes this even multiple steps further, but that's for later.
+
+These are all examples of being generic, modular and extensible at the Substrate level. FRAME takes
+these even further, but more on that later.
+
+---v
+
+### 🤩 Generic, Modular and Extensible Design
+
+- **AlephZero**: Custom finality, DAG-based, 1s block time.
+- **Moonbeam**: Ethereum compatible, build with substrate.
+- **HydraDX**: Custom transaction pool logic to match DEX orders.
+- **Kulupu**: Proof of work, custom hashing.
+
+Notes:
+
+Substrate has been coded, from the ground up, such that it is easy to have multiple implementations
+for certain functions. Heavy use of traits and generics is the key to achieve this. As noted,
+Substrate has a lot of APIs, and optional implementations. You are bound to the API, but not the
+particular implementation.
+
+---
+
+## 🏦 Governance + Upgradeability
+
+- Third, final, and non-negotiable line of defense to survive the test of time.
+
+---v
+
+### 🏦 Governance + Upgradeability
+
+- We have correct code, and components are easy to swap, replace, and upgrade.
+- What use is that, if we cannot agree on what to replace/upgrade?
+- Governance!
+
+Notes:
+
+Even if we are governable, but we still need "trust" to enact the upgrade, it is hardly any better.
+In essence, if an upgrade mechanism is not self-enacting, it might as well just reside offchain and
+be a signaling mechanism.
+
+---v
+
+### 🏦 Governance + Upgradeability
+
+- ✅ Governance: Easy
+- 😢 (Trustless) Upgradeability: Not so much
+
+---v
+
+### 🏦 Governance + Upgradeability
+
+- How does a typical blockchain upgrade itself?
+
+Notes:
+
+1. Discussion, offchain signaling
+2. Possibly onchain voting
+3. Hard(ish) Fork
+
+---v
+
+### 🏦 Governance + Upgradeability
+
+<img src="../../../assets/img/5-Substrate/dev-4-1-substrate-monol.svg" />
+
+---v
+
+### 🏦 Governance + Upgradeability
+
+<img src="../../../assets/img/5-Substrate/dev-4-1-substrate-monol-2.svg" />
+
+Notes:
+
+the problem is that the system is one big monolith protocol. Updating any part of it requires the
+whole thing to be updated.
+
+---v
+
+### 🏦 Governance + Upgradeability
+
+<img src="../../../assets/img/5-Substrate/dev-4-1-substrate-meta-substrate.svg" />
+
+Note:
+
+This is very similar to treating your own runtime as a smart contract.
+
+---v
+
+### 🏦 Governance + Upgradeability
+
+<img src="../../../assets/img/5-Substrate/dev-4-1-substrate-meta.svg" />
+
+Note:
+
+In this figure, the meta-protocol, the substrate node, is not forklessly upgrade-able. It can only
+be upgraded with a fork.
+
+---v
+
+### 🏦 Governance + Upgradeability
+
+_The way to make a protocol truly upgradeable is to design a (fixed) meta-protocol._
+
+---
+
+## Substrate Architecture
+
+<img src="../../../assets/img/5-Substrate/dev-4-1-substrate.svg" />
+
+---v
+
+#### Substrate (simplified) Architecture
+
+<pba-cols>
+
+<pba-col center>
+<h3 style="color: var(--substrate-runtime); top: 0"> Runtime (Protocol) </h3>
+
+- Application logic aka. How we execute block
+- Stored as a part of your chain state as a WASM Blob
+- Upgradeable
+- Also known as: STF
+
+</pba-col>
+
+<pba-col center>
+
+<img width="600px" src="../../../assets/img/5-Substrate/dev-4-1-substrate.svg" />
+
+</pba-col>
+</pba-cols>
+
+---v
+
+#### Substrate (simplified) Architecture
+
+<pba-cols>
+<pba-col center>
+<h3 style="color: var(--substrate-host); top: 0"> Fixed Node (Meta-protocol) </h3>
+
+- Native Binary
+- Executes the Wasm runtime
+- Everything else: Database, Networking, Mempool, Consensus..
+- Also known as: Host, Client
+
+</pba-col>
+
+<pba-col center>
+
+<img width="600px" src="../../../assets/img/5-Substrate/dev-4-1-substrate.svg" />
+
+</pba-col>
+
+</pba-cols>
+
+---
+
+## Core Substrate Philosophies
+
+\*For a system to survive the **test of time\***:
+
+0. Correct and Safe
+1. Generic
+2. Governable
+3. Trust-less-ly Upgradeable.
+
+Substrate's Wasm meta-protocol exactly enables the latest ✅
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+Question: how would you put the meta-protocol of Substrate into words?
+
+The node is basically a wasm meta-protocol that does only one thing. This meta-protocol is
+hardcoded, but the protocol itself is flexible.
+
+---v
+
+## Core Substrate Philosophies
+
+- Why all this complexity? 😵‍💫😵‍💫
+
+<img style="width: 1200px" style="width: 1400px;" src="./img/centuries.png" />
+
+Note:
+
+- Don't care about a timeless system -> Substrate is not the right tool
+- Don't care about a truly resilient platform -> Polkadot is not the right platform
+
+---
+
+## Positive Consequences of _Wasm_ Runtime 🔥
+
+---v
+
+### 🤖 Deterministic Execution
+
+- Portable, yet deterministic bytecode.
+
+Notes:
+
+Wasm's instruction set is deterministic, so all good.
+
+---v
+
+### 🧱 Sandboxing
+
+- Useful when executing untrusted code.
+
+1. Smart contracts
+2. Parachain runtime
+
+Notes:
+
+how can we guarantee that neither enter an infinite loop, or try to access the filesystem?
+
+---v
+
+### 🌈 Easier (light)Node Development
+
+Notes:
+
+for the case of node, your node only needs to implement the host/client, and NOT re-implement the
+business logic.
+
+Simply compare the process to create an alternative node for Ethereum, where you need to
+re-implement the EVM.
+
+Same applies to light node, as they do not need to deal with the state transition function.
+
+---v
+
+### 😎 Forkless Upgrade
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-1-forkless-1.svg" />
+
+---v
+
+### 😎 Forkless Upgrade
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-1-forkless-2.svg" />
+
+---v
+
+### 😎 Forkless Upgrade
+
+This update was:
+
+1. Forkless
+2. Self-enacting
+
+Notes:
+
+take a moment to establish that this upgrade is forkless. The runtime is upgraded, but the node is
+not. In fact, the node didn't need to know about this at all.
+
+This is what the meta-protocol achieves.
+
+---
+
+## Negative Consequences of _Wasm_ Runtime
+
+---v
+
+### 😩 Constrained Resources
+
+👾 memory, speed, host access
+
+Notes:
+
+- 4GB of memory, which we limit even further.
+- Wasm has no allocator+panic handler of its own
+- Can be slower than native, depending on the executor/execution method.
+- Limited access to the host host env, all needs to be done through syscalls.
+
+---v
+
+### 🌈 Node diversification != runtime diversification
+
+Notes:
+
+Less state-transition diversification, because the runtime is the same for all clients. If there a
+bug in it, everyone is affected.
+---v
+
+### 🔄 Metering
+
+- Is not so great in WASM...
+- New experimental work on PolkaVM, based on RiscV.
+
+Notes:
+
+It is possible to meter wasm, but it has overhead, and it is still not perfect. Goes back to the instruction set being relatively large.
+
+Both of the following are amazing reads:
+
+https://forum.polkadot.network/t/eliminating-pre-dispatch-weight/400
+
+https://forum.polkadot.network/t/announcing-polkavm-a-new-risc-v-based-vm-for-smart-contracts-and-possibly-more/3811/32
+
+---
+
+## Communication Paths
+
+<img style="width: 1400px" src="../../../assets/img/5-Substrate/dev-4-1-comms.svg" />
+
+---v
+
+### Communication Paths
+
+<img style="width: 1400px" src="../../../assets/img/5-Substrate/dev-4-1-comms-format.svg" />
+
+---v
+
+### Example: SCALE vs JSON
+
+- SCALE is an efficient, non-descriptive, binary encoding format, used EXTENSIVELY in the Substrate ecosystem.
+
+---v
+
+### Example: SCALE vs JSON
+
+<div class="flex-container text-smaller">
+<div class="left">
+
+```rust
+use parity_scale_codec::{ Encode };
+
+#[derive(Encode)]
+struct Example {
+	number: u8,
+	is_cool: bool,
+	optional: Option<u32>,
+}
+
+fn main() {
+	let my_struct = Example {
+		number: 42,
+		is_cool: true,
+		optional: Some(69),
+	};
+	println!("{:?}", my_struct.encode());
+	println!("{:?}", my_struct.encode().len());
+}
+```
+
+```sh
+[42, 1, 1, 69, 0, 0, 0]
+7
+```
+
+</div>
+<div class="right" style="margin-left: 10px;">
+
+```rust
+use serde::{ Serialize };
+
+#[derive(Serialize)]
+struct Example {
+	number: u8,
+	is_cool: bool,
+	optional: Option<u32>,
+}
+
+fn main() {
+	let my_struct = Example {
+		number: 42,
+		is_cool: true,
+		optional: Some(69),
+	};
+	println!("{:?}", serde_json::to_string(&my_struct).unwrap());
+	println!("{:?}", serde_json::to_string(&my_struct).unwrap().len());
+}
+```
+
+```sh
+"{\"number\":42,\"is_cool\":true,\"optional\":69}"
+42
+```
+
+</div>
+</div>
+
+---
+
+## Substrate and Smart Contracts
+
+<img style="width: 800px;" src="../../../assets/img/5-Substrate/dev-4-1-contracts.svg" />
+
+---v
+
+### Substrate and Smart Contracts
+
+<img style="width: 800px;" src="../../../assets/img/5-Substrate/dev-4-1-contracts-full.svg" />
+
+---v
+
+### Substrate and Smart Contracts
+
+<pba-cols>
+
+<pba-col>
+  <img style="width: 600px;" src="../../../assets/img/5-Substrate/peter-parker-glasses-off.png" />
+</pba-col>
+
+<pba-col>
+  <img src="../../../assets/img/5-Substrate/ethereum-logo.svg" />
+</pba-col>
+
+</pba-cols>
+
+---v
+
+### Substrate and Smart Contracts
+
+<pba-cols>
+
+<pba-col>
+  <img style="width: 600px;" src="../../../assets/img/5-Substrate/peter-parker-glasses-on.png" />
+</pba-col>
+
+<pba-col>
+  <img style="width: 400px; background: white; border-radius: 50%; padding: 30px;" src="../../../assets/img/5-Substrate/substrate-logo.svg" />
+  <p style="font-size: 6rem;">😎</p>
+</pba-col>
+
+</pba-cols>
+
+---v
+
+### Substrate and Smart Contracts
+
+- So when should you write with a smart contract, and when a Runtime (FRAME)?
+
+Notes:
+
+https://paritytech.github.io/polkadot-sdk/master/polkadot_sdk_docs/reference_docs/runtime_vs_smart_contract/index.html
+
+I was asked this yesterday as well. My latest answer is: if you don't need any of the customizations
+that a blockchain node/runtime gives to you, and the performance of a shared platform is okay for
+you, then go with a smart contract. If you need more, you need a "runtime" (some kind of chian,
+parachain or solo)
+
+An example of customization is that a runtime has access to `on_initialize` etc.
+
+Also, a contract can not have fee-less transactions.
+
+Also, a contract usually depends on a token for gas, while a runtime can be in principle token-less
+fee-less.
+
+---
+
+## Development Options
+
+<img style="width: 1000px;" src="../../../assets/img/5-Substrate/dev-4-1-freedom.svg" />
+
+Notes:
+
+OpenZepplin is working on templates for substrate now:
+
+https://github.com/OpenZeppelin/polkadot-runtime-template
+
+We also have some of our own:
+
+https://paritytech.github.io/polkadot-sdk/master/polkadot_sdk_docs/polkadot_sdk/templates/index.html
+
+Omni node:
+
+https://forum.polkadot.network/t/polkadot-parachain-omni-node-gathering-ideas-and-feedback/7823/5
+
+---
+
+## Substrate and Polkadot
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-1-polkadot.svg" />
+
+> ..is the biggest bet against chain maximalism
+
+---v
+
+### Repository Structure
+
+#### [`polkadot-sdk`](https://github.com/paritytech/polkadot-sdk)
+
+- Substrate + FRAME + XCM
+- Cumulus
+- Bridges
+- Polkadot Node
+
+**This is a big repo, please clone and run `cargo build` on it after this lecture**
+
+<br/>
+
+#### [`polkadot-fellowship/runtime`](https://github.com/polkadot-fellows/runtimes)
+
+- Polkadot Runtimes
+
+Notes:
+
+https://paritytech.github.io/polkadot-sdk/master/polkadot_sdk_docs/polkadot_sdk/index.html
+
+---
+
+## Substrate: The Gaming Console of Blockchains!
+
+<pba-cols>
+<pba-col>
+
+<img src="../../../assets/img/5-Substrate/nintendo-console-2.png" style="width:400px;" />
+
+Substrate Node
+
+</pba-col>
+<pba-col>
+
+<img src="../../../assets/img/5-Substrate/nintendo-game.png" style="width:400px;" />
+
+Substrate's Wasm Runtime
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Another good analogy: Node is the FPGA, and FRAME/Wasm is the VHDL.
+
+---
+
+## Lecture Recap - Part 1
+
+- Substrate's design stems from 3 core principles:
+  - **Rust**, **Generic Design**, **Upgradeability/Governance**
+  - **Runtime <> Node** Architecture
+- Positive and negative consequences of Wasm
+- Substrate next to Polkadot and other chains.
+- Development Options
+- Substrate and Smart Contracts.
+
+---v
+
+## Lecture Recap - Part 1
+
+- Questions?
+
+<img src="../../../assets/img/5-Substrate/dev-4-1-substrate.svg" />
+
+---
+
+## Part 2: Substrate Architecture
+
+So far we covered high level facts about Substrate. Now let's dive deeper into its architecture using the Runtime/STF.
+
+---
+
+## State Transition Function
+
+Let's explore this definition of the runtime a bit more.
+
+---v
+
+### State Transition Function
+
+**State**
+
+<img style="width: 600px" src="../../../assets/img/5-Substrate/dev-4-1-state-def.svg" />
+
+Notes:
+
+entire set of data upon which we want to maintain a consensus.
+key value.
+associated with each block.
+
+---v
+
+### State Transition Function
+
+**Transition Function**
+
+<img width="400px" src="../../../assets/img/5-Substrate/dev-4-1-state-transition-def.svg" />
+
+---v
+
+### State Transition Function
+
+$$STF = F(block_{N+1}, state_{N}, code_{N}): state_{N+1}$$
+
+Note:
+
+Who can find a small nitpick issue in this?
+
+Code is part of state.
+
+---v
+
+### State Transition Function
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-1-state.svg" />
+
+Notes:
+
+This diagram should really be 100000% clear to everyone. Pause.
+
+The Wasm runtime in this figure is in fact obtained from the state (see `0x123`)
+
+---v
+
+### State Transition Function
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-1-state-code.svg" />
+
+Note:
+
+now what would happen when we want to execute block N+2?
+
+---v
+
+### State Transition Function
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-1-state-code-next.svg" />
+
+Notes:
+
+THIS IS HOW A META-PROTOCOL MAKES A SYSTEM UPGRADE-ABLE.
+
+Q: could we have updated the code in N+1? By default, no because we load the wasm before you even look
+into the block.
+
+IMPORTANT: State is not IN THE BLOCK, each state has AN ASSOCIATED BLOCK.
+
+Keeping the state is 100% optional. You can always re-create the state of block `N` by re-executing
+block `[0, .., N-1]`.
+
+ofc, changing the Wasm code cannot be done by anyone. That's up to governance.
+
+---v
+
+### The Runtime
+
+<div>
+
+- Blockchain -> **State Machine**
+- Runtime -> **State Transition Function**
+  - &shy;<!-- .element: class="fragment" -->Or, **application logic**.
+  - &shy;<!-- .element: class="fragment" -->Or, **how to execute blocks**
+
+Notes:
+
+- I would personally call the runtime STF to avoid confusion with the "runtime" that is the general
+  programming runtime, but kinda too late for that now.
+- Among the definitions of the Wasm runtime, let's recap what the state transition is.
+- The block execution definition will be described more in the Wasm-meta lecture.
+
+---
+
+## Full Substrate Architecture
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-3-full.svg" />
+
+---
+
+## Consensus <> Runtime 🤔
+
+- Yes, consensus is not a core part of a blockchain runtime. Why?
+- Not part of your STF!
+
+<!-- .element: class="fragment" -->
+
+- The consensus protocol is to your runtime what HTTP is to Facebook.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+comments from Joshy:
+
+I think this is important. The runtime is the application you want to run.
+
+Consensus is outside of this application helping us agree what the official state of this runtime
+is. Last wave I used this analogy.
+
+Imagine a writers room for some TV show. Writers are sitting around coming up with potential plot
+points for future episodes. Any of their ideas could work. But eventually they need to agree what
+the next episode to air actually will be.
+
+---
+
+## Database <> State 🤔
+
+- State is the entire set of key value data that is associated with one block.
+- Database is the component that allows this be stored in disk. May or may not be key-value.
+
+<img style="width: 800px" src="../../../assets/img/5-Substrate/dev-4-1-state-database.svg" />
+
+Notes:
+
+state is sometimes called "storage" asd well.
+
+---
+
+### Database <> Runtime 🤔
+
+- Yes, data is stored outside of the runtime. Why?
+- Wasm runtime does not have the means to store it.
+
+<!-- .element: class="fragment" -->
+
+- Yet, the interpretation of the data is up to the runtime.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Database <> Runtime 🤔
+
+<img style="width: 1200px" src="../../../assets/img/5-Substrate/dev-4-1-state-opaque.svg" />
+
+---v
+
+### The Node: Database 🤔
+
+- The database, from the client's PoV, is a _untyped_, key-value storage.
+- The runtime knows which key/value means what.
+
+---
+
+## Lecture Recap - Part 2
+
+- Full Substrate Architecture
+- State Transition Deep Dive -> Forkless Upgrade
+- Consensus / Database being in node.
+
+---v
+
+### Lecture Recap - Part 2
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-3-full.svg" />
+
+---
+
+## Rest of This Module! 😈
+
+#### Track: Main Lectures
+
+- Wasm Meta Protocol
+- Substrate Storage
+
+#### Track: Aux Lecture
+
+- Tx Pool
+- Interacting with Substrate
+- SCALE Codec
+
+#### Track: Activity
+
+- FRAMELess Runtime
+
+---
+
+## Homework 📚
+
+Highly suggested reading to ingest this lecture better:
+
+- [`polkadot-sdk-docs`](https://paritytech.github.io/polkadot-sdk/master/polkadot_sdk_docs/polkadot_sdk/index.html)
+
+---
+
+## Additional Resources! 😋
+
+> Check speaker notes (click "s" 😉)
+
+<img width="300px" rounded src="../../../assets/img/5-Substrate/thats_all_folks.png" />
+
+Notes:
+
+- Great documentation about all things substrate/blockchain from SMOLDOT: https://docs.rs/smoldot/latest/smoldot/
+
+- Read more about why we use Rust at Parity: https://www.parity.io/blog/why-rust
+
+- An interesting question on JVM/Wasm: https://stackoverflow.com/questions/58131892/why-the-jvm-cannot-be-used-in-place-of-webassembly
+
+- Rust safety: https://stanford-cs242.github.io/f18/lectures/05-1-rust-memory-safety.html
+- https://www.reddit.com/r/rust/comments/5y3cxb/how_many_security_exploits_would_rust_prevent/ <!-- markdown-link-check-disable-line -->
+
+- The substrate clients should still have some level of _determinism in their performance_. If
+  authority nodes have extremely varied performances, they could start finalizing different forks.
+
+- There have been attempts at writing FRAME alternatives, namely AssemblyScript. https://github.com/LimeChain/as-substrate-runtime
+
+- Think about the differences between a runtime and a smart contract.
+
+  - A runtime is in some sense a smart contract as well, but not a user-deployed one.
+  - https://en.wikipedia.org/wiki/Smart_contract
+  - https://www.futurelearn.com/info/courses/defi-exploring-decentralised-finance-with-blockchain-technologies/0/steps/251885#:~:text=to%20the%201990s.-,Writing%20in%201994%2C%20the%20computer%20scientist%20Nick%20Szabo%20defined%20a,of%20artificial%20intelligence%20is%20implied.
+
+- Substrate Primitives (`sp-*`), Frame (`frame-*`) and the pallets (`pallets-*`), binaries (`/bin`)
+  and all other utilities are licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html).
+
+Substrate Client (`/client/*` / `sc-*`) is licensed under [GPL v3.0](https://www.gnu.org/licenses/gpl-3.0.html) with a [classpath linking exception](https://www.gnu.org/software/classpath/license.html).
+
+- Apache2 allows teams full freedom over what and how they release, and giving licensing clarity to
+  commercial teams.
+
+- GPL3 ensures any deeper improvements made to Substrate's core logic (e.g. Substrate's internal
+  consensus, crypto or database code) to be contributed back so everyone can benefit.
+
+- Currently, the Wasm binary spec v1 is used, read more about the new version here: https://webassembly.github.io/spec/core/binary/index.html
+
+### Post Lecture Feedback
+
+- a takeaway after each section, more clear path (shawn).
+
+---
+
+## Appendix
+
+Content that is not covered, but is relevant.
+
+---
+
+### More Diagrams of Substrate and Polkadot
+
+Notes:
+
+I made these figures recently to explain the relationship between Substrate, Cumulus and Polkadot.
+They use the most generic term for client and runtime, namely "Host" and "STF" respectively.
+
+---v
+
+Substrate
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-1-substrate-new-1.svg" />
+
+---v
+
+Polkadot
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-1-substrate-new-2.svg" />
+---v
+
+A Parachain
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-1-substrate-new-3.svg" />
+
+---
+
+## Appendix: What is Wasm Anyways?
+
+> WebAssembly (abbreviated Wasm) is a _binary instruction format_ for a _stack-based virtual
+> machine_. Wasm is designed as a _portable compilation_ target for programming languages, enabling
+> deployment on the web for client and server applications.
+
+---v
+
+### What is Wasm Anyways?
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-1-wasm-langs.svg" />
+
+---v
+
+### What is Wasm Anyways?
+
+<pba-cols>
+<pba-col>
+
+- Wasm ❤️ Web
+- Streaming and rapid compilation.
+- Designed with the concept of host in mind.
+  Sandboxed, permissioned sys-calls.
+
+> Anyone remember "Java Applets"?
+
+</pba-col>
+<pba-col>
+
+<img style="height: 700px;" src="../../../assets/img/5-Substrate/dev-4-1-wasm.svg" />
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+People actually tried sticking things like JVM into the browser (_Java Applets_), but it didn't work.
+
+---v
+
+### How to Write a Wasm Runtime?
+
+- Any language that can compile to Wasm and exposes a fixed set of functions, to be used by the client.
+- ... But, of course, Substrate comes with a framework to make this developer-friendly, **FRAME™️**.
+
+---
+
+## State of Light Client/Nodes
+
+- Node that follows headers, therefore knows state roots and can ask for state-proofs to do more.
+
+Note:
+
+Establish that it is merely an alternative node implementation.
+
+---v
+
+### State of Light Clients
+
+<img src="../../../assets/img/5-Substrate/dev-4-1-smoldot.svg" />
+
+Notes:
+
+What was a light client? follows only block headers, therefore knows state roots, and a few other
+pieces of information, others send it state proofs if it wishes to do more.
+
+SMOLDOT is not exactly a substrate client. It is mainly designed to work with Polkadot. But with
+minimal tweaks, you could make it work for more substrate based chains.
+
+This has to do with the fact that consensus and a few other bits of the client and runtime are not
+100% independent. For example, GRANDPA has a pallet on the runtime side, but is mostly in the
+client. Now, a client that is configured with GRANDPA can only work with runtimes that are also
+configured with GRANDPA.
+
+---v
+
+### State of Light Clients
+
+<img style="width: 800px;" src="../../../assets/img/5-Substrate/dev-4-1-smoldot-browser.svg" />
+
+Note:
+
+Similarly it is dead simple to embed smoldot in mobile etc.
+
+Separate lecture on this later.
+
+---v
+
+### Substrate and Smart Contracts
+
+> SMOLDOT is syncing a chain who's runtime is executing wasm contracts.
+
+Question: How many nested Wasm blobs are executing one another?
+
+---v
+
+### Substrate and Smart Contracts
+
+<pba-cols>
+<pba-col center>
+
+<img style="width: 600px;" src="https://media.tenor.com/Oc4nf8N08jIAAAAM/mind-blow-galaxy.gif" />
+
+</pba-col>
+<pba-col>
+
+- The browser is executing:
+- a Wasm blob (SMOLDOT in extension)
+- that executes a Wasm blob (runtime)
+- that executes a Wasm blob (contract)
+
+</pba-col>
+</pba-cols>
diff --git a/content/6-Protocol_On-Chain/Substrate/2-Wasm-Meta-Protocol-slides.md b/content/6-Protocol_On-Chain/Substrate/2-Wasm-Meta-Protocol-slides.md
new file mode 100644
index 00000000..facdd1c5
--- /dev/null
+++ b/content/6-Protocol_On-Chain/Substrate/2-Wasm-Meta-Protocol-slides.md
@@ -0,0 +1,1406 @@
+---
+title: Substrate Wasm meta-protocol
+description: A deeper dive into how the Wasm is meta-protocol functions in substrate.
+duration: 60 minutes
+---
+
+# Substrate Wasm Meta Protocol
+
+---
+
+# Part 1
+
+- This is a big lecture, so I divided it into two small parts, that's all 🫵🏻
+
+---
+
+## Meta Protocol
+
+- The Node / Runtime division is one of the most important design decisions in Substrate.
+  - &shy;<!-- .element: class="fragment" --> 👿 Bad: _One_ fixed opinion.
+  - &shy;<!-- .element: class="fragment" --> 😇 Good: _Countless_ other things to flexible.
+
+Notes:
+
+Recall that the boundary for this division is the **state transition**
+
+---
+
+## Substrate: a short recap
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-3-full-comm.svg" />
+
+---v
+
+### Substrate: a short recap
+
+- **Host Functions**: Means of a runtime communicating with its host environment, i.e. the Substrate node.
+
+---v
+
+### Substrate: a short recap
+
+- **Runtime API**: The well-defined functions that a Wasm substrate runtime is providing.
+
+Notes:
+
+Building a Wasm module's activity was building something akin to runtime-apis
+
+---v
+
+### Substrate: a short recap
+
+- **Database** is on the node side, storing an opaque key-value state per block.
+
+---v
+
+### Substrate: a short recap
+
+- Communication language of node/runtime is **SCALE**:
+
+<diagram class="mermaid">
+flowchart LR
+  B[Known Type eg. `u32`] --Encode--> V["Vec(u8)"]
+  V --Decode-->B
+</diagram>
+
+---
+
+## Learning with Examples
+
+and some pseudo-code
+
+Notes:
+
+During each example, we deduce what host functions and/or runtime APIs are needed.
+
+---
+
+## Example #1: State
+
+- The runtime wants to add 10 units to Kian's balance.
+
+---v
+
+### Example #1: State
+
+```rust [1-100|1-2|4,5|7,8|10,11|13,14|1-100]
+// the runtime decides what key stores kian's balance.
+key: Vec<u8> = b"kian_balance".to_vec();
+
+// the runtime reads the raw bytes form that key.
+let current_kian_balance_raw: Vec<u8> = host_functions::get(key);
+
+// and needs to know to which type it should be decoded, u128.
+let mut current_kian_balance: u128 = current_kian_balance_raw.decode();
+
+// actual logic.
+current_kian_balance += 10;
+
+// encode this again into an opaque byte-array.
+let new_balance_encoded: Vec<u8> = current_kian_balance.encode();
+
+// write the encoded bytes again.
+host_functions::set(key, new_balance_encoded);
+```
+
+---v
+
+### Example #1: State
+
+- 💡 The runtime needs host functions to read/write to state.
+
+```rust
+fn get(key: Vec<u8>) -> Vec<u8>;
+fn set(key: Vec<u8>, value: Vec<u8>);
+```
+
+Notes:
+
+ofc the IO to these functions is all opaque bytes, because the node does not know the state
+layout.
+
+---v
+
+### Example #1: State
+
+- could we have communicated with the node like this?
+
+```rust
+fn set_balance(who: AccountId, amount: u128)
+```
+
+Notes:
+
+This would imply that the node would have to know, indefinitely, the types needed for account id
+and balance. Also, it would have to know the final key for someone's balance.
+
+---v
+
+### Example #1: State
+
+- [Exceptions](https://paritytech.github.io/polkadot-sdk/master/sp_storage/well_known_keys/index.html):
+
+```rust
+/// The keys known to the node.
+mod well_known_keys {
+  const CODE: &[u8] = b":code";
+}
+```
+
+Notes:
+
+See https://paritytech.github.io/substrate/master/sp_storage/well_known_keys/index.html
+
+---v
+
+### Example #1: State
+
+<img style="width: 1000px;" src="../../../assets/img/5-Substrate/dev-4-1-state-opaque.svg" />
+
+---
+
+## Example #2: Block Import
+
+---v
+
+### Example #2: Block Import
+
+- Node's view of the state -> Opaque.
+- Node's view of the transactions? 🤔
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+Short answer is: anything that is part of the STF definition must be opaque to the node, and is
+upgradeable, but we will learn this later.
+
+Another way to think of it: Anything that we want to keep upgrade-able needs to be opaque.
+
+---v
+
+### Example #2: Block Import
+
+- Transactions format is by definition part of the state transition function as well -> Opaque
+
+Notes:
+
+What about header, and other fields in a typical block?
+
+as in, do we want to able to update our transactions format as well in a forkless manner?
+we want the runtime to be able to change its transactions format as well, in a forkless manner.
+
+The answer to the latter is more involved. The short answer is that these fields like header must be
+known and established between node and runtime. If you want to alter the header format, that's a
+hard fork.
+
+The concept of `digest` is a means through which additional data can be put in the header without
+breaking changes, but that is outside the scope of this lecture.
+
+Yet, as with other primitives, substrate allows you to readily change your header type when you are
+building your blockchain. This is achieved by a set of traits in `sp-runtime`. Notably, `trait Block` and `trait Header` in this crate define what it means to be a header and block, and as long
+as you fulfill that, you are good to go.
+
+Also, substrate provides one set of implementation for all of these types in
+https://paritytech.github.io/substrate/master/sp_runtime/generic/index.html
+
+---v
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-3-block-opaque.svg" />
+
+---v
+
+### Example #2: Block Import
+
+<pba-cols>
+
+<pba-col>
+
+```rust
+struct NodeBlock {
+  header: Header,
+  transactions: Vec<Vec<u8>>
+}
+```
+
+</pba-col>
+
+<pba-col>
+
+```rust
+struct RuntimeBlock {
+  header: Header,
+  transaction: Vec<KnownTransaction>
+}
+```
+
+</pba-col>
+
+</pba-cols>
+
+Notes:
+
+this slide is intentionally using the keyword transaction instead of extrinsic.
+
+---v
+
+### Example #2: Block Import
+
+```rust [1-100|1-2|4-6|8-9|1-100]
+// fetch the block from the outer world.
+let opaque_block: NodeBlock = import_queue::next_block();
+
+// initialize a wasm runtime.
+let code = database::get(well_known_keys::CODE);
+let runtime = wasm::Executor::new(code);
+
+// call into this runtime.
+runtime.execute_block(opaque_block);
+```
+
+---v
+
+### Example #2: Block Import
+
+- 💡 The node needs a runtime API to ask the runtime to execute the block.
+
+```rust
+fn execute_block(opaque_block: NodeBlock) -> Result<_, _> { .. }
+```
+
+Notes:
+
+`execute_block` is the most basic, fundamental runtime API that any substrate based runtime has to
+implement in order to be called a "blockchain runtime".
+
+---
+
+### Example #2: Block Import: Something Missing
+
+```rust
+// 🤔
+let code = database::get(well_known_keys::CODE);
+
+// 🤔
+runtime.execute_block(opaque_block);
+```
+
+<img style="width: 600px" src="../../../assets/img/5-Substrate/dev-4-1-state-database.svg" />
+
+Notes:
+
+- From which block's state do we fetch the code??
+- This probably calls into `host_functions::{get/set}` internally. What do we return
+
+---v
+
+### Example #2: Block Import
+
+```rust [1-100|1-2|4-6|8-10|12-15|17-100]
+// fetch the block from the outer world.
+let block: NodeBlock = import_queue::next_block();
+
+// get the parent block's state.
+let parent = block.header.parent_hash;
+let mut state = database::state_at(parent);
+
+// initialize a wasm runtime FROM THE PARENT `state`!
+let code = state::get(well_known_keys::CODE);
+let runtime = wasm::Executor::new(code);
+
+// call into this runtime, updates `state`.
+state.execute(|| {
+  runtime.execute_block(block);
+});
+
+// create the state of the next_block
+database::store_state(block.header.hash, state)
+```
+
+Notes:
+
+- Question: why is `state` defined as `mut`?
+- within these snippets, more or less, everything inside `state.execute` is executed within Wasm.
+
+---v
+
+### Example #2: Block Import
+
+- _A state key is only meaningful at a given block_
+- &shy;<!-- .element: class="fragment" --> _A `:code` / Runtime is only meaningful at at given block_
+- &shy;<!-- .element: class="fragment" --> _A runtime (API) is only meaningful when executed at a give block_
+
+Notes:
+
+- The same way that Alice's balance value is only meaningful when read at a given block.
+
+- Based on that:
+
+  - The correct runtime code is loaded.
+  - The correct state (and other host functions) is provided.
+
+- Similarly, almost all RPC operations that interact with the runtime have an `Option<Hash>`
+  argument. This specifies "at which block to load the runtime and state from".
+
+---v
+
+### Example #2: Block Import
+
+```rust
+state.execute(|| {
+  // What is the most important check that a runtime must do
+  // inside `execute_block` 🤔?
+  runtime.execute_block(block);
+});
+```
+
+Note: make sure roots in the header match!
+
+---v
+
+### Example #2: Block Import: Recap
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-3-import.svg" />
+
+---
+
+## Example #3: Block Authoring
+
+---v
+
+### Example #3: Block Authoring
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-3-author-pool.svg" />
+
+<div class="fragment fade-out" style="width: 220px; height: 120px; position: fixed; left: 450px; bottom: 180px; background: #140526"></div>
+<div class="fragment fade-out" style="width: 220px; height: 90px; position: fixed; left: 450px; bottom: 180px; background: #140526"></div>
+<div class="fragment fade-out" style="width: 220px; height: 60px; position: fixed; left: 450px; bottom: 180px; background: #140526"></div>
+<div class="fragment fade-out" style="width: 220px; height: 30px; position: fixed; left: 450px; bottom: 180px; background: #140526"></div>
+
+Notes:
+
+The point being, eventually the pool builds a list of "ready transactions".
+
+---v
+
+### Example #3: Block Authoring
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-3-author-builder.svg" />
+
+<div id="pool-1" class="fragment" style="
+    width: 300px; height: 30px; position: fixed; left: 450px; top: 610px;
+    background: #140526"></div>
+
+<div id="block-1" class="fragment fade-out" style="
+    width: 300px; height: 90px; position: fixed; left: 320px; bottom: 400px;
+    background: #BF9001"></div>
+
+<div id="pool-2" class="fragment" style="
+    width: 300px; height: 30px; position: fixed; left: 450px; top: 640px;
+    background: #140526"></div>
+
+<div id="block-2" class="fragment fade-out" style="
+    width: 300px; height: 60px; position: fixed; left: 320px; bottom: 400px;
+    background: #BF9001"></div>
+
+<div id="pool-3" class="fragment" style="
+    width: 300px; height: 30px; position: fixed; left: 450px; top: 670px;
+    background: #140526"></div>
+
+<div id="block-3" class="fragment fade-out" style="
+    width: 300px; height: 30px; position: fixed; left: 320px; bottom: 400px;
+    background: #BF9001"></div>
+
+<!-- This is the box that will unhide the state root. -->
+<div class="fragment fade-out" style="
+  width: 240px; height: 30px; position: fixed; left: 320px; top: 350px;
+  background: #BF9001;"></div>
+
+---v
+
+### Example #3: Block Authoring
+
+```rust [1-100|1-2|4-5|7-9|11-12|14-21|23-100]
+// get the best-block, based on whatever consensus rule we have.
+let (best_number, best_hash) = consensus::best_block();
+
+// get the latest state.
+let mut state = database::state_at(best_hash);
+
+// initialize a wasm runtime.
+let code = state::get(well_known_keys::CODE);
+let runtime = wasm::Executor::new(code);
+
+// get an empty node block.
+let mut block: NodeBlock = Default::default();
+
+// repeatedly apply transactions.
+while let Some(next_ext) = transaction_pool_iter::next() {
+  state.execute(|| {
+    if runtime.apply_extrinsic(next_ext).is_ok() {
+      block.extrinsics.push(next_ext);
+    }
+  });
+}
+
+// set the new state root.
+block.header.state_root = state.root();
+```
+
+Notes:
+
+- What is the type of `next_transaction`? `Vec<u8>`
+- Do we actually loop forever until the tx-pool is empty? probably not!
+
+---v
+
+### Example #3: Block Authoring
+
+- Substrate based runtimes are allowed to perform some operations at the beginning and end of each
+  block.
+- ✋🏻 And recall that a smart contract could not do this.
+
+---v
+
+### Example #3: Block Authoring
+
+```rust [14-15,25-100]
+// get the best-block, based on whatever consensus rule we have.
+let (best_number, best_hash) = consensus::best_block();
+
+// get the latest state.
+let mut state = database::state_at(best_hash);
+
+// initialize a wasm runtime.
+let code = state::get(well_known_keys::CODE);
+let runtime = wasm::Executor::new(code);
+
+// get an empty node block.
+let mut block: NodeBlock = Default::default();
+
+// tell this runtime that you wish to start a new block, and pass in a raw header.
+runtime.initialize_block(&block.header);
+
+// repeatedly apply transactions.
+while let Some(next_ext) = transaction_pool_iter::next() {
+  state.execute(|| {
+    if runtime.apply_extrinsic(next_ext).is_ok() {
+      block.extrinsics.push(next_ext);
+    }
+  });
+}
+
+// finalize and set the final header.
+block.header = runtime.finalize_block();
+```
+
+Notes:
+
+The header interactions here are a substrate implementation detail, not a golden rule. I guess it
+could have been done otherwise. I am mainly covering it because it is relevant to the assignment.
+
+Good question to ask: what about inherents? see appendix slides.
+
+---v
+
+### Example #3: Block Authoring
+
+```rust
+fn initialize_block(raw_header: Header) { ... }
+fn apply_extrinsic(extrinsic: Vec<u8>) { ... }
+fn finalize_block(..) -> Header { ... }
+```
+
+---
+
+## BUT WAIT A MINUTE 😱
+
+- if the `code` changes, all the following can also change:
+
+  - <!-- .element: class="fragment" --> What state key is Kian's balance.
+  - <!-- .element: class="fragment" --> What extrinsic format is valid.
+
+- <!-- .element: class="fragment" --> How on earth is an application (i.e. a wallet) is supposed to survive?
+
+---v
+
+### BUT WAIT A MINUTE 😱
+
+- Metadata 🎉
+
+```rust
+fn metadata() -> Vec<u8> { ... }
+```
+
+Notes:
+
+Notice the opaque return type.
+
+In order the address the mentioned issue, metadata must be a runtime API.
+
+<hr>
+
+- Metadata contains all the basic information to know about all storage items, all extrinsics, and so
+  on. It will also help a node/app decode them into the right type.
+- Substrate itself doesn't impose what the metadata should be. It is `Vec<u8>`.
+- FRAME based runtime expose a certain format, which is extensively adopted in the ecosystem.
+
+---v
+
+### BUT WAIT A MINUTE 😱
+
+- Recall the fact that "runtime is only meaningful at a certain block".
+
+<div class="fragment">
+
+- Two different runtimes at block `N` and `N+1` return different metadata ✅.
+
+</div>
+
+Notes:
+
+By Applications I really mean anyone/anything. Substrate node doesn't really use metadata
+because it is dynamically typed, but if needed, it could.
+
+---
+
+## Radical Upgradeability
+
+Comes at the cost of radical opaque/dynamic typing.
+
+Notes:
+
+I wish you could have both, but not so easy.
+
+Some personal rant: radical upgrade-ability is the biggest advantage, and arguably one of the main
+develop-ability problems of the substrate ecosystem. Writing nodes, such as block explorers,
+scanners, and even exchange integration are orders of magnitude harder than a blockchain that has a
+fixed format and only changes every 18 months at most. That being said, this is a battle that is to
+me obvious: we simply HAVE to win. When ethereum first introduced smart contracts, everyone
+probably had the same class of issues. This is the same matter, on a a different level.
+
+also, as noted in an earlier slide, once you make it work for one chain, it works for many chains.
+
+---
+
+## Oblivious Node 🙈🙉
+
+- The underlying reason why the node is "**kept in the dark**" is so that it wouldn't need to care
+  about the runtime upgrading from one block to the other.
+
+---v
+
+### Oblivious Node 🙈🙉
+
+$$STF = F(blockBody_{N+1}, state_{N}) > state_{N+1}$$
+
+_Anything that is part of the STF is opaque to the node, but it can change forklessly!_
+
+- <!-- .element: class="fragment" --> The `F` itself (your Wasm blob)? It can change!
+- <!-- .element: class="fragment" --> Extrinsic format? It can change!
+- <!-- .element: class="fragment" --> State format? It can change!
+
+Notes:
+
+In essence, all components of the STF must be opaque to the node. `Vec<u8>`.
+Metadata is there to assist where needed.
+This is why forkless upgrades are possible in substrate.
+
+---v
+
+### Oblivious Node 🙈🙉
+
+- What about new host functions?
+- <!-- .element: class="fragment" --> What about a new header field*?
+- <!-- .element: class="fragment" --> What about a new Hashing primitive?
+- <!-- .element: class="fragment" --> A new consensus/networking engine?
+
+🥺 No longer forkless.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+But, recall that substrate's extensibility and generic-ness clause applies here.
+
+For some, like header, some hacks exist, like the `digest` field.
+
+Changing these is hard in a forkless manner. If you want to just change them at genesis and launch a new chain, they are all VERY easy to change.
+
+---
+
+## Substrate: The Full Picture
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-3-full.svg" />
+
+Notes:
+
+time to ask any missing questions.
+
+---
+
+## Activity: Finding APIs and Host Functions
+
+---v
+
+### Finding APIs and Host Functions
+
+- look for `impl_runtime_apis! {...}` and `decl_runtime_apis! {...}` macro calls.
+  - Try and find the corresponding the node code calling a given api as well.
+- Look for `#[runtime_interface]` macro, and try and find usage of the host functions!
+  - Look for `sp_io::storage`
+- You have 15 minutes!
+
+---v
+
+### Defining a Runtime API
+
+```rust [1-7|9-15|17-100|1-100]
+// somewhere in common between node/runtime => substrate-primitive.
+decl_runtime_apis! {
+	pub trait Core {
+		fn version() -> RuntimeVersion;
+		fn execute_block(block: Block) -> bool;
+	}
+}
+
+// somewhere in the runtime code.
+impl_runtime_apis! {
+  impl sp_api::Core<Block> for Runtime {
+    fn version() -> RuntimeVersion { /* stuff */ }
+    fn execute_block(block: Block) -> bool { /* stuff */ }
+  }
+}
+
+// somewhere in the node code..
+let block_hash = "0xffff...";
+let block = Block { ... };
+let outcome: Vec<u8> = api.execute_block(block, block_hash).unwrap();
+```
+
+Notes:
+
+- All runtime APIs are generic over a `<Block>` by default.
+- All runtime APIs are executed on top of a **specific block**. This is the implicit _at_ parameter.
+- Going over the API, everything is SCALE encoded both ways, but abstractions like
+  `impl_runtime_apis` hide that away from you.
+
+---v
+
+### Defining a Host Function
+
+```rust
+// somewhere in substrate primitives, almost always `sp_io`.
+#[runtime_interface]
+pub trait Storage {
+  fn get(&self, key: &[u8]) -> Option<Vec<u8>> {...}
+  fn get(&self, key: &[u8], value: &[u8]) -> Option<Vec<u8>> {...}
+  fn root() -> Vec<u8> {...}
+}
+
+#[runtime_interface]
+pub trait Hashing {
+	fn blake2_128(data: &[u8]) -> [u8; 16] {
+		sp_core::hashing::blake2_128(data)
+	}
+}
+
+// somewhere in substrate runtime
+let hashed_value = sp_io::storage::get(b"key")
+  .and_then(sp_io::hashing::blake2_128)
+  .unwrap();
+```
+
+---v
+
+### Finding APIs and Host Functions
+
+Activity Outcomes:
+
+- `Core` is the essence of import.
+- `TaggedTransactionQueue` and `BlockBuilder` for validators.
+- `header: Header` being passed around.
+
+Notes:
+
+a question that arise here is that why don't have multiple runtimes, where one is only for import,
+one only for authoring, and such? the reality is that while these have different names, the
+underlying code is like 95% the same.
+
+---v
+
+### Finding APIs and Host Functions
+
+<pba-cols>
+<pba-col>
+
+#### Block Import
+
+```rust
+runtime.execute_block(block);
+```
+
+</pba-col>
+<pba-col>
+
+#### Block Authoring
+
+```rust
+runtime.initialize_block(raw_header);
+loop {
+  runtime.apply_extrinsic(ext);
+}
+let final_header = runtime.finalize_block();
+```
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+to be frank, these are still a simplification. Inherent for example are not really represented here.
+
+---v
+
+### Finding APIs and Host Functions
+
+- Most important host functions
+
+```
+sp_io::storage::get(..);
+sp_io::storage::set(..);
+sp_io::storage::root();
+```
+
+---
+
+## Lecture Recap (Part 1)
+
+- Revise "**Runtime API**" and "**Host Function**" concepts.
+- Deep look at block import and authoring.
+- Oblivious node. STF has to be opaque, but can be forklessly upgraded.
+- Metadata to the rescue!
+
+---
+
+# Part 2
+
+---
+
+## Detour: Extrinsic
+
+- Previous slides used the term "transactions" in a simplified way. Let's correct it.
+
+---v
+
+### Detour: Extrinsic
+
+<diagram class="mermaid" center>
+  %%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
+  flowchart TD
+    E(Extrinsic) ---> I(Inherent);
+    E --> T(Transaction)
+    T --> ST("Signed (aka. Transaction)")
+    T --> UT(Unsigned)
+</diagram>
+
+---v
+
+### Detour: Extrinsic
+
+- An Extrinsic is data that come from outside of the runtime.
+- &shy;<!-- .element: class="fragment" -->Inherents are data that is put into the block by the block author, directly.
+- &shy;<!-- .element: class="fragment" -->Yes, transactions are **a type of extrinsic**, but not all extrinsics are transactions.
+- &shy;<!-- .element: class="fragment" -->So, why is it called _Transaction Pool_ and not _Extrinsic Pool_?
+
+Notes:
+
+extrinsics are just blobs of data which can be included in a block. inherents are types of extrinsic
+which are crafted by the block builder itself in the production process. they are unsigned because
+the assertion is that they are "inherently true" by virtue of getting past all validators.
+
+notionally the origin can be said to be a plurality of validators. take for example the timestamp
+set inherent. if the data were sufficiently incorrect (i.e. the wrong time), then the block would
+not be accepted by enough validators and would not become canonicalised. so the "nobody" origin is
+actually the tacit approval of the validators.
+
+transactions are generally statements of opinion which are valuable to the chain to have included
+(because fees are paid or some other good is done). the transaction pool filters out which of these
+are indeed valuable and nodes share them.
+
+---v
+
+### Detour: Extrinsic
+
+More change is coming; advance topic; not needed, but FYI:
+
+https://github.com/paritytech/polkadot-sdk/issues/2415
+
+---
+
+## Considerations: Speed
+
+- (new) Wasmtime is near-native 🏎️.
+- (old) `wasmi` is significantly slower 🐢.
+
+Notes:
+
+slower wasmi was one of the reasons to have native execution.
+there are talks of exploring Risk-v ISA instead of wasm nowadays.
+
+https://github.com/paritytech/substrate/issues/13640
+
+---v
+
+### Considerations: Speed
+
+<pba-cols>
+<pba-col center>
+
+- Host is generally **faster** and **more capable**, but it has a one-time cost of getting there,
+  and copying the data.
+- &shy;<!-- .element: class="fragment" -->🤔 Hashing, Crypto?
+- &shy;<!-- .element: class="fragment" -->🤔 Storage?
+
+</pba-col>
+<pba-col center>
+
+<img style="width: 700px;" src="../../../assets/img/5-Substrate/dev-4-3-io.svg" />
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Hashing and crypto is done as host function for performance
+
+Storage because of the runtime not being capable.
+
+- Going over the runtime boundary is analogous to your CPU needing to go to memory.
+
+On the other hand things as `next_storage` are high cost (generally iteration on state from runtime
+is expensive). This design is related to the memory location, there is alternative but this is
+simple (simple as good design).
+
+- Question: we got host function for running computation intensive code in native, but when simd for
+  wasm would be added, then will host function for a hashing be still useful:
+  A: wait and see, but is possible that simd optimization of the hash function in wasm is way faster.
+
+Again using a host function for speed up needs to be reasoned, cost of transmitting parameter in
+wasm can be bigger than the actual hashing cost.
+
+---
+
+### Runtime Version vs. Node Version
+
+```rust
+#[sp_version::runtime_version]
+pub const VERSION: RuntimeVersion = RuntimeVersion {
+	spec_name: create_runtime_str!("node"),
+	spec_version: 268,
+	impl_version: 0,
+  ..
+};
+```
+
+---v
+
+### Speaking of Versions..
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-1-substrate-meta-version.svg" />
+
+---v
+
+### Speaking of Versions..
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-3-telemetry.png" />
+
+---v
+
+### Speaking of Versions..
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-3-PJS.png" />
+
+---v
+
+### Speaking of Versions..
+
+- What happens when Parity release a new `polkadot` node binary?
+- What happens when the Polkadot fellowship wants to update the runtime?
+
+---
+
+## Considerations: Panic
+
+- What if any of the runtime calls, like `execute_block` or `apply_extrinsic` panics 😱?
+
+---v
+
+### Considerations: Panic
+
+- Panic is a (free) form of wasting a validator's time.
+- Practically Wasm instance killed; State changes reverted.
+  - Any fee payment also reverted.
+
+Notes:
+
+While you might think the state revert is the good thing here, it is the main problem, and the main
+reason you should not let a code-path that is accessible by arbitrary users to panic. Because, any
+fees paid for the wasted execution of that runtime API call is also reverted.
+
+In other words, a panic in the runtime typically allows everyone's time to be wasted, for free,
+indefinitely. In other words, a DOS vector.
+
+> A panic in `initialize_block` and `finalize_block` have even more catastrophic effects, which will
+> be discussed further in the FRAME section.
+
+workshop idea: make a panicing runtime, and DoS it out.
+workshop idea for FRAME: find all instances where the runtime actually correctly panics (wrong timestamp, disabled validator)
+
+---v
+
+### Considerations: Panic
+
+- Panic in a user-callable code path?
+- 🤬 annoy/DOS your poor validators
+- Panic on "automatic" part of your blockchain like "initialize_block"?
+- 😱 Stuck forever
+
+---v
+
+### Considerations: Panic
+
+- This is why, crucially, transaction pool checks always include, despite being costly, at least
+  some sort of nonce and payment checks to make sure you can pay the transaction.
+
+---v
+
+### Considerations: Panic
+
+<diagram class="mermaid">
+graph LR
+    TransactionPool --"😈"--> Authoring --"😇"--> Import
+</diagram>
+
+Notes:
+
+Consider two cases:
+
+1. A transaction that panic-ed
+2. A transaction that cannot pay for fees, but the pool somehow validated it by mistake.
+
+when you author a block, you hope that the tx-pool has pre-validated things for you, but you cannot
+be sure. The pool cannot pre-execute stuff. If it fails, then you have to continue. For example, the
+pool might validate a nonce that becomes invalid. Or a fee payment. In that case, the block author
+wasted time, but everyone else will not.
+
+To the contrary, once you have authored a block, the importers expect you to only have put VALID
+transactions into it, those that will not fail to be **included**.
+
+Note that a transaction might still fail (failed transfer), but so long as it can pay for its fee,
+it **is included** fine.
+
+See the documentation of `ApplyExtrinsicResult` in Substrate for more info about this.
+
+---
+
+## Consideration: Altering Host Function
+
+- A runtime upgrade now requires a new `sp_io::new_stuff::foo()`. Can we do a normal runtime upgrade?
+
+<div>
+
+- Nodes need to upgrade first. No more fully forkless upgrade 😢
+
+</div>
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Consideration: Breaking a Host Function
+
+- Here's another example, from substrate:
+
+```rust
+// old
+fn root(&mut self) -> Vec<u8> { .. }
+
+// new
+fn root(&mut self, version: StateVersion) -> Vec<u8> { .. }
+```
+
+<div>
+
+- For some period of time, the node needs to support both..🤔
+
+</div>
+
+<!-- .element: class="fragment" -->
+
+<div>
+
+- When can the old host function be deleted?
+
+</div>
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Host Functions..
+
+#### NEED TO BE KEPT FOREVER 😈
+
+<!-- .element: class="fragment" -->
+
+- Optional activity: Go to the substrate repo, and find PRs that have altered host functions, and see the PR discussion. There are a few labels that help you find such PRs 😉.
+
+<!-- .element: class="fragment" -->
+
+---
+
+## Activity: Inspecting Wasm Code
+
+---v
+
+- `wasm2wat polkadot_runtime.wasm > dump | rg import`
+
+```
+(import "env" "memory" (memory (;0;) 22))
+(import "env" "ext_crypto_ed25519_generate_version_1" (func $ext_crypto_ed25519_generate_version_1 (type 17)))
+(import "env" "ext_crypto_ed25519_verify_version_1" (func $ext_crypto_ed25519_verify_version_1 (type 18)))
+(import "env" "ext_crypto_finish_batch_verify_version_1" (func $ext_crypto_finish_batch_verify_version_1 (type 11)))
+(import "env" "ext_crypto_secp256k1_ecdsa_recover_version_2" (func $ext_crypto_secp256k1_ecdsa_recover_version_2 (type 19)))
+(import "env" "ext_crypto_secp256k1_ecdsa_recover_compressed_version_2" (func $ext_crypto_secp256k1_ecdsa_recover_compressed_version_2 (type 19)))
+(import "env" "ext_crypto_sr25519_generate_version_1" (func $ext_crypto_sr25519_generate_version_1 (type 17)))
+(import "env" "ext_crypto_sr25519_public_keys_version_1" (func $ext_crypto_sr25519_public_keys_version_1 (type 5)))
+(import "env" "ext_crypto_sr25519_sign_version_1" (func $ext_crypto_sr25519_sign_version_1 (type 20)))
+(import "env" "ext_crypto_sr25519_verify_version_2" (func $ext_crypto_sr25519_verify_version_2 (type 18)))
+(import "env" "ext_crypto_start_batch_verify_version_1" (func $ext_crypto_start_batch_verify_version_1 (type 14)))
+(import "env" "ext_misc_print_hex_version_1" (func $ext_misc_print_hex_version_1 (type 16)))
+(import "env" "ext_misc_print_num_version_1" (func $ext_misc_print_num_version_1 (type 16)))
+(import "env" "ext_misc_print_utf8_version_1" (func $ext_misc_print_utf8_version_1 (type 16)))
+(import "env" "ext_misc_runtime_version_version_1" (func $ext_misc_runtime_version_version_1 (type 21)))
+(import "env" "ext_hashing_blake2_128_version_1" (func $ext_hashing_blake2_128_version_1 (type 22)))
+(import "env" "ext_hashing_blake2_256_version_1" (func $ext_hashing_blake2_256_version_1 (type 22)))
+(import "env" "ext_hashing_keccak_256_version_1" (func $ext_hashing_keccak_256_version_1 (type 22)))
+(import "env" "ext_hashing_twox_128_version_1" (func $ext_hashing_twox_128_version_1 (type 22)))
+(import "env" "ext_hashing_twox_64_version_1" (func $ext_hashing_twox_64_version_1 (type 22)))
+(import "env" "ext_storage_append_version_1" (func $ext_storage_append_version_1 (type 23)))
+(import "env" "ext_storage_clear_version_1" (func $ext_storage_clear_version_1 (type 16)))
+(import "env" "ext_storage_clear_prefix_version_2" (func $ext_storage_clear_prefix_version_2 (type 24)))
+(import "env" "ext_storage_commit_transaction_version_1" (func $ext_storage_commit_transaction_version_1 (type 14)))
+(import "env" "ext_storage_exists_version_1" (func $ext_storage_exists_version_1 (type 22)))
+(import "env" "ext_storage_get_version_1" (func $ext_storage_get_version_1 (type 21)))
+(import "env" "ext_storage_next_key_version_1" (func $ext_storage_next_key_version_1 (type 21)))
+(import "env" "ext_storage_read_version_1" (func $ext_storage_read_version_1 (type 25)))
+(import "env" "ext_storage_rollback_transaction_version_1" (func $ext_storage_rollback_transaction_version_1 (type 14)))
+(import "env" "ext_storage_root_version_2" (func $ext_storage_root_version_2 (type 5)))
+(import "env" "ext_storage_set_version_1" (func $ext_storage_set_version_1 (type 23)))
+(import "env" "ext_storage_start_transaction_version_1" (func $ext_storage_start_transaction_version_1 (type 14)))
+(import "env" "ext_trie_blake2_256_ordered_root_version_2" (func $ext_trie_blake2_256_ordered_root_version_2 (type 26)))
+(import "env" "ext_offchain_is_validator_version_1" (func $ext_offchain_is_validator_version_1 (type 11)))
+(import "env" "ext_offchain_local_storage_clear_version_1" (func $ext_offchain_local_storage_clear_version_1 (type 27)))
+(import "env" "ext_offchain_local_storage_compare_and_set_version_1" (func $ext_offchain_local_storage_compare_and_set_version_1 (type 28)))
+(import "env" "ext_offchain_local_storage_get_version_1" (func $ext_offchain_local_storage_get_version_1 (type 29)))
+(import "env" "ext_offchain_local_storage_set_version_1" (func $ext_offchain_local_storage_set_version_1 (type 30)))
+(import "env" "ext_offchain_network_state_version_1" (func $ext_offchain_network_state_version_1 (type 15)))
+(import "env" "ext_offchain_random_seed_version_1" (func $ext_offchain_random_seed_version_1 (type 11)))
+(import "env" "ext_offchain_submit_transaction_version_1" (func $ext_offchain_submit_transaction_version_1 (type 21)))
+(import "env" "ext_offchain_timestamp_version_1" (func $ext_offchain_timestamp_version_1 (type 15)))
+(import "env" "ext_allocator_free_version_1" (func $ext_allocator_free_version_1 (type 1)))
+(import "env" "ext_allocator_malloc_version_1" (func $ext_allocator_malloc_version_1 (type 0)))
+(import "env" "ext_offchain_index_set_version_1" (func $ext_offchain_index_set_version_1 (type 23)))
+(import "env" "ext_default_child_storage_clear_version_1" (func $ext_default_child_storage_clear_version_1 (type 23)))
+(import "env" "ext_default_child_storage_get_version_1" (func $ext_default_child_storage_get_version_1 (type 24)))
+(import "env" "ext_default_child_storage_next_key_version_1" (func $ext_default_child_storage_next_key_version_1 (type 24)))
+(import "env" "ext_default_child_storage_set_version_1" (func $ext_default_child_storage_set_version_1 (type 31)))
+(import "env" "ext_logging_log_version_1" (func $ext_logging_log_version_1 (type 30)))
+(import "env" "ext_logging_max_level_version_1" (func $ext_logging_max_level_version_1 (type 11)))
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+- `wasm2wat polkadot_runtime.wasm > dump | rg export`
+
+```
+(export "__indirect_function_table" (table 0))
+(export "Core_version" (func $Core_version))
+(export "Core_execute_block" (func $Core_execute_block))
+(export "Core_initialize_block" (func $Core_initialize_block))
+(export "Metadata_metadata" (func $Metadata_metadata))
+(export "BlockBuilder_apply_extrinsic" (func $BlockBuilder_apply_extrinsic))
+(export "BlockBuilder_finalize_block" (func $BlockBuilder_finalize_block))
+(export "BlockBuilder_inherent_extrinsics" (func $BlockBuilder_inherent_extrinsics))
+(export "BlockBuilder_check_inherents" (func $BlockBuilder_check_inherents))
+(export "NominationPoolsApi_pending_rewards" (func $NominationPoolsApi_pending_rewards))
+(export "NominationPoolsApi_points_to_balance" (func $NominationPoolsApi_points_to_balance))
+(export "NominationPoolsApi_balance_to_points" (func $NominationPoolsApi_balance_to_points))
+(export "StakingApi_nominations_quota" (func $StakingApi_nominations_quota))
+(export "TaggedTransactionQueue_validate_transaction" (func $TaggedTransactionQueue_validate_transaction))
+(export "OffchainWorkerApi_offchain_worker" (func $OffchainWorkerApi_offchain_worker))
+(export "ParachainHost_validators" (func $ParachainHost_validators))
+(export "ParachainHost_validator_groups" (func $ParachainHost_validator_groups))
+(export "ParachainHost_availability_cores" (func $ParachainHost_availability_cores))
+(export "ParachainHost_persisted_validation_data" (func $ParachainHost_persisted_validation_data))
+(export "ParachainHost_assumed_validation_data" (func $ParachainHost_assumed_validation_data))
+(export "ParachainHost_check_validation_outputs" (func $ParachainHost_check_validation_outputs))
+(export "ParachainHost_session_index_for_child" (func $ParachainHost_session_index_for_child))
+(export "ParachainHost_validation_code" (func $ParachainHost_validation_code))
+(export "ParachainHost_candidate_pending_availability" (func $ParachainHost_candidate_pending_availability))
+(export "ParachainHost_candidate_events" (func $ParachainHost_candidate_events))
+(export "ParachainHost_session_info" (func $ParachainHost_session_info))
+(export "ParachainHost_dmq_contents" (func $ParachainHost_dmq_contents))
+(export "ParachainHost_inbound_hrmp_channels_contents" (func $ParachainHost_inbound_hrmp_channels_contents))
+(export "ParachainHost_validation_code_by_hash" (func $ParachainHost_validation_code_by_hash))
+(export "ParachainHost_on_chain_votes" (func $ParachainHost_on_chain_votes))
+(export "ParachainHost_submit_pvf_check_statement" (func $ParachainHost_submit_pvf_check_statement))
+(export "ParachainHost_pvfs_require_precheck" (func $ParachainHost_pvfs_require_precheck))
+(export "ParachainHost_validation_code_hash" (func $ParachainHost_validation_code_hash))
+(export "BeefyApi_beefy_genesis" (func $BeefyApi_beefy_genesis))
+(export "BeefyApi_validator_set" (func $BeefyApi_validator_set))
+(export "BeefyApi_submit_report_equivocation_unsigned_extrinsic" (func $BeefyApi_submit_report_equivocation_unsigned_extrinsic))
+(export "BeefyApi_generate_key_ownership_proof" (func $BeefyApi_generate_key_ownership_proof))
+(export "MmrApi_mmr_root" (func $MmrApi_mmr_root))
+(export "MmrApi_mmr_leaf_count" (func $MmrApi_mmr_leaf_count))
+(export "MmrApi_generate_proof" (func $MmrApi_generate_proof))
+(export "MmrApi_verify_proof" (func $MmrApi_verify_proof))
+(export "MmrApi_verify_proof_stateless" (func $MmrApi_verify_proof_stateless))
+(export "GrandpaApi_grandpa_authorities" (func $GrandpaApi_grandpa_authorities))
+(export "GrandpaApi_current_set_id" (func $GrandpaApi_current_set_id))
+(export "GrandpaApi_submit_report_equivocation_unsigned_extrinsic" (func $GrandpaApi_submit_report_equivocation_unsigned_extrinsic))
+(export "GrandpaApi_generate_key_ownership_proof" (func $GrandpaApi_generate_key_ownership_proof))
+(export "BabeApi_configuration" (func $BabeApi_configuration))
+(export "BabeApi_current_epoch_start" (func $BabeApi_current_epoch_start))
+(export "BabeApi_current_epoch" (func $BabeApi_current_epoch))
+(export "BabeApi_next_epoch" (func $BabeApi_next_epoch))
+(export "BabeApi_generate_key_ownership_proof" (func $BabeApi_generate_key_ownership_proof))
+(export "BabeApi_submit_report_equivocation_unsigned_extrinsic" (func $BabeApi_submit_report_equivocation_unsigned_extrinsic))
+(export "AuthorityDiscoveryApi_authorities" (func $AuthorityDiscoveryApi_authorities))
+(export "SessionKeys_generate_session_keys" (func $SessionKeys_generate_session_keys))
+(export "SessionKeys_decode_session_keys" (func $SessionKeys_decode_session_keys))
+(export "AccountNonceApi_account_nonce" (func $AccountNonceApi_account_nonce))
+(export "TransactionPaymentApi_query_info" (func $TransactionPaymentApi_query_info))
+(export "TransactionPaymentApi_query_fee_details" (func $TransactionPaymentApi_query_fee_details))
+(export "TransactionPaymentApi_query_weight_to_fee" (func $TransactionPaymentApi_query_weight_to_fee))
+(export "TransactionPaymentApi_query_length_to_fee" (func $TransactionPaymentApi_query_length_to_fee))
+(export "TransactionPaymentCallApi_query_call_info" (func $TransactionPaymentCallApi_query_call_info))
+(export "TransactionPaymentCallApi_query_call_fee_details" (func $TransactionPaymentCallApi_query_call_fee_details))
+(export "TransactionPaymentCallApi_query_weight_to_fee" (func $TransactionPaymentCallApi_query_weight_to_fee))
+(export "TransactionPaymentCallApi_query_length_to_fee" (func $TransactionPaymentCallApi_query_length_to_fee))
+(export "TryRuntime_on_runtime_upgrade" (func $TryRuntime_on_runtime_upgrade))
+(export "TryRuntime_execute_block" (func $TryRuntime_execute_block))
+(export "__data_end" (global 1))
+(export "__heap_base" (global 2))
+```
+
+---v
+
+### Activity: Inspecting Wasm Code
+
+- Once you reach the Polkadot module, and you build your first parachain, repeat the same, I promise
+  you will learn a thing or two :)
+
+---
+
+## Activity: Expected Panics In The Runtime
+
+- Look into the `frame-executive` crate's code. See instances of `panic!()`, and see if you can make
+  sense out of it.
+- You have 15 minutes!
+
+<diagram class="mermaid">
+graph LR
+    TransactionPool --"😈"--> Authoring --"😇"--> Import
+</diagram>
+
+Note:
+
+you should for example find that a real FRAME-based runtime, in `execute_block`, we certainly do
+panic if any transaction fails to apply.
+
+---
+
+## Lecture Recap (Part 2)
+
+- Considerations:
+
+  - Speed
+  - Versioning
+  - Panics
+  - Altering Host Functions
+
+- Activity:
+  - Inspecting a wasm blob for import and export
+  - Finding panics in `FRAME` runtimes.
+
+---
+
+## Additional Resources! 😋
+
+> Check speaker notes (click "s" 😉)
+
+<img width="300px" rounded src="../../../assets/img/5-Substrate/thats_all_folks.png" />
+
+Notes:
+
+- New runtime API for building genesis config: https://github.com/paritytech/substrate/pull/14310 / https://github.com/paritytech/polkadot-sdk/pull/1492
+
+- New changes to `initialize_block` to support MBM: https://polkadot-fellows.github.io/RFCs/approved/0013-prepare-blockbuilder-and-core-runtime-apis-for-mbms.html
+
+- New metadata version, including types for the runtime API: https://github.com/paritytech/substrate/issues/12939
+
+- Recent development on api versioning: https://github.com/paritytech/substrate/issues/13138
+
+- In Substrate, a type needs to provide the environment in which host functions are provided, and
+  can be executed.
+
+> We call this an "externality environment", represented by `trait Externalities`.
+
+```rust
+SomeExternalities.execute_with(|| {
+    let x = sp_io::storage::get(b"foo");
+});
+```
+
+### Post Lecture Notes
+
+HK:
+
+- The panic section is so important and it comes at the end, therefore hard to understand. Simplify
+  it and deliver it sooner.
+- More examples of unsigned tx
+
+---
+
+## Appendix
+
+Content that is not covered, but is relevant.
+
+---
+
+## Consideration: Runtime API Versioning
+
+- Same principle, but generally easier to deal with.
+- Metadata is part of the runtime, known **per block**.
+- Those written in a dynamically typed languages are usually fine 😎.
+
+Notes:
+
+Also, it is arguable to say that the runtime is the boss here. The node must serve the runtime
+fully, but the runtime may or may not want to support certain APIs for certain applications.
+
+Recall from another slide:
+
+> - A lot of other runtime APIs _could_ be optional depending on the context.
+
+---v
+
+### Consideration: Runtime API Versioning
+
+- The Rust code (which is **statically** typed) in substrate node does care if the change _is breaking_.
+  - For example, input/output types change. Rust code cannot deal with that!
+
+---v
+
+### Consideration: Runtime API Versioning
+
+```rust
+sp_api::decl_runtime_apis! {
+    // latest version
+    fn foo() -> u32;
+
+    // old version
+    #[changed_in(4)]
+    fn foo() -> u64;
+}
+
+let new_return_type = if api.version < 4 {
+    // this weird function name is generated by decl_runtime_apis!
+    let old_return_type = api.foo_before_version_4();
+    // somehow convert it. don't care
+    old_return_type.try_into().unwrap()
+} else {
+    api.foo()
+}
+```
+
+---v
+
+### Consideration: Runtime API Versioning
+
+> Rule of thumb: Every time you change the signature of a host function / runtime API, i.e. change
+> the input/output types, you need to think about this.
+
+But what you have to do is dependent on the scenario.
+
+### Activity: API Versioning
+
+- Look into substrate and find all instances of `#[changed_in(_)]` macro to detect runtime api version.
+- Then see if/how this is being used in the node code.
+
+- Find all the `#[version]` macros in `sp-io` to find all the versioned host functions.
+
+---
+
+## Inherents and Block Authoring
+
+- What about Inherents?
+
+---v
+
+### Inherents and Block Authoring
+
+```rust [14-26]
+// get the best-block, based on whatever consensus rule we have.
+let (best_number, best_hash) = consensus::best_block();
+
+// get the latest state.
+let mut state = database::state_at(best_hash);
+
+// initialize a wasm runtime.
+let code = state::get(well_known_keys::CODE);
+let runtime = wasm::Executor::new(code);
+
+
+// get an empty node block.
+let mut block: NodeBlock = Default::default();
+
+// tell this runtime that you wish to start a new block, and pass in a raw header.
+runtime.initialize_block(&block.header);
+
+let inherents: Vec<Vec<u8>> = block_builder::inherents();
+block.extrinsics = inherents;
+
+// repeatedly apply transactions.
+while let Some(next_ext) = transaction_pool_iter::next() {
+  state.execute(|| {
+    runtime.apply_extrinsic(next_ext);
+  });
+  block.extrinsics.push(next_ext);
+}
+
+// finalize and set the final header.
+block.header = runtime.finalize_block();
+```
+
+Notes:
+
+In reality, the node can either get the inherents itself or ask the runtime about them. There is
+actually a runtime API for this too, but we won't cover it.
+
+while inherents can in principle come at any point in the block, since FRAME restricts them to
+come first, we also keep our example aligned.
+
+Should you wish to see the real version of this, check this crate:
+https://paritytech.github.io/substrate/master/sc_basic_authorship/index.html
+
+---
+
+## Misc
+
+<img rounded style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-3-substrate-wasm.png" />
diff --git a/content/6-Protocol_On-Chain/Substrate/3-Merklized-Storage-slides.md b/content/6-Protocol_On-Chain/Substrate/3-Merklized-Storage-slides.md
new file mode 100644
index 00000000..3d336660
--- /dev/null
+++ b/content/6-Protocol_On-Chain/Substrate/3-Merklized-Storage-slides.md
@@ -0,0 +1,922 @@
+---
+title: Substrate Merklized Storage
+duration: 90mins
+---
+
+# Substrate Storage
+
+---
+
+## What We Know So Far
+
+<img style="width: 900px;" src="../../../assets/img/5-Substrate/dev-storage-1.svg" />
+
+Notes:
+
+- Runtime interacts with Client/Host using Host functions.
+- sp_io::storage helps with saving runtime state in the client using these host functions.
+
+---v
+
+#### Externalities
+
+> Externalities: An environment in which the runtime can access host functions, namely storage ones.
+
+Notes:
+
+- In Substrate, a type needs to provide the environment in which host functions are provided, and can be executed.
+- We call this an "externality environment", represented
+  by [`trait Externalities`](https://paritytech.github.io/substrate/master/sp_externalities/trait.Externalities.html).
+- By convention, an externality has a "**backend**" that is in charge of dealing with storage.
+- Externality is a trait that provides functionality to interact with storage and other extensions registered in the
+  node.
+
+---v
+
+### What We Know So Far
+
+<img style="width: 900px;" src="../../../assets/img/5-Substrate/dev-storage-2.svg" />
+
+---v
+
+### What We Know So Far
+
+- Recall that at the `sp_io` layer, you have **opaque keys and values**.
+
+```rust
+let storage_key = vec![8, 2];
+sp_io::storage::get(storage_key);
+sp_io::storage::set(storage_key, vec![42, 33]);
+```
+
+---v
+
+### What We Know So Far
+
+```rust
+sp_io::TestExternalities::new_empty().execute_with(|| {
+      sp_io::storage::get(..);
+  });
+```
+
+Notes:
+
+- TestExternalities mimic a client.
+
+---
+
+## Key Value
+
+> This seems to indicate our storage could be key-value all the way.. 🤔
+
+---v
+
+### Key Value
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-kv-backend.svg" />
+
+---v
+
+### Key Value
+
+- Concatenate all data and hash to get the root.
+- O(1) read and write.
+
+> Spoiler, that is not how data is stored internally in the database.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+- "_Storage keys_" (whatever you pass to `sp_io::storage`) directly maps to "_database keys_".
+- Probably don't wanna introduce storage key and db key right now.
+  Good time to hammer down what you mean by storage key and what you mean by database key.
+
+literally imagine that in the implementation of `sp_io::storage::set`, we write it to a key-value
+database.
+
+---v
+
+### Key Value: Proof sizes
+
+- Suppose there is a large database.
+- Alice has the state root of this database, wants to lookup her balance from this database.
+- How can Alice verify the balance she receives from a full node is correct?
+
+SEND HER THE WHOLE DATABASE 😱.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+Alice is representing a light client, I represent a full node.
+
+---v
+
+### Key Value: State Root
+
+- If you change a single key-value, we need to re-hash the whole thing again to get the updated state root 🤦.
+
+---
+
+## Substrate Storage: Merklized
+
+> Substrate uses a base-16, (patricia) radix merkle tree.
+
+Notes:
+
+- Find the code at [paritytech/trie](https://github.com/paritytech/trie).
+
+---
+
+### Recap
+
+<pba-cols>
+<pba-col>
+
+<diagram class="mermaid">
+%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
+flowchart TD
+  A["A \n value: Hash(B|C)"] --> B["B \n value: Hash(D|E)"]
+  A --> C["C \n value: Hash(F) \n"]
+  B --> D["D \n value: 0x12"]
+  B --> E["E \n value: 0x23"]
+  C --> F["F \n value: 0x34"]
+</diagram>
+
+</pba-col>
+<pba-col>
+
+- Merkle tree.
+- Typically contains values at leafs.
+
+</pba-col>
+</pba-cols>
+
+---v
+
+### Recap
+
+<pba-cols>
+<pba-col>
+
+<diagram class="mermaid">
+%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
+flowchart TD
+  A["A \n value: Hash(B|C)"] -- v --> B["B \n value: Hash(D|E)"]
+  A --w--> C["C \n Hash(F) \n"]
+  B --"x"--> D["D \n value: 0x12"]
+  B --y--> E["E \n value: 0x23"]
+  C --z--> F["F \n value: 0x34"]
+</diagram>
+
+</pba-col>
+<pba-col>
+
+- Trie aka. Prefix tree
+- Assuming only leafs have data, this is encoding:
+
+<table>
+<tr>
+  <td> "vx" => 0x12</td>
+</tr>
+<tr>
+  <td> "vy" => 0x23</td>
+</tr>
+<tr>
+  <td> "wz" => 0x34</td>
+</tr>
+</table>
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+- this is how we encode key value based data in a trie.
+- Optimization of simple trie,
+
+---v
+
+### Recap
+
+<pba-cols>
+<pba-col>
+
+<diagram class="mermaid">
+%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
+flowchart TD
+  A["A \n Hash(B|C)"] -- v --> B["B \n Hash(D|E)"]
+  A --wz--> F["F \n value: 0x34"]
+  B --"x"--> D["D \n value: 0x12"]
+  B --y--> E["E \n value: 0x23"]
+</diagram>
+
+</pba-col>
+<pba-col>
+
+- Radix Tree.
+- Less nodes to encode the same data.
+
+<table>
+<tr>
+  <td> "vx" => 0x12</td>
+</tr>
+<tr>
+  <td> "vy" => 0x23</td>
+</tr>
+<tr>
+  <td> "wz" => 0x34</td>
+</tr>
+</table>
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+More resources:
+
+- https://en.wikipedia.org/wiki/Merkle_tree
+- https://en.wikipedia.org/wiki/Radix_tree
+- https://en.wikipedia.org/wiki/Trie
+
+Namely:
+
+> The data structure was invented in 1968 by Donald R. Morrison, with whom it is primarily
+> associated, and by Gernot Gwehenberger.
+
+> Donald Knuth, pages 498-500 in Volume III of The Art of Computer Programming, calls these
+> "Patricia's trees", presumably after the acronym in the title of Morrison's paper: "PATRICIA -
+> Practical Algorithm to Retrieve Information Coded in Alphanumeric".
+> Today, Patricia tries are seen
+> as radix trees with radix equals 2, which means that each bit of the key is compared individually
+> and each node is a two-way (i.e., left versus right) branch.
+
+---
+
+### Merklized
+
+- Substrate does in fact use a key-value based database under the hood.
+- But this KV based DB is used to store the trie nodes, not directly the storage keys.
+  <br />
+
+<div>
+
+- We take the **storage key**, and make it to be the path on a trie.
+
+</div>
+<!-- .element: class="fragment" -->
+
+<div>
+
+- Then we store the **trie nodes**, referenced by **their hash**, in the main database.
+
+</div>
+<!-- .element: class="fragment" -->
+
+---v
+
+### Merklized
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/trie-backend-simple-simple.svg" />
+
+Notes:
+
+- imagine: `sp_io::storage::get(b"ad")`
+- We will traverse the path later.
+
+---v
+
+### Merklized
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-simple.svg" />
+
+Notes:
+
+realistically, the storage key is something like `(system_)16`, but I have put the strings here for
+simplification.
+
+---
+
+## Traversing the Trie
+
+- We know the state-root at a given block `n`.
+- Assume this is a base-27, patricia trie.
+  English alphabet along with '\_' is the key-scope.
+- Let's see the steps needed to read `balances_alice` from the storage.
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-walk-m1.svg" />
+
+Notes:
+
+- We start with the state root node.
+- Read its children.
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-walk-0.svg" />
+
+Notes:
+
+- We are interested in "balances\_" so we read that node from database.
+- Did you notice the mistake in the slide? "\_" technically would not be allowed in base-26, so it really is base-27.
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-walk-1.svg" />
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-walk-2.svg" />
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-walk-full.svg" />
+
+---v
+
+## Q/A Break
+
+<img src="../../../assets/img/5-Substrate/dev-4-8-qr-radix-tree-visualization.png" />
+
+Try inserting (and deleting) bunch of keys and see how you fill up the trie in
+the [radix tree visualization](https://www.cs.usfca.edu/~galles/visualization/RadixTree.html).
+
+---
+
+## Merklized: Proofs
+
+Back to our question
+
+> If alice only has this state root, how can she verify her balance is correct?
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-proof.svg" />
+
+Notes:
+
+Give 30 seconds to students to make sense of the image by themselves.
+
+The important point is that for example the whole data under `_system` is hidden away behind one hash.
+
+Receiver will hash the root node, and check it against a publicly known storage root.
+
+This differs slightly from how actual proof generation might work in the code.
+
+In general, you have a tradeoff: send more data, but require less hashing on Alice, or opposite (this is what we call "
+compact proof").
+
+---v
+
+### Merklized: Proofs
+
+- 🏆 Small proof size is a big win for light clients.
+
+---
+
+## Merklized: Recap
+
+<div>
+
+- Storage key (`balances_alice`) is the path on the trie.
+- `sp_io::storage::get("balances_alice");`
+
+</div>
+<!-- .element: class="fragment" -->
+
+<div>
+
+- Storage key is arbitrary length.
+
+</div>
+<!-- .element: class="fragment" -->
+
+<div>
+
+- Intermediary (branch) nodes could contain values.
+  - `:code` contains some value, `:code:more` can also contain value.
+
+</div>
+
+<!-- .element: class="fragment" -->
+
+<div>
+
+- Storage Key != Database Key.
+- 1 Storage access = Many database access.
+
+</div>
+<!-- .element: class="fragment" -->
+
+Notes:
+
+how many database access would do you think it is?
+
+we will explain this in a few slides, but assuming an order `N` tree, and assuming it is balanced,
+it will be `O(LOG_n)`.
+
+---
+
+## Substrate Storage: The Updated Picture
+
+<img style="width: 1000px;" src="../../../assets/img/5-Substrate/dev-storage-3.svg" />
+
+---
+
+### Unbalanced Tree
+
+<img style="width: 800px;" src="../../../assets/img/5-Substrate/dev-trie-backend-unbalanced.svg" />
+
+---v
+
+### Unbalanced Tree
+
+- Unbalanced tree means unbalanced performance.
+  An attack vector, if done wrong.
+- More about this in FRAME storage, and how it is prevented there.
+
+Notes:
+
+- under-estimate weight/gas etc.
+- You as the runtime developer must ensure that you use the right keys.
+- This is particularly an issue if an end user can control where they can insert into the trie!
+- The main prevention is using a cryptographically secure hash function on the frame side.
+
+---
+
+## Trie Caching 🤔
+
+- We rarely care about state root and all the trie shenanigans before the end of the block...
+
+> A block-scoped cache for storage.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+In other words, one should care too much about updating a "trie" and all of its hashing details while the block is still
+being executed?
+All of that can be delayed.
+
+---v
+
+## Overlay
+
+- Is a cache layer **outside of the Runtime**.
+- It works **based on key-values**, **not trie-format**.
+
+---v
+
+### Overlay
+
+- Almost identical semantic to your CPU cache:
+  - <!-- .element: class="fragment" --> Once you read a value, it stays here, and can be re-read for cheap.
+  - <!-- .element: class="fragment" --> Once you write a value, it will only be written here.
+    - It can be read for cheap.
+  - <!-- .element: class="fragment" --> All writes are flushed when all extrinsics for a block are applied.
+- <!-- .element: class="fragment" --> No race conditions as runtime is single-threaded.
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-overlay.svg" />
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-overlay-1.svg" />
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-overlay-2.svg" />
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-overlay-3.svg" />
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-overlay-4.svg" />
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-overlay-5.svg" />
+
+---v
+
+### Overlay
+
+<pba-cols>
+
+<pba-col>
+
+- Cheap != Free
+
+</pba-col>
+<pba-col>
+
+<img style="width: 700px;" src="../../../assets/img/5-Substrate/dev-4-3-io.svg" />
+
+</pba-col>
+
+</pba-cols>
+
+Notes:
+
+- In your code, you often have an option to either pass stack variables around, or re-read code from `sp-io`.
+  Most often, this is a micro-optimization that won't matter too much, but in general you should know that the former is
+  more performant, as won't go the the host at all.
+- A deletion is basically a write to `null`.
+
+---v
+
+### Overlay
+
+- The overlay is also able to spawn child-overlays, known as "_storage layer_".
+- Useful for having a _transactional_ block of code.
+
+```rust
+// spawn a new layer.
+with_storage_layer(|| {
+    let foo = sp_io::storage::read(b"foo");
+    sp_io::storage::set(b"bar", foo);
+
+    if cond {
+        Err("this will be reverted")
+    } else {
+        Ok("This will be commit to the top overlay")
+    }
+})
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+- implement with zero-copy. So, the size of values is not so important, it is more about the number.
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-overlay-nested.svg" />
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-overlay-nested-1.svg" />
+
+---v
+
+### Overlay
+
+- What if I call `sp_io::storage::root()` in the middle of the block?
+- Can the overlay respond to this?
+
+Notes:
+
+NO!
+The overlay works on the level on key-values, it knows nothing of trie nodes, and to compute the root we have to go to
+the trie layer and pull a whole lot of data back from the disk and build all the nodes etc.
+
+---v
+
+### Overlay: More Caches
+
+- There are more caches in the trie layer as well. But outside of the scope of this lecture.
+
+```bash
+./substrate --help | grep cache
+```
+
+Notes:
+
+https://www.youtube.com/embed/OoMPlJKUULY
+
+---
+
+### Substrate Storage: Final Figure
+
+<img style="width: 1000px;" src="../../../assets/img/5-Substrate/dev-storage-externalities-full.svg" />
+
+---v
+
+### Substrate Storage
+
+- Recall: Any code accessing host functions needs to wrapped in something that implements
+  `Externalities`
+
+```rust
+// ❌
+let x = sp_io::storage::get(b"foo");
+
+// error:
+// thread '..' panicked at '`get_version_1` called outside of an Externalities-provided environment.'
+```
+
+```rust
+// ✅
+SomeExternalities.execute_with(|| {
+    let x = sp_io::storage::get(b"foo");
+});
+```
+
+---
+
+## State Pruning
+
+- Each runtime will think that it has access to **_its_** full state, behind `sp_io::storage`.
+- Does the client then store one full trie per-block?
+
+Surely not.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+- Only trie nodes that are updated from one block to the other are created as new DB Keys.
+- For the unchanged ones, we only reference the existing one.
+
+---v
+
+### State Pruning
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-3-pruning-1.svg" />
+---v
+
+### State Pruning
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-3-pruning-2.svg" />
+---v
+
+### State Pruning
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-3-pruning-3.svg" />
+---v
+
+### State Pruning
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-3-pruning-4.svg" />
+
+---v
+
+## State Pruning
+
+- 🧠 Data stored onchain, but rarely changed? De nada.
+- State pruning is an _entirely client side optimization_,
+
+---
+
+## Base 2, Base 16, Base-26?
+
+- Instead of alphabet, we use the base-16 representation of everything.
+
+> Base-16 (Patricia) Merkle Trie.
+
+- `System` -> `73797374656d`
+- `:code` -> `3a636f646500`
+
+---v
+
+### Base 2, Base 16, Base-26?
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-16.svg" />
+<!-- TODO: update figure to represent node size. -->
+
+Tradeoff: "_IO count vs. Node size_"
+
+<!-- .element: class="fragment" -->
+
+Between a light client and a full node, who cares more about which?
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+Light client cares about node size.
+When proof is being sent, there is no IO.
+
+First glance, the radix-8 seems better: you will typically have less DB access to reach a key.
+For example, with binary, with 3 IO, we can reach only 8 items, but with radix-8 512.
+
+So why should not choose a very wide tree?
+Because the wider you make the tree, the bigger each node gets, because it has to store more hashes.
+At some point, this start to screw with both the proof size and the cost of reading/writing/encoding/decoding all these
+nodes.
+
+---v
+
+### Base 2, Base 16, Base-26?
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-16-with-size.svg" />
+
+Note:
+
+Here's a different way to represent it; the nodes are bigger on the base-8 trie.
+
+---v
+
+### Base 2, Base 16, Base-26?
+
+- base-2: Small proofs, more nodes.
+- base-26: Bigger proofs, less nodes.
+
+Notes:
+✅ 16 has been benchmarked as a good middle-ground.
+
+---
+
+#### Lecture Summary/Recap:
+
+<pba-cols>
+
+<pba-col>
+
+- KV-Based storage
+- Merklized storage, and proofs
+- Unbalanced tree
+- State pruning
+- Radix order consequences
+
+In the Appendix, you will find:
+
+- Large nodes affecting the proof
+- Child tries
+
+</pba-col>
+
+<pba-col>
+<img src="../../../assets/img/5-Substrate/dev-storage-full.svg" />
+</pba-col>
+
+</pba-cols>
+
+---
+
+## Additional Resources! 😋
+
+- Check speaker notes (click "s" 😉).
+- Follows some additional content that is not covered.
+
+<img width="300px" rounded src="../../../assets/img/5-Substrate/thats_all_folks.png" />
+
+Notes:
+
+- Shawn's deep dive: https://www.shawntabrizi.com/blog/substrate/substrate-storage-deep-dive/
+
+- Basti's talk on Trie caching: https://www.youtube.com/watch?v=OoMPlJKUULY
+
+- About state version:
+
+  - https://github.com/paritytech/substrate/pull/9732
+  - https://github.com/paritytech/substrate/discussions/11824
+
+- An "old but gold" read about trie in
+  Ethereum: https://medium.com/shyft-network/understanding-trie-databases-in-ethereum-9f03d2c3325d
+
+- On optimizing substrate storage proofs: https://github.com/paritytech/substrate/issues/3782
+- Underlying trie library maintained by Parity: https://github.com/paritytech/trie
+
+- https://github.com/paritytech/trie/
+
+- https://spec.polkadot.network/chap-state#sect-state-storage
+
+- https://research.polytope.technology/state-(machine)-proofs
+
+- An interesting, but heretical idea: can the runtime of block N, access state of block N-1?
+  HELL.
+  NO.
+  It might sound like a "but why nooooot" type of situation, but it breaks down all assumptions
+  about what a state transition is.
+  The runtime is the state transition function.
+  Recall the formula of that, and then you will know why this is not allowed.
+
+### Post Lecture Feedback
+
+Double check the narrative and example of the `BIG_STUFF` node.
+An example/exercise of some sort
+would be great, where students call a bunch of `sp_io` functions, visualize the trie, and invoke
+proof recorder, and see which parts of the trie is exactly part of the proof.
+
+---
+
+## Appendix
+
+Content that is not covered, but is relevant.
+
+---
+
+### Overlay Limits
+
+- There is a limit to how many nested layers you can spawn
+- It is not free, thus it is attack-able.
+
+```rust
+with_storage_layer(|| {
+    let foo = sp_io::storage::read(b"foo");
+    with_storage_layer(|| {
+        sp_io::storage::set(b"foo", b"foo");
+        with_storage_layer(|| {
+            sp_io::storage::set(b"bar", foo);
+            with_storage_layer(|| {
+                sp_io::storage::set(b"foo", "damn");
+                Err("damn")
+            })
+            Ok("what")
+        })
+        Err("the")
+    });
+    Ok("hell")
+})
+```
+
+---
+
+## Trie Format Matters!
+
+- Recall that in our "trie walking", we took the state root, and got the root node from the DB.
+- The state root of any substrate-based chain, including Polkadot, is the hash of the "Trie Node".
+
+> Trie format matters! and therefore it is part of [the polkadot spec](https://spec.polkadot.network).
+
+Notes:
+
+Meaning, if another client wants to sync polkadot, it should know the details of the trie format.
+
+---
+
+## Child Trees
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-4-3-child.svg" />
+
+Notes:
+
+Shawn's answer on usecases: https://substrate.stackexchange.com/questions/139/what-are-good-use-cases-for-child-tries/144#144
+
+- Used in smart contracts for being able to delete contract data and reinstate later.
+- Generating proof of contribution to crowdloan.
+- Alternative trie format.
+
+---v
+
+### Child Trees
+
+- Stored on a different DB Column (async-ish bulk deletion).
+- Easily prove-able
+- Most importantly, alternative trie formats.
+
+---
+
+## Large data nodes 🤔
+
+- Two common problems that merkle proofs have:
+  - If the one of the parent nodes has some large data.
+  - If you want to prove the deletion/non-existence of a leaf node.
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-proof-fat.svg" />
+
+---v
+
+## Large data nodes 🤔
+
+New "trie format" 🌈:
+
+- All data containing more than 32 bytes are replaced with their hash (pointer to the actual value).
+- The (larger than 32 bytes) value itself stored in the database under this hash.
+
+```rust
+struct RuntimeVersion {
+    ...
+    state_version: 0,
+}
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+<img style="width: 1400px;" src="../../../assets/img/5-Substrate/dev-trie-backend-proof-fat-fix.svg" />
+
+What is the ramification of this for full nodes, and light clients?
+
+Notes:
+
+Both read and write have an extra step now, but proof are easier.
+
+Note from emeric: the green node is not really a "real" node, it is just `{ value: BIG_STUFF }` stored in the database.
+I will skip this detail for the sake of simplicity.
+One can assume that the green node is like any other node in the trie.
+
+---
+
+### Storage Implementation
+
+There are multiple implementations of `Externalities`:
+
+- [`TestExternalities`](https://paritytech.github.io/substrate/master/sp_state_machine/struct.TestExternalities.html):
+  - `Overlay`
+  - `TrieDb` with `InMemoryBackend`
+- [`Ext`](https://paritytech.github.io/substrate/master/sp_state_machine/struct.Ext.html) (the real thing 🫡)
+  - `Overlay`
+  - `TrieDb` with a real database being the backend
diff --git a/content/6-Protocol_On-Chain/Substrate/4-Transaction-Pool-slides.md b/content/6-Protocol_On-Chain/Substrate/4-Transaction-Pool-slides.md
new file mode 100644
index 00000000..1a8d8b28
--- /dev/null
+++ b/content/6-Protocol_On-Chain/Substrate/4-Transaction-Pool-slides.md
@@ -0,0 +1,527 @@
+---
+title: Substrate Transaction Pool
+---
+
+# Substrate Transaction Pool
+
+---
+
+## Why Transaction Pool?
+
+Because it is a (⛓️ blockspace) market.
+
+<pba-cols>
+<pba-col>
+<img style="width: 500px;" src="./img/tx-pool/BlockspaceBooth.png" />
+</pba-col>
+
+<pba-col>
+<img style="width: 500px; margin-left: -100px; margin-top: 250px;" src="./img/tx-pool/short-line.png" /> <!-- .element: class="fragment" -->
+</pba-col>
+
+<pba-col>
+<img style="width: 700px; margin-left: -100px; margin-top: 100px;" src="./img/tx-pool/long-line.png" /> <!-- .element: class="fragment" -->
+</pba-col>
+
+</pba-cols>
+
+Notes:
+
+The blockchain produces blockspace, and users buy that blockspace.
+Why do they buy it?
+So they can contribute to the shared story.
+So they can interact with the shared state machine.
+You can think of these users standing in line with transactions in their hand, waiting for the chance to put their transactions into the chain's blockspace.
+Sometimes the demand for blockspace is low and the queue is short.
+In this case the queue gets completely emptied each time a new block is created.
+Other times it gets long and backed up.
+Then when a block comes, only a part of the queue gets emptied.
+
+This simple model provides some good intuition about how the transaction pool works, but it is a bit simplified.
+
+First, It is actually a priority queue.
+You can jump the line by offering to bribe the block producers.
+
+Second, it is more accurate to think of the transactions themselves waiting in line, not the users who sent those transactions.
+
+Let's take a closer look.
+
+---
+
+## Context
+
+<image rounded src="../../../assets/img/5-Substrate/dev-pool-context.svg">
+
+Notes:
+
+- Gossip
+- Queue of all transactions, queue of ready transactions.
+- Then given to the block author, only READY ones.
+
+---v
+
+### Context
+
+Any Transaction Pool has two main objectives:
+
+1. Validate Transactions
+   - Ready, Future, or 🗑️?
+2. Order them
+   - Within each list, who is first?
+
+---
+
+## 1. Transaction Validation
+
+Moving transactions from one list to the other.
+
+<diagram class="mermaid" style="display: flex; width: 80%">
+graph LR
+    W["🤠 Wild West"] --"😈"--> T["🗑️"]
+    W --"😇 ⌛️"--> R["✅ Ready"]
+    W --"😇 ⏳"--> F["⏰ Future"]
+</diagram>
+
+---v
+
+### 1. Transaction Validation
+
+- Transaction validity is exclusively outside of the transaction pool, and is **100% determined by the Runtime**.
+- Transaction validation should be **cheap** to perform.
+- Transaction pool is entirely an **offchain operation**.
+  - No state change
+
+Notes:
+
+Important, must pause and ask!
+
+- Why is it from the runtime? because the transaction format is opaque and the node doesn't even know what to do with it.
+- Why does it have to be cheap? wild west, unpaid, DoS!
+- Pesky question: but be aware that from the runtime's perspective, the node could be malicious. The runtime cannot trust the node to obey.
+  ** THE RUNTIME MUST RE-VALIDATE TRANSACTIONS LATER in block building and import as well **
+
+---v
+
+### 1. Transaction Validation
+
+The runtime API.
+
+```rust[1-100|6]
+impl TaggedTransactionQueue<Block> for Runtime {
+  fn validate_transaction(
+    source: TransactionSource,
+    tx: <Block  as BlockT>::Extrinsic,
+    block_hash: <Block as BlockT>::Hash,
+  ) -> TransactionValidity {
+    ..
+  }
+}
+```
+
+---v
+
+### 1. Transaction Validation
+
+```rust[1-100|5-6|8-9|11-12|14-100|1-100]
+pub type TransactionValidity = Result<ValidTransaction, TransactionValidityError>;
+
+/// This is going into `Ready` or `Future`
+pub struct ValidTransaction {
+  /// If in "Ready", what is the priority?
+  pub priority: u64,
+
+  /// For how long is this validity?
+  pub longevity: u64,
+
+  /// Should be propagate it?
+  pub propagate: bool,
+
+  /// Does this require any other tag to be present in ready?
+  ///
+  /// This determines "Ready" or "Future".
+  pub requires: Vec<Tag>,
+  /// Does this provide any tags?
+  pub provides: Vec<Tag>,
+}
+
+type Tag = Vec<u8>
+```
+
+---v
+
+### 1. Transaction Validation: Banning
+
+- Once certain transaction is discovered to be invalid, **its hash** is banned for a fixed duration of time.
+- Default in substrate is `Duration::from_secs(60 * 30)`, can be configured via CLI.
+
+Notes:
+
+See: https://github.com/paritytech/substrate/pull/11786
+
+we probably also ban the peer who sent us that transaction? but have to learn.
+
+---
+
+## 2. Transaction Ordering
+
+- `provides` and `requires` is a very flexible mechanism; it allows you to:
+  - Specify if a transaction is "Ready" or "Future"
+  - Within each, what transactions should ge before which.
+
+Note: it essentially forms a graph.
+
+Order mostly matters within the ready pool. I am not sure if the code maintains an order in `future` as well. In any
+case, not a big big deal.
+
+---v
+
+### 2. Transaction Ordering: Quiz Time.
+
+<pba-cols>
+<pba-col>
+
+```
+(
+  A,
+  provides: vec![],
+  requires: vec![]
+)
+```
+
+</pba-col>
+
+<pba-col>
+<table>
+<thead>
+  <tr>
+    <th>Ready</th>
+    <th>Future</th>
+  </tr>
+</thead>
+<tbody class="fragment">
+  <tr>
+    <td>
+    <pre>(A, pr: vec![], rq: vec![])</pre>
+    </td>
+    <td></td>
+  </tr>
+</tbody>
+</table>
+</pba-col>
+
+</pba-cols>
+
+---v
+
+### 2. Transaction Ordering: Quiz Time.
+
+<pba-cols>
+<pba-col>
+
+```
+(
+  B,
+  provides: vec![2],
+  requires: vec![1]
+)
+```
+
+</pba-col>
+
+<pba-col>
+<table>
+<thead>
+  <tr>
+    <th>Ready</th>
+    <th>Future</th>
+  </tr>
+</thead>
+<tbody class="fragment">
+  <tr>
+    <td>
+      <pre>(A, pr: vec![], rq: vec![])</pre>
+    </td>
+    <td>
+      <pre>(B, pr: vec![2], rq: vec![1])</pre>
+    </td>
+  </tr>
+</tbody>
+</table>
+</pba-col>
+
+</pba-cols>
+
+---v
+
+### 2. Transaction Ordering: Quiz Time.
+
+<pba-cols>
+<pba-col>
+
+```
+(
+  C,
+  provides: vec![3],
+  requires: vec![2]
+)
+```
+
+</pba-col>
+
+<pba-col>
+<table>
+<thead>
+  <tr>
+    <th>Ready</th>
+    <th>Future</th>
+  </tr>
+</thead>
+<tbody class="fragment">
+  <tr>
+    <td>
+      <pre>(A, pr: vec![], rq: vec![])</pre>
+    </td>
+    <td>
+      <pre>(B, pr: vec![2], rq: vec![1])</pre>
+    </td>
+  </tr>
+  <tr>
+    <td>
+    </td>
+    <td>
+      <pre>(C, pr: vec![3], rq: vec![2])</pre>
+    </td>
+  </tr>
+</tbody>
+</table>
+</pba-col>
+
+</pba-cols>
+
+---v
+
+### 2. Transaction Ordering: Quiz Time.
+
+<pba-cols>
+<pba-col>
+
+```
+(
+  D,
+  provides: vec![1],
+  requires: vec![]
+)
+```
+
+</pba-col>
+
+<pba-col>
+<table>
+<thead>
+  <tr>
+    <th>Ready</th>
+    <th>Future</th>
+  </tr>
+</thead>
+<tbody class="fragment">
+  <tr>
+    <td>
+      <pre>(A, pr: vec![], rq: vec![])</pre>
+    </td>
+    <td>
+    </td>
+  </tr>
+  <tr>
+    <td>
+      <pre>(D, pr: vec![1], rq: vec![])</pre>
+    </td>
+    <td>
+    </td>
+  </tr>
+  <tr>
+    <td>
+      <pre>(B, pr: vec![2], rq: vec![1])</pre>
+    </td>
+    <td>
+    </td>
+  </tr>
+  <tr>
+    <td>
+      <pre>(C, pr: vec![3], rq: vec![2])</pre>
+    </td>
+    <td>
+    </td>
+  </tr>
+</tbody>
+</table>
+</pba-col>
+
+</pba-cols>
+
+Note: The oder in this slide matters and it is top to bottom.
+
+---v
+
+### 2. Transaction Ordering: `priority`
+
+From the **Ready pool**, when all requirements are met, then `priority` dictates the order.
+
+Further tie breakers:
+
+2. ttl: shortest `longevity` goes first
+3. time in the queue: longest to have waited goes first
+
+<!-- .element: class="fragment" -->
+
+Note:
+
+https://github.com/paritytech/polkadot-sdk/blob/bc53b9a03a742f8b658806a01a7bf853cb9a86cd/substrate/client/transaction-pool/src/graph/ready.rs#L146
+
+---v
+
+### 2. Transaction Ordering: `priority`
+
+> How can the pool be a pure FIFO?
+
+Notes:
+
+All priorities set to 0.
+
+---v
+
+### 2. Transaction Ordering: `nonce`
+
+Purposes of a nonce:
+
+1. Ordering
+2. Replay protection
+3. Double spend protection
+
+---v
+
+### 2. Transaction Ordering: `nonce`
+
+- ✅ You will implement a nonce system using the above primitives as a part of your assignment.
+- General idea: `require -> (account, nonce - 1).encode()`, provide: `provides -> (account, nonce).encode()`
+
+Notes:
+
+Transaction Ordering: Each time a transaction is sent from an account, the nonce increases by one. This sequential
+numbering ensures that transactions are processed in the order they are sent.
+
+Double Spending Prevention: Since each transaction has a unique nonce, it's impossible for two transactions with the
+same nonce to both be valid. This stops attackers from attempting to send the same funds twice.
+
+Replay Attack Protection: In a replay attack, a valid transaction is maliciously or fraudulently repeated or delayed.
+With a nonce, once a transaction is executed, any attempt to execute it again will fail since the nonce will no longer
+match the current state of the account.
+
+---
+
+## Shower Thought: Runtime vs STF
+
+> Transaction pool is entirely an **offchain operation**
+
+Note:
+
+what we said before. What does this imply?
+
+---v
+
+### Shower Thought: Runtime vs STF
+
+<img style="width: 1100px;" src="./img/tx-pool/peter-parker-glasses-off.png" />
+
+Notes:
+
+It is commonly said that the runtime is basically your STF.
+This is a good first order approximation.
+It is nearly true.
+---v
+
+### Shower Thought: Runtime vs STF
+
+<img style="width: 1100px;" src="./img/tx-pool/peter-parker-glasses-on.png" />
+
+Notes:
+
+But as we can see here, when we put our glasses on, actually only some of the apis are part of the stf. the non-stf
+parts are runtime APIs that are called and use, but don't really contribute to the STF. typically the runtime cannot
+make assumptions about these. From the PoV of the runtime, when doing the main consensus critical work (authoring,
+importing) these did not happen.
+
+---
+
+## Lecture Recap
+
+- Blockspace Market, Competition.
+- Main tasks:
+  - Validate (valid and invalid)
+  - Order (split valid into "Ready" and "Future")
+    - provides and requires
+    - priority: Fee/tip
+- By Runtime, but not in STF
+
+Notes:
+
+- Each node's pool is a local wild west.
+- Because it is wild west, the transaction pool must only check static and cheap things.
+- The block author won't trust the pool validation, and re-execute all checks.
+- Shower Thought: Transaction queue validation is part of the runtime, but not part of the STF.
+
+---
+
+## Additional Resources
+
+> Check speaker notes (click "s" 😉)
+
+<img width="300px" rounded src="../../../assets/img/5-Substrate/thats_all_folks.png" />
+
+Notes:
+
+https://github.com/paritytech/polkadot-sdk/blob/bc53b9a03a742f8b658806a01a7bf853cb9a86cd/substrate/client/transaction-pool/src/graph/ready.rs#L149
+
+Original pool PR from ages ago, old but gold: https://github.com/paritytech/substrate/issues/728
+
+> Work towards a flexible transaction queue that relies **only on runtime logic to provide comprehensive dependency and queuing management**... should not be aware of the concepts of accounts, signatures, indexes or nonces.
+
+> Returns `Valid` if the transaction can be **statically** validated; ... the u64 is the priority used to determine which of a mutually exclusive set of transactions are better to include... Any transactions that do get included in a block should be instantly discarded (and banned) if they result in a panic execution.
+
+### Post Lecture
+
+More about MEV
+
+---
+
+# Appendix
+
+---
+
+## Transaction Pool Submission API
+
+```rust
+pub enum TransactionStatus<Hash, BlockHash> {
+	/// Transaction is part of the future queue.
+	Future,
+	/// Transaction is part of the ready queue.
+	Ready,
+	/// The transaction has been broadcast to the given peers.
+	Broadcast(Vec<String>),
+	/// Transaction has been included in block with given hash.
+	InBlock(BlockHash),
+	/// The block this transaction was included in has been retracted.
+	Retracted(BlockHash),
+	/// Maximum number of finality watchers has been reached,
+	/// old watchers are being removed.
+	FinalityTimeout(BlockHash),
+	/// Transaction has been finalized by a finality-gadget, e.g GRANDPA
+	Finalized(BlockHash),
+	/// Transaction has been replaced in the pool, by another transaction
+	/// that provides the same tags. (e.g. same (sender, nonce)).
+	Usurped(Hash),
+	/// Transaction has been dropped from the pool because of the limit.
+	Dropped,
+	/// Transaction is no longer valid in the current state.
+	Invalid,
+}
+```
diff --git a/content/6-Protocol_On-Chain/Substrate/9-SCALE-slides.md b/content/6-Protocol_On-Chain/Substrate/9-SCALE-slides.md
new file mode 100644
index 00000000..c6cb0ca2
--- /dev/null
+++ b/content/6-Protocol_On-Chain/Substrate/9-SCALE-slides.md
@@ -0,0 +1,733 @@
+---
+title: SCALE Codec
+description: SCALE Codec for Web3 engineers
+duration: 1 hour
+---
+
+# SCALE Codec
+
+---
+
+## SCALE Codec
+
+At the end of this lecture, you will learn why Substrate uses SCALE codec, how all different kinds of data types are encoded.
+
+---
+
+### SCALE
+
+Simple Concatenated Aggregate Little-Endian
+
+SCALE is a light-weight format which allows encoding (and decoding) which makes it highly suitable
+for resource-constrained execution environments like blockchain runtimes and low-power, low-memory
+devices.
+
+Notes:
+
+- It is a encoding format used to communicate over the wire. Similar to json, protobuf.
+- Extremely light weight, we will see how.
+
+---
+
+### Little-Endian
+
+- Each `word`'s memory address is the address of the smallest byte in the `word`.
+- Do we interpret this as the MSB or LSB?
+- WASM is Little Endian
+
+<img src="../../../assets/img/5-Substrate/endian-egg.png" />
+
+---
+
+### Little-Endian
+
+<img src="../../../assets/img/5-Substrate/endian.png" />
+
+Notes:
+
+- Endianness is the order of bytes.
+- Big Endian => Most significant byte at the smallest address. Similar to English. Generally used in network protocols.
+- Little Endian => Least significant byte at the smallest address.
+
+---
+
+### Why SCALE? Why not X?
+
+- Simple to define.
+- Not Rust-specific (but happens to work great in Rust).
+  - Easy to derive codec logic: `#[derive(Encode, Decode)]`
+  - It does not use Rust `std`, and thus can compile to Wasm `no_std`.
+- Consensus critical / bijective
+- Supports a copy-free decode for basic types on LE architectures.
+
+Notes:
+
+- MaxEncodedLen: Maximum encoded size to make some runtime guarantees about computation.
+- TypeInfo: Used to generate metadata.
+- Bijective exception later.
+  - one value will always encode to one blob and that blob will only decode to that value.
+
+---
+
+### Why SCALE? Why not X?
+
+- It is about as thin and lightweight as can be.
+- Truthfully, ahead of its time in the Rust community
+
+<pba-cols>
+<pba-col center>
+
+<img width="600px" src="../../../assets/img/5-Substrate/lib-bincode.png" style="background-color: white; border-radius: 10%; border: 5px solid red;" />
+
+</pba-col>
+
+<pba-col center>
+
+<img width="600px" src="../../../assets/img/5-Substrate/lib-scale.png" style="background-color: white; border-radius: 10%; border: 5px solid green;" />
+
+</pba-col>
+</pba-cols>
+
+---
+
+### SCALE is NOT Self-Descriptive
+
+- The need for metadata!
+
+note:
+
+- It is important to note that the encoding context (knowledge of how the types and data structures look) needs to be known separately at both encoding and decoding ends.
+- The encoded data does not include this contextual information.
+
+---
+
+### Example: SCALE vs JSON
+
+<div class="flex-container text-smaller">
+<div class="left">
+
+```rust
+use parity_scale_codec::{ Encode };
+
+#[derive(Encode)]
+struct Example {
+	number: u8,
+	is_cool: bool,
+	optional: Option<u32>,
+}
+
+fn main() {
+	let my_struct = Example {
+		number: 42,
+		is_cool: true,
+		optional: Some(69),
+	};
+	println!("{:?}", my_struct.encode());
+	println!("{:?}", my_struct.encode().len());
+}
+```
+
+```sh
+[42, 1, 1, 69, 0, 0, 0]
+7
+```
+
+</div>
+<div class="right" style="margin-left: 10px;">
+
+```rust
+use serde::{ Serialize };
+
+#[derive(Serialize)]
+struct Example {
+	number: u8,
+	is_cool: bool,
+	optional: Option<u32>,
+}
+
+fn main() {
+	let my_struct = Example {
+		number: 42,
+		is_cool: true,
+		optional: Some(69),
+	};
+	println!("{:?}", serde_json::to_string(&my_struct).unwrap());
+	println!("{:?}", serde_json::to_string(&my_struct).unwrap().len());
+}
+```
+
+```sh
+"{\"number\":42,\"is_cool\":true,\"optional\":69}"
+42
+```
+
+</div>
+</div>
+
+---
+
+### Try It Yourself!
+
+```sh
+cargo init temp
+cargo add parity-scale-codec --features derive
+```
+
+---
+
+### Little vs Big Endian Output
+
+It can be confusing to read the output, and keep in mind endianness.
+
+The order of bytes in the vector follow endianness, but the hex and binary representation of each byte is the same, and independent of endianness.
+
+`0b` prefix denotes a binary representation, and `0x` denotes a hex representation.
+
+<pba-cols>
+<pba-col center>
+
+```rust
+fn main() {
+	println!("{:b}", 69i8);
+	println!("{:02x?}", 69i8.to_le_bytes());
+	println!("{:02x?}", 69i8.to_be_bytes());
+	println!("{:b}", 42u16);
+	println!("{:02x?}", 42u16.to_le_bytes());
+	println!("{:02x?}", 42u16.to_be_bytes());
+	println!("{:b}", 16777215u32);
+	println!("{:02x?}", 16777215u32.to_le_bytes());
+	println!("{:02x?}", 16777215u32.to_be_bytes());
+}
+```
+
+</pba-col>
+
+<pba-col center style="margin-left: 10px;">
+
+```sh
+1000101
+[45]
+[45]
+101010
+[00, 2a]
+[2a, 00]
+111111111111111111111111
+[00, ff, ff, ff]
+[ff, ff, ff, 00]
+```
+
+</pba-col>
+</pba-cols>
+
+---
+
+### Fixed Width Integers
+
+Basic integers are encoded using a fixed-width little-endian (LE) format.
+
+```rust
+use parity_scale_codec::Encode;
+
+fn main() {
+	println!("{:b}", 258u16);
+	println!("{:02x?}", 258u16);
+	println!("{:02x?}", 258u16.encode());
+	println!("{:02x?}", 16777215u32.encode());
+}
+```
+
+```sh
+1_00000010
+102
+[02, 01]
+[ff, ff, ff, 00]
+```
+
+Notes: xx notice the first two being the same. SCALE IS NOT DESCRIPTIVE of the type. The decoder is
+responsible for decoding this into some 1 byte-width type, be it u8 or i8 or something else.
+
+Note that a normal <type>.encode() is printed out equivalent to the .to_be_bytes()
+
+---
+
+### Compact Integers
+
+A "compact" or general integer encoding is sufficient for encoding large integers (up to
+2<sup>536</sup>) and is more efficient at encoding most values than the fixed-width version.
+
+Though for single-byte values, the fixed-width integer is never worse.
+
+---
+
+### Compact Prefix
+
+<div class="text-small">
+
+<!-- prettier-ignore -->
+| `0b00` | `0b01` | `0b10` | `0b11` |
+| ------ | ------ | ------ | ------ |
+| **single-byte mode**: upper six bits are the LE encoding of the value. Valid only for values of `0` through `63`. | **two-byte mode**: upper six bits and the following byte is the LE encoding of the value. Valid only for values `64` through `(2^14 - 1)`. | **four-byte mode**: upper six bits and the following three bytes are the LE encoding of the value. Valid only for values `(2^14)` through `(2^30 - 1)`. |**Big-integer mode**: The upper six bits are the number of bytes following, plus four. The value is contained, LE encoded, in the bytes following. The final (most significant) byte must be non-zero. Valid only for values `(2^30)` through `(2^536 - 1)`. |
+
+</div>
+<br>
+
+- Compact/general integers are encoded with the two least significant **bits** denoting the mode.
+
+Note:
+
+- The ranges must not overlap, or else encoding would be ambiguous. We prefer each number to be encoded in the smallest possible number of bits ofc.
+- How is the range 2^536 achieved? (64 + 3) \* 8
+
+---
+
+### Compact Integers: 0
+
+```rust
+use parity_scale_codec::{Encode, HasCompact};
+
+#[derive(Encode)]
+struct AsCompact<T: HasCompact>(#[codec(compact)] T);
+
+fn main() {
+	println!("{:02x?}", 0u8.encode());
+	println!("{:02x?}", 0u32.encode());
+	println!("{:02x?}", AsCompact(0u8).encode());
+	println!("{:02x?}", AsCompact(0u32).encode());
+}
+```
+
+```sh
+[00]
+[00, 00, 00, 00]
+[00]
+[00]
+```
+
+---
+
+### Compact Integers: 42
+
+```rust
+use parity_scale_codec::{Encode, HasCompact};
+
+#[derive(Encode)]
+struct AsCompact<T: HasCompact>(#[codec(compact)] T);
+
+fn main() {
+	println!("{:02x?}", 42u8.encode());
+	println!("{:02x?}", 42u32.encode());
+	println!("{:02x?}", AsCompact(42u8).encode());
+	println!("{:02x?}", AsCompact(42u32).encode());
+}
+```
+
+```sh
+[2a]
+[2a, 00, 00, 00]
+[a8]
+[a8]
+```
+
+- 42 as binary: `0b101010` = `[0x2a]`.
+- Add `00` to the least significant bits.
+- `0b10101000` = `[0xa8]` = 168 as decimal.
+
+---
+
+### Compact Integers: 69
+
+```rust
+use parity_scale_codec::{Encode, HasCompact};
+
+#[derive(Encode)]
+struct AsCompact<T: HasCompact>(#[codec(compact)] T);
+
+fn main() {
+	println!("{:02x?}", 69u8.encode());
+	println!("{:02x?}", 69u32.encode());
+	println!("{:02x?}", AsCompact(69u8).encode());
+	println!("{:02x?}", AsCompact(69u32).encode());
+}
+```
+
+```sh
+[45]
+[45, 00, 00, 00]
+[15, 01]
+[15, 01]
+```
+
+- 69 as binary: `0b1000101` = `[0x45]`.
+- Add `01` to the least significant bits.
+- `0b100010101` = `[0x15, 0x01]` = 277 as decimal.
+
+---
+
+### Compact Integers: 65535 (u16::MAX)
+
+```rust
+use parity_scale_codec::{Encode, HasCompact};
+
+#[derive(Encode)]
+struct AsCompact<T: HasCompact>(#[codec(compact)] T);
+
+fn main() {
+	println!("{:02x?}", 65535u16.encode());
+	println!("{:02x?}", 65535u32.encode());
+	println!("{:02x?}", AsCompact(65535u16).encode());
+	println!("{:02x?}", AsCompact(65535u32).encode());
+}
+```
+
+```sh
+[ff, ff]
+[ff, ff, 00, 00]
+[fe, ff, 03, 00]
+[fe, ff, 03, 00]
+```
+
+- 65535 as binary: `0b1111111111111111` = `[0xff, 0xff]`.
+- Add `10` to the least significant bits.
+- `0b111111111111111110` = `[0xfe, 0xff, 0x03, 0x00]`: 262142 as decimal.
+
+---
+
+### Compact Integers Are "Backwards Compatible"
+
+- For any unsigned integer value, regardless of the size/type , there is only one compact encoding.
+- As you can see, you are able to "upgrade" a type without affecting the encoding.
+
+```rust
+println!("{:02x?}", Compact::<u32>::from(1024).encode());
+println!("{:02x?}", Compact::<u64>::from(1024).encode());
+println!("{:02x?}", Compact::<u128>::from(1024).encode());
+```
+
+---
+
+### Enum
+
+Prefix with index (`u8`), then the value, if any.
+
+```rust
+use parity_scale_codec::Encode;
+
+#[derive(Encode)]
+enum Example {
+	First,
+	Second(u8),
+	Third(Vec<u8>),
+	Fourth,
+}
+
+fn main() {
+	println!("{:02x?}", Example::First.encode());
+	println!("{:02x?}", Example::Second(2).encode());
+	println!("{:02x?}", Example::Third(vec![0, 1, 2, 3, 4]).encode());
+	println!("{:02x?}", Example::Fourth.encode());
+}
+```
+
+```sh
+[00]
+[01, 02]
+[02, 14, 00, 01, 02, 03, 04]
+[03]
+```
+
+---
+
+### Tuple and Struct
+
+Just encode and concatenate the items.
+
+```rust
+use parity_scale_codec::Encode;
+
+#[derive(Encode)]
+struct Example {
+	number: u8,
+	is_cool: bool,
+	optional: Option<u32>,
+}
+
+fn main() {
+	let my_struct = Example {
+		number: 0,
+		is_cool: true,
+		optional: Some(69),
+	};
+	println!("{:02x?}", (0u8, true, Some(69u32)).encode());
+	println!("{:02x?}", my_struct.encode());
+}
+```
+
+```sh
+[00, 01, 01, 45, 00, 00, 00]
+[00, 01, 01, 45, 00, 00, 00]
+```
+
+Notes:
+
+Note that tuple and struct encode the same, even though struct has named fields.
+
+---
+
+## Embedded Compact
+
+```rust
+use parity_scale_codec::Encode;
+
+#[derive(Encode)]
+struct Example {
+	number: u64,
+	#[codec(compact)]
+	compact_number: u64,
+}
+
+#[derive(Encode)]
+enum Choices {
+	One(u64, #[codec(compact)] u64),
+}
+
+fn main() {
+	let my_struct = Example { number: 42, compact_number: 1337 };
+	let my_choice = Choices::One(42, 1337);
+	println!("{:02x?}", my_struct.encode());
+	println!("{:02x?}", my_choice.encode());
+}
+```
+
+```sh
+[2a, 00, 00, 00, 00, 00, 00, 00, e5, 14]
+[00, 2a, 00, 00, 00, 00, 00, 00, 00, e5, 14]
+```
+
+---
+
+### Unit, Bool, Option, and Result
+
+```rust
+use parity_scale_codec::Encode;
+
+fn main() {
+	println!("{:02x?}", ().encode());
+	println!("{:02x?}", true.encode());
+	println!("{:02x?}", false.encode());
+	println!("{:02x?}", Ok::<u32, ()>(42u32).encode());
+	println!("{:02x?}", Err::<u32, ()>(()).encode());
+	println!("{:02x?}", Some(42u32).encode());
+	println!("{:02x?}", None::<u32>.encode());
+}
+```
+
+```sh
+[]
+[01]
+[00]
+[00, 2a, 00, 00, 00]
+[01]
+[01, 2a, 00, 00, 00]
+[00]
+```
+
+---
+
+### Arrays, Vectors, and Strings
+
+- Arrays: Just concatenate the items.
+- Vectors: Also prefix with length (compact encoded).
+- String: Just `Vec<u8>` as utf-8 characters.
+
+```rust
+use parity_scale_codec::Encode;
+
+fn main() {
+	println!("{:02x?}", [0u8, 1u8, 2u8, 3u8, 4u8].encode());
+	println!("{:02x?}", vec![0u8, 1u8, 2u8, 3u8, 4u8].encode());
+	println!("{:02x?}", Compact::<u32>::from(5).encode());
+	println!("{:02x?}", "hello".encode());
+	println!("{:02x?}", vec![0u8; 1024].encode());
+	println!("{:02x?}", Compact::<u32>::from(1024).encode());
+}
+```
+
+```sh
+[00, 01, 02, 03, 04]
+[14, 00, 01, 02, 03, 04]
+[14]
+[14, 68, 65, 6c, 6c, 6f]
+[01, 10, 00, 00, ... snip ... , 00]
+[01, 10]
+```
+
+Notes:
+
+Note that the length prefix can be multiple bytes, like the last example.
+
+---
+
+### Decoding
+
+- We can similarly take raw bytes, and decode it into a well known type.
+- Metadata can be used to convey to a program how to decode a type properly...
+- But bad or no information means the proper format for the data cannot be known.
+
+---
+
+### Decoding Examples
+
+```rust
+use parity_scale_codec::{ Encode, Decode, DecodeAll };
+
+fn main() {
+	let array = [0u8, 1u8, 2u8, 3u8];
+	let value: u32 = 50462976;
+
+	println!("{:02x?}", array.encode());
+	println!("{:02x?}", value.encode());
+	println!("{:?}", u32::decode(&mut &array.encode()[..]));
+	println!("{:?}", u16::decode(&mut &array.encode()[..]));
+	println!("{:?}", u16::decode_all(&mut &array.encode()[..]));
+	println!("{:?}", u64::decode(&mut &array.encode()[..]));
+}
+```
+
+```sh
+[00, 01, 02, 03]
+[00, 01, 02, 03]
+Ok(50462976)
+Ok(256)
+Err(Error { cause: None, desc: "Input buffer has still data left after decoding!" })
+Err(Error { cause: None, desc: "Not enough data to fill buffer" })
+```
+
+Notes:
+
+- Decoding can fail
+- Values can decode badly
+
+---
+
+### Decode Limits
+
+- Decoding isn't free!
+- The more complex the decode type, the more computation that will be used to decode the value.
+- Generally you always want to `decode_with_depth_limit`.
+- Substrate uses a limit of 256.
+
+---
+
+### Decode Bomb
+
+Here is an example of a decode bomb.
+
+```rust
+use parity_scale_codec::{ Encode, Decode, DecodeLimit };
+
+#[derive(Encode, Decode, Debug)]
+enum Example {
+	First,
+	Second(Box<Self>),
+}
+
+fn main() {
+	let bytes = vec![1, 1, 1, 1, 1, 0];
+	println!("{:?}", Example::decode(&mut &bytes[..]));
+	println!("{:?}", Example::decode_with_depth_limit(10, &mut &bytes[..]));
+	println!("{:?}", Example::decode_with_depth_limit(3, &mut &bytes[..]));
+}
+```
+
+```sh
+Ok(Second(Second(Second(Second(Second(First))))))
+Ok(Second(Second(Second(Second(Second(First))))))
+Err(Error { cause: Some(Error { cause: Some(Error { cause: Some(Error { cause: Some(Error { cause: None, desc: "Maximum recursion depth reached when decoding" }), desc: "Could not decode `Example::Second.0`" }), desc: "Could not decode `Example::Second.0`" }), desc: "Could not decode `Example::Second.0`" }), desc: "Could not decode `Example::Second.0`" })
+```
+
+Note:
+
+question to ask: Will encoding of `T` or `Box<T>` differ? no
+
+---
+
+### Exceptions: BTreeSet
+
+- BTreeSet will decode from an unordered set, but will also order them as a result.
+- Be careful... this one isn't bijective.
+
+```rust
+use parity_scale_codec::{ Encode, Decode, alloc::collections::BTreeSet };
+
+fn main() {
+	let vector = vec![4u8, 3u8, 2u8, 1u8, 0u8];
+	let vector_encoded = vector.encode();
+	let btree = BTreeSet::<u8>::decode(&mut &vector_encoded[..]).unwrap();
+	let btree_encoded = btree.encode();
+
+	println!("{:02x?}", vector_encoded);
+	println!("{:02x?}", btree_encoded);
+}
+```
+
+```sh
+[14, 04, 03, 02, 01, 00]
+[14, 00, 01, 02, 03, 04]
+```
+
+note: SCALE is bijective within one type.
+
+---
+
+### Optimizations and Tricks
+
+- `DecodeLength`: Read the length of a collection (like `Vec`) without decoding everything.
+- `EncodeAppend`: Append an item without decoding all the other items. (like `Vec`)
+
+Note:
+
+https://paritytech.github.io/polkadot-sdk/master/frame_support/storage/trait.StorageDecodeLength.html?search=DecodeLength
+https://paritytech.github.io/polkadot-sdk/master/frame_support/storage/trait.StorageDecodeLength.html?search=EncodeAppend
+
+---
+
+### Implementations
+
+SCALE Codec has been implemented in other languages, including:
+
+- Python: [`polkascan/py-scale-codec`](https://github.com/polkascan/py-scale-codec)
+- Golang: [`itering/scale.go`](https://github.com/itering/scale.go)
+- C: [`MatthewDarnell/cScale`](https://github.com/MatthewDarnell/cScale)
+- C++: [`soramitsu/scale-codec-cpp`](https://github.com/soramitsu/scale-codec-cpp)
+- JavaScript: [`polkadot-js/api`](https://github.com/polkadot-js/api)
+- TypeScript: [`scale-ts`](https://github.com/unstoppablejs/unstoppablejs/tree/main/packages/scale-ts#scale-ts)
+- AssemblyScript: [`LimeChain/as-scale-codec`](https://github.com/LimeChain/as-scale-codec)
+- Haskell: [`airalab/hs-web3`](https://github.com/airalab/hs-web3/tree/master/packages/scale)
+- Java: [`emeraldpay/polkaj`](https://github.com/emeraldpay/polkaj)
+- Ruby: [`wuminzhe/scale_rb`](https://github.com/wuminzhe/scale_rb)
+
+---
+
+## Missing Some Metadata?
+
+- To make SCALE useful as an encoding format within the Substrate and Polkadot ecosystem, we need to
+  figure out a way to provide **metadata** about all the types we will expect, and when we will expect
+  them.
+
+- HINT: We do.
+
+---
+
+### Remember, in the end of the day, everything is just 0's and 1's.
+
+---
+
+## Additional Resources! 😋
+
+> Check speaker notes (click "s" 😉)
+
+<img width="300px" rounded src="../../../assets/img/5-Substrate/thats_all_folks.png" />
+
+Notes:
+
+https://www.reddit.com/r/RISCV/comments/131ssuk/why_exactly_riscv_is_little_endian/
diff --git a/content/6-Protocol_On-Chain/Substrate/9-Substrate-FRAME-Tips-Tricks-slides.md b/content/6-Protocol_On-Chain/Substrate/9-Substrate-FRAME-Tips-Tricks-slides.md
new file mode 100644
index 00000000..799ca46c
--- /dev/null
+++ b/content/6-Protocol_On-Chain/Substrate/9-Substrate-FRAME-Tips-Tricks-slides.md
@@ -0,0 +1,1300 @@
+---
+title: Substrate/FRAME Tips and Tricks
+description: Substrate and FRAME Tips and Tricks for Web3 Engineers
+---
+
+# Substrate / FRAME Tips and Tricks
+
+Notes:
+
+- A random collection of things that you should probably know about.
+- These are relevant for coding in FRAME and Substrate.
+
+---
+
+# Part 0 FRAMELess Assignment Retro
+
+---v
+
+## Formatter
+
+`rustfmt` It is a good thing, please use it!
+
+---v
+
+## Options --> Results
+
+```rust
+let signer_balance = Runtime::get_state::<AccountBalance>(&Self::get_storage_key(&signer));
+match signer_balance {
+	Some(_) => (),
+	None => {return Err(TransactionValidityError::Invalid(InvalidTransaction::BadSigner))},
+};
+```
+
+```rust
+let signer_balance = Runtime::get_state::<AccountBalance>(&Self::get_storage_key(&signer))
+	.ok_or(TransactionValidityError::Invalid(InvalidTransaction::BadSigner))?;
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+https://doc.rust-lang.org/std/option/enum.Option.html#method.ok_or
+https://doc.rust-lang.org/std/option/enum.Option.html#method.ok_or_else
+
+---v
+
+## `expect` for Impossible Panics
+
+```rust
+if ext.function.tip.is_some() {
+	let tip_amount = ext.function.tip.unwrap();
+}
+```
+
+```rust
+if ext.function.tip.is_some() {
+  // ..
+  // ..
+  // ..
+  // ..
+	let tip_amount = ext.function.tip.expect("checked to be some; qed");
+}
+```
+
+<!-- .element: class="fragment" -->
+
+---
+
+# Part 1 Substrate Stuff
+
+---
+
+## `<Type as Trait>::AssociatedType`
+
+- The single most useful Rust syntactic detail that you _MUST_ know.
+
+Notes:
+
+what is a type? A struct is a type. An unum is a type. all primitives are type. A lot of things are
+types.
+
+---v
+
+### `<Type as Trait>::AssociatedType`
+
+Example:
+
+```rust [1-4|1-8|1-12|1-100]
+trait Config {
+  type Extrinsic
+  type Header: HeaderT
+}
+
+pub type ExtrinsicFor<C> = <C as Config>::Extrinsic;
+fn process_extrinsic<C>(e: ExtrinsicFor<C>) { .. }
+
+trait HeaderT {
+  type Number;
+}
+
+pub type NumberFor<C> = <<C as Config>::Header as HeaderT>::Number;
+```
+
+Notes:
+
+turbo fish
+fully qualified syntax.
+
+---
+
+## The `std` Paradigm
+
+`std` <-> `core` <-> `no_std`
+
+Notes:
+
+- Recap:
+  - `std` is the interface to the common OS-abstractions.
+  - `core` is a subset of `std` that makes no assumption about the operating system.
+- a `no_std` crate is one that relies on `core` rather than `std`.
+
+---v
+
+### Cargo Features
+
+- Way to compile different code via flags.
+- Crates define some features in their `Cargo.toml`
+- Crates can conditionally enable features of their dependencies as well.
+
+```toml
+[dependencies]
+other-stuff = { version = "1.0.0" }
+
+[features]
+default = [""]
+additional-features = ["other-stuff/on-steroids"]
+```
+
+Notes:
+
+imagine that you have a crate that has some additional features that are not always needed. You put
+that behind a feature flag called `additional-features`.
+
+---v
+
+### Cargo Features: Substrate Wasm Crates
+
+```toml
+[dependencies]
+dep1 = { version = "1.0.0", default-features = false }
+dep2 = { version = "1.0.0", default-features = false }
+
+[features]
+default = ["std"]
+std = [
+  "dep1/std"
+  "dep2/std"
+]
+```
+
+Notes:
+
+every crate will have a feature "std". This is a flag that you are compiling with the standard
+library. This is the default.
+
+Then, bringing a dependency with `default-features = false` means by default, don't enable this
+dependencies "std".
+
+Then, in `std = ["dep/std"]` you are saying "if my std is enabled, enable my dependencies std as
+well".
+
+- The name "`std`" is just an idiom in the rust ecosystem.
+- `no_std` does NOT mean Wasm!
+- `std` does not mean native!
+
+But in substrate, it kinda means like that:
+
+std => native
+no_std => wasm
+
+---v
+
+### The `std` Paradigm
+
+- All crates in substrate that eventually compile to Wasm:
+
+```rust
+#![cfg_attr(not(feature = "std"), no_std)]
+```
+
+---v
+
+### The `std` Paradigm: Adding dependencies
+
+```sh
+error: duplicate lang item in crate sp_io (which frame_support depends on): panic_impl.
+  |
+  = Notes:
+
+
+ the lang item is first defined in crate std (which serde depends on)
+
+error: duplicate lang item in crate sp_io (which frame_support depends on): oom.
+  |
+  = Notes:
+
+
+ the lang item is first defined in crate std (which serde depends on)
+```
+
+---v
+
+### The `std` Paradigm
+
+A subset of the standard types in rust that also exist in rust `core` are re-exported from
+[`sp_std`](https://paritytech.github.io/polkadot-sdk/master/sp_std/index.html).
+
+```rust
+sp_std::prelude::*;
+```
+
+Notes:
+
+Hashmap not exported due to non-deterministic concerns.
+floats are usable, but also non-deterministic! (and I think they lack `encode`, `decode` impl)
+interesting to look at `if_std` macro in `sp_std`.
+
+---
+
+## Logging And Prints In The Runtime.
+
+- First, why bother? let's just add as many logs as we want into the runtime.
+
+<!-- .element: class="fragment" -->
+
+- Size of the wasm blob matters..
+
+<!-- .element: class="fragment" -->
+
+- Any logging increases the size of the Wasm blob. **String literals** are stored somewhere in your
+  program!
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Logging And Prints In The Runtime.
+
+```rust
+#[derive(sp_std::fmt::Debug)]
+struct LONG_AND_BEAUTIFUL_NAME {
+  plenty: u32,
+  of: u32,
+  fields: u32,
+  with: u32,
+  different: u32
+  names: u32
+}
+```
+
+will add a lot of string literals to your wasm blob.
+
+Notes:
+
+- `wasm2wat polkadot_runtime.wasm > dump | rg stripped`
+- Should get you the `.rodata` (read-only data) line of the wasm blob, which contains all the logging
+  noise.
+- This contains string literals form errors, logs, metadata, etc.
+
+---v
+
+### Logging And Prints In The Runtime.
+
+`sp_std::fmt::Debug` vs `sp_debug_derive::RuntimeDebug`
+
+Notes:
+
+https://paritytech.github.io/substrate/master/sp_debug_derive/index.html
+
+---v
+
+### Logging And Prints In The Runtime.
+
+```rust
+#[derive(RuntimeDebug)]
+pub struct WithDebug {
+    foo: u32,
+}
+
+impl ::core::fmt::Debug for WithDebug {
+    fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
+        #[cfg(feature = "std)]
+        {
+          fmt.debug_struct("WithRuntimeDebug")
+            .field("foo", &self.foo)
+            .finish()
+        }
+        #[cfg(not(feature = "std))]
+        {
+          fmt.write("<wasm:stripped>")
+        }
+    }
+}
+```
+
+---v
+
+### Logging And Prints In The Runtime.
+
+- Once types implement `Debug` or `RuntimeDebug`, they can be printed. Various ways:
+- If you only want something in tests, native builds etc
+
+```rust
+sp_std::if_std! {
+  println!("hello world!");
+  dbg!(foo);
+}
+```
+
+---v
+
+### Logging And Prints In The Runtime.
+
+- Or you can use the common `log` crate
+
+```rust
+log::info!(target: "foo", "hello world!");
+log::debug!(target: "bar", "hello world! ({})", 10u32);
+```
+
+---v
+
+### Logging And Prints In The Runtime.
+
+- But `log` crate doesn't doo much in itself! it needs two additional steps to work:
+
+1. `// $ RUST_LOG=foo=debug,bar=trace cargo run`
+2. `sp_tracing::try_init_simple()`
+
+Notes:
+
+https://paritytech.github.io/polkadot-sdk/master/sp_tracing/index.html
+
+Log statements are only evaluated if the corresponding level and target is met.
+
+```rust
+/// only executed if `RUST_LOG=KIAN=trace`
+frame_support::log::trace!(target: "KIAN", "({:?})", (0..100000).into_iter().collect());
+```
+
+`log` in rust does not do anything -- it only tracks what needs to be logged. Then you need a logger
+to actually export them. In rust this is often `env_logger` or `sp_tracing` in substrate tests.
+
+In the runtime, the log messages are sent via the host functions to the client to be printed.
+
+If the interface is built with `disable-logging`, it omits all log messages.
+
+---
+
+## Arithmetic Helpers, and the `f32`, `f64` Story.
+
+- Floating point numbers have different standards, and (**_slightly_**) different implementations on
+  different architectures and vendors.
+
+- If my balance is `10.000000000000001` DOT on one validator and `10.000000000000000` DOT on another validator, game over for your consensus 😮‍💨.
+
+---v
+
+### PerThing.
+
+```python
+> .2 + .2 + .2 == .6
+> false
+```
+
+```
+> a = 10
+> b = 0.1
+> c = 0.2
+> a*(b+c) == a*b + a*c
+> false
+```
+
+- Google "weird float behavior" for more entertainment around this.
+
+---v
+
+### PerThing.
+
+- We store ratios and such in the runtime with "Fixed-Point" arithmetic types.
+
+```rust
+struct Percent(u8);
+
+impl Percent {
+  fn new(x: u8) {
+    Self(x.min(100));
+  }
+}
+
+impl Mul<u32> for Percent {
+  ...
+}
+```
+
+---v
+
+### PerThing.
+
+```rust
+use sp_arithmetic::Perbill;
+
+let p = Perbill::from_part_parts(1_000_000_000u32 / 4);
+let p = Perbill::from_percent(25);
+let p = Perbill::from_rational(1, 4);
+
+> p * 100u32;
+> 25u32;
+```
+
+- Some precision concerns exist, but that's a story for another day.
+
+---v
+
+### Fixed Point Numbers
+
+`Per-thing` is great for representing `[0, 1]` range.
+
+What if we need more?
+
+```
+100 ~ 1
+200 ~ 2
+300 ~ 3
+350 ~ 3.5
+```
+
+---v
+
+### Fixed Point Numbers
+
+```rust
+use sp_arithmetic::FixedU64;
+
+let x = FixedU64::from_rational(5, 2);
+let y = 10u32;
+let z = x * y;
+> 25
+```
+
+---v
+
+### Arithmetic Types
+
+- See [`sp-arithmetic`](https://paritytech.github.io/polkadot-sdk/master/sp_arithmetic/index.html) to
+  learn more.
+
+Notes:
+
+- [`U256`](https://paritytech.github.io/polkadot-sdk/master/sp_core/struct.U256.html), `U512`: battle-tested since the ethereum days.
+- [substrate-fixed](https://github.com/encointer/substrate-fixed): community project. Supercharged `PerThing` and `Fixed`.
+- [`big_uint.rs`](https://paritytech.github.io/polkadot-sdk/master/sp_arithmetic/biguint/index.html) (unaudited)
+
+```rust
+pub struct BigUint {
+	/// digits (limbs) of this number (sorted as msb -> lsb).
+	pub(crate) digits: Vec<Single>,
+}
+```
+
+---
+
+### Fallibility: Math Operations
+
+Things like **addition**, **multiplication**, **division** could all easily fail.
+
+<div>
+
+- Panic
+  - `u32::MAX * 2 / 2` (in debug builds)
+  - `100 / 0`
+    s
+  </div>
+
+<!-- .element: class="fragment" -->
+
+<div>
+
+- Overflow
+  - `u32::MAX * 2 / 2` (in release builds)
+
+</div>
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Fallibility: Math Operations
+
+- `Checked` -- prevention ✋🏻
+
+  ```
+  if let Some(outcome) = a.checked_mul(b) { ... } else { ... }
+  ```
+
+- `Saturating` -- silent recovery 🤫
+
+  ```
+  let certain_output = a.saturating_mul(b);
+  ```
+
+Notes:
+
+Why would you ever want to saturate? only in cases where you know if the number is overflowing,
+other aspects of the system is so fundamentally screwed that there is no point in doing any kind of
+recovery.
+
+There's also `wrapping_op` and `carrying_op` etc on all rust primitives, but not quite
+relevant.
+
+https://doc.rust-lang.org/std/primitive.u32.html#method.checked_add
+https://doc.rust-lang.org/std/primitive.u32.html#method.saturating_add
+
+Also substrate's version of the same:
+https://paritytech.github.io/polkadot-sdk/master/sp_arithmetic/traits/trait.SaturatedConversion.html
+
+---v
+
+### Fallibility: Conversion
+
+```rust
+fn main() {
+    let a = 1000u32 as u8;
+    println!("{}", a); //
+}
+```
+
+Notes:
+
+conversion of primitive number types is also a common point of error. Avoid `as`.
+
+---v
+
+### Fallibility: Conversion
+
+- Luckily, rust is already pretty strict for the primitive types.
+- `TryInto` / `TryFrom` / `From` / `Into`
+
+```rust
+impl From<u16> for u32 {
+  fn from(x: u16) -> u32 {
+    x as u32 // ✅
+  }
+}
+```
+
+<!-- .element: class="fragment" -->
+
+```rust
+impl TryFrom<u32> for u16 {
+  fn try_from(x: u32) -> Result<u16, _> {
+    if x >= u16::MAX { Err(_) } else { Ok(x as u16) }
+  }
+}
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+typically you don't implement `Into` and `TryInto`, because of blanket impls. See:
+https://doc.rust-lang.org/std/convert/trait.From.html
+
+for any T and U, `impl From<T> for U` implies `impl Into<U> for T`
+
+---v
+
+### Fallibility: Conversion
+
+- `struct Foo<T: From<u32>>`
+
+T is u32 or larger.
+
+<!-- .element: class="fragment" -->
+
+- `struct Foo<T: Into<u32>>`
+
+`T` is u32 or smaller.
+
+<!-- .element: class="fragment" -->
+
+- `struct Foo<T: TryInto<u32>>`
+
+`T` can be any of numeric types.
+
+<!-- .element: class="fragment" -->
+
+---
+
+# Part 2: FRAME Stuff
+
+---
+
+## `trait Get`
+
+A very basic, yet very substrate-idiomatic way to pass _values_ through _types_.
+
+```rust
+pub trait Get<T> {
+  fn get() -> T;
+}
+```
+
+```rust
+// very basic blanket implementation, which you should be very versed in reading.
+impl<T: Default> Get<T> for () {
+  fn get() -> T {
+    T::default()
+  }
+}
+```
+
+<!-- .element: class="fragment" -->
+
+```rust
+struct Foo<G: Get<u32>>;
+let foo = Foo<()>;
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+implementing defaults for `()` is a very FRAME-idiomatic way of doing things.
+
+---v
+
+### `trait Get`
+
+```rust
+parameter_types! {
+  pub const Foo: u32 = 10;
+}
+```
+
+```rust
+// expands to:
+pub struct Foo;
+impl Get<u32> for Foo {
+  fn get() -> u32 {
+    10;
+  }
+}
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+You have implemented this as a part of your rust exam.
+
+---
+
+## `bounded`
+
+- `BoundedVec`, `BoundedSlice`, `BoundedBTreeMap`
+
+```rust
+#[derive(Encode, Decode)]
+pub struct BoundedVec<T, S: Get<u32>>(
+  pub(super) Vec<T>,
+  PhantomData<S>,
+);
+```
+
+Notes:
+
+`PhantomData`?
+
+---v
+
+### `bounded`
+
+- Why not do a bounded type like this? 🤔
+
+```rust
+#[cfg_attr(feature = "std", derive(Serialize))]
+#[derive(Encode)]
+pub struct BoundedVec<T>(
+  pub(super) Vec<T>,
+  u32,
+);
+```
+
+Notes:
+
+_`Get` trait is a way to convey values through types. The type system is mostly for compiler, and
+has minimal overhead at runtime._
+
+---
+
+## `trait Convert`
+
+```rust
+pub trait Convert<A, B> {
+	fn convert(a: A) -> B;
+}
+```
+
+```rust
+pub struct Identity;
+// blanket implementation!
+impl<T> Convert<T, T> for Identity {
+	fn convert(a: T) -> T {
+		a
+	}
+}
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+this one's much simpler, but good excuse to teach them blanket implementations.
+
+---v
+
+### Example of `Get` and `Convert`
+
+```rust
+/// Some configuration for my module.
+trait Config {
+  /// Something that gives you a `u32`.
+  type MaximumSize: Get<u32>;
+  /// Something that is capable of converting `u64` to `u32`,
+  /// which is pretty damn hard.
+  type Convertor: Convertor<u64, u32>;
+}
+```
+
+```rust
+struct Runtime;
+impl Config for Runtime {
+  type MaximumSize = ();
+  type Convertor = SomeType
+}
+```
+
+<!-- .element: class="fragment" -->
+
+```rust
+<Runtime as Config>::Convertor::convert(_, _);
+```
+
+<!-- .element: class="fragment" -->
+
+```rust
+fn generic_fn<T: Config>() { <T as Config>::Convertor::convert(_, _)}
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+often times, in examples above, you have to use this syntax: https://doc.rust-lang.org/book/ch19-03-advanced-traits.html#fully-qualified-syntax-for-disambiguation-calling-methods-with-the-same-name
+
+---
+
+## Implementing Traits For Tuples
+
+```rust
+struct Module1;
+struct Module2;
+struct Module3;
+
+trait OnInitialize {
+  fn on_initialize();
+}
+
+impl OnInitialize for Module1 { fn on_initialize() {} }
+impl OnInitialize for Module2 { fn on_initialize() {} }
+impl OnInitialize for Module3 { fn on_initialize() {} }
+```
+
+How can I easily invoke `OnInitialize` on all 3 of `Module1, Module2, Module3`?
+
+Notes:
+
+Alternative, but this needs allocation:
+
+```
+struct Module1;
+struct Module2;
+struct Module3;
+
+trait OnInitializeDyn {
+  fn on_initialize(&self);
+}
+
+impl OnInitializeDyn for Module1 { fn on_initialize(&self) {} }
+impl OnInitializeDyn for Module2 { fn on_initialize(&self) {} }
+impl OnInitializeDyn for Module3 { fn on_initialize(&self) {} }
+
+fn main() {
+    let x: Vec<Box<dyn OnInitializeDyn>> = vec![Box::new(Module1), Box::new(Module2)];
+    x.iter().for_each(|i| i.on_initialize());
+}
+```
+
+---v
+
+### Implementing Traits For Tuples
+
+```rust
+Impl<A, B, C> OnInitialize for (A, B, C)
+where
+  A: OnInitialize,
+  B: OnInitialize,
+  C: OnInitialize,
+{
+  fn on_initialize() {
+    A::on_initialize();
+    B::on_initialize();
+    C::on_initialize();
+  }
+}
+```
+
+```
+// fully-qualified syntax - turbo-fish.
+<(Module1, Module2, Module3) as OnInitialize>::on_initialize();
+```
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+**Tuples** are the natural way to group **types** together (analogous to have a **vector** is the natural way to group **values** together..)
+
+---v
+
+### Implementing Traits For Tuples
+
+Modern syntax of making a trait "_tuple-call-able_"
+
+```rust
+// In the most basic form:
+#[impl_for_tuples(30)]
+pub trait OnTimestampSet<Moment> {
+	fn on_timestamp_set(moment: Moment);
+}
+```
+
+Notes:
+
+https://docs.rs/impl-trait-for-tuples/latest/impl_trait_for_tuples/
+
+Only problem: A lot of boilerplate. Macros!
+
+Historically, we made this work with `macro_rules!`
+
+```rust
+macro_rules! impl_for_tuples {
+    ( $( $elem:ident ),+ ) => {
+        impl<$( $elem: OnInitialize, )*> OnInitialize for ($( $elem, )*) {
+            fn on_initialize() {
+                $( $elem::on_initialize(); )*
+            }
+        }
+    }
+}
+
+impl_for_tuples!(A, B, C, D);
+impl_for_tuples!(A, B, C, D, E);
+impl_for_tuples!(A, B, C, D, E, F);
+```
+
+---
+
+### Debugging Macros Generated Code
+
+<img rounded src="./img/frame-macro-error.gif" />
+
+Notes:
+
+- Crucial to start debugging from the first macro expansion, not the end!
+- This is only when you are working with a framework like FRAME that is a lot of macro-generated code. If you are writing macros, there are different tricks that you can learn about online.
+
+---
+
+## Defensive Programming
+
+> ..is a form of defensive design to ensure the continuing function of a piece of software under
+> unforeseen circumstances... where **high availability**, **safety**, or **security** is needed.
+
+---v
+
+### Defensive Programming
+
+```
+let maybe_value: Option<u32> = Some(42);
+// ...
+let value = maybe_value.unwrap(); // aggressive programming 🤠
+let value = maybe_value.expect("written evidence") // better ✅
+let value = maybe_value.ok_or(Error::DefensiveError)?; // best ✅
+let value = maybe_value.ok_or(Error::IKnowThisWillNeverHappenButIAmOnlyAnApeAndCanMakeMistakes)?; // best ✅
+```
+
+---v
+
+### Defensive Programming
+
+```rust
+let value = maybe_value.ok_or(Error::IKnowThisWillNeverHappenButIAmOnlyAnApeAndCanMakeMistakes)
+  .map_err(|e| {
+    #[cfg(test)]
+    panic!("An impossible error happened!: {:?}", e);
+    log::error!(target: "..", "defensive error happened: {:?}", e);
+    e
+  })?;
+```
+
+---v
+
+### Defensive Programming
+
+[Defensive traits](https://paritytech.github.io/substrate/master/frame_support/traits/trait.Defensive.html)
+
+```rust
+use frame_support::DefensiveOption;
+let value = maybe_value.defensive_ok_or(Error::IKnowThisWillNeverHappenButIAmOnlyAnApeAndCanMakeMistakes)
+```
+
+---
+
+## Final Words on Panics
+
+1. Panics can happen other than `Err(_).unwrap()`
+
+Notes:
+
+- slice/vector indexing can panic if out of bound
+- `.insert`, `.remove`
+- division by zero.
+
+---v
+
+### Final Words on Panics
+
+2. Panics in Internal API --> Well Documented Code.
+
+---v
+
+### Final Words on Panics
+
+````rust
+/// Multiplies the given input by two.
+///
+/// Some further information about what this does, and where it could be used.
+///
+/// ```
+/// fn main() {
+///   let x = multiply_by_2(10);
+///   assert_eq!(10, 20);
+/// }
+/// ```
+///
+/// ## Panics
+///
+/// Panics under such and such condition.
+fn multiply_by_2(x: u32) -> u32 { .. }
+````
+
+Notes:
+
+- Speaking of documentation, [here's a very good guideline](https://doc.rust-lang.org/rustdoc/how-to-write-documentation.html)!
+
+---v
+
+### Final Words on Panics
+
+- Try and not be this guy:
+
+```rust
+/// This function works with module x and multiples the given input by two. If
+/// we optimize the other variant of it, we would be able to achieve more
+/// efficiency but I have to think about it. Probably can panic if the input
+/// overflows u32 lolololooooo
+fn multiply_by_2(x: u32) -> u32 { .. }
+```
+
+---
+
+## Additional Resources! 😋
+
+<img width="300px" rounded src="../../../assets/img/5-Substrate/thats_all_folks.png" />
+
+> Check speaker notes (click "s" 😉)
+
+> Good luck with FRAME!
+
+Notes:
+
+- Rust didn't have u128 until not too long ago! https://github.com/paritytech/substrate/pull/163/files
+- `TryFrom`/`TryInto` are also not too old! https://github.com/paritytech/substrate/pull/163/files#r188938077
+- Remove `As`, which tried to fill the lack of `TryFrom/TryInto` https://github.com/paritytech/substrate/pull/2602
+- Runtime Logging PR: https://github.com/paritytech/substrate/pull/3821
+
+- Impl trait for tuples:
+
+  - https://stackoverflow.com/questions/64332037/how-can-i-store-a-type-in-an-array
+  - https://doc.rust-lang.org/book/ch17-02-trait-objects.html#trait-objects-perform-dynamic-dispatch
+  - https://doc.rust-lang.org/book/ch19-03-advanced-traits.html#fully-qualified-syntax-for-disambiguation-calling-methods-with-the-same-name
+  - https://turbo.fish/
+  - https://techblog.tonsser.com/posts/what-is-rusts-turbofish
+  - https://docs.rs/impl-trait-for-tuples/latest/impl_trait_for_tuples/
+
+- std/no_std
+  - https://paritytech.github.io/substrate/master/sp_std/index.html
+  - https://doc.rust-lang.org/core/index.html
+  - https://doc.rust-lang.org/std/index.html
+  - https://rust-lang.github.io/api-guidelines/naming.html#feature-names-are-free-of-placeholder-words-c-feature
+
+### Feedback After Lecture:
+
+- Update on defensive ops: https://github.com/paritytech/substrate/pull/12967
+- Next time, talk about making a storage struct be `<T: Config>`.
+- SignedExtension should technically be part of the substrate module. Integrate it in the
+  assignment, perhaps.
+- A section about `XXXNoBound` traits.
+
+---
+
+# Appendix
+
+---
+
+## Generics vs. Associated Types
+
+- What is the difference between generics and associated types?
+
+```rust
+trait Block<Extrinsic> {
+  fn execute(e: Extrinsic)
+}
+```
+
+vs
+
+```rust
+trait Block {
+  type Extrinsic;
+  fn execute(e: Self::Extrinsic)
+}
+```
+
+Notes:
+
+In cambridge, I did this this. But since students should now know traits really well, I will drop it.
+
+```rust
+trait Engine {
+    fn start() {}
+}
+
+struct BMW;
+impl Engine for BMW {}
+
+trait Brand {
+    fn name() -> &'static str;
+}
+
+trait Car<E: Engine> {
+    type Brand: Brand;
+}
+
+struct KianCarCo;
+impl Brand for KianCarCo {
+  fn name() -> &'static str {
+    "KianCarCo!"
+    }
+}
+
+struct MyCar;
+impl<E: Engine> Car<E> for MyCar {
+    type Brand = MyBrand;
+}
+
+fn main() {
+    // Car<E1>, Car<E2> are different traits!
+
+    // Generics can be bounded, or constrained
+    // impl<E: Engine> Car<E> {}
+    // impl Car<BMW> {}
+
+    // Associated types can:
+    // only be bounded when being defined,
+    // Can be constrained when being implemented, or when the trait is being used.
+    fn some_fn<E: Engine, C: Car<E, Brand = MyBrand>>(car: C) {
+      // and we are told associated types are more like output types, lets get the brand of car
+      let name = <<C as Car<E>>::Brand as Brand>::name();
+    }
+    fn other_fn<C: Car<BMW, Brand = MyBrand>>(car: C) {
+
+    }
+
+    // now, check this out
+}
+```
+
+---v
+
+### Speaking of Traits..
+
+Both generics and associated types can be specified, but the syntax is a bit different.
+
+```rust
+trait Block<Extrinsic> {
+  type Header
+}
+
+fn process_block<B: Block<E1, Header = H1>>(b: B)
+```
+
+---v
+
+### Speaking of Traits..
+
+- Anything that can be expressed with associated types can also be expressed with generics.
+- Associated Types << Generics
+- Associated types usually lead to less boilerplate.
+
+</div>
+
+---
+
+## Defensive Programming Contd.
+
+- First reminder: don't panic, unless if you want to punish someone!
+- `.unwrap()`? no no
+
+<br/>
+
+- be careful with implicit unwraps in standard operations!
+  - slice/vector indexing can panic if out of bound
+  - `.insert`, `.remove`
+  - division by zero.
+
+---v
+
+### Defensive Programming
+
+- When using operations that could panic, comment exactly above it why you are sure it won't panic.
+
+```rust
+let pos = announcements
+  .binary_search(&announcement)
+  .ok()
+  .ok_or(Error::<T, I>::MissingAnnouncement)?;
+// index coming from `binary_search`, therefore cannot be out of bound.
+announcements.remove(pos);
+```
+
+---v
+
+### Defensive Programming: QED
+
+Or when using options or results that need to be unwrapped but are known to be `Ok(_)`, `Some(_)`:
+
+```rust
+let maybe_value: Option<_> = ...
+if maybe_value.is_none() {
+  return "..."
+}
+
+let value = maybe_value.expect("value checked to be 'Some'; qed");
+```
+
+- Q.E.D. or QED is an initialism of the Latin phrase "quod erat demonstrandum", meaning "**which was to be demonstrated**".
+
+---v
+
+### Defensive Programming
+
+When writing APIs that could panic, explicitly document them, just like the core rust documentation.
+
+```rust
+/// Exactly the same semantics as [`Vec::insert`], but returns an `Err` (and is a noop) if the
+/// new length of the vector exceeds `S`.
+///
+/// # Panics
+///
+/// Panics if `index > len`.
+pub fn try_insert(&mut self, index: usize, element: T) -> Result<(), ()> {
+  if self.len() < Self::bound() {
+    self.0.insert(index, element);
+    Ok(())
+  } else {
+    Err(())
+  }
+}
+```
+
+---v
+
+### Defensive Programming
+
+- Speaking of documentation, [here's a very good guideline](https://doc.rust-lang.org/rustdoc/how-to-write-documentation.html)!
+
+````rust
+/// Multiplies the given input by two.
+///
+/// Some further information about what this does, and where it could be used.
+///
+/// ```
+/// fn main() {
+///   let x = multiply_by_2(10);
+///   assert_eq!(10, 20);
+/// }
+/// ```
+///
+/// ## Panics
+///
+/// Panics under such and such condition.
+fn multiply_by_2(x: u32) -> u32 { .. }
+````
+
+---v
+
+### Defensive Programming
+
+- Try and not be this guy:
+
+```rust
+/// This function works with module x and multiples the given input by two. If
+/// we optimize the other variant of it, we would be able to achieve more
+/// efficiency but I have to think about it. Probably can panic if the input
+/// overflows u32.
+fn multiply_by_2(x: u32) -> u32 { .. }
+```
+
+---v
+
+### Defensive Programming
+
+- The overall ethos of defensive programming is along the lines of:
+
+```rust
+// we have good reasons to believe this is `Some`.
+let y: Option<_> = ...
+
+// I am really really sure about this
+let x = y.expect("hard evidence; qed");
+
+// either return a reasonable default..
+let x = y.unwrap_or(reasonable_default);
+
+// or return an error (in particular in dispatchables)
+let x = y.ok_or(Error::DefensiveError)?;
+```
+
+Notes:
+
+But, for example, you are absolutely sure that `Error::DefensiveError` will never happen, can we enforce it better?
+
+---v
+
+### Defensive Programming
+
+```rust
+let x = y
+  .ok_or(Error::DefensiveError)
+  .map_err(|e| {
+    #[cfg(test)]
+    panic!("defensive error happened: {:?}", e);
+
+    log::error!(target: "..", "defensive error happened: {:?}", e);
+  })?;
+```
+
+---v
+
+### Defensive Programming
+
+- Yes: [Defensive traits](https://paritytech.github.io/substrate/master/frame_support/traits/trait.Defensive.html):
+
+```
+// either return a reasonable default..
+let x = y.defensive_unwrap_or(reasonable_default);
+
+// or return an error (in particular in dispatchables)
+let x = y.defensive_ok_or(Error::DefensiveError)?;
+```
+
+It adds some boilerplate to:
+
+1. Panic when `debug_assertions` are enabled (tests).
+1. append a `log::error!`.
diff --git a/content/6-Protocol_On-Chain/Substrate/9-Substrate-Interactions-slides.md b/content/6-Protocol_On-Chain/Substrate/9-Substrate-Interactions-slides.md
new file mode 100644
index 00000000..f9c739e3
--- /dev/null
+++ b/content/6-Protocol_On-Chain/Substrate/9-Substrate-Interactions-slides.md
@@ -0,0 +1,625 @@
+---
+title: Interacting With a Substrate Blockchain
+duration: 60 minutes
+---
+
+# Interacting With a Substrate Blockchain
+
+---
+
+## Before we start
+
+- Find all the commands that will be used in this workshop in the `speaker notes`:
+- Run these two now:
+
+```
+cargo install staging-chain-spec-builder
+cargo install --force --git https://github.com/kianenigma/pba-omni-node.git
+```
+
+Notes:
+
+Install stuff
+cargo install staging-chain-spec-builder
+cargo install --force --git https://github.com/kianenigma/pba-omni-node.git
+
+generate chain-spec file
+chain-spec-builder create --chain-name pba-chain -r ./target/release/wbuild/minimal-template-runtime/minimal_template_runtime.wasm default
+
+add some stuff to `balances.balances`
+
+["5GrwvaEF5zXb26Fz9rcQpDWS57CtERHpNehXCPcNoHGKutQY", 1000000],
+["5FHneW46xGXgs5mUiveU4sbTyGBzmstUspZC92UhjJM694ty", 1000000],
+["5FLSigC9HGRKVhB9FiEo4Y3koPsNmBmLJbpXg2mp1hXcS59Y", 1000000],
+["5DAAnrj7VHTznn2AWBemMuyBwZWs6FNFjdyVXUeYum3PTXFy", 1000000],
+["5HGjWAeFDfFCWPsjFQdVV2Msvz2XtMktvgocEZcCj68kUMaw", 1000000],
+["5CiPPseXPECbkjWCa6MnjNokrgYjMqmKndv2rSnekmSK2DjL", 1000000],
+["5GNJqTPyNqANBkUVMN1LPPrxXnFouWXoe2wNSmmEoLctxiZY", 1000000],
+["5HpG9w8EBLe5XCrbczpwq5TSXvedjrBGCwqxK1iQ7qUsSWFc", 1000000],
+["5Ck5SLSHYac6WFt5UZRSsdJjwmpSZq85fd5TRNAdZQVzEAPT", 1000000],
+["5HKPmK9GYtE1PSLsS1qiYU9xQ9Si1NcEhdeCq9sw5bqu4ns8", 1000000],
+["5FCfAonRZgTFrTd9HREEyeJjDpT397KMzizE6T3DvebLFE7n", 1000000],
+["5CRmqmsiNFExV6VbdmPJViVxrWmkaXXvBrSX8oqBT8R9vmWk", 1000000],
+["5Fxune7f71ZbpP2FoY3mhYcmM596Erhv1gRue4nsPwkxMR4n", 1000000],
+["5CUjxa4wVKMj3FqKdqAUf7zcEMr4MYAjXeWmUf44B41neLmJ", 1000000]
+
+Change chain typw
+
+"chainType": "Development"
+
+"properties": {
+"tokenDecimals": 1,
+"tokenSymbol": "PBA"
+},
+
+Now you are ready for PJS
+
+---
+
+## Running a Substrate Chain
+
+- The 2024 and beyond edition
+- omni-node-driven-future
+
+Note:
+
+https://forum.polkadot.network/t/polkadot-parachain-omni-node-gathering-ideas-and-feedback/7823/4
+
+---v
+
+## Running a Substrate Chain
+
+- A Substrate node was meant to be oblivious to the runtime
+- Truth is that we have cheated a bit for some optimizations over the years
+  - Genesis state
+  - Native runtime for debugging
+
+...
+
+- Now, we are moving back towards removing the native runtime.
+- Node can be fully oblivious to the runtime, except for some _assumptions_:
+  - Consensus, Block/Header format, database type
+
+#### ☯️ !!Omni Nodes!! ☯️
+
+---v
+
+## Running a Substrate Chain
+
+- A runtime template --> `.wasm` file
+  - Exposes some apis that define how the genesis state should be built
+- A `chain-spec` file
+  - Specification of the chain, most notably includes **genesis state**.
+  - Possibly generated with `chain-spec-builder`
+- `./omni-node --chain spec.json --tmp...`
+
+Note:
+
+https://paritytech.github.io/polkadot-sdk/master/sc_chain_spec/index.html
+
+---
+
+## Interacting With a Substrate Blockchain
+
+> How does a user or an application interact with a blockchain?
+
+Notes:
+
+- Wait for 1 answer from students or at least for 10 seconds.
+
+---v
+
+## Interacting With a Substrate Blockchain
+
+- Usually they connect to a public RPC server, i.e. a substrate node that exposes its RPC interface publicly.
+
+<br/>
+
+- Run their own node.
+
+<!-- .element: class="fragment" -->
+
+---v
+
+## Interacting With a Substrate Blockchain
+
+<img style="width: 1200px;" src="../../../assets/img/5-Substrate/dev-4-1-json.svg" />
+
+---
+
+## JSON-RPC
+
+> JSON-RPC is a remote procedure call protocol encoded in JSON. It is similar to the XML-RPC
+> protocol, defining only a few data types and commands.
+
+---v
+
+### JSON-RPC
+
+```json
+{
+  "jsonrpc": "2.0",
+  "method": "subtract",
+  "params": {
+    "minuend": 42,
+    "subtrahend": 23
+  },
+  "id": 3
+}
+```
+
+<br/>
+
+```json
+{
+  "jsonrpc": "2.0",
+  "result": 19,
+  "id": 3
+}
+```
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### JSON-RPC
+
+- Entirely transport agnostic.
+- Substrate based chains expose both `websocket` and `http` (or `wss` and `https`, if desired).
+
+Notes:
+
+- You could choose which port to run the ws or http server on by using the flags `--ws-port` and `--rpc-port`
+  respectively. By default, port 9944 is used.
+
+---v
+
+### JSON-RPC
+
+The RPC methods that a substrate node exposes are scoped and has the pattern `"<scope>_<method>"`.
+
+```sh
+wscat \
+ -c ws://localhost:9944 \
+ -x '{"jsonrpc":"2.0", "id": 42, "method":"rpc_methods" }' \
+ | jq
+```
+
+---v
+
+### JSON-RPC: Scopes
+
+- &shy;<!-- .element: class="fragment" --> `author`: for submitting extrinsic to the chain.
+- &shy;<!-- .element: class="fragment" --> `chain`: for retrieving information about the _blockchain_ data.
+- &shy;<!-- .element: class="fragment" --> `state`: for retrieving information about the _state_ data.
+- &shy;<!-- .element: class="fragment" --> `system`: information about the chain.
+- &shy;<!-- .element: class="fragment" --> `rpc`: information about the RPC endpoints.
+
+Notes:
+recall:
+
+https://docs.rs/sc-rpc-api/latest/sc_rpc_api/
+
+- The full list can also be seen here: https://polkadot.js.org/docs/substrate/rpc/
+- Specs: https://paritytech.github.io/json-rpc-interface-spec/introduction.html
+- Upcoming changes to JSON-RPC api: https://forum.polkadot.network/t/new-json-rpc-api-mega-q-a/3048
+
+---
+
+## Workshop
+
+We will do a transfer twice:
+
+1. Once using the PJS-APPs.
+2. Once manually using RPC.
+
+---v
+
+## Workshop: Step 0
+
+- Complete the steps in the README
+- Open PJS-APPs and connect to your local node.
+
+> Don't forget to run with `--tmp` flag.
+
+- Ideas:
+
+- Play with `--consensus`
+- Try a `transfer`
+
+---v
+
+### Workshop: Check balance
+
+- Query current balance of Alice and Bob.
+
+* To get the storage key: `Developer -> Extrinsics`
+* `System -> Account`
+
+```sh
+wscat \
+  -c ws://localhost:9944 \
+  -x '{"jsonrpc":"2.0", "id": 42, "method":"state_getStorage", "params": [""] }' \
+  | jq
+```
+
+Notes:
+
+- You will learn how the storage key is calculated in FRAME based substrate chains in the FRAME
+  module.
+
+---v
+
+### Workshop: Metadata
+
+- Recall type information is lost in SCALE encoded data.
+- Substrate exposes type information using metadata.
+
+```sh
+wscat \
+  -c ws://localhost:9944 \
+  -x '{"jsonrpc":"2.0", "id": 42, "method":"state_getMetadata" }' \
+  | jq
+```
+
+<br/>
+
+- This itself is Scale Encoded. See [frame-metadata](https://github.com/paritytech/frame-metadata).
+- Derive type of AccountInfo using this metadata.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+- Use PJS app to get frame-metadata: Developer > RPC Calls > state > getMetadata.
+- [Metadata](https://hackmd.io/@ak0n/rJUhmXmK6) with most details not relevant stripped off.
+
+```
+{
+  magicNumber: 1,635,018,093
+  metadata: {
+    V14: {
+      lookup: {
+        types: [
+          {
+            id: 3
+            type: {
+              path: [
+                frame_system
+                AccountInfo
+              ]
+              params: [
+                {
+                  name: Nonce
+                  type: 4
+                }
+                {
+                  name: AccountData
+                  type: 5
+                }
+              ]
+              def: {
+                Composite: {
+                  fields: [
+                    {
+                      name: nonce
+                      type: 4
+                      typeName: Nonce
+                      docs: []
+                    }
+                    {
+                      name: consumers
+                      type: 4
+                      typeName: RefCount
+                      docs: []
+                    }
+                    {
+                      name: providers
+                      type: 4
+                      typeName: RefCount
+                      docs: []
+                    }
+                    {
+                      name: sufficients
+                      type: 4
+                      typeName: RefCount
+                      docs: []
+                    }
+                    {
+                      name: data
+                      type: 5
+                      typeName: AccountData
+                      docs: []
+                    }
+                  ]
+                }
+              }
+              docs: []
+            }
+          }
+
+          ..
+
+          {
+            id: 4
+            type: {
+              path: []
+              params: []
+              def: {
+                Primitive: U32
+              }
+              docs: []
+            }
+          }
+
+          ..
+
+          {
+            id: 5
+            type: {
+              path: [
+                pallet_balances
+                types
+                AccountData
+              ]
+              params: [
+                {
+                  name: Balance
+                  type: 6
+                }
+              ]
+              def: {
+                Composite: {
+                  fields: [
+                    {
+                      name: free
+                      type: 6
+                      typeName: Balance
+                      docs: []
+                    }
+                    {
+                      name: reserved
+                      type: 6
+                      typeName: Balance
+                      docs: []
+                    }
+                    {
+                      name: frozen
+                      type: 6
+                      typeName: Balance
+                      docs: []
+                    }
+                    {
+                      name: flags
+                      type: 7
+                      typeName: ExtraFlags
+                      docs: []
+                    }
+                  ]
+                }
+              }
+              docs: []
+            }
+          }
+
+          ..
+
+
+          {
+            id: 6
+            type: {
+              path: []
+              params: []
+              def: {
+                Primitive: U64
+              }
+              docs: []
+            }
+          }
+
+          ..
+
+          {
+            id: 7
+            type: {
+              path: [
+                pallet_balances
+                types
+                ExtraFlags
+              ]
+              params: []
+              def: {
+                Composite: {
+                  fields: [
+                    {
+                      name: null
+                      type: 8
+                      typeName: u128
+                      docs: []
+                    }
+                  ]
+                }
+              }
+              docs: []
+            }
+          }
+
+          ..
+
+          {
+            id: 8
+            type: {
+              path: []
+              params: []
+              def: {
+                Primitive: U128
+              }
+              docs: []
+            }
+          }
+
+        ]
+      }
+      pallets: [],
+      extrinsic: {},
+      type: 107
+    }
+  }
+}
+```
+
+---v
+
+### Workshop: Decoding balance
+
+- Use [scale decoder](https://www.shawntabrizi.com/substrate-js-utilities/codec/) to decode balance.
+- Use the following type information for AccountInfo.
+
+```json
+{
+  "info": {
+    "nonce": "u32",
+    "ignore": "(u32, u32, u32)",
+    "balance": {
+      "free": "u64",
+      "ignore": "(u64, u64, u128)"
+    }
+  }
+}
+```
+
+Notes:
+The actual type is:
+
+```json
+{
+  "info": {
+    "nonce": "u32",
+    "ignore": "u32",
+    "providers": "u32",
+    "sufficients": "u32",
+    "balance": {
+      "free": "u64",
+      "reserved": "u64",
+      "frozen": "u64",
+      "flags": "u128"
+    }
+  }
+}
+```
+
+---v
+
+### Workshop: Transfer some tokens
+
+- Take PJS help to get the signed extrinsic.
+  - `Developer -> Extrinsics -> Balances -> Transfer`
+- Use the following command to submit the extrinsic.
+
+```sh
+wscat \
+  -c ws://localhost:9944 \
+  -x '{"jsonrpc":"2.0", "id": 42, "method":"author_submitExtrinsic", "params": [""] }' \
+  | jq
+```
+
+- Check balance again for both accounts.
+- What happens to nonce of Alice?
+
+Notes:
+
+- Students will learn how to build the signed extrinsic themselves in their assignment.
+- Let students do the second part themselves.
+
+---
+
+### Workshop: Versions
+
+- Find runtime version of the polkadot and westend chain `state_getRuntimeVersion`.
+- Find node version of the polkadot and westend chain `system_version`.
+- Change RPC provider and see if any of the above value changes?
+
+<br/>
+
+- For runtime version, you read `specVersion` : `1,005,000` as `1.5.0`.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+- `wscat -c wss://polkadot-rpc.dwellir.com -x '{"jsonrpc":"2.0", "id":1, "method":"state_getRuntimeVersion"}' | jq`.
+- `wscat -c wss://polkadot-rpc.dwellir.com -x '{"jsonrpc":"2.0", "id":1, "method":"system_version"}' | jq`.
+- Show polkadot telemetry: https://telemetry.polkadot.io/.
+
+---
+
+### JSON-RPC: Application
+
+- On top of `SCALE` and `JSON-RPC`, a large array of libraries have been built.
+
+- `PJS-API` / `PJS-APPS`
+- future: `PAPI`
+- `subxt`
+- Any many more!
+
+---
+
+## Additional Resources! 😋
+
+> Check speaker notes (click "s" 😉)
+
+Notes:
+
+- see "Client Libraries" here: https://project-awesome.org/substrate-developer-hub/awesome-substrate
+- https://paritytech.github.io/json-rpc-interface-spec/introduction.html
+- Full subxt guide: https://docs.rs/subxt/latest/subxt/book/index.html
+- https://github.com/JFJun/go-substrate-rpc-client
+- https://github.com/polkascan/py-substrate-interface
+- https://github.com/polkadot-api/polkadot-api
+- more here: https://project-awesome.org/substrate-developer-hub/awesome-substrate
+- Listen to James Wilson introducing subxt: https://www.youtube.com/watch?v=aFk6We_Ke1I
+
+---
+
+### JSON-RPC: Mini Activity
+
+In Kusama:
+
+- Find the genesis hash..
+- Number of extrinsics at block 10,000,000.
+- The block number is stored under `twox128("System") ++ twox128("Number")`.
+- Find it now, and at block 10,000,000.
+
+<br/>
+
+- Refer to the "Substrate; Show Me The Code" lecture to find the right RPC endpoints.
+- You have 15 minutes!
+
+Notes:
+
+```sh
+# 10,000,000 in hex
+printf "%x\n" 10000000
+# Genesis hash
+wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"chain_getBlockHash", "params": ["0x0"] }' | jq
+# Hash of the block at height 10,000,000
+wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"chain_getBlockHash", "params": ["0x989680"] }' | jq
+# The block at height 1,000,000
+wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"chain_getBlock", "params": ["0xdcbaa224ab080f2fbf3dfc85f3387ab21019355c392d79a143d7e50afba3c6e9"] }' | jq
+
+# `0x26aa394eea5630e07c48ae0c9558cef702a5c1b19ab7a04f536c519aca4983ac` now.
+wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"state_getStorage", "params": ["0x26aa394eea5630e07c48ae0c9558cef702a5c1b19ab7a04f536c519aca4983ac"] }' | jq
+# `0x26aa394eea5630e07c48ae0c9558cef702a5c1b19ab7a04f536c519aca4983ac` at block 1,000,000.
+wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"state_getStorage", "params": ["0x26aa394eea5630e07c48ae0c9558cef702a5c1b19ab7a04f536c519aca4983ac", "0xdcbaa224ab080f2fbf3dfc85f3387ab21019355c392d79a143d7e50afba3c6e9"] }' | jq
+```
+
+Notice that this number that we get back is the little endian (SCALE) encoded value that we passed in at first.
+
+---
+
+## `subxt`
+
+- Something analogous to `PJS api` for Rust.
+- The real magic is that it generates the types by fetching the metadata at compile time, or linking
+  it statically.
+- ..It might need manual updates when the code, and therefore the metadata changes.
diff --git a/content/6-Protocol_On-Chain/Substrate/README.md b/content/6-Protocol_On-Chain/Substrate/README.md
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+# Substrate
+
+Total time required 2.5 days.
+
+## Lesson Preparation
+
+This module consists of a combination of lectures, activities, and sections of the accompanying exercises to to students at what time.
+As there is a large amount of variance in student experience around Substrate, we want to make sure that we have a variety of content for students of different experience levels.
+
+### Graded Assignment
+
+> **All graded assignments and solutions must remain private to the Academy staff, faculty, and enrolled students!**
+
+There is a private to the Academy graded exercise, in a _template repository_ titled `frameless-node-template--master` that should be introduced after the first lectures are complete.
+Instructors should create a per cohort, **private**, derived from the master copy, make it a template repo, and configure the cohort Github Classroom to use this new repo as an assignment.
+
+The "`px...` assignment problem" sections indicates that students are now capable of completing them with the content so far covered.
+They should be encouraged to start working on them as time allows _outside of class time!_
+They should not zone-out of class to complete this during class time, they should prioritize in-class activities and exercises over working on the assignment!
+
+### Exercises and Activities
+
+There is a private to the Academy graded exercise, in a _template repository_ titled `pba-wasm-executor--master` that should be introduced after the first lectures are complete.
+Instructors should create a per cohort, **write-access granted to the cohort team**, derived from the master copy, make it a template repo, instruct students to use the `<github username/*` branch namespace for any of their work, with `<github username>` acting as their `main` branch.
+Ensure the `main` branch is write protected, by required a PR first`- no one should be able to push to`main`!
+
+## Lesson Schedule
+
+### Day 1
+
+#### Morning
+
+1. [Introduction](./1-Intro-to-Substrate-slides.md) (60m)
+1. [Wasm Meta Protocol](./2-Wasm-Meta-Protocol-slides.md) (90m)
+
+<!-- FIXME where is this? -->
+
+1. Activity: Finding Runtime APIs and Host Functions in Substrate
+
+#### Afternoon
+
+1. Show Me The Code (60m)
+1. [Substrate Interactions](./9-Substrate-Interactions-slides.md) (60m)
+1. FRAMELess Assignment (60m)
+
+### Day 2
+
+#### Morning
+
+1. [Transaction Pool](./4-Transaction-Pool-slides.md) (60m)
+1. [SCALE](./9-SCALE-slides.md) (60m)
+1. [Substrate and FRAME Tips and Tricks](./9-Substrate-FRAME-Tips-Tricks-slides.md)
+
+#### Afternoon
+
+1. FRAMELess Assignment
+
+### Day 3
+
+#### Morning
+
+1. [Substrate Storage](./3-Merklized-Storage-slides.md) (90m)
+1. FRAMELess Assignment
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+---
+title: Introduction to XCM
+description: What it is, why it's necessary, what we'll cover
+duration: 45 minutes
+---
+
+# XCM
+
+---
+
+## On this module, we'll see
+
+<pba-flex center>
+
+- What XCM is
+- What primitives make up XCMs
+- How XCMs are executed
+- The XCM Pallet
+- How to configure systems to work with XCM
+- How to craft XCMs
+
+---
+
+# The problem
+
+Substrate and FRAME encourage an ecosystem of many blockchains.
+
+We don't want every chain to have to do everything.
+
+---v
+
+## Specialization
+
+Specialization allows chains to focus on their particular value proposition and do it well.
+
+---
+
+# The solution
+
+Messaging.
+
+Notes:
+
+In order for chains to use functionality from other chains,
+we need to pass messages from one chain to another.
+
+---v
+
+## How?
+
+<pba-flex center>
+
+- UMP/DMP: Relay <-> Parachains
+- HRMP: Parachain <-> Parachain
+- Bridges: Polkadot <-> Ethereum and more
+
+Notes:
+
+UMP/DMP stands for Upward/Downward Message Passing.
+HRMP piggybacks on UMP and DMP to send messages to sibling parachains, so it uses the relay chain as a relayer.
+These are the current transport protocols we have in Polkadot.
+An upgrade to HRMP is XCMP which won't use the relay chain at all.
+It's not live yet, still being researched and prototyped.
+
+---v
+
+## What?
+
+What messages do we actually send?
+
+---v
+
+### Native messages
+
+The messages could just be the native transactions of each chain.
+
+Notes:
+
+If we have a message passing protocol, we can just allow one chain
+to post transactions to another chain.
+
+This is very simple and useful, but it has some disadvantages.
+
+---v
+
+### Native messages: disadvantages
+
+- Format changes from system to system, it could also change within the same system, e.g. on a runtime upgrade.
+- Common cross-consensus use-cases don't map one-to-one to a single transaction.
+- Different consensus systems have different assumptions e.g. fee payment.
+
+Notes:
+
+- A system which intends to send messages to more than one destination would need to understand how to author a message for each.
+  On that note, even a single destination may alter its native transaction/message format over time.
+  Smart contracts might get upgrades, blockchains might introduce new features or alter existing ones and in doing so change their transaction format.
+- Special tricks may be required to withdraw funds, exchange them and then deposit the result all inside a single transaction.
+  Onward notifications of transfers, needed for a coherent reserve-asset framework, do not exist in chains unaware of others.
+  Some use-cases don't require accounts.
+- Some systems assume that fee payment had already been negotiated, while some do not.
+
+---v
+
+### A better solution
+
+- A domain-specific language that is agnostic to the underlying chain implementing it.
+- Able to express multiple actions in a single message.
+- Flexible enough to accomodate multiple different paradigms.
+
+---
+
+# XCM
+
+> XCM is a **language** for communicating **intentions** between **consensus systems**.
+
+---v
+
+## Language
+
+Cross-chain DSL.
+
+Each message is a script that allows expressing multiple actions.
+
+---v
+
+## Intentions
+
+Blockchains are sovereign entities, the language only expresses what we _want_
+the receiver to do, it can't enforce it.
+
+Verification can be done on another layer, e.g. checking the expected result with a light client.
+
+Notes:
+
+It's up to the receiver to interpret the message and execute the corresponding actions.
+
+Not every chain might implement every intention, for example swaps.
+
+---v
+
+## Consensus systems
+
+We extend the actors to be consensus systems, not only chains.
+
+This includes smart contracts and any system that achieves consensus in some way.
+
+Notes:
+
+Proof-of-authority web2 systems can also be considered consensus systems.
+
+---v
+
+## Versioned
+
+XCM is a **versioned** language.
+
+Each system declares what version they support.
+
+The latest is version 5.
+
+What goes in each version is defined via an RFC process.
+
+Notes:
+
+This protects against runtime upgrades breaking everything.
+
+---
+
+# XCM vs Message Passing
+
+<img src="img/XCM Post truck.png">
+
+Notes:
+
+XCM is akin to the post card from the post office.
+
+It is _not_ a transport protocol.
+
+A post card doesn't send itself!
+
+As we mentioned, XCM != {UMP, DMP, HRMP, XCMP, Bridges}.
+
+It cannot be used to actually "send" any message between systems; its utility is only in expressing what should be done by the receiver.
+Like many aspects core to Substrate, this separation of concerns empowers us to be far more generic and enable much more.
+A post card relies on the postal service to get itself sent towards its receivers, and that is what a messaging protocol does.
+
+The transport layer concerns itself with sending arbitrary blobs, it doesn't care about the format.
+
+---
+
+### Terminology: XCMs
+
+**XCM**, Cross-Consensus Messaging, is the format.
+
+**An XCM** is a Cross-Consensus Message.
+
+It's not called an XCM message,
+
+the same way it's not called an ATM machine.
+
+We can also call them XCM programs, since they are executable.
+
+Notes:
+
+More about their executable nature later.
+
+---
+
+# Summary
+
+<pba-flex center>
+
+- We learned what XCM is and why it's useful.
+- We learned what transport protocols exist in Polkadot.
+
+---
+
+# Questions?
+
+---
+
+# Example Flow
+
+<img src="img/Example Flow - Introduction.png">
+
+Notes:
+
+We'll build towards this during this module.
+
+---
+
+# Next steps
+
+We'll learn about the primitives that make up any XCM.
diff --git a/content/6-Protocol_On-Chain/XCM/2-Primitives-slides.md b/content/6-Protocol_On-Chain/XCM/2-Primitives-slides.md
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+---
+title: XCM Primitives
+description: Locations, assets and instructions
+duration: 2 hours
+---
+
+# XCM Primitives
+
+---v
+
+## What you'll learn
+
+<pba-flex center>
+
+- Locations
+- Assets
+- Instructions
+
+Notes:
+
+Locations: how an XCM references various entities in the network.
+Assets: how an XCM can specify fungible and non-fungible assets.
+Instructions: how an XCM expresses what actions it wants the receiver to perform.
+
+---
+
+# Locations
+
+Way of referencing any entity in the network, for example, the recipient of the message.
+
+<diagram class="mermaid limit size-50">
+graph LR
+    Message(Message)
+    Alice(Alice)--"?"-->Bob(Bob)
+    Alice--"?"-->AssetHub(Asset Hub)
+    Alice--"?"-->Pallet(Pallet)
+    Alice--"?"-->SmartContract(Smart Contract)
+</diagram>
+
+Notes:
+
+The `Location` is sort of the URL for consensus systems.
+A Location can be a scalable multi-shard blockchain such as Polkadot, an ERC-20 asset account on a parachain, a smart contract, etc.
+They can be relative or absolute.
+They don't need to correspond with the actual path the message will take, that's the job of the transport protocol.
+
+---v
+
+## Interior Locations
+
+> Given two consensus systems, A and B. A is **interior** to B if a state change in A implies a state change in B.
+
+Notes:
+
+An example, a smart contract in Ethereum would be interior to Ethereum itself.
+
+---v
+
+## Location hierarchy
+
+<diagram class="mermaid">
+graph TD;
+    Relay(Relay)-->A(Parachain A)
+    Relay-->B(Parachain B)
+    B-->Alice(Account A)
+    B-->Bob(Account B)
+    A-->Pallet(Pallet Contracts)
+    Pallet-->SCA(Smart Contract A)
+    Pallet-->SCB(Smart Contract B)
+</diagram>
+
+Notes:
+
+Locations form a hierarchy using the interior relation.
+
+---v
+
+## Location Representation
+
+<pba-flex center>
+
+```rust
+struct Location {
+    parents: u8,
+    junctions: Junctions,
+}
+```
+
+<div style="margin-bottom: 2rem;"></div>
+
+```rust
+enum Junction {
+    Parachain(u32),
+    AccountId32 { id: [u8; 32], network: Option<NetworkId> },
+    PalletInstance(u8),
+    GeneralIndex(u128),
+    GlobalConsensus(NetworkId),
+    ...
+}
+```
+
+Notes:
+
+Right now Junctions are limited to 8 because of stack space.
+We also don't expect Junctions being more than 8 levels deep.
+
+It's perfectly possible to create locations that don't point anywhere.
+
+---v
+
+### Network Id
+
+<pba-flex center>
+
+```rust
+enum NetworkId {
+    ByGenesis([u8; 32]),
+    ByFork { block_number: u64, block_hash: [u8; 32] },
+    Polkadot,
+    Kusama,
+    Ethereum { chain_id: u64 },
+    BitcoinCore,
+    BitcoinCash,
+    PolkadotBulletin,
+}
+```
+
+</pba-col>
+
+</pba-cols>
+
+Notes:
+
+Junctions are ways to descend the location hierarchy
+
+---v
+
+## Text notation
+
+<pba-flex center>
+
+<pba-cols>
+
+<pba-col>
+
+```rust
+Location {
+    parents: 1,
+    interior: Parachain(50)
+}
+```
+
+</pba-col>
+<pba-col>
+
+-->
+
+</pba-col>
+<pba-col>
+
+```
+../Parachain(50)
+```
+
+</pba-col>
+
+Notes:
+
+This notation comes from an analogy to a file system.
+
+---v
+
+## Universal Location
+
+> The Universal Location is a **theoretical** location. It's the parent of all locations which generate their own consensus. It itself has no parents.
+
+---v
+
+## Universal Location
+
+<diagram class="mermaid limit size-50">
+graph TD;
+    UniversalLocation(Universal Location)-->Polkadot(Polkadot)
+    UniversalLocation-->Kusama(Kusama)
+    UniversalLocation-->Ethereum(Ethereum)
+    UniversalLocation-->Bitcoin(Bitcoin)
+</diagram>
+
+Notes:
+
+We can imagine a hypothetical location that contains all top-level consensus systems.
+
+---v
+
+## Absolute locations
+
+<pba-flex center>
+
+```rust
+pub type InteriorLocation = Junctions;
+```
+
+Sometimes, absolute locations are necessary, e.g. for bridges.
+
+They don't have parents.
+
+The first junction has to be a `GlobalConsensus`.
+
+Notes:
+
+To write an absolute location, we need to know our location relative to the Universal Location.
+
+---v
+
+## What are `Location`s used for?
+
+<pba-flex center>
+
+- Addressing
+- Origins
+- Assets
+- Fees
+- Bridging
+
+---v
+
+## Cross-Chain Origins
+
+When a receiver gets an XCM, a `Location` specifies the sender.
+
+This `Location` is _relative_ to the receiver.
+
+Can be converted into a pallet origin in a FRAME runtime
+
+Used for determining privileges during XCM execution.
+
+Notes:
+
+Reanchoring:
+
+Since `Location`s are relative, when an XCM gets sent over to another chain, the origin location needs to be rewritten from the perspective of the receiver, before the XCM is sent to it.
+
+---
+
+## Location Examples
+
+---v
+
+### Sibling parachain
+
+`../Parachain(1001)`
+
+<diagram class="mermaid">
+graph TD
+    Polkadot(Polkadot)-->AssetHub("📍 AssetHub (1000)")
+    Polkadot-->Collectives("Collectives (1001)")
+</diagram>
+
+Notes:
+
+What does the location resolve to if evaluated on Parachain(1000)?
+
+---v
+
+### Sibling parachain
+
+`../Parachain(1001)`
+
+<diagram class="mermaid">
+graph TD
+    Polkadot(Polkadot)-->AssetHub("📍 AssetHub (1000)")
+    Polkadot-->Collectives("Collectives (1001)")
+    AssetHub-->Polkadot
+    linkStyle 0 opacity:0.3
+    linkStyle 2 stroke-dasharray:5
+</diagram>
+
+---v
+
+### Parachain account
+
+`Parachain(1000)/AccountId32(0x1234...cdef)`
+
+<diagram class="mermaid">
+graph TD
+    Polkadot("📍 Polkadot")-->AssetHub("AssetHub (1000)")
+    Polkadot-->Collectives("Collectives (1001)")
+    AssetHub-->Account("AccountId32 (0x1234...cdef)")
+</diagram>
+
+Notes:
+
+What does the location resolve to if evaluated on the relay chain?
+
+---v
+
+### Parachain account
+
+`Parachain(1000)/AccountId32(0x1234...cdef)`
+
+<diagram class="mermaid">
+graph TD
+    Polkadot("📍 Polkadot")-->AssetHub("AssetHub (1000)")
+    Polkadot-->Collectives("Collectives (1001)"):::disabled
+    AssetHub-->Account("AccountId32 (0x1234...cdef)")
+    linkStyle 1 opacity:0.3
+    classDef disabled opacity:0.3
+</diagram>
+
+---v
+
+### Bridge
+
+`../../GlobalConsensus(Kusama)/Parachain(1000)`
+
+<diagram class="mermaid">
+graph TD
+    Universe(Universal Location)-->Polkadot(Polkadot)
+    Universe-->Kusama(Kusama)
+    Polkadot-->PolkaA("📍 Asset Hub (1000)")
+    Polkadot-->PolkaB(Bridge Hub)
+    PolkaA-->Alice(Alice)
+    PolkaA-->AssetsPallet(Pallet Assets)
+    AssetsPallet-->Asset(USDT)
+    Kusama-->KusamaA("Asset Hub (1000)")
+    Kusama-->KusamaB(Bridge Hub)
+</diagram>
+
+Notes:
+
+Speak to an example of non-parachain multi-location that would use a bridge
+XCM reasons about addressing (as in a postal address) that must include understanding where you are, not just where you are going!
+This will be very powerful later on (Origins)
+
+---v
+
+### Bridge
+
+`../../GlobalConsensus(Kusama)/Parachain(1000)`
+
+<diagram class="mermaid">
+graph TD
+    Universe(Universal Location)-->Polkadot(Polkadot)
+    Universe-->Kusama(Kusama)
+    Polkadot-->PolkaA("📍 Asset Hub (1000)")
+    Polkadot-->PolkaB(Bridge Hub):::disabled
+    PolkaA-->Alice(Alice):::disabled
+    PolkaA-->AssetsPallet(Pallet Assets):::disabled
+    AssetsPallet-->Asset(USDT):::disabled
+    Kusama-->KusamA("Asset Hub (1000)")
+    Kusama-->KusamB(Bridge Hub):::disabled
+    PolkaA-->Polkadot
+    Polkadot-->Universe
+    linkStyle 0 opacity:0.3
+    linkStyle 2 opacity:0.3
+    linkStyle 3 opacity:0.3
+    linkStyle 4 opacity:0.3
+    linkStyle 5 opacity:0.3
+    linkStyle 6 opacity:0.3
+    linkStyle 8 opacity:0.3
+    linkStyle 9 stroke-dasharray:5
+    linkStyle 10 stroke-dasharray:5
+    classDef disabled opacity:0.3
+</diagram>
+
+Notes:
+
+Even with Bridge Hubs, the relative location is what you'd expect.
+Bridge Hubs are just a way for routing messages.
+They are an implementation detail of the transport layer.
+
+---v
+
+### Bridge (actual routing)
+
+<diagram class="mermaid limit size-50">
+graph TD
+    Universe(Universal Location):::disabled-->Polkadot(Polkadot):::disabled
+    Universe-->Kusama(Kusama)
+    Polkadot-->PolkaA("📍 Asset Hub (1000)")
+    Polkadot-->PolkaB(Bridge Hub)
+    PolkaA-->Alice(Alice):::disabled
+    PolkaA-->AssetsPallet(Pallet Assets):::disabled
+    AssetsPallet-->Asset(USDT):::disabled
+    Kusama-->KusamB(Bridge Hub)
+    Kusama-->KusamA("Asset Hub (1000)")
+    PolkaA-->PolkaB
+    PolkaB--"Bridge"-->KusamB
+    KusamB-->Kusama
+    linkStyle 0 opacity:0.3
+    linkStyle 1 opacity:0.3
+    linkStyle 2 opacity:0.3
+    linkStyle 3 opacity:0.3
+    linkStyle 4 opacity:0.3
+    linkStyle 5 opacity:0.3
+    linkStyle 6 opacity:0.3
+    linkStyle 7 opacity:0.3
+    linkStyle 11 stroke-dasharray:5
+    classDef disabled opacity:0.3
+</diagram>
+
+Notes:
+
+The actual message is routed through Bridge Hub.
+
+---v
+
+## Sovereign Accounts
+
+Locations external to the local system can be represented by a local account.
+
+We call this the **sovereign account** of that location.
+
+They are a mapping from a `Location` to an account id.
+
+---v
+
+<diagram class="mermaid">
+graph TD
+    Polkadot(Polkadot)-->A(AssetHub) & B(Collectives)
+    A-->Alice(Alice)
+    B-->AliceSA("Alice's sovereign account")
+</diagram>
+
+Notes:
+
+A sovereign account is an account on one system that is controlled by another on a different system.
+A single account on a system can have multiple sovereign accounts on many other systems.
+In this example, Alice is an account on AssetHub, and it controls a sovereign account on Collectives.
+
+When transferring between consensus systems, the sovereign account is the one that gets the funds on the destination system.
+
+---v
+
+<diagram class="mermaid">
+graph TD
+    Polkadot(Polkadot)-->A(AssetHub) & B(Collectives)
+    A-->Alice(Alice)
+    B-->AliceSA("Alice's sovereign account")
+    B-->ASA("Asset Hub's sovereign account")
+    A-->BSA("Collective's sovereign account")
+</diagram>
+
+---
+
+# Assets
+
+Most messages will deal with assets in some way.
+
+How do we reference these assets?
+
+---v
+
+### Asset Representation
+
+<pba-flex center>
+
+```rust
+struct Asset {
+    pub id: AssetId,
+    pub fun: Fungibility,
+}
+
+struct AssetId(Location); // <- We reuse the location!
+
+enum Fungibility {
+    Fungible(u128),
+    NonFungible(AssetInstance),
+}
+```
+
+Notes:
+
+We use locations, which we've already discussed, to refer to assets.
+
+A Asset is composed of an asset ID and an enum representing the fungibility of the asset.
+Asset IDs are the location that leads to the system that issues it, this can be just an index in an assets pallet, for example.
+
+Assets can also either be fungible or non-fungible:
+Fungible - each token of this asset has the same value as any other
+NonFungible - each token of this asset is unique and cannot be seen as having the same value as any other token under this asset
+
+---v
+
+### Asset filtering and wildcards
+
+<pba-flex center>
+
+```rust
+enum AssetFilter {
+    Definite(Assets),
+    Wild(WildAsset),
+}
+
+enum WildAsset {
+    All,
+    AllOf { id: AssetId, fun: WildFungibility },
+    // Counted variants
+}
+
+enum WildFungibility {
+    Fungible,
+    NonFungible,
+}
+```
+
+Notes:
+
+Sometimes we don't want to specify an asset, but rather filter a collection of them.
+In this case, we can either list all the assets we want or use a wildcard to select all of them.
+In reality, it's better to use the counted variant of the wildcards, for benchmarking.
+
+---
+
+# Instructions
+
+Every XCM is a sequence of instructions.
+
+---v
+
+## Kinds of instructions
+
+<pba-flex center>
+
+- Command
+- Trusted Indication
+- Information
+- System Notification
+
+Notes:
+
+Most instructions are commands.
+We have a few trusted indications mainly for cross-chain transfers.
+Information instructions are meant to carry over information from other systems.
+System notifications notify when particular events happen, we have these for channels and versioning.
+
+---v
+
+### Instruction Examples
+
+<pba-flex center>
+
+```rust
+WithdrawAsset(Assets)
+```
+
+Notes:
+
+This instruction is a command.
+Gets assets from an account to use them during the execution of the message.
+We'll see registers in the next lecture when we talk about the executor.
+It takes the assets from the account specified in the origin register and puts them in the holding register.
+
+---v
+
+### Instruction Examples
+
+<pba-flex center>
+
+```rust
+DepositAsset { assets: AssetFilter, beneficiary: Location }
+```
+
+Notes:
+
+Another command.
+Will deposit all assets matched by the `assets` filter to the account of `beneficiary`.
+
+---v
+
+### Instruction Examples
+
+<pba-flex center>
+
+```rust
+ReceiveTeleportedAsset(Assets)
+```
+
+Notes:
+
+This instruction is a trusted indication.
+It tells the receiver that the sender has burnt some assets and they should be minted here.
+This is used for teleports, which we'll look into in the next lecture.
+A lot of trust is needed between both systems.
+
+---v
+
+### Instruction Examples
+
+<pba-flex center>
+
+```rust
+ReserveAssetDeposited(Assets)
+```
+
+Notes:
+
+Another trusted indication.
+Used for reserve asset transfers, the second type of cross-chain transfer we'll see in next lecture.
+It tells the current system that assets have been deposited to this system's sovereign account somewhere
+and derivatives matching them should be minted here.
+
+---v
+
+### Instruction Examples
+
+<pba-flex center>
+
+```rust
+QueryResponse {
+    query_id: QueryId,
+    response: Response,
+    max_weight: Weight,
+    querier: Option<Location>,
+}
+```
+
+Notes:
+
+This instruction is reporting back information.
+Different things can be reported, like a certain pallet, the result of an operation, etc.
+
+---
+
+# Summary
+
+<pba-flex center>
+
+- Locations
+- Assets
+- Instructions
+
+---
+
+# Questions?
+
+---
+
+# Workshop
+
+We'll play around with these primitives.
+
+---
+
+# Next steps
+
+We'll look at an example and how these primitives are used.
diff --git a/content/6-Protocol_On-Chain/XCM/2.5-Cross-Consensus-Transfers-slides.md b/content/6-Protocol_On-Chain/XCM/2.5-Cross-Consensus-Transfers-slides.md
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+---
+title: Cross-Consensus Transfers
+description: How assets can be transferred between two consensus systems.
+duration: 15 minutes
+---
+
+# Cross-consensus transfers
+
+Notes:
+
+The two ways of transferring assets between consensus systems are teleports and reserve transfers.
+
+---v
+
+## 1. Asset teleportation
+
+<img rounded style="width: 500px;" src="./img/teleport.png">
+
+Notes:
+
+Teleportation works by burning the assets on the source chain and minting them on the destination chain.
+This method is the simplest one, but requires a lot of trust, since failure to burn or mint on either side will affect the total issuance.
+
+---v
+
+### 1.1. Example: System parachains?
+
+<diagram class="mermaid">
+graph LR
+    BridgeHub(Bridge Hub)--"Trust"-->AssetHub(Asset Hub)
+</diagram>
+
+---v
+
+### 1.2. Example: Polkadot and Kusama?
+
+<diagram class="mermaid">
+graph LR
+    Polkadot(Polkadot)--"No trust"-->Kusama(Kusama)
+</diagram>
+
+---v
+
+## 2. Reserve asset transfers
+
+<img rounded style="width: 400px;" src="./img/reserve-tx.png">
+
+Notes:
+
+Reserve asset transfers are more complicated, since they bring in a third actor called the reserve chain.
+Chain A and B needn't trust each other, they only need to trust the reserve chain.
+The reserve chain holds the real assets, A and B deal only with derivatives.
+The transfer is made by burning derivatives from A, moving them from A's SA to B's SA in R, then minting on B.
+
+In some cases, the sender, A, can also be the reserve for a particular asset, in which case the process is simplified, there's no burning of derivatives.
+This usually happens with parachains' native tokens.
+
+You always trust the issuer of the token to not mint infinite tokens.
+
+---v
+
+### 2.1. Example: Parachain native tokens
+
+<diagram class="mermaid">
+graph LR
+    subgraph A [A = R]
+        Sender(Sender account)--"Move X real asset"-->BSovereignAccount(B's Sovereign Account)
+    end
+    A--"Mint X derivatives"-->B(B)
+</diagram>
+
+Notes:
+
+Most parachains act as the reserve for their own token.
+To transfer their token to other chains, they move the real assets to a sovereign account and then tell the chain to mint equivalent derivatives.
+
+---v
+
+### 2.2. Example: Polkadot to Kusama
+
+<diagram class="mermaid">
+graph LR
+    Polkadot(Polkadot)-->AssetHubP
+    subgraph AssetHubP [Asset Hub Polkadot]
+        Sender(Sender account)--"Move X real DOT"-->KusamaSovereignAccount("Kusama's sovereign account")
+    end
+    AssetHubP--"Mint X DOT derivatives"-->Kusama(Kusama)
+</diagram>
+
+Notes:
+
+AssetHub Kusama acts as the reserve for KSM.
+Kusama doesn't trust Polkadot to teleport KSM to it, but it does trust its own reserve, the AssetHub.
+Polkadot has a sovereign account in Kusama's AssetHub with some amount of KSM.
+Whenever some user in Polkadot wants to get KSM on Kusama, they just give the DOT to Polkadot and the KSM are moved from one sovereign account to another.
+No new trust relationships are added.
+
+---
+
+# Example
+
+Notes:
+
+We'll look at an example and build on it as the lectures go on.
+
+---v
+
+## Locations
+
+<img src="img/Example Flow - Locations.png">
+
+---v
+
+## Assets
+
+<img src="img/Example Flow - Assets.png">
+
+---v
+
+## Instructions (simple)
+
+<img src="img/Example Flow - Instructions (simple).png">
+
+---v
+
+## Instructions (actual)
+
+<img src="img/Example Flow - Instructions (actual).png">
+
+---
+
+# Next steps
+
+How are these instructions executed?
diff --git a/content/6-Protocol_On-Chain/XCM/3-Executor-slides.md b/content/6-Protocol_On-Chain/XCM/3-Executor-slides.md
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+---
+title: XCM Executor
+description: How XCMs are executed.
+duration: 1 hour
+---
+
+# XCM Executor
+
+---v
+
+## What you'll learn
+
+<pba-flex center>
+
+- The XCVM
+- XCM Executor
+
+---
+
+# The XCVM
+
+At the core of XCM lies the **Cross-Consensus Virtual Machine (XCVM)**.
+
+The XCVM is a state machine, state is kept track in **registers**.
+
+How the virtual machine should act is written in the XCM [specification](https://github.com/paritytech/xcm-format).
+
+Notes:
+
+It’s an ultra-high level non-Turing-complete computer.
+Messages are one or more XCM instructions.
+The program executes until it either runs to the end or hits an error, at which point it finishes up and halts.
+
+---v
+
+## XCVM Registers
+
+<pba-flex center>
+
+- Holding
+- Origin
+- Fees
+- ErrorHandler
+- Appendix
+- ...
+
+Notes:
+
+Registers are the state of the XCVM.
+They are transient, temporary.
+
+---v
+
+### The Origin Register
+
+Contains an `Option<Location>` of the cross-consensus origin where the message originated from.
+
+Notes:
+
+This `Location` can change over the course of program execution.
+
+It might be `None` because some instructions clear the origin register.
+
+---v
+
+### The Holding Register
+
+Expresses a number of assets in control of the xcm execution that have no on-chain representation.
+
+They don't belong to any account.
+
+It can be seen as the register holding "unspent assets".
+
+Notes:
+
+Some instructions, like `WithdrawAsset`, put funds in the holding register.
+Other instructions, like `DepositAsset`, take funds out of the holding register.
+
+---v
+
+### The Fees Register
+
+Holds assets destined for fee payment.
+
+---v
+
+## Instructions
+
+Instructions might change a register, the state of the consensus system, or both.
+
+---
+
+# XCVM Operation
+
+---v
+
+## Fetch/execute loop
+
+The XCVM operates in a typical fetch/execute loop.
+
+Each instruction is fetched and executed in order.
+
+---v
+
+## Error handler and appendix
+
+Two additions in the XCVM are the error handler and appendix.
+
+They contain more instructions that are executed if there's an error or unconditionally
+at the end of execution, accordingly.
+
+---
+
+# XCM Executor
+
+Parity provides an implementation of the XCVM spec, the `XcmExecutor`.
+
+It's the entrypoint for executing XCMs.
+
+---v
+
+<pba-flex center>
+
+```rust
+XcmExecutor::prepare_and_execute(
+  origin,
+  xcm,
+  &mut hash,
+  weight_limit,
+  weight_credit,
+);
+```
+
+---v
+
+## Configuration
+
+The `XcmExecutor` is highly configurable, so it can be implemented by many different chains
+just adjusting some configuration items.
+
+These items provide the executor access to the chain's runtime.
+
+This is, for example, how different chains can route different asset instructions to different
+pallets (pallet-balances vs pallet-assets).
+
+Notes:
+
+The executor's state is transient, so any state changes to the underlying system need to happen in these configuration items.
+
+---
+
+# Example (continued)
+
+---v
+
+## Local XCM
+
+---v
+
+<img src="img/Example Flow - Local Instructions (simple).png">
+
+---v
+
+<img src="img/Example Flow - Local Instructions (actual).png">
+
+---v
+
+<img src="img/Example Flow - Local Instructions (step 1).png">
+
+---v
+
+<img src="img/Example Flow - Local Instructions (step 2).png">
+
+---v
+
+<img src="img/Example Flow - Local Instructions (step 3).png">
+
+---v
+
+<img src="img/Example Flow - Local Instructions (final).png">
+
+---v
+
+## Remote XCM
+
+---v
+
+<img src="img/Example Flow - Instructions (actual).png">
+
+---v
+
+<img src="img/Example Flow - Remote Instructions (step 1).png">
+
+---v
+
+<img src="img/Example Flow - Remote Instructions (step 2).png">
+
+---v
+
+<img src="img/Example Flow - Remote Instructions (step 3).png">
+
+---v
+
+<img src="img/Example Flow - Remote Instructions (step 4).png">
+
+---v
+
+<img src="img/Example Flow - Remote Instructions (step 5).png">
+
+---v
+
+<img src="img/Example Flow - Remote Instructions (final).png">
+
+---
+
+# Summary
+
+<pba-flex center>
+
+- XCVM
+- XCM Executor
+
+---
+
+# Next steps
+
+How does the XCM subsystem interact with FRAME?
diff --git a/content/6-Protocol_On-Chain/XCM/4-Pallet-Xcm-slides.md b/content/6-Protocol_On-Chain/XCM/4-Pallet-Xcm-slides.md
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+---
+title: XCM Pallet
+description: The link between XCM and FRAME.
+duration: 1 hour
+---
+
+# XCM Pallet
+
+---v
+
+## What you'll learn
+
+The link between XCM and FRAME.
+
+How to integrate XCM in your chains.
+
+---
+
+# How XCM can be used
+
+<pba-flex center>
+
+- Interacting directly with the executor by writing XCMs
+
+or
+
+- Packaging up all XCM-logic on extrinsics
+
+---
+
+# The XCM Pallet
+
+We have now learnt about the XCVM and FRAME.
+
+The XCM pallet is the bridge between the XCVM subsystem and the FRAME subsystem.
+
+**It allows us both to interact with the executor directly and provides useful extrinsics**.
+
+---v
+
+## Some functionalities of the pallet
+
+<pba-flex center>
+
+- Executing XCMs locally.
+- Sending XCMs to a different location.
+- Cross-Consensus Transfers.
+- Version negotiation
+- Handling responses
+- Asset trapping
+
+---
+
+# Executing XCMs locally
+
+<diagram class="mermaid limit size-40">
+<!-- prettier-ignore-start -->
+flowchart TD
+subgraph paraA[Parachain A              .]
+  executor --"success?"--> palletxcm
+  palletxcm("pallet-xcm") --"execute"--> executor("xcm-executor")
+end
+execute("execute(xcm)") --> palletxcm
+<!-- prettier-ignore-end -->
+</diagram>
+
+Notes:
+
+It checks the origin to ensure that the configured `SendXcmOrigin` filter is not blocking the execution.
+It executes the message **locally** and returns the outcome as an event.
+
+---
+
+# Sending XCMs
+
+<diagram class="mermaid" style="display: flex; width: 150%; justify-content: center; transform: translateX(-17%);">
+<!-- prettier-ignore-start -->
+flowchart LR
+subgraph paraA[Parachain A]
+palletxcma("pallet-xcm") --"deliver"--> routera("xcm-router")
+routera --> mqueuea("message queue")
+end
+
+subgraph paraB[Parachain B]
+mqueueb("message queue") --> executorb("xcm-executor")
+end
+
+send("send(xcm)") --> palletxcma
+mqueuea --> mqueueb
+
+<!-- prettier-ignore-end -->
+</diagram>
+
+Notes:
+
+This extrinsic is a function to send a message to a destination.
+It checks the origin, the destination and the message.
+Then it lets the `XcmRouter` handle the forwarding of the message.
+
+---
+
+# Version negotiation
+
+The XCM pallet stores the latest supported version for all known chains.
+
+The instructions `SubscribeVersion` and `UnsubscribeVersion` are used to subscribe to chains to know their versions.
+
+If the version of a destination is not known, the lowest known XCM version will be used, in order to be compatible.
+
+---
+
+# Handling responses
+
+The XCM pallet allows creating query ids and awaiting for responses to XCMs.
+
+With an instruction like `ReportError`, you can know if your operation was successful or not.
+
+---
+
+# Claiming trapped assets
+
+At the end of execution, if assets are left in the holding register, they are trapped.
+
+These assets live in a storage item under the XCM pallet\*.
+
+The pallet provides an extrinsic to claim them.
+
+Notes:
+
+- Only if the pallet is configured to be the asset trapper.
+
+---
+
+# Example (continued)
+
+---v
+
+<img src="img/Example Flow - XCM Pallet.png">
+
+---
+
+# Summary
+
+<pba-flex center>
+
+- Learnt the link between XCM and FRAME.
+- Learnt what the XCM pallet does.
+
+---
+
+# Next steps
+
+What about the XCM configuration we mentioned before?
diff --git a/content/6-Protocol_On-Chain/XCM/5-Xcm-config-slides.md b/content/6-Protocol_On-Chain/XCM/5-Xcm-config-slides.md
new file mode 100644
index 00000000..9a3b0b97
--- /dev/null
+++ b/content/6-Protocol_On-Chain/XCM/5-Xcm-config-slides.md
@@ -0,0 +1,285 @@
+---
+title: XCM Configuration
+description: Introduction to configuring the XCM executor.
+duration: 1 hour
+---
+
+# XCM Config
+
+Notes:
+
+We mentioned the executor is highly configurable.
+What can we configure?
+
+---v
+
+## What you'll learn
+
+<pba-flex center>
+
+- Different configuration items available in the XCM executor.
+- The tools available to help you configure them.
+
+---
+
+# Config items
+
+<pba-flex center>
+
+- AssetTransactor
+- Barrier
+- IsReserve
+- IsTeleporter
+- LocationConverter
+- Weigher
+
+Notes:
+
+We'll briefly introduce you to all these concepts.
+It might be a bit dry, but the idea is to jump straight to the workshop afterwards.
+
+These are all associated types on an `XcmConfig` struct.
+
+---
+
+# Asset Transactor
+
+---v
+
+<pba-flex center>
+
+Assets can live in different pallets:
+
+- pallet-balances
+- pallet-assets
+- pallet-nfts
+
+You can even have multiple instances of these pallets!
+
+---v
+
+How does the XCM executor know where each asset lives?
+
+You configure it!
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+---v
+
+## Available adapters
+
+<pba-flex center>
+
+- Fungible(s) adapter: pallet-balances/pallet-assets
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Nonfungible(s) adapter: pallet-uniques/pallet-nfts
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+Although you can write your own logic for this, we have some available adapters
+in the `polkadot-sdk` repo in the `xcm-builder` crate.
+Each can be configured to support different assets.
+
+---v
+
+## Example (continued)
+
+<img src="img/Example Flow - Asset Transactor.png">
+
+Notes:
+
+DOT lives in `pallet-balances`.
+USDT lives in an instance of `pallet-assets`.
+`AssetTransactor` is a sequence of transactors, we try them one by now until one
+matches the asset id.
+We'll see how we can configure these later.
+
+---
+
+# Barrier
+
+By default we can receive any message from chains we are connected to.
+
+Do we want to?
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+
+The barrier lets us filter incoming messages based on their structure.
+It's a firewall.
+
+---v
+
+## A firewall for XCMs
+
+Chains can configure its barrier to immediately filter unwanted messages.
+
+---v
+
+<img src="img/Example Flow - Barrier (intro).png">
+
+Notes:
+
+Our example would need to pass the barrier to reach its destination and be executed.
+
+---v
+
+<img src="img/Example Flow - Barrier (wrong origin).png">
+
+Notes:
+
+We can filter messages from unwanted origins.
+We can also filter messages with unwanted instructions.
+For example, this "Random Action" doesn't have to be a transfer, could be trying to execute anything.
+
+---v
+
+## Available barriers
+
+<pba-flex center>
+
+- AllowTopLevelPaidExecutionFrom
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- AllowExplicitUnpaidExecutionFrom
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- ...
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+Notes:
+
+These are two of the most relevant barriers provided.
+There are more.
+TODO: Would be good to have good documentation on barriers to link here.
+You can of course write your own and filter whatever you want.
+They come with some degree of customizability.
+
+---v
+
+### AllowTopLevelPaidExecutionFrom
+
+<img src="img/Example Flow - Barrier (no fees).png">
+
+Notes:
+
+As long as they include the `PayFees` instruction, meaning they intend to pay fees,
+this barrier will allow them to pass.
+
+---v
+
+### AllowExplicitUnpaidExecutionFrom
+
+<img src="img/Example Flow - Barrier (explicit unpaid).png">
+
+Notes:
+
+This barrier will allow messages from some origins when they use the `UnpaidExecution`
+instruction.
+These could be to allow messages from the system.
+It's used a lot between system chains.
+
+---
+
+# LocationConverter
+
+Way to convert from `Location` to `AccountId`.
+
+This is how we get sovereign accounts.
+
+Notes:
+
+We always deal with locations on XCM, never accounts.
+This config item converts locations to accounts.
+This means pallets can have account, external locations can also have accounts.
+
+---v
+
+## Available converters
+
+<pba-flex center>
+
+- AccountId32Aliases
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- HashedDescription
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+The first just grabs an AccountId32 junction and gets the local account from it.
+The second is very generic and can be used to generate accounts for any type of junction.
+
+---
+
+## IsReserve and IsTeleporter
+
+Specifies reserve locations for particular assets.
+
+---v
+
+<img src="img/Example Flow - IsReserve.png">
+
+---v
+
+<img src="img/Example Flow - IsTeleporter.png">
+
+---
+
+## Weigher
+
+The weigher weighs XCMs, it assigns a weight to each instruction.
+
+---v
+
+### Available weighers
+
+<pba-flex center>
+
+- FixedWeightBounds (testing)
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- WeightInfoBounds (production)
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+FixedWeightBounds is only for testing, it assigns a constant weight to each instruction.
+
+WeightInfoBounds uses benchmarks for assigning different weights to different instructions.
+
+---v
+
+### Benchmarks!
+
+XCM instructions need to be weighed by each runtime!
+
+Different configuration items change the benchmarks.
+
+---v
+
+<img src="img/Example Flow - Weigher.png">
+
+Notes:
+
+If you're using `pallet-assets` for example, instructions that use the `AssetTransactor`
+will inevitably be more expensive.
+Always benchmark the worst case.
+
+---
+
+# Next steps
+
+We'll look at the XCM emulator, a tool to let us experiment configuring XCM, sending and executing messages.
diff --git a/content/6-Protocol_On-Chain/XCM/6-Xcm-emulator-slides.md b/content/6-Protocol_On-Chain/XCM/6-Xcm-emulator-slides.md
new file mode 100644
index 00000000..05c911b5
--- /dev/null
+++ b/content/6-Protocol_On-Chain/XCM/6-Xcm-emulator-slides.md
@@ -0,0 +1,170 @@
+---
+title: XCM Emulator
+description: Introduction to the XCM emulator.
+duration: 1 hour
+---
+
+# XCM Emulator
+
+Notes:
+
+The emulator will let us use all the knowledge we've gained so far.
+
+---v
+
+## What you'll learn
+
+- How to use the XCM emulator for testing your cross-chain interactions.
+
+---
+
+# What is it?
+
+A collection of macros that create a mock network we can use test our XCM configuration.
+
+---
+
+# Creating a mock network
+
+---v
+
+## Runtimes
+
+We first need to create our runtimes, a relay chain and a minimum of a parachain.
+
+---v
+
+## Relay chains
+
+```rust
+decl_test_relay_chains! {
+  pub struct Relay {
+    runtime = relay_runtime,
+    core = {
+      SovereignAccountOf: location_converter,
+    },
+    pallets = {
+      ...
+    },
+    genesis = genesis(),
+    on_init = {
+      ...
+    },
+  }
+}
+```
+
+Notes:
+
+XCM emulator provides a macro for declaring mock relay chains.
+
+We need to specify a couple of things:
+
+- runtime: The actual runtime of our relay chain.
+- core: Some core functionality used by the emulator, things like handlers and converters.
+- pallets: All pallets you want to use for tests.
+- genesis: Genesis configuration for testing, you can register assets for example.
+- on_init: You can call some `on_initialize`s here.
+
+---v
+
+## Parachains
+
+```rust
+decl_test_parachains! {
+  pub struct ParaA {
+    runtime = parachain_runtime,
+    core = {
+      ...
+    },
+    pallets = {
+      ...
+    },
+    genesis = genesis(),
+    on_init = {
+      ...
+    },
+  }
+}
+```
+
+Notes:
+
+XCM emulator provides a macro for declaring mock parachains.
+
+We need to specify the same things.
+
+---v
+
+## The entire network
+
+```rust
+decl_test_networks! {
+  pub struct MockNet {
+    relay_chain = Relay,
+    parachains = vec![
+      ParaA,
+      ParaB,
+    ],
+    bridge = (),
+  }
+}
+```
+
+Notes:
+
+We declare our network by specifying our relay chain and parachains.
+We can also declare a bridge to test sending messages to different networks.
+In that case we also use `decl_test_bridges!` to define the bridges.
+
+---
+
+# Simple Test
+
+```rust
+#[test]
+fn test_xcm() {
+  MockNet::reset();
+
+  ParaA::execute_with(|| {
+    let message: Xcm<()> = <some_xcm>;
+    let destination = Location::new(1, [Parachain(2001)]);
+    parachain_runtime::XcmPallet::execute(
+      parachain_runtime::RuntimeOrigin::signed(<some_account>),
+      Box::new(VersionedXcm::V5(message)),
+      Weight::from_parts(...), // Some max weight.
+    );
+  });
+
+  ParaB::execute_with(|| {
+    // Message arrives, do some asserts.
+  })
+}
+```
+
+Notes:
+
+First we reset the state of the network.
+Then we create a message and call the XCM pallet's `execute` extrinsic.
+We must wrap the location and XCM in a `Versioned*` type.
+
+---
+
+# Next steps
+
+- Zombienet
+- Chopsticks
+
+Notes:
+
+In the realm of testing tools we also have Zombienet and Chopsticks.
+
+Zombienet for spawning a local network and testing against it with either typescript or a DSL.
+
+Chopsticks for forking a live chain and testing against it.
+
+---
+
+# Workshop
+
+We'll now jump on the emulator, configure XCM, execute and send messages.
diff --git a/content/6-Protocol_On-Chain/XCM/Cargo.lock b/content/6-Protocol_On-Chain/XCM/Cargo.lock
new file mode 100644
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diff --git a/content/6-Protocol_On-Chain/XCM/Cargo.toml b/content/6-Protocol_On-Chain/XCM/Cargo.toml
new file mode 100644
index 00000000..0da3e40c
--- /dev/null
+++ b/content/6-Protocol_On-Chain/XCM/Cargo.toml
@@ -0,0 +1,9 @@
+[patch."https://github.com/paritytech/polkadot"]
+xcm-executor = { path = "xcm-related-code/xcm-executor" }
+
+[workspace]
+members = [
+  "xcm-related-code/xcm-simulator-for-exercises",
+  "2-XCVM/execution_exercises",
+  "3-Pallet_XCM/constructing-messages-with-simulator",
+]
diff --git a/content/6-Protocol_On-Chain/XCM/README.md b/content/6-Protocol_On-Chain/XCM/README.md
new file mode 100644
index 00000000..9d155779
--- /dev/null
+++ b/content/6-Protocol_On-Chain/XCM/README.md
@@ -0,0 +1,41 @@
+# Cross Consensus Messaging (XCM)
+
+## Learning outcomes
+
+- Students will understand the what and why of XCM.
+- Students will get familiar with writing XCM programs.
+- Students will understand how XCM programs are executed.
+- Students will get familiar with configuring chains for XCM execution.
+
+## Hands-on activities
+
+The whole module will revolve around a workshop, with each lecture introducing the relevant
+concepts needed to get hacking.
+
+## Schedule
+
+### Day 1
+
+#### Morning
+
+Lecture 1 - Presentation (45 minutes)
+Lecture 2 - Primitives (2 hours)
+Workshop - Fundamentals 1, 2 and 3 (1 hour)
+
+#### Afternoon
+
+Lecture 3 - XCM Executor (1 hour)
+Workshop - Fundamentals 4 (1 hour)
+Lecture 4 - Pallet XCM (1 hour)
+Workshop - Fundamentals 5 (1 hour)
+
+### Day 2
+
+#### Morning
+
+Lecture 5 - XCM configuration and XCM simulator (2 hours)
+Lecture 6 - ??? (2 hours)
+
+#### Afternoon
+
+Workshop - Simulator (4 hours)
diff --git a/content/6-Protocol_On-Chain/XCM/img/Example Flow - Asset Transactor.png b/content/6-Protocol_On-Chain/XCM/img/Example Flow - Asset Transactor.png
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overflow-wrap: normal;">Withdraw</div></div></div></foreignObject><text x="153" y="57" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="19px" text-anchor="middle">Withdraw</text></switch></g><rect x="0" y="85" width="300" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 298px; height: 1px; padding-top: 100px; margin-left: 1px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 19px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 14px;"><b style=""><font color="#3333ff">Asset: </font>(100u128, Here).into()</b></font></div></div></div></foreignObject><text x="150" y="106" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="19px" text-anchor="middle">Asset: (100u128, Here).into()</text></switch></g><rect x="0" y="63.46" width="300" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 298px; height: 1px; padding-top: 78px; margin-left: 1px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 19px; font-family: 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new file mode 100644
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Binary files /dev/null and b/content/6-Protocol_On-Chain/XCM/img/failed-ump.png differ
diff --git a/content/xcm/in-use/img/high-level-product-flow.jpg b/content/6-Protocol_On-Chain/XCM/img/high-level-product-flow.jpg
similarity index 100%
rename from content/xcm/in-use/img/high-level-product-flow.jpg
rename to content/6-Protocol_On-Chain/XCM/img/high-level-product-flow.jpg
diff --git a/content/6-Protocol_On-Chain/XCM/img/location_to_account_id_withdraw.svg b/content/6-Protocol_On-Chain/XCM/img/location_to_account_id_withdraw.svg
new file mode 100644
index 00000000..04765684
--- /dev/null
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 118px; height: 1px; padding-top: 110px; margin-left: 161px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font color="#ffffff">PALLET-XCM</font></div></div></div></foreignObject><text x="220" y="114" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">PALLET-XCM</text></switch></g><path d="M 230 20 L 230 63.63" fill="none" stroke="#000000" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 230 68.88 L 226.5 61.88 L 230 63.63 L 233.5 61.88 Z" fill="#000000" stroke="#000000" stroke-miterlimit="10" pointer-events="all"/><rect x="176.25" y="0" width="107.5" height="20" fill="#000000" stroke="rgb(0, 0, 0)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 106px; height: 1px; padding-top: 10px; margin-left: 177px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font color="#ffffff">execute(xcm)</font></div></div></div></foreignObject><text x="230" y="14" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">execute(xcm)</text></switch></g><rect x="20" y="60" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 75px; margin-left: 21px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Chain A</div></div></div></foreignObject><text x="50" y="79" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Chain A</text></switch></g></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
diff --git a/content/6-Protocol_On-Chain/XCM/img/pallet-xcm-reserve-transfer.svg b/content/6-Protocol_On-Chain/XCM/img/pallet-xcm-reserve-transfer.svg
new file mode 100644
index 00000000..cc34fbbe
--- /dev/null
+++ b/content/6-Protocol_On-Chain/XCM/img/pallet-xcm-reserve-transfer.svg
@@ -0,0 +1,4 @@
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 1px; height: 1px; padding-top: 251px; margin-left: 121px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); "><div style="display: inline-block; font-size: 11px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; background-color: rgb(255, 255, 255); white-space: nowrap;"><span style="background-color: rgb(0, 0, 0);"><font color="#ffffff">send(xcm)</font></span></div></div></div></foreignObject><text x="121" y="254" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="11px" text-anchor="middle">send(xcm)</text></switch></g><path d="M 200 140 L 240 140 L 260 160 L 260 280 L 220 280 L 200 260 L 200 140 Z" fill="#000000" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,230,210)" pointer-events="all"/><path d="M 200 140 L 240 140 L 260 160 L 220 160 Z" fill-opacity="0.05" fill="#000000" stroke="none" transform="rotate(90,230,210)" pointer-events="all"/><path d="M 200 140 L 220 160 L 220 280 L 200 260 Z" fill-opacity="0.1" fill="#000000" stroke="none" transform="rotate(90,230,210)" pointer-events="all"/><path d="M 220 280 L 220 160 L 200 140 M 220 160 L 260 160" fill="none" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,230,210)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; 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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 135px; margin-left: 21px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Chain A</div></div></div></foreignObject><text x="60" y="139" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Chain A</text></switch></g><rect x="270" y="90" width="300" height="80" fill="#b266ff" stroke="rgb(0, 0, 0)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe flex-start; width: 298px; height: 1px; padding-top: 130px; margin-left: 272px;"><div style="box-sizing: border-box; font-size: 0px; text-align: left;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font color="#ffffff">Xcm(vec![<br />            SetFeesMode { jit_withdraw: true },<br />            <b>TransferReserveAsset</b> { assets, dest, xcm },<br />])</font></div></div></div></foreignObject><text x="272" y="134" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px">Xcm(vec![...</text></switch></g><rect x="450" y="230" width="90" height="50" rx="7.5" ry="7.5" fill="#000000" stroke="rgb(0, 0, 0)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; 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\ No newline at end of file
diff --git a/content/6-Protocol_On-Chain/XCM/img/pallet-xcm-send-paras.svg b/content/6-Protocol_On-Chain/XCM/img/pallet-xcm-send-paras.svg
new file mode 100644
index 00000000..910561d5
--- /dev/null
+++ b/content/6-Protocol_On-Chain/XCM/img/pallet-xcm-send-paras.svg
@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!-- Do not edit this file with editors other than draw.io -->
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 118px; height: 1px; padding-top: 160px; margin-left: 161px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font color="#ffffff">XcmRouter</font></div></div></div></foreignObject><text x="220" y="164" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">XcmRouter</text></switch></g><path d="M 160 110 L 140 110 L 140 160 L 153.63 160" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 158.88 160 L 151.88 163.5 L 153.63 160 L 151.88 156.5 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 1px; height: 1px; padding-top: 130px; margin-left: 110px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: #FFFFFF; background-color: #000000; "><div style="display: inline-block; font-size: 11px; font-family: Helvetica; color: rgb(255, 255, 255); line-height: 1.2; pointer-events: all; background-color: rgb(0, 0, 0); white-space: nowrap;">deliver()</div></div></div></foreignObject><text x="110" y="134" fill="#FFFFFF" font-family="Helvetica" font-size="11px" text-anchor="middle">deliver()</text></switch></g><path d="M 200 30 L 240 30 L 260 50 L 260 170 L 220 170 L 200 150 L 200 30 Z" fill="#000000" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,230,100)" pointer-events="all"/><path d="M 200 30 L 240 30 L 260 50 L 220 50 Z" fill-opacity="0.05" fill="#000000" stroke="none" transform="rotate(90,230,100)" pointer-events="all"/><path d="M 200 30 L 220 50 L 220 170 L 200 150 Z" fill-opacity="0.1" fill="#000000" stroke="none" transform="rotate(90,230,100)" pointer-events="all"/><path d="M 220 170 L 220 50 L 200 30 M 220 50 L 260 50" fill="none" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,230,100)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 118px; height: 1px; padding-top: 110px; margin-left: 161px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font color="#ffffff">PALLET-XCM</font></div></div></div></foreignObject><text x="220" y="114" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">PALLET-XCM</text></switch></g><path d="M 230 20 L 230 63.63" fill="none" stroke="#000000" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 230 68.88 L 226.5 61.88 L 230 63.63 L 233.5 61.88 Z" fill="#000000" stroke="#000000" stroke-miterlimit="10" pointer-events="all"/><rect x="176.25" y="0" width="107.5" height="20" fill="#000000" stroke="rgb(0, 0, 0)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 106px; height: 1px; padding-top: 10px; margin-left: 177px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font color="#ffffff">send(dest, xcm)</font></div></div></div></foreignObject><text x="230" y="14" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">send(dest, xcm)</text></switch></g><rect x="20" y="60" width="80" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 75px; margin-left: 21px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Parachain A</div></div></div></foreignObject><text x="60" y="79" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Parachain A</text></switch></g><rect x="435" y="40" width="360" height="210" rx="31.5" ry="31.5" fill="none" stroke="rgb(0, 0, 0)" pointer-events="all"/><path d="M 635 130 L 675 130 L 695 150 L 695 270 L 655 270 L 635 250 L 635 130 Z" fill="#000000" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,665,200)" pointer-events="all"/><path d="M 635 130 L 675 130 L 695 150 L 655 150 Z" fill-opacity="0.05" fill="#000000" stroke="none" transform="rotate(90,665,200)" pointer-events="all"/><path d="M 635 130 L 655 150 L 655 270 L 635 250 Z" fill-opacity="0.1" fill="#000000" stroke="none" transform="rotate(90,665,200)" pointer-events="all"/><path d="M 655 270 L 655 150 L 635 130 M 655 150 L 695 150" fill="none" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,665,200)" pointer-events="all"/><path d="M 635 80 L 675 80 L 695 100 L 695 220 L 655 220 L 635 200 L 635 80 Z" fill="#000000" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,665,150)" pointer-events="all"/><path d="M 635 80 L 675 80 L 695 100 L 655 100 Z" fill-opacity="0.05" fill="#000000" stroke="none" transform="rotate(90,665,150)" pointer-events="all"/><path d="M 635 80 L 655 100 L 655 220 L 635 200 Z" fill-opacity="0.1" fill="#000000" stroke="none" transform="rotate(90,665,150)" pointer-events="all"/><path d="M 655 220 L 655 100 L 635 80 M 655 100 L 695 100" fill="none" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,665,150)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 118px; height: 1px; padding-top: 160px; margin-left: 596px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font color="#ffffff">XcmExecutor</font></div></div></div></foreignObject><text x="655" y="164" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">XcmExecutor</text></switch></g><path d="M 735 90 L 755 90 L 755 140 L 741.37 140" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" stroke-dasharray="3 3" pointer-events="stroke"/><path d="M 736.12 140 L 743.12 136.5 L 741.37 140 L 743.12 143.5 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/><path d="M 635 30 L 675 30 L 695 50 L 695 170 L 655 170 L 635 150 L 635 30 Z" fill="#000000" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,665,100)" pointer-events="all"/><path d="M 635 30 L 675 30 L 695 50 L 655 50 Z" fill-opacity="0.05" fill="#000000" stroke="none" transform="rotate(90,665,100)" pointer-events="all"/><path d="M 635 30 L 655 50 L 655 170 L 635 150 Z" fill-opacity="0.1" fill="#000000" stroke="none" transform="rotate(90,665,100)" pointer-events="all"/><path d="M 655 170 L 655 50 L 635 30 M 655 50 L 695 50" fill="none" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,665,100)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 118px; height: 1px; padding-top: 110px; margin-left: 596px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font color="#ffffff">parachain-system</font></div></div></div></foreignObject><text x="655" y="114" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">parachain-system</text></switch></g><rect x="455" y="60" width="80" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 75px; margin-left: 456px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Parachain B</div></div></div></foreignObject><text x="495" y="79" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Parachain B</text></switch></g><rect x="330" y="120" width="105" height="20" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 130px; margin-left: 331px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><span style="background-color: rgb(0, 0, 0);"><font color="#ffffff">send through transport layer </font><br /></span></div></div></div></foreignObject><text x="383" y="134" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">send through tran...</text></switch></g></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
diff --git a/content/6-Protocol_On-Chain/XCM/img/pallet-xcm-teleport.svg b/content/6-Protocol_On-Chain/XCM/img/pallet-xcm-teleport.svg
new file mode 100644
index 00000000..8a7765a4
--- /dev/null
+++ b/content/6-Protocol_On-Chain/XCM/img/pallet-xcm-teleport.svg
@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 1px; height: 1px; padding-top: 250px; margin-left: 120px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); "><div style="display: inline-block; font-size: 11px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; background-color: rgb(255, 255, 255); white-space: nowrap;"><span style="background-color: rgb(0, 0, 0);"><font color="#ffffff">send(xcm)</font></span></div></div></div></foreignObject><text x="120" y="254" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="11px" text-anchor="middle">send(xcm)</text></switch></g><path d="M 200 140 L 240 140 L 260 160 L 260 280 L 220 280 L 200 260 L 200 140 Z" fill="#000000" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,230,210)" pointer-events="all"/><path d="M 200 140 L 240 140 L 260 160 L 220 160 Z" fill-opacity="0.05" fill="#000000" stroke="none" transform="rotate(90,230,210)" pointer-events="all"/><path d="M 200 140 L 220 160 L 220 280 L 200 260 Z" fill-opacity="0.1" fill="#000000" stroke="none" transform="rotate(90,230,210)" pointer-events="all"/><path d="M 220 280 L 220 160 L 200 140 M 220 160 L 260 160" fill="none" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,230,210)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; 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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 1px; height: 1px; padding-top: 190px; margin-left: 80px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); "><div style="display: inline-block; font-size: 11px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; background-color: rgb(255, 255, 255); white-space: nowrap;"><font style="background-color: rgb(0, 0, 0);" color="#ffffff">execute_xcm_in_credit(xcm)</font></div></div></div></foreignObject><text x="80" y="193" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="11px" text-anchor="middle">execute_xcm_in_credit(xcm)</text></switch></g><path d="M 200 90 L 240 90 L 260 110 L 260 230 L 220 230 L 200 210 L 200 90 Z" fill="#000000" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,230,160)" pointer-events="all"/><path d="M 200 90 L 240 90 L 260 110 L 220 110 Z" fill-opacity="0.05" fill="#000000" stroke="none" transform="rotate(90,230,160)" pointer-events="all"/><path d="M 200 90 L 220 110 L 220 230 L 200 210 Z" fill-opacity="0.1" fill="#000000" stroke="none" transform="rotate(90,230,160)" pointer-events="all"/><path d="M 220 230 L 220 110 L 200 90 M 220 110 L 260 110" fill="none" stroke="#ffffff" stroke-miterlimit="10" transform="rotate(90,230,160)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 118px; height: 1px; padding-top: 170px; margin-left: 161px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font color="#ffffff">PALLET-XCM</font></div></div></div></foreignObject><text x="220" y="174" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">PALLET-XCM</text></switch></g><path d="M 230 80 L 230 123.63" fill="none" stroke="#000000" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 230 128.88 L 226.5 121.88 L 230 123.63 L 233.5 121.88 Z" fill="#000000" stroke="#000000" stroke-miterlimit="10" pointer-events="all"/><rect x="180" y="0" width="100" height="80" fill="#000000" stroke="rgb(0, 0, 0)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; 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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 135px; margin-left: 21px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Chain A</div></div></div></foreignObject><text x="60" y="139" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Chain A</text></switch></g><rect x="270" y="90" width="420" height="80" fill="#b266ff" stroke="rgb(0, 0, 0)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe flex-start; width: 418px; height: 1px; padding-top: 130px; margin-left: 272px;"><div style="box-sizing: border-box; font-size: 0px; text-align: left;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><div align="left"><font color="#ffffff">Xcm(vec![<br />            WithdrawAsset(assets),<br />            SetFeesMode { jit_withdraw: true },<br />            <b>InitiateTeleport</b> { assets: Wild(AllCounted(max_assets)), dest, xcm },<br /></font></div><div align="left"><font color="#ffffff">])</font></div></div></div></div></foreignObject><text x="272" y="134" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px">Xcm(vec![...</text></switch></g><rect x="450" y="230" width="90" height="50" rx="7.5" ry="7.5" fill="#000000" stroke="rgb(0, 0, 0)" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 88px; height: 1px; padding-top: 255px; margin-left: 451px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(0, 0, 0); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><div><font color="#ffffff">trusted</font></div><div><font color="#ffffff">destination<br /></font></div></div></div></div></foreignObject><text x="495" y="259" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">trusted...</text></switch></g></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
diff --git a/content/6-Protocol_On-Chain/XCM/img/physical_vs_computed_origin.svg b/content/6-Protocol_On-Chain/XCM/img/physical_vs_computed_origin.svg
new file mode 100644
index 00000000..8c20b096
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+++ b/content/6-Protocol_On-Chain/XCM/img/physical_vs_computed_origin.svg
@@ -0,0 +1,4 @@
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" 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pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="border-color: var(--border-color);"><font color="#00994d">Physical origin:</font><br style="border-color: var(--border-color);" /></b><font color="#000000"><b>MultiLocation::parent()<br /></b></font></div></div></div></foreignObject><text x="394" y="103" fill="#A1E9FF" font-family="Helvetica" font-size="12px" text-anchor="middle">Physical origin:...</text></switch></g><rect x="290" y="136.75" width="214" height="54" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 212px; height: 1px; padding-top: 164px; margin-left: 291px;"><div data-drawio-colors="color: #A1E9FF; " 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rename from content/xcm/intro/img/teleport.png
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diff --git a/content/xcm/intro/img/xcm-executor-routing-calls.png b/content/6-Protocol_On-Chain/XCM/img/xcm-executor-routing-calls.png
similarity index 100%
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diff --git a/content/xcm/in-use/img/xcm-send-1.png b/content/6-Protocol_On-Chain/XCM/img/xcm-send-1.png
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rename from content/xcm/in-use/img/xcm-send-1.png
rename to content/6-Protocol_On-Chain/XCM/img/xcm-send-1.png
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rename from content/xcm/in-use/img/xcm-send-2.png
rename to content/6-Protocol_On-Chain/XCM/img/xcm-send-2.png
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diff --git a/content/xcm/in-use/img/xcm-send-4.png b/content/6-Protocol_On-Chain/XCM/img/xcm-send-4.png
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rename from content/xcm/in-use/img/xcm-send-4.png
rename to content/6-Protocol_On-Chain/XCM/img/xcm-send-4.png
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rename from content/xcm/in-use/img/xcm-send-5.png
rename to content/6-Protocol_On-Chain/XCM/img/xcm-send-5.png
diff --git a/content/6-Protocol_On-Chain/XCM/img/xcm-stack.png b/content/6-Protocol_On-Chain/XCM/img/xcm-stack.png
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diff --git a/content/6-Protocol_On-Chain/XCM/restructuring_notes_and_todo.txt b/content/6-Protocol_On-Chain/XCM/restructuring_notes_and_todo.txt
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@@ -0,0 +1,32 @@
+(Andrew Gorka)
+Module 1
+- Discuss problem of interoperability of consensus systems more
+    - Current bridging solutions(Andrew)
+    - Nomad hack example(Gorka)
+- Why XCM handles these guarantees of interoperability differently
+- Remove Versioning from Module 1 and put in Module 3 
+- Remove convenience code section 
+- Reanchoring section needs more depth and content (Reanchoring example in paper exercise in class exercise)
+- End Module 1 at transferring assets part
+
+(Andrew)
+Module 2 (Dedicated to XCVM)
+- Take XCVM stuff from Module 1 and CURRENT Module 2 and aggregate them into new Module 2
+- Small exercise on XCVM(Local setup for executor with debug statements and some simple messages)
+- Each group gets assigned a specific use case to execute and analyze.
+
+(Andrew Loop in Keith)
+Module 3 (Sending and Execution XCM)
+- Left over after restructuring Mod 1 and 2
+- Focus on exercises(Day 2)
+
+(Gorka)
+Module 4 (Parachain Config)
+- Gorka Lecture
+- Versioning Exercise
+- Try out different configurable scenarios
+- Assignment Transactor pallet(Verify we need to do this) 
+
+(Gorka)
+Module 5 (Testing and Troubleshooting)
+- Debugging in Polkadot XCM
diff --git a/content/6-Protocol_On-Chain/Zombienet-slides.md b/content/6-Protocol_On-Chain/Zombienet-slides.md
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@@ -0,0 +1,905 @@
+---
+title: Zombienet
+description: Zombienet workshop
+duration: 1 hour
+---
+
+<style>
+    .colored {
+        color: var(--r-link-color);
+    }
+
+    .colored-green {
+        color: #18ffb2;
+    }
+
+    .colored-light-green {
+        color: #c2ff33;
+    }
+</style>
+
+# Zombienet
+
+---
+
+## What we will learn?
+
+The goal of the lecture is present Zombienet (<span class="colored">v1/v2</span>) and familiarize with the process of setup, spawn and test in both version.
+
+---
+
+## What is Zombienet?
+
+Zombienet is an <span class="colored">integration testing tool</span> that allows users to _<span class="colored">spawn</span>_ and _<span class="colored">test</span>_ ephemeral substrate based networks.
+
+---
+
+## Why Zombienet?
+
+Integration tests are always <span class="colored">complex</span>:
+
+<br/>
+
+<pba-flex center>
+
+- Setup Configuration
+
+<!-- .element: class="fragment" -->
+
+- Port management
+
+<!-- .element: class="fragment" -->
+
+- Ready state off all artifacts
+
+<!-- .element: class="fragment" -->
+
+- Observability
+
+<!-- .element: class="fragment" -->
+
+- Leaking resources
+
+<!-- .element: class="fragment" -->
+
+</pba-flex>
+
+---v
+
+## Friction to resolve
+
+<br/>
+
+<pba-flex center>
+
+- Config flexibility
+
+<!-- .element: class="fragment" -->
+
+- Local environment
+
+<!-- .element: class="fragment" -->
+
+- Maintenance
+
+<!-- .element: class="fragment" -->
+
+- CI friendly
+
+<!-- .element: class="fragment" -->
+
+- Scaling
+
+<!-- .element: class="fragment" -->
+
+- Test-runner
+
+<!-- .element: class="fragment" -->
+
+</pba-flex>
+
+---v
+
+## Design goals
+
+<br/>
+
+<pba-cols style="align-items:normal">
+    <pba-col>
+
+##### Hassle free setup
+
+- Toml / json
+- Nice defaults
+- Templating lang.
+
+</pba-col>
+<pba-col>
+
+##### Multiple envs
+
+- **Local**
+- **k8s**
+- **podman**
+- **docker**
+
+</pba-col>
+<pba-col>
+
+##### Extensible
+
+- Custom assertions
+- Intuitive <span class="colored">D.S.L</span>
+- Templating lang.
+
+  </pba-col>
+  </pba-cols>
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Phases
+
+---
+
+## Phases
+
+<pba-cols style="align-items:normal">
+<pba-col>
+
+Spawn
+
+- Custom chain-specs
+- Custom command
+- Port-mapping
+- Parachains registration
+
+</pba-col>
+<!-- .element: class="fragment" -->
+<pba-col>
+
+Test
+
+- Custom <span class="colored">D.S.L</span>
+- Multiple assertions
+- Extensible
+- Custom reporting
+
+</pba-col>
+<!-- .element: class="fragment" -->
+</pba-cols>
+
+---
+
+## Zombienet Options
+
+<pba-flex center>
+
+- As binary ([releases](https://github.com/paritytech/zombienet/releases))
+- As library (@zombienet)
+- As container (published in docker hub)
+- From source ([zombienet](https://github.com/paritytech/zombienet) repo)
+
+</pba-flex>
+
+Notes:
+
+- As binary: Binaries for Linux and MacOS are available in each release in Github.
+- npm packages: cli, orchestrator, utils
+- image: docker.io/paritytech/zombienet
+  code is available in GitHub with the instructions on how to build and run Zombienet.
+  (https://github.com/paritytech/zombienet)
+
+---v
+
+### Download Zombienet
+
+```sh
+# macOS (m* chips)
+curl -L https://github.com/paritytech/zombienet/releases/download/v1.3.106/zombienet-macos-arm64
+-o ./zombienet
+
+# linux (x86_64)
+curl -L https://github.com/paritytech/zombienet/releases/download/v1.3.106/zombienet-linux-x64
+-o ./zombienet
+
+# make executable
+chmod +x zombienet
+```
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Let’s spawn a new network!
+
+---v
+
+## But first, try manually…
+
+<br/>
+<div>
+<ul><li>Create chain-spec (parachain)</li></ul>
+
+```sh
+parachain-template-node build-spec --chain local \
+--disable-default-bootnode > /tmp/para.json
+```
+
+</div>
+<!-- .element: class="fragment" -->
+<br/>
+<div>
+<ul><li>Create chain-spec (relay chain)</li></ul>
+
+```sh
+polkadot build-spec --chain rococo-local \
+ --disable-default-bootnode > /tmp/relay.json
+```
+
+</div>
+<!-- .element: class="fragment" -->
+
+Notes:
+
+Tutorials https://docs.substrate.io/tutorials/build-a-parachain/
+
+---v
+
+### Add keys\*
+
+<br/>
+
+When not using --alice or --bob, you need to provide additional `aura` and `grandpa` keys and inject them into the keystore! (**per node**)
+
+```sh
+./target/release/polkadot \
+key insert --base-path /tmp/node01 \
+  --chain /tmp/relay.json \
+  --scheme Sr25519 \
+  --suri <your-secret-seed> \
+  --password-interactive \
+  --key-type aura
+```
+
+<br/>
+
+```sh
+./target/release/polkadot key insert \
+  --base-path /tmp/node01 \
+  --chain /tmp/relay.json \
+  --scheme Ed25519 \
+  --suri <your-secret-key> \
+  --password-interactive \
+  --key-type gran
+```
+
+Notes:
+
+This step is optional if you use the dev accounts (e.g. alice, bob, charlie, dave, etc)
+
+---v
+
+- Start relay chain nodes
+
+```sh[1-2|4-10|12-18]
+# create nodes dirs
+  mkdir -p /tmp/relay/{alice,bob}
+
+  ./target/release/polkadot \
+  --alice \
+  --validator \
+  --base-path /tmp/relay/alice \
+  --chain /tmp/relay.json \
+  --port 30333 \
+  --ws-port 9944
+
+  ./target/release/polkadot \
+  --bob \
+  --validator \
+  --base-path /tmp/relay/bob \
+  --chain /tmp/relay.json \
+  --port 30334 \
+  --ws-port 9945
+```
+
+Notes:
+
+Why do we need to use different ports for Alice and Bob?
+
+---v
+
+- Start collator
+
+```sh
+# create nodes dirs
+mkdir -p /tmp/para/alice
+
+parachain-template-node \
+--alice \
+--collator \
+--force-authoring \
+--chain /tmp/para.json \
+--base-path /tmp/para/alice \
+--port 40333 \
+--ws-port 8844 \
+-- \
+--execution wasm \
+--chain /tmp/relay.json \
+--port 30343 \
+--ws-port 9977
+```
+
+---v
+
+- Register ParaId on relay chain
+
+1. Modify parachain chain-spec and create raw format
+1. Generate genesis wasm and state
+1. Register parachain using sudo call
+
+<br/>
+
+```sh[1,2|4,5|7,8]
+parachain-template-node build-spec --chain /tmp/para-raw.json \
+--disable-default-bootnode --raw > /tmp/para-raw.json
+
+parachain-template-node export-genesis-wasm --chain /tmp/para-raw.json \
+para-2000-wasm
+
+parachain-template-node export-genesis-state --chain /tmp/para-raw.json \
+para-2000-genesis-state
+```
+
+---
+
+<!-- .slide: data-background-color="#4A2439" data-visibility="hidden" -->
+
+# Activity
+
+Follow the [connect a local parachain](https://docs.substrate.io/tutorials/build-a-parachain/connect-a-local-parachain/) to launch your own network.
+
+---
+
+## Non-trivial chore
+
+<pba-flex center>
+<pba-cols style="align-items:normal">
+<pba-col>
+
+- Error prone.
+- Multiple commands.
+- Port management.
+- Multiple process.
+
+</pba-col>
+<pba-cols>
+</pba-flex>
+
+<div class="fragment center" style="font-size:150%;">Zombienet allow you to set everything in <span style="color: var(--r-link-color);font-weight:bold;">just</span> 1 file.</div>
+
+</pba-col>
+</pba-cols>
+
+---v
+
+## Zombienet network definition
+
+Zombienet allow to [define your network](https://paritytech.github.io/zombienet/network-definition-spec.html) with a simple configuration file.
+
+Notes:
+
+https://paritytech.github.io/zombienet/network-definition-spec.html
+
+---v
+
+```toml[1|3-12|14-21]
+# examples/0001-small-network.toml
+
+[relaychain]
+default_image = "docker.io/parity/polkadot:latest"
+default_command = "polkadot"
+chain = "rococo-local"
+
+  [[relaychain.nodes]]
+  name = "sub"
+
+  [[relaychain.nodes]]
+  name = "zero"
+
+[[parachains]]
+id = 1001
+
+  [parachains.collator]
+  name = "collator01"
+  image = "docker.io/parity/polkadot-parachain:latest"
+  command = "polkadot-parachain"
+```
+
+Notes:
+
+https://github.com/pepoviola/zombienet-presentation-examples/blob/main/examples/0001-small-network.toml
+
+---v
+
+### Spawn the network
+
+```sh
+./zombienet spawn examples/0001-small-network.toml
+```
+
+---
+
+<!-- .slide: data-background-color="#4A2439" data-visibility="hidden" -->
+
+# Activity
+
+Try to launch a network with `2` parachains.
+
+<br/>
+
+https://paritytech.github.io/zombienet/
+
+---
+
+## Make the network config dynamic
+
+The network definition supports using [nunjucks](https://mozilla.github.io/nunjucks/) templating language (similar to [tera](https://github.com/Keats/tera)).
+Where <span class="colored-green">{{variables}}</span> are replaced with <span class="colored-green">env vars</span> and you can use all the built-in features.
+
+<br/>
+
+```toml[2]
+[relaychain]
+default_image = "{{ZOMBIENET_INTEGRATION_IMG}}"
+default_command = "polkadot"
+```
+
+---v
+
+## Make the network config dynamic
+
+<img rounded style="width: 1200px" src="../../assets/img/7-Polkadot/zombienet/zombienet-env-vars.png" />
+
+---
+
+## Providers
+
+Zombienet <span class="colored">providers</span> allow to <span class="colored-green">spawn and test</span> networks with in different environments.
+
+---v
+
+<pba-cols style="align-items:normal">
+
+<pba-col>
+
+<span class="colored">Kubernetes</span>
+<br/>
+
+- Used internally, integrated with the [Grafana](https://grafana.com/oss/grafana/) stack.
+- You need to provide your infra stack.
+
+</pba-col>
+
+<pba-col>
+
+<span class="colored">Podman</span>
+<br/>
+
+- Automatically spawn and wire an instance of [Grafana](https://grafana.com/oss/grafana/) stack.
+- Attach a jaeger instance if enabled in the network definition.
+
+</pba-col>
+
+<pba-col>
+
+<span class="colored">Native</span>
+<br/>
+
+- Allow to attach to a running [Grafana](https://grafana.com/oss/grafana/) stack.
+  **(wip)**
+
+</pba-col>
+
+</pba-cols>
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions?
+
+---
+
+## Meet the Test-runner
+
+Zombienet’s built-in <span class="colored">test-runner</span> allows users to use a simple <span class="colored-green">D.S.L.</span> to easily and intuitively write tests with a set of natural language expressions to make assertions.
+
+---v
+
+### Built-in assertions
+
+<br/>
+
+- <span class="colored">Prometheus</span>: Query the exposed metrics/histograms and assert on their values.
+
+- <span class="colored">Chain</span>: Query/subscribe chain's storage/events.
+
+- <span class="colored">Custom scripts</span>: Run custom js scripts or bash scripts (inside the pod).
+
+- <span class="colored">Node's logs</span>: Match regex/glob patterns in the node's logs.
+
+- <span class="colored">Integrations</span>: Zombienet supports multiple integrations, like jaeger spans, polkadot introspector and the backchannel.
+
+---v
+
+```[1-3|6|7|14-16|18-20|22-24|26-28]
+Description: Small Network Paras
+Network: ./0002-small-network-paras.toml
+Creds: config # Only used with k8s
+
+# well known functions
+validator: is up # check all the validators in the group
+validator-0: parachain 1000 is registered within 225 seconds
+
+# ensure parachains are producing blocks
+validator-0: parachain 1000 block height is at least 5 within 300 seconds
+
+# metrics
+validator-0: reports node_roles is 4
+validator-0: reports block height is at least 2 within 15 seconds
+
+# logs (patterns are transformed to regex)
+validator-1: log line matches glob "*rted #1*" within 10 seconds
+validator-1: log line matches "Imported #[0-9]+" within 10 seconds
+
+# system events (patterns are transformed to regex)
+validator-2: system event contains "A candidate was included" within 10 seconds
+validator-2: system event matches glob "*was backed*" within 10 seconds
+
+# custom scripts
+validator-0: js-script ./custom.js with "alice" within 200 seconds
+validator-0: run ./custom.sh within 200 seconds
+```
+
+Notes:
+
+First three lines are the header
+
+Each line represents an assertion
+
+Each assertion is executed sequentially
+
+Assertions on a group check each node
+
+within keyword allows to keep-trying until time expires
+
+---
+
+## DSL extension
+
+Learning a new DSL can be tedious, but if you are using vscode we develop an [extension](https://github.com/paritytech/zombienet-vscode-extension) that can help you to write test easily.
+
+Notes:
+
+Show the extension link
+https://github.com/paritytech/zombienet-vscode-extension
+
+---
+
+# Demo time
+
+```sh
+./zombienet -p native test examples/0002-small-network-paras.zndsl
+```
+
+---
+
+# Extensibility
+
+<span class="colored">Zombienet</span> allow users to use the custom-js assertion to extend and run custom tests.
+
+---v
+
+## Custom-js
+
+```sh
+# custom scripts
+validator-0: js-script ./custom.js with "alice" within 200 seconds
+```
+
+```js
+async function run(nodeName, networkInfo, args) {
+  const { wsUri, userDefinedTypes } = networkInfo.nodesByName[nodeName];
+  const api = await zombie.connect(wsUri, userDefinedTypes);
+  const validator = await api.query.session.validators();
+  return validator.length;
+}
+
+module.exports = { run };
+```
+
+Notes:
+
+Zombienet will load your script and call the run function.
+
+Passing the node name, network info and an array of arguments from the assertion
+
+Your function have access to the zombie object exposing utilities like connect, ApiPromise, Keyring, etc \*
+
+The assertions can validate the return value or the completions of your script.
+
+\*similar to the way that scripts are written in PolkadotJS apps - developer page (https://polkadot.js.org/apps/?rpc=wss%3A%2F%2Frpc.polkadot.io#/js)
+
+---
+
+## More extensibility
+
+<span class="colored">Zombienet</span> also allow users to use as a library to create their own interactions with the running network.
+
+---v
+
+### As a Library
+
+- <span class="colored">@zombienet/orchestrator</span> module expose the start function as entrypoint.
+
+- Returning a [network](https://github.com/paritytech/zombienet/blob/main/javascript/packages/orchestrator/src/network.ts#L77) instance, with all the information about the running topology.
+
+- You can also use the [test](https://github.com/paritytech/zombienet/blob/main/javascript/packages/orchestrator/src/orchestrator.ts#L853) function passing a callback to run your test.
+
+- <span class="colored">@zombienet/utils</span> module expose misc utils functions like _readNetworkConfig_.
+
+---v
+
+```js[1|2|6-7|10-12|14|]
+import {start} from "@zombienet/orchestrator";
+import { readNetworkConfig } from "@zombienet/utils";
+
+const ZOMBIENET_CREDENTIALS = "";
+
+// can be toml or json
+const launchConfig = readNetworkConfig("../examples/0001-small-network.toml");
+
+( async () => {
+    const network = await start(ZOMBIENET_CREDENTIALS, launchConfig, {
+        spawnConcurrency: 5,
+    });
+
+    // write your own test, `network` will have all the network info
+})();
+```
+
+---
+
+## How we use it
+
+We are currenlty using zombienet (v1) as part of our `CI` in polkadot-sdk:
+
+<pba-flex center>
+
+- [Substrate](https://github.com/paritytech/polkadot-sdk/tree/master/substrate/zombienet)
+- [Cumulus](https://github.com/paritytech/polkadot-sdk/tree/master/cumulus/zombienet)
+- [Polkadot](https://github.com/paritytech/polkadot-sdk/tree/master/polkadot/zombienet_tests)
+
+</pba-flex>
+
+---
+
+## The road ahead...
+
+🚧 🚧 <span class="colored"><b>Zombienet v2</b> (a.k.a [SDK](https://github.com/paritytech/zombienet-sdk))</span> is currently _around the corner_ ([PoC of migration](https://github.com/paritytech/polkadot-sdk/pull/4140)) 🚧 🚧
+
+The [SDK](https://github.com/paritytech/zombienet-sdk) will provide a set of building blocks that users can combine to spawn and interact with the network and also a fluent API for crafting different topologies and assertions for the running network.
+
+Notes:
+
+SDK repo: https://github.com/paritytech/zombienet-sdk
+
+---
+
+### SDK fluent api
+
+The new <span class="colored">SDK</span> provide a fluent api for creating the confguration
+
+```rust [21|2|3-6|7-8|10-15|18]
+pub fn minimal_config() -> Result<NetworkConfig, Vec<anyhow::Error>> {
+    let config = NetworkConfigBuilder::new()
+        .with_relaychain(|r| {
+            r.with_chain("rococo-local")
+            .with_default_command("polkadot")
+            .with_default_image("docker.io/parity/polkadot:latest")
+            .with_node(|n| n.with_name("alice"))
+            .with_node(|n| n.with_name("bob"))
+        })
+        .with_parachain(|p| {
+            p.with_id(2000).with_collator(|n| {
+                n.with_name("collator")
+                    .with_command("polkadot-parachain")
+                    .with_image("docker.io/parity/polkadot-parachain:latest")
+        })
+    });
+
+    config.build()
+}
+
+let network_config = minimal_config()?;
+```
+
+---
+
+### Or load a network definiton
+
+You can still use the _toml_ network definition to load the config
+
+```rust
+let network_config = NetworkConfig::load_from_toml("./0001-simple.toml")?;
+```
+
+---
+
+### Spawn from Config
+
+Spawning can be _easily_ abstracted and using some _env_vars_, so the same code works in all the providers\*
+
+```rust
+// Helper that use the env_var `ZOMBIE_PROVIDER` to return the fn to use.
+use zombienet_sdk::environment::get_spawn_fn;
+
+let config = minimal_config();
+let spawn_fn = get_spawn_fn();
+
+let network = spawn_fn(config).await?;
+```
+
+---
+
+### SDK network interactions
+
+The [SDK](https://github.com/paritytech/zombienet-sdk) provides new _interactions_ that allow to interact with the network
+
+<pba-flex center>
+
+- Add / remove nodes (both in relaychain and parachains)
+
+- Add parachains
+
+</pba-flex>
+
+---v
+Example: Add new relaychain node
+
+```rust [5-9|11]
+let config = minimal_config();
+let spawn_fn = get_spawn_fn();
+let network = spawn_fn(config).await?;
+
+let opts = AddNodeOptions {
+    rpc_port: Some(9444),
+    is_validator: true,
+    ..Default::default()
+};
+
+network.add_node("new1", opts).await?;
+```
+
+---v
+Example: [Add a new parachain](https://paritytech.github.io/zombienet-sdk/zombienet_orchestrator/network/struct.Network.html#method.add_parachain) to a running network
+
+```rust [1-7|9]
+let para_config = network
+    .para_config_builder()
+    .with_id(100)
+    .with_default_command("polkadot-parachain")
+    .with_collator(|c| c.with_name("col-100-1"))
+    .build()
+    .map_err(|_e| anyhow!("Building config"))?;
+
+network.add_parachain(&para_config, None, None).await?;
+```
+
+---v
+
+Node interactions:
+
+<pba-flex center>
+
+- Mertics (local prometheus)
+
+- Logs
+
+- Shell Commands (in the _pods_ contexts)
+
+- [Subxt]() client
+
+</pba-flex>
+
+---v
+
+```rust
+// Get a ref to the node
+let alice = network.get_node("alice")?;
+
+// metrics, check best block through metrics with timeout
+alice.wait_metric_with_timeout(
+  "block_height{status=\"best\"}",
+  |x| x > 10_f64, // metrics are f64
+  45
+).await?;
+
+// subxt, wait 3 blocks
+let client = alice.wait_client::<subxt::PolkadotConfig>().await?;
+let mut blocks = client.blocks().subscribe_finalized().await.unwrap().take(3);
+while let Some(block) = blocks.next().await {
+    println!("Block #{}", block.unwrap().header().number);
+}
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Demos
+
+Notes:
+
+- [Zombienet-sdk demos](https://github.com/pepoviola/zombienet-demo)
+
+---
+
+### _SDK test-runner_
+
+The _SDK_ doesn't provide a built-in test-runner as the previous version, currently we are exploring differents options to create an smooth _dx_ using the default [harness]() or [nextest]()
+
+---
+
+## Acknowledgement & Contributions
+
+<span class="colored"><b>Zombienet</b></span> take inspiration and some patterns from <span class="colored-light-green">polkadot-launch</span> and <span class="colored-light-green">SimNet</span>.
+
+We encourage everyone to test it, provide feedback, ask question and contribute.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions?
+
+---
+
+<!-- .slide: data-visibility="hidden" -->
+
+## Activity
+
+- Launch a network with two validators and one parachain.
+
+- Add a test to ensure:
+  - block producing
+  - peers number
+  - node's role
+
+---
+
+## Additional Resources!
+
+> Check speaker notes (click "s" 😉)
+
+Notes:
+
+- Zombienet repo: https://github.com/paritytech/zombienet
+
+- Zombienet docs: https://paritytech.github.io/zombienet/
+
+- Zombienet v2 Roadmap: https://github.com/orgs/paritytech/projects/55
+
+- [Zombienet sub0 slides](https://docs.google.com/presentation/d/1wPjbrqLg9MCfygvBYV5gDra39cSr5TXg)
+
+- [Zombienet sub0 presentation](https://www.youtube.com/watch?v=QKTZZCpdGH4)
+
+- [Setting up a local testnet](https://hackmd.io/kSFS2ButRESeJ7hu_iKKoA)
+
+- [Zombienet presentation examples](https://github.com/pepoviola/zombienet-presentation-examples)
+
+- [Zombienet-sdk docs](https://paritytech.github.io/zombienet-sdk/)
+
+- [Zombienet-sdk demos](https://github.com/pepoviola/zombienet-demo)
+```
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AIzYAFAAAAQGgGLAAAAABCM2ABAAAAEJoBCwAAAIDQDFgAAAAAhGbAAgAAACA0AxYAAAAAoRmwAAAAAAjNgAUAAABAaAYsAAAAAEIzYAEAAAAQmgELAAAAgNAMWAAAAACEZsACAAAAIDQDFgAAAAChGbAAAAAACM2ABQAAAEBoBiwAAAAAQjNgAQAAABCaAQsAAACA0AxYAAAAAIRmwAIAAAAgNAMWAAAAAKEZsAAAAAAIzYAFAAAAQGgGLAAAAABCM2ABAAAAEJoBCwAAAIDQDFgAAAAAhGbAAgAAACA0AxYAAAAAoRmwAAAAAAjNgAUAAABAaAYsAAAAAEIzYAEAAAAQmgELAAAAgNAMWAAAAACEZsACAAAAIDQDFgAAAAChGbAAAAAACM2ABQAAAEBoBiwAAAAAQjNgAQAAABCaAQsAAACA0AxYAAAAAIRmwAIAAAAgNAMWAAAAAKEZsAAAAAAIzYAFAAAAQGgGLAAAAABCM2ABAAAAEJoBCwAAAIDQDFgAAAAAhGbAAgAAACA0AxYAAAAAoRmwAAAAAAjNgAUAAABAaAYsAAAAAEIzYAEAAAAQmgELAAAAgNAMWAAAAACEZsACAAAAIDQDFgAAAAChGbAAAAAACM2ABQAAAEBoBiwAAAAAQjNgAX133GubrQ++ezM9etOKuY5jyuRwfixcfqzS48fkOeuU+Y6fPfv3+lc7Pwbt2Ne4Xi9FJ7zOuQVRGbCAvstvOnfvbqnHLj3/0Y5jyuT4yDmPpj9y7aULz9zccfyYLGsPyVo7tqc/ee2vbVt37zl26fGkvy5oX4O09PrkRVs6XgtADAYsYCAefnBX+vuAFtgN12zrOJ5Mjhuu3pb+yLWXrrlya8fxY7Kc9sZN6Y9dC+iH/7yj41jSf9/4suv1Uuy2W51fEJUBCxiIb13vT+q9dvePd3YcTybHA/cadxfa7T9wEzHpLjnfOxJ76cpLjbvD8MB9rtdLsZ07W3s+Ppq+HoDRM2ABA3HZBVvS3we0wPKP06w5uPOYMv7yX4h9vHbhbd2yu7V6eedxZHKsu9Y7XHrpvSfPdxxL+uuEI1yvl3L5s7DS1wQwegYsYCDe9WYfC1lMM2/Y1HFMGX/5w6pVrLe93pcaTLKf3e8dLkXbtbPlAe5DcN7pnn+1lFv3NY9zgIgMWMBArD3Ug3kX04Xv85e/SXTV5VvTH7X2k3Nhcr3hr7zDpZfuut3HzIfhq1e6Xi/l5pq7W/VK5+sCGC0DFjAwP2n/kq3euvoKzzeZRPmDl1Ws/CYyPY5Mhvf9H+9I7CX/PgzHPXf6HWapl3/JRPq6AEbLgAUMzLVXebZJr/mGqcmTP8tpy2ZvNynaHeu922RSffbjnpXYS+ee5l2Jg5a/O3CXT7cu+T5/mbEYojFgAQNz4ZmeH9Fr85t2dxxPxtvbj/NcuF7atnV3a7UvNZhI373J58yLln/kMn+4eHos6a+z3+HdgfKt0BCRAQsYmLeunUt/F1CBTqx6ePUk+cQHH01/xFpgM8f4GMckamz0FpeiPXDvro7jSP996dOef6WfD8ZvWuF3MYjEgAUMTP7wy/k5H5nqtQ+808dEJsk3r/Nuk1676KxHO44n4+3EVf7A0Uvf+LJvRhuGO2/z/Cv9vI+c498fiMSABQzUv9ziodW99rlLtnQcT8bXww96t0mvfe0qN+2T5rzTfcS8ly440x82Bu3ow5qtHX510S+6Zd32jtcIMDoGLGCgrrzU2/B7zS9Nk+OE1zXTH68KlL8bIj2mjLcvf8a/Db3ko+WD996TPf9K/7+tW3a31h7a+ToBRsOABQzUWaf4RbDX8nfspMeT8fT37/Juk8XkQe6T57bve4tL0TZu8G/CMPjDm9LyUTN9nQCjYcACBuq4w5t7HoKp4uXH7djX+LapSeDdJotv5g0e5D4p8ucjbtnsH4ai5c/RS48l/XfbrcZV/XrXfG5rx+sEGA0DFjBwDz3g2T+99u6T/NVvEtyx3gOBF9tHzvYg3UmRf6ukivexc50Dg7b2kGzPOz6lX+3Bn3r3I0RhwAIG7qav+/a1Xrv0Q25Yxt2ag7PW9m1uiBbbtV/wIPdJkX+rl4r3tqM9/2rQTj/RuKruvXWt8w8iMGABA5ePMOqtG69x0z7u3vVmN0T9yIPcJ8fXv7Qt/fFqP21q7t7z0cv0WNJfn/7olvTQS3u67ALfDA0RGLCAgTvtTW7ge+2eH7tpH3efvMgNUT/avq21591s6fFl/OTXNRXruzd5/tUw3Hqz51+pez/47o6O1wswfAYsYODyrx/e4VOEPbWj/bt0/kyO9JgyPm7+v178/eqUYz3IfdwdNZ21dtqvCpcP4emxpL9WL89am+d93Fvdy38fO+YvfbEOjJoBCxiKu253x9JrbtrH2+wjvsSgX118jmfCjTvPGOqtd77RvwOD9o4TvDa17849bXPH6wYYLgMWMBRfu8ozT3rtorPctI+rt1Tn0h+nFlH+7KT0GDNeLr/AR2qLtnXLbh+fHQKvTe2vG672bxCMmgELGIoLztyc/h6gBXbN57Z2HE/Gw4fO8LrvZ/k7OdNjzHj51vU+Ulu09d/z7J1huGWd16b2XTbryxRg1AxYwFC8dY13ovTabbe6eRlX3nnY3/Jn6Xknynh7+Gc+Ulu0z13i+VeDlo8Sc5nnX2n/veN4H+eFUTJgAUOR/3KYfw24ipc/VNZf/MbT3b5tre+5eRhfxx3ebO32z0Dhzvjb+Y5jSX+97fX+yKaFdcUnDMowSgYsYGi+f4uvp+61/FlK6fEktqOmm75tbQBd/AHPhBtXZ50yn/44tZ/ya8jRh/nms0H7+HmPpode6tqdt/koO4ySAQsYmisv9YDUXvPNN+PnjLe6WR9EHuQ+vvwbUDw3y8PxrW94/pUWVv4u0hNeZ1SGUTFgAUPzfn9977n8xi89nsT22Y+5WR9Ed9/hhn5c3fod78It2pc/40s8hmHjBs9m08K78H3+qAijYsAChsbzT3rvn765veN4Ets/u1kfSDvah3XtoZ3Hm/g8JLt455zqRnnQTqp7/pWK9e0b/E4Go2LAAobqoZ/6K2cvbXhwV8exJK4932jlSwsG1qkneJD7uPkbI0Hh8j/45H/4SY8l/fXhszz/SsV6dPNu34gLI2LAAobqm9d5zkQv5Tcyx7qRGRsnH+VmfZB97FwPch8355+xOf0xaj/df7ePyw7DjddsSw+9tN/efZJvB4VRMGABQ3XJ+f7S2Wvv8cvS2PjI2V7ng+wbX/Eg93Fz9RVb0x+j9tN1X/Q6H4aHHvDOcBXP8+lgNAxYwFC9842b0t8BtMAuu8CD3MfF9V/xF/1Bds+PvTNl3Nyx3jPhipa/ay09jvTXG49spoddWlA/vce/QzAKBixgqNYekrW2u7fvqRu/6q/x4yL/xVaDy4Pcx8vq5Vlr6xbPhCvaiavmOo4l/eWjrVpMb6k5R2HYDFjA0N15m5v7Xrr3Ln/tGwfHvsa3bQ6jU//ag9zHxduP887bovnijuHIP6Yp9donPuh5jDBsBixg6L56pWeh9NKed50c0nk8ieX9p8ynPzoNoI+f58ZhXOQP3Vex1l3rHbfDcL93y2oR3Xrzjo7XFDBYBixg6D7kLfs9l7+TIT2exPL5ywy0w+iGq93gj4v8Z6ViXfwBA+2gHXe4d8tqcW3ftrt19GG+IRqGyYAFDN1J9bn0dwAtsA+f5aYmuvXf87DqYXTPnT5SOy7uv9u7XIp28lGerTNo557mj2lafGe/wzdEwzAZsICRmMv82bOXrrnS1zZHVq9krUc3e20Po507W62jpv3lO7rXv7rZ2mW/KtRcc/eea0l6LOmvq6/wblktvq9/ybuBYZgMWMBI3Pod71Lppdu+73kLkZ1yrIdVD7PT3ugjtdG95yTPhCvaLeu2dxxH+u/uOyyrWnwbN/jCBRgmAxYwEp+7ZEv6O4AW0OZ5f5mPLH+wuIaXb4CK71Mfca0v2uUXbOk4jvSXdwaqn80c448pMCwGLGAk3j/jr/K99paaZ6NE9c3rtqc/Lg2wG6/x0Y3obr7ROVG0U09wMzxovi1W/ezTFxudYVgMWMBIHPsa3/7Ta/mDZ9PjSQwPPbAr/XFpgN33Ew9yj+6Rh50TRdq6ZXdr9cGdx5H++sI/ev6V+tftP/B4BxgWAxYwMg/+1I1NL115qQe5R3TC65rpj0oDLv8IkAe5x+WcKN4PvutGeBjuWO85nOpfu9q/zh73Wv8WwTAYsICR8XGr3vruTR7wG5GvZB9N73qzj1tFdc6pzomiXfEJH0UatKOms9b2bemRlxbX+Wd4dzwMgwELGJlL/sEDr3vpkYd8401EX/6Mj6SMovw6kv4siOGqy50TRXv3SfMdx5H+OuOtnn+l/pf/UTZ9rQH9Z8ACRubUv96U/vuvBZQ/O+zYw71VPRofSRlNN37Vg9yjyj8Op4W3o324jj7MtX3QfAuyBtH8pt2t1cs7X29AfxmwgJFZc3D+Nn5Pcu+l/C/I6fFkdPLX8ratXsuj6P67Pcg9onola83POSeKdMd6r+VhWP89w6oGk4+0w+AZsICRuvO2nem//1pAl1/gOSmRnPYm7yYcVfnDc1//au9aieZv186lPyrtpy99yhd0DFr+DY/5Nz1Kg+gLn3QOw6AZsICRuuZKz0jppXVf87GpSC6/0EdSRtnpJ/qrdzQXnukB7v+PvbPsjuPY2uhfTJw4iYMO2ZbZMsbMFLNMkRlltmOITDIqZmZmRo0Yp98c6ea1U62Zqe5pqO7ee6396a57k1vTajh1zlNOmTOWzlq/lQ4ZAL94dI8uSkS/pYCFiKEqp7aAcx7f5yXJJM+Uc6JmmJQUE+RummU7OObNCa3Zhl/TSei3m5az2QD+IX/Hg36qtF13iOidFLAQMVR/68KYiRuamy2r4HP7emI4vnvTov5EECB0JJon4+HOYFMiGC+eJv8K/GXVPDZUEP2UAhYihm7qPXkUbhjXj7EpExz8C0XYsHn6kI9/k+SADucc2EkR1m9bDxao4roEf7lwstF27SGid1LAQsTQZUfUHcvnsMtngozBhg9B7mY5vj85Q075Y2qNbR3RW8f25boE/5FDArp3tF9/iOiNFLAQMXS3rSGTwg37t3PajQmS9WMGU4bQkWiKa/+oVX8eyMHAH8nN8duSRVyXEAyzRnMgA6JfUsBCxNCdOapaffaDBjevNNnWEoP3/i2yfkxg3eI622+D4SiZZKDPq+cttjVE7z3zN4dtQDCUMRKM6JsUsBAxdHt3SrWe3ALOqKlOt2Z6qOuJwdm9Y8pqYgLWCI4fJHfEFJ895lADJ/zNIQSBWPGOFw0IhtcvKEoj+iUFLEQ0wud88LhCTnFU1xKD8/ehdA+awrNHfDCYYK+v2JBwyvIi8gz9dkQPDtuAYJFrTr0OETF/KWAhohEycuKO+ZMI/g3TLavIbzMFKZpI8UT9jTBYp4+gqOuUYQV86PrtqnnkX0GwbFjKWDuiH1LAQkQjXL2Al0s3bC8hyD1ML5wiU8Ukpv5GcG7YUtR1Rupd2raG6L0yYgwQJDcukVOK6IcUsBDRCMcVcry1G86fIPcnLCV/rDLFrJRJrF/CjnfYnjtOocAJZ8q5hwfhm1fEFECwNDdbVp+v6QpG9FoKWIhohN06VFgN9RQDnCIv5epaYjAOLyBTxTROHKIYELbv31AocEJJMflXfjv4Z+7VEA4LpxDzgOi1FLAQ0RhvX2tWn/2gQd9v2eELw2WzGXs1DTkMQv2dMDgH/UShwClj+1bZ1hG9dcnMGnXZAQKBE0YRvZcCFiIa495t9eqzHzSYNpzcnzA8vIeDB0xDgtx7d6KgG5YLJlMocEJdTdrq+ql9HdFbj3CvhpCorEi3xg2o1yQiupcCFiIaY/HvfPy4gZNuwvHJAzoGTeT3oRR0w7J0E5sQTrh8lpDnIHz+hLFWCI8JA+iyRPRSCliIaIxDfmX8xA3HDtCiHrS9OqWsFr6JjISCbnhev9ik/hyQBTmxUV1D9Nb+P6RaOzMBwoLTohG9lQIWIhpl6j1vmk55fL/Zto7or7NGV6s/AxjCycMEuYehjMnISBzoM2UI3YJ+u3Aqnd0QLg9u846G6KUUsBDRKC+c4gh2p7Q0W1b3jva1RP+UHVUwkxdPCXIPw5E96aB1QlMj9+0gLNtJ/hWEi3QADvyx0nZtIqI7KWAholFuXV2nPvtBg3GFZCwE6dXzjEqZinws9PmaIPeg5VROZ9y6Sv5VEEqHMkDYLJ9Ta7s2EdGdFLAQ0ShnjGQ0yw3Li3g5CkoZlaplVMpoOJkzeA+V0unihF0bycXx2z7fkH8FZnD2GKPtiF5JAQsRjVLCsXnhdE7ZDoLcg3JMnyp1+cEwNi4jHDtoH9yh08UJs8ZQZPXbovHkX4EZSD5gwWf2axQRnUsBCxGN89ljjndzyq0rjKME5eoFjEqZzqkj7HYHqWQ5NTFVq42cYNq7E2Oufrt7C1mFYA7TR1C0RvRCCliIaJx/lzGK4hTZ3ZPRNnUt0XuPHeD6NJ2XzwhyD9JJg+hKdMLDu5xKFoT3btIVCOawdxtjw4heSAELEY2TDhd3DO3CKTdB+PIpHYKmI2PIfb+hwyUo1y3m8A0nMPLtvz2/TFnN1K/AIJ4/YWMF0QspYCGicY7rx26+GxZMrrGtJXprv+/IaIsKjGsE54lDjeryQxYWTuFe7bczR3EgDJjHsG5sNCLmKwUsRDTOrh0qrPo6qgRO2bGO9nS/nTeRUOCosGk5Qe5BSVeiMwZ0pjvQb3euJ/8KzKNkESdGI+YrBSxENNLb10gEdsqFkwRX+23pZj6KosLpcv4eglBGNelK1OfFU8aIgvDmFd4hwDyunufAHcR8pYCFiEYqYZfgjLev+TDyWzntEaLBqxf8PQThrNGMajnh6D7yr/y24PMKq5GzNsBAmhotq9dXdGAi5iMFLEQ00oVTGdVyg2Q0qWuJ3titQ4XVUE+rSVRoDXL/lr8Hv/1zLQHuTlg6mxEiv536G0VVMBeJIlCvWUTUlwIWIhrp4F8q1Wc+aEBwtX9OHMDhAlFjxkj+Hvz24mm6Ep3AabH+u3U1RVUwlyN76MJEzEcKWIhorO/fEgzslA1LCa72y/WL+SiKGptX8vfgt6n3dCXqUvEubVs/9N4r5yiqgrnIfaDLJ/brFhH1pICFiMZ6/gRHszvl+EGCq/1SQsEhWpz5m78HPx3yK52yTjh1lOvRb+UU47paiqpgNmP7VtmuXUTUkwIWIhrrllV0vDjlyYNm2zqiN0pIPkSL1wS5++ofZBU6Yu0f5F/57QRGvSECyJireu0iop4UsBDRWCXPCZzR0mxZ3Tva1xLzc+BPdJpEFQ428M89Wzkt1glj+tB14bcyRg9gOndvsNmI6FYKWIhorHLUcAtNL44ZX8hHktcW/06nSVSZOYogd7+8dYWsIV1qa9JW10/ta4jeSvQARAE5JbfwezZXEN1IAQsRjfbpw2b1uQ85WFHEmIrX7t9Op0lUkVFk9ffE/JViTH0dWUO6XDrdZFtD9FYJxq6u5JqEaLBkRo3tGkbE3FLAQkSjLd/XoD7zIQdlOzmi2Wvv3aKQGlXOHiM42w9lHA702byCQqrfju7NNQnR4dQRnk2IbqSAhYhGu2perfrMhxzcuspOv5d275iympiUiixvXhHk7ocruTc7YvJgRrv9VkLyAaJCTVW69dRM9TpGxOxSwEJEo5WjhsEZdTXp1lEKdS3RnVOHcphA1CkkyN1zj+yhO1aXxoa0VfC5fQ3RW08dJf8KosXU38hoRHQqBSxENFpyVtwxtGulbS3RnTL6A9Fm1hg+Erz28X3GanW5cZmu2CB8/5ZTXyBalG6ut13HiJhdCliIaLwyEgfOWDCZcFCv5FSr6LN1NflDXtrji5TVQv1Km53r+Uj122EFleqyAxjPk4fNtmsZEbNLAQsRjXfPVk6AcwofTN6Zek8HYNQ5d5ywXC+VsRfQZ+YoOgD9Vk7fBYgiQ36lYx7RiRSwENF4F06pUZ/3kIOLHNnuiezqx4O3rwly99INSxmr1UU61Xp9RQab3x4rI5MNosnqBbW26xkRM0sBCxGNd/DPFBGc8u4NH+xeuHQ2u/pxoX9nigheSVi2Pg9uMyIUhK9fkH8F0eQSG46IjqSAhYiRkHBW5/Tj5LW8PbybXf24MJsgd89885L7sS77/mSc228H/cQmF0QXOaVUcgXV6xoR25cCFiJGQoK0nTNjJB/s+cpJa/Fh2xqC3L2w8LuUurSQhfmTOFDDbxfPIGYAos2csbyvIepKAQsRI+HmlWSuOGXjMj7Y87FXp5TVQqNJbJAiuPobo3OLxhHgrks6bVmF39NZ4bd0ykLUOfhXg+26RsT2pYCFiJFw2nA+mpxy/CAf7PkoJ4dBfHhPLpwn7ljHqbC6PH/MNReEzx6z0wDR5u0r7hWIulLAQsRIKKc40Q3jjCcPCQ/Ox+0ldP3FjQEEueftlbNN6rJCBo7soavCb2WkVTrdAKLOqF5VtusbEe1SwELEyCgFGdBHjm/v3tG+jqjnlXN8qMeNOePIGcnHLp9UWNWVVAt0WTKT/Cu/XTCZ/CuIB5tXEPuAqCMFLESMjEf3kXPhlPH92dFzo3yo19bwoR43pKtO/a1R32HdOO3NCUN+rbStIXrr/u2MtEI8uHW1yXZ9I6JdCliIGBlXzqtVn/eQgxVza23riLkd3btKXUqIARdOkQuXj4um0+2iC5lrwfjwLp3ZEA8kJqPvt4y5I+aSAhYiRsYxfSgqOOXATjJY3LhqPsXSOJJ6l7b91qgv3S76nDxCsdRve3NSLMSM4mmMHSPmkgIWIkbGrp9WWPV1jHU54fY1WtLdeKyMcdW4QpC7e+/eoNtFl9UL6H712zljOSkW4gWnRyPmlgIWIkbKm1cI1nZCXW26Nc9JXUfM7vMnbOvHlaLx7HC7sVuHCquxgQ0EXUZzopjvlm6iIzAXF083Wavm1YZuHZmSWlSl0q2bteq1jogfpICFiJFy9xZeWJ0iwcvqOmJm+3Ese6zZXlJv+80xt+MLGeHWpbqKjYMgvHOdjsBcyCmN6rqF4aXTbD7qMmkQxW/EbFLAQsRIyZHZzlk41YwX2Kg4dwLXWJyRjgT1N8fcykgc6HHhJGNAftu9Y8pqoiaSk4E/mbGBtWFpnfqvBhnYtYFNFsRsUsBCxEg58EeOcXcKL0POZCwl3qTeE+TuxvL95MLpsnFZnW390FunjyD/KhdvXplzEua4fnRw6vLoXrNt/RDxgxSwEDFyyvHkoI+07qtriJklZy3+mNKVECWfPmRcS5eJAxkB8lsZBYbsnDpqTiegjNRKvhPkRiIMBvGMQswoBSxEjJxnjzWqz3vIghT81DXE9pWg6oZ6XrLjzryJjNU6sddXKauFfQMt5P5R8Jl9DdFbr19koyEX6xab1Ql47jjvbrqsnMcppoiZpICFiJFz03KyFJxS+H3Kto5od8IAxhySwM71jNU6cdpwxrV0kcKKun7orWw06DFxgFmdgCXF5Ojpcv6EOd1ziKZJAQsRI+fvQ/mYcsrMUdW2dUS7JYt4wU4Cl85QZHDi5pVsGujCKZf+O3kwGw25aGywjOsEHN2L302X+rq01b2jfQ0RkQIWIkbQnl+mrBbiWBwhXWvqOqLdU0cYcUgClSmC3J3I2LY+Ei6urh96KwXV3Ny+Zl4QuORgySEaoAcbj4jtSwELESPp4/tUsJxw4hDt6Dq+fUXQT1IY/DMhubq+4+AMLWRjRTZY1PVDb5UOSsjOnq1mdgJKsDzoUbajwbZ+iEgBCxEj6tG9HOnuBDlBTF1D/K8Df6xUlw1iDEHueg7onFKXDjJw7xb3Wb/t+mmFVVNNF08uFkw28/62aj5j+rq8esEBPIjtSQELESPpirm8BDlBThDr8QWdAdn8Y2qNumwQYwhy11MKfaDH3m1cU347rpAcJR0G/mRmh+nwAjaKnDCiu5m/I2KYUsBCxEg6ujcvsU6RE/bUdcQP7ttery4ZxJgrZwly13HXRv4udKGrz3/XLyb/KhdvXpnducNIsj4blpJfiqhKAQsRI6mEgdbVMEbghJXzam3riB+8d5NctSRRRZC7ltcukDekQ/qfx1Hhd3S5+i0HCuRGDiNR180kjx/kN9Tl+kU2WhBVKWAhYmS9cZkPKycc2EUgaCa7d0xZTVxOiWPIL4xnZFM2Csgb0uPZI7O7XuKgXI+VFVyPuShZZPZm1fIiIiB0aW62rN6dKIwjfiwFLESMrKWbGW1xwp3rBAxncupv1epyQQIwNejYFEf2IK9Gl0OlbBD47cieXI86mB4XMPgXfkcn8JxC/K8UsBAxss6fRLiwE+rr0q072Oo6YoW1aTm5KklE8p3UawE/uHQ2nRK6LJrOR6bfrl7A9ZiLxgbLKvjMvnam+foFOVi6lO+nOI74sRSwEDGycry7c+QEIHUdscI6f4JMjiRy9Tz5ItmUsWPQQ7pK1PVDbz15mPt0Lm5fi8Y9rXwf9xZdZGyWzUfED1LAQsRIy2k2zvhjKl0C7Zl6R65KEqmu4sMgm/dvcbCBDqaf+hYX377meZ+L3Vui0VW6ZAYd9E4Y39/ssVDEIKWAhYiRlhOJnMHIlN1h3cjjSDJDfqVzpj0LPq+wmri9aiGnqqnrh946tAv3aR0kWkFdOxMd+CO/pxO2l9TZ1hAxqVLAQsRIS3aRMy6dicZ4QZAumclOcJJZOCUaH3xBO3FglbpUkIFV88w+9S0OLiOPTQspDKlrZ6ovntJRp4t0w6rrh5hUKWAhYqSdOpTT45zw/i2jLqpyehgkl9JNdCW2Z0kxBQNd5LRGdf3QW8lMys2bl9F6vvPs1Sedtqz+nVO2NURMohSwEDHS9vgiZbUQ0+KI/j/wEvSxj+9zASUZgtzbV8biIDdVKXLUgvDlM7p1cnHySLRGWSWTE/SRLkR1DRGTKAUsRIy8FCCcMXNUtW0Nk2qvr1JWC99FiaaGIPd2ZbxHDznBVF079FZOHNZDuibVtTPZwu9TrZ1FoMeZv7nXIIoUsBAx8h7eQxu6EyQ3TF3DpCrFPAAJiFavjSTb52s+LHXZsJT7qd8WT6NTR4conlT35CEbkLrU1aStgs/sa4iYNClgIWLkXV5EVosTTh5mF+9f/1zLIQBgtY6yqNdGkqWwq8+EAdErGkTNg3+xSZWLxoZoFjfKdvLbOmHacDroESlgIWLkHdWL07Kc8OxRtIJe/fTK2SZ1eSCB7N5CkPvHbltDYVeH+rq01a2Dff3QW+nSyc2tq9HM8ps/ie46J+zdxrMKkQIWIkZeya+R1mrQQzKfJPxeXcekKdeN5B8BXL8YzY8/v7xwkgB3Ha5d4Lrx277fMM6qQ1SL8Py+znj+mA1IRApYiBgL5QMU9JnI2Is1ms49+B+1NQS5f2zFO74odZARZHXt0FvnTaRDRwdZJ3XtouLDu3TYOWFYNzIbMdlSwELEWPjXxnr1GQ9ZWDUvWqcV+eHKeWSnwQf4KGhz8C+V6tJABsij8V8ZmYLc9O8c3a5qfmNnRO20SUSvpYCFiLGQXVpnHCptsK1h0izfT3gsfKD49+h2MHjpwincS3VobmYUOwgf3KY7JxevX0R7rGzOOA6NcMKVc4wuY7KlgIWIsXBA55T6jIcs3L3RbFvDpClZEkmmsiLd2olH3lEbe7ZGM0PGayVLB3LDPdR/e32VslqoX+Xk5JFonyzcqxO/sxOa/nlk9/yS4jkmVwpYiBgb375KdkHCCXJ6VpIzf/p+S3DsueNtHz103LRx4xK72uLNK+QJ6hDV0OwoOWsMnTk6rI3BSNm9m1SwnDB3Ah3DmFwpYCFibDxTTieJE0Z0T27mT9F4ijabV7QFUP/WhcwjQU4yTXJRV2w90bU24ZVdTYrGkX/lt7vIttRifP/oH8pSuonf2gmH9xADgcmVAhYixsaNy+rUZzxkIcmZP4T+W9a0YR8+wCtTFC2E4QXJLeqKo3tzMqcO0r3Z9xtGePz29jW6AXPR2JC2Cj6zr13UnDmKbjsnvH/bkvgNF0yuFLAQMTZO/Y0XICdIEUddw6R443KyP4xaWv6boSGhsGBZi6Ylt6grrijiZE4dnjwg/8pvu3essBo5ZyMnt67GY/RZDkSQbCfQZ0yf6HfeIbqRAhYixkZ5ASIIVJ/LZ+Px4uvUrh0qWjPAkszj+//9AGdUpw05zl29XpLk4d1UDHQ4+BfjO34rHaKQmzhlsUkxDvTZuqotBgAxaVLAQsRY+egeFSxdKt6lbeuXBCUvJOmo+RkLJpMJJkiAuXq9JMmHd7l/6lCc8E69IPxzLZEAOsybGJ9rccc6NlKccOc6naCYTClgIWKspIPAGf1/SF6OS0kxY1LLi/57atXgXwhyFyTAPKm5It07pqxm6ldaDP452VlpQXjtAt04OvTvHJ9nOF13zpAogH7fxef3R9SVAhYixsrlcyhOOGHW6OSdpHXyCEEbo3rZszMqK5I9VvkvST2dc8oQPh51eP2ixbZ26K2MeesRt2ux4HPJPeN3d8LiGfHpwEPUlQIWIsbKkT3pJHHC5hXJy1B486pFXYZEkanLSDLRILkfBBuWMrKlw7ED5F/57aRBjHnrcPJwo23tou71izyHnCAbcuoaIsZdCliIGCvlw7ymmh08XZL28jPwRwqcMpqjrou4cz35I8K+P+MTiuzEU3QmarFi7n/Hb9F7Ny2nmKrD2uL4XYvb1vDbO6GmKt3asaiuI2KcpYCFiLGTHTx9nj2O1whCLhdOIax814b2CzQSBgyWdSuhQe6vXiS7M1GXpI6YBunF0zzDdRhfaB8Fj7qTB9N95xQZ/1bXETHOUsBCxNi5ayOdJLpICGjPL5MTArp3G9dG0fj2R+QG/kR3miDZO10/ta9PnO37bcpK07iak8pU++O36J2yvtVVXIy5kKyobjHsvJFuIhlzB31KN7W/KYUYVylgIWLsnDuBThInSN6IuoZx9e4NjlnLdvJkxTs+HISRPZLVZTNnLAHuOpw9lqyR6zAc04cOHB3i3Cl6hTxGRzx52GxbQ8Q4SwELEWNn4fcp9fkOWVi9IH45Gu0pJxw1JTzmJ9epVYzutLFkZvtdanF1ewmdiTqsX5y8Qy+CtqSYk4R1KN0c364bMtCcM+TXZG26YLKlgIWIsTTpJ8054VBpMk7VkpyIpJMrtJ9CRhv7t8f347A9OYFSj3ExzBwyzTPlCd9l0EQyC9W1i4sTBtCF55SkbEQiihSwEDGWnuYlWBsZq1PXL46yq2tZ63J0kBSNo8gn3L4W3/Gc9pRsJ8hOazZaDDOHTJMxZj36d848Ch51JYOQ06Sdcel0sp5ZmGwpYCFiLN2wlGKFLg31yQitPnecomauvDPJx4Lk/E2IQ7sS3q/DlXN8IPqtnPAIuZETQ9W1i5sXTvG8doKE+vf4Ir5FTcSPpYCFiLF0yhBa0J0wIgGh1amE7+w3NVlW9472dVF9/4bxW2FUr+zFvri4aBqHXuiwdXX27kXM35XzyL/S4cSh7KPgcXD9EjYhnSKHcajriBhHKWAhYizt3jFlNXPgnDbF0+KbpyHSZWJZ927pjYqeP8HOt7B0VjIyRfb9Se6ZDlOH8nHot8cPcu/RYe0f8b83cRqlcw7+lYw8U0QKWIgYWx/eoYKlS+mmeIdWL5lBl0nZDr2X221r2PkWdNcr6t6+xn0yF9K9yHiO/3L4ih5JOEygyycVVhXZfI54+yr+o6WIIgUsRIytcroe6HHlbLzzXWRnMuksmq7XZTd7DEHuwp3reh1rUVZCySXvC7IjRT517dBbB/9Ml6wOrfl8CTlM4OwxOvKckpTRd0y2FLAQMbYunU2ehi6VFWnb+sXJR/foMpExSnVd2rPwO4LchSR8KI7rx5iODnHvUDXBJTPpktXh5pV4bzZ9rIxKgjPktGV1HRHjJgUsRIytEkwO+sT1WO6eX6asloTXr6or060jGeraZFJGEcCyRveO9272qvl8IOpAOLL/HtlDl6wOSSqmjuzJO5xTbiWowInJlQIWIsZW+WCvqWI8RpdZY+L5kTZ9BCNxl047e6lldKONZbPjHZZcvo+iQS7S/zxC+nwdz+K+ST5/QtFch7kT9EbB46C8wyX99GCntPzzZ9T3G+5XGG8pYCFirL16vkl9vkMGNq+MZ+s5oeRW6xqo65LNratYM+HAzngHuT95mPDWRA0e3yf/ym8Lv0+1FgohN/1/SFZx4uQRNlOcUvx7coqcmEwpYCFirN25niPidTl1tNG2fnHw8lmKmDNHOeuumzWarjXh7o34Fi9aR2tpeslJ3IuYJrhwKvlXOrx6nrxT5lbOY8zZKccPxvNdDvFfKWAhYqwtGs+LsS4ywqGuX9SVEYTqhI+Rto5AORwpkBEEOiIsq7HBsrrFNMh92jCKlDr8MZVuBr8t28koqw5JLEwM60YOllOqUmmr66f2tUSMixSwEDHWymgC6CEFC+nKUNcwysqR0knn2WN3hcnXL2jPEcb0iWeQu5xWBbkZ+KPe6Z3oXhnThNysWRjvTL5MvuFQEcdMGhTP5xaiSAELEWPvm5e8/OgSt5eeFXMZP/i7zN0I1Jm/yR4RlhfF86OR3zc3L5+5K/6ivtIdSrenHuP6xev5rOuxA3ToOUXiM9R1RIyLFLAQMfZKthPosXpBvD7WOWXN/W8qof5gWQf/clcANN23dDXkpHx/PH97k2TMX4/6urTVNabjzLmU02DBGQ/vxje/EZECFiLG3vVL+BDX5fDueH2wPX/MR/rYvu527WeMJCNJuHczfh8C/TszWq3D8jnuir+o7+4tHLSiw43LTba1S4qDfyYHyynS1TjwJ8afMZ5SwELE2Dt5MDlIusTpY53RFMtqqHe/a8/6tRHHIPe5E+h60UECpNW1Q2+VZw7kpnRTskfCXpHJ6BiJUFDXETEOUsBCxNjbvWOF1dSkPtqhPRob4nN6zZxxdBDdupLfrr0c2w7uu9hMddcGul5ykXqXtq0beqscGtJM/UoLKTqr65ckj+4lDsAp508k79RKTIYUsBAxET64w1uyLiN7xKPrgI90q3U8R10XJ5If10bcdrKvnqein4sz5Xz8+e3MUWwy6NL/h3idEOzURdPpGnWK5KYVfG5fS8SoSwELEROhBDGDHoumxWOn98YlPtIXTM7vt9y0nPw44VBpfLLhunxSYdVUMRuai5LieBUtTVROSoPcSCesunZJc0BnRtrdIEVidS0Roy4FLERMhEtncYqNLqWb8+vaMUHJfZLdx6QzKM8Q12nD6ZAQ7t+KTzbciO4EIusQt7FRE715hU0GHY4fpBtQ5FAW5+zfHv33OURVCliImAj5aNPnyrn8cpNMcHwhwf3v3+a/a9+rE7vegmToFXxmX58oumQmozi5qKuJTxagqcpokxyQALlZs5BuQFE6YcEZEn6vriNi1KWAhYiJkLEZfSoroh9evLaYjruzx7zZtX/xlF1vYVxhPDpyynbyEZiLy2ejX8Q33am/0d2py7h+8bj35OvCqRTf3TC8IL9ObETTpICFiImR4GJ9JG9CXb8oefIw4eOSX6WuixtZyzZWzotHF8S9mxxokYstq7z528HMbl1Nvp4OMgovI/Hq+iXRvt/SEeyG9Uu4n2G8pICFiImRwFh9Zo+JdvDnm5d0DU0d6s1vuGEpH5rC4d3RD3KXMcgm6pE5mTLEm78dzKyMqkNublymG/BjH9+nAO+U6xe5hjBeUsBCxMQ4ZxwjC7pEuQNh4I/knbW0WFbPL73popNCGFjWgzvRD3KfOIBsuFxIga97R/vaoXdKR1FdLa00Ovy1kRDuj5VQcnBGc7Nl9e7kzfsAoglSwELExFj4XUp9rkMGTpd7k58Uhgsmk5Px6J53xRYphDG28b8g98/t6xMlyYbLza2rdCv47QQKqdoUja+xrV+SnTeR57sb5L1IXUvEqEoBCxETpZzIArmR4G517aLi3m3s0MppTeq65OMzji9vZXz/aIcpHztAgHsudtHx4ruMJevT/wc6Zz62z9ep1g5jcEb5Pm/fCRDDlAIWIibKk0cIgNFBOm68GkEL2rs3yMhYNtvbwPHjB/m7EVbN93Zdg/Y5hciczIp4/l8UPH+C+4kOL59FdyPJT2WcG5yRepduPY1bXUvEKEoBCxET5brF7PzqMnlw9LpNZMSLkGrLGtnD22Oz+btp48ie6O5iSwYKo6DZkc4OsmL8VT6iqyu5EHWQjQN1/bDC2r2FLms3jC+M3jsdYntSwELERDlpENkbuqxZGL1uEym6JZ3aGu93WuVUNrCsh3e9yxYL2hkj+Q1z8TAGQf2mO7o392hdVi+I3jM4COWUZHDOn2ujezgP4sdSwELEREmHjj6HI9htsnEZnUJXz3sfQt3ji5TVwtRG62lOUT2hbusq/jZyISecqeuG3rr2Dw4S0GVsXzpm2lPiDeReDM64d4sCPcZDCliImDjv3+LNR4covuycPUZ1cud6fz7Cnzzk70aQE9TUtYmC5A7lhpO6/PfUUa5DHerr0lbXDvb1wzbJunSOjJBzKADGQQpYiJg4D+zkJC4dGhui9wJd8Y5slTnj/AmhPlbG340Q1bGe928JcM/FgM583Pkt16EeNy5530kbJ+W0UHDOUo8PeEEMQwpYiJg4l8ysUZ/pkIGRPb0NA/fToV0q1X/9RFL4vT8f4SXFjP4IRyN4HPngn/nbyMWLp5z45rfDCrgOdZECjbp++EEy/dxxppyDATD6UsBCxMQ5nJdobRZNj85IzeIZFCZfPffvI5wDENp4fD96o7UyGgfZiWJhMmquKKIIrkuRT520cbF7xxR5pi6oq0lb3SLWWY+oSgELERMnx3jrI8dVq+tnqgd2MeJ28rB/u6sSXk5wrtUaZi8fT+r6mGzpZsZtcsFojf8yhqyHZBUVfhete0wY3rrSpC4daDBtGMVRjLYUsBAxkV45x4uPDn6caOeXD+9SXSlZ5O9HuHQfgWVNHBitIHfJ04HsyAiyum7ora9fkH+lw0vGWbXcXkJh3g17tkZnYxKxPSlgIWIi3bGOFx8dKlNp29qZqByrLZ0xSWeizyfkle+jg0JY+4e/hUIvlY5TGRuBzMjhD+q6obcO+onRfV2OHWCcVcepQ8nBcsOzxxRIMdpSwELERDpnLC8+ugz80fzOhOkj+D0lD6Tgc/vaeOmahWTYCOX7o/OBOaoX2WW5OHXUv9FbbFPyFEGPqJ50GrQFn1VY9XUU590wtKv573WImaSAhYiJtO+3qdacCcjNnAiEyW5bU6f+ayeOuzf8DxeXDi+IVpD78jkUHXMRpY66qHqolO5NXcb08beTNk5eu8B4tBvWFnPPw+hKAQsRE6uc2Aa52bq6zrZ2pnnpDC+x+7f7n2shHV4EuVtWyz+3jh5fRCNkmcJBbigY+O+zRzxvdZCOoq6cEqft1lVsXrnhytno5JsiqlLAQsTEKie2QW7OlJs9XtN6qmQV7XSLptXY1sYPCctvY9KgaBQ9Ht7h98pGTXW69R6irht6Z7/v6HjW5fpFCgtOlPswOEciByQ7VF1PxChIAQsRE6uc2Aa5Mf1EpJE9CQcWfgvoFLUje+joEaIwgtG9Ix1zubh4moKB3y6YTP6VLrs2+N9JGyelW41DKtxRND6YTS9Er6WAhYiJdeJAdu50kJ3zXp3M3albUUQhMsjTIlfNZ72Fv8vMD3KfPJh7XC42LTd/RDrq7tvOqb+6FEUgc9I0iRBwx+Hd5j/DENuTAhYiJlbJ85E2asjNlCHmjksd3UdH0IVTwY15ji+kKCI8eWh+kPv6xeTD5CIqo6BRljFWPWSzqPA7czeLTHXjMu5zbnj/toXxaYykFLAQMdHeu8WLtQ4mn9L17DHhwEEG7cvR5RR+24LcTc8QIecvO40N6dbrWV039E7p3pW/FciN6eP6psqmins4wAKjKAUsREy0ZTvp3tFBco/UtTPBPt8QDizMGBns2MmD2xR+BZM7E8WXz6gcZOPGZfKv/HbO2Gp12SEDxw6Y+Zw13a6fVlg1HOTiCjnFUV1PRNOlgIWIiXbxDMJldbh/y8xxKT6O2sZO+nwdbCfQoVIKv4IcBKGujSn2pbibk53rCcz229JN5F/psnqBufcT0z1/gm5TN9y5bua7HWI2KWAhYqId1o0T7HRobLBaT/tR1y9s5QM06Tx7FPzYyYq5BLkLJndMzB5DcTcXM0cF27mYROUDGfRgnMu968j7c4WM9/Yjdw0jJgUsREy0EmBZlaJNQYdRvcx7ub5+kdOHyvcFX0QZ14/MESGM4qGu20v4oMtGS7Nl9fqKDzc/7d4xZTVxi9aivi5t5CZRVBzdm2eSW2QSQV1PRJOlgIWIiffyWd6wdTDtJUdyL+SlP+msmhf82Em3fz60JAA76ciInqlFkEunua9lQ3Lc1DVDb50+gi5AXWQzRl0/1Fc2IysreCa54eSR4E4xRvRCCliImHjpVNBj9xaz8mLoAmojrLGTezcZDRKmDDFzDI2Puezs+9Os+1kc3V7CiLcuuzZwPebrmXJysNwgAfh0/2GUpICFiIl3FlkxWly7YNYO8do/yGEKc+zk4F8EuQvrF5t3itNvXcj2y8X8SWZ1lMZRRrz1mTPOzEJ4lJQQfHCHqRsxiO1JAQsREy+ndelRXZm2rV2YnjjEbuvNK+EVFZcX8bEgHD9o3vhF8e+crpoNud8Xfm/m6GdclDHjhnoerDrI9UiQdv6O6EHh3i1yWqi6noimSgELEfEfXz5tUZ/n0A6Dfqq0rV1Yvn7Bb1a6ObyXThldBMt6/ti8IPe92xjdyoaJv1ncnDyY+4MuL55yPXrl+ze8F7jhyQMyATE6UsBCRPxH6aKA3BQZMubQ/4eU+q+WSMIcgyJEv43WIPdOZnVP3L7G6FY2juwJ/uTOpLl5JdmSuhwr43r0ypOHeZdzy5BfzNmgRMwmBSxExH9cW8w4lA7b1piR97NgMiNSwsCQO+Lu3iDIXZg61IzCrkhhMTdLZoZX+E2Kl85QRNVl1fzgT5KNqyvm8i7nFskQU9cT0UQpYCEi/uPEAYw76HDmbzPyfvZsZUTq7evwx07KdhLkLmxYakZhVxzbl3tZLob8Gm7hN+5KEbWmmiKqLmGdJBtHh3KAhWsung4vUxPRiRSwEBH/seCzCquJzvOcvHwWftFEvHOdzh8TiolLZ7PbLcjYiro2YblqHr9JNt69MeMeFmfHFVJE1aWuNt1a8FPXEN375iU5WG5obEhbPb4waxwesT0pYCEi/s97NymK5MKEvJ+Czyv+edFS/82Sx8Zl4Xf9jOrFh6rw/Ik5RZGje/njyIZJxca4un4x+Ve6XL9I14vX/l3GPdAts8eYMw6PmEkKWIiI/7NsBy89OkwZEu4LzqRBFE2EsH8Hscsn5C0JUtjtHXJh918f36cQnw1yXvz37DHamXXZuT68k2Tj6tJZdKG65cAuDhRA86WAhYj4PxdNJxhcBwm8V9cuSCVvKOm0NFtWzy/NKJhw4l0b04aFX1CU8Q+5NiAz0jWorht6pxS1KysoausyZ2z49424KYebgDvevjKnmxgxkxSwEBH/59CuvPToICNK6toFKbv7lvXwTrNtXcJy33YC9QUTgtzlNETITHVVurXAoq4beufInjxHdZHOzX7fmbERETclrxPcIX/D6noimiQFLETEj2TnODcPbodbPHn/hhfTQ6XhFhE/dskMOheFk0fCz1aSXDTIzIWT4f9GcVdGNEEPk7Lz4ubhPURCuGXT8vA3YxCzSQELEfEjL51hHCoXclpjtw72tQvCIb+yuy/I6X/q2oTliB78JsLLp+F/jJ4ppzsxGyYcfBB3JSQf9JCwcXX90BuLp7Gx4pabVzhYAM2WAhYi4kf+uZYOBh1Gh5QjQ05ZGyO6m9PiLyNZdTV0Lso4UJ+vwx0HevOK7sRsTBwYzn0rSb59zTWoy6p55mxExM3C71Ot92RwjuQohv0sQ8wmBSxExI+cNZoMGR1kbExduyA8sJOxgJpq83J8ZMcWLGv6iPACmeWDDTLTUJ+2Cj6zrxt659AudGM6YXRvCqp++uwRxVS3/DE1nHc8RB0pYCEifqTsOrFrl5u928I5+lvCy5POlXPmtffL9QDhZocUjac7MRvXL5r3dxM3l80m/0qXutq01fVT+xqidx7YxYaXW44dYLwVzZUCFiKi4oun7NrlIoyPwZ5fplpb25POjnXhFA+zuYi8kVZOHQ0vJHzneoqI2dheYt7fTdws30fBQJdrF4J/hibNBZN5LrmlMmVepzfiv1LAQkRUPH6QENpcVFembevmt9OGM94pzBkb3phaJocXMDokvHoeXpC7dOZBZsIc70yKL5+x+aOLFJzV9UNv7fsNHfX5QGYgmioFLERExbV/MAahw+Cfgw0S37qagH15Ge/3nXnhqrJTK9lcSUd+H/loUtfHb2X9pagM7SOdm9LBqa4beueAzmSwOWH2GAqqQfj4Pm3bbqHIiqZKAQsRUXF8/yr1OQ7tIJk76tr56aXTdJhIh4O6LqYoY6UQTqfPMDrgsnLvVrNtzdBbixkj1qa10P0tBdUg3Pcno9VukcxRdT0RTZACFiKiYrcOFVZjA90Mudi2JrjAaukwqUrxm8h4q7o2prh7Cx8KwuYVwf1d/OviGRQPshHWoRNJ8uBf5F/p8vyxuRsRcZPDLdwjhdaBPwXbaY+oIwUsRMR2vHuDtvNcnD0WXDFlRA86TIS1xbW2tTHF4t/5UBDOlAf3d/GvZTsoHmRj3sRgu0WT6JOHPDN1Kd/PCW9B2btTymohms01K4rMfefA5EoBCxGxHfdtp5skF0EGVi8vIpdMmDDA3FDVoV0pMgqvXwT3d/GvFNwzI10EhQbmxsVJwrKdsWoeRYEgvX+L+6Nbzh0PfkMGMZcUsBAR25E8j9zIB4vsbqpr54dH99Jh0tRoWQWf29fGFAkSbyPofBtGnrPz9CE5Ln4rHW6gz+je5m5ExFHG291TX5c2+r0DkykFLETEdvytC90kOkz9LZjA6mePmAGQLht1XUzz2gWC3IWZo4L5uxA5dCI7h0oZ1/JbyRgDPepq01bXT+1riP45a0y1+jOAA2aMDO55hqgjBSxExAym3tPVkIuSADKZ+nzNeIogpympa2OapZv4kBW2rAouyH3NQsZrs7FoOvlXfvvgNiNaukiRX10/9NceX6SsJvZWXCORGuqaIoYpBSxExAxePM0bTy6O7vO/u2E2u6etSEi6ujamuXAKo0RCkAcc/F3GeG02Bv/CKVp+2vPLlNVC/UqbnespBoTh7WtcpG4JMu8UUUcKWIiIGdy2pk59joPCgzv+j7XJCz9Y1pBfzf8Ql39HsKw3L4N74We8NjNvXgX3OyRVxrOcIRsy6hqi//IekR/DCsx//8DkSAELETGDkmMD2ZFgcQmRVtfOS69fpBOusiJtWxdTrUwx7ykEcfJdr68Yr83G8YPBdcIl1V0bKQzo0nrAwzf+3xfQ7vQRvM/lw/rFwY3FI+aSAhYiYgblhD0+DnMzpo9/JypJ2G1dDT/ChZPR+RC/co6CozBrtP+dFnyUZWfVPP8z+pLu7Wv8vevy/DEdgWHZvaOc1qr+IqAL2W1okhSwEBGzKC+ckJ2ls/z7SBzblxPWhK0BhoLn664NdGQIQfxmEhYPmRnZg7EXPy34nKKAE8r3+58ZiZm9cZliq1skBF86ftU1RQxDCliIiFk8doC381zIEerqunklJ6y1IZ026tqY6vxJBLkLQQS5nzveqP5j4X9UpdJWl0/sa4be+ftQOgCdsJKOwFD9cy0F/3yQZ7u6pohhSAELETGLFFByIxlV6rp5pWTYJB0ZY+3VKTo7n4N/JshdeBtAgPj7N3SIZuL8Cf8LiEmXg06cMbqXf+P2mNspQyi45kMQp04j6kgBCxExi+MLGWHLRXWVfwHjr17wgf7kof8nPXpt6h25ZULh9/4VHgd0Tqn/OPiIDUv9H+FMulfPM5Kli2Q5SqajuoYYnAWfVVj1dTyb3FLxjq5WNEMKWIiIWZQT9hobeOHJxeBfvM+akY9/iOau56UzfNgKs8f4N/rJqGZ2Jgyg28VPu/7zbKyr5dmoixT71DXE4KXomh/jCrmvYvhSwEJEzOGd683qMxwU5k7wPhuBD/Q2opibsmMdQe6CjFipa+OVf21kjTMhXRay+aCuGXrnxIF0JztB7onqGmLwbl7J2Gs++PlMQ9SVAhYiYg73/cmHYi4kHFVdt3zdvYV1F0b3jt6OpxQ0wd8cJsmeg/ah28V/Ny2nEOCEWT52Y6K+FF7z497N6EUaYPykgIWImMPi3/kYz4UfJ67dvkbnm4zoRDE3ZeBPBLkL7974E+QuOSQ11YxvZYIuAf+9cIoDNnSRgzj6fuNfHh7qK89T7p3ukWu5/w9cyxiuFLAQEXM45Fc+xnMhYevquuVjweeSPab+U5LHjUvR7SSRwFf452W/s/cv+yN7ck/KxrRhdLv4qRRQ5fAO0OPZY2+fj5ifF0/TvZoPS2dFL9YA4yUFLEREDVPveVnPhuzK9fnauw/1SYNo8xdKN0U3N4UOjTbmjPW+mLJsdq36j4H/0dxsWT2+8O5ehHbH9OH+7ITyCB7EEWflhFJwz+ly7zvuEZ1IAQsRUUM+xnMzdah3H+q8YLYxb6L34fhBub2E31DwIx/u4F+0J2bi7g0yWvy2pJgCqhNWzKVjxSTH9aMAmw+1NRySgeFKAQsRUcOtq/kYz0XJIu9e0s/8TcFQGPhjpW1tomLRuGr1/04iuXDS+93qB7fJh8uEHP6grhd665ly7s9OGNUregdxxFkZga1K0VWfD4xpY5hSwEJE1HDGSD7Gc1G+37sxifdvWtT/+cTx5lW0c1Mk6BUs6/1bb39HyYdron6QESmcqmuG3kq+nT51NenWgom6hhiu545zE82HPVvZKMDwpICFiKhh706p1pwnyMzDu96M7gz5hYBqIQ45E3IKH1jWAA+D3MmHywynvfnviO7cn51w9Xx0D+KIs4zB5gcHE2CYUsBCRNRUHtiQmaYmyyr4zL5uTl00rUb9n04kkgOmrk3UPH+CXW7By64gGdWF9nnywJsiOmZ25TyuPydsL6FTxURlrBPyY2jX6EYcYLSlgIWIqOnfZQQn50JOp1LXzallO1lnYcqQ/NcybLetITtO8PIj9sQhioKZkHB7db3QW48f5PpzwqzR3hWv0TtlrJPTpfNjbbF3uaeITqSAhYio6eoF7DznYuns/F9oHtwhoLr5nyXo3jH6o1Czx5AdJ1w87d0Y0cundIJmonhadE/tjIqSzQd6yEhrH0ZajfXUUYqx+XDlrHfPNUQnUsBCRNSUo5dzs+/P/DpNenyRslqoX7UW8dS1iaL9viPIXUi9S9vWxo2S70QWX2YG/8xIi5/K+oI+zx6RE2Syq+azKZkPcphIzy8p0GLwUsBCRNS0a4cKq76Or8ds3LiU346cHM0MlnVgV3xGod7SsdHKwB/zL67IOBK0z+sXFAv8dslM8gmdcHRffO7jcXR4AQXZfCkaT9crBi8FLEREB96+1qQ+v+EjaqrzOzJ86yoykwT5UFTXJqqePcaYhjB3Qv6/KZlimTl2gGKB3x7ZQz6hE1YU5T9Sj/7KSbn5cXg3910MXgpYiIgO3LutXn1+g8KQX9x3mkhWEFitO8Pq2kRVipJt7FiX33iteOEUxcBMrJhLscBvnz/hY98JctKduoZolhxKkB9SAMxn0xLRjRSwEBEduHAqIxS5mDfRXaeJvARVpRjRrK7Kr4vNNGeOYuxNuORBkDunZmVmRPf4FH1NtPB78tecUFsTr/t4XF1eRA5Wvnhx+jSiEylgISI6cPAvZCbkYntJnW3ddJQPUIjfyT4Ej7chxSd1bZwonY3QPpUpigV+y+aNM66ej9d9PK7yTpc/W1a5e+dDdCsFLEREh75/yxhFNs4db7StmY7L57ATKmwvyX/UzDQlYBssa9BP7ruE/qCAkBHJWVPXC721bCf5V06I4308rvJ8yo/b1+JxajJGRwpYiIgOPX+CzIRsuD0NjIDgNmaNqbatTdQ9U87fjOB2vFbcs5X8vUysW0wHgN8+vt+sLjtkQU4MVdcQzbR8H+8e+dDSYll9v03Z1hXRLylgISI6lFDq7Mi4WJ9vnL/MPH3IB5KsXRxfBDev4G9G2LnefVfGrSsccJCJcYVksPhp706p1o9U0MPtMxDDcckMulvzZdF095sziE6lgIWI6NDpIwilzsXvQ53tPvf5mpwk4eVTd91rpsvfTBuXXeabdf20wqqv4w+kPepq01bXDvY1Q+8sGsffrxOamizr2oUmjIj3brJ5li8nDjHGjcFJAQsR0aG9vqLYkov1Dkd6ZGwOrNYjvdW1iYPSwcHfjNV6yqa6NjrKKU/QPlfOuSsKor67tzC+CgCZkdOT2UjAoKSAhYjowmePmKfIxt9lDbY1y+aOdXwgCWv/qLWtTVx8+Yy/GUFOvVLXJpcr5nLAQSa2rnZWLEfn0qECALmYMoRRbgxGCliIiC4s30/oZzYe3XN2Ko208YNljY9xls+pIwS5C/MnOc8KOcwBBxmZ6nBcGZ3Z88uU1Uz9CgBy8NdG9xmPiE6kgIWI6MJV8+mIyIZkgBR8Zl+39pR8n7oa5ssaG/TXLIpuXEaQu7Brg/OXfE6Aa5+mRsvq3pGwbD+dOYrxbgDIjTyn1PsHoh9SwEJEdOHYvmTS5ELWSF239iTfp43b1+L98jdtOB/CgtPMph5fpKwW6lftEve/GROUkzMBAHQY4mJEHtGpFLAQEV3IqWC5WTZbL89p9QK62YS925x35kTJXgS5t1Jd6SzIfepvFP4yUbop3n8zJnjzCuPdAKCHTCeo9xBEr6WAhYjo0ltXebHPxr7teh+XcvIeWNYfU51nI0XN508IcheG/Kq/S71hKaOXmZgzlvwrPy34vKJ1tBkAQIcLp+J5kjKaJQUsRESX7tnKaEU2blzWG5V69ZyihuDmdLqoefIwxUphwWT9YuWpo6xZe0g3X5+vyb/yU7r/AMAJjQ1pcgnRdylgISK6dOGUGvXZDR9RU522unxiX7ePLfw+pf7XEknFO2djZVGVbqI2nJzW9PoFBd72IDDYf7eu5u8VAJwxawydseivFLAQEV06+OdK9bkNCrlGpeZNpAgonD+RjLb7qUPp6BCuntfrTiz8jgJvJsp2NtjWC71VDhwAAHDCAe7N6LMUsBAR8/D9W7ojsiEFKnXNPnb3FsYwhc0r62xrE0d7fpmyWviTsaqrcncninPGUfDLxMIEZMaFadcOFVZdLacuAIAzpGtYvZ8geikFLETEPJTOGcjM9pLso1K3r7HDL0wbnpyW+2ePqWAJv3XJ3p0o7lhHgTcTA3/MvX7o3gkDqtQlBwDQYmQP7s/onxSwEBHzUDpnIDPZRuO6dZATrtjhlzDqXp2SE3rKqZNt6HQQXTlLgbc9Xj5jh99vyasDALdsXJaMrnIMRwpYiIh5KJ0zkJk3rzJ/aE4cyA6/kLQw6nWL+TAWSjdn706UEcPqSgq87VG+n4wVv6W7GADconsKNaIbKWAhIuZhr6/I9MlF32/a7y5av4RChnBkT7I+xqcMoXApXL+Y/QV/WDcOicjE8jm1tvVC76R4CgD50NJsWX2+bv/dDzFfKWAhIubpk4fN6rMbPiJTvtOZcnb4hRVFyfoY7/FFqvXlNunU5AhyXzSdEzozIcU9db3QO0f3psgMAPmhMyaP6EYKWIiIeXp0X4P63IaPkE4rdc3Ed29oXRNG96qyrU3cpejbxtCumQsx+7YT4N4eqXdp21qht65ZWKsuOwCAI46VJau7HIOTAhYiYp6unMfLfjbae4kZ/AvjUYIcU9/1U/s1FXf/LqPoKxT/nnmH+s51inztIZ2b6lqht546QncsAORHZSp7lzGiWylgISLm6Zg+jFtko72Q8uJpjEcJuXKQ4uraYoq+wu4t7Qe5c0JnZkqKkzVyG4bv39IdCwD5M3FA8jrM0X8pYCEi5ql00NTX8bGZieZmyyr4/L9rVraDDhxh18b2Cxhxd9Igir5CpgLmuELWJxNj+/JB5KccHgAAXrFjXTLfcdBfKWAhInrgzStN6nMbPmJcv/9+dD64zXiUMHdC5hGyONu9Y0VrYTPp1Na0P2KxegEdau1RV5PMkdsgXV7EtQcA3vDgjr0DHzFfKWAhInqgjAJBZj4+9r57xxTFi//Rv3Nyj5mW0VKwrGEF9iD38v10KLbH5bPtd6yhd5JPBwBekU5b1sAf7c84xHykgIWI6IELJpPplI392z+0kf8+tFr9jxPJm5cttusoSXJ6ZxuSB6euzVNOaWyXLavaP9EUvfPVC/KvAMA7pKtTvc8g5iMFLEREDxz0E7kh2ZARy3/XSj5CwWo96Uu9jpIkY3Jt7Nn634yQXl+lrBZqCO0yZUi17TpC7xzIcwwAPObssWS/66D3UsBCRPTI92/46syEZNf8m/Vz4RRHtAvrFye7m0ROJwLLunH5v2Nx04bTodgeTf/cNiQ7Tb2O0DsXTaeTGAC8RQ45Ug/yQcxHCliIiB557jiFmWz81qWytYhVmeLERkFO4lOvoSQpL7RNnH3wn+KuuHkFHYrtceujLk70x0OljPUCgPdMH0H3LHonBSxERI/kwzM78yfVWMMLGFERJMRewuzVayhpPrxD1pMwovuHkFsZtwA7uzZwHLvfPntEFzEAeM++P7l/o3dSwEJE9Mhpwxj9yca+7fXW+iUU+YQHtzlaWjyyh44PQUa3/l2Tt68pIrTHrDHs4Ptp4Xep1hPDAAC85sXTZB9ag95KAQsR0SN7fpmyWmgoAQ0O7GywXT9JdNV8gtyFvdvadqcHdE6p/xH8g4Ta9+5Ex6KfcpIuAPjJsIIPncaI+UgBCxHRQ588oIIFuVky40PHTZIdX0iQu/BvvtO8iRQR2kNGTdVrB71VOmQBAPxiXcIPrkHvpICFiOihR/cyEgW5GdaNnUix4LOK1tPlko6c0iRB7rs2UkRoj/3byU/xW/LoAMBPrp7nIA70RgpYiIgeumIuI1GQnerK/546l3QlDwws6/jBRuvVC/Kv2mPhFDoW/VTGM2VMEwDAL2SzqtdXjIJj/lLAQkT00NG9GYmC7Fw6wy7kxx4qpWsRsiPZYOp1g945ZywHkACA/8hp1Or9B9GpFLAQET1UOmvqajjKCTLz51pyID6WrkXIBqdX+W/pJkZXAcB/ju7jABvMXwpYiIgee+Nyk/rMBvh/Zo2utl0zSXZsX7oWITN88PjvneuM8QKA/1S8I0IB85cCFiKix5ZuZjcb2iedtqw+3zAO9bFdO1RYjQ10LUL7LJ1da7tm0Du7d0xZTey5AEBAjCusst2HEJ1IAQsR0WNlxh+gPZ4/ZhyqPe/dpAME2mdoF07s9NPpI8i/AoDg2LaGGAXMTwpYiIgeK4HDAO1xrIxxqPY8sIsgd7Aj4ybqtYLeur2EjmEACA7ZsFLvQ4hOpICFiOiD795wJjnYWb2Acaj2XD6HIHewc+poo+1aQW+9fpH5QQAIDolS6P8DUQroXgpYiIg+ePZYo/rMBiD7IYOjexPkDnbW/kHB10+7daiwGurJnwOAYFk6i3s7upcCFiKiD25aXqc+ryHhSFC5fDCq1wpWWF0/rbDq6/iQhv8ihU31WkHvnDyYwjEABM/pcrpr0b0UsBARfXDqUIJx4b/cutpku07wg3euE+QOH6ip4rh1v928ko0WAAie2ho29NC9FLAQEX2wxxcpq4XvcfiIPVvrbdcJfrBsB0Hu8IGLpyn4+u2lM+RfAUA4/D602nZPQtSRAhYiok8+vk8FCz6wcEqN7RrBD0omBsC/yBi2eo2gd8rYbk01Y7sAEA67t7Cph+6kgIWI6JOH99BRAh8Y/HOl7RrBD47qRR4PfGDSIPKv/FQOlAAACItnj1ps9yVEHSlgISL65IoiOkqgjYp3adv1gf9V8o7qaukIgbYDDwo+s18j6J3rF5N/BQDhMrQrG3voXApYiIg+OZqOEvgfZ49x4o6OEnQPcOMy+Vd+K/ckAIAwWftHre3ehJhLCliIiD7Z2lFSQ0cJkOej677t9erSQQLZuZ5sFD+VZ1NlBc8mAAiXy2fZrEDnUsBCRPTRG5foKAFO29F1yYwadekggcwcxd+Ln47sWakuOQBA4DQ2WK2ndqv3KMRsUsBCRPTR0k10lCSdlhbL6vklL2g6jujBh3XSaWm2rF5f8ffip6sXkM8IAGZQNI4NC3QmBSxERB+dN5GOkqTz+H6z7brA9pXRplrGbhPNg9v8vfjtycPkXwGAGRwqbbDdoxCzSQELEdFHB3ROqc9qSBiHd/Ny5sSbVxi7TTL7/iT/ym/fvm5Rlx0AIBTkfiSbV+p9CjGTFLAQEX2Wj4Vks3wOp+w4ce82xm6TzPxJNbZrAr1zaBfGdAHALEb3rrLdqxAzSQELEdFnz/zNuEaSkcBk9ZrAzC6axthtUkmnLavwe/Kv/HTZbPKvAMAsNq/kpGbUlwIWIqLPblxWpz6rISHU1aRpjXfosAI6RJLKs8cttusBvbV8X4O67AAAoXL7WpPtXoWYSQpYiIg+O/W3avVZDQnh2gVeypwqBb+aaoLck8jhPeTF+e3LZ4y0A4BZyGnNfb+l+xb1pICFiOizPb5ItR4ND8lj53oCqd14/SJB7klkyQzyr/yUQ0UAwFQkPkC9ZyG2JwUsRMQAfHSPClYSKRpXbbsWMLe7txDknkSG/EJenJ8Wky8HAIZy4lCj7Z6F2J4UsBARA/DwbnJHkkj/H2iJd+MfU/nQThrv3pB/5bcH/+I5BABmUl2Vtrp+ar9vIapSwEJEDMDlczj5KWm8esEHuVuHdiHIPWmcPMzuu98+eUgnMACYy+TBVbb7FqIqBSxExAAc2ZMP8qRx8ggf5G6VIPfqSoLck8TqBbW26wC9s+83KSvNnxQAGMyujeSGYm4pYCEiBiAnqyWPdYvrbNcB6nv1PEHuSWJUL3be/XTeRMZyAcBsHt9vtt27EFUpYCEiBiQnqyWLiQP5IM/H0k0EuScFyT6RIr96DaB37t3G3xMAmM9gDvPAHFLAQkQMSGmNhmTQ1GRZBZ/brwHUd+EUOkaSwoWTjNv67f1b5F8BgPmsmsc4OWaXAhYiYkDOncAHeVK4d5M2+Hwd8iu5cUlh4zLGbf2055cpq4X6FQBEADY0MJcUsBARA7Lw+5T6nIaYUrajwfb7o3MrU+TGJQHGbf111uhqdckBAIykvi5tde9ov48h/isFLETEAH3zqkV9VkMMWTS9xvbbo3OvnCM3Lu401Ketgs/svz16564NjK8DQHSQort6H0P8VwpYiIgBerq8UX1OQwwZ2pUQUi/kwzv+yOEW6u+O3nrrKoVgAIgOZTvpYsfMUsBCRAzQDUvr1Oc0xIzqSk5U88r5k8iNizvbS+ptvzt6pxwm0digrjoAgLm8ftFiu5ch/isFLETEAJ0yhCySuHPxNB0lXjn4Z4Lc4870EYyK+OnvQ3nmuOHsMYKk0Z3ThvM35wUjetDJju1LAQsRMUC7d0xZzZwGFWu2reFENS9NvSPIPa7IyXhyQp76m6N3yv0InMPJmOjWbh0qrNoanlv5IhML6toiihSwEBED9uFdKlhxZuYoOkq89NIZ8nviyr2bzbbfG7316nn+ftwwZQgnY6J7zx0n7zRfblyimx3blwIWImLAHiolkCSupNOW1ecbOkq8dMc6gtzjyp6t5F/5adcOFVZdLZ0gTpEuaemWVtcTUdeV82rVywocIn+Hfb7m7xDtUsBCRAzYZbN5sYkrzx4TPOq1cycQ5B5X5LdVf2/0zokDq9QlBw3u36IzEPNz0E+VrRtakB8Lp/CMQLsUsBARA3ZkD4Kp40r5fo5+9tqBP/L3Ekfk467vt+yu++mm5eRfuaFsB/dxzN8nD4iLyJe/y/hbRLsUsBARA7bLJxVWTTVbc3Fk1fxa2++N+VtBkHvsePqQLhe/vXCKHB43LJpG1wfm7+4tjL/nS2VFuvWdWV1bTLYUsBARQ/DaBYJ148jYvgT/+iEf4vFDsgDV3xm9Uz76qqso/LphyK+VtvVEdOq0YdXqpQUumDCA9yr8rxSwEBFDcNcGdubiRkN9ujU0Wf2tMX+3lzAKFTcWTafLxU/H9CH/yg3S8aGuJaIb5X2gtoYicr5sL+GwD/yvFLAQEUOwaDzB1HHj1hWOfPbLOePYyY4bg3+hy8VPS4o5LMQN50802tYS0a1nj9E9nC8PbjNujv+VAhYiYggWfp9Sn9EQcSTvQv2d0Rv7/8DfS5x484rTOv32TDkfzm7YvKLOtpaIbl0xl0JyvsiBH3KYi7q2mFwpYCEihuSbly3qcxoizILJjET56bs3/L3EheMH6XLxWw4+cMfUodW2tUR064DOqdYCDOTH8iIOyMEPUsBCRAzJU0fZIY8TA39ih9BPZbQH4sGqeXyM+OmI7pXqkoMGLc2W1fPLlG09EfPx8f1m9VIDh8goprqumFwpYCEihuT6JQRTx4X3bxmJ8ttta/h7iQsje1Ds9dOV8xhbcsODO2TtoPeWbubQnnypr0tbBZ/b1xaTKQUsRMSQnDyYU6LiAruD/jt7DEHucaAqlba6fGL/fdE7ZUQTnHNgV4NtLRHz9fehPLu8YPoIxnuxTQpYiIgh2b1jhdXUpD6iIYpsWk7wr9/2+44g9zhw7jjFXr+VkHxwzpIZ5Bii93btUGHVVBOElS/7/uSgHGyTAhYiYojKyAJEn6m/sTMYhHyYRx8ZnVZ/V/TOwT+Tf+WWoV0ZbUV/lC5tyI8XT4lqwDYpYCEihujBvxrUZzREjJYWgn+Dko+A6DO+f5Xtd0XvXDKzRl1y0KCyIm1bS0SvXFFELp0XDCugyIwUsBARQ3XpLF5qos7DuwT/BuXWVQS5RxkJ4pVxGvV3Re88sodNETdcOMloK/rngM4pK80UYd6sW0wHL1LAQkQMVY47jz6HSgn+DcqZowjDjTJXzzfZflP01udPGLN1w5ZVfBijvz6+T2REvvAMQZECFiJiiMppXDVVbMtFmWWza22/K/pj32/YxY4y29ZQJPDTwu/5+3DLtOHkGKK//rWxXr3swCFy8FGvr4hsSLoUsBARQ1Z2lCC6jOhBJkOQvn5Bh0lUmTaMIoGfLpxK/pUbyDHEIJTDXiB/5k3ktNCkSwELETFkd65nVy6q1NakW7vo1N8U/fNMOUHuUaS52bJ6fEGRwE/LdpJ/5YZH98gxRP+V/L+aalok8+XoXmIbki4FLETEkJ0zjl25qEIeQ/BuXkGQexS5e4Migd+SseMOcgwxKNmAyZ+Kd2wcJl0KWIiIIVv4XUp9PkNEkO459fdEf50+goJvFNm9hb8VP+3dKdU6CgfOkdOA1fVE9MPlczh52gvG9auyrS0mRwpYiIgG+Ipcn0gi3XPqb4n+Kh/qBFVHjyL+Vny1aDz5V24ZXkCOIQZj/848v7yAA0GSLQUsREQDPHWEtvKoIS+h/b4j0ycMXz6j4Bsl5G9FTpBUf0f0TulwA+dUVzKOhMH68C6jvvnCSHqypYCFiGiA6xeT6xM1Xj1vsf2OGIwUfKPFkwd8bPjtvZt8FLvh0mlyDDFYd22k2JwvsilS+D2bIkmVAhYiogFOGlSlPp/BcE4carT9jhiMG5dR8I0SB/8iJNtP5XTHpiZ11UEHRpEwaKcMIcfRC5bMrLGtLSZDCliIiAZY8HmF1URTSaQoKSb4NyynDeMDIEoUT+NDw09njuLvwS1yKIS6noh+2vXTCqu6iiCsfDl1lE3EpEoBCxHREB/cZgQkSkwcwCk4YdmLIPdIMfhnQrL9VE5DBefIPUTuJep6Ivrt6XJ2LPOltiZtdetgX1uMvxSwEBEN8cCuBvX5DIYi3XLSNaf+hhicz58Q5B4F5IRV9bdDb715hflBN5DNhmG5bHatejmCC6YOpYMyiVLAQkQ0RJnnh2jACTjhKxlkYD7Hysi/8lMppDey9+GKw3u4NjEc+3emi9gL5PRVdW0x/lLAQkQ0xOEFleqzGQxl33ZemsJ2/RKC3KPAiiKy4vx06m/kX7ll+RyuTQzPh3eIjciXpw/ZTEyiFLAQEQ2xyycVVnUlW3JRgFDq8JXRATAfKcyrvx1659bVFHLdMqIH1yaG564NZNd5wZBf+TtOmhSwEBEN8so5skyiwG9deGEK255fpqwWYrCMpjKVbi3Mq78deifPDHfUVHNtYrhOGVKlXpbggjUL6aRMmhSwEBENcsc6duRMp7IibfvdMByfPaKCZTJnj3HMuZ92/bTCqquha9cNV8422dYTMUjl75eu+/y5dIa/5aRJAQsR0SDnjGUsynQunOKj3BSPHyTI3WTWLa6z/WboneP708Hhlu0lXJsYvqeO8gzLl8aGtNXji5RtbTG+UsBCRDTIvt9yMo3pSOaM+rthOEqBBMxlXGGV7TdD79ywlOvfLTNHVdvWEzFol86uVS9NcMGccfw9J0kKWIiIhvnqOWNRJjN9BC9KpkiGiLnU16Wtrh3svxl65/kTdG+4QTaJ+nxDxwaGb+H3bFp6waHSBtvaYnylgIWIaJgnD/NRYiryotm7Ex8+pihjAy2cRG4kEi6u/l7onRJAXpXiy9cNTx8229YTMSwf3OEhli9vX7fY1hXjKwUsRETDLFlES7mp8OFjnk8e8vJvIoza+uvoXnQfuuXoPro10Bx3rufwHi+Qe6K6thhPKWAhIhrmxIF8mJhKOR8+xvl3WYP6M4EBTB3KqK2fytHx4I4Vc2tt64kYlpMH887nBZtXsGmSFClgISIaZsHnFVYTU4RGsmoeHz6mubaYD3nTkPtX946M2vrpqSM8JNwyik4NNMiun1ZY1ZWMA+fLrauMrSdFCliIiAZ67xZjUSYypg8fPqY5aRC716Zx+xqjtn77/i2Hfbihribdmh+mridimFKQzp+Wf26JcpK3urYYPylgISIaaNlOxqJMg1PVzLR7xwqrmXqvUZRuqrf9Tuidw7pVqksOmlw9T5cGmufSWXQSe0HxtBrb2mL8pICFiGigi2fUqM9lCJkbl/nwMdXH96lgmcScseRf+enyIj523bJjHcVVNM/C71KtpxxDfhw/2GhbW4yfFLAQEQ2UHXbzKN3Mh4+pyqliYAbyEdbna8Y4/JSDC9wzewzFVTTTB7fZiMmX6qp0a6aYurYYLylgISIaqGR0VKXYjjOJ+ZNoTTfV1QvoSDGFR/fIv/LbVy/Iv3KDFFf7fkNxFc1UugMhfyQXU11bjJcUsBARDfXy2Sb1uQwhMvDHSttvhGY4YQBB7qYg+X3q74PeOfAnunPd8vxxi209EU2RA0m8YdcGuuXjLgUsRERD3V7CbpwpvH3Nh4/JFnxeYTVR7zWChVPpVPTTRdPJR3RL+X6Kq2iuMvpWXUnnfb7QBRx/KWAhIhqqZHWAGZwpJxjUdB/eIT/EBOhU9NdDpeRfuWXVvFrbeiKa5MkjjeplCw6RUeFBP/EcirMUsBARDVWyOjiVxgw2LK2z/T5olof38GEfNi+f0anot88ekX/lljF9yMZBs10ykw5LL1hJsTrWUsBCRDRY+SCE8JkyhJOrTFe6KyBcGNHy137fsanhlrpaTidD8+Vv3BvOn6BrPs5SwEJENNgTh2gnD5vmZsvq8QUnV5nu+EICcMNm+Rx2vf10wWS6M9xy/WKTbT0RTfT+Lcbh86W+Lm1172hfW4yHFLAQEQ22pJiukrCRbCX1d0HzLPiswmqi3hsqw7qRO8YLxEYAAAyoSURBVOKn+7ZzsIdbdq7nZDKMhhzg4w0zR9E5H1cpYCEiGuzEAXSVhM3BvxiLiorsXIdH6l3a9nugt3JQgXvmjONjFqPhxIG893lB2Q7e3eIqBSxERIOlqyR8ls5iLCoqckJbeHBSp7/26pSyWohEdIVkCkm2kLqmiCba5ZMKq7KCIKx8efWCQ0XiKgUsRETDvXeTXfcwGdGdsaiouGIuI7dhIePO6u+B3jlnbLW65KDJy6d8yGK0JP/UG3h/i6cUsBARDVfaoCEcaqrTrbuh6m+CZjq2L6MXYSFrr/4e6J2lm8jFccuxA4wSYbRcPIMDG7xgw9I629pi9KWAhYhouIum8yITFlfOcXJVlOzaocJqbGD0ImjqatJW10/tvwd6553rdOK6ZfUCugMxWsrIq4y+Qn7cuMQ7XBylgIWIaLhDu1aqz2QICDkNSP090GwZuQ2eS2f4SPDT7h1TVlOTuuqgC92BGEV5luVP8z9L2Odr8u/iJgUsRETDlRG2qhRbcWEwewwnV0XNA7sYuQ2azSsZ0/DT6SPIv3JLfV26tTNTXVNE091eUqdezuCChVNqbGuL0ZYCFiJiBJQOBwgWTq6KpsvnEOQeNFOG0OHip9IJCu64cZnuQIymEweQ6egFf5eRgRc3KWAhIkbAP9eyExc0nFwVTUf35qU/SJoaLat7R/vvgN55/SIbGG75ayNj4BhNpfu+soLu+3yRNeQwnnhJAQsRMQLOGs0ISdAcP9ho+x3QfCVMXMaGIBhuXaHDxU+7daiwGuq5nt0ydwLjQxhd5T0E8mfCALqE4yQFLETECCghlJxIEyxrizm5KqpyYltw7NpAh4ufTh5MR2E+9P+BMXCMrpxC7Q0cyBMvKWAhIkbEF09b1Gcy+Mj4/uzYRdWyHQS5B4V0h6rrj94pAfngjlfPGQPHaNv3m5TVwqtf3jy43WxbW4yuFLAQESMireTB0dhgWQWf2X8DjIZLZxHkHgTyYdW7Ex0ufsoBHu45cYgxcIy+d2/QUZwvMsEw8MdK29piNKWAhYgYEdf+wUd5UMgImrr+GB1H9qxUf1LwgYd3+DvxU8lzq6lmdtwtjIFjHOQQH2+QE4rVtcVoSgELETEiykgbBMO+P8lLiLJy4lBdLR/+frN/O38nfjqukHt+PowvZAwco68EkEP+nD1GR2ZcpICFiBgR5TSqxgY+yoOg+HdOroq6t6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ND2nzmbfnSizdmC248kOdLkiRJkiS1V/Xey8p0XghF+b9C0Twr3nQAAACgzYWi9bU1ad/de273Hw+GB6L6cazO+sLWbNH6kJbvqR5mGj/uKer4kDe/uT6bf/NkOl+SJEmSJKm9qvcVRqqvt2ZL/yEU5dPiDQgAAADay7TQaPaEojW4MVuweTK+i7x+cXtV2ltfkf6jkJVz4gVMMdOrHlUdh89szRZdt9Yt/yVJkiRJ0sOs3g+6Llu4LuStC0O2/PnxZgQAAADtYVpImyeGvPzLKxuzN8fD32TqXhcB/CrMGDqxeuyHxouZCkKjeWpIh9+1Ip0bRrz4L0mSJEmS9lPrs4FwfbZwVShaH04umZr7LgAAAG0v5OXf/rr73A1j2eBeg99kq74IYE3aF0I6/I7qoc+M1zIVhLR87+WNc8eH8vj4SJIkSZIkPZzq/Ya1af+25OTkcfGeBAAAAJPb4SEv/2VDOripHV7839Nv7wTQ+nbImy+OF9WpqnPVXa33ZaurtU/Gj2mQJEmSJEmdUX0RwC35+ZeFopyXJMkx8R4FAAAAk9DqU4eefG224MZ2fCf5PS+Ab92YDX4zXlenCkXzqZc0/u7SdjxfkiRJkiSpvar3H0JRfic5Onl+vEcBAADA5NMT8uZgO7+TvH7sa7P+kHQnz4kX12m2nbj0D+/Il/3Thja6U4MkSZIkSWrv6jswjqYDW+N9CgAAACaZkDf7b8wXX9nOFwDsKRRlWS2piNfYSao1tsbSge3x2iVJkiRJkh7JRtL+naHn718Y71UAAAAwWfQkzwp5+dW1af/20X0Mdu1UfQFDKMr/CHnzr+NldpDp1Rp/0gkXa0iSJEmSpPZqJOuv917mJ0nSFW9YAAAAMAmsasy7cSTtu6tTXlCuB9Ed+bKRamm/VzXtvqtte0VIm6+P1yxJkiRJkjQR1ftHG7MFo6EoL4o3LQAAADjQsuSU+vPb1mX9u+KBrl2r72KwJVt0w5350IfCscs76gKAarh+YSian13fIRdrSJIkSZKkNiydvz0UrZ8lSXJCEjruzRcAAADtK+TNP99riOuA1mcDO65K54yGR7XSapmHxOtuV9X5OmNN1jfWKXdrkCRJkiRJ7Ve9L3FLtnRTclTy50nn3X0RAACgTU1PnhiK8t/qd8zHg1wntCEbDFvShReGvHxSvPR2FPLmn1bn6ytjXvyXJEmSJEkHuNFs/l0rG/NuDzOGZyZJclC8jwEAAMAEC3nrzFCUP+3Ud5PXt8lf3xi4pFrni+K1t6PqXC3bmi9a0annS5IkSZIktVf13ktoDD87eWnSFe9jAAAAMMFuTpd8bmO2YEOnvqBc39ngysacEIqyvh1d2wt568ur097bO/WODZIkSZIkqb2qLwDYni09N+TNx8X7GAAAAEywW7Pz16xJ++6Oh7dOavxK9Lz8+3jtbeiUULR+1akXa0iSJEmSpPar/pjCy7pn/3vIlr8g3sgAAABggoR0aHpyePKCrfmiG+PBrdOqLwC4OV/y/fgYtJuvdr3znO35srXe/S9JkiRJkiZL9RsVrm7MvSMU5RvjvQwAAAAmSJg1fPRFXW9YtDFbcFs8uHVa9QUAV6VzRuNj0G7+Y+ZZn7suW3idCwAkSZIkSdJkqr4IIOTl++O9DAAAACZIyFszfz7zA18dywZ2xENbpxYfg3bzy8YHVq5PB251AYAkSZIkSZpMjV8AUHTExy8CAAC0p2oo6/5F4+zvT5ULAOoXzatlHxLy5qHxsWgXV6Zz6nXcFa9NkiRJkiTpQFbffTEU5efjvQwAAAAmSDWUZSvTuaNT5QXl+kr0atknhWLpUfGxaBfe+S9JkiRJkiZj9QUAdxfDX433MgAAAJggoShn1cNZPLB1avVaq2U/OxRDM+Nj0SaOcQGAJEmSJEmajNX7LmPpwKXxZgYAAAATJBRlTzysdXL3XADwzGrd7XoBwPH1XQzidUmSJEmSJB3o6n2Xaxrz1sSbGQAAAEwQFwC0nZNdACBJkiRJkiZj9b7LinTuhngzAwAAgAniAoC2k/sIAEmSJEmSNBmr913WNPpXxJsZAAAATBAXALSdQ+I1SZIkSZIkTYbqfZfrsoU/iTczAAAAmCChKGfVw1k8sHVq91wA8KxQDLXrBQBJvCZJkiRJkqTJUL3vsqsY/kq8lwEAAMAECUWZ/6px7tZqSLs7Hto6sdHdFwA8PjQuODo+Fu1iKl2wIUmSJEmS2qd6z2JHccE34r0MAAAAJkjoKdPLG+deNpoN7IyHtk5tfN3dQwfHx6JdrGjMWTOWDt4Wr0uSJEmSJOlAVr/xIhTlR+K9DAAAACZIyJvHfLnr7X+/IRu8PR7aOq16CP1149yd8TFoN1/u+psP3ZAvvnZ0H2uUJEmSJEk6UN1zAcDfxHsZAAAATJCQN4/8mxkvOHNzvvCWeGjrtOrb0K1q9K6Nj0G7WTLjlWftyIfWuABAkiRJkiRNluoX/69qzLk15K0/i/cyAAAAmCChsWx69eU5W/NFt9SDWjy8dVL1BQDb8sX/ER+DtnNo8tRQtK7o9PMlSZIkSZLap3rfZTQd+HEoyhfHWxkAAABMsFuy83+0Luu/uZPfVV4PoiEvz43X3o6qdfyPtWnfDS4CkCRJkiRJk6GxbDDc3Fj0thc86d0nxPsYAAAATLCQN4duzy+4qlNfUK7XtTKdty3k5Rvjtbejah1nhbz1o049X5IkSZIkqa26+4rG7LtCY/jU5NXJkfE+BgAAABNtRvcrQlF+u1NfUK7f/b8lW/TNao3PjZfelrrqjwEoL1qb9e+1VkmSJEmSpIlsQzq4fW3a/8swa/nB8RYGAAAAB0Z3KMp/iQe4Tqm+Dd3/7T7rbzee9smT4oW3qYNC3px3RWP2+N0N4vVKkiRJkiRNRPW+xHXZeTcOdb1qUTipdAEAAADAZBHyD710ZB+DXLu3IR28fVO64NJw6KLD4zW3s1BceHrIyyXxeiVJkiRJkiai0aoN2eDN9V0lkyTx4j8AAMAkk3XiLeVvyBZvXtj18rlJSKbFC25zh4eZzWeuTOeND9zxuiVJkiRJkh7J6nf/35ov/eWObHh+vGkBAADAJPDLxgd+OJrNv6FTXlC+Ju0NIS8vjdfZQY6sBu2fr/cxAJIkSZIkaYKr7yQZ8nJpvFkBAADAJBHSZU8ORfnDTvhc+XoN1Vp+ErLyvfE6O0nImx+7Op3rLgCSJEmSJGnCqvch1mT9IeTN/xzvVQAAADB5HBKKcuiGbPGaTrgIoBpCP5ycmDw2XmQnCVn5lqrvb8gG91q/JEmSJEnSI9GqtDesSfu2JUnSiPcqAAAAmGRC0XptO3+2/Jq0d9dYOnB9tZSueG2dKOTlaT/rfv93fRSAJEmSJEl6pKv3H0JR/p8kSZ4U71EAAAAwCYWseext2dJVq9O+vYa8yV5954KdxdDV1RqG43V1qpCWM0Oj9eKr03l3d8KdGyRJkiRJ0uRs/CMX89aPQ1aelSTJ4fEeBQAAAJNUffv8W/Ol69rpXeX1EFo93ptCUX4m6UqeFq+pg02r/2dnPvSLNWnf+HGIj40kSZIkSdLDqd4jWpv11x+52Jec9NTT4s0JAAAAJreDQtZ8aSjKf2qHiwDqF71H0vm3VY/3NclLp8at/2Oha+jkkDbPXJHODSPVQB4fI0mSJEmSpIdSvTd0fbZwVcjLD8f7EQAAALSL05MipMOvDEX5/Xjwm0zVL/5vyhZeXz3Ob4RTP9+IlzGFTK96VMian92SnXd9fVV+fKwkSZIkSZIeTPW+y+Zs4WgoWh8M2fIXxJsRAAAAtJO3JYcnByevujk//7rJ+q7ya7PBO6oh9Osha701fvhT1PEhL7+5MRvcFh8rSZIkSZKkB9vN6fkXhaL19HgDAgAAgDYVGsN/cVnj3PFbvo3uYxCc6OrHULchGwy/7j7ng+GUjz4xfsxTXH0ngA/vPlaT/yMcJEmSJEnS5GnPvstYNhhWpb3r4k0HAAAA2lyYOXx06Bp6XMjLL91ZDK040BcBjGUDt4S8+d2QDr+6+toVepoHx495ijsoHDl0ZHVcPhKK8uIt2aKt8TGUJEmSJEmKW58N7BzLBm8JeevnIWueHdLhp8WbDgAAAHSQO2cNvbW+E8DuuwFM7LvL659Zf/33me/6Vmh85NHxY2MfupPn7UyHLqo/wmHP8ZMkSZIkSYqr9w1Wpb23/6LxgR8lSXJMvMUAAABA5zr22saC1sZ0wTWP9McC1BcZ1D+jvu1cyFtfTI5Ifj9+MDygaSFrzd+ULvjFnos34uMsSZIkSZKmZrtf+O8Ll3SffVvSnTw33lQAAACg8x0WitYTQtZ8Vcibc9dl/dvqF+p3t/cg+VDa88L/unT+1puyJT8OefmxkLdOT7qSmfGD4YGFrDy5OoYvrXrvxnTBD9Zm/XfvOWfxsZckSZIkSZ1bvXezZ0+gvmNgyMtvVy0IeeulyZOT7nhPAQAAgKnjkOSI5PiQNz8YivIrO4qhS1ekc3ftGSL3vNv8/j4y4P7+m5XpvLA67b25Gj6/GYrmh6rv/85q/HxO/MN50A6qSkO+/IzqfP1T1cWr074bV6W9e52HfZ0vSZIkSZLUPu1r36XuqnRuGEn7t9yVD18W8tbXQla+JUmTU+NNBAAAAOgORetpIW++POTle6qvH78pX/LVtWnf5avTvlWr0r4b7/2i8upG78bqz369qtG7IhTlp6v/fmnVa6vh81nV33989f0Ojn8A+9UxYVbzcdWxr45386zqmP+X27KlXxpJ+y6rzte6axrzbnURgCRJkiRJ7Vc114eVjXnb11Yz/lg6/+e3Zkv/Z8iay6reG4rl/6nqscnxSSPZ/WYBAAAA+P+annQnJ4ae5gtC3vrT0FO+MxTle0JPa14oWsPVPw9VX4eqPzun+rN3hKJ5ZvXfviQcVz6l+rtHxd+MCVCfr1mt36/Oy2tCXp+T1t9V52n+b8+XJEmSJElqo5ZWDe7edyn/uupV15+0/K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diff --git a/content/6-Protocol_On-Chain/index.md b/content/6-Protocol_On-Chain/index.md
new file mode 100644
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--- /dev/null
+++ b/content/6-Protocol_On-Chain/index.md
@@ -0,0 +1,317 @@
+---
+title: Introduction to Polkadot SDK
+description: In Introduction to Polkadot SDK
+duration: 120 mins
+---
+
+## Meta
+
+Before Getting started
+
+- 👋🏻 Questions
+- ⏰ Slides
+- `@kianenigma` / `kian@parity.io`
+
+Note:
+
+meta questions for ice breaker:
+
+- how many ppl know substrate/frame already?
+- how many ppl feel like they are comfortable with rust
+- with rust generics, traits and associated types
+- how many ppl know what polkadot-sdk is?
+- how many ppl know jam already? do you have the question of why are we still learning all of this?
+
+---
+
+# Introduction to Polkadot SDK
+
+- Polkadot + Substrate + FRAME + XCM
+
+Note:
+
+This lecture is about learning two things:
+
+1. Polkadot
+2. Polkadot SDK
+   1. Substrate
+   2. FRAME
+   3. XCM
+
+There will be amazing modules going into further details of each. This will be very high level.
+
+meta questions for ice breaker:
+
+- how many ppl know substrate/frame already?
+- how many ppl feel like they are comfortable with rust
+- with rust generics, traits and associated types
+- how many ppl know what polkadot-sdk is?
+- how many ppl know jam already? do you have the question of why are we still leaning all of this?
+
+---
+
+## Learning Outcomes
+
+1. Understand what Polkadot is as a developer platform.
+2. Understand the pieces of the Software Development Kit (SDK) of this platform
+
+---
+
+## Polkadot
+
+- As a platform for developers.
+- Polkadot stems from Ethereum. A single threaded smart contract blockchain.
+
+---v
+
+### Polkadot
+
+<img width="800px" rounded src="./img/single-threaded.svg" />
+
+---v
+
+### Polkadot
+
+<img width="800px" rounded src="./img/single-threaded-eth.svg" />
+
+---v
+
+### Polkadot
+
+- O.G ETH2 Vision from 2015
+- Let's make this _sharded_, such that it can achieve execution sharding.
+
+Note:
+
+The holy grain of what ETH 2.0 was meant to be.
+
+---v
+
+### Polkadot
+
+<img width="800px" rounded src="./img/multi-threaded.svg" />
+
+Note:
+
+Have we compromised security in any way in this model?
+
+---v
+
+### Polkadot
+
+<img width="800px" rounded src="./img/multi-threaded-dot.svg" />
+
+Note: Polkadot achieves perfect shared security and sharded execution. The primitives that can
+progress an input in parallel is called a "Core", much like a normal CPU.
+
+---v
+
+### Polkadot
+
+<img width="800px" rounded src="./img/dot-heterogenous.svg" />
+
+Note:
+
+Let's make it heterogenous. The state transition function of these shards need NOT be the same. WASM
+is used.
+
+---v
+
+### Polkadot
+
+<img width="800px" rounded src="./img/dot-parachain.svg" />
+
+Note:
+
+The beautify of a heterogenous system is that we are no longer bound to running a single chain, and
+therefore smart contracts. We can run anything we want. We can run a whole blockchain as a shard.
+
+---v
+
+### Polkadot
+
+<img width="800px" rounded src="./img/dot-parachain-auction.svg" />
+
+Note:
+
+Finally, let's make the deployment of those shards flexible and permissionless. We arrive at
+Polkadot what it is today.
+
+---v
+
+### Polkadot
+
+> Polkadot 1.0 is a platform to launch blockchains that can progress in parallel, whilst absolutely
+> sharing the security of Polkadot Relay Chain.
+
+Terminology:
+
+- Polkadot Relay Chain
+- Parachain
+- Execution Core
+
+Note:
+
+Polkadot initially allowed parachains to compete for deployment on Polkadot via auctioned slots.
+Winners get access to a Core for a long long time. Now, it is moving toward a more agile system where
+parachains can purchase cores on-demand.
+
+In some sense, Polkadot is moving towards a general purpose computer, exposing its Core as the
+primary primitive. Whether they are used to build a Parachain or not, it does not care. The future
+of Polkadot is the World Computer vision.
+
+TODO: maybe turn into slides, maybe leave as notes for now.
+
+---
+
+## Polkadot SDK
+
+> .. So how do we build one of these parachains?
+
+---v
+
+### Polkadot SDK
+
+- Building a blockchain is damn painful hard.
+- This is why Polkadot has pivoted for years to build a modular and extensible blockchain framework
+  called _Substrate_ and _FRAME_.
+
+---v
+
+### Polkadot SDK
+
+⛓️‍💥 Substrate 🤝 FRAME 🤝 Cumulus ⛓️‍💥
+
+<img width="800px" rounded src="./img/substrate-frame-cumulus.svg" >
+
+---v
+
+### Polkadot SDK
+
+- Substrate: Un-opinionated primitives for building blockchains based on a WASM meta-protocol.
+- FRAME: An opinionated way to build that WASM protocol/runtime/STF.
+- Cumulus: Parachain turbocharger
+
+Note:
+
+**FRAME** is a subset of blockchain within Substrate that allow you to focus only on writing the
+state transition function aka. Runtime of your blockchain and not deal with the rest of the
+software. WASM.
+
+---v
+
+### Polkadot SDK
+
+<img style="width: 800px;" src="../../assets/img/5-Substrate/dev-4-1-polkadot.svg" />
+
+All proudly™️ built with Substrate.
+
+1. the mighty Polkadot Relay Chain
+2. all the Polkadot Parachains to date.
+3. (less known) can be used to build any blockchain unrelated to Polkadot.
+
+---v
+
+### Polkadot SDK
+
+Cumulus augments Substrate to make it Polkadot-compatible.
+
+---
+
+## Interoperability
+
+Underrated truth about interoperability of blockchains:
+
+_🚀 Shared security puts communication on steroids 🚀_
+
+Note:
+
+Shared Security is GREAT, but it would be even more FAN-TAS-TIQUE is if these parachains could
+communicate with each other.
+
+https://x.com/TheDotsMagazine/status/1790755070490857778
+
+Chains can trust the execution of each other to a much higher extent. But note that it is still not
+100% guarantee. The Relay Chain cannot guarantee that a parachain won't upgrade itself to go rogue,
+but it can 100% ensure that the parachain will do exactly as stated in its WASM blob.
+
+---v
+
+### Interoperability
+
+<img width="800px" rounded src="./img/dot-parachain-message.svg" />
+
+---v
+
+### Interoperability
+
+Polkadot-SDK's services to developers:
+
+- Transport protocols for parachains/cores to send payloads to one
+  another.
+  - XCMP, HRMP, VMP, DMP 😶‍🌫️
+  - As a developer you won't deal with these! 😮‍💨
+- Language to compose messages and programs and send them over.
+  - XCM
+    - Shared ideas between sovereign consensus systems.
+    - Asynchronous.
+
+Note:
+
+On "XCMP, HRMP, VMP, DMP": It is similar to building a website. You know HTTP and TCP and such
+exist, and you use them via an interface, but you don't need to know them by heart.
+
+Consensus System: Moreover, the sender and recipient of these messages can be contracts, accounts, or any
+other abstract entities within chains, not just the chain itself.
+
+Async and Sync: Disjoint consensus systems are in principle[^1] asynchronous by nature. This is an
+important concept to keep in mind.
+
+[^1]: Technically, if two parachains are co-scheduled in the same core in the same block, they
+could have synchronous communication. But they cannot count on this. So at the programming
+model, one must assume everything is always asynchronous.
+
+---
+
+## Lecture Recap
+
+About Polkadot
+
+- Heterogenous Sharded Execution, Shared Security.
+- Parachain
+- Core
+- Exposing Cores: Auctions -> On-Demand -> World Computer
+
+About Polkadot SDK
+
+- Substrate
+- FRAME
+- XCM
+
+---
+
+## Schedule
+
+(tentative)
+
+- 🤓 _Substrate_: Tuesday -> Thursday
+  - More theory, 2 ungraded activities
+- 🧑‍💻 _FRAME_: Thursday -> Thursday
+  - Main graded assignment
+  - Mix lecture and live-coding
+- 🚀 _XCM_: Friday + Saturday
+  - Hands-on
+
+---
+
+## Additional Resources! 😋
+
+> Check speaker notes (click "s" 😉)
+
+<img width="300px" rounded src="../../assets/img/5-Substrate/thats_all_folks.png" />
+
+Note:
+
+https://blog.kianenigma.nl/posts/tech/polkadot-s-build-horizon/
+https://paritytech.github.io/polkadot-sdk/master/polkadot_sdk_docs/index.html
+https://wiki.polkadot.network/
diff --git a/content/7-dApps_Off-Chain/1-1-polkadot-js-origins-slides.md b/content/7-dApps_Off-Chain/1-1-polkadot-js-origins-slides.md
new file mode 100644
index 00000000..2662b2d6
--- /dev/null
+++ b/content/7-dApps_Off-Chain/1-1-polkadot-js-origins-slides.md
@@ -0,0 +1,195 @@
+---
+title: The Evolution and Impact of Polkadot-JS
+description: Exploring the history, development, and ecosystem influence of Polkadot-JS
+Duration: 30 minutes
+---
+
+# The Origins and Evolution of Polkadot-JS
+
+---
+
+## The Genesis Story
+
+<pba-flex center>
+
+<img rounded src="./img/first-commit.png" />
+
+- A personal side project before Polkadot existed
+- Started when only the specification was available
+- No actual blockchain to interact with initially
+- Built on anticipation and vision
+
+Notes:
+
+Polkadot-JS began as a personal project by its core maintainer at a time when Polkadot itself was still just a specification on paper.
+
+The developer started building the JavaScript implementation based purely on the specifications and their understanding of what would be needed for the future network. This forward-thinking approach allowed the tooling to evolve alongside the blockchain itself, rather than playing catch-up later.
+
+This early start gave Polkadot-JS a unique advantage - it was able to grow and adapt organically with the protocol itself, incorporating feedback and adjusting to changes in real-time as the Polkadot vision materialized into working code.
+
+</pba-flex>
+
+---
+
+## The First Conversation with Gavin Wood
+
+<pba-flex center>
+
+"Cool, not sure how this fits in, but it helps the Polkadot ecosystem, so go on."
+
+</pba-flex>
+
+---
+
+## The Two Pillars of Polkadot-JS
+
+<pba-flex center>
+
+1. **Polkadot-JS API** – Core JavaScript/TypeScript interface
+2. **Polkadot-JS UI** – Web-based interaction platform
+
+</pba-flex>
+
+Notes:
+
+The Polkadot-JS ecosystem expanded to encompass three main components, each serving different but complementary purposes:
+
+1. **Polkadot-JS API**: This is the core JavaScript/TypeScript interface for interacting with Substrate-based chains. It provides developers with the tools to query chain state, submit transactions, subscribe to events, and more. The API forms the foundation upon which other tools and applications are built.
+
+2. **Polkadot-JS UI** (also known as Polkadot-JS Apps): This web-based interface allows users to interact with Substrate-based chains through a graphical user interface. Originally intended as a developer tool, it evolved into a widely used application for managing accounts, transferring tokens, participating in governance, and performing various other on-chain actions.
+
+---
+
+## From Developer Tool to Community Platform
+
+- Initially created as a reference implementation
+- Unexpectedly became the primary user interface during PoC-1
+- Early validators adopted it for operational needs
+- Community-driven feature development began organically
+
+Notes:
+
+The Polkadot-JS UI was originally conceived as a simple developer tool - a reference implementation to demonstrate how the API could be used in a web application. However, during Polkadot's Proof of Concept 1 (PoC-1), it unexpectedly became the primary interface through which users interacted with the network.
+
+Early validators, who needed tools to manage their operations, turned to the Polkadot-JS UI as their dashboard of choice. This organic adoption drove the expansion of the UI beyond its initial scope, with new features being added to support validator operations and network participation.
+
+As the user base grew, community members began contributing features that addressed their specific workflows and needs. This community-driven development model helped the UI evolve from a simple reference implementation into a comprehensive platform for all aspects of network interaction.
+
+This evolution exemplifies how open-source projects in the blockchain space often grow beyond their initial purposes, shaped by the needs and contributions of their communities rather than following a predetermined roadmap.
+
+---
+
+## The Core Maintainer's Philosophy
+
+<pba-flex center>
+
+- API reliability takes highest priority
+- Quick issue resolution to respect developer time
+- Responsive to community needs and questions
+- Balancing new features with stability
+
+</pba-flex>
+
+Notes:
+
+The core maintainer of Polkadot-JS has operated with a clear set of priorities that have shaped the project's development:
+
+First and foremost is the reliability of the API. Since developers rely on it daily to build their applications, ensuring its stability and correctness has always been the highest priority. Breaking changes are carefully managed and documented to minimize disruption to dependent projects.
+
+Issue resolution is treated with urgency, particularly for bugs that block developer progress. The maintainer recognizes that each open issue potentially wastes the time of multiple developers across the ecosystem, creating a multiplier effect that justifies quick responses.
+
+The maintainer has become known for being highly responsive to community needs and questions, often providing guidance and explanations that go beyond simple code fixes. This educational component has been crucial in building a knowledgeable developer community around Polkadot.
+
+There's a constant balance between adding new features to support evolving use cases and maintaining the stability that existing applications depend on. This balancing act has informed many of the architectural decisions in the project's evolution.
+
+---
+
+## Innovative Technical Features
+
+### Dynamic UI from Metadata
+
+<pba-flex center>
+
+- UI automatically adapts to chain's runtime modules
+- No pre-built support needed for new chains
+- Enables seamless interaction with any Substrate chain
+- Reflects runtime upgrades without UI changes
+
+</pba-flex>
+
+Notes:
+
+One of the most innovative features of Polkadot-JS is how the UI dynamically adapts based on the metadata provided by the connected chain. This approach revolutionized how developers and users interact with Substrate-based chains.
+
+When connected to any Substrate chain, the UI automatically detects the available modules, calls, storage items, and other runtime components through the chain's metadata. It then generates the appropriate forms and interfaces without requiring pre-built support for that specific chain.
+
+This means that when a new chain like Edgeware is launched, users can immediately connect to it through Polkadot-JS UI and access all its functionality without waiting for updates to the UI. Similarly, when existing chains add new pallets or functionality through runtime upgrades, the UI automatically reflects these changes.
+
+This dynamic capability significantly reduced the maintenance burden for both the Polkadot-JS team and the broader ecosystem. Instead of requiring UI updates for each new chain or runtime upgrade, the UI remains functional through its ability to interpret metadata on the fly.
+
+---
+
+## Community Growth and Contributions
+
+- Organic adoption by validators and developers
+- Web3 Foundation bounties incentivized contributions
+- Community members added specialized features
+- Expansion from core functionality to ecosystem tools
+
+Notes:
+
+The growth of the Polkadot-JS ecosystem has been largely organic, driven by the needs of validators, developers, and other community members who adopted the tools for their daily operations.
+
+To encourage broader participation, the Web3 Foundation began sponsoring bounties for Polkadot-JS issues, providing financial incentives for external contributors to address bugs, add features, and improve documentation. This program helped distribute the maintenance load and brought fresh perspectives to the project.
+
+Community members have contributed specialized features that address specific use cases, such as enhanced validator tools, integration with hardware wallets, and improved UX for governance participation. These contributions have enriched the ecosystem beyond what the core team could have built alone.
+
+The project has expanded from its core functionality (API, UI, Client) to encompass a broader ecosystem of tools and libraries that support various aspects of the Polkadot and Kusama networks. This expansion reflects the growing maturity and diversity of use cases within the ecosystem.
+
+---
+
+## Integration with the Broader Ecosystem
+
+- Browser extensions for wallet functionality
+- Mobile application support
+- Block explorer data providers
+- Cross-chain communication enablers
+
+Notes:
+
+As Polkadot-JS matured, it began to integrate with and support a broader ecosystem of tools and applications:
+
+Browser extensions like the Polkadot{.js} Extension provide wallet functionality, allowing users to manage their accounts and sign transactions securely across multiple websites without exposing their private keys. This extension has become a crucial piece of infrastructure for dApp developers in the ecosystem.
+
+Mobile application support enables integration with tools like Parity Signer, allowing for secure offline signing of transactions using mobile devices. This integration enhances security by keeping private keys on air-gapped devices.
+
+Polkadot-JS serves as a data provider for block explorers like Polkascan and Subscan, supplying them with decoded transaction data, event information, and account details that make blockchain data accessible to non-technical users.
+
+Perhaps most importantly, Polkadot-JS supports the cross-chain communication capabilities that are central to Polkadot's vision. It provides interfaces for interacting with parachains, handling cross-chain message passing, and participating in the ecosystem's governance across multiple chains.
+
+---
+
+## Vision Alignment with Polkadot
+
+<pba-flex center>
+
+- Enabling cross-chain communication
+- Solving real-world problems, not just technical optimization
+- Building for practical use cases
+- Growing the ecosystem organically
+
+</pba-flex>
+
+Notes:
+
+The development of Polkadot-JS has been guided by a vision that aligns closely with the broader goals of the Polkadot network itself:
+
+A core focus has been enabling cross-chain communication, reflecting Polkadot's foundational goal of allowing different blockchains like Bitcoin, Ethereum, and others to interact seamlessly. Polkadot-JS provides the interfaces through which developers and users can leverage these cross-chain capabilities.
+
+The maintainer has emphasized solving real-world problems rather than just optimizing blockchain parameters. This practical approach has led to tools that address actual user needs rather than theoretical improvements.
+
+The project has prioritized building for practical use cases, with features driven by the requirements of validators, developers, and other ecosystem participants rather than abstract technical goals.
+
+Finally, the organic growth of the ecosystem has been embraced, with community contributions welcomed and incorporated to create a more diverse and robust toolset than could have been achieved through centralized planning alone.
+
+---
diff --git a/content/7-dApps_Off-Chain/1-2-polkadot-js-what-is-it-slides.md b/content/7-dApps_Off-Chain/1-2-polkadot-js-what-is-it-slides.md
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+---
+title: What is Polkadot-JS
+description: A deep dive into the structure and components of Polkadot-JS
+duration: 1 hour
+---
+
+# What is Polkadot-JS
+
+---
+
+### Polkadot-JS Dependency Tree
+
+<img rounded style="width: 900px" src="./img/polkadot-js-dep-tree.png" />
+
+Notes:
+
+This image shows the complex dependency structure of the Polkadot-JS ecosystem. The various packages are highly interconnected, with core utilities at the base and more specialized tools building on them.
+
+This dependency structure illustrates both a strength and a weakness of Polkadot-JS. On one hand, it promotes code reuse and consistency across the ecosystem. On the other hand, it creates tight coupling that can make it difficult to use individual components without pulling in much of the entire system.
+
+Understanding this dependency structure is important for developers working with Polkadot-JS, as it helps explain some of the challenges in bundle size optimization and maintenance that we'll discuss in the limitations section.
+
+---
+
+### @polkadot/dev - Development Infrastructure
+
+<pba-flex center>
+
+- Build configurations and scripts for TypeScript projects
+- Shared ESLint and TSLint configurations
+- Testing frameworks and utilities
+- Common development dependencies
+- Publishing utilities
+
+</pba-flex>
+
+Notes:
+
+The dev repository serves as the foundation that enables consistent development practices across the Polkadot-JS ecosystem. It includes tools for interacting with Polkadot, Kusama, and other Substrate-based blockchains.
+
+Developers working on Polkadot-JS projects can rely on these shared tools rather than having to configure their own development environments from scratch. The repository helps maintain consistency in coding standards, build processes, and testing methodologies across the various components that make up the Polkadot-JS ecosystem.
+
+This standardization of development tools has been critical for maintaining quality and consistency across the numerous packages that form the complete Polkadot-JS ecosystem, especially as the number of contributors has grown over time.
+
+---
+
+### @polkadot/wasm - WebAssembly Cryptography
+
+<pba-flex center>
+
+- WASM implementations of cryptographic functions
+- Performance optimization for critical operations
+- Cross-platform compatibility
+- Bridge between Rust and JavaScript
+- Key generation and verification
+
+</pba-flex>
+
+Notes:
+
+The WASM repository provides WebAssembly versions of critical cryptographic functions used in Polkadot, including hashing algorithms (like Blake2b, SHA-256), signature schemes (like ed25519, sr25519), and other cryptographic primitives.
+
+The WASM implementations offer better performance for cryptographic operations compared to pure JavaScript implementations, which is crucial for blockchain interactions. However, there are tradeoffs to consider:
+
+Advantages of WASM over Pure JavaScript:
+
+- Better Performance – WASM executes at near-native speeds, often 2x–10x faster than JavaScript
+- Optimized for Cryptography – Uses efficient integer operations and avoids JS floating-point limitations
+- No Garbage Collection Overhead – WASM has manual memory management, preventing GC-related slowdowns
+- Access to Optimized Libraries – Many cryptographic libraries are available in WASM
+- Better Security – Less exposure to JavaScript runtime vulnerabilities or side-channel attacks
+
+Potential Drawbacks of WASM:
+
+- Higher Startup Time – WASM modules take longer to instantiate and compile than JavaScript functions
+- Complexity – Requires writing in Rust, C, or C++, then compiling to WASM, adding extra build steps
+- Larger File Sizes – WASM binaries are often larger than equivalent JS code, which can impact load times
+- Interoperability Challenges – Calling WASM from JS incurs a performance cost due to boundary overhead
+- Browser & Environment Limitations – Older browsers and some restricted environments may lack full WASM support
+
+---
+
+### @polkadot/common - Core Utilities
+
+<pba-flex center>
+
+- Cryptographic utilities (key generation, hashing, SS58 encoding)
+- Key management (keypairs, accounts, signing)
+- Network information for Substrate chains
+- Cross-platform compatibility utilities
+- Hardware wallet interfaces
+
+</pba-flex>
+
+Notes:
+
+The `polkadot-js/common` repository is a monorepo that provides essential utilities for working with Substrate-based blockchains. It forms the foundation for most other Polkadot-JS tools and applications.
+
+Key components include:
+
+- Cryptographic utilities for key generation, hashing, and SS58 address encoding
+- Keyring utilities for managing keypairs, accounts, and transaction signing
+- A registry of network information for known Substrate chains
+- Cross-platform compatibility modules like `@polkadot/x-bigint`, `@polkadot/x-randomvalues`, `@polkadot/x-textencoder`, and `@polkadot/x-ws`
+- Interfaces for hardware wallets like Ledger
+
+These utilities are designed to work in both Node.js and browser environments, making them versatile for different types of applications. The common repository is often the most reusable part of the Polkadot-JS ecosystem, with many of its utilities being useful even in applications that don't use the full API.
+
+---
+
+### @polkadot/api - Blockchain Interaction
+
+<pba-flex center>
+
+- Complete blockchain interaction suite
+- Type-safe TypeScript interfaces
+- Reactive programming model with RxJS
+- Automatic codec handling (SCALE)
+- Dynamic metadata adaptation
+- Transaction management
+
+</pba-flex>
+
+Notes:
+
+The API package is the central component for interacting with Substrate-based blockchains. It offers:
+
+- Complete Blockchain Interaction: A full suite of tools to connect to nodes, query blockchain state, submit transactions, and listen to events.
+- Type-Safe Interfaces: Leverages TypeScript to provide strongly-typed interfaces that match the on-chain runtime definitions, reducing errors and improving developer experience.
+- Reactive Programming Model: Built on RxJS, allowing for reactive subscription-based programming patterns to handle blockchain events and state changes.
+- Automatic Codec Handling: Automatically encodes and decodes data between JavaScript objects and the SCALE codec format used by Substrate.
+- Metadata Adaptation: Dynamically adapts to each chain's metadata, allowing it to work with any Substrate-based chain regardless of custom pallets or types.
+- Transaction Management: Provides comprehensive tools for creating, signing, and submitting extrinsics (transactions), including fee estimation and nonce management.
+
+Limitations include:
+
+- Limited light client support
+- Reliance on the older JSON-RPC interface
+- Challenges with static type support for dynamic chain metadata
+
+---
+
+### API Example: Basic Usage
+
+```typescript
+import { ApiPromise, WsProvider } from '@polkadot/api';
+
+async function main() {
+    // Create the API instance
+    const api = await ApiPromise.create({
+      provider: new WsProvider('wss://rpc.polkadot.io')
+    });
+
+    // Get chain information
+    const [chain, nodeName, nodeVersion] = await Promise.all([
+      api.rpc.system.chain(),
+      api.rpc.system.name(),
+      api.rpc.system.version()
+    ]);
+
+    console.log(`Connected to ${chain} using ${nodeName} v${nodeVersion}`);
+
+    // Query account balance
+    const ADDR = '13UVJyLnbVp9RBZYFwFGyDvVd1y27Tt8tkntv6Q7JVPhFsTB';
+    const { data: balance } = await api.query.system.account(ADDR);
+
+    console.log(`Treasury Balance: ${balance.free.toString()}`);
+  }
+
+  main().catch(console.error);</code></pre>
+```
+
+Notes:
+
+This example demonstrates the basic usage of the Polkadot-JS API to connect to a node, retrieve chain information, and query an account balance. The code is straightforward and follows a promise-based pattern that will be familiar to JavaScript developers.
+
+---
+
+### API Example: Historical Queries
+
+```typescript
+import { ApiPromise, WsProvider } from "@polkadot/api";
+
+async function main() {
+  const api = await ApiPromise.create({
+    provider: new WsProvider("wss://rpc.polkadot.io"),
+  });
+
+  // Get a historical block hash
+  const blockHash = await api.rpc.chain.getBlockHash(1000000);
+
+  // Create an API instance at that block
+  const apiAt = await api.at(blockHash);
+
+  // Query historical state
+  const ADDR = "13UVJyLnbVp9RBZYFwFGyDvVd1y27Tt8tkntv6Q7JVPhFsTB";
+  const currentBalance = await api.query.system.account(ADDR);
+  const historicalBalance = await apiAt.query.system.account(ADDR);
+
+  console.log(`Current Balance: ${currentBalance.data.free.toString()}`);
+  console.log(
+    `Balance at Block 1,000,000: ${historicalBalance.data.free.toString()}`,
+  );
+}
+
+main().catch(console.error);
+```
+
+Notes:
+
+This example demonstrates one of Polkadot-JS API's most powerful features: the ability to query historical state at any block height. This capability is essential for applications like block explorers, analytics tools, and any service that needs to understand how the chain state has changed over time.
+
+The `api.at()` method creates a specialized API instance that is pinned to a specific block. All state queries made through this instance will return data as it existed at that block height, allowing for accurate historical analysis.
+
+This historical state capability relies on the node having the state data available, which depends on the node's pruning settings. Archive nodes store all historical state and allow querying at any block height, while pruned nodes may only have recent state available.
+
+The API handles all the complexity of tracking runtime upgrades and metadata changes, ensuring that historical queries work correctly even if the chain's structure has changed between the queried block and the current state.
+
+---
+
+### @polkadot/phishing - Security Protection
+
+<pba-flex center>
+
+- Curated database of known phishing sites
+- Address blacklists for suspicious accounts
+- Community-maintained security resource
+- Integration with wallet extensions
+- Regular updates to protect users
+
+</pba-flex>
+
+Notes:
+
+The polkadot-js/phishing repository is a specialized component of the Polkadot-JS ecosystem focused on security and anti-phishing protection for users of Polkadot and Substrate-based blockchain applications.
+
+Key features include:
+
+- Phishing Site Database: Maintains a curated list of known phishing websites and malicious domains that target Polkadot, Kusama, and other related blockchain users.
+- Address Blacklists: Contains lists of suspicious or known malicious addresses that have been associated with scams or theft.
+- Community Maintenance: The repository is community-run, allowing for rapid response to new threats as they emerge.
+
+This repository serves as a crucial security layer for the ecosystem, helping to protect users from common scams and attacks. The data is used by wallet interfaces, including the Polkadot{.js} Extension, to warn users when they might be interacting with potentially malicious sites or addresses.
+
+The community-driven nature of this repository allows for quick updates as new threats are identified, creating a collaborative defense mechanism against scammers targeting the Polkadot ecosystem.
+
+---
+
+### @polkadot/tools - Developer Utilities
+
+<pba-flex center>
+
+- Command-line interfaces for chain operations
+- Metadata extraction and analysis utilities
+- Network monitoring applications
+- Key management tools
+- Transaction signing utilities
+- JSON-RPC testing interfaces
+
+</pba-flex>
+
+Notes:
+
+The polkadot-js/tools repository provides a collection of useful command-line utilities and developer tools designed to facilitate working with Polkadot, Kusama, and other Substrate-based blockchains.
+
+Key components include:
+
+- CLI Utilities: Command-line interfaces for common operations like querying chain state, submitting transactions, and monitoring events without needing to build a full application.
+- Metadata Extraction: Tools for extracting, analyzing, and working with chain metadata, which is essential for understanding the capabilities and structure of different chains.
+- Monitor Applications: Utilities for monitoring node status, network performance, and blockchain metrics.
+- Key Management: Command-line tools for generating and managing cryptographic keys.
+- Signer Utilities: Tools that help with transaction signing processes, which can be used for testing or automated systems.
+- JSON-RPC Interface Tools: Utilities for exploring and testing the JSON-RPC endpoints exposed by Substrate nodes.
+
+These tools are particularly valuable for developers who need to perform quick operations or automate tasks without building complete applications. They provide a command-line interface to many of the same capabilities available through the API, making them useful for scripts, CI/CD pipelines, and server-side applications.
+
+---
+
+### @polkadot/ui - User Interface Components
+
+<pba-flex center>
+
+- React components for blockchain applications
+- Address formatting and visualization
+- Balance and data formatting utilities
+- Identicon generators
+- Specialized input components
+- Responsive design elements
+- Keyring integration
+
+</pba-flex>
+
+Notes:
+
+The polkadot-js/ui repository provides a collection of user interface components and utilities designed specifically for creating web applications that interact with Polkadot, Kusama, and other Substrate-based blockchains.
+
+Key features include:
+
+- React Components: A library of ready-to-use React components tailored for blockchain applications, including account selection and display, address formatting and visualization, transaction submission forms, and balance displays.
+- UI Utilities: Helper functions for formatting blockchain data in user-friendly ways, such as balance and token formatting, time and block number formatting, and data presentation helpers.
+- Identicon Generators: Various implementations of address visualization (identicons) to help users recognize addresses visually, supporting multiple styles including Polkadot's unique circular format.
+- Input Components: Specialized input components for blockchain-specific data types like addresses and token amounts.
+- Responsive Design: Components designed to work across different screen sizes for mobile and desktop applications.
+- Theming Support: Customizable styling options to match different application designs while maintaining consistent behavior.
+- Keyring Integration: UI components that integrate with the Polkadot-JS keyring for secure key management.
+
+These components help developers create consistent, user-friendly interfaces for Polkadot ecosystem applications without having to build everything from scratch. They ensure that common UI patterns follow best practices and maintain consistency across different applications.
+
+---
+
+### @polkadot/apps - Comprehensive Web Interface
+
+<pba-flex center>
+
+- Feature-rich dashboard for all on-chain functionality
+- Automatic adaptation to any Substrate chain
+- Block explorer and transaction viewer
+- Staking and governance interfaces
+- Parachain tools and cross-chain functionality
+- Developer tools and testing interfaces
+- Account management
+
+</pba-flex>
+
+Notes:
+
+The polkadot-js/apps repository houses the flagship application in the Polkadot-JS ecosystem - a comprehensive web-based interface for interacting with Polkadot, Kusama, and any Substrate-based blockchain. Often referred to as "Polkadot-JS Apps" or simply "the Apps," this is the official reference implementation UI for Substrate chains.
+
+Key features include:
+
+1. Complete Chain Dashboard: A feature-rich interface providing access to virtually all on-chain functionality including account management, transfers, staking, governance, and parachains.
+2. Multi-chain Support: Built to work seamlessly with any Substrate-based chain, automatically adapting its interface based on the connected chain's capabilities and metadata.
+3. Explorer Functions: Comprehensive block explorer functionality including block details, transaction history, events, and state queries.
+4. Staking Management: Complete tools for nominators and validators to participate in network security through staking, including validator selection, reward tracking, and stake management.
+5. Governance Participation: Interfaces for participating in on-chain governance through proposals, referenda voting, and treasury proposals.
+6. Parachain Tools: Specialized interfaces for parachain-specific functions like crowdloans, auctions, and cross-chain messaging.
+7. Developer Tools: Advanced functionality for developers including extrinsic submission, chain state queries, RPC calls, and contract interaction.
+8. Account Management: Comprehensive account management with address book functionality, transaction history, and integration with browser extensions.
+9. Network Customization: Support for connecting to custom networks and local development nodes.
+10. Settings & Flexibility: Extensive customization options for display preferences, connection settings, and advanced features.
+
+The application is designed as a single-page application built with React that leverages the entire Polkadot-JS ecosystem. It's hosted officially at https://polkadot.js.org/apps/, but can also be run locally or self-hosted for additional security.
+
+---
+
+### @polkadot/extension - Browser Extension
+
+<pba-flex center>
+
+- Secure key management in browser environment
+- Separation of dApp and key storage concerns
+- Authorization system for website connections
+- Multiple account management
+- Transaction signing interface
+- Metadata management for chain compatibility
+
+</pba-flex>
+
+Notes:
+
+The Polkadot{.js} Extension (from the polkadot-js/extension repository) provides a secure browser extension for managing accounts and signing transactions for Substrate-based blockchains.
+
+Key features include:
+
+- Secure Key Management: Stores private keys securely within the browser's extension storage, isolating them from potentially malicious websites.
+- dApp Integration: Provides an interface for websites to request accounts and transaction signatures without ever accessing the private keys.
+- Website Authorization: Implements a permission system where users must explicitly authorize websites to access their accounts.
+- Multiple Account Support: Allows users to manage multiple accounts across different networks within a single interface.
+- Transaction Signing: Provides a secure interface for reviewing and signing transactions before they're submitted to the blockchain.
+- Metadata Management: Keeps track of metadata from different chains to ensure accurate transaction construction and display.
+
+The extension follows a security model similar to MetaMask and other Web3 wallets, where the extension maintains custody of private keys and websites can only request signatures for specific operations after receiving user permission.
+
+This clean separation of concerns is crucial for security in blockchain applications, as it prevents websites from directly accessing private keys while still allowing them to request the necessary signatures for blockchain operations.
+
+---
+
+## Key Takeaways
+
+<pba-flex center>
+
+- Polkadot-JS is a comprehensive ecosystem, not a single library
+- Each component serves a specific purpose but works together seamlessly
+- The API provides the core blockchain interaction capabilities
+- Historical metadata support remains unmatched
+- UI components and Apps serve as reference implementations
+- Security and developer experience are prioritized throughout
+
+</pba-flex>
+
+Notes:
+
+Understanding Polkadot-JS as a complete ecosystem rather than a single library is crucial for making the most of its capabilities. Each component is designed to fulfill a specific role while maintaining compatibility with the rest of the ecosystem.
+
+The API remains the heart of the ecosystem, providing the essential capabilities for interacting with Substrate-based chains. Its comprehensive historical metadata support makes it particularly valuable for applications that need to work with chain history.
+
+The UI components and Apps interface serve as reference implementations that demonstrate best practices for blockchain interaction. Developers can learn from these implementations or use them directly in their own applications.
+
+Throughout the ecosystem, there's a consistent focus on security (as seen in the phishing protection and extension design) and developer experience (reflected in the comprehensive tools and documentation).
+
+By understanding the structure and capabilities of each component, developers can make informed decisions about which parts of the ecosystem to use for their specific needs, whether they're building simple scripts or complex applications.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions?
diff --git a/content/7-dApps_Off-Chain/1-3-polkadot-js-importance-slides.md b/content/7-dApps_Off-Chain/1-3-polkadot-js-importance-slides.md
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+---
+title: Why is a Base Understanding of Polkadot-JS Important?
+description: Why is a Base Understanding of Polkadot-JS Important?
+duration: 30 minutes
+---
+
+## Why is a Base Understanding of Polkadot-JS Important?
+
+---
+
+### Polkadot-JS as the Old Industry Standard
+
+- One of the earliest and most comprehensive SDKs for Polkadot
+- Widespread adoption as result of years of continued development
+- Foundation of ecosystem tooling and infrastructure
+
+Notes:
+
+Polkadot-JS has firmly established itself as the old industry standard for interacting with the Polkadot and Kusama networks. As one of the earliest and most comprehensive SDKs for Polkadot, it has been designed and continuously updated to support almost every iteration of the network's evolving metadata, runtime upgrades, and structural changes.
+
+It has become a fundamental building block for anyone developing on Polkadot, and its widespread use has set the baseline for how developers build, integrate, and deploy Polkadot-based applications. This widespread adoption comes as result of years of continued development and maintenance, which has turned the project into a mature set of developer tools.
+
+This widespread adoption is not just because of its maturity and feature set but because Polkadot-JS simplifies the complex task of interacting with a decentralized, multi-chain network. It once served as the go-to library for developers needing to query chain data, send transactions, and handle Polkadot-specific logic.
+
+---
+
+### Influence on Polkadot-Based Applications
+
+- Many existing tools and legacy systems depend on it
+  - chopsticks
+  - zombienet
+  - substrate-api-sidecar
+- Future migrations to new tools require knowledge of Polkadot-JS
+
+Notes:
+
+Without a solid base understanding of how Polkadot-JS works, it becomes difficult to effectively develop or maintain applications within the Polkadot ecosystem. Because it's the first point of contact for interacting with Polkadot and Kusama, many other blockchains and ecosystems look to Polkadot-JS for inspiration in their own SDKs and development frameworks.
+
+By understanding Polkadot-JS, developers can more easily transfer their knowledge to other ecosystems or even contribute to the continued evolution of Polkadot-JS itself.
+
+Even as newer tools emerge, understanding the patterns and approaches used in Polkadot-JS helps developers better understand how to interface with Substrate-based chains and provides valuable context for the design decisions made in newer tools.
+
+---
+
+### Efficient Problem-Solving and Debugging
+
+- Understanding its behavior and design is key to troubleshooting
+- Knowledge of limitations helps avoid repeating design mistakes
+- Provides insight into Substrate architecture and data structures
+
+Notes:
+
+Given that Polkadot-JS is foundational to many applications in the Polkadot ecosystem, understanding its behavior and design is key to troubleshooting and resolving issues. Whether it's debugging failed transactions, understanding chain synchronization problems, or diagnosing issues with the structure of events and extrinsics, a deep knowledge of Polkadot-JS enables developers to quickly pinpoint the source of problems and fix them efficiently.
+
+Since Polkadot-JS is the tool used for many underlying blockchain interactions, errors and issues that arise in other applications or tools often trace back to how Polkadot-JS is being utilized.
+
+Understanding the limitations and flaws of Polkadot-JS also helps avoid these mistakes when developing new solutions. Using Polkadot-JS as the base on which to build a new, more efficient and flexible solution works better when keeping in mind these limitations.
+
+---
+
+### Knowledge Transfer to Future Tools
+
+- Understanding Polkadot-JS helps with migration to newer tools like PAPI
+- Core concepts of chain interaction remain consistent across tools
+- Historical context provides insight into why newer tools make different choices
+
+Notes:
+
+As the ecosystem evolves and newer tools like PAPI (Polkadot API) emerge, understanding Polkadot-JS becomes even more valuable. The knowledge of how Polkadot-JS interacts with Substrate chains transfers directly to these newer tools, making the transition smoother.
+
+The core concepts of chain interaction - connecting to nodes, querying state, constructing and submitting transactions - remain consistent across different tools, though the implementation details may change.
+
+Understanding why Polkadot-JS made certain design choices, and where those choices led to limitations, provides valuable context for appreciating the different approaches taken by newer tools. This historical perspective helps developers make more informed decisions about which tools to use for different projects and use cases.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions?
diff --git a/content/7-dApps_Off-Chain/1-4-polkadot-js-when-to-use-slides.md b/content/7-dApps_Off-Chain/1-4-polkadot-js-when-to-use-slides.md
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+---
+title: When Might You Want to Use Polkadot-JS?
+description: When Might You Want to Use Polkadot-JS
+duration: 30 - 45 minutes
+---
+
+## When Might You Want to Use Polkadot-JS?
+
+---
+
+### Historical Metadata Queries
+
+- Essential for analyzing past chain state
+- Comprehensive support for all historical runtime versions
+- Crucial for block explorers and data analysis tools
+
+Notes:
+
+One of the standout features of Polkadot-JS is its comprehensive support for historical metadata. This makes it the tool of choice for applications that need to analyze or display data from any point in the chain's history.
+
+Block explorers, data analysis tools, and historical auditing applications all benefit from this capability. No other tool currently provides the same level of historical compatibility, making Polkadot-JS irreplaceable for these use cases.
+
+As chains evolve and undergo runtime upgrades, the structure of their data and the methods for interacting with them change. Polkadot-JS maintains backward compatibility with all these changes, allowing developers to decode and interpret data from any block height.
+
+---
+
+### As a Reference or Utility
+
+- Useful for learning Substrate interactions before implementing custom solutions
+- Provides working examples of common blockchain operations
+- Source code serves as documentation for Substrate interaction patterns
+
+Notes:
+
+Even when building custom solutions, Polkadot-JS serves as an invaluable reference. Its source code effectively documents how to interact with Substrate chains at a low level, making it easier to understand the underlying protocols and data structures. That being said, there are definitely exceptions (rpc interface, extension interface, etc).
+
+Many developers start by prototyping their applications with Polkadot-JS before implementing more specialized solutions. This approach allows them to validate their concepts quickly before investing in custom development.
+
+The various utilities provided by Polkadot-JS, particularly in the @polkadot/util and @polkadot/util-crypto packages, remain useful even when building applications that don't use the full API. These well-tested utilities save developers from having to reimplement common cryptographic and formatting functions.
+
+---
+
+### Legacy System Maintenance
+
+- Many existing tools still rely on Polkadot-JS
+- Understanding the library is crucial for maintaining these systems
+- Required for debugging issues in Polkadot-JS-dependent applications
+
+Notes:
+
+A significant portion of the Polkadot ecosystem was built with Polkadot-JS, and these systems will continue to require maintenance for years to come. Understanding Polkadot-JS is essential for developers tasked with maintaining or updating these existing applications.
+
+When issues arise in these systems, debugging often requires a deep knowledge of how Polkadot-JS interacts with the blockchain. Without this understanding, diagnosing and fixing problems becomes significantly more challenging.
+
+Even as new applications increasingly adopt newer tools, the legacy of Polkadot-JS will persist in the ecosystem for the foreseeable future, ensuring that expertise in this library remains valuable.
+
+---
+
+### For Comprehensive Development UIs
+
+- Polkadot.js Apps remains the most generalized UI for chain interaction
+- Provides a sandbox for testing chain functionality
+- Polkadot.js Extension for a airgapped developer first extension
+
+Notes:
+
+The Polkadot.js Apps interface remains one of the most comprehensive UIs for interacting with Substrate-based chains. It provides access to virtually every aspect of chain functionality, from basic transfers to complex governance operations.
+
+This interface serves as an invaluable sandbox for testing and debugging chain functionality. Developers can use it to verify that their on-chain logic works as expected before integrating it into their own applications.
+
+While more specialized and user-friendly interfaces exist for specific chains and use cases, none match the comprehensiveness of Polkadot.js Apps for development and debugging purposes.
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions?
diff --git a/content/7-dApps_Off-Chain/1-5-polkadot-js-limitations-slides.md b/content/7-dApps_Off-Chain/1-5-polkadot-js-limitations-slides.md
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+---
+title: Limitations of Polkadot-JS
+description: Understanding the challenges and limitations that emerged as the ecosystem evolved
+duration: 1 hour
+---
+
+# Limitations of Polkadot-JS
+
+---
+
+### Poor Light Client Support
+
+<pba-flex center>
+
+- Heavy reliance on centralized nodes for queries
+- Limited support for true decentralized applications
+- Challenges for mobile and resource-constrained environments
+
+</pba-flex>
+
+Notes:
+
+One of the most significant limitations of Polkadot-JS is its poor support for light clients. The library is designed to work with full RPC nodes, which typically means relying on centralized infrastructure providers.
+
+This dependency on centralized nodes undermines the decentralized nature of blockchain applications. If these nodes go down or are compromised, applications built on Polkadot-JS may become unavailable or vulnerable.
+
+The lack of efficient light client support also creates challenges for mobile applications and other resource-constrained environments, where downloading and processing large amounts of blockchain data is impractical.
+
+Newer tools and approaches are addressing this limitation by implementing more efficient light client protocols and WASM-based verification that can run directly in browsers and mobile devices.
+
+---
+
+### Overly Coupled Dependencies
+
+<pba-flex center>
+
+- Tightly interconnected packages
+- Difficult to use individual components
+- Increased bundle sizes for web applications
+- Challenges in maintenance and updates
+
+</pba-flex>
+
+Notes:
+
+Polkadot-JS consists of numerous packages that are tightly coupled with each other. This high level of interdependency means that using any single component often requires pulling in large portions of the entire library.
+
+For web applications, this results in larger bundle sizes, which can negatively impact loading times and performance. Even simple applications may end up including substantial amounts of unused code.
+
+The tight coupling also complicates maintenance and updates. Changes to one package often necessitate updates to several others, creating a complex web of dependencies that must be managed carefully.
+
+This architecture made sense in the early days of the ecosystem when rapid development was prioritized over modularity, but it has become increasingly problematic as the ecosystem has matured and more specialized use cases have emerged.
+
+---
+
+### Legacy JSON-RPC Interface
+
+<pba-flex center>
+
+- Designed for full nodes, not light clients
+- Runtime-dependent parameters and return values
+- Lacks proper DoS protection mechanisms
+- Poorly documented edge cases and error handling
+- Not load-balancer friendly
+- Based on Ethereum's RPC with ad-hoc expansions
+
+</pba-flex>
+
+Notes:
+
+Polkadot-JS was built around the original JSON-RPC interface for Substrate, which has several fundamental limitations:
+
+1. Full-node assumptions: Many functions assume a full node implementation, making them inefficient or impossible to implement properly on light clients (e.g., state_getKeysPaged downloads all keys repeatedly on light clients).
+2. Runtime dependencies: Functions like payment_queryInfo depend on specific runtime details, forcing tight coupling between node and runtime versions, undermining the benefits of upgradable runtimes.
+3. Subscription inefficiencies: The existing subscription model doesn't properly separate concerns, making it difficult to implement efficient data streaming and resource management.
+4. Lack of standardization: Inconsistent error handling across functions (some return null, others return errors for the same condition).
+5. Resource management issues: No clear mechanism for clients to signal when they're done with resources, forcing servers to guess about caching strategies.
+
+The new JSON-RPC API addresses these limitations with a consistent naming scheme, proper namespacing, explicit resource management via pinning, clear separation between archive and recent data access patterns, and improved subscription models that provide consistent views of chain state.
+
+---
+
+### Too Many Responsibilities
+
+<pba-flex center>
+
+- Acts as a wallet, RPC client, API, and UI tool
+- Jack of all trades, master of none
+- Difficult to optimize for specific use cases
+- Challenging to maintain and evolve
+
+</pba-flex>
+
+Notes:
+
+Polkadot-JS attempts to fulfill too many diverse functions, from low-level cryptography to high-level UI components. This broad scope makes it difficult to excel in any single area.
+
+For developers with specific needs, this means either accepting suboptimal solutions or building custom implementations. Neither option is ideal, especially for teams with limited resources.
+
+The wide range of responsibilities also complicates maintenance and evolution. Improvements to one aspect of the library might introduce regressions in others, making it challenging to implement significant changes without extensive testing and coordination.
+
+Modern software development generally favors more focused, modular tools that do one thing well and can be combined as needed. Newer tools in the ecosystem are following this approach, providing more specialized solutions for specific use cases.
+
+---
+
+### High Abstraction Complexity
+
+<pba-flex center>
+
+- Many layers of abstraction
+- Difficult debugging process
+- Steep learning curve for new developers
+- Challenges in understanding error sources
+
+</pba-flex>
+
+Notes:
+
+Polkadot-JS employs multiple layers of abstraction to simplify common tasks and hide the complexity of the underlying blockchain protocols. While these abstractions make simple tasks easier, they can make debugging and troubleshooting significantly more complex.
+
+When errors occur, they often happen deep within the library's internals, making it difficult to identify the root cause. The error messages may be cryptic or provide limited information about what went wrong.
+
+This complexity creates a steep learning curve for new developers. Understanding how all the pieces fit together requires significant investment of time and effort, which can be a barrier to entry for those new to the ecosystem.
+
+Even experienced developers may struggle to understand the full implications of certain API calls or the exact data flow through the various abstraction layers.
+
+---
+
+### Handling of Type Information
+
+<pba-flex center>
+
+- Relies on dynamic runtime metadata
+- Can be brittle when chains update
+- Challenges with type consistency across runtime versions
+- Complex type registry management
+
+</pba-flex>
+
+Notes:
+
+Substrate chains provide type information through runtime metadata, which Polkadot-JS uses to interpret the chain's data structures. This approach is flexible but introduces several challenges:
+
+1. Type information is loaded dynamically at runtime, which can lead to errors if the metadata doesn't match the chain's current state.
+
+2. When chains update their types, applications may need to manually update their type definitions to maintain compatibility.
+
+3. Managing custom types across different runtime versions can become complex, especially for applications that need to work with multiple chains or historical data.
+
+4. The type system is intricate and can be difficult to debug when issues arise.
+
+Newer approaches are exploring ways to make type handling more robust and developer-friendly, such as generating static TypeScript definitions from chain metadata or using more structured type systems.
+
+---
+
+## Addressing the Limitations
+
+<pba-flex center>
+
+- PAPI: Next-generation TypeScript SDK with improved modularity
+- Substrate Connect: Light client-focused solution
+- Subxt: Rust-based alternative with strong typing
+- New JSON-RPC API: Addressing fundamental protocol limitations
+- Component-specific libraries for targeted use cases
+
+</pba-flex>
+
+Notes:
+
+Several initiatives are underway to address these limitations:
+
+1. PAPI (Polkadot API) is being developed as a more modular replacement for the Polkadot-JS API, with cleaner separation of concerns and improved light client support.
+
+2. Substrate Connect provides light client functionality specifically designed for browser environments, enabling truly decentralized applications.
+
+3. Subxt offers a Rust-based alternative for developers who prefer stronger typing and better performance characteristics.
+
+4. The new JSON-RPC API aims to address the fundamental limitations in the protocol layer, providing a more robust foundation for client libraries.
+
+5. More specialized, focused libraries are emerging for specific use cases, following the principle of doing one thing well.
+
+These initiatives represent the next evolution of the Substrate development ecosystem, building on the lessons learned from Polkadot-JS while addressing its limitations.
+
+---
+
+## Key Takeaways
+
+<pba-flex center>
+
+- Polkadot-JS's design choices reflect early ecosystem priorities
+- Current limitations affect scalability, maintainability, and DX
+- Understanding these limitations helps with architecture decisions
+- Newer tools are specifically addressing these shortcomings
+- Historical support remains a unique strength despite limitations
+- Gradual migration path exists for developers and applications
+
+</pba-flex>
+
+Notes:
+
+Polkadot-JS's limitations are largely a product of its organic evolution and the priorities of the early Polkadot ecosystem. What began as a flexible solution for a rapidly developing blockchain platform has shown strain as the ecosystem has matured and requirements have become more specialized.
+
+The key limitations around light client support, coupled dependencies, abstraction complexity, and the JSON-RPC interface affect scalability, maintainability, and developer experience. Understanding these limitations helps developers make informed decisions about when to use Polkadot-JS and when alternative approaches might be more appropriate.
+
+While newer tools like PAPI and Substrate Connect are specifically addressing these shortcomings, Polkadot-JS continues to offer unmatched historical support and comprehensive functionality. This creates a gradual migration path where developers can adopt newer tools for new projects while maintaining existing Polkadot-JS implementations.
+
+The lessons learned from Polkadot-JS are informing the design of the next generation of tools, ensuring that they maintain the strengths while addressing the limitations. This evolution reflects the maturation of the Polkadot ecosystem as a whole, as it moves from pioneering innovation to sustainable, production-ready infrastructure.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions?
diff --git a/content/7-dApps_Off-Chain/1-6-polkado-js-future-slides.md b/content/7-dApps_Off-Chain/1-6-polkado-js-future-slides.md
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+---
+title: Future of Polkadot-JS
+description: Where Polkadot-JS is heading and emerging alternatives
+duration: 15 minutes
+---
+
+# Future of Polkadot-JS
+
+---
+
+## Future Directions
+
+<pba-flex center>
+
+- Continued maintenance for legacy support
+- Gradual transition to more modern tooling
+- Community-driven improvements
+- Reference implementation for new tools
+
+</pba-flex>
+
+Notes:
+
+While newer tools are emerging to address some of Polkadot-JS's limitations, it will continue to be maintained for the foreseeable future due to its widespread adoption and the many systems that depend on it.
+
+The knowledge and patterns developed in Polkadot-JS will inform the next generation of Substrate development tools, ensuring that its legacy continues even as newer alternatives gain adoption.
+
+For developers entering the ecosystem today, understanding Polkadot-JS provides valuable context about how Substrate chains work, even if they ultimately build with newer tools.
+
+---
+
+## Modern Alternatives
+
+<pba-flex center>
+
+- **PAPI** - Next-generation TypeScript SDK with improved modularity
+- **Subxt** - Rust-based SDK with strong type safety
+- **Substrate Connect** - Light client solution for browsers
+- **Custom RPC clients** - Specialized solutions for specific use cases
+
+</pba-flex>
+
+Notes:
+
+As the ecosystem matures, several alternatives to Polkadot-JS are emerging, each addressing different limitations:
+
+PAPI (Polkadot API) is being developed as a more modular, modern TypeScript SDK with cleaner separation of concerns and better support for light clients. It aims to provide a more maintainable and extensible foundation for JavaScript/TypeScript applications.
+
+Subxt offers a Rust-based alternative with strong type safety and efficient performance. It's particularly well-suited for backend services and applications where performance is critical.
+
+Substrate Connect focuses specifically on light client functionality, enabling truly decentralized applications that don't rely on centralized RPC endpoints.
+
+Many teams are also developing custom RPC clients tailored to their specific needs, especially for applications with unique requirements or performance constraints.
+
+Understanding the strengths and limitations of Polkadot-JS helps developers make informed decisions about when to use these alternatives and how to effectively migrate to them when appropriate.
+
+---
+
+## Migration Strategies
+
+<pba-flex center>
+
+- Incremental adoption of new tools for specific features
+- Gradual replacement of Polkadot-JS components
+- Hybrid approaches during transition
+- Leveraging common patterns and knowledge
+
+</pba-flex>
+
+Notes:
+
+For existing applications using Polkadot-JS, migration to newer tools will likely be a gradual process:
+
+1. Incremental adoption: Start by using newer tools for specific features or components while maintaining Polkadot-JS for core functionality.
+
+2. Component replacement: Replace individual Polkadot-JS components with their modern equivalents one at a time, starting with those that provide the greatest benefit.
+
+3. Hybrid approaches: During transition, applications may use both Polkadot-JS and newer tools in parallel, especially for critical functions where redundancy provides safety.
+
+4. Knowledge transfer: The patterns and concepts learned from working with Polkadot-JS remain valuable when working with newer tools, as many of the fundamental blockchain interaction patterns remain similar.
+
+These strategies allow applications to benefit from newer tools while minimizing disruption and maintaining compatibility with existing systems.
+
+---
+
+## Preserving the Legacy
+
+<pba-flex center>
+
+- Historical metadata support remains essential
+- Documentation of design decisions and patterns
+- Transfer of community knowledge
+- Learning from both successes and limitations
+
+</pba-flex>
+
+Notes:
+
+As the ecosystem transitions to newer tools, it's important to preserve the valuable legacy of Polkadot-JS:
+
+The historical metadata support in Polkadot-JS remains unmatched and essential for applications that need to interact with the chain's history. This capability needs to be maintained or transferred to newer tools.
+
+Documentation of the design decisions, patterns, and approaches used in Polkadot-JS provides valuable context for future development. Understanding why certain choices were made helps prevent repeating past mistakes.
+
+The extensive community knowledge built around Polkadot-JS represents a significant asset. Facilitating the transfer of this knowledge to newer tools and approaches ensures that the community's expertise continues to benefit the ecosystem.
+
+Both the successes and limitations of Polkadot-JS offer important lessons for future development. By learning from both aspects, the next generation of tools can build on what worked well while addressing the challenges that emerged.
+
+---
+
+## Key Takeaways
+
+<pba-flex center>
+
+- Polkadot-JS has been the cornerstone of Substrate development
+- Knowledge remains valuable even when using newer tools
+- Understanding limitations informs better design choices
+- Migration will be gradual and evolutionary
+- Historical support capabilities must be preserved
+
+</pba-flex>
+
+Notes:
+
+Polkadot-JS has played a crucial role in the growth and development of the Polkadot ecosystem. While it has limitations, its comprehensive functionality and historical support make it an invaluable tool for many development scenarios.
+
+As the ecosystem evolves, developers should understand both when to use Polkadot-JS and when newer tools might be more appropriate for their specific use cases. This balanced understanding will ensure they can make the best technology choices while building on Substrate-based chains.
+
+The knowledge gained from working with Polkadot-JS – understanding chain metadata, transaction construction, and blockchain state management – transfers well to other tooling and provides a solid foundation for Substrate development regardless of the specific libraries used.
+
+Migration from Polkadot-JS to newer tools will be an evolutionary process rather than a revolutionary one, with both approaches coexisting for some time. This gradual transition allows the ecosystem to maintain stability while embracing innovation.
+
+Perhaps most importantly, the valuable capabilities that Polkadot-JS pioneered, particularly around historical data access, must be preserved and enhanced in newer tools to ensure continuity for critical applications.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions?
diff --git a/content/7-dApps_Off-Chain/2-papi-starter-slides.md b/content/7-dApps_Off-Chain/2-papi-starter-slides.md
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+---
+title: Polkadot-API Getting Started
+description: Getting started with Polkadot-API
+---
+
+# dApps / Off-chain
+
+---
+
+## Module Overview
+
+- Understand interaction with a chain
+- Metadata in-depth <!-- .element: class="fragment" -->
+- JSON-RPC Interface <!-- .element: class="fragment" -->
+  - chainHead <!-- .element: class="fragment" -->
+  - storage <!-- .element: class="fragment" -->
+  - transactions <!-- .element: class="fragment" -->
+
+---
+
+## Module Overview
+
+- Polkadot-API
+  - Sub-libraries <!-- .element: class="fragment" -->
+  - Subscriptions <!-- .element: class="fragment" -->
+  - Compatibility API <!-- .element: class="fragment" -->
+  - Signers <!-- .element: class="fragment" -->
+  - Ink! <!-- .element: class="fragment" -->
+- PAPI SDKs <!-- .element: class="fragment" -->
+
+---
+
+## Grading
+
+- Assignment
+  - dApp for specific chain feature <!-- .element: class="fragment" -->
+  - Optional Add-ons <!-- .element: class="fragment" -->
+  - Qualitative grading <!-- .element: class="fragment" -->
+- UI/UX is NOT graded <!-- .element: class="fragment" -->
+- Business logic code <!-- .element: class="fragment" -->
+- Research, considerations <!-- .element: class="fragment" -->
+
+Notes:
+
+Optional Add-ons many are related together, so you might choose to focus on on a specific area within the pallet.
+
+---
+
+## Grading
+
+- During class
+  - Participation
+  - Academic integrity
+  - Cooperation
+  - Overall engagement
+
+Notes:
+
+You MUST pay attention to class and do the assignment after and not in class.
+
+For working with the assignment, we have office hours after lessons.
+
+Depending on timeline, we might have days where we might have some extra class time for assignment Q&A, specially towards the end.
+
+---
+
+## Today
+
+- Getting started - Polkadot-api <!-- .element: class="fragment" -->
+- Dev Tools <!-- .element: class="fragment" -->
+- Assignment description <!-- .element: class="fragment" -->
+
+Notes:
+
+During this module we will go deep through Polkadot-API, from a low-level, interacting with a JSON-RPC endpoint to a higher level like polkadot-api and then its SDKs.
+
+To unblock you from working on the assignment, here's a quick getting started with polkadot-api, which will let you connect with a chain and start interacting with it.
+
+---
+
+# Polkadot-API
+
+## Getting Started
+
+---
+
+## Polkadot-API
+
+Typescript library to interact with Polkadot-based chains
+
+https://papi.how/
+
+---
+
+## Polkadot-API
+
+- 💡 Fully Typed
+- 🪶 Light-client first
+- 🚀 Performant and light-weight
+- 🧩 Modular
+
+Notes:
+
+Full Typed: Not only the library itself, but the interactions with each chain. It even pulls the interaction docs as JSDocs to show them in intellisense.
+
+---
+
+## Concepts
+
+<img rounded src="./img/high-lvl-overview.svg" />
+
+Notes:
+
+https://excalidraw.com/#json=SLLLnZdCrJdd1PYIurjGv,IwZlWHL0yw0GLMW6uMEnZw
+
+---
+
+## Polkadot-API
+
+```sh
+npm install polkadot-api
+
+npx papi add dot -n polkadot
+```
+
+Notes:
+
+Let's jump into live demo
+
+- Basics
+  - Installing papi
+  - Connecting to a chain (westend, will be needed for sending tx)
+- Operations
+  - Query storage: System.account
+  - Runtime call: estimate fees with TransactionPaymentApi.queryInfo
+    - Create extrinsic System.remark
+  - Constant: Balances.ExistentialDeposit
+    - introduce compatibility token
+
+=> Find how much balance does the account holding the sudo key have.
+=> Find all the Proxy(any) accounts
+=> Find out if some account has configured the maximum amount of proxy delegates.
+
+- Transactions
+  - Connect to pjs extension
+  - Get signer from extension
+  - Submit a System.remark to westend
+- Compatibility
+  - Remark the meaning of descriptors
+  - Show example of connecting to a different chain (polkadot) with the same wnd descriptors
+    - System.Remark => works, but throws a payment
+    - Sudo => fails
+
+---
+
+## Devtools
+
+https://dev.papi.how/
+
+https://polkadot.js.org/apps/
diff --git a/content/7-dApps_Off-Chain/3-metadata-slides.md b/content/7-dApps_Off-Chain/3-metadata-slides.md
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+---
+title: Metadata
+description: TODO
+duration: 4 hours
+owner: Carlo Sala
+---
+
+# Metadata
+
+---
+
+## Metadata
+
+#### Content
+
+- Mod. 2 recap:
+  - What is the runtime (and its metadata)?
+  - The metadata sets us apart of other blockchains.
+- Deep dive into metadata
+- Extrinsics
+
+---
+
+## Runtime
+
+- The runtime is the business logic of Polkadot-based networks.
+- It defines the algorithm needed for determining the state of the next block.
+- It is part of the state, not part of the host.
+
+Notes:
+
+Compared to other blockchains (such as Ethereum) the logic to determine the next block state is not part of the
+state itself. Therefore, it can't be modified without a change in the host itself.
+
+---
+
+## Metadata
+
+- The Runtime's Metadata is a bunch of information needed to interact with the Runtime. It defines the shape of the
+  interactions, instead of "what" do they do.
+- It includes _enough_ information to perform any kind of interaction with the blockchain, as well as decoding its state.
+
+---
+
+## Metadata
+
+#### Shape
+
+The metadata is versioned, and its current stable version is `15`.
+
+```typescript [|2|3|4|6|]
+interface RuntimeMetadataV15 {
+  types: Vec<LookupEntry>;
+  pallets: Vec<PalletMetadata>;
+  extrinsic: ExtrinsicMetadata;
+  ty: Type; // not useful, it is the type of the runtime itself
+  apis: Vec<RuntimeApiMetadata>;
+  outer_enums: OuterEnums;
+  custom: CustomMetadata; // we won't enter this one, un-typed extra metadata
+}
+```
+
+---
+
+## Metadata
+
+#### Lookup
+
+The lookup of the metadata defines the shape of all types used in the runtime.
+
+<span style="font-size: 0.6em; opacity: 0.6">(This is already `scale-info`)</span>
+
+```typescript [|2|3,4,6|5|]
+interface LookupEntry {
+  id: u32; // this one is unique, and sequential
+  path: Vec<String>; // where is it found in Rust code
+  type_params: Vec<TypeParameter>; // Rust generics
+  type_def: TypeDef; // THE JUICE!
+  docs: Vec<String>; // Rust docs
+}
+```
+
+Notes:
+
+Docs are self-descriptive. Type params only give information about the generics used in Rust. Path defines the file
+where it is defined in rust.
+
+---v
+
+## Metadata
+
+#### Lookup `type_def`
+
+```typescript [|2|3|4,5|6|7,8|]
+enum TypeDef {
+  Composite, // struct
+  Variant, // enum
+  Sequence, // variable length
+  Array, // fixed length
+  Tuple,
+  Primitive, // essentially integers and booleans
+  Compact,
+  BitSequence,
+}
+```
+
+Notes:
+
+Explain a bit every one. Don't focus particularly, it is just a quick summary of something already explained in mod 2.
+
+---v
+
+## Metadata
+
+#### Lookup challenges
+
+- Circular types
+  - There are types that reference themselves, or form circles.
+  - This makes it difficult to calculate a _checksum_ of the type itself.
+
+<span style="font-size: 0.6em; opacity: 0.6">We used Tarjan's SCC algorithm to detect cycles, see notes</span>
+
+![Image](./img/circular-lookup.svg)
+
+Notes:
+
+https://en.wikipedia.org/wiki/Tarjan's_strongly_connected_components_algorithm
+
+---v
+
+## Metadata
+
+#### Lookup challenges
+
+- Mirrored types
+  - These are types that are completely equivalent, but yet they have different structures that connect them.
+
+<img src="./img/mirrored-lookup.svg" width="50%" />
+
+---v
+
+## Metadata
+
+#### Lookup challenges
+
+- _Second-class_ citizens
+  - Types like balances (_"amount"_) or `AccountId32` are first-class citizens in the blockchains, yet in the Metadata they are not. Identifying them as what they are is a heuristic labour.
+
+---v
+
+#### Example: `AccountId32` and _Balance_
+
+```json [|2-17|18-27]
+[
+  {
+    "id": 0,
+    "path": ["sp_core", "crypto", "AccountId32"],
+    "params": [],
+    "def": {
+      "tag": "composite",
+      "value": [
+        {
+          "type": 1,
+          "typeName": "[u8; 32]",
+          "docs": []
+        }
+      ]
+    },
+    "docs": []
+  },
+  {
+    "id": 63,
+    "path": [],
+    "params": [],
+    "def": {
+      "tag": "compact",
+      "value": 6 // u128
+    },
+    "docs": []
+  }
+]
+```
+
+---v
+
+## Metadata
+
+#### Lookup challenges
+
+- Non-descriptive types
+  - Some types are created in Rust in a way that they get generated in a non-descriptive way.
+  - There are some that are on purpose created this way to save bytes when encoded.
+
+---v
+
+#### Example: `IdentityData`
+
+- A variable length array of bytes `Vec<u8>` (up to `len=32`) is expressed as several variants in an enum.
+
+```json
+{
+  "id": 327,
+  "path": ["pallet_identity", "types", "Data"],
+  "params": [],
+  "def": {
+    "tag": "variant",
+    "value": [
+      {
+        "name": "None",
+        "fields": [],
+        "index": 0,
+        "docs": []
+      },
+      {
+        "name": "Raw0",
+        "fields": [
+          {
+            "type": 328,
+            "docs": []
+          }
+        ],
+        "index": 1,
+        "docs": []
+      },
+      {
+        "name": "Raw1",
+        "fields": [
+          {
+            "type": 329,
+            "docs": []
+          }
+        ],
+        "index": 2,
+        "docs": []
+      },
+      {
+        "name": "Raw2",
+        "fields": [
+          {
+            "type": 330,
+            "docs": []
+          }
+        ],
+        "index": 3,
+        "docs": []
+      },
+      {…},
+      {
+        "name": "Raw32",
+        "fields": [
+          {
+            "type": 1,
+            "docs": []
+          }
+        ],
+        "index": 33,
+        "docs": []
+      },
+      {
+        "name": "BlakeTwo256",
+        "fields": [
+          {
+            "type": 1,
+            "docs": []
+          }
+        ],
+        "index": 34,
+        "docs": []
+      },
+      {…}
+    ]
+  },
+  "docs": []
+}
+```
+
+---v
+
+#### Example: `Vote`
+
+- It encodes `{ aye: boolean; conviction: [0..6] }`
+- `aye` fits in one bit, and `conviction` fits in the rest of the `u8` (aka `u7`).
+- `vote = (aye << 7) + conviction`
+
+```json
+{
+  "id": 155,
+  "path": ["pallet_conviction_voting", "vote", "Vote"],
+  "params": [],
+  "def": {
+    "tag": "composite",
+    "value": [
+      {
+        "type": 2, // u8
+        "docs": []
+      }
+    ]
+  },
+  "docs": []
+}
+```
+
+---v
+
+## Metadata
+
+#### Metadata is autogenerated!
+
+- Many of these flaws arise due to the way the metadata is generated from the Rust code directly.
+- Some of the Runtime implementation details leak to the metadata
+
+---
+
+## Metadata
+
+#### Outer Enums
+
+They are sugar! One can build this type by himself by aggregating all pallets information.
+
+These types are handy though to decode any `call_data`, `event`, or module `error`.
+
+```typescript
+interface OuterEnums {
+  call_enum_ty: Type;
+  event_enum_ty: Type;
+  error_enum_ty: Type;
+}
+```
+
+---
+
+## Metadata
+
+#### Runtime APIs
+
+They allow to execute functions from the Runtime itself.
+Examples:
+
+- Dry Run
+- Fee estimation
+- Metadata
+
+```typescript
+interface RuntimeApiMetadata {
+  name: String;
+  methods: Vec<{
+    name: String;
+    inputs: Vec<{ name: String; ty: Type }>;
+    output: Type;
+    docs: Vec<String>;
+  }>;
+  docs: Vec<String>;
+}
+```
+
+Notes:
+
+Use this slide to exemplify the "pointer" idea of the metadata.
+
+---v
+
+Example: `Metadata` APIs
+
+```json [|4-9|26-31|10-25]
+{
+  "name": "Metadata",
+  "methods": [
+    {
+      "name": "metadata",
+      "inputs": [],
+      "output": 862,
+      "docs": [" Returns the metadata of a runtime."]
+    },
+    {
+      "name": "metadata_at_version",
+      "inputs": [
+        {
+          "name": "version",
+          "type": 4
+        }
+      ],
+      "output": 863,
+      "docs": [
+        " Returns the metadata at a given version.",
+        "",
+        " If the given `version` isn't supported, this will return `None`.",
+        " Use [`Self::metadata_versions`] to find out about supported metadata version of the runtime."
+      ]
+    },
+    {
+      "name": "metadata_versions",
+      "inputs": [],
+      "output": 121,
+      "docs": [
+        " Returns the supported metadata versions.",
+        "",
+        " This can be used to call `metadata_at_version`."
+      ]
+    }
+  ],
+  "docs": [" The `Metadata` api trait that returns metadata for the runtime."]
+}
+```
+
+---
+
+## Metadata
+
+#### Pallets
+
+Every pallet can define an arbitrary number (including none) of **constants**, **calls**, **events**, **errors**,
+**storage queries**. We will walk every one of them.
+
+```typescript
+interface PalletMetadata {
+  name: String;
+  constants: Vec<PalletConstantMetadata>;
+  event: Option<Type>;
+  error: Option<Type>;
+  calls: Option<Type>;
+  storage: Option<PalletStorageMetadata>;
+  index: u8;
+  docs: Vec<String>; // rust docs
+}
+```
+
+---
+
+## Metadata
+
+#### Constants
+
+They represent values that are defined in compile time of the runtime.
+The metadata includes both the type of them and their values.
+
+```typescript
+interface PalletConstantMetadata {
+  name: String;
+  ty: Type;
+  value: Vec<u8>;
+  docs: Vec<String>;
+}
+```
+
+---
+
+## Metadata
+
+#### Events
+
+They are emitted by the runtime when executing certain actions.
+
+There are three types (called `phase`s):
+
+- Initialization: runtime _hooks_ before applying transactions
+- Apply Extrinsic: events emitted by applying transactions
+- Finalization: runtime _hooks_ after applying transactions
+
+They can also include topics, which generally are a vector of hashes. They can be useful to help identify the origin of
+the event (e.g. smart contracts).
+
+---
+
+## Metadata
+
+#### Errors
+
+Pallets can define errors to explain why an extrinsic had no success.
+
+- `System.ExtrinsicSuccess` 🎉
+- `System.ExtrinsicFailed` 🔴
+  - Inside its payoad we find the specific error.
+
+---
+
+## Metadata
+
+#### Calls
+
+They expose all transactions available in that pallet.
+
+We will dig into it during the day.
+
+---
+
+## Metadata
+
+Example: `System`
+
+```json
+{
+  "name": "System",
+  "storage": {…}, // let's follow up with it!
+  "calls": 94,
+  "events": 22,
+  "constants": [
+    {
+      "name": "Version",
+      "type": 508,
+      "value": "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",
+      "docs": [" Get the chain's in-code version."]
+    },
+    {…}
+  ],
+  "errors": 512,
+  "index": 0,
+  "docs": []
+}
+```
+
+---v
+
+## Metadata
+
+Example: `System` calls
+
+```json [|12-24|]
+{
+  "id": 96,
+  "path": ["frame_system", "pallet", "Call"],
+  "params": [
+    {
+      "name": "T"
+    }
+  ],
+  "def": {
+    "tag": "variant",
+    "value": [
+      {
+        "name": "remark",
+        "fields": [
+          {
+            "name": "remark",
+            "type": 14,
+            "typeName": "Vec<u8>",
+            "docs": []
+          }
+        ],
+        "index": 0,
+        "docs": ["Make some on-chain remark.", "", "Can be executed by every `origin`."]
+      },
+      {…}
+    ]
+  },
+  "docs": ["Contains a variant per dispatchable extrinsic that this pallet has."]
+}
+```
+
+---
+
+## Metadata
+
+#### Storage
+
+Every pallet can **optionally** define storage entries. They have the following shape in the metadata:
+
+```typescript [|2|4|5,14|6-13|]
+interface PalletStorageMetadata {
+  prefix: String;
+  entries: Vec<{
+    name: String;
+    modifier: "Optional" | "Default";
+    ty: Enum<{
+      Plain: { value: Type };
+      Map: {
+        hashers: Vec<StorageHasher>;
+        key: Type;
+        value: Type;
+      };
+    }>;
+    default: Vec<u8>;
+    docs: Vec<String>;
+  }>;
+}
+```
+
+---
+
+## Metadata
+
+Example: `System`
+
+```json [|24-33|6-23|]
+{
+  "name": "System",
+  "storage": {
+    "prefix": "System",
+    "items": [
+      {
+        "name": "Account",
+        "modifier": 1,
+        "type": {
+          "tag": "map",
+          "value": {
+            "hashers": [
+              {
+                "tag": "Blake2128Concat"
+              }
+            ],
+            "key": 0,
+            "value": 3
+          }
+        },
+        "fallback": "0x0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000080",
+        "docs": [" The full account information for a particular account ID."]
+      },
+      {
+        "name": "ExtrinsicCount",
+        "modifier": 0,
+        "type": {
+          "tag": "plain",
+          "value": 4
+        },
+        "fallback": "0x00",
+        "docs": [" Total extrinsics count for the current block."]
+      },
+      {…}
+    ]
+  },
+  {…}
+}
+```
+
+---
+
+## Extrinsic
+
+#### Content
+
+- What is an extrinsic?
+- Extrinsic v4 deep dive
+- Future: extrinsic v5
+
+---
+
+## Extrinsic
+
+An **extrinsic** is a request to the runtime to modify the state from outside of it.
+
+TL;DR: **extrinsic** == **transaction**
+
+---
+
+## Extrinsic
+
+#### Type and Versioning
+
+Every extrinsic starts with a version byte, inclunding the extrinsic kind and version.
+
+| Version |   Kind   |    Version Byte     |
+| :-----: | :------: | :-----------------: |
+|    4    | Unsigned |  4 (`0b0000_0100`)  |
+|    4    |  Signed  | 132 (`0b1000_0100`) |
+|    5    |   Bare   |  5 (`0b0000_0101`)  |
+|    5    | General  | 69 (`0b0100_0101`)  |
+
+<span style="font-size: 0.6em; opacity: 0.6">We will focus on version 4, and explain version 5 a bit ahead</span>
+
+---
+
+## Extrinsic
+
+#### Metadata
+
+```typescript
+interface ExtrinsicMetadata {
+  version: 4;
+  address_ty: Type;
+  call_ty: Type;
+  signature_ty: Type;
+  extra_ty: Type;
+  signed_extensions: Vec<{
+    identifier: String;
+    ty: Type;
+    additional_signed: Type;
+  }>;
+}
+```
+
+---
+
+## Extrinsic
+
+#### Signed extensions
+
+Signed extensions are appended to every signed extrinsic with information that is agnostic to the call itself. Examples:
+
+- Mortality (i.e. until which block the transaction should be valid)
+- Tip
+- Genesis hash
+- Nonce
+
+---v
+
+#### `additional_signed`
+
+Some of them are _implicit_. They can only be one single value to be valid. Therefore, they are not encoded in the
+extrinsic to save block space, yet they are signed. Examples:
+
+- Spec version
+- Genesis hash
+
+---v
+
+#### `extra`
+
+These are parts that need to be _explicit_, since multiple values might be valid. They are encoded in the extrinsic.
+Examples:
+
+- Tip
+- Nonce™
+- Mortality
+
+---
+
+## Extrinsic
+
+#### Extrinsic shape
+
+![Image](./img/extrinsic.svg)
+
+<span style="font-size: 0.6em; opacity: 0.6">It is _opaque_ encoded; i.e. prepended by its compact-encoded length</span>
+
+---
+
+## Extrinsic
+
+#### Sign Payload
+
+In order to sign an extrinsic, the payload to be signed by the algorithm is:
+
+![Image](./img/sign-payload.svg)
+
+---
+
+## Extrinsic
+
+#### Future: `v5`
+
+Extrinsic `v5` will rely on extensions to define its origin. I.e. no `origin` or `signature` will be hardcoded.
+
+This increases the flexibility of the extrinsics, leaving the runtime (through extensions) decide the permission level.
+
+![Image](./img/extrinsic-v5.svg)
+
+<span style="font-size: 0.6em; opacity: 0.6">Take it with a pinch of salt, it is still under RFC process (RFC#0124)</span>
diff --git a/content/7-dApps_Off-Chain/4-json-rpc-spec-slides.md b/content/7-dApps_Off-Chain/4-json-rpc-spec-slides.md
new file mode 100644
index 00000000..02df4dd1
--- /dev/null
+++ b/content/7-dApps_Off-Chain/4-json-rpc-spec-slides.md
@@ -0,0 +1,831 @@
+---
+title: JSON-RPC Spec
+description: New JSON-RPC Spec in depth
+---
+
+# JSON-RPC Spec
+
+---
+
+# Recap
+
+## Block States
+
+<img rounded src="./img/block-states.png" />
+
+Notes:
+
+https://excalidraw.com/#json=rV-hfREHgg-bLmhQtMb0o,jc3goNcep8O8tg_HANnz5A
+
+Concepts: Finalized, Pruned, Best, Fork
+
+---
+
+# Recap
+
+## JSON-RPC
+
+- Client - Server RPC protocol with JSON
+- Request
+
+```js
+{ jsonrpc: "2.0", id: "{req_id}", method: "method_name", params: {…} }
+```
+
+- Response
+
+```js
+{ jsonrpc: "2.0", id: "{req_id}", result: {…} }
+```
+
+- Notification
+
+```js
+{ jsonrpc: "2.0", method: "method_name", params: {…} }
+```
+
+---
+
+# Recap
+
+## JSON-RPC Spec
+
+- Spec build for polkadot that uses JSON-RPC
+- Group of functions
+  - rpc
+  - chainSpec
+  - <span class="fragment highlight-red">chainHead</span>
+  - transaction
+  - transactionWatch
+  - archive
+
+Notes:
+
+We will focus on chainHead
+
+---
+
+# JSON-RPC Spec
+
+```js
+>> { jsonrpc: "2.0", id: "1", method: "rpc_methods", params: {} }
+
+<< { jsonrpc: "2.0", id: "1", result: [
+     "rpc_methods",
+     "chainSpec_v1_chainName",
+     "chainSpec_v1_genesisHash",
+     "chainSpec_v1_properties",
+     "chainHead_v1_call",
+     "chainHead_v1_follow",
+     …
+   ]}
+```
+
+Notes:
+
+Mention `id` field can be any string, used to correlate messages.
+
+---
+
+# Chain Head
+
+- Subscription
+  - `chainHead_v1_follow`
+  - `chainHead_v1_unfollow`
+- Operations <!-- .element: class="fragment" -->
+  - `chainHead_v1_header`
+  - `chainHead_v1_body`
+  - `chainHead_v1_storage`
+  - `chainHead_v1_call`
+- Control <!-- .element: class="fragment" -->
+  - `chainHead_v1_continue`
+  - `chainHead_v1_stopOperation`
+  - `chainHead_v1_unpin`
+
+---
+
+# Follow
+
+- Parameters
+  withRuntime: boolean
+  ```ts
+  { jsonrpc: "2.0", id: "1", method: "chainHead_v1_follow", params: [true] }
+  ```
+  <span class="fragment" style="font-size: 0.7em; opacity: 0.7">(Pro tip: Always use `true`)</span>
+- Result: Subscription ID <!-- .element: class="fragment" -->
+  ```ts
+  { jsonrpc: "2.0", id: "1", result: "B4GEopiw1w38Wkr…MxpkWH4JPd4S" }
+  ```
+- Notifications <!-- .element: class="fragment" -->
+  ```js
+  {
+      jsonrpc: "2.0",
+      method: "chainHead_v1_followEvent",
+      params: {
+        subscription: "B4GEopiw1w38Wkr…MxpkWH4JPd4S",
+        result: {…}
+      }
+  }
+  ```
+
+Notes:
+
+Dig a bit into the `withRuntime` parameter, and why using `false` it's a bad idea 99% of the time.
+
+The notifications we will see will be the value of `result`, we omit the JSON-RPC wrapper and subscription parameter for simplicity.
+
+---
+
+## Initialized
+
+```ts
+{
+  event: "initialized",
+  finalizedBlockHashes: [
+    "0x00…000",
+    …
+    "0x00…000"
+  ],
+  finalizedBlockRuntime: {…}
+}
+```
+
+---
+
+## New Block
+
+```ts
+{
+  event: "newBlock",
+  blockHash: "0x00…000",
+  parentBlockHash: "0x00…000",
+  newRuntime: {…}
+}
+```
+
+---
+
+## Best Block Changed
+
+```ts
+{
+  event: "bestBlockChanged",
+  bestBlockHash: "0x00…000"
+}
+```
+
+---
+
+## Finalized
+
+```ts
+{
+  event: "finalized",
+  finalizedBlockHashes: [
+    "0x00…000",
+    …
+    "0x00…000"
+  ],
+  prunedBlockHashes: [
+    "0x00…000",
+    …
+    "0x00…000"
+  ],
+}
+```
+
+---
+
+# Follow
+
+<img rounded src="./img/block-states.png" />
+
+Notes:
+
+Example of notifications emitted by a follow subscription based on this image.
+
+Show papi-console with the following logsRecorder:
+
+```ts
+/*
+import.meta.env.DEV && source.id !== "polkadot_people"
+    ? withLogFollowEvents(console.debug, provider)
+    : provider
+*/
+const withLogFollowEvents = (
+  logFn: (...args: string[]) => void,
+  provider: JsonRpcProvider,
+): JsonRpcProvider => {
+  const events = [
+    "initialized",
+    "newBlock",
+    "bestBlockChanged",
+    "finalized",
+    "stop",
+  ];
+
+  return onMsg => {
+    let followId = "";
+
+    const connection = provider(message => {
+      onMsg(message);
+      if (
+        message.includes(`"id":"${followId}"`)
+        || events.some(m => message.includes(`"event":"${m}"`))
+      ) {
+        const { event, ...rest } = JSON.parse(message)?.params?.result || {};
+        logFn(`<< ${event}`, rest);
+      }
+    });
+
+    return {
+      send(message) {
+        if (message.includes(`"method":"chainHead_v1_follow"`)) {
+          const parsed = JSON.parse(message);
+          followId = parsed.id;
+          logFn(`>> chainHead_v1_follow`, parsed.params);
+        }
+        connection.send(message);
+      },
+      disconnect() {
+        connection.disconnect();
+      },
+    };
+  };
+};
+```
+
+---
+
+# Block Pinning
+
+- Light-client friendly
+- Initialized event `finalizedBlockHashes`
+- New Block event `blockHash`
+- `chainHead_v1_unpin`
+
+---
+
+## Stop
+
+```ts
+{
+  event: "stop";
+}
+```
+
+---
+
+# Operations
+
+- Query the chain
+
+- Send an operation request
+- Receive an Operation ID as a result
+- Receive a Follow Event with the Operation ID with the actual result
+
+---
+
+## Header
+
+<ul>
+<li>
+  Parameters
+
+```ts
+[followSubscription: string, hash: string]
+
+{ jsonrpc: "2.0", id: "1",
+  method: "chainHead_v1_header",
+  params: ["B4GEopiw1w38Wkr…MxpkWH4JPd4S", "0x00…00"]
+}
+```
+
+</li>
+<li class="fragment">
+  Result: SCALE-encoded header
+
+```ts
+{ jsonrpc: "2.0", id: "1", result: "0x00…00" }
+```
+
+</li>
+</ul>
+
+Notes:
+
+The only exception, as the header is guaranteed to be already in the node.
+
+---
+
+## Body
+
+<ul>
+<li>
+  Parameters
+
+```ts
+[followSubscription: string, hash: string]
+
+{ jsonrpc: "2.0", id: "1",
+  method: "chainHead_v1_body",
+  params: ["B4GEopiw1w38Wkr…MxpkWH4JPd4S", "0x00…00"]
+}
+```
+
+</li>
+<li class="fragment">
+  Result: Operation ID
+
+```ts
+{ jsonrpc: "2.0", id: "1", result: "GhwhKA4yL3…Roc29d8e" }
+```
+
+</li>
+<li class="fragment">
+  Notification
+
+```ts
+{
+  event: "operationBodyDone",
+  operationId: "GhwhKA4yL3…Roc29d8e",
+  value: [
+    "0x00…00",
+    …
+    "0x00…00",
+  ]
+}
+```
+
+</li>
+</ul>
+
+Notes:
+
+The only exception, as the header is guaranteed to be already in the node.
+
+---
+
+### JSON-RPC Spec Playground
+
+Notes:
+
+Show basic correlating messages, pinning / unpinning
+
+```ts
+import { chainSpec } from "polkadot-api/chains/westend2";
+import { getSmProvider } from "polkadot-api/sm-provider";
+import { start } from "polkadot-api/smoldot";
+
+const smoldot = start({
+  maxLogLevel: 0,
+});
+
+const provider = getSmProvider(smoldot.addChain({ chainSpec }));
+
+let id = 0;
+const connection = provider(message => {
+  const msg = JSON.parse(message);
+  ellipsisBody(msg);
+  console.log(msg);
+  if (
+    msg.method === "chainHead_v1_followEvent"
+    && msg.params.result.event === "newBlock"
+  ) {
+    const reqId = id++;
+    console.log("Request body", reqId);
+    connection.send(
+      JSON.stringify({
+        jsonrpc: "2.0",
+        id: reqId,
+        method: "chainHead_v1_body",
+        params: [msg.params.subscription, msg.params.result.blockHash],
+      }),
+    );
+  }
+});
+
+connection.send(
+  JSON.stringify({
+    jsonrpc: "2.0",
+    id: id++,
+    method: "chainHead_v1_follow",
+    params: [true],
+  }),
+);
+
+function ellipsisBody(res: any) {
+  if (
+    res.method === "chainHead_v1_followEvent"
+    && res.params.result.event === "operationBodyDone"
+  ) {
+    res.params.result.value = res.params.result.value.map((
+      v: string,
+    ) => (v.length > 32 ? v.slice(0, 32) + "…" : v));
+  }
+}
+```
+
+---
+
+## Runtime Call
+
+<ul>
+<li>
+  Parameters
+
+```ts
+[subscription: string, hash: string, fnName: string, params: string[]]
+
+{ jsonrpc: "2.0", id: "1",
+  method: "chainHead_v1_body",
+  params: [
+    "B4GEo…JPd4S",
+    "0x00…00",
+    "AccountNonceApi_account_nonce",
+    "0x00…00"
+  ]
+}
+```
+
+</li>
+<li class="fragment">
+  Notification
+
+```ts
+{
+  event: "operationCallDone",
+  operationId: "GhwhKA4yL3…Roc29d8e",
+  output: "0x00…00"
+}
+```
+
+</li>
+</ul>
+
+---
+
+### Fetch metadata playground
+
+Notes:
+
+```ts
+import { decAnyMetadata, u32 } from "@polkadot-api/substrate-bindings";
+import { chainSpec } from "polkadot-api/chains/westend2";
+import { getSmProvider } from "polkadot-api/sm-provider";
+import { start } from "polkadot-api/smoldot";
+import { toHex } from "polkadot-api/utils";
+
+const smoldot = start({
+  maxLogLevel: 0,
+});
+
+const provider = getSmProvider(smoldot.addChain({ chainSpec }));
+
+let id = 0;
+const connection = provider(message => {
+  const msg = JSON.parse(message);
+
+  if (msg.method === "chainHead_v1_followEvent") {
+    if (msg.params.result.event === "initialized") {
+      const lastFinalized = msg.params.result.finalizedBlockHashes.at(-1);
+      connection.send(
+        JSON.stringify({
+          jsonrpc: "2.0",
+          id: `${id++}-call`,
+          method: "chainHead_v1_call",
+          params: [
+            msg.params.subscription,
+            lastFinalized,
+            "Metadata_metadata_at_version",
+            toHex(u32.enc(15)),
+          ],
+        }),
+      );
+      msg.params.result.finalizedBlockHashes.forEach((hash: string) =>
+        connection.send(
+          JSON.stringify({
+            jsonrpc: "2.0",
+            id: `${id++}-unpin`,
+            method: "chainHead_v1_unpin",
+            params: [msg.params.subscription, hash],
+          }),
+        )
+      );
+    }
+    if (msg.params.result.event === "newBlock") {
+      connection.send(
+        JSON.stringify({
+          jsonrpc: "2.0",
+          id: `${id++}-unpin`,
+          method: "chainHead_v1_unpin",
+          params: [msg.params.subscription, msg.params.result.blockHash],
+        }),
+      );
+    }
+
+    if (msg.params.result.event === "operationCallDone") {
+      const metadata = decAnyMetadata(msg.params.result.output);
+      console.log("received metadata");
+      console.log(metadata);
+    } else {
+      console.log(msg);
+    }
+  }
+});
+
+connection.send(
+  JSON.stringify({
+    jsonrpc: "2.0",
+    id: id++,
+    method: "chainHead_v1_follow",
+    params: [true],
+  }),
+);
+```
+
+---
+
+# Chain Storage
+
+- State transition function
+- How is the state structured? 🤔
+
+---v
+
+## High-level view
+
+<table>
+  <thead>
+    <tr>
+      <th>Key</th>
+      <th>Value</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>Balance(ALICE)</td>
+      <td>123.21 DOT</td>
+    </tr>
+    <tr>
+      <td>Balance(BOB)</td>
+      <td>72.76 DOT</td>
+    </tr>
+    <tr>
+      <td>Assets(USDC, ALICE)</td>
+      <td>1785.32 USDC</td>
+    </tr>
+    <tr>
+      <td>Votes(BOB, MediumSpender)</td>
+      <td>[{ ref: 1234, vote: 'aye' }]</td>
+    </tr>
+  </tbody>
+</table>
+
+---v
+
+## Inner structure
+
+- It's still a key-value store!
+- But it's ✨Merklized✨
+
+---v
+
+## Merkle Tree Recap
+
+<img rounded src="./img/merkle-tree.png" />
+
+Notes:
+
+https://excalidraw.com/#json=udTXjn9JdUlGMx0UMv3fq,9EeDxmFCZW2IgCwMgSpsjQ
+
+---v
+
+## Merkle Tree Recap
+
+<table>
+  <thead>
+    <tr>
+      <th>Key</th>
+      <th>Value</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>0x45…5f</td>
+      <td>123.21</td>
+    </tr>
+    <tr>
+      <td>0xe4…28</td>
+      <td>72.76</td>
+    </tr>
+    <tr>
+      <td>0x7f…41</td>
+      <td>{ ALICE: 0x45…5f, BOB: 0xe4…28 }</td>
+    </tr>
+    <tr>
+      <td>0x9a…a2</td>
+      <td>1785.32</td>
+    </tr>
+    <tr>
+      <td>0x92…af</td>
+      <td>{ ALICE: 0x9a…a2 }</td>
+    </tr>
+    <tr>
+      <td>0x50…ee</td>
+      <td>[{ ref: 1234, vote: 'aye' }]</td>
+    </tr>
+    <tr>
+      <td>0x2c…72</td>
+      <td>{ BOB: 0x50…ee }</td>
+    </tr>
+    <tr>
+      <td>0x36…c1</td>
+      <td>{ Balance: 0x7f…41, Assets: 0x92…af, Votes: 0x2c…72 }</td>
+    </tr>
+  </tbody>
+</table>
+
+Notes:
+
+Explain structure, then explain an example of how the storage is traversed.
+
+---v
+
+## But there's more!
+
+- It's important to keep the merkle tree balanced.
+- To avoid attacks, keys are hashed.
+- But if they are hashed
+  - It would be hard to know the original key for a given entry
+- Solution
+  - Hash parts of the key individually.
+  - Include the original value in the key\*.
+
+"0x2e7…847{Balances}83a…231{BOB}"
+
+---v
+
+## Key concepts
+
+<pba-cols>
+<pba-col style="flex-shrink: 0">
+
+- Key
+- Value
+- Hash
+- Merkle value
+
+</pba-col>
+<pba-col>
+<img rounded src="./img/merkle-tree.png" style="width: 100%" />
+</pba-col>
+<pba-cols>
+
+---v
+
+<pba-cols>
+<pba-col style="flex-shrink: 0">
+
+## Can do
+
+- Access a value
+- Subtree differences
+- Get values by subtree
+- Get storage proofs
+
+</pba-col>
+<pba-col>
+
+## Can't do
+
+- Query values
+- Get key from a value
+
+</pba-col>
+<pba-cols>
+
+Notes:
+
+Explain that you can't query for specific values unless they are part of a subtree.
+
+E.g. the votes for a given referendum, as the storage is Votes -> Account -> Referendum
+
+---
+
+# Storage
+
+- followSubscription: string
+- hash: string
+- items: Array
+  - key: string
+  - type
+    - value
+    - hash
+    - closestDescendantMerkleValue
+    - descendantsValues
+    - descendantsHashes
+- childTrie
+
+---v
+
+## Storage
+
+- You can query multiple values.
+- The node might drop some of them.
+
+```ts
+{
+  result: "started",
+  operationId: "…",
+  discardedItems: 5
+}
+```
+
+- Just try later!
+
+---v
+
+## Storage
+
+```ts
+{
+  event: "operationStorageItems",
+  operationId: "…",
+  items: [{
+    key: "0x00…00",
+    value: "0x00…00",
+    hash: "0x00…00",
+    closestDescendantMerkleValue: "0x00…00",
+  }, …]
+}
+
+{
+  event: "operationStorageDone",
+  operationId: "…",
+}
+```
+
+---v
+
+## Storage
+
+```ts
+{
+  event: "operationWaitingForContinue",
+  operationId: "…"
+}
+
+// [followSubscription: string, operationId: string]
+{ jsonrpc: "2.0", id: "1",
+  method: "chainHead_v1_continue",
+  params: ["B4GEopiw1w38Wkr…MxpkWH4JPd4S", "…"]
+}
+```
+
+---
+
+## Light-Client and RFC-0009
+
+[Improved light client requests networking protocol](https://github.com/polkadot-fellows/RFCs/blob/main/text/0009-improved-net-light-client-requests.md)
+
+Notes:
+
+tl;dr; Light Clients currently can't request the hashes, they must download the values. RFC-0009 adds more granularity
+
+- Check whether a key exists in the storage.
+- Check for storage changes between two blocks.
+- Query all descendants without needing round trips.
+
+---
+
+# Challenges
+
+---v
+
+## Correlating messages
+
+- It's not a simple `fetch`.
+- Abstraction to correlate
+  - JSON-RPC message ID
+  - Follow Subscription
+  - Operation ID
+- `@polkadot-api/substrate-client`
+
+---v
+
+## Handling forks
+
+<img rounded src="./img/block-states.png" />
+
+---v
+
+### Operation inaccessible
+
+---v
+
+## Block pinning
+
+---v
+
+## Stop event recovery
diff --git a/content/7-dApps_Off-Chain/5-transactions-slides.md b/content/7-dApps_Off-Chain/5-transactions-slides.md
new file mode 100644
index 00000000..ebac0af6
--- /dev/null
+++ b/content/7-dApps_Off-Chain/5-transactions-slides.md
@@ -0,0 +1,287 @@
+---
+title: JSON-RPC Spec Transactions
+description: Handling transactions with JSON-RPC Spec
+---
+
+# JSON-RPC Spec
+
+## Transactions
+
+---
+
+## Transactions
+
+---
+
+## JSON-RPC Transaction
+
+- transaction_v1_broadcast(tx) -> id
+- transaction_v1_stop(id)
+
+Simple? <!-- .element: class="fragment" --->
+
+Notes:
+
+Not so much
+
+---v
+
+## Challenges
+
+- Creating the transaction
+- Transaction validation
+- Tracking transactions
+- Transaction states
+
+---
+
+# Transactions
+
+---v
+
+## Transaction types
+
+<img rounded src="./img/transactions.svg" />
+
+Notes:
+
+https://excalidraw.com/#json=Mv0Y4f-NgpogwQkoTLHfq,JSVgtIc_-tbxSHfuDbZocA
+
+---v
+
+## Extrinsic V4
+
+#### Signed
+
+[0x84 | Address | Signature | Extra | CallData]
+
+#### Unsigned
+
+[0x04 | CallData]
+
+---v
+
+## Signature
+
+- What is being signed?
+  - Call data
+  - Signed extensions
+
+---v
+
+## Call Data
+
+- The information needed to execute the call.
+- Shape:
+  - First byte: the index of the pallet.
+  - Second byte: the index of the call (inside the pallet).
+  - Remaining bytes: the encoded parameters of the call.
+
+Notes:
+
+Ask what is the shortest amount of bytes that a call can have.
+
+---v
+
+## Signed extensions
+
+- Signed extensions are functions that get executed for all transactions, prior to the execution of the call-data. <!-- .element: class="fragment" --->
+- They play 2 important roles: <!-- .element: class="fragment" --->
+  1. Perform checks to determine whether the transaction is valid. <!-- .element: class="fragment" --->
+  2. Provide transversal logic to the execution of a transaction.<!-- .element: class="fragment" --->
+- Important: the evaluation of the call-data is not taken into account for determining the validity of a transaction.<!-- .element: class="fragment" --->
+- Signed extensions are currently not weighted. Therefore, they must be very cheap to compute.<!-- .element: class="fragment" --->
+
+Notes:
+
+- Example: can a transfer that exceeds the free-balance be a valid transaction? Would that tx be valid?
+
+---v
+
+## Signed extensions - Examples:
+
+<ul>
+<li class="fragment">
+
+`CheckGenesis`: ensures that the transaction belongs to this chain.
+
+</li>
+<li class="fragment">
+
+`CheckSpecVersion`: ensures that the transaction was created for this runtime version.
+
+</li>
+<li class="fragment">
+
+`CheckTxVersion`: ensures that we are using the correct tx version.
+
+</li>
+<li class="fragment">
+
+`CheckMetadataHash`: ensures that the signer device used the correct metadata to display the transaction information to the user/signer.
+
+</li>
+<li class="fragment">
+
+`CheckMortality`: determines the range of blocks in which the transaction can be included into a block.
+
+</li>
+<li class="fragment">
+
+`CheckNonce`: prevents replay attacks.
+
+</li>
+<li class="fragment">
+
+`ChargeTransactionPayment`: Handles the logic for charging the fees for the execution of the transaction, it also sets
+the tip for the validator.
+
+</li>
+</ul>
+
+---v
+
+## Signed Extensions: Extra
+
+- Each signed extensions has 2 different kinds of arguments:<!-- .element: class="fragment" --->
+  - Implicitly known data.<!-- .element: class="fragment" --->
+  - "Extraneous" data, which must be included in the "extra" field (so that the signature can be verified).<!-- .element: class="fragment" --->
+- Examples:<!-- .element: class="fragment" --->
+  - The genesis hash, the spec version, the tx version, etc: is known by the chain.<!-- .element: class="fragment" --->
+  - The "nonce", the "asset", the "tip" are extraneous data. Therefore, it must be included in the "extra" field.<!-- .element: class="fragment" --->
+  - "CheckMortality": the "period" and the "phase" are extraneous, the block hash is implicit data.<!-- .element: class="fragment" --->
+
+Notes: explain how the block has can be derived from the period and the phase, explain how inmortal transactions work.
+
+---
+
+# Transaction States
+
+---v
+
+## Transaction Validation
+
+- The validity of a transaction is determined against a particular block.
+
+  - A transaction could be valid against one block, but invalid against a "sibling fork" of the same height.
+
+- Realistically speaking, there are 3 different kinds of validity states:
+  1. Valid: the transaction can be included into the next block.
+  2. Invalid: the transaction will "never" be able to be included into a block (and thus, not be broadcasted).
+  3. "Future" Valid: the transaction can not yet be included into a block, but it may be included in the future. Ie: nonce
+     too high.
+
+Notes:
+
+- Go through different validation states, what they mean
+- Transactions valid in a future block.
+
+---v
+
+## Transaction Result
+
+- Once a transaction is included in a block, then the call-data has been evaluated and we can know its outcome.
+- A failed transaction is a valid transaction that was included into a block, but did not succeed.
+
+Notes:
+
+- Extrinsic Failed / Extrinsic success
+- Difference between failed vs invalid
+
+---v
+
+## Broadcasting
+
+- Once a transaction is deemed as valid it can be broadcasted.
+- Broadcasting is a "fire and forget" operation. There is no response.
+- Once a transaction is deemed as invalid, we must immediatelly stop broadcasting it.
+
+Notes:
+
+Explain what it means to broadcast - it's not cancellable
+
+---
+
+## Putting it all together
+
+# Transaction Tracking
+
+---v
+
+## Transaction Tracking
+
+<img rounded src="./img/block-states.png" />
+
+---v
+
+## Transaction Life Cycle:
+
+For each transaction:
+
+- Validate beforehand against finalized block.
+- Broadcast if it's valid.
+- Track it inside incoming blocks, until there is a finalized block where the transaction is either:
+  - Included
+  - Invalid
+
+Once we find a block where the transaction is either included or invalid, we consider that the transaction is "settled"
+on that block. Which implies that we don't have to run any checks for its descendant blocks.
+
+---v
+
+## Transaction Tracking:
+
+- For every "new block" event:
+
+  - Is this block the descendant of a "settled block"?
+    - Yes: Ignore.
+    - No: Is the transaction present in the body?
+      - No: Is it valid in this block?
+        - Yes: Ignore.
+        - No: Flag the tx for this block as "settled invalid".
+      - Yes:
+        - Check if the transaction was successful.
+        - Flag the tx for this block as "settled successful/unsuccessful"
+
+---v
+
+## Transaction Tracking:
+
+- For every "finalized" event:
+  - Is this a "settled" block (or the descendant of a "settled" block)?
+    - Yes: Stop broadcasting and report the outcome to the user.
+    - No: Ignore
+
+---v
+
+## JSON-RPC TransactionWatch
+
+<pba-cols>
+<pba-col>
+
+- submitAndWatch(tx) => subId
+- unwatch(subId)
+
+</pba-col>
+<pba-col>
+
+- validated
+- bestChainBlockIncluded
+- finalized
+- error
+- invalid
+- dropped
+
+</pba-col>
+</pba-cols>
+
+---v
+
+## Problem
+
+- TransactionWatch is detached from ChainHead
+- Might receive blocks that
+  - ChainHead hasn't received
+  - ChainHead did receive but now unpinned
+- Useful only to know if it has been included.
+- But can't get any other info: events, storage, etc.
diff --git a/content/7-dApps_Off-Chain/6-polkadot-api-slides.md b/content/7-dApps_Off-Chain/6-polkadot-api-slides.md
new file mode 100644
index 00000000..227ee744
--- /dev/null
+++ b/content/7-dApps_Off-Chain/6-polkadot-api-slides.md
@@ -0,0 +1,1191 @@
+---
+title: Polkadot-API
+description: Polkadot-API in depth
+---
+
+# Polkadot-API
+
+<span style="color: lightgray; font-size: 0.8em;">(aka PAPI)</span>
+
+Notes:
+
+So far we've seen the low-level details for interacting with a chain. Now we'll go a higher level of abstraction and see how Polkadot-API, in specific, solves those challenges, and what other features it adds.
+
+---
+
+## PAPI principles
+
+- Light-client first
+- Modular
+- Light weight
+- Composable
+- Simplify dApp development
+
+---v
+
+### Packages
+
+<img rounded src="./img/papi-packages.png" />
+
+Notes:
+
+https://excalidraw.com/#json=MlLv0U2YI3nfTZwEkRTf1,iaAmM8qLSSYKNFkoJtlNsA
+
+Warn that observable-client is opinionated and unstable, it's an implementational detail of papi. The other packages are unopinionated or at least stable.
+
+---v
+
+### Polkadot-API
+
+- Top-level package
+- Main use case: dApps
+- Chain-agnostic
+- Query or subscribe to chain state
+- Send and track transactions
+
+---v
+
+### Polkadot-API
+
+```ts
+import { dot } from "@polkadot-api/descriptors";
+import { createClient } from "polkadot-api";
+import { getWsProvider } from "polkadot-api/ws-provider/web";
+
+const client = createClient(getWsProvider("ws://…"));
+const typedApi = client.getTypedApi(dot);
+
+const ACCOUNT_ID = "15oF4uVJwmo4TdGW7VfQxNLavjCXviqxT9S1MgbjMNHr6Sp5";
+const account = await typedApi.query.System.Account.getValue(ACCOUNT_ID);
+```
+
+---v
+
+### CLI
+
+- Codegen
+- Generate TS types for chains
+- Part of Compatibility API
+
+---v
+
+### Metadata Builders
+
+- Codecs from metadata
+  - Lookup
+  - Storage
+  - Runtime APIs
+  - Transactions
+  - Events
+
+---v
+
+### Metadata Builders
+
+```ts
+import {
+  getDynamicBuilder,
+  getLookupFn,
+} from "@polkadot-api/metadata-builders";
+
+const metadata = getMetadataFromSource();
+const lookup = getLookupFn(metadata);
+const dynamicBuilder = getDynamicBuilder(lookup);
+
+const { keys, value, fallback } = dynamicBuilder.buildStorage(
+  "Pallet",
+  "Entry",
+);
+
+const { codec, location } = dynamicBuilder.buildCall("Pallet", "Name");
+
+const { args, value } = dynamicBuilder.buildRuntimeCall("Api", "Method");
+
+const codec = dynamicBuilder.buildDefinition(134);
+```
+
+---v
+
+### Observable Client
+
+- Internal detail
+- Block pinning
+- Subscriptions
+
+---v
+
+### Observable Client
+
+<!-- prettier-ignore -->
+```ts [|6|8-9|13-15|16-17|19-20]
+import { getObservableClient } from "@polkadot-api/observable-client";
+import { getWsProvider } from "@polkadot-api/ws-provider/web";
+import { createClient } from "@polkadot-api/substrate-client";
+import { firstValueFrom } from "rxjs";
+
+const client = getObservableClient(createClient(getWsProvider("ws://…")));
+
+const chainHead = client.chainHead$();
+const finalized = await firstValueFrom(chainHead.finalized$);
+
+const ACCOUNT_ID = "15oF4uVJwmo4TdGW7VfQxNLavjCXviqxT9S1MgbjMNHr6Sp5";
+const account = await firstValueFrom(
+  chainHead.storage$(
+    finalized.hash,
+    "value",
+    ctx =>
+      ctx.dynamicBuilder.buildStorage("System", "Account").keys.enc(ACCOUNT_ID),
+    null,
+    (data, ctx) => data &&
+      ctx.dynamicBuilder.buildStorage("System", "Account").value.dec(data)
+  )
+);
+```
+
+---v
+
+### Substrate Bindings
+
+- Known codecs for Substrate
+  - SS58 Format
+  - Block header
+  - Metadata v14
+  - Metadata v15
+- Other known utilities
+  - Storage hashers
+  - Multisig account
+
+---v
+
+### Substrate Client
+
+- JSON-RPC Spec
+- TS Interface
+- Correlations
+  - Message IDs
+  - Subscription IDs
+  - Operation IDs
+
+---v
+
+### Substrate Client
+
+<!-- prettier-ignore -->
+```ts [|4|6-7|8-18|20-24]
+import { getWsProvider } from "@polkadot-api/ws-provider/web";
+import { createClient } from "@polkadot-api/substrate-client";
+
+const client = createClient(getWsProvider("ws://…"));
+
+const chainHead = client.chainHead(
+  true,
+  async followEvt => {
+    if (followEvt.type === "initialized") {
+      const finalized = followEvt.finalizedBlockHashes.at(-1)!;
+
+      const result = await chainHead.storage(
+        finalized,
+        "value",
+        "0x{storage key}",
+        null,
+      );
+      console.log("SCALE result: " + result);
+
+      chainHead.unpin(followEvt.finalizedBlockHashes);
+    }
+    if (followEvt.type === "newBlock") {
+      chainHead.unpin([followEvt.blockHash]);
+    }
+  },
+  console.error
+);
+```
+
+---v
+
+### JSON-RPC Providers
+
+```ts
+type JsonRpcProvider = (onMessage: MessageCallback) => JsonRpcConnection;
+
+type MessageCallback = (message: string) => void;
+
+interface JsonRpcConnection {
+  send: (message: string) => void;
+  disconnect: () => void;
+}
+```
+
+---v
+
+### JSON-RPC Providers
+
+Create a `withLogsRecorder`
+
+```ts
+export function withLogsRecorder(
+  persistLog: (msg: string) => void,
+  // Provider wrapped
+  provider: JsonRpcProvider,
+): JsonRpcProvider {
+  // TODO
+}
+```
+
+---
+
+## Subscriptions
+
+---v
+
+### Pull vs Push
+
+<pba-cols style="font-size: 0.8em">
+<pba-col>
+
+<!-- prettier-ignore -->
+```ts
+let lastValue = null;
+while (keepWatching) {
+  const value = await typedApi
+    .query.System.Account
+    .getValue(ACCOUNT_ID);
+
+  if (value !== lastValue) {
+    console.log("new value", value);
+  }
+  lastValue = value;
+
+  await waitMs(1000);
+}
+```
+
+</pba-col>
+<pba-col>
+
+<!-- prettier-ignore -->
+```ts
+typedApi
+  .query.System.Account
+  .watchValue(ACCOUNT_ID)
+  .subscribe(value => {
+    console.log("new value", value);
+  })
+```
+
+</pba-col>
+</pba-cols>
+
+---v
+
+<pba-cols style="font-size: 0.8em">
+<pba-col>
+
+### Pull
+
+Consumer decides when to get the value
+
+</pba-col>
+<pba-col>
+
+### Push
+
+Producer notifies of new changes
+
+</pba-col>
+</pba-cols>
+
+---v
+
+### JSON-RPC Spec
+
+- ChainHead Events: <span class="fragment">Push-based</span>
+- Operations: <span class="fragment">Push/pull?</span>
+  - Low-level: Push <!-- .element: class="fragment" --->
+  - High-level: Pull <!-- .element: class="fragment" --->
+  - Higher-level: Push 🤯 <!-- .element: class="fragment" --->
+
+Notes:
+
+Events (new block, finalized, etc) are push-based, the node notifies us when a new block is produced
+Operations depend on the level we're looking at.
+
+---v
+
+### Working Async
+
+- Push is asynchronous
+- Pull can be sync or async
+- Ancient JS (2014-) used callbacks for async code
+
+```ts
+// Ancient JS Pull
+api.query.System.Account.getValue(ACCOUNT_ID, (error, result) => {
+  if (error) {
+    return console.error("oh no!");
+  }
+  console.log("Result", result);
+});
+
+// Ancient JS Push
+api.query.System.Account.watchValue(
+  ACCOUNT_ID,
+  value => {
+    console.log("Value", value);
+  },
+  error => console.error("oh no!"),
+);
+```
+
+Notes:
+
+In our context, pull is async. If you need the storage, you have to make a request to the node to pull it out for you.
+
+---v
+
+### Enter Promises 🌈
+
+- Technically still using callbacks.
+- Common interface, allows composability.
+- Removes "callback hell"
+- 2017+ enhanced language: async/await
+- Works great for pull operations: fetch
+
+---v
+
+### And for push?
+
+😞 <!-- .element: class="fragment" --->
+
+<div class="fragment">
+
+Async generators?
+
+```ts
+// async generator API
+const account = api.query.System.Account.watchValue(ACCOUNT_ID);
+
+for await (const value of account) {
+  console.log(value);
+}
+```
+
+But that's pull!
+
+</div>
+
+---v
+
+### Enter Observables 🌈
+
+- Promise but for multiple values
+- Common interface, composable
+- Removes "callback hell"
+- Convertible to promises
+- TC-39 Stage 1 <span style="color: darkgray" class="fragment">(big copium)</span>
+- Meanwhile rxjs <!-- .element: class="fragment" -->
+
+---v
+
+### Observables 101
+
+```ts
+import { Observable } from "rxjs";
+
+// Emit one value every second up to 10
+const observable$ = new Observable<number>(subscriber => {
+  let v = 0;
+
+  const token = setInterval(() => {
+    const valueToEmit = v;
+    v++;
+    subscriber.next(valueToEmit);
+    if (valueToEmit === 10) {
+      subscriber.complete();
+    }
+  }, 1000);
+
+  return () => clearInterval(token);
+});
+```
+
+---v
+
+### Observables 101
+
+```ts
+observable$.subscribe(value => {
+  console.log(value);
+});
+
+observable$.subscribe({
+  next: value => console.log(value),
+  error: error => console.error(error),
+  complete: () => console.log("completed"),
+});
+```
+
+Notes:
+
+Showcase / demo how observables are cold by default
+
+---v
+
+### Composing Observables
+
+Operator: `(source: Observable<T>) => Observable<R>`
+
+```ts
+const map = <T, R>(mapFn: (value: T) => R) => (source: Observable<T>) =>
+  new Observable<R>(subscriber => {
+    const subscription = source.subscribe({
+      next: v => subscriber.next(mapFn(v)),
+      error: e => subscriber.error(e),
+      complete: () => subscriber.complete(),
+    });
+
+    return subscription;
+  });
+
+const multipliedBy2$ = observable$.pipe(map(v => v * 2));
+// Same as map(v => v * 2)(multipliedBy2$)
+```
+
+---v
+
+### Composing Observables
+
+Pipe-ing
+
+```ts
+import { interval, map, take } from "rxjs";
+
+// Create an observable of the first 10 even numbers, one second at a time.
+const even$ = interval(1000).pipe(
+  map(v => v * 2),
+  take(10),
+);
+```
+
+---v
+
+### Combining Observables
+
+- `combineLatest`, `merge`, `switchMap`, etc.
+- Endless list: https://rxjs.dev/guide/operators#creation-operators-1
+- Good resource: https://www.learnrxjs.io/learn-rxjs/operators
+
+---v
+
+### Combining Observables
+
+switchMap
+
+```ts
+const switchMap =
+  <T, R>(mapFn: (value: T) => Observable<R>) => (source: Observable<T>) =>
+    new Observable<R>(subscriber => {
+      // TODO
+
+      const subscription = source.subscribe({
+        next: v => {
+          const innerObservable = mapFn(v);
+
+          // TODO
+        },
+        error: e => subscriber.error(e),
+        complete: () => subscriber.complete(),
+      });
+
+      return () => {
+        // TODO
+      };
+    });
+
+const bounty$ = selectedBountyId$.pipe(
+  switchMap(id => {
+    return from(typedApi.query.Bounties.Bounty.getValue(id));
+  }),
+);
+```
+
+---v
+
+### Observable ↔ Promise
+
+```ts
+import { defer, firstValueFrom, from, lastValueFrom } from "rxjs";
+const firstValue = await firstValueFrom(observable$);
+const lastValue = await lastValueFrom(observable$);
+
+const observable$ = from(fetch("…"));
+const observable$ = defer(() => fetch("…"));
+```
+
+Notes:
+
+It's important to keep in mind what these functions do: both firstValueFrom and lastValueFrom subscribe to the observable, and then unsubscribe.
+
+Difference between from and defer.
+
+---v
+
+### Polkadot Chains
+
+- Pull
+  - Constants (metadata)
+  - Runtime APIs
+  - Storage query
+- Push
+  - Blocks
+  - Storage watch
+  - Transactions
+
+Notes:
+
+Pull operations: Easier to offer promises
+Push: Observables all the way.
+
+- Blocks: finalized$
+
+Why transactions are "push"?
+
+---v
+
+### Combining streams
+
+Exercise: Find the referenda where a specific account voted in the same direction as the current outcome.
+
+- Account: 1jbZxCFeNMRgVRfggkknf8sTWzrVKbzLvRuLWvSyg9bByRG
+- Track: 33
+
+Hints:
+
+- `query.ConvictionVoting.VotingFor.watchValue(account, track)`
+- `query.Referenda.ReferendumInfoFor.getValues([number][])`
+
+Notes:
+
+- Don't count delegations.
+- Don't count split votes or abstains.
+
+TODO Maybe find a better example. This one is interesting, but it's a shame it would need to do `watchValue[]` and that just adds boilerplate. Also, not a huge fan of the nesting and the hacks around conviction voting. Plus having to share the account which is just a random string…
+
+```ts
+const getDirectVotes = (voting: ConvictionVotingVoteVoting) => {
+  if (voting.type === "Delegating") return [];
+
+  return voting.value.votes
+    .map(([id, vote]) => {
+      if ("vote" in vote.value) {
+        const direction = vote.value.vote & 0x80 ? "aye" : "nay";
+        return { id, direction };
+      }
+      return null;
+    })
+    .filter(v => v !== null);
+};
+
+dotApi.query.ConvictionVoting.VotingFor.watchValue(
+  "1jbZxCFeNMRgVRfggkknf8sTWzrVKbzLvRuLWvSyg9bByRG",
+  33,
+)
+  .pipe(
+    map(getDirectVotes),
+    switchMap(async voting => {
+      const referenda = await dotApi.query.Referenda.ReferendumInfoFor
+        .getValues(voting.map(v => [v.id]));
+
+      return referenda
+        .filter(v => v != null)
+        .filter((referendum, i) => {
+          const { direction } = voting[i];
+          if (referendum.type !== "Ongoing") {
+            return (direction === "aye" && referendum.type === "Approved")
+              || direction === "nay";
+          }
+          const referendumDirection =
+            referendum.value.tally.ayes > referendum.value.tally.nays
+              ? "aye"
+              : "nay";
+          return direction === referendumDirection;
+        })
+        .map((v, i) => ({
+          ...v,
+          id: voting[i].id,
+        }));
+    }),
+  )
+  .subscribe(r => {
+    console.log(r);
+  });
+```
+
+---v
+
+### Watch Entries
+
+<img rounded src="./img/block-states.png" />
+
+`Observable<Array<[Key, Value]>>?` <!-- .element: class="fragment" -->
+
+Notes:
+
+Remind issue with multiple forks
+
+When watching entries, we might have a large list. When providing an Observable API it's important to note what has changed in specific.
+
+Also, it's expensive, and it might skip some blocks.
+
+---v
+
+### Watch Entries
+
+```ts
+watchEntries().subscribe(result => {
+  // Hash + number + parent
+  console.log(result.blockInfo);
+  // Array<{ args: Key, value: Value }>
+  console.log("deleted", result.deltas.deleted);
+  console.log("upserted", result.deltas.upserted);
+  // Array<{ args: Key, value: Value }>
+  console.log("values", result.values);
+});
+```
+
+Notes:
+
+Exercise - change the previous implementation to watch referenda from any track.
+
+---
+
+## Compatibility API
+
+- Chain interactions are defined in the metadata.
+- The metadata shows the "API" of the runtime.
+- But the runtime is upgradeable!
+- How to approach this?
+
+---v
+
+### Solution #1
+
+- #YOLO #BreakEverything
+- Offer types for interactions
+- If the chain doesn't support it when running, too bad!
+- Polkadot-API: `client.getUnsafeApi()`
+- Polkadot-JS + Type Registry
+
+---v
+
+### Solution #2
+
+- Get a unique value for each interaction
+- Checksum based on the type for the interaction
+- If the checksum changes, then the interaction is not compatible
+
+---v
+
+### Solution #2
+
+<pba-cols style="font-size: 0.8em">
+<pba-col>
+
+```ts
+Referenda.submit({
+  proposal_origin: Enum {
+    BigSpender,
+    MediumSpender,
+    SmallSpender,
+    WishForChange
+  },
+  proposal: Enum {
+    Inline(Binary),
+    Lookup(Binary, number)
+  },
+  enactment_moment: Enum {
+    After(number),
+    At(number)
+  }
+})
+```
+
+</pba-col>
+<pba-col>
+
+```ts
+hash(str) := str // For demo purposes
+Checksum(void) := hash("0")
+Checksum(number) := hash("1")
+Checksum(Binary) := hash("2")
+Checksum((a,b)) := hash("3(" +
+  ChkS(a) + ChkS(b) + ")")
+
+Checksum(Enum) := hash("4(" +
+  forEach variant {
+    name + Checksum(type)
+  } + ")"
+)
+
+Checksum(Struct) := hash("5(" +
+  forEach property {
+    name + Checksum(type)
+  } + ")"
+)
+```
+
+</pba-col>
+</pba-cols>
+
+```ts
+Checksum(proposal_origin) =
+  "4(BigSpender0MediumSpender0Sma…ender0WishForChange0)";
+Checksum((Binary, number)) = "3(21)";
+Checksum(proposal) = "4(Inline2Lookup3(21))";
+Checksum(enactment_moment) = "4(After1At1)";
+Checksum(Referenda.submit) =
+  "5(proposal_origin4(BigSpend…Change0)proposal4(Inline2Lookup3(21))enactm…r1At1))";
+```
+
+---v
+
+### Solution #2
+
+- Checksum changes if anything changes at all
+- `polkadot-api@0.10.0`
+- Problem: Cases where changes should not affect it
+
+---v
+
+### Solution #3
+
+<pba-cols>
+
+<pba-col>
+
+```ts [7]
+Referenda.submit({
+  proposal_origin: Enum {
+    BigSpender,
+    MediumSpender,
+    SmallSpender,
+    WishForChange,
+    CouncilElection
+  },
+  proposal: Enum {
+    Inline(Binary),
+    Lookup(Binary, number)
+  },
+  enactment_moment: Enum {
+    After(number),
+    At(number)
+  }
+})
+```
+
+</pba-col>
+
+<pba-co class="fragment">
+
+- Bundle type definitions
+- Compare metadata types on runtime
+
+</pba-col>
+
+</pba-cols>
+
+Notes:
+
+For instance, how can we do it so that adding a new variant for an enum still makes it compatible?
+
+---v
+
+### Solution #3
+
+- There's more!
+- We can compare based on the actual value
+- Compatibility levels
+  - Identical
+  - Backwards compatible
+  - Partial
+  - Incompatible
+- Different between "in" and "out"
+
+---v
+
+### Solution #3
+
+<table>
+  <thead>
+    <tr>
+      <th>Change</th>
+      <th>Sending</th>
+      <th>Receiving</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>Add a property to a struct</td>
+      <td class="fragment" data-fragment-index="0"><span style="color: #fc8d62">Incompatible</span></td>
+      <td class="fragment" data-fragment-index="0"><span style="color: #80dbde">Backwards compatible</span></td>
+    </tr>
+    <tr>
+      <td>Add an <b>optional</b> property to a struct</td>
+      <td class="fragment" data-fragment-index="1"><span style="color: #80dbde">Backwards compatible</span></td>
+      <td class="fragment" data-fragment-index="1"><span style="color: #80dbde">Backwards compatible</span></td>
+    </tr>
+    <tr>
+      <td>Remove a property from a struct</td>
+      <td class="fragment" data-fragment-index="2"><span style="color: #80dbde">Backwards compatible</span></td>
+      <td class="fragment" data-fragment-index="2"><span style="color: #fc8d62">Incompatible</span></td>
+    </tr>
+    <tr>
+      <td>Make an optional property mandatory</td>
+      <td class="fragment" data-fragment-index="3"><span style="color: #8da0cb">Partial</span></td>
+      <td class="fragment" data-fragment-index="3"><span style="color: #80dbde">Backwards compatible</span></td>
+    </tr>
+    <tr>
+      <td>Add a variant to an Enum</td>
+      <td class="fragment" data-fragment-index="4"><span style="color: #80dbde">Backwards compatible</span></td>
+      <td class="fragment" data-fragment-index="4"><span style="color: #8da0cb">Partial</span></td>
+    </tr>
+    <tr>
+      <td>Remove a variant from an Enum</td>
+      <td class="fragment" data-fragment-index="5"><span style="color: #8da0cb">Partial</span></td>
+      <td class="fragment" data-fragment-index="5"><span style="color: #80dbde">Backwards compatible</span></td>
+    </tr>
+    <tr>
+      <td>Change the type of an optional property</td>
+      <td class="fragment" data-fragment-index="6"><span style="color: #8da0cb">Partial</span></td>
+      <td class="fragment" data-fragment-index="6"><span style="color: #8da0cb">Partial</span></td>
+    </tr>
+    <tr>
+      <td>Change a u8 to a u128</td>
+      <td class="fragment" data-fragment-index="7"><span style="color: #fc8d62">Incompatible</span></td>
+      <td class="fragment" data-fragment-index="7"><span style="color: #fc8d62">Incompatible</span></td>
+    </tr>
+  </tbody>
+</table>
+
+---v
+
+## Practice: Runtime Upgrade 🚀
+
+---
+
+## Descriptors
+
+```ts
+import { dot } from "@polkadot-api/descriptors";
+
+// ...
+
+const dotApi = client.getTypedApi(dot);
+
+const account = await dotApi.query.System.Account.getValue(ALICE);
+```
+
+---v
+
+## Descriptors
+
+- Typescript definitions
+
+```ts
+function api.query.System.Account(id: AccountID): Promise<{
+  nonce: number,
+  data: {
+    free: bigint,
+    reserved: bigint,
+    frozen: bigint
+  }
+}>
+```
+
+- Metadata types
+  - ~500 KB SCALE per each chain
+  - ~1.5 MB JSON
+  - React/Vue: less than 140 KB
+  - How to bundle efficiently?
+
+---v
+
+### Opportunities
+
+1. Lazy-loading
+2. Reduce information
+3. Whitelisting
+4. Common types
+
+---v
+
+### Lazy Loading
+
+- Let the dApp render first
+- Load descriptors in the background
+
+```ts
+// Static import
+import metadata from "./metadata";
+
+// Dynamic import
+const metadataPromise = import("./metadata");
+```
+
+Notes:
+
+Challenges when dealing with promises.
+
+---v
+
+### Lazy Loading
+
+```ts
+import { dot } from "@polkadot-api/descriptors";
+
+// ...
+
+const dotApi = client.getTypedApi(dot);
+
+const account = await dotApi.query.System.Account.getValue(ALICE);
+```
+
+Notes:
+
+How can we let dev start interacting without having to first "await" the descriptors?
+
+---v
+
+### Reduce Information
+
+- Metadata is massive
+- We're only interested in data (lookup)
+- Some types can also be merged (u8, u16, u32, …)
+
+<img rounded src="./img/descriptors.png" />
+
+Notes:
+
+Checksum can be used to deduplicate types
+
+https://excalidraw.com/#json=6r98ZeK6wQ0dsmSon8Lon,ybCarw4wIswxi3Hin5ArlQ
+
+---v
+
+### Whitelisting
+
+- dApps don't use the full list of interactions
+- We can offer API to reduce bundle sizes
+
+Notes:
+
+Explain current solution, possible alternative solutions (vite plugin, import-based, etc.)
+
+---v
+
+### Common types
+
+- Multichain dApps
+- Runtimes are very similar
+- Combine all into one
+
+Notes:
+
+Tradeoff for dApps that are multichain but one at a time.
+
+---
+
+## Signers
+
+---v
+
+## Signers
+
+- Polkadot-API creates a transaction
+- Who signs it? We need a private key!
+- Modular generic interface
+
+---v
+
+### Signers
+
+```ts [|2|4|6-19]
+interface PolkadotSigner {
+  publicKey: Uint8Array;
+
+  signBytes(data: Uint8Array): Promise<Uint8Array>;
+
+  signTx(
+    callData: Uint8Array,
+    signedExtensions: Record<
+      string,
+      {
+        identifier: string;
+        value: Uint8Array;
+        additionalSigned: Uint8Array;
+      }
+    >,
+    metadata: Uint8Array,
+    atBlockNumber: number,
+    hasher: (data: Uint8Array) => Uint8Array,
+  ): Promise<Uint8Array>;
+}
+```
+
+Notes:
+
+Explain broadly the interface
+
+---v
+
+### Polkadot Signer
+
+```ts
+// polkadot-api/signer
+function getPolkadotSigner(
+  publicKey: Uint8Array,
+  signingType: "Ecdsa" | "Ed25519" | "Sr25519",
+  sign: (input: Uint8Array) => Promise<Uint8Array> | Uint8Array,
+): PolkadotSigner;
+```
+
+Notes:
+
+This is the basic signer. I have a function that can sign stuff, give me a polkadot signer that deals with signed extensions, etc.
+
+---v
+
+### Polkadot Signer
+
+```ts
+import { sr25519CreateDerive } from "@polkadot-labs/hdkd";
+import {
+  entropyToMiniSecret,
+  mnemonicToEntropy,
+} from "@polkadot-labs/hdkd-helpers";
+import { getPolkadotSigner } from "polkadot-api/signer";
+
+const alice_mnemonic =
+  "bottom drive obey lake curtain smoke basket hold race lonely fit walk";
+const entropy = mnemonicToEntropy(alice_mnemonic);
+const miniSecret = entropyToMiniSecret(entropy);
+const derive = sr25519CreateDerive(miniSecret);
+const alice = derive("//Alice");
+
+const aliceSigner = getPolkadotSigner(alice.publicKey, "Sr25519", alice.sign);
+```
+
+Notes:
+
+I have a private key from a mnemonic, how do I sign with PAPI?
+
+You don't. Modular design: you use whatever library can sign data, and use `getPolkadotSigner` to do what PAPI knows to do.
+
+---v
+
+### Polkadot-JS Signer
+
+<!-- prettier-ignore -->
+```ts
+import {
+  connectInjectedExtension,
+  getInjectedExtensions
+} from "polkadot-api/pjs-signer";
+
+const extensions = await getInjectedExtensions();
+const extension = await connectInjectedExtension(extensions[0]);
+const accounts = extension.getAccounts();
+
+console.log(accounts[0].address);
+const signer = accounts[0].polkadotSigner;
+```
+
+Notes:
+
+To get a signer from a PJs-based extension
+
+---v
+
+### Meta signers
+
+<img src="./img/meta-signer.svg" />
+
+Notes:
+
+The signer interface is composable: Write a signer that uses another signer
+
+Examples: Multisig, Proxy
+
+Exercise: Implement proxy signer, hands-on.
+
+---
+
+<img style="width: 300px" src="../../assets/img/0-Shared/logo/ink-white.png" />
+
+---v
+
+### ink!
+
+- Smart contracts in Polkadot
+- Implemented in Rust
+- Exports WASM + Metadata
+
+---v
+
+### ink!
+
+- Constructor
+  - Function to deploy a contract
+- Message
+  - Perform an operation, or query info.
+- Events
+- Storage
+
+---v
+
+### Endpoints
+
+- Runtime API: Dry-run
+- Transaction: Perform some change
+
+---v
+
+### ink! + PAPI
+
+```ts
+// pnpm papi ink add metadata.json
+
+import { contracts } from "@polkadot-api/descriptors";
+
+const inkClient = getInkClient(contracts.psp22);
+```
+
+Notes: At this level, PAPI inkClient only gives TS definitions for encoding/decoding messages
+
+---v
+
+### ink! + PAPI
+
+```ts
+// Takes in the message name
+const increaseAllowance = inkClient.message("PSP22::increase_allowance");
+
+// Encode the data for that message
+const messageData = increaseAllowance.encode({
+  delta_value: 100_000_000n,
+  spender: ADDRESS.bob,
+});
+
+const response = await typedApi.apis.ContractsApi.call(
+  ADDRESS.alice, // Origin
+  ADDRESS.psp22, // Contract address
+  0n, // Value
+  undefined, // GasLimit
+  undefined, // StorageDepositLimit
+  messageData,
+);
+```
+
+Notes:
+
+Exercise interact with a chain
diff --git a/content/7-dApps_Off-Chain/7-papi-sdks-slides.md b/content/7-dApps_Off-Chain/7-papi-sdks-slides.md
new file mode 100644
index 00000000..6141582a
--- /dev/null
+++ b/content/7-dApps_Off-Chain/7-papi-sdks-slides.md
@@ -0,0 +1,147 @@
+---
+title: PAPI SDKs
+description: TODO
+duration: 4 hours
+owner: Carlo Sala
+---
+
+# Polkadot-API SDKs
+
+---
+
+## PAPI SDKs
+
+#### Content
+
+- Motivation
+- Goals
+- An example: Governance
+
+---
+
+## PAPI SDKs
+
+#### Motivation
+
+- PAPI is agnostic to the runtime (_aka_ business logic).
+- PAPI SDKs fill the gap for common dApp needs.
+- Avoid reinventing the wheel.
+
+---
+
+## PAPI SDKs
+
+#### Methodology
+
+1. `createXXXSdk(typedApi)`. It defines the expected TS types for descriptors in order to work.
+2. Make incremental releases. Instead of starting with a big API, improve it during the development.
+3. Listen the community.
+
+---
+
+## PAPI SDKs
+
+#### Goals
+
+- Simplify dApp development.
+- Let the dApp developer add value instead of reimplementing the same common logic.
+- Track and adapt to pallet upgrades in advance to ensure seamless transitions.
+- Keep it atomic to avoid and avoid bloated APIs.
+
+---
+
+## PAPI SDKs
+
+#### Governance
+
+- We want to abstract as much as possible the interaction with the chain.
+- We discovered ~~_3.5_~~ 4 main groups of functionality:
+  - Referenda
+  - ConvictionVoting
+  - Bounties / ChildBounties
+
+---
+
+#### Governance - Referenda
+
+**Which problems were identified?**
+
+- State is split among different storage and constant entries; e.g. `Referenda.ReferendumInfoFor`, `Referenda.Tracks`. They
+  have to be matched and combined to get the full picture.
+- There are parts of the state that do not directly appear in the chain state (e.g. when a poll is expected to end) and
+  require some extra computation.
+
+---
+
+#### Governance - Referenda
+
+**What do we want to include in the SDK?**
+
+- Fetch referenda and get information about them (abstract storage) <!-- .element: class="fragment" -->
+  - With extra info. E.g. when is a poll expected to end, resolve preimage, decode call, etc
+- Create referenda <!-- .element: class="fragment" -->
+  - Figure out the track where a referendum should go <!-- .element: class="fragment" -->
+  - Abstract preimages <!-- .element: class="fragment" -->
+
+---
+
+#### Governance - Referenda
+
+**What we do NOT want to include in the SDK?**
+
+- Interactions where we cannot improve the API / add value.
+
+  - E.g. `Referenda.place_decision_deposit(index: u32)`. We cannot add value ==> we do not add the API.
+
+    <span style="font-size: 0.6em; opacity: 0.6">(We are still discussing if this is the best behaviour, take it with a pinch of salt.)</span>
+
+---
+
+#### Governance - ConvictionVoting
+
+**Which problems were identified?**
+
+- Again, state is split among several entries. Besides that, every voting track goes on its own.
+- `Vote` type
+- Derived state: which votes can be removed, and when.
+
+---
+
+#### Governance - ConvictionVoting
+
+**Features:**
+
+- Get votes and delegations for an account. <!-- .element: class="fragment" -->
+  - With enhanced information; e.g. unlock schedule of all votes.
+- Vote <!-- .element: class="fragment" -->
+  - Abstract complex `Vote` type and conviction.
+
+---
+
+#### Governance - Bounties (and ChildBounties)
+
+**Which problems were identified?**
+
+- A bounty can be in a gazillion different states. <!-- .element: class="fragment" -->
+
+---v
+
+![Image](./img/bounties.svg)
+
+---
+
+#### Governance - Bounties (and ChildBounties)
+
+**Which problems were identified?**
+
+- A bounty can be in a gazillion different states.
+- There are many actions to bounties that are performed through referenda. <!-- .element: class="fragment" -->
+
+---
+
+#### Governance - Bounties (and ChildBounties)
+
+**Features:**
+
+- Abstract state of bounties (or child bounties), and expose only relevant actions to the state. <!-- .element: class="fragment" -->
+- Find referenda that change the state of the bounty. <!-- .element: class="fragment" -->
diff --git a/content/7-dApps_Off-Chain/img/block-states.png b/content/7-dApps_Off-Chain/img/block-states.png
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index 00000000..00a791d4
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diff --git a/content/7-dApps_Off-Chain/img/bounties.svg b/content/7-dApps_Off-Chain/img/bounties.svg
new file mode 100644
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--- /dev/null
+++ b/content/7-dApps_Off-Chain/img/bounties.svg
@@ -0,0 +1,2 @@
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new file mode 100644
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diff --git a/content/7-dApps_Off-Chain/img/merkle-tree.png b/content/7-dApps_Off-Chain/img/merkle-tree.png
new file mode 100644
index 00000000..2722a280
Binary files /dev/null and b/content/7-dApps_Off-Chain/img/merkle-tree.png differ
diff --git a/content/7-dApps_Off-Chain/img/meta-signer.svg b/content/7-dApps_Off-Chain/img/meta-signer.svg
new file mode 100644
index 00000000..b6712108
--- /dev/null
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diff --git a/content/7-dApps_Off-Chain/img/polkadot-js-dep-tree.png b/content/7-dApps_Off-Chain/img/polkadot-js-dep-tree.png
new file mode 100644
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diff --git a/content/7-dApps_Off-Chain/img/sign-payload.svg b/content/7-dApps_Off-Chain/img/sign-payload.svg
new file mode 100644
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new file mode 100644
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diff --git a/content/7-dApps_Off-Chain/index.md b/content/7-dApps_Off-Chain/index.md
new file mode 100644
index 00000000..e60490f3
--- /dev/null
+++ b/content/7-dApps_Off-Chain/index.md
@@ -0,0 +1 @@
+# dApps track (Polkadot Hub)
diff --git a/content/8-Governance/Presentation-slides.md b/content/8-Governance/Presentation-slides.md
new file mode 100644
index 00000000..9eb7a388
--- /dev/null
+++ b/content/8-Governance/Presentation-slides.md
@@ -0,0 +1,14 @@
+---
+title: Module 5 - Governance
+description: Governance slides link
+---
+
+# Module Governance
+
+<p>All presentations can be found at the links below:</p>
+<p><a href="https://github.com/Polkadot-Blockchain-Academy/pba-content/blob/main/assets/Gov_PBA6_Lucerne_2025.pdf" target="_blank">PDF format</a></p>
+
+# Polkadot OpenGov
+
+<p>All presentations can be found at the links below:</p>
+<p><a href="https://github.com/Polkadot-Blockchain-Academy/pba-content/blob/main/assets/opengov_pba_lucerne_2025_fin.pdf" target="_blank">PDF format</a></p>
diff --git a/content/8-Governance/README.md b/content/8-Governance/README.md
new file mode 100644
index 00000000..382bf82f
--- /dev/null
+++ b/content/8-Governance/README.md
@@ -0,0 +1,89 @@
+# Module: 8 Governance
+
+The Governance Module aims to equip blockchain developers and founders with the necessary competences to build effective governance systems and navigate their complex political, legal, regulatory, and ethical implications.
+
+#### Prerequisites:
+
+## Learning Outcomes
+
+● Governance Literacy: To provide participants with a comprehensive understanding of various governance frameworks and their relevance to blockchain initiatives, fostering an ability to critically assess and apply these frameworks effectively.
+
+● Regulatory Awareness: Teach participants to adeptly navigate the intricate political, regulatory, and legal landscapes that impact the deployment and operation of blockchain governance structures, preparing them for proactive compliance and strategic planning.
+
+● Governance Design: To enable learners to design and implement effective and adaptable governance systems for their blockchain projects by bridging the gap between theoretical knowledge and practical application.
+
+● Stakeholder Engagement: Focus on strategies for effective stakeholder engagement, emphasizing the importance of building and nurturing a strong, inclusive, and collaborative community as a cornerstone of successful blockchain governance.
+
+● Governance Experimentation: Encourage participants to explore and innovate within the realm of blockchain governance, fostering a culture of continuous improvement and adaptation to emerging challenges and opportunities.
+
+● Talent Pipeline: Support the development of a robust pipeline of skilled professionals who are not only versed in the technical aspects of blockchain but also adept at the complex decision-making and ethical considerations required in effective governance.
+
+## Hands on activities
+
+● Challenge-Based Prototyping & Interactive Workshop
+● Solving Governance Challenges from the Ecosystem provided by experts
+
+## Schedule
+
+## Day 1 (Foundation Module)
+
+### Morning
+
+1. Kick-Off / Presentation & Sharing Circle (1 hour) (Together)
+   a. Introduction to module and faculty
+   b. Student sharing experiences with governance
+
+2. Blockchain Governance in Theory / Lecture & Case Studies (3 hours) (Primavera)
+   a. Governance in general
+   b. Governance in relation to blockchain
+   c. Governance principles, mechanisms and trade-offs
+
+### Afternoon
+
+3. Blockchain Governance in Practice / Lecture & Case Studies (3 hours) (Tara & Felix)
+   a. Governance cookbook (Tara)
+   i. Parameters of governance
+   b. Governance lifecycle (Felix)
+   i. Process design of governance innovation
+   c. Strategy: Progressive Decentralization & Exit to Community (Tara)
+
+4. Introduction to OpenGov / Guest Lecture & Discussion Circle (1 hour) (Maybe Otar Shakarishvili)
+   a. OpenGov as use case to illustrate and explore concepts and insights taught in the previous lectures
+
+5. Takehome Assignment / Case Study
+   a. Exercise on governance trade-off through personal or relatable case study
+
+## Day 2 (Challenge Module)
+
+### Morning & Afternoon
+
+● Kick Off & Assignment Review (1 hour) / Sharing Circle
+○ Share insights from assignment
+○ Refresh cookbook and life cycle
+○ Introduce framework for the challenge
+
+● Blockchain Governance Design Canvas / Challenge-Based Prototyping & Interactive Workshop (5-6 hours)
+○ Ten groups (Defined in advance, 50/50 founders & developers)
+○ Each work on a specific governance challenge sourced from the Polkadot ecosystem
+○ The governance design canvas outlines a set of thematic questions they need to address while working on a solution for the challenge
+
+● Source governance challenges either from Polkadot ecosystem or PBA Founders Track
+○ Request to DOT ecosystem: late March (KILT, Arcla, InvArch)
+○ Request to student: at beginning of the course, 20.05.
+
+● Expert Feedback Session (2h)
+○ Hosted by faculty and mentors from challenge-providing projects
+○ In parallel, each expert gives feedback to 2-3 projects
+
+## Day 3
+
+### Morning
+
+● Group Project Pitch (2h)
+○ Each student group presents their challenge project, using the governance design canvas (each 10 min)
+
+● Cross-Learning Session / Discussion Circle (1h)
+○ Participants explore cross-learnings between their projects and synthesize practical takeaways
+
+● TBD: Governance Outlook / Guest Lecture (1h)
+○ Future Trends, challenges and opportunities for blockchain governance in the Polkadot ecosystem
diff --git a/content/8-Governance/index.md b/content/8-Governance/index.md
new file mode 100644
index 00000000..7e9533b7
--- /dev/null
+++ b/content/8-Governance/index.md
@@ -0,0 +1,25 @@
+# Governance
+
+## Learning Outcomes
+
+● Governance Literacy: To provide participants with a comprehensive understanding of various governance frameworks and their relevance to blockchain initiatives, fostering an ability to critically assess and apply these frameworks effectively.
+
+● Regulatory Awareness: Teach participants to adeptly navigate the intricate political, regulatory, and legal landscapes that impact the deployment and operation of blockchain governance structures, preparing them for proactive compliance and strategic planning.
+
+● Governance Design: To enable learners to design and implement effective and adaptable governance systems for their blockchain projects by bridging the gap between theoretical knowledge and practical application.
+
+● Stakeholder Engagement: Focus on strategies for effective stakeholder engagement, emphasizing the importance of building and nurturing a strong, inclusive, and collaborative community as a cornerstone of successful blockchain governance.
+
+● Governance Experimentation: Encourage participants to explore and innovate within the realm of blockchain governance, fostering a culture of continuous improvement and adaptation to emerging challenges and opportunities.
+
+● Talent Pipeline: Support the development of a robust pipeline of skilled professionals who are not only versed in the technical aspects of blockchain but also adept at the complex decision-making and ethical considerations required in effective governance.
+
+## Slides
+
+<p>All presentations can be found at the links below:</p>
+<p><a href="https://github.com/Polkadot-Blockchain-Academy/pba-content/blob/main/assets/Gov_PBA6_Lucerne_2025.pdf" target="_blank">PDF format</a></p>
+
+# Polkadot OpenGov
+
+<p>All presentations can be found at the links below:</p>
+<p><a href="https://github.com/Polkadot-Blockchain-Academy/pba-content/blob/main/assets/opengov_pba_lucerne_2025_fin.pdf" target="_blank">PDF format</a></p>
diff --git a/content/9-Polkadot/1-polkadot-reintroduction-slides.md b/content/9-Polkadot/1-polkadot-reintroduction-slides.md
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@@ -0,0 +1,686 @@
+---
+title: Polkadot Re-Introduction
+description: A high level overview of Polkadot, summary of key parts and an introduction to parachains protocol
+duration: 45 min
+owner: Maciej Zyszkiewicz
+---
+
+# Polkadot Re-Introduction
+
+Notes:
+Introduction
+
+---
+
+# Polkadot Re-Introduction
+
+## Agenda
+
+- Core Tenets
+- Blockchain Landscape Overview
+- Actors in the Polkadot Network
+- Core Polkadot Technologies Glossary
+- Polkadot Module Agenda Overview
+
+Notes:
+
+---
+
+# Core Tenets
+
+- [...]
+
+- [...]
+
+- [...]
+
+- [...]
+
+- [...]
+
+Notes:
+Before we jump into the main topic let me make a few comments on what are the core tenets of Polkadot. Even tho Polkadot is changing over the years and the protocol evolves those values where accurate when the network first launched, are accurate today and will still be accurate when JAM launches.
+
+---v
+
+# Core Tenets
+
+- **Accessibility**
+
+- [...]
+
+- [...]
+
+- [...]
+
+- [...]
+
+Notes:
+The first one is that Polkadot needs to be accesible which should be apparent with the open-source nature of the community. Negligible barriers to innovation, being easy, fast and cheap are the core properties here.
+
+Hopefully all of you being here in this room learning about Polkadot is a bit of a proof of our values, that access to the protocol and the knowledge of it should be easily accessible.
+
+Remember that all of you are here on this free course because the world largest DAO, Polkadot OpenGov funds it. The eocystsem tries to make itself as accessible as possible. And spread of knowledge is a core component here.
+
+---v
+
+# Core Tenets
+
+- Accessibility
+
+- **Generality**
+
+- [...]
+
+- [...]
+
+- [...]
+
+Notes:
+Polkadot is a ubiquitous computer and every good computer needs to provide some generality. The key pieces to this were supplied by the customizable and programmable substrate/frame chains so something you got to experience in details over the last few weeks. They are fully adjustable state transition machines that can be deployed online. And they will play an intergral role as building blocks for the Polkadot Ecosystem.
+
+---v
+
+# Core Tenets
+
+- Accessibility
+
+- Generality
+
+- **Composability/Interoperability**
+
+- [...]
+
+- [...]
+
+Notes:
+Next one is Composability which can be closely married with interoperability. In Polkadot individual parachains are fully coherent and composable within themselves but to interact between the parachain boundaries you need XCM which grants us native bridging beween the chains. All of that allows various sub-ecosystems to thrive together.
+
+---v
+
+# Core Tenets
+
+- Accessibility
+
+- Generality
+
+- Composability/Interoperability
+
+- **Performance**
+
+- **Resilience**
+
+Notes:
+
+The goal of the next 2 days will be mainly spent understanding how we achieve that last two tenets: Performance and Resilience.
+
+Performance is a big one. We all want a bigger variety of applications hosted on blockchain but this cannot be done unless we provide more throughput and lower latency. Just like web2 systems need to scale their architecture we had to innovate and evolve ours. No longer can every validator EXECUTE and STORE everything and for that we will explore how Polkadot is sharded. In fact we will be exploring both STATE SHARDING and EXECUTION SHARDING in the upcoming lectures.
+
+Do notice that decentralisation is not a core principle, we only care about decentralisation because we believe it provides true resilience. It's not decentralisation for the sake of decentralisation.
+
+---
+
+# Blockchain Landscape
+
+Notes:
+Let's zoom out for a second and remind ourselves how Polkadot overall aims to compare to the blockchain landscape and what it aims to bring to the table. This is my own take on the history but I will try and highlight some core innovations, strenghts and weaknesses of all the different solutions so we can appreciate and understand all the trade-offs.
+
+---v
+
+# Blockchain Landscape
+
+## Simple Monolithic - (Bitcoin etc)
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Shared single state</li>
+    <li>Everyone executes everything</li>
+    <li>Shared single and constant state transition function</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 500px" src="./assets/introduction/decentralised.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+We started with single simple state machine blockchains like Bitcoin. Every node hat to fully sync up and store the state and reexecute all the state transitions. Nevertheless it initially didn't require much hardware and was easy to host so a well diversified networks of nodes quickly arose.
+
+The state transition function was immutable. It was just moving balances left and right so it was all essentially a giant ledger.
+
+And I often here the complaint that blockchains are jsut giant ledgers and it certainly was true in the past. BUt modern blockchains are so so much more than that. They are closer to virtual computers than ledgers.
+
+---v
+
+# Blockchain Landscape
+
+## General Monolithic - (Ethereum 1.0 etc)
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Shared single state</li>
+    <li>Everyone executes everything</li>
+    <li><b>Programmable logic (smart contracts)</b></li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 500px" src="./assets/introduction/decentralised.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+And that was all started with Ethereum. The big innovation was that it was programmable. The state transition function was no longer immutable but instead effectively turing complete. This opened up a lot more demand for blockchain throughput but original Ethereum did really not address this demand. Everything was being reexecuted by every single validator.
+
+This was still a world where each blockchain to communicate with another needed to develop a brand new bridging technique supporting both landscapes.
+
+---v
+
+# Blockchain Landscape
+
+## Supercharged Monolithic - (Solana etc)
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Shared single state</li>
+    <li>Everyone executes everything</li>
+    <li>Programmable logic (smart contracts)</li>
+    <li>[...]</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 500px" src="./assets/introduction/decentralised.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Then there came solutions that tried to quickly boost the throughput. The easiest solution to achieve it was to throw money at it. So all the core state, execution and generality components are the same as previously but the hardware just gets super beefy and expensive.
+
+---v
+
+# Blockchain Landscape
+
+## Supercharged Monolithic - (Solana etc)
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Shared single state</li>
+    <li>Everyone executes everything</li>
+    <li>Programmable logic (smart contracts)</li>
+    <li><b>Just on super expensive hardware</b></li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 500px" src="./assets/introduction/centralised.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Each validator and node is required to use this very expensive hardware which technically allows the monolithic solution to "scale". This solution comes with major trade-offs because running a node gets so expensive only a single operator or maybe a few can afford it which generally sacrifices on the core tenets of blockchain.
+
+It topoligically looks like all other monolithic but just a lot more sparse and centralised.
+
+---v
+
+# Blockchain Landscape
+
+## Fragmented Networks - Cosmos
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li><b>State split between subnetworks</b></li>
+    <li><b>Fragmented economic security</b></li>
+    <li><b>Execution separated and encapsulated within subnetworks</b></li>
+    <li>Programmable logic (usually)</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/introduction/cosmos.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Now we can take a look at solutions that realised a single state machine is not scalable. To scale we need to delegate, separate, split and shard.
+
+One solution like that is Cosmos which features a framework for building blockchains and they provide a shared communication language between chains. Although the chains in the cosmos world all have different security guarantees and different rules and while they can speak the same messaging language it is up to the chains to ensure the message gets to the other chains and is respected there.
+
+In this solution cosmos blockchains are like separate islands, they technically speak the same language but they are so remote and independent it is difficult to fascilitate safe and regular communication. Each island is responsible for their own security and resources needed for maintaining security are spread between the islands.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 250px" src="./assets/introduction/transformation_8.drawio.svg" />
+
+Notes:
+And finally we can take a look at Polkadot. Polkadot since day 1 of its inception was centered around sharding. A single monolithic blockchain cannot scale unless it compromises on core blockchain principles.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/scalability-trilemma.svg" />
+
+Notes:
+and at this point I'm sure you all are very familiar with the blockchain trilemma.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/transformation_1.drawio.svg" />
+
+Notes:
+So on a high level Polkadot also decided to split the state into smaller subnetworks.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/transformation_2.drawio.svg" />
+
+Notes:
+Each subnetwork or shard with a fully programmable runtime logic thanks to substrate and wasm.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/transformation_2b.drawio.svg" />
+
+Notes:
+but then Instead of fully separating the execution and security layers Polkadot instead chooses to start pooling them together. Combining forces.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/transformation_3.drawio.svg" />
+
+Notes:
+From the diagram here you can start noticing that there is a region forming that is crossection between all of the islands. The islands are no longer separated, individual beings, they have something in common.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/transformation_4.drawio.svg" />
+
+Notes:
+And the more and more subnetworks we add the emergent existence of this central core becomes more and more obvious.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/transformation_5.drawio.svg" />
+
+Notes:
+So lets crystalize it a bit. Some nodes remain unique and specialised for the subnetwork while others aim to remain very generic and sitting in the middle. The middle section is not just one node but a full on family of general compute nodes able to fully sync up with every other subnetwork in the ecosystem.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/polkadot_small.drawio.svg" />
+
+Notes:
+The universal nodes in the middle will be a unifying force bringing together all the subnetworks into a single cohesive structure. We will be looking into more and more detail of what is this central structure, but some of you might already now it as the Polkadot Beacon Chain, or Polkadot Relay Chain. This is the auditing layer of Polkadot that is the source of its security and interoperability.
+
+And looking at this diagram it should already be pretty straightforward to see what the Polkadot logo actually represents. Just by adding a bit of color...
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/transformation_7.drawio.svg" />
+
+Notes:
+And we can arrive to our familiar design.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 500px" src="./assets/introduction/transformation_8.drawio.svg" />
+
+Notes:
+Pause
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Sharded state</li>
+    <li><b>Shared security</b></li>
+    <li><b>Sharded execution</b></li>
+    <li>Programmable logic</li>
+    <li>Built in bridging</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 500px" src="./assets/introduction/polkadot_large.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Let's summarize and zoom out for a second.
+
+Polkadot is at its core a sharded network. The state and execution is separated into subnetworks, but the security is pooled and not separated. Individual subnetworks are of course fully programmable with wasm runtimes.
+
+You can think of the polkadot rolay chain as a layer 0 solution. It's like a mothership for all the smaller shards connecting to it.
+
+Additionally Polkadot not only provides a messaging language BUT it also comes with a messaging protocol over which those messages can be sent and received.
+
+---v
+
+# Blockchain Landscape
+
+## Sharded Networks - Polkadot
+
+<img style="width: 700px" src="./assets/introduction/polkadot_large_labeled.drawio.svg" />
+
+Notes:
+In this module we will be mainly focusing on the role of responsibilities of the central nodes. They are the Polkadot validators hosting the Polkadot Relay Chain.
+
+The subnetworks are called parachains, parallel chains -> parachains. And the nodes for parachains are called collators. They are akin to sequencers in other ecosystems and parachains are like rollups or L2 solutions.
+
+---
+
+## Main Actors
+
+Notes:
+So let's do a quick summary of the different actors we'll be seeing in this module. Think of the Polkadot Protocol as a game with different teams and roles and the actors here as players.
+
+---v
+
+## Main Actors
+
+- **Validators**
+- [...]
+- [...]
+- [...]
+
+Notes:
+There will be 4 main actors that we will be discussing. First and foremost we have the Validators. When we say the validators we mean the physical nodes of the Polkadot Relay Chain. They are the general purpose super-validators that allow all the parachains to come together and meet at the relay chain. They are also the block producers of the relay chain.
+
+There is a subflavour of a validator worth mentioning here. Validators are a wide set but only some of them are elected to perform their duties in the active validator set. Usually when we say validator we mean an active validator currently selected by the staking system. The staking elections take place every day but we will discuss that in the next lecture.
+
+---v
+
+## Main Actors
+
+- Validators
+- **Collators**
+- [...]
+- [...]
+
+Notes:
+Another crucial actor is a collator. Collators are parachain or rollup nodes. They are nodes specialized in supporting their own subnetworks. Ther main job managing parachain state and gathering together transactions to then send them over to the relay chain for audting. They also need to manage physical hardware to perform all those duties.
+
+---v
+
+## Main Actors
+
+- Validators
+- Collators
+- **Nominators**
+- [...]
+
+Notes:
+Nominators are a bit more ephemeral. They generally are not physical nodes but abstract account holding some funds. They are all the DOT tokenholders participating in the staking protocol to elect validators. You can think of them as the stakers.
+
+Trivia, validators are often also nominators of themselves.
+
+---v
+
+## Main Actors
+
+- Validators
+- Collators
+- Nominators
+- Users
+
+Notes:
+Users here are a bit of a blanket statement, but I generally mean the people or entities that submit transactions or extrinsics. This might be a proxy or a UI interface that submits it in the end but from the perspective of the protocol we don't care that much.
+
+Disclaimer: This is not en exhaustive list and there are some extra actors as well as various subflavours of the presented here roles. For instance some nodes don't store the fully blockchain history while others don't and we call them archival nodes. There are also light clients and simillar. My aim here is to show you the 4 core roles we'll see in the protocol.
+
+For every lecture or subprotocol we'll be discussing I will try and provide a general outline of what actors will be participating in it.
+
+---
+
+# Core Technologies of Polkadot
+
+Notes:
+Now that we enumerated all the actors it's time for more lists. You all already worked a bunch with various technologies that are foundational to Polkadot but I wanted to make a short glossary of the key pieces. So what core technologies used to power Polkadot today?
+
+---v
+
+# Core Technologies of Polkadot
+
+1. Framework: Substrate
+1. VM: WASM/PolkaVM
+1. Governance: OpenGov
+1. [...]
+1. [...]
+1. [...]
+1. [...]
+1. [...]
+1. [...]
+
+Notes:
+Some of them you are already very familiar with. Substrate is our framework for building modular blockchains and WASM is the go-to runtime featured in Substrate. Substrate and Wasm together gives us monolithic and proggrammable blockchains to play with.
+
+Governance which was already discussed at depth is for the evolutions of the system. Runtimes can be changed over time and system parameters can be adjusted. Governance is also crucial for rescue operations in emergency situations.
+
+---v
+
+# Core Technologies of Polkadot
+
+1. Framework: Substrate
+1. VM: WASM/PolkaVM
+1. Governance: OpenGov
+1. Authority: Nominated Proof of Stake
+1. [...]
+1. [...]
+1. [...]
+1. [...]
+1. [...]
+
+Notes:
+Then we have something a bit newer. The authority modules which essentialy need to decide who gets to be in the temporary priviliged set of relay chain validator nodes running the show. We are using a Nominated Proof of Stake system and we'll dive into it in the next lecture. It's a more energy efficient alternative to Proof of Work, and a more democratic one than Proof of Authority.
+
+---v
+
+# Core Technologies of Polkadot
+
+1. Framework: Substrate
+1. VM: WASM/PolkaVM
+1. Governance: OpenGov
+1. Authority: Nominated Proof of Stake
+1. Block Production: BABE/SASSAFRAS
+1. [...]
+1. [...]
+1. [...]
+1. [...]
+
+Notes:
+Next is block production. Once NPoS selected us some relay chain validator then we need to figure out between them who makes the next block. And Polkadot Relay Chain is just a substrate blockchain in the end. Someone needs to author the relay chain Block and this is where BABE comes in.
+
+In future we will be transition to a newer variant called Sassafras but we will cover that in the Block Production lectures.
+
+---v
+
+# Core Technologies of Polkadot
+
+1. Framework: Substrate
+1. VM: WASM/PolkaVM
+1. Governance: OpenGov
+1. Authority: Nominated Proof of Stake
+1. Block Production: BABE/SASSAFRAS
+1. Sharding: ELVES
+1. [...]
+1. [...]
+1. [...]
+
+Notes:
+
+---v
+
+# Core Technologies of Polkadot
+
+1. Framework: Substrate
+1. VM: WASM/PolkaVM
+1. Governance: OpenGov
+1. Authority: Nominated Proof of Stake
+1. Block Production: BABE/SASSAFRAS
+1. Sharding: ELVES
+1. Shard Interoperability: XCMP + XCM
+1. [...]
+1. [...]
+
+Notes:
+
+---v
+
+# Core Technologies of Polkadot
+
+1. Framework: Substrate
+1. VM: WASM/PolkaVM
+1. Governance: OpenGov
+1. Authority: Nominated Proof of Stake
+1. Block Production: BABE/SASSAFRAS
+1. Sharding: ELVES
+1. Shard Interoperability: XCMP + XCM
+1. Finality: GRANDPA, BEEFY
+1. [...]
+
+Notes:
+
+---v
+
+# Core Technologies of Polkadot
+
+1. Framework: Substrate
+1. VM: WASM/PolkaVM
+1. Governance: OpenGov
+1. Authority: Nominated Proof of Stake
+1. Block Production: BABE/SASSAFRAS
+1. Sharding: ELVES
+1. Shard Interoperability: XCMP + XCM
+1. Finality: GRANDPA, BEEFY
+1. Scheduling: CoreTime
+
+Notes:
+
+---v
+
+# Core Technologies of Polkadot
+
+1. Framework: Substrate
+1. VM: WASM/PolkaVM
+1. Governance: OpenGov
+1. Authority: Nominated Proof of Stake
+1. Block Production: BABE/SASSAFRAS
+1. Sharding: ELVES
+1. Shard Interoperability: XCMP + XCM
+1. Finality: GRANDPA, BEEFY
+1. Scheduling: CoreTime
+1. Database: RocksDB
+1. Encoding: SCALE
+1. Networking: LibP2P/LiteP2P
+
+Notes:
+This isn't a comprehensive list of all the technologies but there are some more generic ones in the backend connected to databases, networking and encoding like RocksDB, SCALE, and LibP2P.
+
+---
+
+# Polkadot Module Agenda
+
+1. Re-Introduction
+1. Staking
+1. Block Production
+1. State Sharding
+1. Data Availability
+1. Execution Sharding
+1. Confirmations and Finality
+1. Scheduling
+1. JAM & Future
+
+Notes:
+Now it's time to have a generak overview of the topics and lectures I have planned specifically for this module.
+
+We will be primarily covering the relay chain protocol aspects. You can think of the relay chain protocol as a big game. Staking is what selects the player for the game. Block production is who gets to make the next move. All the other lectures are trying to explain the rules of them game. To be precise the next ext three lectures of State Sharding, Data Availability and Execution Sharding are all parts of the ELVES protocol. This is how Polkadot scales and guarantees shared security to its rollups.
+
+Finality is a bonus rule to the game that gives us a lot of new features. And scheduling is just some organizational janitorial stuff.
+
+---v
+
+## Why are we learning it?
+
+Notes:
+And I want to make something clear. We will be diving deep into the protocol. This is stuff that's not the easiest but I don't believe you all are here to learn the easy stuff.
+
+Different parts of what we'll be learning will be useful to different people. Some will build light clients, some wallets, some will join parity, others will optimize execution for parachains. There will be something for everyone.
+
+And in general If all you care about is building a simple dapp that moves the balances left and right you might not need to have such an in-depth knowledge, just a bit of solidity is enough.
+
+But if you ever want to innovate and build something new, then you need to learn what the boundaries are before pushing them further. And the boundaries in blockchain mainly arise from the protocol itself.
+
+If you want to build the next uniswap, cryptokitties, next moonbeam or hyperbridge then we have to understand the protocol.
+
+---
+
+# JAM
+
+Notes:
+now let's give a short disclaimer about JAM. I am not focusing on it but it's worth making a stance and how it connects to what I'll be talking about.
+
+---v
+
+# JAM
+
+## Polkadot 3.0
+
+JAM is a further generalization and abstraction of Polkadot.
+
+JAM can do everything the current Polkadot Relay Chain can and more stuff on top of it.slightly different. That means that whatever Polkadot does now will still be very relevant in JAM.
+
+Notes:
+JAM was proposed as a potential next step for the Polkadot Network. Generally think of it as a generalization of the protocol. JAM can do everything the current Polkadot Relay Chain can and more stuff on top of it.
+
+So many of the steps in parachain consensus like finality, block production, approval checking and disputes will be recreated and ported to JAM, so understanding them now gives you an awesome headstart to understanding what JAM truly aims to achieve.
+
+---
diff --git a/content/9-Polkadot/14-jam-math-to-code-slides.md b/content/9-Polkadot/14-jam-math-to-code-slides.md
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+---
+title: JAM - Transforming Math Formulas into Code
+description: How we can read the Graypaper and understand it by coding
+duration: 40+ mins
+---
+
+### Transforming Math Formulas into Code
+
+<img width="700px" src="../../assets/img/7-Polkadot/jam-cartoon.jpg" />
+
+---
+
+## What is this talk NOT About?
+
+- What is JAM 🚫
+- Why JAM is useful 🚫
+- How JAM is different from Polkadot 🚫
+
+---
+
+## What is this talk About?
+
+- Hands-on approach ✅
+- Read (and understand) math formulas ✅
+- Implement JAM in actual code ✅
+
+---
+
+## JAM Crypto Innovations
+
+<img width="1000px" src="../../assets/img/7-Polkadot/jam-comparison.png" />
+
+---
+
+<img width="1000px" src="../../assets/img/7-Polkadot/jam-knife.png" />
+
+---
+
+## JAM Crypto Innovations
+
+<!--  .slide: data-visibility="hidden" -->
+
+- Polkadot Virtual Machine (PVM) - RISC-V
+- Erasure Coding DA
+- VRF Ring Signatures / Bandersnatch
+- In-core + on-chain
+- Parallel Execution
+  - Each Core runs different computing jobs
+  - State components updated in parallel
+- Safrole and Grandpa - less forks
+
+---
+
+# Formal Specification
+
+---
+
+## PVM
+
+<img width="1000px" src="../../assets/img/7-Polkadot/pvm-formula.png" />
+
+---
+
+## Erasure Coding
+
+<img width="1000px" src="../../assets/img/7-Polkadot/erasure-coding.jpg" />
+
+---
+
+## Bandersnatch
+
+<img width="1000px" src="../../assets/img/7-Polkadot/bandersnatch.png" />
+
+---
+
+## Disclaimer ⚠️
+
+- I learnt **Rust** 16 months ago in PBA Hong Kong.
+- 12 months ago I decided to build JAM in **Elixir**
+
+---
+
+## Block Structure
+
+<img width="400px" src="../../assets/img/7-Polkadot/jam-block.png" />
+
+```rust
+struct Block {
+    header: Header,
+    extrinsic: Extrinsic,
+}
+```
+
+---
+
+## Extrinsic Structure
+
+<img width="400px" src="../../assets/img/7-Polkadot/jam-extrinsics.png" />
+
+```rust
+struct Extrinsic {
+    tickets: Vec<Ticket>,
+    disputes: Disputes,
+    preimages: Vec<Preimage>,
+    assurances: Vec<Assurance>,
+    guarantees: Vec<Guarantee>,
+}
+```
+
+---
+
+## State Structure
+
+<img width="600px" src="../../assets/img/7-Polkadot/jam-state.png" />
+
+```rust
+struct State {
+    authorizer_pool: Vec<Vec<Hash>>,         // α
+    recent_history: RecentHistory,           // β
+    safrole: Safrole,                        // γ
+    services: HashMap<u64, ServiceAccount>,  // δ
+    entropy_pool: EntropyPool,               // η
+    ...
+}
+```
+
+---
+
+## State Transition Function
+
+<img width="600px" src="../../assets/img/7-Polkadot/jam-stf.png" />
+
+```rust
+let new_state = state_transition(state, block)
+
+fn state_transition(state: &State, block: Block) -> State {
+  // Logic to update state with new block
+}
+```
+
+---
+
+## State Dependencies
+
+<img width="600px" src="../../assets/img/7-Polkadot/jam-stf-deps.png" />
+
+```rust
+let timeslot_ = get_timeslot(h);
+let history_daga = get_history_data(h, &state.recent_history);
+let history_ = get_history_(h, &ext.tickets, &history_daga, c);
+```
+
+---
+
+## Data Encoding
+
+<img width="600px" src="../../assets/img/7-Polkadot/jam-encoding1.png" />
+
+```rust
+trait Encode {
+    fn e(&self) -> Vec<u8>;
+}
+
+impl Encode for Vec<u8> {
+    fn e(&self) -> Vec<u8> {
+        self.clone()
+    }
+}
+```
+
+---
+
+## Data Encoding
+
+<img width="600px" src="../../assets/img/7-Polkadot/jam-encoding2.png" />
+
+```rust
+struct VariableSize<T> {
+    size: usize,  // Assuming size is stored as usize
+    value: T,     // Generic type to allow flexible values
+}
+
+impl<T: Encode> Encode for VariableSize<T> {
+    fn encode(&self) -> Vec<u8> {
+        let mut encoded = Vec::new();
+        encoded.extend(self.size.to_le_bytes()); // Encode size as bytes
+        encoded.extend(self.value.encode());     // Encode the actual value
+        encoded
+    }
+}
+```
+
+---
+
+## Data Encoding (Elixir)
+
+<img width="600px" src="../../assets/img/7-Polkadot/jam-encoding1.png" />
+<img width="600px" src="../../assets/img/7-Polkadot/jam-encoding2.png" />
+
+```Elixir
+def e(nil), do: []
+def e(x) when is_binary(x), do: x
+def e(%VariableSize{} = x), do: e(x.size) <> e(x.value)
+```
+
+---
+
+## Block Encoding
+
+<img width="700px" src="../../assets/img/7-Polkadot/jam-block-encoding.png" />
+
+```rust
+impl Encode for Block {
+    fn encode(&self) -> Vec<u8> {
+        let mut encoded = Vec::new();
+        encoded.extend(self.header.encode());
+        encoded.extend(self.extrinsic.encode());
+        encoded
+    }
+}
+
+impl Encode for Extrinsic {
+    fn encode(&self) -> Vec<u8> {
+        let mut encoded = Vec::new();
+        encoded.extend(self.tickets.encode());
+        encoded.extend(self.disputes.encode());
+        ...
+        encoded
+    }
+}
+```
+
+---
+
+## Block Encoding (Elixir)
+
+<img width="700px" src="../../assets/img/7-Polkadot/jam-block-encoding.png" />
+
+```Elixir
+  def e(%Block{extrinsic: e, header: h}), do: e({h, e})
+
+  def e(%Block.Extrinsic{} = ex),
+    do: e({vs(ex.tickets), ex.disputes, vs(ex.preimages),
+     vs(ex.assurances), vs(ex.guarantees)
+    })
+```
+
+---
+
+## PVM
+
+<img width="700px" src="../../assets/img/7-Polkadot/jam-pvm.png" />
+
+```rust
+fn f(
+      n: u64,
+      gas: u64,
+      mut registers: Vec<u64>,
+      memory: Memory
+) -> (u64, Vec<u64>, Memory) {
+  if n == GAS {
+      return Host::remaining_gas(gas, registers, memory);
+  }
+  registers[7] = WHAT;
+  (gas.saturating_sub(10), registers, memory)
+}
+```
+
+---
+
+## Conclusion
+
+- Start coding to understand JAM from a developer's perspective
+- Faster development
+- Functional alignment with math
+- Learn Elixir, as its functional features reduces learning curve
diff --git a/content/9-Polkadot/15-JAM-how-to-start-slides.md b/content/9-Polkadot/15-JAM-how-to-start-slides.md
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+---
+title: Yo dawg, I heard yo like JAM
+description: How did we approach building JAM?
+duration: 45+ mins
+---
+
+# Not about JAM
+
+---
+
+#### What is this talk about?
+
+Our aproach <br />
+to learning how <br />
+to implement JAM
+
+Notes:
+We want to share with you how we approached building JAM from scratch in TypeScript
+(crazy idea, I know) in hope to encourage you to do the same in your language
+of choice.
+
+---
+
+#### How do you even start?
+
+- The Gray Paper
+- JAM Lectures (youtube)
+- The Gray Paper
+- Element Rooms (#jam:polkadot.io, #graypaper:polkadot.io)
+- The Gray Paper
+- Did I mention the Gray Paper already?
+
+Notes:
+We want to share with you how we approached building JAM from scratch in TypeScript
+(crazy idea, I know) in hope to encourage you to do the same in your language
+of choice.
+
+---
+
+#### Gray Paper - First impression
+
+<img
+  alt="Gray Paper prose with a bunch of formulas."
+  rounded
+  style="width: 80%;"
+  src="../../assets/img/7-Polkadot/erasure-coding.jpg"
+/>
+
+Gray Paper is a description of the protocol using language-agnostic,
+mathematical notation.
+
+Notes:
+As you probably already know, the main source of truth for JAM is the Gray Paper.
+It's a formal specification of the protocol, which uses a mix of a prose and math
+notation to describe the IMPORTANT (consensus-sensitive) details in a language
+agnostic way.
+
+So when you start off the first thing you'll see is something like.
+
+---v
+
+#### Gray Paper - The scary stuff
+
+<img
+  alt="A scary-looking formula from the Gray Paper describing encoding of a JAM block."
+  rounded
+  style="width: 80%;"
+  src="../../assets/img/7-Polkadot/jam-block-encoding.png"
+/>
+
+Block encoding description.
+
+Notes:
+If you go deeper, things might get a little bit more scary though! :)
+
+---v
+
+#### Gray Paper - Even worse (!)
+
+<img
+  alt="A large formula with dozens of greek symbols."
+  rounded
+  style="width: 80%;"
+  src="../../assets/img/7-Polkadot/pvm-formula.png"
+/>
+
+A recursive step-by-step invocation function describing PVM.
+
+Notes:
+Or even this!
+
+---
+
+#### Bottom-up approach
+
+Start from the very beginning and go through the formulas 1 by 1
+
+<!-- .element: class="fragment" -->
+
+- ✅ straightforward to start
+- ✅ works equally well if you do and don't have experience
+- ❌ you might get stuck
+- ❌ depending on the language you might end up with inefficient architecture
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Top-down approach
+
+Think high level about the client architecture first
+
+<!-- .element: class="fragment" -->
+
+- ✅ you MIGHT build a very efficient client
+- ❌ requires a lot of experience
+- ❌ extremely easy to get wrong
+
+<!-- .element: class="fragment" -->
+
+---v
+
+### Reality (our approach)
+
+- Alternate between bottom-up and top-down.
+
+- Points to consider:
+  - Team composition
+  - Understanding of the domain
+  - Understanding the language/technology
+
+---
+
+#### Who are we?
+
+- JAM implementation in TypeScript
+- JAM tooling (also TS)
+
+- Dev team:
+  - 1 dev with blockchain background
+  - 1-3 TS devs with no prior blockchain background
+  - 2 frontend developers
+
+---
+
+### How did we actually start?
+
+- 📖 Reading the prose of Gray Paper.
+
+  - Getting the gist of what JAM is about.
+
+- 🤖 Figured, we will be working with raw bytes a lot
+  - `Bytes<N>` and `BytesBlob` helpers.
+
+<!-- .element: class="fragment" -->
+
+- 💾 Reading (not running!) JSON tests (w3f/jamtestvectors)
+
+  - Type-safe custom parser.
+
+- ⏱️ Performance measurements from day 1
+  - Micro-benchmarks for "low-level" stuff.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+
+- Reading/loading JSON tests allows us to get some understanding of what's
+  going to be needed and how things might need to be stitched together.
+  While it seems super simple `JSON.parse` we've learned a ton just
+  by trying to model the data structures in a typesafe way.
+- Obviously the choice of the language dictates the steps that you need to
+  tackle first. If you have support for bytes natively - why bother :)
+
+---v
+
+#### `Bytes` helpers
+
+```ts
+export class Bytes<T extends number> extends BytesBlob {
+  readonly length: T;
+  ...
+  static fromBlob<N extends number>(len: N, v: Uint8Array): Bytes<N> {...}
+  static fromNumbers<N extends number>(len: N, v: number[]): Bytes<N> {...}
+  static zero<N extends number>(len: N): Bytes<N> {...}
+  static fill<N extends number>(len: N, input: U8): Bytes<N> {...}
+  static parseBytes<N extends number>(len: N, v: string): Bytes<N> {...}
+
+  /** Compare the sequence to another one. */
+  isEqualTo(other: Bytes<T>): boolean {
+    check(this.length === other.length, "Comparing incorrectly typed bytes!");
+    return u8ArraySameLengthEqual(this.raw, other.raw);
+  }
+}
+```
+
+---v
+
+### Benchmarking examples
+
+- 🤔 What's the most performant way to represent a `Bytes<32>` in TypeScript?
+- 🤠 We need data structures! `Set`, `Dictionary`
+- 🚄 Hashing / Crypto - WASM gives us huge gains.
+
+Notes:
+While it's not strictly necessary to be a performant client for the first milestones
+we are focusing on the performance as we go since our ambitions reach beyond M2/MN2.
+
+---v
+
+### Benchmarking
+
+```ts
+type ArrayHash = Uint8Array;
+type NumberHash = number[];
+type StringHash = string[];
+type PackedNumberHash = number[];
+type BigIntHash = bigint[];
+```
+
+Which one is the fastest?
+
+---v
+
+# OBVIOUSLY IT DEPENDS!
+
+- comparison?
+- ordering?
+- memory consumption?
+- string-parsing?
+- worker-threads passing?
+
+The trade-offs of time-investement might be completely different for your
+language of choice. But the optimisation goal always matters.
+
+---
+
+#### Implementation as exploration
+
+- While re-reading the Gray Paper we started composing the low-level structures
+  and modeling the initial (very rough) architecture.
+- Some other structures were composed based on the W3F JSON test vectors
+  and later fact-checked with the Gray Paper.
+
+<br />
+
+- ✅ GP-navigation skills
+- ✅ Detecting language-specific caveats
+- ✅ Just start coding.
+
+Notes:
+
+By searching the structures in the Gray Paper we were gaining better knowledge
+about the structure of the paper.
+
+---v
+
+### Header code sample
+
+```ts
+export class Header extends WithDebug {
+  ...
+  /**
+   * `H_p`: Hash of the parent header.
+   *
+   * In case of the genesis block, the hash will be zero.
+   */
+  parentHeaderHash: HeaderHash = Bytes.zero(HASH_SIZE).asOpaque();
+  /** `H_r`: The state trie root hash before executing that block. */
+  priorStateRoot: StateRootHash = Bytes.zero(HASH_SIZE).asOpaque();
+  /** `H_x`: The hash of block extrinsic. */
+  extrinsicHash: ExtrinsicHash = Bytes.zero(HASH_SIZE).asOpaque();
+  /** `H_t`: JAM time-slot index. */
+  timeSlotIndex: TimeSlot = tryAsTimeSlot(0);
+  ...
+}
+```
+
+---v
+
+#### Block code sample
+
+```ts
+/**
+ * The block consists of the header and some external input data (extrinsic).
+ *
+ * `B = (H, E)`
+ * https://graypaper.fluffylabs.dev/#/579bd12/089900089900
+ */
+export class Block extends WithDebug {
+  ...
+  constructor(
+    /** `H`: Block header. */
+    public readonly header: Header,
+    /** `E`: Extrinsic data. */
+    public readonly extrinsic: Extrinsic,
+  ) { ... }
+}
+```
+
+---v
+
+#### Gray Paper Reader
+
+<img
+  alt="Gray Paper Reader with code references annotations."
+  rounded
+  style="width: 80%;"
+  src="../../assets/img/7-Polkadot/jam-graypaper-reader.png"
+/>
+
+---
+
+#### In the search of unknown-unknowns
+
+- 😎 known-knowns: Things we are aware of and understand.
+- 😱 known-**unknowns**: Things we are aware of but don't fully understand.
+- 🤯 **unknown-unknowns**: Things we are not even aware exist, so we cannot prepare
+  for them.
+
+Notes:
+
+While you gain understanding of the Gray Paper and the overall domain, you start
+to realize that there are things that you have to do that you didn't even consider
+ealier. These unknown-unknowns turn into known-unknowns.
+
+---v
+
+### How to proceed?
+
+1. Depth-first mode:
+   1. Pick a known-know.
+   1. Research it and uncover known-**\*unknowns**.
+   1. Add them to the list.
+   1. If you have enough items on the list:
+      - go to (2) otherwise go deeper.
+2. Breadth-first mode:
+   1. Parallelize the work
+   1. Go back to (1.) if you run out of tasks.
+
+Notes:
+
+- After we got enough **known-unknowns** we went into breadth-first mode
+- and parallelized the work.
+
+---
+
+### First "proper" tasks
+
+- Codec
+- Merkleization
+- PVM
+- State transitions
+- Running test vectors **\***
+
+Gav's notes on this: <br />
+https://hackmd.io/@polkadot/jamprize#Advice
+
+Notes:
+
+- We figured implementing for JSON test vectors will be simple, so we initially
+  went with things that we believed are going to be hard :)
+
+---v
+
+### First tasks - take aways
+
+- ❌ Don't rely ONLY on JSON test vectors.
+- ✅ Invest in your own unit testing suite.
+
+Notes:
+
+- JSON tests are work in progress and will change.
+
+---
+
+### PVM - alternative implementation
+
+- AssemblyScript - sub-set of TypeScript, can be compiled to WASM
+- Since optimizing stuff to WASM will be needed it was a fun experiment
+  to learn AS via PVM.
+
+Game of life demo: https://todr.me/anan-as/conway.html
+
+---v
+
+### Second PVM - Why?
+
+- Fuzz testing between the two implementations found us a ton of bugs.
+- PVM debuggger was extremely handy in identifying differences.
+- More work, but extremely helpful to share experiences and PoVs.
+
+PVM debugger demo: https://pvm.fluffylabs.dev
+
+---v
+
+### PVM take aways
+
+- 🤠 Building an interpreter is fairly easy (common sense).
+- 🫣 Making it fully compatbile with GP is harder (focus on the formulas).
+- ☠️ Polkadot-level performance (recompiler) - seems very time-consuming.
+
+**\*** There is a Non-PVM Validating Node Path though.
+
+---
+
+### Open ideas
+
+- ⁉️ WASM to PVM recompiler?
+  - AssemblyScript JAM SDK!
+- ⁉️ PVM JAM-Client-Plugin support?
+  - Non-core code: RPC, indexers, protocol extensions, etc.
+- ⁉️ What components does our Web3 stack miss?
+  - Should "Your project is just a web2 database?" be the answer?
+
+---
+
+# Questions?
diff --git a/content/9-Polkadot/2-staking-slides.md b/content/9-Polkadot/2-staking-slides.md
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+---
+title: Polkadot Staking
+description: An introduction to Nominated Proof of Stake in Polkadot
+duration: 1 hour
+owner: Maciej Zyszkiewicz (Kian originally)
+---
+
+# Polkadot Staking
+
+Notes:
+Today we’ll be covering the staking subsystem in Polkadot.
+Who here as ever interacted with the staking system?
+
+---
+
+# Polkadot Staking
+
+## Actors
+
+- Nominators
+- Validators
+
+Notes:
+When it comes to actors this one is surprisingly simple. It is just nominators and validators. In fact this will be the only lecture where we’ll be talking about nominators. Their sole purpose is to interact with staking.
+
+---
+
+# Polkadot Staking
+
+## Problem Statement
+
+Why do we need staking?
+
+Notes:
+So first let’s zoom out for a second and let’s try and see what problem we are even trying to solve with staking. What are we trying to achieve?
+
+---v
+
+# Polkadot Staking
+
+## Problem Statement
+
+- Who gets to build new blocks?
+- Validate transactions?
+- Vote on finality?
+
+<br></br>
+
+In summary we are trying to answer the question of:
+
+**"Who are the authorities?"**
+
+Notes:
+The problem is figuring out who gets to produce or author the next relay chain blocks or perform some other blockchain specific privileged duties. We had to come up with an algorithm or protocol that in the end will appoint the authorities to perform the necessary duties.
+
+---
+
+# What about Proof of Work?
+
+How did Bitcoin solve this problem?
+
+Notes:
+When trying to understand the problem it’s often useful to look at how bitcoin dealt with it. Bitcoin is not perfect but its beauty lies in its simplicity. It’s a minimal viable blockchain.
+
+---
+
+# Proof of Work
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>All miners compute some hashes</li>
+    <li>A sufficiently small hash eables block authoring</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 300px" src="./assets/staking/PoW.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Bitcoin uses proof of work as its authority module. It allows all nodes with some hardware to generate random numbers and if you find the sufficiently small number you get to be the next block author.
+
+---v
+
+# Proof of Work
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>No well defined authority list</li>
+    <li>Endless* arms race</li>
+    <li>Better hardware does not boost throughput only security</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 300px" src="./assets/staking/PoW.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+This solution is quite sleek because there is no well defined authority list. There doesn’t have to be a bounded set. Anyone can mine at any time and you might not even know it until they find the solution.
+
+There are unfortunately some tradeoffs in the PoW design. It’s an endless arms race wasting more hardware and more energy to secure the network. And unfortunately better hardware does not mean that bitcoin gets better performance. Performance capabilities are completely disjoint from the hardware.
+
+There were some alternatives though and one of them was...
+
+---
+
+# Proof of Authority
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Whitelisted set of participants</li>
+    <li>Usually round robin</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/PoA.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Proof of Authority. It was an old alternative to PoW. It was in fact even older than PoW. Instead of playing elaborate games what if we simply chose a set of authorities. Then they might take turns authoring blocks and will perform all the important duties.
+
+This of course comes with huge tradeoffs as it is inherently not decentralized if we just appoint our trusted friends and family.
+
+But this idea of selecting a bounded set of authorities and then working only with them is a useful primitive for later.
+
+---v
+
+# Proof of Authority
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Not inherently bad</li>
+    <li>All depends on how participants get added and/or removed from the set</li>
+    <li>_usually_ a single entity managing the set (!)</li>
+    <li>Prone to corruption, censoring and poor decentralisation</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/PoA.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Proof of Authority. It was an old alternative to PoW. It was in fact even older than PoW. Instead of playing elaborate games what if we simply chose a set of authorities. Then they might take turns authoring blocks and will perform all the important duties.
+
+This of course comes with huge tradeoffs as it is very dependant on how people get added or removed or if there is a super authority that can do it. If yes then this is particularly bad and will inherently suffer from terrible decentralization if we just appoint our trusted friends and family. And in most cases there is a single entity doing the appointing.
+
+But this idea of selecting a bounded set of authorities and then working only with them is a useful primitive for later. Especially if the process is more democratic and representative.
+
+---
+
+# Proof of Stake
+
+## Context for its creation
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>PoW was getting unsustainable</li>
+    <li>Mining hardware = $$$</li>
+    <li>More money meant more mining power</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/scales.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+As PoW was getting more and more popular its downsides were becoming more and more severe. And very soon a new alternative arose on the market and that was Proof of Stake.
+
+The short explainer is that…
+
+In proof of work the more money to buy hardware you had the more influence you had. So at this point might as well skip the hardware step and just verify how much money you have.
+
+---v
+
+# Proof of Stake
+
+## In a Nutshell
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Lock some funds 🔒💰</li>
+    <li>You get power proportional to locked stake 💰👑</li>
+    <li>Use that power for good to gain rewards 📈</li>
+    <li>Misbehave to get slashed 📉</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/stake.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Proof of Stake in a nutshell is a process where stakers, those are the people with tokens lock them. Locking is simillar to spending your money on GPUs or ASICS to mine in PoW. You are committing your resources to the protocol to be invested in it.
+
+The more you invest the more power the protocol gives you. You maybe have a higher chance of authoring a block, you are entrusted more responsibility because you put more faith and resources into the protocol.
+
+But you are still an individual. You can use the power for good and be rewarded for it by the protocol or use it for bad to exploit, double-spend and abuse. Then if the protocol detects it you will be punished and your stake slashed.
+
+---v
+
+# Proof of Stake
+
+## Slashes
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>PoS explicit slashing is an equivalent to the implicit oppurtunity cost of reorging in PoW</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/slash.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Slashing is quite interesting because in PoW you could argue there wasnt an explicit way of punishing someone. But there always was an implciit way of doing it builit into the protocol. If someone built an invalid block other nodes would ignore it and all the effort the attacker put into building it is wasted. This oppurtunity cost is equivalent to the more explicit punishments in PoS.
+
+---v
+
+# Proof of Stake
+
+## Characteristics
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Less energy usage</li>
+    <li>Decoupling throughput scaling with security scaling</li>
+    <li>Stronger hardware = better throughput</li>
+    <li>Ecosystem TVL growing usually automatically improves (economic) security</li>
+    <li>Removes economy of scale</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/slash.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+So some core characteristics of all PoS approaches are for instance much much lower energy usage. Blockchains that moved to PoS from PoW often reduce their energy usage to less than 1% of the original.
+
+PoS additionally does something which is rarely talked about. It decouples throughput scaling with security scaling. In bitcoin better hardware just meant being more secure. In PoS better hardware is generally better throughput.
+
+Security is derived from the total value locked of the tokens being staked. So as the ecoystem grows the economic security grows naturally with it. No hardware adjustments are usually needed. And when we talk about economic security we mean how much resources or money it would take to get enough stake to attack or control the network.
+
+PoS also helps with in reducing the impact of economy of scale which generally leads to centralization. Barely anyone runds a single btc miner nowadays. Only large mining operations can remain profitable.
+
+---v
+
+# Proof of Stake
+
+## Desybilling
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>1 person =/= 1 vote</li>
+    <li>More funds = More power</li>
+    <li>Plutocratic by design</li>
+    <li>but there are addons that can help with it</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/scales.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+There is also one core feature is that it desybils our users. But it doesn't do it perfectly.
+PoW and PoS both share this one feature and a flaw and that is that they dont care who you are or that you are an individual person or a group of people. All that matters is how much funds or resources you have. So 1 person 1 vote are not inherently a part of staking and it is all proportional to the resources.
+
+That being said there are some approaches and research being done to help with that. For instance implementing quadratic voting with a proof of personhood to limit the effects of large stakeholders and empowering the small ones.
+
+---v
+
+# Proof of Stake
+
+## Proof of Authority in Disguise
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>PoS usually tries to elect a small & temporary authority set</li>
+    <li>Once elected it often behaves like a classic PoA</li>
+    <li>PoS is like plutocratic representative government</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/leader.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+One interesting thing about all proof of stake protocols is that they have a proof of authority embedded in them.
+
+Essentially PoS never directly identifies an individual block author or a single privileged entity. It instead introduces election mechanisms that create a small and well bounded temporary set of authorities. The authorities then gain special privileges and can perform some validator duties in exchange for rewards. So every Proof of Stake eventually leads to a temporary Proof of Authority. Think of that as a temporary representative government like a parlament. They authorities change quite regularly and they all keep each other responsible.
+
+And in this lecture we are solely focused on the part of selecting the authorities and not what they do after they are selected.
+
+---
+
+# Proof of Stake
+
+## Subflavours
+
+- Classic PoS
+- Delegated PoS
+- Nominated PoS
+
+Notes: There are a few different ways to approach the elections. Out main goal is to narrow down from a wide set of authority candidates into a smaller well bounded list of active authorities.
+
+The first msot naive approach is a classic PoS, but w ealso have more complex variants like Delegeated Pos and Nominated PoS.
+
+Classic PoS is something akin to initial Ethereum PoS systems, while DPoS is like Tron, EOS and other. NPoS is used in Polkadot and we'll be slowly building towards it.
+
+---
+
+# Proof of Stake
+
+## Prerequisites
+
+- Physical Hardware (Node) & Operators
+- Value Bearing Token
+
+Notes:
+In all of those systems there are some prerequisites.
+There need to be some node operators. The blockchain will be hosted on them and we always need some machines.
+There needs to be a value bearing token that can be at stake. This represents someone’s commitment. The stake can grow or decrease based on various actions.
+
+The difference between the staking flavors is mainly about how the stake interacts with the people operating the hardware.
+
+---
+
+# Classic PoS
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Stakers are also hardware operators</li>
+    <li>A subset of stakers (usually highest n) wins the election</li>
+    <li>Elections repeat regularly</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 700px" src="../../assets/img/5-Substrate/dev-6-x-npos-0.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Classic PoS means that to stake you need to operate the hardware yourself. The stake provider and node operator are exactly the same person. This is the very naive and simple approach. So on the right you can see various different stakers a small subset, usually with highstest stake wins. Then we repeat the elections once in a while.
+
+---v
+
+# Classic PoS
+
+## Drawbacks
+
+- Low amount of stake that we can capture
+- Impossible for those who don't want to run the hardware to join
+
+Notes:
+Because what if I have a lof of stake but I dont want to run a hardware node? What if you like running the node but have little money?
+And finally what if the stake is spread over many people and taking the top N is accounting only for a small amount of stake? This essentially incentives centralisation of stake.
+
+If we were to implement such a protocol very very quickly people would start creating abstractions of it. For instance I pay someone a bit and rent them my stake but they run the nodes for me and we share profits. To account for those needs and remedy the issues people came up with...
+
+---
+
+# Delegated Proof of Stake
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li><b>Validator Candidates</b> are competing for votes</li>
+    <li><b>Delegators</b> vote on candidates with their stake</li>
+    <li>Most total votes decide <b>Active Validators</b></li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 700px" src="../../assets/img/5-Substrate/dev-6-x-npos-1.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+delegated proof of stake. In DPoS we have 3 distinct groups. The Validator Candidates, Active Validators, those are the election winners and the delegators which doing the voting with their stake.
+
+The votes are generally 1:1. If you have some stake you pick a node operator you think will do a good job. The rewards are usually shared between the stake providers and hardware operators.
+
+---v
+
+# Delegated Proof of Stake
+
+## Drawbacks
+
+- Stake gets diluted between all candidates
+- Funds might be delegated to non-winners, which get wasted
+- Leads to centralisation because there is no reward for choosing smaller but trustworthy node operators
+
+Notes:
+But this solution is also far from perfect. Because you have to pick a single validator the stake gets diluted among many many candidates. If your candidate does not win your stake does not contribute to the overall economic security of the chain. So this system has a pretty low stake utilisation rate.
+
+---v
+
+# Multi-Delegated Proof of Stake
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Split your stake amongst multiple candidate when voting</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 700px" src="../../assets/img/5-Substrate/dev-6-x-npos-2.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+To address those issues we need to implement a simple change. Instead of allowing a single delegation let's allow multiple. Then your chances of selecting a winning validator increase! If you would contribute 1 token to every single candidate then tehcnically you have 100% of picking a winning validator.
+
+---v
+
+# Multi-Delegated Proof of Stake
+
+<pba-cols>
+<pba-col>
+  <div><b>Problems?</b></div>
+  <br/>
+  <ul>
+    <li>Your stake is <b>SPLIT</b> amongst multiple candidate</li>
+    <li>Low stake utilization</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 700px" src="../../assets/img/5-Substrate/dev-6-x-npos-2.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+So the same thing that is the strength of this model is also it's weakness. Because splitting your stake means that each individual delegation is worth less and less. In this example we see two delegators on the right that tried to diverisfy and commited some stake to the unsuccesful candidate. The delagators wanted to stake it to earn rewards and secure the network but their stake was not used. It is being wasted. Just as it was in the previous method.
+
+---
+
+# Nominated Proof of Stake
+
+<img style="width: 1000px" src="../../assets/img/5-Substrate/dev-6-x-npos-3.svg" />
+
+Notes:
+And now we organically arrived the the Nominated Proof of Stake which is the next step in the evolution of staking.
+
+In NPoS instead of delegators we have nominators. Nominators dont split their stake in voting, but they simply nominate, or select multiple candidates. It is a binary choice for each validator. You either choose them or not. Often there is a hard cap for how many candidates you can nominate and in Polkadot it is 16.
+
+---v
+
+# Nominated Proof of Stake
+
+<img style="width: 1000px" src="../../assets/img/5-Substrate/dev-6-x-npos-4.svg" />
+
+Notes:
+Next once we have all the nominations there is an algorithm that tries to compute the allocations of stake based on the nominations. This algorithm will never change who you nominate, it will only compute which of the nominations should receive your stake and how much of it. We will explore how it is done in a second.
+
+---v
+
+# Nominated Proof of Stake
+
+- You name up to `N` nominees, an _algorithm_, computed either onchain or offchain, decides
+  the **winners** and **how to distribute the stake among them**.
+- Voters are called **Nominators**.
+
+Notes:
+So to summarize You name up to `N` nominees, and an _algorithm_, computed or verified onchain , decides
+the **winners** and **how to distribute the stake among them**.
+
+- Voters are called **Nominators**.
+
+---v
+
+# Nominated Proof of Stake
+
+- ✅ As a nominator, you are free to express your desire to back non-winners. If you have some other strong nominations you will NOT be disadvantaged.
+
+<!-- .element: class="fragment" -->
+
+- ✅ Has a much higher chance to make sure staked tokens won't get wasted.
+
+<!-- .element: class="fragment" -->
+
+- ✅ Can optimize other criteria other than "who had more votes".
+
+<!-- .element: class="fragment" -->
+
+Notes:
+As a nominator, you are free to express your desire to back non-winners. If you have some other strong nominations you will NOT be disadvantaged.
+
+Has a much higher chance to make sure staked tokens won't get wasted. This leads to a higher stake utilization rate.
+
+Can optimize other criteria other than "who had more votes".
+
+---v
+
+# Nominated Proof of Stake
+
+## Drawbacks
+
+- We decided to solve an NP-hard, multi-winner, approval based, election problem onchain 🤠.
+
+<pba-flex center>
+
+- scalability. <!-- .element: class="fragment" -->
+- scalability. <!-- .element: class="fragment" -->
+- scalability. <!-- .element: class="fragment" -->
+- and scalability. <!-- .element: class="fragment" -->
+
+</widget-text>
+
+- But we get much better economic security measures in return 🌈.
+
+<!-- .element: class="fragment" -->
+
+Notes:
+But as always there are some trade-offs here. Computing the elections is actually an NP-hard problem! Same as the knapsack problem. In general the election algorithm we use is called phragmen. Let's have a very quick look at what we are trying to compute and I'll link you the explainer of the whole algorithm but it is a bit tricky.
+
+---
+
+# Nominated Proof of Stake
+
+## Elections
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Imagine we have 3 nominators each with 10 tokens</li>
+    <li>They can place up to 2 nominations each</li>
+    <li>We need to select 3 validators</li>
+    <li>Who should win?</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/nominations.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+---v
+
+# Nominated Proof of Stake
+
+## Elections
+
+<pba-cols>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/solution2.drawio.svg" />
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/solution3.drawio.svg" />
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./assets/staking/solution1.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+There are multiple solutions. Each one here makes an allocation of stake to some validators and tried to suggest three winners. Which one do you think is the best? What is your reasoning?
+
+---v
+
+# Nominated Proof of Stake
+
+## Scoring Election Solutions
+
+```rust
+pub struct ElectionScore {
+  /// The minimal winner, in terms of total backing stake.
+  ///
+  /// This parameter should be maximized.
+  pub minimal_stake: u128,
+  /// The sum of the total backing of all winners.
+  ///
+  /// This parameter should maximized
+  pub sum_stake: u128,
+  /// The sum squared of the total backing of all winners, aka. the variance.
+  ///
+  /// Ths parameter should be minimized.
+  pub sum_stake_squared: u128,
+}
+```
+
+Notes:
+We need some objective and deterministic ways of comparing and judging solutions.
+
+We trie to maximise the lowest stake. So a solution that has 3 validators, one with a milion, one with 2 millions and 3rd one with 10 tokens would be really bad because the lowest stake is very small.
+
+Next we trie to make it so the total elected stake is very high. This number is how much stake is economically securing the network.
+
+Additionally we try to minimise the variance so trying to make it so all the validators have roughly the same stake at hand.
+
+---v
+
+# Nominated Proof of Stake
+
+## Scoring Election Solutions
+
+[333, 333, 333]
+
+[900, 90, 9]
+
+Note:
+I will give an example why we care about the minimal stake so much.
+
+Imagine we have 3 validators. A total stake is thousand which lets assume is a lot of money.
+
+Now let's compare two examples. One where the stake is evenly distributed and one where some validators have a much higher stake. The protocol to properly function needs to maintain 2/3 honest nodes. So that means that to perform the attack you need to control 1/3 of the nodes.
+
+The system is a secure as it is to attack the weakest 1/3rd of the nodes.
+
+---v
+
+# Nominated Proof of Stake
+
+## Scoring Election Solutions
+
+[333, 333, 333]
+
+[900, 90, 10] <s>9</s>
+
+Note:
+In the second example all you need is 10 tokens and you can outbid the weakest staker that has 9 tokes. SO having evenly distributed stakes drstically increases our stake efficiency. In the first example you would need more than 333 tokens to effectively attack the network.
+
+---v
+
+# Nominated Proof of Stake
+
+## Phragmen
+
+<pba-cols>
+<pba-col>
+  <ul>
+  <li>
+    <a href="https://en.wikipedia.org/wiki/Phragmen%27s_voting_rules">Phragmen Algorithm (link)</a>
+  </li>
+  <li>Does not guarantee an optimal solution, just like greedy algorithms just tries to create a decent one</li>
+  <li>Proved to provide high fairness and justified representation properties whilst being verifiable in
+  linear time.</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 300px" src="./assets/staking/phragmen.jpg" />
+Lars Phragmén
+(1863-1937)
+</pba-col>
+</pba-cols>
+
+Notes:
+Okay so now we've seen how exemplary solutions look like. We know how to compare them to each other so how do we actually find good solutions? Hopefully it is not at random right?
+
+Luckily no. We use an algorithm introduced by Phragmen. It is well defined algorithm that is quite expensive to run but provides decent solutins. It does not guarantee optimal solutions so we still need to verify and compare various options to find the best one we can afford.
+
+Verifying them is luckily linear and this will be crucial in the next steps.
+
+---v
+
+# Nominated Proof of Stake
+
+## Phragmen Examples in Polkadot:
+
+https://wiki.polkadot.network/learn/learn-phragmen/
+
+Notes:
+For those super curious check this resources with some exaples of how exactly phragmen creates the staking solutions in Polkadot.
+
+---
+
+# Nominated Proof of Stake
+
+## Dealing with complexity
+
+- Phragmen is computationally expensive so run it offchain
+- Submit solutions onchain
+- Compare them onchain to find the best one
+
+---v
+
+# Nominated Proof of Stake
+
+## Polkadot Implementation
+
+The current NPoS protocol revolves around an **election round**, which is itself made up of 4 episodes.
+
+---v
+
+# Nominated Proof of Stake
+
+## Episode 1 - **Snapshot**
+
+- Snapshots the state of all nominations and candidate validators
+- Enables multi-block election.
+- Allows us to not need to "freeze" the staking system.
+- Allows us to index stakers, not `AccountIds`.
+
+---v
+
+# Nominated Proof of Stake
+
+## Episode 2 - **Signed Submissions**
+
+- Any signed account can come up with a **NPoS solution** based on that snapshot.
+- Deposits, rewards, slash, other game-theoretic tools incorporated to make to secure.
+
+---v
+
+# Nominated Proof of Stake
+
+## Episode 3 - **Validator Submissions as Fallback**
+
+- As the first backup, any validator can also submit a solution as a part of their block authoring.
+
+---v
+
+# Nominated Proof of Stake
+
+## Episode 4 - **Absolute Fallbacks**
+
+- If all of the above fails, the chain won't rotate validators and the governance can either:
+  - dictate the next validator set.
+  - trigger an onchain election (limited in what it can do).
+
+---
+
+# Nominated Proof of Stake
+
+## Nomination Pools
+
+<img style="width: 900px" src="./assets/staking/NPoS-Pools.png" />
+
+Notes:
+
+---
+
+# Polkadot Staking
+
+# How economically secure is it?
+
+More validators does not always mean more secure.
+
+[100, 100, 100] vs [5, 5, 5, 5]
+
+[210, 210, 210, 210, 210] vs [1000, 10, 10, 10, 10, 10]
+
+Notes:
+
+---v
+
+## Nakamoto Coefficient
+
+<img style="width: 600px" src="./assets/staking/nakamoto.png" />
+
+https://nakaflow.io/
+
+---
+
+# Polkadot Staking
+
+## Parametrisation
+
+- Couple thousands candidate validators
+- 600-1000 elected validators
+- Tens of thousands of nominators
+- 16 nominations per nominator
+- Elections every 24h
+- Minimum nominator stake 250 DOT
+- Minimum stake to join nomination pool 1 DOT
+- Minimum Validator Bond (includes nominations): ~12M DOT
+- Average Staking APY: 8-16%
+- Unbonding Period: 28 days
+
+---
+
+# Polkadot Staking
+
+## Future
+
+- Staking Migration (moving from RLC to a Polkadot Hub System Chain)
+- [Github issue-tracker/project](https://github.com/orgs/paritytech/projects/33)
+- Multi-page election submission
+
+---
+
+# Polkadot Staking
+
+## Usefool Tools
+
+Staking Dashboard: https://staking.polkadot.cloud/#/overview
+
+Validator Insights: https://apps.turboflakes.io/?chain=polkadot#/insights
+
+---
+
+### Further Reading
+
+Starting:
+
+- Staking Guide: https://wiki.polkadot.network/learn/learn-staking/
+- Advanced Staking Concepts: https://wiki.polkadot.network/learn/learn-staking-advanced/
+  Advanced:
+- [A verifiably secure and proportional committee election rule](https://arxiv.org/abs/2004.12990)
+- 4.1 in [Overview of Polkadot and its Design Considerations](https://arxiv.org/abs/2005.13456)
+- [Proportional Justified Representation](https://arxiv.org/abs/1611.09928)
+- [Justified representation - Wikipedia](https://en.wikipedia.org/wiki/Justified_representation)
diff --git a/content/9-Polkadot/3-block-production-slides.md b/content/9-Polkadot/3-block-production-slides.md
new file mode 100644
index 00000000..4c8e4063
--- /dev/null
+++ b/content/9-Polkadot/3-block-production-slides.md
@@ -0,0 +1,334 @@
+---
+title: Polkadot Block Production
+description: Authoring restrictions related to consensus
+duration: 30min
+owner: Maciej Zyszkiewicz (Joshy originally)
+---
+
+# Block Production
+
+Notes:
+In this lecture we’ll be covering what is block authoring as well as how it interacts with various consensus styles.
+
+---
+
+# Block Production
+
+## Agenda
+
+- Authoring Overview
+
+- AURA
+
+- GRANDPA
+
+- Safrole
+
+- Equivocations
+
+---
+
+# Block Production
+
+## Actors
+
+- Validators
+
+---
+
+# Block Production
+
+## Overview
+
+- Leader election problem
+- Most fundemental validator/miner duty
+- Leads to extending the blockchain
+- Unthrottled block authoring would like to a fork chaos
+
+Notes:
+First we are gonna start with a quick overview. Block authoring is the most primitive and fundemental validaot responsibility there is.
+
+In fact in Bitcoin and most proof of work chains it was the only responsibility. There was nothing else than collecting transactions and authoring a block that contains them. This would in turn extend the blockchain. Someone always has to author the block.
+
+We could technically allow anyone to author anytime, but this would lead to a forkful chaos. Chaos like that would be borderline imppossible to manage. All nodes couldnt import all the blocks, reexcuting them localy can be expensive so we need to slow things down.
+
+So the main issue we'll be solving is ordering and throttling of authoring.
+
+We will not be focusing on proof of work or simillar authoring mechanisms on this lecture, instead we will be exploring the authoring methods used in Polkadot and its ecosystem. As you remember from the previous lecture we already are given a few nice primitives from staking.
+
+---
+
+# Block Production
+
+## Prerequisites
+
+- Well bounded set of validators
+- All validators have stake exposure
+
+Notes:
+As one of the prerequisite the staking system already yielded us a small bounded set of authorities and the job of the block authoring module is to further narrow it down into individual block authoring spaced over time.
+
+Additionally all the validators have something at stake. We can leverage that stake to potentially punish them and reward them proportionally.
+
+---
+
+# Block Production
+
+## Throttling
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Split the 24h authority term period into 6s timeslots</li>
+    <li>Ideally there should be 1 block per timeslot</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 700px" src="./img/timeslot.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+To slow down production we introduce the idea of a timeslot. Timeslot corresponds to specific amount of real world time, for instance 6s in Polkadot. We assume that all nodes have access to a commonly synchronised clock. Then based on their clocks we expect that in every time slot there will be a single block created.
+
+---v
+
+# Block Production
+
+## Throttling
+
+<table border="1" cellspacing="0" cellpadding="8">
+  <thead>
+    <tr>
+      <th>Polkadot</th>
+      <th>Time</th>
+      <th>Slots</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>Slot</td>
+      <td>6 seconds</td>
+      <td>1</td>
+    </tr>
+    <tr>
+      <td>Session/Epoch</td>
+      <td>4 hours</td>
+      <td>2_400</td>
+    </tr>
+    <tr>
+      <td>Era</td>
+      <td>24 hours</td>
+      <td>14_400</td>
+    </tr>
+  </tbody>
+</table>
+
+Notes:
+Timeslots are then further grouped into bigger time slices. For instance 4h which are used to schedule validator duties other than block authoring.
+Reminder that elections happe every 24h, so every day our validator set can drastically change.
+
+---
+
+# Block Production
+
+## Aura
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Just a round-robin scheme</li>
+    <li>Problems?</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/aura.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+So now that we have our 14_400 timeslots it is time to figure out who authors when. And the first and most naive solution is just to do a round robin. Pick any atribtrary ordering and everyone takes turns. We have much more timeslots than validators so a full lopp will complete a few times so noone will be omitted.
+
+---v
+
+# Block Production
+
+## Aura
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Just a round-robin scheme</li>
+    <li>Problems?</li>
+      <ul>
+        <li>Next authority is known well in advance</li>
+        <li>Makes it easy to pinpoint DDoS and censor</li>
+    </ul>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/aura.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+The main problem is that it is apparent and public who the next author will be. You don't have to guess and can plan to for instance DDoS them exactly when they are authoring. DDoSing the whole active set is not viable but DDoSing a single author once in a while is totally doable. This could be abused to censor and manipulate the chain or affect the randomness aggregators.
+
+So we need a solution that is a bit more secretive in how it chooses the validators.
+
+---
+
+# Block Production
+
+## BABE
+
+### (Blind Assignment for Block Extension)
+
+Notes:
+And this is where BABE comes in. Babe stands for Blind Assignment for Block Extension so you can already see in the name that it will be trying to be more secretive with the blind part. What we want to achieve is some obfuscation and secrecy hiding who is the next author. It will be someone from the active set, that is our anonymity set but who exactly should be hidden for as long as possible.
+
+---v
+
+# Block Production
+
+## BABE
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>One VRF output per validator per slot</li>
+    <li>Outputs are kept hidden</li>
+    <li>If the output is below a set threshold: </li>
+      <ul>
+    <li>publish output to claim the slot</li>
+    <li>author the corresponding block</li>
+  </ul>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/vrf.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+BABE uses VRFs to achieve its blind assignment. I hope that you all remember what are verifiable random functions. They are random generators where you usually use some entropy context and your private key to generate some outputs which are later verifiable with your corresponding public key. A very useful primitive.
+
+So in Babe every validator generates a VRF output for every slot they see in the future. But they keep those outputs hidden. Then if their random number is below a specific constant threshold it means that they will be able to publish their number and claim the slow to author a block.
+
+Untill you publish your result and prove it noone else knew you would win. This makes it so the attackers don;t even know who to DDoS.
+
+This is exactly like Proof of Work whre they are looking for a small hash, but in BABE the validators get only a single try instead of endlesslly computing the hashes. You either get it or dont. No need to waste energy.
+
+---v
+
+# Block Production
+
+## BABE
+
+<pba-cols>
+<pba-col>
+    <b>Any problems with that approach?</b>
+  <ul>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/vrf.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Does anyone see an obvious issue with this approach of rolling the dice and claiming slots?
+
+---v
+
+# Block Production
+
+## BABE
+
+<pba-cols>
+<pba-col>
+    <b>Any problems with that approach?</b>
+  <ul>
+    <li>Sometimes two validators can claim the same slot</li>
+    <li>Sometimes no validators claim the slot</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/vrf.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+The main problem is that sometimes simply no validator will get a random value below the threshold. This would cause the blockchain to skip a slot which is very undesirable. We want a nice and consistent block time.
+
+And on top of that it is possible that sometimes we will get multiple validators claiming a slot if many of them got lucky. This would in turn cause a fork. We can deal with them in the long run but they waste a lot of computation and add extra complexity.
+
+---v
+
+# Block Production
+
+## BABE
+
+<pba-cols>
+<pba-col>
+
+<ul>
+    <li><b>BABE uses Aura as plan B</b></li>
+    <li>For every slot we try and find a VRF winner and we call those <b>primaries</b></li>
+    <li>If no primary is present default to AURA and select a <b>secondary</b> author</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 600px" src="./img/fusion.jpg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+To deal with the eventuality BABE introduces AURA as a backup plan. We still try to get a VRF winner every slot and those are called primaries. But if it fails and no priamry is selected we default to aura to subbly a backup validator called a secondary.
+
+This combination leads to preserving the security benefits of BABE while benefitting for the predictability and efficiency of AURA. It injects just enough randomness to make censorship and DDoSing very difficult.
+
+In reality VRF thresholds are configured so that around 25% of the slots have a primary author.
+
+---
+
+# Block Production
+
+## Safrole
+
+Notes:
+And finally we can take a look at the newest iteration of the block authoring mechanism and it's called Safrole. Safrole is not something that is being used in Polkadot today but it will is planned to release together with JAM.
+
+---v
+
+# Block Production
+
+## Safrole
+
+- Aims to (mostly) elimate forks
+- Reduce the reliance on AURA
+- Keep complete privacy for ALL block authors
+
+---
+
+# Block Production
+
+## Equivocations
+
+<pba-cols>
+<pba-col>
+    <b>Ambigious or conflicting statements</b>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/equiv.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+We discussed how the protocol operates and if everything goes according to plan validators will start authoring their blocks. Unfortunately there some validators might now want to paly along with the rules. The main malicious behavaiour they can exhibit is called an equiovcation.
+
+An our case equivocation will be strickly referring to giving conflicting statements. Imagine you have a single phone number. You met Alice and Bob and given them your numbers. But you give them two different numbers. At this point we dont even need to check what exact numbers you've given them. As long as we know they were two different numbers we know you lied at some point. You equivocated.
+
+The same malicious behaviour can be done by block authors. An author can technically claim as slot and then author multiple blocks and try to double spend. Other nodes will be importing the blocks and if they detect two blocks from the same author on the same slot they will report him for equivocation. This is very easily provable as long as we have access to the two different blocks.
+
+This proof be permisionlessly provided on chain and will be verified and then trigger slashes to the offending validators.
diff --git a/content/9-Polkadot/4-state-sharding-collators-and-cumulus-slides.md b/content/9-Polkadot/4-state-sharding-collators-and-cumulus-slides.md
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index 00000000..618cd4a9
--- /dev/null
+++ b/content/9-Polkadot/4-state-sharding-collators-and-cumulus-slides.md
@@ -0,0 +1,776 @@
+---
+title: State Sharding (Cumulus & Collators)
+description: Cumulus, architecture and function. Part 1/3 of parachains protocol
+duration: 1 hour
+owner: Maciej Zyszkiewicz (Bradley Olson originally)
+---
+
+# State Sharding
+
+## Collators and Cumulus
+
+Notes:
+Today we'll be covering State Sharding in Polkadot. To understand it we'll be diving deeper into collator nodes as well as a Polkadot-sdk tool called cumulus.
+
+---
+
+# State Sharding
+
+## Actors
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Collators</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/actors.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Our actors here are collators which are parachain nodes and validators which are relay chain elected nodes.
+
+---
+
+# State Sharding
+
+## Agenda
+
+- Elves Overview
+- State
+- State Shards
+- Collator Networks
+- Collations
+- Cumulus
+
+---
+
+# ELVES
+
+<pba-flex center>
+
+1. **Collation: Collect transactions.**
+1. Backing: Assign responsibility.
+1. Availability: Preserve data.
+1. Approval Checking: Verify correctness.
+1. Disputes: Resolve escalations.
+
+</pba-flex>
+
+Notes:
+So today's lecture is part of a 3 lecture sequence describing the ELVES protocol. ELVES is a research paper published by W3F that is describing how polkadot achieves state and execution sharding and how it does it securely.
+
+There are 5 main subprotocols in ELVES. On this lecture we will diving into the Collation side of things. This is everything that happens on the parachain side which is a single Polkadot shard or rollup.
+
+---
+
+# State Sharding
+
+## What is State?
+
+- Status of all the accounts, balances, variables in a blockchain
+- [...]
+- [...]
+
+Notes:
+First a quick reminder to bring everyone up to speed. What is tate in a blockchain context?
+
+Blockchains were often described as big ledgers. This analogy was pretty dismissive of the execution layer of blockchains but it was pretty accurate when it comes to the state layer.
+
+State is all aggregated status of all the data, variables, balances, accounts, smart contracts etc in the blockchain system. If Alice has 10 tokens on her account then this information is a part of the state. State is ofc more than balances. All the blockchain programmables bits, like wasm runtimes, smart contracts etc are also in the state. They are blobs we can interact with.
+
+---v
+
+# State Sharding
+
+## What is State?
+
+- Status of all the accounts, balances, variables in a blockchain
+- State is modified by transactions/extrinsics
+- [...]
+
+Notes:
+State can also be modified by TXs and extrinsics. So if for instance Alice sends 5 DOT to Bob it modifies the bit of state that corresponds to Alice, subtracts 5 from it and moves the 5 to Bob's State. Transactions are effectively operations on the state, they allow us to modify it. Hence we often call executing them state transitions.
+
+---v
+
+# State Sharding
+
+## What is State?
+
+- Status of all the accounts, balances, variables in a blockchain
+- State is modified by transactions/extrinsics
+- State is usually stored by ALL nodes that participate in consensus
+
+Notes:
+That is also why everyone needs to keep track of all the state. Because to apply the transactions we need to have the relevant state. So in most blockchains and I really mean nearly ALL of them. The state is simply and naively just duplicated between ALL the nodes in the network.
+
+---
+
+# (No) State Sharding
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Imagine no state sharding</li>
+    <li>All nodes need to store all the state</li>
+    <li>O(n^2) storage complexity</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/state.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+So in a world with no state sharding all the nodes store all the data entries.
+
+---v
+
+# (No) State Sharding
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Imagine no state sharding</li>
+    <li>All nodes need to store all the state</li>
+    <li>O(n^2) storage complexity</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 600px" src="./img/fully_connected_7_nodes.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+if we have a thousand items in the state and want to have a thousand nodes. That is already a milion things to store across the whole network. It is effectively quadratic in storage complexity.
+
+---v
+
+# (No) State Sharding
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Imagine no state sharding</li>
+    <li>All nodes need to store all the state</li>
+    <li>O(n^2) storage complexity</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 600px" src="./img/fully_connected_20_nodes.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+If we would have a million items to store and a thousand nodes then we already need over a billion of items stored across the network. This is not sustainable and it can lead to centralisation if it imposes higher and higher hardware requirements.
+
+---
+
+# State Sharding
+
+## Data replication
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Data replication is good...</li>
+    <li>but only in moderation</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/state.png" />
+</pba-col>
+</pba-cols>
+
+Notes:
+But data replication is not inherently bad. It is in fact really really good, it provides decentralisation and safety so we don't want to get rid of it. But just by limiting data replication we can achieve simillar security guarantees AND drastically reduce the storage overhead.
+
+---v
+
+# State Sharding
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>State is split into multiple shards (rollups/parachains)</li>
+    <li>Collators store and manage parachain state</li>
+    <li>Validators do NOT store parachain state</li>
+    <li>Validators only store hashes of parachain state and their runtimes</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/state.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+The polkadot network instead of storing it's state in a single monolithic storage decided to split and silo it's storage.
+And this is partially where parachains even come from. Each small silo for a state is their own little blockchain that has it's own sovereign state.
+
+The nodes of each parachain AKA collators are responsible with storing and managing the parachain state. Relay chain validators only store a hash of the parachain state.
+
+Additionally the relay chain also has some state in it, but the general direction is that we want to minimize the state on the relay chain. The relay chain should be completely transactionless and generally unavailable to the end-users. It is a meta-layer to be used by rollups and people. This initiative is often called the Minimal Relay Chain.
+
+---v
+
+# State Sharding
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Relay chain stores the minimum allowed amount of state</li>
+    <li>Ideally there are no transactions at all on the relay chain</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/state.drawio.svg" />
+</pba-col>
+</pba-cols>
+
+Notes:
+Additionally the relay chain also has some state in it, but the general direction is that we want to minimize the state on the relay chain. The relay chain should be completely transactionless and generally unavailable to the end-users. It is a meta-layer to be used by rollups and people. This initiative is often called the Minimal Relay Chain.
+
+---
+
+# State Sharding
+
+## Parachains
+
+- Parachain Runtime (WASM STF)
+- Collator Network
+- State
+
+Notes:
+Now that we've mentioned parachains again it might be time to talk about them a bit more.
+Parachains are generally just sovereign blockchain networks. Most of them are built with Substrate and Frame. Each parachain features a distinct and custom built wasm runtime (that is the state transition funciton), a collator network and a sovereign parachain state over which they preside.
+
+---v
+
+# State Sharding
+
+## Collator Networks
+
+- Choose your own block production engine (usually Aura)
+- Customise your collator incentives
+- Permissioned vs permissionless?
+
+Notes:
+How exactly a collator network should look like is left nearly completely up to the specific parachain and its governance.
+
+The network can decide on things like, what block parachain block authoring to use. Most default to Aura since most of the security will come from the relay chain at later stages anyway.
+
+Parachains also control how to incentivise collators. Some of them run their own staking systems where collators get rewarded for their work. Others prefer it keep things more centralised and under control. Substrate and cumulus allows you to pick from a wide variety of options, everything from a centrally controlled chain run on beefy collators to, decetralised chains is on the table.
+
+---v
+
+# State Sharding
+
+## Collator Duties
+
+- Store parachain state
+- Accept transactions to TX pool
+- Build parachain blocks (a collation of transactions)
+- Send the collations to the relay chain validators
+
+Notes:
+But the one thing all of them need to do no matter what consenus, incentivisation or topology they use is to eventually keep building parachain blocks. Collators are most importantly collecting aggregating and sequencing all parachain transactions into parachain blocks. We often call parachain blocks parablocks. The parablock together with some extra data is sent over to the relay chain.
+
+---
+
+# State Sharding
+
+## Collation Validation
+
+Notes:
+And why do collations get sent over to the relay chain? To get validated of course. The parachains use the rely chain as an auditing layer to inherit its economic security. How relay chain achieves consensus on the validity of collations is a topic for next the next 2 lectures but let's take a look how an singular collation could be verified by a singular other node. No consensus yet, just a local check.
+
+---v
+
+# State Sharding
+
+## Collation Validation
+
+<pba-flex center>
+
+- The relay chain ensures that every parachain block follows the rules defined by that parachain's current code.
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Constraint: The relay chain validators must be able to execute runtime validation of a parachain block without access to the entirety of that parachain's state
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+</pba-flex>
+
+<div class="r-stack">
+<img src="assets/cumulus-deep-dive/runtime_validation_1.svg" style="width: 60%" />
+<img src="assets/cumulus-deep-dive/runtime_validation_2.svg" style="width: 60%" />
+<!-- .element: class="fragment" data-fragment-index="1" -->
+<img src="assets/cumulus-deep-dive/runtime_validation_3.svg" style="width: 60%" />
+<!-- .element: class="fragment" data-fragment-index="2" -->
+</div>
+
+<pba-flex center>
+
+</pba-flex>
+
+Notes:
+Well a parachain block is just a bunch of transactions altering the state.
+
+SWITCH
+
+Here we can see a state transition occuring as a consequence of the transactions.
+
+So if someone has access to the previous state, and appplies the the transactions using the WASM runtime which is the state transition function then they receive the output state. If all the transitions are legal then the resulting state is also legal.
+
+SWITCH
+
+But remember that relay chain validators do NOT store parachain state. So imagine telling your bank to send 100 dollars to Bob, but the bank does not even know how much money you have. Is that a legal transaction? Hard to say we dont know how much you have.
+
+So to answer how we deal with it let's dive into the code and do some inspecting.
+
+---v
+
+# State Sharding
+
+## Collation
+
+```rust[1|8-9|10-11]
+pub struct Collation<BlockNumber = polkadot_primitives::BlockNumber> {
+	/// Messages destined to be interpreted by the Relay chain itself.
+	pub upward_messages: UpwardMessages,
+	/// The horizontal messages sent by the parachain.
+	pub horizontal_messages: HorizontalMessages,
+	/// New validation code.
+	pub new_validation_code: Option<ValidationCode>,
+	/// The head-data produced as a result of execution.
+	pub head_data: HeadData,
+	/// Proof of storage to verify the state transition of the parachain.
+	pub proof_of_validity: MaybeCompressedPoV,
+	/// The number of messages processed from the DMQ.
+	pub processed_downward_messages: u32,
+	/// The mark which specifies the block number up to which all inbound HRMP messages are processed.
+	pub hrmp_watermark: BlockNumber,
+}
+```
+
+Notes:
+Here we have the actual struct used to represent a collation. There is a lot of stuff here but dont worry.
+
+SWITCH
+
+Right now we only care about a few items here. First is head_data. That is the promise of what we should get when we execute the parachain block.
+
+SWITCH
+
+Most importantly there is something called a proof of validity. If we'd inspect this field further eventually we would get here:
+
+---v
+
+# State Sharding
+
+## Collation
+
+```rust [6|9-10|11-12]
+/// The parachain block that is created by a collator.
+///
+/// This is send as PoV (proof of validity block) to the relay-chain validators. There it will be
+/// passed to the parachain validation Wasm blob to be validated.
+#[derive(codec::Encode, codec::Decode, Clone)]
+pub struct ParachainBlockData<B: BlockT> {
+    /// The header of the parachain block.
+    header: B::Header,
+    /// The extrinsics of the parachain block.
+    extrinsics: alloc::vec::Vec<B::Extrinsic>,
+    /// The data that is required to emulate the storage accesses executed by all extrinsics.
+    storage_proof: sp_trie::CompactProof,
+}
+```
+
+Notes:
+To the Parachain block data which is the decoded PoV.
+
+Switch
+
+And as expected we have a list of all transactions here, that's in the extrinsics field
+
+Switch
+
+but we also have a storage proof. Hmmm what's that?
+
+---v
+
+# State Sharding
+
+## Collation Storage Proof
+
+- Makes up most of the information in a collation
+- Acts as a replacement for the parachain's pre-state for the purpose of validating a single block
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- It enables the construction of a sparse in-memory merkle trie
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- State root can then be compared to that from parent header
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+Notes:
+So that field contatins partial parachain state. All the fields being touched by executions we are validating, so read or modified need to be included in the storage proof.
+
+Storage proof in fact makes up most of the collation. Extrinsic calls are usually quite light.
+
+With the storage proof we can reconstruct a small part of the state that is relevant to our current state transition function and ignore other bits. But of course we cannot just trust collators so all the state items are provided as a merkle proof that we compare to the state root from the parent block.
+
+---v
+
+# State Sharding
+
+## Collation Storage Proof Creation
+
+<div class="r-stack">
+<img src="assets/cumulus-deep-dive/pov_witness_data_1.svg" style="width: 70%" />
+<!-- .element: class="fragment fade-out" data-fragment-index="1" -->
+<img src="assets/cumulus-deep-dive/pov_witness_data_2.svg" style="width: 70%" />
+<!-- .element: class="fragment" data-fragment-index="1" -->
+</div>
+
+<br/>
+
+- Only includes the data modified in this block along with hashes of the data from the rest of the trie
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- This makes up the majority of the data in a collation (max 10MB)
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+Notes:
+Let's see an example. Imagine this is our state merkle trie. And imagine Alice from A sends some funds to Bob and Charlie.
+
+The other leafs are also state items but we neither read them or modify them so they are not needed to verify the transactions.
+
+SWITCH
+
+But we still need the hashes of them to have a proper merkle proof. So we need to supply the hashes in the green nodes which together with our data will fully reconstruct the blue node which is the state merkle root. The red leafs were omitted. So we are saving a lot of bandwitdh by not sending them. Usually we only touch a small subset for the whle state sp the savings are quite big.
+
+- orange: Data values modified in this block
+- green: Hash of the siblings node required for the pov
+- white: Hash of the nodes that are constructed with orange and green nodes
+- red: Unneeded hash
+- blue: Head of the trie, hash present in the previous block header
+
+---
+
+# State Sharding
+
+## Parachain STF
+
+- The current STF of each Parachain is stored on the Relay Chain, wrapped as a PVF
+- New state transitions that occur on a parachain must be validated against the PVF
+
+```rust [6]
+/// A struct that carries code of a parachain validation function and its hash.
+///
+/// Should be cheap to clone.
+#[derive(Clone)]
+pub struct Pvf {
+    pub(crate) code: Arc<Vec<u8>>,
+    pub(crate) code_hash: ValidationCodeHash,
+}
+```
+
+<br/>
+
+- PVF ≈ STF = Parachain Runtime = WASM Blob = Parachain's Code
+
+Notes:
+Luckily at least the State transition function is stored on the relay chain. From the perspective of the relay chain it is often called PVF - Parachain Validation Function but that is effectively just a wrapper over the state transition function. Reminder that state transition function is just the WASM blob, the parachain runtime or parachain code. We are terrible at naming things, I know.
+
+---v
+
+#### Why PVF Rather than STF?
+
+<pba-cols>
+<pba-col center>
+
+<img src="assets/cumulus-deep-dive/cumulus_sketch_4.svg" width = "100%"/>
+
+</pba-col>
+<pba-col center>
+
+- The PVF is not just a copy paste of the parachain Runtime
+
+<br/>
+
+- The PVF contains an extra function, `validate_block`
+
+<br/>
+
+**WHY!?**
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+The function `validate_block` needed to interpret all the extra information in a PoV required for validation.
+This extra information is unique to each parachain and opaque to the relay chain.
+
+---v
+
+#### Validation Path Visualized
+
+<div class="r-stack">
+<img src="assets/cumulus-deep-dive/collation_path_1.svg" style="width: 70%" />
+<img src="assets/cumulus-deep-dive/collation_path_2.svg" style="width: 70%" />
+</div>
+
+Notes:
+The input of the runtime validation process is the PoV, and the function called in the PVF is 'validate_block'. Validate block converts the PoV into necessary inputs on top of which a parachain's STF can be run. The output created is called a CandidateReceipt.
+
+---v
+
+#### What Does validate_block Actually Do?
+
+<pba-flex center>
+
+- The parachain runtime expects to run in conjunction with a parachain client
+- But validation is occurring in a relay chain node
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- We need to implement the API the parachain client exposes to the runtime, known as host functions
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- The host functions most importantly allow the runtime to query its state, so we need a light weight replacement for the parachain's state sufficient for the execution of this single block
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+- validate_block prepares said state and host functions, then runs the parachain's STF on top of them
+
+<!-- .element: class="fragment" data-fragment-index="4" -->
+
+</pba-flex>
+
+---v
+
+#### Validate Block in Code
+
+```rust [2|3-4|6|8-11|14]
+// Very simplified
+fn validate_block(input: InputParams) -> Output {
+    // First let's initialize the state
+    let state = input.storage_proof.into_state().expect("Storage proof invalid");
+
+    replace_host_functions();
+
+    // Run Substrate's `execute_block` on top of the state
+    with_state(state, || {
+        execute_block(input.block).expect("Block is invalid")
+    })
+
+    // Create the output of the result
+    create_output()
+}
+```
+
+Notes:
+
+1. We construct the sparse in-memory database from the storage proof and then ensure that the storage root matches the storage root in the `parent_head`.
+2. Replace host functions
+3. Execute block
+4. Create output. We check whether the `storage_root` and other outputs resulting from validation matched the commitments made by the collator
+
+---v
+
+##### Host Function Replacement Visualized
+
+<div class="r-stack">
+<img src="assets/cumulus-deep-dive/replace_host_function_1.svg" style="width: 70%" />
+<!-- .element: class="fragment fade-out" data-fragment-index="1" -->
+<img src="assets/cumulus-deep-dive/replace_host_function_2.svg" style="width: 70%" />
+<!-- .element: class="fragment" data-fragment-index="1" -->
+</div>
+
+---v
+
+# State Sharding
+
+## All Together
+
+<img style="width: 900px" src="./assets/execution-sharding/parachain-validation-multiple.svg" />
+
+---
+
+# State Sharding
+
+## Solochains disclaimer
+
+Notes:
+So you all learned substrate and frame. You can all build substrate chains. And I want to give you a reminder that Substrate is not opinionated about building just for Polkadot. Substrate chains can exist as completely independent blockchains where they try to ensure their own economic security. Substrate chains dont have to be parachains, but if they would like to be, then the transition is super easy
+
+and this is where cumulus comes in.
+
+---
+
+# State Sharding
+
+## Cumulus
+
+Notes:
+So we've discussed all the duties of collators but we ofc dont expect every parachain to reimplement them from scratch. Most of that come built in with Cumulus.
+
+---v
+
+# State Sharding
+
+## Cumulus
+
+<img style="width: 1200px" src="./img/glue.drawio.png" />
+
+Notes:
+Cumulus is an extension tool to Substrate. It is a bunch of libraries, scripts and tools that can take in your classic substrate chain and turn it into a polkadot compatible parachain. Cumulus is like the glue between substrate parachains and the Polkadot relay chain.
+
+So most teams working on parachains in Polkadot develop their parachain purely in substrate just like a solo-chain but then they use cumulus to do the heavy-lifting of integrating with the relay chain.
+
+---v
+
+# State Sharding
+
+## Cumulus' Key Processes
+
+- Follow relay relay chain progression
+- Collation generation and announcement
+- Request parablocks not shared by peers from relay (data recovery)
+
+Notes:
+We discussed a lot of the responsibilities of collators but those are in fact mostly handled by Cumulus. Cumulus has triggers and hooks for building parachain blocks and it also has the integrations to announce them to the relay chain. Additionally Cumulus follows the relay chain to notice any relay chain forks or to find the new best relay chain head.
+
+---v
+
+## Cumulus and Parachain Runtime Upgrades
+
+<pba-flex center>
+
+- Every Substrate blockchain supports runtime upgrades
+
+<!-- .element: class="fragment" data-fragment-index="0" -->
+
+- Every time a validator wants to validate a parablock, it must first compile the PVF
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+##### Problem
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- What happens if PVF compilation takes too long?
+  <!-- .element: class="fragment" data-fragment-index="2" -->
+  - Approval no-shows
+  - In disputes neither side may reach super-majority
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+> Updating a Parachain runtime is not as easy as updating a standalone blockchain runtime
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+</pba-flex>
+
+---v
+
+### Solution
+
+The relay chain needs a fairly hard guarantee that PVFs can be compiled within a reasonable amount of time.
+
+<br/>
+
+- Collators execute a runtime upgrade but it is not applied
+- Code sent in collation `Option<ValidationCode>`
+- The relay chain executes the **PVF Pre-Checking Process**
+- The first parachain block to be included after the end of the process applies the new runtime
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+> Cumulus follows the relay chain, waiting for a go ahead signal to apply the runtime change
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+Notes:
+
+https://github.com/paritytech/cumulus/blob/master/docs/overview.md#runtime-upgrade
+
+---v
+
+##### PVF Pre-Checking Process
+
+<pba-flex center>
+
+- Track
+- Check
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Vote
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- Conclude
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+- Upgrade
+
+<!-- .element: class="fragment" data-fragment-index="4" -->
+
+- Notify
+
+<!-- .element: class="fragment" data-fragment-index="5" -->
+
+</pba-flex>
+
+Notes:
+
+- The relay chain keeps track of all the new PVFs that need to be checked
+- Each validator checks if the compilation of a PVF is valid and does not require too much time, then it votes
+  - binary vote: accept or reject
+- Super majority concludes the vote
+- The new PVF replaces the prior one in relay chain state
+- A "go ahead" signal is sent, telling the parachain to apply the upgrade
+
+reference: https://paritytech.github.io/polkadot/book/pvf-prechecking.html
+
+---
+
+# State Sharding
+
+## Summary
+
+- State is divided into shards called parachains
+- Shard state is managed by the collators
+- Collators aggregate parachain TXs and build parachain blocks
+- Parachain blocks together with state proofs get sent to validators
+- Cumulus transforms Substrate Chains into Parachains
+
+---
+
+## References
+
+1. 🦸 [Bradley Olson](https://github.com/bradleyolson64) original lecturer
+1. 🦸 [Gabriele Miotti](https://github.com/gabriele-0201), who was a huge help putting together these slides
+1. https://github.com/paritytech/cumulus/blob/master/docs/overview.md
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/9-Polkadot/5-data-availability-backing-and-availability-slides.md b/content/9-Polkadot/5-data-availability-backing-and-availability-slides.md
new file mode 100644
index 00000000..f03843c7
--- /dev/null
+++ b/content/9-Polkadot/5-data-availability-backing-and-availability-slides.md
@@ -0,0 +1,695 @@
+---
+title: Data Availability (Backing & Availability)
+description: Data Availability Problem, Erasure coding, Data sharding.  Part 2/3 of parachains protocol
+duration: 1h
+owner: Maciej Zyszkiewicz (Bradley Olson originally)
+---
+
+# Data Availability
+
+## Backing & Availability
+
+---
+
+# Data Availability
+
+## Actors
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Collators</li>
+    <li>Validators</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/actors.png" />
+</pba-col>
+</pba-cols>
+
+---
+
+# Data Availability
+
+## Agenda
+
+- Assignment
+- Backing
+- Availability
+- Erasure Coding
+
+---
+
+# ELVES
+
+<pba-flex center>
+
+1. Collation: Collect transactions.
+1. **Backing: Assign responsibility.**
+1. **Availability: Preserve data.**
+1. Approval Checking: Verify correctness.
+1. Disputes: Resolve escalations.
+
+</pba-flex>
+
+Notes:
+Last time we looked into collators and how they are producing collations. At the end they had to send them over to the relay chain. But what does that mean? To who exactly?
+
+---
+
+# Assignment
+
+Notes:
+To answer that question we'll look into a procedure I call an assignment or backing assignment.
+
+---v
+
+# Assignment
+
+## Active Validators
+
+<img style="width: 500px" src="./assets/execution-sharding/polkadot-components.svg"/>
+
+**Active validators** are given to the parachain protocol by the NPoS election subsystem.
+
+Notes:
+Assignment will be operating only **Active validators**. They are given to the parachain protocol by the NPoS election subsystem. Currently there are 600 validators in the active set in Polkadot and a new active set get's elected every era which is 24h in Polkadot. For those 24h those validators are the core players in the Polkadot game. Others are temporarily sitting on the bench.
+
+---v
+
+# Assignment
+
+## Backing Groups
+
+<img rounded style="width: 1100px" src="./assets/execution-sharding/validator-groups.png" />
+
+Validators are divided into small **Backing Groups**.
+
+Notes:
+Every Session (4 hours in Polkadot), the parachains consensus takes in those active validators and _partitions_ them into small **groups** which work together. Those groups are currently around 5 validators each in Polkadot and Kusama. Those groups are called backing groups.
+
+This is only a teaser but backing groups are mapping 1 to 1 to Polkadot **Execution Core**s, and these assignments are rotated around every few blocks. Currently a parachain is connected to a specific execution core, think of it as a core that executes parachain blocks.
+
+---v
+
+# Assignment
+
+## Execution Cores
+
+<img rounded style="width: 500px" src="./assets/execution-sharding/polkadot-architecture-simple.png" />
+
+Each backing group corresponds to a **Polkadot Execution Core**.
+One execution core can handle a single parachain block every 6s.
+
+Notes:
+In that map the white ovals are the validators. They are grouped into backing groups of size and each group is assigned to a specific execution core - that's the symbolic black square on the purple relay chain ring. Each execution core is capable of serving a single parachain or to be more precise a single parachain block.
+
+---v
+
+# Assignment
+
+## Rotations
+
+<img rounded style="width: 900px" src="./assets/execution-sharding/pairing_backing_groups_with_cores.svg" />
+
+Once every few blocks the backing groups **rotate** around the execution cores.
+
+Notes:
+Once every few blocks the backing groups **rotate** around and they change the execution core they are serving. This makes it so even if a backing group is full of malicious they cannot wholly block a specific execution core for too long.
+
+---v
+
+# Assignment
+
+## Para <-> Execution Core
+
+Parachains or tasks get mapped to specific executions cores
+
+More on this in the scheduling lecture (Agile Coretime)
+
+Notes:
+Each parachain, parathread or a task in the polkadot ecosystem gets matched with a speciifc execution core when it can produce a block.
+We will explore this process in depth in the scheduling lecture.
+
+---v
+
+# Assignment
+
+## Collator Interaction
+
+Collators once they build the parablock need to check who are the validators that are currently assigned to their execution core and send the collations to them over the p2p network.
+
+Notes:
+Collators once they build the parablock (often referred to as candidate parablocks or just candidates) need to check who are the validators that are currently assigned to their execution core and send the collations to them.
+
+---
+
+# Backing
+
+Notes:
+Now we finally arrive at Backing. We just sent some collations to the validators in our backing group. What happens next?
+
+---v
+
+## Backing - Backers
+
+<img rounded style="width: 700px" src="./assets/execution-sharding/polkadot-architecture-simple.png" />
+
+Validators in the backing group are often called backers.
+
+Notes:
+Validators in the backing group are often called backers for those parablocks that are coming in to them from the collators. That is the group we created in the assignment step. The few validators or backers (3 on the image) receive a bunch of parachain blocks / parablocks / collations / candidates (all the same thing).
+
+---v
+
+## Backing - Backers
+
+<img rounded style="width: 700px" src="./assets/execution-sharding/polkadot-architecture-simple-zoom.png" />
+
+Notes:
+We can zoom in on a specific backing group. Here we can see that backers are first point of contact to the outside world. They are the like club bouncers for the relay chain.
+
+---v
+
+## Backing - Checks
+
+The backers receiving collations need to perform some initial checks to ensure their validity.
+
+Notes:
+But for them to do their job correctly backers after receiving collations need to perform some initial checks to ensure their validity. They simply cannot trust random data blobs coming from the external nodes. And to perform those checks they will be utilising the PVF - parachain validation function we introduced last lecture.
+---v
+
+## Backing - PVF definition
+
+<img rounded style="width: 1000px" src="./assets/execution-sharding/runtime_validation_2.svg" />
+
+> **Parachain Validation Function** (PVF) is a function which takes in the current parachain state (PoV), the promised parachain state, and the parachain state transition arguments. It re-executes the parachain logic/runtime/STF using the arguments on the current state and checks if it matches the promised state. If it does, the parachain block is valid.
+
+Notes:
+Read definition.
+PVF reruns the STF in a sandbox environment to test its outputs.
+
+---v
+
+## Backing - STF reminder
+
+<img style="width: 1200px" src="./assets/execution-sharding/parachain-validation.svg" />
+
+Notes:
+
+---v
+
+## Backing - PVF code
+
+From a Validator's perspective, a parachain is a WebAssembly blob which exposes the following (simplified) function:
+
+```rust
+type HeadData = Vec<u8>;
+
+struct ValidationResult {
+  /// New head data that should be included in the relay chain state.
+  pub head_data: HeadData,
+  // more fields, like outgoing messages, updated code, etc.
+}
+
+fn validate_block(parent: HeadData, relay_parent: RelayChainHash, pov: Vec<u8>)
+  -> Result<ValidationResult, ValidationFailed>;
+```
+
+Notes:
+That's a slightly simplified code example of how it might look. The validator has access to the parachain Wasm blob which is the parachain state transition logic. They also have the current state as pointed to by the parent HeadData. We only need to provide the transactions, details about the old state (merkle proof) and the new state root and both of those are located in the PoV variable - Proof of Validity.
+
+PoV contains the elements necessary for the state transition and the resulting state so it's something the validator can easily check if it's correct or not.
+
+---v
+
+## Backing - PVF results
+
+In the end the backer performing the `validate_block` knows that the transition is either correct or not.
+
+Notes:
+In the end the backer performing the `validate_block` knows that the transition is either correct or not. Actually what even can cause it to fail?
+
+---v
+
+### Backing - PVF failure
+
+**Why might `validate_block` fail?**
+
+1. `parent` or `PoV` is malformed - the implementation can't transform it from an opaque to specific representation
+1. `parent` and `PoV` decode correctly but don't lead to a valid state transition
+1. `PoV` is a valid block but doesn't follow from the `parent`
+
+```rust
+fn validate_block(parent: HeadData, relay_parent: RelayChainHash, pov: Vec<u8>)
+  -> Result<ValidationResult, ValidationFailed>;
+```
+
+Notes:
+Point 1. To verify the state transition we need the pre-state and the transition arguments. If we cannot decode them we cannot verify the transition so it fails by definition.
+Point 2. Everything decodes nicely but the state we are reaching using the pre-state and those transition arguments is not allowed by the parachain logic. So it's a bad transition.
+Point 3. Transitions seems legal but they are anchored to a different parent so we cannot allow recontextualizing them.
+
+The biggest one that we are concerned about is point 2. We need to make sure that no malicious actors adds a malicious transaction that suddenly for instance pays them a million coins from an empty account. That would be an example of a bad transition.
+
+---v
+
+## Backing - Statements
+
+<pba-flex center>
+
+- Receive collation
+- Validate
+- Sign a statement
+- Share statement with other backers
+
+</pba-flex>
+
+Notes:
+Once a backer verifies that the parablock is correct they create and sign their backing statement. This will be a receipt, a proof that they approved this block which is crucial for...
+
+---v
+
+## Backing - Skin in the Game
+
+<pba-flex center>
+
+- The main goal of backing is to provide "skin in the game".
+
+- Backers are agreeing that if the parablock turns out to be bad, they will lose 100% of their stake.
+
+</pba-flex>
+
+Notes:
+Making sure that the backers put some skin in the game. Backers are validators so they have a lot of stake, generally millions of DOT, so if they make incorrect statements they are putting a lot on the table.
+
+---v
+
+## Backing - Skin in the Game
+
+<pba-flex center>
+
+- The main goal of backing is to provide "skin in the game".
+
+- Backers are agreeing that if the parablock turns out to be bad, they will lose 100% of their stake.
+
+- Backing on its own does not provide security, only **accountability**.
+
+- Parablock head data as well as the backing statements are embedded into the relay chain (can be multiple parablocks)
+
+</pba-flex>
+
+Notes:
+The main goal of backing is not immediate security but accountability. Backers are doing the checks to protect themselves from being punished. Those details will be embedded into the chain so backers can be held accountable.
+
+---v
+
+## Backing - Networking
+
+<img rounded style="width: 1000px" src="./assets/execution-sharding/backing-networking.png" />
+
+Notes:
+Once a certain threshold of backers (3 of 5 in Polkadot) in the group approves the parablock it moves to the next stage. It can be broadcasted beyond it's backing group.
+
+---v
+
+## Backing - Onchain
+
+Once a block author spots enough backing statements he puts them **on chain** as part of a block authoring inherent.
+
+<img rounded style="width: 500px" src="./img/backing_onchain.png" />
+
+---v
+
+## Block Production - Candidate Receipts
+
+**Candidate receipt:**
+
+- The parachain ID.
+- The collator's ID and signature.
+- A hash of the parent block's candidate receipt.
+- A Merkle root of the block's erasure-coded pieces.
+- A Merkle root of any outgoing messages.
+- A hash of the block.
+- The state root of the parachain before block execution.
+- The state root of the parachain after block execution.
+
+Notes:
+I mentioned that authors add a parablock into the relay chain block they are authoring. But in reality adding a whole parablock to the relay chain block is not feasible. We need a compact representation of the parablock/candidate - a candidate receipt. In it we store all the elements needed to identify the block later on and ensure that the data and transitions match to what was approved.
+
+---
+
+# Data Availability
+
+Notes:
+Backers accepted the responsibility for the parablock but now there's some more work to be done.
+
+---
+
+# (No) Data Availability
+
+Imagine a situation where a backer discards the PoV once he succesfully backs it and no one else keeps it as well.
+
+He already checked, why would he need to keep it?
+
+This would be equivalent to having NO Data Availability
+
+---v
+
+# (No) Data Availability
+
+## Malicious Collator Attack
+
+- Parachains are blockchains, blocks need to reference their parents
+- In the happy case collators share their collations between themselves
+- What if a parachain block author withholds the collation from other collators?
+
+Notes:
+The problem is this can be severely exploited.
+Parachains are blockchains so each block references a specific parent. They cannot build upon something they don't know.
+Normally a parachain block author would send the collation to the relay chain for validation but he would also shares it with other collators. Other collators will build blocks on top of this parablock so they need to learn about it and import it.
+
+---v
+
+# (No) Data Availability
+
+## Malicious Collator Attack
+
+<div class="r-stack">
+<img src="assets/data-availability-and-sharding/DA_Parachains_1.svg" style="width: 70%" />
+<img src="assets/data-availability-and-sharding/DA_Parachains_2.svg" style="width: 70%" />
+<!-- .element: class="fragment" data-fragment-index="1" -->
+</div>
+
+Notes:
+So the attack scenario goes like this. The attack is selected as parachain block author.
+
+They build the collation but they selectively send it only to the relay chain validators and ignore other collators. The relay chain will process the parablock and potentially accept and finalize it.
+
+Other collators in that situation cannot build new blocks because they dont have the exact transactions in that blocks. What ends up on the relay chain is only a hash of them. So they cannot just read it from the relay chain.
+
+What's the solution?
+
+SWITCH
+
+- Validators keep enough info for collators to reconstruct recent parachain blocks
+
+Validators cannot just discard the collations. They need to keep them for some time.
+Then in worst case this information can be requested by collators to reconstruct the missing blocks and unstuck other collators.
+
+---
+
+## (Centralised) Data Availability
+
+So PoV need to be recoverable from the validators.
+
+Can we just make backers keep them?
+
+---v
+
+# (Centralised) Data Availability
+
+## Malicious Backer Attack
+
+😬
+
+---v
+
+# (Centralised) Data Availability
+
+## Malicious Backer Attack
+
+- You can prove data being incorrect
+- You cannot prove someone refusing to send you data
+
+Notes:
+The problem is we cannot trust the backers to distribute it fairly. They can just ignore honest nodes when we need they the data and this can be heavily exploited.
+
+For the parablock to proceed in its lifecycle at one point or another others will need to verify it. To do it they need to have the necessary PoV data. So the data is not only needed for collators in emergencies it is also crucial for upcoming protocol stages.
+
+---v
+
+# (Centralised) Data Availability
+
+## Malicious Backer Attack
+
+<img src="assets/data-availability-and-sharding/DA_Relay_1.svg" style="width: 70%" />
+
+Notes:
+The exact attack goes like this.
+If the malicious backer is the only entity controlling the PoVs then other nodes cannot validate it and potentially raise an alarm. And even worse the attacker can distribute it to other malicious validators while actively avoiding the honest nodes creating an illusion of safety. Honest nodes know something is suspicious because they cannot retrieve the PoVs but it's impossible to prove.
+
+---v
+
+# Data Availability
+
+## Malicious Backer Attack
+
+<img src="assets/data-availability-and-sharding/DA_Relay_2.svg" style="width: 70%" />
+
+Notes:
+If we create a data storage that is not controlled by the attacker then they cannot selectively distribute PoVs. Everyone that needs to check something can check something.
+
+---
+
+# (Naive) Data Availability
+
+Naive approach would be to make every validator store every PoV.
+
+DOES NOT SCALE
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+Notes:
+We already discussed the same classic problem of data replication. This simply wouldnt scale.
+
+---
+
+# Data Availability Problem
+
+How do we ensure a piece of data is retrievable without storing it on every single node forever (on-chain)?
+
+---v
+
+## Availability - Erasure Coding
+
+The goal: Avoid storing full PoV in each validator
+
+<pba-flex center>
+
+- Encode data of K chunks into a larger code word of N chunks
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+- Any K-subset of N chunks can be used to recover the data
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+</pba-flex>
+
+<img rounded style="width: 1000px" src="assets/data-availability-and-sharding/erasure-coding-1.png" />
+
+Notes:
+
+- Erasure coding allows storing only 3x PoV size vs 334x for 1000 validators
+
+---v
+
+## Availability - Erasure Coding
+
+<img rounded style="width: 450px" src="./assets/execution-sharding/line.drawio.svg" />
+
+Notes:
+It all sounds complicated but trust me it isnt. Let me show you an example.
+That's a line. If we have those two red points everyone agrees that there is only 1 specific line we can draw through those. Line is a 1st degree polynomial.
+
+---v
+
+## Availability - Erasure Coding
+
+<img rounded style="width: 450px" src="./assets/execution-sharding/poly-2nd.drawio.svg" />
+
+Notes:
+Let's keep going further... thats a quadratic polynomial. So a second degree. We need exactly 3 points to be able to draw it exactly.
+
+---v
+
+## Availability - Erasure Coding
+
+<img rounded style="width: 450px" src="./assets/execution-sharding/poly-3rd.drawio.svg" />
+
+Notes:
+You might start seeing a pattern but now that's a 3rd degree polynomial, we need exactly 4 points to draw it.
+
+---v
+
+## Availability - Erasure Coding
+
+<img rounded style="width: 450px" src="./assets/execution-sharding/line-redundant.drawio.svg" />
+
+Notes:
+Now let's go back to the nice and simple line. What if they gave us 3 points from the line? We can remove any one of them and we are still able to draw the line. That's a nice property.
+
+Imagine you have 3 friends. Each remembers a single point from the line. But remembering the whole line is too difficult for any of you. If any of you goes missing you can still recreate the line by combining the other two points and remembering a point is much easier than a line.
+
+---v
+
+## Availability - Erasure Coding
+
+<img rounded style="width: 450px" src="./assets/execution-sharding/line-not-enough.drawio.svg" />
+
+Notes:
+Of course if two of your friends go missing we have a problem. We can no longer recreate the line because we don't have enough points.
+
+---v
+
+## Availability - Erasure Coding
+
+- Represent the data as a high degree polynomial (very curvy curve)
+- Each validator is responsible for one point (small availability chunk)
+- Distribute more points than needed
+- As long as enough of these points remain recoverable from validators we can recover the data
+- Each point is much smaller than the whole data entry
+
+Notes:
+In Polkadot instead of a line we have the data needed to verify the parablock but we simply represent it as a very complicated curve. Each validator is responsible for a single point on that curve. And we distribute more points than needed. As long as enough of these points remain recoverable from validators we can recover the data. And that's the core idea of erasure coding. We only need 2/3rds of the points to recover the data. (2/3rds is a custom parameter)
+
+---
+
+## Availability Chunk Distribution
+
+<img src="assets/data-availability-and-sharding/bitfield-chunk-req.svg" style="width: 40%" />
+
+Notes:
+
+- Validator i sees backing statements on chain and requests chunk i for each PoV from its associated backer
+- Backers respond with chunks, or availability times out
+- After backing something there is a time limit how long it can take to become available. If it fails then it times out and something else will have a chance.
+
+---v
+
+## Availability Statement Format: Bitfields
+
+One structure to sign them all!
+
+<img src="assets/data-availability-and-sharding/availability-gossip.svg" style="width: 70%" />
+
+Notes:
+
+- Number of bits equivalent to the number of `AvailabilityCore`s
+- Bit `i` represents one validator's report as to whether it has its chunk of the PoV occupying core `i`
+- Condenses a validator's perspective into a minimal structure to be signed and gossiped
+- Submitted on-chain by block producers
+
+---v
+
+### Availability On-Chain
+
+<img rounded style="width: 600px" src="assets/data-availability-and-sharding/availability-bitfields.png" />
+
+Notes:
+
+- These statements are gossiped off-chain and included in a block in a ParachainsInherent.
+- Why do we need bitfields on-chain?
+
+---v
+
+### Availability Thresholds Visualized
+
+<img src="assets/data-availability-and-sharding/relay-block-construction-I.svg" style="width: 60%"/>
+
+Notes:
+
+- Validator Y is producing a block
+- Statements from validators a, f, g, and b determine availability for blocks occupying 5 cores
+- Candidates 0, 3, and 4 are marked as included. Approvals start. Cores are freed to repeat process.
+
+What is wrong with this diagram?
+
+---v
+
+### PoV Chunk Validation
+
+What happens if there's a bad chunk in the reconstructed PoV?
+
+Solution: Merkle proofs!
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+<pba-flex center>
+
+- PoV chunks form branches of a merkle tree
+
+<!-- .element: class="fragment" data-fragment-index="2" -->
+
+- Proof distributed with each chunk
+
+<!-- .element: class="fragment" data-fragment-index="3" -->
+
+- Chunks checked against erasure_root from CandidateReceipt
+
+<!-- .element: class="fragment" data-fragment-index="4" -->
+
+</pba-flex>
+
+Notes:
+
+- Corrupted PoV -> PVF failure not attributable to backers
+- Can lead to punishment of innocent parties in disputes
+
+---
+
+### Ongoing Work
+
+Reed Solomon is costly, taking 14-20% of validator CPU time.
+
+**Obvious target for optimization!**
+
+<!-- .element: class="fragment" data-fragment-index="1" -->
+
+<pba-flex center>
+
+- Systemic chunks recovery
+  <!-- .element: class="fragment" data-fragment-index="2" -->
+      - Removes need for decoding
+  <!-- .element: class="fragment" data-fragment-index="2" -->
+      - Instead, re-encode to check chunk validity
+  <!-- .element: class="fragment" data-fragment-index="2" -->
+      - ~50% CPU time improvement
+  <!-- .element: class="fragment" data-fragment-index="2" -->
+- Compiler elision of array bounds checks + inlining
+  <!-- .element: class="fragment" data-fragment-index="3" -->
+      - ~33-50% CPU time improvement depending on unsafe Rust use
+  <!-- .element: class="fragment" data-fragment-index="3" -->
+- Better implemented Reed Solomon library (potential 10x improvement!)
+
+<!-- .element: class="fragment" data-fragment-index="4" -->
+
+</pba-flex>
+
+Notes:
+Systemic chunks recovery RFC: https://github.com/alindima/RFCs/blob/av-chunk-indices/text/0047-assignment-of-availability-chunks.md
+
+Better implemented Reed Solomon: https://github.com/paritytech/reed-solomon-novelpoly/issues/40
+
+---
+
+# Summary
+
+- Data flows from collators to backers
+- Backers run initial checks and back collations
+- Collations are stored erasure encoded chunks (DA layer)
+- 10Mb per execution core of DA for 24h
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
+
+---
+
+## References
+
+1. https://www.youtube.com/watch?v=1pQJkt7-R4Q
+1. https://github.com/alindima/RFCs/blob/av-chunk-indices/text/0047-assignment-of-availability-chunks.md
diff --git a/content/9-Polkadot/6-execution-sharding-approvals-and-disputes-slides.md b/content/9-Polkadot/6-execution-sharding-approvals-and-disputes-slides.md
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--- /dev/null
+++ b/content/9-Polkadot/6-execution-sharding-approvals-and-disputes-slides.md
@@ -0,0 +1,570 @@
+---
+title: Execution Sharding (Approvals & Disputes)
+description: Details about the Approval-Voting and Disputes systems and how they work together to provide secure execution sharding in Polkadot through the means of escalation. Part 3/3 of ELVES
+duration: 60 minutes
+owner: Maaciej Zyszkiewicz
+---
+
+# Execution Sharding in Polkadot
+
+Notes:
+Introduction
+
+---
+
+# Execution Sharding in Polkadot
+
+## Actors
+
+<pba-cols>
+<pba-col>
+  <ul>
+    <li>Validators</li>
+  </ul>
+</pba-col>
+<pba-col>
+<img style="width: 400px" src="./img/actors.png" />
+</pba-col>
+</pba-cols>
+
+---
+
+## Execution Sharding in Polkadot
+
+<img style="width: 600px" src="./assets/execution-sharding/scalability-trilemma.svg"/>
+
+Notes:
+First let's outline why we even need to go through all of that trouble. IN short sharding is our answer to scalability. And I could say that in general sharding is **solving** scalability. But in truth as many have heard...
+
+---
+
+## Execution Sharding in Polkadot
+
+<pba-cols>
+    <pba-col>
+        <img style="width: 500px" src="./assets/execution-sharding/scalability-trilemma.svg"/>
+    </pba-col>
+    <pba-col>
+        <blockquote>
+            <p>“There are no solutions. There are only trade-offs.”</p>
+        </blockquote>
+        <footer>― Thomas Sowell</footer>
+    </pba-col>
+</pba-cols>
+
+Notes:
+There are no solutions. There are only trade-offs. And this is no exception to it so we'll look into how sharding gets us closer to better scalability and what are the trade-offs that we have to make to get there. But first let's look at the problem itself.
+
+---
+
+## Scalability of Blockchains
+
+**Why is there even an issue?**
+
+Notes:
+We all heard that blockchains supposedly don't scale. In short what causes blockchains to scale poorly? Anyone wants to give a very short answer?
+
+-Question time-
+
+---
+
+## Scalability of Blockchains
+
+**Why is there even an issue?**
+
+Everyone checking everything is sacrificing scalability for security (and simplicity).
+
+Notes:
+Everyone checking everything is sacrificing scalability for security (and simplicity).
+Everyone checking everything was a nice solution at first for things like BTC because it was the simplest option to guarantee safety. But unfortunately it introduces so much unnecessary work that it stops us for scaling.
+
+---
+
+## Company analogy
+
+- Start-up with 3 employees
+- All make hand-crafted bags
+- At the end of the day they all share their bags between each other to check for defects
+
+Notes:
+Imagine a start-up company with 3 employees. They all make hand-crafted bags and at the end of the day they all share their bags between each other to check for defects. This is a simple approach and ensures that even if one employee was being lazy in the end we'll get a good product because the mistakes will be caught. That was BTC when it was a small network.
+
+---
+
+## Company analogy
+
+- Company grows to **100** employees
+- All make hand-crafted bags
+- At the end of the day they all share their bags between each other to check for defects... **but there are too many bags!**
+
+Notes:
+But what if this company grows? What if we have 100 employees? Issues is there is too many bags to have everyone check everything.
+Okay that's it! We close the company! Bag making clearly cannot be scaled. NO. We change our ways. We introduce new levels, abstractions, and responsibilities.
+
+---
+
+## Company analogy
+
+- Company grows to **100** employees
+- **Most** make hand-crafted bags
+- **Some check for defects**
+
+Notes:
+Maybe people working in this company really dislike checking for defects and would rather make bags. So bag makers simply take turns checking for defects. If a bag checker spots a defect they can escalate the issue and the bag maker will be held accountable. And here we encountered the first absolutely core principle of sharding - **Issue Escalation**.
+
+---
+
+## Company analogy
+
+- Company grows to 100 employees
+- Most make hand-crafted bags
+- Some check for defects
+- **ESCALATE in case of defects**
+
+Notes:
+It's the "Hey, everyone check this out!" in the start-up setting. That's the whisteblowing of corporations, ticket sending of IT, and the "I want to speak to your manager" of Karens. If there is an issue we only need someone, anyone to raise it and then we can escalate and investigate in full force. Now how does that relate to Polkadot?
+
+---
+
+## Escalation in Polkadot
+
+> In Polkadot not all validators checks everything, but enough of them check so that if there is a problem it will be escalated. Escalation causes everyone to check and always means consequences.
+
+Notes:
+Because if you imagine a whisteblower, you only need one such brave person in the most corrupt company to completely ruin their scheme. It's the same in Polkadot because we leverage this property to the fullest. As long as we get at least **one**, a single one validator doing the checks we can escalate them and ruin the day of the attackers, despite only a fraction of the network doing the checks.
+
+---
+
+## Properties of Escalation
+
+Escalation is the happy path optimization. If there is no issue only very few checkers will participate in the process.
+
+Notes:
+Escalation is the happy path optimization. If there is no issue only very few checkers will participate in the process.
+This solution is only effective because in reality most of the blocks produced are indeed valid and honest. So the happy path optimization brings insane gains and allows for shared workload.
+
+It's worth pointing that optimistic rollups are also a happy path optimization, but our approach is just... less optimistic which gives us the perfect balance between security and scalability. And a bit of a spoiler but also reduces our time to finality to manageable numbers.
+
+---
+
+## Properties of Escalation
+
+If there are issues, due to the escalation, everyone will check everything. We temporarily break sharding (slow down) to ensure security.
+
+Notes:
+If there are issues, due to the escalation, everyone will check everything. We temporarily break sharding (slow down) to ensure security.
+If everyone has to check bags for defects they have no time to produce that many bags BUT when the quality of bags it the most important thing in the world for us that's a good trade. And in blockchain security is the most important thing in the world for us. So we are willing to temporarily slow down to maintain absolute security.
+
+---
+
+# ELVES
+
+Notes:
+Now that we have the core principle of sharding and let's see where it manifests the most in the Elves protocol.
+
+---
+
+## ELVES
+
+<pba-flex center>
+
+1. **Collation**: Collect transactions.
+1. **Backing**: Assign responsibility.
+1. **Availability**: Distribute data.
+1. **Approval Checking**: Verify correctness.
+1. **Disputes**: Resolve escalations.
+
+</pba-flex>
+
+Notes:
+ELVES which gives us execution sharding depends on Collation, Backing and Availability, but it primarily happens in the Approval Checking and Disputes protocol.
+
+[Polkadot v1.0: Sharding and Economic Security](https://polkadot.network/blog/polkadot-v1-0-sharding-and-economic-security/) is a comprehensive writeup of the content here in much more detail. Please read it after the lesson if you would like to understand how Polkadot works from top to bottom.
+
+---
+
+## ELVES
+
+Validators are constantly running many instances of these protocols, for candidates at different stages in their lifecycle.
+
+Notes:
+One important note about this whole system is that it runs asynchronously in multiple threads on the same validator. A validator can receive collations for one parachain, while managing availability chunks for a different parablock, while approval checking a totally different parablock. All of that happens at the same time in various subsystems.
+
+---
+
+# Approval Checking
+
+Notes:
+Approval Checking is the most important part of the protocol and it's also the biggest chunk of the work. It's the battle royale for the blocks and only those that survive can get to finalization.
+
+---
+
+# Approval Checking
+
+## Prerequisites
+
+- A parachain block was included on the relay chain
+
+Notes:
+Approval checking is getting triggered by importing a relay chain block that includes some parablocks. Remember that inclusion means it was backed and made available.
+
+---
+
+## Approval Checking - Validation
+
+**What is validating a Parablock?**
+
+<pba-flex center>
+
+1. Recovering the data from the network (by fetching chunks or from backers)
+1. Executing the parablock using the PVF, checking success
+1. Check that outputs match the ones posted to the relay chain by backers
+1. Share a statement with other validators
+
+</pba-flex>
+
+Notes:
+At this stage what does it mean to validate a parablock?
+It is very similar to the initial checks of backers but instead of getting the data from collators data is recovered from backers and if they refuse from availability chunks
+
+Step 3 is of crucial importance.
+Without it, backers could create things like messages and runtime upgrades out of thin air, by backing a valid candidate but lying about the outputs of the candidate.
+
+---
+
+## Approval Checking - Kick-off
+
+When a relaychain block is authored it includes a list of included parablocks chosen by the block author.
+For each of those included parablocks a separate approval checking process is started.
+
+Notes:
+The whole approval checking process is simply started whenever we spot some included blocks. We then move on to the tranche assignment of approval checkers. And remember that a relay chain block includes a bunch of parablocks so we repeat the same process for all of them at the same time.
+
+---
+
+## Approval Checking - Assignment (simplified)
+
+- Imagine you use a VRF to randomize a number between 0 and 100.
+- The number you get is for how much you should wait before doing the check yourself.
+- Others don't know what number you got.
+
+Notes:
+Everyone generates a random number and thus suggests for how long they should wait before doing the check themselves. This essentially makes it so everyone will potentially do the check at one point, but hopefully as explained in a second, in the happy path not everyone will have to.
+
+Polkadot doesn't necessarily use the number 100 and divides the validator into discrete tranches of 2-3 validators by generating the random VRF output.
+
+---
+
+## Approval Checking - Tranches
+
+- Validators starting with the lowest numbers (in the lowest tranches) start validating the parablock.
+
+Notes:
+Validators starting with the lowest numbers (in the lowest tranches) start validating the parablock. So initially the checks are made with people that randomized very low numbers...
+
+---
+
+## Approval Checking - Tranches
+
+- Validators starting with the lowest numbers (in the lowest tranches) start validating the parablock.
+- Gradually higher and higher numbers start revealing themselves continuing the process.
+
+<img style="width: 900px" src="./assets/execution-sharding/tranches.svg" />
+
+Notes:
+but over time more and more people start checking because higher and higher numbers are called in to reveal themselves. This is how it can be visualized. We group up validators with similar roles together into those small tranches. Every single active validator is one of those tranches. The more time passes the more tranches are woken up and do their checks. You can notice that the first tranche is a bit larger. That is because...
+
+---
+
+## Approval Checking - Threshold
+
+- Validators starting with the lowest numbers (in the lowest tranches) start validating the parablock.
+- Gradually higher and higher numbers start revealing themselves continuing the process.
+- Once a certain threshold of validators (30) have submitted valid statements, the parablock is considered **Approved**.
+
+<img style="width: 800px" src="./assets/execution-sharding/tranches_happy.svg" />
+
+Notes:
+The protocol is parametrised to such a way that we require around 30 checks made in total. If we get 30 positive checks the parablock is considered approved. But wait... wait if it's invalid?
+
+---
+
+## Approval Checking - Invalidity
+
+- Validators starting with the lowest numbers (in the lowest tranches) start validating the parablock.
+- Gradually higher and higher numbers start revealing themselves continuing the process.
+- Once a certain threshold of validators (30) have submitted valid statements, the parablock is considered Approved.
+- If even a single validator submits an invalid statement, the issue is **escalated** into a **Dispute**.
+
+Notes:
+So this is the moment we've been building up to all this time. If at least one node out of those 30 is honest then at this point if we have an invalid block it is time to raise the alarm. It is time to escalate the problem. The node will send a special statement called a dispute statement and that will cause the issue to be escalated. We'll cover the consequences of that in the next step.
+
+Also for those wondering what are the chances that all 30 are malicious it's 1/3^30 which is around 1 in 205 trillions.
+
+---
+
+## Approval Checking - No-Shows
+
+- Validators starting with the lowest numbers (in the lowest tranches) start validating the parablock.
+- Gradually higher and higher numbers start revealing themselves continuing the process.
+- Once a certain threshold of validators (30) have submitted valid statements, the parablock is considered Approved.
+- If even a single validator submits an invalid statement, the issue is **escalated** into a **Dispute**.
+- If a validator disappears (no-shows) after revealing themselves we assume a DoS attack and we require more checkers (+ 1 tranche).
+
+Notes:
+Malicious attackers can try and eliminate good guys so that they get the first 30 votes in. The best way to do it is to DoS honest guys causing them to miss their spot. Although assignments are hidden so they don't even know who to DoS. Only option is to DoS them after they reveal themselves which gives us an option to react and be extra cautious when nodes suddenly disappear.
+
+---
+
+## Approval Checking - No-Shows
+
+<img style="width: 800px" src="./assets/execution-sharding/tranches_dos.svg" />
+
+Notes:
+So this will look something like that. In one tranche one of the validators will wake up because it is their time to check. They announce themselves first, start rebuilding the PoV, but before they can publish they PVF result they get DoSed. We never receive their result so remaining validators raise a soft alarm, they start requiring more checkers. And because of that another tranche will be called in before finishing the approval process.
+
+---
+
+## Approval Checking - No-Shows
+
+<img rounded style="width: 700px" src="./assets/execution-sharding/lernaean-hydra.jpg" />
+
+Notes:
+Fighting DoS should be like fighting a hydra. Even if you eliminate a few honest nodes even more will raise in their place. 2/3 \* 3 gives us 2 extra honest nodes per one no-show.
+
+---
+
+## Approval Checking - Summary
+
+<img rounded style="width: 1300px" src="./assets/execution-sharding/approval_flow.svg" />
+
+Notes:
+This is a flow chart from the perspective of an individual approval checker. First once we notice inclusion we generate the assignment. Then we wait for our turn but if the parablock got approved before that we call it a day, we locally mark it as approved for us and finish the process.
+In case our voice is still needed we reveal our assignment, recover data, do checks and send our statement. If we don't like the block we start a dispute with a dispute statement.
+
+## Interesting this state machine either outputs or stalls. In case of stalling it might be because there is a dispute started in the dispute coordinator subsystem.
+
+# Disputes
+
+Notes:
+Disputes are the last step of the protocol. They are the last resort to ensure security. This is the part of the protocol that is definitely not on the happy path, that's the path of war. Disputes is the logic that if written correctly should never ever trigger, because the incentives will be stacked against the attackers so much that why even bother attacking.
+
+---
+
+## Disputes - Gambler's Ruin
+
+The security argument for Polkadot is based on Gambler’s Ruin.
+
+An attacker who can take billions of attempts to brute-force the process would eventually be successful.
+
+But because of slashing, every failed attempt means enormous amounts of DOT slashed.
+
+Disputes is the part of the protocol that is dispensing those consequences and slashes.
+
+Notes:
+The security argument for Polkadot is based on Gambler’s Ruin. It's a very simple game theory argument. The attackers can technically win but it will cost them so many many tries that the expected cost of even attempting it greatly outweighs the potential gains.
+
+---
+
+# Disputes - Initiation
+
+- When validators disagree about the validity of a parablock, a dispute is automatically raised.
+- Disputes involve all validators, which must then check the block and cast a vote.
+- Backing and Approval statements already submitted are counted as dispute votes.
+- Votes are transmitted by p2p and also collected on-chain.
+
+Notes:
+When a dispute is initiated it means that we have two validators with opposing statements for a parablock. One believing it's valid and someone else it's invalid. TO determine the truth we escalate the issue and involve all the validators.
+
+---
+
+# Disputes - Sharding
+
+> In Polkadot disputes break execution sharding. They temporarily sacrifice scalability to ensure security.
+
+Notes:
+Disputes are very inefficient but they are the ultimate source of truth. We forego sharding to ask everyone for their opinion. Majority vote in our system should always reveal the truth because only a 1/3 can be malicious.
+
+---
+
+# Disputes - Resolution
+
+Dispute reaches a resolution when a supermajority of validators (2/3rds) agree on the validity of the parablock.
+
+The parablock was either valid or invalid.
+
+Notes:
+To be extra careful the dispute reaches its resolution only when we get to 2/3rds of the validators agreeing on the validity of the parablock. The parablock was either valid or invalid. This cannot fail. It's expensive to get this confirmation because everyone makes the checks but it reveals the truth. So now that we know it we need to make someone pay for it.
+
+---
+
+# Disputes - Slashing
+
+The validators on the losing side of the dispute are punished.
+
+If block is invalid the backers are slashed 100% of their stake.
+
+If block is valid the dispute initiators are slashed a small part of their stake for raising a false alarm.
+
+Notes:
+In short whoever lost needs to be punished. There is some nuance here but the general idea is that if the block was actually invalid the backers that approved it will pay the price by loosing al their stake.
+If the dispute says that the block was actually valid it means it was a false alarm dispute. Someone might have done it to waste the network's time so the there needs to be a cost. The node that initiated the dispute will pay a small price in their stake.
+
+---
+
+## ELVES
+
+<pba-flex center>
+
+1. **Collation**: Collect transactions.
+1. **Backing**: Assign responsibility.
+1. **Availability**: Distribute data.
+1. **Approval Checking**: Verify correctness.
+1. **Disputes**: Resolve escalations.
+
+</pba-flex>
+
+Notes:
+So now we have the full picture of the path a parablock would take through the ELVES. There's a few more things in the bigger picture and then we'll be done. Just to recap the 5 steps. Collation was the bundling of transactions into parablocks. Backing was the initial checks and accepting responsibility for the parablock. Availability was the encoding and distribution of data. Approval checking was the main part of the protocol where we checked the parablock and in case of issues we escalate into disputes.
+
+---
+
+## Chain Selection Rule
+
+Validators refuse to author relay chain blocks on top of forks containing parablocks which are invalid or have lost disputes.
+This causes a "reorganization" whenever a dispute resolves against a candidate.
+
+<img rounded style="width: 650px" src="./assets/execution-sharding/babe-chain-selection.png" />
+
+Notes:
+The authoring mechanism is also paired with a chain selection logic. This logic helps us leverage forks to our advantage by tactically ignoring relay blocks with invalid parablocks so the chain can easily reorg those out.
+
+---
+
+## Finality
+
+Only relay chain blocks with fully approved parablocks will be considered for finalization
+
+Notes:
+
+---
+
+# The Nitty Gritty Details
+
+> How are complex off-chain systems implemented using Substrate?
+
+Notes:
+That's it from the high-level overview. Now I have a few small minor implementation details and how we make it all work together nicely.
+
+---
+
+## Interaction Between Client & Runtime
+
+Since Polkadot involves not only on-chain logic but off-chain logic, the runtime is the central source of truth about validators, assignments, parachain states, etc.
+
+Clients learn about the state by invoking **Runtime APIs** at recent blocks, and the runtime is updated with **new blocks**.
+
+<img rounded style="width: 900px" src="./assets/execution-sharding/runtime-node-interaction.png" />
+
+Notes:
+
+Because the runtime is updated by new blocks, malicious or poorly connected validators have some choice in which information to provide the runtime with.
+This must be accounted for in the protocol: we cannot assume that the runtime is always perfectly informed.
+
+---
+
+## Orchestra
+
+https://github.com/paritytech/orchestra
+
+**Orchestra** allows us to split up the node's logic into many "Subsystems" which run asynchronously.
+
+These subsystems communicate with message passing and all receive signals which coordinate their activities.
+
+---
+
+## Orchestra: Signals
+
+Signals are sent to all subsystems and act as a "heartbeat".
+
+Messages sent after a signal arrives on one subsystem cannot arrive at another subsystem until it has received the same signal.
+
+---
+
+## Orchestra: Signals in Polkadot
+
+```rust
+/// Signals sent by the overseer (Polkadot's Orchestra name) to all subsystems.
+pub enum OverseerSignal {
+	/// Subsystems should adjust their jobs to start
+	/// and stop work on appropriate block hashes.
+	ActiveLeaves(ActiveLeavesUpdate),
+	/// `Subsystem` is informed of a finalized block
+	/// by its block hash and number.
+	BlockFinalized(Hash, BlockNumber),
+	/// Conclude the work of the `Overseer` and all `Subsystem`s.
+	Conclude,
+}
+```
+
+Notes:
+
+The instantiation of Orchestra in Polkadot is called "Overseer".
+
+---
+
+## Without Orchestra:
+
+```rust
+fn on_new_block(block_hash: Hash) {
+  let work_result = do_some_work(block_hash);
+  inform_other_code(work_result);
+}
+```
+
+Problem: There is a race condition!
+
+The other code may receive `work_result` before learning about the new block.
+
+---
+
+## With Orchestra:
+
+```rust
+fn handle_active_leaves_update(update: ActiveLeavesUpdate) {
+  if let Some(block_hash) = update.activated() {
+    let work_result = do_some_work(block_hash);
+    inform_other_subsystem(work_result);
+  }
+}
+```
+
+This works!
+Orchestra ensures that the message to the other subsystem only arrives after it has received the same update about new blocks.
+
+---
+
+## Examples of Subsystems in Polkadot
+
+<pba-flex center>
+
+- Dispute Participation
+- Candidate Backing
+- Availability Distribution
+- Approval Checking
+- Collator Protocol
+- everything!
+
+</pba-flex>
+
+---
+
+## Implementers' Guide
+
+[The Implementers' Guide](https://paritytech.github.io/polkadot/book) contains information about all subsystems, architectural motivations, and protocols used within Polkadot's runtime and node implementation. This is the gospel for the Chains team.
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
diff --git a/content/9-Polkadot/7-confirmations-and-finality-slides.md b/content/9-Polkadot/7-confirmations-and-finality-slides.md
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+---
+title: Confirmations and Finality
+description: Finality providing methods and mechanisms for blockchains
+duration: 45min
+owner: Maciej Zyszkiewicz (Joshy originally)
+---
+
+# Consensus: Finality
+
+---
+
+## Consensus is...
+
+...a decision making process that strives to achieve acceptance of a decision by all participants.
+
+Notes:
+
+If we have external factors like trust relationships or Social hierarchy it can be quite easy.
+
+Trust example: If everyone trusts each other, then any one person can propose an outcome, and all the others will trust that it is in the community's best interest.
+
+Social Hierarchy example: If a community has an executive (President, Queen, CEO), the executive can propose her preference and everyone will accept it based on the external mechanism that keeps her as the executive.
+
+But these conditions are not interesting, and are often not realistic. It gets interesting when we don't make these simplifying assumption.
+
+---v
+
+## Five Aspects of Blockchain Consensus
+
+<pba-flex center>
+
+- State machine validity
+- Arbitrary / Political validity
+- Authorship throttling
+- Fork choice heuristic
+- Finality
+
+</pba-flex>
+
+---
+
+## What do these things have in common?
+
+<img style="width: 600px" src="./img/roller_coaster.jpg" />
+
+---v
+
+## What do these things have in common?
+
+<img style="width: 600px" src="./img/slackline.jpg" />
+
+---v
+
+## What do these things have in common?
+
+<img style="width: 600px" src="./img/wheel.jpg" />
+
+---v
+
+## What do these things have in common?
+
+<img style="width: 600px" src="./img/ratchet.jpg" />
+
+---
+
+## Adversarial Conditions
+
+- The participants want to agree on _something_
+- They don't trust each other
+- Some could be faulty, or make mistakes
+- Some could be straight up malicious (aka Byzantine)
+
+---
+
+# One Shot Consensus
+
+A single decision to make.
+
+Once it is made, we are done.
+
+---v
+
+## Desired Properties
+
+All honest participants...
+
+- **Termination** - Eventually reach some decision
+- **Agreement** - Reach the same decision
+- **Integrity** - Reach at most one decision, which was proposed by at least one participant.
+
+---v
+
+## Also Validity
+
+If all participants unanimously propose the same decision, all honest participants reach that decision.
+
+Notes:
+
+Another desireable property that is sometimes too obvious to say.
+
+---
+
+## Example: Where to go for dinner
+
+<pba-cols>
+<pba-col>
+
+<img rounded style="width: 20em" src="./img/south-park-consensus.png" />
+
+</pba-col>
+
+<pba-col>
+
+- Termination - Stan, Kyle, and Kenny will each eventually decide where to eat.
+- Agreement - Stan, Kyle, and Kenny will each decide to eat at the same place.
+- Integrity - Stan, Kyle, and Kenny will eat at either Whistlin' Willies or Casa Bonita.
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Stan, Kyle, Kenny, and Cartman are trying to decide where to have dinner.
+Stan, Kyle, and Kenny want to have something yummy and spend time together.
+Cartman is secretly pursuing his own goals and doesn't care whether dinner is yummy.
+In fact he secretly hopes they won't decide at all so he can go home and eat KFC with his mom.
+
+Stan and Kyle both propose Whistlin' Willie's for dinner.
+Kenny and Cartman propose Casa Bonita.
+
+In the end Kenny may not agree that Whistlin' Willie's is the best option for dinner, but he will agree that it is the legitimate group decision.
+
+---v
+
+## Mistakes vs Malice
+
+**Crash Tolerance** - A system can keep operating normally when some actors crash or go offline.
+
+**Byzantine Fault Tolerance** - A system can keep operating normally when some actors are intentionally malicious. Byzantine actors may:
+
+- Crash - Or pretend to have crashed - Byzantine faults are a superset of crash faults
+- Lie - Sending false information to peers
+- Equivocate - Send inconsistent information to different peers
+
+Notes:
+
+These examples and many others are _instances_ of the Byzantine Generals Problem
+
+---v
+
+## Mistake or Malice?
+
+<pba-cols>
+<pba-col>
+
+<img rounded style="width: 600px" src="https://thepointsguy.global.ssl.fastly.net/uk/originals/2020/12/pitot-ice-scaled.jpg" />
+
+</pba-col>
+
+<pba-col>
+
+- Consider an Airplane flight computer.
+- The pilot _must_ know the airspeed at all times.
+- Airspeed sensors can fail.
+- Sensors can be buggy.
+- Are these malicious?
+
+</pba-col>
+</pba-cols>
+
+Notes:
+
+Consider an Airplane flight computer. It is critical that the pilot (human or automated) knows the aircraft's airspeed at all times.
+Airspeed sensors can fail due to extreme temperatures, icing, solar radiation, and other reasons.
+For this reason, there are redundant sensors, and they run a consensus protocol.
+
+Imagine that one of the sensors has an overflow _bug_ such that when the airspeed exceeds a certain threshold, maybe `u8::max_value()`, it actually reports a much lower speed.
+
+Are these crash faults or byzantine?
+
+In a blockchain system, bugs in the code may cause nodes whose operators are intending to be honest, to deviate from the protocol anyway. This is why client diversity is important.
+
+---
+
+## Byzantine Generals Problem
+
+<pba-cols>
+<pba-col>
+
+<img rounded style="width: 700px" src="./img/byzantine-generals.png" />
+
+</pba-col>
+
+<pba-col>
+
+- Divisions plan to attack
+- Must make coordinated attack to succeed
+- Some generals might be traitors and behave maliciously
+
+</pba-col>
+</pba-cols>
+
+[Cornell Lecture Slides](https://www.cs.cornell.edu/courses/cs6410/2018fa/slides/18-distributed-systems-byzantine-agreement.pdf)
+
+Notes:
+
+Several divisions of the Byzantine army are camped around an enemy city.
+They plan to attack the city, but have not yet decided when to attack.
+If the attack is coordinated, they will probably be successful, but if it is uncoordinated, they will probably be defeated.
+What do our three properties mean in this scenario?
+
+- Termination - every honest general will eventually decide when to attack
+- Agreement - honest general will all agree to attack ta the same time
+- Integrity - the attack time will have been proposed by at least one honest general
+
+Leslie Lamport proposed this problem in the form of a story as a typical representative of the distributed consensus problem.
+
+This is a big moment for us, so let's stop and savor it.
+Two days ago Lauren kicked us off by talking about human coordination.
+How it can achieve long railroads and the great pyramids and sports teams and dancing, and even this academic program.
+Since then we've looked through so many layers of abstraction (contracts, smart contracts, state machines, dags) and so many technical implementation details (P2P networking, platform agnostic bytecodes, blockchain headers, merkle proofs).
+We've taken a huge class of problems - human coordination problems - and distilled them down to their absolute essence.
+Human coordinate at global scale reduced to this one cute, carefully stated problem.
+
+---v
+
+## Byzantine Generals: Solved
+
+<img height="600px" src="./img/pbft-cover.png" />
+
+_Miguel Castro and Barbara Liskov, 1999_
+
+Notes:
+
+_Image = Cover page: Practical Byzantine Fault Tolerance_
+
+And great news.
+The problem is solved!
+At least under some conditions.
+And also great news.
+We have a pretty good understanding of under what circumstances it is solvable.
+
+Before I can tell you exactly how and where it can be solved, we have to understand networks a little bit.
+
+---
+
+# History Lesson
+
+---
+
+## Synchrony
+
+A network is one of:
+
+- **Synchronous** - When sent, a message is received immediately by all.
+- **Asynchronous** - When a message is sent it may be received after some delay, or not at all. The sender doe not know whether it is received. Messages may be received in different orders by different parties.
+- **Partially Synchronous** - When a message is sent, it may be received after some delay up to a maximum delay, $T$. It may not be dropped entirely. Messages may be received in different orders by different parties.
+
+Roughly analogous to real-time (async) vs. turn-based (sync) games.
+
+---v
+
+## Sync or Async?
+
+Classify each of these:
+
+<pba-flex center>
+
+- Telephone call
+- Mail communication
+- Text message
+- Jitsi video call
+- Element chat
+
+</pba-flex>
+
+Notes:
+
+- Telephone call is sync. You say something and wait for the other party to reply
+- Mail is async. You send a letter, then go do other stuff for several days
+- Jitsi video call is basically sync just like the phone call.
+- The others can be either. Sometimes you text back and forth quickly and wait for replies. Other times you send and come back later like mail.
+
+---
+
+## Determinism
+
+A system is one of:
+
+- **Deterministic** - The same inputs give the same outputs every time.
+- **Probabilistic** - The same inputs may not give the same outputs.<br/>
+  $~~~~~~~~~~~~~~~~~~~~~~~~~$ Requires a source of entropy. eg coin flipping. <!-- $~~~$ is a hack to put in white space chars -->
+
+---
+
+## FLP Impossibility
+
+<img style="padding: 0 200px 0 0" src="./img/FLP-impossible.png" />
+
+[Excellent Podcast with Ethan Buchman](https://www.youtube.com/watch?v=t0T-5QOXvrQ)
+
+Notes:
+
+Once it was shown that deterministic consensus is impossible in an async network, the field split into two major parts. Either you:
+
+- Assume the network is (at least partially) synchronous
+- Introduce non-determinism
+
+One interesting thing about Nakamoto pow consensus is that it does _both_.
+
+- Nondeterminism because you don't know who will solve the pow first
+- Partial synchrony because it only works if the time to download and execute the block is much less than the time to solve the PoW
+
+---
+
+## Ongoing Consensus
+
+We want to continue agreeing on<br/>an every-growing history of events
+
+Notes:
+
+Blockchains are intended to keep processing and finalizing transactions forever. This is more like deciding where to go to dinner every night over and over.
+
+---v
+
+## Desireable Properties
+
+<pba-flex center>
+
+- **Safety** aka **Finality** - Nothing bad will happen
+- **Liveness** - Something good will eventually happen
+
+</pba-flex>
+
+Notes:
+
+Traditional literature typically uses the term safety. Blockchain folks typically talk about finality. They basically mean the same thing.
+
+Finality can be proved to entities that are not involved in consensus.
+
+We spoke about liveness previously in the authoring system. There it means that more blocks will be authored, more blockspace will be created and put up for sale. Here, in finality, it means that more blocks will be finalized. Of course liveness in the finality depends on liveness in the authoring.
+
+These two decisions can be entirely orthogonal to one another, or wrapped up together.
+
+---v
+
+## Liveness vs Termination
+
+Earlier I described Termination as desireable,<br/>now I'm saying Liveness is desireable.
+
+Are these at odds with each other?
+
+Notes:
+
+Termination guarantees that, for a given decision, each honest participant will eventually decide something. This concept is relevant when there is a single decision to be made. In the blockchain context, it guarantees that we will eventually know which block is final at height n.
+
+Liveness guarantees that a system that is intended to continue making progress, will indeed eventually make progress. In the context of the blockchain, liveness means that once we've decided what block is final at height n, we will eventually go on to decide what block is final at height n + 1.
+
+---
+
+## Finality in Nakamoto Consensus
+
+<pba-flex center>
+
+- Longest chain rule
+- Longest chain is "best"... for now
+- Someone could always start mining a chain<br/>and,with low but non-zero probability,<br/> end up with it longer.
+- There could _already_ be a longer chain<br/>that you just haven't heard of.
+
+<pba-flex>
+
+The finality is only probabilistic.<br/>
+Nakamoto consensus in only safe in a synchronous network.
+
+Notes:
+
+This is to say that Nakamoto consensus is NOT safe on the real asynchronous internet. In practice, as long as
+blocks can be downloaded and executed much more quickly than the target block time, it is usually good enough.
+
+- Longest could also mean most accumulated work
+
+---
+
+## Deterministic Finality
+
+<pba-flex center>
+
+- Based on traditional methods (BFT)
+- Requires an honest-majority finite authority set
+
+</pba-flex>
+
+<!-- two flexes needed so the next bullet points don't show too early, margin hack... TODO -->
+
+<pba-flex center style="margin-left: 48px">
+
+- Consensus protocol that assumes honest majority
+- Economic game that keeps them honest
+
+</pba-flex>
+<!-- .element: class="fragment"-->
+
+Notes:
+
+If you want deterministic finality, it basically means employing BFT agreement protocols that we talked about in the history lesson. This means we need a finite authority set with an honest majority. And that means we need incentives to keep them honest.
+
+---v
+
+## Incentives: Game Theory!
+
+Abstractly: You behave honestly<br/>when the utility of doing so exceeds the cost.
+
+Incentive designers may potentially:
+
+<pba-flex center>
+
+- Reward honest behavior
+- Punish (aka slash) dishonest behavior
+
+</pba-flex>
+
+Notes:
+
+Many systems use both of these, but doing so is not strictly necessary. Even without slashes, the opportunity cost of staking and the missed rewards from authoring invalid blocks may be sufficient.
+
+It is often the case that blockchain systems give rewards in the authorship and punishments in the finality. There is no fundamental reason for this; it is just a little more straightforward to implement.
+
+---v
+
+## What is potentially punishable?
+
+<pba-flex center>
+
+- Authoring when you aren't supposed to
+- Failing to author when you are supposed to
+- Casting finality votes for conflicting blocks
+- Casting a finality vote for a block (or chain)<br/> that includes an invalid state transition.
+
+> How severe are each of these offenses?<br/>
+> Do they all warrant a slash?<br/>
+> A full slash?
+
+Notes:
+
+PoW has inherent punishment through wasted energy. BFT based system's don't.
+
+Instead, aspiring participants will typically lock up a security deposit which can be slashed in part or in whole.
+
+---v
+
+### Concrete Punishment Example
+
+Let's say a slash is 100 units, and the reporter gets 10%.<br/>I plan to attack.
+
+If my attack is successful,<br/>I expect to gain roughly 200 units worth of utility.
+
+I ask another authority to cooperate with me:<br/>"I'll pay you 20 units to _not_ rat me out for my attack".
+
+> How would you respond?
+
+Notes:
+
+"I don't believe you can carry out the attack because _someone else_ will report you and take the 10 units, leaving me with 0."
+
+---
+
+## Case Study: Tendermint
+
+<pba-flex center>
+
+- Authorship is like Aura - simple round robin
+- Naive but **simple** BFT implementation
+- If the block has enough votes<br/>by the end of the slot, it is finalized.<br/>
+  Otherwise, it is rejected via timeout.
+- "Instant finality"
+- Forkless - Forks are disallowed<br/>because blocks can only be authored<br/>on finalized parents.
+
+</pba-flex>
+
+Notes:
+
+Tendermint assumes a partially synchronous network, like all the BFT based systems - That is to say that messages may not arrive immediately, but will arrive within a finite time bound. In practice this means it is slot-based just like so many of the authoring schemes.
+
+Tendermint is often touted as "instant finality". It is instant in the sense that finality is tied to authorship. In practice this means that authorship, which is inherently O(n), is slowed down to stay in sync with finality which is O(n^2). They sacrifice liveness to guarantee absolute safety at all times.
+
+---v
+
+## Tendermint Deep Dive
+
+<pba-flex center>
+<ol>
+<li class="fragment">Wait for a block (or author one if it is your turn)</li>
+<li class="fragment">Prevote
+  <ul>
+    <li>If the block is valid, Prevote for it.</li>
+    <li>If the block is invalid, Prevote `Nil`</li>
+  </ul>
+</li>
+<li class="fragment">Precommit
+  <ul>
+    <li>Wait for 2/3 prevotes then Precommit</li>
+    <li>If you don't get 2/3 prevotes, Precommit `Nil`</li>
+  </ul>
+</li>
+<li class="fragment">Complete
+  <ul>
+  <li>Wait for 2/3 Precommits them finalize</li>
+  <li>If you don't get it, throw the block away</li>
+  </ul>
+</li>
+</ol>
+
+[Very useful blog post](https://medium.com/softblocks/explaining-how-tendermint-consensus-works-433066cbc465) <!-- .element: class="fragment" -->
+
+</pba-flex>
+
+---
+
+## Hybrid Consensus
+
+<pba-cols>
+<pba-col>
+
+<img rounded style="width: 900px;" src="./img/grandpa-abstract.png" />
+
+</pba-col>
+<pba-col>
+<pba-flex center style="font-size: 0.7em; margin-left:-50px">
+
+- Separates block production from finality.
+- Block production stays live even if finality lags.
+- Allows lower overhead in the finality layer.
+- Used in Substrate.
+
+</pba-flex>
+</pba-col>
+</pba-cols>
+
+---v
+
+## What About Re-Orgs
+
+<img style="width: 500px; margin-right: 150px;" src="./img/reorgs-1.svg" />
+<br/>
+<img style="width: 650px;" src="./img/reorgs-2.svg" />
+
+Notes:
+
+Previously we talked about how a node's view of the best block can change, and that is called a re-org.
+
+---v
+
+## Modified Fork Choice Rule
+
+<img style="width: 500px; margin-right: 150px;" src="./img/reorgs-finality-1.svg" />
+<br/>
+<img style="width: 650px" src="./img/reorgs-finality-2.svg" />
+
+Only extend best finalized chain
+Notes:
+
+Once you have a finality gadget installed, you have to make sure you only ever author on top of finalized blocks. Even if another chain is longer.
+
+---
+
+## Case Study: Grandpa
+
+<pba-flex center>
+
+- Deterministic finality _only_
+- Requires an external block authoring scheme<br/> with its own liveness proof.
+- Kind of like Tendermint but better.
+- Finalizes chains, not blocks.
+
+</pba-flex>
+
+---v
+
+## Vote on Chains, not Blocks
+
+<img style="width: 1000px" src="./img/grandpa-round/4.6-validators-vote-on-chain.png"/>
+
+Notes:
+
+BFT finality with $n$ authorities is in $O(n^2)$.
+Tendermint does this at **every block**.
+This bounds the size of the authority set.
+
+With separated, we treat each vote as a vote not only for one block,but also for each ancestor block.
+This significantly reduces the number of total messages sent.
+Allows the chain to stay live even when many validators are offline
+
+---
+
+## A GRANDPA Round
+
+Each validator **broadcasts** a **prevote** for the **highest block** that it thinks **should** be **finalized**
+
+- For **honest** validators, this block **must include** the chain that was previously finalized
+- This **new chain** could be **several blocks** longer than the **last finalized** chain
+
+A **validator** that is designated as the **primary** broadcasts the highest block that it thinks could be final from the previous round
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-1.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-2.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+Each validator **computes** the **highest block** that can be **finalized based** on the set of **prevotes**
+
+- i.e. we find the **common ancestor** of all votes that has **support** from **more** than $\frac{2}{3}N + 1$ validators
+- We refer to this block as the **prevote GHOST**
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-3.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+We define the round **estimate** as the **highest ancestor** of the **prevote GHOST** for which it is **still possible** to **precommit**
+
+- i.e. when **no precommit** votes have been **sent** out yet, then:
+
+`estimate == prevote GHOST`
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-4.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+If the **estimate** extends the **last finalized** chain, then each validator will cast a **precommit** for that chain.
+
+Each validator **waits** to receive **enough precommits** to be able to finalize
+
+- We again find the **common ancestor** of the **estimate** which has **threshold precommits**
+- We declare that **block** as **finalized**
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-5.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-6.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+The **round** is deemed **completable**:
+
+- if the **estimate** is **lower** than the **prevote GHOST**
+- or if it's **impossible** to have a **supermajority** on any **block higher** than the current **estimate**
+
+Validators **start** a **new round** after it becomes **completable**.
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-6.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-7.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-8.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round (Alt)
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-6.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round (Alt)
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-7-alternative.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round (Alt)
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-8-alternative.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## A GRANDPA Round (Alt)
+
+<img style="width: 400px" src="./img/grandpa-round/4.6-grandpa-round-9-alternative.png"/>
+
+Notes:
+
+- 7 = # Validators
+- 5 = # Threshold
+
+---
+
+## Summary
+
+<pba-flex center>
+
+- Networks can be {Synchronous, Asynchronous}
+- Consensus systems can be {Deterministic, Probabilistic}
+- Consensus systems can be {Open participation, Finite participation}
+- There is always an assumption that at least {1/2, 2/3} participants are honest
+- In decentralized systems, we use Economics and Game Theory<br/>to incentivize honest execution of the consensus protocol
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Game Time
+
+> I want to play a game...<br/>a board game!
diff --git a/content/9-Polkadot/8-agile-coretime-slides.md b/content/9-Polkadot/8-agile-coretime-slides.md
new file mode 100644
index 00000000..a845ce41
--- /dev/null
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@@ -0,0 +1,884 @@
+---
+title: Agile Coretime
+description: Details Agile Coretime changes in Polkadot. Covers Bulk Coretime, On-Demand Coretime, Elastic Scaling of Coretime, and the draft pricing model.
+duration: 1 hour
+owner: Maciej Zyszkiewicz
+---
+
+# Agile Coretime
+
+Notes:
+Today we'll be tackling Agile Coretime. How many people heard about it?
+I often see people confused about what coretime truly is, when it comes and what "feature" it is exactly.
+
+---v
+
+# Agile Coretime
+
+## Core Features
+
+- Bulk Coretime Auctions
+- On-Demand Coretime
+- Coretime Interlacing
+- Elastic Scaling
+- Renewals
+- Coretime Markets
+
+Notes:
+In reality agile coretime is a collection of features that all interact with each other to overhaul the way Polkadot manages
+and exposes it's most important resources, execution cores. Essentially it's an alternative scheduling mechanism.
+
+---v
+
+# Agile Coretime
+
+## RFC Disclaimer
+
+<img style="width: 500px" src="./assets/coretime/rfc_1.png"/>
+
+Notes:
+The coretime I will be presenting today is still in development but more than 90% of it has been delivered. The blueprint for it was outlined in the Fellowship RFC 1 and 5 (links in notes) and it is mostly staying true to it but implementation details can be different here and there. Nevertheless the spirit will remain unchanged.
+
+https://github.com/polkadot-fellows/RFCs/blob/main/text/0001-agile-coretime.md
+https://github.com/polkadot-fellows/RFCs/blob/main/text/0005-coretime-interface.md
+
+---v
+
+# Agile Coretime
+
+## JAM Disclaimer
+
+<img style="width: 500px" src="./assets/coretime/jam.png"/>
+
+Notes:
+And we can go further because more importantly coretime will carry over into the future when the chain migrates to JAM. In fact Jam needs coretime as a dependency so what we are learning here will remain very relevant in the upcoming years.
+
+https://graypaper.com/
+
+---
+
+# The Product of Polkadot
+
+**What is the product?**
+
+Notes:
+First let’s zoom out and look at the Polkadot protocol. What does it actually produce? And I don’t mean the individual parachains but the core protocol (mostly living on the relay chain) itself.
+
+---v
+
+# The Product of Polkadot
+
+## Blockspace
+
+<img style="width: 500px" src="./assets/coretime/blockspace.png"/>
+
+Notes:
+It is blockspace! Blockspace is the data that we guarantee consensus on and provide availability for. And not only is it blockspace, it is high quality blockspace.
+The quality is referring to how confidence in it being secure and live, it needs to be durable system that stood the test of time.
+
+---v
+
+# The Product of Polkadot
+
+## Sharding
+
+<img style="width: 500px" src="./assets/coretime/polkadot-architecture.svg"/>
+
+Sharding allows us to produce more blockspace with the same resources
+
+Notes:
+And because Polkadot is effectively sharded it can validate in parallel producing plenty of blockspace.
+
+---v
+
+# The Product of Polkadot
+
+## Blockspace vs Coretime
+
+They are two sides of the same coin. Execution cores enable sharding and they create the highly valuable high quality blockspace.
+
+> (Secure) blockspace is the resource Polkadot provides, which is measured in and allocated through coretime.
+
+Notes:
+There are some caveats to it, but generally coretime and blockspace are very highly coupled in Polkadot. The more coretime you have the more blockspace you gain out of it.
+Coretime is presenting a more execution based perspective and blockspace paints it in a data oriented way.
+
+---v
+
+# The Product of Polkadot
+
+## Pricing blockspace
+
+<img style="width: 300px" src="./assets/coretime/tokens.png"/>
+
+Blockspace needs to be priced and distributed to those that need it.
+
+Notes:
+But for this blockspace to be utilized we need to find appropriate clients and sell it to them. Generally sovereign and usually commercial parachains were the main consumers of blockspace so in what form was it sold and how were they acquiring it?.
+
+---
+
+# Parachain Leases
+
+Notes:
+Originally blockspace was sold in the form of leases.
+
+---v
+
+# Parachain Leases
+
+Lease gave you the right to register your parachain and fully occupy a specific core.
+
+A core is able to validate a single block every 6s and leases were practically always 2 years.
+
+<img  src="./assets/coretime/para.svg"/>
+
+Note:
+This design was very strictly defining the amount and frequency of the blockspace being sold. Teams could only buy the right to validate a single block every 6s for up to 2 years. That is committing to roughly 175 000 blocks! We called that commitment a lease. And most parachains to this day still operate on those leases.
+
+---v
+
+# Parachain Leases
+
+Lease gave you the right to register your parachain and fully occupy a specific core.
+
+A core is able to validate a single block every 6s and leases were practically always 2 years.
+
+<img  src="./assets/coretime/para_0.svg"/>
+
+Note:
+2 years is a really looo-
+
+---v
+
+# Parachain Leases
+
+Lease gave you the right to register your parachain and fully occupy a specific core.
+
+A core is able to validate a single block every 6s and leases were practically always 2 years.
+
+<img  src="./assets/coretime/para_1.svg"/>
+
+Note:
+ooo-
+
+---v
+
+# Parachain Leases
+
+Lease gave you the right to register your parachain and fully occupy a specific core.
+
+A core is able to validate a single block every 6s and leases were practically always 2 years.
+
+<img  src="./assets/coretime/para_2.svg"/>
+
+Note:
+ooo-
+
+---v
+
+# Parachain Leases
+
+Lease gave you the right to register your parachain and fully occupy a specific core.
+
+A core is able to validate a single block every 6s and leases were practically always 2 years.
+
+<img  src="./assets/coretime/para_3.svg"/>
+
+Note:
+-ong time.
+In reality teams could opt for a bit of a shorter time than two years but historically nearly none of them actually bid for periods lower than two years. Turns out that teams actually really really value long-term stability. Let’s remember that. It’s gonna come up.
+
+---v
+
+# Parachain Leases
+
+## Slot Auctions
+
+Leases are acquired on candle auction called Slot Auctions
+
+Notes:
+So now we know what is being sold so how was it sold? Every once in a while when an execution core was unscheduled it was being put up to a slot auction. A slot auction aimed to find a parachain that would occupy it for the next two years. The auction was a candle auction for those that remember how they work. Anyone wants to quickly remind us?
+
+---v
+
+# Parachain Leases
+
+## Slot Auctions
+
+<img  src="./assets/coretime/slot_auctions.png"/>
+
+Notes:
+The auctions required huge amounts of DOT tokens. Often millions of dollars. So to allow amazing but poorly funded teams to flourish a crowd loan system was created. It allowed normal token holders to pool their dot together and lend them to the team. Those tokens were then used to secure a bid in the auction. Of course the token holders were not doing it for free. They were expecting some rewards in return coming from the team behind the project.
+
+https://parachains.info/auctions/polkadot-60-66
+
+---v
+
+# Parachain Leases
+
+## Slot Auctions
+
+Tokens were **refunded** after the lease was over
+
+<img style="width: 300px" src="./assets/coretime/rewards.svg"/>
+
+What was the cost?
+
+Notes:
+And now the most interesting bit after the lease was over the funds were returned to the original owners. Wait?! So what was the cost in that case if they just got them back? Was it free?
+
+---v
+
+# Parachain Leases
+
+## Issues
+
+Why is Polkadot deprecating slot auctions and leases?
+
+Notes:
+Today things are changing but to understand why let’s look at some of the pain points of the original system.
+
+---v
+
+# Parachain Leases
+
+## Issues
+
+- Most parachains didn't fully fill up their blocks (wasted blockspace)
+- ...
+- ...
+- ...
+- ...
+
+Notes:
+Leases were very inflexible and in reality not many blockchains needed as much as a huge block every 6s. There was literally too much throughput for most use cases! But you still had to purchase the whole thing giving you blocks every 6s so the rest was waste
+
+---v
+
+# Parachain Leases
+
+## Issues
+
+- Most parachains didn't fully fill up their blocks (wasted blockspace)
+- Very long commitments
+- ...
+- ...
+- ...
+
+Notes:
+Not only the throughput was massive but the duration of the commitment was very long so small teams couldn’t really compete for slots as teams of erring longer commitments had priority
+
+---v
+
+# Parachain Leases
+
+## Issues
+
+- Most parachains didn't fully fill up their blocks (wasted blockspace)
+- Very long commitments
+- Very large DOT amounts were needed to secure slots
+- ...
+- ...
+
+Notes:
+As mentioned before the amounts of tokens needed were huge. That is a huge responsibility and pressure for a few devs that just
+want to build something cool without too much friction. Bidding with millions of dollars is no joke.
+
+---v
+
+# Parachain Leases
+
+## Issues
+
+- Most parachains didn't fully fill up their blocks (wasted blockspace)
+- Very long commitments
+- Very large DOT amounts were needed to secure slots
+- Some parachains overfilled their blocks
+- ...
+
+Notes:
+I mentioned some parachains underfilled their blocks, well some others in fact overfilled them! There were some amazingly successful
+projects that were bottlenecked as single core producing blocks every 6s was not enough for them.
+
+---v
+
+# Parachain Leases
+
+## Issues
+
+- Most parachains didn't fully fill up their blocks (wasted blockspace)
+- Very long commitments
+- Very large DOT amounts were needed to secure slots
+- Some parachains overfilled their blocks
+- Lease Auctions and Crowd Loans were huge endeavors causing major overhead
+
+Notes:
+And finally slot auctions were a noticeable burden for the teams. Every two years they had to significantly plan around them to garner support, funds, promise a reward scheme for the crowd loans and figure out strategically how to bid at the auctions.
+
+---
+
+# Agile Coretime Mission
+
+- Waste less blockspace
+- Allow for higher max throughout
+- Lower the barriers of entry
+- Maintain some price predictability
+- Remove or simplify the overhead
+
+Notes:
+This is pretty much a direct response to the issues we just listed a moment ago. Agile coretime aims to remove any artificial systemic barriers
+and expand on how builders can utilize the underlying resources of Polkadot. So let's look at how coretime aims to actually achieve that!
+
+---
+
+# Bulk Auctions
+
+Notes:
+We'll start with a method that should be the most familiar and in fact very similar to the old slot auctions - bulk auctions.
+
+---v
+
+# Bulk Auctions
+
+## What is being sold?
+
+Parablock every 6s for 28 days
+
+<img  src="./assets/coretime/para.svg"/>
+
+Notes:
+So how much coretime are we selling this time around? Bit less then previously but still a large chunk of it - a whole bulk of coretime.
+
+---v
+
+# Bulk Auctions
+
+## What method?
+
+Dutch Auctions
+
+<img style="width: 600px" src="./assets/coretime/dutch.jpeg"/>
+
+Notes:
+And to sell all of that we are using the classic dutch auctions. In that case the price decreases over the span
+of weeks so it's not as rapid as the traditional ones, but the principle remains.
+
+---v
+
+# Bulk Auctions
+
+## Where do the funds go?
+
+Price paid will no longer be returned after the "lease" is over. This time the cost is paid upfront instead of
+implicitly through the opportunity cost of locking your funds like in crowd loans.
+
+Notes:
+CUrrent dominant strategy agreed on by the community is to burn the coretime profits. TLDR why is that volatile flows to the treasure are not healthy and introduce complex game theoretical attacks. Read more here: https://github.com/polkadot-fellows/RFCs/blob/main/text/0010-burn-coretime-revenue.md
+
+---v
+
+# Bulk Auctions
+
+## Pricing
+
+Price adapter cycle:
+
+- System starts at target price X
+- Dutch auction initiate with 10X (much more then we expect to sell it for)
+- Price drops to X over a week
+- Price drops to 10% of X over the next week which is the minimum
+- The core sold at the lowest price (or minimum price if no sales) becomes new target price
+
+Notes:
+Pricing could be it's own lecture but to keep it brief. The system starts with some default price X. The dutch auctions enters what we call a leadin period, a period where the price will steeply decrease from 10x to x over a week and then from x to x/10 over the next week. Then it's just a matter of setting a new target price for the next sale. Sales happen every 28 days.
+
+---v
+
+# Bulk Auctions
+
+## Pricing
+
+<img style="width: 500px" src="./assets/coretime/bulk_pricing.png"/>
+
+Notes:
+This very roughly approximates an exponential decay curve with three linear functions. We are actually in discussions to make it smooth and make the potential scope of prices even wider.
+
+---v
+
+# Bulk Auctions
+
+## Leases repackaged?
+
+<img style="width: 500px" src="./assets/coretime/spider.jpg"/>
+
+Notes:
+Although despite this difference at this point you might be asking, hey, this is nearly exactly the same as the method
+before. How is that even new or better? Because that bulk you buy carries a lot more information and flexibility than previous leases.
+
+---v
+
+# Bulk Auctions
+
+## Coretime Regions
+
+Leases when bought were instantly fixed and unchangeable.
+
+Coretime regions are NFTs that are transferrable and programmable\*.
+
+Notes:
+Previously to exchange leases teams had to go through governance and create a referendum. This time coretime regions can easily be reassigned to a different parachain.
+This allows interested parties to buy some off the auction and sell it off for a fixed price to others. Teams that don't want to deal with auctions can
+source it through those brokers. We'll talk about them more soon but region reassignment is just the first step towards coretime programmability. So
+let's now look at interlacing.
+
+---v
+
+# Interlacing
+
+Notes:
+This is the truly exciting stuff. That was fully impossible before.
+
+---v
+
+# Interlacing
+
+<img style="width: 700px" src="./assets/coretime/no_interlacing.svg"/>
+
+Notes:
+So with no interlacing someone could utilize bulk like this. Just naively put out a block every 6s.
+
+---v
+
+# Interlacing
+
+Interlacing two or more different parachains means they can be co-scheduled onto the same execution core.
+
+Notes:
+I hope the name this time around is actually pretty self-descriptive. Interlacing allows to weave two or more different parachains on the
+same core. They might be taking turns or using any other arbitrary co-scheduling pattern.
+
+---v
+
+# Interlacing
+
+## Example
+
+<img style="width: 700px" src="./assets/coretime/interlacing.svg"/>
+
+Notes:
+A concrete example of that would be two parachains coscheduled onto the same core. They would take turns in producing blocks so each on will effectively have a 12s block time.
+
+---v
+
+# Interlacing
+
+## Mask Programmability
+
+Interlacing is achieve through manipulating the coretime region bit masks.
+
+Freshly bought coretime region from the bulk auction would be fully scheduled (complete):
+
+<img style="width: 700px" src="./assets/coretime/complete_mask.svg"/>
+
+---v
+
+# Interlacing
+
+## Mask Programmability
+
+Two parachains interlaced together would split the region into 2 complementary regions:
+
+<img style="width: 700px" src="./assets/coretime/interlaced_regions_masks.svg"/>
+
+Notes:
+
+---v
+
+# Interlacing
+
+## Mask Programmability
+
+Interlacing always should create masks that complement each other (XOR to 1):
+
+<img style="width: 700px" src="./assets/coretime/mask_interlacing.svg"/>
+
+Notes:
+
+---v
+
+# Interlacing
+
+<img style="width: 700px" src="./assets/coretime/triple_interlace.png"/>
+
+Notes:
+This can be pushed quite far triple co-scheduling is not an issue at all and if you want a parachain that makes a block only every 1000th slots you can!
+
+---v
+
+# Interlacing
+
+How to find other parachains willing to interlace with you? And is it all easy to do?
+
+Notes:
+The question is where does this interlacing happen from the user interface perspective? How to find other parachains willing to interlace
+with you? This is where the secondary markets come in.
+
+---
+
+# Secondary Markets
+
+---v
+
+# Secondary Markets
+
+RFC-1:
+
+> "[Agile Coretime] supports the possibility of building rich and dynamic secondary markets to optimize resource allocation and largely avoids the need for parameterization."
+
+Notes:
+Coretime was built with secondary markets in mind. Those would be the interfaces where bulk coretime is bought, then split into smaller regions and potentially sold off to others.
+
+---v
+
+# Secondary Markets
+
+## Current Solutions
+
+<img style="width: 700px" src="./assets/coretime/regionx_land.png"/>
+
+Notes:
+
+https://www.regionx.tech/
+
+---v
+
+# Secondary Markets
+
+## Current Solutions
+
+<img style="width: 700px" src="./assets/coretime/lastic_land.png"/>
+
+Notes:
+
+https://www.lastic.xyz/
+
+---v
+
+# Secondary Markets
+
+## What to expect?
+
+<img style="width: 700px" src="./assets/coretime/regionx.png"/>
+
+---v
+
+# Secondary Markets
+
+## What to expect?
+
+<img style="width: 700px" src="./assets/coretime/lastic.png"/>
+
+Notes:
+Interfaces for buying or auto-bidding on bulk auctions
+Splitting and interlacing automation.
+Automatic renewals.
+Coretime futures (maybe?)
+Who knows what else!
+
+---
+
+# On-Demand Coretime
+
+---v
+
+# On-Demand Coretime
+
+## Disclaimer
+
+**On-Demand Coretime** = Parathreads = Instantaneous Coretime
+
+Note:
+Naming is hard. Parathreads was the original name for that concept that was a part
+of the design since 1.0 days. On-Demand is the generally accepted term nowadays. But seeing this slide I just couldn't stop myself. We already had the version with two but now we graduated to three.
+
+---v
+
+# On-Demand Coretime
+
+## Disclaimer
+
+<img style="width: 500px" src="./assets/coretime/spider3.jpg"/>
+
+Note:
+
+---v
+
+# On-Demand Coretime
+
+## Limitations of Interlacing and Coretime Regions
+
+- Awesome flexibility ✅
+- Requires week-long comittment ❌ (good enough for most)
+
+Notes:
+Interlacing was giving a lot of flexibility in terms of how much throughput and latency you want, but generally you were still committing to it in advance, often even up to weeks before using it.
+
+---v
+
+# On-Demand Coretime
+
+What if we don't even know if we'll need a core in 5 minutes?
+
+On-demand is an **alternative** native method of acquiring coretime that focuses on low latency.
+
+Notes:
+What if we need to more dynamically react to the demand? What if we only want to tinker and play with Polkadot temporarily? On-demand is aiming to solve that by being an alternative native method of acquiring coretime.
+
+---v
+
+# On-Demand Coretime
+
+## Analogy to Cloud Spot Compute
+
+Notes:
+Anyone here has heard of AWS Spot Instances? Or maybe Google Cloud Spot?
+
+---v
+
+# On-Demand Coretime
+
+On-Demand allows to purchase a single block worth of coretime on a very short notice (6-12s).
+
+---v
+
+# On-Demand Coretime
+
+## Core Use Cases
+
+- Temporary parachains
+- Tinkering and experimentation
+- Low latency applications that produce very infrequently (certifications, etc.)
+
+Notes:
+On-demand is perfect when someone’s wants to tinker and only temporarily make a few blocks or maybe for business that produces blocks very rarely and infrequently. Maybe you have an app that rarely get used but when it does it is crucial to quickly execute it with low latency, then hibernating until you get a transaction a only then emitting a single on-demand block is perfect for you!
+
+---v
+
+# On-Demand Coretime
+
+## On-Demand Core Pool
+
+Governance dedicated a fixed minimal amount of cores to be solely available for on-demand use (**on-demand core pool**), but there is a way to further expand
+the on-demand core pool we'll cover later.
+
+Notes:
+Governance dedicated a fixed minimal amounts of cores to be solely available for on-demand use, but there is a way to further expand
+the on-demand core pool we'll cover later. So to summarize most cores will be sold as bulk and then split, interlaced or used directly. Rest of cores
+goes into the on-demand pool and can be purchased well... on-demand.
+
+---v
+
+# On-Demand Coretime
+
+## Pricing
+
+On-demand pricing is detached from the bulk auction pricing.
+
+It's a separate free market system where price is adapted based on the demand and current supply.
+
+<img style="width: 500px" src="./assets/coretime/market_eq.drawio.svg"/>
+
+Notes:
+On-demand pricing is detached from the bulk auction pricing.
+
+It's a separate free market system where price is adapted based on the demand and current supply.
+
+When not enough orders come through price can lower and when there is a backlog of pending orders price goes up.
+
+---
+
+# Elastic Scaling
+
+Notes:
+Now we covered the cases of small and more sporadic uses. What about the big fish, the parachains that are not satisfied with a mere single core?
+
+---v
+
+# Elastic Scaling
+
+What if a single core is not enough for a large parachain project? 🐋
+
+Notes:
+What can they do scale further?
+
+---v
+
+# Elastic Scaling
+
+## Not just a hypothetical
+
+Projects like Moonbeam and soon Mythical are definitely capable of fully utilizing a single core.
+
+<img style="width: 250px" src="./assets/coretime/mythical.png"/>
+
+Early projections show that Mythical will need 2-3 cores (although async backing might lower this demand)
+
+Notes:
+Mythical is coming over to Polkadot with a pretty mature fanbase and a few already successful commercial products. And one big reason why the chose Polkadot is because they can build here what they could not in other decentralised chains, because of our superb scalability. They are projected to need 2-3 cores to fully utilize the blockspace. But they are also looking into async backing which might lower this demand.
+
+---v
+
+# Elastic Scaling
+
+Assume Parachain A is running out of blockspace:
+
+<img style="width: 500px" src="./assets/coretime/elastic_1.svg"/>
+
+Notes:
+We see 2 parachains. Let's assume A is running out of space. They fully utilize the blocks every 6s. Core 2 sits empty there is no 3rd parachain that would like to register.
+
+Looking at this diagram, even if you don't know about coretime I feel like the answer is just too obvious.
+
+---v
+
+# Elastic Scaling
+
+With Elastic Scaling Parachain A can purchase more cores and produce blocks on all of them to get more blockspace:
+
+<img style="width: 500px" src="./assets/coretime/elastic_2_fork.svg"/>
+
+Notes:
+With Elastic Scaling Parachain A can purchase more cores and produce blocks on all of them to get more blockspace. But does anyone see an issue with that? At least based on that diagram.
+
+---v
+
+# Elastic Scaling
+
+Parachain A needs to still produce blocks sequentially so now there needs to be an inner ordering between cores:
+
+<img style="width: 500px" src="./assets/coretime/elastic_2_ordered.svg"/>
+
+Notes:
+This Increases the strain on collators as they not only have to produce multiple blocks per 6s but also share them to the next collator in the chain so they can import and potentially build their collation dependant on it. We generally limit elastic scaling to 3-4 cores max.
+
+---
+
+# Elastic Scaling
+
+- 1 core = 2s ref time with 6s block time and 1.6mb/s DA
+- 3 cores = 6s ref time with 2s block time and 5mb/s DA
+- 12 cores = 6s ref time with 0.5s block time and 20mb/s DA
+
+---
+
+# Renewals
+
+Notes:
+Remember when we discussed how in the old auction model vast majority of teams opted for maximum duration leases of 2 years? Why did they do it?
+
+---v
+
+# Renewals
+
+## Value of Long-Term Stability
+
+Business don't like uncertainty. They want to know they can operate for a long time and budget for their expenses.
+
+<img style="width: 900px" src="./assets/coretime/volatility.png"/>
+
+If every spike on the graph endangers your business you will build it elsewhere.
+
+Notes:
+See that spike around 2021? Gas fees went from 20-30 to 700. Imagine you suddenly can't run your business because the gas is too high. That's a no-go for any serious business. So long-term stability is crucial for any business.
+
+---v
+
+# Renewals
+
+## Price Stability Guarantee
+
+Renewals are a special sort of treatment for teams that value long-term stability extremely highly.
+
+If you don't interlace or split your coretime region and you fully utilize it then you can renew it for the same price you bought it for + small percentage (4% currently).
+
+---v
+
+# Renewals
+
+## Price Stability Guarantee
+
+Renewals can be made in the interlude phase before the actual bulk auction starts:
+
+<img style="width: 500px" src="./assets/coretime/bulk_pricing.png"/>
+
+Notes:
+Making a renewal increases your costs but it gives a solid cap for how much they can increase allowing you to budget well into the future. Additionally if the target price in the market drops heavily the renewal price can also be lowered, but the growth is always capped.
+
+---v
+
+# All Together
+
+Notes:
+Now comes the best part. What happens when all those features go live? They can be combined to fully utilize what Polkadot has to offer.
+
+---v
+
+# All Together
+
+## Leases Landscape
+
+<img style="width: 500px" src="./assets/coretime/dumb_coretime.png"/>
+
+Notes:
+In general we are hoping to migrate from a mundane and inflexible system like this.
+
+---v
+
+# All Together
+
+## Agile Coretime Landscape
+
+<img style="width: 800px" src="./assets/coretime/agile_coretime.png"/>
+
+Notes:
+To a much more free market model where blockspace can be freely allocated, interlaced, exchanged, scaled etc. Giving away the freedom to the users and allowing them to fully utilize the resources of Polkadot.
+
+---v
+
+# All Together
+
+## Agile Coretime Combinations
+
+- On-Demand cores work for Elastic Scaling allowing for quick scaling up and down based on demand
+- Bulk Auctions + On-Demand -> Coretime Regions can be sold to the On-Demand Core Pool to extend its size which can generate profit for the seller
+
+---
+
+# The Coretime Chain
+
+Bulk Auctions and vast majority of the low level interfaces live not on the relay chain but a brand new Coretime Broker Chain
+
+---
+
+# Resources
+
+Check notes!
+
+Notes:
+
+RFCs:
+https://github.com/polkadot-fellows/RFCs/blob/main/text/0001-agile-coretime.md
+https://github.com/polkadot-fellows/RFCs/blob/main/text/0005-coretime-interface.md
+https://github.com/polkadot-fellows/RFCs/blob/main/text/0010-burn-coretime-revenue.md
+
+Bulk pricing blog post by Robert (Parachains lead):
+https://grillapp.net/12935/agile-coretime-pricing-explained-166522?ref=29715
+
+W3F coretime guide:
+https://guide.kusama.network/docs/learn-agile-coretime
+
+Interview with Rob H. co-founder of Parity and major contributor to the ideas behind coretime:
+https://www.youtube.com/watch?v=mH2ABBErpTw
+
+Check out Lastic and RegionX
diff --git a/content/9-Polkadot/9-polkadot-ecosystem-economy-slides.md b/content/9-Polkadot/9-polkadot-ecosystem-economy-slides.md
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+---
+title: Polkadot Ecosystem and Economy
+description: A review of the parts of Polkadot which develop its ecosystem and economy.
+duration: 1 hour
+owner: Maciej Zyszkiewicz (Shawn Tabrizi originally)
+---
+
+# Ecosystem and Economy
+
+---
+
+## Ecosystem and Economy
+
+This presentation will give you a high level overview of the ecosystem and economy of the Polkadot Network.
+
+Unfortunately this presentation could never be fully exhaustive, but perhaps it will shed light on areas previously unknown.
+
+---
+
+# Economy
+
+---
+
+## The DOT Token
+
+<div class="grid grid-cols-2">
+
+<div>
+
+<image src="../../assets/img/7-Polkadot/eco/token.avif" style="width: 400px;">
+
+</div>
+
+<div class="text-left">
+
+DOT is the native token of the Polkadot Network.
+
+DOT tokens can be in one of the following states:
+
+1. Transferable
+2. Frozen (Locked)
+3. Held (Reserved)
+
+</div>
+
+</div>
+
+---
+
+## Frozen vs Held Balance
+
+- Old terms "Reserved" and "Locked" are on their way out...
+- DOT in both states belong to the user... but cannot be spent / transferred.
+- Held balances stack on top of one another.
+  - Useful for user deposits, or other use cases where there is sybil concerns.
+  - Ex: Deposit for storing data on-chain,
+- Frozen balances can overlap each other.
+  - Useful when you want to use the same tokens for multiple use cases.
+  - Ex: Using the same tokens for both staking and voting in governance.
+
+---
+
+## Storage Bloat
+
+One blockchain scaling problem is storage bloat over time.
+
+<br />
+
+Consider the "cost" of storing data on Ethereum:
+
+- A one time gas fee based on the amount of data stored.
+- Once is it placed on the network, it lives there forever, with no additional costs.
+- Over a long enough period of time, the cost of storage per time will reduce to zero.
+
+---
+
+## Storage Deposits
+
+To solve this problem, Polkadot additionally takes a storage deposit (in the form of Reserved Balance) for any data stored in the blockchain.
+
+- This deposit is returned to the user when the user removes the data from the chain.
+
+- This deposit can be quite extreme, since it is returned to the user, and can represent the impermanence or lack of "importance" of the data.
+
+---
+
+## Dust Accounts & Existential Deposit
+
+The most bloat-ful storage on most blockchains are user accounts:
+
+- Both Ethereum and Bitcoin are riddled with "dust accounts" which have such a small balance, they are not worth "cleaning up".
+
+- Polkadot solves this by having an "existential deposit" that all users must hold a minimum amount of DOT, else their account data will be cleaned up.
+
+- Existential deposit can be thought of as a storage deposit for account data.
+
+---
+
+## Scaling with Data Sharding
+
+- Polkadot is already designed to scale by sharding data.
+  - Polkadot only needs to store the merkle root representing large amounts of data.
+- The cost to store data on shards are orders of magnitude cheaper.
+  - We can have decreased storage deposits on these shards:
+    - ED: 1.0 DOT on Polkadot -> .01 DOT on Asset Hub
+    - Identity: 20 DOT on Polkadot -> .2 DOT on People Chain
+
+---
+
+## DOT is a Utility Token
+
+<div class="grid grid-cols-3">
+
+<div>
+
+<image src="../../assets/img/7-Polkadot/eco/utility.avif" style="width: 500px;">
+
+</div>
+
+<div class="text-left col-span-2">
+
+The DOT token serves multiple purposes to help the Polkadot network function:
+
+- Purchasing Blockspace
+- Staking
+- On-Chain Decision Making
+- Value Bearing for Trading / Using
+
+</div>
+</div>
+
+---
+
+## DOT Inflation
+
+<div class="grid grid-cols-2">
+
+<div>
+
+<image src="../../assets/img/7-Polkadot/eco/inflation.svg" style="width: 500px;">
+
+</div>
+
+<div class="text-left">
+
+DOT is currently configured to have a fixed inflation rate of 10% per year.
+
+Newly minted tokens are distributed to the treasury and stakers (validators / nominators).
+
+RFC for Flexible Inflation: https://github.com/polkadot-fellows/RFCs/pull/89
+
+</div>
+
+</div>
+
+---
+
+## Ideal Staking Rate
+
+- We cannot force / tell users how to use their tokens.
+  - So we encourage "ideal" behavior by associating DOT token usage to how inflation is distributed.
+  - There’s a function that redirects staking inflation to the Treasury, instead of the stakers, when `ideal_rate != staking_rate`.
+  - Token holders are financially incentivized to maximize their staking returns, and thus distribute their tokens appropriately.
+- Ideal Staking Rate is in the process of being adjusted since the introduction of coretime sales:
+  - https://forum.polkadot.network/t/adjusting-polkadots-ideal-staking-rate-calculation/3897
+
+---
+
+## DOT Inflation vs Staking
+
+<image src="../../assets/img/7-Polkadot/staking-rate.png" style="width: 900px;">
+
+> Blue: Inflation vs Staking Rate
+>
+> Green: APY of Stakers vs Staking Rate
+>
+> Black: Total Inflation vs Staking Rate
+
+Notes:
+
+Blue line shows that:
+
+- When there is too little being staked, validators are encouraged to stake more.
+- When there is too much being staked, validators are encouraged to stake less.
+
+Green line shows that validator APY goes down whenever more validators enter the staking system, that is unavoidable, but specifically past the ideal staking rate, the decrease in APY sharply decreases.
+
+Black line shows that inflation for for the whole network is fixed at 10%.
+
+The gap between the blue line and the black line shows the amount of inflation that is forwarded to the treasury, as compared to given to validators.
+Event at the ideal staking rate, some percentage of the inflation is guaranteed to go to the treasury.
+
+---
+
+## DOT Utility: Purchasing Blockspace
+
+Polkadot provides many utilities, but arguably its most important utility is providing flexible, secure, and scalable blockspace.
+
+Developers can purchase this blockspace **only** with the DOT token.
+
+<br />
+
+> If you believe that flexible and secure blockspace has value, then you agree that DOT also has value.
+
+---
+
+## Evolution of the Blockspace Marketplace
+
+<div class="grid grid-cols-3">
+
+<div>
+
+<img style="width: 400px;" src="../../assets/img/7-Polkadot/decisions/original-scheduling.png" />
+
+</br></br>
+
+<img style="width: 400px;" src="../../assets/img/7-Polkadot/decisions/exotic-scheduling.png" />
+
+</div>
+
+<div class="col-span-2">
+
+- Initially blockspace was only sold in 2 year slots, in the form of Parachain auctions.
+- We recently transitioned to agile coretime which allows more flexible access to blockspace.
+  - Coretime sales use periodic dutch auctions.
+- JAM will continue to increase the flexibility of allocating and distributing blockspace.
+- Exactly how blockspace is allocated and sold will continue to evolve over time.
+
+</div>
+
+</div>
+
+Notes:
+
+- https://forum.polkadot.network/t/initial-coretime-pricing/5187
+- https://grillapp.net/12935/agile-coretime-pricing-explained-166522
+- https://www.youtube.com/watch?v=ci-h9zC-57Y
+- https://twitter.com/rphmeier/status/1797339044893917397
+
+---
+
+## DOT Utility: Staking
+
+<div class="grid grid-cols-3">
+
+<div class="col-span-2 text-left">
+
+Given the existence of a value bearing token, it can be used to provide security to Polkadot:
+
+- If users want to provide security to the network, they can stake their tokens.
+
+- Stakers are rewarded for good behavior, and punished for bad behavior.
+
+- Punishment is designed to maximize the costs for a rational actor and thereby deter misbehavior.
+
+https://polkadot.network/features/staking/
+
+</div>
+
+<div>
+
+<image src="../../assets/img/7-Polkadot/eco/staking.svg" style="width: 400px;">
+
+</div>
+
+</div>
+
+---
+
+## Staking: Validators and Nominators
+
+<div class="grid grid-cols-3">
+
+<div class="col-span-2 text-left">
+
+In the staking system, there are two roles:
+
+- Validators: Those who run block producing / parachain validating nodes for Polkadot.
+- Nominators: Users who place their tokens behind validators they think will perform their job well.
+
+Validators (and their nominators) are rewarded based on work done for the network. Rewards may vary day to day, but should be consistent over long periods of time.
+
+</div>
+
+<div>
+
+<image src="../../assets/img/7-Polkadot/eco/collab.svg" style="width: 400px;">
+
+</div>
+
+</div>
+
+---
+
+## DOT Utility: Governance
+
+<div class="grid grid-cols-3">
+
+<div class="col-span-2 text-left">
+
+The future of Polkadot is decided by token holders.
+
+Polkadot has an on-chain governance system called OpenGov which is used to:
+
+- Spend Treasury Funds
+- Upgrade the Network
+- Manage the Fellowship
+- Support Parachain Teams
+- etc...
+
+https://polkadot.network/features/opengov/
+
+</div>
+
+<div>
+
+<image src="../../assets/img/7-Polkadot/eco/governance.avif" style="width: 500px;">
+
+</div>
+
+</div>
+
+---
+
+## Conviction Voting
+
+Polkadot utilizes an idea called voluntary locking / conviction voting.
+
+This allows token holders to increase their voting power by locking up their tokens for a longer period of time.
+
+```text
+votes = tokens * conviction_multiplier
+```
+
+The conviction multiplier increases the vote multiplier by one every time the number of lock periods double.
+
+<div class="text-small">
+
+| Lock Periods | Vote Multiplier | Length in Days |
+| ------------ | --------------- | -------------- |
+| 0            | 0.1             | 0              |
+| 1            | 1               | 7              |
+| 2            | 2               | 14             |
+| 4            | 3               | 28             |
+| 8            | 4               | 56             |
+| 16           | 5               | 112            |
+| 32           | 6               | 224            |
+
+</div>
+
+---
+
+## Tracks
+
+The OpenGov system has different voting tracks which have different levels of power, and proportionally different level of difficulty to pass.
+
+Here are just some of the currently 15 tracks:
+
+| ID  |       Origin       | Decision Deposit | Prepare Period | Decision Period | Confirm Period | Min Enactment Period |
+| :-: | :----------------: | :--------------: | :------------: | :-------------: | :------------: | :------------------: |
+|  0  |        Root        |    100000 DOT    |    2 Hours     |     28 Days     |     1 Day      |        1 Day         |
+|  1  | Whitelisted Caller |    10000 DOT     |   30 Minutes   |     28 Days     |   10 Minutes   |      10 Minutes      |
+| 10  |   Staking Admin    |     5000 DOT     |    2 Hours     |     28 Days     |    3 Hours     |      10 Minutes      |
+| 11  |     Treasurer      |     1000 DOT     |    2 Hours     |     28 Days     |    3 Hours     |        1 Day         |
+| 12  |    Lease Admin     |     5000 DOT     |    2 Hours     |     28 Days     |    3 Hours     |      10 Minutes      |
+
+---
+
+## Approval and Support Curves
+
+Each track has their own set of curves which determine if the proposal has passed or failed.
+
+All votes will eventually resolve one way or another.
+
+<image src="../../assets/img/7-Polkadot/eco/pjs-curves.png" style="width: 1000px;">
+
+You can find these curves on the Polkadot JS Developer Console.
+
+---
+
+## Example: Root
+
+The origin with the highest level of privileges. Requires extremely high levels of approval and support for early passing. The prepare and enactment periods are also large.
+
+<image src="../../assets/img/7-Polkadot/eco/root-curve.png" style="width: 800px;">
+
+For instance, a referendum proposed in this track needs to amass 48.2% support (total network issuance) by the end of the first day with over 93.5% approval to be considered to be part of the confirm period.
+
+---
+
+## Governance Token Mechanics
+
+- DOT tokens are frozen when you vote on a proposal.
+- You can reuse your frozen tokens across multiple proposals.
+  - Voting for one proposal does not affect your ability to vote on another proposal.
+- You can also reuse staked tokens (which are also just frozen).
+- You can update your vote while the proposal is ongoing.
+- If you used conviction voting, your tokens might be frozen for long periods of time passed the end of a proposal.
+
+---
+
+## Treasury
+
+<div class="grid grid-cols-3">
+
+<div class="text-left col-span-2">
+
+Polkadot has an on-chain treasury which is used to support permissionless and decentralized development of the network.
+
+- Treasury gets its funds through inflation, slashing, and by taking 80% transaction fees.
+
+- Treasury will automatically burn a 1% of its funds every spending period (24 days), placing pressure on spending the tokens.
+
+</div>
+
+<div>
+
+<img style="width: 500px;" src="../../assets/img/7-Polkadot/decisions/treasury.svg" />
+
+</div>
+
+</div>
+
+---
+
+## Treasury Outlets
+
+- Proposals: Instant payments to individuals approved by governance.
+- Bounties: Multi-stage payments to individuals managed by governance and an appointed bounty curator.
+- Tips: Small payments to individuals that can be made more easily through specific governance tracks.
+
+The Polkadot Treasury currently has over 22,000,000 DOT. (June 2024)
+
+---
+
+# Ecosystem
+
+---
+
+## A Future Full of Clients
+
+The Web3 Foundation is allocating 10 Million DOT for creating a diverse ecosystem of Polkadot clients.
+
+<img style="width: 1200px;" src="../../assets/img/7-Polkadot/eco/jam-clients.png" />
+
+This can help provide additional resilience to the network from software bugs.
+
+---
+
+## System Parachains
+
+- System parachains contain core Polkadot protocol features, on a parachain rather than Polkadot itself.
+- **Polkadot uses its own heterogenous sharded scaling technology to scale itself.**
+- System parachains remove transactions from the main Polkadot chain, allowing it to allocate more blockspace to other services.
+- System parachains are allocated blockspace by governance.
+
+Notes:
+
+- https://wiki.polkadot.network/docs/learn-system-chains
+- https://github.com/polkadot-fellows/RFCs/blob/34d26ff1aa343b0cc980afbf2f40c1d5b6a781ea/text/0032-minimal-relay.md
+
+---
+
+## Current and Future System Parachains
+
+Current:
+
+- Asset Hub: Allows creation and registration of tokens (FT & NFTs).
+- Bridge Hub: A chain for managing bridges to other networks.
+- Coretime Chain: responsible for the sales of coretime.
+- Collectives: Acts as a place for coordination of the Polkadot DAOs.
+- Encointer: A third-party built chain providing Proof of Personhood.
+- People Chain: A chain for managing identity and Personhood.
+
+Future:
+
+- Governance: Manage all the various proposals and tracks.
+- Staking: Manage all the validator and nominator logic, rewards, etc...
+- Eventually everything...
+
+Notes:
+
+https://wiki.polkadot.network/docs/learn-system-chains
+
+---
+
+## Market Bought Blockspace
+
+<div class="grid grid-cols-2">
+
+<div>
+
+Anyone with a great idea, and access to DOT token, can launch an application on Polkadot.
+
+Dozens of teams from around the world have already done that, and are taking advantage of the features that Polkadot provides.
+
+With JAM, this will only get easier.
+
+</div>
+
+<div>
+
+<image src="../../assets/img/7-Polkadot/eco/polkadot-parachains.svg" style="width: 500px;">
+
+</div>
+
+</div>
+
+Notes:
+
+https://polkadot.subscan.io/parachain
+
+---
+
+## Ecosystem Verticals
+
+While this list is not exhaustive, some of the verticals we have seen appear in Polkadot are:
+
+<div class="grid grid-cols-5">
+
+<div class="col-span-3">
+
+- Smart Contract Chains
+- Decentralized Finance (DeFi)
+- Decentralized Social (DeSo)
+- Decentralized Identity (DID) Services
+- Tokenization (Real World Assets)
+
+</div>
+
+<div class="col-span-2">
+
+- Gaming
+- NFTs (Music, Art, etc...)
+- Bridges
+- File Storage
+- Privacy
+
+</div>
+
+</div>
+
+Notes:
+
+https://substrate.io/ecosystem/projects/
+
+---
+
+## Wallets
+
+Thanks to the treasury and Polkadot community, a number of different wallets have been developed across the ecosystem.
+
+<image src="../../assets/img/7-Polkadot/eco/wallets.png" style="width: 1200px;">
+
+https://polkadot.network/ecosystem/wallets/
+
+---
+
+## Generic Ledger Support
+
+<div class="grid grid-cols-3">
+
+<div class="col-span-2">
+
+Polkadot has been working with Ledger to provide rich support for the Polkadot network.
+
+Users can get clear visibility into the transactions they are signing, and perform complicated tasks such as batching, multisigs, staking, governance, and more.
+
+</div>
+
+<div>
+
+<image src="../../assets/img/7-Polkadot/eco/ledger.webp" style="width: 500px;">
+
+</div>
+
+</div>
+
+Notes:
+
+- https://forum.polkadot.network/t/polkadot-generic-ledger-app/4295
+
+---
+
+## Block Explorers
+
+- Polkadot-JS Apps Explorer - Polkadot dashboard block explorer. Supports dozens of other networks, including Kusama, Westend, and other remote or local endpoints.
+- Subscan - Blockchain explorer for Substrate chains.
+- 3xpl.com - Universal block explorer and JSON API with Polkadot support.
+- Blockchair.com - Universal blockchain explorer and search engine with Polkadot support.
+- Statescan.io - Polkadot & Kusama Blockchain explorer.
+
+Notes:
+
+https://wiki.polkadot.network/docs/build-tools-index#block-explorers
+
+---
+
+## Governance Dashboards
+
+The most popular ones at the moment:
+
+<div class="grid grid-cols-2">
+
+<div>
+
+### Polkassembly
+
+<image src="../../assets/img/7-Polkadot/eco/polkassembly.png" style="width: 600px;">
+
+</div>
+
+<div>
+
+### Subsquare
+
+<image src="../../assets/img/7-Polkadot/eco/subsquare.png" style="width: 600px;">
+
+</div>
+
+</div>
+
+---
+
+## Polkadot Forum
+
+<image src="../../assets/img/7-Polkadot/eco/forum.png" style="width: 1200px;">
+
+Notes:
+
+https://forum.polkadot.network/
+
+---
+
+## Fellowship
+
+The Polkadot Fellowship is a decentralized technical collective on the Polkadot network designed to recognize, nurture, and incentivize contributors to the core Polkadot protocol.
+
+---
+
+## Fellowship Manifesto
+
+<image src="../../assets/img/7-Polkadot/eco/fellowship-manifesto.png" style="width: 1200px;">
+
+Notes:
+
+https://github.com/polkadot-fellows
+
+---
+
+## Fellowship Members
+
+<image src="../../assets/img/7-Polkadot/eco/fellowship-members.png" style="width: 1200px;">
+
+Notes:
+
+https://polkadot.js.org/apps/?rpc=wss%3A%2F%2Fkusama-rpc.polkadot.io#/fellowship
+
+---
+
+## RFCs
+
+<image src="../../assets/img/7-Polkadot/eco/rfcs.png" style="width: 1200px;">
+
+---
+
+<!-- .slide: data-background-color="#4A2439" -->
+
+# Questions
+
+Did I miss anything?
diff --git a/content/9-Polkadot/README.md b/content/9-Polkadot/README.md
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+# Module 7: Polkadot, Jam & Future
+
+# Schedule
+
+## Day 1 - POLKADOT 2.0
+
+### Morning
+
+1. Polkadot Reintroduction [Maciej]
+1. Staking [Maciej]
+1. Block Production [Maciej]
+1. State Sharding [Maciej]
+1. Data Availability [Maciej]
+
+### Afternoon
+
+1. Execution Sharding [Maciej]
+1. Confirmations and Finality [Maciej]
+1. Agile Coretime [Maciej]
+1. Ecosystem and Economy [Maciej]
+
+## Day 2 POLKADOT 3.0 JAM & Future
+
+### Morning
+
+1. ???
+
+### Afternoon
+
+1. ???
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+<?xml version="1.0" encoding="UTF-8"?>
+<!-- Do not edit this file with editors other than draw.io -->
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diff --git a/content/polkadot/async-backing-shallow/img/exotic_scheduling.svg b/content/9-Polkadot/assets/coretime/exotic_scheduling.svg
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rename from content/polkadot/async-backing-shallow/img/exotic_scheduling.svg
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diff --git a/content/9-Polkadot/assets/coretime/goods.svg b/content/9-Polkadot/assets/coretime/goods.svg
new file mode 100644
index 00000000..46651065
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diff --git a/content/9-Polkadot/assets/coretime/interlaced_regions_masks.svg b/content/9-Polkadot/assets/coretime/interlaced_regions_masks.svg
new file mode 100644
index 00000000..8a596f32
--- /dev/null
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\ No newline at end of file
diff --git a/content/9-Polkadot/assets/coretime/interlacing.svg b/content/9-Polkadot/assets/coretime/interlacing.svg
new file mode 100644
index 00000000..1d6c0a47
--- /dev/null
+++ b/content/9-Polkadot/assets/coretime/interlacing.svg
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new file mode 100644
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new file mode 100644
index 00000000..21eeddfb
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7.33% 77.2% 0%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;-80&quot; y=&quot;300&quot; width=&quot;930&quot; height=&quot;70.24927160893493&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-2&quot; value=&quot;&quot; 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QGDA8Rn/nWcJAKAiYRSH8A2GEcqRoKBFN69ETpjvXFQmqUZsd3n0kt+BvphRotrOfLTRQAdqh0yK6GcvH0XRo5quf6bf7w3siVln1dp4KUvnG39N9/xHDtGTWadrEAsG5cfdMG0SNwUy3lau7ipg9cm+ppi7bX8w63feJGOf4/75GlpADXF/eouZH1suSi5pG2FxdIsQoiV+1dlzCttf6hQu+9ry75dpyIAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACuS8Q8hkDwBa7LfcfiifIe4G0B4AtNuMXITw/bQqszpqShK31yNLLCQ7q9MTujiEpal18hGmBmk83EgDW/Vrz6/tSmu834YPM06DxXbtEz1mrU1ZHirtzRKpviNTmX6962475Dyyy11FZJGs+pZ9Jz3ubXAmqEcnWJP7YOatLwimlO9VI3nSWVXoe5ps3G26h02Wn8osc/YOC7p+8JN6hKcN1qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggMDKEtAxg9hiUQPOKAiYXSD9AeD4YGIwtRHAOnCYqIwdSj7170LXav+nx8RRXrjQYTXvbkhmukaix+vedKVYHYn59B+GmZ5RcZ8bUoHcIQmqX4oUtVZLcVtNOOBssRtHSEdvELPRcOf2uADw5c2nG3Ppi5uvv5O6N6pnUqN1ExV357D0/fKITB67IIEZr1hd9vAI6oa3XbXoyOSafZtk8ImTBsdE90r1eMn6usuat9g3OSvnv/2UwTvVPtAeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE8kQgbupRizVxXCdPnpzHyGGBxNG+y324uABw3A8lEl7dlUQA2DsynfA6iRr4Rt2il2SKrcQlNTduSNg0pAKrHd97TkaeO2NoO/J8e7hesrFe1n32jQlHp5ZubJCitbXiPntxTlodiA6pPzjJjtTVQejhZ8+oOXI7ZPbCmPinZsVRUSR6xK+zslgmVCDXWugQPZ9xojL68nk5960nDem2dVrnsQMdMv5qt6z777dJ2ZaFU09XXrsmrQHgRP1f6Lg26vnJyzLy/Bnl41moGfsRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEBgBQnoeExsYQRwrAbbZhVI/88U4r8YKY6MtxU5E9oFZ3wJ2yxng8rdbQlHyurUyOe++eSc4G9sP6ZO9cvpLz0g/unEAcfq69dHT9UBV+9wcumJdXD89N8/IJ3fe1YmjnSHz9Pne/onZOpEnwp4tot/YkYq1HzGidIkzw5MzAn+RjulNkL6mb/xhARmF34flbvaYk8xzbbFYpG6N10hq96+Q+wqwE9BAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBOIH46U61SmCCGRDIO0jgEOBuJTPaj7WVIpvTI3Kbale9BR7WcGix5f7YEFdWcJLjqmRsnrEbaKi5/cdeOiYrH7X1Ys2jb/nHNcFzu747jOiA82JiiuJZ9J92PHVjyS6lEqNbZz3OfYEV21pOAW2nnfZbEWPhq69dYvoUcrd/7FfRl48a7Yu0h8EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBDIoMCcAHCKU51msKvcCoGoQPoDwHFfhPgvSrQnC2x4hxOndy6oL1/g7OR3l6sRsEWtVYueoNMoe4emxJlEsHTqdOKga+RmybR11pVGmie9Hj1wXiZf602qvQ7MJlMWC+4mc75uU9hYKWYMAEf6by8pkLZP7RO/mt944nB3ZDdrBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQWGkC8VOdxg98XGkePG9OCKQ9ABz0BQwQFvvCo0MNDV+veJJIdVy5d630/uLQfKcnt0+l/22+a094PtzFTpjpGg0HgJOZl3iqfWCxSxmOTZ8bSjinrx6dKqqfksIkyiMvJD+C1Vmtrp+hYq8oTNud9MjdOWnDlZsOXNsKneJSgfSybU1Ssq4uYR9aP3aDHP/iPRJIIkV3wovRAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJOwBoX19LTYVIQMLtA+gPAcfPzWp2pBYD1iNtERacm1kE9PcftUkrZ1saEwV993chI3VDcqOb57hn/B2G+NpF9SU0YHp5L2TjReOT8hdYeNWdvsiU+UJ/seUtp5yhLXwB4pns0YZf67jss+p23fXqf2IsWnu9X97N0yyrR6bwpCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsPIErE5jKC0QF/daeSI8cS4IGD+1aehxYNZnuKrV5TDUE1WmTvVJUP2aIlFAtfXjN8iJv/yFhOcMTnTRmOP20gJpet/umD3zb872jol/cjZ80KOC0kUJ5iUu3lCfdJrjYjUaNVFqbM+ICoSnFv8Vz9Dk/A8zz17voGq7ZZ4DadjlKC9K6ap6Tt5V79i56Dm9Pz8oo/vPLdom9uDE0R4ZP9Ql1devj909Z7uoqYoA8BwVdiCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsDIECACvjPecb0+Z/gBw3C8hbHG/lEgEqoOuo2oEZvXedYs21aM113/uTXLum0/IbN/4om0jB+0lLtnw+7dLwaqKyK4F15Mn+6LHvEmMrC3d2CCDjxyPnrPYhm6bqHgHkg/m6msF3F4JeZNPQ+BJ8vr6XXh1MPoyylSMZTKX0fMTF9SXLdq09g2bUwoA64sFvf5Fr6kP6pTRFAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEFiZAlaXMZQWP/BxZarw1GYXMH5q09Bbf9z8qXPmZ03inoOPvpYwAKwvU9hUKZu/+Hbpu/+IjDx3RgUqp+e9uqOySGpv2Sw1+zaJvXjhFMCRk0P+oAzEBHNnexMHmCt2tkj9W7ZK/wNHI5eZd63b1d1+5bzHYnfqEciplFAKcwXr6870JE6drNs51Py9nf/2XDjArOvJFv0HsmrPWqm6br3BMpnz3R3DCZuVbKyXVb+yU3rvOZiwrW5Q2FgplbvaErb1TcwkbEMDBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyE+B+LiWf+pittj8fFqeKl8E0h4A9o0bA2jxX5RkIN3nh2T67KAUr61N2NzqsMvqd+5UKYN3iD7P0z8hvolZsdit4Xl+nVXF4UCxxWZNeK1Ig8EnToSvE6nrUbCN778mYfC48T27xabmmL1wzytquOnc/M06/XDLx65X6Z8X74sO5g4+dSpy+7SsJ471yKyySjTStmR9vWz583dK1/97UcYPd837XLEdLFhdIbVv2KQCv+vEVugMH0rFXp+gA8Ah5ZcoTfaqO6+S4tYaGXrmlIy/2i3zTcTurCmRyt1rpOGOberdXOxPbH/jt2cvpBZ4jz+fOgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOSugK3YGEvwq5gTBQGzC6Q9AOyPG0GZzIjb+dDO/8vTsumP7xS7CqgmUywWixSvqQ0vybRfqI0ewdz7i0OGwzp18ODjr8mqt+0w7J+vogONdbdtEXfniMx0j4SDmM6aUilqq076WfRctZ4k01rP14ek9qn4dP8DR6T1YzckbO6sLJZ1v32raJvxV7tEj4j2T86IHnSsA+w6ZbMOtLrUc+r65RadBnxYjeiuuXFDwkuVbW0Uveh35B1zi/5DrLd1sNeh5nt2VpckvEZsg+n2wdgq2wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIILBSBCwSHdymH1kP2CNz6Ep5+bn9nGkPAPtUEC622FUQbilFj+Q9980n1Ty/b0w4YnYp15/vHB04PPeNJ+ZNdzyg0lLXqHlndVAxUdEThJesrwsvidrGHw/6A9J336vxu9NSH3m+XerefKUUJjEnsu6ADubrUcyZKBfuPqBSNrca/tAudl9tXlCn5g3WyxLLyP6zSafGXuItOA0BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRMKqDjIHrAYaQEpjwJM6NG2rJGIJsCi+ceXoaeeYanDFdxlBca6qlUJo9fkO4fvZTKKUtuq4O/7V99VCZP9M57Df0lb//HhyWdk33rX5J0/Msz4RTI83ZimXeGAkE58w8Pi3d0/rmTl/l2KV1OjwLu/MELKhV0MKXzltpYv9ee/3x5qadzHgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOS4gKO8yPAEnqFJQ50KAmYVSH8AeND4ZbBfRgBYIw4+9poaCfyEpHOSbZ3aOBz8fW3+4G/kZeq5ac9+/XE112x6gpLd/7FfRl86F7ldRta+kelwENjvVr9iMVkZffGsnP2nx8IpndPZtYDHJ+1feUR8o8bR6+m8J9dGAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABcwk4KuICwAPGmJe5ektvELgkkPYAcHDGZwjWWu02WWoa6Ei3R18+L8e/eI+MHeyI7FqWdSgYksEnTsixP7lbJhMEfyM31KOST/zVvTJ9dvnmivWooPkZNbpYB7uzUWYvjMlrf/Hz8Py+y3n/8aPdcupLD4h3yDgqPJV7jB/W13hQzak8nMppSbedOjMgJ9SzT53qT/ocGiKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggED+CTgq4wLAcYMe8++JeaJ8EUj7HMAaarZ3XEo2XJor11lbKjql7+UUff7Zrz0u5TtapPrGDVJ25WrRweWlFD3Prg7kXrjnoMx0jaR8CX3Oyb+5T2r2bZJVb79K4lMCJHtBnXZ4UM0t3Kvm/A35AsmelpZ2eiSwHgVdoebdbXzPbnGpd7aUokdH67l0+x86KrM9Y0u5xJxz3CrYfuIvfxF+99q7qKV6TptUd0y3D8jAI8dl9MB5NYt7qmfTHgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBPJNwFVjjI3M9o3n2yPyPHkqkJEAsLtzRAWA66OErpoS0UG85SjjhzpFL7Yip1Rc3SqVu9ukYHWFOMoKxWKbf4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QGDA8Rn/nWcJAKAiYRSH8A2GEcqRoKBFN69ETpjvXFQmqUZsd3n0kt+BvphRotrOfLTRQAdqh0yK6GcvH0XRo5quf6bf7w3siVln1dp4KUvnG39N9/xHDtGTWadrEAsG5cfdMG0SNwUy3lau7ipg9cm+ppi7bX8w63feJGOf4/75GlpADXF/eouZH1suSi5pG2FxdIsQoiV+1dlzCttf6hQu+9ry75dpyIAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACuS8Q8hkDwBa7LfcfiifIe4G0B4AtNuMXITw/bQqszpqShK31yNLLCQ7q9MTujiEpal18hGmBmk83EgDW/Vrz6/tSmu834YPM06DxXbtEz1mrU1ZHirtzRKpviNTmX6962475Dyyy11FZJGs+pZ9Jz3ubXAmqEcnWJP7YOatLwimlO9VI3nSWVXoe5ps3G26h02Wn8osc/YOC7p+8JN6hKcN1qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggMDKEtAxg9hiUQPOKAiYXSD9AeD4YGIwtRHAOnCYqIwdSj7170LXav+nx8RRXrjQYTXvbkhmukaix+vedKVYHYn59B+GmZ5RcZ8bUoHcIQmqX4oUtVZLcVtNOOBssRtHSEdvELPRcOf2uADw5c2nG3Ppi5uvv5O6N6pnUqN1ExV357D0/fKITB67IIEZr1hd9vAI6oa3XbXoyOSafZtk8ImTBsdE90r1eMn6usuat9g3OSvnv/2UwTvVPtAeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE8kQgbupRizVxXCdPnpzHyGGBxNG+y324uABw3A8lEl7dlUQA2DsynfA6iRr4Rt2il2SKrcQlNTduSNg0pAKrHd97TkaeO2NoO/J8e7hesrFe1n32jQlHp5ZubJCitbXiPntxTlodiA6pPzjJjtTVQejhZ8+oOXI7ZPbCmPinZsVRUSR6xK+zslgmVCDXWugQPZ9xojL68nk5960nDem2dVrnsQMdMv5qt6z777dJ2ZaFU09XXrsmrQHgRP1f6Lg26vnJyzLy/Bnl41moGfsRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEBgBQnoeExsYQRwrAbbZhVI/88U4r8YKY6MtxU5E9oFZ3wJ2yxng8rdbQlHyurUyOe++eSc4G9sP6ZO9cvpLz0g/unEAcfq69dHT9UBV+9wcumJdXD89N8/IJ3fe1YmjnSHz9Pne/onZOpEnwp4tot/YkYq1HzGidIkzw5MzAn+RjulNkL6mb/xhARmF34flbvaYk8xzbbFYpG6N10hq96+Q+wqwE9BAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBOIH46U61SmCCGRDIO0jgEOBuJTPaj7WVIpvTI3Kbale9BR7WcGix5f7YEFdWcJLjqmRsnrEbaKi5/cdeOiYrH7X1Ys2jb/nHNcFzu747jOiA82JiiuJZ9J92PHVjyS6lEqNbZz3OfYEV21pOAW2nnfZbEWPhq69dYvoUcrd/7FfRl48a7Yu0h8EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBDIoMCcAHCKU51msKvcCoGoQPoDwHFfhPgvSrQnC2x4hxOndy6oL1/g7OR3l6sRsEWtVYueoNMoe4emxJlEsHTqdOKga+RmybR11pVGmie9Hj1wXiZf602qvQ7MJlMWC+4mc75uU9hYKWYMAEf6by8pkLZP7RO/mt944nB3ZDdrBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQWGkC8VOdxg98XGkePG9OCKQ9ABz0BQwQFvvCo0MNDV+veJJIdVy5d630/uLQfKcnt0+l/22+a094PtzFTpjpGg0HgJOZl3iqfWCxSxmOTZ8bSjinrx6dKqqfksIkyiMvJD+C1Vmtrp+hYq8oTNud9MjdOWnDlZsOXNsKneJSgfSybU1Ssq4uYR9aP3aDHP/iPRJIIkV3wovRAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJOwBoX19LTYVIQMLtA+gPAcfPzWp2pBYD1iNtERacm1kE9PcftUkrZ1saEwV993chI3VDcqOb57hn/B2G+NpF9SU0YHp5L2TjReOT8hdYeNWdvsiU+UJ/seUtp5yhLXwB4pns0YZf67jss+p23fXqf2IsWnu9X97N0yyrR6bwpCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsPIErE5jKC0QF/daeSI8cS4IGD+1aehxYNZnuKrV5TDUE1WmTvVJUP2aIlFAtfXjN8iJv/yFhOcMTnTRmOP20gJpet/umD3zb872jol/cjZ80KOC0kUJ5iUu3lCfdJrjYjUaNVFqbM+ICoSnFv8Vz9Dk/A8zz17voGq7ZZ4DadjlKC9K6ap6Tt5V79i56Dm9Pz8oo/vPLdom9uDE0R4ZP9Ql1devj909Z7uoqYoA8BwVdiCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsDIECACvjPecb0+Z/gBw3C8hbHG/lEgEqoOuo2oEZvXedYs21aM113/uTXLum0/IbN/4om0jB+0lLtnw+7dLwaqKyK4F15Mn+6LHvEmMrC3d2CCDjxyPnrPYhm6bqHgHkg/m6msF3F4JeZNPQ+BJ8vr6XXh1MPoyylSMZTKX0fMTF9SXLdq09g2bUwoA64sFvf5Fr6kP6pTRFAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEFiZAlaXMZQWP/BxZarw1GYXMH5q09Bbf9z8qXPmZ03inoOPvpYwAKwvU9hUKZu/+Hbpu/+IjDx3RgUqp+e9uqOySGpv2Sw1+zaJvXjhFMCRk0P+oAzEBHNnexMHmCt2tkj9W7ZK/wNHI5eZd63b1d1+5bzHYnfqEciplFAKcwXr6870JE6drNs51Py9nf/2XDjArOvJFv0HsmrPWqm6br3BMpnz3R3DCZuVbKyXVb+yU3rvOZiwrW5Q2FgplbvaErb1TcwkbEMDBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyE+B+LiWf+pittj8fFqeKl8E0h4A9o0bA2jxX5RkIN3nh2T67KAUr61N2NzqsMvqd+5UKYN3iD7P0z8hvolZsdit4Xl+nVXF4UCxxWZNeK1Ig8EnToSvE6nrUbCN778mYfC48T27xabmmL1wzytquOnc/M06/XDLx65X6Z8X74sO5g4+dSpy+7SsJ471yKyySjTStmR9vWz583dK1/97UcYPd837XLEdLFhdIbVv2KQCv+vEVugMH0rFXp+gA8Ah5ZcoTfaqO6+S4tYaGXrmlIy/2i3zTcTurCmRyt1rpOGOberdXOxPbH/jt2cvpBZ4jz+fOgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOSugK3YGEvwq5gTBQGzC6Q9AOyPG0GZzIjb+dDO/8vTsumP7xS7CqgmUywWixSvqQ0vybRfqI0ewdz7i0OGwzp18ODjr8mqt+0w7J+vogONdbdtEXfniMx0j4SDmM6aUilqq076WfRctZ4k01rP14ek9qn4dP8DR6T1YzckbO6sLJZ1v32raJvxV7tEj4j2T86IHnSsA+w6ZbMOtLrUc+r65RadBnxYjeiuuXFDwkuVbW0Uveh35B1zi/5DrLd1sNeh5nt2VpckvEZsg+n2wdgq2wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIILBSBCwSHdymH1kP2CNz6Ep5+bn9nGkPAPtUEC622FUQbilFj+Q9980n1Ty/b0w4YnYp15/vHB04PPeNJ+ZNdzyg0lLXqHlndVAxUdEThJesrwsvidrGHw/6A9J336vxu9NSH3m+XerefKUUJjEnsu6ADubrUcyZKBfuPqBSNrca/tAudl9tXlCn5g3WyxLLyP6zSafGXuItOA0BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRMKqDjIHrAYaQEpjwJM6NG2rJGIJsCi+ceXoaeeYanDFdxlBca6qlUJo9fkO4fvZTKKUtuq4O/7V99VCZP9M57Df0lb//HhyWdk33rX5J0/Msz4RTI83ZimXeGAkE58w8Pi3d0/rmTl/l2KV1OjwLu/MELKhV0MKXzltpYv9ee/3x5qadzHgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOS4gKO8yPAEnqFJQ50KAmYVSH8AeND4ZbBfRgBYIw4+9poaCfyEpHOSbZ3aOBz8fW3+4G/kZeq5ac9+/XE112x6gpLd/7FfRl86F7ldRta+kelwENjvVr9iMVkZffGsnP2nx8IpndPZtYDHJ+1feUR8o8bR6+m8J9dGAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABcwk4KuICwAPGmJe5ektvELgkkPYAcHDGZwjWWu02WWoa6Ei3R18+L8e/eI+MHeyI7FqWdSgYksEnTsixP7lbJhMEfyM31KOST/zVvTJ9dvnmivWooPkZNbpYB7uzUWYvjMlrf/Hz8Py+y3n/8aPdcupLD4h3yDgqPJV7jB/W13hQzak8nMppSbedOjMgJ9SzT53qT/ocGiKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggED+CTgq4wLAcYMe8++JeaJ8EUj7HMAaarZ3XEo2XJor11lbKjql7+UUff7Zrz0u5TtapPrGDVJ25WrRweWlFD3Prg7kXrjnoMx0jaR8CX3Oyb+5T2r2bZJVb79K4lMCJHtBnXZ4UM0t3Kvm/A35AsmelpZ2eiSwHgVdoebdbXzPbnGpd7aUokdH67l0+x86KrM9Y0u5xJxz3CrYfuIvfxF+99q7qKV6TptUd0y3D8jAI8dl9MB5NYt7qmfTHgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBPJNwFVjjI3M9o3n2yPyPHkqkJEAsLtzRAWA66OErpoS0UG85SjjhzpFL7Yip1Rc3SqVu9ukYHWFOMoKxWKbf4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LOPVuBQCCCCAAAIIIIAAAgisZAGLxGQYidkUizqilvBhva2ysYb3qXV4W69VrCa6qAF8VodNLGqxOuwqo6VdbGqxFjrFrhZbsVqXFIi9rECs9tQypul4zeDjJ6Xz+8/K+OHulfy6eHYE5gjkVQA49ulKNzfI6nfvkvo3XhH+xUjsMbYRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRyT2DqdL/03X9YLvzskHiHp3LvAegxAhkQyNsAcNRO/QKlcler1N66WU0Mvk6K19Ve/HVKtAEbCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACZhTQGVr1CN/h587IwCPHxd0xbMZu0icETCVgnlm808WiUi+Pvnw+vOhb2EsLpOzK1VKysUGK19RIUUt1OJe8q640nH4gXd3guggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAvML+N0e8fRNyEzPqLg7R2S6fUAmT/bJ5Im+8JSc85/FXgQQmE8g/wPAcU/tn5yVkRfOhpe4QyrHfGF4MnFHeWE4UKzzztuKVP55tVgLHBdz0zvtYnHqXPUqZ73KR29V+esterGpus51r3PbR/Le61z3Mbnww/cLp8NX/0VBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBEwuEFID7cJFr/S2/o9eB0MSCi9BCQV0Xa+DEvSrtZqfN6TWQV9A9AjeoEctah2Y8UrA7RX/tFqmZsU/MSO+sRnxjkyHj5mcgu4hkDMCKy4AvNib0X9o9EJBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEclHAmoudps8IIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnMFCADPNWEPAggggAACCCCAwP/P3n3AuXHdh77/o2zvfZd12TvFLsuqVpdlWe6OS+Qr+8WO73tJPtfPN4njfBQ9v5fYyXUSlxs7zrVl++PromIVO7YKZfVOUqTE3pbc5fbeG7DAO2eoXe4AWGCWBDAA5nc+goAzMzgz5zuHAyz+c85BAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTSUoAAcFqeNg4aAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQCBcgABxuwhIEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgLQUIAKflaeOgEUAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgXABAsDhJixBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE0lKAAHBanjYOGgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEAgXIAAcbsISBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIC0FCACn5WnjoBFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIFwAQLA4SYsQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBNJSgABwWp42DhoBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBAIFyAAHG7CEgQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCAtBQgAp+Vp46ARQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBcAECwOEmLEEAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTSUoAAcFqeNg4aAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQCBfwhi9iCQIIIJB4gezKQqm9dZOUX75c8haXyeCRVul9/Yx0PH5QApP+xB8Ae0gJAZfXI7W3bZSyXculZONCGWvtV+2gQTqeOCQTnYMpcYwchP0COTXFUnPrRilX7SRvQakMHGqRvjcapF1dL4L+gP0HyBHYIpBbVyI1t6h2oT5HcmtLZOBgs/S+pq4fTx6S4BTtwpaTYsNO3XlZM98nitbVyejZbuNzpF19jvh6R2w4InaZigJ5i8ul5uYNxvUiu6JQBt4+d/77xpOHRYLBVDxkjikJAvlLK6T6JtUudi0To1281SQ9rzZI527VLkiOFcivrzSuF2W6XZTmS/8B3S5OS9cfjjrWhIqLFKyokuob1xufI1nFedL/ZuP5dvHsMXgcLFC4stpoF2Xq7xFvYY7071fXi5dPSffzxx2sQtULV9dI9Q3qeqE+RzwFql3o68XLJ6X7xZPgIIAAAkkXcO3efA9/8SadnR0i4GwB/aP99h/dLXkLy8Igel45JW/9xS8JAofJZN4CHfzd/M8fl6rr1oRVbrxjUPZ97scydq43bB0LnCWQt6Rctv/wbslVQeDQ1Kl+cDn45fsJAofCOCCfv6zS+BzJUYGc0NTx1GE59NcPEQQOhcnAvA7+bv23T0vZ9vqw2o029she9Tky2TUUto4FzhIoWlsr2/7jM5JVkh9W8dbf7Jcj9zxGEDhMJvMXFK1fINt+cJfoQE5oavn1Xjn6td+GLibvAIGSyxbL1u//sXjVD/ah6dwvX5fj3/h96GLyDhAo3bbU+L7hyc8Oq23jz16Rk998Mmw5CzJfQN8ksuU7nxRPXni7OHvfi3Lq209nPgI1DBMov2KFXPbtT4gnJytsXcMPnpOG7z0btpwFCCCAQCIFPHfVXHtvIndA2QgggECowK5f/ankLyoPXWzk81UPDR0g7nqGO2kjAmXQwrVfuV3qbt8csUb67tnqG9bJuV+8zo+yEYWcsdDldcvl938xYvBXCxSoIGCW6pnRw520zmgQ79TSneOVyx/4okQK/upNCldUGz/E9KreOqTMFtj4jY9K5VWrIlZSXxsq1A8wzQ/sibiehc4Q8BblyuW/+kLE4K8WKFpTZ0D07T1rPPM/Zwjo68OuX3w+YvBXCxSr4HBAjTCie+yQnCOgR6ja9fPPRwz+aoWSTYvEPzopA2+dcw4KNRU9EtGun/2JRAr+ap5SddOAb3BMBg+2oOUgAd2ZYcdPPhsx+Gu0i61LZaJ7WIbUSHck5wjokUW233d3xOCvVijbUS9jbQMyfLzdOSjUFAEEbBdgDmDbTwEHgICzBHQvDB3kjZaq3rNWxO2KtgnrMkBAB3ijpdyaEinetDDaJqzLcAH9Q1uknr+zq62HYiM5S6B065I5g7/TEjU30S6mLTL12Z3tlcprIgd/p+tcuKpG9A8xJOcKlO2snzP4O61SzfVimsIxz3rqgEg9f2cD8DkyW8MZryuuWDln8HdagHYxLeGc54orV80Z/J1W4O+RaQnnPFeoGxAj9fydLcD3i9kaznhdefXqOYO/0wJ8jkxL8IwAAskSIACcLGn2gwAChkDZjmUxJbyFuVKs5vEjZa6AnkNJz7UWK1lpL7HKYH36CpTtjH290L1A9XDAJOcIWGkXuXWlkruw1DkoDqypvkEo0tBqoRRW2kvoe8hnjoCV7xF61ICs8oLMqTQ1iSmge+DESoVrakX3ICc5R0DfMBIr6aHD9fQDJOcIlFtoFyWbF4m+MY3kHAEr14vSLUtEj2hFco6ApXaxfamIiw4vzmkV1BQB+wX4JLL/HHAECDhKwOoXYJeHy1MmNww9/6+VZLW9WCmLbdJPwOp1wM31Iv1O7iUcsdV2YXW7SzgU3mqjgJvPERv102fXVr9HcL1In3MajyO10i5c6sdZ2kU8tNOnDCvn26VGqXK5+Ts1fc7qpR+plXZhBHMYwezSsdOoBCvtwuXRQT4CfWl0Wi/5UC21C/0ZQrO4ZGsKQAAB6wJ8c7VuxZYIIBAHAStzrE2puZUGmSslDtqpW8TwiQ5jrqRYR9jPnHyxiDJ6fd++szHrN9k/KsOnOmNuxwaZI2Dlc2Sia0jGmnozp9LUJEyg/+1zEvD5w5aHLrDSXkLfQz5zBKyc/9HGHplU1wyScwSstAv93cKnvmOQnCNgpV0MHWuXqZEJ56BQU7HSLgYPt0pg3IeWgwSstIuBt5ol6J9ykApVtdIu+vc3iQSCYCGAAAJJEyAAnDRqdoQAAlpAB3b1D/PRUs8rp9QX5UC0TViX7gLBoHS/cCJqLXRgr/+tc1G3YWVmCwwcOCe+geg/vsZqR5kt5Mza9e9rFP/weNTKdz1/POp6Vqa/QGDMJ72vn4lakbHmPhnhBpGoRpm+sm/PGdE3FkZLXC+i6WTmut7XG2QqRrCmm8+RzDz5UWrV+9ppCUxGv7GI60UUwAxdpX+bCPiiB/G4XmToyY9SrZ6XVbuIEdzlehEFMENX9bx0UoJT0X/L5HqRoSefaiGQwgKeu2quvTeFj49DQwCBTBNQN7r1vHxSam5cL5787LDaDRxsloNfvl/98R39j6ywN7Ig7QR6Xz0tpduWSp6aqzM06aDf/i/8VCY6o98sEPo+8pkloP946n21QWpu2RBxrk/dQ/jQVx7ihpHMOu0xa6PvpO9VQZ2amzdEnG+tR/2Ae+RvH4n5x3fMHbFBygvo7xMVV6yQnMqisGOd6ByUfZ//qfgHxsLWscA5ArpHVv+BJqm5SV0vssKnn+h67rgc/dpv6YnhnCZh1NQYbUj9zVGt20WE4eQ7nz4ix77+O9qFw9qFf3hCBo+2qevF+ojDf7c/flBO/NPjInTcclTL8A+Oy9DxdqlWv19EGt617bcH5OS/POUoEyorxggRIw2dUnXDuojDwrc8vE9Of+dpqBwmMNk7InpkmerrdbsIH+e5+YE90vC9Zx2mQnURQMBuAdfuzffw9dXus8D+EXCgQN6Scln4gW1Sdvly8apA8HjHoOrJ0yAtD+5RPbsYVsspTcKTly2LPrZTylU7yK0rkakJ3aOrQVof3S+jZ7qdwkA9YwgULK+Suju3GO3Ek5MlY6390vtGg+g/oHQvQJIzBQpXVkvd+8+3C5cK7IzrdqGuH0a7mIjeg8eZYplZa29xniz66A7j+pBTXST+ofHz3yce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7.33% 77.2% 0%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;-80&quot; y=&quot;300&quot; width=&quot;930&quot; height=&quot;70.24927160893493&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-2&quot; value=&quot;&quot; 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7p73zyv4G1qXvIVlsuZvbpeiDQtCV80rP9bUE3P73AWl4sr2yOr/+1ZLwd/QAivetULW/NV7jZ7ioevII4AAAggggAACCCCAAAIIIIAAAggggAACCCCAgPMEApMhAeA8AsDOawXpV+Pw6GKc6xAeADb/Q7GyO92DNX9JRcxN+w80Sduj+2NuF7qBHiq5d8/cPXunty9cWT390vRce/tlsvgTlxtzy5pWXEJGB35rbt4o9Z+72gjkmoqaCsq4CgJHS+5sr5rztkiW/cm1MXvORiqn7gNbZeEHt4tbDZt9qcmbnyMr//xG1SN4yUUXNaaC9cGpQNT359aVyuKP77qkgLVuZws/vD3qfliJAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACzhAIDQC7L2K0VWdIUctUEkh4AFjP3Ts7Bf3Rg3izt51+rXuRxkp63tnZc97G2j50fftvD4QuCsvrcd1Dj6XiqlWyQAVLE5XKdi6TRSqoGZpGG2P3iK26YZ3MHgo6tIy58hVXr5Y6FdSOZ9LDQi/543erYbwvbmz8oH9KxtsHoh5SwbJKqbxmTdRtrKzUvbkLVlwYQtvKe9gGAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEMk8gNK4VGvfKvBpTo0wQSHwAOGQI42AgOG83PYxxrKTn/Y0052+s902vH28bkOETHdPZOZ+9JXkz63LrSlRQ84qZfKJeVN+wXkpD5hUebeqNuTv9vvmmnJpiWfKpd1l+mx77Xt/9MjUee25nb1GuLP7UxXuNWhgG2vKBR9nQ5XJJxZWromzBKgQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEHCCQDBojmu5PGr+TRICKS7gTfTxudwh/xBUT935puzy2AHgARUAvtR06rtPRx3GWQev/YNjM7upuXWT6J6tsZK+O2TwWKuMnumWsXO9oi8Weo7e/GVVUryuTjx52bGKkNrbNkn/vrMz211KMFTXI+Dzm+YFnh7CoObmDRHnHZ7Z8TsvBg+3SNt/viUjpzpnVules3V3blV1mnu+37Id9dL5dJWMnO6aeZ/VF9pOLiJ+PNkzbASoc6qL1JDW1pp86balRo/yWMNOWz12tkMAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIE0FAiZnlJP4UlCINUFrEXDLqUWIQHgkBslLJVspQewr3fEUlnRNgqoXqz6YSVlleVL+a7lMTfVgdWG7z8ruofy7DQg54ysHlJ65ZdujjlPb/7SCilSweKho23G+8aa+0QPe20lAK3fEFBDKHc8cUj632w0hlIO+qbEneOVrLICyVZ1GVHBad1Dt/yKFUb50f7X+cxRaf7l62Gb6KDuqX/dLfV/co2Uq6Gr50p6WOuLCQBb6fU8vU8d4D73yzeUe7P4+kbPL1ZtseamDVL3/i2i50iOlozhvheViZWhtqOVwzoEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIX4HQuFZYx8f0rRpHnsECCb9NITgV0jU+JCBsxdajApWx0nQP1ljbxWu97iHq8kbn08Min/r27rDg7+xjGGvpkxP/+HuZtBDALpsVcNYB3Mnu4dlFzfl6rK1fjn3tN9L22P7zPZDVe3XSwzdPqHl1dVBZB75LLlscs4fsZN+ItKn5kj352ZEfeVnS+tBeo4fxXAcUOpz1XNuFLh9XVlaS7rV75t+fk54XT1wI/uo3qp7PHU8ekrM/etFKMZI1a7hvS29gIwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEMgogdCAb2jcK6MqS2UyRiB2ZPVSqxo65PNFBIAnVQ/O/KXRDySr+MLcvNG3jM/anOrimAX1qSGbrcwrPNE5JLpX7aKP7Ihaph7CeHayMp+yHm668ccviZ7jOFbKqTKXH2n7bNVj+LJ//USkVZaXZZfmix4uer69gAPvBK5j7ajl4X0y8HbznJvpXtBDJ9qlaHXtnNvoFVnqOEkIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDgXIHwAPD8pzp1rh41t0sg4QFgPUzx7BT6D2X2urle6zlcY6XchaWxNom5vuKqVVKwvCrqdp1PH5Hx1n6xEiwdOdERtazZK4dPxt7Wyj5nl6lf97xyyph7OHR5pPzFlB+pHCvLcutK5x0AtlKu3iZ0uO1I7xs+FjsA7MnPifRWliGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggIBTBEI6NobGvZzCQD3TSyDhAeDA5PnhhqdZ3F7P9EvLz1YCwOWXr5DWR/aLhA7GbnEvetLuhR/absyDG+0tAweajABwdnlBtM2MdSMNXTG3md5gtLE75py+Ro9UfaFRQxlbTbq3q9WUZaFOVsuKtV2ihlfWw26PqyGvY6XxzsFYm7AeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEHC7gzjLHtayOVupwNqpvs0D0SWzjcHA6IDc7uSzM5zt7e/3ayly3OiBbtrM+9K2W8yVblsQM/urhlIdPdRplBv3mwHakHel5cq0mT06WiEsFd6OkoF/1pp5H8FcXNamGl7aa9DzAyUpZJYkZXnnsXK+6CSB2LaZGJmJvxBYIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDgaAF3trkv5dTYpKM9qHx6CCQ8ABwYMwcVPSH/UKwwDanheqcmzOVEet+ST18hOTWx5+YNfW+2mvt20cd3hi4Oy4+19MnU6Pl/2Hre3lipcFVNrE1m1hesrFbx3+gB4Mnu2PucKVC90AHriXm8Z6JrfuXP3td8X3uLc+f7Fkvbc+eNJSY2QgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQsCoQHg0LiXhSLYBIGkC5hvW0jA7kPvhHBfRA9gXUbvaw1Sde2aqEfoycuWlf/tZjn7oxdk5OT5nrpR36BW6uDv6i/fKtllsYd0Hj7aNlOclcBq0foF0vHkoZn3RHtRvG5BtNXGuonu2HMhzy5Euxm9hmcvjPLaSlBbv737xROWhlmOsisZOdMdbTXrEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHbBULjWqEj39p+gBwAAhEEEh4A9g+bh9qdz7DIs4+365mjMQPAevucikIV0L3NCFL2vHJKRueYhzdvcblU37heynYtEyvzEgcm/NKx+/DMIY019828nutFsQoAL/qjXdL8qzfm2sRYXqkC3gVYywAAMjdJREFU21XXr4u6jV451qyGN55PsjAU8uziRpt6ZmfnfF2wvEra/vMt8fWOzLlNpBVZZflSefVqKb9ihfT/jycibcIyBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCBlBELjWqFxr5Q5UA4EgVkCCQ8A+wbHZu1OxFOQY8pbzYy39svgkVbRQdVYyeV2GcFi3WN4UgUpJzoHRR+Hy+sxevpml+fLfOeg7XjqkPj6Rmd23b+vUXwfHZWs0uhz2VbfsF50z+SWB/dI6EVB3zWi1y/44LaZcud6EZwKSPdzx+daHZflw8fbZVTNoZuvguPRUt7CMll/753S8vA+6Xv9jIT28ja9Vw1rXbS2VqquWyslWxaLy/3OqOPqHJEQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgVQW8IbEtXwD5rhXKh87x+ZcgcQHgEP+IXjzsy9au/HHL8nar74vZtB19g6yywtEPy4lTfaPSscT5qGcdUC28+kjsvAjO2IWXfHulaIfetjosXN94vK4JLuySHJrS1RA1FogtG/PGSOYHXNnl7hBx+MHZdnnr41Zig5qL/nUFbL445fL0Il2Y0ho/9C4Me9wdnmh5KihtbMr1bN67fImfKrpmMfLBggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIDAvARUJzd3btbMW4LBoOhYCAmBVBdIQgD4Qq9ZjeEtyrtoE58KxJ7+t2dk9V/eKu6shB+6cZz+kQk5/d2nJTDpDzvuruePS+V1ayRHBXOtJL2d1W1nl6fHk2/73duzFyXsdd/es6pX8jopWFFtaR86uKt7ZVvpmW2pQDZCAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBFJAwFuUKy4VBJ5Ofj3qrQoCkxBIdYGEd82c7Bo2GWSVXHwAWBc0erZbGn/ystHT1FRwAjI6+HvyX56UsabIc+8GVGD21Ld2iy+Bd3sE/QFp+N4zMtE+kIAaRihSXbhOffcPMp6s/UU4BBYhgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnYLhMa0JkJiXnYfH/tHYC6BhAeAJ7qGTPsO/cdiWmkx0/fGGTn5zScktGyLb7e0mS771L8+NWfwd7qQiY5BOf2d3aJ76cY7BQMBOfvjF2XoaFu8i45a3pQKfOu66/mTE5H0EAnBAHfIJMKWMhFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCA+AqExrUTGpeJzxJSCwHmBhAeA9dDJPt0l/p3k8rjFe4m9gHVRwyc65Oi9j0nXs8fi2hs4MOGX1kf3y5F7HpXRxp7pw476PHq2R4783aPSf6Ap6nbzWTmiejof+/v/FB3stiPp4K/27X7heNx8A/4p6X7ppBxVtr4EBZftsGKfCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkHkC2eUFpkpNdA2a8mQQSFWBpEykO97aL1nFF4Z+1vPg+gcuBIUvFkcHl8/94jXpefWUVFy5Ssq2LVVzDOdeVHF6GOeB/Y3GXLsXE5zU72lQ8xOXbFksdXdskfwlFRd1HPrukY7dh6X7uWNqHPmLKiJub5oam5Smn72qfE/Lwg9tl4KV1aax7q3uyD86Id1qvuTOPxyNy3m3ul+2QwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQuViC7qsj01vHWJE3XadorGQTmL5CUAPDouV4pWls3c3Q51UUycrpzJn+pL0bPdIt+6GBw8foFUrajXnIXlElWaZ4ReNa9jv3D4+ItPB8c1kMr+1XA19c/JkPH26R/f9P544lDwHXgwDnRj+zKQindukQFhJdIbk2xEZh2ud0yNTop7hyv6GPSQyFPDU/IRM+wDB5sNo5jTFlZTe2/f1vyFpXNubkOkMcjjZzqlBP/9LjyzJdSFWQv3abrVCLeYjX5uapTaNLzFo+19InuxTza0CV9+86K7ll9qcnonf3Im+IpyJ6zKD0kt5U0oo6r46lDUTcdePtc1PWsRAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgcwV0B0aZycd7yIhkA4CSQkAjzWZ/0HkVBcnxkbNKzt4qMV4zOzAJUbg1+V1izvbawRgdTA40b1rJ7uHpXP3EeNhHMs7x6GDvzoFfVOiex3LJcyF26t65iYz+fpHpeuZo8bD2K/LZQS2s1QgWHUNPm+revsGxuI/H/J0PXXQOx5JB+JbHtwbj6IoAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBDJQIKfWHM8aa7I2dWgGUlClNBNISgB45EyXiSVvQakpn9CM6tWre/vanqaPY8j2I4nfAagezH41v7N+kBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBjBFwu4zRUGfXZ0SNRktCIB0EwsfvTcBRDx1rN5Wat6TclCeDAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQKoI5NaViDvLM3M4Y639qdHhcOaIeIHA3AJJCQDr+VZnz0erx0z3Fp2fj3fuQ2MNAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskXKFhWZdrp0HFzZ0fTSjIIpJhAUgLAwamADB1rM1W9cE2tKU8GAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgVQQKAqJYw0ebE6Fw+IYELAkkJQAsD6Svj1nTQdUsmmRKU8GAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAdsFXC4p3rDQdBh9e8+a8mQQSGWBpAWAu186aXIo3bpEXNkXxk43rSSDAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAgA0CxRsWmKYy9Q2MygA9gG04E+zyYgWSFgDu398kE11DM8fpycuW8p3LZvK8QAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMBugcprVpsOofMPR0UCQdMyMgikskDSAsASDErrY/tNFpVXm/8BmVaSQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCJAt6SPCnZvNi0x5aH3zTlySCQ6gLJCwAriZaH96k48IU7JApWVEve4vJUN+L4EEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEHCCgOy+6PBfCZ8MnO2SQ4Z8dcOYzq4oXWnAS6jXe0i+9rzWY9lRzy0ZTngwCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACyRZwZXmk6vp1pt22/HqfKU8GgXQQSGoAWIM0/e9XTS5lO+slp6rItIwMAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskU0L1/s4pyZ3bpGxwLm950ZiUvEEhhgaQHgHteOim6u/x0crndUnfn1ukszwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggkVcCd7ZXa2zeb9tn8wB6ZGp00LSODQDoIJD0ArFHO/PAFk03ZrmWSt4S5gE0oZBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBJIiUH3TBskqzpvZlw78Nv38tZk8LxBIJwFbAsAdTxySoWNtM04ul0sWf/JdM3leIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJAMgezyAql97ybTrhrVlKa+3hHTMjIIpIuALQFgjXPyW7tNRoUrqqXiqlWmZWQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE/v/27gTIj6u+E/hvbs3oHt33YcmWfMk2xja+YiA2EIzBpAhQXgJ2NgGScsGyuyQFix2SDZuiqN2tpLJJnBAgYU0IjjHmyBoTwNgY4/vSaWxLsu5bGmkOzbXdY480I/3nPzPyjObf//501d//7tfv//q9z2tMwXf6NQECBAgQGE2B+clDiukS0L3b0ST43fTVn/ce+iaQOYExC4D3/eLF2PXva/uBzf+tN0ZN8lcWNgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKjLdB42RkxZdWCfpd54X/9MDqPtPUrc0AgSwJjFgCnSBu++G/9Xp5dVV8bi2++MqIiS4T6SoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkDWBdOnn+R+8pF+3Dzy1Obbf+3S/MgcEsiYwpgFw646Dkf4VRd9t4oo5MeeGC/oW2SdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwYgIVVZWx5GPXRHVD3bE2O1vbY83t9xw7tkMgqwJjGgCnaFv+5bHYmywH3Xeb/RurYvIFC/sW2SdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwIgILbrosxi+Z0a+tX/3v+6N5095+ZQ4IZFFgzAPgFG31Z/412nY3HfOrqKyIJb93dYw/Y+axMjsECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEXq/A7HetiulXndmvmV0/WRevfOOX/cocEMiqQEkEwEf3HYnn/vBb0dXRecyxsqY6zrj1rTFuzuRjZXYIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQInKrAtCT4nXvDhf1+3rxlX6z53Lf7lTkgkGWBkgiAU8ADT2yK9X/+g36W1ePrYtknr4uaqQ39yh0QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGI5A+vrRhf/hsn4/6WhqjWduvTPSbxuBchEomQA4Bd36rcdj0z893M+2tnF8nPVH74xxc6f0K3dAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCgCjW86I5Z+7JqoqDwejXW1d8az//Vf4shLu4fShDoEMiNw/C4vkS6/8KX7Ytu9T/XrTRoCn/npd8T4Zd4J3A/GAQECBAgQIECAAAECBAgQIECAAAECBAgQIECAQFGBWe84LxbfclVUVB2Pxbq7umL1Z++Ofb94sehvnSSQRYHjd3oJ9X7N7d+Jnfc9369H6XLQyz91XUy+cGG/cgcECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEThKoiJj/wUtj3nvf0O9UGv6u/fy9J2VR/So5IJBhgZIMgKOrO577o7tOehK4sqY6ln78zTH3PRdFVCT/qbURIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQOEGgeuK4WP6f3hYz37Ky35mujs5Y/Zm7Y9s9/Vej7VfJAYGMC1SXbP+TEHjN5+6J9v3NsejDVxzrZkUS/M5+5/kxYfms2PiVB+PonsPHztkhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIt8Ckc+f1ZEs1Uxr6QXQ2H43n/vBbsednG/qVOyBQbgKl+QRwH+UX/ucPY+2f3BvpX2T03SacOStW3v7umH7NWcnTwH3P2CdAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMibQFVDbSz87ctj2SeujRPD39adh+Lxm78s/M3bTZHT8ZbuE8B9JmTrvz4RR17aHed98X1RN3PSsTNV42pi4U1vimlXLI9X7nwkml/ec+ycHQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRwIJA8KTrt8Wcz9zYujJln6+cRt3y9fiueTV48e3XfkxFOOCZSlQCYC4FT+wFOb45H3/02c86c3xvQrl/ebjPGLp8eKz1wf+5/cFNu//WS07jjY77wDAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB8hOYvGpBzL3xoqifN/WkwaWry278u5/FS3c8EJG8etRGIC8CmQmA0wlpT/4y4+k/+HrMfe8b4sz/8raoHl/Xb56mXrQoplywMA4+vTl23vd8z1PD/So4IECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyLZAVUVMvXhJzHr7udEwv7HgWNKVZVf/t7vj0OptBc8rJFDOApkKgHsnYtvdT8TehzbE8v/8tpj99vN6i3u+KyorYkoaBCef5s17Y8+DG2L/Yxuj80hbv3oOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEsiMwbvbkaEyWep52xbKomVRfsOOdLUfj5eSp301fezi6kyeAbQTyKFBx//m3ZfqZ96kXL45ln7w2Jp83f8D56+7siqYNO+JAskR009rt0Za86NtGoBwENuyvi/au5OUGtpIQOHNKa9RUjX1X1if3RYf7Yuwn4rUenDW1Naorx74765L7otN9MfYT8VoPViT3RVUJ3Bdr99Ulqx/575FSuTFWNrZG8reMY76tSe6LbvfFmM9DbwfOTu6LihK4L1bvPfkdWr199H36Bc6Z1nr6L3rCFbuT/ydhzT73xQksY3ZYUdEdZzeO/R++p6sqrnVfjNl9cOKFK5P7YmUJ3BfJ/y0X6/b798WJ8zNWx1WV3bFi6tj/+6IjuS/Wuy/G6jY46brVyX1xVgncF+1JTrfhgH9fnDRBY1RQk9wXZ5bAfRHJk77pa0AnnTsvefBvcdTPnTKgSHdXV2z/3rPx0l/92KtCB1RyIi8CmQ+AeydqxltWxJLf/bWYdPbc3qIBvzsOt0bzxr3Rsm1/8i+BQ3F0d1Mc3X8k2g80R1dbx4C/c4IAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGBkBaom1EXt5IaonTY+amdOivo5k3ve6Vu/sDEqa4ovZps+BLjrR2vipb/9aRx5cffIdkxrBDIqUDYBcK//1EuWxMKb3hTTr1oeFafwaE1Xe0d0NLVFZ/PRSJcJ6Gxt7wmFu9qS7+RPkLqTT/rS8PRfKN3Jn6r1fHd2J09JJH/mmpalf+6a7KeHPf/ou9/byfScjQABAgQIECBAgAABAiMp0PM/QkayQW0RIECAAAECBAgQIJBrgd7liPquSpSU9RSn/+jdT5azqqisTD5JWe9+siRemtFUJN+VybKJ6aci/a6riaq66qgaVxOVDbVRPb6u53MqeU77oZbkid9n4pWvPxItW/fneqoMnsCJAmUXAPcOsG7mxJhzw4XJO4LPjQnLZ/UW+yZAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMigQPqA3v5HX44dP3g2dv5wtVVdMziHunx6BMo2AO7L17BoWsx484povOyMmLxqflQ31PU9bZ8AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAEBdp2HYr9T2yMvQ+/GLt/uj46kid/bQQIFBfIRQDcjyBZkmD80unJU8Gze74bkvXjx82ZEuNmTUrWlp8QlbXF15Lv15YDAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB1yXQcaQt2nY3RdvOQz3LOTdv3pe8z3dXNK3bEWkAbCNAYHgC+Us7k/dipS8BH+hF4FXJevM1k+ujeuK4qEk+VfXJevTJE8OVyXr06br0lemnd6369Dtdw/61dez7r3H/2vr36Zr3PWvhpxOT7Kf/fPWrZ98/CBAgQIAAAQIECBAgMCIC/ofGiDBqhAABAgQIECBAgACB1wSSPKV3e3U3OU6LkoPurnT/te9kPz3u7uyK7o7k09UVXe2dPfvpd1dbR3QdTT7Jd2fL0Vc/zUejvak1eZq3NdoPNPec772WbwIEXr9A/gLgQcw6k78yST82AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZE2gMmsd1l8CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKCwgAC7sopQAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKZExAAZ27KdJgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKFBQTAhV2UEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIHMCAuDMTZkOEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoLCAALiwi1ICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkTkAAnLkp02ECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgUFhAAF3ZRSoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcwJCIAzN2U6TIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcICAuDCLkoJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQOQEBcOamTIcJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQWEAAXNhFKQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBDInIADO3JTpMAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAoLCIALuyglQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA5gQEwJmbMh0mQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAYQEBcGEXpQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMicgAA4c1OmwwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECgsIAAu7KKUAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECmRMQAGduynSYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEChQUEwIVdlBIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBzAgLgzE2ZDhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCwgAC4sItSAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZE5AAJy5KdNhAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFBaoLlyslAABAgQIECBAgAABAgQIECBAgAABAgQIECAwugIz3rwi0s/ElXNi3KxJ0bxpbxxauz22f/fpOPTc1tG9uNYJECBQpgIV959/W3eZjs2wCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVIUqKiIZZ/89Vj8kSsL9q6rvSPWfv67PUFwwQoKCRAgQGBAAUtAD0jjBAECBAgQIECAAAECBAgQIECAAAECBAgQIDAaAlMuWDBg+Jter7KmOlbefkNUNdSOxuW1SYAAgbIWsAR0WU+vwREgQIAAAQIECBAgQIAAAQIECBAgQIAAgeMC4+ZOiUv/+aMRyRO4Y7Ft+urPY+OXH4xpVy4f9PKVNVXReOnS2P2TdYPWVYEAAQIEjgsIgI9b2CNAgAABAgQIECBAgAABAgQIECBAgAABAmUtkD5RWzO5YczGWD9/as+1e78H60j9vFfrD1bPeQIECBA4LmAJ6OMW9ggQIECAAAECBAgQIECAAAECBAgQIECAAIHTIHDw6VeGdJUDz2weUj2VCBAgQOC4gAD4uIU9AgQIECBAgAABAgQIECBAgAABAgQIECBA4DQI7PnZhuhq7yh6pdadB+PQ89uK1nGSAAECBE4WEACfbKKEAAECBAgQIECAAAECBAgQIECAAAECBAgQGEWBlq3744nf+Woc3Xu44FWaNuyIxz/85Yju7oLnFRIgQIDAwALeATywjTMECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAKAkcfOaVePjdfxmTVy2ISSvnREV1VXQcbo2mtdvj4HNboqut+BPCo9QtzRIgQCDzAgLgzE+hARAgQIAAAQIECBAgQIAAAQIECBAgQIAAgewJVNXXJoFvW+x96IWeT98RpGFwZW11dB19/SFwzeT6GL90RoybNzVqG8dH+/4j0bLtQLSmn+0H+1626P64OZOjfkFj1M9vjK7W9uju7IrWHQejedPeaD/QXPS3wzk5bvbkqJ0xMepmJp/pE5NgvDLadjUlfX21vwM9NT2ca6hLgEB5CwiAy3t+jY4AAQIECBAgQIAAAQIECBAgQIAAAQIECJSkwGV3/X5PINu0fkccWrst2nYeioZF02Ji8jTwhGUzY+/PfxXPfOIbPX2ffvWZsfRj1xQdxyvfeDS2f/fpY3UmnTsvFt50Wcy89pyorKk6Vt535+DzW+OVOx+Jnfetju6Ozr6nXt2vqIj02os+ckVMvWjRyeeTkq7kd3se2BBb7nos9j38YsE6gxVOOmduzLru3Jh53TlRP3dK0eppeL31rsdj67efjPZ9R4rWdZIAgXwKVNx//m0W0M/n3Bs1AQIECBAgQIAAAQIECBAgQIAAAQIECORQoLK+ZsijvuAvborGS5YUrf/oTXfE4Rd3Fa3Te7K7vetY0PqWx28bMJhN66eh8KMf+Nuen05JwteLv3JLbzMFv9NAdO0ff6fnXBoWL0k+FUmAO5Stad32eOoPvh5H9xx/J3H6hPJ5X3xfTwA8lDbSOmkf1v3Z96K7vUCYXKCRNOhe+cfvjsnnzS9wtnhRV3tHEgQ/ERu+dN8x0+K/cJYAgbwIeAI4LzNtnAQIECBAgAABAgQIECBAgAABAgQIECBAIBHoamkfskN3V9egdTubjw6rzUEbLFDh8IYd0d3dXTTQTZd5Tir0hLazkidph7NNXDEn3vhPvxtPfvRr0bJ5X8+TyRf8nw/1vJt4OO3Mu/GiGL9kejzxO18tGsqmyzov+b1fi8W3XFU0BC927cqa6ljwwUtjwlmz49lP/XOytPXILUNd7LrOESBQ+gKVpd9FPSRAgAABAgQIECBAgAABAgQIECBAgAABAgTyLJC+K7hl6/6iBBOSAHjxzVckSykPL/ztbTRdevmcP72x5/DsP3nPsMPf3namXLAwln78mt7Dgt9nf/49sfSj15xy+Nu30XRp6kvu/GjUTp/Qt9g+AQI5FhAA53jyDZ0AAQIECBAgQIAAAQIECBAgQIAAAQIECGRF4PC6HUW7Wj1xXCz7xLVF6wx2Mg1vL7rjwzH9qjMHq1r0/OKbr4wJy2cVrHPGrW+NOdevKnjuVAvT8Hrl52441Z/7HQECZSYgAC6zCTUcAgQIECBAgAABAgQIECBAgAABAgQIECBQjgLpe3pPx9Z46dLXfZmKqsqY8+4LTmpn+lXLY8l/vPqk8pEomHHNWTH7neePRFPaIEAg4wLeAZzxCdR9AgQIECBAgAABAgQIECBAgAABAgQIECCQB4Gm9cWfAB7IIH1HcUVtVVRWVw1UZUjlHU2tUTWhruh7iPs2NOvac+KFL93XtygWDzH83fPQC7Hpaz+PQ89vjbT/tTMmxux3nBeLP3JF1E4beKnnMz/9jtj5w9XR3d7Z77oOCBDIl4AAOF/zbbQECBAgQIAAAQIECBAgQIAAAQIECBAgQCCTAsN5Ari7syte/Ksfx54HN8ThDTujIgl/p1+9vGeZ5NrG8UMef9uepnjxL/899v3ypWjdfjCqGmpjwQcuiaW//5ZB3987bvbkaFg0LZo37e253uRVCyJdYnqw7Vd/8aPY+OUH+1U7urspNv/jw7HrR2vi4q/cEmnbhbbaKQ0x7fJlseeB9YVOKyNAICcCloDOyUQbJgECBAgQIECAAAECBAgQIECAAAECBAgQyLJA266mOHqgeUhDWPc/vt8Toqbhb7p1d3TG7h+vi8c+/PfRNcSnYztbjsbTt94Z2+55qif8TdtJn8bd+A8PxZrb70kPB93qkid3e7ehvPd3x/977qTwt/f36XfrtgOx+nPf7lt00v6s6845qUwBAQL5EvAEcL7m22gJECBAgAABAgQIECBAgAABAgQIECBAgEBmBdIANpKnXItt2+55MrZ+6/GCVVo274ttdz8R899/ScHzfQvXfeH70bRmW9+iY/s7vv9sLL75ypiwfNaxskI7tdOPL9ecPg082Db77efFjKvPGqxa0fPpu4DTJ57T0NtGgEA+BTwBnM95N2oCBAgQIECAAAECBAgQIECAAAECBAgQIFCWAumyz8W2vclyzkPZBmtn36ODt1Mz+XhYXT9/6lAu27PMdLrUdLFPsYaqJ4yL+nlTilVxjgCBMhcQAJf5BBseAQIECBAgQIAAAQIECBAgQIAAAQIECBDIk8ChtduLDrd16/6i59OTrTsPRvv+4stNt2w5MGg7UXG8ykDv7T1eY+T2+i49PXKtaokAgawICICzMlP6SYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBQV6DjcGq1biwez7QdairaRnjy8/tV3Bxer2D7E9xH3tjHUdw/31n89332Xnn497fgtAQLZFBAAZ3Pe9JoAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4QaCzpf2EklM77GxJ3jU8wlvLlsGfPB6pS9ZOO/7u4ZFqUzsECGRHoDo7XdVTAgQIECBAgAABAgQIECBAgAABAgQIECBAgEA2BVq27IsJy2YO2vlXvvlodHd0DlqvWIX9j71c7LRzBAiUuYAAuMwn2PAIECBAgAABAgQIECBAgAABAgQIECBAgACBsRc4/MLOmHHNisE70t0dG750X0RX9+B1+9RIn/qde+NFMfWiRXF4w+BLWPf5qV0CBMpMQABcZhNqOAQIECBAgAABAgQIECBAgAABAgQIECBAgEDpCWy964lY9JEro7KmqmjnFnzg0pi4cm6s/8L3omndjqJ105NT3rAo5v/WG2PmW8/uabtt7+FBf6MCAQLlLSAALu/5NToCBAgQIECAAAECBAgQIECAAAECBAgQIECgBARadxyMHf/2bMy94cJBezNl1YK49Jsfj+ZNe2P3z9ZH67aD0b7/SFTUVkf9vCnJZ2rUz58aDQsaw/t+B+VUgUDuBATAuZtyAyZAgAABAgQIECBAgAABAgQIECBAgAABAgTGQmDj3z8YM3/97KhuqBvS5RsWTYtFH7p8SHVVIkCAQK9AZe+ObwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgdETSJ/offZT34yu9s7Ru4iWCRDIvYAAOPe3AAACBAgQIECAAAECBAgQIECAAAECBAgQIEDgdAns+8WLsea2e6K7u3t0Ljla7Y5Ob7VKgMAoCFgCehRQNUmAAAECBAgQIECAAAECBAgQIECAAAECBAgQGEhgxw+ejdbtB2LlbTfE+KUzBqo2rPL0qeL0HcObvvbwsH6nMgEC5ScgAC6/OTUiAgQIECBAgAABAgQIECBAgAABAgQIECBAoMQFDjy1OR5531/H4luujEW/fXlUTxx3Sj3uONwaW+56PF75v49E266mU2rDjwgQKC8BAXB5zafRECBAgAABAgQIECBAgAABAgQIECBAgACBERM48PjG6DjYMmB73V3dcXTv4QHPFzux60ero6Jy4DdVtmzdf9LPt93zZEw4Y+ZJ5b0F7U2tvbsDfrftaYpt9z4dVXUDRyS7frxuwN/3njj4/JbYed/zvYcFv9OQt9jW3dEZL9/xQGz8h4ei8bKlMevas2P61WdFbeP4Yj+L1ObQ6m1x4MlNPWPpPNJWtL6TBAjkS6Di/vNvG6VF5vMFabQECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZEQqBxXE3XTJ0TdjIlRM6Uh0uWdO5JwO/207TkcHYcGDuVH4vraIEAg2wID/3lLtsel9wQIECBAgAABAgQIECBAgAABAgQIECBAgACBTAp0tbZHy5b9PZ9MDkCnCRAYU4GB11YY0265OAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMV0AAPFwx9QkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFCiAgLgEp0Y3SJAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBwBQTAwxVTnwABAgQIECBAgAABAgQIECBAgAABAgQIECCQQ4EVn70+Zr/z/IjKihyO3pAJZEdAAJydudJTAgQIECBAgAABAgQIECBAgAABAgQIECBAgMCYCTQsmhbnfuE34/J7bo3Z168SBI/ZTLgwgeICAuDiPs4SIECAAAECBAgQIECAAAECBAgQIECAAAECBAj0EegJgv/svYLgPiZ2CZSSgAC4lGZDXwgQIECAAAECBAgQIECAAAECBAgQIECAAAECGREQBGdkonQzdwIC4NxNuQETIECAAAECBAgQIECAAAECBAgQIECAAAECBEZOQBA8cpZaIjASAgLgkVDUBgECBAgQIECAAAECBAgQIECAAAECBAgQIEAg5wKC4JzfAIZfMgIC4JKZCh0hQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGRfQBCc/Tk0gmwLCICzPX96T4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoSQFBcElOi07lQEAAnINJNkQCBAgQIECAAAECBAgQIECAAAECBAgQIECAwFgJCILHSt518yogAM7rzBs3AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOA0ChwLgr9za8x516qIyorTeHWXIpAfAQFwfubaSAkQIECAAAECBAgQIECAAAECBAgQIECAAAECYy7QsHBanPPf3xuXC4LHfC50oDwFBMDlOa9GRYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoaQFBcElPj85lWEAAnOHJ03UCBAgQIECAAAECBAgQIECAAAECBAgQIECAQNYFBMFZn0H9LzUBAXCpzYj+ECBAgAABAgQIECBAgAABAgQIECBAgAABAgRyKCAIzuGkG/KoCFTcf/5t3aPSskYJECBAgAABAgQIECBAgAABAgQIECBAgACBMRO48K8/FNWT6sfs+i5cfgLjF0+P6gl1p21gzZv3xst3PBDbv/9sRJc467TBu1DmBQTAmZ9CAyBAgAABAgQIECBAgAABAgQIECBAgAABAicLXP2TT0dt4/iTTyghkDEBQXDGJkx3x1zAEtBjPgU6QIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMJCApaEHklFOoLCAALiwi1ICBAgQIECAAAECBAgQIECAAAECBAgQIECAAIESEugfBF8QUVlRQr3TFQKlIyAALp250BMCBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFBBF4Ngm+My79za8x5lyB4EC6ncyggAM7hpBsyAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCDrAmkQPP/9b4yJK+ZkfSj6T2BEBapHtDWNESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBhlgYPPbYmX/uansfehF0b5SponkD0BAXD25kyPCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQK5FBD85nLaDXqYAgLgYYKpToAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcHoFBL+n19vVsi0gAM72/Ok9AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBsBQS/ZTu1BjaKAgLgUcTVNAECBAgQIECAAAECBAgQIECAAAECBAgQGCuBJz/2j1FZXTlWl3fdMhRY8dnrY9I5807LyAS/p4XZRcpUQABcphNrWAQIECBAgAABAgQIECBAgAABAgQIECCQb4HD63fkG8DoR1yg43DbiLd5YoOC3xNFHBMYvoAAePhmfkGAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDCCAoLfEcTUVO4FBMC5vwUAECBAgAABAgQIECBAgAABAgQIECBAgAABAgTGRkDwOzburlreAgLg8p5foyNAgAABAgQIECBAgAABAgQIECBAgAABAgQIlJyA4LfkpkSHykhAAFxGk2koBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFSFhD8lvLs6Fu5CAiAy2UmjYMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUKICgt8SnRjdKksBAXBZTqtBESBAgAABAgQIECBAgAABAgQIECBAgAABAgTGXkDwO/ZzoAf5ExAA52/OjZgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMKoCgt9R5dU4gaICAuCiPE4SIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMVUDwO1Qp9QiMnoAAePRstUyAAAECBAgQIECAAAECBAgQIECAAAECBAgQyIWA4DcX02yQGREQAGdkonSTAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBqAoLfUpsR/SEQIQB2FxAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAxLQPA7LC6VCZxWAQHwaeV2MQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAdgUEv9mdOz3Pj4AAOD9zbaQECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVMWWP/nP4gjL+0+5d/7IQECp0eg8vRcxlUIECBAgAABAgQIECBAgAABAgQIECBAgAABAgSyLCD8zfLs6XueBATAeZptYyVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKwFBMBlPb0GR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAngQEwHmabWMlQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCsBQTAZT29BkeAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQJ4EBMB5mm1jJUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgrAUEwGU9vQZHgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgECeBATAeZptYyVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKwFBMBlPb0GR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAngQEwHmabWMlQIAAAQIECBAg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8.33% 77.2% 14.67%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;770&quot; y=&quot;300.25&quot; width=&quot;769.95&quot; height=&quot;70&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-3&quot; value=&quot;&quot; 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omFSRw0SNbZrw1paSXx57bvBcz/iCGGlAqxUXfmvm/7CwmvX72vj75c0SqCIFcMmrd0sdemfG2FJPeX3tvWT3j7dCAVwXyye+nS5LfU2c6FZLfT/clv6dKlSGQ7x+MJd/dNuONGUx6hu6/ceWMt0MDXhWoSeIoi5/YXhEcdR0tMffKZdF+/cqYc9nScs/iMzXs0HdeiZf+6z9G14t7zlRFOYELQmDWRghaL1kcl/3i90XbdRef9kGlPX2PppOCP7Qxjj63qzxE82krKiQwiwV23XFJ9LU3z+I7qK6mdzy/uyICwDvffGkMJEOmSJUhsOCZnRURAN5x12UxmHyLUqoMgYVPbq+IAPD2uy+PYvILtlQZAou/uzWiAkak2X7PFVFK/qJWqgyBJcm313PJ9DMznba97cqZboLrjxCoiABwEujzXox4KDO8mUu+WFYJAeD0zw/vxQy/DCMun0++oFwJAeA00Oe9GPFgZnizNpnyriICwI213osZfhdGXr7uWG9lBICb6rwXIx/MDG83HO6umADwwKETcfCbm8pL2ku445Y1Mf/2S6I56SE8OnXcvDpu/tRHY9ffPh6bf/+BGOzqHV1FnsAFITDr/sYvHTN+9UfviFU/+qbymPGjn1KhbyAOPvxS7P/K89Gf/FCQCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZr9AIfkiy4GvbygvaUfBxW+7OuZdvTxzY+k8xMvff3MsvOvyePGXPxedD27K7JchcCEIzKoAcPPK+XH1J95b7uI/+uEUk+FLOr+xIfZ+6ZkYPN43erc8AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAlQgcT6b8TJc0dnTRu64vDxM98tYaFsyJ637vQ7HrM0/Ext/4UhQrYPq+ke2zTWAqBWZNAHjRvVfGFf/xB6K2peEUjyNPbY+df/2d6D94/JR9CggQIECAAAECBAgQIECAAAECBAgQIECAAAECBKpToHvbwdj8u/fHnCsuihU/dEs0LpmXudFl776h3Ev4mZ/+60jrSgQuBIFZMbnX2o/dGdf81vtOCf72H+lOxnD/arz8h18T/L0Q3lb3SIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4jUDXC7vjxf/4D7H7c09FabCYqdG6fnHc/JcfjY5b12TKZQhUq0BFB4BztTVx1W++J1b/2B2n+B/6zsvx4i/9fRx7Zucp+xQQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhcWAKlQjH2fv57seHXvxA9e45kbr52TmNc99//WVyU9AiWCFS7QMUGgPONdcnY7B+MJckE3iNTOtfv9r94NLZ+8qFIJ/uWCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAwJ9Ow4FBt/9Qtx8LEtQ0XldT7peHjFL31/XPzDt2XKZQhUm0BFzgGcb6iN1yXfwmi/cVXGe/BEX2xJhnw+seVAplyGAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwJBAsX8wtv3vb0bvrsPlXr+5XG5oV1zyb94aNfW18UrS2VAiUI0CFdcDOB32+Zr/+oFTgr/9B4/Hpt/4kuBvNb6F7okAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMAUC+778XGz7k4dPmRd47cfuihUfunUKruiUBGZeoOICwFf+6rtiwRvXZ2R6dh6Ojf/5i9G792imXIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAWAKHHt0Sm//gq1HoHchUu+Rn3xZL3p6dijRTQYbALBWoqADwmh9/yykftJ6ka/6mT9wXA0d7ZimxZhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECMykQNfzu2Pz794f6dDQQykdFvqKX/7BmHfdiqEiawJVIVAxAeCFd10ea/7lmzOo/YdOlD+MhZ7+TLkMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbMROLFlfzLv74NRKhaHD8sncwFfm0xNWr9wznCZDQKzXaAiAsBNy9vjyv/0gxnLwRN9SfD3KzFwpDtTLkOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgXASOPr0jdvzlY5lD6+e3xtWfeG/kaioibJZpmwyBcxGY8Tc5/TClH6raOY3D7S8OFmLL7z8QvXvM+TuMYoMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOC8BTof2hR7vvC9zHnar18Zqz96R6ZMhsBsFZjxAPCqH31TzL1yWcZv5998N9Ju+BIBAgQIECBAgAABAgQIECBAgAABAgQIECBAgACByRbY8w9PxbHndmVOu+ojb4o5ly/NlMkQmI0CMxoAblm78JRvUxx+fGt0fn3DbLTUZgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVki8Mr/figzFWm+tiau/JV3GQp6ljw/zTyzwIwGgC/9t++MfF3NcOsGjvXE9r94dDhvgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBUCBSO98W2P3skc+rW9YtjxQdvyZTJEJhtAjMWAF781qui46bVGa8dSfC3cKIvUyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCoE0mGgD35rc+bUa378LVHX0ZIpkyEwmwRmJACcq8nH2o/dmXE6+uzOOPLU9kyZDAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGpFNj1t9+NwREdFGtbGmL1j90+lZd0bgJTKjAjAeCL3nV9NF88f/jGSoPF2PlX3x7O2yBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwHQKDyVDQez73dOZSy997YzQunZcpkyEwWwSmPwCcz8WqH3ljxqfz4U3Rt78rUyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDoEOh/cGH0HTsaq8nW1sfLDb5iOS7sGgUkXmPYA8OJ7roym5e3DN1IcGIw9X/jecN4GAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgekUKBWKsefz2V7AF/3A66KurXk6m+FaBCZFYNoDwCs+dGum4Yce3RKDR3syZTIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEplPg0Hdejv5DJ4YvWdNUH8veff1w3gaB2SIwrQHglnWLou3aFcM2pVIp9n3l+eG8DQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIzIlAoxf6vZuNWF737hhlpiosSOB+BaQ0ALxv1Iel6cU/07Tt2Pu13LAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFJETj4yOZIpy8dSs0rOqL95tVDWWsCs0Jg2gLAudp8LP0n12ZQOr+5KZOXIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBTAoXu/jjyxLbM5Q0DneGQmQUC0xYATr8dUTe3aZhkoKs3jj61fThvgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBMC3Q+lO3AuOCOSyNXWzPTzXJ9AhMWmLYA8II3rM806sgTW6NUKGbKZAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjMpMDxl/ZF/+ETw02obW6IttetGM7bIFDpAtMWAG67YVXG4thzuzJ5GQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKVIDA6jtU+Ks5VCW3UBgJnEpiWAHCuriZa1y8abkOpVIr02xMSAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUoTGB3HmnvVskprovYQOKPAtASAW9cvjvyIsdH79ndFOom2RIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDSBE68fCDTpDmXLc3kZQhUssC0BIDnXLokY9Cz/WAmL0OAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgUgT69h+LYt/gcHMaFs6Juo6W4bwNApUsMC0B4JZVCzIGPbuPZPIyBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpGoBTRuzcbz2pZOb9imqchBMYSmJYAcNPFHZk2pN+akAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUqkDvvmw8q+liAeBKfVbalRWozWanJte8YlQA+EDX1FxonLPmG+uirq056uY1vbpOtmvqa2PwRF8MHOuJwaM95XV/5/EoFYrjnM1uAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBahXoP3A8c2vNozo8ZnbKEKgggWkJADcunZe55f5pDADXtTdH+02ro+Pm1dG8MjsUdaZRIzKF3oE49uzOOPL09jiarIs9AyP22pwNAmmwvzn5Jk7z6gWRDkHeeFFb5PK50zZ90yfui8Gu3tPuU0iAAAECBAgQIECAAAECBAgQIECAAAECBAhcmAJ9ndkOjY1LsvGuC1PFXc8GgSkPAOeb6qK2tXHYojhYiMHjfcP5qdqYe/XyWPL2q6Nl3aLI5U4f+DvTtWuS4GEaNE6X0mAxDj66OXZ/9klBwjOBzXB5rq4m0l7mzUmgt3nV/HLAt2HxvDMGfE9p7hkCw6fUU0CAAAECBAgQIECAAAECBAgQIECAAAECBAhcMAL9h09k7rVh4ZxMXoZApQpMeQB49IdhIBlmeSpTTVN9LP/AzTH/tnWTcplcbT4WvOmSaL9hVez+3FNx4OsbIorJzN/SjAsseee10XbDymhKe/fWTMt01jN+zxpAgAABAgQIECBAgAABAgQIECBAgAABAgQITI/A4JFsTKthkQDw9Mi7yvkKTH0AeEH2wzB4pPt823zG4+dcvjRW/sgbo7695Yx1znVHTXN9rPjALdF+46rY/Lv3R7Fv8FxP5bhJEph39bJyz99JOp3TECBAgAABAgQIECBAgAABAgQIECBAgAABAgSGBQaOZmNaDaNiXsMVbRCoMIEp7zZZN68pc8sDUzT8czrU89p/dfeUBH9H3kDrusWx7qfujXzDlMfOR17WNgECBAgQIECAAAECBAgQIECAAAECBAgQIECAwDQKDJ7oi1Lp5KiwNa0NEaaVnMYn4FLnKjDtAeBC8mGZ7FTf0RJrfuLOyNfWTPapT3u+1iTYvO6n7olc/fRc77SNUEiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDB1Aknst9DTP3z+XC4XdXOzHR+Hd9ogUEECU96NtXbUB2GyA8BpT9y1P3l31M1pnFbWtCfwkrddHXs+9/Q5XTeXBKvr5jZG6pP2kk7nLi5098XAsd5k6YnBZCkNFs/p3OdyUOrYuGRepENd5xvqym0YOHQiBs5iyO702Lq25vJSmzyPYv9gpOfoP3g8Bqeo5/e53KtjCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQITESic6I/a5qTn72spjemcTexk6DhrAtMpMPUB4LQ7/Ig0OOKbEiOKz3lz0V1XRNPy9gkfnwZVj72wK45v2R/p5N3FwUISgG2O+vkt0Xzx/Ghdv3jC51p871XR+dCmCX/QGy9qi7bXXZwsK6N55fxxr3Pilc448tS2ZNkefXuPjlt/9Y+/JfJ1Y/RKToYp2PKHX0u+rnJyuILmVfNj2XtuijmXLjnt+Z/8sT89bXm5MBeJ15Jov2lVtF2/csxvvaRzJqf3cuAbG+NEYi8RIECAAAECBAgQIECAAAECBAgQIECAAAECBCpdoNB9sgdw2taalmzcq9Lbr30XpsCUB4BrGusysmkgcNJSMs76gjsundDpSoVi7L3vmdh//wtJT9vsh3XkCdLA7KJ7r0yCmqsj7co/Vkp7zV70rutj2588PFa1SOcnXvHBW6N5RceY9UbvbFm9INJl2btviBNbO2PHXz4W3cn6TKlx6bxoWtp2pt3l8sZFc6N3z6vB5GXvuykW3X3FuPd5uhPOSwLZKz5wS6TDb08kpVYdt64tL907DpXvZTIDwWlgvzcJkvfsOhw9O5MlXSfLxYn7vGtXTKSJ6hAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEMgKj41qj416ZyjIEKkRg+gPAybDAk5XSnrQTCUAOdPXGlt/76pjB06E2dW87GFs/+VAc37QvVnzo1nGDox23rokdn3osRv8ASM+Xfgtk2T+9Iea/cf245xm6/pnWLasWxKX/9p1Jj+ONsfszT2bGnB86pidp+7gB4KQXchoAXvz2q2PxPVcOHTrhdTpk9YofuiXab1w14WNGV0wD4et/5q2x4y8ejYOPbB69e8L53cnw27VJD/M04Nu7Lwlqj+jZPHSSk32dh0qsCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQITE0inuxyZapqyHR9H7rNNoFIEpjwAnE/mth2Ziv2Fkdnz2l74lsvGPb5ULMbW//XghIK/I0/W+eDGyNXmy71cR5aP3s7l85HOB3zs+V2ZXWnw99Kff3s0jtMjN3PQOJlc0uN54ZsvK/co3vSJ+6LYM5A5onv7wXIP20zhqEw6DPWc3oFyz+VRu8bNpvP6XvoL74iGhXPGrTtehXwyB/LKD78x6hfMiT3/8NR41U+7v+uF3actV0iAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAwBAeDJUHSO6RbIT/UF83XZS5SSOXcnK6XDI4+X0jlnuzbsGa/aafcfeODF8rDCp905orD1kuy8wbn6mlj7k3dNavB3xOWieXlHrP1/7iwHqEeWd287NDJ72u20h/BF/+S6s+6RPHRPkxH8Hdmwpd93bcy5bOnIItsECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgYoQKI6Ka+WSDm4SgUoXyEZnp6C1aQ/ZkalUnJxBedPeqPn68Tswpz15zyd1PrRp3MObLs7O7bvyn98WrWsXjXvc+VSYc+nS8lDMI8/Rk8ytWyqN7ZvObdxyDm27+EOvT+YjXjjycpO2ffEP3xbpHMESAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCSBEbHtXI12bhXJbVVWwgMCUx51O2UD0KhOHTt81rXL2gd9/jevUejd/eRceuNVaHzm5ui78CxsapEOm/wUGpYPDfab14zlB1znX5rpGfH4eh+5UD0dXZFw6K5SZB1QTQt6zild+/pTjT/DetjzxefiYFDJ8q7Cz390d95fFKGaB55vdQ6net4vFQaLMahb2+Jzm++FH37j0U6ZHVT0lt50T1XxNwrl53x8IZkGOgl77ymPLfxGSvZQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYboFRHRtHd3yc7ua4HoGJCEx5ADiSIODINE4H1ZFVx9xumD9+ADgNhp5vKibz5R59eseET7P43ivLgc/xDjiRBH03/7evRuFE3ylVa+c2xfp/fW8SPG0/Zd/IgjS4vvieK2PnX39nuDgNRp/NMM39R7ojHeq6Z9fh6D/QFfnG2qhrb4n6ZBns6i2fd9HdVyT3NPY3WtLgc3o/J7bsH25LujFwdFd5fuTF77g6lr3rhsy+kZmOW9YKAI8EsU2AAAECBAgQIECAAAECBAgQIECAAAECBAjMuMCpPYCzca8Zb6AGEDiNwNQHgEd/M2KSPhc1rQ2nuZ1s0eBpgqvZGpOby9Xmo+P168Y9adfGPbHl9x+IYt/gaesOHuuJTb91X6z7qXvGHXZ5/hvXx86/SQLAr4383LPzcLTfuOq05x1d2PnQxtj56cej2DOQ3bX1ZI/mdEfa03i8tO1PHzkl+DvymH1fejZaVi2IttetHFk8vF3f0RItaxbGiZcPDJfZIECAAAECBAgQIECAAAECBAgQIECAAAECBAjMpEA62unIVCqMPRXnyLq2CcyUwJQHgEd/MyImaWz0od6pY8Gl8wRPZ6pPhjLO1409+Xfq8fIffv2Mwd+h9ha6++OV//GNuOo33ztUdNp1TWNducfu0DDQxYHTB5VHH3zs+V2x/c8fHV18Sr6urTnSa4yXlr33xlj2nhvHrDZez+Q0cC0APCahnQQIECBAgAABAgQIECBAgAABAgQIECBAgMB0CowOABcnZ6rT6bwF17rwBKY+AFwoZFRHf1Mis/MsMhMZ3nm8gONELleb9DRuu2HVmFXTuYaPb9wbDROYl7hn9+FIg7sTSf3J3L59B5M5fccZ7jqdQ3coADyR86ZzD+/4v9+eSNUJDyedtuF8U3PSQ1giQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFSKwOi4VqkgAFwpz0Y7ziww5QHg4kD2g5DOWzsZKQ2MjpfSAHAaVOze2jle1TPun/+mS2LZu888d2164LEXdsfmNACcXG+8dGJzdo7cidQfNwC8sDWObxrvTCf3H9+wN/r2HTtZMMZW/QSC2mMcfla7auc1nVV9lQkQIECAAAECBAgQIECAAAECBAgQIECAAAECUymQq82O/FpKOtlJBCpdYHKisWPcZbE3O79svn5yYs6F431R6Mue+3TNWPiWy05XPOGyBckcu+Ol45v3vVollx0H/rTHjZoT+bR1RhSWJjKUwESuO+KcffsnFvxNDzllCO8R55nszToB4MkmdT4CBAgQIECAAAECBAgQIECAAAECBAgQIEDgPATy9dkAcKF3YlNxnsclHUrgvAWmPABcGB0AbpicAHB658c3vRZ4HYNh/m3rkiGcV45R48y7Ft1zZTQsmnvmCq/tGWpHf2fXuHVb1i0at87ICi1rx68/keGwR56z98D47Ryq338WdYeOOdd1TUNd5Cfx/TjXdjiOAAECBAgQIECAAAECBAgQIECAAAECBAgQIJAKjO7YWOiZ2DSf9AjMpMDkRWPPcBejPwijPyhnOGxCxQe+9mLMu3r5uHVXfviNURwoxLFndo5bd6hC2nN4+ftuGsqecZ3Op3vi5QPl/X0TCJY2Le+IfGNdjO4ZfboLpEMiN04gAD2R6448/8Dh7pHZMbfP5tyHvv3ymOcab2exf7D8nMarZz8BAgQIECBAgAABAgQIECBAgAABAgQIECBAYDoEakZ1XJtIfGc62uUaBMYSmPoA8InsNyFqmuvHas9Z7Tv23K7oTYYzHi9IWpMEXNf95N3R+c1Nse8fnxtz/tvWy5bEoruvjLZrV0yoLZ0PbYpSElxOU1/n8SgNFiNXe+aO1elk4as/eke8/EdfHz7udBdKe8Ku/sjtp9uVKUuDpv2HTmTKxs1MZFjp104y2NUbg8d7o7a1cczTpj299973TPTuOjJmvdPtbFg8Nxbcfmly7OGIsxwi+3TnU0aAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAyBmqZsXGswmaJUIlDpAlMeAB441pMxqJ3EAHB64gNf3xAr3n9z5hpnyix40yWRLt3bDsaJLfuj/2h3NMxvjULPQNR1tETT8vZoWtp2psNPKR/s7os9n3t6uDwNBB/6zsuRDjs9Vkp7La//qXtj8+9/9bQ9gdMg+bqfuidaVi8c6zTlfQe/tTmZqLc0br3zqdD54KZY8s5rxjxFGmS/7Be/L3Z95snoTJ5JqVAcs34kgfB5SZB94ZsvizmXL41cMo/x3i89M/Yx9hIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEplGgpqUhc7WBpOOcRKDSBaY+AJwEWUem0R+UkfvOZTsNNrZfvzJa1y+e8OHNK+dHupxv2vuF70XhRPabHmkP447Xry0HNMc6f+sli+Pq33pfORjd/cqBKPQNRk1TXbSsWhhNKzsinQ93vFRKevLu+8rz41U77/37H3ghFt1zxSnj3I8+cb6uthyMv+j7r4ujyXDbx1/aF+kXANJhwOuSHsT1C+dEw4LW8rppWXvUzW0afQp5AgQIECBAgAABAgQIECBAgAABAgQIECBAgEDFCJzSA/hotuNjxTRUQwiMEJiGAHD2gzDeUMIj2jahzbSn6ct/+LW4NOl92rBgzoSOmYxKR763I/YncxCPTr27j8SRJ7dF+w2rRu86JZ/2mp1z6ZLycsrOCRSkc+72T2De4Qmcaswq6TDQaU/rxW+9asx6QzvTH4Ydt6wpL0Nl1gQIECBAgAABAgQIECBAgAABAgQIECBAgACB2SSQdmpMp/YcSoNJp8BxR0AdqmxNYAYFzjxZ7SQ1qj+ZF3dkqps3+b0+0/HWt/zBA5HOQzsdKQ3+vpLM4RuF0w+9vO1PHo7u7QentCnpENbb/+LRKb3GyJPv+swTcTS5b4kAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcCEIjI5pjY55XQgG7nF2Ckx5ALhvVA/VurbJDwCn9L27jsSm37ovenYdntInceSpbeXg71jf8Cgmwzlv/t37o2//sSlpS++eI8n8wQ9Eqb8wJec/7UmLpXj5f34jjieBZ4kAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUO0CowPAo2Ne1X7/7m/2Ckx5ALjQ3R+D3SfnyU3nia1prp8SsZ7th2LDr3w+9n7pmUjnx53M1H/oRLz8P76RDDf99Ql170+HTd74m/fFoe+8PJnNiIPf2hwbP3HfKXMPT+pFznCy0kAhNv/OV2L//c9Pqm/6juz98rOnHVL7DE1RTIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYUoG69pbM+fsOTE3Hv8xFZAhMgsCUzwGctrFv77GoXbNwuLkNC+dE97apGSI57Zm7+7NPRtpTd/Fbr4551yyPfP253+bg8WT+229siL33PXvWPW4Hj/XE1k8+FAcffilWfPDWaFwyb9jgbDd6krmFd/zlo3F8076zPXRS66e9m3f+zXcjnX94xYdeHy2rF5zz+dOg+v4HXojOhzZFcZqG7z7nxjqQAAECBAgQIECAAAECBAgQIECAAAECBAgQuKAEGha2Zu63d8/RTF6GQKUKnHtk9CzuqDvpmdsyTQHgoWZ1bz0YryRDFucbamPetSui/eY1MeeyJVHTUDdU5YzrtAv/0ae3x5Gnd8Txl5KAa+n0c/2e8QSjdnS9uCde+A+fjeZV86PtdSuT5eJoXNqWqZUGrnM12Q7Z6XDWR55K2pEEs9PezRNJ6X13bdwzZtV0zuTzTWkAf+OvfyEaL2qL9htWRdsNK6NpWfu4p+0/eDxObO0szydc7h19hnmUxz3RBCt0vbg7ahrP/JoXk2G0C5PgMcHmqEaAAAECBAgQIECAAAECBAgQIECAAAECBAjMEoGGBXMyLU3jXRKB2SBw5sjYJLa+e0e2t2/DormTePaxT5X2WD38nVfKS1oz31gXdW3NkY7bnq5rkgDx4Im+GDjaE2mP3XSdHjMVKQ3OpkvaQzkdBrtublPUpu1I1qVkjt1cPle+/kDSjsGkHYWe/rNuxvFNe+Ol39571sed6wG9Sc/kPbufjj2ffzpqmpJ7Su6nNpnnuW7eq7aFpGdvOsRzuqSB9XRo7OlMBx54MdJFIkCAAAECBAgQIECAAAECBAgQIECAAAECBAicjcDoeFbPDgHgs/FTd+YEpicAPGq457TX6EyldKjhvr1Hy8tMtSG97lBQNJK2VEtKA9bloHUV3VO1PBv3QYAAAQIECBAgQIAAAQIECBAgQIAAAQIECJydwOh41olR8a6zO5vaBKZPIDvm8BRdt2tDtkdq04qOKbqS0xIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4P4H6hXOSKSZPTivaf+hE9CcjnUoEZoPAtASA03l0S8XisEfjknnloZiHC2wQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqBCBltULMi3p2rAnk5chUMkC0xIAToddPrHlwLBDOtdt67pFw3kbBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpFoHX94kxTjr2wO5OXIVDJAtMSAE4BDj+5LeMw96plmbwMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUoQmHtlNo51+ImtldAsbSAwIYFpCwAffGRzpkFt16+MyOUyZTIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZlKgedX8aEjmAB5Khb6BOPJEtqPj0D5rApUoMG0B4EOPbonB7r5hg/r2lph3dfbbE8M7bRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYAYEFt1+auerBhzdHsW8wUyZDoJIFpi0AXOwfjH33PZuxmD/qA5TZKUOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgGgXyDbXRftPqzBV3//2TmbwMgUoXmLYAcAqx89NPZDzSHsB1HS2ZMhkCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECMyHQcevaqGmsG750776j0fnwS8N5GwRmg8C0BoC7XtgdXRv2DLvk8vlYfPcVw3kbBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGZEIBex6J4rM5fe/dmnIoqlTJkMgUoXmNYAcIqx4/9+O2My/02XRE1zfaZMhgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMB0CrRdvzIaF88dvmRxYDAZ3fbx4bwNArNFYNoDwHu+8Ez07T827JN2o1/y9quH8zYIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITKtA0vt36fe/LnPJvV98JvoPdGXKZAjMBoFpDwCXBgux7f98K2Oz8M7Lo669OVMmQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGA6BDpevy6aLmobvlSpUIytf/LIcN4GgdkkMO0B4BRn519/N9JJs4dSvr42lr/3pqGsNQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFpEcgno9Uue/f1mWvt+fzT0b21M1MmQ2C2CMxIALjYPxgv/9E3MkbtN62OOZcvzZTJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJhKgYt+8HVRN+/kSLWFvoFT4lhTeX3nJjDZAjMSAE5vYvffPxXHnt+VuZ+L/8VtkW+ozZTJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJgKgZZ1i2LhWy7PnHrb//dw9O49OZJtZqcMgVkgMGMB4CiVYsOvfSFKxeIwU8OCObH8/TcP520QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAqBtFPiqh95Y+TyueHTd+88FFuTALBEYDYLzFwAOFE79vzu2P7nj2b8Frzpkmi/eXWmTIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAZAqkI9M2LJo7fMpS0nnxxV/6h0inMpUIzGaBGQ0Ap3Bb/uBrceLlAxnD9APXtKw9UyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDIEFt51eXTcvCZzqh2f+nYcfnxrpkyGwGwUmPEAcPotimd/7m+j0Dsw7FfTUBdrf+qeqOtoGS6zQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOB8BdquXxnL35edkrRr497Y/Lv3n++pHU+gIgRmPACcKhx/aV9s/I0vZUDq25pjfRIErmmuz5TLECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEDgXgdb1i2PVR27PzPs7eLw3nvnpvzb087mAOqYiBSoiAJzK7P7sk7Hjr76dQWpc2hZrf/LuyNXVZMplCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJyNQONFbbHmY3dGfkTcqVQoxrM//+no2XHobE6lLoGKFqiYAHCqtPE374vOh1/KgLWuWxTr//W9egJnVGQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQmKtC8akFc8jNvi9rmhswhm377y3FwVGwqU0GGwCwUqKgAcBRL8ezP/E0cfWZHhjLtjn/Jz7096tqbM+UyBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMYSmHvVslj/M2+N2jmNmWqv/PFDseNT2dFpMxVkCMxSgcoKACeIhZ7+eOon/iK6NuzJkDYta49Lf+GdkXbPlwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMJ9Bx27pY+7G7oqahLlN1+6ceiy2//0CmTIZAtQhUXAA4hR3s6o0nPvKnSU/gnRnn+o6WuPTn3xFtr7s4Uy5DgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYFggn4tl770xVv3IGyNXkw2HbfuzR2JTMi2pRKBaBbJvfAXdZRoEfvKjfxYHH9uSaVVNc32s+Yk7Y/kHbo7ciEm6M5VkCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIELkiB+gWtccnPvj0W33vVKfe/5Q8eiJf+61dOKVdAoJoEKjYAnCKnw0E/nQwHvevvHj/FfNFdV8TlH//+aF6z8JR9CggQIECAAAECBAgQIECAAAECBAgQIECAAAECBC48gQW3XxKX/9IPROu6RZmbL/YPxnO/8Ol45ZMPZcplCFSjQG2l31SpUIwXf/nz0bVpX1ySTNCdrzvZ5MYl85J5gd8RB7+5KXZ95skonOir9NvRPgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUkWaFrRESs+dGu0rs0GftPL9O45Es/87N/EsWd3TfJVnY5AZQqcjKZWZvuGW7Xzr76TfDB3xtWfeF80LW8fLs/lcrHg9kuj7cZVse/Lz8X+B16IUn9heL8NAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB6hSon98aS7//uui4dW3kknl/R6fOhzbF8//+MzFwtGf0LnkCVSswawLA6RM49vzueOw9fxjrf/reWP7emzIPpba5IZa9+4ZYdPcV5SBw5zc2RqG7P1NHhgABAgQIECBAgAABAgQIECBAgAABAgQIECBAYPYLpKPELnrrVUngd03ka2tOuaHBZNTYTb/15dj92SdP2aeAQLULzKoAcPow0nmBN/zqF2LfV56Py/7dO6NldXYO4Lq5TbHsXTfEkndcE4e/80qk3+zo3tpZ7c/R/REgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEqlogV5OPedetKI8MO+fypZGOEnu6tP+BF2PTJ+6L3r1HT7dbGYGqF5h1AeChJ5IGd9PewOl47qs/cnukgd+RqaahLha86ZLy0rv/WBx5YlsceWpbEgw+GFEqjaxqm8CsFVj0+LYYbKqbte2vtobX9g5WxC0tSX4+DjZ6LyriYSSNyFfItARLHnslCvWnfhOyUpwutHbkB4sVcctLH305irX5imiLRkTkCpXx/6hLv7UlSqcZMsszmhmBXLFC3ouHN88MgKtWrED6bi71XlTM86mUnxXpn2Xei4p5LaJS/p8zbYf3onLei5oK+R01/V3Ze1E570Vt70BFNCb9uzXvRUU8inIjansq471IG5NvqI05ly2NtutXloO/6YiwZ0rHX9oXL/3OV+LgI36HOZOR8gtDIHf/NR+vjL9ROA/v2jmNsfLDb4gVH7g5alsbxzxTOiz0iZcPxIltndG760j07jsafQe6olhBP8zGvAE7CRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJVKFA7rykaFs6JxqVt0bS8PRkFdkE0r5gfuXG+wN697WC8/L8ejL1ffEYnwCp8L9zS2QtURQB46LZrW5N5gN9zY6z44C3RuHjeUPGE1oXkW04DR7pjsKs3Bo8nSxIoLiZLoW8gin2Dry4DhSgmS2kwXYpRKiRLuk6++VwqvrqO9Bv6SQ/jtKzc07i8GhFjH+p9PKJoQg1UiQABAgQIECBAgAABAuMI+DVjHCC7CRAgQIAAAQIECBAYV+CUQZXTgqGhlpPtXPJPpCNHpf+m5cmSS/M1yTqXj1y6ToZqToO2uZqayNfVRC5Z0nW+sTZq6usin4xsWdNcH7XpknTyq01Gea1Lgr+nm8t3rAYf+d6O2P5/Hon9D2wQ+B0Lyr4LTqCqAsDDTy/5QbPgDevionffEAveuD7y9bN2pOvhW7JBgAABAgQIECBAgAABAgQIECBAgAABAgQIELjQBfoPHo+9//hc7P67J+L45v0XOof7J3BageqMjCa9bzu/+VJ5Sb9BsvCOS2PhnZdH+82ro76t+bQQCgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpPIB3i+eC3Nsf+r74Qh5/cFuXRWCuvmVpEoGIEqrMH8Bi8zcl48fOuWh6tlyyOljULk7HjO5Kx5OfpJTyGmV0ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgakWSKfp7Nl1OLp3HIoTSe/ero174+izO6O/8/hUX9r5CVSVQHX2AB7jEXW/0hnpMjrVtTdH/fzWqO9oibpkrPnymPPJuPPlMeib6svj0adDSdc01CZj1de+OmZ9Mn59eez6dCz78pKMcZ9Ptstj37825n15+Pvyf1695FB+dAPkCRAgQIAAAQIECBAgcD4Cye8aEgECBAgQIECAAAECBCZFoHTyLKXSa5l0lWyX88l2KRmNtZwvFF/dTtbFdDtdBpPtgUKyLkSxbzCK/YNR6B2IYrIUuvtj8ESyHO+NwWM90X+kOwYOd0ffga7yvpNXtkWAwLkKXHAB4DNBpT9c0uXEmSooJ0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQIUL5Cu8fZpHgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAhMUEACeIJRqBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqHQBAeBKf0LaR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQkKCABPEEo1AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVLqAAHClPyHtI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwAQFBIAnCKUaAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKl1AALjSn5D2ESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYIICAsAThFKNAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEClS4gAFzpT0j7CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMEEBAeAJQqlGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBShcQAK70J6R9BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmKCAAPAEoVQjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBApQsIAFf6E9I+AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITFCgdoL1LuxquVzkG2ujpr428g11ka+riVyylNe1+cjVjFjyuYhkySXHlNdpPk1JPi0qp+GNtPy1MisCBAgQIECAAAECBAicj0DpfA52LAECBAgQIECAAAECBE4jUHr1F43yang7KSuWopQskZSV18l2cbCYlBejVChGcaAQpSSfrov9g1Hse21JtiUCBKZemXlEGgAAQABJREFU4IINAKcB3OaV86N5RUc0Lm2LxsVzo35+S9R3tEbtvKaom9MYtclS01SXLPVT/yRcgQABAgQIECBAgAABAgQIECBAgAABAgQIECBQxQKlJEBc6BmIwom+GOjqjcFkGTjSHf2HTkTfga7o23csenYdju7th6J395EqlnBrBKZW4IIJADde1BYdt6yJttddHHOvWhYtqxaUe+5OLa+zEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIpAK5fD5qWxrKS8OiuWOiFLr7o+ulfXH0mR1x5Iltcfi7r8Tg8b4xj7GTAIFXBXL3X/Pxqh0oLO3hu/jeK2PRPVfGnEuXeOYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKzUCAdTvrQt1+O/fc/H/sfeLHce3gW3oYmE5gWgaoLAOdqa2Lx266KZe++PtpvWDUpiKV0DPv+ZJz6wWRJx61Pl2QM+3T8+vI6HdM+Heu+kNQrpWPcp8Pevzb2fXn9WjPS7TSNCLmP2Hx1n/8SIECAAAECBAgQIEDgHARy53CMQwgQIECAAAECBAgQIDCmwNAvGrnXNpJVLvkn8uWNyKXlyZKrSZZ0uyaf9PJN88k6idfkavORT6bkzKfb9a+ux7zeBHcW+gZi/1eej52ffjyOPr1jgkepRuDCEaiaAHBNMmTA8vfdFBd/6NZoWDhnQk8wHVO+d+/R6O/sSsaX707GmT/x6njzyRAC6dAChZ7+KPYOlCcnn9AJVSJAgAABAgQIECBAgAABAgQIECBAgAABAgQIEDi9QBIczjfURk1TfbLUvTocdGtj1M5tjPq2lqib31KO8TQunRe1zQ2nP8eo0qPP7Iytf/pwHEh6BUsECLwqMOsDwPn62lj+QzfH6h99U9TNaz7jc00nFj/+0v7oenFPHN+yL7q3HYxiMtG4RGC2C+hFXjlPMPl+W8Uk70XFPIr0+5AVk7wXFfMovBeV8ygqqiV+XlTU46iYxlTKe+HPkIp5JcoN8V5U1vOohNZUyjuRWvh5UQlvxKtt8F5UzrOopJZ4LyrpaVROW7wXlfMsKqkllfBe1LU3R8vqhdF6yeKYe+WyaFwyb0yiro17Y/PvfTUOPvzSmPXsJHAhCMzqAPCiuy+PS3727WN+6NMPfDom/NGntpkc/EJ4oy+we3zw3+Wjp6MS/ii+wODPcLu3/1ohmg+fYec0Fn/9P+Sjb573YhrJx7zUm3+5EI3HxqwyLTsf+E/5GGjxXkwL9gQucufHC1HfPYGKU1zl/l/NR6HRezHFzBM+/d2/WIjavglXn7KK//gb+SjVei+mDPgsT3zvzxciXzjLg6ag+pd/u2YKzuqU5yrwtp+Z+ZeimLwSX/lN78W5PsPJPi43WIq3/kIyH9UMp8Gkk85Xf817McOPYfjyNb2luOffz/x70Z/01/jaL3svhh/MDG/UnSjFXb808+9F79yIb3zcezHDr8Pw5RuOluItvzLz70V3e8RDv+i9GH4wM7zRdKgUd/z6zL8XIxkaL2qLthtWxvzXrxtzJNg0JrThP38xul/pHHm4bQIXlEDtbLzb9Fsel3/8+2P+G9adtvmFZNjmg9/cFAce3Bh9+yrgb91P20qFBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECExHo3X0k9qbL578Xcy5fGgvvuiLmXbP81bmHR5yg45Y1cevf/kRs+7NH4uU/+kaUBmf+C5QjmmeTwLQIzLoA8NIfeF1c+nNvi9pkTPjRKZ23d99XnosDX9tQnr939H55AgQIECBAgAABAgQIECBAgAABAgQIECBAgACB2S2QTveZLulcwUveeW2037Q6csn8wkMpX1cTqz9yeyy849J4/t9/Jro27B3aZU3gghCYNQHgfDIZ+BVJr98l77jmlAdTGizG/q+9EHu/+EykQWCJAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgugV69xyNrX/8UOy779lY9t4by3MFj7zj1vWL46Y//7HY9Ftfjp1/892Ru2wTqGqBWREAblrREdf93gejZc3CUx5G14Y9seMvH4vevUdP2aeAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgugV6dh2Ozb97f7RdvzKWv//mqO9oGb7hfH1tXPaL3xfzrlsRL/7Hz0Wxf3B4nw0C1SpQ8QHg9MN6ze98IOrbmjPPoNA3ELs+/Xh0fmNjplyGAAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgwhM48uS2OPbi7liRBIHnv2F9BmBpMlR00/KO+N7/+6kYONyd2SdDoNoE8pV8Qwvfcllc/z//xSnB3+6dh2LDr3xe8LeSH562ESBAgAABAgQIECBAgAABAgQIECBAgAABAgSmWaDYMxDb/vSRePl/fCMKPdlpQ9uuXRE3/Z+PlOcOnuZmuRyBaRWo2ADwkrdfHVf/9vsi7Zo/Mh16bEts/PUvRt++YyOLbRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoCxx5Ymts+NXPR++eIxmR5ovnx41/+qPRdHFHplyGQDUJVGQAeNHdV8SVv/buyNfWZKz3fvnZ2Pq/vxmlgUKmXIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDASIG+/V2x8Te+FMe37B9ZHI1L5sUNf/xhPYEzKjLVJFBxAeCO29bGVb/xnsjVnGxaqVSKHX/17dj9d09Uk717IUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQmEKBQnd/vPRf/jGOfG9H5iqNi+fF9Z/8cNR3tGTKZQhUg8DJKGsF3E3rukVxzW+/P/J1J3v+lorF2PrJh+LAAy9WQAs1gQABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDYJpCPLvvzfvxYHH3kp0+zmFR1x7X/7YOQbstORZirJEJiFAhUTAK5rb47r/uBDUdvSkGHc/hePxeHvvpIpkyFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwYYFktNltf/atOPLU9swh865ZHlf88g9mymQIzHaByggA53Jx1X9+TzLWelvGc/fnnoqD39yUKZMhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcNYCSRD4lU8+GMc378scuuRtV8eKD96aKZMhMJsFKiIAvPqjt8f816/NOHY+tDH2fv57mTIZAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAucqkA4HveX3H4iePUcyp1j/b+6NuVdelCmTITBbBWY8ADzn8qWx+qN3ZPy6Nu6JdOhniQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBkChS6+2PL7301Brv7hk+br6uJK3/9n5oPeFjExmwWmNEAcK42+TD92rsjn6yH0sCxnnjlfz0UkXTDlwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMtkB/5/HY9icPZ07bsmpBrP3JuzJlMgRmo8CMBoBX/vBt0bp2UcYt/bANJkFgiQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBUCRx9ekcceHBj5vQXJ3MBt166JFMmQ2C2CcxYALhx6bxY/WO3Z7w6v7kpjj23K1MmQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGAqBHb97Xej70DX8KlzNfm47N+9czhvg8BsFJixAPDaj90VNU31w2YDXb2x69OPD+dtECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJhKgWLfYOz41GOZS7Rdd3EsuufKTJkMgdkkMCMB4NZ1i2LJO67OOO3+u8cjnXRbIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBdAunotEee2p653NqP3RmRz2XKZAjMFoEZCQCv/pdviVz+5KW7dx6Kg9/aPFvMtJMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCKBHZ9+rtRKhSH76hl1YJY+s5rhvM2CMwmgZNR2GlqddPFHbHorssyV9v92ScjSpkiGQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLTItC3vysOPvJS5lorf/gNmbwMgdkiMO0B4JX/7PXZ3r/bD8axZ3bOFi/tJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqEKBvV96NkrFk72AW9cvjvlvWFeFd+qWql1gWgPA+aa6WPJ912ZM9335uUxehgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMB0C/QfPB6Hv7s1c9ll770pk5chMBsEpjUAvORtV0dtS8OwS/+R7jj8+NbhvA0CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECMyWw/4EXMpde8Kb1Ub+gNVMmQ6DSBaY1ALzsn96Q8Tj4cDKWesnkvxkUGQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRkR6H6lM7p3Hhq+dr62Ji76weuH8zYIzAaBaQsANy1vj3lXLx82KRVLUQ4AD5fYIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDCzAgcf2pRpwJJ3XJ3JyxCodIFpCwAvuOPSjMXxjXsjHUtdIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFApAoe+/XKUBovDzWlduyialrUP520QqHSBaQsAd9y8JmNx5OntmbwMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZkWKHT3R9dLezPNaL95dSYvQ6CSBaYtADzvuhUZh64NezJ5GQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKVIND1YjaO1fa6iyuhWdpAYEIC0xIAblwyL+rbmocbNNjdF727jwznbRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoFIETW/ZnmjLnsqWZvAyBShaYlgBw66VLMgY92w9l8jIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKkWge9vBKJVKw81pWbMwcrU1w3kbBCpZYHoCwOsXZwx6dh3O5GUIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVIpAsW8w+g8eH25Ovq4mWlbNH87bIFDJAtMSAG6+uCNj0LvnaCYvQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCSBHr3ZuNZTaPiXZXUVm0hMFJgegLAK7IB4L7OrpFtmPLtXH1N5Otrp/w6LlCZAvnGusjVTMurXpkAWkWAAAECBAgQIECAAAECBAgQIECAAAECBAictUD//mw8q3mFHsBnjeiAGRGYlqho0/L2zM2N/sBkdp5Hpq69OdpvXB1pj+O6ec1R19aULM1R01RfPmuhbyAGj/XGwNGeZOmO4y/ti6NP78h04T+Pyzt0JgVyEc0r58fcq5ZH67pFUTsvefZzGqO2tXE4+Fvo6Y/BruT5J0v31s449tyu6Nq0N0r9hZlsuWsTIECAAAECBAgQIECAAAECBAgQIECAAAECFSgwukPj6HhXBTZZkwiUBaY+AJzPRf381mHudMLs/kMnhvPnu1Hb2hBtN62OjptXR8vaRZHLJZHAM6SahrqoWVgXDQvnlGu037AqVnzglujecSiOPLUtDjzwYhS6+89wtOJKFEiD/kveeW20Xb+yHPAdq43pFwHSpWHR3GhN3pVFd10RxYFCHHlyW+z++yejv/PkWP5jncc+AgQIECBAgAABAgQIECBAgAABAgQIECBAoPoF+g9m41lpfEEiMBsEpjwAXN/RMtwDMwUpnOiLUqE4KTbzb1sXy99/c9Q0v9rD91xP2pwMUZ0ui+68PHZ/9sno/OamiNK5ns1x0yGQBnIXv/3qWHT35ZGvO/fXOJ20veOWNZF+GeDAgxvKzz+d2F0iQIAAAQIECBAgQIAAAQIECBAgQIAAAQIELmyBgSPdGYCGRa92MMwUyhCoQIFzj5xN8GaGetsOVR840jO0ec7rumR434v/xW0x75oV53yO0x2YDhd88T+/LRbccWls/eOHondPdnLv0x2jbPoFGhbPjfX/5q2RfrlgslKuNl/uEdy8ckFs/m/3R7F3YLJO7TwECBAgQIAAAQIECBAgQIAAAQIECBAgQIDALBRIpxQdmUbHvEbus02gkgTyU92Y0UG6gWPZD8vZXj8dX/3y//SDkx78HdmO5ovnx/qfeVs0XtQ2sth2BQg0JT21L/m5t09q8HfkbaXzB6fB5XzDlH83YuRlbRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVJjA6AFzX1lxhLdQcAqcXmPIAcN3cpsyV0yGgzzXVzmmMNR+7K2pbGs71FBM+Lm33+p9+azQunTfhY1ScWoF0vt/1P/PWGP1OTfZVW1YviMVvvWqyT+t8BAgQIECAAAECBAgQIECAAAECBAgQIECAwCwSKA0Woth/ctrIdFrJdIpKiUClC0x5ALh2VAB48BwDwOkQvWt+4s5omN86baZpoHGd3qDT5j3ehZa958aobT774H+pePYTOi+658pIv3AgESBAgAABAgQIECBAgAABAgQIECBAgAABAheuwGB3f+bm02lKJQKVLjDl49zWzc0G0QqjPigTBbro3TdEOjzv2aRSsRgDx3pjMB2jPZ8rDxt8tr2H65Pu/Evefk3s/vsnz+bSUb9wTrRdtyLpQdwW6Q+DNBCeBpTTQPZgV9KmpF3pcNj9h07Esed2xfGX9kWUxg9U1jTXRzpE9VgpPX/PrsOZKrnkWynp3MZp79bGJfOivr0l0h9aA8n1jz67M/bf/3ym/imZXCT+i2PuNcujPgnC189rjtq25L6Sb7oMHE/u5eCJ5F6OR+/eo3Ho268k93d+Q32Pvn7L2kXRcfOa0cWnzadt2PePz8WJVw5Ef9KudD7f1K1h0dxYcPsl0XHr2ki/pTNWqmmsi/Zb1sSBr74wVjX7CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSoWKI9sO2Lo53LnsSQOIRGoZIEpDwCP7gpfSIJxZ5vyTXXlwN1EjzuxZX90PvxSHHlyW4wOOKdzu869clksvvfKSIOKE0mL7r0iDjy0sRwsHat+2s5Fd10RbTesjOblHWesWh7CeNnJ3UvefnU5KHzkmR3R+fUN0b3t4Mmdo7YaFs8tD009qjiTTQOfG3/9i8NlaSBzWRJAHz0fc/pDqjE5Xzp8wZkCwHUdLWWr9htWxZnGtk/P05QEuofSsnffGIef2hYHHngx0mcxGWnR3VdM6DQ7P/147P9KEsweFUxP34PurZ2xPVk6H9wY63/2bVHTUDfmOZsM/z2mj50ECBAgQIAAAQIECBAgQIAAAQIECBAgQKDaBdJOZiNT2uFMIlDpAlMeAE6DoiPTyLHSR5aPtT3/DevHDdalxxcHBmPX3z1RDjye6XzFvsFyYDgNDs+5bGms/vE3jzuscL6uNpa+85rY/uePnum00X7z6lj+/pvPeX7aNIi6ILnP+a9fFwe+saHc47jYk/2hkl68d9eRSIc0ziU9ms+U0l7HQ2n+G9fHyh9+w1B24uvk9AvffFmkPa/T3rBnk9Jezh03rS4ve77wdOz5h6fP5vDT1m1Zs/C05SML9ye9dfcnPX/HS2mAffdnnowVP3TLmFUbl5x0HLOinQQIECBAgAABAgQIECBAgAABAgQIECBAgEBVChRGzAGc3uDZxkyqEsVNVbzAlM8BPPqDkAZgzzYtfMtl4x5SSnp8vvI/Hxwz+Dv6JF0b9sTm37k/Cj3Z8dtH10vzc5Jew6dL6dDKa//V3bH6x+445+DvyPP+/+zdB5xcZ3no/2f69t6kreqSLcmSJVtyEy6AMaaEDgZCCSQ3CVzSLqRyk3/uJ+0GbnIhlAAJkHAJEBwDtnHvVbYsWc1qK2mbtvfd2Z3+f9+RZzRntszMamfmzOzv/XA45z3nPee853tmFuxn3ufVgd26W7fIlf/fu6RIpWuOLzqAPtu/eGoBba5H7pZesVpaPnJd/CUS1vUo6Q1/8BZpvmvvZf8hW/W2HbL2N28Rq3PpvzXQKbTjRy/HP0RQTcSeSppud8dQ/CXm1K0FS+/znIuxAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJOIOgNGPpsTXHQnOFkKghkSCDtAWAdTIwtQZ/xixJ7bL7totZqKVBztyYqes7X8Ve7EjWbczycFniRkb2RE1xq3lsdVDUUi0XW/MbNUr6tybB7OSo63fJ6FVjWKZ/jy8wiKaIjbQubKqXlw3vFYkvxFasAtA7Ylm5siFzqstcVV7dKy8eXMAr59TsXqGfRAf7FlqlT/ZLKjwsKF0nRHXlg7/BUZJM1AggggAACCCCAAAIIIIAAAggggAACCCCAAAIIrECBUNwI4Pi41wok4ZFzQMAYnU1Dh+cEIAPBlO7irClN2F6P/tQB4KWW0VfOS9NE4vTNpRvqZeTFs9HbtHz0Oqm4qjlaX+4Ne0mBrP/dN8vJv75P/OMz0cu7O0ekau+6aH2+jdXv2CGuJALn8efqEcN6juTlLjol9NhL52TsYGfKl548dkEO/vr3Uj5vwRNU4L7qusX99Lmz/RMLXoIDCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkP8CelrO2GJNdeBd7MlsI5AhgYwHgPUozlSKs6YkYfPxQ10SmPIkbLdgg0BI+u47LBW7WhdsIqrbsQHB4nV1UnPTxoXbL9MRPfJYB3Nj5x92dw4nvHpR69z00YlO0imnk30m75hbJo/1hOcjDqmgfokaMVy4evE5c5tVcHnyZJ8E3IlTbifq65KPqxHOLb96vZSo95eojDzfnqgJxxFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCPBXQMJLZY7ClmXo09mW0EMiSQ+QCwCramUnQANFFxJ5ESOdE1Bh97TfSSbKl/y9akmnpHpqX35wdl+tyQzPaOiQ4k28sKpVgFW6tv2CAVO1sSXqfquvVqftuD4p+cDbedUSOAUy068O4ZnJTZnjF1nRmxl+p5dYvEUVksEb/62xM/k/5D1/3jl2ToyZMS/0evcnebtH7ixgXn+3Wo5666fr0MPnI81e4vS3u7mkt4zaf3SemmVQmvN364S2YvqPdFQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgRUrMGdgo5UA8Ir9MOTQg6c9AKwDnoZiMdQSVubMuzvPGb5x9zx707fL1VAu5UmkftYjhk9/+UHxqSBwbPFPzITnK9ZBxpaPXp9w1K3VYZO6265QQeBXwpcJzHjDwVxXbeL02PqEme5R6fj+s+JWQeiFih5pXbGzdaHD0f3nvv2UjL18PlqP3RhV+wOzPln/uTfF7jZs6yBxNgLA1Srw3Pj+a8Re7DL0Z76KT41u7vz+c/MdYh8CCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACphZIewA4FIwbGq9S8KZS4keZzneuJcVrzneNVPaVrK8Ti5pHdrGig4in/vb+6Kjdeduq4LgONOoAb6I5fUvU/MOxxTfqlmQCwOOvdkn71x8TSTDyunhtrSTj6CgtkNpbNsd2Zc52yB+UhVIg6Ps4KotE9z8TpbCpUpo+tEdKVYrqZErQ45f2rz0mvpg5l5M5jzYIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQfwLxsZNk4lb5p8AT5ZpA+gPA8bnREwRO4wG9w1Pxu+bUdRrjTBZXXeKRtxPHLywe/I3p8PAL7QkDwM4k7hlzyfBm0OuXrv/3QsLgr26cTDBZt2u+a69eLbnowHnZ1iYZfvrUkq+RzIm2EpesfudOqdm3UQW2k0vHoNN1t3/1UZnpSj3FdjJ9og0CCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjklsCcGENc3Cu3noberhSBjAeAxZZcMC7yArxDiQPAenRnn7waOWVJax3YrL5h/aLndv3H/nDg0lVbtmg7fXDqdH/CNpEG02cGRI+UnvNHJNJArR1q/lqLGikc8gVi9i6+qec01kHNZEqyAeBkrpWojZ57OF3Foj5ftbdtkVV3XiW2ImfSt5k60y9nv/GE+Bn5m7QZDRFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyHeB+BHAQQLA+f7K8+L50h4A1il1Y4vVmdotkxkBXLK5QZxqPlzv4GTsrZLetjh1Cua1kqhv/smZ8DXtKg1yojLbN56oSfS4NvKNzYizauGRzHrkrL5v/HzC0YvMszHdMTzP3vl32ZKYG3f+M1Pf6yhPTwC44upWaXzv7qRHM+ue6zmLe+4+IENPnJA581Wn/micgQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnkkYImLa8XHvfLoUXmUPBJILRq7hAcPzPgMZ1lVsDWVkkwgVQdHm1Tg7+zXH0/l0tG21devF1vh4qNFQ6GQTJ26OKrXN3ExEBy9wDwbhasrRI/sTaZYCx3iqFg8KKrv75+YTeZy0TaegYnodqINPWdxpoqjrHBZb1XUWi1N779WSjYa50lOdJPRl89L94/2q+B75p49UZ84jgACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAuYRsMUHgNXAMgoCZhdIewA4GPdFSDTKNh7M0z8hU+0DUrKuLv6Qoa5Hf9a/dZv033/EsD9RpXx7kzR/YE+iZjJ7YUwCbm+4nXcg8Ujjkg31MvRUcvPc6meLTyEQ3yHfqFtC/uTTP+vzvYOJ02dH7uNZ4ujpyPmprC321NKAL3RtR2WRrH7X1eH5k/WPAJItE8d65MJ/vSLuFEZIJ3tt2iGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggED+CMQPbAzMXIwV5c8T8iT5KJD2AHD8F8FW4EjZUc9lmygArC/a+K5dUri6Urp+8ILE3zf+pjoIqUf+Nn1ojyQTkBw72Bm9hGcocQC49MrGcErnhHPwqrhl9Q0botdeaCOZe8afG/Ak/ysUTxJBbX39gYePSd8DR+NvlXS9uK1a3F0jSbefr6H+EUH9W7ZK/Zu3itWV/EdYz/OrA7+RkdzzXZt9CCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEBEwBoX14rPfBtpxxoBMwkkHz1bYq99cWmLlzLX7OiB8yrF7zWSzNyxVXvWStnWRhlT5+gUv3rkru6DHmGrR4zqeXZLN6+SmjdskmRTEeuUz/0PXBpZPHWyT0LB0KKjdh1qvt6NX3irnP4/D4lnofmAbRZp+7V9Urm7LaHu5InehG0up8HU6X7ReesTBVRrb90ivslZ5aGCwCotdTJFX7Nq7zqpvXmzFDZVyom/vk/0iOaUiw6WX7c+POo3Ucrs2GtPqVTcvT8/KJOvpdcw9p5sI4AAAggggAACCCCAAAIIIIAAAggggAACCCCAQO4LxMe1/CpGQkHA7ALpDwCPG+fLtRctPtfuvGCBkPTdd1ia79o77+H4nfZil9Ts2xRe9DE9f24qKYLjr9f7s4Ph4Ghkv06XPPZKR8LArQ42b/z8HeHgsfvcUDjlcNDnl4KGcilaUyvVKihaumVV5LILrnVgdvCxEwseX44DgWmPDD19SureeMWil7PYrNL47l1SuatNhp89LXpkdPwcujb1jl21peKsKQkH23Xwdykjv2M7UryuNvz+i1qqY3cntV3UWiXrPnNbUm3jG42+dE46vvts/G7qCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsAIE7MXGuJYvLu61Agh4xBwUSHsA2D9pDADH/1IiWbPBx09IUWt1UumS4695OcHf6bODKjB6Ov6S4aBuMiN39UjgpvddEz5/qYHooWdOiQ7Qprv0P3Q0PEo3mZTY+l3oRQfl/apv+hcvIX9QHFVFYi9yLXtX9cjjpQR/dUesjqV/zHXAm4IAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIrT8DisBliDEFfIOEUpCtPiSc2o0Dao1vxc+A6yguX7ND5b8+Lnsc1U8XdMSxn/vHheVMd62P9aj7cVMpSAtGzKn107y9eTeU2S26r0zJ3/3h/yufrEdd6VLNO75yO4G/KHeIEBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQOAyBeJjWr7R6cu8IqcjkBmBtAeAdbrk2BL/ZYk9lmg7FAjK2a89Lu7O4URNL/u4vsfpLz8oAbd3wWv1/PglGXnx7ILHL/eAd8wtZ9QcwpkY/Rvpqx5p3XtfZgLOkXuyRgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTMJhAf04qPeZmtv/QHgYhA2gPA3uFp0YHbSLGXFMjlpNXVqYZP/NW9cuHnB8MphyPXXa51KBgKz4V7+u8XD/5G7nf+X59OSxDYMzAhZ/7hIYkfQR25bzrXvfcclL5fHhFtsdxlpndM/CqwTUEAAQQQQAABBBBAAA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QGDA8Rn/nWcJAKAiYRSH8A2GEcqRoKBFN69ETpjvXFQmqUZsd3n0kt+BvphRotrOfLTRQAdqh0yK6GcvH0XRo5quf6bf7w3siVln1dp4KUvnG39N9/xHDtGTWadrEAsG5cfdMG0SNwUy3lau7ipg9cm+ppi7bX8w63feJGOf4/75GlpADXF/eouZH1suSi5pG2FxdIsQoiV+1dlzCttf6hQu+9ry75dpyIAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACuS8Q8hkDwBa7LfcfiifIe4G0B4AtNuMXITw/bQqszpqShK31yNLLCQ7q9MTujiEpal18hGmBmk83EgDW/Vrz6/tSmu834YPM06DxXbtEz1mrU1ZHirtzRKpviNTmX6962475Dyyy11FZJGs+pZ9Jz3ubXAmqEcnWJP7YOatLwimlO9VI3nSWVXoe5ps3G26h02Wn8osc/YOC7p+8JN6hKcN1qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggMDKEtAxg9hiUQPOKAiYXSD9AeD4YGIwtRHAOnCYqIwdSj7170LXav+nx8RRXrjQYTXvbkhmukaix+vedKVYHYn59B+GmZ5RcZ8bUoHcIQmqX4oUtVZLcVtNOOBssRtHSEdvELPRcOf2uADw5c2nG3Ppi5uvv5O6N6pnUqN1ExV357D0/fKITB67IIEZr1hd9vAI6oa3XbXoyOSafZtk8ImTBsdE90r1eMn6usuat9g3OSvnv/2UwTvVPtAeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE8kQgbupRizVxXCdPnpzHyGGBxNG+y324uABw3A8lEl7dlUQA2DsynfA6iRr4Rt2il2SKrcQlNTduSNg0pAKrHd97TkaeO2NoO/J8e7hesrFe1n32jQlHp5ZubJCitbXiPntxTlodiA6pPzjJjtTVQejhZ8+oOXI7ZPbCmPinZsVRUSR6xK+zslgmVCDXWugQPZ9xojL68nk5960nDem2dVrnsQMdMv5qt6z777dJ2ZaFU09XXrsmrQHgRP1f6Lg26vnJyzLy/Bnl41moGfsRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEBgBQnoeExsYQRwrAbbZhVI/88U4r8YKY6MtxU5E9oFZ3wJ2yxng8rdbQlHyurUyOe++eSc4G9sP6ZO9cvpLz0g/unEAcfq69dHT9UBV+9wcumJdXD89N8/IJ3fe1YmjnSHz9Pne/onZOpEnwp4tot/YkYq1HzGidIkzw5MzAn+RjulNkL6mb/xhARmF34flbvaYk8xzbbFYpG6N10hq96+Q+wqwE9BAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBOIH46U61SmCCGRDIO0jgEOBuJTPaj7WVIpvTI3Kbale9BR7WcGix5f7YEFdWcJLjqmRsnrEbaKi5/cdeOiYrH7X1Ys2jb/nHNcFzu747jOiA82JiiuJZ9J92PHVjyS6lEqNbZz3OfYEV21pOAW2nnfZbEWPhq69dYvoUcrd/7FfRl48a7Yu0h8EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBDIoMCcAHCKU51msKvcCoGoQPoDwHFfhPgvSrQnC2x4hxOndy6oL1/g7OR3l6sRsEWtVYueoNMoe4emxJlEsHTqdOKga+RmybR11pVGmie9Hj1wXiZf602qvQ7MJlMWC+4mc75uU9hYKWYMAEf6by8pkLZP7RO/mt944nB3ZDdrBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQWGkC8VOdxg98XGkePG9OCKQ9ABz0BQwQFvvCo0MNDV+veJJIdVy5d630/uLQfKcnt0+l/22+a094PtzFTpjpGg0HgJOZl3iqfWCxSxmOTZ8bSjinrx6dKqqfksIkyiMvJD+C1Vmtrp+hYq8oTNud9MjdOWnDlZsOXNsKneJSgfSybU1Ssq4uYR9aP3aDHP/iPRJIIkV3wovRAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJOwBoX19LTYVIQMLtA+gPAcfPzWp2pBYD1iNtERacm1kE9PcftUkrZ1saEwV993chI3VDcqOb57hn/B2G+NpF9SU0YHp5L2TjReOT8hdYeNWdvsiU+UJ/seUtp5yhLXwB4pns0YZf67jss+p23fXqf2IsWnu9X97N0yyrR6bwpCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsPIErE5jKC0QF/daeSI8cS4IGD+1aehxYNZnuKrV5TDUE1WmTvVJUP2aIlFAtfXjN8iJv/yFhOcMTnTRmOP20gJpet/umD3zb872jol/cjZ80KOC0kUJ5iUu3lCfdJrjYjUaNVFqbM+ICoSnFv8Vz9Dk/A8zz17voGq7ZZ4DadjlKC9K6ap6Tt5V79i56Dm9Pz8oo/vPLdom9uDE0R4ZP9Ql1devj909Z7uoqYoA8BwVdiCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsDIECACvjPecb0+Z/gBw3C8hbHG/lEgEqoOuo2oEZvXedYs21aM113/uTXLum0/IbN/4om0jB+0lLtnw+7dLwaqKyK4F15Mn+6LHvEmMrC3d2CCDjxyPnrPYhm6bqHgHkg/m6msF3F4JeZNPQ+BJ8vr6XXh1MPoyylSMZTKX0fMTF9SXLdq09g2bUwoA64sFvf5Fr6kP6pTRFAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEFiZAlaXMZQWP/BxZarw1GYXMH5q09Bbf9z8qXPmZ03inoOPvpYwAKwvU9hUKZu/+Hbpu/+IjDx3RgUqp+e9uqOySGpv2Sw1+zaJvXjhFMCRk0P+oAzEBHNnexMHmCt2tkj9W7ZK/wNHI5eZd63b1d1+5bzHYnfqEciplFAKcwXr6870JE6drNs51Py9nf/2XDjArOvJFv0HsmrPWqm6br3BMpnz3R3DCZuVbKyXVb+yU3rvOZiwrW5Q2FgplbvaErb1TcwkbEMDBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyE+B+LiWf+pittj8fFqeKl8E0h4A9o0bA2jxX5RkIN3nh2T67KAUr61N2NzqsMvqd+5UKYN3iD7P0z8hvolZsdit4Xl+nVXF4UCxxWZNeK1Ig8EnToSvE6nrUbCN778mYfC48T27xabmmL1wzytquOnc/M06/XDLx65X6Z8X74sO5g4+dSpy+7SsJ471yKyySjTStmR9vWz583dK1/97UcYPd837XLEdLFhdIbVv2KQCv+vEVugMH0rFXp+gA8Ah5ZcoTfaqO6+S4tYaGXrmlIy/2i3zTcTurCmRyt1rpOGOberdXOxPbH/jt2cvpBZ4jz+fOgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOSugK3YGEvwq5gTBQGzC6Q9AOyPG0GZzIjb+dDO/8vTsumP7xS7CqgmUywWixSvqQ0vybRfqI0ewdz7i0OGwzp18ODjr8mqt+0w7J+vogONdbdtEXfniMx0j4SDmM6aUilqq076WfRctZ4k01rP14ek9qn4dP8DR6T1YzckbO6sLJZ1v32raJvxV7tEj4j2T86IHnSsA+w6ZbMOtLrUc+r65RadBnxYjeiuuXFDwkuVbW0Uveh35B1zi/5DrLd1sNeh5nt2VpckvEZsg+n2wdgq2wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIILBSBCwSHdymH1kP2CNz6Ep5+bn9nGkPAPtUEC622FUQbilFj+Q9980n1Ty/b0w4YnYp15/vHB04PPeNJ+ZNdzyg0lLXqHlndVAxUdEThJesrwsvidrGHw/6A9J336vxu9NSH3m+XerefKUUJjEnsu6ADubrUcyZKBfuPqBSNrca/tAudl9tXlCn5g3WyxLLyP6zSafGXuItOA0BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRMKqDjIHrAYaQEpjwJM6NG2rJGIJsCi+ceXoaeeYanDFdxlBca6qlUJo9fkO4fvZTKKUtuq4O/7V99VCZP9M57Df0lb//HhyWdk33rX5J0/Msz4RTI83ZimXeGAkE58w8Pi3d0/rmTl/l2KV1OjwLu/MELKhV0MKXzltpYv9ee/3x5qadzHgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOS4gKO8yPAEnqFJQ50KAmYVSH8AeND4ZbBfRgBYIw4+9poaCfyEpHOSbZ3aOBz8fW3+4G/kZeq5ac9+/XE112x6gpLd/7FfRl86F7ldRta+kelwENjvVr9iMVkZffGsnP2nx8IpndPZtYDHJ+1feUR8o8bR6+m8J9dGAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABcwk4KuICwAPGmJe5ektvELgkkPYAcHDGZwjWWu02WWoa6Ei3R18+L8e/eI+MHeyI7FqWdSgYksEnTsixP7lbJhMEfyM31KOST/zVvTJ9dvnmivWooPkZNbpYB7uzUWYvjMlrf/Hz8Py+y3n/8aPdcupLD4h3yDgqPJV7jB/W13hQzak8nMppSbedOjMgJ9SzT53qT/ocGiKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggED+CTgq4wLAcYMe8++JeaJ8EUj7HMAaarZ3XEo2XJor11lbKjql7+UUff7Zrz0u5TtapPrGDVJ25WrRweWlFD3Prg7kXrjnoMx0jaR8CX3Oyb+5T2r2bZJVb79K4lMCJHtBnXZ4UM0t3Kvm/A35AsmelpZ2eiSwHgVdoebdbXzPbnGpd7aUokdH67l0+x86KrM9Y0u5xJxz3CrYfuIvfxF+99q7qKV6TptUd0y3D8jAI8dl9MB5NYt7qmfTHgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBPJNwFVjjI3M9o3n2yPyPHkqkJEAsLtzRAWA66OErpoS0UG85SjjhzpFL7Yip1Rc3SqVu9ukYHWFOMoKxWKbf4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7.33% 77.2% 0%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;-80&quot; y=&quot;300&quot; width=&quot;930&quot; height=&quot;70.24927160893493&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-2&quot; value=&quot;&quot; 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TL5FJ1WGwOLvbI2aZOSImU57b14VxeQLU1JlCCz59iuRHyzOeGP23Lo6Ssk3cqXKEFjy6MuRT0eWmeG0+7Y15W9wz3AzXP41gaXf2hK5mX8tYvcb1nomFSRw0SNbZrw1paSXx57bvBcz/iCGGlAqxUXfmvm/7CwmvX72vj75c0SqCIFcMmrd0sdemfG2FJPeX3tvWT3j7dCAVwXyye+nS5LfU2c6FZLfT/clv6dKlSGQ7x+MJd/dNuONGUx6hu6/ceWMt0MDXhWoSeIoi5/YXhEcdR0tMffKZdF+/cqYc9nScs/iMzXs0HdeiZf+6z9G14t7zlRFOYELQmDWRghaL1kcl/3i90XbdRef9kGlPX2PppOCP7Qxjj63qzxE82krKiQwiwV23XFJ9LU3z+I7qK6mdzy/uyICwDvffGkMJEOmSJUhsOCZnRURAN5x12UxmHyLUqoMgYVPbq+IAPD2uy+PYvILtlQZAou/uzWiAkak2X7PFVFK/qJWqgyBJcm313PJ9DMznba97cqZboLrjxCoiABwEujzXox4KDO8mUu+WFYJAeD0zw/vxQy/DCMun0++oFwJAeA00Oe9GPFgZnizNpnyriICwI213osZfhdGXr7uWG9lBICb6rwXIx/MDG83HO6umADwwKETcfCbm8pL2ku445Y1Mf/2S6I56SE8OnXcvDpu/tRHY9ffPh6bf/+BGOzqHV1FnsAFITDr/sYvHTN+9UfviFU/+qbymPGjn1KhbyAOPvxS7P/K89Gf/FCQCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZr9AIfkiy4GvbygvaUfBxW+7OuZdvTxzY+k8xMvff3MsvOvyePGXPxedD27K7JchcCEIzKoAcPPK+XH1J95b7uI/+uEUk+FLOr+xIfZ+6ZkYPN43erc8AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAlQgcT6b8TJc0dnTRu64vDxM98tYaFsyJ637vQ7HrM0/Ext/4UhQrYPq+ke2zTWAqBWZNAHjRvVfGFf/xB6K2peEUjyNPbY+df/2d6D94/JR9CggQIECAAAECBAgQIECAAAECBAgQIECAAAECBKpToHvbwdj8u/fHnCsuihU/dEs0LpmXudFl776h3Ev4mZ/+60jrSgQuBIFZMbnX2o/dGdf81vtOCf72H+lOxnD/arz8h18T/L0Q3lb3SIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4jUDXC7vjxf/4D7H7c09FabCYqdG6fnHc/JcfjY5b12TKZQhUq0BFB4BztTVx1W++J1b/2B2n+B/6zsvx4i/9fRx7Zucp+xQQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhcWAKlQjH2fv57seHXvxA9e45kbr52TmNc99//WVyU9AiWCFS7QMUGgPONdcnY7B+MJckE3iNTOtfv9r94NLZ+8qFIJ/uWCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAwJ9Ow4FBt/9Qtx8LEtQ0XldT7peHjFL31/XPzDt2XKZQhUm0BFzgGcb6iN1yXfwmi/cVXGe/BEX2xJhnw+seVAplyGAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwJBAsX8wtv3vb0bvrsPlXr+5XG5oV1zyb94aNfW18UrS2VAiUI0CFdcDOB32+Zr/+oFTgr/9B4/Hpt/4kuBvNb6F7okAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMAUC+778XGz7k4dPmRd47cfuihUfunUKruiUBGZeoOICwFf+6rtiwRvXZ2R6dh6Ojf/5i9G792imXIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAWAKHHt0Sm//gq1HoHchUu+Rn3xZL3p6dijRTQYbALBWoqADwmh9/yykftJ6ka/6mT9wXA0d7ZimxZhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECMykQNfzu2Pz794f6dDQQykdFvqKX/7BmHfdiqEiawJVIVAxAeCFd10ea/7lmzOo/YdOlD+MhZ7+TLkMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbMROLFlfzLv74NRKhaHD8sncwFfm0xNWr9wznCZDQKzXaAiAsBNy9vjyv/0gxnLwRN9SfD3KzFwpDtTLkOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgXASOPr0jdvzlY5lD6+e3xtWfeG/kaioibJZpmwyBcxGY8Tc5/TClH6raOY3D7S8OFmLL7z8QvXvM+TuMYoMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOC8BTof2hR7vvC9zHnar18Zqz96R6ZMhsBsFZjxAPCqH31TzL1yWcZv5998N9Ju+BIBAgQIECBAgAABAgQIECBAgAABAgQIECBAgACByRbY8w9PxbHndmVOu+ojb4o5ly/NlMkQmI0CMxoAblm78JRvUxx+fGt0fn3DbLTUZgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVki8Mr/figzFWm+tiau/JV3GQp6ljw/zTyzwIwGgC/9t++MfF3NcOsGjvXE9r94dDhvgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBUCBSO98W2P3skc+rW9YtjxQdvyZTJEJhtAjMWAF781qui46bVGa8dSfC3cKIvUyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCoE0mGgD35rc+bUa378LVHX0ZIpkyEwmwRmJACcq8nH2o/dmXE6+uzOOPLU9kyZDAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGpFNj1t9+NwREdFGtbGmL1j90+lZd0bgJTKjAjAeCL3nV9NF88f/jGSoPF2PlX3x7O2yBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwHQKDyVDQez73dOZSy997YzQunZcpkyEwWwSmPwCcz8WqH3ljxqfz4U3Rt78rUyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDoEOh/cGH0HTsaq8nW1sfLDb5iOS7sGgUkXmPYA8OJ7roym5e3DN1IcGIw9X/jecN4GAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgekUKBWKsefz2V7AF/3A66KurXk6m+FaBCZFYNoDwCs+dGum4Yce3RKDR3syZTIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEplPg0Hdejv5DJ4YvWdNUH8veff1w3gaB2SIwrQHglnWLou3aFcM2pVIp9n3l+eG8DQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIzIlAoxf6vZuNWF737hhlpiosSOB+BaQ0ALxv1Iel6cU/07Tt2Pu13LAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFJETj4yOZIpy8dSs0rOqL95tVDWWsCs0Jg2gLAudp8LP0n12ZQOr+5KZOXIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBTAoXu/jjyxLbM5Q0DneGQmQUC0xYATr8dUTe3aZhkoKs3jj61fThvgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBMC3Q+lO3AuOCOSyNXWzPTzXJ9AhMWmLYA8II3rM806sgTW6NUKGbKZAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjMpMDxl/ZF/+ETw02obW6IttetGM7bIFDpAtMWAG67YVXG4thzuzJ5GQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKVIDA6jtU+Ks5VCW3UBgJnEpiWAHCuriZa1y8abkOpVIr02xMSAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUoTGB3HmnvVskprovYQOKPAtASAW9cvjvyIsdH79ndFOom2RIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDSBE68fCDTpDmXLc3kZQhUssC0BIDnXLokY9Cz/WAmL0OAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgUgT69h+LYt/gcHMaFs6Juo6W4bwNApUsMC0B4JZVCzIGPbuPZPIyBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpGoBTRuzcbz2pZOb9imqchBMYSmJYAcNPFHZk2pN+akAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUqkDvvmw8q+liAeBKfVbalRWozWanJte8YlQA+EDX1FxonLPmG+uirq056uY1vbpOtmvqa2PwRF8MHOuJwaM95XV/5/EoFYrjnM1uAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBahXoP3A8c2vNozo8ZnbKEKgggWkJADcunZe55f5pDADXtTdH+02ro+Pm1dG8MjsUdaZRIzKF3oE49uzOOPL09jiarIs9AyP22pwNAmmwvzn5Jk7z6gWRDkHeeFFb5PK50zZ90yfui8Gu3tPuU0iAAAECBAgQIECAAAECBAgQIECAAAECBAhcmAJ9ndkOjY1LsvGuC1PFXc8GgSkPAOeb6qK2tXHYojhYiMHjfcP5qdqYe/XyWPL2q6Nl3aLI5U4f+DvTtWuS4GEaNE6X0mAxDj66OXZ/9klBwjOBzXB5rq4m0l7mzUmgt3nV/HLAt2HxvDMGfE9p7hkCw6fUU0CAAAECBAgQIECAAAECBAgQIECAAAECBAhcMAL9h09k7rVh4ZxMXoZApQpMeQB49IdhIBlmeSpTTVN9LP/AzTH/tnWTcplcbT4WvOmSaL9hVez+3FNx4OsbIorJzN/SjAsseee10XbDymhKe/fWTMt01jN+zxpAgAABAgQIECBAgAABAgQIECBAgAABAgQITI/A4JFsTKthkQDw9Mi7yvkKTH0AeEH2wzB4pPt823zG4+dcvjRW/sgbo7695Yx1znVHTXN9rPjALdF+46rY/Lv3R7Fv8FxP5bhJEph39bJyz99JOp3TECBAgAABAgQIECBAgAABAgQIECBAgAABAgSGBQaOZmNaDaNiXsMVbRCoMIEp7zZZN68pc8sDUzT8czrU89p/dfeUBH9H3kDrusWx7qfujXzDlMfOR17WNgECBAgQIECAAAECBAgQIECAAAECBAgQIECAwDQKDJ7oi1Lp5KiwNa0NEaaVnMYn4FLnKjDtAeBC8mGZ7FTf0RJrfuLOyNfWTPapT3u+1iTYvO6n7olc/fRc77SNUEiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDB1Aknst9DTP3z+XC4XdXOzHR+Hd9ogUEECU96NtXbUB2GyA8BpT9y1P3l31M1pnFbWtCfwkrddHXs+9/Q5XTeXBKvr5jZG6pP2kk7nLi5098XAsd5k6YnBZCkNFs/p3OdyUOrYuGRepENd5xvqym0YOHQiBs5iyO702Lq25vJSmzyPYv9gpOfoP3g8Bqeo5/e53KtjCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQITESic6I/a5qTn72spjemcTexk6DhrAtMpMPUB4LQ7/Ig0OOKbEiOKz3lz0V1XRNPy9gkfnwZVj72wK45v2R/p5N3FwUISgG2O+vkt0Xzx/Ghdv3jC51p871XR+dCmCX/QGy9qi7bXXZwsK6N55fxxr3Pilc448tS2ZNkefXuPjlt/9Y+/JfJ1Y/RKToYp2PKHX0u+rnJyuILmVfNj2XtuijmXLjnt+Z/8sT89bXm5MBeJ15Jov2lVtF2/csxvvaRzJqf3cuAbG+NEYi8RIECAAAECBAgQIECAAAECBAgQIECAAAECBCpdoNB9sgdw2taalmzcq9Lbr30XpsCUB4BrGusysmkgcNJSMs76gjsundDpSoVi7L3vmdh//wtJT9vsh3XkCdLA7KJ7r0yCmqsj7co/Vkp7zV70rutj2588PFa1SOcnXvHBW6N5RceY9UbvbFm9INJl2btviBNbO2PHXz4W3cn6TKlx6bxoWtp2pt3l8sZFc6N3z6vB5GXvuykW3X3FuPd5uhPOSwLZKz5wS6TDb08kpVYdt64tL907DpXvZTIDwWlgvzcJkvfsOhw9O5MlXSfLxYn7vGtXTKSJ6hAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEMgKj41qj416ZyjIEKkRg+gPAybDAk5XSnrQTCUAOdPXGlt/76pjB06E2dW87GFs/+VAc37QvVnzo1nGDox23rokdn3osRv8ASM+Xfgtk2T+9Iea/cf245xm6/pnWLasWxKX/9p1Jj+ONsfszT2bGnB86pidp+7gB4KQXchoAXvz2q2PxPVcOHTrhdTpk9YofuiXab1w14WNGV0wD4et/5q2x4y8ejYOPbB69e8L53cnw27VJD/M04Nu7Lwlqj+jZPHSSk32dh0qsCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQITE0inuxyZapqyHR9H7rNNoFIEpjwAnE/mth2Ziv2Fkdnz2l74lsvGPb5ULMbW//XghIK/I0/W+eDGyNXmy71cR5aP3s7l85HOB3zs+V2ZXWnw99Kff3s0jtMjN3PQOJlc0uN54ZsvK/co3vSJ+6LYM5A5onv7wXIP20zhqEw6DPWc3oFyz+VRu8bNpvP6XvoL74iGhXPGrTtehXwyB/LKD78x6hfMiT3/8NR41U+7v+uF3actV0iAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAwBAeDJUHSO6RbIT/UF83XZS5SSOXcnK6XDI4+X0jlnuzbsGa/aafcfeODF8rDCp905orD1kuy8wbn6mlj7k3dNavB3xOWieXlHrP1/7iwHqEeWd287NDJ72u20h/BF/+S6s+6RPHRPkxH8Hdmwpd93bcy5bOnIItsECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgYoQKI6Ka+WSDm4SgUoXyEZnp6C1aQ/ZkalUnJxBedPeqPn68Tswpz15zyd1PrRp3MObLs7O7bvyn98WrWsXjXvc+VSYc+nS8lDMI8/Rk8ytWyqN7ZvObdxyDm27+EOvT+YjXjjycpO2ffEP3xbpHMESAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCSBEbHtXI12bhXJbVVWwgMCUx51O2UD0KhOHTt81rXL2gd9/jevUejd/eRceuNVaHzm5ui78CxsapEOm/wUGpYPDfab14zlB1znX5rpGfH4eh+5UD0dXZFw6K5SZB1QTQt6zild+/pTjT/DetjzxefiYFDJ8q7Cz390d95fFKGaB55vdQ6net4vFQaLMahb2+Jzm++FH37j0U6ZHVT0lt50T1XxNwrl53x8IZkGOgl77ymPLfxGSvZQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYboFRHRtHd3yc7ua4HoGJCEx5ADiSIODINE4H1ZFVx9xumD9+ADgNhp5vKibz5R59eseET7P43ivLgc/xDjiRBH03/7evRuFE3ylVa+c2xfp/fW8SPG0/Zd/IgjS4vvieK2PnX39nuDgNRp/NMM39R7ojHeq6Z9fh6D/QFfnG2qhrb4n6ZBns6i2fd9HdVyT3NPY3WtLgc3o/J7bsH25LujFwdFd5fuTF77g6lr3rhsy+kZmOW9YKAI8EsU2AAAECBAgQIECAAAECBAgQIECAAAECBAjMuMCpPYCzca8Zb6AGEDiNwNQHgEd/M2KSPhc1rQ2nuZ1s0eBpgqvZGpOby9Xmo+P168Y9adfGPbHl9x+IYt/gaesOHuuJTb91X6z7qXvGHXZ5/hvXx86/SQLAr4383LPzcLTfuOq05x1d2PnQxtj56cej2DOQ3bX1ZI/mdEfa03i8tO1PHzkl+DvymH1fejZaVi2IttetHFk8vF3f0RItaxbGiZcPDJfZIECAAAECBAgQIECAAAECBAgQIECAAAECBAjMpEA62unIVCqMPRXnyLq2CcyUwJQHgEd/MyImaWz0od6pY8Gl8wRPZ6pPhjLO1409+Xfq8fIffv2Mwd+h9ha6++OV//GNuOo33ztUdNp1TWNducfu0DDQxYHTB5VHH3zs+V2x/c8fHV18Sr6urTnSa4yXlr33xlj2nhvHrDZez+Q0cC0APCahnQQIECBAgAABAgQIECBAgAABAgQIECBAgMB0CowOABcnZ6rT6bwF17rwBKY+AFwoZFRHf1Mis/MsMhMZ3nm8gONELleb9DRuu2HVmFXTuYaPb9wbDROYl7hn9+FIg7sTSf3J3L59B5M5fccZ7jqdQ3coADyR86ZzD+/4v9+eSNUJDyedtuF8U3PSQ1giQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFSKwOi4VqkgAFwpz0Y7ziww5QHg4kD2g5DOWzsZKQ2MjpfSAHAaVOze2jle1TPun/+mS2LZu888d2164LEXdsfmNACcXG+8dGJzdo7cidQfNwC8sDWObxrvTCf3H9+wN/r2HTtZMMZW/QSC2mMcfla7auc1nVV9lQkQIECAAAECBAgQIECAAAECBAgQIECAAAECUymQq82O/FpKOtlJBCpdYHKisWPcZbE3O79svn5yYs6F431R6Mue+3TNWPiWy05XPOGyBckcu+Ol45v3vVollx0H/rTHjZoT+bR1RhSWJjKUwESuO+KcffsnFvxNDzllCO8R55nszToB4MkmdT4CBAgQIECAAAECBAgQIECAAAECBAgQIEDgPATy9dkAcKF3YlNxnsclHUrgvAWmPABcGB0AbpicAHB658c3vRZ4HYNh/m3rkiGcV45R48y7Ft1zZTQsmnvmCq/tGWpHf2fXuHVb1i0at87ICi1rx68/keGwR56z98D47Ryq338WdYeOOdd1TUNd5Cfx/TjXdjiOAAECBAgQIECAAAECBAgQIECAAAECBAgQIJAKjO7YWOiZ2DSf9AjMpMDkRWPPcBejPwijPyhnOGxCxQe+9mLMu3r5uHVXfviNURwoxLFndo5bd6hC2nN4+ftuGsqecZ3Op3vi5QPl/X0TCJY2Le+IfGNdjO4ZfboLpEMiN04gAD2R6448/8Dh7pHZMbfP5tyHvv3ymOcab2exf7D8nMarZz8BAgQIECBAgAABAgQIECBAgAABAgQIECBAYDoEakZ1XJtIfGc62uUaBMYSmPoA8InsNyFqmuvHas9Z7Tv23K7oTYYzHi9IWpMEXNf95N3R+c1Nse8fnxtz/tvWy5bEoruvjLZrV0yoLZ0PbYpSElxOU1/n8SgNFiNXe+aO1elk4as/eke8/EdfHz7udBdKe8Ku/sjtp9uVKUuDpv2HTmTKxs1MZFjp104y2NUbg8d7o7a1cczTpj299973TPTuOjJmvdPtbFg8Nxbcfmly7OGIsxwi+3TnU0aAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAyBmqZsXGswmaJUIlDpAlMeAB441pMxqJ3EAHB64gNf3xAr3n9z5hpnyix40yWRLt3bDsaJLfuj/2h3NMxvjULPQNR1tETT8vZoWtp2psNPKR/s7os9n3t6uDwNBB/6zsuRDjs9Vkp7La//qXtj8+9/9bQ9gdMg+bqfuidaVi8c6zTlfQe/tTmZqLc0br3zqdD54KZY8s5rxjxFGmS/7Be/L3Z95snoTJ5JqVAcs34kgfB5SZB94ZsvizmXL41cMo/x3i89M/Yx9hIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEplGgpqUhc7WBpOOcRKDSBaY+AJwEWUem0R+UkfvOZTsNNrZfvzJa1y+e8OHNK+dHupxv2vuF70XhRPabHmkP447Xry0HNMc6f+sli+Pq33pfORjd/cqBKPQNRk1TXbSsWhhNKzsinQ93vFRKevLu+8rz41U77/37H3ghFt1zxSnj3I8+cb6uthyMv+j7r4ujyXDbx1/aF+kXANJhwOuSHsT1C+dEw4LW8rppWXvUzW0afQp5AgQIECBAgAABAgQIECBAgAABAgQIECBAgEDFCJzSA/hotuNjxTRUQwiMEJiGAHD2gzDeUMIj2jahzbSn6ct/+LW4NOl92rBgzoSOmYxKR763I/YncxCPTr27j8SRJ7dF+w2rRu86JZ/2mp1z6ZLycsrOCRSkc+72T2De4Qmcaswq6TDQaU/rxW+9asx6QzvTH4Ydt6wpL0Nl1gQIECBAgAABAgQIECBAgAABAgQIECBAgACB2SSQdmpMp/YcSoNJp8BxR0AdqmxNYAYFzjxZ7SQ1qj+ZF3dkqps3+b0+0/HWt/zBA5HOQzsdKQ3+vpLM4RuF0w+9vO1PHo7u7QentCnpENbb/+LRKb3GyJPv+swTcTS5b4kAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcCEIjI5pjY55XQgG7nF2Ckx5ALhvVA/VurbJDwCn9L27jsSm37ovenYdntInceSpbeXg71jf8Cgmwzlv/t37o2//sSlpS++eI8n8wQ9Eqb8wJec/7UmLpXj5f34jjieBZ4kAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUO0CowPAo2Ne1X7/7m/2Ckx5ALjQ3R+D3SfnyU3nia1prp8SsZ7th2LDr3w+9n7pmUjnx53M1H/oRLz8P76RDDf99Ql170+HTd74m/fFoe+8PJnNiIPf2hwbP3HfKXMPT+pFznCy0kAhNv/OV2L//c9Pqm/6juz98rOnHVL7DE1RTIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYUoG69pbM+fsOTE3Hv8xFZAhMgsCUzwGctrFv77GoXbNwuLkNC+dE97apGSI57Zm7+7NPRtpTd/Fbr4551yyPfP253+bg8WT+229siL33PXvWPW4Hj/XE1k8+FAcffilWfPDWaFwyb9jgbDd6krmFd/zlo3F8076zPXRS66e9m3f+zXcjnX94xYdeHy2rF5zz+dOg+v4HXojOhzZFcZqG7z7nxjqQAAECBAgQIECAAAECBAgQIECAAAECBAgQuKAEGha2Zu63d8/RTF6GQKUKnHtk9CzuqDvpmdsyTQHgoWZ1bz0YryRDFucbamPetSui/eY1MeeyJVHTUDdU5YzrtAv/0ae3x5Gnd8Txl5KAa+n0c/2e8QSjdnS9uCde+A+fjeZV86PtdSuT5eJoXNqWqZUGrnM12Q7Z6XDWR55K2pEEs9PezRNJ6X13bdwzZtV0zuTzTWkAf+OvfyEaL2qL9htWRdsNK6NpWfu4p+0/eDxObO0szydc7h19hnmUxz3RBCt0vbg7ahrP/JoXk2G0C5PgMcHmqEaAAAECBAgQIECAAAECBAgQIECAAAECBAjMEoGGBXMyLU3jXRKB2SBw5sjYJLa+e0e2t2/DormTePaxT5X2WD38nVfKS1oz31gXdW3NkY7bnq5rkgDx4Im+GDjaE2mP3XSdHjMVKQ3OpkvaQzkdBrtublPUpu1I1qVkjt1cPle+/kDSjsGkHYWe/rNuxvFNe+Ol39571sed6wG9Sc/kPbufjj2ffzpqmpJ7Su6nNpnnuW7eq7aFpGdvOsRzuqSB9XRo7OlMBx54MdJFIkCAAAECBAgQIECAAAECBAgQIECAAAECBAicjcDoeFbPDgHgs/FTd+YEpicAPGq457TX6EyldKjhvr1Hy8tMtSG97lBQNJK2VEtKA9bloHUV3VO1PBv3QYAAAQIECBAgQIAAAQIECBAgQIAAAQIECJydwOh41olR8a6zO5vaBKZPIDvm8BRdt2tDtkdq04qOKbqS0xIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4P4H6hXOSKSZPTivaf+hE9CcjnUoEZoPAtASA03l0S8XisEfjknnloZiHC2wQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqBCBltULMi3p2rAnk5chUMkC0xIAToddPrHlwLBDOtdt67pFw3kbBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpFoHX94kxTjr2wO5OXIVDJAtMSAE4BDj+5LeMw96plmbwMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUoQmHtlNo51+ImtldAsbSAwIYFpCwAffGRzpkFt16+MyOUyZTIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZlKgedX8aEjmAB5Khb6BOPJEtqPj0D5rApUoMG0B4EOPbonB7r5hg/r2lph3dfbbE8M7bRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYAYEFt1+auerBhzdHsW8wUyZDoJIFpi0AXOwfjH33PZuxmD/qA5TZKUOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgGgXyDbXRftPqzBV3//2TmbwMgUoXmLYAcAqx89NPZDzSHsB1HS2ZMhkCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECMyHQcevaqGmsG750776j0fnwS8N5GwRmg8C0BoC7XtgdXRv2DLvk8vlYfPcVw3kbBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGZEIBex6J4rM5fe/dmnIoqlTJkMgUoXmNYAcIqx4/9+O2My/02XRE1zfaZMhgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMB0CrRdvzIaF88dvmRxYDAZ3fbx4bwNArNFYNoDwHu+8Ez07T827JN2o1/y9quH8zYIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITKtA0vt36fe/LnPJvV98JvoPdGXKZAjMBoFpDwCXBgux7f98K2Oz8M7Lo669OVMmQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGA6BDpevy6aLmobvlSpUIytf/LIcN4GgdkkMO0B4BRn519/N9JJs4dSvr42lr/3pqGsNQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFpEcgno9Uue/f1mWvt+fzT0b21M1MmQ2C2CMxIALjYPxgv/9E3MkbtN62OOZcvzZTJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJhKgYt+8HVRN+/kSLWFvoFT4lhTeX3nJjDZAjMSAE5vYvffPxXHnt+VuZ+L/8VtkW+ozZTJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJgKgZZ1i2LhWy7PnHrb//dw9O49OZJtZqcMgVkgMGMB4CiVYsOvfSFKxeIwU8OCObH8/TcP520QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAqBtFPiqh95Y+TyueHTd+88FFuTALBEYDYLzFwAOFE79vzu2P7nj2b8Frzpkmi/eXWmTIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAZAqkI9M2LJo7fMpS0nnxxV/6h0inMpUIzGaBGQ0Ap3Bb/uBrceLlAxnD9APXtKw9UyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDIEFt51eXTcvCZzqh2f+nYcfnxrpkyGwGwUmPEAcPotimd/7m+j0Dsw7FfTUBdrf+qeqOtoGS6zQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOB8BdquXxnL35edkrRr497Y/Lv3n++pHU+gIgRmPACcKhx/aV9s/I0vZUDq25pjfRIErmmuz5TLECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEDgXgdb1i2PVR27PzPs7eLw3nvnpvzb087mAOqYiBSoiAJzK7P7sk7Hjr76dQWpc2hZrf/LuyNXVZMplCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJyNQONFbbHmY3dGfkTcqVQoxrM//+no2XHobE6lLoGKFqiYAHCqtPE374vOh1/KgLWuWxTr//W9egJnVGQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQmKtC8akFc8jNvi9rmhswhm377y3FwVGwqU0GGwCwUqKgAcBRL8ezP/E0cfWZHhjLtjn/Jz7096tqbM+UyBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMYSmHvVslj/M2+N2jmNmWqv/PFDseNT2dFpMxVkCMxSgcoKACeIhZ7+eOon/iK6NuzJkDYta49Lf+GdkXbPlwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMJ9Bx27pY+7G7oqahLlN1+6ceiy2//0CmTIZAtQhUXAA4hR3s6o0nPvKnSU/gnRnn+o6WuPTn3xFtr7s4Uy5DgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYFggn4tl770xVv3IGyNXkw2HbfuzR2JTMi2pRKBaBbJvfAXdZRoEfvKjfxYHH9uSaVVNc32s+Yk7Y/kHbo7ciEm6M5VkCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIELkiB+gWtccnPvj0W33vVKfe/5Q8eiJf+61dOKVdAoJoEKjYAnCKnw0E/nQwHvevvHj/FfNFdV8TlH//+aF6z8JR9CggQIECAAAECBAgQIECAAAECBAgQIECAAAECBC48gQW3XxKX/9IPROu6RZmbL/YPxnO/8Ol45ZMPZcplCFSjQG2l31SpUIwXf/nz0bVpX1ySTNCdrzvZ5MYl85J5gd8RB7+5KXZ95skonOir9NvRPgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUkWaFrRESs+dGu0rs0GftPL9O45Es/87N/EsWd3TfJVnY5AZQqcjKZWZvuGW7Xzr76TfDB3xtWfeF80LW8fLs/lcrHg9kuj7cZVse/Lz8X+B16IUn9heL8NAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB6hSon98aS7//uui4dW3kknl/R6fOhzbF8//+MzFwtGf0LnkCVSswawLA6RM49vzueOw9fxjrf/reWP7emzIPpba5IZa9+4ZYdPcV5SBw5zc2RqG7P1NHhgABAgQIECBAgAABAgQIECBAgAABAgQIECBAYPYLpKPELnrrVUngd03ka2tOuaHBZNTYTb/15dj92SdP2aeAQLULzKoAcPow0nmBN/zqF2LfV56Py/7dO6NldXYO4Lq5TbHsXTfEkndcE4e/80qk3+zo3tpZ7c/R/REgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEqlogV5OPedetKI8MO+fypZGOEnu6tP+BF2PTJ+6L3r1HT7dbGYGqF5h1AeChJ5IGd9PewOl47qs/cnukgd+RqaahLha86ZLy0rv/WBx5YlsceWpbEgw+GFEqjaxqm8CsFVj0+LYYbKqbte2vtobX9g5WxC0tSX4+DjZ6LyriYSSNyFfItARLHnslCvWnfhOyUpwutHbkB4sVcctLH305irX5imiLRkTkCpXx/6hLv7UlSqcZMsszmhmBXLFC3ouHN88MgKtWrED6bi71XlTM86mUnxXpn2Xei4p5LaJS/p8zbYf3onLei5oK+R01/V3Ze1E570Vt70BFNCb9uzXvRUU8inIjansq471IG5NvqI05ly2NtutXloO/6YiwZ0rHX9oXL/3OV+LgI36HOZOR8gtDIHf/NR+vjL9ROA/v2jmNsfLDb4gVH7g5alsbxzxTOiz0iZcPxIltndG760j07jsafQe6olhBP8zGvAE7CRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJVKFA7rykaFs6JxqVt0bS8PRkFdkE0r5gfuXG+wN697WC8/L8ejL1ffEYnwCp8L9zS2QtURQB46LZrW5N5gN9zY6z44C3RuHjeUPGE1oXkW04DR7pjsKs3Bo8nSxIoLiZLoW8gin2Dry4DhSgmS2kwXYpRKiRLuk6++VwqvrqO9Bv6SQ/jtKzc07i8GhFjH+p9PKJoQg1UiQABAgQIECBAgAABAuMI+DVjHCC7CRAgQIAAAQIECBAYV+CUQZXTgqGhlpPtXPJPpCNHpf+m5cmSS/M1yTqXj1y6ToZqToO2uZqayNfVRC5Z0nW+sTZq6usin4xsWdNcH7XpknTyq01Gea1Lgr+nm8t3rAYf+d6O2P5/Hon9D2wQ+B0Lyr4LTqCqAsDDTy/5QbPgDevionffEAveuD7y9bN2pOvhW7JBgAABAgQIECBAgAABAgQIECBAgAABAgQIELjQBfoPHo+9//hc7P67J+L45v0XOof7J3BageqMjCa9bzu/+VJ5Sb9BsvCOS2PhnZdH+82ro76t+bQQCgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpPIB3i+eC3Nsf+r74Qh5/cFuXRWCuvmVpEoGIEqrMH8Bi8zcl48fOuWh6tlyyOljULk7HjO5Kx5OfpJTyGmV0ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgakWSKfp7Nl1OLp3HIoTSe/ero174+izO6O/8/hUX9r5CVSVQHX2AB7jEXW/0hnpMjrVtTdH/fzWqO9oibpkrPnymPPJuPPlMeib6svj0adDSdc01CZj1de+OmZ9Mn59eez6dCz78pKMcZ9Ptstj37825n15+Pvyf1695FB+dAPkCRAgQIAAAQIECBAgcD4Cye8aEgECBAgQIECAAAECBCZFoHTyLKXSa5l0lWyX88l2KRmNtZwvFF/dTtbFdDtdBpPtgUKyLkSxbzCK/YNR6B2IYrIUuvtj8ESyHO+NwWM90X+kOwYOd0ffga7yvpNXtkWAwLkKXHAB4DNBpT9c0uXEmSooJ0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQIUL5Cu8fZpHgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAhMUEACeIJRqBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqHQBAeBKf0LaR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQkKCABPEEo1AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVLqAAHClPyHtI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwAQFBIAnCKUaAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKl1AALjSn5D2ESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYIICAsAThFKNAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEClS4gAFzpT0j7CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMEEBAeAJQqlGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBShcQAK70J6R9BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmKCAAPAEoVQjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBApQsIAFf6E9I+AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITFCgdoL1LuxquVzkG2ujpr428g11ka+riVyylNe1+cjVjFjyuYhkySXHlNdpPk1JPi0qp+GNtPy1MisCBAgQIECAAAECBAicj0DpfA52LAECBAgQIECAAAECBE4jUHr1F43yang7KSuWopQskZSV18l2cbCYlBejVChGcaAQpSSfrov9g1Hse21JtiUCBKZemXlEGgAAQABJREFU4IINAKcB3OaV86N5RUc0Lm2LxsVzo35+S9R3tEbtvKaom9MYtclS01SXLPVT/yRcgQABAgQIECBAgAABAgQIECBAgAABAgQIECBQxQKlJEBc6BmIwom+GOjqjcFkGTjSHf2HTkTfga7o23csenYdju7th6J395EqlnBrBKZW4IIJADde1BYdt6yJttddHHOvWhYtqxaUe+5OLa+zEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIpAK5fD5qWxrKS8OiuWOiFLr7o+ulfXH0mR1x5Iltcfi7r8Tg8b4xj7GTAIFXBXL3X/Pxqh0oLO3hu/jeK2PRPVfGnEuXeOYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKzUCAdTvrQt1+O/fc/H/sfeLHce3gW3oYmE5gWgaoLAOdqa2Lx266KZe++PtpvWDUpiKV0DPv+ZJz6wWRJx61Pl2QM+3T8+vI6HdM+Heu+kNQrpWPcp8Pevzb2fXn9WjPS7TSNCLmP2Hx1n/8SIECAAAECBAgQIEDgHARy53CMQwgQIECAAAECBAgQIDCmwNAvGrnXNpJVLvkn8uWNyKXlyZKrSZZ0uyaf9PJN88k6idfkavORT6bkzKfb9a+ux7zeBHcW+gZi/1eej52ffjyOPr1jgkepRuDCEaiaAHBNMmTA8vfdFBd/6NZoWDhnQk8wHVO+d+/R6O/sSsaX707GmT/x6njzyRAC6dAChZ7+KPYOlCcnn9AJVSJAgAABAgQIECBAgAABAgQIECBAgAABAgQIEDi9QBIczjfURk1TfbLUvTocdGtj1M5tjPq2lqib31KO8TQunRe1zQ2nP8eo0qPP7Iytf/pwHEh6BUsECLwqMOsDwPn62lj+QzfH6h99U9TNaz7jc00nFj/+0v7oenFPHN+yL7q3HYxiMtG4RGC2C+hFXjlPMPl+W8Uk70XFPIr0+5AVk7wXFfMovBeV8ygqqiV+XlTU46iYxlTKe+HPkIp5JcoN8V5U1vOohNZUyjuRWvh5UQlvxKtt8F5UzrOopJZ4LyrpaVROW7wXlfMsKqkllfBe1LU3R8vqhdF6yeKYe+WyaFwyb0yiro17Y/PvfTUOPvzSmPXsJHAhCMzqAPCiuy+PS3727WN+6NMPfDom/NGntpkc/EJ4oy+we3zw3+Wjp6MS/ii+wODPcLu3/1ohmg+fYec0Fn/9P+Sjb573YhrJx7zUm3+5EI3HxqwyLTsf+E/5GGjxXkwL9gQucufHC1HfPYGKU1zl/l/NR6HRezHFzBM+/d2/WIjavglXn7KK//gb+SjVei+mDPgsT3zvzxciXzjLg6ag+pd/u2YKzuqU5yrwtp+Z+ZeimLwSX/lN78W5PsPJPi43WIq3/kIyH9UMp8Gkk85Xf817McOPYfjyNb2luOffz/x70Z/01/jaL3svhh/MDG/UnSjFXb808+9F79yIb3zcezHDr8Pw5RuOluItvzLz70V3e8RDv+i9GH4wM7zRdKgUd/z6zL8XIxkaL2qLthtWxvzXrxtzJNg0JrThP38xul/pHHm4bQIXlEDtbLzb9Fsel3/8+2P+G9adtvmFZNjmg9/cFAce3Bh9+yrgb91P20qFBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECExHo3X0k9qbL578Xcy5fGgvvuiLmXbP81bmHR5yg45Y1cevf/kRs+7NH4uU/+kaUBmf+C5QjmmeTwLQIzLoA8NIfeF1c+nNvi9pkTPjRKZ23d99XnosDX9tQnr939H55AgQIECBAgAABAgQIECBAgAABAgQIECBAgACB2S2QTveZLulcwUveeW2037Q6csn8wkMpX1cTqz9yeyy849J4/t9/Jro27B3aZU3gghCYNQHgfDIZ+BVJr98l77jmlAdTGizG/q+9EHu/+EykQWCJAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgugV69xyNrX/8UOy779lY9t4by3MFj7zj1vWL46Y//7HY9Ftfjp1/892Ru2wTqGqBWREAblrREdf93gejZc3CUx5G14Y9seMvH4vevUdP2aeAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgugV6dh2Ozb97f7RdvzKWv//mqO9oGb7hfH1tXPaL3xfzrlsRL/7Hz0Wxf3B4nw0C1SpQ8QHg9MN6ze98IOrbmjPPoNA3ELs+/Xh0fmNjplyGAAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgwhM48uS2OPbi7liRBIHnv2F9BmBpMlR00/KO+N7/+6kYONyd2SdDoNoE8pV8Qwvfcllc/z//xSnB3+6dh2LDr3xe8LeSH562ESBAgAABAgQIECBAgAABAgQIECBAgAABAgSmWaDYMxDb/vSRePl/fCMKPdlpQ9uuXRE3/Z+PlOcOnuZmuRyBaRWo2ADwkrdfHVf/9vsi7Zo/Mh16bEts/PUvRt++YyOLbRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoCxx5Ymts+NXPR++eIxmR5ovnx41/+qPRdHFHplyGQDUJVGQAeNHdV8SVv/buyNfWZKz3fvnZ2Pq/vxmlgUKmXIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDASIG+/V2x8Te+FMe37B9ZHI1L5sUNf/xhPYEzKjLVJFBxAeCO29bGVb/xnsjVnGxaqVSKHX/17dj9d09Uk717IUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQmEKBQnd/vPRf/jGOfG9H5iqNi+fF9Z/8cNR3tGTKZQhUg8DJKGsF3E3rukVxzW+/P/J1J3v+lorF2PrJh+LAAy9WQAs1gQABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDYJpCPLvvzfvxYHH3kp0+zmFR1x7X/7YOQbstORZirJEJiFAhUTAK5rb47r/uBDUdvSkGHc/hePxeHvvpIpkyFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwYYFktNltf/atOPLU9swh865ZHlf88g9mymQIzHaByggA53Jx1X9+TzLWelvGc/fnnoqD39yUKZMhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcNYCSRD4lU8+GMc378scuuRtV8eKD96aKZMhMJsFKiIAvPqjt8f816/NOHY+tDH2fv57mTIZAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAucqkA4HveX3H4iePUcyp1j/b+6NuVdelCmTITBbBWY8ADzn8qWx+qN3ZPy6Nu6JdOhniQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBkChS6+2PL7301Brv7hk+br6uJK3/9n5oPeFjExmwWmNEAcK42+TD92rsjn6yH0sCxnnjlfz0UkXTDlwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMtkB/5/HY9icPZ07bsmpBrP3JuzJlMgRmo8CMBoBX/vBt0bp2UcYt/bANJkFgiQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBUCRx9ekcceHBj5vQXJ3MBt166JFMmQ2C2CcxYALhx6bxY/WO3Z7w6v7kpjj23K1MmQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGAqBHb97Xej70DX8KlzNfm47N+9czhvg8BsFJixAPDaj90VNU31w2YDXb2x69OPD+dtECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJhKgWLfYOz41GOZS7Rdd3EsuufKTJkMgdkkMCMB4NZ1i2LJO67OOO3+u8cjnXRbIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBdAunotEee2p653NqP3RmRz2XKZAjMFoEZCQCv/pdviVz+5KW7dx6Kg9/aPFvMtJMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCKBHZ9+rtRKhSH76hl1YJY+s5rhvM2CMwmgZNR2GlqddPFHbHorssyV9v92ScjSpkiGQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLTItC3vysOPvJS5lorf/gNmbwMgdkiMO0B4JX/7PXZ3r/bD8axZ3bOFi/tJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqEKBvV96NkrFk72AW9cvjvlvWFeFd+qWql1gWgPA+aa6WPJ912ZM9335uUxehgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMB0C/QfPB6Hv7s1c9ll770pk5chMBsEpjUAvORtV0dtS8OwS/+R7jj8+NbhvA0CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECMyWw/4EXMpde8Kb1Ub+gNVMmQ6DSBaY1ALzsn96Q8Tj4cDKWesnkvxkUGQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRkR6H6lM7p3Hhq+dr62Ji76weuH8zYIzAaBaQsANy1vj3lXLx82KRVLUQ4AD5fYIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDCzAgcf2pRpwJJ3XJ3JyxCodIFpCwAvuOPSjMXxjXsjHUtdIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFApAoe+/XKUBovDzWlduyialrUP520QqHSBaQsAd9y8JmNx5OntmbwMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZkWKHT3R9dLezPNaL95dSYvQ6CSBaYtADzvuhUZh64NezJ5GQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKVIND1YjaO1fa6iyuhWdpAYEIC0xIAblwyL+rbmocbNNjdF727jwznbRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoFIETW/ZnmjLnsqWZvAyBShaYlgBw66VLMgY92w9l8jIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKkWge9vBKJVKw81pWbMwcrU1w3kbBCpZYHoCwOsXZwx6dh3O5GUIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVIpAsW8w+g8eH25Ovq4mWlbNH87bIFDJAtMSAG6+uCNj0LvnaCYvQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCSBHr3ZuNZTaPiXZXUVm0hMFJgegLAK7IB4L7OrpFtmPLtXH1N5Otrp/w6LlCZAvnGusjVTMurXpkAWkWAAAECBAgQIECAAAECBAgQIECAAAECBAictUD//mw8q3mFHsBnjeiAGRGYlqho0/L2zM2N/sBkdp5Hpq69OdpvXB1pj+O6ec1R19aULM1R01RfPmuhbyAGj/XGwNGeZOmO4y/ti6NP78h04T+Pyzt0JgVyEc0r58fcq5ZH67pFUTsvefZzGqO2tXE4+Fvo6Y/BruT5J0v31s449tyu6Nq0N0r9hZlsuWsTIECAAAECBAgQIECAAAECBAgQIECAAAECFSgwukPj6HhXBTZZkwiUBaY+AJzPRf381mHudMLs/kMnhvPnu1Hb2hBtN62OjptXR8vaRZHLJZHAM6SahrqoWVgXDQvnlGu037AqVnzglujecSiOPLUtDjzwYhS6+89wtOJKFEiD/kveeW20Xb+yHPAdq43pFwHSpWHR3GhN3pVFd10RxYFCHHlyW+z++yejv/PkWP5jncc+AgQIECBAgAABAgQIECBAgAABAgQIECBAoPoF+g9m41lpfEEiMBsEpjwAXN/RMtwDMwUpnOiLUqE4KTbzb1sXy99/c9Q0v9rD91xP2pwMUZ0ui+68PHZ/9sno/OamiNK5ns1x0yGQBnIXv/3qWHT35ZGvO/fXOJ20veOWNZF+GeDAgxvKzz+d2F0iQIAAAQIECBAgQIAAAQIECBAgQIAAAQIELmyBgSPdGYCGRa92MMwUyhCoQIFzj5xN8GaGetsOVR840jO0ec7rumR434v/xW0x75oV53yO0x2YDhd88T+/LRbccWls/eOHondPdnLv0x2jbPoFGhbPjfX/5q2RfrlgslKuNl/uEdy8ckFs/m/3R7F3YLJO7TwECBAgQIAAAQIECBAgQIAAAQIECBAgQIDALBRIpxQdmUbHvEbus02gkgTyU92Y0UG6gWPZD8vZXj8dX/3y//SDkx78HdmO5ovnx/qfeVs0XtQ2sth2BQg0JT21L/m5t09q8HfkbaXzB6fB5XzDlH83YuRlbRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVJjA6AFzX1lxhLdQcAqcXmPIAcN3cpsyV0yGgzzXVzmmMNR+7K2pbGs71FBM+Lm33+p9+azQunTfhY1ScWoF0vt/1P/PWGP1OTfZVW1YviMVvvWqyT+t8BAgQIECAAAECBAgQIECAAAECBAgQIECAwCwSKA0Woth/ctrIdFrJdIpKiUClC0x5ALh2VAB48BwDwOkQvWt+4s5omN86baZpoHGd3qDT5j3ehZa958aobT774H+pePYTOi+658pIv3AgESBAgAABAgQIECBAgAABAgQIECBAgAABAheuwGB3f+bm02lKJQKVLjDl49zWzc0G0QqjPigTBbro3TdEOjzv2aRSsRgDx3pjMB2jPZ8rDxt8tr2H65Pu/Evefk3s/vsnz+bSUb9wTrRdtyLpQdwW6Q+DNBCeBpTTQPZgV9KmpF3pcNj9h07Esed2xfGX9kWUxg9U1jTXRzpE9VgpPX/PrsOZKrnkWynp3MZp79bGJfOivr0l0h9aA8n1jz67M/bf/3ym/imZXCT+i2PuNcujPgnC189rjtq25L6Sb7oMHE/u5eCJ5F6OR+/eo3Ho268k93d+Q32Pvn7L2kXRcfOa0cWnzadt2PePz8WJVw5Ef9KudD7f1K1h0dxYcPsl0XHr2ki/pTNWqmmsi/Zb1sSBr74wVjX7CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSoWKI9sO2Lo53LnsSQOIRGoZIEpDwCP7gpfSIJxZ5vyTXXlwN1EjzuxZX90PvxSHHlyW4wOOKdzu869clksvvfKSIOKE0mL7r0iDjy0sRwsHat+2s5Fd10RbTesjOblHWesWh7CeNnJ3UvefnU5KHzkmR3R+fUN0b3t4Mmdo7YaFs8tD009qjiTTQOfG3/9i8NlaSBzWRJAHz0fc/pDqjE5Xzp8wZkCwHUdLWWr9htWxZnGtk/P05QEuofSsnffGIef2hYHHngx0mcxGWnR3VdM6DQ7P/147P9KEsweFUxP34PurZ2xPVk6H9wY63/2bVHTUDfmOZsM/z2mj50ECBAgQIAAAQIECBAgQIAAAQIECBAgQKDaBdJOZiNT2uFMIlDpAlMeAE6DoiPTyLHSR5aPtT3/DevHDdalxxcHBmPX3z1RDjye6XzFvsFyYDgNDs+5bGms/vE3jzuscL6uNpa+85rY/uePnum00X7z6lj+/pvPeX7aNIi6ILnP+a9fFwe+saHc47jYk/2hkl68d9eRSIc0ziU9ms+U0l7HQ2n+G9fHyh9+w1B24uvk9AvffFmkPa/T3rBnk9Jezh03rS4ve77wdOz5h6fP5vDT1m1Zs/C05SML9ye9dfcnPX/HS2mAffdnnowVP3TLmFUbl5x0HLOinQQIECBAgAABAgQIECBAgAABAgQIECBAgEBVChRGzAGc3uDZxkyqEsVNVbzAlM8BPPqDkAZgzzYtfMtl4x5SSnp8vvI/Hxwz+Dv6JF0b9sTm37k/Cj3Z8dtH10vzc5Jew6dL6dDKa//V3bH6x+445+DvyPP+/+zdB5xcZ3no/2f69t6kreqSLcmSJVtyEy6AMaaEDgZCCSQ3CVzSLqRyk3/uJ+0GbnIhlAAJkHAJEBwDtnHvVbYsWc1qK2mbtvfd2Z3+f9+RZzRntszMamfmzOzv/XA45z3nPee853tmFuxn3ufVgd26W7fIlf/fu6RIpWuOLzqAPtu/eGoBba5H7pZesVpaPnJd/CUS1vUo6Q1/8BZpvmvvZf8hW/W2HbL2N28Rq3PpvzXQKbTjRy/HP0RQTcSeSppud8dQ/CXm1K0FS+/znIuxAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJOIOgNGPpsTXHQnOFkKghkSCDtAWAdTIwtQZ/xixJ7bL7totZqKVBztyYqes7X8Ve7EjWbczycFniRkb2RE1xq3lsdVDUUi0XW/MbNUr6tybB7OSo63fJ6FVjWKZ/jy8wiKaIjbQubKqXlw3vFYkvxFasAtA7Ylm5siFzqstcVV7dKy8eXMAr59TsXqGfRAf7FlqlT/ZLKjwsKF0nRHXlg7/BUZJM1AggggAACCCCAAAIIIIAAAggggAACCCCAAAIIrECBUNwI4Pi41wok4ZFzQMAYnU1Dh+cEIAPBlO7irClN2F6P/tQB4KWW0VfOS9NE4vTNpRvqZeTFs9HbtHz0Oqm4qjlaX+4Ne0mBrP/dN8vJv75P/OMz0cu7O0ekau+6aH2+jdXv2CGuJALn8efqEcN6juTlLjol9NhL52TsYGfKl548dkEO/vr3Uj5vwRNU4L7qusX99Lmz/RMLXoIDCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkP8CelrO2GJNdeBd7MlsI5AhgYwHgPUozlSKs6YkYfPxQ10SmPIkbLdgg0BI+u47LBW7WhdsIqrbsQHB4nV1UnPTxoXbL9MRPfJYB3Nj5x92dw4nvHpR69z00YlO0imnk30m75hbJo/1hOcjDqmgfokaMVy4evE5c5tVcHnyZJ8E3IlTbifq65KPqxHOLb96vZSo95eojDzfnqgJxxFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCPBXQMJLZY7ClmXo09mW0EMiSQ+QCwCramUnQANFFxJ5ESOdE1Bh97TfSSbKl/y9akmnpHpqX35wdl+tyQzPaOiQ4k28sKpVgFW6tv2CAVO1sSXqfquvVqftuD4p+cDbedUSOAUy068O4ZnJTZnjF1nRmxl+p5dYvEUVksEb/62xM/k/5D1/3jl2ToyZMS/0evcnebtH7ixgXn+3Wo5666fr0MPnI81e4vS3u7mkt4zaf3SemmVQmvN364S2YvqPdFQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgRUrMGdgo5UA8Ir9MOTQg6c9AKwDnoZiMdQSVubMuzvPGb5x9zx707fL1VAu5UmkftYjhk9/+UHxqSBwbPFPzITnK9ZBxpaPXp9w1K3VYZO6265QQeBXwpcJzHjDwVxXbeL02PqEme5R6fj+s+JWQeiFih5pXbGzdaHD0f3nvv2UjL18PlqP3RhV+wOzPln/uTfF7jZs6yBxNgLA1Srw3Pj+a8Re7DL0Z76KT41u7vz+c/MdYh8CCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACphZIewA4FIwbGq9S8KZS4keZzneuJcVrzneNVPaVrK8Ti5pHdrGig4in/vb+6Kjdeduq4LgONOoAb6I5fUvU/MOxxTfqlmQCwOOvdkn71x8TSTDyunhtrSTj6CgtkNpbNsd2Zc52yB+UhVIg6Ps4KotE9z8TpbCpUpo+tEdKVYrqZErQ45f2rz0mvpg5l5M5jzYIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQfwLxsZNk4lb5p8AT5ZpA+gPA8bnREwRO4wG9w1Pxu+bUdRrjTBZXXeKRtxPHLywe/I3p8PAL7QkDwM4k7hlzyfBm0OuXrv/3QsLgr26cTDBZt2u+a69eLbnowHnZ1iYZfvrUkq+RzIm2EpesfudOqdm3UQW2k0vHoNN1t3/1UZnpSj3FdjJ9og0CCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjklsCcGENc3Cu3noberhSBjAeAxZZcMC7yArxDiQPAenRnn7waOWVJax3YrL5h/aLndv3H/nDg0lVbtmg7fXDqdH/CNpEG02cGRI+UnvNHJNJArR1q/lqLGikc8gVi9i6+qec01kHNZEqyAeBkrpWojZ57OF3Foj5ftbdtkVV3XiW2ImfSt5k60y9nv/GE+Bn5m7QZDRFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyHeB+BHAQQLA+f7K8+L50h4A1il1Y4vVmdotkxkBXLK5QZxqPlzv4GTsrZLetjh1Cua1kqhv/smZ8DXtKg1yojLbN56oSfS4NvKNzYizauGRzHrkrL5v/HzC0YvMszHdMTzP3vl32ZKYG3f+M1Pf6yhPTwC44upWaXzv7qRHM+ue6zmLe+4+IENPnJA581Wn/micgQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnkkYImLa8XHvfLoUXmUPBJILRq7hAcPzPgMZ1lVsDWVkkwgVQdHm1Tg7+zXH0/l0tG21devF1vh4qNFQ6GQTJ26OKrXN3ExEBy9wDwbhasrRI/sTaZYCx3iqFg8KKrv75+YTeZy0TaegYnodqINPWdxpoqjrHBZb1XUWi1N779WSjYa50lOdJPRl89L94/2q+B75p49UZ84jgACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAuYRsMUHgNXAMgoCZhdIewA4GPdFSDTKNh7M0z8hU+0DUrKuLv6Qoa5Hf9a/dZv033/EsD9RpXx7kzR/YE+iZjJ7YUwCbm+4nXcg8Ujjkg31MvRUcvPc6meLTyEQ3yHfqFtC/uTTP+vzvYOJ02dH7uNZ4ujpyPmprC321NKAL3RtR2WRrH7X1eH5k/WPAJItE8d65MJ/vSLuFEZIJ3tt2iGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggED+CMQPbAzMXIwV5c8T8iT5KJD2AHD8F8FW4EjZUc9lmygArC/a+K5dUri6Urp+8ILE3zf+pjoIqUf+Nn1ojyQTkBw72Bm9hGcocQC49MrGcErnhHPwqrhl9Q0botdeaCOZe8afG/Ak/ysUTxJBbX39gYePSd8DR+NvlXS9uK1a3F0jSbefr6H+EUH9W7ZK/Zu3itWV/EdYz/OrA7+RkdzzXZt9CCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEBEwBoX14rPfBtpxxoBMwkkHz1bYq99cWmLlzLX7OiB8yrF7zWSzNyxVXvWStnWRhlT5+gUv3rkru6DHmGrR4zqeXZLN6+SmjdskmRTEeuUz/0PXBpZPHWyT0LB0KKjdh1qvt6NX3irnP4/D4lnofmAbRZp+7V9Urm7LaHu5InehG0up8HU6X7ReesTBVRrb90ivslZ5aGCwCotdTJFX7Nq7zqpvXmzFDZVyom/vk/0iOaUiw6WX7c+POo3Ucrs2GtPqVTcvT8/KJOvpdcw9p5sI4AAAggggAACCCCAAAIIIIAAAggggAACCCCAQO4LxMe1/CpGQkHA7ALpDwCPG+fLtRctPtfuvGCBkPTdd1ia79o77+H4nfZil9Ts2xRe9DE9f24qKYLjr9f7s4Ph4Ghkv06XPPZKR8LArQ42b/z8HeHgsfvcUDjlcNDnl4KGcilaUyvVKihaumVV5LILrnVgdvCxEwseX44DgWmPDD19SureeMWil7PYrNL47l1SuatNhp89LXpkdPwcujb1jl21peKsKQkH23Xwdykjv2M7UryuNvz+i1qqY3cntV3UWiXrPnNbUm3jG42+dE46vvts/G7qCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsAIE7MXGuJYvLu61Agh4xBwUSHsA2D9pDADH/1IiWbPBx09IUWt1UumS4695OcHf6bODKjB6Ov6S4aBuMiN39UjgpvddEz5/qYHooWdOiQ7Qprv0P3Q0PEo3mZTY+l3oRQfl/apv+hcvIX9QHFVFYi9yLXtX9cjjpQR/dUesjqV/zHXAm4IAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIrT8DisBliDEFfIOEUpCtPiSc2o0Dao1vxc+A6yguX7ND5b8+Lnsc1U8XdMSxn/vHheVMd62P9aj7cVMpSAtGzKn107y9eTeU2S26r0zJ3/3h/yufrEdd6VLNO75yO4G/KHeIEBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQOAyBeJjWr7R6cu8IqcjkBmBtAeAdbrk2BL/ZYk9lmg7FAjK2a89Lu7O4URNL/u4vsfpLz8oAbd3wWv1/PglGXnx7ILHL/eAd8wtZ9QcwpkY/Rvpqx5p3XtfZgLOkXuyRgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTMJhAf04qPeZmtv/QHgYhA2gPA3uFp0YHbSLGXFMjlpNXVqYZP/NW9cuHnB8MphyPXXa51KBgKz4V7+u8XD/5G7nf+X59OSxDYMzAhZ/7hIYkfQR25bzrXvfcclL5fHhFtsdxlpndM/CqwTUEAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEzCzgKC8ydI8AsIGDiokFlj45arIPFQqJZ2hKCurLomc4q4vFM2AcGRw9mMxGICR9Ki3y+KEuaf34DUueGzb+VtPtA9L1wxdFp3dOuqi+nP/2UzLyfLs0f3ivuGpLkz51voZBfyA8v3DffSoAq7azVS7cfUDGDpyXll+9fll8p071S/+DR2T8cHe2Hon7IoAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJJC+h4Vmy5rNhW7IXYRiDNAukPAKsHmOkZNQaAVZB0Ob4kM10jcuIvfyFFbTVSee0aqdzdJs5K45cxkZ9vYkYFkjtl7GCnTBztSdR8weMTx3rk+BfvkZqbNkjFrlYp2VAvFmvyA6z1r0bGDnbI0FOnxNM/seB9IgeCXn9kM21rHQg/8b/ularr1knVNWukdPMqsdiTfyY9glg/U/+DR8V9buiy+hn0ZicYngnny4LhZAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEiLgKv20uBGfYOZ7tG03IeLIrDcApkJAKv5dCuvbo32XY+SvYzxv9HrRDbc54dELz0/eUlK1tdLYXOVOCqKROdm1+uQLyD20gIJ+vziG58R/8SsWrtFj0qdPjcoskyZjvWIXT2Hrl5sJS4p394shavKxa77odIE6OCp7ovVYRcdeA4vI9PhwLMOkqdSzn/3mfDzLXrOcqRwViO4R547E15sRU4pv0o90+oKsb/uG1KBWXtZoUgwKP4ZrwSmPCrgPxZ+H9MdQxKc8S3axWQP9vz0ZeX6WrLNl62dTmFOQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgZUn4KwtMTy0uyuFDLKGM6kgkFmBjASA3Z0jhqcqaCg31JetogK5U6f7w8uyXXOJF9KBUB04TVfx60C2WjJZAm5vONV1Ju8ZuVc4sKxMKQgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAJgTi41nx8a5M9IF7ILAUgeTz+S7l6q+fM3VmwHB2YVOloU4FAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAbMIWAsc4qy+NAI4qDK8us8zAtgs74d+LC6QkQDw5IleQy+KmqsNdSoIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIImEWgqKVKLBZLtDvT7QOipwKlIJALAhkJAHv6J8Q75o566LlkC9Q8shQEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEzCZQvK7O0KX4wY6Gg1QQMJlARgLA+pnHD3UZHr10yypDnQoCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACZhCIj2ONxcW5zNBH+oDAQgIZCwCPvHjW0IeKHS2GOhUEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEsi2gM9mWbmgwdGNkvzHOZThIBQGTCWQsADz05EnDo5dsahBnzaXJsw0HqSCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQBYGqvevEYr8UQps6MyCzPWNZ6Am3RGBpApc+vUs7P+mzZnpGZfxwd7S9nji75saN0TobCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCGRboOYmY/yq7/7D2e4S90cgJYGMBYB1r3p++rKhc9U3rBexWgz7qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQDYGitbVS2FQZvXXQH5ALPzsYrbOBQC4IZDQA3PfgUfFPzUZdHBVFUrm7LVpnAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIFsCdTdtsVw66GnTol3aMqwjwoCZhfIaAA4OOOT3vuMw+Trb99qdiP6hwACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkOcCzpqSOQMXu3/yUp4/NY+XjwIZDQBrwM7vPyehYDBqWdRSLeVXNUfrbCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQaYGGt24Xi/VS6GzqdL+MPNee6W5wPwQuW+DSp/iyL5XcBWa6R2XgkdcMjVe/62oRpgI2mFBBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBDIjICrvkyqb1hvuNn57z5rqFNBIFcEMh4A1jBnv/G4YRRwYWOl+lJtyBUz+okAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJBHAo3v3W0Y/Tt9fkj67jdOa5pHj8uj5LlAVgLA0+2D0nuv8UvT+O5dYity5jk3j4cAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIGAmgbJtTVKxo8XQpfavPCoSDBn2UUEgVwSyEgDWOO1ffVQCbm/UyV5aIE3vvyZaZwMBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBdApYXXZpvmuP4RZjBzvVdKbHDfuoIJBLAlkLAHv6J+Tct540WOk00GXbmwz7qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQDgE9ONFVUxq9dCgQlBN/dW+0zgYCuSiQtQCwxur4/vMydbrf4Nb6sRvEUV5o2EcFAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgeUUKN/ZIjX7Nhku2fnvKnZ1yhi7MjSggkAOCGQ1ABzyB+TYn/6XBNU6UhxlhbLm128WsVoiu1gjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsGwCztpSafv4jYbrTZ8bVFOYPmbYRwWBXBTIagBYg02e6JWzX3/CYFeysV5aPnKdYR8VBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBC5XwFbklPWfvU30OlKCPr8c/eO7Jej1R3axRiBnBbIeANZy57/ztAw/e8aAWHPTRln1zh2GfVQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQWKqAxWGTdf/9jVKwqsJwidNfekgmj18w7KOCQK4KmCIALKGQ+lXFT2WmZ9TguOptO6TmDcbc64YGVBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIRsBiUdOQvkFK1tUZWvf98rB0/fBFwz4qCOSygDkCwErQN+aWQ5/9gfinZg2ezXftlco9aw37qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQtIAK/rZ+/Aap2NFiOGX8cJcc/+LPDPuoIJDrAqYJAGvI6fZBOfz7PxKdZz1SLFaLtP3aTVL3pisiu1gjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkJSAxanSPn/mVqm+fr2hvbtjWA597ofM+2tQoZIPAqYKAGvQkRfOypHP/0RCgWDU16J+ldH0/mul8X3XRPexgQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggMBiArZil2z8vdulfHuzodls37i88uvfE9/ItGE/FQTyQcB0AWCNOvjYCTn6Rz+VoD9gMK5/85XS9ul9on+pQUEAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEBgIQFXfZls+sO3SnHcnL+zvWNy4FPfFR0EpiCQjwJ2sz5U/4NHJTDrle1//wGxOi91s+ratVLYWClnv/GEePhimvX10S8EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIGsClbvbpOVjN4itwGHog077rEf+Evw1sFDJMwFTjgCOGA89eUoOfPq74h01Dr/XAeAtf/p2qb11S6QpawQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgRUuYCt0SusnbpQ1v3HznODv2MFOeelXv03wd4V/RlbC45s6AKxfwPihLnnpw9+SqTMDhvdhddml+UN7ZMP/eIsUrK4wHKOCAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCwsgQqdrXJlr94p1Rfv37Og/f+4lB40KFvzD3nGDsQyDcB0weANfhMz6js//A/i/5yxpfSjQ2y5YvvkKb3XyO2Elf8YeoIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJ5LFDYXCXrf/fNsva/3SzOymLDkwa9fnntL38hx/70vyTkCxiOUUEgXwUuTa5r8icMzvrCX87hF87Kpi/cIY6ywmiPLTar1L3pSqm+aaMMPHRMBh49LgG3N3qcDQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgfwS0BliG+7cLpXXrBGLxTLn4SZP9cmxP7lbpk71zznGDgTyWSBnAsCRl9B376syuv+cbPmzt0vNvo2R3eG1nsh71Tt2SN3tV8rwM6dl6ImT5HE3CFFBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJYQMV5S69YLXW3bpGybU3zBn6DPr90fPdZOfuNJyXkZ9RvDr9tur5EgZwLAOvn9AxMyKHP/kBqb94kGz9/hxQ2Vhoe3+ZySN1tV4SXqdP9MvLiWRl7pUP8k7OGdlQQyHmBkHqCkP4vihkE5v6+LIu94nORRfy4W5vpK8rnIu7lZLHK5yKL+Ca+NZ8LE7+cLHbNLJ8L/jckix8Ck95afzb5XJj05WSxW3wusohv4lvzuTDxy8li1/hcZBHfvLcO/7s1/v+FeV6Q/p6arOhYUMXuVqnau05cNaUL9m74hXY5+Vf3ibtjeME2HEAg3wUsD2//ogm/xsmzWxw2af7AtdL2qZvm5HWPvUooGJLpswMyebxXps70h7/4pImOFWIbAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEDCHgLO6RIrW1EjJ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8.33% 77.2% 14.67%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;770&quot; y=&quot;300.25&quot; width=&quot;769.95&quot; height=&quot;70&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-3&quot; value=&quot;&quot; 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8.33% 77.2% 14.67%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;1470&quot; y=&quot;300&quot; width=&quot;769.95&quot; height=&quot;70&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-4&quot; value=&quot;&quot; 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omFSRw0SNbZrw1paSXx57bvBcz/iCGGlAqxUXfmvm/7CwmvX72vj75c0SqCIFcMmrd0sdemfG2FJPeX3tvWT3j7dCAVwXyye+nS5LfU2c6FZLfT/clv6dKlSGQ7x+MJd/dNuONGUx6hu6/ceWMt0MDXhWoSeIoi5/YXhEcdR0tMffKZdF+/cqYc9nScs/iMzXs0HdeiZf+6z9G14t7zlRFOYELQmDWRghaL1kcl/3i90XbdRef9kGlPX2PppOCP7Qxjj63qzxE82krKiQwiwV23XFJ9LU3z+I7qK6mdzy/uyICwDvffGkMJEOmSJUhsOCZnRURAN5x12UxmHyLUqoMgYVPbq+IAPD2uy+PYvILtlQZAou/uzWiAkak2X7PFVFK/qJWqgyBJcm313PJ9DMznba97cqZboLrjxCoiABwEujzXox4KDO8mUu+WFYJAeD0zw/vxQy/DCMun0++oFwJAeA00Oe9GPFgZnizNpnyriICwI213osZfhdGXr7uWG9lBICb6rwXIx/MDG83HO6umADwwKETcfCbm8pL2ku445Y1Mf/2S6I56SE8OnXcvDpu/tRHY9ffPh6bf/+BGOzqHV1FnsAFITDr/sYvHTN+9UfviFU/+qbymPGjn1KhbyAOPvxS7P/K89Gf/FCQCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZr9AIfkiy4GvbygvaUfBxW+7OuZdvTxzY+k8xMvff3MsvOvyePGXPxedD27K7JchcCEIzKoAcPPK+XH1J95b7uI/+uEUk+FLOr+xIfZ+6ZkYPN43erc8AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAlQgcT6b8TJc0dnTRu64vDxM98tYaFsyJ637vQ7HrM0/Ext/4UhQrYPq+ke2zTWAqBWZNAHjRvVfGFf/xB6K2peEUjyNPbY+df/2d6D94/JR9CggQIECAAAECBAgQIECAAAECBAgQIECAAAECBKpToHvbwdj8u/fHnCsuihU/dEs0LpmXudFl776h3Ev4mZ/+60jrSgQuBIFZMbnX2o/dGdf81vtOCf72H+lOxnD/arz8h18T/L0Q3lb3SIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4jUDXC7vjxf/4D7H7c09FabCYqdG6fnHc/JcfjY5b12TKZQhUq0BFB4BztTVx1W++J1b/2B2n+B/6zsvx4i/9fRx7Zucp+xQQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhcWAKlQjH2fv57seHXvxA9e45kbr52TmNc99//WVyU9AiWCFS7QMUGgPONdcnY7B+MJckE3iNTOtfv9r94NLZ+8qFIJ/uWCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAwJ9Ow4FBt/9Qtx8LEtQ0XldT7peHjFL31/XPzDt2XKZQhUm0BFzgGcb6iN1yXfwmi/cVXGe/BEX2xJhnw+seVAplyGAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwJBAsX8wtv3vb0bvrsPlXr+5XG5oV1zyb94aNfW18UrS2VAiUI0CFdcDOB32+Zr/+oFTgr/9B4/Hpt/4kuBvNb6F7okAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMAUC+778XGz7k4dPmRd47cfuihUfunUKruiUBGZeoOICwFf+6rtiwRvXZ2R6dh6Ojf/5i9G792imXIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAWAKHHt0Sm//gq1HoHchUu+Rn3xZL3p6dijRTQYbALBWoqADwmh9/yykftJ6ka/6mT9wXA0d7ZimxZhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECMykQNfzu2Pz794f6dDQQykdFvqKX/7BmHfdiqEiawJVIVAxAeCFd10ea/7lmzOo/YdOlD+MhZ7+TLkMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbMROLFlfzLv74NRKhaHD8sncwFfm0xNWr9wznCZDQKzXaAiAsBNy9vjyv/0gxnLwRN9SfD3KzFwpDtTLkOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgXASOPr0jdvzlY5lD6+e3xtWfeG/kaioibJZpmwyBcxGY8Tc5/TClH6raOY3D7S8OFmLL7z8QvXvM+TuMYoMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOC8BTof2hR7vvC9zHnar18Zqz96R6ZMhsBsFZjxAPCqH31TzL1yWcZv5998N9Ju+BIBAgQIECBAgAABAgQIECBAgAABAgQIECBAgACByRbY8w9PxbHndmVOu+ojb4o5ly/NlMkQmI0CMxoAblm78JRvUxx+fGt0fn3DbLTUZgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVki8Mr/figzFWm+tiau/JV3GQp6ljw/zTyzwIwGgC/9t++MfF3NcOsGjvXE9r94dDhvgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBUCBSO98W2P3skc+rW9YtjxQdvyZTJEJhtAjMWAF781qui46bVGa8dSfC3cKIvUyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCoE0mGgD35rc+bUa378LVHX0ZIpkyEwmwRmJACcq8nH2o/dmXE6+uzOOPLU9kyZDAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGpFNj1t9+NwREdFGtbGmL1j90+lZd0bgJTKjAjAeCL3nV9NF88f/jGSoPF2PlX3x7O2yBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwHQKDyVDQez73dOZSy997YzQunZcpkyEwWwSmPwCcz8WqH3ljxqfz4U3Rt78rUyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDoEOh/cGH0HTsaq8nW1sfLDb5iOS7sGgUkXmPYA8OJ7roym5e3DN1IcGIw9X/jecN4GAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgekUKBWKsefz2V7AF/3A66KurXk6m+FaBCZFYNoDwCs+dGum4Yce3RKDR3syZTIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEplPg0Hdejv5DJ4YvWdNUH8veff1w3gaB2SIwrQHglnWLou3aFcM2pVIp9n3l+eG8DQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIzIlAoxf6vZuNWF737hhlpiosSOB+BaQ0ALxv1Iel6cU/07Tt2Pu13LAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFJETj4yOZIpy8dSs0rOqL95tVDWWsCs0Jg2gLAudp8LP0n12ZQOr+5KZOXIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBTAoXu/jjyxLbM5Q0DneGQmQUC0xYATr8dUTe3aZhkoKs3jj61fThvgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBMC3Q+lO3AuOCOSyNXWzPTzXJ9AhMWmLYA8II3rM806sgTW6NUKGbKZAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjMpMDxl/ZF/+ETw02obW6IttetGM7bIFDpAtMWAG67YVXG4thzuzJ5GQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKVIDA6jtU+Ks5VCW3UBgJnEpiWAHCuriZa1y8abkOpVIr02xMSAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUoTGB3HmnvVskprovYQOKPAtASAW9cvjvyIsdH79ndFOom2RIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDSBE68fCDTpDmXLc3kZQhUssC0BIDnXLokY9Cz/WAmL0OAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgUgT69h+LYt/gcHMaFs6Juo6W4bwNApUsMC0B4JZVCzIGPbuPZPIyBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpGoBTRuzcbz2pZOb9imqchBMYSmJYAcNPFHZk2pN+akAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUqkDvvmw8q+liAeBKfVbalRWozWanJte8YlQA+EDX1FxonLPmG+uirq056uY1vbpOtmvqa2PwRF8MHOuJwaM95XV/5/EoFYrjnM1uAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBahXoP3A8c2vNozo8ZnbKEKgggWkJADcunZe55f5pDADXtTdH+02ro+Pm1dG8MjsUdaZRIzKF3oE49uzOOPL09jiarIs9AyP22pwNAmmwvzn5Jk7z6gWRDkHeeFFb5PK50zZ90yfui8Gu3tPuU0iAAAECBAgQIECAAAECBAgQIECAAAECBAhcmAJ9ndkOjY1LsvGuC1PFXc8GgSkPAOeb6qK2tXHYojhYiMHjfcP5qdqYe/XyWPL2q6Nl3aLI5U4f+DvTtWuS4GEaNE6X0mAxDj66OXZ/9klBwjOBzXB5rq4m0l7mzUmgt3nV/HLAt2HxvDMGfE9p7hkCw6fUU0CAAAECBAgQIECAAAECBAgQIECAAAECBAhcMAL9h09k7rVh4ZxMXoZApQpMeQB49IdhIBlmeSpTTVN9LP/AzTH/tnWTcplcbT4WvOmSaL9hVez+3FNx4OsbIorJzN/SjAsseee10XbDymhKe/fWTMt01jN+zxpAgAABAgQIECBAgAABAgQIECBAgAABAgQITI/A4JFsTKthkQDw9Mi7yvkKTH0AeEH2wzB4pPt823zG4+dcvjRW/sgbo7695Yx1znVHTXN9rPjALdF+46rY/Lv3R7Fv8FxP5bhJEph39bJyz99JOp3TECBAgAABAgQIECBAgAABAgQIECBAgAABAgSGBQaOZmNaDaNiXsMVbRCoMIEp7zZZN68pc8sDUzT8czrU89p/dfeUBH9H3kDrusWx7qfujXzDlMfOR17WNgECBAgQIECAAAECBAgQIECAAAECBAgQIECAwDQKDJ7oi1Lp5KiwNa0NEaaVnMYn4FLnKjDtAeBC8mGZ7FTf0RJrfuLOyNfWTPapT3u+1iTYvO6n7olc/fRc77SNUEiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDB1Aknst9DTP3z+XC4XdXOzHR+Hd9ogUEECU96NtXbUB2GyA8BpT9y1P3l31M1pnFbWtCfwkrddHXs+9/Q5XTeXBKvr5jZG6pP2kk7nLi5098XAsd5k6YnBZCkNFs/p3OdyUOrYuGRepENd5xvqym0YOHQiBs5iyO702Lq25vJSmzyPYv9gpOfoP3g8Bqeo5/e53KtjCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQITESic6I/a5qTn72spjemcTexk6DhrAtMpMPUB4LQ7/Ig0OOKbEiOKz3lz0V1XRNPy9gkfnwZVj72wK45v2R/p5N3FwUISgG2O+vkt0Xzx/Ghdv3jC51p871XR+dCmCX/QGy9qi7bXXZwsK6N55fxxr3Pilc448tS2ZNkefXuPjlt/9Y+/JfJ1Y/RKToYp2PKHX0u+rnJyuILmVfNj2XtuijmXLjnt+Z/8sT89bXm5MBeJ15Jov2lVtF2/csxvvaRzJqf3cuAbG+NEYi8RIECAAAECBAgQIECAAAECBAgQIECAAAECBCpdoNB9sgdw2taalmzcq9Lbr30XpsCUB4BrGusysmkgcNJSMs76gjsundDpSoVi7L3vmdh//wtJT9vsh3XkCdLA7KJ7r0yCmqsj7co/Vkp7zV70rutj2588PFa1SOcnXvHBW6N5RceY9UbvbFm9INJl2btviBNbO2PHXz4W3cn6TKlx6bxoWtp2pt3l8sZFc6N3z6vB5GXvuykW3X3FuPd5uhPOSwLZKz5wS6TDb08kpVYdt64tL907DpXvZTIDwWlgvzcJkvfsOhw9O5MlXSfLxYn7vGtXTKSJ6hAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEMgKj41qj416ZyjIEKkRg+gPAybDAk5XSnrQTCUAOdPXGlt/76pjB06E2dW87GFs/+VAc37QvVnzo1nGDox23rokdn3osRv8ASM+Xfgtk2T+9Iea/cf245xm6/pnWLasWxKX/9p1Jj+ONsfszT2bGnB86pidp+7gB4KQXchoAXvz2q2PxPVcOHTrhdTpk9YofuiXab1w14WNGV0wD4et/5q2x4y8ejYOPbB69e8L53cnw27VJD/M04Nu7Lwlqj+jZPHSSk32dh0qsCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQITE0inuxyZapqyHR9H7rNNoFIEpjwAnE/mth2Ziv2Fkdnz2l74lsvGPb5ULMbW//XghIK/I0/W+eDGyNXmy71cR5aP3s7l85HOB3zs+V2ZXWnw99Kff3s0jtMjN3PQOJlc0uN54ZsvK/co3vSJ+6LYM5A5onv7wXIP20zhqEw6DPWc3oFyz+VRu8bNpvP6XvoL74iGhXPGrTtehXwyB/LKD78x6hfMiT3/8NR41U+7v+uF3actV0iAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAwBAeDJUHSO6RbIT/UF83XZS5SSOXcnK6XDI4+X0jlnuzbsGa/aafcfeODF8rDCp905orD1kuy8wbn6mlj7k3dNavB3xOWieXlHrP1/7iwHqEeWd287NDJ72u20h/BF/+S6s+6RPHRPkxH8Hdmwpd93bcy5bOnIItsECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgYoQKI6Ka+WSDm4SgUoXyEZnp6C1aQ/ZkalUnJxBedPeqPn68Tswpz15zyd1PrRp3MObLs7O7bvyn98WrWsXjXvc+VSYc+nS8lDMI8/Rk8ytWyqN7ZvObdxyDm27+EOvT+YjXjjycpO2ffEP3xbpHMESAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCSBEbHtXI12bhXJbVVWwgMCUx51O2UD0KhOHTt81rXL2gd9/jevUejd/eRceuNVaHzm5ui78CxsapEOm/wUGpYPDfab14zlB1znX5rpGfH4eh+5UD0dXZFw6K5SZB1QTQt6zild+/pTjT/DetjzxefiYFDJ8q7Cz390d95fFKGaB55vdQ6net4vFQaLMahb2+Jzm++FH37j0U6ZHVT0lt50T1XxNwrl53x8IZkGOgl77ymPLfxGSvZQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYboFRHRtHd3yc7ua4HoGJCEx5ADiSIODINE4H1ZFVx9xumD9+ADgNhp5vKibz5R59eseET7P43ivLgc/xDjiRBH03/7evRuFE3ylVa+c2xfp/fW8SPG0/Zd/IgjS4vvieK2PnX39nuDgNRp/NMM39R7ojHeq6Z9fh6D/QFfnG2qhrb4n6ZBns6i2fd9HdVyT3NPY3WtLgc3o/J7bsH25LujFwdFd5fuTF77g6lr3rhsy+kZmOW9YKAI8EsU2AAAECBAgQIECAAAECBAgQIECAAAECBAjMuMCpPYCzca8Zb6AGEDiNwNQHgEd/M2KSPhc1rQ2nuZ1s0eBpgqvZGpOby9Xmo+P168Y9adfGPbHl9x+IYt/gaesOHuuJTb91X6z7qXvGHXZ5/hvXx86/SQLAr4383LPzcLTfuOq05x1d2PnQxtj56cej2DOQ3bX1ZI/mdEfa03i8tO1PHzkl+DvymH1fejZaVi2IttetHFk8vF3f0RItaxbGiZcPDJfZIECAAAECBAgQIECAAAECBAgQIECAAAECBAjMpEA62unIVCqMPRXnyLq2CcyUwJQHgEd/MyImaWz0od6pY8Gl8wRPZ6pPhjLO1409+Xfq8fIffv2Mwd+h9ha6++OV//GNuOo33ztUdNp1TWNducfu0DDQxYHTB5VHH3zs+V2x/c8fHV18Sr6urTnSa4yXlr33xlj2nhvHrDZez+Q0cC0APCahnQQIECBAgAABAgQIECBAgAABAgQIECBAgMB0CowOABcnZ6rT6bwF17rwBKY+AFwoZFRHf1Mis/MsMhMZ3nm8gONELleb9DRuu2HVmFXTuYaPb9wbDROYl7hn9+FIg7sTSf3J3L59B5M5fccZ7jqdQ3coADyR86ZzD+/4v9+eSNUJDyedtuF8U3PSQ1giQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFSKwOi4VqkgAFwpz0Y7ziww5QHg4kD2g5DOWzsZKQ2MjpfSAHAaVOze2jle1TPun/+mS2LZu888d2164LEXdsfmNACcXG+8dGJzdo7cidQfNwC8sDWObxrvTCf3H9+wN/r2HTtZMMZW/QSC2mMcfla7auc1nVV9lQkQIECAAAECBAgQIECAAAECBAgQIECAAAECUymQq82O/FpKOtlJBCpdYHKisWPcZbE3O79svn5yYs6F431R6Mue+3TNWPiWy05XPOGyBckcu+Ol45v3vVollx0H/rTHjZoT+bR1RhSWJjKUwESuO+KcffsnFvxNDzllCO8R55nszToB4MkmdT4CBAgQIECAAAECBAgQIECAAAECBAgQIEDgPATy9dkAcKF3YlNxnsclHUrgvAWmPABcGB0AbpicAHB658c3vRZ4HYNh/m3rkiGcV45R48y7Ft1zZTQsmnvmCq/tGWpHf2fXuHVb1i0at87ICi1rx68/keGwR56z98D47Ryq338WdYeOOdd1TUNd5Cfx/TjXdjiOAAECBAgQIECAAAECBAgQIECAAAECBAgQIJAKjO7YWOiZ2DSf9AjMpMDkRWPPcBejPwijPyhnOGxCxQe+9mLMu3r5uHVXfviNURwoxLFndo5bd6hC2nN4+ftuGsqecZ3Op3vi5QPl/X0TCJY2Le+IfGNdjO4ZfboLpEMiN04gAD2R6448/8Dh7pHZMbfP5tyHvv3ymOcab2exf7D8nMarZz8BAgQIECBAgAABAgQIECBAgAABAgQIECBAYDoEakZ1XJtIfGc62uUaBMYSmPoA8InsNyFqmuvHas9Z7Tv23K7oTYYzHi9IWpMEXNf95N3R+c1Nse8fnxtz/tvWy5bEoruvjLZrV0yoLZ0PbYpSElxOU1/n8SgNFiNXe+aO1elk4as/eke8/EdfHz7udBdKe8Ku/sjtp9uVKUuDpv2HTmTKxs1MZFjp104y2NUbg8d7o7a1cczTpj299973TPTuOjJmvdPtbFg8Nxbcfmly7OGIsxwi+3TnU0aAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAyBmqZsXGswmaJUIlDpAlMeAB441pMxqJ3EAHB64gNf3xAr3n9z5hpnyix40yWRLt3bDsaJLfuj/2h3NMxvjULPQNR1tETT8vZoWtp2psNPKR/s7os9n3t6uDwNBB/6zsuRDjs9Vkp7La//qXtj8+9/9bQ9gdMg+bqfuidaVi8c6zTlfQe/tTmZqLc0br3zqdD54KZY8s5rxjxFGmS/7Be/L3Z95snoTJ5JqVAcs34kgfB5SZB94ZsvizmXL41cMo/x3i89M/Yx9hIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEplGgpqUhc7WBpOOcRKDSBaY+AJwEWUem0R+UkfvOZTsNNrZfvzJa1y+e8OHNK+dHupxv2vuF70XhRPabHmkP447Xry0HNMc6f+sli+Pq33pfORjd/cqBKPQNRk1TXbSsWhhNKzsinQ93vFRKevLu+8rz41U77/37H3ghFt1zxSnj3I8+cb6uthyMv+j7r4ujyXDbx1/aF+kXANJhwOuSHsT1C+dEw4LW8rppWXvUzW0afQp5AgQIECBAgAABAgQIECBAgAABAgQIECBAgEDFCJzSA/hotuNjxTRUQwiMEJiGAHD2gzDeUMIj2jahzbSn6ct/+LW4NOl92rBgzoSOmYxKR763I/YncxCPTr27j8SRJ7dF+w2rRu86JZ/2mp1z6ZLycsrOCRSkc+72T2De4Qmcaswq6TDQaU/rxW+9asx6QzvTH4Ydt6wpL0Nl1gQIECBAgAABAgQIECBAgAABAgQIECBAgACB2SSQdmpMp/YcSoNJp8BxR0AdqmxNYAYFzjxZ7SQ1qj+ZF3dkqps3+b0+0/HWt/zBA5HOQzsdKQ3+vpLM4RuF0w+9vO1PHo7u7QentCnpENbb/+LRKb3GyJPv+swTcTS5b4kAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcCEIjI5pjY55XQgG7nF2Ckx5ALhvVA/VurbJDwCn9L27jsSm37ovenYdntInceSpbeXg71jf8Cgmwzlv/t37o2//sSlpS++eI8n8wQ9Eqb8wJec/7UmLpXj5f34jjieBZ4kAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUO0CowPAo2Ne1X7/7m/2Ckx5ALjQ3R+D3SfnyU3nia1prp8SsZ7th2LDr3w+9n7pmUjnx53M1H/oRLz8P76RDDf99Ql170+HTd74m/fFoe+8PJnNiIPf2hwbP3HfKXMPT+pFznCy0kAhNv/OV2L//c9Pqm/6juz98rOnHVL7DE1RTIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYUoG69pbM+fsOTE3Hv8xFZAhMgsCUzwGctrFv77GoXbNwuLkNC+dE97apGSI57Zm7+7NPRtpTd/Fbr4551yyPfP253+bg8WT+229siL33PXvWPW4Hj/XE1k8+FAcffilWfPDWaFwyb9jgbDd6krmFd/zlo3F8076zPXRS66e9m3f+zXcjnX94xYdeHy2rF5zz+dOg+v4HXojOhzZFcZqG7z7nxjqQAAECBAgQIECAAAECBAgQIECAAAECBAgQuKAEGha2Zu63d8/RTF6GQKUKnHtk9CzuqDvpmdsyTQHgoWZ1bz0YryRDFucbamPetSui/eY1MeeyJVHTUDdU5YzrtAv/0ae3x5Gnd8Txl5KAa+n0c/2e8QSjdnS9uCde+A+fjeZV86PtdSuT5eJoXNqWqZUGrnM12Q7Z6XDWR55K2pEEs9PezRNJ6X13bdwzZtV0zuTzTWkAf+OvfyEaL2qL9htWRdsNK6NpWfu4p+0/eDxObO0szydc7h19hnmUxz3RBCt0vbg7ahrP/JoXk2G0C5PgMcHmqEaAAAECBAgQIECAAAECBAgQIECAAAECBAjMEoGGBXMyLU3jXRKB2SBw5sjYJLa+e0e2t2/DormTePaxT5X2WD38nVfKS1oz31gXdW3NkY7bnq5rkgDx4Im+GDjaE2mP3XSdHjMVKQ3OpkvaQzkdBrtublPUpu1I1qVkjt1cPle+/kDSjsGkHYWe/rNuxvFNe+Ol39571sed6wG9Sc/kPbufjj2ffzpqmpJ7Su6nNpnnuW7eq7aFpGdvOsRzuqSB9XRo7OlMBx54MdJFIkCAAAECBAgQIECAAAECBAgQIECAAAECBAicjcDoeFbPDgHgs/FTd+YEpicAPGq457TX6EyldKjhvr1Hy8tMtSG97lBQNJK2VEtKA9bloHUV3VO1PBv3QYAAAQIECBAgQIAAAQIECBAgQIAAAQIECJydwOh41olR8a6zO5vaBKZPIDvm8BRdt2tDtkdq04qOKbqS0xIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4P4H6hXOSKSZPTivaf+hE9CcjnUoEZoPAtASA03l0S8XisEfjknnloZiHC2wQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqBCBltULMi3p2rAnk5chUMkC0xIAToddPrHlwLBDOtdt67pFw3kbBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpFoHX94kxTjr2wO5OXIVDJAtMSAE4BDj+5LeMw96plmbwMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUoQmHtlNo51+ImtldAsbSAwIYFpCwAffGRzpkFt16+MyOUyZTIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZlKgedX8aEjmAB5Khb6BOPJEtqPj0D5rApUoMG0B4EOPbonB7r5hg/r2lph3dfbbE8M7bRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYAYEFt1+auerBhzdHsW8wUyZDoJIFpi0AXOwfjH33PZuxmD/qA5TZKUOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgGgXyDbXRftPqzBV3//2TmbwMgUoXmLYAcAqx89NPZDzSHsB1HS2ZMhkCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECMyHQcevaqGmsG750776j0fnwS8N5GwRmg8C0BoC7XtgdXRv2DLvk8vlYfPcVw3kbBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGZEIBex6J4rM5fe/dmnIoqlTJkMgUoXmNYAcIqx4/9+O2My/02XRE1zfaZMhgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMB0CrRdvzIaF88dvmRxYDAZ3fbx4bwNArNFYNoDwHu+8Ez07T827JN2o1/y9quH8zYIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITKtA0vt36fe/LnPJvV98JvoPdGXKZAjMBoFpDwCXBgux7f98K2Oz8M7Lo669OVMmQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGA6BDpevy6aLmobvlSpUIytf/LIcN4GgdkkMO0B4BRn519/N9JJs4dSvr42lr/3pqGsNQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFpEcgno9Uue/f1mWvt+fzT0b21M1MmQ2C2CMxIALjYPxgv/9E3MkbtN62OOZcvzZTJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJhKgYt+8HVRN+/kSLWFvoFT4lhTeX3nJjDZAjMSAE5vYvffPxXHnt+VuZ+L/8VtkW+ozZTJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJgKgZZ1i2LhWy7PnHrb//dw9O49OZJtZqcMgVkgMGMB4CiVYsOvfSFKxeIwU8OCObH8/TcP520QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAqBtFPiqh95Y+TyueHTd+88FFuTALBEYDYLzFwAOFE79vzu2P7nj2b8Frzpkmi/eXWmTIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAZAqkI9M2LJo7fMpS0nnxxV/6h0inMpUIzGaBGQ0Ap3Bb/uBrceLlAxnD9APXtKw9UyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDIEFt51eXTcvCZzqh2f+nYcfnxrpkyGwGwUmPEAcPotimd/7m+j0Dsw7FfTUBdrf+qeqOtoGS6zQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOB8BdquXxnL35edkrRr497Y/Lv3n++pHU+gIgRmPACcKhx/aV9s/I0vZUDq25pjfRIErmmuz5TLECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEDgXgdb1i2PVR27PzPs7eLw3nvnpvzb087mAOqYiBSoiAJzK7P7sk7Hjr76dQWpc2hZrf/LuyNXVZMplCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJyNQONFbbHmY3dGfkTcqVQoxrM//+no2XHobE6lLoGKFqiYAHCqtPE374vOh1/KgLWuWxTr//W9egJnVGQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQmKtC8akFc8jNvi9rmhswhm377y3FwVGwqU0GGwCwUqKgAcBRL8ezP/E0cfWZHhjLtjn/Jz7096tqbM+UyBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMYSmHvVslj/M2+N2jmNmWqv/PFDseNT2dFpMxVkCMxSgcoKACeIhZ7+eOon/iK6NuzJkDYta49Lf+GdkXbPlwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMJ9Bx27pY+7G7oqahLlN1+6ceiy2//0CmTIZAtQhUXAA4hR3s6o0nPvKnSU/gnRnn+o6WuPTn3xFtr7s4Uy5DgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYFggn4tl770xVv3IGyNXkw2HbfuzR2JTMi2pRKBaBbJvfAXdZRoEfvKjfxYHH9uSaVVNc32s+Yk7Y/kHbo7ciEm6M5VkCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIELkiB+gWtccnPvj0W33vVKfe/5Q8eiJf+61dOKVdAoJoEKjYAnCKnw0E/nQwHvevvHj/FfNFdV8TlH//+aF6z8JR9CggQIECAAAECBAgQIECAAAECBAgQIECAAAECBC48gQW3XxKX/9IPROu6RZmbL/YPxnO/8Ol45ZMPZcplCFSjQG2l31SpUIwXf/nz0bVpX1ySTNCdrzvZ5MYl85J5gd8RB7+5KXZ95skonOir9NvRPgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUkWaFrRESs+dGu0rs0GftPL9O45Es/87N/EsWd3TfJVnY5AZQqcjKZWZvuGW7Xzr76TfDB3xtWfeF80LW8fLs/lcrHg9kuj7cZVse/Lz8X+B16IUn9heL8NAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB6hSon98aS7//uui4dW3kknl/R6fOhzbF8//+MzFwtGf0LnkCVSswawLA6RM49vzueOw9fxjrf/reWP7emzIPpba5IZa9+4ZYdPcV5SBw5zc2RqG7P1NHhgABAgQIECBAgAABAgQIECBAgAABAgQIECBAYPYLpKPELnrrVUngd03ka2tOuaHBZNTYTb/15dj92SdP2aeAQLULzKoAcPow0nmBN/zqF2LfV56Py/7dO6NldXYO4Lq5TbHsXTfEkndcE4e/80qk3+zo3tpZ7c/R/REgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEqlogV5OPedetKI8MO+fypZGOEnu6tP+BF2PTJ+6L3r1HT7dbGYGqF5h1AeChJ5IGd9PewOl47qs/cnukgd+RqaahLha86ZLy0rv/WBx5YlsceWpbEgw+GFEqjaxqm8CsFVj0+LYYbKqbte2vtobX9g5WxC0tSX4+DjZ6LyriYSSNyFfItARLHnslCvWnfhOyUpwutHbkB4sVcctLH305irX5imiLRkTkCpXx/6hLv7UlSqcZMsszmhmBXLFC3ouHN88MgKtWrED6bi71XlTM86mUnxXpn2Xei4p5LaJS/p8zbYf3onLei5oK+R01/V3Ze1E570Vt70BFNCb9uzXvRUU8inIjansq471IG5NvqI05ly2NtutXloO/6YiwZ0rHX9oXL/3OV+LgI36HOZOR8gtDIHf/NR+vjL9ROA/v2jmNsfLDb4gVH7g5alsbxzxTOiz0iZcPxIltndG760j07jsafQe6olhBP8zGvAE7CRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJVKFA7rykaFs6JxqVt0bS8PRkFdkE0r5gfuXG+wN697WC8/L8ejL1ffEYnwCp8L9zS2QtURQB46LZrW5N5gN9zY6z44C3RuHjeUPGE1oXkW04DR7pjsKs3Bo8nSxIoLiZLoW8gin2Dry4DhSgmS2kwXYpRKiRLuk6++VwqvrqO9Bv6SQ/jtKzc07i8GhFjH+p9PKJoQg1UiQABAgQIECBAgAABAuMI+DVjHCC7CRAgQIAAAQIECBAYV+CUQZXTgqGhlpPtXPJPpCNHpf+m5cmSS/M1yTqXj1y6ToZqToO2uZqayNfVRC5Z0nW+sTZq6usin4xsWdNcH7XpknTyq01Gea1Lgr+nm8t3rAYf+d6O2P5/Hon9D2wQ+B0Lyr4LTqCqAsDDTy/5QbPgDevionffEAveuD7y9bN2pOvhW7JBgAABAgQIECBAgAABAgQIECBAgAABAgQIELjQBfoPHo+9//hc7P67J+L45v0XOof7J3BageqMjCa9bzu/+VJ5Sb9BsvCOS2PhnZdH+82ro76t+bQQCgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpPIB3i+eC3Nsf+r74Qh5/cFuXRWCuvmVpEoGIEqrMH8Bi8zcl48fOuWh6tlyyOljULk7HjO5Kx5OfpJTyGmV0ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgakWSKfp7Nl1OLp3HIoTSe/ero174+izO6O/8/hUX9r5CVSVQHX2AB7jEXW/0hnpMjrVtTdH/fzWqO9oibpkrPnymPPJuPPlMeib6svj0adDSdc01CZj1de+OmZ9Mn59eez6dCz78pKMcZ9Ptstj37825n15+Pvyf1695FB+dAPkCRAgQIAAAQIECBAgcD4Cye8aEgECBAgQIECAAAECBCZFoHTyLKXSa5l0lWyX88l2KRmNtZwvFF/dTtbFdDtdBpPtgUKyLkSxbzCK/YNR6B2IYrIUuvtj8ESyHO+NwWM90X+kOwYOd0ffga7yvpNXtkWAwLkKXHAB4DNBpT9c0uXEmSooJ0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQIUL5Cu8fZpHgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAhMUEACeIJRqBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqHQBAeBKf0LaR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQkKCABPEEo1AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVLqAAHClPyHtI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwAQFBIAnCKUaAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKl1AALjSn5D2ESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYIICAsAThFKNAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEClS4gAFzpT0j7CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMEEBAeAJQqlGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBShcQAK70J6R9BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmKCAAPAEoVQjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBApQsIAFf6E9I+AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITFCgdoL1LuxquVzkG2ujpr428g11ka+riVyylNe1+cjVjFjyuYhkySXHlNdpPk1JPi0qp+GNtPy1MisCBAgQIECAAAECBAicj0DpfA52LAECBAgQIECAAAECBE4jUHr1F43yang7KSuWopQskZSV18l2cbCYlBejVChGcaAQpSSfrov9g1Hse21JtiUCBKZemXlEGgAAQABJREFU4IINAKcB3OaV86N5RUc0Lm2LxsVzo35+S9R3tEbtvKaom9MYtclS01SXLPVT/yRcgQABAgQIECBAgAABAgQIECBAgAABAgQIECBQxQKlJEBc6BmIwom+GOjqjcFkGTjSHf2HTkTfga7o23csenYdju7th6J395EqlnBrBKZW4IIJADde1BYdt6yJttddHHOvWhYtqxaUe+5OLa+zEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIpAK5fD5qWxrKS8OiuWOiFLr7o+ulfXH0mR1x5Iltcfi7r8Tg8b4xj7GTAIFXBXL3X/Pxqh0oLO3hu/jeK2PRPVfGnEuXeOYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKzUCAdTvrQt1+O/fc/H/sfeLHce3gW3oYmE5gWgaoLAOdqa2Lx266KZe++PtpvWDUpiKV0DPv+ZJz6wWRJx61Pl2QM+3T8+vI6HdM+Heu+kNQrpWPcp8Pevzb2fXn9WjPS7TSNCLmP2Hx1n/8SIECAAAECBAgQIEDgHARy53CMQwgQIECAAAECBAgQIDCmwNAvGrnXNpJVLvkn8uWNyKXlyZKrSZZ0uyaf9PJN88k6idfkavORT6bkzKfb9a+ux7zeBHcW+gZi/1eej52ffjyOPr1jgkepRuDCEaiaAHBNMmTA8vfdFBd/6NZoWDhnQk8wHVO+d+/R6O/sSsaX707GmT/x6njzyRAC6dAChZ7+KPYOlCcnn9AJVSJAgAABAgQIECBAgAABAgQIECBAgAABAgQIEDi9QBIczjfURk1TfbLUvTocdGtj1M5tjPq2lqib31KO8TQunRe1zQ2nP8eo0qPP7Iytf/pwHEh6BUsECLwqMOsDwPn62lj+QzfH6h99U9TNaz7jc00nFj/+0v7oenFPHN+yL7q3HYxiMtG4RGC2C+hFXjlPMPl+W8Uk70XFPIr0+5AVk7wXFfMovBeV8ygqqiV+XlTU46iYxlTKe+HPkIp5JcoN8V5U1vOohNZUyjuRWvh5UQlvxKtt8F5UzrOopJZ4LyrpaVROW7wXlfMsKqkllfBe1LU3R8vqhdF6yeKYe+WyaFwyb0yiro17Y/PvfTUOPvzSmPXsJHAhCMzqAPCiuy+PS3727WN+6NMPfDom/NGntpkc/EJ4oy+we3zw3+Wjp6MS/ii+wODPcLu3/1ohmg+fYec0Fn/9P+Sjb573YhrJx7zUm3+5EI3HxqwyLTsf+E/5GGjxXkwL9gQucufHC1HfPYGKU1zl/l/NR6HRezHFzBM+/d2/WIjavglXn7KK//gb+SjVei+mDPgsT3zvzxciXzjLg6ag+pd/u2YKzuqU5yrwtp+Z+ZeimLwSX/lN78W5PsPJPi43WIq3/kIyH9UMp8Gkk85Xf817McOPYfjyNb2luOffz/x70Z/01/jaL3svhh/MDG/UnSjFXb808+9F79yIb3zcezHDr8Pw5RuOluItvzLz70V3e8RDv+i9GH4wM7zRdKgUd/z6zL8XIxkaL2qLthtWxvzXrxtzJNg0JrThP38xul/pHHm4bQIXlEDtbLzb9Fsel3/8+2P+G9adtvmFZNjmg9/cFAce3Bh9+yrgb91P20qFBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECExHo3X0k9qbL578Xcy5fGgvvuiLmXbP81bmHR5yg45Y1cevf/kRs+7NH4uU/+kaUBmf+C5QjmmeTwLQIzLoA8NIfeF1c+nNvi9pkTPjRKZ23d99XnosDX9tQnr939H55AgQIECBAgAABAgQIECBAgAABAgQIECBAgACB2S2QTveZLulcwUveeW2037Q6csn8wkMpX1cTqz9yeyy849J4/t9/Jro27B3aZU3gghCYNQHgfDIZ+BVJr98l77jmlAdTGizG/q+9EHu/+EykQWCJAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgugV69xyNrX/8UOy779lY9t4by3MFj7zj1vWL46Y//7HY9Ftfjp1/892Ru2wTqGqBWREAblrREdf93gejZc3CUx5G14Y9seMvH4vevUdP2aeAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgugV6dh2Ozb97f7RdvzKWv//mqO9oGb7hfH1tXPaL3xfzrlsRL/7Hz0Wxf3B4nw0C1SpQ8QHg9MN6ze98IOrbmjPPoNA3ELs+/Xh0fmNjplyGAAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgwhM48uS2OPbi7liRBIHnv2F9BmBpMlR00/KO+N7/+6kYONyd2SdDoNoE8pV8Qwvfcllc/z//xSnB3+6dh2LDr3xe8LeSH562ESBAgAABAgQIECBAgAABAgQIECBAgAABAgSmWaDYMxDb/vSRePl/fCMKPdlpQ9uuXRE3/Z+PlOcOnuZmuRyBaRWo2ADwkrdfHVf/9vsi7Zo/Mh16bEts/PUvRt++YyOLbRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoCxx5Ymts+NXPR++eIxmR5ovnx41/+qPRdHFHplyGQDUJVGQAeNHdV8SVv/buyNfWZKz3fvnZ2Pq/vxmlgUKmXIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDASIG+/V2x8Te+FMe37B9ZHI1L5sUNf/xhPYEzKjLVJFBxAeCO29bGVb/xnsjVnGxaqVSKHX/17dj9d09Uk717IUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQmEKBQnd/vPRf/jGOfG9H5iqNi+fF9Z/8cNR3tGTKZQhUg8DJKGsF3E3rukVxzW+/P/J1J3v+lorF2PrJh+LAAy9WQAs1gQABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDYJpCPLvvzfvxYHH3kp0+zmFR1x7X/7YOQbstORZirJEJiFAhUTAK5rb47r/uBDUdvSkGHc/hePxeHvvpIpkyFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwYYFktNltf/atOPLU9swh865ZHlf88g9mymQIzHaByggA53Jx1X9+TzLWelvGc/fnnoqD39yUKZMhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcNYCSRD4lU8+GMc378scuuRtV8eKD96aKZMhMJsFKiIAvPqjt8f816/NOHY+tDH2fv57mTIZAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAucqkA4HveX3H4iePUcyp1j/b+6NuVdelCmTITBbBWY8ADzn8qWx+qN3ZPy6Nu6JdOhniQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBkChS6+2PL7301Brv7hk+br6uJK3/9n5oPeFjExmwWmNEAcK42+TD92rsjn6yH0sCxnnjlfz0UkXTDlwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMtkB/5/HY9icPZ07bsmpBrP3JuzJlMgRmo8CMBoBX/vBt0bp2UcYt/bANJkFgiQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBUCRx9ekcceHBj5vQXJ3MBt166JFMmQ2C2CcxYALhx6bxY/WO3Z7w6v7kpjj23K1MmQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGAqBHb97Xej70DX8KlzNfm47N+9czhvg8BsFJixAPDaj90VNU31w2YDXb2x69OPD+dtECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJhKgWLfYOz41GOZS7Rdd3EsuufKTJkMgdkkMCMB4NZ1i2LJO67OOO3+u8cjnXRbIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBdAunotEee2p653NqP3RmRz2XKZAjMFoEZCQCv/pdviVz+5KW7dx6Kg9/aPFvMtJMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCKBHZ9+rtRKhSH76hl1YJY+s5rhvM2CMwmgZNR2GlqddPFHbHorssyV9v92ScjSpkiGQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLTItC3vysOPvJS5lorf/gNmbwMgdkiMO0B4JX/7PXZ3r/bD8axZ3bOFi/tJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqEKBvV96NkrFk72AW9cvjvlvWFeFd+qWql1gWgPA+aa6WPJ912ZM9335uUxehgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMB0C/QfPB6Hv7s1c9ll770pk5chMBsEpjUAvORtV0dtS8OwS/+R7jj8+NbhvA0CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECMyWw/4EXMpde8Kb1Ub+gNVMmQ6DSBaY1ALzsn96Q8Tj4cDKWesnkvxkUGQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRkR6H6lM7p3Hhq+dr62Ji76weuH8zYIzAaBaQsANy1vj3lXLx82KRVLUQ4AD5fYIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDCzAgcf2pRpwJJ3XJ3JyxCodIFpCwAvuOPSjMXxjXsjHUtdIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFApAoe+/XKUBovDzWlduyialrUP520QqHSBaQsAd9y8JmNx5OntmbwMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZkWKHT3R9dLezPNaL95dSYvQ6CSBaYtADzvuhUZh64NezJ5GQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKVIND1YjaO1fa6iyuhWdpAYEIC0xIAblwyL+rbmocbNNjdF727jwznbRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoFIETW/ZnmjLnsqWZvAyBShaYlgBw66VLMgY92w9l8jIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKkWge9vBKJVKw81pWbMwcrU1w3kbBCpZYHoCwOsXZwx6dh3O5GUIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVIpAsW8w+g8eH25Ovq4mWlbNH87bIFDJAtMSAG6+uCNj0LvnaCYvQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCSBHr3ZuNZTaPiXZXUVm0hMFJgegLAK7IB4L7OrpFtmPLtXH1N5Otrp/w6LlCZAvnGusjVTMurXpkAWkWAAAECBAgQIECAAAECBAgQIECAAAECBAictUD//mw8q3mFHsBnjeiAGRGYlqho0/L2zM2N/sBkdp5Hpq69OdpvXB1pj+O6ec1R19aULM1R01RfPmuhbyAGj/XGwNGeZOmO4y/ti6NP78h04T+Pyzt0JgVyEc0r58fcq5ZH67pFUTsvefZzGqO2tXE4+Fvo6Y/BruT5J0v31s449tyu6Nq0N0r9hZlsuWsTIECAAAECBAgQIECAAAECBAgQIECAAAECFSgwukPj6HhXBTZZkwiUBaY+AJzPRf381mHudMLs/kMnhvPnu1Hb2hBtN62OjptXR8vaRZHLJZHAM6SahrqoWVgXDQvnlGu037AqVnzglujecSiOPLUtDjzwYhS6+89wtOJKFEiD/kveeW20Xb+yHPAdq43pFwHSpWHR3GhN3pVFd10RxYFCHHlyW+z++yejv/PkWP5jncc+AgQIECBAgAABAgQIECBAgAABAgQIECBAoPoF+g9m41lpfEEiMBsEpjwAXN/RMtwDMwUpnOiLUqE4KTbzb1sXy99/c9Q0v9rD91xP2pwMUZ0ui+68PHZ/9sno/OamiNK5ns1x0yGQBnIXv/3qWHT35ZGvO/fXOJ20veOWNZF+GeDAgxvKzz+d2F0iQIAAAQIECBAgQIAAAQIECBAgQIAAAQIELmyBgSPdGYCGRa92MMwUyhCoQIFzj5xN8GaGetsOVR840jO0ec7rumR434v/xW0x75oV53yO0x2YDhd88T+/LRbccWls/eOHondPdnLv0x2jbPoFGhbPjfX/5q2RfrlgslKuNl/uEdy8ckFs/m/3R7F3YLJO7TwECBAgQIAAAQIECBAgQIAAAQIECBAgQIDALBRIpxQdmUbHvEbus02gkgTyU92Y0UG6gWPZD8vZXj8dX/3y//SDkx78HdmO5ovnx/qfeVs0XtQ2sth2BQg0JT21L/m5t09q8HfkbaXzB6fB5XzDlH83YuRlbRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVJjA6AFzX1lxhLdQcAqcXmPIAcN3cpsyV0yGgzzXVzmmMNR+7K2pbGs71FBM+Lm33+p9+azQunTfhY1ScWoF0vt/1P/PWGP1OTfZVW1YviMVvvWqyT+t8BAgQIECAAAECBAgQIECAAAECBAgQIECAwCwSKA0Woth/ctrIdFrJdIpKiUClC0x5ALh2VAB48BwDwOkQvWt+4s5omN86baZpoHGd3qDT5j3ehZa958aobT774H+pePYTOi+658pIv3AgESBAgAABAgQIECBAgAABAgQIECBAgAABAheuwGB3f+bm02lKJQKVLjDl49zWzc0G0QqjPigTBbro3TdEOjzv2aRSsRgDx3pjMB2jPZ8rDxt8tr2H65Pu/Evefk3s/vsnz+bSUb9wTrRdtyLpQdwW6Q+DNBCeBpTTQPZgV9KmpF3pcNj9h07Esed2xfGX9kWUxg9U1jTXRzpE9VgpPX/PrsOZKrnkWynp3MZp79bGJfOivr0l0h9aA8n1jz67M/bf/3ym/imZXCT+i2PuNcujPgnC189rjtq25L6Sb7oMHE/u5eCJ5F6OR+/eo3Ho268k93d+Q32Pvn7L2kXRcfOa0cWnzadt2PePz8WJVw5Ef9KudD7f1K1h0dxYcPsl0XHr2ki/pTNWqmmsi/Zb1sSBr74wVjX7CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSoWKI9sO2Lo53LnsSQOIRGoZIEpDwCP7gpfSIJxZ5vyTXXlwN1EjzuxZX90PvxSHHlyW4wOOKdzu869clksvvfKSIOKE0mL7r0iDjy0sRwsHat+2s5Fd10RbTesjOblHWesWh7CeNnJ3UvefnU5KHzkmR3R+fUN0b3t4Mmdo7YaFs8tD009qjiTTQOfG3/9i8NlaSBzWRJAHz0fc/pDqjE5Xzp8wZkCwHUdLWWr9htWxZnGtk/P05QEuofSsnffGIef2hYHHngx0mcxGWnR3VdM6DQ7P/147P9KEsweFUxP34PurZ2xPVk6H9wY63/2bVHTUDfmOZsM/z2mj50ECBAgQIAAAQIECBAgQIAAAQIECBAgQKDaBdJOZiNT2uFMIlDpAlMeAE6DoiPTyLHSR5aPtT3/DevHDdalxxcHBmPX3z1RDjye6XzFvsFyYDgNDs+5bGms/vE3jzuscL6uNpa+85rY/uePnum00X7z6lj+/pvPeX7aNIi6ILnP+a9fFwe+saHc47jYk/2hkl68d9eRSIc0ziU9ms+U0l7HQ2n+G9fHyh9+w1B24uvk9AvffFmkPa/T3rBnk9Jezh03rS4ve77wdOz5h6fP5vDT1m1Zs/C05SML9ye9dfcnPX/HS2mAffdnnowVP3TLmFUbl5x0HLOinQQIECBAgAABAgQIECBAgAABAgQIECBAgEBVChRGzAGc3uDZxkyqEsVNVbzAlM8BPPqDkAZgzzYtfMtl4x5SSnp8vvI/Hxwz+Dv6JF0b9sTm37k/Cj3Z8dtH10vzc5Jew6dL6dDKa//V3bH6x+445+DvyPP+/+zdB5xcZ3no/2f69t6kreqSLcmSJVtyEy6AMaaEDgZCCSQ3CVzSLqRyk3/uJ+0GbnIhlAAJkHAJEBwDtnHvVbYsWc1qK2mbtvfd2Z3+f9+RZzRntszMamfmzOzv/XA45z3nPee853tmFuxn3ufVgd26W7fIlf/fu6RIpWuOLzqAPtu/eGoBba5H7pZesVpaPnJd/CUS1vUo6Q1/8BZpvmvvZf8hW/W2HbL2N28Rq3PpvzXQKbTjRy/HP0RQTcSeSppud8dQ/CXm1K0FS+/znIuxAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJOIOgNGPpsTXHQnOFkKghkSCDtAWAdTIwtQZ/xixJ7bL7totZqKVBztyYqes7X8Ve7EjWbczycFniRkb2RE1xq3lsdVDUUi0XW/MbNUr6tybB7OSo63fJ6FVjWKZ/jy8wiKaIjbQubKqXlw3vFYkvxFasAtA7Ylm5siFzqstcVV7dKy8eXMAr59TsXqGfRAf7FlqlT/ZLKjwsKF0nRHXlg7/BUZJM1AggggAACCCCAAAIIIIAAAggggAACCCCAAAIIrECBUNwI4Pi41wok4ZFzQMAYnU1Dh+cEIAPBlO7irClN2F6P/tQB4KWW0VfOS9NE4vTNpRvqZeTFs9HbtHz0Oqm4qjlaX+4Ne0mBrP/dN8vJv75P/OMz0cu7O0ekau+6aH2+jdXv2CGuJALn8efqEcN6juTlLjol9NhL52TsYGfKl548dkEO/vr3Uj5vwRNU4L7qusX99Lmz/RMLXoIDCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkP8CelrO2GJNdeBd7MlsI5AhgYwHgPUozlSKs6YkYfPxQ10SmPIkbLdgg0BI+u47LBW7WhdsIqrbsQHB4nV1UnPTxoXbL9MRPfJYB3Nj5x92dw4nvHpR69z00YlO0imnk30m75hbJo/1hOcjDqmgfokaMVy4evE5c5tVcHnyZJ8E3IlTbifq65KPqxHOLb96vZSo95eojDzfnqgJxxFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCPBXQMJLZY7ClmXo09mW0EMiSQ+QCwCramUnQANFFxJ5ESOdE1Bh97TfSSbKl/y9akmnpHpqX35wdl+tyQzPaOiQ4k28sKpVgFW6tv2CAVO1sSXqfquvVqftuD4p+cDbedUSOAUy068O4ZnJTZnjF1nRmxl+p5dYvEUVksEb/62xM/k/5D1/3jl2ToyZMS/0evcnebtH7ixgXn+3Wo5666fr0MPnI81e4vS3u7mkt4zaf3SemmVQmvN364S2YvqPdFQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgRUrMGdgo5UA8Ir9MOTQg6c9AKwDnoZiMdQSVubMuzvPGb5x9zx707fL1VAu5UmkftYjhk9/+UHxqSBwbPFPzITnK9ZBxpaPXp9w1K3VYZO6265QQeBXwpcJzHjDwVxXbeL02PqEme5R6fj+s+JWQeiFih5pXbGzdaHD0f3nvv2UjL18PlqP3RhV+wOzPln/uTfF7jZs6yBxNgLA1Srw3Pj+a8Re7DL0Z76KT41u7vz+c/MdYh8CCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACphZIewA4FIwbGq9S8KZS4keZzneuJcVrzneNVPaVrK8Ti5pHdrGig4in/vb+6Kjdeduq4LgONOoAb6I5fUvU/MOxxTfqlmQCwOOvdkn71x8TSTDyunhtrSTj6CgtkNpbNsd2Zc52yB+UhVIg6Ps4KotE9z8TpbCpUpo+tEdKVYrqZErQ45f2rz0mvpg5l5M5jzYIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQfwLxsZNk4lb5p8AT5ZpA+gPA8bnREwRO4wG9w1Pxu+bUdRrjTBZXXeKRtxPHLywe/I3p8PAL7QkDwM4k7hlzyfBm0OuXrv/3QsLgr26cTDBZt2u+a69eLbnowHnZ1iYZfvrUkq+RzIm2EpesfudOqdm3UQW2k0vHoNN1t3/1UZnpSj3FdjJ9og0CCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjklsCcGENc3Cu3noberhSBjAeAxZZcMC7yArxDiQPAenRnn7waOWVJax3YrL5h/aLndv3H/nDg0lVbtmg7fXDqdH/CNpEG02cGRI+UnvNHJNJArR1q/lqLGikc8gVi9i6+qec01kHNZEqyAeBkrpWojZ57OF3Foj5ftbdtkVV3XiW2ImfSt5k60y9nv/GE+Bn5m7QZDRFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyHeB+BHAQQLA+f7K8+L50h4A1il1Y4vVmdotkxkBXLK5QZxqPlzv4GTsrZLetjh1Cua1kqhv/smZ8DXtKg1yojLbN56oSfS4NvKNzYizauGRzHrkrL5v/HzC0YvMszHdMTzP3vl32ZKYG3f+M1Pf6yhPTwC44upWaXzv7qRHM+ue6zmLe+4+IENPnJA581Wn/micgQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnkkYImLa8XHvfLoUXmUPBJILRq7hAcPzPgMZ1lVsDWVkkwgVQdHm1Tg7+zXH0/l0tG21devF1vh4qNFQ6GQTJ26OKrXN3ExEBy9wDwbhasrRI/sTaZYCx3iqFg8KKrv75+YTeZy0TaegYnodqINPWdxpoqjrHBZb1XUWi1N779WSjYa50lOdJPRl89L94/2q+B75p49UZ84jgACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAuYRsMUHgNXAMgoCZhdIewA4GPdFSDTKNh7M0z8hU+0DUrKuLv6Qoa5Hf9a/dZv033/EsD9RpXx7kzR/YE+iZjJ7YUwCbm+4nXcg8Ujjkg31MvRUcvPc6meLTyEQ3yHfqFtC/uTTP+vzvYOJ02dH7uNZ4ujpyPmprC321NKAL3RtR2WRrH7X1eH5k/WPAJItE8d65MJ/vSLuFEZIJ3tt2iGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggED+CMQPbAzMXIwV5c8T8iT5KJD2AHD8F8FW4EjZUc9lmygArC/a+K5dUri6Urp+8ILE3zf+pjoIqUf+Nn1ojyQTkBw72Bm9hGcocQC49MrGcErnhHPwqrhl9Q0botdeaCOZe8afG/Ak/ysUTxJBbX39gYePSd8DR+NvlXS9uK1a3F0jSbefr6H+EUH9W7ZK/Zu3itWV/EdYz/OrA7+RkdzzXZt9CCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEBEwBoX14rPfBtpxxoBMwkkHz1bYq99cWmLlzLX7OiB8yrF7zWSzNyxVXvWStnWRhlT5+gUv3rkru6DHmGrR4zqeXZLN6+SmjdskmRTEeuUz/0PXBpZPHWyT0LB0KKjdh1qvt6NX3irnP4/D4lnofmAbRZp+7V9Urm7LaHu5InehG0up8HU6X7ReesTBVRrb90ivslZ5aGCwCotdTJFX7Nq7zqpvXmzFDZVyom/vk/0iOaUiw6WX7c+POo3Ucrs2GtPqVTcvT8/KJOvpdcw9p5sI4AAAggggAACCCCAAAIIIIAAAggggAACCCCAQO4LxMe1/CpGQkHA7ALpDwCPG+fLtRctPtfuvGCBkPTdd1ia79o77+H4nfZil9Ts2xRe9DE9f24qKYLjr9f7s4Ph4Ghkv06XPPZKR8LArQ42b/z8HeHgsfvcUDjlcNDnl4KGcilaUyvVKihaumVV5LILrnVgdvCxEwseX44DgWmPDD19SureeMWil7PYrNL47l1SuatNhp89LXpkdPwcujb1jl21peKsKQkH23Xwdykjv2M7UryuNvz+i1qqY3cntV3UWiXrPnNbUm3jG42+dE46vvts/G7qCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsAIE7MXGuJYvLu61Agh4xBwUSHsA2D9pDADH/1IiWbPBx09IUWt1UumS4695OcHf6bODKjB6Ov6S4aBuMiN39UjgpvddEz5/qYHooWdOiQ7Qprv0P3Q0PEo3mZTY+l3oRQfl/apv+hcvIX9QHFVFYi9yLXtX9cjjpQR/dUesjqV/zHXAm4IAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIrT8DisBliDEFfIOEUpCtPiSc2o0Dao1vxc+A6yguX7ND5b8+Lnsc1U8XdMSxn/vHheVMd62P9aj7cVMpSAtGzKn107y9eTeU2S26r0zJ3/3h/yufrEdd6VLNO75yO4G/KHeIEBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQOAyBeJjWr7R6cu8IqcjkBmBtAeAdbrk2BL/ZYk9lmg7FAjK2a89Lu7O4URNL/u4vsfpLz8oAbd3wWv1/PglGXnx7ILHL/eAd8wtZ9QcwpkY/Rvpqx5p3XtfZgLOkXuyRgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTMJhAf04qPeZmtv/QHgYhA2gPA3uFp0YHbSLGXFMjlpNXVqYZP/NW9cuHnB8MphyPXXa51KBgKz4V7+u8XD/5G7nf+X59OSxDYMzAhZ/7hIYkfQR25bzrXvfcclL5fHhFtsdxlpndM/CqwTUEAAQQQQAABBBBAAA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tl+313S97CMlOdxpr75NS3d4d13TdtRAYBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMDxAl1PH5GJtgFZ9sXrxJOTNeNRe9tmcXk9cvAvHxQJBGeW8wKBTBFIudsbssoLZNv/+kxY8HfoeLsc/6ffE/zNlJZHPRBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBBAsMHm4xphT1DY2b9lRz0wZZf++dpmVkEMgUgZQKALtzvLLlu5+SgvpKk2/f3rNy6ltPSWDMZ1pOBgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIFoAqNne+TE138nE11Dps0W3LlVVvzZDaZlZBDIBIGUCgBv+PsPS8nGhSbX/gNNcuY/npeg3zxGu2kjMggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjMIaCDvye++YRM9o2Ytlj2f1wjdXdsMS0jg0C6C6RMALj+c1dLzU3rTZ7DpzqN4K8EGX/dBEMGAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEBgXgK+3hE59e3dMjU6aXrfunvukKK1daZlZBBIZ4GUCACXbl8qK/7P602O4239cvq7T0vQN2VaTgYBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBixEYb1Hxp3/7gwRmxZ/c2V7Z9M8fE29R7sUUyXsQSDkB2wPA3sIc2fj1D4vLc+FQ/Goi7pPfCr8DI+X0OCAEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIG0Ehg+0SGNP37JdMz5i8plzVfea1pGBoF0FbgQdbWpBqv/6jbJrSmZ2XswEJQzP3xBdDd8EgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALxFujbc0Y6/3DEVGzd7ZdJ1Q3rTMvIIJCOArYGgMvftVwWvH+rya3jyYMydKTVtIwMAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAvEUaHlwr4w29ZiKXPvV94kevZaEQDoL2BYAdnk9qiv97Sa7seY+aXvsgGkZGQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTiLRCcCsjZ+16UgH9qpuicikJZ/l+vn8nzAoF0FLAtALz4U5dLQX3ljJke+rnxJy+J/sdGQgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCDRAuMt/dL++7dNu1n8R7skf9mFGJZpJRkE0kDAlgCwpyBH6j97tYmn+4XjMtpo7mZv2oAMAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnEW6Hj8kEx0Dc2U6vK4ZeX/dcNMnhcIpJuALQHgpXe9W7JL82espkYnpfWRN2fyvEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgGQJBNQR084N7TLuqvnG9FK1fYFpGBoF0EUh6ANidlyWLP7HL5NPx5CHRQWASAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskWGNjfJCMNXabd1n/2KlOeDALpIpD0APDCD26XrJILvX/9w+PS+fSRdPHiOBFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBDJQoPWx/aZaVd+wTvIWl5uWkUEgHQSSHgDWE2fPTl3PHpPApH/2Il4jgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkFSBoSOtMtrUM7NPl9stiz62cybPCwTSRSCpAeCyHfWSv7Rixibgm5KuZ47O5HmBAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAgF0CnU8dNu267o7LxOX1mJaRQSDVBZIaAF74ke0mj/79jeIfnjAtI4MAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIICAHQJ9+86Kf+RC7Cq7rECqb1xnx6GwTwQuWiBpAWBPfrZU37DedKDdL5ww5ckggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggYJdA0B+Q3ldOmXa/4P1bTXkyCKS6QNICwJVXrxZ3tnfGY6JzUIaPt8/keYEAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIICA3QLdL500HULZrmXiKcgxLSODQCoLJC0AXP6u5SaHvn2NpjwZBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBOwWGG/tl7G2/pnDcGd5pGxH/UyeFwikukDSAsCl25aaLAYPt5jyZBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIBYGhQ+Y4Vtl2c5wrFY6RY0BgLoGkBIB1t/j8pRUzxxCcCshIQ9dMnhcIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIpIrA8MkO06EUrV9gypNBIJUFkhIALlpdIy6Xa8ZhrKVPgr6pmTwvEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEgVgZGz3aZDKVpTa8qTQSCVBZITAF5bZzIYa+4z5ckggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkCoCvr5R8Y9MzBxOVnGe5NaVzOR5gUAqCyQlAJy3pNxkoCfPJiGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQqgLjbeZ4Vv6SC9Odpuoxc1wIaIGkBIBD/0FMdA2hjwACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDKCkx0muNZoR0eU/bAOTDHC3iTIZC/2NwDONEB4OzKQsldUCrZpfniLck7/6y65kswKL7BcfEPjolvQD9GZfhEh0yNTiaDgX0ggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgikiUBoPCs03pUm1eAwHSiQlABwTk2xiXai23zHhGnlRWayyvKlbEe9lO1cLgXLKi2XEpwKyPDJDunf3yQDB5pksnfE8nvZEAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIDMFJruHTRXLrWUOYBMImZQVSHgA2FuUK57crBmAqQmfBMZ8M/lLfaF7+y751BVStGGBuFyueRfn8rilaG2d8Vj08Z3S/fwJaX30TXoFz1uSNyCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACmSMw2W/uNJhTVZQ5laMmGS2Q8ABw6D8GPfRyvFLle9bKwg9vF0/OhQDzpZTtcrulSpVZtrNeBYH3S/cLx9Ww0ZdSIu9FAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIRwF/vzmmlV1NADgdz6MTjznhAWDdQ3d2Cv3HMnud1deeghxZ/qfXGb12rb5nPtt5C3NlyaevkILlVdL4k5cIAs8Hj20RQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgQwQCO3UmFNujnllQBWpQoYKuBNdr6ziXNMu/CPjpvy8Mx6XLP9i4oK/s4+n4t0rZel/uUpk/iNLzy6G1wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAmkmMDU2KcGpwMxRe/KzxeX1zOR5gUCqCiQ8AOwtzjfV3T8yacrPN7Pkk++SojV1833bRW+vg8CL1T5JCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACzhKYGjXHtbJK8pwFQG3TUiDhQ0CH/kOYGp24aKjK69ZI5TVrLvr9F/vGquvWSu9rDTJyunPeRWSXF0hOTbFkFeeJV10U9LO4XeIfHBff4Jh6HpPJ7mEZbx+Yd9kX84bsikLJW1wuubXFxnHoeY99vSMy0tgt4y39sYt0uSR/SblklRVIVqmqT2m+eHKzRA+DMKnKmewdlon2QfEPXWJP79hHYnmLLHUO8pdWSI4ajlzfmWMcb/+oTPaNyqiqt089kxBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBUAG/CgB7iy6MdutVI99O9gyHbkYegZQSSHgA2FuQbarw1KjPlLea0YG7BXdutbq50SV/8Eir9O87K+MdKiCpAq2uLI9kq/HZsysKpPSyJVK8caHl8hZ9fKcc/4ffWdo+d2GplG5bKqVbl0q+CrZaSRNdQ9K/v0k9GmXkVPRAc8lli2XJXe+OWmz/m41y7uevzWyTVZZv+JVfsVJcKgAdmrpfOilNP305dPFMvnB1jZTtWCal25eeD2LPrAl/EQwEZOCtc9L17DEZOtoWvsFFLKl932VS9Z61Ud959r4XZehw68w2RevqpPqG9VK8aVHEOusNg4GgDKl20vXCcRlQ/iQEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAYFpADwM9O3kLcmZneY1ASgokPADsVr1DZ6fA5MUFgMsvXybewgt3WMwuM/T14KEWaVTBTJ/q5Rmapnu5dj93XHSgtu59W1Rgsz50s7B8wbIqKdu1TPreOBO2bnqB7g276I92Sdn2+ulFlp9zqoqk5uYNxkP3NG7636/KWHNfxPfrnrZGT+KIa88vLFheNbM2v75CVn35VvHkmM/FzAZRXuTUlshSFWwuXFUTZSvzKt2rWAe/9WOspU8avv+sTKgg/KUk3cM4Vp3zF5WfDwCreaIXf2yXVF2/LuYudTBc3wigHz2vnZamn70iwcmpmO9jAwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEMh8gcCE31RJPcooCYFUF0j4HMCh/xACFxlcsxLM09htv3tLTn17d8Tgb+jJ0MHgMz94TrqeOxa6KmK+bNfyiMv1Qn186//fD15U8De00IIV1bL2b++QhR/dIS5P+Ckaa+2TgC96kDJXBW5FdfTNVsMer/izGy8q+Fvz3k2y7p73zyv4G1qXvIVlsuZvbpeiDQtCV80rP9bUE3P73AWl4sr2yOr/+1ZLwd/QAivetULW/NV7jZ7ioevII4AAAggggAACCCCAAAIIIIAAAggggAACCCCAgPMEApMhAeA8AsDOawXpV+Pw6GKc6xAeADb/Q7GyO92DNX9JRcxN+w80Sduj+2NuF7qBHiq5d8/cPXunty9cWT390vRce/tlsvgTlxtzy5pWXEJGB35rbt4o9Z+72gjkmoqaCsq4CgJHS+5sr5rztkiW/cm1MXvORiqn7gNbZeEHt4tbDZt9qcmbnyMr//xG1SN4yUUXNaaC9cGpQNT359aVyuKP77qkgLVuZws/vD3qfliJAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACzhAIDQC7L2K0VWdIUctUEkh4AFjP3Ts7Bf3Rg3izt51+rXuRxkp63tnZc97G2j50fftvD4QuCsvrcd1Dj6XiqlWyQAVLE5XKdi6TRSqoGZpGG2P3iK26YZ3MHgo6tIy58hVXr5Y6FdSOZ9LDQi/543erYbwvbmz8oH9KxtsHoh5SwbJKqbxmTdRtrKzUvbkLVlwYQtvKe9gGAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEMk8gNK4VGvfKvBpTo0wQSHwAOGQI42AgOG83PYxxrKTn/Y0052+s902vH28bkOETHdPZOZ+9JXkz63LrSlRQ84qZfKJeVN+wXkpD5hUebeqNuTv9vvmmnJpiWfKpd1l+mx77Xt/9MjUee25nb1GuLP7UxXuNWhgG2vKBR9nQ5XJJxZWromzBKgQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEHCCQDBojmu5PGr+TRICKS7gTfTxudwh/xBUT935puzy2AHgARUAvtR06rtPRx3GWQev/YNjM7upuXWT6J6tsZK+O2TwWKuMnumWsXO9oi8Weo7e/GVVUryuTjx52bGKkNrbNkn/vrMz211KMFTXI+Dzm+YFnh7CoObmDRHnHZ7Z8TsvBg+3SNt/viUjpzpnVules3V3blV1mnu+37Id9dL5dJWMnO6aeZ/VF9pOLiJ+PNkzbASoc6qL1JDW1pp86balRo/yWMNOWz12tkMAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIE0FAiZnlJP4UlCINUFrEXDLqUWIQHgkBslLJVspQewr3fEUlnRNgqoXqz6YSVlleVL+a7lMTfVgdWG7z8ruofy7DQg54ysHlJ65ZdujjlPb/7SCilSweKho23G+8aa+0QPe20lAK3fEFBDKHc8cUj632w0hlIO+qbEneOVrLICyVZ1GVHBad1Dt/yKFUb50f7X+cxRaf7l62Gb6KDuqX/dLfV/co2Uq6Gr50p6WOuLCQBb6fU8vU8d4D73yzeUe7P4+kbPL1ZtseamDVL3/i2i50iOlozhvheViZWhtqOVwzoEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIX4HQuFZYx8f0rRpHnsECCb9NITgV0jU+JCBsxdajApWx0nQP1ljbxWu97iHq8kbn08Min/r27rDg7+xjGGvpkxP/+HuZtBDALpsVcNYB3Mnu4dlFzfl6rK1fjn3tN9L22P7zPZDVe3XSwzdPqHl1dVBZB75LLlscs4fsZN+ItKn5kj352ZEfeVnS+tBeo4fxXAcUOpz1XNuFLh9XVlaS7rV75t+fk54XT1wI/uo3qp7PHU8ekrM/etFKMZI1a7hvS29gIwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEMgogdCAb2jcK6MqS2UyRiB2ZPVSqxo65PNFBIAnVQ/O/KXRDySr+MLcvNG3jM/anOrimAX1qSGbrcwrPNE5JLpX7aKP7Ihaph7CeHayMp+yHm668ccviZ7jOFbKqTKXH2n7bNVj+LJ//USkVZaXZZfmix4uer69gAPvBK5j7ajl4X0y8HbznJvpXtBDJ9qlaHXtnNvoFVnqOEkIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDgXIHwAPD8pzp1rh41t0sg4QFgPUzx7BT6D2X2urle6zlcY6XchaWxNom5vuKqVVKwvCrqdp1PH5Hx1n6xEiwdOdERtazZK4dPxt7Wyj5nl6lf97xyyph7OHR5pPzFlB+pHCvLcutK5x0AtlKu3iZ0uO1I7xs+FjsA7MnPifRWliGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggIBTBEI6NobGvZzCQD3TSyDhAeDA5PnhhqdZ3F7P9EvLz1YCwOWXr5DWR/aLhA7GbnEvetLuhR/absyDG+0tAweajABwdnlBtM2MdSMNXTG3md5gtLE75py+Ro9UfaFRQxlbTbq3q9WUZaFOVsuKtV2ihlfWw26PqyGvY6XxzsFYm7AeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEHC7gzjLHtayOVupwNqpvs0D0SWzjcHA6IDc7uSzM5zt7e/3ayly3OiBbtrM+9K2W8yVblsQM/urhlIdPdRplBv3mwHakHel5cq0mT06WiEsFd6OkoF/1pp5H8FcXNamGl7aa9DzAyUpZJYkZXnnsXK+6CSB2LaZGJmJvxBYIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDgaAF3trkv5dTYpKM9qHx6CCQ8ABwYMwcVPSH/UKwwDanheqcmzOVEet+ST18hOTWx5+YNfW+2mvt20cd3hi4Oy4+19MnU6Pl/2Hre3lipcFVNrE1m1hesrFbx3+gB4Mnu2PucKVC90AHriXm8Z6JrfuXP3td8X3uLc+f7Fkvbc+eNJSY2QgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQsCoQHg0LiXhSLYBIGkC5hvW0jA7kPvhHBfRA9gXUbvaw1Sde2aqEfoycuWlf/tZjn7oxdk5OT5nrpR36BW6uDv6i/fKtllsYd0Hj7aNlOclcBq0foF0vHkoZn3RHtRvG5BtNXGuonu2HMhzy5Euxm9hmcvjPLaSlBbv737xROWhlmOsisZOdMdbTXrEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHbBULjWqEj39p+gBwAAhEEEh4A9g+bh9qdz7DIs4+365mjMQPAevucikIV0L3NCFL2vHJKRueYhzdvcblU37heynYtEyvzEgcm/NKx+/DMIY019828nutFsQoAL/qjXdL8qzfm2sRYXqkC3gVYywAAMjdJREFU21XXr4u6jV451qyGN55PsjAU8uziRpt6ZmfnfF2wvEra/vMt8fWOzLlNpBVZZflSefVqKb9ihfT/jycibcIyBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCBlBELjWqFxr5Q5UA4EgVkCCQ8A+wbHZu1OxFOQY8pbzYy39svgkVbRQdVYyeV2GcFi3WN4UgUpJzoHRR+Hy+sxevpml+fLfOeg7XjqkPj6Rmd23b+vUXwfHZWs0uhz2VbfsF50z+SWB/dI6EVB3zWi1y/44LaZcud6EZwKSPdzx+daHZflw8fbZVTNoZuvguPRUt7CMll/753S8vA+6Xv9jIT28ja9Vw1rXbS2VqquWyslWxaLy/3OqOPqHJEQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgVQW8IbEtXwD5rhXKh87x+ZcgcQHgEP+IXjzsy9au/HHL8nar74vZtB19g6yywtEPy4lTfaPSscT5qGcdUC28+kjsvAjO2IWXfHulaIfetjosXN94vK4JLuySHJrS1RA1FogtG/PGSOYHXNnl7hBx+MHZdnnr41Zig5qL/nUFbL445fL0Il2Y0ho/9C4Me9wdnmh5KihtbMr1bN67fImfKrpmMfLBggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIDAvARUJzd3btbMW4LBoOhYCAmBVBdIQgD4Qq9ZjeEtyrtoE58KxJ7+t2dk9V/eKu6shB+6cZz+kQk5/d2nJTDpDzvuruePS+V1ayRHBXOtJL2d1W1nl6fHk2/73duzFyXsdd/es6pX8jopWFFtaR86uKt7ZVvpmW2pQDZCAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBFJAwFuUKy4VBJ5Ofj3qrQoCkxBIdYGEd82c7Bo2GWSVXHwAWBc0erZbGn/ystHT1FRwAjI6+HvyX56UsabIc+8GVGD21Ld2iy+Bd3sE/QFp+N4zMtE+kIAaRihSXbhOffcPMp6s/UU4BBYhgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnYLhMa0JkJiXnYfH/tHYC6BhAeAJ7qGTPsO/cdiWmkx0/fGGTn5zScktGyLb7e0mS771L8+NWfwd7qQiY5BOf2d3aJ76cY7BQMBOfvjF2XoaFu8i45a3pQKfOu66/mTE5H0EAnBAHfIJMKWMhFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCA+AqExrUTGpeJzxJSCwHmBhAeA9dDJPt0l/p3k8rjFe4m9gHVRwyc65Oi9j0nXs8fi2hs4MOGX1kf3y5F7HpXRxp7pw476PHq2R4783aPSf6Ap6nbzWTmiejof+/v/FB3stiPp4K/27X7heNx8A/4p6X7ppBxVtr4EBZftsGKfCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkHkC2eUFpkpNdA2a8mQQSFWBpEykO97aL1nFF4Z+1vPg+gcuBIUvFkcHl8/94jXpefWUVFy5Ssq2LVVzDOdeVHF6GOeB/Y3GXLsXE5zU72lQ8xOXbFksdXdskfwlFRd1HPrukY7dh6X7uWNqHPmLKiJub5oam5Smn72qfE/Lwg9tl4KV1aax7q3uyD86Id1qvuTOPxyNy3m3ul+2QwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQuViC7qsj01vHWJE3XadorGQTmL5CUAPDouV4pWls3c3Q51UUycrpzJn+pL0bPdIt+6GBw8foFUrajXnIXlElWaZ4ReNa9jv3D4+ItPB8c1kMr+1XA19c/JkPH26R/f9P544lDwHXgwDnRj+zKQindukQFhJdIbk2xEZh2ud0yNTop7hyv6GPSQyFPDU/IRM+wDB5sNo5jTFlZTe2/f1vyFpXNubkOkMcjjZzqlBP/9LjyzJdSFWQv3abrVCLeYjX5uapTaNLzFo+19InuxTza0CV9+86K7ll9qcnonf3Im+IpyJ6zKD0kt5U0oo6r46lDUTcdePtc1PWsRAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgcwV0B0aZycd7yIhkA4CSQkAjzWZ/0HkVBcnxkbNKzt4qMV4zOzAJUbg1+V1izvbawRgdTA40b1rJ7uHpXP3EeNhHMs7x6GDvzoFfVOiex3LJcyF26t65iYz+fpHpeuZo8bD2K/LZQS2s1QgWHUNPm+revsGxuI/H/J0PXXQOx5JB+JbHtwbj6IoAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBDJQIKfWHM8aa7I2dWgGUlClNBNISgB45EyXiSVvQakpn9CM6tWre/vanqaPY8j2I4nfAagezH41v7N+kBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBjBFwu4zRUGfXZ0SNRktCIB0EwsfvTcBRDx1rN5Wat6TclCeDAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQKoI5NaViDvLM3M4Y639qdHhcOaIeIHA3AJJCQDr+VZnz0erx0z3Fp2fj3fuQ2MNAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskXKFhWZdrp0HFzZ0fTSjIIpJhAUgLAwamADB1rM1W9cE2tKU8GAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgVQQKAqJYw0ebE6Fw+IYELAkkJQAsD6Svj1nTQdUsmmRKU8GAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAdsFXC4p3rDQdBh9e8+a8mQQSGWBpAWAu186aXIo3bpEXNkXxk43rSSDAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAgA0CxRsWmKYy9Q2MygA9gG04E+zyYgWSFgDu398kE11DM8fpycuW8p3LZvK8QAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMBugcprVpsOofMPR0UCQdMyMgikskDSAsASDErrY/tNFpVXm/8BmVaSQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCJAt6SPCnZvNi0x5aH3zTlySCQ6gLJCwAriZaH96k48IU7JApWVEve4vJUN+L4EEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEHCCgOy+6PBfCZ8MnO2SQ4Z8dcOYzq4oXWnAS6jXe0i+9rzWY9lRzy0ZTngwCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACyRZwZXmk6vp1pt22/HqfKU8GgXQQSGoAWIM0/e9XTS5lO+slp6rItIwMAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskU0L1/s4pyZ3bpGxwLm950ZiUvEEhhgaQHgHteOim6u/x0crndUnfn1ukszwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggkVcCd7ZXa2zeb9tn8wB6ZGp00LSODQDoIJD0ArFHO/PAFk03ZrmWSt4S5gE0oZBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBJIiUH3TBskqzpvZlw78Nv38tZk8LxBIJwFbAsAdTxySoWNtM04ul0sWf/JdM3leIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJAMgezyAql97ybTrhrVlKa+3hHTMjIIpIuALQFgjXPyW7tNRoUrqqXiqlWmZWQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE/v/27gTIj6u+E/hvbs3oHt33YcmWfMk2xja+YiA2EIzBpAhQXgJ2NgGScsGyuyQFix2SDZuiqN2tpLJJnBAgYU0IjjHmyBoTwNgY4/vSaWxLsu5bGmkOzbXdY480I/3nPzPyjObf//501d//7tfv//q9z2tMwXf6NQECBAgQGE2B+clDiukS0L3b0ST43fTVn/ce+iaQOYExC4D3/eLF2PXva/uBzf+tN0ZN8lcWNgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKjLdB42RkxZdWCfpd54X/9MDqPtPUrc0AgSwJjFgCnSBu++G/9Xp5dVV8bi2++MqIiS4T6SoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkDWBdOnn+R+8pF+3Dzy1Obbf+3S/MgcEsiYwpgFw646Dkf4VRd9t4oo5MeeGC/oW2SdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwYgIVVZWx5GPXRHVD3bE2O1vbY83t9xw7tkMgqwJjGgCnaFv+5bHYmywH3Xeb/RurYvIFC/sW2SdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwIgILbrosxi+Z0a+tX/3v+6N5095+ZQ4IZFFgzAPgFG31Z/412nY3HfOrqKyIJb93dYw/Y+axMjsECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEXq/A7HetiulXndmvmV0/WRevfOOX/cocEMiqQEkEwEf3HYnn/vBb0dXRecyxsqY6zrj1rTFuzuRjZXYIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQInKrAtCT4nXvDhf1+3rxlX6z53Lf7lTkgkGWBkgiAU8ADT2yK9X/+g36W1ePrYtknr4uaqQ39yh0QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGI5A+vrRhf/hsn4/6WhqjWduvTPSbxuBchEomQA4Bd36rcdj0z893M+2tnF8nPVH74xxc6f0K3dAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCgCjW86I5Z+7JqoqDwejXW1d8az//Vf4shLu4fShDoEMiNw/C4vkS6/8KX7Ytu9T/XrTRoCn/npd8T4Zd4J3A/GAQECBAgQIECAAAECBAgQIECAAAECBAgQIECAQFGBWe84LxbfclVUVB2Pxbq7umL1Z++Ofb94sehvnSSQRYHjd3oJ9X7N7d+Jnfc9369H6XLQyz91XUy+cGG/cgcECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEThKoiJj/wUtj3nvf0O9UGv6u/fy9J2VR/So5IJBhgZIMgKOrO577o7tOehK4sqY6ln78zTH3PRdFVCT/qbURIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQOEGgeuK4WP6f3hYz37Ky35mujs5Y/Zm7Y9s9/Vej7VfJAYGMC1SXbP+TEHjN5+6J9v3NsejDVxzrZkUS/M5+5/kxYfms2PiVB+PonsPHztkhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIt8Ckc+f1ZEs1Uxr6QXQ2H43n/vBbsednG/qVOyBQbgKl+QRwH+UX/ucPY+2f3BvpX2T03SacOStW3v7umH7NWcnTwH3P2CdAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMibQFVDbSz87ctj2SeujRPD39adh+Lxm78s/M3bTZHT8ZbuE8B9JmTrvz4RR17aHed98X1RN3PSsTNV42pi4U1vimlXLI9X7nwkml/ec+ycHQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRwIJA8KTrt8Wcz9zYujJln6+cRt3y9fiueTV48e3XfkxFOOCZSlQCYC4FT+wFOb45H3/02c86c3xvQrl/ebjPGLp8eKz1wf+5/cFNu//WS07jjY77wDAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB8hOYvGpBzL3xoqifN/WkwaWry278u5/FS3c8EJG8etRGIC8CmQmA0wlpT/4y4+k/+HrMfe8b4sz/8raoHl/Xb56mXrQoplywMA4+vTl23vd8z1PD/So4IECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyLZAVUVMvXhJzHr7udEwv7HgWNKVZVf/t7vj0OptBc8rJFDOApkKgHsnYtvdT8TehzbE8v/8tpj99vN6i3u+KyorYkoaBCef5s17Y8+DG2L/Yxuj80hbv3oOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEsiMwbvbkaEyWep52xbKomVRfsOOdLUfj5eSp301fezi6kyeAbQTyKFBx//m3ZfqZ96kXL45ln7w2Jp83f8D56+7siqYNO+JAskR009rt0Za86NtGoBwENuyvi/au5OUGtpIQOHNKa9RUjX1X1if3RYf7Yuwn4rUenDW1Naorx74765L7otN9MfYT8VoPViT3RVUJ3Bdr99Ulqx/575FSuTFWNrZG8reMY76tSe6LbvfFmM9DbwfOTu6LihK4L1bvPfkdWr199H36Bc6Z1nr6L3rCFbuT/ydhzT73xQksY3ZYUdEdZzeO/R++p6sqrnVfjNl9cOKFK5P7YmUJ3BfJ/y0X6/b798WJ8zNWx1WV3bFi6tj/+6IjuS/Wuy/G6jY46brVyX1xVgncF+1JTrfhgH9fnDRBY1RQk9wXZ5bAfRHJk77pa0AnnTsvefBvcdTPnTKgSHdXV2z/3rPx0l/92KtCB1RyIi8CmQ+AeydqxltWxJLf/bWYdPbc3qIBvzsOt0bzxr3Rsm1/8i+BQ3F0d1Mc3X8k2g80R1dbx4C/c4IAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGBkBaom1EXt5IaonTY+amdOivo5k3ve6Vu/sDEqa4ovZps+BLjrR2vipb/9aRx5cffIdkxrBDIqUDYBcK//1EuWxMKb3hTTr1oeFafwaE1Xe0d0NLVFZ/PRSJcJ6Gxt7wmFu9qS7+RPkLqTT/rS8PRfKN3Jn6r1fHd2J09JJH/mmpalf+6a7KeHPf/ou9/byfScjQABAgQIECBAgAABAiMp0PM/QkayQW0RIECAAAECBAgQIJBrgd7liPquSpSU9RSn/+jdT5azqqisTD5JWe9+siRemtFUJN+VybKJ6aci/a6riaq66qgaVxOVDbVRPb6u53MqeU77oZbkid9n4pWvPxItW/fneqoMnsCJAmUXAPcOsG7mxJhzw4XJO4LPjQnLZ/UW+yZAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMigQPqA3v5HX44dP3g2dv5wtVVdMziHunx6BMo2AO7L17BoWsx484povOyMmLxqflQ31PU9bZ8AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAEBdp2HYr9T2yMvQ+/GLt/uj46kid/bQQIFBfIRQDcjyBZkmD80unJU8Gze74bkvXjx82ZEuNmTUrWlp8QlbXF15Lv15YDAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB1yXQcaQt2nY3RdvOQz3LOTdv3pe8z3dXNK3bEWkAbCNAYHgC+Us7k/dipS8BH+hF4FXJevM1k+ujeuK4qEk+VfXJevTJE8OVyXr06br0lemnd6369Dtdw/61dez7r3H/2vr36Zr3PWvhpxOT7Kf/fPWrZ98/CBAgQIAAAQIECBAgMCIC/ofGiDBqhAABAgQIECBAgACB1wSSPKV3e3U3OU6LkoPurnT/te9kPz3u7uyK7o7k09UVXe2dPfvpd1dbR3QdTT7Jd2fL0Vc/zUejvak1eZq3NdoPNPec772WbwIEXr9A/gLgQcw6k78yST82AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZE2gMmsd1l8CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKCwgAC7sopQAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKZExAAZ27KdJgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKFBQTAhV2UEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIHMCAuDMTZkOEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoLCAALiwi1ICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkTkAAnLkp02ECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgUFhAAF3ZRSoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcwJCIAzN2U6TIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcICAuDCLkoJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQOQEBcOamTIcJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQWEAAXNhFKQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBDInIADO3JTpMAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAoLCIALuyglQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA5gQEwJmbMh0mQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAYQEBcGEXpQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMicgAA4c1OmwwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECgsIAAu7KKUAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECmRMQAGduynSYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEChQUEwIVdlBIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBzAgLgzE2ZDhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCwgAC4sItSAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZE5AAJy5KdNhAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFBaoLlyslAABAgQIECBAgAABAgQIECBAgAABAgQIECAwugIz3rwi0s/ElXNi3KxJ0bxpbxxauz22f/fpOPTc1tG9uNYJECBQpgIV959/W3eZjs2wCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVIUqKiIZZ/89Vj8kSsL9q6rvSPWfv67PUFwwQoKCRAgQGBAAUtAD0jjBAECBAgQIECAAAECBAgQIECAAAECBAgQIDAaAlMuWDBg+Jter7KmOlbefkNUNdSOxuW1SYAAgbIWsAR0WU+vwREgQIAAAQIECBAgQIAAAQIECBAgQIAAgeMC4+ZOiUv/+aMRyRO4Y7Ft+urPY+OXH4xpVy4f9PKVNVXReOnS2P2TdYPWVYEAAQIEjgsIgI9b2CNAgAABAgQIECBAgAABAgQIECBAgAABAmUtkD5RWzO5YczGWD9/as+1e78H60j9vFfrD1bPeQIECBA4LmAJ6OMW9ggQIECAAAECBAgQIECAAAECBAgQIECAAIHTIHDw6VeGdJUDz2weUj2VCBAgQOC4gAD4uIU9AgQIECBAgAABAgQIECBAgAABAgQIECBA4DQI7PnZhuhq7yh6pdadB+PQ89uK1nGSAAECBE4WEACfbKKEAAECBAgQIECAAAECBAgQIECAAAECBAgQGEWBlq3744nf+Woc3Xu44FWaNuyIxz/85Yju7oLnFRIgQIDAwALeATywjTMECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAKAkcfOaVePjdfxmTVy2ISSvnREV1VXQcbo2mtdvj4HNboqut+BPCo9QtzRIgQCDzAgLgzE+hARAgQIAAAQIECBAgQIAAAQIECBAgQIAAgewJVNXXJoFvW+x96IWeT98RpGFwZW11dB19/SFwzeT6GL90RoybNzVqG8dH+/4j0bLtQLSmn+0H+1626P64OZOjfkFj1M9vjK7W9uju7IrWHQejedPeaD/QXPS3wzk5bvbkqJ0xMepmJp/pE5NgvDLadjUlfX21vwM9NT2ca6hLgEB5CwiAy3t+jY4AAQIECBAgQIAAAQIECBAgQIAAAQIECJSkwGV3/X5PINu0fkccWrst2nYeioZF02Ji8jTwhGUzY+/PfxXPfOIbPX2ffvWZsfRj1xQdxyvfeDS2f/fpY3UmnTsvFt50Wcy89pyorKk6Vt535+DzW+OVOx+Jnfetju6Ozr6nXt2vqIj02os+ckVMvWjRyeeTkq7kd3se2BBb7nos9j38YsE6gxVOOmduzLru3Jh53TlRP3dK0eppeL31rsdj67efjPZ9R4rWdZIAgXwKVNx//m0W0M/n3Bs1AQIECBAgQIAAAQIECBAgQIAAAQIECORQoLK+ZsijvuAvborGS5YUrf/oTXfE4Rd3Fa3Te7K7vetY0PqWx28bMJhN66eh8KMf+Nuen05JwteLv3JLbzMFv9NAdO0ff6fnXBoWL0k+FUmAO5Stad32eOoPvh5H9xx/J3H6hPJ5X3xfTwA8lDbSOmkf1v3Z96K7vUCYXKCRNOhe+cfvjsnnzS9wtnhRV3tHEgQ/ERu+dN8x0+K/cJYAgbwIeAI4LzNtnAQIECBAgAABAgQIECBAgAABAgQIECBAIBHoamkfskN3V9egdTubjw6rzUEbLFDh8IYd0d3dXTTQTZd5Tir0hLazkidph7NNXDEn3vhPvxtPfvRr0bJ5X8+TyRf8nw/1vJt4OO3Mu/GiGL9kejzxO18tGsqmyzov+b1fi8W3XFU0BC927cqa6ljwwUtjwlmz49lP/XOytPXILUNd7LrOESBQ+gKVpd9FPSRAgAABAgQIECBAgAABAgQIECBAgAABAgTyLJC+K7hl6/6iBBOSAHjxzVckSykPL/ztbTRdevmcP72x5/DsP3nPsMPf3namXLAwln78mt7Dgt9nf/49sfSj15xy+Nu30XRp6kvu/GjUTp/Qt9g+AQI5FhAA53jyDZ0AAQIECBAgQIAAAQIECBAgQIAAAQIECGRF4PC6HUW7Wj1xXCz7xLVF6wx2Mg1vL7rjwzH9qjMHq1r0/OKbr4wJy2cVrHPGrW+NOdevKnjuVAvT8Hrl52441Z/7HQECZSYgAC6zCTUcAgQIECBAgAABAgQIECBAgAABAgQIECBQjgLpe3pPx9Z46dLXfZmKqsqY8+4LTmpn+lXLY8l/vPqk8pEomHHNWTH7neePRFPaIEAg4wLeAZzxCdR9AgQIECBAgAABAgQIECBAgAABAgQIECCQB4Gm9cWfAB7IIH1HcUVtVVRWVw1UZUjlHU2tUTWhruh7iPs2NOvac+KFL93XtygWDzH83fPQC7Hpaz+PQ89vjbT/tTMmxux3nBeLP3JF1E4beKnnMz/9jtj5w9XR3d7Z77oOCBDIl4AAOF/zbbQECBAgQIAAAQIECBAgQIAAAQIECBAgQCCTAsN5Ari7syte/Ksfx54HN8ThDTujIgl/p1+9vGeZ5NrG8UMef9uepnjxL/899v3ypWjdfjCqGmpjwQcuiaW//5ZB3987bvbkaFg0LZo37e253uRVCyJdYnqw7Vd/8aPY+OUH+1U7urspNv/jw7HrR2vi4q/cEmnbhbbaKQ0x7fJlseeB9YVOKyNAICcCloDOyUQbJgECBAgQIECAAAECBAgQIECAAAECBAgQyLJA266mOHqgeUhDWPc/vt8Toqbhb7p1d3TG7h+vi8c+/PfRNcSnYztbjsbTt94Z2+55qif8TdtJn8bd+A8PxZrb70kPB93qkid3e7ehvPd3x/977qTwt/f36XfrtgOx+nPf7lt00v6s6845qUwBAQL5EvAEcL7m22gJECBAgAABAgQIECBAgAABAgQIECBAgEBmBdIANpKnXItt2+55MrZ+6/GCVVo274ttdz8R899/ScHzfQvXfeH70bRmW9+iY/s7vv9sLL75ypiwfNaxskI7tdOPL9ecPg082Db77efFjKvPGqxa0fPpu4DTJ57T0NtGgEA+BTwBnM95N2oCBAgQIECAAAECBA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7.33% 77.2% 0%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;-80&quot; y=&quot;300&quot; width=&quot;930&quot; height=&quot;70.24927160893493&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-2&quot; value=&quot;&quot; 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8.33% 77.2% 14.67%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;770&quot; y=&quot;300.25&quot; width=&quot;769.95&quot; height=&quot;70&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-3&quot; value=&quot;&quot; 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8.33% 77.2% 14.67%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;1470&quot; y=&quot;300&quot; width=&quot;769.95&quot; height=&quot;70&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-4&quot; value=&quot;&quot; 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TL5FJ1WGwOLvbI2aZOSImU57b14VxeQLU1JlCCz59iuRHyzOeGP23Lo6Ssk3cqXKEFjy6MuRT0eWmeG0+7Y15W9wz3AzXP41gaXf2hK5mX8tYvcb1nomFSRw0SNbZrw1paSXx57bvBcz/iCGGlAqxUXfmvm/7CwmvX72vj75c0SqCIFcMmrd0sdemfG2FJPeX3tvWT3j7dCAVwXyye+nS5LfU2c6FZLfT/clv6dKlSGQ7x+MJd/dNuONGUx6hu6/ceWMt0MDXhWoSeIoi5/YXhEcdR0tMffKZdF+/cqYc9nScs/iMzXs0HdeiZf+6z9G14t7zlRFOYELQmDWRghaL1kcl/3i90XbdRef9kGlPX2PppOCP7Qxjj63qzxE82krKiQwiwV23XFJ9LU3z+I7qK6mdzy/uyICwDvffGkMJEOmSJUhsOCZnRURAN5x12UxmHyLUqoMgYVPbq+IAPD2uy+PYvILtlQZAou/uzWiAkak2X7PFVFK/qJWqgyBJcm313PJ9DMznba97cqZboLrjxCoiABwEujzXox4KDO8mUu+WFYJAeD0zw/vxQy/DCMun0++oFwJAeA00Oe9GPFgZnizNpnyriICwI213osZfhdGXr7uWG9lBICb6rwXIx/MDG83HO6umADwwKETcfCbm8pL2ku445Y1Mf/2S6I56SE8OnXcvDpu/tRHY9ffPh6bf/+BGOzqHV1FnsAFITDr/sYvHTN+9UfviFU/+qbymPGjn1KhbyAOPvxS7P/K89Gf/FCQCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZr9AIfkiy4GvbygvaUfBxW+7OuZdvTxzY+k8xMvff3MsvOvyePGXPxedD27K7JchcCEIzKoAcPPK+XH1J95b7uI/+uEUk+FLOr+xIfZ+6ZkYPN43erc8AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAlQgcT6b8TJc0dnTRu64vDxM98tYaFsyJ637vQ7HrM0/Ext/4UhQrYPq+ke2zTWAqBWZNAHjRvVfGFf/xB6K2peEUjyNPbY+df/2d6D94/JR9CggQIECAAAECBAgQIECAAAECBAgQIECAAAECBKpToHvbwdj8u/fHnCsuihU/dEs0LpmXudFl776h3Ev4mZ/+60jrSgQuBIFZMbnX2o/dGdf81vtOCf72H+lOxnD/arz8h18T/L0Q3lb3SIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4jUDXC7vjxf/4D7H7c09FabCYqdG6fnHc/JcfjY5b12TKZQhUq0BFB4BztTVx1W++J1b/2B2n+B/6zsvx4i/9fRx7Zucp+xQQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhcWAKlQjH2fv57seHXvxA9e45kbr52TmNc99//WVyU9AiWCFS7QMUGgPONdcnY7B+MJckE3iNTOtfv9r94NLZ+8qFIJ/uWCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAwJ9Ow4FBt/9Qtx8LEtQ0XldT7peHjFL31/XPzDt2XKZQhUm0BFzgGcb6iN1yXfwmi/cVXGe/BEX2xJhnw+seVAplyGAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwJBAsX8wtv3vb0bvrsPlXr+5XG5oV1zyb94aNfW18UrS2VAiUI0CFdcDOB32+Zr/+oFTgr/9B4/Hpt/4kuBvNb6F7okAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMAUC+778XGz7k4dPmRd47cfuihUfunUKruiUBGZeoOICwFf+6rtiwRvXZ2R6dh6Ojf/5i9G792imXIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAWAKHHt0Sm//gq1HoHchUu+Rn3xZL3p6dijRTQYbALBWoqADwmh9/yykftJ6ka/6mT9wXA0d7ZimxZhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECMykQNfzu2Pz794f6dDQQykdFvqKX/7BmHfdiqEiawJVIVAxAeCFd10ea/7lmzOo/YdOlD+MhZ7+TLkMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbMROLFlfzLv74NRKhaHD8sncwFfm0xNWr9wznCZDQKzXaAiAsBNy9vjyv/0gxnLwRN9SfD3KzFwpDtTLkOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgXASOPr0jdvzlY5lD6+e3xtWfeG/kaioibJZpmwyBcxGY8Tc5/TClH6raOY3D7S8OFmLL7z8QvXvM+TuMYoMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOC8BTof2hR7vvC9zHnar18Zqz96R6ZMhsBsFZjxAPCqH31TzL1yWcZv5998N9Ju+BIBAgQIECBAgAABAgQIECBAgAABAgQIECBAgACByRbY8w9PxbHndmVOu+ojb4o5ly/NlMkQmI0CMxoAblm78JRvUxx+fGt0fn3DbLTUZgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVki8Mr/figzFWm+tiau/JV3GQp6ljw/zTyzwIwGgC/9t++MfF3NcOsGjvXE9r94dDhvgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBUCBSO98W2P3skc+rW9YtjxQdvyZTJEJhtAjMWAF781qui46bVGa8dSfC3cKIvUyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCoE0mGgD35rc+bUa378LVHX0ZIpkyEwmwRmJACcq8nH2o/dmXE6+uzOOPLU9kyZDAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGpFNj1t9+NwREdFGtbGmL1j90+lZd0bgJTKjAjAeCL3nV9NF88f/jGSoPF2PlX3x7O2yBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwHQKDyVDQez73dOZSy997YzQunZcpkyEwWwSmPwCcz8WqH3ljxqfz4U3Rt78rUyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDoEOh/cGH0HTsaq8nW1sfLDb5iOS7sGgUkXmPYA8OJ7roym5e3DN1IcGIw9X/jecN4GAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgekUKBWKsefz2V7AF/3A66KurXk6m+FaBCZFYNoDwCs+dGum4Yce3RKDR3syZTIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEplPg0Hdejv5DJ4YvWdNUH8veff1w3gaB2SIwrQHglnWLou3aFcM2pVIp9n3l+eG8DQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIzIlAoxf6vZuNWF737hhlpiosSOB+BaQ0ALxv1Iel6cU/07Tt2Pu13LAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFJETj4yOZIpy8dSs0rOqL95tVDWWsCs0Jg2gLAudp8LP0n12ZQOr+5KZOXIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBTAoXu/jjyxLbM5Q0DneGQmQUC0xYATr8dUTe3aZhkoKs3jj61fThvgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBMC3Q+lO3AuOCOSyNXWzPTzXJ9AhMWmLYA8II3rM806sgTW6NUKGbKZAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjMpMDxl/ZF/+ETw02obW6IttetGM7bIFDpAtMWAG67YVXG4thzuzJ5GQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKVIDA6jtU+Ks5VCW3UBgJnEpiWAHCuriZa1y8abkOpVIr02xMSAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUoTGB3HmnvVskprovYQOKPAtASAW9cvjvyIsdH79ndFOom2RIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDSBE68fCDTpDmXLc3kZQhUssC0BIDnXLokY9Cz/WAmL0OAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgUgT69h+LYt/gcHMaFs6Juo6W4bwNApUsMC0B4JZVCzIGPbuPZPIyBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpGoBTRuzcbz2pZOb9imqchBMYSmJYAcNPFHZk2pN+akAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUqkDvvmw8q+liAeBKfVbalRWozWanJte8YlQA+EDX1FxonLPmG+uirq056uY1vbpOtmvqa2PwRF8MHOuJwaM95XV/5/EoFYrjnM1uAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBahXoP3A8c2vNozo8ZnbKEKgggWkJADcunZe55f5pDADXtTdH+02ro+Pm1dG8MjsUdaZRIzKF3oE49uzOOPL09jiarIs9AyP22pwNAmmwvzn5Jk7z6gWRDkHeeFFb5PK50zZ90yfui8Gu3tPuU0iAAAECBAgQIECAAAECBAgQIECAAAECBAhcmAJ9ndkOjY1LsvGuC1PFXc8GgSkPAOeb6qK2tXHYojhYiMHjfcP5qdqYe/XyWPL2q6Nl3aLI5U4f+DvTtWuS4GEaNE6X0mAxDj66OXZ/9klBwjOBzXB5rq4m0l7mzUmgt3nV/HLAt2HxvDMGfE9p7hkCw6fUU0CAAAECBAgQIECAAAECBAgQIECAAAECBAhcMAL9h09k7rVh4ZxMXoZApQpMeQB49IdhIBlmeSpTTVN9LP/AzTH/tnWTcplcbT4WvOmSaL9hVez+3FNx4OsbIorJzN/SjAsseee10XbDymhKe/fWTMt01jN+zxpAgAABAgQIECBAgAABAgQIECBAgAABAgQITI/A4JFsTKthkQDw9Mi7yvkKTH0AeEH2wzB4pPt823zG4+dcvjRW/sgbo7695Yx1znVHTXN9rPjALdF+46rY/Lv3R7Fv8FxP5bhJEph39bJyz99JOp3TECBAgAABAgQIECBAgAABAgQIECBAgAABAgSGBQaOZmNaDaNiXsMVbRCoMIEp7zZZN68pc8sDUzT8czrU89p/dfeUBH9H3kDrusWx7qfujXzDlMfOR17WNgECBAgQIECAAAECBAgQIECAAAECBAgQIECAwDQKDJ7oi1Lp5KiwNa0NEaaVnMYn4FLnKjDtAeBC8mGZ7FTf0RJrfuLOyNfWTPapT3u+1iTYvO6n7olc/fRc77SNUEiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDB1Aknst9DTP3z+XC4XdXOzHR+Hd9ogUEECU96NtXbUB2GyA8BpT9y1P3l31M1pnFbWtCfwkrddHXs+9/Q5XTeXBKvr5jZG6pP2kk7nLi5098XAsd5k6YnBZCkNFs/p3OdyUOrYuGRepENd5xvqym0YOHQiBs5iyO702Lq25vJSmzyPYv9gpOfoP3g8Bqeo5/e53KtjCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQITESic6I/a5qTn72spjemcTexk6DhrAtMpMPUB4LQ7/Ig0OOKbEiOKz3lz0V1XRNPy9gkfnwZVj72wK45v2R/p5N3FwUISgG2O+vkt0Xzx/Ghdv3jC51p871XR+dCmCX/QGy9qi7bXXZwsK6N55fxxr3Pilc448tS2ZNkefXuPjlt/9Y+/JfJ1Y/RKToYp2PKHX0u+rnJyuILmVfNj2XtuijmXLjnt+Z/8sT89bXm5MBeJ15Jov2lVtF2/csxvvaRzJqf3cuAbG+NEYi8RIECAAAECBAgQIECAAAECBAgQIECAAAECBCpdoNB9sgdw2taalmzcq9Lbr30XpsCUB4BrGusysmkgcNJSMs76gjsundDpSoVi7L3vmdh//wtJT9vsh3XkCdLA7KJ7r0yCmqsj7co/Vkp7zV70rutj2588PFa1SOcnXvHBW6N5RceY9UbvbFm9INJl2btviBNbO2PHXz4W3cn6TKlx6bxoWtp2pt3l8sZFc6N3z6vB5GXvuykW3X3FuPd5uhPOSwLZKz5wS6TDb08kpVYdt64tL907DpXvZTIDwWlgvzcJkvfsOhw9O5MlXSfLxYn7vGtXTKSJ6hAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEMgKj41qj416ZyjIEKkRg+gPAybDAk5XSnrQTCUAOdPXGlt/76pjB06E2dW87GFs/+VAc37QvVnzo1nGDox23rokdn3osRv8ASM+Xfgtk2T+9Iea/cf245xm6/pnWLasWxKX/9p1Jj+ONsfszT2bGnB86pidp+7gB4KQXchoAXvz2q2PxPVcOHTrhdTpk9YofuiXab1w14WNGV0wD4et/5q2x4y8ejYOPbB69e8L53cnw27VJD/M04Nu7Lwlqj+jZPHSSk32dh0qsCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQITE0inuxyZapqyHR9H7rNNoFIEpjwAnE/mth2Ziv2Fkdnz2l74lsvGPb5ULMbW//XghIK/I0/W+eDGyNXmy71cR5aP3s7l85HOB3zs+V2ZXWnw99Kff3s0jtMjN3PQOJlc0uN54ZsvK/co3vSJ+6LYM5A5onv7wXIP20zhqEw6DPWc3oFyz+VRu8bNpvP6XvoL74iGhXPGrTtehXwyB/LKD78x6hfMiT3/8NR41U+7v+uF3actV0iAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAwBAeDJUHSO6RbIT/UF83XZS5SSOXcnK6XDI4+X0jlnuzbsGa/aafcfeODF8rDCp905orD1kuy8wbn6mlj7k3dNavB3xOWieXlHrP1/7iwHqEeWd287NDJ72u20h/BF/+S6s+6RPHRPkxH8Hdmwpd93bcy5bOnIItsECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgYoQKI6Ka+WSDm4SgUoXyEZnp6C1aQ/ZkalUnJxBedPeqPn68Tswpz15zyd1PrRp3MObLs7O7bvyn98WrWsXjXvc+VSYc+nS8lDMI8/Rk8ytWyqN7ZvObdxyDm27+EOvT+YjXjjycpO2ffEP3xbpHMESAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCSBEbHtXI12bhXJbVVWwgMCUx51O2UD0KhOHTt81rXL2gd9/jevUejd/eRceuNVaHzm5ui78CxsapEOm/wUGpYPDfab14zlB1znX5rpGfH4eh+5UD0dXZFw6K5SZB1QTQt6zild+/pTjT/DetjzxefiYFDJ8q7Cz390d95fFKGaB55vdQ6net4vFQaLMahb2+Jzm++FH37j0U6ZHVT0lt50T1XxNwrl53x8IZkGOgl77ymPLfxGSvZQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYboFRHRtHd3yc7ua4HoGJCEx5ADiSIODINE4H1ZFVx9xumD9+ADgNhp5vKibz5R59eseET7P43ivLgc/xDjiRBH03/7evRuFE3ylVa+c2xfp/fW8SPG0/Zd/IgjS4vvieK2PnX39nuDgNRp/NMM39R7ojHeq6Z9fh6D/QFfnG2qhrb4n6ZBns6i2fd9HdVyT3NPY3WtLgc3o/J7bsH25LujFwdFd5fuTF77g6lr3rhsy+kZmOW9YKAI8EsU2AAAECBAgQIECAAAECBAgQIECAAAECBAjMuMCpPYCzca8Zb6AGEDiNwNQHgEd/M2KSPhc1rQ2nuZ1s0eBpgqvZGpOby9Xmo+P168Y9adfGPbHl9x+IYt/gaesOHuuJTb91X6z7qXvGHXZ5/hvXx86/SQLAr4383LPzcLTfuOq05x1d2PnQxtj56cej2DOQ3bX1ZI/mdEfa03i8tO1PHzkl+DvymH1fejZaVi2IttetHFk8vF3f0RItaxbGiZcPDJfZIECAAAECBAgQIECAAAECBAgQIECAAAECBAjMpEA62unIVCqMPRXnyLq2CcyUwJQHgEd/MyImaWz0od6pY8Gl8wRPZ6pPhjLO1409+Xfq8fIffv2Mwd+h9ha6++OV//GNuOo33ztUdNp1TWNducfu0DDQxYHTB5VHH3zs+V2x/c8fHV18Sr6urTnSa4yXlr33xlj2nhvHrDZez+Q0cC0APCahnQQIECBAgAABAgQIECBAgAABAgQIECBAgMB0CowOABcnZ6rT6bwF17rwBKY+AFwoZFRHf1Mis/MsMhMZ3nm8gONELleb9DRuu2HVmFXTuYaPb9wbDROYl7hn9+FIg7sTSf3J3L59B5M5fccZ7jqdQ3coADyR86ZzD+/4v9+eSNUJDyedtuF8U3PSQ1giQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFSKwOi4VqkgAFwpz0Y7ziww5QHg4kD2g5DOWzsZKQ2MjpfSAHAaVOze2jle1TPun/+mS2LZu888d2164LEXdsfmNACcXG+8dGJzdo7cidQfNwC8sDWObxrvTCf3H9+wN/r2HTtZMMZW/QSC2mMcfla7auc1nVV9lQkQIECAAAECBAgQIECAAAECBAgQIECAAAECUymQq82O/FpKOtlJBCpdYHKisWPcZbE3O79svn5yYs6F431R6Mue+3TNWPiWy05XPOGyBckcu+Ol45v3vVollx0H/rTHjZoT+bR1RhSWJjKUwESuO+KcffsnFvxNDzllCO8R55nszToB4MkmdT4CBAgQIECAAAECBAgQIECAAAECBAgQIEDgPATy9dkAcKF3YlNxnsclHUrgvAWmPABcGB0AbpicAHB658c3vRZ4HYNh/m3rkiGcV45R48y7Ft1zZTQsmnvmCq/tGWpHf2fXuHVb1i0at87ICi1rx68/keGwR56z98D47Ryq338WdYeOOdd1TUNd5Cfx/TjXdjiOAAECBAgQIECAAAECBAgQIECAAAECBAgQIJAKjO7YWOiZ2DSf9AjMpMDkRWPPcBejPwijPyhnOGxCxQe+9mLMu3r5uHVXfviNURwoxLFndo5bd6hC2nN4+ftuGsqecZ3Op3vi5QPl/X0TCJY2Le+IfGNdjO4ZfboLpEMiN04gAD2R6448/8Dh7pHZMbfP5tyHvv3ymOcab2exf7D8nMarZz8BAgQIECBAgAABAgQIECBAgAABAgQIECBAYDoEakZ1XJtIfGc62uUaBMYSmPoA8InsNyFqmuvHas9Z7Tv23K7oTYYzHi9IWpMEXNf95N3R+c1Nse8fnxtz/tvWy5bEoruvjLZrV0yoLZ0PbYpSElxOU1/n8SgNFiNXe+aO1elk4as/eke8/EdfHz7udBdKe8Ku/sjtp9uVKUuDpv2HTmTKxs1MZFjp104y2NUbg8d7o7a1cczTpj299973TPTuOjJmvdPtbFg8Nxbcfmly7OGIsxwi+3TnU0aAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAyBmqZsXGswmaJUIlDpAlMeAB441pMxqJ3EAHB64gNf3xAr3n9z5hpnyix40yWRLt3bDsaJLfuj/2h3NMxvjULPQNR1tETT8vZoWtp2psNPKR/s7os9n3t6uDwNBB/6zsuRDjs9Vkp7La//qXtj8+9/9bQ9gdMg+bqfuidaVi8c6zTlfQe/tTmZqLc0br3zqdD54KZY8s5rxjxFGmS/7Be/L3Z95snoTJ5JqVAcs34kgfB5SZB94ZsvizmXL41cMo/x3i89M/Yx9hIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEplGgpqUhc7WBpOOcRKDSBaY+AJwEWUem0R+UkfvOZTsNNrZfvzJa1y+e8OHNK+dHupxv2vuF70XhRPabHmkP447Xry0HNMc6f+sli+Pq33pfORjd/cqBKPQNRk1TXbSsWhhNKzsinQ93vFRKevLu+8rz41U77/37H3ghFt1zxSnj3I8+cb6uthyMv+j7r4ujyXDbx1/aF+kXANJhwOuSHsT1C+dEw4LW8rppWXvUzW0afQp5AgQIECBAgAABAgQIECBAgAABAgQIECBAgEDFCJzSA/hotuNjxTRUQwiMEJiGAHD2gzDeUMIj2jahzbSn6ct/+LW4NOl92rBgzoSOmYxKR763I/YncxCPTr27j8SRJ7dF+w2rRu86JZ/2mp1z6ZLycsrOCRSkc+72T2De4Qmcaswq6TDQaU/rxW+9asx6QzvTH4Ydt6wpL0Nl1gQIECBAgAABAgQIECBAgAABAgQIECBAgACB2SSQdmpMp/YcSoNJp8BxR0AdqmxNYAYFzjxZ7SQ1qj+ZF3dkqps3+b0+0/HWt/zBA5HOQzsdKQ3+vpLM4RuF0w+9vO1PHo7u7QentCnpENbb/+LRKb3GyJPv+swTcTS5b4kAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcCEIjI5pjY55XQgG7nF2Ckx5ALhvVA/VurbJDwCn9L27jsSm37ovenYdntInceSpbeXg71jf8Cgmwzlv/t37o2//sSlpS++eI8n8wQ9Eqb8wJec/7UmLpXj5f34jjieBZ4kAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUO0CowPAo2Ne1X7/7m/2Ckx5ALjQ3R+D3SfnyU3nia1prp8SsZ7th2LDr3w+9n7pmUjnx53M1H/oRLz8P76RDDf99Ql170+HTd74m/fFoe+8PJnNiIPf2hwbP3HfKXMPT+pFznCy0kAhNv/OV2L//c9Pqm/6juz98rOnHVL7DE1RTIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYUoG69pbM+fsOTE3Hv8xFZAhMgsCUzwGctrFv77GoXbNwuLkNC+dE97apGSI57Zm7+7NPRtpTd/Fbr4551yyPfP253+bg8WT+229siL33PXvWPW4Hj/XE1k8+FAcffilWfPDWaFwyb9jgbDd6krmFd/zlo3F8076zPXRS66e9m3f+zXcjnX94xYdeHy2rF5zz+dOg+v4HXojOhzZFcZqG7z7nxjqQAAECBAgQIECAAAECBAgQIECAAAECBAgQuKAEGha2Zu63d8/RTF6GQKUKnHtk9CzuqDvpmdsyTQHgoWZ1bz0YryRDFucbamPetSui/eY1MeeyJVHTUDdU5YzrtAv/0ae3x5Gnd8Txl5KAa+n0c/2e8QSjdnS9uCde+A+fjeZV86PtdSuT5eJoXNqWqZUGrnM12Q7Z6XDWR55K2pEEs9PezRNJ6X13bdwzZtV0zuTzTWkAf+OvfyEaL2qL9htWRdsNK6NpWfu4p+0/eDxObO0szydc7h19hnmUxz3RBCt0vbg7ahrP/JoXk2G0C5PgMcHmqEaAAAECBAgQIECAAAECBAgQIECAAAECBAjMEoGGBXMyLU3jXRKB2SBw5sjYJLa+e0e2t2/DormTePaxT5X2WD38nVfKS1oz31gXdW3NkY7bnq5rkgDx4Im+GDjaE2mP3XSdHjMVKQ3OpkvaQzkdBrtublPUpu1I1qVkjt1cPle+/kDSjsGkHYWe/rNuxvFNe+Ol39571sed6wG9Sc/kPbufjj2ffzpqmpJ7Su6nNpnnuW7eq7aFpGdvOsRzuqSB9XRo7OlMBx54MdJFIkCAAAECBAgQIECAAAECBAgQIECAAAECBAicjcDoeFbPDgHgs/FTd+YEpicAPGq457TX6EyldKjhvr1Hy8tMtSG97lBQNJK2VEtKA9bloHUV3VO1PBv3QYAAAQIECBAgQIAAAQIECBAgQIAAAQIECJydwOh41olR8a6zO5vaBKZPIDvm8BRdt2tDtkdq04qOKbqS0xIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4P4H6hXOSKSZPTivaf+hE9CcjnUoEZoPAtASA03l0S8XisEfjknnloZiHC2wQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqBCBltULMi3p2rAnk5chUMkC0xIAToddPrHlwLBDOtdt67pFw3kbBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpFoHX94kxTjr2wO5OXIVDJAtMSAE4BDj+5LeMw96plmbwMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUoQmHtlNo51+ImtldAsbSAwIYFpCwAffGRzpkFt16+MyOUyZTIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZlKgedX8aEjmAB5Khb6BOPJEtqPj0D5rApUoMG0B4EOPbonB7r5hg/r2lph3dfbbE8M7bRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYAYEFt1+auerBhzdHsW8wUyZDoJIFpi0AXOwfjH33PZuxmD/qA5TZKUOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgGgXyDbXRftPqzBV3//2TmbwMgUoXmLYAcAqx89NPZDzSHsB1HS2ZMhkCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECMyHQcevaqGmsG750776j0fnwS8N5GwRmg8C0BoC7XtgdXRv2DLvk8vlYfPcVw3kbBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGZEIBex6J4rM5fe/dmnIoqlTJkMgUoXmNYAcIqx4/9+O2My/02XRE1zfaZMhgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMB0CrRdvzIaF88dvmRxYDAZ3fbx4bwNArNFYNoDwHu+8Ez07T827JN2o1/y9quH8zYIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITKtA0vt36fe/LnPJvV98JvoPdGXKZAjMBoFpDwCXBgux7f98K2Oz8M7Lo669OVMmQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGA6BDpevy6aLmobvlSpUIytf/LIcN4GgdkkMO0B4BRn519/N9JJs4dSvr42lr/3pqGsNQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFpEcgno9Uue/f1mWvt+fzT0b21M1MmQ2C2CMxIALjYPxgv/9E3MkbtN62OOZcvzZTJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJhKgYt+8HVRN+/kSLWFvoFT4lhTeX3nJjDZAjMSAE5vYvffPxXHnt+VuZ+L/8VtkW+ozZTJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJgKgZZ1i2LhWy7PnHrb//dw9O49OZJtZqcMgVkgMGMB4CiVYsOvfSFKxeIwU8OCObH8/TcP520QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmAqBtFPiqh95Y+TyueHTd+88FFuTALBEYDYLzFwAOFE79vzu2P7nj2b8Frzpkmi/eXWmTIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAZAqkI9M2LJo7fMpS0nnxxV/6h0inMpUIzGaBGQ0Ap3Bb/uBrceLlAxnD9APXtKw9UyZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDIEFt51eXTcvCZzqh2f+nYcfnxrpkyGwGwUmPEAcPotimd/7m+j0Dsw7FfTUBdrf+qeqOtoGS6zQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOB8BdquXxnL35edkrRr497Y/Lv3n++pHU+gIgRmPACcKhx/aV9s/I0vZUDq25pjfRIErmmuz5TLECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEDgXgdb1i2PVR27PzPs7eLw3nvnpvzb087mAOqYiBSoiAJzK7P7sk7Hjr76dQWpc2hZrf/LuyNXVZMplCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJyNQONFbbHmY3dGfkTcqVQoxrM//+no2XHobE6lLoGKFqiYAHCqtPE374vOh1/KgLWuWxTr//W9egJnVGQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQmKtC8akFc8jNvi9rmhswhm377y3FwVGwqU0GGwCwUqKgAcBRL8ezP/E0cfWZHhjLtjn/Jz7096tqbM+UyBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMYSmHvVslj/M2+N2jmNmWqv/PFDseNT2dFpMxVkCMxSgcoKACeIhZ7+eOon/iK6NuzJkDYta49Lf+GdkXbPlwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMJ9Bx27pY+7G7oqahLlN1+6ceiy2//0CmTIZAtQhUXAA4hR3s6o0nPvKnSU/gnRnn+o6WuPTn3xFtr7s4Uy5DgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYFggn4tl770xVv3IGyNXkw2HbfuzR2JTMi2pRKBaBbJvfAXdZRoEfvKjfxYHH9uSaVVNc32s+Yk7Y/kHbo7ciEm6M5VkCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIELkiB+gWtccnPvj0W33vVKfe/5Q8eiJf+61dOKVdAoJoEKjYAnCKnw0E/nQwHvevvHj/FfNFdV8TlH//+aF6z8JR9CggQIECAAAECBAgQIECAAAECBAgQIECAAAECBC48gQW3XxKX/9IPROu6RZmbL/YPxnO/8Ol45ZMPZcplCFSjQG2l31SpUIwXf/nz0bVpX1ySTNCdrzvZ5MYl85J5gd8RB7+5KXZ95skonOir9NvRPgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUkWaFrRESs+dGu0rs0GftPL9O45Es/87N/EsWd3TfJVnY5AZQqcjKZWZvuGW7Xzr76TfDB3xtWfeF80LW8fLs/lcrHg9kuj7cZVse/Lz8X+B16IUn9heL8NAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB6hSon98aS7//uui4dW3kknl/R6fOhzbF8//+MzFwtGf0LnkCVSswawLA6RM49vzueOw9fxjrf/reWP7emzIPpba5IZa9+4ZYdPcV5SBw5zc2RqG7P1NHhgABAgQIECBAgAABAgQIECBAgAABAgQIECBAYPYLpKPELnrrVUngd03ka2tOuaHBZNTYTb/15dj92SdP2aeAQLULzKoAcPow0nmBN/zqF2LfV56Py/7dO6NldXYO4Lq5TbHsXTfEkndcE4e/80qk3+zo3tpZ7c/R/REgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEqlogV5OPedetKI8MO+fypZGOEnu6tP+BF2PTJ+6L3r1HT7dbGYGqF5h1AeChJ5IGd9PewOl47qs/cnukgd+RqaahLha86ZLy0rv/WBx5YlsceWpbEgw+GFEqjaxqm8CsFVj0+LYYbKqbte2vtobX9g5WxC0tSX4+DjZ6LyriYSSNyFfItARLHnslCvWnfhOyUpwutHbkB4sVcctLH305irX5imiLRkTkCpXx/6hLv7UlSqcZMsszmhmBXLFC3ouHN88MgKtWrED6bi71XlTM86mUnxXpn2Xei4p5LaJS/p8zbYf3onLei5oK+R01/V3Ze1E570Vt70BFNCb9uzXvRUU8inIjansq471IG5NvqI05ly2NtutXloO/6YiwZ0rHX9oXL/3OV+LgI36HOZOR8gtDIHf/NR+vjL9ROA/v2jmNsfLDb4gVH7g5alsbxzxTOiz0iZcPxIltndG760j07jsafQe6olhBP8zGvAE7CRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJVKFA7rykaFs6JxqVt0bS8PRkFdkE0r5gfuXG+wN697WC8/L8ejL1ffEYnwCp8L9zS2QtURQB46LZrW5N5gN9zY6z44C3RuHjeUPGE1oXkW04DR7pjsKs3Bo8nSxIoLiZLoW8gin2Dry4DhSgmS2kwXYpRKiRLuk6++VwqvrqO9Bv6SQ/jtKzc07i8GhFjH+p9PKJoQg1UiQABAgQIECBAgAABAuMI+DVjHCC7CRAgQIAAAQIECBAYV+CUQZXTgqGhlpPtXPJPpCNHpf+m5cmSS/M1yTqXj1y6ToZqToO2uZqayNfVRC5Z0nW+sTZq6usin4xsWdNcH7XpknTyq01Gea1Lgr+nm8t3rAYf+d6O2P5/Hon9D2wQ+B0Lyr4LTqCqAsDDTy/5QbPgDevionffEAveuD7y9bN2pOvhW7JBgAABAgQIECBAgAABAgQIECBAgAABAgQIELjQBfoPHo+9//hc7P67J+L45v0XOof7J3BageqMjCa9bzu/+VJ5Sb9BsvCOS2PhnZdH+82ro76t+bQQCgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpPIB3i+eC3Nsf+r74Qh5/cFuXRWCuvmVpEoGIEqrMH8Bi8zcl48fOuWh6tlyyOljULk7HjO5Kx5OfpJTyGmV0ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgakWSKfp7Nl1OLp3HIoTSe/ero174+izO6O/8/hUX9r5CVSVQHX2AB7jEXW/0hnpMjrVtTdH/fzWqO9oibpkrPnymPPJuPPlMeib6svj0adDSdc01CZj1de+OmZ9Mn59eez6dCz78pKMcZ9Ptstj37825n15+Pvyf1695FB+dAPkCRAgQIAAAQIECBAgcD4Cye8aEgECBAgQIECAAAECBCZFoHTyLKXSa5l0lWyX88l2KRmNtZwvFF/dTtbFdDtdBpPtgUKyLkSxbzCK/YNR6B2IYrIUuvtj8ESyHO+NwWM90X+kOwYOd0ffga7yvpNXtkWAwLkKXHAB4DNBpT9c0uXEmSooJ0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQIUL5Cu8fZpHgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAhMUEACeIJRqBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqHQBAeBKf0LaR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQkKCABPEEo1AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVLqAAHClPyHtI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwAQFBIAnCKUaAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKl1AALjSn5D2ESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYIICAsAThFKNAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEClS4gAFzpT0j7CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMEEBAeAJQqlGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBShcQAK70J6R9BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmKCAAPAEoVQjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBApQsIAFf6E9I+AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITFCgdoL1LuxquVzkG2ujpr428g11ka+riVyylNe1+cjVjFjyuYhkySXHlNdpPk1JPi0qp+GNtPy1MisCBAgQIECAAAECBAicj0DpfA52LAECBAgQIECAAAECBE4jUHr1F43yang7KSuWopQskZSV18l2cbCYlBejVChGcaAQpSSfrov9g1Hse21JtiUCBKZemXlEGgAAQABJREFU4IINAKcB3OaV86N5RUc0Lm2LxsVzo35+S9R3tEbtvKaom9MYtclS01SXLPVT/yRcgQABAgQIECBAgAABAgQIECBAgAABAgQIECBQxQKlJEBc6BmIwom+GOjqjcFkGTjSHf2HTkTfga7o23csenYdju7th6J395EqlnBrBKZW4IIJADde1BYdt6yJttddHHOvWhYtqxaUe+5OLa+zEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIpAK5fD5qWxrKS8OiuWOiFLr7o+ulfXH0mR1x5Iltcfi7r8Tg8b4xj7GTAIFXBXL3X/Pxqh0oLO3hu/jeK2PRPVfGnEuXeOYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKzUCAdTvrQt1+O/fc/H/sfeLHce3gW3oYmE5gWgaoLAOdqa2Lx266KZe++PtpvWDUpiKV0DPv+ZJz6wWRJx61Pl2QM+3T8+vI6HdM+Heu+kNQrpWPcp8Pevzb2fXn9WjPS7TSNCLmP2Hx1n/8SIECAAAECBAgQIEDgHARy53CMQwgQIECAAAECBAgQIDCmwNAvGrnXNpJVLvkn8uWNyKXlyZKrSZZ0uyaf9PJN88k6idfkavORT6bkzKfb9a+ux7zeBHcW+gZi/1eej52ffjyOPr1jgkepRuDCEaiaAHBNMmTA8vfdFBd/6NZoWDhnQk8wHVO+d+/R6O/sSsaX707GmT/x6njzyRAC6dAChZ7+KPYOlCcnn9AJVSJAgAABAgQIECBAgAABAgQIECBAgAABAgQIEDi9QBIczjfURk1TfbLUvTocdGtj1M5tjPq2lqib31KO8TQunRe1zQ2nP8eo0qPP7Iytf/pwHEh6BUsECLwqMOsDwPn62lj+QzfH6h99U9TNaz7jc00nFj/+0v7oenFPHN+yL7q3HYxiMtG4RGC2C+hFXjlPMPl+W8Uk70XFPIr0+5AVk7wXFfMovBeV8ygqqiV+XlTU46iYxlTKe+HPkIp5JcoN8V5U1vOohNZUyjuRWvh5UQlvxKtt8F5UzrOopJZ4LyrpaVROW7wXlfMsKqkllfBe1LU3R8vqhdF6yeKYe+WyaFwyb0yiro17Y/PvfTUOPvzSmPXsJHAhCMzqAPCiuy+PS3727WN+6NMPfDom/NGntpkc/EJ4oy+we3zw3+Wjp6MS/ii+wODPcLu3/1ohmg+fYec0Fn/9P+Sjb573YhrJx7zUm3+5EI3HxqwyLTsf+E/5GGjxXkwL9gQucufHC1HfPYGKU1zl/l/NR6HRezHFzBM+/d2/WIjavglXn7KK//gb+SjVei+mDPgsT3zvzxciXzjLg6ag+pd/u2YKzuqU5yrwtp+Z+ZeimLwSX/lN78W5PsPJPi43WIq3/kIyH9UMp8Gkk85Xf817McOPYfjyNb2luOffz/x70Z/01/jaL3svhh/MDG/UnSjFXb808+9F79yIb3zcezHDr8Pw5RuOluItvzLz70V3e8RDv+i9GH4wM7zRdKgUd/z6zL8XIxkaL2qLthtWxvzXrxtzJNg0JrThP38xul/pHHm4bQIXlEDtbLzb9Fsel3/8+2P+G9adtvmFZNjmg9/cFAce3Bh9+yrgb91P20qFBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECExHo3X0k9qbL578Xcy5fGgvvuiLmXbP81bmHR5yg45Y1cevf/kRs+7NH4uU/+kaUBmf+C5QjmmeTwLQIzLoA8NIfeF1c+nNvi9pkTPjRKZ23d99XnosDX9tQnr939H55AgQIECBAgAABAgQIECBAgAABAgQIECBAgACB2S2QTveZLulcwUveeW2037Q6csn8wkMpX1cTqz9yeyy849J4/t9/Jro27B3aZU3gghCYNQHgfDIZ+BVJr98l77jmlAdTGizG/q+9EHu/+EykQWCJAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgugV69xyNrX/8UOy779lY9t4by3MFj7zj1vWL46Y//7HY9Ftfjp1/892Ru2wTqGqBWREAblrREdf93gejZc3CUx5G14Y9seMvH4vevUdP2aeAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgugV6dh2Ozb97f7RdvzKWv//mqO9oGb7hfH1tXPaL3xfzrlsRL/7Hz0Wxf3B4nw0C1SpQ8QHg9MN6ze98IOrbmjPPoNA3ELs+/Xh0fmNjplyGAAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgwhM48uS2OPbi7liRBIHnv2F9BmBpMlR00/KO+N7/+6kYONyd2SdDoNoE8pV8Qwvfcllc/z//xSnB3+6dh2LDr3xe8LeSH562ESBAgAABAgQIECBAgAABAgQIECBAgAABAgSmWaDYMxDb/vSRePl/fCMKPdlpQ9uuXRE3/Z+PlOcOnuZmuRyBaRWo2ADwkrdfHVf/9vsi7Zo/Mh16bEts/PUvRt++YyOLbRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoCxx5Ymts+NXPR++eIxmR5ovnx41/+qPRdHFHplyGQDUJVGQAeNHdV8SVv/buyNfWZKz3fvnZ2Pq/vxmlgUKmXIYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDASIG+/V2x8Te+FMe37B9ZHI1L5sUNf/xhPYEzKjLVJFBxAeCO29bGVb/xnsjVnGxaqVSKHX/17dj9d09Uk717IUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQmEKBQnd/vPRf/jGOfG9H5iqNi+fF9Z/8cNR3tGTKZQhUg8DJKGsF3E3rukVxzW+/P/J1J3v+lorF2PrJh+LAAy9WQAs1gQABAgQIECBAgAABAgQIECBAgAABAgQIECBAYDYJpCPLvvzfvxYHH3kp0+zmFR1x7X/7YOQbstORZirJEJiFAhUTAK5rb47r/uBDUdvSkGHc/hePxeHvvpIpkyFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwYYFktNltf/atOPLU9swh865ZHlf88g9mymQIzHaByggA53Jx1X9+TzLWelvGc/fnnoqD39yUKZMhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcNYCSRD4lU8+GMc378scuuRtV8eKD96aKZMhMJsFKiIAvPqjt8f816/NOHY+tDH2fv57mTIZAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAucqkA4HveX3H4iePUcyp1j/b+6NuVdelCmTITBbBWY8ADzn8qWx+qN3ZPy6Nu6JdOhniQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBkChS6+2PL7301Brv7hk+br6uJK3/9n5oPeFjExmwWmNEAcK42+TD92rsjn6yH0sCxnnjlfz0UkXTDlwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMtkB/5/HY9icPZ07bsmpBrP3JuzJlMgRmo8CMBoBX/vBt0bp2UcYt/bANJkFgiQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBUCRx9ekcceHBj5vQXJ3MBt166JFMmQ2C2CcxYALhx6bxY/WO3Z7w6v7kpjj23K1MmQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGAqBHb97Xej70DX8KlzNfm47N+9czhvg8BsFJixAPDaj90VNU31w2YDXb2x69OPD+dtECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJhKgWLfYOz41GOZS7Rdd3EsuufKTJkMgdkkMCMB4NZ1i2LJO67OOO3+u8cjnXRbIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBdAunotEee2p653NqP3RmRz2XKZAjMFoEZCQCv/pdviVz+5KW7dx6Kg9/aPFvMtJMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCKBHZ9+rtRKhSH76hl1YJY+s5rhvM2CMwmgZNR2GlqddPFHbHorssyV9v92ScjSpkiGQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLTItC3vysOPvJS5lorf/gNmbwMgdkiMO0B4JX/7PXZ3r/bD8axZ3bOFi/tJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqEKBvV96NkrFk72AW9cvjvlvWFeFd+qWql1gWgPA+aa6WPJ912ZM9335uUxehgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMB0C/QfPB6Hv7s1c9ll770pk5chMBsEpjUAvORtV0dtS8OwS/+R7jj8+NbhvA0CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECMyWw/4EXMpde8Kb1Ub+gNVMmQ6DSBaY1ALzsn96Q8Tj4cDKWesnkvxkUGQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRkR6H6lM7p3Hhq+dr62Ji76weuH8zYIzAaBaQsANy1vj3lXLx82KRVLUQ4AD5fYIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDCzAgcf2pRpwJJ3XJ3JyxCodIFpCwAvuOPSjMXxjXsjHUtdIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFApAoe+/XKUBovDzWlduyialrUP520QqHSBaQsAd9y8JmNx5OntmbwMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZkWKHT3R9dLezPNaL95dSYvQ6CSBaYtADzvuhUZh64NezJ5GQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKVIND1YjaO1fa6iyuhWdpAYEIC0xIAblwyL+rbmocbNNjdF727jwznbRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoFIETW/ZnmjLnsqWZvAyBShaYlgBw66VLMgY92w9l8jIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKkWge9vBKJVKw81pWbMwcrU1w3kbBCpZYHoCwOsXZwx6dh3O5GUIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVIpAsW8w+g8eH25Ovq4mWlbNH87bIFDJAtMSAG6+uCNj0LvnaCYvQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCSBHr3ZuNZTaPiXZXUVm0hMFJgegLAK7IB4L7OrpFtmPLtXH1N5Otrp/w6LlCZAvnGusjVTMurXpkAWkWAAAECBAgQIECAAAECBAgQIECAAAECBAictUD//mw8q3mFHsBnjeiAGRGYlqho0/L2zM2N/sBkdp5Hpq69OdpvXB1pj+O6ec1R19aULM1R01RfPmuhbyAGj/XGwNGeZOmO4y/ti6NP78h04T+Pyzt0JgVyEc0r58fcq5ZH67pFUTsvefZzGqO2tXE4+Fvo6Y/BruT5J0v31s449tyu6Nq0N0r9hZlsuWsTIECAAAECBAgQIECAAAECBAgQIECAAAECFSgwukPj6HhXBTZZkwiUBaY+AJzPRf381mHudMLs/kMnhvPnu1Hb2hBtN62OjptXR8vaRZHLJZHAM6SahrqoWVgXDQvnlGu037AqVnzglujecSiOPLUtDjzwYhS6+89wtOJKFEiD/kveeW20Xb+yHPAdq43pFwHSpWHR3GhN3pVFd10RxYFCHHlyW+z++yejv/PkWP5jncc+AgQIECBAgAABAgQIECBAgAABAgQIECBAoPoF+g9m41lpfEEiMBsEpjwAXN/RMtwDMwUpnOiLUqE4KTbzb1sXy99/c9Q0v9rD91xP2pwMUZ0ui+68PHZ/9sno/OamiNK5ns1x0yGQBnIXv/3qWHT35ZGvO/fXOJ20veOWNZF+GeDAgxvKzz+d2F0iQIAAAQIECBAgQIAAAQIECBAgQIAAAQIELmyBgSPdGYCGRa92MMwUyhCoQIFzj5xN8GaGetsOVR840jO0ec7rumR434v/xW0x75oV53yO0x2YDhd88T+/LRbccWls/eOHondPdnLv0x2jbPoFGhbPjfX/5q2RfrlgslKuNl/uEdy8ckFs/m/3R7F3YLJO7TwECBAgQIAAAQIECBAgQIAAAQIECBAgQIDALBRIpxQdmUbHvEbus02gkgTyU92Y0UG6gWPZD8vZXj8dX/3y//SDkx78HdmO5ovnx/qfeVs0XtQ2sth2BQg0JT21L/m5t09q8HfkbaXzB6fB5XzDlH83YuRlbRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVJjA6AFzX1lxhLdQcAqcXmPIAcN3cpsyV0yGgzzXVzmmMNR+7K2pbGs71FBM+Lm33+p9+azQunTfhY1ScWoF0vt/1P/PWGP1OTfZVW1YviMVvvWqyT+t8BAgQIECAAAECBAgQIECAAAECBAgQIECAwCwSKA0Woth/ctrIdFrJdIpKiUClC0x5ALh2VAB48BwDwOkQvWt+4s5omN86baZpoHGd3qDT5j3ehZa958aobT774H+pePYTOi+658pIv3AgESBAgAABAgQIECBAgAABAgQIECBAgAABAheuwGB3f+bm02lKJQKVLjDl49zWzc0G0QqjPigTBbro3TdEOjzv2aRSsRgDx3pjMB2jPZ8rDxt8tr2H65Pu/Evefk3s/vsnz+bSUb9wTrRdtyLpQdwW6Q+DNBCeBpTTQPZgV9KmpF3pcNj9h07Esed2xfGX9kWUxg9U1jTXRzpE9VgpPX/PrsOZKrnkWynp3MZp79bGJfOivr0l0h9aA8n1jz67M/bf/3ym/imZXCT+i2PuNcujPgnC189rjtq25L6Sb7oMHE/u5eCJ5F6OR+/eo3Ho268k93d+Q32Pvn7L2kXRcfOa0cWnzadt2PePz8WJVw5Ef9KudD7f1K1h0dxYcPsl0XHr2ki/pTNWqmmsi/Zb1sSBr74wVjX7CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSoWKI9sO2Lo53LnsSQOIRGoZIEpDwCP7gpfSIJxZ5vyTXXlwN1EjzuxZX90PvxSHHlyW4wOOKdzu869clksvvfKSIOKE0mL7r0iDjy0sRwsHat+2s5Fd10RbTesjOblHWesWh7CeNnJ3UvefnU5KHzkmR3R+fUN0b3t4Mmdo7YaFs8tD009qjiTTQOfG3/9i8NlaSBzWRJAHz0fc/pDqjE5Xzp8wZkCwHUdLWWr9htWxZnGtk/P05QEuofSsnffGIef2hYHHngx0mcxGWnR3VdM6DQ7P/147P9KEsweFUxP34PurZ2xPVk6H9wY63/2bVHTUDfmOZsM/z2mj50ECBAgQIAAAQIECBAgQIAAAQIECBAgQKDaBdJOZiNT2uFMIlDpAlMeAE6DoiPTyLHSR5aPtT3/DevHDdalxxcHBmPX3z1RDjye6XzFvsFyYDgNDs+5bGms/vE3jzuscL6uNpa+85rY/uePnum00X7z6lj+/pvPeX7aNIi6ILnP+a9fFwe+saHc47jYk/2hkl68d9eRSIc0ziU9ms+U0l7HQ2n+G9fHyh9+w1B24uvk9AvffFmkPa/T3rBnk9Jezh03rS4ve77wdOz5h6fP5vDT1m1Zs/C05SML9ye9dfcnPX/HS2mAffdnnowVP3TLmFUbl5x0HLOinQQIECBAgAABAgQIECBAgAABAgQIECBAgEBVChRGzAGc3uDZxkyqEsVNVbzAlM8BPPqDkAZgzzYtfMtl4x5SSnp8vvI/Hxwz+Dv6JF0b9sTm37k/Cj3Z8dtH10vzc5Jew6dL6dDKa//V3bH6x+445+DvyPP+/+zdB5xcZ3no/2f69t6kreqSLcmSJVtyEy6AMaaEDgZCCSQ3CVzSLqRyk3/uJ+0GbnIhlAAJkHAJEBwDtnHvVbYsWc1qK2mbtvfd2Z3+f9+RZzRntszMamfmzOzv/XA45z3nPee853tmFuxn3ufVgd26W7fIlf/fu6RIpWuOLzqAPtu/eGoBba5H7pZesVpaPnJd/CUS1vUo6Q1/8BZpvmvvZf8hW/W2HbL2N28Rq3PpvzXQKbTjRy/HP0RQTcSeSppud8dQ/CXm1K0FS+/znIuxAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJOIOgNGPpsTXHQnOFkKghkSCDtAWAdTIwtQZ/xixJ7bL7totZqKVBztyYqes7X8Ve7EjWbczycFniRkb2RE1xq3lsdVDUUi0XW/MbNUr6tybB7OSo63fJ6FVjWKZ/jy8wiKaIjbQubKqXlw3vFYkvxFasAtA7Ylm5siFzqstcVV7dKy8eXMAr59TsXqGfRAf7FlqlT/ZLKjwsKF0nRHXlg7/BUZJM1AggggAACCCCAAAIIIIAAAggggAACCCCAAAIIrECBUNwI4Pi41wok4ZFzQMAYnU1Dh+cEIAPBlO7irClN2F6P/tQB4KWW0VfOS9NE4vTNpRvqZeTFs9HbtHz0Oqm4qjlaX+4Ne0mBrP/dN8vJv75P/OMz0cu7O0ekau+6aH2+jdXv2CGuJALn8efqEcN6juTlLjol9NhL52TsYGfKl548dkEO/vr3Uj5vwRNU4L7qusX99Lmz/RMLXoIDCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkP8CelrO2GJNdeBd7MlsI5AhgYwHgPUozlSKs6YkYfPxQ10SmPIkbLdgg0BI+u47LBW7WhdsIqrbsQHB4nV1UnPTxoXbL9MRPfJYB3Nj5x92dw4nvHpR69z00YlO0imnk30m75hbJo/1hOcjDqmgfokaMVy4evE5c5tVcHnyZJ8E3IlTbifq65KPqxHOLb96vZSo95eojDzfnqgJxxFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCPBXQMJLZY7ClmXo09mW0EMiSQ+QCwCramUnQANFFxJ5ESOdE1Bh97TfSSbKl/y9akmnpHpqX35wdl+tyQzPaOiQ4k28sKpVgFW6tv2CAVO1sSXqfquvVqftuD4p+cDbedUSOAUy068O4ZnJTZnjF1nRmxl+p5dYvEUVksEb/62xM/k/5D1/3jl2ToyZMS/0evcnebtH7ixgXn+3Wo5666fr0MPnI81e4vS3u7mkt4zaf3SemmVQmvN364S2YvqPdFQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgRUrMGdgo5UA8Ir9MOTQg6c9AKwDnoZiMdQSVubMuzvPGb5x9zx707fL1VAu5UmkftYjhk9/+UHxqSBwbPFPzITnK9ZBxpaPXp9w1K3VYZO6265QQeBXwpcJzHjDwVxXbeL02PqEme5R6fj+s+JWQeiFih5pXbGzdaHD0f3nvv2UjL18PlqP3RhV+wOzPln/uTfF7jZs6yBxNgLA1Srw3Pj+a8Re7DL0Z76KT41u7vz+c/MdYh8CCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACphZIewA4FIwbGq9S8KZS4keZzneuJcVrzneNVPaVrK8Ti5pHdrGig4in/vb+6Kjdeduq4LgONOoAb6I5fUvU/MOxxTfqlmQCwOOvdkn71x8TSTDyunhtrSTj6CgtkNpbNsd2Zc52yB+UhVIg6Ps4KotE9z8TpbCpUpo+tEdKVYrqZErQ45f2rz0mvpg5l5M5jzYIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQfwLxsZNk4lb5p8AT5ZpA+gPA8bnREwRO4wG9w1Pxu+bUdRrjTBZXXeKRtxPHLywe/I3p8PAL7QkDwM4k7hlzyfBm0OuXrv/3QsLgr26cTDBZt2u+a69eLbnowHnZ1iYZfvrUkq+RzIm2EpesfudOqdm3UQW2k0vHoNN1t3/1UZnpSj3FdjJ9og0CCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjklsCcGENc3Cu3noberhSBjAeAxZZcMC7yArxDiQPAenRnn7waOWVJax3YrL5h/aLndv3H/nDg0lVbtmg7fXDqdH/CNpEG02cGRI+UnvNHJNJArR1q/lqLGikc8gVi9i6+qec01kHNZEqyAeBkrpWojZ57OF3Foj5ftbdtkVV3XiW2ImfSt5k60y9nv/GE+Bn5m7QZDRFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyHeB+BHAQQLA+f7K8+L50h4A1il1Y4vVmdotkxkBXLK5QZxqPlzv4GTsrZLetjh1Cua1kqhv/smZ8DXtKg1yojLbN56oSfS4NvKNzYizauGRzHrkrL5v/HzC0YvMszHdMTzP3vl32ZKYG3f+M1Pf6yhPTwC44upWaXzv7qRHM+ue6zmLe+4+IENPnJA581Wn/micgQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnkkYImLa8XHvfLoUXmUPBJILRq7hAcPzPgMZ1lVsDWVkkwgVQdHm1Tg7+zXH0/l0tG21devF1vh4qNFQ6GQTJ26OKrXN3ExEBy9wDwbhasrRI/sTaZYCx3iqFg8KKrv75+YTeZy0TaegYnodqINPWdxpoqjrHBZb1XUWi1N779WSjYa50lOdJPRl89L94/2q+B75p49UZ84jgACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAuYRsMUHgNXAMgoCZhdIewA4GPdFSDTKNh7M0z8hU+0DUrKuLv6Qoa5Hf9a/dZv033/EsD9RpXx7kzR/YE+iZjJ7YUwCbm+4nXcg8Ujjkg31MvRUcvPc6meLTyEQ3yHfqFtC/uTTP+vzvYOJ02dH7uNZ4ujpyPmprC321NKAL3RtR2WRrH7X1eH5k/WPAJItE8d65MJ/vSLuFEZIJ3tt2iGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggED+CMQPbAzMXIwV5c8T8iT5KJD2AHD8F8FW4EjZUc9lmygArC/a+K5dUri6Urp+8ILE3zf+pjoIqUf+Nn1ojyQTkBw72Bm9hGcocQC49MrGcErnhHPwqrhl9Q0botdeaCOZe8afG/Ak/ysUTxJBbX39gYePSd8DR+NvlXS9uK1a3F0jSbefr6H+EUH9W7ZK/Zu3itWV/EdYz/OrA7+RkdzzXZt9CCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEBEwBoX14rPfBtpxxoBMwkkHz1bYq99cWmLlzLX7OiB8yrF7zWSzNyxVXvWStnWRhlT5+gUv3rkru6DHmGrR4zqeXZLN6+SmjdskmRTEeuUz/0PXBpZPHWyT0LB0KKjdh1qvt6NX3irnP4/D4lnofmAbRZp+7V9Urm7LaHu5InehG0up8HU6X7ReesTBVRrb90ivslZ5aGCwCotdTJFX7Nq7zqpvXmzFDZVyom/vk/0iOaUiw6WX7c+POo3Ucrs2GtPqVTcvT8/KJOvpdcw9p5sI4AAAggggAACCCCAAAIIIIAAAggggAACCCCAQO4LxMe1/CpGQkHA7ALpDwCPG+fLtRctPtfuvGCBkPTdd1ia79o77+H4nfZil9Ts2xRe9DE9f24qKYLjr9f7s4Ph4Ghkv06XPPZKR8LArQ42b/z8HeHgsfvcUDjlcNDnl4KGcilaUyvVKihaumVV5LILrnVgdvCxEwseX44DgWmPDD19SureeMWil7PYrNL47l1SuatNhp89LXpkdPwcujb1jl21peKsKQkH23Xwdykjv2M7UryuNvz+i1qqY3cntV3UWiXrPnNbUm3jG42+dE46vvts/G7qCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsAIE7MXGuJYvLu61Agh4xBwUSHsA2D9pDADH/1IiWbPBx09IUWt1UumS4695OcHf6bODKjB6Ov6S4aBuMiN39UjgpvddEz5/qYHooWdOiQ7Qprv0P3Q0PEo3mZTY+l3oRQfl/apv+hcvIX9QHFVFYi9yLXtX9cjjpQR/dUesjqV/zHXAm4IAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIrT8DisBliDEFfIOEUpCtPiSc2o0Dao1vxc+A6yguX7ND5b8+Lnsc1U8XdMSxn/vHheVMd62P9aj7cVMpSAtGzKn107y9eTeU2S26r0zJ3/3h/yufrEdd6VLNO75yO4G/KHeIEBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQOAyBeJjWr7R6cu8IqcjkBmBtAeAdbrk2BL/ZYk9lmg7FAjK2a89Lu7O4URNL/u4vsfpLz8oAbd3wWv1/PglGXnx7ILHL/eAd8wtZ9QcwpkY/Rvpqx5p3XtfZgLOkXuyRgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTMJhAf04qPeZmtv/QHgYhA2gPA3uFp0YHbSLGXFMjlpNXVqYZP/NW9cuHnB8MphyPXXa51KBgKz4V7+u8XD/5G7nf+X59OSxDYMzAhZ/7hIYkfQR25bzrXvfcclL5fHhFtsdxlpndM/CqwTUEAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEzCzgKC8ydI8AsIGDiokFlj45arIPFQqJZ2hKCurLomc4q4vFM2AcGRw9mMxGICR9Ki3y+KEuaf34DUueGzb+VtPtA9L1wxdFp3dOuqi+nP/2UzLyfLs0f3ivuGpLkz51voZBfyA8v3DffSoAq7azVS7cfUDGDpyXll+9fll8p071S/+DR2T8cHe2Hon7IoAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJJC+h4Vmy5rNhW7IXYRiDNAukPAKsHmOkZNQaAVZB0Ob4kM10jcuIvfyFFbTVSee0aqdzdJs5K45cxkZ9vYkYFkjtl7GCnTBztSdR8weMTx3rk+BfvkZqbNkjFrlYp2VAvFmvyA6z1r0bGDnbI0FOnxNM/seB9IgeCXn9kM21rHQg/8b/ularr1knVNWukdPMqsdiTfyY9glg/U/+DR8V9buiy+hn0ZicYngnny4LhZAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEiLgKv20uBGfYOZ7tG03IeLIrDcApkJAKv5dCuvbo32XY+SvYzxv9HrRDbc54dELz0/eUlK1tdLYXOVOCqKROdm1+uQLyD20gIJ+vziG58R/8SsWrtFj0qdPjcoskyZjvWIXT2Hrl5sJS4p394shavKxa77odIE6OCp7ovVYRcdeA4vI9PhwLMOkqdSzn/3mfDzLXrOcqRwViO4R547E15sRU4pv0o90+oKsb/uG1KBWXtZoUgwKP4ZrwSmPCrgPxZ+H9MdQxKc8S3axWQP9vz0ZeX6WrLNl62dTmFOQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgZUn4KwtMTy0uyuFDLKGM6kgkFmBjASA3Z0jhqcqaCg31JetogK5U6f7w8uyXXOJF9KBUB04TVfx60C2WjJZAm5vONV1Ju8ZuVc4sKxMKQgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAJgTi41nx8a5M9IF7ILAUgeTz+S7l6q+fM3VmwHB2YVOloU4FAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAbMIWAsc4qy+NAI4qDK8us8zAtgs74d+LC6QkQDw5IleQy+KmqsNdSoIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIImEWgqKVKLBZLtDvT7QOipwKlIJALAhkJAHv6J8Q75o566LlkC9Q8shQEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEzCZQvK7O0KX4wY6Gg1QQMJlARgLA+pnHD3UZHr10yypDnQoCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACZhCIj2ONxcW5zNBH+oDAQgIZCwCPvHjW0IeKHS2GOhUEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEsi2gM9mWbmgwdGNkvzHOZThIBQGTCWQsADz05EnDo5dsahBnzaXJsw0HqSCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQBYGqvevEYr8UQps6MyCzPWNZ6Am3RGBpApc+vUs7P+mzZnpGZfxwd7S9nji75saN0TobCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCGRboOYmY/yq7/7D2e4S90cgJYGMBYB1r3p++rKhc9U3rBexWgz7qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQDYGitbVS2FQZvXXQH5ALPzsYrbOBQC4IZDQA3PfgUfFPzUZdHBVFUrm7LVpnAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIFsCdTdtsVw66GnTol3aMqwjwoCZhfIaAA4OOOT3vuMw+Trb99qdiP6hwACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkOcCzpqSOQMXu3/yUp4/NY+XjwIZDQBrwM7vPyehYDBqWdRSLeVXNUfrbCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQaYGGt24Xi/VS6GzqdL+MPNee6W5wPwQuW+DSp/iyL5XcBWa6R2XgkdcMjVe/62oRpgI2mFBBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBDIjICrvkyqb1hvuNn57z5rqFNBIFcEMh4A1jBnv/G4YRRwYWOl+lJtyBUz+okAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJBHAo3v3W0Y/Tt9fkj67jdOa5pHj8uj5LlAVgLA0+2D0nuv8UvT+O5dYity5jk3j4cAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIGAmgbJtTVKxo8XQpfavPCoSDBn2UUEgVwSyEgDWOO1ffVQCbm/UyV5aIE3vvyZaZwMBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBdApYXXZpvmuP4RZjBzvVdKbHDfuoIJBLAlkLAHv6J+Tct540WOk00GXbmwz7qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQDgE9ONFVUxq9dCgQlBN/dW+0zgYCuSiQtQCwxur4/vMydbrf4Nb6sRvEUV5o2EcFAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgeUUKN/ZIjX7Nhku2fnvKnZ1yhi7MjSggkAOCGQ1ABzyB+TYn/6XBNU6UhxlhbLm128WsVoiu1gjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsGwCztpSafv4jYbrTZ8bVFOYPmbYRwWBXBTIagBYg02e6JWzX3/CYFeysV5aPnKdYR8VBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBC5XwFbklPWfvU30OlKCPr8c/eO7Jej1R3axRiBnBbIeANZy57/ztAw/e8aAWHPTRln1zh2GfVQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQWKqAxWGTdf/9jVKwqsJwidNfekgmj18w7KOCQK4KmCIALKGQ+lXFT2WmZ9TguOptO6TmDcbc64YGVBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIRsBiUdOQvkFK1tUZWvf98rB0/fBFwz4qCOSygDkCwErQN+aWQ5/9gfinZg2ezXftlco9aw37qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQtIAK/rZ+/Aap2NFiOGX8cJcc/+LPDPuoIJDrAqYJAGvI6fZBOfz7PxKdZz1SLFaLtP3aTVL3pisiu1gjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkJSAxanSPn/mVqm+fr2hvbtjWA597ofM+2tQoZIPAqYKAGvQkRfOypHP/0RCgWDU16J+ldH0/mul8X3XRPexgQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggMBiArZil2z8vdulfHuzodls37i88uvfE9/ItGE/FQTyQcB0AWCNOvjYCTn6Rz+VoD9gMK5/85XS9ul9on+pQUEAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEBgIQFXfZls+sO3SnHcnL+zvWNy4FPfFR0EpiCQjwJ2sz5U/4NHJTDrle1//wGxOi91s+ratVLYWClnv/GEePhimvX10S8EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIGsClbvbpOVjN4itwGHog077rEf+Evw1sFDJMwFTjgCOGA89eUoOfPq74h01Dr/XAeAtf/p2qb11S6QpawQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgRUuYCt0SusnbpQ1v3HznODv2MFOeelXv03wd4V/RlbC45s6AKxfwPihLnnpw9+SqTMDhvdhddml+UN7ZMP/eIsUrK4wHKOCAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCwsgQqdrXJlr94p1Rfv37Og/f+4lB40KFvzD3nGDsQyDcB0weANfhMz6js//A/i/5yxpfSjQ2y5YvvkKb3XyO2Elf8YeoIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJ5LFDYXCXrf/fNsva/3SzOymLDkwa9fnntL38hx/70vyTkCxiOUUEgXwUuTa5r8icMzvrCX87hF87Kpi/cIY6ywmiPLTar1L3pSqm+aaMMPHRMBh49LgG3N3qcDQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgfwS0BliG+7cLpXXrBGLxTLn4SZP9cmxP7lbpk71zznGDgTyWSBnAsCRl9B376syuv+cbPmzt0vNvo2R3eG1nsh71Tt2SN3tV8rwM6dl6ImT5HE3CFFBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJYQMV5S69YLXW3bpGybU3zBn6DPr90fPdZOfuNJyXkZ9RvDr9tur5EgZwLAOvn9AxMyKHP/kBqb94kGz9/hxQ2Vhoe3+ZySN1tV4SXqdP9MvLiWRl7pUP8k7OGdlQQyHmBkHqCkP4vihkE5v6+LIu94nORRfy4W5vpK8rnIu7lZLHK5yKL+Ca+NZ8LE7+cLHbNLJ8L/jckix8Ck95afzb5XJj05WSxW3wusohv4lvzuTDxy8li1/hcZBHfvLcO/7s1/v+FeV6Q/p6arOhYUMXuVqnau05cNaUL9m74hXY5+Vf3ibtjeME2HEAg3wUsD2//ogm/xsmzWxw2af7AtdL2qZvm5HWPvUooGJLpswMyebxXps70h7/4pImOFWIbAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEDCHgLO6RIrW1EjJ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AQQQQAABBBBAYAEBd8ewnFbzAvvdHkOLjWo+4Jp9Gw37qCCQ6wKmCQA3vmeXNL3/GoOnzsve/tVHJeQPGPZTQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCAVgdnX405Bnz96msVqla1/814pbKmK7mMDgVwXMEUAuGRTg2z8wh0GS+/ItBr5+5AE3F7DfioIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIILEVg+vSAnPvWUxIKhqKn24tdsv1LHxCryx7dxwYCuSyQ9QCw/jJt+7v3ic3liDoGZn1y5h8fFt8oc/5GUdhAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBC4bIHxg53S/aP9huuUbmyQDb/7ZsM+KgjkqkDWA8DrPnubFLfVGPw6v/+c6GH4FAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQSWW2Dwsddk5MWzhss2ffBaqbx2jWEfFQRyUSCrAeCybY3S8uG9Brehp07K6EvnDPuoIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIILCcAp3/pgYkDkxEL2mxWOSK//lOUkFHRdjIVYHsBYDVl2jzH79N9OTakeIZnJTuH78UqbJGAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIC0CQY9fOv7lGcN8wIVNldL2yZvScj8uikCmBC5FXzN1x9fvs/pdV0vZFasNd+34/rOiv2wUBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBNItMN0+IIOPHjfcpu2TN0rBqnLDPioI5JJAVgLAVpdd1v63mw1OI/vPytSJPsM+KggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgikU+DCzw+Jb8wdvYXVqeJYv3VLtM4GArkmkJUAsJ5Eu6C+LGoV9Pql5ycvR+tsIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJAJgeCsT3ruPmC41aq3XSVFa2oM+6ggkCsCGQ8AW+w2af3o9QafgcdeM/yywnCQCgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJpFBh5oV1mekajd7BYrdL2iRujdTYQyCWBjAeAV739KnHVlkaNAupXFf2/PBKts4EAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBARgVCIr0/O2i4ZcNbt4ur7lJMy3CQCgImFsh4ALj5Q3sMHENPnZKA22vYRwUBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBTAqMHeqU2b7x6C2tDps0vu+aaJ0NBHJFIKMB4LKtjVK6qSFqEwoGZeCRY9E6GwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAghkRUCNAh542Bi3Wv3OnSJWS1a6w00RWKpARgPAje/ZZejn+OFu8Y26DfuoIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJANgZEXz4qevjRSCurLpOamDZEqawRyQiBjAWCryy71b9lqQBl6+pShTgUBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBbAkEPX4Z3X/WcPvVv3K1oU4FAbMLZCwAXH3dOrEXuaIe3pFpmTjSE62zgQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEC2BYaeMg5grL5hveiBjhQEckUgcwHg69cbTMYOnBcJqWTqFAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRMIuDuGBbP4GS0NzaXQyp3t0XrbCBgdoGMBYArdrUZLCaOXTDUqSCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBgBoGJY8YsthVXt5qhW/QBgaQEMhIAthY4pHhtTbRDoWBIps70R+tsIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIGAWgalTxjhW2ZWNZuka/UAgoUBGAsAlG+rFYr10q9m+cdGTaFMQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQMJvA9LlBQ5dKNzcY6lQQMLPApahsGnsZ/6WY6RpJ4924NAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJLF/AOTUlgxhu9gLOyWJy1pdE6GwiYWSAjAeDitkvpnzXGzIVRM5vQNwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgRUuMNs7bhAobqs21KkgYFaBjASAC5uqDM/vGZg01KkggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggYCYBz8CEoTuFzQSADSBUTCtgz0TPilqMAWDvYPoCwNYCh7jqSsVRUSSOcrVUFIqjrFAkJOKbmBG/WvTaN+YWd6dKRR1UByh5I2ArckrRmhpxlBaKvcSllgKxFTtFLBYJuD0SmPaKf9ojOnWDzt/PXNR58+p5EAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEllXAExfPio93LevNuBgCyyiQkQBwQUO5ocvxXxjDwSVUrE67lF/VLJXXrJGyrY1iddiSuooOBE4c6ZaxQ50ycbSHYGBSauZrVKRSLpRf1SJlV66WotYasVgtSXUyFAyKno964rVeGXripHiHp5I6j0YIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQ/wIeNZgsthQ0lMVW2UbAtAJpDwDbil2iR2VGStDnVyMxL02aHdm/lLVNjfBsfO9uqdq9Rqyu1B/FrvpWtXddeNEjQfvuPyz9Dx2VkD+4lO5wToYF9Ejf1e/cqQK/jUu6s8VqDQeMddC4/s1XyujL56X354fE029M6bCki3MSAggggAACCCCAAAIIIIAAAggggAACCCCAAAII5LSAb3Ta0H9XLQFgAwgV0wqkHjVN8VFctaWGM3xjM4b6UivlO1uk5SPXXUzvvNSLxJynA8ir33W1VN+4Qbp/tF/GX+2KOcqmqQTUCN/mD+2R2ps3L1u3dDC46tq1Ur69Wc5/60kZP9y9bNfmQggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJB7Ar5xY0wrPuaVe09Ej1eKgDXdD+qqKTHcIv7LYjiYREWne2771D5Z91u3LlvwN/a2+su77jO3yer37IrdzbZJBPRo8g2/8+ZlDf7GPppNzSG99rdvk6o9a2N3s40AAggggAACCCCAAAIIIIAAAggggAACCCCAAAIrTCA+puWMi3mtMA4eN4cE0h4AtpcXGjj8k7OGeqqV1l+7KSPBuYa3bJPV7yYInOr7SXf7tb91i5RuWZXW2+g5hJvUCGN7aUFa78PFEUAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAwLwCgWmPhIKhaAf11KIWe9pDa9H7sYHAUgXS/il1lBkDwAG3Z6l9lVVqvtfKq1uXfH6qJzbcsU3dc0eqp9E+TQJ6VG7ppvQGfyNd13/EG952VaTKGgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBFagQGDGa3hqe1zcy3CQCgImEUj7HMDxAWC/2/hFSdah8po1sioLAbmGt14lYy93yEzPaLJdjbbT6aqd1cWiR0Frh7CFGl2qR0HrtAH+iRnxjkxLYIkm0RsluaHnOS5YVSEFDeXiqCgU/5RHvGoC89kLY+IbdSd1FYd+lspidX5R+Bo6ZbJ+Fv0cevGpJRQIJnWtVBppy1TScs/2jcvkid5w3/QvdKwuh/IvkNIrVkthY2VSty5ZV5tUOxohgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAfgr4VYxBDxqLFIfKHqpjIRQEzCyQ9gCwreTSl0JDLCnYabNI4/uvScnR3TUiYwfOy2z/RDjQanHYxFlVEg7Ill/VLEVNVUldT6cDbvzANXLmyw8l1V6nDS7f0SIVO1vCqYqtdtui5+nUAdNnB2XslQ4ZO9Qp3sHJRdvrAGZjgvmJJ470yIV7Xolex6qCtDqldd2brhAdSI0vQ8+cls7vPRu/O1p31ZVK5e41ooPwhU2LB08Dsz4Zeb5dBp84EQ4sRy9ymRtl25rEqQLPicpM71j4WabbBxdsWtRWLWvVHNKJrlewukLEoi5zKbvDgtfkAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOSfQDB+BHBc3Cv/npgnygeBudHAZX4qPUI0tgQ9/thqUtuVO1vFqUacJlPcHcPSoYKZMyoAvFDpvedgeCToqjuvkpKN9Qs1i+4v27JayrY3ycTh7ui++A0dZF39Kzul9pbNYrEmn1lbB5hL1teFlyYV5B472CFdP3xxwRG5OoV2UUt1/O0N9VBARSxfDwC76stk4+fvuDj62NAqcUWnMWhWc+FW7m5L3Pj1Fvp9awO9TBy/IOe/83Q4AJ/0BRZoWLw28WhcPUr71P9+QPSI38WK+/ywnP3GE7L5j+5crNnr75EI8KJIHEQAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAII8FAnFxLR0PoiBgdoHMB4C9qQeAa2/bkpTj0NOnpPMHz6thxomHbE6q4KROEbzmN25Oal7h6uvXLxgArtjVKs0f3BNOi5xURxdpVKGC3aUq4Nz784My8MjxOaNPZ7rHwimWLbaFg8wFq8rDd9Cjkdd/7k1LCv5WqefVAenYtAaLdHveQ2VqtPLmP3mbnP3aY6ID85dTCpsXH3msr93/4NGEwd9IHzy945HNBdd69LiEEn+WFrwABxBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCnBYJxcS1boTOnn4fOrwyBtAeA438JEf9FScRc0FihRscmHqU7dapfOv9dBX9VSuWki2p77p+fENtn3ihlWxsXPa1kw/x9qNm3UVo+ev2i56Z6UI+ibXr/teKsKZVuNRo4toT8AdFpjhdLYa3Pd1YVS8vHbhBXbWns6Ult1966JTzyN6nGCRrpfugRyGf+7yMydbIvQeuFD3f92/NStKZm4QbqyNgrnYsejz2onzFRcZ9bOI10onM5jgACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAArkvEPQGDA8Rn/nWcJAKAiYRSH8A2GEcqRoKBFN69ETpjvXFQmqUZsd3n0kt+BvphRotrOfLTRQAdqh0yK6GcvH0XRo5quf6bf7w3siVln1dp4KUvnG39N9/xHDtGTWadrEAsG5cfdMG0SNwUy3lau7ipg9cm+ppi7bX8w63feJGOf4/75GlpADXF/eouZH1suSi5pG2FxdIsQoiV+1dlzCttf6hQu+9ry75dpyIAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACuS8Q8hkDwBa7LfcfiifIe4G0B4AtNuMXITw/bQqszpqShK31yNLLCQ7q9MTujiEpal18hGmBmk83EgDW/Vrz6/tSmu834YPM06DxXbtEz1mrU1ZHirtzRKpviNTmX6962475Dyyy11FZJGs+pZ9Jz3ubXAmqEcnWJP7YOatLwimlO9VI3nSWVXoe5ps3G26h02Wn8osc/YOC7p+8JN6hKcN1qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggMDKEtAxg9hiUQPOKAiYXSD9AeD4YGIwtRHAOnCYqIwdSj7170LXav+nx8RRXrjQYTXvbkhmukaix+vedKVYHYn59B+GmZ5RcZ8bUoHcIQmqX4oUtVZLcVtNOOBssRtHSEdvELPRcOf2uADw5c2nG3Ppi5uvv5O6N6pnUqN1ExV357D0/fKITB67IIEZr1hd9vAI6oa3XbXoyOSafZtk8ImTBsdE90r1eMn6usuat9g3OSvnv/2UwTvVPtAeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE8kQgbupRizVxXCdPnpzHyGGBxNG+y324uABw3A8lEl7dlUQA2DsynfA6iRr4Rt2il2SKrcQlNTduSNg0pAKrHd97TkaeO2NoO/J8e7hesrFe1n32jQlHp5ZubJCitbXiPntxTlodiA6pPzjJjtTVQejhZ8+oOXI7ZPbCmPinZsVRUSR6xK+zslgmVCDXWugQPZ9xojL68nk5960nDem2dVrnsQMdMv5qt6z777dJ2ZaFU09XXrsmrQHgRP1f6Lg26vnJyzLy/Bnl41moGfsRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEBgBQnoeExsYQRwrAbbZhVI/88U4r8YKY6MtxU5E9oFZ3wJ2yxng8rdbQlHyurUyOe++eSc4G9sP6ZO9cvpLz0g/unEAcfq69dHT9UBV+9wcumJdXD89N8/IJ3fe1YmjnSHz9Pne/onZOpEnwp4tot/YkYq1HzGidIkzw5MzAn+RjulNkL6mb/xhARmF34flbvaYk8xzbbFYpG6N10hq96+Q+wqwE9BAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBOIH46U61SmCCGRDIO0jgEOBuJTPaj7WVIpvTI3Kbale9BR7WcGix5f7YEFdWcJLjqmRsnrEbaKi5/cdeOiYrH7X1Ys2jb/nHNcFzu747jOiA82JiiuJZ9J92PHVjyS6lEqNbZz3OfYEV21pOAW2nnfZbEWPhq69dYvoUcrd/7FfRl48a7Yu0h8EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBDIoMCcAHCKU51msKvcCoGoQPoDwHFfhPgvSrQnC2x4hxOndy6oL1/g7OR3l6sRsEWtVYueoNMoe4emxJlEsHTqdOKga+RmybR11pVGmie9Hj1wXiZf602qvQ7MJlMWC+4mc75uU9hYKWYMAEf6by8pkLZP7RO/mt944nB3ZDdrBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQWGkC8VOdxg98XGkePG9OCKQ9ABz0BQwQFvvCo0MNDV+veJJIdVy5d630/uLQfKcnt0+l/22+a094PtzFTpjpGg0HgJOZl3iqfWCxSxmOTZ8bSjinrx6dKqqfksIkyiMvJD+C1Vmtrp+hYq8oTNud9MjdOWnDlZsOXNsKneJSgfSybU1Ssq4uYR9aP3aDHP/iPRJIIkV3wovRAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJOwBoX19LTYVIQMLtA+gPAcfPzWp2pBYD1iNtERacm1kE9PcftUkrZ1saEwV993chI3VDcqOb57hn/B2G+NpF9SU0YHp5L2TjReOT8hdYeNWdvsiU+UJ/seUtp5yhLXwB4pns0YZf67jss+p23fXqf2IsWnu9X97N0yyrR6bwpCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsPIErE5jKC0QF/daeSI8cS4IGD+1aehxYNZnuKrV5TDUE1WmTvVJUP2aIlFAtfXjN8iJv/yFhOcMTnTRmOP20gJpet/umD3zb872jol/cjZ80KOC0kUJ5iUu3lCfdJrjYjUaNVFqbM+ICoSnFv8Vz9Dk/A8zz17voGq7ZZ4DadjlKC9K6ap6Tt5V79i56Dm9Pz8oo/vPLdom9uDE0R4ZP9Ql1devj909Z7uoqYoA8BwVdiCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsDIECACvjPecb0+Z/gBw3C8hbHG/lEgEqoOuo2oEZvXedYs21aM113/uTXLum0/IbN/4om0jB+0lLtnw+7dLwaqKyK4F15Mn+6LHvEmMrC3d2CCDjxyPnrPYhm6bqHgHkg/m6msF3F4JeZNPQ+BJ8vr6XXh1MPoyylSMZTKX0fMTF9SXLdq09g2bUwoA64sFvf5Fr6kP6pTRFAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEFiZAlaXMZQWP/BxZarw1GYXMH5q09Bbf9z8qXPmZ03inoOPvpYwAKwvU9hUKZu/+Hbpu/+IjDx3RgUqp+e9uqOySGpv2Sw1+zaJvXjhFMCRk0P+oAzEBHNnexMHmCt2tkj9W7ZK/wNHI5eZd63b1d1+5bzHYnfqEciplFAKcwXr6870JE6drNs51Py9nf/2XDjArOvJFv0HsmrPWqm6br3BMpnz3R3DCZuVbKyXVb+yU3rvOZiwrW5Q2FgplbvaErb1TcwkbEMDBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyE+B+LiWf+pittj8fFqeKl8E0h4A9o0bA2jxX5RkIN3nh2T67KAUr61N2NzqsMvqd+5UKYN3iD7P0z8hvolZsdit4Xl+nVXF4UCxxWZNeK1Ig8EnToSvE6nrUbCN778mYfC48T27xabmmL1wzytquOnc/M06/XDLx65X6Z8X74sO5g4+dSpy+7SsJ471yKyySjTStmR9vWz583dK1/97UcYPd837XLEdLFhdIbVv2KQCv+vEVugMH0rFXp+gA8Ah5ZcoTfaqO6+S4tYaGXrmlIy/2i3zTcTurCmRyt1rpOGOberdXOxPbH/jt2cvpBZ4jz+fOgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOSugK3YGEvwq5gTBQGzC6Q9AOyPG0GZzIjb+dDO/8vTsumP7xS7CqgmUywWixSvqQ0vybRfqI0ewdz7i0OGwzp18ODjr8mqt+0w7J+vogONdbdtEXfniMx0j4SDmM6aUilqq076WfRctZ4k01rP14ek9qn4dP8DR6T1YzckbO6sLJZ1v32raJvxV7tEj4j2T86IHnSsA+w6ZbMOtLrUc+r65RadBnxYjeiuuXFDwkuVbW0Uveh35B1zi/5DrLd1sNeh5nt2VpckvEZsg+n2wdgq2wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIILBSBCwSHdymH1kP2CNz6Ep5+bn9nGkPAPtUEC622FUQbilFj+Q9980n1Ty/b0w4YnYp15/vHB04PPeNJ+ZNdzyg0lLXqHlndVAxUdEThJesrwsvidrGHw/6A9J336vxu9NSH3m+XerefKUUJjEnsu6ADubrUcyZKBfuPqBSNrca/tAudl9tXlCn5g3WyxLLyP6zSafGXuItOA0BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRMKqDjIHrAYaQEpjwJM6NG2rJGIJsCi+ceXoaeeYanDFdxlBca6qlUJo9fkO4fvZTKKUtuq4O/7V99VCZP9M57Df0lb//HhyWdk33rX5J0/Msz4RTI83ZimXeGAkE58w8Pi3d0/rmTl/l2KV1OjwLu/MELKhV0MKXzltpYv9ee/3x5qadzHgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOS4gKO8yPAEnqFJQ50KAmYVSH8AeND4ZbBfRgBYIw4+9poaCfyEpHOSbZ3aOBz8fW3+4G/kZeq5ac9+/XE112x6gpLd/7FfRl86F7ldRta+kelwENjvVr9iMVkZffGsnP2nx8IpndPZtYDHJ+1feUR8o8bR6+m8J9dGAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABcwk4KuICwAPGmJe5ektvELgkkPYAcHDGZwjWWu02WWoa6Ei3R18+L8e/eI+MHeyI7FqWdSgYksEnTsixP7lbJhMEfyM31KOST/zVvTJ9dvnmivWooPkZNbpYB7uzUWYvjMlrf/Hz8Py+y3n/8aPdcupLD4h3yDgqPJV7jB/W13hQzak8nMppSbedOjMgJ9SzT53qT/ocGiKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggED+CTgq4wLAcYMe8++JeaJ8EUj7HMAaarZ3XEo2XJor11lbKjql7+UUff7Zrz0u5TtapPrGDVJ25WrRweWlFD3Prg7kXrjnoMx0jaR8CX3Oyb+5T2r2bZJVb79K4lMCJHtBnXZ4UM0t3Kvm/A35AsmelpZ2eiSwHgVdoebdbXzPbnGpd7aUokdH67l0+x86KrM9Y0u5xJxz3CrYfuIvfxF+99q7qKV6TptUd0y3D8jAI8dl9MB5NYt7qmfTHgEEEEAA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8.33% 77.2% 14.67%);&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;2170&quot; y=&quot;300.25&quot; width=&quot;769.95&quot; height=&quot;70&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;m1QEX4gwLa7LHTGOXF54-5&quot; value=&quot;&quot; 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7p73zyv4G1qXvIVlsuZvbpeiDQtCV80rP9bUE3P73AWl4sr2yOr/+1ZLwd/QAivetULW/NV7jZ7ioevII4AAAggggAACCCCAAAIIIIAAAggggAACCCCAgPMEApMhAeA8AsDOawXpV+Pw6GKc6xAeADb/Q7GyO92DNX9JRcxN+w80Sduj+2NuF7qBHiq5d8/cPXunty9cWT390vRce/tlsvgTlxtzy5pWXEJGB35rbt4o9Z+72gjkmoqaCsq4CgJHS+5sr5rztkiW/cm1MXvORiqn7gNbZeEHt4tbDZt9qcmbnyMr//xG1SN4yUUXNaaC9cGpQNT359aVyuKP77qkgLVuZws/vD3qfliJAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACzhAIDQC7L2K0VWdIUctUEkh4AFjP3Ts7Bf3Rg3izt51+rXuRxkp63tnZc97G2j50fftvD4QuCsvrcd1Dj6XiqlWyQAVLE5XKdi6TRSqoGZpGG2P3iK26YZ3MHgo6tIy58hVXr5Y6FdSOZ9LDQi/543erYbwvbmz8oH9KxtsHoh5SwbJKqbxmTdRtrKzUvbkLVlwYQtvKe9gGAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEMk8gNK4VGvfKvBpTo0wQSHwAOGQI42AgOG83PYxxrKTn/Y0052+s902vH28bkOETHdPZOZ+9JXkz63LrSlRQ84qZfKJeVN+wXkpD5hUebeqNuTv9vvmmnJpiWfKpd1l+mx77Xt/9MjUee25nb1GuLP7UxXuNWhgG2vKBR9nQ5XJJxZWromzBKgQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEHCCQDBojmu5PGr+TRICKS7gTfTxudwh/xBUT935puzy2AHgARUAvtR06rtPRx3GWQev/YNjM7upuXWT6J6tsZK+O2TwWKuMnumWsXO9oi8Weo7e/GVVUryuTjx52bGKkNrbNkn/vrMz211KMFTXI+Dzm+YFnh7CoObmDRHnHZ7Z8TsvBg+3SNt/viUjpzpnVules3V3blV1mnu+37Id9dL5dJWMnO6aeZ/VF9pOLiJ+PNkzbASoc6qL1JDW1pp86balRo/yWMNOWz12tkMAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIE0FAiZnlJP4UlCINUFrEXDLqUWIQHgkBslLJVspQewr3fEUlnRNgqoXqz6YSVlleVL+a7lMTfVgdWG7z8ruofy7DQg54ysHlJ65ZdujjlPb/7SCilSweKho23G+8aa+0QPe20lAK3fEFBDKHc8cUj632w0hlIO+qbEneOVrLICyVZ1GVHBad1Dt/yKFUb50f7X+cxRaf7l62Gb6KDuqX/dLfV/co2Uq6Gr50p6WOuLCQBb6fU8vU8d4D73yzeUe7P4+kbPL1ZtseamDVL3/i2i50iOlozhvheViZWhtqOVwzoEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIX4HQuFZYx8f0rRpHnsECCb9NITgV0jU+JCBsxdajApWx0nQP1ljbxWu97iHq8kbn08Min/r27rDg7+xjGGvpkxP/+HuZtBDALpsVcNYB3Mnu4dlFzfl6rK1fjn3tN9L22P7zPZDVe3XSwzdPqHl1dVBZB75LLlscs4fsZN+ItKn5kj352ZEfeVnS+tBeo4fxXAcUOpz1XNuFLh9XVlaS7rV75t+fk54XT1wI/uo3qp7PHU8ekrM/etFKMZI1a7hvS29gIwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEMgogdCAb2jcK6MqS2UyRiB2ZPVSqxo65PNFBIAnVQ/O/KXRDySr+MLcvNG3jM/anOrimAX1qSGbrcwrPNE5JLpX7aKP7Ihaph7CeHayMp+yHm668ccviZ7jOFbKqTKXH2n7bNVj+LJ//USkVZaXZZfmix4uer69gAPvBK5j7ajl4X0y8HbznJvpXtBDJ9qlaHXtnNvoFVnqOEkIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDgXIHwAPD8pzp1rh41t0sg4QFgPUzx7BT6D2X2urle6zlcY6XchaWxNom5vuKqVVKwvCrqdp1PH5Hx1n6xEiwdOdERtazZK4dPxt7Wyj5nl6lf97xyyph7OHR5pPzFlB+pHCvLcutK5x0AtlKu3iZ0uO1I7xs+FjsA7MnPifRWliGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggIBTBEI6NobGvZzCQD3TSyDhAeDA5PnhhqdZ3F7P9EvLz1YCwOWXr5DWR/aLhA7GbnEvetLuhR/absyDG+0tAweajABwdnlBtM2MdSMNXTG3md5gtLE75py+Ro9UfaFRQxlbTbq3q9WUZaFOVsuKtV2ihlfWw26PqyGvY6XxzsFYm7AeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEHC7gzjLHtayOVupwNqpvs0D0SWzjcHA6IDc7uSzM5zt7e/3ayly3OiBbtrM+9K2W8yVblsQM/urhlIdPdRplBv3mwHakHel5cq0mT06WiEsFd6OkoF/1pp5H8FcXNamGl7aa9DzAyUpZJYkZXnnsXK+6CSB2LaZGJmJvxBYIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDgaAF3trkv5dTYpKM9qHx6CCQ8ABwYMwcVPSH/UKwwDanheqcmzOVEet+ST18hOTWx5+YNfW+2mvt20cd3hi4Oy4+19MnU6Pl/2Hre3lipcFVNrE1m1hesrFbx3+gB4Mnu2PucKVC90AHriXm8Z6JrfuXP3td8X3uLc+f7Fkvbc+eNJSY2QgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQsCoQHg0LiXhSLYBIGkC5hvW0jA7kPvhHBfRA9gXUbvaw1Sde2aqEfoycuWlf/tZjn7oxdk5OT5nrpR36BW6uDv6i/fKtllsYd0Hj7aNlOclcBq0foF0vHkoZn3RHtRvG5BtNXGuonu2HMhzy5Euxm9hmcvjPLaSlBbv737xROWhlmOsisZOdMdbTXrEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHbBULjWqEj39p+gBwAAhEEEh4A9g+bh9qdz7DIs4+365mjMQPAevucikIV0L3NCFL2vHJKRueYhzdvcblU37heynYtEyvzEgcm/NKx+/DMIY019828nutFsQoAL/qjXdL8qzfm2sRYXqkC3gVYywAAMjdJREFU21XXr4u6jV451qyGN55PsjAU8uziRpt6ZmfnfF2wvEra/vMt8fWOzLlNpBVZZflSefVqKb9ihfT/jycibcIyBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCBlBELjWqFxr5Q5UA4EgVkCCQ8A+wbHZu1OxFOQY8pbzYy39svgkVbRQdVYyeV2GcFi3WN4UgUpJzoHRR+Hy+sxevpml+fLfOeg7XjqkPj6Rmd23b+vUXwfHZWs0uhz2VbfsF50z+SWB/dI6EVB3zWi1y/44LaZcud6EZwKSPdzx+daHZflw8fbZVTNoZuvguPRUt7CMll/753S8vA+6Xv9jIT28ja9Vw1rXbS2VqquWyslWxaLy/3OqOPqHJEQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgVQW8IbEtXwD5rhXKh87x+ZcgcQHgEP+IXjzsy9au/HHL8nar74vZtB19g6yywtEPy4lTfaPSscT5qGcdUC28+kjsvAjO2IWXfHulaIfetjosXN94vK4JLuySHJrS1RA1FogtG/PGSOYHXNnl7hBx+MHZdnnr41Zig5qL/nUFbL445fL0Il2Y0ho/9C4Me9wdnmh5KihtbMr1bN67fImfKrpmMfLBggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIDAvARUJzd3btbMW4LBoOhYCAmBVBdIQgD4Qq9ZjeEtyrtoE58KxJ7+t2dk9V/eKu6shB+6cZz+kQk5/d2nJTDpDzvuruePS+V1ayRHBXOtJL2d1W1nl6fHk2/73duzFyXsdd/es6pX8jopWFFtaR86uKt7ZVvpmW2pQDZCAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBFJAwFuUKy4VBJ5Ofj3qrQoCkxBIdYGEd82c7Bo2GWSVXHwAWBc0erZbGn/ystHT1FRwAjI6+HvyX56UsabIc+8GVGD21Ld2iy+Bd3sE/QFp+N4zMtE+kIAaRihSXbhOffcPMp6s/UU4BBYhgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnYLhMa0JkJiXnYfH/tHYC6BhAeAJ7qGTPsO/cdiWmkx0/fGGTn5zScktGyLb7e0mS771L8+NWfwd7qQiY5BOf2d3aJ76cY7BQMBOfvjF2XoaFu8i45a3pQKfOu66/mTE5H0EAnBAHfIJMKWMhFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCA+AqExrUTGpeJzxJSCwHmBhAeA9dDJPt0l/p3k8rjFe4m9gHVRwyc65Oi9j0nXs8fi2hs4MOGX1kf3y5F7HpXRxp7pw476PHq2R4783aPSf6Ap6nbzWTmiejof+/v/FB3stiPp4K/27X7heNx8A/4p6X7ppBxVtr4EBZftsGKfCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkHkC2eUFpkpNdA2a8mQQSFWBpEykO97aL1nFF4Z+1vPg+gcuBIUvFkcHl8/94jXpefWUVFy5Ssq2LVVzDOdeVHF6GOeB/Y3GXLsXE5zU72lQ8xOXbFksdXdskfwlFRd1HPrukY7dh6X7uWNqHPmLKiJub5oam5Smn72qfE/Lwg9tl4KV1aax7q3uyD86Id1qvuTOPxyNy3m3ul+2QwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQuViC7qsj01vHWJE3XadorGQTmL5CUAPDouV4pWls3c3Q51UUycrpzJn+pL0bPdIt+6GBw8foFUrajXnIXlElWaZ4ReNa9jv3D4+ItPB8c1kMr+1XA19c/JkPH26R/f9P544lDwHXgwDnRj+zKQindukQFhJdIbk2xEZh2ud0yNTop7hyv6GPSQyFPDU/IRM+wDB5sNo5jTFlZTe2/f1vyFpXNubkOkMcjjZzqlBP/9LjyzJdSFWQv3abrVCLeYjX5uapTaNLzFo+19InuxTza0CV9+86K7ll9qcnonf3Im+IpyJ6zKD0kt5U0oo6r46lDUTcdePtc1PWsRAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgcwV0B0aZycd7yIhkA4CSQkAjzWZ/0HkVBcnxkbNKzt4qMV4zOzAJUbg1+V1izvbawRgdTA40b1rJ7uHpXP3EeNhHMs7x6GDvzoFfVOiex3LJcyF26t65iYz+fpHpeuZo8bD2K/LZQS2s1QgWHUNPm+revsGxuI/H/J0PXXQOx5JB+JbHtwbj6IoAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBDJQIKfWHM8aa7I2dWgGUlClNBNISgB45EyXiSVvQakpn9CM6tWre/vanqaPY8j2I4nfAagezH41v7N+kBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBjBFwu4zRUGfXZ0SNRktCIB0EwsfvTcBRDx1rN5Wat6TclCeDAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQKoI5NaViDvLM3M4Y639qdHhcOaIeIHA3AJJCQDr+VZnz0erx0z3Fp2fj3fuQ2MNAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskXKFhWZdrp0HFzZ0fTSjIIpJhAUgLAwamADB1rM1W9cE2tKU8GAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgVQQKAqJYw0ebE6Fw+IYELAkkJQAsD6Svj1nTQdUsmmRKU8GAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAdsFXC4p3rDQdBh9e8+a8mQQSGWBpAWAu186aXIo3bpEXNkXxk43rSSDAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAgA0CxRsWmKYy9Q2MygA9gG04E+zyYgWSFgDu398kE11DM8fpycuW8p3LZvK8QAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMBugcprVpsOofMPR0UCQdMyMgikskDSAsASDErrY/tNFpVXm/8BmVaSQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCJAt6SPCnZvNi0x5aH3zTlySCQ6gLJCwAriZaH96k48IU7JApWVEve4vJUN+L4EEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEHCCgOy+6PBfCZ8MnO2SQ4Z8dcOYzq4oXWnAS6jXe0i+9rzWY9lRzy0ZTngwCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACyRZwZXmk6vp1pt22/HqfKU8GgXQQSGoAWIM0/e9XTS5lO+slp6rItIwMAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskU0L1/s4pyZ3bpGxwLm950ZiUvEEhhgaQHgHteOim6u/x0crndUnfn1ukszwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggkVcCd7ZXa2zeb9tn8wB6ZGp00LSODQDoIJD0ArFHO/PAFk03ZrmWSt4S5gE0oZBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBJIiUH3TBskqzpvZlw78Nv38tZk8LxBIJwFbAsAdTxySoWNtM04ul0sWf/JdM3leIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJAMgezyAql97ybTrhrVlKa+3hHTMjIIpIuALQFgjXPyW7tNRoUrqqXiqlWmZWQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE/v/27gTIj6u+E/hvbs3oHt33YcmWfMk2xja+YiA2EIzBpAhQXgJ2NgGScsGyuyQFix2SDZuiqN2tpLJJnBAgYU0IjjHmyBoTwNgY4/vSaWxLsu5bGmkOzbXdY480I/3nPzPyjObf//501d//7tfv//q9z2tMwXf6NQECBAgQGE2B+clDiukS0L3b0ST43fTVn/ce+iaQOYExC4D3/eLF2PXva/uBzf+tN0ZN8lcWNgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKjLdB42RkxZdWCfpd54X/9MDqPtPUrc0AgSwJjFgCnSBu++G/9Xp5dVV8bi2++MqIiS4T6SoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkDWBdOnn+R+8pF+3Dzy1Obbf+3S/MgcEsiYwpgFw646Dkf4VRd9t4oo5MeeGC/oW2SdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwYgIVVZWx5GPXRHVD3bE2O1vbY83t9xw7tkMgqwJjGgCnaFv+5bHYmywH3Xeb/RurYvIFC/sW2SdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwIgILbrosxi+Z0a+tX/3v+6N5095+ZQ4IZFFgzAPgFG31Z/412nY3HfOrqKyIJb93dYw/Y+axMjsECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEXq/A7HetiulXndmvmV0/WRevfOOX/cocEMiqQEkEwEf3HYnn/vBb0dXRecyxsqY6zrj1rTFuzuRjZXYIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQInKrAtCT4nXvDhf1+3rxlX6z53Lf7lTkgkGWBkgiAU8ADT2yK9X/+g36W1ePrYtknr4uaqQ39yh0QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGI5A+vrRhf/hsn4/6WhqjWduvTPSbxuBchEomQA4Bd36rcdj0z893M+2tnF8nPVH74xxc6f0K3dAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCgCjW86I5Z+7JqoqDwejXW1d8az//Vf4shLu4fShDoEMiNw/C4vkS6/8KX7Ytu9T/XrTRoCn/npd8T4Zd4J3A/GAQECBAgQIECAAAECBAgQIECAAAECBAgQIECAQFGBWe84LxbfclVUVB2Pxbq7umL1Z++Ofb94sehvnSSQRYHjd3oJ9X7N7d+Jnfc9369H6XLQyz91XUy+cGG/cgcECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEThKoiJj/wUtj3nvf0O9UGv6u/fy9J2VR/So5IJBhgZIMgKOrO577o7tOehK4sqY6ln78zTH3PRdFVCT/qbURIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQOEGgeuK4WP6f3hYz37Ky35mujs5Y/Zm7Y9s9/Vej7VfJAYGMC1SXbP+TEHjN5+6J9v3NsejDVxzrZkUS/M5+5/kxYfms2PiVB+PonsPHztkhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIt8Ckc+f1ZEs1Uxr6QXQ2H43n/vBbsednG/qVOyBQbgKl+QRwH+UX/ucPY+2f3BvpX2T03SacOStW3v7umH7NWcnTwH3P2CdAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMibQFVDbSz87ctj2SeujRPD39adh+Lxm78s/M3bTZHT8ZbuE8B9JmTrvz4RR17aHed98X1RN3PSsTNV42pi4U1vimlXLI9X7nwkml/ec+ycHQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRwIJA8KTrt8Wcz9zYujJln6+cRt3y9fiueTV48e3XfkxFOOCZSlQCYC4FT+wFOb45H3/02c86c3xvQrl/ebjPGLp8eKz1wf+5/cFNu//WS07jjY77wDAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB8hOYvGpBzL3xoqifN/WkwaWry278u5/FS3c8EJG8etRGIC8CmQmA0wlpT/4y4+k/+HrMfe8b4sz/8raoHl/Xb56mXrQoplywMA4+vTl23vd8z1PD/So4IECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyLZAVUVMvXhJzHr7udEwv7HgWNKVZVf/t7vj0OptBc8rJFDOApkKgHsnYtvdT8TehzbE8v/8tpj99vN6i3u+KyorYkoaBCef5s17Y8+DG2L/Yxuj80hbv3oOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEsiMwbvbkaEyWep52xbKomVRfsOOdLUfj5eSp301fezi6kyeAbQTyKFBx//m3ZfqZ96kXL45ln7w2Jp83f8D56+7siqYNO+JAskR009rt0Za86NtGoBwENuyvi/au5OUGtpIQOHNKa9RUjX1X1if3RYf7Yuwn4rUenDW1Naorx74765L7otN9MfYT8VoPViT3RVUJ3Bdr99Ulqx/575FSuTFWNrZG8reMY76tSe6LbvfFmM9DbwfOTu6LihK4L1bvPfkdWr199H36Bc6Z1nr6L3rCFbuT/ydhzT73xQksY3ZYUdEdZzeO/R++p6sqrnVfjNl9cOKFK5P7YmUJ3BfJ/y0X6/b798WJ8zNWx1WV3bFi6tj/+6IjuS/Wuy/G6jY46brVyX1xVgncF+1JTrfhgH9fnDRBY1RQk9wXZ5bAfRHJk77pa0AnnTsvefBvcdTPnTKgSHdXV2z/3rPx0l/92KtCB1RyIi8CmQ+AeydqxltWxJLf/bWYdPbc3qIBvzsOt0bzxr3Rsm1/8i+BQ3F0d1Mc3X8k2g80R1dbx4C/c4IAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGBkBaom1EXt5IaonTY+amdOivo5k3ve6Vu/sDEqa4ovZps+BLjrR2vipb/9aRx5cffIdkxrBDIqUDYBcK//1EuWxMKb3hTTr1oeFafwaE1Xe0d0NLVFZ/PRSJcJ6Gxt7wmFu9qS7+RPkLqTT/rS8PRfKN3Jn6r1fHd2J09JJH/mmpalf+6a7KeHPf/ou9/byfScjQABAgQIECBAgAABAiMp0PM/QkayQW0RIECAAAECBAgQIJBrgd7liPquSpSU9RSn/+jdT5azqqisTD5JWe9+siRemtFUJN+VybKJ6aci/a6riaq66qgaVxOVDbVRPb6u53MqeU77oZbkid9n4pWvPxItW/fneqoMnsCJAmUXAPcOsG7mxJhzw4XJO4LPjQnLZ/UW+yZAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMigQPqA3v5HX44dP3g2dv5wtVVdMziHunx6BMo2AO7L17BoWsx484povOyMmLxqflQ31PU9bZ8AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAEBdp2HYr9T2yMvQ+/GLt/uj46kid/bQQIFBfIRQDcjyBZkmD80unJU8Gze74bkvXjx82ZEuNmTUrWlp8QlbXF15Lv15YDAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB1yXQcaQt2nY3RdvOQz3LOTdv3pe8z3dXNK3bEWkAbCNAYHgC+Us7k/dipS8BH+hF4FXJevM1k+ujeuK4qEk+VfXJevTJE8OVyXr06br0lemnd6369Dtdw/61dez7r3H/2vr36Zr3PWvhpxOT7Kf/fPWrZ98/CBAgQIAAAQIECBAgMCIC/ofGiDBqhAABAgQIECBAgACB1wSSPKV3e3U3OU6LkoPurnT/te9kPz3u7uyK7o7k09UVXe2dPfvpd1dbR3QdTT7Jd2fL0Vc/zUejvak1eZq3NdoPNPec772WbwIEXr9A/gLgQcw6k78yST82AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZE2gMmsd1l8CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKCwgAC7sopQAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKZExAAZ27KdJgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKFBQTAhV2UEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIHMCAuDMTZkOEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoLCAALiwi1ICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkTkAAnLkp02ECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgUFhAAF3ZRSoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcwJCIAzN2U6TIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcICAuDCLkoJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQOQEBcOamTIcJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQWEAAXNhFKQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBDInIADO3JTpMAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAoLCIALuyglQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA5gQEwJmbMh0mQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAYQEBcGEXpQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMicgAA4c1OmwwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECgsIAAu7KKUAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECmRMQAGduynSYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEChQUEwIVdlBIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBzAgLgzE2ZDhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCwgAC4sItSAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZE5AAJy5KdNhAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFBaoLlyslAABAgQIECBAgAABAgQIECBAgAABAgQIECAwugIz3rwi0s/ElXNi3KxJ0bxpbxxauz22f/fpOPTc1tG9uNYJECBQpgIV959/W3eZjs2wCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVIUqKiIZZ/89Vj8kSsL9q6rvSPWfv67PUFwwQoKCRAgQGBAAUtAD0jjBAECBAgQIECAAAECBAgQIECAAAECBAgQIDAaAlMuWDBg+Jter7KmOlbefkNUNdSOxuW1SYAAgbIWsAR0WU+vwREgQIAAAQIECBAgQIAAAQIECBAgQIAAgeMC4+ZOiUv/+aMRyRO4Y7Ft+urPY+OXH4xpVy4f9PKVNVXReOnS2P2TdYPWVYEAAQIEjgsIgI9b2CNAgAABAgQIECBAgAABAgQIECBAgAABAmUtkD5RWzO5YczGWD9/as+1e78H60j9vFfrD1bPeQIECBA4LmAJ6OMW9ggQIECAAAECBAgQIECAAAECBAgQIECAAIHTIHDw6VeGdJUDz2weUj2VCBAgQOC4gAD4uIU9AgQIECBAgAABAgQIECBAgAABAgQIECBA4DQI7PnZhuhq7yh6pdadB+PQ89uK1nGSAAECBE4WEACfbKKEAAECBAgQIECAAAECBAgQIECAAAECBAgQGEWBlq3744nf+Woc3Xu44FWaNuyIxz/85Yju7oLnFRIgQIDAwALeATywjTMECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAKAkcfOaVePjdfxmTVy2ISSvnREV1VXQcbo2mtdvj4HNboqut+BPCo9QtzRIgQCDzAgLgzE+hARAgQIAAAQIECBAgQIAAAQIECBAgQIAAgewJVNXXJoFvW+x96IWeT98RpGFwZW11dB19/SFwzeT6GL90RoybNzVqG8dH+/4j0bLtQLSmn+0H+1626P64OZOjfkFj1M9vjK7W9uju7IrWHQejedPeaD/QXPS3wzk5bvbkqJ0xMepmJp/pE5NgvDLadjUlfX21vwM9NT2ca6hLgEB5CwiAy3t+jY4AAQIECBAgQIAAAQIECBAgQIAAAQIECJSkwGV3/X5PINu0fkccWrst2nYeioZF02Ji8jTwhGUzY+/PfxXPfOIbPX2ffvWZsfRj1xQdxyvfeDS2f/fpY3UmnTsvFt50Wcy89pyorKk6Vt535+DzW+OVOx+Jnfetju6Ozr6nXt2vqIj02os+ckVMvWjRyeeTkq7kd3se2BBb7nos9j38YsE6gxVOOmduzLru3Jh53TlRP3dK0eppeL31rsdj67efjPZ9R4rWdZIAgXwKVNx//m0W0M/n3Bs1AQIECBAgQIAAAQIECBAgQIAAAQIECORQoLK+ZsijvuAvborGS5YUrf/oTXfE4Rd3Fa3Te7K7vetY0PqWx28bMJhN66eh8KMf+Nuen05JwteLv3JLbzMFv9NAdO0ff6fnXBoWL0k+FUmAO5Stad32eOoPvh5H9xx/J3H6hPJ5X3xfTwA8lDbSOmkf1v3Z96K7vUCYXKCRNOhe+cfvjsnnzS9wtnhRV3tHEgQ/ERu+dN8x0+K/cJYAgbwIeAI4LzNtnAQIECBAgAABAgQIECBAgAABAgQIECBAIBHoamkfskN3V9egdTubjw6rzUEbLFDh8IYd0d3dXTTQTZd5Tir0hLazkidph7NNXDEn3vhPvxtPfvRr0bJ5X8+TyRf8nw/1vJt4OO3Mu/GiGL9kejzxO18tGsqmyzov+b1fi8W3XFU0BC927cqa6ljwwUtjwlmz49lP/XOytPXILUNd7LrOESBQ+gKVpd9FPSRAgAABAgQIECBAgAABAgQIECBAgAABAgTyLJC+K7hl6/6iBBOSAHjxzVckSykPL/ztbTRdevmcP72x5/DsP3nPsMPf3namXLAwln78mt7Dgt9nf/49sfSj15xy+Nu30XRp6kvu/GjUTp/Qt9g+AQI5FhAA53jyDZ0AAQIECBAgQIAAAQIECBAgQIAAAQIECGRF4PC6HUW7Wj1xXCz7xLVF6wx2Mg1vL7rjwzH9qjMHq1r0/OKbr4wJy2cVrHPGrW+NOdevKnjuVAvT8Hrl52441Z/7HQECZSYgAC6zCTUcAgQIECBAgAABAgQIECBAgAABAgQIECBQjgLpe3pPx9Z46dLXfZmKqsqY8+4LTmpn+lXLY8l/vPqk8pEomHHNWTH7neePRFPaIEAg4wLeAZzxCdR9AgQIECBAgAABAgQIECBAgAABAgQIECCQB4Gm9cWfAB7IIH1HcUVtVVRWVw1UZUjlHU2tUTWhruh7iPs2NOvac+KFL93XtygWDzH83fPQC7Hpaz+PQ89vjbT/tTMmxux3nBeLP3JF1E4beKnnMz/9jtj5w9XR3d7Z77oOCBDIl4AAOF/zbbQECBAgQIAAAQIECBAgQIAAAQIECBAgQCCTAsN5Ari7syte/Ksfx54HN8ThDTujIgl/p1+9vGeZ5NrG8UMef9uepnjxL/899v3ypWjdfjCqGmpjwQcuiaW//5ZB3987bvbkaFg0LZo37e253uRVCyJdYnqw7Vd/8aPY+OUH+1U7urspNv/jw7HrR2vi4q/cEmnbhbbaKQ0x7fJlseeB9YVOKyNAICcCloDOyUQbJgECBAgQIECAAAECBAgQIECAAAECBAgQyLJA266mOHqgeUhDWPc/vt8Toqbhb7p1d3TG7h+vi8c+/PfRNcSnYztbjsbTt94Z2+55qif8TdtJn8bd+A8PxZrb70kPB93qkid3e7ehvPd3x/977qTwt/f36XfrtgOx+nPf7lt00v6s6845qUwBAQL5EvAEcL7m22gJECBAgAABAgQIECBAgAABAgQIECBAgEBmBdIANpKnXItt2+55MrZ+6/GCVVo274ttdz8R899/ScHz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QGDA8Rn/nWcJAKAiYRSH8A2GEcqRoKBFN69ETpjvXFQmqUZsd3n0kt+BvphRotrOfLTRQAdqh0yK6GcvH0XRo5quf6bf7w3siVln1dp4KUvnG39N9/xHDtGTWadrEAsG5cfdMG0SNwUy3lau7ipg9cm+ppi7bX8w63feJGOf4/75GlpADXF/eouZH1suSi5pG2FxdIsQoiV+1dlzCttf6hQu+9ry75dpyIAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACuS8Q8hkDwBa7LfcfiifIe4G0B4AtNuMXITw/bQqszpqShK31yNLLCQ7q9MTujiEpal18hGmBmk83EgDW/Vrz6/tSmu834YPM06DxXbtEz1mrU1ZHirtzRKpviNTmX6962475Dyyy11FZJGs+pZ9Jz3ubXAmqEcnWJP7YOatLwimlO9VI3nSWVXoe5ps3G26h02Wn8osc/YOC7p+8JN6hKcN1qCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggMDKEtAxg9hiUQPOKAiYXSD9AeD4YGIwtRHAOnCYqIwdSj7170LXav+nx8RRXrjQYTXvbkhmukaix+vedKVYHYn59B+GmZ5RcZ8bUoHcIQmqX4oUtVZLcVtNOOBssRtHSEdvELPRcOf2uADw5c2nG3Ppi5uvv5O6N6pnUqN1ExV357D0/fKITB67IIEZr1hd9vAI6oa3XbXoyOSafZtk8ImTBsdE90r1eMn6usuat9g3OSvnv/2UwTvVPtAeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE8kQgbupRizVxXCdPnpzHyGGBxNG+y324uABw3A8lEl7dlUQA2DsynfA6iRr4Rt2il2SKrcQlNTduSNg0pAKrHd97TkaeO2NoO/J8e7hesrFe1n32jQlHp5ZubJCitbXiPntxTlodiA6pPzjJjtTVQejhZ8+oOXI7ZPbCmPinZsVRUSR6xK+zslgmVCDXWugQPZ9xojL68nk5960nDem2dVrnsQMdMv5qt6z777dJ2ZaFU09XXrsmrQHgRP1f6Lg26vnJyzLy/Bnl41moGfsRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEBgBQnoeExsYQRwrAbbZhVI/88U4r8YKY6MtxU5E9oFZ3wJ2yxng8rdbQlHyurUyOe++eSc4G9sP6ZO9cvpLz0g/unEAcfq69dHT9UBV+9wcumJdXD89N8/IJ3fe1YmjnSHz9Pne/onZOpEnwp4tot/YkYq1HzGidIkzw5MzAn+RjulNkL6mb/xhARmF34flbvaYk8xzbbFYpG6N10hq96+Q+wqwE9BAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBOIH46U61SmCCGRDIO0jgEOBuJTPaj7WVIpvTI3Kbale9BR7WcGix5f7YEFdWcJLjqmRsnrEbaKi5/cdeOiYrH7X1Ys2jb/nHNcFzu747jOiA82JiiuJZ9J92PHVjyS6lEqNbZz3OfYEV21pOAW2nnfZbEWPhq69dYvoUcrd/7FfRl48a7Yu0h8EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBDIoMCcAHCKU51msKvcCoGoQPoDwHFfhPgvSrQnC2x4hxOndy6oL1/g7OR3l6sRsEWtVYueoNMoe4emxJlEsHTqdOKga+RmybR11pVGmie9Hj1wXiZf602qvQ7MJlMWC+4mc75uU9hYKWYMAEf6by8pkLZP7RO/mt944nB3ZDdrBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQWGkC8VOdxg98XGkePG9OCKQ9ABz0BQwQFvvCo0MNDV+veJJIdVy5d630/uLQfKcnt0+l/22+a094PtzFTpjpGg0HgJOZl3iqfWCxSxmOTZ8bSjinrx6dKqqfksIkyiMvJD+C1Vmtrp+hYq8oTNud9MjdOWnDlZsOXNsKneJSgfSybU1Ssq4uYR9aP3aDHP/iPRJIIkV3wovRAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHJOwBoX19LTYVIQMLtA+gPAcfPzWp2pBYD1iNtERacm1kE9PcftUkrZ1saEwV993chI3VDcqOb57hn/B2G+NpF9SU0YHp5L2TjReOT8hdYeNWdvsiU+UJ/seUtp5yhLXwB4pns0YZf67jss+p23fXqf2IsWnu9X97N0yyrR6bwpCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsPIErE5jKC0QF/daeSI8cS4IGD+1aehxYNZnuKrV5TDUE1WmTvVJUP2aIlFAtfXjN8iJv/yFhOcMTnTRmOP20gJpet/umD3zb872jol/cjZ80KOC0kUJ5iUu3lCfdJrjYjUaNVFqbM+ICoSnFv8Vz9Dk/A8zz17voGq7ZZ4DadjlKC9K6ap6Tt5V79i56Dm9Pz8oo/vPLdom9uDE0R4ZP9Ql1devj909Z7uoqYoA8BwVdiCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggsDIECACvjPecb0+Z/gBw3C8hbHG/lEgEqoOuo2oEZvXedYs21aM113/uTXLum0/IbN/4om0jB+0lLtnw+7dLwaqKyK4F15Mn+6LHvEmMrC3d2CCDjxyPnrPYhm6bqHgHkg/m6msF3F4JeZNPQ+BJ8vr6XXh1MPoyylSMZTKX0fMTF9SXLdq09g2bUwoA64sFvf5Fr6kP6pTRFAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEFiZAlaXMZQWP/BxZarw1GYXMH5q09Bbf9z8qXPmZ03inoOPvpYwAKwvU9hUKZu/+Hbpu/+IjDx3RgUqp+e9uqOySGpv2Sw1+zaJvXjhFMCRk0P+oAzEBHNnexMHmCt2tkj9W7ZK/wNHI5eZd63b1d1+5bzHYnfqEciplFAKcwXr6870JE6drNs51Py9nf/2XDjArOvJFv0HsmrPWqm6br3BMpnz3R3DCZuVbKyXVb+yU3rvOZiwrW5Q2FgplbvaErb1TcwkbEMDBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyE+B+LiWf+pittj8fFqeKl8E0h4A9o0bA2jxX5RkIN3nh2T67KAUr61N2NzqsMvqd+5UKYN3iD7P0z8hvolZsdit4Xl+nVXF4UCxxWZNeK1Ig8EnToSvE6nrUbCN778mYfC48T27xabmmL1wzytquOnc/M06/XDLx65X6Z8X74sO5g4+dSpy+7SsJ471yKyySjTStmR9vWz583dK1/97UcYPd837XLEdLFhdIbVv2KQCv+vEVugMH0rFXp+gA8Ah5ZcoTfaqO6+S4tYaGXrmlIy/2i3zTcTurCmRyt1rpOGOberdXOxPbH/jt2cvpBZ4jz+fOgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOSugK3YGEvwq5gTBQGzC6Q9AOyPG0GZzIjb+dDO/8vTsumP7xS7CqgmUywWixSvqQ0vybRfqI0ewdz7i0OGwzp18ODjr8mqt+0w7J+vogONdbdtEXfniMx0j4SDmM6aUilqq076WfRctZ4k01rP14ek9qn4dP8DR6T1YzckbO6sLJZ1v32raJvxV7tEj4j2T86IHnSsA+w6ZbMOtLrUc+r65RadBnxYjeiuuXFDwkuVbW0Uveh35B1zi/5DrLd1sNeh5nt2VpckvEZsg+n2wdgq2wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIILBSBCwSHdymH1kP2CNz6Ep5+bn9nGkPAPtUEC622FUQbilFj+Q9980n1Ty/b0w4YnYp15/vHB04PPeNJ+ZNdzyg0lLXqHlndVAxUdEThJesrwsvidrGHw/6A9J336vxu9NSH3m+XerefKUUJjEnsu6ADubrUcyZKBfuPqBSNrca/tAudl9tXlCn5g3WyxLLyP6zSafGXuItOA0BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRMKqDjIHrAYaQEpjwJM6NG2rJGIJsCi+ceXoaeeYanDFdxlBca6qlUJo9fkO4fvZTKKUtuq4O/7V99VCZP9M57Df0lb//HhyWdk33rX5J0/Msz4RTI83ZimXeGAkE58w8Pi3d0/rmTl/l2KV1OjwLu/MELKhV0MKXzltpYv9ee/3x5qadzHgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCOS4gKO8yPAEnqFJQ50KAmYVSH8AeND4ZbBfRgBYIw4+9poaCfyEpHOSbZ3aOBz8fW3+4G/kZeq5ac9+/XE112x6gpLd/7FfRl86F7ldRta+kelwENjvVr9iMVkZffGsnP2nx8IpndPZtYDHJ+1feUR8o8bR6+m8J9dGAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABcwk4KuICwAPGmJe5ektvELgkkPYAcHDGZwjWWu02WWoa6Ei3R18+L8e/eI+MHeyI7FqWdSgYksEnTsixP7lbJhMEfyM31KOST/zVvTJ9dvnmivWooPkZNbpYB7uzUWYvjMlrf/Hz8Py+y3n/8aPdcupLD4h3yDgqPJV7jB/W13hQzak8nMppSbedOjMgJ9SzT53qT/ocGiKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggED+CTgq4wLAcYMe8++JeaJ8EUj7HMAaarZ3XEo2XJor11lbKjql7+UUff7Zrz0u5TtapPrGDVJ25WrRweWlFD3Prg7kXrjnoMx0jaR8CX3Oyb+5T2r2bZJVb79K4lMCJHtBnXZ4UM0t3Kvm/A35AsmelpZ2eiSwHgVdoebdbXzPbnGpd7aUokdH67l0+x86KrM9Y0u5xJxz3CrYfuIvfxF+99q7qKV6TptUd0y3D8jAI8dl9MB5NYt7qmfTHgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBPJNwFVjjI3M9o3n2yPyPHkqkJEAsLtzRAWA66OErpoS0UG85SjjhzpFL7Yip1Rc3SqVu9ukYHWFOMoKxWKbf4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tl+313S97CMlOdxpr75NS3d4d13TdtRAYBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMDxAl1PH5GJtgFZ9sXrxJOTNeNRe9tmcXk9cvAvHxQJBGeW8wKBTBFIudsbssoLZNv/+kxY8HfoeLsc/6ffE/zNlJZHPRBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBBAsMHm4xphT1DY2b9lRz0wZZf++dpmVkEMgUgZQKALtzvLLlu5+SgvpKk2/f3rNy6ltPSWDMZ1pOBgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIFoAqNne+TE138nE11Dps0W3LlVVvzZDaZlZBDIBIGUCgBv+PsPS8nGhSbX/gNNcuY/npeg3zxGu2kjMggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjMIaCDvye++YRM9o2Ytlj2f1wjdXdsMS0jg0C6C6RMALj+c1dLzU3rTZ7DpzqN4K8EGX/dBEMGAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEBgXgK+3hE59e3dMjU6aXrfunvukKK1daZlZBBIZ4GUCACXbl8qK/7P602O4239cvq7T0vQN2VaTgYBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBixEYb1Hxp3/7gwRmxZ/c2V7Z9M8fE29R7sUUyXsQSDkB2wPA3sIc2fj1D4vLc+FQ/Goi7pPfCr8DI+X0OCAEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIG0Ehg+0SGNP37JdMz5i8plzVfea1pGBoF0FbgQdbWpBqv/6jbJrSmZ2XswEJQzP3xBdDd8EgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALxFujbc0Y6/3DEVGzd7ZdJ1Q3rTMvIIJCOArYGgMvftVwWvH+rya3jyYMydKTVtIwMAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAvEUaHlwr4w29ZiKXPvV94kevZaEQDoL2BYAdnk9qiv97Sa7seY+aXvsgGkZGQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTiLRCcCsjZ+16UgH9qpuicikJZ/l+vn8nzAoF0FLAtALz4U5dLQX3ljJke+rnxJy+J/sdGQgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCDRAuMt/dL++7dNu1n8R7skf9mFGJZpJRkE0kDAlgCwpyBH6j97tYmn+4XjMtpo7mZv2oAMAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnEW6Hj8kEx0Dc2U6vK4ZeX/dcNMnhcIpJuALQHgpXe9W7JL82espkYnpfWRN2fyvEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgGQJBNQR084N7TLuqvnG9FK1fYFpGBoF0EUh6ANidlyWLP7HL5NPx5CHRQWASAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskWGNjfJCMNXabd1n/2KlOeDALpIpD0APDCD26XrJILvX/9w+PS+fSRdPHiOBFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBDJQoPWx/aZaVd+wTvIWl5uWkUEgHQSSHgDWE2fPTl3PHpPApH/2Il4jgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkFSBoSOtMtrUM7NPl9stiz62cybPCwTSRSCpAeCyHfWSv7Rixibgm5KuZ47O5HmBAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAgF0CnU8dNu267o7LxOX1mJaRQSDVBZIaAF74ke0mj/79jeIfnjAtI4MAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIICAHQJ9+86Kf+RC7Cq7rECqb1xnx6GwTwQuWiBpAWBPfrZU37DedKDdL5ww5ckggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggYJdA0B+Q3ldOmXa/4P1bTXkyCKS6QNICwJVXrxZ3tnfGY6JzUIaPt8/keYEAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIICA3QLdL500HULZrmXiKcgxLSODQCoLJC0AXP6u5SaHvn2NpjwZBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBOwWGG/tl7G2/pnDcGd5pGxH/UyeFwikukDSAsCl25aaLAYPt5jyZBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIBYGhQ+Y4Vtl2c5wrFY6RY0BgLoGkBIB1t/j8pRUzxxCcCshIQ9dMnhcIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIpIrA8MkO06EUrV9gypNBIJUFkhIALlpdIy6Xa8ZhrKVPgr6pmTwvEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEgVgZGz3aZDKVpTa8qTQSCVBZITAF5bZzIYa+4z5ckggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkCoCvr5R8Y9MzBxOVnGe5NaVzOR5gUAqCyQlAJy3pNxkoCfPJiGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQqgLjbeZ4Vv6SC9Odpuoxc1wIaIGkBIBD/0FMdA2hjwACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDKCkx0muNZoR0eU/bAOTDHC3iTIZC/2NwDONEB4OzKQsldUCrZpfniLck7/6y65kswKL7BcfEPjolvQD9GZfhEh0yNTiaDgX0ggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgikiUBoPCs03pUm1eAwHSiQlABwTk2xiXai23zHhGnlRWayyvKlbEe9lO1cLgXLKi2XEpwKyPDJDunf3yQDB5pksnfE8nvZEAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIDMFJruHTRXLrWUOYBMImZQVSHgA2FuUK57crBmAqQmfBMZ8M/lLfaF7+y751BVStGGBuFyueRfn8rilaG2d8Vj08Z3S/fwJaX30TXoFz1uSNyCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACmSMw2W/uNJhTVZQ5laMmGS2Q8ABw6D8GPfRyvFLle9bKwg9vF0/OhQDzpZTtcrulSpVZtrNeBYH3S/cLx9Ww0ZdSIu9FAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIRwF/vzmmlV1NADgdz6MTjznhAWDdQ3d2Cv3HMnud1deeghxZ/qfXGb12rb5nPtt5C3NlyaevkILlVdL4k5cIAs8Hj20RQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgQwQCO3UmFNujnllQBWpQoYKuBNdr6ziXNMu/CPjpvy8Mx6XLP9i4oK/s4+n4t0rZel/uUpk/iNLzy6G1wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAmkmMDU2KcGpwMxRe/KzxeX1zOR5gUCqCiQ8AOwtzjfV3T8yacrPN7Pkk++SojV1833bRW+vg8CL1T5JCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACzhKYGjXHtbJK8pwFQG3TUiDhQ0CH/kOYGp24aKjK69ZI5TVrLvr9F/vGquvWSu9rDTJyunPeRWSXF0hOTbFkFeeJV10U9LO4XeIfHBff4Jh6HpPJ7mEZbx+Yd9kX84bsikLJW1wuubXFxnHoeY99vSMy0tgt4y39sYt0uSR/SblklRVIVqmqT2m+eHKzRA+DMKnKmewdlon2QfEPXWJP79hHYnmLLHUO8pdWSI4ajlzfmWMcb/+oTPaNyqiqt089kxBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBUAG/CgB7iy6MdutVI99O9gyHbkYegZQSSHgA2FuQbarw1KjPlLea0YG7BXdutbq50SV/8Eir9O87K+MdKiCpAq2uLI9kq/HZsysKpPSyJVK8caHl8hZ9fKcc/4ffWdo+d2GplG5bKqVbl0q+CrZaSRNdQ9K/v0k9GmXkVPRAc8lli2XJXe+OWmz/m41y7uevzWyTVZZv+JVfsVJcKgAdmrpfOilNP305dPFMvnB1jZTtWCal25eeD2LPrAl/EQwEZOCtc9L17DEZOtoWvsFFLKl932VS9Z61Ud959r4XZehw68w2RevqpPqG9VK8aVHEOusNg4GgDKl20vXCcRlQ/iQEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAYFpADwM9O3kLcmZneY1ASgokPADsVr1DZ6fA5MUFgMsvXybewgt3WMwuM/T14KEWaVTBTJ/q5Rmapnu5dj93XHSgtu59W1Rgsz50s7B8wbIqKdu1TPreOBO2bnqB7g276I92Sdn2+ulFlp9zqoqk5uYNxkP3NG7636/KWHNfxPfrnrZGT+KIa88vLFheNbM2v75CVn35VvHkmM/FzAZRXuTUlshSFWwuXFUTZSvzKt2rWAe/9WOspU8avv+sTKgg/KUk3cM4Vp3zF5WfDwCreaIXf2yXVF2/LuYudTBc3wigHz2vnZamn70iwcmpmO9jAwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEMh8gcCE31RJPcooCYFUF0j4HMCh/xACFxlcsxLM09htv3tLTn17d8Tgb+jJ0MHgMz94TrqeOxa6KmK+bNfyiMv1Qn186//fD15U8De00IIV1bL2b++QhR/dIS5P+Ckaa+2TgC96kDJXBW5FdfTNVsMer/izGy8q+Fvz3k2y7p73zyv4G1qXvIVlsuZvbpeiDQtCV80rP9bUE3P73AWl4sr2yOr/+1ZLwd/QAivetULW/NV7jZ7ioevII4AAAggggAACCCCAAAIIIIAAAggggAACCCCAgPMEApMhAeA8AsDOawXpV+Pw6GKc6xAeADb/Q7GyO92DNX9JRcxN+w80Sduj+2NuF7qBHiq5d8/cPXunty9cWT390vRce/tlsvgTlxtzy5pWXEJGB35rbt4o9Z+72gjkmoqaCsq4CgJHS+5sr5rztkiW/cm1MXvORiqn7gNbZeEHt4tbDZt9qcmbnyMr//xG1SN4yUUXNaaC9cGpQNT359aVyuKP77qkgLVuZws/vD3qfliJAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACzhAIDQC7L2K0VWdIUctUEkh4AFjP3Ts7Bf3Rg3izt51+rXuRxkp63tnZc97G2j50fftvD4QuCsvrcd1Dj6XiqlWyQAVLE5XKdi6TRSqoGZpGG2P3iK26YZ3MHgo6tIy58hVXr5Y6FdSOZ9LDQi/543erYbwvbmz8oH9KxtsHoh5SwbJKqbxmTdRtrKzUvbkLVlwYQtvKe9gGAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEMk8gNK4VGvfKvBpTo0wQSHwAOGQI42AgOG83PYxxrKTn/Y0052+s902vH28bkOETHdPZOZ+9JXkz63LrSlRQ84qZfKJeVN+wXkpD5hUebeqNuTv9vvmmnJpiWfKpd1l+mx77Xt/9MjUee25nb1GuLP7UxXuNWhgG2vKBR9nQ5XJJxZWromzBKgQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEHCCQDBojmu5PGr+TRICKS7gTfTxudwh/xBUT935puzy2AHgARUAvtR06rtPRx3GWQev/YNjM7upuXWT6J6tsZK+O2TwWKuMnumWsXO9oi8Weo7e/GVVUryuTjx52bGKkNrbNkn/vrMz211KMFTXI+Dzm+YFnh7CoObmDRHnHZ7Z8TsvBg+3SNt/viUjpzpnVules3V3blV1mnu+37Id9dL5dJWMnO6aeZ/VF9pOLiJ+PNkzbASoc6qL1JDW1pp86balRo/yWMNOWz12tkMAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIE0FAiZnlJP4UlCINUFrEXDLqUWIQHgkBslLJVspQewr3fEUlnRNgqoXqz6YSVlleVL+a7lMTfVgdWG7z8ruofy7DQg54ysHlJ65ZdujjlPb/7SCilSweKho23G+8aa+0QPe20lAK3fEFBDKHc8cUj632w0hlIO+qbEneOVrLICyVZ1GVHBad1Dt/yKFUb50f7X+cxRaf7l62Gb6KDuqX/dLfV/co2Uq6Gr50p6WOuLCQBb6fU8vU8d4D73yzeUe7P4+kbPL1ZtseamDVL3/i2i50iOlozhvheViZWhtqOVwzoEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIX4HQuFZYx8f0rRpHnsECCb9NITgV0jU+JCBsxdajApWx0nQP1ljbxWu97iHq8kbn08Min/r27rDg7+xjGGvpkxP/+HuZtBDALpsVcNYB3Mnu4dlFzfl6rK1fjn3tN9L22P7zPZDVe3XSwzdPqHl1dVBZB75LLlscs4fsZN+ItKn5kj352ZEfeVnS+tBeo4fxXAcUOpz1XNuFLh9XVlaS7rV75t+fk54XT1wI/uo3qp7PHU8ekrM/etFKMZI1a7hvS29gIwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEMgogdCAb2jcK6MqS2UyRiB2ZPVSqxo65PNFBIAnVQ/O/KXRDySr+MLcvNG3jM/anOrimAX1qSGbrcwrPNE5JLpX7aKP7Ihaph7CeHayMp+yHm668ccviZ7jOFbKqTKXH2n7bNVj+LJ//USkVZaXZZfmix4uer69gAPvBK5j7ajl4X0y8HbznJvpXtBDJ9qlaHXtnNvoFVnqOEkIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDgXIHwAPD8pzp1rh41t0sg4QFgPUzx7BT6D2X2urle6zlcY6XchaWxNom5vuKqVVKwvCrqdp1PH5Hx1n6xEiwdOdERtazZK4dPxt7Wyj5nl6lf97xyyph7OHR5pPzFlB+pHCvLcutK5x0AtlKu3iZ0uO1I7xs+FjsA7MnPifRWliGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggIBTBEI6NobGvZzCQD3TSyDhAeDA5PnhhqdZ3F7P9EvLz1YCwOWXr5DWR/aLhA7GbnEvetLuhR/absyDG+0tAweajABwdnlBtM2MdSMNXTG3md5gtLE75py+Ro9UfaFRQxlbTbq3q9WUZaFOVsuKtV2ihlfWw26PqyGvY6XxzsFYm7AeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEHC7gzjLHtayOVupwNqpvs0D0SWzjcHA6IDc7uSzM5zt7e/3ayly3OiBbtrM+9K2W8yVblsQM/urhlIdPdRplBv3mwHakHel5cq0mT06WiEsFd6OkoF/1pp5H8FcXNamGl7aa9DzAyUpZJYkZXnnsXK+6CSB2LaZGJmJvxBYIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDgaAF3trkv5dTYpKM9qHx6CCQ8ABwYMwcVPSH/UKwwDanheqcmzOVEet+ST18hOTWx5+YNfW+2mvt20cd3hi4Oy4+19MnU6Pl/2Hre3lipcFVNrE1m1hesrFbx3+gB4Mnu2PucKVC90AHriXm8Z6JrfuXP3td8X3uLc+f7Fkvbc+eNJSY2QgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQsCoQHg0LiXhSLYBIGkC5hvW0jA7kPvhHBfRA9gXUbvaw1Sde2aqEfoycuWlf/tZjn7oxdk5OT5nrpR36BW6uDv6i/fKtllsYd0Hj7aNlOclcBq0foF0vHkoZn3RHtRvG5BtNXGuonu2HMhzy5Euxm9hmcvjPLaSlBbv737xROWhlmOsisZOdMdbTXrEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHbBULjWqEj39p+gBwAAhEEEh4A9g+bh9qdz7DIs4+365mjMQPAevucikIV0L3NCFL2vHJKRueYhzdvcblU37heynYtEyvzEgcm/NKx+/DMIY019828nutFsQoAL/qjXdL8qzfm2sRYXqkC3gVYywAAMjdJREFU21XXr4u6jV451qyGN55PsjAU8uziRpt6ZmfnfF2wvEra/vMt8fWOzLlNpBVZZflSefVqKb9ihfT/jycibcIyBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCBlBELjWqFxr5Q5UA4EgVkCCQ8A+wbHZu1OxFOQY8pbzYy39svgkVbRQdVYyeV2GcFi3WN4UgUpJzoHRR+Hy+sxevpml+fLfOeg7XjqkPj6Rmd23b+vUXwfHZWs0uhz2VbfsF50z+SWB/dI6EVB3zWi1y/44LaZcud6EZwKSPdzx+daHZflw8fbZVTNoZuvguPRUt7CMll/753S8vA+6Xv9jIT28ja9Vw1rXbS2VqquWyslWxaLy/3OqOPqHJEQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgVQW8IbEtXwD5rhXKh87x+ZcgcQHgEP+IXjzsy9au/HHL8nar74vZtB19g6yywtEPy4lTfaPSscT5qGcdUC28+kjsvAjO2IWXfHulaIfetjosXN94vK4JLuySHJrS1RA1FogtG/PGSOYHXNnl7hBx+MHZdnnr41Zig5qL/nUFbL445fL0Il2Y0ho/9C4Me9wdnmh5KihtbMr1bN67fImfKrpmMfLBggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIDAvARUJzd3btbMW4LBoOhYCAmBVBdIQgD4Qq9ZjeEtyrtoE58KxJ7+t2dk9V/eKu6shB+6cZz+kQk5/d2nJTDpDzvuruePS+V1ayRHBXOtJL2d1W1nl6fHk2/73duzFyXsdd/es6pX8jopWFFtaR86uKt7ZVvpmW2pQDZCAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBFJAwFuUKy4VBJ5Ofj3qrQoCkxBIdYGEd82c7Bo2GWSVXHwAWBc0erZbGn/ystHT1FRwAjI6+HvyX56UsabIc+8GVGD21Ld2iy+Bd3sE/QFp+N4zMtE+kIAaRihSXbhOffcPMp6s/UU4BBYhgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAnYLhMa0JkJiXnYfH/tHYC6BhAeAJ7qGTPsO/cdiWmkx0/fGGTn5zScktGyLb7e0mS771L8+NWfwd7qQiY5BOf2d3aJ76cY7BQMBOfvjF2XoaFu8i45a3pQKfOu66/mTE5H0EAnBAHfIJMKWMhFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCA+AqExrUTGpeJzxJSCwHmBhAeA9dDJPt0l/p3k8rjFe4m9gHVRwyc65Oi9j0nXs8fi2hs4MOGX1kf3y5F7HpXRxp7pw476PHq2R4783aPSf6Ap6nbzWTmiejof+/v/FB3stiPp4K/27X7heNx8A/4p6X7ppBxVtr4EBZftsGKfCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkHkC2eUFpkpNdA2a8mQQSFWBpEykO97aL1nFF4Z+1vPg+gcuBIUvFkcHl8/94jXpefWUVFy5Ssq2LVVzDOdeVHF6GOeB/Y3GXLsXE5zU72lQ8xOXbFksdXdskfwlFRd1HPrukY7dh6X7uWNqHPmLKiJub5oam5Smn72qfE/Lwg9tl4KV1aax7q3uyD86Id1qvuTOPxyNy3m3ul+2QwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQuViC7qsj01vHWJE3XadorGQTmL5CUAPDouV4pWls3c3Q51UUycrpzJn+pL0bPdIt+6GBw8foFUrajXnIXlElWaZ4ReNa9jv3D4+ItPB8c1kMr+1XA19c/JkPH26R/f9P544lDwHXgwDnRj+zKQindukQFhJdIbk2xEZh2ud0yNTop7hyv6GPSQyFPDU/IRM+wDB5sNo5jTFlZTe2/f1vyFpXNubkOkMcjjZzqlBP/9LjyzJdSFWQv3abrVCLeYjX5uapTaNLzFo+19InuxTza0CV9+86K7ll9qcnonf3Im+IpyJ6zKD0kt5U0oo6r46lDUTcdePtc1PWsRAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgcwV0B0aZycd7yIhkA4CSQkAjzWZ/0HkVBcnxkbNKzt4qMV4zOzAJUbg1+V1izvbawRgdTA40b1rJ7uHpXP3EeNhHMs7x6GDvzoFfVOiex3LJcyF26t65iYz+fpHpeuZo8bD2K/LZQS2s1QgWHUNPm+revsGxuI/H/J0PXXQOx5JB+JbHtwbj6IoAwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBDJQIKfWHM8aa7I2dWgGUlClNBNISgB45EyXiSVvQakpn9CM6tWre/vanqaPY8j2I4nfAagezH41v7N+kBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBjBFwu4zRUGfXZ0SNRktCIB0EwsfvTcBRDx1rN5Wat6TclCeDAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQKoI5NaViDvLM3M4Y639qdHhcOaIeIHA3AJJCQDr+VZnz0erx0z3Fp2fj3fuQ2MNAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskXKFhWZdrp0HFzZ0fTSjIIpJhAUgLAwamADB1rM1W9cE2tKU8GAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgVQQKAqJYw0ebE6Fw+IYELAkkJQAsD6Svj1nTQdUsmmRKU8GAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAdsFXC4p3rDQdBh9e8+a8mQQSGWBpAWAu186aXIo3bpEXNkXxk43rSSDAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAgA0CxRsWmKYy9Q2MygA9gG04E+zyYgWSFgDu398kE11DM8fpycuW8p3LZvK8QAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMBugcprVpsOofMPR0UCQdMyMgikskDSAsASDErrY/tNFpVXm/8BmVaSQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCJAt6SPCnZvNi0x5aH3zTlySCQ6gLJCwAriZaH96k48IU7JApWVEve4vJUN+L4EEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEHCCgOy+6PBfCZ8MnO2SQ4Z8dcOYzq4oXWnAS6jXe0i+9rzWY9lRzy0ZTngwCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACyRZwZXmk6vp1pt22/HqfKU8GgXQQSGoAWIM0/e9XTS5lO+slp6rItIwMAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAskU0L1/s4pyZ3bpGxwLm950ZiUvEEhhgaQHgHteOim6u/x0crndUnfn1ukszwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggkVcCd7ZXa2zeb9tn8wB6ZGp00LSODQDoIJD0ArFHO/PAFk03ZrmWSt4S5gE0oZBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBJIiUH3TBskqzpvZlw78Nv38tZk8LxBIJwFbAsAdTxySoWNtM04ul0sWf/JdM3leIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJAMgezyAql97ybTrhrVlKa+3hHTMjIIpIuALQFgjXPyW7tNRoUrqqXiqlWmZWQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE/v/27gTIj6u+E/hvbs3oHt33YcmWfMk2xja+YiA2EIzBpAhQXgJ2NgGScsGyuyQFix2SDZuiqN2tpLJJnBAgYU0IjjHmyBoTwNgY4/vSaWxLsu5bGmkOzbXdY480I/3nPzPyjObf//501d//7tfv//q9z2tMwXf6NQECBAgQGE2B+clDiukS0L3b0ST43fTVn/ce+iaQOYExC4D3/eLF2PXva/uBzf+tN0ZN8lcWNgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKjLdB42RkxZdWCfpd54X/9MDqPtPUrc0AgSwJjFgCnSBu++G/9Xp5dVV8bi2++MqIiS4T6SoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkDWBdOnn+R+8pF+3Dzy1Obbf+3S/MgcEsiYwpgFw646Dkf4VRd9t4oo5MeeGC/oW2SdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwYgIVVZWx5GPXRHVD3bE2O1vbY83t9xw7tkMgqwJjGgCnaFv+5bHYmywH3Xeb/RurYvIFC/sW2SdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwIgILbrosxi+Z0a+tX/3v+6N5095+ZQ4IZFFgzAPgFG31Z/412nY3HfOrqKyIJb93dYw/Y+axMjsECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEXq/A7HetiulXndmvmV0/WRevfOOX/cocEMiqQEkEwEf3HYnn/vBb0dXRecyxsqY6zrj1rTFuzuRjZXYIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQInKrAtCT4nXvDhf1+3rxlX6z53Lf7lTkgkGWBkgiAU8ADT2yK9X/+g36W1ePrYtknr4uaqQ39yh0QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGI5A+vrRhf/hsn4/6WhqjWduvTPSbxuBchEomQA4Bd36rcdj0z893M+2tnF8nPVH74xxc6f0K3dAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCgCjW86I5Z+7JqoqDwejXW1d8az//Vf4shLu4fShDoEMiNw/C4vkS6/8KX7Ytu9T/XrTRoCn/npd8T4Zd4J3A/GAQECBAgQIECAAAECBAgQIECAAAECBAgQIECAQFGBWe84LxbfclVUVB2Pxbq7umL1Z++Ofb94sehvnSSQRYHjd3oJ9X7N7d+Jnfc9369H6XLQyz91XUy+cGG/cgcECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEThKoiJj/wUtj3nvf0O9UGv6u/fy9J2VR/So5IJBhgZIMgKOrO577o7tOehK4sqY6ln78zTH3PRdFVCT/qbURIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQOEGgeuK4WP6f3hYz37Ky35mujs5Y/Zm7Y9s9/Vej7VfJAYGMC1SXbP+TEHjN5+6J9v3NsejDVxzrZkUS/M5+5/kxYfms2PiVB+PonsPHztkhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIt8Ckc+f1ZEs1Uxr6QXQ2H43n/vBbsednG/qVOyBQbgKl+QRwH+UX/ucPY+2f3BvpX2T03SacOStW3v7umH7NWcnTwH3P2CdAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMibQFVDbSz87ctj2SeujRPD39adh+Lxm78s/M3bTZHT8ZbuE8B9JmTrvz4RR17aHed98X1RN3PSsTNV42pi4U1vimlXLI9X7nwkml/ec+ycHQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRwIJA8KTrt8Wcz9zYujJln6+cRt3y9fiueTV48e3XfkxFOOCZSlQCYC4FT+wFOb45H3/02c86c3xvQrl/ebjPGLp8eKz1wf+5/cFNu//WS07jjY77wDAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB8hOYvGpBzL3xoqifN/WkwaWry278u5/FS3c8EJG8etRGIC8CmQmA0wlpT/4y4+k/+HrMfe8b4sz/8raoHl/Xb56mXrQoplywMA4+vTl23vd8z1PD/So4IECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyLZAVUVMvXhJzHr7udEwv7HgWNKVZVf/t7vj0OptBc8rJFDOApkKgHsnYtvdT8TehzbE8v/8tpj99vN6i3u+KyorYkoaBCef5s17Y8+DG2L/Yxuj80hbv3oOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEsiMwbvbkaEyWep52xbKomVRfsOOdLUfj5eSp301fezi6kyeAbQTyKFBx//m3ZfqZ96kXL45ln7w2Jp83f8D56+7siqYNO+JAskR009rt0Za86NtGoBwENuyvi/au5OUGtpIQOHNKa9RUjX1X1if3RYf7Yuwn4rUenDW1Naorx74765L7otN9MfYT8VoPViT3RVUJ3Bdr99Ulqx/575FSuTFWNrZG8reMY76tSe6LbvfFmM9DbwfOTu6LihK4L1bvPfkdWr199H36Bc6Z1nr6L3rCFbuT/ydhzT73xQksY3ZYUdEdZzeO/R++p6sqrnVfjNl9cOKFK5P7YmUJ3BfJ/y0X6/b798WJ8zNWx1WV3bFi6tj/+6IjuS/Wuy/G6jY46brVyX1xVgncF+1JTrfhgH9fnDRBY1RQk9wXZ5bAfRHJk77pa0AnnTsvefBvcdTPnTKgSHdXV2z/3rPx0l/92KtCB1RyIi8CmQ+AeydqxltWxJLf/bWYdPbc3qIBvzsOt0bzxr3Rsm1/8i+BQ3F0d1Mc3X8k2g80R1dbx4C/c4IAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGBkBaom1EXt5IaonTY+amdOivo5k3ve6Vu/sDEqa4ovZps+BLjrR2vipb/9aRx5cffIdkxrBDIqUDYBcK//1EuWxMKb3hTTr1oeFafwaE1Xe0d0NLVFZ/PRSJcJ6Gxt7wmFu9qS7+RPkLqTT/rS8PRfKN3Jn6r1fHd2J09JJH/mmpalf+6a7KeHPf/ou9/byfScjQABAgQIECBAgAABAiMp0PM/QkayQW0RIECAAAECBAgQIJBrgd7liPquSpSU9RSn/+jdT5azqqisTD5JWe9+siRemtFUJN+VybKJ6aci/a6riaq66qgaVxOVDbVRPb6u53MqeU77oZbkid9n4pWvPxItW/fneqoMnsCJAmUXAPcOsG7mxJhzw4XJO4LPjQnLZ/UW+yZAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMigQPqA3v5HX44dP3g2dv5wtVVdMziHunx6BMo2AO7L17BoWsx484povOyMmLxqflQ31PU9bZ8AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAEBdp2HYr9T2yMvQ+/GLt/uj46kid/bQQIFBfIRQDcjyBZkmD80unJU8Gze74bkvXjx82ZEuNmTUrWlp8QlbXF15Lv15YDAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB1yXQcaQt2nY3RdvOQz3LOTdv3pe8z3dXNK3bEWkAbCNAYHgC+Us7k/dipS8BH+hF4FXJevM1k+ujeuK4qEk+VfXJevTJE8OVyXr06br0lemnd6369Dtdw/61dez7r3H/2vr36Zr3PWvhpxOT7Kf/fPWrZ98/CBAgQIAAAQIECBAgMCIC/ofGiDBqhAABAgQIECBAgACB1wSSPKV3e3U3OU6LkoPurnT/te9kPz3u7uyK7o7k09UVXe2dPfvpd1dbR3QdTT7Jd2fL0Vc/zUejvak1eZq3NdoPNPec772WbwIEXr9A/gLgQcw6k78yST82AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZE2gMmsd1l8CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKCwgAC7sopQAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKZExAAZ27KdJgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKFBQTAhV2UEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIHMCAuDMTZkOEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoLCAALiwi1ICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkTkAAnLkp02ECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgUFhAAF3ZRSoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcwJCIAzN2U6TIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcICAuDCLkoJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQOQEBcOamTIcJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQWEAAXNhFKQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBDInIADO3JTpMAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAoLCIALuyglQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA5gQEwJmbMh0mQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAYQEBcGEXpQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMicgAA4c1OmwwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECgsIAAu7KKUAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECmRMQAGduynSYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEChQUEwIVdlBIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBzAgLgzE2ZDhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCwgAC4sItSAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZE5AAJy5KdNhAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFBaoLlyslAABAgQIECBAgAABAgQIECBAgAABAgQIECAwugIz3rwi0s/ElXNi3KxJ0bxpbxxauz22f/fpOPTc1tG9uNYJECBQpgIV959/W3eZjs2wCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVIUqKiIZZ/89Vj8kSsL9q6rvSPWfv67PUFwwQoKCRAgQGBAAUtAD0jjBAECBAgQIECAAAECBAgQIECAAAECBAgQIDAaAlMuWDBg+Jter7KmOlbefkNUNdSOxuW1SYAAgbIWsAR0WU+vwREgQIAAAQIECBAgQIAAAQIECBAgQIAAgeMC4+ZOiUv/+aMRyRO4Y7Ft+urPY+OXH4xpVy4f9PKVNVXReOnS2P2TdYPWVYEAAQIEjgsIgI9b2CNAgAABAgQIECBAgAABAgQIECBAgAABAmUtkD5RWzO5YczGWD9/as+1e78H60j9vFfrD1bPeQIECBA4LmAJ6OMW9ggQIECAAAECBAgQIECAAAECBAgQIECAAIHTIHDw6VeGdJUDz2weUj2VCBAgQOC4gAD4uIU9AgQIECBAgAABAgQIECBAgAABAgQIECBA4DQI7PnZhuhq7yh6pdadB+PQ89uK1nGSAAECBE4WEACfbKKEAAECBAgQIECAAAECBAgQIECAAAECBAgQGEWBlq3744nf+Woc3Xu44FWaNuyIxz/85Yju7oLnFRIgQIDAwALeATywjTMECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAKAkcfOaVePjdfxmTVy2ISSvnREV1VXQcbo2mtdvj4HNboqut+BPCo9QtzRIgQCDzAgLgzE+hARAgQIAAAQIECBAgQIAAAQIECBAgQIAAgewJVNXXJoFvW+x96IWeT98RpGFwZW11dB19/SFwzeT6GL90RoybNzVqG8dH+/4j0bLtQLSmn+0H+1626P64OZOjfkFj1M9vjK7W9uju7IrWHQejedPeaD/QXPS3wzk5bvbkqJ0xMepmJp/pE5NgvDLadjUlfX21vwM9NT2ca6hLgEB5CwiAy3t+jY4AAQIECBAgQIAAAQIECBAgQIAAAQIECJSkwGV3/X5PINu0fkccWrst2nYeioZF02Ji8jTwhGUzY+/PfxXPfOIbPX2ffvWZsfRj1xQdxyvfeDS2f/fpY3UmnTsvFt50Wcy89pyorKk6Vt535+DzW+OVOx+Jnfetju6Ozr6nXt2vqIj02os+ckVMvWjRyeeTkq7kd3se2BBb7nos9j38YsE6gxVOOmduzLru3Jh53TlRP3dK0eppeL31rsdj67efjPZ9R4rWdZIAgXwKVNx//m0W0M/n3Bs1AQIECBAgQIAAAQIECBAgQIAAAQIECORQoLK+ZsijvuAvborGS5YUrf/oTXfE4Rd3Fa3Te7K7vetY0PqWx28bMJhN66eh8KMf+Nuen05JwteLv3JLbzMFv9NAdO0ff6fnXBoWL0k+FUmAO5Stad32eOoPvh5H9xx/J3H6hPJ5X3xfTwA8lDbSOmkf1v3Z96K7vUCYXKCRNOhe+cfvjsnnzS9wtnhRV3tHEgQ/ERu+dN8x0+K/cJYAgbwIeAI4LzNtnAQIECBAgAABAgQIECBAgAABAgQIECBAIBHoamkfskN3V9egdTubjw6rzUEbLFDh8IYd0d3dXTTQTZd5Tir0hLazkidph7NNXDEn3vhPvxtPfvRr0bJ5X8+TyRf8nw/1vJt4OO3Mu/GiGL9kejzxO18tGsqmyzov+b1fi8W3XFU0BC927cqa6ljwwUtjwlmz49lP/XOytPXILUNd7LrOESBQ+gKVpd9FPSRAgAABAgQIECBAgAABAgQIECBAgAABAgTyLJC+K7hl6/6iBBOSAHjxzVckSykPL/ztbTRdevmcP72x5/DsP3nPsMPf3namXLAwln78mt7Dgt9nf/49sfSj15xy+Nu30XRp6kvu/GjUTp/Qt9g+AQI5FhAA53jyDZ0AAQIECBAgQIAAAQIECBAgQIAAAQIECGRF4PC6HUW7Wj1xXCz7xLVF6wx2Mg1vL7rjwzH9qjMHq1r0/OKbr4wJy2cVrHPGrW+NOdevKnjuVAvT8Hrl52441Z/7HQECZSYgAC6zCTUcAgQIECBAgAABAgQIECBAgAABAgQIECBQjgLpe3pPx9Z46dLXfZmKqsqY8+4LTmpn+lXLY8l/vPqk8pEomHHNWTH7neePRFPaIEAg4wLeAZzxCdR9AgQIECBAgAABAgQIECBAgAABAgQIECCQB4Gm9cWfAB7IIH1HcUVtVVRWVw1UZUjlHU2tUTWhruh7iPs2NOvac+KFL93XtygWDzH83fPQC7Hpaz+PQ89vjbT/tTMmxux3nBeLP3JF1E4beKnnMz/9jtj5w9XR3d7Z77oOCBDIl4AAOF/zbbQECBAgQIAAAQIECBAgQIAAAQIECBAgQCCTAsN5Ari7syte/Ksfx54HN8ThDTujIgl/p1+9vGeZ5NrG8UMef9uepnjxL/899v3ypWjdfjCqGmpjwQcuiaW//5ZB3987bvbkaFg0LZo37e253uRVCyJdYnqw7Vd/8aPY+OUH+1U7urspNv/jw7HrR2vi4q/cEmnbhbbaKQ0x7fJlseeB9YVOKyNAICcCloDOyUQbJgECBAgQIECAAAECBAgQIECAAAECBAgQyLJA266mOHqgeUhDWPc/vt8Toqbhb7p1d3TG7h+vi8c+/PfRNcSnYztbjsbTt94Z2+55qif8TdtJn8bd+A8PxZrb70kPB93qkid3e7ehvPd3x/977qTwt/f36XfrtgOx+nPf7lt00v6s6845qUwBAQL5EvAEcL7m22gJECBAgAABAgQIECBAgAABAgQIECBAgEBmBdIANpKnXItt2+55MrZ+6/GCVVo274ttdz8R899/ScHzfQvXfeH70bRmW9+iY/s7vv9sLL75ypiwfNaxskI7tdOPL9ecPg082Db77efFjKvPGqxa0fPpu4DTJ57T0NtGgEA+BTwBnM95N2oCBAgQIECAAAECBAgQIECAAAECBAgQIFCWAumyz8W2vclyzkPZBmtn36ODt1Mz+XhYXT9/6lAu27PMdLrUdLFPsYaqJ4yL+nlTilVxjgCBMhcQAJf5BBseAQIECBAgQIAAAQIECBAgQIAAAQIECBDIk8ChtduLDrd16/6i59OTrTsPRvv+4stNt2w5MGg7UXG8ykDv7T1eY+T2+i49PXKtaokAgawICICzMlP6SYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBQV6DjcGq1biwez7QdairaRnjy8/tV3Bxer2D7E9xH3tjHUdw/31n89332Xnn497fgtAQLZFBAAZ3Pe9JoAAQIECBAgQIAAAQIECBAgQIAAAQIECBA4QaCzpf2EklM77GxJ3jU8wlvLlsGfPB6pS9ZOO/7u4ZFqUzsECGRHoDo7XdVTAgQIECBAgAABAgQIECBAgAABAgQIECBAgEA2BVq27IsJy2YO2vlXvvlodHd0DlqvWIX9j71c7LRzBAiUuYAAuMwn2PAIECBAgAABAgQIECBAgAABAgQIECBAgACBsRc4/MLOmHHNisE70t0dG750X0RX9+B1+9RIn/qde+NFMfWiRXF4w+BLWPf5qV0CBMpMQABcZhNqOAQIECBAgAABAgQIECBAgAABAgQIECBAgEDpCWy964lY9JEro7KmqmjnFnzg0pi4cm6s/8L3omndjqJ105NT3rAo5v/WG2PmW8/uabtt7+FBf6MCAQLlLSAALu/5NToCBAgQIECAAAECBAgQIECAAAECBAgQIECgBARadxyMHf/2bMy94cJBezNl1YK49Jsfj+ZNe2P3z9ZH67aD0b7/SFTUVkf9vCnJZ2rUz58aDQsaw/t+B+VUgUDuBATAuZtyAyZAgAABAgQIECBAgAABAgQIECBAgAABAgTGQmDj3z8YM3/97KhuqBvS5RsWTYtFH7p8SHVVIkCAQK9AZe+ObwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgdETSJ/offZT34yu9s7Ru4iWCRDIvYAAOPe3AAACBAgQIECAAAECBAgQIECAAAECBAgQIEDgdAns+8WLsea2e6K7u3t0Ljla7Y5Ob7VKgMAoCFgCehRQNUmAAAECBAgQIECAAAECBAgQIECAAAECBAgQGEhgxw+ejdbtB2LlbTfE+KUzBqo2rPL0qeL0HcObvvbwsH6nMgEC5ScgAC6/OTUiAgQIECBAgAABAgQIECBAgAABAgQIECBAoMQFDjy1OR5531/H4luujEW/fXlUTxx3Sj3uONwaW+56PF75v49E266mU2rDjwgQKC8BAXB5zafRECBAgAABAgQIECBAgAABAgQIECBAgACBERM48PjG6DjYMmB73V3dcXTv4QHPFzux60ero6Jy4DdVtmzdf9LPt93zZEw4Y+ZJ5b0F7U2tvbsDfrftaYpt9z4dVXUDRyS7frxuwN/3njj4/JbYed/zvYcFv9OQt9jW3dEZL9/xQGz8h4ei8bKlMevas2P61WdFbeP4Yj+L1ObQ6m1x4MlNPWPpPNJWtL6TBAjkS6Di/vNvG6VF5vMFabQECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZEQqBxXE3XTJ0TdjIlRM6Uh0uWdO5JwO/207TkcHYcGDuVH4vraIEAg2wID/3lLtsel9wQIECBAgAABAgQIECBAgAABAgQIECBAgACBTAp0tbZHy5b9PZ9MDkCnCRAYU4GB11YY0265OAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMV0AAPFwx9QkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFCiAgLgEp0Y3SJAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBwBQTAwxVTnwABAgQIECBAgAABAgQIECBAgAABAgQIECCQQ4EVn70+Zr/z/IjKihyO3pAJZEdAAJydudJTAgQIECBAgAABAgQIECBAgAABAgQIECBAgMCYCTQsmhbnfuE34/J7bo3Z168SBI/ZTLgwgeICAuDiPs4SIECAAAECBAgQIECAAAECBAgQIECAAAECBAj0EegJgv/svYLgPiZ2CZSSgAC4lGZDXwgQIECAAAECBAgQIECAAAECBAgQIECAAAECGREQBGdkonQzdwIC4NxNuQETIECAAAECBAgQIECAAAECBAgQIECAAAECBEZOQBA8cpZaIjASAgLgkVDUBgECBAgQIECAAAECBAgQIECAAAECBAgQIEAg5wKC4JzfAIZfMgIC4JKZCh0hQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGRfQBCc/Tk0gmwLCICzPX96T4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoSQFBcElOi07lQEAAnINJNkQCBAgQIECAAAECBAgQIECAAAECBAgQIECAwFgJCILHSt518yogAM7rzBs3AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOA0ChwLgr9za8x516qIyorTeHWXIpAfAQFwfubaSAkQIECAAAECBAgQIECAAAECBAgQIECAAAECYy7QsHBanPPf3xuXC4LHfC50oDwFBMDlOa9GRYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoaQFBcElPj85lWEAAnOHJ03UCBAgQIECAAAECBAgQIECAAAECBAgQIECAQNYFBMFZn0H9LzUBAXCpzYj+ECBAgAABAgQIECBAgAABAgQIECBAgAABAgRyKCAIzuGkG/KoCFTcf/5t3aPSskYJECBAgAABAgQIECBAgAABAgQIECBAgACBMRO48K8/FNWT6sfs+i5cfgLjF0+P6gl1p21gzZv3xst3PBDbv/9sRJc467TBu1DmBQTAmZ9CAyBAgAABAgQIECBAgAABAgQIECBAgAABAicLXP2TT0dt4/iTTyghkDEBQXDGJkx3x1zAEtBjPgU6QIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMJCApaEHklFOoLCAALiwi1ICBAgQIECAAAECBAgQIECAAAECBAgQIECAAIESEugfBF8QUVlRQr3TFQKlIyAALp250BMCBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFBBF4Ngm+My79za8x5lyB4EC6ncyggAM7hpBsyAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCDrAmkQPP/9b4yJK+ZkfSj6T2BEBapHtDWNESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBhlgYPPbYmX/uansfehF0b5SponkD0BAXD25kyPCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQK5FBD85nLaDXqYAgLgYYKpToAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcHoFBL+n19vVsi0gAM72/Ok9AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBsBQS/ZTu1BjaKAgLgUcTVNAECBAgQIECAAAECBAgQIECAAAECBAgQGCuBJz/2j1FZXTlWl3fdMhRY8dnrY9I5807LyAS/p4XZRcpUQABcphNrWAQIECBAgAABAgQIECBAgAABAgQIECCQb4HD63fkG8DoR1yg43DbiLd5YoOC3xNFHBMYvoAAePhmfkGAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDCCAoLfEcTUVO4FBMC5vwUAECBAgAABAgQIECBAgAABAgQIECBAgAABAgTGRkDwOzburlreAgLg8p5foyNAgAABAgQIECBAgAABAgQIECBAgAABAgQIlJyA4LfkpkSHykhAAFxGk2koBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFSFhD8lvLs6Fu5CAiAy2UmjYMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUKICgt8SnRjdKksBAXBZTqtBESBAgAABAgQIECBAgAABAgQIECBAgAABAgTGXkDwO/ZzoAf5ExAA52/OjZgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMKoCgt9R5dU4gaICAuCiPE4SIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMVUDwO1Qp9QiMnoAAePRstUyAAAECBAgQIECAAAECBAgQIECAAAECBAgQyIWA4DcX02yQGREQAGdkonSTAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBqAoLfUpsR/SEQIQB2FxAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAxLQPA7LC6VCZxWAQHwaeV2MQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAdgUEv9mdOz3Pj4AAOD9zbaQECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVMWWP/nP4gjL+0+5d/7IQECp0eg8vRcxlUIECBAgAABAgQIECBAgAABAgQIECBAgAABAgSyLCD8zfLs6XueBATAeZptYyVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKwFBMBlPb0GR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAngQEwHmabWMlQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCsBQTAZT29BkeAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQJ4EBMB5mm1jJUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgrAUEwGU9vQZHgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgECeBATAeZptYyVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKwFBMBlPb0GR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAngQEwHmabWMlQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCsBQTAZT29BkeAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQJ4EBMB5mm1jJUCAAAECBAgQIECAAAECBAgQIE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new file mode 100644
index 00000000..c623a79b
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new file mode 100644
index 00000000..ff7a1503
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diff --git a/content/polkadot/async-backing-deep/img/context.jpeg b/content/9-Polkadot/assets/execution-sharding/context.jpeg
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diff --git a/content/polkadot/async-backing-deep/img/cumulus.png b/content/9-Polkadot/assets/execution-sharding/cumulus.png
similarity index 100%
rename from content/polkadot/async-backing-deep/img/cumulus.png
rename to content/9-Polkadot/assets/execution-sharding/cumulus.png
diff --git a/content/9-Polkadot/assets/execution-sharding/cumulus_sketch_1.svg b/content/9-Polkadot/assets/execution-sharding/cumulus_sketch_1.svg
new file mode 100644
index 00000000..e3ac4f0c
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diff --git a/content/9-Polkadot/assets/execution-sharding/cumulus_sketch_2.svg b/content/9-Polkadot/assets/execution-sharding/cumulus_sketch_2.svg
new file mode 100644
index 00000000..8104fb88
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diff --git a/content/9-Polkadot/assets/execution-sharding/cumulus_sketch_3.svg b/content/9-Polkadot/assets/execution-sharding/cumulus_sketch_3.svg
new file mode 100644
index 00000000..43a8330d
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diff --git a/content/9-Polkadot/assets/execution-sharding/cumulus_sketch_4.svg b/content/9-Polkadot/assets/execution-sharding/cumulus_sketch_4.svg
new file mode 100644
index 00000000..b8183bfa
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new file mode 100644
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similarity index 100%
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new file mode 100644
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new file mode 100644
index 00000000..8e385ccd
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new file mode 100644
index 00000000..ed9d2c35
--- /dev/null
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new file mode 100644
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diff --git a/content/polkadot/xcmp/img/messaging-kinds.svg b/content/9-Polkadot/assets/execution-sharding/messaging-kinds.svg
similarity index 100%
rename from content/polkadot/xcmp/img/messaging-kinds.svg
rename to content/9-Polkadot/assets/execution-sharding/messaging-kinds.svg
diff --git a/content/polkadot/xcmp/img/mqc.svg b/content/9-Polkadot/assets/execution-sharding/mqc.svg
similarity index 100%
rename from content/polkadot/xcmp/img/mqc.svg
rename to content/9-Polkadot/assets/execution-sharding/mqc.svg
diff --git a/content/polkadot/availability-cores/img/occupied.png b/content/9-Polkadot/assets/execution-sharding/occupied.png
similarity index 100%
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diff --git a/content/9-Polkadot/assets/execution-sharding/occupying_assigned_cores_on_demand.svg b/content/9-Polkadot/assets/execution-sharding/occupying_assigned_cores_on_demand.svg
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new file mode 100644
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diff --git a/content/polkadot/execution-sharding/img/parachain-finality.png b/content/9-Polkadot/assets/execution-sharding/parachain-finality.png
similarity index 100%
rename from content/polkadot/execution-sharding/img/parachain-finality.png
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diff --git a/content/9-Polkadot/assets/execution-sharding/parachain-validation-multiple.svg b/content/9-Polkadot/assets/execution-sharding/parachain-validation-multiple.svg
new file mode 100644
index 00000000..d5d31b95
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new file mode 100644
index 00000000..ac96ff0d
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new file mode 100644
index 00000000..b21fb4d7
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diff --git a/content/9-Polkadot/assets/execution-sharding/pov_path_1.svg b/content/9-Polkadot/assets/execution-sharding/pov_path_1.svg
new file mode 100644
index 00000000..c575d9e8
--- /dev/null
+++ b/content/9-Polkadot/assets/execution-sharding/pov_path_1.svg
@@ -0,0 +1,16 @@
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diff --git a/content/9-Polkadot/assets/execution-sharding/pov_path_2.svg b/content/9-Polkadot/assets/execution-sharding/pov_path_2.svg
new file mode 100644
index 00000000..b938d063
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+++ b/content/9-Polkadot/assets/execution-sharding/pov_path_2.svg
@@ -0,0 +1,16 @@
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new file mode 100644
index 00000000..f54dc3c6
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diff --git a/content/9-Polkadot/assets/execution-sharding/pov_witness_data_2.svg b/content/9-Polkadot/assets/execution-sharding/pov_witness_data_2.svg
new file mode 100644
index 00000000..4cb9aa74
--- /dev/null
+++ b/content/9-Polkadot/assets/execution-sharding/pov_witness_data_2.svg
@@ -0,0 +1,17 @@
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diff --git a/content/polkadot/execution-sharding/img/pvf_duality.svg b/content/9-Polkadot/assets/execution-sharding/pvf_duality.svg
similarity index 100%
rename from content/polkadot/execution-sharding/img/pvf_duality.svg
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diff --git a/content/polkadot/blockspace/img/reimbursement-layer.svg b/content/9-Polkadot/assets/execution-sharding/reimbursement-layer.svg
similarity index 100%
rename from content/polkadot/blockspace/img/reimbursement-layer.svg
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diff --git a/content/polkadot/blockspace/img/reimbursement-status-quo.svg b/content/9-Polkadot/assets/execution-sharding/reimbursement-status-quo.svg
similarity index 100%
rename from content/polkadot/blockspace/img/reimbursement-status-quo.svg
rename to content/9-Polkadot/assets/execution-sharding/reimbursement-status-quo.svg
diff --git a/content/9-Polkadot/assets/execution-sharding/replace_host_function_1.svg b/content/9-Polkadot/assets/execution-sharding/replace_host_function_1.svg
new file mode 100644
index 00000000..03855455
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new file mode 100644
index 00000000..2100a899
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similarity index 100%
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similarity index 100%
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diff --git a/content/9-Polkadot/assets/execution-sharding/runtime_validation_2.svg b/content/9-Polkadot/assets/execution-sharding/runtime_validation_2.svg
new file mode 100644
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diff --git a/content/9-Polkadot/assets/execution-sharding/runtime_validation_3.svg b/content/9-Polkadot/assets/execution-sharding/runtime_validation_3.svg
new file mode 100644
index 00000000..bca28303
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diff --git a/content/polkadot/intro/img/smart_coretime.png b/content/9-Polkadot/assets/execution-sharding/smart_coretime.png
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AAIIIIAAAggggAACCCCAAAIIIJAZAQLozDizFwQQQAABBBBAAAEEEEAAAQQQQAABBBBAIHACBNCBm3IGjAACCCCAAAIIIIAAAggggAACCCCAAAIIZEaAADozzuwFAQQQQAABBBBAAAEEEEAAAQQQQAABBBAInAABdOCmnAEjgAACCCCAAAIIIIAAAggggAACCCCAAAKZESCAzowze0EAAQQQQAABBBBAAAEEEEAAAQQQQAABBAInQAAduClnwAgggAACCCCAAAIIIIAAAggggAACCCCAQGYECKAz48xeEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBwAkQQAduyhkwAggggAACCCCAAAIIIIAAAggggAACCCCQGQEC6Mw4sxcEEEAAAQQQOcNdtAAAIABJREFUQAABBBBAAAEEEEAAAQQQQCBwAgTQgZtyBowAAggggAACCCCAAAIIIIAAAggggAACCGRGgAA6M85Zv5eEEqERGpE8HyZqYvLX0faXvRKpg1/y16UZU/r8+tGvgzU4+b391T8xTMOS2w0plN7+0myX9yCAAAIIIIAAAggggAACCCCAAAII/IbAr+Q9P5f5tP69X9py6yyxVd7Tkva4rMd9o8t7yHo4PdMCBNABPReGa3jYBc2TNTk8QRPcxSHWwRTRSjuAbhqcSAfTXKg6eEbYPQIIIIAAAggggAACCCCAAAII+EbAhc1DNCQ8W7ND1aoKTZA8O/h4Bw7Asp5Ky3q6JbMey6Lc8fAKoAABdI5PevpOl33I3Vy7oDn99aORu0C6Sg90iSjWxZLoirW1ctnF2qVHtWp6hhTuYtspDynR2b69zOqVi+3XfPu1wDYSTSyuXk7Y3S2vwX6/yb5qbUe19muN7XhhWJoTVmh2geJzTtbT8xcqtjCqgkWeCha+ovcX/krY7I47+WXHmKyYJpjO8ZOW4SGAAAIIIIAAAggggAACCCCAwM8KpHMeV1RoT663flr9Z58sP14D875UdUVUKm+SV9FJRWX/1AEVlvd08xTuZhm1ZT0qtZyn1DZQYhlQkf0aDSnuMp/ky3IfL6xwve3bFS/WWUhTY7+3wLKeRY3Km9dNTTNf0WOzb1WkpliJRVLhvOc0cd4vTOHinMfVTI/SKI+cJ/dPdgLoHJxjdzHaUTtGqlTlRveTyuYztFVRX/VYt07N69mfr7+v+vdZR1162r+vbCeE++oat5tkdWpyrTF+5Xrxc9e29Pt/+mctvxNSifIUUaguofAcO9a5CTXPLlb/aXfruanzNGOy3Q6bXKHyz07Qg3N+YefhgRoYWVNrelyocvAEZkgIIIAAAggggAACCCCAAAIIILBYoKVosMp9udCl+edoEvaeG/XxWnHVr2Xh8BorqWTNI7X5ag2q62GhclfLX1ayjKeb5T15tcm857deS77jlzunera1fPuryDIo27flPIkZFljPyFPjjFs04ZtG6bOw8j/rpeiXQzS6/mf2nKyUfkWvxAmjf2te/Pnnv32++XNcgTrqH/r52CVpiQrnSvUvLVO0943aa+2Fqt1CCm+5hjr1K1F+WUxesTsBFqheDZZTW4Xy4obP9s8xu1jYn1rB8eJXaDnOl0SrK5Tr85ywaDsRdl/pzbqQ2y6Q9khGhaIWTltI3ZinaO3/NGd6nRo+aVLJxytr0ntX6p0pnyo0vUpTFiwxwVYd7SqkZeMfTp+hQJ39DBYBBBBAAAEEEEAAAQQQQACB3BFo9SS7y3jc10/aVmyjXqusq9VXGabKfnO1aOOwIhusp7J+ERVWuCpm20bEMh/NVo0lO4vjlySS/Vvc3p/KapY382md9bithuw34iHr9RFpPRMWRqu7lSG2HEGoLiqv5nPN/axe4f/20Ly379eLXz2mwm/e0iSrml78SmY8buQ8BZ875/VyBIq5M3i/j8TdAXNfNo4fVTn/U3v0mS7tcKq23rxc0QGNim3SoOaC9GS7sNlVOLvg134vbtXI9rhD2P7RXXhcyJxwSXG7nhtuJ+4CZb+kfg3Zcxx2DbRg2v2GBdR25yxZKZ2cJquWVoEitVGFP4sr/sU/9NbEBtW/3VkbvHOqbmp9oUpe1axCOrqP9onTX8jvZznHjwACCCCAAAIIIIAAAggggEBuC6R7N1tLDReC/ORJ9pt1wDpzVbPFAdpowIbqum6Nmtaz71mz0dKddHhTZ9/mSv5SWY+LVuKWobhEJfWW9s97fpr1JCzr8VzOY8G0HbEdXbFlPe6A3D8XKNpsYfj7Jar7YKTef6dBReNO06NfLTHbUZftkO/4+zPQriGjv2my8+hTgbOr9F3cy7lSfQoHqV+/PbV+ZYlC+/dU5w3s8YYuc1SdvE3mLj4W5Lqm88n5dilzenTtHTQvj2LLBSv1t8UV3XYvze7guT9w43F30OwmYFO+Os+booWfztKUlztpp3Gn6rr/PacJlr8vfrne0cnxcudseWaD70EAAQQQQAABBBBAAAEEEEAAgbYUaKlydoGwe457uNv04irnrbRaUYGKe9+gvTeJq3mnzircak11WaVRXqdF9vR4feoJdteqwp5eb4l9Wv6WtVlPOudJZT2pYkQ36JacJ25BeVcrQ7RCxAWfaubn9vtjGjX9xTP0wedv6IvqlP3ifIcwui3PxsxsiwA6M84rvBdrzB6xO2FuO4tXL71Ge228nXr/bgv12mW+GnZwf2gXJOvk05y8tRRV1N6bvNOVrCpe4YPo4A2kLlh2cQ0lmu3RDjuciGcX3sJk4w5bE9HGbq07vrav/96k8e/Ye8YN1XPvLXHYEesrFKKvUAdPJrtHAAEEEEAAAQQQQAABBBBAIGACv/Qk+7U6vuscfbrjiarcalUVbVqv5s2a5RU6HtdKw/7dFRYmIgq7Hsnut90T5O3+9Hp7T0/rnMeeireMJxEqtnzHtYh1MZYF0m/HNeuF6/T5M8P1/PhWx2PjH2xvGr04I2vvY2X7Kybg+1ByxYaf3d/duu9PMl211wDr8/M37bPdBup0XBeVbTZbdeXuQmQPMLibRvaesN1Ca3m8IhdC51+boR8qpVt6S7uLk7UWsbA9Yf2kS9yjHNV1qpvymRa+MEN1T16spya+rxmz09tMV5NTGZ3dnwOODgEEEEAAAQQQQAABBBBAAAE/CvywZley1rnVk+yV0d1UvOZ+6r9tkbocsIaKNmnSolXm2QpdFjwnA1jXq7mlTaqLnIOT86QCnuR0u4xHVnTYUyV1MU3/bJLCd1+hcU89oPe/SZ0PrjUtT7z74MNBAJ2Fk+QuUHZ5cY3bF/f9uUp7b32CNjk0ougg+wCuUmeXJKvwtftCkZi7GrX00+Flbi6o9+zOmfUcSUTs7qBF0W5hQ1mldN5XVin+glVHv1yrQvt1bOve0RGrMrcac+6ecRYhgAACCCCAAAIIIIAAAggggMDyC/xSpfMl2nPAZlp1l1211k7WTmMn20N+oz3L7p5mt17IFrWGmy3jcY2bc+JJ9uUXbPlOs3AVzokmWTtrS8DKkpXRkfkVij32hD4ZPUiPPdtqH1HL01yFeGqBxRXdO9/flgIE0G2puYLbSgXPbk6S1c6u78/R2rJyN/U9uZcqdpimhSUtzeRDdgvIvc3/j1usINmvfntLhXQo4RY0dC/P7py5QLq7Su3iHpsyQdPGLVLTfRfoxQkfa+r81MaSPYVcVXTLxY4LV3vOEdtGAAEEEEAAAQQQQAABBBBAIBcEXAAxwvKE1DpUydYQLojurI/X2ka99uuu4gN7qbzfPNVU1Fq9obXUcKmDl1o0kIznV06C1BPwlu8klzIMO1x78j1Wo4b/fqKZN12gV559S5OSRYbOnCfds+8TRQCdJXOS6vG8+AJ1qFYb0ktz/tSg2u2tkle1Vu9sLSWsIjrZoJ15W455a6mOTsTtzlmeC/DLTLQlZE581qzok1fpxeeu1asvL7Fp7qAthzXfggACCCCAAAIIIIAAAggggEAQBFJ5jstpFj/FPlR79d5F6++xtVbaq1b1e1gGke/apzZaQe//s3cf8FFV6f/Hv1PSSEIHRRSxr6JYWHuLrr0glqBYUdaKvYuFoKLYu66KitgJFsSClSgoNqxrW11FRQSkk4QkM3Pn/5yQ+5Pdv6sJmSRzZz7XF691cebec97nzJ3kuc95To6tZLcU54zZr6u1x9gFoy2+Y7GdeDRqYXyLlVmaYe7HE/TFPeWa9VC5Kiob2mTxs6QL8JMR3dqD9DvXI5DZxoOwYtZzmUqiB2utgzdUydm/avpWcSse4XY0XV56vf4Tw3ilYLz+OzPaPT1zsKuoqC6p2Kcfa96j12rak+Wa/qN/OfeFMk7juHGlwJ9TIIAAAggggAACCCCAAAIIIBBkgRX27HLhhPpkwr5apfBG7bvt5trC9uyq3WGe5q1WYwmFDRvqNWQ6s5I9VePuYjtJC5W5fcBcreguamcVtONffqzZtw3T6480ZETXZ6Tbn/pKAxxtJ0BAs43sXTC5oa5P/Y1qpPbY/VRtd3ZC8b0Wq9qe4BTazSlhHyRqO7f0EPl1o93TM7t5qZNVi7ankpUd1G7COH0+foq+fP4eTY81tCNkwegwweiWHhXOjwACCCCAAAIIIIAAAggggEB6Cfxebecy7dX3bO2xX50WDMhRzpaVWmq5zmGrWBy1esT1tUHZs6uFh9Elby7fvFHhdpZjXqDczyfqq6tL9fAjDZeu36yQQHQLD8QfnJ4AdBvYN9yw6p++3K/SjUrUu6y3Oh04U0uiVqPY6ju7evMeGc+tPDb/lRltNYUS6mpZ6FYn+uN/au5jXyr+8Gm6f5YfiOYpWisPEJdDAAEEEEAAAQQQQAABBBBAoA0EGlavu2BNQ+nUfu12Vd8dC9XhhC20ys4/aWEXt4VgfTCnPufZ5eUm3es5WlUg5P2WEV2gOtVVfKH48O11zZuuGSuWv23VZnExSjq05hxYsdzGBSrtcKVKz1iqD8+LK7eo2nJu8xVJWFSaJ2OtOSj/41rLawqFEzHFI/bVEWpvo2O1uBfVSY/cqqnPXKlXX13hrRELRid5kpYGA0cTEEAAAQQQQAABBBBAAAEEEEidgIvRLN/7zo6/a+vVz9DOB62lwqMtxtOvxiIFVRbmzFdO3AWcCTqnDr45Z3IZ0XEbNs/GZBXbAew7zb/3Jr135T2aWl9qdcXE0OZch/c2XoAM6MZbNfOVZfbka3nNmck6ab8N1fFqT4mNPVsaELaN8awMhN2oeCDQTOSUv92vKeRuW3bYGCbVUx28jzXn9QVacudz+nLSTZq2rOHCFLhP+QhwQgQQQAABBBBAAAEEEEAAAQRaV6AhQOkuWh8MeFVbrV+jfifvo14D5qqytwtu2mEpziG3IR7Zzq07PI262vJV7nKlOSIu8raKOv/wkT4ZuYXGjm7YmNA9XKjPaOdoeQEC0C1svOIyjaHaqsuZ2vmKXupw8q/2jCxiO5/aZ8GClgSeW3gYUnL6hhIdiVqrFe1qChVaRScLTH/8o2ruvl4vPfmAPvq14ULUFkqJOCdBAAEEEEAAAQQQQAABBBBAoHUE/rvMhrvqczpsx79p/WPjSg7yFMlfpGUWDYjG3Z5eZDu3zrik4ioWcI7bBoXRTrbjWq6SE27WV8OGqfwLOzebFKYCuBHnIADdCKSVfcmKKf3P6Zh999VG1/2sJRva/pzJqNV6phD9ysq27fuWZ0UnPbeUw+0lGbHnB6uq6Ku39ePDj+vze27TFD8QbZsa1me31y/V4UAAAQQQQAABBBBAAAEEEEAAgfQTWLE2sIvlbK4Ze5RondMst3n3JVqWk7Tf++3fPdu3i2zn9Bu+RrXIRtCz0qqW8pwI91T3uYtVdHEXnTi64c31m7E16kS8aKUECECvFFtj3lRqqfzliRu1bcEQrX9hnTa4tEqLQnnL6wLVV6bnCL6Au4G5m5TLiu5s+6za/5n3kxbfc43eeOBhffitfyNjt9XgjzU9QAABBBBAAAEEEEAAAQQQyByB/39jwZLoxlr9gD207ikWaN51ga1cdwvWLYEwQQJh5oy7lU1J1KguUmQPExbKe/hyvXTOQ/p0rvWQkhwtOMwEoFsG1wWY4+eo5C/XaJ87Z2vpLlLMZjI3rZbhbvuzLn+StrxOtH05WW2hop+n6odHxumr225TxcyGFpIR3fZDRQsQQAABBBBAAAEEEEAAAQSyXGDFFevu3zfSN6V7aoMzrCTwtpW2qaCteK5fue5+x6dsauZNlpCNrY2xdSwZXk3tv3xVX52yu8ZULB/vpKvrzUr2FA87AegUgq5YpH6udt8nop3urlXV6jZ/rdazPTTjyHgBv060qy3UVe1saYe36GctvmukXhv9qD77rgEgYnMlaX9Y3pHxM4IOIoAAAggggAACCCCAAAIIpJGAy3J1v4vb7+Ql0b7q3b9Evc/KV3iH+aq2dLKwZxmylNlIowFryaZYDCdRrXhkDbWveU7fnHuQHrzDXW/Fkiwtef1sOjcB6BSN9opPzxZq5Dl2L7uqUpW5LuvZLuFucBxZJLBiRrSrEbWqimdO1fdjntHXt9yginkNFPWZ8lnEQlcRQAABBBBAAAEEEEAAAQQQaHWBMssMtD/uqE8EG6+j9tlT618QV2ynZfZruSWPsVdXq49KelzQij8nYvIi+bZBYVeF7h6h6WeXaWL1inG+9GhpsFtBADol41dm87XM21arFzytY26z4OOQmGLJiMWdWaqREuDAnmTFjOgulhEdU/Ln+Vp63ZWa8vBYvTffdczd1IZrOEs8AjvKNBwBBBBAAAEEEEAAAQQQQCAdBVZcqe7a94pO2aGfVr24UOE9rFyqldCMkPGcjgPXym1ysRtXdiWukG1Q2OGVK/XakWV6eS6Z0KkbCALQzbesL1J+r9ZaZWcdcX9XaZ9qJWxn1JArGINv830z4gz/XSO6u4o+naLv79xJd9/TUFsoZF+M7g9lOTJixOkEAggggAACCCCAAAIIIIBAWwk0bDDo4jX1q46f1J5bHKAB5yzWzENrlYzELOc5VxE2F2yrAUrT61rxlfps6B4q/vIiTT7ser32qTWVzQlTMF4ESJuBWGqTsNyCz+9o8Hpbq+cTvyi0eVJe3NKhIwSfmwGbwW/1M6JrrUZ0e1ve0Un5b43Qa1eW6bVJDd22ZUH1/xCIzuB5QNcQQAABBBBAAAEEEEAAAQRSL+ACzwM1MFyuclcO1Wr59ut1h3Y8q6OKT/xZtQW5tj2X1Xj27HUWuuFA4HcFEnF7SNFDRbOuUMXRl+uV1whCN3+mEIBeecP6+r1v6oQtttLa422jubUKFGKzwZX3zKp3ukL39m0YsjpT4e4q1BxVPvW0vhh5liZ+6CBKbDOEClVQHzqrZgWdRQABBBBAAAEEEEAAAQQQWFmBFWv2lmn/diXqeepO6j10lpb2st+9LQUsHLfAMwmDKwucRe9zMRvLko90VsfFIfU8qlBHTyQI3bwJQAB65fzckzLvDZ2+3V/VffyvWtojX1HP6sXwBG3lPLP2Xa40h213ELKNCkNdVFD1q2Kjy/XPa87SU784FIreZ+3UoOMIIIAAAggggAACCCCAAAKNEGgot+HiW/UriX/UIwe01+eXh5TXd6GqLfAccdnQYVaqNwKTl/yfgIvX1CkezlcsVqjI34t03Vj7j/XJqDA1XYAAdNPNcuwtsak6eZt+6vHsXFV3s6doCbvLuZowHAg0WcCV5bAvQm/5rqtRFSj67dP68prvteH9DaU47MGGe4krK86BAAIIIIAAAggggAACCCCAAAJOYMXVw1er/+aH6y9lHZTff4nqrNSGpbAqYr9IkyzIbFk5AVeuJWbzx+I0dTF1Pr6HznRBaGpCrwQnAeimodVPsgoN3XYbCz7bjqldyXxuGiCv/t8CfiA6boHoVVWk+aqZ8k/NHba77pnq3uV2Xx2ncV7DpoVQIoAAAggggAACCCCAAAIIIJCVAg2rhV2SVvJ6Dep6kNY5v5cKTpqrqmKX4GWBQxF4zsqpkfJON6xct0zocDJXqxzTQWc8ZBchE7qJ0gSgGw9WH3yeqlP/+let8uwvVnajQDmU3Wi8H69spIC7ubkdeXMUCueo0Ouin+66ub4+9BTKcjTSkJchgAACCCCAAAIIIIAAAghknkBDuQ1X/rR+k8EHdMhhA7XZpZVattEyq4xgmwxaeYSkCw5yIJAyARenSVj51Fzl1Bao8phi3TTOJQn6m12m7EIZfCIC0I0a3FILPpcnpunvG26qtV6ZqyU9yXxuFBwvapZAyCq7JGyjwrxQO4Vm/qC64VfrmwcbbnC2cUKSbOhm+fJmBBBAAAEEEEAAAQQQQACBoAisuEfSu3pw/d764spOal/6i5ZYAlckYQEu6jwHZTAD2E4XhK6xmtCrq7jmbk09+FRNeoEgdOMHkgD0n1j5N7gPdHSvTbTlpF/0/Yb5KrCaz0lqPjd+nvHKlRRwZTnsrQkryxG1OlZaqtjEe/VBWZle+tCdkpvdSsLyNgQQQAABBBBAAAEEEEAAgUAIrJj1XKbS3N3U5eyttMb5c1XZyZNnZRGiSYvRuKxoDgRaVMDVhK5TItxJ7eaO0GsDrtcb04jLNI6cAPQfODXc5JKlWrvDOA2Y+L1yd2zHhoONm1m8KqUC7kmbfaHaP164p7osnqYfRw7TxNsqNKPGLkQ2dEq1ORkCCCCAAAIIIIAAAggggEA6CKyY9Xyj9t3xLO107TxVbrNMMct6DrsyHGQ9p8NAZVEb/JrQq6jDj5fo5T2u1eSvV5ynWUTRpK4SgP5jrrA9yQjdrPUeTSpnYESxuKWjUkuoSVOMF6dSwD6wiVrFIwVW2aq9ct8o15eXHK3H6jcpdIFo+1NfB4sDAQQQQAABBBBAAAEEEEAAgaAKNCQEupiVV6p+He7WwItCqjp7iepyogrHLd3ZErFsp0EOBNpAwILQ8Zji0Z7q8MkVemNXW6W+wJrhsvCtlCrH7wnwYf2f82J53ed5Gn51UokLLcU+bhOM4DOfozYXcGU57Is2aRsVhrurY3VU3a4fqruuuUfTq61xZEO3+QjRAAQQQAABBBBAAAEEEEAAgZUVWDGb9DUdv/cG6nZtnkIb11i+VVQRz4LTlNtYWVzelzIBlyBoscJIL3WaMEI1Bw3XcFdC1Z6KhOr/l+M/BQhA/86M8Ou3zNd5f0+o3b11qvOiCrkd4fDiE5Q2AlZ7yLKhY5GI7fTbSV0/mKXep6+nw6e5BlKDKG2GiYYggAACCCCAAAIIIIAAAgg0QmDFrOch2rbzEG162ZZa4wyr9WzBmLAlBSbJem6EIy9pHYHle3ZFLC6zNLqmdr4xpAPPsSu7xNV467QgWFchoPpf4+U/aXtMO21Xqp1fmal4QZ6VFOIJW7Amdra0dvkNL+TZ0o9IsUJVs1R17VS9ffWJmh5zQehxGufx9C1bZgP9RAABBBBAAAEEEEAAAQSCKbBi1vNt2n/XU7XrTXM1v2+d4knLeiYmE8xhzfhWu5iMZ8mBeYqHp+inwQfq0Yes05Ti+J2RJwC9Aop/w7tQ+3a6SDu8tVhLN8yxlHr3SCPjPzV0MNACYYUtCO2F7WGJuin/zbv10Tkn6ckPXKfIhg700NJ4BBBAAAEEEEAAAQQQQCBjBRqynl3ALnGcti++WXtfFlPtOZWqsxqoEct6Zh+ujB38DOmYC0LHLDNwVRUuekvf7LKLxnxMHOb/H1wC0P9pUr+JW1JXPfmTlhzkdlQl+Jwhd4Qs6MbyJ29Kxq0eVgflLflEP1+2s+69paHrbFCYBXOALiKAAAIIIIAAAggggAACQRFoCD675ibHa+jW26n4tqiiW1pdXcsCDBGPCcpA0k6X8pyosnrQa6vDxwdp7G5P66uFluTq/mFTwob5QQC6AcJ/OvGmTjhrE/W4sUp1CauxS+YzN5LACVjJDcuGToQ7qcAKD8UnXKG3z79Rr/3LOhK2L/gkJTkCN6Q0GAEEEEAAAQQQQAABBBDIMIFSi7eUJ9xK9L217Mx+6nj5HC0pdLWeLR7t6uhyIBAoAbcpoUWbI7Y6/f7eGjXExWDsDwFoAtC/zWO/9MbTOqbfXlqnYp6WtYvaPKHuc6A+6zR2BQGXDZ2wYLNnZTnWULdfvtPCc9bRyMfcS8rsJmh/uAkyYxBAAAEEEEAAAQQQQAABBFpVYMWSGw+p/7pHaq2bZqvTfjFVW62NaMIaQyJgq44IF0ulgFVRsHrQsUhYfY/srKMeoRTHb7pZnwHtL/koUZ/Cp3Xwm5WKbR5VyArc2yarHAgEXMCy+BPVqot0VTt9pQWjr9Pb55Zr+mL3pW5znw0KAz6+NB8BBBBAAAEEEEAAAQQQCIrAisG40TqkdLD+evMPqlzN1u4mLPPZVuwShwnKWNLO3xdwK9Jt40ytqi6zh+u1nUfppX9b0muIUhx8uP9vg7ZfNez6hMLnJJSwGx+lN7iZZI6ABaG9hLyQ/a8Vxe8+fbSmnXq8nnjHekhJjswZZnqCAAIIIIAAAggggAACCKSzgCurET9L2xbcqL1GLpZ31hLVaPneW8Rg0nngaFvTBOxhilerWHh1Fb4Y1WX72LvZk8sQsjrL1y+9cYl2KxmuXSf9oiU5dvML8dStaR8uXh0YgURMyUiBYsvC6ndhVw261bWcJSGBGT8aigACCCCAAAIIIIAAAggESqBh1bmLPXlnaMe+V+pvdyxS3Q5WNdKz1efEXwI1mjS2sQJW89QrUk74n/rlpB10z93EXbI4AO2X3ijT/gXDtM1bFnzeLE9Rz1PSFQnnQCAjBVxRfKsNHYlahfPOav/gyZp49n2atsA6W/80OiM7TacQQAABBBBAAAEEEEAAAQRaXaBshf2HZujiI3qp6JaZWtTF9txyK88pudHqI8IFW0vAleKIKx7qpOKFU/XJ1nup/Fs/Cba12pBu18naDGj/6cM0Db1iQ3W9pFK1ibDCFLtPtxlKe1Iu4DYodE/jbJtNC0S3+3CJJp24jt76wC5ESY6Ua3NCBBBAAAEEEEAAAQQQQCD7BEqt7EC5JUDtr37tRmr7a3up09CFVnKjgMS/7JsMWdpjy26tX4XeQdFn2uuKAwlAZ+FE8IPPr+isTbZUh7eWqrbQnsBZTijZz1k4HbK5y5YN7UXaq2jRbC06fwNdf+9yjDK7T5ZZjJoDAQQQQAABBBBAAAEEEEAAgSYL1Ne8HashGx+lvnfO1uwd7RfMZMSqwNr/Zm0iZJMVeUPgBSzmkuikdpFJ+tchh+jhJ7M5CJ2VH/zlNZ6TqtZVzy/Q0r1z6p/AWUIoBwJZJuCWhcQUD3e059A/aOGdF2vShc/q66XGQJH8LJsLdBcBBBBAAAEEEEAAAQQQaI7lfsT5AAAgAElEQVRAQ3DNQi5KjtYhpYO12Z0/aXHXPOVYyQ234pbgc3N8eW/wBFwZVFfqN0/hr0fqg+1v1KSFIzQiZJ+VrEv6y7oAtP+0YYKOOWJXrfXwYtVa5DlE8Dl4n2NanCIBm/zJuJKW/h8O91DRtHJ9eOxAlX9t2xNaELo8kaLLcBoEEEAAAQQQQAABBBBAAIEMFfBXmrv9tqRLhy9Q9JJq1VjZx0jc/s7tOcSBQFYKuCC0xV0iEXUY2VUXXJKtWdBZFYB2gzxcw5MjtEuHodr53TrVrWfBZ8+ewlH7OStvA3TaF6hfEmB1oZcpEVlTHWc9oE9O+Lsef97+LmyfG/dP1j2dY3YggAACCCCAAAIIIIAAAgg0SqB+Be1QbdXlOg34x3xVHxJS3EpuuFKnZD03SpAXZbSAVV1IdlTesgf0Yb/TNPGrbAxCZ1UA2n8iF9N5w+Ypf6TLhLebIdnPGf0xp3NNEbCSHHHbqTXaTsWxzvrq4pAevs69Pxtvjk1x47UIIIAAAggggAACCCCAQJYK1Aefb9XhWw3SWvfapmt9Lb/JSm6EKLmRpROCbv//ArYKIJGraGShlj2+vq4f5CfI2ufEJQNmxZE1AWi3DMQGVvfr2NUP1tofL1VVJ57GZcUcp5NNFHB1oRNK2F2wILSawvedqbeH3qYXa/0HOE08HS9HAAEEEEAAAQQQQAABBBDIMIGGGIuLKXkzdOURayrf6j3/2j5HkQSrzDNssOlOswXcqvM6y4LupQ5J23tr96v0xuRsi7FkTQC61MpslNtTuX/rwruKFTnJnsp5rgh+s2cRJ0AgAwXczdF+oEhaAehwNxVXnKRnjx2jd2ZYV13trngGdpkuIYAAAggggAACCCCAAAIINELAj6+4l36viy7roOiIRVpmW9vnEnxuhB8vyU4BC0Am6hSPdFbHihe07m4DNdCVOiUDOpOmg3uqME7jvBHae5PhKnnzRy1ob6nv1CLKpEGmLy0kkLRi+VFbUrXs21+08eDNNfgtF4R2y0eyaalIC+FyWgQQQAABBBBAAAEEEEAgUAJ+8HmCNijuq31vb6+io6sV86L19Z5tb3sOBBD4nwKeJcMWKS/8vfIHbK4LJ2RTudOsyID2B3S+ykbbLqxDchRO2GMGNh7kpoBAowRCcU+JaGcVLVginbKqLnnC3hayz5X7w+aEjTLkRQgggAACCCCAAAIIIIBAsAVKVBKtUEV8go7bYH+t99BsLd3SAmqJiEKRrEnjDPYQ0vo2FrBEvkSNaiJrquc752jarh3Up3a4hiezIcEv4wPQDcHn5J3qv8mR2uL9parNsYHN+H638WeKy2eYgKsLbUtFwsXK9RYrNmwtjbrGdbHMSnTYH4LQGTbedAcBBBBAAAEEEEAAAQQQ8AVcvWcrFxAuV3miXEeW9NeGD/+iJT1zrd6zK21qwWdiLEwXBBotELKHNonQfOUevpEuf2LFkjaNPkUAX5jxNwk/+3mGzh9bqNyj6pRwpQPIfg7gZKXJbStga6lc0fxQB7WzOl+zxzyjyBllus2SoqkL3bYjw9URQAABBBBAAAEEEEAAgZYRaNhs0J08OV5HDjpAG971s5Z0yLfgMyvLW8acs2a2gEvwi8sLd1XRu2fohx3v0T2xhs9ZRi8kyOgAtL+j5OXabZNLtdsUaj9n9oeY3rW8gNuc0H7I8MJWOH9VbTz5ZX18zJ668adsqlvU8spcAQEEEEAAAQQQQAABBBBoe4EVg2If6MKL1lPOFYsUi+RaWVOLlJHY1/ZDRAsCKmCla5KFyg/9qKoDNtW1z2ZDTCXDA9CKlNsuk3M14tZaVZ8WVTRuN9BoQOcnzUYgjQTC8Wotja6t7l8+q28OHaAxn/kPfNKokTQFAQQQQAABBBBAAAEEEEBgJQT83+9O0955t2r3OxZo0ZAq1cnKbngWPGOzwZUw5S0I+AIWjPVqFA6vrgVv3K93dz9R+9tDncyuBZ2xAWj/6cHdOrrXYVr7s0rVFoetLBG1ifjAI5AaAfs8WfH8mGVCt5/3vL4YeLAenSyV2uYT47xsKKCfGkXOggACCCCAAAIIIIAAAgikl4AfTzlf2xdfpX3GzNLSgyzibHVrw9R7Tq+hojUBFXCry+OKaxV1TlykV/e7Qa++5G/yGdAu/WmzMz4APUMnXV6oHpfGVOs2SuMp3Z9OCV6AQOMFXO2iWtucsKc6LH1G/xxSqkdt0YHbhCKZFbu4Nl6KVyKAAAIIIIAAAggggAAC6S/gB8FO1far3ax9H7HNBksiisQtXsZq8vQfPloYIAELyFoddS9SoJxxJ+qrw8dleDJfRgagG57WJcu0fpfhKn13hry18i0mZkExAtAB+jDS1GAIuJumbe4ZWU3t657QZ2cfqcfvIAgdjLGjlQgggAACCCCAAAIIIIDACgIuyBw/RdtseLP2K5+jqj5W6Dkhhaj3zDRBoAUEXPJee+XV3q13+52rF7+0eGbI/rgE2ow7MjIA7T+xu0eHHX+o+tyzVFWeLRUJUX4j4+YvHUoTASvH4cVsb8I8a0++el7dXqcOc0Fou3G6fzLy5pkm9DQDAQQQQAABBBBAAAEEEEiFgAsyJy7VztteqL89vFDL1g4rTOZzKmQ5BwL/W8DLUSS8WHW3ratrTs/kzQgzLgDdsEurStQ771Wd8PIsLd7RBpMdWvm4I9DCAq4ch21GYVfxwqup8C7pkqGuFvSKOye3cBM4PQIIIIAAAggggAACCCCAQNMF6jOfF+qiAcXKv3+WajpFbc8f+zsyn5tuyTsQaLSAi6PY3lqh3uoy+2K93u8qvTQ7U7OgMy4A7ZffmKYzt1tP7afWKuZq0WZcPxs9m3khAq0vkLDH5FaSo/DJizV5yDV6dXEmP8VrfV6uiAACCCCAAAIIIIAAAgg0X6AhWciVKk3M0ojjbUXrnUtUHS1Q1CUXUcK0+cScAYE/FHCbESbkeR2UHxmrj4YO1YQ7M3UzwowLzPqBrrd04v0badVjqxXzrJPcOPnQI9CqAsmEPS6PdFO7N07Xy4Pu0ZRfCEK36gBwMQQQQAABBBBAAAEEEEDgfwr4q8ftBckfNOyCIkVGVasumaNokuAzEweB1hNw+2pZSVNL4utQsZvu3rtCM2rt8ym3orz1WtHyV8qoALS/1N/t1nqj9v5otiq7W/kNj80HW34icQUEfkcgbju6Rrur+IMz9dJBd+rNn0pVGilXuVvKxYEAAggggAACCCCAAAIIINAGAg3JQe7K3o+6YGSh8oYtU9z2zqqPeGVUnKgNeLkkAk0WcJsR5ikn9JUWbruDbnsnExP4MurG4qepT9X5p26k3NuWKZGwJwbULGry1OcNCKRKIBS35SQWhC764jQ9d/A9mvYVQehU2XIeBBBAAAEEEEAAAQQQQKBpAivu0WPB5xst+HyWZT4nogqHCT43zZJXI5AqAfvsee2UE/5cc+7eQf84iQB0qmRb4Dz+8pF+6hd9V4c+/7Pm756raNz+3hXT50AAgTYTSCa8+nIcRd+cY0Ho2zXtM4LQbTYYXBgBBBBAAAEEEEAAAQSyVMAParnkvbHa5rZC5Z60TLF4xBL3CD5n6aSg22kh4DYjjCkRthXkMy/UK5vcrIpFKz4sSotGNrMRGZMB7d9Ib9QBmxyjTd+zXSTzwrZyhJtoM2cIb0cgJQIuEzoR7abiGafq2UGj9e47sh96pArbr5ADAQQQQAABBBBAAAEEEECgJQV+Cz73zn9Qg/5RpOgxtmeWy3x2wWcOBBBoY4GkbUbYTu31jV4+eitVPJJpmxFmXAD6M51btrraDa+2+kVsPtjGnx4uj8B/CLhM6GSkq4pmX6xJpTdo6lT7z65EDjWhmSkIIIAAAggggAACCCCAQAsJrBh8HqNDHyhW7mFW85nM5xby5rQIrIyAZUHH66yKQy+FHhuhnCPtc2tJtclkpmxGmDEBaJeafqL+Gr1Iu3+cr/BG9gTPPcTLmP6tzOTlPQikoUDCUp4tCB2eW6fvD++oR16zNroyOWRCp+Fg0SQEEEAAAQQQQAABBBAIukCpJf2UJzZT745P67AH2yunP5nPQR9T2p+JAhbATFpsU3nKW/yAftrsXN33Q5kUtj9W1TT4R0YEaP16smXaq2S4dnlphhbk5itiA0cAOvhTlB5kmoCrbVSreLhI3SsjmndEJ139LEHoTBtl+oMAAggggAACCCCAAAJtLeBnPj+nXp021WGPFSh/zxrbcDDChoNtPTRcH4HfFbAAdMI2I4zMlgZvqMvH2mc4ZH8IQKfLfPHrokzSkGu2VM/za2wpiUXW2XwwXQaIdiDwXwJhK7tRp1jEfgCqrFKHY3rr3KcIQjNNEEAAAQQQQAABBBBAAIHUCPiJepN10Oo7aNNxcxXb1hIp4/a7WJSaz6kx5iwItICAF1Y4VKOlk3rrln38h0gtcJ1WP2XgM6D9XSG31wbFUzV48o9a1C9XkYTdUF1tWQ4EEEhTAX+X1yLlxpKKH9lFV40jCJ2mg0WzEEAAAQQQQAABBBBAIDACZQ3L9t/Sgd230ubPzFT1tvkKWZwkRJwkMKNIQ7NRwJXhqFEi1FsdFlyjaZtfqIk/+nHPoHsEPgDtP9W7XHtsfaq2e2uZasMW2Ap8v4I+sWg/Ao0RsKfvyTq7uRYot3qZOh/RS2c9QxC6MXK8BgEEEEAAAQQQQAABBBD4/wX8GMmbGtZjG3lPz1R463a2uZltCM8qcSYMAgEQSMrz8tQ+PF2vnLinJt/jV30IQNP/sImZEKi1GJaS/9LZw7qo8EqrLZuw0s881Qv6zKT9WSOwPBM6Hi5Uu5qwalxNaMpxZM3o01EEEEAAAQQQQAABBBBInUCZxUfKvLfVp/NWOvupn/TVzpbsk7DgMzGS1CFzJgRaVMACtfEahaK9VfeIdO1RIY0IJTU8abGTQFfPyYQAdP3Af6+L3rElJVtbarrbezBj+tWis5qTI5AmAlbjyKurD0KHl9iH9/DOuup5a5p7Qh9PkybSDAQQQAABBBBAAAEEEEAgbQV+y3xetdu2OnLcTKmkQHlkPqftiNEwBH5fwCXpJSw+UqwOP26ne7b+XDNmZ0IZjkAHav0BuF2Hrj9Um0+foYVF+YrUR6CZyAggECyBkAWh43aTzVd+dUSrD+ysv1sQusSC0BUEoYM1lLQWAQQQQAABBBBAAAEEWlHA36hs+d5YB5XPUM6eBYpb8Lk+qYcDAQSCJ+DlKxp+Q//e80A98nKp7XNXLlnFh+AegQ7U+nVQXtCup22jv91arUovYtnPBKCDOyFpeXYLLM+ErrNM6MIFEa1V2lFHvy6V2nKx8kDfaLN7VOk9AggggAACCCCAAAIItJSAn/m8mXp3HK/DHrOSG3uFFYvbhoMEn1sKnfMi0OICyUSeopGfVXVzX914ll3OlR+2Z0rBPQIbgF6e/TzQBqDcdnI959EZyh+Ub8v17e+5yQZ3PtJyBNxdNVFnNcoKFV+c1JRDuuqdVzOl6D7DiwACCCCAAAIIIIAAAgikSsDPfO6n1do9qWOeaK+c/ZZZ8NmW8BMXSRUy50GgDQQsWJu0peChIoU+76SRG7dBE1J+yYAHoEPJvlqn+zv6+5R5WrR+jqKeBaDdUwEOBBAIsEDYah7VKRTupIJ5P2rCQX303hSC0AEeUJqOAAIIIIAAAggggAACKRVoCD5bTGSVds/p2IcKlXugCz7bqvBooHcqS6kSJ0MgmAIuAF0rL9RLxdU3652tztbEz/0HTsHsUYBrJfvLTF7QwO230YZv2o3WFX4m+BzUmUi7EfgvgZCSibhlQueqaN5leqH/3Xp7mv+5BwsBBBBAAAEEEEAAAQQQyFYBfz+sUvXJvUH9HypSzsCqhuBztprQbwQyTcDiIV43tQvfpfeGWgD6zqAn5QU2A9omVn39k+91wfn2pO+auBKuRqzViuVAAIEMEkhYIDrSWUUzztLEfe7UO18ShM6g0aUrCCCAAAIIIIAAAggg0CSBhuBzyIJR4Qe1zb1Fyh1M5nOTCHkxAoEQsIBtrE6JnB7q8nCuzj+qIeYZ2P2xghyArp8wn+qsl3qoaI+YEq4YNxnQgfgY0UgEmiKQdE+XIt1V9NWZembfu/T+d0FfetKU3vNaBBBAAAEEEEAAAQQQQMAJ+MFn+1dvhoZdX6zoOdVkPjM5EMhIAQvYJmLyLBZS+NkuurtkmmYuCHIsJNAB6PvUv/gobfnv2arqlqNw0uocBbo/GfmJoVMIpEbAnjAlXRD6g7P0+l536LX5Qb7xpoaEsyCAAAIIIIAAAggggECWCbhV34kfdPFlRQqPsMznRFhhVoJn2SSgu9kh4OpAJ+yxUwflxy7VG9verNc/DPKK8EAGbP3A03Xae9eztONLs7QkSgA6Oz6A9DKrBSwTOhlZRe0qLtGk/tfqraV+7bOsVqHzCCCAAAIIIIAAAgggkA0CUetk/CddckY7hW+uVl0iqnCYRLxsGHr6mMUCiYg9ZPKUM7iHhj9oDvXliIPoEcgAdD/1y5mu6bFndMKwXbTqyKWKezYClN8I4gykzQg0TSBuQehoDxVOvFKvDixTRZ09kHL/BPIG3LSu82oEEEAAAQQQQAABBBDIUoH6zOdfNGxwjqIPLFNd0oLPlhvJKvAsnQ90O2sEkolc5US+17z7ttSdf7duuziuffSDdwQuAN2Q8eiCzYmk7hw/Q98dnK/8eFKeexrIgQACmS+QiFsdpFXV6cFcXTA4yDfgzB8qeogAAggggAACCCCAAALNEbDNBqMVqojP040HhrTo0SrFcnMVClkGTuDiOc1x4L0IZKOAK8PhyQvl255YXXTJhkE2CNwNyy+/saf6dH5apZPnq7ZvVCELRou6R0GeibQdgaYJ1GdCr67C26WLTx+ogeFxGueFFArkk8CmdZ1XI4AAAggggAACCCCAQDYI+PVef9YzuxXo/acr5RXl2v5Xtj9O4GI52TBe9BGBVAu4AHSdEqHV1anqQX3a9zg9+l1QS5EG7qbl34B30fqbTtIx0+ZoaQH1n1M9xTkfAkEQSNqDp3CkvWouL9YNw63Fga2FFARt2ogAAggggAACCCCAAAKtJ+DHPo7TVn+9Trs9VyVvlVxFPAs+U3609YaBKyHQ5gIJecnuKkreoLcOHaYXxwd1I8LABaBt5OtrH72ncw5aWwVP1slLNPxdm08KGoAAAq0nsHwpSjKZo7zwq/rm9MP1yG3+8rTWawVXQgABBBBAAAEEEEAAAQRSK+AHmE7U1uvdogNeWqCqtewKVnWD4HNqpTkbAukvYCU4Eh2UH3lB3151qB6+OKhxjyAGoOsLbn+rC0a2V85FVgvWbT5G+Y30/8zQQgRSLuCC0FaKw54Gtos/pS8HHaZHnwrqzTjlOJwQAQQQQAABBBBAAAEEAifgL68/QSVdb9duL89R5eYRhUm8C9xI0mAEUiNgpUbjtYpF19Qqz4R0zoF21rDdJ6wOT7BKkAYxAF0/gp/rrBe7q3CvmEuC5ClgamY1Z0EggAJhhbwaxcM91X7Jk/pmz8M05h2/VnwAu0OTEUAAAQQQQAABBBBAIEsFGn6PSd6tE6KDteaEX1W5t9XbsOBziKS7LJ0TdBsBC9wmLPk20kVFnx6ox3Z5SZ8vCGLMI5AB6DLbBXaotp9Rp2RPuxknbdexQPaDjxECCKRGwN2Qa5WI9FDhzJf13a77a8w3Qa2LlBoRzoIAAggggAACCCCAAAJBEmjIfHaxDS+p60b/pPlDoorELeQRDVI/aCsCCKRWwK38jskLraLiyt1133Zv6rvPghjvCFTg1l+K8rgOXb9UfT+ZqaX5bgdYAtCpndycDYEgCrhM6GWqC/fWah8+ppl7Hq4b5gXxqWAQ7WkzAggggAACCCCAAAIINE/ALyWY1NARP6jzZbmKW/A5RPC5eay8G4EMEUgmcpQT+VE/7t1PYyZZp+r3xwtS5wIVgPaDSXdpwMGD1a/8V1WFcghAB2m+0VYEWlogbje16FLVPX+MHi+dppm1QayN1NJInB8BBBBAAAEEEEAAAQTSR8APPj+hI47bUxuMrlS1Z3Wfrc4rq73TZ5RoCQJtKRCKR+yB1DIlz+mtkTcSgG7hsfBvyjdon+Gnaruyuaqym3LIqnBwIIAAAssFPNuXsFC5kQWq/sc6uu5kd2O2ILQXtAL9jCcCCCCAAAIIIIAAAghkvoCfaPe4jtjjIG04YbYq82ylt/1eQ/A580efHiLQWIGQF7X450ItG7OBbjjW3uUSiu0ZVXCOQGVA+wHotzT04b+o8xE1VofbZTsGh5uWIoBASwu4m1rcAs6Fygkv0LJL19V1V7ogtP0J1PKUlnbi/AgggAACCCCAAAIIINDmAvW/pzyjwZvsq3Ve/VmV3fMUtRrQSRLt2nxoaAAC6SSwPAA9T9XvbaQbt06nljW2LYEJQPv1n12h7XHa8tUZml+Sr0jCwv3sBtvY0eZ1CGSJgCvSb7vEesXKi8xR5WB7Qvig/wArSwjoJgIIIIAAAggggAACCKSxgB/jeEnHrrGb1n/lJy3agOBzGg8YTUOgDQVcjCNhGxEWq3Deffq019kqX9aGzVmpSwcmAO0vS7ElKT0e0eGT56lqg6jCBKBXath5EwKZL2ApA8k6W7jWXYU1H+vfB2yjMa8EcafYzB8peogAAggggAACCCCAQHYJNMQ3VKYz2w/X5hP/rY92KFShxTeSJNhl11Sgtwg0SsAFoGMWgO6h4pon9EW/I/XIF/5DrEadIA1eFJgAtB842k7rbfamjn1zlpYUswFhGswgmoBAGgtY3WfPnhKGbbfYmRfphd3u1wdf+w+z0rjZNA0BBBBAAAEEEEAAAQQyVKAhaORKbCQ+0SkPdlf7o5OWXGf/n+Bzho453UIgFQK2ytsS7IqSozX9wFP19ISgJdgFJgDtL5+/VrvucZJ2fmmpliXC7AqbijnMORDIcIGku1dEOin//ZM16W/3663KMivYb39sXw8OBBBAAAEEEEAAAQQQQKBVBerrPv+gCy/ooIJRVapJWOIMwedWHQIuhkDwBCy5LtlNRaH79MG5Q/XMDQSgW24M62/SC3XRsTUK32//Hrcnh2xA2HLenBmBDBJIJjz7oa678h7L1fDDXRb0cA1P2g96gdo1NoMGhK4ggAACCCCAAAIIIJB1An5i3WyNOiBPlU9W2vbpVlo0bL+UBCY5MOsGjQ4jkCYCCdvqqrMKoo/r0zuGaPyp/dQvZ7qmx9KkeX/ajCDd5NwSFe9fuuCKDsq5xMFbCRQC0H86xLwAAQRcvST7mc6LqTqyhna9NKT9ryyRohX2IAsdBBBAAAEEEEAAAQQQQKClBfxsxeO13Wa3ar+X52hxt3xFPU9JF+vgQAABBP5QwBLo4rWKRXup24SwzhtgL65P1A0KW5AC0PWm3+n8sYXKOcrWznuWAc2NOigzjXYi0MYCy3eNlVcgz5uobwYN1pNPltoNuzxAN+w2JuTyCCCAAAIIIIAAAgggsBIC/mZhJ6hf11s04PV5qtokqggxjZWw5C0IZKuAxTQSMSUiPdThrcP1yK7l+rwuSBsRBioA7WC/0wVvFil3B8uAthg0Aehs/eDRbwRWRsAFoS3l2XaOLVpYrk//NkiPfxS0ukkr02/egwACCCCAAAIIIIAAAm0j4G86eIJOCN+m3uN/1dL+YYXYdLBthoOrIhBYgeUBaC+yitr/q78eKnlJX/7iyovan0DsbxWoAHQf9cl9Vvt+W6ScNSwA7Wq3Bqr9gZ3lNByBDBJwN+1axSO91PWLiZq66wF6dk6Qnhpm0FDQFQQQQAABBBBAAAEEskGgfpl8Uvdf95O+ODeqXILP2TDq9BGBFAu4hDoLQIdWVdGiA/XIjs/ry38GKaEuEAFcPzg0WkM6H661f5qnpe1yFHYR6EC0P8VzjtMhgEAzBax2ki1388JWw+e5v+nZgz/X525TUzYlbKYrb0cAAQQQQAABBBBAAIHfBPzg0Asaetz2WvW+xapM5CjCpoNMEgQQaLKAH4BeTe2TJRq901R9N5UAdJMZ//gNfkr5WB268UBt8uFcVebYTrEpvgqnQwCBbBKwB1jxXEWiC7Xs+vV1/XnW94gFoT0LTrvVFRwIIIAAAggggAACCCCAQHMEXNDCe1gDtz9QG70wXzVFuQqHbK08iXTNUeW9CGS1QDKRp7zI2/qs//56cmKJSqIVqrBKo+l/BOLG5wegH1Dp7odp05d+VWWIAHT6Ty5aiEA6CyzflNDzrKZ8ZJ4qj11XN44J0tPDdLalbQgggAACCCCAAAIIZLOAH8N4WOevPlBFU35Rde88W8VN8DmbZwV9R6D5ApYw54LN0Vwlj++iq0bbv9eX+Gn+mVv+DIEIQPtBoft18DGDtNkY2zE2GbEnhy3PwxUQQCCTBWzzD69GsdCa6lY1Vl/tdIzu+yhIRfwzeWzoGwIIIIAAAggggAACQRTwNx0crJKcB3TiU9/p3b3bqdBqQFsYgwMBBBBohoDb0yqscGSJ6srW07Uj7FT1Ky2accpWe2sggrh+APoBHXLBodp01HxVexGFqMHRatOECyGQuQKuHnTc7uFRRT66SG/tOkYViy0IHQrKTrKZOzL0DAEEEEAAAQQQQACBQArUZyR+rNOu6K68S6Q8y04k+BzIkaTRCKSfQMLioZFKxe9eR9ecZM1zcd1AlBENRADar2lytwZef7Q2OccyoA08zNPD9Psg0CIEgiqQsJthpIuKHs3VsCOC9BQxqOC0GwEEEEAAAQQQQACBTBPwYxc/atQBHVT15FJ5ljmXJHku0waa/iDQZgIhS8hVuEqx8Wvr2tI2a8ZKXDhQAeiJ6j9mJ211zFLbOdalnK9Ef3kLAggg8LsCVg860VHtIu/q53N20903Ug+aiYIAAggggAACCCCAAAKNFfBL+Z2hXTa4SftO/kFzeh/X/UgAACAASURBVBQo1/MIQDeWkNchgMCfCvgB6LqKtXXdLn/68jR6QSAC0LJdHWW7OiZ15oQZKu6fr4T9u+zvOBBAAIHUCDSU4kh2UEH1eP1z/+NU/oZUag+6ygNR0D81CpwFAQQQQAABBBBAAAEEmirQUPdZZ2nb/Mu150sLVb1jrnISFnwmca6pmLweAQT+SKB+T7xK1fxzHV2/ub3QbUoYiCPtA9D+jdw0kzFd+/ovmr9LjiJWwL9+p0cOBBBAIGUCLghdp1h4dXX7/lFN2/4oPfULmxKmjJcTIYAAAggggAACCCCQcQIuZrGLdolUWNJcnW669VfNPi2kqAWFkiTNZdxo0yEE2lzA1fQJ1Sk8+0RN7/2iXqxt8xY1sgFBCUAnbQfZ/Hu1+5uztHTLXIUJQDdygHkZAgg0TSCkZKJakcjaqpwwUK8MLNfnbsdqz4LTgSjs37Te8moEEEAAAQQQQAABBBBojoAVYY2U26aD9+rgIw9V37GLtcyLKhy2Xx7SPt7SnH7zXgQQaH0Bu6lYcm4stKp6VD+jwtUG6sTFDYm7aR+vSPsbop99WKo+nR/REW/8osUb55IB3fqznCsikF0C8bByozO1ePhfddPl1vX6nayzi4DeIoAAAggggAACCCCAwB8J+PGKBzWo7xHaxOIVSzrYiu0kdZ+ZNwgg0BICywPQXqirCmsf1wfrHacJPxGATpH0bwHoTXs+rIFvzNaSdXIV9QyYnWRTZMxpEEDgPwXcTd1+aEy2t1LzMxUdsKGGT2RTQmYJAggggAACCCCAAAII+AIuVvG5ykKDtFXH/XXoKz9r9uZ5VveZcqHMEQQQaEmBuDx1V1FsnD7b4mg98U8C0CnS9gPQB2uz9R5V6eQ5WtrTnigSgE6RL6dBAIHfFwgp7NWoJtRbq828SK+VjNLz31EPmtmCAAIIIIAAAggggAACDQIuKc72kDn1/tlqf2yOlfJLKsReVUwPBBBoUQEXgO6mQu8xfb7jcXr87aDEKdK+BIefdXiwNu77mA6vsAzoTgSgW3Quc3IEEPi/nyhDCauvFClU/ouv6sv9B6rc1VXyAEIAAQQQQAABBBBAAIHsFfDjFJ/p4qO6KWesp1r7HSHEKu3snRL0HIFWE1gegC5KPqrP9h2iJ14kAJ0iev/GfoD6bj1eh02epSUFtglhkoL+KQLmNAgg8IcCnrxEBxVE/qlfL9hWt19LKQ4mDAIIIIAAAggggAAC2SvgB3vO1R4bX6c9Jv+ouZ2tTKjbsTztE/yyd9ToOQKZI+AC0FYDWo/p40OH6MlxQYlRpP0N0oc8UH12GGcZ0LO0NEIAOnM+OPQEgXQXcPWgE/K8QuVWl+uTvU7QhLeDcoNPd1vahwACCCCAAAIIIIBAAAVC9vtAzj3a8JVK1e4UVYS6zwEcRJqMQFAFfgtAf3LMEI0fG5T4RNoHoEtUEq1QRdwC0Ls+oUGvzVZlMkdh8XQxqB8V2o1A8ARCClltt0S4lzp+MUqf7nCRHl1khf4txcElOnAggAACCCCAAAIIIIBANgj4gZ6EHho5Wx8PCyk/Yfkq1H3OhsGnjwikiYAlyCW7qDD0mD47eYjG/YMAdIoGZoUA9F4WgH5xtqq8HIVY3pIiX06DAAKNE7CAc8KyGyKLVDt6A113vFQaSWqcRxC6cX68CgEEEEAAAQQQQACBIAv4QZ4HNGivgdr4mflaErX9qcIkxwV5VGk7AsETcAFoK8ERelyfnHWsxt9MADpFY+gHoPurT//xGjTBMqAtCBTmCWOKfDkNAgg0TmB5KY5kokg5kZ+05JhNdPNDQbnRN66HvAoBBBBAAAEEEEAAAQR+T8CSUUIu8eReDVpliDZ+y34fWCdPOZ7tF8PGg0wZBBBoVQGLS3hd1C5sAehhx2n81UGJSwSmBMcA9Tl4nAaNtwzoeFShaKuOLhdDAAEETCBspThqFA/3VNGv72j8Djvqk38FZcdZBhABBBBAAAEEEEAAAQSaLtAQfA5bkEej1PuxIuWVWgaild4QiXFN5+QdCCDQTAE/AP2EPrnCMqAv8xN3m3naFn97gALQGw20TQif+EWVMasBndPiMlwAAQQQ+B0Bu2km7IZvP2wWvH6WPtt7nMbF3MsoxcF0QQABBBBAAAEEEEAg8wT87MJPdOopa6jzHdWKxSMKWTk++xWAAwEEEGhlgRUyoK+2DOhhBKBTNAA+5AARgE4RKadBAIFmC4TiYXnRTup0ZZ7Ov9RO51ZlxJt9Wk6AAAIIIIAAAggggAACaSPgr3Z8U2VbbK2cijlaUpRric8ewee0GSMagkC2CawQgL7WAtAXEIBO0QwgAJ0iSE6DAAIpE1heD9rz2ikvdp+m732enqugFEfKeDkRAggggAACCCCAAAJtLuBKb7hGHK1N212rfV+3mhtbWeZzwjKfKb3R5qNDAxDIXgFXAqiLCiOP6dMbh6j8HALQKZoLBKBTBMlpEEAgpQJWcsOrs3rQvbTK12fp2W1uVsVi+yGVUhwpVeZkCCCAAAIIIIAAAgi0mUD9KseYRo1coKXDltd9DhF8brPh4MIIIOAE/AC0bUJ4q2VAn0EAOkXzggB0iiA5DQIIpFzAAs4JW4IX+VLzbt9J/zjN1YezmtAe9aBTTs0JEUAAAQQQQAABBBBoNQF/deP12menIfrrpCrF8iz7OUTd51YbAi6EAAL/Q8APQNsmhHfYJoSnEoBO0VQhAJ0iSE6DAAIpF3ClOOJWimMVFYff0nf77KL7JvmblKT8YpwQAQQQQAABBBBAAAEEWlzAld6whJLQKSppd4f2mfajFmxsSSee/X24xS/OBRBAAIE/EfitBMcndw7R+KEEoFM0ZQhApwiS0yCAQIsIuFIc9gUQjij87SmauP3T+uRXy4ygFEeLaHNSBBBAAAEEEEAAAQRaTsAFn0doRMgyoL2pOvmmDdT1TCu7l7Cf+Sm90XLsnBkBBJogsEIA+jYLQJ9OALoJeH/0UgLQKYLkNAgg0GICrhRH1EpxtFN0dLHKjicLusWoOTECCCCAAAIIIIAAAi0mUCaF7Y/3qk7ebUf1fOlXVdmOg5TeaDFwTowAAk0W+K0G9Me3HKcnzyQA3WTC338DAegUQXIaBBBoUQHPNiUpVH5osd45pLcmPW0Xc0v0vBa9KCdHAAEEEEAAAQQQQACBlAi47Gd3ooO0Yed/qPTtmOLr2ypHSm+kRJeTIIBAqgRW2ITwJtuE8GwC0CmSJQCdIkhOgwACLSqwvB50MlSgdj88oX9vM1RjZvubl7TohTk5AggggAACCCCAAAIINFvAX8VYrbI7lih2SsJ+vLef8aPNPjEnQAABBFIo8FsA+rMbjtO4cwlApwiXAHSKIDkNAgi0uEBI4URMlZE1tONYy50Y7GrFufIc9r+uLDQHAggggAACCCCAAAIIpKVAma1eLPOu0977n6RtnlqkZaGowmH7Ib4+K5oDAQQQSBcBezjmdVG78OP65BrLgL6QAHSKRsaHPEB9DinXoPLZqopHZd8FHAgggECaCbgs6KRtShhVPPSF5h9ZotGPlTXUkUuzptIcBBBAAAEEEEAAAQQQMAF/1eLt+luXU7TXuzM1b50cRSm9wexAAIG0FPgtAP3x5VYDejgB6BQN028Z0BsOGKcjniYAnSJYToMAAi0iYNnOXp28cC91nD1aFVserxdnUoqjRag5KQIIIIAAAggggAACzRZwpTfGaZzt3XLKvd+r65ACxROWVBJp9ok5AQIIINACAr8FoD+95DiVjyQAnSJkH7K/Nt53vAY9N1tLE7YUhi+DFPlyGgQQSL2AZUIn7CfYSEx6vLeuGuT/UEspjtRbc0YEEEAAAQQQQAABBFZWwK/7/JqG7L+pej9dqyrbSZzSGyvryfsQQKDlBVYowXGeleC43r+PtfyVm3eFtK9ntEIJjj2tBMcky4D2chRyBVXTvu3NGxrejQACQRVwpTg8eV6hisLVevOg1fTyM0H5UgiqOe1GAAEEEEAAAQQQQKApArZXS8gSRLSvNun4sAa8u0zx9WxPF0pvNAWR1yKAQKsL2CaEya4qDD2mT0+zDOjbgxJrSPsgrg/ZX312Ga/DX/9FS5WrsNVZJQDd6rOcCyKAQKMFXCmOmBLhDur47dV6bqtRmrrIfsi1GxcbEjYakRcigAACCCCAAAIIINBCAn6sYaFG3VynJWfEl28ezmrrFvLmtAggkBoBF4DuYgHoJ/TxCcfqyXsJQKfGVT7kAdp4OyvBUTFLS3MIQKcIl9MggECLClgZDq9Y0fDnmnfLdrrzzKB8MbQoCidHAAEEEEAAAQQQQKCNBfw9WkZpn51O0zYvzld1Xg6lN9p4VLg8Agg0RiAuT5YBrcf12eHHadxjQYkzBCYDeoA26VeuwyZbALqYAHRjpiSvQQCBthZwpTjsy8HroqL4e5qxe4lGT2FDwrYeFa6PAAIIIIAAAggggIDCt2rvnNO045QftHjLPEUpvcGkQACBQAj4Aegn9Fn/YzVuYlBiDIEJQB+sjfo8rsNdBnTXXL4cAvGhoJEIIOBqBYU8+4IIFytv+vF6acdyTasxF6sixIEAAggggAACCCCAAAKtLeBnC36goRetpS5XWe1nLyzbe5ADAQQQCICAC0B3V1HyCX36t2M0bjIB6BQNmg85QBuvY5sQvjFLS3oSgE4RLqdBAIFWEbBos9WT8yLF6nZJsc4ZWSpFyu3vWuXiXAQBBBBAAAEEEEAAAQTqBfzg83sa02dDffv2IiWLovb3tlcLAWjmCAIIBEKgIQCdGK/Ptj1ST7xPADpFw+ZDlmrTno+o9I3ZqlwnRxGWx6TIl9MggEDLCzRsSGhPKYsX36ApJRdr0qdBqdPU8jpcAQEEEEAAAQQQQACB1hFw8YXhGp6s1DUvLtTCPXOV43m2WrF1rs5VEEAAgeYLLA9AF8bG6cNNj9bTX9oDtJDFHNJ+lXXal+DwIUvVp/OjOtxlQG+cq0jCZNmdtvnzljMggEArCdhPtYlaJSO9lPOSNGJv+4Jw91/bp5ADAQQQQAABBBBAAAEEWlrAT257UX8fsqNWH71INYmwwsQVWhqe8yOAQMoE3D5TdfJCq6m45gX9e50DdP8sAtAp4v0tAF2a+6i2eHOWFm1NADpFuJwGAQRaVcCizV472137e80+sZ9G3xOUpTKtisTFEEAAAQQQQAABBBBIsYCf+XyN+q9xvDZ/e5liPSJW9pnSGymG5nQIINCiAi4AbbU8Q0WKVt6rd1Y9Ty9XEYBOEXkDpDtbMqay135R7a45Csft712pJg4EEEAgMAKuFEet4qE11XXOsXpy2zF65wf7YThkf8iEDswo0lAEEEAAAQQQQACBIAnY6mm39LB+9WGdrh77q5YcZZnPlPUM0iDSVgQQ8AUsGBoO2QqOn9fX9WvbX9YFhSbtS3A0QLpgswWd75s4Q1/sl68C+3ePAHRQZhntRACB/xOwm27Cos2ROsUfXEvXDrb/4GrOEYBmjiCAAAIIIIAAAggg0AIC/t4rr+icPfsqOimuqBdi08EWkOaUCCDQCgLJiD1Tq1TssyF6b4sKVcRb4ZopuUQgAtAlKok61Cm69JGNlDh8mUJxWyxDADolU4CTIIBAawsklPRWUaHe1r92K9HYyZTiaO0R4HoIIIAAAggggAAC2SDgfs52/Vymz4tHaZ/Xf9Bnm+epXdIS2th4MBsmAH1EIOMEQp4Vrg9bAHrK2rpm5yBsPugPQaAC0Hdqn9uP0/ZDf9XShNVrYrOAjPsg0SEEskPAZUHXKRHpqvbvDdUrO49RRZ39cOz+IRM6O6YAvUQAAQQQQAABBBBoHQEXN0h8pwvOzVPiurDyElbOk1hC69hzFQQQSLnA8gB0leomrK3rBqT89C14wkAEoP0lMw9q4PBSbVI2X9UGHuKJZQtODE6NAAItK2A/+CYKlRuZqh9O309jbvPvcy17Vc6OAAIIIIAAAggggEB2CPirDC9USe+LtMv0StV0ClspaFcTOjsE6CUCCGSggCXkhiJLFb93XV1zgvXP3c/stpb+RyBuvH5g5gEdfNKh2uyu+aqyR5bhQLQ9/acALUQAgbYQcLvXxqz08xrqMPcpvf/Xg/XUzxaUtm+PUCC+PNrCjGsigAACCCCAAAIIINB4gdJIUuNsheGZY39SxyNzVGcbD5LI1ng/XokAAmko0BCAjo1cV9deYu0LzJ5SgQji+k8u71fpIYPUt/xXVcl2fUzDeUCTEEAAgSYJuJIb4Vp596+lUUPcvW64hicJQjfJkBcjgAACCCCAAAIIIPAfAn4S26sauvtm6jaxRjVRS2ILk/3MREEAgWALhOJWgiO6WDpjfY281fpSX2YoCH0KVAB6jAbudKg2mWwB6DAB6CBML9qIAAJ/JOCyoOvkJddQ+/g1enPPizSpglIczBkEEEAAAQQQQAABBFZewFYVhkIaESpRRe6r2v2NWVq6VY4ilv2cJItt5Vl5JwIIpIGAJavFrepGNE9LBnXWrY9bk6L2x/4u/Y9ABaAf1aC/HKw+n8xRZS4B6PSfXLQQAQT+XMB+Ck7U2oaE3VT89rX6ZJcylcfth2OyoP+cjlcggAACCCCAAAIIIPA7AqWWEViemK0Tzkxo1ZtCitevOoQKAQQQCLpAUp7tJVUUeUyj9zpZM14qUUm0QhUEoFM1sMufYIaSN2lwx+O17syFqiy0AHSS5TOpEuY8CCDQlgJ2L/MKFA3PVmLoRhp5p192qC3bxLURQAABBBBAAAEEEAiagF/S7mbtvtbp2ubtmfK65dZvPEj2c9DGkvYigMB/CjTsIxXqoeJYiR7e6S19+U6QVlAHIgPaJ+8n5Tyh874tVl6vhC1bt78PVPv58CCAAAK/J2AP2LxaxUK9VDznHL3w15s0bZb98ByyPy5bgwMBBBBAAAEEEEAAAQQaIeAHYyo1avQCLR5iweeE/UDtaqRyIIAAAoEW8APQq6pw7iEWgH5WX39NALqFhtQ9zTxKy6YUKbqdVdi27xGeYrYQNadFAIHWF0iEFYrMV809fXTDiWRBt/4AcEUEEEAAAQQQQACB4Ar4Pz+PVenOB2jD1yoVt5XUlN4I7ojScgQQWFHAJa7VKRHuoaKvB+ixkhf0+ewgxQ0Cl0H8jc4vb6+cQwhA80FEAIFMEnBPMxNW+7mbCuOfatUdt9Tf3wvSl0kmjQV9QQABBBBAAAEEEAiWgCvbOcI2HqzQmNwHddhr+YpY0lqS2s/BGkZaiwACfyBgMYNETF5kFRW+M0APlryob2v9ksVBgAtSANq1Nfmdzr2lUPmne1Z422pwsJQmCLOMNiKAQKMElj/RjIU7Kvfl9rpiL/v/7r5HGY5G6fEiBBBAAAEEEEAAgWwV8Jehz9MpRyfV/cE61SRCChMvyNYJQb8RyEABiw/EaxSL9la3F0I6b1/rYtgC0Em3Z14QuhukALTbtdaboQvPK1DkWsuAtl0ek9EgINNGBBBAoDECLgs6bl8gnVWYnKxvB+6nMU8FaVfbxvSR1yCAAAIIIIAAAgggkEqBhlWDyQu0W/tLtfP781W1Xp4inkfJzlQycy4EEGhjgaQFoHMtDvqDvLF/1ahj+qlfznRNj7Vxsxp9+SAFoF2wOf6tTj20WB0ft+U0BKAbPcy8EAEEgiJgT9oStUpEeqrj+/vosV2200HLhmt4YJ5qBsWZdiKAAAIIIIAAAghkhoBftu5LXTCsm/JG1iruUfs5M8aWXiCAwG8CrqyQld8I36a3Rp6jFy8JWrJaYALQPuxe+kvJszrq9TmqTEYUclnRHAgggEBGCdj6GS9f0fDnmnvKTvrHXdSCzqjhpTMIIIAAAggggAACKRL4Lft5hzWu1F4f/qKlnXMUTdqydGIFKTLmNAggkB4CCXnJrioMjdXHJ56oJ+/xSw+lR+v+vBWBCUD7sHtpg74WgJ4yW5Xtc2xZDV8sfz7IvAIBBAInYDHopBW5z/3pYk3a6l69M9f1ICi1nQKnTYMRQAABBBBAAAEEAingJ2p8rrPv7Kp2JyeUsGqdIWo/B3I0aTQCCPwvAVeu0zYgDK2iIu8BTd/3JD09KWiJaoEJQPuw+2nTnk9qYMUcLV2XADQfTgQQyFyBpG20mhNZTfGRIV11SdCebmbuuNAzBBBAAAEEEEAAgXQQ8GMEJ2ibLW7X/lNslXR+1DbxtkyOwMQ50sGRNiCAQPoL/BaALqwZqw+3OF5Pf0kAuoXGzTKdQy77b7BK8u/SHq/P0+Jto4pYgMaSBDkQQACBDBOw+51tnJIIFSh/6fP6tt9RevjbMtvl1v54GdZVuoMAAggggAACCCCAwMoIuDIbtir6+ud+0tx9rfQG8YGVUeQ9CCCQ9gLLA9AJy4DutHiCflx9oO6sTPtG/1cDA/NksCEA7b5g7Evl8qe/V/WAAkXi9vduc0IOBBBAIBMFPFfr3pP3UA9dfbR1sP6H7EzsKH1CAAEEEEAAAQQQQKCxAv7qwOd0XP8SrfXUQlWFogqT/dxYQF6HAAJBE7DgZzi0SMs+X0/XbxLE8pyBCUC7mdFP/XKma3rsJR1x61Za/7QqLUuEFSYDOmgfG9qLAAKNEnBPOeuUUE918O7W+yVD9fRUSnE0io4XIYAAAggggAACCGSogEtOG6ERobf1VMHzOvTVn7Vkm3xbHW1ZGsQGMnTM6RYCCIQ8KzEUnqdlz2ykGw40DxfPtaIQwTkCFYAuUUm0QhXxW9T/jJO15c1zVJWM2BOA4HDTUgQQQKBpAnaDS9hmA5Fi5b+6mybuM1372yqQ4ckgPvFsWs95NQIIIIAAAggggAAC/79AWUNZund14pC11X10THE2HmSiIIBApgskLAM6skA11/9F159HALqFh9svsP0PHbD/YG05Ya4q3TKbFr4qp0cAAQTaViApL1GkgvAT+mTACXrqWf+H7rZtFVdHAAEEEEAAAQQQQKB1BRpKc2qwNutwo/p/uEzxtSwikGTjwdYdB66GAAKtLRCK2xKPaEyRk1bX5Xfb1d2KD3v4FpwjUNnDfgD6fh2x0RHq8+EcLcnLUZgvm+DMN1qKAAIrIWA3aq/WltusKX1wjyZtd6I+iNuKm0Att1mJbvMWBBBAAAEEEEAAAQT+Q8AvR/esjr5gN607ar6qE7YqmtIbzBMEEMhwgWQiT5HIdNXuuYeuezmIpTkDFYD2Z9NE9Wu3l/b4cZZCXXJ52pnhHzK6hwACTsCyPbywCsML9P4RfTTh0SB+4TCSCCCAAAIIIIAAAgisrMDyhLThyb9p7e6v6IT3ftSiNfIUtYS0JMuiVxaV9yGAQNoLuL2hrCxnaFUV1Wyvu7Z9Xz9/HMR4QCAD0G52fKOz322vdlslLChjY8EXTtp/ZGggAgg0R8DVgq5VMrKmIh8N1dSd7tDkKnc+akE3R5X3IoAAAggggAACCARIwP3e732sEy9bVd1HeEq45edkPwdoAGkqAgg0XcB+5/diSoS7qfCb/nq45BV9PcuvENH0s7XdO4IYgK7f6fFrnftgJ+UfHbfaqHzptN0E4soIINB6Au6Lx0LOYU+dj+upsx8I4lPP1tPiSggggAACCCCAAAKZItBQ+zn5oDbtebQO+OgnxbvmuMCAy8fgQAABBDJYwOIA8VrFo2uq0+QRmrRHmSri/j0xSN0O4s26/qnn5zr/om7KvYoAdJCmG21FAIHmCLgAtN3zQl0V/fYafbxZmSYuW/5zNwcCCCCAAAIIIIAAApkr4CdeLNJF1y1W5Nxcy35OKkT2c+YOOT1DAIH/EwjZHlCK2qqPsatr1DEl9u8Vkvu7QB1BDEDX7/Q4SycPiKjr0zYAFvlXNFDqNBYBBBBYSQG733m2+UD4Z9WduamuuYUs6JWE5G0IIIAAAggggAACgRBoWGqeHKO91z5Y2767RNWdw4pQ+zkQo0cjEUCguQIJq/zQXcWRmzX1sgv04hX91C9nuqbHmnve1n5/4ALQfrDlCPXZcrQOe3ueqqJRhe3Lh6U3rT15uB4CCLS+gKsFXad4uJe6fnu6Jm5/q96cN0IjQvaDuZXn4EAAAQQQQAABBBBAIOME6stwLtZFt1UpdKr7edh+/yf7OeOGmQ4hgMDvCdgqaK2i4uRdmjboTD33RFCT0AIXgPYLbe+kddZ4SYPf+FVVa+UozBcQn1MEEMgaASvFYbXvk5Faxc7rreuuD+IGBFkzWHQUAQQQQAABBBBAYKUF/Dqnj+rgvxyszT+co8p8S0ALXBxjpQF4IwIIZLWA3eySMSvDuZqKl43WB9uepKc/CWL9ZzeIgbtx+9AnWMr53Trs5R80r8SWoxOAzuqPJJ1HILsE3JeQLcNRR7Wbc6um9R2mF+fZvdFu6CHqQWfXVKC3CCCAAAIIIIBARguUWqbzOCW9BRp5X7WWHhux3/2tw2Q/Z/So0zkEEPAF3O/+cSVCndV+zn2avebpuq02qDqBC0A76BKVWMHtivg7GvrAuuo8uNbqQFtHqAMd1FlIuxFAoMkCrhZ0gaLhH7Rg5Oa6/ZKgLsNpcsd5AwIIIIAAAggggEBWCDT8fOvdrv03H6ItJ8/XsqKIQi7jIpBxjKwYNDqJAAKpFvBybA+o2Vr6xia6uSTVJ2/N8wXyxu0HoEdqzwvO006jbBmOZ19E4daE41oIIIBAWwosrwXthXqpw+yTNWF7qwf1A7Wg23JEuDYCCCCAAAIIIIBAKgVcoNll/81T2SN1qjuc2s+p1OVcCCAQDIFkIkfRyBwtuX1j3XKatbm+Jn4w2v6frQxkANrP9LtR++1/irZ+Zq6qwlYHKoj+tBkBBBBYaQG76yVs58GI1YQqW1OjRlALeqUpeSMCCCCAAAIIIIBAGgn4P9c+oMM3O0wbvT9PlZEItZ/TaIRoCgIItI5AKG773kUXKXb8eho12q7pgp8WBgjeEcgAtF8HeqyOWutIbfTpT1pUDpHJdwAAIABJREFUlKtIkqU4wZuAtBgBBFZeYHkt6KQ6KO/XG1TRp0wVrha0ZYpQC3rlVXknAggggAACCCCAQBoIuDrPiTkqeyim2iPD9ZtwU/s5DcaFJiCAQKsKJK0ER374Zz2742aaPlUqtXtjubsfBu4IZADaV3aBlnm64us6LVvPvpAIQAdu+tFgBBBoroA9+vQKlRP+txZe9lfdegW1oJsryvsRQAABBBBAAAEE2lLA/Tw7TuO8+3VY3yO18RtzVV0cpfZzWw4J10YAgTYQcAlntto51EUFs/fW/du9qR++D/Kq5yAHoOvrnnyoMx6zGqiH1SnuUtCpw9EGHwouiQACbSdg2c6e3f9cLegZJ+rF7e/Wm7OpBd1248GVEUAAAQQQQAABBJon4Nd+rtLIuxZq6UlWbrO+7Fzzzsq7EUAAgWAJuLr3tUpE1lSnin00eq8X9W1tkFc8BzkAXV/35EudfnZXdbghpriloIf4UgrW54nWIoBACgT8DVlqFT57LV15E1nQKUDlFAgggAACCCCAAAKtLuAHV8br4PX21iYfL1BtO8t+ZrVzq48EF0QAgbYWsIdx8Vyr/zxTlfdsrptPLFFJtEIV8bZu18peP8gB6PqaUF/piV266OPXY/ZU1BKiCUCv7EzgfQggEFgBlwWdkBdur/wZd2l63wv07NIgPxkN7EDQcAQQQAABBBBAAIHmCtT/nv+Lzr3DU/4pIXmsdG6uKO9HAIFACsSV9HqoKHyFJp9+uV69jQB0Gw2jX/dkV228zrMaOG2BqrvZzpA8GW2j8eCyCCDQtgIWcPbaKS/8oxacualuvYUs6LYdD66OAAIIIIAAAggg0DQBv/bzvdptvcHa5a3ZquySo4j9jp+k1GbTKHk1AggEXMDVf66z+s89VFx7u97e/Ww9PyXov+MHNgPaz+4r1bYF49T/lR+0aPs8RRKWok4WdMA/aDQfAQSaLuDKcNQoEe6tDl9epBd2uFpTFlELuumOvAMBBBBAAAEEEECgzQTqy2zW6PxRcxW9INd+vqX2c5uNBRdGAIE2FFi+AWEi1E0d5t6ij9a/UOWLg77KObABaDcP/PTzL3TG6C4qHhKXF7cORdtwjnBpBBBAoE0E3BeU7cOaTKguHNUaf19Vp91nDalfwtgmDeKiCCCAAAIIIIAAAgg0UsAPrEzU+j130mGfVirWKayQ+wE30DGLRnaflyGAAAL/LeBZkm34Jy2esplu3cn+o7sX2i0xuEegb+b91C9nuqbHLtVuZ16mXW76RZWebVDA8pzgzkdajgACzRBYXgs6abWg/x979wEnVXX2cfx/Z2Yby9JB6RY0RtQQURFsWDBWbAE19tiiRKNYXxtgLDGK2CMqxpJYQATFXnBtWJBYIvYo2GhSd5dtU97n7O4VVJTdZWd35t7ffD4rsszce8/3nJk797nPeU5k9mS9ss1xKq7I9ruk68DBSxFAAAEEEEAAAQSyRMCfWj5VJ1y+h3pesEwVSQtAc22fJf3HYSKAQFMLpBJ5ikU/15Jrt9XNZ9nWa2aINPVemnN7WR2A9k9SV2vv3c7QDk9+q9JcWyGSOtDNOYLYFwIIZJRA0mpBd1SrSLE+OnZv/fvubK8TlVG4HAwCCCCAAAIIIIBAkwvUre+UOkBb9JioQ19fqNKuMcWo/dzk0mwQAQSyRyCVsBr40SpFDuuuSx8kAN3CPedn9t2iP7Q/UVt8/K2Wd86tWaSAaTot3DXsHgEEWkwglYgqEilVfOafNXnnJ/VZlX1W2oeil9XTdVqMkx0jgAACCCCAAAIIpFXAT5h4SsefN0A9/rZSVQn77sraTmlVZ+MIIJCpAq68piWWqUj58Uv12jbX6Kn36m7UkQHdwp1WUwflXf3l9e4qGmCrRLoOYapOC3cKu0cAgZYRqFusQN3VTmM1Y+i5mvaYXy+/ZY6IvSKAAAIIIIAAAgggsGYBP6lsqH5VNFFH/Oc7lW9syRRkPzNgEEAgtAKutGZciUg7FX78W92802eav4gAdGYMh5o6KK/rrOs2VavTKxS3ADR3SzOjazgKBBBoCQH7UExUKxltq8Kp1ypxyCiNqsl+Jgu6JXqDfSKAAAIIIIAAAgj8nICf/fyijj+mn3rcVaKqlNV+zupSofQ2AgggsC4Cdt0er1Ii1l2tHr5MyWEWfHbX81k/ozkIH+w1AeivdPRB+drg4WpVJwhAr8tQ57UIIBAEAZuyk2qrPD2m//Y/XJPfDsId0yD0C21AAAEEEEAAAQQQ+IFAZJj6xiZo+CsrVL6NZT8nLcpC+Q0GCQIIhFggFZdaxeJ67eJeeuKy/uqfM0uzqrMdJOsD0H5QZbS6b3qmTppVqvLCiFXgoA50tg9Njh8BBNZRoKZ2XkLe3T102bG2raxfNXcdPXg5AggggAACCCCAQAYJ+NnPL+iI/bbWppNLVBGLWvYz1/IZ1EkcCgIINKuAK6lppYW9bmpdfYGe2e9qvfSM/1nZrAeShp1lfQDarxm1lbYqfFXDn1mm0kExRRLcNU3DaGGTCCCQNQKublSV4l5PFS25VZ/vcIomfDJGYzy7aZfVCxdkTQdwoAgggAACCCCAAAI/K+Cu42sKxFmwJa5Lp3yrlQfm2nW8fVEl+5lxgwACoRVwn4mVqvJ6q+f8CXqv7wmasMSPe2Y7StYHoOs6IGZ/xlO68Oa5Sp2aV/P/cr/jgQACCIRWIKJovFKlsfU16K95GnaJQbgv9FamiAcCCCCAAAIIIIAAAi0nUDeTOXWadu43Wru9UalKu36n9nPL9Qh7RgCBzBDwkp7ikYTaT++h83cPUinNQASgB2twrFjF8Zu09x+P0w4Tlqg0ZVnQlOHIjHcPR4EAAi0k4O6eupUKoop/9Qc9uvXz+mhxUO6ethApu0UAAQQQQAABBBBoAgF/Svl/deadPdTmuJWqtqBLTck4HggggEBoBez6PVmoXO89fTlqZ935VwLQGTYUVtWB3nOLS7TrjC+1rChPURd4CUSAPcO4ORwEEMgiAXcCK1J+ZJa+PW1X3XpTkE5gWdQNHCoCCCCAAAIIIIBAnYD/ffRMDe4zVr9780stbZ+nHFt8MEUAmlGCAAIhF0gl8hSLLlGbXTfROcWj7cac/QSijGZgArQu2DxGo73zlJq9SFWb5dSsnssJLOTvXJqPQOgFXC3ouJKRtsqZfbpe2uYuFVfaZ6OruOeSo3kggAACCCCAAAIIINCsAn7286c6b0xrRS+xL6WuRBy1n5u1F9gZAghkmoC7dk8oESlSwYIT9FT/SXrtmyAlkAUmAO13yss6+c4ttJ5N4YkzhSfT3k0cDwIItIhAUqlke+WnntJXRxyiOx70yxa1yMGwUwQQQAABBBBAAIHQCvjl4EZr/07nasB/Fqu0Z0xRksdCOyJoOAII+AIWgI5XKxnrrIInd9QjB8zSrOogldAMXAD6Y51zdCcV3F2h6oR1HndReS8jgEDoBWwuY6JKieh66vD07/TkflYzP0EWdOiHBQAIIIAAAggggECzC/iJY+/o7JN7q/BWaj83exewQwQQyFABT5F4QtWxVup0eQedc9Fgyda7UzxDD7fBhxW4APRN+l3fIzXwP2WqzLEAdGDa1+Ce5QUIIIDAagIWcE4VKJb8Qr0G9NeJ/7Ev/579BKKWFB2NAAIIIIAAAgggkDUC3jD1zRmjPWd0UuHWVirOlYWj9nPWdB8HigAC6RCw4GXKsp/VVW2S5+up4WP10sNBm7kcmACtn5a+kdq3naUzXyxV+W9i8izLj1pS6XhzsE0EEMguAbcYoQWgIx/py1sH6a5TglRLKrt6gqNFAAEEEEAAAQTCKeAHU67XPnudrp0fm6ul0TxFU249p3CK0GoEEECgVsDVf65UdaS3Oiy6VtP7n6VnvgpS+Y3aNgbkUdcx7s6pBZ3H3DpXFSfnW/q61T6NBaSJNAMBBBBotIA7oVUpHumpDgvP05O/uVrF8wlCN5qTFyKAAAIIIIAAAgg0XCBq3z9T58q7a5HKj8pVNG7X8VyvN9yRVyCAQOAEPDc72WKa1S930993djfmXFZ0kJoZmAC065T+6p/jinTfoaHHDNc2d61QeTJqfcYd1SANWdqCAAKNF0glopYFvUJLRm6im68L2pSexrvwSgQQQAABBBBAAIF0CviJDxO154Z7aNC7K1VZZNfqZD+nE51tI4BA1gi4GcuFyo18qsUXbqsbrwhisligAtB+B11kJ7W/aveZc7SkYz5TerLmDceBIoBAegXsAz9hdaWiXVX0+hDdvmux5lQEbVpPegXZOgIIIIAAAggggEBjBFYtPnjaRb3V/q8rFU/ad1NqPzcGk9cggEDgBNyaTa2U6/1TswaM1GNvEoDOgi72gymzdcaMLioaWK1EXRp7Fhw8h4gAAgikWaDuxJb6t97d88+aOp3FCNMMzuYRQAABBBBAAIGQC9Rdo2uYBubfot3frVJyE1cezmaXE4AO+dig+QggUFv/OalkJF85n/5W1w/4UsuXBjFRLFAZ0G7g+ncJXtKJY7ZS90vKVMWdVd7RCCCAwCqBZEyRSLWqJ3bXVYfaF387D7hKRTwQQAABBBBAAAEEEGh6Ab/s2zQdceju2uz+xSqTfR91xU0DF49oej22iAACQRewD8Jqm6mc011tJkR1wQnWXrtAT7nAdKCu0wP3ge8HoGfqjB36qO0rK1Vl0RVXu5sHAggggIBbyKBSCa+n2i+/VS9sM0JPfxbE6T30NAIIIIAAAggggEDLC6zKfh4Wmah+D8/RiqEFisWTLD7Y8p3DESCAQIsLuOvzhJXfaKsC+4x896TjNfn2oK7VFLjArB9I2U7dOz6lE2fa4gYbsrhBi7+nOAAEEMggAc/OcdXKj7bX7DFFmjhaGhaVJiUy6BA5FAQQQAABBBBAAIEACPjX50dqu9/cpH1eL1NFXoTs5wD0LE1AAIGmEHAB6KqaBLGipado2o7j9cYHQU0QC1wAum4AeK6u6XnSXYtUeVSOInG78xprisHBNhBAAIFsF3CLEcaViHZQ+9n76tYdbTHCZUE9yWV7X3H8CCCAAAIIIIBAlgu4mEPqY507tqPyRlYpbkkPniU/8EAAAQQQ8BRJVqos0kubz7pU32w3SqNdjcxAld7wezmQAej+6p8zS7OqP9Bup3TQbrckVWInuSgnOd7bCCCAwPcCqUSBfS6+p+WH7KIbp9iv3fnALdrKAwEEEEAAAQQQQACBJhO4Uvu2P10DP1is0vUtOSxF7ecmo2VDCCCQ5QL2eZgsVCzyrpZcs4tuOifIiWGBDED7HTZSu/5mrH730lwtaZOnnKRlQbPKbpa/OTl8BBBoGgH78LfPxJiXr6VPddCN+wRxld2mkWIrCCCAAAIIIIAAAo0RGGZl3iZZmbcrtfdJ52jHW79VqU1L9rgmbwwmr0EAgUAK2HV4qrXyvXf01e676I7pBKCzsJtr76qmtERj/lOuin5RRQlAZ2E/csgIIJAeAfcBWWG1pjZQm7Kxenabs1X8EUHo9FizVQQQQAABBBBAIGwC/uKDtpiWBaF3frRK1Xtb7WdKY4ZtINBeBBD4WQF3TW4Lsnp5is0bott/87bmLwryNXkgM6Bd7/p3W4t14tit1WNkiSqT1ljutvLmRwABBOoE3HSfPEUjs1U2ehddOyaoq+3S4QgggAACCCCAAALNK+Bfj9+uoVsN1zYzSrWyFYsPNm8fsDcEEMhsAU+eFcVPxDqozf3H6O2jbMaIK4kZyPrPricCG4D209bv0eE7DtWvXi5TFQHozH7vcXQIINDMAm4xwkrFo73V6a1ddfeuL+j9stoTgxfYk14zE7M7BBBAAAEEEEAgrAIu+Sv5P509uo0KRlWz+GBYxwHtRgCBnxWIJDyVR8v025P66Mjb+0u2np2qgwoW2AC0n7beRx3azNCJs+KK9nHp7Sx4ENShTLsQQKCRAslWytF4vbXHeXq82LJVIq5WXyO3xcsQQAABBBBAAAEEEKgR2Ft7592ufu9b3eeN61a6Dmz8gS5HAAEEGiJgSV/JSlVHeqvjd3/Sw4PG641Pg1z/2dkE/QQQcQW9pdtu/EqfjchRntWcSsYaMih4LgIIIBBwgWSkZjGYnAnra/QJdecFMqAD3uk0DwEEEEAAAQQQSJeAX35jsoYO3VeDpi7UUi9HUZLB0gXOdhFAIBsFElZ+I1qk9tPb6fzd/c/NbGxIfY850AFov57pVF3x+51V+mC5m1iuFHWg6zs6eB4CCARewM0MqVLc667O3/1bczY7RjcvDvLCB4HvUBqIAAIIIIAAAgi0uMBou+YenUzp5HvnqMuR+UpYIphIBGvxfuEAEEAgUwRsVkiyrfIiMzRn5O/0z3EEoDOlZxp5HH76+qnadv2bdeibc7SwZ75y7ERIELqRpLwMAQQCKGAr76baK997QLNOOV6P3spihAHsZJqEAAIIIIAAAgg0g4B/DX6Ytt/gDh342jItXS+qmGU/cw3eDPzsAgEEskTArsHVRvmJpzS373Dd+XEYksACnQHtxp1/F+ET/eWhtio6OKGkKz8VzZIxyWEigAACaRdwq+9W2eq7vdTu6eG6d+gkzbYslVSKxQjTTs8OEEAAAQQQQACBoAnULD74hc4+uVB5t8aVcmuLcP0dtF6mPQgg0GgBC8QmLDAZLVDOKzvpod1na3YVAehGc2bOC+vuwKae15+O3F5d71miilRUXuAD75nTAxwJAghkuoArw2E359RerSqP1uRBk/Xu22GYApTp/cLxIYAAAggggAAC2Srwsc55rb3yBlgA2qpvkP2crf3IcSOAQDoEvLhdg8cqVX7RBrr28mEWjJ5kQel07CmTthn4QKx/F+FcDel2jgZ+XKXq1q4SNA8EEEAAgR8IJGKKRJerYswmuma0/UtN9gpGCCCAAAIIIIAAAgjUR8BP/rpBB257irabMU8rojmKsPhgffB4DgIIhEKgdg2mhHqqbeWJmvK7CZr5UliSvwIfifUD0O5keI4iU5aqfKhlQCfsNizTgELx9qaRCCBQHwF3Iowr6bVV6/89pXc3H65JVfV5Hc9BAAEEEEAAAQQQQMAJDLaMvmIp/q3GXp/SgtM9xSi/wdBAAAEEVhNw5TdsZkjUZoi892cVD7hLxRVhKL/hCAIfgK49EQ62E2FxfJqO/PNAbXRjpeI16e68CxBAAAEEagXq7sR6PdQudZve2vsUTX7aX0QGIwQQQAABBBBAAAEEfknAD6Dsqy3bP6ajXpqrxVvkKUriF8MGAQQQWE3AFh9MtlOB96Q+u2mY7jk9LNnPoQlA+x16pLb7zb065MU5Wtw2XzlJVuLlcwABBBD4gYBdJCSjCeWO76VL/+TfvMMIAQQQQAABBBBAAIFfEvBrmL6oI/bcXBs9Ua2ES3ZzJd14IIAAAgjUCbi1lzooX2/p49130f3Tw5T0FYoMaHc3tjba7qU+0znFRcrd2Trdapt6lOHgYwABBBCoE3DTgSqViPZWh09+p9t2ekb/WximEyIDAQEEEEAAAQQQQKDRAu6aO/WNLrgpJm9Ewq1xTdnLRmPyQgQQCJ6AxSST9tkYaaPIp9fqzn6j9e3KsJTfqI3JhuThB1Ee07Fn7KaNxi3WylRUkdC0PyTdTDMRQGAdBaw+fiJfUe9lLTzwQI2fFqYpQetIx8sRQAABBBBAAIFQCqxad2n/Vqer/6crVdnN1l1i8cFQjgYajQACPydgAei4/VtspVJXbawrzrf/d7NELDk2HI/QBGD9k+Jl2qf3n7TNRxWqzo+EJ/4ejtFMKxFAoCkEEnZzLmorEE7oqctOsA3WZLM0xYbZBgIIIIAAAggggEDwBPyEhXt06MGHa6vJ87QiFbOEhuC1lBYhgAACjRNway5ZaSJ1VZvq4zV133s087mwlbwM3UnBZUKfKU0tU+V+Lv3doiqU4Wjc+4dXIYBAAAXcidGmBXlWJ3/R1ZqxyVV6bnmYpgUFsEtpEgIIIIAAAgggkFYBPwD9kUbe214FR9SV34ildadsHAEEEMgiAVfustrWW+qk1u8co8cHTdJrFXadXVMqOIuasU6HGqoAtH934QWdcHxfdb0jrkRN+vs6CfJiBBBAIGACdmJUNxXpfr1zxNGadB9lOALWwTQHAQQQQAABBBBoIgG/1OXe2qrHEzri1bla3CtPMVvYmkSvJiJmMwggEACBpJKJdmoVfVIf/32Y/n1eGK+xQxWA9k+Ow7R1n4k67JU5+m49y/KzLOgUq/MG4A1NExBAoKkEUgmbNhlZpJUP9dW1w93JcaImJsN0d7apJNkOAggggAACCCAQZAE/iDJNRx86UL0fqFKCxQeD3OG0DQEEGiWQsCSvDirQNH3Q/zA9+HbYsp8dWqgC0K7B/gnyG108xVP8APuVFfz2KMPRqLcQL0IAgSAKuPJEFYpHNlCneXtrwqCn9NEc/wZeENtLmxBAAAEEEEAAAQQaLVCzXsgiXfKAzTA+1FVzI/u50Za8EAEEAijgylxa3NFWIEzOPEqvDSpWcbzmFyFbayl0AWg/iPKQjjhyP/363kUqTdmCW6FzCOB7miYhgECTCqQSecqJPqvPjjlM990TxilCTcrJxhBAAAEEEEAAgYAJ+OuEnK1BXc7T7p9WKd7GEhkC1kqagwACCKybgH0uWsA5FfOUd35XjbrKtuaSYN1skVA9Qnd28E+Sd2hYh9+r76elquwQtaLf7u5DqHqexiKAAAK/IOAWSbCfSFTRRzrrrweBhQACCCCAAAIIIIDA6gJ+gsKDOuzEA7XFbQtJ7mKAIIAAAj8QcFnOVprIW19FpSdp2uC79cassCZ3hTXoWjNN6DtddFeVUsd4TBPiIwIBBBD4iYCrS5WjWOlovbzJLSqe79/AgwoBBBBAAAEEEEAg3ALue+EYjfFshnHyfZ31aBfl72fTyylvGe5hQesRQOBHAi6xywLQ0V5q89Jw3Tdkkma7bOhUGNdXCmUAerAUK5bi7+jYg7up10NxVXOi5GMCAQQQ+JGALZSQ6qLW3lR9eOyh+vfd1IFmiCCAAAIIIIAAAgg4Af974YHqt8EUHTljjhZ2zVdO0gIrEYQQQAABBGoFEkol26sg8qQ+OH+YHrgqrNnPziKUAWj/ZDlMv+08UcNnzNWyPnmKslgCnxAIIIDADwRSiZiikfkqeWgrXT88zCdLBgYCCCCAAAIIIIDAKoHBGmxJXcXxB3TUYUO0wf0VSiRd+TaMEEAAAQRWCSQsBN1eRRUPa87mR+uOL8I8qziUAWg3FPxAyiQdcfNe2uTU5apMRuRxwuSTAgEEEKgTsGlByQrFIxuo45wDdP8Oj+rtb8mCZngggAACCCCAAAIImIDnyrWV6NIJtq7ScW6aua2r5BbW4oEAAggg4D4kaxcajBQod2o7jT649lf2wRnSR2gD0HVBlNT9Omq7g7XZawtU4sW4YRvStwHNRgCBnxOws2OyQDHvWX1+8KH611Q/2wUxBBBAAAEEEEAAgXAK+Bl8p2nvNher/0fVSnS1ZK6UfW8MbXwhnCOBViOAwC8J2GdlopVyo/foP4f+RdMmhn1GcehPEC4QfYxKZxQobzs7YdpJk5pVfIQggAACvoC7a5tUKtpOBTcV6pLTwn7XlpGBAAIIIIAAAgiEXcCfEfe4jt9rd2305ELLgyaZK+yjgvYjgMDqArWziattNnHn/x2gu2028fsL7bOzZuHWsEqFPQDtpgglluiqU8u19Oao1YF2gZawDgbajQACCPxYwE4SKftc9Ozz8Yur9HHfcZpUHua6VYwQBBBAAAEEEEAg7AL+jLh3dMH4btKJcZsxZyZcR4d9YNB+BBD4XsBlP+cqFv1ci24aoFtPC3v2s4MJdQDav3N7pn7X51rt8sqXWt7FBghZ0HxoIIAAAqsJxK10VRe11ov6bpff6fqXqAPN8EAAAQQQQAABBMIpUJeIoHM1tPVV2u21Ofqmb75yqP8czuFAqxFAYA0CLomrSgmvu9ol79Mng47WP9/gGjrkAWg3TobZndpJlgU9S6c92FNth1crGbfBEuNdhAACCCBQK5BSMpGjguhXmn1df008kzrQjAwEEEAAAQQQQCCcAv73wIPVd9cHddgT81Sal2PJz9R/Dud4oNUIIPBTAVd+I2kB6NZqPbONLtze/h7ahQdX1wl1BnRtAHqYBaAnJe/Q8AOOVb8p32p5KqZo6F34EEEAAQR8AVcHusLKE22gnP+crpmDbtQTVe4MyomUMYIAAggggAACCIRLwE/gmqk/j9pA7UfbAoRWgYMErnCNAlqLAAJrEbDyG9HoZ1o8Ynvdcos9t6b8b9jVCLTWjQBbwTfvQvX7MCVvg7pbE9iE/d1B+xFAoEbA3cGtVrXXVR1XHq7793xI78wgC5rBgQACCCCAAAIIhEvAXwekv/rnPKd9X12p+LYR+55ov4+ES4LWIoAAAmsWqL12TkS6qWjR/vrnwCf12f8ov1FrRZC11sGdMJPzdOWlnkouTsqzOxMsRsgHCgIIILCaQDxHkdgnWnr+Drr5Kj/7BSEEEEAAAQQQQACBcAj4QZQbNGzzo/Tr98pUHbUAdDgaTysRQACBeghYADperXisg9o8UKgL/mB/d/HG0Gc/E4CuGzz+apSTNW7r3bX45TIlC9wIoY5VPd5dPAUBBEIh4MpwJO3GXIHynjpZs/ez0kW22EzKowxHKLqfRiKAAAIIIIAAAvID0E/oj2fsog3GLdVKS32OEIFmbCCAAAJ1AgklU13URhP0zsGnauJUP94IEBnQNWOgLoji2VSiaLEOfnyZSoZYHei4/Z7FCHmXIIAAAnUCFoBWoXJL79PMTUboifkEoBkaCCCAAAIIIIBAeAT8QMo8XfZ4QqX7WPDZZfW52qY8EEAAgdAL2N24VLXdlOukys/v0JTNT9dnlaFHWQ2Au5V1GH4905u0/wknaNsRDUIxAAAgAElEQVTbF9nd3Ch3c3mvIIAAAt8LJO1ubjsVeK/pq0OG6I4plgXj2U8SIgQQQAABBBBAAIFgC/jZz6dq8Po3a7/X52ph7zzlUP852N1O6xBAoAECbtawzRCOxuVd0kOX/dVeWlPutwGbCPRTCUD/qHsn6Nyiw9Xpw+/0XfccxVKU4Qj0+KdxCCDQAAE7cybbKt8r1v8m7K+7T2Q6UQPweCoCCCCAAAIIIJDFAn7C1inaYej12ufhBSrxYpawxfVyFncqh44AAk0mULf4oNdNbZaep+IdxuqZj7he/iEvAegfetTcnfhWF15u/3OBTS+3GqdMKWqydyQbQgCBrBZwd3RtRd/o+mr73ll6ebsb9WSVfU7a0jPu2oMHAggggAACCCCAQIAFXKmNxHcadXmlqi+wxQcpWRngzqZpCCDQYIG4fS7GrJrCA1tq3OFu1sgojUpxrbzKkQD0amPKvztxnnbe8jLt9eo8rWidYxnz3NVt8BuPFyCAQAAFXE2rKiW97mpdeqaeG3Kjil/nrm4AO5omIYAAAggggAACqwn46370UZ+8N/SH6RWKD7JAC+U3GCUIIICACdReJyfUS+1S1+iVoefo8ce5Tv7p0CAA/aMTq/uru0Pxoc6a3F75B9uiW3H7FYsR8rGCAAII1Hw+RuNJlcVaaYfT2+uQG+s+H93nJA8EEEAAAQQQQACBAAr4AejndOdG2+mrD5erPNfKb1CuMoB9TZMQQKDhAi4AHVfKa628d6+XtmadpDUbEoD+kYt/l+Ia7XvwSO046Wst83KsCgdZ0A1/E/IKBBAInoDdoLMAtGIFSk68QXluapFdfFCGI3g9TYsQQAABBBBAAIFagboFCFOP68hjd9Imd5aoMmmBBFe+kgcCCCCAgJXvzVMs+qWWjvitbrrFQFh8cA2jggD0z7xVRmtw7Azt+l6pKn4dtYxoAtB8piCAAAK104ssAO3lKXfBiXqg7xR9tNjPisEHAQQQQAABBBBAIHgCfpLWGzp9Yh+1HVahBAHo4HUzLUIAgUYIuOvjhJJqp4J5w3TvgCf12dd1N+3sspnH6gIEoNc8HmruVryjkSN7qvVYW2QhYfEWt+gCDwQQQCD0AhZwThUpz/tQ83cfoFunc4IN/ZAAAAEEEEAAAQQCKuASDVwKwvnao83f9LtZc7VoY8v0S1iCFtfHAe1zmoUAAvUXcDOEK5WMdVN0fK4u+5O9kuznn+EjAL0GGD+Yspc222CSDpu5QpUdbZEFynDU/z3IMxFAIMACdsGRbKN8b7r+d+0BuvtsAtAB7myahgACCCCAAAKhFhhsM4OLVRw/VtsMmaCDHvtaK3JzFWWGcKhHBY1HAAEnULv4YFI9VVR9l97c9Y96ZAaLD/782CAA/fM2EZfll9ANE77WV8flKT+esrsavM0QQAABBLyk3daNrFT1mxvp7wNqSxRRB5pxgQACCCCAAAIIBE3AD0A/oT9esL16XF6ueNy++HFdHLSOpj0IINAYgaSV7PXKpJc30uW71MakXe4qjzUJEID+mXHh37W4W3/Y9Q/a/Jl5KomyGCFvIgQQQMCdVb2klSaK9FbHhf+nZwf+Tc99ThY0IwMBBBBAAAEEEAiWgL/Oh/ued6FyHrJr4oNyFKH8RrC6mdYggEDjBZK5yoks0cdHbKoH7httSVr2Q+3nn/EkAP3LA82zk64W6qIZNoK2d2tv2a0MVvtt/JuTVyKAQEAE4komu6pIp+jRQ+/QGw/52TEBaR7NQAABBBBAAAEEQi/gJxhsqm6dZuj4d6oU726JCJTfCP3IAAABBFxSll0TRzqp8LN/6NYBI/X1EpKy1hJgZdj8vIB/9+JhHXXYYG10f4WqWIyQAYMAAgjUClTbSTfHpmFesZGuunCYLUQzSbLPSB4IIIAAAggggAACQRDwgylTddQAux5+vUzVSctgIyErCJ1LGxBAYF0FbDaIF41o5aiuGnfpYCtNVCzF13WjQX49GdC/0Lv+CXcH/apouo58bYFW9s2Rx5SjIL8jaBsCCNRLwE4eiYRS0bYqeGawHtlvlmZV+9M067UBnoQAAggggAACCCCQ0QJ118Opl3TK2b9Rl7+XEoDO6P7i4BBAoHkEaktSxiO91HbJpXrtt6M17Uuyn9duTwB6LUZ+Vt883XdOQm/+ParWFoC2OuM8EEAAgRALuFUHk0p5BcpZur8e3OJVffwtJ90QDwiajgACCCCAAAKBE/C/283QqY9tpk772sw3MqAD18s0CAEEGipgpXmt9nM0skyVt2yiv4/gOrh+ggSg1+JUl9Gnv2vYemdr27e/0nfr5dqivzbgsKvfGONZCCAQUAF34i20RRc+V8keW+va5znxBrSjaRYCCCCAAAIIhE7AXQe7Rv9dB7Q+Vzu896UWb2CLbdmaSClKcIRuNNBgBBDwBVwils0EVgcVlP9dLw4cref/a9fBnv2w+OBahglB1Hq8j/ygyhxdcE2homdVKcGd33q48RQEEAi2gAtAt7YA9Gua+9e9dNcoTrzB7m9ahwACCCCAAALhERimYba+x6TEn7T94Fs09MmvtDzfMv5YgDA8Q4CWIoDAGgU8q/OciiWVfPAO5f9hlEbZZbHLUPVq/uTx8wIEoOsxOvzaV3/Xfn1O1YBZy1ReaDU43OjCrx5+PAUBBAIrYPWIIpHlqnhxU10zmAzowPYzDUMAAQQQQACBkAkM1mBbUKs4/oiOHbmLeo8tU2XCU4RSlCEbBzQXAQRWCbjs52ol1F1tq8/Vs0PH6oWn/Zt1OK1dgADq2o1qnuEGVV/1TZ2s6jvtTscxEUXiNv0oVs+X8zQEEEAgcAL+4gu91f7bKzRj6wv16AKC0IHrZhqEAAIIIIAAAiETqCtD6WIFVnLjmnvmatFR+YpW2/zynJBR0FwEEEDgewF3/RtX0uugnNev1ks7j1axK7tB6Y16jhEC0PWE8u9qnKMhu/xNezz9jRbn5lALup56PA0BBIIo4N8B7qa28VP12EG3acbj3AEOYk/TJgQQQAABBBAIk0BdADrVQ206vKszX61Q1WaWgEX95zANAtqKAAI/EbDPxlSBcrwvtPjQ/rp5IslXDRskBKAb5DU6Mtqef64WPPedOg3OUcLVwGIRhgYZ8mQEEAiYQDyiaGyFll28qW68rL/658zSrOqAtZHmIIAAAggggAACoRHwgyr36YSt9lGPt638hmeZf8QOQjMCaCgCCPxYwGU/W/mNyPoqnH2EHth+kmaXWUCa2s8NGCqcRBqA5Z+IZ+u8A7oqf2q5qmxpYE7EDSDkqQggEDAB+wyM24k4tr5aP5ijCw+3v9tpmBNxwLqZ5iCAAAIIIIBAiAT86973dMaxPdX2nytVnbTAAYlXIRoDNBUBBH4oYNe4iXzlRGdr/siddds4Zv42fIQQgG6AWe1UJOlMDcq/Svu+Ml+lW+cokrAsaBZjaIAjT0UAgeAIuDvBCSUjrZQ/e2uN23GOli3zp20Gp5W0BAEEEEAAAQQQCI9AXQA6NV0n3Ly1epxSpioC0OHpflqKAAI/EnDXvFWKRzqrzbcn6eFt/qVZ8+1z0rMf6j83YLQQgG4AlnuqvxrwazrphF9p/dvKa+4GewSgG+jI0xFAIBgCrg500jKeWys/PkLTtvyX3vqYWljB6FtagQACCCCAAALhFPCTCT7S2TM7KH8bW3TLBVnIgA7ncKDVCIRewJJOk0XKiczWwisG6h8Xkv3cuCFBALqBbnUnY/1RO7S+WfvMXKQVm9pihFYLOsUJuYGWPB0BBIIh4E7IreyE/LVWHLylxk0hAB2MfqUVCCCAAAIIIBA+AT/4fLUO6nK2Brw3V0vXy1PUrX1E7CB8w4EWIxB6AZdw5UpM5qjV0hP0YL9H9P7XlJxs3LDgJNIINz+48pb+fOrG6ngzNbEagchLEEAgMAJ+APp9zfvbTrrt/whAB6ZraQgCCCCAAAIIhEzAz+w7X7vt+VftNu1bleTmEoAO2SiguQgg4AtYpmm8UpFYNy26Jkfjz5FG268ovdGYEUIAuhFqfhb0Serf5gYdNGuRyjaOKZIkC7oRmLwEAQSyXsAPQH+o76YP0s27E4DO+i6lAQgggAACCCAQUoH+6p8zS7OqL9ZuZ1ys3cfN14pETFFKToZ0PNBsBMIs4Go/V6vK66z1ljykKTscqVc/Ga5hkUmalAizS2PbTgC6kXL+neE3dMrIjdVprBUktwFILehGcvIyBBDIYoHaE3Mi0kWtv/qb3t18tCaVshBhFncoh44AAggggAACYRZwpSWTi3XRHeVKHm+R52pLNsgJMwhtRwCBsAp4iaQqo3na9NbOOukUaZh9JBJ8buxoIADdSDk/w+9obdfxTh046xst75VLLehGavIyBBDIZgFXF6tSca+X2q88X4/t/ne9+joLM2Rzj3LsCCCAAAIIIBBGAT+BoL+6tXpFpz77nUoH2UzfhAWgyYAO44CgzQiEWMBd47o05yJFy9/Q2/321GOfkmS1bgOCAPQ6+PkBltc04oLN1fnyElUl7XYxixGugykvRQCB7BOoOzmn2ikWuV8LTj5R428brMGxYhXHs681HDECCCCAAAIIIBBOAT/J6ijtv+FN6v+fElW2i8pjAcJwDgdajUCoBSLyElWqjnZTt/ExnfEnykyu+3AgAL0Ohn4t6OP020436aD3lql8PRuktj4mKwSvAysvRQCBLBSIKBqvUGmstwZc7+mwM6wJMfshAJ2FfckhI4AAAggggEA4BUZbMpX9JOfo7l2L9On0SiUoMxnOoUCrEQi1gEuwiiupTsovmar5gw/TP94ZruHUfl7HUUEAeh0BV9WCPnXUhuowOs5Jeh1FeTkCCGSjgJ1M3BVKtEh69gQ9st8kza5iilI29iTHjAACCCCAAAJhFfAD0G/o+HP7qPtVlaomAB3WwUC7EQi3QM21bYFS93XSlUcYhStDxMKD6zgmCECvI+CqWtD9e92pQ978Rsu65CrHpimlKMWxjra8HAEEskeg9i5xyuuggrnbaMLADzV3HtOUsqf/OFIEEEAAAQQQQMAPQL+uP9+/qTocVqF40lS4rmVoIIBAqASSSqbaqzD+or4ZsI9ufZvr2qbpfgLQTeDoZ0G/pFOu7qf1zl6hSqsF7XGibgJbNoEAAtkj4E7UbZWfOlIP9HtEH/2XE3X29B1HigACCCCAAAIIuFKSLqngvzrzvfXVestqJQhAMywQQCBUAhbIS1hiVbSdWj3QWhcf7n8uhgohTY0lAN0EsHVBltTR6t/zJh3wTonK21ELuglg2QQCCGSZQCqRp5zoIpUcuJnGPTK6ro5gljWCw0UAAQQQQAABBEIn4JdOG6/9O52kgR/M1fLOeYqyAGHoRgINRiC8Au4GnNXZSHVQfvlkfbLnkbr3NWo/N914IADdRJZ+pt9bOu2vPdXmokTNuK2pE8MDAQQQCItAMk+xyCdaevFA3XgZAeiwdDvtRAABBBBAAIFsF/CvZy/TXjueq52enacV+bkEoLO9Wzl+BBBogIBb16hayWhrtX2wvc4/3KutbEDt5wYY/tJTCUA3EaQ7YY/SqNTh2rrrfTps5pda3NUyAakF3US+bAYBBLJCIJlfE4D+7sHtdcthBKCzos84SAQQQAABBBBAQIM1OFas4vjF2uOPl2jXCRaATuVYPpWbfg4PAgggEAYBV1LSsp+rntXH2x2g+9+jpGTT9jonkyb09AfnS/rTxf3U9dIVqqAWdBP6sikEEMhsATuhJOOKRtprxezWun4LO1p3jrHrFh4IIIAAAggggAACmSzQX/1zZmlW9Twd8Lek+p/nqTxuX+VimXzMHBsCCCDQVAJ+7ef2an9Hoc490bbrsp9dHXweTSRAALqJIN1m6upm6RTt2O4qDXmvRBU9rBY0dbOa0JhNIYBA5gq4mlmVSni91HbReM3c4hRNWejXE8zco+bIEEAAAQQQQAABBPxgS1JXTvxKy4blKha373EEoBkaCCAQeAErtZFMKOm1VnT5M1q+w3Dd8OFojfEsyZQAdBP2PgHoJsR0m/KzoN/WaWd0VZtxdtJOWPoftaCb2JnNIYBA5gm4AHSVnbi7qnXFNXp5zwv09MvDNCw6SZOom5V53cURIYAAAggggAACNQJ+wsDe6tPmIR393BKt3DamCNexjA8EEAiJgJdIaGW0hwbd4mnYiGEWw5tE7ecm73sC0E1M6k7eY+xOycea1uE+/f6VuVq2qa0enCQI3cTQbA4BBDJOwAWgq22Nhm5q612sZ064UsUTCEBnXDdxQAgggAACCCCAwA8E/CSqvurcZ6ZOf32xyjrGaq5hU24KOg8EEEAgsALuGtbVjGylnOVn6dl+EzRjLrN409PdBKDT4OoHXF7Wyaf2U7ebl1kt6Gjt6pk8EEAAgaALVHtK5FSq09Ub6Jxz/XqCQW807UMAAQQQQAABBLJVwM/2e1IXDxwgzahQwk075/o1WzuU40YAgYYIJCxeF/1KJX/bRjf8X91nH6U3GiJYz+cSgK4nVEOe5teCPlaD867X4P+UqOrXNqC5g9wQRJ6LAAJZKWD1s+KVisd6q8ND0rnD7e+uHSxEmJW9yUEjgAACCCCAQEgEahbb+kQXHdde3p3Vilv5NI8ykiHpfJqJQFgFXO3nKlV7PdVh/qG6f9uJeudbV9GA2s/pGREEoNPjKj8L+lOdf0SRvH+lFCEAnSZrNosAApkjYCeVRFzJaAcVzNxT9+3+qj4uYQpT5vQPR4IAAggggAACCKxBwMUFUrN0+tW91fbsKjKgGSQIIBACgaSSiXYqiL6hr0bvrjvGUD4yvZ1OADpNvn4t6NkqbvWghj7/leZtm6tcF4TmTnKazNksAgi0vIC7ixxXItJBhfN214RBr2vOHL+uYMsfHUeAAAIIIIAAAggg8HMB6Lf1l0d6qs1QAtCMEQQQCLqAq/2ctIm6rZT37Xma1u82zVps8Tqbv+sxezdNnU8AOk2wbrP+3ZMXNWJ4P3V8sETVFn323Fx03NPozqYRQKBlBexOcqqDWqX20oRtXtLct7mT3LL9wd4RQAABBBBAAIH6CLynMz7oqqJfWwkOd8nKNWt90HgOAghkq0BN7edvtezM3+rm60iaSn83clJpHmO7s3Lp9K+0ctdcVhNOvzh7QACBFhZIJXIVi/5Py/YboBsft4NxMz+sliAPBBBAAAEEEEAAgUwS8EuljdOB7UZou8/ma0XHHEVSJE1lUi9xLAgg0JQCrmxkleKRnur4/qG6Z3BfDVvmtk/t56ZU/um2CECn1/f7LOhztMtOV2jIc/NUFsuxu8mc0NMMz+YRQKAFBWoD0AtVcubmuu46O5CahW1a8IDYNQIIIIAAAggggMAaBPysv2u0b//TNfCl+SptRQCaoYIAAkEWsNIbyXbKjbyuBUfuoVv/zYzd5ultAtBpdvZrQbs7KZ/q7HvbKO/IhFIuE5Ba0Gm2Z/MIINBiAkmb7RGZpxW3bKnrR9hR1Cxs02JHw44RQAABBBBAAAEE1ijgB16u0X6/twD0xPkq8QhAM1gQQCCoAm7Nompbs6id2rzcRhfszLVq8/U0AehmsPbvKl+hfTY9U4NmLVJJYY7Fn8mCbgZ8doEAAi0hkMyzAPRcLXtya924Dyf1lugC9okAAggggAACCKxdYLAGx4pVHL9MQ0aeq8FjF6g0aXVR3ew1HggggECgBOoWHky1UevkfD07ZBMVF1P7ufm6mAB0M1mPtino9pP8VuddHlHsAsuMTloAmhN7M/mzGwQQaFaBmguXZUp89Cv97dfNumd2hgACCCCAAAIIIFBvgf7qnzNLs6of0BHj9tWmZyxXRTwiL1bvDfBEBBBAIGsEUrbwYCS6TBUP/kpjD3PB51EalbKsaGbrNkMfEoBuBmS3i7q7KqmrtWfnEdrlze+0opfVSLXFCVMEoZupD9gNAgg0j4C7s1ylhNddHb8brzkbjtAtpf4CN81zBOwFAQQQQAABBBBAYG0Cdd/P3PVoIqWxD8zVgkPzlBO33xOAXhse/44AAlkl4K5Rq5VKradW5VfplQGX6OnZZD83bxcSgG5Gb7++1nI9cGq5Zt6cUH7CU4pa0M3YB+wKAQTSL1AbgE5666t1yY16dfuz9eQHnNzT784eEEAAAQQQQACBhgj4CQInWRb0dTrome9UOtjqP1swmvWKGuLIcxFAIPMF7BrVZulGIhVKXNNLV54zuq5KQeYfeXCOkAB08/elN1A98h/RH2cklOhncRpKcTR/H7BHBBBIo0Dt3WUXgG6TuEGv7nu2Hn+alYXTCM6mEUAAAQQQQACBRgj4Aeid1Kfzszq2eKFKN7e1iuz6lFm6jeDkJQggkKECVlbIFh6Me+1V+PU1emv70Xp0niVIefaTzNBDDuRhEYBu5m71swAn6egD9tAGD5er2q1FSBZ0M/cDu0MAgfQKxJW06U2tvRs148Sz9cQd/gI36d0rW0cAAQQQQAABBBCor4B/bbq7Ntr0MUuQWqTSjgSg66vH8xBAIHsEXO3nWDRf5We21TXXkRzVMj1HALqZ3d1d5jEa483WpNi/dOSUeVq6T75iCbvtQhC6mfuC3SGAQPoEEkom1lNRdKxeuuT/9PRf/QVu0rdHtowAAggggAACCCDQEAE/CDNIG207Xce9vkhllhkVIUbQEESeiwACmS6QtAxoq3Wfev8wPTJwsIatZOHBlukyTi4t4O6f6O/V7wcdrn7Tv1FZTq48t+wm/dEC/cEuEUAgHQLJ6qQKclpp9i0dNHEEAeh0GLNNBBBAAAEEEEBgnQRcElRipo4csqE2fqZK1XH7OwsQrhMpL0YAgUwSsDhbskCxyHR9+vvf6/7JrE3Ucr1DwLPl7N1qw8lFuujWSiVOtjvN1Npqub5gzwgg0MQCnry4XcTEeqnzRE/nHGqbj9oMkKT93r4D8EAAAQQQQAABBBDIAIGaAPQXOuuYQrW6y0qoWQA6RQA6AzqGQ0AAgXUXsKBbosLWHuyqwicGaeqB+2v/BNnP6+7a2C0QgG6s3Dq+ru6ui/bTb7o+qkPf+Forulm9rRQLPqwjLC9HAIGMELCTS8IWIox2Vqvn99b0vYpVHPcXusmIA+QgEEAAAQQQQAABBGqSov6rkReur8LLqpVI2N8pDcm4QACBrBew69FUla1L1E2ty+/Rm4OP16Nvkf3cst1KALoF/f1SHC/ohBFbqdtN5apKRBThhN+CfcKuEUCgaQQs09lWGk5E1lPhu0P1wG5Pa/YSAtBNY8tWEEAAAQQQQACBJhJw8YDUBxp5iyUNnGLJAwSgmwiWzSCAQMsKuIQo+0CLFkhjO+qKs+turrnPOB4tJEAAuoXg3W7rgjHeaA2LjdI2L36ppdvnKkopjhbsE3aNAAJNI+AHoDur8Msh+udOr+jzL7nj3DS2bAUBBBBAAAEEEGhKgdk6Y0oXFR1oAeikXaW6rGgeCCCAQNYK+Nei3dXmswN118Bp+mSxxd9s0TXKQbZkpxKAbkl927cfkBmtPXc+Wzs9s0zlOZYCzYKELdwv7B4BBNZNYFUAunXJfrpr++f12QcEoNfNlFcjgAACCCCAAALpEHhfI1+1WWuDCECnQ5dtIoBAcwskbTZHgfK8dzX/uN00/h6/+kBzHwf7+6EAAegMGBHDbFrAJJseMEfn3ZajyIkReQlbpYtSHBnQNxwCAgg0TsDV3LKFbGTZNNpON25vJ/83OfE3zpJXIYAAAggggAAC6RT4WCM/ba/CPnG5y1BLEuSBAAIIZKmAS4Sy2s+RXmrz3Bg9vfdoFdvMDrsw5dHiApxcWrwLarOg3Uqcl2vfXhdqj9fnat56ecqxCQKc/DOgezgEBBBopICd5eNFyo1dp9f3GKWnnicA3UhIXoYAAggggAACCKRJ4J86Nv8obfT1N1rZMVeRFNegaYJmswggkHYBlwTl6ggVKa/8Or26yyV6ZhazcNPOXu8dEICuN1V6n+i/KV7WiNM3VbvrEzXvG1F/K73sbB0BBNIq4MVj8mL2UXZYF136oO3Kzexg4Ye0mrNxBBBAAAEEEEBg7QL+4tC364geR2uLDxZoWVGOogSg107HMxBAIEMFLPs5nlDSrj+jY3voMhYezLB+IgCdIR3iL0i4gTbI/VDHv7BQZdvn2YKESRaByJAe4jAQQKARAgm7kIl+o5LT++m6G+tuqjH9qRGQvAQBBBBAAAEEEGhKAT8B6mYd2O8EbfPaApXmWzlIAtBNicy2EECg2QRc6Y1Kxb3eaj/3Qj0+6HK9NN/tnIUHm60L1rojAtBrJWq+J/jT02/VQUOO0daPLVJZzL4EsCBh83UBe0IAgaYVqAlAf6ey0b/WtWMIQDctLltDAAEEEEAAAQQaK+AHoP+hg3b7o/o/bQFod+1JALqxoLwOAQRaWMBLRuVFPtGC43fS7XdSeqOFu2MNuycAnXl94spuJMt0+d3LVHq0p4grYUMpjszrJ44IAQTWLmAB6Eh0ocqv76uxZ9jT3TnHLW7DAwEEEEAAAQQQQKAFBfzkpxs09OCTtO1km4GrGBUgW7BH2DUCCDRWwAJmiSqlop1V8Ozemr5PsS08aFUGUmQ/N1Y0Pa8jAJ0e10Zvta4Uhw7QFj3u12GvLVZp95iV4rDfE4RutCovRACBlhHwkhaAjixQ2T1b6NpjCEC3TC+wVwQQQAABBBBA4McCfgD6Rh1w3Ina9s5FKk1FbfYtUggggEA2CbiFB6uVSHZWYdmdemePEXp4pv/5lk3tCMOxcoLJwF723ywv6tTj+6rT7VbHJmHR5ygrEmdgZ3FICCDwCwLfB6AfswD0/gSgGSwIIIAAAggggEBmCAzW4JhlCcav19CRJ2u7sVb+sWb6emYcHUeBAAII1FvA1k7zIh2lKwp0+YX2Kha+rzdd8z6RAHTzetdrby4Leri9gdZXn9gNOu6RL63LzP8AACAASURBVFX6u1wrqG4BaL4Q1EuQJyGAQGYI1AagF6r01b4at2NmHBNHgQACCCCAAAIIILBaAPpSC0BfbBnQCcuAdoEbHggggEBWCEQsTlaleKSDWv33FE0eeK/eW2nxNBYezNDeIwCdoR3jF0y/Svv++nht+2aFKgrtC4ErnkqfZWifcVgIIPATgZQtQuhZRs1/N9e1W+GDAAIIIIAAAgggkBkC/dU/Z5ZmVVsG9HUWgP4LAejM6BeOAgEE6idg9Z2TCSVSbdQqOUfz9tlK/3iO0hv1s2upZxHMbCn5+u23ZupAqf7v/HLFrqy2Uhz2JosQhK4fHs9CAIEWF0jlWgD6W5V+sZXGbdTiR8MBIIAAAggggAACCNQIrBaAvsMC0MdbwkDcSnDE4EEAAQSyQcAynRN2rRmdp7Lb7FrzZILPmd9rBKAzuI9cKY4xGuPNUXHuZRpYbJ01wALQCTtkpkZlcL9xaAgg8L1AzWI2ZapadJ6+6DpJk9znFw8EEEAAAQQQQACBlhdwweb4Ev393yu1+A9RxeJ2/UkAuuX7hSNAAIG1CNSV3vB6qsPX1+j1bc7RlEWU3sj8YUMAOsP7yC/FcZ+O3vFwbT79ay2LxiygQxZ0hncch4cAAq5eUKpSCa+32i59VJ/1PkB3lrgba3YjzT7CeCCAAAIIIIAAAgi0oIBbX8jWGfrb5LlaenAeAegW7Ap2jQAC9RVw15hxpVKd1Spyh2Ye/mc9+gDZz/XVa9nnEYBuWf967d0PQs/QiHGbqP0Z1bJSN2RB18uOJyGAQMsJuC8HVUp6XVW44na996sRmjSfAHTL9Qd7RgABBBBAAAEEnEDd97Ga/63UlY8v0LJ9cghAMzgQQCA7BBIJpaK5ypvaRaMOdlUDRmlUiiSnzO88AtCZ30eqC0DrIG3W/kEd+9o3WrpJvmJ2tzrl7lrzQAABBDJSwAWg7YaZt55al03Q21udqsmfE4DOyK7ioBBAAAEEEEAgRAL+9zH3pwWgn1uoFbvlKJKwKWqUegzROKCpCGSbgJ/g1EtFSx7WjG0P0eNcX2ZRJxKAzpLO8rOgp+voAwZo46lLVJm0bwcEoLOk/zhMBMIo4Aeg11fhytv1n21GaMqHBKDDOBJoMwIIIIAAAghkkoD/fewk9c+5SQc/P18lOxGAzqQe4lgQQGBNApblHLef2Bda+peBuvkGSm9k1zghAJ1d/eXuSCeW66J7l6v6SJsmZXepbY0vHggggEAGCqzKgC6suEOzBo7Q1Hf8m2kZeLgcEgIIIIAAAgggEAoBPwC9v/q3mqxDnpuvFQMJQIei62kkAlkrYNeWiUqLf/VWuxeGa+q+k/RalX2WJSm9kT1dSgA6e/rq+1Icp2rn7jfrwJe+1PzeucpJUYojizqRQ0UgRAKrAtBFlXdq5s6naOqbBKBDNABoKgIIIIAAAghkpIAfgN5bfdpM1THTF6isPwHojOwqDgoBBEzAXVfaQmipAkVWPqD3d3KJTcyszb6hQQA6y/rMn2LwocYc0kElD8WVm7BOJAs6y/qRw0UgDAKr1YCuHq+Zu5+uR14mAB2GnqeNCCCAAAIIIJDJAv73sX21ZfuHdegLC1T6GwLQmdxjHBsC4Raw+vSJfEWiZWp1Vi9dcK1p1FQHCLdK9rWeAHT29Zk7Ylf7OblM199ZpnnHRRSlFEd29iNHjUCgBVbLgE6M15t7WQD6OQLQge5yGocAAggggAACWSDgfx/bU1t1mabhLgC9eY6iLHKfBX3HISIQNgFXeiNhpTei8p4frxl7zVbn1ERNpPRGFg4EAtBZ2Gm1Xxikh1XYaS+tnLFIlRvn2puSVYuzsDM5ZAQCLPDDAPTMfU7X1GcIQAe4w2kaAggggAACCGSFgP99bB/1XX+KDncB6M0IQGdF13GQCIRKwOo7J6uUiPRS0Yp/6Y3tjtKjH3M9mb1DgAB0lvad/6Z7WsP330GbPbJU8VTMSuNYEJo+zdI+5bARCJrAaiU4krdq1r5/0ZSn+MIQtF6mPQgggAACCCCQbQL+97Hf6dddH9URxRaA3pQAdLb1IseLQCgErORsNPqNSkdso3G3cC2Z3X1OsDKr+2+0leIYbXeELrjpO8VGSHFXA4d60Fndpxw8AsERWD0Afbtm7v9nPfIEXxqC07+0BAEEEEAAAQSyU+CHAeg/vGiLEG5CADo7+5KjRiCoAq70RpWS0V4qmLarXji4WMUpW3iQ0htZ3OEEoLO48/xSHEfrifZjNeSlCiU3jylC7a4s7lMOHYEgCaxWgiN1u14f+mdNe8xfSDVI7aQtCCCAAAIIIIBANgn4Aej9tGn3h3RM8UKV9CEAnU09yLEiEGwBdx2ZtDUGc9Vh8VN6daCV3viMRKbs73MC0Fneh34wZ7x+v+dJ2vaJL7XUsxWM3SKFPBBAAIEWFVg9AG2LEB5gixBOIwDdol3CzhFAAAEEEEAAAf0wAH30iwtVujEBaAYGAghkjkAykafcaIX++8fumvJPOy4309/N+OeRxQIEoLO48/xD979AvKczxnVSwRlWqJ0FCQPQrzQBgWwXWK0ER+oOvX7ACD1GADrbO5XjRwABBBBAAIGsFyADOuu7kAYgEFgBT6lEXF40V22m/kMVh8zWbG+iJlJ6IwA9TgA6AJ1odXA8Czp7g9WvzQs6qvhLLfxNrqIEoQPQtzQBgWwWoAZ0Nvcex44AAggggAACQRVYvQb0IzrSleBgEcKgdjbtQiCLBCyulbTSst4Gii64VY8NPEXvzKH0RhZ14FoOlQB0QPrSn9Z+nw7fcS/1eXalqnOiVoojJdHHAeljmoFAtgmsVoIjMV4z9zldU5/hC0S29SLHiwACCCCAAAJBE/C/jw3VFutN0mHFC1S6GSU4gtbLtAeB7BNwiwwWqVVksb7+w4Yafz/XjtnXh790xAQng9WfNXVxPtElF3ZS8jK7c5S0v1MPOlh9TGsQyBqB1QPQt+mtPU/TlOl8icia7uNAEUAAAQQQQCCgAv73sT21VZdpGv6CBaA3JwAd0M6mWQhkiYAlT8aj8mLzVHLbb3XDydJoS6gclbKsaPsnHkEQIAAdhF6sa0NdKY7ISTopcqU2eKxMZXvmKGmlODwXmOaBAAIINKvAagHo6gl6a8ipmvIiAehm7QJ2hgACCCCAAAII/ETA/z62vzbt9JCOtQD0ii1sIXtKODJWEECgRQRc6Y1KxSO91WH2GD2542gVr7D4FsHnFumN9O2UAHT6bFtky/6XiZs1sM+p2v3lOUqsl69Iyt68ZEK3SI+wUwTCK7BaDeiqOzRz1xF6ZAYB6PCOB1qOAAIIIIAAApkh4H8fO1D92k3U71+Yr9J+BKAzo284CgTCJuCuGRMWbC5Q6/Ipmr3bCbrvTa4ZgzkKCEAHsF/9etBf68zhRer4YIlWJi0F2s1boL8D2N80CYFMFVgVgC6ssBrQg07Xo2/zZSJTe4vjQgABBBBAAIGwCNTNnE1ZCY7CaTp0+gKVbEcAOiy9TzsRyBwBd72YstKxCRVEe+jTcz3962ppcEwqjmfOUXIkTSVAQLKpJDNoO7VfKIZbxvOkxHs67abOKhphZTjsDZyyNzIPBBBAoHkE/AD0+ipcOV7v9D9Nkz/yL3ia5wjYCwIIIIAAAggggMCPBfzvY3urT94UHfvcQpXuSACacYIAAs0tYNeLibgS0S7q+Fiuzhk6Rp43itIbzd0NzbY/AtDNRt28O6r7UuGdrz+0vVI7Tv+f/tevUAVJu7tEKY7m7Qr2hkBoBVYFoFuXTtD7W56iB+YQgA7tcKDhCCCAAAIIIJAhAv73Mfdnpa54fqFKdrVFCOP2dxKWMqSPOAwEgi4QsbrP1Yp7HdX6qxF6dMd/auZXzJYNdq8TgA5w//pv3gd03NYHa+OXrbZXQa4iSlKKI8C9TtMQyByB2gB0wltPRSvu0Lu/GqFJ8wlAZ07/cCQIIIAAAgggEE6Buu9jrvGpCl32pGVA70UAOpxjgVYj0BICdXWfk4WKRspVdHA3nTfVLyXbEsfDPptHgAB08zi35F6s/LMSk3TEGUO0ybgSVSRiikSoB92SXcK+EQiHgPtiUWUB6J5qv2yaPul1gO4sCUfLaSUCCCCAAAIIIJDxAjXXiRUaPXWhKg+wEhxkQGd8l3GACARGIOHJi65QfNyvdNVIMp8D06+/2BAC0AHv57q72xF7Q6dGKXfy1yo5MCYvYQFo94WDBwIIIJA2AReAjividVDFwlZq3dXTaJuAwQMBBBBAAAEEEEAgAwRcuQ0LOo+/f44+OSxfBfb/SUpwZEDHcAgIBFnA1X2uUjLaTa3f6q8bB7+nBeUWt0pZQNrCVDyCLEAAOsi9W9c2/27SXzRgvcu19+tLVLFBrqLJpFLUgw5B/9NEBFpQIGWfNd48lX62pcZt0oLHwa4RQAABBBBAAAEEVhPor/45szSr+jVddfsmWnJCpWJxjxrQjBEEEEijQG3pDaWsROPyaZq968H617uU3kgjeIZtmgB0hnVIug7Hf1N/oz2H5Gv3x8u1JBq1wBClONIlznYRQMDKzSdtOmdkkcpmba5rt0EEAQQQQAABBBBAIDME/AD037THuJHa7YwFWpGIKsIs2czoHo4CgUAKWKZzIk/R6NP6/JgjdN89lN4IZDf/bKMIQIeov/0g9BxdeHY7Ra8uUzxpA4As6BCNAZqKQPMK1AagbWGb6X01bvfm3Td7QwABBBBAAAEEEPg5gcEaHCtWcfwmHTDmeG1zyXcqIwDNcEEAgbQIuMznVE0p2GSsnYr+UagLTrUdxVxAmtIbaSHPyI0SgM7IbknrQbmAc/JDjZzYVgXDbJoV9aDTys3GEQizgJ8BXfrw5hp3iEm4cw61vcI8JGg7AggggAACCGSEgB+AvkFDzzpJ211jM9aSUXkkJ2VE73AQCAROoCbu1EWFr16uZ/cYpRcqx2iMZxnQrBEUuK7++QYRgA5RZ7um1k1x0Aka0Pl2HTL9f1q0eaFyk3bniS8bIRsLNBeB9At8nwF9m2VAn0wAOv3i7AEBBBBAAAEEEKiPgD879gbtf+xJGvDPRSpNWQkO4gP1weM5CCBQbwELNKVs0UGvjfIXnKMndr5db34y2mbi2w/B53orBuOJnGCC0Y8NaoVfZ2eyjth2f21evEAlBTGrxEE96AYx8mQEEFi7QCLHanxZRs3lVgP6Int6zQyMtb+MZyCAAAIIIIAAAgikU8APQF+n/fc7RQMeXaBSz0qn2TT5mhlrPBBAAIF1FqhddDCVaqW8SIWWHNxNN0xh0cF1Zs3aDXByydquW+cDdwtMJB7SUX/aTRv+Y6XicftFlC8c6+zKBhBAYJWABaAj0fkqP2NLjb2eADRDAwEEEEAAAQQQyAwBPynpJh008ET1t6Sk0lwC0JnRNxwFAkERcDWeo5aQVKXUFb10+YUu+DxRE20tMo+yjEHp5Aa0gwB0A7CC9FT7IPDsTW8BZ7shpctvm6uyE3KtKLy1kZWPg9TRtAWBFhXw4jF5sbgiR3bTpf+u+3xxnzM8EEAAAQQQQAABBFpQoO56MGUB6E1P0Db/WaiSQgLQLdgh7BqBgAnY1NeEld6IdlDuk/vppaG26Kkr/Zoi+Bywjm5AcwhANwAraE91Xzpcm87Tjq1Ha6/nFqlkuzzlJJKy8l88EEAAgXUUsNva8VbKiU3R+3v9UZOfZrrVOoLycgQQQAABBBBAoIkE/AD0Y/pD+320xRdfannbPJsQy4zYJgJmMwiEWMCCzMlKVUe6qf1XL2rGjkM07Ut/1kWIWULfdALQIR8CfkDoYu2z5SXa9flvtbBTrvLsi0eSRQlDPjZoPgLrIuDqfcWt3HMnFXrba/yAd/X1mwSg10WU1yKAAAIIIIAAAk0v4IJCx2rl3Hzl9kjKEhSpAd30yGwRgRAJ1F4HplLrqyjxuD7a50Dd8xzB5xANgF9oKgFoxoH8oNAS3Xt4Uv/9d7liLgWaADRjAwEEGi3gvnhU22rHFoBeto/uHVisTz4iAN1oTl6IAAIIIIAAAgikTeC/OvONrmq9nU2Xt8WiU1wHpk2aDSMQbIG6RQeTBYpFn9PnZx+qf4+1FtesPxbsltO6+ggQgK6PUjieU/OhME8Xjc6TN6pcibgNjlg4mk4rEUCgqQXctKtqJSKdVfTZUN2zy7P6+FvufDe1MttDAAEEEEAAAQTWScDFA1IfaOTDndXqoGqlCECvEycvRiDsAl68StWx3up+9xgt/aNd/9lqgykWHQz7sKhrPwFoBkKNQF0NMDcekh/rwgeK5B1q8Wi7S+VRD5oxggACDRawD5OEZUBHO6nVG/vowT2KNbvUrzXY4I3xAgQQQAABBBBAAIF0CPgB6Js6q3CEJQ+wKH06lNkmAiEQcNd/dgcr2kWFr16u1/ccrWkruf4LQcc3oIkEoBuAFfSn1mUnpm5Rr3an6OjnvlBi61aK2DwspmEFve9pHwJNLWAZ0Hb3Ox7rqXaPezp/f/u7u9Fl/7Wb4DwQQACBDBPwF2Ze22GN0ZjvvzuP0qh6fZ7xubc2Vf4dAQRaUMCV20jO1l/O76I2VxKAbsGeYNcIZLGAP/u1UJHPr9Qre1yjl75g9msWd2iaDp0AdJpgs3Wz/ofECzp8s+3V98UFKumSp5itRkEQOlv7lONGoGUEUtVRRXIWq/zOzXXt8YM1OFas4njLHAt7RQCBIAj4QeLVg8CzNbvmu+ykmgbW/PfHQeHV/16vgHEzW/34u/jqf6/5f6uf//0h9VXfmjasHvwmwN3MPcbuEAiWQE0Zxm902aE5qnjAFg6z72opyjAGq49pDQJpFXDB50rF1VPtqyZqzt6H69Zi1v5JK3nWbpwAdNZ2XToPfJh9EZlkK5Yeu9cQ9XlkocpiUXkubZHxkk52to1AgAQSSiZs5ePolSq+9BI9O6q/+ufM0qzqADWRpiCAQBMKuOCyH1h2QeVFWuSVqKTme4d9drigq83qrPlpssfq+yzUjIIOyq9ZeCuuwrxcm8ERV6XtN5ZTrmSeZ7NKc5Qbq1Ykf9UBWKl7VdmTopGIIvE8xStiynPflxIpFVVI39lTO+kplax0gWMXNE5TsNgdd9Q+Z1WkolRndU6tHqhO0z6brB/YEAIItJyAHyQ6S/vvOEr9X16hqqRdCHLd13Jdwp4RyCoB+wJSc9cqT/ZVSK3+1FkXjCf4nFVd2KwHS0CxWbmzamc1d8Mf1tEjd9IGY62QfDxi9aAJQmdVH3KwCLSYgAWgU13U2rtJrx1/lh6/kwzoFusKdoxAiwn8OKg86acZyn5Gcr0zk/dWn7wqxVqnVGk/yk8pVtBeqYLrtWHRUg3smKvlbSKKFloR00ILvLayMmKt7ctuKzsW+9NrZTHs1hZbKbCCQEX2+wK7ZrK/K9JD7SJ5ilrQxUvZTfdISom678gRt3iOu76y3UXc72qC1LUP9zu3YJfnWZEhP0juSg1ZpNxLJux3Ofb/c7TMItWWVyiV2XNX2nNL3Z+2AauNr3L7s8T2uzKiZJm91p6jspSS5YUqXPGWliy5Qc/Yc70K+zd7btJem28/ORUFKi1/Up9VNqCD/e/93//psqt/nFVNwLoBojwVgSwX8ANF22r9vi/rtNcWqqQoRxH3gUacIMv7lsNHoDkE7LMinqtorFLeuB66dKTtM2bfm+xLFGUXm8M/2/bBiSXbeqyZjreuWLwFnFN2DXfp+LmqONHuasXt70zJaqY+YDcIZKuAnVhSVUp6XVWUuEGv7n22nniWGmDZ2pscNwJrF/ADzX7mspXbqVnU2H7cYlb1evxTx7ZbrMXrW3R3vZTi61sA1/5UZ/t7+z/ptwX5alMUV9yCzikLLKfaWcC2vft/+/fWtpPcMtuVZ0He2piJiwX7f7rd//jrrv/v7t9q/7+iJkBcGwev/bP2NQ35orx6FN1VvXevdv/NV8yi1j8+rtWPzyf64TG744jZ6wqUW7Mda2uV/bnMtrvMnumC16UuYG1bLy3XhkvH619LjNzSrqPzo0otqLQfWwho/nGa+F0DLgRrsqntpuH3mdRpzNyu19jgSQggkD4B//vZEP2q26M66sVFKu2ToyjlF9NHzpYRCIyAfRexVUtT0ZgSTxynhw+2m+LV9t0lXbO9AuMW5oY05Ht1mJ1C2Xb3hcRddIzRrnkXaa8n52nZYLvIsWmlctnRPBBAAIE1CqwKQLdZ8Q/N2uYvmvwpAWgGCwLZK7B6JrM0+vuGjLJYbd0XyTVmMLuZD1HNb1uusnbt1a7dLTqs3RLNtyBzTlfLMO5mG7I/va7tVdC9l9q3q1aVlbpQnm0sd3WthVpp0WwXYF7z11YL7ibdT13QeQ1PsgTlnzz8Q6/9h3R+If4pzpqygmoyqFd71ISc7ZeWC10bGLes7DWvx+GeE1Gluli5D/9h7bGkAVXmKFa52MqEfK3vlprfN/a7efZv31qA/8tOinxzp2bOf1ZfL7e6Isssg2nZL2VUu4xIe63nj4DZGub5pUVqDcl2yt53OUceVoG6pKPUYG2Q/6T++MwirdzJMqC53gvrgKDdCNRTwO5WJypUHe2lLh89ozt320sfzuN6r554IX5aOr9vh5g1UE2vWRn5XA3ucaGGFC9X6cb2pYS74oHqYhqDQNMKuKnolTZVvZetaXO7nt3wZGo/Ny0wW0MgjQJ+sNmymCOuBrPVX15rJvM4HdiuROW9Y4r2TCjec3dt22ugOncr1bKuVg6jq8Wp17cwaqdyyzJeUxA5biFWu4ixIOqq6hZuQRtX4sKCnlZ72f3eDyL7gWP391VB5KBPF3eNre12P8jrB6y/D/paDcZkTYmQ1QPVfhZ1nnJ+MmrcBi3obFnW0eX2wvkGPi9f3rzl2nD+LbrrG/vdl7bbr9qq1Zen6dFv1zLs3L5d5rT8GtR2IdqkNbvTOOzZNAJhF6gpvZjQVfd9rSWH2+eCZTGu4UMj7Eq0HwEEagRcXbIKK1XWVW2Wvqqvh+ymf8yi7jODoz4CBKDroxTy5/gfJhM0eMejNfjxr1XRJp+pWSEfFTQfgV8USFpAI7JIy1/pqxt2chET+1ljhiSOCCDQ/AIuyOz26i/65x+BBQzd//4kaOgWEY1pSQerbNzhZv2+V1KVm9vzNrOfjQqV13szdWxjBSysvnKq0F2XrLCM5VILNkdrJkzVvvVddqwFmK1aRk2Q1P1m9e+gP0lRDnpAOZ29vipYvWovdWVF6j6HV2VbWwa6RfotgbzuUVvqw2VTd6wrIuKV2+y3sgUqKf1KJV9ZpvnnVs/6007q9P5YPfvlG5q/pJVyl7yqj0t+pk2RunH1/T9T0iOdvc+2EWi4gL9Q9K36/RVHa6v/W6zyuNXCp+xiwyl5BQKBF3DB52pLEOisVsnn9cVh++rOydbomptYgW88DVxnAQLQ60wYjg34C4iV6ITfV6jnfZWqsFo/7qIlrbNWw4FLKxEInkDSsmci36j09t9o3Ek18Yw1BLWC12xahEBmCqye1WyZze4gXbHkNT5cNvNylfWxhUT7FCinz2navrtlMW9kf9/Q3sgbVirxg6CE/d5W0ateLbPZS0ZtplRtzWMXbK7NVCagnJljwx1VbcDadVHNumMuBm0XlwnLpLZVGWs+vFM1mdJ5liu96uHqU1tPK7LIvgt+3kZ5cx7Wu3P+o/lzLKf6f5bT/tlleumLX2h11IJekY20UdKV8SBbOnPHB0cWfAE/2egq7XX8mdrxjgVWYt5VrudzO/h9TwsRaIiA+75g3/uSrZQffU1z/7Kv/nkDC803RJDnEoBmDDRAwEpAqzi+XH89rUIVN9hUz4RdYLoLFMZRAxR5KgLBF0glchWL2jTOs/rp5mutvQSgg9/ptDADBH4hs/knWc1bqlf7Xspvf6X22myFqvpbhvJv8hTddGv1aJ9Qwhb5U2sXeFykMhePrA1T2sNSXOoyXFYlLbsos998vhNkwEBookNYPZPaMqVdgHr1ALRFq10iQiriOt/diGhnyyXaTQs3GKrsNyti6rLkbX32mZVy+W8ntZk1VR98+C+9v7iVOn1npV2qf3SYZEo3Ub+xGQQaKuDXbb1a+w3+i7Z/er5K/5+984CPqmra+HN3Nz0hoVdpYgPEAij2UBUVRRFU7Cj2jr0mYkUUe0FQPxtKFFGxIChRbIiIqGDBQu8lpCfbvpndvbDwoiYh2ey997n8Ykxyy5n/nN09Z86cZxJF+ii0IlXde/F8EiAB+xKQcaZfxoruQhQ91BGPXqfDQvmdZBuwBoR9vV67lvFDpXZ52vpukSIVoWSY1bj1QcmAvq4CPglCu1iU0Naep3EkUG0Cfpm4uMvRdOBuuOqjcMyK27KqTZEXkEAVCGjgQPWa/y2z+QoMTMqCt3MpKjsfj733OQIdJehcuqdkuHUS6YwUfYyZ6Vos8gvmIZ/vPvmsD6syMJO5Ct5w3imRILVuiBMNar8GrHQyqv1FwtVepEtIWqVYVAIkrP9trJAFykUlKP1lDL78y4D/dxeSFz2AmaI3vdNDdaUN1ZWejMmc5Dqvi9HiGBJ4Gmc1G4nOv65EQUPZ9cAAdAzZ81EkEP8EDJ/U+fDI53He/Zg2PAf5WhdMNN0YfI5/38VPCxmAjh9fWKIlZhBa32zW4raXZfvlGRKE9klHok6YJTzIRpJA3RKIbM2STLjU8vPwfo88zFnEish1y5x3dwaBHbObF2KhkYc8DQ5vl918CNo0eggXtvZheXc/DMlsxv690LalBJsbS7aqFAssl5xmLfgXHgKGi/1tO8K/D2tEM/vNGX2rtq3cljmtGZSaR7/t0OC0BqO14GQzpGmYWsaQCRsCWLXqS5Qs8CLl+2ZY8t2j+Fr0pZtvkH4u2dTRx1B3jkh26G9USzrSh1ljoLadyPs5lsAvGLWwMVI6y05X/WzYVhnWsURoOAmQgIwWA7LI7GqFjM/vxjcDKGEhaQAAIABJREFUc/BeKed37Bc1IcAAdE2oOfyaSBBa6py3z3wJw94Rrb8jZXTi16wXh6Oh+STgeAIazNIBSkOkLjoCT2XPx5r1HKA4vlsQQA0J6OftMAxzSaBZx2s71W3OQb+2a1G2/5U4rEt7ZO1XgvL9Jdi8V7RcQqFkNYczUDU11SXFpUKqCVpHhtrMNfQNL6sZgfCCR6gIYiCsM23I2FF/TETm9rGuDfK3+RK+XjAGs34qgWtRE+AHybja2evAI1nS+i9ALema+YVXkYAQCK0+zsdVr+2GBqdXws8ANLsFCZCAvjFInMdwN0ba77fj475jkL+Cczt2jJoSYAC6puQcfp35pvMenm59PLbMXILNe6fAI0vluu2SBwmQgFMJSHDBVynbs9qiyXu5KBmswYDIohUz1JzaKWh3lQlEZznLaycsrRt1tEVmw7EY0qwlEg4sgvfIjsg6cC80ay2vudYFUgpQAgZmZrNZTC50NbOaq+wCnhhjAuFs6bC+dHQqfljGIxwRayqZ0rLRbksCylctxrJf/wC+bIoms6/H1L+aYr/NskAT/TpxS0E1aGFDZkjH2Jl8nNUJhOp1fI9rb2yLtPvlc0VeV7pAxIMESMCpBMzEoiQE1j6M7wfej5nzzaKlTmVCu3eNAAPQu8bP0Vebbz6f4+xuPbHnjLUoapbMILSj+wSNJwGJIviS4PL8gaJHeuHRa7qje8JOik0RFAmQgBDYIcNZg2jbLdTkIDt9Bcp7HI99DjgWe/TchJKeUuStkwlPJLBCchpuCdNJ1rNXJgqhzGYzeEfIJGBVAtu0pTVTOihBsIBLl1dSkYTkUGDakLx+32rRk/5uE0q/uxszf2yAzLnj8OnKndjMDGmrdgS2O5YEQvU6VuOSgR40/cALLwPQsaTPZ5FAnBHQbXKVCASbIKN8PjJOOgxXfiw7jTxSc2SnO/LirPlsTpwSYAA6Th1joWaFBiszcUH/w9F+2hoUJSZL0QqtRmMhG9hUEiCBWiCgAQOv5LC1RIZxKz4eMQafvcCBSi2A5S1sRUCDzrnINXQnkRi23SC+C5qm34lBrTOAwzOQOOAwdNhXggAdSlCZXCz5zSKdEVLUNbNGRT9XxJpVToNSGrbqJDRmOwLbNKUN0e7Qf+HFG/l9qPKRLsA0ktB0IhKX/olNf/6MFd9koPH0MZj583Qs3LQDTtGQzolkR4fKInJ3DvsbCQgBc3frBei6z8MY+m0RytJUq521ANg9SMB5BMI1fRBMlKSGZGSNbIAbJjDz2Xn9oC4sZpCwLqg6755agNAnQegzD0P759eh2C0ZkCryx/7lvL5Aix1MQAcrslJuSIGKkrH46qib8f48aoQ5uEPQ9BCBf9Nxnoyh7mn4s8tF6HXggWh98GaUHpWOxH30w1P0cVEoBQM1ACCBZ59EqyPZzfxsZdciASVgZklLgCzgR8AjX4bsEAiFovUog3+dhM8+L0LqV3fh7UXpSPr+ccxevwM9eWllu2S3AfWj2a0cTcAcr3VHx8yvcN4na1HSPQFulVGjvKKjewaNdyKBgHysJiHBLcu0tzTBXfcJg1DSoRNZ0ObaJcAAYe3ydOTdoibX/hk4//Ij0f7xdSgJyHZgFjdyZI+g0U4loDphohnoaonM5VMxv9Mw5FU6lQXtdjYBM8s5X7Kc83fIcj4J3ZpdhIOPaAhj0EHo0FUWbdpLplnj8oh+sz+U4ayZzUZAgs/MbnZ2V6L1VSRg7goQJWnZhafJ0QH5j6Ff8i+AxsgIJsCzeA3W/zwfGz5agIIZr2DxqoVYGP055ZEMr+BkTA7IVcyMriJ7nmYrAiEd6C24/dUi+Ibr4qd8nmmiEQ8SIAEHEIhkPkvw2eXxIfhwS9wzisFnBzg+hiYyAB1D2A54VGhlbBrOz+2FtndUoMwvk2fRomS2lgN8TxNJQAkEkuBxLcaGD3vhqWP1tc/tzewYTiEQyR77n8KB+vv1+Kzn/Til+xYs7ZuEpL6pSMgsE/WNIlGxDes3G36R0tBCbG5+Zjqlx9DOuiawvY50IEHlayQIjSzRkfYh4CtAxdwmSJj+CuZ+/Q2K57/wv9nRoYKGDEjXtad4/3ghYNbtuAcDbr0eR969BsV+SShiIcJ4cRDbQQJ1TMDMfJbvzzXHPRfK42Q1VhMjuChbx+gdc3sGoB3j6ro3NKzHN0xm0JNFfeOyR/5G0ytTUOmXtywOXOoeP59AAnFAIOhPRoJLJix3dsbDo3NEN0y+5P2ABwnYk0DUDiDNltza1yfigYwG+PEgCXYddyK6HFKBin03olj0ND0hDWfN0gxnOOswzNDBPbc427OL0Ko4IbB9hrS+3gwZnIY11VWyIwvpv87Hkh9+QslHLfHDjK9w4hpZPIr+/PLI61QWijgJjxOXshl1QMDUeM1Fv+NuwVFTV6HEkyiLo1wYrQPYvCUJxBkBLSQvr3fJfA5MuRLvnJ6HhV4Gn+PMSTZoDgPQNnBiPJmgk/FwbXLZP4zcF5ei7BzZwiFB6JBuEA8SIAEbE1AdTsnsdE3GL30uwuRZDEDb2NkONS0q4KwEttPCG4pue92OYw5tBE+fTGT1c6O8hQzisQmlIR1nCUZLwUHZ2S8LM5zMO7QD0ey4IqCLQLpwJJle7kr4jQzJjE6RYLQbFWUb4J2ThPRpOfjwq6YYMGeHYLRLAnUGM6Pjyp1sTC0QCCcTGcFncXqTC7H/oqXY1DRJisvzM6sW4PIWJBDHBHSB1Q23WySsZpyESafMwR+FrOMTxw6zcNMYgLaw8+K16ZE3K0gF5aRr0Ov1ZVh3ggznGYSOV4exXSRQCwR00UmCbYZkka3fH091/xOrlnPgUgtgeYu4IKCT8t7o7c5Hvgadt2rDPocz2njgPX4wuh7fAJ4eG1DSXCNaPvmnGxYl8ByQ1Vc9n0HnuPAkG0EC/0vAzI6WQLQE2oKugGivJ4R2JwSRgeSKNKTNfRc/53tRnvcEVi+S9wFZTNp6eDQ4vUOAmphJwLIETPm033Dj7IbwHC6fZvqxxl06lvUoG04C/05AF2NlDudqgIRv+2Pysd/i142cw7HX1BUBBqDriqzD72uuoOdgaPodOOCd5djSh0Foh3cKmm9rAvJh4pdJijsLnukjMOUE2bZVab4P2NpwGmdLAmYRQRmAq33bycicgK7dHkDfQyRX8vgWSOstfT9tI0okHTqkL+uTAoLMcrZlr6BRTiFgBqT1te+DX7cjo5EIdaQgwbsKhX9kIPWN+/H5p0tQ+l0evi6L4iKZ0ZDM6CCLGDqls9jQTvnUU/m04BxcdvceaHJLObwMQNvQzzSJBJSArCz5pQi2uyXSF3+LH445Am/9ZUrxkBAJ1AUBBqDrgirvGSJgvnndi76Nb0Lfj1agsEcC3KymzP5BAjYk4JLXdiWKPM1x2JgkDL1RTNSq6dFZYja0mibZjcA/aTpPwAmdgMTBZ6JbP+nrvTajLFOzI2XbviIIemSXj47jqeVstx5Be5xOwCxkKC9w0esIuFSgQzUxVTe6AdLnTMPCL4pRNuU0TPp6B31oakY7vfNY1P5IADowD5ce0x5NPqyAV7s/pRQt6k82mwT+iYDUIQmUw+dqgcyl32PJMYdi/K8MPrO/1DUBBqDrmrDD729mQN6KPu1y0O/j1SjcM4Ga0A7vFTTfbgR0gl4p8huSDep/CN8PuwVvT8lGtmeHbcp2M5v22IRAVNBZs7y2ymucIJrOD2FgnwD8w9sj80D5Y+p6yXTWQwLOurji0mxnamPapCPQDBKoAoFtAemgyyu60VmSFy3a0d6l2PybSHW8+gy+nQkc9L0pyRGRM5CM0pwgZTqqAJin1DsBc+v94ejY9gOc890WlDf1iC40P+vq3TVsAAnUGgEz81nmbps/w4qBR2P8HLm5LjRtV9+k1h7IG5FAhAAD0OwKdU7AXEnLwYC9b0P2NNm+uDuD0HWOnQ8ggZgRUO2wSllBb4PMtffjk/1uxSdrKb8RM/x8UA0JRCbZqmu5NVN/Mvplbkajwedj3xMqgSOLUdFEby8ZIlpeN+ARTWeJUbs5Ea8hdF5GAjYhYAaiA7JmJRId7iRZltJJVSIS/VlImPU1/pyeh78njcOnK6NM9lAv2iYdwMZmRMZv6I7unjk45e1V2HIcd7Da2OE0zXEEZOAbFNkNoyUyCr7E0sF98NxnTBxyXDeoN4MZgK439M56sLmafgv6drsLfd+TIHRbBqGd1QdorX0JSDAukAKP63ds/LQXnuzLwhX29bXVLdO+CdF1zglnOoeynQegW9oRaHbIBehxRmMkH+uDp9l6FIeCScx0trrH2X4SqHsCGozWNxP5HhAteLdXNKMbikiHJJJtXouyj5aj4LX7MHPuJ/h7baQ1+vZi6DsRs6Lr3j98QvUJSPA5YR7mef/G6DuTUSIfmS4Wk68+Rl5BAnFHYJvsRnrJF1hySj9M/EgaycznuPOUfRvEALR9fRt3lm3LhO7b7Tb0eXcVitoxCB13bmKDSKDaBDQAnYoE158ouLkHHn1AJtQ6sd6ucFu1b8oLSKAWCews23k8TtpzD7Q8PRsdjt6MokM0aKSZzpoZQk3nWoTPW5GAgwhoMFoD0VKUN1SM1MyMzkTyb1tQOf3/MH/qKLw7KwpJqHBhHrc9O6iXxL+p5pztJvQZcB8GTFuKTQnSlynDEf+uYwtJ4B8JmJnPLZBR9BWWDpXM5+nMfGaHiTUBBqBjTdzhz9s2oOnb8270eWclilpKQZcACzc5vGPQfEsTiASg8Q5WHnQuJsxjBrSl3Wmbxus24lzkhrIM5QgtiByK3ZvJZ0/2fmhyYSNk9NgoxQRFZgMJ8AREYkP+UdPZNh2AhpBAPRMIZ0arTHwg6JXMaLe8w8jEv7IC635eAffEW/DJjLfww2KzmeEdGqE9GlzArWffOf3xpozapchOvwfZP5egop1bJKg4X3N6z6D9ViWgmc8VIpfYDGnlX2LV0H54ZprYwsxnqzrUwu1mANrCzrNq080g9K3o3yMX2aItVthGtMW4tcuqDmW7HU1AdXF98LsaI31BNzx85B/YVEj9Z0d3iXo3fmfZzuMw6MDzsM9pSWgwqBQVe1dIPFp0yyXw7PLLoFy1OHQQzoMESIAE6oSAflbKjbVegscQpehUed9xI7AlC63eycP8t4Zi/HtyjlkE1S1jZeQhj8Wg6sQbvGlVCJjJBDMx4pWeaDdcFms1rT+0SMKDBEjAOgS2aT6nl36OpcP7Y8I7ZjzGOlawpXYhwAC0XTxpMTvMN72b0f+w0egzdRUKmngkA02SRTiwsZgv2VynEwh6XXAlFMD72N4YcxUHNE7vD/Vjv5ntrE83swcvwXENr0LP/uXYePF+aNNjBbZkaCK0ZCH6DbhCO+VZTLB+/MWnkoBTCUSKF0pmdDAYgOH2yQ6MlsgMrEflj4VYM+E7fPDe2Vi1LMLHpTs47sSdEvjbGpx2KjraHWMCZgB6MXJOaYxgXhm8slOIAegYu4GPI4FdIhCl+Vw5G8sk+PzcW3JDZj7vElVevCsEGIDeFXq8dpcImJpDGoS+C73flEzoFokscrFLTHkxCcSagGQ/B6WKcuAqTD3tKXz3JrXEYu0BZz8vkm2vA2mfSeI6HNnhTBxwRmc0G1qI8m5yDkrghehX6jkubiF2dp+h9SQQLwTCetEuv2yL9shuDCRr2VO415cj+NYL+HbSTfjg86i2enRxjfIc8eI9+7fDDEDfjdN2uwR7/Cg1ErIkmEUdaPu7nhbahMC24HNGhWg+ny2az5M1UWgyJqvsnLnjxibW0gyrEGAA2iqesmk7t2VC9z5qNPpJJnRhlmpxMkBgU4fTLFsR0C3F5ahwtcduK+/DFwfcgrz1lN+wlYvj1pgofeeQVqoufIxB90MrUHT5wWh71BZUNJNsLQnnGLKF3TBksMNs57j1JhtGAs4msE0rOih7NHQnYBCt0bBsAZZ95UGzpyfi51njkLdJKem4uQu6BJkV7ew+EwvrI+M53VVk3InUKcuw8cQkJPgCCHhi8Xw+gwRIoOYETM3n5kj3fY6/zh6AFybJ3Zj5XHOkvLKWCDAAXUsgeZuaEzAzJm9Cv36j0fuN1ShqpLqc1OSsOVNeSQKxIWAE3PAaRWgwuRNuOy1Hskvli8WTYgPfkU+JZGTp2CWkjXouspOPR5uTBqPz2QUoO0aKJKFItrTLd58Mvpnt7MheQqNJwLoEwhIdRigrOk20orVwYSqSFv2GLS++KlnRY5C/ImKdnDpUgtXUibaut+O/5eYcbQYuvvwANHm8An6RsDJYMyH+XccWOphAdOazyG6M6I/xr2nwWRaVmPns4H4RL6YzAB0vnnB4O8xM6FvQu+9d6D9JMqGbSmFCZkI7vF/Q/PgmILPkQAaSXL+j/KQeuO8dzZLh9uD49plVWxfJxNIaAaHA82Q82aIVFp67Fxqfk4qEvTeIyEb4MyMkUMlsZ6s6mu0mARIIEQhnRYe+ZFU34NJQdBZSVi7C+rwnMWf8BHzzSwQVdaLZZ+qMgCnDcS367vkQjv5mCTY0FKkYynDUGXHemAR2jYBuoZGFIqM5MnxfYMW5/fDMqxp8NsfPu3Z3Xk0Cu06AAehdZ8g71BIBc5X9VvQ56E70z1uDLW0loOCTwAO3etUSY96GBGqLgE6OZVJsJCF17QsIdLseOevMiUptPYP3IYHI4qRm1Ye06sZiyN6X4bCzKrBlhGintihGuW5ZD8qumYCcxKwsdhkSIAHbEVC5Ky1a6IXfnSlK0V4YlZnwT56OX14chDc/iTLYI+dphiq1PW3XC+rPIFNa7U/cMDMdnj7+UP9i0fj68wifTAI7JyDBZ3+5fE60QFrh51h+1gA89y6Dz+wt8UaAAeh484jD27MtE7r//iLH8fZKbGkvQWjKcTi8X9D8+CMgE1xfpSwOtUHg+dG4f2ROuImU34g/V1myRTtKbbyEs7oejjZXtkfmicuxsZlb1Z0lKCPbDDU2zYxnS3qZjSYBEqgOAX3PkwU3fc9z6VaQRkj3VgCffofVj96Hn2fkIz9UjFXfP6kRXR2yPPffCEQ+j4NzceXIvdDo2SJUyjZ+3WzEgwRIIF4IbJPdyCz6An8O64eJH5lxlXhpI9tBAkqAAWj2g7gjsK0wYd/Ouej79moU7ilbD5kJHXeeYoOcTEBKJQVS0SCwEO+feji+nGLuYHAyE9q+6wR2HCzfi+MPuQQ9LpbBypmV8LlKJfcvWYogSf8TLTuOYXadOO9AAiRgRQISbPBJRrTHkIB0urwrJiHp4/fx2/gheHFKVAY0M6Kt6Nw4a7O5u+0hnLjbuej6UxmCmbLdiDIcceYnNse5BKIyn9fNxqpT++OZfKGRIF9e51Kh5fFKgAHoePWMw9tlBiFuw4AOuciWTOjC/ViY0OGdgubHDQHNwpKJr6sp0v84GzMPyEN+sblFM24ayYZYikBkgqttDmXRv4TTDj4c7UdJxvOxshMmTfqcpFsZWjxFwi3c+msp57KxJEACdUIgUrBQ5LBkSU50ojMlDC3HN19h1biJ+GpqHhZW6i8oj1Un+J12U63xYdyCRi+twYozEpCoC8GUSHRaL6C9cUfAJRJ05ah0NUfm2q+w5OS+eO4rZj7HnZvYoCgCDECzO8QtAfPN80b0a3sv+kxZgcLuzISOW3exYQ4iEC4+mOj6BsseG4Dnr+JAx0HOr2VTd9R4vh/HHnkRel1pwD+kAj6UyZcUPPJJgIUT3Vpmz9uRAAnYh4BM6Px+WZyT90pDihWqSNGXn+KvJ/4PJXl5yAsVb5VDdo4EdSGPGtH2cX1MLDF3uX2Dp0/bE0teKUOCYciiR0wezoeQAAnslIDuhJHgs6c5spZ/j3VDDsOjc+VEHS+H5Jh4kEA8EmAAOh69wjZtJWAGtnIwqMltOGTqKhQdJpnQlONgHyGBeiSgxZAkAG3Mxpqex+HZ75hdVY/OsOijIxnzOnkNBUYmYkiP3uh4Uzs0OkFklxI0s0++NFDiotSGRZ3MZpMACcSUQDgjGgEJROv8zpUuGdESoJCM6KXjvsFfU3LCGtGhTFb5Ys2GmHrH2g8zd7kNx74NX8Dw79eiQGr0eLQ4JoPQ1nYtW29RAmHZjaC7ORr8vgCrTuqFxxcNlUXGvMi42qJmsdkOIMAAtAOcbHUTzeDWzejbeDT65K1EUe9EGBK0YGDC6r5l+61HQLOsJMPKnYT0WUfhtWMWYqFXJiBaEI4ZVdZzZ8xbvKPUxoM49uAL0OMiN1xnl8LnrhC5OtnpwsKzMfcMH0gCJGAnAmbBQr9kqTZCqpgWnDUTf4wdjJc/iNgpH+dDJYaxNTvaTubTljogYCYFzcCIcQeh7dXFLEZYB5R5SxL4bwIy4fLJQqNkPmPR5yg7pT8e+UWuYubzf6PjGXFAgAHoOHACm/DfBMxBz/3ol3kdej+/AiUnJyDolwG21MHgQQIkEAsC4eyqQEBEEdxpmHtRI7w/HsiWAU8oq4oHCfwrgehCla/jnN0PQZsbWyP1jDUoTtXVC3kz1/d0ZjyzH5EACZBALRDYlhEdcMl7q5Eiy3upcE+fifVjj8fjMyOPoCxHLbB2wi3MLOipuGbfo5A5vwQVbsmwd4LptJEE4oaABp/dEnxORIMvF6HZsMNx/ipKIcaNe9iQKhDgp0YVIPGU+CBgZkLrAAjIfXIDApdItlxAMudYlCo+XMRW2JyAZlRpoYv2aLbiVrx70D2YvSaXW3lt7vVdM29HqY1HRdP/HPS62I2ky4pR1qBSFDiY8bxrjHk1CZAACfwXATMj2gufqxkaBr0oevU3zHjoIMz9gYHo/6LHvyuByOc5ZDHZPR39312HkoGSgcAdS+weJBADArqgKDtaAklIcHsReOc8TB0xHQs3yU4Wyd/gTpYYuICPqCUCDEDXEkjeJjYEIkHooG75fw8jbj8au+euRpEUqXJLFXAuw8fGC3yKUwlo+rMUhHOtR+lTe2PsZVxxd2pPqJrd5vu1zlsHoXvqCHS+vDc6XVyKyg5+CTzL4qFkPIMZz1XDybNIgARIYJcImBnRXvjdEpBGFjILf8aKF6fhlzH34NOVZiBavptFC3fpebzYfgTMnUyPYcAZ5+LgVwolICbZmKrBxpiC/dxNi+KEQDj4jGAS3C4JPk8YjlevyMeScmo+x4mD2IxqEeCHRbVw8eR4IBBZgde+G/gYIy4+Ah0fWYuiJAlCizat7uLmQQIkUBcEtGJROhIqH8OXPe7AzJ9ZyKguKFv/njvqPM/AOUN6oN3tSfDstxGlIlLnFsmWoGz75oTV+t6mBSRAAlYkoPUcJBvanSmiHFLFYf0GFI69D19NmIivJaOOhQqt6NNYtNlcWL4Ew7OewlFf/43f9kpBqhQjDLAYYSwcwGc4joDuXvEhoMl2krARvLsZ7rldIbAAvOO6gm0MZgDaNq50liEahM5FbqiK90cYOSQb7V5Yg6KMZCQEAhwEOasz0NqYEJABkE9eW540ZEx5BJVD78SdooXDwoMxgW+th2wtgjJVCgwej363b8am4yRjQ1LqggEPJZOs5U22lgRIwLYEzC3dEm8WLV+gJZoumIs1Dx6EMa9GjKY+tG29X3PDzN1vv+P+2xphy+gKuAIGggxA1xwprySBnRIQjfVAGfyuVBGr88AzqjHueFhO1EA052DsM5YlwAC0ZV3HhkcIhIIdn+DiPoeizRtrUNhEsux06yAzodlFSKBWCbgkeFgRWIWuJ+2Pc6ZlS7XlfHnt1eojeDPLEojOxDgbh7R+DIfdkozU81ejIikpJLXhktUKTlAt62A2nARIwLYETGkOqasiBYYT5YPdePclfD/6RnzwnRqt27wnywIiF51t2wWqZZhZjHAcTm45AvstKkJZlksWl3mQAAnUHgHNfJY6Ka5WSC+pwIaL0vGILgxyUbD2EPNO9USAAeh6As/H1h4BcyX+K6nKfAhaTl6Ngr21QqwMhTzynQcJkMAuEtCtujIxdbVF87kXY1Lv8ZhXztX3XYRqk8t3LDL4La4a2ROtbliBLZ1Uqz8RBqWRbOJrmkECJGBvAhLwkPfrgEv0+Y00JJQbSHryLEwa8zZ+XBexXKOMqsbFw+EEzEXnNbj5UclEuNItfUfmXEz+cXi/oPm1Q0B3nfrg9zRC2pqnMfvs6/DxDA0+yxf1+WsHMe9SjwQYgK5H+Hx0rRIIvSlPx20d9oL3pQwkHV6GSr8MolngqlYx82ZOJCAT0mADJBvzsPqs3nj2FeqOObEXbG+zBp6HYZgrL1J5+2EMOuoaHH/3Biw/vAReSKEUTkbZTUiABEjAggQ0804KFboStVQsjL/nY13uBGx+Rd/vmQ1tQYfWQZPN5J8bceS+9+PYL5ZhU4aKBLC2Qx3A5i0dRUDkbESfP+huhQZ/3IgZpz2EWfMEgCTVBWU3IaUPHdUZbGosA9A2daxDzQoFobujY+YHGP6kdO4zKuELquaopGuwrzu0U9DsXSOgE1G/ZERlIeWnm/F1z8fxYaXckZsLdg2rxa/OkSy4HO0DwUHo3uQ1DLpd3mMvLUCRx4MkqUQkw2fKbVjcx2w+CZCAkwmoLEcgLLvh9sh7elM0/PApfHHLZZj6Q4QLs/Gc3EHEdjMZYRGufbkZ0s+UnXIaIGMWtMP7Bc2vOQEDAQk+GxJ8Tp99Gz4893588Ze52FPzu/JKEogvAgzKxZc/2JpdJBCdmbkeObmyU/AOyYRGAtxSoZn6o7uIl5c7k4DuJHAvx8aRPfD0BA6EnNkJ1Oods55n4JLh+6HxXRKJ3r1CVEMT4JH3WYk/8yABEiABErAFAV2EVjkl2Q6uhbCKNqB8zMOY//h4zNwiBrIYli28XDMjInOu4P04uttlOHReIcpcWu+hZnfjVSTgXAL6Piu7TWX/YIKrHVJeHYfvR16LvDLuOHVun7Cz5fyQsLN3HWqbWRxDzS842aGHAAAgAElEQVTGzef5kfKoDIoyJBPaJ3/TooU8SIAEqkAgrP3sF+3nrEUj8Mbh7TG4UC+TARE1IKvAz06nRA+Cn8eJnc9D97vWwzfEL2EJ6QyquS+FUbjTxE4+py0kQAIkYBLQ8YBftoUnyi8ao8W8xUi9YW+M/FT/zoVp5/YTc2ywCre/LMsUZ6oWtIwJmAXt3C5By6tJQHYNiuSRz5WEDNlp8scDwAs3q9QG31erCZKnW4YAA9CWcRUbWh0C0YWxbkSfI+9B3xdXobCDZEJTl7Q6IHmuowmo9nMmUozvse78o/Dk8xwMOa87RL+XTsZQd1e0uqg5Gt1dgvKGsi07om7E3SXO6xm0mARIwGkEVJZDFhoDlfC60+GuKIb/qW8xP3cYs6Gd1hW22muOC6/HEQeOwbGfLUNBmmqHc0HasV2ChleDgGY+yw5Cl0hulE/Dn1eejBefk8sNWdjRLyb7VIMlT7UOAQagreMrtrRmBEIaddejz+73YsArK1HQS1KgQ5ICFLGtGVBe5QwCYe3noEsKev4wDj8fnIM8r1jOl40z3B+y0txeq36/V7KeR6Drg8nwHFuECik15OaOEgf1BZpKAiRAAiYBydgLFclKkE0vjZD6Qx4W3HQGJk+P/J3a0A7rKmYW9C8Y9UJTpJ4rATVqQTusD9Dc6hHQAJzuHpRvnuZI//tTLD5vAF74TEbeImt0Z5DFBqvHk2dbiwAD0NbyF1tbAwLmwOhBDEi7Dr2fK0D56cWoDMjA2Uzfq8FdeQkJ2JuAbreV8p2uJSg79WA8mkcdMnv7e0frhsoW2jzpA5oB/SOuvbIbWt++Ahsaa+BBvmSATLkNZ/UIWksCJEAC2wiY2dBeBNzNkOI14Hv8fHyc+yrmqFSXJHmEChhy0doBnSayUwpjMWivi9Dje5E9TKYWtAMcTxNrREDfO6W4eyAZCe5S+Gb/jqXn9sNrUmwwPO6u0U15EQlYiAAD0BZyFptacwLRwbPpOG/0Eeh42zqUIFmy+KTKN3Wha46WV9qQQFj7udLdDnt9eh5ePa4ETb2TMZmTSRv6ekeTzImk/D74KobscSq6PbAOlSfJlmskwUMJIwf0AZpIAiRAAlUloPqlWitCvos2dNaCNWh1RUecNVuvp2xXVSla/zyz/s5a5I7xofx6akFb36e0oPYJ6O7Scnh1dykq4fu/4Zh0dT6WFMiTNBahGdE8SMD2BBiAtr2LaaBJIBKE1h8D7+Oss/phjydWoqhBChK1wrfU0OJBAiSgBOT1EJTFmeB7WN77XPzf55xEOqNfRC/UzcPgM9uj19gSFDSXAq66+KD9gu+TzugKtJIESIAEqkxAM/p0bF0pCncNgbK/UP7gPZh5Tx4WVnL8UGWMlj5Rxw9qQCnyW92P/l8sQ9FuSSEtaI4bLO1YNr7WCGhyj+4YaY1M/3pU3NYCOffrzbnDtNYQ80YWIcAAtEUcxWbWKoGQPt2nuKR7b3SS4oQbuurPslrvilTUqtWH8WYkYCUCOkCSCYPbBfcrLXD3WdJ2nVSwEIaVnFjNtkYXGjwPBzR9BoMfLIP/nCLJz6DWczVh8nQSIAEScCgBlyxWSoDFlSDDhkZI/vR1zLvqbLz9s44jdGGbkhz27himhMBSXHt1EtLG+akFbW+H07oqE5D3Pp/Ibngk6W3ZFPxyyUhM/kAuFo2ioKR3UKqoyiB5oi0IMABtCzfSiBoQCAWhB6F7k0fQ97EsJJ1eBm9QihOycnMNYPISexDQrWGSwQRZnd9wA2Ye8RBmLs5FLisx28O9O7UiWnJjGq45ogeSnxIZuq4+0aeTRTlmL9nY9zSNBEiABGqbQEQbWjRO4UpHYMPvaHDTwbhloj6HmX61TTsu72d0QqfEeTjzK6m3c6BKtDALOi79xEbFgIC+H4rUZ8AHn2Q+N/r8ekw/fxzy/5BHUyc/Bvz5iPgkwAB0fPqFrYoNga2VutfglluTkHhHMcoT3aILLZ8X1IWOjQ/4lDgiIJMEv8gtuMth3NQOdz/ArbNx5Jw6aEo2sj35yPepn0ej/agOyMxdj5JkyWLje2Ad8OYtSYAESMApBHQ3lSxkuhsgVdROkyZchqk3TsTXmzTwIl8stGXTjmCOG/8Pw/qdgM7TSlDh0R2mLFxsU4fTrH8kINtHRXIj6E6Rt7zGaPlsLj66NgfvlXJuxU7jdAIMQDu9Bzjc/mhd6OUYOTAFrZ+uRGU72RXjk9w/WZ2UFEAeJOAAApr9LP3dJQOl+SfhpUOlKEaFmM0K9jb1vTkAfhlntuyOZk+1QoPBBSjTQoPMVrKpz2kWCZAACcSSgI4rZNs5RJLDJXIMCxbCc3F/3PONBqFlwZuFjWPpjBg+Sxe35StwJzwTVqLsPNlbqgsOuvDAgwQcQUAX4EqlmHtbZBW/hUWjTsNr49VwBp8d4X4a+R8EGFxjFyGBMIFQ9dlrcHjHBzHgmXUo66+it1rFWSJwHDSxl9iagG4R88tkMBUe7zT8etzZyPuUgyR7ujyy6KYLC8GXcdoRZ+KAZ9ehcB8v/Jr9Th18e7qdVpEACZBAPRIwfAHRP22OzC3LsWFUR4wNSXJwnFGPLqnDR5tSKxfg4DZSkPC7cviaUeKwDoHz1nFDQLKedbVFxthBVyu0+GkafrxgECZ+Kw2kDn7ceIkNqW8CDEDXtwf4/LghYA6EH8PApDPRJ9eHzTdWSOaGFOFiRmDceIkNqSMC/gC8ok+29+PAiKt6o7d7Fmb5WRijjmjX022j9Tc/x/mX74d29xegJE2y02S8bHChrZ78wseSAAmQgN0JaEZgheigZiIFK1D4zBLsPWoQLioVuynJYU/nhwpYL8AN53RE2otbUO4XPWiOM+zpa1qlEWbZ8SH1pFwNZC/hBpS+mIP86ydh3ga+x7F7kMD2BBiAZo8ggSgCkYJcIdmBt3D2SYPQ5aE1KOjgkQ8VebFomVq+ZthjbEVAt8iKTqMrGQm/34sZh4wTjcbo14GtjHW2MaFJ/hU4uMFDGPx4OcrPLkAFEmWBTQqk6ESRBwmQAAmQAAnUGQHNDvQhKEVWXK7maJk/FXMvOAn/96fkQsvnUx51oeuMfOxvrOPIYRjmyhO/LsS1bzZGyhDJgudid+xdwSfWMQHdRaq1BitF8741GhZtROUNzXHHM5HHcoGtjvnz9tYjwGCa9XzGFtcxgUjwTV8bgRkY2vZg7PmEpGgMki1kSBZ9VAZr6tgBvH3MCESkN4JZSDHWYOWxnfDsR/LwUNZKzBrBB8WCQEhiaAR67PU0Bj+/DiWHqo8lCCCjZgafY+EAPoMESIAESMAkEJRsaK+7DTJXvIoF556LNz/RsYd8HgW588o+vcSU/BJpw/bXof+3S7GxSZK4mck89vGx0y0x51EBWVRrgsSv7sPnV4/GJ3OFiyH9X784n3J6J6H9/0OAAWh2ChL4ZwJbVy2X4bZRrZA+ehUKUsLb1XWgzGxodh7LE5Bim27Pevge6Yb7rlEZmsmYzMJAlndr2IDIYpouKPiX4rF+GVg/XmSFOsjvffI7DUrzIAESIAESIIGYE5APJr/svnInI6PShR9GNULeEwzaxNwNdf5AU/rrdQw/YwA6vlwKf0Dq63AOVefk+YC6JxD0e+U9TGSFgpnwPnotPr1FdpGWRcbXOs7mQQIksBMCDECzW5DAvxCI1ky9HUcfcRMOe3Qjig5wSSa0yHIYsqzJ1xB7kCUJqFZZqWS/doDr+6fw7FGXYX0ps48s6cqdNjpaRuUv3HB+EyQ/sQXeZFlV4xZY+7iZlpAACZCAZQmoLrRfAjhuEYPKRONxY7D5Os0YjB57W9Y4NjxEIDIWcatfb0fj8Wux7HwgQRN5qAfNPmJJAmEpIYiUkCFSQhkrJmHBqOGYNFmNYWFVS7qUjY4xAQbPYgycj7MegegswiswsMFjGHzPFqy6fIvopybAYDDHei51fIt18CSr9sEmSC2dhT+OPBYvzeeEzz7dwvSlDoTvQYd7miDlxmJUyvuViwVV7eNmWkICJEACliegW9iDCOhnk7s50t+8AtMvfBpfbB4qAcq80IIpD6sTMBfEr0Z21m3o/2UZijqzwLvVverM9oeLqWrWcxLWoXjqbKy++gK8tlQXVKSfcwepM7sFra4mAQagqwmMpzuXQPSq5mScdspQ7Dd2LYrb+eUDR5bxmQ3t3K5hKct1sifbXv0ZSPZ8jeUXD8TEZ1kAyFIu/K/GhqSDnkSX9MNw7NMdkXrmFlQGZLGM71H/RY5/JwESIAESqC8Cfqmx4m6CtO8vxttnvIh5v0pDQvUL6qtBfG6tEgiNTX7DUUe0RP8Pt6BYJQ05LqlVxLxZXREwCw3Kipi8RyUVrkXF7e1w32P6vGxke/KRz/epuoLP+9qOAAPQtnMpDapLAtHZ0JNw3m490HisVHYeVgyvjJJD2tDcUlaXDuC9a4OAaJZVuNti3wkGzh2pfZar9rWBtf7vYWY+v4PTm5+A9pPWwNPbD59P9BbFx5QLqn8PsQUkQAIkQAL/QsDngstjwLe0CAec0QmnfhkZVzMT2gbdxgzUbcDoy4CKJypEBlyKTrIehQ18a2cTpI8G/PC7JGtfKrSnf74Y7159FL6eLzazcKqdHU/b6owAA9B1hpY3tjOB6Gzo1cg5Ox3GfYUoaxWQDylmGtrZ81a3zQjJljVF2px7MKNfDvKp+2x1l0bab07sJuO8zidg7zdXo2CfJKi/WWzQJi6mGSRAAiTgBAI+2VnoyYJrQzEqzm2Jse8zCG0rt2th5MAy3DpB/ud8t2zKkwVyBqFt5WJ7GBOWBwoGvJKok4rkskYovvdq/Pzg4/iwQt+TmLxjDz/TitgTYAA69sz5RJsQiGRD62socAEO6vAkTnmwAmVDNqNUtVb9smLKKs828bUdzNAVfJHecCUhadUDmN73IXz9K3Wf7eBZwPTjGzjnsCHYc9IKbNktGQkB2c6sEz0eJEACJEACJGAZAjpekToVrgyk+AtReUk73P2cNN4j424dW0u8kodVCZhzp4HolP4BzvxwCcoPTZE5kxR15w5SqzrVhu1WrWd5D3InyNpICyR/8ZIUGjwHed+qqZw72dDhNCmmBBiAjiluPsymBEK6Zmrb6zj9giHomrsRpa188EuFXHeQQSCbet1CZkWKDqIRUip+x+ITDsArM1ip2UIO/JemZsukPF80MifjzP4nYe9JK1HUOAkeySiStx8eJEACJEACJGBBAi4JQlfCZzSQYl8b4btmd9z7qJgh0eeg6EkxCG1Bl25tshnAm4nhHQ/Dfp+uxcZ2XDS3skft0/bwfEkSnyWBoxkySn7C+ge+wm9jrmTWs32cTEvqnQAD0PXuAjbADgQigyk1JfAWLmhzIJrck4Gks0tQgUQYEpxmNrQd/GxFG3QLmWxn9cvg3lMJ78WtcN+zLJhhRU9u32bNIhqGYa485Pkn4YyTTkGXV1diS0oyPMx8tr57aQEJkAAJOJ6ABoN8EgxKRYKrQIp+dcQDdwsU6q7aomfkiHtzAtMw8tD+aDdzNYo4frGFXy1thGQ9+93N0ACF2Pz5UnS57iCcN1ctYtazpf3KxscZAQag48whbI61CUQH9lbgilMao+ld6+HbB1KkUAPR3GJmbf9arfX6Bu9HQIPP7koER7fC3Xfo5E0XSqxmC9u7PQFzMCzB5+FD0Pm5VShMlczngASmKbvBzkICJEACJGALAmZGYjoSJQhddl8HjLlFDGMmtA28mx3ZwTUN5w7tj06vrEGxJxEuTW9nfMIG/rWKCbrbQuZKogHjcslO0YI38Uvu79jjMRln61yJWs9WcSTbaRkCfIO3jKvYUKsQiNaGvhDZTZ7GgTnlSLtgPSqTEuEW/TrN3uDgyir+tGo7zcznFMl8Lofvqda4V6qOcyBlVX+a7Y7OfH4dwy88GV2fWoUtbmY+W92zbD8JkAAJkMDOCOh4RjKh/WkyntmM8od3x5hRDELbo68MlXFpnuRKSBD60v7Y/cl1KPFLHR2XRP4Yo7CHi+PWim1FBgPuNKRAip6++QmW33Y+XvlN318kAK1fTNiJWw+yYVYlwDd3q3qO7bYCAdVg9WlDp+D0PoPRPXctNh9eITmpSXDL74OyqsoBlhUcabU26hu7FBz0S/DZXQHfpBPw8TnzME91gamdaDVnRrVXg8+5yA0NiCXzeaRkPj+9GoWuRKnNxMxnCzuWTScBEiABEvhXAuFxTTCgmdCbUPaIBKGvYRDa+p0mvKhuiJwY/O/inDsOR5vcUhm/uildaH3nxrEFWmRQ5AndMn5GFjyLlmHd6E548nVtstbImYzJAWrNx7ED2TRLE2AA2tLuY+PjnUB0NvQgdE8djUMv2Q+tbl6OwsZSuVD2yrslcBTglvl4d6TF2ieFL32q+VyGynfOwuun5WNJOfXLLObEHZq7vebzaSNPwb6h4LNU6Gbw2dquZetJgARIgASqQMDMhJYgtGcTSsftjgevlcuoCV0FdvF8Sniu1FumRfmSKJHzwBKU3ZAsO0bDvmWiTjz7zmptk6CySNWpMKbPlYbE0g0of+JhfPrgeMzboAtazHq2mkfZXisSYADail5jmy1HwNxipg1/AsfueTp63CI6Z2dtQpHLgySJQBuSm0rtVss5Ng4bLCv6vhR4RHbD+/6pePv0L/FbEYPPceioajZJMzK04ODrOP2CIejy7CoUGSLpI+8bnJxVEyVPJwESIAESsCgBc4eXBKHdm1AhQegHGIS2qC+jmx1J2NFfyaL6uw8vRf41SUgR+YMgNaFt4N/6NsGU25Ahs1u0ntEMjT9+Dl/mXog3v4q0beuu5fpuK59PAnYnwAC03T1M++KGQGRwpdnOuqovgejBfS/DwNEbsPyQ0lCRQq72x42zLNgQU/NZtIBV83nasXj+tB+xtoTBZws6c4cmbws+Dz/tZHR5aQ2K3Amh4DMXrazvXVpAAiRAAiRQHQLRmdCbUXpvRzx4q1zPYmHVgRiH50bGq1pgUgLPNzy6BBlXJKLU7xJNaC62x6HDLNIkzXr2wq87BuWfsfgnrM25C79PzpeM+xzJsr9T1jwot2ERZ7KZtiDAALQt3EgjrEQgMsDSJss2oKAxF5dc3B1tr1+Pkg6i2ythJQ1QGxxsWcmpcdBWqeAc0nwuhz/vVLx1PjOf48AptdCEbGR7dJD8Bk4fJAUH31iJwpQkePS9g9I9tcCXtyABEiABErAeAVMTWrbRuzai/NY98MC9GoSWr1CSBw9rEtg+E3rEfRvQ/qYKlAbcXHS3pkPrt9V+LwKi8+xGKpI2p6PyqdPw9sN5WLgp0iwdR7PIYP36iE93IAEGoB3odJocHwSiM1MvRc/dbsBRIzOQfk0xgukJqJDVWNWHZpApPrwVv60IZz4HAkkSfK6E98Wr8d5FMriqZOZz/Pqsqi0zM5/fwPB+J6HrlFXYksHgc1Xp8TwSIAESIAE7E9iWCZ3g2QzflR1x7+NiL7fSW9zp0Yk6b+Gcmwdhj3tXo0gLuGtqNGMXFvdvXTc/rPOscWXD1Qip3i0ozXsTv9x9Gd7+RZ+tspiTJcueWc917QnenwR2ToBv4uwZJFD/BLYOlh9Hv30vx143bkDT0ytR7tI0jgS4/LL1TLM6eJDAdgREO1y2lQVkZd/tKkdwbGvcc72eEMkg0TobPCxKIFsm0fmA702cfcBg7DV9BQqbMvhsUWey2SRAAiRAAnVCQFIYgzoOkkxooxQ4uw3uelkexEzoOqEd85tqnCI4Dedc2B97PCJBaN0BJoUKgzpv4kEC2xGQzuKXOjiuAPxGGjJQgrIZH+Pnuy/Au59HTqRMD/sMCcQBAQag48AJbAIJhFf79cgJbQX6GDcfdRCSbpVtQ/3Xyap/Ijx+ebFSloNdZSsBDT5LoUGp4uyRqVfi9c2RM1b+yGrwtugjOTKnzglMwyUd+2O3mauxpYNk/nAhyha+pREkQAIkQAK1SSCi8Wo0QEJFJVqc1AyXfWTKV9Xmc3iv2BLQZIpc5BoyRwp8iHNO6Is9X1yNwoY6J5K/MTEntu6I26fpTghpXKACXndDyZMPovH3fnxy3+PoMUX7js6N5Lv+o9xG3HqRDXMSAQagneRt2moBAqHAk7Yz9CH5PkYe3x8dbypEyWEVImsXkEIJHrhkaxEzoi3gzLpsouia+d0t0XBTGdIvy8TlrzP4XJe4Y3dvUzplOk5qNgC9P1iCZd1TkOiXNwROtmLnBj6JBEiABEjAQgSkUJ0EoCpdTZC54W+8f2xXfDXXlLGykBls6s4JhHaKfoSLDzoSLSdtQmlHlyzKMzHH2d1FF54k41kgBF0u+d4CTX+agzVPlyPtud7I8SkdyhE6u4/Q+vgkwAB0fPqFrXIwgYh8glkYISgD6MSRaDSsF1pe74ar2wbZVCRBaK0KrZWiWYjMQX1FV/nF5xKMDHoaIW3BfZh9/mh8PE+Dz+aihYNw2M5UU/cwG+0TZ2HQlL+RMTBVJl0SfOZ2U9t5mwaRAAmQAAnUJgHdgi/FvKXoWNri6zG130uYt4wBqNokXH/3MhcTPsPzu+2PjePLsPEYnyw6yMq8zIWoC11/non9k8MZz4ZfMp49WUiRH4zlFQg8dCvmvDwR0yMFBoeK3MZk6jzH3j18Ign8JwEGoP8TEU8ggfojED1wHoouieeg1+m90f6qclQeUA6fav3KHjSRu6I8R/05KUZPDmubBdyGCLI0Qeqb1+H9Sx/H7PXyeGodxsgHMXhMyJe/4PrHMpF2hYFK0Tpk8DkG3PkIEiABEiABWxAISoIG3JlI/+wqTDl2POaVyVg6JONgC/OcbURojKTyKq+i170p8FxfIrtD3RKMjIyFnU3H5tZvn/EMtETW73Ox4tWZWPHkLXh7Y8R8zols3g9onvUJMABtfR/SApsTiMqI1gGWVO/NTr8Iew45GK2vlB8P3IxSGXy5A6IJrAFpZkTbsD/IoMsnW0s9acjypmDRnR+gcsww5Pm5vdQ+zjZ9uRg3XN0UKeNKUC7bS92U3bCPi2kJCZAACZBATAgEtRiZuxUyX3Hj5rNyQhqwYWk7HtYmEO3LP3H/8EYoebgU/uYyA/LJWFmyXpkNbW0P/2/rNfCsG0Cl7o1oPKdqxvPqQpQ//gC+eeEp5K8xA8+yyBTkQpPdvE977EiAAWg7epU22ZZAdMBxIDolXY4jJSO6w6VlqOxZKhnRMgCTjGi3flCzYKENeoEOunxSzVmyO4yWaP7ru/jx0hPx/CwxTeVXxN+685CH1QmYr+tfcOOgNkh9pwBlKrMT2mNoddvYfhIgARIgARKIPYGgz4dkz25YcpuBF+7RrNlZmCULuxw3xd4XtfvE6MScS9Frn8dwwpNrUNEbqNCEHBYorF3c9XK3iORgQCQHJbHKkB8NtEajhd9jxUvv4ZcJOVulNuBRaUK+ruvFTXwoCdSIACe3NcLGi0ig/gjsmBGdI4PqbHQZdDBaXuyFb8BmbJHGJSEBbskGCDIboP5ctUtP1qxnkdzwNEUa/sCm58dhwS0T8Mlauan4NEhds12iGz8XR17PwXPRfe8HcdwsyfBoES40yt0M8eMltoQESIAESMBKBDSAJWOoQCpSfe/g56HnYfJ7On6Sr9BuQh62IBDy58M4JOUydLy2AHvdVoZNyUlIlwJ0Ac5/LOpi2dEruz59nmRJxUgT2UEJQi8sxJYnxmL+648gvyBiluxqCP3jzgaL+pnNdi4BBqCd63tabgMC22tED3Vfiia9D0aPy5Kxtu86lGRIMRbNkg3Jc8hYnIU6LOBzWTSQIoOQis6GZD67/pyHNTcMxIQp5oBLvnOwZQE/VqWJkdevbBnMTroJ/WeKnM5hurgg11JKpyoAeQ4JkAAJkAAJ/AMBDULrLjKR4lj7Bn7PHo4Xf2VRQnt1l2h/5uHKQ09B94dWY2GvgAQvJTqtiw3cEWoBl+tcVXd2asazfm+NLP+v2DB7FTY8+wV+ejcH80ojZjAJxwL+ZBNJ4N8IMADN/kECFicQyaDULABZ8Q8f56PHQTehz6nNkX6OH/7GBbItzSMDcRmO6dY0+V8e8UYgPPgKBL3wuFOkcY2Q8fR1eG/0I5i9WgfQXOmPN4/VSntC2TtB3P3cCpRcIAsO8hrm67NWyPImJEACJEACjicgYyt/KSrdHdHmm2F46Zg8zCvSAt7csm+frhG9MzQHF6YOhfuqtmh1QwGKs2T4HEiQNf2wlAOPeCOgBdbFN0alOCoVyfIv6JXUqdeewbev3Iz3Z0a1l4HneHMe20MCNSTAAHQNwfEyEohHApFMAH1dh7YYXo2jW56Hvc/shiZnlAH7bUKJ/FaG3cyKjhv3aYZOqLoG/C63bDVrgfLZk/DH7cPx9mfaSGbrxI2rarUhpu7zLIw4vzt2m7AFFX4JQLPoYK1S5s1IgARIgARIQMfEQfc6FD+xPx6/QnhQisOenUKDzKFdgqoN/SSGjS5E4ZAtKBeHu1S6Tv7CQHR9ul7nPFrGRoLO6gtDioUa6UhBQwT/WIYVb8+DMeFkPPd7pI2GzIGMO3EnF4zq02l8NgnUMgEGoGsZKG9HAvFAIBLc0k/30EDsWVyYsAx/H38DjjwlAP8pMkJLLJKsaP1jomhFS+YttdJi7LhwgQ34vfB7MkSzOwXuPxbDO3YKvpiYg3zNZmfWc4x9EqvHmYsKr+GcLsej02dbUNowXHSQE6NY+YDPIQESIAEScA4BLVSWhiT3Rmw5Y3eMey26qLdzKNjf0h3r5LyJM4cMwl7Xl8B7cBm8mgntlxo5BjOiY9sXIoFnv0hDukSb3ZWpuc7yrwESP3oDv73xE3545378tNkMPMvr05WHPOq1x9ZNfBoJxIQAA9AxwcyHkED9EIgMxPR1vlU3WILRu+8N19CukhWdBHfXjSgVeY4EbaBkB2h+dKhEON8b6shlZsZzQAZgSUJeBmGrF9tEB5IAACAASURBVGHD+Jcw57Fx+HpT+LE5skbAwhp15IJ4uK3rJTyYchZSZy3F3z2TkRSp9B0PTWMbSIAESIAESMBeBKSuRqAcPqMdMtddg3d7P4JvfuEOM3v5ONoas8aG/C44AN3SbsRhp++HxjelInH39bIbVILQMi9iRnRd9oBwoo0hX6F/IQmUJlJWMAnG359h+cw0lE64Hsu+zw8n3cgxVJKhJrPIel06hfcmgTggwCBTHDiBTSCBuiaggeje6O3e9iEPXIjuCYNw2PEDsefxBVh9ohsJjb0iI10qGQIe0cwTvWgdNDAzupaco7InEnSWgjgBd7oMv2QQvP43rJ/4CuaPH4vP/448xqNZOtQmrCXocXYbfR0Ow7BQVsdPuGZsU6SMku2H6m9Kb8SZr9gcEiABEiABexHQIHSlyJ1lyeLvdXjn6PGYp3VRuL3fXm7e0RqtexMKcJ6O7k0GY6/zB6PLhcUo71guyiySCS0a0SoJEZJl4VELBFTXWRKZgvJa88guW9nhqSrcRoX8btoDyH8vCXhHdnoWRD2Kc59a4M5bkIBVCDAAbRVPsZ0kUAsENACmt8lFrupqbc2KvgAHt7kUB/WRjICzuqLlgUUoa7QZZaqZFtKLNjOj9VpmR1fdERGZDR2HSeA56E6VQVgaklf+gXX/9zi+eFYmP8v0broVdDJX/asO1qJnmlt+F+Pyo5ujxfuFkoXjhsEK7Rb1J5tNAiRAAiRgLQIScvRnIcU9Fytv7YPx91KKw1r+q0lrde4TPe85Ap2a5qD3OfuixUUZSOwk2uChjGjVLZQ0Xe4CrSbk6ExnQ1jLfMdIllSmpkgvWY0tC1ei/PVvUfjeZZj4R9StQzKD1HeuJmyeTgI2IMAAtA2cSBNIoCYEIvIcuuKvgeitwejROG6flkg57nz0OHwzSvvJ39IkS1NCZZUaLAt64NFiLhI0o17tP3HX1X9JpghWoNKTJsNaLXwiOs8LFmDVyx/gj5dz8PG6yLVuGYAFoxcDauJLXhP/BCKvt+DZOKjx4zh2TiHKd9cJD3UI4993bCEJkAAJkIA9CGhShU8SNEX+rGQyFva/AHnfMghtD9/+lxVR855QRvRQZKcPQZvThqDzaVtQ1ldTbopDcx1XQCZHWqeFCQL/ANXUdJadnYYoa7tF0lH2dnpCYhuZSP36O6z65CP89qHMd76KvkU2sj2zMIs7Pf+rs/LvJGBjAgxA29i5NI0EqkpAtdL0XF2Njg5GD8f+e9yB7H7lCA7bD827SBGPppskFG2Ec6MlMzo0PjN0xVsvdGp2dHggFvpP6LsW2IBU3W6DZoU/YePsRBSOfwZzP38EP4S2nClvrvpXtXfa4zxzguvH/RMlI2SEdBBZpKD0hj28SytIgARIgASsQkDHr1KG29UWSd++iBePOg9LKinFYRXv7Xo7d8yIHoouiTeh/+E++C7ohpZ9SlDeXAPRiaH4sybohOc5Tp3jKPHIPEcnfRpkDkk0aoXAVAk7N0Fq0TIU/V6C0rdn4o8PpuDPxflYWBzxlO64Dc0ROe/Z9b7LO5CAHQgwAG0HL9IGEqhFApHCHRqQjhSFCN/8MQxs40EDyRY55MgKFBwhA4/dJYtEFKODqJD/auaABy6fZvvKYfsM6chgTDJpZP1fBmKGEEgLrf67ZEDmnlOJvWdOxEt5ozBtQZR7qHNWi33VKrcyg88vYMigU7DfWwUoM0RnnfrqVnEg20kCJEACJGArAhJIE+1fl0vkF+7oikdGMwvaVu6tkjE7ZkTrRbfg6JZDsc+p+6PlCRtR3Ft/Jxm+Ms/xqZKx3xUKStu/Po45x9HdnD54pWJj0HBJSD5FJ3ih+Z57TQZcX3yFX7/5BkWfjsK783eA7pHXVFBrnlTJGTyJBEjAMQQYgHaMq2koCVSPgJkhoFftmBndE+1byJa1PU9B56MSEDi6LRrvU4Fgo02S9euNBKNFrkMzPPVyyRwI/48eVswgiMpwNk0I+KW4hmYCyMq/DMk8FV6UL1uMwrfLsGnqtZjz85f4rShiMnXOqtf1bHV2ZIJjPIsbMy5Eo6+XYdM+sk2R0hu28jKNIQESIAESsBIBleKolKCijF9LrsEHRz6C/B8iCRhbJemsZA/bWnMCO8x3Qv4fiE5JR2K/zqeg09HJwKltkLnnBlSkSna0yhHqV2SOY1h+F+gOuzg1u1nSizSxxpDQe5loOWfJPCexsBzrlv4N16xl2DzjVsz6+QcsWRJFnZnONe+CvJIEHEWAAWhHuZvGkkDNCegArbdkbebvoBmtd3wax7deD98RI7F3z+Zo3rUM3m6lCLQIJ1Ebkjkg4Vr5p4MZ1UfWDAIt9BGOTcfftjadmITl3wxZ+ffrtjvJVg3KAMythUo041nCzgmF8vO3z+G7ryUDfEYhen65g5azR3+mvnPN+5wdrjQntL9h1FgpfDRK5Fl0chOSvOFBAiRAAiRAAiRQPwR0PCq72KRAdOInF+OXoyVbMyK5UD/t4VPrn8DOsqK1Vc/ghB5d0Pjow7HnIcXw9pLFi8Y6F9C0mrLIhlGVVnPrdCEkS2jI3CG+auVEdJtDhdGj5zchUY3Q7k1PyAEaYNc5jiQU/ZSOfX9+ClPnlaFw9nV479cdPKRxJJ3r+DnXqf++yxaQgFUIMABtFU+xnSQQRwQ0qLYQC43IYD08Aoscuo2xFHPaPYXdO5TgoO4+lPVsi4wDM5DarBLBdI28bZEMglLJlNZBjl4oitI+3dKlA79wUFqPoPk/4Z+isqh3BYW50h+5p3zT+HLoJ3m4EdRtZhIk1OKMoaOpCGtogyTLuXAVipZtQEl+YzScdSXe/WUzGojOWX60VEkosEgtwV3xkH2uNbf0jsJRPcfi6M+XoTBRFzHibVJiH+K0hARIgARIgASqTkDGfIFMpLh+wLoRR+CJF5gFXXV2dj4znBVtSFZv6NguK/5wdNwzF0fu1RZNj6qEv88eaNxRRv4ZJZJfI8UMZZQXnhRJso1MJoxA9NzGrJljsquLuU14HqKHzm9Css2h/5eEmnCEWX+Sr6ZID53pgrvMQGXBr9j8YxqS587HmrmPIn9xJposfQ/zSqP8rJdFmORQ09nOLwDaRgJ1SIAB6DqEy1uTgFMI6OBqGIa5JCCtAVjvjnbr35/DyXuUINBNsqL36Yc99uiK5u0lU3o3GZy1kmB0ogziwvnRkUNHTOWSVbDjm9T2K/hbh1JbA+Dbnh0ujBgd0I4e6Ol6v1Zs1sD3tmcGJcPZEI2z5I0uBJfKsGzp8/jul2JUfN8aWd+dgdeW7mhbd3RPGIRBXP13Smevnp0h+ZUrgI9k22Z/1Q/UbPrq3YJnkwAJkAAJkAAJ1AWBiBSH0QrpK0cgr/vL+HG9Fk1jRmdd0LbuPf+pPo5a9DSGti5DeY+uSOveH107l8JoL6kGbb3wNy2VYobhBJvwoTKF4b2h2+YeVZ/XbJ2tbJess/3cBqpVHZrdRB/6tHSImAiM1TIIXS6a1ksn4Nu/pIrNogQk/NQJ3kXH4sOKnXjIky2/nIWgX5N0rOtBtpwESCBeCDAAHS+eYDtIwCYEtlWXXijvL6HtjNtlSJtmqr6aaIw1kxBz0zNxUNPjJGN6Awo7eeDZTVIN2kj16TZt0SDLD1eCDN101V41l6MTmKtELHq0FFq6DwUBA14poFG5AltKRbV6mQSaZRDm/0sym//8GoV/PYp312Qhdc1U/FCwk4fobTSwGGRF5yq5wJEnmVlU83DDGXsg7ZVCVARkOkDpDUf2BhpNAiRAAiQQvwSCftnl5v4dG8cdiqeuZRZ0/Hqqvlu2bY6To3OBnUq29EP3zCA2N+8h9XKuRnbHTdjUSeT7OopodMemaNouC0aaDxUyt3ElhIuY78oRboYEh/0yd/JJEo13I0pKNqNytfxhufxtuRueP8vg//MqvLNG5lMb0uFe9+62OjXRDw9Pk0JZzpzj7IpXeC0JkMA/E9i19zySJQESIIEqEjCzpNdjvSGyFXpVtHTF/9xFJwB74PfMTahoLoUOG8ooT/TW0EgGT5kyoEqV4VaaXJQq/58g/58cva1Nzq2UN7dKGUNpNrZsHzMK5Tz5cm2RzOZNfvjWtkLDNZNQVvAfFZpd2ch2yYAxOBmTA1z9r6KzHX5aZPIavASHZ43DgLlrUbK7TG51GyYD0A7vGzSfBEiABEggvghoZoNXVBbaoEHFTPx8yAC89kNEC5gZn/HlqrhsTdQuUI2rqFzHPxaylLmE24eZDbdgZQsDCc0lEaeJzE0ayNykgVyk8xvVxRAhaZ3XhESZE+X/y6UcYKgvRuY3RRK8FtmMYIn8XKTzGjlngxfG5qZIWv8b1qzL2V4ecGfc3LKD09URHQNd0CXIjP+47FpsFAnYkgAD0LZ0K40igfgnYGYRRLSkzQabg7ZYD/q3rvprQ8yVf/1/Bp3jvy/FWwtN7efZuOy2fdBotGx11K2LlN6IN0exPSRAAiRAAiQQImBIheCAy4WEd1rhrsHyC10w/sdAIqGRwD8R2Mn85h93g8aA4tb5jYxNocFm7t6MAXU+ggRI4B8JMADNzkECJBC3BMKFO4Bc5Ia+a7Bav2sWdXSjiyDJADscGcjYLoitWcx6ijn4Ck03qGcWt763asMiWVM4Gd1av4bTvhNZmWZaFZ3Zz1b1KNtNAiRAAiRgdwKRLOhgC2T4X8SCQRdi8nRzMdnuttO+2BKInttUZ15jtjJ6fhM9t9G/M7gcW1/yaSRAAtUnwAB09ZnxChIgARIgARL4BwI5kjWVEyjFs49uxO9XepBM6Q32FRIgARIgARKIcwLy4e2vRMDdFOn5J+PFYz7AYpFyY7JCnLuNzSMBEiABErAQAQagLeQsNpUESIAESCB+CWi21GTkBSbh6M4nof+X67G2gVQXV80+ftbGr9vYMhIgARIgARIIEZDP60AqElwz8PfJw/DS2yxIyI5BAiRAAiRAArVHgJPi2mPJO5EACZAACTiUQFh6Q6VicgJ+jHhiOVpdlgy/VCWn9rNDuwTNJgESIAESsBwBQwpOa8Fg15w78eER4zHPJ5/vlGyznB/ZYBIgARIggXgkwAB0PHqFbSIBEiABErAUATNL6jPsv0cXDJtXicJ0qVLO7GdLeZGNJQESIAEScDKBsBa0H6IFbTyPBUMvRt6b2cj25CPf52QutJ0ESIAESIAEaoMAA9C1QZH3IAESIAEScDQBMwD9OS5/uhsaXVwCn2RRSQSaBwmQAAmQAAmQgGUImFrQTZA2+1hMHDALf1do41m42jIuZENJgARIgATilAAD0HHqGDaLBEiABEjAGgQiwefgheje8VGc8O16lDVKgJvFB63hPraSBEiABEiABLYjENaC9ri+wJ9HD8KrM+Rz3pCvADGRAAmQAAmQAAnUnAAD0DVnxytJgARIgARIAFp8MA95/nxckrsfmt5Rgkq/Cy430ZAACZAACZAACViRwFYt6I9a4u6BYoHOmSUuzYMESIAESIAESKCmBBiArik5XkcCJEACJOB4Aqb0xlAc0HQShs5ZhcL2kv0clKJFlN9wfO8gABIgARIgASsSCGtBB9ASmeWvYG6f8zDlG3Ox2Yr2sM0kQAIkQAIkEA8EGICOBy+wDSRAAiRAApYkYAag5+PqC3ZDxnMV8FP72ZKeZKNJgARIgARIYBsBFwxfGQKe9vA8Y2D0JfIX3dnkJyMSIAESIAESIIGaEWAAumbceBUJkAAJkAAJ6H5cI1e0Ia9H6tebsKGnBwnMfma/IAESIAESIAGLE9As6IB8yqchae3ZmNT9Xfy2ylx0trhpbD4JkAAJkAAJ1AsBBqDrBTsfSgIkQAIkYHUC5nbcO9C/bw76fLAMBYlJIfmNkFYkDxIgARIgARIgAQsTMIsRLkHB5QfgsScZgLawM9l0EiABEiCBeifASXK9u4ANIAESIAESsCKBobIdd7IkSC3Dbc8mIDhS4s4+SZjyWNEWtpkESIAESIAESGB7AgaMgB8BIwuJC8bC6H4ncoKaGU1OJEACJEACJEAC1SfAAHT1mfEKEiABEiABhxMws6AewG6tLsfF321CYUsPPAEWH3R4x6D5JEACJEACtiGgwWap7WC0Q1blnZh5zF34ZBaLEdrGvTSEBEiABEggxgQYgI4xcD6OBEiABEjAFgRcYkXwT5xxeiY6vVoJb0B+1t/xIAESIAESIAESsA8B2d0ETwUCj3XA/VdlI9uTj3z9HQ8SIAESIAESIIFqEGAAuhqweCoJkAAJkAAJKAHVedbMqMXImZ6Jyv6qvSG/ZgCa3YMESIAESIAEbERAZTi88Lmao8Gfh+LJXvOwaoPsdpIxgEEpDhv5maaQAAmQAAnUPQEGoOueMZ9AAiRAAiRgIwLmxHMMBu9+PQ6dvxQbM1h80EYOpikkQAIkQAIksD2BQBI8rnz8fvwQvP5+jiw4y5fufOJBAiRAAiRAAiRQRQIMQFcRFE8jARIgARIgASVgbr99H6ddeSj2erRE5DfckhGtWdEkRAIkQAIkQAIkYDsCgRR4jBUoeGFfPHY+A9C28y8NIgESIAESiAEBTpZjAJmPIAESIAESsAeBSPYzpAihcScSpixB4YnJ8Pjk9x57WEgrSIAESIAESIAEogmo5JZfZDdSkLT8duR3fgr5xZThYB8hARIgARIggeoRYAC6erx4NgmQAAmQgIMJSOBZtt3mBG7DhbuPQos5pfA2ckniM7OfHdwpaDoJkAAJkICtCWgAuhJ+tEXDwH3IP/kWfPTuUAx15yHPb2vDaRwJkAAJkAAJ1CIBBqBrESZvRQIkQAIkYHsCWmgwsBrjh3mw5A0vDJl8BkWBgwcJkAAJkAAJkIB9CRg+GQB4NqHk0c545GpTjsu+9tIyEiABEiABEqhdAgxA1y5P3o0ESIAESMDeBPRzMzgHIyfugZbnlYv+s0g/MwBtb5/TOhIgARIgAYcTkA9/fwX87nbI/HIY3uufh6/LKMPh8E5B80mABEiABKpFgAHoauHiySRAAiRAAk4n8CwuTDgVbX4rQVkHkd8IUn7D6T2C9pMACZAACdidQFgHOoAspFQcj5d65uPPnynDYXev0z4SIAESIIHaJMAAdG3S5L1IgARIgARsS8DUf34OJ/cagZ6fr0BBQiLcDEDb1uM0jARIgARIgASiCQT9CfC4V6DovAPwyIvyF90BRR1odhISIAESIAESqAIBBqCrAImnkAAJkAAJkICp9/gwjht1KXqNXY/SgBuGakLzIAESIAESIAESsD+BQDLcxgoUv9gN40aIuSFZLvubTQtJgARIgARIYNcJMAC96wx5BxIgARIgAWcQCGU6leG+V9aj4AzJgvKJ/qPHGabTShIgARIgARJwOoGgVB12G8Wo+K0jxuxjiAyX04nQfhIgARIgARKoKgEGoKtKiueRAAmQAAk4loApv9EPHTM/wIj8NSjePwHugASgmQHt2F5Bw0mABEiABJxEQHWgKxEw2iCj9EX8cOD5yPvNHB84iQNtJQESIAESIIGaEGAAuibUeA0JkAAJkICjCJiFhg5Em25f45Kv1qIoLQEu6j87qhfQWBIgARIgAScT0AC0VwLQLZEZvAfTz85B/issROjkHkHbSYAESIAEqkOAAejq0OK5JEACJEACjiRgTjAn4MRBQ7D/u6Wo9MvWW5Xk4EECJEACJEACJOAQAqK5IYUIve5VaDNmf1x1Y3d0T5iHeV6HmE8zSYAESIAESKDGBBiArjE6XkgCJEACJOAgAiq1EViBW29LAEb7EdSq9wxAO6gD0FQSIAESIAESMODyVaDc0w4dphq47CQh4hI5riD1oNk3SIAESIAESODfCTAAzR5CAiRAAiRAAlUk8COuzmuJjFNkC25AduJS/7mK3HgaCZAACZAACdiBgASaAz4EXI2QtOBk5PWZjoWbqANtB8/SBhIgARIggbomwAB0XRPm/UmABEiABGxD4C/ctCgVrn00+ixG8TPUNp6lISRAAiRAAiTw3wQ0AO2F39Uc6QWH4MlDv8fqXxiA/m9uPIMESIAESIAEOHlmHyABEiABEiCBKhB4G1dnDUKrJSuxITMRHhYgrAIznkICJEACJEACdiMQlCB0Gtyu17DqyEsxYTYLEdrNw7SHBEiABEigLggwAF0XVHlPEiABEiAB2xAwM5sexwk9RqLnl+tQkpggko+SAs3PUNt4mYaQAAmQAAmQQFUJGD4pAuFxI+usJrj+FblKa0JobQgeJEACJEACJEAC/0CAk2d2DRIgARIgARL4FwJmAPoJDB52AXq8sQ7F8IDyz+w0JEACJEACJOBQAn4ZB7jXojh3XzySIwxChYodyoJmkwAJkAAJkECVCDAAXSVMPIkESIAESMCpBLKR7clHvu8pnHTtCBz40HqUBtwwGIF2aoeg3SRAAiRAAg4nYAQ8Mg7YiPIX9sHYEQJD59RaG4IHCZAACZAACZDAPxBgAJpdgwRIgARIgAT+hYAZgB6H4x68FIdeJxnQsvXW8BAaCZAACZAACZCAEwmEA9CbUDZ9bzx0jBMJ0GYSIAESIAESqC4BBqCrS4znkwAJkAAJOIpAdyBhHuBdg4de9mPtmQYSfJLoxAC0o3oBjSUBEiABEiCBrQSCCXAba1D0s0hwdJPfMvuZnYMESIAESIAE/oMAA9DsIiRAAiRAAiTw7wRC2o5B3D9tKTYflwSPL8gANPsMCZAACZAACTiVQNBA0AjAvT4XH7Yej3lep4Kg3SRAAiRAAiRQVQIMQFeVFM8jARIgARJwHAEJNBsGjKAWIrwJnk/WoShbsp78kuqkFe95kAAJkAAJkAAJOIyATKCDlfAbbZBV+DqWtT8DT282xwsOQ0FzSYAESIAESKDKBBiArjIqnkgCJEACJOA0AuaEcgC6pU3DqZ+uQeFBDEA7rRfQXhIgARIgARLYRkAD0F4EjGZIL3kB33W9BFOXMADNHkICJEACJEAC/06AAWj2EBIgARIgARL4BwKa+SxfgYE4oOlUnJK/FkWdE+BiBjR7DAmQAAmQAAk4lIAZgG6O9IoXMO/gi/H2AnO84FAkNJsESIAESIAE/pMAA9D/iYgnkAAJkAAJOJXAtgB0pzZTca4EoIt3lwxo0YMOqi40DxIgARIgARIgAYcR2BaAzvA+j3m9L8GULxmAdlgnoLkkQAIkQALVJsAAdLWR8QISIAESIAGnEDAnlIPQpe2bOOOztShszwC0U7xPO0mABEiABEjgfwlEBaD9E/Fd30vx9mcMQLOnkAAJkAAJkMC/E2AAmj2EBEiABEiABP6BgDmhHIC9OryHsyQAXbwbA9DsLiRAAiRAAiTgXAJREhx+keAYKBIcMxiAdm5/oOUkQAIkQAJVI8AAdNU48SwSIAESIAEHEjAnlMdjnz3exJmfrUNRSwagHdgRaDIJkAAJkAAJRBHwIYDmyAhOxP+3dydwclTVHsf/Vd09e1ayEQhJWCQYZDHsYBjWgAooOFHEoA9lEQGND1DUZybKpg/hgYiI8gRRBOYBAURkEUZZZDGBSACjBEJIyEqW2ZeuqnduT3fSgUAWZjLTXb/i0yTp6a6+93vvdHedOnXuzOPO1l33E4BmeiCAAAIIIPD+AgSgmSEIIIAAAgi8h0DugHKSxu98rz7/V1uEkAA0swUBBBBAAIGYC6wLQD/3ibM14wEC0DGfEHQfAQQQQGCjAgSgN0rEAxBAAAEE4ipACY64jjz9RgABBBBAYMMC+SU4btTzx5ytOx8hAM1sQQABBBBA4P0FCEAzQxBAAAEEEHgPgfxFCOv0+XorwTGWEhxMFwQQQAABBOIrkBeATv9Ss444R3f9lQB0fOcDPUcAAQQQ2DQBAtCb5sSjEEAAAQRiKJA7oDxeu46s05R6W4RwFwLQMZwIdBkBBBBAAIGsQF4AuuNGzTrUakA/TQCa6YEAAggggMD7CxCAZoYggAACCCDwHgJ5NaAH36dTHluiNXtYADqIpARoCCCAAAIIIBA/gbwAdNsv9fw+5+jOlwhAx28e0GMEEEAAgc0TIAC9eV48GgEEEEAgRgKRIs+TF31J1WU36KjHFqvxgBL5BKBjNAfoKgIIIIAAAvkCuQD0MFU03aC/7XaeHliY+76AFAIIIIAAAghsWIAANDMDAQQQQACB9xDIP6Bs0yWPLFPDESkl03Z/EjQEEEAAAQQQiJ+AC0B3KO1tp+Fr7ld61An6ViMB6PjNA3qMAAIIILB5AgSgN8+LRyOAAAIIxE/AldsI0rpkxiI1nlCiBAHo+M0BeowAAggggEBOwCpxhV5C/d46Ry/sUKe6ABoEEEAAAQQQeH8BAtDMEAQQQAABBN5HYIImpGZqZudvNPnGkzT+tFVqS/vyyIBm1iCAAAIIIBBLAS9MyfeXqGHmR3T1PrEkoNMIIIAAAghspgAB6M0E4+EIIIAAAvESqFZ1sl716at13MVnab/vLlNzkJDPIoTxmgb0FgEEEEAAgayAFybl+SvVeu84/eQEWBBAAAEEEEBg4wIEoDduxCMQQAABBGIsUKOahLu89jp9+mun6aPXLldzZAFoPj9jPCfoOgIIIIBArAWCpJ2IXqHm6z+sq75qEu47gZXlYEMAAQQQQACB9xLgAJq5gQACCCCAwPsI5ALQP9Xxx5+u/WYsU5PV3/AxQwABBBBAAIF4CmQC0I3qvGgn/ehyI3BfCsJ4UtBrBBBAAAEENk2AAPSmOfEoBBBAAIGYCuRWtr9VJ4+frI/8fZHWlNlChJGlOvEZGtM5QbcRQAABBOIs4KVL5CfnquEzB+vqO00is1hxnEXoOwIIIIAAAhsT4OB5Y0L8HAEEEEAg1gK5APQZOq7iUu29oF2d29gihASgYz0r6DwCCCCAQFwFAoXRUFVGR+rGg57Q/GdyV0rF1YN+I4AAAgggsCkCBKA3RYnHIIAAAgggYAIvaurMEar8sYK1jgAAIABJREFUaKciu9Q2og4HswIBBBBAAIEYCXjywk4FvgWgl03Srw/5q177d61qfbtRgiNG84CuIoAAAghsvgAB6M034xkIIIAAAvETyCww9LKm3jRElV9ME4CO3wygxwgggAACsRewLwNBh4LEthrwzEm68/D7NLOFAHTspwUACCCAAAKbIEAAehOQeAgCCCCAQOwFMgsMvaXvfz2p4KquAHSm5iMbAggggAACCMREwDKg04GCZIXKbhus2pOz3wWo/xyT8aebCCCAAAJbLkAAesvteCYCCCCAQEwEcvUd6/TlI47Qdo+0qdMONj0C0DEZf7qJAAIIIICAEwjsBPQwVfo/0zPTvqn7fjBBE1IzNbMTHQQQQAABBBB4fwEC0MwQBBBAAAEENiKQu7x2gkaOe0pnP7VUTYNSSoS2QCF1oJk9CCCAAAIIxEDADpyjToWerQURXqPHTzpfD81gAcIYDDxdRAABBBDoFgEC0N3CyE4QQAABBIpZwALNnl12Gx2nCRV1+uxDy/T2wRaADiLKcBTzsNM3BBBAAAEE1gq4ALTVf/a216CGX2nOuDP128W57wcwIYAAAggggMD7CxCAZoYggAACCCCwSQLVSak+3aEpv1isnc4oUUfaAtB2HxsCCCCAAAIIxEAgTMjzmxTO3EmX7ROD/tJFBBBAAAEEuk2AAHS3UbIjBBBAAIFiFqhWdbLeAtDX6NjTT9chN6xQY5SQz+doMQ86fUMAAQQQQGCdQFiqpL9Aq6/aW9d80+523wHsXDQbAggggAACCGxMgAPnjQnxcwQQQAABBDJHmF1lOH6pT+x2mg6auVCN5SXyIzvy5LOUGYIAAggggEDxCwQp+YkGBSdZBvRd1l23GLEtSsyGAAIIIIAAAhsT4KB5Y0L8HAEEEEAAgXcIrNLUF5pVtWdCaQtAW1yaDQEEEEAAAQSKVsDVf07bAoQDVb5isuoOeEBz5uUWKC7aTtMxBBBAAAEEulGAg+ZuxGRXCCCAAAJFL+BbD8N/6oL/HqKy8zuUtswnz2VAsSGAAAIIIIBAkQrYFVDpdgXJ0ar605m6+/gbNNPWgbBT0HZlVJF2mW4hgAACCCDQrQIEoLuVk50hgAACCBSzQI1dbltnl9v+QVMmHaAxf+pQEFp/XVCaDQEEEEAAAQSKViC0E84ViXY984Oxun9abl2Iou0uHUMAAQQQQKCbBQhAdzMou0MAAQQQKF6BXB3oCRq97bM666lFWj0mpWRo9xOELt5hp2cIIIAAAjEWcOU37ISzN0oDOi7X04d/R/c+SfmNGE8Iuo4AAgggsEUCBKC3iI0nIYAAAgjEVaBGNZYFXRe8oYtuKpH3RbsAN23Hpsm4etBvBBBAAAEEilnAymxY+nPgV6jqlUH67njKbhTzaNM3BBBAAIGeEiAA3VOy7BcBBBBAoCgFcpfdXqpJU76t6pvf1BqVWBUOKwLJZ2pRjjidQgABBBCIt0AUlCqVWKQ1l++hqy+qtdJbdnMluNgQQAABBBBAYBMFOFjeRCgehgACCCCAgBPIleG4SMcO/bb2n9OgtmFJ+REBaOYHAggggAACRSkQliqp2Vo58XBd+6T10C0+bDWh2RBAAAEEEEBgUwUIQG+qFI9DAAEEEEAgK1CbzX6arW/8Znv1n9KuNIsRMjsQQAABBBAoMgE7WA46FSaGq+rZg3TdYTP1Vgv1n4tskOkOAggggMBWESAAvVWYeREEEEAAgSITSFgmdPiovnbUXtrmwXYFBKCLbIDpDgIIIIAAAp58O8PckUxq29rhmjq9WkrWS7b2AxsCCCCAAAIIbI4AAejN0eKxCCCAAAIImEAu+2kvjRn4jM54YqkaxqeUCC0o7QOEAAIIIIAAAoUvYAfKkZ1g9nbQwJaL9fgB39cfXyT7ufDHlR4ggAACCPSOAAHo3nHnVRFAAAEEClygxmpA1tmluct0/qUdKrnICkIGVgfa1YVkQwABBBBAAIECF7DP9LBMCe91rX54H/10EsHnAh9Qmo8AAggg0KsCBKB7lZ8XRwABBBAoVIHcgejlmjT+Wzr8mTe0srJUCRYjLNQBpd0IIIAAAgjkCbgAtH2u+8uVPmk3XXYXAWimBwIIIIAAAlsuQAB6y+14JgIIIIBAzAVyB6PP62v3jdLgT9ilupF9sFKGI+bzgu4jgAACCBS2gCcv7LTyG9up37+m6IEDb9UTq6zMlmf3W1yaDQEEEEAAAQQ2V4AA9OaK8XgEEEAAAQSyAtkAdPSyLvn4MLX+oSsAbcenbAgggAACCCBQsAIWbA5KVZJ4UUunH6bra6tVbYsP1rP4YMGOKA1HAAEEEOhtAQ6Se3sEeH0EEEAAgYIVyGVDnaHjKq7XIX95Uyv3sct1g5Ba0AU7pjQcAQQQQCDeAi77uU1pf4z6r7pIf9jvcv1tnp1w9uxmH+9sCCCAAAIIILAlAgSgt0SN5yCAAAIIIJAVyGVFzdT5Z45R2c8tC9oOUD0WI2SGIIAAAgggUJgC9jme8pNafuMwXfcVaj8X5iDSagQQQACBviVAALpvjQetQQABBBAoMIFsFrTO1bH9rtDE2Uu1anRKKVuMMKIWdIGNJc1FAAEEEIi3gB0cRy7NucKuZpqpVyccqd//gwB0vOcEvUcAAQQQ6B4BAtDd48heEEAAAQRiLJA7OJ2p8y4cq4E/alU6ZDHCGE8Iuo4AAgggUJACvvx0mzqSozXsNuk/Pz/d1nWYpsit78DigwU5ojQaAQQQQKCvCBCA7isjQTsQQAABBApWIJcF/R/ae8jPddJzy9W0Q1IJsqALdkRpOAIIIIBA3ARc9nPags3DVNU+Q/866rO6+cka1STqVBfEzYL+IoAAAggg0N0CBKC7W5T9IYAAAgjEUiB3kPq0zv72ztrmsnalA8uYohZ0LGcDnUYAAQQQKDwBLwwV+GUqv3uIpp1o7XeltFh4sPAGkhYjgAACCPRBAQLQfXBQaBICCCCAQOEJZMtwROfqY0Ou0DGzlqphu5SSZEEX3lDSYgQQQACBmAl01X6OVKny8O96+8AjdfVz1H6O2SSguwgggAACPSpAALpHedk5AggggECcBHIHq8/rm98Yo35XtaiTWtBxmgD0FQEEEECgIAUs1TloV5TYTmW3JDXtVFday3WE2s8FOZw0GgEEEECgDwoQgO6Dg0KTEEAAAQQKUyBXC/p8HV1xiQ59dpmaP5yUF9r97jJeNgQQQAABBBDoYwK52s+DVNrwRz0/sUYz5kzWZJ/az31soGgOAggggEBBCxCALujho/EIIIAAAn1NoEayBYsU/EOnnTJMw24J5bv6kdSC7msDRXsQQAABBBDoEggDlfgjtPyalH72ddnCg2LhQeYGAggggAAC3SpAALpbOdkZAggggEDcBVwW9HRN99ZoTemV2ueBNzTz0FJVWBZ0SBZ03CcH/UcAAQQQ6FMCLvs5sM/twSp/6wzds89vNXOJfY5TeqNPjRKNQQABBBAoBgEC0MUwivQBAQQQQKBPCeRqQf9Kpxx8onaqb1Xge5Th6FNjRGMQQAABBBCwKs9pS3dOLFDzufvqf35WY9nPlN5gXiCAAAIIIND9AgSgu9+UPSKAAAIIIOAEXNmNYKVqf96s1rNSSgahLXAEDQIIIIAAAgj0voAdCNvCg2FitAY+c4FuPeIN7dp2h+6wxYO9qPdbRwsQQAABBBAoLgEC0MU1nvQGAQQQQKCPCLgs6GmaFl2s48d8T9VPvKGlI0qVsgt7WZCwjwwRzUAAAQQQiLGAlcaKypUKZ2jO0afp7kdzVy/FmISuI4AAAggg0GMCBKB7jJYdI4AAAgjEXSB3Ke9cTT+9n1pukJK2ICEB6LjPC/qPAAIIINC7ArYoQ5CWl0gpdcNw1Z5prXHrNLhFg9kQQAABBBBAoAcECED3ACq7RAABBBBAwAm4BQntUl67ljeK0rr8T0u0+mg72A1DFiRkgiCAAAIIINArAva5HLbb5/Noea9PV/3HpumJxW7xYMuAJgDdKyPCiyKAAAIIxEGAAHQcRpk+IoAAAgj0mkAuC/oufXn3IzTq8Qa1909aohWlOHptSHhhBBBAAIFYC0SBp2SiWfNO3lm33kbpjVhPBjqPAAIIILCVBAhAbyVoXgYBBBBAIL4CuSD0MzrnwnEa8qNGtQW+fBYkjO+UoOcIIIAAAr0g4MsLOtWZGKIdbivXOSfL1muwG5nPvTAWvCQCCCCAQLwECEDHa7zpLQIIIIBALwjkSnHUqtq/QIf/cYVajiqVH9gRL0HoXhgPXhIBBBBAIH4CrvRG2tZhGKGSt+7V4P1P1LmLKL0Rv3lAjxFAAAEEekeAAHTvuPOqCCCAAAIxE8hd4vstHTb+Uh1Rv1BNg0ss/kwpjphNBLqLAAIIINArApEtMlgi339Ir510im69q9YWHrQb2c+9Mhq8KAIIIIBA3AQIQMdtxOkvAggggECvCeRKcSzU+WdWqOr6FrVbKQ6PLOheGxFeGAEEEEAgDgJ20Bsk7PM2qdQNg1V7plRjn711QRz6Th8RQAABBBDoCwIEoPvCKNAGBBBAAIE4CVi9SYVz9c1b+6vU6k96gWVlEYSO0wygrwgggAACW03Ald4IFPhJlb5wlZ6sLtchje7F7coksp+32ijwQggggAACcRcgAB33GUD/EUAAAQS2qkC2FEd0vHYfdo9O+8vrWrxruUpCSnFs1WHgxRBAAAEEYiBgZ3yjNgUapX6tMzSr+iTd9VyuJFYMuk8XEUAAAQQQ6DMCBKD7zFDQEAQQQACBuAjkDn7v0GmHnKidH1msxlRSnmeZ0Hwux2US0E8EEEAAgR4XsBTndJVKkyvVfO6O+vG1uVJYPf7CvAACCCCAAAIIrCfAgS4TAgEEEEAAgd4RcGU3gt/rc1OP1i5XtipI2x0JgtC9Mxi8KgIIIIBA0QnYOgtR4m01/nq8rj3NemefsVFoJTnso5YNAQQQQAABBLamAAHoranNayGAAAIIIJAVsINgb7I8f7xqo2nq9+sFWnZqSsm0XS2cBAkBBBBAAAEEtlzAlx+2qMUfq11n/lSLDz9PtY32uWuXGRF83nJVnokAAggggMCWCxCA3nI7nokAAggggMAHEnBBaHcwfKEO7jddn/jzcjXtm7KsaBYl/ECsPBkBBBBAIMYCdoAbuEUHh6vf6jv1+sTP6cY5lN6I8YSg6wgggAACfUKAAHSfGAYagQACCCAQV4HcQfE3NHG3/9ahj7ylzpEl8iNKccR1RtBvBBBAAIEtFbCD2yiwW5mqor/opZqT9Lu7a6z0Rp0Fpbd0nzwPAQQQQAABBD64AAHoD27IHhBAAAEEEPhAArkg9FJNmeRp93vatdIWJUywKOEHUuXJCCCAAAJxEnDBZ1fj2VfCaj2/esG2uu0K678ra2XlrdgQQAABBBBAoDcFCED3pj6vjQACCCCAwFqBGluDsC5YrO9/NaXoujalw6Q8L5SVrGRDAAEEEEAAgY0IeOm0OpOjtN2vpPPOsBJXbtHBgLrPTBwEEEAAAQR6X4CD2t4fA1qAAAIIIICALY2UqQdtQWil39BFP6pS6sIWdaYT8liUkPmBAAIIIIDA+wpEVvc5Smyrqocu1uzjalXXkVtnATgEEEAAAQQQ6H0BAtC9Pwa0AAEEEEAAgYxA9mDZs5Ic3hXa6aYBKv1Cszpc9pYLTLMhgAACCCCAwLsEvLQtOpi0RQdnXaSHJ/1E9StqJd9udhERGwIIIIAAAgj0BQEC0H1hFGgDAggggAACWYFcxtYEjaz4jT5z5yBVHmNVONziSQShmSUIIIAAAgjkCdgJ2jCtwB+qfq9dqAePuUZ//Xetai34XEvwmZmCAAIIIIBAHxIgAN2HBoOmIIAAAggg4ARyB8+1mjJsmg54cJ7m7VWl8iC0y4sRQgABBBBAAAFLcZYftqvDH6LKJefr4U/+XE/MzC3qiw8CCCCAAAII9C0BAtB9azxoDQIIIIAAAhmBXBD6EZ224+Ha+YEFWv2hUqVCy5D2IUIAAQQQQCDOAp4Fnzst87lciZaUDvr0QH38IYLPcZ4R9B0BBBBAoK8LEIDu6yNE+xBAAAEE4izgMp6DB3XOuIna7v5lWrVjiZJBRDmOOM8J+o4AAgjEWsC3shsdFnyuUKI1odTnB6l2Ro19LtbZ52WsYeg8AggggAACfViAAHQfHhyahgACCCCAgAlkgtAP6ey9qjXywcVqHFaqhJXjoCY0swMBBBBAIF4C2ZrPXoVKQk/JLw3W939rAkm7peMlQW8RQAABBBAoLAEC0IU1XrQWAQQQQCCGAtV2cF1vB9f36cv7HaWxM5aocdsygtAxnAl0GQEEEIivgNWfitIKVWHlqJoUfGUHXXqTaWRO0sZXhZ4jgAACCCBQGAIEoAtjnGglAggggEDMBXI1oe/Vlw44Wrvcu1QNQ0uVDG1hQmpCx3xu0H0EEECg2AVc5nOgwGU+q0EdZ4zR5b+yPpP5XOwDT/8QQAABBIpGgAB00QwlHUEAAQQQKHaBCVJqptRpQeh9LQh9zxI1kAld7INO/xBAAIGYC+TKblSqNGhQ+5kWfP5fIyHzOebzgu4jgAACCBSWAAHowhovWosAAgggEHOBXCb0AzrtwCM19q5FahxRZrUwQ4VkQsd8btB9BBBAoNgEPPlhWmm/UsmoVemvbNcVfCbzudgGmv4ggAACCBS9AAHooh9iOogAAgggUGwC1dma0A/rrL0nasydb2nl2HKVpC0I7Q7K2RBAAAEEECh4AV9e0KH2RLnKmlvV/8s76MLbrVNkPhf8yNIBBBBAAIE4ChCAjuOo02cEEEAAgYIXqFFNok51gWVC73qExt7zltbsWqqSIOo6OGdDAAEEEECgYAVc2Y12dfpV2rYxobdPHaSLZ1hnyHwu2BGl4QgggAACcRcgAB33GUD/EUAAAQQKWSBzMP4XnbfLgdqpbpkW72mXK6etFkfSAtFsCCCAAAIIFKCAl07b59hQBUvb1HHyIF35GMHnAhxGmowAAggggECeAAFopgMCCCCAAAIFLFBjGc91UvCYJgwZr8NukSqO6VBnOiEvYUFoPucLeGxpOgIIIBBDgSBQlBiqqn/V6oHPX64nbO1dym7EcB7QZQQQQACBIhPgwLTIBpTuIIAAAgjEUiBTE/No7VF5oz55fYUSX2hR2gpCex5B6FjOBzqNAAIIFKJAkFaYGKGqWefqvs/9Qs/8W6q2K33qLSGaDQEEEEAAAQQKWYAAdCGPHm1HAAEEEEAgK1CrWt9uYbUdrN+ig64sV+LcNnVGCfkiCM00QQABBBDoqwJ2QBpFVvM5rXRipAY98HU9POVn+vPbubUO+mq7aRcCCCCAAAIIbLoAAehNt+KRCCCAAAII9GmBSJFnCzdlyj8v1Penlsv/UaPaUqXyWZywT48cjUMAAQTiKeAWGwwzXe/wR2ror87TY+f8VA+0506qxlOFXiOAAAIIIFB8AgSgi29M6RECCCCAQIwFskFo9/kertY3PlOh/jcsVeegpC1OaD9zixayIYAAAggg0OsCvgWfOxX5ZepUifb64QCd8n1rlGfBZ3frikuzIYAAAggggEBRCBCALophpBMIIIAAAgi8S8AFm9N/0IEH7avjbgnUsKMd1weWbeZTkoPZggACCCDQuwJR0K4gsb0GrL5bL35tsm671dpjn09RlLuSp3fbx6sjgAACCCCAQHcKEIDuTk32hQACCCCAQN8SyAShv6mJoy7VMb9cqqZJCUVhgsUJ+9Yo0RoEEEAgJgLu4DOwzyVbJDc5XFX/ukcvn/op3fJMV/DZ6kjZLSYUdBMBBBBAAIFYCRCAjtVw01kEEEAAgbgJ5Opo1trihNNUfcUaRV9vULtS1IWO21SgvwgggECvCnSV3AhVpZS/RE0PvaB5XzlZ97xpjcqcLO3VxvHiCCCAAAIIINCjAgSge5SXnSOAAAIIIND7AvmLOd2hL3z1RO32kwVaXV6mEjvgpy50748QLUAAAQSKW8AFn1uU9vurTI1qv/oz+s13Zuqtlmo7OVqveoLPxT389A4BBBBAAAERgGYSIIAAAgggEAOB7OKEvnU1uEOnHlKjPX+5RG+Ps1WeQrvToy50DCYBXUQAAQR6QcAOOANbbDAxSpWrF6nhG9vrxze7ZmQ/lyi50QtjwksigAACCCCwtQUIQG9tcV4PAQQQQACB3hVIuCD0OTp45Jna76pR6j95lVotJy0VWjDABajZEEAAAQQQ+MAC9oESWckNO8/pJ/qr9Llr9ZezvqtHZ9mOE/Z5E7LY4AcmZgcIIIAAAggUjAAB6IIZKhqKAAIIIIBA9wjUWjTAbhYUkF7XhReN1qD/Wqg15dSF7h5f9oIAAgjEXcCV3OhQ4A+w05v9VXLjt3T/1B/ryUYXfLabrUPIhgACCCCAAAJxEiAAHafRpq8IIIAAAghkBbJ1od2lz9HlOnriWTrop43q2MP+GabkeRad5jsCswUBBBBAYEsE0q0KkqM04O279dJFn9Xvful2UqOaRJ3qCD5viSjPQQABBBBAoMAFOLgs8AGk+QgggAACCGypQH5d6Kk6cPCV+viVjQq+uEptSilhMWhKcmypLc9DAAEE4iZgJTXCQIGXUNIbodIn6/TPr07W7140B98+byJKbsRtRtBfBBBAAAEE1gkQgGY2IIAAAgggEHOBalUn61Wfdgz/pymnH6/dfvS2mgYFioKkPJ9s6JhPELqPAAIIbFTAS4cKk0NUGc3Rqiv/oJm1tapvsqcl7Zb5fGFDAAEEEEAAgfgKEICO79jTcwQQQAABBNYKZEtyuH+Ht2nK7gdq5FVVKjmyWZ2ZbGgWKGSyIIAAAgi8U6Ar6zlyhZ19+/u8pWqfuqeuuM89Lvu5kllvgA0BBBBAAAEE4i1AADre40/vEUAAAQQQWE8glw3tanVerp0uHKGK761Ua0VCfuBZSQ4rGs13B+YMAggggICFnZVOW63nfiqxhQb7//oruuM7N+m5JUaTsJOWISU3mCQIIIAAAgggkBPgIJK5gAACCCCAAALrCeQvUPiKTj1wkEZfHapp30Bldi21TzY08wUBBBCIsUBX1nPoro7xh2nAwl/p6QtP152/dyRkPcd4YtB1BBBAAAEE3keAADTTAwEEEEAAAQTeJZC/QOG5Orb0Gp15/ko99+0mtVcllQp8u9qashxMHAQQQCA+AnbgGFnWcxgqSgxWuV7R8t/dpXnfvUR/fMMUWGgwPlOBniKAAAIIILDZAgSgN5uMJyCAAAIIIBAfAVeKo051gevxr3Xivl/SMVcu1fxD2i37rYTa0PGZCPQUAQRiLZDLevYt0JxU4vVFWv2tvXVtnUPJ/5yINRKdRwABBBBAAIH3FCAAzeRAAAEEEEAAgfcVcHWf7QuDrTGl9B2qLRmnJd/cXWOmLtTqYS4jzi7DjiwjzuISbAgggAACxSTg3uPt/T20Ws+J/pb1PFD9rp+s26fXddV6Juu5mAabviCAAAIIINCDAgSgexCXXSOAAAIIIFBMArUWbLBb6Pr0VR2860/08csihZ9eoSaXDR1YoNoFqdkQQAABBIpAwGU9dyjtl1v1/6EaMus6/eWir2nGQ65rNfZ+fwcLDRbBKNMFBBBAAAEEto4AAeit48yrIIAAAgggUBQC+bWhXYf+qNNO+Zh2qm1Uy85ppS1MkXDlOghEF8Vo0wkEEIijgB0gBmmFdlVL5G2ngatmavE1s9T24zN1Q4t5kPUcx0lBnxFAAAEEEPiAAgSgPyAgT0cAAQQQQCCOArWqtWzoWkt6VnSHPrTdETpyarl2OG+V1qTsy0VomXO2SKH4nhHHyUGfEUCgIAW6Fhn0gg51JoeonzoUzfiO/vRf1+upOa5D1HouyGGl0QgggAACCPQJAQ4M+8Qw0AgEEEAAAQQKUyA/IPG/Omn/YzTuhymVHtWqZkuDTlgKnSfLmqY+dGEOL61GAIEYCLjAs3XTym2EiTK7jmWIKv7xB82/+ATdkFlk0LaEvY+7E4vucWwIIIAAAggggMBmCxCA3mwynoAAAggggAAC+QLZbGh3V+j+/nW9cKqng74fqnFsg+XQlVIfmgmDAAII9EkBV+e5U4Hvy9d2qmp4WguuvFKP/7ROL620Bnv2nu5umdr/bAgggAACCCCAwJYKEIDeUjmehwACCCCAAALrCWQD0ZlAxS9UM2B/jfzmnhpx5kI1DrfsOaXs0m77kdUPpTQHUwcBBBDoTQFPfhi6aklW53mIKoNVavn9E5p7yWd05z9duyi30Zujw2sjgAACCCBQfAIEoItvTOkRAggggAACvSbQtUjhZCu5UeeCzTpbB+z2Qx36n+UqP22p2r1SF+2wGDRlOXptiHhhBBCIsUAm4mxZz21qTZTbacESlT/6W82+5Fzd/WiWhUUGYzw/6DoCCCCAAAI9JUAAuqdk2S8CCCCAAAIxFugKRHsJI0g7hnpNOuwQTfzWSrVO6lAmNh0m7JJvAtExniR0HQEEtpqACzqH7h03cxVKWtvrQ3Oe1VuXXaEXb6/rOmFI4HmrjQYvhAACCCCAQPwECEDHb8zpMQIIIIAAAltNIL8+tHvRv+n84z6i/hfYpd8fW61WW6jQD2yhQspybLUR4YUQQCBOAl0LDHpBmzqTA1VmXU++2a4VP7lcC27+H81Y7SwotxGnGUFfEUAAAQQQ6B0BAtC9486rIoAAAgggECuBbCDaAiGKajS+5GwdVLOvRn+nQx0fblGn3e1ZRrRHRnSsZgWdRQCBnhJYl/EcWUkk2QKDA998SUtvulezr/6O/vx29nXdVSqZS1LYEEAAAQQQQACBnhQgAN2TuuwbAQQQQAABBNYKZMtyuGBIJuBxhiYM+Kz2PPUgjT3XynLsskZtLiM6bQ9IsFAhEwcBBBDYfIFcxnO70sn+lvFs76mN9t76i2v05HVX6K+v5wIF2ipAAAAVxklEQVTP9n5sKxB67qQgGwIIIIAAAggg0OMCBKB7nJgXQAABBBBAAIF3CmQzokN3f40Fos/Wfv+xr7Y9L61gbKParTq0H1ppDjKimToIIIDAJgi4wLO9oWYWeHXvnSPUf9lLWvx/t+uVKy7WQwSeN8GQhyCAAAIIIIBAzwkQgO45W/aMAAIIIIAAAu8j8M6M6K9o/+E1+sh/HKoxZ7Sq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diff --git a/content/9-Polkadot/assets/execution-sharding/spc_2.svg b/content/9-Polkadot/assets/execution-sharding/spc_2.svg
new file mode 100644
index 00000000..fcb64b99
--- /dev/null
+++ b/content/9-Polkadot/assets/execution-sharding/spc_2.svg
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diff --git a/content/9-Polkadot/assets/execution-sharding/spc_3.svg b/content/9-Polkadot/assets/execution-sharding/spc_3.svg
new file mode 100644
index 00000000..3e073462
--- /dev/null
+++ b/content/9-Polkadot/assets/execution-sharding/spc_3.svg
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new file mode 100644
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height: 1px; padding-top: 40px; margin-left: 633px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Tranche n</div></div></div></foreignObject><text x="672" y="44" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Tranche n</text></switch></g><rect x="99.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 101px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">0-10</div></div></div></foreignObject><text x="152" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">0-10</text></switch></g><rect x="219.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 221px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">11</div></div></div></foreignObject><text x="272" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">11</text></switch></g><rect x="299.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 301px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">12</div></div></div></foreignObject><text x="352" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">12</text></switch></g><rect x="3" y="90" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 105px; margin-left: 4px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="font-size: 14px;">VRF values:</b></div></div></div></foreignObject><text x="33" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">VRF values:</text></switch></g><rect x="379.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 381px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">13</div></div></div></foreignObject><text x="432" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">13</text></switch></g><path d="M 152 120 L 152 153.63" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 152 158.88 L 148.5 151.88 L 152 153.63 L 155.5 151.88 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/><rect x="112" y="170" width="80" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 185px; margin-left: 113px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Around 30~ validators</div></div></div></foreignObject><text x="152" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Around 30~ va...</text></switch></g><rect x="242" y="170" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 185px; margin-left: 243px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">On av. 2-3 validators</div></div></div></foreignObject><text x="272" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">On av. 2-3...</text></switch></g><rect x="459.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 461px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">14</div></div></div></foreignObject><text x="512" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">14</text></switch></g><path d="M 271.66 120 L 271.66 153.63" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 271.66 158.88 L 268.16 151.88 L 271.66 153.63 L 275.16 151.88 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/><rect x="3" y="25" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 40px; margin-left: 4px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="font-size: 14px;">Tranches:</b></div></div></div></foreignObject><text x="33" y="44" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Tranches:</text></switch></g><rect x="3" y="170" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 185px; margin-left: 4px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="font-size: 14px;">Expected numbes:</b></div></div></div></foreignObject><text x="33" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Expected n...</text></switch></g><rect x="322" y="170" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 185px; margin-left: 323px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">On av. 2-3 validators</div></div></div></foreignObject><text x="352" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">On av. 2-3...</text></switch></g><path d="M 351.66 120 L 351.66 153.63" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 351.66 158.88 L 348.16 151.88 L 351.66 153.63 L 355.16 151.88 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
diff --git a/content/9-Polkadot/assets/execution-sharding/tranches_dos.svg b/content/9-Polkadot/assets/execution-sharding/tranches_dos.svg
new file mode 100644
index 00000000..573b9bc8
--- /dev/null
+++ b/content/9-Polkadot/assets/execution-sharding/tranches_dos.svg
@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
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text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 40px; margin-left: 633px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Tranche n</div></div></div></foreignObject><text x="672" y="44" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Tranche n</text></switch></g><rect x="99.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 101px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">0-10</div></div></div></foreignObject><text x="152" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">0-10</text></switch></g><rect x="219.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 221px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">11</div></div></div></foreignObject><text x="272" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">11</text></switch></g><rect x="299.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 301px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">12</div></div></div></foreignObject><text x="352" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">12</text></switch></g><rect x="3" y="90" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 105px; margin-left: 4px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="font-size: 14px;">VRF values:</b></div></div></div></foreignObject><text x="33" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">VRF values:</text></switch></g><rect x="379.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 381px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">13</div></div></div></foreignObject><text x="432" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">13</text></switch></g><path d="M 152 120 L 152 153.63" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 152 158.88 L 148.5 151.88 L 152 153.63 L 155.5 151.88 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/><rect x="112" y="170" width="80" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 185px; margin-left: 113px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Around 30~ validators</div></div></div></foreignObject><text x="152" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Around 30~ va...</text></switch></g><rect x="242" y="170" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 185px; margin-left: 243px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">On av. 2-3 validators</div></div></div></foreignObject><text x="272" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">On av. 2-3...</text></switch></g><rect x="459.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 461px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">14</div></div></div></foreignObject><text x="512" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">14</text></switch></g><path d="M 271.66 120 L 271.66 153.63" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 271.66 158.88 L 268.16 151.88 L 271.66 153.63 L 275.16 151.88 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/><rect x="3" y="25" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 40px; margin-left: 4px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="font-size: 14px;">Tranches:</b></div></div></div></foreignObject><text x="33" y="44" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Tranches:</text></switch></g><rect x="3" y="170" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 185px; margin-left: 4px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="font-size: 14px;">Expected numbes:</b></div></div></div></foreignObject><text x="33" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Expected n...</text></switch></g><rect x="322" y="170" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 185px; margin-left: 323px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">On av. 2-3 validators</div></div></div></foreignObject><text x="352" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">On av. 2-3...</text></switch></g><path d="M 351.66 120 L 351.66 153.63" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 351.66 158.88 L 348.16 151.88 L 351.66 153.63 L 355.16 151.88 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
diff --git a/content/9-Polkadot/assets/execution-sharding/tranches_happy.svg b/content/9-Polkadot/assets/execution-sharding/tranches_happy.svg
new file mode 100644
index 00000000..f56448f3
--- /dev/null
+++ b/content/9-Polkadot/assets/execution-sharding/tranches_happy.svg
@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
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text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 40px; margin-left: 633px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Tranche n</div></div></div></foreignObject><text x="672" y="44" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Tranche n</text></switch></g><rect x="99.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 101px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">0-10</div></div></div></foreignObject><text x="152" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">0-10</text></switch></g><rect x="219.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 221px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">11</div></div></div></foreignObject><text x="272" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">11</text></switch></g><rect x="299.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 301px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">12</div></div></div></foreignObject><text x="352" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">12</text></switch></g><rect x="3" y="90" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 105px; margin-left: 4px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="font-size: 14px;">VRF values:</b></div></div></div></foreignObject><text x="33" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">VRF values:</text></switch></g><rect x="379.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 381px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">13</div></div></div></foreignObject><text x="432" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">13</text></switch></g><path d="M 152 120 L 152 153.63" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 152 158.88 L 148.5 151.88 L 152 153.63 L 155.5 151.88 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/><rect x="112" y="170" width="80" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 185px; margin-left: 113px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Around 30~ validators</div></div></div></foreignObject><text x="152" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Around 30~ va...</text></switch></g><rect x="242" y="170" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 185px; margin-left: 243px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">On av. 2-3 validators</div></div></div></foreignObject><text x="272" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">On av. 2-3...</text></switch></g><rect x="459.5" y="90" width="105" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 103px; height: 1px; padding-top: 105px; margin-left: 461px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">14</div></div></div></foreignObject><text x="512" y="109" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">14</text></switch></g><path d="M 271.66 120 L 271.66 153.63" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 271.66 158.88 L 268.16 151.88 L 271.66 153.63 L 275.16 151.88 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/><rect x="3" y="25" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 40px; margin-left: 4px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="font-size: 14px;">Tranches:</b></div></div></div></foreignObject><text x="33" y="44" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Tranches:</text></switch></g><rect x="3" y="170" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 185px; margin-left: 4px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><b style="font-size: 14px;">Expected numbes:</b></div></div></div></foreignObject><text x="33" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">Expected n...</text></switch></g><rect x="322" y="170" width="60" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 58px; height: 1px; padding-top: 185px; margin-left: 323px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">On av. 2-3 validators</div></div></div></foreignObject><text x="352" y="189" fill="rgb(0, 0, 0)" font-family="Helvetica" font-size="12px" text-anchor="middle">On av. 2-3...</text></switch></g><path d="M 351.66 120 L 351.66 153.63" fill="none" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="stroke"/><path d="M 351.66 158.88 L 348.16 151.88 L 351.66 153.63 L 355.16 151.88 Z" fill="rgb(0, 0, 0)" stroke="rgb(0, 0, 0)" stroke-miterlimit="10" pointer-events="all"/></g><switch><g requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"/><a transform="translate(0,-5)" xlink:href="https://www.drawio.com/doc/faq/svg-export-text-problems" target="_blank"><text text-anchor="middle" font-size="10px" x="50%" y="100%">Text is not SVG - cannot display</text></a></switch></svg>
\ No newline at end of file
diff --git a/content/polkadot/async-backing-shallow/img/unincluded_segment_1.svg b/content/9-Polkadot/assets/execution-sharding/unincluded_segment_1.svg
similarity index 100%
rename from content/polkadot/async-backing-shallow/img/unincluded_segment_1.svg
rename to content/9-Polkadot/assets/execution-sharding/unincluded_segment_1.svg
diff --git a/content/polkadot/async-backing-shallow/img/unincluded_segment_2.svg b/content/9-Polkadot/assets/execution-sharding/unincluded_segment_2.svg
similarity index 100%
rename from content/polkadot/async-backing-shallow/img/unincluded_segment_2.svg
rename to content/9-Polkadot/assets/execution-sharding/unincluded_segment_2.svg
diff --git a/content/9-Polkadot/assets/execution-sharding/validate_block.svg b/content/9-Polkadot/assets/execution-sharding/validate_block.svg
new file mode 100644
index 00000000..62d73c40
--- /dev/null
+++ b/content/9-Polkadot/assets/execution-sharding/validate_block.svg
@@ -0,0 +1,16 @@
+<svg version="1.1" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 740.838838335262 328.62450298186343" width="740.838838335262" height="328.62450298186343">
+  <!-- svg-source:excalidraw -->
+  
+  <defs>
+    <style class="style-fonts">
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style=&quot;ellipse;whiteSpace=wrap;html=1;aspect=fixed;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;rotation=-179;&quot; vertex=&quot;1&quot; parent=&quot;30&quot;&gt;&#10;          &lt;mxGeometry x=&quot;79&quot; y=&quot;178&quot; width=&quot;40&quot; height=&quot;40&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;34&quot; value=&quot;&quot; style=&quot;ellipse;whiteSpace=wrap;html=1;aspect=fixed;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;rotation=-179;&quot; vertex=&quot;1&quot; parent=&quot;30&quot;&gt;&#10;          &lt;mxGeometry x=&quot;226&quot; y=&quot;81&quot; width=&quot;40&quot; height=&quot;40&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;35&quot; value=&quot;&quot; style=&quot;ellipse;whiteSpace=wrap;html=1;aspect=fixed;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;rotation=-179;&quot; vertex=&quot;1&quot; parent=&quot;30&quot;&gt;&#10;          &lt;mxGeometry x=&quot;51&quot; y=&quot;38&quot; width=&quot;40&quot; height=&quot;40&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;36&quot; value=&quot;&quot; style=&quot;ellipse;whiteSpace=wrap;html=1;aspect=fixed;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;rotation=-179;&quot; vertex=&quot;1&quot; parent=&quot;30&quot;&gt;&#10;          &lt;mxGeometry x=&quot;121&quot; y=&quot;89&quot; width=&quot;40&quot; height=&quot;40&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;37&quot; value=&quot;&quot; style=&quot;ellipse;whiteSpace=wrap;html=1;aspect=fixed;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;rotation=-179;&quot; vertex=&quot;1&quot; parent=&quot;30&quot;&gt;&#10;          &lt;mxGeometry x=&quot;40&quot; y=&quot;118&quot; width=&quot;40&quot; height=&quot;40&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;38&quot; value=&quot;&quot; style=&quot;ellipse;whiteSpace=wrap;html=1;aspect=fixed;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;rotation=-179;&quot; vertex=&quot;1&quot; parent=&quot;30&quot;&gt;&#10;          &lt;mxGeometry x=&quot;-2&quot; y=&quot;237&quot; width=&quot;40&quot; height=&quot;40&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;39&quot; value=&quot;&quot; style=&quot;ellipse;whiteSpace=wrap;html=1;aspect=fixed;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;rotation=-179;&quot; vertex=&quot;1&quot; parent=&quot;30&quot;&gt;&#10;          &lt;mxGeometry x=&quot;202&quot; width=&quot;40&quot; height=&quot;40&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;40&quot; value=&quot;&quot; style=&quot;endArrow=classic;startArrow=classic;html=1;rounded=0;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;&quot; edge=&quot;1&quot; parent=&quot;30&quot; source=&quot;34&quot; target=&quot;32&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;328&quot; y=&quot;148&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;271&quot; y=&quot;225&quot; as=&quot;targetPoint&quot; /&gt;&#10;          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style=&quot;endArrow=classic;startArrow=classic;html=1;rounded=0;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;&quot; edge=&quot;1&quot; parent=&quot;30&quot; source=&quot;36&quot; target=&quot;35&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;112&quot; y=&quot;105&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;69&quot; y=&quot;121&quot; as=&quot;targetPoint&quot; /&gt;&#10;          &lt;/mxGeometry&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;46&quot; value=&quot;&quot; style=&quot;endArrow=classic;startArrow=classic;html=1;rounded=0;movable=1;resizable=1;rotatable=1;deletable=1;editable=1;locked=0;connectable=1;&quot; edge=&quot;1&quot; parent=&quot;30&quot; source=&quot;32&quot; target=&quot;33&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; 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tbwa02Efn6U5asUPJ72hRbOp4Imu/RbdLM7dvDgnChdOJ8xoX0Dgn2VeEEiIaXu+h8CDZHiO4rT+8L7O273NOh2IGBKaQRQYeb7WjhurNl/6V/clPMG8gbQh5jXBj3yYqDvASYifoKkF0ZQqUbCQD2uxl2hcgjTBO3pLEQg7w1jReGDFOrHzkrhEy1BRj+4CRYa3NLA2PH6qXOH1jdQFDKNWiZ9pRjxlIfKhJesh5CZVQXVo/+grO24T1GKphTAKmG7dQMfO2oi6eccY/2SfjDc+RVkbfrPpK1Lku/T1kGQ/JwPU2uJU0YtbJzfsM0wtrb0I74NdntQ5sOKXPOwhsOyXIl7s56eXrzBuN+0gvtS18pGIzCEp0df4VIO2OLdfuXc/Mou8+tvbPG5AGPKwZI+5YnwHJr2HU4i6Uvp3fST2pF8Nnjyyw4mHXdWYQqz/QaxxXLiawH0o+Xsq4fzGkkNwS3+QVkG3DodiabvGYYN+PXCMRqH4uiJhjYF0v+rzDnq95MU+duFU3G12cOLKEDiMvt0nuND7oW2F31NMYxodXCutZs54nHMlmhDTu63LsaNkQDGL5feHHm0xcRC2pt1lq4WqvFFmVQFcO7iWu1jbl5jV4T1JK8GIVX8pQ5kt+JvtIqfC9kW4jJARQtPKHozUwUiYN/udfOePiK2cOtaj68CecDj2oca5EqWIghGA8eZP9F/IrMtJF78fZAK5t6nQhRCHOIrGeIpN8eApsDTvdumw1Ar5HT3JIHuyahYcgD/Zti1D04lVGiqMazJANDSh5U7AZaz40GuOWS9Gfp0PhIi2VicM/+BXsLNf1UduVicI0yOAfWTjKlUZFG3cUiP08eMUZIitcJhIBQeVcMqaMVvVvsIboB5BOdf10aSyNJ+4qtCvb0bh8OLbLTiHqE0vaHzvldG8+orCNrygBtWcWLp3kRIY6YfXsvvG1cBxhxMcJhXs6Nt9fr1T8M5ezkS+GHL4q8SK9DVvzBIZrr8Kt8cOtnW598RdPjTbf/O4VtA7dH1cNAxLsTp+BcJCr20zrUn7++JeOs9IWjedO6B84To1cN4HWDJPDtZY5chxwmz7CodIuXDCN4K3pmNw0nr57F9jxwo9cIyeO6HkXOmK9YaPQlkKKSPkJgZV5V9VCSKHogXx2q2eOB+cuAjQxbbaiZ4qDpj2nDoV6mJttJBC64GgImaW+0WCRAdJ8Fp8slnRa3EXgKYbLJZ5IEXpX1sFhe6uO7evnX9mzBZ+d2CULJrhp/H6mqoOezPR0faj/nvguVVSNhAF1N0Rss/lgAQjX1V2BIMOGoAjfNO9o7qIJBetQogb/b0ibMVxXXG5+UFZfM1Xw7YgdQPUz2S+vd5ieqj/9LVY+/qQ7vW5KNxmguLkkKlLJizvDV0n8PXl1Rs266kSsslDVdBLJ2IGHzC6P70qhzz+0tIFm0pswJBJ6W/4btKXIfGDKBc5dklQQVyyIYYBVQmiVKdHtw3ryg8SCEYStJpNV1l2C8unoyV3DR8ZhJYhcjVB0D3j3+eh/r1YM7U7vg2CWouvqZOa7z8XBiuAqROGevn1Ux97kwiKIUz+q9gs/bfCztf6qxkn3ZOajKPvL37qgKh1f7iCjBo/ZL9hBbpYvtnfYmmxO4/3ILlBvsh8eb+XEa7ex2FYojbPiE5EGVfSbOxQoOxvIS7QOQ5TRhMeb3QAIXjwl00WPWtLOzCj0jqjmHsvk9jGAlmhLo1cJQpq1ThSEnF9E3DyOnyBgMikkEWL7K7xAbHTnkxqPKv6rfMKKi1zRbXikm7uQW9YFxQMC+WHd/aEeaPySC+SHuXtY13Bm0m+pODMZoKsGhiATw5v8hePsKhjYeExESHvo3vc5J/UHUA5zplKyWpSoMoqjKQfa8IJrsi7pnbF+jH0TjggWXcL9ekXMZ/vkwgz4L4+S1WhtFKmYtTnaZEnUFwaVuonPC5ddqy2X48lYilf2tbvFLqfZMuTfE/b36u/ENTNJy4lc5mRWnsdRGsoUFoN64Ke8jVA4owpcRhvyV5uS2SOBoHccIehMevrIxJQkr5xfxWLRIQMNQXA35DvAt7vTDSCADUt/2lExxwOExngFClwbViVaGXP0GEHXpOddlr1icQn11BOvmj43n9smwa5H1Vrrb4wJ/feEKZzpkdywkP1AQkMDALrDlNvjO9CH1EGiOqN1p4EKVMAIigYK1lw/Jf0qZJGpAwFL34ZAXRZJj+gqFYKrB25eQHLo5B0y9+n4G2FCCCsPATVBrWXFD+0RhfyR39n2d7Aa9hn2ucVHypDt9Dq+Hx4GtSZ7gadXHAM1u70btEVt0aC9mluQywIoAcKvUfGJG20QGaK1WTSd6eljhAYMhF/RjDtZLWl2dkz4RsfSU4opM9vXf7XZdUyBUgbc4oYxLeDOwMKv1r8TXK4UGfLH5gk1cJkMMIVfY5PV6IlOEtIDsNcTOgpZfdL8EVy1U4n7bxRvS7Bhv+syoiJE5ba1TXes5zCzat6GGmNNrlZxsCY93ZrLwyYL0bZtYdJeN/I2EYIErHDIG3KFf73ulJk9q9aqEoAifkzgVo/6ZkCxp3wuJ/EpAUd3KBCqmthelfTIw/SLVJuQ1NMP1xUHywSHcrrAQsNWOfxa9IbBnBvDLLMhgk/nKMNRP6owmBWAog46LhM+wiSUcwSQJBhnMtChmDNz5Zv5xnDEy/MDBd4g41t/PPn2jmlcFkTsUETKTWNZ5J/xI1kOpkAXNOOWwn2/XdDDVfSvT5aV4srAGgxCDFyGP3ClvsZJXIGZsYAA6sQCFNoJT7mrBzDuomTq/Iovv4K4FmgNoVgJgRt/05fAMF/Bjk3uOOKrj9Vy4rLB0EziGBMiRvTkCYiN+XiNI0yBwyr40U4M/m6qECBZ0pZLCEEEdZJgnaTFCMwGriqR3jS5LX6EjPi8NMB/49HdAuIPPa4zaGqWlPYZZ1kkSzkF6g2gJ3wT751X3kxegeVSzLww5/gCqq/5Jb4LNbgsTyq1vWhl2DwFIc8rABZ+0AeUs5TSwwduedAzZI3CSiL1Qd7b2v0U5JmMdkygQ/xBRPU3yF1Mc8dwM6TID4VPO6x0osYF6jDFY+p1Zzv7qfPFt+in1zladDYSnlAk0/MeQNKKd4H0esb3oOlOyxWucl8mr4eqXqmLCCbPI2L22Uk4BZ9xRhqa487sr78u2fmROwIpKDzKscihNXgjkK5zYR9/78Wrcy/K8r6Nqe9v6b+Xjpdn+HR81vFBdl6XKWxjh+8pwIx+WP7TDdwVwf1snaXLOWmEqRcXCgSzx0HEq1cVFN2muT63xjEYCjRJf071UUxeuzdBcgJMy6VTmXxe+lIbumX9/JMlb8KIM1K9Didb4aVhVP1yjvqwNOq7H6VmSiYM2Z8XLe14sVeMmNTJx8immeS37/BOlzNwgytgCZ/1TFEAN/S/YTX5A6QRVBUGR1gTZYhCDCIdA9xwYho62Y726sI/x/+i12QD2r2087i1yOaU6ZRfL2I3yY+fX7OrZ4TwvYIrJQgkI3t0VC9GWcUPySwDoYPeDRRmJfk164BUXTW9qjbBcjldA0DP7RTwr2FwRZZZkm5rxxY1TTtwnDRoEHb3ed7YQt7iUrXmMyX5PA7VcyVSanvuxIvDqhhoUYlswMzS6bBAFC0Qcp40wtcI+y9TIBsgwcj4+K08+3tZKKY6HM5jiFv57hC8qgh/Uzcc82AQrqCwalEsiJ2hkirqcXpG2mkei1ADSTI9SSeg1m0VcbBnti8UOdEu1NL6esHWeA9G5+UYCJQr6c7+3NfXRVkFb8qXuvRcvGfzWecYjkFz3kCo+/t+nFLlK96o0BLBl/dBiU2Q/6r+poVST+zbwgiCeUtATnIuARKNGWaCEEgnOoibKXXZ6gbCd9fo0qBG3+dXRXiFH0roP7j/M9QAHyAfMRsKmZe4doNQJxjei1Pv2L8TerA0A6LPGKd6zQtPHXE/UxTQ8wgtAfCtDwcMkAleC8i/3HG8BwbUCetz6+8X8RFTr43IUBvY5leTwKoWiJEldq5+SoqinuGPIcwzC96+Rm23PN7SQl+1cwMAnfZh1eAaXH2DqmOYqLFe89TThr9dXT/Oo0Cu2BlTQ2aaTetMbu2Xd7ypdYTv9h4uR+SX70Td8/h4+bJa8amRylfPmft5fRA+qYSGGxgoSHagYyTipq14Q742BKb0wD0J8bl4E958y+89zUK4tBQp93/ksJe/+YAo+5lBwiLRAOsGeQhusIgVowXFK/0telyq0t0wHuKhMTtJcTS31iaMAjQSARdELrAnJprZc5ZJgZbaOTzm9bpRQpyr+koEDMvu/P80oHFtovOcqRdQAxAL/ZR04aSB++plCHaYhxOPNpid+lmWfhA0j/KLUvOTl0vRr4uRhS+WJgbDXtp4zHQqd1kXSOrRrWkXtzZipmOC4fQbRXvEr3F1hgAGwOpTfU/c6/7MJzelSJ2/mtrDcvr5sO66VhYkub4zjxzE3VsUerm2oAjShKHdNH1jEEeEI2dPSwFL9a+Y6uGdXFO6sHbultBYl93etp3RGDJh80hbbX87damgqOD9psteRFzw7JL173EvsDiSiG0VrpuLZcxHEM8Dj3uToFFY9ws56eakSGpIZuRlHgrC1Kn5Fu4k2T+yHhEsNFglssySWgHy9OBZLbB/8GfjiSj5wvPzpVoorGSO/GUxr/bGCh4Nt4qdO/4slW6XJdA5G5X8ZL6XOry19eB83vgzA4zeAOvHYn9Np1Fsh2IeaNLi+c0S0GLIb9Ud44adUnfP0eXtc/81jbhf7loMYyXz1jZiOQitmrVhHcCQxbpdmvoQHmOlapel/XH0HvBJrqhDG6iVW/8hiEArlB70DX4+MDRdICFiyIAKXqtdX9QfCAoFgeXWH5fUZjtvP/vOyX2JK342T+dQ3AM0hvj/nLO6HpdgbCFmm2iQd0wq6d5lAO+Wj6lNHwzTJMS2HX2gAS5ZtWQBCL8IqXdwUm4lKvT10Xbf/m0hrVNwkU5mBjx+uvmPUYvcD/qb2BWQGuW1ouFKYSSYaO0Zgb59SERZB73ViQ/IhicFc5VQsHk/MfJS0+Jqpycm+cRKxmCoJrcOrywtP1ol15Yk+mh4MbS4b8EOXNzLhHTmei8g6VBhfFM7TbM0zM/diiGpQy/IyqwwuYyuun8XMcbnbGmHXqGjd/9YTJdUnDjwTq+TqJw/eXaRXdqB/4A+OLKkWgbul6XPet2QHWW65XnoblYs3wkH4QYYKVVSYwZLVabXlJPttvEMikTmgo/tsUA8CqOpsPXe1gda4d1vpj07d7fWybL9sNvVfzRxIwHTEd9QV97OLlfUAy4EpzBtBhoCmqdxCg1HFZbXQKyOrHAM8tu2uraVB/+tu/I2c3lpgxlptIxKKPvH4FJmCQg5zzXO3wBxtkuvotusiWkiMiEvGN61IRTTWdRYb7KM5wfHcmUPcfNyf0Lv7Y5PPTU0xXkeddlLsMLmk5p3EzN28Syzwi1Z86XvqYJRxd/LinGRPGUBgmS+rvyZaZLER1w7V/Mw/5RlRHh+UcTRguGiDOq84c4Ztix3kBPLfVm0af7raURXa7Vt7i/rvE9nXUX7LqwXwfN+zWBshlZJMynb6OOPVdLSJtvl5K/cZ/2VYfoIBT0DKFngaK92iBPkODU0v6qT4XVN877qz19nVnp+EXJxv4wSt7eLzppslecwESMUUo+kz4k8t8OSCaBiONHUs0w9fxZjFy196+uPFOuHYGc+O9FvI1c6ifjzAvfrWzLDyOEYhOWIlefh4+5RKKpkdUD78Frduffh4Y7TpWm3SoBNqO8/gUA2xv5lPwXi8amUSavwS2o5eTVMubIHhPFJjZVThGiDhROFnbifVXozKhIdrPzwM2yWpXfIVq9KRkeQRDz0ei0/KC8niIAHVdX3+QRG7IQhrFK7/YqqAq89LoJ7cg13YRpDJkfhxzHGw7MgrUjOBCmImxgSudrqkc/geQMqmjFDawIfInsn+qbwxIfoE9T/ASmcirIntNfhly9zJjfrGXaFruAuw5CFy8zkWG4d1FB51AAE1FeYzq97qxqZjSvbmNk2X9z2wHV30BD8FIrDI0cuMGpvZ3cepePx1bD2889ss5/LyeGhafrVzPVvNLyMkAeCsqfgCh3oTV7v51R8N9vAF75JCKISJrTuNGqR6fllUb85EjnyO9aUnf0ragHYV8lVa6JGMfx1yRy8aZ377sf6pbyZHBiKBI9SCSRK+FTs/8ydXgEfAJjf3iblO9X3zpwItjkNH0qbSol5dyqWfma0DPFI/sNzDHhsf1VmBe4W/yH0lwvqVBiVrifGuGZd9LWbeMBOll0kzP9hbD7pBWYZ8mZ7E2VH9sPCHkYwZjWH+WP3qEpW3UdSFJPZdZpssdHsYUe8TnCrmG+2azjVJvXIAAxOgQWCcNaKczo0vqONsmQqmdNgy9CXrjbJwAJflQn/r1AvCtMZimg2hCDs0VDx8B+gKAGoPq5nqDa9g3Dw6Qq7aMUiRs/w/wVf8zhWb3MKjHCEwmSvSeuSgVmfQ/fREq9+MVoLRigIa9YblbGBm+86ha/wanKpHrSGBz+yPXFRKcnVlJ2+etldiwKhDm2Xy80NhFE6TRuG+15HE9TbohLdxTLmv2RK2lII7FwU81Utmb7QtprIAdqtX9vqpIYjUmPdVdR1N3nmiZG7V3q7GYBOq3RCgCFosgr3ePwKrm9T3ANLUmg74jrGd0rVsOlLeNQWHN9EHItXV8+QhC89viUy7oZQd0A4vPu/V6F4eh5uk4orMg3AOvv2PA5lJLek33IJyTr7JNp/mzUoGBD7k/1bM7SrFd/a5zw3lBtwpPEkizLg1WXieW1ygSP3EY1lSTAetwvizjZdhe4LIhM9csD1gUa7xTUz5N84q9eisjhuVU5kBN8s02EHcf2C1c/DN2g7kKL6gwiuJ9/3bTCY/fY/3hE3RB1nPIqGyOwpEmetA29xnVij7XJ+8LP1w4Cuj7akH98vxz9hUjwow4xC96ApXw+97haBPQ8mYphASVN1W+xWdHjZljOEDEOwtUOJDN/xzpQCCUZbIJskxxfLsAGcaBi6cdXfCXub1O2qLGZF+6+a1egujbCAzki6fKuK/Jqr2aBdN/lCIaX1LOQr0aQzpoQAxpfvUONq1d4jFEcZ7XVk0zq4j7AZnGIil+FGusU1bBqbyM59sKwUf5vuKAHksaqnlmFZwP43nkUTIhJ0GsM91cG5ghqDRXRuigYNeS9fu8a+bsY8VD7scRGEsNMmEePTlV/PORgGEXNdZKCipo+qlcKgEt1fxXu4E0e31yoHUSzZo+WjwnDL9EebNwwzOs+xp3F5h3bV6xMYfRO94fvDrMXMLu+FGn08UYJqQ9Na5IGO1nWRhbBH+VG6skjK5E37VPbESGZoXxOMUNum3ZsEZ81uFdcebDpcGzdBYN85M+7trrqDXPk3ZIR8l1utMHwl8l49qpKbPtBF84j7qXdIv0vJI5ipKllT1z+H8Y3sriC04nZby32hGfBDl8YrID1U6iGkqMOiL+sR/0ogv6BaYFyYbhiivrzZQJ5hCX9mVrr6l/nXtR5Ze2N4klk1F+o25Z+34NMeSiK/VFfMh+wxW0WQaUYSFET0xF5HMv9C9R+OpAFQVVrtyKqA2iFH76V9KBTYqWgDA+o6R+wnCOvtjh5sx19/N9+cyZwS0V7uRsdW9pDvN293Ygkf6FoMrOHErrvpRf9MUoXMZTF6hInUcN1jScD6NR1F4yPrQjPM9Z8zkSImiclz0oDlsnjCP4IZ6+OtHhmFbLFfk0RkZhF4L/tUSfW5/Il+oOtmzaCO4PTV71zijC3gNUf4kqrvcWjucMw9a2cJP2VFA6yejxyKCpaVvntprPtFegfxehsF7Nj0HOyC8eVFDXwu+PVfuK6+h9GYzTTafXY8GPC63Z+rdhYkI8bC+2qQPs3EH9aaJBuT501aHZr+vMMDYyJPdOUukYBnCLRc/ZIYDaigYqaTpA3wtWiapASOkm604v8XMp/IkEJBbOK+gos5CPqBKRS0awNg3UrQiOWaTQzKcLAZwBdJdYDA9eYGilcQm6dYDnvbvge1SrNmX51jRpvjkFYWECxCt/A5cIUM8qY8N5aqOqDM6OXj9mL6KKQjuYotcfa7BkXbQtmRgba4mnwKLJYuzPSvVzNy/nugzKJs9Qtq7azEisWIhRrArR9JUsbRNdx5velRzMNycYPBwISoBnM5P6az2Z/jC6IaeRMm9YQRos8BHD8cLB1m1ucMUfIMa17SxIJrdwQc6VL/F1bjZpiq/jFjvLAQee1vMop/jqdMpTlOJpInjsYMdBTw65Z24g8IQS5YK4yYo2j/ZPRxfFuu/pLsF9EmmVxurO+DE0sM9jgChQPNrQDWiD+HzMaNqQ3+bf9RciSBsVdxxs22NjkyTo+RKZDeyS3ua/PpLCNl+SYR+00kwfPdLjoZiaJexN/UBmCl8/5jlIs3PmBFqFgdWqTHVCQvOcb3er4fATxfBOxeGnzPmZkdvqSoYrzjDAhbwZ9sDXUjGh7v7Q+oELvI3Ppib+BGJgDZzbe2vtJMb6GyyuWVWlf6k5W4Rj1Pl8v66L4u4N2/VBO7SqPmuDBqo9lHLWdxEGYhy6AROAAhmNJAGotQPMyc4EdpL2CAq75dsjK54CtB/Qyf8rnAA7rBS1w8plECA70cX+q6shzvISgR25McdqPd7sn31o+EpB/kcQA4qQ9dtREXxl8mYuc8B8pJyM2aCBzbAGnREnBGXa7RKX5dejYt2ykTi1E6oGVG7CT1bo3puEJpbhLOZCP2rOS3gwzMrWv859vCxHUvhsSJjd4Vs5YG/GmlNHVaJb09xPvS++96oGeAa0iejXJNCUAMlxJHnunp1ahyRzqHV2nNfbW50v3SK9u17X7wKULY46TD00RhswQ9hHDkUt6+zeGctoIaPt/d1/HbF3s+S9StVqh3PDAL5NMYwYh+2jNA3dKgzdTKgPErtGKAu8ThGjLAk4VejOPQ38IoDDUiLWzzkKiTQnISv2dDRLZRjBPNO7iZa1nR4asgPP67C6onUU1zY5zEdlo3dyzShTNli+/P5iS8rPP75JOPvXgToenOckevNFbJe+qWfQPsWTDUO2tf1o9zrKAn6VEbaP9EvsxUp6fBjPqVO6v9JmoMsi4D7ZXbf8svq0SyC0aEsYejmDg7ycgQ+eeSPCVxhnZTQKSFgkYRpSe4abEIx/Qpif8Ue17OIkAyPYTRoEsCTcaqTnJMFvH0CVfeCEcV7UhjUaVILjieI0H+ZrFxTztKFTsYKkZAHTyXwgOALHhlzi9E3IsjXXCqDJ+P58X4fhvqzCi1HU/WqjL8K8YDUmVPv423pwz73yuokCpeYwt28D7xdqibWkKq/pQuh7k9APohikEbWuB5LF4z1BdR9JgxrEJu76v6I1QtMb1pjsH6m/GaF83c4RGVE4pJmcQF/nVbJOV85UKj25n+5p9wF09sZfVa+4ymycr4yVo5F8w70XQBfzOM7nipRlM+rwZfuqsDLB3msOhLGM7JpAEqCM8eZSURgjqfyMS+r6XouyVvI6Qovre7voouwdPwTOunzG3DT3XC45S/MKi2AS5tQPCtEx2JQi8x9pxiQN+vLLUfG9Wdp21l/dv7D+hj2N484wRIZ1X2EwuM00wQMOVy97vG6Eosp8o+Hiop+RlmMVbePrWJ+SAm0yXnAKbrXNGvSTrN9codMJIfiXvr2fuf3IA0Xsdoqt8+VBNSCYa3XQE779tVah030BkyuIFqEUnacVs22C0AhvVKLlNMXhMA71uDv5dudflhy9DI3liNGnkZqYyjidDNsjkt/nOcYfgTY/iXFrHIZShuO/TLN+pyoTXp6+tevzM8wn2gYuJWCpAL06BhIS+kELNvjSLA7zPmNyBtX7LG404iSE72tXItvO4xhRrA2cVfr7Qhb515kMWNdNs8t8UY9rntFi+fgXB/58fissBEmF2s6bj/7ZdwTppesv2wZZx/+5oHxf8jtHVSWtRTe+aoJWwsiSbUiv3CqgJpUl8eH3XiLQOjjM4wcA3AtBwcJyDrQcxCGBAYkZPfzNpBrgDqMt1A0/R0BVHqnlVR0imQSaUHytQH73u1nBx/eHIPKntD8bmqU2eyxEPRIcagYx6w3DIRYsArk9mm7eo0Dc7FFLT6Gk8m2QkQ5FTQ6gjkVfyTgZZ8wDfVzc1AEiu7ubZSTEsAcKK53v7ftbQPWNtd2ofXN6hh7E7OH+NcX+tuJ9hF5d8NXk9qU8gcpNeLis4vKunfpiMoKloLRFm9da3/xaTTwaYX7mhCCjU5u80Alsv2d+K0eZIP60iPjR+Q4q0CoL6TOlm3dwG7GFwe8irm/6X8ghRtA8NvwIfXgd/1B7/NzNObnY2QUagaVAdDxKdKFL1wPXZsRtcxKsGvKGwpWRJldNO2x7Jv30tLp/rRzyoHJ8SoOYaZv6S/mC4liBKF/7YnsvtIMG0L/mEkmD7WwscInrkl6hvunelRIDwgmQJW1aejQWXYxEKA+zhpNXLgE/KK8siqgzH7r8s6XhdG3jEH6q1HnR2ccyKGplccN4xqo1wyOJ5CW7HrLqQCz+MYnykUgrjPJKTmU3iJ2zq//23jiWQwzhL5yWAgLVjdm1LnucOungAfKArb4dQq16gBmExf3kwM4daDkmK0/nUyYdIZXHgqZ+YAPi3z5wdP9rjALZFv6zDK0tjfol59V7nFBX7ZGwkAV2DalrOnwF6AhF+tYWKCx4EpCv1WbIf5sw8ervW4QH0zCs4TR26l9aigXvWKmv5W3rL7FtWDZhCCbSn+jG0nZsdgfa2jKFLjRHqm7rtGSqBTJXN4yJp31Mf2mwq0/sscDRzQAtizVoA2vk18nFf/OPqFwCsv52l2Y/fWse8mq20D6aYqIZ01sQ6bGRcIaSFHjbyQvWXAJenoH+g7Bi5/lE+Hz1p0nM53WWcsu6ZfFyT87l7gw5hht8n7qTDRYEdIfHKVS8Eosxebcv6N7R2OUA1os+lluBCuGmG2helZSQHRt3XFN1gShrrOkFKASmmIwsVz5Cxh/9LqjE71/jQmewdlepeINXTBWNSneTy3nxO3bS6DIhsK+N1j7lq63QPdmEvJjgJ3yHWFriiBB/+05dFaM+Z2st2QLBFejWX2U28vYD1BFts083fZHx0GevDWt1LUWf33829s1E9tK4RXN4JWwgr93CeATfBRD1YU0LeOUs17yu+ekVNr6eKr6Q73FGlRjp60x9DFT+yN8KFoFOCgdpnQ76EJF5PIPK/nA5Mv5zSrZ7Q9PUntxmCxm5+hi/z19firEa4RMMeg7k9uZP1zkhQbg5gT60OcjsXnSPSP8shweMr2jKBipqaUJu13SF2MtY83PUto6UBb34WhqKzp9toX6iIjFO03yR3KyNFS6P5r/SnaW/Jkbsfay4M+yYL6lmnVRVRm5ZL+ecDLpmSbd2AoNWaqlheQyzYRsTQHHbfpHUzylG/Oud2/2KCyp77PEHj8wyKJox5tTuG6MjyDRJKldgzK5JR0p57bgAlX/NXceu8rlVE/oviRsVr42YKXeE6f3tCpIfKQP8SsmpsYThpPo6ccJ76NNeR3CZJ5YdtsfXmPuSOevPj8Fes747l63K/R/2/Wh+laHzGIMe652XoAFmSXvwMcbW1IOmTL8KA3hMq/0zSBXylFKBhPBVZf6kZIjAcI56E4cZgWTPcjT9EOyQ0nttx9v45ijmYmmZ1hdZb8+DKh5tnbmLJA8mBc6GUTrd7v1Smpz3nLDH3JopV/XDp5RKU8B2x/CgOAZyud0Wblw9Cgze76bUqFyH+txpAlEza1cLHw7cMPkkTsC6D8Dx3Ew1Jk5DXw97le3gmEyiOraGBt3d7IOQGa0UsmdyhMH+qRR5cYzVQ1+rP8sHbJLdJpbbtG0b0IOucgx61TolqdkLds81Uyumn+vKuAD6K9XVvgIPasSg7NjqZJd9G9gtKnOs6f/sbQsGC/QLuY2y0afro1ih2MWZjTcbsApUxDUSpBhfn7iulJwgM8901biMKsg3VtIGVRYWmk+WTE5H26OtZ+MJheWq+7WZ3VBBWdU40DPl5f6x0mATTa0BjdfvryoM6ssNyQY6oh+RpufxmjCSpmgXggUcv/EU/H8iQpdOtQee3Jo8yTI+G1ZiMTB4i5iBTFw+1LD5AD+rf93rp4zYKt+/uXFJeP23q0JusNqxerANgIfY5FUPX9LYTBSyuF1gbosO/jZ1gibdi0TN4wLI+7AbFFXPMby0B3tE9mtzc8DhtiHuEvQCfGDXLf9yYuoFK+HhahWZmMN8dc3KmQ3O3s21ReLgFA3RIw6JyTt7qphc7ASrSK9BWwJjXZq6d96yXObHziEH6qSAC1AJx5OkUUw1u411SriM0LwMNJVeVp5dG1LbF6gO3CFF63Q4Cx9IkmljADD+bWuc50AEoiz/4Dizg+UnsMWQ1F7MnEceHgyDaf5Va07rKArDGxHjI63jf6M6cH7sPvSi9nKW3jRfhQKtHMbGacHOzf0CrzfGcX/56kJZzQ3Dwl/LNAuG3kAzMCIo5ykL4pQI/6CXENopef9LyhzYW/uA5ioJg+3Np41e71pOHXsCmPE8rIrpbAMOfmM/C0G4rx04ULag5FQsi0ySr4487rCCj5OAZCRVaAsGrS9RTseqtA7Z/bbOWTPg+4+QRIA61ZJZPwLfqjfTJbGYXqSuk9sx0U3Pl0NWlS0PxiN3QzR1wGJu/F2osmqI8Lpe1Ti7OOS/9B8pwSRXooa4/N9kcncFsGSr+cc2LhITX+1xi/g3kiEJ7/cn/1Q07VPKR04pbh3ck2XT8Aue8sizhAPnCrHC//WshhDcdp712unzWc853BVMFvYqbluHlehvYkh48oG0EmySt55fIdIRIeO02Z2lB1y2azzUn9ANQ4MLKi2wPeL3o/Kg+E/n5qL1kKuKzwxy1MAF5vjgQAypQAaN9liBzGKYSGznJPdq+ys4duwiBg4+oi3GFwezXpYETWB3fFabv5AUUardMxKrGI23+wr6y5AEuv9ylBhE4jtLH4oGKKkrQQqhmImH0UCZeC6TqT2ziBIw2s9pBQ8uORJHvyk6dZud1mh5C8rTSj4CNvpMX6YudFOaGeePj/MmqD7aUoyV4IUXkxGvKVulif++2Jcks6oI22nxzwtin+clbQzPBQyjW0WDyN0TN9AjNZOr8zX7s/AbpVLgd/VjWxY7Q74T509DM43uupwkH5DgML5sVza+FDoFaNF/WmHjGlD0IXuENENUeU6hAn8Mkh1wW9NcmBEExBrWH+1Ufr4AqimGKFp10QewteulTRuPlM10oMkHTGOAjPnKq7sGk1utrhGaw6K+TCDOgIRLpeoWPdzF9nB7S1I6qkIQBB6W8fOSPd0nQLoK4v98JfKAT2vVypJP+L7NmNaW+CQUUMYVA49tM47VTzp1BY6tEXSqmZ57kwImcJzICK+t2Jgp61VXZ6PWNF0RQi6tCX4VJkVaNY/XjYlRviELJ5zAe57KcE4sSYnbcIp8gWEwzHZ+uPdJNp2wDz//REFnGNfoWDr8KhUIm49TC5pfC1jy5RksiUH01TLv3pRdb1X0kNkrwsj+xmzH8URVFJ2DA99sYKlvAplIVf+8ompGoRNVfphejtob8sPZdckEk+ekwuaoacgx/xdN17EkK5IEfwkKVRzRWmtuaK1Vwdcv2W/2MDu2Nm3dkER6uIdUqFP7VEvSUSOOHTXvrfCljlSX6Diosux5a5DsMbiIDGASwKfs6auoXtb4nAiJk53R/8Tl83KZ+lStLvsGLknATxP8dQu2fQ/vXMkmiyOSGXxsJ7QeuMBN/4pw1bC115LAVx7kjZ6TbClpTVOctoAC+4vLCw8jReCjvc7bCPwc4IHEOaJ3tu8tCypiS9auNR583l9y2PwBePb8NgQIJizyHwczf5WV48jiqz2qtzuJuY9c/yTPhqhmD9dJFX5NNBmUN/H8HCIBX1PimFL517xMjcwokKvXNJS6euSjHDt0LMDX0s/i/mrOgtnQh/uUzrLCrMFrgI8AsPY6wcOE19K+dJ2h8vSEoMeSdQqiLvBCG4tSC5VUuKVI0gR4BXWeLJNd1OovN02SZMqmfUb5tk6/z5K3Y4icKjvxnPVRuGt8mc6Ej064FyAvyV3oiynWWdz2vzgwT1CQH/Z/NTdakZBWHioWNivsPJCNIyVu+aCIjIelqnyzMG3xDXnyPjPRNe1cFN3LD2mwA43TaCFx+iyCenCaYi8GZ4drc/fjVbc3EYCGh30yZ+j+61UVOEALMCUIUh8M3uIL7VsCTc2M83zO+ldvWZYoxcQ9fbLqJaHLKY/OgTO3Pi4a/1VWVflq7hC1EvhXlFDMrIJ7O/I+X7OGlmiW+v3gnPls4QoZ8PLEDEA1cv9FkBuF1H+1bi+A3nJ8sNlHxfRuaB70lV/E3O6096AEDn/mHSPAcB/pqXh5xFe/DX+IoxDya8RdvT+53TiBObI8+VPPEGD08Yf/hn7gnUhZNAFqgVOl4BC5fHQ4wIhXY1WWdW4C+dBUTSCKlxgariMBqDlNBtIIbNt04gQhMbz4hKOICNMZK+arMAnzGZmoTj9KGfP+J5hG4AHT5OJtiLb4TxzL83/sYM7pvgnRmPNyjFUJ/amrgSY8mLco7FL/Ie/rYCSucxhGpIDzjc+XHHxRNqM7+uOwFtetSd+14LvoltOi9GdTQB9AWe5mjaL6HZXaJ8LQFNIOFOdlw1zDOVheQxra9RbzQDvVgzAbtctWtC79/PbEICWd144TlOZ+NBQwWwmlBVqU4Q3ol5VuQy4C4qkiSJgiD+ix4LPv8iO/RRuPPBE2+VliGMTrDzk+ZtEHDb4fyErBg8IrgpHpY4+gxb/3CxcGu8Lrs4K3q1w2AnXPkqQcfn1p9E1RdLQHE1koqKhSz+stl6BHsveSUsbHpupNy3XSkw5U1mFkddMUuVcQ9aMECjzit9ge174+MoKjxbW9X5tiekrRxCHPyvKvUORz+366Y6DDno6EuRzhtizG9ljTeIUka2kf0E/E9ntPIWugL38vK99h5uGK79jnKZ71Ax4ah5aq5Tuv7UJQWwtp6xhg5SLLNiWF5IQoV/o7MtlhMEJiNloK3ct5v62HE99Xwwe8nuwLWphmV7HYBwm54zIkiybp26qG1Kq6b08bg8YylMBfO2Zi5FyUvkGqdltKttFwQ+eFMHv/rJBqxpAG9lMWXzmKPzo6m8TcwJwpitiQzd9FdDdE5EkOvt11NJ7QBQz08B4mhkjsBLa5jkwikDAAvstgKajeKeChBXEuHGoZRD0vQ1P7Zim/7Jrrw9eDBNiERsbJHE1ilb2F/FbWamzFcO7DRSCiJqDbAO+fuHVIlYBURhY+VOOIXBrLfpq9iIlPKuFfHYlMkKhgyTSmHgzfP5+JKyumEC/Q0EHDmfjdyR44UumK2DMofq9wtF0LOxmNo6gSJv7oWREKOzZ/f3+yIL+/eHYIsgTrD4uVXYTvnUvP3ye17B9UqGsIAh4L/+9qamXRFnz4g23I5yF5Ij6cbbTrJot7KA7FmYYVxHKmunLLX+dcmZu/7ZfuDLXgPfQ1/9LOQgZLSuTXFpTqNRHdScV1jUMvy0RJHBPwPuULlkV53Ph+eueUmq1aXMmSPMbhcwp+CUcMugWGJWGSeKrun/T+MDXVSVNTt7Drz8A5NfWTOmqmMpR3/saySOxsWyh20/KrZ3C4oqxEhyRVgFljLtipbY2Ce2EahZDwEseR9XR9QBLq+G5pxNrorVS3Clxzt6KPbXNXJlLxaZaFUlUMfQLu4II4uGJYoFyLJl+iR4svkiyzqsB+LDQg7Dc8ffHfkJ3ggxXfNUmf/u+SrL2IiCLI4ZtKyi6hv54xnyfjPTr7IJrBWvydJ/IBSOv/2jRuslriy1Jr8iKAlTBIzb754+ciRLsvc4gKPwauyvEIKRVqlLH6/jd+J/mvEX/4TI4N6o328mVlBYKyG/sXqFXsBV8ifrAFFvq8pMvvJ+WXdF3F/Giz/1JqBegpbckdYalRYOVJMPwmp3jpotOxqn86l3pRBpVJg7VflaTpNa9UXBW6WkcH+X6ztmQxLVdxMgcJHMXwJSUyQIQkHEOhlh461VLds0/JnR8MeoOIETS3Ak3ZcOG+TqBk+m9i1ttfNMFb9U2INi+jLUbzRArdYI5puKo2LJ/zJMlhCLTYG3eyGE6j7Nh72TZTreol4W0GU4Om6QJSOgAT7yLI27jTj/7SeuvTPxIBmziBiNj+uUmDLD7zSPTB1xzCc7jj8JGadSbP/UswJENJ6Qd6NS8PSNmZCW6IfKYgIC1wVjAIfAdJmwzwejgVPoWgKu9+QeIVcbNR82wKYl81CqN51sdDhOjNbcdIXz2TXmInQZD30ouk8QqkCEfJPdXv3lkuZhhLSgduxijXTVR5Zm8ziHL11u4v9kM9IGAC1YZUWNm3guJ8/55lp+IDg/gjsdifynK/SbWkOCxHBY8rTXoIr6mULF6SOH+sL5sxCOcJWa5LwmtFgOqhOYKuMJrsh0ulwHsgVMRQODJV5r4T0iuZLDnp05fPtyI3Kd26Zdet1eHrL334o+S5HkGQdVWYiv0lJmhQCl3khnH/ED3dTgOQu89aDl8UO0PlmGKeBP61qu05ANds+bjF9/dNP2N7quG5ztuat5qum3a0pZ8DjwVH8v0SKVXQAj97ucjEzEJ9okphWWu9h4KXD0DqtDzrXDLSGwm19XNk9RengBmKTY78VD9/fTEDwQvnNgMt4DjJERfJK1DSV1wfe77lzROn/CY+KJH31TyrkTshe/+SdkVZMH85BkxfdSiayjVIeu2T2bFRh7Xs0oixSjmL6VG6BPFOSjLYiq/Wq7CHqNJTzOcPuGwgFHnSRKqoaiCiGolvulkm5xD/CvrlCsWjeGe8SuB+rOc6lqPZ9QPT7419pYxWd6K4tifyZSOiAXmU3Id4p/8LNmCPWc4F4u0u+KC/Fi78diw+t7j4iTOfdeBmnkgLdOployCfKfOk2XHmr8Ja4dfDCnCGEGgFY8/UzjsMh/jRaquzHINr9/hn+s1Dud/Do4WEgpWo2MBH6OssHhj4ecDYmgf7iXT0q3Cifzj1DfjwHo5bwOYNAnFc5fzm32+5LyCZ9P7/SUm+hNwYx/g3jYVTq92JMjaC9omLvUXB91elOjLzKtHN1RjOaZilUWjZojKao17xzs8Xg50U/Fkrf/tcpklm9EiFN/6rSqHU2zzd2L3J2WCoXz+pG5rV3ocFyvESmaKvQQzJVGp5E+Bz+QQRqLzJfz/f/VdGd5YUPigRbVHVq0E5qqZauhX6ym4DKXBnaatk27ryHEbfH1mXw9q42eKRPD7r6mPP0UFENl0R0w5+WZhfa5EcuAj7//q1bE+i5RzcZQXbCbUp8DJ+LSsd/qICCFufeHkHezxioM57ZE3sFIlweJY9VbLycoT25CoMzZZSLE0b4YfzPPphDIW/4s58ACZodL4FqS9si6JdFdZS6YPEVBa8bFo7msgMfubTNIoZjgcGwkpFmWPz78E8f74yeOZ+sapjqHLDkAoqPip+neD8YOoOgSFZxf5Jlid/b5bnlxH1Fc0TfGljiFt1liLL4jjJ5nw6/hDqFxZ9JPTzuIA8/vW1vGXzduf5HE1ZHM8zV7SZyrHcOD7IsZ04ciUxHsfJuDwbcwrjGPCouSgxTsd51c3EzwlgWRe/BwhLkl9MHcKXXoXyPSXONOYZFyU//OhekwD8CIySpPrbAPgxgHNXt0A1ZkZraRvUzmV8dpgCXn/pev+KPEgvOVwnzwTOeywlTCNMX5TUv5ZHUfdxKVJUl9LjQLyVXOQfKEV8bINuek2Kj59HvY50jehpCF7WPVm+D1GIuwPDpwqxPAgaVpVqWsHfcafxSWGkFkY3TKMkT3+AnvHyCiKcQW7kcI5dWJaFDZn0uCyvvqfu1lB+BR8vOPB2kHhj5F8YmLKsrqTjsLXvYHwVsGBzZ95MKt1UDRLv5fMDfe68dprIzbz0F1iLxVIMFRmtkgFlCd+XQZRk9x6LzXMgLgaB2IBbCWs9kRJfqbToQYrTvTfRU0bRtNg0nMVgmYLJMy7WSpV8tSk+dD9aRB5kfnefUM6rLRoqbPCl3EpcalQbs56Ab0X87c61EHlGXWF/QJx2JHQnBQC1yaxIfORkY4NIiKm5afLeWw5dePZpPzrHBcIPbnjnXgrtyeWwj4JvANqvVaDloK4rDZ0eECL9rQEjl6j1PC+qP0IpnuFqBwngTCNtlfADBV/7d3apYlyGAKW1y81gCCFFy6+hev8V1aY+0t8wm9PznRaBCWI9RdWKIA//GjHF9nwcEKD8It/Vmu6k/JCEjX2f9tS0Yjq/GoGSB0x66J93B5RCRmxlNF33Q7KcrC6iLmI/yBYTvjhwdMuPqNZur/GcalX4zyPY96TWjRMqpnvWpO3UAmAYMhYAc+77gyDRnEBLtfqaDdR+XOzGAFPRNvU5HiQK70z6pC+6B5N/GCvcI8eOQ5jI5bjFzCTAhnYZgObrkAfr7VjlA95QjAXuXLXY0JFhXWQhLhmKmGVTtOH8bkZdzHUaW/2zrj982AmsXXZdPWP5aXg5iwCYOblBgHQQLd3hMWRpMiRLgTMnpE5bOUjwWt+aR2ENNcm6gG7UsXg+0fw7op52ZHaMkeb3/SUaMyIji5PIKCZEGATH8FPru6ioi+HcSa79J4yJPF0Ap95/vPN4lt95QjynAOnaa+mrAZgcTReoBmI3pq3uA8CVX+6yJujm8jO32Se13Sc+EaSQudB57ZsnLg8RPjEtlnrDWNzsYw1OWmgi0Uy8nFan0f72ea6yqkrBdYynNVGYm4doJqpAWSbcbDsEFMSD8WRiG+fomGGmj2Vhi2uNu935wWFQbnavHmxFq094vY1CmKTPP3+yBUWPocei7VVe3SmZQCEDs8GMWcONMgHMkT1NGf+6lh899jO5GTZYteh23IylDGHd1T9TKDkWRc4WysghekX1dNEDkJWdeu6c/+gXgutu/s0gux1esJSgiXKPY3NpGIzPp7vzroi139Kk3iZW//qwMzboGsgsw4e0n9JWjZWegutE4RNzjcfHvBX971/FBh8ZXEt9iaV7dJ6rfG2Td9lf7ipg4GqHVzpKC+YXTLyTJpTFjBJfD5NEURip/5hOs5MdOCDIPqZJ0q2iLM/dPpnAv9RRZF8qfaEXS2sS53Hez9PZrbqqlyR4y4MuL0cSIfyHNzSlpaAdgusXZMsm2XKHZ0ap6QnysjzKPA9Pz05EvrzEexMksRs79vZq6FdqSNlGg8mPCCmMwDJv3HZSpfEJZPGYn6cVlhWjmHkh2imeyKeFVgFfPHa+2ZOgm5dJtWMV3i+vzPfJs5L2ZYQKZagJLxYTegKJabfxqIgbbH77aAvMckU2ZIVPUIZYyWSeNVdkU9Oq022i0s71+upfoJD1rs+UTwe/9xib3e8pj/ZdndL0buJyOHq1F2jc1m9hESAKq4TokjiHcriK122Fz9iKiQO/ZsyGRE0TtyxYnFR0ubCOXLYtqmhQtsT3NVoLUi9KK/W8VlAlWAiXDwhpbED2oq/aaX9Y/OSEGKUmPZ2DCam7YOKg8OYL1ATMVDSl83+DYLjHMCjL8Ltfqoln3pvbyNZPbJAmPjW/hhulDZ1h5lnq9EBhTNq+xOffsAiAwQxiBCpkzm7d6nxbDT8h7CwG2FgRRDXDejSIr9twkE0k0BzOZPQiKll8neTn4gNHVhgiCS4/9hkQXcy2HH6Bc57ryehwj1NpjYMuMM/cp0zj/f5S+3p82pmUictel2PRzEvPGUbmYKeWuupHGUaVUDBnWRHMXS79Kg/b93gvv2oud7bdW0wqqIDfd9gHP8UviFVlsv7T/fwb1b8M1BhAZVQmUP/6nEtQ7IGs2KmM2w8Rka+XjdirfBycHt06QUcxtXLK2JrKa5La1qDLtvmXHPuvbOHptoW97oP+Lq+5frYbGeO4grKFQyPOjT/rn50V/gf/d5y54Lg5eToBvqlBllGV5/9FU80PywJa8rpPYddGiJAlrgKhqMv+sM82OpsptvTwA75l60p+ykH+wMwgWEIf94R4pB4MHVjuiJoAYPQLC9a/CWQYjXMQy68Iki/vx6o0d989AVQe0uXBceCHh0u+/8Y4k+0j20Xo7iVXHCh+mj0Moi0vrG7FS8WoGJfcmBe4jKWUoLfYL8m6AABjZu+7Cqk1UV0zVuTQ1aB/YJo0D0cxzWvXxbBJQE90Z8G8OyPuxB8gABdwMShT4kHlVH8hBPVcCI/mzoQSrE732yeV1Ke9nrzxPrBSGSVB/spX/QDlhmjJMu2T5WT4X4XCwL4aVRTMZ5te/UKhj2lFNhsc5fqZv8ccYvgnXc2pZf1YMb93gPK//oFwFDhfZ0QU5dOA7Ejt/cQPQIofqQEV6z/lVSq+T6f3qyxm4OdA1Y+4Yqu75kbi6a2YFy8e6TYj2WlM9InS0xZBLSg6P1WujzSKCLRMcro4fdVUjFRHkqheVKtL4h8KlxOekWs+dPZkq32ZlgQ/ghnj1bklTkWl4QHPo02p2ZN8YfMQPv9A7WgapmKeLTDqW8mP44Td/JuguXntRRynGVMfIj3v4FW+Z7paxy8Rik7LR5MA0eu75NwHGS4fzue+o35MMCgAXY0Uzr/IF9wX/hzSYP+sn+b9ldPLrKtvpg510o7Hqjv2ud9NSk6TK9mGEr88giL4Mfbw2fzru3EPRzX+jN74hgjIYVWLfISxYg2jjawHPbfwXBFcQf4uC3A94aoEXGFWzqW0iVia97IpkgQuvcMo1EgJlJlrnFDxjENbvaNSNSe9NJRalIRWqN5HySKmCl7i5aa2fOuxomPhqOnF1ruhuUUJiEK088JoefWSDTDciq6qnCV2v4r98zn+m+SRsgRouOXTLnyp4AcyZee1qHnAyKWTuysj+92MjfPjDaX+oQ4l083jgxPvlV1BPLEQ/AmcryAWL39Llpvkp/WDag8RhLfZi51/oNO4+0LEyNANmKQYRSMgIaNzT8rNx7KOjAQZZiB98hzbnrtmKZDRDw69n8t7J3L2qtU54KYj1w2sMaQRtuFn4+DinCM2H/t6Ta7+snw59zMsB4z//eDyUwIo/wUZ17epO44oaNK4TFcGOL8lo4jMEMRr2Bj7okblc9AlDGmUvz8FCAgceYFz8dbySgHBxGtun3DhUzUX6FmqK8wzf++xEMupKfCZ5DPX5KbKrv3pSWnzeM17a42adGBpA8zmG//lbD0vz8tzkVqZ/lKU+HIud4L9SNOHJxU1eQl4C80DV/WCRZsk728bia3m6kaKxBc5u7jJ4aGiTYuiUPpi6BwXYwjk9e68sXmsJ7vZi5I2zL3DEdN1edrvWSilcG77595T9IMuItOLM0dBKr3xbV/sW11LaCk3zIREp+qq05K9/6lOdfdaMEIk9vaZAOadH5v3xl/mv7/U6IlONpeHQQNjVdBeIaqJhaRR2cX9BjMveMLv43G5vR3btweEi00m763jOKqjZtxOiWNZUbtcTsewpSGUwcz2+zdYn0kj8+KojSlFKnm1ubJpoyouRfMEtJ6Nsrup50TOENXkNYcXxsuAvVFGHLsKVGV+dU8IqeM2ujQom0CN5J9PBwxB/XqYmICnrwVZHIvN+lR2BfIHNfEyHK5TotSWRPfG5duBAcT2A2HciAy54TAswH+BBInnaxhe7CeOhOW4OB/ICqcixGlJHNlXMcM3lIRFvHzKRQyF10Lj5UqqOgi8i7V1jcjazMj7pXQDYXJkCNokjlb9lFhu7hXFfA/U6TjqWA9/LbEGR3nt6GmAW6ZAyg/BifXzXSk1G886qkmuCRlUXAx+egncKxa+DSwoeN5NADPNON2e+3Cr0dQJvzLbLGbtOHjkFSOVSC/QA4LJabgmQpernTX1jwPcn38CPFzMx5lOR6uNYuutPGDwIDnyycuTc6ocq6pcTgcFlO8dG8O/uCgu7nmWn6FbX/9OXYbVp+4u5BUeH0HKYbRbVHyiHBfFimrJ2KaICK1aAjlKQBgCsq2mOECFX/4a2D9x9pm14gXQxhSa9+ZNz2A/0l9UiCBVWwenEgU2Sa7TjyJmE2h7Pjdn6AGFS9i2gfP76zfcRtwjmDgMmvHRVv0gPG5x2ubDK3xQUZ2UjNk38AbwC0FuHg3nfL/POX4gJPouJU3heYpJBCGFNDr4H2rZ/dWdUx77Sa6ZMEtwhuE3wEZW0WncsKHiLDccxjDcGlLtBuHqfNblRuAW3srV/rnIMjeVk1d2PBq3GaeYv1uDcaAW8burfZeTvLf8RbCdPIN+HgyhsNxwxUKKH2WBCq4sGdETB46p9sWvjVfFv9pd6SNpm1+5YmomBsPfp+9cG8y2pVk0MabxDFmZ2fXXMYETZ013lvZOFmPBdXal4uqao5PXOWrTq5wx0R4AXGKI2hO4wNbvdyP3pK0CCEL44QVZdLrHEunIE7oII0+JtOH6/lXfuEce5bYjk3m99uGnIxkC+LN0gGcjRFGSXACxlYmUXGcpCTdO1eRT954cIU6zwc7j6mr9Px9FWrPDd32nit+FIM37qb8ZPs9ple1TrToaT57kZxJmloO+vwGSOGaaGwriKkvppHzefIptpa3yucByX96Fi2JEUbcsafy0cRfX+no1VY2vvv9GK8VapqEiKMOirEi6ad/nKIXi7ZdxODZPbXxFvZ6aWDkJSlDlq1legAGoSI+XLgDGS7+KUqXQVWYiSBFG7Ga9tOYZ1ABRrtN5hdepTr14HsWpYJEiIuerdgdinZWdDHfBHVJRFSXww4W6ZL1DF7CfPLvvslw2F2QZ0EISELLWccH9rP2P+VoTyYUM7+qhrW3eCpv1SEl8p+zUT7N40QQnT9q5uo9LaHNoIA6+nhGf97qYf0zFjT3TGH7hevCz40yTCM6TYl/WGpVP+WSWNPF3I+qExeb6eybsFGqXYOWDoL1O6FXDFv2ejEJVTG01SxVxFNXUkxSDWUhXTmlNjcbUEEUy6lXc1Asvh5lZLxGAae+/xKCWpMhdztkMzmEs4KenqRLUiR5ZwJSodvBfQSSKW/7KUhnM2iPyml7Wy1YikS1HZjTVcAa3XG9t7ZcSzL0Lep4WLb3Iv/Trq/FGtsCxf1HKJDHdRvHsZb9rQDJeAXASBrUSvUTE390/oWds29k+mkTL53ZgMx4lT2l6QPMZWge86EJhYkuju1yUxf18+34x+VURu4q0GUi92PLycuBtXiFYcUS0h0MG0fGQpkgYe/GzONeVBbqmzADSfKgfT0MTlWvXQOIvH5F8Bm9oTW0zdwaKiBThai8Y1prspLsridQvIHO235dce3n6N2+btNUrUMtGe20JX4oBCEAy1gdmTvfjQEjPfTrMrZ/MXwUwUEreE4SAdaE81Xif6Rh4nduH3PjwUqkgroCd9fyUp/45OeYRWPtmap9a/72xgx6GzP7OBrN7S4yqGaSiKEYFa4cC5nPAvzGPXqZ4ftkDhKoKGBc5WfYYfgFiPkQCj3WSlTwLbaDxUqUiqxDKtM/0hmIqd8ubPVLpxHqtJmP7g5W+Wsa2B4oeT+WENOt0EzMrUVe1Z0H9lb09kT+O4yRj24/gqPRzf0YbhyQJ9r6BXY6Zhpx6iax2ReT6MRaByLQ3kstRAZk+dJbfXGDl7JFyIyC4xNXc0VCofZpguK3Ej6hToPqB+K5mMNbfje2f3UHn+OM29lgtqGms0x5dkeUcK0TvxrIODedRJ2vel6chH4EUOQ+Tw8+i/8r3u3WSfs5OOXRL0nSiScBoSNIc56Eo/hSdLNjMDN3dJtabJOZpFayPJRvz71P9jqK4Xv/JgVyCxqjUwtdUt5VriS5/bPfp8kjVFjA7YIcXajTYb3dEkwp0CefDeM72Q24gdu5I1vtJAidNgeWfwIKAy8daGDUDs51J2bqBKxx+87pCRROABCf/AWjBfK8pL0BAQUeKbDwk4K9T219VAzoaFb1BpiQ2C9To++S7pOcefnwkj21GR/i+DDDOqq7KM5QzV76QXnfGxQkTDyLDH65jGOVzqoI2LIT/7eq+h/uGh+mp8Sy4CNnIPwanqzw2VTt+SvN2rXx2AxueXvCrRjgrB1f84EtWjE0hOCcS6nlcsFDwNy8SvOrZBacRu/YFoiVSwYiFEj9e+WV4rFySOiP30vUt3/wbpi+Ln/zYQMz2Fn3Y7PS9KClFCTzNpd+v4tevQqatpYJR5WfzrJn6A6rC551Aylza+Eli8qxBqv8Igz3OM+mBOaCKmWT5cDbjl5jPj7rB/Dl+MCUTH9cPq50v/ka+xUb5N5GcJL8MVt76k/OtKFQNORHjvOb5wMrlroQXRWkJPH6rR4aVjMUupPxeLWd3tgNu5YSxG8+AWW3UpCasI4O8jAhzjMK/V+vccb/4lyfgD8SeoNLcgwDlH98Xt10wxn//KcqIePx859HuJM2+PzfL6XVgZCBaEIAQwpQLD5HqHRySNiEPXu8iuROx0k0IO/zXLLp14vukj+DoBJpZRoOhF5o3TTUzj7M8IBqyINnOTZZlneHvxw7PuhLdKYISbn1QI1nzgQHiykwuAIezMx3fWx6Tmw9O69tQd7Um0pZ8JvnICKf2bKB407PEkv1l2Yl/j7Xkzeko9VEQf0A4e3MkOYTTIBv+zogFZyQ3Td0PbYHt4ekL6ZP+Zmqqa57aFWv8GYlxnoPLyyl4riJ1m21ESl88ffGvJeFMwlVGcOwc5U7W1tfFqAK8WdilY39bMwZeezLcagKfJCtnVI6Xsn3kiF5H8Qucoc24MLsGDfWfVYEehE/1GYZHoirNZzbry0mRkyguNG/gEVDhBm6tKKjyIX563leITvoFGXlHAR5Inv8Gd6TWWfJTd5fwyX349XZWzxzHfoA+BX1Nc9x1SAwtnzQGI7CnT4WIB2jKsl/FRX5eb/jMico1PCSAxhdG4CBuaBxovQ/fFNr+AaUqfEGuc7n3NazvFklQfxUfWY7jH4QoxLTbp5PHMUiA8s9LB81PCkK7vsHYPhHeCcMZT2IgQh8pLaIXWVQ3rW+QjsKcIdIyDOdW1yApbQ6F9pAQk29VDYjnja7pqGeHWz3yQK2Bhwscq+F7TUGM8SXqEXk+W/7f2PM4/MtDbEiVHPuL6hKjNCdKHoViEMlxw3slDDFug0x9Z/ixO5DP1PQlPFFIzsJCbSGAmnPGNIE4BmElr0OMqE2bbnPkX9ziXIjdiC+6YqB4Ck8FveS/SG538ZElNLp8gSS5Mi3BQTTv0cA+ID50Exy2o2tUlvlH5sUXoqHyLFUVV6o/0ez8ClKG9CcU/wax6uXU8ocx7Cmxz/j7N9ufVees/RI9hrjiZv6xkwC2qAale3Yh4k5rZ4KGHlFz1TroNB9PCXp9nfl7sBjxq8gx1Q7Vba04JfPna7/+TuXLgbDR96v/xWOBYxgLzGCi0yVMW7n6Fs/sj9W9PMZ9+Kz/CfV7SDIjTa+WoHD0g8HQ1y0d1LKMTuA4urHAyRnFi64gXs7r2XzkuGUr6ShUhWqq+X+LLec8hj/YMphalqbS9rTb8N/kjv33fJ90oKdpmV9FIyobPsOr07xvZOhEC2XGqoFR9ZVb4IoQodPje8gQGINkMy8PGIOLcw5mQ1qoGNxynErcyDVy92knAc+gmLY+sP7LJwIEBCtml3A58eMX3emC/kU6gFaq8/wbctLTDCBi5HpYp07zVUVNZ7H0a6dVw3BB/c9OUSYF4bGAOOKf8ZPYmWFUL/JstlpZnIy3Ozcf0f5k3VNXzXtYXTFyRjUZ6k8Apruv5bNbpoUhE+50iqQAd4uoILnn60zhBGc3yWB/y1Bec1NMrXu+hKRplXngQYrTEr7c+6nsdjZnpJOHQeStfpQYg+Ok/WEUOReZUqzOwTQPC+9q2L0VT2cXpHI147LUsqV7c/3ba3Y8DH4qSJNyN4aQ7e+XpdIaAui/ebhLuBjvsaeD7xs4zJqh+a2xWKGqlEwbo6qB6fNhrZbnlQQGgo8aQtTzpClOxluVv+7xLdQvnpBf+og/67eDaAlIRAhDHztC5Q37fjtduPBAWM5E0X64nShb9LcrojiQEXj1C5LtRQrlpugINbLK4HeJg0ryk+UkE0LZ3L7tlvODMgl+NQiw0t9xHJqg+HJ5k/arVfyBQZQ0LclifL69+cgIsTsiQE4Etom0VX7aSn6J1Rp1BA58QTjSaIvaX2oPgBGNSCKm/UakuRigukizyVp0mNXd73NrB7wuorB6myg86ZJZEBE6fTuJ1lFJp86zhFW2EW9P7wEb1C1w7hAbxxd5DpjI/ef6TwGjPjm44QvYcHwn7o0Yagx9XpzAYNAJzGcIHf3EJUlDc4P9H0Ki1Z56l86fXZmFtlw6SOpMkfPD5OjL4kJzFUeceWTPxGVtJ5UPPE00za9hIcPTXQInddNrNZVJM2APNA8iZzgo8cdJf/vF27xnOPIjQQghSbavBsEJtIauAUryjM9ZX9pGXh9GFRa4KwpjQOwLZHtucLfGnoEfmZi+N4eDbrJaHl/Qhg53HMgF1X/bR/frrpgmMN9e87z6pUmAZMz8xXYVWBV912oT/lXPgLNBzhCETg5iOAZFFD8rNi8PYrufdPuV5JrJ7hbQjrHdmSLInzWsitahvf1z2tkCVij/+A7Jj2E7QIy5g7ucNWjWOvj2rG5S5o9V8yDrlXv1i7H0tpf6clzVi7my6kStKbjihg4+SDuOKW3ofR/mpFfAGhKq5BeEfvl7Af97DIBH2sFCIhF4bnCaW7LJ7j7QZuSXXd1B+UEm2B3iW2r5bRfLASNIK4aHPw04MOnHLPQ/Jsd7Zkv0rVjRNDNjCjT/7VD4U5UgIub9rYfD/pZmfRyEEJr39nQx8ddu+Pnr2GjO8hl3X0fGWu8K4zqhloiMLn0vJCCO0FpQFb7ZEPH1B3W64BU3pfznTDr+4uRlfl/9RuPmy9xB8oOjreMjC374JGCPeupcjx6EF6yVx7DvfaSWq+yFRpos5GIPwO8RNwhal3/tSyN8Fd4eON/v+drR35rS9GorgPyi+MSw9HjAf0xDeYMldHQD7Tka4xqNfvLULCZAJZwnWCB87WyjA5sBJAvsTsf1DgNSqfnK31jPRVs+ed7CJGX41MfSnyutEGR2Hon4baIR8HxavUYVDETjyaPZn7/1sgtYI8UHlnkwkNl0ZSNPn70JXhlVK5YewI76ogTlOt8W+jIMDzyxxsSKZNqoJOW2QRp4UOQI87GNM08sNP3F3ZaNtQ3FnAN/8RxGyjY/yb9dGd3JAQcAnvrz118/wCGBEF/E/Zsc0j8kgc7pd9cEcmv8DE8tqpK5O/UC2OCO5UJp6qj9/7wx9NDrGqm8W8zOdIFjChuF86Q7Q9JyLK0tNEtJLLCVSJtJccuIwgVuBxHzBNoLoiSnQm2P/Bv+BQGLEkRjbmDLwBEZkJ5BaoGKYV4sAI8nl95VkS3k+cuLDKu5fDwydOTTNr21M8g2CrV3Ia9/5j+/qBYs8IfG6qJqUMfMga3Dboe19w/QDrnVxzpCGp91Yo6EYRBZk8thBeOy6df7C8IVn/YKTAkZ+gawzaa/CQIYPkagrlLBOUTEJt5UH6ggJ2A3IGfyCg0MvrBi3armK5Lr8ANb3BYaZPTEVFy3Fi3Qzno9Vtd5Fr7wBSBPqVGUAYNoD7hRSiN0d4h850zcfqArIUdNuA6L7jcmphbjfzNllhKH/2XAA0wlJsCh6CEGE50R/yJ8ojp1AhOUj8DpHrSzk8wooUffe4i29HseE40cTZ2/KOjZUC5FtpXy1ftX42CFMVWcO9Dw1OjicGRxwlzya++bWm8ZwgfZaRrIfc5rstsWAUb40CERFoB8IgRDlrqy4wEM1FG7IMdPzB7i0z4YiBkgAAFRTiyhuMPQjixojgX3G/S3gXu98MTP7crlb6A1VA4lVyvnaMBmO+Kfk7W9KaAvxX5PA5Ufdh+QAtESYwCVE8MaEvCZ33Z4v3alSgkDXIGOz8g9Ssbr///C0e8XkjiHL6a44jz5otqZWS3rhRfbrRp7sZGPXluV/Wqj3PHGC+OvT2GyK0ySMDIYBqy2Y0Kgg8Mokl8PTeW18L7NSpqAq5XKUV7alyGK6NowIIUQvyeR2MdfZAPk6MQ9IGKQGC323abJKJOwRwDX5pvJsPc74L7jmx/DmA4l7bYM/IGm5bqVIPhe+x7ofAQK9oA1sBLSur9xqY1axIt9Iu4KYqrsBwpWml+u97FQnOfJAK57/LMfIFc1v7cSZFGMU5z/PZW6z6AAkCGr0Bj/eLinGyj4M7TyOwhIfzkyS9ac3owF5BUQZSUNmGz2+mxOmZwSxkHQF0+3J70m3yeJ2pWAjB6q1ou4iAQqOJpyL4PPE7l6lLMUsrk0xCUJBUximftw6Alouzm1SMqP48MjhFNuJalpr+eOSCmtFos+jqBdFVFfyVrA1BLWIzoLpu7TlCbbMm5NodrPCphagUG/iBxqbVrlxutk/6vZvPQ16s/D0pEkgKAlWKuK7mYIKpjB0Z/7Fjx+RRg9uwn4gabBfrvg4TJpOJPSovedtI/o1/bCUXyJky5HyTE85QAV/7Em1hI63D8LzDWykqlsCIngQGJ3H5/LoU4s3BV/eqUjTFAJW0IFfDO3nKqxepHzLzYRMu0A7OHHIi53KOSmQX7wxEEXZS2hM7H1F+SpTJYRh4+o5SO9liqN1pr8ck3MqVesiV+R85QJqLch6McUQ898DEVzup/JbKnKHxlA4dTPD/tOXels6+ucseY4etlsYCzLc0+OyuW3+Lso4K5hFEtiv5yfKFRq8zCJamDuuF7s5HnaBre1mPf624NWFprB6fe+ZPKcxIhAaQxBi20+IK4R68eHdQ52jrjV5rzjPsB8Llqa1ZgxKCH0cSGfWHsZWVi6cOeiH6YoKEm3k6/RPU3TH8MahGgSMDc9nBoeRQCjABvjML0Us/K+s5xNrQlNNa5SKVSVr6SglE/Q5zChl599O67wol4qHf5t2xQEqk8NnCWwbrl8AmCynFdstU8xXitTJYcWOEXR1viqjL5qCTMST6+sj6seyltBwojaN4CX4Qg06IZvvY5+YbOxf6tJ4Zzsg+xvW1JQVZ2U9DmkRjMM9nculPFKoh1/lbQTfeDfJ2M9NqSR7/DoTq87Vm6a7eB/f9/VclTI/yjj/2OWvUFZ6u5utptlxZ99Hdk023hVVRMlsZvHMRZ9CBxD6V913rn6b68mh4T4bVU+7VLES6GiH2daS8YQFA/ILjdlxDkxjz/GjQFucWlzL4ngGICNQc/s61QfwvT7WRN7tatQNQqe5s7y8zAumdrtvUtUDXPLRV+vQVCAnvFWamZ+D3aiLYxSUyFFw/yF2FO99r2yvjrDPDhKEZ5jVy1NTf2FoGmfe7HERzcQpRtFoT3XhEv26NWPkm5pNdsAaiPp1zTo1OhoA5Izugs5a2xQlEKmqA3VsCiBboedGQTNdoM2ei7Mupraw2qqoTepsXFydHXBKL4RY1UiQ2/C9vuQo88wFsrZSRdE1StLpOl15iWW+IbT7o0A9AggA1wPcfyCzCjlopWkiIUmjJ30XgN0pCwO1OQwlDb5yfsRGkW1FHic8fhokrWeMAAur0uDNRRb+UT8OWm4o9ZOeyhhvziG2lRHG4voaXdNUVRFcT1n+RYQN44vwm5Ov2p+A6zX5QXKOI6NwexGtYFWWseVjmJ0h395kZuaELXU8bUUqP5Rfxrh5FDmaseVM7kW5nmwxapxfvYi25tnK/sgmK3Q/mhGjKgR8n1EuotP20oizVQyhVG4RdCTGZvrS+N2GuT3eIODf9iYPHKODck2de8nyq2MGBsEK+pd1Cj6lEyNKriOoZ9FZhhNK275NVMf9OFG06JcPW/eUcN6qXbrOwAOemHXMvWTIlLZXAc0hjK8quAsDOxRwGT8Vc3wZP0X89ETBcZ+HblpFFyzhM2DaEfZlDzM/RgQvQyNLSUMpai0FQaOzemWyOezl+eAmMAk1IMiXzCv3WwbMfaWRQZ6WdbyNzBFcVBj2SstNl5hYbMyQ1G8XMc5eZ2TIx00SloK2DuuBV4i+6vrtmPNbg2XfthSfLmlzsyq69WdrdTE8uE+njh4csUJQvF9xmQQfnD7wgwj+k6+9gb3qWU/AWyRoZ04bCTKT2ieWRhdckRF9hVW0/lhVzl7jHQ7H4ksjyoEMJwPRbFAhHVpSdXBS/SlaJ5eTTzxEa+97IrV43oWhJeBsv6iTdxDkiKBM3xOYb3j2MpCfAf0ct04sTp1WijMaPY0x4mkcTQW4jqe+1GeR8hacnvp+1V9LzEjMoIsq4apUdNqbxoEN4E/GjhT9yV0nd9zuYHEX+sbTNoNkHBKalBC5WyXRzFoa1GoQIFV7/z+14Ka/Tpm19O07cUsPTolFD8pZqO/Sy7TU1heSXw5Dl4H39mSPut3c0HFYykoWwTx8J81Nasx+jM1hzDINASpfkQQ264wzyiCcTGLxDQcxPAUQQWcQGF08wqyR1DSmKAxJIdTx4098V7KZ0JmMqi2Z8iaeEhQ/uqLAXD/BZ8+LHn28J7luKEyHIE5almVMjIIPI62kkvC7tA7Hz337knv3kPjHllXZNtpPSHefc6ucOPuKYn5cU3NU+JF9T8q+RItN4YGFDEX2CcWdCV8w73DMGf56pZaWm6RcTx64ilOojgl8i6M/JkKFRoHN/NLn+rqAWS9MxGdMs6ef/kvAC23J2Qgo40JqCPXVtCMyRz+kG4o/xpDPCK7eI+RM0Qh7+gb2qZYXweTPeOobyh2TfTUskLsKfU48xhP0e/3alGG8fmqqbc+eQI3QbsHz0T9gLbETLANk85vEYTnx1/qKqMkvo607Mz14CP+7fKo9Tv/Rkn70hX5ZqZVddXrwaszZyq6EpZYov2FpNtJ5BqHo6Wechr7ZQ+xni3f+ZOu/0VdEiX+20Wjo1Z/QAGraPXfmonyuLdJEY1DeX1FTjEiRy/2QQ1S1IoJp/nVwGETHLwCPr4PVfiLWlT3TXzHmNBdcvsgcQakAALkU1uGxu/eMhDqmb/x3fQjipCE/luhTaCoGnVgCduoZMSF2nbXrlhTDdps0UaSuP7MLS3qv07fcLTCOuvBxhmbfphh5Mezca3HcD+PdiwyoLrD7uqjoireom9KoCRQgS3bfr18y9/iIDbpqdg6SWd7eNXHzvvjwg81fH6ZKdGUwC5zs2do/3GKIUUYdPoQDrba3T3xAcdk0yI/EIGDGK5HE8g9DBBisC/7kPh2iaG/oEyop9X4WXKklD97IjUWMxMrNg6HmGzFBlIBPfpnrdn7mZbStBR6+lVaKVsvo+OTNOFQKCazLz2VoclmY3kI5KqgsRtDdTjiJ/FRf1gCfs/QIo22GNyd5ybv6u8/RtrIgCe0I7uh6E1UiMZhmcWP2lFWlEE1mfiKQ+2mFfIE6JGHgmBnNCXXNUiM0/14bbbCN5nTV6bd4eihGLOQJpL+1BoZBYenP58Ve+RnHfoDnQOdSE0EtDgA0bXDseMbkCPa8ePwd9A0CffUL8f4Umn72AfPqhd9kB7aEDYOVGyVPk6cFU4JlmDISsVEy5e6WKWSRZrSqeXlEtZC4ywII4AuFl79tTteC7pPbWwZGxL6MrUqm+gitCzcTnapOrhlfbHXzreoXV+LtISyXcrIs8TfIyr9e2XSpTnRw6d3Q5+M1JawVYW5W1zs/fCe3B2ywTEknXvG6o7vyzZA8Lg4gjmcatEHGhwu3FRVJi5P0n3p4QB56u1gxyVOxfY0DN4np+hoqqy2EuJpuc/BJBiP5F9xZNMQwWLwNmi3IrnphQUI8p2HC3viWtXraDY79qJmnSCxCMpUaIFismqpEfWXbdt43mOsejQ9MxRDcZAkY6R/ztPtTAwjxYnMqqOGof9WLa3OzlA0tVoNHA1OB8+3eR+ywnC+76eiJAaSb4O8Th/IPbtQ3bqyQVsjmkP3uzBPbnpyih5CkWq/dqPGMU1zU/Jtf2VwJaWCXnAnYeQlvM4E1Sjt4CoU+E3BcILvr7G/Tw/7ny/PV6/L3ChO7CwdEfmGhDMf6og4YCH7CQwtj4xVFyFekC1hUpSGsSSdurhM+tqycndO+rO5aVHbK2N3hnl10aICrNKgzwTwK1Y8opUTxWoKtU+EdM6yv1zHxoQRNrZIL2JJCAOlXIWFYuaCz93rEyJmR9E/Zi7ROUk/+NoQ39wni+3SKdWa3I6PoK+G09EG8AssCKdlBZ6M6eNr8I4viSrgSTpkDx/4IbLYo81TzKsDUiaLB3mDlo+4t6lw8mh57/jWj/uU98+JoioXgOtZ5RIj+bsHvSdHenBgXS+D5dGrEtexElkjtWwUTG3/3czrj//SKBJ6VA26cC3jWgSDZk31njVCDFQlbYulSKfHSEHAVdPX8k6vlF3CloZ+VqzOk3lqbyYf44ZbazjVi8NActfSn+RXTKNK7swqRUvc7TTdw6pmcOY48telIP1tEAJxuQ/qpob8WSAdk+9iBHHNeQ5dxdFz+PIMRrPyQCvA5YhV7Jeipudjco7a/yPqKpYl1aLs1/QclyGZQOLuM9zd+frm3HodPXkR9aKS4hy2rLU1XJnnua77giY74PC1ruaXu6716psWs3zW75wMP/dXwhyqKhgra17rO/Yr2aopvmzXk3QWfWxVZdKclXei++sziYoD5f8aD8m1RpNsPjW6K/6W3ZdV5uQpc+FfP03ZwxdZgXtvEUazPwC69CxbNfPSO4PdUsnY+sCMKpaj6cmjuYrnFsiAKy+eotu/9r694UJGsR0N3ASsoR16pfFiLJ4wLC6hnlF2GaXSh7kwqpIyfv+NIP7bM4/U1B5VlWxCmtrckWPj5Pp8SiGVv95CyNmcL++LJPNUrljI8l+A1PHTLrVVwg1zF9LX9G+ixdx0wMa/Pm1vxRK7wvAsZuVKpgrlRdBqW3IZyZ2F5eucVv1+6tkUGctZxZeuuSYzYMxZlp8C9mursb529nUwUdF/bvfzx0ggaEc6n7nL/eprTmcKakvpVpnTl5PxkKtKmSmW7EvBuo5dRyZKV9skLmv38BOxZ+WycqAf1R0I46rmqZc7dKbqRWMJexqlx91dZIiRiSwTl69HCIgqVKmq81VKpUvWAgyDRynh9hCoO1gCw8Ydr3BRl94IZnU1cZLzFxQwXxSj66EInGNgrNMDYbM5fr4hv/2gzKRoKo015PkrbIq1mEvILyxCfU4R2J1apZ37WXVEC4mDtABa4Pnx8ww7RYOaLFbZHdZhmFGNLKCAOs/Xmin5aQSX4Gn5Qv+rnSKv6zzj4ReWn5vFWRw4L8xTboI6x2MsUmCKYoOqRWLw/OqprLIWAyQSMxDNBo6W4lTW8zoj2O1R9BpV1ZAVLSkIxGLJsG1rcxY3Ccs5gXHupRDEOWoss3RTAxbPIFbck2vGUfgbefiV+YGLR9tav7tVL1MfhYIY/E0A7xthUOdvy+IUEwGFGIVGNM8ZQqOcJg8wE5Unb5gCYM0pxRSmsQxCjPtvwTk3XiiiEvfN2goniZP7/Xl17Vhyuw6oqhZwiKYRjhd0Bo4bBJ+ftcvM1NMKXeXuQg5d95rE/HA0/6/aE9+hQI8fmQwRGCWJgVLcC8NjMcWxCMoR6GkHNiZxnzPvAxCXYvzRx2CgAwge2hnCm9/a/rnNozmgWt/2X72IAM5ABGoGIVTmUPql49B/8IOPBvfJk4NlPf4hivWvmXg6nIXe8qbFvzfqekvwGy4A0m6eD6kUXcOoguqrgOJhRcGANV2pdpDOy14QVgifSzetoSamDvOWskm9BJRx8vTXV5qKk0yOA9Fes/twE+d69TB9A5X+kUZMZwc8IzykjbSoXHP+ohfxL0qBR3zW9nWvZLVpqztsswtvcnnZVYuxX6wMT2D2oli+iFjk7PJR8087auH3UWf/Y0ZljJsMXK8N43xENYyWZo4vjKutRdVU/QWU4cnPcc3pgepy0Jw4+avFSeVijjL302oLSccDga5ItAuqPnNlcI/1vC/4d7SZias+ctnHoeK7rkkW7HVh/VCEfJ7/9bpF6oNNj8xorZ0/CwUBP3AEw3qOe1Hkik9qOiFp9Fl2Wa7A1Ln2AcRA+4t9YDmLUCA3L0h0EhCt9nWFTFZHxHH7T5qMfR12IAboj1LENWr+WqPzHCQRgRYRf4vUfwxY5c5n+zwVD0QYsHBuB1HVZA41+KZHK0I8l9O73IXXPO2rB5gV+lctCCJNCv+XqcrvRiNiUlBn8y9FoENG0nUkimKcofgGuY/zHvvNJVBQoS9bFRSXUt/rHE1liAbEyIulPiNY3iCRj1eZ+sF0zGksKhOgiyEqoQAIBU1tQejYH71DoacdfiuvfWXahekwLGVytQnOwbCcczYXc4OwgznWxnex069mCVLKDUjvH1c8YdhzS/l7h3uKKa7mGT+E9OyM3H7Ea/1KSlyF0gEZA3NushUe11Dx4sv+uPC26HpSIUlTY3z50UE/SJdlQ6pLqloTJUbbJfzb1cLd0xXKPivPAf+1NEx/x5reuA4TQS5TKp36sKna/mqBOwn5Fzdy3fuJe7WoE35OptfbsuOlXpV40118VUfUn5RaxodfnjIXKhC+b/bf8uO/Nv8Z3//ULxGLFM09IGZEHAFqYFTRIpDZ2X6eQgWvjsbdAQqM1S38G1MLqhOg/YuuC417Whq7XQ2cFbZrhYsQWAhq5D6vik/sk/PKGdZIWjQjyAwVPa22aatBOBYr4FkSEeSlliTLNGmLEfOFb+EESa1381pUwOz4yAuWCtTFXM9FoMW3UmgcuoL+ibhuzSR/VpzVOIbDOIBdQoVhOAKYStMhMfzE+dFegAFXtwvoI4L3SqakIjBCvIvnqHSa74LgS0V6YQzP4axyMqDDEGa0Mma3Un4ZUx5SwzHwasmKAWbv196CKri/suBL22hYXMwsu1r2xWnxKIhACj8WDfKlMgn2evDA8iF8kq1//QznSc/mkrufe61fF/eUsHss1/C6Ndy4OTzyk79lCfLqHCb5QseagaUP5HXRHIGf87A60leqR2lc3tr5MxMXBNVETYC9j4S4XEA48bf2SEc26iB3rThoo5lMcj+ONmrlIXl5WONombLbHALfVT5jwFoQ0TJzKJWY8MjcPq/FJ9M6YjOqESZN0HS0o96EcZ7pzYH2nKgd7TVXPPckLi8k5nX5aWH8BP2HF9Sf2y8ykGoeCbDp7z5CsLnuc/xNugtUUUqg45hBMC1Es0JDbF5s90krUsOSJT68aCqO1c+1uwZ6uINclpr3zIccP+CgMZBD5Hi0zsqzPASR3p3+a2HGQbvqgeK91TreRj7EdVQvyFbQWL7oNcnui0BQA8qFIDiAU+H3X5B8OG6uyfU1qldCehlGx5BRfGsKT9MULh60V91OolnL/1AyBmY2+tk+RESkJ6+HPT/tIn5DSHVfnHNGpdCBmtlkI7aTkrajKWkSm58BHk76J8I7b1ZXgIIE8/GKC7iSvy6EVTcOdGjAjkV+72VcGDcoMeS/eVhLtYL0EUaCbCkYWPv5a+74C3h75mko9AWQceTSl2JiwGwRuyP14annpuYwKuNwn5r56Kb5PFlbk3Biw+HE5VDyElblSy5R21te1zoAyeBOvv5bY/OTwKAloHM02RMN+pwXIZL2uVM8nv1tDPz4pPgy8M/I3icHmfNEmEzdFS3Xwh6UVD0+lnX5m93y772xF2rfjOqOSbJpMavCph+ZUSWJL+ixzSBQHnyZzq84+m3Up7EsZd961CtgguZIPZIdldmDFP7azoMytlLnRTaxQYogN/RX7+N0eyZ6dR+tU+1/tsDNL7JmQYW02eSz95GZH3FFV6FytulISSl4ADTezfflqyJ/gmzwR6/muDtjo2Tx89uZxVJ2f1s1nXH9iZh+HLtug69H4Nn64pT78eZDzOC/qh9YLnI/0QaH5r31bwxwEWh32R+v73yekBu6eeMbHkuLXacPco7tBmba15srSqJWBKhpxILhwcsUmYStCK9tAsiA00kLw9NRwq5RO1Qf9BsQ4S9ybjctuQ5AdghCHm7RyAlYB4IwyoUkP9GkOuyC9LH7SgOqybTouPFwoO5SQGu71am8Z/CrbUBe54bsdmxXimiSaZrUP8+hSxKVqmRlCgJPPerfhvYNy9YFPs+2aj+f4fi7hz41jAIAamegYurlGuwd/1WRDxF7wTE9huuclftxdtwS2H6KT0T9IfQA5k8P4AyffzB0aZu6ToG9jOw7u424wVXmh//VNsz/iWHgoih5WCoWkiKMLnhMOWXg6SeoqGqcuYG+5wXqHs5LEno7QG53MALcgAbvs4DJ6rx65tXrAazkS0fREFf4h2t5xBdOZnqFUBMpUQKOUT4H8iPuURRoSdp9/9bCH0/adov02Yt0ilr1r/br95U5/dT7E4Y6xhJX8RiNjiUtjup5I+N+5arLIY3/VnUt9Y8rd0+w65K3dOOBD1Nd+W0BnNWhIsO5/LfowXlQ9uILQhEVpVpPKsFAOUjTRGLZw8mCRRg913j0r/gFZLaDmQVjbISDl0+DiEZ4JLpbTeEazTNqAQwbp8eCeknCjeDZBYawQ3CDpbC5/ZpuDj3cOciiYDp9G+icsLTFv+hK0G5lI2kGXDvk83iYyZh8JxEvD9ZuLZ9VGsF7KTFurO3O20ie0e83pr0XRGBXsl4pbfxiI1sNGkjkRZvDcTnb1jwWssgR5yloSS68ksEFEPvPUQQNAA+BVNC2oXx0MS2A3v5tRdp/EjB6ObXlYoXYsgTHW+Vb7gRmgQB4NBjaTN/4lGFUASJN5Q5baQxtDG7OQIFi/JmopP+U4yxVZNEVUTGkSN45mtlMFn1nvZUnhLmqrHAdEn6AkAZ8SBhBxZw+ZIxsa7JtAPV0vAloC3GfBvtSSbh+UElLuhooBze0ZtKHt4OQ0pnff3kJM4bUiIyu+YP4s7WVxBgm85oU+GZRiskwxuy2Cl+3zNbtjIl7Vbgz6ZU+TnA2ry2t2JrNXyu1fKWobMHE9vZ8GhTO4GEU+bJdnXrl7HtOkvJk3setbP1S87DCACXimurzPXUZSdpnJg1AEMtBNtUJ91znWv5WQdiNAzyO5kIyOHS3EbRO/QnXJ+2FhGwSsRwmLciGQTXAl6QH7O42xQBff3oM7UaXpkMOXYDM2N9YRE1PrFho8oTCc0rO+7m2IzAK3ejRFQX9qTwbfR+KUEz02HZYKvL5e1PAP2hOoVwQ5Mxf6EwdXVXvGyrS47bXeSmenXRSQHcEhLqfuByTkGH03xg0SdVmKcpXEdbC/9YpfORGS5bA/ZULfCVZ8reAoV1yat/zRK/vpMu4/o+0Nrxmc6lmTr8GKDShX45poNuG/KVysqybWfIgsH3fZmDyC1qdPJdIio0dadknXzq6JZLK03DVZcEA75ADvVT5QM2l6MEXAEm6fYWrMVLkNSd2GVjJh7S3PAvqRCEz7P0dcP/fpmZNjDw4SLGSTaBxW2dGNpJQaZuFTkdMs92BAQsicJgeFQrIFWxTptGHhSgDxp5US3pNGblEAQpBSXdYKOlmZtFeERv0ATJnd2GkMzkaWvPHV/MfqH+IC36PCCQJ03ZmaFVLv44A6NCGsqXojjzzlIY7d3uUP4T6/WRN8mIL5PTQy+Lgk2MYXkX572TaKLrNbj3N0RBYomFl/P6lHk9q43lZH51l4h8IS7U9ITLzDd1+K9VJJMraE7DNx3K0jklDmZeXQYcsyDcOvJ/lrXSVYryHzJ3w7DBY/aBLV86LkSLIbBUOvOGy4qDm7Ldk/bPpKOt92jnjJPTl6ijxJFSGOw0JmGpvM9LH/qs10+m8ozQiwoziQ5FV89fgWRR7UiBQPExJFhc9dHup1t52dQZq+AFbZz5qYdCP89cN+VLYo3gBcWRyOKVrVyqGHpJuvhLM+EWjgSKVRNSgeh38YGvxN1BoBdCzeAjSgt9JOyHUdP71zIE0zQ75lnAU92nxmkxOBypu5JGRzAHjNPG3Mkl/FtxXtot+cqMRjuvBs1wtaq9G/yafNa4muHnpscQDUuRx+ks0wRFwjORlQZiBCXXK8uk/506nsPjblGGmRRghxscddjlGFxeodvuoGLEuss+ftSqw1YkllP5jU+hgQcGsft99VMoOagNCtiqGv2/fFBccJ6Ljwg7CAPRMmWscnCNx9Ied8fTux5rBvdxCZKy2P/26NBsxW11PC9zVEsu/7HrBKVs//AQcRlIqOdSUw1Cf0OHXxfRe2gYoikQ0RNGTiDvYZFvRCcvfb0x0+tq1hflj2LS6mN9fZS9b4qcJJa0UJUt7Rdlfc46TCYX+W5UBuq+JRrtj3cX2C1ybiX0x98vsbCnI5VCOsgMCdLZlAWG1gOCAb3d3VkDefYi5G3wcCr4mUuJMmz1lJEcuqAMziOoHtyO6B3HjueZOEDrBtAPjFrb6DwD7/JT+mPdF9X2+I2eI5hDSJw+YZIokUJ5CiVQqN/QQeDDzmM9bZAoUBUridcUr+g9dgXAmoEvocwNWQF0tgeUF/OePxPn3Lc88AZU3FYBDW+GT6L3/JbJ+goEPrEFGHPHXHzyJcFHkWiBXina0jU2tPwmGFK0IOD5wbCqkKF3JGcj1BEADrkJ7DpQhF8nxioeCjn9GFsSNXHMVpiBT/PeoUOMGdas0MrpZ5uo8HxxDyEKYTiL7m7jvAF6CegDxfbwejV/5adhYJ5UFE1VG1YNzW6Ti+yRx2z3KSQC/nZ/4UZ+JKwyHTPXYp9QDIceQMXcJ/PO1rlDKXDgudKo3uwQJKUMfyn3UNH7mr+hVYeHwJ5qIi+EIPDY1dLrvKvcEedJloj3Q/2mygSxDUg196L88BjCe2LyqMXWeBIWUUnLwl/Pap8Bvbkde1vWY4eO0BqS9pZeTZqSbP44dnoHvMDZI3XPfSqSW33YOvHrRkdpE68qK9tjusMjZwY8xmyFZY4ypTpfdns/PpX7PpEdhHMbzhresFmI6dmBlZTIl+/NnDky15cQxxMqnA+8M+WMzjivSOlmcEHIfSha16mRSAqe1zA2Hj4FRE8z622Mclg8LsZdShP2jhiEsNesED9fd+AQwqE8kA2u4HJg+ne3WvHFAl+CAXgbt/x6VJal46wJdLuodlKp7m01th1fA+wdChQzVf2d9COggHILz29mHRP7yfDd3SwXxncIzraEcaawGOgicH7M2OZ5yO/YiodrItj/gL7PfdqID7KZpzP14nw+l3Gd22AePkTO65tqBSi+V2SX8b0inS2HPCkVZUeiJOvVkDZQYW3NjjwrygvM//5rXWFasED+engyWOn6WX278VAqo867E9SIoYidnRx+BqV2PDxsubGm+ui6coWS7vQOTu95Pluc5C0lKRvsqGhwJeSI7hz4UZkbscExxgNZwFBlyEoudWaZtNLC3004yBLQsDxhV01raJW6PRCsdNwwimUdczWi48D6DRGJ+JsiU8HFUAkidhUx8/LVKZpN6Z265SV35w1PgVfjT+sSG/jMCCJFHQdO7hQMnMqbObJRuqx0Ix+FYx8Su+On461rERBhKey+Qv9wqMRZ9ja0LPXUPTDlN9bYKFPggqUtIBinmfe4v7spUJg8zYFwMbyLgxtfA8fZzkTMYBr4mzF6ueo0t88JNdrF6mhR4sVqsWRDaCMolc+QD6bRv5dPHUwfeWHzNvDLg4+7ciuV8a9dTVQt2vKhz3W93/pgtIO1JFPcBG4tb5riRnSlqthkmU2Q40oqdLAYKyVLdLWvIxRxc5jJprSH/I46Y+U0lndN9vsK+dpEmITxPXWy6Pb/69LEm0RM9L1boPYMaf7TkdQSsV8ssjSyjfnP8tV5fZGMZm7HeP6vEEmbAViUSjz8RDgNnYDFlVf3k0YXn2rTdT/8jfaTC/cdMkPm7l2e8GEe9UG4Jz0A7U1pGvXihSFls/e+gxvZnQl6xoADgjFLOPjUl+ZAC6HzgiQMiIq9sf39ZPljlYigoBuIFQcm3DqV1YdHeaZtjf3w96XQW8+d46NCmW0b2JX44TD3YSD3PQ5ERLDkXHWoQwPMTZQVFl8ceKvfYor9OaKEWxCe89Zpm4aymv3GgZJIQq0U6oD30jnLauw/SMKXGApmbUXHqHd0ExZraLOuDB8eAH+NnAc6UkVrOLiowOKMp2KDyjDdeLyH3KDsJHTL/Nbkkn+n5P5ndWXImX9LA/q1gwDTSIQLQ/CMlqWYNj4Mv99X8NS7VjQi4lEDsKjG98CKJFyx3D5/eaMBltavUX6LvvxYHPJZq84uoGt0mG4FNDsNoWvPSg8H/oT4UkuCf+Bu8QK1L4CXFgu1VPPdVoFMYIwPgrVvBa2HohXqaghVWFjbXnyXq1oprj15COxLwJ1nwqYzMuXuPnzSrx21HEyNNqTttshEGfVSnCBZtX9e2eK8Wxrk2eRTDvPJZfm1ZaUpIRMhkUc7/hgFQVAFvPpoUhyFr37RFLk8ewNKq/OR6+qSjxlIIByGyzDt2/sBp3ARxAl8Y6dZ98S22SMkLDO3fnZj0ZQeKScz7kCGDTcJ89bEB4Btgz/H+5Vk+IDh4kFNLYeGYuJecbcniDUVCVJgbfzrVs+wTX+Gsl46nU0DdD1fA6+8X7+eoFD+PTMfDhTlMkqHY6FmKYWu3HAQBS/xi/7pwDnQEZiObq/RRZKZq2vI8+2Cy9bdRfGr8sc18IApxUdoQqOfkB8XPo0FZN2OsL6WqQ3Q7T6EMRfcCK3U++ln3X3H38kIQ+qYpF0MgKJhiPqPC2rmeCP+ORuCc0zAIl+/g8X2qkotmCKPYIgQASXVnAEhkeEcP4ye6p3CA5oS2Hr+25aHdpv6WxANQZTw94IA8bfC3+flLvd7eXxHhxLk0UrHJ6+H/3eUnPYRrQULBjqm/Mfh5pyzkcKP8T5PMrzXz2J0fptLxUrwOjdSrS5urqdekru3OKmltN62qZbSRCJSJT5V1owAHN32CGGas9kP6V7zl6doqPA9M36eHWA6x/w1JV1ME1c+W9gF7aCYNFXAQbzfcRnawCgOhwWfN+yPx+/QvO0FJGxCtFzj5cTZo2cKmVzMIWkIf4P9XJWiCpXK9P39Yuv8GUgPJ8U99sjD6yvkIhit/EJzHQ/Qhrfv4ik+rEYtTn/iWb9WpJd2ugsWljO1aH08pora6FE+gR53V57p69aLvx0egYObHfKEy0mOhp5o+SSJ6j4UfDvevL87b8K92yMxExSmfLM2R6bWxyKg6Ga/xHYlcVa50N50XBfp8oST6taDk4NuOy/En3utviPjWq53nvx2ALx+WwNcS5mjJF9b9iTBPA/vzV0LTaP2VHIW+kiPkd2BLLB/+LUta8vyOKdr4/U3F3DPoXgEeiBqEdWNI+Mtd7rkM1+tkmim6aePWpnQPkkENQk4wCeHYQQR03MTUmNptvw0QXLnZC3OSXQJVm517T6xdb+D9L1f+PbJjwsS3TSoI+vfqikEE07QCQ/jjR5yidfvWNKmiQAOXeBjohqMgKB2dkSIIVQUvCqcb0l/6coWuqugXFLn0I/uKyAR8OSqE2N9A2J0EcYmQkMT4hIpoetj9+hdI/KjTXwgb/HFwVLzYgq9vqz/ke90tZKgvTqOCVxwvaQ3UVHPTlZzoTS5emhjCGZuyKoa/bwZk+MH/GwvoI/N1TinQd3UQeKXAQPEWz9JkdOF/b/vHgF6cteMImW2bY0eyOaQxJ60hNMncdVWjPU7OupPCYda1Z7fS19F0U6oFSa3Dyo7ENk4GjwxiEi2CFPQeAcjX63yCJj6IkxZAJ1b6CYJnpCPUJ4F5bKkBfEgQb85CQqAYialu5SjiEu9h9jj96m9SHJopbLjoW9x9J3cXSGFPHkIehT/qriqACF+bY4BQGl+Rn1TtCRIXF+7jyUgAl6AK8+NH1b09+ZcQmfIbcM8/w1XIHs2kiEXoX6BuXRXRJMDDZzp8JZY4Kb09JEqOmtVI3Sv+i72ljRL3FTmDogiCLZ1clqUMGDAXiShvKVtM3JupekI0dNhU62kJ+nynSfHw1mvlqj0fp/THTSZeXBvkNsW9avv1UJfPGKwBQXY47LwTzvPGHMFLzVcBLohPI2koI7V6pksCwRKOP3lubN1BSbY5oY6F/qRJtesyoqmoC2HAbN7dCcSpobAezx4FgRvLk/DYBeJdcWe1/76v2e9K2R8gc+NVt+ufRWu6zNc+y4Zu6+jp8W/hammPXgb6ahaxjmnFpJgQcbMXGn+T++7W1h1xyTQiVMO4DY9Ow6ZrKo4DLzwokzOE6PVNrSNVLFuEoUteDBHoOWl2URGFqz8cUIfnELlP2zMx6293HsjfcmZ/zZZH5mz/NcOhMZBTodUvhyShFVzVrYZuLX4UE+gh/LI0dlqcVYPD0e+DHD26+A/qVI6Gq0AnvFZMErPOheS32fPu1s+TvZwNBJ94Ioq0b2hNvOMPMxJu6J0WXwXYgte8Ojf3cBWbh9S2Jh49JMHcmnE3EyogWpNjqCENUTurlZwE/yBrKo9gSdoPFw17xL63uDRQui2NVamJGZMlx5yabtP4i+joByH3ZU5/DgED8L/H9CFA1i8VNdaRg9QuyM7SjCPZgS0UdpO+gw27OAVEGPaH3d5bt4f3I//Pv3574i/7hC7JHCOCd/3Vq4Oxh41xkuHWH/1dkHq2rKQwF2MUBPZafBQVbvpB2C8uFfTsu/DeulfIIKCuN8TE7l/AjaN9k0LaAO5qs26PBWg5vZsh6oMD+dEkmWbN7dlmBimVDsHjzgRfB96uJn0B8QtpXyatl/3Dbdt1a3bla14MIeRnaMHXvxCVCctfK+Tf/GWu+0CgyJ8PacWDpoHx/zC+iDWr2aJJbQrgjBlNbtlK6z/QM4FMmel+TI/93J073PDOhdvOWq/yIFL1RHtNaaW1vTdm8UdaHtiTQbTwu3B2iaNEVPuEENAJHDOZdhe5QImfPjljnNfUWK2bPukOhy7olRlERSYa77CLZm0gSq9Q2yIM5LKTOrpHnjRlFJjiO+Uo1nL917ZlC9leJ7QWFnpAt/pj+fpSwaGF25RrsxMlIWhY8xmw8jNuiu3NFMsCWJAmD8yFMKiz/uX0cCpaV0ppz+hm92O0wQHFH4rjeL5mQzfpWw+Usnpi3S575FSXpJXlbgJMnAi8jrFvW7HOj4PQ1Gf6YI6XP8bcw8vTjRGvXyrGAsdbGLpmO3eaHH7MfrgfUz/gjAd/RdSA3b0bWmQ2Bu6v6q4KaZLkCsf61HxUSauWuZa/9XoAElhB9OzZtxfrPr4gz6shlbo6vA2z7+BYsKe+WIXFnXu1uVkE5vgDZ2RksPzQGBPOJiBCtfhaOD0ZAt4Ap4ZyjXR0kcAimbshBEuHqfjp4CD60WnHHjLQj27gavm3cxb02CZU20EyYjNgkNJHkriBrm3bN27aTG7m1UED+Xpw4S9hWfBL086kbTLff96/2bApYuo68UA+nvc+ZVy+CEtjQ1VkRo7/Qjfz/WDmx5u/T7vl8rkdmynEqC1zJwHsIoT0HgvcHrDWeHLr2XnVTCZ+mvAa9xiPVLpbMa1fKMIgEjEC2bUO7JX6WAI2ScdEvLJ+sOG2/vnT9dVZhULcW05F49tIKAGeXVwWklXSCv2tX/XtEnsVoUVdvOzCFUWZl8X/6O40fGA7K6KSCa8pKaiOrcklkoO/3/tau8HtkktxIdyvA0rjz+L1sotfOMBH6mulvxD0yArPG17hO1+MWR9zuieGvp+yald8m/8UQa9c2vPbZmKl6ItzYN+3+TVtXyZd+Yr6SywtEQKB3Iv+Tvw3LJnEZV4k/ekw24G5qX69u5ntWXVDfWha6Gxkitqka0nkVxRzW8ZceOZ2TPKd9htac30dYl7OPyho89cXVZSLnKQuD26yn8pAIZIXdYf+Nsfq5gQdJFZu1bqE7JoJ5DDWqOGn0AdeQ9+Jjsb3yxrgw79CQEq7JAinwo4Zzu53rr18wonpb202QnT18FBjLmwu2b50EKC/Msh3aR0dbOZPxhZR+1G0f/9cMaMOpE8KWPFIXxvL28Msfqe1MP0NLmZ/hs/0erTBUpv6+8Xjo7ne2zK/sq4EVxemi+0vfgU4SEHhw1aNzgsui5V4mT0eaichvb9WtrXpbL0rzV2vre80HsW8ZOqhg6EEbt3vOYsjxA3Ll0YuMKjo1uwOdI3OVam+rl7A2q55EPXp3R5KWtXUmVeg3bkEHcU852rmtpbfpZgAJ0MrrUnaI2LtMJuDTXUYDvbGHXxRxwCSvYl8E7/mIParSM8aR/PBQnte+H0irkYrHhZc5hKc+XVpDpQUKBp2C0gMcCAmrRML7XfwNj0bFMxxJ2l3kuhBrrHlmm74dzYfyRDbVMZvjKJ2ZwIICRTGfY7P7yScFHphgq6dW+LOLxQUbztdlekMY5S5toubEX2UOoLC7GJHpZFKUqXl4r4xvAc+ahZjBn4PVcb6YCL360Xbq5xzV1i/iwgEkls3/JFS7Kff2ZPrgLF42PXpxiqvcHXE4Fzt2oXqOcpKJlRKroJu8VvpXAPTcrheWyyC69xFh4Op31MwjDmf3C/Jdm+8S1ftXzpMTq7adYyCflVteZm/bAf3JS1fYgsgqztX17quKMgWoXfyFmPbF5NHJBt7w2Ej65Chv9vJ5jtbR+hER8gthJf4pGbnPtNX0CNQo1QcrPCtINIbeIHA6PXoqqfj26vrSelqqlPMEOYKQUKWl5wnL6LKSRWrJS9FCyo9H5Z9gxSPQO7K68xwryWn+vmfW/nWBKLuOZQ/qfNhuH0q4HvKFf6/Tb0VwJ+mRtIFGwDENnd3FEuKfFvm2ojWLPQBBhUG7gJtcMZOqWO2fpJ1j7TIhzkowR0VCmMlgH4flln6QfK86Ka0mvTytbdANQAeb1WMutuxTtYhKt+JLaqfGDo6w52TAi3MPJl+WsZVesRJr4cqYPBAoq339wjpD2QZSoy34kbWsBzIqpzUE8Xza2TswIZWbjZ8BQQ2Pjz0XTpH9iCwDZ1nnjnI7L9xKYT6RKAXJbWeEEtQFhw+zPpH2eHpA88hXEcYpNXGYelXLT+hA+9N+zUZJpz6+/7RiP43jDx7vwEi2idTrjkCHQVtVrE/6cOjncLLW+wAqqIK3sO0GT3IySVJ6j5fDFPXfatS1Oi4jiq+XYdurdu2Ubp/x4nrLBkf/zxFhFhHfu50v1cbFvUoC31OVlcnTnXGj/8PhxcoVzI/hgHjFr7MF/txBHRjrKvlahQkxydAH7slf6Jdcr8cM0fX+1wisfnVd7Iu5FdkydbetocSFepgyXJqtDfS6v4l2q/4HuZvmuZfqGQC98z2046/SlfKRzDcTm4DPYmEJ6rwNeE/2nb6ykfPs9VAlSrr/wq0F00Uxkn0bDiiW2RrzsyL1Q7OkfdmYlBe3K2+GU8BGF/JH62RxLAKyolKImsRWv6LwmyDmjuChhAroRW7MWY64n3a0ZM34o+Hi39rCw/CDlS/caEYUfbXFsd9vdEUIKy1JZB39LohjrX3wdlST9ZbrEFBcf9nUz1u7tL2wyTEyjavPmt68P0yfH4LdZEeBYbt3PEeKEeSqNkTtyxBTF+CE58M26oRqhg0IUgkicd71QchOn/FWWFB7QOdtmCm8anjjeK4oSdTTx2l0/y3y9QQrEEn6gLW5EkF2Q+h3uTxrrklJko21Ig/71uIp8Ef57zRmy05Fx9SAm+77RL/7hCeO5Vx/0p0wSgPwNv911jDD/rLU1IRfj/yD6hpzBRZT8T6FkGp0qi8SI4UqyTbdhncn2JrieeO9V7ohudk0q+qBgjPC58uBwQneHvg0jYgut9A9taXP5e/jPWYBIhnzTMkRboKzsNMTFV/qEDwFx7+Gp/q/r5+O/hNyh1TzXi4Z/HssqtcFLr40j6x55pwSE+yVlW9zDZUzdegrbbYJhTGcfbPtkBlZOliiAToOnWJPGzYPLs6MSNynBkubM5xLnvOcdstSfXRyC0xqO5jAEM2Et8vkKON6vYSr8R9oh3M3UpdyP/FWT65FKCtFsTwJBV45+doR0noUKSVa6+6FUJcF8QX9jm87DtNCfDsYGz154cxVgsR2ksjigY1bjiyq3hKZ7mVPqMyR9/FIUAc4DeoE6QRseQA7oN90rr4sN0al+/ZbMu6Iu83fDCk3jSVkZjeGXguyPYixFbh36bMVokGyIJYnhw5ywT7b1Kn4qrWfH8c09vjdASPlrDA5IauYFt0Bg5NYYJIaTIarOEcIhPaZX5E3396xtuO+Vvsci/Kl8XG7LLkEubSwamyJXYP5ExqLwq/M3p/fZuZLO5pfBYk9IS0+avCTm8I/xGFWuTKj5VUOAPktVLMeZD2D6nr1Gy85OL0OEAnclgI1blN4i6kIgb/1+MCyO4nHZakT7v5E2cSxzg190fiVifqiJf8Eszrh3WWGGK5Zci/NVsiSaRtw60jczCox9N2/ROfA52sEIabmCie5EPGDdCx2CUyW/dEMFWA/4ReoCs819O7/Js7WA2OxLfd0b0TanEPy/5+eK+weUzx8frUa7+a4O8UT/lh8EMoVgxu4TRI+612etMOaWjyLYAuo53uGBHWlOe01us+f8F3YF5IKDJf44p48+eARdSfGa4bmxFV6Gtq7CL/npdDirV1nJjZpybHcd12mpUzWqZXL8HL7TNm1NSv+LhfL5eXswNdHi66P7JIf6JDHVuBiIL+BTdjn/hRdwyeZ09CVtAwaZ3mTuG0PvGKt8T97PPfU3+p3tdNz1rVnNcfMR80c29JWpjUVLIiZ8l09ELMtRoI2g3BnFr16tzGnAydI8r8pOmArlzoab6wlkCP+v6D3ft8VkoQkpPKkr1sp8W33IOFhnQqqoBIpD/U86+8vyXM/QfWQX3MFmJn9aVXTL0lmFHWLAMiNev8og4MiowZUMDptxkITXv55P/tKbsAQVhd6sGDZZrQ48UwTTQ1IfxVlIA0T2h6ucjnujSjknjU2JCYMWDNlIb7VI1fAu9FXlKi/1z9/bro2TtfBoRpgzIvDY3gBh3a2IL7VuobBY6iU77u9N4S0XbwDyiG6YIEtDq0KjIhiIFrk8chCJu+Ugx4ffu3dbQc0pSEYIuCXM8tk3lFGvHZgLQ8jcsX6ocqv4ySFsVJxNlBTEzHWuTwK5KC6Cn37OLlaW5nwPFi2giQoet7q4/wH5Tlfz2D8q14rwVgZbxMCxnZ9raWJ/5Jmf3EY9RaUDeeZPyoBO/bu/L+w1ViNWNY80GMCROsgGvlGlu2pCnp3MTLXG2CYAsJ1Mo/5pdB2si6XuHhSViSPmK87k+S0si6mzHeK3Fn2rUECmp2/CNHV8ix5UFGwOnpo+ugjoxTtsjZ2q8xQCDAJDyz/4yPyJYf7htc1RXbfuVx2UrCGWSMCpfsiEpvwY+LZ8B6DyOKbMtelL3DBo+1JEOFMoVXdbIwixOTp3gPfHf05QOxukDpONEIU5rvi53vHMNVS27ty0ZFGxyhHpKGMaLVv7bRuIiv7y8JfWByFHujGL0s1mgxdeLf9Ut9pw1f9/xkXzw3cmJtsEW3hdcbPbk4CEDdQINw785du6R8usINoQrVJUkGoypa46Zc1282Kvd7ku5yra4vsV0fzolfRCF6kycaILzj0Ka/CgZ6CBmScc1hhjl9gaB4xgfC0eWdu/ln2MHfOb4itZf22kijjeL1fE+7JkU2KzCGv5pehNj+1ggAoNmhxNVAjSukwLWVGhm11ctqdo+PaFl2bPvgnQ5au00bI43Qk0B1o5e0h7fLy12BI8AioRMmFGU5z798b0yb56RYhfgZdq+718rXO53AShNMIRYaFM5+b+Xj33RpOzqppK1Bk6WZvLhvbaapyGpptQl2UAkuwSmyiYWjgRwzBYHdBenUZmYuAgpbJzRrAc5wmmY0mZdX7Tuu0xyv3jllNkwJRMBBLw1hao8Odz8yzn+LARAnnOLMW3Ro39H9WwHekObHQzj9YC2trx/JsAKaxIUbRIQ3ZXJ4ub1PsOblZWhu0yFp8lOBIpMz/9tFC6riyzPw0mu/3E9yZ2ttueWvjZa7Gv1l5aNqavVf1AOlry8jn7bvwCxTMsy3dBGd8jmIO10haKwaKqSzicHnVrNfU54vROLNbjNZpjmM/pE5OESdUMMfYR2c0fnic7RufzHv7xpY48NFcUwpKEQ8xG+2dhCDIweNU/ed4C+TFnEXLGaDh0TgvM+ibg77mjNjopjWAaX/HKili92kI17OVDGS4SQ6wH4ZoQ2aPefrAtvVwuBJuspf56sFloUppXtirAzIT+iOvLzNGAVfeowYCs63ytUPILEGM7NnQou3Bk3Eim09lmL+OtCzkURNDreziqaw+NY2vyk+tatJvvfO7Dl3DhPWw6QA8moGSlZm21H/BdK+YjBwL5IBCdMApkrpUhQQK0z0JmbOPGDVM4MffP1A84r3FB9PY/Mp0YqTT4GPPcEZHwjPHJYiHnYleo4u+4b5G4HqVq+NoJePAMLOQl+flMX+Ji1nzb9pTL4L8tHUvMmMhTCqZWCgy4EehQt1T//GJx4EkG6QjZrusNiJ2FcnfZPzvq7wE6Kjdf+KFQwbPWmH57nRPvvRcHBEyR2D8zXEucl+uMvb8TBf8OT1vL8u/bjMGSz0Bk37R/Nt9MBGD/biMJ02EBNnY1fm83+14jxnEPedHYbx3im5dPFvR1bSyKXitVZp/OODXxNaRo/nmsA8dHV29uYUHDgFPxHddBE0KnlxCrm/abMy9ry/v2iCODL4hHIJh1zlmqiNb+Fl43+pCFfvXefFebs4fpdMltSQ+f8oH7Z8Sr28LTH2e5RqgSfUKdkUvt/qE1Mdf+1xJBF7SIO71wgbkA4cyg60WU1GUoJx24svMv0wpHF/C6oAwm6GfMOjuvbtRpRcaNEGBaI4BmXDeXqXRMmMHGVdy42BaTEllj7aB4JgpknvxlbS3c/0zuyD2RMQoXWvSDN89ZSi+rXYk7hFnv5dlSsZVYvl2Auh/fq78ifxN8jYeY5AC1IC/XxbzMS0ebvgn5FC23cwJtiJQGExjurw8TeTTVTZvzUD+R3DZNAEIFGZruxV1DgSnzd+kZHImyAeJ+s2Zsre9weR3GfaLoS54Udzmgj3hme1BpBFjcLeN9NX2ktnzpwlMLMV9nsFkBFUZCQLE6qe1oXStc/fwquUhfXg0T9/eZkm39gy6vn7MOhLAqERiWBeq03Grmre4Sk+iPdYgQaNLeDLHUrun7hKrV5imA/zQqQni+CA+ec24v31p9hfAzuk3oSPIR6sJOsUCCXA7sJ1k5Xa/2JzXl0B3Vw4MgMdJF8bYcuddsC6QhtZ7UUZBAjBMFzp5sUhdZnrifA0ZQl9N0Uaan7Mj94ZMGntLhhRiAeNTVnzGkxjv+pkFlHv9QMfAyS8/tJbTvoP8yxRSaROA77FSiY7vEptPpvcMjzO9mMspq2bHSeVnv95+7H9ftn4fe2S5ni2+TVB5z9PvRTx3nIJWbZTORGPZAmvO4TN02+RCntBJwBmIxuxEHGRgrunlhmUYKFPzfzL6lSFIFX6+EJsRUQ+VScDANVBH5tHHHkZVjuH3Isk+gvdkL+ozNcWQ3QJ8nYufzSlO3+a/LnalisHmL0uNNodc2hXqLH3I1GbdLcFqYXsX6RtyIMOJaQGLvYh5QwNvqjkcD9C/TDqpxtVnXfOBKG0FKHXNAGhajHHcQ872cc/4rL5nj/jpKUoP3yggzyKwO6GHjnyAuTE6F8ub/J5Z7oeDGHBeUQZTVhXf2Y/toavUOVgLY5vWSHPCNDTe+YpXS18oVn7f+aI8J8XMiTNLZHnTQ4HSpukgEGqnMgwLndeXDA8tj3dDRFY6w8tspSOjXm91N4ab1FF+9VGL2BFyps+L5Dh/0IcfGCs+7QQxLWrWGkBL1A0Pogr8QK+AV4qsDREF9OTRC08D39zJoxMsvxHJ+wRx0ADhzPTiWCbp/LQg0z0sv88Sh2Yev78qGi1vwUOP9Ba0ziizPCLyXvRrhLuqlFte6LhF1szFfJ+bYvDCXyC+Qu9L9ed1PFK16QZkD6UfvdXlFSwWJU/MntRs4go+SjgyEzWsc6dNpYbftAZmrTd8YY0zQPLbE73q7ZHBJjc+6Ht5nql7DpatAdFCSidNtpV1c5W+nwYKwe9XQaIqU5r2tHOC0C/v4wEZAcl6I6rXxwv83Z2dtZ1hfx8tZj6PeTcFtOm7E7txdYsmXV8jZf/VaihEB3TlkVTgi765n1bEUMWQd1D/oaUePX/tl1cGei3f0OVdXTpNu9F0z8l9OJu5Y6CPPhqTialFz2qYfb9DKOWJG7V6Uq0odQsYGEDonCf8Y8BjHui/aqXKRM7tbReFXOVRAyiOLtmUcQWIY1QAbFODLXtdzpXZ4En2h5fWMGHKCtr8/PqPu1o6mp1WqDco47i3N1wd1Wr2T+rlQ+SsMGrxkSsgFTTS3NfzOQdDvab8DCtma1dpQ5Z5N5XLP53R2p3ffkMJLWMzxREvtygRVq68vq7cTszubFvvyDhjI2qYjcsGo/Stp54sF5Iiy4Peg/LBlKGcvcpkv03SzBbdSavhMTr5uWOLBYNojVS50uOYMe87uXvFB/N9z4KeFeHF+tRWSCf0NKXtsWASJXeIW4qGjiq0GR0E8LWQ/kgml8iAhlb8Q4puG4WH9VIZCAGd+43VfZGEB5RGXtdoCwksMwhoP1vRj+oQ/yZOgB+11/UWfR6lVR9H2YmI7wXNdwFuy4EOqd3kDTMhdHcylqJTkK8LvuWbKgmhuWHlqv/o+h4/tO63onargxek25b1wmaBlP/O8GdJ/9VlNKqYh1x71gjlAk6RmbLJxbxtH+RRkLWkNJUVx/2e5wObID+qDATF12YbJ1jzM/SnYetgBZCPnWKBVQzZh44nSQ+mZlJZVXsfxEeqK5SmLvLcymiEdeVQKovzPoVuv/nvLBU1kmKfAHFEE/1lRCsHpjjL+TErmXM7xSYTB3jbtyYtQasOQ6klJmSXrp2+P7E0bU/kat/2B6V96P6MnZBnYFXY+qv7Y9AXhGcm0yQoGBt1Z7CjdewozW8gz6k9nRipDCJ7iv5Ozp9TAR2bC17qUevMNT1zRl7E3JMQyxSOwx1o1wPgzrzL/STUuTgFyESVVNAXpzbEldcWPIYfccdosc2B7vQr8zJ3MbHnvpDNgdUJD/MzsXboJvBHlJSJaDoZzp8pBxIQOHzXEX60DwLQI7vDe8TLZzWpzTApzTUepRBTBNN/wa+GEhsxmTRVRvZfGBg1cCUHz7dbvilz7QR6Er/XKeHNMJS/mQsPPKKRLXl3ne6QletsTA0Oj524LnRTwyXrLqpTDGwNBgO2tv6QFD2aOnA6qLPJ6AngC3DPO+hB1NVBO+T32MyXyKZC/cx/5en61qSFFmWv4QWj1BoWRSaN7TWmq+/ZM+eazZrY7bd012QkR7uIWePoWRFwJ5f/9Ly99jEX2G1+ucCjta52frHACIzl2lbwG4wIpW3M3/hRg6tQRzPf64wnv1XhpWCKniWLV2vRPngE3nd/pZvjVA2GYc+2Mwp+YZGvxTdFtfc6yd19Qb4tWCZF8mkWhgGpDYRo4JvFhZZtR7M0ob6xl38nR6b1jY9psCl+PcR3KHtQ8s3TiJC1fL95TKn9muoYc66O70arh9S+pXWN1oN6MjHeuwS4UQhUhuxMmWvO8uBiztUuumul8b6ueZ9sTYXxZbBO3MJb4VblKqwwYHJuLDZqoMwbvUAZQR8B3EY039aNMjFOD7y1XWngAX5V51nVK7dnJ8Bf8D/eMVYUgIZw9kRMrtiqZUVb2z/nHrQkcnrGDDdfZlJIlrjQ9v8lMWY82KVDbbUs1a2OIdZOKaRpI1ech8sPkMD2nER+tXCrNE7Qphyw6Ry1dwpkpJOEXv0/l8NsIMfuhL8wJUlTzsBBqnqEnMJj9Tn4dJ/BwGPBlS7Y5JGuh1CVBSxv0gy9tTW4Rr+2hIb/C157/bCadvUOCEn92SjeHryWzdfDK/6RT4KMtvv7n2DjIj87OvXyb54Kc218PAN4P1BpNePz0UGRWboBmtlFk9jnCtf58XeqwlB3C9JLFf2OwAh5rSvcpEJSikmssKgECwS/23s63ZKlrHQ73K4viZXr8DS5FeZWHaZuBEo8WcLUq3/BkfAk8NNBaBitLWno2ZKxN9YVfC1MiwvkVC5gkI4PeGf4Ka8Wiyefao70qDg7LENu5HCl6Gxa7ZYWyFGyWtJQDFDhA6UKb6gelDiS5VsF54dw2/Is78zgnVkUYAhdHagBIqguy/WB5j76V1q+16jH62/FlrS0Zcg9gr+hEcKq9PIS21qViEkwktKRiZtXcbGz94V8loD97+bZ2+NS9qj8r9CzB7S+UiQDZPPlI6XowS9nlMZyn4tloqdZOViKLVY1twCaZ+9T+yboGzH/GjXkKTSq5ZfhVnxiMKq05Dfuyc6esn+y8CjJ//EF66WmzXckqx8Brb0P71jyXcvXC6yLy2wX+Fg+yOV+hW/+GNufUX5BVmI9WncgtgLYEGi0NSI4X1COKmReI8Xo5Yl9Bw5YYmwsC79enuWVdTyX22O6GpOkzv5s03fjq1G391EEq+X3vdJ/YJDLJemmWNSzu6EfbFKZljlxwuu5dl3YlhAVbFKltPLTH/ZsU0rDSZoJVMlpvuqze8KL999tmrlDmL8RTuZ55ldOLMQSE0ZP6Z7wdZ7n9zaS7dD5ZnydSFidliKL6jeBgqQgioBFbOHFDXu1LlyazTNWFRRd/s+KKiUejQ1/GRFQcDIrPW8+4YjIUFStZLulL0K8CQQ8up/xs+7U5xDnXQPtH8KRXKhT9cN1sf21Hj/WMgX+4zDJ8yPfXf+8Faz7lkeBQX+yM/sLcnnkiJ+klSIQJsGwqoyrKtefsW2cy5oWX75bEHpiICCMK5g0eq1MtXzgCHH5G9zhIiRBnfNVCfQ0HscmG2CCjr08zfKyMxMWRJHe9udFVWCzY4Ve8ZIofLsMK2mOWawF3UXpluDK5qxV8P8DgJSNAnejvNXvcjFA948FNA5oc2KG30T0g9h+iOsb7b4WfXOR6Oi+LB7IvkFJaMDuhGmMayGmcZJhqETh1BUfypgtzpgWZpU9KgW5QusfEfGYfnmlR64CgFABnNJo7+MHo/J0oZ65PuyZ+eaPy+DFN37b8E3gIbBBzn53whK8ARa8pByZlXRhn+2KQR8x+ox+xuXIjNZd3wSaCm1leyjCyHcKQFd7yNH4aaat16cFiSp/piIX+GEVL71d6mla8I+YWK2r9azAWENeWfjeq260PT1WywJ9wcC41Sh0PSGrMqDMYzBPqv57RwsJWL0HOS67P1/S0dZgYGD0OG4RvHPdB2CFLUibpbDqn+SLMFdpL5gGsQl7j1TDBAo7b2fOq+fbs1RjFO8BEKLJqUfWvI90YxoCpSssXnnRcFdhL6ROueZkIY9YQw2fCSmN8Breoj4G5Dgcm+vPH92HIn80pNX6OfvQ3Vx7IspYuDQW483Q9Kb88bbHf43J6bak0gN7F/h7KpBCujDhQYLqUC9zp5S1TghaX3mdcZP75+iXKlDf783mXrsqEwZBAK0oC8O0yZXKt0S/Tni6uJ5nvspRtxnanik3MePCgi4tYP/nuTvC6OYXQy6XrunTT4nRhIzx4HnYCAJuiQ9PYBh/ECGF/+kgIAChTsdVFSQr7xsTYs8rJc+MKMXl2ViukrtzqzJg7CjsHWKcObL9EMljLFZaVyUXRgIUkUHWupy3jLSjNvjYmeF3IOBlRr88n0tfVG+H2EYvpNZjxL9IutGaJV0RH83zJDiC9FgiNLKu3cbZ3i2/ZVDYr39NpNqGO8ePcMXC+q16nRu0SJgzQM95ONiwZ3Sp26Jg6kHURlFQWlNdrX1CB6ZZxz90TYF6YkK1E2M/1xdwY5/mP59MV2r9k8sWrAOKQzziUyMm4zI4dNbwnFlmaTR1dDqJFvWk2TLpEj7t33UCEcN4rA5N73+8h3Vs4jPhO58qw8znoXq7+NF6y1Odq1atLles3C4g9nng71oXl25Z4skz8NewusX9L329if5brPiqL+Zq8e/SotPhYHEpJZ3aSyC4yu2T19DulmMD0emz01/j9ea/9o8jZF6b3NkgCSM2CexulmSDKuHgts0uYgJyUrA+f6u4CQRmLRDX/eOZ1zxjovFOE1MRPvNxFDPQ3txv3PW1Ee3mw6Fpd2FZSkGhe3sYTd7Zs0dd1UvnNfTgjs+XhQ7lBN5EHkIrANCVRua17NlWhBQNkAsKv5kL+mn9fntK/59DwTDsrmZ/kYCspZIV80iaQBIcLX7Fc1JfMJJdv5qxITFm0h+Wp7FQ47ZMwltDm/CUowQFoW45rAQE8SI2u9GZv8BhGyckunILRxqTs/PsDkv7zdk4o76MQQPa+l+h+VWzMVZ/pZt0y2EikcFP1+lFHuW/7GMYEM7MRx2RxmUuM7w8Eq+T0FE0/z3eGmOi3HWTMM6IN9lzT/4MAvuYYOCgPJVkuqaqt5OmPr8u2bLuy68YKYK8uc8oYgFf35DYtQefsJP/6QONmVhKsz3wx4u91ehU0SeH8BD/yMiWyys9DNM+yky8TB7e1tPcienxSZbMy47IH5Th68BN4FKRV24Gvs2rF1HAVcL4bT5l+8ER9Kfonv6sswCquekfHuzslmalt0QNrR9Wv7fgmL2RaKhIJwpUPla7UnK42E24seheQ+CGMUtJZEw05Y4x9fyo7AQOUQ5lhpBUJ9asi9sYPGNz9zE6QfRe5msPF5LUA6BbydSMUzP1dv94uf2WigIQAZzDB/aCKkOqr9K5hX6OLfrri5m4MN0BFkZ45bU5BOnRJtV7mc1JbjlU7rUl9gLHJigbOhvpPuzJ3Eq4ttfryv6sIbinuAO/ima3m0/jJwb/56xlLTFmewQDNE5oC7dP89acd8vUv8eCJ+n9llF36ne7zMDEob2/WtQ9eQ7Tq7O0+/bQ9KvzeCxuycFZ9JsVNiXuVWYXhik8bTXAe8d7vvoPAbIdPTve1mJC3xGU9L9ZoZWZXPjybryJBMuIm2Sv5xTi5coOE5N6rxjUVeLc+QrekjXYHFhBbeDXrCQF5fxpMcIKv9OmEHqVahwyd+9nVsQ4poxpXfqQ0diDi4CI6LDvb5QzhBdb3DGKFrN19x/RBE8ZeDDT74/lYRCkyNMeGCeNxvmE7o1L1fEppg65ovjIR5K8jqrShYyKFtgdI94/hJ/tjDxXr8FGtdIJtJtlzmFI8vwH3NkA9ZGFEv65BiCFsbeT821hdM/5E3Z+XdPqKbT049meZ1L0Vq5QxAj2scwznnovTJJlOHnIZRdjLIx7zjNEff9viG249wmnAdraGsfQ2zYBs+hT9Xibcu37cZ8eJkRdWyMMODgQshXI+k5hHumvg/f6VFTgj0Jf7O0zlnSGyBaP+coZL72gjre6GpTXYWq6RBsoIC85l4cgciShm0ODwndRenSlS8RAhN5Yw78WiYfoKV20KclMdbPZORwwiHBwpS0ed/75H1qMTEuSmhFT22i9Vzuu4i/hcrWfbyi+yyw+hoIiz33tZcn9YFU6d/yqR3vJm255uT69otHuThf2uWPPc2lcWEoP7t2kBripS3nOirnc2U8DYmZSkL2C0cfL17tuRK8qKzNflR+kXlhy2vPtGFK3+HXUXj1lUtCEqt+bs2fPeN8pR/+VbkamyL7h9L7YQgTSEAOrAKwN78et12933sxeH7N8w8rhmlXEoBqli+nKNAKyJv9XvqYfCQKeGXsRw3LNWbpwfKcpcrviWnqASfWi5uymArXilDYN7Nc+eofeaD+zHyPjL2b166JQdp3FftFfcJeD5DB4ROc2cC+a2ExUJH6MrKdO93ihbrSz343xS+vcgWfr9qE65kZ7oFT+Jshr5QhMfqK9pPx1NXwCrkYiytZjOJRkgczVtjNg06ZKeVnVfD2m1we/m/ClDDk+jPUmLiY/YrUqoylBwdmbrED9VnII5TB/a2gmKCzaYqZzrt3HzBpJSG6AYOM7ox50g3D1STiJ3iF6qHd9I8Ei9PZ14P40MvZ8Tz91R9DzbEmqvRsjThitLpMlKH/j4azDTvqrM6MXyJzfqw+fBgoallX5IfTJvp1lzLg4DXEE2PPWY9mc15vlH+7uD/QnQUPkziqLjOQPgTmECAPzkBwza6aR9HxiP0uIHzvCIRClnX84iZbo3xhMcOHO2uiny+3vp7KLq21Tzbjdv2puo0ni6INJ/t/E+3YLmEYYSpnzkKvA6GPM1MWCt8uejiSNhj7Y4sNmJiv4ytGY05Ri/BZrqtDB2r3DGjhH2Z5bHYZ4hi/JNiINQoA57bvlYk/nxs07bIZOfcLSViNKJNNWwiRd08v99xXxCk7BOo4/fMbu+ZUPliHMOOHT7aS0qn8monAL5n2fR4Hib5Jh7XZoYxnat4VdTXFDiodfG/jt+6eF2s1yrnymn7tNa772jnq31Df/M0g+e5/Acx7mYss1bQ5ItE0CTVtum0KNoAGVwxlVHKtt6oxV+NREgVHjj8TiPjYX7ZWRQqUG2Z/nKqR0KHBW9IP4WXph8zuE+e+zUagCRhLOD9welTG+aY6GE+6rHHChvGU6yY408glzzQv/xt576uGGehHDUS5R2aotLfNNSA9yJtJGax6v3IPlr/h7e7jQtwrfWm6qh5yIkjObEUw3WBBgLfekEyjXnFaKd3zFZUqOeMsXFgeY/L8ICZzV6bbwNjtdtFoRQPf5NE7j0arnm2hdv4WdljvXdLX8kKrJMWNrpqIZ/V6e0OCTA3SuMf5gr+8FdRNmaUeCNMXwOweePuv0f6nRxuC4zwuZBQdomWt6RnzZwz2zP1sKTeN9TaO+zcNIA2goyFwSxDRCSfD0ODeTnyTNe2wy8qSnWys2ovRYXsrpYokrci6VtnGpwvMzFfAOMHLBWa1Wm9tushMCF/ucpJ9DG5NHgzME5gaPsUK60rZ7BOgBb7+ucezZiQkKtkHyw0nlweEzDMJslnV86XzyqydvUX4KKjN277Pc5P+tZSQXiD29qG0O1r2LuUv3062+hdgT2OiiYAmc++xbmZ8+BSEqkPvcAGUFnc0rMYMnOgINEzgcp7zW1qbt69EAMqm4/VV3GUq4l/tjAQ5vvSXSK5fGwfZP+J1qUn+RV6xhjR3OA+rObbKdaVC8yUir0uIAj9IAeOaIvUxYJhVlN/3grFWhgZV8zFMs2VvdIX+1NNjjxK2FJ+kTQet/5wgcf1VQxlfJPeh83ljpLg8J7oMS4TTEeB0P98BOxbsohEo8eiERYUsfc6SecUu638/4Mh+NyJy41GPHrywEKjVUDjLC5rq21XfcuDQYOZF4zWMXTGCQutw44wMNqbfqz53es8g1FHylsUeIG9zhfnS5Lfv5FzUp9HmO9M023wfMp3gVfetjC8+jiZE4jR2G4g0e+ky2/JfLWjPRdDU5LzSriYbP5Oh6udjjU8IOSxTf211+0z8mCCyHR1ApySDgEF7L947VqqJVSWivTFd3AgZvQFY6X/N1FFXDandbeyZdKe6Gbkvsse6+G0L6xYdxGLtB2OsUuRqlWUR1MBWFjjEwku3nNsH7nNAjZOntuIJlEx+bd4zqkQlYCR06R7JcN2XjAKEPJQ/7VSAwsBXijKO0ykwHin/UIJhcG0ndkypLLXzG2NqLdclXubDfeAwpfcCdpw9+KSnVByHZ3U8ta/EJ9HPg+EopIlxqQUsT8AW1UBgeW6FGL//aiSCajDRGIGPPV1izIvAiWYpVXOOagQSV1N3SKlxDmc7OvR50D0nMhSMraSPTMMEEVg+CVVce4Mw9RNOmHfpS7KT+5N9pfPrIEXNY1bIOndSOMED0wS1P4aL5mtPqga5UN8NlDok1JNun4UdfOlzsG0kZPX3whI4H8nsONKayhaUOzVdSs+DpE/ocYuAsl7d9rF/3g0pdRKWLlXDH0iWUBAhoUYpjh11/PxXq/LSI/ABFSqtB7r78Gxnb3OtrRWPIUv43UiTvUHw+scVQ0CHATUiOEIYn0oQBeP1IR4ziHeW97eO1r2Hl9WzYSBT07CS1l6a70Zo29VYRNAjkhsoCsmt7i4vqo2C36vCmYu98cW4iryScfKQczX9qZCqwHP8XqJBAdM9JVpZrrZjU25aDdgUKmdpCQ7lkD2MFwFwQyW6iHl6oWIgkDiXCn9TfAoVZ9D6fbXKcPnhvZS4x8bd+vp0zhBohMpilKkhqy4zEDMa8BvV95QXNbmwflxZGMuXyIPvXCewSIPhB2y5f4t11XcfUzlbBVmfXzvovJP4f+y9vKgtZ+3ZPxlXAJx3xXu5b0ipYlwWqqYlnrCL4RDvPOM7525CJkZduE4CjbISPtssjhP9PQhzOa3NCVHIrm5qqUd5p11aC37eJ6bjYwWOjVZ3uooILj+J9PhLHLsJrJIY+mI5lidVT+/dNNNC8jd+9pSb9G/gcTvU1lMNaAOZ2U5OOGoyJuejsQadZXoUMUL6AHsj/T0nQYRAJttTo3VIurkpq7lliYQmp+B18yER/Zx4+6kfMt1so2NkiAOC74l1fTecxktpd95/jKPBqxOELwZqhTKusiZ5TnZoEu61aEho6x5ccxhITps2yvEg7EI6f7bRruo5xRIPsQpTG3WJ/RDhuGhl0rzOUvQl2s0dVqq49aBMqFo1yVsyHkEEEiMSR0ghQ/4L55/ky4AMGybne4uPAZQ8YQK3iJ40vlfeJ2aet63Ze2GWGPeE57tGaa/gVHklfOIW+P67SY6fR0bbWbnNfL3qbfq46b/u+dkSUh7kgJUDDdp4UDYkTpDoaIPp3EhKGtzxmnlL+QVStA1IIC2OW1MhRgcZ4FzDDEZrCbfZIogSCG0qSI/+2Rle8xv8Yk3EW54OUJokCUp7nyefxM4G957wm6URXqlQfHzgCDQYscDi62G3vOcpXkMTT71vKIk3uvzh0x/5vi+iYDy2dp7eeAUYicF+1toCatjX9yBGO4J+4GkdkTt9tpW20scg66K66n072bSDEr3wYP9n51XO/Wb/tiOW4J/ZxNqTl+lxMyNDZgBQuo2jiidmEVGYBEJ5DlhIaxc3UPUcXpFSzgHr1O3Tnw392oevJ78Y7WI47E3m8xnlByv4D1Whx9eZ1tRYMvWmFDRANdENLxGjmE6kAZkhXg/UGkFex7Ad5WjfxNn2YW4pZMjn3ueupZJf5lmkwVTxsD9p16iMo37Pk/oODIJ03lOxGDMM6abOweaZ1FWiqglrD4o7hgxzrvVE62F81DiyEJ/MzOWQkUkmkY0lL4n/NM9G6yRS7/q4RKbfPgpuGjsIxEk3ard7oIX9qQwyAzJAwkDkdJ4jx3rjcqVu0sLNrvIrkm8yHz4YZSaMBAj4LMYlVzEee5rV62zTK76PFsaTo/nlOU0RkCW48cGv+ZtPdrCNse5y9976qAKNlcIJDD98nNc0ZC0gb0dIsAODiHLN657lq9lbmTKNsK/J/v6iH/4jf3GQEnp4+N7hAbPzQ7CJVs8PkJs+se1vhC+jZ2d6LMiko4uGTCA/Klj2ZjrCySL8Y+iLGOdC5fZBia4IgzQpNNYvuV93NPQxse5Fp2nKVXicwJCWiCaDyASJA5Cp+k36mkCpq3ZeFwu1zlpMu0qxhoIkS6/Ud/b4exyzrKI3+fHNPXbqvhqGmK8MO8UgOqKmmg/QJDk/9bnlDRbIPLeATVvsPn+irALzW1jDkQdf69bYPnkGk1OTfRBEF4MpEF17a5v3l3iy8rLnlqmpoBjzC4NFgn95DSfdGcZ+5MRQSvXnl6PfiK+PBVob8juqbBnOGBUVpBTShZh/+0+lUgr+1pb9ARTgjP8W9RGRIVZiaXudOKV60C95Pl+h4v/e47YzjfAymnJiwzZ3v6h+Ol/LoHZkqF9BvcEKzwx6kHM0pJOxw6NmVzMyL33vfBRPZ6/UqZP40+edgZ4SirT9r7pZwTfJmvLo7EX6wOAYd/zq6ZyuxiL9m8RBwKb9dHh4ad9u+tvLU0CQcU+vnAHJ3SPND+giC60QgHGlDt6YuYxO0HwEC3RwMozntmFbhkTzc65vAl2smc7JSt22aOJiU0x0YLMJS5a4gp7k+wY6ZP2tqawxD36T4EsSriHucw1kMxx/vcGioNHMUKiCP+bGsddkb2whmmN3TCrYmSNudojBpfgu2lOhAbrX2L/qC344wy4FNoMSMIWBTD53yUppYrtwdHife9zLe8pW24BfLD8oWY2BMfDppsBnzIx/Q42vtf6b9qe/ly4pzibZPvdEQ2UcQWNbWixsHoscHACABidL+npyB1PTPtl5/gSJYZqR+EplwK1a04qz9ypoyLDmGwbUWV8Jg5E/yN+wxjRQV4D9oPbZ+4uyAN8uPfQKLEYbJL3C3GrUIJMy0c+HMXjQICDoMfq62dWcdjGH4LWlwwjaj+4z8wdyeQXj1u6Jh4ek2b6zLcvKq/JdizdJJsUYf8arNpJV0f/m0896xluXfacyz6bQiiTGX3DscEHAUX/5hwUwhhScRcT+VsgfIWT4QX63bVhRwFNrnQf5JMwJQfWr3PU/DZBYqmgh1o+d2SDgr9JkRcWdTlqOkN4r7wxdupwI61l/EqkODALMJQjZ9nEQwOux4u/3J62U1zQPGbOBgXuMMX3k4sA8GOEqafcQD/0YFiAiq4ph9A+sr32k+z7fEdGV0JRGDsBkySV8T+UTIvjeOV8mX1suAKHSA3lAwbk90NhBJd696ndKPIXo0RvpbeWswgitbpjOM85mf8u6tftgSoR1STrBXZQNu9pBHbd8lY5lYfgzCIriJ6xxD68aXN/fDFFuEBcTkCRa6YYXgu4Pml+7+iGz/rqo/NG0CjwqWuhinCjAjl2u+StkPaIzzBFYfZUBQvx238GJ1sGk13V/2Ysa0OQhwSZKdqsKJIF50Osh9BXxWIngegsO/aLTk5lX4Ygdfdw07u/UX/MneoBpJMN3Cm9Ds4Nxuzi1sMzwrl/wGziHQXF/OedSZNiXG4VCY0HZUOLflFcVKKLIoktQ+oF7XdKFY67s9GI599mSlFprfL1LhRMJ70WbX21l3O+FadlcQYXV7b20HtDy5dgWi7rHn6dVNxl3dp58+SL7yOjaFY1kGQRX99uC4X/d6H5K4624ePVLp5iBunSReWnn8oqCZbrlXBQ1DDY0jFA41T/NWiA/1Oco0483nEtzl+vCkDthrj9ws/LZeYGJF4vrn3iM71ZdvvcvhcOaV0SmKkiU86rzfI1hIfZEr2Q7be7I2y73ednjo+Q9pRNNZcjQ6JJ1uvt/wxSyrcfmn/rXcDyy5SihuK7AJlRUQpja/8taddMrjK2+NKxHfjHB1emgFiyMijNquPVQTi58g+IxUV7haFQnkhE048qJfZkGUqAqjckDb2V2hfPl58uHgAO8HlYWzSEdZRDDsUAz/n6pSccp3Ssuu/gJN71/30ZWzY1/qLAfJvqBREz/Eo/h50tcVzoQKyiYyUMi6wr33zRBEy+qjyeD8YoCL3/iVGljm6BdVSXDDSRuYcsxCkOa2FsooiI4kji/K4vjdfR1e0HNODf8+AvAF+QyYjvCWZoBI4KEfXmZjrKFzVp7xpg2TOn1Xy2JKfRK4KB5IAPXxptXfwk7BNBHaGJf8Tp/y1uwO0gYpy5NEJDfEaKXtn/DTYHo42/Y4NyThwZQMx5yg41T6fJhSCG1sGlmcaQrUVM2mnKHsZqrHoWP/rREKaP/Jvn1xV8HSviz3FadHvus8q/s8q0OesBZRDn3rg4dWdP65674qsH4B4em01Fa5F9MPUK39ir+xovTTdprwYV+XvlbUQzl9biNNRoTZrqRHh3veve/f8R+uked773qdxIsLMObfk8fSyrzz4vF79O8pLrNOupqKW8V2aAgdo/T3GT22KV7r44wppxvyncvMTWHk/9u1r6lFnliwjhP+V7bYpPrWEbfqHQI2aP1GVSXEiOzcZk7OlYggbJJYapLVy27pvTz8Uzmy15sNLi3FmbVq70cGmor8gE6YVx7334feNDChOqjCho3UZkgdmqY4v6mYyCwLlPpI0EhuAgcfl5KyunDBJ4XeOSYhV6fsHmp9WNOuGdepNb426CYmn/qtrHQ0TL0aWImXtXGBic4GbgXReqNydIOm5n9nKfjoJkhRjDFFsbxQOF38fIkxvdkP3yVUU+pffMxYIv+Y4KxKjWUufjUqo/B6/cJGuS1YjNQsfv8ge2XYFuU4E4LPC/szX0YFjOT6EvAX+fZt+PHz4KQrUjgV56B1ZLDwvRer9+aRPx2P5KNOvbgPHb0o4JYDfdyNtL5QajVdQLuHfI/63DJHsyFFXILh+2jahyN4kAwkNIVZrrpXspxUug78Emeksrbv0LKefRCUZ4KbZ7S1RbUyo4cmsA25hlOch0zV/bjCBTD8bt/nZP3mQNjBNnVJPa/GvzosyC7SwXF8Rk51QdizhSUzLDItin5VtgMSUIBgebbV6F4ytsIlCc3/PtF8K1DxKmgrJ5WdVpId5bHmeCz5fB0R1KDtfw+BBzOizIz40mU7M3fIlaQmbrsJSXARObsuDaEvI1AhIbPn3sjbZnp9MTo0cdEsu1u8OqWMN4KOYjUc+V9nV8cNYmeDwvEAdmXzzMb8fJB/4b1T3ShsqQ95O8ZUgXlfBQiSr1l84ToLCH++8rzLy4UVznVIIAGvEYPqq0ZT523Y//WLCPa2nbT0PHZv+OvutouX/2Ggi9rhtX2cOT2o1qUUndRWetThdMkYz1JPyhIhgAvVLV0ihL3MU8Q46691s1z93WSVj8KFTd5qeQzMeLwba4Ek1KW7SCMwikWs3+NnS2F75A0FA6mmH4chboa3McB0M5wghDsV2u1GLV3z258PxRb5kK5czQZPP+qGGvY1HJm1FFyp4gvzATCoFL5Xp3pIA6NoLLKpvMSEmhAKLHpIibMOzdXZSKCzps4OY7kFVpl7PPTrBIz+/ivrGXGmOHt+veTI2tkLNthwkZk1ZAySPPerL/eSKfn7MoQy/X2jd94hpCFfB9ftQnPShltILRzYJagPUAzz2A1fiBMjCSh6G4idfg3SL4ZMuQVchanJVM42RhYzyM4FlxWL6UKSQlYhhccxAJPg1Su79sAVezCtvAI5EwzDNm37/VP3vW39tLovXKFDQFh8irv3e2n1q9kW9c5Q2BjTX92czpPX0LQopCdYwgP2GEryHmnWgGuoecW2OfT/XVCUF6YhBv1KgrgRLMdGViYCakP/M+QQwERt8f16anz8gNBG7Vc1bbbSeqZKbSFMNQ3EuwHitxaTTf+ZkIzHupEwPKwR6Ub8VebPNp8XoKn7+sS/+IEwedhOUkSgTPwlGXP8/nBjQ3ZexqyD6z8o17283pinMhRqbOnvxF6cdLKnUjfgD+I5SJIVYnuo5e3FSC2BdVzEr4Y+wskkT5kv4NWP9Xjax8T0BICDxDURc8Icbc5HH3kF8t2F62ASwdf/GFC9K9XpUHCJ+IUXQiNAtDvMcuhlwz1UCb8TUG/uShDnpXEgYAR0Cdk1pz0XuY+vd6AfzmmBdNwh+Plr0jS2H9Jut+JgbiA9TWCaMUiip/0q4fXlz/PiZi7l36zngqbn8uv+aYtqQQrpuUkXGbYPN/8awMtJvjEuydPrjkOrjUWjiU8w9/gFhQf1IbpjI1BqdJvBkmF5m/rE20gGiv+LHrDuJod/mIhNOxkOz2/uAnSgTn9cgyayNod9uYKAO2yQ8HrQT8vfX/gF0pBIUqexaCJg738wBPzYUjv7Fy4fiJwsMOIHSPxBXE/r4Cgn/XZbNyysIjIvoztb2cLBWGPFoAyOoSe+cDW9g9zs78GVDPnQsGxl3fEFJdstP+KjFL/Sp3LzEsBz7NhocAIN4LTC8wtFhpib3sITrPnpZztfNvDKDKMDc5XS75xmdba+I2L5ZLfxi5kbIazYu5XhuvIelXSh4oz8Bx759LmAc574JXP0X39LWFlyDAJCA3erkj6F1IaOhqvhkNg7yu89LRk+I63PDson/yYy48ZWlHWwhDqP9zvugzrNiF3oMQHsJsEGcUvg2me4Lillnpw/CH2CoOMsGfsTymqm39IkHv31hk63FSuv6qcNjo4v+lBr7chfrviPdyK4YzSZxYXeeBTYszvcK6byyoKCrwKDrgaWki4pNSZlhjEmupsIE6DHlVWgYA9A2nXxiLdFd0WdFNEGpTNsorJtcTAzjj3CYwIoiWIt+RvVwd9tBT+Cpjz34iCOocIk9y8CSk/IKoCLhDcwBeYXgvUgbXqvbBNYe9XNH7u/JIGyVbbZPspXSiVTob/JUTk2VXYogk3JY07eugu/k4n2zQXel0/+foh3n62lzwVRlIY2TpMkvtkeD3HEqoqmqzC8WHv3K837PlEV38Xm9uQutyfYETPfVPDPUV7oPRoqypeNR/MoUn/aRkBj/eJvv/Wf9EWnqTi+hDFRFxQ92EUEBv5SgOspt+/AuAtRz3lEy2D4ZqFHv8+809e/Ss9rI+t8n/iP3UW3zegWO7/WjVoVpsmhXlI3O9IvZFWinllOAHuEIh34tmX/dtA5G2KNY5T3MnwVzFVq/YKFBnJuAThAwixqIhCjDiSVQcUyh7035x9jL0Ne3L1w3hYc2QWofPxg6+ASwMJ2nNEIBZOkb/ZM045M7vCKgwojhPQL9JNl3N1hF+dAyWv/96GdNd4F8BehwXBRvac983U3EHEFwXr4lHW2r8Oq/1U4NFCjCXzkTjglwSbi/ersMlb+NWazVwbDaOawLgB8JxNNya75v18G5HNyyzMKKvuFVPQZ0jQjM170DOV3hLyg2FreAnu7w5nwwd920LIfWEWYuw+USi8kDH2UT25qe5EEjc1zKc1BODqxeMaJO6MVpGUhssjywX/PDjsersh72KbgXIH+99WLxS9GIWThVlcQVMX81qtvWrhyUInwbkcKPcC+KsrJM0yKt6h1pdC6sh6MVuyO4JiMt/LQs4K9VFeEbYM/QDRf/W1mS/GAlELJKujB8soZCjkchSB+adott+Lgbe8KYgXWCODkv5qFME3f5unJlVUlhqWa9kO0j994xbsiB5fw8QluTWZ2w+Z/istZ29qLiOfgrXE8YL/dUAFmXbUloo7pS+d80vXIAaqkolnerfJbniN9C8J33T7N0dLXMvWrZkr1C6lBHYgnwzkeUuB1b6TSqA08iEFz1S4v0qh/rK2saVswVEjBf9Q2bA/S7JsLuTVU/Axss0su+ajz2IeP+lfHGRL/FElNJr0DDMvvugRtil7fxyv7cYUtF2Vz69TN9I3TL8d0gNmGIvphsjvE7KpkO41od+PM/5r64bV38EHs4F+2Q7r6HybpiedqOIG5g0O9QeMLLIV90H2XHpiG9lf5dt237uAE5kIUpB/lP4YiiH5zznOrnplPFeBLKQcI/hKOVC6O412rRO/ZBOrKqq7wL0TyvGiazpOkY9JS8E0Lt53m2eEyEifcwfOFJJ0HL+ksFTzTccQngbLXu9XRZt07N4YoTeVzK4IQ4d4AzRLbXf4/Lf43AthlLA0A93kgjSmg75wGMFyILJKBwQSRZwi6IUPu1qcPHam59f7vl9U4Tlkg4453GGfrMeeV02s99mIpppnK5tnf33+4SWUGkm5LKiVqb5oebWRsqLW2lhQcFHusTjS4TJqx4WeelmU+bVxd/tMYo5hyTpwrq0UNK/+CvRVVOS1J0DtyfVCnZWb9jX2CNq8dPpuoPf0encFWPD2FdIy+clHuB3360//+oHmfGuTtTmee/to3VMYKIXw+3hzN8YrSc8vHiESc+PF0ViXmKHMSuiU4F+uzYfvdBNCOM4CGQV9/t0HR88JxDIvJx4UnUjHRgsklAR8hTy3b35rdU1EOGgGKlJkKxRv/i5feanqHiZByDpGX/oDfjjT/hvHLwBkYr0ww//VqwpzttABxUHfh2JOj/nr7neWCOa+AsaJVx8BwrSMNvDVzIAbDMwCskjrjR3HNhMeGlOe/fudmxaK2+J44erLSGpOPY3yerNL5R2uN6QzAcMLjQ4z9dwkwxkK+lJytVB2Iz9OL72HLIu1bsIIEj60eMfKfXwfi/o50AHjjq212f6QY9paBybnbPjsKHpqE/F9rYCUV3V09umQzB/h9o6/hBc6ny/MCVWS0WOPA+YqQphsW2JiWZLJfT4f+zn8nOrXxIoMmdMv/CBBLdA5sqg6ScwnpPrjtCyNgWdeEw3y+35AdLUKM/tgp0Kb7BzJvM+WCs/JHaPbh3avUW9xh8hVYc5BxsmcocY0GL4beNDlFIusqFR6wkGejMeEhqz9h7qQ7urL59QtneJPooTiFkC0NVljWTMzVH/88rXIiPly4DlI/r+qSIbKwfIGFh9q5mTVcTUVLTDCk2dKmYEmPtUxye801SQWkb9fNQyRCI1ewHXMNcNukbsNz1/Z/YzC2ffs61aRvgcT5VmO7wf4Fa83MWfdGJDvL9M6G7l5VuHPKd974VfHKf6jCIPxlGpFMMJlW7uX+Pe9pAqdI+mEfB7j2V9jloCrO+5n6/ATbJBl9x3u/upTOzy2CWqeT/dv62xW0Av7rCteiE40VVoyc0v74X00ztm5gj6Nl6OJmb2SJZN1bilWIYp79G/vAO4cyXNwWrrEWayE6R/e/UA6rDVe5GazGUc+xXdwvqJDb5RtTw48hpuJCaWoE7pZya1u6i+kkWbN2zZUuUu4tXzV6CiItUgaiUTNtGT2pNmfASXnXAnR3sUnCoighEPn0KWl3fc2KLRE4uMg85yMOKuwcigQsgOTgdYnW7moxFXFMNSU9sdxKLqluRIjkBAlvy/Qvjg77+TfnEaAiDjCWPWRX9mXKnYwplCw6sSk5GcNfSoK/3QHqAStCPmmNsw98K0n+xqPi68YF/oLGQdmqVvq/2xIZRX/jqQ8hQxqhM90ycBJ+CYQjvmEnpSRPD/HQgJFDVf+kbHnA82tDf3syxFEOC+Q0Sqtr1qpfd7dj+Frq3HYGMPwrLebIBkh8FTQI3ucjUQGVCawbsxkqzbbapf+NwFDCIHWJ09VX2CQb4uTddE3pLAta6dKqLX2sZbrv/9mFfw90qXs/wTLokWFW2OxFmD+14a7/JFnuZbLX5zJCuMqsgZvw4SSBYlRhpF1LaCKNZkDLfwXSvickZ8gCIXuj3TkNPkct9cWGrPr8kc9nGHpq+FGoYuAyxyTjR3CdqkRQFn3Kl2E22nSgy2rEHxaDYg1e0yKhzppqugOGP7+BCz7+uSJQ6j9NYwFIQjqK3GfO4X3DUdt1atZl2nQb3NyB/Ekn81N5sFIbpIrwaXmOHAaLxONBTvRvtuZoKjk/vU+JOCUdSLRc7YAbXjsLUWpvQsCSNCcUDjKv+D7Uo7iRaygg6P65UvHCd713wRgXvEXR/ktq6lFH68PQ19zvr/Z05NMXIKxTY5ypYI7qx5JLvrHB37DBD+6m9UGKnOTWTb0zx/GSHRrGaAWjKKjpV5yOnsnTEk196fiRc80r1PUKhqKs7LjBcdQHzr+mftuXhTz1yBdWK41OBEUG5CLAd0+lc5fNnb+0d+t8VlKrCSexWHJx5jIzgcsqctGSYtULxERlZYGLZbvGVXnrMpGJbyk4/0hRo9rsez11VhhTSr4syuP3PoZoY8ocWyJMH5pN3+NCqmp/l6bFBjzibcfFaarAKLPDo+MFXhhKtrUqFt8seRsSzYV4i/m5K1KcQ7c+ykbbwUhWSQy/SwXP5Oh3/1sJ/cabIaI/5pvtL8hWv/+7E9XWBwj9Fmh76RvRanyXkkjeZkwktAl2EwnkFUpMPliQpur72a8+X0REwEaHsjiTslZMrTZJKHXS9k2BLAWZozyC9gh0vvjV8UYBgIQe1bsH3+mP/MqHpjSoESZPucVoPjFSTw+xTWPb7RWwHDevoIDJPEx5XzosZvakKI+8dloB1yn+ZCZuBcW6/A9xKCJwwXzwgX40hPEoIg5SiizxV9mU2UDqixrtv3yIWHG8f6Xo6DXID6X2w4tikpzlOJ6eDEwnZKWqVLb/yao0QMxr+rs5lkG7weIhu155r5gxx61kRb3gJZl1ttT3kUdgKb1KxVBt6oJ94Uwwoal1Egi0dnyPum7KXbjYbL8OAaB25kCNUn4LntBUNg+KwKo8QSqZtuLJMbbabyvr8Iy0CufSru3Wy7/trXJdv1k/hG+QhrCZXvr4A5BOe0yMNF46APHQcyaqK+/Rblf2s4JYcHQ7kDNB9pz6myI9tZmUJgCzHH3BrxoPefJjoHszkdH6Woi1iQ+ddWgdelL7xLMgJkcsOmYyVQXwk8+xxB1fP8vnMN5CXbRrRNYh4Q6WplOGETKNq6TdAtPf7s/uRLR/lZ5I/YX5RYIEitRZhe6QIpAfMBVI5mWpfo+q8ib2Ijm74AYTR3G4hhoxBYw5+5BSMrQCh8jE5/orIQjRkzhaXyJr95XiS66qy0IaGnBtwkaI+sS5WT6frGrgoAKiX6udVcN2EjHnt2fpjMAenyWlZ4/10en5cv/iN8e08Lt4/4svvhI41xi6YTORGKWQmzoNXTcVLxD4ve7yCBc/X7yE6olKAdtuceauvKad0H2uxoOPHBQlFph1ND2p4H44qvT3LzzkxbY5ayVOvMKmWHsu77Epr64+1k9YKuwJjHSHM4rqL1Zpqz4giyg8zPaSfT78aisj8WWr/ygxtNqtSf9W2v+gi6+Idbf0pCfBcfsHTA3lqOgzJhIfwa5i4NuePWV1Agi3YfYzjccF5FXhP8QQDYwn3MSH3jCyJNvZ0JOT4cXV1hi1wIRjW0FjcgsheUN1MtA2ELzUPJr3fDLwPOjMo6+hsw3Z7mL3R5/a7a+3wavY+xYYWHkksy8H3H4anEJnVB0BJVGGTQGYUa+NrIleg9NMUlQzn7R334UOndaL8/5mrtjaZvn6kPJjck1TANhJ2bXD6bt08+DQBrnb07AM5c0wc73q2V16TGRiA7NgElthiA/3ik4Y0ho4gmljC2Q/ngqIgr3XvXEzsNy7W8uEUvvah20aDLdfw+6qc9vdWIS6eKu6WBkLoS2rtvjeGric5Oa4Y6Dl7lsA96hHgi7jUT2haMvx6En1LG6ePBqOpkzmyQpUk0rHH7cqJDOm6JyaV2J47h6jHxg9NWWfVRHm2krVKqLdqkU0XUN/pTg0L5pHVy0HbjQGWJH0xxuoPqDtYIhqnjSkJuqIKi9OJsnTqnH3T8ZFesIJgNMwYa28eQ4Uhx/ZuVfCaIGogvpt1O7yhzSIJpiwsoNsFMtBWejQdjNteBJuv2goDfiL9jdNEGgHv43XBar6R0NGMTgEJTyV/r+HQZ+uvqJHKmYWpaEvhLDP5JobzahIqsBnm9S+mTfx1D0+/mTkEXxeH+Ty5ul1iehfaGBHH+NIIaDjT3acdYniIpyuSfITtPtP0BkGoyybz5/4e6XZwCkMT+FItB6xPWLtKnYdd2LrX/ezyXVKBnP3+kDX+bPA+HgOO3MDoJJ9PUPmjugc6NTCFuPHxmLdZLLt5A4Xj4uunry4E9TLEwNoB6KNK5riqdzROK+yQBZPz1RRroHpCygO3ejbJ0hWmy4+RhSHNvKoHVSQ7nApUKPS3ZLMA4/jexqlbjEQG0zWD70cRSSCwFYf/sn3H9Qx4o+lnzjhzicr16IALUyHWVw90vInnnKsAidVAgoCPcRtO/7sU8LGywy/DGSwpWZ66V54qPfE4knmJE/9zlo69ermayGmpEWUNIgvtHfmDUAGFZvJ81+jwfb0qXEXichMMNupjIc/xvqIbw3w2sj4utxEFLFRjjl2ifZ0dN1XBaJMrJhnhavXIbhllMrPxeNy6/8b5zm579ETWdEPVaaHKy6Z0+6uugojbTiFY6JichkEnAYEtx8miz2BBCmKYuqEr8NwdMzeO+6zOLrQ6+9KOzBOIFhZazn+YLn5CxGfxowG7HAAVxtqPjzANkkIJKb0bxfTPJ7snJy7LYKmNuRufoKctb2l0V0vX5vYx7gXZgFGSNxfh7B/rD1VWxBOO+7OvWQeBgD6XlJKXqhfJjnh0CQ+tPOpl13FELCO1VswWGR39iAOxzBUFobEWTZYPxyugftHp/G/o+l69h1HdmBX/P2ClZaKgcrZ2unnHPW1z/1uQMMBgPMsS11s8mqIpscbXDhQlhgImtgoaG1b4nH2UJaIzFMRl4cTpjFMaXIs1pN2EnFT9IRBkpe+/VuVdpdm/9JiKmabWMokhN7+U8B5/jageHzfn/guGHXswxkb/I3SNjhGo735Lnu8oBLLn5EXTLNrQZc/82j90Fhq7Dcbcedd7uj82e4nmHRezc7zAeUmLzHCpwlJU2hUWJ8wgYd5ci/3A9EfaQwJzkHIiYW/2/GgW3q8FdlR0MC4E7XJyrS4wEEu6kVVDHw4In+1hZgVjLxsl0AzcigAPPJ1wUHMxMFET23my+H+TcBbbM1uh/Zmrp4SBuIe096eS50+kwXug6ZG/kHHecpycn4RjbsQrO1mN5/KFqm0RlsNgPM7YManek600M+lKhCmJnqrszgQFEESgEpBVR4iA5LENuQ9c2LroCyB12dp/jnXf+LiKQU1dUQaISa/OU/Z4hAs/fshIzF9naBuNNNgdHRqqti16N5xxbMOfoFgIY72ZGs9wQj8GesUnoSnU41BltLthxQ8Dp1izUEXAqbPxTHE9oL9Sn4QjJmHN5/pWnoVCB0b1J5gkfTMgHNcziOfsH2E3Uv/p01Bp/eIGJSnGslC8p8mHCyGC+Vk7n+2qSKW4S/K2842l/SopTLu/a6v+PJCKuRgPHCd3xPU2oIUVhw83PJ/HF+y+roDs69kDzMyOcgnT5LeBrwUn/13LKrEYLWEmsTepeZDLndv0AK+db1RI8SCx2WyhqbVQBKJmS0RsNh1/7YHNrq3jslmnGGyFDk6AZZr9evjN963a3jr1aRx8wXh1WEPeZxLOeTjci5Erp1rrOwiUDi5lxQknkpuSY/lq8cUqi8LcxMAkS0ym7curiCOxNOIEzjtis65Hda7WQrghH+LPX35QFNi0gqEnhn5MUgCi3TBU7G9CKUepqhOBq4r/b6sVmUlIO1eAltzntXPUwtRTfi+VJW2bsJj2NBSOXx1iBUf2wdGaJCCPCtVsB0mDEwhwvVQ0r8eq3m6h0RlzYGRb4vuFinXwr/erVn3AHRxwGpaEbsQYIN5QCKlKh0kq6FHDZj/nWFWe7aKsJc6IOwHOJS9n6WGsDVaiK6OhS15Ebror3zte8ZuNh+y+LB/qh8x+2lC8BGZO5LdhLhNVai0YmsRIp0HqchIogUbed+8syDkwlRmeVh6B99s/tnaO6ClmBZJaShknQ3aLAIMjkJaYpo1/LeCL4dNV4fR0IhZNinjjwviPJ7LPIfbozY3VzB26nzcBFwB4691LnJhYdigj4luu4EjMcQJHmU8DmzMM7GDmHVFTu0dU2kyIkNzC5RxM9+azLguK8DDftXv/FbTvBt2RMIBrCjSnql6rOg+end0fcaGVud4v1jeEIMHFqafgsTastOEUO02mIPpMWWVaMGZ9gRB0AIAHwm1j/19Apfo28+d57joqd0ByQM1DNdBOS2WYxYn4MXuid1L6CxpcyPVIQT3Un0eynpjOiI6lcfKiHzoiVYKJe5DljYDewrVbaNHz0eOJbp2vJE//eIQ+IOebtBVWweR19/rBerAMmC3V/Qn+gGF/drTe7j81BEu5Gbs2RLLOPl9yusRV7UGbU88l95FXnur38Qi02wUH01T9PFKs71fTO7nY/fYmQq/hWA7/bdyPx9t58zxZyMAriFn1WZyinqe3nIS2yIjwbZP3Xg3nAWbvV1YfkeyCv1NwrsDL1pYU3ip7iVwpymnEjJOp6Q2FSiRWTbTee0SYXsD/Y7Ku6W39r7KMBngAiCyjXa/Ooc24KsrQgbBOazRywScbPhYIKrELDaLzuQUOBcuhIwRTdE/mJUbBX8lhh1kYgqvCiWpiHQmCQOUG/+jI77w4OxZlfFQhUefpnsNaG/o9mPM9hmmwU5xQARnzvNHYfNQot26lS2H7n8jd/teJHPXPuCBrdDF6kAk/ZzvqoebKZh/NcojjTjIT/uF9WiDM2E67D91yNDI/5a/As1nbiraUUrFq8Qen1NlE6TanxSAe7zXtZtlPM1WTfd6N/GO+c6hmGlsNwHhKtkcv4yIwzLj1GR9/rL6vh7QDMJqz6uR6iE7uZbgEqiZq5gXLaQeYLnd//EGwZDoCgbDmj2IR/tuX3FQGoknpC4T1Ro36WBEw95NuE/CQPgqDxvTnPpOHWHLzdAiZfx4fpzgsORmwbHX5/cePEmNsJOfMMN5t3V8jftXvWgBN3AK9z50GzPbxo6HMwG7TgZxzG4cz4H2p3v+hNohwI5rS5mWeabNxT8DU1LhIcqcGeBuP34w2wtjI1hVgacYCDfKMMQy+v66ejsez4UXD5Mdd2U1ciF2wh2gyy/aueli0OnXL+NWsNovAOoKE2Eeov5RnJYd5+Vldl8Jl1ngp1owHqdxYCYf4VFafwDlnyl36Vup0LXdLzanTtBUYJI9glBiIVf/7prIk+2oe514avkOESydVkhEeuE5Ma6ERLOMlUTqMNOPX/3TBNu4brsi+rLMCz4vqOVQ63eueTc56+f48oeG3vkNo+dqYm6BFRNBlpbkaAXkTZw9aA9HvjZ6Fb3+pHBiGNGywOI9oSPHxwEiLM5BWNuZRSBGRi6NfT4qKMje4NubgDa/JjSOBE8XfEN6g8AWabKiyczBx3nGW72ZlgM5SwvDIKi8X0zF5Bh2xBVW5JwoCc+HDrSG8LEe27DWCFXpFP2o1a9hP1kvtLdvrbCpdwFJhKq7oaSSP7iIUchwWe5f8QBJolbJTEIpBC6dh0AfZFRX8dg7lXID1sr0Ybjyw/aGC8qlLRDJCiyuAtOUohqIYRfoS1fw3efYNmG38cE78SWNsfOpe+ks/xsFYCZczqWLCO0I+JjPvEpzwUhuJGmv6xYud+lWL/D3vrjEukWumhKdoTqabzel/y0OuS8eB81EtlQnwfpkfXJREzAjDT4sfjX4uC4DrBN1n9XLBhgO5YBalNWi8mElB07bpyB/qTy6J2UrdwzWD9KOHysZaftJD8f/Vaf7rqfbdjGS/6iCev5SLo7pd18WK8yJIJdtZkXVfUCV49N1PylIHmiTj2CcqLIyE+7ZQU4KT62WUnRE0lbJNfz+RNgaZ0F/XCZvYvQbBHCsAZSMUlwN1grDPiqhcFguNgLwYefFPiB12D/BtACZ+E2cAQXhehrRTd/J9SACKdqKBnMZBcovK/CEPijvEWdAB8OT4jmxzRiPSIpGQq5+dyC16f4B3f9Xf7uqgVliAnGtw7GES/Mxnahs/2zhSZxMeQqcfbjAOFuoIsOrtsBHRIOOUl5M4vr3JVnCU0wZQWeavxqeGCleJJTJJWvCOemQ77EcNxzE8ASFU18XHiH/1omNqkehNjYUggXO6Lik0Dy/z5gVQ4P3wq2ZFYU7se+5zc/VJVRiWALlOk4U7SVP6G7g+XkOEf7Fo8HinwARBFiwKSYGuDHIJ3X40DPDx82MNasR+GQxGMb7vL5obNxfTBZQPeSo3M7gwuio6DPGXFp63WCIwotAjZJ50v+Wx/HI+w+9qhhr38tkgiKUEMXCqKcxU3IPqfyDGiSOeBcT1XSQvMBFbSgOlj4ayyhuTEKSP/RcDDhm1H8fSphrDrg9W4FVBTf5UBYQMdJ/0WXxk8QZ8gReT9t3DQKPSAy2k8cy87NcJqgyAkidVb+67CbaFhGGQYafH59VHv7XuyI9dOUOYNtmNm8rf03h1zbn6/CQicege2YCwgVvOO3XxbTNdfFv56hSDBB7+0/bchiXeCxoMxR2mrnGF9lpyp+43ldoeH6rLAE9I2zD8yDSq6KPLPuXByK5X4wI0Usp3Rq8/lL9/n4ujBM1N3fY0/dGluYU33294yJPvnko86Kq0ioseifk6FYX+aHyZCcadxoJmKajg+utIqmqnUplZEQoDWfkBv9E7+0+vI6xzQwi6aeDUWiXKPVCnEYIDvRdH+SIm2SEu9N75taHKIUt5yz96p9QoFlV6Ahqw06D4h+ITujp/3fSEadtypy8mDVOgS4+MKhc9IQ0kv8F8CbD/9buSVD8BErNjBSUwSlDkVOAhMYzxj6gbWzl2Zteo3HDNeVz/yFH57p6OAHA2GDUumweZr9o/3iCwPvCnzz4mEOaLqTFwfDOZ50/4Wckj2ULVFQ8CuRTVPMyMqu92k7s/g+ixVDMB928Ge2F0Bc9IyqFv/lcgCrAc7nYDKZRl2ldtRzL2vrLuRuTfpCSJUtfFEUgiySdKJOwTE8zwUoDC4XJRV2zh1giuRPGkYvl8C5ri770HCYwLALF/0Zi94QCjzIlhdmkpG9dsccOMSmvffdDEu4urzx+BCr5JmwJZFEI8yMfI8FWFe75Ps9ffN5qsLPWGdVe7JITRzuE9uA207whKw5QUzekP7DVUA3PeyEbBQHmPwET0C5i1mRsi/UQzP9X0dCIX932Rl+RoGAB+4LE4n2vxp9myGDPk9+f2zhey1hvkVHGD+nyfMVm1nx1ZrLWXiqLkw7aL+huQFyCbp3AAUDTs78Ro3hZZEL3albdnxWkdfjmnIj/QQmjpHYaAHh5dJ4ZDZNlUdlxYqCutT+row+vWZyxMEoq7/fczbmq5hRxPP6Qn2mkE3iwhoGHmKPTaD3C5oKSET7K3ICgvUblZCSM1/SkQJIEAk/kIwROv+JwQsVclhYQknocLjww72Lcs/L57UIMwr2MDn+CAwJGYkWjfsuZjKB7W144aYzI88nMQi0sMQyidIXR9rH4HeDsBova0xJ6uCI8NfIPkF8oArxUwcjFie9r6rq/4jp1nSyvQv+jZhKnoe4diLxghed/XtIg20qhJJdiQzP88w1XMko83HZ03ze75EyVKH58X3G4mUZpyJtlm8vV8FV58hwCYjcXi3QVeXx48N/955HO+pW6cIDh3SMa/dHWTk7fxuky5mXfVhYvWDUvkpV1tLKly03VTPZBU6qq+dDoEyVn+kvZoNIKfRm8zyoNZJZrgvxN7l4tpWkx7ftxm15G10ccMWs6nB08VS2/hpq8vNbK6J7TevOJ6PpTzOC4lzQhAvAblP4awrWMPPDfcK4BMJwFsQ6kPAZhxjhy9yQxwJ/2l1XbAUsHEKf8L6yEtteWgdRJrVKRFMGM73yXbuzWE3LCBSMWYnj4Y/ebb7Ux9dbbwlvH7aoG/KXn7gy5JlWbaqln6OHbZNZWtHS7xYdeSkGcRNMWrYo5A4ocm1qy0iFlxa/YArdQARW9G04hbV1HFgS9VnqykypqdJqkBCRyC5IhMkKOv3zpRmE2OAln6A8sZzssK6BO3igRYcGvZAZYZI/O89y+G8c8BoX7oFCF4VWEtDZmaBBaJSfnBxHoCROSPxP1f0fuIK0fLYbCwKK2TIYdCdl+E3/KsCPUmoNDrwSPDBC8UGor+4L0j8puHkEOKEZucT+HlZRdFcaXDOkHc9mfFGqMUYktE6mNo8ofuNVwfvp4yjylwFOjmfoS1P/bPrfUyByVM2RMRSLvHkM/yuODsYA53B29HhfGI2zVHcGrEFuP+7+OtW4ip+hwQIvKQTCtv2H9RdqQ9xW9H8LbO9qBkmMgFHJMCQ1Cu0MxI0X9Aj6byn+AFMEbQzf05Fue1q7aWLoSwzvyr9TPj4k9FeBjIEe+oIBn0GlWQU6CDcezxP0N/UUEA0UXS4pWyfnyDSHNrjX4aY7QjDgwhfK2cm6F1QxAXUNZI4J+C9glyD3m5dL+HA7hJtfQcE/l5BR1HVHrPs3tqt7lAc59xwo1gwQL1/OQ86TS11nMt9iiVnXYYYGucK4w+xZq/Rkvtp+9GRj3PmKHXAMzBZDmNZqYQ6qhmCgpv3iiME8CpTZiN3wAfDO+8ZmeeOQXaH3+pUyAoJeAqZNsz0YWfjFpdxI4W2PzpqDkoduwuXJX4hkrTquro/81whWbn+RbdsjpaxcRRu+7w5JsqE0sK0odo/x4/kBLirQeUIvvLk6mVvRUKPzl2a8h/hjgThjdYbR8Fp7gXXFnXZf+jQiC1i+U04MpCVLKHeNq7NT38+mlpD/DQJ9SbzseATz86T6FgkpaDJTTa4jJDuuIvcXqhEkGWeiOl0ATlrGRfkJtnYzYtlh+HjWRpHpXuAZkkCZwSsnuYYDy9uRLSkxP31dM200pzVdQrJeroYz/uuwoUTYWKJunJT+0LVsBfJPcLO/KxTFjYkcMpqPsrq7I9FUZQdyCVwp0CVrFRzMGn45L1etqVrm+1GAuiWAQ34Aubhsijw9UdKWpH7nSgrc5rL5uiQfXHZ4HeEpMi9qNB+PjR5po0KDH9UB4pGNYZAewDETlBKBbIOwxIdycr8PhiwgGdUks//hDkW3fWMBFqlNav1syb63jqTGrHKRRetfie+82BptwNvQVMi9MV5xNwf9bRIaMsBzIzV/2qTWAWdLROPxNwRb2CnE6RXI3RqqTnxiGmAcAx5tnTUEXUK4sak3AGMUtXTooBal0h8NvGe8ka1IxqGiBVdPwZiFuTRLNJliaAYvg1glFKQH4Wtp8bO6OcwmQQB21IE68hTE+46ldtQZyLvbQYShMiS4APbY0eYDLf4Qf47jDbnO56vbheYP2IeIhQNHc7O+CYucRIOQcKELst6orr32ITwS8XxfXCOBNvR3JtqsHp+JyILNjsxCljoGFhGuNj9n+cYfHaiuPPWrisZxaHHiGc2f6Bg82ZfUz0gFNyqYOqtn4LQ8ioLSGCCLIzZfdvunX7aYanWyKUVOWHzYehb5Cf9tf9dPCd2AFCnTsOHp/JiHIdDkXgD1vU81eFQKGU+m9fpuw+SJ+a/RPYApdrJlK09EUH8TXBwLELMoeFnzCC5rCPN8oiGvCOEwYffvQ0hJSJLwboT5xyyK9znc8/3BqXGnDfYSxhCKRdpF+AuXy5oPEkxzH0dyJ+xCiAfC1PpXZ74Sk1VE7n1Mnlz5qGayBEtkcv4MlzT9wnQwbluQ0PtJDXe9tEB6MRG/Sna8sX0cdy72uVFkB/mJIT1uAMLJKIfrP7mMhjjfoH/vkWC+3rpJyHC77aTa8nsIto/e7T6TzbGBEsVK57zCTY73y40DucRCAPypPfRGL7jA5BJbkTgHZRQvr/Zaa+VHcOCiqfb1sOASo5ooLDCS8632xbmektqfQZUPFmRSfclO2hDLff/L4rvFd4phLQB2Wi2/7eLPsijgTw+QmSJsMwZ8mzFJPUxeJogq78vOqntNnxQ+SxS3J3H5xtNqem/ofI+OuEVQAREDJOZDMqW6VTAWi2fBrBo2Zdgu7VW9H7PfNf68h+bSPOxTSLzsapRQSDtiblpT04tpd2E4rJewYglTcqd/hidUZ8Wl/rkmSU6HAZslOkGMFwkvFCLbx41+1vNBZmY4EBzMLhK+6gE65D1T5dVhNZpcOfbx68hgx6yJyEc9l2btVtltbQfE+WuWqglffaOax+1/griTWP7E6qs8R/dT3bBYRmKJdLZxGFsUrPCCyodhcN+YxN5XVqL78IbkyryXlLzMB/uN5uyNP3ntWuyTCtWezjIxt7mE3O0ArMhFihDunF85x3isfYoNBjkCgIUHDp8PvzY56M/XF0PMIfGBSz7Ikd6YClovCTZBUxkFIao8n7H12+JiM84/tlrWHAgSgh4cAZrtd7VVKTkI4nwWEobi5F9Nx/vHZK2Z3bZ2ewfDO+SoWRu9oAAwL+HzmPV7IItwEK4G6q+GAzlFX6htEtjDBHxA6kRf6ZzsTLwJQbvrcV2y8STyztwP2pGuxzKfjYKImRVB3GCO0rg7kKkZiBSzj5hXbn9QxAvHCXLOKVv8oMlq8o++KvxLLsiPauo8W9c0liQMBODLpKT13cEcWamr7mLgVEHqDGLF/JXaT2f7jj1/j8tTDAd6Cd48LHrs76lvlqc0PZk6NEkzD/rWsIHtg8Vyc0AIWQILJxkU2zI+3rVvZDrhjnRj4Q2LZcIiH/JDhBCCcJwJz3Z25E/awL7O5bMXRbtEUSSKBOocIWo0zNQwDH9J8qarzQQWZncCItKo0XJ8agQVzMQiHcN+BPn10W57ysgVGfrRhoQW3bJci+sXoBmzlKVJD5eNIW4Z8Yane4vVW73x3TD/KtFnwOobSzqXIw9cMsch5UG3ohg6LY8utdkw+W+ujQWtfwWbzKUxAl4Y5hBL0ecDchWPo43H/DOun/DrL/m72edBgXIQFY4nsDBr7oACWsEN9JxFWSs49rP4tNy2toK/r7yU4FmvFlWt/KoxhKZ+GAsEQwuzwOLBnZAqqY95dKkmdAadc8NvdbN39dBj/qsb5Ctgh1ovIrGCBvdMYolgk+mR38+yEYyBcl7vZCkGFBlWYfSJs6Fok/RPIZpr+4WJts08ksa7yXHrxb6LNCcpGJwsqzFmf4TxMUKHi+A3vAAN6JifMHpjfTCfUGu+blu40z7IyTbykr+i5kcYYTl8/tPBPg6VYJjmXCxtvx5XEsSRvlLZ5iA4imId6kUcjiNHm27LGKwzqWTMWypYE120/oRS3E5OXMhGN9usFtOOy++FdA3fYUDDpNhEcB8Km/6kPNIb6afxggbfKeEosO+5EKIXTeOO1hk2QVDsK6T3NzHSxaDhfZpieoGpRrccslNRlqPs+7bsGmd7moeHytUj8gJN/5zW5GUYUlIlsLn043kdnAAT//B+gF2J/oaidjFcc69QonqP1YhWBo3BrUXSMnNLkPu6NfgqQHEjE/kHG2EPkTymAWhKiDbqvtYkFxI/p2pYtp99yli9DTrZAejQU6HSo6+uJlz3QDL8BewvNQVt7SYX/1VtP17+rckWVtZRpEBob2/foGd+GIfqyZFBtk69XqBPp92+W2naT8JTVHf3XqDwbQ0I0QU9OU3guMG3T7E0oinQKAzRNhDsNd8ikedltIsXwuZhN1tMi6TtEzb/ZtIIQdc0BsVND2cBqwsrGEDN+A7QziZV4jx7xFfHfHuZkfSs69JMGvU0qDZJYu1h2CGmv9KMXX+e50qZAm768VFqdwosUL/VquD2PDwye1cvC77U1hTcnHa01Qb+ikA6p4OO1VhCXJiCSvKvfboLtGoKE1C2D/p5gRZZzPssERipJWB3jxCf6UZsRKfczGjxxQmFGZnVb02C2gGmJA5NHLqCYINEqUtEdU7caxQ93TrkeF7c9rP1hrihSTXBADRhf5GLp3+cuE7/FDE5sJlau1e+lL/OXFLvKWvIuM9rIHQJkAJcyMjPf3PQtX6k2GXp/oabeQ9JGyAusS8AT6I7QWrit03p39SZFdTFAjS7qHRt7BK4JyjAHf6TYQYe0edPGjCcOZCUIEASlQPqZfZJ4yB2cIvrDIY0LqliDRi0Lt15R0eSkfIsbuqilvv6KU/jX8jxwAVsf+s4Z525XV309K/TDVhQ/h6TduMFBHlAfZ7wRUYVFH9ZXDUiZHpgjlMGam5FcnCuKvn99zED+lC8WXlO5/scQ7e8Dxmqpk8N/KhnI1m2LEycrdhdZ+c/VDc8tXR+k+SNozTHrRLrBm5EM3zzDN5eVqu8fC8Pf+7E/oZBUU1ccF4WkRq4KczVP3OEtH3m71tqnqg3gVtIKZjUCpblG9MKIzefNh+ZePmabOa0c1nslDoJDCv35z3AJwaMRQGKMGKZ3kyfUrn2AuUfyQr1yq8AYNrdcWq0ce6l0JpsMxRx3X7yN0I00wBTZ2hH1VHMAKWvdT0yVBDYBgfb1ydq812ZoQ7Pdit4Y2izxX728kS527XM8P4AYqvcQEpwIWQkIk+5NLOy9RFLhBd2XKPo3YOrqOi7eX/4eQ+LPsz2IyEDWBG0pJecK/L9X+6/VPX7MbGKXOAiXNXV2Q/PZH0GfrTf3pWLGkyiPXirsegkX+5iONFVCm/V9ZoU0W7r3VwCHPT0VYHGb0wVHjGE6/5xX18zVNRogeO/9sywzMmIpg33Fa9IU8DHZavu1KkEsc/L5zL+Cka2UHU/OzB9rCPcCOLUzQqJ77FH19heW13YTUlk0IJh1DzAh4f6ropOT7uGmTgXPjjGcpQiZweOACqhcySQpf4Crr4BIrxt5gRFofpAbNWZsj84prLOowynRMJcoJCoDtUyNUJQaG2a/HgLOgb+u9eOLyo7L4WxROWGPjH2UF7qdJKhX38pQFrogz5nE2nFTmTG8T+xOuALux6mIhBR7pmRhIrL2wc1gEmzntTfmCzwlIpbCEta9b277ORMzrZIzWoqwQsBHe5fXwizwSW0ASmpsVczIXtDgs/7tYevlBbYLOSzOnYZtSq8fMH5VZg7tGNiuHmeUitsNQvxN3eZIjA/DTAJ1pUjDFjtk4RReEHn2Y1FWKledb3up8NCqg/d7YBVfyCwG2N5DlSL3fnLqiTBx99zXPwRlSbxgOu8fSbnlxOsbtPFLetdUS+LtO7cmZw0lMangEnWM5XmsfrGmjRoBaqLzbSGgxIFQllbX+vsLEJyZs9q5iA74NbYvcp2uTlaJNrtxNKUfPpvKIdEpiRJhgJRyLBSehVhVBoT/1PAZfYc1th7IjTNrcx5MO+1ilQ7XW4wiHHxBfFRSp4SCRspfkkkPOHf9BAp4foLKCwnUJdJy2nXeYzbmNXI5uu0uejBzovSnVwYscEk0bE1F+z4g8auU/MhRWhaZPnCZBczW+ZmEEsooTMow6onP5DcZAbMQ1uuhy3XiKTEyXzwNNs/muAHgB32keoyL/Z6rThQVOmucaDKBlApK0gKkY6LGqruD9S8e88fkhdUhuaGfM8dpyYmSbe+WtUFy3ZD+3t+IM5i282rsr8BBenWBPPfJoH0VY+A+wADkDsjd9i9boz+6gdVHVwm0kzpk5yEMga6SAm98Y38+TtV/TxNG+7p4iRtibd+4+iTsP33M++MZuBSiU9RzbaywYV+TJlt+o3HLveZ0i+cL88st3zVt/esvG11a8mkqdWj9PGtTL9I0Gd77R0tOwHPtAcbTt7OBe5FU90Lh2jbbH4dJFg6AIhEkc5klP1l1I8EOgzRrM6T1J60+gKB+iKwvxLSFKji1TpkfzY6H7FSII8CdKCYWFx1SxPusjwfgT9pNg2Hb9yfIW+VsaKov6CuOS/VtdwhzO71Lyqh207KLxs+ElQQqX289JP88fLqqRLQKEkrf8ElEbqdCW2T1g8Y6v6FeyDjCqUEwnScmYIfFSKzpJn9a5g39rLP/Qxsdy3po7s3IKHD+f3Vml18HGuQQdqrVUnfrdd3M+M9KMy7hIKXPdOYhoT2yyKO4wtiVmiT1ux/SOpw01BDjhfUmemMROTRwEdsxyxvQb5Ze9mfCwZyWBSWxusC/kXdb0Ycrbi14V3V4HVWStjDycLfxQBp2IT8RQUSTzQ/z5y3I666ELuoiF5LXKA/AEP61G+CU9vpm/QCXw/CueAcX0WRySxbF6ZByFP07diwoReI7cRS/Kn2zEm/KE+x3Un3XNg+uIEcB+51ytPdS4bIqgT5gavjyFon+8zCGByi+tzwyJHRCUXs0y323m1T+WIaUek4zph5yVZ/aoHNNKFjBC3/QM6QIJJvQRro5aJyakxEJC6oif9mg/DXynydi5toT6v0QfWXyTdXsAiAGcE7g83ow7suIdlt5GaM3f++0Ga4bfZr2QBO9NFUoYTpEMiyI8Je2MQiovB1gkEFMMN194wNfD1O/8aEDTYWmnUSamK2nr9Af35xIwRV66rW7fSlZvhLZCX5U30EoX+wQqz7HspHdSu6+dz0lF9ZdIR/ucBIhOYvXb0QrAyt3hXbgJiUWRQYDukyFB0mFIYYcCNxAhviHz4xIUsnJLfqweIedMcEA2+vhVneTnuKy8sc+Hxy1yO7I4kW6I2j1beEqbRvciaWb/rUfahvKYS6R2/qYey9K6yfkXgAhnnGX82hkf4icK+gcCz/wUIO/FpWtJLzCVjrCoxz1fw0jnvF1b4cokE3pejM45uu/8ikZRnVx7bs/KIqQmBXuSs7TQH2SjTFggfJMFFBoi49jFEIVoL0CD490Qj4JbkyhZmSX44j4CTpF7HkwTxgoSLxu817LfDd3K/BrB5m7h0vsm58U3oSywtOj0fHLAibUQ+U2T4j+oZ/cBAdRMIa7OzrMIwBEYf84a8hNYwlhpqGpOKfbnoc80IRQqIPRcqW2qG8PLleA2IGtZb5Ad6/PUgb3aRc7mjPLWnnczvRePEc0jaD2F1F7vKYKuYn5WFfGkwqdk0HhxFpJb9F/yiGDX6caae/VqzsoFwB87oHv5E47/AhtP55x5Ms3OZPNQTjWyhJZ9gmxwa8WDvWpDGE8WyGl9ptmm9rNMRCsQS4xFU+yOxeHXwTSFhQ9x558WZica2BiHFLcEHqrQMhJ07qg7GqfMc+wqyz0oC5svSi8CLfF/P39XZ4B8DheNh66R7A5R782n+ZRuXGUUhsmYhA8AmqT07i34IzVgrlu93apCYfC9gWc6+Nil5t2ws+1qPAv+KNfUbEIBpuUpG/+42IWlfzVqLIeyLCo3ihtgF0aEW6SnWqymiBcDO3U96t8gIDR/jDfB18M3YQzIP+J+8v6K1iokBwPVw4yT2g+SMicanLOFk0EkHlK58RkKMubHQiJgnpf5h/sWtBYx+XKUXmp0EPw83z7/v5VrNYjp9S4IONP1WJa/ztW099OFtePCb73CZK541bYZ+BoE0jNP3goP0sZqejrk2dPjtC+/FI92fyz0/Y5S0oIIW2b+6py6DOv97wJ/Zk+gCY7DmX2a5pc1k97ijH6EMtanwEnuLe9EdRtObS1ovhxc+oQV2BqpsQoiYnh541EYP0uzmOjr7st+7F2LMq5mK6UT0OIqzXU5Oc5ddO9693lrNEROCR3EbXN7JW195qyjlKtFKiDY3zOGsob43EgHl8vXpnSrli5prIj+IveZNQ4drIbjf3ihwFfk7oXRiJE+PnEcC3A0TN3zDhYZh54iJNPomuwBS+1xJ3mmSKcSWhg7+j4N/QyGntPOPetpzUM1bTGbTNGIrH+WfPkKgKjpdy0YXs1npLtD4p3lTHf1OR2eNOdMUp4hUd49wscWAZzqOuPjLyO0idnajYQoT5fnT4YzrppYWCf+2SmooJmqgESn72zzW7QVAQGYbFn/8GrE9FAe3hkq2I9P1cunNu5ydY/XJ4JojKTcy6lAbCotwV3299PY6Pd2s4fvpwGW5yWZTSA3ViWJwZiP/8fla6PqN6CwZ+qOPF4M/UEM989TtbIveeI4ACuRZH06loy6UsB7SWJJD0BbT/3G2IGLRh7xNV6u12JIEo2dKgJwAjveDtix2Oi+ypXlrt0g039ZPIeufpVA/lYtxi3UOUOWkJXo8QV2rG4Ue8rM5C0Ggxic2gsp/W24a9Ph0KaviJKYOJYoaGx++Z9ZAEOylFyp5bwCXyAbf6LqkH2wBmsVRKOtwc9ldF8ZMaHZ5u6u/y6y/X0BleAS3BiRmvRKJC0WNvWcMYYDASBAPCnC7a+8lYfjUAbWT1B3CUkyEXFaPIif4peCOn7J7sEYK9fkdI2LsjKv2nSc2X5E2lOsewZsThQeAzdMTkrJYg+CWT+KRtPp3XTX2NCk8mBboQuVSKi4qvEQ5VVb4BaYVnKJ4QHe6RePQOyd8ZBZQGMVkXid9FfkA11siIugGkITpzak+15Wgq7/iYuDYUYHoXp7lfv7Rc8xPCb2l3lEy8TNWq0hZdSq6bzxVSnRoLPQ4LqTLtepus4FlM/sb7HuNIrICif4YcnKRb63RN+KWZl41oleJZzKk7FaNYJeZchoojc9mKkSdMTrzPuNRlOe6n0HEu3Fra7zG0baz/aohdNXxdPRpP07+TEGVatOaeVH/s6ZcaTYu/R6FlqznCUmuLQ/uVMjxbJ9114HX1+5F4srq4gSbfh50srvnx8FnKJTUHO/1ipeYKuUHiP+Hsd9u39+j2mJgZaydx/umxS/9K/I0m7SA0Iaq9HIiisQ+etH0V6S+/qf/yGbRn27CJFcWxuF6RzU7d/SRb7po6tRJafR9cXluPtQEuq0W5JpFBdbIfo1czN61Js3kJWcEvYasv+g16LM0WlGVRZ/k5W/GsPdFQcK8M2UFKLZ+XZZ//u7KoJF2GWfNMaQ2cp5pNKHLhKsmUJitfIWiNAmjzy/Sx/9jyYH6Gfsdykjg0IUcjJeEnHFauE5y/aH2muYypYqHsA99D85/f+MtwXwkmU2fWmRxeorEsnN0zho/MnH5chb3nE4h9IgnoZp0nbvTu1jgktEJ7SYcin2ca/sRqglKC+SS2+arqIXtx7K/kwUfsA9w7F57OQWahY3GOaf5qfUU6fQ5J15jBhwkbNYsiQFvs8xtetqRRyjfnFkzynrZ6uD3ZoFLfe6oKOXzcYT8HDDNzstbijjNR5f50l9uU0vUTEPUyVtLf9ALmEtTI0QJrE6yTBLaS2GG7sXQZ+3A8+cluFtb6O2+lT/uFqLAH/zG/da89rVi+OHQETLtQv9sZ1KLoBPLXOpNspRids/2B8XdOojB837R/HGEkDYwrLCZnfX5jFwCQEelJNVWfS4DPF1/52gMXQvkRHqAboP2CJH/zHbFq6ARTxIXjUH0q7n3yIo4+2l5H4P7NTBnjLgTulsuZe1PVLBzT/dOZdoLgWYvgI4nyunpLw/MZrNNyD3Ro9ENFw4gYnNwaeBgzTqUrCz3OEBS7wV4YcYcOkcLiP2UBDTWXbrXAFlK66FComQCuvUdk1EqUIYMbcy6k+lnU+GRlqMEw0bXVSKyXlZ6rj76Vi/RaLHOFK6RMmmgp0h+cGYPa+vJhVX93oUlGUgN3deSTjz5u5XuOzNBaykw9geupVtI8DbikUHNtyma8qOI0yVs/TOxDwfTfRZuRX9+Lq1Bqr8Or5O/8KWHPs/5uwn1A5QeA4WuNh5MPwS63UK41/+raER3zJsOo4iqm0nZofr+0vWVGZ7Rf5Mo/ho+j4ccrsOfQJcdLtCb/5JZ/XofTOHT+q+gXQLA/nmfoinZrQ+DeRxUnp/c77Sc/ta91lFuFrSEd/A9K0eZdhfgjnaSn4aEOqjqbNhVLOspM8jklTDMc65NQCv29nU4iQrRk6dxQLmajx9vyZz0kRctqrSwEgHTMZFYuMLqhv5ymyK4v3o9O0zk/GyGTywfI1uzYPqz93bwegPtIMvSS0DXkxsa3af7m8bD+Wh4DwWZGsdCL0pHerT7NYJ70lvupUS6kZnU3aVfdWVaaf2IG8bJ4PMxJ6DSZDrUmiSmKgVOg2ZOkpv486B7hnS8GyQh6QrRG4P9+NuIpGIaGL9sYHaCJSnB5E2lvY0SfpTPat9+owj0ghjGJVerOblzj+vubQEJGB1dMf20/gA6E/tXCZC/o+VG9ckcvE7/YVCfqVtWdgB5GciyQRq8+00UFLZtlBkHD/YsZ0ML7bhoRMs+XjQpwz4XRhdPzdXb7vNuV0fLAdjnOesxN44nBArXp4eECbSond95vPCta5a2KI5ermJLPYr2wRmKhvRODv35LNbAzofM7VOC27hvH4no8nGDt/9RR0xk+9iP9Misrr3hQwHWMtVmWbT8j/Kh966+KNpWo+dKopVv07L6+VDq45iHcNMAmBZXO2VrfXy4Cob7NWYT6G8/hkvf8PTl6We4azMoQjDAMqVEEmfZAanbEfkGBSFJiiAlq8dQk+Dj+Tzlh0i1Ppjor4E/ZT0U+clHhdjCWr/M9j5I02H5BfV4sQjy6AEtRelUvRzpq4S57M2vE7LgXLpleqj+ANAKE1G8YmjuMXZZV3EQZus4gsuoF2STiTGjHNFX/JaVDTMwV/eFkFrYeTvbj1mENHoixHpi/ptfdSwCxSVDbGU+cQZgCxz4xt37GTZHkJ2WOJx8DPFJez6Djj+V58/xcJcjnF5/yFta27rG4kqaOPp/6t/feTNe8R9PPy/2hJ91RXw2Wea9UBS41CBdCEmZBcidl2Bfd1tpqv+6gihp6zUGiKXfN0pX7FH92/BK7lh4kfBt7YmkSLzaW8QPWugZO5ksYzd/M1aWUTrrkIfbcc5h9qaQ9l+yvhPn+q+P0SPz1gQfKm8Moq9zsqf09wNA0gSCFEitLhLd/VfcHux0wwOBIkuFLx34XzAGL+qGcHgaNmWdhABsQyfCiBT9M7n3VGoio+AqLA5nOX4vhojC1tw7ylXZstBq7vQ/rOF+Tv+WQlU22eOSddHKP6HPny1lM9NmlOlfokVTI1VHIw/m6GmrevuxW1htwNZfYGwsZUJ0gNurdV7BAICTofa/mICX6ExnKK6MsJB2M7WRgb1tEofeTFcX6JT8YjoaA/kb9JL10S3BBzbGkExuKBakmZePfhOb10AuwksFi65WGdr0KdI39hlDe59fikDooFT4brmNFviIuD/IQGKkfKP5yG67tZNf4Z+PKLwmIwOw2N+Di4wXSbP0D0gZ4VLlC2DA26c958QouzflS2haffhwae+32jajTXJCtN/DlWXKUqB+YnEAVYFXCFlgF0TCsU0XFt0NLwx9Prmz3v3P34tzcn7TABjc2l+PIyQzUefT6CeVprwN510qQvwnBrPb7ocM2MDn2IbXJN90RbeA5ms3vAvzUk+V9U6IWle/OCapHBkvCZ56+ltf3ZsazU066Q89fqibXfazsaOL3K/24awp4vrb+UJEZzeFmKFTvh9DbTlKH6E7RQ+pZHRP+Q90oxeSZ1x+0xh6x2hPUFSky8slJsQui7auZhC56eAq7JY4nByEdYE91Q4Jsr/POfFb4ak8/oavVL8QwyXju7ftnsepF+54eNqUvDF91yet3WU+PeomgkSpk294iP4uCMKf4TVJWSH73OSnn79SCXEt4NszIy5prp5DrpSfP/Xw/8pmvNeDnQ6/lVeNy1IqVPQWMN0822zZxVzY0o63tM66egs+BBXqKM4rNC96Nq97EyHQgXwrKd75JJuWHlUPe+qY9DXTiotnUDb4kdDumnvGPyyRFV4No9WwtIonl9bHo9OWockl/o/T0ch2HvqZ/0ixPhncnv2agY3VbDTz2Gcv1BTU985WtQampsxO1k/kNI61x9MxaSl1bznkIfNuHTMQDXgALV8ue7G3Rtr7BZ8pctMGzNjNVtiWwpkFMHMTIYGg6k0CP981cgXYii1EwJOBDx//Wjf3zK9tMtpCfypVTBOVSMbWDmtKsDO1TsdNZ1p4VMBY+OGxHIrVpKI6TQ7c5nW7i5iUVtfBf7+QuLwh4r5jJufKOpr7gYo81cCrtaSa4/f7izU9HhGGxpcS8HegS3g9NRDa2U0UqnB9rBaoK00Za/FdMFPqb9UP5ZdO2T3w9WhO9jDgJt82BTBOQ5UIPWLd/zXgczb+p2x/KwB3mr9Hrl+vW3mToDb7D8q8tH2wQqToQ0FFkEFI0xHZ8U7KWO5yGBZgpK7vQPT+aqETijQCs2Nz6eD/SUy6D1/trJuObQjZ8gOpAgmD4I8WchYlNPhdE8j/MbHjXtxCSC1QOohSXa958kHqAAteRegRYkfjUd558eavom2OrBT+3gOhTtX5qBd/ZHsLWX82bB6swXCiFs+15n6Az0v/1QN24Efm7pw/u1iXlKVgtOjwhIhuiU8Gb0lnYC3iLhADw55QE5ZBtBOrZTwLTJwnkC/kjvZZoSIS3yBkWJSdlvCZwZP7t5lLY+nmRim8gW5exrHOXly6zkVT5r9xaPFooIQ2XE3l6ktbjK8b5WOmxEso546GurTW7Xnp25HUcV51KPydz3UW25/wexnfdgqtb+YXUXeX+gqofvzP+mXd8VKbXn7sv8DrVr7yIg/Vy93DpZu+uIfnhWHGd2ajpJDrQYO+RX9P8ElMppf1H/CTfL6uXkhCyv9jHDyd+msazPGu9bWTEtkdAbPPn7NZqqfVXamPACfgw4iP4s7WQAG/HLUsTHvuiHLQQ4X+1S9QNkMrh/LHkvj1O2xBtyJhrJxn1m5vfDn8hBAm/pPKxoUrtcu1lK1EO3O6Wwha2UgThhoTl/gvWH9hIIkAucSdIu7bS224096cClW9Tm5mg/Z4Q/A1cg/bfJgS5MENy8yRsbv1sefuxVz8Hx08ITiqrknD69W4yXOjvMIhHcdqhwc7TX3SYhDQF3lG4hHqhHfKguiT280P083//rupDWYAF3/MLilVo4jBFVPAHrGkJJPDLl2iAGLTRmhQ04LiEnIFfM5JdNngyJ+N5YobX0N3hPQSRVrRtj//3zY0NgmyWqxQ016Elf2x2rNqFY3K8qrFCJD6UHejHR1uLJvE9UFQwnk6LCRwGoZOMQyUfDjAMV5AUSlFy+Jr+0hNHRJ+mygdg7Y+hsgO0E4ew90gyUU8BbV7AfL5JhVGJOh1p6FfgMrOxmwgdqfS/B+NFUo7LXbuJpCBS2EfzXkIPfLFaCq/c1Ltz7A5ym7Jmtg+045ACH39NrZ52Ioz2Ce6GDFl9UOSw7mHi+3k+V59QYQfVXAYYaWS6HJaRvLqbOSdAzZDdJHWPs/R5TqZf5ltuunmi4XlXfWXQifi8UsdRPfMp56zxOHVBDW4MMO3ftTggRM+Ladt+FlaUFZTfegH/1zOtLEJ4unxBDa/JXzDwxkoyTa4mb20hLtJjWONHDUK5jmZprx6btPy6J8sIQTtH9IdVxc7udfb7/rqHbbaox5pdVMgc1XzHj+U3fUoeN9g3RNHGkDLnyECu6ElC2ho6fYb8l9YmYSu1j1qWtGQIc/Pd6obTsaHZmA2xI9d4TQ2TcbutaQbhZmzzccfYvswb7XL4PBh5p76nQKfjglbaQg1WQCwFqy37cIRu0OKR6zbhCY39x6IXeyL2vykCCJTtB4H8FcUY6P+Zuo5lR5Ut+zU9xwg3xEp4D4IZ3nvP1zepU+9137gRVVFVR4LMbdbalkuQr7s5308admAXchBV52g9XIrEsaTFaCJRCQfEVQ+VvZWpGvSuntCFhgeX077PZ+6pfgYvan/QiL6s7xHx+9z5tJXFUJagP0+1Ve/JuVGyzHKGXMmGUCJpS/QP9uv8eJAW1yL4Q4ufK/Sw9pQZCR+NIvJjmn6IK4Xu3p2N/TFXpAMK2cTf2iSroW1/ciDKQqYHLD2cqwZlWKybIogjwHpisu91juc/0nfbCG7cp+70IIQMytrWlSZyotjGhebo1b5DWIZ7z9G6S2GVkJHHWSp5AS2cz5F1ruD2BcbqmiUroktpVWCYQJ1N6lOvUuFm3IhIyyel3Tqr2CYeiMWE6XW3g+QkXabgaZFTl4qmH/LBELXOh696cSRtFpj+QfXxnT/+CHjpAHSLpJCN3faggfthjKCDsws3DMyAX1N2nvMIgYzlPMPac7qwq/DDGD3qS3qPK9ba4gbh7+jBGZuliuzbsB4C2+u3kxayPIVt7QiJCgnuGDbS5Eftu8OlaIumIQzlqI2k50+kaZSn6YF0QciJGZzwnEXx+qd6+RdZS0QWt19ScN+jOlwzgk1jZ4VtoVu4E2xnSX+EudFEplHVQrvd0JBh2XqgLLH88tjQC9Ml/CGLso6hZsUzzwnTuBgJwIH2U/plk0/fDzIrmHRYPMjLTcJDMnWT6PhApI/iQdVh+jqqvdD1UWpsW39dzU7KMd0Q3ILxsLHzahuwAQNbbRu2MosrSqDmWuCbgSfl2NAfZ/35uEQmNtfchMbDpURaO+hASkxmYT+Ur0tKoldg1YNAw+KitKmUw+f3t0NPTHn9ti9SqAgkoBP5FwKoelANs62YnbP92lyRnk3ICrz7A3rU/L3qInSsuo6+U/jaS3SLwY8JNqhjpQCxpIhwl/M9EUB8IZgMQJNbyaTeUb63wj3CMVV6GkHtHpkSHXqo8Nr0SsrqVJRfFVhnLmBhUBQVCgZhHnWmi4nqPe8ndChOwTCKQJlM5uD7ADfOUMg/kbx4U/i3w6p1FpY7BjMOhMMQfEr8yg3UIUqC3NAHH4NsvboRG1/nb0aqkTWvz05a9EPJ8Iaw0c3DFNhwmlG/3Yf8qG/sAEc3NMb7kypG9mm51thnZSApkcNAO4S0lE7DglagPN8epH8/Kuew7/AdhkkYbnaSGckNZdajLYxAlKzAiwzmM7J1f3DzNO3cFWiTHawc5h8pYMyoBDTF6j9FpKliJp7xMb5959U3LP3h36HVmxXJFqxbfKXiW4n2keG/MWxKTYgSt04tUl9HswnnVSGxNC9Oo/O8bSXVJX2Yonpk70gMYEgGFXBfoRyPw0C5uGkUgoLWaR5PllDYggsY4fUJCAeoKG3SCh1OeBP/IozMSapODEeTKS9vsZHvSGoWSjdwajmrNukvB5MTNE4uJSHW5UO2G2K70gPC+849CqSxGZ1zlKYvHsMWLH6qarrd67J/BwtoThht2pbo1IRuZu7eoiJOCPeh9CFxrtrgKXWzg6HgR7CtyKd3M5MfFXmI6KRmLiEI7J1q8me2COOGmUSVB9Ocxu19DG8u9ECkjymCQ6jN57BV5T0PUt0LzO2Yw1tQoQM3kzAYuzdjq1MnaPDVcXNVRZ820ky+tGCR3qfPTOW7d7ghqB9+fZgwdD9ZEFOZ4ImpbOEfTBHh0m86d9nk4Yq0ADPbxwE7b987a5bnatU9z1JheD4ZE7h740419QjGgyD4q3kQ1/Aymew1qPRDA51CXs42S1+uGiQfMY3yl+EGhTx/FhRnqKhOflVe1VXWPS+/tjmtrZeCgFiQMKOScOsHWP4oXXVP47xTsofUFBDvM2D4lAB46cf2Yg+wRTwn7r43VntFKPfRA4gyXPXmuIfBc3VlC8VR0cBvvUjjvfCxMHB8F/WnPLRvR/m8pW0JAVCJWsnXoCBYz0ayRogPeXMYq8KGaev5PS0WB8ephvl8ugPBcJpmu587zwUamYFvGIaP/XiiHU0++o6tXxTtjW2LUnybQAC1R4G0c6TkvE3mtVeXK7E8v+qUpDjolYPXUGyVfTd25tIPT05dsilzs3lYOjL1A0KK34sGxUIDEb4F7DKgUaEzPqnqNxM7R2V2tDgE0ttVE/YQRbZ500E8KJ0hPNCpMVmrVmmNn8Q4fc0jS4tvlPyM5nUg3JLrMFAmANxtkI1Jf1Oxs5KhxRrPqMB6BZToMrxBfQgSrJEkMYrwOfllwCdaTXXlFWg4FtBfhInMM+NDECWBgd5uCvXzPf+usJdBBjR/fCzWsaAQaCghjL6sQJ20ApJuLXg3+zDw7P3Fi8R4K+UckuT46LhQrhFAFjiB/OFfouz6OcfXLTnrk6xfH5D0of6ABnM0oT3smaCF1G+6BFPrW+Yw+1ar9We0SKEpzyyEHHyLmdCmB2HGwEv3bAoO4LiMqL0kBv7S0/fXzTwKoELBN7BJ1bjXYqQdSe3DTFDTkW9sC5CQO9cJYjt9DOa0gCHggB/94hhk2sRZOxE+sEbHLe2KJibfrKpBWs+/UCNCB2YjLVsQu5atg6X0HiuWUPH89UbeQl5CUKsIrTSvkY6+b+DPkAYYg9fqZ+0ceCcE+06v02/6JTVv9vGzQrRaVLlJW94HQRxPHIjFSzBrew4r8Q9oG6XOYy4TwxpV9N/sfFcxuAXgwTS4j9sDZRhFuD41t2zNewx3dlQRqM6Fd4C7JlQHvV+hHGrLbz/q7llC9V0Toju7mXDS45l6s2mKLeFhrW9S17pUvnZ/J/BXLiGszEvoXf6CJp7USfVwNegY0itFcO3ELs1Gx9273TbVYlDL/E5rbcLf0Jky9RBfcBGYxSPKZpmPjWMy/Gyl32Skn1+1cFhTc3ULsxEC//G5GFPZvXnTioB61oMs+Lcg6nffkCy0Xx+9kDx2VfYHaj9MIr28UfwuVTHYYqUx74KVnbqVy9oSESocfv2yciJogMf0QyWlX/VYbdmLf+oIrjzyI/+R460S9tqmEOmt3d2bfuSuanPOKPyfWJY03wUJ7kCtGCNb4CFjIgAeJGilrjgM72VtfNwvoGDKy5SU8dQF0cIk8+QKUK3Gj+/Un+rLyOU+akdatt8dvatlxbMQkLXUzWypQjD4e1oAyVI8PrsD3dcwCTKZW8/+5hqCJPZvv3X+qBZFOd95v5NTCdPw9YXxKgP4R+e6iiQyiDP61rB1/lDfAGxnxgpcB9X9638icF1LciRvVsQhEK0OYbSRmg/C+T9coRkbkek7WqN2PwOM9dqpl79Ha06150ECzf57nuk3HY70/+0IkMg9wzfTggj2V9csvDCg+L8JXt/HtPRknAGJTS+H2NGDwah7ntLBjDCKxwx8/0Xb/gdMs9gcNEEB3JmoMkYtNG2brOyR32BuI1Uuk9o71aDyW4QBZg/LG/6EIA4NURGYZyEQDU6ndPn5zbj3190wENfLdyHwym7VlKXelwztP2A7KXiXSqo/5CnjConGSOLEqfA9vGynQUNO8w6FEd86vfNIRiwLvfHOS/OlFTGG+mwamNRensuNyhrTB6v7k0u55xRAjTMwO4qwwJqOi5BG+Nf7CubnBaN/bXYM6CSL5pn57QkO4lR/Uzu2c4lck8TnlTgyyYtUn+ryRbTkMsEqooB0opO1oJiVmDvxnhg2UB8dGndU2tC0E/XjK6oSLYF5dsLq4/nxm3es4qrZbBF4FukHSeDYqh6tfJANbWSQzJMghmLQPCNHRyE37HM8wyzyAstWU9OUg71NZDYtzHM2pFNaYsfZu9mD80Gym/LprpOsf6kKGJdlV4qFW8SZkSomh4xI8MZY8WbEQNPV62AZ/jN4HcC6NmQXHf2fOdswyX6WMezOKmAN1q0WktQH4IZ5VYp/s5cVJLf4aEHTRTa7EtjIIEcOgxe9ZP+IGKcSco8a8YoTeQID8Ii/xBwxOJkUo588CN+NQk4cnjU9/eFY3KyYxHhooLvtmy5h5r8NsQ+z/KEUVBRLGDipTVg0zwmWvcZXcGcJ9XxJnuB6fq4j96DDDHDQg1l0YsEpoI9Zr2sYdsFLD54kEYAer3qbnPwjuse/XryPPt/YLxSq7UTbg4zPbz4ohR2OAlskrXJIn0FEhZs3mNFkyx9KVsoHFvK5z3NEk2Fh1XDIC3l9Mfm5PPnxwYti/ZaWk/cYdMYGePufl9NgAgT/hFQL76/IUmiyRPup/IbmwXdmoN8vUZx5Y+cR+ABfvMeVCdmMM5nZq4m+fKCdBN2fzH588PDFW4iC3sry2hHuxl0ZU0fKbOIAFQs0mDCzWFq1EFtcmZqQ5WSWL+mWR7EWyD7RRQl951X8KxdRq6iiB1EUGbMDuK2zrcaKog1TlSbsUKyLHtZL+1yZRVJvWQd3GNOdHUnT4OO7n0q3gAoRuGcjmI+GhqP5sr/cIB8fo7khmhc8PlK6GJ8f5htSa3p+E4Ato62oNmN+sxHV7mhufycI34u+yZ0yXQpB7Ed76VhWkOxYzv4E/HO0VG1UL5jlnc9KvV4U2p7R5wU5Td+D+WUCCuRygShg/5ja6Os6n1/hD53BaByNOSkdXgyfoqtw9fkWtBzl/Jg4x+PMce/1W82ox1qNIrCRTskalBe6zKCg6S8qB1yXA++Jzpt636ctCirngEW+LAhsmxCmiULvbZrTFRd7bv1qGLqG64YQVP9jvOeZCLv/qb8ZSWIE7qU+xcxtQg809AWiisoi9tlaTkcsxBNyAX4k1EzJs+zk4PvJJQo1e8Flkpp/4YghRKjOpG8gtNpvBG+W729D5OAwhcghBwHlrUOQm4CvB3sT6+tMp94LWx5WzvMeofNuZLr2+jb1hsI82XfnlVmWhHTB8lSIB02Xpo+LmhpVMxuL+KZqUYr20PisW8puY9mhy4kjW6+dj3S2MwUhrQtCX8x135WFLM9e1BKJj2/8t7Ie9+9Ui65gVwcyvu++9b7Y25ZkvRD3rS1Y0gsqv1UeJ9WXjwyq4rcUGIkc+8LGOLrluGOki3XgTunaU8FWzRc6jINuXXpA6nqT38wvOFEM9Rc79aJVd2bPqJToT4MqIYSKUTmOElLNOuOButvjm3pHynVvRW+qCeBQpSDSJ6hHGG9++w1vis9Mt91e+7MXk/WhfHEABv42qBemzhUeQ1jLwaOk7Rfzm4NI1CxkfI3754kpHJ1ifOjjb79WFro7QYGot2gCiRHeZw+BkPob6jJKXy/YJNzdmszk8fUwncpovrpzV+kahY7WoiPTTdy1VnnDAafbtuvyjaLdGyTw1XPV0IWDoUMRvpybCYOMNCdHS+8ytA377Ub0MHak7Nge8yBZJBVOyEFWiQ8YYz6WsBiO0lVfAUcPmU949gIyBYRArWUwQUs6LbTi+M0SwRsNYjxNLjX146oCOYLMpaa+9jtQorv01YkKIEyo09ycg8RVIZ3RpWmSTiaKfbCeHoE6HiZtnmQYFqY6R0BBgN4MO0Naxyum/aKWO7kx6bFf61ETkRzaQ1WN+qYWjO3Vwm0pFI2MuPS1qaiuvfVVrJb3An2JyJdfFyUf30kwx8YejVGQR9hQx8m1ZIYAI70Ej2ld4G5zuB+5Nxy6vAuixPpMXxct7xs+GgyzvNU6TtAcUmiQJ5dwkNy1GPOBwpZ6tEYVFrQZSpVs02Ilmw3jccOfZbCe+ys/MIq+fSvQS9xQduCtYKJD966uBYr8/mo97hJb+Nt5Lbpv1jqZ2410yn8us21wnMSutPbuCx7jWw51j3lH3XXlDkh0omCigNAmP8XeUZNTsnz9EjNap2lCYhkF77fvkcFvnAKYOswAiJhGloRG1IM8b5giiDdCkg/YTPClSKvpgu7437/r8lpfoE+REVUgVHuuTJgGY9D2WB53w9meYTafT4VCPn6c1oHHpNvpVQgIsqVaFF0xwDrBE2YsQT1/GONm3uEvdmdI3lJQa531XL9LhAAbThnIRWKveClmCjzvynB0lyznfTWpqD0m7DeYDb4PPpB6zJQ/jq4er+c0E+IFW63ACus0eRFH7vWbVKrr3uGWEJMLWZZEDCpQviccA2EWCVhoNSG9qxC1Au/nQn/LRwviO5h8ZnVbNqDNqIJEXobPa6GDbJmP2UQtJhLU5fh1tgaJVO7edxQsHWfaHbx+fIgGYkTukoTFd/6Ao7Y5Az//Be9dhRxT4a1k19tbWZuuHDhk37G1P69OaTHlqDWwzsTuKfysDd26fO4j5xKu82a+CIJLuGeXpt8Q8w2L8Td51/xAGP/Y+b49O55v3oNLN+2wFE7g+qXb8qL5couHhbmCPFlm5dmPJpAl40ubmn+m0WdYZWbWhoyF6+dLQe4u4M7VmKPjkYqGwwhiJHePo7KZdHEe70sCor4TF6N73IW/9tmdAqFE2P81BvI9Q0T3msnv+D5x77m87de4CiCnl29GBM9gFySDfdVRKwoa2Mf6bEvwEXi25zthIpuu/JaAoZselOwWFQE8ZMgqv2K0HhDwLapNteEeFS80rntVSZbSkDBLMbYLy4fvDGLDt52/tcWGCGWqUtgA3OPua0IgDIlSEeShVX3C2uznSAwKkNN1B4DCa7EXTkqywlQvlYZHs2vyT5WszfSy7PI9t50WiylXJNyQc4tbX83+7cGz1zdK1Ld+g/qiTklwQPHCtcFwlpTNTO8MjfP+adSebPW03gAZ7MH63a99WYHzO9pA/MwEcWM9fiz7bw6pEGzBqwut2NgBo9JPbOG49MF/7PQaqJeRvPe0CePgLsl26tqrt2GB6c6wVM+EgBFHKBEZSCsoRZPnlAPQ/9K90dtw/8x/ZRIdficKQb9wuV284I2Tgfztufns2uzBKKX3jW+9Ofbc6vUEMRzklqljII0yeU6h3nTnYA14GTNgfsSIyGvucmL72A9aEvhCpqINGLEht7ZgMmaNkz4gSoiNPhw2LUouy4KgX/RkHjvU9u/g+QHgvZIRdqjj0lNJ26CNdfXugU1u1IWnvvXii8LjFqU9DCmyWsEXGsnZi6TwF0lhq/AKqDb9dDyi7b2C6eZaHaBgRNHsGsF/yTqBQn81GBHzG3M/ZmnQHsvy907PzdYPb420VFCYNYa+s15DbqtNtko/kGIroM0KlbrObhLYSOP73TNWfN30Pf+qq4CLp8iXhH2+vfEgGwxHoz8Og01AE2T1WxFa/VmnHJwMtaEfFH0YQOxdy/wq11jEROiTCousxnTQxG/3tckv3p4VqeGAUZS+mkL11Et4sEz/pgjGmb2sZgRteISBX2HPpzwCpdAsh3rq/g00/UxC+hKUCsmBhguHzhz6SemGXzk1eIjOc1GizG/kxJDXPdlkKUc0y8HNzVgbYIMn9Vpqck8t4YXP9Dn/Vt6GRo382tu63526BlH/hlSDv4OxLpbxd/CFELBV3AZ6oU/Gg6R2vrpqkzYpwcxkfr8XV4MMeGRwen9O5csu/sGOikfNGhvukzWkaUi0Jt2cn3QGXSbenzUpgUtZrgbP4i+6pO58iv4tBOUN3q38yedJ+X9MFvzfP85Tgmhl6t3pqh7+EOotSVx1BPtrjQ7VnST4jnXQ2p9gyKlAfm3b/SjodWBbjZYYDHdKF5z9C64ea/Lt0Xr/5PRBhxmI2QrshC2EP6rwYQXz51egq5TeJ03YMG/4S6jnhxnw2/qeGSVE3JUivjsSqSAekCfiTN5s/9t7+NXhZP6vHHbJe/oCn0D2o099yaJD5uBugpKyD9rtfbBFleGt3wS7x6yLxekBGl/dCP5K0fvbN//atV4kkAMpK9fw+1V+NRoIhqkxcf/mzqZ5VAwpe/m3DTKA5JDGx8mrjxSuIC2hpmSZpPbWLSmLZRsTq4tbMZlLUHJKDuiUspyaASEHd4PiiJOl6WOsZ0/99EZ5/OdGMjawPDAedsyWz05XwCZvDAUGtyofGPKgD/zVY6zec2CKOd9H/q4OR9w917+jBsOvI71kgcH1+W/vpW2E4QdALfpRkGx/4e/wefP4U9+jIfiqUfFq0gv88gupz5IMFHSO9XyXqecvcv7hIN8XMoXgaxZ52sYJ5qeYe33p14fGPyBe12uRnX7uSxw/47USfmIYDjFX+418vjuIK+DUN9/7ZM32GdgZtOvuiPQYcb1646Pu7MMn5+sc+T7dSZ8WHRjfM6cPUMO5v8ZjqfO7Ad/TlExwf8ob/1IseF5znzkDhN0itboi9uanuQJtJsIZh7u92htlZd6Q1n++6PVlk81w4NJPRinOdfi3iicPqA8DYwq0EMGfIBBHDMumAzjt/fNGxgsqNKUPdP+k9jw3uvlGoajdIvczXHwAnND1bXTVyojM7vgTlk6UngIpRAO8gfpvWKF6lxq/MC4YA/S8rA1kqoi+2P+TZOB/cnfhvRG6DLQHj+LZb8gc8lyM38hzpg+nR/Or85MIZAz8fiZA2RNzPzx5naF5T9d9yxo4+9xAu3bycs2fVx8eR3FPTv3iaZ6ntppIte+7ELkpYvaV7AnPJGPVvWHsanuTJcKPf5FMSmafT/v9BTm1WEsPZHH1ZMcc9d9pPvfPb0qYcWWcwTFAKXPPocTzPL9ADpYqxhensAKFKNj7hDrtMUQ8QsXREt87poxmXSkYJYkUaK/Oz0r/e5tyy3MInOkwGPrbB64uU6EauaL3G1sY8zEn5s3kKpnH7TVmwdXvIJD3qU0pXKCFItBdezh2uHfcy8iqNUd69qLgYfwK3l3+n1f2vG7+AJV/ry/AVagVQN+0spPsLRP5v9juy4EWbQ8dg+UO+wEw+tW8R8xgmdgOQNXWOTlgRHP2vgmcgYDMkNX3xpF97n8ry0CEOszExq5eO0GLbI5qG/CoQrgbjgwQDiN9Xgkq+Zx8HTqvh/mxl/GDlJR32F6HRlw6se6w3vhWTwccFDKBMSsgzeMvAtp2I/l/76SmYUXPb77t+Mc/R6o+auHld6U2634LX53UaHxai3MqLRQjTYQlPTZqbYlgceRSefQ2FbpLjS/kY62biZhFVU226Xv1vbQuB2eOC4DSrpF3trP9OkebVuzP/Q3x17OWSFaAvXl9j9/YoIwxSorKJK0PXeBAf2YS8BznIKntHRwZqMa/7994xMReRmamgO15YTAVYzI1PxjrsSb+uWUrxT6EdCeOQ7BXBpBfpkd2H0GPX2wwXnt0xfdJp1C0yF/I/Uo+f98lkAgCz94bngMQwIvtWNrLnbinfhJG7oQ90g3DV65/Nt8dodXRQcjiu5lLggdeY9OxMglUYDj1ceTqVx0Y8CLEg0WNuCxDF0qXqVYflVUd1sIz7LGpjRK7dm95B8r/xtDC6xfHQE4C/rPxwJzwBzy+v4XII7JVuwVTrFMHLzQtB0RTmO9d65wo8ZcthOtgXRNERtlIWLzO6m5HGtQUGX9MAI28QRMUr6tuSlNRapV6TmDDBisnDifopCDefuUviHZ7Dj74e0qTnHMjEGidyTNuvcn8JVlCVO87oGZC//3EMXwi17j3RupshPw28uzq89/WT1g1P6kX6LTImElx0Ps+CTlB1p+tFOBtJK1PJpsm+yLC+POoIOXf6Y/6TF8OtCkyomfsuOfOJUMTYbcRVPVrAU8/q4FWx+bvoLEBO+Cd0nlao2m6oPmWNz07yzN0lGCASbPrYzxwXFl+O/5ey2MCRKhVDpfmB/sQerJDHPfc1+oUSMauRtHpK9cS9Q4h7RUa4YJQ8UdgbwyLv9yZFFGuHnrNfdF5TRMq3fIU/YXBfRNkiqUvsfg3LYFqZWnNUr8dKfRFDiv+V6p6/Pns02Ef2yVVv7FC/qzZKZb5JQHQc1pUmOQEaI1whcnbXTjOIMc7jpUuLO9zccs5I9AtYNli1agWQl1YPMaRlagQAcP7GSEQFrfXijE9TRZxRLTK3mNySn6LeDY+9Xt6yIu2IBXBEZ9IQ3XNWxCPtdavxXF18wu+0YX/QroQi7pxvQLFOHsjiBgOTXk6lknY5c1H1lTrECdR7LZVbDkRHoJimjWB4Wnmw2lmgMDTuAJ2VcTu2pZulQn8IVfeyrsAWWgKqLWz8nhxcvSu53QN7xiDART9bUjJAx79bXKeXWnESUUOB9oVYC+DF7yfb+WxI7/6c3+9p2j/fv8FDjXxy2kPydwpquFYO7fpE6RWVqcb69e/iAFySLvfUwBcE/aa5asyt6T8Rg1A/gFkifffUGpeSo2+tb4nl3RbZS2/2LQonV9+jMtgNVUcI36OqwEqnm1gPBXdCKSWn8dj0hHlk69mSLvop39Nf5/M9kbvfBIcFKcLl79YkXg3EX2jgzhq75GTj/xnDkGhSV1HaZI0qXkYzJksMPf6wyPdx7qsSVgHE+63cT+lW/XLlEccc9m6ppPSWV2g2YZsb5B7b7MEeISRdYiCl3sK83QMVbVKRXyhxqBOhNdNx77Slw2qe623+9gWU5ahMkJUlm9Yr0KQtpwVN4FCvw0PghXYpI9vgr1jra24mShv+Qpr5BxURRVoSY+dT1WJn+4Qk85XL0FUiaLgC/cWIFkuymas6KFsOH4QI4m1lyFEGctm6Shyi5l5CJLrluW88v36Fnk/NunTVytZu+i21IKFeV8NmFKtc5edHjFnfTsfVdsiCzYzfNdhW9OcTwdI7PrSHrRq2CfoHQSk7DQSJpveIfJlc6tFOais29BKQPNOUlqJruxvR3NBiFTPf1PKyei8s8WXJ6DKyHvZvnP2UuAK5aVslkZKiq3zle+olZMmTyvsp/JiuF+TNN7J/P2prQtuyn/d2Xi6ndOeGe/fcqQr93NBkDjojK5oUVQ0e7U5yaDEnmI4ZeyWED9o/QPVtlZvz39T/8JjMzVpMcN1wkZ+tdFpedaXqAgm8Rkz+tXwrtLo77yekcU21PBzo+OEOqAmg/PQs/TxbBbqG4r6lxpyoLYp+ub5LBPE41ojkqPxAAroUB3S9x0WXgT4rFaA4BWwoQAex6UOmNSxtfo3OIcf89Dp16BFutWJwUb4pd/x0bhFgoK6BbGOXRc62tolbedNUb29Fm9Doz74LlVNST4f+SuqZe1cC/fnutHC4m9e1F5zAmuxiDKuh3pGGyStSA24zY8iE0SaQhtwOyQKKZXaYPazeZFS8alFZugL01IdS3YL9rncweSdUHQdh1Qr7DfDkkYWdgbXsYF8bt1N04rT7ZR4/lKxksdBUsihcEiip0VhZuCWeOq/qOcZNAWjvsBwOPsH2JvykQ+mTbx9oD3dnTFYy2mGhgWKU/mlm4ielnjZ1NWaugKKw5Uj2IxjxdBzjXi0fR1LmMHkX9Qf5FtRdMpfL0PDSZpmeryGPpaQ+Rk1yr0AvxrpZQU+/fIVl72sfWRpgWUYDPm6ooBS+LK91yGxUMXCexfpywG8oQB9/6g88lHIyyE+X4CwSiyIPRZRsYq0BHYWeRJXYTKqg4b8Di/shzMQDbvMSRnfeuyvWwMrofXIjC/n1guuw3oOsM3R719GGU3aAPDzdYbDmob6q52dG/fSKOwJRAOIpeCy49eOARgSfv1OcADQOWsKT82tMnhULcF54NzoplJL+YvH6kz7Us3CczOaDC2sum2OCscuVGgLIuNgrfnw6XKZZVd/KKW94r8FSjNuotC1Ew85uSbts03m3mSCbKqG253Eq4u8t2Ta1tsyWbMVK0H40G417UVTciVSpmKWoVZys9HVRr9lA9QjeUZO45AoeUIOD1vZAH14vPlvDXueeRIrvx/NW7WsGPlS/xXRSer3ezvgYifv2NMZsT4zBwP+FpOFnLZflG1wfRp6EGFGKD2LqGgGDmczUgAdMm2QWsiUeRsFPXUw7TZKLwWmjcA5CtnkdmambjF7EP+CRBvn57ZCpnNwlC1txeWCydljwbx2Hx4fPXwpHnzqkIT3BiJTp3J9HKTHjyOKOowW9Kl2u9WKJu2OrozbnBYWar0a5Xt/G/bOWWPz1QnYnmIeh/WlX5rH6MOnar1GHHhuHwNefIKAFLyJTT6+8JIx0N0f+UEzawwT3aak2bQZZmPKdqvcOhKLron6THudrQQtB90xuo0GXrUWLMNjwyWv3QVy7+4DA69y2EY27fbJVtexv05J7vQWUuFGtMTYAdNiK+4KnLZbWLaqWJSwDC5MCtsMdDmgtRq4ie7EsHn3I9FohX5oGNF0SXbNzFCGsFevcsTJZq5C7EtVXcqv8ubjt6+tneb39fz6sK5hKRpumrL+1TZtHQrImDcgqkyEol+8aZqUbUX58MuY0yzXV0qbXQpkuHRm4u/j8y44gmnXm5p8QhoTgBMVF3YyyKpiXaYMUmNEXjnmwjvUZjuHF3mm+vZdBcdDcO+jWYJJsdWmwDs64g8Cv+GKQnbWhHWcwAkDMULLGD+Y6GrtYOWXGfbfc2GjePJ50Zdczv/mv9D59vp85oedJRKUFCztvqcPQemXwFCL9I6V37C+LaaHNprOdbl/09AiXD72j54Zqlf7CAGjo6UqBmG65itAjLyZ3BBESepS1yL3Q99crMX0WEW33UtvFsZGU/TGLDFnemVxs/GlDLtdzrT85g7XULjHpsAVq1YfZJrCclxEp67jj0ffqubrR2s6dk2VEMiqSNAJ6U6Ao29LlC6qdfFf1aCb+t5qCwtxif7qE9HsawvD7DmTAKD1W9VYVT3xHSG0w0KAK0t5t6HmI6rlh6/eg94klvIYUtaxP1Ya3JclN83InxLtr7sl3rNRNfjdXI81oInG/byW1htajxdQ3oXGwEBCyhXmDVLeJOZv1BEAKLhnnq0y36QLha3KL0EyNdpl6ViwPSONTVhBWXv+fPf7pY40c2off5JxftqGrnDZUqpsVqYdkxENtolf7KhbDwriqbY55UyCpGDizHt4tLawK5YJZtZkOOyWD9qkZxowJ0+9xXdfvPsY3RMxYBmFCyRxWB2CPZuSUSVzaEeL5WXJbgAl3nZdeknF16KPdxnrcOcqaO38iw/evod2pVtaGOQNIi9a7Tqs0nfPoZS4yxt15VzHPS28X/GuFh/WFJxOEm6QDIEpzFU+vdXkMdBUHKROrZMAwbPvuvgPuZxaSrOqdO/x75wLwdqXAcEtSfxbmnz06HlheK7Mhh2+owCiae7C2eYx0Pj4orEPKPBKG7X2nqf9qufrN0xyQ8ohQR6EnX/wX+IEMvoIvg561o5X9nlE93/AEsvOilMY0nm84Xb6ebLfquSXk0mPlbwJd7TVh8gj9Mg02ghYuDa69lrVSw3e5BRUpUOmiJ9M17LA4KGTo5EqiljXWi68JSqZu6E+0r5ysNwv6E2/IwfrGzRTcvcRaYiF5aXBwpEn3sG9ixytTcGqIYhQsPZl36NAh8KV+PocajVSVusCvSxvU0VaKAMUuA4y71S1Yvg4gNgCYcYZ8cSFER0PbuRCOJjAx1nCnu4AkarOG641bN72sOGnZ9s400BmyWHeRSd0dBeNHUyhYN/4rHhU81h+E8Yr7yvbdDVDXWFGJW6e9IA6FE8ZBBOyddMadeQ7RJLJYT3Nv2jxOEHu46jhh5XA+bIz31k8WTH4DhXlYTTDwdc4NMvo0dQ3zPvT4tE0Sb2kQh0OtxZeoNVAF/hGFCHnARvgkl7CZt6FwFghzZeM2aqrvTJGQ4ZUiFcXJ0pSReuhaI+9pY7jcN4lokuNqJgwIHUn9Qu/V/RD3TknotEXXAo0m8U69xeHR1MKP1Ed6R0x2Hu/vC/4csZK4FALXfbrVfT2UsUsuswIioH4Igp93n32LQEXwKJ43+MDR+BRbL+ntXygzevwj4uZN+8tOv++GPYMCs0yAMJjoNXfr9sVZdyIfwOPLDyHkKVSv9FBHbgCxQgugOwrcCsu90XbC8QvC+UgXtmj2ATR96SxXjcFI3dI7iLqvtdlQdxsMCAhmuZoqIljXOcmr+sxnEC2WRCg4eGnsR/uIsl2m4uuMf1+WSzXecxGoEd2SHgv2vOWJ3bCP3oeUTxNuCfbZnH/x5I96WqsDEF0qv6GLPweOiScKdqmO2scQcXN60PYvXv1EL494JVTokinNBRtzre5PQh3oDXOF/kNgsuZVdetUoV3hpOmyYZ61KidPMvq7cODsIDgUiB28Hghx1ogUuAL+gPQLNNrt5wx2mUrgpd/BqbwEVBu/Q0PhCCRliNIGCxGNsncuifP41XJedmQJb/ydTOPODbdh5jBtvi6wTsdnGgrIsRuPP9Wi3eVSWrAve1gOEW/I0PEV2F/xZc3lnohCb20VcZUUB392F3D1S0vlI9m9lK5r1zBnL4FT1ZfthLoa1RdfwjtqpI60NopVqLdJjTIMQRYzy0UDg/z0MQbSr/SkMVAvbTFReEwTxO1enlObt3LSnPYAPmZ07luiPrU8DjgtODgQWc6bFpc2nhh6tCyKvhHi78vV5fVgGCCu3KdI5Y1gfzQvGBQRr5CScPR1Osr30SXLVRy3tMvKVF9G9OVGsHr5xveX/snzc8d9uIsPrpj+BW8qAjFjrv7GGnFu82/oeHMb6Uo/GJT1Mhv14MuoBWUcWIqzMxfeSd1Z81bBzM91liHFJ6vhgLZVPLkc1EuzcdFw0R/PwoAXEBCd3ZcXdHQPZyNCYf1BmMRdKdtamfKNKSK7bqJQ6XlXdQGdcDGBoclXGHlm+UszQ07/zobWg9oE6UjerrOBU8o6R0OsQ0xriQv5PZVnVQjXo9Vnn2egCFPFrt3O76V3JLeGd8Gg/7VN0ZYdleJ4w/Cco6wiOpz6zLn5pMfKZgrxeWU8dL6XfG+ZeXLXWi+GGedQr+Ebh5DZMlteUcVyvXotAm8glKfMnzgHqj2ZNA9P9GXrah6iPZS8hpyvnF8/g6lpNM1dAdsUl/v3XH7weukyPnEPoWRjTxOjj4LzoSLH9SmFq3GSneKQ+Ro8I+FzqFURqEzmPEDMXKitnTNIZc+stuuwWJA1aHcg9+0Ssv4kVnoTVHxdFvanJ2U6qg4FUeyErjs9/FvQhboJhjvbJ8PjQ0/D0BeMl8sYm4ukJfHB97iW4IVSY3Hm9glOaxAJp8UPd9ckKycLGP1IQBqt0VhAndNouL2vhqMWxxlmkQffmNTj989fJuS3vms3zL5Fng3ntf6+IgamrhGDZnXeylPH9N2rslcAcRgYtibidg4Xzv3CoteIcbm9n4rlZbIn7/dnJBVBbnuD1DY2zfvQ4oAGRIID0GGjrmx462s05S+lybDVHl1XyrvZktIYOsJAEoZt9hSFl/DQGvkSHN8PFkTJH/e/vAbYxWF5MbeX6ilJA8/m1nrwhot5CamNMl8wZ+HWD7m88I4MspA4I8IFaxhsn7wAWZYYlqYxk9OEDlaL1OLGMan0+Tv91u9hTe6XT+QypL3SDT7t7BpWsgkk75NqGJiTkwnDIHIDZqzzVa48nIOv+r6d1mfL1jgj1ATQbi/4unpgPqbPky+QwOhHCeAAYlEG9cW4VvlL/zEuPmsechfuYZ81cd9oPkYeQPwQViAaOIXJmFxniD4+YzjQVt62uL8Vgv1e1BOLrcO8LSCMv+y4rgKgqOIV4SXPpUQenBOUZke9zE5R3Tp94XzIy3StSJEttTqDPa43Xccso14+RBBiQgvB1AH6mhV+qQDRktfPnhs5EbK8ETiWGArtkcFUr3PI9PmCG4DSLOPMr8uceFQHz2DN3Hf3S8XNNVDKysDofjB7AiDcRp2JxGFI6ei5HaCKxjwpylceBY7M21Vq5xYkWHEhpXo4/MYpu6x5RZtPWi6EenJGAWXQRLWOab1tZYjsU75ZyWg2ZzugYVsar3APKpXMUv0zn7cMYrQvXK4o7TIl3bpnxdenfEA/1nlYs3yZYJXCiUjwD/0a8Yo5FWIpk+BIB6q7v6e7S1Bbajv/fZvvbvTwfYbMc9k0UE/Sfro09aHuZnlOVEUTllz2lQRYgoUfQ8xI9135DufJl2M2m+IUlxM7xBJvtsa2nM2BRdU1fv3bl8nxoZsWb1idjGTft752fQe+MRszUyIHJeturblwu51J6efG66tvxxr1hu74SAnTl2bg5M6lnBybZpUMwb0nFZCDqQhn/mAWEDdCYi1p7yU+9lI+HraM9SGbV8/diloXc8zRjUiQZwK/YjXx7EjhuqCNo4bOgjSQufLcHo5rmKoiw1rseJZ96tMSJUsbo0Qcl+Qd5+cDt+TPl80ITkrdTzSZiVGdiwKdVEtKsTiwbqd27/tcLPpsuqIyFmmgM5ux7rKEklL9aOwd1jBRTIigyl0tkXVD+tjbJsh6ZEVPYadEr0M7fSTwS1PsY3A8As/WjZtiqxRMaVg8qNZsixIOdyWwEulSLv7aDcT7AGVE9+0q87I+SiWO8koti4FLw82O/FgGYsr285h5XYuh/x3y0gZET5HULWPvL6Yt15ScFuS+qnTFb+CS8ZuLUsTb97XNM1IjNOgTuRUZJYFXOuNb76uvzI3anUcp0SmXHCk06YGrRSBnQPRzvwzN1cf3mqxYkOkkYhyTO8MAblVPbUpC1dCeAFIggTAcyMActl8WBnB1/dEqKXqy2irU01t4l2rcJecMPZC7veGTfEEIlyVv79mCO+Q8gPnROSfo1HvyCrnIFIkdrE2PpIO/DjtYegJDfJr07Uz6NP7uZ1AY5ZgDa5jv109LTbyeV4Pzfdu5pDTWDcUgy9FurF5RpVL3gkIh4wsJk2/R6sOIW58NcL3pqRaZUq5EDkROhI0PN6fOxuNWfSMYcDwrMVtmnpbjFsFvAS6TlcOqvqVbRbWVwI9SgBAYpKlQPO0t2iZ5ZVjeazkR2JoHNYjTRkQPrDYgg5ZWhS+Eco9KKgNGULFumM12eHXfwayR5OuKZiT4Jhcc4HpggBMoMOv79nav0XEPVUyw3EOnlVdfZIush++MzV0r3uJktnF58174F0gSzq7MoxLs2JNu5Dd2ZxsCKRkJmXATltzMdXRBrM86sfbMLfOMcamS0s/BwDTNUqvkheMlZdp2mfRFPeQlAezV0yad0vH60qpwN0VRCmmbQs9eWUzYKTCDs950VwVFcWOXgjq5Vb6S6K5xQizgPW4rR+1Ahm39gF/jaKTlPfcZ7ji6DcHfhAEJ1sDYAI7/0+Fih4inX35/lEfWgjkRdMmOAXH9dsGJbwvevbfGXaFlYUwnZGwE7QEzRY7xorob+ubtpxGIaCVBUwbiM5ulvt5NiqRGE0OmFJ1+CK/yt3fxlIAFLoUZFOyiMsR6L5VHlppYKkICgZmLVtW2CCWhFaVDJfxZQAe6D2MtRLsJfmCeH1/B99MuV349YJWqtc59LtO3OePHDHfCJlxQ935PDz18Ue5QCC0QdodjWFSg+McHQsg8lUjZP96B7EsI8kvk++IfMkGvHvuXqEbST6IvwvCde2lskFA9QdjfPRg3X+tzqWVUBRxEzckIEbayRdK1U720FAlb/UeSXv/o3UvgR8eBHtOXJL73QdPQSLYHXXe5XG3mQ2taVxaZqShws+XzVfSyMOsOZ5NJ9m2wJuHfcnh9/u46NOrl/RGA2QsNDg81bC8pwxC+73bXxHNXObXjfjCsvteIFYNOj7vvGC9PYc9SDZXjDQMR1VouRZm8XuEB6ROh13xEj6AuUV8WXrioIvLJFcTXc3+x3fyFkmyw+JCHxdNb76Sh6ma9Bi8I66OdXaD+4+lsmhceek4fW7WoUND18lE8FsNUg2YWQ7ChviwMjF4Zpaqgnn/DN/JQ4Bzd6Wl5w8tRp1C/+S1kI3eiCfSYjwQDzugIs7Nonao1IWN9ZOmNQaOk5cnuW1YlZLfoGC/DQiTzfjFPVofynxz5JlQSLZJr4GxDSH05iftuK6JJXmEku09f/er6NprS5vjJVE6eTfxXmV8706tbiLMoalWzduiOL15hMvZDsyvqG+4aRoTr1FZgGVZNSRzdit+cJ2CD03e0H01DnLu5RTZQ0I2oqcOcnk/0DJDct/q4bJOEQubpbhDznYcePSNfptDxcYidH9tif2FTtKvaQoryjNjB/k3YgqIbO+hD9AIy97lQOMGqiVXC+qa9RqhfjOSyCLPEfj6tbvSOQNSFtLxoKK1SsJ+05Tut7nmRA+QtBZdETQm9IhO3ef38RtphgxqlAJgQA2/FWaU289TF709OdOVbS8QWECdX3ONhqB57v7aCRYfbqwvvP5+UDY6kGxQ8ylVK0LnW4bNbJ4eHtfiFqEpMtam2xKX31bFdfQnQFXH92chsSK/E+13Ifc4dwqWL0TSKXYT20hsUfIFZHvSb920rOBgNrxwJjNNreaUbp68wxUsP8gIL1+i1/ruzHY549UQPdB503Hc10ky9vhtTOash9lDlHNVSAYnVO76ZxeLUWsrwjgvrFxYjD3Ma8u/t9KgV+RquA6nG7FbjLWOuWqnBa4MAlPLhoR85P5fpZywyJk195QK/9m9xQFBbQx30lANMGjtIWqHGPVHxAe0f6iMQlAkzvlZirJs47fRlIIqmvM3gQA4YixFoGB/sD36Wf0pRjZNK/HouFQf2ETtfCmP9lvqBfiPgX3rdfpoAhwiXG0Dq8Q6VP5y7Vp2aj6h0mRD0DheuxseR60jwAF2Z7RHDnQtPRrlahtzLWds7Be50dlUG4Y75P0lSm/IkZTIUU7c2fupinE26z+freCI3XdgwZN9Jqo4ok2sCQuAT5FjIeNTt3VNhM82xlLMWfri0/Jwyc9/K697fox+YwhRINZfUIRPpfXrfS9ObLsch2JGxSpS2CovtnLLlr1ZtCnomad5+gFwwz3M3UHL4bhZvJyFZkFpwi9RrjlriS4zKBjclT4n5rNxk2gFs4kFI0vIL95x7BVE4Y6AMyCMtVwh4uzx314W5Neb8PHvRZeBM/R1GHvoAzSBByek26f5a9P7Jv3Vsjw//wF5KF6c3+sKaTH0hZfxMbUIDAYhCHj4G2IM5THx5aEHpWQfKU81Eb7H+n/b+65tx40k26/px9GCIdwjvCe8fQMI7z0BfP0FeKoklaS+3Xem+047Li3VQZJwGZERe0dGRk7pa0Ott1RL6PFunk/DyYOO4sy9pm6IbD0phM8afroDKXMjz3rstSdRBCCaZtwFiBhnpESr2bucAQnQ5DpYP7/lmd6W50hfCPc6lUz0gQ2PFqoLDFJFNXQsXrUj0UYAnUurW/jCl10L7CtH5uQL2K1dnkoOkIz6UVi5PtbTmyxdLmZrBaVBI0BlggKPljVYZx928U/fM8uJQtmmO+SOIJiSbZ5zGpmGJp8s+OlctS/zhR+a63mgm7jZUkZQVrWPBKFf86APN5iQkf0V7rJ3Abyg3TT5nhoH4PoTJSFxgN4s3A9GEvYUpZ/sWA5gvoXQqTbUljuZ6AmDMUpwIimrz5y6Bf4oHuj6AmKqzvN8xCfvXJoWkx2Cf3YmXVqh2FrByDuKGBIXV4bTmiB8ryPk8olCY088+gfOl0+JYDeKBETDeMrObYMu6VC+qeXHfH7PPCZnxdOrPQxuGMDb82cyAn0kHDogzRbwi64+nBTkuoEkgISl6h7jZj8eEdEGODejrIW57L/uLZ74hC+OXgOhRjYZrD+VB+ym2PmpKwDCGH4vtaFwBstAuk7BTzkEmH8UEfxYbOnJoO9qXipnxV8H01oF5quETihgj8szOdrbqbgbFrzv4OHVW1afEo31TmxUxiFTaGm25uRyKVHlYOFdxTndB7dGHYuJH/nEQ/kDDkMtsk2+UOjmC12Ngya4N4TRLpDEvlqgqcV7+L3LQeJpi8tuXyRedIwfSwEsMNTmjF8swSm04/uudTsI7UWdt6We9yqe7/lBGxzWbtHjZlnqzxw26IbTrPGB4iSz/bI8EZof0r3rBtWl67keTzA5V7ama1ZtZ4QR5lGscTRIBLlWXqiKE/i5O362JVxzr0ejaIOqh3vbAAr9KrtAESIqYES304NC77lKYNco6fT7WZGWUAUI3uf043o270ZtXGtOBe6GnU+hn/KqyBhIt9Yiawhn0zFxQjJinEBJ8phQDPBCcroHZR8+QezeyJ1Ls2WC4U0qlqdOv7AVA504C+pTt3xPftSFTUiGfZiVdAA/52Tb+U776Cds4YtVLoIk9cKxBU7bybZUc56BhG8EHJdVyYKIzM/vLMFXnej7cdex4bBNx4LqEgYhmuCSdSW6Ebitb9aMfy+8s0j+tIENLX/KbyyQp0BAfG/ISznLOfrYtqmfReXaHdxvFaWpn+FKfpq6iw5ua5b212PRaykjGxYeA3GyftWabwEC4Env1Ad0/Y6U6hMn7hpdLy1jP5UTDB45PtvBigzAZVJLIS6apGvmC93lV9wUv3sf9CRsEqKub361WqlQI7vgXNA1EoPCSPOtX59oFrjbPT7kbYXpT4Yp/tlu92OYUDRGPj6oymnw9r3QdjveW9rLp1zvQcjbTPW3MicIdOdX4bP6pSh9BSD0okZedKQtFmsFCkPdUO8wBWHEh+GrtAIxksOJJwm0WavKMLfy4mJ2p4q4ncIayfHuSz9/2yLappsGwTo4cFNe5S9FkgnlgqAEJbopicuSiTtdt99Osh1Yt1d2eBguSr18LbXibs+VC/AqA/hnL2F1ssEavv6551E4jvj1eDu0x+PRc/xn8yX4hfLYnH54lYoqPhyjd2ThRFEiJBYuclWiMcE3wH8t5uci9Fag+zmkWzO2lFgdNDiP4AygRYP054hinfZJCE2eUrlhJE3Pn5TxlvdQVUhls8QB4Jlk0wv2K2+t1h1U5ok64Ly9gQ/pK2EYKWDnEYntmAzYlAZL67txy+CZVTC+oVdXbQzhgg8r5gabvj32RAkH76yyT9ZuR7yiMjsRV94B7Xvm/LnvYimWLM+Ve7x6/idzP0ZOW9ewDSqdgRMa8+674LQf+0vxzwcZsBGJyu/Xuk3jp67fjLXjpxcZGr6ePJTPvfHB1TsmeJgdsUK9noZFQEtjOmRwal7lNYMXfyZcxIvz0uy8nFiyvRcybsLgkmAX3RvhlBWzgz4hc6KgqbT7X8Z59YY6YsPAe/zikLHxLuETxzEXQiyy5mcbHugwCSJ4EtN5AeQLt6xIHUqi5wU+6UqLzoSAg7ayd1OFs7A6rBbv9QiOJePJy1UPoc1K9XU87lxmCge+lhpxg5dYDDi/SZJCHcsxKVeZaTNabFCfJwGepuhMcFzo9LHbB/tbwZqvjavv9UI/W/bTNOl3XDG9hlzdKVKoImal63IVDC3pg+b0uXMvJyxFYKaHxIhKd8ZN/LaEjdwOHWxTGO2zaUth5A62gudF/nrb6sjXIb5JPsN2bMraGoFO/nYPqpFV4zt2uwmHbiCygbCmv8bvGsDMycG+Q6vzXS87Doci6f4t6hrdFabGhYnnXxYUsg+01l9akVEv757KMjAnQwfsUrdVVLlmdVG4Ujd4fTIqPTyfN5c6phgbjrrekmRVOSz6zHc+z0r8vn7q0x+BPSPBPVy1CWBn0hByC9gSw/usbrf4xQ9u0+OssOoKZAZ197w6lsnYM+mOxzI6HoWn3CjlOp1Tl/oy9xLDicOEj3ZQowJcVMYHE5PbIeRnTiKIaKeBTVH75hzkQNcsggq1nl1Kcu72rUQL7Uke8EJLEdTMIR4cXdsiCvzWtctWvRYTO4WX9XQ4kgKKOblgdp/YN8R3crPX7iX8LFuq321wUunA9DzYzfM89owgmLblGuz4plKxUKxYvq1ezWXEtar2KsYLhVhRNxCRkDYKEhiZhUdKptfoq9t90bwz89TAey87YBoMK0KtcwHlThqWgmi1fnmu8PogRscQ34sEYpvRKMS9auzVk3SOaTZWGjfE4XvkwRarfobGr9Y0LZxjy3Leby9I3fsWHPgg37u9lMGLCkY9X88hGufT02iP9xo/KVnRUy3Uz9YUX4sKtli3DM9wkJ4c4Aynb0ZtgEkWbbG4t4/ZoNPPh1mprK0LAWvmWJvw18BgzR4KA1AfoYv4z7r6jArhCPOexIWRhpBBx4ouuyl384DyJjz1hp7B+bPCQiqVMidnNVzbCSGNkooWX3FcSCGuJvdXq1lPNYgDSgs7N4Vm45AIKKGkJ2QaTysCwKhhgpOqW/MVRU8r1q2wbS5lCJKReEo3xOKWa7zbAQSbPLuAcNm6snO4ipOpPqk+wlk1W17lqZl8ffJ/VT2CJKNd9OlttFzmaiVlMinQkkV+HBSlnjiVKzOIrJTPACi/2ztoXOBclwC7kXtWQ6xO71FueJmJdTt/hBoznfCPXdunk09TlqWLEVVk5d0An1ksmyBIzyr4O1tIelRVqSoMrCU/r63USDMMQg5ap/k5pLHjDXPwftRrHdqexHUxp6zxEKKBzJB7t3ZtKMZQKDbeCDCe7DqYHNumOWyWTCvXqP7sv6wPkimzoEAu1COxkHMPCvJTk2+2wCWSQdckhsGjxxreHScMJ32MccSY0qOzbpYuEbbb2LBvt5+p9CSf/TAYRcKkoTWYyCFURvXwH8AYyApHPNb3IUPp6Dh98/KlbHtGDQw7360Ix6lSOc9QUXd7x9gNE5vNsEWQHHtL07UWM6K2JEntCYBQE2LJmpZaiFT9wA8XoMOsaH2b62q03pJXS11SnZpUNMsHS9A+R9eL9U5kz1ZjnYFOKalJIax8wJTog+32uMlwT64utnUpc2TyFkA8j4My5hfwpyiljIQXQ78fkvGrenGuUQJjBAyTNf1WS8pPnsw3O/ySmFMzwibqVgcCZgeCousBa1A659NqPc96caI7JJ1sJ5xIaAkLQC+seFLv1M7gi83bXRQhAQQ66jTpBT+eS4AGz0B+7I6iNdPQ0OWh6whfy6RhkyX8NtiwQJDxZZC1KNmuXJOc+PZQbWkG7PXl8uYSqG0HlydK984HOl89DMSdFmgV5g/gqC2CA5/qbfqeWiuXZffZ+ip5eEbRj2Vwkd2f1+jNuoU1ZYyMUfEMJw/SLwIpQuWDjVbbeuprwsmEY02+bULV6nP1OVsZbGJ1EQ6PWNufcfx6Q/sUK51XXW7ca++UbJqIPT6xBWgxwWmDCa5Ns2EgnVp6zJY6sjkdiKNJO6RBxXbdWmG+kjLF0rMYnL1jUCS5a5TRKQ/WEAOzc8SaHeiQt3r24Mec9wIEIB74ExEPSNOkLnkhGPRqI0JrlPg1FfWZ+SGOwMIrgI7BbnuIp0GxOX9Zmdh6jUy1yclH3CXKqeaLikU1ZDSALvTauLBD6Y59ucAOqoPZJTChmkG0pSoSB3vXBq0Cg0E1tAg4Q+guuC0j8giYQy0y9EuiAq/BLsX+3YDJHs0E78hDbrFY/mCcu/Ay5cMbfJZP5VK8W5wCoZl82IAoHBMYB4eL8PaacBKNN8sUMW1e3cYLx6fEDpMHtFQEGTmwdKAxOSJaNFnoz6IgX/xRITX2RqC0W6cRk485Y61XDgrJcgMmWCB8l3iVs1YRw1N5nSI2lyImT+fYigdvOGNjGI7h0pZjNALlswk7sZSt+ojSvOHCqdPqTYwBNukC/jCSck6cA/NGW3V2WYewaAnAyQ0QTb9sdOvXCh4okzsjth27Ns/zmqomADTuLigTPnZDLNMootLLh7ySWNmRp9DUaoYTlKXvmkmST0CNj4H6VJjWiVYBUG3odlStN32fPHbd2B1l135r7N4CHaLQCvgcNLGO7V1Vonty8MxL47W/S2Or/QsVkI5I9b3y+FxPpsJcFucxJE2HCF+EAbzExi7NEXXF7kLCN886CgKpVaeNbVulu/Re/Hgja816Vl4TcWslKsniQWHkWqldgP7b2qY5fwDpiSUm711v/Ipmsy9IWhzLMncdGfRGYzAtKtOEva8B0ZL9ko5klwUuepUvUB1FwxCNUfoMn4k2ju3z9HoTf7bQTY7kfYA7JOUaoZpluHR48WUNlmkWgIWwjqpN+4PpTdo/9DEB/R3vDmJXP/tQIa9cmnJgfBW7PZoVe5mpJ82XtHk2JmO0J5rNqarM0ronZHjZ5NvOaO2N2mS0YDcw8fLXvoHe6pz6HgzLo78XtI7AyPudvNQ+FIefXap8mjCPy26n1SVxXaX6nEyipefHlo6qe0rboXa3bxSul++SDmUf9IXLgzQ/Pl2AX90eGOmoaEjnGWb2sz4ub/oM74ntfsQFYwSjY149sOSiGWJV/EOKvSdvN5pkjGJkGCRbmo35eJVpXtE0KfYPkyxt1mS4yGQP1mxo2vOe/aM2+Vw3D2sV5+R9FzHiAvyyvhRrIKoDibKR9LaE8QyDFNgRfZisWgrzV7xBy9qrh9dUa8Dh0qsifOjP9NhjBHRaaZhfVNwsEDZaFYCds9euugHy/RvpbovSLbTZVBXDTwNHOc+EBpzeE1na8ei2r6/hcPWLComXR80rWS6m6ElZ7TgsTs5uut1mIryjd2TtvERhpvppBXo4adFYaR0wSTzKxGhiBshiiw0gi7JjMaopOIrLEoIgzwVpcS44yvJAzQ0kGk1QBAubD8UprgaJ2NbFHgzbgbE9u2fwqTCK6E1dk+SsEd0adRy+9Kp3XLd9ZfWFakHIc+/kvUsl1PeI9QV4o9jwKe1Dsn48wYNpnipK4RvAly9qqYZjWbAl4c24OpJqmIKR8+/96Zl3Y5ZwJWyvl9ANSyjiYNJBS/hePICe7rTEwHwGG/tEvNzwyDSzH6waZ8+FZ3JetFMLrVy07MeWC3YDSDKykJWE0hTD7E0/ew4cQykJeKASqe7aRjEUhY4TyIGeMvmiEXq3XEfcbcGuJCWzfdwBF/ecNMn+hF4iokeZW9/UkNTOQHp39J4844v9Um/SLZBakHMTLGplyp0j07vSTV29zl+AQPEMopCVZjDh8Sh45/3SRLvpiTR8cQifizr1jnVnTqjELEuY6RvxOlgAfqtA0Xq4HW+8vVUIn4+8e+nbaOwamozIHcsMOdCZS84sAUqSxWj02MmhAcWkrMIbqafiLKZpREnvVY4xoCNZKIClbQPSuEFxPFukfrZrM5Z6J51+tAx+6IW2QV0W2CKsQq4Os6oNIHTEUazVvnLIYGxzOSArjpWtylMTk6E4wle1t5xpmJq18idxfmvi0jIpphEpm3Upard7TCuZpjvfju6rLGUSmg2gaidRUlIKDUT03EkTZeOENLaMd8VeKi1i/Y4XVn2SMvwDopP76Cl355ajTpGi+FMbCFsGRbCy41lWjV6yFsmhIYemmKcZWpJMEtfL703EeKQTuDzfRKzWFpzViMJpCfLYUlrEDdqtr8nW5ZMcYhqPItExslSylxL/uEYdAPXRPJ1ekXMiC9Kvp3vcm9343kXstc4MKcMyaBJQrZydFOW1k8W75DMKxYtyYO4KCw/v0jg0eyOqLFZiTdOhdpcIBUA3ERAHzLdiTdzWISvXIXf9iL2XUZLBu1R2jcfyd6VpCF0VFQBfvtkyDKYmRSu0csoAAuWmFTyfyWUV1NdTjEMAbAhYMDUjOkbrPqRjMhUXOhtHjkKFIlXEvqdXLxNprYmIdxaiV5z5UOEyWN29u5MPzDeZbXv+ZghpusNiL4a+dO/x4hQ29SYYvaerhVPJI98CJ0Gd2zRhpHj04OpUaFZ4XMCees9iWhyyf5isidBMtYggiqUISr1VgXRCX8AlzmZzqwFaJzoz+uCU9tncTv7j4rTdrl/wdo1Udh7i4J6vetF3hNJIxcdF6NH9De5Ab99L+zL/XDMExQ9bh1mCdeKEZJ6TM9lG7t71fCg9DE2Ws8CK4zixcPImoWTSlQf+aMMxqqcoKMHx4tCm5LTLc2Brr0t2jnGdGlCsCY9OTAr57BxCKo6eFZoJXNI50VMQQvGC8M/RminRZNR+njeTIg8J12IcJhrcG1jt6Y2jEyvBtMkKrgOgf2wFD0ur0RuvO3o71yWf033eIEffATyAWh0DXxre3ektPKIO+EfrV3uwXQgsW3of30InrZPbuLzxxQPCRZ2bYI9AfMEnpUpYjXv5n52AudrbXXTsV2ThnEoLyGNsosvwU85JDUPVI5M+wM6ZNKHycoeSaOc6Gi2HRWJQccVnBD3GwtjNAXv2fUqj6PAsX6y1GHVR5hKj3zPmYdAwOtO8mB5QSUd1+qUSzjLezqqVC2as45VZttQ8YlQW/Kx61eZmE1evY7bp7YxDKxxLyg/63r6KixtwO02MKnhG4PxZi4rxjdvP7THLmtWThizyr+Z9+FYgqk7VsN3jjTcSGRQObSj1Dakl218eB6BtuC72tIw8X6mXu2T/KOnXpSRQYVu87BZDrySIH1CGrmLHmZumoIhtWHBmWBBv4zEb5vhR/L7Tyyf4vnnTQ+zZSb5sPfkcRrfD4PTAtbevTPBxnIe43UkcXDik7WyJbyat2JKF1aXhH2HwRujh6GMJoP13aN5bcVDzuzUJuzatwj1uQPTaj91qTjlctiIX3jQ7DugLEWFdAsfv05XcpfBDB7tiljNrUUlbeFmmWMVYtWqDXnNtozrE+dJIvXcoJ7TEV0RYHim6xkkFAStETT6qpCEONcu7YzlTDx87+NeaXz0oS1ZveiLZF4czGLncl/2mlIR8ziMyE5/XFwnkguuq5eBdDbU+EV8mgQjTJ+hnJoSgvEyuK2rWPKTnywF+CkFZzJt5p/MCjHckhCC0KvlUzFxNAICgJ7akrMoOk+eIac6WfStWvS5LpFTRZuEzqZsJkr9jZmYj8qYP56cUXqyXi4rKADwFJyu2qvku0XpxBVEBBmP4IIQFhh8FmH5LSbj+O0hQPqSLT1bGYxF0/LP+RN5AYxQy0ML7+KxTgBTpoO1wrKsMUhSVy534Od5yyR0nJtr9LZJObL6rNcw4fBdWi6RZvtEy6YbHUWgY+W5KzXJi8GJ7ccoK/lD4t4OeuGdl7JYUqHWOW7zR7JaIEuYqwDRSMqFm9E1Upq0tmrhjOWN0mQGOcsmXJFIhU2nMHV2rXNdNUNxgiRLBIYuUczFSyb53rWsk04U7ehZ/ygTFFCMY3Dj1yYpWrpnaWQ7xrHmTc4zeWhp08OQTaJJlzsYA8RU6NSf14ybO0f0WylnDZ4xgBA+9T83d/Ggz8vccImjcThHo6BiItIaiaESC7cpnWbU6tQCe2jMiUNmRIPgNboXEJxz5MlNG2xvDcb0YHL+oC+I/BCBSA9z3L4xmbM/PQvLiSKs7LwG/o/3rbftfn0p0SkFGaXQpDiH3E+iDwe4TbnTPA4BlnhVHpIJSNF3swkM8iY0OhKuCeQudSCmenm6lZzR36OPU7UKdL0r6NYCSG5q8A4wD8vNwbM4Ynbe+U69Liu/5AoCGK0hW7e6cYQGvHRkH6yHKiiyZHz9DGhaNGYUON5i6dGWU1AKmKWjb7MB8F77yNVM+qtGutg6abIaCgtWu8uUVO/CbFJW4aDAcjzb8gfv2Q5f17MhDHEUojN+90xrnXutbuozytAiKqqSwZ168YdLKvububqHeWbNqp9tbt5yw9JnVcgcu7d/11Sfjq485H3qO91z/OraEg7tThDM99EhiX10WEPeAF63yzdTIHMtxFEmZETvwF7jpVMM1GPXipfK8v2iSprnaPotj3QNk/1DOxFl4RZ+iwTun5V4lq2SkQ/YGyKUdidD0KzeCw7689TYQL5b295PvEfIxmW2DdfCCaFrimcdFYySxHgWmpuagHjW1YKk8RBWaevaJwkOmY1rdSIBWUPdcwhYls7PFmw5yie/TUlRdgxowc8kCbJTZdwLBElOVfX45tN7gNwaH8aN35eZif3QjiPYnNakwVFerekpilyxxykapdMaRlbmxAyHgygCNP5U/61W/ABv64CgOmk4snt9lJd5TaJw/tG/UcbfOG6imAkEBX1gs0amR4NLzkyagT9ADTxkfbYlGwrOZxIVPFSEcgO/8zONyEsjSPhUs0JAHuzFDtn92dNgyu9P1KjLHkRjdm+DG0bg9o15At7GFgWzwaYm87EQgOa8mfW8I0SojQ+2Gm3kLOzpoM4aj5N/kS0BX67FH2j3V25WIQ41aPJf3kUJ10gvYuleWN9Ga2fLscEqHSTdy7He7w1EdjMrGAo+LPQPZSof8Jc97+hh9q2bK8sLEe6UTXAA6+GzRNe/3OM1Mf4PpEVDzwMEGxt9kqOneGF0qtmEEBSHLrKa+yYXOjSMGgXkklSJ+5KcsPfp6uNmrNiifNbQMfBdYDR76XdQhtPw+GmlD1pEwIiuxuzQlj7gFdulhJV6PmU+tk/KpCz1eVqzr31lXOiJl1C57AVd3kAsSZArBeTv+NY4R+w2LSGr1uFHDfbBn5yaP090rmrI8/C+zgFHhDTCdBCAyExBWAE3q2HxOholFd9pKQ1RHZ1/UICkITZJednZv3cXh1a0dYL1/2/Hm+//vP+6SkJRf3eGnvr7b7JHNbv/Vd7MB3hetJOudYBSTHWyrhobct+aNIFRdfktPgxup1eIMuzbclDCixbcG+i2TtPls930EE6nWSZZOpfmBFL3IGGYeMG/sThV0M3DM87uw9idDWs0QLPnUDhIFHesD8xZd+PjU34MF7IFDsADrHjatYPySFG5YYpHQJWnVX0ia3ekh8GZ6Q/3Gv17MRgBdN0TEu6tTmTHrliCrCzgWaWztRLwLaTzDkrlhSL3xdkm6dHq7p0nezVV299e5QmbLFCNt8ySwOTD8aQY7MBUxcpTxfGhFcAY11mQkxMi1yTFITZWhaDloaCofRMy1rmhzaHUOT5KU+0MsJc9x8gmHQ1Nzie0DVtIJFN6+ypmifCFDmUESWT9rw3JEZYyeksm6Cl9dvq8zOcO8pz5ra6rJVcJxVwOTgUvQRNBe3FAuhF6rPmG1Dwjw46h/LtMD7ssxc9LQnQw3NMMGlnbn0QpvJgc9Dn+h2j2OtZir7lFJzIiub1t7Rz9HO7cfT7J1VoY1pZx+lmkZtGp8fmlNyerBA7FetzesRcx27Fjzi0/uQlp//URnEuGekdnhniLeKQQ38bpV9PnGCbeKNwQHsWiC7n6KEuKzQzreE66AhFt2MGgsnwqOyw/yeNgincJ8BkZZ8+4NqMeJjimScCbYdTMfdT3Jk3qv3UglB3BnsWbOT2UeTponbkO9pyihOn/X0xJumFfqKy2zbQDamFSvKbyFIUsnigyQ8Lr1WzrfRWDDCts/m1fprWjb8CdE5M9N4cbaGtE1ldLs9lolyTIHoDd6ljAuxcFOcnY1KR+I9OYaBxBSq+f7WCJ7xALyehJAF4EYIB5Vixsb3K8eK512iQFTIGS1JaQLM4w7TGLpc/GyH/Ig7M+CeZI7a0L2cLJ7hXQPeUcf6qcyS0e9PzU9hSlHNR/ePzkUZPKl/MHTNR0HvsEAwREn6MQXWXygPPsYERaRueX5Vd2Li+8Tblyfpe56p1zhaheuiKzf6bVbzC/iMAUQ3PnCG9q6oevJLw+/cg3vnO93i3EXn9te2BKYQLrB+jIBMDRl05KAKKuRC7pAgW3VFQwh48UDzde6aUcT7hkmNOtcY49sCIkXFNJtBBBtYTbNWBYOUtQEYQSo/maMNq0I+d4rd4M4aD+we29rCgnVon6F6/NTJXLqP0XKgG8LdA+c/uSjbpsQeiO4sJ5VAh6shAOg6CMWn7O3QJ/lPbdSfOSbuilaXe8+ERecuV8QKXso9k0lCbK7K5aSh6DSbgAcQ7HLyjlF5rTWehrWvPbHZXV9L8NCFLmdqb7yW29J79JQ996CYgYR9aC/gZd1G1YJZZdDo+M369eouEqbr8XZKx116p2FK5Rl2RZD0p2VSXT3s+3DY4bOnvAzB9WXtBB3QBcUaWQfUriUl1AVRSeQCYuJhfCQUTjKHZmaRYefe4pJ8xsidHhDxvDZ3a5yXZK5TYQ2+tqQD0c70Pe9Aw/LowUe+CUUaH5/toctMHx/Cd0Z2yjybIQCdLDoCD748oVk8zbrnXZD/ss6anrxKb48gRXxJQL8/dksXAPkiWBHsNdfiw+ZiSXrUByrRO3DOubhqblPFxCErD2l8wNzem+FYCuaUh1cOvzJrFWFLj1GXvCiIUpsX1mSvPiyf2MVt5O3aS8/lb5vc/9leLAbbFJwNhq7FMw8dj9uuM0ti/ACUUHtyYz6k/jk/HjD9UC30Vr0+UA8LyN8L3LdDEuTBsXc4cAH++icl84R9WTvNeGxr3J+wSbzXkgQzyJwqAhA8vLe2kBUlJaldjMWcV1UlZ3FfjQyixPDps5k1hnjoBkrFsJiygXPgoZIYYS9OzYXZTE5CV98USSSKH4+oadfB8t1zWRI5iFY4kcnMBfEgHnEtl5FAhGvHfYm8/KT9jvKuQ2P52ZZVhZ6rNhLhHEBgjE/DpC337kQhAlxD5Wb7ATwJLADjU2WKq3elsmF9tmuLyCG+T1WlRCHPtieF1MgVG4TDyEBHu5gDusb84cl6mFR6olwj3kiyDvx452jQ8aPNClBwMCVSgUToXsumArFRBgtd9Iqcac1cssn+/tTKujmRbeBSrZllrFPpliITC8RwvYRQlMtTdv35hnKMQtOIyZbQCD5MZ4VH0sZ2NqCgrrqOxASDR0Rgjc5pBK81/uIMpGQm08yImgBpDc/xot8bZJZZFvautQcd4o8os/NB07/8bwtHgqvr0/1KIvNYc+X4NFaQBRXTlcZjIJAT4o39xGZ+EUF6zdwzw4kvQ6WthDfmNAn34HSYs3Q3e8GWjq0Yy+/z+58XO7zBpq0iEYV7RnRHvf6rpwIpyxMPMkLzFtLdxoyUZEAFwJYCfXSzZGfytdl+zVOvs9P5VnFlhTZWit81Tixl6cOLWuQrUuZPwVO69wL8Y2NBXuI7WYT+HixfXTRp3fr5fTegZaqtsdx2s8GFD6VZ85s8jFRSuicucerJRChpdbHx9R3LwlaLcI7CtkYwEZ43zkjsqlpu5EaUF4/lEQE9hVFFMNpfXSRuhaqBP+2oJPvt94ZYTAADgG5SQD6ng4Q++yCSHfUVjryigsoEJaIb9RRsjr4c+Sm+KuGWHmUDOxBiEIKCsmFnQe04rzeA3NSBEWdaR/T5pZItS3j4OIEgFfloWAVJuOFguNITQi025LWYUOLCMlJQtH9cKGnETHA7K0zjO5ItaCemgPzC00AwIcmUkmS3LtBaAhVtJOjGC8BQbFUXRGQ/OGFSap5gUsw+YFmGpJMzZxh/IYlqYevoKxvHikdQr/w0Lm8iV6jAeupZutYPjjttn4rEMERWGUL6nfQJV70TfHG+Rw8Ude9h5vh2gzDXoUHc7y86LoBsA7Fxujc4CW54ICcnJjhKgYTTt6huui7oJWYBFFIvBRu6T4bNm3g7fCVGQujLkbh8Lbm0wZhnl6BOf2q2iR1qJwDJVEZLAbSVO8zLUjVLjEJeuaFd3JdNbm+Ddb03IBJewzN8WLWeXqASMtjwvyplrV1YJH5zANsY8wsFEMZCwZoWSqmWmBHUWR9M1H29AgbybP4FYE9lgQbtOv8iumeKll6Bohmg5Ql5h1mUS0zT0/tZ7uSptSWcEGe7EKu88Kr83FMt398ehFIMBjzIZ473GXeBtnXnfWhgA2+oaK99YiQwJJaQCEZJQrkE5G9Qw7gfBkeH+zSGbdqHQsTmTGWF8Pec7vF8e5hE/YaKO6u0WVlMCiy+mCYV99AdqDoesoQsR6mSERiVKAQ+nbHJ2Y0yCYpB5q9AR/qTmMkGypJ6PBzeqCPu2D2zDOWHiSpoppLefX8fZLB2Pc9A7B5x/0e8s5CMjwlXbaDx+inIvfv3YNYqRRaUbIynr+0p2mMIDgnnS3oMx5i8j7/AebW1RhGl/XnFTVphjycwXmObIZvSTckW1mdPVvEmEFhrmvuRVFVz8Zk2GWsrnt9shheQRA8vn3H/PO1Jcut7uSjelL2JqPDzT3J+8M2nF1bq9HS9J/gC7Jd+gJs6bSk+5/gC7JB4FfTcMGJbvlVE8z+CabbnU/7Nl2my/gB30+4E/TvU45vx/C343eZLMVXGw58ayvSMi++XRbG8K/GaP5qyH++9mcj3M8d/3SvCKPTpvn+AJ+/IaBMvl3k2xtEzYVKPy1/gtDmugN1gSxgXo7mqxkd1/5ubcou/a/vT3F1CgDexVCRT1cAWd8t/zWXZ/r1FQQP++eL7ydff+Xf/v3c4v79H97lr72QPUXdXC5l332/5D16P1f98U5X8/BLG/TDTaGrR8phvg6od1EuqTVEr/ub9xQNV1uxtFfnMeD157xMfZ3SfdNPnzNh8oHQHPrzN943icHfXsH6vAEDIt+O/+jMrGyaX7WDDwCB0L+NZiHwT8gPqgU98N+pFgih33/1a+VCgP+5bj3+o1v/urr1+I1uwcD/V91C/qNb/7K6BeLY/67hQv+jXP/CyoX/71ou7A+U6zd9/xd6PLo3pbufKCv3NPkjETAExF3o8A9F8GPXQg+axpG/TddiD+An/AGBt7BgEMGIH3Et/ntcC2LwT+ivTsF/3+V/5if/Ewngv1f2JE+tb4f9tBR93ndRw/7SSk392iV3ZzPAdfTLb5S+H76JpUqX5fim3dG69D8K7VeqDwG/V33u8/lDif156X69x/3wP0hs7tfp9a2J+KuFOKVNtJTbj5f6o27+dqrelx9D9V344I80BgJ+I6klmvJ0+XbWb4T182P8VfIj/qx5Tsrtv2tOYeB35hR4/dznvzR+7/3fmV0hjZJ0+ssm94dn/I0e/qJl4H/D8P71o/5vaVCxB/oTCv9mqCM/EfDvRzsK/QSCvx/ij8dPAPY/H9bfFfAfTC+oPjn+H7Xizz50PP2jK9StSuUrasimzLvru+U2j38nNYMef+BR/oyOgSD0t1Ey8C+7739V6IQhwE8EBv/sjR8/SgN7XIP+V5/H74RzuXII/pUzR38vJ4j4Cf3h8zfw9yD07ywz8CfkGx7DiQf2o8xgEPgJ+bXM/mFE9kdxyX8TkeEQ/n8R2T/wMPujeN+/jcyIn8DvArv7/p9kmP1RGO1fg4wSD+Sfgox+F/U/Pxu9BDMd/rcbfA6C+wF/Qr4fMvu3B/46Or4d/ekvs1jwG3L74pB/+v/LbAnwN8HIvx+zBf8oOPS/T2H+XaktcYGnfwxqi/9D6sV/qO3fS83+V6jtH8XV/k3wG4Eg/5TUFvqjmNe/jczQf0ZqC/0bR5BAAIZ/kNlvkNU/7jj7Nw4hXUJ7/EBuf3RV/7gDDf69iP7DrH7Dor4zjr8/jQJBEP8Jw77FRy5dQH8c+yDyEwz8fuz/BZL1B7dB/gJd+yKW/w269lnycwPgX35+je1C7ZP0/sX/AQ==&lt;/diagram&gt;&lt;/mxfile&gt;"><defs/><g><image 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diff --git a/content/9-Polkadot/img/state_sharding.drawio.svg b/content/9-Polkadot/img/state_sharding.drawio.svg
new file mode 100644
index 00000000..71fc0347
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+++ b/content/9-Polkadot/index.md
@@ -0,0 +1,20 @@
+# Polkadot
+
+## Learning Outcomes
+
+- Mission
+  - What are the goals behind Polkadot?
+- Elections
+  - How do we get validators to play our game?
+  - NPoS
+- Consenus
+  - How validators play the consensus game?
+  - Data collation
+  - Availability sharding
+  - Execution sharding
+  - Scheduling (+Coretime)
+  - XCMP
+- Tooling
+  - What extra tools are available to build on Polkadot?
+  - Cumulus
+  - Zombienet (Covered previously)
diff --git a/content/README.md b/content/README.md
index cd3c224b..254708a3 100644
--- a/content/README.md
+++ b/content/README.md
@@ -1,34 +1,13 @@
-# Course Materials Book
-
-This book is the home of the majority of materials used within the Core Developer Track of the [Polkadot Blockchain Academy](https://dot.li/pba-github).
-
-## Read the Book
-
-We suggest the [online](#hosted-online) version for general use, but cloning, installing, and building this book [offline](#build-offline) is a great option on-the-go.
-
-### Hosted Online
-
-The latest version is hosted at: <a target="_blank" href="https://polkadot-blockchain-academy.github.io/pba-book/">https://polkadot-blockchain-academy.github.io/pba-book/</a>
-
-### Build Offline
-
-The Core Developer Track of the Academy is Rust _heavy_ and as such, you need to [install rust](https://www.rust-lang.org/tools/install) before you can continue.
-
-In order to `make` your life easy 😉, there is a set of tasks that use [`cargo make`](https://sagiegurari.github.io/cargo-make/#overview).
-
-With [`cargo make`](https://sagiegurari.github.io/cargo-make/#installation) installed, you can list all tasks included to facilitate further installation, building, serving, formatting, and more with:
-
-```sh
-# Run from the top-level working dir of this repo
-makers --list-all-steps
-```
-
-The tasks should be self-explanatory, if they are not - please file an issue to help us make them better.
-
-## License and Use Policies
-
-All materials found within this repository are licensed under Mozilla Public License Version 2.0 - See the [License](./LICENSE.md) for details.
-
-In addition to the license, we ask you read and respect the Academy's [Code of Conduct](./CODE-OF-CONDUCT.md) and help us foster a healthy and scholarly community of high academic integrity.
-
-<h3 align="center"><a href="https://dot.li/pba-github">Learn more about and apply for the next Academy today!</a></h3>
+# Syllabus
+
+| Module | Name                                                                                                         |
+| ------ | ------------------------------------------------------------------------------------------------------------ |
+| 1      | [Cryptography for Blockchain](./1-Cryptography/index.md)                                                     |
+| 2      | [Interdisciplinary Concepts for Decentralized Devs (Econ, Polisci)](./2-Economics/index.md)                  |
+| 3      | [Blockchain](./3-Blockchain/index.md)                                                                        |
+| 4      | [Core and Basics](./4-Core_and_Basics/index.md)                                                              |
+| 5      | [PVM, Polkadot Architecture and Smart Contracts](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/index.md) |
+| 6      | [Protocol track (Polkadot Cloud)](./6-Protocol_On-Chain/index.md)                                            |
+| 7      | [dApps track (Polkadot Hub)](./7-dApps_Off-Chain/index.md)                                                   |
+| 8      | [Governance](./8-Governance/index.md)                                                                        |
+| 9      | [Polkadot, JAM and the future](./9-Polkadot/index.md)                                                        |
diff --git a/content/SUMMARY.md b/content/SUMMARY.md
index 0190420b..23a4025b 100644
--- a/content/SUMMARY.md
+++ b/content/SUMMARY.md
@@ -8,145 +8,145 @@
 
 ---
 
-- [🔐 Cryptography](./cryptography/index.md)
-
-  - [Introduction to Cryptography](./cryptography/intro/page.md)
-  - [Addresses and Keys](./cryptography/addresses/page.md)
-    - [`subkey` Demo](./cryptography/_materials/subkey-demo.md)
-  - [Hash Functions](./cryptography/hashes/page.md)
-  - [Many Time Pad](./cryptography/_materials/many-time-pad.md)
-  - [Encryption](./cryptography/encryption/page.md)
-  - [Digital Signature Basics](./cryptography/basic-signatures/page.md)
-  - [Advanced Digital Signatures](./cryptography/advanced-signatures/page.md)
-  - [Hash Based Data Structures](./cryptography/hash-based-data-structures/page.md)
-  - [Exotic Primitives](./cryptography/exotic-primitives/page.md)
-  - [Cryptography In Context](./cryptography/in-context/page.md)
-
-- [🪙 Economics and Game Theory](./economics/index.md)
-
-  - [Basics](./economics/basics/page.md)
-  - [Game Theory](./economics/game-theory/page.md)
-  - [Price Finding Mechanisms](./economics/price-finding-mechanisms/page.md)
-  - [Collective Decision Making](./economics/collective-decision-making/page.md)
-  - [The Economics of Polkadot](./economics/economics-of-polkadot/page.md)
-
-- [⛓️ Blockchains and Smart Contracts](./blockchain-contracts/index.md)
-
-  - [Overview](./blockchain-contracts/overview/page.md)
-  - [Rocket Cash](./blockchain-contracts/_materials/rocket-cash.md)
-  - [Digital Services as State Machines](./blockchain-contracts/services-as-state-machines/page.md)
-  - [Blockchain from Scratch](./blockchain-contracts/_materials/from-scratch.md)
-  - [Peer-to-Peer (P2P) Networking](./blockchain-contracts/p2p/page.md)
-  - [Blockchain from Scratch](./blockchain-contracts/_materials/from-scratch.md)
-  - [Platform Agnostic Bytecode](./blockchain-contracts/bytecode/page.md)
-  - [Wasm Executor](./blockchain-contracts/_materials/wasm-executor.md)
-  - [Blockchain Structure](./blockchain-contracts/structure/page.md)
-  - [Blockchain from Scratch](./blockchain-contracts/_materials/from-scratch.md)
-  - [Consensus Authoring](./blockchain-contracts/authoring/page.md)
-  - [Manual Consensus (aka BitStory)](./blockchain-contracts/_materials/manual-consensus-bitstory.md)
-  - [Econ & Game Theory in Blockchain](./blockchain-contracts/econ-game-theory/page.md)
-  - [Blockchain from Scratch](./blockchain-contracts/_materials/from-scratch.md)
-  - [Unstoppable Applications](./blockchain-contracts/unstoppable-apps/page.md)
-  - [Consensus Finality](./blockchain-contracts/finality/page.md)
-  - [Grandpa Board Game](./blockchain-contracts/_materials/grandpa-board-game.md)
-  - [Designing DAG-based consensus](./blockchain-contracts/dag/page.md)
-  - [Accounting Models & User Abstractions in Blockchains](./blockchain-contracts/accounting/page.md)
-  - [Adding Privacy to the UTXO model](./blockchain-contracts/utxo-privacy/page.md)
-  - [Light Clients and Bridges](./blockchain-contracts/light-clients-bridges/page.md)
-  - [EVM, Solidity, and Vyper](./blockchain-contracts/languages/page.md)
-  - [Contract Writing Workshop](./blockchain-contracts/_materials/contract-workshop.md)
-  - [Start Your Own Blockchain](./blockchain-contracts/_materials/start-your-own-blockchain.md)
-  - [Blockchain Forks](./blockchain-contracts/forks/page.md)
-  - [ink! Workshop](./blockchain-contracts/ink-workshop/page.md)
-  - [Additional Lessons](./additional.md)
-    - [Coordination and Trust in Web3](./blockchain-contracts/coordination-trust/page.md)
-    - [Resources, Fees, Ordering](./blockchain-contracts/resources-fees-ordering/page.md)
-    - [The Quest for Infrastructure](./blockchain-contracts/infrastructure/page.md)
-    - [Wasm Smart Contracts in Ink!](./blockchain-contracts/ink/page.md)
-
-- [🧬 Substrate](./substrate/index.md)
-
-  - [Introduction](./substrate/intro/page.md)
-  - [Wasm Meta-Protocol](./substrate/wasm/page.md)
-  - [Show me the Code](./substrate/code/page.md)
-  - [Interacting with a Substrate Blockchain](./substrate/interact/page.md)
-  - [Transaction Pool and it's Runtime API](./substrate/txpool-api/page.md)
-  - [SCALE Codec](./substrate/scale/page.md)
-  - [Substrate and FRAME Tips and Tricks](./substrate/tips-tricks/page.md)
-  - [Merklized Storage](./substrate/storage/page.md)
-
-- [🧱 FRAME](./frame/index.md)
-
-  - [Introduction](./frame/intro/page.md)
-  - [Proof of Existence Runtime](./frame/_materials/proof-of-existence.md)
-  - [Pallet Coupling](./frame/coupling/page.md)
-  - [Pallets & Traits](./frame/traits/page.md)
-  - [FRAME Storage](./frame/storage/page.md)
-  - [Events and Errors](./frame/events-errors/page.md)
-  - [Calls](./frame/calls/page.md)
-  - [Hooks](./frame/hooks/page.md)
-  - [Origin](./frame/origin/page.md)
-  - [Outer Enum](./frame/outer-enum/page.md)
-  - [Construct Runtime](./frame/construct-runtime/page.md)
-  - [Benchmarking 1](./frame/benchmarking-1/page.md)
-  - [Benchmarking 2](./frame/benchmarking-2/page.md)
-  - [Benchmarking Activity](./frame/_materials/benchmarking-activity.md)
-  - [Deep Dive](./frame/dive/page.md)
-  - [Signed Extensions](./frame/extensions/page.md)
-  - [Migrations and Try Runtime](./frame/migrations/page.md)
-  - [Extras](./frame/extras/page.md)
-
-- [🟣 Polkadot](./polkadot/index.md)
-
-  - [Introduction](./polkadot/intro/page.md)
-  - [The Decisions of Polkadot](./polkadot/decisions/page.md)
-  - [What is Shared Security?](./polkadot/shared-security/page.md)
-  - [Execution Sharding in Polkadot](./polkadot/execution-sharding/page.md)
-  - [Data Availability and Sharding](./polkadot/data-sharding/page.md)
-  - [Cumulus](./polkadot/cumulus/page.md)
-  - [Ecosystem and Economy](./polkadot/ecosystem-economy/page.md)
-  - [Register a Parachain](./polkadot/_materials/regiser.md)
-  - [Cross-Chain Message Passing (XCMP)](./polkadot/xcmp/page.md)
-  - [Zombienet](./polkadot/zombienet/page.md)
-  - [Asynchronous Backing (Shallow)](./polkadot/async-backing-shallow/page.md)
-  - [Light Clients and Unstoppable Apps](./polkadot/light-clients/page.md)
-  - [Blockchain Scaling - Monolithic and Homogeneous](./polkadot/scaling-homogeneous/page.md)
-  - [Blockchain Scaling - Modular and Heterogeneous](./polkadot/scaling-heterogeneous/page.md)
-  - [Additional Lessons](./additional.md)
-    - [Asynchronous Backing (Deep)](./polkadot/async-backing-deep/page.md)
-    - [Blockspace: The Product of Polkadot](./polkadot/blockspace/page.md)
-    - [Build a Parachain](./polkadot/build-a-parachain/page.md)
-    - [Availability Cores](./polkadot/availability-cores/page.md)
-    - [Polkadot Fellowship](./polkadot/fellowship/page.md)
-    - [Nominated Proof of Stake](./polkadot/npos/page.md)
-    - [OpenGov](./polkadot/opengov/page.md)
-
-- [💱 XCM](./xcm/index.md)
-
-  - [Introduction to Cross Consensus Messaging (XCM)](./xcm/intro/page.md)
-  - [XCVM](./xcm/xcvm/page.md)
-  - [XCM Pallet](./xcm/pallet/page.md)
-  - [Parachain XCM Configuration](./xcm/config/page.md)
-  - [Additional Lessons](./additional.md)
-    - [XCM Activities](./xcm/_materials/activities.md)
-    - [XCM in Polkadot](./xcm/polkadot/page.md)
-    - [XCM in Use](./xcm/in-use/page.md)
-    - [Beyond Asset Transfers](./xcm/beyond/page.md)
-
-# 🍰 Additional Content
-
----
-
-- [🕵️ Applied Security](./security/index.md)
-
-  - [Cybersecurity Overview](./security/overview/page.md)
-  - [Awareness](./security/awareness/page.md)
-  - [User Centric](./security/user-centric/page.md)
-  - [Infrastructure](./security/infrastucutre/page.md)
-  - [Application](./security/appsec/page.md)
-  - [Common Security Risks](./security/risks/page.md)
-
-- [𝞨 Formal Methods for Rust](./formal-methods/intro/page.md)
+- [Cryptography](./1-Cryptography/index.md)
+
+  - [Intro](./1-Cryptography/1-Intro-slides.md)
+  - [Addresses](./1-Cryptography/2-Addresses-slides.md)
+  - [Hashes](./1-Cryptography/3-Hashes-slides.md)
+  - [Encryption](./1-Cryptography/4-Encryption-slides.md)
+  - [Basic Signatures](./1-Cryptography/5-Basic_Signatures-slides.md)
+  - [Advanced Signatures](./1-Cryptography/6-Advanced_Signatures-slides.md)
+  - [Hash Based Data Structures](./1-Cryptography/7-Hash_Based_Data_Structures-slides.md)
+  - [Exotic Primitives](./1-Cryptography/8-Exotic_Primitives-slides.md)
+  - [ZK Proofs](./1-Cryptography/9-ZK_Proofs-slides.md)
+  - [Advanced ZK proofs](./1-Cryptography/10-Advanced_ZK_proofs-slides.md)
+  - [Cryptography In Context](./1-Cryptography/11-Cryptography_In_Context-slides.md)
+
+- [Economics and Game Theory](./2-Economics/index.md)
+
+  - [Economics basics](2-Economics/1-Economics_Basics-slides.md)
+  - [Game theory](2-Economics/2-Game_Theory-slides.md)
+  - [Price finding mechanisms](2-Economics/3-Price_Finding_Mechanisms-slides.md)
+  - [Economics of polkadot](2-Economics/4-Economics_of_Polkadot-slides.md)
+
+- [Blockchain](./3-Blockchain/index.md)
+
+  - [Coordination and centralization](./3-Blockchain/1-Coordination_And_Centralization-slides.md)
+  - [P2P Network](./3-Blockchain/2-P2P_Networks-slides.md)
+  - [State Machines](./3-Blockchain/2.5-State_Machines-slides.md)
+  - [Blockchain structrucre](./3-Blockchain/3-Blockchain_Structure-slides.md)
+  - [Accounts and UTXOs](./3-Blockchain/4-Accounts_and_UTXOs-slides.md)
+  - [Consensus Authoring](./3-Blockchain/5-Consensus-Authoring-slides.md)
+  - [Econ and Game Theory in Blockchain](./3-Blockchain/6-Econ_and_Game_Theory_in_Blockchain-slides.md)
+  - [Forks](./3-Blockchain/7-Forks-slides.md)
+  - [Consenus finality](./3-Blockchain/8-Consensus_Finality-slides.md)
+  - [Light clients and bridges](./3-Blockchain/9-Light_Clients_and_Bridges-slides.md)
+
+- [Core and Basics](./4-Core_and_Basics/index.md)
+
+  - [JSON-RPC](./4-Core_and_Basics/2-JSON-RPC-slides.md)
+  - [Metadata](./4-Core_and_Basics/2-Metadata-slides.md)
+  - [Runtime](./4-Core_and_Basics/2-Runtime-slides.md)
+  - [Scale](./4-Core_and_Basics/2-scale-slides.md)
+
+- [PVM, Polkadot Architecture and Smart Contracts](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/index.md)
+
+  - [Polkadot Architecture](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/1-Polkadot_Architecture-slides.md)
+  - [Smart contracts 101](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/2-Smart-Contracts-101-slides.md)
+  - [Platform agnostic bytecode](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/3-Platform_Agnostic_Bytecode-slides.md)
+  - [PVM](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/4-PVM-slides.md)
+  - [History of contracts on Polkadot](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/5-History_of_Contracts_on_Polkadot-slides.md)
+  - [Smart contracts Polkadot](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-0-smart-contracts-polkadot-slides.md)
+  - [Revive compiler](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-1-Revive-compiler-slides.md)
+  - [Pallet-revive-runtime](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-2-pallet-revive-runtime-slides.md)
+  - [Blockchain Asset-hub](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/6-3-Blockchain_Asset-Hub-slides.md)
+  - [Hackathon](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/8-Hackathon-slides.md)
+  - [Inkubator](./5-PVM-Polkadot-Architecture-and-Smart-Contracts/11-inkubator-presentation-slides.md)
+
+- [Protocol track - Polkadot Cloud](./6-Protocol_On-Chain/index.md)
+
+  - [Substrate](./6-Protocol_On-Chain/Substrate/README.md)
+
+    - [Intro](./6-Protocol_On-Chain/Substrate/1-Intro-to-Substrate-slides.md)
+    - [WASM meta-protocol](./6-Protocol_On-Chain/Substrate/2-Wasm-Meta-Protocol-slides.md)
+    - [Merklalized Storage](./6-Protocol_On-Chain/Substrate/3-Merklized-Storage-slides.md)
+    - [Transaction pool](./6-Protocol_On-Chain/Substrate/4-Transaction-Pool-slides.md)
+    - [text](./6-Protocol_On-Chain/Substrate/9-SCALE-slides.md)
+    - [text](./6-Protocol_On-Chain/Substrate/9-Substrate-FRAME-Tips-Tricks-slides.md)
+    - [text](./6-Protocol_On-Chain/Substrate/9-Substrate-Interactions-slides.md)
+
+  - [FRAME](./6-Protocol_On-Chain/FRAME/lectures.md)
+
+    - [Intro](./6-Protocol_On-Chain/FRAME/1-Intro_to_FRAME/Intro_to_FRAME-slides.md)
+
+      - [Pallet coupling](./6-Protocol_On-Chain/FRAME/1-Intro_to_FRAME/Pallet_Coupling-slides.md)
+      - [Pallets traits](./6-Protocol_On-Chain/FRAME/1-Intro_to_FRAME/Pallets_Traits-slides.md)
+
+    - [Basics](./6-Protocol_On-Chain/FRAME/2-FRAME_Basics/index.md)
+
+      - [Calls](./6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Calls-slides.md)
+      - [Events and errors](./6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Events_and_Errors-slides.md)
+      - [Frame Storage](./6-Protocol_On-Chain/FRAME/2-FRAME_Basics/FRAME_Storage-slides.md)
+      - [pallet-hookst](./6-Protocol_On-Chain/FRAME/2-FRAME_Basics/Pallet_Hooks-slides.md)
+
+    - [Runtime: Construct](./6-Protocol_On-Chain/FRAME/3-FRAME_Runtime/Construct_Runtime-slides.md)
+    - [Runtime: Origins](./6-Protocol_On-Chain/FRAME/3-FRAME_Runtime/Origins-slides.md)
+
+    - [Production: Benchmarking](./6-Protocol_On-Chain/FRAME/4-FRAME_Production/Benchmarking-slides.md)
+    - [Production: Migrations and try](./6-Protocol_On-Chain/FRAME/4-FRAME_Production/Migrations_and_try_runtime-slides.md)
+
+    - [Extras](./6-Protocol_On-Chain/FRAME/5-FRAME_Extras/FRAME-Extras-slides.md)
+
+      - [Deep dive](./6-Protocol_On-Chain/FRAME/5-FRAME_Extras/FRAME-Deep-Dive-slides.md)
+      - [Misc](./6-Protocol_On-Chain/FRAME/5-FRAME_Extras/FRAME-Miscellaneous-slides.md)
+      - [Outer enum](./6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Outer_Enum-slides.md)
+      - [Signed Extensions](./6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Signed_Extensions-slides.md)
+      - [Transaction Extensions](./6-Protocol_On-Chain/FRAME/5-FRAME_Extras/Transaction_Extensions-slides.md)
+
+  - [XCM](./6-Protocol_On-Chain/XCM/README.md)
+
+    - [Intro](./6-Protocol_On-Chain/XCM/1-Introduction-slides.md)
+    - [Primitives](./6-Protocol_On-Chain/XCM/2-Primitives-slides.md)
+    - [Cross-consensus transfers](./6-Protocol_On-Chain/XCM/2.5-Cross-Consensus-Transfers-slides.md)
+    - [Executor](./6-Protocol_On-Chain/XCM/3-Executor-slides.md)
+    - [Pallet-XCM](./6-Protocol_On-Chain/XCM/4-Pallet-Xcm-slides.md)
+    - [XCM-config](./6-Protocol_On-Chain/XCM/5-Xcm-config-slides.md)
+    - [XCM-emulator](./6-Protocol_On-Chain/XCM/6-Xcm-emulator-slides.md)
+
+  - [Zombienet](./6-Protocol_On-Chain/Zombienet-slides.md)
+
+- [dApps track - Polkadot Hub](./7-dApps_Off-Chain/index.md)
+
+  - [PolkadotJS - origins](./7-dApps_Off-Chain/1-1-polkadot-js-origins-slides.md)
+  - [PolkadotJS - What is it](./7-dApps_Off-Chain/1-2-polkadot-js-what-is-it-slides.md)
+  - [PolkadotJS - Importance](./7-dApps_Off-Chain/1-3-polkadot-js-importance-slides.md)
+  - [PolkadotJS - When to use it](./7-dApps_Off-Chain/1-4-polkadot-js-when-to-use-slides.md)
+  - [PolkadotJS - Limitations](./7-dApps_Off-Chain/1-5-polkadot-js-limitations-slides.md)
+  - [PolkadotJS - Future](./7-dApps_Off-Chain/1-6-polkado-js-future-slides.md)
+  - [PAPI starter](./7-dApps_Off-Chain/2-papi-starter-slides.md)
+  - [Metadata](./7-dApps_Off-Chain/3-metadata-slides.md)
+  - [JSON-RPC spec](./7-dApps_Off-Chain/4-json-rpc-spec-slides.md)
+  - [Transactions](./7-dApps_Off-Chain/5-transactions-slides.md)
+  - [Polkadot API](./7-dApps_Off-Chain/6-polkadot-api-slides.md)
+  - [PAPI SDKs](./7-dApps_Off-Chain/7-papi-sdks-slides.md)
+
+- [Governance](./8-Governance/index.md)
+
+- [Polkadot, JAM and the Future](./9-Polkadot/index.md)
+
+  - [Polkadot reintroduction](./9-Polkadot/1-polkadot-reintroduction-slides.md)
+  - [Staking](./9-Polkadot/2-staking-slides.md)
+  - [Block production](./9-Polkadot/3-block-production-slides.md)
+  - [State sharding collators and cumulus slides](./9-Polkadot/4-state-sharding-collators-and-cumulus-slides.md)
+  - [Data availability (backing and availability)](./9-Polkadot/5-data-availability-backing-and-availability-slides.md)
+  - [Execution Sharding (approvals and disputes)](./9-Polkadot/6-execution-sharding-approvals-and-disputes-slides.md)
+  - [Confirmations and finality](./9-Polkadot/7-confirmations-and-finality-slides.md)
+  - [Agile coretime](./9-Polkadot/8-agile-coretime-slides.md)
+  - [Polkadot Ecosystem Economy](./9-Polkadot/9-polkadot-ecosystem-economy-slides.md)
+  - [JAM - Math to code](./9-Polkadot/14-jam-math-to-code-slides.md)
+  - [JAM - How to start](./9-Polkadot/15-JAM-how-to-start-slides.md)
+
+- [Formal Methods for Rust](./formal-methods/intro/page.md)
 
 # 👪 Contributing
 
diff --git a/content/blockchain-contracts/README.md b/content/blockchain-contracts/README.md
deleted file mode 120000
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--- a/content/blockchain-contracts/README.md
+++ /dev/null
@@ -1 +0,0 @@
-index.md
\ No newline at end of file
diff --git a/content/blockchain-contracts/_materials/contract-workshop.md b/content/blockchain-contracts/_materials/contract-workshop.md
deleted file mode 100644
index b62da7d3..00000000
--- a/content/blockchain-contracts/_materials/contract-workshop.md
+++ /dev/null
@@ -1,7 +0,0 @@
-# Contract Workshop
-
-Web2 digital cash example.
-
-## 📥 Clone to start: <a target="_blank" href="https://github.com/Polkadot-Blockchain-Academy/contract-workshop">Contract Workshop</a>
-
-See the README included in the repository for further instructions.
diff --git a/content/blockchain-contracts/_materials/from-scratch.md b/content/blockchain-contracts/_materials/from-scratch.md
deleted file mode 100644
index f6b0a439..00000000
--- a/content/blockchain-contracts/_materials/from-scratch.md
+++ /dev/null
@@ -1,8 +0,0 @@
-# Blockchain from Scratch
-
-Learn the fundamentals of blockchain by building it from scratch.
-In Rust.
-
-## 📥 Clone to start: <a target="_blank" href="https://github.com/Polkadot-Blockchain-Academy/blockchain-from-scratch">Blockchain from Scratch</a>
-
-See the README included in the repository for further instructions.
diff --git a/content/blockchain-contracts/_materials/grandpa-board-game.md b/content/blockchain-contracts/_materials/grandpa-board-game.md
deleted file mode 100644
index dde3c474..00000000
--- a/content/blockchain-contracts/_materials/grandpa-board-game.md
+++ /dev/null
@@ -1,220 +0,0 @@
-# Grandpa - The Board Game
-
-> - Players: 5+ (4 actual players, 1 author)
-> - Play time: 15 - 60 min
-> - Materials: A large whiteboard and many colored markers
-
-## Overview
-
-Grandpa is a Byzantine fault tolerant blockchain finality gadget ([formal spec](https://arxiv.org/pdf/2007.01560.pdf)).
-This collaborative board game allows players to learn and practice the Grandpa protocol while also having fun together.
-
-Your goal in the game is to finalize blocks in an ever-growing blockchain data structure.
-You will work together to share information with other players and reach consensus.
-But watch out; some players may be Byzantine!
-
-<center>
-<figure>
-    <img src="./img/generals-board-game.jpg" />
-    <figcaption><b>Pictured: Byzantine Generals solving distributed consensus via a board game.</b></figcaption>
-</figure>
-</center>
-
-Some less important details of the grandpa protocol (such as primaries, and timeout conditions) are omitted from the board-game for the sake of playability and clarity.
-
-## Setup
-
-Select one participant to act as the "author" who is responsible for creating the blockchain structure, but will not actually play the grandpa protocol.
-The remaining participants are all players in the grandpa protocol.
-
-Give one marker to each participant including the author.
-Each player should have their own marker color.
-Avoid colors that are hard to distinguish such as light red and pink.
-If you have colorblind players, take special care when choosing marker colors.
-
-Choose a goal number of blocks that you wish to finalize together as a team.
-The game will end when you reach this block number.
-
-### Views and Gossip
-
-The grandpa protocol operates in a decentralized asynchronous blockchain network.
-As such, there is no universal view of the blockchain data structure or the messages that are being passed between players in the protocol.
-Some players may see more information than others and information may arrive to the various players in different orders.
-
-Divide the whiteboard into a dedicated space for each player in the protocol.
-Each player should have roughly 50cm X 50cm.
-The author does not need their own dedicated space.
-
-<center>
-<img src="./img/board-setup.svg" />
-</center>
-
-Throughout the game all participants including the author are responsible for communicating with other players by adding information _to other players dedicated spaces_.
-In fact, most of the marks that you make during the game will be on someone else's space rather than your own.
-For a more realistic game, take care to share information with other players in a different order each time.
-
-### Genesis Block
-
-Before game play begins, the author draws a single genesis block labeled `G` on each player's view.
-Each player marks the genesis block as final by shading it with their color in their own view.
-
-<center>
-<img src="./img/genesis.svg" />
-</center>
-
-## Authoring
-
-The author is responsible for creating the blockchain data structure and gossiping it to the players.
-As the game progresses the author will grow the blockchain by creating descendant blocks of this genesis block.
-The author may create blocks anywhere in the chain they see fit.
-They may create forks, or linear runs without forks.
-They may create a long chain and then go back and create shorter forks from earlier in the chain.
-
-When the author creates a block they should gossip it to all players by drawing it on each player's view.
-A block is drawn with a pointer to its parent block and a short unique block identifier like a few characters or digits.
-The author should take care to vary to order in which they place new blocks on various players' views.
-In fact, the author may even gossip multiple blocks to a single player before going back and gossiping any of them to other players.
-However the author should ensure that all blocks are eventually gossiped to all players.
-
-<center>
-<figure>
-    <img src="./img/authoring-gossip.svg" />
-    <figcaption><b>Two blocks have been authored since genesis. Not all players have heard about block <code>DEF</code> yet.</b></figcaption>
-</figure>
-</center>
-
-In some ways the author acts as a "party host" or "dungeon master" for the game.
-They should observe the players progress, struggles, and enthusiasm, and author accordingly.
-If players are struggling to keep up or getting frustrated or overwhelmed the author should slow down the authoring rate or build a simpler chain with fewer forks.
-If players are easily finalizing blocks or getting bored the author should speed up, create a more complex tree with many forks, or decrease the synchrony.
-
-## Game Play
-
-The Grandpa protocols proceeds in rounds.
-Each player has their own view of what round they are on, and not all players will be on the same round at the same time.
-In each round, each player casts two votes known as the "prevote" and "precommit" in that order.
-Each player begins in round 1.
-
-Like many other BFT protocols, Grandpa requires strictly greater than 2/3 of players (not counting the author) to be properly following the protocol.
-For the remainder of this section this will be referred to as a "threshold".
-
-### Prevoting
-
-Each player begins a round by casting their prevote.
-A prevote can be thought of as a non-binding signal for what the player hopes to finalize in this round.
-Generally the prevote should be for the longest chain that extends the best finalized block.
-A player casts their prevote by writing the current round number off to the right of the block they are prevoting for first on their own view, and then on other players' views.
-Remember you should send your prevotes out to other players in a different order each time, and it is okay to allow some latency between sending it to each player.
-
-<center>
-<figure>
-    <img src="./img/prevote.svg" />
-    <figcaption><b>Players 1 and 4 have cast prevotes for block <code>ABC</code> in round 2. Their prevote has not yet been gossiped to all players. Players 2 and 4 have not yet cast prevotes for round 2.</b></figcaption>
-</figure>
-</center>
-
-If a player hasn't yet seen the block you're prevoting for, you may add the block and its parents to their view.
-
-### The Prevote Ghost
-
-When a player has seen a threshold of prevotes in the current round, they can _may_ mark the round's "Prevote Ghost" on their own view.
-They may also choose to wait a short time to see if any new prevotes are coming in.
-The prevote ghost is defined as the highest block that has a threshold of prevotes, and it is marked by drawing the letters `PG` and a round number off to the left of the block.
-For example `PG2` for the round two prevote ghost.
-(Or optionally `👻2` if you are feeling artistic).
-
-<center>
-<figure>
-    <img src="./img/prevote-ghost.svg" />
-    <figcaption><b>Now that player 1 has seen a threshold of prevotes (3 in this case of 4 players), they can mark the prevote ghost. No other players have seen enough prevotes to mark a prevote ghost yet.</b></figcaption>
-</figure>
-</center>
-
-### The Estimate
-
-As you mark your prevote ghost, also mark your estimate on your own view to the left of the same block that is the prevote ghost with the letter `E` and a round number.
-For example, `E4` for round four's estimate.
-
-<center>
-<figure>
-    <img src="./img/mark-estimate.svg" />
-    <figcaption><b>In round 4, Player 1 has marked their prevote ghost previously, and is now setting the estimate to the same slide.</b></figcaption>
-</figure>
-</center>
-
-A round's estimate is defined as the highest block that is in the chain of the prevote ghost that could possibly achieve a threshold of precommits.
-So while the estimate _begins_ at the same block as the prevote ghost, it may move up the chain as more precommits come in.
-
-### Precommitting
-
-Once you have marked a prevote ghost, you may, again, wait a short time for any more prevotes to come in.
-Once you get tired of waiting (or when you have seen all the prevotes), you may cast your precommit for the block that you see as the prevote ghost.
-Mark your precommit first on your own view and then on other players' views by writing the round number off to the right of the block and circling it.
-Precommits are distinguished from prevotes by the circle.
-Remember not all players will agree on which block is the prevote ghost, so others may precommit for blocks different than you have.
-
-<center>
-<figure>
-    <img src="./img/precommitting.svg" />
-    <figcaption><b>Player 1 casts their round 4 precommit for the block that they see as the prevote ghost. They have also observed a Player 2's precommit.</b></figcaption>
-</figure>
-</center>
-
-As you observe more precommits appearing on your view, your estimate may change. Specifically it may move up the chain to ancestor blocks.
-
-<center>
-<figure>
-    <img src="./img/estimate-moves.svg" />
-    <figcaption><b>As Player 1 observes more precommits arriving, it becomes impossible for block<code>GHI</code> to achieve a threshold of precommits, and thus the estimate moves up the chain.</b></figcaption>
-</figure>
-</center>
-
-### Completing a Round
-
-We will decide that _some_ block is finalized in each round, although it may be a block that was already finalized in a previous round.
-We will only ever finalize an ancestor of the estimate.
-Once some ancestor of the estimate has achieved a threshold of precommits, you can declare that block finalized by shading it with your color on your view.
-
-<center>
-<img src="./img/finalizing.svg" />
-</center>
-
-After a round has completed, you may choose to erase the votes for that round from your view to keep the board tidy.
-But you are not required to do so.
-Be careful not to erase votes for _future_ rounds by accident as some players may have advanced to the next round before you.
-
-<center>
-<figure>
-    <img src="./img/erasing.svg" />
-    <figcaption><b>As Player 1 has completed round 4 and has erased markings related to round 4. They have NOT erased marking related to round 5.</b></figcaption>
-</figure>
-</center>
-
-Proceed to the next round.
-
-## Ending the Game
-
-Grandpa is intended to continue finalizing blocks forever.
-Since you likely don't want to play this board game forever, the board game does have an end.
-
-The honest players win when they all finalize the goal number of blocks chosen at the beginning without a safety violation.
-
-The Byzantine players (if any; see next section) win when two honest players finalize conflicting blocks or the honest players get fed up and flip the whiteboard over.
-
-## Byzantine Actors
-
-Once you have played a few rounds of the game and are able reliably finalize new blocks, you can spice things up by assigning one or more players to be Byzantine.
-Byzantine players are not required to follow the protocol rules.
-For example they may:
-
-- Prevote for chains that do not extend the latest finalized chain
-- Precommit for blocks other than the ones indicated by the prevote
-- Go back and cast votes in previous rounds
-- Fail to participate at all.
-
-When first adding Byzantine players, you may assign the Byzantine roles such that everyone knows who is Byzantine.
-Or, for a more realistic experience, you may assign it blindly by eg drawing straws.
-Remember that in order for Grandpa to work you must have strictly less than one third of grandpa players Byzantine.
-
-For the most realistic experience, allow players to self select whether they are Byzantine.
-By doing this there is no guarantee that the honest super majority criteria is met and you experience safety faults where different players finalize conflicting chains.
diff --git a/content/blockchain-contracts/_materials/img/authoring-gossip.svg b/content/blockchain-contracts/_materials/img/authoring-gossip.svg
deleted file mode 100644
index 26c68df0..00000000
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diff --git a/content/blockchain-contracts/_materials/img/finalizing.svg b/content/blockchain-contracts/_materials/img/finalizing.svg
deleted file mode 100644
index fb4bb175..00000000
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diff --git a/content/blockchain-contracts/_materials/img/generals-board-game.jpg b/content/blockchain-contracts/_materials/img/generals-board-game.jpg
deleted file mode 100644
index 3fd4a818..00000000
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diff --git a/content/blockchain-contracts/_materials/img/genesis.svg b/content/blockchain-contracts/_materials/img/genesis.svg
deleted file mode 100644
index a15d1c78..00000000
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 1px; height: 1px; padding-top: 260px; margin-left: 225px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: #D92F78; "><div style="display: inline-block; font-size: 24px; font-family: Helvetica; color: rgb(217, 47, 120); line-height: 1.2; pointer-events: all; font-weight: bold; white-space: nowrap;"><font color="#24CC85">4</font></div></div></div></foreignObject><text x="225" y="267" fill="#D92F78" font-family="Helvetica" font-size="24px" text-anchor="middle" font-weight="bold">4</text></switch></g><rect x="197" y="305" width="21" height="40" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 1px; height: 1px; padding-top: 325px; margin-left: 208px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: #D92F78; "><div style="display: inline-block; font-size: 24px; font-family: Helvetica; color: rgb(217, 47, 120); line-height: 1.2; pointer-events: all; font-weight: bold; white-space: nowrap;">4</div></div></div></foreignObject><text x="208" y="332" fill="#D92F78" font-family="Helvetica" font-size="24px" text-anchor="middle" font-weight="bold">4</text></switch></g><rect x="199" y="241" width="21" height="40" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; 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diff --git a/content/blockchain-contracts/_materials/img/precommitting.svg b/content/blockchain-contracts/_materials/img/precommitting.svg
deleted file mode 100644
index 033a4134..00000000
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diff --git a/content/blockchain-contracts/_materials/img/prevote-ghost.svg b/content/blockchain-contracts/_materials/img/prevote-ghost.svg
deleted file mode 100644
index 34d949f1..00000000
--- a/content/blockchain-contracts/_materials/img/prevote-ghost.svg
+++ /dev/null
@@ -1,4 +0,0 @@
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\ No newline at end of file
diff --git a/content/blockchain-contracts/_materials/img/prevote.svg b/content/blockchain-contracts/_materials/img/prevote.svg
deleted file mode 100644
index db56b5e4..00000000
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diff --git a/content/blockchain-contracts/_materials/manual-consensus-bitstory.md b/content/blockchain-contracts/_materials/manual-consensus-bitstory.md
deleted file mode 100644
index b9c8d5df..00000000
--- a/content/blockchain-contracts/_materials/manual-consensus-bitstory.md
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@@ -1,113 +0,0 @@
-# Manual Consensus (aka BitStory)
-
-In this activity students will encounter and explore blockchain consensus mechanisms such as PoW, PoA, and PoS by acting them out manually.
-
-Students will collaborate in telling a shared story.
-The shared story is represented by a blockchain with one word in each block.
-To add a word to the story, a student must create a valid block, and draw that block on the community whiteboard\*
-
-<pba-flex center>
-
-<img src="./img/bitStoryLive.jpg" style="width:700px;" />
-
-</pba-flex>
-
-- If no whiteboard is available, you may be able to substitute; a paper, online drawing tool, or even a chalkboard if you are desperate.
-
-## Proof of Work
-
-The PoW phase is the original, and a working hasher tool is available here: <https://joshorndorff.github.io/BitStory/bitStoryLive.html>
-
-To begin we'll explore the Nakamoto style Proof of Work.
-To add a block a student must:
-
-- Choose a parent block hash to build on
-- Choose a word to add to the story
-- Find a nonce so that the block's hash meets the required difficulty
-
-The process of finding a nonce is accomplished by entering the parent hash and word into [the hasher](https://joshorndorff.github.io/BitStory/bitStoryLive.html) and repeatedly mashing the `increment nonce` button until you find a valid one.
-In this way students are manually performing the preimage search.
-
-The game ends at a pre-determined time.
-The winner is the person who authors the most blocks in the longest chain at the end of the game.
-
-### Attacks
-
-The instructor can encourage student groups to perform various attacks on the PoW network.
-
-- Censor specific words or plot points by forking around them.
-- Publish invaild blocks to trick other miners into wasting their hash rate on invalid chains.
-- Perform a hard fork where your block start to have two words each.
-  Some students will like the two-words-per-block rule and keep building on them.
-  Other students (ideally ones who don't know the instructor is in on the shenanigans) may think the two-word blocks are not following the rules, and choose to ignore them.
-  Welcome to bitstory cash.
-
-## Formalize the Language
-
-Our previous story had basically no structure.
-Let's change it to specifically allow a small set of "transaction types".
-From here on each block will contain a very short sentence (can be abbreviated on the whiteboard) The following is an _example_ and your group is encouraged to make modifications if you like.
-The degree of formalization is up to you.
-The more formal it gets, the more it starts to look like real world blockchains.
-
-- Choose a fixed cast of max 3 or 4 characters
-- Choose a fixed set of a few locations
-- Allow one simple action in each block (a character moves, or does one simple thing)
-- Consider letting your characters affect your "real world" by letting them change the difficulty necessary for a block to be valid.
-  You now have a difficulty adjustment algorithm.
-
-Play a few more games.
-This time each miner write down a few goals that they want to accomplish in-story (eg, bob and alice have a fight, charlie is elected mayor).
-This time the winners are whoever best accomplishes their in-story goals.
-Notice that in some cases the goals may al lbe mutually compatible, and in other cases they may not.
-In subsequent rounds, establish goals together.
-Try to play at least one round where there are incompatible goals.
-Miners may choose to form alliances (pools) and censor blocks that don't build on their allies' in-story goals.
-
-## Proof of Authority (Aura)
-
-In this phase, students will choose some authorities to act as block authors and a slot duration and they will take turns authoring in order.
-They should observe that this method is much simpler and less chaotic.
-It does indeed take less work.
-
-## Attacks
-
-- You can skip your slots to slow the progress of the story once it isn't going your way.
-- Censor plot points.
-- Publish blocks in slots in which they are not valid to try to trick other miners.
-  This may be particularly convincing when the correct author is skipping their slot.
-- Polarize the authorities to work on two different forks
-
-## Discussion
-
-What attacks worked best in PoW vs PoA.
-What strengths and weaknesses does each have.
-
-## Proof of Stake
-
-One weakness of PoA is that only some of the participants are authors.
-We can improve this situation by allowing the authority set to rotate.
-Challenge the students to consider ways in which the authority set might change.
-What if the story itself is about who is elected as authorities?
-
-Notice that this is the foundation of proof of stake.
-The on-chain story is about people bonding and unbonding their security deposits.
-Formalize a new language around this story.
-
-### Mixed PoW PoA
-
-Some early PoS designs envisioned interleaving PoS and PoW blocks.
-Invent such a scheme, and try it out.
-
-## Grandpa and finality
-
-This one is a little different.
-Here we assume an external block production method.
-At first this can just be one student who is not playing grandpa, but instead being the sole block producer.
-
-The other students use a shared whiteboard to post their pre-votes and pre-commits and personal paper to track which blocks they have finalized.
-
-## Hybrid Consensus
-
-If there is time in the activity slot, we can combine any of the block production methods with grandpa.
-My personal favorite is PoW + Grandpa.
diff --git a/content/blockchain-contracts/_materials/rocket-cash.md b/content/blockchain-contracts/_materials/rocket-cash.md
deleted file mode 100644
index 7378f181..00000000
--- a/content/blockchain-contracts/_materials/rocket-cash.md
+++ /dev/null
@@ -1,7 +0,0 @@
-# Rocket Cash
-
-Web2 digital cash example.
-
-## 📥 Clone to start: <a target="_blank" href="https://github.com/Polkadot-Blockchain-Academy/rocket-cash">Rocket Cash</a>
-
-See the README included in the repository for further instructions.
diff --git a/content/blockchain-contracts/_materials/start-your-own-blockchain.md b/content/blockchain-contracts/_materials/start-your-own-blockchain.md
deleted file mode 100644
index 602f8356..00000000
--- a/content/blockchain-contracts/_materials/start-your-own-blockchain.md
+++ /dev/null
@@ -1,82 +0,0 @@
-# Start Your Own Blockchain
-
-<!-- FIXME this is _mostly_ faculty facing, adapted to "you" as the reader (student). We want these to be student facing? faculty guide can pull these in. -->
-
-In this activity, you will get hands on experience operating a blockchain node and seeing it interact with other blockchain nodes.
-
-## 📥 Clone to start: <a target="_blank" href="https://github.com/Polkadot-Blockchain-Academy/Academy-PoW">Academy PoW Node</a>
-
-See the README included in the repository for further instructions.
-
-## Learning objectives:
-
-1. How to run a node
-1. What the log messages mean
-1. Preview: How to configure a network with a chain spec
-1. Experience peer connections coming and going
-1. Practice checking for common not-peering issues (different genesis, firewall)
-
-## Outline
-
-### Clone & Compile
-
-> ⏰ **Because the compile time is quite long, this should be done in advance of class.**
-
-Ideally, compilation will be given to you as as homework on the day before to run (at worst) over night.
-The faculty may also have a docker image ready to go, please request this if needed.
-
-### Generate User Keys
-
-With Polkadot JS
-
-### Get Tokens
-
-You request tokens from the teacher by sharing your address with the teachers in a public channel.
-After the first five you have tokens, we pass them on to your peers.
-This manual approach allows you to get familiar with sending and receiving tokens in your wallet.
-
-Optionally, we may install a faucet or UBI pallet in the chain to allow you to self service _after_ the initial manual distribution.
-
-### Optional Treasure Hunt
-
-You could have tokens stored at eg the Alice key or other leaked keys and challenge you to find and recover the tokens.
-Make up a story/myth about some mysterious figure who lost your key and left clues, etc.
-
-### Run Nodes
-
-You start your own nodes and join the network
-
-### Start Mining
-
-Node runners can contribute PoW hashrate to the network in exchange for tokens.
-
-### Fork the Network
-
-In BA we forked the difficulty, but maybe there is something more compelling.
-Maybe fork to adjust max block size.
-Nice because it happened for real in bitcoin.
-Maybe hard because I believe max block size is controlled in the runtime.
-
-Another idea:
-When we launch the chain, we allow PoW block to have either of two valid kinds of seals.
-For example, one based on `sha3` and another based on `keccak`.
-Then we pretend there is a cultural war and some people like one function or the other hand some people don't care.
-When the time comes to fork, we have three different versions of the node available: 1 only accepts `sha3`, 2 only accepts `keccak`, 3 is the original that accepts either.
-In this way we can see that there will be at least two viable chains (the sha 3 chain and the `keccak` chain).
-If there are a lot of nodes that still run the old version and accept either hash, we will form a third chain.
-But if there are only a few such nodes, we will re-org into one of the other two chains, and potentially reorg back and forth between them.
-
-<!--
-### Light Clients
-
-TODO
-
-### Other Infrastructure
-
-Like block explorer or indexer?
--->
-
-### Smart Contracts
-
-The Smart Contracts module has an activity about launching smart contracts on a running chain.
-When these modules are run back-to-back, it makes an excellent learning experience to use this same chain we just launched to also launch the smart contracts.
diff --git a/content/blockchain-contracts/_materials/wasm-executor.md b/content/blockchain-contracts/_materials/wasm-executor.md
deleted file mode 100644
index 874c6416..00000000
--- a/content/blockchain-contracts/_materials/wasm-executor.md
+++ /dev/null
@@ -1,7 +0,0 @@
-# Wasm Executor
-
-In this activity, you will practice compiling Rust code to a few different wasm targets. You will also learn to embed a web assembly executor in your own binary application. We will focus on Rust, but also briefly look at executing wasm from Python to demonstrate the platform agnostic nature of Wasm.
-
-## 📥 Clone to start: <a target="_blank" href="https://github.com/Polkadot-Blockchain-Academy/wasm-executor">Wasm Executor Activity</a>
-
-See the README included in the repository for further instructions.
diff --git a/content/blockchain-contracts/accounting/img/3.2-thinking-cartoon.png b/content/blockchain-contracts/accounting/img/3.2-thinking-cartoon.png
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diff --git a/content/blockchain-contracts/accounting/page.md b/content/blockchain-contracts/accounting/page.md
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--- a/content/blockchain-contracts/accounting/page.md
+++ /dev/null
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-# Accounting Models & User Abstractions in Blockchains
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/accounting/slides.md b/content/blockchain-contracts/accounting/slides.md
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--- a/content/blockchain-contracts/accounting/slides.md
+++ /dev/null
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----
-title: Accounting Models & User Abstractions in Blockchains
----
-
-# Accounting Models & User Abstractions in Blockchains
-
----
-
-## Overview
-
-- Cryptography, Signatures, Hash functions, Hash based Data Structures
-  <!-- .element: class="fragment" data-fragment-index="2" -->
-- Economics/Game Theory
-  <!-- .element: class="fragment" data-fragment-index="3" -->
-- Blockchain structure
-  <!-- .element: class="fragment" data-fragment-index="4" -->
-
----
-
-## Where do we go from here?
-
-- We have some base elements, ideas, and concepts
-  <!-- .element: class="fragment" data-fragment-index="2" -->
-- Now, let's put them together into something cool..
-  <!-- .element: class="fragment" data-fragment-index="3" -->
-
----
-
-## What are we talking about?
-
-<pba-cols>
-<pba-col style="font-size:smaller">
-
-- Now that we have this structured decentralized tamper proof state machine..
-- Let's think of ways we can formulate a state and a state transition in terms of representing users
-
-</pba-col>
-
-<img rounded style="width: 400px;float:right; margin-right:5px" src="./img/3.2-thinking-cartoon.png" />
-
----
-
-## State User Model
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_1.svg" />
-
----
-
-## State User Model
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_2.svg" />
-
----
-
-## How to represent Joshy and Andrew?
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_1.svg" />
-
----
-
-## User Representation
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_3.svg" />
-
----
-
-## How to send from Joshy to Andrew? What do you need?
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_4.svg" />
-
-Notes:
-
-What would be catastrophic if we got wrong??
-
----
-
-## What if we want to spend this?
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_5.svg" />
-
-Notes:
-
-Why do we say spend here and not modify?
-
----
-
-## Input
-
-<img rounded style="width: 1200px;" src="./img/utxo_transaction_1.svg" />
-
----
-
-## Transaction
-
-<img rounded style="width: 1200px;" src="./img/utxo_transaction_2.svg" />
-
-Notes:
-
-Why do we not send all of the 70 to Andrew?
-
----
-
-## How to verify this state change is valid?
-
-- We can actually spend this thing signature verification!
-- Sum of the inputs is >= sum of the outputs
-- No coins are worth 0
-- Has this already been spent before?
-
-Notes:
-
-Which did I forget??
-
----
-
-## Our new state
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_6.svg" />
-
----
-
-## How do we generalize beyond money?
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_7.svg" />
-
----
-
-## How do we generalize beyond money?
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_8.svg" />
-
-Notes:
-
-How are we going to verify now that the state transition is valid?
-
----
-
-## Transaction
-
-<img rounded style="width: 1200px;" src="./img/utxo_transaction_3.svg" />
-
----
-
-## Transaction
-
-<img rounded style="width: 1200px;" src="./img/utxo_transaction_4.svg" />
-
----
-
-## Is this a good model? Why or why not? Let's discuss
-
-- Scalability
-- Privacy
-- General Computation
-
----
-
-## Is there a different way?
-
-<img rounded style="width: 1200px;" src="./img/utxo_state_7.svg" />
-
-Notes:
-
-Now ease them to the solution of Accounts
-
----
-
-## Accounts
-
-<img rounded style="width: 1200px;" src="./img/accounts_state_1.svg" />
-
-Notes:
-
-Now ease them to the solution of Accounts
-
----
-
-## State Transition Accounts
-
-<img rounded style="width: 1200px;" src="./img/accounts_transaction_1.svg" />
-
----
-
-## State Transition Accounts
-
-<img rounded style="width: 1200px;" src="./img/accounts_transaction_2.svg" />
-
----
-
-## How do we verify and handle this transaction?
-
-- Verify enough funds are in Joshy's account
-- Verify this amount + Andrews amount don't exceed the max value
-- Check the nonce of the transaction
-- Do the actual computation of output values
-
-Notes:
-
-Did I forget any?
-
----
-
-## State Transition Accounts
-
-<img rounded style="width: 1200px;" src="./img/accounts_transaction_3.svg" />
-
----
-
-## What did we do differently in Accounts vs UTXO model?
-
-Notes:" />
-
-Verify as opposed to determining the outcome.
-Not submitting output state in transaction
-
----
-
-## Account Arbitrary Data
-
-<img rounded style="width: 1200px;" src="./img/accounts_state_2.svg" />
-
----
-
-## Is this a good model? Why or why not? Lets Discuss
-
-- Scalability
-- Privacy
-- General Computation
-
-Notes:
-
-Parallelization? Storage space, privacy solutions?
-
----
-
-## Small shill... Tuxedo 👔
-
-> <https://github.com/Off-Narrative-Labs/Tuxedo>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/blockchain-contracts/authoring/page.md b/content/blockchain-contracts/authoring/page.md
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--- a/content/blockchain-contracts/authoring/page.md
+++ /dev/null
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-# Consensus Authoring
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/authoring/slides.md b/content/blockchain-contracts/authoring/slides.md
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--- a/content/blockchain-contracts/authoring/slides.md
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----
-title: Consensus Authoring
-description: Authoring restrictions related to consensus
-duration: 30min
----
-
-# Consensus: Authoring
-
----v
-
-### Consensus is...
-
-...a decision making process that strives to achieve acceptance of a decision by all participants.
-
----v
-
-## Blockchain Consensus is...
-
-...a decentralized consensus system to reach agreement over a shared history of a state machine.
-
----v
-
-## Blockspace
-
-<img style="width: 00px" src="./img/blockspace-machine.svg" />
-
-Blockchain consensus systems produce a resource called blockspace.
-
-Strong incentive alignments and strong guarantees make for high quality blockspace.
-
-Notes:
-
-As we discussed blockspace represents the right to contribute to the shared history.
-This is a valuable resource that is offered to users as a product.
-We will discuss the selling of this resource in a later lecture on allocation and fees.
-The consensus system used plays a large role in determining the quality of the blockspace.
-
----
-
-## Forks Review
-
-<img style="width: 500px" src="./img/forks-some-invalid.svg" />
-
-There are going to be forks.
-We need to decide which one is the real one.
-
-We can rule some forks out to reduce the problem space.
-Then we are left to decide which is canonical.
-
-Notes:
-
-Forks represent alternate courses that history could take.
-They arise every time there is a difference of opinion.
-
-You can think of them at a social level.
-Court cases, arguments, wars.
-Ideally we can resolve them peacefully
-
-You can think of them at a very low physics-y level.
-Every time an electron encounters a potential barrier it either reflects of tunnels.
-When consensus is high-quality, the result is as objective as the outcome of a physical process.
-
----
-
-## Five Aspects of Consensus
-
-<pba-flex center>
-
-- State machine validity
-- Arbitrary / Political validity
-- Authorship throttling
-- Fork choice heuristic
-- Finality
-
-</pba-flex>
-
-Notes:
-
-The first two aspects are relatively simple and I'll discuss them briefly right now.
-The third and fourth are the main topic of this lecture.
-The fifth is covered in detail two lectures from now in great detail.
-
-The first three aspects are about ruling possibilities out.
-The fourth and fifth are about deciding between any remaining possibilities.
-
----v
-
-## State Machine Validity
-
-Some forks can be ruled out simply because they contain invalid state transitions.
-
-<img style="width: 00px" src="./img/invalid-state-transition.svg" />
-
-Notes:
-
-Example spending more money than you have.
-Noting your present location such that you would have traveled faster than speed of light since last record.
-Calling a smart contract with invalid parameters.
-
----v
-
-## Arbitrary / Political Validity
-
-Similar to state machine validity.<br />
-Examples:
-
-<pba-flex>
-
-- Blocks that are too big
-- Blocks that have "hack" transactions
-- Empty blocks
-- Block with Even state roots
-
-</pba-flex>
-
-<img style="width: 00px" src="./img/politically-invalid-state-transition.svg" />
-
-Notes:
-
-This concept is similar to the previous slide.
-In some sense this is even the same.
-This allows us to rule out some forks just for not having properties that we like.
-Or for having properties that we dislike.
-
-Not everyone will agree on these properties ad that leads to long-term network splits.
-
----
-
-## Authorship Throttling
-
-Real-world blockchains impose additional restrictions on who can author blocks.
-Why?
-
-<img style="width: 00px" src="./img/fork-chaos.svg" />
-
-Notes:
-
-These blockchains are supposed to be permissionless right? At least many of them are.
-Some are even very hardcore about that goal.
-So why would we want to restrict the authoring.
-Answer: So the nodes are not overwhelmed.
-Unthrottled authoring leads to fork chaos.
-If anyone authored at any moment there would be blocks raining down left and right.
-It would be impossible to check them all.
-It would be DOS central.
-So we need some organization / order to the process.
-
----v
-
-## Leader Election
-
-We need to elect a small set (or ideally a single) entity who are allowed to author next.
-
-In pre-blockchain consensus this was called the "leader", and still often is.
-
-Notes:
-
-By electing a few leaders, we are able to throttle the authoring.
-
----v
-
-## Liveness
-
-The ability of the system to keep authoring new blocks
-
-Notes:
-
-Before we go on, I want to introduce the concept of liveness.
-It is a desireable property that consensus systems want to have.
-Systems that have better liveness properties offer higher quality blockspace.
-Chains without liveness guarantees become stalled.
-
----
-
-## Proof of Work
-
-Satoshi's Big invention.
-
-Solve a Pre-image search - earn the right to author.
-
----v
-
-## Proof of Work: Pros
-
-<pba-flex center>
-
-- Permissionless (or so we thought)
-- Requires an external scarce resource: Energy
-- Blind: Nobody knows the next author until the moment they publish their block
-- Expensive to author competing forks - Clear incentive
-
-</pba-flex>
-
-Notes:
-
-On the surface one big strength of PoW is that anyone can spin up a node and join at any time without anyone's permission.
-This is clearly how it was described in the whitepaper.
-In practice, many systems now have such a high hashrate that your home computer is useless.
-It is now permissioned by who can afford and acquire the right hardware.
-
-The reliance on an external resource is good in some sense because it is an objective measure of the market's valuation of the consensus system.
-This helps valuate the blockspace.
-
-The blindness is a good property because it makes it impossible to perform a targeted attack (DOS or physical) on the next leader to stall the network.
-
-Some attacks rely on the leader authoring two competing forks and gossiping them to different parts of the network.
-With PoW, it costs energy for every block you author.
-This makes it expensive to perform such attacks.
-This provides an economic incentive for authors to only author blocks on the "correct" fork.
-
----v
-
-## Proof of Work: Cons
-
-<pba-flex center>
-
-- Energy Intensive
-- Irregular block time
-- Not so permissionless
-
-</pba-flex>
-
-Notes:
-
-Energy consumption is more often considered a negative property.
-Sometimes called proof of _waste_.
-I won't go that far, but in a world where climate change is a reality, it is certainly not ideal to be spending so much energy if we can get away with far less.
-
-Worth noting that some PoW schemes (eg Monero's) strive to minimize the energy impact by choosing algorithms that are "asic resistant".
-While these are decidedly better than Bitcoin's, they do not fundamentally solve the problem.
-Just alleviate it somewhat in practice.
-
-Secondly, the block time is only probabilistically known.
-When waiting for block to be authored, there are sometimes spurts of blocks followed by long stretches without any.
-
-Although it seems permissionless on its face, in practice, to be a bitcoin miner you need to have expensive specialized hardware.
-
----v
-
-## Why Author at All?
-
-- Altruism - You feel good about making the world a better place
-- Your Transitions - Because you want to get your own transitions in
-- Explicit incentives - Eg block reward
-
-Notes:
-
-If it costs energy to author blocks, why would anyone want to author to begin with?
-
-Mining only when you want to get your transaction in seems like a good idea to me.
-People who don't want to self author, can pay other a fee to do it for them.
-This is the purpose of transaction fees.
-Most chains have transaction fees specified in the transactions themselves which go to the author
-
-Some networks also add an explicit incentives such as a 50BTC reward per block.
-
----
-
-## Proof of Authority
-
-Traditional class of solutions.
-
-Divide time into slots.
-
-Certain identities are allowed to author in each slot.
-
-Prove your identity with a signature.
-
----v
-
-## Proof of Authority: Pros
-
-<pba-flex center>
-
-- Low energy consumption
-- Stable block time
-
-</pba-flex>
-
-Notes:
-
-Stable block time is a property of high-quality block space.
-It allows applications that consume the blockspace to have expectations about throughput.
-In PoW you will occasionally have long periods without a block which can negatively affect applications.
-
----v
-
-## Proof of Authority: Cons
-
-<pba-flex center>
-
-- Permissioned
-- No external resource to aid valuation
-- Incentives for honesty are not always clear
-
-</pba-flex>
-
-Notes:
-
-Does anything bad happen if they misbehave? Not inherently.
-We will need an incentive for that.
-
----
-
-# Some PoA Schemes
-
-Reminder: PoA is a family of leader election schemes
-
----v
-
-## Aura
-
-The simple one.
-
-Everyone takes turns in order.
-
-```rust
-authority(slot) = authorities[slot % authorities.len()];
-```
-
-Notes:
-
-Pros:
-
-- Simple
-- Single leader elected in each slot
-
-Cons:
-
-- Not blind - welcome targeted attacks
-
----v
-
-## Babe
-
-**B**lind **A**ssignment for **B**lockchain **E**xtension
-
-- In each slot, compute a VRF output.
-- If it is below a threshold, you are eligible to author. <!-- .element: class="fragment" data-fragment-index="2" -->
-- If eligible, author a block showing VRF proof <!-- .element: class="fragment" data-fragment-index="3" -->
-- If NOT eligible, do nothing <!-- .element: class="fragment" data-fragment-index="4" -->
-
-Notes:
-
-Pros:
-
-- No fixed order helps alleviate DOS attacks
-
-Cons:
-
-- Some slots have no authors - There is a workaround for this.
-- Other slots have multiple authors which leads to forks - There is **no** workaround for this.
-
----v
-
-## Sassafras
-
-<pba-cols>
-<pba-col>
-<img rounded style="width: 500px" src="./img/Sassafras-albidum.jpg" />
-</pba-col>
-<pba-col>
-
-Single blind VRF-based leader election
-
-🙈TBH, IDK how it works internally. <!-- .element: class="fragment" data-fragment-index="2" -->
-
-But Jeff does! <!-- .element: class="fragment" data-fragment-index="3" -->
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- Has most of the Pros of PoW (except for the external resource based valuation hint)
-- Has all the Pros of PoA
-
----v
-
-## Sassafras Analogy
-
-<pba-cols>
-<pba-col>
-<img rounded style="width: 500px" src="./img/jeff.jpeg" />
-</pba-col>
-<pba-col>
-
-> Sassafras is kinda cards against humanity
-
-</pba-col>
-</pba-cols>
----v
-
-## Sassafras Analogy
-
-<img rounded width="400px" style="float: left; padding: 1px;" src="./img/caa_black.png" />
-<img rounded width="400px" style="float: left; padding: 1px;" src="./img/caa_white_1.png" />
-<!-- .element: class="fragment" data-fragment-index="2" -->
-<img rounded width="400px" style="float: left; padding: 1px;" src="./img/caa_white_2.png" />
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
----v
-
-## Sassafras Analogy
-
-<pba-cols>
-<pba-col>
-<img rounded width="500px" src="./img/jeff.jpeg" />
-</pba-col>
-<pba-col>
-<blockquote style="font-size: 80%">Ring VRF outputs are "cards".  You anonymously "play" the best aka smallest cards in your hand.</blockquote>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-<blockquote style="font-size: 80%">Those cards are sorted, not by funniness since they're just numbers, but by the number.</blockquote>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-<blockquote style="font-size: 80%">The order in which they wind up is the block production order.</blockquote>
-<!-- .element: class="fragment" data-fragment-index="4" -->
-<blockquote style="font-size: 80%">You claim the ones that're yours by doing a non-ring VRF with identical outputs.</blockquote>
-<!-- .element: class="fragment" data-fragment-index="5" -->
-</pba-col>
-</pba-cols>
-
----v
-
-# Proof of Stake
-
-It's just PoA in disguise 🤯
-
-Uses an economic staking game to select the authorities.
-
-Restores the permissionlessness to at least PoW levels.
-
-Restores clear economic incentives
-
-Notes:
-
-There is an economic game called staking as part of the state machine that allows selecting the authorities who will participate in the PoA scheme.
-Actually there isn't just _one_ way to do it, there are many.
-Kian will talk a lot more about this and about the way it is done in Polkadot later.
-I'll just give the flavor now.
-
-The basic idea is that anyone can lock up some tokens on chain (in the state machine).
-The participants with the most tokens staked are elected as the authorities.
-There is a state transition that allows reporting authority misbehavior (eg authoring competing blocks at the same height), and the authority loses their tokens.
-There are often block rewards too like PoW.
-
----v
-
-## 💒 Consensus 🪢 State Machine
-
-- Loose coupling between consensus and state machine is common
-- Eg Block rewards, slashing, authority election
-- In PoW there is a difficulty adjustment algorithm
-
-In Substrate there is a concept of a **Runtime API** - Consensus can read information from state machine.
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-So far I've presented consensus as orthogonal to the state machine.
-This is mostly true.
-But in practice it is extremely common for there to be some loose coupling.
-We already saw an example when we talked about block rewards.
-The consensus authors are rewarded with tokens (in the state machine) for authoring blocks.
-Now we see that they can have tokens slashed (in state machine) for breaking consensus protocol.
-And we see that even the very authorities can be elected in the state machine.
-
----
-
-# Fork Choice Heuristics
-
-Each node's preference for which fork is best
-
-<pba-flex center>
-
-- Longest chain rule
-- Most accumulated work
-- Most blocks authored by Alice
-- Most total transactions (or most gas)
-
-<img style="width: 500px" src="../finality/img/reorgs-1.svg" />
-
-</pba-flex>
-
-Notes:
-
-The fork choice allows you, as a network participant, to decide which fork you consider best for now.
-It is not binding.
-Your opinion can change as you see more blocks appear on the network
-
----v
-
-## Reorganizations
-
-<img style="width: 500px" src="../finality/img/reorgs-1.svg" />
-
-<img style="width: 500px" src="../finality/img/reorgs-2.svg" /> <!-- .element: class="fragment" data-fragment-index="2" -->
-
-Dropped transactions re-enter tx pool and re-appear in new blocks shortly <!-- .element: class="fragment" data-fragment-index="3" -->
-
-Notes:
-
-Having seen more blocks appear, we now have a different opinion about what chain is best.
-This is known as a reorg.
-Re-orgs are nearly inevitable.
-There area ways to make sure they don't happen at all, but there are significant costs to preventing them entirely.
-Typically short reorgs are not a big problem, but deep reorgs are.
-
-You can experience this in a social way too.
-
-- Imagine that you are waiting for a colleague to submit a paper.
-  You believe they have submitted it yesterday, but it turns out that they didn't submit it until today or won't submit it until tomorrow.
-  Might be annoying, but not world shattering (usually).
-- Imagine that you believe the colleague submitted the paper months ago and the paper has been published.
-  You have applied on a job having listed the publication.
-
----v
-
-## Double Spends
-
-<img style="width: 800px" src="./img/double-spend-1.svg" />
-
-Notes:
-
-The name comes from bitcoin, but the attack generalizes.
-It exploits the existence of forks.
-Attacker has to get two conflicting transactions into two forks.
-And convince a counterparty to believe one chain long enough to take an off-chain action before they see the reorg.
-
----v
-
-## Double Spends
-
-<img style="width: 800px" src="./img/double-spend-2.svg" />
-
----
-
-## Five Aspects of Consensus
-
-<pba-flex center>
-
-- State machine validity
-- Arbitrary / Political validity
-- Authorship throttling
-- Fork choice heuristic
-- Finality
-
-</pba-flex>
-
-Notes:
-
-We just discussed the first four aspects.
-Finality will be discussed in an upcoming lesson
diff --git a/content/blockchain-contracts/bytecode/img/question-mark.svg b/content/blockchain-contracts/bytecode/img/question-mark.svg
deleted file mode 100644
index a48d9f64..00000000
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diff --git a/content/blockchain-contracts/bytecode/page.md b/content/blockchain-contracts/bytecode/page.md
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-# Platform Agnostic Bytecode
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/bytecode/slides.md b/content/blockchain-contracts/bytecode/slides.md
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--- a/content/blockchain-contracts/bytecode/slides.md
+++ /dev/null
@@ -1,692 +0,0 @@
----
-title: Platform Agnostic Bytecode
-description: What are PABs and why they exist?
-duration: 1 hour
----
-
-# Platform Agnostic Bytecode
-
----
-
-## Review of Compilers
-
-<img src="./img/compiling.png" />
-
-🤯 Fun Side Reading: <!-- .element: class="fragment" data-fragment-index="1" -->
-[Reflections on Trusting Trust](https://www.cs.cmu.edu/~rdriley/487/papers/Thompson_1984_ReflectionsonTrustingTrust.pdf) <!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-Just a very quick reminder of how compilers work.
-Humans write programs in some human readable language like Lauren talked about.
-Then the compiler translates the semantics of that program into an equivalent program in a much lower more machine-readable language called a bytecode.
-
-CLICK
-
-Whenever I show this diagram or talk about compilers, I always like to mention one of my favorite essays ever.
-Ken Thompson's 1984 Turing Award lecture.
-
----
-
-## Definition
-
-A PAB is a bytecode that follows two main principles:
-
-- Turing Completeness, as a standard bytecode would respect
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Support for tooling that makes it executable on every machine
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-Ideally a bytecode like this is designed to be executed on a virtual machine that follows general known patterns.
-
----
-
-<pba-cols>
-<pba-col left>
-
-<pba-flex center>
-
-###### High Level Languages
-
-<img style="width: 30%" src="./img/rust_logo.png" />
-
-<img style="width: 30%" src="./img/c_logo.png" />
-
-<img style="width: 30%" src="./img/c++_logo.png" />
-
-</pba-flex>
-</pba-col>
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-<pba-col center>
-<pba-flex center>
-
-###### PABs
-
-<img style="width: 30%" src="./img/jvm_logo.png" />
-<img style="width: 30%" src="./img/wasm_logo.png" />
-<img style="width: 20%" src="./img/eth_logo.png" />
-<img style="width: 30%" src="./img/risc-v_logo.png" />
-
-</pba-flex>
-</pba-col>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-<pba-col right>
-<pba-flex center>
-
-###### Architecture's bytecode
-
-<img style="width: 30%" src="./img/intel_logo.png" />
-<img style="width: 30%" src="./img/arm_logo.jpg" />
-<img style="width: 30%" src="./img/risc-v_logo.png" />
-
-</pba-flex>
-</pba-col>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-</pba-cols>
-
-Notes:
-
-From left to right you can see different levels of abstraction over the program that will ultimately be run on some machine.
-Generally, from a high level language you need two compilation step if you want to pass through a PAB.
-
-Other examples of PABs used right now:
-
-- Inside the Linux Kernel -> eBPF
-- Inside browsers -> Wasm
-- Inside Blockchains -> Wasm
-  - Full nodes
-  - Light nodes (Wasm inside Wasm)
-- LLVM Toolchain -> LLVM IR
-
----v
-
-## Compiling in a PAB
-
-<img src="./img/compiling_twice.png" />
-
-Notes:
-
-So when we are using a PAB, we need to compile twice.
-This is, of course, the cost to using a PAB.
-In this lesson we'll also explore the advantages.
-
----
-
-#### What a PAB allows is:
-
-<pba-flex center>
-
-- Portability
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-      - Avoid Hardware Centralization
-  <!-- .element: class="fragment" data-fragment-index="3" -->
-- Determinism
-  <!-- .element: class="fragment" data-fragment-index="2" -->
-      - Make consensus possible
-  <!-- .element: class="fragment" data-fragment-index="4" -->
-
-</pba-flex>
-
-Notes:
-
-The main goal of a PAB is to make the code **portable**, you should be able to compile it once and then share it around without caring about the architecture on which will be executed.
-Of course in a decentralized network we want that different nodes, with different architectures came up to the same result if the input are the same, that's called **determinism**, if a PAB would not have determinism then reaching consensus is impossible.
-
----v
-
-##### That's why PABs are so important
-
----
-
-## Desireable Features
-
-- Hardware Independence
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Efficiency
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- Tool Simplicity
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-- Support as Compilation Target
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-- Sandboxing
-
-<!-- .element: class="fragment" data-fragment-index="5" -->
-
-Notes:
-
-- Hardware Independence: It should not be tightly related to a specific architecture, otherwise the execution on different machine could be convoluted
-- Efficiency: the execution of a PAB should be efficient, the problem for a PAB is that in the execution time is also considered the "translation" to the machine's bytecode or the interpretation
-- Support as Compilation Target: The PAB should be possible to be compiled by as many as possible High Level languages
-- Tool Simplicity: If the tools that makes the PAB executable are extremely complex then nobody will use it
-
----v
-
-### Sandboxing?
-
-An environment for running untrusted code without affecting the host.
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-<img style="height: 300px" src="./img/sandbox.jpg" />
-
-A SmartContract is _Arbitrary Code_ that may be executed on other people's infrastructure, we don't want SmartContracts capable of destroying the nodes on which they are executed
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-CLICK read definition
-
-The term sandbox is an analogy to kids playing in a sandbox.
-The parent puts the kid in the sandbox and tells them they can play in the sandbox and they are safe as long as they stay in.
-Don't go in the woods and get bitten by a snake or in the road and get hit by a car.
-Just stay in the sandbox.
-
-Of course the analogy isn't perfect.
-The children in the sandbox stay there because the parent asked them to.
-They could leave anytime they wanted to.
-For actual untrusted code, a better analogy would be a walled garden or a Jail
-
----v
-
-### Sandboxing?
-
-<img src="./img/jail.jpg" /> <!-- .element: class="fragment" data-fragment-index="1" -->
-
-A sandboxed environment must be created by the executor of the PAB.
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-Of course the security can be seen by various point of view and some examples are:
-
-- Compilation takes too much time -> compiling bomb
-- Access to the environment -> "buffer overflow" techniques
-
-Those things can't be addressed by the PAB itself but they can give good guidelines and code design to make an 100% secure implementation of the executor possible.
-
----
-
-## PAB's lifecycle example
-
-<div class="r-stack">
-<img style="width: 70%" src="./img/pab_path_1.svg" />
-<img style="width: 70%" src="./img/pab_path_2.svg"/>
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img style="width: 70%" src="./img/pab_path_3.svg"/>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-<img style="width: 70%" src="./img/pab_path_4.svg"/>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-<img style="width: 70%" src="./img/pab_path_5.svg"/>
-<!-- .element: class="fragment" data-fragment-index="4" -->
-<img style="width: 70%" src="./img/pab_path_6.svg"/>
-<!-- .element: class="fragment" data-fragment-index="5" -->
-</div>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-<img rounded style="width: 300px" src="./img/question-mark.svg" />
-
----
-
-<pba-cols>
-<pba-col center>
-
-# WebAssembly
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-</pba-col>
-<pba-col center>
-
-<img style="width: 70%" src="./img/wasm_logo.png" />
-
-</pba-col>
-</pba-cols>
-
----
-
-## Wasm's key points
-
-<pba-flex center>
-
-- Hardware-independent
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-  - Binary instruction format for a stack-based virtual machine
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-- Supported as compilation target by many languages
-  <!-- .element: class="fragment" data-fragment-index="2" -->
-  - Rust, C, C++ and many others
-  <!-- .element: class="fragment" data-fragment-index="2" -->
-- Fast (with near-native performance)
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-- Safe (executed in a sandboxed environment)
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-- Open (programs can interoperate with their environment)
-
-<!-- .element: class="fragment" data-fragment-index="5" -->
-
-</pba-flex>
-
-Notes:
-
-Wasm seems to respect every rating points we defined before
-
----
-
-## Stack-Based Virtual Machine Example
-
-<pba-cols>
-<pba-col center>
-
-Adding two number in wasm text representation (.wat)
-
-<!-- .element: class="fragment fade-out" data-fragment-index="1" -->
-
-```wasm [1-12|5|6|8]
-(module
-  (import "console" "log" (func $log (param i32)))
-  (func $main
-    ;; load `10` and `3` onto the stack
-    i32.const 10
-    i32.const 3
-
-    i32.add ;; add up both numbers
-    call $log ;; log the result
-  )
-  (start $main)
-)
-```
-
-<!-- .element: class="fragment" data-fragment-index="0" -->
-
-</pba-col>
-<pba-col center>
-
-<div class="r-stack">
-<img src="./img/stack_1.svg" style="width: 100%">
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img src="./img/stack_2.svg" style="width: 100%">
-<!-- .element: class="fragment" data-fragment-index="2" -->
-<img src="./img/stack_3.svg" style="width: 100%">
-<!-- .element: class="fragment" data-fragment-index="3" -->
-<img src="./img/stack_4.svg" style="width: 100%">
-<!-- .element: class="fragment" data-fragment-index="4" -->
-<img src="./img/stack_5.svg" style="width: 100%">
-<!-- .element: class="fragment" data-fragment-index="5" -->
-<img src="./img/stack_6.svg" style="width: 100%">
-<!-- .element: class="fragment" data-fragment-index="6" -->
-</div>
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Wasm has also a text representation,
-Wat has some features that allow for better readability:
-
-- Stack push operations can be grouped to its consuming instruction.
-- Labels can be applied to elements.
-- Blocks can enclosed with parenthesis instead of explicit start/end instructions.
-
-Instructions push results to the stack and use values on the stack as arguments, the compilation process generally translate this stack-based bytecode to register based, where registers are used to pass values to instructions as a primary mechanism.
-The compilation will try to elide the wasm stack and work with only the architecture registers.
-
-There is another type of stack used in wasm and that's called: shadow stack, resource to learn more: <https://hackmd.io/RNp7oBzKQmmaGvssJDHxrw>
-
----
-
-## Wasm seems to be a perfect PAB, but
-
-- How does communication with the environment work?
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- How the memory is managed?
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- How is it executed?
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-Notes:
-
-Assuming all the things we said before wasm seems to be perfect but how those things really works?
-
----
-
-## Communication with the Environment
-
-Let's call **Embedder** the program that will take the wasm blob as input and execute it
-
-<!-- .element: class="fragment" data-fragment-index="0" -->
-
-- the wasm blob may expect parameters from the embedder
-  - embedder -> wasm
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- the embedder may act on a return value from the wasm
-  - wasm -> embedder
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
----v
-
-### Problem
-
-**Wasm has no ambient access to the computing environment in which code is executed**
-
-</br>
-
-### Solution
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-<img src="./img/env_communication.svg" style="width: 70%">
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-- Every interaction with the environment can be done only by a set of functions, called **Host Functions**, provided by the embedder and imported in wasm
-- The embedder is able to call the functions defined in wasm blob, called **Runtime API**, and pass arguments through a shared memory
-
----
-
-## Memory
-
-In addition to the stack Wasm has also access to memory provided by the embedder, the **Linear Memory**.
-
-<!-- .element: class="fragment" data-fragment-index="0" -->
-
-</br>
-
-- This area will be used also used as a frontier for data sharing
-- To make everything secure the Embedder is doing incredibly convoluted things
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-From Wasm the Linear Memory is byte addressable
-Linear Memory can be manipulated using functions called 'store' and 'load'
-
-The Rust compiler uses for dynamic/heap memory and to pass non primitives values to functions by emulating an additional stack within the linear memory, this emulated stack (the shadow stack) is what we would understand as stack in other architectures
-
----v
-
-### Example
-
-<div class="r-stack">
-<img src="./img/linear_memory_1.svg" style ="width: 70%">
-<!-- .element: class="fragment fade-out" data-fragment-index="1" -->
-<img src="./img/linear_memory_2.svg" style ="width: 70%">
-<!-- .element: class="fragment" data-fragment-index="1" -->
-</div>
-
-Notes:
-
-Here's an example, wasm sees linear memory like a byte array and if it tries to access the second byte, it would use an index 1.
-When it's time to execute it the embedder will see this access and translate the linear memory access at index 1 to a standard memory access to base_linear_memory + 1.
-
-Buffer overflow? Wasm uses 32 bit, this makes impossible to have an offset bigger then 4GiB, this means that the embedder can leave those 4GiB free in its virtual memory to makes impossible to the wasm blob to access any environment information.
-Even if the offset is only positive there are embedded that are defining as protected the 2GiB before the BLM so that if for some reason the wasm code trick the embedder to treat the offset as a signed number that would cause an Operating System error.
-
----
-
-## How Wasm is executed
-
-<pba-flex left>
-
-There are multiple ways to execute wasm:
-
-- Ahead Of Time Compilation
-- Just in Time Compilation
-- Single Pass Compilation
-- Interpretation
-- ...
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-</pba-flex >
-
-Notes:
-
-AOT: Compile all the code at the beginning, this allows to makes a lot of improvement to the final code efficiency
-JIT: The code is compiled only when needed, examples are functions that are compiled only when called, this leave space only to partials improvements
-SPC: This is a specific technique of compilation that is made in linear time, the compilation is done only passing once on the code
-Interpretation: The wasm blob is treated as any other interpreted language and executed in a Virtual Machine
-
----v
-
-### Wasmtime
-
-- It is a stand alone wasm environment
-- Wasmtime is built on the optimizing Cranelift code generator to quickly generate high-quality machine code either at runtime (JIT) or ahead-of-time (AOT)
-- It executes the compiled wasm blob in sandboxed environment while keeping everything extremely secure
-
-<!--TODO: graphics-->
-
-Notes:
-
-- wasmtime book: <https://docs.wasmtime.dev/>
-- Used in substrate as embedder for the blockchain logic
-
-Cranelift is a fast, secure, relatively simple and innovative compiler backend.
-It takes an intermediate representation of a program generated by some frontend and compiles it to executable machine code
-
----v
-
-#### Wasm lifecycle in Wasmtime
-
-<div class="r-stack">
-<img style="width: 70%" src="./img/wasmtime_exec_1.svg" />
-<img style="width: 70%" src="./img/wasmtime_exec_2.svg"/>
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img style="width: 70%" src="./img/wasmtime_exec_3.svg"/>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-<img style="width: 70%" src="./img/wasmtime_exec_4.svg"/>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-</div>
-
----v
-
-### Wasmi
-
-- It is a wasm environment with support for embedded environment such as WebAssembly itself
-- Focus on simple, correct and deterministic WebAssembly execution
-- The technique of execution is interpretation but:
-  - The wasm code is transpiled to WasmI IR, another stack-based bytecode
-  - The WasmI IR is then interpreted by a Virtual Machine
-
-<!--TODO: graphics-->
-
-Notes:
-
-proposal to switch from a stack based ir to registry based ir <https://github.com/paritytech/wasmi/issues/361>
-
-paper explaining the efficiency of translating wasm to registry based code <https://www.intel.com/content/www/us/en/developer/articles/technical/webassembly-interpreter-design-wasm-micro-runtime.html>
-
-Due to it's characteristics it is mainly used to execute SmartContracts on chain
-
----v
-
-#### Wasm lifecycle in Wasmi
-
-<div class="r-stack">
-<img style="width: 70%" src="./img/wasmi_exec_1.svg" />
-<img style="width: 70%" src="./img/wasmi_exec_2.svg"/>
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img style="width: 70%" src="./img/wasmi_exec_3.svg"/>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-<img style="width: 70%" src="./img/wasmi_exec_4.svg"/>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-</div>
-
-<!-- Really nice slide but there's not enough knowledge about substrate
-
-There are also light clients, where both Runtime and Client are implemented in wasm, so we have:
-
-- A browser as embedder of the node's client
-  - the node's client as embedder for the node's runtime
-    - the node's runtime as embedder for the SmartContract
-
-<img style="height: 30vh" src="./img/mind-blown-explosion.gif" />
-
-We have a double recursion of a PAB that embed itself
-
--->
-
----
-
-# Alternatives
-
----v
-
-## EVM
-
-- The **Ethereum Virtual Machine** executes a stack machine
-  - Interesting: here the bytecode was create to be executed in a blockchain, so instructions are not hardware-dependent but there are instruction tightly related to Cryptography and others blockchain instructions
-
----v
-
-## CosmWasm
-
-- Wasm is always used but with different tools
-- They use CosmWasm as Embedder and internally is used Wasmer, a Single Pass Compiler
-
----v
-
-## Solana eBPF
-
-- eBPF is used as PAB, but intrinsically eBPF has a lot of restrictions
-- Solana forked the eBPF backend of LLVM to makes every program to be compiled in eBPF
-- The Embedder is rBFP, a virtual machine for eBPF programs
-
-Notes:
-
-<https://forum.polkadot.network/t/ebpf-contracts-hackathon/1084>
-
----v
-
-## RISC-V ?!
-
-- RISC-V is a new instruction-set architecture
-- main goals are:
-  - real ISA suitable for direct native hardware implementation
-  - avoids “over-architecting”
-
-</br>
-
-Being so simple and "Hardware-Independent" there are work in progress experiments to test if it is suitable to become the new polkadot smart contract language
-
-Notes:
-
-Discussion about using RISC-V as smart contract language: <https://forum.polkadot.network/t/exploring-alternatives-to-wasm-for-smart-contracts/2434>
-
-RISC-V Instruction Set Manual, Unprivileged ISA: <https://github.com/riscv/riscv-isa-manual/releases/download/Ratified-IMAFDQC/riscv-spec-20191213.pdf>
-
----
-
-## Activity: Compiling Rust to Wasm
-
-- Let's make a simple Rust crate that compiles to Wasm!
-- Clone the repo
-
----v
-
-### Activity: Compiling Rust to Wasm
-
-- A target triple consists of three strings separated by a hyphen, with a possible fourth string at the end preceded by a hyphen.
-- The first is the **architecture**, the second is the **"vendor"**, the third is the **OS type**, and the optional fourth is environment type.
-
-* `wasm32-unknown-emscripten`: Legacy, provides some kind of `std`-like environment
-* `wasm32-unknown-unknown` ✓ WebAssembly: Can compile anywhere, can run anywhere, no `std`
-* `wasm32-wasi` ✓ WebAssembly with WASI
-
----v
-
-### Rust -> Wasm Details
-
-```rust
-#[no_mangle] // don't re-name symbols while linking
-pub extern "C" fn add_one() { // use C-style ABI
-  ...
-}
-```
-
-and if a library:
-
-```
-[lib]
-crate-type = ["cdylib"]
-```
-
----v
-
-### Activity: Compiling Rust to Wasm
-
-```
-rustup target add wasm32-unknown-unknown
-
-cargo build --target wasm32-unknown-unknown --release
-
-wasmtime ./target/wasm32-unknown-unknown/release/wasm-crate.wasm --invoke <func_name> <arg1> <arg2> ...
-```
-
----v
-
-## Additional Resources! 😋
-
-> Check speaker notes (click "s" 😉)
-
-Notes:
-
-- More on PAB:
-
-  - <https://github.com/gabriele-0201/IPABDN/blob/main/thesis/IPABDN.pdf>
-
-- More on Rust target spec:
-
-  - <https://rust-lang.github.io/rfcs/0131-target-specification.html>
-
-- Lin Clark's awesome talks on WASI (not super relevant to our work though):
-
-  - <https://www.youtube.com/watch?v=fh9WXPu0hw8>
-  - <https://www.youtube.com/watch?v=HktWin_LPf4>
-
-- `wasm-unknown` vs `wasm-wasi`:
-
-  - <https://users.rust-lang.org/t/wasm32-unknown-unknown-vs-wasm32-wasi/78325/5>
-
-- `extern "C"`:
-
-  - <https://doc.rust-lang.org/std/keyword.extern.html>
-  - <https://doc.rust-lang.org/book/ch19-01-unsafe-rust.html#using-extern-functions-to-call-external-code>
-
-- Chapter 11 of this book is a great read: <https://nostarch.com/rust-rustaceans>
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-# Coordination and Trust in Web3
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Coordination and Trust in Web3
-description: Principles of coordination, contracts, smart contracts, and comparison with traditional legal infrastructure adn web3 infrastructure.
----
-
-# Coordination and Trust in Web3
-
-Notes:
-
-In this module we're going to talk about Smart Contracts.
-
----
-
-# Smart Contracts
-
-## Two Definitions
-
-### Broad Definition <!-- .element: class="fragment" data-fragment-index="1" -->
-
-_aka Szabo definition_ <!-- .element: class="fragment" data-fragment-index="1" -->
-
-<blockquote>A machine program with rules that we could have defined in a contract, but instead a machine performs or verifies performance.</blockquote> <!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-The first question we should answer is "wtf is a smart contract"?
-The term has been around for a long time (longer than any blockchain platform) and has evolved over time.
-It was first introduced by this guy Nick Szabo in the '90s.
-
-CLICK - read szabo definition
-
-Szabo's definition is primitive and kind of vague.
-It might even be argued that it includes all computer programs.
-But it gets at the essence of his thinking at the time.
-Szabo studied both law and computer science and his big idea was that agreements that are traditionally legal contracts could be better expressed and enforced as computer programs.
-Over time, as this vision was gradually realized, the term took on a more specific meaning and was refined quite a bit.
-
----
-
-# Smart Contracts
-
-## Two Definitions
-
-### Narrow Definition <!-- .element: class="fragment" data-fragment-index="1" -->
-
-_aka web3 definition_ <!-- .element: class="fragment" data-fragment-index="1" -->
-
-<blockquote>A program that specifies how users can interact with a state machine and is deployed permissionlessly to a blockchain network</blockquote> <!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-click - read web3 definition.
-This definition is clearly more technical and precise, which is helpful in a lot of ways.
-At this point though, we haven't even learned all the terms in this web3 definition.
-As an educator, that deeply pains me.
-So - my promise to you - by the end of the week, this sentence will 100% make sense to you.
-The broad definition (szabo's - the first one we just saw) is useful in understanding the broader space, historical context, and its philosophy.
-This though, the narrow definition is useful when you're talking about deploying code to actual blockchain platforms.
-In this first lesson today, we'll focus mostly on Szabo's broader notion and explore the ways in which smart contracts are a modern extension to an ancient technology: contracts.
-We'll also look at some criticisms of the term "smart contract" and some alternatives that might have been better if it weren't already way too late.
-
----
-
-## Coordination
-
-<img rounded src="./img/railroad.jpeg" />
-
-Examples of coordinated activities:
-
-<pba-flex center>
-
-- dancing, music band
-- money, business, trade
-- rowing team
-- building homes, buildings, roads
-
-</pba-flex>
-
-Doing the above safely through bureaucracies like inspection and certification procedures, automobile registration
-
-Notes:
-
-Okay so let's do that! Let's rewind a bit.
-Because before we can understand the ways in which smart contracts are "smart" versions of contracts, we need to understand what contracts are in the first place.
-
-After all, we are standing on the shoulders of giants here.
-
-So, in order to understand what contracts are, we'll start all the way back at human coordination.
-
-We'll see that contracts are just a pretty good technology to achieve coordination, and that smart contracts are an improvement on that technology.
-
-So, let's start here.
-I'm going to assert that coordinated activity is the basis of so much human behavior.
-Consider the building we're in right now.
-It has technicians, janitors, grounds people to run it, not to mention the crew it took to build it.
-Coordination is what allows this team of workers pictured here to complete a railroad that stretches across a continent.
-Obviously some coordination require more bureaucracy than others.
-Building a railroad that crosses many state lines? That will require government approval, inspection, and certification procedures - especially as it relates to safety.
-But two people dancing? That most definitely could be categorized as coordinate - but can be negotiated or navigated between two individuals.
-
----
-
-## Coordination
-
-<img rounded style="width: 500px" src="./img/basketball-strategy.webp" />
-
-Notes:
-
-There are so many examples of things we as humans can achieve only through coordination, not as individuals, it would be impossible to list them all.
-I hope it's evident that I think coordination is good a good thing! Because of it, we can build big big things and create beautiful music in a symphony together because of it.
-
----
-
-## Coordination
-
-<img rounded style="width: 500px" src="./img/org-chart.jpg" />
-
-Notes:
-
-It is how massive organizations like corporations and governments are able to function.
-
----
-
-## Voluntary vs Forced Coordination
-
-<img rounded style="width: 500px" src="./img/voluntary-coordination.jpeg" />
-
-Notes:
-
-A clarifying attribute of coordination is that it can happen voluntarily or by force.
-Here, we have a picture of folks working together, let's assume it's voluntarily - as it looks like they're volunteering their time at a community garden.
-This is a wonderful example of human coordination at its best.
-
----
-
-## Voluntary vs Forced Coordination
-
-<img rounded src="./img/forced-coordination.jpeg" />
-
-Notes:
-
-But like all things, of course coordination can have it's ugly side.
-Pictured here, a slave boat, is categorically a coordinated effort; people are forced to work together.
-Most of us consider slavery a bad outcome.
-It IS a bad outcome.
-Even those with sketchier moral compasses would agree that _they_ don't want to be the slaves.
-
-The point I'm making here is this: We want to create conditions (otherwise known as, incentives) where voluntary coordination can happen freely and easily.
-And thus make slavery as an outcome unlikely.
-And by building proper tools for voluntary coordination, we can help prevent forced coordination from happening in the first place.
-And again, voluntary coordination is a good thing between individuals - it's how we together achieve things that are impossible otherwise on our own.
-Thinking back to our first example of building a railroad - if I were to drive railroad spikes every day for the rest of my life, say I start in Miami where I live now? Maybe I eventually would make it to Georgia? But big collaborative coordination efforts? Railroads made it California! They stretch all over and across a continent!
-
----
-
-## Business and Trade
-
-<pba-flex center>
-
-- primitive trade
-- dead weight loss
-- counterparty risk
-
-</pba-flex>
-
-Notes:
-
-From a historical perspective, one of the first forms of coordination was simple trading.
-Let's imagine that I grow food and you make houses.
-So, I'll give you some food, if you build me a house, and I pay your daily wage by giving you food as long as you're building my house.
-This is a classic example of what is called primitive trade.
-You the house builder - you need food, so you can only build houses for people who grow food.
-As in, you can't earn food by building houses for randos who don't have food to pay you with.
-Obviously there are a whole lot of problems within this situation and it won't scale over time.
-But it's also a classic example of what is called 'deadweight loss' - The definition of which is: "a cost to society created by market inefficiency, which occurs when supply and demand are out of equilibrium".
-Another classic example would be if I, for example, grow corn in the summer and you ice fish in the winter.
-And together, we _would love_ to have some way to feed each other during our off seasons - me to feed you in the summer and you to feed me in the winter - but there's no way to coordinate that because someone has to go first.
-So let's say I go first and I just give you half of my corn all summer.
-It's within reason that you could just, you know, piece out and I'm… left with nothing all winter.
-And that is what we call counterparty risk.
-And because I don't want to take on that counterparty risk, I don't engage in such a deal, which is then deadweight loss.
-So, despite the fact that we both kinda want to trade, we have no real way of making it happen.
-So are we stuck?? Do we just not do the deals because we're afraid of counterparty risk and deadweight loss?
-
----
-
-# Trust
-
-So you want to coordinate with someone.
-
-But you don't want to get ripped off.
-
-Notes:
-
-Let’s then move on to talk about trust - as it makes sense that it's one common way to achieve coordination.
-Because let's imagine, you want make an agreement, but you don't want to get ripped off.
-Trust means that we decide to trust whoever we're coordinating with - we're creating an agreement between one another to not to rip each other off.
-Say for example we're builders - you and I decide to build your house this week.
-Well then I in turn believe that we’ll build mine next week.
-
----
-
-# Personal/Real Trust
-
-## vs
-
-# Rational Expectations
-
-Personal trust - you can build it over time through a slow give and take like you do with your family or long term business partners. <!!-- .element: class="fragment" -->
-
-Notes:
-
-For those houses to be built, for that coordination to happen, we need credible expectations that the promises we make to one another will be upheld.
-AKA I have to be willing to trust you - that you are going to fulfill your end of the bargain.
-So here on the slide, I have two concepts: Personal or 'real' trust vs. rational expectation.
-CLICK - I like to think of personal trust, as a familial thing - or something that's been developed between people over time - I for example trust that my mom, who is watching my son right now, is taking good care of him.
-But she and I have gradually built up that trust over many years.
-This sort of trust happens within families, between friends or neighbors, but it can also happen in business relationships - say for example, you have a new business partner and you start that relationship off by doing say one small deal together.
-And yeah, you may choose to take on a little risk within the deal, but it’s small.
-And then the next time you interact, the deal evolves and becomes a little bigger.
-And maybe that time the other party/person takes on that little bit of risk.
-At no point is there SO much risk that you could get completely wrecked if they rip you off.
-Again, there's some, and so by accepting that risk slowly more and more over the years, you two are able to actually build up that personal and real trust.
-
----
-
-# Trust: A Dirty Word
-
-_Less Trust, More Truth_ <!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-Okay pause - I should fully acknowledge that I'm talking a whole lot about this thing _trust_, and who here has heard or seen ppl in the web3 world wearing hats saying - CLICK - less trust, more truth.
-Anyone? (check for nods)
-
-_So, some personal historical context on me_, when I was a newbie in the web3 space, I hadn’t heard this phrase (or slogan rather?).
-I saw it on ppl’s shirts and felt sort of confused and honestly, kind of excluded from what felt like maybe an inside joke.
-I remember thinking, _wait, I trust people, does that make me wrong... Is that a bad thing_?
-I asked myself the question, _why is trust such a dirty world in our world_?
-Well, in time, thanks to some of my fellow instructors in the room, I came to understand that this phrase is referring to the fact that life is not all sunshine and roses! Not all relationships and interactions are filled with trustful actors.
-In fact, most aren't!
-Literally every day we're in situations in which we are forced to treat complete strangers as if we've established real, authentic trust between one another.
-Treat them as if they're a close friend or business partner.
-And _that_ is definitely bad, and is a dirty word, and is a thing that we really shouldn't do.
-And yet! This literally happens all the time - every day really -when you give a merchant your credit card number and you trust that they won't go off on an amazon spree with it.
-Or when you give your social security number to a new employer and you trust that they won't steal your identity.
-Or when you give your passport to a border agent and you trust that they won't sell it on the black market.
-Okay, end pause - back to the slides.
-
----
-
-# Personal/Real Trust
-
-# vs
-
-# Rational Expectations
-
-- Personal trust - you can build it over time through a slow give and take like you do with your family or long term business partners. <!-- .element: class="fragment" data-fragment-index="1" -->
-- Rational expectations - you can believe that a person will act faithfully because they are incentivized to do so. <!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-So.
-We know that we don't have the luxury of only interacting with people we truly personally trust.
-It's impossible to get personal trust with every person you'd in theory like to because it takes a super long time to bootstrap that real kind of relationship.
-And frankly, sometimes you want to interact with a stranger more immediately, say today, and not have to court them for years upon years.
-So, again, this should lead us to the question of - how do you handle these every day situations? How DO I trust that the coffee guy isn't going to run off with my credit card details?
-CLICK - Well, that's where rational expectations come into play.
-This is a game theory, incentives-based concept.
-Where you believe credibly that a person _will_ act faithfully according to an agreement you've made - because the incentives make them do so.
-So, in a sorta loose way you could say this is another kind of trust? But it's not the genuine, real, authentic kind.
-It's more like, I trust that you will act in a certain way because you are _so incentivized_ to do so and being truthful and upholding your end of the agreement ultimately is your best strategy and option.
-
----
-
-## Personal Trust for Performance
-
-Personal trust can make things _really_ efficient, and it's reasonable to leverage this trust _when it's warranted_
-
-Notes:
-
-Again, I want to make sure you're all hearing me when I say that personal/familial trust is not wrong, or bad, or dirty.
-I don’t want us all walking out here calling our moms and dissolving our trust with them.
-That just isn’t the scenario we speak to when we say 'trust is dirty'.
-And further, if you have someone who you genuinely trust, you can actually get things done a whole lot faster and more efficiently by leveraging that trust.
-So, it may be worth it to bootstrap genuine personal trust.
-You know, start small, accept a small bit of risk and gradually increase that over time.
-Again, it's only bad when you have to do that with someone that you don't know or you actively distrust AND they aren't incentivized to return that trust.
-
----
-
-## Promises and Reputation
-
-<pba-flex center>
-
-- how enforceable is it?
-- does it work in small setting?
-- does it work in a large setting?
-
-</pba-flex>
-
-Notes:
-
-So these incentives are obviously really important.
-Let's talk about what they are or could be.
-Often they are civic duty based - the fear that society or your town will turn on you if you break your promise.
-OR they're morality or religion based - you know, you keep your promise to someone out of fear of otherwise going to hell.
-Or they are based on the fact that you have a reputation to uphold.
-You don't want to be known as a liar or a cheat.
-I think you get what I'm saying here, yeah?
-It's social norms and expectations that keep people.
-Reputation is on the line.
-And this can get society pretty far.
-But, it's not perfect.
-It's not always enforceable - or rather - a threat of a bad reputation isn't always enough to keep people in line.
-Or a town grows enough that you can't keep track of everyone's reputation.
-Or, you know, you're in a big city and you don't care about your reputation because you're never going to see these people again.
-F trust.
-F reputation.
-Outlaw life is for me!
-
-From a sociological perspective, we know that if people within a society tend to keep promises, the society tends to prosper.
-But! Eventually, it will be sufficiently profitable to defect and to break promises.
-womp womp!
-
-And this is why we started the lecture off with discussing coordination.
-So let's quickly merge some of the concepts we’ve discussed thus far.
-Coordination and trust.
-Because let’s be real, to achieve things on this planet, it requires some coordination between the 8 billion people here.
-And sure, genuine personal trust can help in a small village.
-And promises based on societal reputation and civic incentives can help getting things done across a town.
-But promises don't get us all the way up to scalable, global trust.
-When talking with Joshy, about this problem his example, that I can’t seem to get out of my head was that: “It's the modern equivalent of a primitive village deciding "okay everyone, let's all agree we're going to poop in the same corner of our village, not just wherever we feel like it.” So as he says: Promises can make a village of 100 shit in the same corner, but not 8 billion.
-I think this is his way of saying that we need some bigger and more resilient coordination tools.
-
----
-
-# Contracts
-
-<pba-flex center>
-
-- **Contracts are Promises**
-- Some involve money, but they're much **more general than just money**.
-- Traditionally, contracts are special promises that the **government will enforce**.
-
-</pba-flex>
-
-Notes:
-
-So how do we incentivize people to keep their promises beyond a civic duty?
-Ding ding ding - Finally! This brings us to the idea of contracts.
-They're basically, pretty much, promises.
-They could involve money, a lot of them do, though they don't have to.
-Ultimately, think of them as abstractions over promises.
-And someone is enforcing the contract.
-
-On a very small scale, think of siblings fighting over a toy, a parent might encourage them to agree to take turns.
-Later when it is time to tarde, the parent might remind the child, "you said you would trade in 5 minutes, so now you have to." The parent is big enough to physically overpower the child if it were to come to that, and the child knows it, so therefore it rarely comes to that.
-The parent in this situation is the enforcer.
-
-Same thing in sports.
-We all agree to the rules, and agree to let a referee make the judgement calls.
-The ref is the enforcer.
-In big leagues, where there can suspend players and affect their career, this works.
-In the public park, it doesn't always, because the ref is just a peer and there is no real power differential.
-
-Traditionally what you've probably learned is that "enforcer" of these contracts (or promises) is the government.
-The government, by being the enforcer, can help people engage in so much voluntary coordination just by making them keep their own promises.
-
-And sure, that's valuable because governments are big and powerful.
-You could say that even in some sense, the government enforcing it is a lot like God enforcing it.
-As in, the government is big enough to have power over individuals interacting, and if anyone tries to rip someone else off, the government will step in and make sure the contract is upheld.
-
-This essentially allows us to interact as if we trusted each other.
-And over time, the stickiness sets in and people actually do start to trust each other! Yay, happy days - But wait! What am I talking about? We know the unfortunate truth which is that government having such a power differential over the people is not always a good thing...
-
----
-
-# Promises with Force
-
-<div>
-  <img rounded style="width: 500px" src="./img/whitehouse-construction.jpeg" />
-  <img rounded style="width: 500px" src="./img/pyramid-construction.jpeg" />
-</div>
-<!-- .element: class="fragment" -->
-
-Notes:
-
-This is a picture of the white house being built - CLICK - and of course the pyramids.
-
-Both are impressive works of human coordination.
-But to the workers they are much different.
-The construction crew building the white house was engaged in voluntary coordination through employment and they were probably excited about their new government too.
-The slaves building the pyramids, are engaged in forced coordination, and when they die, their corpses won't even make it in that pyramid, they'll just get thrown out in the desert.
-Our job, in this smart contract module, is to design systems of coordination that make it likely and easy for voluntary coordination so that it is not necessary or desireable to resort to forced coordination.
-
----
-
-# Promises with Force
-
-<img rounded src="./img/big-brother.jpeg" />
-<!-- .element: class="fragment" -->
-Notes:
-
-We're doing that because contracts, which often require enforcers, who usually is the government - CLICK - Yeah, which could of course not always be a good thing...
-
----
-
-## What is a Contract Again?
-
-(to summarize)
-
-A promise, made between parties, backed by the government, to coordinate together to accomplish something together.
-
-Notes:
-
-So yeah, that's the goal and what we're trying to solve.
-But, again, just before we go any further, let’s make sure we’re all on the same page about what a contract itself is.
-A promise, made between parties, backed by the government, to coordinate together to accomplish something together.
-The notion of promise is very abstract:
-
-- It could involve coordinating over time.
-- It could involve money or even credit.
-- It also could have multiple possible valid outcomes.
-
-Okay.
-Cool.
-All on the same page? Nodding heads? We can agree we understand this concept?
-
----
-
-# Smart Contracts 🎉
-
-<img rounded style="width: 500px" src="./img/szabo.jpeg" /> <!-- .element: class="fragment" -->
-
-Notes:
-
-Amazing… because, now onto smart contracts! - CLICK - We've finally made it here, folks, horary!
-Back in the 90s, this CS guy, Nick Szabo, and some other cypherpunks realized that contract law and computer science actually had a lot in common, and thus developed the _idea_ of smart contracts.
-And together we'll develop and tease out those same comparisons here.
-
----
-
-## Smart Contracts - Szabo Definition
-
-<blockquote>A machine program with rules that we could have defined in a contract, but instead a machine performs or verifies performance.</blockquote>
-
-Broad definition _aka Szabo definition_ formulated c 1997
-
-Notes:
-
-So Szabo has this idea of the smart contract - which is basically to write contractual agreements as computer programs in programming languages.
-And then to run those programs on a computer that will then execute the instructions faithfully with machine-like precision.
-He was pretty excited about some of the research in multi-party computation that was happening at the time and had a sense that this vision might be right around the corner.
-Remember, there is a second smart contract definition that we called the "web3 definition" right at the beginning of this lecture.
-That definition is heavily dependent on content you'll learn during the blockchain module - so Joshy will be sure to build off of that later this week.
-
-<https://nakamotoinstitute.org/the-god-protocols/>
-<https://nakamotoinstitute.org/formalizing-securing-relationships/>
-
----
-
-## Smart Contracts 😠👎
-
-<img rounded style="width: 900px" src="./img/vitalik.jpeg" />
-
-Notes:
-
-Of course, I want to caveat that the term isn't perfect and not everybody likes it.
-As you can see in the tweet, Vitalik has worried that the term is too catchy and gives the wrong impression...
-
-With these caveats and criticisms in mind, it is still worth exploring the idea of contracts as computer programs.
-
----
-
-## Quick review of how we got here
-
-Notes:
-
-So remember we started all the way back at simple primitive trade.
-One solution to those problems were to have personal trust with one another.
-But that doesn't work for everything.
-So we evolved to use rational expectations based on incentives and reputation and societal norms.
-But then we had the problem of scalability.
-Which brought us to, contracts, aka promises, which allowed us to really scale and achieve some incredible coordination.
-And to ensure that those contracts were upheld, the government functioned as a central point of enforcement.
-But, as we've seen, that's not always a good thing.
-And so now, we're going make the next iteration in this long, rich history of how to coordinate: which is the smart contract.
-
----
-
-## Smart Contract Objectives
-
-<pba-flex center>
-
-- Retain all the value of traditional governmental contracts
-  - Can trust strangers promises
-  - Can coordinate with little risk
-  - etc.
-- Remove the need for a powerful government
-- Remove ambiguity about what contracts are enforceable
-- Make writing and understanding contracts more approachable
-- Make contract execution and enforcement more efficient
-
-</pba-flex>
-
-Notes:
-
-These are the goals of a smart contract.
-We basically want to keep all the good stuff that contracts brought us, but then of course make them better by not making the government the central point of enforcement.
-We want to know, without a doubt that the contracts will be enforced.
-We want them to be approachable, legibility wise, and we want them to be efficient.
-
----
-
-# Smart Contracts - Two Parts
-
-<pba-flex center>
-
-1. Expression
-1. Execution / Enforcement
-
-</pba-flex>
-
-Notes:
-
-So, we'll look at smart contracts in two parts.
-Expression - this is the part about actually codifying or expressing what you agree to unambiguously.
-From a programmer's perspective, this is by writing code.
-Or from a lawyer's perspective, this is writing up a bunch of pages of legalese, which basically is a DSL for being really specific in a legal contract.
-And then the part about making sure it actually happens? and what to do if something goes wrong? That’s the execution or enforcement part.
-Execution is ultimately where the two worlds contrast - running unstoppable code on a blockchain vs. having courts and judges and police officers and things like that.
-Essentially the idea of a smart contract is: we're going to take a contract, which we all feel really confident in our definition, and we're going to glue it together with all of Szabo’s incredible Computer Science research that's come out way more recently than contract research, and that all together is the next iteration and improvement on contracts.
-I should note - of these two parts, Programming languages are good at part 1 and computers are good at part 2.
-
----
-
-# Expression -- Pt. 1
-
-_Domain Specific Languages_
-
-_Legalese:_ In witness whereof, the parties hereunto have set their hands to these presents as a deed on the day month and year hereinbefore mentioned.
-
-_ink!:_ `signatures = [alice, bob]`
-
-Notes:
-
-Okay when we're talking expression we're really talking - Domain Specific Languages (which we say DSL for short).
-Humans have been inventing DSL forever.
-
----
-
-## Domain Specific Languages
-
-<img rounded style="width: 900px" src="./img/linearb.jpeg" />
-
-Notes:
-
-From the ancient greek accounting and administrative language, [linear b](https://en.wikipedia.org/wiki/Linear_B),
-
----
-
-## Domain Specific Languages
-
-<img rounded style="width: 500px"  src="./img/chess.jpeg" />
-
-Notes:
-
-to the shorthand for summarizing chess games,
-
----
-
-## Domain Specific Languages
-
-<img rounded style="width: 500px" src="./img/ink.jpeg" />
-
-Notes:
-
-to the ink! programming language that you will soon learn.
-Contract law is a DSL and is an important part of society.
-It’s hard to read (read the sentence on the slide).
-Computer Programming languages are also DSLs, which of course had it’s own evolution, independent from contract law.
-It can be quite hard to read (asm or solidity), whereas good ones can also be easier to read.
-But really, the point I'm trying to make here is that legalese contract law and computer programming languages are not so different.
-They are both DSL meant to precisely express the nuances of detailed human agreements.
-And they're both hard to read for non experts.
-Szabo recognized this similarity and thus had the idea that programming may be the future of law.
-
----
-
-## Coding Style
-
-- Adding laws vs negative diffs
-- Elegance vs handling each special case
-- Testing and Repeatability
-
-Notes:
-
-Back to the thing about both being hard to read for non-experts, a goal of mine is to make smart contracts more accessible to everyday people so that people can read their own contracts!
-
-HOWEVER since we're talking similarities - we should also speak to the differences.
-And hence be careful with this legal and coding comparison.
-The culture of the two can certainly be different:
-
----
-
-# Execution / Enforcement -- Pt. 2
-
-<img rounded style="width: 500px" src="./img/court.jpeg" />
-
-Notes:
-
-Okay, so now that we understand what it means to express and write a contract, imagine now that the legal agreement has been made, what comes next?
-
----
-
-# Execution / Enforcement -- Pt. 2
-
-<img rounded style="width: 500px" src="./img/moonbeam.jpeg" />
-
-Notes:
-
-Well it must be executed / enforced.
-Where does that happen? How does that work?
-
----
-
-## Traditional Execution
-
-<pba-flex center>
-
-- There is rarely an official submission moment.
-- Parties Self Execute
-- Sometimes, that's it.
-  Success.
-- Sometimes it goes to court.
-
-</pba-flex>
-
-Notes:
-
-So - let’s talk about execution.
-In a traditional sense, parties often just sign the contract - maybe there is a witness, sometimes even a notary, rarely does it actually get submitted to a judge.
-On the happy path, no further action is necessary - this is actually a decided strength of the traditional system - it is maximally lazy.
-When there is a dispute though, parties can go to court for a human judge to rule.
-A judge enforces through powerful agencies like police and jails, and also through social consensus.
-In practice there is little consideration for scaling, queue length, ruling priority, resource exhaustion.
-But in principle there could be.
-The existing systems of the nation states could be optimized considerably without having to even adopt any real smart contract.
-
----
-
-# Computerized Execution
-
-<pba-flex center>
-
-- There is a deployment moment
-- Sometimes there are checkpoints or milestones or other official interactions
-- Sometimes there is dispute resolution
-
-</pba-flex>
-
-Notes:
-
-Moving beyond traditional execution to computerized: you start some process on some computer and that computer faithfully executes the program for users to interact with.
-At first you can think of it like a computer in the basement and we walk up to it when we want to interact.
-This is how nintendo works.
-Multiple controllers and multiple physically present users.
-The internet makes it better in some ways.
-We can interact with our smart contract remotely instead of being physically present.
-But now, there is the question of the server operator.
-Are they really executing the correct contract?
-A corrupt server operator is essentially the same as a corrupt judge.
-Hmmm...
-so I wonder how we might solve this?
-
----
-
-# Code is Law
-
-<img rounded style="width: 500px" src="./img/codeislaw.jpeg" />
-
-Notes:
-
-So, after all of that talk comparing law and code, it's inevitable that we get here: 'Code is law' which is another web3-ism you'll hear quite often.
-We know tech can be used to enforce rules.
-So we might wonder, do we actually need lawyers? Can code dictate what we can and cannot do? Can smart contracts be the answer? I'm not coming for lawyers.
-I'm sure they're nice.
-But could this be the answer to make life more trustless and secure?
-But this is where we'll end it today.
-I hope I've primed you with a few lingering questions.
-These smart contracts do sound cool, but perhaps the execution, where it actually happens, hopefully is a bit opaque and puzzling still.
-That's what Joshy will be able to speak to this week.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Activity
-
-Notes:
-
-Any questions?
-
-Now I'm going to turn it over to Aaron to demonstrate this idea of expressing contracts as programming code.
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-# Designing DAG-based consensus
-
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-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
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----
-title: Designing DAG-based consensus
-description: A formal, yet friendly consensus framework
----
-
-# Designing DAG-based consensus
-
----
-
-## Goals of this lecture
-
-<br />
-
-1. formalize the consensus problem and related concepts <!-- .element: class="fragment"-->
-2. provide a framework for designing DAG-based consensus protocols <!-- .element: class="fragment"-->
-
----
-
-## What is consensus?
-
-<br />
-
-- a **process** of agreeing on the same result among a group of participants
-- a fundamental **problem** in distributed computing
-- a key **component** of blockchain technology stack
-
----
-
-## Consensus features
-
-<br />
-
-liveness, safety, integrity
-
----
-
-## We have already seen some
-
-<br />
-
-Nakamoto
-
-Babe
-
-Grandpa
-
-Sassafras
-
-Tendermint
-
-...
-
----
-
-## Who is running the protocol?
-
-<br />
-
-Participants, called **nodes**
-
----
-
-## Nodes
-
-<br />
-
-- nodes can be either honest or malicious
-- honest nodes follow the protocol
-- malicious nodes can deviate from the protocol in any way they want
-- malicious nodes can collude with each other
-- malicious nodes can be controlled by an adversary
-
----
-
-## Public key infrastructure
-
-<br />
-
-- every node has its own <font color="#c2ff33">private</font> and <font color="#e6007a">public</font> key
-- every node <font color="#c2ff33">signs</font> messages with its <font color="#c2ff33">private</font> key
-- every node <font color="#e6007a">verifies</font> messages with other nodes' <font color="#e6007a">public</font> keys
-
----
-
-## Public key infrastructure
-
-<br />
-
-authenticated point-to-point communication
-
----
-
-## Adversary
-
-<br />
-
-Adversary **can** control the network delays, but is _computationally bounded_, i.e. it **cannot** break the cryptography (like forging the signatures).
-
----
-
-## Network
-
-<br />
-
-Communication via network... but what kind of network?
-
----
-
-## Network models
-
-<br />
-
-synchronous
-
-partially synchronous
-
-asynchronous
-
----
-
-## Network models: synchronous
-
-<br />
-
-> There exists a known upper bound \\(\Delta\\) on message delivery time.
-
-<br />
-<br />
-
-_Intuition: there's a well-defined notion of a protocol round_
-
----
-
-## Network models: asynchronous
-
-<br />
-
-> There is no upper bound on message delay, though delivery is guaranteed.
-
-<br />
-<br />
-
-_Intuition: you can't tell whether a node has crashed or has a long delay_
-
----
-
-## Network models: asynchronous
-
-<br />
-
-> There is no upper bound on message delay, though delivery is guaranteed.
-
-<br />
-<br />
-
-- We assume that the adversary has full control over the message delays.
-- The concept of a timeout is basically useless.
-
----
-
-## Network models: partially synchronous
-
-<br />
-
-> There exists a known bound \\(\Delta\\), and an unknown point in time **GST** after which the communication becomes synchronous with a delay \\(\Delta\\).
-
-<br />
-<br />
-
-_Intuition: protocol will eventually work synchronously, but it needs to be safe before_
-
----
-
-## Crucial theoretical results
-
-<br />
-
-> \[FLP theorem\] It is impossible to have a deterministic protocol that solves consensus in an asynchronous system in which at least one process may fail by crashing.
-
-<br />
-<br />
-
-> \[Castro-Liskov theorem\] It is impossible to have a protocol that solves consensus in a partially synchronous system with \\(3f+1\\) nodes in which more than \\(f\\) processes are byzantine.
-
----
-
-## Crucial theoretical results
-
-<br />
-
-> \[FLP theorem\] It is impossible to have a <font color="#c2ff33">deterministic</font> protocol that solves consensus in an <font color="#c2ff33">asynchronous</font> system in which at least one process may fail by crashing.
-
-<br />
-<br />
-
-> \[Castro-Liskov theorem\] It is impossible to have a protocol that solves consensus in a <font color="#c2ff33">partially synchronous</font> system with \\(3f+1\\) nodes in which <font color="#c2ff33">more than</font> \\(f\\) processes are byzantine.
-
----
-
-## Consequence
-
-<br />
-
-The best one can hope for in **asynchronous** scenario is **probabilistic** protocol tolerating **up to** \\(f\\) faults for \\(3f+1\\) participants.
-
-<br />
-
-> ✅ <font color="#c2ff33"> **Doable!**</font>
-
-<!-- .element: class="fragment"-->
-
----
-
-## Note on randomness
-
-<br />
-
-Real probability is actually needed in the extremely hostile environment.
-In case where the adversary is not legendarily vicious, even a dumb (but non-trivial) randomness source will do.
-
----
-
-## Responsiveness
-
----
-
-## Responsiveness
-
-<br />
-
-Protocols that are **not responsive** have to **wait for** \\(\Delta\\) **time** to proceed to the next round.
-<br />
-
----
-
-## Responsiveness
-
-<br />
-
-Protocols that are **not responsive** have to **wait for** \\(\Delta\\) **time** to proceed to the next round.
-<br />
-<br />
-
-- \\(\Delta\\) must be long enough to allow all honest nodes to send their messages.
-- \\(\Delta\\) must be short enough to allow the protocol to make progress.
-- In case of failure, they have to perform a pretty expensive recovery procedure (like the leader change).
-
----
-
-## Responsiveness
-
-<br />
-
-Protocols that are **responsive** **wait for** \\(2f+1\\) **messages** to proceed to the next round.
-
-<br />
-<br />
-
-> <font color="#c2ff33">Why \\(2f+1\\)?</font>
-
-<!-- .element: class="fragment"-->
-
----
-
-## Responsiveness
-
-<br />
-
-Protocols that are **responsive** **wait for** \\(2f+1\\) **messages** to proceed to the next round.
-
-<br />
-<br />
-
-> <font color="#c2ff33">Among \\(2f+1\\) nodes, there are at least \\(f+1\\) honest ones, i.e. honest majority.</font>
-
----
-
-## Responsiveness
-
-<br />
-
-Protocols that are **responsive** **wait for** \\(2f+1\\) **messages** to proceed to the next round.
-<br />
-<br />
-
-- Asynchronous protocols must be responsive.
-- In good network conditions, they significantly much faster.
-
----
-
-## Checkpoint
-
-<br />
-
-Up to this point, we covered:
-
-- consensus problem
-- node types and adversary
-- inter-node communication
-- network models (synchronicity)
-- protocol limitations in asynchronous network (honesty fraction and the need for randomness)
-- responsiveness
-
----
-
-## Warmup exercise: broadcast
-
-<br />
-
-> (In an asynchronous network) **reliably** send a single message to all other nodes.
-
-<br />
-<br />
-
-- (_validity_) If the sender is honest and broadcasts a message \\(m\\), then every honest node outputs \\(m\\).
-
-<!-- .element: class="fragment"-->
-
-- (_integrity_) If an honest node outputs a message \\(m\\), then it must have been broadcast by the sender.
-
-<!-- .element: class="fragment"-->
-
-- (_agreement_) If an honest node outputs a message \\(m\\), every other honest node outputs \\(m\\).
-
-<!-- .element: class="fragment"-->
-
----
-
-## Reliable broadcast protocol (RBC)
-
-<br />
-
-<img rounded style="width: 1200px;" src="./img/3.10-rbc.svg" />
-
----
-
-## Reliable broadcast in practice
-
-<br />
-
-Due to the very high communication complexity we use heuristics or cryptography-based tricks.
-
----
-
-## Blockchain protocol vs Atomic broadcast
-
-<br />
-
-Atomic broadcast
-<br />
-
-<img rounded style="width: 700px;" src="./img/3.10-atomic-broadcast.svg" />
-
----
-
-## Randomness formalized
-
-<br />
-
-Randomness beacon
-<br />
-
-<img rounded style="width: 700px;" src="./img/3.10-randomness-beacon.svg" />
-
----
-
-## Atomic broadcast: timeline
-
-<br />
-
-<img rounded style="width: 1200px;" src="./img/3.10-timeline-1.svg" />
-
----
-
-## Atomic broadcast: timeline
-
-<br />
-
-<img rounded style="width: 1200px;" src="./img/3.10-timeline-2.svg" />
-
----
-
-## Fun fact
-
-<br />
-
-Aleph paper, as the first, also achieved fully asynchronous randomness beacon:
-
-- with efficient setup (\\(O(1)\\) rounds, \\(O(N^2)\\) communication)
-- with \\(O(1)\\) expected rounds to output a random value with \\(O(N)\\) communication per round
-
----
-
-## Consensus protocols (selection)
-
-<br />
-
-<pba-cols>
-<pba-col>
-
-### Classical protocols:
-
-- \[DLS’88\], \[CR’92\],
-- PBFT \[CL’99\]
-- Random Oracles … \[CKS’05\]
-- Honey Badger BFT \[MXCSS’16\]
-- Tendermint \[BKM’18\]
-- VABA \[AMS’19\]
-- Flexible BFT \[MNR’19\]
-- HotStuff \[YMRGA’19\]
-- Streamlet \[CS’20\]
-- Grandpa \[SKK'20\]
-
-</pba-col>
-<pba-col>
-
-### DAG-based protocols:
-
-- \[L. Moser, P. Meliar-Smith ‘99\]
-- Hashgraph \[B’16\]
-- Aleph \[GLSS’18\]
-- DAG-Rider \[KKNS’21\]
-- Highway \[KFGS’21\]
-- Narwhal&Tusk \[DKSS’22\]
-- Bullshark \[SGSK’22\]
-
-</pba-col>
-</pba-cols>
-
----
-
-## DAG-based protocols
-
----
-
-## DAG
-
-<br />
-
-Directed Acyclic Graph
-<br />
-
-<img rounded style="width: 700px;" src="./img/3.10-dag.svg" />
-
----
-
-## How does it relate to consensus?
-
-<br />
-
-Intuition: graph represents the dependencies between messages (units).
-<br />
-
-<img rounded style="width: 700px;" src="./img/3.10-message-dependency.svg" />
-
----
-
-## Framework core
-
-<br />
-
-1. We maintain a local DAG representing our knowledge of the units. <!-- .element: class="fragment"-->
-2. We perform a local, offline consensus on our DAG. <!-- .element: class="fragment"-->
-
----
-
-## Framework core
-
-<br />
-
-1. We maintain a local DAG representing our knowledge of the units.
-2. We perform a local, <font color="#c2ff33"> **offline consensus**</font> on our DAG.
-
----
-
-## Framework core (in other words)
-
-<br />
-
-1. (online): sending and receiving units that contribute to the local DAG
-2. (offline): everybody performs a local consensus on the DAG, just by looking at it
-
----
-
-## Clue observations
-
-<br />
-
-- local DAGs might differ... <!-- .element: class="fragment"-->
-- but they are guaranteed to converge to the same DAG <!-- .element: class="fragment"-->
-- the offline consensus is guaranteed to produce the same result <!-- .element: class="fragment"-->
-
----
-
-## Adversary control
-
-<br />
-
-<img rounded style="width: 600px;" src="./img/3.10-adversarial-control.svg" />
-
----
-
-## Randomness? Where is randomness?
-
-<br />
-
-It is put into the local consensus protocol.
-
----
-
-## Relation to the atomic consensus problem
-
-<br />
-
-- nodes receive transactions and put them into units
-- nodes send each other their new units
-- (locally) nodes come up with a linear ordering of the units and make blocks from chunks
-
----
-
-## Digression: block production, information dissemination and finalization
-
-<br />
-
-The common approach (e.g. in Substrate):
-
-- production and dissemination is done in the same layer
-- afterwards, nodes perform consensus on finalizing disseminated blocks
-
-<br />
-
-Natural approach for DAG-based protocols:
-
-- information dissemination happens as 'the first phase'
-- block building and (instant) finalization happens locally
-
----
-
-## Main consequences of the different separation
-
-<br />
-
-- block signatures
-- speed
-
----
-
-## Local consensus: goal
-
-<br />
-
-Local copies might differ significantly, blocks might have not come to all nodes yet, etc...
-but we have to make common decision about unit ordering!
-
----
-
-## Key concept: availability
-
-<br />
-
-Intuitively, a unit is **available** if:
-
-<br />
-
-- most of the nodes have it <!-- .element: class="fragment"-->
-- it was distributed pretty promptly (we won't call a unit available, if it finally arrived everywhere after a month) <!-- .element: class="fragment"-->
-- most of the nodes know that most of the nodes know that most of the nodes know... that it is available (mutual awareness) <!-- .element: class="fragment"-->
-
----
-
-## Availability
-
-<br />
-
-If a unit is available, it is a good candidate for being chosen as an 'anchor' in extending current ordering.
-
----
-
-## Lightweight case study
-
-<br />
-
-Aleph Zero BFT protocol
-
----
-
-## Head
-
-<br />
-
-<img rounded style="width: 600px;" src="./img/3.10-heads.svg" />
-
----
-
-## Building blocks
-
-<br />
-
-<img rounded style="width: 800px;" src="./img/3.10-building-blocks.svg" />
-
----
-
-## Choosing head
-
-<br />
-
-<img rounded style="width: 500px;" src="./img/3.10-choosing-head.svg" />
-
----
-
-## Availability determination
-
-<br />
-
-Units vote for each other's availability.
-
----
-
-## (Part of) availability determination
-
-<br />
-
-Vote<sub><font color="#c2ff33">U</font></sub>(<font color="#e6007a">V</font>) =
-
-- \[\[<font color="#c2ff33">U</font> is parent of <font color="#e6007a">V</font>\]\] if <font color="#e6007a">V</font> is from the round just after the round of <font color="#c2ff33">U</font>
-- `0`/`1` if all children of <font color="#c2ff33">U</font> voted `0`/`1`
-- `CommonVote(round(`<font color="#c2ff33">U</font> `), round(`<font color="#e6007a">V</font> `))` otherwise
-  <br />
-  <br />
-
-_(U comes from the earlier round than V)_
-
----
-
-## Bonus: generating randomness
-
-<br />
-
-Sig<sub> `sk`</sub>(nonce)
-
-<!-- .element: class="fragment"-->
-<br />
-
-<div class="fragment">
-
-- randomness must be unpredictable
-- delayed reveal
-- must depend on \\(f+1\\) nodes
-- cannot be disturbed by the adversary
-
-</div>
-
----
-
-## Standard way
-
-<br />
-
-<img rounded style="width: 600px;" src="./img/3.10-shamir.svg" />
-
----
-
-## Standard way
-
-<br />
-
-<img rounded style="width: 600px;" src="./img/3.10-shamir-2.svg" />
-
-Problem: need for trusted dealer! <!-- .element: class="fragment"-->
-
----
-
-## One simple trick
-
-<br />
-
-<font color="#c2ff33">Everybody is dealing secrets</font> <!-- .element: class="fragment"-->
-
----
-
-## Combining randomness
-
-<br />
-
-<img rounded style="width: 600px;" src="./img/3.10-xoring.svg" />
diff --git a/content/blockchain-contracts/econ-game-theory/page.md b/content/blockchain-contracts/econ-game-theory/page.md
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-# Econ & Game Theory in Blockchain
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/econ-game-theory/slides.md b/content/blockchain-contracts/econ-game-theory/slides.md
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----
-title: Econ & Game Theory in Blockchain
-description: Blockchain applications of Econ & Game Theory
-duration: 60 minutes
----
-
-# **Econ & Game Theory in Blockchain**
-
-Notes:
-
-- Presenter Introduction
-- Timeline clarification (after mod 2 and 3)
-- Today we'll be going through a brand new lecture on Econ & Game Theory in Blockchain
-
----
-
-# What's the goal?
-
-Notes:
-
-What's the goal of this lecture?
-
----v
-
-## What's the goal?
-
-<pba-cols>
-    <pba-col>
-        <img style="width: 500px" src="./img/Econ_Box_Open.svg" alt="Econ Box Open" />
-    </pba-col>
-    <pba-col>
-        <ul>
-            <li> Demand & Supply </li>
-            <li> Markets </li>
-            <li> Nash Equilibrium </li>
-            <li> Schelling Point </li>
-            <li> <strong>...</strong> </li>
-        </ul>
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-By now you all should be familiar with all the terms and techniques from the Economy and Game Theory module like the Demand & Supply or Nash equilibrium.
-
----v
-
-## What's the goal?
-
-<pba-cols>
-    <pba-col>
-        <img style="width: 280px; margin-top: 190px" src="./img/Econ_Box_Closed.svg"
-            alt="Econ Box" />
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/Blockchain_Box_Open.svg" alt="Blockchain Box Open" />
-    </pba-col>
-    <pba-col>
-        <ul>
-            <li> Consensus </li>
-            <li> Protocol </li>
-            <li> Tokens </li>
-            <li> State Transition Functions </li>
-            <li> <strong>...</strong> </li>
-        </ul>
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-And you also just finished covering the basics of Blockchains so you all should be familiar with state transition functions as well as have some understanding of consensus protocols.
-
----v
-
-## What's the goal?
-
-<img style="width: 800px; margin-top: 130px" src="./img/Econ_Handshake_Blockchain.svg"
-    alt="Econ and Blockchain Handshake" />
-
-Notes:
-
-Having all that in mind, the goal of this lecture is to combine the two and see how the economy and game theory can be applied to blockchain.
-To do that we'll provide some exemplary use-cases and case studies.
-
----
-
-# Landscape
-
-Notes:
-
-But first let's start with a quick summary of how we'll be approaching to bridge the gap between the two modules.
-
----v
-
-## Landscape
-
-<pba-cols>
-    <pba-col>
-        <ul>
-            <li> Systems as Games </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/game.svg" alt="Game Pad" />
-    </pba-col>
-
-Notes:
-
-Firstly, we'll be looking at various blockchain systems as isolated games.
-
----v
-
-## Landscape
-
-<pba-cols>
-    <pba-col>
-        <ul>
-            <li> Systems as Games </li>
-            <li> Nodes/Miners/Validators as Players </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/player.svg" alt="Laptop user cheering" />
-    </pba-col>
-
-Notes:
-
-Participants in those games will be for instance the miners, like in the Bitcoin protocol, maybe the validators in the Polkadot protocol or just some users of your smart contract.
-
----v
-
-## Landscape
-
-<pba-cols>
-    <pba-col>
-        <ul>
-            <li> Systems as Games </li>
-            <li> Nodes/Miners/Validators as Players </li>
-            <li> Protocols as Game Rules</li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 300px" src="./img/assumptions.drawio.svg" alt="Checklist with points" />
-    </pba-col>
-
-Notes:
-
-The protocol is essentially a set of rules that will define the game itself.
-The one we will be analyzing.
-
----v
-
-## Landscape
-
-<pba-cols>
-    <pba-col>
-        <ul>
-            <li> Systems as Games </li>
-            <li> Nodes/Miners/Validators as Players </li>
-            <li> Protocols as Game Rules</li>
-            <li> Cryptocurrencies as Points </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 400px" src="./img/bitcoin.svg" alt="BTC symbol" />
-    </pba-col>
-
-Notes:
-
-And to properly analyze those games we need to have some value representation, which in our case will be usually cryptocurrencies.
-
----v
-
-## Landscape
-
-<pba-cols>
-    <pba-col>
-        <ul>
-            <li> Systems as Games </li>
-            <li> Nodes/Miners/Validators as Players </li>
-            <li> Protocols as Game Rules</li>
-            <li> Cryptocurrencies as Points </li>
-            <li> Rewards & Punishments as Incentives</li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/gavel.svg" alt="Gavel Hammer" />
-    </pba-col>
-
-Notes:
-
-And finally we'll be having various reward and punishment schemes that will shape the incentives of the players.
-
-Now that we have all the elements defining our blockchain games we can look for further parallels.
-
----v
-
-# Market Emergence
-
-Notes:
-
-And first let's take a look at something that hopefully very familiar: Markets
-
----v
-
-## Market Emergence
-
-_"A market is a composition of systems, institutions, procedures, social relations or infrastructures whereby parties engage in exchange."_
-
-Notes:
-
-So a market is a composition of systems where ppl exchange stuff.
-This is the simplest way of putting it.
-
-And Markets are the cornerstone of our economy and they are everywhere which also means they are thoroughly studied.
-Which is very fortunate for us.
-
-Now let's look at something that might also be pretty familiar to many...
-
----v
-
-## Market Emergence
-
-#### _Fee Market_
-
-<img style="width: 1200px" src="./img/fees.png"
-    alt="Chart of Bitcoin fees over time" />
-
-Notes:
-
-The fee market.
-That's a chart of the average transaction fees in the Bitcoin network over time.
-As you can see the price is constantly fluctuating.
-
----v
-
-## Market Emergence
-
-#### _Fee Market_
-
-<pba-cols>
-    <pba-col>
-        <strong> Fees/Tips </strong>
-        <ul>
-            <li> Users bid with the fees </li>
-            <li> Miners select highest fee transactions </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/scales.svg" alt="Scales Icon" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Let's dive a bit deeper.
-So the users are bidding with how much they are willing to pay and miners are choosing the most lucrative transactions.
-If miners already included all the best transactions and there are not many new ones coming in they need to start accepting lower fees, so the price drops.
-But wait...?
-
----v
-
-## Market Emergence
-
-#### _Fee Market_
-
-<pba-cols>
-    <pba-col>
-        <strong> What is the product? </strong>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/blockspace.drawio.png" alt="Blockspace in Polkadot" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-What is the actual product being exchanged here? When you have the crude oil market the goods being exchanged are clearly defined.
-It's crude oil barrels.
-What is actually being traded in here?
-
-Anyone has an idea what it might be?
-
----v
-
-## Market Emergence
-
-#### _Fee Market_
-
-<pba-cols>
-    <pba-col>
-        <strong> What is the product? </strong>
-        <ul>
-            <li> What is being exchanged is the blockspace </li>
-            <li> Miners produce blockspace and effectively auction it to users </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/blockspace.drawio.png" alt="Blockspace in Polkadot" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-It's the BLOCKSPACE.
-Miners secure and produce blockspace and sell it in an auction to various users.
-Blockspace as a product is actually a pretty new way of thinking about blockchains so I highly suggest checking out the article linked in the notes.
-
-- <https://www.polkadot.network/blog/blockspace-blockspace-ecosystems-how-polkadot-is-unlocking-the-full-potential-of-web3/>
-
----v
-
-## Market Emergence
-
-#### _Fee Market_
-
-<pba-cols>
-    <pba-col>
-        <strong> Market Equilibrium </strong>
-        <ul>
-            <li> The transactions that manage to get into the blocks have fees representative of the current market equilibrium </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/market_eq.drawio.svg" alt="Chart showing a market equilibrium" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-The price of blockspace is determined by the market equilibrium of supply and demand.
-Demand force is the users willing to transact and supply is the miners producing the blockspace.
-Transactions that are actually included represent the current equilibrium.
-
----v
-
-## Market Emergence
-
-#### _Fee Market_
-
-<pba-cols>
-    <pba-col>
-        <strong> Supply & Demand </strong>
-        <ul>
-            <li> In extreme cases the demand can raise so much that the fees overwhelm the network </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/rising.svg" alt="Rising graph icon" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-We all know that the transaction fees can sometimes get outrageous.
-In cases where many users want to transact the demand can skyrocket.
-And what we see is the price equilibrium following suit.
-
----v
-
-## Market Emergence
-
-#### _Fee Market_
-
-<pba-cols>
-    <pba-col>
-        <strong> Supply & Demand </strong>
-        <ul>
-            <li> In extreme cases the demand can raise so much that the fees overwhelm the network </li>
-            <li> Most economic markets can react to growing demand with increased supply, but that is not directly possible in most blockchains </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 300px" src="./img/goods.svg" alt="Stack of goods on a conveyor belt" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-And now let's think of what normal markets do.
-If our demand and price go extremely high the suppliers would have an incentive to produce more.
-But in blockchains that's not directly possible.
-More miners often don't mean more blockspace but MORE SECURE blockspace.
-That means a better quality blockspace.
-
-So the supply is often fixed and the demand is fluctuating.
-This is often the cause for the very volatile fee market.
-
----v
-
-## Market Emergence
-
-#### _Fee Market_
-
-<pba-cols>
-    <pba-col>
-        <strong> Supply & Demand </strong>
-        <ul>
-            <li> In extreme cases the demand can raise so much that the fees overwhelm the network </li>
-            <li> Most economic markets can react to growing demand with increased supply, but that is not directly possible in most blockchains </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/kitty.png" alt="CryptoKitties Logo" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-And according to that theory some large blockchains actually tried implementing variable size blocks to react to the demand, but it's a pretty complex task and a big tradeoff.
-
-Some of you maybe recognize this image as the CryptoKitties game on Ethereum.
-It's a game where you can buy and breed digital cats.
-It was so popular that it actually clogged the Ethereum network and made normal transactions nearly unfeasible.
-And maybe now you have some additional insights into what actually happened there.
-
-=5 sec pause=
-
----
-
-# Nash Equilibrium
-
-Notes:
-
-Now let's look at something a bit different that allows us to predict what users would do...
-a Nash Equilibrium.
-
----v
-
-## Nash Equilibrium
-
-- Strategy from which no player wants to deviate
-- But what's the strategy for BTC mining?
-
-Notes:
-
-Nash Equilibrium is strategy from which no player wants to deviate.
-Pretty simple but what's the strategy for BTC mining? How can we leverage that knowledge?
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 500px" src="./img/honest_mining_meme.jpg" alt="Honest Mining Meme"/>
-
-Notes:
-
-And more importantly...
-being honestly is the answer, right?
-
----v
-
-## Nash Equilibrium
-
-#### _Bitcoin Mining_
-
-<img style="width: 400px" src="./img/bitcoin.svg" alt="Bitcoin Logo" />
-
-Notes:
-
-Let's dive in and actually see what's the answer.
-What's the Nash Equilibrium of Bitcoin mining? Is it being honest or dishonest?
-
----v
-
-## Nash Equilibrium
-
-<pba-cols>
-    <pba-col>
-        <strong>Assumptions:</strong>
-        <ul>
-            <li> Only 2 miners </li>
-            <li> Block reward = 2 </li>
-            <li> Difficulty scales with number of honest miners </li>
-            <li> Miners are rational actors </li>
-            <li> Dishonest miners do not cooperate </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/nash.drawio.svg" alt="Payoff Table" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Here we have a few assumptions, but the main ones are:
-
-- imagine we have only 2 miners
-- the block rewards is 2
-- miners can be honestly following the protocol or try to cheat and push invalid blocks (for instance one where they get 999 bitcoins)
-
-Let's figure out how many bitcoins each one of them will mine on average.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (1).svg" alt="Payoff Table" />
-
-Notes:
-
-If both miners are not mining honestly, none of them produce valid bitcoin blocks...
-then there are no ACTUAL bitcoins being mined.
-Remember that they don't cooperate but for instance try and push blocks with 9999 BTC in their account.
-So the reward is 0 for both.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (2).svg" alt="Payoff Table" />
-
-Notes:
-
-If both are working honestly and making valid blocks they have an equal chance to mine a block and reap the rewards.
-Rest of the nodes will accept those blocks but the two miners compete for the same resource so each one will get a single BTC on average (as the mining reward is 2).
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (3).svg" alt="Payoff Table" />
-
-Notes:
-
-If one of them is dishonest the other one can still keep working honestly and reap greater rewards as there is no competition.
-In that case the honest party gains 2 BTC.
-
-Now that we know who earns how many bitcoins in each scenario we need to shift out attention to another important force.
-Things like Twitter, Facebook or Bitcoin are often deemed as valuable because of their Network Effect.
-
----v
-
-## Nash Equilibrium
-
-<br />
-
-#### _Network Effect_
-
-_"The network effect is a business principle that illustrates the idea that when more people use a product or service,
-its value increases."_
-
-Notes:
-
-Generally the more ppl use some platform or believe in something the more valuable it is.
-It's a pretty simple concept but it's very important in the blockchain space.
-Bitcoin is precious to many because many people believe in it and mine it and exchange it.
-In blockchains if more people use your chain it's more valuable.
-
----v
-
-## Nash Equilibrium
-
-<br />
-
-#### _Network Effect_
-
-<br />
-<strong>Assumptions revisited:</strong>
-<ul>
-    <li style="color: grey;"> Only 2 miners </li>
-    <li style="color: grey;"> Block reward = 2 </li>
-    <li style="color: grey;"> Difficulty scales linearly with number of honest miners </li>
-    <li style="color: grey;"> Miners are rational actors </li>
-    <li style="color: grey;"> Dishonest miners do not cooperate </li>
-    <li> Token price scales quadratically with the number of honest miners
-        <ul>
-            <li>1 honest miner -> 1$</li>
-            <li>2 honest miners -> 4$</li>
-    </li>
-</ul>
-
-Notes:
-
-Let's add this extra assumption into our model.
-If there are more miners securing the network the coins itself are more valuable.
-We will use a super simple model here where the price of a coin is a square of the number of miners.
-We will be investigating small systems so it is a good enough approximation.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (4).svg" alt="Payoff Table" />
-
-Notes:
-
-We can apply the changes by changing the evaluations of the miners coins.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (4b).svg" alt="Payoff Table" />
-
-Notes:
-
-If both miners honestly secure the network the coin price is 4 and in case of single honest miner the price is 1.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (5).svg" alt="Payoff Table" />
-
-Notes:
-
-Now we can actually focus on finding the Nash Equilibrium
-so let's used the simplest method.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (6).svg" alt="Payoff Table" />
-
-Notes:
-
-Assuming Miner B is honest the Miner A needs to choose between a payoff of 4 or 0.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (7).svg" alt="Payoff Table" />
-
-Notes:
-
-He ofc chooses 4 as it's higher.
-We temporarily mark it with the red circle.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (8).svg" alt="Payoff Table" />
-
-Notes:
-
-Same reasoning for B being dishonest and A chooses 2 over 0.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (9).svg" alt="Payoff Table" />
-
-Notes:
-
-Now we reverse the assumptions and assume A is honest and then B chooses between 4 and 0.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (10).svg" alt="Payoff Table" />
-
-Notes:
-
-Similarly as before he should choose 4 as it's higher.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (10b).svg" alt="Payoff Table" />
-
-Notes:
-
-And the last remaining options will result in the circled 2.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (12).svg" alt="Payoff Table" />
-
-Notes:
-
-Now the square with all the options circled is the Nash Equilibrium.
-In our case it seems to be being honest.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (13).svg" alt="Payoff Table" />
-
-Notes:
-
-Not a big surprise, and being dishonest lands you with zero coins so it was too be expected.
-But what if we change the assumptions a bit?
-
----v
-
-## Nash Equilibrium
-
-<br />
-What does it mean exactly to be <strong>dishonest</strong>?
-<br />
-<br />
-
-<div>
-    There are some mainstream rules (the protocol) and if an individual miner breaks them it seems like an isolated
-    mistake or an attempt at cheating.
-</div>
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-<br />
-<br />
-
-If multiple miners break the protocol <strong>in the same way</strong>, it can be seen as a new protocol deviating from
-the main one.
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-We were assuming that miners are either honest or dishonest, but what does being DISHONEST actually mean?
-
-=fragment=
-
-There are some mainstream rules (the protocol) and if an individual miner breaks them it seems like an isolated mistake or an attempt at cheating.
-This is what we were analyzing before.
-
-=fragment=
-
-But what if multiple miners break the protocol in the same way? It can be seen as a new protocol deviating from the main one.
-And that's what we'll be looking at next.
-The dishonest miners are cooperating.
-
----v
-
-## Nash Equilibrium
-
-<pba-cols>
-    <pba-col>
-        <strong>Assumptions:</strong>
-        <ul>
-            <li> Only 2 miners </li>
-            <li> Block reward = 2 </li>
-            <li> Difficulty scales with number of honest miners </li>
-            <li> Token price scales quadratically wih the number of honest miners </li>
-            <li> Miners are rational actors </li>
-            <li> Decision between which protocol to follow </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/nash.drawio (14).svg" alt="Payoff Table" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Assumptions are pretty much the same but this time around the dishonest miners will cooperate.
-Effectively they will be following a different modified protocol.
-
-So we will no longer consider them dishonest but they simply follow a different set of rules.
-Now miners choose to mine for the bitcoin BTC protocol or the bitcoin cash BCH protocol.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (15).svg" alt="Payoff Table" />
-
-Notes:
-
-Let's quickly fill up this table with the same rules as before.
-Only this time of both miners follow BCH they ofc get the rewards in the BCH token.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (16).svg" alt="Payoff Table" />
-
-Notes:
-
-Just as before we take the extra step and apply the network effect.
-If both miners secure the network price is 4 and if only 1 the price is 1.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (17).svg" alt="Payoff Table" />
-
-Notes:
-
-Here we have all the prices adjusted.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (18).svg" alt="Payoff Table" />
-
-Notes:
-
-Now let's take a look at what happens if Miner B miners BTC.
-Miner A would prefer to also mine bitcoin.
-So they are both mining the same thing.
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (19).svg" alt="Payoff Table" />
-
-Notes:
-
-On the other hand if miner B mines BCH then it seems that Miner A prefers to mine BCH...
-
----v
-
-## Nash Equilibrium
-
-<img style="width: 700px" src="./img/nash.drawio (20).svg" alt="Payoff Table" />
-
-Notes:
-
-And in fact what we have in here is two distinct Nash Equilibria!
-
----v
-
-## Nash Equilibrium
-
-So is being honest the best strategy?
-
-<br />
-<br />
-
-Not always.
-If the majority of people are honest then honesty pays off.
-If the majority of people are _dishonest_ in the
-same way then be _dishonest_ with them.
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-<br />
-<br />
-<div>
-    In fact it was proven that in PoW following the majority is the true Nash Equilibrium no matter what
-    strategy/protocol they are using as long as it's consistent.
-</div>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-So is being honest the best strategy?
-
-=fragment=
-
-Not always.
-If the majority of people are honest then honesty pays off.
-If the majority of people are _dishonest_ in the same way then be _dishonest_ with them.
-
-=fragment=
-
-In fact it was proven that in PoW following the majority is the true Nash Equilibrium no matter what strategy/protocol they are using as long as it's consistent.
-So Bitcoin mining is in fact a huge coordination game and this is why honesty AKA following the BTC protocol usually pays off.
-
-- More complex examples will be explored later in the forks lecture on Friday
-- Paper investigating PoW Nash Equilibrium and following the majority:
-  <https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=7bf78054192d98e999edcdf08971a5eed42518d2>
-
----
-
-# Schelling Point
-
-Notes:
-
-On that topic...
-What if we have multiple Nash Equilibria? Schelling point often comes to the rescue.
-
----v
-
-## Schelling Point
-
-- A solution that people tend to choose (easiest to coordinate on)
-- Generally it is also a Nash Equilibrium
-- How in the world can it be useful in Blockchain?
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-So first a Schelling point is a strategy people tend to choose.
-It is generally a Nash Equilibrium
-
-=fragment=
-
-But how in the world is it useful to us in Blockchain?
-
----v
-
-## Schelling Point
-
-#### Detective game
-
-<pba-cols>
-    <pba-col>
-        <ul>
-            <li> Two partners in crime</li>
-            <li> Detective interrogates them individually </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 700px" src="./img/detective.drawio.png" alt="Detective and 2 robbers" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-But before we can fully answer that let's explore a different game that can show you how Schelling points work.
-And I promise it will be applicable to Blockchain.
-
-So the story goes like that.
-We have to bank robbers and a detective.
-The detective interrogates he robbers and tries to make them confess or catch them lying.
-
----v
-
-## Schelling Point
-
-#### _Detective game_
-
-<img style="width: 550px" src="./img/interrogation_small.drawio.svg" alt="Interrogation Game Payoff Table" />
-
-Notes:
-
-If any of the robbers spill the beans and tell the truth they both loose the game and go to prison.
-If both of them lie they get away with it.
-Seems super simple and it should be pretty straightforward that they both simply need to lie.
-
-Seems like a safe strategy, right? But remember than both of them witnessed the same real events of the robbery...
-
----v
-
-## Schelling Point
-
-#### _Detective game_
-
-<img style="width: 700px" src="./img/interrogation_large.drawio.svg" alt="Interrogation Game Large Payoff Table" />
-
-Notes:
-
-But there are multiple lies they can construct.
-If they have inconsistent stories the detective will catch them.
-So now they need to coordinate on a specific lie and have all the details exactly the same or they are screwed.
-
-Contrast it with how easy it would be to just tell the truth.
-They both witnessed the truth so talking about it in a consistent way is trivial.
-
----v
-
-## Schelling Point
-
-#### _Detective game_
-
-Truthful answers are one of the easiest strategies coordinate on, so they are the Schelling Points.
-
-Notes:
-
-That's why we can say that Truthful answers are one of the easiest strategies coordinate on, so they are the Schelling Points.
-The truth itself is a Schelling point.
-
-And this concept is vital to something in blockchain called...
-
----v
-
-## Schelling Point
-
-#### _Oracles_
-
-Oracles are blockchain entities that provide information from the outside world to the blockchain.
-<br />
-<br />
-<img style="width: 700px" src="./img/oracles.drawio.svg" alt="Oracle getting information from real world" />
-
-Notes:
-
-Oracles.
-Firstly who in the room heard of oracles? Raise your hands.
-Oracles are super interesting because what they are trying to achieve is to provide information from the outside world to the blockchain.
-And that's a very very hard task.
-
----v
-
-## Schelling Point
-
-#### _Oracles_
-
-Oracles are blockchain entities that provide information from the outside world to the blockchain.
-<br />
-<br />
-
-<div>
-    <strong>External Information Examples:</strong>
-    <ul>
-        <li> What's the temperature in Berkeley? </li>
-        <li> Who won the election? </li>
-        <li> What's the exchange rate of USD to BTC? </li>
-    </ul>
-</div>
-
-Notes:
-
-Some examples of the information they can provide are for instance what's the current temperature in Berkeley? Who won the election? What's the exchange rate of USD to BTC? and may others.
-
-Let's actually see how they might work is a slightly simplified version with the temperate example.
-
----v
-
-## Schelling Point
-
-#### _Oracles_
-
-<br />
-<br />
-<img style="width: 900px" src="./img/temp1.drawio.svg" alt="Temperature Line" />
-
-Notes:
-
-So what's the temperature in Berkeley? Imagine you have a garden in Berkeley and you have on chain insurance that if the temperature is too high you get a payout.
-So you want to know the temperature in Berkeley.
-
-We know the answer lies somewhere on this axis.
-But what it is exactly?
-
----v
-
-## Schelling Point
-
-#### _Oracles_
-
-<br />
-<br />
-<img style="width: 900px" src="./img/temp2.drawio.svg" alt="Temperature Line with Some Measurements" />
-
-Notes:
-
-We can ask some users to submit what they think the temperature is.
-Some of them will check it themselves, some will use weather apps and some will just guess.
-
----v
-
-## Schelling Point
-
-#### _Oracles_
-
-<img style="width: 900px" src="./img/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
-
-Notes:
-
-What we are hoping for is that the cluster of votes you can see here will be around the actual temperature.
-The best approach would be to check the median.
-And why is that?
-
----v
-
-## Schelling Point
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <ul>
-            <li> Honest participants are naturally coordinated </li>
-            <li> Attackers could try to coordinate and lie </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Honest voters are naturally coordinated.
-They will check the temperature and vote honestly all within some small margin of error.
-
-People that would lie to skew the results and would submit random values generally wouldn't cluster like the honest voters.
-To make a more dangerous attack they would need to strategically coordinate on a specific value and all lie about it.
-It's much harder to pull of than simply checking the temperature outside.
-
-Submitting the truth is the Schelling Point in here and it makes it easy to be honest.
-
----v
-
-## Schelling Point
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        What to do with attackers?
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-But what if there are some attackers? What can we do about them?
-
----v
-
-## Schelling Point
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        What to do with attackers?
-        <br /><br />
-        If they go unpunished they can repeat the attack until successful
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-If we never punish them they can repeat the attack until they are successful.
-And that's not good.
-
----v
-
-## Schelling Point
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        What to do with attackers?
-        <br /><br />
-        If they go unpunished they can repeat the attack until successful
-        <br /><br />
-        Or even worse, they can make a million fake identities and spam incorrect votes
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Or even worse, they can make a million fake identities and spam incorrect votes.
-So we need to punish them.
-
-But this is no longer a problem of a Schelling Point.
-The Schelling point did its job already.
-What we are talking about right now are...
-
----
-
-# Incentives
-
-Notes:
-
-Incentives.
-Incentives are the next big topic we will be exploring.
-And they are vital to the blockchain space.
-
----v
-
-## Incentives
-
-_"Something that encourages a person to do something."_
-<br /><br />
-
-<div>In our case we want to shape incentives that motivate the users to submit honest values.</div>
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-Incentives are things that encourage people to do something.
-
-=fragment=
-
-In our case we want to shape incentives that motivate the users to submit honest values.
-We need to build out incentives in a way that shapes the expected behavior of the users to honesty.
-
----v
-
-## Incentives
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        What to do with attackers?
-        <br /><br />
-        If they go unpunished they can repeat the attack until successful
-        <br /><br />
-        Or even worse, they can make a million fake identities and spam incorrect votes
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/temp3.drawio.svg" alt="Temperature Line with a Cluster of Measurements" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-So going back to our oracle problem how can we deal with attackers?
-
----v
-
-## Incentives
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <div style="color: grey;">What to do with attackers?
-        <br /><br />
-        If they go unpunished they can repeat the attack until successful
-        <br /><br /></div>
-        <strong>Or even worse, they can make a million fake identities and spam incorrect votes</strong>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/mask.svg" alt="Mask" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Let's focus on the second issue of fake identities.
-How can we prevent that?
-
----v
-
-## Incentives
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <strong> Sybil Attacks </strong>
-        <br /><br />
-        Common problem in blockchain.
-        <br /><br />
-        <div>If deploying on a chain, an easy solution is to make users lock some funds.</div>
-        <!-- .element: class="fragment" data-fragment-index="1" -->
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/mask.svg" alt="Mask" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-An attack where a single entity creates multiple fake identities is called a sybil attack and is super common in blockchain.
-This is one of the things you always will need to ask yourself when you deploy things in blockchain.
-Is whatever I built safe from Sybil Attacks?
-
-=fragment=
-
-One easy ready solution that is often used is making users lock some funds.
-Only a user with some funds locked can vote.
-The strength of the vote is proportional to the stake so making a million accounts makes no sense.
-This is a very simple solution but it's not always applicable.
-
----v
-
-## Incentives
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <div style="color: grey;">What to do with attackers? </div>
-        <br />
-        <strong>If they go unpunished they can repeat the attack until successful</strong>
-        <br /><br />
-        <div style="color: grey;">Or even worse, they can make a million fake identities and spam incorrect votes </div>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/gavel.svg" alt="Gavel Hammer" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Now let's go back to the first issue of unpunished attackers.
-How can we deal with them so they don't continue attacking us?
-
----v
-
-## Incentives
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <strong> Punishments </strong>
-        <br /><br />
-        We already laid out the foundation for punishments.
-        <br /><br />
-        <div> Our solution for de-sybiling users makes them lock funds.
-        <br /><br />
-        If such a user would vote incorrectly, we can slash their funds.
-        </div>
-        <!-- .element: class="fragment" data-fragment-index="1" -->
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/gavel.svg" alt="Gavel Hammer" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Interestingly we already laid out the foundation for the defense.
-Voters have some funds locked in the system so they have Skin in the game.
-
-=fragment=
-
-If they vote incorrectly we can slash their funds.
-This is a very common solution in blockchain.
-Incorrect in that case would be very far from the median.
-
-We have designed some protective incentives and now the system seems safe.
-
----v
-
-## Incentives
-
-#### _Oracles_
-
-<br />
-Did we forget about something?
-
-<br /><br />
-
-**Why would anyone participate in this system?**
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-But did we forget about something? Anyone has any idea what it might be? What we are missing?
-
-=fragment=
-
-Why would anyone participate in this system? Why would anyone vote? Why would anyone lock their funds and take the risk?
-
----v
-
-## Incentives
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <strong> Ghost Town </strong>
-        <br /><br />
-        No user wants to participate
-        <br /><br />
-        Getting information from the real world is an effort and they voters are doing the protocol a service
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/ghost.svg" alt="Ghost" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Getting information from the real world is an effort and they voters are doing the protocol a service.
-So we need to incentivize them to participate.
-We need a rewards scheme or otherwise the network will be a ghost town.
-
----v
-
-## Incentives
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <strong> Reward Scheme </strong>
-        <br /><br />
-        If users are doing the protocol a service they need to be rewarded
-        <br /><br />
-        <div> One way to do it is to mint some token rewards for well-behaved voters </div>
-        <!-- .element: class="fragment" data-fragment-index="1" -->
-        <br />
-        <div> Or distribute them from a previously acquired pool of rewards </div>
-        <!-- .element: class="fragment" data-fragment-index="2" -->
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/rewards.svg" alt="Hand receiving some money" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-If users are doing the protocol a service they need to be rewarded.
-
-=fragment=
-
-One way to do it is to mint some token rewards for well-behaved voters.
-
-=fragment=
-
-Or distribute them from a previously acquired pool of rewards.
-
-But what is crucial here the protocol is safe and dependable only if there is enough voters so the incentives need to be designed in a way that encourages participation.
-
-More precisely, incentives need to be roughly proportional to the value an attacker could gain by compromising the system.
-Low-stakes oracles don't need to have super aggressive incentives.
-
----v
-
-## Incentives
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <strong> Reward Scheme Question</strong>
-        <br /><br />
-        <div>
-        Can we distribute fixed value rewards for correct votes?
-        <br />Correct vote = 10$
-        </div>
-        <br /><br />
-        <div>
-         No.
-         We should base rewards on the size of the voter's stake.
-        </div>
-        <!-- .element: class="fragment" data-fragment-index="1" -->
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/questions.svg" alt="Raised Hands" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Let's do a quick question.
-Can we distribute fixed value rewards for correct votes? As an example each Correct vote = 10$
-
-=question time=
-
-=fragment=
-
-No.
-We should base rewards on the size of the voter's stake.
-Otherwise the system is vulnerable to sybil attacks.
-If you have a million fake identities you can vote a million times and get a million times the reward.
-So the reward should be proportional to the stake.
-
----v
-
-## Incentives
-
-**In summary:**
-
-- Make it easy to honest users and hard for attackers
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Service to the protocol needs to be rewarded
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- Destructive or interfering actions need to be punished
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-- De-Sybiling the users can help defend against spam
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-Notes:
-
-Now let's summarize the main points.
-
-We need to make it easy for honest nodes and hard for attackers.
-The Schelling Point as the foundational part of the design handles that for us.
-
-=fragment=
-
-Service to the protocol needs to be rewarded.
-We need to incentivize participation to guarantee reliable results.
-
-=fragment=
-
-Destructive or interfering actions need to be punished.
-We need to disincentivize bad behavior.
-In our case we did the slashes.
-
-=fragment=
-
-De-Sybiling the users can help defend against spam.
-
-We we have all of that our systems should be properly incentivized and safe...
-and on that note what happens when the incentives are...
-
----
-
-# Misaligned Incentives
-
-Notes:
-
-Misaligned.
-When they promote some behavior that is not good for the network.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<img style="width: 200px" src="./img/eth.svg" alt="Ethereum Logo" />
-
-Notes:
-
-Let's take a look at Ethereum.
-Ethereum is a blockchain that has a lot of smart contracts.
-And smart contracts are basically programs that run on the blockchain.
-They are stored on chain and they can be executed by anyone.
-For them to work a bunch of code needs to be deployed on the chain.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> State Storage Replication </strong>
-        <br /><br />
-        Whenever we store something on chain (like a smart contract) it needs to be at least partially replicated among the nodes.
-        <br /><br />
-        <div> Multiple nodes store the same data.</div>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/replication.drawio.svg" alt="Data Replication Diagram" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-And moreover whenever we store something on chain (like a smart contract) it needs to be at least partially replicated among the nodes.
-Thousands of nodes store the same data which is not super efficient.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> State Storage Replication Costs </strong>
-        <br /><br />
-        Ethereum deals with the burden of replication by charging more gas for submitting bulky data.
-        <br /><br />
-        All of that is ON TOP OF any computation gas costs.
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/storage_costs.drawio.svg" alt="Stacks of coins next to data blobs" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Ethereum attempts to deal with it by introducing scaling fees.
-The more data you put in the state the more you need to pay.
-And that's on top of any computation costs.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> State Storage Duration</strong>
-        <br /><br />
-        This particular part of the state might be relevant for future state transitions so nodes cannot simply discard it.
-        <br /><br />
-        <div> Full nodes need to keep ALL the data.</div>
-    </pba-col>
-    <pba-col>
-        <img style="width: 500px" src="./img/data_no_changes.drawio.svg" alt="Data same over time" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Note that once we put something in state it has to stay there pretty much indefinitely until we use it again.
-Because who knows, it might be relevant to some future state transitions.
-So nodes cannot simply discard it.
-
-Now let's explore an example.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> Meet Bob </strong>
-        <br /><br />
-        Bob happily deploys his awesome smart contract in Ethereum.
-        He paid a hefty gas fee but so be it.
-        <br /><br />
-    </pba-col>
-    <pba-col>
-        <img style="width: 600px" src="./img/smart_contract.drawio.svg" alt="Deploying a smart contract on chain" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-So let's meet Bob.
-Bob is a developer and he happily deploys his awesome smart contract in Ethereum.
-He paid a hefty gas fee but so be it.
-His code was added to the state and now many nodes hold a copy of it.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> The Problem </strong>
-        <br /><br />
-        Bob decided to become a musician or just no longer likes programming.
-        <br /><br />
-        He doesn't care about his smart contract anymore.
-    </pba-col>
-    <pba-col>
-        <img style="width: 600px" src="./img/smart_contract_deployed.drawio.svg" alt="Smart contract deployed on chain" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-But imagine that one day Bob decides to become a musician or he just no longer likes programming.
-He doesn't care about his smart contract anymore.
-But the chain doesn't know about it.
-His code still lives in the state and has to be continuously replicated and maintained.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> The Problem Made Worse </strong>
-        <br /><br />
-        Many others like Bob follow suit.
-        <br /><br />
-        Some of them continue developing but, <strong>why bother</strong> removing old data? They already paid for it.
-    </pba-col>
-    <pba-col>
-        <img style="width: 600px" src="./img/smart_contract_many.drawio.svg" alt="Many smart contracts deployed on chain" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Now imagine there are hundreds of people like Bob.
-Some of them even continue developing but, WHY BOTHER removing old data? They already paid for it.
-And some of them just don't care anymore.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> "Why Bother?" </strong>
-        <br /><br />
-        Getting data on chain is expensive, but there is no incentive to clean it up.
-        <br /><br />
-        This is a core misalignment of incentives that lead to Ethereum state size growing out of control.
-    </pba-col>
-    <pba-col>
-        <img style="width: 600px" src="./img/smart_contract_many.drawio.svg" alt="Many smart contracts deployed on chain" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-We need to focus on this "why bother" part.
-This is a core example of a misalignment of incentives that lead to Ethereum state size growing out of control.
-
-Getting the data to state is indeed expensive but once we do...
-why clean it? There is no incentive to do so.
-So the chain was getting overwhelmed in junk.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> The Goal </strong>
-        <br /><br />
-        Design new protocol rules that shape the behavior of the users in a way that they start cleaning up the state.
-    </pba-col>
-    <pba-col>
-        <img style="width: 600px" src="./img/smart_contract_clean.drawio.svg" alt="Cleaned smart contracts on chain" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-So what can we do about it? What's the goal? We need to design new protocol rules that shape the behavior of the users in a way that they start cleaning up the state.
-Hopefully without any side effects.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> The Solution </strong>
-        <br /><br />
-        State Storage Gas Refunds
-        <br /><br />
-        Pay a hefty fee when deploying data to state, but get some of it refunded when removing it.
-    </pba-col>
-    <pba-col>
-        <img style="width: 600px" src="./img/smart_contract_burn.drawio.svg" alt="Burning a smart contract" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-One of the proposed solutions was the introduction of a Gas Refund.
-You pay a hefty fee when deploying data to state, but get some of it refunded when removing it.
-So now there is an incentive to clean up the state.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<br /><br />
-<strong>behavior Before</strong>
-
-<img style="width: 900px" src="./img/developer_musician.drawio.svg" alt="Developer becoming a musician" />
-
-Notes:
-
-So what we had originally is Bob paid for his smart contract and then simply went away to play a guitar.
-
----v
-
-## Misaligned Incentives
-
-#### _Ethereum State Storage Issue_
-
-<br /><br />
-<strong>behavior After</strong>
-
-<img style="width: 900px" src="./img/developer_musician2.drawio.svg" alt="Developer removing his contract and becoming a musician" />
-
-Notes:
-
-Afterwards Bob deploys his contract in the same way but before running of to play a guitar he removes it from the state and gets some of the gas back.
-He likes the extra money so he has an incentive to clean.
-In here we're presenting the version where he recovers the full value for educational purposes but Ethereum only refunds a portion of the gas.
-
-But wait...
-So what is the actual cost if he paid 10 and got 10 back? Anyone has any idea? Cost might not be obvious but it is an...
-
----
-
-# Opportunity Cost
-
-Notes:
-
-Opportunity Cost.
-It's a very important concept in economics and it's also crucial in blockchain.
-
----v
-
-## Opportunity Cost
-
-_"The loss of other alternatives when one option is chosen."_
-
-<img style="width: 400px" src="./img/opp_cost.drawio.svg" alt="Multiple alternatives with opportunity cost" />
-
-Notes:
-
-d
-Generally opportunity cost is the loss of other alternatives when making a choice.
-When choosing between 10 and 30$ the opportunity cost of picking 30 is 10, the other option you are forgoing.
-
----v
-
-## Opportunity Cost
-
-#### _Ethereum State Storage_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> The Real Cost </strong>
-        <br /><br />
-        Instead of having the funds locked in the storage deposit/refund scheme, Bob could have invested them somewhere else and gain some profit.
-        <br /><br />
-        <div>Just locking your funds is sort of a punishment by itself.</div><!-- .element: class="fragment" data-fragment-index="1" -->
-    </pba-col>
-    <pba-col>
-        <img style="width: 600px" src="./img/opp_cost_locking.drawio.svg" alt="Locking Funds vs Investing" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Going back to the topic of Ethereum the real cost for Bob is not the 10$ he paid for storage as he regains it later.
-The cost is in losing the opportunity of investing the money elsewhere.
-
-=fragment=
-
-Just locking your funds is sort of a punishment by itself.
-Even if you regain them later.
-This is especially true in inflationary systems, and spoiler alert that most of them.
-
-The opportunity cost is a clever mechanism that allows us to include costs without directly charging them, and we also need to be super aware so we don't accidentally punish the users by not thinking of some external opportunity costs.
-
----v
-
-## Opportunity Cost
-
-#### _Extra Examples_
-
-- Creating invalid blocks in Bitcoin never gets directly punished even if the block is rejected by the network.
-  The real cost is the opportunity cost, as the miner could have mined a valid block instead.
-- Polkadot native token DOT is inflationary (\~7.5% per year) but it can be staked to earn rewards (~15% per year).
-  Not staking DOT has an opportunity cost which incentives staking to secure the network.
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-There is a lot of awesome examples of opportunity costs in blockchain.
-For instance Creating invalid blocks in Bitcoin never gets directly punished even if the block is rejected by the network.
-The real cost is the opportunity cost, as the miner could have mined a valid block instead.
-
-=fragment=
-
-and the Polkadot native token DOT is inflationary (\~7.5% per year) but it can be staked to earn rewards (~15% per year).
-Not staking DOT has an opportunity cost which incentives staking to secure the network.
-
-And there are also many other staking and DeFi examples out there.
-
----
-
-# Externalities
-
-Notes:
-
-Now to actually appreciate what the we did in the previous section we need to talk about externalities.
-
----v
-
-## Externalities
-
-_"A consequence of an economic activity that is experienced by unrelated third parties."_
-
-Notes:
-
-An externality is a consequence of an economic activity that is experienced by some third parties.
-
-As an example, think of the pollution you emit when driving a car.
-It's a negative externality that affects all the people around you.
-Alternatively imagine planting a tree in your garden simply because you like how it looks and gives you some shade.
-The tree improves the quality of air in the neighborhood and that's a positive externality for the people around you.
-
----v
-
-## Externalities
-
-#### _Ethereum State Storage_
-
-The clogging of the chain with useless data is a negative externality that affects all the users of the chain.
-
-As protocol designers we need to be aware of such externalities and we can try and limit their effects by **pricing them in**.
-
-Notes:
-
-In the Ethereum example you could argue that the network getting clogged is the externality of the single developer not cleaning after himself.
-And it affects all the users of the chain.
-The chain is an example of a common good.
-
-As protocol engineers or system designers you need to identify those externality costs and price them in.
-
----v
-
-## Externalities
-
-#### _Ethereum State Storage_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> Negative Externality Cost </strong>
-        <br /><br />
-        In the Ethereum State Storage problem we priced in the negative externality as the opportunity cost of locking your funds.
-    </pba-col>
-    <pba-col>
-        <img style="width: 700px" src="./img/opp_cost_locking.drawio.svg" alt="Lucking Funds vs Investing" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-That's what we did with the opportunity cost in Ethereum.
-We made it so burdening the chain is actually expensive for the perpetrator.
-We aligned his incentives with the incentives of the chain.
-
----v
-
-## Externalities
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> Positive Externality </strong>
-        <br /><br />
-        Providing the voting services in the Oracle scheme can be seen as a positive externality for the network that can further use this extra information.
-        <br /><br />
-        The voters are providing a valuable service to the protocol.
-    </pba-col>
-    <pba-col>
-        <img style="width: 700px" src="./img/oracles.drawio.svg" alt="Information from the external world entering Blockchain" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-But not all externalities are negative.
-
-For example the whole oracle scheme makes it so the chain can get information from the real world.
-This is a positive externality for the network that can further use this extra information.
-
----v
-
-## Externalities
-
-#### _Oracles_
-
-The voters are providing a valuable service to the protocol.
-
-So if they submit the vote on chain through a transaction, should they pay any fees? <!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-The honest voters are providing a valuable service to the protocol.
-
-=fragment=
-
-So having that mind should they pay any transaction fees when submitting votes?
-
----v
-
-## Externalities
-
-#### _Oracles_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> Beneficial Transactions </strong>
-        <br /><br />
-        Such a transaction can be totally free.
-        <br /><br />
-        <div>But make sure it cannot be spammed!</div><!-- .element: class="fragment" data-fragment-index="1" -->
-    </pba-col>
-    <pba-col>
-        <img style="width: 300px" src="./img/free.svg" alt="Sticker with Free on it" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-And contrary to the common belief such a transaction can be totally free.
-
-=fragment=
-
-But make sure it cannot be spammed! And it's super important, because if it is free it can be trivial.
-In our oracle system we can make sure there is only ONE vote per stake.
-This way we remain safe and can make the transaction free to further incentivize participation.
-
----v
-
-## Free Transactions
-
-<pba-cols>
-    <pba-col>
-        <br />
-        There are other free transactions that are not necessarily positive externalities.
-        <br /><br />
-        <strong> Inherent Transactions </strong>
-        <ul>
-            <li> Block rewards in BTC </li>
-            <li> Any logic that needs to be executed for every block (is inherent to the block) </li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 300px" src="./img/free.svg" alt="Sticker with Free on it" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-There are other free transactions that are not necessarily positive externalities.
-For instance in Bitcoin after mining a block you get a reward.
-This is a free transaction that is not a positive externality.
-It's just inherent to the block.
-Usually any logic that needs to be executed for every block (is inherent to the block) is free.
-
----
-
-# Complete vs Partial Information Games
-
-Notes:
-
-Now let's look at something totally different.
-We will talk about a concept crucial to game theory and that is information.
-
----v
-
-## Complete vs Incomplete Information Games
-
-_Do players know everything about the game state?_
-
-_Do players **NEED** to know everything about the game state?_
-
-Notes:
-
-We'll be looking at questions like do players know everything about the game state? Do they NEED to know everything about the game state? And how does it affect the game?
-
----v
-
-## Complete vs Incomplete Information Games
-
-#### _Polkadot Approval Voting (Simplified)_
-
-<img style="width: 900px" src="./img/Approval_checkers.drawio.svg" alt="Five validators and three approval checkers among them" />
-
-Notes:
-
-To investigate this topic we'll dive deeper into Polkadot and particularly the Approval Voting subsystem.
-This is something I personally work on at Parity and you will learn a lot more about it in the later modules.
-
-What you need to understand now is that there are some special nodes called validators.
-They as they name suggests validate if the new blocks in the network are valid and correct.
-
----v
-
-## Complete vs Incomplete Information Games
-
-#### _Polkadot Approval Voting (Simplified)_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> Approval Checkers </strong>
-        <br /><br />
-        In Polkadot when new blocks are validated, not everyone does the work.
-        Only some randomly chosen validators - called <strong>Approval Checkers</strong> - are selected to validate candidate blocks.
-    </pba-col>
-    <pba-col>
-        <img style="width: 700px" src="./img/Approval_checkers.drawio.svg" alt="Five validators and three approval checkers among them" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-But in Polkadot not every validator does all the work.
-They share the work and each block is checked only by a subset of validators.
-They are called Approval Checkers.
-
----v
-
-## Complete vs Incomplete Information Games
-
-#### _Polkadot Approval Voting (Simplified)_
-
-<pba-cols>
-    <pba-col>
-        <br />
-        <strong> Attackers </strong>
-        <br /><br />
-        We assume that attackers can DDoS some but not ALL Validators.
-        <br /><br />
-        Being DDoS'ed makes them unable to vote in time.
-    </pba-col>
-    <pba-col>
-        <img style="width: 700px" src="./img/validators_attack.drawio.svg" alt="Attackers eliminated some validators" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-We also need to make some assumptions about the attackers willing to disrupt the network.
-We assume that attackers can DDoS some but not ALL Validators.
-Being DDoS'ed makes them unable to vote in time.
-
----v
-
-## Complete vs Incomplete Information Games
-
-#### _Polkadot Approval Voting_
-
-**Default Scenario**
-
-- Randomly select 3 Approval Checkers and announce them
-- Approval Checkers publish votes if they are selected
-- If all the votes received confirm the block is fine it passes
-
-<img style="width: 600px" src="./img/Approval_checkers.drawio.svg" alt="Five validators and three approval checkers among them" />
-
-Notes:
-
-A default validation scenario would go like that.
-We randomly select 3 Approval Checkers and announce them.
-Approval Checkers publish votes if they are selected.
-If all the votes received confirm the block is fine it passes.
-
-But there is a problem with it? Does anyone know what it is?
-
----v
-
-## Complete vs Incomplete Information Games
-
-#### _Polkadot Approval Voting_
-
-**Default Scenario**
-
-- Randomly select 3 Approval Checkers and announce them
-- Approval Checkers publish votes if they are selected
-- **Attackers use the information and DDoS the selected before they publish the vote** (except their insider)
-- If all the votes received confirm the block is fine it passes
-
-<img style="width: 600px" src="./img/validators_target_attack.drawio.svg" alt="Eliminated approval checkers" />
-
-Notes:
-
-If the attackers learn who the designated approval checkers are they can focus their attack.
-And only eliminate the relevant targets thus compromising the network.
-
----v
-
-## Complete vs Incomplete Information Games
-
-#### _Polkadot Approval Voting_
-
-**What was the Problem?**
-
-- Attackers learned everything about the game
-- Attackers could use this information before the validators could respond
-
-**How do we fix it?**
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Limit the information the attackers have access to so they cannot plan ahead
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-So let's ask ourselves what was the problem? The attackers learned everything about the game and could use this information before the validators could respond.
-The information is the weapon.
-
-=fragment=
-If we could somehow limit the information the game would change in our favour.
-We need to make this a game of incomplete information, where some things are hidden.
-
----v
-
-## Complete vs Incomplete Information Games
-
-#### _Polkadot Approval Voting_
-
-**Improved Scenario**
-
-- Each validator uses a VRF to generate a random number
-- Validators with a sufficiently small number will have the right to be Approval Checkers
-- Approval Checkers reveal themselves by showing their low numbers and publish a vote at the same time <!-- .element: class="fragment" data-fragment-index="2" -->
-- If all the votes received confirm the block is fine it passes <!-- .element: class="fragment" data-fragment-index="2" -->
-
-<br />
-
-Notes:
-
-- Let's imagine this new improved scenario.
-  Each validator uses a VRF to generate a random number.
-- There is some threshold and validators with a sufficiently small number will have the right to be Approval Checkers.
-
-=fragment=
-
-- Approval Checkers reveal themselves by showing their low numbers (with a vrf proof attached) and publish a vote at the same time.
-  If all the votes received confirm the block is fine it passes.
-
-This method has this nice property that attackers don't learn who the approval checkers are until they reveal themselves.
-So they cannot plan ahead.
-
----v
-
-## Complete vs Incomplete Information Games
-
-#### _Polkadot Approval Voting_
-
-**What can the Attackers do?**
-
-- They no longer know who the Approval Checkers are so they have to guess
-- If they don't guess correctly they get heavily slashed
-
-<img style="width: 700px" src="./img/validators_random_attack.drawio.svg" alt="Some validators are eliminated" />
-
-Notes:
-
-So what can the attackers do? If they can no longer target DDoS they only can attack at random.
-This vastly reduces their chances of success and makes thm vulnerable to punishment if they fail.
-
-This is pretty much the method used in Polkadot and it's called a VRF based random assignment.
-It's a game of incomplete information.
-
----v
-
-## Complete vs Incomplete Information Games
-
-#### _Extra Examples_
-
-- BABE is a Polkadot mechanism for selecting new block producers (further covered in Polkadot module).
-  It also uses a similar VRF scheme to generate random assignments
-
-Notes:
-
-Some other notable examples you will learn about in later modules are connected to BABE the Polkadot mechanism for selecting new block producers.
-It also uses a similar VRF scheme to generate random assignments.
-
----
-
-# Shifting Assumptions
-
-Notes:
-
-By now you might have noticed a pattern that usually we have a list of assumptions.
-
----v
-
-## Shifting Assumptions
-
-<pba-cols>
-    <pba-col>
-        Every game has some assumptions that need to be made before reasoning about them.
-        <ul>
-            <li>Number of players</li>
-            <li>Available actions</li>
-            <li>Access to information</li>
-            <li>etc</li>
-        </ul>
-    </pba-col>
-    <pba-col>
-        <img style="width: 200px" src="./img/assumptions.drawio.svg" alt="Board with assumptions" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Some of the assumptions are connected to the number of players or maybe the access to information.
-And they are usually pretty stable.
-
----v
-
-## Shifting Assumptions
-
-<pba-cols>
-    <pba-col>
-        If any of the assumptions change the game changes as well.
-        Old incentives that were previously sensible may now motivate a vastly different behavior.
-    </pba-col>
-    <pba-col>
-        <img style="width: 300px" src="./img/assumptions_change.drawio.svg" alt="Some of the assumptions on the board change" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-What happens when for some reason the assumptions evolve and change?
-The game changes as well.
-Old incentives that were previously sensible may now motivate a vastly different behavior.
-
----v
-
-## Shifting Assumptions
-
-#### _Restaking_
-
-<pba-cols>
-    <pba-col>
-        Restaking through EigenLayer incentives Ethereum stakers to stake the same funds for multiple apps at the same time.
-        <br /><br />
-        The incentive game will be vastly different and the capital will effectively be leveraged (double risk and double rewards).
-    </pba-col>
-    <pba-col>
-        <img style="width: 600px" src="./img/eigen.drawio.png" alt="EigenLayer Logo" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-A super good example of that is what is very recently happening in Ethereum.
-And I mean literally this month.
-There is a new layer 2 protocol called EigenLayer that allows stakers to stake the same funds for multiple apps at the same time.
-This is called restaking.
-
-This is not something natively available in Ethereum and it wasn't taken into consideration when slashes/rewards were designed.
-
----v
-
-## Shifting Assumptions
-
-#### _Restaking_
-
-<pba-cols>
-    <pba-col>
-        <strong> Consequences </strong>
-        <br /><br />
-        Restaking consequences are still not fully understood and the research is ongoing.
-        <br /><br />
-        Speaker Notes ("S") for further reading.
-    </pba-col>
-    <pba-col>
-        <img style="width: 600px" src="./img/eigen.drawio.png" alt="EigenLayer Logo" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-The consequences of restaking are still not fully understood and the research is ongoing.
-I encourage you to read the speaker notes for further reading.
-The whole field of blockchain incentivization and protocol design is still developing so there are many unknowns but overall I hope all the methods shown today help you in making more informed decisions later down the line.
-Thats it...
-
-- Podcast: <https://www.youtube.com/watch?v=aP9f_1v9Ulc>
-- Whitepaper: <https://2039955362-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FPy2Kmkwju3mPSo9jrKKt%2Fuploads%2F9tExk4U2OdiRKGEsUWqW%2FEigenLayer_WhitePaper.pdf?alt=media&token=c20ac4bd-badd-4826-9fb6-492923741c9e>
-
----
-
-## Summary
-
-- Markets - Fee Markets
-- Nash Equilibrium - BTC Mining
-- Schelling Point - Oracles
-- Incentivization - Oracles
-- Opportunity cost - Ethereum State Storage Refunds
-- Externalities - Ethereum State Storage and Oracles
-- Complete vs Incomplete Information Games - Polkadot Approval Voting
-- Assumptions - Restaking
-
-Notes:
-
-So to summarize we talked about:
-
----
-
-# Thanks everyone!
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-
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-<center>
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-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
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-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Consensus Finality
-description: Finality providing methods and mechanisms for blockchains
-duration: 45min
----
-
-# Consensus: Finality
-
----
-
-## Consensus is...
-
-...a decision making process that strives to achieve acceptance of a decision by all participants.
-
-Notes:
-
-If we have external factors like trust relationships or Social hierarchy it can be quite easy.
-
-Trust example: If everyone trusts each other, then any one person can propose an outcome, and all the others will trust that it is in the community's best interest.
-
-Social Hierarchy example: If a community has an executive (President, Queen, CEO), the executive can propose her preference and everyone will accept it based on the external mechanism that keeps her as the executive.
-
-But these conditions are not interesting, and are often not realistic.
-It gets interesting when we don't make these simplifying assumption.
-
----v
-
-## Five Aspects of Blockchain Consensus
-
-<pba-flex center>
-
-- State machine validity
-- Arbitrary / Political validity
-- Authorship throttling
-- Fork choice heuristic
-- Finality
-
-</pba-flex>
-
----v
-
-## Adversarial Conditions
-
-- The participants want to agree on _something_
-- They don't trust each other
-- Some could be faulty, or make mistakes
-- Some could be straight up malicious (aka Byzantine)
-
----
-
-# One Shot Consensus
-
-A single decision to make.
-
-Once it is made, we are done.
-
----v
-
-## Desired Properties
-
-All honest participants...
-
-- **Termination** - Eventually reach some decision
-- **Agreement** - Reach the same decision
-- **Integrity** - Reach at most one decision, which was proposed by at least one participant.
-
----v
-
-## Also Validity
-
-If all participants unanimously propose the same decision, all honest participants reach that decision.
-
-Notes:
-
-Another desireable property that is sometimes too obvious to say.
-
----
-
-## Example: Where to go for dinner
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="width: 20em" src="./img/south-park-consensus.png" />
-
-</pba-col>
-
-<pba-col>
-
-- Termination - Stan, Kyle, and Kenny will each eventually decide where to eat.
-- Agreement - Stan, Kyle, and Kenny will each decide to eat at the same place.
-- Integrity - Stan, Kyle, and Kenny will eat at either Whistlin' Willies or Casa Bonita.
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Stan, Kyle, Kenny, and Cartman are trying to decide where to have dinner.
-Stan, Kyle, and Kenny want to have something yummy and spend time together.
-Cartman is secretly pursuing his own goals and doesn't care whether dinner is yummy.
-In fact he secretly hopes they won't decide at all so he can go home and eat KFC with his mom.
-
-Stan and Kyle both propose Whistlin' Willie's for dinner.
-Kenny and Cartman propose Casa Bonita.
-
-In the end Kenny may not agree that Whistlin' Willie's is the best option for dinner, but he will agree that it is the legitimate group decision.
-
-Image source: <https://southparkstudios.mtvnimages.com/images/shows/south-park/clip-thumbnails/season-14/1402/south-park-s14e02c03-ill-show-them-f-obscene-16x9.jpg>
-
----v
-
-## Mistakes vs Malice
-
-**Crash Tolerance** - A system can keep operating normally when some actors crash or go offline.
-
-**Byzantine Fault Tolerance** - A system can keep operating normally when some actors are intentionally malicious.
-Byzantine actors may:
-
-- Crash - Or pretend to have crashed - Byzantine faults are a superset of crash faults
-- Lie - Sending false information to peers
-- Equivocate - Send inconsistent information to different peers
-
-Notes:
-
-These examples and many others are _instances_ of the Byzantine Generals Problem
-
----v
-
-## Mistake or Malice?
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="width: 600px" src="./img/pitot-ice-scaled.webp" />
-
-</pba-col>
-
-<pba-col>
-
-- Consider an Airplane flight computer.
-- The pilot _must_ know the airspeed at all times.
-- Airspeed sensors can fail.
-- Sensors can be buggy.
-- Are these malicious?
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Consider an Airplane flight computer.
-It is critical that the pilot (human or automated) knows the aircraft's airspeed at all times.
-Airspeed sensors can fail due to extreme temperatures, icing, solar radiation, and other reasons.
-For this reason, there are redundant sensors, and they run a consensus protocol.
-
-Imagine that one of the sensors has an overflow _bug_ such that when the airspeed exceeds a certain threshold, maybe `u8::max_value()`, it actually reports a much lower speed.
-
-Are these crash faults or byzantine?
-
-In a blockchain system, bugs in the code may cause nodes whose operators are intending to be honest, to deviate from the protocol anyway.
-This is why client diversity is important.
-
-Image source: <https://thepointsguy.global.ssl.fastly.net/uk/originals/2020/12/pitot-ice-scaled.jpg>
-
----
-
-## Byzantine Generals Problem
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="width: 700px" src="./img/byzantine-generals.png" />
-
-</pba-col>
-
-<pba-col>
-
-- Divisions plan to attack
-- Must make coordinated attack to succeed
-- Some generals might be traitors and behave maliciously
-
-</pba-col>
-</pba-cols>
-
-[Cornell Lecture Slides](https://www.cs.cornell.edu/courses/cs6410/2018fa/slides/18-distributed-systems-byzantine-agreement.pdf)
-
-Notes:
-
-Several divisions of the Byzantine army are camped around an enemy city.
-They plan to attack the city, but have not yet decided when to attack.
-If the attack is coordinated, they will probably be successful, but if it is uncoordinated, they will probably be defeated.
-What do our three properties mean in this scenario?
-
-- Termination - every honest general will eventually decide when to attack
-- Agreement - honest general will all agree to attack ta the same time
-- Integrity - the attack time will have been proposed by at least one honest general
-
-Leslie Lamport proposed this problem in the form of a story as a typical representative of the distributed consensus problem.
-
-This is a big moment for us, so let's stop and savor it.
-Two days ago Lauren kicked us off by talking about human coordination.
-How it can achieve long railroads and the great pyramids and sports teams and dancing, and even this academic program.
-Since then we've looked through so many layers of abstraction (contracts, smart contracts, state machines, dags) and so many technical implementation details (P2P networking, platform agnostic bytecodes, blockchain headers, merkle proofs).
-We've taken a huge class of problems - human coordination problems - and distilled them down to their absolute essence.
-Human coordinate at global scale reduced to this one cute, carefully stated problem.
-
----v
-
-## Byzantine Generals: Solved
-
-<img height="600px" src="./img/pbft-cover.png" />
-
-_Miguel Castro and Barbara Liskov, 1999_
-
-Notes:
-
-_Image = Cover page: Practical Byzantine Fault Tolerance_
-
-And great news.
-The problem is solved!
-At least under some conditions.
-And also great news.
-We have a pretty good understanding of under what circumstances it is solvable.
-
-Before I can tell you exactly how and where it can be solved, we have to understand networks a little bit.
-
----
-
-# History Lesson
-
----
-
-## Synchrony
-
-A network is one of:
-
-- **Synchronous** - When sent, a message is received immediately by all.
-- **Asynchronous** - When a message is sent it may be received after some delay, or not at all.
-  The sender doe not know whether it is received.
-  Messages may be received in different orders by different parties.
-- **Partially Synchronous** - When a message is sent, it may be received after some delay up to a maximum delay, $T$.
-  It may not be dropped entirely.
-  Messages may be received in different orders by different parties.
-
-Roughly analogous to real-time (async) vs. turn-based (sync) games.
-
----v
-
-## Sync or Async?
-
-Classify each of these:
-
-<pba-flex center>
-
-- Telephone call
-- Mail communication
-- Text message
-- Jitsi video call
-- Element chat
-
-</pba-flex>
-
-Notes:
-
-- Telephone call is sync.
-  You say something and wait for the other party to reply
-- Mail is async.
-  You send a letter, then go do other stuff for several days
-- Jitsi video call is basically sync just like the phone call.
-- The others can be either.
-  Sometimes you text back and forth quickly and wait for replies.
-  Other times you send and come back later like mail.
-
----
-
-## Determinism
-
-A system is one of:
-
-- **Deterministic** - The same inputs give the same outputs every time.
-- **Probabilistic** - The same inputs may not give the same outputs.<br />
-  $~~~~~~~~~~~~~~~~~~~~~~~~~$ Requires a source of entropy. eg coin flipping. <!-- $~~~$ is a hack to put in white space chars -->
-
----
-
-## FLP Impossibility
-
-<img style="padding: 0 200px 0 0" src="./img/FLP-impossible.png" />
-
-[Excellent Podcast with Ethan Buchman](https://open.spotify.com/episode/7z7qnOrLTVGa5T0s0MquJd)
-
-Notes:
-
-Once it was shown that deterministic consensus is impossible in an async network, the field split into two major parts.
-Either you:
-
-- Assume the network is (at least partially) synchronous
-- Introduce non-determinism
-
-One interesting thing about Nakamoto pow consensus is that it does _both_.
-
-- Nondeterminism because you don't know who will solve the pow first
-- Partial synchrony because it only works if the time to download and execute the block is much less than the time to solve the PoW
-
----
-
-## Ongoing Consensus
-
-We want to continue agreeing on<br />an every-growing history of events
-
-Notes:
-
-Blockchains are intended to keep processing and finalizing transactions forever.
-This is more like deciding where to go to dinner every night over and over.
-
----v
-
-## Desireable Properties
-
-<pba-flex center>
-
-- **Safety** aka **Finality** - Nothing bad will happen
-- **Liveness** - Something good will eventually happen
-
-</pba-flex>
-
-Notes:
-
-Traditional literature typically uses the term safety.
-Blockchain folks typically talk about finality.
-They basically mean the same thing.
-
-Finality can be proved to entities that are not involved in consensus.
-
-We spoke about liveness previously in the authoring system.
-There it means that more blocks will be authored, more blockspace will be created and put up for sale.
-Here, in finality, it means that more blocks will be finalized.
-Of course liveness in the finality depends on liveness in the authoring.
-
-These two decisions can be entirely orthogonal to one another, or wrapped up together.
-
----v
-
-## Liveness vs Termination
-
-Earlier I described Termination as desireable,<br />now I'm saying Liveness is desireable.
-
-Are these at odds with each other?
-
-Notes:
-
-Termination guarantees that, for a given decision, each honest participant will eventually decide something.
-This concept is relevant when there is a single decision to be made.
-In the blockchain context, it guarantees that we will eventually know which block is final at height n.
-
-Liveness guarantees that a system that is intended to continue making progress, will indeed eventually make progress.
-In the context of the blockchain, liveness means that once we've decided what block is final at height n, we will eventually go on to decide what block is final at height n + 1.
-
----
-
-## Finality in Nakamoto Consensus
-
-<pba-flex center>
-
-- Longest chain rule
-- Longest chain is "best"... for now
-- Someone could always start mining a chain<br />and,with low but non-zero probability,<br /> end up with it longer.
-- There could _already_ be a longer chain<br />that you just haven't heard of.
-
-<pba-flex>
-
-The finality is only probabilistic.<br />
-Nakamoto consensus in only safe in a synchronous network.
-
-Notes:
-
-This is to say that Nakamoto consensus is NOT safe on the real asynchronous internet.
-In practice, as long as
-blocks can be downloaded and executed much more quickly than the target block time, it is usually good enough.
-
-- Longest could also mean most accumulated work
-
----
-
-## Deterministic Finality
-
-<pba-flex center>
-
-- Based on traditional methods (BFT)
-- Requires an honest-majority finite authority set
-
-</pba-flex>
-
-<!-- two flexes needed so the next bullet points don't show too early, margin hack... TODO -->
-
-<pba-flex center style="margin-left: 48px">
-
-- Consensus protocol that assumes honest majority
-- Economic game that keeps them honest
-
-</pba-flex>
-<!-- .element: class="fragment"-->
-
-Notes:
-
-If you want deterministic finality, it basically means employing BFT agreement protocols that we talked about in the history lesson.
-This means we need a finite authority set with an honest majority.
-And that means we need incentives to keep them honest.
-
----v
-
-## Incentives: Game Theory!
-
-Abstractly: You behave honestly<br />when the utility of doing so exceeds the cost.
-
-Incentive designers may potentially:
-
-<pba-flex center>
-
-- Reward honest behavior
-- Punish (aka slash) dishonest behavior
-
-</pba-flex>
-
-Notes:
-
-Many systems use both of these, but doing so is not strictly necessary.
-Even without slashes, the opportunity cost of staking and the missed rewards from authoring invalid blocks may be sufficient.
-
-It is often the case that blockchain systems give rewards in the authorship and punishments in the finality.
-There is no fundamental reason for this; it is just a little more straightforward to implement.
-
----v
-
-## What is potentially punishable?
-
-<pba-flex center>
-
-- Authoring when you aren't supposed to
-- Failing to author when you are supposed to
-- Casting finality votes for conflicting blocks
-- Casting a finality vote for a block (or chain)<br /> that includes an invalid state transition.
-
-> How severe are each of these offenses?<br />
-> Do they all warrant a slash?<br />
-> A full slash?
-
-Notes:
-
-PoW has inherent punishment through wasted energy.
-BFT based system's don't.
-
-Instead, aspiring participants will typically lock up a security deposit which can be slashed in part or in whole.
-
----v
-
-### Concrete Punishment Example
-
-Let's say a slash is 100 units, and the reporter gets 10%.<br />I plan to attack.
-
-If my attack is successful,<br />I expect to gain roughly 200 units worth of utility.
-
-I ask another authority to cooperate with me:<br />"I'll pay you 20 units to _not_ rat me out for my attack".
-
-> How would you respond?
-
-Notes:
-
-"I don't believe you can carry out the attack because _someone else_ will report you and take the 10 units, leaving me with 0."
-
----
-
-## Case Study: Tendermint
-
-<pba-flex center>
-
-- Authorship is like Aura - simple round robin
-- Naive but **simple** BFT implementation
-- If the block has enough votes<br />by the end of the slot, it is finalized.<br />
-  Otherwise, it is rejected via timeout.
-- "Instant finality"
-- Forkless - Forks are disallowed<br />because blocks can only be authored<br />on finalized parents.
-
-</pba-flex>
-
-Notes:
-
-Tendermint assumes a partially synchronous network, like all the BFT based systems - That is to say that messages may not arrive immediately, but will arrive within a finite time bound.
-In practice this means it is slot-based just like so many of the authoring schemes.
-
-Tendermint is often touted as "instant finality".
-It is instant in the sense that finality is tied to authorship.
-In practice this means that authorship, which is inherently O(n), is slowed down to stay in sync with finality which is O(n^2).
-They sacrifice liveness to guarantee absolute safety at all times.
-
----v
-
-## Tendermint Deep Dive
-
-<pba-flex center>
-<ol>
-<li class="fragment">Wait for a block (or author one if it is your turn)</li>
-<li class="fragment">Prevote
-  <ul>
-    <li>If the block is valid, Prevote for it.</li>
-    <li>If the block is invalid, Prevote `Nil`</li>
-  </ul>
-</li>
-<li class="fragment">Precommit
-  <ul>
-    <li>Wait for 2/3 prevotes then Precommit</li>
-    <li>If you don't get 2/3 prevotes, Precommit `Nil`</li>
-  </ul>
-</li>
-<li class="fragment">Complete
-  <ul>
-  <li>Wait for 2/3 Precommits them finalize</li>
-  <li>If you don't get it, throw the block away</li>
-  </ul>
-</li>
-</ol>
-
-[Very useful blog post](https://medium.com/softblocks/explaining-how-tendermint-consensus-works-433066cbc465) <!-- .element: class="fragment" -->
-
-</pba-flex>
-
----
-
-## Hybrid Consensus
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="width: 900px;" src="./img/grandpa-abstract.png" />
-
-</pba-col>
-<pba-col>
-<pba-flex center style="font-size: 0.7em; margin-left:-50px">
-
-- Separates block production from finality.
-- Block production stays live even if finality lags.
-- Allows lower overhead in the finality layer.
-- Used in Substrate.
-
-</pba-flex>
-</pba-col>
-</pba-cols>
-
----v
-
-## What About Re-Orgs
-
-<img style="width: 500px; margin-right: 150px;" src="./img/reorgs-1.svg" />
-<br />
-<img style="width: 650px;" src="./img/reorgs-2.svg" />
-
-Notes:
-
-Previously we talked about how a node's view of the best block can change, and that is called a re-org.
-
----v
-
-## Modified Fork Choice Rule
-
-<img style="width: 500px; margin-right: 150px;" src="./img/reorgs-finality-1.svg" />
-<br />
-<img style="width: 650px" src="./img/reorgs-finality-2.svg" />
-
-Only extend best finalized chain
-Notes:
-
-Once you have a finality gadget installed, you have to make sure you only ever author on top of finalized blocks.
-Even if another chain is longer.
-
----
-
-## Case Study: Grandpa
-
-<pba-flex center>
-
-- Deterministic finality _only_
-- Requires an external block authoring scheme<br /> with its own liveness proof.
-- Kind of like Tendermint but better.
-- Finalizes chains, not blocks.
-
-</pba-flex>
-
----v
-
-## Vote on Chains, not Blocks
-
-<img style="width: 1000px" src="./img/validators-vote-on-chain.png"/>
-
-Notes:
-
-BFT finality with $n$ authorities is in $O(n^2)$.
-Tendermint does this at **every block**.
-This bounds the size of the authority set.
-
-With separated, we treat each vote as a vote not only for one block,but also for each ancestor block.
-This significantly reduces the number of total messages sent.
-Allows the chain to stay live even when many validators are offline
-
----
-
-## A GRANDPA Round
-
-Each validator **broadcasts** a **prevote** for the **highest block** that it thinks **should** be **finalized**
-
-- For **honest** validators, this block **must include** the chain that was previously finalized
-- This **new chain** could be **several blocks** longer than the **last finalized** chain
-
-A **validator** that is designated as the **primary** broadcasts the highest block that it thinks could be final from the previous round
-
----
-
-## A GRANDPA Round
-
-<img style="width: 400px" src="./img/grandpa-round-1.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round
-
-<img style="width: 400px" src="./img/grandpa-round-2.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round
-
-Each validator **computes** the **highest block** that can be **finalized based** on the set of **prevotes**
-
-- i.e. we find the **common ancestor** of all votes that has **support** from **more** than $\frac{2}{3}N + 1$ validators
-- We refer to this block as the **prevote GHOST**
-
----
-
-## A GRANDPA Round
-
-<img style="width: 400px" src="./img/grandpa-round-3.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round
-
-We define the round **estimate** as the **highest ancestor** of the **prevote GHOST** for which it is **still possible** to **precommit**
-
-- i.e. when **no precommit** votes have been **sent** out yet, then:
-
-`estimate == prevote GHOST`
-
----
-
-## A GRANDPA Round
-
-<img style="width: 400px" src="./img/grandpa-round-4.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round
-
-If the **estimate** extends the **last finalized** chain, then each validator will cast a **precommit** for that chain.
-
-Each validator **waits** to receive **enough precommits** to be able to finalize
-
-- We again find the **common ancestor** of the **estimate** which has **threshold precommits**
-- We declare that **block** as **finalized**
-
----
-
-## A GRANDPA Round
-
-<img style="width: 400px" src="./img/grandpa-round-5.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round
-
-<img style="width: 400px" src="./img/grandpa-round-6.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round
-
-The **round** is deemed **completable**:
-
-- if the **estimate** is **lower** than the **prevote GHOST**
-- or if it's **impossible** to have a **supermajority** on any **block higher** than the current **estimate**
-
-Validators **start** a **new round** after it becomes **completable**.
-
----
-
-## A GRANDPA Round
-
-<img style="width: 400px" src="./img/grandpa-round-6.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round
-
-<img style="width: 400px" src="./img/grandpa-round-7.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round
-
-<img style="width: 400px" src="./img/grandpa-round-8.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round (Alt)
-
-<img style="width: 400px" src="./img/grandpa-round-6.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round (Alt)
-
-<img style="width: 400px" src="./img/grandpa-round-7-alternative.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round (Alt)
-
-<img style="width: 400px" src="./img/grandpa-round-8-alternative.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## A GRANDPA Round (Alt)
-
-<img style="width: 400px" src="./img/grandpa-round-9-alternative.png"/>
-
-Notes:
-
-- 7 = # Validators
-- 5 = # Threshold
-
----
-
-## Summary
-
-<pba-flex center>
-
-- Networks can be {Synchronous, Asynchronous}
-- Consensus systems can be {Deterministic, Probabilistic}
-- Consensus systems can be {Open participation, Finite participation}
-- There is always an assumption that at least {1/2, 2/3} participants are honest
-- In decentralized systems, we use Economics and Game Theory<br />to incentivize honest execution of the consensus protocol
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Game Time
-
-> I want to play a game...<br />a board game!
diff --git a/content/blockchain-contracts/forks/page.md b/content/blockchain-contracts/forks/page.md
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-# Blockchain Forks
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/forks/slides.md b/content/blockchain-contracts/forks/slides.md
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----
-title: Blockchain Forks
-description: Detailed Classification for Blockchain Forks Types
-duration: 60 minutes
----
-
-# Blockchain Forks
-
----
-
-# Landscape
-
----v
-
-## Landscape
-
-#### Ideal World
-
-In an ideal world blockchains would look like this:
-<br /><br />
-
-<img style="width: 800px" src="./img/no_fork.drawio.svg" />
-
----v
-
-## Landscape
-
-#### Real World
-
-Things don't always go according to plan:
-
-<br />
-
-<img style="width: 800px" src="./img/fork_small.drawio.svg" />
-
----v
-
-## Landscape
-
-#### Chaotic Real World
-
-And sometimes they get extra messy:
-
-<br />
-
-<img style="width: 800px" src="./img/fork_chaos.drawio.svg" />
-
----
-
-# What's the goal?
-
----v
-
-## What's the goal?
-
-#### _Fork Identification_
-
-<img style="width: 500px" src="./img/forks_and_boxes.drawio.svg" />
-
-Notes:
-
-There are different forks, they can have different shapes and reasons.
-We'll try to identify some examples.
-
----v
-
-## What's the goal?
-
-#### _Fork Categorization_
-
-<img style="width: 800px" src="./img/forks_in_boxes.drawio.svg" />
-
-Notes:
-
-Why?
-Forks in the same category will exhibit similar behavior and will require similar handling.
-Then when making changes we can easily figure out to which box the change belongs and react accordingly.
-
-It's also worth pointing out that the whole web3 space is still very young and we are still figuring out how to name things appropriately.
-There is definitely still a lot of confusion about the fork types and the convention I will be using here today is based on the naming proposed by the MIT Digital Currencies Initiative.
-It will cover most of the common terms and hopefully will not be as self-contradictory as some of the terms used within the community.
-
----v
-
-## What's the goal?
-
-#### _Fork Confusion_
-
-<br />
-BABE (sometimes):
-<br /><br />
-<img style="width: 800px" src="./img/transitory_fork_unresolved.drawio.svg" />
-
-Notes:
-
-To demonstrate the confusion think of BABE.
-BABE can have multiple block authors create blocks at the same time and then the chain forks.
-What type of a fork is it?
-Some of you might have heard about soft forks and hard forks, any idea which one it is?
-
----
-
-# Fork Categorization
-
----v
-
-## Fork Categorization
-
-#### _Forks Family Tree_
-
-<br />
-<img style="width: 800px" src="./img/fork_family.drawio.svg" />
-
-Notes:
-
-This is the core categorization of forks we'll be waking you through today.
-You don't need to understand the whole tree as we'll be going step by step.
-For now let's actually go back to the example from BABE and let's place it on the map.
-
----
-
-# Transitory Forks
-
-Notes:
-
-For that we'll talk about transitory forks.
-
----v
-
-## Fork Categorization
-
-#### _Transitory Forks_
-
-<br />
-<img style="width: 800px" src="./img/fork_family_transitory.drawio.svg" />
-
-Notes:
-
-One of the simplest forks that is rarely talked about so the name might not sound familiar.
-They are often also called short-lived forks or temporary forks.
-
----v
-
-## Transitory Forks
-
-<br />
-<img style="width: 800px" src="./img/transitory_forks.drawio.svg" />
-
-Notes:
-
-They usually arise from the fundamental protocol uncertainty or networking lag, but luckily they are usually resolved quickly by the network itself.
-For instance in BABE even if all the nodes are running the same software those forks can still happen when two nodes roll low enough numbers.
-In Bitcoin two miners might mine a block at roughly the same time.
-Over time one of the blocks wins due to some heuristics like the longest chain.
-Those forks are generally not a problem and only live on short timescales.
-
----
-
-# Consensus Forks
-
-Notes:
-
-So now let's move to something more interesting.
-Consensus forks.
-
----v
-
-## Fork Categorization
-
-#### _Consensus Forks_
-
-<br />
-<img style="width: 800px" src="./img/fork_family_consensus.drawio.svg" />
-
-Notes:
-
-Usually when you hear about forks you hear about those guys.
-They are the other branch and they also come in many flavours we'll discuss in a minute.
-
----v
-
-# Consensus Forks
-
-## _Validity Set_
-
-Notes:
-
-But first before we understand the intricacies of consensus forks we need to understand the concept of the validity set and how it connects to the protocol.
-
----v
-
-## Consensus Forks
-
-#### _Validity Set_
-
-<br />
-<img style="width: 800px" src="./img/BTC_block.drawio.svg" />
-
-Notes:
-
-It's best to see it through an example so let's look at the BTC block.
-You don't need to understand all the fields that are in it but for now take a look at the blocksize field as well as the block header itself.
-
-#### _Validity Set_
-
-<br />
-<img style="width: 300px" src="./img/BTC_header.drawio.svg" />
-
----v
-
-## Consensus Forks
-
-#### _Validity Set_
-
-<br />
-<img style="width: 500px" src="./img/BTC_header_constraints.drawio.svg" />
-
----v
-
-## Consensus Forks
-
-#### _Validity Set_
-
-<br />
-<img style="width: 500px" src="./img/validity_set.drawio.svg" />
-
-Notes:
-
-So the validity set is a set of all hypothetical blocks that could be produced by the protocol.
-It's a set of all valid blocks under those rules.
-
-So if there is a block D that for instance is too big, it's blocksize is bigger than the allowed one...
-
----v
-
-## Consensus Forks
-
-#### _Validity Set_
-
-<br />
-<img style="width: 500px" src="./img/universal_set.drawio.svg" />
-
-Notes:
-
-Then it falls out of the validity set into the universal set of all possible data blobs.
-Only some of those data blobs are valid blocks.
-
----v
-
-## Consensus Forks
-
-#### _Validity Set_
-
-<br />
-<img style="width: 500px" src="./img/validity_set_old.drawio.svg" />
-
-Notes:
-
-Let's actually look at an example.
-Imagine this is Bitcoins validity set and here we see a few blocks from it.
-The numbers at the top are initial few digits from the hashes representing those blocks.
-
-Imagine all the Bitcoin nodes suddenly decide they really dislike when the first hash digit is odd.
-They only like when it's even so they band together and change the protocol to only accept hashes with an even first digit.
-
----v
-
-## Consensus Forks
-
-#### _Validity Set_
-
-<br />
-<img style="width: 500px" src="./img/validity_set_new.drawio.svg" />
-
-Notes:
-
-This change in the protocol would reduce the validity set.
-It would be more constrained then before.
-Some of the previously valid blocks would no longer be valid under the new rules.
-What happens in that case?
-Can we predict that?
-
----v
-
-## Consensus Forks
-
-#### _Validity Set_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 500px" src="./img/validity_set_new.drawio.svg" />
-    </pba-col>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_soft.drawio.svg" />
-		<div style="font-size: 50px;">N ⊆ O</div>
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-To generally represent the same idea we'll be using the simpler representation on the right.
-Where the new set N is contained within the old set O.
-The fancy notion at the bottom says the same N is contained in O.
-
----
-
-# Soft Forks
-
-To understand the example from a second ago we'll dive into soft forks.
-
----v
-
-## Fork Categorization
-
-#### _Soft Forks_
-
-<br />
-<img style="width: 800px" src="./img/fork_family_soft.drawio.svg" />
-
-Notes:
-
-Firstly soft forks are a type of a consensus fork and they are results of a change in the protocol and thus the validity set.
-
----v
-
-## Fork Categorization
-
-#### _Soft Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_soft.drawio.svg" />
-		<div style="font-size: 50px;">N ⊆ O</div>
-    </pba-col>
-    <pba-col>
-		<ul>
-			<li>Backwards Compatible</li>
-			<li>By making the consensus rules more restrictive the set of valid blocks gets smaller.</li>
-			<li>Not every (and often none) of the blocks produced under old rules will get accepted by new nodes.</li>
-		</ul>
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-So based on the venn diagram we have on the side we can see that the new consensus rules are more restrictive as the validity set shrinks.
-
-New nodes produce blocks that are always accepted by old nodes.
-Old nodes generally don't produce blocks accepted by the new nodes.
-
-Before we jump into demonstration is decreasing or increasing blocksize a soft fork?
-
----v
-
-## Fork Categorization
-
-#### _Soft Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_soft.drawio.svg" />
-		<div style="font-size: 50px;">N ⊆ O</div>
-    </pba-col>
-    <pba-col>
-		<strong>Examples:</strong>
-		<br /><br />
-		<ul>
-			<li>Decreasing blocksize</li>
-			<li>Accepting only even/odd hashes</li>
-			<li>Disallowing some transaction types</li>
-		</ul>
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Decreasing the block size restricts how many different blocks can be constructed so it makes the set smaller.
-It is a soft fork.
-The example we had a moment ago with the even hashes is also a soft fork as it adds another constraint on the previous protocol rules restricting them even further.
-Another good example would be banning some transaction types from use.
-
-Now let's take a look at how forks work in practice and how they vary based on the hash power or staking power in favour of the protocol change.
-
----v
-
-## Fork Categorization
-
-#### _Soft Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_soft.drawio.svg" />
-		<div style="font-size: 50px;">N ⊆ O</div>
-    </pba-col>
-    <pba-col>
-		<img style="width: 800px" src="./img/soft_forks_s50.drawio.svg" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-So in this scenario we'll be looking at what happens if nodes with less than 50% hash power or stake want to soft fork.
-Remember that soft forking is simply making the consensus stricter.
-
-In that case the blocks produced by new nodes are marked with N and they are accepted by the old chain but the old chain mines faster so they don't care about the new nodes.
-Blocks produced by old nodes are NOT accepted by the new nodes so the longest chain for new nodes is the short chain with only the N blocks.
-This is effectively a permanent fork.
-
----v
-
-## Fork Categorization
-
-#### _Soft Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_soft.drawio.svg" />
-		<div style="font-size: 50px;">N ⊆ O</div>
-    </pba-col>
-    <pba-col>
-		<img style="width: 800px" src="./img/soft_forks_g50.drawio.svg" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-In the similar example when the new nodes control more than 50% power the situation changes drastically.
-The new nodes mine faster and are the longest chain.
-But remember that old nodes accept the new blocks so if they new nodes mine faster the old nodes blocks get constantly reorged out.
-They are forced to update the software if they want their blocks to get accepted at all otherwise they loose all the rewards.
-
----
-
-# Hidden Forks
-
-Notes:
-
-Now let's take a look at something a bit less known.
-Hidden forks.
-
----v
-
-## Fork Categorization
-
-#### _Hidden Forks_
-
-<br />
-<img style="width: 800px" src="./img/fork_family_hidden.drawio.svg" />
-
-Notes:
-
-An edge case of soft forks.
-
----v
-
-## Fork Categorization
-
-#### _Hidden Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_hidden.drawio.svg" />
-		<div style="font-size: 50px;">N ⊆ O</div>
-    </pba-col>
-    <pba-col>
-		<ul>
-			<li>Conflict-less</li>
-			<li>The old, now excluded blocks were allowed but never used in practice.</li>
-			<li>New nodes are theoretically stricter but practically accept all old blocks.</li>
-			<li>Old nodes accept new blocks.</li>
-		</ul>
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-So the venn diagram is exactly the same as in the normal soft fork case.
-But imagine that the the orange crescent, this is the part we're excluding from the old protocol when shifting to the new one... was never actually used.
-So for instance the block had an empty field that could have some arbitrary data inside, but everyone left it empty and never checked what was inside.
-The new protocol puts something meaningful in the empty field but doesn't require it.
-Because old nodes never used this field pretty much all old blocks will be accepted under the new rules.
-
-TL;DR the stuff we removed from the validity set wasn't even used despite being technically valid.
-
----v
-
-## Fork Categorization
-
-#### _Hidden Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_hidden.drawio.svg" />
-		<div style="font-size: 50px;">N ⊆ O</div>
-    </pba-col>
-    <pba-col>
-		<strong>Examples:</strong>
-		<br /><br />
-		<ul>
-			<li>Assigning non-conflicting uses to empty opcodes.</li>
-			<li>BTC Ordinals using empty opcodes to implement BTC NFTs.</li>
-		</ul>
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-A good example of that assigning new optional use-cases for previously unused opcodes as with the example of the recent Bitcoin Ordinals update.
-
----v
-
-## Fork Categorization
-
-#### _Hidden Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_hidden.drawio.svg" />
-		<div style="font-size: 50px;">N ⊆ O</div>
-    </pba-col>
-    <pba-col>
-		<img style="width: 800px" src="./img/soft_forks_hidden.drawio.svg" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-And the reason why they are hidden... is they are not even manifesting as forks despite the consensus change.
-All nodes effectively accept each others blocks so there is no conflict.
-
----
-
-# Hard Forks
-
-Notes:
-
----v
-
-## Fork Categorization
-
-#### _Hard Forks_
-
-<br />
-<img style="width: 800px" src="./img/fork_family_hard.drawio.svg" />
-
----v
-
-## Fork Categorization
-
-#### _Hard Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_hard.drawio.svg" />
-		<div style="font-size: 50px;">O ⊆ N</div>
-    </pba-col>
-    <pba-col>
-		<ul>
-			<li>Forwards Compatible</li>
-			<li>By making the consensus rules less restrictive the set of valid blocks gets bigger.</li>
-			<li>Not every (and often none) of the blocks produced under new rules will be accepted by the old nodes.</li>
-			<li>Every block produced under old rules will get accepted by new nodes.</li>
-		</ul>
-    </pba-col>
-</pba-cols>
-
----v
-
-## Fork Categorization
-
-#### _Hard Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_hard.drawio.svg" />
-		<div style="font-size: 50px;">O ⊆ N</div>
-    </pba-col>
-    <pba-col>
-		<strong>Examples:</strong>
-		<br /><br />
-		<ul>
-			<li>Increasing blocksize</li>
-			<li>BTC Cash fork at first*</li>
-			<li>Adding new transaction types</li>
-			<li>Increasing max nonce value</li>
-		</ul>
-    </pba-col>
-</pba-cols>
-
----v
-
-## Fork Categorization
-
-#### _Hard Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_hard.drawio.svg" />
-		<div style="font-size: 50px;">O ⊆ N</div>
-    </pba-col>
-    <pba-col>
-			<img style="width: 800px" src="./img/hard_forks_s50.drawio.svg" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-First let's go through the scenario of a hard fork with less than 50% support.
-Remember that the rules were loosened this time.
-If new guys accept old blocks so because they have less than 50% power they get constantly reorged out.
-There is no permanent fork in this scenario and the change will not go through if if it has this limited support.
-
----v
-
-## Fork Categorization
-
-#### _Hard Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 300px" src="./img/venn_hard.drawio.svg" />
-		<div style="font-size: 50px;">O ⊆ N</div>
-    </pba-col>
-    <pba-col>
-			<img style="width: 800px" src="./img/hard_forks_g50.drawio.svg" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-In the case of more than 50% support the new guys miner faster but they are no accepted by the old nodes so they go ahead.
-Old nodes maintain the old chain and the community is split.
-So if there is a major change that most people accept but not everyone it will always fork the chain.
-
----
-
-## Small Summary
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 400px" src="./img/soft_forks_s50.drawio.svg" />
-		<br />
-		<img style="width: 400px" src="./img/soft_forks_g50.drawio.svg" />
-    </pba-col>
-	<pba-col>
-		<img style="width: 400px" src="./img/hard_forks_s50.drawio.svg" />
-		<br />
-		<img style="width: 400px" src="./img/hard_forks_g50.drawio.svg" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-Now that we've seen both soft and hard forks...
-If we'd manually increase the difficulty of mining in the BTC network would that be a soft or hard fork?
-Hard.
-
-Also let's reiterate.
-We only have permanent forks in soft forks with under 50% support and in hard forks with over 50% support.
-
----
-
-# Full Forks
-
----v
-
-## Fork Categorization
-
-#### _Full Forks_
-
-<br />
-<img style="width: 800px" src="./img/fork_family_full.drawio.svg" />
-
----v
-
-## Fork Categorization
-
-#### _Full Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 200px" src="./img/venn_full.drawio.svg" />
-		<div style="font-size: 50px;">O ∩ N = ∅</div>
-    </pba-col>
-    <pba-col>
-		<ul>
-			<li>Fully Incompatible</li>
-			<li>Soft + Hard</li>
-			<li>By changing the consensus rules the sets can become disjoint or overlapping.</li>
-			<li>Most (and often all) blocks produced under one ruleset are not accepted under the other.</li>
-		</ul>
-    </pba-col>
-</pba-cols>
-
----v
-
-## Fork Categorization
-
-#### _Full Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 200px" src="./img/venn_full.drawio.svg" />
-		<div style="font-size: 50px;">O ∩ N = ∅</div>
-    </pba-col>
-    <pba-col>
-		<strong>Examples:</strong>
-		<br /><br />
-		<ul>
-			<li>Changing the hashing function</li>
-			<li>Changing the signature scheme</li>
-			<li>Specific combinations of soft and hard forks</li>
-			<li>BTC Cash fork in the end*</li>
-		</ul>
-    </pba-col>
-</pba-cols>
-
----v
-
-## Fork Categorization
-
-#### _Full Forks_
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 200px" src="./img/venn_full.drawio.svg" />
-		<div style="font-size: 50px;">O ∩ N = ∅</div>
-    </pba-col>
-    <pba-col>
-		<img style="width: 600px" src="./img/full_forks__&_50.drawio.svg" />
-    </pba-col>
-</pba-cols>
-
----
-
-## Summary
-
-<pba-cols>
-    <pba-col>
-		<img style="width: 400px" src="./img/soft_forks_s50.drawio.svg" />
-		<br />
-		<img style="width: 400px" src="./img/soft_forks_g50.drawio.svg" />
-    </pba-col>
-	<pba-col>
-		<img style="width: 400px" src="./img/hard_forks_s50.drawio.svg" />
-		<br />
-		<img style="width: 400px" src="./img/hard_forks_g50.drawio.svg" />
-    </pba-col>
-    <pba-col>
-		<img style="width: 400px" src="./img/full_forks__&_50.drawio.svg" />
-    </pba-col>
-</pba-cols>
-
-Notes:
-
-- Bitcoin cash pivot from hard to full because they didn't have enough HP.
-- Soft are often preferred for changes because with >50%HP they do not fracture the community (BTC community logic)
-- Hard can be preferred as they seem to better represent minorities.
-  If some people don't agree with the majority they naturally fork off and are not peer pressured to follow (ETH community logic)
-
----
-
-# Thank you!
-
----
-
-<img style="width: 1800px" src="./img/forks.drawio.svg" />
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-# ⛓️ Blockchains and Smart Contracts
-
-Blockchain and applications built on them covered in depth conceptually and hands-on operation and construction.
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-# The Quest for Infrastructure
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: The Quest for Infrastructure
-description: Summary and review Smart Contract principles, and observation that we have not yet thwarted the tyrannical server operator
----
-
-# The Quest for Infrastructure
-
-OR
-
-Where can I actually run these things!?
-
----
-
-# Quick Review of Smart Contracts
-
----v
-
-## Expression
-
-Write code instead of long confusing legalese
-
----v
-
-## Execution
-
-Let the computer run it instead of the judge interpreting it.
-
----
-
-# Quick Review of Service Providers
-
-They are the technicians that keep the infra running.
-
-They are the technicians that keep the infra running.
-
-They don't have any particular morals, certainly not the same ones you have.
-
-Notes:
-
-We need people to keep the computers online and replace broken hardware and make sure the data is backed up etc.
-But those people should be just that, technicians.
-They are not elected officials or Judges or anything like that.
-So we don't want to accidentally let them fil that role.
-
-Many, probably even most, data center workers are perfectly good people not trying to scam anyone.
-The point is that any individual server operator could be evil and it will be easier to coordinate voluntarily if people don't have to trust the server operator to do it.
-
----
-
-# Where to Run the Contracts?
-
-Notes:
-
-We know we need somewhere to run these things with no back door or trusted party.
-
-We have seen some hints so far.
-Let's check them out.
-
----v
-
-## Diversity and Redundancy
-
-- Geographical - for natural disasters and terrorist attacks
-- Jurisdictional - to resist the incumbent governments - they are the ultimate server operators
-- Moral - so all compasses are represented in the network, and no group can impose hegemony
-- Of compute hardware - incase some is bugged or backdoored or prohibitively expensive
-
-Notes:
-
-Web2 gets a lot of this right.
-At least they are good at the first two and preventing accidental data loss etc.
-There is a lot to be kept from web 2.
-Some digital services, or subsystems of digital services may never even need web3 upgrades.
-
-But indeed there is also some to be thrown out or improved.
-
----v
-
-## P2P Networking
-
-Replace the operator with a system where peers all have power.
-
-Notes:
-
-We saw well how this worked out well in the file sharing and anonymous browsing domains (bit torrent,)
-
----v
-
-## Reproducible Execution
-
-- Computers are better than courts
-- PABs make distributed code execution practical
-
-Notes:
-
-We saw even back in the early 2000s with java web applets that allowing more people to run the same program is hugely useful.
-
-A few decades later we have much better tech for this, and it is even more valuable.
-
-PABs make it practical for diverse parties all over the world to run the same software deterministically on their bespoke hardware in their unique environments.
-
----
-
-# Blockchain
-
-## Solves ALL Your Problems
-
-<img rounded src="./img/moses-blockchain.png" />
-
----v
-
-## Solves Some Specific Problems
-
-Allows us to replace the central server operator with a P2P network and Consensus System
-
-Notes:
-
-Actually it is a fallacy that blockchain solves all our problems.
-It actually solves some very specific coordination problems.
-It also brings some efficiency improvements to modern bureaucracies.
-It does not automatically make everyone believe the same things or magically arrive in happy unicorn bunny land.
-Tomorrow and Thursday will dig in on how the blockchain and its P2P network work together.
-
----v
-
-## Blockchain Data structure
-
-<img width="60%" src="../structure/img/forks.svg">
-
-Notes:
-
-We'll discuss two new blockchain related topics.
-First is the blockchain data structure which you can see here.
-This one is forked which is when things get really interesting, and when you need to invoke the second part
-
----v
-
-## Blockchain Consensus
-
-<img width="60%" src="../finality/img/byzantine-generals.png">
-
-Notes:
-
-Consensus deals with how we agree which version of the data structure is real.
-It is an interesting and complex topic, but we first need to learn a bit more about how the data structure allows us to track a shared story.
-
----v
-
-## Reading Assignment
-
-For tomorrow please read the bitcoin whitepaper
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-# ink! Workshop
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: ink! Workshop
-description: An introduction to the ink! workshop.
-duration: 20 min
----
-
-<img rounded style="width: 1200px; padding-top:15px;" src="./img/beginners-workshop.jpg" />
-
-Notes:
-
-This workshop was an idea that came from first wave of PBA in Cambridge.
-The first time it was ever played was back in Buenos Aires.
-It's very much a PBA right of passage, so it's exciting to be able to play today.
-
----
-
-# Day 1
-
----
-
-<img rounded style="margin-top: 25px; width: 1200px;" src="./img/beamer.png" />
-
-Notes:
-
-This is us playing in BA earlier this year.
-
----
-
-## Components
-
-<br />
-
-<div class="flex-container fragment">
-<div class="left"> <!-- Gotcha: You Need an empty line to render MD inside <div> -->
-<div style="text-align: center"> <center><h2><pre> game.contract </pre></h2></center> </div>
-<ul>
-<li>We deploy + run.</li>
-<li>Runs game loop.</li>
-<li>Invokes each player.</li>
-<li>Determines the score.</li>
-</ul>
-</div>
-
-<div class="left fragment"> <!-- Gotcha: You Need an empty line to render MD inside <div> -->
-<div style="text-align: center"> <center><h2><pre> player.contract </pre></h2></center> </div>
-
-<ul>
-<li>Your job.</li>
-</ul>
-</div>
-<div class="right fragment"> <!-- Gotcha: You Need an empty line to render MD inside <div> -->
-<div style="text-align: center"> <center><h2><pre> frontend </pre></h2></center> </div>
-<ul>
-<li>On big screen during game.</li>
-</ul>
-</div>
-</div>
-
-Notes:
-
-The game has three components:
-
-- **click** the first is a game contract, which is something that we have taken care of.
-  I will deploy it and run it on Rococo.
-  The game contract runs the game loop.
-  It invokes each player contract and it determines the score.
-- **click** And the player.contract, that's your job.
-  so we we have a template for a very basic player and you can basically modify it in any way you like.
-  I will explain the scoring function in a moment.
-- **click** Lastly, we have a front-end that we will put on the big screen here, but it's online, you can open it up on your laptop and follow the game locally.
-
----
-
-## The Process
-
-1. 🧠 Create contract that plays on your behalf<!-- .element: class="fragment" data-fragment-index="1" -->
-1. 🚀 Deploy contract to Rococo testnet <!-- .element: class="fragment" data-fragment-index="2" -->
-1. 🤝 Register contract as player with game contract<!-- .element: class="fragment" data-fragment-index="3" -->
-1. ️🎮 We start the game<!-- .element: class="fragment" data-fragment-index="4" -->
-1. 📺️️ It runs for some minutes, we watch it on screen<!-- .element: class="fragment" data-fragment-index="5" -->
-
-Notes:
-
-So the process is as follows:
-
-- **click** - you brainstorm and create a contract that plays on your behalf ideally in a better way than the other contracts
-- **click** - you deploy the contract to the Rococo testnet
-- **click** - you register your contract as a player with the game contract.
-  We will publish the addresses and it's it's not complicated you can just use contracts UI.
-  I will also show it in a second
-- **click** - then we start the game.
-  We have a script that calls the game contract regularly and the front end will display the changes
-- **click** - so the game will run for some minutes.
-  Your contract will already be uploaded at this point - so you can't do anything.
-  The contract will play on your behalf.
-  Meaning it's hands off.
-  I mean you can also change it with upgradable contract patterns and stuff, but in general, you won't have to.
-  So you can just watch the game play out.
-  If you're familiar with AI agents, that's also a similar idea, where you have an agent that plays a game on your behalf.
-
----
-
-## How the Game looks
-
-<img rounded src="./img/splash-2.png" />
-
-Notes:
-
-This is what the game board itself looks like.
-You can see, it's a it's a coordinate grid.
-
----
-
-## How the Game looks
-
-<img rounded src="./img/splash-9.png" />
-
-Notes:
-
-this is X1 y0.
-And the idea is for you, as a contract developer, to paint as many fields of this canvas of the script as possible.
-There's an API function for how to paint.
-I'll show it in a minute, but the idea is that in the end the contract that painted the most Fields wins.
-
----
-
-## How the Game looks
-
-<img rounded src="./img/splash-10.png" />
-
-Notes:
-
-So yeah, there's bit of scoring to be done.
-There's also scoreboard here on the side, where all players will be shown as well as their rank.
-You will be assigned a random color to your player contract.
-
----
-
-## How to score?
-
-- Use as little gas as possible to paint as many fields as possible.
-
-<!-- .element: class="fragment" -->
-
-- Stay within your gas budget.
-
-<!-- .element: class="fragment" -->
-
-- The later you manage to still paint a field the better you score.
-
-<!-- .element: class="fragment" -->
-
-- No overpainting! First player to paint a field owns it.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-This game was designed in a way where all of the best practices for smart contract development will make your player run better.
-We really tried to gamify some of the concepts that are really best practices of how you should develop a smart contract.
-
-- **click** - first one is to use as little gas as possible to paint as many fields as possible.
-  Gas consumption is a super big thing as user fees derived from that and the transaction throughput also relates to how big a contract is so the less complex your contract is the better it will do.
-- **click** - There's a certain gas budget allocated per player and if you if you're above that then you just won't make a turn.
-  So you have to stay in an optimal gas budget.
-- **click** - the later in the in the game that you still manage to paint the field the better you score because what will happen is that there will be all kinds of fields painted and it will convert to a place where there's only a few left.
-  so if you have a player that just randomly tries to paint things then at some at some point it just won't no longer work because it doesn't paint the unpainted fields.
-  But in order to find those, you will have to have some more complex logic in your contract.
-- **click** - and lastly, there's no overpainting.
-  So the first player to paint a field owns it.
-  So if you have a contract that just paints the same field over and over again, it will just not work.
-  So you have to have some logic in there that checks whether a field is already painted or not.
-
----
-
-## Basic Player Contract
-
-```rust [1-2,19|3-4|7-10|12-17|1-19]
-#[ink::contract]
-mod player {
-    #[ink(storage)]
-    pub struct Player {}
-
-    impl Player {
-        #[ink(constructor)]
-        pub fn new() -> Self {
-            Self {}
-        }
-
-        /// Called during every game round.
-        /// Return `(x, y)` coordinate of pixel you want to color.
-        #[ink(message, selector = 0)]
-        pub fn your_turn(&self) -> Option<(u32, u32)> {
-            Some(1, 2)
-        }
-    }
-}
-```
-
-Notes:
-
-So this is a very basic player contract.
-We have a repository app set up with the template for this - I will share the link in a second.
-How it looks is - it's a contract that defines the player module.
-
-- **click** - a super simple player doesn't have to contain any storage whatsoever.
-- **click**- a super simple player also doesn't have to contain any Constructor arguments
-- **click** - and it can just return a random constant value.
-  So this is the most simple player ever.
-  What your player needs to do is to have one message, that has a defined selector, so you don't have to think more about this.
-  It's just that it needs to have this function and this function is called by the game with every round.
-  And whatever you return from this function.
-  This is your your turn for the game.
-  So if in this case you return an option some(1,2), this would mean you paint the pixel at X1 Y2.
-  In that case, it would be a very boring play.
-  Who can tell me what would happen here?
-  _(a player that only makes one turn - it always tries to paint the same field_.
-  _And if someone else also chose the same magic numbers then it wouldn't even make a turn at all_.)
-- **click** - So there's a couple things of how you can improve on that and I will show some hints later, but for now what we're gonna do is look at the repository and see how we can get started with this.
-
----
-
-## How to play
-
-<img rounded src="./img/github.png" />
-
-Notes:
-
-This is the Squink-Splash-beginner Repository - it contains a couple of things.
-
----
-
-## How to play
-
-<img rounded src="./img/github1.png" />
-Notes:
-
-It contains the cargo.toml file and the lib.rs, which is the player that I just showed.
-
----
-
-## How to play
-
-<img rounded src="./img/github2.png" />
-
-Notes:
-
-It contains the game metadata.
-You will need this in order to interact with the game itself, to register your player and so on.
-but yeah we will show that.
-
----
-
-## How to play
-
-<img rounded src="./img/github3.png" />
-
-Notes:
-
-And it has 2 `todo` files.
-The first is some instructions on General setup and the second one is in order to build your player.
-
----
-
-## Now (1)
-
-[github.com/paritytech/squink-splash-beginner ➜ todo-1.md](https://github.com/paritytech/squink-splash-beginner/blob/main/todo-1.md)
-
-Notes:
-
-So, the first thing that we are going to do is that I would ask all of you to go to this link here and follow the instructions.
-We will go around and help whoever has an issue.
-I think you might even have already used some of the requirements in there, so it may not be super complicated.
-
----
-
-## Now (2)
-
-[github.com/paritytech/squink-splash-beginner ➜ todo-2.md](https://github.com/paritytech/squink-splash-beginner/blob/main/todo-2.md)
-
-Notes:
-
-For this stage, you will need the address of the game.
-We'll post it in the chat.
-This is a simple example - we're just giving you exposure to the flow of uploading your player contract.
-
----
-
-## 🕹️🎮 Let's play! 🕹️🎮
-
-[https://splash.use.ink](https://splash.use.ink)
-
-Notes:
-
-The next slides go over strategy.
-(maybe wait to to go through until you've played one game)
-
----
-
-## The Game Contract
-
-> [`ink-workshop/game/lib.rs`](https://github.com/paritytech/ink-workshop/blob/main/game/lib.rs)
-
-- `pub fn submit_turn(&mut self)`
-
-<!-- .element: class="fragment" -->
-
-- `pub fn board(&self) -> Vec<Option<FieldEntry>>`
-
-<!-- .element: class="fragment" -->
-
-- `pub fn gas_budget(&self) -> u64`
-
-<!-- .element: class="fragment" -->
-
-- `pub fn dimensions(&self) -> (u32, u32)`
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-When you deployed it you already saw that there's different functions that you can call.
-There are a lot of functions that are interesting.
-
-- **click** - the game runner calls this - if you're interested, you can take a look how it works and there might be some hints for for the game.
-- **click** - then there's a function to to query the board in order to find out if certain fields are already occupied or if they are still free.
-- **click** - there's a function for the gas budget so you can find out how much gas your player is allowed to use per one round.
-  Because worst thing is if you are above this gas budget, then you just won't execute any turn during that round.
-- **click** - there's also function to query the game dimensions.
-  Same thing there, if you paint outside the bounds, then also you just missed one turn.
-
----
-
-## Things to consider 🧠
-
-- Develop a strategy for your player.<br /><br />
-- Use as little gas as possible to paint as many fields as possible.
-- Stay within your gas budget.
-- The later you manage to still paint a field, the better you score.<br /><br />
-- No overpainting! First player to paint a field owns it.
-- [paritytech/squink-splash-advanced](https://github.com/paritytech/squink-splash-advanced)
-
----
-
-## How to test locally?
-
-[paritytech/squink-splash-advanced](https://github.com/paritytech/squink-splash-advanced)
-
-Notes:
-
-There's details in here.
-You could deploy locally to test things out.
-there's also commands you can use to deploy not using the UI.
-
----
-
-## Hint: Playfield Dimensions
-
-- Paint within the bounds of the playfield!
-- Otherwise you wasted a turn.
-
----
-
-## Ideas
-
-- You can call your own contract as often as you want!
-
-<!-- .element: class="fragment" -->
-
-- Random number
-
-<!-- .element: class="fragment" -->
-
-- Query which fields are free
-  - Query game state via cross-contract call
-  - Off-chain computation
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-- **click** Lastly, some ideas for for your agent in the game you can you yourself can call your contract.
-  As often as you want and this won't contribute to the gas used during the game.
-  You can during the game you could also call a set of function of your contract if you want to adapt something.
-- **click** You could also Generate random numbers.
-  There are a couple of libraries out there, if you want to go along those lines you have to pay attention that it's a no standard Library.
-  typically a random number generator libraries they typically have a feature that you need to enable in order to make them no standard compatible
-- **click** A clever strategy would be a query which fields are free.
-  that's a bit more complex with the with the code snippet that we have in this Advanced repository, this would give you a hint.
-
----
-
-<!-- .slide: data-background="./img/Questions_2.svg"" -->
-
----
-
-# Day 2
-
----
-
-<img rounded style="width: 1400px; padding-top:15px;" src="./img/advanced-workshop.jpg" />
-
----
-
-<pba-cols>
-<pba-col center>
-
-### Now
-
-We help you debug!
-
-</pba-col>
-<pba-col center>
-
-### Then
-
-🕹️🎮🕹️🎮
-
-</pba-col>
-<pba-col center>
-
-### Thereafter
-
-Solutions Explainer
-
-</pba-col>
-</pba-cols>
-
-<br />
-
-<blockquote style="text-align: left; font-size: 0.9em;">
-Use as little gas as possible to paint as many fields as possible.<br /><br />
-Stay within your gas budget.<br /><br />
-The later you manage to still paint a field, the better you score.<br /><br />
-No overpainting! First player to paint a field owns it.<br />
-</blockquote>
-
-<br />
-<br />
-
-[paritytech/squink-splash-advanced](https://github.com/paritytech/squink-splash-advanced)
-
----
-
-## Frontend
-
-[https://splash.use.ink](https://splash.use.ink)
-
----
-
-## Questions
-
-- What strategy did the winner choose?
-
-<!-- .element: class="fragment" -->
-
-- What strategies did the others choose?
-
-<!-- .element: class="fragment" -->
-
-- What do you think would be the perfect strategy?
-
-<!-- .element: class="fragment" -->
-
----
-
-## Board Dimensions
-
-- Worst 😱
-  - Cross-contract call to `game`<br /><br />
-
-```rust
-#[ink(message)]
-pub fn dimensions(&self) -> (u32, u32)
-```
-
-<br /><br />
-
-<!-- .element: class="fragment" -->
-
-- Best 👍️
-  - `const width: u32`
-  - `new(width: u32, height: u32)`
-
-<!-- .element: class="fragment" -->
-
----
-
-## More Pitfalls
-
-<img rounded style="margin-top: 25px; width: 400px;" src="./img/oopsie.gif" />
-
-- Forgetting `--release`
-
-<!-- .element: class="fragment" -->
-
-- Iterating over a datastructure in your contract
-
-<!-- .element: class="fragment" -->
-
----
-
-## Avoid iteration
-
-<pba-cols>
-<pba-col center>
-
-```
-#[ink(message)]
-fn pay_winner()
-  let winner = self.players.find(…);
-
-  self.transfer(winner, …);
-}
-```
-
-</pba-col>
-<!-- .element: class="fragment" -->
-<pba-col center>
-
-```rust
-#[ink(message)]
-fn pay_winner(
-    winner: AccountId
-) {
-  assert!(is_winner(winner));
-
-  self.transfer(winner, …);
-}
-```
-
-</pba-col>
-<!-- .element: class="fragment" -->
-</pba-cols>
----
-
-## Strategy 1<br />Return Random Numbers
-
-<img rounded style="margin-top: 25px; width: 500px;" src="./img/0.png" />
-
----
-
-## Strategy 1<br />Return Random Number
-
-- Wasm-compatible RNG
-
-<!-- .element: class="fragment" -->
-
-- Use Storage to hold seed for random number
-
-<!-- .element: class="fragment" -->
-
-- 📈 Uses little Gas
-
-<!-- .element: class="fragment" -->
-
-- 📉 Quickly runs into collisions
-
-<!-- .element: class="fragment" -->
-
-- 📉 Score function rewards players that late in game still paint fields
-
-<!-- .element: class="fragment" -->
-
----
-
-## Strategy 2<br />Paint only free fields
-
-<img rounded style="margin-top: 25px; width: 500px;" src="./img/1.png" />
-
----
-
-## Strategy 2<br />Paint only free fields
-
-- Query board for free fields
-- 📈 Succeeds late in game
-
-<!-- .element: class="fragment" -->
-
-- 📉 Cross-contract call 💰️
-- 📉 Need to iterate over `Mapping`: `O(n)`
-
-<!-- .element: class="fragment" -->
-
----
-
-## Strategy 3<br />Shift computation off-chain
-
-<img rounded style="margin-top: 25px; width: 500px;" src="./img/2.png" />
-
----
-
-## Strategy 3<br />Shift computation off-chain
-
-- Off-chain Script
-  - Query board ➜ Search free field<br /><br />
-
-<!-- .element: class="fragment" -->
-
-- ```rust[1-2|1-7]
-  #[ink(message)]
-  fn set_next_turn(turn: …) {}
-
-  #[ink(message, selector = 0)]
-  pub fn your_turn(&mut self) -> {
-    self.next_turn
-  }
-  ```
-
-<!-- .element: class="fragment"  -->
-
----
-
-## Strategy 4<br />Exploit player sorting in game loop
-
-<img rounded style="margin-top: 25px; width: 500px;" src="./img/3.png" />
-
----
-
-## Strategy 4<br />Exploit player sorting in game loop
-
-- On top of Strategy 3 (off-chain computation).
-
-<!-- .element: class="fragment"  -->
-
-- Game loop calls players in same order each time.
-
-<!-- .element: class="fragment"  -->
-
-```rust
-#[ink(message)]
-fn submit_turn(&mut self) {
-    // -- snip --
-
-    for (idx, player) in players.iter_mut().enumerate() {
-        …
-    }
-
-  // -- snip --
-}
-```
-
-<!-- .element: class="fragment"  -->
-
----
-
-## Strategy 4<br />Exploit player sorting in game loop
-
-```rust
-impl<T: Config> AddressGenerator<T> for DefaultAddressGenerator {
-	fn generate_address(
-		deploying_address: &T::AccountId,
-		code_hash: &CodeHash<T>,
-		input_data: &[u8],
-		salt: &[u8],
-	) -> T::AccountId {
-
-    // -- snip --
-
-	}
-}
-```
-
-➜ All inputs are known
-
-<!-- .element: class="fragment"  -->
-
-➜ Generate low `T::AccountId` with known inputs
-
-<!-- .element: class="fragment"  -->
-
----
-
-## Strategy 5<br />Checking these slides already yesterday
-
-<img rounded style="margin-top: 25px; width: 500px;" src="./img/4.png" />
-
----
-
-<!-- .slide: data-background="./img/Questions_2.svg"" -->
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-   width="337.91998pt"
-   height="216.95999pt"
-   viewBox="0 0 337.91998 216.95999"
-   version="1.1"
-   id="svg71"
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diff --git a/content/blockchain-contracts/ink/img/storage.svg b/content/blockchain-contracts/ink/img/storage.svg
deleted file mode 100644
index 34336175..00000000
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deleted file mode 100644
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diff --git a/content/blockchain-contracts/ink/img/trap.gif b/content/blockchain-contracts/ink/img/trap.gif
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diff --git a/content/blockchain-contracts/ink/page.md b/content/blockchain-contracts/ink/page.md
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-# Wasm Smart Contracts in Ink!
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/ink/slides.md b/content/blockchain-contracts/ink/slides.md
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--- a/content/blockchain-contracts/ink/slides.md
+++ /dev/null
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----
-title: Wasm Smart Contracts in Ink!
-description: A working programmer’s guide to the crypto industry
----
-
-<img rounded style="width: 600px;" src="./img/ink-logo-with-squid-white.svg" />
-
-# Wasm Smart Contracts in Ink!
-
-A working programmer’s guide
-
-Notes:
-
-- ask questions during the lecture, don't wait until the end
-- practical, but we go deeper where needed
-- some complexity is omitted in the examples (examples are not a production code)
-
----
-
-## Intro: ink! vs. Solidity
-
-|                 | ink!                        | Solidity      |
-| --------------- | --------------------------- | ------------- |
-| Virtual Machine | Any Wasm VM                 | EVM           |
-| Encoding        | Wasm                        | EVM Byte Code |
-| Language        | Rust                        | Standalone    |
-| Constructors    | Multiple                    | Single        |
-| Tooling         | Anything that supports Rust | Custom        |
-| Storage         | Variable                    | 256 bits      |
-| Interfaces?     | Yes: Rust traits            | Yes           |
-
-Notes:
-
-- students are freshly of an EVM lecture so might be wondering why another SC language
-- Virtual Machine: any Wasm VM: yes in theory, in practice bound pretty close to the platform it runs on (Substrate & the contracts pallet)
-- Tooling: Solidity has been around for years, enjoys the first-to-market advantage (but ink! is a strong contender)
-- The EVM operates on 256 bit words (meaning anything less than 32 bytes will be treated by the EVM as having leading zeros)
-
----
-
-## Intro: ink! overview
-
-- DSL in Rust
-- Inherits all the benefits of Rust
-  - Modern functional language
-  - Type & Memory safety
-- Compiled to Wasm
-  - Ubiquitous
-  - Fast
-
-Notes:
-
-- ink! is not a separate language
-- enjoys access to a vast collection of libraries developed for other purposes
-- Wasm is targeting the browsers and quickly becoming the "assembly" od the web in lieu of JS
-
----
-
-## Intro: ink! & Substrate
-
-<img rounded style="width: 900px;" src="./img/lego0.png" />
-
-Notes:
-
-- Technically you could take a SC written in ink! and deploy it to any Wasm-powered blockchain.
-  - in practice not that straight-forward.
-- ink! is closely tied to the larger Substrate framework.
-- Substrate is a framework for developing customized blockchain runtimes from composable pallets.
-
----
-
-## Intro: ink! & Substrate
-
-<img rounded style="width: 900px;" src="./img/lego1.png" />
-
-Notes:
-
-- contracts written in ink! are compiled to Wasm bytecode
-- pallet contracts provides
-  - instrumentation
-  - execution engine
-  - gas metering
-
----
-
-<img rounded style="width: 800px;" src="./img/schema1.png" />
-
-Notes:
-
-- pallet contracts is oblivious to the programming language
-- it accepts Wasm bytecode and executes it's instructions
-
----
-
-<img rounded style="width: 800px;" src="./img/schema2.png" />
-
-Notes:
-
-- contracts itself can be written in ink!
-
----
-
-<img rounded style="width: 800px;" src="./img/schema3.png" />
-
-Notes:
-
-- But also any other language that compilers to Wasm
-  - Solang
-  - or ask!
-
----
-
-## Development: Prerequisites
-
-Install the required tooling
-
-```sh
-sudo apt install binaryen
-rustup component add rust-src --toolchain nightly
-rustup target add wasm32-unknown-unknown --toolchain nightly
-cargo install dylint-link
-cargo install cargo-contract --force
-```
-
-- [binaryen](https://github.com/WebAssembly/binaryen) is a compiler for WebAssembly.
-- [dylint-link](https://github.com/trailofbits/dylint) adds DSL specific lints.
-
-Notes:
-
-- Binaryen is a compiler and toolchain infrastructure library for WebAssembly
-- at the moment ink! uses a few unstable Rust features, thus nightly is require
-- rust source code is needed to compile it to wasm
-- wasm target is added
-- cargo-contract is a batteries included CLI tool for compiling, deploying and interacting with the contracts
-
----
-
-## Development: cargo-contract
-
-Create a contract
-
-```sh
-cargo contract new flipper
-```
-
-```sh
-/home/CloudStation/Blockchain-Academy/flipper:
-  drwxrwxr-x 2 filip filip 4096 Jul  7 11:11 .
-  drwxr-xr-x 5 filip filip 4096 Jul  7 11:11 ..
-  -rwxr-xr-x 1 filip filip  573 Jul  7 11:11 Cargo.toml
-  -rwxr-xr-x 1 filip filip  285 Jul  7 11:11 .gitignore
-  -rwxr-xr-x 1 filip filip 5186 Jul  7 11:11 lib.rs
-```
-
-Notes:
-
-- ask how many student have written some code in Rust, this should feel familiar to them
-
----
-
-## Development: Cargo.toml
-
-<div style="font-size: 0.72em;">
-
-```toml
-[package]
-version = "0.1.0"
-authors = ["fbielejec"]
-edition = "2021"
-
-[dependencies]
-ink = { version = "=4.2.1", default-features = false }
-scale = { package = "parity-scale-codec", version = "3", default-features = false, features = ["derive"] }
-scale-info = { version = "2.6", default-features = false, features = ["derive"], optional = true }
-
-[lib]
-path = "lib.rs"
-
-[features]
-default = ["std"]
-std = [
-  "ink/std",
-  "scale/std",
-  "scale-info/std",
-]
-```
-
-</div>
-
-Notes:
-
-- who knows why is the std library not included by default?
-- Answer: contracts are compiled to Wasm (executed ib a sandboxed environment with no system interfaces, no IO, no networking)
-
----
-
-## Developing contracts
-
-contract code
-
-<div style="font-size: 0.62em;">
-
-```rust
-#[ink::contract]
-pub mod flipper {
-
-    #[ink(storage)]
-    pub struct Flipper {
-        value: bool,
-    }
-
-    impl Flipper {
-        #[ink(constructor)]
-        pub fn new(init_value: bool) -> Self {
-            Self { value: init_value }
-        }
-
-        #[ink(constructor)]
-        pub fn default() -> Self {
-            Self::new(Default::default())
-        }
-
-        #[ink(message)]
-        pub fn flip(&mut self) {
-            self.value = !self.value;
-        }
-
-        #[ink(message)]
-        pub fn get(&self) -> bool {
-            self.value
-        }
-    }
-}
-```
-
-</div>
-
-Notes:
-
-- basic contract that flips a bit in storage
-- contract will have a storage definition, constructor(s), messages
-- grouped in a module
-
----
-
-## Developing contracts: Compilation & artifacts
-
-Compile:
-
-```sh
-cargo +nightly contract build
-```
-
-Artifacts:
-
-```
- [1/*] Building cargo project
-    Finished release [optimized] target(s) in 0.09s
-
-The contract was built in RELEASE mode.
-
-Your contract artifacts are ready.
-You can find them in:
-/home/CloudStation/Blockchain-Academy/flipper/target/ink
-
-  - flipper.contract (code + metadata)
-  - flipper.wasm (the contract's code)
-  - flipper.json (the contract's metadata)
-```
-
-Notes:
-
-- produces Wasm bytecode and some additional artifacts:
-- .wasm is the contract compiled bytecode
-- .json is contract ABI aka metadata (for use with e.g. dapps)
-  - definitions of events, storage, transactions
-- .contracts is both of these together
-
----
-
-## Developing contracts: instantiate
-
-Deploy:
-
-```sh
-cargo contract instantiate --constructor default --suri //Alice
-  --skip-confirm --execute
-```
-
-Output:
-
-<div style="font-size: 0.82em;">
-
-```sh [13-14]
- Dry-running default (skip with --skip-dry-run)
-    Success! Gas required estimated at Weight(ref_time: 138893374, proof_size: 16689)
-...
-  Event Contracts ➜ CodeStored
-         code_hash: 0xbf18c768eddde46205f6420cd6098c0c6e8d75b8fb042d635b1ba3d38b3d30ad
-       Event Contracts ➜ Instantiated
-         deployer: 5GrwvaEF5zXb26Fz9rcQpDWS57CtERHpNehXCPcNoHGKutQY
-         contract: 5EXm8WLAGEXn6zy1ebHZ4MrLmjiNnHarZ1pBBjZ5fcnWF3G8
-...
-       Event System ➜ ExtrinsicSuccess
-         dispatch_info: DispatchInfo { weight: Weight { ref_time: 2142580978, proof_size: 9009 }, class: Normal, pays_fee: Yes }
-
-   Code hash 0xbf18c768eddde46205f6420cd6098c0c6e8d75b8fb042d635b1ba3d38b3d30ad
-    Contract 5EXm8WLAGEXn6zy1ebHZ4MrLmjiNnHarZ1pBBjZ5fcnWF3G8
-```
-
-</div>
-
-Notes:
-
-- we see a bunch of information on gas usage
-- we see two events one for storing contract code another for instantiating the contract
-  - why is that?
-  - code & instance are separated, we will come back to that
-- finally we see code hash and the newly created contracts address
-
----
-
-## Interacting with the contracts: queries
-
-```sh
-cargo contract call --contract 5EXm8WLAGEXn6zy1ebHZ4MrLmjiNnHarZ1pBBjZ5fcnWF3G8
-  --message get --suri //Alice --output-json
-```
-
-- contract state?
-- tip: `default` constructor was called
-
-Notes:
-
-- who can tell me what will be the contract state at this point?
-
----
-
-## Interacting with the contracts: queries
-
-<!-- Query the contract state: -->
-
-<!-- ```sh -->
-<!-- cargo contract call --contract 5EXm8WLAGEXn6zy1ebHZ4MrLmjiNnHarZ1pBBjZ5fcnWF3G8 -->
-<!--   --message get --suri //Alice --output-json -->
-<!-- ``` -->
-
-<!-- Result: -->
-
-```[6]
-"data": {
-  "Tuple": {
-    "ident": "Ok",
-    "values": [
-      {
-        "Bool": false
-      }
-    ]
-  }
-}
-```
-
----
-
-## Interacting: transactions
-
-Sign and execute a transaction:
-
-```sh
-cargo contract call --contract 5EXm8WLAGEXn6zy1ebHZ4MrLmjiNnHarZ1pBBjZ5fcnWF3G8
-  --message flip --suri //Alice --skip-confirm --execute
-```
-
-Query the state:
-
-```sh
-cargo contract call --contract 5EXm8WLAGEXn6zy1ebHZ4MrLmjiNnHarZ1pBBjZ5fcnWF3G8
-  --message get --suri //Alice --output-json
-```
-
-Result:
-
-<div style="font-size: 0.82em;">
-
-```[6]
-"data": {
-  "Tuple": {
-    "ident": "Ok",
-    "values": [
-      {
-        "Bool": true
-      }
-    ]
-  }
-}
-```
-
-</div>
-
-Notes:
-
-- if I query it again the bit is flipped
-- no surprises there
-
----
-
-## Dev environment: Contracts UI
-
-<img rounded style="width: 1400px;" src="./img/contracts_ui_1.jpg" />
-
-Notes:
-
-- there is also a graphical env for deploying & interacting with contracts
-- deploy & create an instance of flipper
-
----
-
-## Dev environment: Contracts UI
-
-<img rounded style="width: 1400px;" src="./img/contracts_ui_2.jpg" />
-
-Notes:
-
-- call a transaction
-
----
-
-## Dev environment: Contracts UI
-
-<img rounded style="width: 1400px;" src="./img/contracts_ui_3.jpg" />
-
-Notes:
-
-- query state
-
----
-
-## Developing contracts: Constructors
-
-```rust [7,12,17|13,18,7-9|2-4,8]
-#[ink(storage)]
-pub struct Flipper {
-    value: bool,
-}
-
-#[ink(constructor)]
-pub fn new(init_value: bool) -> Self {
-    Self { value: init_value }
-}
-
-#[ink(constructor)]
-pub fn default() -> Self {
-    Self::new(Default::default())
-}
-
-#[ink(constructor)]
-pub fn non_default() -> Self {
-    Self::new(false)
-}
-```
-
-Notes:
-
-- lets dissect what a contract code is built like
-- no limit of the number of constructors
-- constructors can call other constructors
-- constructors return the initial storage
-- a lot of complexity conveniently hidden behind macros
-
----
-
-## Developing contracts: Queries
-
-```rust
-#[ink(message)]
-pub fn get(&self) -> bool {
-    self.value
-}
-```
-
-- `#[ink(message)]` is how we tell ink! this is a function that can be called on the contract
-- `&self` is a reference to the contract's storage
-
-<!-- #you’re calling this method on  -->
-
-Notes:
-
-- returns information about the contract state stored on chain
-- reaches to the storage, decodes it and returns the value
-
----
-
-## Developing contracts: Mutations
-
-```rust [1-2|6]
-#[ink(message, payable)]
-pub fn place_bet(&mut self, bet_type: BetType) -> Result<()> {
-    let player = self.env().caller();
-    let amount = self.env().transferred_value();
-    ...
-    self.data.set(&data);
-    ...
-```
-
-- `&mut self` is a mutable reference to the object you’re calling this method on
-- `payable` allows receiving value as part of the call to the ink! message
-
-Notes:
-
-- constructors are inherently payable
-- ink! message will reject calls with funds if it's not marked as such
-- mutable references allow me to modify the storage.
-- queries are for free, mutations are metered (you pay gas)
-  - you will also pay for queries within such transactions
-
----
-
-## Contracts: Error handling
-
-<div style="font-size: 0.72em;">
-
-```rust [1-4|8-11,16|14,20]
-pub enum MyResult<T, E> {
-    Ok(value: T),
-    Err(msg: E),
-}
-
-#[derive(Debug, PartialEq, Eq, Encode, Decode)]
-#[cfg_attr(feature = "std", derive(scale_info::TypeInfo))]
-pub enum MyError {
-    InkEnvError(String),
-    BettingPeriodNotOver,
-}
-
-#[ink(message)]
-pub fn spin(&mut self) -> Result<()> {
-    if !self.is_betting_period_over() {
-        return Err(MyError::BettingPeriodNotOver);
-    ...
-};
-
-pub type Result<T> = core::result::Result<T, MyError>;
-```
-
-</div>
-
-- ink! uses idiomatic Rust error handling: `Result<T,E>` type
-- Use the Err variant to pass your own semantics
-- Type aliases reduce boilerplate & enhance readability
-
-Notes:
-
-- ink! uses idiomatic Rust error handling
-- ~~messages are the `system boundary`~~
-- returning error variant or panicing reverts the transaction
-  - panicing is the same as returning Err variant (`Result` is just being nice)
-
----
-
-## Error handling: call stack
-
-```rust
-#[ink(message)]
-pub fn flip(&mut self) {
-    self.value = !self.value;
-
-    if self.env().block_number() % 2 != 0 {
-      panic!("Oh no!")
-    }
-
-}
-```
-
-- what is the state of this contract if the tx is called in an odd block number?
-
-Notes:
-
-- answer: whatever it was prior to the tx:
-  - returning error variant reverts the entire tx on the call stack
-
----
-
-## Contracts: Events
-
-```rust
-#[ink(event)]
-#[derive(Debug)]
-pub struct BetPlaced {
-    #[ink(topic)]
-    player: AccountId,
-    #[ink(topic)]
-    bet_type: BetType,
-    amount: Balance,
-}
-```
-
-- Events are a way of letting the outside world know about what's happening inside the contract.
-- `#[ink(event)]` is a macro that defines events.
-- Topics mark fields for indexing.
-
-Notes:
-
-- events are especially important for dapps
-- storage is expensive: reading e.g. aggregate data from chain directly is impossible / impractical
-- dapps the can listen to the event, normalize & store off-chain and answer e.g. complex queries
-
----
-
-## Contracts: Events
-
-```rust
-#[ink(message)]
-pub fn flip(&mut self) {
-
-    Self::emit_event(
-        self.env(),
-        Event::Flipped(Flipped { }),
-    );
-
-    self.value = !self.value;
-
-    if self.env().block_number() % 2 == 0 {
-      panic!("Oh no!")
-    }
-
-}
-```
-
-- What happens to the events from reverted transactions?
-- Will this event be emitted in an odd block?
-
-Notes:
-
-- answer: yes, but only because I reverted the condition :)
-
----
-
-## Contracts: Defining shared behaviour
-
-<div style="font-size: 0.5em;">
-
-```rust [1-14|17,22]
-#[ink::trait_definition]
-pub trait PSP22 {
-    #[ink(message)]
-    fn total_supply(&self) -> Balance;
-
-    #[ink(message)]
-    fn balance_of(&self, owner: AccountId) -> Balance;
-
-    #[ink(message)]
-    fn approve(&mut self, spender: AccountId, amount: Balance) -> Result<(), PSP22Error>;
-
-    #[ink(message)]
-    fn transfer(&mut self, to: AccountId, value: Balance, data: Vec<u8>) -> Result<(), PSP22Error>;
-    ...
-
-impl SimpleDex {
-    use psp22_trait::{PSP22Error, PSP22};
-
-    /// Returns balance of a PSP22 token for an account
-    fn balance_of(&self, token: AccountId, account: AccountId) -> Balance {
-        let psp22: ink::contract_ref!(PSP22) = token.into();
-        psp22.balance_of(account)
-    }
-    ...
-```
-
-</div>
-
-- Trait Definition: `#[ink::trait_definition]`.
-- Sharing the trait definition to do a cross-contract call.
-
-Notes:
-
-- (part of) PSP22 (ERC20 like) contract definition
-- all contracts that respect this definition need to implement it
-- you can now share the trait definition with other contracts
-- while getting a typed reference to an instance
-
----
-
-## Deeper dive: Storage
-
-```rust
-use ink::storage::Mapping;
-
-#[ink(storage)]
-#[derive(Default)]
-pub struct Token {
-    total_supply: Balance,
-    balances: Mapping<AccountId, Balance>,
-    allowances: Mapping<(AccountId, AccountId), Balance>,
-}
-```
-
-Notes:
-
-- now that we dipped our toes lets dissect more
-- starting with the storage
-- what does this code actually put into the chain storage?
-
----
-
-<img rounded style="width: 1000px;" src="./img/storage.svg" />
-
-<font color="#8d3aed">SCALE</font> (_<font color="#8d3aed">S</font>imple <font color="#8d3aed">C</font>oncatenated <font color="#8d3aed">A</font>ggregate <font color="#8d3aed">L</font>ittle <font color="#8d3aed">E</font>ndian_)
-
-Notes:
-
-- Pallet contracts storage is organized like a key-value database
-- each storage cell has a unique storage key and points to a SCALE encoded value
-- SCALE codec is not self-describing (vide metadata)
-
----
-
-## SCALE: examples of different types
-
-<div style="font-size: 0.72em;">
-
-| Type         | Decoding                              | Encoding                     | Remark                                                                         |
-| ------------ | ------------------------------------- | ---------------------------- | ------------------------------------------------------------------------------ |
-| Boolean      | true                                  | 0x0                          | encoded using least significant bit of a single byte                           |
-|              | false                                 | 0x1                          |                                                                                |
-| Unsigned int | 42                                    | 0x2a00                       |                                                                                |
-| Enum         | enum IntOrBool { Int(u8), Bool(bool)} | 0x002a and 0x0101            | first byte encodes the variant index, remaining bytes encode the data          |
-| Tuple        | (3, false)                            | 0x0c00                       | concatenation of each encoded value                                            |
-| Vector       | \[4, 8, 15, 16, 23, 42\]              | 0x18040008000f00100017002a00 | encoding of the vector length followed by conatenation of each item's encoding |
-| Struct       | {x:30u64, y:true}                     | \[0x1e,0x0,0x0,0x0,0x1\]     | names are ignored, Vec<u8> structure, only order matters                       |
-
-</div>
-
-Notes:
-
-- this table is not exhaustive
-- struct example: stored as an vector, names are ignored, only order matters, first four bytes encode the 64-byte integer and then the least significant bit of the last byte encodes the boolean
-
----
-
-## Storage: Packed Layout
-
-```rust [6]
-use ink::storage::Mapping;
-
-#[ink(storage)]
-#[derive(Default)]
-pub struct Token {
-    total_supply: Balance,
-    balances: Mapping<AccountId, Balance>,
-    allowances: Mapping<(AccountId, AccountId), Balance>,
-}
-```
-
-- By default ink! stores all storage struct fields under a single storage cell (`Packed` layout)
-
-Notes:
-
-- We talked about the kv database that the storage is, now how is it used precisely
-- Types that can be stored entirely under a single storage cell are called Packed Layout
-- by default ink! stores all storage struct fields under a single storage cell
-- as a consequence message interacting with the contract storage will always need to read and decode the entire contract storage struct
-- .. which may be what you want or not
-
----
-
-## Storage: Packed Layout
-
-```rust [1-4,7]
-use ink::storage::traits::{
-    StorageKey,
-    ManualKey,
-};
-
-#[ink(storage)]
-pub struct Flipper<KEY: StorageKey = ManualKey<0xcafebabe>> {
-    value: bool,
-}
-```
-
-- The storage key of the contracts root storage struct defaults to `0x00000000`
-- However you may store it under any arbitrary 4 bytes key instead
-
----
-
-## Storage: Packed Layout
-
-<div style="font-size: 0.82em;">
-
-```json
-"storage": {
-  "root": {
-    "layout": {
-      "struct": {
-        "fields": [
-          {
-            "layout": {
-              "leaf": {
-                "key": "0xcafebabe",
-                "ty": 0
-              }
-            },
-            "name": "value"
-          }
-        ],
-        "name": "Flipper"
-      }
-    },
-    "root_key": "0xcafebabe"
-  }
-}
-```
-
-</div>
-
-Notes:
-
-- demonstration of the packed layout - value is stored under the root key
-
----
-
-## Storage: Un-packed Layout
-
-```rust [1,7-8]
-use ink::storage::Mapping;
-
-#[ink(storage)]
-#[derive(Default)]
-pub struct Token {
-    total_supply: Balance,
-    balances: Mapping<AccountId, Balance>,
-    allowances: Mapping<(AccountId, AccountId), Balance>,
-}
-```
-
-- Mapping consists of a key-value pairs stored directly in the contract storage cells.
-- Each Mapping value lives under it's own storage key.
-- Mapping values do not have a contiguous storage layout: **it is not possible to iterate over the contents of a map!**
-
-Notes:
-
-- Use Mapping when you need to store a lot of values of the same type.
-- if your message only accesses a single key of a Mapping, it will not load the whole mapping but only the value being accessed.
-- there are other collection types in ink!: HashMap or BTreeMap (to name a few).
-  - these data structures are all Packed, unlike Mapping!
-
----
-
-## Storage: working with `Mapping`
-
-```rust
-pub fn transfer(&mut self) {
-    let caller = self.env().caller();
-
-    let balance = self.balances.get(caller).unwrap_or(0);
-    let endowment = self.env().transferred_value();
-
-    balance += endowment;
-}
-```
-
-- what is wrong here?
-
-Notes:
-
-- working with mapping:
-- Answer: Mapping::get() method will result in an owned value (a local copy), as opposed to a direct reference into the storage.
-  Changes to this value won't be reflected in the contract's storage "automatically".
-  To avoid this common pitfall, the value must be inserted again at the same key after it was modified.
-  The transfer function from above example illustrates this:
-
----
-
-## Storage: working with `Mapping`
-
-```rust
-pub fn transfer(&mut self) {
-    let caller = self.env().caller();
-
-    let balance = self.balances.get(caller).unwrap_or(0);
-    let endowment = self.env().transferred_value();
-
-    self.balances.insert(caller, &(balance + endowment));
-}
-```
-
-- `Mapping::get()` returns a local copy, not a mutable reference to the storage!
-
-Notes:
-
-- working with mapping:
-- `Mapping::get()` method will result in an owned value (a local copy).
-- Changes to this value won't be reflected in the contract's storage at all!
-- you need to inserted it again at the same key.
-
----
-
-## Storage: Lazy
-
-```rust [1,5]
-use ink::storage::{traits::ManualKey, Lazy, Mapping};
-
-#[ink(storage)]
-pub struct Roulette {
-    pub data: Lazy<Data, ManualKey<0x44415441>>,
-    pub bets: Mapping<u32, Bet, ManualKey<0x42455453>>,
-}
-```
-
-- Every type wrapped in `Lazy` has a separate storage cell.
-- `ManualKey` assignes explicit storage key to it.
-- Why would you want to use a `ManualKey` instead of a generated one?
-
-Notes:
-
-- packed layout can get problematic if we're storing a large collection in the contracts storage that most of the transactions do not need access too
-- there is a 16kb hard limit on a buffer used for decoding, contract trying to decode more will trap / revert
-- lazy provides per-cell access, like a mapping
-- lazy storage cell can be auto-assigned or chosen manually
-- using ManualKey instead of AutoKey might be especially desirable for upgradable contracts, as using AutoKey might result in a different storage key for the same field in a newer version of the contract.
-  - This may break your contract after an upgrade!
-
----
-
-## Storage: Lazy
-
-<img rounded style="width: 1000px;" src="./img/storage-layout.svg" />
-
-Notes:
-
-- only the pointer (the key) to the lazy type is stored under the root key.
-- only when there is a read of `d` will the pointer be de-referenced and it's value decoded.
-- lazy is a bit of a mis-nomer here, because storage is already initialized.
-
----
-
-## Contracts upgradeability: `set_code_hash`
-
-```rust [3]
-#[ink(message)]
-pub fn set_code(&mut self, code_hash: [u8; 32]) -> Result<()> {
-    ink::env::set_code_hash(&code_hash)?;
-    Ok(())
-}
-```
-
-- Within SC's lifecycle it is often necessary to perform an upgrade or a bugfix.
-- Contract's code and it's instance are separated.
-- Contract's address can be updated to point to a different code stored on-chain.
-
-Notes:
-
-- append only != immutable
-- proxy pattern known from e.g. solidity is still possible
-- within the Substrate framework contract's code is stored on-chain and it's instance is a pointer to that code
-- incentivizes cleaning up after oneself
-- big storage optimization
-
----
-
-## Contracts upgradeability: access control
-
-```rust [3]
-#[ink(message)]
-pub fn set_code(&mut self, code_hash: [u8; 32]) -> Result<()> {
-    ensure_owner(self.env().caller())?;
-    ink::env::set_code_hash(&code_hash)?;
-    Ok(())
-}
-```
-
-Notes:
-
-- you DO NOT want to leave this message un-guarded
-- solutions to `ensure_owner` can range from a very simple ones address checks
-- to a multiple-role database of access controlled accounts stored and maintained in a separate contract
-
----
-
-## Upgradeability: storage
-
-<div style="font-size: 0.72em;">
-
-```rust [1-4,6-10|1-4,12-16|18-21|23-26]
-#[ink(message)]
-pub fn get_values(&self) -> (u32, bool) {
-    (self.x, self.y)
-}
-
-#[ink(storage)]
-pub struct MyContractOld {
-    x: u32,
-    y: bool,
-}
-
-#[ink(storage)]
-pub struct MyContractNew {
-    y: bool,
-    x: u32,
-}
-```
-
-</div>
-
-- Make sure your updated code is compatible with the existing contracts state.
-- Will the getter work with the new definition and the old storage ?
-
-Notes:
-
-- Various potential changes that can result in backwards incompatibility:
-  - Changing the order of variables
-  - Introducing new variable(s) before any of the existing ones
-  - Changing variable type(s)
-  - Removing variables
-- Answer: no, SCALE encoding is oblivious to names, only order matters
-
----
-
-## Upgradeability: storage migrations
-
-<div style="font-size: 0.82em;">
-
-```rust [1-13|15-17]
-// new contract code
-#[ink(message)]
-pub fn migrate(&mut self) -> Result<()> {
-    if let Some(OldContractState { field_1, field_2 }) = get_contract_storage(&123)? {
-        self.updated_old_state.set(&UpdatedOldState {
-            field_1: field_2,
-            field_2: field_1,
-        });
-        return Ok(());
-    }
-
-    return Err(Error::MigrationFailed);
-}
-
-// old contract code
-#[ink(message)]
-pub fn set_code(&mut self, code_hash: [u8; 32], callback: Option<Selector>)
-```
-
-</div>
-
-Notes:
-
-- if the new contract code does not match the stored state you can perform a storage migration
-- think of regular relational DB and schema migrations
-- a good pattern to follow is to perform the update and the migration in one atomic transaction:
-  - if anything fails whole tx is reverted
-  - won't end up in a broken state
-  - make sure it can fit into one block!
-
----
-
-## Common Vulnerabilities
-
-```rust
-impl MyContract {
-
-  #[ink(message)]
-  pub fn terminate(&mut self) -> Result<()> {
-      let caller = self.env().caller();
-      self.env().terminate_contract(caller)
-  }
-
-  ...
-}
-```
-
-- What is wrong with this contract?
-- How would you fix it?
-
-Notes:
-
-- we start easy
-- answer: no AC in place
-- parity wallet 150 million `hack`
-
----
-
-## Common Vulnerabilities: blast from the past
-
-<img rounded style="width: 900px;" src="./img/anyone_can_kill_it.jpg" />
-
-<div style="font-size: 0.72em;">
-
-- [Details](https://github.com/openethereum/parity-ethereum/issues/6995) of the exploit:
-- <https://etherscan.io/address/0x863df6bfa4469f3ead0be8f9f2aae51c91a907b4#code>
-
-<!-- ```solidity -->
-<!-- function kill(address _to) onlymanyowners(sha3(msg.data)) external { -->
-<!--   suicide(_to); -->
-<!-- } -->
-
-<!-- function initMultiowned(address[] _owners, uint _required) only_uninitialized { -->
-<!--   m_numOwners = _owners.length + 1; -->
-<!--   m_owners[1] = uint(msg.sender); -->
-<!--   m_ownerIndex[uint(msg.sender)] = 1; -->
-<!--   for (uint i = 0; i < _owners.length; ++i) -->
-<!--   { -->
-<!--     m_owners[2 + i] = uint(_owners[i]); -->
-<!--     m_ownerIndex[uint(_owners[i])] = 2 + i; -->
-<!--   } -->
-<!--   m_required = _required; -->
-<!-- } -->
-<!-- ``` -->
-
-</div>
-
-Notes:
-
-- might seem trivial but a very similar hack has happend in the past trapping a lot of funds
-- see: <https://etherscan.io/address/0x863df6bfa4469f3ead0be8f9f2aae51c91a907b4#code>
-- hacker has "accidentally" called an unprotected `initMultiowned` and proceeded to delete the contract code
-
----
-
-## Common Vulnerabilities
-
-```rust [3,8,12-14]
-    #[ink(storage)]
-    pub struct SubstrateNameSystem {
-        registry: Mapping<AccountId, Vec<u8>>,
-    }
-
-    impl SubstrateNameSystem {
-        #[ink(message, payable)]
-        pub fn register(&mut self, name: Vec<u8>) {
-            let owner = self.env().caller();
-            let fee = self.env().transferred_value();
-
-            if !self.registry.contains(owner) && fee >= 100 {
-                self.registry.insert(owner, &name);
-            }
-        }
-```
-
-- On-chain domain name registry with a register fee of 100 pico.
-- Why is this a bad idea?
-
-Notes:
-
-- everything on-chain is public
-- this will be front-run in no time
-- Can you propose a better design?
-- Answer: commit / reveal or an auction
-
----
-
-## Common Vulnerabilities
-
-<div style="font-size: 0.72em;">
-
-```rust [3-7,12,18]
-#[ink(message)]
-pub fn swap(
-    &mut self,
-    token_in: AccountId,
-    token_out: AccountId,
-    amount_token_in: Balance,
-) -> Result<(), DexError> {
-    let this = self.env().account_id();
-    let caller = self.env().caller();
-
-    let amount_token_out = self.out_given_in(token_in, token_out, amount_token_in)?;
-
-    // transfer token_in from user to the contract
-    self.transfer_from_tx(token_in, caller, this, amount_token_in)?;
-
-    // transfer token_out from contract to user
-    self.transfer_tx(token_out, caller, amount_token_out)?;
-    ...
-}
-```
-
-</div>
-
-- Contract is a <font color="#8d3aed">DEX</font> <font color="#8d3aed">D</font>ecentralized <font color="#8d3aed">EX</font>change, follows the popular <font color="#8d3aed">AMM</font> (<font color="#8d3aed">A</font>utomated <font color="#8d3aed">M</font>arket <font color="#8d3aed">M</font>aker) design.
-- Tx swaps the specified amount of one of the pool's PSP22 tokens to another PSP22 token according to the current price.
-- What can go wrong here?
-
-Notes:
-
-Answer:
-
-- no slippage protection in place.
-- bot will frontrun the victim's tx by purchasing token_out before the trade is executed.
-- this purchase will raise the price of the asset for the victim trader and increases his slippage
-- if the bot sells right after the victims tx (back runs the victim) this is a sandwich attack
-
----
-
-## Common Vulnerabilities
-
-```rust [7,12-14]
-#[ink(message)]
-pub fn swap(
-    &mut self,
-    token_in: AccountId,
-    token_out: AccountId,
-    amount_token_in: Balance,
-    min_amount_token_out: Balance,
-) -> Result<(), DexError> {
-
-    ...
-
-    if amount_token_out < min_amount_token_out {
-        return Err(DexError::TooMuchSlippage);
-    }
-
-...
-}
-```
-
-Notes:
-
-- slippage protection in place
-
----
-
-## Common Vulnerabilities
-
-- Integer overflows
-- Re-entrancy vulnerabilities
-- Sybil attacks
-- ...
-- Regulatory attacks 😅
-- ...
-
-Notes:
-
-- long list of possible attacks
-- too long to fit into one lecture
-- baseline: get an audit from a respectable firm
-- publish your source code (security by obscurity is not security)
-
----
-
-## Pause
-
-Optional challenge: [github.com/Polkadot-Blockchain-Academy/adder](https://github.com/Polkadot-Blockchain-Academy/ink-adder)
-
-Notes:
-
-Piotr takes over to talk about making runtime calls from contracts and writing automated tests.
-There is a 15 minute challenge for you in the meantime.
-
----
-
-## Interacting with the execution environment
-
-```rust [5-6]
-impl MyContract {
-  ...
-  #[ink(message)]
-  pub fn terminate(&mut self) -> Result<()> {
-      let caller = self.env().caller();
-      self.env().terminate_contract(caller)
-  }
-  ...
-}
-```
-
----
-
-## Blockchain node onion
-
----
-
-## Blockchain node onion
-
-<br />
-
-<img style="margin-top: 50px;margin-bottom: 50px" width="800" src="./img/onions.png" />
-
----
-
-## Blockchain node onion
-
-<img style="margin-top: 10px" width="600" src="./img/blockchain-onion-1.svg" />
-
-- networking
-- block production, dissemination, finalization
-- storage management
-- off-chain maintenance, querying, indexing
-
----
-
-## Blockchain node onion
-
-<img style="margin-top: 50px;margin-bottom: 50px" width="800" src="./img/blockchain-onion-2.svg" />
-
-- computing new state based on the previous one and a single transaction
-
----
-
-## Blockchain node onion
-
-<img style="margin-top: 100px;margin-bottom: 50px" width="800" src="./img/blockchain-onion-3.svg" />
-
-- executing contract calls
-
----
-
-## Standard API
-
-- `caller()`
-- `account_id()`
-- `balance()`
-- `block_number()`
-- `emit_event(event: Event)`
-- `transfer(dest: AccountId, value: Balance)`
-- `hash_bytes(input: &[u8], output: &mut [u8])`
-- `debug_message(msg: &str)`
-- [_and many more_](https://docs.rs/ink_env/4.2.1/ink_env/index.html#functions)
-
----
-
-## Standard API
-
-```rust
-impl MyContract {
-  ...
-  #[ink(message)]
-  pub fn terminate(&mut self) -> Result<()> {
-      let caller = self.env().caller();
-      self.env().terminate_contract(caller)
-  }
-  ...
-}
-```
-
----
-
-## Interacting with the state transition function
-
-<br />
-
-<div class="flex-container fragment">
-<div class="left">
-<div style="text-align: center"> <center><h2><pre> User API </pre></h2></center> </div>
-
-<ul>
-<li>token transfer</li>
-<li>staking</li>
-<li>voting</li>
-<li>contract call</li>
-<li>...</li>
-</ul>
-</div>
-
-<div class="left fragment">
-<div style="text-align: center"> <center><h2><pre> Contract API </pre></h2></center> </div>
-
-<ul>
-<li>advanced cryptography</li>
-<li>bypassing standard restrictions</li>
-<li>outsourcing computation</li>
-<li>...</li>
-</ul>
-</div>
-</div>
-
----
-
-## Interacting with the state transition function
-
-<br />
-
-<div class="flex-container">
-<div class="left">
-<div style="text-align: center"> <center><h2><pre> User API </pre></h2></center> </div>
-<div style="text-align: center"> <center><h2><pre> (usually for humans) </pre></h2></center> </div>
-
-<ul>
-<li>token transfer</li>
-<li>staking</li>
-<li>voting</li>
-<li>contract call</li>
-<li>...</li>
-
-**_runtime call_**
-
-</ul>
-</div>
-
-<div class="left">
-<div style="text-align: center"> <center><h2><pre> Contract API </pre></h2></center> </div>
-<div style="text-align: center"> <center><h2><pre> (only for contracts) </pre></h2></center> </div>
-
-<ul>
-<li>advanced cryptography</li>
-<li>bypassing standard restrictions</li>
-<li>outsourcing computation</li>
-<li>...</li>
-
-<br />
-
-**_chain extension_**
-
-</ul>
-</div>
-</div>
-
----
-
-## Runtime
-
-<br />
-
-In Polkadot ecosystem _state transition function_ is called **_runtime_**
-
----
-
-## Calling runtime
-
-<br />
-
-```rust [7-10]
-#[ink(message)]
-pub fn transfer_through_runtime(
-    &mut self,
-    receiver: AccountId,
-    value: Balance,
-) -> Result<(), RuntimeError> {
-    let call_object = RuntimeCall::Balances(BalancesCall::Transfer {
-        receiver,
-        value,
-    });
-
-    self.env().call_runtime(&call_object)
-}
-```
-
----
-
-## Calling runtime
-
-<br />
-
-```rust [12]
-#[ink(message)]
-pub fn transfer_through_runtime(
-    &mut self,
-    receiver: AccountId,
-    value: Balance,
-) -> Result<(), RuntimeError> {
-    let call_object = RuntimeCall::Balances(BalancesCall::Transfer {
-        receiver,
-        value,
-    });
-
-    self.env().call_runtime(&call_object)
-}
-```
-
----
-
-## Chain extensions
-
-<br />
-
-Chain extension is a way to extend the runtime with custom functionalities _dedicated to contracts_.
-
----
-
-## Chain extensions
-
-<br />
-
-**ink! side:**
-
-- provide `ChainExtension` trait
-- include extension in the `Environment` trait instantiation
-
-<br />
-
-**runtime side:**
-
-- handling extension calls
-- extension logic itself
-
----
-
-## Provide `ChainExtension` trait
-
-```rust [1-7]
-#[ink::chain_extension]
-pub trait OutsourceHeavyCrypto {
-  type ErrorCode = OutsourcingErr;
-
-  #[ink(extension = 41)]
-  fn outsource(input: Vec<u8>) -> [u8; 32];
-}
-
-pub enum OutsourcingErr {
-  IncorrectData,
-}
-
-impl ink::env::chain_extension::FromStatusCode for OutsourcingErr {
-  fn from_status_code(status_code: u32) -> Result<(), Self> {
-    match status_code {
-      0 => Ok(()),
-      1 => Err(Self::IncorrectData),
-      _ => panic!("encountered unknown status code"),
-    }
-  }
-}
-```
-
----
-
-## Provide `ChainExtension` trait
-
-```rust [9-21]
-#[ink::chain_extension]
-pub trait OutsourceHeavyCrypto {
-  type ErrorCode = OutsourcingErr;
-
-  #[ink(extension = 41)]
-  fn outsource(input: Vec<u8>) -> [u8; 32];
-}
-
-pub enum OutsourcingErr {
-  IncorrectData,
-}
-
-impl ink::env::chain_extension::FromStatusCode for OutsourcingErr {
-  fn from_status_code(status_code: u32) -> Result<(), Self> {
-    match status_code {
-      0 => Ok(()),
-      1 => Err(Self::IncorrectData),
-      _ => panic!("encountered unknown status code"),
-    }
-  }
-}
-```
-
----
-
-## Include extension in the `Environment` trait instantiation
-
-<br />
-
-```rust
-pub enum EnvironmentWithOutsourcing {}
-impl Environment for EnvironmentWithOutsourcing {
-    ... // use defaults from `DefaultEnvironment`
-    type ChainExtension = OutsourceHeavyCrypto;
-}
-
-#[ink::contract(env = crate::EnvironmentWithOutsourcing)]
-mod my_contract {
-  ...
-}
-```
-
----
-
-## Include extension in the `Environment` trait instantiation
-
-<br />
-
-```rust
-#[ink::contract(env = crate::EnvironmentWithOutsourcing)]
-mod my_contract {
-  fn process_data(&mut self, input: Vec<u8>) -> Result<(), OutsourcingErr> {
-    self.env().extension().outsource(subject)
-  }
-}
-```
-
----
-
-## Handling extension calls
-
-<br />
-
-```rust [5-11]
-pub struct HeavyCryptoOutsourcingExtension;
-
-impl ChainExtension<Runtime> for HeavyCryptoOutsourcingExtension {
-  fn call<E: Ext>(&mut self, env: Env) -> Result<RetVal, DispatchError> {
-    match env.func_id() {
-      41 => internal_logic(),
-      _ => {
-        error!("Called an unregistered `func_id`: {func_id}");
-        return Err(DispatchError::Other("Unimplemented func_id"))
-      }
-    }
-    Ok(RetVal::Converging(0))
-}
-```
-
----
-
-## Chain extension: reaching even further
-
-<img style="margin-top: 100px;margin-bottom: 50px" width="800" src="./img/chain-extension-reach.svg" />
-
----
-
-## Testing contracts
-
----
-
-## Testing contracts
-
-<br />
-
-<img style="margin-top: 100px;margin-bottom: 50px" width="800" src="./img/blockchain-onion-3.svg" />
-
----
-
-## Testing contracts
-
-<img style="margin-top: 100px;margin-bottom: 50px" width="1000" src="./img/testing-contract-stack.svg" />
-
----
-
-## Unit tests
-
-<br />
-
-```rust [1-3]
-#[ink::test]
-fn erc20_transfer_works() {
-  let mut erc20 = Erc20::new(100);
-
-  assert_eq!(erc20.balance_of(BOB), 0);
-  // Alice transfers 10 tokens to Bob.
-  assert_eq!(erc20.transfer(BOB, 10), Ok(()));
-  // Bob owns 10 tokens.
-  assert_eq!(erc20.balance_of(BOB), 10);
-
-  let emitted_events = ink::env::test::recorded_events().collect::<Vec<_>>();
-  assert_eq!(emitted_events.len(), 2);
-
-  // Check first transfer event related to ERC-20 instantiation.
-  assert_transfer_event(
-    &emitted_events[0], None, Some(ALICE), 100,
-  );
-  // Check the second transfer event relating to the actual transfer.
-  assert_transfer_event(
-    &emitted_events[1], Some(ALICE), Some(BOB), 10,
-  );
-}
-```
-
----
-
-## Unit tests
-
-<br />
-
-```rust [5-9]
-#[ink::test]
-fn erc20_transfer_works() {
-  let mut erc20 = Erc20::new(100);
-
-  assert_eq!(erc20.balance_of(BOB), 0);
-  // Alice transfers 10 tokens to Bob.
-  assert_eq!(erc20.transfer(BOB, 10), Ok(()));
-  // Bob owns 10 tokens.
-  assert_eq!(erc20.balance_of(BOB), 10);
-
-  let emitted_events = ink::env::test::recorded_events().collect::<Vec<_>>();
-  assert_eq!(emitted_events.len(), 2);
-
-  // Check first transfer event related to ERC-20 instantiation.
-  assert_transfer_event(
-    &emitted_events[0], None, Some(ALICE), 100,
-  );
-  // Check the second transfer event relating to the actual transfer.
-  assert_transfer_event(
-    &emitted_events[1], Some(ALICE), Some(BOB), 10,
-  );
-}
-```
-
----
-
-## Unit tests
-
-<br />
-
-```rust [11-22]
-#[ink::test]
-fn erc20_transfer_works() {
-  let mut erc20 = Erc20::new(100);
-
-  assert_eq!(erc20.balance_of(BOB), 0);
-  // Alice transfers 10 tokens to Bob.
-  assert_eq!(erc20.transfer(BOB, 10), Ok(()));
-  // Bob owns 10 tokens.
-  assert_eq!(erc20.balance_of(BOB), 10);
-
-  let emitted_events = ink::env::test::recorded_events().collect::<Vec<_>>();
-  assert_eq!(emitted_events.len(), 2);
-
-  // Check first transfer event related to ERC-20 instantiation.
-  assert_transfer_event(
-    &emitted_events[0], None, Some(ALICE), 100,
-  );
-  // Check the second transfer event relating to the actual transfer.
-  assert_transfer_event(
-    &emitted_events[1], Some(ALICE), Some(BOB), 10,
-  );
-}
-```
-
----
-
-## E2E tests
-
-<br />
-
-```rust [1-7]
-#[ink_e2e::test]
-async fn e2e_transfer(mut client: ink_e2e::Client<C, E>) -> E2EResult<()> {
-  let constructor = Erc20Ref::new(total_supply);
-  let erc20 = client
-          .instantiate("erc20", &ink_e2e::alice(), constructor, 0, None)
-          .await
-          .expect("instantiate failed");
-
-  let mut call = erc20.call::<Erc20>();
-  let total_supply_msg = call.total_supply();
-  let total_supply_res = client
-          .call_dry_run(&ink_e2e::bob(), &total_supply_msg, 0, None)
-          .await;
-  ...
-}
-```
-
----
-
-## E2E tests
-
-<br />
-
-```rust [9-13]
-#[ink_e2e::test]
-async fn e2e_transfer(mut client: ink_e2e::Client<C, E>) -> E2EResult<()> {
-  let constructor = Erc20Ref::new(total_supply);
-  let erc20 = client
-          .instantiate("erc20", &ink_e2e::alice(), constructor, 0, None)
-          .await
-          .expect("instantiate failed");
-
-  let mut call = erc20.call::<Erc20>();
-  let total_supply_msg = call.total_supply();
-  let total_supply_res = client
-          .call_dry_run(&ink_e2e::bob(), &total_supply_msg, 0, None)
-          .await;
-  ...
-}
-```
-
----
-
-## E2E tests
-
-<br />
-
-```rust [14]
-#[ink_e2e::test]
-async fn e2e_transfer(mut client: ink_e2e::Client<C, E>) -> E2EResult<()> {
-  let constructor = Erc20Ref::new(total_supply);
-  let erc20 = client
-          .instantiate("erc20", &ink_e2e::alice(), constructor, 0, None)
-          .await
-          .expect("instantiate failed");
-
-  let mut call = erc20.call::<Erc20>();
-  let total_supply_msg = call.total_supply();
-  let total_supply_res = client
-          .call_dry_run(&ink_e2e::bob(), &total_supply_msg, 0, None)
-          .await;
-  ...
-}
-```
-
----
-
-## E2E pipeline: traps, traps everywhere
-
-<div style="font-size: 0.6em">
-
-1. Preparing and encoding transaction data (_client side_)
-1. Signing the transaction (_client side_)
-1. Sending transaction to a node (_client side_)
-1. Block and event subscribing (_client side_)
-1. Transaction pool processing (_node side_)
-1. Block building (_node side_)
-1. Block dissemination (_node side_)
-1. Import queue processing (_node side_)
-1. Block finalizing (_node side_)
-1. Block execution (_node side_)
-1. Transaction execution (_runtime side_)
-1. Event emitting (_node side_)
-1. Event capturing (_client side_)
-1. Event processing (_client side_)
-1. State fetching via RPC calling (_client side_)
-1. State report (_node side_)
-1. State validation (_client side_)
-
-</div>
-
----
-
-## E2E pipeline: traps, traps everywhere
-
-<img style="margin-top: 100px;margin-bottom: 50px" width="800" src="./img/trap.gif" />
-
----
-
-## Test core
-
-<br />
-
-1. Preparing and encoding transaction data (_given_)
-1. Transaction execution (_when_)
-1. State validation (_then_)
-
----
-
-## quasi-E2E tests
-
-<br />
-
-Interact directly with runtime, skipping node layer.
-
----
-
-## quasi-E2E tests
-
-<br />
-
-```rust
-#[test]
-fn flipping() -> Result<(), Box<dyn Error>> {
-  let init_value = Session::<MinimalRuntime>::new(transcoder())?
-      .deploy_and(bytes(), "new", &["true".to_string()], vec![])?
-      .call_and("flip", &[])?
-      .call_and("flip", &[])?
-      .call_and("flip", &[])?
-      .call_and("get", &[])?
-      .last_call_return()
-      .expect("Call was successful");
-
-  assert_eq!(init_value, ok(Value::Bool(false)));
-
-  Ok(())
-}
-```
-
----
-
-## Local playing with contracts using `drink-cli`
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-# EVM, Solidity, and Vyper
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/languages/slides.md b/content/blockchain-contracts/languages/slides.md
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----
-title: EVM, Solidity, and Vyper
-description: Overview and history of the EVM and languages that compile to it.
-  Focus on architecting real-world smart contracts.
----
-
-# EVM, Solidity, and Vyper
-
----
-
-## EVM
-
-**Ethereum Virtual Machine**
-
-A VM designed specifically for the constraints and features of Ethereum
-
----
-
-## EVM Properties
-
-- Deterministic: execution outcome easy to agree upon
-- Spam-resistant: CPU and other resources are metered at a very granular level
-- Turing-complete (with a caveat)
-- Stack-based design
-- Ethereum-specific (EVM can query block hash, accounts and balances, etc.)
-
-Notes:
-
-It is critical that the EVM be 100% deterministic and that each implementation
-produce the same outcome.
-Even the smallest discrepancy between two running
-nodes would lead to different block hashes, violating consensus about the
-results.
-
----
-
-## History of Ethereum
-
-<pba-flex center>
-
-- Nov 2013: Vitalik released WP
-- Apr 2014: Gav released YP
-- July 2014: $18M raised (ICO lasted 42 days)
-- July 2015: Frontier released -- bare bones, Proof of Work
-- Sept 2015: Frontier "thawed", difficulty bomb introduced
-- July 2016: DAO Fork
-- 2016-2019: Optimizations, opcode cost tuning, difficulty bomb delays
-- 2020: Staking contract deployed, Beacon Chain launched
-- 2021: EIP-1559, prep for The Merge
-- 2022: The Merge (Proof of Stake)
-- 2023: Staking withdraw support
-
-</pba-flex>
-
----v
-
-## DAO Hack
-
-1. 2016: raised $150M worth of ETH
-1. Later that year: 3.6M ETH drained
-1. Reentrancy attack
-1. "Mainnet" Ethereum forks to retroactively undo hack
-1. Ethereum Classic: code is law
-
-Notes:
-
-A DAO ("Decentralized Autonomous Organization") is much like a business entity run by code rather than by humans.
-Like any other business entity, it has assets and can carry out operations, but its legal status is unclear.
-
-The earliest DAO ("The DAO") on Ethereum suffered a catastrophic hack due to a bug in its code.
-The DAO community disagreed on whether or not to hard-fork and revert the hack, resulting in Ethereum splitting into two different chains.
-
----v
-
-## The first smart contracting platform
-
-Ethereum has faced many challenges as the pioneer of smart contracts.
-
-- Performance: Underpriced opcodes have been attacked as a spam or DoS vector
-- High gas fees: Overwhelming demand low block-space supply
-- Frontrunning: Inserting transactions before, after, or in place of others in order to economically benefit
-- Hacks: Many hacks have exploited smart contract vulnerabilities
-- Problems with aggregating smart contract protocols together
-- Storage bloat: Misaligned incentives with burden of storage
-
----v
-
-## Idiosyncrasies
-
-- Everything is 256bits
-- No floating point arithmetic
-- Revert
-- Reentrancy
-- Exponential memory expansion cost
-
----
-
-## Gas
-
-> Turing completeness and the Halting Problem
-
-- EVM: Turing-complete instruction set
-
-- But what about the Halting Problem?
-- Obviously cannot allow infinite loops
-- Solution: Gasometer, a way to pre-pay for each opcode execution
-
-Notes:
-
-The Halting Problem tells us that it's not possible to know that an arbitrary program will properly stop.
-To prevent such abuse, we check that there is gas remaining before every single opcode execution.
-Since gas is limited, this ensures that no EVM execution will run forever and that all work performed is properly paid for.
-
----v
-
-## Gasometer
-
-<img style="width: 1200px" src="./img/GasometerDiagram.png" />
-
-- Checks before each opcode to make sure gas can be paid
-- Safe: prevents unpaid work from being done
-- Deterministic: results are unambiguous
-- Very inefficient: lots of branching and extra work
-
-Notes:
-
-This not only makes it possible to prevent abuse, but crucially allows nodes to agree on doing so.
-A centralized service could easily impose a time limit, but decentralized nodes wouldn't be able to agree on the outcome of such a limit (or trust each other).
-
----v
-
-## Gas limits and prices
-
-Gas: unit of account for EVM execution resources.
-
-- `gas_limit`: specifies the maximum amount of gas a txn can pay
-- `gas_price`: specifies the exact price a txn will pay per gas
-
-A txn _must_ be able to pay `gas_limit * gas_price` in order to be valid.
-
-Notes:
-
-This amount is initially deducted from the txn's sender account and any remaining gas is refunded after the txn has executed.
-
----v
-
-## EIP-1559
-
-An improvement to gas pricing mechanism.
-
-```
-gas_price --> max_base_fee_per_gas
-          \-> max_priority_fee_per_gas
-```
-
-<!-- FIXME TODO mermaid or img for above -->
-
-- Separates tip from gas price
-- `base_fee` is an algorithmic gas price, this is exactly what is paid and is burned
-- ...plus maybe tip if (`base_fee < max_base_fee + max_priority_fee`)
-- Algorithmic, congestion-based multiplier controls `base_fee`
-
-Notes:
-
-<https://eips.ethereum.org/EIPS/eip-1559>
-Introduced in London hard-fork.
-
----v
-
-## OOG and Gas Estimation
-
-If a txn exhausts its `gas_limit` without finishing, it will produce an OOG (out-of-gas) error and all changes made in the EVM are reverted (except for fee payment).
-
-In order to estimate the amount of gas a txn will need, an RPC method (`eth_estimateGas`) can perform a dry-run of the txn and record the amount used.
-
-However, there are a few caveats:
-
-- Run against current state (state may change)
-- The RPC node could lie to you
-- This is expensive infrastructure overhead and can be a spam vector
-
----
-
-## Account Types
-
-There are two types of Ethereum accounts.
-Both use 160-bit account IDs and can hold and send Ether, but they are controlled very differently.
-
----v
-
-## Account Types
-
-<pba-cols>
-<pba-col>
-
-**Externally-owned Account (EOA)**
-
-- Traditional user-controlled account
-- Controlled via private keys
-- Account ID generated by hashing public key
-- Uses an incrementing nonce to prevent replay attacks
-
-</pba-col>
-<pba-col>
-
-**Contract Account**
-
-- Controlled by immutable bytecode
-- May only ever do precisely what the code specifies
-- Account ID generated deterministically when bytecode is deployed
-
-</pba-col>
-</pba-cols>
-
----
-
-## Transactions
-
-A transaction is a signed payload from an EoA which contains details about what the transaction should do and how it will pay for itself.
-
----v
-
-## Transactions fields:
-
-- **value**: 0 or more Ether to send with the txn
-- **to**: the target of this transaction
-- **input**: Optional input data for creating or calling a contract
-- **gas_limit**: Max gas the txn will pay
-- **gas_price**: (or EIP-1559 equivalent)
-- **nonce**: prevents replay attacks and forces ordering
-- **signature**: proves ownership of private keys, allows receiving Account ID
-- _there can be more_
-
----v
-
-## Possible use-cases:
-
-- Call a contract's external function (`input` specifies function and arguments)
-- Create a contract (`input` specifies contract's bytecode)
-- Neither (`input` empty)
-
-In all cases, Ether can be sent (`Neither` being a normal Ether send).
-
----v
-
-## Transaction Validity
-
-Before executing (or gossiping) txns, some validity checks should be run:
-
-- Is the `gas_limit` sufficient? (`21_000` minimum at least pays for processing)
-- Is the signature valid? (Side effect: public key recovered)
-- Can the account pay for `gas_limit * gas_price`?
-- Is this a valid (and reasonable) nonce for the account?
-
-Notes:
-
-These checks come with overhead, so it's important to discard invalid txns as quickly as possible if it is invalid.
-This includes not gossiping it to peers, who have to also verify it.
-
----
-
-## Opcodes and Bytecode
-
-An opcode is a single byte which represents an instruction for the VM to execute.
-
-The EVM executes bytecode one opcode at a time until it is done, explicitly halts, or the gasometer runs out of gas.
-
-Notes:
-
-Functions compile down into a sequence of opcodes, which we call bytecode.
-This bytecode is bundled together and becomes the on-chain contract code.
-
----
-
-## ABI
-
-ABI ("Application Binary Interface") describes the bytecode for a contract by annotating where functions and other objects exist and how they are formatted.
-
----v
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Exercise
-
-Review this [Contract Code on Etherscan](https://etherscan.io/token/0x1f9840a85d5af5bf1d1762f925bdaddc4201f984?a=0xd0fc8ba7e267f2bc56044a7715a489d851dc6d78#code)
-
----v
-
-## Sandboxed Contract State
-
-`Contract Account`s contain a sandboxed state, which stores everything that the
-contract writes to storage.
-Contracts may not write to storage outside of their own sandbox, but they can call other contracts whose bytecode _might_ write to their respective storage.
-
----v
-
-## Calling Contracts
-
-Contract functions can be invoked in two ways different ways:
-
-- EoAs can call a contract functions directly
-- Contracts can call other contracts (called "messaging")
-
----v
-
-## Types of contract messaging
-
-- Normal `call`: Another contract is called and can change its own state
-- `staticcall`: A "safe" way to call another contract with no state changes
-- `delegatecall`: A way to call another contract but modify our state instead
-
-Notes:
-
-Transactions are the only means through which state changes happen.
-
----v
-
-## Message Object
-
-Within the context of a contract call, we always have the `msg` object, which lets us know how we were called.
-
-```
-msg.data (bytes): complete calldata (input data) of call
-msg.gas (uint256): available gas
-msg.sender (address): sender of the current message
-msg.sig (bytes4) first 4 bytes of calldata (function signature)
-msg.value (uint256) amount of Ether sent with this call
-```
-
----v
-
-## Ether Denominations
-
-Ether is stored and operated on through integer math.
-In order to avoid the complication of decimal math, it's stored as a very small integer: `Wei`.
-
-```
-1 Ether = 1_000_000_000_000_000_000 Wei (10^18)
-```
-
-Notes:
-
-Integer math with such insignificant units mostly avoids truncation issues and makes it easy to agree on outcomes.
-
----v
-
-## Named Denominations
-
-Other denominations have been officially named, but aren't as often used:
-
-```
-wei                 = 1 wei
-kwei (babbage)      = 1_000 wei
-mwei (lovelace)     = 1_000_000 wei
-gwei (shannon)      = 1_000_000_000 wei
-microether (szabo)  = 1_000_000_000_000 wei
-milliether (finney) = 1_000_000_000_000_000 wei
-ether               = 1_000_000_000_000_000_000 wei
-```
-
-`gwei` is often used when talking about gas.
-
----
-
-## Programming the EVM
-
-The EVM is ultimately programmed by creating bytecode.
-While it is possible to write bytecode by hand or through low-level assembly language, it is much more practical to use a higher-level language.
-We will look at two in particular:
-
-<pba-flex center>
-
-- Solidity
-- Vyper
-
-</pba-flex>
-
----
-
-## Solidity
-
-<pba-flex center>
-
-- Designed for EVM
-- Similar to C++, Java, etc.
-- Includes inheritance (including MI)
-- Criticized for being difficult to reason about security
-
-</pba-flex>
-
----v
-
-## Basics
-
-```Solidity
-// 'contract' is analogous to 'class' in other OO languages
-contract Foo {
-    // the member variables of a contract are stored on-chain
-    public uint bar;
-
-    constructor(uint value) {
-        bar = value;
-    }
-}
-```
-
----v
-
-## Functions
-
-```Solidity
-contract Foo {
-    function doSomething() public returns (bool) {
-        return true;
-    }
-}
-```
-
----v
-
-## Modifiers
-
-A special function that can be run as a precondition for other functions
-
-```Solidity
-contract Foo {
-    address deployer;
-
-    constructor() {
-        deployer = msg.sender;
-    }
-
-    // ensures that only the contract deployer can call a given function
-    modifier onlyDeployer {
-        require(msg.sender == deployer);
-        _; // the original function is inserted here
-    }
-
-    function doSomeAdminThing() public onlyDeployer() {
-        // this function can only be called if onlyDeployer() passes
-    }
-}
-```
-
-Notes:
-
-Although Modifiers can be an elegant way to require preconditions, they can do
-entirely arbitrary things, and auditing code requires carefully reading them.
-
----v
-
-## Payable
-
-```Solidity
-contract Foo {
-    uint256 received;
-    // this function can be called with value (Ether) given to it.
-    // in this simple example, the contract would never do anything with
-    // the Ether (effectively meaning it would be lost), but it will faithfully
-    // track the amount paid to it
-    function deposit() public payable {
-        received += msg.value;
-    }
-}
-```
-
-Notes:
-
-The actual payment accounting is handled by the EVM automatically, we don't need
-to update our own account balance.
-
----v
-
-## Types: "Value" Types
-
-```Solidity
-contract Foo {
-    // Value types are stored in-place in memory and require
-    // a full copy during assignment.
-    function valueTypes() public {
-        bool b = false;
-
-        // signed and unsigned ints
-        int32 i = -1;
-        int256 i2 = -10000;
-        uint8 u1 = 255;
-        uint16 u2 = 10000;
-        uint256 u3 = 99999999999999;
-
-        // fixed length byte sequence (from 1 to 32 bytes)
-        // many bitwise operators can be performed on these
-        bytes1 oneByte = 0x01;
-
-        // address represents a 20-byte Ethereum address
-        address a = 0x1010101010101010101010101010101010101010;
-        uint256 balance = a.balance;
-
-        // also: Enums
-
-        // each variable is an independent copy
-        int x = 1;
-        int y = x;
-        y = 2;
-        require(x == 1);
-        require(y == 2);
-    }
-
-}
-```
-
----v
-
-## Types: "Reference" Types
-
-```Solidity
-contract Foo {
-    mapping(uint => uint) forLater;
-
-    // Reference types are stored as a reference to some other location.
-    // Only their reference must be copied during assignment.
-    function referenceTypes() public {
-        // arrays
-        uint8[3] memory arr = [1, 2, 3];
-
-        // mapping: can only be initialized from state variables
-        mapping(uint => uint) storage balances = forLater;
-        balances[0] = 500;
-
-        // dynamic length strings
-        string memory foo = "<3 Solidity";
-
-        // also: Structs
-
-        // Two or more variables can share a reference, so be careful!
-        uint8[3] memory arr2 = arr;
-        arr2[0] = 42;
-        require(arr2[0] == 42);
-        require(arr[0] == 42); // arr and arr2 are the same thing, so mod to one affects the other
-    }
-}
-```
-
----v
-
-## Data Location
-
-`Data Location` refers to the storage of `Reference Types`.
-As these are passed by reference, it effectively dictates where this reference points to.
-It can be one of 3 places:
-
-- memory: Stored only in memory; cannot outlive a given external function call
-- storage: Stored in the contract's permanent on-chain storage
-- calldata: read-only data, using this can avoid copies
-
----v
-
-## Data Location Sample
-
-```Solidity
-contract DataLocationSample {
-    struct Foo {
-        int i;
-    }
-
-    Foo storedFoo;
-
-    // Data Location specifiers affect function arguments and return values...
-    function test(Foo memory val) public returns (Foo memory) {
-        // ...and also variables within a function
-        Foo memory copy = val;
-
-        // storage variables must be assigned before use.
-        Foo storage fooFromStorage = storedFoo;
-        fooFromStorage.i = 1;
-        require(storedFoo.i == 1, "writes to storage variables affect storage");
-
-        // memory variables can be initialized from storage variables
-        // (but not the other way around)
-        copy = fooFromStorage;
-
-        // but they are an independent copy
-        copy.i = 2;
-        require(copy.i == 2);
-        require(storedFoo.i == 1, "writes to memory variables cannot affect storage");
-
-        return fooFromStorage;
-    }
-}
-```
-
----v
-
-## Enums
-
-```Solidity
-contract Foo {
-    enum Suite {
-        Hearts,
-        Diamonds,
-        Clubs,
-        Spades
-    }
-
-    function getHeartsSuite() public returns (Suite) {
-        Suite hearts = Suite.Hearts;
-        return hearts;
-    }
-}
-```
-
----v
-
-## Structs
-
-```Solidity
-contract Foo {
-    struct Ballot {
-        uint32 index;
-        string name;
-    }
-
-    function makeSomeBallot() public returns (Ballot memory) {
-        Ballot memory ballot;
-        ballot.index = 1;
-        ballot.name = "John Doe";
-        return ballot;
-    }
-}
-```
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Solidity Hands-On
-
----v
-
-## Dev Environment
-
-We will use the online [Remix IDE](https://remix.ethereum.org) for our sample coding.
-It provides an editor, compiler, EVM, and debugger all within the browser, making it trivial to get started.
-
-> <https://remix.ethereum.org>
-
----v
-
-## Flipper Example
-
-Code along and explain as you go
-
----v
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Exercise: Multiplier
-
-- Write a contract which has a `uint256` storage value
-- Write function(s) to multiply it with a user-specified value
-- Interact with it: can you force an overflow?
-
-> Overflow checks have been added to Solidity.
-> You can disable these by specifying an older compiler.
-> Add this to the very top of your `.sol` file:
->
-> ```Solidity
-> pragma solidity ^0.7.0;
-> ```
-
----v
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-#### Bonus:
-
-- Prevent your multiplier function from overflowing
-- Rewrite this prevention as a `modifier noOverflow()`
-
-> The constant `constant public MAX_INT_HEX = 0xffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff;` may be helpful.
-
----
-
-## Vyper
-
-- Also designed for the EVM
-- Similar to Python
-- Intentionally lacks some features such as inheritance
-- Auditable: "Simplicity for the reader is more important than simplicity for the writer"
-
----v
-
-## Compared to Solidity
-
-Vyper mostly lacks features found in Solidity, all in the spirit of improving
-readability.
-Some examples:
-
-- No Inheritance
-- No modifiers
-- No function overloading
-- No recursive calling (!)
-- No infinite-loops
-
----v
-
-## Basics
-
-```Python
-# There is no `contract` keyword.
-# Like Python Modules, a contract is implicitly
-# scoped by the file in which it is found.
-
-# storage variables are declared outside of any function
-bar: uint
-
-# init is used to deploy a contract and initialize its state
-@external
-def __init__(val):
-    self.bar = val
-```
-
----v
-
-## Functions
-
-```Python
-@external
-def doSomething() -> bool:
-    return True
-```
-
----v
-
-## Decorators and Payable
-
-```Python
-# Vyper contains decorators for restricting functions:
-
-@external # function can only be called externally
-@internal # function can only be called within current context
-@pure # cannot read state or environment vars
-@view # cannot alter contract state
-@payable # function may receive Ether
-
-# also, to cover the most common use case for Solidity's modifiers:
-@nonreentrant(<unique_key>) # prevents reentrancy for given id
-```
-
-Notes:
-
-source: <https://docs.vyperlang.org/en/stable/control-structures.html#decorators-reference>
-
----v
-
-## Types
-
-```Python
-# value types are small and/or fixed size and are copied
-@external
-def valueTypes():
-    b: bool = False
-
-    # signed and unsigned ints
-    i: int128 = -1
-    i2: int256 = -10000
-    u: uint128 = 42
-    u2: uint256 = 42
-
-    # fixed-point (base-10) decimal values with 10 decimal points of precision
-    # this has the advantage that literals can be precisely expressed
-    f: decimal = 0.1 + 0.3 + 0.6
-    assert f == 1.0, "decimal literals are precise!"
-
-    # address type for 20-byte Ethereum addresses
-    a: address = 0x1010101010101010101010101010101010101010
-    b = a.balance
-
-    # fixed size byte arrays
-    selector: bytes4 = 0x12345678
-
-    # bounded byte arrays
-    bytes: Bytes[123] = b"\x01"
-
-    # dynamic-length, fixed-bounds strings
-    name: String[16] = "Vyper"
-
-# reference types are potentially large and/or dynamically sized.
-# they are copied-by-reference
-@external
-def referenceTypes():
-    # fixed size list.
-    # It can also be multidimensional.
-    # all elements must be initialized
-    list: int128[4] = [1, 2, 3, -4]
-
-    # bounded, dynamic-size array.
-    # these have a max size but initialize to empty
-    dynArray: DynArray[int128, 3]
-    dynArray.append(1)
-    dynArray.append(5)
-    val: int128 = dynArray.pop() # == 5
-
-    map: HashMap[int128, int128]
-    map[0] = 0
-    map[1] = 10
-    map[2] = 20
-```
-
----v
-
-## Enums
-
-```Python
-enum Suite {
-    Hearts,
-    Diamonds,
-    Clubs,
-    Spades
-}
-
-# "hearts" would be considered a value type
-hearts: Suite = Suite.Hearts
-```
-
----v
-
-## Structs
-
-```Python
-struct Ballot:
-    index: uint256
-    name: string
-
-# "someBallot" would be considered a reference type
-someBallot: Ballot = Ballot({index: 1, name: "John Doe"})
-name: string = someBallot.name
-```
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Vyper Hands-On
-
----v
-
-## Remix Plugin
-
-Remix supports Vyper through a plugin, which can be easily enabled from within
-the IDE.
-First, search for "Vyper" in the plugins tab:
-
-<img rounded style="width: 500px;" src="./img/RemixInstallVyper1.png" />
-
----v
-
-## Remix Plugin
-
-Use Vyper through the new Vyper tab and use "Remote Compiler"
-
-<img rounded style="width: 500px" src="./img/RemixInstallVyper2.png" />
-
----
-
-## Reentrancy
-
-The DAO Vulnerability
-
-```Java
-    function withdraw() public {
-        // Check user's balance
-        require(
-            balances[msg.sender] >= 1 ether,
-            "Insufficient funds.
- Cannot withdraw"
-        );
-        uint256 bal = balances[msg.sender];
-
-        // Withdraw user's balance
-        (bool sent, ) = msg.sender.call{value: bal}("");
-        require(sent, "Failed to withdraw sender's balance");
-
-        // Update user's balance.
-        balances[msg.sender] = 0;
-    }
-```
-
-We make a call to withdraw user's balance before updating our internal state.
-
----v
-
-## How can this be avoided?
-
-- Commit state BEFORE contract call
-- Modifier that prevents reentrancy (Solidity)
-- `@nonreentrant` decorator (Vyper)
-
----
-
-## Storing Secrets On-Chain
-
-Can we store secrets on-chain?
-
-What if we want to password-protect a particular
-contract call?
-
-Obviously we can't store any plaintext secrets on-chain, as doing so reveals
-them.
-
-<!-- .element: class="fragment" -->
-
----v
-
-## Storing Hashed Secrets On-Chain
-
-What about storing the hash of a password on chain and using this to verify some
-user-input?
-
-Accepting a pre-hash also reveals the secret.
-This reveal may occur in a txn
-before it is executed and settled, allowing someone to frontrun it.
-
-<!-- .element: class="fragment" -->
-
----v
-
-## Verifying with commit-reveal
-
-One potential solution is a commit-reveal scheme where we hash our reveal with
-some salt, then later reveal it.
-
-```
-// stored on-chain:
-secret_hash = hash(secret)
-```
-
-```
-// first txn, this must execute and settle on chain before the final reveal.
-// this associates a user with the soon-to-be-revealed secret
-commitment = hash(salt, alleged_secret)
-```
-
-```
-// final reveal, this must not be made public until commitment is recorded
-reveal = alleged_secret, salt
-verify(alleged_secret == secret)
-verify(commitment == hash(salt, alleged_secret))
-```
-
----v
-
-## Alternative: Signature
-
-Another approach is to use public-key cryptography.
-We can store the public key
-of some key pair and then demand a signature from the corresponding private-key.
-
-This can be expanded with multisig schemes and similar.
-
-How does this differ from the commit-reveal scheme?
-
-Notes:
-
-Commit-reveal requires that a specific secret be revealed at some point for
-verification.
-A signature scheme provides a lot more flexibility for keeping the
-secret(s) secure.
diff --git a/content/blockchain-contracts/light-clients-bridges/page.md b/content/blockchain-contracts/light-clients-bridges/page.md
deleted file mode 100644
index 36aa097c..00000000
--- a/content/blockchain-contracts/light-clients-bridges/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Light Clients and Bridges
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/light-clients-bridges/slides.md b/content/blockchain-contracts/light-clients-bridges/slides.md
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----
-title: Light Clients and Bridges
-description: Light clients principles and application in bridges
----
-
-# Light Clients
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="width:400px" src="./img/tomaka.png" />
-
-</pba-col>
-<pba-col>
-
-> <div> What can I say?</div> <!-- .element: class="fragment" -->
-> <div> It's a client but light.</div>  <!-- .element: class="fragment" -->
-
-</pba-col>
-</pba-cols>
-
----
-
-## 😢 Running a Node is Hard 😭
-
-<pba-cols>
-<pba-col>
-<pba-flex center>
-
-Ideally:
-
-- Everyone runs their own node.
-
-</pba-flex>
-</pba-col>
-<pba-col>
-
-<pba-flex center>
-
-<div>
-Reality:
-
-- It takes a lot of disk, memory, etc
-- It takes some know-how
-- I don't need it _all the time_
-
-</div>
-<!-- .element: class="fragment" -->
-
-</pba-flex>
-</pba-col>
-</pba-cols>
-
-Notes:
-
-The bitcoin whitepaper clearly assumes that users will run their own nodes.
-This is the most trustless and decentralized way to operate, and you should do it whenever you can.
-If you think you can't you're probably wrong.
-Just ask the Monero community.
-
-There are _some_ reasons not to run a full node and the reality is that not everyone will.
-So even though we should always run our own nodes, let's look at some alternatives and ways we can make node running more accessible.
-
----v
-
-## RPC Nodes
-
-AKA, trust somebody else's node.
-
-<pba-flex center>
-
-<ul>
-<li>🕵️ Spy on you (<a href="https://decrypt.co/115486/infura-collect-metamask-users-ip-ethereum-addresses-after-privacy-policy-update">like infura</a>).</li> <!-- .element: class="fragment" -->
-
-<li>🔞 Censor you <!-- .element: class="fragment" -->
-<li>🤥 Lie to you <!-- .element: class="fragment" -->
-<li>💔 Steal your boyfriend <!-- .element: class="fragment" -->
-</ul>
-
-</pba-flex>
-
-Notes:
-
-The easiest thing to do is just trust some expert to run a node for you.
-Very web2.
-Lot's of things can go wrong.
-
-So this is definitely not the best option.
-Let's see if we can do better.
-
----v
-
-## Lighten the Load
-
-For resource constrained systems and people in a hurry
-
-<pba-flex center>
-
-- Phone
-- Raspberry pi
-- Microcontroller
-- Inside Web Browser
-
-</pba-flex>
-
-Notes:
-
-One of the complaints was that the node takes too much resources.
-This is especially true if we want people to be able to run the node in all kinds of exotic environments.
-And we do want that because we want people to run their own node even when they're just paying the bill at dinner from their phone or liking social posts while scrolling on the bus.
-Let's make the client lighter so it doesn't require as much resources.
-
----v
-
-## Light Client Duties
-
-<pba-flex center>
-
-- ❌ Sync blocks
-- ❌ Execute blocks
-- ✅ Sync headers
-- ❔ Maintain Transaction Pool
-- ✅ Checks consensus
-- ❌ Maintains state
-
-</pba-flex>
-
-Notes:
-
-This is what a typical light client does.
-There is not a single definition of light client.
-There are varying degrees of lightness to suit your needs.
-
----v
-
-## Trustless
-
-<img rounded style="width:900px; margin-top:-30px" src="./img/bitcoin-spv.png" />
-
-<pba-flex center>
-
-- Relies on full node for data
-- Does not have to trust data
-- State root helps a lot
-
-</pba-flex>
-
-Notes:
-
-The figure is from the Bitcoin whitepaper.
-The concept of light clients has been around since bitcoin.
-At that time it was known as Simplified Payment Verification.
-You could confirm that a payment was sent or received.
-But you couldn't confirm that the tokens in question still existed or anything else about the state.
-
-Chains with state roots can have much more powerful light clients
-
----v
-
-## Syncing Strategies
-
-<pba-flex center>
-
-- Full header sync
-- Checkpoints in code
-- Warp sync
-
-</pba-flex>
-
-Notes:
-
-We also need to address the use case of clients that are not always on.
-For example if you only need your node on your phone, or when using a specific web page, that means it will have some syncing to do.
-
-Doing a full sync is already a lot faster than on a full client because you aren't downloading or executing the blocks.
-But by the time you have a few million headers, it does still take some time.
-
-The naive solution is to just have relatively recent headers hard-coded in the client.
-This works pretty well.
-You already have to trust the client developers for the entire implementation so you aren't trusting a new party at least.
-
-Warp sync is possible when you have deterministic finality.
-In dead simple PoA you just check that the authorities have signed the latest block and you are good.
-If you have authority hand-offs, there is more work to be done.
-You have to check that each authority set signs the transition to the next authority set.
-But this is still only even N blocks instead of every block.
-
----v
-
-## Self Defense
-
-Stay in the gossip protocol or you might get got.
-
-<img rounded width="500px" src="./img/wanka.jpg" />
-<!-- .element: class="fragment" -->
-
-Notes:
-
-In the main gossip protocol, if authorities finalize two conflicting blocks, then we can prove that they have broken the rules and slash them.
-If we don't watch the gossip and only peer with a single full node, then our view is entirely defined by that node.
-They may gossip us an attack chain and we won't know.
-So it is important to communicate with many different full nodes.
-
----
-
-## Bridges
-
-Transport layers between independent consensus systems
-
-<img rounded width="700px" src="./img/basic-bridge.svg" />
-
-Notes:
-
-Generally speaking bridges move arbitrary data between unrelated consensus systems.
-Basically between different blockchains, and those messages can evoke arbitrary side effects on the target chain.
-To keep it concrete, we'll mostly talk about moving tokens.
-
----v
-
-## Source and Target Chain
-
-<img rounded width="700px" src="./img/bridge-source-target.svg" />
-
-Notes:
-
-By convention we speak of bridges as being one-directional.
-When we talk about trustless bridge design this is a core concept in the design.
-It is less critical but still useful for trusted bridges.
-
-A two-way bridge is really just two one-way bridge.
-Think of a two-way
-street.
-There is a dedicated lane for each direction.
-
----v
-
-## Source Chain Re-Orgs
-
-<img rounded width="900px" src="./img/bridge-reorg.png" />
-
-Notes:
-
-On PoW chains this is truly just a judgement call and a prayer.
-If the source chain has deterministic finality we can do better.
-We need to wait for finality.
-But even this isn't foolproof.
-More on this after we cover the basic design.
-
----v
-
-## Bridge Models
-
-<pba-cols>
-<pba-col>
-
-### Trust-based
-
-Trusted intermediary makes a transfer manually.<br />
-Eg. Wrapped bitcoin on ethereum (WBTC)
-
-</pba-col>
-<pba-col>
-
-### Trustless
-
-Trustless is the goal,<br />like almost everything in web3.
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-The trust based bridges are not at all ideal.
-You have to entirely trust an intermediary.
-You send the intermediary tokens on the source chain.
-Once the intermediary is satisfied that they really own the source tokens, they send you some target tokens on the target chain.
-Or they don't whatever, not their problem.
-
-You can make they trust properties slightly better by using a multisig or a group of people so you only have to trust some subset of them.
-But this does not fundamentally eliminate the trust agreement.
-One classic example is the WBTC foundation.
-You send them bitcoin, they wait for "enough" block confirmations, and then they mint you an ERC20 token on Ethereum.
-And they provide the same service in reverse too.
-
-A lot of the trusted bridge design can be improved and we'll talk about that in detail in the next few slides.
-But it's worth observing here that we will never be able to eliminate the part about "Once the intermediary is satisfied that they really own the source tokens".
-The bridge can never be stronger than the consensus on the source chain
-
----
-
-## Trustless bridge design
-
-<pba-flex center>
-
-- Most trustless way to interact with blockchain<br />is to run a node
-- This is true for individuals _and_ other blockchains
-- A blockchain is extremely resource constrained.
-- Run a source chain light client on the target chain
-
-</pba-flex>
-
-Notes:
-
----v
-
-## BTC Relay
-
-<img rounded width="1000px" src="./img/btc-relay.svg" />
-
----
-
-## Bridge Design Challenges
-
-<img rounded width="1100px" src="./img/bridge-collapse.webp" />
-
-Notes:
-
-Bridges present their own set of design challenges beyond what we encounter in regular stand-alone light clients.
-
----v
-
-## Peers?
-
-<pba-flex center>
-
-- How can we peer without networking?
-- Enter the **Relayer** - a permissionless and trustless role
-- Need at least one honest relayer
-
-</pba-flex>
-
-Notes:
-
-On-chain logic doesn't have network IO, so how do we peer?
-There is a role known as a relayer.
-It is an off-chain agent who watches the source chain, and submits headers and finality proofs from the source chain to the target chain through transactions.
-Anyone can start a relayer.
-It is typically a little piece of software that you run.
-But there is nothing magic about it.
-You could perform the relayer task manually by copying header data from an explorer into metamask for example.
-
-You do need at least one honest relayer for the chain to get the correct header info.
-For this reason a large decentralized relayer group is nice.
-But even if you don't trust any relayer out there, you can always run your own.
-
----v
-
-## Finality and Equivocation
-
-<section class="!flex">
-  <img rounded width="500px" src="./img/bridge-incentives-achiles.jpg" />
-  <img rounded width="700px" src="./img/bridge-double-finalized.svg" />
-</section>
-
-Notes:
-
-It is not safe to accept headers as finalized immediately even if there is a deterministic finality proof.
-Let that sink in.
-Even if there is a valid finality proof, it is not safe to accept them as finalized.
-Why not?
-
-Because the validators may be equivocating.
-They don't send equivocations to real nodes on the network because those equivocations will be gossiped around and reported on the source chain and the validators will be slashed accordingly.
-But remember a light client on the target chain has no way to report such equivocations back to the source chain.
-
----v
-
-## Equivocation Incentives
-
-<pba-flex center>
-
-- Add a **Challenge Period** and
-- Add Fishermen - reverse of relayers
-
-<div>
-
-**OR**
-
-- Stake Relayers
-  so they can be slashed
-
-</div>
-<!-- .element: class="fragment" -->
-
-</pba-flex>
-
-Notes:
-
-There are basically two classes of solutions.
-Both of them require a waiting period aka challenge period before accepting a header with a finality proof as final.
-
-One is to add a role of fishermen.
-They are responsible for noticing when the header candidate on the target chain is different from the one in the main source chain protocol and reporting this behavior back to the source chain so the validators can be slashed there.
-Two problems:
-
-1. Fishermen have weak incentives.
-   If they do a good job there will be no equivocations and they will not get paid.
-1. Target chain is relying on the foreign source chain to keep the bridge secure instead of owning that security itself.
-
-The other is to have the relayer role require a security deposit.
-If it turns out that a relayer relays an attack header, that relayer is slashed and the relayer who reports it gets a reward.
-Relayers will expect to earn some reward for the opportunity cost of their stake which makes the bridge operation more expensive.
-
----
-
-## Multichain Apps
-
-<img rounded width="800px" src="./img/bridge-multichain-stack.svg" />
-
----v
-
-## We have a header, now what?
-
-<pba-flex center>
-
-- App users submit proofs
-- Need a source chain transaction?<br />
-  Submit an spv-style transaction proof
-- Need some source chain state?<br />
-  Submit a state proof
-
-</pba-flex>
-
-Notes:
-
-The header sync is just the foundation.
-Now Applications can build on top of it with the best possible trust guarantees.
-
-If you need some source chain transaction, your app needs to require an spv-style transaction proof to check against the header's extrinsics root.
-
-If you need some source chain state, your app needs to require a state proof to check against the header's state root.
-
----v
-
-## Multichain Security
-
-<img rounded style="width: 500px; margin-top:-30px" src="./img/strong-and-weak-.png" />
-
-Notes:
-
-This kind of trustless bridge _with proper incentives_ gets us information about the source chain to the target chain with security about as high as it was on the source chain.
-If you are building an app that spans multiple chains consider the security guarantees on both chains.
-The weaker security of the two is the security your app has.
-More abstractly, your app consumes two different kinds of blockspace that may be of different qualities.
-Your app is only as quality as the lower of the blockspaces.
-
----v
-
-## Example: Depository Mint Model
-
-- Send tokens to a contract on source chain
-- Message is relayed to destination chain
-  - Offchain relay and transaction
-  - XCM
-  - "Somehow"
-- New "wrapped" tokens are minted on the destination chain
-
-<!-- TODO really needs a figure -->
-
-Notes:
-
-The same process works in reverse to get the original tokens back.
-This can get get complex when there are multiple bridges.
-Are their wrapped tokens interchangeable?
-What if one of the bridges gets hacked?
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-# Blockchains and Smart Contracts Overview
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/overview/slides.md b/content/blockchain-contracts/overview/slides.md
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----
-title: Blockchains and Smart Contracts Overview
-description: Initial look at web history and the problems blockchain and web3 are solving
-duration: 30 - 45 minutes
----
-
-# Blockchains and Smart Contracts Overview
-
----
-
-## Upholding Expectations
-
-What is the core problem we want to solve?
-
-Trustless provisioning of infrastructure.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Something kind of like a server, that doesn't rely on a server operator, and has strong guarantees like Cryptography has to offer.
-
-One framing: Coming to a shared understanding of a common history, and therefore a common state, of a system.
-
----
-
-## Comparison with Cryptography
-
-Cryptography provides strong guarantees about _messages_ without a trusted party, regardless of the conduit over which a message was transported.
-
-Notes:
-
-Crypto guarantees:
-
-- No tampering
-- No eavesdropping
-- Authorship
-
----
-
-## Application Disentanglement
-
-Removing trust allows us to unpackage applications.
-
-<img rounded style="width: 800px; padding-right: 2em" src="./img/application-disentanglement.png" />
-
-Notes:
-
-The idea here is to discuss how applications are often seen as an entire bundle: e.g.
-Instagram is the database, the algorithms, the UX.
-But when we have credible expectations that we're interacting with the same system, rules, data, it's possible to build lots of ways to access and interact with the system.
-It also removes the need for a central authority to deal with all appeals/complaints from various users.
-
----
-
-# Desired Properties
-
----v
-
-## Permissionless access
-
-Anyone should be able to access and interact with the system.
-
----v
-
-## Privacy
-
-Users should have credible expectations about what information they give up about themselves.
-
----v
-
-## Authenticity
-
-Users should have credible expectations about the messages they see, regardless of the platform the messages are on.
-
----v
-
-## Finality
-
-Users should be able to form credible expectations about when a state transition is final.
-
----v
-
-## Behavior
-
-The system should behave as expected, even if system operators do not.
-
----v
-
-## _Unstoppability_
-
-No individual actor, company, state, or coalition should be able to degrade any of these properties.
-
----
-
-## A Shared History
-
-<img style="height: 500px;" src="./img/sapiens.jpg" />
-
-Notes:
-
-So now we understand the goals of web3.
-How do we achieve them? The key is allowing users to agree on a shared history.
-The simplest blockchains do nothing more than timestamp and attest to a stream of historical records.
-In Web 2 users have no visibility into the history of the app.
-They must trust the provider to accurately represent the current state.
-By giving the service provider the power to change the story, we give them the power to shape our understanding of reality and consequently our behavior.
-
----v
-
-## A Shared History
-
-> Any large-scale operation - whether a modern state, a medieval church, or an archaic tribe - is rooted in common stories that exist only in people's collective imaginations.
-
-> Telling effective stories is not easy.
-> The difficulty lies ... in convincing everyone else to believe it.
-> Much of history revolves around this question: How does one convince millions of people to believe particular stories about gods, nations, or LLCs?
-
-<!-- .element: class="fragment" -->
-
-_-- Yuval Noah Harari, Sapiens --_
-
----v
-
-## Shared Story of a State Machine
-
-<pba-cols>
-<pba-col>
-<pba-flex center>
-
-If we agree on:
-
-- The starting state<br />(aka genesis state)
-- The history of transitions
-
-</pba-col>
-<pba-col>
-</pba-flex>
-
-Then we _MUST_ agree on:
-
-<pba-flex center>
-
-- The current state
-
-</pba-flex>
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Now that we have a formal math-y model of systems that we care about, we can see that the notion of shared stories being powerful is more than slick language of philosophical mumbo jumbo.
-Even the term genesis state (or genesis block) is taken straight from mythology.
-We aren't newly discovering or inventing the idea that having a shared understanding of our past is important.
-It dates back to pre-history.
-We are just formalizing it and applying it to digital services.
-
----
-
-## Blockchains (Finally)
-
-A blockchain can be thought of in three parts
-
-<pba-cols>
-<pba-col>
-<pba-flex center>
-
-**State Machine**
-
-What does the state hold?
-
-What are the _rules_ to change it?
-
-</pba-flex>
-</pba-col>
-<pba-col>
-<pba-flex center>
-
-**Shared History** (data structure)
-
-Which potential histories exist?
-
-</pba-flex>
-</pba-col>
-<pba-col>
-
-<pba-flex center>
-
-**Consensus**
-
-Which history is the real one?
-
-What part of history is final?
-
-</pba-flex>
-</pba-col>
-</pba-cols>
-
-Notes:
-
-First, each blockchain tracks some state machine.
-We've discussed several examples of what that might be already, we'll code some simple examples shortly, and we'll spend all of module 5 digging into how to create a blockchain-friendly production-ready state machine.
-
-Next is the Blockchain Data structure.
-This data structure is basically a linked list of state transitions.
-But unlike the linked lists you studied in your data structures course, it isn't just linked by memory addresses or any other malleable thing.
-Instead it is cryptographically linked so that if anyone presents a different history, you can tell right away that you don't agree on a shared history.
-We'll dive into this data structure in the next lesson.
-
-Finally, is a consensus mechanism.
-Defining a state machine alone does not uniquely define a history.
-There are many possible valid histories.
-Just like the many worlds interpretation of quantum mechanics.
-To really agree on the current state, we need to agree on which of the possible histories is the real one.
-
----v
-
-## Short History of Blockchains
-
----v
-
-## Bitcoin
-
-<img rounded style="width: 500px;" src="./img/bitcoin-transaction.png" />
-
-Uses an unspent transaction output (UTXO) model & Proof of Work (PoW) consensus.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Who knows where the figure is from?
-
-CLICK
-
-Bitcoin was first.
-It was a money app.
-The first app chain.
-It hosts a smart contract in the broad definition.
-
-It was the first time most people considered a digital service that was not run by a particular person.
-
-Figure source: [Bitcoin white paper](https://bitcoin.org/en/bitcoin-paper)
-
----v
-
-## Litecoin, Monero, Dogecoin
-
-<img rounded src="./img/altcoins.png" />
-
-Notes:
-
-Only a few year later people realized they could fork the code and make small changed and improvements.
-Some changes were trivial.
-Some were interesting: monero and privacy.
-
-For me personally, this was a small crisis.
-I thought bitcoin was the one global one.
-Aren't these other coins undermining the narrative?
-NO! The point is that anytime you don't like the system or have an idea for a better one, you can do it!
-If you don't like bitcoin, build your own coin and make it better.
-Let the market decide.
-
----v
-
-## Ethereum
-
-- Generalization of Bitcoin: provides a quasi-Turing-complete VM
-- Uses an account-based system
-- Accounts can store balances, but can also store executable code (smart contracts)
-- Each contract can have its own internal state and API
-
----v
-
-## Smart contracts - Two Definitions
-
-<br />
-<br />
-
-#### Broad Definition <small style="margin-top:20px;"> _"Szabo definition"_</small>
-
-<blockquote>A machine program with rules that we could have defined in a contract, but instead a machine performs or verifies performance.</blockquote>
-
-#### Narrow Definition <small style="margin-top:20px;"> _"web3 definition"_</small>
-
-<blockquote>A program that specifies how users can interact with a state machine and is deployed permissionlessly to a blockchain network</blockquote>
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deleted file mode 100644
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 204px; margin-left: 517px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: #ffffff; "><div style="display: inline-block; font-size: 20px; font-family: Architects Daughter; color: rgb(255, 255, 255); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">client</div></div></div></foreignObject><text x="556" y="210" fill="#ffffff" font-family="Architects Daughter" font-size="20px" text-anchor="middle">client</text></switch></g><rect x="277" y="311" width="91" height="64" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; 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diff --git a/content/blockchain-contracts/p2p/img/napster_4.svg b/content/blockchain-contracts/p2p/img/napster_4.svg
deleted file mode 100644
index cf92f370..00000000
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text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 78px; height: 1px; padding-top: 204px; margin-left: 517px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: #ffffff; "><div style="display: inline-block; font-size: 20px; font-family: Architects Daughter; color: rgb(255, 255, 255); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">client</div></div></div></foreignObject><text x="556" y="210" fill="#ffffff" font-family="Architects Daughter" font-size="20px" text-anchor="middle">client</text></switch></g><rect x="277" y="311" width="91" height="64" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 89px; height: 1px; padding-top: 343px; margin-left: 278px;"><div style="box-sizing: border-box; font-size: 0px; text-align: center;" data-drawio-colors="color: rgb(240, 240, 240); "><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(240, 240, 240); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><font style="font-size: 20px;" color="#48cc81">Request:<br />Sublime</font></div></div></div></foreignObject><text x="323" y="347" fill="rgb(240, 240, 240)" font-family="Helvetica" font-size="12px" text-anchor="middle">Request:...</text></switch></g><rect x="159" y="71" width="131" height="30" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject style="overflow: visible; text-align: left;" pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; 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diff --git a/content/blockchain-contracts/p2p/img/p2p_topology_2.svg b/content/blockchain-contracts/p2p/img/p2p_topology_2.svg
deleted file mode 100644
index edcadfff..00000000
--- a/content/blockchain-contracts/p2p/img/p2p_topology_2.svg
+++ /dev/null
@@ -1,4 +0,0 @@
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diff --git a/content/blockchain-contracts/p2p/page.md b/content/blockchain-contracts/p2p/page.md
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-# Peer-to-Peer (P2P) Networking
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/p2p/slides.md b/content/blockchain-contracts/p2p/slides.md
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----
-title: Peer-to-Peer (P2P) Networking
-description: Peer-to-Peer (P2P) networking for web3 builders
----
-
-# Peer-to-Peer Networking
-
----
-
-## Introduction/Agenda
-
-- History of p2p networks <!-- .element: class="fragment" data-fragment-index="1" -->
-- Discuss the network layer and network conditions that blockchains operate on(Mostly) <!-- .element: class="fragment" data-fragment-index="2" -->
-- Talk about traditional web2 network overlays pros vs cons with web3 network overlays <!-- .element: class="fragment" data-fragment-index="3" -->
-- Discuss attacks and how to address along with the underlying threat model <!-- .element: class="fragment" data-fragment-index="4" -->
-
----
-
-## ARPANET
-
-- First operational packet-switching network <!-- .element: class="fragment" data-fragment-index="2" -->
-- Developed in the late 1960s by DARPA(The Defense Advanced Research Projects Agency) <!-- .element: class="fragment" data-fragment-index="3" -->
-- Laid the foundation for the modern internet <!-- .element: class="fragment" data-fragment-index="4" -->
-
-Notes:
-
-Total Information Awareness (TIA): In the early 2000s, DARPA initiated the TIA program aimed at developing technologies for mass surveillance and data analysis. The project raised concerns about privacy and civil liberties, eventually leading to its cancellation in 2003 due to public outcry.
-
----
-
-## Packet Switching
-
-- Mode of data transmission in which a message is broken into a number of parts that are sent independently(Packets) <!-- .element: class="fragment" data-fragment-index="2" -->
-- Packets are sent over whatever route is optimal <!-- .element: class="fragment" data-fragment-index="3" -->
-- Packets are reassembled at the destination <!-- .element: class="fragment" data-fragment-index="4" -->
-
----
-
-## Packet Switching
-
-<img style="width: 600px" src="./img/message_packet.svg" />
-
-Notes:
-
-Mention that headers contain some addressing, destination information, and ordering typically depending
-
----
-
-## Packet Switching
-
-<img style="width: 600px" src="./img/packet_switching_1.svg"  />
-
----
-
-## Packet Switching
-
-<img  style="width: 600px" src="./img/packet_switching_2.svg" />
-
----
-
-## Packet Switching
-
-<img style="width: 600px" src="./img/packet_switching_3.svg" />
-
----
-
-## Packet Switching
-
-<img style="width: 600px" src="./img/packet_switching_4.svg" />
-
----
-
-## Peer-to-Peer (P2P) Networks
-
-- P2P is a decentralized form of network structure <!-- .element: class="fragment" data-fragment-index="2" -->
-- Unlike client-server model, all nodes (peers) are equal participants <!-- .element: class="fragment" data-fragment-index="3" -->
-- Data is shared directly between systems without a central server <!-- .element: class="fragment" data-fragment-index="4" -->
-- Peers contribute resources, including bandwidth, storage space, and processing power <!-- .element: class="fragment" data-fragment-index="5" -->
-
----
-
-## Historical P2P applications
-
-Notes:
-
-Napster, Limewire
-
----
-
-## Napster
-
-- Launched in 1999, popular P2P platform <!-- .element: class="fragment" data-fragment-index="2" -->
-- Central server for indexing, P2P for transfers <!-- .element: class="fragment" data-fragment-index="3" -->
-- Shutdown in 2001 due to legal issues <!-- .element: class="fragment" data-fragment-index="4" -->
-
-Notes:
-
-Napster's story is closely tied with the band Metallica.
-In 2000, Metallica discovered that a demo of their song "I Disappear" was being circulated via Napster before its official release.
-This led to Metallica filing a lawsuit against Napster for copyright infringement.
-Napster had to comply by banning hundreds of thousands of users from their platform who were sharing Metallica's music.
-This was a turning point in digital copyright law and played a significant role in Napster's eventual shutdown in 2001.
-
----
-
-## Napster Setup
-
-<img style="width: 600px" src="./img/napster_1.svg" />
-
----
-
-## Napster Setup
-
-<img style="width: 600px" src="./img/napster_2.svg" />
-
----
-
-## Napster Setup
-
-<img style="width: 600px" src="./img/napster_3.svg" />
-
----
-
-## Napster Setup
-
-<img style="width: 600px" src="./img/napster_4.svg" />
-
----
-
-## Gnutella(Limewire)
-
-- Each node serves as both a client and a server no central server <!-- .element: class="fragment" data-fragment-index="2" -->
-- Query all connected nodes for files <!-- .element: class="fragment" data-fragment-index="3" -->
-- Gain peer connections to the network via Bootnodes <!-- .element: class="fragment" data-fragment-index="4" -->
-- Ordered to shutdown in 2010 by United States Court <!-- .element: class="fragment" data-fragment-index="5" -->
-
-Notes:
-
-- Check local filestore for file and if it is not available, forward the request to all connected peers.
-- Gnutella generates a significant amount of network traffic by flooding the network with requests.
-
----
-
-<section>
-    <h2>Client-Server vs Peer-to-Peer (P2P) Networks</h2>
-    <table>
-        <thead>
-            <tr>
-                <th></th>
-                <th>Client-Server Network</th>
-                <th>P2P Network</th>
-            </tr>
-        </thead>
-        <tbody>
-            <tr class="fragment">
-                <td>Structure</td>
-                <td>Centralized: One or more central servers control the network</td>
-                <td>Decentralized: All nodes (peers) participate equally</td>
-            </tr>
-            <tr class="fragment">
-                <td>Data Flow</td>
-                <td>Server provides data to clients</td>
-                <td>Peers directly share data with each other</td>
-            </tr>
-            <tr class="fragment">
-                <td>Resource Management</td>
-                <td>Servers manage resources and control access</td>
-                <td>Peers contribute resources including bandwidth, storage space, and processing power</td>
-            </tr>
-            <tr class="fragment">
-                <td>Scalability</td>
-                <td>Can be limited by server capacity</td>
-                <td>Highly scalable due to the distribution of resources</td>
-            </tr>
-            <tr class="fragment">
-                <td>Security</td>
-                <td>Centralized security measures, single point of failure</td>
-                <td>Potential for some security issues, malware(Depending on how it is implemented)</td>
-            </tr>
-        </tbody>
-    </table>
-</section>
-
----
-
-## Centralized vs Decentralized Networks
-
-<img style="width: 600px" src="./img/client_server_1.svg" />
-
-Notes:
-
-Talk about how when a partition happens in P2P vs Centralized.
-In p2p, only one node needs to have a full copy in order for the file to be able to be distributed across the network.
-
----
-
-## Centralized vs Decentralized Networks
-
-<img style="width: 600px" src="./img/client_server_2.svg" />
-
----
-
-## Centralized vs Decentralized Networks
-
-<img style="width: 600px" src="./img/p2p_topology_1.svg" />
-
----
-
-## Centralized vs Decentralized Networks
-
-<img style="width: 600px" src="./img/p2p_topology_2.svg" />
-
----
-
-## Advantages to Decentralized Networks
-
-- No privileged nodes <!-- .element: class="fragment" data-fragment-index="2" -->
-- Less bottlenecks with bandwidth <!-- .element: class="fragment" data-fragment-index="3" -->
-- DOS resistant <!-- .element: class="fragment" data-fragment-index="4" -->
-- No centralized infrastructure necessary (Except internet for now...) <!-- .element: class="fragment" data-fragment-index="5" -->
-
-Notes:
-
-1. No single node or nodes (CDN) have access to all of the content or files or is critical for operating the network.
-   Each node has a copy of the data.
-1. No central node carrying all of the load of traffic.
-   Block production and Block peering/importing can be mentioned here.
-1. Difficult to overload the network or DOS (Not a single node is privileged).
-1. Although many nodes are run on Centralized cloud compute platforms, they don't have to be (Typically).
-
----
-
-## Difficulties or Disadvantages
-
-- Since it is permissionless, a node can share malicious resources <!-- .element: class="fragment" data-fragment-index="2" -->
-- Latency <!-- .element: class="fragment" data-fragment-index="3" -->
-- Difficult to regulate illicit activity <!-- .element: class="fragment" data-fragment-index="4" -->
-- The network is limited by nodes with the weakest hardware <!-- .element: class="fragment" data-fragment-index="5" -->
-
-Notes:
-
-1. Latency may be an issue if we need to wait for many peers to receive the data produced from a single node since everyone may not have a direct connection.
-   Mention finality time!
-1. No central point to go and snoop all users data (for better or for worse).
-1. Why we have hardware requirements for blockchain networks.
-
----
-
-## Gossip Protocol
-
-<img style="width: 500px" src="./img/3.7-p2p-gossip-1.svg" />
-
-Notes:
-
-- Talk about how we have and want block 45 being peered to others
-
----v
-
-## Gossip Protocol
-
-<img style="width: 85s0px" src="./img/3.7-p2p-gossip-2.svg" />
-
-Notes:
-
-Talk about advertising vs just blind sending and how that can be inefficient
-
----
-
-<section>
-    <h2>Structured vs Unstructured P2P Networks</h2>
-    <table>
-        <thead>
-            <tr>
-                <th></th>
-                <th>Structured P2P Networks</th>
-                <th>Unstructured P2P Networks</th>
-            </tr>
-        </thead>
-        <tbody>
-            <tr class="fragment">
-                <td>Organization</td>
-                <td>Nodes are organized following specific protocols and structures (like Distributed Hash Tables)</td>
-                <td>Nodes are connected in an ad-hoc manner without any particular organization</td>
-            </tr>
-            <tr class="fragment">
-                <td>Search Efficiency</td>
-                <td>Efficient search operations due to structured nature</td>
-                <td>Search operations may be less efficient and can involve flooding the network</td>
-            </tr>
-            <tr class="fragment">
-                <td>Flexibility</td>
-                <td>Less flexible as changes in topology require restructuring</td>
-                <td>Highly flexible as nodes can freely join, leave, and reorganize</td>
-            </tr>
-            <tr class="fragment">
-                <td>Privacy</td>
-                <td>Data location is predictable due to structured organization</td>
-                <td>Greater potential for anonymity</td>
-            </tr>
-        </tbody>
-    </table>
-</section>
-
----
-
-## Discovery
-
-1. Connect to a peer <!-- .element: class="fragment" data-fragment-index="2" -->
-1. Ask peer for a list of their known nodes <!-- .element: class="fragment" data-fragment-index="3" -->
-1. Connect to random subset of peers from the list <!-- .element: class="fragment" data-fragment-index="4" -->
-1. Repeat steps 2 and 3 <!-- .element: class="fragment" data-fragment-index="5" -->
-
----
-
-## Applications
-
-Notes:
-
-1. What are some of the types of applications that lend themselves to this kind of network topology? Can anyone think of any?
-1. File sharing(Music)?
-1. Messaging and communication?
-
----
-
-## Initial Discovery
-
-- Bootnode/bootnodes (More on this later in Substrate)
-
-Notes:
-
-1. Must know someone who is participating in the network initially(Bootnode)
-
----
-
-## Attacks
-
-Notes:
-
-- Can anyone think of a way to exploit some of these networks?
-- What would be some things to try to take advantage of?
-
----
-
-## Attacks
-
-<img style="width: 600px" src="./img/eclipse_attack_1.svg"/>
-
-Notes:
-
-1. Distorts view of the healthy normal honest state of the network
-1. Transaction confirmations can be fictions
-
----
-
-## Attacks
-
-<img style="width: 600px" src="./img/eclipse_attack_2.svg"/>
-
----
-
-## Eclipse Attack Execution
-
-1. Flood a target node with a bunch of malicious peer addresses <!-- .element: class="fragment" data-fragment-index="2" -->
-1. The targeted node then stores these malicious peers and utilizes them when re-syncing on next bootup <!-- .element: class="fragment" data-fragment-index="3" -->
-1. DOS targeted node to take it offline to force a resync with these new malicious peers <!-- .element: class="fragment" data-fragment-index="4" -->
-
----
-
-## Preventing Attacks
-
-- Restrict inbound connections in some way <!-- .element: class="fragment" data-fragment-index="2" -->
-- Random selection of peers to connect with <!-- .element: class="fragment" data-fragment-index="3" -->
-- Deterministic node selection (Bootnodes) <!-- .element: class="fragment" data-fragment-index="4" -->
-- Restricting new nodes (Probably not what we want...) <!-- .element: class="fragment" data-fragment-index="5" -->
-
-Notes:
-
-1. Be wary of new connections with other nodes
-1. Don't just take the most recent request for connections to avoid the flooding
-1. Bootnodes with higher credibility and trust (Can be a bottleneck) - Rotate bootnodes as they are also subject to attacks
-
----
-
-## Conclusion
-
-P2P networks offer us a path forward towards applications which are more decentralized and censorship resilient
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-# Resources, Fees, Ordering
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/resources-fees-ordering/slides.md b/content/blockchain-contracts/resources-fees-ordering/slides.md
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----
-title: Resources, Fees, Ordering
-description: Fees and ordering in blockchains
-duration: 1 hour
----
-
-# Resources, Fees, Ordering
-
----
-
-## Overview
-
-<pba-flex center>
-
-1. [Fees and ordering](#fees--ordering)
-1. [Execution models](#execution-models)
-
-</pba-flex>
-
-Notes:
-
-- This lecture is a bit all over the place.
-- A bunch of stuff worth covering, but not all directly related.
-
----
-
-# Fees & Ordering
-
----
-
-## Fees & Ordering
-
-Blockchains are open, shared systems.
-They are unrestricted in access.
-
-But restricted in resources.
-
----
-
-## Permissionless Access
-
-Free _ability_ to access does not mean free _cost_ to access.
-
----
-
-## Threads
-
-A blockchain runtime is single-threaded.
-
-(For now)
-
----
-
-## Time
-
-A block must terminate in some amount of time.
-
----
-
-## Network
-
-Besides execution time, blocks need to propagate throughout the network.
-
----
-
-## Demand
-
-Many people may want to use the system concurrently.
-
-But the system needs to decide:
-
-- Which state transition calls to include in a block, and
-- How to order them.
-
----
-
-## Brief Interruption #1
-
-> The block body contains an ordered set of _extrinsics_: Packets from the outside world with _zero_ or more signatures attached.
-
-Notes:
-
-Recall from Lecture 1.
-
----
-
-## Brief Interruption #1 (cont.)
-
-These packets include:
-
-- A call to the system's state transition function
-- Some contextual information (e.g. a spec version)
-- Perhaps some additional information that would help block authors prioritise
-
----
-
-## No-Longer Brief Interruption #1 (cont.)
-
-Consider packets with:
-
-- zero signatures attached as "inherents" or "unsigned extrinsics"
-- one or more signatures attached as "transactions"
-
-This will be pretty straightforward until it's not.
-
----
-
-## Fee Models
-
-Different blockchains have different fee models.
-
-For this lecture, we will look at three:
-
-- Size (Bitcoin)
-- Step Metering (Ethereum)
-- Time (Polkadot)\*
-
-\* (and coming soon, space)
-
----
-
-## Size
-
-Bitcoin has a very simple STF: Namely verifying signatures and reassigning UTXOs.
-
-Its block size is limited, and each transaction has some byte-length (instruction, signature, etc.)
-
-Block authors will normally choose the set of transactions that would yield the highest gross fee.
-
----
-
-## Bitcoin Fee Market
-
-<img style="width: 800px" src="./img/3.3-fees-bitcoin-average-fee.png" />
-
-Notes:
-
-- Fee market evolves based on demand
-
-[Source: Y Charts](https://ycharts.com/indicators/bitcoin_average_transaction_fee_btc)
-(Couldn't find the chart I really wanted (per-byte rate), but can discuss)
-
----
-
-## Metering
-
-Ethereum has a more complex STF than Bitcoin, namely one that is quasi-Turing-complete.
-
-Users could submit transactions with an unknown number of steps to terminate.
-
-The system uses "gas metering" to halt execution of a transaction and continue to the next.
-
----
-
-## Metering
-
-Ethereum's STF defines a VM with instruction set, where each instruction costs some "gas".
-
-Users specify:
-
-- Max amount of gas to use
-- Cost, in ETH, per unit of gas they are willing to pay
-
----
-
-## Metering
-
-Each time an instruction is executed, the system deducts its cost from the max gas.
-
-If the program terminates, it only charges for the gas used.
-
-If it runs out of gas, it terminates the program.
-
----
-
-## Gas Rates
-
-<img style="width: 800px" src="./img/3.3-fees-ethereum-average-gas-price.png" />
-
-Notes:
-
-[Source: Etherscan](https://etherscan.io/chart/gasprice)
-
----
-
-## Weight
-
-Instead of metering during runtime, meter ahead of time.
-
-Charge a fixed\* fee for dispatching some call.
-
----
-
-## \*Fixed
-
-```rust
-#[pallet::weight(100_000_000)]
-fn my_variable_weight_call(input: u8) -> Refund {
-	let mut refund: Refund = 0;
-	if input > 127 {
-		let _ = do_some_heavy_computation();
-	} else {
-		let _ = do_some_light_computation();
-		refund = 80_000_000;
-	}
-	refund
-}
-```
-
----
-
-## Time
-
-Weight is picoseconds of execution time (`10E-12`).
-
-Calls are benchmarked on some "standard hardware".
-
-(There are some changes in the works about making two-dimensional weight.)
-
----
-
-## Weight
-
-Using weight reduced the overhead of runtime metering, but requires some more care from developers.
-
-- It must be possible to meter before runtime
-- So, users should not be able to deploy untrusted code
-- There is no safety net on execution
-- Some computation is OK, but should be possible from call inspection
-
-Notes:
-
-Examples:
-
-- User-supplied length of a list that will be iterated over
-- Number of calls within a batch
-
----
-
-## Brief Interruption #2
-
-Some of the gas and weight systems are evolving.
-
-- Ethereum recently added EIP1559, which uses a fee + tip mechanism
-- Parity and Web3 Foundation are discussing some changes to the weights model
-
----
-
-## Fee Strategies
-
-Block authors can include transactions using several strategies:
-
-- Just take those with the highest fee
-- Take those with the highest fee to {length, gas, weight} ratio
-
----
-
-## Fee Burning
-
-Not all the fees must go to the block author (depends on system design).
-
-In fact, this is often a bad design. Block authors will want fees to go up, so may indulge in no-op transactions to boost fees.
-
----
-
-## Fee Burning Examples
-
-- Polkadot only gives 20% of fees to block authors (80% goes to an on-chain Treasury)
-- Since EIP1559, Ethereum burns some of its fees (its "base") from each transaction
-
-In both systems, users can add "tips" to increase the priority of their transaction with authors.
-
----
-
-## Filling a Block
-
-Depending on the limiting factor, systems can have different limits to call a block full.
-
-- Bitcoin: Size (in bytes)
-- Ethereum: Gas limit (sum of all gas limits of transactions)
-- Polkadot: Weight (sum of all max expected weights)
-
----
-
-## Ordering
-
-We've selected some transactions, but the runtime is single-threaded.
-
-Block authors must order them.
-
----
-
-## Priority Basis
-
-The naive solution is to maintain an order of pending transactions by some "priority".
-
-And just include the top `N` transactions that fit in a block.
-
----
-
-## More Advanced
-
-But, many small transactions might result in a higher fee for greedy block authors.
-
-So there could exist a set of transactions that is more profitable than just the top `N`.
-
-Even some that could be considered attacks.
-
----
-
-# Execution Models
-
----
-
-## Transactional Execution
-
-Most blockchains have a "transactional" execution model.
-
-That is, they need to be woken up.
-
-A smart contract, for example, won't execute any code unless someone submits a signed, fee-paying transaction to the system.
-
----
-
-## Brief Interruption #3
-
-All of the "packets from the outside world" in these systems are signed.
-
-Some key holder signs an instruction that authorises a call and is willing to pay for its execution.
-
-Now is the time to enter the world of unsigned packets.
-
----
-
-## Free Execution
-
-State machines can have autonomous functions in their state transition function.
-
-System designers can make these functions execute as part of the STF.
-
-In this model, block authors _must_ execute some logic.
-
----
-
-## Free Execution
-
-These added function calls are powerful, but some care must be taken:
-
-- They still consume execution resources (e.g., weight)
-- They need some method of verification (other nodes should be able to accept/reject them)
-
----
-
-## Hooks
-
-The Substrate lectures will get into these, but for now just a look at some APIs:
-
-```rust
-pub trait Hooks<BlockNumber> {
-	fn on_initialize(_n: BlockNumber) -> Weight {}
-	fn on_finalize(_n: BlockNumber) {}
-	fn on_idle(_n: BlockNumber, _remaining_weight: Weight) -> Weight {}
-	fn on_runtime_upgrade() -> Weight {}
-	fn offchain_worker(_n: BlockNumber) {}
-}
-```
-
-Source: [`/frame/support/src/traits/hooks.rs`](https://github.com/paritytech/polkadot-sdk/blob/a13382f/substrate/frame/support/src/traits/hooks.rs)
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-# Digital Services as State Machines
-
-<!-- markdown-link-check-disable -->
-<center>
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-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
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----
-title: Digital Services as State Machines
-description: Digital Services approximate smart contracts; both are modeled as state machines.
----
-
-# Digital Services as State Machines
-
----
-
-## Web0
-
-Telegraph, Telephone
-
-Users transmit information peer-to-peer.
-
-Crypto not typically used except by military, but upheld guarantees when used.
-
-<img src="./img/Web0.png" />
-
-Notes:
-
-I want to go through a brief history of the web.
-This is not a history course, but it is important to understand the context of the web and how we got to where we are today.
-I will be using the term "web" to refer to the internet, but I will also be using it to refer to the world wide web.
-The internet is the physical infrastructure that allows computers to communicate with each other.
-The world wide web is one of the several utilizes including e-mail, File Transfer Protocol (FTP), Internet Relay Chat (IRC), Telnet, and Usenet that form the Internet.
-Okay so let's back up before all of that though - The term web0 isn't a common nomenclature - but basically this is old school Telegraph and telephones and in this era users transmitted information peer-to-peer.
-There was no intermediary.
-There was no service provider.
-There was no web server.
-There was no database.
-I would call up a friend - be connected via a wire - and we would talk, end to end.
-sure there are switchboard operators, but you could think of it as one really long wire connecting me to my friend I'm calling.
-Which is actually a perfect scenario for cryptography to uphold its guarantees.
-Once I talk to the switchboard operator and get routed to you, then we can just talk over our Cipher.
-It's really peer to peer, which is great!
-However, people were not really aware of the threat model and cryptography was not really used except by the military.
-But when it was used, it was used to uphold its guarantees.
-So this is like a property that we want to try to restore in web3.
-
----
-
-## Web1
-
-Introduction of always-on servers.
-
-Still mostly peer-to-peer.
-
-Cryptography more often, but still not ubiquitous.
-
-<img style="width: 300px;" src="./img/Web1.png" />
-
-Notes:
-
-Web 1 brings us to the 70s and 80s (maybe early 90s).
-This is an introduction to always-on servers.
-so with web0, with the telephone - I pick up my phone when I'm calling someone or when someone calls me and then I put it down and I'm offline the rest of the time.
-But in web1, we have these always on servers but it's still mostly peer-to-peer because people, at least two kind of a first order approximation had their own servers so in the clipart, we've got users and their servers - these pink lines are a connection to your own server.
-So this user has her own server and these two users maybe share a server - I don't know, they work for the same company or go to the same University or something and then this user doesn't have her own, maybe she's just consuming information and she's more of a casual user.
-So web1 is pretty similar to web0 and cryptography did start to become used a little bit more, but it still was not very ubiquitous and it's basically just because of the kinds of applications that people were using web1 for - it was mostly just for sharing information.
-Classic example is publishing - you would publish your paper or your data set and the whole idea is if you're publishing something, you really don't need to be keeping it secret, and in fact you're actually trying to NOT have it be secret.
-You're trying to put it out there for everyone to use and read.
-Now authenticity guarantees for sure would have still been great here - to know that your data didn't get tampered with along the wire...
-but again the threat model just wasn't in practice quite so bad and so like people got away without cryptography.
-
----
-
-## Web2
-
-Introduction of **Digital Services** with **Rich State**.
-
-Administered by service providers: "Send _us_ your information."
-
-However, users must place faith in the service provider.
-
-Cryptographic guarantees are about interactions with the service provider, not peers.
-
-<img style="width: 300px;" src="./img/Web2.png" />
-
-Notes:
-
-So that brings us to web2.
-1999 or 2004, wherever you want to put it really.
-Web2 brings the introduction of Digital Services with Rich state - so we're talking about web apps.
-Who here remembers Myspace? I was obsessed with curating my top 8.
-And then of course Facebook or whatever social media platform and beyond.
-But it's not just media either, there's eBay and Amazon and you can register to vote online and there's all these Services where you just go online you fill some data into a web form - maybe you don't even have to do a page reload - and that basically submits a transaction to some back-end server somewhere!
-So we begin to get these really really useful Digital Services.
-You can even think about things like Google search for example, that hardly existed in web1.
-Notice that there are no more pink lines in the diagram - people don't have their own servers - they're all connected to this one Central server.
-Obviously in reality it isn't a single Central server, but the the point kind of remains - it's a small number of centralized service providers.
-
----v
-
-## Digital Services
-
-People rely on digital services every day.
-They are inescapable and valuable.
-
-- Game Servers (AOE or Minecraft)
-- Twitter, Instagram, Facebook, etc.
-- Journalism and sources
-- Banks
-- Lawyers, notaries, regulators
-
-Notes:
-
-I should note - Digital services are not bad in and of themselves.
-They are very valuable.
-We use all of these every day.
-We are even using some to administer this course.
-But they are also hard to escape.
-What are other examples? I have some listed here - online banking, what else?
-
-And the key thing here is that they're all administered by these service providers and the model is - don't call your friend on the phone and communicate directly with them anymore - instead send us your information -
-
----v
-
-## Trust Example
-
-Two users on Twitter:
-
-- Trust that we are seeing information from the same database\*
-- Trust that if a tweet is from X, then X wrote that tweet\*
-- Trust that others see our messages as from us\*
-- Trust that the messages we see are the messages the users wrote\*
-- Trust that we're interacting with the application as equals
-
-Notes:
-
-Or rather, send your Tweet directly to Twitter server and then we'll publish it and then when your friend comes to us, we'll tell them that this is what you tweeted.
-trust me bro, this is what lauren tweeted, it's real.
-So this is asking you to place trust in the service provider.
-Once web2 became popular, cryptography became a bit more widespread.
-Look at the icon at the top of your browser - let's use github for example - That is ensuring me that I'm communicating over SSL to GitHub and they're encrypting all the communication and I am too, which is awesome! Because suddenly we're using this really cool cryptography that we've been developing over decades!
-But here's the thing - say if you go to pull my repo, you're not pulling it from me anymore, you're pulling it from github.
-So GitHub knows that nothing was corrupted between me and them and you know that nothing was corrupted between GitHub and you.
-But the thing is, github's right there - they could change my repo if they wanted to or they could maybe even have the power to take my repo offline.
-But here, the slide reminds us that we all essentially accept a trusting relationship with the service provider.
-We trust that we're seeing information from the same database, we trust that if a tweet is from Aaron, then Aaron wrote that tweet, we trust that others see our messages as from us, we trust that the messages we see are the messages the users wrote, and we trust that we're interacting with the application as equals.
-Cryptography actually provides a lot of these guarantees, but not when an intermediary has stepped in between users.
-
----v
-
-## God Mode Enabled
-
-In web 2, service providers can perform abuses:
-
-- Censoring user interaction
-- Restricting users interaction
-- Failing to produce requested data
-- Mutating state opaquely
-
-Notes:
-
-Okay in summary, these are the problems that trusted service providers can do to us.
-They can censor our interactions, they can restrict our interactions, they can fail to produce requested data, and they can mutate state opaquely.
-
----v
-
-## Thought experiment: Digital Currency
-
-Bitcoin's application was digital currency - a trivially simple application.
-
-Could this be built with Web2 technology?
-
-Notes:
-
-Let's do a thought experiment.
-Bitcoin came out 2009, it's a trivially simple application.
-n Bitcoin's application was digital currency.
-When you think about just the money thing - sending money from one person to another.
-How many of you think that if I give you like a weekend hackathon project, you could develop some kind of web2 style service and deploy it to AWS or digitalocean or wherever - that would basically act like a currency where I could log in and send my peers money.
-Could you build this with web2 technology?
-Yep you absolutely could.
-This is the kind of simple app you might build in a Freshman year course.
-You just need to maintain a set of bank notes and their owners (or alternatively a set of accounts and their balances.)
-So why didn't this exist in web 2? I hope this is pretty obvious.
-Because the provider could print money.
-Or steal money.
-Right? The moment somebody pisses me off I can go and freeze their funds or whatever.
-So even though coding the cryptocurrency application is like super simple it's totally useless because there's no incredible way to build trust in it.
-And that's what the blockchain is about.
-And that's what Joshy is going to speak to very soon.
-
----v
-
-## Distributed Applications in Web 2
-
-Providers run redundant data centers to prevents accidents.
-
-But it still assumes benevolent participants and some trusted leader.
-
-Notes:
-
-Something we should call out - there are some distributed applications in web2, but it's a little bit different than what we're talking about here.
-It's not like AWS folks are noobs and they have all their stuff in one Data Center and the moment that there's an earthquake or a fire or whatever everything that hosted on AWS goes down.
-They're better than that, they have data centers all over the world.
-But the difference there is that all of those data centers are operating as trusted peers.
-So one of them will lead and those changes will be synced to the others and the moment one goes down it fails back to the next one to keep the services live.
-Which is for sure a good thing, I'm not hating on that aspect of it, but the point that I'm making is that it doesn't make it trustless just because it's geographically distributed.
-It just makes it more resistant to accidents.
-AWS could still cut it down.
-Ultimately, the point is that in web2, the masses become beholden to the service providers who were free to extract value and manipulate the users.
-
----
-
-## Web3
-
-A provision of digital services without the need to trust a service _provider_.
-
-Providers do not need to be trusted; they are economically incentivized to behave honestly.
-
-Notes:
-
-Okay so web3 - We want to maintain the value, versatility, and richness of Web2, but remove the trust, and possibility of extractive behavior.
-Here I have: It's a provision of digital services without the need to trust a service provider.
-At an abstract level, the way that we make people trustworthy is that we give them economic incentives to behave honestly.
-So throughout this course we're going to design protocols and we're going to say things like, as long as two-thirds of the operators in this protocol are following the protocol, then all these guarantees I talked about are upheld! That's great.
-But then the glaring question is: well okay - how do you make sure that two-thirds of the operators are following the protocol? It always come back to economic incentives.
-Hence why you had econ and tokenomics last week.
-Because that's how we're going to get all of these mutually distrusting, not otherwise incentive aligned parties to agree to follow the protocol - by creating the incentive such that following the protocol is the best strategy: they can maximize their own utility by following the protocol.
-
----v
-
-## Desired Approach
-
-Allow users to interact with a common system without trusting any intermediaries.
-
-Opens the door to new application stacks:
-
-- Shared state and state change rules
-- Custom rendering, moderation, interfaces
-
-Notes:
-
-We want to allow users to interact with the system without having to trust intermediaries who might stand in the middle between the users.
-If we can do that, it opens the door to this new application stack where we disentangle all the layers.
-
-OKAY - so we're at the halfway point within this lecture, let's check in.
-At this point, we've been through the history of the web and hopefully understand the evolution from simple peer to pee communications to straight up digital services.
-
-Adding to that, from my from first lecture, we ALSO understand that both software and contracts are solutions to expressing agreements, and during Aaron's activity, we practiced building a simple web2 style smart contract.
-
-Now I want to start formalizing the semantics of how we actually build a smart contract.
-
-It turns out there is a mathematical (or computer science maybe?) term called a state machine.
-And it maps really well to what we just built and the kinds of interactions we want to build.
-
----
-
-## State Machines
-
-<img width="800px" src="./img/state-machine-general.svg" />
-
-Notes:
-
-What's interesting is that most systems, maybe all of them, but definitely most that we care about can be modeled as state machines.
-So State machine, it's not a real machine that you can build and touch and operate and stuff like that.
-It's a model comprised of a set of states and a set of rules about how to transition between the states.
-Looking at the diagram, maybe my state machine starts in state one over here and then somebody pokes it in some particular way, or to use more blockchain-y lingo, they send a transaction and that puts the state machine into into State-two.
-And so, what we're going to be doing with the blockchain is tracking a complete history of all of these transitions and if we know the history of all the transitions, then we should know what state we're in right now
-
----v
-
-## Labelled Transition Systems
-
-Sometimes you can map the entire state space as an LTS.
-
-Other times it is too big.
-
-<img src="./img/state-machine-arbitrary-history.png" />
-
-Notes:
-
-There's this notion of a labelled transition system.
-Sometimes if your state machine is simple enough you can actually map the entire State space as a labeled transition system.
-Most of the times when we're building real world applications, it's a little too big.
-But labeled transition systems are a really good model to keep in your mind when you're thinking about designing your state machines.
-Consider if we tried to map all possible states of a social media app or a digital currency.
-Sometimes an LTS drawing like this is useful, other times it would be too large or even infinite.
-Even still, sometimes drawing part of it can help you think about what the states and transitions might be.
-
----v
-
-## Example: Light Switch
-
-Simple Switch: 2 States, 1 Transition
-
-**Labelled Transition System** <!-- .element: class="fragment" data-fragment-index="2" -->
-
-<img src="./img/light-switch-lts.svg" /> <!-- .element: class="fragment" data-fragment-index="2" -->
-
-**History** <!-- .element: class="fragment" data-fragment-index="3" -->
-
-<img src="./img/light-switch-history.svg" /> <!-- .element: class="fragment" data-fragment-index="3" -->
-
-Notes:
-
-Let's look at a simple example.
-A light switch.
-CLICK
-It has two states: on and off.
-And one transition: flipping the switch.
-We can draw this as a labeled transition system.
-CLICK
-And we can also draw a history of the transitions that have happened.
-So if we know the history of all the transitions, then we should know what state we're in right now.
-So we start in some State down here for example where the light is on and then when a transition comes in it's we already know what kind of transition it's going to be.
-There's only one - it's the toggle transition that turns the light off and Etc and Etc and this could go on forever.
-Right now this is such a simple State machine that like this isn't going to be a very interesting history it's just going to be toggle toggle toggle toggle forever.
-But with that information, if if for some reason knowing whether this light was on or off is like super important to your Society or your community, you've now achieved it - or at least we know a way to start achieving it.
-
----v
-
-## State Machine Example: Digital Cash
-
-Each state is a set of bank notes.
-Where a bank note has an amount and an owner.
-A transition involves a user consuming (spending) some bank notes and creating new ones.
-
-<img width="800px" src="./img/state-machine-cash.svg" />
-
-Notes:
-
-Let's look at a more interesting example.
-Digital cash.
-This is one where I can't draw the entire label transition system because it's way too huge.
-But I can draw a little bit of it.
-Each state is a set of bank notes.
-Where a bank note has an amount and an owner.
-A transition involves a user consuming (spending) some bank notes and creating new ones.
-Not all conceivable transitions are valid.
-Imagine a user consuming a bank note worth 5 coins, and creating two new ones each worth 3 coins.
-That's not allowed.
-So we have to be careful about what transitions are allowed and what transitions are not allowed.
-And again, if we know the history of all the transitions, then we should know what state we're in right now.
-
----v
-
-## Sate Machine Example: Social Media
-
-Each state is a set of posts and their associated comments and emoji reaction counts.
-A transition involves, making a new post, or reacting to someone elses, or commenting
-
-<img src="./img/state-machine-social.svg" />
-
-Notes:
-
-state is a set of posts and their associated comments and emoji reaction counts.
-A transition involves, making a new post, or reacting to someone elses, or commenting
-There is not a single model here.
-Some state machines will allow deleting or editing posts, while others will not.
-Some will allow disliking posts while others only allow liking.
-Here the diagram basically we see - if the state starts out simple with this one Post in it and then someone makes a new post (and there would have to be more details in here about who's posting and what they're posting)But then we get to this new state and then maybe the next transition is that somebody likes post number one and so now the state contains a record that this thing is liked.
-Just to drive the point home the idea is that if you know the starting State and you know the history of the transitions, then you know the the current state and so you can sit and watch as every transition comes in you can validate them yourselves and say this one's good we're adding it to our history or this one's bad we're chucking it's invalid transition.
-And then therefore you can know the final state
-
----v
-
-## More State Machine Examples:
-
-<pba-flex center>
-
-- Ride sharing platform
-- Voting system
-- Blackjack table
-- The app you just built
-
-</pba-flex>
-
-Notes:
-
-There are all kinds of these - uber, polkadot's governance, and gambling!
-Take a moment to brainstorm with your table about each of these three examples as well as the app you built in the previous activity.
-For each example, write out what are the state transitions and the the states.
-If possible, draw a complete LTS.
-If that is not possible, draw a partial LTS.
-
----v
-
-## Garage Door Lock
-
-<img rounded width="60%" src="./img/garage-door-keypad.jpg" />
-
-Notes:
-
-One more team exercise.
-Draw a state transition diagram for a garage door lock keypad.
-
-If the user enters the correct 4 digits, the door opens (or closes if it was already open).
-The thing is, you could enter some random digits before you enter the correct code, and it would still open after the correct code.
-As you sketch your states, be sure to handle that correctly.
-
-This example is drawn from https://eng.libretexts.org/Under_Construction/Book%3A_Discrete_Structures/09%3A_Finite-State_Automata/9.02%3A_State_Transition_Diagrams which has many other excellent examples
-
----
-
-## Build Some State Machines
-
-Blockchain From Scratch Activity
-
-Chapter 1 State Machines
-
-Notes:
-
-This activity is going to run over the next four days.
-We will have a good amount of time to work on it in class.
-We will also set some minimum completion goals each evening.
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" 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diff --git a/content/blockchain-contracts/structure/page.md b/content/blockchain-contracts/structure/page.md
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-# Blockchain Structure
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/structure/slides.md b/content/blockchain-contracts/structure/slides.md
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----
-title: Blockchain Structure
-description: The Blockchain data structure including hash-linking, forks, header vs body, and extrinsics.
-duration: 30 min
----
-
-# Blockchain Structure
-
-<img style="width: 1000px" src="./img/opaque-blockchain.svg" />
-
----
-
-## Shared Story
-
-A Blockchain **cryptographically guarantees** that a history of events has not been tampered with.
-This allows interested parties to have a **shared history**.
-
-Notes:
-
-And it allows them to know whether they have identical histories in O(1) by just comparing the tip of the chain.
-
----
-
-## Hash Linked List
-
-<img style="width: 1000px" src="./img/hash-linked-1.svg" />
-
-Notes:
-
-This is a simplified blockchain.
-Each block has a pointer to the parent block as well as a payload.
-
----v
-
-## Hash Linked List
-
-<img style="width: 1000px" src="./img/hash-linked-2.svg" />
-
-Notes:
-
-The pointer is a cryptographic hash of the parent block.
-This ensures data integrity throughout the entire history of the chain.
-This is the simplest form that a blockchain could take and indeed it allows us to agree on a shared history.
-
----v
-
-## Hash Linked List
-
-<img style="width: 1000px" src="./img/hash-linked-3.svg" />
-
-Notes:
-
-This ensures data integrity throughout the entire history of the chain.
-This is the simplest form that a blockchain could take and indeed it allows us to agree on a shared history.
-
----v
-
-### Genesis Block
-
-<img style="width: 1000px" src="./img/hash-linked-genesis.svg" />
-
-Notes:
-
-The first block in the chain is typically called a the "Genesis block" named after the first book in the judaeo-christian mythology - The beginning of our shared story.
-The parent hash is chosen to be some specific value.
-Typically we use the all-zero hash, although any fixed widely agreed-upon value would also do.
-
----
-
-## State Machines (Again)
-
-A state machine defines:
-
-<pba-flex center>
-
-- Set of valid states
-- Rules for transitioning between states
-
-</pba-flex>
-
-<img style="width: 900px;" src="./img/state-machine-general.svg" />
-
----v
-
-### Blockchain meet State Machine
-
-<img style="width: 1000px" src="./img/blockchain-meet-state-machine.svg" />
-
-Notes:
-
-The simplest way to join a blockchain to a state machine is to to make the blockchain's payload a state machine transition.
-By doing so, we effectively track the history of a state machine in a cryptographically guaranteed way.
-
----v
-
-### Where do the States Live?
-
-Somewhere else!
-
-<img style="width: 1000px" src="./img/blockchain-with-state-outside.svg" />
-
-Notes:
-
-There is a state associated with each block.
-But typically the state is NOT stored in the block.
-This state information is redundant because it can always be obtained by just re-executing the history of the transitions.
-It is possible to store the state in the blocks, but the redundancy is undesirable.
-It wastes disk space for anyone who wants to store the history of the chain.
-Storing the state in the block is not done by any moderately popular blockchain today.
-If you _want_ to store the states, you are welcome to do so.
-Software that does this is known as an Archive node or an indexer.
-But it is stored separately from the block
-...Pause...
-One more time to make sure it sinks in: The state is NOT in the block.
-
----v
-
-### State Roots
-
-A cryptographic anchor to the state
-
-<img style="width: 1000px" src="./img/blockchain-with-state-roots.svg" />
-
-Notes:
-
-Some data redundancy can be good to help avoid corruption etc.
-It is common for a block to contain a cryptographic fingerprint of
-the state.
-This is known as a state root.
-You think of it as a hash of the state.
-In practice, the state is typically built into a Merkle tree like structure and the tree root is included.
-Not all blockchains do this.
-Notably bitcoin doesn't.
-But most do.
-We'll go into details about exactly how this state root is calculated for Substrate in the next two modules, but for now we just consider the state root to be some kind of cryptographic fingerprint.
-
----
-
-## Forks
-
-<img style="width: 1000px" src="./img/forks.svg" />
-
-A state machine can have different possible histories.
-These are called forks.
-
-Notes:
-
-You can think of them like alternate realities.
-We need to decide which of the many possible forks is ultimately the "real" one.
-This is the core job of consensus and we will talk about it in two upcoming lessons in this module.
-
----v
-
-## Invalid Transitions
-
-<img style="width: 1000px" src="./img/forks-some-invalid.svg" />
-
-Notes:
-
-Before we even get to hardcore consensus, we can rule out _some_ possibilities based on the state machine itself
-
----
-
-## Realistic Blockchain Structure
-
-<img width="600px" src="./img/header-body.svg" />
-
-- Header: Summary of minimal important information about this block
-- Body: A batched list of state transitions
-
-Notes:
-
-The header is a minimal amount of information.
-In some ways it is like metadata.
-The body contains the real "payload".
-It is almost always a batch of state transitions.
-There are many name aliases for what is included in the body:
-
-- Transitions
-- Transactions
-- Extrinsics
-
----v
-
-## Blocks in Substrate
-
-```rust
-/// Abstraction over a Substrate block.
-pub struct Block<Header, Extrinsic: MaybeSerialize> {
-	/// The block header.
-	pub header: Header,
-	/// The accompanying extrinsics.
-	pub extrinsics: Vec<Extrinsic>,
-}
-```
-
-Notes:
-
-This example is from Substrate and as such it strives to be a general and flexible format, we will cover Substrate in more depth in the next module.
-This is representative of nearly all real-world blockchains
-
----
-
-## Headers
-
-Exact content varies per blockchain.
-Always contains the parent hash.
-Headers are the _actual_ hash-linked list, not entire blocks.
-
-Notes:
-
-The parent hash links blocks together (cryptographically linked list).
-The other info is handy for other infrastructure and applications (more on that later).
-
----v
-
-## Header Examples
-
-<pba-cols>
-<pba-col>
-
-<pba-flex center>
-
-**Bitcoin**
-
-</pba-flex>
-
-- Version
-- Previous Hash
-- Tx Merkle Root
-- Time
-- N_Bits
-- Nonce
-
-</pba-col>
-<pba-col>
-
-<pba-flex center>
-
-**Ethereum**
-
-</pba-flex>
-
-- Time
-- Block Number
-- Base Fee
-- Difficulty
-- Mix Hash
-- Parent Hash
-- State Root
-- Nonce
-
-</pba-col>
-</pba-cols>
-
----v
-
-## Substrate Header
-
-- Parent hash
-- Number
-- State root
-- Extrinsics root
-- Consensus Digest
-
-Notes:
-
-Extrinsics root is a crypto link to the body of the block.
-It is very similar to the state root.
-Consensus Digest is information necessary for the consensus algorithm to determine a block's validity.
-It varies widely with the consensus algorithm used and we will discuss it in two upcoming lectures.
-
----v
-
-## Substrate Header (Full Picture)
-
-<img style="width: 1000px" src="./img/headers-link-state-body.svg" />
-
----
-
-## Extrinsics
-
-Packets from the outside world with _zero_ or more signatures attached.
-
-- Function calls to the STF
-- Some functions require signatures (e.g., transfer some tokens)
-- Others don't, but usually have some validation means
-
----
-
-## DAGS
-
-**Directed Acyclic Graphs**
-
-<img style="margin-left: 215px;" src="./img/forks.svg" />
-
-Notes:
-
-In math there is a notion of a Directed Acyclic Graph.
-Define graph, than directed, than acyclic.
-Blockchains are examples of DAGs.
-Actually blockchains are a specific kind of a DAG called a tree.
-Sometimes you will hear me talk about the "block tree" which really means all the histories of the chain.
-
-But there are more kinds of DAGs than just trees.
-Consider if someone authored a block that looks like this.
-
-CLICK
-
----v
-
-## DAGS
-
-**Directed Acyclic Graphs**
-
-<img style="width: 1000px" src="./img/dag.svg" />
-
-Notes:
-
-What if a block could have more than one parent!?
-It could allow parallelization and increased throughput!
-But it also leads to problems.
-What if there are conflicting transactions in the two parent histories?
-How do you even know if there are conflicting histories?
-
----
-
-<!-- FIXME TODO
-
-This might be a good place to split the lesson.
-The part before this is about a data structure.
-The part after this is about a P2P network of nodes that track this data structure.
--->
-
-## Blockchain 💒 P2P Networks
-
-<img style="width: 900px;" src="./img/blockchain_p2p.svg" />
-
-Notes:
-
-So hopefully some parts of this figure look familiar.
-What do you see here?
-
-- Diverse servers.
-- In a p2p network.
-- Each with their own view of the blockchain.
-
----v
-
-## Nodes
-
-Software agents that participate in blockchain network.<br />
-May perform these jobs:
-
-<pba-cols>
-<pba-col>
-<pba-flex center>
-
-- Gossip blocks
-- Execute and Validate blocks
-- Store blocks
-- Store states
-- Gossip transactions
-
-</pba-flex>
-</pba-col>
-<pba-col>
-<pba-flex center>
-
-- Maintain a transaction pool
-- Author blocks
-- Store block headers
-- Answer user requests for data (RPC)
-
-</pba-flex>
-</pba-col>
-</pba-cols>
-Notes:
-
-Many nodes only perform a subset of these tasks
-
----v
-
-## Types of Nodes
-
-<pba-flex center>
-
-- Full Nodes
-- Light Nodes (aka Light clients)
-- Authoring nodes
-- Archive nodes
-- RPC nodes
-
-</pba-flex>
-
----
-
-## Blockspace
-
-A resource created, and often sold, by a decentralized blockchain network.
-
-<img style="width: 700px;" src="./img/Web2Web3Stacks.png" />
-
-#### Learn more:
-
-- Article: <https://a16zcrypto.com/posts/article/blockspace-explained/>
-- Article: <https://www.rob.tech/polkadot-blockspace-over-blockchains/>
-- Podcast: <https://www.youtube.com/watch?t=5330&v=jezH_7qEk50>
-
-Notes:
-
-A Blockchain network is a replacement for a centralized server.
-It sells a product to application deployers.
-The state machine is the application layer, and the blockchain is the server replacement.
-In the same way that applications pay data centers for server resources like cpu time, disk space, bandwidth etc.
-Applications (maybe via their developers or users) pay for the privilege of having their history attested to and their state tracked by a trustless unstoppable consensus layer.
-
----v
-
-## Transaction Pool
-
-- Contains transactions that are not yet in blocks.
-- Constantly prioritizing and re-prioritizing transactions.
-- Operates as a blockspace market.
-
-Notes:
-
-Sometimes known as mempool (thanks bitcoin 🙄)
-Authoring nodes determine the order of upcoming transactions.
-In some sense they can see the future.
-
-Foreshadow forks where players disagree on the rules
-History: dao fork bch fork
-foreshadow consensus: arbitrary additional constraints for a block to be valid
-
----
-
-# Let's #BUIDL It
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-# Unstoppable Applications
-
-<!-- markdown-link-check-disable -->
-<center>
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-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
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----
-title: Unstoppable Applications
-description: Unstoppable Applications in web3
-duration: 1 hour
----
-
-# Unstoppable Applications
-
-Notes:
-
-Much like tokenomic design, that is a large component in unstoppable apps that incorporate cryptocurrency or other motivating factors, this lesson is far far too short to give you all the tools and techniques to make a robust DApp design.
-
-Instead we strive to highlight the problem space we face and some classes of solutions to them.
-
----
-
-## Motivation
-
-So far, we have discussed state machines and consensus... in _isolation_.
-
-Does the _contexts in which they operate within_ matter?
-
-Notes:
-
-- So far _mostly_ on simplified, idealized systems.
-  - "Black boxes" of cryptography
-  - Rational actors and assumed complete models of behavior in economics
-  - Blockchains as an "[isolated system](https://en.wikipedia.org/wiki/Isolated_system)" of sorts - external systems _cannot_ be reasoned about in the same way...
-    We will talk about the Oracle Problem.
-- In _practice_ there are far more ["unknown unknowns"](#🙈-unknown-unknowns) and "black swan" behavior.
-  More to come on that in this lesson.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Discussion
-
-> What properties of a system make it "stoppable"?
-
-Notes:
-
-- Web2 context: central providers & authorities, ...
-- Web3 context: decentralized, ...
-- What properties of a system make it "stoppable"?
-
----
-
-### Unstoppable Apps Properties
-
-<pba-flex center>
-
-- Anitfragile
-- Trustless\*
-- Censorship-less\*
-- Accessible\*
-- ...perhaps more?
-
-</pba-flex>
-
-Notes:
-
-The "\*" indicates the web3 context for defining properties, not generally.
-Not all of these can apply, nor is is possible all simultaneously apply.
-We need to craft the system properties based on what we must achieve.
-In reality we strive for Absolute Unstoppability, but likely cannot grantee it in _every possible scenario_.
-
----
-
-## Anitfragile
-
-<pba-cols>
-<pba-col>
-<div style="font-size:smaller">
-
-> Some things benefit from shocks; they thrive and grow when exposed to volatility, randomness, disorder, and stressors and love adventure, risk, and uncertainty.
-> Yet, in spite of the ubiquity of the phenomenon, there is no word for the exact opposite of fragile.
-> Let us call it antifragile.
-> Antifragility is beyond resilience or robustness.
-> The resilient resists shocks and stays the same; the antifragile gets better.
->
-> -- [Antifragile](https://en.wikipedia.org/wiki/Antifragile_%28book%29) --
-
-</div>
-
-</pba-col>
-<pba-col>
-<img rounded style="width: 550px" src="./img/hydra-Gustave_Moreau.jpg" />
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- Read Antifragile quote, recommend book recommended, see the links throughout slides for more after class.
-- Hydra fable & lore: <https://en.wikipedia.org/wiki/Lernaean_Hydra> - even though can be almost completely destroyed, it is _resilient_ and recovers.
-  Absolutely Unstoppable doesn't mean it cannot be damaged or even paused temporarily, it means it cannot cease to exist and will eventually recover, and ideally come back stronger in doing so.
-
----
-
-## An N-lemma
-
-Hypothesis: a _absolutely_ Unstoppable App cannot exist.
-
-We must make trade-offs out of all N properties<br />that a _absolutely_ Unstoppable App would possess.
-
-<pba-cols>
-<pba-col>
-<img rounded style="width: 600px" src="./img/trilemma.svg" />
-</pba-col>
-<pba-col>
-<img rounded style="width: 600px" src="./img/scalability-trilemma.svg" />
-</pba-col>
-</pba-cols>
-
-Notes:
-
-As with crypto, we can have astronomically good odds...
-But they are not perfect.
-We want the most robust system possible, given the _environment and context_ the consensus system lives in.
-
-More relevant trilemma:
-
-- [Scalability](https://vitalik.ca/general/2021/04/07/sharding.html#the-scalability-trilemma)
-- [Zooko's Triangle](https://en.wikipedia.org/wiki/Zooko's_triangle) (Network IDs)
-- More likely!
-
----
-
-## Web3 Tech Stack
-
-<img style="width: 1200px" src="./img/3.4-web3-stack.png" />
-
-Notes:
-
-This diagram is a bit dated with advancements in the field, but a good approx.
-representation.
-
-Observation and clarification: DApps canonically refer to smart contract applications.
-These exist _within the context_ of consensus systems that themselves inherit properties of unstoppability from.
-The academy is more focused on _consensus system engineering_ - we reason about blockchains themselves - rather than "DApp"s that _use_ those as platforms to operate in or on.
-The Smart contracts lessons _may_ include detains on unstoppable dapps design considerations.
-
-<!-- FIXME TODO: update this graphic, rather stale (Joe mentioned in Cambridge) -->
-<!-- FIXME TODO: clarify based on smart contract content - does it inform on system design considerations for unstoppable dapps? -->
-
----
-
-## Much More Than Blockchain Architecture...
-
-<pba-cols>
-<pba-col>
-
-Blockchains only form one part of the stack.
-
-Web3 applications must prevent attacks at all layers.
-
-</pba-col>
-<pba-col>
-
-<pba-flex center>
-
-- Networking
-- Consensus
-- Node access
-- Validator power
-- Inter-consensus trust
-- _Human factors_
-- _Extrinsic factors_
-
-</pba-flex>
-</pba-col>
-</pba-cols>
-
-Notes:
-
-These are for discussion today, but there are _many more_ thank those listed here!
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Human Level
-
----
-
-## Attacking Web3
-
-<img rounded style="width: 1000px" src="./img/3.4-xkcd-security.png" />
-
-Notes:
-
-Key point: your "perfect" system in is likely weak to things outside of the "rules"!
-especially
-
-Image Source: <https://xkcd.com/538/>
-
----v
-
-## Web3 Criticisms
-
-<pba-cols>
-<pba-col>
-
-There are [valid criticisms](https://moxie.org/2022/01/07/web3-first-impressions.html) of how many Web3 apps operate today.
-
-</pba-col>
-<pba-col>
-
-<pba-flex center>
-
-- Humans are cheap & lazy...<br />
-  No individuals run servers.
-- RPC node providers
-- A _protocol_ improves<br />slowly vs. a platform.
-- False marketing,<br />frauds, & scams!
-
-</pba-flex>
-</pba-col>
-</pba-cols>
-
-Notes:
-
-<https://moxie.org/2022/01/07/web3-first-impressions.html> great critique on the state of the space, but founder of [Signal messenger](https://signal.org).
-
-Not all hope is lost!
-This is valid mostly in the present, we will discuss these and what we're building to realize a better stack.
-
-<!-- TODO FIXME: more slides on this section! -->
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Systems Level
-
----v
-
-## Prove it!
-
-We use the word "proof" a lot...<br />it means many things in [different contexts](https://en.wikipedia.org/wiki/Provable):
-
-<pba-flex center>
-
-- Math → **Provable Correct** (algo)
-- Consensus → Proof of X (security)
-- Crypto → \[ZK | VRF | Validity | ... \] Proofs
-
-</pba-flex>
-
-Notes:
-
-The one so far not covered is Provable Correctness - where we can use maths to _prove_ that our logic cannot do unexpected behavior.
-An interesting example is [Cardano's design value proposition](https://docs.cardano.org/explore-cardano/cardano-design-rationale/) using haskell and provably correct most parts of their platform.
-
-> We have a lesson and exercise on formal verification methods latter on - this is how we can approach Provable Correctness in the context of Rust and thus Substrate.
-
-BUT this property assumes a complete system model!
-Nuke proposes that when considering factors outside the consensus system, there cannot be a rigorous proof of correctness as we cannot model the universe.
-
----v
-
-## 🔮 Oracle Problem
-
-An [oracle](https://en.wikipedia.org/wiki/Category:Computation_oracles) provides eternal data to a consensus system.<br />(i.e. a partial state of an external chain)
-
-The [oracle problem](https://chain.link/education-hub/oracle-problem) relates to the _trust_ in the oracle.
-
-Notes:
-
-- Example: Random Oracle, NOT like VRF we saw in the crypto module that can be in the consensus system.
-- Oracle needed for _input_ from anything that lives outside of the boundary of the consensus system.
-  - Everything in a chain is self-referential.
-    Applications in a consensus system may want to _try_ and reason about something outside itself.
-- Inclusive of bridges
-
----v
-
-## 🦢 Black Swans
-
-<pba-flex center>
-
-- known bounds of operation</br> _assumed_ impossible
-- death spirals
-
-</pba-flex>
-
-Notes:
-
-Explain example of luna or other system collapse.
-
-- 📔[The Black Swan: The Impact of the Highly Improbable](https://en.wikipedia.org/wiki/The_Black_Swan:_The_Impact_of_the_Highly_Improbable)
-- [Wiki Black Swan Theory](https://en.wikipedia.org/wiki/Black_swan_theory)
-
----v
-
-## 🤯 Complexity
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="height: 700px;" src="./img/Genealogy_map_of_topics_treated_by_Nassim_Taleb.jpg" />
-
-</pba-col>
-<pba-col>
-
-- Illustrating how to map the intricacies of _coupled, complicated, interactions of systems_.
-- \* You are not expected to understand this plot 😅
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- Great talk by the author: <https://www.youtube.com/watch?v=S3REdLZ8Xis> reference talk by book author.
-
-Example: irrational actors can be represented in a very simple model as a completely random act, or opposite act of what a rational actor would do.
-If you "fuzz" you system you may discover fragility to irrational actions that could undermine your system.
-Perhaps it's far easier and more likely than it at first appears to experience a black swan event.
-
-- Image [source](https://en.wikipedia.org/wiki/Nassim_Nicholas_Taleb#/media/File:Genealogy_map_of_topics_treated_by_Nassim_Taleb.jpg) - Describes the various categories of uncertainty, epistemology limits and statistical subjects touching on Taleb's Black swan / antifragility etc. ideas
-
----v
-
-## 👪 Dependency
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="width: 500px" src="./img/3.4-xkcd-dependency.png" />
-
-</pba-col>
-<pba-col>
-
-- [Confusion](https://secureteam.co.uk/2021/02/24/what-is-a-dependency-confusion-attack/)
-- [Hijacking](https://blog.sonatype.com/bladabindi-njrat-rat-in-jdb.js-npm-malware)
-- [Hardware side-channel attacks](https://hackaday.com/2019/09/13/side-channel-attack-shows-vulnerabilities-of-cryptocurrency-wallets/)
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- yes in software and hardware, you are at risk of attack from poisoned deps through non-maintenance, up to targeted exploitation.
-  One mitigation is vendoring these, need systems inn place to monitor.
-  Dependabot is not sufficient.
-- Also in dependance on specific operational contexts.
-  For example that it is legal to operate the software for nodes.
-
-Image source: <https://xkcd.com/2347/>
-
----v
-
-## 🦸 Dependency in Polkadot
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="width: 500px" src="./img/dependency-polkadot-js.png" />
-
-</pba-col>
-<pba-col>
-
-> _Foundational_ to Polkadot ecosystem!
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- [Jaco](https://github.com/jacogr) is effectively the only maintainer of how _just about everything_ communicates with Substrate nodes!
-- [Capi](https://github.com/paritytech/capi) is on the way, but just getting started.
-
----v
-
-## 🙈 Unknown unknowns
-
-<img rounded style="width: 800px" src="./img/DiveEdge.gif" />
-
-Notes:
-
-Outside of the system itself, we cannot guarantee/prove that every possible condition is accounted for in our models & system design.
-We must expect forces outside our system & it's model may interact in unexpected ways.
-Assumptions about context must be rigorously evaluated (i.e. - what does finality mean in the chain this pallet or contract lives in?)
-(Formal mathematical proofs reason only about the things we can and do account for.)
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Network Level
-
----v
-
-## 🕸️ Peer-to-Peer Networks
-
-<img style="width: 1000px" src="./img/3.4-network-topologies.png" />
-
----v
-
-## Network Attacks
-
-<pba-flex center>
-
-- Entry/Boot nodes and peer discovery
-- Data center faults
-- Traffic analysis and targeted takedowns
-- Eclipse attacks
-
-</pba-flex>
-
-Notes:
-
-The network lesson covers these, just a reminder that the network is not in the direct command of the consensus system, so it's a threat!
-
-- security & stability
-- privacy!
-  On chain might be ZK, but how about the gossip and RPCs?
-
-Boot nodes typically _hard coded_ to "bootstrap" and start peer discovery.
-Boot nodes can decide what peers to advertize, or can be inaccessible.
-Common data centers (AWS, GCP, ...) could fail or censor, potentially large number of peers go dark.
-Hard to hide! Most p2p traffic is easy to identify vs. web2 traffic.
-
----v
-
-## Node Queries
-
-Running a node is hard, most people outsource.
-
-<img style="width: 1000px" src="./img/3.4-node-queries.png" />
-
-These service have power to deceive, censor, and surveil.
-
----v
-
-## Multi-Chain Applications
-
-If running _one_ node is burdensome, try multiple.
-
-<img style="width: 700px" src="./img/3.4-multi-chain-apps.png" />
-
----v
-
-## Trustless Messaging
-
-In order to handle messages _without trust_,<br />systems must share common finality guarantees.
-
-`A` should never process a message from `B`,<br />where `B` is reverted and `A` is not.
-
----v
-
-## A Note on Synchronicity
-
-Smart contracts on a single chain (e.g. Ethereum)<br />can interact trustlessly because of their shared view of finality.
-
-Asynchronous systems can also share finality.<br />
-i.e., be members of the same consensus system.
-
----v
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Discussion
-
-**Minimum viable decentralization.**
-
-> What key aspects should be considered?
-
-Notes:
-
-- Quantitative: nodes needed (for what), incentives, ... FIXME TODO
-- Qualitative: social norms, ... FIXME TODO
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Consensus
-
----v
-
-## Mining Pools
-
-Proof of Work authority sets have no finite bound.<br />
-But people like to organize.
-
-\[Collaborating | Colluding\] authority sets creates risk.
-
-Notes:
-
-Call out that Nomination pools exist and are discussed in the NPoS lesson latter.
-Similar issues, but in a more bounded set.
-
----v
-
-## Mining Pools
-
-<img rounded style="width: 1000px" src="./img/mining-pools.png" />
-
-Notes:
-
-Source: [Buy Bitcoin Worldwide](https://buybitcoinworldwide.com/pages/mining/pools/img/pool-graph.png)
-
----v
-
-## Security Dilution
-
-Security is always a finite resource:
-
-<pba-flex center>
-
-- Centralized: Cost of corruption/influence
-- Proof of Work: Number of CPUs in the world
-- Proof of Stake: Value (by definition, finite)
-
-</pba-flex>
-
----v
-
-## Security Dilution
-
-Consensus systems compete for security,<br />and they have reason to attack each other.
-
-Emergence of obscure/niche "Proof of X" algorithms<br />to shelter from attack only goes so far.
-
----v
-
-## ⚔ Blockchain Wars
-
-Systems with high security have the<br />incentive to attack systems with low security<br />whom they perceive as competitors.
-
-> For fun and profit.
-
-Notes:
-
-"In ~~a galaxy~~ the universal consensus ~~far far away~~ not so far away..."
-
----v
-
-## ⚔ Proof of Work Battles
-
-<img rounded style="width: 1300px;" src="./img/3.4-51-percent-cost.png" />
-
-> What might it cost to successfully attack?
-
-Notes:
-
-- For PoW, hashing power for the same algo can be attacked!
-  Buying hash power is possible:
-- Most GPU miners switch tasks to the mine the highest paying (relative to some base currency) chain using software like <https://www.nicehash.com/>.
-- ASICs are less flexible, but also can to the highest paying coin.
-- Example: [ETH classic deep re-ogs](https://coingeek.com/ethereum-classic-experiences-51-attack-and-3000-block-reorg/)
-
----v
-
-## Proof of...<br />Nothing at Stake
-
-Forks are "free" to vote in favor of...<br />
-vote on them all!
-
-(If you are not eventually slashed!)
-
-> What might it cost to successfully attack?
-
-Notes:
-
-- Unlike PoW where voting on a chain costs something _extrinsic_ to the system, PoS has only _intrinsic_ measures to do accounting of consensus rules.
-- **Critical:** This was a problem with early naive implementations of PoS.
-  Modern PoS schemes avoid this specific problem by having the security deposit and slashing for equivocation (in a few slides)
-- Good explainer, source of image: <https://golden.com/wiki/Nothing-at-stake_problem-639PVZA>
-
----v
-
-## Proof of...<br /> _Relatively_ Nothing at Stake
-
-Risk-to-reward ratio of attacks is<br /> _relative to the valuation of the staked assets_.
-
-Rational actors take into account<br /> _extrinsic motivators_ in calculating the highest reward.
-
-> What might it cost to successfully attack?
-
-Notes:
-
-- Again PoS ha only _intrinsic_ measures to do accounting of consensus rules, but the system doesn't exist in a vacuum: the relative valuation of what is at stake needs to be accounted for.
-
----v
-
-## Validator Consolidation
-
-How many validators does a system need?
-
-Higher numbers should lead to a decrease in the ability for entities to collude.
-
-But validators are expensive, both economically and computationally.
-
-Notes:
-
-Yet another N-lemma to consider.
-
----v
-
-## PoS Economic Security
-
-Proposition: The upper bound of economic security in PoS is relative valuation can secure, that is correlated with the market capitalization of the network.
-
-> Market capitalization refers to the total market value of all assets inherent to a single company/chain/token.
-
-Notes:
-
-- This market capitalization could be company shares, or total ETH in existence, or total X token associated with a specific smart contract or parachain.
-
----v
-
-## ⚔ PoS Economic Security Battles
-
-<img rounded style="width: 1150px;" src="./img/market-cap-pos.png" />
-
-Notes:
-
-Here like in PoW we have relative safety in networks, but there is no way to "hop" from one chain to another, so the war is still in the relative security, but one stake cannot _directly_ attach another stake in a separate consensus system...
-
-What about an system of value _within_ consensus?
-
----v
-
-## DApp PoS Economic Security
-
-<img rounded style="width: 1200px;" src="./img/market-cap-polkadot-chains.png" />
-
-Notes:
-
-Consideration: these notes are an oversimplification! We may talk more about this kind of problem in NPoS lesson (Nuke thinks at least).
-The details of a formal analysis are out of scope for this Academy.
-
-Proposition: Total applications valuation of their assets (tokens on smart contracts, or parachains) is limited and that limit is correlated with the total economic security of the consensus system they reside in.
-
-In Polkadot's relay chain model, Nuke would argue it's feasible that an attack to extract value from a very highly valued asset could outweighs the cost of obtaining a _byzantine level of stake_ to execute.
-Therefore the sum of all parachains market cap is also limited as that same level of stake control would enable take over of all chains on it.
-
-Nuke argue this is the same for the sum of all contracts valuations on something like Ethereum.
-
----v
-
-## Authority Misbehavior
-
-<pba-flex center>
-
-- Equivocation
-  - Authorship: Proposing mutually<br />exclusive chains
-  - Finality: Voting for mutually<br />exclusive chains to be final
-- Invalidity
-- Lack of availability
-- **Intentional protocol abuse** ([selfish mining](https://golden.com/wiki/Selfish_mining_attack-39PMNNA))
-
-</pba-flex>
-
-Notes:
-
-We already talked consensus faults, but abuse is newer.
-Nuke argues "abuse" as a term here isn't the intended mechanism design, and is adverse to the health of the system.
-Selfish mining where it's impossible to _prove_ an author is withholding valid blocks to "cheat" by mining ahead of the rest of th network is a good example in the class of attacks that consensus authorities and others may have.
-
-...Could other actors abuse the protocols?
-
----v
-
-## Accountability of Authority
-
-Authority should imply accountability.
-
-No matter how you design an authority selection mechanism, some people will have a privileged position within it.
-
-Those who _choose_ to become authorities should be liable for their actions.
-
----v
-
-## Provability and Equivocation
-
-Some types of misbehavior are harder to prove than others.
-
-**Equivocation** is simple:<br />Someone can just produce two signed messages as cryptographic proof.
-
-Others rely on challenge-response games and dispute resolution.
-
-Notes:
-
-Nothing at stake solution, with the possible caveat of long range attacks
-[Weak subjectivity](https://blog.ethereum.org/2014/11/25/proof-stake-learned-love-weak-subjectivity) can still potentially cause the same behavior in a much harder to orchestra way, with bad actors having already have their stake released to produce a valid, finalized fork.
-
----v
-
-## Design Considerations<br />in Polkadot
-
-- More validators increases the state transition throughput of the network: parachains.
-- Individual shards have full economic freedom by being members of a larger consensus system.
-- _Superlinear_ slashing puts colluding validators at existential risk,<br />while well-meaning ones should have little to worry about).
-
-Notes:
-
-A few interesting design decisions in Polkadot's architecture.
-
-We will cover polkadot much more in depth latter!
-
----v
-
-## Transaction Censorship and Ordering
-
-Block authors choose the transactions they include and in what order.
-
-<pba-flex center>
-
-- Censorship attacks
-- "Maximal extractable value" (MEV)
-
-</pba-flex>
-
----v
-
-## Web3 Goal: Non-Censorship
-
-There are a lot more system users than system authorities.
-
-However, every transaction must be included by an authority.
-
-If no authority will include a user's transaction, they do not have _permissionless_ access.
-
-_If any authority (author) decides not to censor, it **may** be included._
-
-Notes:
-
-Most present systems have no mechanism to penalize censorship, and a much harder problem can be the ability to discover this is happening on the network at all, depending on the actors involved.
-
----v
-
-## Maximal Extractable Value (MEV)
-
-A measure of the value that block authors can extract based on their knowledge of pending transactions and ability to order them.
-
-<pba-flex center style="margin-left: -90px">
-
-- Frontrunning
-- Backrunning
-- Sandwiching
-
-</pba-flex>
-
-> <https://www.mev.wiki/>
-
-Notes:
-
-Emergent behavior.
-Not realized as possible by many until it quietly became the norm.
-
----v
-
-## Maximal Extractable Value
-
-> An environment in which detection means certain death...<br />
-> ...identifying someone’s location is as good as directly destroying them.<br /><br />
-> -- [Ethereum is a Dark Forest](https://www.paradigm.xyz/2020/08/ethereum-is-a-dark-forest) --
-
-Notes:
-
-Tell the story of this article, basically a white hat engineered obfuscation to try and remove funds in a bugged contract -> someone decoded, realized extractable valued, and front-ran them.
-
-This is now the norm on Ethereum at least, and further _it's becoming institutionalized_.
-
-<!-- FIXME TODO Dark Forest game on Ethereum testnet... or other zk game? -->
-
----v
-
-## 👼 Flashbots
-
-> Flashbots is a research and development organization formed to mitigate the negative externalities posed by Maximal Extractable Value (MEV) to stateful blockchains, starting with Ethereum.<br /><br />
-> -- [Flashbots](https://www.flashbots.net/) --
-
-Notes:
-
-This might be misleading, in that they are profiting in making MeV more effective and institutionalized!
-
----v
-
-## Flashbots 😈
-
-- **Flashbots Auction**: a marketplace for transaction ordering including the Flashbots Relay and MEV-Geth.
-- **MEV-Boost**: an out-of-protocol implementation of proposer-builder separation (PBS) for proof-of-stake Ethereum.
-- **Flashbots Protect**: an rpc endpoint that anyone can use for protection from frontrunning and failed transactions.
-- **Flashbots Data**: tools and dashboards to improve the transparency of MEV activity on Ethereum and the Flashbots Auction.
-
-Notes:
-
-Centralizing force, as information asymmetry generally drives towards a monopoly on MeV.
-Competitive landscape for this exists, and to Flashbots' credit, they seem genuine in trying to help the health of Ethereum by decentralizing...
-
-(BUT FIRST a discussion!)
-Especially in light of recent OFAC pressures revealing fragility in the system...
-
----v
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Discussion
-
-Front-running as a Service (FaaS) & MEV Auctions (MEVA)
-
-_A solution or crutch?_
-
-Notes:
-
-- Flashbots & Friends
-
----v
-
-## Compliance
-
-<img rounded style="width: 1000px" src="./img/tornado-ofac.png" />
-
-Notes:
-
-<https://cryptoslate.com/op-ed-is-ethereum-now-under-u-s-control-99-of-latest-relay-blocks-are-censoring-the-network/>
-
-- code is unstoppable, but platform _can_ sensor.
-  Ability -> responsibility (we may talk more on that latter)
-
----v
-
-## Social Context
-
-Social systems and norms can help _cover up_ weaknesses in protocols.
-
-> Public monitor to shame OFAC censors:
->
-> <https://www.mevwatch.info/>
-
-Notes:
-
-- Pressure from peers through breaking norms, perhaps even losing of authority in consensus due to this.
-  Peer reputation in computer networks, and here also in human ones.
-- Sometimes social pressures are healthy for the system, sometimes toxic depending on point of view and who benefits!
-- In monero "run your own node" culture helps keep it decentralized.<br />
-  Bitcoin big block wars show social pressures help decide the canonical forks.
-- Normalizing MEV for the profit of middlemen, providing extraction services in the worst case.
-
----v
-
-## Unbundling
-
-<img style="width: 1200px" src="./img/3.4-web3-stack.png" />
-
-Notes:
-
-From before, but here point out how this is getting more fine grained as well, and where a single actor would do it all (early bitcoin for example) we are moving more and more to appear.
-
-- Especially if more things like MeV can be enhanced by doing so.
-- This introduces more complexity and interfaces that can provide weakness (especially when a network is required!)
-
----v
-
-## Unbundling
-
-### _The vision of "blockspace" leads</br>more and more to this end_
-
----v
-
-## Diversity
-
-<img style="width: 1200px" src="./img/eth-client-diversity.png" />
-
-Notes:
-
-- Parity saved ETH (alt clients, and diversity)
-  - same runtime on chain, it's impossible to have an alt runtime.
-- all on GCP
-- All run same hardware (CPU, etc.)
-- ...
-
-- Image source, and good reference on this: <https://mirror.xyz/jmcook.eth/S7ONEka_0RgtKTZ3-dakPmAHQNPvuj15nh0YGKPFriA>
-
----
-
-## Final Thoughts
-
-- Complexity generally increases the risks of failures, but we should not fear it.<br />
-  $~~~$_Hypothesis: this \_usually_ makes systems more brittle.\_
-- Observable behavior trumps models and theory.<br />
-  $~~~$_Complex systems are not intuitive and may show your assumptions and models are wrong!_
-- This lesson was a _start_ down holes...
-  $~~~$_We encourage you to keep diving deeper!_
-
-Notes:
-
-- Risks and unknown unknowns increase exponentially so in many cases.
-- Examples of observables in things like MEV OFAC dominance and Babe fallback dominance etc.
-- Looking forward to explore the great unknown horizons in web3 together!
-
----
-
-## 🤝 Together, into the Deep
-
-<img rounded style="width: 800px" src="./img/DiveEdge.gif" />
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
----
-
-<!-- .slide: data-background-color="#000000" -->
-
-# Additional Slides
-
-Notes:
-
-For reference mostly, outside of formal class time 😀
-
----
-
-## Governance... Unstoppable?
-
-<iframe width="1120" height="630" src="https://www.youtube-nocookie.com/embed/Q6euy5W1js4" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
-
-[Unstoppable Code: The Difference Between Can't and Won't](https://www.youtube-nocookie.com/embed/Q6euy5W1js4)
-
-Notes:
-
-Watch _after class_!
-Perhaps assigned informally to everyone to watch in the next few days.
-
----v
-
-## Unstoppable Code
-
-> It seizes power from dominate forms of power: governments, corporations, states, associations, cultures, religions.
-> It seizes power, from these big things and gives it to little people.
-> And sooner or later, the people who are losing their undeserved, abusively applied power will start to fight back.
-> And at that point, we will start to find out how unstoppable our code is.<br /><br />
-> -- Andreas Antonopoulos --
-
----v
-
-## Can't vs. Won't
-
-> The moment you go over the the line from "can't to won't, what started as an ability becomes a responsibility.
-> And then if you claim that you don't have the ability anymore, that responsibility just became negligence, criminal negligence.<br /><br />
-> -- Andreas Antonopoulos --
-
-Notes:
-
-- The difference?
-- Silk road founder getting 2 life sentences + 40 years.
-- moral relativism -> "who's law?"
-- Don't make your "oops clause" -> not too narrow.
-
----
-
-## DAOs
-
-Decentralized Autonomous Organizations ([DAOs](https://www.investopedia.com/tech/what-dao/)).
-
-> A **coordination** mechanism.
-
----v
-
-## Democratic Systems
-
-Democratic Mediums is a directory of patterns<br /> for decision, deliberation, and noise.
-
-<pba-flex center>
-
-- <https://medlabboulder.gitlab.io/democraticmediums/>
-- <https://metagov.org/> -- weekly seminar
-- <https://www.smartcontractresearch.org/>
-
-</pba-flex>
-
-Notes:
-
-Very much encouraged to explore after class!
-Many novel and niece definitions in this wiki.
-
----
-
-## Modeling Behavior
-
-> [Token Engineering](https://tokenengineeringcommunity.github.io/website/)<br />
-> {especially the Academy & cadCAD Edu}
-
-Notes:
-
-Mostly free education and tools to dive deeper on tokenomics.
-Remember, these are _models_ of idealized systems in general, real world conditions will differ!
diff --git a/content/blockchain-contracts/utxo-privacy/page.md b/content/blockchain-contracts/utxo-privacy/page.md
deleted file mode 100644
index e573508b..00000000
--- a/content/blockchain-contracts/utxo-privacy/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Adding Privacy to the UTXO model
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/blockchain-contracts/utxo-privacy/slides.md b/content/blockchain-contracts/utxo-privacy/slides.md
deleted file mode 100644
index b8677093..00000000
--- a/content/blockchain-contracts/utxo-privacy/slides.md
+++ /dev/null
@@ -1,116 +0,0 @@
----
-title: Adding Privacy to the UTXO model
-description: Explore some techniques for adding privacy to the UTXO model
-duration: 30min
----
-
-# Adding Privacy to the UTXO model
-
----
-
-## Input/Output-based Cryptocurrencies
-
-- Transactions have a list of unspent transaction outputs (UTXOs) as its inputs
-- Each input is signed
-- The transaction is allowed to spend as much funds as the sum of its inputs
-- The transaction spends funds by creating outputs and by paying a fee
-
----
-
-## Input/Output-based Cryptocurrencies
-
-- Inputs must only refer to actually existing outputs (membership)
-- The output spent must not be prior spent (linkability)
-- The output's owner must consent to this transaction (ownership)
-- The transaction's inputs and outputs must be balanced (sum check)
-
----
-
-## Bitcoin
-
-- Bitcoin specifies the spent output.
-  This satisfies membership and linkability
-- Each Bitcoin output has a small, non-Turing complete program (Script) specifying how it can be spent
-- Each input has a `scriptSig` which proves the script is satisfied and this is an authorized spend (ownership)
-- The outputs cannot exceed the inputs, and the remainder becomes the fee (sum check)
-
----
-
-## ZK Proofs
-
-- ZK-SNARKs - A small proof that's fast to verify (<= $O(\sqrt{n})$)
-- ZK-sNARKs - A small proof that's not fast to verify (>= $O(n)$, frequently $O(n log n)$)
-- ZK-STARKs - A small proof that's fast to verify, based on hash functions
-- All of these can prove the execution of an arbitrary program (via an arithmetic circuit)
-- None of these reveal anything about the arguments to the program
-
----
-
-## Merkle Proofs
-
-- Merkle proofs support logarithmically proving an item exists in a tree
-- For 2\*\*20 items, the proof only requires 20 steps
-- Even if a ZK proof is superlinear, it's a superlinear encoding of a logarithmic solution
-
----
-
-## Private Membership
-
-- When an output is created on-chain, add it to the Merkle tree
-- When an input specifies an output, it directly includes the output it's spending
-- It also includes a Merkle proof the output exists _somewhere_ on chain, embedded in a ZK proof
-
----
-
-## Pedersen Commitments
-
-- A Pedersen commitment has a value (some number) and a mask (also some number)
-- There's as many masks as there private keys, hiding the contained value
-- Pedersen commitments can be extended to support multiple values
-
----
-
-## A New Output Definition
-
-<pba-flex center>
-
-- ID
-- Amount
-- Owner
-- Mask
-- All in a single<br />
-  Pedersen commitment
-
-</pba-flex>
-
----
-
-## Private Membership
-
-- We don't prove the included output exists on chain
-- We prove an output with identical fields exists on chain _yet with a different mask_
-- This allows spending a specific output without revealing which it is
-
----
-
-## Ownership and linkability
-
-- A ZK proof can take the output ID and apply some transformation
-- For every output ID, the transformation should output a single, unique ID
-- Not just anyone should be able to perform this transformation
-- This provides linkability, and if only the owner can perform the transformation, ownership
-
----
-
-## Sum check
-
-- One final ZK proof can demonstrate the sum of inputs - the sum of outputs = fee
-- There are much more efficient ways to prove this
-
----
-
-# Summary
-
-- This hides the output being spent and the amounts transacted
-- Combined with a stealth address protocol, which replaces addresses with one time keys, it hides who you're sending to as well
-- This builds a currency which is private w.r.t. its on-chain transactions
diff --git a/content/cryptography/README.md b/content/cryptography/README.md
deleted file mode 120000
index dd0ea36c..00000000
--- a/content/cryptography/README.md
+++ /dev/null
@@ -1 +0,0 @@
-index.md
\ No newline at end of file
diff --git a/content/cryptography/_materials/subkey-demo.md b/content/cryptography/_materials/subkey-demo.md
deleted file mode 100644
index f8c0213c..00000000
--- a/content/cryptography/_materials/subkey-demo.md
+++ /dev/null
@@ -1,124 +0,0 @@
-# Subkey Signature and HDKD (Hierarchical Deterministic Key Derivation) Demo
-
-Here are subkey examples for reference on use.
-Compliments the formal documentation [found here](https://github.com/paritytech/polkadot-sdk/tree/master/substrate/bin/utils/subkey#subkey).
-
-## Key Generation
-
-```sh
-subkey generate
-
-Secret phrase:       desert piano add owner tuition tail melt rally height faint thunder immune
-  Network ID:        substrate
-  Secret seed:       0x6a0ea68072cfd0ffbabb40801570fa5e9f3a88966eaed9dedaeb0cf140b9cd8d
-  Public key (hex):  0x7acdc47530002fbc50f413859093b7df90c27874aee732dca940ea4842751d58
-  Account ID:        0x7acdc47530002fbc50f413859093b7df90c27874aee732dca940ea4842751d58
-  Public key (SS58): 5Eqipnpt5asTm7sCFWQeJjsNJX5cYVJMid3zjKHjDUGKBJTo
-  SS58 Address:      5Eqipnpt5asTm7sCFWQeJjsNJX5cYVJMid3zjKHjDUGKBJTo
-```
-
-## Sign
-
-```sh
-echo -n 'Hello Polkadot Blockchain Academy' | subkey sign --suri 'desert piano add owner tuition tail melt rally height faint thunder immune'
-```
-
-> Note, this changes each execution, this is one viable signature: `f261d56b80e4b53c70dd2ba1de6b9384d85a8f4c6d912fd86acab3439a47992aa85ded04ac55c7525082dcbc815001cd5cc94ec1a907bbd8e3138cfc8a382683`
-
-## Verify
-
-```sh
-echo -n 'Hello Polkadot Blockchain Academy' | subkey verify  '0xf261d56b80e4b53c70dd2ba1de6b9384d85a8f4c6d912fd86acab3439a47992aa85ded04ac55c7525082dcbc815001cd5cc94ec1a907bbd8e3138cfc8a382683' \
-    '0x7acdc47530002fbc50f413859093b7df90c27874aee732dca940ea4842751d58'
-```
-
-> Expect `Signature verifies correctly.`
-
-## Tamper with the Message
-
-> Last char in `Public key (hex)` - AKA URI - is changed:
-
-```sh
-echo -n 'Hello Polkadot Blockchain Academy' | subkey verify \
-	'0xf261d56b80e4b53c70dd2ba1de6b9384d85a8f4c6d912fd86acab3439a47992aa85ded04ac55c7525082dcbc815001cd5cc94ec1a907bbd8e3138cfc8a382683' \
-    '0x7acdc47530002fbc50f413859093b7df90c27874aee732dca940ea4842751d59'
-Error: SignatureInvalid
-```
-
-## Hard Derivation
-
-```sh
-subkey inspect 'desert piano add owner tuition tail melt rally height faint thunder immune//polkadot' --network polkadot
-
-Secret Key URI `desert piano add owner tuition tail melt rally height faint thunder immune//polkadot` is account:
-  Network ID:        polkadot
- Secret seed:       0x3d764056127d0c1b4934725cb9faecf00ed0996daa84d24a903b906f319e06bf
-  Public key (hex):  0xce6ccb0af417ade10062ac9b553d506b67d16c61cd2b6ce85330bc023db7e906
-  Account ID:        0xce6ccb0af417ade10062ac9b553d506b67d16c61cd2b6ce85330bc023db7e906
-  Public key (SS58): 15ffBb8rhETizk36yaevSKM2MCnHyuQ8Dn3HfwQFtLMhy9io
-  SS58 Address:      15ffBb8rhETizk36yaevSKM2MCnHyuQ8Dn3HfwQFtLMhy9io
-```
-
-```sh
-subkey inspect 'desert piano add owner tuition tail melt rally height faint thunder immune//kusama' --network kusama
-
-Secret Key URI `desert piano add owner tuition tail melt rally height faint thunder immune//kusama` is account:
-  Network ID:        kusama
- Secret seed:       0xabd92064a63df86174acfd29ab3204897974f0a39f5d61efdd30099aa5f90bd9
-  Public key (hex):  0xf62e5d444f89e704bb9b412adc472f990e9a9f40725ac6ff3abee1c9b7625a63
-  Account ID:        0xf62e5d444f89e704bb9b412adc472f990e9a9f40725ac6ff3abee1c9b7625a63
-  Public key (SS58): J9753RnTdZJct5RmFQ6gFVdKSyrEjzYwvYUBufMX33PB7az
-  SS58 Address:      J9753RnTdZJct5RmFQ6gFVdKSyrEjzYwvYUBufMX33PB7az
-```
-
-## Soft Derivation from Secret
-
-```sh
-subkey inspect 'desert piano add owner tuition tail melt rally height faint thunder immune//polkadot/0' --network polkadot
-
-Secret Key URI `desert piano add owner tuition tail melt rally height faint thunder immune//polkadot/0` is account:
-  Network ID:        polkadot
- Secret seed:       n/a
-  Public key (hex):  0x4e8dfdd8a386ae37b8731dba5480d5cc65739023ea24f1a09d88be1bd9dff86b
-  Account ID:        0x4e8dfdd8a386ae37b8731dba5480d5cc65739023ea24f1a09d88be1bd9dff86b
-  Public key (SS58): 12mzv68gS8Zu2iEdt4Ktkt48JZSKyFSkAVjvtgYhoa42NLNa
-  SS58 Address:      12mzv68gS8Zu2iEdt4Ktkt48JZSKyFSkAVjvtgYhoa42NLNa
-```
-
-```sh
-subkey inspect 'desert piano add owner tuition tail melt rally height faint thunder immune//polkadot/1' --network polkadot
-
-Secret Key URI `desert piano add owner tuition tail melt rally height faint thunder immune//polkadot/1` is account:
-  Network ID:        polkadot
- Secret seed:       n/a
-  Public key (hex):  0x2e8b3090b17b12ea63029f03d852af71570e8e526690cc271491318a45785e33
-  Account ID:        0x2e8b3090b17b12ea63029f03d852af71570e8e526690cc271491318a45785e33
-  Public key (SS58): 1242YwUZGBQ84btGSGdSX4swf1ibfSaCDR1sr1ejC9KQ1NbJ
-  SS58 Address:      1242YwUZGBQ84btGSGdSX4swf1ibfSaCDR1sr1ejC9KQ1NbJ
-```
-
-## Soft Derivation from Public
-
-Note: We use addresses here because Subkey does not derive paths from a raw public key (AFAIK).
-
-```sh
-subkey inspect 12mzv68gS8Zu2iEdt4Ktkt48JZSKyFSkAVjvtgYhoa42NLNa/0
-
-Public Key URI `12mzv68gS8Zu2iEdt4Ktkt48JZSKyFSkAVjvtgYhoa42NLNa/0` is account:
-  Network ID/Version: polkadot
-  Public key (hex):   0x40f22875159420aca51178d1baf2912c18dcb83737dd7bd39dc6743da326dd1c
-  Account ID:         0x40f22875159420aca51178d1baf2912c18dcb83737dd7bd39dc6743da326dd1c
-  Public key (SS58):  12UA12xuDnEkEsEDrR4T4Cf3S1Hyi2C7B6hJW8LTkcsZy8BX
-  SS58 Address:       12UA12xuDnEkEsEDrR4T4Cf3S1Hyi2C7B6hJW8LTkcsZy8BX
-```
-
-```sh
-subkey inspect 12mzv68gS8Zu2iEdt4Ktkt48JZSKyFSkAVjvtgYhoa42NLNa/1
-
-Public Key URI `12mzv68gS8Zu2iEdt4Ktkt48JZSKyFSkAVjvtgYhoa42NLNa/1` is account:
-  Network ID/Version: polkadot
-  Public key (hex):   0xc62ec5cd7d83e1f41462d455bb47b6bad9ed5a14741a920ead8366c63746391b
-  Account ID:         0xc62ec5cd7d83e1f41462d455bb47b6bad9ed5a14741a920ead8366c63746391b
-  Public key (SS58):  15UrNnNSMpX49F3mWcCX7y4kMGcvnQxCabLMT3d8U5abpwr3
-  SS58 Address:       15UrNnNSMpX49F3mWcCX7y4kMGcvnQxCabLMT3d8U5abpwr3
-```
diff --git a/content/cryptography/addresses/page.md b/content/cryptography/addresses/page.md
deleted file mode 100644
index a3f19032..00000000
--- a/content/cryptography/addresses/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Addresses and Keys
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/cryptography/addresses/slides.md b/content/cryptography/addresses/slides.md
deleted file mode 100644
index 87e56c11..00000000
--- a/content/cryptography/addresses/slides.md
+++ /dev/null
@@ -1,307 +0,0 @@
----
-title: Addresses and Keys
-description: Addresses and keys in cryptography
-duration: 30 min
----
-
-# Addresses and Keys
-
----
-
-# Outline
-
-<pba-flex center>
-
-1. Binary Formats
-1. Seed Creation
-1. Hierarchical Deterministic Key Derivation
-
-</pba-flex>
-
----
-
-## Binary Display Formats
-
-When representing binary data, there are a few different display formats you should be familiar with.
-
-Hex: 0-9, a-f
-
-Base64: A-Z, a-z, 0-9, +, /
-
-Base58: Base64 without 0/O, I/l, +, and /
-
-Notes:
-
-Be very clear that this is a display format that we use to _transmit binary data through text_. The same data can be encoded with any of these formats, it's just important to know which one you're using to decode. Data is not typically stored in these formats unless it has to be transmitted through text.
-
----
-
-## Binary Display Formats Example
-
-Every hex character is 4 bits.</br>
-Every base64 character is 6 bits.</br>
-base58 characters are usually _about_ 6 bits.</br>
-
-```text
-binary: 10011111 00001010 10011110 10011000 01001100 11010011 10110010 00000101
-hex:    9   f    0   a    9   e    9   8    4    c   d   3    b   2    0   5
-base64: n     w      q      e      m     E      z      T      s     g      U=
-base58: T     b      u      H      z     e      3      c      t     k      c
-
-hex:    9f0a9e984cd3b205
-base64: nwqemEzTsgU=
-base58: TbuHze3ctkc
-```
-
-Notes:
-
-It turns out that converting from hex/base64 to base58 can in theory take n^2 time!
-
----
-
-# Mnemonics and Seed Creation
-
-Notes:
-
-These are all different _representation_ of a secret. Fundamentally doesn't really change anything.
-
----
-
-## Seeds are secrets
-
-Recall, both symmetric and asymmetric cryptography require a secret.
-
----
-
-## Mnemonics
-
-Many wallets use a dictionary of words and give people phrases,<br />often 12 or 24 words, as these are easier to back up/recover than byte arrays.
-
-Notes:
-
-High entropy needed.
-People are _bad_ at being random.
-Some people create their own phrases... this is usually stupid.
-
----
-
-## Dictionaries
-
-<pba-cols>
-<pba-col>
-
-There are some standard dictionaries to define which words (and character sets) are included in the generation of a phrase. Substrate uses the dictionary from BIP39.
-
-</pba-col>
-<pba-col>
-
-| No. | word    |
-| --- | ------- |
-| 1   | abandon |
-| 2   | ability |
-| 3   | able    |
-| 4   | about   |
-| 5   | above   |
-
-<pba-flex style="font-size: .6em;" center>
-
-_The first 5 words of the [BIP39 English dictionary](https://github.com/bitcoin/bips/blob/master/bip-0039/english.txt)_
-
-</pba-col>
-</pba-cols>
-
----
-
-## Mnemonic to Secret Key
-
-Of course, the secret key is a point on an elliptic curve, not a phrase.
-
-BIP39 applies 2,048 rounds of the SHA-512 hash function<br />to the mnemonic to derive a 64 byte key.
-
-Substrate uses the entropy byte array from the mnemonic.
-
----
-
-## Portability
-
-Different key derivation functions affect the ability to use the same mnemonic in multiple wallets as different wallets may use different functions to derive the secret from the mnemonic.
-
----
-
-## Cryptography Types
-
-Generally, you will encounter 3 different modern types of cryptography across most systems you use.
-
-- Ed25519
-- Sr25519
-- ECDSA
-
-We will go more in depth in future lectures!
-
-Notes:
-
-You may have learned RSA in school. It is outdated now, and requires _huge_ keys.
-
----
-
-## What is an address?
-
-An address is a representation of a public key, potentially with additional contextual information.
-
-Notes:
-
-Having an address for a symmetric cryptography doesn't actually make any sense, because there is no
-public information about a symmetric key.
-
----
-
-## Address Formats
-
-Addresses often include a checksum so that a typo cannot change one valid address to another.
-
-```text
-Valid address:   5GEkFD1WxzmfasT7yMUERDprkEueFEDrSojE3ajwxXvfYYaF
-Invalid address: 5GEkFD1WxzmfasT7yMUERDprk3ueFEDrSojE3ajwxXvfYYaF
-                                          ^
-                                          E changed to 3
-```
-
-Notes:
-
-It hasn't been covered yet, but some addresses even go _extra fancy_ and include an error correcting code in the address.
-
----
-
-## SS58 Address Format
-
-SS58 is the format used in Substrate.
-
-It is base58 encoded, and includes a checksum and some context information.
-Almost always, it is 2 bytes of context and 2 bytes of checksum.
-
-```text
-base58Encode( context | public key | checksum )
-```
-
-Notes:
-`|` here stands for concatenation.
-
-For ECDSA, the public key is 33 bytes, so we use the hash of it in place of the public key.
-
-There are a lot more variants here, but this is by far the most common one.
-
-[reference](https://docs.substrate.io/reference/address-formats/)
-
----
-
-## HDKD
-
-Hierarchical Deterministic Key Derivation
-
-<img style="width: 1100px;" src="./img/HD-Deterministic-Wallet.png" />
-
----
-
-## Hard vs. Soft
-
-Key derivation allows one to derive (virtually limitless)<br />child keys from one "parent".
-
-Derivations can either be "hard" or "soft".
-
----
-
-## Hard vs. Soft
-
-<img style="width: 1200px;" src="./img/soft-vs-hard-derivation.png" />
-
----
-
-## Hard Derivation
-
-Hard derivation requires the secret key and derives new child secret keys.
-
-Typical "operational security" usages should favor hard derivation over soft derivation because hard derivations avoid leaking the sibling keys, unless the original secret is compromised.
-
-Always do hard paths first, then conclude in soft paths.
-
----
-
-## Hard Derivation in Wallets
-
-Wallets can derive keys for use in different consensus systems while only needing to back up one secret plus a pattern for child derivation.
-
-<img style="width: 1000px;" src="./img/Hard-Derivation-in-Wallets.png" />
-
----
-
-## Hard Derivation in Wallets
-
-Let's imagine we want to use this key on multiple networks, but we don't want the public keys to be connected to each other.
-
-<img style="width: 1000px;" src="./img/Hard-Derivation-in-Wallets.png" />
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Subkey Demo
-
-## Hard Derivation
-
-Notes:
-
-Hard keys: Take a _path_ (data like a name/index), concatenate with the original key, and hash it for a new key.
-They reveal nothing about keys above them, and only with the _path_ between it and children could they be recovered.
-
----
-
-## Soft Derivation
-
-Soft derivation allows one to create derived addresses from only the public key.
-Contrary to hard derivation, _all_ keys are related.
-
-Notes:
-
-- With any key and the paths to children and. or parents, the public _and_ private keys can be recovered.
-- Soft derivations can break some niche advanced protocols, but our sr25519 crate avoids supporting protocols that conflict with soft derivations.
-
----
-
-## Soft Derivation
-
-- Note that these generate new addresses, but use the same secret seed.
-- We can also use the same paths, but only using the Account ID from `//polkadot`. It generates the same addresses!
-
----
-
-## Soft Derivation in Wallets
-
-Wallets can use soft derivation to link all payments controlled by a single private key, without the need to expose the private key for the address derivation.
-
-**Use case:** _A business wants to generate a new address for each payment, but should be able to automatically give customers an address without the secret key owner deriving a new child._
-
-Notes:
-
-On the use case, taking each payment at a different address could help make the association between payment and customer.
-
-See: <https://wiki.polkadot.network/docs/learn-accounts#soft-vs-hard-derivation>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Subkey Demo
-
-## Soft Derivation
-
-Notes:
-
-See the Jupyter notebook and/or HackMD cheat sheet for this lesson.
-
-Mention that these derivations create entirely new secret seeds.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/cryptography/advanced-signatures/page.md b/content/cryptography/advanced-signatures/page.md
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-# Advanced Digital Signatures
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
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diff --git a/content/cryptography/advanced-signatures/slides.md b/content/cryptography/advanced-signatures/slides.md
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----
-title: Advanced Digital Signatures
-description: More exotic digital signature methods
-duration: 1 hour
----
-
-# Advanced Digital Signatures
-
----
-
-### Certificates
-
-A certificate is essentially a witness statement concerning one or more public keys. It is a common usage of digital signatures, but _it is not a cryptographic primitive_!
-
-Notes:
-
-A certificate is one issuing key signing a message containing another certified key, which attests to some properties or relationship about the certified key.
-
-We must already trust the issuing key to give this attestation any significance, traditionally provided under "Certificate Authority" or "Web of Trust" schemes.
-
----
-
-### Certificates
-
-A certification system specified conventions on who is allowed to issue certificates, the rules over their issuance (e.g. time limits and revocation) as well as their format and semantics.
-
-For example, the certificate transparency protocol for TLS certificates helps protect against compromised Certificate Authorities.
-
-Notes:
-
-Certificate transparency: [explanation](https://certificate.transparency.dev/howctworks/) and [dashboard](https://ct.cloudflare.com/)
-
-- Maybe mention PGP web-of-trust style schemes
-
----
-
-### Certificates in Web3
-
-We are building systems that don't have a "Certificate Authority".<br />
-But we can still use certificates in some niche instances.
-
-Notes:
-
-Potential example to give verbally:
-
-- Session keys are a set of keys that generally run in online infrastructure.
-  An account, whose keys are protected, can sign a transaction to certify all the keys in the set.
-- Session keys are used to sign operational messages, but also in challenge-response type games to prove availability by signing a message.
-
----
-
-### Multi-Signatures
-
-We often want signatures that must be signed<br />by multiple parties to become valid.
-
-<pba-flex center>
-
-- Require some threshold of members to<br />agree to a message
-- Protect against key loss
-
-</pba-flex>
-
----
-
-### Types of Multi-Signature
-
-<pba-flex center>
-
-- Verifier enforced
-- Cryptographic threshold
-- Cryptographic non-threshold<br />(a.k.a. signature aggregation)
-
----
-
-### Verifier Enforced Multiple Signatures
-
-We assume that there is some verifier, who can check that some threshold of individual keys have provided valid signatures.
-
-This could be a trusted company or third party.
-For our purposes, _it's a blockchain_.
-
----
-
-### Verifier Enforced Multiple Signatures
-
-Multiple signatures enforced by a verifier generally provide a good user experience, as no interaction is required from the participants.
-
-Notes:
-
-This good experience comes at the cost of using state and more user interactions with the system, but is generally low.
-
-Even in a web3 system, the verifier can be _distinct_ from the blockchain. 5 people can entrust a verifier with the identity of "all 5 signed this" associated to a verifier-owned private key.
-
----
-
-### Cryptographic Multi-Sigs
-
-We want a succinct way to demonstrate that everyone from some set of parties have signed a message. This is achieved purely on the signer side (without support from the verifier).
-
-<pba-flex center>
-
-_Example: "The five key holders have signed this message."_
-
----
-
-### Key Generation for Multi-Sigs
-
-In regular multi-signatures,<br />signatures from individual public keys are aggregated.
-
-Each participant can choose their own key to use for the multi-signature.
-
-Notes:
-
-In some cases, a security requirement of these systems is that every participant demonstrates ownership of the public key submitted for the multi-signature, otherwise security can be compromised.
-
----
-
-### Cryptographic Threshold Multi-Sigs
-
-This makes more compact signatures compatible with legacy systems. Unlike a regular multi-sig, the public key is associated with a _threshold_ number of signing parties, so not all parties are needed to take part in the signing process to create a valid signature.
-
-This requires MPC protocols and may need multiple rounds of interaction to generate the final signature. They may be vulnerable to DoS from a malfunctioning (or malicious) key-holder.
-
-<pba-flex center>
-
-_Example: "5 of 7 key holders have signed this message."_
-
-Notes:
-
-These require multi-party computation (MPC) protocols, which add some complexity for the signing users.
-
----
-
-### Key Generation - Threshold
-
-Threshold multi-signature schemes require that all signers run a _distributed key generation_ (DKG) protocol that constructs key _shares_.
-
-The secret encodes the threshold behavior, and signing demands some threshold of signature _fragments_.
-
-This DKG protocol breaks other useful things, like hard key derivation.
-
----
-
-### Schnorr Multi-Sigs
-
-Schnorr signatures are primarily used for threshold multi-sig.
-
-- Fit legacy systems nicely, and can reduce fees on blockchains.
-- Reduce verifier costs in bandwidth & CPU time, so great for certificates.
-- Could support soft key derivations.
-
----
-
-### Schnorr Multi-Sigs
-
-However, automation becomes tricky.
-
-We need agreement upon the final signer list and two random nonce contributions from each prospective signer, before constructing the signature fragments.
-
----
-
-### BLS Signatures
-
-BLS signatures are especially useful for aggregated (non-threshold) multi-signatures (but can be used for threshold as well).
-
-Signatures can be aggregated without advance agreement upon the signer list, which simplifies automation and makes them useful in consensus.
-
-Verifying individual signatures is _slow_, but verifying aggregated ones is relatively fast.
-
-(Coming to Substrate soonish.)
-
----
-
-### BLS Signatures
-
-Allows multiple signatures generated under multiple public keys for multiple messages to be aggregated into a single signature.
-
-<pba-flex center>
-
-- Uses heavier pairing friendly elliptic curves than ECDSA/Schnorr.
-- Very popular for consensus.
-
-<pba-flex>
-
----
-
-### BLS Signatures
-
-However...
-
-- DKGs remain tricky (for threshold).
-- Soft key derivations are typically insecure for BLS.
-- Verifiers are hundreds of times slower than Schnorr, due to using pairings, for a single signature.
-- But for hundreds or thousands of signatures on the same message, aggregated signature verification can be much faster than Schnorr.
-
----
-
-### Schnorr and BLS Summary
-
-Schnorr & BLS multi-signatures avoid complicating verifier logic,<br />but introduce user experience costs such as:
-
-- DKG protocols
-- Reduced key derivation ability
-- Verification speed
-
----
-
-### Ring Signatures
-
-- Ring signatures prove the signer lies within some "anonymity set" of signing keys, but hide which key actually signed.
-- Ring signatures come in many sizes, with many ways of presenting their anonymity sets.
-- Anonymous blockchain transactions typically employ ring signatures (Monero, ZCash).
-
-Notes:
-
-- ZCash uses a ring signature based upon Groth16 zkSNARKs which makes the entire chain history be the anonymity set.
-- Monero uses ring signatures with smaller signer sets.
-- Ring signatures trade some _non-repudation_ for _privacy_.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/cryptography/basic-signatures/page.md b/content/cryptography/basic-signatures/page.md
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-# Digital Signature Basics
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
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diff --git a/content/cryptography/basic-signatures/slides.md b/content/cryptography/basic-signatures/slides.md
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----
-title: Digital Signature Basics
-description: Hands-on application of digital signature
-duration: 1 hour
----
-
-# Digital Signatures Basics
-
----
-
-## Signature API
-
-Signature libraries should generally all expose some basic functions:
-
-- `fn generate_key(r) -> sk;` <br /> Generate a `sk` (secret key) from some input `r`.
-- `fn public_key(sk) -> pk;` <br /> Return the `pk` (public key) from a `sk`.
-- `fn sign(sk, msg) -> signature;` <br /> Takes `sk` and a message; returns a digital signature.
-- `fn verify(pk, msg, signature) -> bool;` <br /> For the inputs `pk`, a message, and a signature; returns whether the signature is valid.
-
-Notes:
-
-The input `r` could be anything, for example the movement pattern of a mouse.
-
-For some cryptographies (ECDSA), the verify might not take in the public key as an input. It takes in the message and signature, and returns the public key if it is valid.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Subkey Demo
-
-## Key Generation and Signing
-
-Notes:
-
-See the Jupyter notebook and/or HackMD cheat sheet for this lesson.
-
-1. Generate a secret key
-1. Sign a message
-1. Verify the signature
-1. Attempt to alter the message
-
----
-
-## Hash Functions
-
-There are two lessons dedicated to hash functions.<br />But they are used as part of all signing processes.
-
-For now, we only concern ourselves with using Blake2.
-
----
-
-## Hashed Messages
-
-As mentioned in the introduction,<br />it's often more practical to sign the hash of a message.
-
-Therefore, the sign/verify API may be _used_ like:
-
-<pba-flex center>
-
-- `fn sign(sk, H(msg)) -> signature;`
-- `fn verify(pk, H(msg), signature) -> bool;`
-
-</pba-flex>
-
-Where `H` is a hash function (for our purposes, Blake2).<br />
-This means the verifier will need to run the correct hash function on the message.
-
----
-
-## Cryptographic Guarantees
-
-Signatures provide many useful properties:
-
-- Confidentiality: Weak, the same as a hash
-- Authenticity: Yes
-- Integrity: Yes
-- Non-repudiation: Yes
-
-Notes:
-
-If a hash is signed, you can prove a signature is valid _without_ telling anyone the actual message that was signed, just the hash.
-
----
-
-## Signing Payloads
-
-Signing payloads are an important part of system design.<br />
-Users should have credible expectations about how their messages are used.
-
-For example, when a user authorizes a transfer,<br />they almost always mean just one time.
-
-Notes:
-
-There need to be explicit rules about how a message is interpreted. If the same signature can be used in multiple contexts, there is the possibility that it will be maliciously resubmitted.
-
-In an application, this typically looks like namespacing in the signature payload.
-
----
-
-## Signing and Verifying
-
-<img style="height: 600px" src="./img/sig-verify-flow.svg" />
-
-Notes:
-
-Note that signing and encryption are _not_ inverses.
-
----
-
-## Replay Attacks
-
-Replay attacks occur when someone intercepts and resends a valid message.<br />
-The receiver will carry out the instructions since the message contains a valid signature.
-
-<pba-flex center>
-
-- Since we assume that channels are insecure, all messages should be considered intercepted.
-- The "receiver", for blockchain purposes, is actually an automated system.
-
-</pba-flex>
-
-Notes:
-
-Lack of _context_ is the problem.
-Solve by embedding the context and intent \_within the message being signed.
-Tell the story of Ethereum Classic replays.
-
----
-
-## Replay Attack Prevention
-
-Signing payloads should be designed so that they can<br />only be used _one time_ and in _one context_.<br />
-Examples:
-
-<pba-flex center>
-
-- Monotonically increasing account nonces
-- Timestamps (or previous blocks)
-- Context identifiers like genesis hash and spec versions
-
----
-
-# Signature Schemes
-
----
-
-## ECDSA
-
-- Uses Secp256k1 elliptic curve.
-- ECDSA (used initially in Bitcoin/Ethereum) was developed to work around the patent on Schnorr signatures.
-- ECDSA complicates more advanced cryptographic techniques, like threshold signatures.
-- Nondeterministic
-
----
-
-## Ed25519
-
-- Schnorr signature designed to reduce mistakes in implementation and usage in classical applications, like TLS certificates.
-- Signing is 20-30x faster than ECDSA signatures.
-- Deterministic
-
----
-
-## Sr25519
-
-Sr25519 addresses several small risk factors that emerged<br />from Ed25519 usage by blockchains.
-
----
-
-## Use in Substrate
-
-- Sr25519 is the default key type in most Substrate-based applications.
-- Its public key is 32 bytes and generally used to identify key holders (likewise for ed25519).
-- Secp256k1 public keys are _33_ bytes, so their _hash_ is used to represent their holders.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/cryptography/encryption/page.md b/content/cryptography/encryption/page.md
deleted file mode 100644
index 8c094b17..00000000
--- a/content/cryptography/encryption/page.md
+++ /dev/null
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-# Encryption
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/cryptography/encryption/slides.md b/content/cryptography/encryption/slides.md
deleted file mode 100644
index 567f155d..00000000
--- a/content/cryptography/encryption/slides.md
+++ /dev/null
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----
-title: Encryption
-description: A lesson on symmetric and asymmetric encryption.
-duration: 1 hour
----
-
-# Encryption
-
----
-
-## Goals for this lesson
-
-<pba-flex center>
-
-- Learn about the differences between symmetric and asymmetric encryption.
-
-</pba-flex>
-
----
-
-## Symmetric Cryptography
-
-Symmetric encryption assumes all parties begin with some shared secret information, a potentially very difficult requirement.<br />The shared secret can then be used to protect further communications from others who do not know this secret.
-
-In essence, it gives a way of _extending_ a shared secret over time.
-
----
-
-## Symmetric Encryption
-
-<img style="width: 1100px" src="./img/Symmetric-Cryptography.png" />
-
-Examples: ChaCha20, Twofish, Serpent, Blowfish, XOR, DES, AES
-
----
-
-## Symmetric Encryption API
-
-Symmetric encryption libraries should generally all expose some basic functions:
-
-- `fn generate_key(r) -> k;` <br /> Generate a `k` (secret key) from some input `r`.
-- `fn encrypt(k, msg) -> ciphertext;` <br /> Takes `k` and a message; returns the ciphertext.
-- `fn decrypt(k, ciphertext) -> msg;` <br /> Takes `k` and a ciphertext; returns the original message.
-
-It always holds that `decrypt(k, encrypt(k, msg)) == msg`.
-
-Notes:
-
-The input `r` is typically a source of randomness, for example the movement pattern of a mouse.
-
----
-
-## Symmetric Encryption Guarantees
-
-Provides:
-
-- Confidentiality
-- Authenticity\*
-
-Does not provide:
-
-- Integrity\*
-- Non-Repudiation
-
-Notes:
-
-- Authenticity: The message could only be sent by someone who knows the shared secret key. In most cases, this is functionally authentication to the receiving party.
-- Integrity: There is no proper integrity check, however the changed section of the message will be gibberish if it has been changed. Detection of gibberish could function as a form of integrity-checking.
-
----
-
-## Non-repudiation for Symmetric Encryption
-
-There is cryptographic proof that the secret was known to the producer of the encrypted message.
-
-<br />
-
-_However_, knowledge of the secret is not restricted to one party: Both (or all) parties in a symmetrically encrypted communication know the secret. Additionally, in order to prove this to anyone, they must _also_ gain knowledge of the secret.
-
-Notes:
-
-The degree of non-repudiation given by pure symmetric crytography is not very useful.
-
----
-
-## Symmetric Encryption
-
-#### _Example: XOR Cipher_
-
-<pba-cols>
-<pba-col>
-
-The encryption and decryption functions are identical: applying a bitwise XOR operation with a key.
-
-</pba-col>
-<pba-col style="padding-right: 100px">
-
-```text
-Plain: 1010  -->Cipher: 0110
-Key:   1100  |          1100
-       ----  |          ----
-       0110--^          1010
-```
-
-Notes:
-
-A plaintext can be converted to ciphertext, and vice versa, by applying a bitwise XOR operation with a key known to both parties.
-
-</pba-col>
-</pba-cols>
-
----
-
-## Symmetric Encryption
-
-#### ⚠ Warning ⚠
-
-We typically expect symmetric encryption to preserve little about the original plaintext.
-We caution however that constructing these protocols remains delicate, even given secure primitives, with two classical examples being unsalted passwords and the [ECB penguin](https://tonybox.net/posts/ecb-penguin/).
-
----
-
-### ECB penguin
-
-<pba-cols>
-<pba-col>
-
-<img style="width: 300px" src="./img/ECB-Penguin.png" />
-
-_Original image_
-
-</pba-col>
-<pba-col>
-
-<img style="width: 300px" src="./img/ECB-Penguin-Encrypted.png" />
-
-_Encrypted image_
-
-(by blocks)
-
-</pba-col>
-<pba-col>
-
-<img style="width: 300px" src="./img/ECB-Penguin-Secure.png" />
-
-_Encrypted image_
-
-(all at once)
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-The ECB penguin shows what can go wrong when you encrypt a small piece of data, and do this many times with the same key, instead of encrypting data all at once.
-
-Image sources: <https://github.com/robertdavidgraham/ecb-penguin/blob/master/Tux.png> and <https://github.com/robertdavidgraham/ecb-penguin/blob/master/Tux.ecb.png> and <https://upload.wikimedia.org/wikipedia/commons/5/58/Tux_secure.png>
-
----
-
-## Asymmetric Encryption
-
-- Assumes the sender does not know the recipient's secret "key" 🎉😎
-- Sender only knows a special identifier of this secret
-- Messages encrypted with the special identifier can only be decrypted with knowledge of the secret.
-- Knowledge of this identifier does not imply knowledge of the secret, and thus cannot be used to decrypt messages encrypted with it.
-- For this reason, the identifier may be shared publicly and is known as the _public key_.
-
----
-
-## Asymmetric Encryption
-
-<img style="height: 600px" src="./img/asymmetric-crypto-flow.svg" />
-
----
-
-## Why "Asymmetric"?
-
-_Using only the public key_, information can be transformed ("encrypted") such that only those with knowledge of the secret are able to inverse and regain the original information.
-
-i.e. Public key is used to encrypt but a different, _secret_, key must be used to decrypt.
-
----
-
-## Asymmetric Encryption API
-
-Asymmetric encryption libraries should generally all expose some basic functions:
-
-- `fn generate_key(r) -> sk;` <br /> Generate a `sk` (secret key) from some input `r`.
-- `fn public_key(sk) -> pk;` <br /> Generate a `pk` (public key) from the private key `sk`.
-- `fn encrypt(pk, msg) -> ciphertext;` <br /> Takes the public key and a message; returns the ciphertext.
-- `fn decrypt(sk, ciphertext) -> msg;` <br /> For the inputs `sk` and a ciphertext; returns the original message.
-
-It always holds that `decrypt(sk, encrypt(public_key(sk), msg)) == msg`.
-
-Notes:
-
-The input `r` is typically a source of randomness, for example the movement pattern of a mouse.
-
----
-
-## Asymmetric Encryption Guarantees
-
-Provides:
-
-- Confidentiality
-
-Does not provide:
-
-- Integrity\*
-- Authenticity
-- Non-Repudiation
-
-Notes:
-
-- Authenticity: The message could only be sent by someone who knows the shared secret key. In most cases, this is functionally authentication to the receiving party.
-- Integrity: There is no proper integrity check, however the changed section of the message will be gibberish if it has been changed. Detection of gibberish could function as a form of integrity-checking.
-
----
-
-## Diffie-Hellman Key Exchange
-
-<img style="height: 500px" src="./img/Diffie-Hellman_Key_Exchange_horizontal.svg" />
-
-Mixing Paint Visualization
-
-Notes:
-
-Mixing paint example.
-Image Source: <https://upload.wikimedia.org/wikipedia/commons/4/46/Diffie-Hellman_Key_Exchange.svg>
-
----
-
-## Authenticated Encryption
-
-Authenticated encryption adds a **M**essage **A**uthentication **C**ode to additionally provide an _authenticity_ and _integrity_ guarantee to encrypted data.
-
-A reader can check the MAC to ensure the message was constructed by someone knowing the secret.
-
-Notes:
-
-Specifically, this authenticity says that _anyone who does not know the sender's secret_ could not construct the message.
-
-Generally, this adds ~16-32 bytes of overhead per encrypted message.
-
----
-
-## AEAD (**A**uthenticated **E**ncryption **A**dditional **D**ata)
-
-AEAD is authenticated with some extra data which is unencrypted, but does have integrity and authenticity guarantees.
-
-Notes:
-
-Authenticated encryption and AEAD can work with both symmetric and asymmetric cryptography.
-
----
-
-## AEAD Example
-
-Imagine a table with encrypted medical records stored in a table, where the data is stored using AEAD. What are the advantages of such a scheme?
-
-```text
-UserID -> Data (encrypted), UserID (additional data)
-```
-
-Notes:
-By using this scheme, the data is always associated with the userID. An attacker could not put that entry into another user's entry.
-
----
-
-## Hybrid Encryption
-
-Hybrid encryption combines the best of all worlds in encryption. Asymmetric encryption establishes a shared secret between the sender and a specific public key, and then uses symmetric encryption to encrypt the actual message. It can also be authenticated.
-
-Notes:
-
-In practice, asymmetric encryption is _almost always_ hybrid encryption.
-
----
-
-## Cryptographic Properties
-
-| Property        | Symmetric | Asymmetric | Authenticated | Hybrid + Authenticated |
-| --------------- | --------- | ---------- | ------------- | ---------------------- |
-| Confidentiality | Yes       | Yes        | Yes           | Yes                    |
-| Authenticity    | Yes\*     | No         | Yes\*         | Yes                    |
-| Integrity       | No\*      | No\*       | Yes           | Yes                    |
-| Non-repudiation | No        | No\*       | No            | No\*                   |
-
-Notes:
-
-- Symmetric-Authentication and Authenticated-Authenticity: The message could only be sent by someone who knows the shared secret key. In most cases, this is functionally authentication to the receiving party.
-- Symmetric-Integrity and Asymmetric-Integrity: There is no proper integrity check, however the message will be gibberish if it has been changed. Detection of gibberish could function as a form of integrity-checking.
-- Non-Repudation: Even though none of these primitives provide non-repudiation on their own, it's very possible to add non-repudation to asymmetric and hybrid schemes via signatures.
-- Note that encryption also, most importantly, makes the data _available_ to everyone who should have access.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/cryptography/exotic-primitives/page.md b/content/cryptography/exotic-primitives/page.md
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-# Exotic Primitives
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
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diff --git a/content/cryptography/exotic-primitives/slides.md b/content/cryptography/exotic-primitives/slides.md
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----
-title: Exotic Primitives
-description: More cutting edge cryptography used in blockchain
-duration: 1 hour
----
-
-# Exotic Primitives
-
----
-
-# Outline
-
-<pba-flex center>
-
-1. [Verifiable Random Functions (VRFs)](#verifiable-random-functionsvrfs)
-1. [Erasure coding](#erasure-coding)
-1. [Shamir Secret Sharing](#shamir-secret-sharing)
-1. [Proxy Re-Encryption](#proxy-reencryption)
-1. [ZK Proofs](#zk-proofs)
-
-</pba-flex>
-
----
-
-## Verifiable Random Functions<br />(VRFs)
-
-<widget-center>
-
-- Used to obtain <ins>private randomness</ins>, that is <ins>publicly verifiable</ins>
-
-- A variation on a signature scheme:
-  - still have private/public key pairs, input as message
-  - in addition to signature, we get an output
-
----
-
-## VRF Interface
-
-- `sign(sk, input) -> signature`
-
-- `verify(pk, signature) -> option output`
-
-- `eval(sk,input) -> output`
-
-Notes:
-
-The output of verification being an option represents the possibility of an invalid signature
-
----
-
-## VRF Output properties
-
-- Output is a deterministic function of _key_ and _input_
-  - i.e. eval should be deterministic
-- It should be pseudo-random
-- But until the VRF is revealed, only the holder<br />of the secret key knows the output
-- Revealing output does not leak secret key
-
----
-
-## VRF Usage
-
-- Choose input after key, then the key holder cannot influence the output
-- The output then is effectively a random number known only to the key holder
-- But they can later reveal it, by publishing the VRF proof (signature)
-
-Notes:
-
-The signature proves that this is the output associated to their input and public key.
-
----
-
-## VRF Example
-
-- Playing a card game in a distributed and trustless way
-- For player A to draw a card, the players agree on a new random number x
-- A's card is determined by
-  `eval(sk_A,x) mod 52`
-- To play the card, A publishes the signature
-
----
-
-## VRF Extensions
-
-- Threshold VRFs / Common coin
-
-  - Generate the same random number if $t$ out of $n$ people participate
-
-- RingVRFs
-
-  - The VRF output could be from any one of a group of public keys.
-
-Notes:
-
-Common coins were used in consensus before blockchains were a thing.
-Dfinity based their consensus on this.
-But this needs a DKG, and it's unclear if a decentralized protocol can do those easily.
-
-A participant in a RingVRF could still only reveal _one_ random number.
-
----
-
-## Erasure Coding
-
-_Magical data expansion_
-
-- Turn data into pieces (with some redundancy) so it can be reconstructed even if some pieces are missing.
-
-- A message of $k$ symbols is turned into a coded message of $n$ symbols and can be recovered from any $k$ of these $n$ symbols
-
----
-
-## Erasure Coding Intuition
-
-Erasure coding relies on both parties sharing an understanding of what possible messages are valid. This lets mistakes be noticed and corrected.
-
-Imagine you are receiving a message, and you know ahead of time that the only two possible messages you would receive are `file` and `ruin`.
-
-Notes:
-
-This concept of a subset of messages being valid is super common in real life, and occurs all over the place.
-At a restaurant, when they ask you if you want soup or salad, even if you mumble they will probably understand you.
-
----v
-
-## Erasure Coding Intuition
-
-How would you classify each of the following words?
-
-<span style="color: red;">file</span> pile pale tale tall rule tail rail rain <span style="color: blue;">ruin</span>
-
----v
-
-## Erasure Coding Intuition
-
-How would you classify each of the following words?
-
-<span style="color: red;">file pile pale tale tall</span> <span style="color: purple;">rule</span> <span style="color: blue;"> tail rail rain ruin</span>
-
-You can classify them based on how close they are to a valid input. This also means we can find the errors in these messages.
-
-Notes:
-
-There is no perfect way to separate these, but one very reasonable one is to do it based on the edit distance of the received word with any valid messsage you could receive.
-
----v
-
-## Erasure Coding Intuition
-
-Now, you are receiving messages that could be `msg1` or `msg2`. Can you apply the same technique? Is it as easy to separate received messages?
-
-What if you receive `msg3`?
-
-Notes:
-
-If the messages are not far apart, it is impossible to distinguish in many cases. There is not enough "distance" between the two possibilities.
-
----v
-
-## Erasure Coding Intuition
-
-With erasure coding, we extend each message magically so they are different enough. The sender and receiver know the same encoding procedure. These extensions will be very different, even if the messages are similar.
-
-`msg1`<span style="color: red;"> `jdf`</span> and `msg2`<span style="color: red;"> `ajk`</span>
-
-Notes:
-
-It is actually always possible to make the extra magic only appended to the message. This is called a _systematic encoding_.
-
-For those curious about how the "magic" works:
-
-The magic here is polynomials, and the fact that a polynomial of degree $n$ is completely determined by $n+1$ points. There are many good explanations online.
-
----
-
-## Erasure Coding
-
-<img style="width: 1000px;" src="./img/erasure-code.svg" />
-
----
-
-## Erasure Coding Classical use
-
-- Used for noisy channels
-- If a few bits of the coded data are randomly flipped,<br /> we can still recover the original data
-- Typically $n$ is not much bigger than $k$
-
----
-
-## Use in Decentralized Systems
-
-- We have data we want to keep publicly available
-
-  - but not have everyone store
-  - but we don't trust everyone who is storing pieces
-
-- Typically we use $n$ much bigger than $k$
-
----
-
-## Shamir Secret Sharing
-
-_Redundancy for your secrets_
-
-- Turn data (typically a secret) into pieces so it can be reconstructed from some subset of the pieces.
-
-- A secret is turned into $n$ shares, and be recovered by any $k$ of the shares. $k-1$ shares together reveals nothing about the secret.
-
----
-
-## Shamir Secret Sharing
-
-<img style="height: 600px" src="./img/shamir-secret-sharing.png" />
-
-Notes:
-
-Image source: <https://medium.com/clavestone/bitcoin-multisig-vs-shamirs-secret-sharing-scheme-ea83a888f033>
-
----
-
-## Pros and Cons
-
-- Can reconstruct a secret if you lose it.
-- So can other people who collect enough shares.
-
----
-
-## Proxy Reencryption
-
-Generate keys to allow a third party to transform encrypted data so someone else can read it, without revealing the data to the third party.
-
----
-
-## Proxy Reencryption
-
-<img rounded style="height: 600px" src="./img/proxy-reencryption.png" />
-
-Notes:
-
-[img source](https://scrapbox.io/layerx/Proxy_Re-Encryption%28PRE%29%E3%81%A8NuCypher)
-
----
-
-## Proxy Reencryption API
-
-- `fn encrypt(pk, msg) -> ciphertext;` <br /> Takes your public key and a message; returns ciphertext.
-- `fn decrypt(sk, ciphertext) -> msg;` <br /> Takes your private key and a ciphertext; returns the message.
-- `fn get_reencryption_key(sk, pk) -> rk;` <br /> Takes your private key, and the recipient's public key; returns a reencryption key.
-- `fn reencrypt(rk, old_ciphertext) -> new_ciphertext;` <br /> Take a reencryption key, and transform ciphertext to be decrypted by new party.
-
----
-
-## ZK Proofs
-
-How do we do private operations on a public blockchain<br />and have everyone know that they were done correctly?
-
-Notes:
-
-(we are working on substrate support for these and will use them for protocols)
-
----
-
-## What is a ZK Proof?
-
-- A prover wants to convince a verifier that something is true without revealing why it is true.
-
-- They can be interactive protocols, but mostly we'll be dealing with the non-interactive variety.
-
----
-
-## What can we show?
-
-- NP relation: `function(statement, witness) -> bool`
-
-- Prover knows a witness for a statement:
-
-  - They want to show that they know it (_a proof of knowledge_)
-
-  - ... Without revealing anything about the witness (_ZK_)
-
----
-
-## ZK Proof Interface
-
-- NP relation: `function(statement, witness) -> bool`
-
-- `prove(statement, witness) -> proof`
-
-- `verify(statement, proof) -> bool`
-
----
-
-## ZK Proof Example
-
-_Example:_ Schnorr signatures are ZK Proofs
-
-- They show that the prover knows the private key (the discrete log of the public key) without revealing anything about it.
-- The statement is the public key and the witness the private key.
-
----
-
-## zk-SNARK
-
-**Z**ero-**K**nowledge **S**uccinct **N**on-interactive **Ar**gument of **K**nowledge
-
-- **Zero knowledge** - the proof reveals nothing about the witness that was not revealed by the statement itself.
-- **Succinct** - the proof is small
-- **Proof of knowledge** - if you can compute correct proofs of a statement, you should be able to compute a witness for it.
-
----
-
-## What can we show?
-
-- NP relation: `function(statement, witness) -> bool`
-
-  - They want to show that they know it (_a proof of knowledge_)
-
-  - ... Without revealing anything about the witness (_ZK_)
-
-- With a small proof even if the witness is large (_succinctness_)
-
----
-
-## What can we show?
-
-- There are many schemes to produce succinct ZK proofs of knowledge (_ZK-SNARKs_) for every NP relation.
-
----
-
-## ZK Proof Scaling
-
-A small amount of data, a ZK proof, and execution time can be used to show properties of a much larger dataset which the verifier doesn't need to know.
-
----
-
-## Scaling via ZK Proofs in Blockchain
-
-- Large amount of data - a blockchain
-- Verifier is e.g. an app on a mobile phone
-
-Notes:
-
-e.g. Mina do a blockchain with a constant size proof (of correctness of execution and consensus) using recursive SNARKs.
-
----
-
-## Scaling via ZK Proofs in Blockchain
-
-- The verifier is a blockchain: very expensive data and computation costs.
-
-- Layer 2s using ZK rollups
-
-Notes:
-
-Of which Ethereum has many, ZKsync, ZKEVM etc.
-Polkadot already scales better!
-
----
-
-## Privacy
-
-<pba-flex center>
-
-A user has private data, but we can show<br />publicly that this private data is correctly used.<br />
-An example would a private cryptocurrency:
-
-- Keep who pays who secret
-- Keep amounts secret, <br /> _But show they are positive!_
-
-</pba-flex>
-
-Notes:
-
-You can do some of keeping amounts secret without ZK-SNARKs, but the positive part is difficult.
-To do everything well, ZK-SNARKs are needed in e.g. ZCash and its many derivatives e.g. Manta.
-
----
-
-## Practical Considerations
-
-- Very powerful primitive
-
-- Useful for both scaling and privacy
-
-- One can design many protocols with ZK Proofs that wouldn't otherwise be possible
-
----
-
-## Downside
-
-- Slow prover time for general computation
-- To be fast, need to hand optimize
-- Very weird computation model:<br />
-  Non-deterministic arithmetic circuits
-
----
-
-## Downsides Conclusion?
-
-- So if you want to use this for a component,<br />expect a team of skilled people to work for at least a year on it...
-- But if you are watching this 5 years later,<br />people have built tools to make it less painful.
-
----
-
-## Succinct Proving<br />with Cryptography?
-
-<pba-flex center>
-
-- ZK friendly hashes
-- Non-hashed based data structures
-  - RSA accumulators
-  - Polynomial commitment based<br />
-    (Verkle trees)
-
-</pba-flex>
-
----
-
-## Summary
-
-- VRF: Private randomness that is later publicly verifiable
-- Erasure Coding: Making data robust against losses with redundancy
-- Shamir Secret Sharing: Redundancy for your secrets.
-- Proxy Re-encryption: Allow access to your data _with cryptography_.
-- ZK Proofs: Just magic, but expensive magic
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/cryptography/hash-based-data-structures/page.md b/content/cryptography/hash-based-data-structures/page.md
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-# Hash Based Data Structures
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
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-
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diff --git a/content/cryptography/hash-based-data-structures/slides.md b/content/cryptography/hash-based-data-structures/slides.md
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----
-title: Hash Based Data Structures
-description: Hash functions in Substrate
-duration: 1 hour
----
-
-# Hash Based Data Structures
-
----
-
-## Comparison to<br />Pointer Based Data Structures
-
-- A hash references the _content_ of some data;
-- A pointer tells you where to find it;
-- We can not have cycles of hashes.
-
----
-
-## Hash Chains
-
-<img style="width: 800px" src="./img/Hash-Chains.png" />
-
-A hash chain is a linked list using hashes to connect nodes.
-
-Notes:
-
-Each block has the hash of the previous one.
-
----
-
-## Merkle Trees
-
-<img style="width: 800px" src="./img/Merkle-tree-all-purple.png" />
-
-A binary Merkle tree is a binary tree using hashes to connect nodes.
-
-Notes:
-
-Ralph Merkle is a Berkeley alum!
-
----
-
-## Proofs
-
-- The root or head hash is a commitment to the entire data structure.
-- Generate a proof by expanding some but not all hashes.
-
-_Crucial for the trustless nature of decentralised cryptographic data systems!_
-
----
-
-## Proofs: Merkle Copaths
-
-<img style="width: 800px" src="./img/Merkle-Copaths.png" />
-
-Notes:
-
-Given the children of a node, we can compute a node
-Given the purple nodes and the white leaf, we can compute the white nodes bottom to top.
-If we compute the correct root, this proves that the leaf was in the tree
-
----
-
-## Security
-
-Collision resistance: we reasonably assume only one preimage for each hash,<br />therefore making the data structure's linkage persistent and enduring (until the cryptography becomes compromised 😥).
-
-Notes:
-
-Explain what could happen when this fails.
-
----
-
-## Proof Sizes
-
-Proof of a leaf has size $O(\log n)$<br />and so do proofs of updates of a leaf
-
----
-
-## Key-Value Databases and Tries
-
----
-
-## Key-value database
-
-The data structure stores a map `key -> value`.<br />
-We should be able to:
-
-<pba-flex center>
-
-- `put(key, value)`
-- `get(key)`
-- `delete(key)`
-
-</pba-flex>
-
----
-
-## Provability in key-value databases
-
-We should also be able to perform the following operations for a provable key-value database:
-
-1. For any key, if `<key,value>` is in the database, we can prove it.
-1. If no value is associated to a key, we need to be able to prove that as well.
-
----
-
-## Types of Data Structures
-
-- _**Trees**_ are rooted, directed acyclic graphs where each child has only one parent.
-- _**Merkle Trees**_ are _trees_ which use hashes as links.
-- _**Tries**_ are a particular class of _trees_ where:
-  - Given a particular piece of data, it will always be on a particular path.
-- _**Radix Tries**_ are a particular class of a trie where:
-  - The location of a value is determined the path constructed one digit at a time.
-- _**Patricia Tries**_ are _radix tries_ which are optimized to ensure lonely node-paths are consolidated into a single node.
-
-Notes:
-
-Just a selection we'll cover in this course.
-
----
-
-## Radix Trie
-
-_Words:_ to, tea, ted, ten, inn, A.
-
-<img style="width: 800px" src="./img/Trie.png" />
-
-Each node splits on the next digit in base $r$
-
-Notes:
-
-In this image, $r$ is 52 (26 lowercase + 26 uppercase).
-
----
-
-## Patricia Trie
-
-_Words:_ to, tea, ted, ten, inn, A.
-
-<img style="width: 700px" src="./img/Patricia-Trie.png" />
-
-If only one option for a sequence we merge them.
-
-<!-- TODO maybe some code stuff with extension nodes etc. -->
-
----
-
-## Patricia Trie Structures
-
-```rust
-pub enum Node {
-  Leaf {
-    partial_path: Slice<RADIX>,
-    value: Value
-  },
-  Branch {
-    partial_path: Slice<RADIX>,
-    children: [Option<Hash>; RADIX],
-    value: Option<Value>,
-  },
-}
-```
-
-Notes:
-
-The current implementation actually makes use of dedicated "extension" nodes instead of branch nodes that hold a partial path. There's a good explanation of them [here](https://ethereum.stackexchange.com/questions/39915/ethereum-merkle-patricia-trie-extension-node).
-
-Additionally, if the size of a value is particularly large, it is replaced with the hash of its value.
-
-<!-- TODO: Add a nice illustration similar to Shawn's dev-trie-backend-walk here. -->
-
----
-
-## Hash Trie
-
-- Inserting arbitrary (or worse, user-determined) keys into the Patricia tree can lead to highly unbalanced branches, enlarging proof-sizes and lookup times.
-- Solution: pre-hash the data before inserting it to make keys random.
-- _Resistance against partial collision is important._
-- Could be a Merkle trie or regular.
-
----
-
-## Computational and Storage <br />Trade-offs
-
-What radix $r$ is best?
-
-- Proof size of a leaf is $r \log_r n$
-  - $r=2$ gives the smallest proof for one leaf
-
-...but:
-
-- Higher branching at high levels of the tree can give smaller batch proofs.
-- For storage, it is best to read consecutive data so high $r$ is better.
-
----
-
-## Merkle Mountain Ranges
-
-- Efficient proofs and updates for a hash chain
-- Append only data structure
-- Lookup elements by number
-
----
-
-## Merkle Mountain Ranges
-
-<img style="width: 800px" src="./img/U-MMR-13.png" />
-
-Notes:
-
-we have several Merkle trees of sizes that are powers of two.
-The trees that are here correspond to the binary digits of 13 that are 1.
-
----
-
-## Merkle Mountain Ranges
-
-<img style="width: 800px" src="./img/U-MMR-14.png" />
-
----
-
-## Merkle Mountain Ranges
-
-<img style="width: 800px" src="./img/MMR-13.png" />
-
-Notes:
-
-- Not as balanced as a binary tree but close
-- Can update the peak nodes alone on-chain
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/cryptography/hashes/img/Hash-Chains.png b/content/cryptography/hashes/img/Hash-Chains.png
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diff --git a/content/cryptography/hashes/page.md b/content/cryptography/hashes/page.md
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-# Hash Functions
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/cryptography/hashes/slides.md b/content/cryptography/hashes/slides.md
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----
-title: Hash Functions
-description: Hash functions in Substrate
-duration: 1 hour
----
-
-# Hash Functions
-
----
-
-## Introduction
-
-We often want a succinct representation of some data<br />with the expectation that we are referring to the same data.
-
-##### A "fingerprint"
-
----
-
-## Hash Function Properties
-
-<pba-flex center>
-
-1. Accept unbounded size input
-1. Map to a bounded output
-1. Be fast to compute
-1. Be computable strictly one-way<br />(difficult to find a pre-image for a hash)
-1. Resist pre-image attacks<br />(attacker controls one input)
-1. Resist collisions<br />(attacker controls both inputs)
-
-</pba-flex>
-
----
-
-## Hash Function API
-
-A hash function should:
-
-- Accept an unbounded input size (`[u8]` byte array)
-- Return a fixed-length output (here, a 32 byte array).
-
-```rust
-fn hash(s: &[u8]) -> [u8; 32];
-```
-
----
-
-## Example
-
-**Short input (5 bytes):**
-
-```text
-hash('hello') =
- 0x1c8aff950685c2ed4bc3174f3472287b56d9517b9c948127319a09a7a36deac8
-```
-
-**Large input (1.2 MB):**
-
-```text
-hash(Harry_Potter_series_as_string) =
- 0xc4d194054f03dc7155ccb080f1e6d8519d9d6a83e916960de973c93231aca8f4
-```
-
----
-
-## Input Sensitivity
-
-Changing even 1 bit of a hash function _completely_ scrambles the output.
-
-```text
-hash('hello') =
- 0x1c8aff950685c2ed4bc3174f3472287b56d9517b9c948127319a09a7a36deac8
-```
-
-```text
-hash('hellp') =
- 0x7bc9c272894216442e0ad9df694c50b6a0e12f6f4b3d9267904239c63a7a0807
-```
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Rust Demo
-
-## Hashing a Message
-
-Notes:
-
-See the Jupyter notebook and/or HackMD cheat sheet for this lesson.
-
-1. Use a longer message
-1. Hash it
-1. Verify the signature on the hash
-
----
-
-## Speed
-
-Some hash functions are designed to be slow.
-
-These have applications like password hashing, which would slow down brute-force attackers.
-
-For our purposes, we generally want them to be fast.
-
----
-
-## Famous Hash Algorithms
-
-<pba-flex center>
-
-- xxHash a.k.a TwoX (non-cryptographic)
-- MD5
-- SHA1
-- RIPEMD-160
-- SHA2-256 (aka SHA256) &c.
-- SHA3
-- Keccak
-- Blake2
-
-xxHash64 is about 20x faster than Blake2.
-
-</pba-flex>
-
----
-
-## Hash Functions in Blockchains
-
-<pba-flex center>
-
-- Bitcoin: SHA2-256 & RIPMD-160
-- Ethereum: Keccak-256 (though others supported via EVM)
-- Polkadot: Blake2 & xxHash (though others supported via host functions)
-
-</pba-flex>
-
-Notes:
-
-Substrate also implements traits that provide 160, 256, and 512 bit outputs for each hasher.
-
-Exercise: Write your own benchmarking script that compares the performance of these algorithms with various input sizes.
-
----
-
-### Hashing Benchmarks
-
-<img rounded style="height: 650px" src="./img/crypto-bench.png" />
-
-Notes:
-
-Benchmarks for the _cryptographic_ hashing algorithms.
-Source: <https://www.blake2.net/>
-
----
-
-#### XXHash - _Fast_ hashing algorithm
-
-<img rounded style="height: 600px" src="./img/Benchmark-XXHash.png" />
-
-Notes:
-
-Benchmarks for the XX-hash algorithms.
-Source: <https://github.com/Cyan4973/xxHash#benchmarks>
-
----
-
-## Non-Cryptographic Hash Functions
-
-Non-cryptographic hash functions provide weaker<br />guarantees in exchange for performance.
-
-They are OK to use when you know that the input is not malicious.
-
-**If in doubt, use a cryptographic hash function.**
-
----
-
-## One Way
-
-Given a hash, it should be difficult to find an input value (pre-image)<br />that would produce the given hash.
-
-That is, given `H(x)`, it should be difficult to find `x`.
-
-Notes:
-
-We sometimes add random bytes to pre-images to prevent guesses based on context (e.g., if you are hashing "rock, paper, scissors", then finding a pre-image is trivial without some added randomness.)
-
----
-
-## Second Pre-Image Attacks
-
-Given a hash and a pre-image, it should be difficult to find _another_<br />pre-image that would produce the same hash.
-
-Given `H(x)`, it should be difficult to find any `x'`
-
-such that `H(x) == H(x')`.
-
-Notes:
-
-Since most signature schemes perform some internal hashing, this second pre-image would also pass signature verification.
-
----
-
-## Collision Resistance
-
-It should be difficult for someone to find two messages that<br />hash to the same value.
-
-It should be difficult to find an `x` and `y`
-
-such that `H(x) == H(y)`.
-
----
-
-## Collision Resistance
-
-**Difference from second pre-image attack:**
-
-In a second pre-image attack, the attacker only controls one input.
-
-In a collision, the attacker controls both inputs.
-
-They may attempt to trick someone into signing one message.
-
-Notes:
-
-Attacker has intention to impersonate the signer with the other. Generally speaking, even finding a
-single hash collision often results in the hash function being considered unsafe.
-
----
-
-## Birthday Problem
-
-<pba-cols>
-<pba-col style="font-size:smaller">
-
-> With 23 people, there is a 6% chance that someone will be born on a specific date, but a 50% chance that two share a birthday.
-
-- Must compare each output with every other, not with a single one.<br />
-- Number of possible "hits" increases exponentially for more attempts, reducing the expected success to the square-root of what a specific target would be.
-
-</pba-col>
-<pba-col>
-
-<img style="width: 700px; border-radius: 0;" src="./img/birthday-problem.svg" />
-
-</pba-col>
-</pba-cols>
-
----
-
-## Birthday Attack
-
-Thus, with a birthday attack, it is possible to find a collision of a hash function in $\sqrt {2^{n}}=2^{^{\frac{n}{2}}}$, with $\cdot 2^{^{\frac{n}{2}}}$ being the classical preimage resistance security.
-
-So, hash function security is only half of the bit space.
-
-Notes:
-
-e.g., a 256 bit hash output yields 2^128 security
-
-- <https://en.wikipedia.org/wiki/Birthday_attack>
-
-- <https://en.wikipedia.org/wiki/Birthday_problem>
-
----
-
-## Partial Resistance
-
-It should be difficult for someone to partially (for a substring of the hash output) find a collision or "second" pre-image.
-
-- Bitcoin PoW is a partial pre-image attack.
-- Prefix/suffix pre-image attack resistance reduces opportunity for UI attacks for address spoofing.
-- Prefix collision resistance important to rationalize costs for some cryptographic data structures.
-
----
-
-## Hash Function Selection
-
-<pba-flex center>
-
-When users (i.e. attackers) have control of the input, cryptographic hash functions must be used.
-
-When input is not controllable (e.g. a system-assigned index), a non-cryptographic hash function can be used and is faster.
-
-Notes:
-
-Only safe when the users cannot select the pre-image, e.g. a system-assigned index.
-
-Keccak is available for Ethereum compatibility.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Applications
-
----
-
-## Cryptographic Guarantees
-
-Let's see which cryptographic properties apply to hashes.
-
----v
-
-## Confidentiality
-
-Sending or publically posting a hash of some data $D$ keeps $D$ confidential, as only those who already knew $D$ recognize $H(D)$ as representing $D$.
-
-Both cryptographic and non-cryptographic hashes work for this. _only if the input space is large enough_.
-
----v
-
-## Confidentiality Bad Example
-
-Imagine playing rock, paper, scissors by posting hashes and then revealing. However, if the message is either "rock", "paper", or "scissors", the output will always be either:
-
-```text
-hash('rock') = 0x10977e4d68108d418408bc9310b60fc6d0a750c63ccef42cfb0ead23ab73d102
-hash('paper') = 0xea923ca2cdda6b54f4fb2bf6a063e5a59a6369ca4c4ae2c4ce02a147b3036a21
-hash('scissors') = 0x389a2d4e358d901bfdf22245f32b4b0a401cc16a4b92155a2ee5da98273dad9a
-```
-
-The other player doesn't need to undo the hash function to know what you played!
-
-Notes:
-
-The data space has to be _sufficiently large_.
-Adding some randomness to input of the hash fixes this. Add x bits of randomness to make it x bits of security on that hash.
-
----v
-
-## Authenticity
-
-Anyone can make a hash, so hashes provide no authenticity guarantees.
-
----v
-
-## Integrity
-
-A hash changes if the data changes, so it does provide integrity.
-
----v
-
-## Non-Repudiation
-
-Hashes on their own cannot provide authenticity, and as such cannot provide non-repudiation.
-
-However, if used in another cryptographic primitive that _does_ provide non-repudiation, $H(D)$ provides the same non-repudation as $D$ itself.
-
-Notes:
-
-This is key in digital signatures. However, it's important to realize that if $D$ is kept secret, $H(D)$ is basically meaningless.
-
----
-
-## Content-Derived Indexing
-
-Hash functions can be used to generate deterministic<br />and unique lookup keys for databases.
-
-Notes:
-
-Given some fixed property, like an ID and other metadata the user knows beforehand, they can always find the database entry with all of the content they are looking for.
-
----
-
-## Data Integrity Checks
-
-Members of a peer-to-peer network may host and share<br />file chunks rather than large files.
-
-In [Bittorrent](https://en.wikipedia.org/wiki/BitTorrent), each file chunk is hash identified so peers can<br /> _request and verify_ the chunk is a member of the larger,<br /> _content addressed_ file.
-
-Notes:
-
-The hash of the large file can also serve as a signal to the protocol that transmission is complete.
-
----
-
-## Account Abstractions
-
-Public keys can be used to authorize actions by signing of instructions.
-
-The properties of hash functions allow other kinds of representations.
-
----
-
-## Public Key Representation
-
-Because hashes serve as unique representations of other data,<br />that other data could include public keys.<br />
-A system can map a plurality of key sizes to a fixed length<br />(e.g. for use as a database key).
-
-For example, the ECDSA public key is 33 bytes:
-
-```text
-Public key (hex):
-  0x02d82cdc83a966aaabf660c4496021918466e61455d2bc403c34bde8148b227d7a
-
-Hash of pub key:
-  0x8fea32b38ed87b4739378aa48f73ea5d0333b973ee72c5cb7578b143f82cf7e9
-                                                                    ^^
-```
-
----
-
-## Commitment Schemes
-
-It is often useful to commit to some information<br /> without storing or revealing it:
-
-- A prediction market would want to reveal predictions only after the confirming/refuting event occurred.
-- Users of a system may want to discuss proposals without storing the proposal on the system.
-
-However, participants should not be able to modify their predictions or proposals.
-
----
-
-## Commit-Reveal
-
-<pba-flex center>
-
-1. Share a hash of data as a commitment ($c$)
-1. Reveal the data itself ($d$)
-
-<pba-flex>
-
-It is normal to add some randomness to the message<br />to expand the input set size:
-
-$$ hash(message + randomness) => commitment $$
-
-<pba-flex style="font-size: smaller;">
-
-Commitment: `0x97c9b8d5019e51b227b7a13cd2c753cae2df9d3b435e4122787aff968e666b0b`
-
----
-
-## Reveal
-
-Message with some added randomness:
-
-<pba-flex style="font-size: smaller;">
-
-> "I predict Boris Johnson will resign on 7 July 2022. facc8d3303c61ec1808f00ba612c680f"
-
----
-
-## Data Identifiers
-
-Sometimes people want to store information in one place and reference it in another. For reference, they need some "fingerprint" or digest.
-
-As an example, they may vote on executing some privileged instructions within the system.
-
-The hash of the information can succinctly represent the information and commit its creator to not altering it.
-
----
-
-## Data Structures (in Brief)
-
-This is the focus of a later lesson.
-
-Notes:
-For now, just a brief introduction.
-
----
-
-## Pointer-Based Linked Lists
-
-Pointer-based linked lists are a foundation of programming.
-
-But pointers are independent from the data they reference,<br />so the data can be modified while maintaining the list.
-
-That is, pointer-based linked lists are not tamper evident.
-
-<img src="./img/Hash-Chains.png" />
-
----
-
-## Hash-Based Linked Lists
-
-Hash-based lists make the reference related to the data they are referencing.<br />
-The properties of hash functions make them a good choice for this application.
-
-Any change at any point in the list would create downstream changes to all hashes.
-
----
-
-## Merkle Trees
-
-<img  src="./img/Merkle-Tree.png" />
-
-Notes:
-
-Each leaf is the hash of some data object and each node is the hash of its children.
-
----
-
-## Proofs
-
-Merkle trees allow many proofs relevant to the rest of this course,<br />e.g. that some data object is a member of the tree<br />without passing the entire tree.
-
-**_More info in the next lesson._**
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
----
-
-<!-- TODO: migrate below to Substrate slides? Or...?  -->
-
-## Hash Examples in Substrate
-
-**Sr25519 Signatures**
-
-Sr25519 hashes the message as part of its signing process.
-
-**Transactions**
-
-In transactions in Substrate, key holders sign a<br /> _hash of the instructions_ when the instructions<br />are longer than 256 bytes.
-
----
-
-## Database Keys
-
-**TwoX64** is safe to use when users (read: attackers)<br />cannot control the input, e.g. when a<br />database key is a system-assigned index.
-
-**Blake2** should be used for everything else.
-
-_Again, there is a whole lesson on hash-based data structures._
-
----
-
-## Other Uses of Hashes in Substrate
-
-Hashes are also used for:
-
-<pba-flex center>
-
-- Generating multisig accounts
-- Generating system-controlled accounts
-- Generating proxy-controlled accounts
-- Representing proposals
-- Representing claims (e.g. the asset trap)
-
-</pba-flex>
diff --git a/content/cryptography/in-context/page.md b/content/cryptography/in-context/page.md
deleted file mode 100644
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--- a/content/cryptography/in-context/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Cryptography In Context
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/cryptography/in-context/slides.md b/content/cryptography/in-context/slides.md
deleted file mode 100644
index 6a6daa3e..00000000
--- a/content/cryptography/in-context/slides.md
+++ /dev/null
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----
-title: Cryptography In Context
-description: Real-world considerations around cryptography
-duration: 1 hour
----
-
-# Cryptography in Context
-
----
-
-# Outline
-
-<pba-flex center>
-
-1. Keeping Secrets Secret
-1. Security and Usability
-
-</pba-flex>
-
----
-
-## Secrets
-
-What _is_ a secret in cryptography?
-
-Data that you know, that nobody else knows.
-
----
-
-## How Secrets Stay Secret
-
-In order for a cryptographic secret to stay secret, the _only_ thing about it that can be revealed is the output of known, secured cryptographic operations.
-
-- A (sufficiently random) secret can be hashed, and the hash revealed.
-- A private key can be used to generate a public key, and the public key revealed.
-- A private key can be used to generate a signature, and the signature revealed.
-
----
-
-## How Secrets Get Leaked
-
-1. Inadvertently leaking information about the secret during normal operation.
-1. Compromised digital or physical security leading to private key loss.
-
-Notes:
-
-Let's go over each of these in order.
-
----
-
-## Bad Randomness
-
-Some algorithms require randomness. If the randomness is compromised, the private key or encrypted message can possibly be exposed.
-
-Notes:
-
-[one source](https://learn.saylor.org/mod/book/view.php?id=36341&chapterid=18921)
-
----
-
-## Side Channel Attacks
-
-A side channel attack is when a cryptographic system is attacked, and the attacker has another source of information outputted by the system.
-
----
-
-## Timing Attacks
-
-A timing attack can be possible if any of the following<br /> depend on the contents of a secret:
-
-<pba-flex center>
-
-- Which instructions execute
-- Branching (if statements)
-- Memory access patterns
-
-</pba-flex>
-
-Notes:
-
-There are many crazy forms of side channel attack, but the primary one is timing. Timing is also the only one that gets reliably sent back over a long distance.
-
----
-
-## An Example
-
-Imagine this is the source code for a password checker:
-
-```rust
-fn verify_password(actual: &[u8], entered: &[u8]) -> bool {
- if actual.len() != entered.len() {
-    return false;
- }
-
- for i in 0..actual.len() {
-  if entered.get(i) != actual.get(i) {
-   return false;
-  }
- }
- true
-}
-```
-
-What's the problem?
-
-Notes:
-
-Imagine you compile this into a little binary, and you are able to hit it repeatedly. When sending a guess into this, what information do you get back?
-
-A boolean, and the amount of time from sending the password to getting back a response.
-
-The problem is that the amount of time for a response reveals information about the password. An attacker can send in guesses repeatedly, and if it takes a longer amount of time to respond, that means more of the guess is correct.
-
----
-
-## Example (Cont)
-
-What if we changed the code to look like this?
-
-```rust
-fn verify_password(actual: &[u8], entered: &[u8]) -> bool {
- actual == entered
-}
-```
-
-Is this safe?
-
-Notes:
-Now, we don't see any difference in the amount of lines of code or loops, right?
-
----
-
-## Example (Cont)
-
-What does the source code look like?
-
-```rust[0|1|7-9|15]
-// Use memcmp for bytewise equality when the types allow
-impl<A, B> SlicePartialEq<B> for [A]
-where
-    A: BytewiseEq<B>,
-{
-    fn equal(&self, other: &[B]) -> bool {
-        if self.len() != other.len() {
-            return false;
-        }
-
-        // SAFETY: `self` and `other` are references and are thus guaranteed to be valid.
-        // The two slices have been checked to have the same size above.
-        unsafe {
-            let size = mem::size_of_val(self);
-            memcmp(self.as_ptr() as *const u8, other.as_ptr() as *const u8, size) == 0
-        }
-    }
-}
-```
-
-Is this safe?
-
-Notes:
-
-Ok, still no. It looks like now the attacker can still figure out if the length of the password based on an early return. But what if we make sure all passwords are 16 bytes long. Now we are just using a single syscall. Is is safe then?
-
----
-
-## Example (Cont)
-
-Let's check on `memcmp`.
-
-```text
-memcmp(3) — Linux manual page
-
-/* snip */
-
-NOTES
-       Do not use memcmp() to compare security critical data, such as
-       cryptographic secrets, because the required CPU time depends on
-       the number of equal bytes.  Instead, a function that performs
-       comparisons in constant time is required.  Some operating systems
-       provide such a function (e.g., NetBSD's consttime_memequal()),
-       but no such function is specified in POSIX.  On Linux, it may be
-       necessary to implement such a function oneself.
-```
-
----
-
-## So how could we do it?
-
-This is from the `subtle` crate, which provides constant time equality.
-
-```rust[0|14-15|20-28]
-impl<T: ConstantTimeEq> ConstantTimeEq for [T] {
-    /// Check whether two slices of `ConstantTimeEq` types are equal.
-    ///
-    /// # Note
-    ///
-    /// This function short-circuits if the lengths of the input slices
-    /// are different.  Otherwise, it should execute in time independent
-    /// of the slice contents.
-    /* snip */
-    #[inline]
-    fn ct_eq(&self, _rhs: &[T]) -> Choice {
-        let len = self.len();
-
-        // Short-circuit on the *lengths* of the slices, not their
-        // contents.
-        if len != _rhs.len() {
-            return Choice::from(0);
-        }
-
-        // This loop shouldn't be shortcircuitable, since the compiler
-        // shouldn't be able to reason about the value of the `u8`
-        // unwrapped from the `ct_eq` result.
-        let mut x = 1u8;
-        for (ai, bi) in self.iter().zip(_rhs.iter()) {
-            x &= ai.ct_eq(bi).unwrap_u8();
-        }
-
-        x.into()
-    }
-}
-```
-
-Notes:
-
-Now we've seen how hard it can be just to stop a very simple leak of timing information. Let's see what an actual cryptographic library concerns itself with.
-
----
-
-## Ed25519's Guarantees
-
-This is an excerpt from the [ed25519](https://ed25519.cr.yp.to/) description.
-
-- **Foolproof session keys**. Signatures are generated deterministically; key generation consumes new randomness but new signatures do not. This is not only a speed feature but also a security feature.
-- **Collision resilience**. Hash-function collisions do not break this system. This adds a layer of defense against the possibility of weakness in the selected hash function.
-
----
-
-## Ed25519's Guarantees (Cont.)
-
-- **No secret array indices**. The software never reads or writes data from secret addresses in RAM; the pattern of addresses is completely predictable. The software is therefore immune to cache-timing attacks, hyperthreading attacks, and other side-channel attacks that rely on leakage of addresses through the CPU cache.
-- **No secret branch conditions**. The software never performs conditional branches based on secret data; the pattern of jumps is completely predictable. The software is therefore immune to side-channel attacks that rely on leakage of information through the branch-prediction unit.
-
----
-
-## Takeway
-
-Preventing side channel attacks is _hard_! Noticing sidechannel attacks is even harder!
-
-### DO NOT ROLL YOUR OWN CRYPTO
-
-Notes:
-
-Be very, very careful whenever you do _anything_ that touches a secret. That includes any operation involving the secret, or reading/writing it somewhere.
-
-When necessary, talk to a security expert or cryptographer.
-
----
-
-## Using Cryptographic Libraries Safely
-
-- Stay _above_ the abstraction barrier
-- Validate each primitive's assumptions when combining primitives
-- Use the most reputable library you can
-- Realize when things need serious consideration
-  - Some potentially scary terms: Curve point, padding schemes, IV, twisted curve, pairings, ElGamal
-
-Notes:
-
-Reputableness of a library is some combination of:
-
-- used by many people
-- audited for security
-- reliable cryptographic literature
-- minimal external dependencies
-- recommended by cryptographers
-
-If you get low-level enough in cryptography libraries to see these terms referenced in more than just a description, you're probably too low level.
-
----
-
-# Horror Stories
-
-Notes:
-
-Only go through a few of these based on interest and remaining time.
-
----v
-
-## PS3 Secret Key Leak
-
-**Problem**: Bad randomness
-
-**Description**: The ps3 developers didn't use randomness when signing with an algorithm that required randomness.
-
-**Consequence**: Every PS3 was hardcoded to trust that key. When hackers got the key, they were then able to pretend to be Sony and write any software that ran on the PS3. In practice, it made running pirated games trivial.
-
-Notes:
-
-[source](https://www.engadget.com/2010-12-29-hackers-obtain-ps3-private-cryptography-key-due-to-epic-programm.html)
-
----v
-
-## IOTA's Novel Hash Function
-
-**Problem**: Rolling your own crypto
-
-**Description**: IOTA was a cryptocurrency with a value of 1.9B at the time. They wrote their own hash function, and researchers found severe vulnerabilities.
-
-**Consequence**: Kind security researchers reported the flaw directly to devs. They had to pause the blockchain for 3 days, generate new address for _all_ accounts, and swap to KECCAK.
-
-Notes:
-
-IOTA originally rolled their own hash function in an effort to be quantum-proof.
-
-Some hash function weaknesses are weak. This was not. The proof of concept exploit literally found two hashes that correspond to a message for the blockchain sending a small amount of currency, and another that corresponded to a message sending a huge amount of money.
-
-[exploit POC](https://github.com/mit-dci/tangled-curl/blob/master/vuln-iota.md)
-[shutdown source](https://www.bitfinex.com/posts/215)
-
----v
-
-## How the NSA wiretapped all cellphone calls for years
-
-**Problem**: Small key space / secret technique
-
-**Description**: The standard for cellphone calls up until the mid-late 2000s (GSM A5/1) used 54-bit keys, and the method was meant to be secret. It did not stay secret, and became extremely easily crackable.
-
-**Consequence**: Intelligence agencies could and did easily wiretap calls. There were many brute-force attacks against the key space.
-
-Notes:
-
-When the standardization process started, professors proposed 128-bit keys. Western european (british especially) intelligence agencies wanted weaker security. Snowden eventually came out and said the NSA could easily read A5/1 calls.
-
-[article source](https://goodenoughsecurity.blogspot.com/2011/10/gsm-a51-substandard-security-pt2.html)
-[source on weakening](https://www.aftenposten.no/verden/i/Olkl/sources-we-were-pressured-to-weaken-the-mobile-security-in-the-80s)
-
----v
-
-## Why HTTPS isn't as secure as you'd hope
-
-**Problem**: Cryptographic primitive assumptions not upheld
-
-**Description**: Encryption _does not_ generally hide the length of the underlying message. HTTPS often uses compression before encryption. The compression makes duplicated strings smaller.
-
-**Consequence**: An exploit called BREACH can reveal a secret from an HTTPS-protected website in under 30 seconds. All websites have had to add mitigation to offset this attack.
-
-Notes:
-
-Mitigation looks like:
-
-- randomizing size of response content after compression
-- separating secrest from user input
-- disabling HTTP compression (this is expensive though)
-- randomizing secrets per request
-
-[source](https://arstechnica.com/information-technology/2013/08/gone-in-30-seconds-new-attack-plucks-secrets-from-https-protected-pages/)
-
----
-
-## Physical Security
-
-<img style="width: 900px;" src="./img/xkcd-physical-security.png" />
-
-Notes:
-
-Source is a classic XKCD comic.
-
----
-
-## Physical Security
-
-Full physical access to a running computer can usually let an attacker have full access to your secrets with enough effort.
-
-Some possible means:
-
-- Scanning all disk storage
-- Take out the RAM and swap it into a different computer to read (cold boot attack)
-- Proximate side-channel attacks
-  - RF emissions
-  - Power consumption
-  - Sound of a computer running
-
-Notes:
-
-Sources for exotic attacks:
-
-- [general survey of EM side channel attacks](https://arxiv.org/abs/1903.07703)
-- [sound-based attack](https://www.iacr.org/archive/crypto2014/86160149/86160149.pdf)
-- [EM side channel attack from 15m with 500 traces only](https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A1648290&dswid=6646)
-
----
-
-## HSMs
-
-An HSM is a **h**ardware **s**ecurity **m**odule. HSMs can make it much harder to impossible to steal cryptographic keys. An HSM will hold cryptographic keys, and perform operations on them.
-
-Notes:
-
-We don't go into this much, as there are many available resources around physical security and HSMs. This is just bringing up the ideas, in the context of what makes a cryptographic secret actually _secret_.
-
----
-
-## Security and Usability
-
-The accessibility of a secret is typically inversely proportional to the security.
-
-Making a secret more secure is often impractical, depending on the usage.
-
-Notes:
-
-This is not explicitly true in all cases, but it is a good rule of thumb. Additionally, note that impractical != impossible.
-
----
-
-## Thought Experiment
-
-Suppose I give you a secret that's too long to memorize.
-
-At the end of a year, if nobody else knows the secret, I'll give you a million dollars.
-
-What do you do?
-
----
-
-## Thought Experiment
-
-Suppose I give you a secret that's too long to memorize.
-
-At the end of a year, if nobody else knows the secret, I'll give you a million dollars.
-
-What do you do?
-
-### Destroy it
-
----
-
-## Thought Experiment
-
-Suppose I give you a secret that's too long to memorize.
-
-At the end of a year, if nobody else knows the secret **and you present me the secret**, I'll give you a million dollars.
-
-What do you do?
-
----
-
-## Thought Experiment
-
-Suppose I give you a secret that's too long to memorize.
-
-At the end of a year, if nobody else knows the secret **and you present me the secret**, I'll give you a million dollars.
-
-What do you do?
-
-### Hide it somewhere secure
-
-Notes: Like a bank vault, box buried in the woods, etc
-
----
-
-## Thought Experiment
-
-Suppose I give you a secret that's too long to memorize.
-
-At the end of a year, if nobody else knows the secret **and you present me the secret once per month**, I'll give you a million dollars.
-
-What do you do?
-
----
-
-## Thought Experiment
-
-Suppose I give you a secret that's too long to memorize.
-
-At the end of a year, if nobody else knows the secret **and you present me the secret every day**, I'll give you a million dollars.
-
-What do you do?
-
----
-
-## Application to Cryptographic Secrets
-
-Cryptographic secrets are easy to have multiple of.
-
-So don't make users use the same one for everything!
-
-As much as possible, one root secret shouldn't be _both_ used regularly, and extremely valuable.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/cryptography/index.md b/content/cryptography/index.md
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-# 🔐 Cryptography
-
-> “Cryptography rearranges power: it configures who can do what, from what”
->
-> Phillip Rogaway, [The Moral Character of Cryptographic Work](https://eprint.iacr.org/2015/1162.pdf)
-
-_Applied_ cryptography concepts and introduction to many common tools of the trade for web3 builders.
diff --git a/content/cryptography/intro/page.md b/content/cryptography/intro/page.md
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-# Introduction to Cryptography
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Introduction to Cryptography
-description: Cryptographic primitives for web3 builders
-duration: 1 hour
----
-
-# Introduction to Cryptography
-
----
-
-## Some Useful Equations
-
-<img rounded style="height: 600px" src="./img/scary-equations.png" />
-
-Notes:
-
-Just kidding!
-
----
-
-## Goals for this lesson
-
-<pba-flex center>
-
-- Understand the goals of cryptography
-- Understand some network and contextual assumptions
-- Learn what expectations cryptography upholds
-- Learn the primitives
-
-</pba-flex>
-
-Notes:
-
-In this first lesson,
-
----
-
-## Cryptography Landscape
-
-<img style="height: 700px; padding-left:100px" src="./img/crypto-mind-map.svg" />
-
-Notes:
-
-What is covered in this course is all connected subjects.
-We will not cover any details for hybrid or interactive protocols in the course.
-
----
-
-## Operating Context
-
-##### _The internet is a public space._
-
-We communicate over public channels.
-Adversaries may want to:
-
-<pba-flex center>
-
-- Read messages not intended for them
-- Impersonate others
-- Tamper with messages
-
-</pba-flex>
-
-Notes:
-
-Use e-mail as an example of an flawed system.
-
-Some examples include:
-
-- An attacker may impersonate your boss, trying to get you to send them money
-- An attacker may change a message sent over a network, e.g. an instruction to transfer 100 EUR to 10000 EUR
-
-Probably best for the teacher to ask students to participate with examples of application messages,
-not just person-to-person messages.
-
----
-
-## Operating Context
-
-##### _Resources are constrained._
-
-- **Network, storage, computation, etc.**: We don't want to send, store, or operate on the same data, but we want guarantees about it, e.g. that we agree on a message's contents.
-- **Privacy**: We must assume that all channels can be monitored, and thus closed channels are heavily constrained (i.e. assumed to not exist).
-
----
-
-## Open vs. Closed Channels
-
-_Cryptography based on public systems is more sound._
-
-**Kerckhoff's Principle:** Security should not rely on secret _methods_,<br />but rather on secret _information_.
-
-Notes:
-
-There is no such thing as a "closed channel" :)
-
-- Methods can be reverse engineered.
-  After that, the communication channel is completely insecure.
-  For example, CSS protection for DVDs.
-- We always work with public, open protocols.
-
----
-
-## Cryptographic Guarantees\*
-
-<pba-flex center>
-
-- Data confidentiality
-- Data authenticity
-- Data integrity
-- Non-repudiation
-
-</pba-flex>
-
-Notes:
-
-Cryptography is one of the (most important) tools we have to build tools that are _guaranteed_ to work correctly.
-This is regardless of who (human, machine, or otherwise) is using them and their intentions (good or bad).
-
-Why an asterisk?
-There generally are no perfect & absolute guarantees here, but for most practical purposes the bounds on where these fail are good enough to serve our needs as engineers and users.
-Do note the assumptions and monitor their validity over time (like quantum tech).
-
----
-
-## Important Non-Guarantee
-
-<pba-flex center>
-
-- Data availability
-
-</pba-flex>
-
-<br />
-
-Cryptography alone cannot make strong guarantees that data is available to people when they want to access it.
-
-Notes:
-
-There are many schemes to get around this, and this topic will come up later in the course.
-We will touch on erasure coding, which makes data availability more efficient.
-
----
-
-## Data Confidentiality
-
-A party may gain access to information<br />if and only if they know some secret (a key).
-
-<br />
-
-Confidentiality ensures that a third party cannot read my confidential data.
-
-Notes:
-
-The ability to decrypt some data and reveal its underlying information directly implies knowledge of some secret, potentially unknown to the originator of the information.
-Supplying the original information (aka plain text message) can be used in a "challenge game" mechanism as one means of proving knowledge of the secret without compromising it.
-
-Mention use of the term "plaintext".
-
-Allegory: A private document stored on server where sysadmin has _access_ can be subpoenaed, violating assumed Attorney-Client Privilege on the document.
-
----v
-
-<!-- This slide should potentially be pushed into the lecture on encryption. I can see it in either spot. Alternately, could be cut entirely, as encrypted communication is not an emphasized topic. -->
-
-## Confidentiality in Communication Channels
-
-Suppose Alice and Bob are sending confidential messages back and forth. There are some subtypes of confidentiality here:
-
-- **Forward Secrecy**: Even if an adversary temporarily learns Alice's secret, it cannot read future messages after some point.
-- **Backwards Secrecy**: Even if an adversary temporarily learns Alice's secret, it cannot read past messages beyond some previous point.
-
----
-
-## Data Authenticity
-
-Users can have the **credible** expectation that the stated origin of a message is authentic.
-
-<br />
-
-Authenticity ensures that a third party cannot pretend I created some data.
-
-Notes:
-
-- Digital signatures should be difficult (practically speaking: impossible) to forge.
-- Digital signatures should verify that the signer knows some secret, without revealing the secret itself.
-
----
-
-## Data Integrity
-
-If data is tampered with, it is detectable. In other words, it possible to check if the current state of some data is the consistent with when it was created.
-
-<br />
-
-Integrity ensures that if data I create is corrupted, it can be detected.
-
----v
-
-## Physical Signatures
-
-Physical signatures provide weak authenticity guarantees<br />(i.e. they are quite easy to forge), and no integrity guarantees.
-
----v
-
-## An Ideal Signature
-
-<img style="width: 900px;" src="./img/Data-Integrity.png" />
-
-Notes:
-
-For example, if you change the year on your university diploma, the dean's signature is still valid.
-Digital signatures provide a guarantee that the signed information has not been tampered with.
-
----
-
-## Non-repudiation
-
-The sender of a message cannot deny that they sent it.
-
-<br />
-
-Non-repudiation ensures if Bob sends me some data, I can prove to a third party that they sent it.
-
----
-
-## One-Way Functions
-
-One-way functions form the basis of both<br /> **(cryptographic) hashing** and **asymmetric cryptography**. A function $f$ is one way if:
-
-- it is reasonably fast to compute
-- it is very, very slow to undo
-
-Notes:
-
-There are a lot of assumptions about why these functions are hard to invert, but we cannot rigorously prove it.
-We often express inversion problems in terms of mathematical games or oracles.
-
----
-
-## Hash Functions
-
-**Motivation:** We often want a succinct, yet unique representation of some (potentially large) data.
-
-</br>
-
-A fingerprint, which is much smaller than a person, yet uniquely identifies an individual.
-
-Notes:
-
-The following slides serve as an intro.
-Many terms may be glossed over, and covered in detail later.
-There are lessons later in this module dedicated to hashes and hash-based data structures.
-
----v
-
-## Hash Function Applications
-
-Hashes can be useful for many applications:
-
-<pba-flex center>
-
-- Representation of larger data object<br />(history, commitment, file)
-- Keys in a database
-- Digital signatures
-- Key derivation
-- Pseudorandom functions
-
-</pba-flex>
-
----
-
-## Symmetric Cryptography
-
-Symmetric encryption assumes all parties begin with some shared secret information, a potentially very difficult requirement.<br />The shared secret can then be used to protect further communications from others who do not know this secret.
-
-In essence, it gives a way of _extending_ a shared secret over time.
-
-Notes:
-
-Remember that these communications are over an _open channel_, as we assumed that all channels can be monitored.
-
----
-
-## Symmetric Encryption
-
-For example, the Enigma cipher in WW2. A _channel_ was initiated by sharing a secret ("key") between two participants. Using the cipher, those participants could then exchange information securely.
-
-However, since the key contained only limited _entropy_ ("information"), enough usage of it eventually compromised the secret and allowed the allies to decode messages. Even altering it once per day was not enough.
-
-Notes:
-
-When communicating over a channel that is protected with only a certain amount of entropy, it is still possible to extend messages basically indefinitely by introducing _new entropy_ that is used to protect the channel sufficiently often.
-
----
-
-## Asymmetric Cryptography
-
-- In asymmetric cryptography, we devise a means to transform one value (the "secret") into some corresponding counterpart (the "public" key), preserving certain properties.
-
-- We believe that this is a one-way function (that there is no easy/fast inverse of this function).
-
-- Aside from preserving certain properties, we believe this counterpart (the "public key") reveals no information about the secret.
-
----
-
-## Asymmetric Encryption
-
-_Using only the public key_, information can be transformed ("encrypted") such that only those with knowledge of the secret are able to inverse and regain the original information.
-
----
-
-## Digital Signatures
-
-- _Using the secret key_, information can be transformed ("signed") such that anyone with knowledge of the information and the counterpart public key is able to affirm the operation.
-
-- Digital signatures provide message authenticity and integrity guarantees.
-
-- _There are two lessons are dedicated to digital signatures,<br />this is strictly an intro._
-
----
-
-## Digital Signatures
-
-**Signing function**: a function which operates on some<br /> _message data_ and some _secret_ to yield a _signature_.
-
-A **signature** _proves_ that the signer had knowledge of the secret,<br />without revealing the secret itself.
-
-The signature cannot be used to create other signatures, and is unique to the message.
-
-Notes:
-
-A **signing function** is a pure function which operates on some _message data_ (which may or may not be small, depending on the function) and some _secret_ (a small piece of information known only to the operator).
-The result of this function is a small piece of data called a _signature_.
-
-Pure means that it has no side effects.
-
-It has a special property: it proves (beyond reasonable doubt) that the signer (i.e. operator of the signing function) had knowledge of the secret and utilized this knowledge with the specific _message_ data, yet it does not reveal the secret itself, nor can knowledge of the signature be used to create other signatures (e.g. for alternative message data).
-
----
-
-## Non-repudiation for Crypgraphic Signatures
-
-There is cryptographic proof that the secret was known to the producer of the signature.
-
-<br />
-
-The signer cannot claim that the signature was forged, unless they can defend a claim that the secret was compromised prior to signing.<br />
-
----
-
-## Practical Considerations
-
-**Symmetric cryptography** is much faster, but requires more setup (key establishment) and trust (someone else knows the secret).
-
-**Asymmetric cryptography** is slow, but typically preserves specific algebraic relationships, which then permit more diverse if fragile protocols.
-
----
-
-## Hybrid Cryptography
-
-Hybrid cryptography composes new mechanisms from different cryptographic primitives.
-
-For example:
-
-- Symmetric encryption can provide speed, and often confidentiality,
-- Hash functions can reduce the size of data while preserving identity,
-- Asymmetric cryptography can dictate relations among the participants.
-
----
-
-## Certifications
-
-Certifications are used to make attestations about public key relationships.
-
-Typically in the form of a _signature_ on:
-
-- One or more cryptographically strong identifiers (e.g. public keys, hashes).
-- Information about its ownership, its use and any other properties that the signer is capable of attesting/authorizing/witnessing.
-- _(Meta-)information_ about this information itself, such as how long it is valid for and external considerations which would invalidate it.
-
-Notes:
-
-- Real application is the hierarchy of SSL certs.
-  - Root keys -> State level entities -> Smaller entities.
-- Web of Trust & GPG cross-signing
-- In the case of signature-based certificates, as long as you have the signature, data, and originating public key, you can trust a certificate no matter where it came from. It could be posted on a public message board, sent to you privately, or etched into stone.
-
----
-
-## Entropy, Randomness, and Key Size
-
-- Entropy: Amount of non-redundant information contained within some data.
-- Randomness: Unpredictability of some information. Less random implies lower entropy.
-- Key size: Upper limit of possible entropy contained in a key. Keys with less random (more predictable) data have less entropy than this upper bound.
-- One-time pad: A key of effectively infinite size. If it is perfectly random (i.e. has maximal entropy), then the cipher is theoretically unbreakable.
-
-Notes:
-
-Mention the upcoming "many time pad" activity, that exploits using a one time pad multiple times.
-
----
-
-## Randomness Generation
-
-```rust
-fn roll_die() -> u32 {
-  // Guaranteed random: it was achieved through a real-life die-roll.
-  4u32
-}
-```
-
-- Pseudo-random sequences
-- Physical data collection (e.g. cursor movement, LSB of microphone)
-- Specialised hardware (e.g. low-level noise on silicon gates, quantum-amplifiers)
-
-Notes:
-
-LSB := Least Significant Bit
-
----
-
-## Summary
-
-Cryptography is much more than encryption.
-
-<pba-flex center>
-
-- Communicate on public networks, in the open
-- Access information
-- Have expectations about a message's authenticity and integrity
-- Prove knowledge of some secret information
-- Represent large amounts of data succinctly
-
-</pba-flex>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
-<img style="height: 600px" src="./img/crypto-mind-map.svg" />
-
-##### _What insights did you gain?_
-
-Notes:
-
-Class discussion.
-Last slide.
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-# Economics Basics
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Economics Basics
-description: Economics Basics for web3 builders
-duration: 2 hour
----
-
-# Economics Module
-
----
-
-# Overview
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Economics Basics</li>
-<li class="fragment">Game Theory Basics</li>
-<li class="fragment">Price Finding Mechanisms</li>
-<li class="fragment">Collective Decision Making</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- Focus on the pure economic concepts and not diving into blockchain yet.
-- That is covered by another lecture doing so.
-- Economics of polkadot for the founders track later.
-- Interactive: Ask questions!
-
----
-
-# Economics Basics
-
----
-
-<pba-cols>
-<pba-col>
-<pba-flex center>
-
-#### Cryptography
-
-- Provides assurances about the conduct of machines
-- Objective in nature
-- Promotes deterministic actions
-- Serves as a toolbox to secure certain actions in the digital world.
-
-</pba-flex>
-</pba-col>
-<pba-col>
-<pba-flex center>
-
-#### Economics
-
-- Offers predictions about the actions of people
-- Intrinsically subjective
-- Driven by individual preferences
-- Serves as a toolbox to understand which actions humans are likely to undertake.
-
-</pba-flex>
-</pba-col>
-</pba-cols>
-
-🤖$~~~$ 🤝 $~~~$👪
-
-Notes:
-
-- Cryptography would be meaningless without humans using it.
-- Crypto & Econ pair well! Together they are the toolbox to design unstoppable systems.
-- They have a great symphony: where cryptography's has boundaries, economics offers solutions and vice versa.
-
----
-
-## Why are economic concepts<br />important?
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">help make better decisions in daily- and professional life.</li>
-<li class="fragment">model & reason about how others make decisions.</li>
-<li class="fragment">better understand (crypto-)economic protocols.</li>
-<li class="fragment">understand the broader context of web3/blockchain.</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- It is also important to understand the limits of these economic concepts and when they might not work as intended.
-
----
-
-## Outline
-
-<pba-flex center>
-
-<ul>
-<li class="fragment"><strong>Lesson</strong>
-    <ul>
-    <li class="fragment">Incentives: What motivates others to do things?</li>
-    <li class="fragment">Demand & Supply: Market Equilibrium, Influences, and Elasticity.</li>
-    <li class="fragment">Market Forms: Monopoly, Oligopoly, and Perfect Competition.</li>
-    <li class="fragment">Economics of Specialization: Comparative Advantage, Opportunity Costs, Gains from Trade.</li>
-    <li class="fragment">Time as Ultimate Resource: The interaction between Time and Value.</li>
-    <li class="fragment">Behavioral Biases: Where human decision making might be different than traditional economic theories predict.</li>
-    </ul>
-</li>
-<li class="fragment"><strong>Discussion & Workshop</strong>
-    <ul>
-    <li class="fragment">Discussions to foster and apply concepts we learned.</li>
-    <li class="fragment">Hands-on applications.</li>
-    </ul>
-</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Guiding Human Behavior
-
-> An incentive is a bullet, a key:<br />an often tiny object with astonishing power to change a situation.<br />-- Steven Levitt --
-
-Notes:
-
-- Human behavior is driven by incentives.
-- The aggregation of these behaviors lead to societies.
-- Carefully designing incentives lays the ground for functioning systems.
-- You might be asked to implement certain protocols, which you have to judge if they make sense / can be improved.
-
----
-
-## Understanding Incentives
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Motivate individuals or groups to perform certain actions.</li>
-<li class="fragment">Historically, incentives were designed to influence human behavior both on a macroeconomic and microeconomic level.</li>
-<li class="fragment">Most commonly, people refer to money, that fall under the umbrella of extrinsic incentives.</li>
-<li class="fragment">But not all incentives are monetary!</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Different Types of Economic Incentives
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">In a workplace setting (microeconomic level), employees are often motivated by various forms of economic incentives:
-    <ul>
-    <li class="fragment">Flat Rate: A fixed amount of salary irrespective of performance.</li>
-    <li class="fragment">Piece Rate: Pay based on the quantity of output produced.</li>
-    <li class="fragment">Bonus: Additional rewards for excellent performance.</li>
-    <li class="fragment">Relative Incentives: Rewards relative to the performance of others (competitive incentives).</li>
-    </ul>
-</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- **Question: What are the advantages / disadvantages of those incentives?**
-
----
-
-## Rationality in Economics
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Economic theories often assume rationality, implying that actors:
-    <ul>
-    <li class="fragment">Are primarily driven by monetary gains (payoff maximization).</li>
-    <li class="fragment">Act in self-interest.</li>
-    <li class="fragment">Have unlimited cognitive resources.</li>
-    </ul>
-</li>
-<li class="fragment">Remark: In this, all factors can be translated into monetary terms.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Incentives often work well
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Interest rates set by central banks.</li>
-<li class="fragment">Lower rates: Encourage borrowing and investing.</li>
-<li class="fragment">Higher rates: Slow down inflation and stabilize the economy.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Incentives can Backfire
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">In India during British rule, the British Government was concerned about the large number of venomous Cobras.
-    <ul>
-    <li class="fragment">They offered a bounty for every dead cobra.</li>
-    <li class="fragment">People started to breed cobras at home to sell them.</li>
-    <li class="fragment">Once the government stopped the program, breeders released the cobras causing larger numbers than before.</li>
-    </ul>
-</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Goodhart's Law
-
-> When a measure becomes a target, it ceases to be a good measure
-
----
-
-## Crowding Out
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">In Haifa (Israel) parents often got their kids late from day care.</li>
-    <ul>
-    <li class="fragment">This caused childcare workers frustration.</li>
-    <li class="fragment">Idea: fine parents for getting their kids late.</li>
-    <li class="fragment">The program was rolled out in some day cares and not others.</li>
-    </ul>
-<li class="fragment">Traditional economic theory:</li>
-    <ul>
-    <li class="fragment">Less or at least equally many late parents.</li>
-    <li class="fragment">BUT: The opposite happened, the number of late parents even increased.</li>
-    <li class="fragment">After the fine was abolished, parents still were more late.</li>
-    </ul>
-</li>
-<li class="fragment">Extrinsic motivation can crowd out intrinsic motivation.</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- **Question: Why did that happen?**
-- Gneezy & Rustichini (2000): A fine is a price.
-
----
-
-## The Power of Intrinsic Incentives
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Beyond monetary gain, people are also motivated by intrinsic factors.</li>
-    <ul>
-    <li class="fragment">Social preferences (Reciprocity, Fairness, Social Norms, Inequality Aversion, Altruism).</li>
-    <li class="fragment">Personal morals, and deeply-held beliefs.</li>
-    </ul>
-<li class="fragment">Economic models often fail to account for these motivations, leading to unexpected outcomes in real-world applications.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## From Humans to Automated Agents
-
-<pba-flex center>
-<ul>
-<li class="fragment">The digital age emphasizes the importance of automated actors in our economic systems.</li>
-<li class="fragment">Algorithms and bots, respond to incentives, often financial ones, automatically.</li>
-<li class="fragment">This shifts the application of incentives beyond a human context and into the realm of digital systems and automated processes.</li>
-</ul>
-</pba-flex>
-
-Notes:
-
-- Still, not always financial incentives - reputation scores
-- While automated agents existed for a while, they become much more accessible for everybody due to blockchain technology
-- Your electric car might soon have a wallet that automatically pays for charging at a red light.
-- Or you might be able to pay for priority green lights.
-
----
-
-## Conclusion
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Incentives continue to be fundamental to interactions in society, whether among humans or between automated systems.</li>
-<li class="fragment">As we understand more about incentives in different contexts, we can better design them to influence behavior effectively.</li>
-<li class="fragment">Intrinsic motivations remain important, but in certain contexts, like automated systems, monetary incentives also play a significant role.</li>
-<li class="fragment">The challenge is to balance these factors to achieve the desired outcomes.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Demand & Supply: The Pillars of Market Equilibrium
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">A common model to help predict and rationalize the price<br />which emerges from a market.</li>
-<li class="fragment">Can be used to (gu)estimate the quantity<br />of produced goods vs. their market prices.</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- A famous artist dies and her art increases in price.
-- An unusually nice summer reduces hotel prices in popular vacations destinations.
-
----
-
-## Law of Demand: A Basic Principle
-
-- When prices increase, quantity demanded of a good (generally) decreases.
-
-Notes:
-
-- **Question: Anybody know exceptions?**
-- Exception are "Veblen goods" where demand increases when price increases.
-  These are typically luxury goods that signal something (e.g. status, reputation) in addition to being useful to consumption.
-  Examples are jewelry, luxury cars, etc.
-- This is not a contradiction to the law of demand because the good's social value depends on the price; i.e., the good "changes" and becomes more desirable as the price increases.
-
----
-
-## Visualizing Demand: The Demand Curve
-
-<img rounded style="width:900px" src="./img/market-demand.png" />
-
-Notes:
-
-- **Question: What influences the aggregate market demand?**
-- The market demand is the sum of all individual curves.
-
----
-
-## Influences on demand?
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Price (Demand moves along the curve)</li>
-<li class="fragment">Size of consumer base</li>
-<li class="fragment">Average disposable income of consumer base</li>
-<li class="fragment">Price of substitution goods</li>
-<li class="fragment">Preferences prevalent within consumer base</li>
-<li class="fragment">Expectations prevalent within consumer base</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- In the ice cream example, a substitution good could be frozen yoghurt: if its price goes down, the demand for ice cream will decrease.
-- If people's appetite for ice cream increases (perhaps via advertisement), the demand will increase.
-- In people expect a shortage of ice cream in the near future, the demand will increase immediately.
-
----
-
-## Moving the demand curve
-
-<img rounded style="width:1100px" src="./img/demand-curve.png" />
-
----
-
-## Law of Supply: The Other Side of the Coin
-
-- If the price of a good increases, the quantity supplied also increases
-
-(because suppliers can make more profit!).
-
-Notes:
-
-- That is, assuming that suppliers manage to sell all produced goods at said price.
-- For example, if the ice cream price increases the store will hire a second employee to sell more scoops per hour.
-- As another example, some petroleum deposits are easier and cheaper to extract than others, so some deposits will be extracted only if the oil price is above a certain threshold.
-
----
-
-## Demand and Supply Interplay: Market Equilibrium
-
-<img rounded style="width: 600px;" src="./img/supply-and-demand.png" />
-
-- What happens when Price is higher than the Eq. Price?
-- What if the Quantity is lower than the Eq. Quantity?
-- Moving either supply or demand leads to new Eq.
-
-Notes:
-
-- Where the curves meet we obtain a point of equilibrium, which establishes a market quantity and a market price.
-- If price is higher than equilibrium price, there is more supply than demand, so some goods remain unsold, and sellers will be forced to reduce the price to get rid of their stock.
-  Similarly if the price is lower than equilibrium price, there is more demand than supply, which leads to shortages of the good; sellers will notice this and increase the price.
-  Hence, we always converge to the equilibrium price.
-- Similarly, if the quantity supplied is too low, there is a business opportunity to supply more unit of the good and make a profit, so eventually someone will increase the supply quantity.
-
----
-
-## Elasticity
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Measures how much buyers and sellers respond to changes in market conditions.</li>
-<li class="fragment">Sensitivity of quantity demanded or supplied to changes in price.</li>
-    <ul>
-    <li class="fragment">High elasticity: small price changes have large impact on quantity demanded or supplied.</li>
-    <li class="fragment">Low elasticity (== inelasticity): price changes do not affect quantity demanded or supplied.</li>
-    </ul>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- Draw a diagram with price on y and quantity on x and draw an almost vertical line tilted towards the left.
-  - Demand for Gasoline.
-    Low elasticity: If price goes up people buy only a little less, if price goes up they only buy a little more.
-- High Elasticity: luxury goods, where buyers can easily adjust their consumption.
-- Low Elasticity: essential goods such as energy / medicine.
-
----
-
-## Conclusion: The Dynamics of Demand and Supply
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Demand/supply model forces in markets and can be used to estimate equilibrium quantity/price.</li>
-<li class="fragment">All other things being equal:
-    <ul>
-    <li class="fragment">demand decreases with increasing price.</li>
-    <li class="fragment">supply increases with increasing price.</li>
-    </ul>
-</li>
-<li class="fragment">There are different factors influencing supply & demand curves.
-    <ul>
-    <li class="fragment">Elasticity.</li>
-    <li class="fragment">Some shift the equilibrium on the curve.</li>
-    <li class="fragment">Others move the entire curves.</li>
-    </ul>
-</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Market forms
-
-### (Or: why monopoly bad?)
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Typically, economists distinguish between three market forms.
-    <ul>
-    <li class="fragment">Perfect competition: Many firms, many consumers.</li>
-    <li class="fragment">Oligopoly: Few firms, many consumers.</li>
-    <li class="fragment">Monopoly: One firm, many consumers.</li>
-    </ul>
-</li>
-<li class="fragment">The more competition a firm faces, the less market power it has.</li>
-<li class="fragment">Market power: ability to affect the price (through choosing a certain production level).</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- Special form of Oligopoly is the Duopoly with two firms, something that we see later.
-
----
-
-## Market Form Examples
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Monopoly:
-    <ul>
-    <li class="fragment">Postal services in many European countries.</li>
-    <li class="fragment">Railway services in many European countries.</li>
-    </ul>
-</li>
-<li class="fragment">Oligopoly:
-    <ul>
-    <li class="fragment">Cloud provider (AWS, Google, ...)</li>
-    <li class="fragment">Mobile phone service.</li>
-    </ul>
-</li>
-<li class="fragment">Perfect Competition:
-    <ul>
-    <li class="fragment">Consumer products with low barrier to entry (e.g., kebab stand in Berlin, espresso bar in Italy)</li>
-    </ul>
-</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Why discuss this?
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Current web2 landscape consists of several firms with a lot of market power in their respective market segment.</li>
-<li class="fragment">We want to understand, from an economic perspective, why too much market power is not a good thing.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Perfect Competition
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Under perfect competition ...
-    <ul>
-    <li class="fragment">there are so many firms that a single firm's production quantity does not affect market price.</li>
-    <li class="fragment">the marginal costs (cost of one additional unit) of production equals the market price.</li>
-    <li class="fragment">firms have 0 profit.</li>
-    </ul>
-</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- This makes sense: The firm produces up to the point where an additional unit costs exactly what it gets for it on the market.
-- Notice that having the market price be equal to the marginal production costs is pretty surprising, as it is ideal from a point of view of society welfare, even though every firm is acting selfishly.
-- In this perfect world, firms will have zero economic profit, meaning they make just enough money to cover production costs and keep the company running.
-
----
-
-## Monopoly
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Monopolist: single seller of the good or service, serves the entire market.</li>
-<li class="fragment">Market characterized by a high barrier of entry (e.g. big investment, legal restrictions).</li>
-<li class="fragment">Monopolist is therefore sole price-setter and serves only to maximize their own profits.</li>
-<li class="fragment">This leads to sub-optimal pricing and sub-optimal society welfare: consumers either pay more than they should ("monopolist tax") or are excluded from market.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Oligopolies
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Oligopolies are somewhere between monopolies and perfect competition.</li>
-<li class="fragment">Because of the competition between firms
-    <ul>
-    <li class="fragment">prices are lower, and</li>
-    <li class="fragment">overall market participation is higher.</li>
-    </ul>
-</li>
-</ul>
-
-</pba-flex>
-
----
-
-## What did we learn?
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Markets differ in how much market power the firms possess.</li>
-<li class="fragment">Economics typically distinguishes between three forms (ordered by increasing market power):
-    <ul>
-    <li class="fragment">Perfect competition: many firms in the market.</li>
-    <li class="fragment">Oligopoly: few firms in the market.</li>
-    <li class="fragment">Monopoly: one firm in the market.</li>
-    </ul>
-</li>
-<li class="fragment">The problem of monopoly is the result of an inefficiently high price.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Economics of Specialization
-
-#### _(or: why bother trading at all?)_
-
-> It is the maxim of every prudent master of a family, never to attempt to make at home what it will cost him more to make than to buy.<br />-- Adam Smith, 1776 --
-
-Notes:
-
-- In this part, we take a closer look at the following concepts:
-  - Comparative advantage.
-  - Opportunity costs.
-  - Gains from trade.
-
----
-
-## The economic question
-
-<pba-flex center>
-
-<ul>
-    <li class="fragment">Empirical puzzle: many countries trade even though one has an absolute advantage in producing many of the traded goods.</li>
-    <li class="fragment">E.g., the US is well-equipped to cheaply produce both
-        <ul>
-            <li class="fragment">complex computer chips, and</li>
-            <li class="fragment">agricultural goods (e.g., potatoes).</li>
-        </ul>
-    </li>
-    <li class="fragment">However, the US specializes in producing the former and importing many agricultural goods.</li>
-    <li class="fragment">Question: Why do countries specialize; why do they trade?</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Comparative advantage
-
-<pba-flex center>
-
-<ul>
-    <li class="fragment">Consider the following example:
-        <ul>
-            <li class="fragment">Suppose Alice can produce 10kg of meat and 20kg of potatoes per hour.</li>
-            <li class="fragment">Suppose Bob can produce 2kg of meat and 10kg of potatoes per hour.</li>
-        </ul>
-    </li>
-    <li class="fragment">Alice has an <em>absolute</em> advantage over Bob at producing both goods.
-    <li class="fragment">BUT, Alice has only a <em>comparative</em> advantage over Bob at producing meat.
-        <ul>
-            <li class="fragment">Alice has lower <em>opportunity</em> costs of producing meat (in terms of foregone potatoes).</li>
-            <li class="fragment">That is, to produce one kg of meat Alice gives up much less produced potatoes than Bob would.</li>
-        </ul>
-    </li>
-    <li class="fragment">By the same observation, Bob has a comparative advantage at producing potatoes.</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- Comparative advantage of meat:
-  - Opp. cost Alice: **1kg meat = 2kg potatoes**
-  - Opp. cost Bob: 1kg meat = 5kg potatoes
-- Comparative advantage of potatoes:
-  - Opp. cost Alice: 1kg potatoes = 1/2kg meat
-  - Opp. cost Bob: **1kg potatoes = 1/5kg meat**
-
----
-
-## Comparative advantage II
-
-<pba-flex center>
-
-<ul>
-    <li class="fragment">If both focus on their comparative advantage, then total welfare is higher than in a situation of autarky!</li>
-    <li class="fragment">Why?
-        <ul>
-            <li class="fragment">Suppose both require both meat and potatoes.</li>
-            <li class="fragment">Situation A - Autarky: both divide their time equally between producing meat and producing potatoes.</li>
-            <li class="fragment">Situation B - Trade: Alice focuses most of her time to produce meat and some to produce potatoes, while Bob focuses only on producing potatoes.</li>
-            <li class="fragment">Total production of meat and potatoes is higher in Situation B!</li>
-        </ul>
-    </li>
-    <li class="fragment"><strong>Specialization result</strong>: With trade, both are both better off than in Situation A.</li>
-</ul>
-</pba-flex>
-
-Notes:
-
-- Assume one working day with one worker (8 hrs).
-- Autarky:
-  - Alice: 4hrs _ 10 meat, 4hrs _ 20 potatoes = 40 meat, 80 potatoes
-  - Bob: 4hrs _ 2 meat, 4hrs _ 10 potatoes = 8 meat, 40 potatoes
-- Trade:
-
-  - Alice: 5hrs _ 10 meat, 3hrs _ 20 potatoes = 50 meat, 60 potatoes
-  - Bob: 0hrs _ 2 meat, 8hrs _ 10 potatoes = 0 meat, 80 potatoes
-  - Alice could trade 9 meat for 30 potatoes:
-    - Alice: 41 meat, 90 potatoes
-    - Bob: 9 meat, 50 potatoes
-
----
-
-## Absolute vs Comparative Advantage
-
-<pba-flex center>
-<ul>
-    <li class="fragment">Alice can produce both meat and potatoes more efficiently than Bob - this is an absolute advantage.</li>
-    <li class="fragment">However, the choice to specialize isn't just about absolute production efficiency.</li>
-    <li class="fragment">What matters for trade is which good Alice can produce at a lower opportunity cost - this is comparative advantage.</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- What does that tell us about daily life?
-  - **Stick with what you are good at**: It's often good to stick things where you have a comparative advantage: For example, assume you are a great software engineer with a job that has a high salary, but you also want to help clean up the ocean. Instead of giving up your job and go clean the ocean, you might want to allocate some of your salary to ocean cleanup, having a larger effect.
-  - **Realize that absolute advantage is not all**Only because one co-worker has a total advantage in two dimensions of the job, another co worker can still have the comparative advantage in one of the tasks.
-  - **Question**: What are your opportunity costs of being here?
-
----
-
-## Time: The Ultimate Resource
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Time is the one resource that is uniformly distributed and yet cannot be accumulated or saved for later.</li>
-<li class="fragment">It's always moving, never at rest.</li>
-<li class="fragment">This unique property of time lends it incredible implications.</li>
-<li class="fragment">This concept has big impact in the context of money and finance.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## The Relationship of Time and Money
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Money now is worth more than the same amount in the future.</li>
-<li class="fragment">Why?
-    <ul>
-    <li class="fragment">Again, opportunity costs: The money at hand now could be invested, potentially earning more money.</li>
-    <li class="fragment">This potential earning capacity bestows more value to present money over future money.</li>
-    </ul>
-</ul>
-
-</pba-flex>
-
----
-
-## Present Value: The Value of Now
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Present Value brings some future value back to the present moment.</li>
-<li class="fragment">It estimates what value would make you indifferent between getting some value now vs. later.</li>
-<li class="fragment">It reflects the worth of a future promise in today's terms, based on the potential earnings we could achieve now.</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- There are formulas to calculate how much a future payout in the future is worth today.
-- You need to make assumptions about your rate of return in the meantime.
-- Often risk free rate is used.
-
----
-
-## Time Value of Money: A Guiding Principle
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">It underlines the importance of wise decisions today for a brighter tomorrow.</li>
-<li class="fragment">It shows that nothing is for free. You always give up something.</li>
-<li class="fragment">It's a fundamental cornerstone guiding personal savings, investments, and wide-ranging financial decisions.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Behavioral Biases
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Behavioral biases are systematic errors in decision-making when people use mental shortcuts (heuristics) to process information and make judgments.</li>
-<li class="fragment">For a long time economic theory was built on the assumption that all actors are <em>rational</em>.
-    <ul>
-    <li class="fragment">No regard for fairness, altruism, equality.</li>
-    <li class="fragment">All available information is considered.</li>
-    <li class="fragment">No influence of emotions.</li>
-    </ul>
-</li>
-<li class="fragment">This works well in many circumstances (e.g., on an aggregate level or assuming highly rational actors like firms executives) but in many it doesn't.</li>
-<li class="fragment">Most humans are prone to behavioral biases and are influenced by social preferences.</li>
-</ul>
-
-</pba-flex>
-
----
-
-## Behavioral Economics
-
-<pba-flex center>
-
-<ul>
-<li class="fragment">Behavioral economics is mainly concerned with the bounds of rationality of economic agents.</li>
-<li class="fragment">Influenced by psychological aspects such as emotions, cognition as well as cultural and societal factors.</li>
-<li class="fragment">Psychologist Daniel Kahnemann received the 2002 Nobel Prize for <em>Prospect Theory</em>, a fundamental theory in Behavioral Economics.</li>
-<li class="fragment">PT models the fact that individuals assess their losses differently than their gains.</li>
-</ul>
-</pba-flex>
-
----
-
-## Behavioral Economics
-
-<pba-flex center>
-
-<ul>
-<li class="fragment"><strong><em>Behavior is not random!</em></strong></li>
-<li class="fragment">Key behavioral biases include:
-    <ul>
-    <li class="fragment"><strong>Confirmation Bias</strong> - Decision makers focus on information that cater to their prior belief / opinion and neglect other information.</li>
-    <li class="fragment"><strong>Sunk Cost Fallacy</strong> - Instead of cutting losses, decision makers continue to pour resources into a failed endeavour.</li>
-    <li class="fragment"><strong>Herding Effect</strong> - People follow the crowd without making their own informed decision.</li>
-    <li class="fragment"><strong>Gambler's Fallacy</strong> - In many situations probabilities of repeated events are independent from each other. Often decision makers fail to understand this.</li>
-    <li class="fragment"><strong>Default Effect</strong> - People tend to stick with pre-selected choices.</li>
-    <li class="fragment"><strong>Overconfidence</strong> - People overestimate their abilities.</li>
-    </ul>
-</li>
-<li class="fragment">Any other biases you know?</li>
-</ul>
-
-</pba-flex>
-
-Notes:
-
-- Confirmation bias especially pronounced in todays time where people get trapped in echo chambers fostered by algorithms that keep feeding you information that you want to hear.
-- Overconfidence: If asked, more than 50% of people think they drive above average.
-  BUT has also positive effects.
-  Sometimes overconfident people are better than others and statistically perform better in practice.
-- Anchoring Effect
-- Endowment Effect: This bias occurs when we overvalue something simply because we own it.
-- Hindsight Bias - This is the tendency to believe, after an outcome is already known, that you would have predicted or could have foreseen the outcome.
-  It is often referred to as the "I knew it all along" effect.
-- Availability Bias - People make decisions based on the information that is readily available to them, rather than the complete data set.
-  This bias can often lead to inaccurate conclusions.
-
----
-
-## Behavioral Economics
-
-> Simply put, the stock market is a creation of man and therefore reflects human idiosyncrasy.<br />-- Ralph Nelson Elliott --
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-# Break (10 minutes)
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Classroom Discussions
-
-Notes:
-
-- Roughly 20 minutes
-
----
-
-## Behavioral Biases
-
-- Which biases might be responsible for the following situations?
-- How can we mitigate the impact of those biases?
-
----
-
-## Situation 1:
-
-> Warren Buffett announces that he increased his exposure to Apple by buying more stocks.
-> The price of AAPL goes up.
-
-Notes:
-
-- Herding effect
-- Cannot be in the hope of a price response by Buffett's trade because it already happened.
-- Self-fulfilling prophecy
-- Maybe still rational?
-
----
-
-## Situation 2:
-
-> A stock investor bought a big position in Disney at around 100 USD per share.
-> Then, the scandal unfolds and the price plummets.
-> The investor keeps buying in at 80 USD, 50 USD and finally at 5 USD, 3 USD and 1 USD.
-> When a friend asks him to stop he keeps arguing to recover the losses by "buying the dip" and to "further reducing the average buying price".
-
-Notes:
-
-- Sunk Cost Fallacy
-- Learn to accept losses
-
----
-
-## Situation 3:
-
-> Peter wants to buy a new smartphone and fancies the new iPhone.
-> Mentally, he is already looking forward to finally buy it, but a friend urges him to do some more research.
-> He agrees and is reading through articles that pop up after googling "Why you should buy the new iPhone".
-
-Notes:
-
-- Confirmation Bias
-- Mitigating by actively looking outside the echo-chamber that is just catering to your opinion.
-
----
-
-## Situation 4:
-
-> A Swiss energy company could increase the number of new renewable electricity contracts from 3% to 80-90% by pre-selecting the green option when customers were renewing their energy contracts.
-
-Notes:
-
-- Default effect
-- Is it always good?
-  People might consume more energy because they feel better about their contract, companies can exploit this effect "default to accept all cookies".
-- <https://www.bbc.com/news/science-environment-56361970>
-- [Paper](https://www.nature.com/articles/s41562-021-01070-3)
-
----
-
-## Titan Submersible Incident
-
-<ul>
-    <li class="fragment">On 18 June 2023, Titan, a submersible operated by American tourism company OceanGate, imploded during an expedition to the Titanic wreck.</li>
-</ul>
-<span style="display:flex; justify-content:center; align-items:center;">
-<img rounded style="width:600px" class="fragment" src="./img/ocean-gate.png" />
-</span>
-
----
-
-## Titan Submersible Incident
-
-<ul>
-    <li class="fragment">On board were Stockton Rush (OceanGate CEO), Paul-Henri Nargeolet (deep sea explorer), Hamish Harding and Shahzada Dawood (billionaire businessmen), and Suleman Dawood (Shahzada's son).</li>
-    <li class="fragment">Communication was lost 1 hour and 45 minutes into the dive and the vessel failed to resurface later that day.</li>
-    <li class="fragment">Four days later, a debris field containing parts of Titan was discovered near the Titanic.</li>
-</ul>
-
----
-
-## Prior Safety Concerns
-
-<ul>
-    <li class="fragment">Many industry experts had expressed safety concerns about Titan.</li>
-    <li class="fragment">OceanGate, including CEO Rush, had not sought certification for Titan.</li>
-    <li class="fragment">They published the following blog post to give reasoning:</li>
-</ul>
-<span style="display:flex; justify-content:center; align-items:center;">
-<img rounded style="width:600px" src="./img/ocean-gate-blog-post.png" class="fragment" />
-</span>
-
-Notes:
-
-- What biases could be happening here?
-- **Survivor bias**: is the logical error of concentrating on entities that passed a selection process while overlooking those that did not.
-  This can lead to incorrect conclusions because of incomplete data.
-- What bias are we facing maybe? **Hindsight Bias**: is the common tendency for people to perceive past events as having been more predictable than they were.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Where do you see yourself or others suffer from behavioral biases?
-
-Notes:
-
-Open class discussion.
-
----
-
-## Monopoly
-
-- We have seen: Monopolists' market power leads to inefficient outcomes.
-- Web 2.0 is full of firms that have a monopoly-like position in their respective domain:
-  - Google
-  - Uber
-  - AirBnb
-  - ...
-- How do these firms exert their market power, if not over price-setting?
-
-Notes:
-
-- transparency? (stealing tips!)
-- fees (uber, airbnb)
-- surge pricing (uber)
-- opaque auction mechanism (google in the case of online ads)
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Activities
-
----
-
-# Academy Games
-
-<!-- .slide: data-background-color="#4A2439" -->
-
----
-
-## Activities Today & Tomorrow
-
-- You can earn points by applying the concepts presented in this course to similar situations when playing with/against your colleagues.
-- In session 2.1, 2.2 and 2.3, you can increase your budget (starting at 0) during several economic games.
-- We have a total budget of $2250 for this.
-- The budget is split between all the games that we play and total points earned by all of you are dynamically adjusted to correspond to the budget.
-- In 2.3, there is a big final: You can use your earnings to bid for amazing NFTs by a professional artist in an experimental auction setting.
-
----
-
-## Sign-in
-
-- You will sign in to each of the games with your Polkadot wallet.
-- You should always sign in with the same wallet to keep earning points to that wallet.
-- Make sure not to forget your wallet credentials, because your final payout / NFT will be tied to that wallet.
-
----
-
-## Disclaimer
-
-1. If a bug occurs and the reward points are messed up or something else goes wrong, we may intervene.
-1. We cannot help you recovering your Polkadot wallet.
-   If you lose access, you need to create a new account in the games but you will lose previous earnings.
-
----
-
-## Tracking your payoff
-
-- Your balance is tracked in a wallet app.
-- The points are translated to USD after each game.
-- You can constantly check your balance by opening the wallet app link and sign in with your wallet.
-
-Notes:
-
-- Completely trusted and centralized xD
-- If you leave your cookies you can simply log back in otherwise you need to log in again.
-
----
-
-# Everybody got a wallet?
-
----
-
-## Game 1: Ultimatum game
-
-- You are randomly matched with another student in the classroom.
-- The interaction is anonymous.
-- Player 1 gets an endowment of 100 points.
-- Player 1 can offer Player 2 between 0 and 100 points.
-- Player 2 sees the offer and can decide to accept or reject the offer.
-- If the offer is accepted, the endowment is split according to the offer.
-- If the offer is rejected, both get 0 points.
-- Budget for the game $500.
-- There is no right or wrong here.
-  It is your choice how to behave in this context!
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Game 1: Questions?
-
----
-
-## Let's start!
-
-Link will be distributed!
-
----
-
-## Game 1: Discussion
-
-- What were your strategies here?
-- What do you think we would expect from rational players?
-- Why did people offer something?
-- What did we measure here?
-
-Notes:
-
-- What would we expect from rational players (they do not know the concept of Nash Equilibrium yet but intuitively they can argue).
-- What do you expect the data to look like?
-- Did we measure fairness?
-  No.
-- How could we measure fairness?
-  - Dictator game
-- Talk about results in the literature:
-  - Many people offer 40-50%
-  - Almost nobody offers more than 50%
-  - Many people reject below 30%
-  - This is not only because of the stakes.
-    There are experiments in Thailand and Indonesia where they play with half year salary.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Game 1: Results!
-
----
-
-## Game 2: Cournot Competition
-
-- Economic model
-- Firms compete by setting quantities
-- Identical product
-- Demand always meets supply
-- Named after French mathematician Augustin Cournot.
-
-Notes:
-
-- Game 1: Cournot Competition with 2 firms (players from the audience) for 10 rounds
-- THe basic outline was given by Antoine Augustin Cournot in 1844, we will hear it again in GT.
-
----
-
-## Game 2: Overview
-
-- Cournot competition (Duopoly!)
-- 2 firms (you play 1 firm!)
-- Each of you individually set a quantity to produce.
-- All units are sold, but the price decreases in the quantity.
-- Repeated over 10 rounds
-- Points accumulate and are added to your budget.
-- Budget for the game: $500
-
----
-
-## Game 2: Rules
-
-<img rounded style="width:1200px" src="./img/cournot-1-instructions.png" />
-
-Notes:
-
-- 10 rounds not 2.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Game 2: Questions?
-
----
-
-## Let's start!
-
-Link will be distributed!
-
----
-
-## Game 2: Discussions
-
-- What strategy did you employ?
-- Did your behavior change over the rounds?
-- What was the best choice for each firm?
-
-Notes:
-
-- Calculate equilibrium:
-- $\pi = P(Q) * q$
-- For Firm 1: $\pi = (60 - q_1 - q_2) * q_1$
-- solve for optimal $q_1$ -> delta-pi / delta-q1 = -2q_1 - q_2 + 60 =! 0
-- q_1\* = (60 - q_2) / 2
-- q_2\* = (60 - q_1) / 2
-- q1* = (60 - (60-q1*)/2) / 2
-- = 30 - 15 + (q_1*/4) = q_1*
-- = q_1* = q_2* = 20
-- Show with example.
-  If firm 1 plays 20 then 19 leads to smaller payoff and 21 for other firm.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Game 2: Results!
-
----
-
-## Conclusion
-
-We learned:
-
-- fundamental economic concepts that are important to navigate in private- and professional life.
-- the notion of rationality and what to expect from actors that behave this way.
-- that especially human individuals deviate from rationality and behave differently.
-- the importance of time on value.
-- to engage in economic situations with other human actors.
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-# Collective Decision Making
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
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----
-title: Collective Decision Making
-description: Collective Decision Making for web3 builders
-duration: 1 hour
----
-
-# Collective Decision Making
-
----
-
-## Lesson highlights
-
-<pba-cols>
-<pba-col>
-<pba-flex center>
-
-##### Decision<br />making systems
-
-- Common systems
-- Goals and trade-offs
-
-</pba-flex>
-</pba-col>
-<pba-col>
-<pba-flex center>
-
-##### Voting mechanisms
-
-- Common mechanisms
-- Desirable criteria
-
-</pba-flex>
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- This lesson will be markedly less "exact" than the previous ones in the module.
-  It will be less math and more critical thinking.
-- Hence, I encourage class participation.
-- However, many topics may be contentious and we might not be able to agree, especially not within the lesson time.
-  The objective of the lesson is to awaken your curiosity on the topic, and I encourage you to continue the discussions outside the classroom.
-- In the second half of the lesson we'll talk about voting mechanisms, which are widely used within many decision making systems.
-
----
-
-## Collective decision making
-
-An umbrella term that contains voting mechanisms,<br />governance processes, policy making, budget allocation.
-
----
-
-## Collective decision making
-
-- A way to gather the opinions of a heterogenous collective.
-- A way to aggregate their preferences in a concise way.
-- A way to reach a _decision_ over the definition, resources, privilege or authority of a collective.
-
-Notes:
-
-- In this lesson we will study some of the different ways in which people can make decisions as a unit.
-- When people think of collective decision making, they usually only think of voting for a representative or representatives, and then letting them make all the decisions.
-  But it is important to remember that this is just one of many possible mechanisms to reach a decision as a collective.
-
----
-
-## Why?
-
-- A prerequisite for the formation of countries, companies, dynasties, i.e., _strong institutions_.
-- Agile decision making helps collective react to _external_ changes: war, trade, migration.
-- _Internally_, they enable stability and progress: money, laws, private property.
-
----
-
-## Why?
-
-- Even high tech, highly automated projects remain human collectives at their core.
-- A project's decision-making mechanisms ensure its strength and relevance over time.
-- We should consider these mechanisms along with the project's economics and security.
-
-Notes:
-
-- We use the words "collectives" in a very broad sense, to include not only nations and dynasties, but also modern collectives like tech companies, social networks, and online communities.
-  It is important to remember that these are human collectives, no matter how technical or automated they appear.
-- Only well designed decision-making mechanisms can ensure that a collective stays strong and relevant over time.
-  Otherwise, it will disintegrate due to internal discontent or external changes.
-- Hence, analyzing a project's decision making mechanisms is just as important as analyzing the soundness of its cryptography, economics and security.
-
----
-
-## A more profound interpretation
-
-Long you live and high you fly<br />
-Smiles you'll give and tears you'll cry<br />
-**And all you touch and all you see<br />
-Is all your life will ever be**<br />
-
--- Pink Floyd (Breathe)
-
-Any single entity may be identified as the aggregate of _its (inter-)actions with its external environment_. If a system's governance wholly defines these, it may properly be considered to identify the entity.
-
----
-
-## Common systems
-
-- Dictator, unelected or elected.
-- Unelected committee (Zurich guilds).
-- Representative democracy -- elected committee.
-- Political parties
-- Direct democracy -- all participate in all decisions.
-
-Notes:
-
-- Can you think of other examples?
-- In the middle ages, the city of Zurich in Switzerland was run by guilds (merchants, farmers, tailors).
-  Women, and anyone outside these guilds, had no say in the decision-making process.
-
----
-
-## Goals
-
-<!-- prettier-ignore -->
-|                  |                                                                                 |
-| :--------------: | :-----------------------------------------------------------------------------: |
-|   **Utility**    | - decision maximizes society's welfare<br /> - it reflects people's preferences |
-|  **Legitimacy**  |          - decision is considered fair<br />- people trust the process          |
-| **Practicality** |              - process is fast<br /> - it is simple to understand               |
-|                  |                                                                                 |
-
-Notes:
-
-- The three key goals of any decision making process are utility, legitimacy and practicality.
-- While _utility_ is about the objective quality of the final result, _legitimacy_ is about the perceived quality of the process.
-  A mechanism is considered legitimate if most people trust the process, agree with it and feel empowered by it, even if they may not personally like the outcome.
-- For instance, if Fifa had decided unilaterally that Argentina wins the world cup, this decision making mechanism would have the same utility but not the same legitimacy as playing the games: everyone would be angry at it.
-- Finally, the _practicality_ goal plays an important role especially if we have a very large population, or a short time window to make a decision, e.g., in an emergency.
-
----
-
-## Goals
-
-<pba-flex center>
-
-- A dictator is practical.
-  Is it legitimate?
-- Direct democracy is legitimate.
-  Why not always use this?
-- Which mechanism maximizes utility?
-- Which is best in case of war?
-
-</pba-flex>
-
-Notes:
-
-- This is the type of questions we are gonna explore in this lesson.
-- Direct democracy is considered legitimate but is unfortunately slow.
-  If would not be the right mechanism for an emergency, such as war.
-- In the next slides, we look more closely at some of the most common systems.
-
----
-
-## Dictator
-
-<pba-flex center>
-
-- Legitimate?
-- It is _very_ practical.
-- Good in case of an emergency.
-- Only stable as long as the individual is stable (unlikely to be forever!).
-
-</pba-flex>
-
-Notes:
-
-- What's wrong with a dictator?
-  We typically think of it as illegitimate, but keep in mind that kings used to be considered legitimate in the past.
-  And even today, the owner of a large tech company may be able to make unilateral decisions that impact millions of lives, and we consider this to be legitimate.
-- It is practical and allows for fast decision making in case of an emergency.
-  For example, in the next pandemic, would you like to have every city vote on whether and when face masks should be mandatory in public spaces?
-  Or would you prefer to have an authority impose it?
-- You could also argue that it leads to stability, as people can expect things to stay the way they are for the foreseeable future, and can plan accordingly.
-  However, we also have several real-life examples where a dictator behaves erratically.
-
----
-
-## Democracy
-
-<img rounded style="width: 900px;" src="./img/democracy-meme.png" />
-
-Notes:
-
-- Lots of different things to lots of different people.
-- Democracy doesn't really exist, only systems which are democratic to a some degree.
-
----
-
-## Simple Direct Democracy
-
-<pba-flex center>
-
-- Every person is consulted on every decision.
-- Considered highly legitimate.
-- Good at revealing the collective's opinions.
-- Leads to progress as anyone can propose ideas.
-
-</pba-flex>
-
-Notes:
-
-- Direct democracy represents an extreme where every person is consulted on every decision, for instance via referendums.
-- It is great at revealing the people's opinions, and adapting at evolving opinions.
-- Similarly, if we assume that anyone is free to raise a proposal in direct democracy, then there is a sort of "free market of ideas".
-  This leads to quick progress, because innovative ideas that challenge the status quo are not silenced.
-
----
-
-## Simple Direct democracy
-
-<img rounded style="width: 900px;" src="./img/direct-democracy.png" />
-
-Compare to a two-party system
-
-Notes:
-
-- For instance, imagine a two-party system like the US where people are forced to pick one of two parties, instead of directly casting their vote on every decision.
-  Imagine the left party traditionally supports legalizing abortion and banning firearms, while the right party traditionally supports banning abortion and legalizing firearms.
-  Such idiosyncrasy could have made sense in the past, but if there is a shift in preferences whereby more and more people want to legalize both abortions and guns, the system will not have the means to detect these preferences and adapt properly.
-- Similarly, if neither the left party nor the right party supports universal healthcare, then people who support healthcare do not have a voice.
-- Of course, similar issues remain for a multi-party system (more than two political parties), and the issues are even worse in a dictatorship.
-
----
-
-## Simple Direct democracy
-
-<pba-flex center>
-
-- Not very practical:<br />asking everyone to vote.
-- One decision at a time.
-- Not great for emergencies.
-
-</pba-flex>
-
-Notes:
-
-- On the down side, direct democracy is unfortunately not very practical for two reasons.
-  First, because asking every person to vote very slow.
-  In particular, having a referendum would probably not be wise in an emergency such as war, or a detected vulnerability in a computer network.
-
----
-
-## Voting paradox
-
-Does direct democracy maximize **utility**?
-_Probably not._
-
-Example:
-_Option A_: 0 dollars
-_Option B_: 100 dollars
-
-Prob. that _my vote_ flips the result from A to B: <0.1%.
-
-So, my expected profit for voting is <10 cents.
-
-Notes:
-
-- We saw that direct democracy is legitimate but not practical.
-  How does it fare in terms of utility?
-  Relatively well, but we argue here that it is not ideal, due to something called the voting paradox.
-- Suppose the collective must decide between options A and B, and I personally value option A as worth zero and option B as worth $100 to me.
-- Now, if most people vote for A, then A wins even if I vote for B, and if most people vote for B, then B wins even if I don't vote at all.
-  Hence the most likely event is that my vote does not change the outcome.
-- When the number of voters is in the millions, the likelihood that my vote actually changes the outcome is tiny, well below $0.1\%$.
-  My _expected profit_ for voting is then
-  (my profit for B - myr profit for A)$\times$prob.
-  that my vote flips the result.
-- In this example, my expected profit is less than 10 cents, which probably does not justify the effort of voting.
-
----
-
-## Voting paradox
-
-**Voting paradox:** For a rational, self-interested voter, voting costs will normally exceed the expected benefits.
-
-Minimal chance that single vote changes collective decision, so most of the time the individual voting benefit is zero.
-
-A _common good_ game: globally optimal if everyone votes, but personally optimal not to vote.
-
-Notes:
-
-- Voting paradox is a known concept in voting theory: if voters are rational and self interested, they should not vote.
-  The fact that many people vote means that they are either not rational, or not self interested.
-
----
-
-## Voting paradox
-
-**Voting paradox:** For a rational, self-interested voter, voting costs will normally exceed the expected benefits.
-
-It leads to a low _turnout_, which affects legitimacy.
-
-**Turnout:** percentage of people who choose to vote.
-
-Notes:
-
-- Indeed, we see for instance that in Switzerland, where direct democracy is used, the turnout is typically around 30%, and it's even lower in other systems.
-- Only a basic interpretation. Better technology and progressive voting systems (OpenGov!) can mitigate this issue.
-
----
-
-## Rational ignorance
-
-**Rational ignorance:** refraining from learning
-when the cost of educating oneself on an issue
-exceeds the expected potential benefit.
-
-As a result, most people will not vote _judiciously_.
-
-Notes:
-
-- A notion related to the voting paradox is that of rational ignorance: when the expected benefit we obtain from voting is minimal, we might not vote judiciously, even when we vote.
-- We have limited time and limited capacity to learn things, so we will give preference to acquiring the knowledge that personally brings us the most expected potential benefit.
-- In the previous example, if our expected benefit for voting at most 10 cents, and it takes us two hours to understand what the best option is, it may be wiser to vote at random even if we vote, and use that time to learn to code, or learn to play guitar, etc.
-
----
-
-## Rational ignorance
-
-Whether or not someone votes can be biasable.
-
-_40% of the population supports a new proposal,
-while 60% rejects it.
-However, a company
-who will profit from the decision lobbies for the 'aye'.
-50% of supporters and 30% of detractors vote.
-As a result, the proposal passes._
-
-Notes:
-
-- Another consequence of rational ignorance is that someone's vote can be biasable.
-  If you don't have a strong opinion about a vote because you haven't spent the time to learn about the issue deeply, you're more likely to be easily influenceable.
-
----
-
-## Solutions to the voting paradox
-
-- **Representative democracy**: elect a committee,
-  whose members represent well
-  the preferences of the _passive people_.
-
-- **Delegated voting**: give your voting power
-  to a person who understands the issue well,
-  so you don't have to.
-
-Notes:
-
-- We saw that a critique of direct democracy is that it's unrealistic to expect everyone in the population to invest their time to understand every issue, and then vote.
-- This leads to low turnout, which raises the question of legitimacy if a majority of the population does not voice their opinion.
-
----
-
-## Advanced Forms of Democracy
-
-<pba-flex center>
-
-- Liquid democracy/delegation
-- OpenGov/multi-track delegation
-- Quadratic "replacement" voting
-- OpenGov/Optimistic approval
-- ...
-
-</pba-flex>
-
----
-
-## Solutions to the voting paradox
-
-- Both solutions based on desire of
-  representing every _clique_ in the collective.
-- Delegated voting is organic, helps with turnout,
-  but remains slow.
-- A committee ignores preferences of small cliques,
-  but can take complex decisions fast.
-
-Notes:
-
-- However, people naturally tend to congregate with other people with similar preferences, to form what we call cliques.
-  So, you tend to be well represented by voters in your clique.
-  The idea of both systems is to "sample" some opinions for every clique.
-- From my point of view, delegated voting remains very close in spirit to direct democracy, as every individual remains free to vote directly if they choose to do so, or they can choose a representative that represents them very well.
-  We gain in terms of practicality as now fewer people need to vote, but the process is still slow and can only take binary decisions.
-- On the other hand, a committee is a bit closer to a dictator.
-  It does a good job at representing the most common preferences of the collective, but not the preferences of small cliques.
-  On the other hand, it can make subtle, non-binary decisions, and can make them fast.
-- Hence, it could be a good idea to use delegated voting for important, binary decisions (such as whether to make abortions legal), and an elected committee to make emergency decisions (such as what to do in case of war).
-  I encourage you to consider how you would design an ideal decision making system.
-
----
-
-## System capture
-
-Does a dictatorship maximize utility?
-Also **probably not**.
-
-**System capture:** A decision-making system
-in which a clique manages to impose
-its opinion consistently.
-
-Their special interest is prioritized
-over the interest of the collective,
-leading to a decrease of general welfare.
-
-Notes:
-
-- Before we argued that pure direct democracy might not maximize utility.
-  Now we also argue that a pure dictatorship is also not ideal for utility.
-
----
-
-## System capture
-
-_Example:_ in a movie club,
-40% of people like comedy,
-30% like drama, 30% like action.
-
-Should they watch a comedy every time?
-
-What if it was 60%, 20%, 20%?
-
-Notes:
-
-- Imagine that a group of friends meet every week to watch a movie, and 40% of members always pick comedy while 30% pick dramas and 30% pick action movies.
-- Would it be fair if a comedy is chosen every time?
-  Or what would decision-making system would you choose?
-- What if the percentages were 60%, 20%, 20%?
-  Is it now fair to always pick a comedy, since it makes a majority of people happy?
-
----
-
-## System capture
-
-<pba-flex center>
-
-- A dictatorship system is captured by definition.
-- A majority vote can lead to capture<br />if the minority's opinion is consistently ignored.<br />
-  Known as "tyranny of the majority".
-- It can affect legitimacy.
-
-</pba-flex>
-
-Notes:
-
-- Although a dictatorship is obviously a captured system, other systems also have varying degrees of risk of being captured.
-- For instance, as we saw with the movie club example, a majority vote can also lead to capture.
-- In turn, this can not only negatively affect the utility goal but also the legitimacy goal, if a group of people feel that their voice is always ignored.
-
----
-
-## Random dictator
-
-Whenever there is a decision to be made,<br />pick a person at random in the collective<br />and let them decide as a dictator.
-
-Notes:
-
-- As a curious note, we mention a system called random dictator.
-- It works quite well in the example of the movie club: every week, pick a person at random and let them select the movie to watch.
-- On the other hand, it would be a bad idea for a country to let a random dictator decide on the tax policy every month.
-  This is because in the case stability is more important than avoiding a tyranny of the majority.
-
----
-
-## Random dictator
-
-<pba-flex center>
-
-- _Very_ efficient.
-- _Very_ capture resistant (on average).
-- Terrible for stability.
-- Where is it used?
-
-Notes:
-
-- A random dictator system is captured in the short term, but it is highly resistant to capture in the long term.
-  This is because every clique, even very small ones, will have their voice heard with a frequency proportional to the clique size.
-- In fact, a version of random dictator is used in most blockchain consensus protocol, both based in proof-of-work and proof-of-stake.
-  We do this for efficiency, and because stability of block production is not a priority, while the highest priority is to resist capture by an adversarial minority.
-- This is because, if most block producers act honestly, then it is a Nash equilibrium to also act honestly when it is your turn to produce a block.
-  But if a minority manages to capture the system for some amount of time, and arbitrarily decide on the content of a majority of blocks produced during this time, then the minority has an incentive to attack the network for personal gain.
-
----
-
-## Capture resistance vs. stability
-
-<pba-flex center>
-
-- A dictatorship is _fully captured_ but also stable.
-- Direct democracy is at _risk of capture_, and still stable.
-- A random dictatorship is _most resistant to capture_, but unstable.
-
-</pba-flex>
-
-Notes:
-
-- In this chart we consider the size of a clique or constituent, and plot it against the influence it will have over the collective decision in expectation.
-- For instance, if there is an unelected dictator then no clique, big or small, has any influence on decisions.
-- In a two-party system, only fairly large constituents will have a voice, while small constituents will have no voice.
-- If we elect a larger committee then smaller constituents are more likely to be represented and hence have an influence on the final decision.
-- Finally, in a random dictator system we have that every constituent, no matter how small, has a chance of influencing the final decision in proportion to the constituent size.
-- In general, we see that there is a trade-off between being resistant to capture and being stable.
-
----
-
-## Recap
-
-- Goals: utility, legitimacy and practicality.
-- In emergencies, practicality may be more relevant.
-- Simple direct democracy is legitimate, not so practical.
-- Dictatorship is practical, not legitimate.
-- Probably neither extreme maximizes utility.
-- With new technology, we have better tools & mechanisms to make direct democracy effective
-
----
-
-## Voting mechanisms
-
-- Widely used within decision-making systems.
-- _Candidates_ to choose from: people, policies.
-- _Voters_ who declare preferences through _ballots_.
-- A mechanism takes these ballots as input,
-  and outputs a single candidate as the _winner_.
-- Many _criteria_ to judge the mechanism.
-
-Notes:
-
-- New topic, wake up!
-- Voting mechanisms are some of the most popular ways to make collective decisions, and have been for centuries.
-- Why do you think that is? They are used for the election of leaders, for decision making within a governance body, choosing the winners in contests, among friends to decide on a restaurant, or in a family to name a dog.
-- Without a doubt, one of the most desirable criteria for a collective decision making mechanism is _simplicity_, meaning that it should be easy to understand and participate for the population.
-  This is probably a big pro for voting mechanisms.
-- In the next slides we will explore some of the most popular voting mechanisms, along with some of the most popular criteria used to compare them.
-- What criteria do you think are most intuitive and desirable for a mechanism? Fairness? Proportionality? Utility? How would you define these terms precisely?
-
----
-
-## Voting mechanisms
-
-We will see the following notions:
-
-- _Single-vote mechanisms:_ plurality, two-round.
-- _Ranked-vote mechanisms:_ Borda count, ranked-pairs.
-- Vote splitting, strategic voting.
-- Monotonicity criterion.
-
-Notes:
-
-- Two main types, depending on how the voters declare their preferences: in single-vote mechanisms, each voter selects one candidate, while in ranked-vote mechanisms, each voter ranks all candidates.
-
----
-
-## Single-vote mechanisms
-
-Mechanisms where each voter picks _one_ candidate.
-
-- **Plurality voting:** Candidate with most votes wins,
-  even if they do not receive an absolute majority of votes.
-- **Two-round voting:** Top two candidates are voted on again.
-  The candidate with most votes in second round wins.
-
-Notes:
-
-- These are some of the most popular voting mechanisms.
-  They are certainly among the simplest ones.
-- Plurality is also known as "first past the post" in the UK, where it is widely used.
-- Consider also the generalization - multi-round mechanisms
-
----
-
-## Single-vote mechanisms
-
-<pba-cols>
-<pba-col>
-
-**Plurality:** **8 votes for A,** 5 votes for B, 7 votes for C.
-
-**Two-round:**
-
-- 1st: **8 votes for A,** 5 votes for B, **7 votes for C**.
-- 2nd: 8 votes for A, **12 votes for C**.
-
-</pba-col>
-
-<pba-col>
-
-<!-- prettier-ignore -->
-|          | 1st | 2nd | 3rd |
-| -------- | --- | --- | --- |
-| 8 voters | A   | B   | C   |
-| 7 voters | C   | B   | A   |
-| 5 voters | B   | C   | A   |
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- Recall that voters only vote for a single voter per round.
-  But for convenience in what follows we assume we know the full candidate ranking of each voter, so we can analyze what would happen if any two out of the three candidates go head to head in the second round.
-- Are they equivalent?
-  No.
-  Look at the example above where there are three candidates A, B and C, and 20 voters with three types of preferences.
-- In plurality voting, we would only get to see the first column, and elect A with 8 votes.
-- In two-round, candidates A and C would go to second round, where the 5 voters in the last row would change their vote from B to C, and candidate C would win with 12 votes.
-- In general, several seemingly reasonable mechanisms result in different winners for the same collection of voters' preferences.
-  This is why we need to look more closely into what properties we want out of a mechanism.
-
----
-
-## Vote splitting
-
-<img rounded style="width: 900px;" src="./img/vote-splitting.png" />
-
-Notes:
-
-- Which of these mechanisms is better?
-  Here is an argument against plurality voting.
-- In 2014, Candidate Chandu Sahu, from a political party called BJP in India, was a favorite to win in an election against opponent Ajit Jogi.
-  To his surprise, on the day of the elections there were 10 other independent candidates registered with the same exact name.
-  Apparently most of these candidates had no history in politics, but someone found them and offered them money to run on the elections.
-  Of course, the obvious suspect is the opponent, but it was never proven.
-  Luckily, the original Chandu Sahu still managed to win, but by only a razor-thin margin of 1200 votes, as the other 10 fake candidates accumulated around 70 thousand votes.
-- This technique is known as vote splitting, and plurality voting is well known to be susceptible to it.
-
-Image source: <https://indianexpress.com/article/political-pulse/the-10-other-sahus-how-namesakes-almost-cost-bjps-chandu-lal-sahu-a-win/>
-
----
-
-## Vote splitting
-
-<pba-cols>
-<pba-col>
-
-- Imagine B and C are similar candidates,
-  and most people prefer either over A.
-- Known issue in plurality.
-  Two-round helps alleviate it.
-
-</pba-col>
-<pba-col>
-
-<!-- prettier-ignore -->
-|          | 1st | 2nd | 3rd |
-| -------- | --- | --- | --- |
-| 8 voters | A   | B   | C   |
-| 7 voters | C   | B   | A   |
-| 5 voters | B   | C   | A   |
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- Imagine that candidates B and C are very similar, i.e., they have similar points of view (or a similar name!) In the example, we see that a majority of the population prefers either of them to A, but since their votes are split, both candidates would lose out to A in plurality voting.
-- This issue is known as _vote splitting_.
-  Two-round voting helps reduces its effect.
-- In electoral systems that implement plurality voting, vote splitting is sometimes used as a weapon by the less popular party (in our example, A), who strategically nominates a candidate similar to their rival to split their votes.
-- In turn, a common defense against vote splitting is to form alliances among similar candidates.
-
----
-
-## Monotonicity criterion
-
-- A voter raising their rank for the winning candidate,
-  or lowering their rank for a losing candidate,
-  should not change the winner.
-- Plurality is monotonic, _two-round voting is not_.
-
-Notes:
-
-- Conversely, here is an argument against two-round voting.
-- Monotonicity is one of the most intuitive criteria that we would expect from a voting rule.
-  It says that the winning candidate should be stable relative to monotonic changes of the voter's preferences.
-  In particular, if a voter raises their preference for the current winner, or lowers their preference for other candidates, then the winner should not change.
-- Failure of this criterion means that the mechanism is susceptible to strategic voting, because a rational voter may be better off hiding their real preferences.
-
----
-
-## Monotonicity Criterion
-
-<pba-cols>
-<pba-col>
-
-**Two-round:**
-
-- 1st: **8 votes for A**, 6 votes for B, **7 votes for C**.
-- 2nd: **11 votes for A**, 10 votes for C.
-
-</pba-col>
-<pba-col>
-
-<!-- prettier-ignore -->
-|          | 1st | 2nd | 3rd |
-| -------- | --- | --- | --- |
-| 6 voters | A   | B   | C   |
-| 2 voters | A   | C   | B   |
-| 3 voters | B   | A   | C   |
-| 3 voters | B   | C   | A   |
-| 5 voters | C   | B   | A   |
-| 2 voters | C   | A   | B   |
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- We will see now that two-round voting is not monotonic.
-- In this example, there are 21 voters, with 6 types of preferences.
-- In two-round voting, A and C go to the second round, where A wins 11 against 10.
-
----
-
-## Monotonicity Criterion
-
-<pba-cols>
-<pba-col>
-
-Bottom-row voters _raise their preference for A_.
-
-**Two-round:**
-
-- 1st: **10 votes for A**, **6 votes for B**, 5 votes for C.
-- 2nd: 10 votes for A, **11 votes for B**.
-
-</pba-col>
-<pba-col>
-
-<!-- prettier-ignore -->
-|          | 1st   | 2nd   | 3rd |
-| -------- | ----- | ----- | --- |
-| 6 voters | A | B | C |
-| 2 voters | A | C | B |
-| 3 voters | B | A | C |
-| 3 voters | B | C | A |
-| 5 voters | C | B | A |
-| 2 voters | **A** | **C** | B |
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- But now suppose the 2 voters in the bottom row raise their preference for A.
-  They simply swap the positions of A and C in their ranking.
-- Now C doesn't make it to the second round.
-  In the second round, now B wins 11 to 10 against A.
-- Hence, two-round voting is not monotonic.
-
-- If the bottom-row voters want candidate A to win, they are better off marking C as their top preference.
-
----
-
-## Strategic voting
-
-A mechanism in which a voter
-increases the chances of a candidate
-by _not voting for them_.
-
-Notes:
-
-- A mechanism that is not monotone is susceptible to strategic voting.
-- This is the case with two-round voting.
-- Indeed, in the previous example, the bottom-row voters want candidate A to win, but are better off marking C as their top preference.
-
----
-
-## Ranked-vote mechanisms
-
-<pba-cols>
-<pba-col>
-
-Mechanisms where each voter ranks _all_ candidates.
-
-- In 1770, Jean-Charles de Borda showed 2-round
-  may elect a candidate that would lose out
-  head-to-head to _every other candidate_.
-
-</pba-col>
-<pba-col>
-
-<!-- prettier-ignore -->
-|          | 1st | 2nd | 3rd |
-| -------- | --- | --- | --- |
-| 8 voters | A | B | C |
-| 7 voters | C | B | A |
-| 5 voters | B | C | A |
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- Are there monotonic mechanisms better than plurality voting?Yes!
-- But they require more information from the voters: they need to rank all the candidates.
-- The unfair nature of plurality voting was pointed out in 1770 by French mathematician Jean-Charles de Borda, in a presentation at the French Royal Academy of Sciences.
-- He proved that plurality voting can elect the least favorite candidate: one that would be defeated by every other candidate in a head-to-head election.
-- Going back to our first example, recall that A was the winner in plurality voting, yet if A and B go head-to-head, A loses 8 to 12, and if A and C go head-to-head, again A loses 8 to 12.
-- Finally, if B and C go head-to-head, B would win 15 to 5, so in a sense B is the overall winner of pair-wise elections.
-
----
-
-## Borda count
-
-<pba-flex center>
-
-- Each voter gives a rank of all $k$ candidates
-- Interpreted as if giving $k-1, k-2, \cdots, 1, 0$ points
-- Add up all points, select candidate with most points.
-- Borda count is _monotone_.
-
-</pba-flex>
-
-Notes:
-
-- Borda proposed a new election mechanism, known today as the Borda count, that can be thought of as a generalization of two-round voting.
-- If there are $k$ candidates, this is interpreted as if the a voter gives $k-1$ points to their favorite candidate, $k-2$ points to their second favorite candidate, and so on until their least favorite candidate gets zero points.
-  Then, we elect the candidate that received the most points overall.
-
----
-
-## Borda Count
-
-<!-- prettier-ignore -->
-|          | 2 points | 1 point | 0 points |
-| -------- | -------- | ------- | -------- |
-| 8 voters | A | B | C |
-| 7 voters | C | B | A |
-| 5 voters | B | C | A |
-
-<br />
-
-16 points for A, **25 points for B**, 19 points for C.
-
-Notes:
-
-- In our example, we see that B wins, as expected.
-  We highlight that for the exact same example, the winner was A under plurality and C under two-round!
-
----
-
-## Recap
-
-<pba-flex center>
-
-- Borda count is arguably more fair.
-- But plurality and two-round voting are simpler.
-- Simplicity seems to be important in practice.
-- No voting mechanism is perfect.
-
-</pba-flex>
-
-Notes:
-
-- In the area of voting theory, there are many other voting mechanisms known, and many other possible criteria to classify them.
-  Voting theory is a fascinating topic at the intersection between mathematics and political theory.
-- In general, we see that the rules with better properties tend to be more complicated, which is unfortunately why they are not used as much.
-  Hence, we can say that no mechanism is perfect.
-- Still, some mechanisms will be a better fit than others depending on our priorities for a system.
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-# Break
-
-Notes:
-
-10 minutes
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Discussion
-
----
-
-## Goals clash
-
-<pba-flex style="padding: 0 3em 0 3em" center>
-
-We mentioned that the main goals of a decision-making system are utility, legitimacy and practicality.
-
-**Can you think of real-life scenarios where these goals clash?**
-
-</pba-flex>
-
-Notes:
-
-- We saw that ranked-based voting, like Borda count, seems to be more fair (utility), but it is less simple to participate (practicality), which is probably why it's not so popular.
-
----
-
-## Sampling voters
-
-<pba-flex style="padding: 0 3em 0 3em; font-size: smaller;" center>
-
-In a country that runs referendums periodically, the turnout is only 2%, and older people tend to vote much more often than younger people.
-
-The president changes the voting mechanism so that in each referendum, only 5% of the population elected uniformly at random is _allowed_ to vote.
-As a result, every person is allowed to participate in one out of 20 referendums on average.
-
-It is now observed that 80% of the people allowed to vote actually vote, so the global turnout grows from 2% to 4%.
-Moreover, the previously correlation between age and willingness to vote decreases considerably.
-
-**Would you support this new mechanism?**
-
-</pba-flex>
-
-Notes:
-
-- We saw that representative democracy and delegated voting can be seen as sampling opinions from the collective, so that not everyone has to vote.
-  In the exercise we take the sampling idea literally.
-- Is this new mechanism more or less legitimate?
-  Does it have higher utility?
-  I think it has higher utility but less legitimacy.
-- Is it practical?
-  It could be an issue to have a sampling process that is verifiably random and unbiased.
-  This affects practicality and legitimacy.
-
----
-
-## A holy grail
-
-<pba-flex style="padding: 0 3em 0 3em" center>
-
-A "holy grails" of voting theory is finding a voting mechanism that simultaneously offers _local privacy_ and _global transparency_: no one should be able to see another person's ballot, but enough aggregate information about the ballots should be public so that everyone can verify the correctness of the result.
-
-Suppose such a mechanism is created using cryptography; however, it requires every voter to use a private key and be trained in the basics of cryptography.
-A nation's president proposes to use such a mechanism, but the feedback from the population is negative, because people don't trust digital voting or cryptography.
-
-**What goals are at odds here?**
-**What would you do as president?**
-
-</pba-flex>
-
-Notes:
-
-- While there is a lot of active research in this topic, there is no fully satisfactory solution yet.
-- The goals at odds are legitimacy and utility.
-  If people don't trust the process then it is not legitimate, even if it has many advantages in theory.
-- The president could try to educate people about the new system, but should probably not impose it.
-
----
-
-## Proof of Stake
-
-<pba-flex style="padding: 0 3em 0 3em" center>
-
-In a Proof-of-stake (PoS) based blockchain network, _validators_ are the nodes that participate in the consensus protocol and produce blocks.
-While it is possible to have a "pure" PoS mechanism where every token holder can participate in consensus directly (imitating PoW), most high-profile projects bound the number of validators that get to be active at any given moment.
-
-Instead, these project opt for "representative democracy" and let token holders express their preferences for the set of active validators.
-Examples of blockchain projects that do this are: Polkadot, Cardano, Cosmos, EOS, Tezos and Tron.
-
-**What do you think are the main reasons behind this choice?**
-
-</pba-flex>
-
-Notes:
-
-- Mostly for operational reasons
-- As the validator set size increases, the communication costs grow quickly (superlinearly), while the increase in security grows slowly past a certain point.
-- It is not sensible to run nodes for only sporadic participation.
-  Validators would naturally tend to form pools anyway, to decrease the variance of their revenue, and profit from economies of scale.
-
----
-
-## Secure Validators
-
-We saw that it's critically important for security to ensure that the set of validators is not captured by an adversary.
-Suppose we succeed, so that a super majority of validators participate in consensus honestly.
-
-A priori, the mechanism for electing validators can be completely independent of the mechanism for deciding on upgrades.
-However, some projects merge them together.
-In particular, consider a project that on any referendum, delegates the voting power of all the passive stakeholders to the set of validators.
-
-**Does this constitute _capture_ of the governance body?**
-
-**Can you think of examples where the interests of validators are markedly different from the interests of the collective?**
-
-Notes:
-
-- Yes, for instance if we vote to increase the staking rewards, all validators would support it, but this negatively affects stakeholders who are using their tokens in other ways (such as in financial applications like lending).
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-# The Economics of Polkadot
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
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-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: The Economics of Polkadot
-description: Tokenomics of Relay Chains and more
-duration: 2 hour
----
-
-# The Economics of Polkadot
-
----
-
-## Overview
-
-<ul>
-<li class="fragment">Which economic pieces build the the Polkadot Network?</li>
-<li class="fragment">What are their mechanisms and incentives?</li>
-<li class="fragment">How are those pieces interrelated?</li>
-</ul>
-
-<p class="fragment">Remark: There are currently many changes planned</p>
-
----
-
-<img rounded style="width: 1200px; margin-right: 50px;" src="./img/polkadot_pieces.svg" />
-
----
-
-# Token Economics
-
----
-
-## DOT Token
-
-<ul>
-<li class="fragment">Native token of the Polkadot network.</li>
-<li class="fragment">1 DOT = \(1\mathrm{e}{10}\) Plancks</li>
-<li class="fragment">
-    Planck = smallest unit of account.
-    <ul>
-        <li class="fragment">Reference to Planck Length = the smallest possible distance in Physics.</li>
-    </ul>
-</li>
-<li class="fragment">
-    <strong>Utility Token</strong> with several use-cases:
-    <ul>
-        <li class="fragment">Governance (decentralization)</li>
-        <li class="fragment">Bonding in slot auctions (utility)</li>
-        <li class="fragment">Staking (security)</li>
-        <li class="fragment">Message passing (e.g., transfers)</li>
-    </ul>
-</li>
-</ul>
-
----
-
-## Inflation Model
-
-<ul>
-<li class="fragment">Expansion in token supply.</li>
-<li class="fragment">Token minted from thin air.
-  <ul>
-  <li class="fragment">Used to pay staking rewards for validators and nominators.</li>
-  <li class="fragment">(Indirectly) fund Treasury.</li>
-  </ul>
-</li>
-<li class="fragment">Central economic variables of the model are:</li>
-<li class="fragment"><strong>Exogenous</strong>:
-  <ul>
-  <li class="fragment">Staking rate (Total amount of staked DOT / Total amount of DOT).</li>
-  </ul>
-</li>
-<li class="fragment"><strong>Endogenous</strong>:
-  <ul>
-  <li class="fragment">Optimal staking rate (a sufficient backing for validators to provide reasonable security).</li>
-  </ul>
-</li>
-<li class="fragment">Total inflation rate (10%).</li>
-</ul>
-
----
-
-## Inflation Model
-
-<ul>
-<li class="fragment">Different <strong>states</strong> of DOT:
-  <ul>
-  <li class="fragment"><strong>Liquid</strong>: Used for messaging and liquidity on markets.</li>
-  <li class="fragment"><strong>Bonded (Staking)</strong>: Economic mass that guarantees the security of the network.</li>
-  <li class="fragment"><strong>Bonded (Parachains)</strong>: The demand for DOT tokens by parachains.</li>
-  </ul>
-</li>
-<li class="fragment">The goal is to obtain (some) <strong>sensible ratio</strong> between those three token states.</li>
-</ul>
-
----
-
-## Inflation Model
-
-<div style="display: flex; justify-content: center; align-items: center;">
-    <div style="flex: 1; text-align: center;">
-        <img rounded style="width: 650px; margin-right: 50px;" src="./img/current_inflation_model_polkadot.png" />
-    </div>
-    <div style="flex: 1;">
-        <ul>
-            <li class="fragment"><strong>Central variable</strong>: Ideal staking rate (currently ~53.5%).</li>
-            <li class="fragment">Highest staking rewards at the ideal staking rate.</li>
-            <li class="fragment">Incentives to (increase) decrease the staking rate it is (below) above the optimal.</li>
-            <li class="fragment">Staking inefficiencies -> Treasury.</li>
-            <li class="fragment">Ideal staking rate scales with number of active parachains (0.5% less with each parachain).</li>
-        </ul>
-    </div>
-</div>
-
----
-
-## Inflation
-
-<ul>
-    <li class="fragment">In the fiat-world, inflation has a negative connotation.</li>
-    <li class="fragment">This is a general discussion in economics.</li>
-    <li class="fragment">My take on this:</li>
-    <ul>
-        <li class="fragment">Predictable (maximum) inflation is good.</li>
-        <li class="fragment">It incentivizes to work with the tokens (i.e., bond for good parachains, use for message passing).</li>
-        <li class="fragment">Deflation can cause a halt of economic activity, because people start hoarding tokens.</li>
-    </ul>
-</ul>
-
-Notes:
-
-Question: What do you think about Inflation?
-
----
-
-## Potential changes incoming
-
-<ul>
-    <li class="fragment">The current system incentivizes to move the staking rate to the ideal rate.</li>
-    <li class="fragment">Then, Treasury inflow would be 0 DOT.</li>
-    <li class="fragment">That is not sustainable.</li>
-    <li class="fragment">Proposed change: Detach inflation to stakers from total inflation and divert the rest to Treasury directly.</li>
-</ul>
-
----
-
-## Staking: Concept
-
-<ul>
-    <li class="fragment"><strong>Nominated Proof-Of-Stake (NPoS)</strong>.</li>
-    <li class="fragment">Economic incentives of <strong>validators</strong> and <strong>nominators</strong> are aligned with those of the network.</li>
-    <ul>
-        <li class="fragment">Good behavior is rewarded with staking rewards.</li>
-        <li class="fragment">Malicious / Neglecting behavior is punished (slashed).</li>
-    </ul>
-    <li class="fragment">Currently, minimum total stake is ~1.6M DOTs.</li>
-    <li class="fragment">The total stake in the system directly translates to the <strong>economic security</strong> that it provides.</li>
-    <li class="fragment">Total stake is pooled from validators (self-stake) and their nominators (nominated stake)</li>
-    <ul>
-        <li class="fragment">High degree of inclusion</li>
-        <li class="fragment">High security</li>
-        <li class="fragment">The goal is to get as much <strong>skin-in-the-game</strong> as possible.</li>
-    </ul>
-</ul>
-
----
-
-## Validators
-
-<ul>
-    <li class="fragment">What makes Validators resilient:</li>
-    <ul>
-        <li class="fragment">Self-stake</li>
-        <li class="fragment">Reputation (identity)</li>
-        <li class="fragment">High future rewards (self-stake + commission)</li>
-    </ul>
-</ul>
-
----
-
-## Nominators
-
-<ul>
-    <li class="fragment">Bond tokens for up to 16 validators that they deem trustworthy.</li>
-    <li class="fragment">They have an incentive to find the best ones that match their preferences.</li>
-    <li class="fragment">They are tasked to collectively curate the set of active validators.</li>
-</ul>
-
----
-
-## Rewards
-
-<pba-cols>
-<pba-col>
-<pba-flex center>
-
-<img rounded style="width: 700px;" src="./img/rewards_flow.png" />
-
-</pba-flex>
-</pba-col>
-<pba-col>
-
-<ul>
-    <li class="fragment"><em>What are staking rewards for?</em></li>
-    <li class="fragment"><strong>Validators</strong>: Hardware, networking, and maintenance costs, <strong>resilience</strong>.</li>
-    <li class="fragment"><strong>Nominators</strong>: Curation of the active set of validators, sort out the good from the bad ones (Invisible Hand).</li>
-</ul>
-
-</pba-col>
-</pba-cols>
-
----
-
-## Validator Selection
-
-<ul>
-    <li class="fragment">The job of nominators is to find and select suitable validators.</li>
-    <li class="fragment">Nominators face several trade-offs when selecting validators:</li>
-    <ul>
-        <li class="fragment">Security, Performance, Decentralization</li>
-        <li class="fragment">Ideally those variables in their historic time-series.</li>
-    </ul>
-    <li class="fragment">Economic Background:</li>
-    <ul>
-        <li class="fragment">Self-stake as main indicator of skin-in-the-game.</li>
-        <li class="fragment">Higher commission, ceteris paribus, leaves a validator with more incentives to behave.</li>
-    </ul>
-    <li class="fragment">Various sources of trust</li>
-    <li class="fragment">Efficient validator recommendation is one of my research topics.</li>
-</ul>
-
----
-
-# Parachains
-
----
-
-## What are Parachains?
-
-<ul>
-    <li class="fragment">Parachains (or cores) are the layer-1 part of the protocol.</li>
-    <li class="fragment">Blockchains of their own that run in parallel.</li>
-    <ul>
-        <li class="fragment">Highly domain specific and have high degree of flexibility in their architecture.</li>
-        <li class="fragment">Share same messaging standard to be interoperable and exchange messages through the Relay Chain.</li>
-    </ul>
-    <li class="fragment">Polkadot: 43 Parachains, Kusama: 46 Parachains.</li>
-    <li class="fragment">Their state transition function (STF) is registered on the Relay Chain.</li>
-    <ul>
-        <li class="fragment">Validators can validate state transitions without knowing all the data on the Parachain.</li>
-        <li class="fragment">Collators keep the parachain alive (but are not needed for security).</li>
-    </ul>
-    <li class="fragment">Offer their utility to the network.</li>
-</ul>
-
----
-
-## Parachain Slots
-
-<ul>
-    <li class="fragment">The access to the network is abstracted into the notion of “slots”.</li>
-    <ul>
-        <li class="fragment">Leases for ~2 years on Polkadot (~1 year on Kusama).</li>
-        <li class="fragment">Only limited amount of slots available (networking).</li>
-        <li class="fragment">The slots are allocated through a candle auction.</li>
-    </ul>
-    <li class="fragment">Bonded tokens held (trustlessly) in custody on the Relay Chain.</li>
-    <li class="fragment">The tokens will be refunded after the slot expires.</li>
-</ul>
-
----
-
-## Economic Intuition
-
-<ul>
-    <li class="fragment">Tokens cannot be used for anything (staking, transacting, liquidity, governance).</li>
-    <ul>
-        <li class="fragment">That means, tokens locked cause opportunity costs.</li>
-        <li class="fragment">An approximation is the trust-free rate of return from staking.</li>
-    </ul>
-    <li class="fragment">Parachains need to compete with those costs and generate benefits that exceed those opportunity costs.</li>
-    <ul>
-        <li class="fragment">Sufficient crowdloan rewards.</li>
-        <li class="fragment">Sufficient economic activity on-chain that justifies renewal.</li>
-    </ul>
-    <li class="fragment">Slot mechanism creates constant demand for DOT token.</li>
-    <li class="fragment">It is costly to be and remain a parachain.</li>
-    <ul>
-        <li class="fragment">Natural selection mechanism to select useful parachains.</li>
-        <li class="fragment">Continuous pressure to gather funds for extending slots.</li>
-    </ul>
-</ul>
-
----
-
-## What do Parachains get?
-
-<ul>
-    <li class="fragment"><strong>Parachains pay for security</strong>.</li>
-    <ul>
-        <li class="fragment">Every parachain is as secure as the Relay Chain.</li>
-        <li class="fragment">Polkadot is a security alliance with network effects.</li>
-        <li class="fragment">Not only scaling number of transactions, but it also scaling of security.</li>
-    </ul>
-    <li class="fragment">Security is a pie of limited size, because financial resources are limited.</li>
-    <li class="fragment">Every chain that secures itself need cut a piece of the cake, which leaves less to others (zero-sum).</li>
-    <li class="fragment">Shared security protocols allow to keep the cake whole and entail it to all participants.</li>
-    <li class="fragment">Shared security is a scaling device, because the amount of stake you need to pay stakers to secure 100 shards is less than you need to pay stakers to secure 100 individual chains.</li>
-</ul>
-
----
-
-## Outlook Polkadot 2.0
-
-<ul>
-    <li class="fragment">Based on Gav’s Keynote at Polkadot Decoded 2023.</li>
-    <li class="fragment">A new narrative of the whole Polkadot system.</li>
-    <li class="fragment">We move away from regarding Parachains as a distinct entity but rather regard Polkadot as global distributed computer.</li>
-    <li class="fragment">It's spaces and apps rather than chains.</li>
-    <li class="fragment">This computer has computation cores that can be allocated flexible to applications that need it.</li>
-    <li class="fragment">Coretime can be bought, shared, resold.</li>
-</ul>
-
----
-
-## Core Attributes of Blockspace
-
-<ul>
-    <li class="fragment"><strong>Security</strong>: The scarcest resource in blockchain, crucial in preventing consensus faults or 51% attacks that could compromise transactions.</li>
-    <li class="fragment"><strong>Availability</strong>: Ensuring blockspace is available without long waiting times or uncertain costs for a smooth, seamless interaction within the decentralized ecosystem.</li>
-    <li class="fragment"><strong>Flexibility</strong>: The ability of blockspace to be fine-tuned by the consumer for specific use-cases.</li>
-</ul>
-
----
-
-## Blockspace Ecosystem
-
-<ul>
-    <li class="fragment">A networked collection of individual blockspace producers (blockchains) offering secured, fit-for-purpose, efficiently-allocated, and cost-effective blockspace.</li>
-    <li class="fragment">A valuable aspect of a blockspace ecosystem is its connective tissue of shared security and composability.</li>
-    <li class="fragment">Dapp developers or blockspace providers can focus on their unique features, reusing existing capabilities within the ecosystem.</li>
-    <li class="fragment">For example, a supply chain traceability application could use different types of blockspace for identity verification, asset tokenization, and source traceability.</li>
-</ul>
-
----
-
-## Bulk markets
-
-<ul>
-    <li class="fragment">It's not yet finalized how they work but likely:</li>
-    <ul>
-        <li class="fragment">Around 75% of cores are allocated to the market.</li>
-        <li class="fragment">Cores are sold for 4 weeks as NFT by a broker.</li>
-        <li class="fragment">Unrented cores go to the instantaneous market.</li>
-        <li class="fragment">Price de-/increases relative to demand.</li>
-        <li class="fragment">Current tenants have a priority buy right for their core(s).</li>
-    </ul>
-</ul>
-
----
-
-## Why the change?
-
-<ul>
-    <li class="fragment">This allows for low barriers of entry for people to simply deploy their code to a core and test stuff</li>
-    <li class="fragment">It makes blockspace more efficient, because not all teams can/want to have a full block every 6/12 seconds.</li>
-</ul>
-
----
-
-# Treasury
-
-<ul>
-    <li class="fragment">The treasury is an on-chain fund that holds DOT token and is governed by all token holders of the network.</li>
-    <li class="fragment">Those funds come from:</li>
-    <ul>
-        <li class="fragment">Transactions</li>
-        <li class="fragment">Slashes</li>
-        <li class="fragment">Staking inefficiencies (deviations from optimal staking rate)</li>
-    </ul>
-    <li class="fragment">Through governance, everybody can submit proposals to initiate treasury spending.</li>
-    <li class="fragment">It currently holds around 46M DOT.</li>
-    <li class="fragment">Spending is incentivized by a burn mechanism (1% every 26 days).</li>
-</ul>
-
----
-
-## Treasury as DAO
-
-<ul>
-    <li class="fragment">A DAO (decentralized autonomous organization) that has access to funds and can make funding decisions directed by the collective (that have vested interest in the network).</li>
-    <li class="fragment">This has huge potential that might not yet have been fully recognized by the people.</li>
-    <li class="fragment">This provides the chain the power to fund its own existence and improves the utility in the future. It will pay…</li>
-    <ul>
-        <li class="fragment">… <strong>core developers</strong> to improve the protocol.</li>
-        <li class="fragment">… <strong>researchers</strong> to explore new directions, solve problems and conduct studies that are beneficial for the network.</li>
-        <li class="fragment">… for campaigns <strong>educating people</strong> about the protocol.</li>
-        <li class="fragment">… for <strong>systems-parachains</strong> (development & collators).</li>
-    </ul>
-    <li class="fragment">A truly decentralized and self-sustaining organization.</li>
-</ul>
-
----
-
-# How does it all fit together?
-
----
-
-<div style="display: flex; justify-content: center; align-items: center;">
-    <img src="./img/Polkadot-Economics-Cycle.svg" style="width: 1200px;" />
-</div>
-
----
-
-## Takeaways
-
-<ul>
-    <li class="fragment">Polkadot is a system that offers shared security and cross-chain messaging.</li>
-    <li class="fragment">Security scales, i.e., it takes less stake to secure 100 parachains than 100 individual chains.</li>
-    <li class="fragment">The DOT token captures the utility that the parachains provide and converts it to security.</li>
-    <li class="fragment">The slot mechanics (renewal, auctions) creates a market where parachains need to outcompete opportunity costs to be sustainable (i.e., they need to be useful).</li>
-    <li class="fragment">Polkadot is a DAO that will be able to fund its own preservation and evolution.</li>
-    <li class="fragment">There are many changes to come with Polkadot 2.0 creating a much more agile system.</li>
-</ul>
-
----
-
-## Further Resources
-
-- [Agile Coretime RFC](https://github.com/polkadot-fellows/RFCs/pull/1)
-- [Discussion on Changing Inflation Model](https://forum.polkadot.network/t/adjusting-the-current-inflation-model-to-sustain-treasury-inflow/3301)
-- [Talk about Polkadot 2.0](https://www.youtube.com/watch?v=GIB1WeVuJD0)
-- [Nominating and Validator Selection On Polkadot](https://www.polkadot.network/blog/nominating-and-validator-selection-on-polkadot/)
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-
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----
-title: Game Theory Basics
-description: Game Theory Basics for web3 builders
-duration: 1 hour lesson + 2 hours activities
----
-
-# Game Theory Basics
-
-Notes:
-
-Game theory is a field of study at the intersection of mathematics and economics.
-It consider an economic system to be a game and people to be players.
-According to the rules of the game, it analyzes the players' best strategies and then uses this analysis to explain the observed behavior of the economic system.
-
-Game theory is an interesting an powerful tool, because it's fairly simple and intuitive, yet extremely powerful to make predictions.
-Hence, it's a good idea to learn game theoretical principles and keep them in the back of your mind when designing economic systems.
-
----
-
-# Outline
-
-<ul>
-    <li class="fragment">Lesson
-        <ul>
-            <li class="fragment">What is Game Theory?</li>
-            <li class="fragment">What is a Game?</li>
-            <li class="fragment">Types of Games</li>
-            <li class="fragment">Common Games</li>
-            <li class="fragment">Nash Equilibrium</li>
-            <li class="fragment">Equilibrium Selection</li>
-        </ul>
-    </li>
-    <li class="fragment">Workshop & Activities
-        <ul>
-            <li class="fragment">Discussions & more games</li>
-        </ul>
-    </li>
-</ul>
-
----
-
-## What is Game Theory?
-
-> Game theory studies strategic situations where the outcome for each participant or 'player' depends on the actions of all others. It formulates models to represent these scenarios and predicts the most likely or optimal outcomes.
-
-Notes:
-
-- Game theory is all about the power of incentives.
-- Helps you understand and design systems and guide behavior of participants.
-
----
-
-## Game Theory in Web3
-
-In the context of blockchains, game theoretic reasoning is used for <span style="font-style: italic;">modelling</span> and <span style="font-style: italic;">understanding</span>.
-
-Notes:
-
-- The term is heavily over-used.
-- 9/10 times people using the term they simply mean there is some economic structure behind their protocols.
-- Rarely real game theoretic analysis is done.
-
----
-
-## Modelling
-
-<ul>
-<li class="fragment"><strong>Tokenomics:</strong> Macroeconomic design of a token (inflation, utility, etc.).</li>
-<li class="fragment"><strong>Business Logic:</strong> Interaction of the token with different modules of a protocol.</li>
-<li class="fragment"><strong>Consensus:</strong> Providing sufficient incentives to guarantee that participating nodes agree on a distributed state of the network.</li>
-<li class="fragment"><strong>Collaboration:</strong> Nudging (aggregated) human behavior and their interaction with the protocol.</li>
-</ul>
-
----
-
-## Understanding
-
-<ul>
-<li class="fragment"><strong>Economics:</strong> Interaction between different protocols and how finite resources are allocated among all of them.</li>
-<li class="fragment"><strong>Security:</strong> Testing economic security of protocols against various types of attacks.</li>
-</ul>
-
----
-
-## History of Game Theory
-
-<ul>
-<li class="fragment">Early “game theoretic” considerations going back to ancient times.</li>
-<li class="fragment">“Game theoretic” research early 19th century, still relevant.</li>
-<li class="fragment">The systematic study of games with mathematically and logically sound frameworks started in the 20th century.</li>
-<li class="fragment">Modern game theory is used in economics, biology, sociology, political science, psychology, among others.</li>
-<li class="fragment">In economics, game theory is used to analyze many different strategic situations like auctions, industrial economics, and business administration.</li>
-</ul>
-
-Notes:
-
-- In Plato's texts, Socrates recalls the following considerations of a commentator of the Battle of Delium:
-  - An example is a soldier considering his options in battle: if his side is likely to win, his personal contribution might not be essential, but he risks injury or death.
-    If his side is likely to lose, his risk of injury or death increases, and his contribution becomes pointless.
-  - This reasoning might suggest the soldier is better off fleeing, regardless of the likely outcome of the battle.
-  - If all soldiers think this way, the battle is certain to be lost.
-  - The soldiers' anticipation of each other's reasoning can lead to a self-fulfilling prophecy: they might panic and retreat before the enemy even engages, resulting in a defeat.
-- Spanish conqueror Cortez, when landing in Mexico with a small force who had good reason to fear their capacity to repel attack from the far more numerous Aztecs, removed the risk that his troops might think their way into a retreat by burning the ships on which they had landed
-- Antoine Augustin Cournot, a french mathematician, already described a duopoly game with respective solution in 1844.
-  - We will see this later.
-- Examples:
-  - Biology: Animals fight for resources or are peaceful, why cooperation evolved
-  - Political science: Art of conflict, escalation and de-escalation between nations.
-
----
-
-## Game theory is <span style="font-style: italic;">abstract</span>
-
-<ul>
-<li class="fragment">Game theoretic models aim to get at the essence of a given strategic problem.</li>
-<li class="fragment">This often requires many simplifying assumptions.</li>
-<li class="fragment">Pro: <em>Abstraction</em> makes the problem amenable to analysis and helps to identify the key incentives at work.</li>
-<li class="fragment">Con: A certain lack of realism.</li>
-<li class="fragment">In any case: Modeling a strategic situation always entails a tradeoff between tractability and realism.</li>
-</ul>
-
-Notes:
-
-- Need to explain what we mean by lack of realism:
-- Often people have more choices than we model.
-- Often people take other things into consideration when making choices than the model allows.
-- Often people know more/less than we assume.
-- How to resolve the tradeoff between tractability and realism is often subjective and depends on the taste of the modeler.
-
----
-
-# What is a Game?
-
----
-
-## Definition: (Economic) Game
-
-<ul>
-<li class="fragment">A game is a strategic interaction among several players, that defines <em>common knowledge</em> about the following properties:</li>
-<li class="fragment">all the possible <em>actions</em> of the players</li>
-<li class="fragment">all the possible <em>outcomes</em></li>
-<li class="fragment">how each combination of actions affects the outcome</li>
-<li class="fragment">how the players value the different outcomes</li>
-</ul>
-
----
-
-## Definition: Common Knowledge
-
-<ul>
-<li class="fragment">An event $X$ is common knowledge if:</li>
-<ul>
-<li class="fragment">everyone knows $X$,</li>
-<li class="fragment">everyone knows that everyone knows $X$,</li>
-<li class="fragment">everyone knows that everyone knows that everyone knows $X$,</li>
-<li class="fragment">... and so on ad infinitum.</li>
-</ul>
-</ul>
-
----
-
-### Examples: Common Knowledge
-
-<pba-cols>
-<pba-col>
-
-##### Auctions
-
-- Actions: Bids.
-- Outcome: Winner and Payment.
-
-</pba-col>
-<pba-col>
-
-##### Price-competition<br />between firms
-
-- Actions: Price charged.
-- Outcome: Demand for each firm, profit of each firm.
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Crucial feature of a game: outcome not only depends on own actions but also on the actions of the other players.
-
----
-
-## Types of games
-
-Game theory distinguishes between:
-
-<ul>
-<li class="fragment">static & dynamic games</li>
-<li class="fragment">complete & incomplete information games</li>
-</ul>
-
----
-
-## Static and Dynamic Games
-
-|                  | Static Game                                     | Dynamic Game                                                                                           |
-| ---------------- | ----------------------------------------------- | ------------------------------------------------------------------------------------------------------ |
-| Definition       | All players take their actions at the same time | Players move sequentially and possibly multiple times, (at least partially) observing previous actions |
-| Simple Example   | Rock-Paper-Scissors                             | Tic-Tac-Toe                                                                                            |
-| Economic Example | Sealed-bid auction.                             | All bidders submit their bids simultaneously (in a sealed envelope).                                   |
-|                  | English auction.                                | Auctioneer publicly raises price if at least one bidder accepts the price.                             |
-| Representation   | Payoff Matrix                                   | Decision Tree                                                                                          |
-
-Notes:
-
-- Also referred to as simultaneous or sequential games
-
----
-
-## Completeness of Information in Games
-
-|                       | Game of Complete Information                          | Game of Incomplete Information                             |
-| --------------------- | ----------------------------------------------------- | ---------------------------------------------------------- |
-| Information available | All information relevant to decision-making is known. | Not all information relevant to decision-making is known.  |
-| Simple Example        | Chess                                                 | Poker                                                      |
-| Economic Example      | Sealed auction for seized Bitcoin.                    | Used-car market: the resale value of a used car is opaque. |
-
-Notes:
-
-- There is also the notion of perfect and imperfect information which we should skip here.
-  More info: <https://economics.stackexchange.com/questions/13292/imperfect-vs-incomplete-information>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Quiz
-
----
-
-### Three firms want to hire an engineer...
-
-<pba-cols>
-<pba-col>
-
-- The engineer brings added value to each firm of 300,000 USD per year.
-- The payoff of the firm is known by everyone to be 300,000 USD minus the salary.
-- The payoff to the engineer is salary minus cost of working, which is known to everyone.
-- All firms make a salary offer at the same time.
-
-</pba-col>
-<pba-col>
-
-### Quiz Questions:
-
-1. Is this game static or dynamic?
-   What would need to change in the description of the game such that it would fall in the other category?
-1. Is this game of complete or incomplete information?
-   What would need to change in the description of the game such that it would fall in the other category?
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-1. The game is static.
-   For it to be dynamic, firms would need to make offers sequentially, _knowing what the firms before had offered_.
-
-2. The game is of complete information.
-   To make information incomplete, we would need to have that the value of hiring the engineer differs between firms and is unknown between firms.
-   Or that the cost of working for the engineer is not known to the firms.
-   The point is that we need to have uncertainty over payoffs.
-
-- This lesson focuses on static games of complete information.
-- When we look at auctions in lesson Price finding mechanisms, we will also consider games of incomplete information, both dynamic and static.
-
----
-
-## Utility
-
-<ul>
-    <li class="fragment">Core concept of Game Theory.</li>
-    <li class="fragment">Can transform any outcome to some value that is comparable.
-        <ul>
-            <li class="fragment">For example: What is better? Scenario A: Going for a vacation to France and drink Wine, or Scenario B: going to Germany and drink Beer?</li>
-            <li class="fragment">Those dimensions are only comparable if we give both some value like U(A) = 5, U(B) = 3.</li>
-        </ul>
-    </li>
-    <li class="fragment">Essential assumption: Agents are utility maximizers.</li>
-    <li class="fragment">Monetary payouts can also be transformed to utility.
-        <ul>
-            <li class="fragment">Simplest assumption U(x) = x.</li>
-            <li class="fragment">But that is likely not true in reality.</li>
-        </ul>
-    </li>
-    <li class="fragment">Most things have <strong>diminishing rates of returns</strong>.</li>
-</ul>
-
-Notes:
-
-- Expected Utility is the average utility we get from comparing several outcomes and weigh them with the probability they occur.
-- In the following, we won't need that, because either we deal with money or other dimensions that are comparable.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Common Games
-
----
-
-## Prisoners' Dilemma
-
-A fundamental problem:
-
-> Even though everyone knows there is a socially optimal course of actions, no one will take it because they are rational utility maximizers.
-
-It's a static game of complete information.
-
-Notes:
-
-One of the most famous games studied in game theory.
-
-- Static because both players take their action at the same time.
-- Complete because everybody is aware of all the payouts.
-
----
-
-## Bonnie and Clyde
-
-Bonnie and Clyde are accused of robbing two banks:
-
-<ul>
-<li class="fragment">The evidence for the first robbery is overwhelming and will certainly lead to a conviction with two years of jail.</li>
-<li class="fragment">The evidence for the second robbery is not sufficient and they will be convicted only if at least one of them confesses to it.</li>
-</ul>
-
----
-
-## Bonnie and Clyde
-
-In the interrogation they both are offered the following:
-
-<ul>
-<li class="fragment">If you both confess you both go to jail for 4 years.</li>
-<li class="fragment">If you do not confess but your partner does, you go to jail for 5 years: 1 extra year for obstruction of justice.</li>
-<li class="fragment">However, if you confess but your partner does not, we reduce your jail time to one year.</li>
-</ul>
-
-Notes:
-
-They are interrogated in different rooms, apart from each other.
-
----
-
-## Bonnie and Clyde
-
-- **Cooperate** ($C$) with each other and not say anything
-- **Defect** ($D$) and confess their crime
-
-<img rounded style="width: 650px; margin-right: 150px;" src="./img/Bonnie-clyde-1.png" />
-
-Notes:
-
-- They can either cooperate or defect
-- First payoff is Clyde, second is Bonnie
-
----
-
-## Bonnie and Clyde
-
-<img rounded style="width: 800px; margin-right: 250px;" src="./img/Bonnie-clyde-2.png" />
-
-Choosing D is a <span style="font-style: italic;">dominant strategy</span>: a strategy that is always optimal for a player, regardless of what the other players do.
-
-Notes:
-
-No matter what Clyde does, D is always the best choice.
-So, they end up both defecting, resulting in 4 years each.
-It would be in their best interest to cooperate and not to say anything.
-This would minimize the total jail time for the two.
-However, both Bonnie and Clyde are rational utility maximizers.
-So, they end up in a situation where they not only fare worse _individually_ (4 instead of 2) but also _jointly_ (the total jail time is 8 years rather than 4 years).
-
----
-
-## Nash-Equilibrium
-
-<ul>
-<li class="fragment">Fundamental concept in Game Theory</li>
-<li class="fragment">A NE is a set of strategies, one for each player, such that no player can unilaterally improve their outcome by changing their strategy, assuming that the other player's strategy remains the same.</li>
-<li class="fragment">In the Prisoner's Dilemma, D/D is the only NE.</li>
-</ul>
-
----
-
-## Prisoners' Dilemma IRL
-
-<ul>
-<li class="fragment"><strong>Nuclear Arms Race:</strong> <a href="https://www.history.com/topics/cold-war/arms-race">NATO and Russia</a> prefer no arms race to an arms race. Yet, having some arms is preferable to having no arms, irrespective of whether the other one is armed.</li>
-<li class="fragment"><strong>OPEC:</strong> <a href="https://www.opec.org/opec_web/en/">Limiting oil supply</a> is in the best interest of all. However, given the high price that thus results, everyone has an incentive to increase individual oil supply to maximize profits.</li>
-</ul>
-
----
-
-Notes:
-
-OPEC: Organization of the Petroleum Exporting Countries.
-It is something like a cartel that agree on limiting the global oil production and keep the oil price artificially high.
-
-OPEC and Cartels generally seems to overcome the Prisoners' Dilemma...
-More on that later.
-
----
-
-## Ultimatum Game
-
-<ul>
-    <li class="fragment">We played it before.</li>
-    <li class="fragment">Sequential game.</li>
-    <li class="fragment">The Nash Equilibrium can be reasoned by <strong>backwards induction.</strong></li>
-    <li class="fragment">The proposer has the following considerations:
-    <ul>
-        <li class="fragment">What would the recipient accept?</li>
-        <li class="fragment">Answer: every payoff (larger than 0).</li>
-        <li class="fragment">Therefore, I should offer, since I want to maximize my payout, something equal or slightly higher than 0.</li>
-    </ul>
-    </li>
-    <li class="fragment">That means, the proposer offering something small and the recipient always accepting is the only NE.</li>
-</ul>
-
-Notes:
-
-- We saw that empirically that is not the case.
-- Fairness concerns are too strong in that setting.
-
----
-
-## Coordination Game
-
-<ul>
-<li class="fragment">The prediction of play in the Prisoner's Dilemma was easy: both will defect.
-  <ul>
-  <li class="fragment">This is the optimal thing to do no matter what the other player does.</li>
-  </ul>
-</li>
-<li class="fragment">In other games, predictions of play are not so clear.
-  <ul>
-  <li class="fragment">One instance is the coordination game.</li>
-  </ul>
-</li>
-</ul>
-
----
-
-## Coordination Game
-
-> A coordination game is a type of static game in which a player will earn a higher payoff when they select the same course of action as another player.
-
----
-
-## Coordination Game Example
-
-<pba-cols>
-<pba-col>
-
-- Choose $L$ or $R$.
-- The numbers represent the payoffs a player receives.
-- The players only obtain utility if they coordinate their actions.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="width: 550px;" src="./img/Players.png" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Examples:
-
-- Driving on the right/left side of the road.
-- Money adoption.
-- Standard adoption.
-
----
-
-## Coordination Game Example
-
-<pba-cols>
-<pba-col>
-
-- The coordination game has two outcomes $(L,L)$ and $(R,R)$ that stand out.
-- Clearly, if the other player chooses $L$ ($R$), then it is optimal for the other to do so also.
-- So, in the outcomes $(L,L)$ and $(R,R)$ the players choose mutually optimal actions.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="width: 550px;" src="./img/Players.png" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- That is, for both players it holds:
-  - Playing $L$ is a _best response_ to the other player playing $L$.
-  - Playing $R$ is a _best response_ to the other player playing $R$.
-
----
-
-## Coordination Game Example
-
-<pba-cols>
-<pba-col>
-
-- Both $(L,L)$ and $(R,R)$ are instances of Nash equilibrium.
-- By their very nature, coordination games always have multiple equilibria.
-- The outcome $(D,D)$ in the Prisoner's dilemma is the unique Nash equilibrium.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="width: 550px;" src="./img/Players.png" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Nash equilibrium: If other players follows the recommended strategy, then the best response for you is to do the same.
-As the same logic is true for other players, it's reasonable to assume that everybody will indeed follow the recommended strategy.
-
-However, a Nash equilibrium is a weaker notion than a dominant strategy, because if the other players don't follow the recommended strategy, it is not clear what your best response should be.
-
----
-
-## Equilibrium selection
-
-<ul>
-    <li class="fragment">So, which outcome does the theory of Nash equilibrium predict in the coordination game?</li>
-      <ul>
-      <li class="fragment">None? Both?</li>
-      </ul>
-    <li class="fragment">Sometimes people switch between equilibria (if they are made to)...</li>
-</ul>
-<div class="fragment">
-    <img rounded style="width: 550px;" src="./img/sweden-1967.jpg" /><br />
-    <p>Sweden, 1967.</p>
-</div>
-
-Notes:
-
-- The NE does not predict any outcome.
-- Sweden switched from left-side driving to right-side.
-
----
-
-## Schelling Points
-
-<ul>
-<li class="fragment">Nash equilibrium <span style="font-style: italic;">does not</span> predict which strategies the players actually take.</li>
-<li class="fragment">This is especially pronounced in games with multiple equilibria (e.g., coordination games).</li>
-<li class="fragment">There are theories that offer insights into which strategies players actually take.</li>
-</ul>
-
-Notes:
-
-- In the 1950s American economist Thomas Schelling ran a couple of informal experiments in which he asked his students (quote on slide)
-
----
-
-## Schelling Points
-
-> If you are to meet a stranger in New York City, but you cannot communicate with the person, then when and where will you choose to meet?
-
-<ul>
-<li class="fragment">Literally any point and time is a Nash equilibrium...</li>
-<ul>
-<li class="fragment">However, most people responded: noon at (the information booth at) Grand Central Terminal.</li>
-</ul>
-<li class="fragment">Basic idea: in case of multiple equilibria, social norms may help to choose one.</li>
-</ul>
-
-Notes:
-
-- Imagine you are held in prison.
-- You and your significant other is asked to guess a number.
-- If you both guess the same number, you are set free.
-- You have the following options: 0.231, 1, or 0.823
-- Guessing both the same number is a NE every time.
-- It's highly likely you will walk free.
-
----
-
-# Summary (so far...)
-
-<ul>
-<li class="fragment">Typology of games: static/dynamic, complete/incomplete information.</li>
-<li class="fragment">Three canonical games: Prisoner's Dilemma, Ultimatum-, and Coordination Game.</li>
-<li class="fragment">The Prisoner's Dilemma has a unique Nash equilibrium, which is dominant, whereas the Coordination game has two Nash equilibria.</li>
-<li class="fragment">To select among multiple equilibria, the concept of a <span style="font-style: italic;">Schelling Point</span> is sometimes used.</li>
-</ul>
-
----
-
-## Why are theories of equilibrium important?
-
-<ul>
-<li class="fragment">Nash Equilibria are used to predict the behavior of others in a closed system.</li>
-<li class="fragment">If you can identify a unique Nash Equilibrium or the Schelling point in a system, you have a strong prediction of user behavior.</li>
-<li class="fragment">So, you can begin to drive user behavior by designing incentives accordingly.</li>
-</ul>
-
----
-
-## Public Goods
-
-<ul>
-<li class="fragment"><strong>Non-excludable</strong> No-one can be excluded from consumption</li>
-<li class="fragment"><strong>Non-rivalrous</strong> My consumption does not affect yours</li>
-<li class="fragment">e.g., fireworks, street-lighting.</li>
-</ul>
-
-Notes:
-
-- We will now talk about public goods and common goods, which are goods enjoyed by everyone.
-- This is, of course, a very important and very tricky class of goods in a collective.
-
----
-
-## Common Goods
-
-<ul>
-<li class="fragment"><strong>Non-excludable</strong> No-one can be excluded from consumption</li>
-<li class="fragment"><strong>Rivalrous</strong> My consumption reduces your possibility to consume</li>
-<li class="fragment">i.e., a public park, an office coffee machine.</li>
-</ul>
-
-Notes:
-
-- Recall: Public good was _non_-rivalrous.
-
-Examples:
-
-- Public park: anyone can go; too many people spoil the experience or kills the grass.
-- Coffee machine in the office: anyone can use it; too many users may cause congestion or the amount of coffee may be limited.
-
----
-
-## Public vs.
-
-<ul>
-<li class="fragment">Main difference is that in a <span style="font-style: italic;">common good</span> your consumption reduces the value of the good to others.</li>
-<li class="fragment">This is called a <span style="font-style: italic;">consumption externality</span> that you impose on others (and others impose on you.)</li>
-<li class="fragment"> The <span style="font-style: italic;">tragedy of the commons</span> is that, because you do not take this externality into account, consumption is higher than would be socially optimal. </li>
-</ul>
-
----
-
-## Stylized Public Good Game:
-
-<ul>
-<li class="fragment">$N$ players have 10 US dollars each, say, $N=4$.</li>
-<li class="fragment">Each player can choose how much to place into a project.</li>
-<li class="fragment">Funds in the project are magically multiplied by a factor $\alpha$, say, $\alpha=2$.</li>
-<li class="fragment">Finally, the funds in the project are split equally among all players.</li>
-<ul>
-  <li class="fragment">What would be best for the individual?</li>
-  <li class="fragment">What would be best for the collective?</li>
-<ul>
-</ul>
-
-Notes:
-
-- As long as $\alpha>1$, it's best for the collective to contribute as much money as possible, because the money in the project increases magically, so we end up with more money that we started with.
-- However, the problem is that everyone benefits from the project funds regardless of their individual contribution (it is a common good). If a player decreases their initial contribution by one dollar, their individual payoff decreases by $\alpha/N$ dollars, so as long as $\alpha<N$, it is best for each individual to contribute zero.
-- As a result, we can expect that no one will contribute anything, and the money-multiplying powers of the project will be unused. This opportunity cost is a tragedy of the commons.
-- Finally, if $\alpha\geq N$ then it would be individually better to contribute everything, and we would not have a tragedy of the commons.
-
----
-
-## Overfishing
-
-<ul>
-<li class="fragment">Fishing gives private benefit but might destroy the broader ecosystem, which has its own value for everyone (e.g., due to tourism).</li>
-<li class="fragment">Because individual fishermen do not pay for the damage they cause to the broader ecosystem, they will fish too much.</li>
-</ul>
-
----
-
-## Air pollution
-
-<ul>
-<li class="fragment">Producing a good yields private profit but reduces air quality for everyone.</li>
-<li class="fragment">Because there is no price attached to air quality, the firms do not have to pay for its reduction and, hence, will produce too much.</li>
-</ul>
-
----
-
-## But...
-
-<ul>
-<li class="fragment">There should be fishing/production/mining! After all, there are always benefits to these activities.</li>
-<li class="fragment">The tragedy of the commons is that the externality is not priced into these activities, driving them to inefficiently high levels.</li>
-</ul>
-
-Notes:
-
-To be precise, in the last example the so-called "tragedy" is not that producing a good leads to air pollution; after all, this may be unavoidable if we want to consume the good.
-The tragedy is that even if we agree on the level of production and air pollution that is economically ideal for the collective, we will end up with more pollution.
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-# Break (10 minutes)
-
-Notes:
-
-- Next up class activities.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Open Source
-
-> Providing open-source software is like contributing to a public good and the community will therefore sooner or later collapse!
-
-Notes:
-
-- Why it might not fail:
-  - Other incentives:
-    - Intrinsic motivation
-    - Reputation concerns (your github history is part of your CV)
-    - Reciprocity
-    - Direct benefit: Some contributors also use the software and benefit from improvements.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Design a 2x2 game
-
-> Jack and Christine are rivals and keep taunting each other in front of others.
-> At one time, Jack challenges Christine to a game of chicken.
-> He proposes that they both get in their cars and drive towards each other on a road.
-> In the middle of the distance between each other, there is a small bridge with a single lane.
-> Whoever swerves away before the bridge <span style="font-style: italic;">chickened out</span>.
-> If both keep straight, there is no way to avoid a strong collision between the two cars.
-> All friends will be present to see the result.
-
-Design this game in a 2x2 matrix and assign payoffs to the different outcomes.
-
-Notes:
-
-- Need a white board!
-- Give Class about 5 minuets to discuss in small groups on this
-- Then have 10 minutes to ask the class you solve the 2x2 matrix and discuss (on next slide).
-
----
-
-## Design a 2x2 game
-
-- What is/are the Nash Equilibrium/Equilibria here?
-- Which type of games does this remind you of?
-- How would you translate this game to real scenarios?
-
-Notes:
-
-- Game of chicken or Hawk-Dove Game
-- "Anti-Coordination Game" with the tension between competition and mutual benefit of compromise.
-- Real-world situations of conflict, where both would prefer not to fight but would actually like to intimidate, leading to a real conflict.
-- Two businesses would be better off not to engage in price war, but it would be good to be the only one to reduce the price to grab some market share.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Workshop: Games
-
-Notes:
-
-- roughly 70 minutes
-
----
-
-## Game 1: Guessing Game
-
-- We divide the classroom into three groups and play a guessing game.
-- The budget for this game is: $250.
-- The game is simple: each player enters a number from 1 to 100.
-- The player who guessed closest to 2/3 of the average number wins.
-- If multiple people win, the payoff is split equally.
-- The game is repeated for ten rounds.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Game 1: Questions?
-
-### Don't ask about strategies!
-
----
-
-## Game 1: Guessing Game
-
-Link will be distributed!
-
----
-
-## Game 1: Discussion
-
-- What number did you choose / what was your strategy?
-  (which group were you in?)
-- Did your strategy change over time?
-
-Notes:
-
-- A number above 2/3\*100 does not make sense
-- If everybody believes that, choosing a number above 2/3\*2/3\*100 does not make sense
-- ... it goes to 0
-- But does 0 Win? No!
-- **Question: Who made these considerations?**
-- Empirical results:
-  - Financial Times asked their readers to submit their solution: Winning number was 13 (~1500 participants)
-  - Other news magazine: ~3700 subjects, winning number 16.99, ~2800 subjects, winning number 14.7
-  - There were spikes at 33 (response to randomness), 22 (response to that), and 0 (rationality)
-- Level-k-thinking: 1 or 2 steps most prevalent, seldom more than that.
-- **Question: What would be the NE for multiplication of 1 of the mean?**
-  - It becomes a coordination game where all players choose the same value.
-
-## Game 1: Results!
-
----
-
-## Game 2: Prisoner's Dilemma
-
-- You play a Prisoner's Dilemma (groups of 2) over 10 rounds.
-- You will be randomly matched to another student in the class.
-- Budget for this game: $500
-- You have the option to chat between rounds.
-- Important: Keep the chat civil and do not reveal any identifying information about yourself.
-- We will read the chat.
-
----
-
-## Game 2: Payoffs
-
-|           |             | **_The other participant_** |                        |
-| --------- | ----------- | --------------------------- | ---------------------- |
-|           |             | _Cooperate_                 | _Defect_               |
-| **_You_** | _Cooperate_ | 200 points, 200 points      | 0 points, 300 points   |
-|           | _Defect_    | 300 points, 0 points        | 100 points, 100 points |
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Game 2: Questions?
-
----
-
-## Game 2: Let's go!
-
-Link will be distributed!
-
----
-
-## Game 2: Results!
-
----
-
-## Game 3: Public Good Game
-
-- We will play a public good game as presented in the lesson.
-- Budget for this game: $500
-- Groups of 4 over 10 periods.
-- Money in the project is multiplied by factor $1.6$.
-- With one additional mechanism: After each round each player sees the contributions of the other players and can decide to deduct points from them (at own costs).
-
----
-
-## Game 3: Instructions
-
-<img rounded style="width: 1000px;" src="./img/pgg-instructions.png" />
-
----
-
-## Game 3: Contribution
-
-<img rounded style="width: 1000px;" src="./img/pgg-contribution.png" />
-
----
-
-## Game 3: Punishment
-
-<img rounded style="width: 900px;" src="./img/pgg-punishment.png" />
-
----
-
-## Game 3: Payout
-
-<img rounded style="width: 1000px;" src="./img/pgg-result.png" />
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Game 3: Questions?
-
----
-
-## Game 3: Let's go!
-
-Link will be distributed!
-
----
-
-## Game 3: Discussion
-
-- What was your strategy?
-- Were your groups able to sustain cooperation?
-- Did you cooperate?
-- Did you punish?
-
-Notes:
-
-- Additional free rider problem: Punishment was fixed to 100% of the other's points.
-  That means, it was better to hope for other players to punish a player.
-- They cooperate maybe because they did not understand the game.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Game 3: Results!
-
----
-
-## Game 3: Discussion
-
-<ul>
-    <li class="fragment">How could we characterize players to types?
-     <ul>
-            <li class="fragment">Freerider</li>
-            <li class="fragment">Cooperators</li>
-            <li class="fragment">Altruists</li>
-        </ul>
-    <li class="fragment">What do you think happens when playing this ...
-        <ul>
-            <li class="fragment">... for one round?</li>
-            <li class="fragment">... for many rounds?</li>
-            <li class="fragment">... when allowing for communication?</li>
-            <li class="fragment">... with different group sizes?</li>
-        </ul>
-    </li>
-</ul>
-
-Notes:
-
-What about empirical evidence?
-
-- One Round: Little contribution.
-- Many Rounds: Some little contribution but quickly to 0.
-- Some longer and stronger contribution but eventually going to 0 quickly
-- Different group sizes: Larger groups are more prone to freeriding, i.e., cooperation collapses more quickly.
-- **Question: How can we distinguish freerider from those that only freeride because they expect others to freeride?**
-  - Answer: Ask them to provide a "conditional cooperation table" - i.e., they should state how much they contribute given other's /(average) contributions.
-  - Real freeriders have 0 even if others contribute.
-
----
-
-## Summary
-
-- the basics of game theoretic concepts.
-- different types of games.
-- how games can be modeled.
-- how to apply game theoretic thinking in our decision making in certain games.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
----
-
-## Further Reading
-
-- [Comprehensive introduction to Game Theory](https://plato.stanford.edu/entries/game-theory/)
diff --git a/content/economics/index.md b/content/economics/index.md
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-# 🪙 Economics and Game Theory
-
-_Applied_ economics and game theory fundamental to the architecture and operation of web3 applications.
-
-## Learning Outcomes
-
-Completing this module will enable you to:
-
-- Understand and discuss the basic principles of economics, including the influence of incentives on human behavior, supply and demand, the value of time, and the role of prices in allocating resources.
-- Analyze and comprehend the principles of game theory, including strategic games, Nash equilibrium, and the role of incentives in shaping outcomes.
-- Understand and apply the concepts of price discovery mechanisms and their implications in various market settings.
-- Understand the principles of collective decision-making, including voting systems, group decision-making processes, and the role of consensus in collective decisions.
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-# Price Finding Mechanisms
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Price Finding Mechanisms
-description: Auction Basics for web3 builders
-duration: 1 hour
----
-
-# Price Finding Mechanisms
-
----
-
-## Introduction
-
-- A central topic of economics is _price finding_ in markets.
-- How does a buyer and a seller agree on the price of a good?
-
----
-
-## Supply / demand for BIG markets
-
-<img rounded style="width: 800px; margin-right: 200px;" src="../basics/img/supply-and-demand.png" />
-
-Notes:
-
-- As we saw yesterday, a market price must balance supply and demand.
-- Demand: number of items bought by consumers at a given price.
-- Supply: number of items produced and sold at a given price.
-
----
-
-## Supply-demand for BIG markets
-
-- Supply-demand model works well for _big_ markets.
-- We have lots of buyers, sellers, lots of info.
-- Predictable _market price_, balancing supply and demand.
-- Only sensible price at which a buyer and seller can trade.
-
-Notes:
-
-- When a particular good has a large number of buyers and sellers, and we have a well established market with lots of real-life trading data, we can develop a supply-demand model.
-- It allows us to accurately predict the price at which the market will converge to for a good, which is the point at which supply and demand balance out.
-- It only makes sense to trade at market price: if lower, the seller can easily find another buyer willing to pay more, if higher, the buyer can easily find another seller willing to charge less.
-
----
-
-## What about _difficult_ markets?
-
-<img rounded style="width: 900px;" src="./img/auction-platform.png" />
-
-Notes:
-
-Image source: <https://funkypriceguide.com/collectible/512-gold-hopper-2018-sdcc-fundays/>
-
----
-
-## What about _difficult_ markets?
-
-Today we focus on markets with few buyers or sellers,
-few trades, or non-standardized goods.
-
-<pba-flex center>
-
-- Gov't sells radio frequencies to broadcasters.
-- A painting by a famous artist trades hands.
-- An oil well goes on sale with unknown amount of oil.
-
-</pba-flex>
-
-Notes:
-
-- The supply-demand model does not work in these examples
-- First example: there is a single buyer
-- Second example: very few buyers and sellers, trades are very infrequent, and goods are not standardized
-- Third example: not enough public data about the good.
-- In second and third cases, buyers may have wildly different personal valuations of the good.
-- A standardized good could be a liter of milk.
-  A less standardized good is a wedding ring, or a painting
-
----
-
-## A simple model
-
-<pba-flex center>
-
-- Selena wants to sell one item of a good.
-- Two buyers, Alice and Bob.
-- Each buyer has a secret _valuation_ $v_A$ and $v_B$:<br />
-  how much they are willing to pay for the item.
-
-</pba-flex>
-
-How does Selena _optimally_ sell the item?
-
-Notes:
-
-- We consider the limit case of one single seller and two buyers, to keep things simple.
-- Throughout the talk we assume that a buyer will purchase the item if the price is below or equal to their valuation.
-
----
-
-## Let's assume...
-
-<pba-flex center>
-
-- All of Selena's income is profit.
-- Alice and Bob each have random valuations between 0 and 1.
-- The valuations are secret but their distribution is well-known.
-
-</pba-flex>
-
-Notes:
-
-- We saw the notion of an abstraction already in game theory class: we lose a bit in realism, but gain in structure which allows us to make precise statements, and develop a richer theory.
-  The intuition and conclusions still apply in real life.
-- In particular, we are assuming that each of the three characters has a certain amount of information about the valuations of the other players, namely the distribution they are sampled from, and they can use this info to strategize their actions.
-- Assuming that each valuation $v_i$ follows a uniform distribution between 0 and 1 simplifies Selena's life, because she knows that for any value $x\in \[0,1\]$, the probability that a bidder's valuation is below $x$ is exactly $x$, i.e., $P\[v_i\leq x\]=x$.
-- However, assuming a uniform distribution is just for pedagogical reasons: most results in auction theory can be extended to more general distributions.
-
----
-
-## Price posting
-
-- Simplest solution: Selena posts a price $p$, sells item to first taker.
-- What is her _optimal price_ $p$?
-  One maximizing her _expected revenue_.
-- Expected revenue: price $\times$ prob. of making a sale.
-- For price $p$, prob. of making a sale is $(1-p^2)$.
-- Hence her expected revenue is $p \cdot ( 1-p^2)$.
-
-Notes:
-
-- If both buyers accept the posted price, we assume the firm selects a random buyer to trade with.
-- The proof of this and all other math formulas can be found in the slides, for anyone interested.
-- Assuming that 100% of the sale price is profit for the seller, this profit is
-
-  - $p$ in case of selling, $0$ otherwise, where
-  - $(1-p^2)$ is the probability of selling the item.
-  - To see this probability, consider conversely that the probability that none of the buyers accepts the price must be $p^2$, because each valuation must be below $p$, and these are two individual events each happening with probability $p$ (recall: valuations are uniformly distributed between 0 and 1).
-
-- $Pr\{v_i \leq x\}$ is the probability that the randomly drawn value of valuation $v_i$ is below $x$.
-- Independent values will be important: when is this (not) a sensible assumption?
-  (Example: oil drilling rights auctions, ...)
-- Uniform distribution is just for pedagogical reasons; standard model allows for more general distributions.
-
----
-
-## Price posting
-
-<pba-cols>
-<pba-col>
-
-- At the optimum point, expected revenue is $\approx 0.38$.
-- We will see that **an auction can do better**.
-
-</pba-col>
-
-<pba-col>
-
-<img rounded style="width: 600px; margin-right: 10px;" src="./img/price-posting.png" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- Prices, valuations, and revenue are given in the same currency unit, say, USD.
-- How do we maximize the expected revenue function $f(p)=p ( 1-p^2)$?
-  The function has a unique peak, so at the maximum, the first derivative must be zero.
-- The function is maximized for a $p$ satisfying $$ f'(p)=1-p^2 - 2p^2 = 0 \implies p = \sqrt{1/3}.$$
-- Expected revenue is then $f(\sqrt{1/3})=\frac{2}{3}\sqrt{1/3}\approx 0.38.$
-
----
-
-## Auctions
-
-<img rounded style="width: 500px;" src="./img/auctioneer.gif" />
-
----
-
-## Lesson summary
-
-<pba-flex center>
-
-- Auctions can be superior to posting a price.
-- We discuss four important auction formats.
-- How to make buyers reveal their secret valuations.
-- Bid shilling.
-- The revenue-equivalence theorem.
-- Guides on what auction format to use in practice.
-
-</pba-flex>
-
-Notes:
-
-- Auctions can provide more revenue to the seller, as we will see.
-- In a market with a posted price, buyers never need to reveal their valuation (i.e., how much they would actually be willing to pay for an item).
-  In auctions, the same is generally true, as they may bid values much lower than their valuations, but there is an auction format where they tend to bid their actual valuations (called truthful bidding).
-- There is a specific sense in which, in theory, all four auction formats provide the same revenue for Selena.
-- However, in practice, some formats may be better suited than others, and we will see some such examples.
-
----
-
-## Auctions
-
-- Alice and Bob (bidders) submit bids based on own valuations.
-- Selena (auctioneer) selects winner to allocate the item to.
-- The winner's payment is a function of the bids.
-
-_An auction is a competitive game for buyers, where the seller makes the rules._
-
-Notes:
-
-- Bidders submit bids to auctioneer, which are a declaration of how much they are willing to pay for the item.
-  In an ideal world, a bid equals the bidder's valuation (this is called a truthful bid), but of course depending on the bidder's strategy they may choose to underbid or overbid.
-- In this lesson we will have some fun analyzing the bidders' best strategies as well as the auctioneer's best strategies.
-- Both the winner and the winner's payment will dependent on the bids and the auction rules.
-  The payment cannot be higher than the winner's bid, but it could be lower.
-- Auctions yield a higher revenue because they create competition among buyers.
-
----
-
-## Auction formats
-
-<pba-flex center>
-
-1. There are two broad classes:
-   1. _Static Auctions:_ bidders submit their bids at the same time.
-   1. _Dynamic Auctions:_ bidders submit bids over time.
-
-- The difference is whether or not bidders can react to the bids of others and adjust their own.
-- Static auctions are also called _sealed-bid auctions_.
-
-</pba-flex>
-
-Notes:
-
-- In static auctions, bidders give their bids simultaneously and cannot change it later.
-- Static auctions are also called sealed-bid auctions, as many times in practice the bids are submitted in sealed envelopes to the auctioneer.
-
----
-
-## Auction formats
-
-Four auction formats we discuss today:
-
-<pba-flex center>
-
-- Static auctions
-  - with a first-price payment rule
-  - with a second-price payment rule
-- Dynamic Auctions
-  - with ascending price (a.k.a. English auctions)
-  - with descending price (a.k.a. Dutch auction)
-
-</pba-flex>
-
-Notes:
-
-- Example, Selena auctions off a painting.
-  Suppose in a static auction, Alice bids 1000 and Bob bids 2000.
-  In a first-price format, Bob wins and pays 2000.
-  In a second-price format, Bob still wins but only pays 1000.
-- The English format became popular in England.
-  Selena continuously raises the price as long as at least 2 bidders accept it.
-  As soon as only one bidder remains, they win and pay the current price.
-- The Dutch format became popular in the Netherlands, particularly in the tulip market.
-  Selena starts at a high price and continuously lowers it as long as there are no takers.
-  As soon as a bidder accepts the price, they win and pay the current price.
-- We are gonna analyze each of these four formats, and take the opportunity to discuss relevant notions in auction theory along the way.
-- For me, the second-price auction is the least intuitive format.
-  But it turns out to be one of the nicest and easiest to analyze, so we will start there.
-
----
-
-## Second-price auction
-
-- Why make the winner pay the second highest bid?
-- Least intuitive format, but strategically simplest for bidders.
-- Simply bid your valuation truthfully!
-- A bidder wants to maximize their _expected profit_:
-  - own valuation - price paid, in case they win
-  - zero, otherwise
-
-Notes:
-
-- Out of the four formats, we start our analysis with second-price static auctions, i.e., Alice and Bob give their bids in sealed envelopes to Selena, and she declares the winner to be the one with the highest bid, but the price to pay is only second highest bid.
-- To analyze the bidders' best strategy, we assume that each bidder wants to maximize their expected profit.
-  Again, this is a sensible but strong assumption, as they could have some other equally sensible objectives.
-  By the end of the lesson we will highlight how this assumption can be a bit unrealistic in practice.
-
----
-
-## Second-price auction
-
-- **Truthful equilibrium**: a _dominant strategy_ to bid truthfully.
-- **Dominant strategy**: outcome is at least as good as the outcome of any other strategy, _no matter what the other bidder bids_.
-
-<img rounded style="width: 1300px;" src="./img/second-price-auction.svg" />
-
-Notes:
-
-- We can immediately say that you should never overbid (i.e., bid above your valuation), because in that case your profit can only be zero (if you lose) or negative (if you win).
-  So the key question is whether you should ever underbid.
-- In the case that Bob's bid is higher than your valuation, bidding truthfully or underbidding both lead to losing and having a revenue of zero.
-- But if Bob's bid is lower than your valuation, any bid between these two values leads to you winning and having the same profit (namely the difference of these values), hence there is no gain in underbidding.
-  However if you underbid too much, you run the risk of losing and having zero profit.
-- Hence in both cases we see that underbidding does not increase your profit, and can only decrease your chance of winning.
-  So it is better to bid exactly your valuation.
-- The proof can be easily generalized to any number of bidders (to obtain that in a second-price auction, it is a dominant strategy for each bidder to bid truthfully.
-
-TIP: use arrow chars in unicode for style: <https://www.htmlsymbols.xyz/arrow-symbols>
-
----
-
-## Second-price auction
-
-**Expected revenue**
-
-- Selena's expected revenue is expected value of 2nd highest valuation.
-- For two independent variables uniformly sampled from $\[0,1\]$,
-  the expected value of the minimum is $1/3\approx 0.33$.
-- This is not quite as good as posting a price
-  (which provided expected revenue $0.38$).
-  Why not?
-
-Notes:
-
-- Let $F(x)$ be the cumulative density function (CDF) of the lowest of Alice and Bob's valuations, $\min\{v_A, v_B\}$, where $v_A$ and $v_B$ are independent variables sampled uniformly from $\[0,1\]$.
-- By definition, for any $x$ in $\[0,1\]$, $F(x)$ is the probability that the lower valuation is below $x$, or equivalently, $g(x):=1-F(x)$ is the probability that both valuations are above $x$; clearly $g(x)=(1-x)^2$, and hence $F(x)=1-(1-x)^2$.
-- From the CDF, we can compute the probability density function (PDF) by derivation: $f(x)=\frac{d}{dx}F(x)=2(1-x)$.
-- Finally, the expected value is computed from the PDF with the integral formula
-  $$\int_0^1 x\cdot f(x) dx = 2\int_0^1 (x-x^2)dx=2\cdot \left(\frac{1}{2}-\frac{1}{3}\right)=\frac{1}{3}.$$
-
----
-
-## Reserve price
-
-- Because the format we considered is not optimal for the auctioneer!
-- The optimal auction involves a _reserve price_ $r>0$:
-  - If no bid is above $r$, nobody wins.
-  - If one bid is above $r$, the payment is $r$.
-  - If both bids are above $r$, the payment is the second-highest bid.
-
----
-
-## Reserve price
-
-**Fact:** Under any reserve price $r$, it is still optimal to bid truthfully, and if Selena sets $r=0.5$, her expected revenue is $\approx 0.42$, so it is better than posted price (where expected revenue was $\approx 0.38$).
-
----
-
-## Reserve price
-
-<img rounded style="width: 1400px;" src="./img/reserve-price.svg" />
-
-Notes:
-
-- The proof idea is that if $r=0.5$, half of the time one valuation is above it and the other is below it, and the reserve price increases the paying price.
-  On the other hand, if both valuations are below $r$ then there is no sale, which decreases Selena's revenue, but this case only happens one quarter of the time.
-  Finally, if both valuations are above $r$, the presence of a reserve price does no affect the result.
-  Overall, there is a positive net gain in Selena's expected revenue.
-  Below we present the formal proof.
-- The probability that both valuations are below $r$ is $r^2$, the prob. that $r$ is in between the valuations is $2r(1-r)$, and the prob.that both valuations are above $r$ is $(1-r)^2$.
-  You can check that these probabilities sum up to one.
-- In the first case Selena's revenue is zero, and in the second case it is $r$.
-  Hence the expected revenue for the first two cases is $2r^2(1-r)$.
-- To compute the expected revenue of the third case, we simply copy the integral formula for the expected value (from a couple of slides ago), but we restrict the integration limits to $\[r, 1\\]$:
-  \begin{align}
-  \int_r^1 x\cdot f(x) dx &= 2\int_r^1 (x-x^2)dx\\
-  &=2\cdot \left\[\frac{x^2}{2}-\frac{x^3} {3}\right\\]\_r^1 \\&=\frac{1}{3} - r^2 + \frac{2}{3}r^3.
-  \end{align}
-- Putting all terms together, we obtain that the expected revenue is
-  $$R(r)=0+2r^2(1-r)+\left(\frac{1}{3} - r^2 + \frac{2}{3}r^3\right)=\frac{1}{3}+r^2-\frac{4}{3}r^3.$$
-- To maximize the auctioneer's expected revenue function $R(r)$ above:
-  - We evaluate the function at all the local extrema (minima and maxima).
-  - Since the function is continuous and differentiable, the local extrema are found at the borders $r=0$ and $r=1$, and at the roots of the derivative $R'(r)=2r-4r^2=0$.
-    These roots are $r=0$ and $r=1/2$.
-  - By inspecting all these points, we find that the global maximum is found at $r=1/2$, with a value of $R(1/2)=5/12\approx 0.42$.
-- Literature: Myerson, Roger B. "Optimal auction design." Mathematics of Operations Research 6, No. 1 (1981): 58-73.
-
----
-
-## English auction
-
-Recall the rules:
-
-<pba-flex center>
-
-- Selena continually raises the price.
-- At any price, you decide whether to stay or leave.
-- If you leave, you may not return.
-- If you are the last one in the auction you win<br />
-  and pay the price at which the second-to-last<br /> bidder left.
-
-</pba-flex>
-
-Notes:
-
-- Next we move to English auctions, which have a very similar analysis.
-- Notice it has a flavor of a second-price auction: the price you pay is decided by another bidder, not you.
-- In a sense, these two auction formats are strategically equivalent!
-
----
-
-## English auction
-
-- English auction is **strategically equivalent** to static second-price auction.
-- It is a dominant strategy to stay until the price reaches one's valuation.
-- The expected revenue for Selena is the also the same!
-- Consequently, these two formats are also **revenue equivalent**.
-
-Notes:
-
-- Why is staying until the price reaches your valuation a dominant strategy?
-  - If you leave you get zero utility.
-  - If you stay while the price is below your valuation, your eventual utility may be zero or positive, so there is no incentive to leave.
-  - If you stay while the price is above your valuation, your utility is zero or negative, so you should leave immediately.
-
----
-
-## Shill bidding
-
-- Second-price and English auctions popular among theorists, not so popular among practitioners.
-- One reason is that they are prone to _shill-bidding_: bidder that acts on behalf of the auctioneer to drive up the price.
-
-Notes:
-
-- Both second-price auctions and English auctions have the truthful bidding property, which is very satisfactory for theorists.
-  However, as you can probably tell, they are not so popular in practice.
-- A shill bidder has no intention of winning, but just increasing the price that the winner must pay.
-  They do it to benefit the auctioneer.
-- Shill bidding is frowned upon, sometimes illegal, but it is usually hard or impossible to prove and to prevent.
-
----
-
-## First-price auction
-
-<pba-flex center>
-
-- The winning bidder pays her bid.
-- Other rules same as in the second-price auction; i.e.,
-  - all bidders submit their bids simultaneously,
-  - the highest bid wins.
-
-</pba-flex>
-
-Notes:
-
-- New topic, time to wake up!
-- We move on to first-price auction, which as you recall, is a type of sealed auction.
-- Its analysis is more involved, and the resulting optimal bidding strategy is quite different from before.
-
----
-
-## First-price auction
-
-Bidding in the first-price auction is **not** truthful.
-
-- Bidding truthfully can never be optimal:
-  if you win, you earn nothing.
-- Underbidding is strictly better, you win sometimes
-  and when you do you have a positive utility.
-
----
-
-## First-price auction
-
-**Equilibrium strategy:** It is a _Nash equilibrium_ for each bidder to bid **half** their own valuation.
-
-_Nash equilibrium:_ A set of strategies, one per player, where no one has an incentive to change their strategy.
-
-Notes:
-
-- Recall Nash equilibrium we already covered.
-- A Nash equilibrium is a "recommended strategy per player", such that if you assume that the other bidder will follow their recommendation, then the best you can do is to follow yours.
-- As the same is true for the other players, it is indeed a reasonable assumption to think the other players will follow their recommendation.
-- However, if the other players picks an unexpected strategy, your recommended strategy may be suboptimal.
-  In this sense, a Nash equilibrium is a weaker concept than a dominant strategy, in which the strategy of the other players is irrelevant.
-
----
-
-## First-price auction
-
-**Intuition:** suppose you are Alice
-
-- If you bid 0, winning prob. is zero.
-- If you bid your valuation, profit is zero.
-- Hence, there is a sweet spot between 0 and your valuation
-  where your expected profit is maximal.
-- It turns out this is bidding half your valuation,
-  at which point you and Bob each wins _half of the time_.
-
-Notes:
-
-- Unfortunately, the full proof is outside the scope of the presentation, but we provide it here in the lesson notes.
-- Assume you are Alice, with valuation $v_A$ and bid $b_A$.
-- Assuming that Bob's bid $b_B$ equals half his valuation $v_B$, that $v_B$ is sampled uniformly at random between 0 and 1, and that your bid $b_A$ is at most $1/2$, your winning probability is:
-  \begin{align}
-  Pr\[winning\] &= Pr\[b_B\leq b_A\] \\
-  &= Pr\[v_B/2 \leq b_A\] \\
-  &= Pr\[v_B \leq 2b_A\] \\
-  &= 2b_A.
-  \end{align}
-- Your profit in case of winning is $(v_A-b_A)$, hence your expected profit is $2b_A(v_A-b_A)$.
-- It can be checked that this expression is maximized for $b_A=v_A/2$.
-- In summary, if Bob bids half his valuation, it is optimal for Alice to bid has her valuation, and vice versa.
-  Together we have a Nash equilibrium.
-
----
-
-## First-price auction
-
-**Expected revenue**
-
-- Reasonable to assume each bidder bids half their valuation.
-- Hence, Selena's revenue is $\frac{1}{2}\max\{v_A, v_B\}$.
-- The expected value of $\max\{v_A, v_B\}$ is $2/3$.
-- Hence, her expected revenue is $1/3$.
-
-The same as in second-price auction!
-
-Notes:
-
-- I find this result fascinating.
-  The optimal strategies are so different, but somehow the fact that you underbid is exactly compensated by the fact that you pay more when you win.
-- Is there a deeper connection going on here?
-  Or is it just a coincidence that the expected revenues are all the same so far?
-- Formal proof of the expected revenue: recall that the valuations $v_A$ and $v_B$ are assumed to be independent variables uniformly drawn from $\[0,1\]$.
-- The cumulative density function (CDF) of the higher valuation, $\max\{v_A, v_B\}$, is $F(x)=x^2$.
-  This is because $F(x)$ is lower than $x$ only if both valuations are below $x$, and these are two independent events each happening with probability $x$.
-- Then, the probability density function (PDF) is $f(x)=F'(x)=2x$.
-- And the formula for the expected value of $\max\{v_A, v_B\}$ is
-  $$R = \int\limits_0^1 x\cdot f(x)\mathrm d x = \int\limits_0^1 2x^2 \mathrm d v = \frac{2}{3}.$$
-
----
-
-## Revenue Equivalence
-
-**Fact:** When valuations are secret and independent,
-there is no reserve price, and item goes to highest bidder,
-then _all auction mechanisms_ are _revenue equivalent_.
-
-Notes:
-
-- This is a theorem established by Myerson in 1981.
-- Notice all auction formats are **not** strategically equivalent (namely, you should bid truthfully in some formats but not in others), yet they are still _revenue equivalent_ for the auctioneer.
-- This result is very surprising to me, and one of the coolest results in game theory.
-
----
-
-## Dutch auctions
-
-<pba-flex center>
-
-- Selena continually lowers the price.
-- As soon as a bidder accepts the price,<br />
-  they are declared winners and auction is over.
-- Winner pays the price they accepted.
-
-</pba-flex>
-
-Notes:
-
-- We finally say a few words about the fourth and last auction format.
-- Notice it has a flavor of a first-price auction: you pick the price you pay.
-  So you definitely **do not** want to bid truthfully, but rather underbid.
-
----
-
-## Dutch Auction
-
-Recall the rules:
-
-- The auctioneer continually lowers the price.
-- At any price, you can decide whether or not to accept the price.
-- If you are the first to accept the price, you win and pay the price you just accepted.
-
----
-
-## Dutch Auction
-
-- It turns out that the Dutch auction is strategically equivalent and revenue equivalent to the static first-price auction.
-- The price that you accept in the Dutch auction corresponds to the price that you'd bid in a static first-price auction.
-- The tradeoffs that the bidders face are very similar: take the current price or wait a bit at the risk of another bidder accepting first.
-  It is an equilibrium to wait till the price is half your valuation.
-
----
-
-## Recap
-
-<pba-cols>
-<pba-col>
-
-**Analyzed important auction formats:**
-
-- Static first-price auction.
-- Static second-price auction.
-- English auction.
-- Dutch auction.
-
-</pba-col>
-<pba-col>
-
-**Learned under standard assumptions:**
-
-- First-price and Dutch auctions are strategy equivalent.
-- Second-price and English auctions are strategy equivalent.
-- All four actions are revenue equivalent.
-- Having a reserve price increases the expected revenue,
-  and it beats posting a price.
-
-</pba-col>
-</pba-cols>
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-## Break (10 minutes)
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Discussion
-
----
-
-## Independence of valuations
-
-In our analysis, it was important to assume that
-bidders' valuations are independent from one another.
-
-_Can you think of examples where this assumption isn't sensible?_
-
----
-
-## Independence of valuations
-
-_Answer:_
-
-**Sensible:** - a piece of art, where the bidders are final clients.
-
-**Not sensible:** drilling rights to an oil well.
-Bidders will have similar estimates of amount of oil,
-hence valuations are highly correlated.
-
----
-
-## Common value auctions
-
-Special scenario: there is a unique valuation of item,
-but each bidder only has a private estimate of it.
-
-In these cases, it is observed that sealed-bid auctions
-tend to give higher revenue than dynamic auctions.
-
-_Why do you think this is the case?_
-
----
-
-## Common value auctions
-
-_The auction may be used as a means of gathering information from other participants to triangulate a price_
-
-_Answer_: In a dynamic auction, a bidder can use the bids of others as additional signals of the correct valuation.
-If bids so far seem high, my initial estimate must be low, and vice versa, so I can adjust my personal estimate.
-Hence estimates converge.
-
-In a static auction, there is no convergence of estimates, so it is more likely that some bidders keep unusually high estimates.
-As a result, there is a higher chance that the winner ends up paying more than the correct valuation.
-This is known as the _winner's curse_.
-
----
-
-## Equivalence of revenues
-
-It is observed in practice that first-price auctions lead to higher revenue than second-price auctions.
-
-This _violates_ the equivalence of revenues, so an assumption in our analysis fails consistently.
-
-_What do you think it is?_
-
----
-
-## Equivalence of revenues
-
-_Answer:_ **Risk aversion.** People prefer lower uncertainty games, even if this means lower expected profits.
-
-_Would you rather win a million dollars with a 50% chance, or 300 thousand with a 90% chance?_
-
-In Nash equilibrium analysis for first-price auctions, we claimed that if Bob bids half his valuation, then Alice should bid half hers, so each wins 50% of time.
-But we implicitly assumed that Alice is risk neutral.
-Yet she might prefer to bid more and win more often.
-
-Notes:
-
-- Of course, Bob may react the same way and also bid more in an attempt to bid more often.
-  As a result, they may still win about 50% of the time each, but both end up bidding too much due to their risk aversion.
-- In contrast, in our analysis for second-price auctions, the bidders' aversion to risk is not a factor.
-- Important: If you want to maximize the auctioneer's revenue and don't mind playing psychological games with the bidders, you should choose first price auctions over second-price auctions.
-
----
-
-## Front Running
-
-Computer systems may have _front runners_: special nodes can see an incoming bid, react by creating their own bid, and make it look like their bid was created first.
-
-If you run an auction on a system with front runners, which of the four auctions would you use?
-Why?
-
-Notes:
-
-- Front runners are a known problem in eBay, trading platforms, and blockchain networks, etc.
-- Front runners have a special, faster setup that allows them to see an incoming message from a bidder, react to it by creating their own message, and make their message get registered first in the system.
-
----
-
-## Front Running
-
-_Answer:_ Meet front runner _Fred_.
-
-In a Dutch auction, if Fred is a bidder he waits for first bidder to signal accepting the price, and Fred makes the signal first.
-He's guaranteed to win with least possible price.
-
-In second-price auction, if Fred is auctioneer he can shill bid successfully: when a highest bid arrives, he creates bid slightly under it and makes it appear as if it was created first.
-
----
-
-## Front Running
-
-_Answer:_ Meet front runner _Fred_.
-
-In a first-price auction, if Fred is bidder and if he can "open the seals" he can win by slightly outbidding highest bid.
-(Poor data privacy, a common issue in computer systems)
-
-Hence, it might be best to run an English auction.
-
----
-
-## Sniping
-
-In a dynamic auction with a fixed bidding time window, _sniping_ is placing a highest bid as late as possible, so other bidders can't react and overbid you.
-The practice leads to low revenue.
-Particularly bad when done by a front runner (microseconds).
-
-How to protect an auction from snipers?
-
-Notes:
-
-- eBay uses such types of auctions, and is infamous for having snipers.
-
----
-
-## Sniping
-
-_Answer:_ **candle auctions.**<br />
-Dynamic first-price auction with _random ending time._
-
-<img rounded style="width: 600px;" src="./img/candle-auction-photo.jpg" />
-
----
-
-## Sniping
-
-_Answer:_ **candle auctions.**<br />
-Dynamic first-price auction with _random ending time._
-
-- Similar to first-price auction
-- except that ending time is unpredictable.
-- At ending time, current highest bidder wins, pays own bid.
-- Sniping protection: the longer you wait to bid, the higher the chances the auction ends.
-
-Notes:
-
-- Fun fact: candle auctions were popular in England in the 17th and 18th centuries.
-- They would use a candle (hence the name).
-  When the flame extinguishes, the auction is over.
-- Fun fact: Polkadot implemented a candle auction for assigning block space to applications.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Workshop: Auction Games
-
----
-
-## NFT Auction
-
-- You have the chance to bid on one of 25 unique NFTs that are created by a professional artist.
-- Use your budget that you accumulated during the last Academy Games.
-- Everything that you will not use for bidding (or if your bid was lower than your budget), you will receive in cash at the end of the Academy.
-- 100% of the revenue of the auctions goes to the artist.
-- You are randomly assigned to one of three auction formats
-
----
-
-# The Artist & NFTs!
-
----
-
-## Jeremy Gluck (Nonceptualism)
-
-- Canadian Artist living in Great Britain.
-- Diverse Practice: Post-digital fine art in NFT, digital art, film, photography, sound and video art, installation, and performance.
-- Exhibitions: Works showcased offline in cities like London, Sydney, Bath, Anglesey, and Swansea, and online in various publications.
-- Art is exhibited in Tides Fine Art Gallery, Mumbles, Wales.
-
----
-
-<img rounded style="width:600px" src="./img/collection-preview.jpg" />
-
----
-
-### Format 1: Activity Rule Auction
-
-- The initial bidding phase lasts 30 seconds.
-- Every valid bid resets the timer.
-- You need to bid at least 30 cents more than the previous highest bid.
-- Whoever has the highest bid at the end, wins.
-  Winners pay their bids.
-
----
-
-### Format 2: Candle Auction
-
-- Auction Format from the 16th Century.
-- The auction lasts for exactly 4 minutes.
-- A “candle mechanism” randomly determines, after the auction, when the auction ended
-- Grace-period of 1 minute.
-- Candle Phase of 3 minutes.
-- Whoever had the highest bid when the auction actually ended, wins.
-
----
-
-### Format 3: Hard Close Auction
-
-- Similar to eBay auctions.
-- Auction lasts for 4 minutes.
-- Whoever has the highest bid at the end of the auction, wins.
-- Winners pay their bids.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Auction 2: Questions?
-
----
-
-## Auction 2: NFT Auction
-
-Link will be distributed!
-
----
-
-## Auction 2: Discussion
-
----
-
-## Auction 2: Results!
-
----
-
-## Further Reading
-
-Polkadot & Kusama Auctions<br />Data & Background information:
-
-<pba-flex center>
-
-- [Kusama Auctions 1-5](https://www.polkadot.network/blog/making-history-an-overview-of-the-first-five-parachain-slot-auctions-on-kusama/)
-- [Kusama Auctions 6-10](https://www.polkadot.network/blog/kusama-batch-2-auctions-report/)
-- [Polkadot Auctions 1-5](https://www.polkadot.network/blog/making-history-again-polkadot-auctions-1-5/)
-
-</pba-flex>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
----
-
-## Bonus Game: Dollar Auction
-
-<pba-flex center>
-
-- Each group of five players is bidding on a one dollar note.
-- Minimum bid is 5 cents, bid increments of 5 cents.
-- Auction lasts 90 seconds.
-- Highest bidder gets the prize.
-- **Both** highest and second highest bidders pay respective bids.
-
-</pba-flex>
-
-Notes:
-
-- Thought experiment designed by economist Martin Shubik.
-- Serves as analogy for war: it may be apparent for both sides that even winning the war won't make up for the losses, yet both sides are motivated to keep spending money on it.
-- You could get 1 dollar for 5 cents if no one else bids.
-- But if you end up second you have a loss.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Dollar Auction: Questions?
-
----
-
-# Dollar Auction
-
----
-
-## Discussion
-
-- Would you consider the auction paradoxical?
-- Did you catch yourself acting irrational?
-- Did you observe any phases in the game?
-- Why do you think the game could be considered an analogy for war?
-
----
-
-## Auction 1: Results!
diff --git a/content/frame/README.md b/content/frame/README.md
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-index.md
\ No newline at end of file
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-# Benchmarking Activity
-
-Practice with FRAME benchmarking.
-
-## 📥 Clone to start: <a target="_blank" href="https://github.com/Polkadot-Blockchain-Academy/frame-benchmarking-activity">Benchmarking Activity</a>
-
-See the README included in the repository for further instructions.
diff --git a/content/frame/_materials/proof-of-existence.md b/content/frame/_materials/proof-of-existence.md
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-# Proof of Existence Runtime
-
-Follow along the docs here: <https://docs.substrate.io/tutorials/build-application-logic/use-macros-in-a-custom-pallet/>
diff --git a/content/frame/benchmarking-1/page.md b/content/frame/benchmarking-1/page.md
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-# Benchmarking
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/benchmarking-1/slides.md b/content/frame/benchmarking-1/slides.md
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----
-title: FRAME Benchmarking 1
-description: How to benchmark Pallets in FRAME.
-duration: 1 hours
----
-
-# FRAME Benchmarking
-
-## Lesson 1
-
----
-
-## Overview
-
-- Quick Recap of Weights
-- Deep Dive Into Benchmarking
-
----
-
-## Blockchains are Limited
-
-Blockchain systems are extremely limited environments.
-
-Limited in:
-
-- Execution Time / Block Time
-- Available Storage
-- Available Memory
-- Network Bandwidth
-- etc...
-
----
-
-## Performance vs Centralization
-
-Nodes are expected to be decentralized and distributed.
-
-Increasing the system requirements can potentially lead to centralization in who can afford to run that hardware, and where such hardware may be available.
-
----
-
-## Why do we need benchmarking?
-
-Benchmarking ensures that when users interact with our Blockchain, they are not using resources beyond what is available and expected for our network.
-
----
-
-## What is Weight?
-
-Weight is a general concept used to track consumption of limited blockchain resources.
-
----
-
-## What is Weight in Substrate?
-
-We currently track just two main limitations:
-
-- Execution Time on "Reference Hardware"
-- Size of Data Required to Create a Merkle Proof
-
-```rust
-pub struct Weight {
-	/// The weight of computational time used based on some reference hardware.
-	ref_time: u64,
-	/// The weight of storage space used by proof of validity.
-	proof_size: u64,
-}
-```
-
-This was already expanded once, and could be expanded in the future.
-
----
-
-## Weight limits are specific to each blockchain.
-
-- 1 second of compute on different computers allows for different amounts of computation.
-- Weights of your blockchain will evolve over time.
-- Higher hardware requirements will result in a more performant blockchain (i.e. TXs per second), but will limit the kinds of validators that can safely participate in your network.
-- Proof size limitations can be relevant for parachains, but ignored for solo-chains.
-
----
-
-## What can affect relative Weight?
-
-<pba-cols>
-
-<pba-col>
-
-- Processor
-- Memory
-- Hard Drive
-  - HDD vs. SSD vs. NVME
-- Operating System
-- Drivers
-- Rust Compiler
-
-</pba-col>
-<pba-col>
-
-- Runtime Execution Engine
-  - compiled vs. interpreted
-- Database
-  - RocksDB vs. ParityDB vs. ?
-- Merkle trie / storage format
-- and more!
-
-</pba-col>
-</pba-cols>
-
----
-
-## Block Import Weight Breakdown
-
-<img style="height: 500px;" src="./img/block-import.svg" />
-
----
-
-# The Benchmarking Framework
-
----
-
-## The Benchmarking Plan
-
-<div class="flex-container">
-<div class="left-large">
-
-- Use empirical measurements of the runtime to determine the time and space it takes to execute extrinsics and other runtime logic.
-- Run benchmarks using worst case scenario conditions.
-  - Primary goal is to keep the runtime safe.
-  - Secondary goal is to be as accurate as possible to maximize throughput.
-
-</div>
-<div class="right">
-
-<img style="height: 600px;" src="./img/benchmarking.svg" />
-
-</div>
-</div>
-
----
-
-## The `#[benchmarks]` Macro
-
-```rust
-#[benchmarks]
-mod benchmarks {
-	use super::*;
-
-	#[benchmark]
-	fn benchmark_name() {
-		/* setup initial state */
-
-		/* execute extrinsic or function */
-		#[extrinsic_call]
-		extrinsic_name();
-
-		/* verify final state */
-		assert!(true)
-	}
-}
-```
-
----
-
-## Multiple Linear Regression Analysis
-
-<div class="flex-container">
-<div class="left-small">
-
-<img style="height: 600px;" src="./img/linear-regression.svg" />
-
-</div>
-<div class="right">
-
-- We require that no functions in Substrate have superlinear complexity.
-- Ordinary least squared linear regression.
-  - linregress crate
-- Supports multiple linear coefficients.
-  - Y = Ax + By + Cz + k
-- For constant time functions, we simply use the median value.
-
-</div>
-</div>
-
----
-
-## The `benchmark` CLI
-
-Compile your node with `--features runtime-benchmarks`.
-
-```sh
-➜  ~ substrate benchmark --help
-Sub-commands concerned with benchmarking.
-The pallet benchmarking moved to the `pallet` sub-command
-
-Usage: polkadot benchmark <COMMAND>
-
-Commands:
-  pallet     Benchmark the extrinsic weight of FRAME Pallets
-  storage    Benchmark the storage speed of a chain snapshot
-  overhead   Benchmark the execution overhead per-block and per-extrinsic
-  block      Benchmark the execution time of historic blocks
-  machine    Command to benchmark the hardware
-  extrinsic  Benchmark the execution time of different extrinsics
-  help       Print this message or the help of the given subcommand(s)
-
-Options:
-  -h, --help     Print help information
-  -V, --version  Print version information
-```
-
----
-
-## `pallet` Subcommand
-
-- Benchmark the weight of functions within pallets.
-  - Any arbitrary code can be benchmarked.
-- Outputs Autogenerated Weight files.
-
-```rust
-pub trait WeightInfo {
-   fn transfer() -> Weight;
-   fn transfer_keep_alive() -> Weight;
-   fn set_balance_creating() -> Weight;
-   fn set_balance_killing() -> Weight;
-   fn force_transfer() -> Weight;
-}
-```
-
----
-
-# Deep Dive
-
-So let’s walk through the steps of a benchmark!
-
-Reference: `frame/benchmarking/src/lib.rs`
-
-```rust
--> fn run_benchmark(...)
-```
-
----
-
-## The Benchmarking Process
-
-For each component and repeat:
-
-1. Select component to benchmark
-1. Generate range of values to test (steps)
-1. Whitelist known DB keys
-1. Setup benchmarking state
-1. Commit state to the DB, clearing cache
-1. Get system time (start)
-1. Execute extrinsic / benchmark function
-1. Get system time (end)
-1. Count DB reads and writes
-1. Record Data
-
----
-
-## Benchmarking Components
-
-- Imagine a function with 3 components
-  - let x in 1..2;
-  - let y in 0..5;
-  - let z in 0..10;
-- We set number of steps to 3.
-- Vary one component at a time, select high value for the others.
-
-<!-- prettier-ignore -->
-|   | Δx | Δy | Δy | Δz | Δz | max |
-| - | -- | -- | -- | -- | -- | --- |
-| x | 1  | 2  | 2  | 2  | 2  | 2   |
-| y | 5  | 0  | 2  | 5  | 5  | 5   |
-| z | 10 | 10 | 10 | 0  | 5  | 10  |
-
----
-
-## Benchmarks Evaluated Over Components
-
-<img style="height: 600px;" src="./img/components.svg" />
-
----
-
-## Whitelisted DB Keys
-
-```rust [3]
-/// The current block number being processed. Set by `execute_block`.
-#[pallet::storage]
-#[pallet::whitelist_storage]
-#[pallet::getter(fn block_number)]
-pub(super) type Number<T: Config> = StorageValue<_, BlockNumberFor<T>, ValueQuery>;
-```
-
-- Some keys are accessed every block:
-  - Block Number
-  - Events
-  - Total Issuance
-  - etc…
-- We don’t want to count these reads and writes in our benchmarking results.
-- Applied to all benchmarks being run.
-- This includes a “whitelisted account” provided by FRAME.
-
----
-
-## Example Benchmark
-
-The Identity Pallet
-
-<img style="height: 500px;" src="./img/identity-icon.svg" />
-
----
-
-## Identity Pallet
-
-- Identity can have variable amount of information
-  - Name
-  - Email
-  - Twitter
-  - etc…
-- Identity can be judged by a variable amount of registrars.
-- Identity can have a two-way link to “sub-identities”
-  - Other accounts that inherit the identity status of the “super-identity”
-
----
-
-## Extrinsic: Kill Identity
-
-```rust
-pub fn kill_identity(
-	origin: OriginFor<T>,
-	target: AccountIdLookupOf<T>,
-) -> DispatchResultWithPostInfo {
-	T::ForceOrigin::ensure_origin(origin)?;
-
-	// Figure out who we're meant to be clearing.
-	let target = T::Lookup::lookup(target)?;
-
-	// Grab their deposit (and check that they have one).
-	let (subs_deposit, sub_ids) = <SubsOf<T>>::take(&target);
-	let id = <IdentityOf<T>>::take(&target).ok_or(Error::<T>::NotNamed)?;
-	let deposit = id.total_deposit() + subs_deposit;
-	for sub in sub_ids.iter() { <SuperOf<T>>::remove(sub); }
-
-	// Slash their deposit from them.
-	T::Slashed::on_unbalanced(T::Currency::slash_reserved(&target, deposit).0);
-	Self::deposit_event(Event::IdentityKilled { who: target, deposit });
-	Ok(())
-}
-```
-
----
-
-## Handling Configurations
-
-- `kill_identity` will only execute if the `ForceOrigin` is calling.
-
-```rust
-T::ForceOrigin::ensure_origin(origin)?;
-```
-
-- However, this is configurable by the pallet developer.
-- Our benchmark needs to always work independent of the configuration.
-- We added a special function behind a feature flag:
-
-```rust
-/// Returns an outer origin capable of passing `try_origin` check.
-///
-/// ** Should be used for benchmarking only!!! **
-#[cfg(feature = "runtime-benchmarks")]
-fn successful_origin() -> OuterOrigin;
-```
-
----
-
-## External Logic / Hooks
-
-```rust
-// Figure out who we're meant to be clearing.
-let target = T::Lookup::lookup(target)?;
-```
-
-- In general, hooks like these are configurable in the runtime.
-- Each blockchain will have their own logic, and thus their own weight.
-- We run benchmarks against the real runtime, so we get the real results.
-- **IMPORTANT!** You need to be careful that the limitations of these hooks are well understood by the pallet developer and users of your pallet, otherwise, your benchmark will not be accurate.
-
----
-
-## Deterministic Storage Reads / Writes
-
-```rust
-// Grab their deposit (and check that they have one).
-let (subs_deposit, sub_ids) = <SubsOf<T>>::take(&target);
-let id = <IdentityOf<T>>::take(&target).ok_or(Error::<T>::NotNamed)?;
-```
-
-- 2 storage reads and writes.
-- The size of these storage items will depends on:
-  - Number of Registrars
-  - Number of Additional Fields
-
----
-
-## Variable Storage Reads / Writes
-
-```rust
-for sub in sub_ids.iter() { <SuperOf<T>>::remove(sub); }
-```
-
-enchmarkinghere you store balances!
-
-- What happens with slashed funds is configurable too!
-
----
-
-## Whitelisted Storage
-
-```rust
-Self::deposit_event(Event::IdentityKilled { who: target, deposit });
-```
-
-- We whitelist changes to the Events storage item, so generally this is “free” beyond computation and in-memory DB weight.
-
----
-
-## Preparing to Write Your Benchmark
-
-- 3 Components
-
-  - `R` - number of registrars
-  - `S` - number of sub-accounts
-  - `X` - number of additional fields
-
-- Need to:
-  - Set up account with funds.
-  - Register an identity with additional fields.
-  - Set up worst case scenario for registrars and sub-accounts.
-  - Take into account `ForceOrigin` to make the call.
-
----
-
-## Kill Identity Benchmark
-
-```rust
-#[benchmark]
-fn kill_identity(
-	r: Linear<1, T::MaxRegistrars::get()>,
-	s: Linear<0, T::MaxSubAccounts::get()>,
-	x: Linear<0, T::MaxAdditionalFields::get()>,
-) -> Result<(), BenchmarkError> {
-	add_registrars::<T>(r)?;
-
-	let target: T::AccountId = account("target", 0, SEED);
-	let target_origin: <T as frame_system::Config>::RuntimeOrigin = RawOrigin::Signed(target.clone()).into();
-	let target_lookup = T::Lookup::unlookup(target.clone());
-	let _ = T::Currency::make_free_balance_be(&target, BalanceOf::<T>::max_value());
-
-	let info = create_identity_info::<T>(x);
-	Identity::<T>::set_identity(target_origin.clone(), Box::new(info.clone()))?;
-	let _ = add_sub_accounts::<T>(&target, s)?;
-
-	// User requests judgement from all the registrars, and they approve
-	for i in 0..r {
-		let registrar: T::AccountId = account("registrar", i, SEED);
-		let balance_to_use =  T::Currency::minimum_balance() * 10u32.into();
-		let _ = T::Currency::make_free_balance_be(&registrar, balance_to_use);
-
-		Identity::<T>::request_judgement(target_origin.clone(), i, 10u32.into())?;
-		Identity::<T>::provide_judgement( RawOrigin::Signed(registrar).into(), i, target_lookup.clone(), Judgement::Reasonable, T::Hashing::hash_of(&info),
-		)?;
-	}
-	ensure!(IdentityOf::<T>::contains_key(&target), "Identity not set");
-	let origin = T::ForceOrigin::successful_origin();
-
-	#[extrinsic_call]
-	kill_identity<T::RuntimeOrigin>(origin, target_lookup)
-
-	ensure!(!IdentityOf::<T>::contains_key(&target), "Identity not removed");
-	Ok(())
-}
-```
-
----
-
-## Benchmarking Components
-
-```rust
-fn kill_identity(
-	r: Linear<1, T::MaxRegistrars::get()>,
-	s: Linear<0, T::MaxSubAccounts::get()>,
-	x: Linear<0, T::MaxAdditionalFields::get()>,
-) -> Result<(), BenchmarkError> { ... }
-```
-
-- Our components.
-  - R = Number of Registrars
-  - S = Number of Sub-Accounts
-  - X = Number of Additional Fields on the Identity.
-- Note all of these have configurable, known at compile time maxima.
-  - Part of the pallet configuration trait.
-  - Runtime logic should enforce these limits.
-
----
-
-## Set Up Logic
-
-```rust
-add_registrars::<T>(r)?;
-
-let target: T::AccountId = account("target", 0, SEED);
-let target_origin: <T as frame_system::Config>::RuntimeOrigin = RawOrigin::Signed(target.clone()).into();
-let target_lookup = T::Lookup::unlookup(target.clone());
-let _ = T::Currency::make_free_balance_be(&target, BalanceOf::<T>::max_value());
-```
-
-- Adds registrars to the runtime storage.
-- Set up an account with the appropriate funds.
-- Note this is just like writing runtime tests!
-
----
-
-## Reusable Setup Functions
-
-```rust
-let info = create_identity_info::<T>(x);
-Identity::<T>::set_identity(target_origin.clone(), Box::new(info.clone()))?;
-let _ = add_sub_accounts::<T>(&target, s)?;
-```
-
-- Using some custom functions defined in the benchmarking file:
-- Give that account an Identity with x additional fields.
-- Give that Identity `s` sub-accounts.
-
----
-
-## Set Up Worst Case Scenario
-
-```rust
-// User requests judgement from all the registrars, and they approve
-for i in 0..r {
-	let registrar: T::AccountId = account("registrar", i, SEED);
-	let balance_to_use =  T::Currency::minimum_balance() * 10u32.into();
-	let _ = T::Currency::make_free_balance_be(&registrar, balance_to_use);
-
-	Identity::<T>::request_judgement(target_origin.clone(), i, 10u32.into())?;
-	Identity::<T>::provide_judgement( RawOrigin::Signed(registrar).into(), i, target_lookup.clone(), Judgement::Reasonable, T::Hashing::hash_of(&info),
-	)?;
-}
-```
-
-- Add r registrars.
-- Have all of them give a judgement to this identity.
-
----
-
-## Execute and Verify the Benchmark:
-
-```rust
-ensure!(IdentityOf::<T>::contains_key(&target), "Identity not set");
-let origin = T::ForceOrigin::successful_origin();
-
-#[extrinsic_call]
-kill_identity<T::RuntimeOrigin>(origin, target_lookup)
-
-ensure!(!IdentityOf::<T>::contains_key(&target), "Identity not removed");
-Ok(())
-```
-
-- First ensure statement verifies the “before” state is as we expect.
-- We need to use our custom origin.
-- Verify block ensures our “final” state is as we expect.
-
----
-
-## Executing the Benchmark
-
-```sh
-./target/production/substrate benchmark pallet \
-	--chain=dev \				# Configurable Chain Spec
-	--steps=50 \				# Number of steps across component ranges
-	--repeat=20 \				# Number of times we repeat a benchmark
-	--pallet=pallet_identity \	# Select the pallet
-	--extrinsic=* \				# Select the extrinsic(s)
-	--wasm-execution=compiled \ # Always used `wasm-time`
-	--heap-pages=4096 \			# Not really needed, adjusts memory
-	--output=./frame/identity/src/weights.rs \	# Output results into a Rust file
-	--header=./HEADER-APACHE2 \	# Custom header file to include with template
-	--template=./.maintain/frame-weight-template.hbs # Handlebar template
-```
-
----
-
-# Looking at Raw Benchmarking Data
-
----
-
-## Results: Extrinsic Time vs. # of Registrars
-
-<img style="height: 500px;" src="./img/identity-raw-registrars.png" />
-
-Notes:
-
-Graph source: <https://www.shawntabrizi.com/substrate-graph-benchmarks/old/>
-
----
-
-## Results: Extrinsic Time vs. # of Sub-Accounts
-
-<img style="height: 500px;" src="./img/identity-raw-sub.png" />
-
-Notes:
-
-Graph source: <https://www.shawntabrizi.com/substrate-graph-benchmarks/old/>
-
----
-
-## Results: Extrinsic Time vs. Additional Fields
-
-<img style="height: 500px;" src="./img/identity-raw-fields.png" />
-
-Notes:
-
-Graph source: <https://www.shawntabrizi.com/substrate-graph-benchmarks/old/>
-
----
-
-## Result: DB Operations vs. Sub Accounts
-
-<img style="height: 500px;" src="./img/identity-db-sub.png" />
-
-Notes:
-
-Graph source: <https://www.shawntabrizi.com/substrate-graph-benchmarks/old/>
-
----
-
-## Final Weight
-
-```rust
-// Storage: Identity SubsOf (r:1 w:1)
-// Storage: Identity IdentityOf (r:1 w:1)
-// Storage: System Account (r:1 w:1)
-// Storage: Identity SuperOf (r:0 w:100)
-/// The range of component `r` is `[1, 20]`.
-/// The range of component `s` is `[0, 100]`.
-/// The range of component `x` is `[0, 100]`.
-fn kill_identity(r: u32, s: u32, x: u32, ) -> Weight {
-	// Minimum execution time: 68_794 nanoseconds.
-	Weight::from_ref_time(52_114_486 as u64)
-		// Standard Error: 4_808
-		.saturating_add(Weight::from_ref_time(153_462 as u64).saturating_mul(r as u64))
-		// Standard Error: 939
-		.saturating_add(Weight::from_ref_time(1_084_612 as u64).saturating_mul(s as u64))
-		// Standard Error: 939
-		.saturating_add(Weight::from_ref_time(170_112 as u64).saturating_mul(x as u64))
-		.saturating_add(T::DbWeight::get().reads(3 as u64))
-		.saturating_add(T::DbWeight::get().writes(3 as u64))
-		.saturating_add(T::DbWeight::get().writes((1 as u64).saturating_mul(s as u64)))
-}
-```
-
----
-
-## WeightInfo Generation
-
-```rust
-/// Weight functions needed for pallet_identity.
-pub trait WeightInfo {
-	fn add_registrar(r: u32, ) -> Weight;
-	fn set_identity(r: u32, x: u32, ) -> Weight;
-	fn set_subs_new(s: u32, ) -> Weight;
-	fn set_subs_old(p: u32, ) -> Weight;
-	fn clear_identity(r: u32, s: u32, x: u32, ) -> Weight;
-	fn request_judgement(r: u32, x: u32, ) -> Weight;
-	fn cancel_request(r: u32, x: u32, ) -> Weight;
-	fn set_fee(r: u32, ) -> Weight;
-	fn set_account_id(r: u32, ) -> Weight;
-	fn set_fields(r: u32, ) -> Weight;
-	fn provide_judgement(r: u32, x: u32, ) -> Weight;
-	fn kill_identity(r: u32, s: u32, x: u32, ) -> Weight;
-	fn add_sub(s: u32, ) -> Weight;
-	fn rename_sub(s: u32, ) -> Weight;
-	fn remove_sub(s: u32, ) -> Weight;
-	fn quit_sub(s: u32, ) -> Weight;
-}
-```
-
----
-
-## WeightInfo Integration
-
-```rust
-#[pallet::weight(T::WeightInfo::kill_identity(
-	T::MaxRegistrars::get(), // R
-	T::MaxSubAccounts::get(), // S
-	T::MaxAdditionalFields::get(), // X
-))]
-pub fn kill_identity(
-	origin: OriginFor<T>,
-	target: AccountIdLookupOf<T>,
-) -> DispatchResultWithPostInfo {
-
-	// -- snip --
-
-	Ok(Some(T::WeightInfo::kill_identity(
-		id.judgements.len() as u32,      // R
-		sub_ids.len() as u32,            // S
-		id.info.additional.len() as u32, // X
-	))
-	.into())
-}
-```
-
----
-
-## Initial Weight
-
-```rust
-#[pallet::weight(T::WeightInfo::kill_identity(
-	T::MaxRegistrars::get(), // R
-	T::MaxSubAccounts::get(), // S
-	T::MaxAdditionalFields::get(), // X
-))]
-```
-
-- Use the WeightInfo function as the weight definition for your function.
-- Note that we assume absolute worst case scenario to begin since we cannot know these specific values until we query storage.
-
----
-
-## Final Weight (Refund)
-
-```rust
-pub fn kill_identity(...) -> DispatchResultWithPostInfo { ... }
-```
-
-```rust
-Ok(Some(T::WeightInfo::kill_identity(
-	id.judgements.len() as u32,      // R
-	sub_ids.len() as u32,            // S
-	id.info.additional.len() as u32, // X
-))
-.into())
-```
-
-- Then we return the actual weight used at the end!
-- We use the same WeightInfo formula, but using the values that we queried from storage as part of executing the extrinsic.
-- This only allows you to **decrease** the final weight. Nothing will happen if you return a bigger weight than the initial weight.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
-In another presentation we will cover some of the things we learned while benchmarking, and best practices.
-
----
-
-# Benchmarking Exercise
diff --git a/content/frame/benchmarking-2/page.md b/content/frame/benchmarking-2/page.md
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-# Benchmarking
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/benchmarking-2/slides.md b/content/frame/benchmarking-2/slides.md
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----
-title: FRAME Benchmarking 2
-description: How to benchmark Pallets in FRAME.
-duration: 1 hours
----
-
-# FRAME Benchmarking
-
-## Lesson 2
-
----
-
-## Overview
-
-- Databases
-- Our Learnings Throughout Development
-- Best Practices and Common Patterns
-
----
-
-# Databases
-
----
-
-### RocksDB
-
-A Persistent Key-Value Store for Flash and RAM Storage.
-
-- Keys and values are arbitrary byte arrays.
-- Fast for a general database.
-
-See: <https://rocksdb.org/>.
-
-Big project, can be very tricky to configure properly.
-
-Notes:
-
-(also a big part of substrate compilation time).
-
----
-
-### ParityDB
-
-An Embedded Persistent Key-Value Store Optimized for Blockchain Applications.
-
-- Keys and values are arbitrary byte arrays.
-- Designed for efficiently storing Patricia-Merkle trie nodes.
-  - Mostly Fixed Size Keys.
-  - Mostly Small Values.
-  - Uniform Distribution.
-- Optimized for read performance.
-
-Notes:
-
-See: <https://github.com/paritytech/parity-db/issues/82
-
-Main point is that paritydb suit the triedb model.
-Indeed triedb store encoded key by their hash.
-So we don't need rocksdb indexing, no need to order data.
-Parity db index its content by hash of key (by default), which makes access faster (hitting entry of two file generally instead of possibly multiple btree indexing node).
-Iteration on state value is done over the trie structure: having a KVDB with iteration support isn't needed.
-
-Both rocksdb and paritydb uses "Transactions" as "writes done in batches".
-We typically run a transaction per block (all in memory before), things are fast (that's probably what you meant).
-In blockchains, writes are typically performed in large batches, when the new block is imported and must be done atomically.
-See: <https://github.com/paritytech/parity-db>
-
-Concurrency does not matter in this, paritydb lock access to single writer (no concurrency).
-Similarly code strive at being simple and avoid redundant feature: no cache in parity db (there is plenty in substrate).
-
-'Quick commit' : all changes are stored in memory on commit , and actual writing in the WriteAheadLog is done in an asynchronous way.
-
-TODO merge with content from <https://github.com/paritytech/parity-db/issues/82>
-
----
-
-### ParityDB: Probing Hash Table
-
-ParityDB is implemented as a probing hash table.
-
-- As opposed to a log-structured merge (LSM) tree.
-  - Used in Apache AsterixDB, Bigtable, HBase, LevelDB, Apache Accumulo, SQLite4, Tarantool, RocksDB, WiredTiger, Apache Cassandra, InfluxDB, ScyllaDB, etc...
-- Because we do not require key ordering or iterations for trie operations.
-- This means read performance is constant time, versus $O(\log{n})$.
-
----
-
-### ParityDB: Fixed Size Value Tables
-
-- Each column stores data in a set of 256 value tables, with 255 tables containing entries of certain size range up to 32 KB limit.
-
-<div class="text-smaller">
-
-```rust
-const SIZES: [u16; SIZE_TIERS - 1] = [
-	32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 50, 51, 52, 54, 55, 57, 58, 60,
-	62, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 88, 90, 93, 95, 98, 101, 103, 106, 109,
-	112, 115, 119, 122, 125, 129, 132, 136, 140, 144, 148, 152, 156, 160, 165, 169, 174, 179, 183,
-	189, 194, 199, 205, 210, 216, 222, 228, 235, 241, 248, 255, 262, 269, 276, 284, 292, 300, 308,
-	317, 325, 334, 344, 353, 363, 373, 383, 394, 405, 416, 428, 439, 452, 464, 477, 490, 504, 518,
-	532, 547, 562, 577, 593, 610, 627, 644, 662, 680, 699, 718, 738, 758, 779, 801, 823, 846, 869,
-	893, 918, 943, 969, 996, 1024, 1052, 1081, 1111, 1142, 1174, 1206, 1239, 1274, 1309, 1345,
-	1382, 1421, 1460, 1500, 1542, 1584, 1628, 1673, 1720, 1767, 1816, 1866, 1918, 1971, 2025, 2082,
-	2139, 2198, 2259, 2322, 2386, 2452, 2520, 2589, 2661, 2735, 2810, 2888, 2968, 3050, 3134, 3221,
-	3310, 3402, 3496, 3593, 3692, 3794, 3899, 4007, 4118, 4232, 4349, 4469, 4593, 4720, 4850, 4984,
-	5122, 5264, 5410, 5559, 5713, 5871, 6034, 6200, 6372, 6548, 6729, 6916, 7107, 7303, 7506, 7713,
-	7927, 8146, 8371, 8603, 8841, 9085, 9337, 9595, 9860, 10133, 10413, 10702, 10998, 11302, 11614,
-	11936, 12266, 12605, 12954, 13312, 13681, 14059, 14448, 14848, 15258, 15681, 16114, 16560,
-	17018, 17489, 17973, 18470, 18981, 19506, 20046, 20600, 21170, 21756, 22358, 22976, 23612,
-	24265, 24936, 25626, 26335, 27064, 27812, 28582, 29372, 30185, 31020, 31878, 32760,
-];
-```
-
-</div>
-
-- The last 256th value table size stores entries that are over 32 KB split into multiple parts.
-
----
-
-### ParityDB: Fixed Size Value Tables
-
-- More than 99% of trie nodes are less than 32kb in size.
-- Small values only require 2 reads: One index lookup and one value table lookup.
-- Values over 32kb may require multiple value table reads, but these are rare.
-- Helps minimize unused disk space.
-- For example, if you store a 670 byte value, it won't fit into 662 bucket, but will into 680 bucket, wasting only 10 bytes of space.
-
-Notes:
-
-That fact that most values are small allows us to address each value by its index and have a simple mechanism for reusing the space of deleted values without fragmentation and periodic garbage collection.
-
----
-
-### ParityDB: Asynchronous Writes
-
-- Parity DB API exposes synchronous functions, but underlying IO is async.
-- The `commit` function adds the database transaction to the write queue, updates the commit overlay, and returns as quickly as possible.
-- The actual writing happens in the background.
-- The commit overlay allows the block import pipeline to start executing the next block while the database is still writing changes for the previous block.
-
----
-
-### Practical Benchmarks and Considerations
-
-Let's now step away from concepts and talk about cold hard data.
-
----
-
-### Common Runtime Data Size and Performance
-
-<br />
-
-<div class="flex-container">
-<div class="left">
-
-- Most runtime values are 80 bytes, which are user accounts.
-- Of course, this would depend on your chain's logic.
-
-</div>
-<div class="right" style="padding-left: 10px;">
-
-<div class="r-stack">
-	<img style="height: 500px;" src="./img/polkadot-size-histogram.png" />
-	<img style="height: 500px;" class="fragment" src="./img/polkadot-size-histogram-alpha.png" />
-</div>
-</div>
-
-Notes:
-
-Impact of keys size is slightly bigger encoded node.
-Since eth scaling issue, we usually focus on state nodes.
-Other content access can be interesting to audit enhance though (with paritydb).
-
-See more details here:
-
-<https://substrate.stackexchange.com/questions/525/how-expensive-is-it-to-access-storage-items/526#526>
-
----
-
-### RocksDB vs ParityDB Performance
-
-At 32 KB, performance decreases for each additional 4 KB.
-
-<img style="height: 500px" src="./img/paritydb-vs-rocksdb-read.png" />
-
----
-
-### RocksDB Inconsistency
-
-<img style="width: 1200px;" src="./img/rocksdb-hiccups.png" />
-
-When doing benchmarking, we saw some really bizarre, but reproducible problems with RocksDB.
-
----
-
-## Things we tried
-
-## Things we learned
-
----
-
-## Isolating DB Benchmarks (PR #5586)
-
-<pba-cols>
-<pba-col>
-
-### We tried…
-
-To benchmark the entire extrinsic, including the weight of DB operations directly in the benchmark. We wanted to:
-
-- Populate the DB to be “full”
-- Flush the DB cache
-- Run the benchmark
-
-</pba-col>
-<pba-col>
-
-### We learned…
-
-RocksDB was too inconsistent to give reproducible results, and really slow to populate.
-So we use an in-memory DB for benchmarking.
-
-<img style="height: 200px;" src="./img/rocksdb-hiccups.png" />
-
-</pba-col>
-</pba-cols>
-
----
-
-## Fixing Nonlinear Events (PR #5795)
-
-<pba-cols>
-<pba-col>
-
-### We tried…
-
-Executing a whole block, increasing the number of txs in each block. We expected to get linear growth of execution time, but in fact it was superlinear!
-
-<img style="height: 250px;" src="./img/nonlinear-events.png" />
-
-</pba-col>
-<pba-col>
-
-### We learned…
-
-Each time we appended a new event, we were passing the growing event object over the Wasm barrier.
-
-We updated the append api so only new data is pushed.
-
-<img style="height: 200px;" src="./img/event-fix.png" />
-
-</pba-col>
-</pba-cols>
-
----
-
-## Enabling Weight Refunds (PR #5584)
-
-<pba-cols>
-<pba-col>
-
-### We tried…
-
-To assign weights to all extrinsics for the absolute worst case scenario in order to be safe.
-
-In many cases, we cannot know accurately what the weight of the extrinsic will be without reading storage… and this is not allowed!
-
-</pba-col>
-<pba-col>
-
-### We learned…
-
-That many extrinsics have a worst case weight much different than their average weight.
-
-So we allow extrinsics to return the actual weight consumed and refund that weight and any weight fees.
-
-</pba-col>
-</pba-cols>
-
----
-
-## Customizable Weight Info (PR #6575)
-
-<pba-cols>
-<pba-col>
-
-### We tried…
-
-To record weight information and benchmarking results directly in the pallet.
-
-</pba-col>
-<pba-col>
-
-### We learned…
-
-This was hard to update, not customizable, and not accurate for custom pallet configurations.
-
-</pba-col>
-</pba-cols>
-
-So we moved the weight definition into customizable associated types configured in the runtime trait.
-
-```rust
-#[weight = 45_000_000 + T::DbWeight::get().reads_writes(1,1)]
-```
-
-turned into...
-
-```rust
-#[weight = T::WeightInfo::transfer()]
-```
-
----
-
-## Inherited Call Weight Syntax (PR #13932)
-
-```rust
-#[pallet::call(weight(<T as Config>::WeightInfo))]
-impl<T: Config> Pallet<T> {
-
-	pub fn create(
-		...
-```
-
----
-
-## Custom Benchmark Returns / Errors (PR #9517)
-
-```rust
-override_benchmark {
-	let b in 1 .. 1000;
-	let caller = account::<T::AccountId>("caller", 0, 0);
-}: {
-	Err(BenchmarkError::Override(
-		BenchmarkResult {
-			extrinsic_time: 1_234_567_890,
-			reads: 1337,
-			writes: 420,
-			..Default::default()
-		}
-	))?;
-}
-```
-
----
-
-## Negative Y Intercept Handling (PR #11806)
-
----
-
-## Multi-Dimensional Weight (Issue #12176)
-
-```rust
-#[derive(
-	Encode, Decode, MaxEncodedLen, TypeInfo, Eq, PartialEq, Copy, Clone, RuntimeDebug, Default,
-)]
-#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
-pub struct Weight {
-	#[codec(compact)]
-	/// The weight of computational time used based on some reference hardware.
-	ref_time: u64,
-	#[codec(compact)]
-	/// The weight of storage space used by proof of validity.
-	proof_size: u64,
-}
-```
-
----
-
-# Best Practices & Common Patterns
-
----
-
-## Initial Weight Calculation Must Be Lightweight
-
-- In the TX queue, we need to know the weight to see if it would fit in the block.
-- This weight calculation must be lightweight!
-- No storage reads!
-
-Example:
-
-- Transfer Base: ~50 µs
-- Storage Read: ~25 µs
-
----
-
-## Set Bounds and Assume the Worst!
-
-- Add a configuration trait that sets an upper bound to some item, and in weights, initially assume this worst case scenario.
-- During the extrinsic, find the actual length/size of the item, and refund the weight to be the actual amount used.
-
----
-
-## Separate Benchmarks Per Logical Path
-
-- It may not be clear which logical path in a function is the “worst case scenario”.
-- Create a benchmark for each logical path your function could take.
-- Ensure each benchmark is testing the worst case scenario of that path.
-
----
-
-## Comparison Operators in the Weight Definition
-
-```rust
-#[pallet::weight(
-   T::WeightInfo::path_a()
-   .max(T::WeightInfo::path_b())
-   .max(T::WeightInfo::path_c())
-)]
-```
-
----
-
-## Keep Extrinsics Simple
-
-- The more complex your extrinsic logic, the harder it will be to accurately weigh.
-- This leads to larger up-front weights, potentially higher tx fees, and less efficient block packing.
-
----
-
-## Use Multiple Simple Extrinsics
-
-- Take advantage of UI/UX, batch calls, and similar downstream tools to simplify extrinsic logic.
-
-Example:
-
-- Vote and Close Vote (“last vote”) are separate extrinsics.
-
----
-
-## Minimize Usage of On Finalize
-
-- `on_finalize` is the last thing to happen in a block, and must execute for the block to be successful.
-- Variable weight needs at can lead to overweight blocks.
-
-<img style="height: 200px;" src="./img/on-finalize.svg" />
-
----
-
-## Transition Logic and Weights to On Initialize
-
-- `on_initialize` happens at the beginning of the block, before extrinsics.
-- The number of extrinsics can be adjusted to support what is available.
-- Weight for `on_finalize` should be wrapped into on_initialize weight or extrinsic weight.
-
----
-
-## Understand Limitations of Pallet Hooks
-
-- A powerful feature of Substrate is to allow the runtime configuration to implement pallet configuration traits.
-- However, it is easy for this feature to be abused and make benchmarking inaccurate.
-
----
-
-## Keep Hooks Constant Time
-
-- Example: Balances hook for account creation and account killed.
-- Benchmarking has no idea how to properly set up your state to test for any arbitrary hook.
-- So you must keep hooks constant time, unless specified by the pallet otherwise.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/frame/calls/page.md b/content/frame/calls/page.md
deleted file mode 100644
index 014c85e7..00000000
--- a/content/frame/calls/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Calls
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
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diff --git a/content/frame/calls/slides.md b/content/frame/calls/slides.md
deleted file mode 100644
index afb228c0..00000000
--- a/content/frame/calls/slides.md
+++ /dev/null
@@ -1,282 +0,0 @@
----
-title: FRAME Calls
-description: FRAME Calls for web3 builders.
-duration: 1 hour
----
-
-# FRAME Calls
-
----
-
-## Overview
-
-Calls allow users to interact with your state transition function.
-
-In this lecture, you will learn how to create calls for your Pallet with FRAME.
-
----
-
-## Terminology
-
-The term "call", "extrinsic", and "dispatchable" all get mixed together.
-
-Here is a sentence which should help clarify their relationship, and why they are such similar terms:
-
-> Users submit an **extrinsic** to the blockchain, which is **dispatched** to a Pallet **call**.
-
----
-
-## Call Definition
-
-Here is a simple pallet call. Let's break it down.
-
-```rust
-#[pallet::call(weight(<T as Config>::WeightInfo))]
-impl<T: Config> Pallet<T> {
-	#[pallet::call_index(0)]
-	pub fn transfer(
-		origin: OriginFor<T>,
-		dest: AccountIdLookupOf<T>,
-		#[pallet::compact] value: T::Balance,
-	) -> DispatchResult {
-		let source = ensure_signed(origin)?;
-		let dest = T::Lookup::lookup(dest)?;
-		<Self as fungible::Mutate<_>>::transfer(&source, &dest, value, Expendable)?;
-		Ok(())
-	}
-}
-```
-
----
-
-## Call Implementation
-
-Calls are just functions which are implemented on top of the `Pallet` struct.
-
-You can do this with any kind of function, however, "FRAME magic" turns these into dispatchable calls through the `#[pallet::call]` macro.
-
----
-
-## Call Origin
-
-Every pallet call must have an `origin` parameter, which uses the `OriginFor<T>` type, which comes from `frame_system`.
-
-```rust
-/// Type alias for the `Origin` associated type of system config.
-pub type OriginFor<T> = <T as crate::Config>::RuntimeOrigin;
-```
-
----
-
-## Origin
-
-The basic origins available in frame are:
-
-```rust
-/// Origin for the System pallet.
-#[derive(PartialEq, Eq, Clone, RuntimeDebug, Encode, Decode, TypeInfo, MaxEncodedLen)]
-pub enum RawOrigin<AccountId> {
-	/// The system itself ordained this dispatch to happen: this is the highest privilege level.
-	Root,
-	/// It is signed by some public key and we provide the `AccountId`.
-	Signed(AccountId),
-	/// It is signed by nobody, can be either:
-	/// * included and agreed upon by the validators anyway,
-	/// * or unsigned transaction validated by a pallet.
-	None,
-}
-```
-
-We will have another presentation diving deeper into Origins.
-
----
-
-## Origin Checking
-
-Normally, the first thing you do in a call is check that the origin of the caller is what you expect.
-
-Most often, this is checking that the extrinsic is `Signed`, which is a transaction from a user account.
-
-```rust
-let caller: T::AccountId = ensure_signed(origin)?;
-```
-
----
-
-## Call Parameters
-
-Pallet calls can have additional parameters beyond `origin` allowing you to submit relevant data about what the caller would like to do.
-
-All call parameters need to satisfy the `Parameter` trait:
-
-```rust
-/// A type that can be used as a parameter in a dispatchable function.
-pub trait Parameter: Codec + EncodeLike + Clone + Eq + fmt::Debug + scale_info::TypeInfo {}
-impl<T> Parameter for T where T: Codec + EncodeLike + Clone + Eq + fmt::Debug + scale_info::TypeInfo {}
-```
-
----
-
-## Parameter Limits
-
-Most everything can be used as a call parameter, even a normal `Vec`, however, FRAME ensures that encoded block are smaller than a maximum block size, which inherently limits the extrinsic length.
-
-In Polkadot this is currently 5 MB.
-
----
-
-## Compact Parameters
-
-Parameters that are compact encoded can be used in calls.
-
-```rust
-pub fn transfer(
-	origin: OriginFor<T>,
-	dest: AccountIdLookupOf<T>,
-	#[pallet::compact] value: T::Balance,
-) -> DispatchResult { ... }
-```
-
-This can help save lots of bytes, especially in cases like balances as shown above.
-
----
-
-## Call Logic
-
-The most relevant part of a call is the "call logic".
-
-There is really nothing magical happening here, just normal Rust.
-
-However, you must follow one important rule...
-
----
-
-## Calls MUST NOT Panic
-
-Under no circumstances (save, perhaps, storage getting into an irreparably damaged state) must this function panic.
-
-Allowing callers to trigger a panic from a call can allow users to attack your chain by bypassing fees or other costs associated with executing logic on the blockchain.
-
----
-
-## Call Return
-
-Every call returns a `DispatchResult`:
-
-```rust
-pub type DispatchResult = Result<(), sp_runtime::DispatchError>;
-```
-
-This allows you to handle errors in your runtime, and NEVER PANIC!
-
----
-
-## Returning an Error
-
-At any point in your call logic, you can return a `DispatchError`.
-
-```rust
-ensure!(new_balance >= min_balance, Error::<T, I>::LiquidityRestrictions);
-```
-
-When you do, thanks to transactional storage layers, all modified state will be reverted.
-
----
-
-## Returning Success
-
-If everything in your pallet completed successfully, you simply return `Ok(())`, and all your state changes are committed, and the extrinsic is considered to have executed successfully.
-
----
-
-## Call Index
-
-It is best practice to explicitly label your calls with a `call_index`.
-
-```rust
-#[pallet::call_index(0)]
-```
-
-This can help ensure that changes to your pallet do not lead to breaking changes to the transaction format.
-
----
-
-## Call Encoding
-
-At a high level, a call is encoded as two bytes (plus any parameters):
-
-1. The Pallet Index
-1. The Call Index
-
-Pallet Index comes from the order / explicit numbering of the `construct_runtime!`. If things change order, without explicit labeling, a transaction generated by a wallet (like a ledger) could be incorrect!
-
-Notes:
-
-Note that this also implies there can only be 256 calls per pallet due to the 1 byte encoding.
-
----
-
-## Weight
-
-Each call must also include specify a call `weight`.
-
-We have another lecture on Weights and Benchmarking, but the high level idea is that this weight function tells us how complex the call is, and the fees that should be charged to the user.
-
----
-
-## Weight Per Call
-
-This can be done per call:
-
-```rust [3]
-#[pallet::call]
-impl<T: Config> Pallet<T> {
-	#[pallet::weight(T::WeightInfo::transfer())]
-	#[pallet::call_index(0)]
-	pub fn transfer(
-		origin: OriginFor<T>,
-		dest: AccountIdLookupOf<T>,
-		#[pallet::compact] value: T::Balance,
-	) -> DispatchResult {
-		let source = ensure_signed(origin)?;
-		let dest = T::Lookup::lookup(dest)?;
-		<Self as fungible::Mutate<_>>::transfer(&source, &dest, value, Expendable)?;
-		Ok(())
-	}
-}
-```
-
----
-
-## Weight for the Pallet
-
-Or for all calls in the pallet:
-
-```rust [1]
-#[pallet::call(weight(<T as Config>::WeightInfo))]
-impl<T: Config> Pallet<T> {
-	#[pallet::call_index(0)]
-	pub fn transfer(
-		origin: OriginFor<T>,
-		dest: AccountIdLookupOf<T>,
-		#[pallet::compact] value: T::Balance,
-	) -> DispatchResult {
-		let source = ensure_signed(origin)?;
-		let dest = T::Lookup::lookup(dest)?;
-		<Self as fungible::Mutate<_>>::transfer(&source, &dest, value, Expendable)?;
-		Ok(())
-	}
-}
-```
-
-In this case, the weight function name is assumed to match the call name for all calls.
-
-Notes:
-
-<https://github.com/paritytech/substrate/pull/13932>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/frame/construct-runtime/page.md b/content/frame/construct-runtime/page.md
deleted file mode 100644
index 5bf4c191..00000000
--- a/content/frame/construct-runtime/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Construct Runtime
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/construct-runtime/slides.md b/content/frame/construct-runtime/slides.md
deleted file mode 100644
index da37c952..00000000
--- a/content/frame/construct-runtime/slides.md
+++ /dev/null
@@ -1,584 +0,0 @@
----
-title: Construct Runtime
-description: Deep dive into the Construct Runtime macro
-duration: 1 hour
----
-
-# `construct_runtime!` and Testing 🔨
-
----
-
-# Part 1: Runtime Construction
-
----
-
-<img style="height: 600px" src="../intro/img/frame1.svg" />
-
----
-
-## Pallet <=> Runtime
-
-A runtime is really ✌️ things:
-
-1. A struct that implements `Config` of all pallets.
-2. A type that helps `Executive` implement `RuntimeApis`.
-
----v
-
-### Pallet <=> Runtime
-
-We build a runtime, using `construct_runtime`, typically twice:
-
-1. Per pallet, there is a mock runtime.
-2. A real runtime elsewhere.
-
-Note:
-
-Benchmarking can then use both of these runtimes.
-
----
-
-## `construct_runtime`: `Runtime` type
-
-```rust [1-100|2]
-frame_support::construct_runtime!(
-  pub struct Runtime {
-    System: frame_system,
-    Timestamp: pallet_timestamp,
-    Balances: pallet_balances,
-    Aura: pallet_aura,
-    Dpos: pallet_dpos,
-  }
-);
-```
-
----v
-
-### `Runtime` type
-
-- It implements [A LOT OF STUFF](https://paritytech.github.io/substrate/master/kitchensink_runtime/struct.Runtime.html)!
-- But most importantly, the `Config` trait of all of your pallets 🫵🏻.
-
-```rust
-impl frame_system::Config for Runtime { .. }
-impl pallet_timestamp::Config for Runtime { .. }
-impl pallet_dpos::Config for Runtime { .. }
-```
-
----v
-
-### `<T: Config>` ==> `Runtime`
-
-> Anywhere in your pallet code that you have `<T: Config>` can now be replaced with `Runtime`.
-
-```rust[1-2|3-4|5-6]
-// a normal pub function defined in
-frame_system::Pallet::<Runtime>::block_number();
-// a storage getter of a map.
-frame_system::Pallet::<Runtime>::account(42u32);
-// A storage type.
-frame_system::Account::<Runtime>::get(42u32);
-```
-
----
-
-## `construct_runtime`: Pallet List
-
-```rust [3-7|8|1-100]
-frame_support::construct_runtime!(
-  pub struct Runtime {
-    System: frame_system,
-    Timestamp: pallet_timestamp,
-    Balances: pallet_balances,
-    Aura: pallet_aura,
-    Dpos: pallet_dpos,
-    <NameYouChoose>: path_to_crate,
-  }
-);
-```
-
----v
-
-### Pallet List
-
-- Crucially, under the hood, this generates:
-
-```rust
-type System = frame_system::Pallet<Runtime>;
-type Balances = pallet_balances::Pallet<Runtime>;
-..
-type DPos = pallet_dpos::Pallet<Runtime>;
-```
-
-- Recall that `Runtime` implements `<T: Config>` of all pallets.
-
----v
-
-### Pallet List
-
-```rust
-frame_system::Pallet::<Runtime>::block_number(); // 🤮
-System::block_number(); // 🥳
-
-frame_system::Pallet::<Runtime>::account(42u32); // 🤮
-System::account(42u32); // 🥳
-```
-
----v
-
-### Pallet List
-
-- Next crucial piece of information that is generated is:
-
-```rust
-type AllPallets = (System, Balances, ..., Dpos);
-```
-
-<div>
-
-- This is used in `Executive` to dispatch pallet hooks.
-
-```rust
-<AllPallets as OnInitialize>::on_initialize();
-<AllPallets as OnInitialize>::on_finalize();
-```
-
-</div>
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Question: What will be the order of `fn on_initialize()`?
-There's also `type AllPalletsWithoutSystem` and some other variants that are no longer
-
----v
-
-### Pallet List + Outer Enums
-
-- Generates some outer types:
-
-  - `RuntimeCall`
-  - `RuntimeEvent`
-  - `RuntimeOrigin`
-  - `RuntimeGenesisConfig`
-
-Notes:
-
-See the lecture on individual item, and the "Outer Enum" lecture.
-
----v
-
-### Pallet List: `RuntimeCall` Example
-
-```rust
-// somewhere in your pallet, called `my_pallet`
-#[pallet::call]
-impl<T: Config> Pallet<T> {
-  fn transfer(origin: OriginFor<T>, from: T::AccountId, to: T::AccountId, amount: u128);
-  fn update_runtime(origin: OriginFor<T>, new_code: Vec<u8>);
-}
-```
-
-```rust
-// expanded in your pallet
-enum Call {
-  transfer { from: T::AccountId, to: T::AccountId, amount: u128 },
-  update_runtime { new_code: Vec<u8> },
-}
-```
-
-<!-- .element: class="fragment" -->
-
-```rust
-// in your outer runtime
-enum RuntimeCall {
-  System(frame_system::Call),
-  MyPallet(my_pallet::Call),
-}
-```
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Pallet List: Pallet Parts
-
-```rust [1-100|3-5]
-frame_support::construct_runtime!(
-  pub struct Runtime {
-    System: frame_system::{Pallet, Call, Config, Storage, Event<T>},
-    Balances: pallet_balances::{Pallet, Call, Storage, Config<T>, Event<T>},
-    Dpos: pallet_dpos,
-  }
-);
-```
-
-- Omitting them will exclude them from the metadata, or the "outer/runtime types"
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Pallet List: Pallet Index
-
-```rust [3-5]
-frame_support::construct_runtime!(
-  pub struct Runtime {
-    System: frame_system::{Pallet, Call, Config, Storage, Event<T>} = 1,
-    Balances: pallet_balances = 0,
-    Dpos: pallet_dpos = 2,
-  }
-);
-```
-
----
-
-## `construct_runtime`: Final Thoughts
-
-- Order in the `construct_runtime` matters!
-- Recall `integrity_test()` is called upon `construct_runtime`.
-
-```sh
-test mock::__construct_runtime_integrity_test::runtime_integrity_tests ... ok
-```
-
----v
-
-### Preview
-
-Of the next potential syntax:
-
-```rust
-#[frame::construct_runtime]
-mod runtime {
-  #[frame::runtime]
-  pub struct Runtime;
-
-  #[frame::executive]
-  pub struct Executive;
-
-  #[frame::pallets]
-  #[derive(RuntimeGenesisConfig, RuntimeCall, RuntimeOrigin)]
-  pub type AllPallets = (
-    System = frame_system = 0,
-    BalancesFoo = pallet_balances = 1,
-    BalancesBar = pallet_balances = 2,
-    Staking = pallet_staking = 42,
-  );
-}
-```
-
-Notes:
-
-See: <https://github.com/paritytech/polkadot-sdk/issues/232>
-
----
-
-# Part 2: Testing
-
----
-
-## Testing and Mocks
-
-A test requires a mock runtime, so we need to do a full `construct_runtime` 😱
-
-.. but luckily, most types can be mocked 😮‍💨
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Testing and Mocks
-
-- `u32` account id.
-- `u128` balance.
-- `u32` block number.
-- ...
-
----
-
-## Testing: `Get<_>`
-
-- Next, we want to supply some value to those `Get<_>` associated types.
-
-```rust
-#[pallet::config]
-pub trait Config: frame_system::Config {
-  type MaxVoters: Get<u32>;
-}
-```
-
----v
-
-### Testing: `Get<_>`
-
-```rust
-parameter_types! {
-  pub const MyMaxVoters: u32 = 16;
-}
-```
-
-```rust
-impl pallet_template::Config for Runtime {
-  type MaxVoters = MyMaxVoters;
-}
-```
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Testing: `Get<_>`
-
-- Or, if your value is always constant:
-
-```rust
-impl pallet_dpos::Config for Runtime {
-  type MaxVoters = frame_support::traits::ConstU32<16>;
-}
-```
-
----v
-
-### Testing: `Get<_>`
-
-- Or, if you want to torture yourself:
-
-```rust
-pub struct MyMaxVoters;
-impl Get<u32> for MyMaxVoters {
-  fn get() -> u32 {
-    100
-  }
-}
-
-impl pallet_dpos::Config for Runtime {
-  type MaxVoters = MyMaxVoters;
-}
-```
-
----
-
-## Testing: Genesis and Builder
-
-- Next, if you want to feed some data into your pallet's genesis state, we must first setup the
-  genesis config correctly.
-
-```rust
-#[pallet::genesis_config]
-#[derive(frame_support::DefaultNoBound)]
-pub struct GenesisConfig<T: Config> {
-	pub voters: Vec<(T::AccountId, Option<Vote>)>,
-}
-
-#[pallet::genesis_build]
-impl<T: Config> BuildGenesisConfig for GenesisConfig<T> {
-  fn build(&self) {
-    for (voter, maybe_vote) in &self.voters {
-      // do stuff.
-    }
-  }
-}
-```
-
----v
-
-### Testing and Mocks: Genesis and Builder
-
-- Then, we build a builder pattern to construct the genesis config.
-
-```rust
-#[derive(Default)]
-pub struct Builder {
-  pub voters: Vec<(u64, Option<Vote>)>,
-}
-```
-
-```rust
-impl Builder {
-  pub fn add_voter(mut self, who: u64) -> Self {
-    self.voters.push((who, None));
-    self
-  }
-}
-```
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Testing and Mocks: Genesis and Builder
-
-- Finally:
-
-```rust
-impl Builder {
-  pub fn build(self) -> TestExternalities {
-    let system = frame_system::GenesisConfig::<Runtime>::default();
-    let template_module = crate::GenesisConfig { voters: self.voters, ..Default::default() };
-    RuntimeGenesisConfig { system, template_module }.build_storage().unwrap().into()
-  }
-
-  pub fn build_and_execute(self, f: impl FnOnce()) {
-    let mut ext = self.build();
-    ext.execute_with(f);
-    // any post checks can come here.
-  }
-}
-```
-
----v
-
-### Testing and Mocks
-
-- Finally, this allows you to write a test like this:
-
-```rust
-#[test]
-fn test_stuff() {
-  let mut ext = Builder::default()
-    .add_voter_with_vote(2, Vote::Aye)
-    .add_voter(3)
-    build_and_execute(|| {
-      // do stuff
-    });
-}
-```
-
----
-
-## Testing: static `parameter_types!`
-
-- What if you want to change that `MyMaxVoters`?
-
-<div>
-
-```rust
-parameter_types! {
-  pub static MyMaxVoters: u32 = 100;
-}
-```
-
-```rust
-MyMaxVoters::set(200);
-MyMaxVoters::get();
-```
-
-<!-- .element: class="fragment" -->
-
-</div>
-
----
-
-## Test ing: Progressing Blocks
-
-- Often times, in your test, you want mimic the progression of an empty block.
-- De-nada! We can fake everything in tests 🤠
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Progressing Blocks
-
-```rust
-pub fn next_block() {
-  let now = System::block_number();
-  Dpos::on_finalize(now);
-  System::on_finalize(now);
-
-  System::set_block_number(now + 1);
-
-  System::on_initialize(now + 1)
-  Dpos::on_initialize(now + 1);
-}
-```
-
----v
-
-### Progressing Blocks
-
-```rust
-pub fn next_block() {
-  let now = System::block_number();
-  AllPallets::on_finalize(now);
-
-  System::set_block_number(now + 1);
-
-  AllPallets::on_initialize(now + 1)
-}
-```
-
----v
-
-### Progressing Blocks
-
-````rust
-```rust
-#[test]
-fn test() {
-  let mut ext = Builder::default()
-    .add_validator(1)
-    .set_minimum_delegation(200)
-    .build();
-  ext.execute_with(|| {
-    // initial stuff
-    next_block();
-
-    // dispatch some call
-    assert!(some_condition);
-
-    next_block();
-
-    // repeat..
-  });
-}
-````
-
-```
----
-
-## Additional Resources 😋
-
-> Check speaker notes (click "s" 😉)
-
-Notes:
-
-- This PR was actually an outcome Cambridge PBA: <https://github.com/paritytech/substrate/pull/11932>
-- <https://github.com/paritytech/substrate/pull/11818>
-- <https://github.com/paritytech/substrate/pull/10043>
-- On usage of macros un Substrate: <https://github.com/paritytech/substrate/issues/12331>
-- Discussion on advance testing: <https://forum.polkadot.network/t/testing-complex-frame-pallets-discussion-tools/356>
-- Reserve topic: Reading events.
-- Reserve-topic: try-state.
-
-### Original Lecture Script
-
-this is your bridge from a pallet into a runtime.
-
-a runtime amalgamator is composed of the following:
-
-1. all pallet's `Config` implemented by a `struct Runtime`;
-1. construct `Executive` and use it to implement all the runtime APIs
-1. Optionally, some boilerplate to setup benchmarking.
-1. invoke `construct_runtime!`.
-1. Alias for each pallet.
-
-The `construct_runtime!` itself does a few things under the hood:
-
-1. crate `struct Runtime`.
-1. amalgamate `enum RuntimeCall`; // passed inwards to some pallets that want to store calls.
-1. amalgamate `enum RuntimeEvent`; // passed inwards to all pallets.
-1. amalgamate `enum RuntimeOrigin` (this is a fixed struct, not an amalgamation);
-1. Create a very important type alias:
-
-- `type AllPallets` / `type AllPalletsWithoutSystem`
-
-1. run `integrity_test()`.
-
-> Note that there is no such thing as `RuntimeError`. Errors are not amalgamated, they just are. This should be in the error lecture.
-
-- Ordering in `construct_runtime` matters.
-- Pallet parts can be optional in `construct_runtime!`.
-```
diff --git a/content/frame/coupling/page.md b/content/frame/coupling/page.md
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-# Pallet Coupling
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/coupling/slides.md b/content/frame/coupling/slides.md
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----
-title: FRAME Pallet Coupling
-description: A look into how multiple pallets interact.
-duration: 1 hour
----
-
-# Pallet Coupling
-
----
-
-## Overview
-
-Substrate believes in building modular and composable blockchain runtimes.
-
-The building blocks of a FRAME runtime are Pallets.
-
-Pallet coupling will teach you how to configure multiple pallets to interact with each other.
-
----
-
-## Types of Coupling
-
-- Tightly Coupled Pallets
-
-  - Pallets which are directly connected to one another.
-  - You must construct a runtime using exactly the pallets which are tightly coupled.
-
-- Loosely Coupled Pallets
-
-  - Pallets which are connected "loosely" with a trait / interface.
-  - You can construct a runtime using any pallets which satisfy the required interfaces.
-
----
-
-## Tightly Coupled Pallets
-
-Tightly coupling is often an easier, but less flexible way to have two pallets interact with each other.
-
-It looks like this:
-
-```rust [2]
-#[pallet::config]
-pub trait Config: frame_system::Config + pallet_treasury::Config {
-	// -- snip --
-}
-```
-
-Note that everything is tightly coupled to `frame_system`!
-
----
-
-## What Does It Mean?
-
-If Pallet A is tightly coupled to Pallet B, then it basically means:
-
-> This Pallet A requires a runtime which is also configured with Pallet B.
-
-You do not necessarily need Pallet A to use Pallet B, but you will always need Pallet B if you use Pallet A.
-
----
-
-## Example: Treasury Pallet
-
-The Treasury Pallet is a standalone pallet which controls a pot of funds that can be distributed by the governance of the chain.
-
-There are two other pallets which are tightly coupled with the Treasury Pallet: Tips and Bounties.
-
-You can think of these like "Pallet Extensions".
-
----
-
-## Treasury, Tips, Bounties
-
-`pallet_treasury`
-
-```rust
-#[pallet::config]
-pub trait Config<I: 'static = ()>: frame_system::Config { ... }
-```
-
-`pallet_tips` & `pallet_bounties`
-
-```rust
-#[pallet::config]
-pub trait Config<I: 'static = ()>: frame_system::Config + pallet_treasury::Config<I> { ... }
-```
-
----
-
-## Tight Coupling Error
-
-Here is the kind of error you will see when you try to use a tightly coupled pallet without the appropriate pallet dependencies configured:
-
-```rust
-error[E0277]: the trait bound `Test: pallet_treasury::Config` is not satisfied
-   --> frame/sudo/src/mock.rs:149:17
-    |
-149 | impl Config for Test {
-    |                 ^^^^ the trait `pallet_treasury::Config` is not implemented for `Test`
-    |
-n o t e: required by a bound in `pallet::Config`
-   --> frame/sudo/src/lib.rs:125:43
-    |
-125 |     pub trait Config: frame_system::Config + pallet_treasury::Config{
-    |                                              ^^^^^^^^^^^^^^^^^^^^^^^ required by this bound in `Config`
-
-For more information about this error, try `rustc --explain E0277`.
-error: could not compile `pallet-sudo` due to previous error
-warning: build failed, waiting for other jobs to finish...
-```
-
----
-
-## Advantage of Tight Coupling
-
-With tight coupling, you have direct access to all public functions and interfaces of another pallet. Just like directly using a crate / module.
-
-Examples:
-
-```rust
-// Get the block number from `frame_system`
-frame_system::Pallet::<T>::block_number()
-```
-
-```rust
-// Use type configurations defined in another pallets.
-let who: T::AccountId = ensure_signed(origin)?;
-```
-
-```rust
-// Dispatch an error defined in another pallet.
-ensure!(
-	bounty.value <= max_amount,
-	pallet_treasury::Error::<T, I>::InsufficientPermission
-);
-```
-
----
-
-## When To Use Tight Coupling
-
-Tight coupling can make a lot of sense when trying to break apart a single "large" pallet into smaller, yet fully dependant pieces.
-
-As mentioned before, you can think of these as "extensions".
-
-Since there is less flexibility in how you can configure tightly coupled pallets, there is also less chance for error in configuring them.
-
----
-
-## Loosely Coupled Pallets
-
-Loose coupling is the "preferred" way to build Pallets, as it emphasizes the modular nature of Pallet development.
-
-It looks like this:
-
-```rust [3]
-#[pallet::config]
-pub trait Config<I: 'static = ()>: frame_system::Config {
-	type NativeBalance: fungible::Inspect<Self::AccountId> + fungible::Mutate<Self::AccountId>;
-
-	// -- snip --
-}
-```
-
-Here you can see that this pallet requires some associated type `NativeBalance` to be configured which implements some traits `fungible::Inspect` and `fungible::Mutate`, however there is no requirements on how or where that type is configured.
-
----
-
-## Trait Definition
-
-To begin loose coupling, you need to define a trait / interface that can be provided and depended on. A very common example is the `fungible::*` traits, which most often is implemented by `pallet_balances`.
-
-```rust
-/// Trait for providing balance-inspection access to a fungible asset.
-pub trait Inspect<AccountId>: Sized {
-	/// Scalar type for representing balance of an account.
-	type Balance: Balance;
-
-	/// The total amount of issuance in the system.
-	fn total_issuance() -> Self::Balance;
-
-	/// The total amount of issuance in the system excluding those which are controlled by the
-	/// system.
-	fn active_issuance() -> Self::Balance {
-		Self::total_issuance()
-	}
-
-	// -- snip --
-}
-```
-
-`frame/support/src/traits/tokens/fungible/regular.rs`
-
----
-
-## Trait Implementation
-
-This trait can then be implemented by a Pallet, for example `pallet_balances`.
-
-```rust
-impl<T: Config<I>, I: 'static> fungible::Inspect<T::AccountId> for Pallet<T, I> {
-	type Balance = T::Balance;
-
-	fn total_issuance() -> Self::Balance {
-		TotalIssuance::<T, I>::get()
-	}
-	fn active_issuance() -> Self::Balance {
-		TotalIssuance::<T, I>::get().saturating_sub(InactiveIssuance::<T, I>::get())
-
-	// -- snip --
-}
-```
-
-`frame/balances/src/impl_fungible.rs`
-
-Any pallet, even one you write, could implement this trait.
-
----
-
-## Trait Dependency
-
-Another pallet can then, separately, depend on this trait.
-
-```rust [3]
-#[pallet::config]
-pub trait Config: frame_system::Config {
-	type NativeBalance: fungible::Inspect<Self::AccountId> + fungible::Mutate<Self::AccountId>;
-}
-```
-
-And can use this trait throughout their pallet:
-
-```rust [4-5]
-#[pallet::weight(0)]
-pub fn transfer_all(origin: OriginFor<T>, to: T::AccountId) -> DispatchResult {
-	let from = ensure_signed(origin)?;
-	let amount = T::NativeBalance::balance(&from);
-	T::NativeBalance::transfer(&from, &to, amount, Expendable)
-}
-```
-
----
-
-## Runtime Implementation
-
-Finally, in the runtime configuration, we concretely define which pallet implements the trait.
-
-```rust
-/// Configuration of a pallet using the `fungible::*` traits.
-impl pallet_voting::Config for Runtime {
-	type RuntimeEvent = RuntimeEvent;
-	type NativeBalance = pallet_balances::Pallet<Runtime>;
-}
-```
-
-This is the place where things are no longer "loosely" defined.
-
----
-
-## Challenges of Loose Coupling
-
-Loose coupling is more difficult because you need to think ahead of time about developing a flexible API that makes sense for potentially multiple implementations.
-
-You need to try to not let implementation details affect the API, providing maximum flexibility to users and providers of those traits.
-
-When done right, it can be very powerful; like the ERC20 token format.
-
----
-
-## Challenges of Generic Types
-
-Many new pallet developers also find loose coupling challenging because associated types are not concretely defined... on purpose.
-
-For example, note that the `fungible::*` trait has a generic `Balances` type.
-
-This allows pallet developers can configure most unsigned integers types (`u32`, `u64`, `u128`) as the `Balance` type for their chain, however, this also means that you need to be more clever when doing math or other operations with those generic types.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
-Next we will look over common pallets and traits, and will see many of the pallet coupling patterns first hand.
diff --git a/content/frame/dive/page.md b/content/frame/dive/page.md
deleted file mode 100644
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-# Deep Dive
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
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diff --git a/content/frame/dive/slides.md b/content/frame/dive/slides.md
deleted file mode 100644
index eb5408a9..00000000
--- a/content/frame/dive/slides.md
+++ /dev/null
@@ -1,213 +0,0 @@
----
-title: FRAME Deep Dive
-description: FRAME, Pallets, System Pallet, Executive, Runtime Amalgamator.
-duration: 1 hour
----
-
-# FRAME Deep Dive
-
----v
-
-## Agenda
-
-Recall the following figure:
-
-<img style="height: 600px" src="./img/frame0.svg" />
-
-Notes:
-
-Without frame, there is the runtime and there is the client, and an API that sits in between.
-
----v
-
-## Agenda
-
-By the end of this lecture, you will fully understand this figure.
-
-<img style="height: 600px" src="../intro/img/frame1.svg" />
-
----
-
-## Expanding A Pallet
-
-- Grab a simple pallet code, and expand it.
-
-- `Pallet` implements the transactions as public functions.
-- `Pallet` implements `Hooks`, and some equivalents like `OnInitialize`.
-- `enum Call` that has in itself is just an encoding of the transaction's data
-
-- and implements `UnfilteredDispatchable` (which just forward the call back to `Pallet`)
-
----v
-
-### Expanding A Pallet
-
-- Make sure you understand why these 3 are the same!
-
-```rust
-let origin = ..;
-
-// function call
-Pallet::<T>::set_value(origin, 10);
-
-// dispatch
-Call::<T>::set_value(10).dispatch_bypass_filter(origin);
-
-// fully qualified syntax.
-<Call<T> as UnfilteredDispatch>::dispatch_bypass_filter(Call::<T>::set_value(10), origin);
-```
-
----
-
-## `construct_runtime!` and Runtime Amalgamator.
-
-- Now, let's look at a minimal runtime amalgamator.
-
----v
-
-### `construct_runtime!` and Runtime Amalgamator.
-
-- struct `Runtime`
-- implements the `Config` trait of all pallets.
-- implements all of the runtime APIs as functions.
-- `type System`, `type SimplePallet`.
-- `AllPalletsWithSystem` etc.
-  - and recall that all pallets implement things like `Hooks`, `OnInitialize`, and all of these traits are tuple-able.
-- enum `RuntimeCall`
-- enum `RuntimeEvent`, `GenesisConfig`, etc. but we don't have them here.
-
----
-
-## Executive
-
-- This part is somewhat optional to know in advance, but I want you to re-visit it in a week and then understand it all.
-
-- I present to you, Executive struct:
-
-```rust
-pub struct Executive<
-  System,
-  Block,
-  Context,
-  UnsignedValidator,
-  AllPalletsWithSystem,
-  OnRuntimeUpgrade = (),
->(..);
-```
-
----v
-
-#### Expanding The Generic Types.
-
-```rust
-impl<
-    // System config, we know this now.
-    System: frame_system::Config,
-    // The block type.
-    Block: sp_runtime::traits::Block<Header = System::Header, Hash = System::Hash>,
-    // Something that has all the hooks. We don't know anything else about pallets here.
-    AllPalletsWithSystem: OnRuntimeUpgrade
-      + OnInitialize<System::BlockNumber>
-      + OnIdle<System::BlockNumber>
-      + OnFinalize<System::BlockNumber>
-      + OffchainWorker<System::BlockNumber>,
-    COnRuntimeUpgrade: OnRuntimeUpgrade,
-  > Executive<System, Block, Context, UnsignedValidator, AllPalletsWithSystem, COnRuntimeUpgrade>
-where
-  // This is the juicy party, and we have to learn more sp_runtime traits to follow.
-  Block::Extrinsic: Checkable,
-  <Block::Extrinsic as Checkable>::Checked: Applyable
-  <<Block::Extrinsic as Checkable>::Checked as Applyable>::Call: Dispatchable<_>,
-{...}
-```
-
----v
-
-#### `Block::Extrinsic: Checkable`
-
-- Who implements `Checkable`?
-- That's right, the `generic::UncheckedExtrinsic` that we indeed used as `Block::Extrinsic` in the
-  top level runtime. Recall:
-
-```rust
-type UncheckedExtrinsic = generic::UncheckedExtrinsic<_, _, _, _>;
-type Header = ..
-type Block = generic::Block<Header, UncheckedExtrinsic>;
-type Executive = frame_executive::Executive<_, Block, ...>;
-```
-
----v
-
-#### What Does `Checkable<_>` Do?
-
-- Signature verification!
-
-```rust
-impl Checkable<_> for UncheckedExtrinsic<_, _, _, _> {
-  // this is the output type.
-  type Checked = CheckedExtrinsic<AccountId, Call, Extra>;
-
-  fn check(self, lookup: &Lookup) -> Result<Self::Checked, TransactionValidityError> {
-    ..
-  }
-}
-```
-
----v
-
-#### `<Block::Extrinsic as Checkable>::Checked: Applyable`
-
-- `UncheckedExtrinsic::Checked` is `CheckedExtrinsic`.
-- And it surely does implement `Applyable`.
-
----v
-
-#### What Does `Applyable<_>` Do?
-
-- TLDR: `Ok(self.call.dispatch(maybe_who.into()))`
-
----v
-
-#### Lastly: `<<Block::Extrinsic as Checkable>::Checked as Applyable>::Call: Dispatchable`
-
-- And guess who implemented `Dispatchable`, which we already looked at!
-- The `enum Call` that we had in our expanded file!
-
----v
-
-### Circling Back..
-
-So, to recap:
-
-```rust
-struct Runtime;
-
-impl frame_system::Config for Runtime {}
-impl simple_pallet::Config for Runtime {}
-
-enum Call {
-  System(frame_system::Call<Runtime>),
-  SimplePallet(simple_pallet::Call<Runtime>),
-}
-
-impl Dispatchable for Call {
-  fn dispatch(self, origin: _) -> Result<_, _> {
-    match self {
-      Call::System(system_call) => system_call.dispatch(),
-      Call::SimplePallet(simple_pallet_call) => system_pallet_call.dispatch(),
-    }
-  }
-}
-
-struct UncheckedExtrinsic {
-  function: Call,
-  signature: Option<_>,
-}
-
-type Executive = Executive<_, UncheckedExtrinsic, ...>;
-
-//
-let unchecked = UncheckedExtrinsic::new();
-let checked = unchecked.check();
-let _ = checked.apply();
-```
diff --git a/content/frame/events-errors/page.md b/content/frame/events-errors/page.md
deleted file mode 100644
index e0e0674c..00000000
--- a/content/frame/events-errors/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Events and Errors
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/events-errors/slides.md b/content/frame/events-errors/slides.md
deleted file mode 100644
index dfaa72a7..00000000
--- a/content/frame/events-errors/slides.md
+++ /dev/null
@@ -1,594 +0,0 @@
----
-title: Events and Errors
-description: FRAME Events and Errors for web3 builders.
-duration: 1 hour
----
-
-# Events and Errors
-
----
-
-## Events and Errors
-
-In this presentation, we will go over two of the tools you have access to when developing FRAME Pallets to express how your runtime calls are executing.
-
----
-
-# Errors
-
----
-
-## Intro to Errors
-
-Not all extrinsics are valid. It could be for a number of reasons:
-
-- The extrinsic itself is badly formatted. (wrong parameters, encoding, etc...)
-- The state transition function does not allow it.
-  - Maybe a timing problem.
-  - User might be lacking resources.
-  - State transition might be waiting for other data or processes.
-  - etc...
-
----
-
-## Dispatch Result
-
-All pallet calls return at the end a `DispatchResult`.
-
-From: `substrate/frame/support/src/dispatch.rs`
-
-```rust
-pub type DispatchResult = Result<(), sp_runtime::DispatchError>;
-```
-
-So a function can either return `Ok(())` or some `DispatchError`.
-
----
-
-## Dispatch Error
-
-From: `substrate/primitives/runtime/src/lib.rs`
-
-```rust [0|6-10|13-14|15-16]
-/// Reason why a dispatch call failed.
-#[derive(Eq, Clone, Copy, Encode, Decode, Debug, TypeInfo, PartialEq, MaxEncodedLen)]
-#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
-pub enum DispatchError {
-	/// Some error occurred.
-	Other(
-		#[codec(skip)]
-		#[cfg_attr(feature = "serde", serde(skip_deserializing))]
-		&'static str,
-	),
-	/// Failed to lookup some data.
-	CannotLookup,
-	/// A bad origin.
-	BadOrigin,
-	/// A custom error in a module.
-	Module(ModuleError),
-	/// At least one consumer is remaining so the account cannot be destroyed.
-	ConsumerRemaining,
-	/// There are no providers so the account cannot be created.
-	NoProviders,
-	/// There are too many consumers so the account cannot be created.
-	TooManyConsumers,
-	/// An error to do with tokens.
-	Token(TokenError),
-	/// An arithmetic error.
-	Arithmetic(ArithmeticError),
-	/// The number of transactional layers has been reached, or we are not in a transactional
-	/// layer.
-	Transactional(TransactionalError),
-	/// Resources exhausted, e.g. attempt to read/write data which is too large to manipulate.
-	Exhausted,
-	/// The state is corrupt; this is generally not going to fix itself.
-	Corruption,
-	/// Some resource (e.g. a preimage) is unavailable right now. This might fix itself later.
-	Unavailable,
-	/// Root origin is not allowed.
-	RootNotAllowed,
-}
-```
-
----
-
-## Module Errors
-
-From: `substrate/primitives/runtime/src/lib.rs`
-
-```rust
-/// The number of bytes of the module-specific `error` field defined in [`ModuleError`].
-/// In FRAME, this is the maximum encoded size of a pallet error type.
-pub const MAX_MODULE_ERROR_ENCODED_SIZE: usize = 4;
-
-/// Reason why a pallet call failed.
-#[derive(Eq, Clone, Copy, Encode, Decode, Debug, TypeInfo, MaxEncodedLen)]
-#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
-pub struct ModuleError {
-	/// Module index, matching the metadata module index.
-	pub index: u8,
-	/// Module specific error value.
-	pub error: [u8; MAX_MODULE_ERROR_ENCODED_SIZE],
-	/// Optional error message.
-	#[codec(skip)]
-	#[cfg_attr(feature = "serde", serde(skip_deserializing))]
-	pub message: Option<&'static str>,
-}
-```
-
-So an error is at most just 5 bytes.
-
----
-
-## Declaring Errors
-
-```rust [0|23-30|47-48]
-#![cfg_attr(not(feature = "std"), no_std)]
-
-pub use pallet::*;
-
-#[frame_support::pallet]
-pub mod pallet {
-	use frame_support::pallet_prelude::*;
-	use frame_system::pallet_prelude::*;
-
-	/// Configure the pallet by specifying the parameters and types on which it depends.
-	#[pallet::config]
-	pub trait Config: frame_system::Config {
-		/// Because this pallet emits events, it depends on the runtime's definition of an event.
-		type RuntimeEvent: From<Event<Self>> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
-	}
-
-	#[pallet::pallet]
-	pub struct Pallet<T>(_);
-
-	#[pallet::storage]
-	pub type CurrentOwner<T: Config> = StorageValue<_, T::AccountId>;
-
-	// Errors inform users that something went wrong.
-	#[pallet::error]
-	pub enum Error<T> {
-		/// There is currently no owner set.
-		NoOwner,
-		/// The calling user is not authorized to make this call.
-		NotAuthorized,
-	}
-
-	#[pallet::event]
-	#[pallet::generate_deposit(pub(super) fn deposit_event)]
-	pub enum Event<T: Config> {
-		/// The owner has been updated.
-		OwnerChanged,
-	}
-
-	#[pallet::call]
-	impl<T: Config> Pallet<T> {
-		/// This function allows the current owner to set a new owner.
-		/// If there is no owner, this function will return an error.
-		#[pallet::weight(u64::default())]
-		#[pallet::call_index(0)]
-		pub fn change_ownership(origin: OriginFor<T>, new: T::AccountId) -> DispatchResult {
-			let who = ensure_signed(origin)?;
-			let current_owner = CurrentOwner::<T>::get().ok_or(Error::<T>::NoOwner)?;
-			ensure!(current_owner == who, Error::<T>::NotAuthorized);
-			CurrentOwner::<T>::put(new);
-			Self::deposit_event(Event::<T>::OwnerChanged);
-			Ok(())
-		}
-	}
-}
-```
-
----
-
-## Using Errors
-
-When writing tests, you can use errors to make sure that your functions execute exactly as expected.
-
-```rust
-#[test]
-fn errors_example() {
-	new_test_ext().execute_with(|| {
-		assert_noop!(TemplateModule::change_ownership(Origin::signed(1), 2), Error::<T>::NoOwner);
-		CurrentOwner::<T>::put(1);
-		assert_ok!(TemplateModule::change_ownership(Origin::signed(1), 2));
-		assert_noop!(TemplateModule::change_ownership(Origin::signed(1), 2), Error::<T>::NotAuthorized);
-	});
-}
-```
-
----
-
-## Encoding Errors
-
-All errors ultimately become a `DispatchError`, which is the final type returned by the runtime.
-
-```rust
-println!("{:?}", Error::<T>::NoOwner.encode());
-println!("{:?}", Error::<T>::NotAuthorized.encode());
-let dispatch_error1: DispatchError = Error::<T>::NoOwner.into();
-let dispatch_error2: DispatchError = Error::<T>::NotAuthorized.into();
-println!("{:?}", dispatch_error1.encode());
-println!("{:?}", dispatch_error2.encode());
-```
-
-```sh
-[0]
-[1]
-[3, 1, 0, 0, 0, 0]
-[3, 1, 1, 0, 0, 0]
-```
-
----
-
-## Dispatch Error Encoding
-
-<table>
-<tr>
-	<td>3</td>
-	<td>1</td>
-	<td>1</td>
-	<td>0</td>
-	<td>0</td>
-	<td>0</td>
-</tr>
-<tr>
-	<td>DispatchError::Module</td>
-	<td>Pallet #2</td>
-	<td>Error #2</td>
-	<td>(unused)</td>
-	<td>(unused)</td>
-	<td>(unused)</td>
-</tr>
-</table>
-
-Encoding based on configuration:
-
-<div class="flex-container">
-<div class="left" style="max-width: 700px;">
-
-```rust
-// Configure a mock runtime to test the pallet.
-frame_support::construct_runtime!(
-	pub struct Test {
-		System: frame_system::{Pallet, Call, Config, Storage, Event<T>},
-		TemplateModule: pallet_template,
-	}
-);
-```
-
-</div>
-<div class="right" style="margin-left: 10px; max-width: 700px;">
-
-```rust
-// Errors inform users that something went wrong.
-#[pallet::error]
-pub enum Error<T> {
-	/// There is currently no owner set.
-	NoOwner,
-	/// The calling user is not authorized to make this call.
-	NotAuthorized,
-}
-```
-
-</div>
-</div>
----
-
-## Nested Errors
-
-Errors support up to 5 bytes, which allows you to create nested errors, or insert other minimal data with the `PalletError` derive macro.
-
-```rust
-#[derive(Encode, Decode, PalletError, TypeInfo)]
-pub enum SubError {
-	SubError1,
-	SubError2,
-	SubError3,
-}
-
-use frame_system::pallet::Error as SystemError;
-
-// Errors inform users that something went wrong.
-#[pallet::error]
-pub enum Error<T> {
-	/// There is currently no owner set.
-	NoOwner,
-	/// The calling user is not authorized to make this call.
-	NotAuthorized,
-	/// Errors coming from another place.
-	SubError(SubError),
-	/// Errors coming from another place.
-	SystemError(SystemError<T>),
-	/// Some Error with minimal data
-	DataError(u16),
-}
-```
-
-Notes:
-
-<https://github.com/paritytech/substrate/pull/10242>
-
----
-
-# Events
-
----
-
-## Intro to Events
-
-When an extrinsic completes successfully, there is often some metadata you would like to expose to the outside world about what exactly happened during the execution.
-
-For example, there may be multiple different ways an extrinsic completes successfully, and you want the user to know what happened.
-
-Or maybe there is some significant state transition that you know users
-
----
-
-## Declaring and Emitting Events
-
-```rust [10-15|32-37|50]
-#![cfg_attr(not(feature = "std"), no_std)]
-
-pub use pallet::*;
-
-#[frame_support::pallet]
-pub mod pallet {
-	use frame_support::pallet_prelude::*;
-	use frame_system::pallet_prelude::*;
-
-	/// Configure the pallet by specifying the parameters and types on which it depends.
-	#[pallet::config]
-	pub trait Config: frame_system::Config {
-		/// Because this pallet emits events, it depends on the runtime's definition of an event.
-		type RuntimeEvent: From<Event<Self>> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
-	}
-
-	#[pallet::pallet]
-	pub struct Pallet<T>(_);
-
-	#[pallet::storage]
-	pub type CurrentOwner<T: Config> = StorageValue<_, T::AccountId>;
-
-	// Errors inform users that something went wrong.
-	#[pallet::error]
-	pub enum Error<T> {
-		/// There is currently no owner set.
-		NoOwner,
-		/// The calling user is not authorized to make this call.
-		NotAuthorized,
-	}
-
-	#[pallet::event]
-	#[pallet::generate_deposit(pub(super) fn deposit_event)]
-	pub enum Event<T: Config> {
-		/// The owner has been updated.
-		OwnerChanged,
-	}
-
-	#[pallet::call]
-	impl<T: Config> Pallet<T> {
-		/// This function allows the current owner to set a new owner.
-		/// If there is no owner, this function will return an error.
-		#[pallet::weight(u64::default())]
-		#[pallet::call_index(0)]
-		pub fn change_ownership(origin: OriginFor<T>, new: T::AccountId) -> DispatchResult {
-			let who = ensure_signed(origin)?;
-			let current_owner = CurrentOwner::<T>::get().ok_or(Error::<T>::NoOwner)?;
-			ensure!(current_owner == who, Error::<T>::NotAuthorized);
-			CurrentOwner::<T>::put(new);
-			Self::deposit_event(Event::<T>::OwnerChanged);
-			Ok(())
-		}
-	}
-}
-```
-
----
-
-## Deposit Event
-
-```rust
-#[pallet::generate_deposit(pub(super) fn deposit_event)]
-```
-
-Simply generates:
-
-```rust
-impl<T: Config> Pallet<T> {
-	pub(super) fn deposit_event(event: Event<T>) {
-		let event = <<T as Config>::Event as From<Event<T>>>::from(event);
-		let event =
-			<<T as Config>::Event as Into<<T as frame_system::Config>::Event>>::into(event);
-		<frame_system::Pallet<T>>::deposit_event(event)
-	}
-}
-```
-
-<br />
-
-`frame/support/procedural/src/pallet/expand/event.rs`
-
----
-
-## Deposit Event in System
-
-Events are just a storage item in FRAME System.
-
-`frame/system/src/lib.rs`
-
-```rust
-/// Events deposited for the current block.
-///
-/// N O T E: The item is unbound and should therefore never be read on chain.
-/// It could otherwise inflate the PoV size of a block.
-///
-/// Events have a large in-memory size. Box the events to not go out-of-memory
-/// just in case someone still reads them from within the runtime.
-#[pallet::storage]
-pub(super) type Events<T: Config> =
-	StorageValue<_, Vec<Box<EventRecord<T::RuntimeEvent, T::Hash>>>, ValueQuery>;
-
-/// The number of events in the `Events<T>` list.
-#[pallet::storage]
-#[pallet::getter(fn event_count)]
-pub(super) type EventCount<T: Config> = StorageValue<_, EventIndex, ValueQuery>;
-```
-
----
-
-## Deposit Events in System
-
-Depositing events ultimately just appends a new event to this storage.
-
-`frame/system/src/lib.rs`
-
-```rust [0|1-4|34|13-16]
-/// Deposits an event into this block's event record.
-pub fn deposit_event(event: impl Into<T::RuntimeEvent>) {
-	Self::deposit_event_indexed(&[], event.into());
-}
-
-/// Deposits an event into this block's event record adding this event
-/// to the corresponding topic indexes.
-///
-/// This will update storage entries that correspond to the specified topics.
-/// It is expected that light-clients could subscribe to this topics.
-pub fn deposit_event_indexed(topics: &[T::Hash], event: T::RuntimeEvent) {
-	let block_number = Self::block_number();
-	// Don't populate events on genesis.
-	if block_number.is_zero() {
-		return
-	}
-
-	let phase = ExecutionPhase::<T>::get().unwrap_or_default();
-	let event = EventRecord { phase, event, topics: topics.to_vec() };
-
-	// Index of the to be added event.
-	let event_idx = {
-		let old_event_count = EventCount::<T>::get();
-		let new_event_count = match old_event_count.checked_add(1) {
-			// We've reached the maximum number of events at this block, just
-			// don't do anything and leave the event_count unaltered.
-			None => return,
-			Some(nc) => nc,
-		};
-		EventCount::<T>::put(new_event_count);
-		old_event_count
-	};
-
-	Events::<T>::append(event);
-
-	for topic in topics {
-		<EventTopics<T>>::append(topic, &(block_number, event_idx));
-	}
-}
-```
-
----
-
-## You Cannot Read Events
-
-- The events storage are an unbounded vector of individual events emitted by your pallets.
-- If you ever read this storage, you will introduce the whole thing into your storage proof!
-- Never write runtime logic which reads from or depends on events.
-- Tests are okay.
-
----
-
-## You Cannot Read Events
-
-`frame/system/src/lib.rs`
-
-```rust
-/// Get the current events deposited by the runtime.
-///
-/// Should only be called if you know what you are doing and outside of the runtime block
-/// execution else it can have a large impact on the PoV size of a block.
-pub fn read_events_no_consensus(
-) -> impl sp_std::iter::Iterator<Item = Box<EventRecord<T::RuntimeEvent, T::Hash>>> {
-	Events::<T>::stream_iter()
-}
-
-/// Get the current events deposited by the runtime.
-///
-/// NOTE: This should only be used in tests. Reading events from the runtime can have a large
-/// impact on the PoV size of a block. Users should use alternative and well bounded storage
-/// items for any behavior like this.
-///
-/// NOTE: Events not registered at the genesis block and quietly omitted.
-#[cfg(any(feature = "std", feature = "runtime-benchmarks", test))]
-pub fn events() -> Vec<EventRecord<T::RuntimeEvent, T::Hash>> {
-	debug_assert!(
-		!Self::block_number().is_zero(),
-		"events not registered at the genesis block"
-	);
-	// Dereferencing the events here is fine since we are not in the
-	// memory-restricted runtime.
-	Self::read_events_no_consensus().map(|e| *e).collect()
-}
-```
-
----
-
-## Testing Events
-
-Remember to set the block number to greater than zero!
-
-Some tools in FRAME System for you:
-
-`frame/system/src/lib.rs`
-
-```rust
-/// Set the block number to something in particular. Can be used as an alternative to
-/// `initialize` for tests that don't need to bother with the other environment entries.
-#[cfg(any(feature = "std", feature = "runtime-benchmarks", test))]
-pub fn set_block_number(n: BlockNumberFor<T>) {
-	<Number<T>>::put(n);
-}
-
-/// Assert the given `event` exists.
-#[cfg(any(feature = "std", feature = "runtime-benchmarks", test))]
-pub fn assert_has_event(event: T::RuntimeEvent) {
-	assert!(Self::events().iter().any(|record| record.event == event))
-}
-
-/// Assert the last event equal to the given `event`.
-#[cfg(any(feature = "std", feature = "runtime-benchmarks", test))]
-pub fn assert_last_event(event: T::RuntimeEvent) {
-	assert_eq!(Self::events().last().expect("events expected").event, event);
-}
-```
-
----
-
-## Using Events in Tests
-
-```rust
-#[test]
-fn events_example() {
-	new_test_ext().execute_with(|| {
-		frame_system::Pallet::<T>::set_block_number(1);
-		CurrentOwner::<T>::put(1);
-		assert_ok!(TemplateModule::change_ownership(Origin::signed(1), 2));
-		assert_ok!(TemplateModule::change_ownership(Origin::signed(2), 3));
-		assert_ok!(TemplateModule::change_ownership(Origin::signed(3), 4));
-
-		let events = frame_system::Pallet::<T>::events();
-		assert_eq!(events.len(), 3);
-		frame_system::Pallet::<T>::assert_has_event(crate::Event::<T>::OwnerChanged { old: 1, new: 2}.into());
-		frame_system::Pallet::<T>::assert_last_event(crate::Event::<T>::OwnerChanged { old: 3, new: 4}.into());
-	});
-}
-```
-
-Remember other pallets can deposit events too!
-
----
-
-## Summary
-
-- Events and Errors are two ways you can signal to users what is happening when they dispatch an extrinsic.
-- Events usually signify some successful thing happening.
-- Errors signify when something has gone bad (and all changes reverted).
-- Both are accessible by the end user when they occur.
diff --git a/content/frame/extensions/page.md b/content/frame/extensions/page.md
deleted file mode 100644
index 3574a057..00000000
--- a/content/frame/extensions/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Signed Extensions
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/extensions/slides.md b/content/frame/extensions/slides.md
deleted file mode 100644
index c4962dc7..00000000
--- a/content/frame/extensions/slides.md
+++ /dev/null
@@ -1,342 +0,0 @@
----
-title: Signed Extensions
-description: Signed Extensions, Transaction Priority.
----
-
-# Signed Extensions
-
----v
-
-- In this lecture you will learn above one of the most advance FRAME concepts, _Signed Extensions_.
-
-* They allow for a multitude of custom features to be added to FRAME transactions.
-
----
-
-## History
-
-- Signed Extensions originally where added to implement tipping in a reasonable way.
-
-* Originally, your dumb instructor (@kianenigma) had the idea of hard-coding it into the `UncheckedExtrinsic`, until @gavofyork jumped in with the idea of signed extensions.
-
-> [Tipped Transaction Type. by kianenigma · Pull Request #2930 · paritytech/substrate](https://github.com/paritytech/substrate/pull/2930/files) > [Extensible transactions (and tips) by gavofyork · Pull Request #3102 · paritytech/substrate](https://github.com/paritytech/substrate/pull/3102/files)
-
----v
-
-### History
-
-- In essence, they are a generic way to **extend** the transaction. Moreover, if they have additional payload, it is signed, therefore _`SignedExtension`_.
-
----
-
-## Anatomy
-
-A signed extension can be either combination of the following things:
-
-- Some additional data that is attached to the transaction.
-  - The tip!
-
-<!-- .element: class="fragment" -->
-
-- Some hooks that are executed before and after the transaction is executed.
-  - Before each transaction is executed, it must pay its fee upfront.
-  - Perhaps refund the fee partially 🤑.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Anatomy
-
-- Some additional validation logic that is used to validate the transaction, and give feedback to the pool.
-  - Set priority of transaction priority based on some metric!
-
-<!-- .element: class="fragment" -->
-
-- Some additional data that must be present in the signed payload of each transaction.
-  - Data that the sender has, the chain also has, it is not communicated itself, but it is part of the signature payload.
-  - Spec version and genesis hash is part of all transaction's signature payload!
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Anatomy: Let's Peek at the Trait
-
-```rust [1-100|4|6-7|9-10|12]
-pub trait SignedExtension:
-	Codec + Debug + Sync + Send + Clone + Eq + PartialEq + StaticTypeInfo
-{
-	fn additional_signed(&self) -> Result<Self::AdditionalSigned, TransactionValidityError>;
-
-	fn validate(..) -> TransactionValidity;
-	fn validate_unsigned(..) -> TransactionValidity;
-
-	fn pre_dispatch() -> Result<Self::Pre, TransactionValidityError>;
-	fn pre_dispatch_unsigned() -> Result<(), TransactionValidityError>;
-
-	fn post_dispatch() -> Result<(), TransactionValidityError>;
-}
-```
-
----
-
-## Grouping Signed Extension
-
-- Is also a signed extension itself!
-
-- You can look at the implementation yourself.. but the TLDR is:
-
-- Main takeaways:
-  - `type AdditionalSigned = (SE1::AdditionalSigned, SE2::AdditionalSigned)`,
-  - all of hooks:
-    - Executes each individually, combines results
-
-Notes:
-
-TODO: how `TransactionValidity` is `combined_with` is super important here, but probably something to cover more in 4.3 and recap here.
-
----v
-
-## Usage In The Runtime
-
-- Each runtime has a bunch of signed extensions. They can be grouped as a tuple
-
-```rust
-pub type SignedExtra = (
-	frame_system::CheckNonZeroSender<Runtime>,
-	frame_system::CheckSpecVersion<Runtime>,
-	frame_system::CheckTxVersion<Runtime>,
-	frame_system::CheckGenesis<Runtime>,
-	pallet_asset_tx_payment::ChargeAssetTxPayment<Runtime>,
-);
-
-type UncheckedExtrinsic = generic::UncheckedExtrinsic<Address, Call, Signature, SignedExtra>;
-```
-
-- Signed extensions might originate from a pallet, but are applied to ALL EXTRINSICS 😮‍💨!
-
-Notes:
-
-We will get to this later as well, but recall that SignedExtensions are not a _FRAME/Pallet_
-concept per se. FRAME just implements them. This also implies that everything regarding signed
-extensions is applied to **all transactions**, throughout the runtime.
-
----
-
-## Encoding
-
-```rust
-struct Foo(u32, u32);
-impl SignedExtension for Foo {
-  type AdditionalSigned = u32;
-  fn additional_signed(&self) -> Result<Self::AdditionalSigned, TransactionValidityError> {
-    Ok(42u32)
-  }
-}
-
-pub struct UncheckedExtrinsic<Address, Call, Signature, (Foo)>
-{
-	pub signature: Option<(Address, Signature, Extra)>,
-	pub function: Call,
-}
-```
-
-- 2 u32 are decoded as, `42u32` is expected to be in the signature payload.
-
-Notes:
-
-Here's the `check` function of `CheckedExtrinsic` extensively documented to demonstrate this:
-
-```rust
-// SignedPayload::new
-pub fn new(call: Call, extra: Extra) -> Result<Self, TransactionValidityError> {
-	// asks all signed extensions to give their additional signed data..
-	let additional_signed = extra.additional_signed()?;
-	// this essentially means: what needs to be signed in the signature of the transaction is:
-	// 1. call
-	// 2. signed extension data itself
-	// 3. any additional signed data.
-	let raw_payload = (call, extra, additional_signed);
-	Ok(Self(raw_payload))
-}
-
-// UncheckedExtrinsic::check
-fn check(self, lookup: &Lookup) -> Result<Self::Checked, TransactionValidityError> {
-	Ok(match self.signature {
-		Some((signed, signature, extra)) => {
-			let signed = lookup.lookup(signed)?;
-			// this is the payload that we expect to be signed, as explained above.
-			let raw_payload = SignedPayload::new(self.function, extra)?;
-			// encode the signed payload, and check it against the signature.
-			if !raw_payload.using_encoded(|payload| signature.verify(payload, &signed)) {
-				return Err(InvalidTransaction::BadProof.into())
-			}
-
-			// the extra is passed again to `CheckedExtrinsic`, see in the next section.
-			let (function, extra, _) = raw_payload.deconstruct();
-			CheckedExtrinsic { signed: Some((signed, extra)), function }
-		},
-		// we don't care about signed extensions at all.
-		None => CheckedExtrinsic { signed: None, function: self.function },
-	})
-}
-```
-
----
-
-## Transaction Pool Validation
-
-- Each pallet also has `#[pallet::validate_unsigned]`.
-- This kind of overlaps with creating a signed extension and implementing `validate_unsigned`.
-
-Notes:
-
-- <https://github.com/paritytech/substrate/issues/6102>
-- <https://github.com/paritytech/polkadot-sdk/issues/365>
-
----v
-
-### Transaction Pool Validation
-
-- Recall that transaction pool validation should be minimum effort and static.
-- In `executive`, we only do the following:
-  - check signature.
-  - call `Extra::validate`/`Extra::validate_unsigned`
-  - call `ValidateUnsigned::validate`, if unsigned.
-  - NOTE dispatching ✅!
-
-Notes:
-
-> Transaction queue is not part of the consensus system. Validation of transaction are _free_. Doing
-> too much work in validation of transactions is essentially opening a door to be DOS-ed.
-
----v
-
-### Transaction Pool Validation
-
-- Crucially, you should make sure that you re-execute anything that you do in transaction pool validation in dispatch as well:
-
-```rust
-/// Do any pre-flight stuff for a signed transaction.
-///
-/// Make sure to perform the same checks as in [`Self::validate`].
-fn pre_dispatch() -> Result<Self::Pre, TransactionValidityError>;
-```
-
-- Because conditions that are not stateless might change over time!
-
----
-
-## Post Dispatch
-
-- The dispatch result, plus generic type (`type Pre`) returned from `pre_dispatch` is passed to `post_dispatch`.
-- See [`impl Applyable for CheckedExtrinsic`](https://github.com/paritytech/polkadot-sdk/blob/bc53b9a/substrate/primitives/runtime/src/generic/checked_extrinsic.rs#L69) for more info.
-
----
-
-## Notable Signed Extensions
-
-- These are some of the default signed extensions that come in FRAME.
-- See if you can predict how they are made!
-
----v
-
-### `ChargeTransactionPayment`
-
-Charge payments, refund if `Pays::Yes`.
-
-```rust
-type Pre = (
-  // tip
-  BalanceOf<T>,
-  // who paid the fee - this is an option to allow for a Default impl.
-  Self::AccountId,
-  // imbalance resulting from withdrawing the fee
-  <<T as Config>::OnChargeTransaction as OnChargeTransaction<T>>::LiquidityInfo,
-);
-```
-
-<!-- .element: class="fragment" -->
-
----v
-
-### `check_genesis`
-
-Wants to make sure you are signing against the right chain.
-
-Put the genesis hash in `additional_signed`.
-
-<!-- .element: class="fragment" -->
-
-`check_spec_version` and `check_tx_version` work very similarly.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### `check_non_zero_sender`
-
-- interesting story: any account can sign on behalf of the `0x00` account.
-- discovered by [@xlc](https://github.com/xlc).
-- uses `pre_dispatch` and `validate` to ensure the signing account is not `0x00`.
-
-Notes:
-
-<https://github.com/paritytech/substrate/pull/10413>
-
----v
-
-### `check_nonce`
-
-- `pre_dispatch`: check nonce and actually update it.
-- `validate`: check the nonce, DO NOT WRITE ANYTHING, set `provides` and `requires`.
-
-<!-- .element: class="fragment" -->
-
-<div>
-
-- remember that:
-  - `validate` is only for lightweight checks, no read/write.
-  - anything you write to storage is reverted anyhow.
-
-</div>
-
-<!-- .element: class="fragment" -->
-
----v
-
-### `check_weight`
-
-- Check there is enough weight in `validate`.
-- Check there is enough weight, and update the consumed weight in `pre_dispatch`.
-- Updated consumed weight in `post_dispatch`.
-
-<!-- .element: class="fragment" -->
-
----
-
-## Big Picture: Pipeline of Extension
-
-- Signed extensions (or at least the `pre_dispatch` and `validate` part) remind me of the extension
-  system of `express.js`, if any of you know what that is
-
----v
-
-## Big Picture: Pipeline of Extension
-
-<img rounded src="./img/signed-extensions.svg" />
-
----
-
-## Exercises
-
-- Walk over the notable signed extensions above and riddle each other about how they work.
-- SignedExtensions are an important part of the transaction encoding. Try and encode a correct
-  transaction against a template runtime in any language that you want, using only a scale-codec
-  library.
-- SignedExtensions that logs something on each transaction
-- SignedExtension that keeps a counter of all transactions
-- SignedExtensions that keeps a counter of all successful/failed transactions
-- SignedExtension that tries to refund the transaction from each account as long as they submit less
-  than 1tx/day.
diff --git a/content/frame/extras/page.md b/content/frame/extras/page.md
deleted file mode 100644
index a4b2e760..00000000
--- a/content/frame/extras/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Extras
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/hooks/page.md b/content/frame/hooks/page.md
deleted file mode 100644
index 5b220161..00000000
--- a/content/frame/hooks/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Hooks
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/hooks/slides.md b/content/frame/hooks/slides.md
deleted file mode 100644
index d05500e7..00000000
--- a/content/frame/hooks/slides.md
+++ /dev/null
@@ -1,495 +0,0 @@
----
-title: FRAME/Pallet Hooks
-description: FRAME/Pallet Hooks
-duration: 1 hour
----
-
-# 🪝 FRAME/Pallet Hooks 🪝
-
----
-
-## Hooks: All In One
-
-- Onchain / STF
-  - `on_runtime_upgrade`
-  - `on_initialize`
-  - `poll` (WIP)
-  - `on_finalize`
-  - `on_idle`
-- Offchain:
-  - `genesis_build`
-  - `offchain_worker`
-  - `integrity_test`
-  - `try_state`
-
-Notes:
-
-<https://paritytech.github.io/substrate/master/frame_support/traits/trait.Hooks.html>
-
----v
-
-### Hooks: All In One
-
-```rust
-#[pallet::hooks]
-impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
-  fn on_runtime_upgrade() -> Weight {}
-  fn on_initialize() -> Weight {}
-  fn on_finalize() {}
-  fn on_idle(remaining_weight: Weight) -> Weight {}
-  fn offchain_worker() {}
-  fn integrity_test() {}
-  #[cfg(feature = "try-runtime")]
-  fn try_state() -> Result<(), &'static str> {}
-}
-
-#[pallet::genesis_build]
-impl<T: Config> BuildGenesisConfig for GenesisConfig<T> {
-	fn build(&self) {}
-}
-```
-
-Notes:
-
-Many of these functions receive the block number as an argument, but that can easily be fetched from
-`frame_system::Pallet::<T>::block_number()`
-
----
-
-## Hooks: `on_runtime_upgrade`
-
-- Called every time the `spec_version`/`spec_name` is bumped.
-- Why would might you be interested in implementing this?
-
-Notes:
-
-Because very often runtime upgrades needs to be accompanied by some kind of state migration.
-Has its own lecture, more over there.
-
----
-
-## Hooks: `on_initialize`
-
-- Useful for any kind of **automatic** operation.
-- The weight you return is interpreted as `DispatchClass::Mandatory`.
-
----v
-
-### Hooks: `On_Initialize`
-
-- `Mandatory` Hooks should really be lightweight and predictable, with a bounded complexity.
-
-```rust
-fn on_initialize() -> Weight {
-  // any user can create one entry in `MyMap` 😱🔫.
-  <MyMap<T>>::iter().for_each(do_stuff);
-}
-```
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Hooks: `On_Initialize`
-
-- &shy;<!-- .element: class="fragment" --> Question: If you have 3 pallets, in which order their `on_initialize` are called?
-- &shy;<!-- .element: class="fragment" --> Question: If your runtime panics `on_initialize`, how can you recover from it?
-- &shy;<!-- .element: class="fragment" --> Question: If your `on_initialize` consumes more than the maximum block weight?
-
-Notes:
-
-- The order comes from `construct_runtime!` macro.
-- Panic in mandatory hooks is fatal error. You are pretty much done.
-- Overweight blocks using mandatory hooks, are possible, ONLY in the context of solo-chains. Such a
-  block will take longer to produce, but it eventually will. If you have your eyes set on being a
-  parachain developer, you should treat overweight blocks as fatal as well.
-
----
-
-## Hooks: `on_finalize`
-
-- Extension of `on_initialize`, but at the end of the block.
-- Its weight needs to be known in advance. Therefore, less preferred compared to `on_initialize`.
-
-```rust
-fn on_finalize() {} // ✅
-fn on_finalize() -> Weight {} // ❌
-```
-
-<!-- .element: class="fragment" -->
-
-- Nothing to do with _finality_ in the consensus context.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Hooks: `on_finalize`
-
-> Generally, avoid using it unless if something REALLY needs to be happen at the end of the block.
-
-Notes:
-
-Sometimes, rather than thinking "at the end of block N", consider writing code "at the beginning of block N+1"
-
----
-
-## Hooks: `poll`
-
-- The non-mandatory version of `on_initialize`.
-- In the making 👷
-
-Notes:
-
-See: <https://github.com/paritytech/substrate/pull/14279> and related PRs
-
----
-
-## Hooks: `on_idle`
-
-- **_Optional_** variant of `on_finalize`, also executed at the end of the block.
-- Small semantical difference: executes one pallet's hook, per block, randomly, rather than all
-  pallets'.
-
----v
-
-## The Future: Moving Away From Mandatory Hooks
-
-- `on_initialize` -> `poll`
-- `on_finalize` -> `on_idle`
-- New primitives for multi-block migrations
-- New primitives for optional service work via extrinsics.
-
-Notes:
-
-This is all in the agenda of the FRAME team at Parity for 2023.
-
-<https://github.com/paritytech/polkadot-sdk/issues/206>
-<https://github.com/paritytech/polkadot-sdk/issues/198>
-
----
-
-## Recap: Onchain/STF Hooks
-
-<diagram class="mermaid">
-%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
-graph LR
-    subgraph AfterTransactions
-        direction LR
-        OnIdle --> OnFinalize
-    end
-
-    subgraph OnChain
-        direction LR
-        Optional --> BeforeExtrinsics
-        BeforeExtrinsics --> Inherents
-        Inherents --> Poll
-        Poll --> Transactions
-        Transactions --> AfterTransactions
-    end
-
-    subgraph Optional
-
-OnRuntimeUpgrade
-end
-
-    subgraph BeforeExtrinsics
-        OnInitialize
-    end
-
-    subgraph Transactions
-        Transaction1 --> UnsignedTransaction2 --> Transaction3
-    end
-
-    subgraph Inherents
-        Inherent1 --> Inherent2
-    end
-
-</diagram>
-
-Notes:
-
-implicit in this:
-
-Inherents are only first, which was being discussed: <https://github.com/polkadot-fellows/RFCs/pull/13>
-
----
-
-## Hooks: `genesis_build`
-
-- Means for each pallet to specify a $f(input): state$ at genesis.
-- This is called only once, by the client, when you **create a new chain**.
-  - &shy;<!-- .element: class="fragment" --> Is this invoked every time you run `cargo run`?
-- `#[pallet::genesis_build]`.
-
----v
-
-### Hooks: `genesis_build`
-
-```rust
-#[pallet::genesis_build]
-pub struct GenesisConfig<T: Config> {
-  pub foo: Option<u32>,
-  pub bar: Vec<u8>,
-}
-```
-
-<!-- .element: class="fragment" -->
-
-```rust
-impl<T: Config> Default for GenesisConfig<T> {
-  fn default() -> Self {
-    // snip
-  }
-}
-```
-
-<!-- .element: class="fragment" -->
-
-```rust
-#[pallet::genesis_build]
-impl<T: Config> GenesisBuild<T> for GenesisConfig<T> {
-  fn build(&self) {
-    // use self.foo, self.bar etc.
-  }
-}
-```
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Hooks: `genesis_build`
-
-- `GenesisConfig` is a composite/amalgamated item at the top level runtime.
-
-```rust
-construct_runtime!(
-  pub enum Runtime where {
-    System: frame_system,
-    Balances: pallet_balances,
-  }
-);
-```
-
-```rust
-struct RuntimeGenesisConfig {
-  SystemConfig: pallet_system::GenesisConfig,
-  PalletAConfig: pallet_a::GenesisConfig,
-}
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-<https://paritytech.github.io/substrate/master/node_template_runtime/struct.RuntimeGenesisConfig.html>
-
----v
-
-### Hooks: `genesis_build`
-
-- Recent changes moving `genesis_build` to be used over a runtime API, rather than native runtime.
-- `#[cfg(feature = "std")]` in pallets will go away.
-
-Notes:
-
-<https://github.com/paritytech/polkadot-sdk/issues/25>
-
----
-
-## Hooks: `offchain_worker`
-
-**Fully offchain application**:
-
-- Read chain state via RPC.
-- submit desired side effects back to the chain as transactions.
-
-**Runtime Offchain Worker**:
-
-- &shy;<!-- .element: class="fragment" --> Code lives onchain, upgradable only in synchrony with the whole runtime 👎
-- &shy;<!-- .element: class="fragment" --> Ergonomic and fast state access 👍
-- &shy;<!-- .element: class="fragment" --> State writes are ignored 🤷
-- &shy;<!-- .element: class="fragment" --> Can submit transactions back to the chain as well ✅
-- &shy;<!-- .element: class="fragment" --> Source of many confusions!
-
-Notes:
-
-People have often thought that they can do magic with things with OCW, please don't. BIG warning to
-founders to be careful with this!
-
-<https://paritytech.github.io/substrate/master/pallet_examples/index.html>
-
----v
-
-### Hooks: `offchain_worker`
-
-- Execution entirely up to the client.
-- Has a totally separate thread pool than the normal execution.
-
-```
---offchain-worker <ENABLED>
-    Possible values:
-    - always:
-    - never:
-    - when-authority
-
---execution-offchain-worker <STRATEGY>
-    Possible values:
-    - native:
-    - wasm:
-    - both:
-    - native-else-wasm:
-```
-
----v
-
-### Hooks: `offchain_worker`
-
-- Threads can **overlap**, each is reading the state of its corresponding block
-
-<img style="height: 500px" src="./img/ocw.svg"  />
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-<https://paritytech.github.io/substrate/master/sp_runtime/offchain/storage_lock/index.html>
-
----v
-
-### Hooks: `offchain_worker`
-
-- &shy;<!-- .element: class="fragment" -->Offchain workers have their own **special host
-  functions**: http, dedicated storage, time, etc.
-- &shy;<!-- .element: class="fragment" -->Offchain workers have the same **execution limits** as
-  Wasm (limited memory, custom allocator).
-
-- &shy;<!-- .element: class="fragment" -->Source of confusion, why OCWs cannot write to state.
-
-Notes:
-
-These are the source of the confusion.
-
-Word on allocator limit in Substrate Wasm execution (subject to change).
-
-- Max single allocation limited
-- Max total allocation limited.
-
----
-
-## Hooks: `integrity_test`
-
-- Put into a test by `construct_runtime!`.
-
-```rust
-__construct_runtime_integrity_test::runtime_integrity_tests
-```
-
-<!-- .element: class="fragment" -->
-
-```rust
-fn integrity_test() {
-  assert!(
-    T::MyConfig::get() > 0,
-    "Are all of the generic types I have sensible?"
-  );
-  // notice that this is for tests, std is available.
-  assert!(std::mem::size_of::<T::Balance>() > 4);
-}
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-I am in fan of renaming this. If you are too, please comment here
-
----
-
-## Hooks: `try_state`
-
-- A means for you to ensure correctness of your $STF$, after each transition.
-- &shy;<!-- .element: class="fragment" -->Entirely offchain, custom runtime-apis, conditional
-  compilation.
-  - &shy;<!-- .element: class="fragment" -->Called from `try-runtime-cli`, which you will learn about next week, or anyone else
-- &shy;<!-- .element: class="fragment" -->Examples from your assignment?
-
-Notes:
-
-What is a transition? Either a block, or single extrinsic
-
----
-
-## Hooks: Recap
-
-<diagram class="mermaid">
-%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
-graph LR
-    subgraph Offchain
-        OffchainWorker
-        TryState
-    end
-
-    subgraph Genesis
-        GenesisBuild
-    end
-
-    subgraph AfterTransactions
-        direction LR
-        OnIdle --> OnFinalize
-    end
-
-    subgraph OnChain
-        direction LR
-        Optional --> BeforeExtrinsics
-        BeforeExtrinsics --> Inherents
-        Inherents --> Poll
-        Poll --> Transactions
-        Transactions --> AfterTransactions
-    end
-
-    subgraph Optional
-
-OnRuntimeUpgrade
-end
-
-    subgraph BeforeExtrinsics
-        OnInitialize
-    end
-
-    subgraph Transactions
-        Transaction1 --> UnsignedTransaction2 --> Transaction3
-    end
-
-    subgraph Inherents
-        Inherent1 --> Inherent2
-    end
-
-</diagram>
-
-- What other hooks can you think of?
-
-Notes:
-
-What other ideas you can think of?
-
-- a hook called once a pallet is first initialized.
-  <https://github.com/paritytech/polkadot-sdk/issues/109>
-- Local on Post/Pre dispatch: <https://github.com/paritytech/polkadot-sdk/issues/261>
-- Global on Post/Pre dispatch is in fact a signed extension. It has to live in the runtime, because you have to specify order.
-
----
-
-## Additional Resources! 😋
-
-> Check speaker notes (click "s" 😉)
-
-Notes:
-
-## Post lecture Notes
-
-Regarding this drawback to offchain workers that you can only upgrade in cadence with the network.
-Offchain worker, like tx-pool api, is only called from an offchain context. Node operators can
-easily use the runtime overrides feature to change the behavior of their offchain worker anytime
-they want.
diff --git a/content/frame/index.md b/content/frame/index.md
deleted file mode 100644
index 52e56be4..00000000
--- a/content/frame/index.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# 🧱 FRAME
-
-The primary Substrate runtime framework used for parachain development.
diff --git a/content/frame/intro/page.md b/content/frame/intro/page.md
deleted file mode 100644
index f6a4e07a..00000000
--- a/content/frame/intro/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Pallets & Traits
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/intro/slides.md b/content/frame/intro/slides.md
deleted file mode 100644
index def5efb7..00000000
--- a/content/frame/intro/slides.md
+++ /dev/null
@@ -1,353 +0,0 @@
----
-title: Introduction to FRAME
-description: An introduction into FRAME, a framework for building Substrate runtimes.
-duration: 1 hour
----
-
-## Lesson Plan
-
-<table class="no-bullet-padding">
-<tr>
-  <td>Monday</td>
-  <td>Tuesday</td>
-  <td>Wednesday</td>
-  <td>Thursday</td>
-  <td>Friday</td>
-  <td>Weekend</td>
-</tr>
-<tr class="text-small">
-<td>
-
-- Substrate Lectures
-
-</td>
-<td>
-
-- Substrate Lectures
-
-</td>
-<td>
-
-- Introduction to FRAME
-- 👩‍💻 Exercise: Proof of Existence Runtime
-- Announce FRAME Assignment
-
-</td>
-<td>
-
-- Pallet Coupling
-- FRAME Common Knowledge (Pallets & Traits)
-- FRAME Storage
-
-</td>
-<td>
-
-- Events & Errors
-- Calls
-- Origins
-- Outer Enum
-- Hooks
-
-</td>
-<td>
-
-- Complete FRAMEless Exercise
-
-</td>
-</tr>
-<tr class="text-small">
-<td>
-
-- Construct Runtime + Tests
-- 👨‍💻 Exercise: Tests
-- FRAME Benchmarking
-- 👨🏾‍💻 Exercise: Benchmarking
-
-</td>
-<td>
-
-- FRAME Under the Hood
-  - Deep Dive
-  - Executive
-- Signed Extensions
-- Migrations & Try Runtime
-
-</td>
-<td>
-
-- Spill Over + Live Coding
-- Polkadot Lectures
-
-</td>
-
-<td>
-
-- Polkadot Lectures
-
-</td>
-<td>
-
-- Polkadot Lectures
-
-</td>
-<td>
-
-- Complete FRAME Exercise
-
-</td>
-</tr>
-</table>
-
----
-
-# Introduction to FRAME
-
----
-
-## What is FRAME?
-
-FRAME is a Rust framework for more easily building Substrate runtimes.
-
----
-
-## Explaining FRAME Concisely
-
-<pba-flex center>
-
-Writing the Sudo Pallet:
-
-Without FRAME: 2210 lines of code.
-
-With FRAME: 310 lines of code.
-
-7x Smaller.
-
-</pba-flex>
-
----
-
-## Goals of FRAME
-
-- Make it easy and concise for developers to do development.
-- Provide maximum flexibility and compatibility for pallet developers.
-- Provide maximum modularity for runtime developers.
-- Be as similar to vanilla Rust as possible.
-
----
-
-## Building Blocks of FRAME
-
-- FRAME Development
-  - Pallets
-  - Macros
-- FRAME Coordination
-  - FRAME System
-  - FRAME Executive
-  - Construct Runtime
-
----
-
-## Pallets
-
-FRAME takes the opinion that the blockchain runtime should be composed of individual modules. We call these Pallets.
-
-<img style="height: 600px" src="./img/frame1.svg" />
-
----
-
-## Building Blocks of Pallets
-
-Pallets are composed of multiple parts common for runtime development:
-
-- Dispatchable extrinsics
-- Storage items
-- Hooks for:
-  - Block initialization,
-  - Finalizing block (_!= block finality i.e. GRANDPA_)
-
----
-
-## More Building Blocks of Pallets
-
-And some less important ones:
-
-- Events
-- Errors
-- Custom validation/communication with tx-pool
-- Offchain workers
-- A lot more! but you will learn about them later.
-
----
-
-### "Shell" Pallet
-
-```rust
-pub use pallet::*;
-
-#[frame_support::pallet]
-pub mod pallet {
-  use frame_support::pallet_prelude::*;
-  use frame_system::pallet_prelude::*;
-
-  #[pallet::pallet]
-  #[pallet::generate_store(pub(super) trait Store)]
-  pub struct Pallet<T>(_);
-
-  #[pallet::config]  // snip
-  #[pallet::event]   // snip
-  #[pallet::error]   // snip
-  #[pallet::storage] // snip
-  #[pallet::call]    // snip
-}
-```
-
----
-
-## FRAME Macros
-
-Rust allows you to write Macros, which is code that generates code.
-
-FRAME uses Macros to simplify the development of Pallets, while keeping all of the benefits of using Rust.
-
-We will look more closely at each attribute throughout this module.
-
----
-
-## See For Yourself
-
-- `wc -l` will show the number of lines of a file.
-- `cargo expand` will expand the macros to "pure" Rust.
-
-```sh
-➜  substrate git:(master) ✗ wc -l frame/sudo/src/lib.rs
-    310 frame/sudo/src/lib.rs
-
-➜  substrate git:(master) ✗ cargo expand -p pallet-sudo | wc -l
-    2210
-```
-
----
-
-## FRAME System
-
-The FRAME System is a Pallet which is assumed to always exist when using FRAME. You can see that in the `Config` of every Pallet:
-
-```rust
-#[pallet::config]
-pub trait Config: frame_system::Config { ... }
-```
-
-It contains all the most basic functions and types needed for a blockchain system. Also contains many low level extrinsics to manage your chain directly.
-
-<div class="flex-container">
-<div class="left-small">
-
-- Block Number
-- Accounts
-- Hash
-- etc...
-
-</div>
-<div class="right text-small">
-
-- `BlockNumberFor<T>`
-- `frame_system::Pallet::<T>::block_number()`
-- `T::AccountId`
-- `T::Hash`
-- `T::Hashing::hash(&bytes)`
-
-</div>
-</div>
-
----
-
-## FRAME Executive
-
-The FRAME Executive is a "coordinator", defining the order that your FRAME based runtime executes.
-
-```rust
-/// Actually execute all transitions for `block`.
-pub fn execute_block(block: Block) { ... }
-```
-
-- Initialize Block
-  - `on_runtime_upgrade` and `on_initialize` hooks
-- Initial Checks
-- Signature Verification
-- Execute Extrinsics
-  - `on_idle` and `on_finalize` hooks
-- Final Checks
-
----
-
-## Construct Runtime
-
-Your final runtime is composed of Pallets, which are brought together with the `construct_runtime!` macro.
-
-```rust
-// Create the runtime by composing the FRAME pallets that were previously configured.
-construct_runtime!(
-	pub struct Runtime {
-		System: frame_system,
-		RandomnessCollectiveFlip: pallet_randomness_collective_flip,
-		Timestamp: pallet_timestamp,
-		Aura: pallet_aura,
-		Grandpa: pallet_grandpa,
-		Balances: pallet_balances,
-		TransactionPayment: pallet_transaction_payment,
-		Sudo: pallet_sudo,
-		// Include the custom logic from the pallet-template in the runtime.
-		TemplateModule: pallet_template,
-	}
-);
-```
-
----
-
-## Pallet Configuration
-
-Before you can add a Pallet to the final runtime, it needs to be configured as defined in the `Config`.
-
-<div class="flex-container text-small">
-<div class="left" style="max-width: 50%;">
-
-In the Pallet:
-
-```rust
-/// The timestamp pallet configuration trait.
-#[pallet::config]
-pub trait Config: frame_system::Config {
-  type Moment: Parameter + Default + AtLeast32Bit + Scale<Self::BlockNumber, Output = Self::Moment> + Copy + MaxEncodedLen + scale_info::StaticTypeInfo;
-
-  type OnTimestampSet: OnTimestampSet<Self::Moment>;
-
-  #[pallet::constant]
-  type MinimumPeriod: Get<Self::Moment>;
-
-  type WeightInfo: WeightInfo;
-}
-```
-
-</div>
-
-<div class="right" style="max-width: 50%; padding-left: 10px;">
-
-In the Runtime:
-
-```rust
-/// The timestamp pallet configuration.
-
-impl pallet_timestamp::Config for Runtime {
-  type Moment = u64;
-
-  type OnTimestampSet = Aura;
-
-
-  type MinimumPeriod = ConstU64<{ SLOT_DURATION / 2 }>;
-
-  type WeightInfo = ();
-}
-```
-
-</div>
-</div>
diff --git a/content/frame/migrations/page.md b/content/frame/migrations/page.md
deleted file mode 100644
index 1a39e1ef..00000000
--- a/content/frame/migrations/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Migrations and Try Runtime
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/migrations/slides.md b/content/frame/migrations/slides.md
deleted file mode 100644
index d4d4268c..00000000
--- a/content/frame/migrations/slides.md
+++ /dev/null
@@ -1,600 +0,0 @@
----
-title: Migrations and Try Runtime
-description: Runtime upgrades and how to survive them
----
-
-# Migrations and Try Runtime
-
----
-
-## Runtime upgrades...
-
-### _and how to survive them_
-
----
-
-### _At the end of this lecture, you will be able to:_
-
-- Justify when runtime migrations are needed.
-- Write a the full a runtime upgrade that includes migrations, end-to-end.
-- Test runtime upgrades before executing on a network using `try-runtime` and `remote-externalities`.
-
----
-
-## When is a Migration Required?
-
----v
-
-### When is a Migration Required?
-
-- In a typical runtime upgrade, you typically only replace `:code:`. This is _**Runtime Upgrade**_.
-- If you change the _storage layout_, then this is also a _**Runtime Migration**_.
-
-> Anything that changes **encoding** is a migration!
-
----v
-
-### When is a Migration Required?
-
-```rust
-#[pallet::storage]
-pub type FooValue = StorageValue<_, Foo>;
-```
-
-```rust
-// old
-pub struct Foo(u32)
-// new
-pub struct Foo(u64)
-```
-
-- A clear migration.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### When is a Migration Required?
-
-```rust
-#[pallet::storage]
-pub type FooValue = StorageValue<_, Foo>;
-```
-
-```rust
-// old
-pub struct Foo(u32)
-// new
-pub struct Foo(i32)
-// or
-pub struct Foo(u16, u16)
-```
-
-- The data still _fits_, but the _interpretations_ is almost certainly different!
-
-<!-- .element: class="fragment" -->
-
----v
-
-### When is a Migration Required?
-
-```rust
-#[pallet::storage]
-pub type FooValue = StorageValue<_, Foo>;
-```
-
-```rust
-// old
-pub struct Foo { a: u32, b: u32 }
-// new
-pub struct Foo { a: u32, b: u32, c: u32 }
-```
-
-- This is still a migration, because `Foo`'s decoding changed.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### When is a Migration Required?
-
-```rust
-#[pallet::storage]
-pub type FooValue = StorageValue<_, Foo>;
-```
-
-```rust
-// old
-pub struct Foo { a: u32, b: u32 }
-// new
-pub struct Foo { a: u32, b: u32, c: PhantomData<_> }
-```
-
-- If for whatever reason `c` has a type that its encoding is like `()`, then this would work.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### When is a Migration Required?
-
-```rust
-#[pallet::storage]
-pub type FooValue = StorageValue<_, Foo>;
-```
-
-```rust
-// old
-pub enum Foo { A(u32), B(u32) }
-// new
-pub enum Foo { A(u32), B(u32), C(u128) }
-```
-
-- Extending an enum is even more interesting, because if you add the variant to the end, no migration is needed.
-
-<!-- .element: class="fragment" -->
-
-- Assuming that no value is initialized with `C`, this is _not_ a migration.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### When is a Migration Required?
-
-```rust
-#[pallet::storage]
-pub type FooValue = StorageValue<_, Foo>;
-```
-
-```rust
-// old
-pub enum Foo { A(u32), B(u32) }
-// new
-pub enum Foo { A(u32), C(u128), B(u32) }
-```
-
-- You probably _never_ want to do this, but it is a migration.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### 🦀 Rust Recall 🦀
-
-Enums are encoded as the variant enum, followed by the inner data:
-
-- The order matters! Both in `struct` and `enum`.
-- Enums that implement `Encode` cannot have more than 255 variants.
-
----v
-
-### When is a Migration Required?
-
-```rust
-#[pallet::storage]
-pub type FooValue = StorageValue<_, u32>;
-```
-
-```rust
-// new
-#[pallet::storage]
-pub type BarValue = StorageValue<_, u32>;
-```
-
-- So far everything is changing the _value_ format.<br />
-
-<div>
-
-- The _key_ changing is also a migration!
-
-</div>
-
-<!-- .element: class="fragment" -->
-
----v
-
-### When is a Migration Required?
-
-```rust
-#[pallet::storage]
-pub type FooValue = StorageValue<_, u32>;
-```
-
-```rust
-// new
-#[pallet::storage_prefix = "FooValue"]
-#[pallet::storage]
-pub type I_can_NOW_BE_renamEd_hahAA = StorageValue<_, u32>;
-```
-
-- Handy macro if you must rename a storage type.<br />
-- This does _not_ require a migration.
-
-<!-- .element: class="fragment" -->
-
----
-
-## Writing Runtime Migrations
-
-- Now that we know how to detect if a storage change is a **migration**, let's see how we write one.
-
----v
-
-### Writing Runtime Migrations
-
-- Once you upgrade a runtime, the code is expecting the data to be in a new format.
-- Any `on_initialize` or transaction might fail decoding data, and potentially `panic!`
-
----v
-
-### Writing Runtime Migrations
-
-- We need a **_hook_** that is executed **ONCE** as a part of the new runtime...
-- But before **ANY** other code (on_initialize, any transaction) with the new runtime is migrated.
-
-> This is `OnRuntimeUpgrade`.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Writing Runtime Migrations
-
-- Optional activity: Go into `executive` and `system`, and find out how `OnRuntimeUpgrade` is called only when the code changes!
-
----
-
-## Pallet Internal Migrations
-
----v
-
-### Pallet Internal Migrations
-
-One way to write a migration is to write it inside the pallet.
-
-```rust
-#[pallet::hooks]
-impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
-  fn on_runtime_upgrade() -> Weight {
-    migrate_stuff_and_things_here_and_there<T>();
-  }
-}
-```
-
-> This approach is likely to be deprecated and is no longer practiced within Parity either.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Pallet Internal Migrations
-
-```rust [4-8]
-#[pallet::hooks]
-impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
-  fn on_runtime_upgrade() -> Weight {
-    if guard_that_stuff_has_not_been_migrated() {
-      migrate_stuff_and_things_here_and_there<T>();
-    } else {
-      // nada
-    }
-  }
-}
-```
-
-- If you execute `migrate_stuff_and_things_here_and_there` twice as well, then you are doomed 😫.
-
----v
-
-### Pallet Internal Migrations
-
-**Historically**, something like this was used:
-
-```rust [1-7|9-19]
-#[derive(Encode, Decode, ...)]
-enum StorageVersion {
-  V1, V2, V3, // add a new variant with each version
-}
-
-#[pallet::storage]
-pub type Version = StorageValue<_, StorageVersion>;
-
-#[pallet::hooks]
-impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
-  fn on_runtime_upgrade() -> Weight {
-    if let StorageVersion::V2 = Version::<T>::get() {
-      // do migration
-      Version::<T>::put(StorageVersion::V3);
-    } else {
-      // nada
-    }
-  }
-}
-```
-
----v
-
-### Pallet Internal Migrations
-
-- FRAME introduced macros to manage migrations: `#[pallet::storage_version]`.
-
-```rust
-// your current storage version.
-const STORAGE_VERSION: StorageVersion = StorageVersion::new(2);
-
-#[pallet::pallet]
-#[pallet::storage_version(STORAGE_VERSION)]
-pub struct Pallet<T>(_);
-```
-
-- This adds two function to the `Pallet<_>` struct:
-
-```rust
-// read the current version, encoded in the code.
-let current = Pallet::<T>::current_storage_version();
-// read the version encoded onchain.
-Pallet::<T>::on_chain_storage_version();
-// synchronize the two.
-current.put::<Pallet<T>>();
-```
-
----v
-
-### Pallet Internal Migrations
-
-```rust
-#[pallet::hooks]
-impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
-  fn on_runtime_upgrade() -> Weight {
-    let current = Pallet::<T>::current_storage_version();
-    let onchain = Pallet::<T>::on_chain_storage_version();
-
-    if current == 1 && onchain == 0 {
-      // do stuff
-      current.put::<Pallet<T>>();
-    } else {
-    }
-  }
-}
-```
-
-Stores the version as u16 in [`twox(pallet_name) ++ twox(:__STORAGE_VERSION__:)`](https://github.com/paritytech/polkadot-sdk/blob/c7c5fc7/substrate/frame/support/src/traits/metadata.rs#L163).
-
----
-
-## External Migrations
-
----v
-
-### External Migrations
-
-- Managing migrations within a pallet could be hard.
-- Especially for those that want to use external pallets.
-
-Alternative:
-
-- Every runtime can explicitly pass anything that implements `OnRuntimeUpgrade` to `Executive`.
-- End of the day, Executive does:
-  - `<(COnRuntimeUpgrade, AllPalletsWithSystem) as OnRuntimeUpgrade>::on_runtime_upgrade()`.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### External Migrations
-
-- The main point of external migrations is making it more clear:
-- "_What migrations did exactly execute on upgrade to spec_version xxx_"
-
----v
-
-### External Migrations
-
-- Expose your migration as a standalone function or struct implementing `OnRuntimeUpgrade` inside a `pub mod v<version_number>`.
-
-```rust
-pub mod v3 {
-  pub struct Migration;
-  impl OnRuntimeUpgrade for Migration {
-    fn on_runtime_upgrade() -> Weight {
-      // do stuff
-    }
-  }
-}
-```
-
----v
-
-### External Migrations
-
-- Guard the code of the migration with `pallet::storage_version`
-- Don't forget to write the new version!
-
-```rust
-pub mod v3 {
-  pub struct Migration;
-  impl OnRuntimeUpgrade for Migration {
-    fn on_runtime_upgrade() -> Weight {
-      let current = Pallet::<T>::current_storage_version();
-      let onchain = Pallet::<T>::on_chain_storage_version();
-
-      if current == 1 && onchain == 0 {
-        // do stuff
-        current.put::<Pallet<T>>();
-      } else {
-      }
-    }
-  }
-}
-```
-
----v
-
-### External Migrations
-
-- Pass it to the runtime per-release.
-
-```rust
-pub type Executive = Executive<
-  _,
-  _,
-  _,
-  _,
-  _,
-  (v3::Migration, ...)
->;
-```
-
----v
-
-### External Migrations
-
-- Discussion: Can the runtime upgrade scripts live forever? Or should they be removed after a few releases?
-
-Notes:
-
-Short answer is, yes, but it is a LOT of work. See here: <https://github.com/paritytech/polkadot-sdk/issues/296>
-
----
-
-### Utilities in `frame-support`.
-
-- `translate` methods:
-  - For `StorageValue`, `StorageMap`, etc.
-- <https://paritytech.github.io/substrate/master/frame_support/storage/migration/index.html>
-
-* `#[storage_alias]` macro to create storage types for removed for those that are being removed.
-
-Notes:
-
-Imagine you want to remove a storage map and in a migration you want to iterate it and delete all items. You want to remove this storage item, but it would be handy to be able to access it one last time in the migration code. This is where `#[storage_alias]` comes into play.
-
----
-
-## Case Studies
-
-1. The day we destroyed all balances in Polkadot.
-1. First ever migration ([`pallet-elections-phragmen`](https://github.com/paritytech/substrate/pull/3948)).
-1. Fairly independent migrations in `pallet-elections-phragmen`.
-
----
-
-## Testing Upgrades
-
----v
-
-### Testing Upgrades
-
-- `try-runtime` + `RemoteExternalities` allow you to examine and test a runtime in detail with a high degree of control over the environment.
-
-- It is meant to try things out, and inspired by traits like `TryFrom`, the name `TryRuntime` was chosen.
-
----v
-
-### Testing Upgrades
-
-Recall:
-
-- The runtime communicates with the client via host functions.
-- Moreover, the client communicates with the runtime via runtime APIs.
-- An environment that provides these host functions is called `Externalities`.
-- One example of which is `TestExternalities`, which you have already seen.
-
----v
-
-### Testing Upgrades: `remote-externalities`
-
-`remote-externalities` ia a builder pattern that loads the state of a live chain inside `TestExternalities`.
-
-```rust
-let mut ext = Builder::<Block>::new()
-  .mode(Mode::Online(OnlineConfig {
-  	transport: "wss://rpc.polkadot.io",
-  	pallets: vec!["PalletA", "PalletB", "PalletC", "RandomPrefix"],
-  	..Default::default()
-  }))
-  .build()
-  .await
-  .unwrap();
-```
-
-Reading all this data over RPC can be slow!
-
----v
-
-### Testing Upgrades: `remote-externalities`
-
-`remote-externalities` supports:
-
-- Custom prefixes -> Read a specific pallet
-- Injecting custom keys -> Read `:code:` as well.
-- Injecting custom key-values -> Overwrite `:code:` with `0x00`!
-- Reading child-tree data -> Relevant for crowdloan pallet etc.
-- Caching everything in disk for repeated use.
-
----v
-
-### Testing Upgrades: `remote-externalities`
-
-`remote-externalities` is in itself a very useful tool to:
-
-- Go back in time and re-running some code.
-- Write unit tests that work on the real-chain's state.
-
----
-
-## Testing Upgrades: `try-runtime`
-
-- `try-runtime` is a CLI and a set of custom runtime APIs integrated in substrate that allows you to do detailed testing..
-
-- .. including running `OnRuntimeUpgrade` code of a new runtime, on top of a real chain's data.
-
----v
-
-### Testing Upgrades: `try-runtime`
-
-- A lot can be said about it, the best resource is the [rust-docs](https://paritytech.github.io/substrate/master/try_runtime_cli/index.html).
-
----v
-
-### Testing Upgrades: `try-runtime`
-
-- You might find some code in your runtime that is featured gated with `#[cfg(feature = "try-runtime")]`. These are always for testing.
-- `pre_upgrade` and `post_upgrade`: Hooks executed before and after `on_runtime_upgrade`.
-- `try_state`: called in various other places, used to check the invariants the pallet.
-
----v
-
-### Testing Upgrades: `try-runtime`: Live Demo.
-
-- Let's craft a migration on top of poor node-template 😈..
-- and migrate the balance type from u128 to u64.
-
----
-
-## Additional Resources 😋
-
-> Check speaker notes (click "s" 😉)
-
-Notes:
-
-- Additional work on automatic version upgrades: <https://github.com/paritytech/substrate/issues/13107>
-- A Great talk about try-runtime and further testing of your runtime: <https://www.youtube.com/watch?v=a_u3KMG-n-I>
-
-#### Reference material:
-
-- 📺 [Substrate Seminar on Migrations](https://www.youtube.com/watch?v=MQgDV37JrIY>)
-
-Notes:
-
-FIXME: `docs.google.com/presentation/d/1hr3fiqOI0JlXw0ISs8uV9BXiDQ5mGOQLc3b_yWK6cxU/edit#slide=id.g43d9ae013f_0_82` was listed here as a reference but is not public!
-
-#### Exercise ideas:
-
-- Find the storage version of nomination pools pallet in Kusama.
-- Give them a poorly written migration code, and try and fix it. Things they need to fix:
-  - The migration depends on `<T: Config>`
-  - Does not manage version properly
-  - is hardcoded in the pallet.
-- Re-execute the block at which the runtime went OOM in May 25th 2021 Polkadot.
diff --git a/content/frame/origin/page.md b/content/frame/origin/page.md
deleted file mode 100644
index 364de462..00000000
--- a/content/frame/origin/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Origin
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/origin/slides.md b/content/frame/origin/slides.md
deleted file mode 100644
index 9314b0e7..00000000
--- a/content/frame/origin/slides.md
+++ /dev/null
@@ -1,373 +0,0 @@
----
-title: FRAME Origin
-description: Deep dive into FRAME Origins
-duration: 1 hour
----
-
-# Origin
-
----
-
-## Origin
-
-This presentation will cover the use of Origin in FRAME, and how you can customize and extend this abstractions.
-
----
-
-## What is Origin?
-
-All dispatchable calls have an `Origin` that describes where the call originates from.
-
-```rust
-/// Make some on-chain remark.
-#[pallet::weight(T::SystemWeightInfo::remark(_remark.len() as u32))]
-pub fn remark(origin: OriginFor<T>, _remark: Vec<u8>) -> DispatchResultWithPostInfo {
-	ensure_signed_or_root(origin)?;
-	Ok(().into())
-}
-```
-
----
-
-## FRAME System `RawOrigin`
-
-These are origins which are included with FRAME by default.
-
-```rust
-/// Origin for the System pallet.
-#[derive(PartialEq, Eq, Clone, RuntimeDebug, Encode, Decode, TypeInfo, MaxEncodedLen)]
-pub enum RawOrigin<AccountId> {
-	/// The system itself ordained this dispatch to happen: this is the highest privilege level.
-	Root,
-	/// It is signed by some public key and we provide the `AccountId`.
-	Signed(AccountId),
-	/// It is signed by nobody, can be either:
-	/// * included and agreed upon by the validators anyway,
-	/// * or unsigned transaction validated by a pallet.
-	None,
-}
-```
-
----
-
-## How is it used?
-
-The Runtime Origin is used by dispatchable functions to check where a call has come from.
-
-This is similar to `msg.sender` in Solidity, but FRAME is more powerful, and so is `Origin`.
-
----
-
-## Origin Checks
-
-```rust
-/// Ensure that the origin `o` represents the root. Returns `Ok` or an `Err` otherwise.
-pub fn ensure_root<OuterOrigin, AccountId>(o: OuterOrigin) -> Result<(), BadOrigin>
-```
-
-```rust
-/// Ensure that the origin `o` represents a signed extrinsic (i.e. transaction).
-/// Returns `Ok` with the account that signed the extrinsic or an `Err` otherwise.
-pub fn ensure_signed<OuterOrigin, AccountId>(o: OuterOrigin) -> Result<AccountId, BadOrigin>
-```
-
-```rust
-/// Ensure that the origin `o` represents an unsigned extrinsic. Returns `Ok` or an `Err` otherwise.
-pub fn ensure_none<OuterOrigin, AccountId>(o: OuterOrigin) -> Result<(), BadOrigin>
-```
-
-```rust
-/// Ensure that the origin `o` represents either a signed extrinsic (i.e. transaction) or the root.
-/// Returns `Ok` with the account that signed the extrinsic, `None` if it was root,  or an `Err`
-/// otherwise.
-pub fn ensure_signed_or_root<OuterOrigin, AccountId>(o: OuterOrigin) -> Result<Option<AccountId>, BadOrigin>
-```
-
----
-
-## Examples: Signed Origin
-
-A Simple Balance Transfer.
-
-```rust
-#[pallet::call_index(0)]
-#[pallet::weight(T::WeightInfo::transfer())]
-pub fn transfer(
-	origin: OriginFor<T>,
-	dest: AccountIdLookupOf<T>,
-	#[pallet::compact] value: T::Balance,
-) -> DispatchResultWithPostInfo {
-	let transactor = ensure_signed(origin)?;
-	// -- snip --
-}
-```
-
-Most extrinsics use a `Signed` origin.
-
----
-
-## Examples: Root Origin
-
-The extrinsic to upgrade a chain.
-
-```rust
-/// Set the new runtime code.
-#[pallet::call_index(2)]
-#[pallet::weight((T::BlockWeights::get().max_block, DispatchClass::Operational))]
-pub fn set_code(origin: OriginFor<T>, code: Vec<u8>) -> DispatchResultWithPostInfo {
-	ensure_root(origin)?;
-	Self::can_set_code(&code)?;
-	T::OnSetCode::set_code(code)?;
-	Ok(().into())
-}
-```
-
-`Root` has access to many functions which can directly modify your blockchain. Assume Root access can do anything.
-
----
-
-## Examples: None Origin
-
-Setting the timestamp of the block.
-
-```rust
-	/// Set the current time.
-	#[pallet::call_index(0)]
-	#[pallet::weight((T::WeightInfo::set(), DispatchClass::Mandatory))]
-	pub fn set(origin: OriginFor<T>, #[pallet::compact] now: T::Moment) -> DispatchResult {
-		ensure_none(origin)?;
-		// -- snip --
-	}
-}
-```
-
-`None` origin is not very straight forward. More details next...
-
----
-
-## None for Inherents
-
-`None` origin can be used to represents extrinsics which are specifically included by the block author, also known as an inherent.
-
-In those cases, it includes inherent checking logic with `ProvideInherent`.
-
-```rust
-#[pallet::inherent]
-impl<T: Config> ProvideInherent for Pallet<T> {
-	type Call = Call<T>;
-	type Error = InherentError;
-	const INHERENT_IDENTIFIER: InherentIdentifier = INHERENT_IDENTIFIER;
-
-	// -- snip --
-```
-
----
-
-## None for Unsigned
-
-`None` can also be used to represent "unsigned extrinsics", which are intended to be submitted by anyone without a key.
-
-In those cases, it includes unsigned validation logic with `ValidateUnsigned`.
-
-```rust
-#[pallet::validate_unsigned]
-impl<T: Config> ValidateUnsigned for Pallet<T> {
-	type Call = Call<T>;
-	fn validate_unsigned(source: TransactionSource, call: &Self::Call) -> TransactionValidity {
-		Self::validate_unsigned(source, call)
-	}
-
-	fn pre_dispatch(call: &Self::Call) -> Result<(), TransactionValidityError> {
-		Self::pre_dispatch(call)
-	}
-}
-```
-
----
-
-## Custom Origins
-
-Origins are extensible and customizable.
-
-Each pallet can introduce new Origins which can be used throughout the runtime.
-
-```rust
-/// The `#[pallet::origin]` attribute allows you to define some origin for the pallet.
-#[pallet::origin]
-pub struct Origin<T>(PhantomData<(T)>);
-```
-
----
-
-## Example: Collective Pallet
-
-```rust
-/// Origin for the collective module.
-pub enum RawOrigin<AccountId, I> {
-	/// It has been condoned by a given number of members of the collective from a given total.
-	Members(MemberCount, MemberCount),
-	/// It has been condoned by a single member of the collective.
-	Member(AccountId),
-	/// Dummy to manage the fact we have instancing.
-	_Phantom(PhantomData<I>),
-}
-```
-
-This custom origin allows us to represent a collection of users, rather than a single account.
-For example: `Members(5, 9)` represents that 5 out of 9 members agree on something as controlled by the collective pallet logic.
-
----
-
-## Example: Parachain Origin
-
-```rust
-/// Origin for the parachains.
-#[pallet::origin]
-pub enum Origin {
-	/// It comes from a parachain.
-	Parachain(ParaId),
-}
-```
-
-This is a custom origin which allows us to represent a message that comes from a parachain.
-
----
-
-## Re-Dispatching
-
-You can actually dispatch a call within a call with an origin of your choice.
-
-```rust [11]
-#[pallet::call_index(0)]
-#[pallet::weight({ let dispatch_info = call.get_dispatch_info(); (dispatch_info.weight, dispatch_info.class) })]
-pub fn sudo(
-	origin: OriginFor<T>,
-	call: Box<<T as Config>::RuntimeCall>,
-) -> DispatchResultWithPostInfo {
-	// This is a public call, so we ensure that the origin is some signed account.
-	let sender = ensure_signed(origin)?;
-	ensure!(Self::key().map_or(false, |k| sender == k), Error::<T>::RequireSudo);
-
-	let res = call.dispatch_bypass_filter(frame_system::RawOrigin::Root.into());
-	Self::deposit_event(Event::Sudid { sudo_result: res.map(|_| ()).map_err(|e| e.error) });
-	// Sudo user does not pay a fee.
-	Ok(Pays::No.into())
-}
-```
-
-Here, Sudo Pallet allows a `Signed` origin to elevate itself to a `Root` origin, if the logic allows.
-
----
-
-## Example: Collective Pallet
-
-Here you can see the Collective Pallet creating, and dispatching with the `Members` origin we showed previously.
-
-```rust [5-6]
-	fn do_approve_proposal(seats: MemberCount, yes_votes: MemberCount, proposal_hash: T::Hash, proposal: <T as Config<I>>::Proposal) -> (Weight, u32) {
-		Self::deposit_event(Event::Approved { proposal_hash });
-
-		let dispatch_weight = proposal.get_dispatch_info().weight;
-		let origin = RawOrigin::Members(yes_votes, seats).into();
-		let result = proposal.dispatch(origin);
-		Self::deposit_event(Event::Executed { proposal_hash, result: result.map(|_| ()).map_err(|e| e.error) });
-		// default to the dispatch info weight for safety
-		let proposal_weight = get_result_weight(result).unwrap_or(dispatch_weight); // P1
-
-		let proposal_count = Self::remove_proposal(proposal_hash);
-		(proposal_weight, proposal_count)
-	}
-```
-
----
-
-## Custom Origin Checks
-
-You can then write logic which is only accessible with custom origins by implementing the `EnsureOrigin` trait.
-
-```rust
-/// Some sort of check on the origin is performed by this object.
-pub trait EnsureOrigin<OuterOrigin> { ... }
-```
-
-These need to be configured in the Runtime, where all custom origins for your runtime are known.
-
----
-
-## Example: Alliance Pallet
-
-Pallet's can allow for various origins to be configured by the Runtime.
-
-```rust
-#[pallet::config]
-pub trait Config<I: 'static = ()>: frame_system::Config {
-	/// Origin for admin-level operations, like setting the Alliance's rules.
-	type AdminOrigin: EnsureOrigin<Self::RuntimeOrigin>;
-	/// Origin that manages entry and forcible discharge from the Alliance.
-	type MembershipManager: EnsureOrigin<Self::RuntimeOrigin>;
-	/// Origin for making announcements and adding/removing unscrupulous items.
-	type AnnouncementOrigin: EnsureOrigin<Self::RuntimeOrigin>;
-	// -- snip --
-}
-```
-
----
-
-## Example: Alliance Pallet
-
-Pallet calls can then use these custom origins to gate access to the logic.
-
-```rust [5]
-/// Set a new IPFS CID to the alliance rule.
-#[pallet::call_index(5)]
-#[pallet::weight(T::WeightInfo::set_rule())]
-pub fn set_rule(origin: OriginFor<T>, rule: Cid) -> DispatchResult {
-	T::AdminOrigin::ensure_origin(origin)?;
-
-	Rule::<T, I>::put(&rule);
-
-	Self::deposit_event(Event::NewRuleSet { rule });
-	Ok(())
-}
-```
-
----
-
-## Example: Alliance Pallet
-
-Finally, the Runtime itself is where you configure what those Origins are.
-
-```rust
-impl pallet_alliance::Config for Runtime {
-	type AdminOrigin = EitherOfDiverse<
-		EnsureRoot<AccountId>,
-		EnsureProportionAtLeast<AccountId, AllianceCollective, 1, 1>,
-	>;
-	type MembershipManager = EitherOfDiverse<
-		EnsureRoot<AccountId>,
-		EnsureProportionMoreThan<AccountId, AllianceCollective, 2, 3>,
-	>;
-	type AnnouncementOrigin = EitherOfDiverse<
-		EnsureRoot<AccountId>,
-		EnsureProportionMoreThan<AccountId, AllianceCollective, 1, 3>,
-	>;
-}
-```
-
-As you can see, they can even support multiple different origins!
-
----
-
-## Fees
-
-Fees are usually handled by some pallet like the Transaction Payments Pallet.
-
-However, if there is no `Signed` origin, you can't really take a fee.
-
-You should assume any transaction which is not from the `Signed` origin is feeless, unless you explicitly write code to handle it.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/frame/outer-enum/page.md b/content/frame/outer-enum/page.md
deleted file mode 100644
index f825922f..00000000
--- a/content/frame/outer-enum/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Outer Enum
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
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diff --git a/content/frame/outer-enum/slides.md b/content/frame/outer-enum/slides.md
deleted file mode 100644
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--- a/content/frame/outer-enum/slides.md
+++ /dev/null
@@ -1,325 +0,0 @@
----
-title: Outer Enum
-description: FRAME Outer Enum web3 builders.
-duration: 1 hour
----
-
-# Outer Enum
-
----
-
-## Outer Enum
-
-In this presentation, you will learn about a common pattern used throughout FRAME, which abstracts many separate types into a single unified type that is used by the Runtime.
-
-This is also known as "aggregate" types.
-
----
-
-## Enums in FRAME
-
-There are 4 main Enums which you will encounter throughout your FRAME development:
-
-- The Call Enum
-- The Event Enum
-- The Error Enum
-- The Origin Enum
-
-All of these enums have some representation within individual pallets, but also the final FRAME runtime you develop.
-
----
-
-### Breaking It Down (Without Substrate)
-
-```rust [0|10-30|32-52|54-80|82-97|99|102-107|109-114|116-140]
-#![allow(non_camel_case_types)]
-#![allow(dead_code)]
-
-use parity_scale_codec::Encode;
-
-pub type AccountId = u16;
-pub type Balance = u32;
-pub type Hash = [u8; 32];
-
-mod balances {
-	use crate::*;
-
-	#[derive(Encode)]
-	pub enum Call {
-		transfer { to: AccountId, amount: Balance },
-		transfer_all { to: AccountId },
-	}
-
-	#[derive(Encode)]
-	pub enum Error {
-		InsufficientBalance,
-		ExistentialDeposit,
-		KeepAlive,
-	}
-
-	#[derive(Encode)]
-	pub enum Event {
-		Transfer { from: AccountId, to: AccountId, amount: Balance },
-	}
-}
-
-mod democracy {
-	use crate::*;
-
-	#[derive(Encode)]
-	pub enum Call {
-		propose { proposal_hash: Hash },
-		vote { proposal_id: u32, aye: bool },
-	}
-
-	#[derive(Encode)]
-	pub enum Error {
-		DuplicateProposal,
-	}
-
-	#[derive(Encode)]
-	pub enum Event {
-		Proposed { proposal_index: Hash },
-		Passed { proposal_index: Hash },
-		NotPassed { proposal_index: Hash },
-	}
-}
-
-mod staking {
-	use crate::*;
-
-	#[derive(Encode)]
-	pub enum Call {
-		unstake,
-		stake { nominate: Vec<AccountId>, amount: Balance },
-	}
-
-	#[derive(Encode)]
-	pub enum Error {
-		TooManyTargets,
-		EmptyTargets,
-		AlreadyBonded,
-	}
-
-	impl Into<DispatchError> for Error {
-		fn into(self) -> DispatchError {
-			DispatchError::Module(
-				ModuleError {
-					pallet: runtime::Runtime::Staking as u8,
-					error: self as u8,
-				}
-			)
-		}
-	}
-}
-
-// Similar to `sp-runtime`
-mod runtime_primitives {
-	use crate::*;
-
-	#[derive(Encode)]
-	pub struct ModuleError {
-		pub pallet: u8,
-		pub error: u8,
-	}
-
-	#[derive(Encode)]
-	pub enum DispatchError {
-		BadOrigin,
-		Module(ModuleError),
-	}
-}
-
-mod runtime {
-	use crate::*;
-
-	#[derive(Encode)]
-	pub enum PalletIndex {
-		Balances = 0,
-		Democracy = 1,
-		Staking = 2,
-	}
-
-	#[derive(Encode)]
-	pub enum RuntimeCall {
-		BalancesCall(balances::Call),
-		DemocracyCall(democracy::Call),
-		StakingCall(staking::Call),
-	}
-
-	#[derive(Encode)]
-	pub enum RuntimeEvent {
-		BalancesEvent(balances::Event),
-		DemocracyEvent(democracy::Event),
-		// No staking events... not even in the enum.
-	}
-
-	// Imagine this for all of the possible types above...
-	impl Into<RuntimeEvent> for balances::Event {
-		fn into(self) -> RuntimeEvent {
-			RuntimeEvent::BalancesEvent(self)
-		}
-	}
-
-	// Imagine this for all of the possible types above...
-	impl TryFrom<RuntimeEvent> for balances::Event {
-		type Error = ();
-
-		fn try_from(outer: RuntimeEvent) -> Result<Self, ()> {
-			match outer {
-				Event::BalancesEvent(event) => Ok(event),
-				_ => Err(())
-			}
-		}
-	}
-}
-
-use runtime_primitives::*;
-
-fn main() {
-	let democracy_call = democracy::Call::propose { proposal_hash: [7u8; 32] };
-	println!("Pallet Call:   {:?}", democracy_call.encode());
-	let runtime_call = runtime::RuntimeCall::Democracy(democracy_call);
-	println!("Runtime Call:  {:?}", runtime_call.encode());
-	let staking_error = staking::Error::AlreadyBonded;
-	println!("Pallet Error:  {:?}", staking_error.encode());
-	let runtime_error: DispatchError = staking_error.into();
-	println!("Runtime Error: {:?}", runtime_error.encode());
-	let balances_event = balances::Event::Transfer { from: 1, to: 2, amount: 3 };
-	println!("Pallet Event:  {:?}", balances_event.encode());
-	let runtime_event: runtime::RuntimeEvent = balances_event.into();
-	println!("Runtime Event: {:?}", runtime_event.encode());
-}
-```
-
----
-
-## Outer Enum Encoding
-
-This now explains how all the different runtime types are generally encoded!
-
-```rust [2,4,6,8,10,12]
-fn main() {
-	let democracy_call = democracy::Call::propose { proposal_hash: [7u8; 32] };
-	println!("Pallet Call:   {:?}", democracy_call.encode());
-	let runtime_call = runtime::RuntimeCall::Democracy(democracy_call);
-	println!("Runtime Call:  {:?}", runtime_call.encode());
-	let staking_error = staking::Error::AlreadyBonded;
-	println!("Pallet Error:  {:?}", staking_error.encode());
-	let runtime_error: DispatchError = staking_error.into();
-	println!("Runtime Error: {:?}", runtime_error.encode());
-	let balances_event = balances::Event::Transfer { from: 1, to: 2, amount: 3 };
-	println!("Pallet Event:  {:?}", balances_event.encode());
-	let runtime_event: runtime::RuntimeEvent = balances_event.into();
-	println!("Runtime Event: {:?}", runtime_event.encode());
-}
-```
-
-```sh
-Pallet Call:   [0, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]
-Runtime Call:  [1, 0, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]
-Pallet Error:  [2]
-Runtime Error: [1, 2, 2]
-Pallet Event:  [0, 1, 0, 2, 0, 3, 0, 0, 0]
-Runtime Event: [0, 0, 1, 0, 2, 0, 3, 0, 0, 0]
-```
-
----
-
-## Real Runtime
-
-This was directly added to `substrate/bin/node-template/runtime/src/lib.rs`:
-
-```rust [7,9,11,13,15,17]
-#[test]
-fn outer_enum_tests() {
-	use sp_runtime::{DispatchError, MultiAddress};
-	use sp_core::crypto::AccountId32;
-	use codec::Encode;
-
-	let balances_call = pallet_balances::Call::<Runtime>::transfer { dest: MultiAddress::Address32([1u8; 32]), value: 12345 };
-	println!("Pallet Call:   {:?}", balances_call.encode());
-	let runtime_call = crate::RuntimeCall::Balances(balances_call);
-	println!("Runtime Call:  {:?}", runtime_call.encode());
-	let balances_error = pallet_balances::Error::<Runtime>::InsufficientBalance;
-	println!("Pallet Error:  {:?}", balances_error.encode());
-	let runtime_error: DispatchError = balances_error.into();
-	println!("Runtime Error: {:?}", runtime_error.encode());
-	let balances_event = pallet_balances::Event::<Runtime>::Transfer { from: AccountId32::new([2u8; 32]), to: AccountId32::new([3u8; 32]), amount: 12345 };
-	println!("Pallet Event:  {:?}", balances_event.encode());
-	let runtime_event: crate::RuntimeEvent = balances_event.into();
-	println!("Runtime Event: {:?}", runtime_event.encode());
-}
-```
-
----
-
-## Real Runtime Output
-
-```sh
-Pallet Call:   [0, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 229, 192]
-Runtime Call:  [5, 0, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 229, 192]
-Pallet Error:  [2]
-Runtime Error: [3, 5, 2, 0, 0, 0]
-Pallet Event:  [2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 57, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
-Runtime Event: [5, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 57, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
-```
-
-Everything is just like our FRAME-less mock, but the types are more complex.
-
----
-
-## Using Outer Enums
-
-The path for using outer enums can be a bit confusing.
-
-- The types which compose the outer enum come from pallets.
-
-- They are aggregated in the runtime.
-
-- They can be passed BACK to the pallets and used in pallet logic through associated types.
-
----
-
-### System Aggregated Associated Types
-
-You can see these "aggregate" types are associated types in FRAME System.
-
-```rust
-/// System configuration trait. Implemented by runtime.
-#[pallet::config]
-#[pallet::disable_frame_system_supertrait_check]
-pub trait Config: 'static + Eq + Clone {
-	/// The `RuntimeOrigin` type used by dispatchable calls.
-	type RuntimeOrigin: Into<Result<RawOrigin<Self::AccountId>, Self::RuntimeOrigin>> + From<RawOrigin<Self::AccountId>> + Clone + OriginTrait<Call = Self::RuntimeCall>;
-
-	/// The aggregated `RuntimeCall` type.
-	type RuntimeCall: Parameter + Dispatchable<RuntimeOrigin = Self::RuntimeOrigin> + Debug + From<Call<Self>>;
-
-	/// The aggregated event type of the runtime.
-	type RuntimeEvent: Parameter + Member + From<Event<Self>> + Debug + IsType<<Self as frame_system::Config>::RuntimeEvent>;
-
-	// -- snip --
-}
-```
-
----
-
-## Pallet Event
-
-You can now see why we need to add an `Event` associated type to each pallet which uses events:
-
-```rust
-/// Configure the pallet by specifying the parameters and types on which it depends.
-#[pallet::config]
-pub trait Config: frame_system::Config {
-	/// Because this pallet emits events, it depends on the runtime's definition of an event.
-	type RuntimeEvent: From<Event<Self>> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
-}
-```
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/frame/storage/page.md b/content/frame/storage/page.md
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-# FRAME Storage
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
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diff --git a/content/frame/storage/slides.md b/content/frame/storage/slides.md
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--- a/content/frame/storage/slides.md
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----
-title: FRAME Storage
-description: Deep dive into FRAME Storage
-duration: 1 hour
----
-
-# FRAME Storage
-
----
-
-## FRAME Storage
-
-In this presentation, we will go even deeper into the concepts of Substrate storage, and see what kind of storage primitives FRAME provides you with to make Pallet development easy.
-
----
-
-<div class="flex-container">
-
-<div class="left-small">
-	<table class="storage-layer-table">
-	<tr><td class="ends">Developer</td></tr>
-	<tr><td style="background-color: pink;">Runtime Storage API</td></tr>
-	<tr><td style="background-color: pink;">Storage Overlays</td></tr>
-	<tr><td>Patricia-Merkle Trie</td></tr>
-	<tr><td>Key-Value Database</td></tr>
-	<tr><td class="ends">Computer</td></tr>
-	</table>
-</div>
-<div class="right">
-
-### Storage layers
-
-As we have learned, there are four core layers to Substrate's storage system.
-
-Today we will focus on the top two layers: Runtime Storage APIs and Storage Overlays, which FRAME uses to improve developer experience.
-
-</div>
-</div>
-
----
-
-### Overlay Deep Dive
-
-<br />
-<div class="flex-container">
-<div class="left-small" style="font-size:0.9em">
-
-The overlay stages changes to the underlying database.
-
-</div>
-
-<div class="right">
-
-<table class="overlay-table">
-<tr><td style="background-color: red;">Runtime Logic</td></tr>
-<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: green;">
-<tr><td>Runtime Storage API</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Overlay Change Set</td></tr>
-<tr>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-</tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: blue;">
-<tr><td>Memory / Database Interface</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Database</td></tr>
-<tr>
-	<td>Alice: 10</td>
-	<td>Bob: 20</td>
-	<td>Cindy: 30</td>
-	<td>Dave: 40</td>
-</tr>
-</table>
-
-</div>
-
----
-
-### Overlay: Balance Transfer
-
-<div class="flex-container">
-<div class="left-small" style="font-size:0.9em">
-
-1. Runtime Logic Initiates.
-1. Calls the Runtime Storage API.
-1. First we query the Overlay Change Set.
-   - Unfortunately it's not there.
-1. Then we query the underlying Database.
-   - Very slow as you have learned so far.
-
-</div>
-
-<div class="right">
-
-<table class="overlay-table">
-<tr><td style="background-color: red;">Runtime Logic</td></tr>
-<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: green;">
-<tr><td>Runtime Storage API</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Overlay Change Set</td></tr>
-<tr>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-</tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: blue;">
-<tr><td>Memory / Database Interface</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Database</td></tr>
-<tr>
-	<td>Alice: 10</td>
-	<td>Bob: 20</td>
-	<td>Cindy: 30</td>
-	<td>Dave: 40</td>
-</tr>
-</table>
-
-</div>
-
----
-
-### Overlay: Balance Transfer
-
-<br />
-<div class="flex-container">
-<div class="left-small">
-
-- As we return the data back to the runtime, we cache the values in the overlay.
-- Subsequent reads and writes happen in the overlay, since the data is there.
-
-</div>
-<div class="right">
-
-<table class="overlay-table">
-<tr><td style="background-color: red;">Runtime Logic</td></tr>
-<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: green;">
-<tr><td>Runtime Storage API</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Overlay Change Set</td></tr>
-<tr>
-	<td>Alice: 10</td>
-	<td>Bob: 20</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-</tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: blue;">
-<tr><td>Memory / Database Interface</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Database</td></tr>
-<tr>
-	<td>Alice: 10</td>
-	<td>Bob: 20</td>
-	<td>Cindy: 30</td>
-	<td>Dave: 40</td>
-</tr>
-</table>
-
-</div>
-
----
-
-### Overlay: Balance Transfer
-
-<br />
-<div class="flex-container">
-<div class="left-small">
-
-- The actual transfer logic happens in the runtime memory.
-- At some point, the runtime logic writes the new balances to storage, this updates the overlay cache.
-- The underlying database is not updated yet.
-
-</div>
-<div class="right">
-
-<table class="overlay-table">
-<tr><td style="background-color: red;">Runtime Logic</td></tr>
-<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: green;">
-<tr><td>Runtime Storage API</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Overlay Change Set</td></tr>
-<tr>
-	<td style="color: yellow;">Alice: 15</td>
-	<td style="color: yellow;">Bob: 15</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-</tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: blue;">
-<tr><td>Memory / Database Interface</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Database</td></tr>
-<tr>
-	<td>Alice: 10</td>
-	<td>Bob: 20</td>
-	<td>Cindy: 30</td>
-	<td>Dave: 40</td>
-</tr>
-</table>
-
-</div>
-
----
-
-### Overlay: Balance Transfer
-
-<br />
-<div class="flex-container">
-<div class="left-small">
-
-- At the end of the block, staged changes are committed to the database all at once.
-- Then storage root is recomputed a single time for the final block state.
-
-</div>
-<div class="right">
-
-<table class="overlay-table">
-<tr><td style="background-color: red;">Runtime Logic</td></tr>
-<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: green;">
-<tr><td>Runtime Storage API</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Overlay Change Set</td></tr>
-<tr>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-</tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: blue;">
-<tr><td>Memory / Database Interface</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Database</td></tr>
-<tr>
-	<td style="color: lightgreen;">Alice: 15</td>
-	<td style="color: lightgreen;">Bob: 15</td>
-	<td>Cindy: 30</td>
-	<td>Dave: 40</td>
-</tr>
-</table>
-
-</div>
-
----
-
-### Overlay: Implications
-
-<br />
-<div class="flex-container">
-<div class="left-small">
-
-- Reading the same storage a second or more time is faster (not free) than the initial read.
-- Writing the same value multiple times is fast (not free), and only results in a single final Database write.
-
-</div>
-<div class="right">
-
-<table class="overlay-table">
-<tr><td style="background-color: red;">Runtime Logic</td></tr>
-<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: green;">
-<tr><td>Runtime Storage API</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Overlay Change Set</td></tr>
-<tr>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-	<td>&nbsp;</td>
-</tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: blue;">
-<tr><td>Memory / Database Interface</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Database</td></tr>
-<tr>
-	<td>Alice: 15</td>
-	<td>Bob: 15</td>
-	<td>Cindy: 30</td>
-	<td>Dave: 40</td>
-</tr>
-</table>
-
-</div>
-
-Notes:
-
-also this means that cross implementation of substrate/polkadot can be tricky to ensure determinism (also true for next slide).
-
----
-
-### Additional Storage Overlays (Transactional)
-
-<br />
-<div class="flex-container">
-<div class="left-small text-small">
-
-- The runtime has the ability to spawn additional storage layers, called "transactional layers".
-- This can allow you to commit changes through the Runtime Storage API, but then drop the changes if you want before they get to the overlay change set.
-- The runtime can spawn multiple transactional layers, each at different times, allowing the runtime developer to logically separate when they want to commit or rollback changes.
-
-</div>
-<div class="right text-small">
-
-<table class="overlay-table">
-<tr><td style="background-color: red;">Runtime Logic</td></tr>
-<tr><td style="background-color: darkred;">Runtime Memory</td></tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: green;">
-<tr><td>Runtime Storage API</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Transactional Layer</td></tr>
-<tr>
-	<td style="color: yellow;">Alice: 25</td>
-	<td>&nbsp;</td>
-	<td style="color: yellow;">Cindy: 20</td>
-	<td>&nbsp;</td>
-</tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Overlay Change Set</td></tr>
-<tr>
-	<td>Alice: 15</td>
-	<td>&nbsp;</td>
-	<td>Cindy: 30</td>
-	<td>&nbsp;</td>
-</tr>
-</table>
-
-<br />
-<table class="overlay-table" style="background-color: blue;">
-<tr><td>Memory / Database Interface</td></tr>
-</table>
-
-<br />
-<table class="overlay-table">
-<tr><td colspan=4>Database</td></tr>
-<tr>
-	<td>Alice: 15</td>
-	<td>Bob: 15</td>
-	<td>Cindy: 30</td>
-	<td>Dave: 40</td>
-</tr>
-</table>
-
-</div>
-
----
-
-### Transactional Implementation Details
-
-- Non-Zero Overhead (but quite small)
-  - 0.15% overhead per key written, per storage layer.
-- Values are not copied between layers.
-  - Values are stored in heap, and we just move pointers around.
-  - So overhead has nothing to do with storage size, just the number of storage items in a layer.
-- Storage layers use client memory, so practically no upper limit.
-
-Notes:
-
-For more details see:
-
-- <https://github.com/paritytech/substrate/pull/10413>
-- <https://github.com/paritytech/substrate/pull/10809>
-
-In module 6, we can take a closer look at how this functionality is exposed in FRAME.
-
-See: <https://github.com/paritytech/substrate/pull/11431>
-
----
-
-## Storage Layer by Default
-
-All extrinsics execute within a transactional storage layer.
-
-This means that if you return an `Error` from your extrinsic, all changes to storage caused by that extrinsic are reverted.
-
-This is the same behavior as you would expect from smart contract environments like Ethereum.
-
----
-
-### Transactional Layer Attack
-
-Transactional layers can be used to attack your chain:
-
-<br />
-
-- Allow a user to spawn a lot of transactional layers.
-- On the top layer, make a bunch of changes.
-- All of those changes will need to propagate down each time.
-
-**Solution:**
-
-- Do not allow the user to create an unbounded number of layers within your runtime logic.
-
----
-
-# Runtime Storage APIs
-
----
-
-## Patricia Trie
-
-<img style="height: 500px;" src="./img/patricia-trie.svg" />
-
----
-
-## Storage Keys
-
-<img style="height: 500px;" src="./img/navigate-storage-2.svg" />
-
----
-
-## FRAME Storage Keys
-
-We follow a simple pattern:
-
-```
-hash(name) ++ hash(name2) ++ hash(name3) ++ hash(name4) ...
-```
-
-For example:
-
-```
-twox128(pallet_name) ++ twox128(storage_name) ++ ...
-```
-
-We will get into more details as we look at the specific storage primitives.
-
----
-
-## Pallet Name
-
-The pallet name comes from the `construct_runtime!`.
-
-```rust
-// Configure a mock runtime to test the pallet.
-frame_support::construct_runtime!(
-	pub enum Test {
-		System: frame_system::{Pallet, Call, Config, Storage, Event<T>},
-		Example: pallet_template,
-	}
-);
-```
-
-This means that changing the name of your pallet here is a **BREAKING** change, since it will change your storage keys.
-
----
-
-## FRAME Storage Primitives
-
-- `StorageValue`
-- `StorageMap`
-- `CountedStorageMap`
-- `StorageDoubleMap`
-- `StorageNMap`
-
-We will go over all of them, and many important and subtle details along the way.
-
----
-
-## Storage Value
-
-Place a single item into the runtime storage.
-
-```rust
-pub struct StorageValue<Prefix, Value, QueryKind = OptionQuery, OnEmpty = GetDefault>(_);
-```
-
-Storage Key:
-
-```rust
-Twox128(Prefix::pallet_prefix()) ++ Twox128(Prefix::STORAGE_PREFIX)
-```
-
----
-
-## Storage Value: Example
-
-```rust
-#[pallet::storage]
-pub type Item1<T> = StorageValue<_, u32>;
-```
-
-```rust
-#[test]
-fn storage_value() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		assert_eq!(Item1::<T>::get(), None);
-		Item1::<T>::put(10u32);
-		assert_eq!(Item1::<T>::get(), Some(10u32));
-	});
-}
-```
-
----
-
-## Storage "Prefix"
-
-The first generic parameter in any FRAME storage is the `Prefix`, which is used to generate the storage key.
-
-`Prefix` implements `StorageInstance` which has:
-
-```rust
-pub trait StorageInstance {
-	const STORAGE_PREFIX: &'static str;
-
-	fn pallet_prefix() -> &'static str;
-}
-```
-
-`STORAGE_PREFIX` is the name of the storage, and `pallet_prefix()` is the name of the pallet that this storage is in.
-
-This is populated thanks to FRAME's macro magic.
-
-Notes:
-
-<https://substrate.stackexchange.com/questions/476/storage-definition-syntax/478#478>
-
----
-
-## Storage Value Key
-
-```rust
-use sp_core::hexdisplay::HexDisplay;
-println!("{}", HexDisplay::from(&Item1::<T>::hashed_key()));
-```
-
-This will depend on your pallet's name of course...
-
-```sh
-e375d60f814d02157aaaa18f3639a254c64445c290236a18189385ed9853fb1e
-```
-
-```sh
-e375d60f814d02157aaaa18f3639a254 ++ c64445c290236a18189385ed9853fb1e
-```
-
-```sh
-twox128("Example") = e375d60f814d02157aaaa18f3639a254
-twox128("Item1") = c64445c290236a18189385ed9853fb1e
-```
-
----
-
-## Demystifying FRAME Storage
-
-This shows _basically_ what is going on when you use pallet storage. NOT accurate, but should be informative. As you can see, it is really not that complex.
-
-```rust
-struct Prefix;
-impl StorageInstance for Prefix {
-	const STORAGE_PREFIX: &'static str = "MyStorage";
-
-	fn pallet_prefix() -> &'static str {
-		"MyPallet"
-	};
-
-	fn prefix() -> Vec<u8> {
-		twox_128(Self::pallet_prefix()) ++ twox_128(STORAGE_PREFIX)
-	}
-}
-
-type MyStorage = StorageValue<Prefix, Type>;
-trait StorageValue<Prefix, Type> {
-    fn get() -> Option<Type> {
-        sp_io::storage::get(Prefix::prefix())
-    }
-
-    fn set(value: Type) {
-        sp_io::storage::set(Prefix::prefix(), value)
-    }
-
-    fn kill() {
-        sp_io::storage::clear(Prefix::prefix())
-    }
-
-    // etc...
-}
-```
-
----
-
-## All Storage is an Option
-
-- At the Runtime Storage API level, a storage key will either have a value or not have a value.
-- If there is no value, any query from the backend will be `None`.
-- If there is a value, the query will be `Some(value)`.
-- However, we can also hide this with a `Default` value.
-
----
-
-## Query If Storage Actually Exists
-
-There are APIs which expose to you whether the value actually exists in the database.
-
-```rust
-#[pallet::storage]
-pub type Item1<T> = StorageValue<_, u32>;
-```
-
-```rust
-#[test]
-fn storage_value() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		// Nothing is actually there yet.
-		assert_eq!(Item1::<T>::exists(), false);
-		assert_eq!(Item1::<T>::try_get().ok(), None);
-	});
-}
-```
-
----
-
-## Query Kind
-
-- `OptionQuery`: Default choice, represents the actual DB state.
-- `ValueQuery`: Return a value when `None`. (`Default` or configurable)
-
-```rust
-#[pallet::storage]
-pub type Item2<T> = StorageValue<_, u32, ValueQuery>;
-```
-
-```rust
-#[test]
-fn value_query() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		// `0u32` is the default value of `u32`
-		assert_eq!(Item2::<T>::get(), 0u32);
-		Item2::<T>::put(10u32);
-		assert_eq!(Item2::<T>::get(), 10u32);
-	});
-}
-```
-
-Remember that 0 is not actually in storage when doing the first query.
-
----
-
-## On Empty
-
-You can control the `OnEmpty` value with:
-
-```rust
-#[pallet::type_value]
-pub fn MyDefault<T: Config>() -> u32 { 42u32 }
-
-#[pallet::storage]
-pub type Item3<T> = StorageValue<_, u32, ValueQuery, MyDefault<T>>;
-```
-
-```rust
-#[test]
-fn my_default() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		// `42u32` is the configured `OnEmpty` value.
-		assert_eq!(Item3::<T>::get(), 42u32);
-		Item3::<T>::put(10u32);
-		assert_eq!(Item3::<T>::get(), 10u32);
-	});
-}
-```
-
-Remember that 42 is not actually in storage when doing the first query.
-
----
-
-## Not Magic
-
-These "extra features" are just ways to simplify your code.
-
-You can get the same effect without any magic:
-
-```rust
-let value = Item1::<T>::try_get().unwrap_or(42u32);
-```
-
-But you wouldn't want to do this every time.
-
----
-
-## Set vs Put
-
-- `pub fn set(val: QueryKind::Query)`
-- `pub fn put<Arg: EncodeLike<Value>>(val: Arg)`
-
-For Example:
-
-```rust
-#[pallet::storage]
-pub type Item1<T> = StorageValue<_, u32>;
-```
-
-```rust
-Item1::<T>::set(Some(42u32));
-Item1::<T>::put(42u32);
-```
-
----
-
-## Don't Put The Option AS the Storage Value
-
-This is basically an anti-pattern, and it doesn't really make sense to do.
-
-```rust
-#[pallet::storage]
-pub type Item4<T> = StorageValue<_, Option<u32>>;
-
-#[pallet::storage]
-pub type Item5<T> = StorageValue<_, Option<u32>, ValueQuery>;
-```
-
-```rust
-#[test]
-fn nonsense() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		assert_eq!(Item4::<T>::exists(), false);
-		assert_eq!(Item5::<T>::exists(), false);
-		Item4::<T>::put(None::<u32>);
-		Item5::<T>::put(None::<u32>);
-		assert_eq!(Item4::<T>::exists(), true);
-		assert_eq!(Item5::<T>::exists(), true);
-	});
-}
-```
-
----
-
-## Unit Type Instead of Bool
-
-You might want to simply signify some true or false value in storage...
-
-Save some bytes! Use the unit type.
-
-```rust
-#[pallet::storage]
-pub type Item6<T> = StorageValue<_, ()>;
-```
-
-```rust
-#[test]
-fn better_bool() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		// false case
-		assert_eq!(Item6::<T>::exists(), false);
-		Item6::<T>::put(());
-		// true case
-		assert_eq!(Item6::<T>::exists(), true);
-	});
-}
-```
-
----
-
-## Kill Storage
-
-Remove the item from the database using `kill()` or `take()`.
-
-```rust
-#[pallet::type_value]
-pub fn MyDefault<T: Config>() -> u32 { 42u32 }
-
-#[pallet::storage]
-pub type Item3<T> = StorageValue<_, u32, ValueQuery, MyDefault<T>>;
-```
-
-```rust
-#[test]
-fn kill() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		assert_eq!(Item3::<T>::get(), 42u32);
-		Item3::<T>::put(10u32);
-		assert_eq!(Item3::<T>::get(), 10u32);
-		//Item3::<T>::kill();
-		let old_value = Item3::<T>::take();
-		assert_eq!(Item3::<T>::get(), 42u32);
-		assert_eq!(old_value, 10u32);
-	});
-}
-```
-
----
-
-## Mutate
-
-Execute a closure on a storage item.
-
-```rust
-#[test]
-fn mutate() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		Item2::<T>::put(42u32);
-		Item2::<T>::mutate(|x| {
-			if *x % 2 == 0 {
-				*x = *x / 2;
-			}
-		});
-		assert_eq!(Item2::<T>::get(), 21);
-	});
-}
-```
-
----
-
-## Try Mutate
-
-Execute a closure on a storage item, but only write if the closure returns `Ok`.
-
-```rust
-#[test]
-fn try_mutate() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		Item2::<T>::put(42u32);
-		assert_noop!(Item2::<T>::try_mutate(|x| -> Result<(), ()> {
-			*x = *x / 2;
-			if *x % 2 == 0 {
-				Ok(())
-			} else {
-				Err(())
-			}
-		}), ());
-		// Nothing written
-		assert_eq!(Item2::<T>::get(), 42);
-	});
-}
-```
-
----
-
-## Assert Noop
-
-You may have noticed we just used `assert_noop!` instead of `assert_err!`.
-
-```rust
-/// Evaluate an expression, assert it returns an expected `Err` value and that
-/// runtime storage has not been mutated (i.e. expression is a no-operation).
-///
-/// Used as `assert_noop(expression_to_assert, expected_error_expression)`.
-#[macro_export]
-macro_rules! assert_noop {
-	(
-		$x:expr,
-		$y:expr $(,)?
-	) => {
-		let h = $crate::storage_root($crate::StateVersion::V1);
-		$crate::assert_err!($x, $y);
-		assert_eq!(h, $crate::storage_root($crate::StateVersion::V1), "storage has been mutated");
-	};
-}
-```
-
-There is also `assert_storage_noop!` which does not care what is returned, just that storage is not changed.
-
----
-
-## Vec Tricks
-
-You can use `decode_len()` and `append()` to work with a `Vec` without decoding all the items.
-
-```rust
-#[pallet::storage]
-#[pallet::unbounded]
-pub type Item7<T> = StorageValue<_, Vec<u8>, ValueQuery>;
-```
-
-```rust
-#[test]
-fn vec_tricks() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		assert_eq!(Item7::<T>::decode_len(), None);
-		Item7::<T>::put(vec![0u8]);
-		assert_eq!(Item7::<T>::decode_len(), Some(1));
-		Item7::<T>::append(1u8);
-		Item7::<T>::append(2u8);
-		assert_eq!(Item7::<T>::get(), vec![0u8, 1u8, 2u8]);
-		assert_eq!(Item7::<T>::decode_len(), Some(3));
-	});
-}
-```
-
----
-
-## Bounded Storage
-
-You may have noticed `#[pallet::unbounded]` on the storage item in the previous slide.
-
-Remember that blockchains are limited by:
-
-- Computation Time
-- Memory Limits
-- Storage Size / Proof Size
-
-In general, every storage item in FRAME should be **bounded** in size.
-
-We will talk about this more when we discuss benchmarking.
-
----
-
-## Bounded Vector
-
-We have bounded versions of unbounded items like `Vec`, `BTreeSet`, etc...
-
-```rust
-#[pallet::storage]
-pub type Item8<T> = StorageValue<_, BoundedVec<u8, ConstU32<100>>, ValueQuery>;
-```
-
-A second `Get<u32>` type is used to give a maximum number of values.
-
-```rust
-#[test]
-fn bounded_vec() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		for i in 0u8..100u8 {
-			assert_ok!(Item8::<T>::try_append(i));
-		}
-		// Only supports at most 100 items.
-		assert_noop!(Item8::<T>::try_append(100), ());
-	});
-}
-```
-
----
-
-## Storage Map
-
-Store items in storage as a key and value map.
-
-```rust
-pub struct StorageMap<Prefix, Hasher, Key, Value, QueryKind = OptionQuery, OnEmpty = GetDefault, MaxValues = GetDefault>(_);
-```
-
-Storage Key:
-
-```rust
-Twox128(Prefix::pallet_prefix()) ++ Twox128(Prefix::STORAGE_PREFIX) ++ Hasher1(encode(key))
-```
-
----
-
-## Storage Map: Example
-
-```rust
-#[pallet::storage]
-pub type Item9<T: Config> = StorageMap<_, Blake2_128, u32, u32>;
-```
-
-```rust
-#[test]
-fn storage_map() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		Item9::<T>::insert(0, 100);
-		assert_eq!(Item9::<T>::get(0), Some(100));
-		assert_eq!(Item9::<T>::get(1), None);
-	});
-}
-```
-
----
-
-## Storage Map Key
-
-With a storage map, you can introduce a "key" and "value" of arbitrary type.
-
-```rust
-pub struct StorageMap<Prefix, Hasher, Key, Value, ...>(_);
-```
-
-The storage key for a map uses the hash of the key. You can choose the storage hasher, these are the ones currently implemented:
-
-- Identity (no hash at all)
-- Blake2_128
-- Blake2_256
-- Twox128
-- Twox256
-- Twox64Concat (special)
-- Blake2_128Concat (special)
-
----
-
-## Value Query: Balances
-
-```rust
-#[pallet::storage]
-pub type Item10<T: Config> = StorageMap<_, Blake2_128, T::AccountId, Balance, ValueQuery>;
-```
-
-```rust
-#[test]
-fn balance_map() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		// these would normally would be 32 byte addresses
-		let alice = 0u64;
-		let bob = 1u64;
-		Item10::<T>::insert(alice, 100);
-
-		let transfer = |from: u64, to: u64, amount: u128| -> Result<(), &'static str> {
-			Item10::<T>::try_mutate(from, |from_balance| -> Result<(), &'static str> {
-				Item10::<T>::try_mutate(to, |to_balance| -> Result<(), &'static str> {
-					*to_balance = to_balance.checked_add(amount).ok_or("overflow")?;
-					*from_balance = from_balance.checked_sub(amount).ok_or("not enough balance")?;
-					Ok(())
-				})
-			})
-		};
-
-		assert_noop!(transfer(bob, alice, 10), "not enough balance");
-		assert_ok!(transfer(alice, bob, 10));
-		assert_noop!(transfer(alice, bob, 100), "not enough balance");
-
-		assert_eq!(Item10::<T>::get(alice), 90);
-		assert_eq!(Item10::<T>::get(bob), 10);
-	});
-}
-```
-
----
-
-## Prefix Tries
-
-All pallets and storage items naturally form "prefix tries".
-
-<img style="height: 500px;" src="./img/balance-trie.svg" />
-
-In this diagram, a pallet "Balances" has a storage value "Total Issuance" and a map of "Accounts" with balances as the value.
-
----
-
-## Prefix Trie Keys
-
-Let's now look at the keys of these storage items:
-
-```rust
-use sp_core::hexdisplay::HexDisplay;
-println!("{}", HexDisplay::from(&Item2::<T>::hashed_key()));
-println!("{}", HexDisplay::from(&Item10::<T>::hashed_key_for(0)));
-println!("{}", HexDisplay::from(&Item10::<T>::hashed_key_for(1)));
-```
-
-```sh
-e375d60f814d02157aaaa18f3639a2546fe5a43b77d7334acfb711a021a514b8
-e375d60f814d02157aaaa18f3639a254ca79d14bc48854f664528f3a696b6c27c804ce198ec337e3dc762bdd1a09aece
-e375d60f814d02157aaaa18f3639a254ca79d14bc48854f664528f3a696b6c279ea2d098b5f70192f96c06f38d3fbc97
-```
-
-<table style="font-size: 24px">
-<tr>
-	<td><span style="color: red;">e375d60f814d02157aaaa18f3639a254</span></td>
-	<td><span style="color: lightblue;">6fe5a43b77d7334acfb711a021a514b8</span></td>
-	<td>&nbsp;</td>
-</tr>
-<tr>
-	<td><span style="color: red;">e375d60f814d02157aaaa18f3639a254</span></td>
-	<td><span style="color: lightgreen;">ca79d14bc48854f664528f3a696b6c27</span></td>
-	<td><span style="color: pink;">c804ce198ec337e3dc762bdd1a09aece</span></td>
-</tr>
-<tr>
-	<td><span style="color: red;">e375d60f814d02157aaaa18f3639a254</span></td>
-	<td><span style="color: lightgreen;">ca79d14bc48854f664528f3a696b6c27</span></td>
-	<td><span style="color: orange;">9ea2d098b5f70192f96c06f38d3fbc97</span></td>
-</tr>
-</table>
-
----
-
-## Storage Iteration
-
-Because all storage items form a prefix trie, you can iterate the content starting with any prefix:
-
-```rust [0|6-7]
-impl<T: Decode + Sized> Iterator for StorageIterator<T> {
-	type Item = (Vec<u8>, T);
-
-	fn next(&mut self) -> Option<(Vec<u8>, T)> {
-		loop {
-			let maybe_next = sp_io::storage::next_key(&self.previous_key)
-				.filter(|n| n.starts_with(&self.prefix));
-			break match maybe_next {
-				Some(next) => {
-					self.previous_key = next.clone();
-					let maybe_value = frame_support::storage::unhashed::get::<T>(&next);
-					match maybe_value {
-						Some(value) => {
-							if self.drain {
-								frame_support::storage::unhashed::kill(&next);
-							}
-							Some((self.previous_key[self.prefix.len()..].to_vec(), value))
-						},
-						None => continue,
-					}
-				},
-				None => None,
-			}
-		}
-	}
-}
-```
-
----
-
-## You can...
-
-- Iterate all storage on the blockchain using prefix `&[]`
-- Iterate all storage for a pallet using prefix `hash(pallet_name)`
-- Iterate all balances of users using prefix `hash("Balances") ++ hash("Accounts")`
-
-This is not an inherit property!
-
-This is only because we "cleverly" chose this pattern for generating keys.
-
-Note that iteration has no "proper" order. All keys are hashed, and we just go in the order of the resulting hash.
-
----
-
-## Opaque Storage Keys
-
-But there is a problem...
-
-Let's say I iterate over all users' balances...
-
-- I will get all the balance values.
-- I will get all the storage keys.
-  - Which are all hashed.
-- I will NOT get the actual accounts which hold these balances!
-
-For this, we need **transparent storage keys**.
-
----
-
-## Transparent Hashes
-
-- Twox64Concat
-- Blake2_128Concat
-
-Basically:
-
-```sh
-final_hash = hash(preimage) ++ preimage
-```
-
-From this kind of hash, we can always extract the preimage:
-
-```sh
-"hello" = 0x68656c6c6f
-blake2_128("hello") = 0x46fb7408d4f285228f4af516ea25851b
-blake2_128concat("hello") = 0x46fb7408d4f285228f4af516ea25851b68656c6c6f
-```
-
-```sh
-"world" = 0x776f726c64
-twox64("world") = 0xef51ee66fefb78e7
-twox64concat("world") = 0xef51ee66fefb78e7776f726c64
-```
-
----
-
-## Better Balance Map
-
-<div class="text-small">
-
-We should use `Blake2_128Concat`!
-
-```rust
-#[pallet::storage]
-pub type Item11<T: Config> = StorageMap<_, Blake2_128Concat, T::AccountId, Balance, ValueQuery>;
-```
-
-```rust
-#[test]
-fn better_balance_map() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		for i in 0u64..10u64 {
-			Item10::<T>::insert(i, u128::from(i * 100u64));
-			Item11::<T>::insert(i, u128::from(i * 100u64));
-		}
-		// cannot call iter for 10 because it cannot returns the keys
-		let all_10: Vec<_> = Item10::<T>::iter_values().collect();
-		let all_11: Vec<_> = Item11::<T>::iter().collect();
-		println!("{:?}\n{:?}", all_10, all_11);
-
-		assert!(false)
-	});
-}
-```
-
-```sh
-[600, 500, 300, 100, 800, 400, 700, 900, 0, 200]
-[(6, 600), (5, 500), (3, 300), (1, 100), (8, 800), (4, 400), (7, 700), (9, 900), (0, 0), (2, 200)]
-```
-
-</div>
-
----
-
-## Which Hasher to Use?
-
-Now that we know that transparent hashers are extremely useful, there are really just 3 choices:
-
-- `Identity` - No Hash at all
-- `Twox64Concat` - Non-Cryptographic and Transparent Hash
-- `Blake2_128Concat` - Cryptographic and Transparent Hash
-
----
-
-## Unbalanced Trie
-
-<div class="flex-container">
-<div class="left">
-
-<img src="./img/unbalanced-tree.svg" />
-
-</div>
-<div class="right">
-
-- We mentioned that unbalanced tries can be good at times...
-- But in this case, we must select a hasher which prevents a user from manipulating the balance of our prefix trie.
-
-</div>
-</div>
-
----
-
-## Which Hasher to Use?
-
-Basically, you should just always use `Blake2_128Concat` since it is hardest for a user to influence.The difference in time to execute is probably nominal (but not properly benchmarked afaik).
-
-Some reasonable exceptions:
-
-- If the key is already an uncontrollable cryptographic hash, you can use `Identity`.
-- If the key is simple and controlled by runtime (like an incremented count), `Twox64Concat` is good enough.
-
-More info in the docs...
-
----
-
-### Read the StorageMap Docs for API
-
-<https://crates.parity.io/frame_support/pallet_prelude/struct.StorageMap.html>
-
----
-
-### StorageDoubleMap and StorageNMap
-
-Basically the same idea as `StorageMap`, but with more keys:
-
-```rust
-pub struct StorageDoubleMap<Prefix, Hasher1, Key1, Hasher2, Key2, Value, QueryKind = OptionQuery, OnEmpty = GetDefault, MaxValues = GetDefault>(_);
-```
-
-```sh
-Twox128(Prefix::pallet_prefix()) ++ Twox128(Prefix::STORAGE_PREFIX) ++ Hasher1(encode(key1)) ++ Hasher2(encode(key2))
-```
-
-```rust
-pub struct StorageNMap<Prefix, Key, Value, QueryKind = OptionQuery, OnEmpty = GetDefault, MaxValues = GetDefault>(_);
-```
-
-```sh
-Twox128(Prefix::pallet_prefix())
-		++ Twox128(Prefix::STORAGE_PREFIX)
-		++ Hasher1(encode(key1))
-		++ Hasher2(encode(key2))
-	++ ...
-	++ HasherN(encode(keyN))
-```
-
----
-
-## StorageNMap: Example
-
-```rust
-#[pallet::storage]
-pub type Item12<T: Config> = StorageNMap<
-	_,
-	(
-		NMapKey<Blake2_128Concat, u8>,
-		NMapKey<Blake2_128Concat, u16>,
-		NMapKey<Blake2_128Concat, u32>,
-	),
-	u128,
->;
-```
-
-Treat the key as a tuple of the composite keys.
-
-```rust
-#[test]
-fn storage_n_map() {
-	sp_io::TestExternalities::new_empty().execute_with(|| {
-		Item12::<T>::insert((1u8, 1u16, 1u32), 1u128);
-		assert_eq!(Item12::<T>::get((1u8, 1u16, 1u32)), Some(1u128));
-	});
-}
-```
-
----
-
-## Map Iteration Complexity
-
-- Iterating over a map is extremely expensive for computational and storage proof resources.
-- Requires `N` trie reads which is really `N * log(N)` database reads.
-- Takes up `32 bytes per hash * 16 hashes per node * N * log(N)` proof size.
-
-Generally you should not iterate on a map. If you do, make sure it is bounded!
-
----
-
-## Remove All
-
-Implemented on Storage Maps:
-
-```rust
-// Remove all value of the storage.
-pub fn remove_all(limit: Option<u32>) -> KillStorageResult
-```
-
-Where:
-
-```rust
-pub enum KillStorageResult {
-    AllRemoved(u32),
-    SomeRemaining(u32),
-}
-```
-
-Rather than trying to delete all items at once, you can "freeze" the state machine, and have a user call `remove_all` multiple times using a limit.
-
----
-
-## Counted Storage Map
-
-A wrapper around a `StorageMap` and a `StorageValue<Value=u32>` to keep track of how many items are in a map, without needing to iterate all the values.
-
-```rust
-pub struct CountedStorageMap<Prefix, Hasher, Key, Value, QueryKind = OptionQuery, OnEmpty = GetDefault, MaxValues = GetDefault>(_);
-```
-
-This storage item has additional storage read and write overhead when manipulating values compared to a regular storage map.
-
----
-
-## Counted Storage Map Demystified
-
-```rust
-#[pallet::storage]
-pub type Item13<T: Config> = CountedStorageMap<_, Blake2_128Concat, T::AccountId, Balance>;
-```
-
-This `CountedStorageMap` is exactly the same as:
-
-```rust
-#[pallet::storage]
-pub type Item13<T: Config> = StorageMap<_, Blake2_128Concat, T::AccountId, Balance>;
-
-/// Counter is always prefixed with "CounterFor"
-#[pallet::storage]
-pub type CounterForItem13<T: Config> = StorageValue<_, u32>;
-```
-
-With some additional logic to keep these two in check.
-
----
-
-## Architecture Considerations
-
-- You know that accessing very large items from the database is not efficient:
-  - Databases like ParityDB are optimized for items under 32 KB.
-  - Decoding is non-zero overhead.
-- You know that accessing lots of storage items in a map is also very bad!
-  - Lots of overhead constantly calling host functions.
-  - Lots of overhead from the merkle trie lookup, and database reads.
-  - Lots of **additional** overhead in the storage proof
-
-So what do you pick?
-
----
-
-## It depends! Sometimes both!
-
-The choice of storage depends on how your logic will access it.
-
-<div class="text-small">
-
-- Scenario A: We need to manage millions of users, and support balance transfers.
-
-  - We should obviously use a map! Balance transfers touch only 2 accounts at a time. 2 map reads is way more efficient than reading all million users to move the balance.
-
-- Scenario B: We need to get the 1,000 validators for the next era.
-
-  - We should obviously use a bounded vector! We know there is an upper limit of validators, and we will need to read them all for our logic!
-
-- Scenario C: We need to store some metadata about the configuration of each validator.
-
-  - We should probably use a map! We will be duplicating some data from from the vector above, but the way we access configuration stuff usually is on a per-validator basis.
-
-</div>
-
----
-
-## Summary
-
-- FRAME Storage is just simple macros which wrap the underlying Substrate Storage APIs.
-- The principles of Substrate Storage directly inform what kinds of behaviors you can do in FRAME.
-- Just because something does not exist in FRAME does not mean you cannot do it!
-- Just because something does exist in FRAME does not mean you can use it without thinking!
diff --git a/content/frame/traits/page.md b/content/frame/traits/page.md
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-# Outer Enum
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/frame/traits/slides.md b/content/frame/traits/slides.md
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----
-title: FRAME Pallets & Traits
-description: A review of common Pallets & Traits.
-duration: 1 hour
----
-
-# FRAME Pallets & Traits
-
----
-
-## Overview
-
-We will walk through the codebase and touch on various commonly used pallets and traits.
-
-The goal is to learn by example, and show how you can use the Substrate codebase to self-educate and solve problems.
-
----
-
-## System Pallet
-
----
-
-## Utility Pallet
-
----
-
-## Proxy Pallet
-
----
-
-## Multisig Pallet
-
----
-
-## Held vs Frozen Balance
-
-- Reserved -> Held
-- Locked -> Frozen
-- Both states belong to the user... but cannot be spent / transferred.
-- Held balances stack on top of one another.
-  - Useful for user deposits, or other use cases where there is sybil concerns.
-  - Ex: Deposit for storing data on-chain,
-- Frozen balances can overlap each other.
-  - Useful when you want to use the same tokens for multiple use cases.
-  - Ex: Using the same tokens for both staking and voting in governance.
-
----
-
-## Held Balances
-
-```text
-  Total Balance
-┌─────────────────────────────────────────────────────────┐
-┌────────────────────────────────┼────────────────────────┐
-│┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼                     |ED│
-└────────────────────────────────┼────────────────────────┘
-   Held Balance                      Transferable Balance
-
-┌───────────┐
-│┼┼┼┼┼┼┼┼┼┼┼│  Various Storage Deposits
-└───────────┤
-            ├──────┐
-            │┼┼┼┼┼┼│  Treasury Proposal Deposit
-            └──────┤
-                   ├──────────┐
-                   │┼┼┼┼┼┼┼┼┼┼│  Multisig Deposit
-                   └──────────┤
-                              ├──┐
-                              │┼┼│  Proxy Deposit
-                              └──┘
-```
-
----
-
-## New Holds Example
-
-```text
-  Total Balance
-┌─────────────────────────────────────────────────────────┐
-┌────────────────────────────────┼────────────────────────┐
-│┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼                     |ED│
-└────────────────────────────────┼────────────────────────┘
-   Held Balance                      Transferable Balance
-
-
-                                     ┌────────────────────┐
-              New Hold Successful!   │┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼│
-                                     └────────────────────┘
-
-                         ┌────────────────────────────────┐
-    New Hold Failed :(   │┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼│
-                         └────────────────────────────────┘
-```
-
----
-
-## Frozen Balances
-
-```text
-  Total Balance
-┌─────────────────────────────────────────────────────────┐
-┌────────────────────────────────┼────────────────────────┐
-│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX                     |ED│
-└────────────────────────────────┼────────────────────────┘
-   Frozen Balance                    Transferable Balance
-
-┌───────────────────────┐
-│XXXXXXXXXXXXXXXXXXXXXXX│  Vesting Balance
-└───────────────────────┘
-
-┌────────────────────────────────┐
-│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX│  Staking Bond Freeze
-└────────────────────────────────┘
-
-┌─────────────────┐
-│XXXXXXXXXXXXXXXXX│  Governance Vote Freeze
-└─────────────────┘
-```
-
----
-
-## New Freeze Example
-
-```text
-  Total Balance
-┌─────────────────────────────────────────────────┐
-┌────────────────────────────────┼────────────────┐
-│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX             |ED│
-└────────────────────────────────┼────────────────┘
-   Frozen Balance                    Transferable Balance
-
-┌───────────────────────┐
-│XXXXXXXXXXXXXXXXXXXXXXX│  New Freeze Successful!
-└───────────────────────┘
-
-┌─────────────────────────────────────────────────┐
-│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX│  New Freeze Successful!
-└─────────────────────────────────────────────────┘
-
-┌─────────────────────────────────────────────────────────┐
-│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX│  New Freeze Successful!
-└─────────────────────────────────────────────────────────┘
-```
-
----
-
-## Freeze and Hold Overlap
-
-```text
-  Total Balance
-┌──────────────────────────────────────────────────────────────┐
-   Held Balance
-┌────────────────────────────────┼─────────────────────────────┐
-│┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼┼                                | E │
-│XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX                         | D │
-└────────────────────────────────┼─────────────────────────────┘
-   Frozen Balance                    Transferable Balance
-```
-
----
-
-## Balances Pallet & Fungible Traits
-
----
-
-## Assets Pallet & Fungibles Traits
-
----
-
-## NFT Pallet & Non-Fungibles Traits
-
----
-
-## Transaction Payment Pallet
-
----
-
-## Sudo Pallet
-
----
-
-## Conviction Voting + Referenda Pallet
-
-(Open Governance)
-
----
-
-## Ranked Collectives + Whitelist Pallet
-
-(Technical Fellowship)
-
----
-
-## Scheduler Pallet
-
----
-
-## Polkadot Deep Dives
-
-<img style="height: 500px" src="./img/polkadot-deep-dive.png" />
-
-> <https://www.youtube.com/watch?v=_FwqB4FwWXk&list=PLOyWqupZ-WGsfnlpkk0KWX3uS4yg6ZztG>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/README.md b/content/polkadot/README.md
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-index.md
\ No newline at end of file
diff --git a/content/polkadot/_materials/regiser.md b/content/polkadot/_materials/regiser.md
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-# Register a Parachain
-
-Follow along the docs here: <https://docs.substrate.io/tutorials/build-application-logic/use-macros-in-a-custom-pallet/>
-
-Specifically you will need to:
-
-1. Setup a relay chain - <https://docs.substrate.io/tutorials/build-a-parachain/prepare-a-local-relay-chain/>
-1. Connect a parachain - <https://docs.substrate.io/tutorials/build-a-parachain/connect-a-local-parachain/>
-
-The remainder are extra fun.
diff --git a/content/polkadot/async-backing-deep/img/Statement_Distribution.svg b/content/polkadot/async-backing-deep/img/Statement_Distribution.svg
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diff --git a/content/polkadot/async-backing-deep/page.md b/content/polkadot/async-backing-deep/page.md
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-# Asynchronous Backing (Deep)
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/polkadot/async-backing-deep/slides.md b/content/polkadot/async-backing-deep/slides.md
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----
-title: Deep Dive, Asynchronous Backing
-description: Decoupling Backing and Inclusion Through Advance Work Based on Happy Path Assumptions
-duration: 1 hour
----
-
-# Deep Dive, Asynchronous Backing
-
-Notes:
-
-I'll be presenting the second of 3 lectures providing a window into Polkadot core, a slice of where we're at and where we're headed.
-
-This lecture covers asynchronous backing, the new feature with potential to deliver shorter parachain block times and an order of magnitude increase in quantity of Polkadot blockspace.
-
-Lets get to it
-
----
-
-## Overview
-
-<pba-flex center>
-
-- Async Backing Motivation
-- Laying the Groundwork, Contextual Execution of Parablocks
-- Prospective Parachains, Storing Products of the Backing Process
-- Supporting Changes
-- Async Backing Advantages, Current and Future
-
-</pba-flex>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Async Backing Motivation
-
----
-
-## Terminology: Backable vs Backed
-
-<pba-flex center>
-
-- Backable candidate:
-  - Output of the off-chain backing process
-  - Received a quorum of "valid" votes from its backing group
-- Backed candidate:
-  - A backable candidate that has been placed on-chain
-  - Also termed "pending availability"
-
-</pba-flex>
-
-Notes:
-
-We avoid backing any candidate on the relay chain unless we know there is room for that candidate in the availability process.
-To do otherwise risks wasted on-chain work.
-
-When a candidate is backed on-chain it immediately occupies an availability core and enters the availability, or erasure coding, process.
-
----
-
-## Synchronous Backing
-
-<img rounded style="width: 1500px" src="../async-backing-shallow/img/async_backing_3.svg" />
-
-Note:
-
-Can anyone spot a problem with synchronous model?
-
-- Problem 1
-
-  - Can only start work on new parablock when prior is included
-  - One relay block for backing, one for inclusion
-  - Minimum block time of 12 seconds
-
-- Problem 2
-  - Minimal time to submit collation for 12 second total block time
-  - About .5 seconds
-  - Not enough to fill block fully
-
----
-
-## Asynchronous Backing
-
-<img rounded style="width: 1500px" src="../async-backing-shallow/img/async_backing_3.svg" />
-
-Notes:
-
-- Point out the two independent processes and the "stopping points between them"
-- Walk through, starting with unincluded segment
-
----
-
-## The Async Backing Reasonable Collator Assumptions
-
-<pba-flex center>
-
-1. "The best existing parablock I'm aware of will eventually be included in the relay chain."
-1. "There won't be a chain reversion impacting that best parablock."
-
-</pba-flex>
-
-<br />
-<br />
-
-> The Stakes Are Low
-
-Notes:
-
-Best is determined by a process similar to the BABE fork choice rule.
-Brief BABE fork choice rule review
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Contextual Execution of Parablocks
-
----
-
-## Async Backing Execution Context
-
-<pba-cols>
-<pba-col center>
-
-- From relay chain
-  - Base constraints
-  - Relay parent
-- From unincluded segment
-  - Constraint modifications
-  - Required parent
-
-</pba-col>
-<pba-col>
-
-<img rounded style="width: 500px" src="./img/context.jpeg" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- How it was before:
-  - Required parent included in relay parent
-  - No need for constraint modifications
-- Relay parent vs required parent
-- Base constraints vs modifications
-
----
-
-## Constraints and Modifications
-
-```rust
-pub struct Constraints {
-	/// The minimum relay-parent number accepted under these constraints.
-	pub min_relay_parent_number: BlockNumber,
-	/// The maximum Proof-of-Validity size allowed, in bytes.
-	pub max_pov_size: usize,
-	/// The maximum new validation code size allowed, in bytes.
-	pub max_code_size: usize,
-	/// The amount of UMP messages remaining.
-	pub ump_remaining: usize,
-	/// The amount of UMP bytes remaining.
-	pub ump_remaining_bytes: usize,
-	/// The maximum number of UMP messages allowed per candidate.
-	pub max_ump_num_per_candidate: usize,
-	/// Remaining DMP queue. Only includes sent-at block numbers.
-	pub dmp_remaining_messages: Vec<BlockNumber>,
-	/// The limitations of all registered inbound HRMP channels.
-	pub hrmp_inbound: InboundHrmpLimitations,
-	/// The limitations of all registered outbound HRMP channels.
-	pub hrmp_channels_out: HashMap<ParaId, OutboundHrmpChannelLimitations>,
-	/// The maximum number of HRMP messages allowed per candidate.
-	pub max_hrmp_num_per_candidate: usize,
-	/// The required parent head-data of the parachain.
-	pub required_parent: HeadData,
-	/// The expected validation-code-hash of this parachain.
-	pub validation_code_hash: ValidationCodeHash,
-	/// The code upgrade restriction signal as-of this parachain.
-	pub upgrade_restriction: Option<UpgradeRestriction>,
-	/// The future validation code hash, if any, and at what relay-parent
-	/// number the upgrade would be minimally applied.
-	pub future_validation_code: Option<(BlockNumber, ValidationCodeHash)>,
-}
-
-/// Modifications to constraints as a result of prospective candidates.
-#[derive(Debug, Clone, PartialEq)]
-pub struct ConstraintModifications {
-	/// The required parent head to build upon.
-	pub required_parent: Option<HeadData>,
-	/// The new HRMP watermark
-	pub hrmp_watermark: Option<HrmpWatermarkUpdate>,
-	/// Outbound HRMP channel modifications.
-	pub outbound_hrmp: HashMap<ParaId, OutboundHrmpChannelModification>,
-	/// The amount of UMP messages sent.
-	pub ump_messages_sent: usize,
-	/// The amount of UMP bytes sent.
-	pub ump_bytes_sent: usize,
-	/// The amount of DMP messages processed.
-	pub dmp_messages_processed: usize,
-	/// Whether a pending code upgrade has been applied.
-	pub code_upgrade_applied: bool,
-}
-```
-
-Notes:
-
-Constraints to Highlight:
-
-- required_parent: Fragment would place its corresponding candidate here for children
-- min_relay_parent_number: Monotonically increasing rule, max_ancestry_len
-- ump_messages_sent mods ump_remaining
-- code_upgrade_applied: Only one in the unincluded segment at a time!
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Prospective Parachains
-
-Storing Products of the Backing Process
-
----
-
-## Prospective Parachains Snapshot
-
-<img rounded style="width: 1500px" src="../async-backing-shallow/img/Prospective_Parachains_Overview.svg" />
-
-Notes:
-
-- Fragment trees only built for active leaves
-- Fragment trees built per scheduled parachain at each leaf
-- Fragment trees may have 0 or more fragments representing potential parablocks making up possible futures for a parachain's state.
-- Collation generation, passing, and seconding work has already been completed for each fragment.
-
----
-
-## Anatomy of A Fragment Tree
-
-<img rounded style="width: 1500px" src="./img/Fragment_Tree_Dissected.svg" />
-
-Notes:
-
-In this order
-
-- Scope
-- Root node: corresponds to most recently included candidate
-- Child nodes: Mention required parent rule
-- `FragmentNode` contents
-- `CandidateStorage`
-- `GetBackableCandidate`
-
----
-
-<img rounded style="width: 500px" src="./img/checklist.jpeg" />
-
-## Fragment Tree Inclusion Checklist
-
-When and where can a candidate be included in a fragment tree?
-
-<pba-flex center>
-
-- Required parent is in tree
-  - Included as child of required parent, if at all
-- `Fragment::validate_against_constraints()` passes
-- Relay parent in scope
-
-</pba-flex>
-
----
-
-## Relay Parent Limitations for Fragments
-
-What does it mean for a relay parent to be in scope?
-
-When is a relay parent allowed to be out of scope?
-
-Notes:
-
-In Scope:
-
-- On same fork of the relay chain
-- Within `allowed_ancestry_len`
-
-Out of scope:
-
-- Candidates pending availability have been seen on-chain and need to be accounted for even if they go out of scope.
-  The most likely outcome for candidates pending availability is that they will become available, so we need those blocks to be in the `FragmentTree` to accept their children.
-- Relay parent can't move backwards relative to that of the required parent
-
----
-
-## Assembling Base Constraints
-
-Excerpt from `backing_state()` in `runtime/parachains/src/runtime_api_impl/vstaging.rs`
-
-```rust
-let (ump_msg_count, ump_total_bytes) = <ump::Pallet<T>>::relay_dispatch_queue_size(para_id);
-let ump_remaining = config.max_upward_queue_count - ump_msg_count;
-
-let constraints = Constraints {
-		min_relay_parent_number,
-		max_pov_size: config.max_pov_size,
-		max_code_size: config.max_code_size,
-		ump_remaining,
-		ump_remaining_bytes,
-		max_ump_num_per_candidate: config.max_upward_message_num_per_candidate,
-		dmp_remaining_messages,
-		hrmp_inbound,
-		hrmp_channels_out,
-		max_hrmp_num_per_candidate: config.hrmp_max_message_num_per_candidate,
-		required_parent,
-		validation_code_hash,
-		upgrade_restriction,
-		future_validation_code,
-	};
-```
-
----
-
-## Applying Constraint Modifications
-
-Excerpt from `Constraints::apply_modifications()`
-
-```rust
-if modifications.dmp_messages_processed > new.dmp_remaining_messages.len() {
-	return Err(ModificationError::DmpMessagesUnderflow {
-		messages_remaining: new.dmp_remaining_messages.len(),
-		messages_processed: modifications.dmp_messages_processed,
-	})
-} else {
-	new.dmp_remaining_messages =
-		new.dmp_remaining_messages[modifications.dmp_messages_processed..].to_vec();
-}
-```
-
----
-
-## Validating Against Constraints
-
-`Excerpt from Fragment::validate_against_constraints()`
-
-```rust
-if relay_parent.number < constraints.min_relay_parent_number {
-	return Err(FragmentValidityError::RelayParentTooOld(
-		constraints.min_relay_parent_number,
-		relay_parent.number,
-	))
-}
-```
-
----
-
-## AsyncBackingParams
-
-```rust
-pub struct AsyncBackingParams {
-	/// The maximum number of para blocks between the para head in a relay parent
-	/// and a new candidate. Restricts nodes from building arbitrary long chains
-	/// and spamming other validators.
-	///
-	/// When async backing is disabled, the only valid value is 0.
-	pub max_candidate_depth: u32,
-	/// How many ancestors of a relay parent are allowed to build candidates on top
-	/// of.
-	///
-	/// When async backing is disabled, the only valid value is 0.
-	pub allowed_ancestry_len: u32,
-}
-```
-
-</br>
-<pba-flex center>
-
-Numbers in use for testing Prospective Parachains:
-
-- `max_candidate_depth` = 4
-- `allowed_ancestry_len` = 3
-
-</pba-flex>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Supporting Changes
-
----
-
-## Statement Distribution Changes
-
-<img rounded style="width: 1500px" src="./img/Statement_Distribution.svg" />
-
-Notes:
-
-Why do we need the refactor?
-
-Answer: Cap on simultaneous candidates per backing group ~3x higher
-
-Mention
-
-- Announcement - Acknowledgement
-- Request - Response
-
----
-
-## Provisioner Changes
-
-Function `request_backable_candidates` from the Provisioner subsystem
-
-```rust
-/// Requests backable candidates from Prospective Parachains subsystem
-/// based on core states.
-///
-/// Should be called when prospective parachains are enabled.
-async fn request_backable_candidates(
-	availability_cores: &[CoreState],
-	bitfields: &[SignedAvailabilityBitfield],
-	relay_parent: Hash,
-	sender: &mut impl overseer::ProvisionerSenderTrait,
-) -> Result<Vec<CandidateHash>, Error> {
-	let block_number = get_block_number_under_construction(relay_parent, sender).await?;
-
-	let mut selected_candidates = Vec::with_capacity(availability_cores.len());
-
-	for (core_idx, core) in availability_cores.iter().enumerate() {
-		let (para_id, required_path) = match core {
-			CoreState::Scheduled(scheduled_core) => {
-				// The core is free, pick the first eligible candidate from
-				// the fragment tree.
-				(scheduled_core.para_id, Vec::new())
-			},
-			CoreState::Occupied(occupied_core) => {
-				if bitfields_indicate_availability(core_idx, bitfields, &occupied_core.availability)
-				{
-					if let Some(ref scheduled_core) = occupied_core.next_up_on_available {
-						// The candidate occupying the core is available, choose its
-						// child in the fragment tree.
-						(scheduled_core.para_id, vec![occupied_core.candidate_hash])
-					} else {
-						continue
-					}
-				} else {
-					if occupied_core.time_out_at != block_number {
-						continue
-					}
-					if let Some(ref scheduled_core) = occupied_core.next_up_on_time_out {
-						// Candidate's availability timed out, practically same as scheduled.
-						(scheduled_core.para_id, Vec::new())
-					} else {
-						continue
-					}
-				}
-			},
-			CoreState::Free => continue,
-		};
-
-		let candidate_hash =
-			get_backable_candidate(relay_parent, para_id, required_path, sender).await?;
-
-		match candidate_hash {
-			Some(hash) => selected_candidates.push(hash),
-			None => {
-				gum::debug!(
-					target: LOG_TARGET,
-					leaf_hash = ?relay_parent,
-					core = core_idx,
-					"No backable candidate returned by prospective parachains",
-				);
-			},
-		}
-	}
-
-	Ok(selected_candidates)
-}
-```
-
-Notes:
-
-- Per core
-  - Discuss core states free, scheduled, occupied
-  - Discuss core freeing criteria
-    - `bitfields_indicate_availability`
-      - next_up_on_available
-    - availability time out
-      - next_up_on_timeout
-  - Explain what required path is
-  - Why is required path left empty?
-
----
-
-<img rounded style="width: 500px" src="./img/cumulus.png" />
-
-## Cumulus Changes
-
-<pba-flex center>
-
-- Consensus driven block authoring
-- Parachain consensus refactor
-  - Aura rewrite
-  - Custom sequencing consensus:
-    - Tendermint
-    - Hotshot consensus
-
-</pba-flex>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Async Backing Advantages, Current and Future
-
----
-
-## Advantages of Asynchronous Backing
-
-<pba-flex center>
-
-1. 3-5x more extrinsics per block
-1. Shorter parachain block times 6s vs 12s
-1. Resulting 6-10x boost in quantity of blockspace
-1. Fewer wasted parachain blocks
-
-</pba-flex>
-
-Notes:
-
-1. Collators have more time to fill each block
-1. Advance work ensures backable candidates for each parachain are present to be backed on the relay chain every 6 seconds
-1. Self explanatory
-1. Allow parachain blocks to be ‘reused’ when they don’t make it onto the relay chain in the first attempt
-
----
-
-## Async Backing and Exotic Core Scheduling
-
-<pba-flex center>
-
-- What is exotic core scheduling?
-  - Multiple cores per parachain
-  - Overlapping leases of many lengths
-  - Lease + On-demand
-- How does asynchronous backing help?
-
-<pba-flex>
-
-Notes:
-
-- The unincluded segment is necessary to build 2 or more parablocks in a single relay block
-
----
-
-<img rounded style="width: 500px" src="./img/stopwatch.png" />
-
-## Shorter Block Times?
-
-<pba-flex center>
-
-- Async backing gives us unincluded block queuing
-- What else we need for useful shorter times:
-  - Soft finality
-  - Inclusion dependencies (comes with elastic scaling)
-
-<pba-flex>
-
-Notes:
-
-- Soft finality means that the collators will submit as many new blocks with the same extrinsics as needed to retain the same ordering if a parablock candidate is dropped.
-- Inclusion dependencies: Take two parablocks a and b, where a is built on top of b.
-  Then if a and b are being made available on two different cores during the same block we need to ensure that b waits for inclusion until a is also included.
-
----
-
-## Resources
-
-<pba-col center>
-
-1. [Polkadot Async Backing PR](https://github.com/paritytech/polkadot/pull/5022)
-1. [Implementers Guide: Prospective Parachains](https://github.com/paritytech/polkadot/blob/631b66d5daa642fad7ed0a9712194c5b85b96563/roadmap/implementers-guide/src/node/backing/prospective-parachains.md)
-   <!-- FIXME above guide is deprecated -->
-   </pba-col>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/async-backing-shallow/img/synchronous_backing_simplified.svg b/content/polkadot/async-backing-shallow/img/synchronous_backing_simplified.svg
deleted file mode 100644
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--- a/content/polkadot/async-backing-shallow/img/synchronous_backing_simplified.svg
+++ /dev/null
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diff --git a/content/polkadot/async-backing-shallow/page.md b/content/polkadot/async-backing-shallow/page.md
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-# Asynchronous Backing (Shallow)
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/polkadot/async-backing-shallow/slides.md b/content/polkadot/async-backing-shallow/slides.md
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----
-title: Shallow Dive, Asynchronous Backing
-description: Decoupling Backing and Inclusion Through Advance Work Based on Happy Path Assumptions
-duration: 30 min
----
-
-# Shallow Dive, Asynchronous Backing
-
-Notes:
-
-Hello again everyone
-
-Today I'll be speaking to you about asynchronous backing, the new feature which delivers shorter parachain block times and an order of magnitude increase in quantity of Polkadot blockspace.
-
-Lets get to it
-
----
-
-## Overview
-
-<pba-flex center>
-
-- Synchronous vs asynchronous
-- Why is asynchronous backing desirable?
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- High level mechanisms of async backing
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- The unincluded segment, and prospective parachains
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-- Async backing enabling other roadmap items
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-</pba-flex>
-
----
-
-## Synchronous Backing Simplified
-
-<img rounded style="width: 1100px" src="./img/synchronous_backing_simplified.svg" />
-
-Notes:
-
-- The dividing line between the left and right is when a candidate is backed on chain
-- Approvals, disputes, and finality don't immediately gate the production of farther candidates.
-  So we don't need to represent those steps in this model.
-
----
-
-## Async Backing Simplified
-
-<div class="r-stack">
-<img rounded style="width: 1100px" src="./img/async_backing_simplified_1.svg" />
-<img rounded style="width: 1100px" src="./img/async_backing_simplified_2.svg" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img rounded style="width: 1100px" src="./img/async_backing_simplified_3.svg" />
-<!-- .element: class="fragment" data-fragment-index="2" -->
-</div>
-
-Notes:
-
-Our cache of parablock candidates allows us to pause just before that dividing line, on-chain backing
-
----
-
-## The Async Backing Optimistic Collator Assumptions
-
-<pba-flex center>
-
-1. "The best existing parablock I'm aware of will eventually be included in the relay chain."
-1. "There won't be a chain reversion impacting that best parablock."
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-</pba-flex>
-
-<br />
-<br />
-
-> The Stakes Are Low
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-Best is determined by a process similar to the BABE fork choice rule.
-Brief BABE fork choice rule review
-
----
-
-## Advantages of Asynchronous Backing
-
-<pba-flex center>
-
-1. 3-5x more extrinsics per block
-1. Shorter parachain block times 6s vs 12s
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-1. Resulting 6-10x boost in quantity of blockspace
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-1. Fewer wasted parachain blocks
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-</pba-flex>
-
-Notes:
-
-1. Collators have more time to fill each block
-1. Advance work ensures backable candidates for each parachain are present to be backed on the relay chain every 6 seconds
-1. Self explanatory
-1. Allow parachain blocks to be ‘reused’ when they don’t make it onto the relay chain in the first attempt
-
----
-
-## Parablock Validation Pipelining
-
-<img rounded style="width: 1100px" src="./img/async_backing_pipelining.svg" />
-
----
-
-## Synchronous Backing, Another Look
-
-<div class="r-stack">
-<img rounded style="width: 1100px" src="./img/synchronous_backing_1.svg" />
-<img rounded style="width: 1100px" src="./img/synchronous_backing_2.svg" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img rounded style="width: 1100px" src="./img/synchronous_backing_3.svg" />
-<!-- .element: class="fragment" data-fragment-index="2" -->
-</div>
-
-Notes:
-
-Image version 1:
-
-- Now let's take a closer look at when each step of backing and inclusion takes place both with synchronous and asynchronous backing.
-
-Image version 3:
-
-- Whole process is a cycle of duration 12 seconds (2 relay blocks).
-- No part of this cycle can be started for a second candidate of the same parachain until the first is included.
-
----
-
-## Async Backing, Another Look
-
-<div class="r-stack">
-<img rounded style="width: 1500px" src="./img/async_backing_1.svg" />
-<img rounded style="width: 1500px" src="./img/async_backing_2.svg" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img rounded style="width: 1500px" src="./img/async_backing_3.svg" />
-<!-- .element: class="fragment" data-fragment-index="2" -->
-</div>
-
-Note:
-
-Image version 1:
-
-- Candidates stored in prospective parachains (detail on that later)
-
-Image version 2:
-
-- Now we see our relay block cycle.
-- It is 6 seconds rather than 12.
-- It completes on-chain backing for one candidate and inclusion for another each cycle.
-
-Image version 3:
-
-- Collation generation and off-chain backing are outside of the relay block cycle.
-- Because of this, collators have the freedom to work several blocks in advance. In practice, even working 2-3 blocks in advance gives a collator ample time to fully fill blocks (PoV size 5MiB)
-- Notice that a part of the collation generation context, the unincluded segment, comes from the collator itself.
-
----
-
-## The Unincluded Segment
-
-<pba-flex center>
-
-- A parachain's record of all parablocks on a particular chain fork produced but not yet included
-- Used to apply limitations when constructing future blocks
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Lives in the parachain runtime
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- Viewed from the perspective of a new parablock under construction
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-</pba-flex>
-
-Notes:
-
-Limitation example, upward messages remaining before the relay chain would have to drop incoming messages from our parachain
-
----
-
-## Unincluded Segment
-
-<img rounded style="width: 1100px" src="./img/unincluded_segment_1.svg" />
-
-Notes:
-
-- Segment added to as each new block is imported into the parachain runtime
-- Segment shrinks when one of its ancestor blocks becomes included
-- Maximum unincluded segment capacity is set both on the parachain and relay chain
-
----
-
-## Unincluded Segment
-
-<img rounded style="width: 1100px" src="./img/unincluded_segment_2.svg" />
-
-Notes:
-
-UsedBandwidth:
-
-- pub ump_msg_count: u32,
-- pub ump_total_bytes: u32,
-- pub hrmp_outgoing: BTreeMap\<ParaId, HrmpChannelUpdate\>,
-
----
-
-## Prospective Parachains
-
-<pba-flex center>
-
-- The relay chain's record of all candidates on all chain forks from all parachains
-- As if you folded all unincluded segments into one huge structure
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Used to store candidates and later provide them to the on-chain backing process
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- Lives in the relay client (off chain)
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-</pba-flex>
-
----
-
-## Prospective Parachains Snapshot
-
-<img rounded style="width: 1500px" src="./img/Prospective_Parachains_Overview.svg" />
-
-Notes:
-
-- Fragment trees only built for active leaves
-- Fragment trees built per scheduled parachain at each leaf
-- Fragment trees may have 0 or more fragments representing potential parablocks making up possible futures for a parachain's state.
-- Collation generation, passing, and seconding work has already been completed for each fragment.
-
----
-
-## Async Backing Simplified
-
-<div class="r-stack">
-<img rounded style="width: 1100px" src="./img/async_backing_simplified_3.svg" />
-</div>
-
-Notes:
-
-Returning to our most basic diagram
-
-- Q: Which structure did I leave out the name of for simplicity, and where should that name go in our diagram?
-- Q: Which did I omit entirely?
-
----
-
-## Async Backing and Exotic Core Scheduling
-
-<img rounded style="width: 1100px" src="./img/exotic_scheduling.svg" />
-
-Notes:
-
-- What is exotic core scheduling?
-  - Multiple cores per parachain
-  - Overlapping leases of many lengths
-  - Lease + On-demand
-- How does asynchronous backing help?
-- The unincluded segment is necessary to build 2 or more parablocks in a single relay block
-
----
-
-## Resources
-
-<pba-col center>
-
-1. [Polkadot Async Backing PR](https://github.com/paritytech/polkadot/pull/5022)
-1. [Cumulus Async Backing PR](https://github.com/paritytech/cumulus/pull/2300)
-1. [Implementers Guide: Prospective Parachains](https://github.com/paritytech/polkadot/blob/631b66d5daa642fad7ed0a9712194c5b85b96563/roadmap/implementers-guide/src/node/backing/prospective-parachains.md)
-   <!-- FIXME above guide is deprecated -->
-   </pba-col>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/availability-cores/page.md b/content/polkadot/availability-cores/page.md
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-# Availability Cores
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/polkadot/availability-cores/slides.md b/content/polkadot/availability-cores/slides.md
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----
-title: Deep Dive, Availability Cores
-description: The Polkadot Abstraction for Flexible Blockspace Allocation
-duration: 1 hour
----
-
-# Deep Dive, Availability Cores
-
-Notes:
-
-Hello!
-
-I'm Bradley Olson
-
-Was student at first Academy
-
-Currently on Parachains Core Team
-
-Will present 3 lectures providing a window into Polkadot core, a slice of where we're at and where we're headed.
-
-First a look at availability cores, the abstraction enabling flexible purchases of blockspace under the umbrella of Polkadot shared security.
-
-Lets get to it
-
----
-
-## Addressing the Dual Naming
-
-<pba-flex center>
-
-- In the code: Availability core
-- Outside the code: Execution core
-
-</pba-flex>
-
----
-
-## Overview
-
-<pba-flex center>
-
-- What do availability cores represent?
-
-<!-- .element: class="fragment" data-fragment-index="0" -->
-
-- How do cores map parachain leases and claims to validator subsets?
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- How do cores gate each step of the parachains protocol?
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- What advantages do cores give us now?
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-- What roadmap items do cores accommodate?
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-</pba-flex>
-
----
-
-## Review, Blockspace
-
-> Blockspace is the capacity of a blockchain<br />to finalize and commit operations
-
-Polkadot's primary product is _blockspace_.
-
----
-
-## Blockspace, Use It or Lose It
-
-Polkadot blockspace is consumed in two ways:
-
-<pba-flex center>
-
-1. When the relay chain validates, includes, <br /> and finalizes a parachain block
-
-<!-- .element: class="fragment" data-fragment-index="0" -->
-
-1. When the capacity to validate a parachain block<br /> is left unused and expires
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-</pba-flex>
-
-<img rounded style="width: 500px" src="../async-backing-deep/img/stopwatch.png" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
----
-
-## Availability Core Defined
-
-<pba-cols>
-<pba-col center>
-
-- Availability cores are the abstraction we use to allocate Polkadot's blockspace.
-
-<!-- .element: class="fragment" data-fragment-index="0" -->
-
-- Allocated via leases and on-demand claims
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Cores divide blockspace supply into discrete units, 1 parachain block per relay chain block per core
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- Why "availability"?
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-- Why "core"?
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-</pba-col>
-<pba-col center>
-
-<img rounded style="width: 500px" src="./img/Processor_Cores.jpeg" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- "Availability", because a core is considered occupied by a parachain block candidate while that candidate is being made available. But cores mediate access to the entire parablock validation pipeline, not just availability.
-- "Core", because many candidates can be made available in parallel, mimicking the parallel computation per core in a computer processor.
-
----
-
-## Availability
-
-Though cores gate the entire parachain block pipeline,<br /> the availability process alone determines when these cores are considered occupied vs free.
-
-To recap, the goals of availability are:
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-1. To ensure that approvers will always be able to recover the PoVs to validate their assigned blocks
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-2. To ensure that parachain nodes can recover blocks in the case that a parablock author fails to share them, through malintent or malfunction
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
----
-
-## Core States
-
-<pba-cols>
-<pba-col center>
-
-Free
-
-<img rounded style="height: 300px" src="./img/free.png" />
-
-</pba-col>
-<pba-col center>
-
-Scheduled
-
-<img rounded style="height: 300px" src="./img/scheduled.png" />
-
-</pba-col>
-
-<pba-col center>
-
-Occupied
-
-<img rounded style="height: 300px" src="./img/occupied.png" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- Before going any farther we need to talk about core states
-- CoreState: Free -> core has not been assigned a parachain via lease or on-demand claim
-- CoreState: Scheduled -> Core has an assigned parachain and is currently unoccupied
-- CoreState: Occupied -> Core has assignment and is occupied by a parablock pending availability
-
----
-
-## The Availability Process
-
-<pba-flex center>
-
-1. Block author places a candidate on-chain as backed, immediately occupying its scheduled core
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-1. Candidate backers distribute erasure coded PoV chunks
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-1. Validators distribute statements as to which candidates they have chunks for
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-1. Availability threshold is met (2/3 vs the 1/3 needed to reconstruct POV)
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-1. Candidate marked as included on chain and core freed
-
-<!-- .element: class="fragment" data-fragment-index="5" -->
-
-1. Approvers or parachain nodes retrieve PoV chunks as needed
-
-<!-- .element: class="fragment" data-fragment-index="6" -->
-
-</pba-flex>
-
----
-
-## Cores and Blockspace Over Time
-
-<img rounded style="width: 1100px" src="./img/Train.jpeg" />
-
-Notes:
-
-Metaphor:
-
-- Relay chain: Train loading bay
-- Relay block: Train leaving station every 6 seconds
-- Parachain block: One train car worth of cargo
-- Availability core: Car index within all trains
-
-If you have a lease on core 4, then you have the right to fill train car 4 on each train with whatever you want to ship.
-
-Q: How would an on-demand claim be represented in this metaphor?
-
----
-
-# Mapping Leases and Claims to Validator Subsets
-
----
-
-## The Big Picture
-
-<img rounded style="width: 1100px" src="./img/cores_big_picture.svg" />
-
-Notes:
-
-- Which steps of the parachains protocol are missing, and why?
-- Going to dive into each piece
-- Questions?
-
----
-
-## Assigning Leases and Claims to Cores
-
-<img rounded style="width: 1100px" src="./img/pairing_leases_and_claims_with_cores.svg" />
-
-Notes:
-
-- Leases have indices and pair to cores with the same index
-- Cores not designated as on-demand and without a paired lease are left free, their blockspace wasted
-- When on-demand claims are queued, they are each assigned a designated core in ascending order, looping when reaching the last core
-
----
-
-## Assigning Backing Groups to Cores
-
-<img rounded style="width: 1100px" src="./img/pairing_backing_groups_with_cores.svg" />
-
-Notes:
-
-- Round robin, fixed intervals
-
-This prevents a byzantine backing group from interrupting the liveness of any one parachain for too long.
-
----
-
-## Backing Group Formation
-
-<img rounded style="width: 1100px" src="../execution-sharding/img/validator-groups.png" />
-
-Notes:
-
-- Validators randomly assigned to groups at start of session.
-- Group count is active validator count / max group size rounded up
-- Groups are partitioned such that the largest group and smallest group have a size difference of 1
-
----
-
-<img rounded style="width: 300px" src="./img/dice.jpeg" />
-
-## Assigning Approvers to Cores
-
-<pba-flex center>
-
-- Randomness via schnorrkel::vrf
-- Approver assignments activated with delay tranches until threshold met
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Results in 30-40 approvers checking each block
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- Different assignments each block prevent DOS
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-</pba-flex>
-
----
-
-## Putting the Pieces Together
-
-<img rounded style="width: 1100px" src="./img/cores_big_picture.svg" />
-
----
-
-## Occupying Assigned Cores: With Lease
-
-<img rounded style="width: 1100px" src="./img/occupying_assigned_cores_with_lease.svg" />
-
-Notes:
-
-Q: What step of the parachains protocol takes place between "Supplied backable candidate" and "availability process?
-
----
-
-## Occupying Assigned Cores: On Demand
-
-<img rounded style="width: 1100px" src="./img/occupying_assigned_cores_on_demand.svg" />
-
----
-
-## Core States in the Runtime
-
-In file: polkadot/runtime/parachains/src/scheduler.rs
-
-<div style="font-size: 0.82em;">
-
-```rust[1|3-8|5,10-16]
-pub(crate) type AvailabilityCores<T> = StorageValue<_, Vec<Option<CoreOccupied>>, ValueQuery>;
-
-pub enum CoreOccupied {
-    /// A parathread (on-demand parachain).
-    Parathread(ParathreadEntry),
-    /// A lease holding parachain.
-    Parachain,
-}
-
-/// Parathread = on-demand parachain
-pub struct ParathreadEntry {
-	/// The claim.
-	pub claim: ParathreadClaim,
-	/// Number of retries.
-	pub retries: u32,
-}
-```
-
-</div>
-
-Notes:
-
-Q: When Option is None, what does that indicate?
-
-- Which para occupies a core is stored separately in the following structure
-
----
-
-## Core Assignments in The Runtime
-
-In file: polkadot/runtime/parachains/src/scheduler.rs
-
-<div style="font-size: 0.82em;">
-
-```rust[1|3-10|9,12-17]
-pub(crate) type Scheduled<T> = StorageValue<_, Vec<CoreAssignment>, ValueQuery>;
-
-pub struct CoreAssignment {
-    /// The core that is assigned.
-    pub core: CoreIndex,
-    /// The unique ID of the para that is assigned to the core.
-    pub para_id: ParaId,
-    /// The kind of the assignment.
-    pub kind: AssignmentKind,
-}
-
-pub enum AssignmentKind {
-	/// A parachain.
-	Parachain,
-	/// A parathread (on-demand parachain).
-	Parathread(CollatorId, u32),
-}
-```
-
-</div>
-
-Notes:
-
-- Vec of all core assignments
-- Pairs ParaId with CoreIndex
-- AssignmentKind carries retry info for on-demand
-
----
-
-## How Cores Gate Each Step of the Parachains Protocol
-
----
-
-## How Core Assignments Mediate Backing
-
-Each parablock candidate is built in the context of a particular `relay_parent`.
-
-Validators query their core assignment as of `relay_parent` and refuse to second candidates not associated with their backing group.
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-- Relay parent context: max PoV size, current parachain runtime code, and backing group assignments.
-
----
-
-### How Core Assignments Mediate Backing (Cont.)
-
-`handle_second_message()` in the Backing Subsystem.
-
-```rust[1|6]
-if Some(candidate.descriptor().para_id) != rp_state.assignment {
-	gum::debug!(
-		target: LOG_TARGET,
-		our_assignment = ?rp_state.assignment,
-		collation = ?candidate.descriptor().para_id,
-		"Subsystem asked to second for para outside of our assignment",
-	);
-
-	return Ok(())
-}
-```
-
----
-
-## Cores and Backing On-Chain
-
-<pba-flex center>
-
-- For each core that is either unoccupied or is about to be a new candidate is found
-- A candidate for the parachain scheduled next on that core is provided to the block author
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Backed on-chain -> immediately occupies core
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-</pba-flex>
-
-Notes:
-
-- Review possible core states
-- Mention time-out vs made available
-
-Q: What does "immediately occupies core" imply?
-
----
-
-## Cores and Backing On-Chain, Code
-
-<div style="font-size: 0.82em;">
-
-Code determining whether to back a candidate and which, greatly simplified
-
-```rust[1|24|2-4|5-13|13-23|28-29]
-	let (para_id) = match core {
-		CoreState::Scheduled(scheduled_core) => {
-			scheduled_core.para_id
-		},
-		CoreState::Occupied(occupied_core) => {
-			if current_occupant_made_available(core_idx, &occupied_core.availability)
-			{
-				if let Some(ref scheduled_core) = occupied_core.next_up_on_available {
-					scheduled_core.para_id
-				} else {
-					continue
-				}
-			} else {
-				if occupied_core.time_out_at != current_block {
-					continue
-				}
-				if let Some(ref scheduled_core) = occupied_core.next_up_on_time_out {
-					scheduled_core.para_id
-				} else {
-					continue
-				}
-			}
-		},
-		CoreState::Free => continue,
-	};
-
-	let candidate_hash =
-		get_backable_candidate(relay_parent, para_id, required_path, sender).await?;
-```
-
-</div>
-
-Notes:
-
-- Discuss core freeing criteria
-- `bitfields_indicate_availability`
-  - next_up_on_available
-- availability time out
-  - next_up_on_timeout
-
----
-
-## Cores and Approvals, Disputes, Finality
-
-Each included candidate has already occupied an availability core
-
-Approvals, Disputes, and Finality are only provided to included candidates
-
----
-
-## Advantages Cores Give us Now
-
-<pba-flex center>
-
-1. Predictability of parachain execution
-1. Predictability of allocation for execution sharding
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-</pba-flex>
-
-<img rounded style="width: 500px" src="./img/advantage.png" />
-
-Notes:
-
-- Regularly rotating pairings between cores and backing groups lessen the impact of potential bad validator subsets
-- Cores accommodate advance allocation making costs for parachains predictable
-- Core time can be resold or split for precise allocation
-
----
-
-# Cores and Roadmap Items
-
-<img rounded style="width: 600px" src="./img/road.jpeg" />
-
----
-
-## Exotic core scheduling
-
-<pba-flex center>
-
-- Multiple cores per parachain
-- Overlapping leases of many lengths
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Lease + On-demand
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-</pba-flex>
-
-<img rounded style="width: 1500" src="./img/exotic_core_scheduling.svg" />
-
-Notes:
-
-- Each color represents a parachain
-  Metaphor:
-- Multiple cars on the same train
-- Overlapping time spans of rights to fill different train cars
-- Long term rights to one car and buy rights to others for just one train
-
----
-
-## Divisible and Marketable Blockspace
-
-We want Parachains to buy, sell, and split blockspace such that they are allocated exactly as much as fits their needs.<br /><br />
-
-<pba-flex center>
-
-- Core sharing via use-threshold blockspace regions
-- Secondary markets for blockspace regions
-
-</pba-flex>
-
-Notes:
-
-- Example: Region spanning 100 blocks. Split the region use so that each of two parties can submit up to 50 parablocks. Ownership proportion is enforced throughout the region such that each party can't submit more than 5 out of the first 10 blocks.
-
----
-
-## Framing Shift: Blockspace vs Core Time
-
-Blockspace is a universal term for the product of blockchains, while core time is Polkadot's particular abstraction for allocating blockspace or other computation.
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Cores can secure computation other than blocks. For example, a smart contract could be deployed on a core directly.
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Allocating cores by time rather than for a fixed block size could allow for smaller or larger parachain blocks to be handled seamlessly.
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
----
-
-## Resources
-
-<pba-col center>
-
-1. [Implementers Guide: Scheduler Pallet](https://paritytech.github.io/polkadot/book/runtime/scheduler.html)
-1. [RFC: Agile Coretime](https://github.com/polkadot-fellows/RFCs/pull/1)
-1. [RFC: Coretime Scheduling Regions](https://github.com/polkadot-fellows/rfcs/pull/3)
-1. [Rob Habermeier's Blog: Polkadot Blockspace Over Blockchains](https://www.rob.tech/polkadot-blockspace-over-blockchains/)
-
-</pba-col>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/blockspace/page.md b/content/polkadot/blockspace/page.md
deleted file mode 100644
index 23a9de16..00000000
--- a/content/polkadot/blockspace/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Blockspace: The Product of Polkadot
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/polkadot/blockspace/slides.md b/content/polkadot/blockspace/slides.md
deleted file mode 100644
index 50aae9a4..00000000
--- a/content/polkadot/blockspace/slides.md
+++ /dev/null
@@ -1,289 +0,0 @@
----
-title: "Blockspace: The Product of Polkadot"
-description: Deep Dive into Coretime and Blockspace Allocation
-duration: 30-40 minutes
----
-
-## Blockspace
-
-In this lesson, we will cover:
-
-<pba-flex center>
-
-1. Blockspace as a concept and historical interpretations
-1. Blockspace as a product of blockchains
-1. The importance of efficient allocation of blockspace
-1. The design space of blockspace allocation mechanisms within Polkadot
-
-</pba-flex>
-
-Notes:
-
-Deep Dive Article is <https://www.rob.tech/polkadot-blockspace-over-blockchains/>
-
----
-
-## Blockspace: Definition
-
-> Blockspace is the capacity of a blockchain to finalize and commit operations.
-
----
-
-## Measuring Blockspace
-
-Blockspace can be measured in a few different ways:
-
-<pba-flex center>
-
-1. Size: Bytes used by transactions (e.g. Bitcoin)
-1. Computation: Gas used by transactions (e.g. Ethereum)
-1. Data: Size of data required to validate transactions (PoV size in Polkadot)
-1. Or some combination of the above
-
-</pba-flex>
-
----
-
-## Blockspace Markets
-
-Fee markets in blockchains are examples of blockspace markets.
-
-The blockchain sells blockspace on-demand, and users pay fees in order to utilize the blockspace.
-
----
-
-## Blockspace Markets
-
-Parachain slot auctions are another example of a blockspace market.
-
-Instead of selling blockspace on-demand, blockspace is sold in bulk up-front with an auction mechanism.
-
----
-
-## Blockspace: Supply and Demand
-
-<img rounded width="900px" src="./img/blockspace-supply-demand.svg" />
-
----
-
-## Blockspace in Ethereum: GasToken
-
-GasToken (https://GasToken.io) was an early Blockspace Futures Market on Ethereum.
-
-Ethereum provides a gas refund for storage slots being cleared in smart contract execution.
-
-By "pre-buying" storage when gas is cheap and getting the refund when gas is expensive, users can perform blockspace arbitrage in Ethereum!
-
----
-
-## Evaluating Blockspace
-
-3 Properties of Blockspace:
-
-<pba-flex center>
-
-1. Quality: How secure is the blockspace? What are the economic guarantees of finality?
-1. Availability: How much blockspace is _available_ on the market?
-1. Flexibility: How many applications can the blockspace be used for?
-
-</pba-flex>
-
----
-
-## Polkadot's Blockspace: Quality
-
-Polkadot's Execution Sharding guarantees that all blockspace generated by Polkadot is highly secure, with economic guarantees of finality under the 33% BFT assumption.
-
----
-
-## Polkadot's Blockspace: Availability
-
-With sharding, Polkadot has the capability to produce large amounts of blockspace. This is another lens to view the blockchain scaling problem through: creating more blockspace.
-
----
-
-## Polkadot's Blockspace: Flexibility
-
-Polkadot provides blockspace in a highly flexible format due to key design choices:
-
-<pba-flex center>
-
-1. WebAssembly: This turing-complete language allows all kinds of computation to be done.
-1. PoV Blobs: Unopinionated about storage formats or access patterns.
-1. Head-Data blobs: Parachains can use any header format they like and don't even have to be blockchains, strictly speaking.
-
-</pba-flex>
-
----
-
-## Substrate: The Blockspace Transformer
-
-Since Polkadot provides highly flexible blockspace, it can be transformed into a variety of different, more specialized blockspace products.
-
-<img rounded width="900px" src="./img/blockspace-transformation.svg" />
-
----
-
-## Principles of Blockchain Application Development
-
-<pba-flex center>
-
-1. Acquire generalized blockspace (from Polkadot, from validators directly)
-1. Specialize blockspace for a particular use-case or requirement
-1. Downstream demand drives upstream demand.
-
-</pba-flex>
-
-Notes:
-
-By (3) I mean that the amount of demand for (2) should inform the amount to which the application does (1).
-
----
-
-## Problem: Ghost Chains
-
-It's quite common for chains to produce mostly empty blocks.
-
-This is a problem: chains are buying more blockspace than they need!
-
-They are paying validators to do nothing of value, and this will lead to depreciation of their token.
-
----
-
-## Solution: Acquire Blockspace on-demand
-
-Blockchains as needing to produce blocks every X seconds or minutes.
-
-Blockchains should only produce blocks when they have a good reason to.
-
-The main reason this is not done is because there are no good primitives for it.
-
----
-
-## Polkadot's Architecture: Execution Cores
-
-<img rounded width="900px" src="./img/execution-cores-with-blockchains.svg" />
-
-Notes:
-
-Cores, by metaphor, are like CPU cores. Code and data are scheduled onto them by the "Operating System" and then executed.
-
----
-
-## Polkadot's Architecture: Execution Cores
-
-<img rounded width="900px" src="./img/execution-cores.svg" />
-
----
-
-## Long-term vs. on-demand
-
-On-demand are analogous to "spot" instances and slot auctions are analogous to "reserved" instances in cloud computing.
-
-Spot instances may be more expensive if overall demand is high, but help to soothe load.
-
----
-
-## Coretime
-
-Within Polkadot, we measure the amount of blockspace that an application can use in _coretime_.
-
-Just like a CPU and OS, there is a scheduler that multiplexes many<br /> different processes onto execution cores.
-
-Coretime is acquired through either primary or secondary marketplaces.
-
-## Elastic Scaling (planned upgrade)
-
-What if parachains could acquire not just _one_ execution core at a time, but multiple?
-
-Parachains would then be able to _elastically scale_ during periods of higher demand.
-
-Notes:
-
-This scaling can occur as a result of the property that in Polkadot, parablock state transitions are completely encapsulated and validation of block X+1 can occur in parallel with validation of block X.
-
-However, the parablocks still must be _authored_ sequentially by collators, and for that reason this can only be used to scale up to the maximum throughput of collators authoring blocks.
-
----
-
-## Reimbursement Layer: Status Quo
-
-<img rounded width="900px" src="./img/reimbursement-status-quo.svg" />
-
----
-
-## Reimbursement Layer: Generalizing
-
-<img rounded width="1000px" src="./img/reimbursement-layer.svg" />
-
-Notes:
-
-User could be a collator itself, or perhaps just someone fulfilling a market need (blockspace arbitrage!)
-
----
-
-## Reimbursement Layer: Use Cases
-
-<pba-flex center>
-
-1. Pay Collators _somewhere other_ than the chain they build upon
-1. Pay Collators in stablecoins or other tokens
-1. Tokenless parachain
-1. Parachain Launch Pad (e.g. pay out of "credits" on some other system)
-1. Generalized Collator Pool (plug and play, no need to run nodes specific to parachain)
-
-</pba-flex>
-
----
-
-## Blockspace and Interoperability
-
-In interoperable blockchain applications, the application is only as good as the weakest chain it relies upon.
-
-It is important not to mix high-quality blockspace with low-quality, due to toxicity risks.
-
----
-
-## Ephemeral Chains
-
-Is there any reason a blockchain should run forever?
-
-Why not create blockchains that run for a limited period of time, e.g. to run some specific protocol or computation, and then conclude?
-
----
-
-## Coretime Futures Markets
-
-With the right core-level primitives, it will be possible to transfer claims on future coretime.
-
-Secondary markets can emerge, perhaps using NFTs, on parachains themselves, to facilitate the market for future coretime.
-
-This will create an efficient market and price discovery for coretime via arbitrage.
-
----
-
-## Future Coretime Allocation Mechanisms
-
-If coretime is the "product" of Polkadot, then allocation mechanisms are the "packaging".
-
-RFC-1 proposes mechanisms for bulk coretime to be sold off, renewed, split up, resold, and transferred.
-
----
-
-## Blockspace: Conclusions
-
-<pba-flex center>
-
-1. Blockspace is an conceptual distillation of blockchain resources
-1. Blockspace provides new lenses on the scheduling and lifecycle of blockchains
-1. Polkadot measures blockspace allocation using coretime
-1. Efficient allocation of blockspace will be critical as Web3 systems scale to serve 8 billion people.
-1. Polkadot's architecture is blockspace-centric, not blockchain-centric, and provides many options for builders to use its product.
-
-</pba-flex>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/build-a-parachain/page.md b/content/polkadot/build-a-parachain/page.md
deleted file mode 100644
index 38b30a01..00000000
--- a/content/polkadot/build-a-parachain/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Build a Parachain
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/polkadot/build-a-parachain/slides.md b/content/polkadot/build-a-parachain/slides.md
deleted file mode 100644
index 08e7b568..00000000
--- a/content/polkadot/build-a-parachain/slides.md
+++ /dev/null
@@ -1,204 +0,0 @@
----
-title: Build a Parachain
-description: Build a simple parachain without Cumulus
-duration: 1.5 hours
----
-
-# Build a Parachain
-
-> _NOTE_ this is using the archived repo of the Polkadot v1.0.0 release.
-
-<!-- FIXME update to https://github.com/paritytech/polkadot-sdk/ next time -->
-
----
-
-## Agenda
-
-- Build a simple collator without Cumulus
-- Introduction to Cumulus and how to build a Parachain
-- Workshop: Manually registering a parachain
-- Workshop: How to acquire a parachain slot
-
----
-
-## Before we begin:
-
-```sh
-# We will need a polkadot binary, e.g.
-git clone https://github.com/paritytech/polkadot/
-cd polkadot
-cargo build --release
-
-# Compile this in advance to save time:
-git clone https://github.com/Polkadot-Blockchain-Academy/cumuless-parachain-PBA-BA-2023
-cd cumuless-parachain-PBA-BA-2023
-# Ma a branch *for yourself*
-git checkout -b <YOUR GITHUB USERNAME HERE>
-cargo build --release
-```
-
----
-
-## Build Simple Parachain
-
-We're going to build a simple parachain without Cumulus!
-
-<pba-flex center>
-
-- PVF
-- Collator
-
-<pba-flex>
-
-Notes:
-
-This will be a parachain built without using FRAME.
-There will be only one collator and no collator selection logic.
-No message processing.
-No transactions.
-No runtime upgrades.
-No parachain full nodes.
-
----
-
-## Parachain requirements
-
-A parachain needs two things:
-
-<pba-flex center>
-
-1. A Wasm runtime with `validate_block` function exposed
-1. Node side that can sync relay chain blocks and talk to the relay chain
-
-<pba-flex>
-
-Notes:
-
-Talking to the relay chain means speaking the networking protocol of Polkadot to distribute the PoV.
-
----
-
-## Minimal parachain runtime (PVF)
-
-```rust
-#![no_std]
-#![cfg_attr(
-	not(feature = "std"),
-	feature(core_intrinsics, lang_items, core_panic_info, alloc_error_handler)
-)]
-
-// Make the Wasm binary available.
-#[cfg(feature = "std")]
-include!(concat!(env!("OUT_DIR"), "/wasm_binary.rs"));
-
-#[cfg(feature = "std")]
-/// Wasm binary unwrapped. If built with `BUILD_DUMMY_Wasm_BINARY`, the function panics.
-pub fn wasm_binary_unwrap() -> &'static [u8] {
-	Wasm_BINARY.expect(
-		"Development wasm binary is not available. Testing is only \
-						supported with the flag disabled.",
-	)
-}
-
-#[cfg(not(feature = "std"))]
-#[panic_handler]
-#[no_mangle]
-pub fn panic(_info: &core::panic::PanicInfo) -> ! {
-	core::intrinsics::abort()
-}
-
-#[cfg(not(feature = "std"))]
-#[alloc_error_handler]
-#[no_mangle]
-pub fn oom(_: core::alloc::Layout) -> ! {
-	core::intrinsics::abort();
-}
-
-#[cfg(not(feature = "std"))]
-#[no_mangle]
-pub extern "C" fn validate_block(_params: *const u8, _len: usize) -> u64 {
-	loop {}
-}
-```
-
-Notes:
-
-The panic and oom handlers are Rust-specific things you don't need to worry about.
-If we actually include an infinite loop into the `validate_block` function, a parablock will never be backed/included by the relay chain validators.
-
----
-
-## Parachain node side
-
-<pba-flex center>
-
-- Our node will sync relay chain blocks
-- When importing the new best block,<br />we'll connect to the backing group
-- Then we'll advertise our block ("collation")<br />to a validator in the group
-- The validator will request the collation<br />from us using `collator-protocol`
-- Now it's in the hands of validators<br />to include our block
-
-<pba-flex>
-
-Notes:
-
-Validators are shuffled into small backing groups, which rotate
-regularly with `group_rotation_frequency`.
-Currently, collators can only produce the next block after their previous
-block has been included by the relay chain (remember `CandidateIncluded`).
-Since inclusion happens in the next block after candidate being backed,
-this means collators can only produce blocks every 12s. Async backing
-will change that.
-
----
-
-## Collator-protocol
-
-Polkadot contains the implementation of the both collator and validator
-side of the collator protocol.
-
-```rust
-/// What side of the collator protocol is being engaged
-pub enum ProtocolSide {
-	/// Validators operate on the relay chain.
-	Validator {
-		/// The keystore holding validator keys.
-		keystore: SyncCryptoStorePtr,
-		/// An eviction policy for inactive peers or validators.
-		eviction_policy: CollatorEvictionPolicy,
-	},
-	/// Collators operate on a parachain.
-	Collator(
-		PeerId,
-		CollatorPair,
-		IncomingRequestReceiver<request_v1::CollationFetchingRequest>,
-	),
-}
-```
-
-Notes:
-
-We're going to use Polkadot as a library configured for the collator side.
-
----
-
-## Time to look into the code
-
-Our PBA parachain is a trimmed down version of:
-
-- <https://github.com/paritytech/polkadot/tree/master/parachain/test-parachains/adder>
-
----
-
-## Exercise
-
-Make the state of the Parachain a fixed sized 2d field (e.g. 25x25) that evolves at each block according to Game of Life and print the state at each block.
-
-- <https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life>
-- <https://www.rosettacode.org/wiki/Conway%27s_Game_of_Life>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Questions
diff --git a/content/polkadot/cumulus/page.md b/content/polkadot/cumulus/page.md
deleted file mode 100644
index 308c093a..00000000
--- a/content/polkadot/cumulus/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Cumulus
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/polkadot/cumulus/slides.md b/content/polkadot/cumulus/slides.md
deleted file mode 100644
index bdf0bd74..00000000
--- a/content/polkadot/cumulus/slides.md
+++ /dev/null
@@ -1,719 +0,0 @@
----
-title: Cumulus Deep Dive
-description: Cumulus, architecture and function
-duration: 1.25 hours
----
-
-# Cumulus Deep Dive
-
-Notes:
-
-Cumulus is the glue which attaches substrate based chains to Polkadot, converting them into parachains.
-
----
-
-### Outline
-
-<pba-flex center>
-
-1. What is Cumulus?
-1. Cumulus and Para-Relay Communication
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-1. How Cumulus Keeps a Parachain Node Informed
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-1. Collation Generation and Advertisement
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-1. How Cumulus Collations Enable Parablock Validation
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-1. How Cumulus Enables Runtime Upgrades
-
-<!-- .element: class="fragment" data-fragment-index="5" -->
-
-</pba-flex>
-
----
-
-## What is Cumulus
-
-A collection of code libraries extending a Substrate FRAME chain so that it can interface with the Polkadot API, run relay chain based consensus, and submit parachain blocks for validation.
-
----
-
-<div class="r-stack">
-<img src="./img/spc_1.svg" style="width: 70%" />
-<img src="./img/spc_2.svg" style="width: 70%" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img src="./img/spc_3.svg" style="width: 70%" />
-<!-- .element: class="fragment" data-fragment-index="2" -->
-</div>
-
-Notes:
-
-- Substrate is a framework for building blockchains
-- But only "solo" chains
-- Split into runtime/node side
-- Both Polkadot and Cumulus extend substrate
-- Polkadot provides APIs to collators
-
----
-
-## Review, Collators and Collations
-
-<pba-flex center>
-
-> What is a collator?
-
-> What is a collation?
-
-> What is the PoV?
-
-</pba-flex>
-
-Notes:
-
-- Collator:
-  - Part of consensus authority set
-  - Author and submit collations
-- Collation: Info necessary for validators to process and validate a parachain block.
-- Collations include: upward and horizontal messages, new validation code, resulting head data, proof of validity, processed downward messages, and hrmp_watermark (relay block up to which all hrmp messages have been processed)
-- PoV: The smallest bundle of information sufficient to validate a block.
-  Will revisit in more detail.
-
----
-
-## Cumulus' Key Processes
-
-- Follow relay "new best head" to update para "new best head"
-- Follow relay finalized block to update para finalized block
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Request parablocks not shared by peers from relay (data recovery)
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- Collation generation and announcement
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-Notes:
-
-- New best head: New block at the head of the fork most preferred by BABE
-
----
-
-## Cumulus and Para-Relay Communication
-
-<div class="r-stack">
-<img src="./img/para-relay_communication_1.svg" style="width: 1100px" />
-<img src="./img/para-relay_communication_2.svg" style="width: 1100px" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-</div>
-
-Notes:
-
-- How do these communication channels service our key processes?
-
----
-
-## Handling Incoming Relay Information
-
-Before addressing collation generation let's first address the other three key Cumulus processes.
-These drive parachain consensus and ensure the availability of parachain blocks.
-
-<br />
-Together they keep parachain nodes up to date such that collating is possible.
-
-Notes:
-
-To recap, these key processes are:
-
-- Follow relay "new best head" to update para "new best head"
-- Follow relay finalized block to update para finalized block
-- Request parablocks not shared by peers from relay (data recovery)
-
----
-
-### Consensus Mechanism
-
-Parachain consensus is modified to:
-
-<pba-flex center>
-
-- Achieve sequencing consensus
-- Leave finality to the relay chain
-
-</pba-flex>
-
-Notes:
-
-- Sequencing consensus: Decide on an accepted ordering of blocks and of transactions within a block
-- Sequencing consensus requires that we update our knowledge of the new best head of the parachain.
-  That way nodes are in agreement about which block to build on top of.
-- Sequencing options: Aura consensus, tendermint style consensus
-- When a parablock is included in a relay block that becomes finalized, that parablock is finalized by extension.
-
----
-
-### Import Driven Block Authoring
-
-Collators are responsible for authoring new blocks, and they do so when importing relay blocks.
-Honest Collators will choose to author blocks descending from the best head.
-
-```rust[|4-8]
-// Greatly simplified
-loop {
-    let imported = import_relay_chain_blocks_stream.next().await;
-
-    if relay_chain_awaits_parachain_candidate(imported) {
-        let pov = match parachain_trigger_block_authoring(imported) {
-            Some(p) => p,
-            None => continue,
-        };
-
-        relay_chain_distribute_pov(pov)
-    }
-}
-```
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-- `parachain_trigger_block_authoring` itself can decide if it wants to build a block.
-- e.g. the parachain having a block time of 30 seconds
-- With asynchronous backing, parachain block authoring is untethered from relay block import.
-
----
-
-### Finality
-
-To facilitate shared security, parachains inherit their finality from the relay chain.
-
-<br />
-
-```rust[|4-8]
-// Greatly simplified
-loop {
-    let finalized = finalized_relay_chain_blocks_stream.next().await;
-
-    let finalized_parachain_block =
-      match get_parachain_block_from_relay_chain_block(finalized) {
-        Some(b) => b,
-        None => continue,
-    };
-
-    set_finalized_parachain_block(finalized_parachain_block);
-}
-```
-
----
-
-### Ensuring Block Availability
-
-As a part of the parachains protocol, Polkadot makes parachain blocks available for several hours after they are backed.
-<br /><br />
-
-<pba-flex center>
-
-- Why is this needed?
-  - Approvals
-  - Malicious collator
-
-</pba-flex>
-
-Notes:
-
-- Approvers need the PoV to validate
-- Can't just trust backers to distribute the PoV faithfully
-- Malicious or faulty collators may advertise collations to validators without sharing them with other parachain nodes.
-- Cumulus is responsible for requesting missing blocks in the latter case
-
----
-
-#### Brief Aside, Candidate Receipt
-
-The PoV is too big to be included on-chain when a parablock is backed, so validators instead produce a constant size **Candidate Block Receipt** to represent the freshly validated block and its outputs
-
-Notes:
-
-The Candidate Receipt contains mainly Hashes so the only valuable use is to be used to verify the correctness of known PoVs
-The Candidate Receipt only references a PoV, it does not substitute it
-
----
-
-### Malicious collator example
-
-<div class="r-stack">
-<img src="./img/malicious_collator_1.svg" style="width: 900px" />
-<!-- .element: class="fragment fade-out" data-fragment-index="1" -->
-<img src="./img/malicious_collator_2.svg" style="width: 900px" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img src="./img/malicious_collator_3.svg" style="width: 900px" />
-<!-- .element: class="fragment" data-fragment-index="2" -->
-</div>
-
-Notes:
-
-- On a Parachain, a block only needs to be accepted by the relay chain validators to be part of the canonical chain,
-- The problem is that a collator can send a block to the relay chain without distributing it in the Parachain network
-- So, the relay chain could expect some parent block for the next block that no one is aware of
-
----
-
-### The Availability Process
-
-<pba-flex center>
-
-- Erasure coding is applied to the PoV, breaking it into chunks
-- 3x original PoV size, vs 300x to store copies
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- 1/3 of chunks sufficient to assemble PoV
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- 2/3 of validators must claim to have their chunks
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-</pba-flex>
-
----
-
-## Availability Outcome
-
-<img src="./img/malicious_collator_4.svg" style="width: 70%" />
-
----
-
-# Collation Generation and Advertisement
-
----
-
-## Collation Generation
-
-The last of our key processes
-
-<pba-flex center>
-
-1. Relay node imports block in which parachain's avail. core was vacated
-1. `CollationGeneration` requests a collation from the collator
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-1. Parachain consensus decides whether this collator can author
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-1. Collator proposes, seals, and imports a new block
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-1. Collator bundles the new block and information necessary to process and validate it, a **collation!**
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-</pba-flex>
-
-Notes:
-
-- Aura is current default parachain consensus, but this consensus is modular and changeable
-
----
-
-## Collation Distribution
-
-<img src="./img/para-relay_communication_1.svg" style="width: 1100px" />
-
-Notes:
-
-A subset of Para-Relay communication
-
----
-
-#### From Collator to Relay Node and Parachain Nodes
-
-- Sent from Collator, which owns both `CollatorService` and `ParachainConsensus`
-- Sent to tethered relay node `CollationGeneration` subsystem to be repackaged and forwarded to validators
-- Sent to parachain node import queues
-
-```rust[1|5]
-let result_sender = self.service.announce_with_barrier(block_hash);
-
-tracing::info!(target: LOG_TARGET, ?block_hash, "Produced proof-of-validity candidate.",);
-
-Some(CollationResult { collation, result_sender: Some(result_sender) })
-```
-
----
-
-# How Cumulus Collations Enable Parablock Validation
-
----
-
-### What is Runtime Validation?
-
-<pba-flex center>
-
-- The relay chain ensures that every parachain block follows the rules defined by that parachain's current code.
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Constraint: The relay chain must be able to execute runtime validation of a parachain block without access to the entirety of that parachain's state
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-</pba-flex>
-
-<div class="r-stack">
-<img src="./img/runtime_validation_1.svg" style="width: 60%" />
-<img src="./img/runtime_validation_2.svg" style="width: 60%" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<img src="./img/runtime_validation_3.svg" style="width: 60%" />
-<!-- .element: class="fragment" data-fragment-index="2" -->
-</div>
-
-<pba-flex center>
-
-- Building Blocks to make this possible, the PVF and PoV, are delivered within collations
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-</pba-flex>
-
----
-
-#### Parachain Validation Function - PVF
-
-- The current STF of each Parachain is stored on the Relay Chain, wrapped as a PVF
-
-```rust [6]
-/// A struct that carries code of a parachain validation function and its hash.
-///
-/// Should be cheap to clone.
-#[derive(Clone)]
-pub struct Pvf {
-    pub(crate) code: Arc<Vec<u8>>,
-    pub(crate) code_hash: ValidationCodeHash,
-}
-```
-
-<br />
-
-- New state transitions that occur on a parachain must be validated against the PVF
-
-Notes:
-
-The code is hashed and saved in the storage of the relay chain.
-
----
-
-#### Why PVF Rather than STF?
-
-<pba-cols>
-<pba-col center>
-
-<img src="./img/cumulus_sketch_4.svg" width = "100%"/>
-
-</pba-col>
-<pba-col center>
-
-- The PVF is not just a copy paste of the parachain Runtime
-
-<br />
-
-- The PVF contains an extra function, `validate_block`
-
-<br />
-
-**WHY!?**
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-PVF not only contains the runtime but also a function `validate_block` needed to interpret all the extra information in a PoV required for validation.
-This extra information is unique to each parachain and opaque to the relay chain.
-
----
-
-#### Validation Path Visualized
-
-<div class="r-stack">
-<img src="./img/collation_path_1.svg" style="width: 70%" />
-<img src="./img/collation_path_2.svg" style="width: 70%" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-</div>
-
-Notes:
-
-The input of the runtime validation process is the PoV and the function called in the PVF is 'validate_block', this will use the PoV to be able to call the effective runtime and then create an output representing the state transition, which is called a CandidateReceipt.
-
----
-
-#### What Does validate_block Actually Do?
-
-<pba-flex center>
-
-- The parachain runtime expects to run in conjunction with a parachain client
-- But validation is occurring in a relay chain node
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- We need to implement the API the parachain client exposes to the runtime, known as host functions
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- The host functions most importantly allow the runtime to query its state, so we need a light weight replacement for the parachain's state sufficient for the execution of this single block
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-- `validate_block` prepares said state and host functions
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-</pba-flex>
-
----
-
-#### Validate Block in Code
-
-```rust [2|3-4|6|8-11]
-// Very simplified
-fn validate_block(input: InputParams) -> Output {
-    // First let's initialize the state
-    let state = input.storage_proof.into_state().expect("Storage proof invalid");
-
-    replace_host_functions();
-
-    // Run Substrate's `execute_block` on top of the state
-    with_state(state, || {
-        execute_block(input.block).expect("Block is invalid")
-    })
-
-    // Create the output of the result
-    create_output()
-}
-```
-
-<br />
-
-> But where does `storage_proof` come from?
-
-Notes:
-
-We construct the sparse in-memory database from the storage proof and
-then ensure that the storage root matches the storage root in the `parent_head`.
-
----
-
-##### Host Function Replacement Visualized
-
-<div class="r-stack">
-<img src="./img/replace_host_function_1.svg" style="width: 70%" />
-<!-- .element: class="fragment fade-out" data-fragment-index="1" -->
-<img src="./img/replace_host_function_2.svg" style="width: 70%" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-</div>
-
----
-
-### Collation Revisited
-
-```rust[1|2-5|12-15|6-7|8-11]
-pub struct Collation<BlockNumber = polkadot_primitives::BlockNumber> {
-	/// Messages destined to be interpreted by the Relay chain itself.
-	pub upward_messages: UpwardMessages,
-	/// The horizontal messages sent by the parachain.
-	pub horizontal_messages: HorizontalMessages,
-	/// New validation code.
-	pub new_validation_code: Option<ValidationCode>,
-	/// The head-data produced as a result of execution.
-	pub head_data: HeadData,
-	/// Proof to verify the state transition of the parachain.
-	pub proof_of_validity: MaybeCompressedPoV,
-	/// The number of messages processed from the DMQ.
-	pub processed_downward_messages: u32,
-	/// The mark which specifies the block number up to which all inbound HRMP messages are processed.
-	pub hrmp_watermark: BlockNumber,
-}
-```
-
-Notes:
-
-Code highlighting:
-
-- CandidateCommitments: Messages passed upwards, Downward messages processed, New code (checked against validation outputs)
-- head_data & PoV (the validation inputs)
-
----
-
-### Proof of Validity (Witness Data)
-
-- Acts as a replacement for the parachain's pre-state for the purpose of validating a single block
-- It allows the reconstruction of a sparse in-memory merkle trie
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- State root can then be compared to that from parent header
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
----
-
-### Example of Witness Data Construction
-
-<div class="r-stack">
-<img src="./img/pov_witness_data_1.svg" style="width: 70%" />
-<!-- .element: class="fragment fade-out" data-fragment-index="1" -->
-<img src="./img/pov_witness_data_2.svg" style="width: 70%" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-</div>
-
-<br />
-
-- Only includes the data modified in this block along with hashes of the data from the rest of the trie
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- This makes up the majority of the data in a collation (max 5MiB)
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-Notes:
-
-orange: Data values modified in this block
-green: Hash of the siblings node required for the pov
-white: Hash of the nodes that are constructed with orange and green nodes
-red: Unneeded hash
-blue: Head of the trie, hash present in the previous block header
-
----
-
-#### Parablock Validation in Summary
-
-```rust [2|3-4|6]
-// Very simplified
-fn validate_block(input: InputParams) -> Output {
-    // First let's initialize the state
-    let state = input.storage_proof.into_state().expect("Storage proof invalid");
-
-    replace_host_functions();
-
-    // Run `execute_block` on top of the state
-    with_state(state, || {
-        execute_block(input.block).expect("Block is invalid")
-    })
-
-    // Create the output of the result
-    create_output()
-}
-```
-
-- Now we know where the **storage_proof** comes from!
-- **into_state** constructs our storage trie
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Host functions written to access this new storage
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
----
-
-## Cumulus and Parachain Runtime Upgrades
-
-<pba-flex center>
-
-- Every Substrate blockchain supports runtime upgrades
-
-<!-- .element: class="fragment" data-fragment-index="0" -->
-
-##### Problem
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- What happens if PVF compilation takes too long?
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-  - Approval no-shows
-  - In disputes neither side may reach super-majority
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-> Updating a Parachain runtime is not as easy as updating a standalone blockchain runtime
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-</pba-flex>
-
----
-
-### Solution
-
-The relay chain needs a fairly hard guarantee that PVFs can be compiled within a reasonable amount of time.
-
-<!-- .element: class="fragment" data-fragment-index="0" -->
-
-<br />
-
-- Collators execute a runtime upgrade but it is not applied
-- Collators send the new runtime code to the relay chain in a collation
-- The relay chain executes the **PVF Pre-Checking Process**
-- The first parachain block to be included after the end of the process applies the new runtime
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-> Cumulus follows the relay chain, waiting for a go ahead signal to apply the runtime change
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-<https://github.com/paritytech/polkadot-sdk/blob/9aa7526/cumulus/docs/overview.md#runtime-upgrade>
-
----
-
-##### PVF Pre-Checking Process
-
-- The relay chain keeps track of all the new PVFs that need to be checked
-- Each validator checks if the compilation of a PVF is valid and does not require too much time, then it votes
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-  - binary vote: accept or reject
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-- Super majority concludes the vote
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- The state of the new PVF is updated on the relay chain
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-Notes:
-
-Reference: <https://paritytech.github.io/polkadot/book/pvf-prechecking.html>
-
----
-
-## References
-
-1. 🦸 [Gabriele Miotti](https://github.com/gabriele-0201), who was a huge help putting together these slides
-1. <https://github.com/paritytech/polkadot-sdk/blob/9aa7526/cumulus/docs/overview.md>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/data-sharding/page.md b/content/polkadot/data-sharding/page.md
deleted file mode 100644
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--- a/content/polkadot/data-sharding/page.md
+++ /dev/null
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-# Data Availability and Sharding
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/polkadot/data-sharding/slides.md b/content/polkadot/data-sharding/slides.md
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index a232d872..00000000
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+++ /dev/null
@@ -1,338 +0,0 @@
----
-title: Data Availability and Sharding
-description: Data Availability Problem, Erasure coding, Data sharding.
-duration: 30-45 mins
----
-
-# Data Availability and Sharding
-
----
-
-### Outline
-
-<pba-flex center>
-
-1. [Data Availability Problem](#data-availability-problem)
-1. [Erasure coding](#erasure-coding)
-1. [Data Availability Sampling](#data-availability-sampling)
-1. [References](#references)
-
-</pba-flex>
-
----
-
-## Data Availability Problem
-
-How do we ensure a piece of data is retrievable without storing it on every single node forever?
-
-Incorrectness can be proven (fraud proofs), but unavailability can't.
-
----v
-
-### Data Availability Problem: Parachains
-
-Imagine a parachain collator produces a block, but only sends it to relay chain validators to verify.
-
-What could such a collator do?
-
-<pba-flex center>
-
-- Prevent nodes and users from learning the parachain state
-- Prevent other collators from being able to create blocks
-
-</pba-flex>
-
-We want other collators to be able to reconstruct the block from the relay chain.
-
----v
-
-### Data Availability Problem: Relay Chain
-
-If that block's PoV is only stored by a few validators, what if they go offline or rogue?
-
-<pba-flex center>
-
-- Honest approval-checkers are not able to verify validity
-
-</pba-flex>
-
-Notes:
-
-This is really bad.
-It means we could finalize an invalid parachain block.
-
----
-
-## Problem
-
-<img rounded style="width: 800px" src="./img/comic.png" />
-
-Notes:
-
-I really like this comic from the paradigm article about Data Availability Sampling. But it works for our case as well with data sharding.
-
----
-
-## Erasure coding
-
-The goal:
-
-<pba-flex center>
-
-- Encode data of K chunks into a larger encoded data of N chunks
-- Any K-subset of N chunks can be used to recover the data
-
-</pba-flex>
-
-<img rounded style="width: 1000px" src="./img/erasure-coding-1.png" />
-
----v
-
-### In code
-
-```rust
-type Data = Vec<u8>;
-
-pub struct Chunk {
-	pub index: usize,
-	pub bytes: Vec<u8>,
-}
-
-pub fn encode(_input: &Data) -> Vec<Chunk> {
-	todo!()
-}
-
-pub fn reconstruct(_chunks: impl Iterator<Item = Chunk>) -> Result<Data, Error> {
-	todo!()
-}
-```
-
----
-
-### Polynomials
-
-<img rounded style="width: 1000px" src="./img/line.svg" />
-
----v
-
-### Polynomials: Line
-
-<img rounded style="width: 1000px" src="./img/line-extra.svg" />
-
----v
-
-### Even More Polynomials
-
-<img rounded style="width: 1000px" src="./img/polynomial-2.png" />
-
----v
-
-### Polynomial we need
-
-<img rounded style="width: 800px" src="./img/reed-solomon.png" />
-
-We want to have a polynomial, such that:
-
-$$ p(x_i) = y_i$$
-
-Notes:
-
-Question: what is x_i and y_i wrt to our data?
-
----
-
-### Lagrange interpolating polynomial
-
-<!-- prettier-ignore -->
-$$ \ell_j(x) = \frac{(x-x_0)}{(x_j-x_0)} \cdots \frac{(x-x_{j-1})}{(x_j-x_{j - 1})} \frac{(x-x_{j+1})}{(x_j-x_{j+1})} \cdots \frac{(x-x_k)}{(x_j-x_k)} $$
-
-<!-- prettier-ignore -->
-$$ L(x) = \sum_{j=0}^{k} y_j \ell_j(x) $$
-
----
-
-### Reed-Solomon codes
-
-Congrats! You've just learned Reed-Solomon encoding (almost).
-
-Actual Reed-Solomon codes are defined over finite-fields.
-
-It can detect and correct combinations of errors and erasures.
-
-Notes:
-
-The simplest example of a finite field is arithmetic mod prime number.
-Computers are quite bad at division by prime numbers.
-Reed-Solomon codes are used in CDs, DVDs, QR codes and RAID 6.
-
----v
-
-### Reed-Solomon with Lagrange interpolation
-
-1. Divide the data into elements of size $P$ bits.
-1. Interpret the bytes as (big) numbers $\mod P$.
-1. Index of each element is $x_i$ and the element itself is $y_i$.
-1. Construct the interpolating polynomial $p(x)$ and evaluate it at additional $n - k$ points.
-1. The encoding is $(y_0, ..., y_{k-1}, p(k), ... p(n - 1))$ along with indices.
-
-Notes:
-
-How do we do reconstruction?
-
----
-
-## Polkadot's Data Availability Protocol
-
-<pba-flex center>
-
-- Each PoV is divided into $N_{validator}$ chunks
-- Validator with index i gets a chunk with the same index
-- Validators sign statements when they receive their chunk
-- Once we have $\frac{2}{3} + 1$ of signed statements,<br />PoV is considered available
-- Any subset of $\frac{1}{3} + 1$ of chunks can recover the data
-
-</pba-flex>
-
-Notes:
-
-The total amount of data stored by all validators is PoV \* 3.
-With 5MB PoV and 1k validators, each validator only stores 15KB per PoV.
-With this protocol, we've killed two birds with one stone!
-
----
-
-### CandidateIncluded
-
-<img rounded style="width: 1000px" src="./img/candidate-included.png" />
-
----
-
-### Availability Bitfields
-
-<img rounded style="width: 600px" src="./img/availability-bitfields.png" />
-
-Notes:
-
-Each validator actually signs a statement per relay chain block, not per PoV to reduce the number of signatures.
-These statements are gossiped off-chain and included in a block in a ParachainsInherent.
-
----
-
-### Challenge 1
-
-How does a validator know if a chunk corresponds to the committed data?
-
-<img rounded style="width: 600px" src="./img/not-that-merkel.jpg" />
-
----v
-
-### Not that Merkle!
-
-<img rounded style="width: 600px" src="./img/Ralph_Merkle.png" />
-
----
-
-### Challenge 2
-
-How do we know if what can be reconstructed from chunks is the same data that was encoded with Reed-Solomon?
-
-<pba-flex center>
-
-- Polkadot uses approval-voting/disputes mechanism for that
-- Celestia uses Fraud Proofs
-- Danksharding uses KZG commitments
-
-</pba-flex>
-
----
-
-## Data Availability Sampling
-
-Ethereum (Danksharding) and Celestia adopt an approach of Data Availability Sampling, where each light client makes its own judgement of availability by sampling and distributing a few random chunks.
-
-This can eliminate honest majority assumption!
-
-This approach guarantees there's at least one honest full nodes that has the data with high probability.
-
-<br />
-
-> <https://arxiv.org/abs/1809.09044>
-
----
-
-## Safety of Polkadot's protocol
-
-If we have at most $f$ out of $3f + 1$ malicious + offline validators, then if the data is marked as available, it **can** be recovered.
-
-What if that assumption is broken?
-
-If $2f + 1$ are malicious, every PoS is doomed anyway.
-
-Notes:
-
-We'll see in the next lesson, how approval-voting can prevent unavailable blocks from being finalized even with $>f$ malicious nodes.
-
----
-
-## 2D Reed-Solomon Encoding
-
-<img rounded style="width: 800px" src="./img/2d-reed-solomon.png" />
-
-Notes:
-
-The approach of 2D Reed-Solomon Encoding can reduce the size of
-a Fraud Proof used by Celestia.
-But it adds an overhead computationally and on the amount of data stored.
-
----
-
-## Comparison with other approaches
-
-- Both Danksharding and Celestia use 2D encoding and DAS
-- Celestia doesn't implement data sharding
-- Data availability is only part of ensuring validity
-- Polkadot's DA is able to process dozens of MB per second
-
-Notes:
-
-Danksharding is aiming at 1.3 MB/s and Celestia < 1 MB/s.
-
----
-
-## Ideas to Explore
-
-<pba-flex center>
-
-- Data Availability Sampling for parachain<br />light clients and full nodes
-- Consider using KZG commitments
-- Reducing the number of signatures to verify
-- A Data Availability Parachain
-
-</pba-flex>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
----
-
-### Bonus
-
-<pba-flex center>
-
-- Polkadot uses a field of size $2^{16}$ with efficient arithmetic
-- Polkadot uses an FFT-based Reed-Solomon algorithm (no Lagrange)
-
-</pba-flex>
-
-> <https://github.com/paritytech/reed-solomon-novelpoly>
-
----
-
-## References
-
-1. <https://www.youtube.com/watch?v=1pQJkt7-R4Q>
-1. <https://notes.ethereum.org/@vbuterin/proto_danksharding_faq>
-1. <https://www.paradigm.xyz/2022/08/das>
diff --git a/content/polkadot/decisions/page.md b/content/polkadot/decisions/page.md
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-# The Decisions of Polkadot
-
-<!-- markdown-link-check-disable -->
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-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
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----
-title: The Decisions of Polkadot
-description: A High Level Review of the Key Decisions of Polkadot
-duration: 1 hour
----
-
-# The Decisions of Polkadot
-
----
-
-## The Decisions of Polkadot
-
-This presentation will try to explain the core decisions which define the Polkadot network.
-
----
-
-## Creating an “Invention Machine”
-
-Jeff Bezos outlined in an annual letter to Amazon shareholders how he approaches decision making, by categorizing decisions as either Type 1 or Type 2 decisions.
-
-Notes:
-
-<https://www.sec.gov/Archives/edgar/data/1018724/000119312516530910/d168744dex991.htm>
-
----
-
-## Type 1 Decisions
-
-> Some decisions are consequential and irreversible or nearly irreversible – <span style="color:#d92f78"> **one-way doors**</span> – and these decisions must be made methodically, carefully, slowly, with great deliberation and consultation. If you walk through and don't like what you see on the other side, you can't get back to where you were before. We can call these Type 1 decisions.
-
----
-
-## Type 2 Decisions
-
-> But most decisions aren't like that – they are changeable, reversible – <span style="color:#d92f78"> **they're two-way doors**</span>. If you've made a suboptimal Type 2 decision, you don't have to live with the consequences for that long. You can reopen the door and go back through. Type 2 decisions can and should be made quickly by high judgment individuals or small groups.
-
----
-
-## In the context of blockchains...
-
-<pba-cols>
-<pba-col>
-
-### Type 1 Decisions
-
-Decisions that cannot easily be changed in the future.
-
-- Must be a part of the original protocol design.
-- Changes might as well be considered a new protocol.
-
-</pba-col>
-<pba-col>
-
-### Type 2 Decisions
-
-Decisions that can be easily changed in the future.
-
-- Can be included into the protocol at a later time.
-- Changes can be considered as part of the evolution of the protocol.
-
-</pba-col>
-</pba-cols>
-
----
-
-## The Philosophies of Polkadot
-
----
-
-<img style="width: 1000px; filter: invert();" src="./img/less-trust-more-truth.svg" />
-
-Notes:
-
-This is the slogan of the Web3 Summit, and seeing that Polkadot is our biggest bet on a Web3 future, it is apt that we use this phrase as a staple of the philosophy which backs Polkadot. The whole reason we have developed blockchain technologies was to address the trust problems that we face with those who wield power in our world.
-
-I want to note the phrase is NOT “No Trust, Only Truth”. This, from what I can tell so far, is mostly impossible. We should not use points of trust to invalidate working solutions. For example, it is not an expectation everyone who uses Polkadot will read each individual line of open source code before they run it. Our goal should be to minimize trust, where possible, and make it obvious to everyone who uses our tools what kinds of trust assumptions they run on
-
----
-
-## Against Blockchain Maximalism
-
-<img width="1000px" src="../../substrate/intro/img/dev-4.1-maximalism.png" />
-
-Notes:
-
-Polkadot fundamentally believes in a multi-chain future. One where chains cooperate and provide greater value to one another, rather than where they strictly compete and try to kill one another. This is rare to find today, since cryptocurrencies are prone to becoming “investment vehicles”, where the creation of a new blockchain can be seen as a threat to the existing “investments”. With the blockchain maximalism mentality, people are choosing to value their “investments” over innovation and progression, and this isn’t best for our goals to provide the best technologies to the world.
-
----
-
-## “The best blockchain today will not be the best blockchain tomorrow.”
-
-Notes:
-
-This philosophy is a realization that building a blockchain is trying to build a piece of software which will last forever. The we will not be successful engineering Polkadot simply for the problems we find today. By the time we have built X, the world will need Y, and so on. This is why we have invested so much time building platforms and SDKs, not just products. We need to make sure these technologies are able to adapt and evolve in order to stay relevant for users
-
----
-
-## The Goals of Polkadot
-
----
-
-## The Blockchain Scalability Trilemma
-
-<div class="grid grid-cols-2">
-
-<div>
-
-<img style="height: 400px;" src="./img/trilemma.svg" />
-
-</div>
-
-<div>
-
-- Security: How much does it cost to attack the network?
-
-- Scalability: How much work can the network do?
-
-- Decentralization: How decentralized is the network?
-
-</div>
-
-</div>
-
----
-
-## In one sentence...
-
-> Polkadot’s mission is to provide secure, scalable, and resilient infrastructure for Web3 applications and services.
-
-Notes:
-
-Note the difference between “decentralization” as a mission vs "resilience".
-
----
-
-Polkadot tries to accomplish that mission by solving three problems:
-
-<pba-flex center>
-
-1. Computational Scalability
-1. Shared Security
-1. Interoperability
-
-</pba-flex>
-
----
-
-## The Decisions
-
-What are the type 1 decisions which make Polkadot... Polkadot?
-
----
-
-## Wasm
-
-<div class="grid grid-cols-3">
-
-<div>
-
-<img style="width: 400px;" src="./img/webassembly-blue.png" />
-
-</div>
-
-<div class="col-span-2">
-
-WebAssembly is the backbone of Polkadot. It is a fast, safe, and open meta-protocol which powers all of the state transitions of our ecosystem.
-
-It standardizes how chains execute, sandboxes that execution for improved security, and allows teams to build on Polkadot using any language that can be compiled into Wasm.
-
-</div>
-
-</div>
-
----
-
-## Sharding
-
-<div class="grid grid-cols-2">
-
-<div>
-
-Polkadot scales primarily by parallelizing execution on separate data shards.
-
-These parallel chains (shards) are called Parachains.
-
-</div>
-
-<div>
-
-<img style="width: 500px;" src="./img/sharding.svg" />
-
-</div>
-
-</div>
-
----
-
-## App-Chains
-
-<div class="grid grid-cols-2">
-
-<div>
-
-<img style="width: 500px;" src="./img/app-chain.svg" />
-
-</div>
-
-<div>
-
-Another key scaling decision is the choice of heterogeneous shards, allowing for application specific chains.
-
-Specialized solutions for problems are more performant than generalized solutions, as they can incorporate more details about the problem space.
-
-</div>
-
-</div>
-
----
-
-## Interoperability
-
-<div class="grid grid-cols-2">
-
-<div>
-
-Individual application chains will inherently lack the ability to provide a full suite of optimized solutions for end users.
-
-Interoperability allows parachains to work together to complete, complex end-to-end scenarios.
-
-</div>
-
-<div>
-
-<img style="height: 500px;" src="./img/xcmp-2.svg" />
-
-A visual of XCMP channels between Parachains.
-
-</div>
-
-</div>
-
----
-
-## Shared Security
-
-<div class="grid grid-cols-2">
-
-<div>
-
-An often overlooked problem is economic scaling of the entire blockchain ecosystem.
-
-Polkadot is unique in that it provides all connected parachains with the same security guarantees as the Relay Chain itself.
-
-</div>
-
-<div>
-
-<img style="width: 500px" src="./img/parachains-transparent.png" />
-
-</div>
-
-</div>
-
-Notes:
-
-Security in proof-of-stake networks depends on economics, so there can only exist a limited amount of security in the world because economic value is, by definition, limited. As the number of blockchains increases due to scaling issues on single chains, their economic value — and therefore their security — gets spread out over multiple chains, leaving each one weaker than before.
-
-Polkadot introduces a shared security model so that chains can interact with others while knowing full well that their interlocutors have the same security guarantees as their own chain. Bridge-based solutions — where each chain handles its own security — force the receiver to trust the sender. Polkadot’s security model provides the necessary guarantees to make cross-chain messages meaningful without trusting the security of the sender.
-
----
-
-## Execution Cores
-
-Polkadot's Shared Security is powered through the creation and allocation of execution cores.
-
-<img style="width: 1000px;" src="./img/exotic-scheduling.png" />
-
-Execution cores provide blockspace-as-a-service, and are designed to work with any kind of consensus system.
-
----
-
-## Trust-Free Interactions
-
-<div class="grid grid-cols-3">
-
-<div>
-
-<img style="height: 500px;" src="./img/xcmp-finalization.svg" />
-
-</div>
-
-<div class="col-span-2 text-left">
-
-A key result of shared security through the Relay Chain is that it keeps track of the state of all parachains and keeps them in lock step.
-
-That means blocks which are finalized on Polkadot imply **finalization of all interactions** between all parachains at the same height.
-
-So, shared security not only secures the individual chains, but the interactions between chains too.
-
-This is continuing to evolve with the addition of "accords" / SPREE.
-
-</div>
-
-</div>
-
----
-
-## Hybrid Consensus
-
-<div class="grid grid-cols-2">
-
-<div>
-
-### Block Production
-
-<img style="width: 500px;" src="./img/babe.svg" />
-
-Current implementation is BABE, which is forkful with probabilistic finality.
-
-</div>
-
-<div>
-
-### Finality Gadget
-
-<img style="width: 400px;" src="./img/grandpa.png" />
-
-Current implementation is GRANDPA, which is robust and scalable against network partitions.
-
-</div>
-
-</div>
-
----
-
-## Light Client First Mentality
-
-<div class="text-left">
-
-Polkadot has a strong belief that light clients are a necessary component for a Web3 future. It has been uncompromising in enabling first class light client support as a primary part of its development process:
-
-- In-Browser Wasm Client (Substrate Connect)
-  - Wasm state transition function too!
-- Consensus data integrated into block headers
-- Merkle Tries and other LC compatible data structures
-- Maximizing statically known metadata to offset reliance on full nodes.
-
-</div>
-
----
-
-## On-Chain Runtime & Forkless Upgrades
-
-<div class="grid grid-cols-3">
-
-<div class="col-span-2 text-left">
-
-The Polkadot protocol specification defines a clear separation between the blockchain client and runtime (state transition function).
-
-This is primarily useful to implement the Parachains protocol, but also allows for chains to “forklessly” upgrade their code.
-
-This gives the Polkadot Relay Chain and all connected parachains an evolutionary advantage over others in the blockchain space.
-
-</div>
-
-<div>
-
-<img style="width: 400px;" src="./img/runtime-upgrade.png" />
-
-</div>
-
-</div>
-
----
-
-## On-Chain Governance
-
-<div class="grid grid-cols-3">
-
-<div class="col-span-2 text-left">
-
-Polkadot and its parachains need to change over time to stay relevant, and the network was designed from the beginning to have a transparent and sophisticated process to not only approve or reject changes but also **enact them automatically**.
-
-- Governance decisions can literally change the underlying code of the chain (since it is on-chain).
-- 50% of the total stake in the system should be able to control the future of the system.
-
-</div>
-
-<div>
-
-<img style="width: 400px;" src="./img/voting.svg" />
-
-</div>
-
-</div>
-
----
-
-## On-Chain Treasury
-
-<div class="grid grid-cols-2">
-
-<div class="text-left">
-
-Polkadot has designed at its core a self-funded treasury pool to incentivize the development and evolution of the protocol.
-
-It is entirely controlled on-chain by the governance system of Polkadot, which means that it is immune to the regulations which would normally be imposed to centralized entities.
-
-</div>
-
-<div>
-
-<img style="width: 600px;" src="./img/treasury.svg" />
-
-</div>
-
-</div>
-
----
-
-## The Implementation of Polkadot
-
-What are the type 2 decisions of Polkadot?
-
----
-
-## Parachains
-
-Polkadot was designed around Parachains, but the exact meaning and manifestation of a Parachain is evolving.
-
-<div class="grid grid-cols-2">
-
-<div>
-
-<img style="height: 200px;" src="./img/original-scheduling.png" />
-
-</div>
-
-<div>
-
-<img style="height: 200px;" src="./img/exotic-scheduling.png" />
-
-</div>
-
-</div>
-
-<br />
-
-- Originally, parachains would be long term applications-chains.
-- On-Demand Parachains (formerly parathreads) changed that viewpoint to also include chains which can spin-up and spin-down at will.
-- The future protocol will have even more exotic core scheduling and even more agile core usage, all because the type 1 decision around parachains is actually **execution cores**.
-
-Notes:
-
-- <https://hackmd.io/9xhCNYIOQny0v0QTsWuNwQ#/>
-- <https://www.youtube.com/watch?v=GIB1WeVuJD0>
-
----
-
-## XCM
-
-### Cross-Consensus Message Format
-
-<div class="grid grid-cols-2">
-
-<div>
-
-<img style="height: 500px;" src="./img/xcm-stack.svg" />
-
-Instructions to teleport an asset between parachains.
-
-</div>
-
-<div>
-
-While cross-chain interoperability (XCMP) is a type 1 decision, exactly the language that chains speak to each other is not.
-
-XCM is Parity's current flavor of a cross-consensus message format, but we already see other teams try out their own ideas, or push updates to the XCM format specification.
-
-</div>
-
-</div>
-
-Notes:
-
-<https://github.com/paritytech/xcm-format>
-
----
-
-## Nominated Proof-of-Stake
-
-<div class="grid grid-cols-3 text-small">
-<div>
-
-One of Polkadot’s primary functions is to provide security not only to itself, but also to the connected Parachains.
-
-The staking system is a critical focus of the network, and we have one of the most advanced staking systems to date.
-
-</div>
-
-<div class="col-span-2">
-
-- NPoS over DPoS to better allocate stake.
-  - We see ~25% more stake behind the elected set on NPoS compared with DPoS.
-  - At the cost of complexity and scaling.
-- Economic incentives to distribute funds evenly across validators.
-- Super-linear slashing system to discourage validator centralization.
-- Actual value being generated by staking, justifying rewards.
-
-</div>
-
-</div>
-
-<br />
-
-The protocol has been actively evolving over time, making it more performant and accessible to users, for example with nomination pools.
-
----
-
-## SASSAFRAS
-
-While hybrid consensus is a type 1 decision, the underlying protocols can continue to evolve, such as from BABE to SASSAFRAS.
-
-> Semi Anonymous Sortition of Staked Assignees For Fixed-time Rhythmic Assignment of Slots
-
-An extension of BABE and acts as a constant-time block production protocol. This approach tries to address the shortcomings of BABE by ensuring that exactly one block is produced with time-constant intervals. The protocol utilizes zk-SNARKs to construct a ring-VRF and is a work in progress.
-
----
-
-## OpenGov
-
-The specifics of Polkadot's on-chain governance system has changed multiple times in its history.
-
-- To bootstrap the network, a Sudo account was used to initialize the chain.
-- Then a multi-party system, including token holders, an elected council, and a technical council was used.
-- Most recently, the councils have been removed, and token holders are now in full control of the Polkadot governance systems.
-
----
-
-## Treasury and Fellowships
-
-An on-chain treasury has and will always exist; but how exactly it spends funds and to whom has evolved over time:
-
-- Initially there were just simple proposals which were approved by the governance system.
-- Then Bounties and Tips were introduced, increasing access to larger and smaller funding mechanisms.
-- Most recently, fellowships have started to form, which represent organizations who can earn regular salaries from the network itself.
-
----
-
-## and many more...
-
-Polkadot is **designed** to evolve, and make type 2 decision making fast and easy.
-
-An invention machine.
-
----
-
-## A Format for Discussing Decisions
-
-What questions should you ask when learning about the decisions of a Protocol?
-
-<br />
-
-- What is (the decision)?
-- What do we need to consider when making (the decision)?
-  - Is it a Type 1 or Type 2 decision?
-- What decisions has (chain) decided to make and why?
-  - What tradeoffs have they chosen?
-- What decisions have others decided to make?
-  - How might those decisions be better or worse?
-- Where can the blockchain community still improve on (the decision)?
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
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-# Polkadot Ecosystem and Economy
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
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-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
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----
-title: Polkadot Ecosystem and Economy
-description: A review of the parts of Polkadot which develop its ecosystem and economy.
-duration: 1 hour
----
-
-# Ecosystem and Economy
-
----
-
-## Ecosystem and Economy
-
-This presentation will give you a high level overview of the ecosystem and economy of the Polkadot Network.
-
-Unfortunately this presentation could never be fully exhaustive, but perhaps it will shed light on areas previously unknown.
-
----
-
-# Economy
-
----
-
-## The DOT Token
-
-<div class="grid grid-cols-2">
-
-<div>
-
-<img src="./img/token.avif" style="width: 400px;">
-
-</div>
-
-<div class="text-left">
-
-The DOT token can be in one of the following states:
-
-1. Transferable
-2. Locked (Frozen)
-3. Reserved (Held)
-
-</div>
-
-</div>
-
----
-
-## Reserved vs Locked Balance
-
-- New terms "Frozen" and "Held" are not quite used in Polkadot yet...
-- Both states belong to the user... but cannot be spent / transferred.
-- Reserved balances stack on top of one another.
-  - Useful for user deposits, or other use cases where there is sybil concerns.
-  - Ex: Deposit for storing data on-chain,
-- Locked balances can overlap each other.
-  - Useful when you want to use the same tokens for multiple use cases.
-  - Ex: Using the same tokens for both staking and voting in governance.
-
----
-
-## Storage Bloat
-
-One blockchain scaling problem is storage bloat over time.
-
-<br />
-
-Consider the "cost" of storing data on Ethereum:
-
-- A one time gas fee based on the amount of data stored.
-- Once is it placed on the network, it lives there forever, with no additional costs.
-- Over a long enough period of time, the cost of storage per time will reduce to zero.
-
----
-
-## Storage Deposits
-
-To solve this problem, Polkadot additionally takes a storage deposit (in the form of Reserved Balance) for any data stored in the blockchain.
-
-- This deposit is returned to the user when the user removes the data from the chain.
-
-- This deposit can be quite extreme, since it is returned to the user, and can represent the impermanence or lack of "importance" of the data.
-
----
-
-## Dust Accounts & Existential Deposit
-
-The most bloat-ful storage on most blockchains are user accounts:
-
-- Both Ethereum and Bitcoin are riddled with "dust accounts" which have such a small balance, they are not worth "cleaning up".
-
-- Polkadot solves this by having an "existential deposit" that all users must hold a minimum amount of DOT, else their account data will be cleaned up.
-
-- Existential deposit can be thought of as a storage deposit for account data.
-
----
-
-## DOT is a Utility Token
-
-<div class="grid grid-cols-3">
-
-<div>
-
-<img src="./img/utility.avif" style="width: 500px;">
-
-</div>
-
-<div class="text-left col-span-2">
-
-The DOT token serves multiple purposes to help the Polkadot network function:
-
-- Staking
-- Bonding for Parachain Slots / Execution Cores
-- On-Chain Decision Making
-- Value Bearing for Trading / Using
-
-</div>
-</div>
-
----
-
-## Ideal Usage of DOT Tokens
-
-<img src="./img/ideal-token-distribution.svg" style="width: 1000px;">
-
-Approximately...
-
-Notes:
-
-- 50% Staking / Governance
-- 30% Parachains
-- 20% Tradable / Useable
-
----
-
-## DOT Inflation
-
-<div class="grid grid-cols-2">
-
-<div>
-
-<img src="./img/inflation.svg" style="width: 500px;">
-
-</div>
-
-<div class="text-left">
-
-DOT is currently configured to have a fixed inflation rate of 10% per year.
-
-Newly minted tokens are distributed to stakers (validators / nominators) and the treasury.
-
-</div>
-
-</div>
-
----
-
-## Ideal Staking Rate
-
-We cannot force / tell users how to use their tokens, so we encourage "ideal" behavior by associating DOT token usage to how inflation is distributed.
-
-There’s a function that redirects some of the 10% inflation to the Treasury, instead of the stakers, when `ideal_rate != staking_rate`.
-
-Token holders are financially incentivized to maximize their staking returns, and thus distribute their tokens appropriately.
-
----
-
-## DOT Inflation vs Staking
-
-<img src="./img/staking-rate.png" style="width: 900px;">
-
-> Blue: Inflation vs Staking Rate
->
-> Green: APY of Stakers vs Staking Rate
->
-> Black: Total Inflation vs Staking Rate
-
----
-
-## DOT Utility: Parachains
-
-Polkadot provides many utilities, but arguably its most important utility is providing flexible, secure, and scalable blockspace.
-
-Developers can purchase this blockspace as fixed-term or on-demand Parachains, **only** with the DOT token.
-
-<br />
-
-> If you believe that flexible and secure blockspace has value, then you agree that DOT also has value.
-
----
-
-## Expected Parachain Costs
-
-Back of the napkin math:
-
-- ~1 Billion DOT
-- 30% Locked Up for Parachains = 300 Million
-- ~100 Parachain = 3 Million DOT per Parachain Slot
-
-At equilibrium...
-
----
-
-## Parachain Economics Updates
-
-There is a lot of ongoing discussion about updating the economics of Parachains.
-
-Likely, these mechanics will update pretty soon, and continually over time.
-
----
-
-## DOT Utility: Staking
-
-<div class="grid grid-cols-3">
-
-<div class="col-span-2 text-left">
-
-Given the existence of a value bearing token, it can be used to provide security to Polkadot:
-
-- If users want to provide security to the network, they can stake their tokens.
-
-- Stakers are rewarded for good behavior, and punished for bad behavior.
-
-- Punishments are aggressive enough that rational actors would never act maliciously.
-
-<https://www.polkadot.network/features/staking/>
-
-</div>
-
-<div>
-
-<img src="./img/staking.svg" style="width: 400px;">
-
-</div>
-
-</div>
-
----
-
-## Staking: Validators and Nominators
-
-<div class="grid grid-cols-3">
-
-<div class="col-span-2 text-left">
-
-In the staking system, there are two roles:
-
-- Validators: Those who run block producing / parachain validating nodes for Polkadot.
-- Nominators: Users who place their tokens behind validators they think will perform their job well.
-
-Validators (and their nominators) are rewarded based on work done for the network. Rewards may vary day to day, but should be consistent over long periods of time.
-
-</div>
-
-<div>
-
-<img src="./img/collab.svg" style="width: 400px;">
-
-</div>
-
-</div>
-
----
-
-## DOT Utility: Governance
-
-<div class="grid grid-cols-3">
-
-<div class="col-span-2 text-left">
-
-The future of Polkadot is decided by token holders.
-
-Polkadot has an on-chain governance system called OpenGov which is used to:
-
-- Spend Treasury Funds
-- Upgrade the Network
-- Manage the Fellowship
-- Support Parachain Teams
-- etc...
-
-<https://www.polkadot.network/features/opengov/>
-
-</div>
-
-<div>
-
-<img src="./img/governance.avif" style="width: 500px;">
-
-</div>
-
-</div>
-
----
-
-## Conviction Voting
-
-Polkadot utilizes an idea called voluntary locking / conviction voting.
-
-This allows token holders to increase their voting power by locking up their tokens for a longer period of time.
-
-```text
-votes = tokens * conviction_multiplier
-```
-
-The conviction multiplier increases the vote multiplier by one every time the number of lock periods double.
-
-<div class="text-small">
-
-| Lock Periods | Vote Multiplier | Length in Days |
-| ------------ | --------------- | -------------- |
-| 0            | 0.1             | 0              |
-| 1            | 1               | 7              |
-| 2            | 2               | 14             |
-| 4            | 3               | 28             |
-| 8            | 4               | 56             |
-| 16           | 5               | 112            |
-| 32           | 6               | 224            |
-
-</div>
-
----
-
-## Tracks
-
-The OpenGov system has different voting tracks which have different levels of power, and proportionally different level of difficulty to pass.
-
-Here are just some of the currently 15 tracks:
-
-| ID  |       Origin       | Decision Deposit | Prepare Period | Decision Period | Confirm Period | Min Enactment Period |
-| :-: | :----------------: | :--------------: | :------------: | :-------------: | :------------: | :------------------: |
-|  0  |        Root        |    100000 DOT    |    2 Hours     |     28 Days     |     1 Day      |        1 Day         |
-|  1  | Whitelisted Caller |    10000 DOT     |   30 Minutes   |     28 Days     |   10 Minutes   |      10 Minutes      |
-| 10  |   Staking Admin    |     5000 DOT     |    2 Hours     |     28 Days     |    3 Hours     |      10 Minutes      |
-| 11  |     Treasurer      |     1000 DOT     |    2 Hours     |     28 Days     |    3 Hours     |        1 Day         |
-| 12  |    Lease Admin     |     5000 DOT     |    2 Hours     |     28 Days     |    3 Hours     |      10 Minutes      |
-
----
-
-## Approval and Support Curves
-
-Each track has their own set of curves which determine if the proposal has passed or failed.
-
-All votes will eventually resolve one way or another.
-
-<img src="./img/pjs-curves.png" style="width: 1000px;">
-
-You can find these curves on the Polkadot JS Developer Console.
-
----
-
-## Example: Root
-
-The origin with the highest level of privileges. Requires extremely high levels of approval and support for early passing. The prepare and enactment periods are also large.
-
-<img src="./img/root-curve.png" style="width: 800px;">
-
-For instance, a referendum proposed in this track needs to amass 48.2% support (total network issuance) by the end of the first day with over 93.5% approval to be considered to be part of the confirm period.
-
----
-
-## Governance Token Mechanics
-
-- DOT tokens are locked when you vote on a proposal.
-- You can reuse your locked tokens across multiple proposals.
-  - Voting for one proposal does not affect your ability to vote on another proposal.
-- You can also reuse staked tokens (which are also just locked).
-- You can update your vote while the proposal is ongoing.
-- If you used conviction voting, your tokens might be locked for long periods of time passed the end of a proposal.
-
----
-
-## Treasury
-
-Polkadot has an on-chain treasury which is used to support permissionless and decentralized development of the network.
-
-Treasury gets its funds through inefficiencies in the inflation curve, slashing, and by taking 80% transaction fees.
-
-Treasury will automatically burn a 1% of its funds every spending period (24 days), placing pressure on spending the tokens.
-
----
-
-## Treasury Outlets
-
-- Proposals: Instant payments to individuals approved by governance.
-- Bounties: Multi-stage payments to individuals managed by governance and an appointed bounty curator.
-- Tips: Small payments to individuals that can be made more easily through specific governance tracks.
-
-The Polkadot Treasury currently has over 45,000,000 DOT.
-
----
-
-# Ecosystem
-
----
-
-## Alternative Polkadot Clients
-
-The main Polkadot Client is built using Rust in Substrate.
-
-However, other clients for Polkadot are under development:
-
-- Kagome (C++17): <https://github.com/qdrvm/kagome>
-- Gossamer (Go): <https://github.com/ChainSafe/gossamer>
-
-Over time, this can help provide additional resilience to the network from software bugs.
-
----
-
-## Types of Parachains
-
-- Polkadot System Chains
-- Market Bought Parachains
-
-<br />
-
-Perhaps this list will grow once more agile core allocation systems are implemented.
-
----
-
-## System Chains
-
-- System parachains contain core Polkadot protocol features, on a parachain rather than the Relay Chain.
-- Polkadot uses its own parallel execution scaling technology scale itself.
-- System parachains remove transactions from the Relay Chain, allowing more Relay Chain blockspace to be used for Polkadot's primary purpose: validating parachains.
-- System Chains are allocated by governance.
-
-Notes:
-
-<https://wiki.polkadot.network/docs/learn-system-chains>
-
----
-
-## Current and Future System Chains
-
-Current:
-
-- Asset Hub: Allows creation and registration of tokens (FT & NFTs).
-- Collectives: Acts as a place for coordination of the Polkadot DAOs.
-- Bridge Hub: A chain for managing bridges to other networks.
-- Encointer: A third-party built chain providing Proof of Personhood.
-
-Future:
-
-- Staking: Manage all the validator and nominator logic, rewards, etc...
-- Governance: Manage all the various proposals and tracks.
-- Eventually everything...
-
-Notes:
-
-<https://wiki.polkadot.network/docs/learn-system-chains>
-
----
-
-## Market Bought Parachains
-
-<div class="grid grid-cols-2">
-
-<div>
-
-Anyone with a great idea, and access to DOT token, can launch a parachain on Polkadot.
-
-Dozens of teams from around the world have already done that, and are taking advantage of the features that Polkadot provides.
-
-</div>
-
-<div>
-
-<img src="./img/polkadot-parachains.svg" style="width: 500px;">
-
-</div>
-
-</div>
-
-Notes:
-
-<https://polkadot.subscan.io/parachain>
-
----
-
-## Ecosystem Verticals
-
-While this list is not exhaustive, some of the verticals we have seen appear in Polkadot are:
-
-<div class="grid grid-cols-5">
-
-<div class="col-span-3">
-
-- Smart Contract Chains
-- Decentralized Finance (DeFi)
-- Decentralized Social (DeSo)
-- Decentralized Identity (DID) Services
-- Tokenization (Real World Assets)
-
-</div>
-
-<div class="col-span-2">
-
-- Gaming
-- NFTs (Music, Art, etc...)
-- Bridges
-- File Storage
-- Privacy
-
-</div>
-
-</div>
-
-Notes:
-
-<https://substrate.io/ecosystem/projects/>
-
----
-
-## Wallets
-
-Thanks to the treasury and Polkadot community, a number of different wallets have been developed across the ecosystem.
-
-<div class="text-small">
-
-|     Wallet      |                  Platforms                  | Staking and Nomination Pools | NFTs | Crowdloans | Ledger support | Governance |
-| :-------------: | :-----------------------------------------: | :--------------------------: | :--: | :--------: | :------------: | :--------: |
-|     Enkrypt     | Brave, Chrome, Edge, Firefox, Opera, Safari |            No, No            | Yes  |     No     |      Yes       |     No     |
-|    PolkaGate    |        Brave, Chrome, Firefox, Edge         |           Yes, Yes           |  No  |    Yes     |      Yes       |    Yes     |
-|    SubWallet    | Brave, Chrome, Edge, Firefox, iOs, Android  |           Yes, Yes           | Yes  |    Yes     |      Yes       |     No     |
-|    Talisman     |        Brave, Chrome, Edge, Firefox         |           Yes, Yes           | Yes  |    Yes     |      Yes       |     No     |
-| Fearless Wallet |         Brave, Chrome, iOS, Android         |           Yes, Yes           |  No  |     No     |       No       |     No     |
-|   Nova Wallet   |                iOS, Android                 |           Yes, Yes           | Yes  |    Yes     |      Yes       |    Yes     |
-|   Polkawallet   |                iOS, Android                 |           Yes, Yes           |  No  |    Yes     |       No       |    Yes     |
-
-</div>
-
-<!-- FIXME TODO ensure this is updated! Consider more pretty with icons or other images -->
-
-Notes:
-
----
-
-## Ledger Support w/ Metadata
-
-<div class="grid grid-cols-3">
-
-<div class="col-span-2">
-
-Polkadot has been working with Ledger to provide rich support for the Polkadot network.
-
-Users can get clear visibility into the transactions they are signing, and perform complicated tasks such as batching, multisigs, staking, governance, and more.
-
-</div>
-
-<div>
-
-<img src="./img/ledger.webp" style="width: 500px;">
-
-</div>
-
-</div>
-
----
-
-## Block Explorers
-
-- Polkadot-JS Apps Explorer - Polkadot dashboard block explorer. Supports dozens of other networks, including Kusama, Westend, and other remote or local endpoints.
-- Polkascan - Blockchain explorer for Polkadot, Kusama, and other related chains.
-- Subscan - Blockchain explorer for Substrate chains.
-- DotScanner - Polkadot & Kusama Blockchain explorer.
-- 3xpl.com - Fastest ad-free universal block explorer and JSON API with Polkadot support.
-- Blockchair.com - Universal blockchain explorer and search engine with Polkadot support.
-- Polkaholic.io - Polkadot & Kusama Blockchain explorer with API and DeFi support across 40+ parachains.
-
-Notes:
-
-<https://wiki.polkadot.network/docs/build-tools-index#block-explorers>
-
----
-
-## Governance Dashboards
-
-The most popular ones at the moment:
-
-<div class="grid grid-cols-2">
-
-<div>
-
-### Polkassembly
-
-<img src="./img/polkassembly.png" style="width: 600px;">
-
-</div>
-
-<div>
-
-### Subsquare
-
-<img src="./img/subsquare.png" style="width: 600px;">
-
-</div>
-
-</div>
-
----
-
-## Polkadot Forum
-
-<img src="./img/forum.png" style="width: 1200px;">
-
-Notes:
-
-<https://forum.polkadot.network/>
-
----
-
-## Fellowship
-
-The Polkadot Fellowship is a decentralized technical collective on the Polkadot network designed to recognize, nurture, and incentivize contributors to the core Polkadot protocol.
-
----
-
-## Fellowship Manifesto
-
-<img src="./img/fellowship-manifesto.png" style="width: 1200px;">
-
-Notes:
-
-<https://github.com/polkadot-fellows>
-
----
-
-## Fellowship Members
-
-<img src="./img/fellowship-members.png" style="width: 1200px;">
-
-Notes:
-
-<https://polkadot.js.org/apps/?rpc=wss%3A%2F%2Fkusama-rpc.polkadot.io#/fellowship>
-
----
-
-## RFCs
-
-<img src="./img/rfcs.png" style="width: 1200px;">
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
-Did I miss anything?
diff --git a/content/polkadot/execution-sharding/page.md b/content/polkadot/execution-sharding/page.md
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-# Execution Sharding in Polkadot
-
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-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Execution Sharding in Polkadot
-description: Details the Collation, Backing, Approval-Voting, and Disputes systems and how they work together to provide secure execution sharding in Polkadot.
-duration: 45 minutes
----
-
-# Execution Sharding in Polkadot
-
----
-
-## Execution Sharding
-
-> Execution Sharding is the process of distributing blockchain execution responsibilities across a validator set.
-
----
-
-## Execution Sharding in Polkadot
-
-> In Polkadot, all validators execute every relay chain block, but only a subset execute each parachain block.
-
-This enables Polkadot to scale.
-
----
-
-## Lesson Agenda
-
-<pba-flex center>
-
-1. Discuss the high-level protocols and principles of Execution Sharding in Polkadot
-1. Provide background on how complex on & offchain logic is implemented with Substrate
-
-</pba-flex>
-
-Notes:
-
-[Polkadot v1.0: Sharding and Economic Security](https://www.polkadot.network/blog/polkadot-v1-0-sharding-and-economic-security/) is a comprehensive writeup of the content here in much more detail.
-Please read it after the lesson if you would like to understand how Polkadot works from top to bottom.
-
----
-
-## Goals of Execution Sharding
-
-<pba-flex center>
-
-1. A minimal amount of validator nodes should check every parachain block while still maintaining security
-1. The relay chain will provide ordering and finality for parachain blocks
-1. Only valid parachain blocks will become finalized
-
-</pba-flex>
-
-Notes:
-
-Because GRANDPA finality faults require 33% or more stake to be slashed, Goal (3) implies Shared Security
-
----
-
-## Forkfulness
-
-Before finality, the relay chain can _fork_, often accidentally due to races.
-
-Tool: deliberately fork away from unfinalized blocks we don't like.
-
-<img rounded style="width: 700px" src="./img/BABE-is-forkful.png" />
-
-Notes:
-
-In the slides, we will look at single instances of the protocols, but it should be known that the validators are actually doing these steps in parallel with each other and often many times at a time.
-
----
-
-## Parachains Protocols
-
-<pba-flex center>
-
-1. **Collation**: Making parachain blocks
-1. **Backing**: Validator initial checks & sign-off of blocks
-1. **Availability**: Distributing data needed for checking
-1. **Approval Checking**: Checking blocks
-1. **Disputes**: Holding backers accountable
-
-</pba-flex>
-
----
-
-Validators are constantly running many instances of these protocols, for candidates at different stages in their lifecycle.
-
----
-
-### Candidate Lifecycle
-
-<img rounded style="width: 1000px" src="./img/candidate_paths.svg" />
-
----
-
-## 10,000 foot view
-
-Polkadot's approach is to have few validators check every parablock in the best case.
-
-First, **backers** introduce new candidates to other validators and provide "skin in the game".
-
-Then, **approval checkers** keep them accountable.
-
----
-
-Goal: Have as few checkers as reasonably possible.
-
----
-
-#### Validator Group Assignments and Execution Cores
-
-<img rounded style="width: 1100px" src="./img/validator-groups.png" />
-
-Notes:
-
-Every Session (4 hours), validators are _partitioned_ into small **groups** which work together.<br />
-Groups are assigned to specific **Execution Core**s, and these assignments change every few blocks.
-
----
-
-## Definition: Candidate
-
-> A **Candidate** is a parachain block<br />which has not yet been finalized in the relay chain.
-
----
-
-## Definition: HeadData
-
-> **Head Data** is an opaque and compact representation of a parachain's current state.
-> It can be a hash or a small block header, but must be small.
-
----
-
-## Definition: Parachain Validation Function (PVF)
-
-From a Validator's perspective, a parachain is a WebAssembly blob which exposes the following (simplified) function:
-
-```rust
-type HeadData = Vec<u8>;
-struct ValidationResult {
-  /// New head data that should be included in the relay chain state.
-  pub head_data: HeadData,
-  // more fields, like outgoing messages, updated code, etc.
-}
-
-fn validate_block(parent: HeadData, relay_parent: RelayChainHash, pov: Vec<u8>)
-  -> Result<ValidationResult, ValidationFailed>;
-```
-
----
-
-#### Why might `validate_block` fail?
-
-1. `parent` or `PoV` is malformed - the implementation can't transform it from an opaque to specific representation
-1. `parent` and `PoV` decode correctly but don't lead to a valid state transition
-1. `PoV` is a valid block but doesn't follow from the `parent`
-
-```rust
-fn validate_block(parent: HeadData, relay_parent: RelayChainHash, pov: Vec<u8>)
-  -> Result<ValidationResult, ValidationFailed>;
-```
-
----
-
-## Relay Chain Block Contents
-
-<img rounded style="width: 1000px" src="./img/block_contents.svg" />
-
----
-
-Any node can be selected as the next Relay Chain block author, so these data must be widely circulated.
-
----
-
-## Collation
-
-The collator's job is to build something which passes `validate_block`.
-
-In the Collation phase, a collator for a scheduled parachain builds a parachain block and produces a candidate.
-
-The collator sends this to validator group assigned to the parachain over the p2p network.
-
----
-
-Some collator pseudocode:
-
-```rust
-fn simple_collation_loop() {
-  while let Some(relay_hash) = wait_for_next_relay_block() {
-    let our_core = match find_scheduled_core(our_para_id, relay_hash) {
-      None => continue,
-      Some(c) => c,
-    };
-
-    let parent = choose_best_parent_at(relay_hash);
-    let (pov, candidate) = make_collation(relay_hash, parent);
-    send_collation_to_core_validators(our_core, pov, candidate);
-  }
-}
-```
-
----
-
-<img rounded style="width: 1000px" src="./img/pvf_duality.svg" />
-
----
-
-## Backing
-
-In the backing phase, the validators of the assigned group share the candidates they've received from collators, validate them, and sign statements attesting to their validity.
-
-Validate means roughly this: execute `validate_block` and check the result.
-
-They distribute their candidates and statements via the P2P layer, and then the next relay chain block author bundles candidates and statements into the relay chain block.
-
----
-
-## Backing: Networking
-
-<img rounded style="width: 1000px" src="./img/backing-networking.png" />
-
----
-
-## Backing: Skin in the Game
-
-The main goal of backing is to provide "skin in the game".
-
-Backers are agreeing that if the parablock turns out to be bad, they will lose 100% of their stake.
-
-Backing on its own does not provide security, only accountability.
-
-Notes:
-
-The current minimum validator bond as of Aug 1, 2023 is ~1.7 Million DOT.
-
----
-
-## Availability
-
-At this point, the backers are responsible for making the data needed to check the parablock available to the entire network.
-
-Validators sign statements about which data they have and post them to the relay chain.
-
-If the parablock doesn't get enough statements fast enough, the relay chain runtime just throws it out.
-
----
-
-#### Erasure Coding
-
-<div class="grid grid-cols-3">
-
-<div>
-
-<img rounded style="width: 450px" src="./img/erasure_coding.png" />
-
-</div>
-
-<div class="col-span-2">
-
-Each validator is responsible for one piece of this data.
-As long as enough of these pieces stay available, the data is recoverable.
-
-The statements validators sign and distribute to all other validators essentially say "I have my piece".
-
-Once 2/3 or more such statements land on-chain, the candidate is ready to be checked and is **included**.
-
-</div>
-
-</div>
-
----
-
-Some pseudocode for availability:
-
-```rust
-fn get_availability_chunks() {
-  while let Some(backed_candidate, backing_group) = next_backed_candidate() {
-    let my_chunk = fetch_chunk(
-      my_validator_index,
-      backed_candidate.hash(),
-      backing_group,
-    );
-    let signed_statement = sign_availability_statement(backed_candidate.hash());
-    broadcast_availability_statement(signed_statement);
-  }
-}
-```
-
----
-
-<img rounded style="width: 1300px" src="./img/availability-inclusion.png" />
-
-Notes:
-
-In practice, we allow more than a single block for availability to be timed out.
-
----
-
-## Parablock Inclusion and Finality
-
-<img rounded style="width: 600px" src="./img/parachain-finality.png" />
-
----
-
-## Parablock Inclusion and Finality
-
-> (3) Only valid parachain blocks will become finalized
-
-Notes:
-
-Remember our goal from earlier?
-
----
-
-## Parablock Inclusion and Finality
-
-To fulfill this goal we need 2 things.
-
-<pba-flex center>
-
-1. A protocol for proving validity of included candidates
-1. Consensus rules for the relay chain<br />to avoid building on or finalizing<br />relay chain forks containing bad candidates.
-
-</pba-flex>
-
----
-
-## What is "Checking" a Parablock?
-
-Checking involves three operations:
-
-<pba-flex center>
-
-1. Recovering the data from the network (by fetching chunks)
-1. Executing the parablock, checking success
-1. Check that outputs match the ones posted<br />to the relay chain by backers
-
-</pba-flex>
-
-Notes:
-
-Step 3 is of crucial importance.
-Without it, backers could create things like messages and runtime upgrades out of thin air, by backing a valid candidate but lying about the outputs of the candidate.
-
----
-
-## Security Model: Gambler's Ruin
-
-The security argument for Polkadot is based on Gambler’s Ruin.
-
-An attacker who can take billions of attempts to brute-force the process would eventually be successful.
-
-But because of slashing, every failed attempt means enormous amounts of DOT slashed.
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-## Approval Checking
-
----
-
-Every validator tracks its opinion about the validity of every unfinalized, included candidate in a local **state machine**.
-
-This state machine always either outputs "approved" or stalls.
-
----
-
-#### Key properties:
-
-<pba-flex center>
-
-1. The state machine output on a validator is based on the statements it has received.
-1. If the parachain block is really valid (i.e. passes checks) then it will eventually output "approved" on honest nodes.
-1. If the parachain block is invalid, it is much more likely to be detected than to output "approved" on enough honest nodes.
-
-</pba-flex>
-
-Notes:
-
-Honest nodes output "approved" only if there is a very large amount of malicious checkers and they mainly see votes
-from those checkers as opposed to honest checkers.
-
-Low probability here means 1 in 1 billion or so (assuming 3f < n)
-Not cryptographic low probability, but good enough for crypto-economics.
-
----
-
-Validators keep track of statements about **every** candidate.
-
-Validators only issue statements about **a few** candidates.
-
----
-
-Validators issue two types of statements:
-
-- Assignments: "I intend to check X"
-- Approvals: "I checked & approved X"
-
----
-
-<img rounded style="width: 1300px" src="./img/approval_state.svg" />
-
----
-
-Every validator is assigned to check every parablock, but at different times.
-
-Validators always **generate** their assignments, but keep them secret unless they are needed.
-
----
-
-<img rounded style="width: 1300px" src="./img/approval_flow.svg" />
-
----
-
-Validator assignments are secret until **revealed**.
-
-Validators **distribute** revealed assignments before checking the candidate.
-
-Assignments without following are called **no-shows**.
-No-shows are suspicious, and cause validators to raise their bar for approval.
-
-Notes:
-
-If validators began downloading data before revealing their assignment, an attacker might notice this and attack them without anybody noticing.
-
----
-
-<img rounded style="width: 1300px" src="./img/approval_state.svg" />
-
-<img rounded style="width: 700px" src="./img/lernaean-hydra.jpg" />
-
-Notes:
-
-Approval Checking is like the hydra.
-Every time an attacker chops off one head, two more heads appear.
-
----
-
-It only takes one honest checker to initiate a dispute.
-
----
-
-## Disputes
-
-When validators disagree about the validity of a parablock, a dispute is automatically raised.
-
-Disputes involve all validators, which must then check the block and cast a vote.
-
-Backing and Approval statements already submitted are counted as dispute votes.
-
-Votes are transmitted by p2p and also collected on-chain.
-
----
-
-## Dispute Resolution
-
-<img rounded style="width: 700px" src="./img/validator-dispute-participation.png" />
-
-Notes:
-
-resolution requires a supermajority in either direction.
-
----
-
-## Dispute Slashing
-
-The validators on the losing side of the dispute are slashed.
-
-The penalty is large when the candidate is deemed invalid by the supermajority and small when it is deemed valid.
-
----
-
-## GRANDPA Voting Rules
-
-Instead of voting for the longest chain, validators vote for the longest chain where all unfinalized included candidates are
-
-<pba-flex center>
-
-1. approved (according to their local state machine)
-1. undisputed (according to their best knowledge)
-
-</pba-flex>
-
-<img rounded style="width: 650px" src="./img/grandpa-voting-rule.png" />
-
----
-
-## BABE Chain Selection Rule
-
-Validators refuse to author relay chain blocks on top of forks containing parablocks which are invalid or have lost disputes.
-This causes a "reorganization" whenever a dispute resolves against a candidate.
-
-<img rounded style="width: 650px" src="./img/babe-chain-selection.png" />
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-> How are complex off-chain systems<br />implemented using Substrate?
-
----
-
-## Interaction Between Client & Runtime
-
-Since Polkadot involves not only on-chain logic but off-chain logic, the runtime is the central source of truth about validators, assignments, parachain states, etc.
-
-Clients learn about the state by invoking **Runtime APIs** at recent blocks, and the runtime is updated with **new blocks**.
-
-<img rounded style="width: 900px" src="./img/runtime-node-interaction.png" />
-
-Notes:
-
-Because the runtime is updated by new blocks, malicious or poorly connected validators have some choice in which information to provide the runtime with.
-This must be accounted for in the protocol: we cannot assume that the runtime is always perfectly informed.
-
----
-
-## Orchestra
-
-> <https://github.com/paritytech/orchestra>
-
-**Orchestra** allows us to split up the node's logic into many "Subsystems" which run asynchronously.
-
-These subsystems communicate with message passing and all receive signals which coordinate their activities.
-
----
-
-## Orchestra: Signals
-
-Signals are sent to all subsystems and act as a "heartbeat".
-
-Messages sent after a signal arrives on one subsystem cannot arrive at another subsystem until it has received the same signal.
-
----
-
-## Orchestra: Signals in Polkadot
-
-```rust
-/// Signals sent by the overseer (Polkadot's Orchestra name) to all subsystems.
-pub enum OverseerSignal {
-	/// Subsystems should adjust their jobs to start
-	/// and stop work on appropriate block hashes.
-	ActiveLeaves(ActiveLeavesUpdate),
-	/// `Subsystem` is informed of a finalized block
-	/// by its block hash and number.
-	BlockFinalized(Hash, BlockNumber),
-	/// Conclude the work of the `Overseer` and all `Subsystem`s.
-	Conclude,
-}
-```
-
-Notes:
-
-The instantiation of Orchestra in Polkadot is called "Overseer".
-
----
-
-## Without Orchestra:
-
-```rust
-fn on_new_block(block_hash: Hash) {
-  let work_result = do_some_work(block_hash);
-  inform_other_code(work_result);
-}
-```
-
-Problem: There is a race condition!
-
-The other code may receive `work_result` before learning about the new block.
-
----
-
-## With Orchestra:
-
-```rust
-fn handle_active_leaves_update(update: ActiveLeavesUpdate) {
-  if let Some(block_hash) = update.activated() {
-    let work_result = do_some_work(block_hash);
-    inform_other_subsystem(work_result);
-  }
-}
-```
-
-This works!
-Orchestra ensures that the message to the other subsystem only arrives after it has received the same update about new blocks.
-
----
-
-## Examples of Subsystems in Polkadot
-
-<pba-flex center>
-
-- Dispute Participation
-- Candidate Backing
-- Availability Distribution
-- Approval Checking
-- Collator Protocol
-- everything!
-
-</pba-flex>
-
----
-
-## Implementers' Guide
-
-[The Implementers' Guide](https://paritytech.github.io/polkadot/book/) contains information about all subsystems, architectural motivations, and protocols used within Polkadot's runtime and node implementation.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/fellowship/page.md b/content/polkadot/fellowship/page.md
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-# Polkadot Fellowship
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Polkadot Fellowship
-duration: 30 mins
----
-
-# Polkadot Fellowship
-
----
-
-## Prelude: Decentralization
-
-- Decentralization can come in many fashions.
-- Some of my (somewhat) personal opinions.. 💭
-
----v
-
-### Prelude: Decentralization
-
-#### 1. Technical 🔐
-
-- Can the software be executed in a decentralized manner?
-
-<!-- .element: class="fragment" -->
-
-- Can multiple nodes actually run the software and come to consensus?
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-- Nakatomo coefficient
-- Most blockchain systems actually already have this.
-
----v
-
-### Prelude: Decentralization
-
-#### 2. Operational ⚙️
-
-- The software is capable of running in a decentralized manner. But is it actually?
-  <!-- .element: class="fragment" -->
-  - Intermediaries, gateways, pools.
-  <!-- .element: class="fragment" -->
-- Is the right "software" being executed by node operators?
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-- Metamask
-- Mining/Staking Pool getting to large.
-
-- **Node operators** are a concept here. They have the duty to run the "correct software". But how
-  they come to this decision is something that needs knowledge, which brings us to the next point.
-
-<https://moxie.org/2022/01/07/web3-first-impressions.html>
-
----v
-
-### Prelude: Decentralization
-
-#### 3. Intellectual 🧠
-
-- How many people know the existing protocol well enough to understand it.
-
-<!-- .element: class="fragment" -->
-
-- Which subset of these people make decisions about the future?
-
-<!-- .element: class="fragment" -->
-
-- Important to remember that node operators are usually in neither.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-1. the cathedral and bazaar
-1. the papal model
-
-<https://en.wikipedia.org/wiki/The_Cathedral_and_the_Bazaar>
-
----v
-
-### Prelude: Decentralization
-
-#### 3. Intellectual 🧠
-
-> My trust in Polkadot’s credible future should not rely on knowing that Parity, Gav or Shawn will
-> continue to act benevolently.
-
-- This is where a meta-protocol, and rule-based upgrade systems becomes important.
-
-Notes:
-
-Recall how if the governance of the chain decide to upgrade to protocol, node-operators don't have a
-say in that by default.
-
-This is taking away the "power of default" to be in the hands of the token holders, not the
-node-operators.
-
----v
-
-### Prelude: Decentralization
-
-#### Geopolitical 🌎
-
-- How many of protocol experts/node operators are under the same juristiction?
-
----
-
-## The Fellowship
-
-The fellowship is a **_technical decision making body_** onchain, aimed at alleviating the above
-facades of centralization, but more so than anything else, the intellectual aspect.
-
-Notes:
-
-- Technical, high focus on core protocol aspects for now.
-- decision-making: not saying it has absolute power yet.
-
----v
-
-## The Fellowship
-
-- Imperfect, not for everyone, opinionated 🥲!
-- Strictly better than not taking an action.
-
-Notes:
-
-It is an _attempt_ at solving the issue. We believe it is strictly better than defining no rule
-around it and letting it be as-is, but it might be sub-optimal.
-
-> The Polkadot Fellowship aims to be one example of such an explicit action. The Fellowship is a
-> rules-based social organisation with several aims centred around the support and recognition of
-> the technical expertise needed for technical stability, security and progress of the network.
-
----
-
-## The Fellowship Lifecycle
-
-1. Initial seed
-
-<!-- .element: class="fragment" -->
-
-1. Entry
-
-<!-- .element: class="fragment" -->
-
-1. Promotion
-
-<!-- .element: class="fragment" -->
-
-1. Continuation
-
-<!-- .element: class="fragment" -->
-
-1. Gradual demote every 3-6 months.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### The Fellowship Lifecycle: Evaluation
-
-> Evaluation is subjective, based on merits of "core blockchain engineering".
-
-The manifesto provides one such example
-
-1. API and code design.
-1. Code contribution.
-1. Social interactions.
-1. Voting.
-
-- Activity
-- Agreement.
-
----
-
-## The Fellowship Structure
-
-<table>
-<tr>
-	<td>Dan</td>
-	<td>Name</td>
-	<td>Group</td>
-	<td>Exp from Dan I</td>
-	<td>Material</td>
-</tr>
-<tr class="fragment">
-	<td>0</td>
-	<td>Candidate</td>
-	<td>n/a</td>
-	<td>n/a</td>
-	<td>n/a</td>
-</tr>
-<tr class="fragment">
-	<td>1</td>
-	<td>Humble</td>
-	<td>Members</td>
-	<td>n/a</td>
-	<td>Graphite</td>
-</tr>
-<tr class="fragment">
-	<td>2</td>
-	<td>Proficient</td>
-	<td>Members</td>
-	<td>1 years</td>
-	<td>Stibnite</td>
-</tr>
-<tr class="fragment">
-	<td>3</td>
-	<td>Fellow</td>
-	<td>Fellows</td>
-	<td>2 years</td>
-	<td>Galena</td>
-</tr>
-<tr class="fragment">
-	<td>4</td>
-	<td>Architect</td>
-	<td>Architects</td>
-	<td>3+ years</td>
-	<td>Obsidian</td>
-</tr>
-<tr class="fragment">
-	<td>5</td>
-	<td>Architect Adept</td>
-	<td>Architects</td>
-	<td>4+ years</td>
-	<td>Ilvaite</td>
-</tr>
-<tr class="fragment">
-	<td>6</td>
-	<td>Grand Architect</td>
-	<td>Architects</td>
-	<td>5+ years</td>
-	<td>Magnetite</td>
-</tr>
-<tr class="fragment">
-	<td>7</td>
-	<td>Free Master</td>
-	<td>Masters</td>
-	<td>6+ years</td>
-	<td>Black Spinel</td>
-</tr>
-<tr class="fragment">
-	<td>8</td>
-	<td>Master Constant</td>
-	<td>Masters</td>
-	<td>11+ years</td>
-	<td>Carborundum</td>
-</tr>
-<tr class="fragment">
-	<td>9</td>
-	<td>Grand Master</td>
-	<td>Masters</td>
-	<td>19+ years</td>
-	<td>Carbandos</td>
-</tr>
-</table>
-
----
-
-## Dan 0: The Candidate
-
-- No requirement, no implication
-- Deposit held for storage usage etc.
-
----
-
-## Dan I: The Humble
-
-- The (potentially) softest of the materials
-- Wide range of hardness (1-3 Moh)
-- Shares the exact same chemical composition as the material of the highest rank Grand Master—the hardest material—symbolizing the individual’s potential to go all the
-  way.
-
----v
-
-## Dan I: The Humble
-
-- Clear aspiration to learn and evangelize the protocol.
-- Deep knowledge at least one key component.
-- Independent, vision-driven contribution.
-- Being available and playing a crucial operational role for a network fix.
-
----
-
-## Dan II: The Proficient
-
-- ~1 Year of experience passed since acquiring Dan I.
-- Responsible for research, analysis and implementation of a key component of the system.
-- Potentially "on-call" for the same component.
-- At least one published long-form semi-technical article concerning Polkadot.
-
----
-
-## Fellowship: Kusama
-
-- Used in conjuncture with `pallet-whitelist` and `pallet-preimage`.
-- The fellowship can whitelist certain pre-images, which in turn can lead to faster execution.
-- End of the day, it is all (virtual) runtime origins:
-  - `Fellows`,
-  - `Fellowship3Dan`,
-  - `WhitelistedCaller`
-  - ...
-
----
-
-## Fellowship: The Near Future
-
-- Payroll
-- Delegation
-- Runtimes moved to the fellowship repository
-
----
-
-## Polkadot Fellowship
-
-Learn more:
-
-- <https://github.com/polkadot-fellows>
-- <https://kusama.subscan.io/fellowship>
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-# 🟣 Polkadot
-
-The Polkadot blockchain covered in depth, focus on high-level design and practically how to utilize it's blockspace.
-Dive into the purpose, implementation, and protocols of Polkadot, the sharded multichain system.
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-# Introduction to Polkadot
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/polkadot/intro/slides.md b/content/polkadot/intro/slides.md
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----
-title: Introduction to Polkadot
-description: An introduction to the key concepts of Polkadot.
-duration: 1 hour
----
-
-<!-- .slide: data-background-color="#000" -->
-
-# Introduction to Polkadot
-
----
-
-## What is Polkadot?
-
-> Polkadot is a scalable, heterogeneous, sharded, multi-chain network.
-
-> Polkadot is a permissionless and ubiquitous computer
-
-> Polkadot is a decentralized open-source community
-
-> Polkadot is a digital-native sovereign network
-
----
-
-## Environment
-
-Polkadot has many faces, both technical and social.
-
-It is the real-world instantiation of the technology described within this module.
-
-These technologies only define the limits of the environment.
-Polkadot is everything which happens within it.
-
----
-
-### Agents
-
-Within the environment, various types of agents may take action according to its rules.
-
-These may be human users, silicon users, governments, or legal entities.
-
-They likely have different agendas and activity levels, and may be located anywhere in the world.
-
-Polkadot is an online economy for smart agents.
-
----
-
-### Games
-
-Polkadot fulfills its goals with a combination of mechanisms and games which provide incentives and disincentives for nodes to work together and construct this environment.
-
----
-
-### All Together
-
-<img rounded width="1200px" src="./img/gav_header_photo.jpg" />
-
-Notes:
-
-source: banner image from <https://twitter.com/gavofyork>
-
----
-
-## Goals of the Environment
-
-1. Real-time, secure, global consensus on system state
-1. Trustless, censorship-resistant, and permissionless transaction at scale
-1. Explicit network-wide governance and co-evolution
-1. General programmable computation with full security
-1. Secure and trust-minimized interoperability between processes
-
----
-
-## Goals: Breakdown
-
-> (1) Real-time, secure, global consensus on system state
-
-Polkadot's state should update as close to real-time as possible.
-
-A global, unique history of everything that has happened is maintained.
-
-Notes:
-
-State consisting of account balances, chains, governance votes, etc.
-
----
-
-## Goals: Breakdown
-
-> (2) Trustless, censorship-resistant, and permissionless transaction at scale
-
-Only a private key and a balance is needed to interact with the network, and without trusting any single third party.
-
-It aims to do so at high scale.
-
----
-
-## Goals: Breakdown
-
-> (3) Explicit network-wide governance and co-evolution
-
-Polkadot stakeholders explicitly govern and evolve the network,<br />with the ability to set new rules.
-
----
-
-## Goals: Breakdown
-
-> (4) General programmable computation with full security
-
-Polkadot is extended by general programs, usually taking the form of blockchains which themselves may be programmable environments.
-
-Generalized computation allows the capabilities of the network to be extended arbitrarily, while inheriting the full security of the network.
-
----
-
-## Goals: Breakdown
-
-> (5) Secure and trust-minimized interoperability between processes
-
-Processes deployed on Polkadot need to:
-
-<pba-flex center>
-
-- Communicate with each other.
-- "Trade" with each other without entirely trusting them.
-- Protect trade routes and enforced trade agreements.
-
-</pba-flex >
-
----
-
-## Validators
-
-Validators decide to participate in the upkeep of the network.
-
-Validators participate in the core **games** of Polkadot.
-
----
-
-## Validators
-
-Validators are _incentivized_ to do things like put user transactions in blocks or contribute to other activities, but may opt out of many of these tasks.
-
-Validators are strongly punished for explicitly doing their job wrongly.
-
-The games work as long as enough validators are doing their job<br />and also not misbehaving.
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-# Polkadot Architecture
-
-Notes:
-
-A high level look into the architecture of Polkadot and the actors which maintain the network.
-
----
-
-## Polkadot: Major Systems
-
-<img rounded width="800px" src="./img/polkadot-components.svg" />
-
----
-
-Validators are made to provide accurate execution for processes deployed on top of Polkadot.
-
-These processes, defined as WebAssembly Code, are colloquially known as **parachains**.
-
-Polkadot scales by sharing the load of validating these parachains across many validators.
-
----
-
-<img rounded width="700px" src="./img/polkadot-architecture.svg" />
-
----
-
-<img rounded width="900px" src="./img/polkadot-architecture-simple.png" />
-
-Notes:
-
-Simplified Polkadot Architecture (Parachains)
-
----
-
-## The Relay Chain
-
-The relay chain is the "hub" of Polkadot, providing the main games which validators play.
-It is built with Substrate.
-
-Notably, the functionality of the relay chain is minimized,<br />with the expectation that more complex functionalities will be pushed to less critical parts of the system.
-
----
-
-## Relay Chain Functionality:
-
-<pba-flex center>
-
-- Governance (moving to parachain)
-- Staking
-- Registration, scheduling,<br />and advancement of parachains
-- Communication between parachains
-- Consensus Safety
-- Balance Transfers
-
-</pba-flex>
-
----
-
-## Relay Chain Games:
-
-The Relay Chain consists of two key games:
-
-<pba-flex center>
-
-- Relay Chain Consensus
-- Parachain Consensus
-
-</pba-flex>
-
-These games are the enablers of all activity within Polkadot.
-
----
-
-## Game: Relay Chain Consensus (simplified)
-
-<div style="font-size: 0.8em">
-
-<pba-flex left>
-
-**Goal:**
-
-- Grow and finalize the relay chain, comprised of only valid blocks
-
-</pba-flex>
-<pba-flex left>
-
-**Rules:**
-
-</pba-flex>
-
-- Validators put skin in the game in the form of tokens.
-- Validators are incentivized to make new relay chain blocks (BABE)
-- Validators are incentivized to vote to finalize recent relay chain blocks (GRANDPA)
-- Validators are incentivized to include user transactions in their relay chain blocks.
-- Validators get nothing for building bad blocks or building on top of them.
-- Validators are slashed for making blocks out of turn.
-
-</div>
-
-<br />
-
-**The game works whenever <1/3 of validators misbehave.**
-
----
-
-## Game: Parachain Consensus (simplified)
-
-<div style="font-size: 0.8em">
-
-<pba-flex left>
-
-**Goal:**
-
-- Grow registered parachains and post only valid updates to the Relay Chain
-
-</pba-flex>
-<pba-flex left>
-
-**Rules:**
-
-</pba-flex>
-
-- Validators are incentivized to attest to new parachain updates
-- Whichever Validator makes the next Relay Chain block includes some attested parachain updates
-- Validators are slashed if they attest to incorrect parachain updates
-  - incorrect means "not according to the parachain's Wasm code"
-- Validators check each others' work to initiate the slashing procedure
-
-</div>
-
-<br />
-
-**The game works whenever <1/3 of validators misbehave.**
-
----
-
-All other functionalities of the relay chain (staking, governance, balances, etc.) are just baked into the definition of **valid block** and **valid transaction**.
-
----
-
-## Staking: Nominated Proof-of-Stake
-
-As the Relay Chain progresses, it operates a system for selecting and accruing capital behind validators.
-
-Accounts on Polkadot may issue a "nominate" transaction to select validators they support.
-Every day, an automated election selects the validators for the next 24 hours.
-
-Nominators share in both the reward and slashing of their nominees.
-
----
-
-## Message Passing: Trustless Communication
-
-The Relay Chain manages message queues and channels between parachains, as well as between each parachain and the Relay Chain itself.
-
-Part of the Validators' job is to ensure that message queues are properly maintained and updated.
-
----
-
-## Registering Parachains
-
-In 1.0: this is done via Slot Auctions to get a large bulk allocation
-
-In the future: this will be done on a more granular / ad-hoc basis
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-## Governance & Evolution
-
----
-
-## OpenGov
-
-Polkadot has on-chain governance by stakeholder referendum, voting on subjects such as:
-
-<pba-flex center>
-
-- Forkless upgrades of the network
-- Administration of the Treasury funds
-- Configuration of the Parachains protocol
-- Configuration of fees
-- Rescue & recovery operations
-- All other mechanisms of control over the platform
-
-</pba-flex>
-
-Notes:
-
-<https://www.polkadot.network/features/opengov/>
-
----
-
-## Treasury
-
-<pba-flex center>
-
-- Polkadot ensures that a portion of network fees are collected treasury.
-- The treasury is managed by governance.
-- Tokens are burned if they are not spent.
-
-</pba-flex>
-<br />
-
-The intention of the treasury is to pay people to help grow Polkadot itself.
-As tokens are burned, this creates pressure to fund public projects.
-
----
-
-### The Fellowship
-
-A collective of developers, coordinated through on-chain activities.
-
-These are node maintainers, developers, or researchers.
-
-They set the technical direction for the network through RFCs.
-
----
-
-<!-- .slide: data-background-color="#111" -->
-
-<pba-cols>
-
-<img rounded width="400px" src="./img/rfc_1.png" />
-<img rounded width="400px" src="./img/rfc_3.png" />
-<img rounded width="400px" src="./img/rfc_10.png" />
-
-</pba-cols>
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-## Revisiting Goals
-
----
-
-> (1) Real-time, secure, global consensus on system state
-
-This is provided by the validators participating in **Relay Chain Consensus**.
-Every block they make and finalize advances the system state.
-
----
-
-> (2) Trustless and permissionless transaction at scale
-
-"at scale" is the caveat that drives most of the engineering in Polkadot.
-
-Polkadot scales by virtue of the **Parachain Consensus** game, where the parachains themselves process most of the transactions in the network.
-
-The more efficiently this game is implemented, the more Polkadot scales.
-
----
-
-> (3) Explicit network-wide governance and co-evolution
-
-This is handled by OpenGov and the Treasury.
-Polkadot is a "meta-protocol" where OpenGov can update anything in the network, including the network's own rules.
-
----
-
-> (4) General programmable computation with full security
-
-This is provided by the **Parachain Consensus** game, as most parachains are registered by users and validators are on the hook for valid updates.
-
-Parachains themselves may also provide generalized computational functionality, e.g. EVM contracts.
-
----
-
-> (5) Secure and trust-minimized interoperability between processes
-
-The Relay Chain maintains message queues between chains to provide interoperability (protected trade routes), however, full trust-minimization (enforced trade agreements) requires future protocol features to land.
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-## At Scale: Polkadot's Value Proposition
-
----
-
-## From This
-
-<img rounded width="600px" src="./img/terrarium_bottle.jpg" />
-
----
-
-## To This
-
-<img rounded width="800px" src="./img/amazon_terrarium.jpg" />
-
----
-
-## Blockchain Scalability Trilemma
-
-<pba-cols>
-<pba-col>
-<pba-flex center>
-
-1. Security: how much does it _cost_ to attack the network?
-1. Scalability: how much work can the network do?
-1. Decentralization: how decentralized is the network?
-
-</pba-flex>
-</pba-col>
-<pba-col>
-
-<img rounded width="800px" src="./img/scalability-trilemma.svg" />
-
-</pba-col>
-</pba-cols>
-
-Challenge: Scale while navigating the trilemma.
-
----
-
-## Scaling vs. Scheduling
-
-Scaling is important, but resources must be _allocated_ efficiently to make best use of that.
-
-Polkadot allocates its resources to parachains through **Execution Cores**.
-
----
-
-## Execution Cores
-
-Just like a decentralized CPU, Polkadot multiplexes many processes across cores.
-
-When a parachain is assigned to a core, it can advance.<br />
-Otherwise, it lies dormant.
-
-Execution Cores enable efficient allocation through _Coretime_ trading.
-
----
-
-<!-- .slide: data-background-color="#000000" -->
-
-## One Chain Per Core
-
-<img rounded width="1000px" src="./img/dumb_coretime.png" />
-
-Time -->
-
----
-
-<!-- .slide: data-background-color="#000000" -->
-
-## Execution Cores: Endgame
-
-<img rounded width="1000px" src="./img/smart_coretime.png" />
-
-Time -->
-
----
-
-## Coretime: Polkadot's Product
-
-Coretime is what applications buy to build on Polkadot.<br />
-Goal: be like cloud.
-
-Primary and secondary markets are key enablers.
-
-Scalability + Scheduling
-
----
-
-## Full Circle
-
-> Polkadot is a scalable, heterogeneous, sharded, multi-chain network.
-
-> Polkadot is a permissionless and ubiquitous computer
-
-> Polkadot is a decentralized open-source community
-
-> Polkadot is a digital-native sovereign network
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
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-
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-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
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-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
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-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Light Clients and Unstoppable Apps
-description: Light Clients and Unstoppable Apps, for web3 builders.
-duration: 45+ mins
----
-
-# Light clients<br />and<br />Unstoppable Apps
-
----
-
-#### Traditional Web 2
-
-<img rounded style="width: 80%;" src="./img/web2.png" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-Before I proceed with anything, let's take a moment to see the current state of the majority of the World Wide Web as we know it.
-
-Welcome to the realm of Web 2.0, where the majority of web applications currently reside.
-While I won't be roasting anyone, it's essential to recognize that platforms like Facebook, Twitter, WhatsApp, and many others fall under this category; (Describe image)
-
----v
-
-#### The Web 3 vision
-
-<img rounded style="width: 80%;" src="./img/web3.png" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-This represents the vision of what web3 should aspire to become:
-a truly interconnected network where validators and end-users from all corners of the world can seamlessly connect, share information, and collaborate.
-
-Now, show of hands:
-
-- how many of you believe that we are close to achieving this vision at the moment?
-- And how many think we still have a considerable distance to go?
-
----v
-
-#### The Web 3 reality
-
-<img rounded style="width: 80%;" src="./img/web3_reality.png" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-Let's take a closer look at the reality of the situation.
-As it stands, our entry into the blockchain network is channeled through a central access point, represented by a JSON-RPC node.
-This node serves as the gateway to access the entire blockchain network.
-
-While many applications claim to be decentralized, we must ask ourselves, how truly decentralized are they?
-
-Now, I want to emphasize one crucial point - and I encourage you to take a moment to reflect on it.
-I will pause there for a few seconds to let this sink in;
-
----v
-
-<h1 style="font-size:7rem; font-weight: bold">Blockchain "decentralized” apps are still centralized</h1>
-
-Notes:
-
-I will pause there for a few seconds to let this sink in;
-
----v
-
-<img rounded style="width: 30%;" src="./img/learn-student.gif" />
-
-Notes:
-
-I will pause there for a few seconds to let this sink in;
-
----
-
-# Node types in the network
-
-<p style="text-align: left; padding-bottom: 2rem">The type of each node depends on different characteristics:</p>
-
-<ul>
-  <li>
-    <span class="font-bold underline">Validator:</span> node configured to potentially produce blocks.
-  </li>
-<!-- .element: class="fragment" data-fragment-index="1" -->
-  <li>
-    <span class="font-bold underline">JSON-RPC:</span> node which gives public access to its JSON-RPC endpoint.
-  </li>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-  <li>
-    <span class="font-bold underline">Bootnode:</span> node whose address can be found in the chain specification file (chainspec).
-      Necessary to kick-off the network.
-  </li>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-  <li>
-    <span class="font-bold underline">Archive:</span> stores the entire state of the chain at each block since block #0.
-      Useful to access historical data.
-  </li>
-<!-- .element: class="fragment" data-fragment-index="4" -->
-  <li>
-    <span class="font-bold underline text-[var(--r-heading-color)]">Light client:</span><span class="text-[var(--r-heading-color)]"> doesn’t store the entire state of the chain but requests it on demand.</span>
-  </li>
-<!-- .element: class="fragment" data-fragment-index="5" -->
-</ul>
-
-Notes:
-
-Before anything else – lets remember the node types in the network
-
-Validator Nodes: These nodes are responsible for producing new blocks and validating transactions.
-They participate in the consensus mechanism and play a crucial role in securing the network.
-
-JSON-RPC nodes: serve as an interface for developers and applications to interact with the blockchain by sending JSON-formatted requests and receiving JSON-formatted responses.
-
-Bootnodes: Bootnodes are nodes with well-known addresses that serve as entry points for new nodes joining the network.
-They help new nodes discover and connect to other peers in the network.
-
-Light Nodes: Light nodes are a lightweight version of full nodes that do not store the entire blockchain but rely on full nodes for transaction verification.
-They are useful for users who want to interact with the network without the need to download the entire blockchain.
-
-(......After the Clicks!....)
-
-Any combination of “validator”, “bootnode” and “JSON-RPC node” is possible, except for “light” and “archive” that are mutually incompatible.
-
----v
-
-#### The reality of blockchains today
-
-<img rounded style="width: 100%;" src="./img/reality_bc_today.png" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-Here is how this is happening in reality at the moment, or how one could possibly connect to the network today
-
-(read slides)
-
-Make a note that: For simplicity reasons from now on I will be using the word "UI" to refer to a client/user/app etc/
-Ask: WHAT ARE THE WAYS to connect to the network from a UI like (e.g. polkadotJS apps or any custom one) today?
-
----v
-
-#### USER-CONTROLLED NODE
-
-<pba-cols>
-  <pba-col left>
-    <div>App connects to a node client that the user has installed on their machine</div>
-    <div class="bg-green-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Secure</span><br />Trustless: connects to multiple nodes, verifies everything</div>
-    <div class="bg-red-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Convenient:</span> Works transparently</div>
-  </pba-col>
-  <!-- .element: class="fragment" data-fragment-index="2" -->
-   <pba-col left>
-      <img rounded src="./img/USER-CONTROLLED-NODE.png" />
-  </pba-col>
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-</pba-cols>
-
-Notes:
-
-(Read slides)
-
----v
-
-#### PUBLICLY-ACCESSIBLE NODE
-
-<pba-cols>
-  <pba-col left>
-    <div>App connects to a third-party-owned publicly-accessible
-node client</div>
-    <div class="bg-red-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Centralized and insecure:</span> Publicly-accessible node can be malicious</div>
-    <div class="bg-green-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Convenient:</span> Works transparently</div>
-  </pba-col>
-  <!-- .element: class="fragment" data-fragment-index="2" -->
-  <pba-col left>
-    <img rounded src="./img/PUBLICLY-ACCESSIBLE-NODE.png" />
-  </pba-col>
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-</pba-cols>
-
-Notes:
-
-(Read slides)
-
----v
-
-#### Why this needs fixing?
-
-<pba-cols>
-  <pba-col left>
-      <h4>Reliability</h4>
-      <!-- .element: class="fragment" data-fragment-index="1" -->
-      <div>"The middleman" can stop working for a reason or another, leaving end users incapable of interacting with the blockchain.</div>
-      <!-- .element: class="fragment" data-fragment-index="2" -->
-  </pba-col>
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-   <pba-col left>
-    <h4>Possibility of censorship or hijacking</h4>
-    <!-- .element: class="fragment" data-fragment-index="3" -->
-    <div>"The middleman" can decide to ban some end users or some transactions, or can be taken control of by an attacker.</div>
-    <!-- .element: class="fragment" data-fragment-index="4" -->
-  </pba-col>
-  <!-- .element: class="fragment" data-fragment-index="3 " -->
-   <pba-col left>
-     <h4>Frontrunning problem</h4>
-     <!-- .element: class="fragment" data-fragment-index="5" -->
-     <div>"The middleman" knows all the transactions that are submitted before they are actually applied, and can inject its own transactions ahead of time for its own monetary gains.</div>
-     <!-- .element: class="fragment" data-fragment-index="6" -->
-  </pba-col>
-  <!-- .element: class="fragment" data-fragment-index="5" -->
-</pba-cols>
-
-Notes:
-
-In the 3rd party case the user relies on the 3rd party node to connect to, in order to communicate with the network.
-(audience) With a show of hands Why this needs fixing?
-(pause and wait for possible answer)
-
-- (we need) Reliability
-- (there is a) Possibility of censorship or hijacking
-- Front running is the act of placing a transaction in a queue with the knowledge of a future transaction
-
----v
-
-## The reality of blockchains we want
-
-<img rounded style="width: 100%;" src="./img/reality_we_want.png" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
----v
-
-# The solution
-
-<img rounded src="./img/feather.png" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-# Light Clients
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
----
-
-# What is a light client?
-
-<p style="font-size:4rem">It's a client (a node)...</p>
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-<p style="font-size:1.5rem">...but lighter!</p>
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-When I joined the team of substrate connect, I asked this same question.
-And the response I got was…. (\*)
-Back then I was like… “Yeah – thanks I guess”
-
-But that was actually true!
-
----v
-
-# What is a light client?
-
-<ul>
-  <li>
-    It is a client that is lighter than a full node, in terms of memory consumption, number of threads, and code size;</li>
-<!-- .element: class="fragment" data-fragment-index="1" -->
-  <li> Allows a dApp to access and interact with a blockchain in a secure and decentralized manner without having to sync the full blockchain;</li>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-  <li> It is a node that doesn’t store the entire state of the chain but requests it on demand;</li>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-  <li> It connects and interacts with the network in a fully trust-less way with it;</li>
-<!-- .element: class="fragment" data-fragment-index="4" -->
-  </li>
-  <!-- .element: class="fragment" data-fragment-index="4" -->
-</ul>
-
-Notes:
-
-In the next slides we will explain "What is a light client" in a generic manner but also I will add some extra information around the Polkadot ecosystem solution that is implemented;
-
-Bullet 1) A "light client" is a type of node implementation that allows applications to interact with the network, consuming fewer resources compared to full nodes, making them more suitable for resource-constrained devices like mobile phones, or light enough for running in browsers (see substrate connect);
-
-Bullet 2) Instead of maintaining a complete copy of the blockchain, the node only carries a minimal amount of data necessary for its operations (e.g.chain specs).
-It relies on full nodes or other network participants to provide the additional information it needs;
-
-Bullet 3) ....
-based on the request it either provides the response from existing data, if any, or propagates the request to a full node and returns the response;
-
-Bullet 4) Light clients can synchronize with the blockchain more quickly since they only need to fetch recent data, using justifications (we will talk about it in a while), reducing the time needed to get up-to-date with the network (few seconds).
-They fetch less data from the network and consume less bandwidth.
-This is especially advantageous for users on limited data plans or slow internet connections
----v
-
-### Real-life example
-
-<video controls width="100%">
-    <source src="./img/LightClients.mp4" type="video/mp4">
-    Sorry, your browser doesn't support embedded videos.
-</video>
-
-Notes:
-
-"Slow internet connections": lets see a real-life example.
-Time: Polkadot decoded 2022; Stage: Co-founder of Talisman wallet, Jonathan Dunne, takes the stage demo of our Light client solution (smoldot) is integrated in the wallet, and what are the benefits - using a very "questionable internet connection" which had a very bad day due to way-too-many-connected people;
-Once the [talisman wallet](https://www.talisman.xyz/) loads up, pay attention to the spinners - Polkadot is loading with a light client while Kusama with the usual JSON-RPC method
-
-Full video: <https://www.youtube.com/watch?v=oaidhA5eL_8>
-
----v
-
-<h2>How does a light client know where to connect to</h2>
-
-<pba-cols>
-  <pba-col left>
-    <img rounded style="width: 100%" src="./img/where_to_1.png" />
-  </pba-col>
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-  <pba-col left>
-    <img rounded style="width: 100%" src="./img/where_to_2.png" />
-  </pba-col>
-  <!-- .element: class="fragment" data-fragment-index="2" -->
-</pba-cols>
-
-Notes:
-
-As you probably already learned a chain specification is a configuration file that defines the parameters and initial settings for a blockchain network.
-
-It serves as a blueprint for launching and running a new blockchain node, providing essential information to set up the network;
-
-Our Substrate nodes can produce what is called a Chain spec which Smoldot then uses in order to spin up a light client node based on that chain-spec;
-(Show the chainspec on screen)
-
----v
-
-### How does a light client know what/who to trust
-
-<img rounded style="margin-top: 150px; width: 70%" src="./img/know-who-to-trust.png" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-As we know Substrate chains provides the concept of FINALITY which is VERY important for the light clients!
-Once a block has been finalized, it is guaranteed to always be part of the best chain.
-By extension, the parent of a finalized block is always finalized as well etc etc
-For finality Substrate/Polkadot nodes use the GrandPa algorithm.
-Authorized nodes, emit votes on the network, when 2/3rds or more have voted for a specific block, it effectively becomes finalized.
-These votes are been collected in what is called a **justification**
-
-**Justifications** play a crucial role in providing security and validity guarantees for light clients.
-As said before, light clients are nodes that do not store blockchain's data but rely on other full nodes or the network to verify the blockchain's state and transactions.
-While light clients offer reduced resource requirements and faster synchronization, they face the challenge of trusting the information they receive from other nodes.
-
-Justifications address this trust issue for light clients by providing cryptographic proofs of the finality and validity of blocks.
-When a block is justified, it means that it has been confirmed and agreed upon by a supermajority of validators, making it part of the finalized state of the blockchain.
-
-It is also used by nodes who might not have received all the votes, or for example if they were offline, In order to verify the authenticity of the blocks;
-
-A Light client receives these justifications and this way it verifies the authenticity of a block.
-
----v
-
-<section>
-  <diagram class="mermaid limit size-80">
-    sequenceDiagram
-        Network->>Justification: Finality and create
-        Network->>Justification: Finality and create
-        App->>LightClient: Wake up and sync!
-        LightClient->>Justification: Hey! I'm here!
-        Justification-->>LightClient: Here you go
-        Justification-->>LightClient: Here you go
-        Justification-->>LightClient: Here you go
-        App->>LightClient: Ready?!
-        LightClient->>App: Not yet! Syncing
-        Justification-->>LightClient: Here you go
-        LightClient-->>App: Verified and synced!
-        App->>LightClient: 'right! Now gimme stuff
-        LightClient->>Network: Lets talk! App wants stuff
-        Network-->>LightClient: Ok then!
-        LightClient-->>App: Here you go!
-  </diagram>
-</section>
-
----v
-
-<pba-cols>
-  <pba-col left>
-    <h2 style="text-align: center">Full node</h2>
-  </pba-col>
-  <pba-col left>
-    <h2 style="text-align: center">Light client</h2>
-  </pba-col>
-</pba-cols>
-<pba-cols>
-  <pba-col left>
-    <div class="white, bg-[var(--r-heading-color)] text-base rounded-2xl p-4 !mt-2">Fully verifies all blocks (authenticity/validity)</div>
-    <div class="white, bg-[var(--r-heading-color)] text-base rounded-2xl p-4 !mt-2">Holds all the chain’s storage in its database</div>
-    <div class="white, bg-[var(--r-heading-color)] text-base rounded-2xl p-4 !mt-2">Holds all past blocks in its database</div>
-    <div class="white, bg-[var(--r-heading-color)] text-base rounded-2xl p-4 !mt-2">At initial startup, can take hours to be
-ready</div>
-  </pba-col>
-
-<pba-col left>
-    <div class="white, bg-[var(--r-heading-color)] text-base rounded-2xl p-4 !mt-2">Only verifies the authenticity of blocks</div>
-    <div class="white, bg-[var(--r-heading-color)] text-base rounded-2xl p-4 !mt-2">Requests state of the chain on demand</div>
-    <div class="white, bg-[var(--r-heading-color)] text-base rounded-2xl p-4 !mt-2">No database whatsoever</div>
-    <div class="white, bg-[var(--r-heading-color)] text-base rounded-2xl p-4 !mt-2">Initializes in few seconds</div>
-  </pba-col>
-</pba-cols>
-
----
-
-<img src="./img/words.png" />
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-Notes:
-
-Now, let's dive into the Polkadot solution of light clients for all Substrate chains.
-
-As we progress through the slide, you might have come across or heard various terms and concepts related to light clients.
-
-At this point, it's crucial to draw a clear distinction;
-Let's proceed with a more focused and detailed exploration of light clients in the Polkadot Ecosystem.
-
----v
-
-<h1>Smoldot<h1>
-
-<div style="font-size:2.5rem; color: #fff">light client implementation from scratch</div>
-  <!-- .element: class="fragment" data-fragment-index="1" -->
-
-## rust
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-<div>
-  <div style="font-size:1.75rem; color: #fff">smoldot-light-js (/wasm-node) - npm/deno</div>
-  <!-- .element: class="fragment" data-fragment-index="3" -->
-  <div style="font-size:1.75rem; color: #fff">smoldot (/lib) - Rust library</div>
-  <!-- .element: class="fragment" data-fragment-index="4" -->
-  <div style="font-size:1.75rem; color: #fff">smoldot-light (/light-base)</div>
-  <!-- .element: class="fragment" data-fragment-index="5" -->
-  <div style="font-size:1.75rem; color: #fff">smoldot-full-node (/full-node)</div>
-  <!-- .element: class="fragment" data-fragment-index="6" -->
-</div>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-<p class="inline-table">
-  <img style="width: 10rem; padding-top: 3rem" src="../../blockchain-contracts/light-clients-bridges/img/tomaka.png" />
-  <!-- .element: class="fragment" data-fragment-index="7" -->
-  <div style="font-size:1.5rem; color: #fff">Pierre Krieger - tomaka</div>
-  <!-- .element: class="fragment" data-fragment-index="7" -->
-</p>
-<!-- .element: class="fragment" data-fragment-index="7" -->
-
-<a href="https://github.com/smol-dot/smoldot/">https://github.com/smol-dot/smoldot/</a>
-
-<!-- .element: class="fragment" data-fragment-index="8" -->
-
-Notes:
-
-Smoldot - is the light client implementation from scratch - meaning, we did not make substrate lighter.
-It was rewritten from scratch, in rust - and it comes with:
-
-- smoldot-light-js (/wasm-node): A JavaScript package that can connect to a Substrate-based chains as a light client.
-  Works both in the browser and in NodeJS/Deno.
-  This is the main component of this repository.
-- smoldot (/lib): An unopinionated Rust library of general-purpose primitives that relate to Substrate and Polkadot.
-  Serves as a base for the other components.
-- smoldot-light (/light-base): A platform-agnostic Rust library that can connect to a Substrate-based chain as a light client.
-  Serves as the base for the smoldot-light-js component explained above.
-- smoldot-full-node (/full-node): A work-in-progress prototype of a full node binary that can connect to Substrate-base chains.
-  Doesn't yet support many features that the official client supports.
-
-Powered by Pierre Krieger (a.k.a. tomaka)
-
----v
-
-## Substrate Connect
-
-<div style="font-size:1.75rem; color: #fff">uses smoldot as an implementation detail</div>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-<div style="font-size:1.5rem; color: #d92f78; margin: 0.5rem 0">javascript/typescript</div>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-  <img width="900" src="./img/wellknown.png"  style="margin: 1rem 15%" />
-  <!-- .element: class="fragment" data-fragment-index="4" -->
-<p style="font-size:1.5rem; margin-top: 1rem"><a href="https://github.com/paritytech/substrate-connect/">https://github.com/paritytech/substrate-connect/</a></p>
-<!-- .element: class="fragment" data-fragment-index="5" -->
-
-Notes:
-
-- npm package
-- rpc provider from polkadotJS
-- Chrome and Mozilla extension
-- Comes with 4 integrated "Well Known" chains (Kusama, Polkadot, Westend, Rococo) - which means these chains can be used without the need of providing chainspecs;
-
----v
-
-## On a diagram
-
-<section>
-  <diagram class="mermaid">
-    stateDiagram-v2
-      Smoldot_Light_Client --> Substrate_connect
-      Substrate_connect --> PolkadotJS_API
-      PolkadotJS_API --> UI_dAPP
-
-    Smoldot_Light_Client --> Custom_Code\n(with_JSON_RPC_API)
-    Custom_Code\n(with_JSON_RPC_API) --> UI_dAPP
-
-</diagram>
-</section>
-
----
-
-## Smoldot Light Client
-
-- (As Substrate, it also) supports the new JSON-RPC protocol that has been developed;
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Light and fast enough so that it can be embedded into a mobile application or an application in general;
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-- new JSON-RPC protocol: https://github.com/paritytech/json-rpc-interface-spec/
-- As showcased in Decoded 2023 by Daan van der Plas: "Smoldot in Mobile Apps" (https://www.youtube.com/watch?v=Z7FiFHgotzE&feature=share)
-
-We'll be using substrate connect's TS/JS code as pseudo-code for our examples
-
----
-
-## Publicly Accessible Node
-
-The dApp (UI) connects to a third-party-owned publicly-accessible node client
-
-<p class="bg-red-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Centralized and insecure:</span> Publicly-accessible node can be malicious</p>
-<p class="bg-green-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Convenient:</span> Works transparently</p>
-
----v
-
-## So what one needs to do
-
-- Find the web-socket url of a 3rd party node (JSON-RPC node) that one trusts;
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Add it to the code and use it;
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
----v
-
-## In your dApp
-
-```javascript[0|1|3-5|7-9]
-import { ApiPromise, WsProvider } from "@polkadot/api";
-
-// Maybe some more code that does some magic here
-const provider = new WsProvider("wss://westend-rpc.polkadot.io");
-const api = await ApiPromise.create({ provider });
-
-// Interact using polkadotJS API
-const header = await api.rpc.chain.getHeader();
-const chainName = await api.rpc.system.chain();
-```
-
----
-
-## User-Controlled Node
-
-The dApp (UI) connects to a node client that the user has installed on their machine
-
-<p class="bg-green-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Secure Trustless:</span> connects to multiple nodes, verifies everything</p>
-<p class="bg-red-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Inconvenient:</span> Needs an installation process and having a node up and running, plus maintenance effort</p>
-
----v
-
-## So what one needs to do
-
-<pba-flex center>
-
-1. Install dependencies<br />
-   (e.g. rust, openssl, cmake, llvm etc);
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-1. Clone from github the "polkadot" repo;
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-1. Build the node locally;
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-1. Start the node locally;
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-1. Wait for the node to synchronize;
-   <!-- .element: class="fragment" data-fragment-index="5" -->
-   <pba-flex>
-
----v
-
-<p>...wait for the node to synchronize...</p>
-<!-- .element: class="fragment" data-fragment-index="1" -->
-<p>.......</p>
-<!-- .element: class="fragment" data-fragment-index="2" -->
-<p>..........</p>
-<!-- .element: class="fragment" data-fragment-index="3" -->
-<p>..................</p>
-<!-- .element: class="fragment" data-fragment-index="4" -->
-<p>......wait for it.......</p>
-<!-- .element: class="fragment" data-fragment-index="5" -->
-<p>..............................</p>
-<!-- .element: class="fragment" data-fragment-index="6" -->
-<p>ok</p>
-<!-- .element: class="fragment" data-fragment-index="7" -->
-
----v
-
-## In your dApp
-
-```javascript[|1|3-5|7-9]
-import { ApiPromise, WsProvider } from "@polkadot/api";
-
-// Maybe some more code that does some magic here
-const provider = new WsProvider("wss://127.0.0.1:9944");
-const api = await ApiPromise.create({ provider });
-
-// Interact using polkadotJS API
-const header = await api.rpc.chain.getHeader();
-const chainName = await api.rpc.system.chain();
-```
-
----
-
-## Light Client in the Browser
-
-The uApp (UI) connects to an _integrated_ light client
-
-<p class="bg-green-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Secure Trustless:</span> connects to multiple nodes, verifies everything</p>
-<p class="bg-green-600 rounded-2xl p-4 !mt-2"><span class="font-bold">Convenient:</span> Works transparently</p>
-
----v
-
-## So what one needs to do
-
-<pba-flex center>
-
-1. Install and configure the light client inside the dApp
-
-</pba-flex>
-
----v
-
-## With PolkadotJS API
-
-```javascript[0|1-2|4-7|9-11]
-import { ScProvider } from "@polkadot/rpc-provider/substrate-connect";
-import * as Sc from '@substrate/connect';
-
-// Maybe some more code that does some magic here
-const provider = new ScProvider(Sc, Sc.WellKnownChain.westend2);
-await provider.connect();
-const api = await ApiPromise.create({ provider });
-
-// Interact using polkadotJS API
-const header = await api.rpc.chain.getHeader();
-const chainName = await api.rpc.system.chain();
-```
-
----v
-
-### Or even without PolkadotJS API
-
-```javascript[0|1|4|5-10|12-15]
-import { createScClient, WellKnownChain } from "@substrate/connect";
-
-// Maybe some more code that does some magic here
-const scClient = createScClient();
-const mainChain = await scClient.addWellKnownChain(
-  WellKnownChain.polkadot,
-  jsonRpcCallback = (response) {
-    console.log(response);
-  }
-);
-
-// Communicate with the network
-mainChain.sendJsonRpc(
-  '{"jsonrpc":"2.0","id":"1","method":"chainHead_unstable_follow","params":[true]}',
-);
-```
-
----v
-
-### Or even without PolkadotJS API
-
-### and with a Custom Chainspec
-
-```javascript[0|1|2,4|7|8,13|9|10-12| 15-18]
-import { createScClient, WellKnownChain } from "@substrate/connect";
-import myLovelyChainspec from './myLovelyChainspecFromSubstrateChain.json';
-
-const myLovelyChainspecStringified = JSON.stringify(myLovelyChainspec);
-
-// Maybe some more code that does some magic here
-const scClient = createScClient();
-const mainChain = await scClient.addChain(
-  myLovelyChainspecStringified,
-  jsonRpcCallback = (response) {
-    console.log(response);
-  }
-);
-
-// Communicate with the network
-mainChain.sendJsonRpc(
-  '{"jsonrpc":"2.0","id":"1","method":"chainHead_unstable_follow","params":[true]}',
-);
-```
-
----v
-
-### Or even only with smoldot
-
-```javascript[0|1|3|5,13|6-12|15|17|18|20|21]
-import * as smoldot from "smoldot";
-
-const chainSpec = new TextDecoder("utf-8").decode(fs.readFileSync('./westend-chain-specs.json'));
-
-const client = smoldot.start({
-    maxLogLevel: 3,  // Can be increased for more verbosity
-    forbidTcp: false,
-    forbidWs: false,
-    forbidNonLocalWs: false,
-    forbidWss: false,
-    cpuRateLimit: 0.5,
-    logCallback: (_level, target, message) => console.log(_level, target, message)
-});
-
-client.addChain({ chainSpec, disableJsonRpc: true });
-
-console.log('JSON-RPC server now listening on port 9944');
-console.log('Please visit: https://cloudflare-ipfs.com/ipns/dotapps.io/?rpc=ws%3A%2F%2F127.0.0.1%3A9944');
-
-// Now spawn a WebSocket server in order to handle JSON-RPC clients.
-// See JSON-RPC protocol: https://github.com/paritytech/json-rpc-interface-spec/
-```
-
----
-
-# Some demo maybe…?
-
-<p class="inline-table">
-  <img src="./img/code.jpg" />
-</p>
----
-
-#### Known vulnerabilities
-
-- Eclipse attacks (Full node & Light client)
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Long-range attacks (Full node & Light client)
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- Invalid best block (Only Light client)
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-- Finality stalls (Mostly Light client)
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-Notes:
-
-Stay with me - the next is the last but not the easiest part:
-
-- **Eclipse attacks (full nodes and light clients both affected)**.
-  Blockchain is a P2P network - and Smoldot tries to connect to a variety of nodes of this network (from the bootnodes).
-  Imagine if all these nodes were to refuse sending data back, that would isolate smoldot from the network - The way that smoldot learns which nodes exist, is from the nodes themselves (bootnodes).
-  If smoldot is only ever connected to malicious nodes, it won't ever be able to reach non-malicious nodes - if the list of bootnodes only contains malicious nodes, smoldot will never be able to reach any non-malicious node.
-  If the list of bootnodes contains a single honest node, then smoldot will be able to reach the whole network.
-  !!! this attack is effectively a denial-of-service, as it will prevent smoldot from accessing the blockchain!
-
-- **Long-range attacks (full nodes and light clients both affected)**.
-  If more than 2/3rds of the validators collaborate, they can fork a chain, starting from a block where they were validator, even if they are no longer part of the active validators at the head of the chain.
-  If some validators were to fork a chain, the equivocation system would punish them by stealing their staked tokens.
-  However, they cannot be punished if they unstake their tokens (which takes 7 days for Kusama or 28 days for Polkadot) before creating the fork.
-
-  If smoldot hasn't been online since the starting point of the fork, it can be tricked (through an eclipse attack) into following the false fork.
-  In order to not be vulnerable, smoldot shouldn't stay offline for more than the unstaking delay time (as said 7 days for Kusama or 28 days for Polkadot) in a row.
-  Alternatively, smoldot isn't vulnerable if the checkpoint provided in the chain specification, is not older than the unstaking delay.
-
-  Given that this attack -> requires the collaboration of many validators, -> is "all-in", -> is detectable ahead of time, -> it requires being combined with an eclipse attack, and that it doesn't offer any direct reward, it is considered not a realistic threat.
-
-- **Invalid best block (light clients only)**.
-  Light clients don't verify validity but only authenticity of blocks.
-
-  A block is authentic if it has been authored by a legitimate validator, at a time when it was authorized to author a block.
-  A validator could author a block that smoldot considers as authentic, but that contains completely arbitrary data.
-
-  Invalid blocks aren't propagated by honest full nodes on the gossiping network, but it is possible for the validator to send the block to the smoldot instance(s) that are directly connected to it or its complicit.
-  While this attack requires a validator to be malicious and that it doesn't offer any direct reward it is unlikely to happen, but it is still a realistic threat.
-  For this reason, when using a light client, do not assume any storage data coming from a best, that hasn't been finalized yet to be accurate.
-
-  Once a block has been finalized, it means that at least 2/3rds of the validators consider the block valid.
-  While it is still possible for a finalized block to be invalid, this would require the collaboration of 2/3rds of the validators.
-  If that happens, then the chain has basically been taken over, and whether smoldot shows inaccurate data **doesn't really matter anymore**.
-
-- **Finality stalls (mostly light clients)**.
-  Because any block that hasn't been finalized yet can become part of the canonical chain in the future, a node, in order to function properly, needs to keep track of all the valid (for full nodes) or authentic (for light clients) non-finalized blocks that it has learned the existence of.
-  Under normal circumstances, the number of such blocks is rather low (typically 3 blocks).
-  If, however, blocks cease to be finalized but new blocks are still being authored, then the memory consumption of the node will slowly increase over time for each newly-authored block until there is no more memory available and the node is forced to stop.
-  Substrate mitigates this problem by forcing blocks authors to gradually slow down the blocks production when the latest known finalized block is too far in the past.
-  Since it is normally not possible for finality to stall unless there is a bug or the chain is misconfigured, this is not really an attack but rather the consequences of an attack.
-  Full nodes are less affected by this problem because they typically have more memory available than a light client, and have the possibility to store blocks on the disk.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/npos/page.md b/content/polkadot/npos/page.md
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-# Nominated Proof of Stake
-
-<!-- markdown-link-check-disable -->
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-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
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----
-title: Nominated Proof of Stake
-description: An introduction to Nominated Proof of Stake in Polkadot
-duration: 1 hour
----
-
-# Nominated Proof of Stake
-
-## _in Polkadot_
-
----
-
-## Why Proof of Stake Ser?
-
-Why do we use PoS?
-
-<div>
-
-- Tokens locked + prone to being slashed.
-- Economic Security 💸🤑.
-
-</div>
-
-<!-- .element: class="fragment" -->
-
-- Everything else (finality, parachains, etc.) is built on top of this base layer of economic security.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Why Proof of Stake Ser?
-
-- Remember that Polkadot is at the end of the day a validator-set-as-a-service.
-- Secure Blockspace, the main product of Polkadot is provided by these validators.
-
-<img style="width: 1000px" src="./img/dev-6-x-npos-vsas.svg" />
-
----
-
-## What is NPoS: Assumptions
-
-Assumptions:
-
-- **Validators**: those who intend to author blocks. i.e. _Validator candidate_.
-
-<!-- .element: class="fragment" -->
-
-- **Nominators/Delegators**: Those who intend to support wanna-be authors.
-
-<!-- .element: class="fragment" -->
-
-- Validation and nomination intentions can change, therefore we need **periodic elections** to
-  always choose the **active/winner validators/delegators** + hold them slashable.
-
-<!-- .element: class="fragment" -->
-
-- Every election period is called an **_Era_**, e.g. 24hrs in Polkadot.
-
-<!-- .element: class="fragment" -->
-
----
-
-### What is NPoS: Re-inventing the Wheel
-
----v
-
-**Solo-POS**
-
-<img style="width: 1000px" src="./img/dev-6-x-npos-0.svg" />
-
----v
-
-### What is NPoS: Re-inventing the Wheel
-
-- Authority-wanna-bees aka. validators bring their own stake. No further participation. Top validators are elected.
-
-- Problems?
-
-Notes:
-
-Low amount of stake that we can capture, impossible for those who don't want to run the hardware to join.
-
----v
-
-**Single-Delegation-POS**
-
-<img style="width: 1000px" src="./img/dev-6-x-npos-1.svg" />
-
----v
-
-### What is NPoS: Re-inventing the Wheel
-
-- Anyone can dilute themselves in any given validators. Top validator based on total stake are
-  elected.
-- Voters are called **delegators**.
-
-- Problems?
-
-Notes:
-
-- Better, but funds might be delegated to non-winners, which get wasted.
-- In other words, there is no incentive to delegate to those that are non-winners.
-
----v
-
-**Multi-Delegation-POS**
-
-<img style="width: 1000px" src="./img/dev-6-x-npos-2.svg" />
-
----v
-
-### What is NPoS: Re-inventing the Wheel
-
-Your stake is divided $\frac{1}{N}$ (or arbitrarily) among $N$ validators.
-
-Problems?
-
-Notes:
-
-Same issue as before.
-
----v
-
-**Nominated Proof of Stake**
-
-<img style="width: 1000px" src="./img/dev-6-x-npos-3.svg" />
-
----v
-
-**Nominated Proof of Stake**
-
-<img style="width: 1000px" src="./img/dev-6-x-npos-4.svg" />
-
----v
-
-### What is NPoS: Re-inventing the Wheel
-
-- You name up to `N` nominees, an _algorithm_, computed either onchain or offchain, decides
-  the **winners** and **how to distribute the stake among them**.
-- Voters are called **Nominators**.
-
----v
-
-### What is NPoS: Re-inventing the Wheel
-
-- ✅ As a nominator, you are free to express your desire to back non-winners as well. Once enough people have expressed the same desire, the non-winner will become a winner.
-
-<!-- .element: class="fragment" -->
-
-- ✅ Has a much higher chance to make sure staked tokens won't get wasted.
-
-<!-- .element: class="fragment" -->
-
-- ✅ Can optimize other criteria other than "who had more approval votes".
-
-<!-- .element: class="fragment" -->
-
----
-
-## NPoS Drawbacks
-
-- We decided to solve an np-hard, multi-winner, approval based, election problem onchain 🤠.
-
-<pba-flex center>
-
-- scalability. <!-- .element: class="fragment" -->
-- scalability. <!-- .element: class="fragment" -->
-- scalability. <!-- .element: class="fragment" -->
-- scalability. <!-- .element: class="fragment" -->
-- and scalability. <!-- .element: class="fragment" -->
-
-</widget-text>
-
-- But we (strive to) get much better economic security measures in return 🌈.
-
-<!-- .element: class="fragment" -->
-
-- Long term, this can in itself be solved by what Polkadot provides best, more Blockspace 🎉!
-
-## <!-- .element: class="fragment" -->
-
-### NPoS Protocol Overview
-
-- The current NPoS protocol revolves around an **election round**, which is itself made up of 4
-  episodes.
-- This gives you an idea about how we solved the scalability issue for the time being.
-
----v
-
-### NPoS Protocol Overview: Episode 1
-
-**Snapshot**
-
-- Enables multi-block election.
-- Allows us to not need to "freeze" the staking system.
-- Allows us to index stakers, not `AccountIds`.
-
----v
-
-### NPoS Protocol Overview: Episode 2
-
-**Signed Submissions**
-
-- Any signed account can come up with a **NPoS solution** based on that snapshot.
-- Deposits, rewards, slash, other game-theoretic tools incorporated to make to secure.
-
----v
-
-### NPoS Protocol Overview: Episode 3
-
-**Validator Submissions as Fallback**
-
-- As the first backup, any validator can also submit a solution as a part of their block authoring.
-
----v
-
-### NPoS Protocol Overview: Episode 4
-
-**Fallbacks**
-
-- If all of the above fails, the chain won't rotate validators and the governance can either:
-  - dictate the next validator set.
-  - trigger an onchain election (limited in what it can do).
-
-## This was recently [used in Kusama](https://forum.polkadot.network/t/kusama-era-4543-slashing/1410) 🦜.
-
-## NPoS Objective
-
-- Given the powerful tool of NPoS, what should we aim for?
-- Let's first recap:
-
-1. Polkadot validators are the source of truth for the state transition of both the relay chain and all of the parachains + bridges.
-
-<!-- .element: class="fragment" -->
-
-2. Polkadot validator are assigned to parachains as backing group, and swapped over time.
-
-<!-- .element: class="fragment" -->
-
-3. Polkadot validators all author the same number of blocks, i.e. they are of same importance.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Point 2 is not to imply that the polkadot validator set's security is partitioned among parachains,
-security comes from approval voters.
-<https://www.polkadot.network/blog/polkadot-v1-0-sharding-and-economic-security/>
-
----v
-
-### NPoS Objective: Election Score
-
-```rust
-pub struct ElectionScore {
-  /// The minimal winner, in terms of total backing stake.
-  ///
-  /// This parameter should be maximized.
-  pub minimal_stake: u128,
-  /// The sum of the total backing of all winners.
-  ///
-  /// This parameter should maximized
-  pub sum_stake: u128,
-  /// The sum squared of the total backing of all winners, aka. the variance.
-  ///
-  /// Ths parameter should be minimized.
-  pub sum_stake_squared: u128,
-}
-```
-
----v
-
-### NPoS Objective: Election Score
-
-- NPoS allows us to incentivize the formation of a validator set that optimized the aforementioned `ElectionScore`.
-
-- This score is ALWAYS calculate and checked onchain. This is why we can accept solutions from the outer world.
-
-Notes:
-
-A common example: we allow signed submissions. What if they send solutions that are censoring a particular validator? if it can achieve a better score, so be it! we don't care.
-
----v
-
-### NPoS Objective: Election Score
-
-- The default algorithm used in both the onchain/offchain solvers is the [Phragmen algorithm](https://en.wikipedia.org/wiki/Phragmen%27s_voting_rules).
-- Proved to provide high fairness and justified representation properties whilst being verifiable in
-  linear time.
-
----
-
-## NPoS Future
-
-- Fresh from the oven (Jan 2023): [Future of Polkadot Staking in the Polkadot forum](https://forum.polkadot.network/t/the-future-of-polkadot-staking/1848/2).
-- [Github issue-tracker/project](https://github.com/orgs/paritytech/projects/33)
-
-<hr>
-
-- Nomination Pools
-- Multi-page election submission
-- Operators as first class citizens.
-- fast-unstake.
-
----
-
-## Additional Resources! 😋
-
-<img width="300px" rounded src="../../substrate/scale/img/thats_all_folks.png" />
-
-> Check speaker notes (click "s" 😉)
-
-Notes:
-
-### Further Reading
-
-- Recent Kusama slashing: https://forum.polkadot.network/t/kusama-era-4543-slashing/1410
-- [A verifiably secure and proportional committee election rule](https://arxiv.org/abs/2004.12990)
-- 4.1 in [Overview of Polkadot and its Design Considerations](https://arxiv.org/abs/2005.13456)
-- [Proportional Justified Representation](https://arxiv.org/abs/1611.09928)
-- [Justified representation - Wikipedia](https://en.wikipedia.org/wiki/Justified_representation)
-
-### NPoS Protocol: More Details, Backup Slides
-
-- `bags-list`: how to store an unbounded semi-sorted linked-list onchain.
-- Nomination pools: best of both.
-- Minimum-untrusted score.
-- PJR checking: why we don't do it.
-- `reduce` optimization.
-
-### Feedback After Lecture:
diff --git a/content/polkadot/opengov/page.md b/content/polkadot/opengov/page.md
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-# OpenGov
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
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diff --git a/content/polkadot/opengov/slides.md b/content/polkadot/opengov/slides.md
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----
-title: OpenGov
-description: The Polkadot ecosystem on-chain governance solution
-duration: 1 hour
----
-
-# OpenGov
-
-Notes:
-
-Hello!
-
-I'm Bradley Olson
-
-Was student at first Academy in Cambridge
-
-Currently on Parachains Core Team at Parity
-
-Making Polkadot truly decentralized requires a robust, agile, and democratic system of governance.
-
-Gavin has put a lot of effort over the last year or so into crafting a system which does those words justice, OpenGov.
-
-I'm here to give you an overview of what OpenGov is and to surface some new information about how it is performing on Kusama.
-
-So lets get to it
-
----
-
-## Overview
-
-<pba-flex center>
-
-- Why blockchain governance?
-- Why on-chain?
-- Goals of on-chain governance
-- Initial Solution, Governance V1
-- Improvement, OpenGov
-- How is it going? By the numbers.
-- OpenGov and you
-
-</pba-flex>
-
----
-
-## Reasons for Blockchain Governance
-
-<pba-flex center>
-
-- Software as executive branch
-  - Applies existing laws (code) in pre-defined ways
-  - Protocol security ensures the letter of those laws is followed
-- But evolving protocols need a legislative branch
-  - To update the laws (code)
-  - To rectify cases where letter != spirit (bugs)
-  - To trigger parts of the system that aren't on a set schedule
-  - To spend treasury funds
-- Legeslative can be on or off chain
-
-</pba-flex>
-
----
-
-## Why On-chain?
-
-<pba-cols style="font-size:smaller">
-<pba-col center>
-
-- Off-chain governance
-
-  - Formal proposal by dev team
-  - Discussions, debates, and media campaigns
-  - Hard fork
-
-- Issues
-  - Centralization
-  - Low throughput
-  - Long decision period
-  - Little accessibility
-
-</pba-col>
-<pba-col center>
-
-<!-- set height*width in px, where full screen is 1920*1080 -->
-<img rounded style="width: 300px" src="./img/Bitcoin.png" />
-
-<!-- set height*width in px, where full screen is 1920*1080 -->
-<img rounded style="width: 200px" src="./img/Ethereum.png" />
-
-</pba-col>
-</pba-cols>
-
----
-
-## Goals of On-chain Governance
-
-<pba-flex center>
-
-- **Transparency**: Decisions by who and by what rules?
-- **Decentralization**: Distributed power, weighted only by commitment and conviction
-- **Security**: Harmful proposals don't pass or have limited scope
-- **Accessibility**: Easy to draft proposal, to receive vote, to vote yourself, and to vote by proxy
-- **Concurrency**: Maximize simultaneous referenda as security allows
-- **Speed**: Each referendum completed as fast as security allows
-- **Agility**: Speed is responsive to support/controversy
-
-</pba-flex>
-
----
-
-## Governance V1
-
-<pba-cols>
-<pba-col center>
-
-<!-- set height*width in px, where full screen is 1920*1080 -->
-<img rounded style="width: 300px" src="./img/Polkadot.png" />
-
-</pba-col>
-<pba-col center style="font-size:smaller">
-
-- Tri-cameral system: Referenda, council, and technical committee
-- Single track
-- 1 referendum at a time
-- Root origin (Unlimited Power!)
-- 28 day referendum
-- 1 month minimum enactment period
-- Emergency handled technical committee
-- Cancellations by council and technical committee
-- Most proposals initiated by council
-- Fully council controlled roles such as tipping
-
-</pba-col>
-</pba-cols>
-
----
-
-## Gov V1, Room for Improvement
-
-<pba-cols>
-<pba-col left>
-
-The good:
-
-- Security
-- Transparency
-
-The bad:
-
-- Decentralization
-- Concurrency
-- Speed
-- Agility
-
-</pba-col>
-<pba-col center>
-
-<!-- set height*width in px, where full screen is 1920*1080 -->
-<img rounded style="width: 500px" src="./img/Snail.jpeg" />
-
-</pba-col>
-</pba-cols>
-
----
-
-## OpenGov Overview
-
-<pba-cols>
-<pba-col center>
-
-- Origins and tracks
-- Lifecycle of a referendum
-- Support and approval threshold curves
-- The Polkadot Fellowship
-- Vote delegation by track
-- OpenGov and governance goals
-
-</pba-col>
-<pba-col center>
-
-<!-- set height*width in px, where full screen is 1920*1080 -->
-<img rounded style="width: 500px" src="./img/overview.png" />
-
-</pba-col>
-</pba-cols>
-
----
-
-## Origins
-
-<pba-flex center>
-
-- Level of privilege that code executes with
-- Similar to user on Unix
-- Proposal is two things
-  - Operation: What should happen
-  - Origin: Who authorizes it
-- Many operations require a specific origin
-
-</pba-flex>
-
----
-
-<!-- set height*width in px, where full screen is 1920*1080 -->
-<img rounded style="width: 300px" src="./img/rail_road_tracks.jpeg" />
-
-## Origins and Tracks
-
-- Each origin is served by a referendum track
-- A track can serve more than one origin
-- These tracks are totally independent from one another
-- Track examples: Root, ParachainAdmin, BigSpender, Tipper
-- Emergency tracks: ReferendumCanceler, ReferendumKiller
-
----
-
-## Track Parameters
-
-<pba-cols>
-<pba-col>
-
-Parameters give us the ability to find an optimal balance between security and throughput.
-
-The security needs of the Tipper track are very different than those of the Root track.
-
-</pba-col>
-<pba-col>
-<pba-flex center>
-
-- Lead-in period duration
-- Decision period duration
-- Confirmation period duration
-- Minimum enactment period
-- Concurrency, how many referenda can run in this track at a time
-- Support and Approval threshold curves
-
-</pba-flex>
-</pba-col>
-</pba-cols>
-
----
-
-<pba-cols>
-<pba-col>
-
-### OpenGov Tracks
-
-</pba-col>
-<pba-col>
-
-<img rounded style="width: 600px" src="./img/TracksTable.webp" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Highlight difference between parameters of WhiteListedCaller and Root tracks
-
----
-
-## Criteria for Passing a Proposal
-
-- Approval: Approving votes/total votes cast, weighted by conviction
-  - Conviction: Locking tokens for longer periods scales their voting impact up to a maximum of 6x with a lockup duration of 896 days
-- Support: Approving votes/total possible vote pool, disregarding conviction
-
----
-
-## Decision and Confirmation Periods
-
-- If Approval and Support thresholds met, confirmation period begins
-- Approval and Support must remain above respective thresholds for entire confirmation period
-- Confirmation period concludes -> proposal approved early
-- Decision period expires -> proposal rejected
-- There is only one decision period, during which a proposal can potentially enter and leave many confirmation periods if thresholds aren't consistently met
-
----
-
-## Lifecycle of A Referendum
-
-<!-- set height*width in px, where full screen is 1920*1080 -->
-<img rounded style="width: 1000px" src="./img/lifecycle_of_a_referendum.png" />
-
-Notes:
-
-Steps in order: **Proposing, Lead In, Deciding, Confirming, Enactment**
-
----
-
-## Support and Approval Threshold Curves
-
-<pba-flex center>
-
-- We want agility
-  - Well supported proposals pass quickly
-  - Controversial proposals get more deliberation
-- Addressed with time varying curves
-  - Support threshold
-    - Starts at ~50%
-    - Ends at minimum secure turnout for track <br />(EX: Big Spender ends at 0 + epsilon %)
-  - Approval threshold
-    - Starts at 100%
-    - Ends at 50 + epsilon %
-- Monotonically decreasing at rates determined by track specific security needs
-
-</pab-flex>
-
----
-
-## Example Support and Approval Curves
-
-<img rounded style="width: 1400px" src="./img/support_and_approval_curves.png" />
-
-Notes:
-
-From PolkaWorld Article in Resources
-
----
-
-## Vote Delegation
-
-<pba-cols style="font-size:smaller">
-<pba-col center>
-
-- Traditional delegation: You entrust one third party with your vote on all matters
-- Delegation by track: You may delegate your vote to one or more third parties on a per track basis
-- EX: Tipper vote delegated to local ambassador, WhiteListedCaller vote delegated to Parity Technologies, vote retained for all other tracks
-- This is likely a first!
-
-</pba-col>
-<pba-col center>
-
-<img rounded style="width: 500px" src="./img/vote.jpeg" />
-
-</pba-col>
-</pba-cols>
-
----
-
-<img rounded style="width: 400px" src="../async-backing-deep/img/stopwatch.png" />
-
-## OpenGov Acting Under Pressure
-
-Typical path to safety: Lower throughput and restricted origins
-
-But in emergencies we may need to pass proposals that both require root origin and are time critical!
-
-Solution: Some sort of oracle capable of providing expert information
-
----
-
-## Oraclization of Expert Information
-
-<pba-flex center>
-
-1. Track everyone's level of expertise
-1. Allow experts to register sentiment
-1. Aggregate opinions by level of expertise
-
-</pba-flex>
-
-> But how are these steps accomplished?
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-## Enter...<br /><br />The Polkadot Fellowship
-
----
-
-Purely on-chain membership body to recognize and compensate all individuals who hold and use expert knowledge of Polkadot in line with its broad interest and philosophy
-
-Members hold rank denoting proven level of expertise and commitment as recognized by their peers and, for higher ranks, through general referendum.
-
----
-
-## Who Make up the Fellowship?
-
-<pba-col center>
-
-- Experts in the Polkadot core protocol who maintain a consistent level of active contribution
-- Notably this does not include core developers of independent parachain protocols, which should develop their own protocol specific fellowships as needed.
-- Trajectory
-  - Currently: < 100 core developers, mostly from Parity or the Web3 Foundation
-  - Next year or two: Hundreds
-  - Ideal far future: Tens of thousands, independent of any centralized entity
-- Only one fellowship for Polkadot and Kusama
-
-</pba-col>
-
----
-
-## Function of the Fellowship
-
-<pba-col center>
-
-- WhiteListedCaller track
-  - Root privileges
-  - More agile
-  - Maintains reasonable safety via Fellowship
-- White list proposals must pass two votes
-  - Expertise weighted Fellowship vote via second referendum pallet instantiation
-  - Same general referendum as other tracks, still requiring majority vote from DOT holders
-- Just an oracle!
-- Secondarily intended to cultivate a long term base of Polkadot core developers outside of Parity
-
-</pba-col>
-
-Notes:
-
-Stress that as an oracle, the Fellowship can't take any action on its own. Any white listed call will still require substantial DOT-holder backing.
-
----
-
-## OpenGov and Governance Goals
-
-<pba-col center>
-
-- Open source + single process + track abstraction -> Transparency
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-- Liberal proposal creation + greater throughput + per-track delegation -> Accessibility
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-- Accessibility + No special bodies -> Decentralization
-
-<!-- .element: class="fragment" data-fragment-index="3" -->
-
-- Limited origins + emergency tracks + white list -> Security
-
-<!-- .element: class="fragment" data-fragment-index="4" -->
-
-- Multiple tracks + low risk tracks -> Concurrency
-
-<!-- .element: class="fragment" data-fragment-index="5" -->
-
-- Low risk tracks + early confirmation -> Speed
-
-<!-- .element: class="fragment" data-fragment-index="6" -->
-
-- Support and approval threshold curves + white list -> Agility
-
-<!-- .element: class="fragment" data-fragment-index="7" -->
-
-</pba-col>
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-# OpenGov<br /><br />By The Numbers
-
----
-
-## Governance Activity
-
-<!-- set height*width in px, where full screen is 1920*1080 -->
-<img rounded style="width: 900px" src="./img/proposals_per_day.png" />
-
-> 5.5x more daily governance activity
-
----
-
-## Proposal Origins
-
-<!-- set height*width in px, where full screen is 1920*1080 -->
-<img rounded style="width: 900px" src="./img/proposals_from_democracy.png" />
-
-> Proposals now primarily authored via democracy
-
----
-
-## Treasury Usage
-
-<img rounded style="width: 900px" src="./img/treasury_waste_since_opengov.png" />
-
-> Treasury funds used more efficiently
-
----
-
-## OpenGov and You
-
-<pba-col center>
-
-- Participate in OpenGov and Polkadot Fellowship on Polkadot and Kusama
-- Can customize OpenGov instances per parachain
-- Custom fellowships per parachain
-- Potentially create non-technical fellowships, such as a fellowship for brand ambassadors
-
-</pba-col>
-
----
-
-## Resources
-
-<pba-col center>
-
-1. [PolkaWorld Hands-On OpenGov](https://polkaworld.medium.com/a-hands-on-guide-for-kusamas-open-gov-governance-system-98277629b0c5)
-1. [OpenGov Article from Moonbeam Team](https://moonbeam.network/blog/opengov/)
-1. [Gavin’s Polkadot Decoded 2022 talk](https://www.youtube.com/watch?v=EF93ZM_P_Oc)
-1. [Gov (OpenGov and V1) tracking](https://polkadot.polkassembly.io/opengov)
-1. [OpenGov tracking](https://kusama.subsquare.io/)
-
-</pba-col>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
----
-
-## OpenGov in Action
-
-<pba-flex center>
-
-- Vote - <https://kusama.subsquare.io/referenda>
-- Delegate vote - <https://kusama.subsquare.io/referenda>
-- Submit proposal - <https://polkadot.js.org/apps/?rpc=wss%3A%2F%2Fkusama-rpc.dwellir.com#/referenda>
-
-</pba-flex>
diff --git a/content/polkadot/scaling-heterogeneous/page.md b/content/polkadot/scaling-heterogeneous/page.md
deleted file mode 100644
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+++ /dev/null
@@ -1,16 +0,0 @@
-# Blockchain Scaling - Modular and Heterogeneous
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
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diff --git a/content/polkadot/scaling-heterogeneous/slides.md b/content/polkadot/scaling-heterogeneous/slides.md
deleted file mode 100644
index 5ea69af0..00000000
--- a/content/polkadot/scaling-heterogeneous/slides.md
+++ /dev/null
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----
-title: "Blockchains Scaling 2: Modular and Heterogeneous"
-duration: 45 mins
----
-
-# Blockchain Scaling
-
-## Modular and Heterogeneous
-
----
-
-## Modularity: decoupling roles of an L1
-
-- Sequencing: ordering operations as input to STF
-  - Necessary, but always off-chain
-- Ordering state transitions
-  - Definition of a blockchain
-  - In the case of L2s: commitments to state transitions (usually state roots) of other chains stored on L1 chain
-- Executing state transitions
-  - By definition L2s move execution off-chain
-- Data Availability
-  - Decoupling DA from ordering is often referred to as "modular blockchains" (Celestia)
-
----
-
-## Taxonomy of L2s
-
-<img rounded style="width: 550px" src="./img/L2Beat.png" />
-
-Notes:
-
-- <https://l2beat.com/scaling/summary>
-
----
-
-## Taxonomy of L2s
-
-- Sidechains
-  - Inherit ordering from L1
-  - Honest majority bridge (e.g. 5-of-8 multisig)
-
----
-
-## Taxonomy of L2s
-
-- Smart Contract Rollups
-  - Inherit ordering and availability from L1
-  - "Trust-minimized" bridge:
-    - STF correctness with validity or fraud proofs
-    - Inbox: option for transactions proposed through base layer to avoid sequencer/proposer censorship
-
----
-
-## Taxonomy of L2s
-
-- Validiums
-  - Inherit ordering from L1
-  - Trust-minimized bridge
-  - Off-chain DA
-
-Notes:
-
-https://www.starknet.io/en/posts/developers/rollup-validium-volition-where-is-your-data-stored
-
----
-
-## Taxonomy of L2s
-
-- Sovereign Rollups
-  - Inherit ordering and availability from L1 (even Bitcoin lol)
-  - No trust-minimized bridge: correctness and censorship-resistance entirely off-chain
-
-Notes:
-
-- <https://celestia.org/learn/sovereign-rollups/an-introduction/>
-- <https://rollkit.dev/blog/sovereign-rollups-on-bitcoin-with-rollkit>
-
----
-
-## Settlement?
-
-- Many in the Ethereum community define rollups by their bridges
-  - Makes sense if the purpose is scaling ETH transactions
-- Rollup nodes can fork the rollup and point at different bridge
-  - L1 native tokens remain locked
-  - L2 native tokens retain value
-- Some modular consensus layers don't allow settlement: Polkadot and Celestia
-
-Notes:
-
-- <https://dba.mirror.xyz/LYUb_Y2huJhNUw_z8ltqui2d6KY8Fc3t_cnSE9rDL_o>
-
----
-
-## Data Availability
-
----
-
-## Data Availability
-
-- _Not_ data storage. Only for a limited time.
-- Two purposes:
-  - Security: to verify STF correctness in optimistic systems (one week in ORUs, ~30s in Polkadot)
-  - Liveness: for sequencers to download in order to build on top of. Must be a bit longer than STF correctness (~1 day in Polkadot, 30 days in danksharding)
-- Cannot use fraud proofs (fisherman's dilemma)
-- Simplest option is to post on L1 (Ethereum calldata)
-
----
-
-## Data Availability Committee (DAC)
-
-- Nodes each redundantly hold data
-- Can be off-chain or using committees of L1 validators
-- Post threshold signature to L1 attesting to availability
-- Coordination can be expensive for rollup users: which shard has my data?
-
----
-
-## Data Availability Sampling (DAS)
-
-- Data is erasure encoded
-- Light clients can verify availability by randomly sampling nodes
-- e.g. Celestia (standalone DA layer), Danksharding (Ethereum roadmap), Polygon Avail (built on Substrate), ZKPorter, Eigenlayer
-
-Notes:
-
-- <https://arxiv.org/abs/1809.09044>
-- <https://github.com/availproject/data-availability/blob/master/reference%20document/Data%20Availability%20-%20Reference%20Document.pdf>
-
----
-
-## How to ensure coding was done correctly?
-
-- SNARKs: too expensive
-- Fraud proofs: requires 2D encoding to be efficient
-- KZG commitments: also allows distributed reconstruction (chunking)
-
----
-
-## 2D Reed Solomon
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="width: 400px" src="./img/2dReedSolomon.png" />
-
-</pba-col>
-<pba-col>
-
-- Computes Merkle roots for rows and columns
-- Requires storing 2$\sqrt{n}$ state roots instead of one
-- Allows O($\sqrt{n}$) fraud proofs of encoding
-
-</pba-col>
-</pba-cols>
-
----
-
-## DA in Celestia
-
-- Full nodes each redundantly hold erasure coded data off-chain
-- Light clients sample 50% and participate in consensus
-- Possible incentive problem: easier to scale data than execution so standalone DA layers can more easily be undercut
-
-Notes:
-
-- <https://docs.celestia.org/learn/how-celestia-works/data-availability-layer>
-
----
-
-## DA in Danksharding
-
-- 2D erasure coded using KZG polynomial commitments
-  - Also provide proof of encoding
-  - KZG requires trusted setup, ceremony done earlier this year
-- Distributed construction: no nodes need build all rows and columns
-- Distributed reconstruction:
-  - Chunking and sharding similar to Polkadot
-  - Higher threshold due to 2D encoding
-- Allows light client consensus through sampling
-- Data removed after 30 days
-
-Notes:
-
-- <https://notes.ethereum.org/@vbuterin/proto_danksharding_faq>
-- <https://dankradfeist.de/ethereum/2020/06/16/kate-polynomial-commitments.html>
-- <https://www.youtube.com/watch?v=4L30t_6JBAg>
-
----
-
-## Rollup Security
-
----
-
-## Validity Proofs for Scaling
-
-- Recursive proofs for constant space blockchains (Mina)
-- zk-rollups
-  - Transactional (private or public): e.g. Aztec
-  - Application-specific: e.g. STARKDex, Loopring
-  - Smart contract: e.g. ZEXE (Aleo), zkEVM (Polygon, ZKSync, Scroll)
-
-Notes:
-
-- <https://medium.com/hackernoon/scaling-tezo-8de241dd91bd>
-- <https://eprint.iacr.org/2020/352.pdf>
-- <https://github.com/barryWhiteHat/roll_up>
-- <https://zkhack.dev/whiteboard/>
-
----
-
-## Optimistic Rollups: Fraud Proofs
-
-“Don’t go to court to cash a check — just go if the check bounces.”
-
-- Proposers post a state root to L1 with deposit
-- Challengers can submit fraud proofs within period (typically 7 days)
-  - If successful, rewarded portion of deposit
-- Fraud proofs can be interactive (Arbitrum) or non-interactive (Optimism)
-
-Notes:
-
-- <https://www.usenix.org/system/files/conference/usenixsecurity18/sec18-kalodner.pdf>
-
----
-
-## Rollup Training Wheels
-
-<div style="font-size: 0.82em;">
-
-- Stage 0
-  - On-chain DA
-  - Must have inbox
-  - No STF correctness
-- Stage 1
-  - STF correctness (fraud or validity proof)
-  - 6-of-8 multisig can override SC security
-  - SC upgrades with either same multisig threshold or same delay as challenge period
-- Stage 2
-  - Security override only in case of bugs (discrepancy between two prover implementations)
-  - Upgrades must have delay greater than 30 days
-
-</div>
-
-Notes:
-
-- <https://ethereum-magicians.org/t/proposed-milestones-for-rollups-taking-off-training-wheels/11571>
-
----
-
-## Rollup Sequencers
-
-- Currently centralized (unlike Polkadot collators)
-- Shared sequencing: e.g. Espresso, OP Superchain
-- Proposer-builder separation
-
-Notes:
-
-- <https://docs.espressosys.com/sequencer/espresso-sequencer-architecture/readme>
-- <https://stack.optimism.io/docs/understand/explainer/>
-- <https://ethereum.org/nl/roadmap/pbs/>
-
----
-
-## Optimistic Rollups: Permissionless?
-
-- Spam state roots stall the chain
-  - Arbitrum allows multiple to be posted (fork and prune) similar to Nakamoto consensus
-- Spam challenges can delay confirmation
-  - They typically must be executed separately and sequentially to prevent collusion
-  - Arbitrum BOLD allows challenges to be executed together, bounds time at 7 days
-- Spam necessitates permissioned proposer/verifier sets
-
-Notes:
-
-- <https://github.com/OffchainLabs/bold/blob/main/docs/research-specs/BOLDChallengeProtocol.pdf>
-- <https://medium.com/offchainlabs/solutions-to-delay-attacks-on-rollups-434f9d05a07a>
-
----
-
-## Optimistic Rollups: Verifier’s Dilemma
-
-- Challenge reward isn't enough to incentivize verifying all state roots
-  - Proposers don't face gambler's ruin on L1
-  - Verifiers aren't rewarded for executing valid state transitions
-- Attention challenges
-
-Notes:
-
-- <https://medium.com/offchainlabs/the-cheater-checking-problem-why-the-verifiers-dilemma-is-harder-than-you-think-9c7156505ca1>
-- <https://medium.com/offchainlabs/cheater-checking-how-attention-challenges-solve-the-verifiers-dilemma-681a92d9948e>
-
----
-
-## Rollup Security Assumptions
-
-- ORUs are only as secure as their verifiers
-  - Typically centralized or small permissioned set
-  - Don't have similar incentives to L1 validation
-  - Reputational damage argument
-- Bridging is slow
-  - LPs can provide exit liquidity for small transactions...
-  - ...but then a small number of whales are checking all rollups
-
----
-
-## How Does Polkadot Compare to Other Rollup Protocols?
-
-<img rounded style="width: 700px" src="./img/polkadot-rollup.png" />
-
-- Approval checking is a decentralized shared watchtower network
-- The value proposition of Polkadot is making consistent security assumptions across the modular stack
diff --git a/content/polkadot/scaling-homogeneous/img/trilemma.svg b/content/polkadot/scaling-homogeneous/img/trilemma.svg
deleted file mode 120000
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-../../decisions/img/trilemma.svg
\ No newline at end of file
diff --git a/content/polkadot/scaling-homogeneous/page.md b/content/polkadot/scaling-homogeneous/page.md
deleted file mode 100644
index 2c8910ec..00000000
--- a/content/polkadot/scaling-homogeneous/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Blockchain Scaling - Monolithic and Homogeneous
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
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diff --git a/content/polkadot/scaling-homogeneous/slides.md b/content/polkadot/scaling-homogeneous/slides.md
deleted file mode 100644
index b2527ce4..00000000
--- a/content/polkadot/scaling-homogeneous/slides.md
+++ /dev/null
@@ -1,285 +0,0 @@
----
-title: "Blockchain Scaling 1: Monolithic and Homogeneous"
-duration: 45 mins
----
-
-# Blockchain Scaling
-
-## Monolithic and Homogeneous
-
----
-
-## Lesson format
-
-- Two approaches:
-  - Historically, we move from protocols that are monolithic and homogeneous to ones that are modular and heterogeneous
-  - Structurally, we can compare in terms of security assumptions and design trade-offs
-- First half covers theory, homogeneous sharding, shared security
-- Second half is rollups and beyond
-
----
-
-## What do we mean by scaling?
-
-<img rounded style="width: 700px" src="./img/VisaScale.png" />
-
-- Increasing throughput: data executed through state transitions
-- TPS:
-  - Widely stated
-  - Often gamed
-    - Individually signed user transactions (no inherents)
-    - Peak vs. sustained load
-    - sTPS used in Polkadot (no db caching)
-  - Not currently the driver of throughput needs (DeFi + NFT drops)
-
----
-
-## Horizontal vs. Vertical Scaling
-
-<img rounded style="width: 800px" src="./img/horizontal-vs-vertical-scaling-diagram.png" />
-
-- Vertical scaling: adding more resources per machine
-- Horizontal scaling: adding more machines
-
----
-
-## Scalability Trilemma
-
-<img style="width: 400px" rounded src="./img/trilemma.svg" />
-
-- Why do we care about horizontal scaling for blockchains?
-  - Lower barrier of entry -> more decentralization
-
----
-
-## Vertical scaling approaches
-
-- Adaptive responsiveness (HotStuff)
-- Mempool optimization:
-  - Pipelining: building future blocks before previous ones have been included
-  - DAG-based (Narwhal)
-  - To avoid MEV (for Polkadot: Sassafras)
-- Parallel execution
-  - UTXOs
-  - Move Language: STM with linear types
-  - For Polkadot: elastic scaling
-
-Notes:
-
-- <https://dahliamalkhi.files.wordpress.com/2018/03/hot-stuff-arxiv2018.pdf>
-- <https://arxiv.org/pdf/2305.13556.pdf>
-- <https://arxiv.org/pdf/2105.11827.pdf>
-- <https://eprint.iacr.org/2023/031.pdf>
-- <https://move-book.com/>
-
----
-
-## Restaking
-
-<img rounded style="width: 700px" src="./img/Eigenlayer.webp" />
-
-- Existing validator sets (Cosmos Hub, Ethereum with Eigenlayer) can opt-in to validating other protocols using same bond
-- Capital scaling, not throughput scaling
-- All validators must validate all protocols in order to have the same security
-
----
-
-## Restaking
-
-- Two arguments in favor (shared with Polkadot)
-  - Shared economic security against market buying tokens to attack PoS
-  - Reduces capital costs to validators, while increasing revenue sources -> security is much cheaper for client protocols
-- Appchain thesis: flexible blockspace has advantages over generalized smart contract platforms (including for throughput)
-
----
-
-## Sharding
-
----
-
-## Sharding
-
-<img rounded style="width: 700px" src="./img/committees.png" />
-
-- Term from traditional databases
-- Definition: distributing over subsets of machines (committees)
-- Execution vs. data sharding
-
-Notes:
-
-- <https://vitalik.ca/general/2021/04/07/sharding.html>
-
----
-
-## Problem Space: Byzantine Thresholds
-
-- Typically can't assume f holds within committees
-  - Unless they're statistically representative
-  - Alternatively we rely on 1-of-n assumptions
-
----
-
-## Problem Space: Adaptive Corruption
-
-- Easier to corrupt (DOS, bribe, etc.) small committees than entire validator set
-- Must be sorted with strong on-chain randomness (e.g. VRFs not PoW hashes)
-- Must be frequently rotated
-- Weaker assumption: adaptive corruption isn't immediate
-
----
-
-## Problem Space: Cross-shard Messaging
-
-- Imbalanced message queues (different with heterogeneous vs. homogeneous shards)
-- Creates a dependency when shards are rolled back -> easier when finality is tied together and fast
-- Undirected graph approach (Casper/Chainweb):
-  - Only allows messaging between adjacent shards
-  - Adjacent shards are validated together
-
----
-
-## Solutions: 1-of-n assumptions
-
-- Polkadot (eager)
-- Optimistic rollups (lazy)
-- Nightshade (Near)
-  - Optimistic homogeneous sharding
-  - Availability protocol based on Polkadot's
-
-Notes:
-
-- <https://near.org/papers/nightshade>
-
----
-
-## Solutions:
-
-## Statistically Representative Committees
-
-<img rounded style="width: 700px" src="./img/Omniledger.png" />
-
-- Statistically representative committees (Omniledger, Polkadot with multiple relay chains)
-- Very large validator sets (thousands)
-- Large (hundreds) statistically representative committees
-- Committees aren't rotated every block (weaker adaptive corruption assumption)
-- 4f trust assumption in validator set -> 2f+1 in Committees
-- Separate "beacon" chain for Sybil resistance
-
-Notes:
-
-- <https://eprint.iacr.org/2017/406.pdf>
-
----
-
-## Solutions: Validity proofs (zk-rollups)
-
-- Cryptographic proofs of execution
-- Asymmetry between proving and verifying times
-  - Proving is slow
-  - Verifying is fast and constant time
-- Proofs are succinct, can go on chain
-- Typically ZK proofs, but not necessary
-
----
-
-## State Channels, Plasma, and Beyond
-
----
-
-## State Channels
-
-<img rounded style="width: 700px" src="./img/Lightning-layers.png" />
-
-- Part of state is locked, updated off-chain between closed set of participants, then unlocked and committed to chain
-- Payment channels, e.g. Lightning network, are a special case
-- Composition between channels sharing parties
-- Can be application-specific or generalized (e.g. Counterfactual)
-
-Notes:
-
-- <https://vitalik.ca/general/2021/01/05/rollup.html>
-- <https://www.jeffcoleman.ca/state-channels/>
-- <https://lightning.network/lightning-network-paper.pdf>
-
----
-
-## State Channels
-
-- Greater liveness assumptions:
-  - The chain will accept stale state transitions as final
-  - Someone must be regularly online to submit later ones
-  - This can be outsourced to watchtower networks
-  - Typically challenge period after closing channel
-
----
-
-## State Channels
-
-- Cannot be used for all kinds of operations
-  - Sending funds to new parties outside the channel
-  - State transitions with no owner (e.g. DEX operations)
-  - Account-based systems
-
----
-
-## Plasma
-
-<img rounded style="width: 700px" src="./img/Plasma.jpg" />
-
-<div style="font-size: 0.82em;">
-
-- "Ether + Lightning"
-- Like state channels, but hashes published to L1 at regular checkpoints
-- "Map-reduce" blockchains, PoS on top of PoW Ethereum
-- Downsides:
-  - State transitions still need "owner"
-  - Still not ideal for account-based systems
-  - Mass exit problem in case of data unavailability
-
-</div>
-
-Notes:
-
-- <https://plasma.io/plasma-deprecated.pdf>
-
----
-
-## Flavors of Plasma
-
-<img rounded style="width: 700px" src="./img/plasma_world_map.png" />
-
-- Plasma MVP: UTXO-based
-- Plasma Cash: NFT-based -> only prove ownership of own coins
-- Polygon: Plasma and PoS bridges
-
-Notes:
-
-- <https://ethresear.ch/t/plasma-world-map-the-hitchhiker-s-guide-to-the-plasma/4333>
-- <https://ethresear.ch/t/plasma-cash-plasma-with-much-less-per-user-data-checking/1298>
-- <https://ethresear.ch/t/minimal-viable-plasma/426>
-
----
-
-## The Life and Death of Plasma
-
-<pba-cols>
-<pba-col>
-
-<img rounded style="width: 500px" src="./img/L2Evolution.png" />
-
-</pba-col>
-<pba-col>
-
-- 2017-2019: Plasma paper to the emergence of rollups
-  - zk-rollups
-  - Merged consensus
-  - Generalized fraud proofs
-- Plasma Group becomes Optimism
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-- <https://medium.com/dragonfly-research/the-life-and-death-of-plasma-b72c6a59c5ad>
-- <https://ethresear.ch/t/minimal-viable-merged-consensus/5617>
diff --git a/content/polkadot/shared-security/page.md b/content/polkadot/shared-security/page.md
deleted file mode 100644
index dcb57118..00000000
--- a/content/polkadot/shared-security/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# What is Shared Security?
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
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diff --git a/content/polkadot/shared-security/slides.md b/content/polkadot/shared-security/slides.md
deleted file mode 100644
index f67b9575..00000000
--- a/content/polkadot/shared-security/slides.md
+++ /dev/null
@@ -1,595 +0,0 @@
----
-title: What is Shared Security?
-description: A high level overview of Shared Security in Polkadot
-duration: 1 hour
----
-
-# What is Shared Security?
-
----
-
-## On the surface...
-
-Shared Security is an Economic Scaling Solution for Blockchains.
-
----
-
-<div class="grid grid-cols-2">
-<div>
-
-But that is just an answer that sits at the surface.
-The topic goes much deeper than that.
-
-Let’s explore…
-
-</div>
-<div>
-
-<img style="width: 500px" src="./img/iceburg.jpg" />
-
-</div>
-</div>
-
----
-
-## What is Security?
-
-Nearly every attack to a blockchain falls into one of these two buckets:
-
-- Technical Security (cryptography)
-- Economic Security (game theory + economics)
-
-We will focus on Economic Security.
-
----
-
-Economic Security is represented by the economic cost to change the canonical history of a blockchain.
-
-<img style="width: 1000px" src="./img/chain-fork.svg" />
-
-Chains with higher security are more resilient to malicious activity, like a double spend attack.
-
----
-
-## Note that a double spend is not inherently an attack!
-
-<pba-cols>
-<pba-col>
-
-It is perfectly allowed in all blockchain protocols to sign and submit two messages which conflict with one another.
-
-It is up to the blockchain to come to consensus as to which of these two transactions is canonical.
-
-</pba-col>
-<pba-col>
-
-<img style="width: 500px" src="./img/double-spend.svg" />
-
-</pba-col>
-</pba-cols>
-
----
-
-## What does an attack look like?
-
-In this example, someone is explicitly taking advantage of fragmentation in the network to try and create two different canonical chains.
-
-<img style="width: 900px" src="./img/network-attack.svg" />
-
----
-
-## What happens after the attack?
-
-Eventually, the network fragmentation will resolve, and consensus messages will allow us to prove that the malicious nodes **equivocated**.
-
-<img style="width: 900px" src="./img/network-attack-2.svg" />
-
-That is, they signed messages that validated two conflicting chains.
-
----
-
-## What is the economic cost?
-
-This will result in **slashing** the malicious nodes, which should be economically large enough to deter these kinds of malicious activities from occurring.
-
----
-
-So Economics and Security are tightly coupled in Blockchains.
-
-<img style="width: 900px" src="./img/economics-security.svg" />
-
----
-
-# The Bootstrapping Problem
-
----
-
-### What is the Bootstrapping Problem?
-
-The bootstrapping problem is the struggle that new chains face to keep their chain secure, when their token economics are not yet sufficient or stable.
-
-Arguably, the scarcest resource in blockchain is economic security - there simply is not enough to go around.
-
----
-
-<pba-cols>
-<pba-col>
-
-## New Chains Have Small Market Cap
-
-<img style="width: 500px" src="./img/small-market-cap.svg" />
-
-</pba-col>
-<pba-col>
-
-## New Chains Are More Speculative
-
-<img style="width: 500px" src="./img/speculative-graph.svg" />
-
-</pba-col>
-</pba-cols>
-
----
-
-# How do we solve this problem?
-
----
-
-# Shared Security
-
-<img style="width: 900px" src="./img/spongebob.jpg" />
-
----
-
-## Different Forms of "Shared Security" Today
-
-- Native: Native shared security is implemented at the protocol level, and is represented as a Layer 0 blockchain, working underneath Layer 1 chains.
-- Rollups: Optimistic and Zero-Knowledge Rollups use a settlement layer to provide security and finality to their transactions.
-- Re-Staking: Some protocols allow the use of already staked tokens to secure another network, usually through the creation of a derivative token.
-
-## but these different forms are not equal…
-
----
-
-# Deep Dive Into Polkadot Shared Security
-
----
-
-## Polkadot’s Shared Security
-
-<pba-cols>
-
-<pba-col>
-
-<img style="width: 500px" src="../decisions/img/parachains-transparent.png" />
-
-</pba-col>
-
-<pba-col>
-
-Polkadot is unique in that it provides all connected parachains with the same security guarantees as the Relay Chain itself.
-
-This is native to the protocol, and one of its core functionalities.
-
-</pba-col>
-
-</pba-cols>
-
----
-
-## Building Blocks of Shared Security
-
-<pba-cols>
-
-<pba-col>
-
-1. Execution Meta-Protocol
-1. Coordination / Validation
-1. Security Hub / Settlement Layer
-
-</pba-col>
-
-<pba-col>
-
-- Wasm
-- Parachains Protocol
-- Relay Chain
-
-</pba-col>
-
-</pba-cols>
-
----
-
-# Wasm
-
----
-
-## You can't overemphasize Wasm
-
-<pba-cols>
-
-<pba-col>
-
-<img style="width: 700px" src="./img/wasm-in-storage.png" />
-
-</pba-col>
-
-<pba-col>
-
-In the Polkadot ecosystem, each chain has their state transition function represented by a Wasm blob which is stored on the blockchain itself.
-
-This has many implications, which we have covered, but the key point in this context is that it is very easy to share, generic, and safe to execute.
-
-</pba-col>
-
-</pba-cols>
-
----
-
-## Game Console Analogy
-
-<pba-cols>
-
-<pba-col>
-
-<img style="width: 500px" src="./img/nintendo-console-2.png" />
-
-Basic Substrate Client
-
-</pba-col>
-
-<pba-col>
-
-<img style="width: 250px" src="./img/nintendo-game-acala.png" />
-<img style="width: 250px" src="./img/nintendo-game-astar.png" />
-<img style="width: 250px" src="./img/nintendo-game-moonbeam.png" />
-<img style="width: 250px" src="./img/nintendo-game-polkadot.png" />
-
-Wasm Runtimes
-
-</pba-col>
-
-</pba-cols>
-
----
-
-## A Polkadot Validator Node
-
-<img style="width: 1000px" src="./img/nintendo-console-extreme.png" />
-
----
-
-## In short...
-
-- As you have learned, the Polkadot Client is basically a Wasm executor.
-- All of the chains in our ecosystem use Wasm for their state transition function.
-- The Wasm meta-protocol allows Polkadot to execute any chain on the fly!
-
-> Note that we ACTUALLY EXECUTE the blocks of other chains.
->
-> Less trust, more truth!
-
----
-
-# Parachain Validation
-
----
-
-## Maximizing Scaling
-
-A scalable proof of stake system is one where:
-
-- security is as **shared** as possible
-- execution is as **sharded** as possible
-
-Notes:
-
-You should not confuse shared security with sharded security.
-
-a.k.a. cosmos is a sharded security network.
-
----
-
-## Execution Sharding
-
-Execution Sharding is the process of distributing blockchain execution responsibilities across a validator set.
-
-In Polkadot, all validators execute every relay chain block, but only a subset execute each parachain block.
-
-This enables Polkadot to scale.
-
----
-
-## How to validate a block?
-
-<img style="width: 1200px" src="./img/parachain-validation.svg" />
-
----
-
-## Submitting Parachain Blocks
-
-Parachains submit new blocks with a proof-of-validity to the network.
-
-<img style="width: 900px" src="./img/parachain-validation-multiple.svg" />
-
-Wasm Runtime and latest state root for Parachains already stored on the relay chain.
-
----
-
-Parachains Protocol has new blocks that it needs to validate and include.
-
-<img style="width: 600px" src="./img/parachain-validators.svg" />
-
-## Polkadot Validators
-
----
-
-A random subset of validators are assigned to execute the parachain blocks.
-
-<img style="width: 600px" src="./img/parachain-validators-colored.svg" />
-
-The new state root is then committed to the relay chain so the process can repeat.
-
----
-
-## How do we stop things from going wrong?
-
-- Data Availability
-  - Polkadot uses erasure encoding across the validators assigned to a parachain to make sure the data needed to validate a block stays available.
-- Approval Checking
-  - Every validator node is running approval checking processes for a random subset of parachain blocks in every relay chain block.
-    If the initially assigned approvers for a parablock "no-show", then we assume an attack and in the worst case escalate to have the entire validator set check the block.
-- Disputes Handling
-  - When someone disputes the validity of a parablock, all validators must then check the block and cast a vote.
-    The validators on the losing side of the dispute are slashed.
-
----
-
-# The Relay Chain
-
----
-
-## The Security Hub for Polkadot
-
-<pba-cols>
-
-<pba-col>
-
-<img style="width: 500px" src="../../polkadot/decisions/img/parachains-transparent.png" />
-
-</pba-col>
-
-<pba-col>
-
-The Relay Chain is the anchor for the Polkadot Network.
-
-- Provides a base economic utility token with DOT.
-- Provides a group of high quality Validators.
-- Stores essential data needed for each parachain.
-- Establishes finality for parachain blocks.
-
-</pba-col>
-
-</pba-cols>
-
----
-
-## Parachain Blocks Get Finalized
-
-<pba-cols>
-
-<pba-col>
-
-<img style="width: 500px" src="./img/parachain-finalization.svg" />
-
-</pba-col>
-
-<pba-col>
-
-Relay chain block producers commit the new state root to the relay chain once the Parachains Protocol has been completed.
-
-Thus, when a relay chain block is finalized all included parachain blocks will also be finalized!
-
-The Parachain state committed on Polkadot is the **canonical chain**.
-
-</pba-col>
-
-</pba-cols>
-
----
-
-## Trust-Free Interactions
-
-<pba-cols>
-
-<pba-col>
-
-<img style="width: 500px" src="../decisions/img/xcmp-finalization.svg" />
-
-</pba-col>
-
-<pba-col>
-
-This also means that finalization on Polkadot implies finalization of all interactions between all parachains at the same height.
-
-So, shared security not only secures the individual chains, but the interactions between chains too.
-
-</pba-col>
-
-</pba-cols>
-
----
-
-## Building Blocks of Shared Security
-
-<pba-cols>
-
-<pba-col>
-
-1. Execution Meta-Protocol
-1. Coordination / Validation
-1. Security Hub / Settlement Layer
-
-</pba-col>
-
-<pba-col>
-
-Other protocols say they are providing shared security... but do they have these key building blocks?
-
-</pba-col>
-
-</pba-cols>
-
----
-
-# Comparing Options
-
----
-
-## Re-Staking Solution
-
-<div class="grid grid-cols-3 text-small">
-
-<div>
-
-### Pros
-
-- Seems to be protocol agnostic, and can be “backported” to new and existing chains.
-- Smaller / newer chains can rely on more valuable and stable economies.
-
-</div>
-
-<div class="col-span-2">
-
-### Cons
-
-- As tokens are continually re-staked, the economic “costs” needed to attack secured chains decreases.
-- No real computational verification or protection provided by these systems.
-- Seems to ultimately fall back on centralized sources of trust.
-
-</div>
-
-</div>
-
-Notes:
-
-See the section on "Key Risks and Vulnerabilities" here:
-
-<https://consensys.net/blog/cryptoeconomic-research/eigenlayer-a-restaking-primitive/>
-
-> Generally there are two main attack vectors of EigenLayer.
-> One is that many validators collude to attack a set of middleware services simultaneously.
-> The other is that the protocols that leverage EigenLayer and are built through it may have unintended slashing vulnerabilities and there is a risk of honest nodes getting slashed.
->
-> Much of the EigenLayer mechanism relies upon a rebalancing algorithm that takes into account the different validators and their accompanying stake and security capacity and usage.
-> This underpins the success of the protocol.
-> If this rebalancing mechanism fails (e.g. slow to adjust, latency, incorrect parameters) then EigenLayer opens itself up to different attack vectors, particularly around cryptoeconomic security.
-> It essentially replicates the same vulnerabilities that it sought to solve with merge-mining.
-> So attention must be paid to ensuring that the system is accurately updating any outstanding restaked $ETH and that it remains fully collateralized.
-
----
-
-## Optimistic Rollups
-
-<div class="grid grid-cols-3 text-small">
-
-<div>
-
-### Pros
-
-- Not limited by the complexity of the on-chain VM.
-- Can be parallelized.
-- They can stuff a lot of data in their STF.
-- They can use compiled code native to modern processors.
-
-</div>
-
-<div class="col-span-2">
-
-### Cons
-
-- Concerns around centralization and censorship of sequencers.
-- Long time to finality due to challenge periods.
-  (could be days)
-- Settlement layers could be attacked, interfering with the optimistic rollup protocols.
-- Suffers from the same problems allocating blockspace as on-chain transactions.
-  - On-chain costs to perform the interactive protocol.
-  - Congestion of the network.
-
-</div>
-
-</div>
-
----
-
-## Zero-Knowledge Rollups
-
-<div class="grid grid-cols-3 text-small">
-
-<div>
-
-### Pros
-
-- Honestly, they are pretty great.
-- Proven trustlessly.
-- Minimal data availability requirements.
-- Instant Finality (at high costs).
-- Exciting future if recursive proofs work out.
-
-</div>
-
-<div class="col-span-2">
-
-### Cons
-
-- Concerns around centralization of sequencers and provers.
-- Challenging to write ZK Circuits.
-  - Turing complete, but usually computationally complex.
-  - Hard to bound complexity of circuits when building apps.
-- Suffers from the same problems allocating blockspace as on-chain transactions.
-  - On-chain costs to submit and execute proofs on settlement layer.
-  - Congestion of the network.
-
-</div>
-
-</div>
-
----
-
-## Polkadot Native Shared Security
-
-<div class="grid grid-cols-2 text-small">
-
-<div>
-
-### Pros
-
-- Protocol level handling of sharding, shared security, and interoperability.
-- Easy to develop STF: Anything that compiles to Wasm.
-- Probably the best time to finality, usually under a minute.
-- Data availability provided by the existing validators.
-- Much less concern of centralization from collators vs sequencers and provers.
-
-</div>
-
-<div>
-
-### Cons
-
-- Certain limitations enforced to keep parachains compatible with the parachains protocol.
-  - Wasm STF
-  - No Custom Host Function
-  - Constrained Execution Environment
-- Wasm is unfortunately still 2x slower than native compilation.
-- Requires lot of data being provided and available in PoV.
-
-</div>
-
-</div>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/xcmp/page.md b/content/polkadot/xcmp/page.md
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-# Cross-Chain Message Passing (XCMP)
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
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diff --git a/content/polkadot/xcmp/slides.md b/content/polkadot/xcmp/slides.md
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----
-title: Cross-Chain Message Passing (XCMP)
-description: Introduction to Cross-Chain Message Passing in Polkadot
-duration: 45 minutes
----
-
-# XCMP: Cross Chain Message Passing
-
----
-
-Previous lectures discussed how Polkadot provides a secure environment for general code execution, and how it scales.
-
----
-
-This lecture is about how processes communicate within that environment.
-
----
-
-<img rounded width="1200px" src="./img/large_environment.svg" />
-
----
-
-<img rounded width="1200px" src="./img/small_environment.svg" />
-
----
-
-<img rounded width="1200px" src="./img/small_environment_movement.svg" />
-
----
-
-<img rounded width="1200px" src="./img/large_environment_movement.svg" />
-
----
-
-The Relay Chain Runtime maintains messaging queues for parachains.
-
-It acts as a bridge for parachains to each other and to itself.
-
----
-
-To do this, it adds additional limitations to candidates to ensure messaging rules are respected.
-
----
-
-## XCMP in Practice
-
----
-
-## XCMP vs XCM
-
-XCMP is the data layer, while XCM is the language.
-
-XCMP only focuses on the transmission of raw bytes between chains.<br />
-In this lesson we will focus only on XCMP.
-
-<img rounded width="400px" src="./img/people-talking.jpg" />
-
-Notes:
-
-Communication requires a medium and a language to convey semantic meaning.
-XCMP is the medium, like sound or writing, rather than the language.
-
----
-
-<img rounded width="1300px" src="./img/messaging-kinds.svg" />
-
----
-
-Downward and Upward channels are implicitly available.
-
-XCMP Channels must be explicitly opened.
-
----
-
-XCMP Channels are one-way, and for two-way communication two channels must be opened.
-
----
-
-## Using Messaging in Practice
-
-This lesson is meant to communicate the underlying protocols and mechanics by which messages are sent and received.
-
-In practice, these mechanisms are abstracted by the libraries you work with.
-
----
-
-## Revisiting PVFs and Outputs
-
-<img rounded width="800px" src="./img/PVF.svg" />
-
-```rust
-fn validate_block(ValidationParams) -> Result<ValidationResult, ValidationFailed>;
-```
-
----
-
-## Validation Inputs
-
-```rust
-/// Parameters provided to a PVF for validation
-pub struct ValidationParams {
-	/// The parent parachain block's Head Data
-	pub parent_head: HeadData,
-	/// The Proof-of-Validity.
-	pub pov: PoV,
-	/// The current relay-chain block number.
-	pub relay_parent_number: RelayChainBlockNumber,
-	/// The relay-chain block's storage root.
-	pub relay_parent_storage_root: Hash,
-}
-```
-
-Here, note that the `relay_parent_storage_root` allows us to handle **Merkle Proofs** of the Relay Chain state within the parachain.
-
----
-
-## Validation Outputs
-
-```rust
-/// Outputs of _successful_ validation of a parachain block.
-pub struct ValidationResult {
-	/// The head-data produced as a result of execution.
-	pub head_data: HeadData,
-	/// Upward messages sent by the Parachain.
-	pub upward_messages: Vec<UpwardMessage>,
-	/// Outbound horizontal messages sent by the parachain.
-	pub horizontal_messages: Vec<OutboundHrmpMessage>,
-	/// Number of downward messages that were processed by the Parachain.
-	///
-	/// It is expected that the Parachain processes them from first to last.
-	pub processed_downward_messages: u32,
-	/// The mark which specifies the block number up to which all inbound HRMP messages are processed.
-	pub hrmp_watermark: RelayChainBlockNumber,
-
-	// ... more fields
-}
-```
-
----
-
-The `ValidationResult` is the output of successful PVF execution.
-
-Validators are responsible for checking that the outputs are correct.
-
----
-
-## Unpacking Candidates
-
----
-
-Candidates are posted to the relay chain in their entirety - everything except for the PoV.
-
----
-
-## Candidate Breakdown
-
-<pba-flex center>
-
-1. Descriptor: defines inputs to the validation function
-1. Commitments: expected outputs from the validation function
-
-</pba-flex>
-
----
-
-```rust
-pub struct CandidateDescriptor {
-  /// Relay chain block hash
-  pub relay_parent: RelayChainBlockHash,
-  /// The hash of the PoV
-  pub pov_hash: Hash,
-  /// Parent head data hash.
-  pub parent_hash: Hash,
-  /// The unique ID of the parachain.
-  pub para_id: ParaId,
-
-  // .. a few more fields
-}
-```
-
----
-
-```rust
-pub struct CandidateCommitments {
-  /// Messages destined to be interpreted by the Relay chain itself.
-  pub upward_messages: UpwardMessages,
-  /// Horizontal messages sent by the parachain.
-  pub horizontal_messages: HorizontalMessages,
-  /// The head-data produced as a result of execution.
-  pub head_data: HeadData,
-  /// The number of messages processed from the DMQ.
-  pub processed_downward_messages: u32,
-  /// The mark which specifies the block number up to which all inbound HRMP messages are processed.
-  pub hrmp_watermark: RelayChainBlockNumber,
-}
-```
-
----
-
-Notice the similarities to `ValidationOutputs`?
-
----
-
-<img rounded style="width: 1000px" src="../../polkadot/execution-sharding/img/block_contents.svg" />
-
----
-
-(Polkadot runtime, simplified)
-
-```rust
-// Relay chain drains, parachain posts
-UpwardMessages: StorageMap<ParaId, Deque<Message>>;
-
-// Relay chain posts, parachain drains
-DownwardMessages: StorageMap<ParaId, Deque<Message>>;
-
-// (sender, receiver)
-// Sender posts, receiver drains
-HrmpChannels: StorageMap<(ParaId, ParaId), Deque<Message>>;
-```
-
----
-
-(in Polkadot runtime, simplified, inclusion pallet)
-
-```rust
-fn process_backed_candidate(CandidateDescriptor, CandidateCommitments) {
-  let para_id = descriptor.para_id;
-
-  assert!(is_scheduled_on_empty_core(para_id));
-  assert!(descriptor.parent_hash == current_parachain_head);
-  assert!(is_in_this_chain_recently(descriptor.relay_parent));
-
-  // fails if too many
-  assert!(check_upward(para_id, commitments.upward_messages).is_ok());
-
-  // fails if too many or sending to a chain without a channel open.
-  assert!(check_hrmp_out(para_id, commitments.hrmp_messages).is_ok());
-
-  // fails if attempting to process more messages than exist.
-  assert!(check_downward(para_id, commitments.processed_downward_messages).is_ok());
-
-  // fails if the watermark is lower than the previous one.
-  // updates all channels where this is a _receiver_.
-  assert!(check_hrmp_in(para_id, commitments.hrmp_watermark).is_ok());
-}
-```
-
----
-
-Candidates can't be _backed_ unless they pass all these checks.
-
-The relay chain block author is responsible for selecting candidates which pass these checks.
-
----
-
-Messages are not added to queues until the candidate is included (available).
-
-This allows messages to be passed and acted upon before finality.
-
----
-
-If the candidate turns out to be bad, the whole relay chain is forked to a point before messages were queued or acted upon.
-
----
-
-## Parachain Host Configuration
-
-```rust
-pub struct HostConfiguration {
-  // ... many many fields
-}
-
-// In Polkadot runtime storage:
-CurrentConfiguration: StorageValue<HostConfiguration>;
-```
-
-These variables are updated by governance.
-
----
-
-The host configuration specifies things like:
-
-- How many messages can be in the upward, downward, or HRMP queues for a parachain
-- How many bytes can be in the upward, downward, or HRMP queues for a parachain
-- How large a single message can be in the upward, downward, or HRMP queues.
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-## What are messages?
-
----
-
-Messages are just `Vec<u8>` byte strings.
-
----
-
-The Relay Chain interprets upward messages as XCM.
-
-The main takeaway for now is that it allows parachains to execute `Call`s on the Relay Chain.
-
----
-
-```rust
-// Act as a regular account with a deterministic ID based
-// on the Para ID.
-Origin::Signed(AccountId),
-// Act as the parachain itself, for calls which may be made by parachains.
-// Custom origin type added to the Relay Chain.
-Origin::Parachain(ParaId),
-```
-
-Notes:
-
-When parachains execute `Call`s on the Relay Chain, they have access to two origin kinds.
-
-Note that this is only the case for the Relay Chain and parachains messages may be interpreted differently on other chains.
-
----
-
-Parachains are free to interpret their incoming downward or HRMP messages however they like.
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-## Respecting Limits
-
----
-
-Problem: Parachain candidates can't be backed unless they respect the constraints on sending & receiving messages. How do they ensure this?
-
----
-
-Solution: PVFs can _read relay chain state_ to find out these limits. They include these proofs in the PoV.
-
----
-
-```rust
-/// Parameters provided to a PVF for validation
-pub struct ValidationParams {
-	/// The relay-chain block's storage root.
-	pub relay_parent_storage_root: Hash,
-	pub pov: PoV,
-
-	// ...
-}
-```
-
----
-
-```rust
-fn validate_block(ValidationParams) -> Result<ValidationResult, ValidationFailed> {
-  // simplified
-  let storage_proof = extract_storage_proof(pov);
-
-  // state of queues, and subset of `HostConfiguration`.
-  let (message_queues, current_config) = check_storage_proof(
-    relay_parent_storage_proof,
-    storage_proof,
-  )?;
-
-  // process incoming messages and send outgoing while respecting limits in config.
-}
-```
-
----
-
-<!-- .slide: data-background-color="#000" -->
-
-## Opening Channels
-
----
-
-The protocol for opening an HRMP channel is as follows:
-
-<pba-flex center>
-
-1. Chain A sends an upward message requesting a channel to Chain B
-1. Chain B receives a downward message notifying of the channel request
-1. Chain B sends an upward message accepting or rejecting the channel
-1. The channel is either opened or rejected in the Relay Chain as a result
-
-</pba-flex>
-
----
-
-There are no fees for XCMP messages, but every channel comes with a `max_capacity` and `max_message_size`.
-
-Each channel comes with a corresponding _deposit_ of DOT tokens to pay for the relay chain state utilization.
-
-This deposit is returned when the channel is closed.
-
----
-
-<img rounded width="1000px" src="./img/hrmp-channel.svg" />
-
----
-
-## Message Queue Chains (MQC)
-
-Let's take a small detour into a data structure used in DMP and XCMP.
-
-**Problem**: Parachains should be able to cheaply determine the state of the entire message queue.
-
-**Problem**: Relay Chain state proofs are expensive and should be minimized.
-
-Solution: Message Queue Chains (MQC)
-
----
-
-## MQC Architecture
-
-<img rounded width="700px" src="./img/mqc.svg" />
-
----
-
-With MQCs, learning about all incoming messages for a single queue requires only one storage proof and one MQC entry (70 bytes) per incoming message.
-
----
-
-## UMP Configuration
-
-```rust
-pub struct HostConfiguration {
-	/// Total number of individual messages allowed in the
-	/// parachain -> relay-chain message queue.
-	pub max_upward_queue_count: u32,
-	/// Total size of messages allowed in the
-	/// parachain -> relay-chain message queue.
-	pub max_upward_queue_size: u32,
-	/// The maximum size of an upward message that can be sent by a candidate.
-	///
-	/// This parameter affects the size upper bound of the `CandidateCommitments`.
-	pub max_upward_message_size: u32,
-	/// The maximum number of messages that a candidate can contain.
-	///
-	/// This parameter affects the size upper bound of the `CandidateCommitments`.
-	pub max_upward_message_num_per_candidate: u32,
-	// ... more fields
-}
-```
-
----
-
-## Validation Outputs for UMP
-
-```rust
-/// Outputs of _successful_ validation of a parachain block.
-pub struct ValidationResult {
-	/// Upward messages sent by the Parachain.
-	pub upward_messages: Vec<UpwardMessage>,
-	// ... more fields
-}
-```
-
----
-
-## DMP Configuration
-
-```rust
-pub struct HostConfiguration {
-	/// The maximum size of a message that can be put in a downward message queue.
-	pub max_downward_message_size: u32,
-}
-```
-
----
-
-## Validation Outputs for DMP
-
-```rust
-/// Outputs of _successful_ validation of a parachain block.
-pub struct ValidationResult {
-	/// Number of downward messages that were processed by the Parachain.
-	///
-	/// It is expected that the Parachain processes them from first to last.
-	pub processed_downward_messages: u32,
-	// ... more fields
-}
-```
-
-Notes:
-
-Parachains can "process" messages simply by ignoring them.
-The Relay Chain doesn't care what parachains do with the messages.
-They can just be thrown out.
-
----
-
-## Validation Outputs for HRMP
-
-```rust
-/// Outputs of _successful_ validation of a parachain block.
-pub struct ValidationResult {
-	/// Outbound horizontal messages sent by the parachain.
-	pub horizontal_messages: Vec<OutboundHrmpMessage>,
-	/// The mark which specifies the block number up
-	/// to which all inbound HRMP messages are processed.
-	pub hrmp_watermark: RelayChainBlockNumber,
-
-	// ... more fields
-}
-
-pub struct OutboundHrmpMessage {
-	/// The para that will get this message in its downward message queue.
-	pub recipient: ParaId,
-	/// The message payload.
-	pub data: sp_std::vec::Vec<u8>,
-}
-```
-
----
-
-## HRMP Configuration
-
-```rust
-pub struct HostConfiguration {
-	pub hrmp_max_parachain_outbound_channels: u32,
-
-	pub hrmp_sender_deposit: Balance,
-	pub hrmp_recipient_deposit: Balance,
-
-	pub hrmp_channel_max_capacity: u32,
-	pub hrmp_channel_max_total_size: u32,
-
-	pub hrmp_max_parachain_inbound_channels: u32,
-	pub hrmp_channel_max_message_size: u32,
-
-  // more fields...
-}
-```
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/polkadot/zombienet/page.md b/content/polkadot/zombienet/page.md
deleted file mode 100644
index 8329f2cd..00000000
--- a/content/polkadot/zombienet/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Zombienet
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/polkadot/zombienet/slides.md b/content/polkadot/zombienet/slides.md
deleted file mode 100644
index dcc7bde6..00000000
--- a/content/polkadot/zombienet/slides.md
+++ /dev/null
@@ -1,695 +0,0 @@
----
-title: Zombienet
-description: Zombienet workshop
-duration: 1 hour
----
-
-<style>
-    .colored {
-        color: var(--r-link-color);
-    }
-
-    .colored-green {
-        color: #18ffb2;
-    }
-
-    .colored-light-green {
-        color: #c2ff33;
-    }
-</style>
-
-# Zombienet
-
----
-
-## What is Zombienet?
-
-Zombienet is an <span class="colored">integration testing tool</span> that allows users to _<span class="colored">spawn</span>_ and _<span class="colored">test</span>_ ephemeral substrate based networks.
-
----
-
-## Why Zombienet?
-
-Integration tests are always <span class="colored">complex</span>:
-
-<br />
-
-- Setup Configuration
-
-<!-- .element: class="fragment" -->
-
-- Port management
-
-<!-- .element: class="fragment" -->
-
-- Ready state off all artifacts
-
-<!-- .element: class="fragment" -->
-
-- Observability
-
-<!-- .element: class="fragment" -->
-
-- Leaking resources
-
-<!-- .element: class="fragment" -->
-
----v
-
-## Friction to resolve
-
-<br />
-
-- Config flexibility
-- Local environment
-- Maintenance
-- CI friendly
-- Scaling
-- Test-runner
-
----v
-
-## Goals
-
-<br />
-
-<pba-cols style="align-items:normal">
-    <pba-col>
-
-##### Hassle free setup
-
-- Toml / json
-- Nice defaults
-- Templating lang.
-
-</pba-col>
-<pba-col>
-
-##### Multiple envs
-
-- **Local**
-- **k8s**
-- **podman**
-
-</pba-col>
-<pba-col>
-
-##### Extensible
-
-- Custom assertions
-- Intuitive <span class="colored">D.S.L</span>
-- Templating lang.
-
-  </pba-col>
-  </pba-cols>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Phases
-
----
-
-## Phases
-
-<pba-cols style="align-items:normal">
-<pba-col>
-
-Spawn
-
-- Custom chain-specs
-- Custom command
-- Port-mapping
-- Parachains registration
-
-</pba-col>
-<!-- .element: class="fragment" -->
-<pba-col>
-
-Test
-
-- Custom <span class="colored">D.S.L</span>
-- Multiple assertions
-- Extensible
-- Custom reporting
-
-</pba-col>
-<!-- .element: class="fragment" -->
-</pba-cols>
-
----
-
-## Zombienet Options
-
-<pba-flex center>
-
-- As binary ([releases](https://github.com/paritytech/zombienet/releases))
-- As library (@zombienet)
-- As container (published in docker hub)
-- From source ([zombienet](https://github.com/paritytech/zombienet) repo)
-
-</pba-flex>
-
-Notes:
-
-- As binary: Binaries for Linux and MacOS are available in each release in Github.
-- npm packages: cli, orchestrator, utils
-- image: docker.io/paritytech/zombienet
-  code is available in GitHub with the instructions on how to build and run Zombienet.
-  (https://github.com/paritytech/zombienet)
-
----v
-
-### Download Zombienet
-
-```sh
-# macOS
-curl -L https://github.com/paritytech/zombienet/releases/download/v1.3.63/zombienet-macos
--o ./zombienet
-
-# linux
-curl -L https://github.com/paritytech/zombienet/releases/download/v1.3.63/zombienet-linux
--o ./zombienet
-
-# make executable
-chmod +x zombienet
-```
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Let’s spawn a new network!
-
----v
-
-## But first, try manually…
-
-<br />
-<div>
-<ul><li>Create chain-spec (parachain)</li></ul>
-
-```sh
-parachain-template-node build-spec --chain local \
---disable-default-bootnode > /tmp/para.json
-```
-
-</div>
-<!-- .element: class="fragment" -->
-<br />
-<div>
-<ul><li>Create chain-spec (relay chain)</li></ul>
-
-```sh
-polkadot build-spec --chain rococo-local \
- --disable-default-bootnode > /tmp/relay.json
-```
-
-</div>
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Tutorials <https://docs.substrate.io/tutorials/build-a-parachain/>
-
----v
-
-### Add keys\*
-
-<br />
-
-When not using --alice or --bob, you need to provide additional `aura` and `grandpa` keys and inject them into the keystore! (**per node**)
-
-```sh
-./target/release/polkadot \
-key insert --base-path /tmp/node01 \
-  --chain /tmp/relay.json \
-  --scheme Sr25519 \
-  --suri <your-secret-seed> \
-  --password-interactive \
-  --key-type aura
-```
-
-<br />
-
-```sh
-./target/release/polkadot key insert \
-  --base-path /tmp/node01 \
-  --chain /tmp/relay.json \
-  --scheme Ed25519 \
-  --suri <your-secret-key> \
-  --password-interactive \
-  --key-type gran
-```
-
-Notes:
-
-This step is optional if you use the dev accounts (e.g. alice, bob, charlie, dave, etc)
-
----v
-
-- Start relay chain nodes
-
-```sh[1-2|4-10|12-18]
-# create nodes dirs
-  mkdir -p /tmp/relay/{alice,bob}
-
-  ./target/release/polkadot \
-  --alice \
-  --validator \
-  --base-path /tmp/relay/alice \
-  --chain /tmp/relay.json \
-  --port 30333 \
-  --ws-port 9944
-
-  ./target/release/polkadot \
-  --bob \
-  --validator \
-  --base-path /tmp/relay/bob \
-  --chain /tmp/relay.json \
-  --port 30334 \
-  --ws-port 9945
-```
-
-Notes:
-
-Why do we need to use different ports for Alice and Bob?
-
----v
-
-- Start collator
-
-```sh
-# create nodes dirs
-mkdir -p /tmp/para/alice
-
-parachain-template-node \
---alice \
---collator \
---force-authoring \
---chain /tmp/para.json \
---base-path /tmp/para/alice \
---port 40333 \
---ws-port 8844 \
--- \
---execution wasm \
---chain /tmp/relay.json \
---port 30343 \
---ws-port 9977
-```
-
----v
-
-- Register ParaId on relay chain
-
-1. Modify parachain chain-spec and create raw format
-1. Generate genesis wasm and state
-1. Register parachain using sudo call
-
-<br />
-
-```sh[1,2|4,5|7,8]
-parachain-template-node build-spec --chain /tmp/para-raw.json \
---disable-default-bootnode --raw > /tmp/para-raw.json
-
-parachain-template-node export-genesis-wasm --chain /tmp/para-raw.json \
-para-2000-wasm
-
-parachain-template-node export-genesis-state --chain /tmp/para-raw.json \
-para-2000-genesis-state
-```
-
----
-
-<!-- .slide: data-background-color="#4A2439" data-visibility="hidden" -->
-
-# Activity
-
-Follow the [connect a local parachain](https://docs.substrate.io/tutorials/build-a-parachain/connect-a-local-parachain/) to launch your own network.
-
----
-
-## Non-trivial chore
-
-<pba-cols style="align-items:normal">
-<pba-col>
-
-- Error prone.
-- Multiple commands.
-- Port management.
-- Multiple process.
-
-</pba-col>
-<pba-col>
-
-<div class="fragment center" style="font-size:150%;">Zombienet allow you to set everything in <span style="color: var(--r-link-color);font-weight:bold;">just</span> 1 file.</div>
-
-</pba-col>
-</pba-cols>
-
----v
-
-## Zombienet network definition
-
-Zombienet allow to [define your network](https://paritytech.github.io/zombienet/network-definition-spec.html) with a simple configuration file.
-
-Notes:
-
-<https://paritytech.github.io/zombienet/network-definition-spec.html>
-
----v
-
-```toml[1|3-12|14-21]
-# examples/0001-small-network.toml
-
-[relaychain]
-default_image = "docker.io/parity/polkadot:latest"
-default_command = "polkadot"
-chain = "rococo-local"
-
-  [[relaychain.nodes]]
-  name = "sub"
-
-  [[relaychain.nodes]]
-  name = "zero"
-
-[[parachains]]
-id = 1001
-cumulus_based = true
-
-  [parachains.collator]
-  name = "collator01"
-  image = "docker.io/parity/polkadot-parachain:latest"
-  command = "polkadot-parachain"
-```
-
-Notes:
-
-<https://github.com/pepoviola/zombienet-presentation-examples/blob/main/examples/0001-small-network.toml>
-
----v
-
-### Spawn the network
-
-```sh
-./zombienet spawn examples/0001-small-network.toml
-```
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Activity
-
-Try to launch a network with `2` parachains.
-
-<br />
-
-<https://paritytech.github.io/zombienet/>
-
----
-
-## Make the network config dynamic
-
-The network definition supports using [nunjucks](https://mozilla.github.io/nunjucks/) templating language (similar to [tera](https://github.com/Keats/tera)).
-Where <span class="colored-green">{{variables}}</span> are replaced with <span class="colored-green">env vars</span> and you can use all the built-in features.
-
-<br />
-
-```toml[2]
-[relaychain]
-default_image = "{{ZOMBIENET_INTEGRATION_IMG}}"
-default_command = "polkadot"
-```
-
----v
-
-## Make the network config dynamic
-
-<img rounded style="width: 1200px" src="./img/zombienet-env-vars.png" />
-
----
-
-## Providers
-
-Zombienet <span class="colored">providers</span> allow to <span class="colored-green">spawn and test</span> networks with in different environments.
-
----v
-
-<pba-cols style="align-items:normal">
-
-<pba-col>
-
-<span class="colored">Kubernetes</span>
-<br />
-
-- Used internally, integrated with the [Grafana](https://grafana.com/oss/grafana/) stack.
-- You need to provide your infra stack.
-
-</pba-col>
-
-<pba-col>
-
-<span class="colored">Podman</span>
-<br />
-
-- Automatically spawn and wire an instance of [Grafana](https://grafana.com/oss/grafana/) stack.
-- Attach a jaeger instance if enabled in the network definition.
-
-</pba-col>
-
-<pba-col>
-
-<span class="colored">Native</span>
-<br />
-
-- Allow to attach to a running [Grafana](https://grafana.com/oss/grafana/) stack.
-  **(wip)**
-
-</pba-col>
-
-</pba-cols>
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
----
-
-## Meet the Test-runner
-
-Zombienet’s built-in <span class="colored">test-runner</span> allows users to use a simple <span class="colored-green">D.S.L.</span> to easily and intuitively write tests with a set of natural language expressions to make assertions.
-
----v
-
-### Built-in assertions
-
-<br />
-
-- <span class="colored">Prometheus</span>: Query the exposed metrics/histograms and assert on their values.
-
-- <span class="colored">Chain</span>: Query/subscribe chain's storage/events.
-
-- <span class="colored">Custom scripts</span>: Run custom js scripts or bash scripts (inside the pod).
-
-- <span class="colored">Node's logs</span>: Match regex/glob patterns in the node's logs.
-
-- <span class="colored">Integrations</span>: Zombienet supports multiple integrations, like jaeger spans, polkadot introspector and the backchannel.
-
----v
-
-```[1-3|6|7|14-16|18-20|22-24|26-28]
-Description: Small Network Paras
-Network: ./0002-small-network-paras.toml
-Creds: config # Only used with k8s
-
-# well known functions
-validator: is up # check all the validators in the group
-validator-0: parachain 1000 is registered within 225 seconds
-validator-0: parachain 1001 is registered within 225 seconds
-
-# ensure parachains are producing blocks
-validator-0: parachain 1000 block height is at least 5 within 300 seconds
-validator-0: parachain 1001 block height is at least 5 within 300 seconds
-
-# metrics
-validator-0: reports node_roles is 4
-validator-0: reports block height is at least 2 within 15 seconds
-
-# logs (patterns are transformed to regex)
-validator-1: log line matches glob "*rted #1*" within 10 seconds
-validator-1: log line matches "Imported #[0-9]+" within 10 seconds
-
-# system events (patterns are transformed to regex)
-validator-2: system event contains "A candidate was included" within 10 seconds
-validator-2: system event matches glob "*was backed*" within 10 seconds
-
-# custom scripts
-validator-0: js-script ./custom.js with "alice" within 200 seconds
-validator-0: run ./custom.sh within 200 seconds
-```
-
-Notes:
-
-First three lines are the header
-
-Each line represents an assertion
-
-Each assertion is executed sequentially
-
-Assertions on a group check each node
-
-within keyword allows to keep-trying until time expires
-
----
-
-## DSL extension
-
-Learning a new DSL can be tedious, but if you are using vscode we develop an [extension](https://github.com/paritytech/zombienet-vscode-extension) that can help you to write test easily.
-
-Notes:
-
-Show the extension link
-<https://github.com/paritytech/zombienet-vscode-extension>
-
----
-
-# Demo time
-
-```sh
-./zombienet -p native test examples/0002-small-network-paras.zndsl
-```
-
----
-
-# Extensibility
-
-<span class="colored">Zombienet</span> allow users to use the custom-js assertion to extend and run custom tests.
-
----v
-
-## Custom-js
-
-```sh
-# custom scripts
-validator-0: js-script ./custom.js with "alice" within 200 seconds
-```
-
-```js
-async function run(nodeName, networkInfo, args) {
-  const { wsUri, userDefinedTypes } = networkInfo.nodesByName[nodeName];
-  const api = await zombie.connect(wsUri, userDefinedTypes);
-  const validator = await api.query.session.validators();
-  return validator.length;
-}
-
-module.exports = { run };
-```
-
-Notes:
-
-Zombienet will load your script and call the run function.
-
-Passing the node name, network info and an array of arguments from the assertion
-
-Your function have access to the zombie object exposing utilities like connect, ApiPromise, Keyring, etc \*
-
-The assertions can validate the return value or the completions of your script.
-
-\*similar to the way that scripts are written in PolkadotJS apps - developer page (https://polkadot.js.org/apps/?rpc=wss%3A%2F%2Frpc.polkadot.io#/js)
-
----
-
-## More extensibility
-
-<span class="colored">Zombienet</span> also allow users to use as a library to create their own interactions with the running network.
-
----v
-
-### As a Library
-
-- <span class="colored">@zombienet/orchestrator</span> module expose the start function as entrypoint.
-
-- Returning a [network](https://github.com/paritytech/zombienet/blob/main/javascript/packages/orchestrator/src/network.ts#L77) instance, with all the information about the running topology.
-
-- You can also use the [test](https://github.com/paritytech/zombienet/blob/main/javascript/packages/orchestrator/src/orchestrator.ts#L853) function passing a callback to run your test.
-
-- <span class="colored">@zombienet/utils</span> module expose misc utils functions like _readNetworkConfig_.
-
----v
-
-```js[1|2|6-7|10-12|14|]
-import {start} from "@zombienet/orchestrator";
-import { readNetworkConfig } from "@zombienet/utils";
-
-const ZOMBIENET_CREDENTIALS = "";
-
-// can be toml or json
-const launchConfig = readNetworkConfig("../examples/0001-small-network.toml");
-
-( async () => {
-    const network = await start(ZOMBIENET_CREDENTIALS, launchConfig, {
-        spawnConcurrency: 5,
-    });
-
-    // write your own test, `network` will have all the network info
-})();
-```
-
----
-
-## The road ahead...
-
-🚧 🚧 <span class="colored"><b>Zombienet v2</b> (a.k.a [SDK](https://github.com/paritytech/zombienet-sdk))</span> is currently under construction 🚧 🚧
-
-The [SDK](https://github.com/paritytech/zombienet-sdk) will provide a set of building blocks that users can combine to spawn and interact with the network and also a fluent API for crafting different topologies and assertions for the running network.
-
-Notes:
-
-SDK repo: https://github.com/paritytech/zombienet-sdk
-
----
-
-## Acknowledgement & Contributions
-
-<span class="colored"><b>Zombienet</b></span> take inspiration and some patterns from <span class="colored-light-green">polkadot-launch</span> and <span class="colored-light-green">SimNet</span>.
-
-We encourage everyone to test it, provide feedback, ask question and contribute.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
----
-
-## Activity
-
-- Launch a network with two validators and one parachain.
-
-- Add a test to ensure:
-  - block producing
-  - peers number
-  - node's role
-
----
-
-## Additional Resources!
-
-> Check speaker notes (click "s" 😉)
-
-Notes:
-
-Zombienet:
-
-- [repo](https://github.com/paritytech/zombienet/)
-- [docs](https://paritytech.github.io/zombienet/)
-- [v2 Roadmap](https://github.com/orgs/paritytech/projects/55/)
-- [sub0 slides](https://docs.google.com/presentation/d/1wPjbrqLg9MCfygvBYV5gDra39cSr5TXg/edit)
-- [sub0 presentation](https://www.youtube.com/watch?v=QKTZZCpdGH4)
-- [Presentation examples](https://github.com/pepoviola/zombienet-presentation-examples)
-- [Setting up a local testnet](https://hackmd.io/kSFS2ButRESeJ7hu_iKKoA)
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-# Application
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Application Security
-description: Application Security session slides
-duration: 60 min
----
-
-Security is a matter of balance, not too much, not less. Only **adequate security**.
-
-<img rounded style="height: 600px" src="./img/adequate-security.jpg" />
-
----
-
-Security is about your **residual risks**, not what you have prevented.
-
-<img rounded style="height: 600px" src="./img/residual-risk.jpg" />
-
----
-
-# Application Security
-
----
-
-## Overview
-
-<pba-flex center>
-
-1. [Securing SDLC](#securing-sdlc)
-1. [Appsec Design Principles](#appsec-design-principles)
-1. [Components of AppSec](#components-of-appsec)
-1. [Known Attack Surfaces and Vectors](#known-attack-surfaces-and-vectors)
-
-</pba-flex>
-
----
-
-# Securing SDLC
-
----
-
-## The Big Picture of AppSec
-
-<img rounded style="height: 600px" src="./img/ssdlc.png" />
-
-We will visit this picture multiple times.
-
----
-
-## Security Enforced Through Controls
-
-Controls must be:
-
-<pba-flex center>
-
-- Designed
-- Developed
-- Implemented
-- Configured
-- Operated
-- Monitored
-- Improved
-
-</pba-flex>
-
----
-
-## How do we decide on Controls?
-
-The likelihood of a threat exploiting a vulnerability and thereby causing damage to an asset.
-
-<img rounded style="height: 600px" src="./img/risk-risk-everywhere.jpg" />
-
----
-
-## ICYMI: The CIA Triad
-
-<img rounded style="height: 600px" src="./img/cia-triad.png" />
-
----
-
-## Things to Ensure
-
-- **Confidentiality:** Ensure that only authorized people can access their authorized entities.
-- **Integrity:** Ensure that only authorized changes are made by authorized entities.
-- **Availability:** Ensure that the data will always be available when it is required.
-
----
-
-## The AAA + NR
-
-- **Authentication:** Who you are
-- **Authorization:** What you allowed to do
-- **Accountability:** Who is responsible
-- **Non-Repudiation:** Can't deny your involvement
-
----
-
-# Appsec Design Principles
-
-_In Brief_
-
----
-
-## Good Enough Security
-
-Don’t spend $10.000 on a safe to protect a $20 bill
-
-<img rounded style="height: 600px" src="./img/good-enough-security.png" />
-
----
-
-## Least Privilege
-
-Don't give your safe's key to everybody, give only what they need
-
-<img rounded style="height: 600px" src="./img/least-privilege.jpg" />
-
----
-
-## Separation of Duties
-
-Don't give the power of creating invoices, approving invoices and sending money to one person
-
-<img rounded style="height: 600px" src="./img/separation-of-duties.png" />
-
----
-
-## Defense in Depth
-
-A castle has a moat, thick walls, restricted access points, high points for defense, multiple checkpoints inside etc.; what do you have?
-
-<img rounded style="height: 600px" src="./img/defense-in-depth.png" />
-
----
-
-## Fail-Safe
-
-Any function that is not specifically authorized is denied by default
-
-<img rounded style="height: 600px" src="./img/fail-safe.jpg" />
-
----
-
-## Economy of Mechanism
-
-Security is already a complex topic, don’t make it more complicated (KISS)
-
-<img rounded style="height: 600px" src="./img/economy-of-mechanism.png" />
-
----
-
-## Complete Mediation
-
-Every critical operation must have verification at every time.
-
-<img rounded style="height: 600px" src="./img/complete-mediation.png" />
-
----
-
-## Open Design
-
-Don't even try: Security over obscurity
-
-<img rounded style="height: 600px" src="./img/open-design.png" />
-
----
-
-## Least Common Mechanism
-
-Is like the rarest key that opens specific locks, not used often but still can cause significant damage when it does.
-
-<img rounded style="height: 600px" src="./img/least-common-mechanism.png" />
-
----
-
-## Psychological Acceptability
-
-There is no point if users cannot use your security controls seamlessly.
-
-<img rounded style="height: 600px" src="./img/psychological-acceptability.png" />
-
----
-
-## Weakest Link
-
-A chain is only as strong as its weakest link
-
-<img rounded style="height: 600px" src="./img/weakest-link.png" />
-
----
-
-## Leverage Existing Components
-
-Fewer components, fewer attack surface, but more;
-
-<img rounded style="height: 600px" src="./img/leverage-existing-components.png" />
-
----
-
-## Single Point of Failure
-
-If SPoF fails, means the entire system fails
-
-<img rounded style="height: 600px" src="./img/spof.png" />
-
----
-
-## Securing Software is Very Simple(!?)
-
----
-
-<pba-flex center>
-
-- **Identify Attack Surfaces**
-  What potential surfaces do you have?
-- **Identify Attack Vectors**
-  What potential vectors do you have?
-- **Allocate Security Controls**
-  Risk based approach + Security Controls
-
-</pba-flex>
-
----
-
-## Security Controls are Easy(!?)
-
----
-
-## Security controls can be;
-
-- **Directive (Safeguard \[Proactive\] - means before the incident)** \* The policy is an example. This is what you are allowed to do, or you are not allowed to do
-
-<img rounded style="height: 600px" src="./img/directive.png" />
-
----
-
-## Security controls can be;
-
-- **Deterrent (Safeguard \[Proactive\] - means before the incident)**
-  - Discourage somebody from doing something wrong. For ex. watching people with a security camera. Once they know they are under observation, they will hesitate.
-
----
-
-### Deterrent
-
-<img rounded style="height: 600px" src="./img/deterrent.png" />
-
----
-
-## Security controls can be;
-
-- **Preventive (Safeguard \[Proactive\] - means before the incident)** \* Try to stop a person from doing something wrong. For ex. Password is a preventive control.
-
-<img rounded style="height: 600px" src="./img/prevention.png" />
-
----
-
-## Security controls can be;
-
-- **Detective (Countermeasures \[Reactive\] - means in the incident moment or afterwards)** \* Trying to detect an incident. For ex. logs
-
-<img rounded style="height: 600px" src="./img/reading-toilet.png" />
-
----
-
-## Security controls can be;
-
-- **Corrective (Countermeasures \[Reactive\] - means afterwards)** \* Tries to reestablish control after an incident and correct the immediate problem.
-
-<img rounded style="height: 600px" src="./img/corrective.png" />
-
----
-
-## Security controls can be;
-
-- **Restoration/Recovery (Countermeasures \[Reactive\] - means afterwards)** \* Try to rebuild and get back to normal.
-
-<img rounded style="height: 600px" src="./img/restoration.png" />
-
----
-
-## Implementation is tough, sorry
-
-<pba-flex center>
-
-- Secure coding practices
-- Separation of environments
-- Proper testing
-- Validation and discovery
-- Mitigation
-- Root cause analysis
-- Documentation in every steps
-
-</pba-flex>
-
----
-
-# Components of AppSec
-
----
-
-<pba-flex center>
-
-- **Threat Modelling:** Manuel or Automated
-- **Security Testing:** SAST, DAST, IAST, SCA, RASP
-- **Vuln. Collection & Prioritization:** Jira, Asana
-
-</pba-flex>
-
----
-
-There will be blood (**risk**), you need to manage the blood. But how?
-
-<img rounded style="height: 600px" src="./img/there-will-be-blood.png" />
-
----
-
-## Risk Management but how?
-
-- **Risk Avoidance:** This approach mitigates risk by refraining from activities that could negatively impact the organization.
-
----
-
-## Risk Management but how?
-
-- **Risk Reduction:** This risk management method aims to limit the losses rather than completely eradicate them. It accepts the risk but works to contain potential losses and prevent their spread.
-
----
-
-## Risk Management but how?
-
-- **Risk Sharing:** In this case, the risk of potential loss is distributed among a group instead of being borne by an individual.
-
----
-
-## Risk Management but how?
-
-- **Transferring Risk:** This involves contractually shifting risk to a third party. For instance, insuring against property damage or injury transfers the associated risks from the property owner to the insurance company.
-
----
-
-## Risk Management but how?
-
-- **Risk Acceptance and Retention:** After applying risk sharing, risk transfer, and risk reduction measures, some risk inevitably remains, as it's virtually impossible to eliminate all risks. This remaining risk is known as residual risk.
-
----
-
-## Vulnerability Disclosure Program vs Bug Bounty
-
----
-
-## Shifting Left vs Right
-
-<img rounded style="height: 600px" src="./img/left-vs-right.png" />
-
----
-
-# Known Attack Surfaces and Vectors
-
----
-
-## Known Rust Vulnerabilities
-
-<pba-flex center>
-
-1. Rust-specific issues
-1. Unsafe code
-1. Cryptographic errors
-
-</pba-flex>
-
----
-
-## Known Substrate Vulnerabilities
-
-<pba-flex center>
-
-1. Insufficient testing
-1. Centralization vulnerabilities
-1. Pallet-specific vulnerabilities
-
-</pba-flex>
-
----
-
-## Known ink! Vulnerabilities
-
-<pba-flex center>
-
-1. Incorrect access control
-1. Denial-of-Service (DoS)
-1. Timestamp dependence
-1. Outdated version
-
-</pba-flex>
-
----
-
-**Summary:** Do the damn input validation, good to go!
-
-<img rounded style="height: 600px" src="./img/input-validation.png" />
-
----
-
-**Question:** How would you defend a castle if there is no castle to defend?
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-# Awareness
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Security Awareness in web3
-description: A sentence for what these slides are about.
-duration: 45 minutes
----
-
-# Security Awareness in web3
-
-## The context, impacts, and mitigations
-
----
-
-### _Lesson Objectives:_
-
-<pba-flex center>
-
-- Be able to describe the threats which exist in the web3 space
-- Navigate the risks posed with confidence
-- Understand the measures taken to minimize impact
-
-</pba-flex>
-
----
-
-## The Inevitable Jargon
-
-Time for a quick speedrun
-
-Notes:
-
-Security folks love their jargon and acronyms, you may be familiar with some of these, but no worries if not.
-
----v
-
-#### Threat Actor
-
-Any individual, group, or entity that poses a potential risk or threat to the security of a system or organization.
-
-Notes:
-
-Threat actors can be hackers, cybercriminals, social engineers, insiders, state-sponsored groups, or other malicious actors.
-
----v
-
-#### Attack Surface
-
-The points of entry, or potential vulnerabilities in a system that could be exploited by a threat actor to compromise or gain unauthorized access.
-
-Notes:
-
-This ranges from network interfaces, APIs, software, hardware and infrastructure, through to human factors.
-
----v
-
-#### Attack Vector
-
-Specific paths or methods that threat actors use to launch attacks against a system or organization.
-
-Notes:
-
-These can include various techniques, some of which could be phishing emails, software vulnerabilities, social engineering, malware, or brute-force attacks.
-
----
-
-## Eyes are on us
-
-<pba-flex center>
-
-- Crypto Market Capitalization: $1,231,359,133,397
-- 24 Hour Trading Volume: $39,807,353,848
-
-</pba-flex>
-
-Notes:
-
-Those are some big numbers, that's $1.23 Trillion.
-As a result, there are a lot of eyes on the industry as a whole - not just because people are excited about decentralization and web3.
-These projects carry a lot of influence and responsibility, from maintaining infrastructure through to securing funds.
-
----
-
-## In the real world
-
-#### _there is no scope_
-
-Notes:
-
-In the real world, there is minimal scope - financially motivated attackers do not follow a code of ethics, and will monetize whatever they can get their hands on.
-
----v
-
-#### Funds
-
-Quickest and easiest way to make money: attack wallets and services
-
-Notes:
-
-Financially motivated attacks are among the most common, earnings from these can be used to fund more advanced future attacks, for market manipulation, or directly cashed out
-
----v
-
-#### Networks & Infrastructure
-
-<pba-flex center>
-
-- Smart Contracts
-- Ransomware
-- Impact on network availability
-- Malicious code injection/node creation
-
-</pba-flex>
-
-Notes:
-
-Attackers can and will exploit anything, these can be on-chain attacks - such as exploitation of vulnerabilities in smart contracts, or even crafting and sending their own malicious smart contracts
-
-Ransomware and denial of service attacks can be utilized to reduce confidence in or extort funds from projects
-
-Mechanics of protocols themselves can be taken advantage of through 51% attacks, double spends, or malicious validation
-
----v
-
-#### Personally Identifiable Information
-
-<pba-flex center>
-
-- Account takeover
-- Identity theft
-- Impersonation
-
-</pba-flex>
-
-Notes:
-
-You know you're you, and your teams know you're you - this trust can be taken advantage of by attackers, impersonating people with social capital and good social standing to pivot deeper into organizations and networks - or even something as simple as identity theft to launder money.
-
-It may sound far-fetched, but this is a very real problem in the web3 ecosystem - so if a request seems a bit bizarre, it's never a bad idea to check in and verify via an alternative line of communication which has already been established.
-
----
-
-## A look at potential adversaries
-
-<pba-flex center>
-
-- Lazarus Group (APT 38)
-- Sanctioned Nation States
-- Future Adversaries
-
-</pba-flex>
-
-Notes:
-
-So now we know some of the ways that threat actors can strike, let's take a moment to look at who and why.
-As mentioned before, a lot of attacks in the web3 ecosystem are financially motivated - especially for nation states which are experiencing financial sanctions due to whatever geopolitical antics they are involved in.
-While that's true, we can't rule out politically motivated attacks.
-
-- Lazarus Group
-  - $400m in 2021
-  - $1.7b in 2022
-- Russia
-- US in future
-- More advanced & persistent
-  - Resources
-  - Driven
-
----
-
-## Up to date devices are great
-
-### _but there's more to it than that_
-
----
-
-# Types of Adversaries
-
-### A Deeper Dive
-
----v
-
-#### Opportunists
-
-Individuals or small groups who take advantage of easily exploitable vulnerabilities without significant planning, often targeting low-hanging fruit and utilizing readily available tools and techniques.
-
-Notes:
-
-Opportunists can impact us from phishing through to being in the wrong place at the wrong time.
-Keep your guard up when in transit or a public place, all it takes is a momentary lapse in focus for a device to be stolen.
-
----v
-
-#### I Pickpocketed a Pickpocket
-
-<img rounded style="width: 1100px" src="./img/pickpocket.gif" />
-
-Notes:
-
-Source: <a href="https://www.youtube.com/watch?v=j25VkESewZg">I Pickpocketed a Pickpocket</a>
-
----v
-
-#### Organized Crime Groups (OCGs)
-
-More sophisticated adversaries with dedicated resources and a more defined focus.
-They operate like traditional criminal organizations and often engage in large-scale, financially motivated attacks.
-
-Notes:
-
-OCGs will have more information than a mere opportunist, with more time spent assessing their targets - vulnerabilities affecting the cyber realm, but even social media, gaining a better understanding - for example: knowledge of frequent travel locations, offices, events, etc.
-This knowledge can be used to carry out more advanced phishing campaigns, also known as spearphishing - but more on that later.
-
-These details can be used for extortion, be it compromising information or physical threats, through to kidnap for those higher value targets.
-
----v
-
-#### Nation States
-
-The most sophisticated and well-resourced adversaries in the landscape.
-They have significant technical capabilities and may engage in cyber-espionage sabotage, or warfare.
-
-Notes:
-
-Nation states can act similarly to OCGs, but with increased skill and greater financial backing, with the added benefit of additional operating locations: think airports, border crossings, police forces.
-
-In the context of web3, nation states may be interested in:
-
-- Money
-- Service Disruption
-- Undermining Integrity
-
----
-
-# Methods of Adversaries
-
----v
-
-#### Theft
-
-<pba-cols>
-<pba-col center>
-
-- Laptops
-- Phones
-- Keys
-
-</pba-col>
-<pba-col center>
-
-- Auld Wallets
-- ID Documents
-- Hardware Wallets
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-A lot is at stake, even when an opportunist strikes - for most people our entire lives are on our devices these days.
-Losing a device can mean lost, and potentially compromised, second factor authentication - locking you out, but letting a crook in, but also the potential exposure of your wallet seeds, along with whatever is signed in.
-
-Lost or stolen keys and ID documents pose an increased physical threat: the leak of your home address and the means to access it, which can also extend to workplaces or infrastructure locations
-
----v
-
-#### Tampering
-
-<iframe width="1440" height="646" src="https://www.youtube-nocookie.com/embed/meNlOrdQJFo?autoplay=1&showinfo=0&controls=0&mute=1"data-preload data-autoplay></iframe>
-
-Notes:
-
-Computers are small but powerful - think about the size of the Apollo flight computer, while nowadays we have a computer with much greater processing power in our pockets, but the progress hasn't stopped - there are powerful SoCs, Systems on a Chip, which can be utilized by attackers.
-
-They range from devices, such as the Rubber Ducky, through to a simple USB-USB cable which looks innocuous enough, but can wreak havoc - and even exfiltrate data or allow for remote control.
-
-These can put your devices - be it phone, laptop, or hardware wallet - at risk of malware injection or firmware integrity
-
----v
-
-#### Tampering: Mitigations
-
-<img rounded style="width: 500px" src="./img/cables.png" />
-
-Notes:
-
-So what can we do to mitigate these attacks?
-For a start use our own, trusted, cables - consider identifying them in a distinctive way: that could be wrapping some tape around the end, breaking out the ol' sharpie (other permanent markers are available), or applying a coat of nail polish.
-
-Don't use that charger you found randomly left in a café, even if it was offered to you by a nice businessman, and it's probably best to not pick up that mysterious USB on the side of the road anyway.
-
----v
-
-#### Hacking
-
-<pba-flex center>
-
-- Direct attacks
-- DNS poisoning
-- Targeted Man in the Middle attacks
-
-</pba-flex>
-
-Notes:
-
-If you're on a network that isn't your own or trusted (home, hotspot, place of work), pop on your VPN for additional protection and privacy.
-
----v
-
-#### Social Engineering
-
-Phishing and its counterparts, vishing, smishing, etc.
-
-Notes:
-
-Phishing and attacks under its umbrella are still a very real threat, but often downplayed - but more on them later.
-
----
-
-# Situational Awareness
-
----v
-
-### Shoulder Surfing
-
-Notes:
-
-Privacy screens are a mitigation, but they're not infallible - they reduce the viewing angle, but those behind you still have the best seats in the house.
-
----v
-
-### Shoulder Surfing
-
-<img rounded style="width: 350px" src="./img/com-truise.png" />
-
-Notes:
-
-Besides, we know that Mr Tom Cruise runs at a 22° angle, rendering privacy screens useless.
-
----v
-
-### Shoulder Surfing
-
-<img rounded style="width: 700px" src="./img/shoulder-pads.jpg" />
-
-Notes:
-
-It's unrealistic that you can wear shoulder pads all the time to block the view of your sweet sweet screen real estate.
-
----v
-
-### Shoulder Surfing
-
-<img rounded style="width: 700px" src="./img/scousers.jpg" />
-
-Notes:
-
-Nor are you going to be able to rapidly grow out your hair
-
----v
-
-### Shoulder Surfing
-
-<img rounded style="width: 700px" src="./img/shouldersurf.jpg" />
-
-Notes:
-
-In Feng Shui, having a solid wall behind you is considered favorable, especially when sitting at a desk.
-A solid wall represents support, stability, and protection.
-
-There's truth to this, it also adds privacy - so if you happen to be working in a public place, consider the flow of energy and listen to Feng Shui - find a nice wall to sit against.
-
----
-
-# Visual Cues
-
-Notes:
-
-It’s no secret that folks in tech love their stickers, they make our devices unique versus our friends and colleagues - but this also comes with downsides.
-There’s a tipping point between a casual interest and direct involvement: stickers can act like a fingerprint, but what kind of information can we glean from them?
-
----v
-
-### Device Stickers
-
-Some things can be identified from these, such as:
-
-<pba-flex center>
-
-- Role
-- Industry
-- Employer/Projects
-
-</pba-flex>
-
-Notes:
-
-- Role
-  - Developers: Framework/Language/Software stickers
-  - DevOps: Cloud service/provider stickers
-  - Security: Security tools and software
-- Employer
-  - Lots of brand-specific stickers can indicate affiliation to an organization or project
-
-Cover in transit - benefit of protected device
-
----v
-
-<pba-cols>
-  <pba-col>
-    <h3>Clothing, Swag, Drip</h3>
-    Call it what you will, but it can be a source of information disclosure
-  </pba-col>
-  <pba-col center>
-    <img rounded style="width: 500px" src="./img/btc-coat.png" />
-  </pba-col>
-</pba-cols>
-
-Notes:
-
-Donning the latest swag is turning yourself into a billboard
-
-- Advertising the project mentioned
-- Advertising potential affiliations
-- Advertising why you would make a financially sound target
-
-The last point applies to tattoos too, unless it's a Dogecoin tattoo.
-
----
-
-# Digital Footprint
-
----v
-
-### Social Media
-
-<pba-cols>
-<pba-col center>
-
-#### The Usual Suspects
-
-- Twitter
-- Meta
-- Linkedin
-
-</pba-col>
-<pba-col center>
-
-#### The Less Obvious
-
-- Telegram
-- WhatsApp
-- Discord
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Data can be inferred through social media, listing your position on LinkedIn gives attackers confirmation of your presence, the format of email addresses is likely easily discoverable, opening the door to spearphishing attacks.
-
-Messaging apps are rapidly becoming social media, remember that posts and stories aren't necessarily private and can be viewed by anyone with your number.
-We can mitigate the impact of these by ensuring device separation - which is also great for work-life balance, which is a great opportunity to revisit phishing.
-
----
-
-# Phishing
-
-Humans get distracted, stressed, and tired, this is when phishers thrive.
-
-If it didn't work, they would have stopped by now.
-
-Notes:
-
-Phishing is still highly effective, at the end of the day we're only human.
-The cost of phishing is constantly dropping, making it easier for the masses to be reached
-Actions and decisions are circumstantial
-
----v
-
-### Rise of AI
-
-Phishing is easier than ever, just ask ChatGPT:
-
-<img rounded style="width: 1000px" src="./img/gpt-github-email.png" />
-
-Notes:
-
-Not only is phishing getting cheaper, the bar to entry has been significantly lowered.
-Existing trusted email infrastructure and its exploitation leads to more and more convincing attacks, paired with the rise of services like ChatGPT, the risk is increasing.
-
----v
-
-### Beyond the Nigerian prince
-
-Phishers are getting smarter, and your digital footprint is on their radar.
-
-<img rounded style="width: 800px" src="./img/gpt-travel-email.png" />
-
-Notes:
-
-Posting online comes with its share of danger, broadcasting your location to the world.
-Think again before you post, could an adversary use this information to target you, your family, or colleagues - is it advertising that your team is all in one place, or perhaps alerting them to the fact that your team is distracted and probably stressed with travel?
-
-There is also the issue of consent - avoid blindly tagging people and tainting their operational security, ask first - it's also just a nice thing to do, rather than making bold assumptions about what they are on board with.
-
-Not to say don't post, but add a delay to obscure your live location and minimize physical risks
-
----v
-
-### Reacting to a Phish
-
-<pba-flex center>
-
-1. Stop
-1. Take a moment
-1. Verify
-1. Report
-
-</pba-flex>
-
-Notes:
-
-So why is phishing suddenly important?
-It's not, it's always been important - but downplayed.
-We're in a rapidly evolving space, which comes with a lot of eyes - for better or for worse.
-
-It's always preferred to be interrupted for a second opinion on a potential phishing attempt than an unfolding incident, it'll even put a big smile on the faces of security folks all over.
-After all, we're there to help, rather than preach from our ivory towers and reprimand those who make mistakes.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
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-# 🕵️ Applied Security
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-# Infrastructure Security
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Web3 Infrastructure Security
-description: This is about how securely deploy your web3 infrastructure.
-duration: 50 minutes
----
-
-# Web3 Infrastructure Security
-
-Notes:
-
-I'm going to speak about how securely deploy your web3 infrastructure.
-But, instead of talking about very common information topics like best practices, strong authentication and others well discussed like firewalling, I’m going to talk about some often overlooked problems that significantly affects web3 infrastructure protection and about how they should be handled.
-
-But if you want to ask me about firewalling, welcome to the Q&A section!
-
----
-
-## Overview
-
-<pba-flex left>
-
-- Concentration and deplatforming risks
-  - Digging into the Solana case (end of 2022)
-  - Selection of providers
-  - Mitigation of the risks
-- Supply chain attacks
-  - Where it can happen and how to prevent
-- Two uncommon attacks against infrastructure
-- Tips about key and password management
-
-</pba-flex>
-
----
-
-## Deplatforming risk
-
-<pba-flex center>
-
-- Deplatforming happens when some resource is removed from service by a provider.
-- Web3 is supposed to be decentralized, but it may rely on the centralized infrastructure behind it, with some legal and technical rules.
-  Therefore, this risk should not be overlooked.
-
-</pba-flex>
-
-Notes:
-
-The first overlooked risk is the deplatforming risk.
-Deplatforming is, briefly speaking, when someone or something, suddenly goes offline without a wish to do it.
-It can happen on any layer of the technological stack, with everyone/everything, with proper legal ground or not.
-Today web3 and cryptoassets are receiving a lot of attention from different regulators.
-If some platform decides that your web3 stuff is unwanted, they can just suspend the accounts and delete the data.
-From this perspective, web3 infrastructure, which is running on top of centralized infrastructure, is still unfortunately partly centralized.
-
----
-
-### Solana case (Nov. 22)
-
-<img rounded style="width: 1000px" src="./img/solana.png" />
-
-[Web source: 1000 solana validators go offline by TheBlock](https://www.theblock.co/post/182283/1000-solana-validators-go-offline-as-hetzner-blocks-server-access)
-
-Notes:
-
-At the beginning of November 2022, the nodes of Solana in Hetzner, were removed at one moment.
-A big pain for the node operators, a major reputational risk for the network.
-Solana tokens became cheaper the next few days (to be honest, I can’t say that there is a straight connection between the event and the token price, but anyway).
-
----
-
-### Solana case. Going deeper
-
-_What’s Hetzner in a nutshell? Why did many people go to it?_
-
-- A German Hosting Provider
-- Gives people extremely cheap bare metal servers
-- Price per CPU/RAM is very low
-- True power of raw non-virtualized hardware
-- Control over the CPU/RAM for people who want to control the environment.
-
-Notes:
-
-Sounds good, isn’t it? But, Germany has high electricity prices, human work is expensive, and the hosting is still so cheap, why?
-
----
-
-### Solana case. Going deeper
-
-_Why is Hetzner so cheap?_
-
-- Mostly consumer-level hardware, not “robust enterprise servers” in terms of Service Level Agreement.
-  It can be seen if you see the available configurations.
-- _Covert expectations of low resource load from the customers_
-
-Notes:
-
-The first is almost clear.
-Now lets explain what the second means.
-
----
-
-### ToS/ToU/EULA that people don’t read
-
-_A small cool story first_
-
-<img rounded style="width: 1400px" src="./img/eula.png" />
-
-[Web source: PCMatic](https://www.pcmatic.com/blog/it-pays-to-read-license-agreements-7-years-later/)
-
-Notes:
-
-There is a small joke, which is actually not a joke, about the fact that people just skip over the reading of license agreements.
-Some company offered a prize for reading ToS till the end, by placing an easter egg in the text of ToS.
-
----
-
-### Hetzner strikes back
-
-<img rounded style="width: 1400px" src="./img/hetzner.png" />
-
-[Web source: Reddit](https://www.reddit.com/r/hetzner/comments/wucxs4/comment/ilfoj8u/)
-
-Notes:
-
-Literally Hetzner said: we don’t care about your consensus (PoW vs PoS), we just call everything “mining”, please remove your software or we do it by ourselves.
-
----
-
-### But… Why and how?
-
-Q: **Why** do providers act against blockchain, and **how** do they detect it?
-
-- A1: Business model: _covert expectations of low resource load from the customers:_
-  - Nominal link speed is probably not fully guaranteed, but shared.
-  - Crypto databases tear the ordinary disks.
-    They die 10x faster.
-  - The nodes are attacked 24x7.
-    Headache for network engineers.
-  - Server consumes not “average” power, but more close to the limit.
-- A2: More direct reasons: regulations/sanctions/other paper blockers.
-
-Notes:
-
-In short, the hardware resources are shared where possible, the hardware is low-level, and the business model is similar to insurance companies or banks from a far perspective.
-If all of the users demand their resources at one time, the company just doesn’t have them available.
-
----
-
-### How do ISPs detect blockchain?
-
-- Q: And why a Blockchain node wasn't banned immediately?
-- A: It has not been detected on time, probably.
-  Or the size of a particular setup is not worth the deplatforming efforts.
-
-Let’s talk about the detection.
-
----
-
-### How do ISPs detect blockchain?
-
-Joke: how does a provider see your node:
-
-<img rounded style="width: 600px" src="./img/rack.png" />
-
-Notes:
-
-It is a joke of course, but how the provider engineer can see your web3 server.
-
----
-
-### How do ISPs detect blockchain?
-
-- Known “bad” DNS names resolution and contact with specific IP addresses
-- Memory (RAM) Scanning for virtual machines:
-- Example, Google Cloud case for [their VMs](https://cloud.google.com/security-command-center/cryptomining-protection-program#section-4).
-
-Notes:
-
-In short, it is very hard to hide the node.
-Tricks like VPN, obfuscation give a lot of performance penalty.
-
----
-
-### Okay, and how to mitigate that?
-
-Moving to platform independency:
-
-- Decomposition of the solution layers from the beginning is the best friend (opposite to the classical monolithic configuration, which is target-dependent)
-- Modern DevOps and CI/CD
-- Partial “landing” of the infrastructure from the clouds
-- Client-side only websites (no backend)
-
-Notes:
-
-It is impossible to mitigate this risk in full.
-
----
-
-## Deplatforming risk mitigation
-
-Idea #1. Decomposition of the solution
-
-<img rounded style="width: 1000px" src="./img/stack.png" />
-
-Notes:
-
-Instead of having all-in-one solution (example: manually go to the server and compile/configure from scratch, or use a specific toolkit for a single provider like AWS), we can have the following independent components, even for a couple of servers.
-
-- Build services - produce clean, ready to use, tested images (containers, virtual machines). Key target: readiness (achievable by regular testing).
-- Provider-agnostic provisioning of the infrastructure - makes a “landscape” to fill it with the services. Key target: minimal dependencies from a particular vendor.
-- Automatic server configuration and delivery of the services: Key target: no manual intervention, clear feedback about actions.
-- Monitoring. It gives the health metrics/feedback in the long run.
-
-It is not a full set of blocks, but the major parts.
-
----
-
-### Modern DevOps and CI/CD
-
-Idea #2. _One of the solutions_ - IaC:
-
-- Infrastructure as a code (IaC) approach. Clear, declarative, history trackable configuration storage
-- IaC can utilize regular CI/CD processes to control provision and configuration for servers.
-- Separation of provision (example - Terraform) and configuration (example - Ansible) makes the solution close to be provider-agnostic.
-- Only really unique data is backup-ed or synchronized - quick move & restore procedures.
-
----
-
-### Partial “landing” of the external dependencies
-
-Idea #3. Working with dependencies.
-
-- Instead of having just one ecosystem, be adaptive to another one. Example: Github <-> Gitlab (caveat: up to 100% of additional work).
-- Use configuration bastion approach (example: your own Gitlab server).
-- Have multiple service image registries and other storages
-- Fork 3rd party local source code to your repos (to prevent abandoning of dependencies and supply chain attacks caused by abandoning).
-- Use centralized facilities? Typical: a single RPC server? Run your own or use light clients.
-
----
-
-### Deplatforming risk mitigation
-
-**Final objective**: to find a proper balance between duplication of efforts and the time to recover if a resource disappears.
-
----
-
-### Concentration risk
-
-One picture that says everything (on Polkadot - the whole ecosystem):
-
-<img rounded style="width: 1200px" src="./img/concentration.png" />
-
-[Web Source: Polkawatch](https://polkadot.polkawatch.app/network/)
-
----
-
-### Concentration risk
-
-- It is a consequence of decentralization. People are free to do this.
-- About 17% of DOT rewards are coming to nodes in Hetzner (July 2023).
-- Four of the major providers take 50% of the rewards (July 2023).
-
-Notes:
-
-This is a concentration risk in one picture. Since the web3 world is decentralized, there is no proper handle to prevent this. However, node operators should realize that their individual actions affect the whole ecosystem.
-
----
-
-## Caveats of the supply chain management
-
-- Let’s assume that we have deplatforming-resistance infrastructure and some well known preventions in place. Your password is not your name plus your birthday.
-
-What’s next?
-
-- Now let’s talk about the modern issues of supply chain management in the infrastructure.
-- Supply chain attack: when someone compromises only a small component of a product and gets access to the whole product.
-- The same can be applied to any part on a random entity (orgs, dev libs, people relations)
-
----
-
-## Supply chain protection basics
-
-Like dependencies in the regular code, all of the infrastructure components can be compromised by supply chain attacks as well. The most risky components are ... (spoiler - almost all).
-
----
-
-### Where to expect the attack
-
-- Integrations that can’t be restricted by scope to a specific need. Example: [GitHub OAuth token leak'22](https://github.blog/2022-04-15-security-alert-stolen-oauth-user-tokens/)
-- Yet another small component that solves once again a well known problem. Usage of it increases the attack surface.
-- Components that don’t have proper support. Can be abandoned and squatted one day.
-- Suddenly, most popular products, but for another reason: be careful with the names and scopes to avoid [typosquatters](https://en.wikipedia.org/wiki/Typosquatting).
-
----
-
-### Basic prevention of the supply chain attacks
-
-- Prevention of replacing the content of dependency (80% result by 20% of efforts):
-  - Scoping dependencies. For some ecosystems (ex. - Docker, NPM) - the same thing can be looked up in different locations. Specific lookup locations (repos) are highly recommended.
-  - Pinning dependency to a specific commit (e.g. lib@aaabbbccc…). Pinning to a tag (lib@tagname) is not efficient. Commit is a hash, tag is human-defined.
-  - Forking and re-targeting the dependency to the new controllable fork.
-
----
-
-### Basic prevention of the supply chain attacks
-
-- Increasing the dependency quality (20% of result by 80% efforts):
-  - For advanced usage: tracking the vulnerabilities related to the component (update or downgrade the version)
-  - self reviewing the code of the component
-  - extracting the direct functionality from the dependency.
-
----
-
-## Uncommon infrastructure attacks
-
-Some examples.
-
-Simple, but very efficient.
-
----
-
-### Abusing of CI/CD misconfigurations
-
-- Abusing CI/CD by triggering the pipeline with modified code, which makes malicious actions - steal your repo secrets or break your CI/CD.
-- Mitigation: understand the triggering event, restrict who can trigger the CI and set the scopes for the CI/CD:
-  - Runners
-  - Secrets
-  - Other components
-
----
-
-### Social engineering: forging the GIT commits
-
-**We can commit on behalf of someone else!** But there is a small detail…
-
----
-
-### Git doesn’t have authentication
-
-How does it work:
-
-GIT itself is not responsible for authentication. Everyone can set random username and email in the commit metadata, and to push the branch or create a pull request.
-
-It is the nature of git. A great field for social engineering!
-
----
-
-### Exploiting git
-
-Get a target repo, find a "victim" - a popular person,<br />uses mixed verified and unverified commits:
-
-<img rounded style="width: 1000px" src="./img/commit-forgery1.png" />
-
-- <https://github.com/ethereum/research/commits?author=vbuterin>
-- <https://github.com/jayphelps/git-blame-someone-else>
-
----
-
-### Exploiting git
-
-Clone the repo and find the victim’s git metadata
-
-`git show --quiet 6355f3a`
-
-<img style="width: 800px" src="./img/commit-forgery2.png" />
-
----
-
-### Exploiting git
-
-Change the local git settings.
-
-```sh
-git config commit.gpgSign false
-git config user.email v@buterin.com
-git config user.name "Vitalik Buterin"
-```
-
----
-
-### Exploiting git
-
-Make a definitely trustworthy commit:
-
-```sh
-echo "I'm Vitalik Buterin, trust me, send all the ethers on ..." > message.txt
-git add message.txt
-git commit -a -m "wallet update"
-git push origin master
-```
-
-**What stops the app-ocalypse**: an attacker needs write permissions to push, which is defined by credentials from the code storage.
-
-But the attacker still can play around Pull Requests, mix forged/non-forged commits, etc.
-
----
-
-### Exploiting git
-
-See the result (a fork was created to have write access):
-
-<https://github.com/pavelsupr/research/commit/99cb1cbe3b729cfada10aa53d531b5f2bcb5aa7f>
-
-<img rounded style="width: 1000px" src="./img/commit-forgery3.png" />
-
----
-
-### Mitigation from commit forgery
-
-- Commit signing + Vigilant mode, protection of the branches, reviewing the pull request about what’s going on - and reviewing them one more time!
-
-- Dismiss a pull request when new commits arrived
-- Caveat: impossible to properly revoke the signing key - all the previous commits will be considered as “unverified” in the Vigilant mode.
-
-- Solution: use hardware keys, which is very hard to compromise + destroy all the software keys, but don’t remove the public key fingerprint from the repo storage.
-
----
-
-## Secure key management on the nodes
-
-Polkadot-specific.
-
----
-
-### Basics
-
-- A separated browser profile or/and OS account for web3 operations
-- Lock this profile with a password to prevent stealing the data
-- No 3rd-party operations and browser extensions on the “secured” profile
-  - Or, replacing all the above: A separated device as an ideal paranoid mode option
-- All significant accounts only on a cold wallet + paper seed backup (ref: Banana Split)
-- Client disk encryption and other device health checks
-
----
-
-### Node running
-
-- Node accounts: proper combination of Stash and Staking proxy (prev. Controller) accounts
-  - Stash - use cold wallet
-  - Controller != Stash
-- Remember that a node process has to store some keys on the disk (session keys). Keep the node isolated
-- Apply all the well known measures: firewalling, strong passwords, 2FA, disk encryption, etc.
-- Containers are NOT protecting your node from the OS/kernel
-
----
-
-### Password management for the infrastructure
-
-- Use keys instead of passwords where possible
-- SSH and GPG keys on hardware keys (one primary key and backup)
-- 2FA everywhere, hardware based when possible
-- Use password manager (preferable with API), don't re-use passwords
-- NEVER place any secrets in the code or files, even for testing, use environment variables instead
-- Advanced: connect your code with the API of your password manager
-- (life hack only for Bash users) one space before `export VAR=SECRET_VALUE` command will not place this command in the Bash history
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
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-# Cybersecurity Overview
-
-<!-- markdown-link-check-disable -->
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-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Cybersecurity Overview
-description: "Key drivers around Cyber Security, Introduction to the other modules
-  Security Awareness (40/50mn)
-  User Centric Security in Web3 (40/50mn)
-  Infrastructure Security (40/50mn)
-  Application Security (1h)"
-duration: 30 minutes
----
-
-# Cybersecurity Overview
-
----
-
-## Outline
-
-<pba-flex center>
-
-1. Threat landscape
-1. Risk management
-1. Development
-1. Conclusion
-1. Q&A
-
-</pba-flex>
-
-Notes:
-
-- Threat landscape
-  - Key threat actors
-  - Largest crypto heists
-  - Crypto incidents
-- Risk management
-  - Inherent & Residual
-  - Key steps of an attack
-  - Importance of culture
-- Development
-  - Development and key focus
-  - CI/CD
-- Conclusion
-- Q&A
-
----
-
-#### Cyber Threat - 6 Main Actors
-
-<img rounded style="width: 1300px" src="./img/2-landscape.png" />
-
-Notes:
-
-Different actors with different drivers but commonalities on modus operandi.
-
----
-
-#### Largest Crypto Losses
-
-<img rounded style="width: 900px" src="./img/3-loss.png" />
-
-> Some were Ponzi schemes, most were breaches/exploits
-
-Notes:
-
-On the crypto ecosystem there have been number of cyber events!
-<https://medium.com/ngrave/the-history-of-crypto-hacks-top-10-biggest-heists-that-shocked-the-crypto-industry-828a12495e76>
-
----
-
-#### More Recent Crypto Incidents
-
-<img rounded style="width: 1300px" src="./img/4-incidents.png" />
-
-> Strong cyber control foundation decrease exposure to incidents.
-
-Notes:
-
-- <https://www.forbes.com/sites/ninabambysheva/2022/12/28/over-3-billion-stolen-in-crypto-heists-here-are-the-eight-biggest/?sh=5d411c13699f>
-- <https://www.zdnet.com/article/iota-cryptocurrency-shuts-down-entire-network-after-wallet-hack/>
-- <https://news.bitcoin.com/kucoin-boss-on-strategy-after-hack-we-chose-to-act/>
-- <https://www.halborn.com/blog/post/explained-the-ronin-hack-march-2022>
-- <https://www.bitdefender.com/blog/hotforsecurity/cryptocurrency-monero-website-hacked-original-binaries-replaced/>
-- <https://www.coindesk.com/markets/2020/02/10/new-crypto-exchange-altsbit-says-it-will-close-following-hack/>
-- <https://peckshield.medium.com/akropolis-incident-root-cause-analysis-c11ee59e05d4>
-- <https://www.coindesk.com/markets/2020/12/21/bitgrail-operator-may-have-hacked-own-exchange-to-steal-120m-police-allege/>
-- <https://coinmarketcap.com/academy/article/bitgrail-hack-one-of-the-largest-crypto-hacks-in-history>
-- <https://www.coindesk.com/tech/2020/04/08/hacker-exploits-flaw-in-decentralized-bitcoin-exchange-bisq-to-steal-250k/>
-- <https://www.coindesk.com/policy/2021/02/20/cryptopia-exchange-currently-in-liquidation-gets-hacked-again-report/>
-- <https://bravenewcoin.com/insights/cryptopia-exchange-liquidator-releases-third-report>
-- <https://www.elementus.io/blog-post/cryptopia-hack-transparency>
-- <https://blog.merklescience.com/hacktrack/hack-track-eterbase-cryptocurrency-exchange>
-- <https://www.reuters.com/investigates/special-report/fintech-crypto-binance-dirtymoney/>
-
----
-
-#### InfoSec & Cyber Risk - Taxonomy
-
-<img rounded style="width: 1300px" src="./img/5-taxonomy.png" />
-
-Notes:
-
-When a threat is leveraging a vulnerability, the consequence is a risk.
-Usually Threats cannot be influenced, when vulnerabilities can be.
-Both Threats and Vulnerabilities are evolving over time based on multiple factors, so the importance of deploying controls to identify, prevent, detect and respond & recover against them (NIST)
-
----
-
-#### Taxonomy - Threats Examples
-
-- Cyber Criminal : In the last 12 months, cyber criminal activity +200%
-- Insider / Disgruntled employee : lot of evolution on resources
-- Hacktivist : Crypto projects and web3 have some detractors
-- Terrorist : they are increasingly using cyber as a weapon
-- Nation state : Geopolitical evolution with China, North Korean, Russia/Ukraine
-- "Government" : There is lot of regulatory scrutiny on crypto area
-- Media : Web3 & cryptocurrency evolutions are regularly in the media
-- Competitors : Polkadot approach is a game changer
-
----
-
-#### What Is Cyber Risk Management?
-
-<img rounded style="width: 1300px" src="./img/7-risk.png" />
-
----
-
-#### What Is Cyber Risk Management?
-
-<img rounded style="width: 1300px" src="./img/8-risk.png" />
-
----
-
-#### Inherent And Residual Risk
-
-<img rounded style="width: 900px" src="./img/9-inherent.png" />
-
-> Having visibility of inherent risk facilitates a common view on area of focus and priorities.
-
-Notes:
-
-- It is foundational to identify inherent risk. Including in partnership with asset owner. Especially from an impact perspective
-
-- Controls are key to :
-  - Reduce likelihood of initial compromise
-  - Limit the impact of compromise once a foothold has been established
-
-And to enhance ability to detect compromise asap
-
-Starting from the inherent risk is foundational as the threat landscape will evolve including the effectiveness of the control
-
----
-
-#### Attack Kill Chain
-
-<img rounded style="height: 700px" src="./img/10-attack.png" />
-
-Notes:
-
-Usually an attacker is not attacking directly the target but :
-
-1. Collect information leveraging the digital footprint available (linkedin profile, dns records, website, repositories, 3rd parties, anything publicly available)
-2. Use information available and vulnerabilities to create a “weapon” to prepare an attack
-3. Deliver the “weapon” via available channels : email (prof./person.), usb, WhatsApp/Signal/Telegram, webpage (legit or squatting), code update, etc
-4. Use the “weapon” delivered on the victim’s system to execute code
-5. Get a foothold on the target
-6. Move laterally smoothly to reach the target objective including staying hidden for a period of time
-7. Execute final objective : ransom, denial or service, data exfiltration, corruption, fund stealing
-
----
-
-#### Importance Of Culture
-
-<img rounded style="width: 1300px" src="./img/11-culture.png" />
-
----
-
-#### InfoSec & Cyber Risk - Embedded
-
-Security embedded and partnering at each steps with key success factors:
-
-<pba-cols>
-<pba-col>
-
-- Upfront threat modeling
-- Peers code review
-- Code scanning
-- Independent security code review
-
-</pba-col>
-<pba-col>
-
-- Penetration testing (pentest)
-- Secret management
-- Supply chain management
-- Monitoring
-- Playbooks
-
-</pba-col>
-</pba-cols>
-
----
-
-#### InfoSec & Cyber Risk - CI/CD
-
-<img rounded style="width: 11 00px" src="./img/13-cicd.png" />
-
-Notes:
-
-This is a continuous process, at each step.
-
----
-
-#### Conclusion
-
-<img rounded style="width: 1300px" src="./img/14-conclusion.png" />
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
-
----
-
-#### Next Practical Sessions
-
-- Security Awareness (40/50mn) :
-  Context and adversaries, Attack Surface and Social Engineering
-- User Centric Security in Web3 (40/50mn) :
-  Wallet landscape, Key management and User device protection
-- Infrastructure Security (40/50mn) :
-  Concentration, deplatforming, supply chain risks, Key management on the nodes and Passwords management for Infrastructure
-- Application Security (60mn) :
-  Securing SDLC, Components of AppSec and Known Attack Surfaces & Vectors
-
----
-
-#### Appendix - Streetlight Effect
-
-<img rounded style="width: 1100px" src="./img/18-street.png" />
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-# Common Security Risks in Polkadot SDK Development
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: Common Security Risks in Polkadot SDK Development # Also update the h1 header on the first slide to the same name
-description: A session to explain common security risks in the development using Polkadot SDK.
-duration: 60 minutes.
-separator: "\r?\n---\r?\n"
-verticalSeparator: "\r?\n---v\r?\n"
-revealOptions:
-  transition: "slide" # animation between slides = none/fade/slide/convex/concave/zoom
-	backgroundTransition: "fade" # background swap between slides = none/fade/slide/convex/concave/zoom
-	slideNumber: true
-	controls: true
-	progress: true
-  
----
-
-# Common Security Risks in **Polkadot SDK** Development
-
----
-
-<pba-cols>
-<pba-col left>
-
-This presentation discuss common security risks in **Polkadot SDK (Polkadot, Substrate, Cumulus, etc.)** development, and methods to mitigate them.
-
-Each security risk is composed of: **Challenge, Risk, Case Studies, Mitigation and Takeaways**.
-
-</pba-col>
-<pba-col left>
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-## Security Risks
-
-1. Insecure Randomness
-2. Storage Exhaustion
-3. Insufficient Benchmarking
-4. Outdated Crates
-5. XCM Misconfiguration
-6. Unsafe Math
-7. Replay Issues
-8. Unbounded Decoding
-9. Verbosity Issues
-10. Inconsistent Error Handling
-
-</pba-col>
-</pba-cols>
-
----
-
-## Disclaimer
-
-> Apart from the mitigations suggested here, it is always important to **ensure a properly audit and intense testing**.
->
-> Specially, if your system handles real value assets, considering that if they are exploited, it could hurt their owners.
-
----
-
-## Insecure Randomness
-
----v
-
-### Challenge
-
-**On-chain randomness on any public, decentralized, and deterministic system like a blockchain is difficult!**
-
-<pba-cols>
-<pba-col>
-
-- Use of **weak cryptographic algorithms** or **insecure randomness** in the system can compromise the integrity of critical functionalities.
-- This could allow attackers to predict or manipulate outcomes of any feature that rely on secure randomness.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 450px" src="./img/cloudflare.webp" />
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Risk
-
-<pba-cols>
-<pba-col>
-
-- Manipulation or prediction of critical functionalities, leading to compromised integrity and security.
-- Potential for attackers to gain an unfair advantage, undermining trust in the system.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 350px" src="./img/hack-casino.webp" />
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Case Study - Randomness Collective Flip
-
-- Randomness Collective Flip pallet from Substrate provides a random function that generates low-influence random values based on the block hashes from the previous 81 blocks.
-- Low-influence randomness can be useful when defending against relatively weak adversaries.
-- Using this pallet as a randomness source is advisable primarily in low-security situations like testing.
-
----v
-
-### Case Study - Randomness Collective Flip
-
-<div style="font-size: smaller">
-
-```rust [1-12|14-36]
-/// substrate/frame/insecure-randomness-collective-flip/src/lib.rs
-fn on_initialize(block_number: BlockNumberFor<T>) -> Weight {
-    let parent_hash = <frame_system::Pallet<T>>::parent_hash();
-    /// ...
-    <RandomMaterial<T>>::mutate(|ref mut values| {
-        if values.try_push(parent_hash).is_err() {
-            let index = block_number_to_index::<T>(block_number);
-            values[index] = parent_hash;
-        }
-    });
-    /// ...
-}
-/// ...
-fn random(subject: &[u8]) -> (T::Hash, BlockNumberFor<T>) {
-    let block_number = <frame_system::Pallet<T>>::block_number();
-    let index = block_number_to_index::<T>(block_number);
-    /// ...
-    let hash_series = <RandomMaterial<T>>::get();
-    let seed = if !hash_series.is_empty() {
-        // Always the case after block 1 is initialized.
-        hash_series
-            .iter()
-            .cycle()
-            .skip(index)
-          // RANDOM_MATERIAL_LEN = 81
-            .take(RANDOM_MATERIAL_LEN as usize)
-            .enumerate()
-            .map(|(i, h)| 
-              (i as i8, subject, h)
-              .using_encoded(T::Hashing::hash)
-          ).triplet_mix()
-    } else {
-        T::Hash::default()
-    };
-    (seed, block_number.saturating_sub(RANDOM_MATERIAL_LEN.into()))
-}
-```
-
-</div>
-
----v
-
-### Case Study - VRF
-
-- There are two main secure approaches to blockchain randomness in production today: [RANDAO](https://github.com/randao/randao) and VRF. **Polkadot uses VRF**.
-
-  > **VRF**: mathematical operation that takes some input and produces a random number along with a proof of authenticity that this random number was generated by the submitter.
-
-- With VRF, the proof can be verified by any challenger to ensure the random number generation is valid.
-
----v
-
-### Case Study - VRF
-
-<div style="font-size: smaller">
-
-- Babe pallet randomness options
-  1. Randomness From Two Epochs Ago
-     - Use Case: For consensus protocols that need finality.
-     - Timing: Uses data from two epochs ago.
-     - Risks: Bias if adversaries controlling block production at specific times.
-  2. Randomness From One Epoch Ago (**Polkadot Parachain Auctions**)
-     - Use Case: For on-chain actions that don't need finality.
-     - Timing: Uses data from the previous epoch.
-     - Risks: Bias if adversaries control block prod. at end/start of an epoch.
-  3. Current Block Randomness
-     - Use Case: For actions that need fresh randomness.
-     - Timing: Appears fresh but is based on older data.
-     - Risks: Weakest form, bias if adversaries don't announce blocks.
-- Randomness is affected by other inputs, like external randomness sources.
-
-</div>
-
----v
-
-### Case Study - VRF
-
-<div style="font-size: smaller">
-
-```rust [1-19|21-36|37-46]
-/// substrate/frame/babe/src/lib.rs
-/// Compute randomness for a new epoch. rho is the concatenation of all
-/// VRF outputs in the prior epoch.
-/// an optional size hint as to how many VRF outputs there were may be provided.
-fn compute_randomness(
-	last_epoch_randomness: BabeRandomness,
-	epoch_index: u64,
-	rho: impl Iterator<Item = BabeRandomness>,
-	rho_size_hint: Option<usize>,
-) -> BabeRandomness {
-	let mut s = Vec::with_capacity(
-      40 + rho_size_hint.unwrap_or(0) * RANDOMNESS_LENGTH);
-	s.extend_from_slice(&last_epoch_randomness);
-	s.extend_from_slice(&epoch_index.to_le_bytes());
-	for vrf_output in rho {
-		s.extend_from_slice(&vrf_output[..]);
-	}
-	sp_io::hashing::blake2_256(&s)
-}
-/// ...
-/// Call this function exactly once when an epoch changes, to update the
-/// randomness. Returns the new randomness.
-fn randomness_change_epoch(next_epoch_index: u64) -> BabeRandomness {
-    let this_randomness = NextRandomness::<T>::get();
-    let segment_idx: u32 = SegmentIndex::<T>::mutate(|s| sp_std::mem::replace(s, 0));
-    // overestimate to the segment being full.
-    let rho_size = (segment_idx.saturating_add(1) * UNDER_CONSTRUCTION_SEGMENT_LENGTH) as usize;
-    let next_randomness = compute_randomness(
-        this_randomness,
-        next_epoch_index,
-        (0..segment_idx).flat_map(|i| UnderConstruction::<T>::take(&i)), // VRF (From Digest)
-        Some(rho_size),
-    );
-    NextRandomness::<T>::put(&next_randomness);
-    this_randomness // -> Randomness::<T>::put(..);
-}
-/// substrate/frame/babe/src/randomness.rs
-impl<T: Config> RandomnessT<T::Hash, BlockNumberFor<T>> for RandomnessFromOneEpochAgo<T> {
-  fn random(subject: &[u8]) -> (T::Hash, BlockNumberFor<T>) {
-    let mut subject = subject.to_vec();
-    subject.reserve(RANDOMNESS_LENGTH);
-    subject.extend_from_slice(&NextRandomness::<T>::get()[..]); 
-
-    (T::Hashing::hash(&subject[..]), EpochStart::<T>::get().1)
-  }
-}
-```
-
-</div>
-
----v
-
-### Mitigation
-
-- All validators can be trusted
-
-  > VRF
-
-- Not all validators can be trusted
-  - Profit from exploiting randomness is substantially more than the profit from building a block
-
-    > Trusted solution (Oracles, MPC, Commit-Reval, etc.)
-
-  - Otherwise
-
-    > VRF
-
----v
-
-### Takeaways
-
-- On-chain randomness is difficult.
-- Polkadot uses VRF (i.e. Auctions).
-- On VRF (Pallet BABE), randomness can only be manipulated by the block producers. If all nodes are trusted, then the randomness can be trusted too.
-- You can also inject trusted randomness into the chain via a trusted oracle.
-- **Don’t use Randomness Collective Flip in production!**
-
----
-
-## Storage Exhaustion
-
----v
-
-### Challenge
-
-**Your chain can run out of storage!**
-
-<pba-cols>
-<pba-col left>
-
-- Inadequate charging mechanism for on-chain storage, which allows users to occupy storage space without paying the appropriate deposit fees.
-- This loophole can be exploited by malicious actors to fill up the blockchain storage cheaply, making it unsustainable to run a node and affecting network performance.
-
-</pba-col>
-<pba-col right>
-
-<img rounded style="height: 550px" src="./img/low-disk-space.webp" />
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Risk
-
-- Unsustainable growth in blockchain storage, leading to increased costs and potential failure for node operators.
-- Increased susceptibility to DoS attacks that exploit the inadequate storage deposit mechanism to clutter the blockchain.
-
----v
-
-### Case Study - Existential Deposit
-
-- If an account's balance falls below the existential deposit, the account is reaped, and its data is deleted to save storage space.
-- Existential deposits are required to optimize storage. The absence or undervaluation of existential deposits can lead to DoS attacks.
-- The cost of permanent storage is generally not accounted for in the weight calculation for extrinsics, making it possible for an attacker to fill up the blockchain storage by distributing small amounts of native tokens to many accounts.
-
----v
-
-### Case Study - Existential Deposit
-
-```rust [1-10|12-20]
-/// relay/polkadot/constants/src/lib.rs
-/// Money matters.
-pub mod currency {
-  /// The existential deposit.
-  pub const EXISTENTIAL_DEPOSIT: Balance = 100 * CENTS;
-  /// ...
-  pub const UNITS: Balance = 10_000_000_000;
-  pub const DOLLARS: Balance = UNITS; // 10_000_000_000
-  pub const CENTS: Balance = DOLLARS / 100; // 100_000_000
-}
-
-/// relay/polkadot/src/lib.rs
-parameter_types! {
-  pub const ExistentialDeposit: Balance = EXISTENTIAL_DEPOSIT;
-  /// ...
-}
-impl pallet_balances::Config for Runtime {
-  type ExistentialDeposit = ExistentialDeposit;
-  /// ...
-}
-```
-
----v
-
-### Case Study - General Storage Usage System
-
-<img rounded style="height: 550px" src="./img/general-storage-usage-system-issue.webp" />
-
-[Issue in Polkadot SDK](https://github.com/paritytech/polkadot-sdk/issues/207)
-
----v
-
-### Case Study - NFT Pallet Manual Deposit
-
-<div style="font-size: smaller">
-
-```rust [1-22|24-49|29-30]
-/// substrate/frame/nfts/src/lib.rs
-/// ...
-/// Origin must be either `ForceOrigin` or Signed and the sender should be the Admin of the
-/// `collection`.
-///
-/// If the origin is Signed, then funds of signer are reserved according to the formula:
-/// `MetadataDepositBase + DepositPerByte * data.len` taking into
-/// account any already reserved funds.
-/// ...
-#[pallet::call_index(24)]
-#[pallet::weight(T::WeightInfo::set_metadata())]
-pub fn set_metadata(
-  origin: OriginFor<T>,
-  collection: T::CollectionId,
-  item: T::ItemId,
-  data: BoundedVec<u8, T::StringLimit>,
-) -> DispatchResult {
-  let maybe_check_origin = T::ForceOrigin::try_origin(origin)
-    .map(|_| None)
-    .or_else(|origin| ensure_signed(origin).map(Some).map_err(DispatchError::from))?;
-  Self::do_set_item_metadata(maybe_check_origin, collection, item, data, None)
-}
-
-/// substrate/frame/nfts/src/features/attributes.rs
-fn do_set_item_metadata {
-  /// ...
-  let mut deposit = Zero::zero();
-  if collection_config.is_setting_enabled(CollectionSetting::DepositRequired) 
-    // Next line was added to fix the issue 
-    || namespace != AttributeNamespace::CollectionOwner
-  {
-    deposit = T::DepositPerByte::get()
-      .saturating_mul(((data.len()) as u32).into())
-      .saturating_add(T::MetadataDepositBase::get());
-  }
-  
-  let depositor = maybe_depositor.clone().unwrap_or(collection_details.owner.clone());
-  let old_depositor = old_deposit.account.unwrap_or(collection_details.owner.clone());
-  
-  if depositor != old_depositor {
-    T::Currency::unreserve(&old_depositor, old_deposit.amount);
-    T::Currency::reserve(&depositor, deposit)?;
-  } else if deposit > old_deposit.amount {
-    T::Currency::reserve(&depositor, deposit - old_deposit.amount)?;
-  } else if deposit < old_deposit.amount {
-    T::Currency::unreserve(&depositor, old_deposit.amount - deposit);
-  }
-  /// ...
-}
-```
-
-</div>
-
-[Commit](https://github.com/paritytech/substrate/commit/e907e15e0bda28b5c5db90e6a0bce3393fbc59f1)
-
----v
-
-### Mitigation
-
-- **Existential Deposit:** ensure a value similar to the defined by the relay chain.
-- **Storage Deposit:** implement a good logic similar to the following:
-
-<div style="font-size: smaller">
-
-```rust
-// Deposit calculation (bytes * deposit_per_byte + deposit_base)
-let mut deposit = T::DepositPerByte::get()
-        .saturating_mul(((key.len() + value.len()) as u32).into())
-        .saturating_add(T::DepositBase::get());
-
-// Deposit reserve (dynamic data size)
-if old_deposit.account.is_some() && 
-   old_deposit.account != Some(origin.clone()) {
-    T::Currency::unreserve(
-      &old_deposit.account.unwrap(), old_deposit.amount);
-    T::Currency::reserve(&origin, deposit)?;
-} else if deposit > old_deposit.amount {
-    T::Currency::reserve(&origin, deposit - old_deposit.amount)?;
-} else if deposit < old_deposit.amount {
-    T::Currency::unreserve(&origin, old_deposit.amount - deposit);
-}
-```
-
-</div>
-
----v
-
-### Takeaways
-
-- Always explicitly require a deposit for on-chain storage (in the form of Reserved Balance).
-- Deposit is returned to the user when the user removes the data from the chain.
-- Ensure the existential deposit is greater than N. To determine N you can start from values similar to relay chain and monitor users activity.
-- If possible, limit the amount of data that a pallet can have. Otherwise, ensure some friction (reserve deposit) in the storage usage.
-
----
-
-## Insufficient Benchmarking
-
----v
-
-### Challenge
-
-**Benchmarking can be a difficult task...**
-
-<pba-cols>
-<pba-col>
-
-- Incorrect or missing benchmarking can lead to overweight blocks, causing network congestion and affecting the overall performance of the blockchain.
-- This can happen when the computational complexity or storage access is underestimated, leading to inaccurate weight for extrinsics.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 550px" src="./img/benchmarking.webp" />
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Risk
-
-<pba-cols>
-<pba-col>
-
-- **Overweight extrinsics** can slow down the network.
-
-- Leads to delays in transaction processing and affects UX.
-
-</pba-col>
-<pba-col>
-
-- **Underweight extrinsics** can be exploited to spam the network.
-
-- Leads to a potential Denial of Service (DoS) attack.
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Case Study - Benchmark Input Length - Issue
-
-<div style="font-size: smaller">
-
-```rust [0|9-10|27-29]
-/// substrate/frame/remark/src/lib.rs (modified)
-#[frame_support::pallet]
-pub mod pallet {
-	/// ...
-	#[pallet::call]
-	impl<T: Config> Pallet<T> {
-		/// Index and store data off chain.
-		#[pallet::call_index(0)]
-		#[pallet::weight(T::WeightInfo::store())]
-		pub fn store(origin: OriginFor<T>, remark: Vec<u8>) -> DispatchResultWithPostInfo {
-			ensure!(!remark.is_empty(), Error::<T>::Empty);
-			let sender = ensure_signed(origin)?;
-			let content_hash = sp_io::hashing::blake2_256(&remark);
-			let extrinsic_index = <frame_system::Pallet<T>>::extrinsic_index()
-				.ok_or_else(|| Error::<T>::BadContext)?;
-			sp_io::transaction_index::index(extrinsic_index, remark.len() as u32, content_hash);
-			Self::deposit_event(Event::Stored { sender, content_hash: content_hash.into() });
-			Ok(().into())
-		}
-	}
-	/// ...
-}
-
-
-/// substrate/frame/remark/src/benchmarking.rs (modified)
-benchmarks! {
-	store {
-		let caller: T::AccountId = whitelisted_caller();
-	}: _(RawOrigin::Signed(caller.clone()), vec![])
-	verify {
-		assert_last_event::<T>(Event::Stored { sender: caller, content_hash: sp_io::hashing::blake2_256(&vec![0u8; l as usize]).into() }.into());
-	}
-
-	impl_benchmark_test_suite!(Remark, crate::mock::new_test_ext(), crate::mock::Test);
-}
-```
-
-</div>
-
----v
-
-### Case Study - Benchmark Input Length - Mitigation
-
-<div style="font-size: smaller">
-
-```rust [0|9-10|27-30]
-/// substrate/frame/remark/src/lib.rs
-#[frame_support::pallet]
-pub mod pallet {
-	/// ...
-	#[pallet::call]
-	impl<T: Config> Pallet<T> {
-		/// Index and store data off chain.
-		#[pallet::call_index(0)]
-		#[pallet::weight(T::WeightInfo::store(remark.len() as u32))]
-		pub fn store(origin: OriginFor<T>, remark: Vec<u8>) -> DispatchResultWithPostInfo {
-			ensure!(!remark.is_empty(), Error::<T>::Empty);
-			let sender = ensure_signed(origin)?;
-			let content_hash = sp_io::hashing::blake2_256(&remark);
-			let extrinsic_index = <frame_system::Pallet<T>>::extrinsic_index()
-				.ok_or_else(|| Error::<T>::BadContext)?;
-			sp_io::transaction_index::index(extrinsic_index, remark.len() as u32, content_hash);
-			Self::deposit_event(Event::Stored { sender, content_hash: content_hash.into() });
-			Ok(().into())
-		}
-	}
-	/// ...
-}
-
-
-/// substrate/frame/remark/src/benchmarking.rs
-benchmarks! {
-	store {
-		let l in 1 .. 1024*1024;
-		let caller: T::AccountId = whitelisted_caller();
-	}: _(RawOrigin::Signed(caller.clone()), vec![0u8; l as usize])
-	verify {
-		assert_last_event::<T>(Event::Stored { sender: caller, content_hash: sp_io::hashing::blake2_256(&vec![0u8; l as usize]).into() }.into());
-	}
-
-	impl_benchmark_test_suite!(Remark, crate::mock::new_test_ext(), crate::mock::Test);
-}
-```
-
-</div>
-
----v
-
-### Mitigation
-
-- Run benchmarks using the worst case scenario conditions.
-
-  > For example, more amount of DB reads and write that could ever happen in a extrinsic.
-
-- Primary goal is to keep the runtime safe.
-- Secondary goal is to be as accurate as possible to maximize throughput.
-- For non-hard deadline code use **metering**.
-
----v
-
-### Takeaways
-
-- Benchmarking ensures that parachain’s users are not using resources beyond what is available and expected for our network.
-- Weight is used to track consumption of limited blockchain resources based on Execution Time (Reference Hardware) and Size of Data required to create a Merkle Proof.
-- 1 second of compute on different computers allows for different amounts of computation.
-
----
-
-## Outdated Crates
-
----v
-
-### Challenge
-
-**Dependencies can become a nightmare!**
-
-<pba-cols>
-<pba-col>
-
-- Using outdated or known vulnerable components, such as pallets or libraries, in a Substrate runtime can expose the system to broad range of security risks and exploits.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 500px" src="./img/dependencies.webp" />
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Risk
-
-- Exposure to known vulnerabilities that could be exploited by attackers.
-- Compromised network integrity and security, leading to potential data breaches or financial loss.
-
----v
-
-### Case Study - Serde Precompiled Binary
-
-<pba-cols>
-<pba-col>
-
-- Polkadot uses `serde` with the `derive` feature as a dependency.
-- **Issue**: Serde developers decided to ships it as a precompiled binary. [Article](https://www.bleepingcomputer.com/news/security/rust-devs-push-back-as-serde-project-ships-precompiled-binaries/).
-- **Mitigation**: Dependency was fixed to a version that doesn't include the precompiled binary.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 450px" src="./img/serde.webp" />
-
-</pba-col>
-</pba-cols>
-
-**A trustless system, such as Polkadot, can't blindly trust binaries.**
-
----v
-
-### Mitigation
-
-- Always uses the latest stable version of Polkadot, Substrate, Cumulus, and any other third party crate.
-- If possible, avoid using too many crates.
-- Use tools such as `cargo audit` or `cargo vet` to monitor the state of your system’s dependencies.
-- Don't use dependencies that include precompiled binaries.
-
----v
-
-### Takeaways
-
-- Outdated crates can lead to vulnerabilities in your system even if the crate don’t have a vulnerability.
-- Outdated crates can contain known vulnerabilities that could be easily exploited in your system.
-- Don’t use the latest version of a crate (in production) until it is declared as stable.
-
----
-
-## XCM Misconfiguration
-
----v
-
-### Challenge
-
-**Configuring correctly XCM needs a lot of attention!**
-
-- XCM needs to be configured through different pallets and configs.
-- Determining the access control to the XCM pallet and the incoming queues needs to be done carefully.
-- For new parachains, it is difficult to determine which XCM messages are needed and which are not.
-- If the config is not correctly setup the chain could be vulnerable to attacks, become spam targets if incoming XCM messages are not handled as untrusted and/or sanitized properly, or even be used as a **bridge** to attack other parachains by not enforcing a good Access Control in **send** operations.
-
----v
-
-### Risk
-
-- Unauthorized manipulation of the blockchain state, compromising the network's integrity.
-- Execution of unauthorized transactions, leading to potential financial loss.
-- Be used as an attack channel to parachains.
-
----v
-
-### Case Study - Rococo Bridge Hub - Description
-
-- The `MessageExporter` type (`BridgeHubRococoOrBridgeHubWococoSwitchExporter`) in the Rococo's Bridge Hub XcmConfig was using the `unimplemented!()` macro in [`validate`](https://github.com/paritytech/polkadot-sdk/blob/f6560c2b7226ea756ade18df42018c3eaf3be2e0/cumulus/parachains/runtimes/bridge-hubs/bridge-hub-rococo/src/xcm_config.rs#L391) and `deliver` methods, what is equivalent to the `panic!()` macro. This was exposing the Rococo Bridge Hub runtime to non-skippable panic reachable by any parachain allowed to send messages to the Rococo Bridge Hub.
-- This issue was trivial to execute for anyone that can send messages to the Bridge Hub, as the only needed is to send a valid XCM message that includes an ExportMessage instruction trying to bridge to a network that is not implemented.
-
----v
-
-### Case Study - Rococo Bridge Hub - Issue
-
-```rust [0|14-21|22-29|30]
-/// cumulus/parachains/runtimes/bridge-hubs/bridge-hub-rococo/src/xcm_config.rs
-pub struct BridgeHubRococoOrBridgeHubWococoSwitchExporter;
-impl ExportXcm for BridgeHubRococoOrBridgeHubWococoSwitchExporter {
-	type Ticket = (NetworkId, (sp_std::prelude::Vec<u8>, XcmHash));
-
-	fn validate(
-		network: NetworkId,
-		channel: u32,
-		universal_source: &mut Option<InteriorMultiLocation>,
-		destination: &mut Option<InteriorMultiLocation>,
-		message: &mut Option<Xcm<()>>,
-	) -> SendResult<Self::Ticket> {
-		match network {
-			Rococo => ToBridgeHubRococoHaulBlobExporter::validate(
-				network,
-				channel,
-				universal_source,
-				destination,
-				message,
-			)
-			.map(|result| ((Rococo, result.0), result.1)),
-			Wococo => ToBridgeHubWococoHaulBlobExporter::validate(
-				network,
-				channel,
-				universal_source,
-				destination,
-				message,
-			)
-			.map(|result| ((Wococo, result.0), result.1)),
-			_ => unimplemented!("Unsupported network: {:?}", network),
-		}
-```
-
----v
-
-### Case Study - Rococo Bridge Hub - XCM Config
-
-<div style="font-size: smaller">
-
-```rust [0|30|7|40-59|48-50|13|61-88|71-73]
-/// cumulus/parachains/runtimes/bridge-hubs/bridge-hub-rococo/src/xcm_config.rs
-pub struct XcmConfig;
-impl xcm_executor::Config for XcmConfig {
-	type RuntimeCall = RuntimeCall;
-	type XcmSender = XcmRouter;
-	type AssetTransactor = CurrencyTransactor;
-	type OriginConverter = XcmOriginToTransactDispatchOrigin;
-	// BridgeHub does not recognize a reserve location for any asset. Users must teleport Native
-	// token where allowed (e.g. with the Relay Chain).
-	type IsReserve = ();
-	type IsTeleporter = TrustedTeleporters;
-	type UniversalLocation = UniversalLocation;
-	type Barrier = Barrier;
-	type Weigher = WeightInfoBounds<
-		crate::weights::xcm::BridgeHubRococoXcmWeight<RuntimeCall>,
-		RuntimeCall,
-		MaxInstructions,
-	>;
-	type Trader =
-		UsingComponents<WeightToFee, TokenLocation, AccountId, Balances, ToStakingPot<Runtime>>;
-	type ResponseHandler = PolkadotXcm;
-	type AssetTrap = PolkadotXcm;
-	type AssetLocker = ();
-	type AssetExchanger = ();
-	type AssetClaims = PolkadotXcm;
-	type SubscriptionService = PolkadotXcm;
-	type PalletInstancesInfo = AllPalletsWithSystem;
-	type MaxAssetsIntoHolding = MaxAssetsIntoHolding;
-	type FeeManager = XcmFeesToAccount<Self, WaivedLocations, AccountId, TreasuryAccount>;
-	type MessageExporter = BridgeHubRococoOrBridgeHubWococoSwitchExporter;
-	type UniversalAliases = Nothing;
-	type CallDispatcher = WithOriginFilter<SafeCallFilter>;
-	type SafeCallFilter = SafeCallFilter;
-	type Aliasers = Nothing;
-}
-
-/// This is the type we use to convert an (incoming) XCM origin into a local `Origin` instance,
-/// ready for dispatching a transaction with Xcm's `Transact`. There is an `OriginKind` which can
-/// biases the kind of local `Origin` it will become.
-pub type XcmOriginToTransactDispatchOrigin = (
-	// Sovereign account converter; this attempts to derive an `AccountId` from the origin location
-	// using `LocationToAccountId` and then turn that into the usual `Signed` origin. Useful for
-	// foreign chains who want to have a local sovereign account on this chain which they control.
-	SovereignSignedViaLocation<LocationToAccountId, RuntimeOrigin>,
-	// Native converter for Relay-chain (Parent) location; will convert to a `Relay` origin when
-	// recognized.
-	RelayChainAsNative<RelayChainOrigin, RuntimeOrigin>,
-	// Native converter for sibling Parachains; will convert to a `SiblingPara` origin when
-	// recognized.
-	SiblingParachainAsNative<cumulus_pallet_xcm::Origin, RuntimeOrigin>,
-	// Superuser converter for the Relay-chain (Parent) location. This will allow it to issue a
-	// transaction from the Root origin.
-	ParentAsSuperuser<RuntimeOrigin>,
-	// Native signed account converter; this just converts an `AccountId32` origin into a normal
-	// `RuntimeOrigin::Signed` origin of the same 32-byte value.
-	SignedAccountId32AsNative<RelayNetwork, RuntimeOrigin>,
-	// Xcm origins can be represented natively under the Xcm pallet's Xcm origin.
-	XcmPassthrough<RuntimeOrigin>,
-);
-
-pub type Barrier = TrailingSetTopicAsId<
-	DenyThenTry<
-		DenyReserveTransferToRelayChain,
-		(
-			// Allow local users to buy weight credit.
-			TakeWeightCredit,
-			// Expected responses are OK.
-			AllowKnownQueryResponses<PolkadotXcm>,
-			WithComputedOrigin<
-				(
-					// If the message is one that immediately attempts to pay for execution,
-					//then allow it.
-					AllowTopLevelPaidExecutionFrom<Everything>,
-					// Parent, its pluralities (i.e. governance bodies) and relay treasury
-					// pallet get free execution.
-					AllowExplicitUnpaidExecutionFrom<(
-						ParentOrParentsPlurality,
-						Equals<RelayTreasuryLocation>,
-					)>,
-					// Subscriptions for version tracking are OK.
-					AllowSubscriptionsFrom<ParentOrSiblings>,
-				),
-				UniversalLocation,
-				ConstU32<8>,
-			>,
-		),
-	>,
->;
-```
-
-</div>
-
----v
-
-### Mitigation
-
-- Constantly, verify all your configs and compare with other chains.
-- In XMC pallet, limit usage **execute** and **send** until XCM security guarantees can be ensured.
-- In XCM executor, ensure a correct access control in your `XcmConfig`:
-  - Only trusted sources can be allowed. Filter origins with `OriginConverter`.
-  - Only the specific messages structures your parachain needs to receive can be accepted. Filter message structures with `Barrier` (general), `SafeCallFilter` (transact), `IsReserve` (reserve), `IsTeleporter` (teleport), `MessageExporter` (export), `XcmSender` (send), etc.
-- In XCMP queue, ensure only trusted channels are open.
-
----v
-
-### Takeaways
-
-- XCM development and audits are still going on, so its security guarantees can be ensured at the moment.
-- Allowing any user to use execute and send can have a serious impact on your parachain.
-- Incoming XCMs need to be handled as untrusted and sanitized properly.
-- Insufficient Access Control in your parachain can enable bad actors to attack other parachains through your system.
-
----
-
-## Unsafe Math
-
----v
-
-### Challenge
-
-- Unsafe math operations in the codebase can lead to integer overflows/underflows, divisions by zero, conversion truncation/overflow and incorrect end results which can be exploited by attackers to manipulate calculations and gain an unfair advantage.
-- This involve mainly the usage of primitive arithmetic operations.
-
-<img rounded style="height: 300px" src="./img/overflow.webp" />
-
----v
-
-### Risk
-
-- Manipulation of account balances, leading to unauthorized transfers or artificial inflation of balances.
-- Potential disruption of network functionalities that rely on accurate arithmetic calculations.
-- Incorrect calculations, leading to unintended consequences like incorrect account balances or transaction fees..
-- Potential for attackers to exploit the vulnerability to manipulate outcomes in their favor.
-
----v
-
-### Case Study - Frontier Balances - Description
-
-- Frontier's [CVE-2022-31111](https://github.com/paritytech/frontier/security/advisories/GHSA-hc8w-mx86-9fcj) disclosure describes the issues found in the process of converting balances from EVM to Substrate, where the pallet didn't handle it right, causing the transferred amount to appear differently leading to a possible overflow.
-- This is risky for two reasons:
-  1. It could lead to wrong calculations, like messed-up account balances.
-  2. People with bad intentions could use this error to get unfair advantages.
-- To fix this, it's important to double-check how these conversions are done to make sure the numbers are accurate.
-
----v
-
-### Case Study - Frontier Balances - Issue
-
-<div style="font-size: smaller">
-
-```rust [0|10|16]
-/// substrate/frame/evm/src/lib.rs
-#[pallet::genesis_build]
-	impl<T: Config> GenesisBuild<T> for GenesisConfig {
-		fn build(&self) {
-			for (address, account) in &self.accounts {
-				let account_id = T::AddressMapping::into_account_id(*address);
-
-				// ASSUME: in one single EVM transaction, the nonce will not increase more than
-				// `u128::max_value()`.
-				for _ in 0..account.nonce.low_u128() {
-					frame_system::Pallet::<T>::inc_account_nonce(&account_id);
-				}
-
-				T::Currency::deposit_creating(
-					&account_id,
-					account.balance.low_u128().unique_saturated_into(),
-				);
-```
-
-</div>
-
----v
-
-### Case Study - Frontier Balances - Mitigation
-
-<div style="font-size: smaller">
-
-```rust [0|15-18|24]
-/// substrate/frame/evm/src/lib.rs
-#[pallet::genesis_build]
-  impl<T: Config> GenesisBuild<T> for GenesisConfig
-  where
-    U256: UniqueSaturatedInto<BalanceOf<T>>,
-  {
-    fn build(&self) {
-      const MAX_ACCOUNT_NONCE: usize = 100;
-
-      for (address, account) in &self.accounts {
-        let account_id = T::AddressMapping::into_account_id(*address);
-
-        // ASSUME: in one single EVM transaction, the nonce will not increase more than
-        // `u128::max_value()`.
-        for _ in 0..min(
-          MAX_ACCOUNT_NONCE,
-          UniqueSaturatedInto::<usize>::unique_saturated_into(account.nonce),
-        ) {
-          frame_system::Pallet::<T>::inc_account_nonce(&account_id);
-        }
-
-        T::Currency::deposit_creating(
-          &account_id, 
-          account.balance.unique_saturated_into()
-        );
-```
-
-</div>
-
----v
-
-### Mitigation
-
-- Arithmetic
-  - Simple solution but (sometimes) more costly
-
-    > Use checked/saturated functions like `checked_div`.
-
-  - Complex solution but (sometimes) less costly
-
-    > Validate before executing primitive functions. For example: balance > transfer_amount
-
-- Conversions
-  - Avoid downcasting values. Otherwise, use methods like `unique_saturated_into` instead of methods like `low_u64`.
-  - **Your system should be designed to avoid downcasting!**
-
----v
-
-### Takeaways
-
-- While testing pallets, system will panic (crash) if primitive arithmetic operation leads to overflow/underflow or division by zero.
-  However, on release (production), pallets will not panic on overflow.
-  Always ensure no unexpected overflow/underflow can happen.
-- Checked operations use slightly more computational power than primitive operations.
-- While testing pallets, system will panic (crash) if conversion leads to overflow/underflow or truncation.
-  However, on release (production), pallets will not panic.
-  Always ensure no unexpected overflow/underflow or truncation can happen.
-- In a conversion, smaller the new type, more chances a overflow/underflow or truncation can happen.
-
----
-
-## Replay Issues
-
----v
-
-### Challenge
-
-<pba-cols>
-<pba-col>
-
-- Replay issues, most commonly arising from unsigned extrinsics, can lead to spamming and, in certain scenarios, double-spending attacks.
-- This happens when nonces are not managed correctly, making it possible for transactions to be replayed.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 500px" src="./img/nonce.webp" />
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Risk
-
-- Spamming the network with repeated transactions, leading to congestion and reduced performance.
-- Potential for double-spending attacks, which can compromise the integrity of the blockchain.
-
----v
-
-### Case Study - Frontier STF - Description
-
-- [CVE-2021-41138](https://github.com/paritytech/frontier/security/advisories/GHSA-vj62-g63v-f8mf) describes the security issues arose from the changes made in [Frontier #482](https://github.com/paritytech/frontier/pull/482). Before this update, the function `validate_unsigned` was used to check if a transaction was valid. This function was part of the **State Transition Function** (STF), which is important when a block is being made. After the update, a new function validate_self_contained does the job but it's not part of the STF. This means a malicious validator could submit invalid transactions, and even reuse transactions from a different chain.
-- In the following sample from [Frontier](https://github.com/paritytech/frontier/blob/0a8e696fdfb9ce73a7f99941a2f2ec22eefd4f38/frame/ethereum/src/lib.rs#L249) is possible to observe how the `do_transact` function was used before the update, where the `validate_self_contained` was not used.
-- In a later [commit](https://github.com/paritytech/frontier/commit/146bb48849e5393004be5c88beefe76fdf009aba), this is patch by adding the validations on block production. Between the changes can be observe that replace of `do_transact` for `validate_transaction_in_block` that contains the logic to validate a transaction that was previously in `validate_self_contained`.
-
----v
-
-### Case Study - Frontier Balances - Issue
-
-<div style="font-size: smaller">
-
-```rust [0|]
-fn on_initialize(_: T::BlockNumber) -> Weight {
-  Pending::<T>::kill();
-  // If the digest contain an existing ethereum block(encoded as PreLog), If contains,
-  // execute the imported block firstly and disable transact dispatch function.
-  if let Ok(log) = fp_consensus::find_pre_log(&frame_system::Pallet::<T>::digest()) {
-    let PreLog::Block(block) = log;
-    for transaction in block.transactions {
-      let source = Self::recover_signer(&transaction).expect(
-        "pre-block transaction signature invalid; the block cannot be built",
-      );
-
-      Self::do_transact(source, transaction).expect(
-        "pre-block transaction verification failed; the block cannot be built",
-      );
-    }
-  }
-
-  0
-}
-```
-
-</div>
-
----v
-
-### Case Study - Frontier Balances - Mitigation
-
-<div style="font-size: smaller">
-
-```rust [0|12-14|32-39]
-fn on_initialize(_: T::BlockNumber) -> Weight {
-  Pending::<T>::kill();
-  // If the digest contain an existing ethereum block(encoded as PreLog), If contains,
-  // execute the imported block firstly and disable transact dispatch function.
-  if let Ok(log) = fp_consensus::find_pre_log(&frame_system::Pallet::<T>::digest()) {
-    let PreLog::Block(block) = log;
-    for transaction in block.transactions {
-      let source = Self::recover_signer(&transaction).expect(
-        "pre-block transaction signature invalid; the block cannot be built",
-      );
-
-      Self::validate_transaction_in_block(source, &transaction).expect(
-        "pre-block transaction verification failed; the block cannot be built",
-      );
-      Self::apply_validated_transaction(source, transaction).expect( // do_transact
-        "pre-block transaction execution failed; the block cannot be built",
-      );
-    }
-  }
-
-  0
-}
-
-// Common controls to be performed in the same way by the pool and the
-// State Transition Function (STF).
-// This is the case for all controls except those concerning the nonce.
-fn validate_transaction_common(
-  origin: H160,
-  transaction: &Transaction,
-) -> Result<U256, TransactionValidityError> {
-  // ...
-  if let Some(chain_id) = transaction.signature.chain_id() {
-    if chain_id != T::ChainId::get() {
-      return Err(InvalidTransaction::Custom(
-        TransactionValidationError::InvalidChainId as u8,
-      )
-      .into());
-    }
-  }
-  // ...
-}
-```
-
-</div>
-
----v
-
-### Mitigation
-
-- Ensure that the data your system is receiving from untrustworthy sources:
-  - Can’t be re-used by implementing a nonces mechanism.
-  - Is intended for your system by checking any identification type like ID, hashes, etc.
-
----v
-
-### Takeaways
-
-- Replay issues can lead to serious damage.
-- Even if the chain ensure a runtime transaction can’t be replayed, external actors could replay a similar output by passing similar inputs if the they are not correctly verified.
-
----
-
-## Unbounded Decoding
-
----v
-
-### Challenge
-
-<pba-cols>
-<pba-col>
-
-- Decoding objects without a nesting depth limit can lead to stack exhaustion, making it possible for attackers to craft highly nested objects that cause a stack overflow.
-- This can be exploited to disrupt the normal functioning of the blockchain network.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 350px" src="./img/recursion.webp" />
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Risk
-
-- Stack exhaustion, which can lead to network instability and crashes.
-- Potential for Denial of Service (DoS) attacks by exploiting the stack overflow vulnerability.
-
----v
-
-### Case Study - Whitelist Pallet - Description
-
-- In [Substrate #10159](https://github.com/paritytech/substrate/pull/10159), the `whitelist-pallet` was introduced. This pallet contains the extrinsic `dispatch_whitelisted_call` that allow to dispatch a previously whitelisted call.
-- In order to be dispatched, the call needs to be decoded, and this was being done with the decode method.
-- Auditors detected this method could lead to an stack overflow and suggested the developers to use decode_with_depth_limit to mitigate the issue.
-- Risk was limited due to the origin had specific restrictions, but if the issue is triggered, the resulting stack overflow could cause a whole block to be invalid and the chain could get stuck failing to produce new blocks.
-
----v
-
-### Case Study - Whitelist Pallet - Issue
-
-<div style="font-size: smaller">
-
-```rust [0|18-19]
-/// Remake of vulnerable whitelist pallet
-pub fn dispatch_whitelisted_call(
-    origin: OriginFor<T>,
-    call_hash: PreimageHash,
-    call_encoded_len: u32,
-    call_weight_witness: Weight,
-) -> DispatchResultWithPostInfo {
-    T::DispatchWhitelistedOrigin::ensure_origin(origin)?;
-
-    ensure!(
-        WhitelistedCall::<T>::contains_key(call_hash),
-        Error::<T>::CallIsNotWhitelisted,
-    );
-
-    let call = T::Preimages::fetch(&call_hash, Some(call_encoded_len))
-        .map_err(|_| Error::<T>::UnavailablePreImage)?;
-
-    let call = <T as Config>::RuntimeCall::decode(&mut &call[..])
-        .map_err(|_| Error::<T>::UndecodableCall)?;
-```
-
-</div>
-
----v
-
-### Case Study - Whitelist Pallet - Exploit PoC
-
-<div style="font-size: smaller">
-
-```rust [0|5-8|14-20|22-31|37-47]
-/// Remake of vulnerable whitelist pallet
-#[test]
-fn test_unsafe_dispatch_whitelisted_call_stack_overflow() {
-	new_test_ext().execute_with(|| {
-		let mut call = 
-			RuntimeCall::System(
-				frame_system::Call::remark_with_event { remark: vec![1] }
-			);
-		let mut call_weight = call.get_dispatch_info().weight;
-		let mut encoded_call = call.encode();
-		let mut call_encoded_len = encoded_call.len() as u32;
-		let mut call_hash = <Test as frame_system::Config>::Hashing::hash(&encoded_call[..]);
-
-		// The amount of nested calls to create
-		// This test will not crash as it the following value is less than minimum
-		// amount of calls to cause a stack overflow
-		let nested_calls = sp_api::MAX_EXTRINSIC_DEPTH;
-
-		// The following line to get a stack overflow error on decoding (pallet)
-		let nested_calls = nested_calls*4;
-
-		// Create the nested calls
-		for _ in 0..=nested_calls {
-			call = RuntimeCall::Whitelist(crate::Call::dispatch_whitelisted_call_with_preimage {
-				call: Box::new(call.clone()),
-			});
-			call_weight = call.get_dispatch_info().weight;
-			encoded_call = call.encode();
-			call_encoded_len = encoded_call.len() as u32;
-			call_hash = <Test as frame_system::Config>::Hashing::hash(&encoded_call[..]);
-		}
-
-		// Whitelist the call to being able to dispatch it
-		assert_ok!(Preimage::note(encoded_call.into()));
-		assert_ok!(Whitelist::whitelist_call(RuntimeOrigin::root(), call_hash));
-
-		// Send the call to be dispatched
-		// This will throw a stack overflow if the nested calls is too high
-		println!("Dispatching with {} nested calls", nested_calls);
-		assert_ok!(
-			Whitelist::dispatch_whitelisted_call(
-				RuntimeOrigin::root(),
-				call_hash,
-				call_encoded_len,
-				call_weight
-			),
-		);
-	});
-}
-```
-
-</div>
-
----v
-
-### Case Study - Whitelist Pallet - Exploit Results
-
-<img rounded style="height: 500px" src="./img/stack-overflow.webp" />
-
----v
-
-### Case Study - Whitelist Pallet - Mitigation
-
-<div style="font-size: smaller">
-
-```rust [0|18-22]
-/// Remake of vulnerable whitelist pallet
-pub fn dispatch_whitelisted_call(
-    origin: OriginFor<T>,
-    call_hash: PreimageHash,
-    call_encoded_len: u32,
-    call_weight_witness: Weight,
-) -> DispatchResultWithPostInfo {
-    T::DispatchWhitelistedOrigin::ensure_origin(origin)?;
-
-    ensure!(
-        WhitelistedCall::<T>::contains_key(call_hash),
-        Error::<T>::CallIsNotWhitelisted,
-    );
-
-    let call = T::Preimages::fetch(&call_hash, Some(call_encoded_len))
-        .map_err(|_| Error::<T>::UnavailablePreImage)?;
-
-    let call = 
-        <T as Config>::RuntimeCall::decode_all_with_depth_limit(
-            sp_io::MAX_EXTRINSIC_DEPTH,
-            &mut &call[..],
-        ).map_err(|_| Error::<T>::UndecodableCall)?;
-```
-
-</div>
-
----v
-
-### Mitigation
-
-- Use the `decode_with_depth_limit` method instead of `decode` method.
-- Use `decode_with_depth_limit` with a depth limit lower than the depth that can cause an stack overflow.
-
----v
-
-### Takeaways
-
-- Decoding untrusted objects can lead to stack overflow.
-- Stack overflow can lead to network instability and crashes.
-- Always ensure a maximum depth while decoding data in a pallet.
-
----
-
-## Verbosity Issues
-
----v
-
-### Challenge
-
-<pba-cols>
-<pba-col>
-
-- Lack of detailed logs from collators, nodes, or RPC can make it difficult to diagnose issues, especially in cases of crashes or network halts.
-- This lack of verbosity can hinder efforts to maintain system health and resolve issues promptly.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 400px" src="./img/logs.webp" />
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Risk
-
-- Difficulty in diagnosing and resolving system issues, leading to extended downtime.
-- Reduced ability to identify and mitigate security threats compromising network integrity.
-
----v
-
-### Case Study
-
-<pba-cols>
-<pba-col>
-
-- During [recent Kusama issue](https://kusama.polkassembly.io/referenda/263), the chain stopped block production for some hours.
-- Engineers needed to check all the logs to understand what caused it or what triggered the incident.
-- Logging system allowed them to detect that the cause was a dispute in a finalized block.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 500px" src="./img/kusama-incident.webp" />
-
-</pba-col>
-</pba-cols>
-
-- Consensus systems are complex and almost never halt, but when they do, it is difficult to recreate the scenario that led to it.
-- A good logging system can therefore help to reduce downtime.
-
----v
-
-### Mitigation
-
-- Regularly review logs to identify any suspicious activity, and determine if there is sufficient verbosity.
-- Implement logs in the critical parts of your pallets.
-- Implement dashboards to detect anomaly patterns in logs and metrics. A great example is Grafana that is used by some node maintainers to be aware of recent issues.
-
----v
-
-### Takeaways
-
-- Logs are extremely important to diagnose and resolve system issues.
-- Insufficient verbosity can lead to extended downtime.
-
----
-
-## Inconsistent Error Handling
-
----v
-
-### Challenge
-
-<pba-cols>
-<pba-col>
-
-- Errors/exceptions need to be handled consistently to avoid attack vectors in critical parts of the system.
-- While processing a collection of items, if one of them fails, the whole batch fails. This can be exploited by an attacker that wants to block the execution. This can become a critical problem if the processing is happening in a privileged extrinsic like a hook.
-
-</pba-col>
-<pba-col>
-
-<img rounded style="height: 600px" src="./img/inconsistent-error-handling.webp" />
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Risk
-
-- Privileged extrinsics Denial of Service (DoS).
-- Unexpected behavior in the system.
-
----v
-
-### Case Study - Decode Concatenated Data - Issue
-
-```rust [0|6-11]
-fn decode_concatenated_extrinsics(
-  data: &mut &[u8],
-) -> Result<Vec<<T as Config>::RuntimeCall>, ()> {
-  let mut decoded_extrinsics = Vec::new();
-  while !data.is_empty() {
-    let extrinsic =
-      <T as Config>::RuntimeCall::decode_with_depth_limit(
-        sp_api::MAX_EXTRINSIC_DEPTH, 
-        data
-      ).map_err(|_| ())?;
-    decoded_extrinsics.push(extrinsic);
-  }
-  Ok(decoded_extrinsics)
-}
-```
-
----v
-
-### Case Study - Decode Concatenated Data - Issue
-
-```rust [0|6-14]
-fn decode_concatenated_extrinsics(
-  data: &mut &[u8],
-) -> Result<Vec<<T as Config>::RuntimeCall>, ()> {
-  let mut decoded_extrinsics = Vec::new();
-  while !data.is_empty() {
-    if let Ok(extrinsic) =
-      <T as Config>::RuntimeCall::decode_with_depth_limit(
-        sp_api::MAX_EXTRINSIC_DEPTH, 
-        data
-      ) {
-        decoded_extrinsics.push(extrinsic);
-    } else {
-      /// Handle corrupted extrinsic...
-    } 
-  }
-  Ok(decoded_extrinsics)
-}
-```
-
----v
-
-### Mitigation
-
-- Verify the error handling is consistent with the extrinsic logic.
-- During batch processing
-  - If all items need to be processed always
-
-    > Propagate directly the error to stop the batch processing.
-
-  - If only some items need to be processed
-
-    > Handle the error and continue the batch processing.
-
----v
-
-### Takeaways
-
-- Ensure error handling.
-- Optimize your batch processing to handle errors instead of losing execution time.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-### Questions
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-# User Centric
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
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----
-title: User Centric Security in Web3
-description: Describe your slides here
-duration: 45 min
----
-
-# User Centric Security in Web3
-
-Notes:
-
-In this session we will cover the basic of wallet (private and public pairs of keys), key management (how to protect your public-private keys), how to protect the endpoint you are using to manage your keys, and some tips, tricks and security best practices and logics.
-
-In the end, we will give you some advice in case you are compromised.
-
-The objective of the session is to provide a set of guidelines and mental models to questions the operational security of your keys.
-Some of you might find these advices basic, while others will find it useful.
-Some of the ideas are just abstractions of more complex technical concepts, as we would like to approach it in a high level educational piece.
-But also give the opportunity to dig into the rabbit holes for those who may want to follow Alice in that direction.
-
----
-
-## Goal for today:
-
-<pba-flex center>
-
-- Understand the different types of wallets - and the risks associated with them
-- Get the basic foundation to be able to outline a strategy to protect your private keys
-- Be familiar with the best practices to protect your computer and digital tools
-
-</pba-flex>
-
----
-
-> Security is a process, not a product.
-
-_Bruce Scheiner ([Click here to kill everybody](https://en.wikipedia.org/wiki/Click_Here_to_Kill_Everybody), 2019)_
-
-Notes:
-
-Security is not something that is set in stone, it some that is in changing from - it is framework/it is mental model that helps you to tackle the specific problem of protecting your assets.
-Security is something that is different for everyone, for every moment or use cases.
-
----
-
-## Threats or what we need to be worried about
-
-<pba-flex center>
-
-- Vulnerabilities on laptops/phones
-- Network vulnerabilities
-- Poor Operational Security
-
-</pba-flex>
-
-Notes:
-
-What is a threat?
-It is a _potential_ danger that can trespass security and put your assets are risks.
-The threats are the events/things/personas in the horizon we need to have an eye on them.
-
-Different security context - have a different security threats.
-Edward Snowden faces different security threats (changing geopolitical situations, nation state actors, ...) than a regular random internet user (script kidding phishing attempt, port scanning, non targeted malware, ...).
-
----
-
-### Vulnerably on Laptop - What not to do
-
-<img rounded style="width: 800px" src="./img/vuln.jpg" />
-
----
-
-### Vulnerability on Network - What not to do
-
-<img rounded style="width: 800px" src="./img/Network_vuln.jpg" />
-
----
-
-### Poor Operational Security - What not to do
-
-<img rounded style="width: 800px" src="./img/PoorOpSec.jpg" />
-
----
-
-# Risk
-
-... What is risk?
-
-Notes:
-
-What is a risk?
-
-According to Oxford English Dictionary is the _possibility_ of loss, injury, or other adverse or welcome circumstance; a chance or situation of situation of something bad happening.
-But that is what _bad_ means in security terms?
-
----
-
-## Let's visit the `C` `I` `A` triad
-
-- `C`onfidentiality - keep information private.
-- `A`vailability - have information accessible when you need it.
-- `I`ntegrity - keep information as you have note it down when you stored it.
-
-Notes:
-
-We will see this many times!
-
----
-
-## Risks: what can go wrong
-
-<pba-flex center>
-
-- Keys compromised - Loss of confidentiality
-- Keys lost - Loss of availability/integrity
-
-</pba-flex>
-
-Notes:
-
-In this case, which risks (things that can go wrong) we need to be aware?
-That someone else has access to our keys?
-Then they are compromised.
-Or that we cannot access back our keys because we cannot access them or they are noted/stored wrongly.
-By our fault or others fault.
-
-But - what are these keys?
-
----
-
-## Keys compromised - Bad risk management
-
-<img rounded style="width: 800px" src="./img/compromised.jpg" />
-
----
-
-## Keys lost - Bad risk management
-
-<img rounded style="width: 800px" src="./img/keyslost.jpg" />
-
----
-
-### What are the private-public keys ?
-
-(in **web3** context)
-
-Notes:
-
-Simplifying, Private keys are a type of digital signature that allow you to prove ownership of your tokens on a blockchain network.
-The public key is used to receive tokens (this is the “address” where tokens are received).
-
-These pairs of keys are generated by a cryptographic process, generating a public and private key.
-This key pair has a very particular relationship, the public key can be derived from the private key, but not the other way around (asymmetric encryption).
-In mathematical lingo it is called a one-way function, as it only works in one direction.
-Also, another property, using the public key you can verify that a message or a signature has been created by the associated private key without disclosing the private key itself.
-The public key is meant to be shared, the private key is meant to be kept, as its name states, private.
-
----
-
-## And the seeds?
-
-The seed is a list of random words that is generated when you create a new “wallet” (a pair of cryptographic keys).
-
-With the seed, you can generate a private and public key.
-This could mean a seed phrase is the mnemonic human readable version of a private key.
-
----
-
-It is easier to note down this
-
-"caution juice atom organ advance problem want pledge someone senior holiday very
-
-than the following private key.
-
-0x056a6a4e203766ffbea3146967ef25e9daf677b14dc6f6ed8919b1983c9bebbc
-
----
-
-## Key management
-
-A key is protected by
-
-<pba-flex center>
-
-- Strong math, overall length, ...
-- **Handling of the key (key management) by humans or machines**
-
-</pba-flex>
-
-Notes:
-
-We have determined that this keys are important for the user to operate on the blockchain.
-But how secure they are?
-They are protected by strong math (the encryption algorithms that they confer their particular asymmetric properties).
-They are long, so any adversary will need to take longer to(if) calculate the original private key with a longer key than when a shorter key (is just a cases of attempts, cpu speed and probabilistic).
-And the most important - and most of the time the weakest: how we handle these keys.
-
----
-
-## Key management risks - again
-
-<pba-flex center>
-
-- Loss of confidentiality - your key is leaked or compromised.<br />
-  i.e: someone else has access to the wallet.
-- Loss of availability - you cannot access your key anymore.<br />
-  i.e: you don't know where you noted.
-- Loss of integrity - your key is wrong.<br />
-  i.e: you noted the key incorrectly.
-
-</pba-flex>
-
-Notes:
-
-When handling the keys, what we need are the 3 key points we mentioned earlier.
-The private key stays in secret (don't leaked in their internet, don't be part of a screenshot uploaded to a cloud service, ...).
-That they key is available - you can access to it when you need it - the hard disk where you have it noted is wrong, And that the key you stored is correct: That you noted it well, in these cases a "3 cannot be an 8, a 4 cannot be a 9", or we cannot forget to select the last character when copy and paste.
-
----
-
-## _Keys overly simplified_
-
-## Cryptocurrency user definitions
-
-- The public key is used to receive tokens (**public**)
-
-- The private key is used to sign transactions (**private**)
-
-- The seed is used to calculate the private key (**private**)
-
----
-
-### Multisig accounts
-
-<img rounded style="width: 900px" src="./img/multiSig.jpg" />
-
-<pba-flex center>
-
-- One or more keys and a threshold
-- The threshold defines how many signatories<br />must sign for a sig check t be valid.
-
-</pba-flex>
-
-Notes:
-
-These pub keys (addresses) can be distributed among different individuals - even in different locations - so a transaction is only validated when the minimum required of signatures are achieved.
-This way the individuals-parties need to agree on signing a particular transactional.
-This is a common way to protect corporate funds or big amount of tokens - and not to rely in one individual or single point of failure.
-
-Another method - for protecting individual funds, is that one individual is keeping different wallets of a multisig account.
-This way, if one of the wallets is exposed, compromise or lost.
-The individual can still operate with this wallet (and most recommended, migrate the tokens to another multi-sig wallet where they have control over all the addresses).
-
----
-
-## What is a wallet
-
-<img rounded style="width: 800px" src="./img/keymaker.jpg" />
-
-A wallet holds a pair of cryptographic keys (public and private).
-
-Notes:
-
-A wallet is a software application that stores your private keys and allows you to receive tokens through a public key.
-As the wallet contains the keys in order to operate with the tokens, a keychain could be a better metaphor.
-
----
-
-## Wallets
-
-Hot n Cold
-
-<img rounded style="width: 500px" src="./img/hotncold.jpg" />
-
-Notes:
-
-We have been talking about keys, and in the blockspace there is a great differentiation between to what are your keys exposed.
-Hot/Cold is a metaphor of the amount of risk we want to expose our private keys.
-
----
-
-## Hot wallets
-
-<pba-flex center>
-
-1. Heavy clients - full nodes (deprecated use as wallet)
-1. Light clients
-
-</pba-flex>
-
-Notes:
-
-Heavy client -
-
-Light client - A light client or light node is a piece of software that connects to full nodes to interact with the blockchain.
-Unlike their full node counterparts, light nodes don’t need to run 24/7 or read and write a lot of information on the blockchain.
-In fact, light clients do not interact directly with the blockchain; they instead use full nodes as intermediaries.
-This is the todays standard for hot wallets.
-
----
-
-## Internet connection = _bigger_ risk
-
-<img rounded style="width: 800px" src="./img/listening.jpg" />
-
-The listening post (2005) - Exhibited in the British Museum
-
----
-
-## Cold wallets
-
-<pba-flex center>
-
-1. Full node offline (_old school_)
-1. Paper wallet (beware fo the change address!)
-1. (Hybrid?) Hardware wallet
-1. Offline seed backup
-1. EXTRA BALL: Polkadot Vault
-
-</pba-flex>
-
-Notes:
-
-On the other hand, the cold wallets are not connected to the internet, they are air-gapped from the network, substantially reducing all risks that might come from there.
-These wallet concepts are more suitable for long term storage, or wallets that don't need constant operation.
-
-Heavy client offline - is a the full implementation of a node.
-It is possible to use a "full" node in order to create a priv/public key pair.
-The client is disconnected from the internet - not even synced with the chain -, but is able to receive transactions.
-In order to operate with received tokens, we just need to connect the node to the net, and allow it syncing.
-Due to progressive weight (in Gigabytes) of the chains, this method is deprecated.
-
-Paper Wallet - A paper wallet is a paper document that contains your seed or private key and the public key.
-It would need to be accessed and copied to compromise your private keys, but at the same time the paper needs to be properly stored and/or backed up.
-As being a totally analog format, they are immune to digital attacks but subject to events on the physical world.
-
-Depending on the chain there are some offline tools that allows you generate derived private or public keys while being offline.
-
-Ideally they are printed using an offline (ideally a dedicated clean air-gapped computer for this purpose) and local printer.
-
-A paper wallet cannot be used to transfer fund from the same address various times, it generates a change address that might not be in possession of the sender.
-It is possible to set the outputs of the transaction, but technical knowledge is required for this configuration.
-
-Hardware wallets - There are several commercial projects that offer a reasonable level of protection when protecting your tokens.
-These are - usually - hardware devices that allow you to create a seed - for the whole device, and the rest of private keys (usually kept in the device) and public keys (to receive tokens).
-
-In most of the systems, the device includes some other manual controls that need to be physically manipulated in order to, for example, validate a transaction.
-The need to the physical interaction for this restricts the operation of the hardware wallet - as the rules of the objects of the physical world, to a certain place in a certain time.
-
----
-
-## [Polkadot Vault](https://signer.parity.io/)
-
-<img rounded style="width: 800px" src="./img/vault.jpg" />
-
-Polkadot Vault is a software app that transforms an Android or iOS device in an air-gapped hardware wallet.
-
-Notes:
-
-The signing of the transactions is made by a series of QR communications between computer and the Vault Device.
-The wallet is not connected to the net or even to the device which is interacting with the blockchain.
-
-Some hardware wallets are completely air-gapped - like Vault, software installed in a android or iOS device in Airplane mode -
-
-Other hardware wallets require connection between the computer/phone and the hardware wallet.
-This connection can be via a cabled connection (recommended) or wireless connection (not recommended, as we would like not to radiate - even in an encrypted form - anything related to these blockchain operations).
-
----
-
-## Sharding (or divide and not be conquered)
-
-Sharding is a technique to divide your secret in different parts, so an adversary could not have access to the full secret in case one of the pieces is compromised.
-
-Notes:
-
-Traditional methods for encryption are ill-suited for simultaneously achieving high levels of confidentiality and reliability.
-This is because when storing the encryption key, one must choose between keeping a single copy of the key in one location for maximum secrecy, or keeping multiple copies of the key in different locations for greater reliability.
-Increasing reliability of the key by storing multiple copies lowers confidentiality by creating additional attack vectors; there are more opportunities for a copy to fall into the wrong hands.
-
----
-
-### Sharding challenges:
-
-- Recovery
-- Fault tolerance - storage/persons
-- Still secret?
-
-Notes:
-
-How to divide the secret in a way that is recoverable correctly, how to make it fault tolerant (as now they are many pieces to take care of, do we need to protect them all to ensure recovery, can I trust all people to keep their part secret all time?), how to make sure that with one of the pieces of the secret, the rest cannot be inferred.
-
----
-
-### Secret Sharing Technique
-
-Is a method to distribute a secret in different parts/persons, in a way that no part holds any intelligible information about the secret.
-But the secret can be reconstructed with a minimum number of shares.
-
-**And remember:** These secrets are managed by humans - that are driven by motivations.
-And motivations change.
-
----
-
-### Requisites for successful secret sharing
-
-- Information should stay secure
-- Flexible (n of m pieces required)
-- Recoverable
-
-Notes:
-
-We need a technology that will allow us, when we divide our secret:
-
-- That the secret stays _confidential_, and the different individual shards cannot be used to infer the original secret.
-- That the recovery is flexible, meaning that we would need only n of m pieces of the secret to recover it.
-  This can be because the secrets are no longer _available_ (are lost), or because we cannot trust the persons we gave the secret piece anymore.
-- That the secret is recoverable with no glitches/errors: Integrity.
-
----
-
-### How we can achieve this?
-
-**Using strong Math**
-
----
-
-### Shamir Secret Sharing - Banana Split
-
-Shamir Secret Sharing is an efficient Secret Sharing algorithm for distributing private information.
-
-The secret is mathematically divided into parts (the "shares") from which the secret can be reassembled only when a sufficient number of shares are combined.
-
-There are different implementation of it: we will take a look to Banana Split
-
-Notes:
-
-SSS is used to secure a secret in a distributed form, most often to secure encryption keys.
-The secret is split into multiple shares, which individually do not give any information about the secret.
-
-To reconstruct a secret secured by SSS, a number of shares is needed, called the threshold.
-No information about the secret can be gained from any number of shares below the threshold (a property called perfect secrecy).
-
-It was invented in the late 70's by the Israeli cryptographer.
-He is the S on the RSA algorithm (Rivest-Shamir-Adleman)
-
----
-
-### Banana Split - [bs.parity.io](https://bs.parity.io)
-
-- Offline HTML file used to generate and recover secrets
-- To be used in air-gapped computers and local printers
-- Uses QR codes to store information and cameras to retrieve
-- It is flexible allowing n:m type of shared secret creation
-
----
-
-### Key protection Operational Security Logics
-
-- Security is contextual
-- Define your risk appetite
-- Backups not only of information also for processes.<br />
-  Do not rely on single point of failure.
-- Don't put all your eggs in the same basket
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-### Some mental exercises (1)
-
-> What is the operational model to a wallet that is transferring funds to third parties every day?
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-### Some mental exercises (2)
-
-> How to protect a personal wallet with 10 million tokens?
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-### Some mental exercises (3)
-
-> How to protect an corporate wallet with 100 million tokens?
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-### Some mental exercises (4)
-
-> sHow to ensure `C` `I` `A` of a wallet, in a future when we would not be around?
-
----
-
-### Last but not least - Basic laptop/phone hygiene
-
-- Software up-to-date
-- Use of different profiles or even different computers
-- Avoid malicious environments (links containing malware)
-- Double-triple check the software we download for the internet
-- Second factor of authentication where possible - physical key preferred
-
----
-
-### Never Assume - Practice a legitimate distrust.
-
-- Many actors or institutions have different objectives of the one you have.
-
-- Software have bugs and errors.
-  They are made by people like you and me,<br />which needs to eat and go to sleep.
-- No technology is agnostic.
-  This includes they technology we communicate with,<br />we work with or the one we use to keep us entertained.
-- Sometimes we are our worst adversary.
-
-> Be diligent. 🖖
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/substrate/README.md b/content/substrate/README.md
deleted file mode 120000
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--- a/content/substrate/README.md
+++ /dev/null
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-index.md
\ No newline at end of file
diff --git a/content/substrate/code/page.md b/content/substrate/code/page.md
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--- a/content/substrate/code/page.md
+++ /dev/null
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-# Substrate; Show Me The Code
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/substrate/code/slides.md b/content/substrate/code/slides.md
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--- a/content/substrate/code/slides.md
+++ /dev/null
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----
-title: Substrate; Show Me The Code
-description: A hands-on dive into practical matters of substrate, such as docs, CLI and folder structure.
-duration: 60 minutes
----
-
-# Substrate; Show Me The Code 👨‍💻
-
----
-
-## Substrate; Show Me The Code 👨‍💻
-
-Previous lecture was all about high level information; now we want to bridge that to real code.
-
----
-
-## A Word on Previous Versions
-
-- This is a brand new lecture replacing two old ones, with more focus on rust-docs.
-- Since this is the first time, I have kept the old versions around for you to look into
-
-> Cambridge-y (adj) - Overall good quality, but with rough edges or imperfections. Especially when related to PBA content.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### A Word on the Rust Exam
-
-Two main takeaways from the previous cohort:
-
-- Write more rust-docs, expect them to be read.
-- Extensive use of type-system, to prepare you better for FRAME.
-
-Notes:
-
-Personally doing my best to make it hard, but reasonable, such that it prepares you best for
-in-depth development of Substrate.
-
----v
-
-### Interactive
-
-- This lecture will be interactive.
-- Try and learn the technique, not the specific topic. <!-- .element: class="fragment" -->
-- Try and repeat the process later. <!-- .element: class="fragment" -->
-
-Notes:
-
-what I am trying to do here is to teach you how to plant a tree rather than giving you the apple.
-
----
-
-## Documentation Resources
-
-Core
-
-- paritytech.github.io
-  - `substrate` crate
-  - WIP: `frame`, `cumulus` and `polkadot` crate.
-- Github
-- Substrate/Polkadot StackExchange
-
-High level
-
-- `substrate.io`\*
-- Discord, Telegram, etc.
-
----
-
-## Exploring the `substrate` crate.
-
-<https://paritytech.github.io/substrate/master/substrate/index.html>
-
----v
-
-### Substrate From Within
-
-Division of substrate when seen from inside:
-
-1. `sp`
-2. `sc`
-3. `frame/pallet/runtime`
-
-Notes:
-
-this should be covered
-
----v
-
-### Substrate Binaries
-
-Notes:
-
-alternative way is to search for `[[bin]]` in all toml files.
-
----v
-
-### Structure of a Binary Crate
-
-Division of a typical substrate-based project:
-
-1. `node`
-   1. Contains a `main.rs`
-   2. `service.rs`
-   3. and more!
-2. `runtime`
-   1. Contains a `/src/lib.rs` ("_runtime amalgamator_")
-3. more!
-
-Notes:
-
-node is client side entry point, `runtime amalgamator for the runtime`.
-
-- looking at node-template, it only has the two.
-- node has even more
-- polkadot has even more.
-
----v
-
-### Substrate CLI
-
-Study in the docs:
-
-- `--dev`
-- `--chain`
-- `--tmp`, `--base-path`, `purge-chain`.
-
-Notes:
-
-all commands: <https://paritytech.github.io/substrate/master/sc_cli/commands/index.html>
-all args to a typical run command <https://paritytech.github.io/substrate/master/sc_cli/commands/struct.RunCmd.html>
-
-But then each node can decide which subset of these it chooses, and how it implements it.
-
-<https://paritytech.github.io/substrate/master/node_template/cli/enum.Subcommand.html>
-<https://paritytech.github.io/substrate/master/node_cli/enum.Subcommand.html>
-
-- execution strategies
-- database type
-- logs
-- RPC
-- pruning
-- sync modes
-
----v
-
-## Wasm Build + `std` feature.
-
-- How to compile to wasm? `build.rs`!
-- just get your `std` features right please!
-
-Notes:
-
-<https://crates.io/crates/substrate-wasm-builder> (seen env variables, pretty useful!)
-<https://docs.substrate.io/build/build-process/>
-
----v
-
-## Chain Specification
-
-Notes:
-
-raw vs not-raw
-
----
-
-## #1 Rust-Docs Tip Of All Time
-
-- Search traits, find implementations.
-- Examples: `trait Block`, `trait Extrinsic`, `trait Header`.
-
-```rust
-trait Config {
-  type Foo: SomeTrait<Bar>
-}
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Especially in FRAME, oftentimes you have to parameterize your pallets with a pattern like above.
-Simply search the trait in the rust-docs, and find the implementors!
-
----
-
-## Additional Resources! 😋
-
-> Check speaker notes (click "s" 😉)
-
-<img width="300px" rounded src="../scale/img/thats_all_folks.png" />
-
-Note:
-
-One important concept that is important to substrate-based chains, but is somewhat missing here is
-`chain-spec`. Make sure to read up about it in the substrate docs.
diff --git a/content/substrate/index.md b/content/substrate/index.md
deleted file mode 100644
index 2a274889..00000000
--- a/content/substrate/index.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# 🧬 Substrate
-
-The blockchain framework canonical to Polkadot and Parachains covered in depth, at a lower level.
diff --git a/content/substrate/interact/page.md b/content/substrate/interact/page.md
deleted file mode 100644
index 9c6c9a22..00000000
--- a/content/substrate/interact/page.md
+++ /dev/null
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-# Interacting With a Substrate Blockchain
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/substrate/interact/slides.md b/content/substrate/interact/slides.md
deleted file mode 100644
index 94056b4a..00000000
--- a/content/substrate/interact/slides.md
+++ /dev/null
@@ -1,281 +0,0 @@
----
-title: Interacting With a Substrate Blockchain
-duration: 60 minutes
----
-
-# Interacting With a Substrate Blockchain
-
----
-
-## Interacting With a Substrate Blockchain
-
-<img style="width: 1200px;" src="../intro/img/dev-4-1-json.svg" />
-
-Notes:
-
-Many of these interactions land in a wasm blob.
-
-So what question you need to ask yourself there? which runtime blob.
-
-almost all external communication happens over JSPN-RPC, so let's take a closer look.
-
----
-
-## JSON-RPC
-
-> JSON-RPC is a remote procedure call protocol encoded in JSON. It is similar to the XML-RPC
-> protocol, defining only a few data types and commands.
-
----v
-
-### JSON-RPC
-
-```json
-{
-  "jsonrpc": "2.0",
-  "method": "subtract",
-  "params": { "minuend": 42, "subtrahend": 23 },
-  "id": 3
-}
-```
-
-<br />
-
-```json
-{ "jsonrpc": "2.0", "result": 19, "id": 3 }
-```
-
-<!-- .element: class="fragment" -->
-
----v
-
-### JSON-RPC
-
-- Entirely transport agnostic.
-- Substrate based chains expose both `websocket` and `http` (or `wss` and `https`, if desired).
-
-> with `--ws-port` and `--rpc-port`, 9944 and 9934 respectively.
-
----v
-
-### JSON-RPC
-
-- JSON-RPC methods are conventionally written as `scope_method`
-
-  - e.g. `rpc_methods`, `state_call`
-
-- &shy;<!-- .element: class="fragment" --> `author`: for submitting stuff to the chain.
-- &shy;<!-- .element: class="fragment" --> `chain`: for retrieving information about the _blockchain_ data.
-- &shy;<!-- .element: class="fragment" --> `state`: for retrieving information about the _state_ data.
-- &shy;<!-- .element: class="fragment" --> `system`: information about the chain.
-- &shy;<!-- .element: class="fragment" --> `rpc`: information about the RPC endpoints.
-
-Notes:
-
-Recall:
-
-- <https://paritytech.github.io/substrate/master/sc_rpc_api/index.html>
-- <https://paritytech.github.io/substrate/master/sc_rpc/index.html>
-
-The full list can also be seen here: <https://polkadot.js.org/docs/substrate/rpc/>
-
----v
-
-### JSON-RPC
-
-- Let's look at a few examples:
-
-- `system_name`, `system_chain`, `system_chainType`, `system_health`, `system_version`, `system_nodeRoles`, `rpc_methods`, `state_getRuntimeVersion`, `state_getMetadata`
-
-```sh
-wscat \
-  -c wss://kusama-rpc.polkadot.io \
-  -x '{"jsonrpc":"2.0", "id": 42, "method":"rpc_methods" }' \
-  | jq
-```
-
----v
-
-### JSON-RPC: Runtime Agnostic
-
-- Needless to say, RPC methods are runtime agnostic. Nothing in the above tells you if FRAME is
-  being used or not.
-- <!-- .element: class="fragment" --> Except... metadata, to some extent.
-
----v
-
-### JSON-RPC: Runtime API
-
-- While agnostic, many RPC calls land in a runtime API.
-- &shy;<!-- .element: class="fragment" --> RPC Endpoints have an `at: Option<hash>`, runtime APIs do too, what a coincidence! 🌈
-  - &shy;<!-- .element: class="fragment" --> Recall the scope `state`?
-
----v
-
-### JSON-RPC: Extending
-
-- The runtime can extend more custom RPC methods, but the new trend is to move toward using `state_call`.
-
----v
-
-### JSON-RPC: Safety
-
-- Some PRC methods are unsafe 😱.
-
----v
-
-### JSON-RPC: Resilience
-
-RPC-Server vs. Light Client
-
----
-
-### JSON-RPC: Application
-
-- On top of `SCALE` and `JSON-RPC`, a large array of libraries have been built.
-
-- &shy;<!-- .element: class="fragment" --> `PJS-API` / `PJS-APPS`
-- &shy;<!-- .element: class="fragment" --> `capi`
-- &shy;<!-- .element: class="fragment" --> `subxt`
-- &shy;<!-- .element: class="fragment" --> Any many more!
-
-Notes:
-
-<https://github.com/JFJun/go-substrate-rpc-client>
-<https://github.com/polkascan/py-substrate-interface>
-more here: <https://project-awesome.org/substrate-developer-hub/awesome-substrate>
-
----
-
-### JSON-RPC: Mini Activity
-
-In Kusama:
-
-- Find the genesis hash..
-- Number of extrinsics at block 10,000,000.
-- The block number is stored under `twox128("System") ++ twox128("Number")`.
-  - Find it now, and at block 10,000,000.
-
-<br />
-
-- Refer to the "Substrate; Show Me The Code" lecture to find the right RPC endpoints.
-- You have 15 minutes!
-
-Notes:
-
-```sh
-# 10,000,000 in hex
-printf "%x\n" 10000000
-# Genesis hash
-wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"chain_getBlockHash", "params": ["0x0"] }' | jq
-# Hash of the block at height 10,000,000
-wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"chain_getBlockHash", "params": ["0x989680"] }' | jq
-# The block at height 1,000,000
-wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"chain_getBlock", "params": ["0xdcbaa224ab080f2fbf3dfc85f3387ab21019355c392d79a143d7e50afba3c6e9"] }' | jq
-
-# `0x26aa394eea5630e07c48ae0c9558cef702a5c1b19ab7a04f536c519aca4983ac` now.
-wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"state_getStorage", "params": ["0x26aa394eea5630e07c48ae0c9558cef702a5c1b19ab7a04f536c519aca4983ac"] }' | jq
-# `0x26aa394eea5630e07c48ae0c9558cef702a5c1b19ab7a04f536c519aca4983ac` at block 1,000,000.
-wscat -c wss://kusama-rpc.polkadot.io -x '{"jsonrpc":"2.0", "id":72, "method":"state_getStorage", "params": ["0x26aa394eea5630e07c48ae0c9558cef702a5c1b19ab7a04f536c519aca4983ac", "0xdcbaa224ab080f2fbf3dfc85f3387ab21019355c392d79a143d7e50afba3c6e9"] }' | jq
-```
-
-Notice that this number that we get back is the little endian (SCALE) encoded value that we passed in at first.
-
----
-
-## Polkadot JS API
-
-A brief introduction.
-
-Excellent tutorial at: <https://polkadot.js.org/docs/>
-
----v
-
-## Polkadot JS API
-
-<img src="./img/pjs.png" style="width: 500px" />
-
----v
-
-### PJS: Overview
-
-- `api.registry`
-- `api.rpc`
-
----v
-
-### PJS: Overview
-
-Almost everything else basically builds on top of `api.rpc`.
-
-- `api.tx`
-- `api.query`
-- `api.consts`
-- `api.derive`
-
-Please revise this while you learn FRAME, and they will make perfect sense!
-
----v
-
-### PJS: Workshop 🧑‍💻
-
-Notes:
-
-```ts
-import { ApiPromise, WsProvider } from "@polkadot/api";
-const provider = new WsProvider("wss://rpc.polkadot.io");
-const api = await ApiPromise.create({ provider });
-api.stats;
-api.isConnected;
- // where does this come from?
-api.runtimeVersion;
-// where does this come from?
-api.registry.chainDecimals;
-api.registry.chainTokens;
-api.registry.chainSS58;
-// where does this come from?
-api.registry.metadata;
-api.registry.metadata.pallets.map(p => p.toHuman());
-api.registry.createType();
-api.rpc.chain.getBlock()
-api.rpc.system.health()
-await api.rpc.system.version()
-await api.rpc.state.getRuntimeVersion()
-await api.rpc.state.getPairs("0x")
-await api.rpc.state.getKeysPaged("0x", 100)
-await api.rpc.state.getStorage()
-await api.rpc.state.getStorageSize("0x3A636F6465"),
-```
-
-<https://polkadot.js.org/docs/substrate/rpc#getstoragekey-storagekey-at-blockhash-storagedata>
-
-A few random other things:
-
-```ts
-api.createType("Balance", new Uint8Array([1, 2, 3, 4]));
-
-import { blake2AsHex, xxHashAsHex } from "@polkadot/util-crypto";
-blake2AsHex("Foo");
-xxHashAsHex("Foo");
-```
-
----
-
-## `subxt`
-
-- Something analogous to `PJS` for Rust.
-- The real magic is that it generates the types by fetching the metadata at compile time, or linking
-  it statically.
-- ..It might need manual updates when the code, and therefore the metadata changes.
-
----
-
-## Additional Resources! 😋
-
-> Check speaker notes (click "s" 😉)
-
-Notes:
-
-- see "Client Libraries" here: <https://project-awesome.org/substrate-developer-hub/awesome-substrate>
-- <https://paritytech.github.io/json-rpc-interface-spec/introduction.html>
-- Full `subxt` guide: <https://docs.rs/subxt/latest/subxt/book/index.html>
diff --git a/content/substrate/intro/img/dev-4-1-comms-format.svg b/content/substrate/intro/img/dev-4-1-comms-format.svg
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-# Introduction to Substrate
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/substrate/intro/slides.md b/content/substrate/intro/slides.md
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----
-title: Introduction to Substrate
-description: Substrate Overview for web3 builders
-duration: 60 minutes
----
-
-# Introduction to Substrate
-
----
-
-## Before Going Any Further 🛑
-
-While I speak, please clone `polkadot-sdk`, and run `cargo build && cargo build --release`.
-
-> <https://github.com/paritytech/polkadot-sdk/>
-
----
-
-## About These Lectures and Lecturer
-
-- Ground-up, low-level, but hands-on.
-- Intentionally avoiding FRAME, but giving you the tools to be successful at it.
-- Narratives above facts all.
-- Interrupts and questions are always welcome.
-
----
-
-## What is Substrate?
-
-Substrate is a **Rust framework** for **building blockchains**.
-
----v
-
-### Why Substrate?
-
-<img rounded width="1000px" src="./img/dev-4-1-substrate-website.gif" />
-
-Notes:
-
-Highlight the multi-chain part.
-
----v
-
-### Why Substrate?
-
-<img rounded width="1000px" src="./img/dev-4.1-maximalism.png" />
-
-Notes:
-
-Polkadot is the biggest bet in this ecosystem against chain maximalism, and Substrate plays a big
-role in this scenario.
-
----v
-
-### Why Substrate?
-
-- ⛓️ Future is multi-chain.
-
-<!-- .element: class="fragment" -->
-
-- 😭 Building a blockchain is hard. Upgrading it even harder.
-
-<!-- .element: class="fragment" -->
-
-- 💡 Framework!
-
-<!-- .element: class="fragment" -->
-
-- 🧐 But which attitude to take?
-
-<!-- .element: class="fragment" -->
-
----
-
-## Core Philosophies of Substrate 💭
-
-The **pre-substrate** way of thinking:
-
-- 😭 _Building a blockchain is hard. Upgrading it even harder_.
-- 💪🏻 We are going to spend maximal resources at making sure we get it right.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Core Philosophies of Substrate 💭
-
-But has this worked?
-
-- 😭 Bitcoin block size debate
-
-<!-- .element: class="fragment" -->
-
-- 2️⃣ L2s and beyond
-
-<!-- .element: class="fragment" -->
-
-- 📈 Ethereum gas price
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Bitcoin block size has never been and is an ongoing debate.
-
-I am not against L2s per se, but it is true that they mostly exist because the underlying protocol is too hard/slow to upgrade itself.
-ETH Gas prices also show that the underlying protocol cannot meet the demands of today.
-
-<https://en.wikipedia.org/wiki/Bitcoin_scalability_problem>
-<https://ycharts.com/indicators/ethereum_average_gas_price>
-
----v
-
-### Core Philosophies of Substrate 💭
-
-The **Substrate** way of thinking:
-
-- ☯️ Society and technology evolve
-
-<!-- .element: class="fragment" -->
-
-- 🦸 Humans are fallible
-
-<!-- .element: class="fragment" -->
-
-- 🧠 Best decision of today -> mistake of tomorrow
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Core Philosophies of Substrate 💭
-
-Outcomes of this:
-
-- 🦀 Rust
-- 🤩 Generic, Modular and Extensible Design
-- 🏦 Governance + Upgradeability
-
-Notes:
-
-Think about how each of these links back to "whatever you decide today will be a mistake soon".
-
----
-
-## 🦀 Rust
-
-- First line of defense: prevent human error when possible.
-- Safe language, no memory safety issues.
-
-Notes:
-
-So at least we don't want to deal with human error, and only deal with the fact that we cannot
-predict the future.
-
-Memory safety is a fundamental issue in most major system-level programming languages.
-
-Some such mistakes are impossible to make in Rust.
-
----v
-
-### 🦀 Rust
-
-```c
-int main() {
-    int* x = malloc(sizeof(int));
-    *x = 10;
-    int* y = x;
-    free(x);
-    printf("%d\n", *y);  // Accessing memory after it's been freed
-}
-```
-
-<br />
-
-```rust
-fn main() {
-    let x = Box::new(10);
-    let y = x;
-    println!("{}", *y); // ❌
-}
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-another one:
-
-```c
-int* foo() {
-    int x = 10;
-    return &x;
-}
-
-int main() {
-    int* y = foo();
-    printf("%d\n", *y); // Accessing memory out of its scope
-}
-```
-
-<br />
-
-```rust
-fn foo() -> &'static i32 {
-    let x = 10;
-    &x
-}
-
-fn main() {
-    let y = foo();
-    println!("{}", y); // ❌
-}
-```
-
----v
-
-### 🦀 Rust
-
-> Microsoft and Google have each stated that software memory safety issues are behind around 70 percent of their vulnerabilities.
-
-Notes:
-
-<https://www.nsa.gov/Press-Room/News-Highlights/Article/Article/3215760/nsa-releases-guidance-on-how-to-protect-against-software-memory-safety-issues/#:~:text=Microsoft%20and%20Google%20have%20each,70%20percent%20of%20their%20vulnerabilities.>
-
----v
-
-### 🦀 Rust
-
-- 🏎️ Most Rust abstractions are **zero-cost**.
-- ⏰ Rust has (almost) no "runtime".
-
-<br />
-
-<img rounded width="900px" src="./img/dev-4-1-speed.png" />
-
-Notes:
-
-this is not 100% accurate though, rust has a small runtime that is the panic handler etc. Rust for
-Rustacean's chapter on `no_std` covers this very well.
-
-Also, this is a good time to talk about how we use "Runtime" in a different way.
-
----
-
-## 🤩 Generic, Modular and Extensible Design
-
-- Second line of defense.
-- Our _execution_ (possibly thanks to Rust) is perfect, but we can't predict the future.
-
-Notes:
-
-this is where a module, generic design is useful. You can change components easily based on the
-needs of the future.
-
----v
-
-### 🤩 Generic, Modular and Extensible Design
-
-- Multiple consensus engines (BABE/Grandpa/AURA/PoW/Sassafras)
-
-<!-- .element: class="fragment" -->
-
-- Multiple network protocols (QUIC, TCP)
-
-<!-- .element: class="fragment" -->
-
-- Multiple database implementations (ParityDB, RocksDB)
-
-<!-- .element: class="fragment" -->
-
-- Highly configurable, graph-based transaction-pool.
-
-<!-- .element: class="fragment" -->
-
-- Easy to change primitives: AccountId, Signature, BlockNumber, Header, Hash, and many more.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-FRAME takes this even multiple steps further, but that's for later.
-
-These are all examples of being generic, modular and extensible at the Substrate level. FRAME takes
-these even further, but more on that later.
-
----v
-
-### 🤩 Generic, Modular and Extensible Design
-
-- **AlephZero**: Custom finality, DAG-based, 1s block time.
-- **Moonbeam**: Ethereum compatible, build with substrate.
-- **HydraDX**: Custom transaction pool logic to match DEX orders.
-- **Kulupu**: Proof of work, custom hashing.
-
-Notes:
-
-Substrate has been coded, from the ground up, such that it is easy to have multiple implementations
-for certain functions. Heavy use of traits and generics is the key to achieve this. As noted,
-Substrate has a lot of APIs, and optional implementations. You are bound to the API, but not the
-particular implementation.
-
----
-
-## 🏦 Governance + Upgradeability
-
-- Third, final, and non-negotiable line of defense to survive the test of time.
-
----v
-
-### 🏦 Governance + Upgradeability
-
-- We have correct code, and components are easy to swap, replace, and upgrade.
-- What use is that, if we cannot agree on what to replace/upgrade?
-- Governance!
-
-<!-- .element: class="fragment" -->
-
-- What use is governance, if the upgrade cannot be enacted?
-
-<!-- .element: class="fragment" -->
-
-- (trustlessly) Upgradeability!
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Even if we are governable, but we still need "trust" to enact the upgrade, it is hardly any better.
-In essence, if an upgrade mechanism is not self-enacting, it might as well just reside offchain and
-be a signaling mechanism.
-
----v
-
-### 🏦 Governance + Upgradeability
-
-- ✅ Governance: Easy
-- 😢 Upgradeability: Not so much
-
----v
-
-### 🏦 Governance + Upgradeability
-
-- How does a typical blockchain upgrade itself?
-
-Notes:
-
-1. Discussion, offchain signaling
-2. Possibly onchain voting
-3. Hard(ish) Fork
-
----v
-
-### 🏦 Governance + Upgradeability
-
-<img src="./img/dev-4-1-substrate-monol.svg" />
-
----v
-
-### 🏦 Governance + Upgradeability
-
-<img src="./img/dev-4-1-substrate-monol-2.svg" />
-
-Notes:
-
-the problem is that the system is one big monolith protocol. Updating any part of it requires the
-whole thing to be updated.
-
----v
-
-### 🏦 Governance + Upgradeability
-
-_The way to make a protocol truly upgradeable is to design a meta-protocol that is not upgradeable._
-
----v
-
-### 🏦 Governance + Upgradeability
-
-<img src="./img/dev-4-1-substrate-meta.svg" />
-
-Note:
-
-In this figure, the meta-protocol, the substrate client, is not forklessly upgrade-able. It can only
-be upgraded with a fork. The Wasm protocol, though, can be upgraded forklessly.
-
----v
-
-### 🏦 Governance + Upgradeability
-
-<img src="./img/dev-4-1-substrate-meta-substrate.svg" />
-
----v
-
-### 🏦 Governance + Upgradeability
-
-- Fixed meta-protocol?
-- &shy;<!-- .element: class="fragment" --> "_State machine as stored Wasm_" in the Substrate client.
-- <!-- .element: class="fragment" --> inherently upgradeable protocol?
-- <!-- .element: class="fragment" --> Substrate Wasm Runtime
-
----
-
-### Substrate Architecture
-
-<img src="./img/dev-4-1-substrate.svg" />
-
----v
-
-#### Substrate (simplified) Architecture
-
-<pba-cols>
-
-<pba-col center>
-<h3 style="color: var(--substrate-runtime); top: 0"> Runtime (Protocol) </h3>
-
-- Application logic
-- Wasm (maybe **FRAME**)
-- Stored as a part of your chain state
-- Also known as: STF
-
-</pba-col>
-
-<pba-col center>
-<h3 style="color: var(--substrate-host); top: 0"> Client (Meta-protocol) </h3>
-
-- Native Binary
-- Executes the Wasm runtime
-- Everything else: Database, Networking, Mempool, Consensus..
-- Also known as: Host
-
-</pba-col>
-
-</pba-cols>
-
----
-
-## The Runtime
-
-<div>
-
-- Runtime -> **Application Logic**.
-
-</div>
-<!-- .element: class="fragment" -->
-<div>
-
-- A _fancy_ term: Runtime -> **State Transition Function**.
-
-</div>
-<!-- .element: class="fragment" -->
-<div>
-
-- A _technical_ term: Runtime -> **how to execute blocks**.
-
-</div>
-<!-- .element: class="fragment" -->
-
-Notes:
-
-- I would personally call the runtime STF to avoid confusion with the "runtime" that is the general
-  programming runtime, but kinda too late for that now.
-- Among the definitions of the Wasm runtime, let's recap what the state transition is.
-- The block execution definition will be described more in the Wasm-meta lecture.
-
----
-
-## State Transition Function
-
-**State**
-
-<img style="width: 600px" src="./img/dev-4-1-state-def.svg" />
-
-Notes:
-
-entire set of data upon which we want to maintain a consensus.
-key value.
-associated with each block.
-
----v
-
-### State Transition Function
-
-**Transition Function**
-
-<img width="400px" src="./img/dev-4-1-state-transition-def.svg" />
-
----v
-
-### State Transition Function
-
-$$STF = F(block_{N}, state_{N}, code_{N}): state_{N+1}$$
-
----v
-
-### State Transition Function
-
-<img style="width: 1200px;" src="./img/dev-4-1-state.svg" />
-
-Notes:
-
-The Wasm runtime in this figure is in fact obtained from the state (see `0x123`)
-
----v
-
-### State Transition Function
-
-<img style="width: 1200px;" src="./img/dev-4-1-state-code.svg" />
-
----v
-
-### State Transition Function
-
-<img style="width: 1200px;" src="./img/dev-4-1-state-code-next.svg" />
-
-Notes:
-
-THIS IS HOW A META-PROTOCOL MAKES A SYSTEM UPGRADE-ABLE.
-
-could we have updated the code in N+1? By default, no because we load the wasm before you even look
-into the block.
-
-IMPORTANT: State is not IN THE BLOCK, each state has AN ASSOCIATED BLOCK.
-
-Keeping the state is 100% optional. You can always re-create the state of block `N` by re-executing
-block `[0, .., N-1]`.
-
-ofc, changing the Wasm code cannot be done by anyone. That's up to governance.
-
----
-
-## Full Substrate Architecture
-
-<img style="width: 1400px;" src="./img/dev-4-3-full.svg" />
-
----
-
-## Positive Consequences of _Wasm_ Runtime 🔥
-
----v
-
-### 🤖 Deterministic Execution
-
-- Portable, yet deterministic.
-
-Notes:
-
-Wasm's instruction set is deterministic, so all good.
-
----v
-
-### 🧱 Sandboxing
-
-- Useful when executing untrusted code.
-
-1. Smart contracts
-2. Parachain runtime
-
-Notes:
-
-How can we guarantee that neither enter an infinite loop, or try to access the filesystem?
-
----v
-
-### 🌈 Easier (light)Client Development
-
-Notes:
-
-for the case of client, your client only needs to implement a set of host environments, and NOT
-re-implement the business logic.
-
-Simply compare the process to create an alternative client for Ethereum, where you need to
-re-implement the EVM.
-
-Same applies to light client, as they do not need to deal with the state transition function.
-
----v
-
-### 😎 Forkless Upgrade
-
-<img style="width: 1400px;" src="./img/dev-4-1-forkless-1.svg" />
-
----v
-
-### 😎 Forkless Upgrade
-
-<img style="width: 1400px;" src="./img/dev-4-1-forkless-2.svg" />
-
----v
-
-### 😎 Forkless Upgrade
-
-This update was:
-
-1. Forkless
-2. Self-enacting
-
-Notes:
-
-take a moment to establish that this upgrade is forkless. The runtime is upgraded, but the client is
-not. In fact, the client didn't need to know about this at all.
-
-This is what the meta-protocol achieves.
-
----
-
-## Negative Consequences of _Wasm_ Runtime
-
-- 😩 Constrained resources (memory, speed, host access).
-- 🌈 Client diversification != state-transition diversification
-
-Notes:
-
-- 4GB of memory, which we limit even further.
-- Wasm has no allocator+panic handler of its own
-- Can be slower than native, depending on the executor/execution method.
-- Limited access to the host host env, all needs to be done through syscalls.
-
-Less state-transition diversification, because the runtime is the same for all clients.
-If there is a bug in it, everyone is affected.
-
----
-
-## Consensus <> Runtime 🤔
-
-- Yes, consensus is not a core part of a blockchain runtime. Why?
-- Not part of your STF!
-
-<!-- .element: class="fragment" -->
-
-- The consensus protocol is to your runtime what HTTP is to Facebook.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-comments from Joshy:
-
-I think this is important. The runtime is the application you want to run.
-
-Consensus is outside of this application helping us agree what the official state of this runtime
-is. Last wave I used this analogy.
-
-Imagine a writers room for some TV show. Writers are sitting around coming up with potential plot
-points for future episodes. Any of their ideas could work. But eventually they need to agree what
-the next episode to air actually will be.
-
----
-
-## Database <> State 🤔
-
-- State is the entire set of key value data that is associated with one block.
-- Database is the component that allows this be stored in disk. May or may not be key-value.
-
-<img style="width: 800px" src="./img/dev-4-1-state-database.svg" />
-
-Notes:
-
-State is sometimes called "storage" as well.
-
----
-
-## Database <> Runtime 🤔
-
-- Yes, data is stored outside of the runtime. Why?
-- Wasm runtime does not have the means to store it.
-
-<!-- .element: class="fragment" -->
-
-- Yet, the interpretation of the data is up to the runtime.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Database <> Runtime 🤔
-
-<img style="width: 1200px" src="./img/dev-4-1-state-opaque.svg" />
-
----v
-
-## The Client: Database 🤔
-
-- The database, from the client's PoV, is an _untyped_, key-value storage.
-- The runtime knows which key/value means what.
-
----
-
-## State of Light Clients
-
-- Client that follows headers, therefore knows state roots and can ask for state-proofs to do more.
-
----v
-
-### State of Light Clients
-
-<pba-cols>
-<pba-col>
-
-- Not only possible, but they can also run as Wasm, in the browser!
-- "Substrate Connect" / SMOLDOT
-
-</pba-col>
-<pba-col>
-
-<img style="width: 600px;" src="./img/dev-4-1-smoldot.svg" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-What was a light client? follows only block headers, therefore knows state roots, and a few other
-pieces of information, others send it state proofs if it wishes to do more.
-
-SMOLDOT is not exactly a substrate client. It is mainly designed to work with Polkadot. But with
-minimal tweaks, you could make it work for more substrate based chains.
-
-This has to do with the fact that consensus and a few other bits of the client and runtime are not
-100% independent. For example, GRANDPA has a pallet on the runtime side, but is mostly in the
-client. Now, a client that is configured with GRANDPA can only work with runtimes that are also
-configured with GRANDPA.
-
----
-
-## Communication Paths
-
-<img style="width: 1400px" src="./img/dev-4-1-comms.svg" />
-
----v
-
-### Communication Paths
-
-<img style="width: 1400px" src="./img/dev-4-1-comms-format.svg" />
-
----v
-
-### Example: SCALE vs JSON
-
-- SCALE is an efficient, non-descriptive, binary encoding format, used EXTENSIVELY in the Substrate ecosystem.
-
----v
-
-### Example: SCALE vs JSON
-
-```rust
-use parity_scale_codec::{Encode};
-
-#[derive(Encode)]
-struct Example {
-	number: u8,
-	is_cool: bool,
-	optional: Option<u32>,
-}
-
-fn main() {
-	let my_struct = Example {
-		number: 42,
-		is_cool: true,
-		optional: Some(69),
-	};
-	println!("{:?}", my_struct.encode());
-	// [42, 1, 1, 69, 0, 0, 0]
-	println!("{:?}", my_struct.encode().len());
-	// 7
-}
-```
-
----v
-
-### Example: SCALE vs JSON
-
-```rust
-use serde::{Serialize};
-
-#[derive(Serialize)]
-struct Example {
-	number: u8,
-	is_cool: bool,
-	optional: Option<u32>,
-}
-
-fn main() {
-	let my_struct = Example {
-		number: 42,
-		is_cool: true,
-		optional: Some(69),
-	};
-	println!("{:?}", serde_json::to_string(&my_struct).unwrap());
-	// "{\"number\":42,\"is_cool\":true,\"optional\":69}"
-	println!("{:?}", serde_json::to_string(&my_struct).unwrap().len());
-	// 42
-}
-```
-
----
-
-## Substrate and Polkadot
-
-<img style="width: 1400px;" src="./img/dev-4-1-polkadot.svg" />
-
----
-
-## Substrate and Smart Contracts
-
-<img style="width: 800px;" src="./img/dev-4-1-contracts.svg" />
-
----v
-
-### Substrate and Smart Contracts
-
-> A Substrate-Connect extension is syncing a chain who's runtime is executing wasm contracts.
-
-Question: How many nested Wasm blobs are executing one another?
-
----v
-
-### Substrate and Smart Contracts
-
-<pba-cols>
-<pba-col center>
-
-<img style="width: 600px;" src="./img/mind-blow-galaxy.gif" />
-
-</pba-col>
-<pba-col>
-
-- The browser is executing:
-- a Wasm blob (substrate-connect)
-- that executes a Wasm blob (runtime)
-- that executes a Wasm blob (contract)
-
-</pba-col>
-</pba-cols>
-
----v
-
-### Substrate and Smart Contracts
-
-<img style="width: 1000px;" src="./img/dev-4-1-ink.jpeg" />
-
----v
-
-### Substrate and Smart Contracts
-
-- So when should you write with a smart contract (Ink!) and when a Runtime (FRAME)?
-
-Notes:
-
-I was asked this yesterday as well. My latest answer is: if you don't need any of the customizations
-that a blockchain client/runtime gives to you, and the performance of a shared platform is okay for
-you, then go with a smart contract. If you need more, you need a "runtime" (some kind of chian,
-parachain or solo)
-
-An example of customization is that a runtime has access to `on_initialize` etc.
-
-Also, a contract can not have fee-less transactions.
-
-Also, a contract usually depends on a token for gas, while a runtime can be in principle token-less
-fee-less.
-
----
-
-## Technical Freedom vs Ease
-
-<img style="width: 1000px;" src="./img/dev-4-1-freedom.svg" />
-
----
-
-### Substrate: The Gaming Console of Blockchains!
-
-<pba-cols>
-<pba-col>
-
-<img src="./img/nintendo-console-2.png" style="width:400px;" />
-
-Substrate Client
-
-</pba-col>
-<pba-col>
-
-<img src="./img/nintendo-game.png" style="width:400px;" />
-
-Substrate's Wasm Runtime
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Another good analogy: Client is the FPGA, and FRAME/Wasm is the VHDL.
-
----
-
-## Lecture Recap
-
-- Substrate's design stems from 3 core principles:
-  - **Rust**, **Generic Design**, **Upgradeability/Governance**
-- Client / Runtime architecture
-- State Transition
-- Positive and negative consequences of Wasm
-- Substrate next to Polkadot and other chains.
-- Substrate for Smart Contracts.
-
----v
-
-### Recap: Substrate Architecture
-
-<img style="width: 1400px;" src="./img/dev-4-3-full.svg" />
-
----v
-
-## Recap: 🏦 Governance and Upgradeability
-
-A timeless system must be:
-
-1. Generic
-2. Governable
-3. Trust-less-ly Upgradeable.
-
-Substrate's Wasm meta-protocol exactly enables the latest ✅
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Question: how would you put the meta-protocol of Substrate into words?
-
-The client is basically a wasm meta-protocol that does only one thing. This meta-protocol is
-hardcoded, but the protocol itself is flexible.
-
----
-
-## Rest of This Module! 😈
-
-#### Track: Main Lectures
-
-- Wasm Meta Protocol
-- Substrate Storage
-
-#### Track: Aux Lecture
-
-- TX-Pool
-- Substrate: Show Me The Code
-- Substrate Interactions
-- SCALE
-
-#### Track: Graded Activity
-
-- FRAME-Less
-
----v
-
-### Rest of This Module! 😈
-
-#### Day 0
-
-- Introduction ✅ (60m)
-- Wasm Meta Protocol (120+m)
-  - Activity: Finding Runtime APIs and Host Functions in Substrate
-- 🌭 _Lunch Break_
-- Show Me The Code (60m)
-- Substrate Interactions (60m)
-- FRAME-Less Activity (60m)
-
-Notes:
-
-We are aware that the module is highly skewed in terms of lecture time, but it is intentional and we
-want to see how it works. This allows you to kickstart with your assignment earlier.
-
----v
-
-## Rest of This Module! 😈
-
-#### Day 1
-
-- Transaction Pool (60m)
-- SCALE (60m)
-- Substrate/FRAME Tips and Tricks
-- 🌭 _Lunch Break_
-- FRAME-Less Activity
-
----v
-
-## Rest of This Module! 😈
-
-#### Day 2
-
-- Substrate Storage (90m)
-- FRAME-Less Activity
-- 🌭 _Lunch Break_
-- End of Module 🎉
-
----
-
-## Additional Resources! 😋
-
-> Check speaker notes (click "s" 😉)
-
-<img width="300px" rounded src="../scale/img/thats_all_folks.png" />
-
-Notes:
-
-- Great documentation about all things substrate/blockchain from smoldot: <https://docs.rs/smoldot/latest/smoldot/>
-
-- Read more about why we use Rust at Parity: <https://www.parity.io/blog/why-rust/>
-
-- An interesting question on JVM/Wasm: <https://stackoverflow.com/questions/58131892/why-the-jvm-cannot-be-used-in-place-of-webassembly>
-
-- Rust safety: <https://stanford-cs242.github.io/f18/lectures/05-1-rust-memory-safety.html>
-- <https://www.reddit.com/r/rust/comments/5y3cxb/how_many_security_exploits_would_rust_prevent/>
-
-- The substrate clients should still have some level of _determinism in their performance_. If
-  authority nodes have extremely varied performances, they could start finalizing different forks.
-
-- There have been attempts at writing FRAME alternatives, namely AssemblyScript. <https://github.com/LimeChain/as-substrate-runtime>
-
-- Think about the differences between a runtime and a smart contract.
-
-  - A runtime is in some sense a smart contract as well, but not a user-deployed one.
-  - <https://en.wikipedia.org/wiki/Smart_contract>
-  - <https://www.futurelearn.com/info/courses/defi-exploring-decentralised-finance-with-blockchain-technologies/0/steps/251885#:~:text=to%20the%201990s.-,Writing%20in%201994%2C%20the%20computer%20scientist%20Nick%20Szabo%20defined%20a,of%20artificial%20intelligence%20is%20implied.>
-
-- Substrate Primitives (`sp-*`), Frame (`frame-*`) and the pallets (`pallets-*`), binaries (`/bin`)
-  and all other utilities are licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html).
-
-Substrate Client (`/client/*` / `sc-*`) is licensed under [GPL v3.0](https://www.gnu.org/licenses/gpl-3.0.html) with a [classpath linking exception](https://www.gnu.org/software/classpath/license.html).
-
-- Apache2 allows teams full freedom over what and how they release, and giving licensing clarity to
-  commercial teams.
-
-- GPL3 ensures any deeper improvements made to Substrate's core logic (e.g. Substrate's internal
-  consensus, crypto or database code) to be contributed back so everyone can benefit.
-
-- Currently, the Wasm binary spec v1 is used, read more about the new version here: <https://webassembly.github.io/spec/core/binary/index.html>
-
-### Post Lecture Feedback
-
-- a takeaway after each section, more clear path (shawn).
-
----
-
-## Appendix: What is Wasm Anyways?
-
-> WebAssembly (abbreviated Wasm) is a _binary instruction format_ for a _stack-based virtual
-> machine_. Wasm is designed as a _portable compilation_ target for programming languages, enabling
-> deployment on the web for client and server applications.
-
----v
-
-### What is Wasm Anyways?
-
-<img style="width: 1400px;" src="./img/dev-4-1-wasm-langs.svg" />
-
----v
-
-### What is Wasm Anyways?
-
-<pba-cols>
-<pba-col>
-
-- Wasm ❤️ Web
-- Streaming and rapid compilation.
-- Designed with the concept of host in mind.
-  Sandboxed, permissioned sys-calls.
-
-> Anyone remember "Java Applets"?
-
-</pba-col>
-<pba-col>
-
-<img style="height: 700px;" src="./img/dev-4-1-wasm.svg" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-People actually tried sticking things like JVM into the browser (_Java Applets_), but it didn't work.
-
----v
-
-### How to Write a Wasm Runtime?
-
-- Any language that can compile to Wasm and exposes a fixed set of functions, to be used by the client.
-- ... But, of course, Substrate comes with a framework to make this developer-friendly, **FRAME™️**.
-
----
-
-## Appendix: More Diagrams of Substrate and Polkadot
-
-Notes:
-
-I made these figures recently to explain the relationship between Substrate, Cumulus and Polkadot.
-They use the most generic term for client and runtime, namely "Host" and "STF" respectively.
-
----v
-
-Substrate
-
-<img style="width: 1400px;" src="./img/dev-4-1-substrate-new-1.svg" />
-
----v
-
-Polkadot
-
-<img style="width: 1400px;" src="./img/dev-4-1-substrate-new-2.svg" />
----v
-
-A Parachain
-
-<img style="width: 1400px;" src="./img/dev-4-1-substrate-new-3.svg" />
diff --git a/content/substrate/scale/page.md b/content/substrate/scale/page.md
deleted file mode 100644
index 9a691c8c..00000000
--- a/content/substrate/scale/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# SCALE Codec
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/substrate/scale/slides.md b/content/substrate/scale/slides.md
deleted file mode 100644
index cbea1e59..00000000
--- a/content/substrate/scale/slides.md
+++ /dev/null
@@ -1,669 +0,0 @@
----
-title: SCALE Codec
-description: SCALE Codec for web3 builders
-duration: 1 hour
----
-
-# SCALE Codec
-
----
-
-## SCALE Codec
-
-At the end of this lecture, you will learn why Substrate uses SCALE codec, how all different kinds of data types are encoded.
-
----
-
-### SCALE
-
-Simple Concatenated Aggregate Little-Endian
-
-SCALE is a light-weight format which allows encoding (and decoding) which makes it highly suitable for resource-constrained execution environments like blockchain runtimes and low-power, low-memory devices.
-
----
-
-### Little-Endian
-
-Little endian systems store the least significant byte at the smallest memory address.
-
-Wasm is a little endian system, which makes SCALE very performant.
-
-<pba-cols>
-<pba-col center>
-
-<img src="./img/Big-Endian.svg" style="background-color: white; border-radius: 10%; border: 5px solid red;" />
-
-</pba-col>
-
-<pba-col center>
-
-<img src="./img/Little-Endian.svg" style="background-color: white; border-radius: 10%; border: 5px solid green;" />
-
-</pba-col>
-</pba-cols>
-
----
-
-### Why SCALE? Why not X?
-
-- Simple to define.
-- Not Rust-specific (but happens to work great in Rust).
-  - Easy to derive codec logic: `#[derive(Encode, Decode)]`
-  - Viable and useful for APIs like: `MaxEncodedLen` and `TypeInfo`
-  - It does not use Rust `std`, and thus can compile to Wasm `no_std`.
-- Consensus critical / bijective; one value will always encode to one blob and that blob will only decode to that value.
-- Supports a copy-free decode for basic types on LE architectures.
-- It is about as thin and lightweight as can be.
-
----
-
-### SCALE is NOT Self-Descriptive
-
-It is important to note that the encoding context (knowledge of how the types and data structures look) needs to be known separately at both encoding and decoding ends.
-
-The encoded data does not include this contextual information.
-
----
-
-### Example: SCALE vs JSON
-
-<div class="flex-container text-smaller">
-<div class="left">
-
-```rust
-use parity_scale_codec::{ Encode };
-
-#[derive(Encode)]
-struct Example {
-	number: u8,
-	is_cool: bool,
-	optional: Option<u32>,
-}
-
-fn main() {
-	let my_struct = Example {
-		number: 42,
-		is_cool: true,
-		optional: Some(69),
-	};
-	println!("{:?}", my_struct.encode());
-	println!("{:?}", my_struct.encode().len());
-}
-```
-
-```sh
-[42, 1, 1, 69, 0, 0, 0]
-7
-```
-
-</div>
-<div class="right" style="margin-left: 10px;">
-
-```rust
-use serde::{ Serialize };
-
-#[derive(Serialize)]
-struct Example {
-	number: u8,
-	is_cool: bool,
-	optional: Option<u32>,
-}
-
-fn main() {
-	let my_struct = Example {
-		number: 42,
-		is_cool: true,
-		optional: Some(69),
-	};
-	println!("{:?}", serde_json::to_string(&my_struct).unwrap());
-	println!("{:?}", serde_json::to_string(&my_struct).unwrap().len());
-}
-```
-
-```sh
-"{\"number\":42,\"is_cool\":true,\"optional\":69}"
-42
-```
-
-</div>
-</div>
-
----
-
-### Try It Yourself!
-
-```sh
-mkdir temp
-cd temp
-cargo init
-cargo add parity-scale-codec --features derive
-```
-
----
-
-### Little vs Big Endian Output
-
-It can be confusing to read the output, and keep in mind endianness.
-
-The order of bytes in the vector follow endianness, but the hex and binary representation of each byte is the same, and independent of endianness.
-
-`0b` prefix denotes a binary representation, and `0x` denotes a hex representation.
-
-<pba-cols>
-<pba-col center>
-
-```rust
-fn main() {
-	println!("{:b}", 69i8);
-	println!("{:02x?}", 69i8.to_le_bytes());
-	println!("{:02x?}", 69i8.to_be_bytes());
-	println!("{:b}", 42u16);
-	println!("{:02x?}", 42u16.to_le_bytes());
-	println!("{:02x?}", 42u16.to_be_bytes());
-	println!("{:b}", 16777215u32);
-	println!("{:02x?}", 16777215u32.to_le_bytes());
-	println!("{:02x?}", 16777215u32.to_be_bytes());
-}
-```
-
-</pba-col>
-
-<pba-col center style="margin-left: 10px;">
-
-```sh
-1000101
-[45]
-[45]
-101010
-[2a, 00]
-[00, 2a]
-111111111111111111111111
-[ff, ff, ff, 00]
-[00, ff, ff, ff]
-```
-
-</pba-col>
-</pba-cols>
-
----
-
-### Fixed Width Integers
-
-Basic integers are encoded using a fixed-width little-endian (LE) format.
-
-```rust
-use parity_scale_codec::Encode;
-
-fn main() {
-	println!("{:02x?}", 69i8.encode());
-	println!("{:02x?}", 69u8.encode());
-	println!("{:02x?}", 42u16.encode());
-	println!("{:02x?}", 16777215u32.encode());
-}
-```
-
-```sh
-[45]
-[45]
-[2a, 00]
-[ff, ff, ff, 00]
-```
-
-Notes:
-
-notice the first two being the same. SCALE IS NOT DESCRIPTIVE of the type. The decoder is responsible for decoding this into some 1 byte-width type, be it u8 or i8 or something else.
-
----
-
-### Compact Integers
-
-A "compact" or general integer encoding is sufficient for encoding large integers (up to 2<sup>536</sup>) and is more efficient at encoding most values than the fixed-width version.
-
-Though for single-byte values, the fixed-width integer is never worse.
-
----
-
-### Compact Prefix
-
-<div class="text-small">
-
-<!-- prettier-ignore -->
-| `0b00` | `0b01` | `0b10` | `0b11` |
-| ------ | ------ | ------ | ------ |
-| single-byte mode; upper six bits are the LE encoding of the value. Valid only for values of `0` through `63`. | two-byte mode: upper six bits and the following byte is the LE encoding of the value. Valid only for values `64` through `(2^14 - 1)`. | four-byte mode: upper six bits and the following three bytes are the LE encoding of the value. Valid only for values `(2^14)` through `(2^30 - 1)`. |Big-integer mode: The upper six bits are the number of bytes following, plus four. The value is contained, LE encoded, in the bytes following. The final (most significant) byte must be non-zero. Valid only for values `(2^30)` through `(2^536 - 1)`. |
-
-</div>
-
-Compact/general integers are encoded with the two least significant **bits** denoting the mode.
-
----
-
-### Compact Integers: 0
-
-```rust
-use parity_scale_codec::{Encode, HasCompact};
-
-#[derive(Encode)]
-struct AsCompact<T: HasCompact>(#[codec(compact)] T);
-
-fn main() {
-	println!("{:02x?}", 0u8.encode());
-	println!("{:02x?}", 0u32.encode());
-	println!("{:02x?}", AsCompact(0u8).encode());
-	println!("{:02x?}", AsCompact(0u32).encode());
-}
-```
-
-```sh
-[00]
-[00, 00, 00, 00]
-[00]
-[00]
-```
-
----
-
-### Compact Integers: 42
-
-```rust
-use parity_scale_codec::{Encode, HasCompact};
-
-#[derive(Encode)]
-struct AsCompact<T: HasCompact>(#[codec(compact)] T);
-
-fn main() {
-	println!("{:02x?}", 42u8.encode());
-	println!("{:02x?}", 42u32.encode());
-	println!("{:02x?}", AsCompact(42u8).encode());
-	println!("{:02x?}", AsCompact(42u32).encode());
-}
-```
-
-```sh
-[2a]
-[2a, 00, 00, 00]
-[a8]
-[a8]
-```
-
-- 42 as binary: `0b101010` = `[0x2a]`.
-- Add `00` to the least significant bits.
-- `0b10101000` = `[0xa8]` = 168 as decimal.
-
----
-
-### Compact Integers: 69
-
-```rust
-use parity_scale_codec::{Encode, HasCompact};
-
-#[derive(Encode)]
-struct AsCompact<T: HasCompact>(#[codec(compact)] T);
-
-fn main() {
-	println!("{:02x?}", 69u8.encode());
-	println!("{:02x?}", 69u32.encode());
-	println!("{:02x?}", AsCompact(69u8).encode());
-	println!("{:02x?}", AsCompact(69u32).encode());
-}
-```
-
-```sh
-[45]
-[45, 00, 00, 00]
-[15, 01]
-[15, 01]
-```
-
-- 69 as binary: `0b1000101` = `[0x45]`.
-- Add `01` to the least significant bits.
-- `0b100010101` = `[0x15, 0x01]` = 277 as decimal.
-
----
-
-### Compact Integers: 65535 (u16::MAX)
-
-```rust
-use parity_scale_codec::{Encode, HasCompact};
-
-#[derive(Encode)]
-struct AsCompact<T: HasCompact>(#[codec(compact)] T);
-
-fn main() {
-	println!("{:02x?}", 65535u16.encode());
-	println!("{:02x?}", 65535u32.encode());
-	println!("{:02x?}", AsCompact(65535u16).encode());
-	println!("{:02x?}", AsCompact(65535u32).encode());
-}
-```
-
-```sh
-[ff, ff]
-[ff, ff, 00, 00]
-[fe, ff, 03, 00]
-[fe, ff, 03, 00]
-```
-
-- 65535 as binary: `0b1111111111111111` = `[0xff, 0xff]`.
-- Add `10` to the least significant bits.
-- `0b111111111111111110` = `[0xfe, 0xff, 0x03, 0x00]`: 262142 as decimal.
-
----
-
-### Compact Integers Are "Backwards Compatible"
-
-As you can see, you are able to "upgrade" a type without affecting the encoding.
-
----
-
-### Enum
-
-Prefix with index (`u8`), then the value, if any.
-
-```rust
-use parity_scale_codec::Encode;
-
-#[derive(Encode)]
-enum Example {
-	First,
-	Second(u8),
-	Third(Vec<u8>),
-	Fourth,
-}
-
-fn main() {
-	println!("{:02x?}", Example::First.encode());
-	println!("{:02x?}", Example::Second(2).encode());
-	println!("{:02x?}", Example::Third(vec![0, 1, 2, 3, 4]).encode());
-	println!("{:02x?}", Example::Fourth.encode());
-}
-```
-
-```sh
-[00]
-[01, 02]
-[02, 14, 00, 01, 02, 03, 04]
-[03]
-```
-
----
-
-### Tuple and Struct
-
-Just encode and concatenate the items.
-
-```rust
-use parity_scale_codec::Encode;
-
-#[derive(Encode)]
-struct Example {
-	number: u8,
-	is_cool: bool,
-	optional: Option<u32>,
-}
-
-fn main() {
-	let my_struct = Example {
-		number: 0,
-		is_cool: true,
-		optional: Some(69),
-	};
-	println!("{:02x?}", (0u8, true, Some(69u32)).encode());
-	println!("{:02x?}", my_struct.encode());
-}
-```
-
-```sh
-[00, 01, 01, 45, 00, 00, 00]
-[00, 01, 01, 45, 00, 00, 00]
-```
-
-Notes:
-
-Note that tuple and struct encode the same, even though struct has named fields.
-
----
-
-## Embedded Compact
-
-```rust
-use parity_scale_codec::Encode;
-
-#[derive(Encode)]
-struct Example {
-	number: u64,
-	#[codec(compact)]
-	compact_number: u64,
-}
-
-#[derive(Encode)]
-enum Choices {
-	One(u64, #[codec(compact)] u64),
-}
-
-fn main() {
-	let my_struct = Example { number: 42, compact_number: 1337 };
-	let my_choice = Choices::One(42, 1337);
-	println!("{:02x?}", my_struct.encode());
-	println!("{:02x?}", my_choice.encode());
-}
-```
-
-```sh
-[2a, 00, 00, 00, 00, 00, 00, 00, e5, 14]
-[00, 2a, 00, 00, 00, 00, 00, 00, 00, e5, 14]
-```
-
----
-
-### Unit, Bool, Option, and Result
-
-```rust
-use parity_scale_codec::Encode;
-
-fn main() {
-	println!("{:02x?}", ().encode());
-	println!("{:02x?}", true.encode());
-	println!("{:02x?}", false.encode());
-	println!("{:02x?}", Ok::<u32, ()>(42u32).encode());
-	println!("{:02x?}", Err::<u32, ()>(()).encode());
-	println!("{:02x?}", Some(42u32).encode());
-	println!("{:02x?}", None::<u32>.encode());
-}
-```
-
-```sh
-[]
-[01]
-[00]
-[00, 2a, 00, 00, 00]
-[01]
-[01, 2a, 00, 00, 00]
-[00]
-```
-
----
-
-### Arrays, Vectors, and Strings
-
-- Arrays: Just concatenate the items.
-- Vectors: Also prefix with length (compact encoded).
-- String: Just `Vec<u8>` as utf-8 characters.
-
-```rust
-use parity_scale_codec::Encode;
-
-fn main() {
-	println!("{:02x?}", [0u8, 1u8, 2u8, 3u8, 4u8].encode());
-	println!("{:02x?}", vec![0u8, 1u8, 2u8, 3u8, 4u8].encode());
-	println!("{:02x?}", "hello".encode());
-	println!("{:02x?}", vec![0u8; 1024].encode());
-}
-```
-
-```sh
-[00, 01, 02, 03, 04]
-[14, 00, 01, 02, 03, 04]
-[14, 68, 65, 6c, 6c, 6f]
-[01, 10, 00, 00, ... snip ... , 00]
-```
-
-Notes:
-
-Note that the length prefix can be multiple bytes, like the last example.
-
----
-
-### Decoding
-
-We can similarly take raw bytes, and decode it into a well known type.
-
-Metadata can be used to convey to a program how to decode a type properly...
-
-But bad or no information means the proper format for the data cannot be known.
-
----
-
-### Decoding Examples
-
-```rust
-use parity_scale_codec::{ Encode, Decode, DecodeAll };
-
-fn main() {
-	let array = [0u8, 1u8, 2u8, 3u8];
-	let value: u32 = 50462976;
-
-	println!("{:02x?}", array.encode());
-	println!("{:02x?}", value.encode());
-	println!("{:?}", u32::decode(&mut &array.encode()[..]));
-	println!("{:?}", u16::decode(&mut &array.encode()[..]));
-	println!("{:?}", u16::decode_all(&mut &array.encode()[..]));
-	println!("{:?}", u64::decode(&mut &array.encode()[..]));
-}
-```
-
-```sh
-[00, 01, 02, 03]
-[00, 01, 02, 03]
-Ok(50462976)
-Ok(256)
-Err(Error { cause: None, desc: "Input buffer has still data left after decoding!" })
-Err(Error { cause: None, desc: "Not enough data to fill buffer" })
-```
-
-Notes:
-
-- Decoding can fail
-- Values can decode badly
-
----
-
-### Decode Limits
-
-- Decoding isn't free!
-- The more complex the decode type, the more computation that will be used to decode the value.
-- Generally you always want to `decode_with_depth_limit`.
-- Substrate uses a limit of 256.
-
----
-
-### Decode Bomb
-
-Here is an example of a decode bomb.
-
-```rust
-use parity_scale_codec::{ Encode, Decode, DecodeLimit };
-
-#[derive(Encode, Decode, Debug)]
-enum Example {
-	First,
-	Second(Box<Self>),
-}
-
-fn main() {
-	let bytes = vec![1, 1, 1, 1, 1, 0];
-	println!("{:?}", Example::decode(&mut &bytes[..]));
-	println!("{:?}", Example::decode_with_depth_limit(10, &mut &bytes[..]));
-	println!("{:?}", Example::decode_with_depth_limit(3, &mut &bytes[..]));
-}
-```
-
-```sh
-Ok(Second(Second(Second(Second(Second(First))))))
-Ok(Second(Second(Second(Second(Second(First))))))
-Err(Error { cause: Some(Error { cause: Some(Error { cause: Some(Error { cause: Some(Error { cause: None, desc: "Maximum recursion depth reached when decoding" }), desc: "Could not decode `Example::Second.0`" }), desc: "Could not decode `Example::Second.0`" }), desc: "Could not decode `Example::Second.0`" }), desc: "Could not decode `Example::Second.0`" })
-```
-
----
-
-### Exceptions: BTreeSet
-
-BTreeSet will decode from an unordered set, but will also order them as a result.
-
-Be careful... this one isn't bijective.
-
-```rust
-use parity_scale_codec::{ Encode, Decode, alloc::collections::BTreeSet };
-
-fn main() {
-	let vector = vec![4u8, 3u8, 2u8, 1u8, 0u8];
-	let vector_encoded = vector.encode();
-	let btree = BTreeSet::<u8>::decode(&mut &vector_encoded[..]).unwrap();
-	let btree_encoded = btree.encode();
-
-	println!("{:02x?}", vector_encoded);
-	println!("{:02x?}", btree_encoded);
-}
-```
-
-```sh
-[14, 04, 03, 02, 01, 00]
-[14, 00, 01, 02, 03, 04]
-```
-
----
-
-### Optimizations and Tricks
-
-- `DecodeLength`: Read the length of a collection (like `Vec`) without decoding everything.
-
-- `EncodeAppend`: Append an item without decoding all the other items. (like `Vec`)
-
----
-
-### Implementations
-
-SCALE Codec has been implemented in other languages, including:
-
-- Python: [`polkascan/py-scale-codec`](https://github.com/polkascan/py-scale-codec/)
-- Golang: [`itering/scale.go`](https://github.com/itering/scale.go/)
-- C: [`MatthewDarnell/cScale`](https://github.com/MatthewDarnell/cScale/)
-- C++: [`soramitsu/scale-codec-cpp`](https://github.com/qdrvm/scale-codec-cpp/)
-- JavaScript: [`polkadot-js/api`](https://github.com/polkadot-js/api/)
-- TypeScript: [`scale-ts`](https://github.com/unstoppablejs/unstoppablejs/tree/main/packages/scale-ts#scale-ts)
-- AssemblyScript: [`LimeChain/as-scale-codec`](https://github.com/LimeChain/as-scale-codec/)
-- Haskell: [`airalab/hs-web3`](https://github.com/airalab/hs-web3/tree/master/packages/scale/)
-- Java: [`emeraldpay/polkaj`](https://github.com/emeraldpay/polkaj/)
-- Ruby: [`wuminzhe/scale_rb`](https://github.com/wuminzhe/scale_rb/)
-
----
-
-## Missing Some Metadata?
-
-To make SCALE useful as an encoding format within the Substrate and Polkadot ecosystem, we need to figure out a way to provide **metadata** about all the types we will expect, and when we will expect them.
-
-HINT: We do.
-
----
-
-### Remember, in the end of the day, everything is just 0's and 1's.
-
----
-
-## Additional Resources! 😋
-
-> Check speaker notes (click "s" 😉)
-
-<img width="300px" rounded src="./img/thats_all_folks.png" />
-
-Notes:
diff --git a/content/substrate/storage/img/dev-kv-backend.svg b/content/substrate/storage/img/dev-kv-backend.svg
deleted file mode 100644
index ff54cedf..00000000
--- a/content/substrate/storage/img/dev-kv-backend.svg
+++ /dev/null
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deleted file mode 100644
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diff --git a/content/substrate/storage/page.md b/content/substrate/storage/page.md
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-# Substrate Merklized Storage
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
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diff --git a/content/substrate/storage/slides.md b/content/substrate/storage/slides.md
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----
-title: Substrate Merklized Storage
-duration: 60mins
----
-
-# Substrate Storage
-
----
-
-## What We Know So Far
-
-<img style="width: 900px;" src="./img/dev-storage-1.svg" />
-
----v
-
-### What We Know So Far
-
-- Recall that at the `sp_io` layer, you have **opaque keys and values**.
-
-- `sp_io::storage::get(vec![8, 2])`;
-  - `vec![8, 2]` is a "storage key".
-- `sp_io::storage::set(vec![2, 9], vec![42, 33])`;
-
----v
-
-### What We Know So Far
-
-Nomenclature (with some simplification):
-
-> Environment providing host functions, namely storage ones: "`Externalities` Environment".
-
-Notes:
-
-- In Substrate, a type needs to provide the environment in which host functions are provided, and can be executed.
-- We call this an "externality environment", represented by [`trait Externalities`](https://paritytech.github.io/substrate/master/sp_externalities/trait.Externalities.html).
-- By convention, an externality has a "**backend**" that is in charge of dealing with storage.
-
----v
-
-### What We Know So Far
-
-```rust
-sp_io::TestExternalities::new_empty().execute_with(|| {
-  sp_io::storage::get(..);
-});
-```
-
----v
-
-### What We Know So Far
-
-<img style="width: 900px;" src="./img/dev-storage-2.svg" />
-
----
-
-## Key Value
-
-- How about a key-value storage externality? why not? 🙈
-
----v
-
-### Key Value
-
-<img style="width: 1200px;" src="./img/dev-kv-backend.svg" />
-
----v
-
-### Key Value
-
-- "_Storage keys_" (whatever you pass to `sp_io::storage`) directly maps to "_database keys_".
-- O(1) read and write.
-- Hash all the data to get the root.
-
-Notes:
-
-Good time to hammer down what you mean by storage key and what you mean by database key.
-
-literally imagine that in the implementation of `sp_io::storage::set`, we write it to a key-value
-database.
-
----v
-
-### Key Value
-
-- If alice only has this root, how can I prove to her how much balance she has?
-
-SEND HER THE WHOLE DATABASE 😱.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Alice is representing a light client, I represent a full node.
-
----v
-
-### Key Value
-
-- Moreover, if you change a single key-value, we need to re-hash the whole thing again to get the updated state root 🤦.
-
----
-
-## Substrate Storage: Merklized
-
-- This brings us again to why blockchain based systems tend to "merkelize" their storage.
-
----v
-
-### Merklized
-
-> Substrate uses a base-16, (patricia) radix merkle trie.
-
----v
-
-<pba-cols>
-<pba-col>
-
-<diagram class="mermaid">
-%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
-flowchart TD
-  A["A \n value: Hash(B|C)"] --> B["B \n value: Hash(B|E)"]
-  A --> C["C \n value: Hash(F) \n"]
-  B --> D["D \n value: 0x12"]
-  B --> E["E \n value: 0x23"]
-  C --> F["F \n value: 0x34"]
-</diagram>
-
-</pba-col>
-<pba-col>
-
-- Merkle tree.
-- Typically contains values at leafs.
-
-</pba-col>
-</pba-cols>
-
----v
-
-<pba-cols>
-<pba-col>
-
-<diagram class="mermaid">
-%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
-flowchart TD
-  A --b--> C["C \n Hash(F) \n"]
-  A["A \n value: Hash(B|C)"] -- a --> B["B \n value: Hash(B|E)"]
-  B --c--> D["D \n value: 0x12"]
-  B --d--> E["E \n value: 0x23"]
-  C --e--> F["F \n value: 0x34"]
-</diagram>
-
-</pba-col>
-<pba-col>
-
-- Trie.
-- Assuming only leafs have data, this is encoding:
-
-<table>
-<tr>
-  <td> "ac" => 0x12</td>
-</tr>
-<tr>
-  <td> "ad" => 0x23</td>
-</tr>
-<tr>
-  <td> "be" => 0x34</td>
-</tr>
-</table>
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-this is how we encode key value based data in a trie.
-
----v
-
-<pba-cols>
-<pba-col>
-
-<diagram class="mermaid">
-%%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
-flowchart TD
-  A["A \n Hash(B|C)"] -- a --> B["B \n Hash(B|E)"]
-  A --be--> F["F \n value: 0x34"]
-  B --c--> D["D \n value: 0x12"]
-  B --d--> E["E \n value: 0x23"]
-</diagram>
-
-</pba-col>
-<pba-col>
-
-- Radix Tree.
-- Less nodes to encode the same data.
-
-<table>
-<tr>
-  <td> "ac" => 0x1234</td>
-</tr>
-<tr>
-  <td> "ad" => 0x1234</td>
-</tr>
-<tr>
-  <td> "be" => 0x1234</td>
-</tr>
-</table>
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-More resources:
-
-- <https://en.wikipedia.org/wiki/Merkle_tree>
-- <https://en.wikipedia.org/wiki/Radix_tree>
-- <https://en.wikipedia.org/wiki/Trie>
-
-Namely:
-
-> The data structure was invented in 1968 by Donald R. Morrison, with whom it is primarily
-> associated, and by Gernot Gwehenberger.
-
-> Donald Knuth, pages 498-500 in Volume III of The Art of Computer Programming, calls these
-> "Patricia's trees", presumably after the acronym in the title of Morrison's paper: "PATRICIA -
-> Practical Algorithm to Retrieve Information Coded in Alphanumeric".
-> Today, Patricia tries are seen
-> as radix trees with radix equals 2, which means that each bit of the key is compared individually
-> and each node is a two-way (i.e., left versus right) branch.
-> ---v
-
-### Merklized
-
-> Substrate uses a base-16, (patricia) radix merkle trie.
-
----v
-
-### Merklized
-
-- Substrate does in fact use a key-value based database under the hood..
-- In order to store trie nodes, not direct storage keys!
-
-<br />
-
-<div>
-
-- We take the **storage key**, and make it be the path on a trie.
-
-</div>
-<!-- .element: class="fragment" -->
-
-<div>
-
-- Then we store the **trie nodes**, referenced by **their hash**, in the main database.
-
-</div>
-<!-- .element: class="fragment" -->
-
----v
-
-### Merklized
-
-<img style="width: 1400px;" src="./img/trie-backend-simple-simple.svg" />
-
-Notes:
-
-imagine:
-
-sp_io::storage::get(b"ad")
-
----v
-
-### Merklized
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-simple.svg" />
-
-Notes:
-
-realistically, the storage key is something like `(system_)16`, but I have put the strings here for
-simplification.
-
----
-
-## Trie Walking Example
-
-- We know the state-root at a given block `n`.
-- assume this is a base-26, patricia trie.
-  English alphabet is the key-scope.
-- Let's see the steps needed to read `balances_alice` from the storage.
-
----v
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-walk-m1.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-walk-0.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-walk-1.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-walk-2.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-walk-full.svg" />
-
----
-
-## Merklized: Proofs
-
-- If alice only has this root, how can I prove to her how much balance she has?
-
----v
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-proof.svg" />
-
-Notes:
-
-The important point is that for example the whole data under `_system` is not hidden away behind one hash.
-
-Dark blue are the proof, light blue's hashes are present.
-
-Receiver will hash the root node, and check it against a publicly known storage root.
-
-This differs slightly from how actual proof generation might work in the code.
-
-In general, you have a tradeoff: send more data, but require less hashing on Alice, or opposite (this is what we call "compact proof").
-
----v
-
-### Merklized: Proofs
-
-- 🏆 Small proof size is a big win for light clients, _and_ **Polkadot**.
-
----
-
-## Merklized: Recap
-
-<div>
-
-- Storage key (whatever you pass to `sp_io`) is the path on the trie.
-
-</div>
-<!-- .element: class="fragment" -->
-
-<div>
-
-- Storage key is arbitrary length.
-
-</div>
-<!-- .element: class="fragment" -->
-
-<div>
-
-- Intermediary (branch) nodes could contain values.
-  - `:code` contains some value, `:code:more` can also contain value.
-
-</div>
-
-<!-- .element: class="fragment" -->
-
-<div>
-
-- Storage Key != Database Key.
-- 1 Storage access = Many data base access.
-
-</div>
-<!-- .element: class="fragment" -->
-
-Notes:
-
-how many database access would do you think it is?
-
-we will explain this in a few slides, but assuming an order `N` tree, and assuming it is balanced,
-it will be `O(LOG_n)`.
-
----
-
-## Base 2, Base 16, Base-26?
-
-- Instead of alphabet, we use the base-16 representation of everything.
-
-> Base-16 (Patricia) Merkle Trie.
-
-- `System` -> `73797374656d`
-- `:code` -> `3a636f646500`
-
----v
-
-### Base 2, Base 16, Base-26?
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-16.svg" />
-<!-- TODO: update figure to represent node size. -->
-
-Tradeoff: "_IO count vs. Node size_"
-
-<!-- .element: class="fragment" -->
-
-Between a light clint and a full node, which one cares more about which?
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Light client cares about node size.
-When proof is being sent, there is no IO.
-
-First glance, the radix-8 seems better: you will typically have less DB access to reach a key.
-For example, with binary, with 3 IO, we can reach only 8 items, but with radix-8 512.
-
-So why should not choose a very wide tree?
-Because the wider you make the tree, the bigger each node gets, because it has to store more hashes.
-At some point, this start to screw with both the proof size and the cost of reading/writing/encoding/decoding all these nodes.
-
----v
-
-### Base 2, Base 16, Base-26?
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-16-with-size.svg" />
-
-Note:
-
-Here's a different way to represent it; the nodes are bigger on the base-16 trie.
-
----v
-
-### Base 2, Base 16, Base-26?
-
-- base-2: Small proofs, more nodes.
-- base-8: Bigger proofs, less nodes.
-
-✅ 16 has been benchmarked and studies years ago as a good middle-ground.
-
-Notes:
-
-Anyone interested in blockchain and research stuff should look into this.
-
----
-
-### Unbalanced Tree
-
-<img style="width: 800px;" src="./img/dev-trie-backend-unbalanced.svg" />
-
----v
-
-### Unbalanced Tree
-
-- Unbalanced tree means unbalanced performance.
-  An attack vector, if done right.
-- More about this in FRAME storage, and how it is prevented there.
-
-Notes:
-
-- under-estimate weight/gas etc.
-- You as the runtime developer must ensure that you use the right keys.
-- This is particularly an issue if an end user can control where they can insert into the trie!
-- The main prevention is using a cryptographically secure hash function on the frame side.
-
----
-
-## WAIT A MINUTE... 🤔
-
-- Two common scenarios that merkle proofs are kinda unfair:
-  - If the one of the parent nodes has some large data.
-  - If you want to prove the deletion/non-existence of a leaf node.
-
----v
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-proof-fat.svg" />
-
----v
-
-## WAIT A MINUTE... 🤔
-
-New "tie format" 🌈:
-
-- All data containing more than 32 bytes are replaced with their hash.
-- The (larger than 32 bytes) value itself stored in the database under this hash.
-
-```rust
-struct RuntimeVersion {
-  ...
-  state_version: 0,
-}
-```
-
-<!-- .element: class="fragment" -->
-
----v
-
-<img style="width: 1400px;" src="./img/dev-trie-backend-proof-fat-fix.svg" />
-<!-- TODO: update figure. -->
-
-What is the ramification of this for full nodes, and light clients?
-
-Notes:
-
-Both read and write have an extra step now, but proof are easier.
-
-Note from emeric: the green node is not really a "real" node, it is just `{ value: BIG_STUFF }` stored in the database.
-I will skip this detail for the sake of simplicity.
-One can assume that the green node is like any other node in the trie.
-
----
-
-## Substrate Storage: The Updated Picture
-
-<img style="width: 1000px;" src="./img/dev-storage-3.svg" />
-
----
-
-## WAIT A MINUTE... 🤔
-
-- We rarely care about state root and all the trie shenanigans before the end of the block...
-
-> A block-scoped cache for storage.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-In other words, one should care too much about updating a "trie" and all of its hashing details while the block is still being executed?
-All of that can be delayed.
-
----
-
-## Overlay
-
-- Is a cache layer outside of the Runtime.
-- It works **based on key-values**, **not trie-format**.
-
----v
-
-### Overlay
-
-- Almost identical semantic to your CPU cache:
-  - <!-- .element: class="fragment" --> Once you read a value, it stays here, and can be re-read for cheap.
-  - <!-- .element: class="fragment" --> Once you write a value, it will only be written here.
-    - It can be read for cheap.
-  - <!-- .element: class="fragment" --> All writes are flushed at the end of the runtime api call.
-- <!-- .element: class="fragment" --> No race conditions as runtime is single-threaded.
-
----v
-
-<img style="width: 1400px;" src="./img/dev-overlay.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-overlay-1.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-overlay-2.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-overlay-3.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-overlay-4.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-overlay-5.svg" />
-
----v
-
-### Overlay
-
-<pba-cols>
-
-<pba-col>
-
-- Cheap != Free
-
-</pba-col>
-<pba-col>
-
-<img style="width: 700px;" src="./img/dev-4-3-io.svg" />
-
-</pba-col>
-
-</pba-cols>
-
-Notes:
-
-- In your code, you often have an option to either pass stack variables around, or re-read code from `sp-io`.
-  Most often, this is a micro-optimization that won't matter too much, but in general you should know that the former is more performant, as won't go the the host at all.
-- A deletion is basically a write to `null`.
-
----v
-
-### Overlay
-
-- The overlay is also able to spawn child-overlays, known as "_storage layer_".
-- Useful for having a _transactional_ block of code.
-
-```rust
-// spawn a new layer.
-with_storage_layer(|| {
-    let foo = sp_io::storage::read(b"foo");
-    sp_io::storage::set(b"bar", foo);
-
-    if cond {
-        Err("this will be reverted")
-    } else {
-        Ok("This will be commit to the top overlay")
-    }
-})
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-- implement with zero-copy. So, the size of values is not so important, it is more about the number.
-
----v
-
-<img style="width: 1400px;" src="./img/dev-overlay-nested.svg" />
-
----v
-
-<img style="width: 1400px;" src="./img/dev-overlay-nested-1.svg" />
-
----v
-
-### Overlay
-
-- There is a limit to how many nested layers you can spawn
-- It is not free, thus it is attack-able.
-
-```rust
-with_storage_layer(|| {
-    let foo = sp_io::storage::read(b"foo");
-    with_storage_layer(|| {
-        sp_io::storage::set(b"foo", b"foo");
-        with_storage_layer(|| {
-            sp_io::storage::set(b"bar", foo);
-            with_storage_layer(|| {
-                sp_io::storage::set(b"foo", "damn");
-                Err("damn")
-            })
-            Ok("what")
-        })
-        Err("the")
-    });
-    Ok("hell")
-})
-```
-
----v
-
-### Overlay
-
-- What if I call `sp_io::storage::root()` in the middle of the block?
-- Can the overlay respond to this?
-
-Notes:
-
-NO!
-The overlay works on the level on key-values, it knows nothing of trie nodes, and to compute the root we have to go to the trie layer and pull a whole lot of data back from the disk and build all the nodes etc.
-
----v
-
-### Overlay: More Caches
-
-- There are more caches in the trie layer as well.
-  But outside of the scope of this lecture.
-
-```bash
-./substrate --help | grep cache
-```
-
-Notes:
-
-<https://www.youtube.com/embed/OoMPlJKUULY>
-
----
-
-### Substrate Storage: Final Figure
-
-<img style="width: 1000px;" src="./img/dev-storage-full.svg" />
-
----v
-
-### Substrate Storage
-
-There are multiple implementations of `Externalities`:
-
-- [`TestExternalities`](https://paritytech.github.io/substrate/master/sp_state_machine/struct.TestExternalities.html):
-  - `Overlay`
-  - `TrieDb` with `InMemoryBackend`
-- [`Ext`](https://paritytech.github.io/substrate/master/sp_state_machine/struct.Ext.html) (the real thing 🫡)
-  - `Overlay`
-  - `TrieDb` with a real database being the backend
-
----v
-
-### Substrate Storage
-
-- Recall: Any code accessing host functions needs to wrapped in something that implements
-  `Externalities`
-
-```rust
-// ❌
-let x = sp_io::storage::get(b"foo");
-
-// error:
-// thread '..' panicked at '`get_version_1` called outside of an Externalities-provided environment.'
-```
-
-```rust
-// ✅
-SomeExternalities.execute_with(|| {
-  let x = sp_io::storage::get(b"foo");
-});
-```
-
----
-
-## State Pruning
-
-- Each runtime will think that it has access to **_its_** full state, behind `sp_io::storage`.
-- Does the client then store one full trie per-block?
-
-Surely not.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-- Only trie nodes that are updated from one block to the other are created as new DB Keys.
-- For the unchanged ones, we only reference the existing one.
-
----v
-
-### State Pruning
-
-<img style="width: 1400px;" src="./img/dev-4-3-pruning-1.svg" />
----v
-
-### State Pruning
-
-<img style="width: 1400px;" src="./img/dev-4-3-pruning-2.svg" />
----v
-
-### State Pruning
-
-<img style="width: 1400px;" src="./img/dev-4-3-pruning-3.svg" />
----v
-
-### State Pruning
-
-<img style="width: 1400px;" src="./img/dev-4-3-pruning-4.svg" />
-
----v
-
-## State Pruning
-
-- 🧠 Data stored onchain, but rarely changed? De nada.
-- State pruning is an _entirely client side optimization_,
-
----
-
-## Child Trees
-
-<img style="width: 1400px;" src="./img/dev-4-3-child.svg" />
-
----v
-
-### Child Trees
-
-- Stored on a different DB Column (async-ish bulk deletion).
-- Most importantly, alternative trie formats.
-
----
-
-## Trie Format Matters!
-
-- Recall that in our "trie walking", we took the state root, and got the root node from the DB.
-- The state root of any substrate-based chain, including Polkadot, is the hash of the "Trie Node".
-
-> Trie format matters! and therefore it is part of [the polkadot spec](https://spec.polkadot.network).
-
-Notes:
-
-Meaning, if another client wants to sync polkadot, it should know the details of the trie format.
-
----
-
-#### Lecture Summary/Recap:
-
-<pba-cols>
-
-<pba-col>
-
-- KV-Based storage
-- Merklized storage, and proofs
-- Large nodes
-- Radix order consequences
-- Unbalanced trie
-- State pruning
-
-</pba-col>
-
-<pba-col>
-<img src="./img/dev-storage-full.svg" />
-</pba-col>
-
-</pba-cols>
-
----
-
-## Additional Resources! 😋
-
-> Check speaker notes (click "s" 😉)
-
-<img width="300px" rounded src="../scale/img/thats_all_folks.png" />
-
-Notes:
-
-- Shawn's deep dive: <https://www.shawntabrizi.com/substrate/substrate-storage-deep-dive/>
-
-- Basti's talk on Trie caching: <https://www.youtube.com/watch?v=OoMPlJKUULY>
-
-- About state version:
-
-  - <https://github.com/paritytech/substrate/pull/9732>
-  - <https://github.com/paritytech/substrate/discussions/11824>
-
-- An "old but gold" read about trie in Ethereum: <https://medium.com/shyft-network/understanding-trie-databases-in-ethereum-9f03d2c3325d>
-
-- On optimizing substrate storage proofs: <https://github.com/paritytech/substrate/issues/3782>
-- Underlying trie library maintained by Parity: <https://github.com/paritytech/trie>
-
-- <https://github.com/paritytech/trie/>
-
-- <https://spec.polkadot.network/chap-state#sect-state-storage>
-
-- <https://research.polytope.technology/state-(machine)-proofs>
-
-- An interesting, but heretical idea: can the runtime of block N, access state of block N-1?
-  HELL.
-  NO.
-  It might sound like a "but why nooooot" type of situation, but it breaks down all assumptions
-  about what a state transition is.
-  The runtime is the state transition function.
-  Recall the formula of that, and then you will know why this is not allowed.
-
-### Post Lecture Feedback
-
-Double check the narrative and example of the `BIG_STUFF` node.
-An example/exercise of some sort
-would be great, where students call a bunch of `sp_io` functions, visualize the trie, and invoke
-proof recorder, and see which parts of the trie is exactly part of the proof.
diff --git a/content/substrate/tips-tricks/page.md b/content/substrate/tips-tricks/page.md
deleted file mode 100644
index 3dd1abfa..00000000
--- a/content/substrate/tips-tricks/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Substrate and FRAME Tips and Tricks
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/substrate/tips-tricks/slides.md b/content/substrate/tips-tricks/slides.md
deleted file mode 100644
index c15b44c9..00000000
--- a/content/substrate/tips-tricks/slides.md
+++ /dev/null
@@ -1,1160 +0,0 @@
----
-title: Substrate and FRAME Tips and Tricks
-description: Substrate and FRAME Tips and Tricks for web3 builders
----
-
-# Substrate and FRAME Tips and Tricks
-
-Notes:
-
-- A random collection of things that you should probably know about.
-- These are relevant for coding in FRAME and Substrate.
-
----
-
-# Part 1 Substrate Stuff
-
----
-
-## `<Type as Trait>::AssociatedType`
-
-- The single most useful Rust syntactic detail that you _MUST_ know.
-
-Notes:
-
-what is a type? A struct is a type. An unum is a type. all primitives are type. A lot of things are
-types.
-
----v
-
-### `<Type as Trait>::AssociatedType`
-
-Example:
-
-```rust [1-4|1-8|1-12|14|1-100]
-trait Config {
-  type Extrinsic
-  type Header: HeaderT
-}
-
-pub type ExtrinsicFor<C> = <C as Config>::Extrinsic;
-fn process_extrinsic<C>(<C as Config>::Extrinsic) { .. }
-fn process_extrinsic<C>(BlockFor<C>) { .. }
-
-trait HeaderT {
-  type Number;
-}
-
-pub type NumberFor<C> = <<C as Config>::Header as HeaderT>::Number;
-```
-
-Notes:
-
-turbo fish
-fully qualified syntax.
-
----v
-
-### Speaking of Traits..
-
-- What is the difference between generics and associated types?
-
-```rust
-trait Block<Extrinsic> {
-  fn execute(e: Extrinsic)
-}
-```
-
-vs
-
-```rust
-trait Block {
-  type Extrinsic;
-  fn execute(e: Self::Extrinsic)
-}
-```
-
-Notes:
-
-In cambridge, I did this this. But since students should now know traits really well, I will drop it.
-
-```rust
-trait Engine {
-    fn start() {}
-}
-
-struct BMW;
-impl Engine for BMW {}
-
-trait Brand {
-    fn name() -> &'static str;
-}
-
-trait Car<E: Engine> {
-    type Brand: Brand;
-}
-
-struct KianCarCo;
-impl Brand for KianCarCo {
-  fn name() -> &'static str {
-    "KianCarCo!"
-    }
-}
-
-struct MyCar;
-impl<E: Engine> Car<E> for MyCar {
-    type Brand = MyBrand;
-}
-
-fn main() {
-    // Car<E1>, Car<E2> are different traits!
-
-    // Generics can be bounded, or constrained
-    // impl<E: Engine> Car<E> {}
-    // impl Car<BMW> {}
-
-    // Associated types can:
-    // only be bounded when being defined,
-    // Can be constrained when being implemented, or when the trait is being used.
-    fn some_fn<E: Engine, C: Car<E, Brand = MyBrand>>(car: C) {
-      // and we are told associated types are more like output types, lets get the brand of car
-      let name = <<C as Car<E>>::Brand as Brand>::name();
-    }
-    fn other_fn<C: Car<BMW, Brand = MyBrand>>(car: C) {
-
-    }
-
-    // now, check this out
-}
-```
-
----v
-
-### Speaking of Traits..
-
-Both generics and associated types can be specified, but the syntax is a bit different.
-
-```rust
-trait Block<Extrinsic> {
-  type Header
-}
-
-fn process_block<B: Block<E1, Header = H1>>(b: B)
-```
-
----v
-
-### Speaking of Traits..
-
-- Anything that can be expressed with associated types can also be expressed with generics.
-- Associated Types << Generics
-- Associated types usually lead to less boilerplate.
-
----
-
-## The `std` Paradigm
-
-- Recap:
-
-  - `std` is the interface to the common OS-abstractions.
-  - `core` is a subset of `std` that makes no assumption about the operating system.
-
-- a `no_std` crate is one that relies on `core` rather than `std`.
-
----v
-
-### Cargo Features
-
-- Way to compile different code via flags.
-- Crates define some features in their `Cargo.toml`
-- Crates can conditionally enable features of their dependencies as well.
-
-```toml
-[dependencies]
-other-stuff = { version = "1.0.0" }
-
-[features]
-default = [""]
-additional-features = ["other-stuff/on-steroids"]
-```
-
-Notes:
-
-imagine that you have a crate that has some additional features that are not always needed. You put
-that behind a feature flag called `additional-features`.
-
----v
-
-### Cargo Features: Substrate Wasm Crates
-
-```toml
-[dependencies]
-dep1 = { version = "1.0.0", default-features = false }
-dep2 = { version = "1.0.0", default-features = false }
-
-[features]
-default = ["std"]
-std = [
-  "dep1/std"
-  "dep2/std"
-]
-```
-
-Notes:
-
-every crate will have a feature "std". This is a flag that you are compiling with the standard
-library. This is the default.
-
-Then, bringing a dependency with `default-features = false` means by default, don't enable this
-dependencies "std".
-
-Then, in `std = ["dep/std"]` you are saying "if my std is enabled, enable my dependencies std as
-well".
-
----v
-
-### Cargo Features
-
-- The name "`std`" is just an idiom in the rust ecosystem.
-- `no_std` does NOT mean Wasm!
-- `std` does not mean native!
-
-Notes:
-
-But in substrate, it kinda means like that:
-
-std => native
-no_std => wasm
-
----v
-
-### The `std` Paradigm
-
-- All crates in substrate that eventually compile to Wasm:
-
-```rust
-#![cfg_attr(not(feature = "std"), no_std)]
-```
-
----v
-
-### The `std` Paradigm: Adding dependencies
-
-```sh
-error: duplicate lang item in crate sp_io (which frame_support depends on): panic_impl.
-  |
-  = Notes:
-
-
- the lang item is first defined in crate std (which serde depends on)
-
-error: duplicate lang item in crate sp_io (which frame_support depends on): oom.
-  |
-  = Notes:
-
-
- the lang item is first defined in crate std (which serde depends on)
-```
-
----v
-
-### The `std` Paradigm
-
-A subset of the standard types in rust that also exist in rust `core` are re-exported from
-[`sp_std`](https://paritytech.github.io/substrate/master/sp_std/index.html).
-
-```rust
-sp_std::prelude::*;
-```
-
-Notes:
-
-Hashmap not exported due to non-deterministic concerns.
-floats are usable, but also non-deterministic! (and I think they lack `encode`, `decode` impl)
-
-interesting to look at `if_std` macro in `sp_std`.
-
----
-
-## Logging And Prints In The Runtime.
-
-- First, why bother? let's just add as many logs as we want into the runtime.
-
-<!-- .element: class="fragment" -->
-
-- Size of the wasm blob matters..
-
-<!-- .element: class="fragment" -->
-
-- Any logging increases the size of the Wasm blob. **String literals** are stored somewhere in your
-  program!
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Logging And Prints In The Runtime.
-
-- `wasm2wat polkadot_runtime.wasm > dump | rg stripped`
-
-- Should get you the `.rodata` (read-only data) line of the wasm blob, which contains all the logging
-  noise.
-
-- This contains string literals form errors, logs, metadata, etc.
-
----v
-
-### Logging And Prints In The Runtime.
-
-```rust
-#[derive(sp_std::fmt::Debug)]
-struct LONG_AND_BEAUTIFUL_NAME {
-  plenty: u32,
-  of: u32,
-  fields: u32,
-  with: u32,
-  different: u32
-  names: u32
-}
-```
-
-will add a lot of string literals to your wasm blob.
-
----v
-
-### Logging And Prints In The Runtime.
-
-`sp_std::fmt::Debug` vs `sp_debug_derive::RuntimeDebug`
-
-Notes:
-
-<https://paritytech.github.io/substrate/master/sp_debug_derive/index.html>
-
----v
-
-### Logging And Prints In The Runtime.
-
-```rust
-#[derive(RuntimeDebug)]
-pub struct WithDebug {
-    foo: u32,
-}
-
-impl ::core::fmt::Debug for WithDebug {
-    fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
-        #[cfg(feature = "std)]
-        {
-          fmt.debug_struct("WithRuntimeDebug")
-            .field("foo", &self.foo)
-            .finish()
-        }
-        #[cfg(not(feature = "std))]
-        {
-          fmt.write("<wasm:stripped>")
-        }
-    }
-}
-```
-
----v
-
-### Logging And Prints In The Runtime.
-
-Once types implement `Debug` or `RuntimeDebug`, they can be printed. Various ways:
-
-- If you only want something in tests, native builds etc
-
-```rust
-sp_std::if_std! {
-  println!("hello world!");
-  dbg!(foo);
-}
-```
-
----v
-
-### Logging And Prints In The Runtime.
-
-- Or you can use the common `log` crate
-
-```rust
-log::info!(target: "foo", "hello world!");
-log::debug!(target: "bar", "hello world! ({})", 10u32);
-```
-
----v
-
-### Logging And Prints In The Runtime.
-
-- But `log` crate doesn't do much in itself! it needs two additional steps to work:
-
-1. `// $ RUST_LOG=foo=debug,bar=trace cargo run`
-2. `sp_tracing::try_init_simple()`
-
-Notes:
-
-<https://paritytech.github.io/substrate/master/sp_tracing/index.html>
-
----v
-
-### Logging And Prints In The Runtime.
-
-- Log statements are only evaluated if the corresponding level and target is met.
-
-```rust
-/// only executed if `RUST_LOG=KIAN=trace`
-frame_support::log::trace!(target: "KIAN", "({:?})", (0..100000).into_iter().collect());
-```
-
-Notes:
-
-`log` in rust does not do anything -- it only tracks what needs to be logged. Then you need a logger
-to actually export them. In rust this is often `env_logger` or `sp_tracing` in substrate tests.
-
-In the runtime, the log messages are sent via the host functions to the client to be printed.
-
-If the interface is built with `disable-logging`, it omits all log messages.
-
----
-
-## Arithmetic Helpers, and the `f32`, `f64` Story.
-
-- Floating point numbers have different standards, and (**_slightly_**) different implementations on
-  different architectures and vendors.
-
-- If my balance is `10.000000000000001` DOT on one validator and `10.000000000000000` DOT on another validator, game over for your consensus 😮‍💨.
-
----v
-
-### PerThing.
-
-```python
-> .2 + .2 + .2 == .6
-> false
-```
-
-```
-> a = 10
-> b = 0.1
-> c = 0.2
-> a*(b+c) == a*b + a*c
-> false
-```
-
-- Search "weird float behavior" for more entertainment around this.
-
----v
-
-### PerThing.
-
-- We store ratios and such in the runtime with "Fixed-Point" arithmetic types.
-
-```rust
-struct Percent(u8);
-
-impl Percent {
-  fn new(x: u8) {
-    Self(x.min(100));
-  }
-}
-
-impl Mul<u32> for Percent {
-  ...
-}
-```
-
----v
-
-### PerThing.
-
-```rust
-use sp_arithmetic::Perbill;
-
-let p = Perbill::from_part_parts(1_000_000_000u32 / 4);
-let p = Perbill::from_percent(25);
-let p = Perbill::from_rational(1, 4);
-
-> p * 100u32;
-> 25u32;
-```
-
-- Some precision concerns exist, but that's a story for another day.
-
----v
-
-### Fixed Point Numbers
-
-`Per-thing` is great for representing `[0, 1]` range.
-
-What if we need more?
-
-```
-100 ~ 1
-200 ~ 2
-300 ~ 3
-350 ~ 3.5
-```
-
----v
-
-### Fixed Point Numbers
-
-```rust
-use sp_arithmetic::FixedU64;
-
-let x = FixedU64::from_rational(5, 2);
-let y = 10u32;
-let z = x * y;
-> 25
-```
-
----v
-
-### Larger Types
-
-- [`U256`](https://paritytech.github.io/substrate/master/sp_core/struct.U256.html), `U512`: battle-tested since the ethereum days.
-- [substrate-fixed](https://github.com/encointer/substrate-fixed): community project. Supercharged `PerThing` and `Fixed`.
-- [`big_uint.rs`](https://paritytech.github.io/substrate/master/sp_arithmetic/biguint/index.html) (unaudited)
-
-```rust
-pub struct BigUint {
-	/// digits (limbs) of this number (sorted as msb -> lsb).
-	pub(crate) digits: Vec<Single>,
-}
-```
-
----v
-
-### Arithmetic Types
-
-- See [`sp-arithmetic`](https://paritytech.github.io/substrate/master/sp_arithmetic/index.html) to
-  learn more.
-
----
-
-### Fallibility: Math Operations
-
-Things like **addition**, **multiplication**, **division** could all easily fail.
-
-<div>
-
-- Panic
-  - `u32::MAX * 2 / 2` (in debug builds)
-  - `100 / 0`
-
-</div>
-
-<!-- .element: class="fragment" -->
-
-<div>
-
-- Overflow
-  - `u32::MAX * 2 / 2` (in release builds)
-
-</div>
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Fallibility: Math Operations
-
-- `Checked` -- prevention ✋🏻
-
-  ```
-  if let Some(outcome) = a.checked_mul(b) { ... } else { ... }
-  ```
-
-- `Saturating` -- silent recovery 🤫
-
-  ```
-  let certain_output = a.saturating_mul(b);
-  ```
-
-Notes:
-
-Why would you ever want to saturate? only in cases where you know if the number is overflowing,
-other aspects of the system is so fundamentally screwed that there is no point in doing any kind of
-recovery.
-
-There's also `wrapping_op` and `carrying_op` etc on all rust primitives, but not quite
-relevant.
-
-<https://doc.rust-lang.org/std/primitive.u32.html#method.checked_add>
-<https://doc.rust-lang.org/std/primitive.u32.html#method.saturating_add>
-
----v
-
-### Fallibility: Conversion
-
-```rust
-fn main() {
-    let a = 1000u32 as u8;
-    println!("{}", a); //
-}
-```
-
-Notes:
-
-conversion of primitive number types is also a common point of error. Avoid `as`.
-
----v
-
-### Fallibility: Conversion
-
-- Luckily, rust is already pretty strict for the primitive types.
-- `TryInto` / `TryFrom` / `From` / `Into`
-
-```rust
-impl From<u16> for u32 {
-  fn from(x: u16) -> u32 {
-    x as u32 // ✅
-  }
-}
-```
-
-<!-- .element: class="fragment" -->
-
-```rust
-impl TryFrom<u32> for u16 {
-  fn try_from(x: u32) -> Result<u16, _> {
-    if x >= u16::MAX { Err(_) } else { Ok(x as u16) }
-  }
-}
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Typically you don't implement `Into` and `TryInto`, because of blanket impls. See:
-<https://doc.rust-lang.org/std/convert/trait.From.html>
-
-For any T and U, `impl From<T> for U` implies `impl Into<U> for T`
-
----v
-
-### Fallibility: Conversion
-
-- `struct Foo<T: From<u32>>`
-
-T is u32 or larger.
-
-<!-- .element: class="fragment" -->
-
-- `struct Foo<T: Into<u32>>`
-
-`T` is u32 or smaller.
-
-<!-- .element: class="fragment" -->
-
-- `struct Foo<T: TryInto<u32>>`
-
-`T` can be any of numeric types.
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Fallibility: Conversion
-
-- Substrate also provides a trait for infallible saturated conversion as well.
-- See `sp-arithmetic` for more handy stuff.
-
-```rust
-trait SaturatedConversion {
-  fn saturated_into<T>(self) -> T
-}
-
-assert_eq!(u128::MAX.saturating_into::<u32>(), u32::MAX);
-```
-
-Notes:
-
-<https://paritytech.github.io/substrate/master/sp_arithmetic/traits/trait.SaturatedConversion.html>
-
----
-
-# Part 2: FRAME Stuff
-
----
-
-## `trait Get`
-
-A very basic, yet very substrate-idiomatic way to pass _values_ through _types_.
-
-```rust
-pub trait Get<T> {
-  fn get() -> T;
-}
-```
-
-```rust
-// very basic blanket implementation, which you should be very versed in reading.
-impl<T: Default> Get<T> for () {
-  fn get() -> T {
-    T::default()
-  }
-}
-```
-
-<!-- .element: class="fragment" -->
-
-```rust
-struct Foo<G: Get<u32>>;
-let foo = Foo<()>;
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-implementing defaults for `()` is a very FRAME-idiomatic way of doing things.
-
----v
-
-### `trait Get`
-
-```rust
-parameter_types! {
-  pub const Foo: u32 = 10;
-}
-```
-
-```rust
-// expands to:
-pub struct Foo;
-impl Get<u32> for Foo {
-  fn get() -> u32 {
-    10;
-  }
-}
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-You have implemented this as a part of your rust exam.
-
----
-
-## `bounded`
-
-- `BoundedVec`, `BoundedSlice`, `BoundedBTreeMap`, `BoundedSlice`
-
-```rust
-#[derive(Encode, Decode)]
-pub struct BoundedVec<T, S: Get<u32>>(
-  pub(super) Vec<T>,
-  PhantomData<S>,
-);
-```
-
-- &shy;<!-- .element: class="fragment" --> `PhantomData`?
-
----v
-
-### `bounded`
-
-- Why not do a bounded type like this? 🤔
-
-```rust
-#[cfg_attr(feature = "std", derive(Serialize))]
-#[derive(Encode)]
-pub struct BoundedVec<T>(
-  pub(super) Vec<T>,
-  u32,
-);
-```
-
----v
-
-### `bounded`
-
-_`Get` trait is a way to convey values through types. The type system is mostly for compiler, and
-has minimal overhead at runtime._
-
----
-
-## `trait Convert`
-
-```rust
-pub trait Convert<A, B> {
-	fn convert(a: A) -> B;
-}
-```
-
-```rust
-pub struct Identity;
-// blanket implementation!
-impl<T> Convert<T, T> for Identity {
-	fn convert(a: T) -> T {
-		a
-	}
-}
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-this one's much simpler, but good excuse to teach them blanket implementations.
-
----v
-
-### Example of `Get` and `Convert`
-
-```rust
-/// Some configuration for my module.
-trait Config {
-  /// Something that gives you a `u32`.
-  type MaximumSize: Get<u32>;
-  /// Something that is capable of converting `u64` to `u32`,
-  /// which is pretty damn hard.
-  type Convertor: Convertor<u64, u32>;
-}
-```
-
-```rust
-struct Runtime;
-impl Config for Runtime {
-  type MaximumSize = ();
-  type Convertor = SomeType
-}
-```
-
-<!-- .element: class="fragment" -->
-
-```rust
-Runtime as Config>::Convertor::convert(_, _);
-```
-
-<!-- .element: class="fragment" -->
-
-```rust
-fn generic_fn<T: Config>() { <T as Config>::Convertor::convert(_, _)}
-```
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-often times, in examples above, you have to use this syntax: <https://doc.rust-lang.org/book/ch19-03-advanced-traits.html#fully-qualified-syntax-for-disambiguation-calling-methods-with-the-same-name>
-
----
-
-## Implementing Traits For Tuples
-
-```rust
-struct Module1;
-struct Module2;
-struct Module3;
-
-trait OnInitialize {
-  fn on_initialize();
-}
-
-impl OnInitialize for Module1 { fn on_initialize() {} }
-impl OnInitialize for Module2 { fn on_initialize() {} }
-impl OnInitialize for Module3 { fn on_initialize() {} }
-```
-
-How can I easily invoke `OnInitialize` on all 3 of `Module1, Module2, Module3`?
-
-Notes:
-
-Alternative, but this needs allocation:
-
-```
-struct Module1;
-struct Module2;
-struct Module3;
-
-trait OnInitializeDyn {
-  fn on_initialize(&self);
-}
-
-impl OnInitializeDyn for Module1 { fn on_initialize(&self) {} }
-impl OnInitializeDyn for Module2 { fn on_initialize(&self) {} }
-impl OnInitializeDyn for Module3 { fn on_initialize(&self) {} }
-
-fn main() {
-    let x: Vec<Box<dyn OnInitializeDyn>> = vec![Box::new(Module1), Box::new(Module2)];
-    x.iter().for_each(|i| i.on_initialize());
-}
-```
-
----v
-
-### Implementing Traits For Tuples
-
-1. `on_initialize`, in its ideal form, does not have `&self`, it is defined on the **type**, not a **value**.
-
-1. **Tuples** are the natural way to group **types** together (analogous to have a **vector** is the natural way to group **values** together..)
-
-```rust
-// fully-qualified syntax - turbo-fish.
-<(Module1, Module2, Module3) as OnInitialize>::on_initialize();
-```
-
----v
-
-### Implementing Traits For Tuples
-
-Only problem: A lot of boilerplate. Macros!
-
-Historically, we made this work with `macro_rules!`
-
-Notes:
-
-```rust
-macro_rules! impl_for_tuples {
-    ( $( $elem:ident ),+ ) => {
-        impl<$( $elem: OnInitialize, )*> OnInitialize for ($( $elem, )*) {
-            fn on_initialize() {
-                $( $elem::on_initialize(); )*
-            }
-        }
-    }
-}
-
-impl_for_tuples!(A, B, C, D);
-impl_for_tuples!(A, B, C, D, E);
-impl_for_tuples!(A, B, C, D, E, F);
-```
-
----v
-
-### Implementing Traits For Tuples
-
-And then someone made `impl_for_tuples` crate.
-
-```rust
-// In the most basic form:
-#[impl_for_tuples(30)]
-pub trait OnTimestampSet<Moment> {
-	fn on_timestamp_set(moment: Moment);
-}
-```
-
-Notes:
-
-<https://docs.rs/impl-trait-for-tuples/latest/impl_trait_for_tuples/>
-
----
-
-## Defensive Programming
-
-> ..is a form of defensive design to ensure the continuing function of a piece of software under
-> unforeseen circumstances... where **high availability**, **safety**, or **security** is needed.
-
-- As you know, you should (almost) never panic in your runtime code.
-
----v
-
-### Defensive Programming
-
-- First reminder: don't panic, unless if you want to punish someone!
-- `.unwrap()`? no no
-
-<br />
-
-- be careful with implicit unwraps in standard operations!
-  - slice/vector indexing can panic if out of bound
-  - `.insert`, `.remove`
-  - division by zero.
-
----v
-
-### Defensive Programming
-
-- When using operations that could panic, comment exactly above it why you are sure it won't panic.
-
-```rust
-let pos = announcements
-  .binary_search(&announcement)
-  .ok()
-  .ok_or(Error::<T, I>::MissingAnnouncement)?;
-// index coming from `binary_search`, therefore cannot be out of bound.
-announcements.remove(pos);
-```
-
----v
-
-### Defensive Programming: QED
-
-Or when using options or results that need to be unwrapped but are known to be `Ok(_)`, `Some(_)`:
-
-```rust
-let maybe_value: Option<_> = ...
-if maybe_value.is_none() {
-  return "..."
-}
-
-let value = maybe_value.expect("value checked to be 'Some'; qed");
-```
-
-- Q.E.D. or QED is an initialism of the Latin phrase "quod erat demonstrandum", meaning "**which was to be demonstrated**".
-
----v
-
-### Defensive Programming
-
-When writing APIs that could panic, explicitly document them, just like the core rust documentation.
-
-```rust
-/// Exactly the same semantics as [`Vec::insert`], but returns an `Err` (and is a noop) if the
-/// new length of the vector exceeds `S`.
-///
-/// # Panics
-///
-/// Panics if `index > len`.
-pub fn try_insert(&mut self, index: usize, element: T) -> Result<(), ()> {
-  if self.len() < Self::bound() {
-    self.0.insert(index, element);
-    Ok(())
-  } else {
-    Err(())
-  }
-}
-```
-
----v
-
-### Defensive Programming
-
-- Speaking of documentation, [here's a very good guideline](https://doc.rust-lang.org/rustdoc/how-to-write-documentation.html)!
-
-````rust
-/// Multiplies the given input by two.
-///
-/// Some further information about what this does, and where it could be used.
-///
-/// ```
-/// fn main() {
-///   let x = multiply_by_2(10);
-///   assert_eq!(10, 20);
-/// }
-/// ```
-///
-/// ## Panics
-///
-/// Panics under such and such condition.
-fn multiply_by_2(x: u32) -> u32 { .. }
-````
-
----v
-
-### Defensive Programming
-
-- Try and not be this guy:
-
-```rust
-/// This function works with module x and multiples the given input by two. If
-/// we optimize the other variant of it, we would be able to achieve more
-/// efficiency but I have to think about it. Probably can panic if the input
-/// overflows u32.
-fn multiply_by_2(x: u32) -> u32 { .. }
-```
-
----v
-
-### Defensive Programming
-
-- The overall ethos of defensive programming is along the lines of:
-
-```rust
-// we have good reasons to believe this is `Some`.
-let y: Option<_> = ...
-
-// I am really really sure about this
-let x = y.expect("hard evidence; qed");
-
-// either return a reasonable default..
-let x = y.unwrap_or(reasonable_default);
-
-// or return an error (in particular in dispatchables)
-let x = y.ok_or(Error::DefensiveError)?;
-```
-
-Notes:
-
-But, for example, you are absolutely sure that `Error::DefensiveError` will never happen, can we enforce it better?
-
----v
-
-### Defensive Programming
-
-```rust
-let x = y
-  .ok_or(Error::DefensiveError)
-  .map_err(|e| {
-    #[cfg(test)]
-    panic!("defensive error happened: {:?}", e);
-
-    log::error!(target: "..", "defensive error happened: {:?}", e);
-  })?;
-```
-
----v
-
-### Defensive Programming
-
-- Yes: [Defensive traits](https://paritytech.github.io/substrate/master/frame_support/traits/trait.Defensive.html):
-
-```
-// either return a reasonable default..
-let x = y.defensive_unwrap_or(reasonable_default);
-
-// or return an error (in particular in dispatchables)
-let x = y.defensive_ok_or(Error::DefensiveError)?;
-```
-
-It adds some boilerplate to:
-
-1. Panic when `debug_assertions` are enabled (tests).
-1. append a `log::error!`.
-
----
-
-## Additional Resources! 😋
-
-<img width="300px" rounded src="../scale/img/thats_all_folks.png" />
-
-> Check speaker notes (click "s" 😉)
-
-> Good luck with FRAME!
-
-Notes:
-
-- Rust didn't have u128 until not too long ago! <https://github.com/paritytech/substrate/pull/163/files>
-- `TryFrom`/`TryInto` are also not too old! <https://github.com/paritytech/substrate/pull/163/files#r188938077>
-- Remove `As`, which tried to fill the lack of `TryFrom/TryInto` <https://github.com/paritytech/substrate/pull/2602>
-- Runtime Logging PR: <https://github.com/paritytech/substrate/pull/3821>
-
-- Impl trait for tuples:
-
-  - <https://stackoverflow.com/questions/64332037/how-can-i-store-a-type-in-an-array>
-  - <https://doc.rust-lang.org/book/ch17-02-trait-objects.html#trait-objects-perform-dynamic-dispatch>
-  - <https://doc.rust-lang.org/book/ch19-03-advanced-traits.html#fully-qualified-syntax-for-disambiguation-calling-methods-with-the-same-name>
-  - <https://turbo.fish/>
-  - <https://techblog.tonsser.com/posts/what-is-rusts-turbofish>
-  - <https://docs.rs/impl-trait-for-tuples/latest/impl_trait_for_tuples/>
-
-- std/no_std
-  - <https://paritytech.github.io/substrate/master/sp_std/index.html>
-  - <https://doc.rust-lang.org/core/index.html>
-  - <https://doc.rust-lang.org/std/index.html>
-  - <https://rust-lang.github.io/api-guidelines/naming.html#feature-names-are-free-of-placeholder-words-c-feature>
-
-### Feedback After Lecture:
-
-- Lecture is still kinda dense and long, try and trim
-- Update on defensive ops: <https://github.com/paritytech/substrate/pull/12967>
-- Next time, talk about making a storage struct be `<T: Config>`.
-- Cargo format
-- SignedExtension should technically be part of the substrate module. Integrate it in the
-  assignment, perhaps.
-- A section about `XXXNoBound` traits.
-- A section about reading your compiler errors top to bottom, especially with an example in FRAME.
diff --git a/content/substrate/txpool-api/page.md b/content/substrate/txpool-api/page.md
deleted file mode 100644
index 89be422f..00000000
--- a/content/substrate/txpool-api/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Substrate Transaction Pool and its Runtime API
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/substrate/txpool-api/slides.md b/content/substrate/txpool-api/slides.md
deleted file mode 100644
index b980302d..00000000
--- a/content/substrate/txpool-api/slides.md
+++ /dev/null
@@ -1,279 +0,0 @@
----
-title: Substrate's Transaction Pool and its Runtime API
-duration: 30 minutes
----
-
-# Substrate's Transaction Pool
-
----
-
-## Transaction Pools
-
-<pba-cols>
-<pba-col>
-
-<img style="width: 500px;" src="./img/BlockspaceBooth.png" />
-
-</pba-col>
-
-<pba-col>
-<img style="width: 500px; margin-left: -100px; margin-top: 250px;" src="./img/short-line.png" /> <!-- .element: class="fragment" -->
-</pba-col>
-
-<pba-col>
-<img style="width: 700px; margin-left: -100px; margin-top: 100px;" src="./img/long-line.png" /> <!-- .element: class="fragment" -->
-</pba-col>
-
-</pba-cols>
-
-Notes:
-
-The blockchain produces blockspace, and users buy that blockspace.
-Why do they buy it?
-So they can contribute to the shared story.
-So they can interact with the shared state machine.
-You can think of these users standing in line with transactions in their hand, waiting for the chance to put their transactions into the chain's blockspace.
-Sometimes the demand for blockspace is low and the queue is short.
-In this case the queue gets completely emptied each time a new block is created.
-Other times it gets long and backed up.
-Then when a block comes, only a part of the queue gets emptied.
-
-This simple model provides some good intuition about how the transaction pool works, but it is a bit simplified.
-
-First, It is actually a priority queue.
-You can jump the line by offering to bribe the block producers.
-
-Second, it is more accurate to think of the transactions themselves waiting in line, not the users who sent those transactions.
-
-Let's take a closer look.
-
----v
-
-### Paths of a Transaction
-
-<img style="width: 900px;" src="./img/blockchain_p2p.svg" />
-
-Notes:
-
-Previously, in the blockchain module, we saw this figure.
-It points out that each node has its own view of the blockchain.
-Now I'll show you another layer of detail which is that each node also has its own transaction pool
-CLICK
-
----v
-
-### Paths of a Transaction
-
-<img style="width: 900px;" src="./img/blockchain_p2p_with_pool.svg" />
-
-Notes:
-
-There are many paths a transaction can take from the user who signed it to a finalized block.
-Let's talk through some.
-Directly to user's authoring node and into chain is simplest.
-Could also be gossiped to other author.
-Could even go in a block, get orphaned off, back to tx pool, and then in a new block
-
----v
-
-### Pool Validation
-
-- Check signature
-- Check that sender can afford fees
-- Make sure state is ready for application
-
-Notes:
-
-When a node gets a transaction, it does some light pre-validation sometimes known as pool validation.
-This checking determines whether the transactions is {valid now, valid in some potential future, invalid}.
-There is periodic re-validation if transactions have been in the pool for a long time.
-
----v
-
-### Pool Prioritization
-
-- Priority Queue
-- Prioritized by...
-  - Fee
-  - Bribe
-  - Fee per blockspace
-- This is all off-chain
-
-Notes:
-
-There are a few more things the Substrate tx pool does too, and we will look at them in detail soon.
-
----
-
-## Tx Pool Runtime Api
-
-```rust
-pub trait TaggedTransactionQueue<Block: BlockT>: Core<Block> {
-    fn validate_transaction(
-        &self,
-        __runtime_api_at_param__: <Block as BlockT>::Hash,
-        source: TransactionSource,
-        tx: <Block as BlockT>::Extrinsic,
-    ) -> Result<TransactionValidity, ApiError> { ... }
-}
-```
-
-[`TaggedTransactionQueue` Rustdocs](https://paritytech.github.io/substrate/master/sp_transaction_pool/runtime_api/trait.TaggedTransactionQueue.html)
-
-Introduced in [paritytech/substrate#728](https://github.com/paritytech/substrate/issues/728)
-
-Notes:
-
-This is another runtime api, similar to the block builder and the core that are used for creating and importing blocks.
-Like most others, it requires that the Core api also be implemented.
-
-This one is slightly different in that it is actually called from off-chain, and is not part of your STF.
-So let's talk about that for a little bit.
-
----v
-
-### Runtime vs STF
-
-<img style="width: 1100px;" src="./img/peter-parker-glasses-off.png" />
-
-Notes:
-
-It is commonly said that the runtime is basically your STF.
-This is a good first order approximation.
-It is nearly true.
-
----v
-
-### Runtime vs STF
-
-<img style="width: 1100px;" src="./img/peter-parker-glasses-on.png" />
-
-Notes:
-
-But as we can see here, when we put our glasses on, actually only some of the apis are part of the stf.
-
----v
-
-## Why is pool logic in the runtime?
-
-- Transaction type is Opaque
-- Runtime logic is opaque
-- You must understand the transaction to prioritize it
-
-Notes:
-
-So if this is not part of the STF why is it in the runtime at all?
-This logic is tightly related to the runtime application logic.
-The types are opaque outside of the runtime.
-So this logic must go in the runtime.
-
-But if it is not on-chain, can individual validators customize it.
-In short yes.
-There is a mechanism for this.
-We won't go deeply into the mechanism, but validators can specify alternate wasm blocs to use instead of the official one.
-
----
-
-## Jobs of the API
-
-- Make fast pre-checks
-- Give the transaction a priority
-- Determine whether the transaction is ready now or may be ready in the future
-- Determine a dependency graph among the transactions
-
-Notes:
-
-So we spoke earlier about the jobs of a transaction pool in general.
-Specifically the pre-checks and the priority
-Here is a more specific list of tasks that Substrate's TaggedTransactionPool does.
-
-The second two points are the new additions, and they are the duty of the "tags" after which the tagged transaction queue is named.
-
-The results of all of this are returned to the client side through a shared type `ValidTransaction` or `InvalidTransaction`
-
----v
-
-### `ValidTransaction`
-
-```rust
-pub struct ValidTransaction {
-    pub priority: TransactionPriority,
-    pub requires: Vec<TransactionTag>,
-    pub provides: Vec<TransactionTag>,
-    pub longevity: TransactionLongevity,
-    pub propagate: bool,
-}
-```
-
-[`ValidTransaction` Rustdocs](https://paritytech.github.io/substrate/master/sp_runtime/transaction_validity/struct.ValidTransaction.html)
-
-Notes:
-
-We indicate that the transaction passes the prechecks at all by returning this valid transaction struct.
-If it weren't even valid, we would return a different, `InvalidTransaction` struct.
-You learned yesterday how to navigate the rustdocs to find the docs on that one.
-
-Priority we've discussed.
-It is worth noting that the notion of priority is intentionally opaque to the client.
-The runtime may assign this value however it sees fit.
-
-Provides and requires all forming a dependency graph between the transactions.
-Requires is a list of currently unmet dependency transactions.
-This transaction will be ready in a future where these dependencies are met so it is kept in the pool.
-
-A simple intuitive example of this is payments.
-Image alice pays bob some tokens in transaction1.
-Then bob pays those same tokes to charlie in transaction2.
-trasnaction2 will be valid only after transaction1 has been applied.
-It is a dependency.
-
-Longevity is a field I'm not so familiar with.
-It is how long the transaction should stay in the pool before being dropped or re-validated.
-
-<!-- FIXME TODO what are the units? How does one set it? -->
-
-And finally whether the transaction should be gossiped.
-This is usually true.
-Only in special edge cases would this be false.
-
----v
-
-### Example 1: UTXO System
-
-<img src="./img/utxo.svg" />
-
-Notes:
-
-Prioritize by implicit tip (difference of inputs and outputs)
-Requires all missing input transactions
-provides this input
-
----v
-
-### Example 2: Nonced Account System
-
-<img src="./img/accounts.svg" />
-
-Notes:
-
-Prioritize by explicit tip
-Requires all previous nonces for this account
-provides this nonce for this account
-
-This demonstrates one of the biggest downsides of the Accounts system.
-Transactions cannot deterministically specify the initial state on which they operate.
-There is only an inherent ordering between transactions from the same account.
-
----v
-
-## Always Re-check On-chain
-
-<img style="width: 900px;" src="./img/blockchain_p2p_with_pool.svg" />
-
-Notes:
-
-None of this new pool information changes the fundamentals you learned last week.
-You must execute the state transitions in full on chain.
-
-Most of the time you are not the block author.
-When you import a block from another node, you cannot trust them to have done the pre-checks correctly.
diff --git a/content/substrate/wasm/img/dev-4-1-state-database.svg b/content/substrate/wasm/img/dev-4-1-state-database.svg
deleted file mode 100644
index bb4d498d..00000000
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+++ /dev/null
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diff --git a/content/substrate/wasm/page.md b/content/substrate/wasm/page.md
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-# Substrate Wasm meta-protocol
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/substrate/wasm/slides.md b/content/substrate/wasm/slides.md
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----
-title: Substrate Wasm meta-protocol
-description: A deeper dive into how the Wasm is meta-protocol functions in substrate.
-duration: 60 minutes
----
-
-# Substrate Wasm Meta Protocol
-
----
-
-# Part 1
-
-- This is a big lecture, so I divided it into two small parts, that's all 🫵🏻
-
----
-
-## It All Began With a Runtime..
-
-<img rounded style="width: 1200px;" src="./img/dev-4-3-substrate-wasm.png" />
-
----v
-
-### It All Began With a Runtime..
-
-- Personal opinion:
-
-> Substrate technology stack will put "Wasm stored onchain" on the map,<br />
-> the same way Ethereum put "smart contracts stored onchain" on the map.
-
-Notes:
-
-> It is only a matter of time until every blockchain is doing the same thing.
-
----v
-
-## It All Began With a Runtime..
-
-- The Client / Runtime division is one of the most important design decisions in Substrate.
-  - 👿 Bad: Fixed opinion. <!-- .element: class="fragment" -->
-  - 😇 Good: Enables countless other things to not be fixed. <!-- .element: class="fragment" -->
-
-Notes:
-
-Recall that the boundary for this division is the **state transition**
-
----
-
-## Substrate: a short recap
-
-<img style="width: 1200px;" src="./img/dev-4-3-full-comm.svg" />
-
----v
-
-### Substrate: a short recap
-
-- **Host Functions**: Means of a runtime communicating with its host environment, i.e. the Substrate client.
-
----v
-
-### Substrate: a short recap
-
-- **Runtime API**: The well-defined functions that a Wasm substrate runtime is providing.
-
-Notes:
-
-Building a Wasm module's activity was building something akin to runtime-apis
-
----v
-
-### Substrate: a short recap
-
-- Database is on the client side, storing an opaque key-value state per block.
-
----v
-
-### Substrate: a short recap
-
-- Communication language of client/runtime is SCALE:
-
-<diagram class="mermaid">
-flowchart LR
-  B[Known Type eg. `u32`] --Encode--> V["Vec(u8)"]
-  V --Decode-->B
-</diagram>
-
----
-
-## Learning with Examples
-
-and some pseudo-code
-
-Notes:
-
-During each example, we deduce what host functions and/or runtime APIs are needed.
-
----
-
-## Example #1: State
-
-- The runtime wants to add 10 units to Kian's balance.
-
----v
-
-### Example #1: State
-
-```rust [1-100|1-2|4,5|7,8|10,11|13,14|1-100]
-// the runtime decides what key stores kian's balance.
-key: Vec<u8> = b"kian_balance".to_vec();
-
-// the runtime reads the raw bytes form that key.
-let current_kian_balance_raw: Vec<u8> = host_functions::get(key);
-
-// and needs to know to which type it should be decoded, u128.
-let mut current_kian_balance: u128 = current_kian_balance_raw.decode();
-
-// actual logic.
-current_kian_balance += 10;
-
-// encode this again into an opaque byte-array.
-let new_balance_encoded: Vec<u8> = current_kian_balance.encode();
-
-// write the encoded bytes again.
-host_functions::set(key, new_balance_encoded);
-```
-
----v
-
-### Example #1: State
-
-- 💡 The runtime needs host functions to read/write to state.
-
-```rust
-fn get(key: Vec<u8>) -> Vec<u8>;
-fn set(key: Vec<u8>, value: Vec<u8>);
-```
-
-Notes:
-
-ofc the IO to these functions is all opaque bytes, because the client does not know the state
-layout.
-
----v
-
-### Example #1: State
-
-- could we have communicated with the client like this?
-
-```rust
-fn set_balance(who: AccountId, amount: u128)
-```
-
-Notes:
-
-This would imply that the client would have to know, indefinitely, the types needed for account id
-and balance. Also, it would have to know the final key for someone's balance.
-
----v
-
-### Example #1: State
-
-- Exceptions:
-
-```rust
-/// The keys known to the client.
-mod well_known_keys {
-  const CODE: &[u8] = b":code";
-}
-```
-
-Notes:
-
-See <https://paritytech.github.io/substrate/master/sp_storage/well_known_keys/index.html>
-
----v
-
-### Example #1: State
-
-<img style="width: 1000px;" src="./img/dev-4-1-state-opaque.svg" />
-
----
-
-## Example #2: Block Import
-
----v
-
-### Example #2: Block Import
-
-- Client's view of the state -> Opaque.
-- Client's view of the transactions? 🤔
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-Short answer is: anything that is part of the STF definition must be opaque to the client, and is
-upgradeable, but we will learn this later.
-
----v
-
-### Example #2: Block Import
-
-- Transactions format is by definition part of the state transition function as well.
-- What about header, and other fields in a typical block?
-
-Notes:
-
-as in, do we want to able to update our transactions format as well in a forkless manner?
-we want the runtime to be able to change its transactions format as well, in a forkless manner.
-
-The answer to the latter is more involved. The short answer is that these fields like header must be known and established between client and runtime. If you want to alter the header format, that's a hard fork.
-
-The concept of `digest` is a means through which additional data can be put in the header without breaking changes, but that is outside the scope of this lecture.
-
-Yet, as with other primitives, substrate allows you to readily change your header type when you are building your blockchain.
-This is achieved by a set of traits in `sp-runtime`.
-Notably, `trait Block` and `trait Header` in this crate define what it means to be a header and block, and as long as you fulfill that, you are good to go.
-
-Also, substrate provides one set of implementation for all of these types in <https://paritytech.github.io/substrate/master/sp_runtime/generic/index.html>
-
----v
-
-<img style="width: 1200px;" src="./img/dev-4-3-block-opaque.svg" />
-
----v
-
-### Example #2: Block Import
-
-<pba-cols>
-
-<pba-col>
-
-```rust
-struct ClientBlock {
-  header: Header,
-  transactions: Vec<Vec<u8>>
-}
-```
-
-</pba-col>
-
-<pba-col>
-
-```rust
-struct RuntimeBlock {
-  header: Header,
-  transaction: Vec<KnownTransaction>
-}
-```
-
-</pba-col>
-
-</pba-cols>
-
-Notes:
-
-this slide is intentionally using the keyword transaction instead of extrinsic.
-
----v
-
-### Example #2: Block Import
-
-```rust [1-100|1-2|4-6|8-9|1-100]
-// fetch the block from the outer world.
-let opaque_block: ClientBlock = networking::import_queue::next_block();
-
-// initialize a wasm runtime.
-let code = database::get(well_known_keys::CODE);
-let runtime = wasm::Executor::new(code);
-
-// call into this runtime.
-runtime.execute_block(opaque_block);
-```
-
----v
-
-### Example #2: Block Import
-
-- 💡 The client needs a runtime API to ask the runtime to execute the block.
-
-```rust
-fn execute_block(opaque_block: ClientBlock) -> Result<_, _> { .. }
-```
-
-Notes:
-
-`execute_block` is the most basic, fundamental runtime API that any substrate based runtime has to
-implement in order to be called a "blockchain runtime".
-
----
-
-### Example #2: Block Import: Something Missing
-
-```rust
-// 🤔
-let code = database::get(well_known_keys::CODE);
-
-// 🤔
-runtime.execute_block(opaque_block);
-```
-
-<img style="width: 600px" src="./img/dev-4-1-state-database.svg" />
-
-Notes:
-
-- From which block's state do we fetch the code??
-- This probably calls into `host_functions::{get/set}` internally.
-  What do we return
-
----v
-
-### Example #2: Block Import
-
-```rust [1-100|1-2|4-6|8-10|12-15|17-100]
-// fetch the block from the outer world.
-let block: ClientBlock = networking::import_queue::next_block();
-
-// get the parent block's state.
-let parent = block.header.parent_hash;
-let mut state = database::state_at(parent);
-
-// initialize a wasm runtime FROM THE PARENT `state`!
-let code = state::get(well_known_keys::CODE);
-let runtime = wasm::Executor::new(code);
-
-// call into this runtime, updates `state`.
-state.execute(|| {
-  runtime.execute_block(block);
-});
-
-// create the state of the next_block
-database::store_state(block.header.hash, state)
-```
-
-Notes:
-
-- Question: why is `state` defined as `mut`?
-- within these snippets, more or less, everything inside `state.execute` is executed within Wasm.
-
----v
-
-### Example #2: Block Import
-
-- A state key is only meaningful at a given block.
-- A :code is only meaningful at at given block.
-
-<!-- .element: class="fragment" -->
-
-- 💡 A runtime (API) is only meaningful when executed at a give block.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-- The same way that Alice's balance value is only meaningful when read at a given block.
-
-- Based on that:
-
-  - The correct runtime code is loaded.
-  - The correct state (and other host functions) is provided.
-
-- Similarly, almost all RPC operations that interact with the runtime have an `Option<Hash>`
-  argument.
-  This specifies "at which block to load the runtime and state from".
-
----v
-
-### Example #2: Block Import
-
-- I can add one more small touch to this to make it more accurate.. 🤌
-
----v
-
-### Example #2: Block Import
-
-```rust [14-20]
-// fetch the block from the outer world.
-let block: ClientBlock = networking::import_queue::next_block();
-
-// get the parent hash. Note that `sp_runtime::traits::Header` provides this.
-let parent = block.header.parent_hash;
-let mut state = database::state_at(parent);
-
-// initialize a wasm runtime FROM THE PARENT `state`!
-let code = state::get(well_known_keys::CODE);
-let runtime = wasm::Executor::new(code);
-
-// call into this runtime, update `state`.
-state.execute(|| {
-  // within this, we probably call into `host_functions::set` a lot.
-  runtime.execute_block(block);
-
-  let new_state_root = host_functions::state_root();
-  let claimed_state_root = block.header.state_root;
-  assert_eq!(new_state_root, claimed_state_root);
-});
-
-// create the state of the next_block
-database::store_state(block.header.hash, state)
-```
-
----v
-
-### Example #2: Block Import: Recap
-
-<img style="width: 1200px;" src="./img/dev-4-3-import.svg" />
-
----
-
-## Detour: Extrinsic
-
-- Previous slides used the term "transactions" in a simplified way.
-  Let's correct it.
-
----v
-
-### Detour: Extrinsic
-
-<diagram class="mermaid" center>
-  %%{init: {'theme': 'dark', 'themeVariables': { 'darkMode': true }}}%%
-  flowchart TD
-    E(Extrinsic) ---> I(Inherent);
-    E --> T(Transaction)
-    T --> ST("Signed (aka. Transaction)")
-    T --> UT(Unsigned)
-</diagram>
-
----v
-
-### Detour: Extrinsic
-
-- An Extrinsic is data that come from outside of the runtime.
-- &shy;<!-- .element: class="fragment" -->Inherents are data that is put into the block by the block author, directly.
-- &shy;<!-- .element: class="fragment" --> Yes, transactions are **a type of extrinsic**, but not all extrinsics are transactions.
-- &shy;<!-- .element: class="fragment" --> So, why is it called _Transaction Pool_ and not _Extrinsic Pool_?
-
-Notes:
-
-Extrinsics are just blobs of data which can be included in a block.
-Inherents are types of extrinsic which are crafted by the block builder itself in the production process.
-They are unsigned because the assertion is that they are "inherently true" by virtue of getting past all validators.
-Notionally the origin can be said to be a plurality of validators.
-Take for example the timestamp set inherent.
-If the data were sufficiently incorrect (i.e. the wrong time), then the block would not be accepted by enough validators and would not become canonicalized.
-So the "nobody" origin is actually the tacit approval of the validators.
-Transactions are generally statements of opinion which are valuable to the chain to have included (because fees are paid or some other good is done).
-The transaction pool filters out which of these are indeed valuable and nodes share them.
-
----
-
-## Example #3: Block Authoring
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-0-author-pool.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-1-author-pool.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-2-author-pool.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-3-author-pool.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-4-author-pool.svg" />
-
-Notes:
-
-The point being, eventually the pool builds a list of "ready transactions".
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-0-author-builder.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-1-author-builder.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-2-author-builder.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-3-author-builder.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-4-author-builder.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-5-author-builder.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-6-author-builder.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-<img style="width: 1400px;" src="./img/dev-4-3-7-author-builder.svg" />
-
----v
-
-### Example #3: Block Authoring
-
-```rust [1-100|1-2|4-5|7-9|11-12|14-20|21-100]
-// get the best-block, based on whatever consensus rule we have.
-let (best_number, best_hash) = consensus::best_block();
-
-// get the latest state.
-let mut state = database::state_at(best_hash);
-
-// initialize a wasm runtime.
-let code = state::get(well_known_keys::CODE);
-let runtime = wasm::Executor::new(code);
-
-// get an empty client block.
-let mut block: ClientBlock = Default::default();
-
-// repeatedly apply transactions.
-while let Some(next_transaction) = transaction_pool_iter::next() {
-  state.execute(|| {
-    runtime.apply_extrinsic(next_transaction);
-  });
-  block.extrinsics.push(next_transaction);
-}
-
-// set the new state root.
-block.header.state_root = state.root();
-```
-
-Notes:
-
-- What is the type of `next_ext`? `Vec<u8>`
-- Do we actually loop forever until the tx-pool is empty? probably not!
-
----v
-
-### Example #3: Block Authoring
-
-- Substrate based runtimes are allowed to perform some operations at the beginning and end of each block.
-- ✋🏻 And recall that a smart contract could not do this.
-
----v
-
-### Example #3: Block Authoring
-
-```rust [14-15,25-26]
-// get the best-block, based on whatever consensus rule we have.
-let (best_number, best_hash) = consensus::best_block();
-
-// get the latest state.
-let mut state = database::state_at(best_hash);
-
-// initialize a wasm runtime.
-let code = state::get(well_known_keys::CODE);
-let runtime = wasm::Executor::new(code);
-
-// get an empty client block.
-let mut block: ClientBlock = Default::default();
-
-// tell this runtime that you wish to start a new block.
-runtime.initialize_block();
-
-// repeatedly apply transactions.
-while let Some(next_ext) = transaction_pool_iter::next() {
-  state.execute(|| {
-    runtime.apply_extrinsic(next_ext);
-  });
-  block.extrinsics.push(next_ext);
-}
-
-// tell the runtime that we are done.
-runtime.finalize_block();
-
-// set the new state root.
-block.header.state_root = state.root();
-```
-
----v
-
-### Example #3: Block Authoring
-
-- What about Inherents?
-
----v
-
-### Example #3: Block Authoring
-
-```rust [14-26]
-// get the best-block, based on whatever consensus rule we have.
-let (best_number, best_hash) = consensus::best_block();
-
-// get the latest state.
-let mut state = database::state_at(best_hash);
-
-// initialize a wasm runtime.
-let code = state::get(well_known_keys::CODE);
-let runtime = wasm::Executor::new(code);
-
-// get an empty client block.
-let mut block: ClientBlock = Default::default();
-
-// tell this runtime that you wish to start a new block.
-runtime.initialize_block();
-
-let inherents: Vec<Vec<u8>> = block_builder::inherents();
-block.extrinsics = inherents;
-
-// repeatedly apply transactions.
-while let Some(next_ext) = transaction_pool_iter::next() {
-  state.execute(|| {
-    runtime.apply_extrinsic(next_ext);
-  });
-  block.extrinsics.push(next_ext);
-}
-
-// tell the runtime that we are done.
-runtime.finalize_block();
-
-// set the new state root.
-block.header.state_root = state.root();
-```
-
-Notes:
-
-while inherents can in principle come at any point in the block, since FRAME restricts them to
-come first, we also keep our example aligned.
-
-Should you wish to see the real version of this, check this crate:
-https://paritytech.github.io/substrate/master/sc_basic_authorship/index.html
-
----v
-
-### Example #3: Block Authoring
-
-```rust
-fn initialize_block(..) { ... }
-// note the opaque extrinsic type.
-fn apply_extrinsic(extrinsic: Vec<u8>) { ... }
-fn finalize_block(..) { ... }
-```
-
-Notes:
-
-in fact, the client also builds its inherent list with the help of the runtime.
-
----
-
-## BUT WAIT A MINUTE 😱
-
-- if the `code` changes, all the following can also change:
-
-  - <!-- .element: class="fragment" --> What state key is Kian's balance.
-  - <!-- .element: class="fragment" --> What extrinsic format is valid.
-
-- <!-- .element: class="fragment" --> How on earth is an application (i.e. a wallet) is supposed to survive?
-
----v
-
-### BUT WAIT A MINUTE 😱
-
-- Metadata 🎉
-
-```rust
-fn metadata() -> Vec<u8> { ... }
-```
-
-Notes:
-
-Notice the opaque return type.
-
-In order the address the mentioned issue, metadata must be a runtime API.
-
-<hr>
-
-- Metadata contains all the basic information to know about all storage items, all extrinsics, and so on.
-  It will also help a client/app decode them into the right type.
-- Substrate itself doesn't impose what the metadata should be.
-  It is `Vec<u8>`.
-- FRAME based runtime expose a certain format, which is extensively adopted in the ecosystem.
-
----v
-
-### BUT WAIT A MINUTE 😱
-
-- Recall the fact that "runtime is only meaningful at a certain block".
-
-<div class="fragment">
-
-- Two different runtimes at block `N` and `N+1` return different metadata ✅.
-
-</div>
-
-Notes:
-
-By Applications/Clients I really mean anyone/anything.
-Substrate client doesn't really use metadata because it is dynamically typed, but if needed, it could.
-
----
-
-### Radical Upgradeability
-
-Comes at the cost of radical opaque/dynamic typing.
-
-Notes:
-
-I wish you could have both, but not so easy.
-
-Some personal rant: radical upgrade-ability is the biggest advantage, and arguably one of the main develop-ability problems of the substrate ecosystem.
-Writing clients, such as block explorers, scanners, and even exchange integration are orders of magnitude harder than a blockchain that has a fixed format and only changes every 18 months at most.
-That being said, this is a battle that is to me obvious: we simply HAVE to win.
-When ethereum first introduced smart contracts, everyone probably had the same class of issues.
-This is the same matter, on a a different level.
-
-also, as noted in an earlier slide, once you make it work for one chain, it works for many chains.
-
----
-
-## Oblivious Client 🙈🙉
-
-- The underlying reason why the client is "**kept in the dark**" is so that it wouldn't need to care
-  about the runtime upgrading from one block to the other.
-
----v
-
-## Oblivious Client 🙈🙉
-
-$$STF = F(blockBody_{N}, state_{N}) > state_{N+1}$$
-
-_Anything that is part of the STF is opaque to the client, but it can change forklessly!_
-
-- <!-- .element: class="fragment" --> The `F` itself (your Wasm blob)? It can change!
-- <!-- .element: class="fragment" --> Extrinsic format? It can change!
-- <!-- .element: class="fragment" --> State format? It can change!
-
-Notes:
-
-In essence, all components of the STF must be opaque to the client.
-`Vec<u8>`.
-Metadata is there to assist where needed.
-This is why forkless upgrades are possible in substrate.
-
----v
-
-## Oblivious Client 🙈🙉
-
-- What about new host functions?
-- <!-- .element: class="fragment" --> What about a new header filed*?
-- <!-- .element: class="fragment" --> What about a new Hashing primitive?
-
-🥺 No longer forkless.
-
-<!-- .element: class="fragment" -->
-
-Notes:
-
-But, recall that substrate's extensibility and generic-ness clause applies here.
-
-For some, like header, some hacks exist, like the `digest` field.
-
-Changing these is hard in a forkless manner.
-If you want to just change them at genesis and launch a new chain, they are all VERY easy to change.
-
----
-
-## Substrate: The Full Picture
-
-<img style="width: 1200px;" src="../intro/img/dev-4-3-full.svg" />
-
-Notes:
-
-time to ask any missing questions.
-
----
-
-## Activity: Finding APIs and Host Functions
-
----v
-
-### Finding APIs and Host Functions
-
-- look for `impl_runtime_apis! {...}` and `decl_runtime_apis! {...}` macro calls.
-  - Try and find the corresponding the client code calling a given api as well.
-- Look for `#[runtime_interface]` macro, and try and find usage of the host functions!
-- You have 15 minutes!
-
----v
-
-### Finding APIs and Host Functions
-
-Activity Outcomes:
-
-- `Core` is the essence of import.
-- `TaggedTransactionQueue` and `BlockBuilder` for validators.
-- `header: Header` being passed around.
-
-Notes:
-
-a question that arise here is that why don't have multiple runtimes, where one is only for import,
-one only for authoring, and such? the reality is that while these have different names, the
-underlying code is like 95% the same.
-
----v
-
-### Finding APIs and Host Functions
-
-<pba-cols>
-<pba-col>
-
-#### Block Import
-
-```rust
-runtime.execute_block(block);
-```
-
-</pba-col>
-<pba-col>
-
-#### Block Authoring
-
-```rust
-runtime.initialize_block(raw_header);
-loop {
-  runtime.apply_extrinsic(ext);
-}
-let final_header = runtime.finalize_block();
-```
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-to be frank, these are still a simplification.
-Inherent for example are not really represented here.
-
----v
-
-### Finding APIs and Host Functions
-
-- Most important host functions
-
-```
-sp_io::storage::get(..);
-sp_io::storage::set(..);
-sp_io::storage::root();
-```
-
----
-
-## Lecture Recap (Part 1)
-
-- Revise "**Runtime API**" and "**Host Function**" concepts.
-- Deep look at block import and authoring.
-- Oblivious client.
-- Metadata
-
----
-
-# Part 2
-
----
-
-## Defining a Runtime API
-
-```rust [1-7|9-15|17-100|1-100]
-// somewhere in common between client/runtime => substrate-primitive.
-decl_runtime_apis! {
-	pub trait Core {
-		fn version() -> RuntimeVersion;
-		fn execute_block(block: Block) -> bool;
-	}
-}
-
-// somewhere in the runtime code.
-impl_runtime_apis! {
-  impl sp_api::Core<Block> for Runtime {
-    fn version() -> RuntimeVersion { /* stuff */ }
-    fn execute_block(block: Block) -> bool { /* stuff */ }
-  }
-}
-
-// somewhere in the client code..
-let block_hash = "0xffff...";
-let block = Block { ... };
-let outcome: Vec<u8> = api.execute_block(block, block_hash).unwrap();
-```
-
-Notes:
-
-- All runtime APIs are generic over a `<Block>` by default.
-- All runtime APIs are executed on top of a **specific block**.
-  This is the implicit _at_ parameter.
-- Going over the API, everything is SCALE encoded both ways, but abstractions like
-  `impl_runtime_apis` hide that away from you.
-
----
-
-## Defining a Host Function
-
-```rust
-// somewhere in substrate primitives, almost always `sp_io`.
-#[runtime_interface]
-pub trait Storage {
-  fn get(&self, key: &[u8]) -> Option<Vec<u8>> {...}
-  fn get(&self, key: &[u8], value: &[u8]) -> Option<Vec<u8>> {...}
-  fn root() -> Vec<u8> {...}
-}
-
-#[runtime_interface]
-pub trait Hashing {
-	fn blake2_128(data: &[u8]) -> [u8; 16] {
-		sp_core::hashing::blake2_128(data)
-	}
-}
-
-// somewhere in substrate runtime
-let hashed_value = sp_io::storage::get(b"key")
-  .and_then(sp_io::hashing::blake2_128)
-  .unwrap();
-```
-
----
-
-## Considerations
-
----
-
-## Considerations: Speed
-
-- (new) Wasmtime is near-native 🏎️.
-- (old) `wasmi` is significantly slower 🐢.
-
-Notes:
-
-slower wasmi was one of the reasons to have native execution.
-there are talks of exploring Risk-v ISA instead of wasm nowadays.
-
-https://github.com/paritytech/substrate/issues/13640
-
----v
-
-### Considerations: Speed
-
-<pba-cols>
-<pba-col center>
-
-- Host is generally **faster** and **more capable**, but it has a one-time cost of getting there,
-  and copying the data.
-- &shy;<!-- .element: class="fragment" -->🤔 Hashing, Crypto?
-- &shy;<!-- .element: class="fragment" -->🤔 Storage?
-
-</pba-col>
-<pba-col center>
-
-<img style="width: 700px;" src="../storage/img/dev-4-3-io.svg" />
-
-</pba-col>
-</pba-cols>
-
-Notes:
-
-Hashing and crypto is done as host function for performance
-
-Storage because of the runtime not being capable.
-
-- Going over the runtime boundary is analogous to your CPU needing to go to memory.
-
-On the other hand things as `next_storage` are high cost (generally iteration on state from runtime
-is expensive).
-This design is related to the memory location, there is alternative but this is
-simple (simple as good design).
-
-- Question: we got host function for running computation intensive code in native, but when simd for
-  wasm would be added, then will host function for a hashing be still useful:
-  A: wait and see, but is possible that simd optimization of the hash function in wasm is way faster.
-
-Again using a host function for speed up needs to be reasoned, cost of transmitting parameter in
-wasm can be bigger than the actual hashing cost.
-
----
-
-### Consideration: Native Runtime
-
-<img style="width: 1200px;" src="./img/dev-4-3-native.svg" />
-
----v
-
-### Consideration: Native Runtime
-
-- Remember the `fn version()` in `Core` API!
-
-```rust [1-100|4-5]
-/// Runtime version.
-#[sp_version::runtime_version]
-pub const VERSION: RuntimeVersion = RuntimeVersion {
-	spec_name: create_runtime_str!("node"),
-	spec_version: 268,
-	impl_name: create_runtime_str!("substrate-node"),
-	impl_version: 0,
-	authoring_version: 10,
-	apis: RUNTIME_API_VERSIONS,
-	transaction_version: 2,
-	state_version: 1,
-};
-```
-
----v
-
-### Consideration: Native Runtime
-
-- Native is only an option if spec versions match!
-
-```rust
-fn execute_native_else_wasm() {
-  let native_version = runtime::native::api::version();
-  let wasm_version = runtime::wasm::api::version();
-
-  // if spec name and version match.
-  if native_version == wasm_version {
-    runtime::native::execute();
-  } else {
-    runtime::wasm::execute();
-  }
-}
-```
-
----v
-
-### Consideration: Native Runtime
-
-- The days of native runtime are numbered 💀.
-
----v
-
-### Consideration: Native Runtime
-
-- Question: what happens if you upgrade your runtime, but forget to bump the spec version?
-- &shy;<!-- .element: class="fragment" --> Question: What if a runtime upgrade is only tweaking implementation details, but not the specification?
-
-Notes:
-
-If everyone is executing wasm, technically nothing, but that's super confusing, don't do it.
-But, if some are executing native, then you will have a consensus error.
-
----v
-
-## Speaking of Versions..
-
-- Make sure you understand the difference! 👍
-  - Client Version
-  - Runtime Version
-
----v
-
-### Speaking of Versions..
-
-<img style="width: 1200px;" src="./img/dev-4-1-substrate-meta-version.svg" />
-
----v
-
-### Speaking of Versions..
-
-<img style="width: 1200px;" src="./img/dev-4-3-telemetry.png" />
-
----v
-
-### Speaking of Versions..
-
-<img style="width: 1200px;" src="./img/dev-4-3-PJS.png" />
-
----v
-
-### Speaking of Versions..
-
-- What happens when Parity release a new `parity-polkadot` client binary?
-- What happens when the Polkadot fellowship wants to update the runtime?
-
----
-
-## Considerations: Panic
-
-- What if any of the runtime calls, like `execute_block` or `apply_extrinsic` panics 😱?
-- To answer this, let's take a step back toward validator economics.
-
----v
-
-### Considerations: Panic
-
-- In a more broad sense, all validators never want to avoid wasting their time.
-- While building a block, sometimes it is unavoidable (when?). <!-- .element: class="fragment" -->
-- While importing a block, nodes will not tolerate this. <!-- .element: class="fragment" -->
-
----v
-
-### Considerations: Panic
-
-- Panic is a (free) form of wasting a validator's time.
-- Practically Wasm instance killed; State changes reverted.
-  - Any fee payment also reverted.
-- Transactions that consume resources but fail to pay fees are similar. <!-- .element: class="fragment" -->
-
-Notes:
-
-While you might think the state revert is the good thing here, it is the main problem, and the main
-reason you should not let a code-path that is accessible by arbitrary users to panic.
-Because, any
-fees paid for the wasted execution of that runtime API call is also reverted.
-
-In other words, a panic in the runtime typically allows everyone's time to be wasted, for free,
-indefinitely.
-In other words, a DOS vector.
-
-> A panic in `initialize_block` and `finalize_block` have even more catastrophic effects, which will
-> be discussed further in the FRAME section.
-
-workshop idea: make a panicing runtime, and DoS it out.
-workshop idea for FRAME: find all instances where the runtime actually correctly panics (wrong timestamp, disabled validator)
-
----v
-
-### Considerations: Panic
-
-- Panic in a user-callable code path?
-- 🤬 annoy/DOS your poor validators <!-- .element: class="fragment" -->
-- Panic on "automatic" part of your blockchain like "initialize_block"? <!-- .element: class="fragment" -->
-- 😱 Stuck forever <!-- .element: class="fragment" -->
-
----v
-
-### Considerations: Panic
-
-- This is why, crucially, transaction pool checks always include, despite being costly, at least
-  some sort of nonce and payment checks to make sure you can pay the transaction.
-
----v
-
-### Considerations: Panic
-
-<diagram class="mermaid">
-graph LR
-    TransactionPool --"😈"--> Authoring --"😇"--> Import
-</diagram>
-
-Notes:
-
-Consider two cases:
-
-1. A transaction that panic-ed
-1. A transaction that cannot pay for fees, but the pool somehow validated it by mistake.
-
-when you author a block, you hope that the tx-pool has pre-validated things for you, but you cannot be sure.
-The pool cannot pre-execute stuff.
-If it fails, then you have to continue.
-For example, the pool might validate a nonce that becomes invalid.
-Or a fee payment.
-In that case, the block author wasted time, but everyone else will not.
-
-To the contrary, once you have authored a block, the importers expect you to only have put VALID
-transactions into it, those that will not fail to be **included**.
-
-Note that a transaction might still fail (failed transfer), but so long as it can pay for its fee,
-it **is included** fine.
-
-See the documentation of `ApplyExtrinsicResult` in Substrate for more info about this.
-
----
-
-### Consideration: Altering Host Function
-
-- A runtime upgrade now requires a new `sp_io::new_stuff::foo()`.
-  Can we do a normal runtime upgrade?
-
-<div>
-
-- Clients need to upgrade first.
-  No more fully forkless upgrade 😢
-
-</div>
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Consideration: Breaking a Host Function
-
-- Here's another example, from substrate:
-
-```rust
-// old
-fn root(&mut self) -> Vec<u8> { .. }
-
-// new
-fn root(&mut self, version: StateVersion) -> Vec<u8> { .. }
-```
-
-<div>
-
-- For some period of time, the client needs to support both..🤔
-
-</div>
-
-<!-- .element: class="fragment" -->
-
-<div>
-
-- When can the old host function be deleted?
-
-</div>
-
-<!-- .element: class="fragment" -->
-
----v
-
-### Host Functions..
-
-## NEED TO BE KEPT FOREVER 😈
-
-<!-- .element: class="fragment" -->
-
-- Optional activity: Go to the substrate repo, and find PRs that have altered host functions, and see the PR discussion. There are a few labels that help you find such PRs 😉.
-
-<!-- .element: class="fragment" -->
-
----
-
-## Workshop: Inspecting Wasm Code
-
----v
-
-- `wasm2wat polkadot_runtime.wasm > dump | rg import`
-
-```
-(import "env" "memory" (memory (;0;) 22))
-(import "env" "ext_crypto_ed25519_generate_version_1" (func $ext_crypto_ed25519_generate_version_1 (type 17)))
-(import "env" "ext_crypto_ed25519_verify_version_1" (func $ext_crypto_ed25519_verify_version_1 (type 18)))
-(import "env" "ext_crypto_finish_batch_verify_version_1" (func $ext_crypto_finish_batch_verify_version_1 (type 11)))
-(import "env" "ext_crypto_secp256k1_ecdsa_recover_version_2" (func $ext_crypto_secp256k1_ecdsa_recover_version_2 (type 19)))
-(import "env" "ext_crypto_secp256k1_ecdsa_recover_compressed_version_2" (func $ext_crypto_secp256k1_ecdsa_recover_compressed_version_2 (type 19)))
-(import "env" "ext_crypto_sr25519_generate_version_1" (func $ext_crypto_sr25519_generate_version_1 (type 17)))
-(import "env" "ext_crypto_sr25519_public_keys_version_1" (func $ext_crypto_sr25519_public_keys_version_1 (type 5)))
-(import "env" "ext_crypto_sr25519_sign_version_1" (func $ext_crypto_sr25519_sign_version_1 (type 20)))
-(import "env" "ext_crypto_sr25519_verify_version_2" (func $ext_crypto_sr25519_verify_version_2 (type 18)))
-(import "env" "ext_crypto_start_batch_verify_version_1" (func $ext_crypto_start_batch_verify_version_1 (type 14)))
-(import "env" "ext_misc_print_hex_version_1" (func $ext_misc_print_hex_version_1 (type 16)))
-(import "env" "ext_misc_print_num_version_1" (func $ext_misc_print_num_version_1 (type 16)))
-(import "env" "ext_misc_print_utf8_version_1" (func $ext_misc_print_utf8_version_1 (type 16)))
-(import "env" "ext_misc_runtime_version_version_1" (func $ext_misc_runtime_version_version_1 (type 21)))
-(import "env" "ext_hashing_blake2_128_version_1" (func $ext_hashing_blake2_128_version_1 (type 22)))
-(import "env" "ext_hashing_blake2_256_version_1" (func $ext_hashing_blake2_256_version_1 (type 22)))
-(import "env" "ext_hashing_keccak_256_version_1" (func $ext_hashing_keccak_256_version_1 (type 22)))
-(import "env" "ext_hashing_twox_128_version_1" (func $ext_hashing_twox_128_version_1 (type 22)))
-(import "env" "ext_hashing_twox_64_version_1" (func $ext_hashing_twox_64_version_1 (type 22)))
-(import "env" "ext_storage_append_version_1" (func $ext_storage_append_version_1 (type 23)))
-(import "env" "ext_storage_clear_version_1" (func $ext_storage_clear_version_1 (type 16)))
-(import "env" "ext_storage_clear_prefix_version_2" (func $ext_storage_clear_prefix_version_2 (type 24)))
-(import "env" "ext_storage_commit_transaction_version_1" (func $ext_storage_commit_transaction_version_1 (type 14)))
-(import "env" "ext_storage_exists_version_1" (func $ext_storage_exists_version_1 (type 22)))
-(import "env" "ext_storage_get_version_1" (func $ext_storage_get_version_1 (type 21)))
-(import "env" "ext_storage_next_key_version_1" (func $ext_storage_next_key_version_1 (type 21)))
-(import "env" "ext_storage_read_version_1" (func $ext_storage_read_version_1 (type 25)))
-(import "env" "ext_storage_rollback_transaction_version_1" (func $ext_storage_rollback_transaction_version_1 (type 14)))
-(import "env" "ext_storage_root_version_2" (func $ext_storage_root_version_2 (type 5)))
-(import "env" "ext_storage_set_version_1" (func $ext_storage_set_version_1 (type 23)))
-(import "env" "ext_storage_start_transaction_version_1" (func $ext_storage_start_transaction_version_1 (type 14)))
-(import "env" "ext_trie_blake2_256_ordered_root_version_2" (func $ext_trie_blake2_256_ordered_root_version_2 (type 26)))
-(import "env" "ext_offchain_is_validator_version_1" (func $ext_offchain_is_validator_version_1 (type 11)))
-(import "env" "ext_offchain_local_storage_clear_version_1" (func $ext_offchain_local_storage_clear_version_1 (type 27)))
-(import "env" "ext_offchain_local_storage_compare_and_set_version_1" (func $ext_offchain_local_storage_compare_and_set_version_1 (type 28)))
-(import "env" "ext_offchain_local_storage_get_version_1" (func $ext_offchain_local_storage_get_version_1 (type 29)))
-(import "env" "ext_offchain_local_storage_set_version_1" (func $ext_offchain_local_storage_set_version_1 (type 30)))
-(import "env" "ext_offchain_network_state_version_1" (func $ext_offchain_network_state_version_1 (type 15)))
-(import "env" "ext_offchain_random_seed_version_1" (func $ext_offchain_random_seed_version_1 (type 11)))
-(import "env" "ext_offchain_submit_transaction_version_1" (func $ext_offchain_submit_transaction_version_1 (type 21)))
-(import "env" "ext_offchain_timestamp_version_1" (func $ext_offchain_timestamp_version_1 (type 15)))
-(import "env" "ext_allocator_free_version_1" (func $ext_allocator_free_version_1 (type 1)))
-(import "env" "ext_allocator_malloc_version_1" (func $ext_allocator_malloc_version_1 (type 0)))
-(import "env" "ext_offchain_index_set_version_1" (func $ext_offchain_index_set_version_1 (type 23)))
-(import "env" "ext_default_child_storage_clear_version_1" (func $ext_default_child_storage_clear_version_1 (type 23)))
-(import "env" "ext_default_child_storage_get_version_1" (func $ext_default_child_storage_get_version_1 (type 24)))
-(import "env" "ext_default_child_storage_next_key_version_1" (func $ext_default_child_storage_next_key_version_1 (type 24)))
-(import "env" "ext_default_child_storage_set_version_1" (func $ext_default_child_storage_set_version_1 (type 31)))
-(import "env" "ext_logging_log_version_1" (func $ext_logging_log_version_1 (type 30)))
-(import "env" "ext_logging_max_level_version_1" (func $ext_logging_max_level_version_1 (type 11)))
-```
-
-<!-- .element: class="fragment" -->
-
----v
-
-- `wasm2wat polkadot_runtime.wasm > dump | rg export`
-
-```
-(export "__indirect_function_table" (table 0))
-(export "Core_version" (func $Core_version))
-(export "Core_execute_block" (func $Core_execute_block))
-(export "Core_initialize_block" (func $Core_initialize_block))
-(export "Metadata_metadata" (func $Metadata_metadata))
-(export "BlockBuilder_apply_extrinsic" (func $BlockBuilder_apply_extrinsic))
-(export "BlockBuilder_finalize_block" (func $BlockBuilder_finalize_block))
-(export "BlockBuilder_inherent_extrinsics" (func $BlockBuilder_inherent_extrinsics))
-(export "BlockBuilder_check_inherents" (func $BlockBuilder_check_inherents))
-(export "NominationPoolsApi_pending_rewards" (func $NominationPoolsApi_pending_rewards))
-(export "NominationPoolsApi_points_to_balance" (func $NominationPoolsApi_points_to_balance))
-(export "NominationPoolsApi_balance_to_points" (func $NominationPoolsApi_balance_to_points))
-(export "StakingApi_nominations_quota" (func $StakingApi_nominations_quota))
-(export "TaggedTransactionQueue_validate_transaction" (func $TaggedTransactionQueue_validate_transaction))
-(export "OffchainWorkerApi_offchain_worker" (func $OffchainWorkerApi_offchain_worker))
-(export "ParachainHost_validators" (func $ParachainHost_validators))
-(export "ParachainHost_validator_groups" (func $ParachainHost_validator_groups))
-(export "ParachainHost_availability_cores" (func $ParachainHost_availability_cores))
-(export "ParachainHost_persisted_validation_data" (func $ParachainHost_persisted_validation_data))
-(export "ParachainHost_assumed_validation_data" (func $ParachainHost_assumed_validation_data))
-(export "ParachainHost_check_validation_outputs" (func $ParachainHost_check_validation_outputs))
-(export "ParachainHost_session_index_for_child" (func $ParachainHost_session_index_for_child))
-(export "ParachainHost_validation_code" (func $ParachainHost_validation_code))
-(export "ParachainHost_candidate_pending_availability" (func $ParachainHost_candidate_pending_availability))
-(export "ParachainHost_candidate_events" (func $ParachainHost_candidate_events))
-(export "ParachainHost_session_info" (func $ParachainHost_session_info))
-(export "ParachainHost_dmq_contents" (func $ParachainHost_dmq_contents))
-(export "ParachainHost_inbound_hrmp_channels_contents" (func $ParachainHost_inbound_hrmp_channels_contents))
-(export "ParachainHost_validation_code_by_hash" (func $ParachainHost_validation_code_by_hash))
-(export "ParachainHost_on_chain_votes" (func $ParachainHost_on_chain_votes))
-(export "ParachainHost_submit_pvf_check_statement" (func $ParachainHost_submit_pvf_check_statement))
-(export "ParachainHost_pvfs_require_precheck" (func $ParachainHost_pvfs_require_precheck))
-(export "ParachainHost_validation_code_hash" (func $ParachainHost_validation_code_hash))
-(export "BeefyApi_beefy_genesis" (func $BeefyApi_beefy_genesis))
-(export "BeefyApi_validator_set" (func $BeefyApi_validator_set))
-(export "BeefyApi_submit_report_equivocation_unsigned_extrinsic" (func $BeefyApi_submit_report_equivocation_unsigned_extrinsic))
-(export "BeefyApi_generate_key_ownership_proof" (func $BeefyApi_generate_key_ownership_proof))
-(export "MmrApi_mmr_root" (func $MmrApi_mmr_root))
-(export "MmrApi_mmr_leaf_count" (func $MmrApi_mmr_leaf_count))
-(export "MmrApi_generate_proof" (func $MmrApi_generate_proof))
-(export "MmrApi_verify_proof" (func $MmrApi_verify_proof))
-(export "MmrApi_verify_proof_stateless" (func $MmrApi_verify_proof_stateless))
-(export "GrandpaApi_grandpa_authorities" (func $GrandpaApi_grandpa_authorities))
-(export "GrandpaApi_current_set_id" (func $GrandpaApi_current_set_id))
-(export "GrandpaApi_submit_report_equivocation_unsigned_extrinsic" (func $GrandpaApi_submit_report_equivocation_unsigned_extrinsic))
-(export "GrandpaApi_generate_key_ownership_proof" (func $GrandpaApi_generate_key_ownership_proof))
-(export "BabeApi_configuration" (func $BabeApi_configuration))
-(export "BabeApi_current_epoch_start" (func $BabeApi_current_epoch_start))
-(export "BabeApi_current_epoch" (func $BabeApi_current_epoch))
-(export "BabeApi_next_epoch" (func $BabeApi_next_epoch))
-(export "BabeApi_generate_key_ownership_proof" (func $BabeApi_generate_key_ownership_proof))
-(export "BabeApi_submit_report_equivocation_unsigned_extrinsic" (func $BabeApi_submit_report_equivocation_unsigned_extrinsic))
-(export "AuthorityDiscoveryApi_authorities" (func $AuthorityDiscoveryApi_authorities))
-(export "SessionKeys_generate_session_keys" (func $SessionKeys_generate_session_keys))
-(export "SessionKeys_decode_session_keys" (func $SessionKeys_decode_session_keys))
-(export "AccountNonceApi_account_nonce" (func $AccountNonceApi_account_nonce))
-(export "TransactionPaymentApi_query_info" (func $TransactionPaymentApi_query_info))
-(export "TransactionPaymentApi_query_fee_details" (func $TransactionPaymentApi_query_fee_details))
-(export "TransactionPaymentApi_query_weight_to_fee" (func $TransactionPaymentApi_query_weight_to_fee))
-(export "TransactionPaymentApi_query_length_to_fee" (func $TransactionPaymentApi_query_length_to_fee))
-(export "TransactionPaymentCallApi_query_call_info" (func $TransactionPaymentCallApi_query_call_info))
-(export "TransactionPaymentCallApi_query_call_fee_details" (func $TransactionPaymentCallApi_query_call_fee_details))
-(export "TransactionPaymentCallApi_query_weight_to_fee" (func $TransactionPaymentCallApi_query_weight_to_fee))
-(export "TransactionPaymentCallApi_query_length_to_fee" (func $TransactionPaymentCallApi_query_length_to_fee))
-(export "TryRuntime_on_runtime_upgrade" (func $TryRuntime_on_runtime_upgrade))
-(export "TryRuntime_execute_block" (func $TryRuntime_execute_block))
-(export "__data_end" (global 1))
-(export "__heap_base" (global 2))
-```
-
----v
-
-### Workshop: Inspecting Wasm Code
-
-- Once you reach the Polkadot module, and you build your first parachain, repeat the same, I promise
-  you will learn a thing or two :)
-
----
-
-### Activity: Expected Panics In The Runtime
-
-- Look into the `frame-executive` crate's code.
-  See instances of `panic!()`, and see if you can make sense out of it.
-- You have 15 minutes!
-
-<diagram class="mermaid">
-graph LR
-    TransactionPool --"😈"--> Authoring --"😇"--> Import
-</diagram>
-
----
-
-## Lecture Recap (Part 2)
-
-- Recap the syntax of host functions and runtime APIs.
-- Considerations:
-  - Speed
-  - Native Execution and Versioning
-  - Panics
-  - Altering Host Functions
-
----
-
-## Additional Resources! 😋
-
-> Check speaker notes (click "s" 😉)
-
-<img width="300px" rounded src="../scale/img/thats_all_folks.png" />
-
-Notes:
-
-- Some very recent change the the block building API set: https://github.com/paritytech/substrate/pull/14414
-
-- New runtime API for building genesis config: https://github.com/paritytech/substrate/pull/14310
-
-- All Substrate PRs that have added new host functions: https://github.com/paritytech/substrate/issues?q=label%3AE4-newhostfunctions+is%3Aclosed
-
-- All substrate PRs that have required the client to be update first: https://github.com/paritytech/substrate/issues?q=is%3Aclosed+label%3A%22E10-client-update-first+%F0%9F%91%80%22
-
-- New metadata version, including types for the runtime API: https://github.com/paritytech/substrate/issues/12939
-
-- Recent development on api versioning: https://github.com/paritytech/substrate/issues/13138
-
-- In Substrate, a type needs to provide the environment in which host functions are provided, and
-  can be executed.
-
-> We call this an "externality environment", represented by `trait Externalities`.
-
-```rust
-SomeExternalities.execute_with(|| {
-    let x = sp_io::storage::get(b"foo");
-});
-```
-
-### Post Lecture Notes
-
----
-
-## Appendix
-
-Content that is not covered, but is relevant.
-
----v
-
-### Consideration: Runtime API Versioning
-
-- Same principle, but generally easier to deal with.
-- Metadata is part of the runtime, known **per block**.
-- Those written in a dynamically typed languages are usually fine 😎.
-
-Notes:
-
-Also, it is arguable to say that the runtime is the boss here.
-The client must serve the runtime fully, but the runtime may or may not want to support certain APIs for certain applications.
-
-Recall from another slide:
-
-> - A lot of other runtime APIs _could_ be optional depending on the context.
-
----v
-
-### Consideration: Runtime API Versioning
-
-- The Rust code (which is **statically** typed) in substrate client does care if the change _is breaking_.
-  - For example, input/output types change.
-    Rust code cannot deal with that!
-
----v
-
-### Consideration: Runtime API Versioning
-
-```rust
-sp_api::decl_runtime_apis! {
-    // latest version
-    fn foo() -> u32;
-
-    // old version
-    #[changed_in(4)]
-    fn foo() -> u64;
-}
-
-let new_return_type = if api.version < 4 {
-    // this weird function name is generated by decl_runtime_apis!
-    let old_return_type = api.foo_before_version_4();
-    // somehow convert it. don't care
-    old_return_type.try_into().unwrap()
-} else {
-    api.foo()
-}
-```
-
----v
-
-### Consideration: Runtime API Versioning
-
-> Rule of thumb: Every time you change the signature of a host function / runtime API, i.e. change
-> the input/output types, you need to think about this.
-
-But what you have to do is dependent on the scenario.
-
-### Activity: API Versioning
-
-- Look into substrate and find all instances of `#[changed_in(_)]` macro to detect runtime api version.
-- Then see if/how this is being used in the client code.
-
-- Find all the `#[version]` macros in `sp-io` to find all the versioned host functions.
diff --git a/content/xcm/README.md b/content/xcm/README.md
deleted file mode 120000
index dd0ea36c..00000000
--- a/content/xcm/README.md
+++ /dev/null
@@ -1 +0,0 @@
-index.md
\ No newline at end of file
diff --git a/content/xcm/_materials/activities.md b/content/xcm/_materials/activities.md
deleted file mode 100644
index e193ee1b..00000000
--- a/content/xcm/_materials/activities.md
+++ /dev/null
@@ -1,7 +0,0 @@
-# XCM Activities
-
-Various XCM activities and exercises.
-
-## 📥 Clone to start: <a target="_blank" href="https://github.com/Polkadot-Blockchain-Academy/xcm-activities">XCM Activities</a>
-
-See the README included in the repository for further instructions.
diff --git a/content/xcm/beyond/page.md b/content/xcm/beyond/page.md
deleted file mode 100644
index d4854284..00000000
--- a/content/xcm/beyond/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# XCM Beyond Asset Transfers
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/xcm/beyond/slides.md b/content/xcm/beyond/slides.md
deleted file mode 100644
index 66f2a91e..00000000
--- a/content/xcm/beyond/slides.md
+++ /dev/null
@@ -1,522 +0,0 @@
----
-title: XCM Beyond Asset Transfers
-description: Deep dive on advanced XCM use cases beyond asset transfers and bridging
-duration: 1 hour
----
-
-# XCM Beyond Asset Transfers
-
----
-
-## Outline
-
-<pba-flex center>
-
-1. Pre-requisites
-1. XCMultisig
-1. XCM Universal Interface
-1. General XCM Tips
-1. Conclusion
-1. Next Steps
-1. References
-
-</pba-flex>
-
----
-
-## Pre-requisites
-
-The following are expected:
-
-<pba-flex center>
-
-- Knowledge of core XCM concepts
-- Knowledge of XCM chain configuration
-
-</pba-flex>
-
----
-
-## XCMultisig
-
-[InvArch Network](https://invarch.network/) has the concept of XCMultisigs, these are entities that exist on the InvArch Network runtime and provide advanced multisig capabilities to users across many other blockchains.
-
-Let's go over how that works!
-
-Notes:
-
-The reason for the name comes from their XCM functionality, more specifically from the idea that these entities have their logic defined in the InvArch Network runtime, but exist in all other connected chains with the same exact account address, thus allowing them to transact in these chains through XCM.
-
----v
-
-### Overview
-
-<diagram class="mermaid">
-stateDiagram-v2
-state Polkadot {
-    direction LR
-
-    state InvArch {
-        direction LR
-        v0: Multisig ID 0
-        sxc: Send XCM Call
-        vacc: 0x123...
-
-        state if_state <<choice>>
-        v0 --> if_state
-
-        if_state --> sxc
-        if_state --> vacc
-
-        vacc --> [*]: Transact
-
-
-        sxc --> h0
-        sxc --> i0
-        sxc --> b0
-    }
-
-    state HydraDX {
-        direction LR
-
-        h0: Multisig ID 0
-        hmxs: **XCM Converters**
-        hacc: 0x123...
-
-        h0 --> hmxs
-        hmxs --> hacc
-        hacc --> [*]: Transact
-    }
-
-    state Interlay {
-        direction LR
-
-        i0: Multisig ID 0
-        imxs: **XCM Converters**
-        iacc: 0x123...
-
-        i0 --> imxs
-        imxs --> iacc
-        iacc --> [*]: Transact
-    }
-
-    state Bifrost {
-        direction LR
-
-        b0: Multisig ID 0
-        bmxs: **XCM Converters**
-        bacc: 0x123...
-
-        b0 --> bmxs
-        bmxs --> bacc
-        bacc --> [*]: Transact
-    }
-
-}
-</diagram>
-
----v
-
-### Message details
-
-To better understand how this all works, let's go over the messages being sent and their origins.
-
-```rust [0|1-13|15-33|35|37-53|55|57-75]
-let multisig: MultiLocation = MultiLocation {
-  parents: 1,
-  interior: Junctions::X3(
-    Junction::Parachain(<T as pallet::Config>::ParaId::get()),
-    Junction::PalletInstance(<T as pallet::Config>::INV4PalletIndex::get()),
-    Junction::GeneralIndex(0u128),
-  ),
-};
-
-let multisig_interior = Junctions::X2(
-  Junction::PalletInstance(<T as pallet::Config>::INV4PalletIndex::get()),
-  Junction::GeneralIndex(0u128),
-);
-
-let destination = MultiLocation {
-  parents: 1,
-  interior: Junctions::X1(
-    Junction::Parachain(1234)
-  ),
-};
-
-let fee_asset_location = MultiLocation {
-  parents: 1,
-  interior: Junctions::X2(
-    Junction::Parachain(1234),
-    Junction::GeneralIndex(0),
-  ),
-};
-
-let fee_multiasset = MultiAsset {
-  id: AssetId::Concrete(fee_asset_location),
-  fun: Fungibility::Fungible(1000000000000),
-};
-
-let call = vec![...];
-
-let message = Xcm(vec![
-  Instruction::WithdrawAsset(fee_multiasset.clone().into()),
-  Instruction::BuyExecution {
-    fees: fee_multiasset,
-    weight_limit: WeightLimit::Unlimited,
-  },
-  Instruction::Transact {
-    origin_kind: OriginKind::Native,
-    require_weight_at_most: 5000000000,
-    call: <DoubleEncoded<_> as From<Vec<u8>>>::from(call),
-  },
-  Instruction::RefundSurplus,
-  Instruction::DepositAsset {
-    assets: MultiAssetFilter::Wild(WildMultiAsset::All),
-    beneficiary: multisig,
-  },
-]);
-
-pallet_xcm::Pallet::<T>::send_xcm(multisig_interior, destination, message)?;
-
-// Pallet XCM will then add a DescendOrigin instruction to index 0 of the message.
-Instruction::DescendOrigin(multisig_interior)
-
-// Which mutates the initial Origin
-MultiLocation {
-  parents: 1,
-  interior: Junctions::X1(
-    Junction::Parachain(<T as pallet::Config>::ParaId::get()),
-  ),
-}
-// Becomes
-MultiLocation {
-  parents: 1,
-  interior: Junctions::X3(
-    Junction::Parachain(<T as pallet::Config>::ParaId::get()),
-    Junction::PalletInstance(<T as pallet::Config>::INV4PalletIndex::get()),
-    Junction::GeneralIndex(0u128),
-  ),
-}
-```
-
----v
-
-### XCM Converters
-
-Now that we understand the origin and message structure, let's take a look at those _XCM Converters_!
-
-<diagram class="mermaid">
-stateDiagram-v2
-  direction LR
-
-    para: Parachain 2125
-    pal: Pallet 51
-    m: Mulisig ID 0
-    acc: 0x123...
-
-    para --> if
-    pal --> if
-    m --> hash
-
-      state Checks {
-        if: Parachain == 2125 && Pallet == 51
-        if --> [*]: No Match
-        if --> Hasher: Match
-      }
-
-      state Hasher {
-        cs: Constant Salt
-
-        cs --> hash
-      }
-
-    hash --> acc
-
-</diagram>
-
-Notes:
-
-The reason for the custom hasher is to replicate the account generation in the origin chain.
-The combination of these checks and the hasher makes up the converters that return AccountIds and native Origins for our MultiLocation.
-
----v
-
-### What happens if we map AccountId origins to the exact accounts within?
-
-## Account Impersonation!
-
-<!-- .element: class="fragment" data-fragment-index="0" -->
-
-Hey Chain B, I'm sending you a balance transfer request from one of my users, their address is "Chain B's treasury" ;)
-
-<!-- .element: class="fragment" data-fragment-index="1" -->
-
-# TRUST!
-
-<!-- .element: class="fragment" data-fragment-index="2" -->
-
-Notes:
-
-Emphatically explain this!
-
----
-
-## XCM Universal Interface
-
-XCM can be used as a general API abstraction on top of multiple blockchains.
-With some clever usage, we can build chains that can be integrated by dApps in a generic manner, and also dApps that easily integrate multiple chains without any custom logic.
-
----v
-
-## Concept
-
-###### XCM Powered Multichain NFT Marketplace
-
-Imagine an NFT marketplace where not only multiple chains are supported, but also any standards these chains choose to implement!
-
----v
-
-### How?
-
-<diagram class="mermaid">
-stateDiagram-v2
-  direction TB
-
-    ui: UI
-    xcm: XCM API
-    indexer: Indexer
-
-    ui --> xcm
-
-    indexer --> ui
-
-    xcm --> axti
-    xcm --> mxti
-    xcm --> cxti
-
-    state Asset_Hub {
-      axti: XCM AssetExchanger
-      apu: Pallet Uniques
-      apn: Pallet NFTs
-
-      axti --> apu
-      axti --> apn
-    }
-
-    state Moonbeam {
-      mxti: XCM AssetExchanger
-      mpe: Pallet EVM
-
-      mxti --> mpe
-    }
-
-    state Chain_C {
-      cxti: XCM AssetExchanger
-      cpu: Pallet Uniques
-      cpc: Pallet Contracts
-
-      cxti --> cpu
-      cxti --> cpc
-    }
-
-</diagram>
-
----v
-
-### Matching NFTs
-
-```rust [0|4-15|18-21]
-MultiAsset {
-  // Where to find the NFT (contract or collection in an NFT pallet)
-  id: AssetId::Concrete (
-    Multilocation {
-      parents: 0,
-      interior: Junctions::X3(
-        // Parachain ID just so we can pre-check if this message was intended for this chain
-        Junction::Parachain (para_id),
-        // Pallet ID so we know which pallet we should be using to look up the NFT
-        Junction::PalletInstance(pallet_id),
-        // General Index to select a specific collection by integer id
-        // Or GeneralKev to select a specific collection bv it's contract id
-        Junction::GeneralIndex(collection_id) or Junction::GeneralKey(contract_address),
-      )
-    }
-  ),
-  // The NFT itself
-  fun: Fungibility::NonFungible(
-    // Specific NFT instance inside the collection selected by it's id
-    AssetInstance::Instance(nft_id)
-  )
-}
-```
-
----v
-
-### Implementing AssetExchanger
-
-```rust [1-20|22-38|40-48]
-pub trait AssetExchange {
-	/// Handler for exchanging an asset.
-	///
-	/// - `origin`: The location attempting the exchange; this should generally not matter.
-	/// - `give`: The assets which have been removed from the caller.
-	/// - `want`: The minimum amount of assets which should be given to the caller in case any
-	///   exchange happens. If more assets are provided, then they should generally be of the
-	///   same asset class if at all possible.
-	/// - `maximal`: If `true`, then as much as possible should be exchanged.
-	///
-	/// `Ok` is returned along with the new set of assets which have been exchanged for `give`. At
-	/// least want must be in the set. Some assets originally in `give` may also be in this set. In
-	/// the case of returning an `Err`, then `give` is returned.
-	fn exchange_asset(
-		origin: Option<&MultiLocation>,
-		give: Assets,
-		want: &MultiAssets,
-		maximal: bool,
-	) -> Result<Assets, Assets>;
-}
-
-struct MyNftStandardExchanger;
-
-impl AssetExchange for MyNftStandardExchanger {
-	fn exchange_asset(
-		origin: Option<&MultiLocation>,
-		give: Assets,
-		want: &MultiAssets,
-		maximal: bool,
-	) -> Result<Assets, Assets> {
-    match (give, want) {
-      (FUNGIBLE, NONFUNGIBLE) => MyNftPallet::buy(...),
-      (NONFUNGIBLE, FUNGIBLE) => MyNftPallet::sell(...),
-      (NONFUNGIBLE, NONFUNGIBLE) => MyNftPallet::swap(...),
-      (FUNGIBLE, FUNGIBLE) => Err(give),
-    }
-	}
-}
-
-impl xcm_executor::Config for XcmConfig {
-  ...
-  type AssetExchanger = (
-    MyNftStandardExchanger,
-    EvmNftExchanger,
-    PalletUniquesExchanger
-  );
-  type AssetTransactor = AssetTransactors;
-}
-```
-
----
-
-## General XCM Tips
-
-In this section we will go over some general tips on how to build with XCM.
-
----v
-
-### MultiLocations & MultiAssets
-
-Deciding how to map MultiLocations to entities in your runtime is very important, as these MultiLocations will end up being used across other XCM-connected chains.
-
-```rust [1-4|6-8|10-11|13-14|16-17|19-24|26-32]
-// Main runtime token
-Junctions::X1(Parachain(para_id));
-Junctions::X2(Parachain(para_id), GeneralIndex(main_token_id));
-Junctions::X2(Parachain(para_id), PalletInstance(balances_pallet_id));
-
-// Other tokens
-Junctions::X2(Parachain(para_id), GeneralIndex(token_id));
-Junctions::X3(Parachain(para_id), PalletInstance(tokens_pallet_id), GeneralIndex(token_id));
-
-// Runtime protocols (i.e. Treasury or it's account)
-Junctions::X2(Parachain(para_id), PalletInstance(treasury_pallet_id));
-
-// Wasm smart contracts
-Junctions::X3(Parachain(para_id), PalletInstance(contracts_pallet_id), AccountId32(wasm_contract_account));
-
-// EVM smart contracts
-Junctions::X3(Parachain(para_id), PalletInstance(evm_pallet_id), AccountKey20(evm_contract_account));
-
-// Wasm or EVM contracts
-Junctions::X3(
-  Parachain(para_id),
-  PalletInstance(contracts_pallet_id || evm_pallet_id),
-  AccountId32(wasm_contract_account) || AccountKey20(evm_contract_account),
-);
-
-// NFTs
-MultiAsset {
-  // Match collection
-  id: Concrete(wasm_or_evm_multilocation || X2(Parachain(para_id), PalletInstance(nft_pallet_id))),
-  // Match item
-  fun: Fungibility::NonFungible(AssetInstance::Index(nft_id))
-};
-```
-
----v
-
-### Message Instructions
-
-```rust [1-23|25-45]
-// Pay for execution fees and refund surplus
-Xcm(vec![
-  // Withdraw asset to use within this message, places the amount in the holding register.
-  Instruction::WithdrawAsset(fee_multiasset.into()),
-  // Pay for execution fees during this message.
-  Instruction::BuyExecution {
-    // The asset and amount we withdrew in the first instruction.
-    fees: fee_multiasset,
-    // Max amount of weight we are willing to buy.
-    weight_limit: WeightLimit::Unlimited,
-  },
-  // An instruction or set of instructions that will require payment of execution fees.
-  <Instruction that pays execution fee>,
-  // Refund unused purchased weight back to the holding register.
-  Instruction::RefundSurplus,
-  // Deposit assets from the holding register back into the balance of an account.
-  Instruction::DepositAsset {
-    // Match total amount of all assets in the holding register.
-    assets: MultiAssetFilter::Wild(WildMultiAsset::All),
-    // The receiver of the refunded fees, usually the origin that paid for the fees in the first place.
-    beneficiary: account_id_multilocation,
-  },
-]);
-
-// XCM assertions
-
-// Errors is described pallet does not exist in the runtime.
-ExpectPallet {
-  // Pallet index.
-  index: 21,
-  // Pallet name.
-  name: "Referenda".as_bytes().to_vec(),
-  // Name of the module.
-  module_name: "pallet_referenda".as_bytes().to_vec(),
-  // Major version of the crate.
-  crate_major: 4,
-  // Minimum minor version acceptable.
-  min_crate_minor: 0,
-}
-
-// Errors if described asset and amount are not present in the holding register.
-ExpectAsset(MultiAsset {
-	id: AssetId::Concrete(asset_multilocation),
-  fun: Fungibility::Fungible(1_000_000_000_000u128),
-})
-```
-
----
-
-## Conclusion
-
-During this presentation we went through a couple real world XCM use cases and some general tips for working with the message standard, the goal here is to leave you with some inspiration and some ideas, so that you can start tinkering with XCM to power your own ideas and supercharge blockchain applications!
-
----
-
-## References
-
-- [XCM source code](https://github.com/paritytech/polkadot-sdk/tree/master/polkadot/xcm) - The source code for the main XCM implementation in the paritytech/polkadot repository.
-
-<!-- FIXME new repo expected soon for XCM outside SDK -->
-
-- [XCM Documentation](https://paritytech.github.io/xcm-docs/) - The official documentation for XCM: Cross-Consensus Messaging.
-- [InvArch's Pallet Rings](https://github.com/InvArch/InvArch-Frames/tree/main/pallet-rings) - Reference implementation of an XCM abstraction pallet for XCMultisigs.
diff --git a/content/xcm/config/page.md b/content/xcm/config/page.md
deleted file mode 100644
index 494d4fc9..00000000
--- a/content/xcm/config/page.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Parachain XCM Configuration
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/xcm/config/slides.md b/content/xcm/config/slides.md
deleted file mode 100644
index 208949b1..00000000
--- a/content/xcm/config/slides.md
+++ /dev/null
@@ -1,520 +0,0 @@
----
-title: Parachain XCM Configuration # Also update the h1 header on the first slide to the same name
-description: XCM configuration overview and considerations, for parachains.
-duration: 1 hour
----
-
-# Parachain XCM Configuration
-
----v
-
-## _At the end of this lecture, you will be able to:_
-
-<pba-flex center>
-
-- Understand the different XCM configurable parts of a chain
-- Construct different XCM configurations for chains with different needs
-
----
-
-## 🛠️ Configurables in `XcmConfig`
-
-Notes:
-
-The XCM Configuration has many configurable items
-
-EXERCISE: ask the class to raise hands and postulate on what they think should be configurable.
-
----v
-
-## 🛠️ Configurables in `XcmConfig`
-
-```rust [1-2|6-7|8-9|10-11|12-13|14-15|16-31]
-// How we convert locations into account ids
-type SovereignAccountOf = SovereignAccountOf;
-
-pub struct XcmConfig;
-impl Config for XcmConfig {
-  // The absolute Location of the current system
-  type UniversalLocation = UniversalLocation;
-  // Pre-execution filters
-  type Barrier = Barrier;
-  // How we withdraw/deposit assets
-  type AssetTransactor = LocalAssetTransactor;
-  // How we convert a Location to a FRAME dispatch origin
-  type OriginConverter = LocalOriginConverter;
-  // How we route the XCM outside this chain
-  type XcmSender = XcmRouter;
-  // Who we trust as reserve chains
-  type IsReserve = ?;
-  // Who do we trust as teleporters
-  type IsTeleporter = ?;
-  // How we weigh a message
-  type Weigher = ?;
-  // How we charge for fees
-  type Trader = ?;
-  // How we handle responses
-  type ResponseHandler = ?;
-  // How we handle asset traps
-  type AssetTrap = ?;
-  // How we handle asset claims
-  type AssetClaims = ?;
-  // How we handle version subscriptions
-  type SubscriptionService = ?;
-}
-```
-
-Notes:
-
-- `SovereignAccountOf`: Means of converting a `Location` into an account ID
-  Used later for: `OriginConverter` , `AssetTransactor`
-
-- `xcm-pallet` is a pallet that not only allows sending and executing XCM messages, but rather it also implements several of the configuration traits and thus can be used perform several XCM configuration actions.
-
----v
-
-## 🛠️ `xcm-builder`
-
-`xcm-builder` is a crate containing common configuration shims to facilitate XCM configuration.
-
-Most pre-built configuration items can be found in `xcm-builder`.
-
-It allows to use the XCM executor in FRAME.
-
----
-
-### 🤔 Grab your chain's requirements before starting
-
-Questions that you should have answers for:
-
-- _Is my chain going to transfer just the native token?_
-  _Is my chain going to receive several other kinds of assets?_
-
-- _Is my chain going to allow free execution?_
-  _Maybe only limited to some parachains/relay chain?_
-
-- _Is my chain a 20 byte account chain?_
-  _a 32 byte account chain?_
-
-- _How will my chain accept fee payment?_
-  _In one asset?_
-  _In several?_
-
-Notes:
-
-- Some of the answers to these questions might imply you need to use your own custom primitives.
-
----v
-
-### Our starting example setup requirements
-
-1. Parachain that does not charge for relay incoming messages.
-2. Parachain that trusts the relay as the reserve chain for the relay chain tokens.
-3. Parachain that mints in `pallet-balances` when it receives relay chain tokens.
-4. Users can execute XCMs locally.
-
----
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- Defines how we convert a `Location` into a local account ID.
-- Useful when we want to withdraw/deposit tokens from a `Location` defined origin
-- Useful when we want to dispatch as signed origins from a `Location` defined origin.
-
-<diagram class="mermaid">
-graph TD;
-  Location("AccountId32 { id: [18, 52, ..., 205, 239], network: Some(Rococo) }")-- SovereignAccountOf -->Account("0x123..def (Alice)")
-</diagram>
-
-Notes:
-
-- This will define how we convert a `Location` into a local account ID.
-- This is useful when we want to withdraw/deposit tokens from a `Location` defined origin or when we want to dispatch as signed origins from a `Location` defined origin.
-
----v
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- `HashedDescription`: Hashes the description of a `Location` and converts that into an `AccountId`.
-
-```rust
-pub struct HashedDescription<AccountId, Describe>(PhantomData<(AccountId, Describe)>);
-impl<
-  AccountId: From<[u8; 32]> + Clone,
-  Describe: DescribeLocation
-> ConvertLocation<AccountId> for HashedDescription<AccountId, Describe>
-{
-	fn convert_location(value: &Location) -> Option<AccountId> {
-		Some(blake2_256(&Describe::describe_location(value)?).into())
-	}
-}
-```
-
----v
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- `HashedDescription`. An example of a converter definition:
-
-<pba-flex center>
-
-```rust
-pub type LocationToAccount =
-  HashedDescription<AccountId, (
-    LegacyDescribeForeignChainAccount, // Legacy conversion - MUST BE FIRST!
-    DescribeTerminus,
-    DescribePalletTerminal
-  )>;
-```
-
----v
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- `DescribeLocation`: Means of converting a location into a stable and unique descriptive identifier.
-
-```rust
-pub trait DescribeLocation {
-	/// Create a description of the given `location` if possible. No two locations should have the
-	/// same descriptor.
-	fn describe_location(location: &Location) -> Option<Vec<u8>>;
-}
-```
-
-Notes:
-
-[Impl for Tuple](https://github.com/paritytech/polkadot-sdk/blob/342d720/polkadot/xcm/xcm-builder/src/location_conversion.rs#L34)
-
----v
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- `DescribeAccountId32Terminal`
-
-```rust
-fn describe_location(l: &Location) -> Option<Vec<u8>> {
-	match (l.parents, &l.interior) {
-		(0, X1(AccountId32 { id, .. })) => Some((b"AccountId32", id).encode()),
-		_ => return None,
-	}
-}
-```
-
----v
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- `DescribeTerminus`
-
-```rust
-fn describe_location(l: &Location) -> Option<Vec<u8>> {
-	match (l.parents, &l.interior) {
-		(0, Here) => Some(Vec::new()),
-		_ => return None,
-	}
-}
-```
-
----v
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- `DescribePalletTerminal`
-
-```rust
-fn describe_location(l: &Location) -> Option<Vec<u8>> {
-	match (l.parents, &l.interior) {
-		(0, X1(PalletInstance(i))) =>
-			Some((b"Pallet", Compact::<u32>::from(*i as u32)).encode()),
-		_ => return None,
-	}
-}
-```
-
----v
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- `DescribeAccountKey20Terminal`
-
-```rust
-fn describe_location(l: &Location) -> Option<Vec<u8>> {
-	match (l.parents, &l.interior) {
-		(0, X1(AccountKey20 { key, .. })) => Some((b"AccountKey20", key).encode()),
-		_ => return None,
-	}
-}
-```
-
----v
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- `AccountId32Aliases`: Converts a local `AccountId32` `Location` into an account ID of 32 bytes.
-
-- `Account32Hash`: Hashes the `Location` and takes the lowest 32 bytes as account.
-
-- `ParentIsPreset`: Converts the parent `Location` into an account of the form `b'Parent' + trailing 0s`
-
----v
-
-### 📁 `SovereignAccountOf` via `xcm-builder`
-
-- `ChildParachainConvertsVia`: Converts the **child** parachain `Location` into an account of the form `b'para' + para_id_as_u32 + trailing 0s`
-
-- `SiblingParachainConvertsVia`: Convert the **sibling** parachain `Location` into an account of the form `b'sibl' + para_id_as_u32 + trailing 0s`
-
----
-
-### `UniversalLocation`
-
-The absolute location of the consensus system being configured.
-
-<pba-flex center>
-
-```rust
-parameter_types! {
-  pub const UniversalLocation: InteriorLocation = GlobalConsensus(NetworkId::Polkadot).into();
-}
-```
-
----
-
-### 🚧 `Barrier` via `xcm-builder`
-
-- Barriers specify whether or not an XCM is allowed to be executed on the local consensus system.
-- They are checked before the actual XCM instruction execution.
-- **Barriers should not involve any heavy computation.**
-
-Notes:
-
-**At the point at which barriers are checked nothing has yet been paid for its execution**.
-
----v
-
-### 🚧 `Barrier` via `xcm-builder`
-
-Physical vs Computed origin
-
-- Physical origin: the consensus system that built this particular XCM and sent it to the recipient
-- Computed origin: the entity that ultimately instructed the consensus system to build the XCM
-
-Notes:
-
-If an EOA transfers some funds via XCM, then the computed origin would be its account, but the physical origin would be the platform that was used (e.g. parachain).
-
----v
-
-### 🚧 `Barrier` via `xcm-builder`
-
-Barriers that operate upon **computed origins** must be put inside of `WithComputedOrigin`.
-
-Allows for origin altering instructions at the start.
-
-<pba-flex center>
-
-```rust
-pub struct WithComputedOrigin<InnerBarrier, LocalUniversal, MaxPrefixes>;
-```
-
----v
-
-### 🚧 `Barrier` via `xcm-builder`
-
-- `TakeWeightCredit`: Subtracts the maximum weight the message can consume from the available weight credit.
-  Usually configured for local `xcm-execution`
-
----v
-
-### 🚧 `Barrier` via `xcm-builder`
-
-- `AllowTopLevelPaidExecutionFrom<T>`: For origins contained in `T`, it makes sure the first instruction puts asset into the holding register, followed by a `BuyExecution` instruction capable of buying sufficient weight.
-  **Critical to avoid free DOS**.
-
-Notes:
-
-- A chain without `AllowTopLevelPaidExecutionFrom` could potentially receive several heavy-computation instructions without paying for it.
-  Checking that the first instructions are indeed paying for execution helps to quick-discard them.
-
-- While `BuyExecution` is crucial for messages coming from other consensus systems, local XCM execution fees are paid as any other substrate extrinsic.
-
----v
-
-### 🚧 `Barrier` via `xcm-builder`
-
-- `AllowExplicitUnpaidExecutionFrom<T>`: Allows free execution if `origin` is contained in `T` and the first instruction is `UnpaidExecution`.
-
-Notes:
-
-- **This fulfills our requirements**
-- To meet our example use case, we only need the relay to have free execution.
-
----v
-
-### 🚧 `Barrier` via `xcm-builder`
-
-- `AllowKnownQueryResponses`: Allows the execution of the message if it contains only an expected `QueryResponse`
-- `AllowSubscriptionsFrom<T>`: If the `origin` that sent the message is contained in `T`, it allows the execution of the message if it contains only a `SubscribeVersion` or `UnsubscribeVersion` instruction
-
----
-
-### 🪙 `AssetTransactor` via `xcm-builder`
-
-- Define how we are going to withdraw and deposit assets
-- Heavily dependant on the assets we want our chain to transfer
-
-<diagram class="mermaid">
-graph LR
-  Withdraw("WithdrawAsset((Here, 100u128).into())")-->DOT(100 tokens from e.g. pallet-balances)
-</diagram>
-
-Notes:
-
-- The relay chain is a clear example of a chain that handles a **single token**.
-- AssetHub on the contrary acts as an asset-reserve chain, and it needs to handle **several assets**
-
----v
-
-### 🪙 `AssetTransactor` via `xcm-builder`
-
-- `FungiblesAdapter`: Used for depositing/withdrawing from a set of defined fungible tokens.
-  An example of these would be `pallet-assets` tokens.
-- `NonFungiblesAdapter`: Used for depositing/withdrowing NFTs. For example `pallet-nfts`.
-
-Notes:
-
-- **Matcher**: Matches the `Asset` against some filters and returns the amount to be deposited/withdrawn
-- **AccountIdConverter**: Means of converting a `Location` into an account
-
-- For our example, it suffices to uses `CurrencyAdapter`, as all we are going to do is mint in a single currency (Balances) whenever we receive the relay token.
-
----v
-
-### 🪙 `AssetTransactor` via `xcm-builder`
-
-<pba-flex center>
-
-```rust
-fn withdraw_asset(
-	what: &Asset,
-	who: &Location,
-	_maybe_context: Option<&XcmContext>,
-) -> result::Result<xcm_executor::Assets, XcmError> {
-	let (asset_id, amount) = Matcher::matches_fungibles(what)?;
-	let who = AccountIdConverter::convert_location(who)
-		.ok_or(MatchError::AccountIdConversionFailed)?;
-	Assets::burn_from(asset_id, &who, amount, Exact, Polite)
-		.map_err(|e| XcmError::FailedToTransactAsset(e.into()))?;
-	Ok(what.clone().into())
-}
-```
-
----v
-
-### 🪙 `AssetTransactor` via `xcm-builder`
-
-<pba-flex center>
-
-```rust
-fn deposit_asset(
-  what: &Asset,
-  who: &Location,
-  _context: &XcmContext
-) -> XcmResult {
-	let (asset_id, amount) = Matcher::matches_fungibles(what)?;
-	let who = AccountIdConverter::convert_location(who)
-		.ok_or(MatchError::AccountIdConversionFailed)?;
-	Assets::mint_into(asset_id, &who, amount)
-		.map_err(|e| XcmError::FailedToTransactAsset(e.into()))?;
-	Ok(())
-}
-```
-
----
-
-### 📍 `OriginConverter` via `xcm-builder`
-
-- Defines how to convert an XCM origin, defined by a `Location`, into a frame dispatch origin.
-- Used in the `Transact` instruction.
-
-Notes:
-
-- `Transact` needs to dispatch from a frame dispatch origin.
-  However the `xcm-executor` works with XCM origins which are defined by `Location`s.
-- `OriginConverter` is the component that converts one into the other
-
----v
-
-### 📍 List of origin converters
-
-- `SovereignSignedViaLocation`: Converts the `Location` origin (typically, a parachain origin) into a signed origin.
-
-- `SignedAccountId32AsNative`: Converts a local 32 byte account `Location` into a signed origin using the same 32 byte account.
-
-- `ParentAsSuperuser`: Converts the parent origin into the root origin.
-
-- `SignedAccountKey20AsNative`: Converts a local 20 byte account `Location` into a signed origin using the same 20 byte account.
-
-Notes:
-
-- `ParentAsSuperuser` can be used in common-good chains as they do not have a local root origin and instead allow the relay chain root origin to act as the root origin.
-
----
-
-## 🛠️ XcmRouter in `XcmConfig`
-
-- `ParentAsUmp` routes XCM to relay chain through UMP.
-- `XcmpQueue` routes XCM to other parachains through XCMP.
-
-<pba-flex center>
-
-```rust
-pub type XcmRouter = (
-	// Two routers - use UMP to communicate with the relay chain:
-	cumulus_primitives_utility::ParentAsUmp<ParachainSystem, PolkadotXcm>,
-	// ..and XCMP to communicate with the sibling chains.
-	XcmpQueue,
-);
-```
-
-Notes:
-
-- `ParachainSystem` is a pallet in cumulus that handles incoming DMP messages and queues, among other miscellaneous parachain-related matters.
-- If the destination location matches the form of `Location { parents: 1, interior: Here }`, the message will be routed through UMP.
-  The UMP channel is available by default.
-- If the destination matches the form of `Location { parents: 1, interior: X1(Parachain(para_id)) }`, the message will be routed through XCMP.
-  As of today, an HRMP channel should be established before the message can be routed.
-- The tuple implementation of this item means the executor will try using the items in order.
-
----v
-
-## Router
-
-```rust
-pub trait SendXcm {
-  type Ticket;
-
-  fn validate(
-    destination: &mut Option<Location>,
-    message: &mut Option<Xcm<()>>,
-  ) -> SendResult<Self::Ticket>;
-
-  fn deliver(ticket: Self::Ticket) -> Result<XcmHash, SendError>;
-}
-```
-
-Notes:
-
-It's important to validate that the message can indeed be sent before sending it.
-This ensures you pay for sending fees and you actually do send it.
-
----
-
-## Summary
-
-In this lecture, we learnt:
-
-- How chains interpret locations and turn them to accounts and FRAME origins
-- How to set a barrier to protect our chain from undesired messages
-- How to handle assets in XCM
-- Other configuration items relevant for XCM
diff --git a/content/xcm/in-use/page.md b/content/xcm/in-use/page.md
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-# XCM in Use
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/xcm/in-use/slides.md b/content/xcm/in-use/slides.md
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----
-title: XCM in Use # Also update the h1 header on the first slide to the same name
-description: Leverage HRMP to remote compound on Substrate-based DEX
-duration: 2 hours
----
-
-# XCM in Use
-
-### Build dApps with XCM leveraging polkadot.js.org/apps and node.js
-
-Notes:
-
-As we learned in Chapter 3, the XCM pallet serves as a bridge between the XCVM subsystem and the FRAME subsystem.
-It enables us to send and execute XCM and interact with the XCM executor.
-In this chapter, I, as the founder of OAK Network and a parachain developer, will demonstrate how to build products using XCM and dispatch them from both polkadot.js apps and Javascript code.
-
----
-
-### _At the end of this lecture, you will be able to:_
-
-<pba-flex center>
-
-1. Configure XCM for parachain HRMP messages.
-1. Understand the construction and execution of XCM messages.
-1. Perform HRMP transactions between parachains using templates.
-1. Develop proficiency in debugging XCM using xcm-tools.
-
-</pba-flex>
-
----
-
-# Overview
-
-<pba-flex center>
-
-1. Define the product
-1. Preparation
-1. Compose XCM message
-1. Build client code
-1. Debug live
-
-</pba-flex>
-
-Notes:
-
-In this session, I will guide you through the process of building a real use case of XCM, specifically from the perspective of a parachain developer.
-Our main focus will be on developing for a parachain, not a relay chain like Polkadot.
-Consequently, we will primarily concentrate on HRMP messages, enabling horizontal communication between two parachains.
-
-1. Define Your Product: We'll start by defining the product or application we want to build, clarifying its objectives and functionalities.
-1. Prepare Chain Config: Next, we'll prepare the necessary chain configurations, ensuring that our application is well-integrated with the target blockchain environment.
-1. Compose XCM Message: We'll dive into composing XCM messages, which are crucial for communication and interactions between different components of our application.
-1. Build Client Code: This step will involve the actual development of the client code for our application, implementing the logic and functionality we designed earlier.
-1. Debug Live: Finally, we'll explore how to debug our application in a live environment, ensuring that it functions correctly and efficiently.
-
-By the end of this presentation, you'll have a comprehensive understanding of the XCM framework and be well-equipped to build your own applications effectively.
-
-Let's get started!
-
----
-
-# Define the product
-
-Objective: establish a seamless monthly recurring payment of MOVR on the Moonriver parachain.
-
-Notes:
-
-In this demo, our main objective is to establish a seamless monthly recurring payment of MOVR on the Moonriver parachain.
-To accomplish this, we will utilize a powerful extrinsic call, `automationTime.scheduleXcmpTask`, executed remotely on the Turing Network.
-This will trigger a payment at the end of each month, ensuring a smooth and automated payment process.
-
----v
-
-## What we need to do
-
-We need to perform one essential operation, which is to remotely execute automationTime.scheduleXcmpTask on the Turing Network.
-
-To execute this operation, we will interact with the following components:
-
-- Source Chain: Moonriver
-- Source XCM Version: V3
-- Source Extrinsic: `xcmTransactor.transactThroughSigned`
-
-<br />Consequently, it will initiate the remote execution of the following call:
-
-- Target Chain: Turing Network
-- Target XCM Version: V3
-- Target Extrinsic: `automationTime.scheduleXcmpTask`
-
----v
-
-Upon successful XCM execution, a TaskScheduled event will fire on the Turing Network, indicating that the remote call has been executed successfully, thereby creating an automation task.
-
-<figure>
-  <img rounded style="width: 900px;" src="./img/high-level-product-flow.jpg" />
-  <figcaption>High-level product flow between Moonriver and Turing Network</figcaption>
-</figure>
-
-Notes:
-
-explanation - The XCM call sets up a recurring task, that will auto-transfer of MOVR at the end of every month.
-Turing Network is responsible for triggering the action when its condition is met.
-The overall flow of the entire product is shown in the diagram below.
-
----
-
-# Preparation
-
-To kickstart our journey, we will begin by interacting with Moonriver's `xcmTransactor` pallet, which is similar to Polkadot/Kusama's `xcmPallet`.
-Before diving into the actual XCM message, it is essential to ensure that we meet certain prerequisites:
-
-Notes:
-
-For this demo, we are using the existing xcmPallet built in Polkadot and Kusama.
-This pallet provides common extrinsic interfaces that developers can use to easily compose an XCM message.
-Moonriver has further encapsulated the function to make their own xcmTransactor.
-
----v
-
-1. Ensure Barriers on the recipient chain.<br />
-   In this case, an Allow Barrier\*\* `WithComputedOrigin<Everything>`, needs to be configured in the XCM config of Turing Network.
-   This Barrier will allow the DescendOrigin instruction in XCM, which will reassign the origination of the transaction on Turing from Moonriver's sovereign account to the user's proxy account.
-1. Configure user’s remote wallet on the recipient chainThe remote wallet, or proxy wallet acts as an account abstraction, allowing the blockchain to execute specific code on behalf of the user.
-
-Notes:
-
-1. We covered the Barrier topic in the previous chapter.
-   Barriers are responsible for creating Allow or Deny rules for incoming messages.
-   By adding this Barrier, we allow the DescendOrigin instruction in XCM, which will reassign the origination of the transaction on Turing from Moonriver's sovereign account to the user's proxy account.
-1. This remote wallet acts as an account abstraction, empowering the blockchain to execute specific code on behalf of the user.
-   By utilizing a user's sub-wallet for a specific extrinsic call, we create granular control, allowing the user's wallet to perform the necessary actions efficiently and securely.
-
----
-
-# Compose XCM message
-
-In this section, we will initiate the execution by calling the `xcmTransactor.transactThroughSigned` extrinsic on Moonriver.
-
-Notes:
-
-This extrinsic serves as the gateway to composing the XCM message, incorporating all the necessary instructions for the desired cross-chain message.
-
----v
-
-## XCM configs
-
-The following are the parameters you need to decide before sending an XCM message:<br /><br />
-
-1. **Version number**: Check the XCM version on both recipient (Turing Network) and source (Moonriver) chains.
-   Ensure their XCM versions are compatible.
-1. **Weight**: Each chain defines a different weight for XCM instructions, impacting computation, storage, and gas fees.
-1. **Fee per Second**: If using an asset other than the recipient chain's native token (TUR) to pay fees, establish the MOVR-to-TUR conversion rate.
-
-Notes:
-
-In section #4 of the Chain Config in XCM document, we have reviewed various chain configurations.
-In this section, we will illustrate their usage through our demo.
-Although there are several variables to be decided, once you become familiar with them and establish a few templates, you can continue to use them.
-
-1. For example, V3 is backward compatible with V2 but the its config requires safeXcmVersion set.
-1. The weight of an XCM instruction is defined with a different value on each chain.
-   It specifies how much computational power as well as storage (PoV size), are required for the execution of each instruction and determines the gas, or fee, for the XCM execution.
-1. In addition to the weight, if we use an asset other than the native token of the recipient chain, TUR in this case, to pay for the fee, the value of the asset must be converted in relation to the recipient chain's native token.
-   The Fee per Second defines the conversion rate between MOVR and TUR, assuming we want to use MOVR to pay for all the fees in this transaction.
-
-With these parameters decided, proceed to construct the instruction sequence for the XCM message.
-
----v
-
-## Message elements
-
-To construct the XCM message, we utilize Moonriver's `xcmTransactor.transactThroughSigned` extrinsic.
-It requires the following parameters:
-
-**Destination**: It specifies the target chain, or for our case, the Turing Network, identified by {Relay, 2114} on Kusama.
-
-<br />
-
-<figure>
-  <img rounded style="width: 900px;" src="./img/xcm-transactor-extrinsic.png" />
-  <figcaption>The parameters in the `transactThroughDerivative()` extrinsic</figcaption>
-</figure>
-
----v
-
-**InnerCall**
-
-This represents the encoded call hash of the transaction on the destination chain.
-This value will be passed on to the Transact XCM instruction.
-
-**Fees**
-
-`transactRequiredWeightAtMost` restricts the gas fee of the innerCall, preventing excessive fee token costs.
-Likewise, `overallWeight` sets an upper limit on XCM execution, including the Transact hash.
-
----v
-
-## Initiating the XCM Message
-
----v
-
-<img rounded style="width: 770px;" src="./img/xcm-send-1.png"/>
-
-Once all the parameters are set, we can proceed by submitting and signing the transaction.
-The XCM message can be conveniently triggered directly from the extrinsic tab of [polkadot.js apps](https://polkadot.js.org/apps/).
-
----v
-
-<img rounded style="width: 770px;" src="./img/xcm-send-2.png"/>
-
-`DescendOrigin(descend_location)`: The first instruction in the XCM array is DescendOrigin, transferring authority to the user's proxy account on the destination chain.
-
----v
-
-<img rounded style="width: 770px;" src="./img/xcm-send-3.png"/>
-
-`WithdrawAsset` and `BuyExecution`: These two instructions work together to deduct XCM fees from the user's proxy wallet and reserve them for execution.
-
----v
-
-<img rounded style="width: 770px;" src="./img/xcm-send-4.png"/>
-
-XCM message - Buy Execution
----v
-
-<img rounded style="width: 770px;" src="./img/xcm-send-5.png"/>
-
-`Transact(origin_type, require_weight_at_most, call)`: The Transact instruction executes the encoded innerCall on the target chain.
-We ensured that the gas cost does not exceed the specified limit by setting requireWeightAtMost during the call.
-
----v
-
-<img rounded style="width: 770px;" src="./img/xcm-send-5.png"/>
-
-<div style="font-size: 0.82em;">
-
-`RefundSurplus` and `DepositAsset`: In case there is any remaining fee token after Transact execution, these instructions ensure that they are refunded and transferred to the specified location, typically the user's wallet.
-
-After successfully firing the message, XCM events from both the sender and recipient parachains should appear in the Polkadot.js app Network tab.
-
-</div>
-
----v
-
-## Inspection of the message
-
-Once the transaction above is submitted and finalized on the chain, we can use the xcm-tools built by the Moonbeam team to inspect the XCM message.
-The code and scripts for the tool are listed in [this Github repo](https://github.com/Moonsong-Labs/xcm-tools).
-An example of the script is shown below:
-
-`yarn xcm-decode-para --w wss://wss.api.moonbeam.network --b 1649282 --channel hrmp --p 2000`
-
----v
-
-<pba-flex center>
-
-The output of the script reflects the sequence of instructions we constructed for the XCM message earlier.
-
-1. `DescendOrigin`
-1. `WithdrawAsset`
-1. `BuyExecution`
-1. `Transact`
-1. `RefundSurplus`
-1. `DepositAsset`
-
-</pba-flex>
-
----
-
-# Client code (node.js)
-
-After proving that the XCM message above executes correctly, we can replicate the procedure from the client of a dApp.
-Below is a node.js code snippet we created for this particular demo.
-
-👉 [xcm-demo Github Repo](https://github.com/OAK-Foundation/xcm-demo/blob/master/src/moonbeam/moonbase-alpha.js) 👈
-
-To run the program, clone it using git and execute the following command:
-
-```sh
-PASS_PHRASE=<PASS_PHRASE> PASS_PHRASE_ETH=<PASS_PHRASE_ETH> npm run moonbase-alpha
-```
-
----v
-
-### Example
-
-<div style="font-size: 0.7em;">
-
-```text
-const tx = parachainHelper.api.tx.xcmTransactor.transactThroughSigned(
-        {
-            V3: {
-                parents: 1,
-                interior: {
-                    X1: { Parachain: 2114 },
-                },
-            },
-        },
-        {
-            currency: {
-                AsCurrencyId: 'SelfReserve',
-            },
-            feeAmount: fungible,
-        },
-        encodedTaskViaProxy,
-        {
-            transactRequiredWeightAtMost: {
-                refTime: transactRequiredWeightAtMost,
-                proofSize: 0,
-            },
-            overallWeight: {
-                refTime: overallWeight,
-                proofSize: 0,
-            },
-        },
-    );
-```
-
-</div>
-
-Notes:
-
-As you can see from the code, there are several preparation steps leading up to the main code block, which constructs the XCM message.
-With the help of the following code, we can easily dispatch the message repeatedly and test out different input values.
-
----
-
-## Debugging Live
-
-When working with XCM messages, potential issues can arise in two areas: during message construction and during transaction execution on the target chain.
-
----v
-
-**Message Formatting Issues**: If the XCM message is malformed, the recipient chain may not process it correctly.
-To interpret XCM messages on-chain, we can use the xcm-tool covered in Chapter 5.
-Some common problems and solutions include:
-
-- Incorrect Fee and Weight Inputs: Ensure that the maximum weight specified in the XCM call is accurate.
-  If the actual weight slightly exceeds the limit, the recipient chain might deny the call.
-  In this case, increase the maximum weight parameter and retry.
-- Version Mismatch: A VersionMismatch error occurs when the recipient chain does not accept the Multi-location version specified in Destination or FeeAsset.
-  Check the recipient XCM version and adjust the multi-location version to V2 or V3 accordingly.
-
----v
-
-**Transact Encoded Call Issues**: To examine encoded call hash in the Transact instruction, locate the specific transaction on the recipient chain, which will be an event occurring after `XcmMessageQueue.success`.
-Unfortunately, there is no automated tool to directly correlate `XcmMessageQueue.success` with the event of the encoded call.
-However, we can manually analyze it by matching the message hash with the source chain.
-
-Notes:
-
-does anybody have a great tool to correlate the XcmMessageQueue.success with the Transact hash?
-
----
-
-## Summary
-
-In this section, we explained the backbone of a recurring payment dApp leveraging XCM.
-
----v
-
-### Lesson Recap
-
-To create a successful XCM message between chains, ensure you have the following elements prepared:
-
-- Type: Identify whether it's VRP (Vertical Relay Process) or HRMP (Horizontal Relay Process), representing the two parties involved in the communication.
-
-- Goal: Determine the specific extrinsic to call or what actions will be included in the transaction.
-
-- Details: Adjust the chain configurations as needed.
-  Decide on DescendOrigin, choosing between descending to the user's remote wallet or using a parachain’s sovereign account.
-  Also, specify the Sequence, outlining the instructions to be included in the message.
-
----v
-
-After preparing these elements, assemble them to form the XCM message and carefully troubleshoot it.
-Once you establish a reliable template, consider automating the construction process using the polkadot.js JavaScript library.
-
-Alternatively, you can write a wrapper in the parachain's Rust code, such as the commonly used `xTokens.transferMultiasset` or Moonriver’s `xcmTransactor.transactThroughSigned`.
-
----
-
-<!-- .slide: data-background-color="#4A2439" -->
-
-# Questions
diff --git a/content/xcm/index.md b/content/xcm/index.md
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-# 💱 XCM
-
-The cross consensus messaging format covered from first principals to use in protocols.
diff --git a/content/xcm/intro/page.md b/content/xcm/intro/page.md
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-# Introduction to Cross Consensus Messaging (XCM)
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/xcm/intro/slides.md b/content/xcm/intro/slides.md
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----
-title: Introduction to Cross Consensus Messaging (XCM)
-description: XCM Core Concepts, Terms, and Logic for web3 builders
-duration: 1 hour
----
-
-# Introduction to Cross-Consensus Messaging (XCM)
-
-## _Core Concepts, Terms, and Logic_
-
-Notes:
-
-**Pre-requisites**
-
-- FRAME (Storage Items, Dispatchables, Event, Errors, etc.)
-- Polkadot & parachains conceptually
-- Assets (NFTs and fungibles)
-
----v
-
-## _At the end of this lecture, you will be able to:_
-
-<pba-flex center>
-
-- Define the concepts, syntax, and terms of XCM
-- Navigate existing resources that relate to XCM
-- Differentiate between XCM and message-passing protocols like XCMP
-
----
-
-# Cross-chain use cases
-
-Why would we want to perform operations on different blockchains?
-
-Notes:
-
-EXERCISE: ask the class to raise hands and postulate on generally what one might do.
-We are expecting them to say transfers, but there are so many other things you could do, so many more problems worth solving with cross-chain:
-
-- One contract calling another contract
-- Credential checking
-- Voting
-
----v
-
-## 🎬 Some Concrete Use-cases
-
-<pba-flex center>
-
-- Cross-consensus asset transfers
-- Execute platform-specific actions such as governance voting
-- Enables single use-case chains
-  - [Collectives](https://github.com/paritytech/polkadot-sdk/tree/72c4535/cumulus/parachains/runtimes/collectives)
-  - Identity chains
-
-Notes:
-
-While the goal of XCM is to be general, flexible and future-proof, there are of course practical needs which it must address, not least the transfer of tokens between chains.
-We need a way to reason about, and pay for, any required fees on the receiving CS.
-Platform-specific action; for example, within a Substrate chain, it can be desirable to dispatch a remote call into one of its pallets to access a niche feature.
-XCM enables a single chain to direct the actions of many other chains, which hides the complexity of multi-chain messaging behind an understandable and declarative API.
-
----
-
-> XCM is a **language** for communicating **intentions** between **consensus systems**.
-
----v
-
-### Consensus systems
-
-A chain, contract or other global, encapsulated, state machine singleton.
-
-<pba-flex center>
-
-It does not even have to be a _distributed_ system, only that it can form _some_ kind of consensus.
-
-Notes:
-
-A consensus system does not necessarily have to be a blockchain or a smart contract.
-It can be something that already exists in the Web 2.0 world, such as an EC2 instance in an AWS server.
-XCM is Cross-Consensus since it's much more than cross chain.
-
----v
-
-### ✉️ A Format, not a Protocol
-
-XCM is a **_messaging format_**.
-
-It is akin to the post card from the post office.
-
-It is _not_ a messaging protocol!
-
-A post card doesn't send itself!
-
-Notes:
-
-It cannot be used to actually "send" any message between systems; its utility is only in expressing what should be done by the receiver.
-Like many aspects core to Substrate, this separation of concerns empowers us to be far more generic and enable much more.
-A post card relies on the postal service to get itself sent towards its receivers, and that is what a messaging protocol does.
-
-The transport layer concerns itself with sending arbitrary blobs, it doesn't care about the format.
-A common format has its benefits though, as we'll see next.
-
----v
-
-### Versioning
-
-XCM is a **versioned** language.
-
-It's currently in version 3.
-
-What goes in each version is defined via an RFC process.
-
----v
-
-### Terminology: XCMs
-
-**XCM**, Cross-Consensus Messaging, is the format.
-
-**An XCM** is a Cross-Consensus Message.
-
-It's not called an XCM message,
-
-the same way it's not called an ATM machine.
-
----
-
-## 😬 Why not _native_ messages?
-
-Drawbacks of relying on native messaging or transaction format:
-
-<pba-flex center>
-
-- Native message format changes from system to system, it also could change within the _same_ system, e.g. when upgrading it
-- Common cross-consensus use-cases do not map one-to-one to a single transaction
-- Different consensus systems have different assumptions e.g. fee payment
-
-Notes:
-
-- A system which intends to send messages to more than one destination would need to understand how to author a message for each.
-  On that note, even a single destination may alter its native transaction/message format over time.
-  Smart contracts might get upgrades, blockchains might introduce new features or alter existing ones and in doing so change their transaction format.
-- Special tricks may be required to withdraw funds, exchange them and then deposit the result all inside a single transaction.
-  Onward notifications of transfers, needed for a coherent reserve-asset framework, do not exist in chains unaware of others.
-  Some use-cases don't require accounts.
-- Some systems assume that fee payment had already been negotiated, while some do not.
-  <!--
-  FIXME TODO: Why not just send EVM programs. Why XCVM instead of EVM?
-  Add Shawn's picture.
-  -->
-  It's up to the interpreter to interpret the intention how it makes sense.
-
----v
-
-### Message format changes
-
-<img style="width: 1050px;" src="./img/against-native-messaging.svg" />
-
----v
-
-### Message format changes
-
-<img style="width: 1050px;" src="./img/against-native-messaging-2.svg" />
-
----v
-
-### Message format changes
-
-<img rounded style="width: 1050px" src="./img/xcm-executor-routing-calls.png" />
-
-Notes:
-
-XCM abstracts away the actual on-chain operation that will be called, which lets the recipient redirect calls to always make them valid.
-
----v
-
-### No one-to-one mapping
-
-<diagram class="mermaid limit size-50">
-graph TD
-    subgraph Message
-        WithdrawAsset(WithdrawAsset)-->DepositAlice("DepositAsset(Alice)")
-        DepositAlice-->DepositBob("DepositAsset(Bob)")
-    end
-</diagram>
-
-Notes:
-
-You might want to withdraw some assets and deposit some amount to one account and another to another.
-Using transactions, you'd have to send many messages to achieve this.
-
----v
-
-### Different assumptions
-
-<diagram class="mermaid">
-graph LR
-    A(Chain A)--"Pays for fees"-->B(Chain B)
-    A--"Doesn't pay for fees"-->C(Chain C)
-</diagram>
-
-Notes:
-
-Different systems have different assumptions.
-Using native messages, you'd have to tailor your messages to all systems you want to message.
-
----
-
-## Four 'A's
-
-XCM assumes the following things from the underlying environment.
-
-<pba-flex center>
-
-- **Agnostic**
-- **Absolute**
-- **Asynchronous**
-- **Asymmetric**
-
-Notes:
-
-The 4 'A's are assumptions XCM makes over the transport protocol and overall the environment where these messages are sent and processed.
-
----v
-
-## Agnostic
-
-XCM makes no assumptions about the nature of the Consensus System between which messages are being passed.
-
-Notes:
-
-XCM is not restricted to Polkadot, it's a language that can be used for communication between any systems.
-For example, EVM-chains or Cosmos hubs.
-
----v
-
-## Absolute
-
-XCM assumes that the environment guarantees delivery, interpretation, and ordering of messages.
-
-Notes:
-
-The message format does not do much about the message possibly not being delivered.
-In IBC, for example, you factor in fallibility of the transport protocol into your messages.
-
----v
-
-## Asynchronous
-
-XCMs crossing the barrier between a single consensus system cannot generally be synchronous.
-
-XCM in no way assume that the sender will be blocking on messages.
-
-Notes:
-
-You can't just block execution in the middle of a block, it has to be asynchronous.
-Different systems have different ways of tracking time.
-No assumption of blocking for sender/receiver.
-
-Generally, consensus systems are not designed to operate in sync with external systems.
-They intrinsically need to have a uniform state to reason about and do not, by default, have the means to verify states of other consensus systems.
-Thus, each consensus system cannot make any guarantees on the expected time required to deliver results; doing so haphazardly would cause the recipient to be blocked waiting for responses that are either late or would never be delivered, and one of the possible reasons for that would be an impending runtime upgrade that caused a change in how responses are delivered.
-
----v
-
-## Asymmetric
-
-XCM doesn't assume there'll be messages flowing in the other direction.
-
-If you want to send responses, you have to make it explicitly.
-
-Notes:
-
-There are no results or callbacks.
-Any results must be separately communicated to the sender with an additional message.
-The receiver side can and does handle errors, but the sender will not be notified, unless the error handler specifically tries to send back an XCM that makes some sort of XCM that notifies status back to the origin, but such an action should be considered as constructing a separate XCM for the sole purpose of reporting information, rather than an intrinsic functionality built into XCM.
-XCM is a bit like REST.
-XCMP is a bit like TCP/IP but not quite.
-Analogies can often hurt more than they help.
-
----
-
-## 📍 Locations in XCM
-
-<pba-flex center>
-
-Before sending a message to another system, we need a way to address it.
-
-<diagram class="mermaid">
-graph LR
-    Message(Message)
-    Alice(Alice)--"?"-->Bob(Bob)
-    Alice--"?"-->AssetHub(Asset Hub)
-    Alice--"?"-->Pallet(Pallet)
-    Alice--"?"-->SmartContract(Smart Contract)
-</diagram>
-
-Notes:
-
-XCM defines a `Location` type that acts as a URL for consensus systems.
-
-The `Location` type identifies any single _location_ that exists within the world of consensus.
-Representing a scalable multi-shard blockchain such as Polkadot, an ERC-20 asset account on a parachain, a smart contract on some chain, etc.
-It is usually represented as a location _relative_ to the current consensus system.
-Relative locations are easier to handle due to the fact that the network structure can change.
-
-Locations don't define the actual path to get there, just a way of addressing.
-
----v
-
-## Interior locations
-
-> Given two consensus systems, A and B. A is **interior** to B if a state change in A implies a state change in B.
-
-Notes:
-
-An example, a smart contract in Ethereum would be interior to Ethereum itself.
-
----v
-
-## Location hierarchy
-
-<diagram class="mermaid">
-graph TD;
-    Relay(Relay)-->A(Parachain A)
-    Relay-->B(Parachain B)
-    B-->Alice(Account A)
-    B-->Bob(Account B)
-    A-->Pallet(Pallet Contracts)
-    Pallet-->SCA(Smart Contract A)
-    Pallet-->SCB(Smart Contract B)
-</diagram>
-
-Notes:
-
-Locations form a hierarchy using the interior relation.
-
----v
-
-## Location Representation
-
-<pba-flex center>
-
-```rust
-struct Location {
-    parents: u8,
-    junctions: Junctions,
-}
-```
-
-<div style="margin-bottom: 2rem;"></div>
-
-```rust
-enum Junction {
-    Parachain(u32),
-    AccountId32 { id: [u8; 32], network: Option<NetworkId> },
-    PalletInstance(u8),
-    GeneralIndex(u128),
-    GlobalConsensus(NetworkId),
-    ...
-}
-```
-
-Notes:
-
-Right now Junctions are limited to 8 because of stack space.
-We also don't expect Junctions being more than 8 levels deep.
-
-It's perfectly possible to create locations that don't point anywhere.
-
----v
-
-### Network Id
-
-<pba-flex center>
-
-```rust
-enum NetworkId {
-    ByGenesis([u8; 32]),
-    ByFork { block_number: u64, block_hash: [u8; 32] },
-    Polkadot,
-    Kusama,
-    Westend,
-    Rococo,
-    Wococo,
-    Ethereum { chain_id: u64 },
-    BitcoinCore,
-    BitcoinCash,
-}
-```
-
-</pba-col>
-
-</pba-cols>
-
-Notes:
-
-Junctions are ways to descend the location hierarchy
-
----v
-
-## Text notation
-
-<pba-flex center>
-
-<pba-cols>
-
-<pba-col>
-
-```rust
-Location {
-    parents: 1,
-    interior: Parachain(50)
-}
-```
-
-</pba-col>
-<pba-col>
-
--->
-
-</pba-col>
-<pba-col>
-
-`../Parachain(50)`
-
-</pba-col>
-
-Notes:
-
-This notation comes from an analogy to a file system.
-
----v
-
-## Universal Location
-
-> The Universal Location is a **theoretical** location. It's the parent of all locations which generate their own consensus. It itself has no parents.
-
----v
-
-## Universal Location
-
-<diagram class="mermaid limit size-50">
-graph TD;
-    UniversalLocation(Universal Location)-->Polkadot(Polkadot)
-    UniversalLocation-->Kusama(Kusama)
-    UniversalLocation-->Ethereum(Ethereum)
-    UniversalLocation-->Bitcoin(Bitcoin)
-</diagram>
-
-Notes:
-
-We can imagine a hypothetical location that contains all top-level consensus systems.
-
----v
-
-## Absolute locations
-
-<pba-flex center>
-
-```rust
-pub type InteriorLocation = Junctions;
-```
-
-Sometimes, absolute locations are necessary, e.g. for bridges.
-
-They don't have parents.
-
-The first junction has to be a `GlobalConsensus`.
-
-Notes:
-
-To write an absolute location, we need to know our location relative to the Universal Location.
-
----v
-
-## What are `Location`s used for?
-
-<pba-flex center>
-
-- Addressing
-- Origins
-- Assets
-- Fees
-- Bridging
-
----v
-
-## Cross-Chain Origins
-
-When a receiver gets an XCM, a `Location` specifies the sender.
-
-This `Location` is _relative_ to the receiver.
-
-Can be converted into a pallet origin in a FRAME runtime
-
-Used for determining privileges during XCM execution.
-
-Notes:
-
-Reanchoring:
-
-Since `Location`s are relative, when an XCM gets sent over to another chain, the origin location needs to be rewritten from the perspective of the receiver, before the XCM is sent to it.
-
----
-
-## Location Examples
-
----v
-
-### Sibling parachain
-
-`../Parachain(1001)`
-
-<diagram class="mermaid">
-graph TD
-    Polkadot(Polkadot)-->AssetHub("📍 AssetHub (1000)")
-    Polkadot-->Collectives("Collectives (1001)")
-</diagram>
-
-Notes:
-
-What does the location resolve to if evaluated on Parachain(1000)?
-
----v
-
-### Sibling parachain
-
-`../Parachain(1001)`
-
-<diagram class="mermaid">
-graph TD
-    Polkadot(Polkadot)-->AssetHub("📍 AssetHub (1000)")
-    Polkadot-->Collectives("Collectives (1001)")
-    AssetHub-->Polkadot
-    linkStyle 0 opacity:0.3
-    linkStyle 2 stroke-dasharray:5
-</diagram>
-
----v
-
-### Parachain account
-
-`Parachain(1000)/AccountId32(0x1234...cdef)`
-
-<diagram class="mermaid">
-graph TD
-    Polkadot("📍 Polkadot")-->AssetHub("AssetHub (1000)")
-    Polkadot-->Collectives("Collectives (1001)")
-    AssetHub-->Account("AccountId32 (0x1234...cdef)")
-</diagram>
-
-Notes:
-
-What does the location resolve to if evaluated on the relay chain?
-
----v
-
-### Parachain account
-
-`Parachain(1000)/AccountId32(0x1234...cdef)`
-
-<diagram class="mermaid">
-graph TD
-    Polkadot("📍 Polkadot")-->AssetHub("AssetHub (1000)")
-    Polkadot-->Collectives("Collectives (1001)"):::disabled
-    AssetHub-->Account("AccountId32 (0x1234...cdef)")
-    linkStyle 1 opacity:0.3
-    classDef disabled opacity:0.3
-</diagram>
-
----v
-
-### Bridge
-
-`../../GlobalConsensus(Kusama)/Parachain(1000)`
-
-<diagram class="mermaid">
-graph TD
-    Universe(Universal Location)-->Polkadot(Polkadot)
-    Universe-->Kusama(Kusama)
-    Polkadot-->PolkaA("📍 Asset Hub (1000)")
-    Polkadot-->PolkaB(Bridge Hub)
-    PolkaA-->Alice(Alice)
-    PolkaA-->AssetsPallet(Pallet Assets)
-    AssetsPallet-->Asset(USDT)
-    Kusama-->KusamaA("Asset Hub (1000)")
-    Kusama-->KusamaB(Bridge Hub)
-</diagram>
-
-Notes:
-
-Speak to an example of non-parachain multi-location that would use a bridge
-XCM reasons about addressing (as in a postal address) that must include understanding where you are, not just where you are going!
-This will be very powerful later on (Origins)
-
----v
-
-### Bridge
-
-`../../GlobalConsensus(Kusama)/Parachain(1000)`
-
-<diagram class="mermaid">
-graph TD
-    Universe(Universal Location)-->Polkadot(Polkadot)
-    Universe-->Kusama(Kusama)
-    Polkadot-->PolkaA("📍 Asset Hub (1000)")
-    Polkadot-->PolkaB(Bridge Hub):::disabled
-    PolkaA-->Alice(Alice):::disabled
-    PolkaA-->AssetsPallet(Pallet Assets):::disabled
-    AssetsPallet-->Asset(USDT):::disabled
-    Kusama-->KusamA("Asset Hub (1000)")
-    Kusama-->KusamB(Bridge Hub):::disabled
-    PolkaA-->Polkadot
-    Polkadot-->Universe
-    linkStyle 0 opacity:0.3
-    linkStyle 2 opacity:0.3
-    linkStyle 3 opacity:0.3
-    linkStyle 4 opacity:0.3
-    linkStyle 5 opacity:0.3
-    linkStyle 6 opacity:0.3
-    linkStyle 8 opacity:0.3
-    linkStyle 9 stroke-dasharray:5
-    linkStyle 10 stroke-dasharray:5
-    classDef disabled opacity:0.3
-</diagram>
-
-Notes:
-
-Even with Bridge Hubs, the relative location is what you'd expect.
-Bridge Hubs are just a way for routing messages.
-They are an implementation detail of the transport layer.
-
----v
-
-### Bridge (actual routing)
-
-<diagram class="mermaid">
-graph TD
-    Universe(Universal Location):::disabled-->Polkadot(Polkadot):::disabled
-    Universe-->Kusama(Kusama)
-    Polkadot-->PolkaA("📍 Asset Hub (1000)")
-    Polkadot-->PolkaB(Bridge Hub)
-    PolkaA-->Alice(Alice):::disabled
-    PolkaA-->AssetsPallet(Pallet Assets):::disabled
-    AssetsPallet-->Asset(USDT):::disabled
-    Kusama-->KusamB(Bridge Hub)
-    Kusama-->KusamA("Asset Hub (1000)")
-    PolkaA-->PolkaB
-    PolkaB--"Bridge"-->KusamB
-    KusamB-->Kusama
-    linkStyle 0 opacity:0.3
-    linkStyle 1 opacity:0.3
-    linkStyle 2 opacity:0.3
-    linkStyle 3 opacity:0.3
-    linkStyle 4 opacity:0.3
-    linkStyle 5 opacity:0.3
-    linkStyle 6 opacity:0.3
-    linkStyle 7 opacity:0.3
-    linkStyle 11 stroke-dasharray:5
-    classDef disabled opacity:0.3
-</diagram>
-
-Notes:
-
-The actual message is routed through Bridge Hub.
-
----
-
-## Sovereign Accounts
-
-Locations external to the local system can be represented by a local account.
-
-We call this the **sovereign account** of that location.
-
-They are a mapping from a `Location` to an account id.
-
-<diagram class="mermaid">
-graph TD
-    Polkadot(Polkadot)-->A(A) & B(B)
-    A-->Alice(Alice)
-    B-->AliceSA("Alice's sovereign account")
-</diagram>
-
-Notes:
-
-A sovereign account is an account on one system that is controlled by another on a different system.
-A single account on a system can have multiple sovereign accounts on many other systems.
-In this example, Alice is an account on AssetHub, and it controls a sovereign account on Collectives.
-
-When transferring between consensus systems, the sovereign account is the one that gets the funds on the destination system.
-
----v
-
-## Sovereign Accounts again
-
-<diagram class="mermaid">
-graph TD
-    Polkadot(Polkadot)-->A(A) & B(B)
-    A-->Alice(Alice)
-    B-->AliceSA("Alice's sovereign account")
-    B-->ASA("Asset Hub's sovereign account")
-    A-->BSA("Collective's sovereign account")
-</diagram>
-
----
-
-<pba-col>
-
-## 💰 Assets in XCM
-
-Most messages will deal with assets in some way.
-
-How do we address these assets?
-
----v
-
-### Asset Representation
-
-```rust
-struct Asset {
-    pub id: AssetId,
-    pub fun: Fungibility,
-}
-
-struct AssetId(Location); // <- We reuse the location!
-
-enum Fungibility {
-    Fungible(u128),
-    NonFungible(AssetInstance),
-}
-```
-
-Notes:
-
-We use locations, which we've already discussed, to refer to assets.
-
-A Asset is composed of an asset ID and an enum representing the fungibility of the asset.
-Asset IDs are the location that leads to the system that issues it, this can be just an index in an assets pallet, for example.
-
-Assets can also either be fungible or non-fungible:
-Fungible - each token of this asset has the same value as any other
-NonFungible - each token of this asset is unique and cannot be seen as having the same value as any other token under this asset
-
----v
-
-### Asset filtering and wildcards
-
-```rust
-enum AssetFilter {
-    Definite(Assets),
-    Wild(WildAsset),
-}
-
-enum WildAsset {
-    All,
-    AllOf { id: AssetId, fun: WildFungibility },
-    // Counted variants
-}
-
-enum WildFungibility {
-    Fungible,
-    NonFungible,
-}
-```
-
-Notes:
-
-Sometimes we don't want to specify an asset, but rather filter a collection of them.
-In this case, we can either list all the assets we want or use a wildcard to select all of them.
-In reality, it's better to use the counted variant of the wildcards, for benchmarking.
-
----
-
-## Reanchoring
-
-How do different locations reference the same asset?
-
-<diagram class="mermaid limit size-70">
-graph TD
-    Polkadot(Polkadot)-->AssetHub("Asset Hub (1000)")
-    Polkadot-->BridgeHub("Bridge Hub (1002)")
-    AssetHub-->Alice(Alice)
-    AssetHub-->AssetsPallet(Pallet Assets)
-    AssetsPallet-->Asset(USDT)
-</diagram>
-
-Notes:
-
-Locations are relative, so they must be updated and rewritten when sent to another chain, for them to be interpreted correctly.
-
-<!-- FIXME TODO: Move elsewhere. -->
-
-Native tokens are referenced by the location to their system.
-
----v
-
-### USDT from Asset Hub
-
-`PalletInstance(50)/GeneralIndex(1984)`
-
-<diagram class="mermaid limit size-70">
-graph TD
-    Polkadot(Polkadot):::disabled-->AssetHub("📍 Asset Hub (1000)")
-    Polkadot-->BridgeHub("Bridge Hub (1002)"):::disabled
-    AssetHub-->Alice(Alice):::disabled
-    AssetHub-->AssetsPallet(Pallet Assets)
-    AssetsPallet-->Asset(USDT)
-    linkStyle 0 opacity:0.3
-    linkStyle 1 opacity:0.3
-    linkStyle 2 opacity:0.3
-    classDef disabled opacity:0.3
-</diagram>
-
----v
-
-### USDT from Bridge Hub
-
-`../Parachain(1000)/PalletInstance(50)/GeneralIndex(1984)`
-
-<diagram class="mermaid limit size-70">
-graph TD
-    Polkadot(Polkadot)-->AssetHub("Asset Hub (1000)")
-    Polkadot-->BridgeHub("📍 Bridge Hub (1002)")
-    AssetHub-->Alice(Alice):::disabled
-    AssetHub-->AssetsPallet(Pallet Assets)
-    AssetsPallet-->Asset(USDT)
-    BridgeHub-->Polkadot
-    linkStyle 1 opacity:0.3
-    linkStyle 2 opacity:0.3
-    linkStyle 5 stroke-dasharray:5
-    classDef disabled opacity:0.3
-</diagram>
-
----v
-
-### Reanchoring to the rescue
-
-<diagram class="mermaid">
-graph LR
-    subgraph OutgoingMessage[Outgoing message from Bridge Hub]
-        USDTBridgeHub(USDT from Bridge Hub's perspective)
-    end
-    USDTBridgeHub--Reanchoring-->USDTAssetHub
-    subgraph IncomingMessage[Incoming message in Asset Hub]
-        USDTAssetHub(USDT from Asset Hub's perspective)
-    end
-</diagram>
-
----
-
-## 🤹 Cross-consensus transfers
-
-Notes:
-
-The two ways of transferring assets between consensus systems are teleports and reserve transfers.
-
----v
-
-### 1. Asset teleportation
-
-<img rounded style="width: 500px;" src="./img/teleport.png" />
-
-Notes:
-
-Teleportation works by burning the assets on the source chain and minting them on the destination chain.
-This method is the simplest one, but requires a lot of trust, since failure to burn or mint on either side will affect the total issuance.
-
----v
-
-### 1.1. Example: System parachains?
-
-<diagram class="mermaid">
-graph LR
-    BridgeHub(Bridge Hub)--"Trust"-->AssetHub(Asset Hub)
-</diagram>
-
----v
-
-### 1.2. Example: Polkadot and Kusama?
-
-<diagram class="mermaid">
-graph LR
-    Polkadot(Polkadot)--"No trust"-->Kusama(Kusama)
-</diagram>
-
----v
-
-### 2. Reserve asset transfers
-
-<img rounded style="width: 400px;" src="./img/reserve-tx.png" />
-
-Notes:
-
-Reserve asset transfers are more complicated, since they bring in a third actor called the reserve chain.
-Chain A and B needn't trust each other, they only need to trust the reserve chain.
-The reserve chain holds the real assets, A and B deal only with derivatives.
-The transfer is made by burning derivatives from A, moving them from A's SA to B's SA in R, then minting on B.
-
-In some cases, the sender, A, can also be the reserve for a particular asset, in which case the process is simplified, there's no burning of derivatives.
-This usually happens with parachains' native tokens.
-
-You always trust the issuer of the token to not mint infinite tokens.
-
----v
-
-### 2.1. Example: Parachain native tokens
-
-<diagram class="mermaid">
-graph LR
-    subgraph A [A = R]
-        Sender(Sender account)--"Move X real asset"-->BSovereignAccount(B's Sovereign Account)
-    end
-    A--"Mint X derivatives"-->B(B)
-</diagram>
-
-Notes:
-
-Most parachains act as the reserve for their own token.
-To transfer their token to other chains, they move the real assets to a sovereign account and then tell the chain to mint equivalent derivatives.
-
----v
-
-### 2.2. Example: Polkadot to Kusama
-
-<diagram class="mermaid">
-graph LR
-    Polkadot(Polkadot)-->AssetHubP
-    subgraph AssetHubP [Asset Hub Polkadot]
-        Sender(Sender account)--"Move X real DOT"-->KusamaSovereignAccount("Kusama's sovereign account")
-    end
-    AssetHubP--"Mint X DOT derivatives"-->Kusama(Kusama)
-</diagram>
-
-Notes:
-
-AssetHub Kusama acts as the reserve for KSM.
-Kusama doesn't trust Polkadot to teleport KSM to it, but it does trust its own reserve, the AssetHub.
-Polkadot has a sovereign account in Kusama's AssetHub with some amount of KSM.
-Whenever some user in Polkadot wants to get KSM on Kusama, they just give the DOT to Polkadot and the KSM are moved from one sovereign account to another.
-No new trust relationships are added.
-
----
-
-## Summary
-
-- XCM
-- XCM vs XCMP
-- Locations
-- Sovereign Accounts
-- Assets
-- Reanchoring
-- Cross-consensus transfers
-  - Teleports
-  - Reserve asset transfers
-
----v
-
-## Next steps
-
-<pba-flex center>
-
-1. Blog series introducing XCM: Parts [1](https://medium.com/polkadot-network/xcm-the-cross-consensus-message-format-3b77b1373392), [2](https://medium.com/polkadot-network/xcm-part-ii-versioning-and-compatibility-b313fc257b83), and [3](https://medium.com/polkadot-network/xcm-part-iii-execution-and-error-management-ceb8155dd166).
-2. XCM Format [repository](https://github.com/paritytech/xcm-format)
-3. XCM [Docs](https://paritytech.github.io/xcm-docs/)
-
----v
-
-<figure>
-    <img rounded style="width: 50%;" src="./img/subscan-xcm-dashboard.png" />
-    <figcaption>Source: <a href="https://polkadot.subscan.io/xcm_dashboard">Subscan</a></figcaption>
-</figure>
diff --git a/content/xcm/pallet/page.md b/content/xcm/pallet/page.md
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-# XCM Pallet
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/xcm/pallet/slides.md b/content/xcm/pallet/slides.md
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----
-title: XCM Pallet
-description: Introduction to `pallet-xcm`, its interface and features implemented here.
-duration: 1 hour
----
-
-# XCM Pallet
-
----
-
-#### Lesson goals:
-
-- Understand what the interface of the pallet is and its implementation.
-- How versioning discovery works.
-- How receiving responses work.
-- Understand how to craft XCM in FRAME pallets.
-
----
-
-## The XCM pallet
-
-We have now learnt about the XCVM and FRAME.
-
-The XCM pallet is the bridge between the XCVM subsystem and the FRAME subsystem.
-
-**It also allows us to send/execute XCM and interact with the XCM executor**.
-
----
-
-## How XCM is expected to be used
-
-XCM is not intended to be written by end-users.
-
-Instead, _developers_ write XCVM programs, and package them up into FRAME extrinsics.
-
-Notes:
-
-How do wallets wallet providers use XCM ?
-
-We will see examples of XCM being built in the runtime when exploring `teleport_assets` and `reserve_transfer_assets` extrinsics.
-
----
-
-### Key roles of `pallet-xcm`
-
-<pba-flex center>
-
-1. Allows to interact with the `xcm-executor` by executing xcm messages.
-   These can be filtered through the `XcmExecuteFilter`.
-1. Allows sending arbitrary messages to other chains for certain origins.
-   The origins that are allowed to send message can be filtered through `SendXcmOrigin`.
-1. Provides an easier interface to do reserve based transfers and teleports.
-   The origins capable of doing these actions can be filtered by `XcmTeleportFilter` and `XcmReserveTransferFilter`.
-1. Handles XCM version negotiation duties.
-1. Handles asset-trap/claim duties.
-1. And other state based requirements of the XCVM.
-
-</pba-flex>
-
-Notes:
-
-- Even when the XCM pallet allows any FRAME origin to send XCMs, it distinguishes root calls vs any other origin calls.
-  In the case of the latter, it appends the `DescendOrigin` instruction to make sure non-root origins cannot act on behalf of the parachain.
-
----
-
-## The XCM Pallet
-
-`pallet-xcm` provides default implementations for many traits required by `XcmConfig`.
-
-`pallet-xcm` also provides an interface containing 10 different extrinsics, which can be split into three categories:
-
-- Primitive functions to locally `execute` or `send` an XCM.
-- High-level functions for asset transfers between systems, e.g. teleportation and reserve asset transfers.
-- Extrinsics aimed exclusively at version negotiation.
-
----
-
-## `pallet-xcm` Primitive extrinsics
-
-- `execute`
-
-  Direct access to the XCM executor.
-  Executed on behalf of FRAME's signed origin.
-
-<diagram class="mermaid limit size-40">
-flowchart TD
-subgraph paraA[Parachain A              .]
-  executor --"success?"--> palletxcm
-  palletxcm("pallet-xcm") --"execute"--> executor("xcm-executor")
-end
-execute("execute(xcm)") --> palletxcm
-</diagram>
-
-Notes:
-
-It checks the origin to ensure that the configured `SendXcmOrigin` filter is not blocking the execution.
-It executes the message **locally** and returns the outcome as an event.
-
----v
-
-## `pallet-xcm` Primitive extrinsics
-
-- `send`
-
-Sends a message to the provided destination.
-
-<diagram class="mermaid" style="display: flex; width: 150%; justify-content: center; transform: translateX(-17%);">
-flowchart LR
-subgraph paraA[Parachain A]
-  palletxcma("pallet-xcm") --"deliver"--> routera("xcm-router")
-  routera --> mqueuea("message queue")
-end
-subgraph paraB[Parachain B]
-mqueueb("message queue") --> executorb("xcm-executor")
-end
-send("send(xcm)") --> palletxcma
-mqueuea --> mqueueb
-</diagram>
-
-Notes:
-
-This extrinsic is a function to send a message to a destination.
-It checks the origin, the destination and the message.
-Then it lets the `XcmRouter` handle the forwarding of the message.
-
----
-
-## `pallet-xcm` Asset Transfer extrinsics
-
-<pba-cols>
-<pba-col>
-<img rounded style="width: 400px;" src="../intro/img/teleport.png" />
-</pba-col>
-
-<pba-col>
-<img rounded style="width: 400px;" src="../intro/img/reserve-tx.png" />
-</pba-col>
-</pba-cols>
-
-Notes:
-
-We have already seen what teleports and reserve transfers mean in lesson 7.1; A quick reminder.
-
----v
-
-## `pallet-xcm` Asset Transfer extrinsics
-
-`limited_teleport_assets`
-
-This extrinsic allows the user to perform an asset teleport.
-
-<diagram class="mermaid">
-flowchart LR
-subgraph paraA[Parachain A]
-  palletxcma("pallet-xcm") --"1. execute"--> executora("xcm-executor")
-  executora --"send"--> sendera("xcm-sender")
-end
-subgraph tdestination[Trusted Destination]
-end
-lteleport("limited_teleport_assets(\n  dest,\n  beneficiary,\n  assets,\n  fee_asset_item,\n  weight_limit\n)"):::left --> palletxcma
-sendera --"2."--> tdestination
-classDef left text-align:left
-</diagram>
-
----v
-
-### `limited_teleport_assets`
-
-<ol>
-
-<li> <code>pallet-xcm</code> composes the following XCM and passes it to <code>xcm&#8209;executor</code></li>
-
-```rust
-Xcm(vec![
-  WithdrawAsset(assets),
-  SetFeesMode {jit_withdraw: true},
-  InitiateTeleport {assets: Wild(AllCounted(max_assets)), dest, xcm},
-])
-```
-
-<li>Parachain A then sends the following message to the trusted destination</li>
-
-```rust
-Xcm(vec![
-  ReceiveTeleportedAsset(assets),
-  ClearOrigin,
-  BuyExecution { fees, weight_limit },
-  DepositAsset { assets: Wild(AllCounted(max_assets)), beneficiary },
-])
-```
-
-</ol>
-
----v
-
-## `pallet-xcm` Asset Transfer extrinsics
-
-`limited_reserve_transfer_assets`
-
-Allow the user to perform a reserve-backed transfer from the reserve chain to the destination.
-
-<diagram class="mermaid" style="display: flex; width: 150%; justify-content: center; transform: translateX(-17%);">
-flowchart LR
-subgraph reserve[Reserve Chain]
-  palletxcma("pallet-xcm") --"1. execute"--> executora("xcm-executor")
-  executora --"send"--> sendera("xcm-sender")
-end
-subgraph destination[Destination]
-end
-lteleport("limited_reserve_transfer_assets(\n  dest,\n  beneficiary,\n  assets,\n  fee_asset_item,\n  weight_limit\n)"):::left --> palletxcma
-sendera --"2."--> destination
-classDef left text-align:left
-</diagram>
-
----v
-
-### `limited_reserve_transfer_assets`
-
-<ol>
-
-<li> <code>pallet-xcm</code> composes the following XCM and passes it to <code>xcm&#8209;executor</code></li>
-
-```rust
-Xcm(vec![
-  SetFeesMode { jit_withdraw: true },
-  TransferReserveAsset { assets, dest, xcm },
-])
-```
-
-<li>Reserve Chain then sends the following mesasge to the destination</li>
-
-```rust
-Xcm(vec![
-  ReserveAssetDeposited(assets),
-  ClearOrigin,
-  BuyExecution { fees, weight_limit },
-  DepositAsset { assets: Wild(AllCounted(max_assets)), beneficiary },
-])
-```
-
-</ol>
-
----
-
-## 🗣️ version negotiation with `pallet-xcm`
-
-XCM is a **versioned message format**.
-
-One version may contain more or different instructions than another, so for parties to communicate via XCM, it is important to know which version the other party is using.
-
-The version subscription mechanism allows parties to subscribe to version updates from others.
-
-<pba-flex center>
-
-```rust
-pub enum VersionedXcm {
-  V2(v2::Xcm),
-  V3(v3::Xcm),
-}
-```
-
-Notes:
-
-- V0 and V1 were removed with the addition of XCM v3.
-
----v
-
-## 🗣️ version negotiation with `pallet-xcm`
-
-But chains need to be aware of the version supported by each other.
-`SubscribeVersion` and `QueryResponse` play a key role here:
-
-<pba-flex center>
-
-```rust
-enum Instruction {
-  // --snip--
-  SubscribeVersion {
-        query_id: QueryId,
-        max_response_weight: u64,
-  },
-  QueryResponse {
-        query_id: QueryId,
-        response: Response,
-        max_weight: u64,
-  },
-  // --snip--
-}
-```
-
-Notes:
-
-- `query_id` would be identical in the `SubscribeVersion` and `QueryResponse` instructions.
-- Likewise, `max_response_weight` should also match `max_weight` in the response
-
----v
-
-## 🗣️ version negotiation with `pallet-xcm`
-
-- `ResponseHandler`: The component in charge of handling response messages from other chains.
-- `SubscriptionService`: The component in charge of handling version subscription notifications to other chains
-
-<pba-flex center>
-
-```rust
-impl Config for XcmConfig {
- // --snip--
- type ResponseHandler = PalletXcm;
- type SubscriptionService = PalletXcm;
-}
-```
-
-Notes:
-
-- `PalletXcm` keeps track of the versions of each chain when it receives a response.
-- It also keeps track of which chains it needs to notify whenever we change our version
-
----
-
-## Subscription Service
-
-Any system can be notified of when another system changes its latest supported XCM version.
-This is done via the `SubscribeVersion` and `UnsubscribeVersion` instructions.
-
-The `SubscriptionService` type defines what action to take when processing a `SubscribeVersion` instruction.
-
-Notes:
-
-`pallet-xcm` provides a default implementation of this trait.
-When receiving a `SubscribeVersion`, the chain sends back an XCM with the `QueryResponse` instruction containing its current version.
-
----
-
-## Version Negotiation
-
-The subscription service leverages any kind of exchange of XCMs between two systems to begin the process of version negotiation.
-
-Each time a system needs to send a message to a destination with an unknown supported XCM version, its location will be stored in the `VersionDiscoveryQueue`.
-This queue will then be checked in the next block and `SubscribeVersion` instructions will be sent out to those locations present in the queue.
-
-Notes:
-
-SubscribeVersion - instructs the local system to notify the sender whenever the former has its XCM version upgraded or downgraded.
-UnsubscribeVersion - if the sender was previously subscribed to XCM version change notifications for the local system, then this instruction tells the local system to stop notifying the sender on version changes.
-
----v
-
-## 🗣️ XCM Version Negotiation
-
-XCM version negotiation:
-<pba-flex center>
-
-1. Chain A sends `SubscribeVersion` to chain B.
-1. Chain B responds `QueryResponse` to chain A with the same query_id and max_weight params, and puts the XCM version in the response
-1. Chain A stores chain B's supported version on storage.
-1. The same procedure happens from chain B to chain A.
-1. Communication is established using the highest mutually supported version.
-
----v
-
-## 🗣️ XCM Version Negotiation
-
-In the following scenario Chain A is using XCM v2
-
-<diagram class="mermaid limit size-80">
-flowchart BT
-subgraph registryA[Chain A's Registry]
-  chainB("Chain B \n\n v2")
-  chainC("Chain C \n\n v3")
-  chainD("Chain D \n\n v1")
-  chainE("Chain E \n\n v3")
-end
-</diagram>
-
-<diagram class="mermaid limit size-70">
-flowchart LR
-chainARequest("Chain A") --"Chain E ? \n\n v2"--> chainERequest("Chain E")
-</diagram>
-
----
-
-## Response Handler
-
-Version negotiation is just one example among many kinds of queries one chain can make to another.
-Regardless of which kind of query was made, the response usually takes the form of a `QueryResponse` instruction.
-
----v
-
-## Response Handler
-
-We have talked about XCM being asymmetric, so why are there responses ?
-
----v
-
-## Information Reporting
-
-Every instruction used for information reporting contains `QueryResponseInfo`.
-
-<pba-flex center>
-
-```rust
-pub struct QueryResponseInfo {
-    pub destination: MultiLocation,
-    pub query_id: QueryId,
-    pub max_weight: Weight,
-}
-```
-
-Notes:
-
-All Information Reporting instructions contain a `QueryResponseInfo` struct, which contains information about the intended destination of the response, the ID of the query, and the maximum weight that the dispatchable call function can use.
-The dispatchable call function is an optional operation that XCM author can specify, and is executed upon receiving the response, effectively acting as a lifecycle hook on response.
-
----v
-
-## Information retrieval
-
-<pba-flex center>
-
-```rust
-enum Instruction {
-    // --snip--
-    QueryResponse {
-        query_id: QueryId,
-        response: Response,
-        max_weight: Weight,
-        querier: Option<MultiLocation>,
-    },
-    // --snip--
-}
-```
-
-Notes:
-
-The above instruction is the one used for offering some requested information that the local system is expecting.
-`querier` parameter should be checked to ensure that the system that requested the information matches with what is expected.
-
----
-
-## Asset Trap/Claims with `pallet-xcm`
-
-What happens when there are still funds in the holding register after the execution of every instruction is done?
-
-Any situation in which the holding register contains assets after the execution of the XCM message would lead to asset trapping.
-
-These traps need to be **stored** to allow for future claiming of these trapped assets, FRAME provide us with means for this.
-
-Notes:
-
-- This is handled in the `post_execute` function of the xcm-executor.
-
----v
-
-## Asset Trap/Claims with `pallet-xcm`
-
-- **`pallet-xcm` asset trapper**: Trapped assets are stored in the `AssetTraps` storage item and indexed by origin and assets
-
-- **`pallet-xcm` asset claimer**: `pallet-xcm` also allows for claiming trapped assets, providing that:
-  - the origin claiming the assets is identical to the one that trapped them.
-  - the `Asset` being claimed is identical to the one that was trapped
-
-Notes:
-
-- Each map element on `AssetTraps` holds a counter of how many times such origin has trapped such `Asset`.
-- Every time such `Asset` gets reclaimed, the counter decrements by one.
-
----
-
-## Extrinsic breakdown
-
-Let's jump into the code and have a look at `limited_teleport_assets` extrinsic.
-
-[source 🔍](https://github.com/paritytech/polkadot-sdk/blob/342d720/polkadot/xcm/pallet-xcm/src/lib.rs#L1099)
-
----
-
-## Summary
-
-In this lecture, we learnt:
-
-- What the XCM pallet is and what it's used for.
-- How XCM is intended to be used, both by wallet and runtime developers.
-- The useful extrinsics in the XCM pallet.
-- How XCM versioning works.
-- How the XCM pallet is used to receive responses.
-- How assets might be trapped and how to use the XCM pallet to claim them.
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-# XCM in Polkadot
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
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----
-title: XCM in Polkadot # Also update the h1 header on the first slide to the same name
-description: XCM in the Polkadot Context for web3 builders
-duration: 1 hour
----
-
-# XCM in Polkadot
-
----
-
-## _At the end of this lecture, you will be able to:_
-
-<pba-flex center>
-
-- Understand the configuration of the Rococo chain
-- Send real-world messages between parachain A <-> Rococo
-- Identify potential errors on XCM messages
-
----
-
-## 🤔 Considerations
-
-- There should be no trust assumption between chains unless explicitly requested.
-- We cannot assume chains will not act maliciously
-- Spamming XCM messages creates a DoS problem
-
----
-
-## 🛠️ Rococo Configuration
-
-- Barriers
-- Teleport filtering
-- Trusted reserves
-- Asset transactors
-- Fee payment
-- Proper XCM Instruction Weighting
-- Location to Account/FRAME Origin conversions
-
-Notes:
-
-From now on, we will use the Rococo runtime as a reference.
-Rococo is a testnet for
-Polkadot and Kusama that we will use in to test our XCM messages.
-Most of the Rococo configuration
-is identical to that in Polkadot.
-
----
-
-## 🚧 XCM `Barrier` in Rococo
-
-```rust
-/// The barriers one of which must be passed for an XCM message to be executed.
-pub type Barrier = (
-  // Weight that is paid for may be consumed.
-  TakeWeightCredit,
-  // If the message is one that immediately attempts to pay for execution, then allow it.
-  AllowTopLevelPaidExecutionFrom<Everything>,
-  // Messages coming from system parachains need not pay for execution.
-  AllowUnpaidExecutionFrom<IsChildSystemParachain<ParaId>>,
-  // Expected responses are OK.
-  AllowKnownQueryResponses<XcmPallet>,
-  // Subscriptions for version tracking are OK.
-  AllowSubscriptionsFrom<Everything>,
-);
-```
-
----v
-
-## 🚧 XCM `Barrier` in Rococo
-
-- `TakeWeightCredit` and `AllowTopLevelPaidExecutionFrom` are used to prevent spamming for local/remote XCM execution.
-- `AllowUnpaidExecutionFrom` lets a system parachain have free execution in the relay.
-- `AllowKnownQueryResponses` and `AllowSubscriptionsFrom`, as we know already, are mostly used for versioning.
-
-Notes:
-
-- Child system parachains are parachains that contain core polkadot features, and they will get a paraId of less than 1000.
-  They are allocated by Polkadot governance and get free execution.
-- `AllowKnownQueryResponses` will check pallet-xcm storage to know whether the response is expected. -`AllowSubscriptionsFrom` determines that any origin is able to subscribe for version changes.
-
----
-
-## 🤝 Trusted teleporters in Rococo
-
-```rust [0|2|6-8|18-22]
-parameter_types! {
-  pub const RocLocation: MultiLocation = Here.into();
-  pub const Rococo: MultiAssetFilter =
-    Wild(AllOf { fun: WildFungible, id: Concrete(RocLocation::get()) });
-
-  pub const AssetHub: MultiLocation = Parachain(1000).into();
-  pub const Contracts: MultiLocation = Parachain(1002).into();
-  pub const Encointer: MultiLocation = Parachain(1003).into();
-
-  pub const RococoForAssetHub: (MultiAssetFilter, MultiLocation) =
-    (Rococo::get(), AssetHub::get());
-  pub const RococoForContracts: (MultiAssetFilter, MultiLocation) =
-    (Rococo::get(), Contracts::get());
-  pub const RococoForEncointer: (MultiAssetFilter, MultiLocation) =
-    (Rococo::get(), Encointer::get());
-}
-
-pub type TrustedTeleporters = (
-  xcm_builder::Case<RococoForAssetHub>,
-  xcm_builder::Case<RococoForContracts>,
-  xcm_builder::Case<RococoForEncointer>,
-);
-```
-
----v
-
-## 🤝 Trusted teleporters in Rococo
-
-- Teleporting involves trust between chains.
-- 1000 (Asset Hub) and 1001 (Contracts) and 1002 (Encointer) are allowed to teleport tokens represented by the **Here**
-- **Here** represents the relay token
-
-```rust
-impl xcm_executor::Config for XcmConfig {
-  /* snip */
-  type IsTeleporter = TrustedTeleporters;
-  /* snip */
-}
-```
-
-Notes:
-
-- Asset Hub, Rococo and Encointer are able to teleport the relay chain token
-- Any other chain sending a `ReceiveTeleportedAsset` or any other token being teleported will be rejected with `UntrustedTeleportLocation`.
-
----
-
-## 💱Trusted reserves in Rococo
-
-- Rococo does not recognize any chain as reserve
-- Rococo prevents reception of any **ReserveAssetDeposited** message
-
-```rust
-impl xcm_executor::Config for XcmConfig {
-  /* snip */
-  type IsReserve = ();
-  /* snip */
-}
-```
-
-Notes:
-
-- Trusting other parachains (e.g., common good parachains) to be reserves of the relay native token would cause rare situations with the total issuance.
-  For instance, users could drain reserves of the sovereign account with teleported funds.
-
----
-
-## 📁 `LocationToAccountId` in Rococo
-
-- Conversion between a multilocation to an AccountId is a key component to withdraw/deposit assets and issue `Transact` operations.
-- Parachain origins will be converted to their corresponding sovereign account.
-- Local 32 byte origins will be converted to a 32 byte defined AccountId.
-
-```rust
-pub type LocationConverter = (
-  // We can convert a child parachain using the standard `AccountId` conversion.
-  ChildParachainConvertsVia<ParaId, AccountId>,
-  // We can directly alias an `AccountId32` into a local account.
-  AccountId32Aliases<RococoNetwork, AccountId>,
-);
-```
-
-Notes:
-
-- Any other origin that is not a parachain origin or a local 32 byte account origin will not be convertible to an accountId.
-- Question class what happens if a message coming from a parachain starts with `DescendOrigin`?
-  XcmV2 will reject it at the barrier level (Since **_AllowTopLevelPaidExecutionFrom_** expects the first instruction to be one of **_ReceiveTeleportedAsset_** , **_WithdrawAsset_** , **_ReserveAssetDeposited_** or **_ClaimAsset_** - XcmV3 will pass the barrier as **_AllowTopLevelPaidExecutionFrom_** is inside **_WithComputedOrigin_**.
-
----
-
-## 🪙 Asset Transactors in Rococo
-
-<div style="font-size: smaller">
-
-```rust
-pub type LocalAssetTransactor = XcmCurrencyAdapter<
-  // Use this currency:
-  Balances,
-  // Use this currency when it is a fungible asset
-  // matching the given location or name:
-  IsConcrete<RocLocation>,
-  // We can convert the MultiLocations
-  // with our converter above:
-  LocationConverter,
-  // Our chain's account ID type
-  // (we can't get away without mentioning it explicitly):
-  AccountId,
-  // It's a native asset so we keep track of the teleports
-  // to maintain total issuance.
-  CheckAccount,
->;
-
-impl xcm_executor::Config for XcmConfig {
-  /* snip */
-  type AssetTransactor = LocalAssetTransactor;
-  /* snip */
-}
-```
-
-</div>
-
----v
-
-## 🪙 `asset-transactors` in Rococo
-
-- Single asset-transactor in Rococo
-- Asset-transactor is matching the **Here** multilocation id to the Currency defined in **Balances**, which refers to **_pallet-balances_**
-- Essentially, this is configuring XCM such that the native token (DOT) is associated with the multilocation **Here**.
-
-Notes:
-
-- Rococo is tracking teleports in the **CheckAccount**, which is defined in **palletXcm**.
-  This aims at maintaining the total issuance even if assets have been teleported to another chain.
-
----
-
-## 📍`origin-converter` in Rococo
-
-```rust
-type LocalOriginConverter = (
-  // Converts to a signed origin with "LocationConverter"
-  SovereignSignedViaLocation<LocationConverter, RuntimeOrigin>,
-  // Converts a child parachain multilocation to a parachain origin
-  ChildParachainAsNative<parachains_origin::Origin, RuntimeOrigin>,
-  // Converts a local 32 byte multilocation to a signed
-  // origin
-  SignedAccountId32AsNative<WestendNetwork, RuntimeOrigin>,
-  // Converts system parachain origins into root origin
-  ChildSystemParachainAsSuperuser<ParaId, RuntimeOrigin>,
-);
-```
-
-```rust
-impl xcm_executor::Config for XcmConfig {
-  /* snip */
-  type OriginConverter = LocalOriginConverter;
-  /* snip */
-}
-```
-
----v
-
-## 📍`origin-converter` in Rococo
-
-- Defines ways in which we can convert a multilocation to a dispatch origin, typically used by the `Transact` instruction:
-- Child parachain origins are converted to signed origins through **_LocationConverter_** (`OriginKind == Sovereign`).
-- Child parachains can also be converted to native parachain origins (`OriginKind == Native`).
-- Local 32 byte origins are converted to signed 32 byte origins (`OriginKind == Native`).
-
-Notes:
-
-- There exists the concept of a "parachain dispatch origin" which is used for very specific functions (like, e.g., opening a channel with another chain).
-  This gets checked with the _ensure_parachain!_ macro.
-- System parachains are able to dispatch as root origins, as they can bee seen as an extension to the rococo runtime itself.
-
----
-
-### 🏋️ `Weigher` in Rococo
-
-- Uses `WeightInfoBounds` with benchmarked values with `pallet-xcm-benchmarks`
-- Full list of weights can be seen [here](https://github.com/paritytech/polkadot-sdk/tree/cc9f812/polkadot/runtime/rococo/src/weights/xcm)
-
-```rust
-impl xcm_executor::Config for XcmConfig {
-  /* snip */
-type Weigher = WeightInfoBounds<
-		crate::weights::xcm::RococoXcmWeight<RuntimeCall>,
-		RuntimeCall,
-		MaxInstructions,
-	>;
- /* snip */
-}
-```
-
----
-
-## 🔧 `WeightTrader` in Rococo
-
-- Weight is converted to fee with the **_WeightToFee_** type.
-- The asset in which we charge for fee is **_RocLocation_**.
-  This means we can only pay for xcm execution in the **native currency**
-- Fees will go to the block author thanks to **_ToAuthor_**
-
-```rust
-impl xcm_executor::Config for XcmConfig {
-  /* snip */
-  type Trader = UsingComponents<
-    WeightToFee,
-	RocLocation,
-	AccountId,
-	Balances,
-	ToAuthor<Runtime>>;
-  /* snip */
-}
-```
-
-Notes:
-
-- Trying to buyExecution with any other token that does not match the specified AssetId (in this case, `RocLocation`, which represents the native token) **will fail**.
-
-- **_WeightToFee_** contains an associated function that will be used to convert the required amount of weight into an amount of tokens used for execution payment.
-
----
-
-## 🎨 `XcmPallet` in Rococo
-
-```rust
-impl pallet_xcm::Config for Runtime {
-  /* snip */
-  type XcmRouter = XcmRouter;
-  type SendXcmOrigin =
-    xcm_builder::EnsureXcmOrigin<RuntimeOrigin, LocalOriginToLocation>;
-  // Anyone can execute XCM messages locally.
-  type ExecuteXcmOrigin =
-    xcm_builder::EnsureXcmOrigin<RuntimeOrigin, LocalOriginToLocation>;
-  type XcmExecuteFilter = Everything;
-  type XcmExecutor = xcm_executor::XcmExecutor<XcmConfig>;
-  // Anyone is able to use teleportation
-  // regardless of who they are and what they want to teleport.
-  type XcmTeleportFilter = Everything;
-  // Anyone is able to use reserve transfers
-  // regardless of who they are and what they want to transfer.
-  type XcmReserveTransferFilter = Everything;
-  /* snip */
-}
-```
-
----v
-
-## 🎨 XcmPallet in Rococo
-
-- No filter on messages for Execution, Teleporting or Reserve transferring.
-- Only origins defined by **_LocalOriginToLocation_** are allowed to send/execute arbitrary messages.
-- **_LocalOriginToLocation_** defined to allow council and regular account 32 byte signed origin calls
-
-```rust
-pub type LocalOriginToLocation = (
-  // We allow an origin from the Collective pallet to be used in XCM
-  // as a corresponding Plurality of the `Unit` body.
-  CouncilToPlurality,
-  // And a usual Signed origin to be used in XCM as a corresponding AccountId32
-  SignedToAccountId32<RuntimeOrigin, AccountId, RococoNetwork>,
-);
-```
-
-Notes:
-
-- **_LocalOrigin_** allows to go from a frame dispatch origin to a multilocation.
-  This is necessary because **we enter the xcm-executor with xcm origins, not with frame dispatch origins**.
-  Note that this is an extrinsic in a frame pallet, and thus, **we call it with frame origins**.
-
-- Council decisions are converted to `Plurality` junction multilocations.
-
-- Signed origins are converted to `AccountId32` junction multilocations.
-
----
diff --git a/content/xcm/xcvm/page.md b/content/xcm/xcvm/page.md
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-# XCVM
-
-<!-- markdown-link-check-disable -->
-<center>
-<iframe style="width: 90%; aspect-ratio: 1400/900; margin: 0 0; border: none;" src="slides.html"></iframe>
-<br />
-<a target="_blank" href="../../contribute/how-to/page.md#-how-to-use-revealjs-slides"><i class="fa fa-pencil-square"></i> How to use the slides</a> -
-<a target="_blank" href="slides.html"><i class="fa fa-share-square"></i> Full screen (new tab)</a>
-</center>
-<!-- markdown-link-check-enable -->
-
-<!-- Optionally, place other content for this lesson in the page *only* here -->
-
-<center style="margin: 1.3em 0; font-size: 1.2em;"><i class="fa fa-chevron-circle-down"></i> <strong>Slides Content </strong><i class="fa fa-chevron-circle-down"></i></center>
-{{#include slides.md}}
-<a href="#top" style="position: fixed; right: 11%; bottom: 3%;"><i style="font-size: 1.3em;" class="fa fa-arrow-up"></i></a>
diff --git a/content/xcm/xcvm/slides.md b/content/xcm/xcvm/slides.md
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----
-title: XCVM
-description: Learning about the XCVM state machine
-duration: 1 hour
----
-
-# XCVM
-
----
-
-# 🫀 The XCVM
-
-At the core of XCM lies the **Cross-Consensus Virtual Machine (XCVM)**.
-
-A “message” in XCM is an XCVM program, which is a sequence of instructions.
-
-The XCVM is a state machine, state is kept track in **registers**.
-
-Notes:
-
-It’s an ultra-high level non-Turing-complete computer.
-Messages are one or more XCM instructions.
-The program executes until it either runs to the end or hits an error, at which point it finishes up and halts.
-An XCM executor following the XCVM specification is provided by Parity, and it can be extended or customized, or even ignored altogether and users can create their own construct that follows the XCVM spec.
-
----
-
-# 📜 XCVM Instructions
-
-XCVM Instructions might change a register, they might change the state of the consensus system or both.
-
----v
-
-## Kinds of instructions
-
-<pba-flex center>
-
-- Command
-- Trusted Indication
-- Information
-- System Notification
-
----v
-
-## Example: TransferAsset
-
-An instruction used to transfer assets to some other address.
-
-<pba-flex center>
-
-```rust
-TransferAsset {
-    assets: Assets,
-    beneficiary: Location,
-}
-```
-
-Notes:
-
-This instruction is a command.
-It needs to know which assets to transfer and to which account to transfer them to.
-
----
-
-# XCVM Registers
-
-<diagram class="mermaid">
-graph LR
-    subgraph Registers[ ]
-        Holding(Holding)
-        Origin(Origin)
-        More(...)
-    end
-</diagram>
-
-Notes:
-
-Registers _are_ the state of XCVM.
-Note that they are temporary/transient.
-We'll talk about are the `holding` and `origin` registers, but there are more.
-
----v
-
-## 📍 The Origin Register
-
-Contains an `Option<Location>` of the cross-consensus origin where the message originated from.
-
-Notes:
-
-This `Location` can change over the course of program execution.
-
-It might be `None` because some instructions clear the origin register.
-
----v
-
-### 💸 The Holding Register
-
-Expresses a number of assets in control of the xcm execution that have no on-chain representation.
-
-They don't belong to any account.
-
-It can be seen as the register holding "unspent assets".
-
----
-
-# Basic XCVM Operation
-
-<diagram class="mermaid">
-graph LR
-    subgraph Program
-        WithdrawAsset-->BuyExecution
-        BuyExecution-->DepositAsset
-        DepositAsset
-    end
-    Program-.->Fetch
-    Fetch(Fetch Instruction)-->Execute(Execute instruction)
-    Execute-->Fetch
-    Execute-.->Registers
-    subgraph Registers
-        Holding(Holding)
-        Origin(Origin)
-        More(...)
-    end
-</diagram>
-
-Notes:
-
-The XCVM fetches instruction from the program and executes them one by one.
-
----v
-
-## XCVM vs. Standard State Machine
-
-<pba-flex center>
-
-1. Error _handler_ register
-2. Appendix register
-
-Notes:
-
-1. Code that is run in the case where the XCM program fails or errors.
-   Regardless of the result, when the program completes, the error handler register is cleared.
-   This ensures that error handling logic from a previous program does not affect any appended code (i.e. the code in the error handler register does not loop infinitely, the code in the Appendix register cannot access the result of the code execution in the error handler).
-2. Code that is run regardless of the execution result of the XCM program.
-
----v
-
-## More complete XCVM operation
-
-<diagram class="mermaid">
-graph LR
-    subgraph Program
-        WithdrawAsset-->BuyExecution
-        BuyExecution-->DepositAsset
-        DepositAsset
-    end
-    Program-.->Fetch
-    Fetch(Fetch Instruction)-->Execute(Execute instruction)
-    Execute-->Fetch
-    Execute-.->Registers
-    subgraph Registers
-        Holding(Holding)
-        Origin(Origin)
-        ErrorRegister(Error)
-        ErrorHandler(Error Handler)
-        AppendixRegister(Appendix)
-        More(...)
-    end
-    Execute-- Error -->Error(Error Handler)
-    Error-.->ErrorHandler
-    Error-.->ErrorRegister
-    Error-->Appendix
-    Appendix-.->AppendixRegister
-    Execute-->Appendix
-</diagram>
-
----
-
-# 💁 XCM by example
-
----v
-
-## The `WithdrawAsset` instruction
-
-<pba-flex center>
-
-```rust
-enum Instruction {
-    /* snip */
-    WithdrawAsset(Assets),
-    /* snip */
-}
-```
-
-Notes:
-
-There are a number of instructions
-which place assets on the Holding Register.
-One very simple one is the
-`WithdrawAsset` instruction.
-
-It withdraws some assets from the account of the location specified in the Origin Register.
-But what does it do with them?
-If they don’t get deposited anywhere then it's a pretty useless operation.
-These assets are held in the holding register until something is done with them, for example, using the following instruction.
-
----v
-
-## The `BuyExecution` instruction
-
-<pba-flex center>
-
-```rust
-enum Instruction {
-    /* snip */
-    BuyExecution {
-        fees: Asset,
-        weight_limit: WeightLimit,
-    },
-    /* snip */
-}
-```
-
-Notes:
-
-This instruction uses the specified assets in the Holding register to buy weight for the execution of the following instructions.
-It's used in systems that pay fees.
-
-`weight_limit` is a sanity check, to make sure that the execution errors if you would buy more than that weight.
-The estimate for the weight has to come from using the recipient's weigher, not the sender's.
-The recipient is the one who actually executes the message.
-
----v
-
-## The `DepositAsset` instruction
-
-<pba-flex center>
-
-```rust
-enum Instruction {
-    /* snip */
-    DepositAsset {
-        assets: AssetFilter,
-        beneficiary: Location,
-    },
-    /* snip */
-}
-```
-
-Notes:
-
-Takes assets from the holding register and deposits them in a beneficiary.
-Typically an instruction that places assets into the holding register would have been executed previously.
-
----v
-
-## Putting it all together
-
-<pba-flex center>
-
-```rust
-Xcm(vec![
-    WithdrawAsset((Here, amount).into()),
-    BuyExecution {
-        fees: (Here, amount).into(),
-        weight_limit: Limited(sanity_check_weight_limit)
-    },
-    DepositAsset { assets: All.into(), beneficiary: AccountId32 { ... }.into() },
-])
-```
-
-Notes:
-
-All examples in these slides use the latest xcm version.
-
----v
-
-## Good pattern
-
-<pba-flex center>
-
-```rust
-Xcm(vec![
-    WithdrawAsset((Here, amount).into()),
-    BuyExecution {
-        fees: (Here, amount).into(),
-        weight_limit: Limited(sanity_check_weight_limit)
-    },
-    DepositAsset { assets: All.into(), beneficiary: AccountId32 { ... }.into() },
-    RefundSurplus,
-    DepositAsset { assets: All.into(), beneficiary: sender }
-])
-```
-
----
-
-# Reserve asset transfer
-
-<pba-flex center>
-
-```rust
-Xcm(vec![
-    WithdrawAsset(asset),
-    InitiateReserveWithdraw {
-        assets: All.into(),
-        reserve: reserve_location,
-        xcm: /* ...what to do with the funds in the reserve... */,
-    },
-])
-```
-
-Notes:
-
-This message is executed locally.
-Then, a message is sent to the `reserve` location.
-That message contains the custom `xcm` provided along with other instructions.
-
----v
-
-## Message received in reserve
-
-<pba-flex center>
-
-```rust
-Xcm(vec![
-    WithdrawAsset(reanchored_asset),
-    ClearOrigin, // <- Why is this needed?
-    /* ...custom instructions... */
-])
-```
-
-Notes:
-
-This is the message the reserve receives.
-
-The `ClearOrigin` instruction deletes the content of the origin register.
-This is needed because we don't trust the origin to do anything other than move its own assets.
-
----v
-
-## Custom XCM
-
-<pba-flex center>
-
-```rust
-let xcm_for_reserve = Xcm(vec![
-    DepositReserveAsset {
-        assets: All.into(),
-        dest: location,
-        xcm: Xcm(vec![
-            DepositAsset {
-                assets: All.into(),
-                beneficiary: AccountId32 { ... }.into(),
-            },
-        ]),
-    },
-]);
-```
-
-Notes:
-
-For a simple reserve asset transfer, this message will work.
-
----v
-
-## Message received in destination
-
-<pba-flex center>
-
-```rust
-Xcm(vec![
-    ReserveAssetDeposited(reanchored_asset),
-    ClearOrigin, // <- Why is this needed?
-    /* ...custom instructions... */
-])
-```
-
-Notes:
-
-A very clear exploit in not having `ClearOrigin` here is syphoning all funds from
-the reserve's sovereign account in the destination.
-The destination can't trust the reserve to totally speak for the source, only for the assets.
-
----
-
-# Summary
-
-<pba-flex center>
-
-- XCVM
-- Kinds of instructions
-- Registers
-  - Origin
-  - Holding
-  - Error handler
-  - Appendix
-- Instructions
-  - WithdrawAsset, BuyExecution, DepositAsset
-  - RefundSurplus
-  - InitiateReserveWithdraw, ReserveAssetDeposited
-
----v
-
-## Next steps
-
-<pba-flex center>
-
-1. Blog series introducing XCM: Parts [1](https://medium.com/polkadot-network/xcm-the-cross-consensus-message-format-3b77b1373392), [2](https://medium.com/polkadot-network/xcm-part-ii-versioning-and-compatibility-b313fc257b83), and [3](https://medium.com/polkadot-network/xcm-part-iii-execution-and-error-management-ceb8155dd166).
-1. XCM Format [repository](https://github.com/paritytech/xcm-format)
-1. XCM [Docs](https://paritytech.github.io/xcm-docs/)